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Due to its impact on society, the design of new drugs has the potential to interest a wide audience, and provides a rare opportunity to introduce several concepts in chemistry and biochemistry. Drug design can be seen as a multiobjective cyclic optimization process. Indeed, it is important to develop the understanding not only that a drug is generally an effective ligand for a protein of therapeutic interest, but also that these molecules need to have drug-like properties. Computer-aided drug design and bioinformatics approaches play a fundamental role in addressing these different challenges. Here we introduce a new freely available integrated web-based educational tool, Drug Design Workshop, which presents the basics of drug design and provides anyone with access to computational methods and resources to conceive and evaluate molecules for their potential to become actual drugs. We provide 3 examples of drug design targets for the discovery of common or state-of-the-art drugs, which can be used by educators to introduce easily the different concepts related to drug discovery: anti-inflammatory agents and drugs for immunotherapy or targeted cancer therapy. Since 2015, the workshop has been successfully given to over 1,500 people. The Web site was optimized on the basis of the positive and constructive comments from high-school teachers and students (15-19 years old).

Preterm birth, affecting about 10% of pregnancies, significantly contributes to perinatal morbidity and mortality. Recent research indicates that metabolomics could enhance pregnancy outcomes and reduce costs by identifying biomarkers related to common pregnancy complications. Our team focused on analyzing amniotic fluid collected during the second trimester to identify potential biomarkers for preterm birth using 1H-NMR metabolomic analysis. We compared amniotic fluid samples from women who delivered prematurely with those who delivered at term. Multivariate principal component analysis revealed dimethylglycine, glucose, myo-inositol, and succinic acid as potential biomarkers for preterm birth prognosis and early diagnosis. Further analysis demonstrated distinct regulation patterns of these metabolites in relation to fetal growth centiles. For instance, dimethylglycine and glucose were upregulated in fetuses above the 20th centile, while citrate and succinate were upregulated in those below it. With Area Under the Curve (AUROC) values over 0.75 and p-values less than 0.05, these metabolites show promise as reliable biomarkers for predicting fetal growth restriction. This approach could significantly impact maternal-fetal medicine by facilitating early diagnosis and personalized interventions. Future research should focus on validating these findings in larger populations and exploring the underlying mechanisms of metabolite regulation.

Introduction: Laparoscopic adrenalectomy is considered to be the gold standard approach in the field of adrenal surgery. This technique offers advantages of great importance compared to variant laparotomy techniques. Notwithstanding, a technique that needs to be mentioned is the thoracoabdominal approach which facilitates the anatomic exposure of the retroperitoneum, adrenal gland, and great vessels and is strongly recommended for the surgery of large, malignant adrenal tumors. Aim: The objective of this study is to evaluate the effectiveness and outcomes of the thoracoabdominal approach in adrenal surgery for large adrenal tumors. By presenting our results and experiences, we aim to highlight the advantages of this technique in providing optimal anatomic exposure of the retroperitoneum, adrenal gland, and great vessels, and to establish its role as a viable alternative to laparoscopic adrenalectomy in complex cases. Materials and methods: We reviewed retrospectively the data of our patients admitted to our Surgical Department and treated surgically with the thoracoabdominal incision, performed by a single surgeon at our tertiary care center, over the period 01/01/20-31/12/23. Results: All patients had large retroperitoneal masses of varying complexity, requiring maximal surgical exposure. Seventeen patients in total underwent operation with the indication of unilateral adrenal tumor. Five of those patients underwent a laparoscopic tumor resection, while 12 patients were treated by thoracoabdominal approach. Our study group included 7 women (58%) and 5 men (42%), with average age 57 years. The mean maximum tumor diameter was 10.8 cm. Conclusion: The advantages of the thoracoabdominal approach regarding the exposure of the operative field in challenging cases, together with the low incidence of complications noted in our experience, render this technique an excellent alternative if indicated.

Lymphangioma, a benign mass of lymphatic origin, primarily affects the head, neck, and oral cavity, with the abdomen being an uncommon location. Clinical presentation is defined by site of origin and size. We present the case of a 10-month-old male infant with no previous medical history, admitted to our department with diffuse abdominal pain and distension. Physical examination revealed a huge, palpable mass arising from the left abdomen, abdominal tenderness, guarding, and rigidity. Abdominal ultrasound revealed a multilocular, non-measurable mass with both cystic and solid components that were suggestive of a giant cystic lymphangioma. Multidetector computed tomography and magnetic resonance imaging were performed to estimate the size and extension of the tumor for preoperative planning. Moreover, an elevated alpha-fetoprotein level further supported the neoplastic origin of the tumor. Exploratory laparotomy was performed, and a mass measuring approximately 13.9×16.7×15.4 cm was identified and completely excised in negative margins. Histopathological findings confirmed the initial diagnosis. Our patient had an uncomplicated postoperative course and recovery, with no signs of recurrence on a 6-month follow-up. Giant abdominal lymphangiomas in infants are extremely rare and close attention for complications is vital. Surgical intervention with complete resection is considered the optimal management.

Abstract This study aimed to explore the antioxidant potential of the ethyl acetate extract of Streptomyces coeruleofuscus SCJ strain, along with its inhibitory effects on the triple-negative human breast carcinoma cell line (MDA-MB-468). The ethyl acetate extract’s total phenolic and flavonoid contents were quantified, and its antioxidant activity was investigated using DPPH (1,1-Diphenyl-2-picrylhydrazyl), ABTS (2,2’-azino-bis (3-ethylbenzothiazoline-6-sulphonic acid), and FRAP (Ferric Reducing Antioxidant Power) assays. Furthermore, the cytotoxic effect of the organic extract from Streptomyces coeruleofuscus SCJ on MDA-MB-468 cancer cells was assessed via the crystal violet assay. In tandem, a thorough computational investigation was conducted to explore the pharmacokinetic properties of the identified components of the extract, utilizing the SwissADME and pKCSM web servers. Additionally, the molecular interactions between these components and Estrogen Receptor Beta, identified as a potential target, were probed through molecular docking studies. The results revealed that ethyl acetate extract of SCJ strain exhibited remarkable antioxidant activity, with 39.899 ± 1.56% and 35.798 ± 0.082% scavenging activities against DPPH and ABTS, respectively, at 1 mg/mL. The extract also displayed significant ferric reducing power, with a concentration of 1.087 ± 0.026 mg ascorbic acid equivalents per mg of dry extract. Furthermore, a strong positive correlation (p

Abstract Despite the constant development of antimicrobial resistance (AMR), few new antimicrobials are currently becoming available clinically. Alternative approaches, such as different mechanisms to fund their use, are being explored to encourage development of new antimicrobials.

Purpose: Non-obstructive azoospermia (NOA) represents the persistent absence of sperm in ejaculate without obstruction, stemming from diverse disease processes. This survey explores global practices in NOA diagnosis, comparing them with guidelines and offering expert recommendations. Materials and Methods:Materials and Methods: A 56-item questionnaire survey on NOA diagnosis and management was conducted globally from July to September 2022. This paper focuses on part 1, evaluating NOA diagnosis. Data from 367 participants across 49 coun-tries were analyzed descriptively, with a Delphi process used for expert recommendations. Results:Results: Of 336 eligible responses, most participants were experienced attending physicians (70.93%). To diagnose azoosper-mia definitively, 81.7% requested two semen samples. Commonly ordered hormone tests included serum follicle-stimulating hormone (FSH) (97.0%), total testosterone (92.9%), and luteinizing hormone (86.9%). Genetic testing was requested by 66.6%, with karyotype analysis (86.2%) and Y chromosome microdeletions (88.3%) prevalent. Diagnostic testicular biopsy, distinguishing obstructive azoospermia (OA) from NOA, was not performed by 45.1%, while 34.6% did it selectively. Differ-entiation relied on physical examination (76.1%), serum hormone profiles (69.6%), and semen tests (68.1%). Expectations of finding sperm surgically were higher in men with normal FSH, larger testes, and a history of sperm in ejaculate. Conclusions:Conclusions: This expert survey, encompassing 367 participants from 49 countries, unveils congruence with recommended guidelines in NOA diagnosis. However, noteworthy disparities in practices suggest a need for evidence-based, international consensus guidelines to standardize NOA evaluation, addressing existing gaps in professional recommendations.

The standard treatment procedures for managing renal calculi in the pediatric population are similar to those in adults. The application of flexible ureteroscopy has contributed to the increased popularity of retrograde intrarenal surgery (RIRS) as an alternative therapeutic modality that can be successfully applied in children. One of the most significant innovations of the last decade is the introduction of single-use flexible ureteroscopes (fURSs). In this case report, we present the case of a 2-year-old boy with multiple large calculi in his right kidney, which were successfully removed after a single session of RIRS using a 7.5 F single-use fURS and high-power laser settings. The total operative and lithotripsy times were estimated at 90 and 75 min, respectively. No complications were recorded. The hemoglobin loss was calculated at 0.3 mg/dL, while the creatinine level was decreased by 0.1 mg/dL. The urethral catheter was removed on the first postoperative day, and the patient was discharged. The management of multiple or large kidney stones is very challenging in the pediatric population under the age of three years. Convenient preoperative planning and the appropriate use of available equipment may lead to excellent outcomes accompanied by a reduced risk for complications.

Abstract A precise quantification of mitral regurgitation (MR) severity is essential for treatment and outcome of patients with MR. 3D echocardiography facilitates estimation of MR but selection of patients with necessity of invasive treatment remains challenging. We investigate effective regurgitation orifice area (EROA) quantification by 3D compared to 2D echocardiography in patients with MR and highlight the improved discrimination of MR severity. We consecutively enrolled fifty patients with primary or secondary and at least moderate MR undergoing 2D and 3D colour Doppler echocardiography prior to transcatheter edge-to-edge repair (TEER). Improved accuracy of MR grading using 3D vena contracta area (VCA) as an estimate of EROA was compared to 2D proximal isovelocity surface area (PISA) quantification method and a multiparameter reference standard. Quantification of EROA remarkably varies between 2D and 3D echocardiography and the discrimination between moderate and severe MR was significantly (p = 0.001) different using 2D PISA or 3D VCA, respectively. 3D VCA correlated significantly (r = 0.501, p

Abstract Background Duchenne muscular dystrophy (DMD) is a rare disease that causes progressive muscle degeneration resulting in life-threatening cardiac complications. The objective of this systematic literature review was to describe and grade the published evidence of predictors of cardiac disease in DMD. Methods The review encompassed searches of Embase, MEDLINE ALL, and the Cochrane Database of Systematic Reviews from January 1, 2000, to December 31, 2022, for predictors of cardiac disease in DMD. The certainty of evidence (i.e., very low to high) was assessed using the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) framework. Results We included 33 publications encompassing 9,232 patients with DMD. We found moderate- to high-quality evidence that cardiac medication (i.e., ACE inhibitors [enalapril and perindopril], β-blockers [carvedilol], and mineralocorticoid receptor antagonists [eplerenone]) are significantly associated with preserved left ventricular ejection fraction (LVEF), left ventricular end-systolic volume (LVESV), and left ventricular circumferential strain (LVCS). DMD mutations in exons 51 and 52 were found to be significantly associated with lower risk of cardiomyopathy; deletions treatable by exon 53 skipping and mutations in the Dp116 coding region with improved LVEF and prolonged cardiac dysfunction-free survival; and exons 45–50 and 52 with early left ventricular systolic dysfunction (low/very low-quality evidence). We found high-quality evidence that glucocorticoids (deflazacort) are significantly associated with preserved LVEF and improved fractional shortening (FS), and low-quality evidence that glucocorticoids (deflazacort, prednisone, and/or prednisolone) are associated with improved ejection fraction (EF) and lower risk of cardiomyopathy, ventricular dysfunction, and heart failure-related mortality. Full-time mechanical ventilation was found to be significantly correlated with LVEF (low-quality evidence), muscle strength with FS (low-quality evidence), and genetic modifiers (i.e., LTBP4 rs10880 and ACTN3) with LVEF, lower risk of cardiomyopathy and left ventricular dilation (low-quality evidence). Conclusion Several sources of cardiac disease heterogeneity are well-studied in patients with DMD. Yet, the certainty of evidence is generally low, and little is known of the contribution of non-pharmacological interventions, as well as the impact of different criteria for initiation of specific treatments. Our findings help raise awareness of prevailing unmet needs, shape expectations of treatment outcomes, and inform the design of future research.

Abstract Background In response to the global scope of forced displacement, international organizations highlight the need of scalable solutions to support individuals’ health and integration into host societies. Exposure to high mental and physical stress perceived before, during, and after displacement can impair functional capabilities, essential for adapting to a new environment. This secondary analysis examined the impact of an exercise and sport intervention on cognitive function and pain severity among individuals living in a refugee camp in Greece. Methods We implemented a randomized controlled trial involving n = 142 (52.8% women) forcibly displaced individuals from Southwest Asia and Sub-Saharan Africa. Participants were randomly assigned to a waitlist or a 10-week co-designed exercise and sport intervention with a 1:1 allocation rate between groups and sexes. Assessments at baseline and follow-up included the Flanker task, the Oddball paradigm, pain severity via visual analog scales, and the Åstrand-Rhyming indirect test of maximal oxygen uptake. We analyzed the intervention effects using structural equation modeling. Results Our findings did not indicate a direct intervention effect on cognitive function or pain (p ≥ .332). However, the intervention group significantly improved cardiorespiratory fitness, ß = .17, p = .010, which was associated with faster reaction times in cognitive tasks, ß = − .22, p = .004. Moreover, there was some evidence that adherence might be linked to reduced pain severity, ß = − .14, p = .065. Conclusions Exercise and sport did not directly impact cognitive function and pain severity among a sociodemographically diverse sample living in a refugee camp, suggesting the need for complementary measures. Nevertheless, our results indicate that improvements in cardiorespiratory fitness benefit aspects of attention. Trial registration The study was approved by the local ethics committee of the University of Thessaly (no. 39) and registered prospectively on February 8, 2021 at the ISRCTN registry (no. 16291983).

Abstract The aim of this study is to compare the diagnostic performance of magnetic resonance imaging (MRI) against computed tomography (CT) in various aspects of local staging in colon cancer patients. This study was a prospective single arm diagnostic accuracy study. All consecutive adult patients with confirmed colon cancer that met the current criteria for surgical resection were considered as eligible. Diagnostic performance assessment included T (T1/T2 vs T3/T4 and T3cd) and N (N positive) staging, serosa and retroperitoneal surgical margin (RSM) involvement and extramural vascular invasion (EMVI). Imaging was based on a 3 Tesla MRI system and the evaluation of all sequences (T1, T2 and diffusion-weighted imaging-DWI series) by two independent readers. CT scan was performed in a 128 row multidetector (MD) CT scanner (slice thickness: 1 mm) with intravenous contrast. Pathology report was considered as the gold standard for local staging. Sensitivity (SE), specificity (SP), and area under the curve (AUC) were calculated for both observers. MRI displayed a higher diagnostic performance over CT in terms of T1/T2 vs T3/T4 (SE: 100% vs 83.9%, SP: 96.6% vs 81%, AUC: 0.825 vs 0.983, p

Abstract Scandinavian electronic health-care registers provide a unique setting to investigate potential unidentified side effects of drugs. We analysed the association between prescription drugs dispensed in Norway and Sweden and the short-term risk of developing pulmonary embolism. A total of 12,104 pulmonary embolism cases were identified from patient- and cause-of-death registries in Norway (2004–2014) and 36,088 in Sweden (2005–2014). A case-crossover design was used to compare individual drugs dispensed 1–30 days before the date of pulmonary embolism diagnosis with dispensation in a 61–90 day time-window, while controlling for the receipt of other drugs. A BOLASSO approach was used to select drugs that were associated with short-term risk of pulmonary embolism. Thirty-eight drugs were associated with pulmonary embolism in the combined analysis of the Norwegian and Swedish data. Drugs associated with increased risk of pulmonary embolism included certain proton-pump inhibitors, antibiotics, antithrombotics, vasodilators, furosemide, anti-varicose medications, corticosteroids, immunostimulants (pegfilgrastim), opioids, analgesics, anxiolytics, antidepressants, antiprotozoals, and drugs for cough and colds. Mineral supplements, hydrochlorothiazide and potassium-sparing agents, beta-blockers, angiotensin 2 receptor blockers, statins, and methotrexate were associated with lower risk. Most associations persisted, and several additional drugs were associated, with pulmonary embolism when using a longer time window of 90 days instead of 30 days. These results provide exploratory, pharmacopeia-wide evidence of medications that may increase or decrease the risk of pulmonary embolism. Some of these findings were expected based on the drugs' indications, while others are novel and require further study as potentially modifiable precipitants of pulmonary embolism.

Abstract Standardized assessment of the gastroesophageal valve during endoscopy, attainable via the Hill classification, is important for clinical assessment and therapeutic decision making. The Hill classification is associated with the presence of hiatal hernia (HH), a common endoscopic finding connected to gastro-esophageal reflux disease. A novel efficient medical artificial intelligence (AI) training pipeline using active learning (AL) is designed. We identified 21,970 gastroscopic images as training data and used our AL to train a model for predicting the Hill classification and detecting HH. Performance of the AL and traditionally trained models were evaluated on an external expert-annotated image collection. The AL model achieved accuracy of 76%. A traditionally trained model with 125% more training data achieved 77% accuracy. Furthermore, the AL model achieved higher precision than the traditional one for rare classes, with 0.54 versus 0.39 (p

Abstract Formalin-fixed paraffin-embedded (FFPE) tissue represents a valuable source for translational cancer research. However, the widespread application of various downstream methods remains challenging. Here, we aimed to assess the feasibility of a genomic and gene expression analysis workflow using FFPE breast cancer (BC) tissue. We conducted a systematic literature review for the assessment of concordance between FFPE and fresh-frozen matched tissue samples derived from patients with BC for DNA and RNA downstream applications. The analytical performance of three different nucleic acid extraction kits on FFPE BC clinical samples was compared. We also applied a newly developed targeted DNA Next-Generation Sequencing (NGS) 370-gene panel and the nCounter BC360® platform on simultaneously extracted DNA and RNA, respectively, using FFPE tissue from a phase II clinical trial. Of the 3701 initial search results, 40 articles were included in the systematic review. High degree of concordance was observed in various downstream application platforms. Moreover, the performance of simultaneous DNA/RNA extraction kit was demonstrated with targeted DNA NGS and gene expression profiling. Exclusion of variants below 5% variant allele frequency was essential to overcome FFPE-induced artefacts. Targeted genomic analyses were feasible in simultaneously extracted DNA/RNA from FFPE material, providing insights for their implementation in clinical trials/cohorts.

Abstract Accurate survival prediction for Non-Small Cell Lung Cancer (NSCLC) patients remains a significant challenge for the scientific and clinical community despite decades of advanced analytics. Addressing this challenge not only helps inform the critical aspects of clinical study design and biomarker discovery but also ensures that the ‘right patient’ receives the ‘right treatment’. However, survival prediction is a highly complex task, given the large number of ‘omics; and clinical features, as well as the high degree of freedom that drive patient survival. Prior knowledge could play a critical role in uncovering the complexity of a disease and understanding the driving factors affecting a patient’s survival. We introduce a methodology for incorporating prior knowledge into machine learning–based models for prediction of patient survival through Knowledge Graphs, demonstrating the advantage of such an approach for NSCLC patients. Using data from patients treated with immuno-oncologic therapies in the POPLAR (NCT01903993) and OAK (NCT02008227) clinical trials, we found that the use of knowledge graphs yielded significantly improved hazard ratios, including in the POPLAR cohort, for models based on biomarker tumor mutation burden compared with those based on knowledge graphs. Use of a model-defined mutational 10-gene signature led to significant overall survival differentiation for both trials. We provide parameterized code for incorporating knowledge graphs into survival analyses for use by the wider scientific community.

Purpose: Augmented adiposity may negatively impact sexual sphere through its metabolic effects and its detrimental impact on reproductive hormones. Moreover, a dysregulated metabolic pathway may promote apoptosis among spermatogenic cells. Based on these premises, a relation between weights loss and ameliorate semen parameters seems beneficial. To investigate if physical activity may affect semen parameters and fertility rate, a systematic literature search on major dataset has been performed. Materials and Methods: The search terms included: “Assisted reproduction therapies,” “fertility,” “semen parameters,” “sperm parameters,” and “physical activity.” This analysis was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-analysis guidelines and it was registered on PROSPERO (CRD42023384471). A total of 47 studies have been identified; 1 reference has been eliminated after duplication check. After preliminary screening 32 papers have been excluded. Considering the exclusion criteria, 15 full-text articles were evaluated for eligibility. After a full-text review, six studies published during a span of eight years (2014–2022) have been included in the meta-analysis. Semen parameters, pregnancy and birth rates were investigated. The revised Cochrane risk of bias tool (Rob2) has been used to check the risk of bias. Results: The number of patients enrolled in studies ranges from 17 to 521; in the end, a total of 1,637 patients have been enrolled in the study. Fertility parameters investigated were semen quality parameters and pregnancy rates and live births. A statistically significant relationship between physical exercise and sperm concentration (p=0.02), total sperm motility (p

Purpose: Varicocele has been associated with high seminal oxidative stress (OS), impaired semen quality, and reduced male fertility potential. However, the exact mechanism(s) underlying the development of varicocele-mediated infertility and the cause-effect relationship between varicocele and testicular dysfunction are not fully understood. The aim of this systematic review and meta-analysis (SRMA) is to investigate the impact of varicocele on testicular OS markers and sperm parameters in experimental animals with varicocele as compared to animals without varicocele. Materials and Methods: A literature search was performed using the Scopus and PubMed databases on studies that investigated testicular OS markers and sperm parameters in animals with varicocele. The primary outcomes included malondialdehyde (MDA) (nmol/mg) levels whereas the secondary outcomes included total sperm count (×106), sperm vitality (%), total sperm motility (%), and sperm DNA fragmentation (SDF) (%). Standardized mean difference (SMD) (95% confidence interval [CI]) was chosen to express the effect size. The quality of the included studies was evaluated using the Cambridge Quality Checklist. Results: Out of 76 identified articles, 6 studies on rats were included in the meta-analysis. The analysis showed a significant increase of MDA (SMD: 15.61 [1.93, 29.29]; p=0.03) in rats with varicocele vs. controls. We also observed a significant decrease in total sperm count (SMD: -17.45 [-28.97, -5.93]; p

Abstract Microbial NAT enzymes, which employ acyl-CoA to acylate aromatic amines and hydrazines, have been well-studied for their role in xenobiotic metabolism. Some homologues have also been linked to secondary metabolism, but this function of NAT enzymes is not as well-known. For this comparative study, we surveyed sequenced microbial genomes to update the list of formally annotated NAT genes, adding over 4000 new sequences (mainly bacterial, but also archaeal, fungal and protist) and portraying a broad but not universal distribution of NATs in the microbiocosmos. Localization of NAT sequences within microbial gene clusters was not a rare finding, and this association was evident across all main types of biosynthetic gene clusters (BGCs) implicated in secondary metabolism. Interrogation of the MIBiG database for experimentally characterized clusters with NAT genes further supports that secondary metabolism must be a major function for microbial NAT enzymes and should not be overlooked by researchers in the field. We also show that NAT sequences can be associated with bacterial plasmids potentially involved in horizontal gene transfer. Combined, our computational predictions and MIBiG literature findings reveal the extraordinary functional diversification of microbial NAT genes, prompting further research into their role in predicted BGCs with as yet uncharacterized function.

Abstract Older adults (OAs) are typically slower and/or less accurate in forming perceptual choices relative to younger adults. Despite perceptual deficits, OAs gain from integrating information across senses, yielding multisensory benefits. However, the cognitive processes underlying these seemingly discrepant ageing effects remain unclear. To address this knowledge gap, 212 participants (18–90 years old) performed an online object categorisation paradigm, whereby age-related differences in Reaction Times (RTs) and choice accuracy between audiovisual (AV), visual (V), and auditory (A) conditions could be assessed. Whereas OAs were slower and less accurate across sensory conditions, they exhibited greater RT decreases between AV and V conditions, showing a larger multisensory benefit towards decisional speed. Hierarchical Drift Diffusion Modelling (HDDM) was fitted to participants’ behaviour to probe age-related impacts on the latent multisensory decision formation processes. For OAs, HDDM demonstrated slower evidence accumulation rates across sensory conditions coupled with increased response caution for AV trials of higher difficulty. Notably, for trials of lower difficulty we found multisensory benefits in evidence accumulation that increased with age, but not for trials of higher difficulty, in which increased response caution was instead evident. Together, our findings reconcile age-related impacts on multisensory decision-making, indicating greater multisensory evidence accumulation benefits with age underlying enhanced decisional speed.

Abstract Background Since the beginning of the coronavirus disease 2019 pandemic, the most common skin lesions observed due to infection with the severe acute respiratory syndrome coronavirus 2 are pseudochilblains (or coronavirus disease toes). However, this pathology remains infrequent and difficult to diagnose, as no specific test exists. Case presentation Two Caucasian women, 30 and 22 years old, presented to our General Medicine Unit with perniosis lesions on the feet during the first two waves of the coronavirus disease 2019 pandemic. They did not have respiratory or general symptoms of severe acute respiratory syndrome coronavirus 2 infection, the reverse transcription polymerase chain reaction on nasopharyngeal swabs was negative, and the serology was positive only in the first case. The clinical presentation differed for the two cases, as the second patient suffered from swelling and burning after cold application. The diagnosis was based on clinical presentation, temporality, exclusion of other differential diagnoses, and blood test results (positive serology in the first case and high level of CXCL13 and VEGF in the second), supported by current literature. Lesions resolved spontaneously in the first patient. The second case was hospitalized for pain management and received corticosteroid therapy with resolution of the symptoms. Conclusion These two cases with different clinical presentations illustrate the diagnostic approach to coronavirus disease 2019, a challenging disease with diverse manifestations, including, in some cases, coronavirus disease toes. We present a literature review that illustrates the progression of scientific research. Skin lesions associated with coronavirus disease 2019 infection could be the expression of an important interferon type 1 response and should be considered in the differential diagnosis in a primary care setting.

Abstract Do motor patterns of object lifting movements change as a result of ageing? Here we propose a methodology for the characterization of these motor patterns across individuals of different age groups. Specifically, we employ a bimanual grasp-lift-replace protocol with younger and older adults and combine measurements of muscle activity with grip and load forces to provide a window into the motor strategies supporting effective object lifts. We introduce a tensor decomposition to identify patterns of muscle activity and grip-load force ratios while also characterizing their temporal profiles and relative activation across object weights and participants of different age groups. We then probe age-induced changes in these components. A classification analysis reveals three motor components that are differentially recruited between the two age groups. Linear regression analyses further show that advanced age and poorer manual dexterity can be predicted by the coupled activation of forearm and hand muscles which is associated with high levels of grip force. Our findings suggest that ageing may induce stronger muscle couplings in distal aspects of the upper limbs, and a less economic grasping strategy to overcome age-related decline in manual dexterity.

Abstract The dynamics of nonlinear ion-acoustic solitary waves in the presence of kinetic (Landau type) damping have been investigated in a collisionless, non-magnetized electron-ion plasma. A cold ion fluid model, coupled to a Vlasov-type kinetic equation for the electron dynamics, has been adopted as a starting point. The electron population was assumed to be in a kappa-distributed state, in account of the non-Maxwellian behavior of energetic (suprathermal) electrons often observed in Space. A multiscale perturbation technique has led to an evolution equation for the electrostatic potential, in the form of a modified Korteweg-de Vries (KdV) equation, incorporating a non-local term accounting for Landau damping (associated with the electron statistics). Exact analytical solutions have been obtained, representing solitary waves undergoing amplitude decay over time. The combined effect of Landau damping and non-Maxwellian electron statistics (via the kappa parameter) on the characteristics of IASWs has been examined. Numerical integration of the evolution equation has been undertaken, to elucidate the importance of kinetic Landau damping on a shock-shaped initial condition. The results of this investigation aim to improve our understanding of the dynamics of nonlinear electrostatic waves under the influence of Landau damping in various space plasma environments.

The blood-brain barrier (BBB) plays a pivotal role in protecting the central nervous system (CNS), and shielding it from potential harmful entities. A natural decline of BBB function with aging has been reported in both animal and human studies, which may contribute to cognitive decline and neurodegenerative disorders. Limited data also suggest that being female may be associated with protective effects on BBB function. Here, we investigated age and sex-dependent trajectories of perfusion and BBB water exchange rate (kw) across the lifespan in 186 cognitively normal participants spanning the ages of 8–92 years old, using a non-invasive diffusion-prepared pseudo-continuous arterial spin labeling (DP-pCASL) MRI technique. We found that the pattern of BBB kw decline with aging varies across brain regions. Moreover, results from our DP-pCASL technique revealed a remarkable decline in BBB kw beginning in the early 60 s, which was more pronounced in males. In addition, we observed sex differences in parietal and temporal regions. Our findings provide in vivo results demonstrating sex differences in the decline of BBB function with aging, which may serve as a foundation for future investigations into perfusion and BBB function in neurodegenerative and other brain disorders.

Freshwater crayfish are amongst the largest macroinvertebrates and play a keystone role in the ecosystems they occupy. Understanding the global distribution of these animals is often hindered due to a paucity of distributional data. Additionally, non-native crayfish introductions are becoming more frequent, which can cause severe environmental and economic impacts. Management decisions related to crayfish and their habitats require accurate, up-to-date distribution data and mapping tools. Such data are currently patchily distributed with limited accessibility and are rarely up-to-date. To address these challenges, we developed a versatile e-portal to host distributional data of freshwater crayfish and their pathogens (using Aphanomyces astaci, the causative agent of the crayfish plague, as the most prominent example). Populated with expert data and operating in near real-time, World of Crayfish™ is a living, publicly available database providing worldwide distributional data sourced by experts in the field. The database offers open access to the data through specialized standard geospatial services (Web Map Service, Web Feature Service) enabling users to view, embed, and download customizable outputs for various applications. The platform is designed to support technical enhancements in the future, with the potential to eventually incorporate various additional features. This tool serves as a step forward towards a modern era of conservation planning and management of freshwater biodiversity.

Background Whole-body magnetic resonance imaging is accurate, efficient and cost-effective for cancer staging. Machine learning may support radiologists reading whole-body magnetic resonance imaging. Objectives To develop a machine-learning algorithm to detect normal organs and cancer lesions. To compare diagnostic accuracy, time and agreement of radiology reads to detect metastases using whole-body magnetic resonance imaging with concurrent machine learning (whole-body magnetic resonance imaging + machine learning) against standard whole-body magnetic resonance imaging (whole-body magnetic resonance imaging + standard deviation). Design and participants Retrospective analysis of (1) prospective single-centre study in healthy volunteers > 18 years (n = 51) and (2) prospective multicentre STREAMLINE study patient data (n = 438). Tests Index: whole-body magnetic resonance imaging + machine learning. Comparator: whole-body magnetic resonance imaging + standard deviation. Reference standard Previously established expert panel consensus reference at 12 months from diagnosis. Outcome measures Primary: difference in per-patient specificity between whole-body magnetic resonance imaging + machine learning and whole-body magnetic resonance imaging + standard deviation. Secondary: per-patient sensitivity, per-lesion sensitivity and specificity, read time and agreement. Methods Phase 1: classification forests, convolutional neural networks, and a multi-atlas approaches for organ segmentation. Phase 2/3: whole-body magnetic resonance imaging scans were allocated to Phase 2 (training = 226, validation = 45) and Phase 3 (testing = 193). Disease sites were manually labelled. The final algorithm was applied to 193 Phase 3 cases, generating probability heatmaps. Twenty-five radiologists (18 experienced, 7 inexperienced in whole-body magnetic resonance imaging) were randomly allocated whole-body magnetic resonance imaging + machine learning or whole-body magnetic resonance imaging + standard deviation over two or three rounds in a National Health Service setting. Read time was independently recorded. Results Phases 1 and 2: convolutional neural network had best Dice similarity coefficient, recall and precision measurements for healthy organ segmentation. Final algorithm used a ‘two-stage’ initial organ identification followed by lesion detection. Phase 3: evaluable scans (188/193, of which 50 had metastases from 117 colon, 71 lung cancer cases) were read between November 2019 and March 2020. For experienced readers, per-patient specificity for detection of metastases was 86.2% (whole-body magnetic resonance imaging + machine learning) and 87.7% (whole-body magnetic resonance imaging + standard deviation), (difference −1.5%, 95% confidence interval −6.4% to 3.5%; p = 0.387); per-patient sensitivity was 66.0% (whole-body magnetic resonance imaging + machine learning) and 70.0% (whole-body magnetic resonance imaging + standard deviation) (difference −4.0%, 95% confidence interval −13.5% to 5.5%; p = 0.344). For inexperienced readers (53 reads, 15 with metastases), per-patient specificity was 76.3% in both groups with sensitivities of 73.3% (whole-body magnetic resonance imaging + machine learning) and 60.0% (whole-body magnetic resonance imaging + standard deviation). Per-site specificity remained high within all sites; above 95% (experienced) or 90% (inexperienced). Per-site sensitivity was highly variable due to low number of lesions in each site. Reading time lowered under machine learning by 6.2% (95% confidence interval −22.8% to 10.0%). Read time was primarily influenced by read round with round 2 read times reduced by 32% (95% confidence interval 20.8% to 42.8%) overall with subsequent regression analysis showing a significant effect (p = 0.0281) by using machine learning in round 2 estimated as 286 seconds (or 11%) quicker. Interobserver variance for experienced readers suggests moderate agreement, Cohen’s κ = 0.64, 95% confidence interval 0.47 to 0.81 (whole-body magnetic resonance imaging + machine learning) and Cohen’s κ = 0.66, 95% confidence interval 0.47 to 0.81 (whole-body magnetic resonance imaging + standard deviation). Limitations Patient whole-body magnetic resonance imaging data were heterogeneous with relatively few metastatic lesions in a wide variety of locations, making training and testing difficult and hampering evaluation of sensitivity. Conclusions There was no difference in diagnostic accuracy for whole-body magnetic resonance imaging radiology reads with or without machine-learning support, although radiology read time may be slightly shortened using whole-body magnetic resonance imaging + machine learning. Future work Failure-case analysis to improve model training, automate lesion segmentation and transfer of machine-learning techniques to other tumour types and imaging modalities. Study registration This study is registered as ISRCTN23068310. Funding This award was funded by the National Institute for Health and Care Research (NIHR) Efficacy and Mechanism Evaluation (EME) programme (NIHR award ref: 13/122/01) and is published in full in Efficacy and Mechanism Evaluation; Vol. 11, No. 15. See the NIHR Funding and Awards website for further award information. Plain language summary Whole-body magnetic resonance imaging demonstrates the entire body and can detect the spread of tumour, without the burden of ionising radiation. Recently, the STREAMLINE study reported that whole-body magnetic resonance imaging is accurate, efficient and cost-effective for cancer staging. However, whole-body magnetic resonance imaging is complex to report. Machine learning is a type of artificial intelligence whereby a computer learns from being given previous data to undertake a task, using techniques such as classification forests, convolutional neural networks, and multi-atlas approaches. Our aim was to develop a machine-learning method to automatically detect lesions on whole-body magnetic resonance imaging to support radiologists by potentially improving their ability to correctly detect disease and reduce the reading time of whole-body magnetic resonance imaging scans in patients with cancer. Firstly, whole-body magnetic resonance imaging scans from 51 healthy volunteers were used to develop machine-learning methods to automatically detect normal organs. Secondly, machine-learning methods were trained to detect cancer lesions, using 271 whole-body magnetic resonance imaging scans from a previous study. Finally, the refined machine-learning technique was tested in 188 patient scans from a previous study, to see if the technique could improve radiology reporting by increasing accuracy and speed in detecting disease. We designed a system to test the accuracy of radiologists reading whole-body magnetic resonance imaging with or without machine-learning support in a near-real clinical National Health Service setting. Twenty-five independent radiologists (18 experienced in reading whole-body magnetic resonance imaging and 7 radiologists inexperienced in whole-body magnetic resonance imaging) were randomly allocated whole-body magnetic resonance imaging scans to read with or without machine-learning support. We found that machine-learning support resulted in similar accuracy for detecting disease and was slightly more efficient in the reading time than for radiological reads without machine-learning support. Differences in interpretation between experienced readers were considered moderate in both cases. Overall, the study was an ambitious attempt to undertake a highly complex machine-learning task, to detect cancer on whole-body magnetic resonance imaging. Many important steps have been taken but the current machine-learning algorithm did not result in a significant improvement in the radiologist’s accuracy for disease detection, although it may have slightly reduced the time taken to read the study. Future work is advocated to further develop machine-learning tools to improve the accuracy of tumour detection. Scientific summary Background Whole-body magnetic resonance imaging (WB-MRI) has been developed in the last decade and it has been proposed as an alternative to multimodality cancer staging pathways. The STREAMLINE study has demonstrated that staging of lung and colon cancer via WB-MRI was of similar accuracy to standard care staging pathways but resulted in fewer tests being required, and a reduction in staging time and cost. However, this technique has not widely translated into clinical practice, being limited to a few expert centres. A barrier to translation may be the complexity of interpretation by inexperienced readers. A machine-learning (ML) algorithm for automated detection of cancer lesions, to assist radiologists, may allow clinical translation of WB-MRI for the benefit of patient care. Objective The objective of Phases 1 and 2 was to develop a ML method for automatic detection of cancer lesions on WB-MRI. The primary objective of Phase 3 was to compare the diagnostic test accuracy of WB-MRI in patients being staged for cancer with and without ML support, when read by independent, experienced readers. The reference standard was the consensus reference panel from the STREAMLINE study, which had recorded the sites of disease in the STREAMLINE patients using all available clinical information for a 12-month follow-up from time of enrolment. The planned secondary objectives of this study were: to compare the reading time of WB-MRI scans, with and without ML support; to determine the interobserver variability of WB-MRI diagnosis by different radiologists, with and without ML support; to evaluate the diagnostic accuracy of WB-MRI read by non-experienced readers, with and without ML support; to evaluate different combinations of acquired MRI sequences; all the above with and without ML support (not achieved); to determine any difference in costs related to radiology reading time by means of a simple cost-effectiveness analysis (not achieved). Design This was an observational study (study limited to working with data), using different patient cohorts, and methodologies, being evaluated in series during three consecutive phases. Phase 1: Previously acquired WB-MRI scans in 51 healthy volunteers were stitched into imaging volumes. The normal organs and skeleton were segmented by a trained radiologist. We compared and tested several state-of-the-art medical image segmentation methods to train an algorithm to automatically detect and segment the organs. This included a multi-atlas (MA) approach, classification forests (CFs) and convolutional neural networks (CNNs) methods. For the CFs method, we used 50 trees with a maximum tree depth of 30 in the segmentation. The stopping criterion for growing trees was if either the objective function (information gain) could not be further improved or the number of training samples in a leaf fell below a threshold of four samples. For the CNNs method, we employed a dual pathway (2 resolutions), 11-layer deep CNN, where the last 2 layers correspond to fully connected layers, which combine the features extracted on the 2 resolution pathways. We adopted 50–70 feature maps (different kernels) for each layer. The network architecture was fully convolutional and there were no max-pooling layers, which we found to increase segmentation accuracy. The CNN architecture was a balance between model capacity, training efficiency, and memory demands. The third algorithm was based on a MA label propagation approach. MA segmentation uses a set of atlases (images with corresponding segmentations) that represent the interparticipant variability of the anatomy to be segmented. Each atlas was registered to the new image to be segmented using a deformable image registration. The MA approach accounts for anatomical shape variability and is more robust than single-atlas propagation methods, in that at any errors associated with propagation were averaged out when combining multiple atlases. The approach employed here makes use of efficient 3D–3D intensity-based image registration with free-form deformations as the transformation model and correlation coefficient as the similarity measure. Majority voting is used to derive the final tissue label at each voxel. Phase 2: Available WB-MRI scans from the STREAMLINE study (n = 438) were allocated by the study statistician to Phase 2 (model training) and clinical validation (hold-out set of 193 cases). The visible lesions in cases allocated to Phase 2 were segmented by trained radiologists, using the defined consensus reference standard for the sites of disease. Using 226 evaluable and annotated cases, we trained a model for lesion detection and localisation rather than attempting accurate automated segmentation. We found that lesion detection in WB-MRI was suboptimal with the CNN alone. An optimal ‘two-stage’ ML method was developed and tested. In the first stage of the ‘two-stage’ method, the information from Phase 1 was used to identify the position of organs and bones and in stage two, the lesions were detected. Stage two could be modular with respect to the anatomical location in which the suspected lesion could be found. The architecture and configuration of the used CNN were modified to achieve optimal performance. Phase 3: The final two-stage ML algorithm from Phase 2 was applied to the 193 cases that were held out for Phase 3, generating probability heatmap volumes. WB-MRI scans were reported by 25 independent radiologists (18 radiologists experienced in reading WB-MRI and 7 radiologists inexperienced in WB-MRI). All radiologists took part in the 1st and 2nd round reads which incorporated inter-rater reads, and 8 participated in the 3rd round read for intrarater reads. All reads were undertaken in an NHS radiology reporting room, although using a separate cloud-based picture archiving and communication system (PACS). Based on experience level, 10–16 cases were randomly allocated by the study statistician to the reading lists for inexperienced or experienced radiologists. Each radiologist read both lung and colon cases with and without ML as a paired cohort. There were at least 4 weeks interval between each reading round for individual radiologists. Cases allocated to round 1 would be a random mixture of cases with and without ML support and then in round 2 the cases would be reversed such that each case was read once with and once without ML support. The number of cases with and without ML output was balanced in each reading round. A scribe recorded reading time. Results Phase 1 results We found that CNNs outperformed CFs and the MA algorithm when T2w volumes were used as input to the algorithms and when using pooled overlap-evaluation metrics [Dice similarity coefficient (DSC), recall (RE), precision (PR)] to assess the accuracy of segmentation. When the performance of the algorithms was assessed, with pooled surface distance metrics [average surface distance (ASD), root-mean-square surface distance (RMSSD), and Hausdorff distance (HD)], it was the MA algorithm that performed best. Single misinterpreted voxels in CFs and CNNs can greatly elevate ASD, RMSSD, and HD; these metrics are particularly sensitive to outliers. We then assessed the pooled metrics performance of CFs and CNNs when using all imaging combinations [T2w + T1w + diffusion-weighted imaging (DWI)] as input, arguing that maximisation of training information to the algorithms might improve the performance of segmentation. We found that the performance of CFs was improved, however not significantly, when using all imaging combinations as input for training. The opposite was observed for CNNs. The findings for the pooled metrics analysis, described above, were corroborated by a ‘per-organ’ quantitative analysis of the commonly used DSC, to assess the performance of our segmentation algorithms. This analysis confirmed that for all individual anatomical structures (except for the bladder), the algorithm that returned the greatest DSC was CNNs with T2w images only used as input. As our morphological T2w and T1w scans were acquired using breath-holds and the DWI sequence was acquired with free breathing, we found that there was significant displacement between soft tissues in anatomical areas adjacent to the diaphragm between these types of scans. As the employed affine registration method could not fully compensate for nonlinear motions caused by breathing, we assumed that misregistration could be the reason why the performance of CNNs, despite performing better than the other two algorithms when using T2w volumes as input only, was degraded when using all imaging combinations as input for training. A more robust, nonlinear registration method could improve the accuracy of CNNs and further improve the performance of CFs. The performance of our methods cannot be directly compared to similar methods in the literature because there is no previous work describing automatic, simultaneous segmentation of healthy organs and bones in multiparametric WB-MRI. We believe, however, that our methods may compare favourably to other ML methods for detection and segmentation in medical imaging because our classifiers are inherently multilabel and effective training was achieved when using a relatively small number of data sets, something that is very important in the clinical setting. However, we still need to address the performance limitations of our algorithms when segmenting organs with big variability in appearance (e.g. the gallbladder or the pancreas). Phase 2 results We tested different ML methods for lesion detection. We found that using CNNs was not optimal for lesion detection on WB-MRI. This may have been due to the small fraction of lesion volume occupying the scanned space, when compared to the WB volume. It may also have been due to the complexity of intensities in background tissue and the lesion with weak boundaries causing challenges for the CNNs. We, therefore, adapted our process to become an optimal two-stage process, with an initial stage for detection of organs as per the Phase 1 technique followed by a CNN to detect lesions. Stage two could be modular with respect to the anatomical location where the suspected lesion can be found. The architecture and configuration of the used CNN could be modified to achieve optimal performance for lesion detection. Phase 3 results All radiology reads were completed between November 2019 and March 2020. Among the 193 cases allocated to Phase 3, 188 WB-MRI scans were evaluable (117 colon and 71 lung cancer) and 50/188 cases had metastases. Per-patient specificity for detection of metastases within experienced readers was 86.2% (WB-MRI + ML) and 87.7% [WB-MRI + standard deviation (SD)], [difference −1.5%, 95% confidence interval (CI) −6.4%, 3.5%; p = 0.387]. Per-patient sensitivity produced results of 66.0% (WB-MRI + ML) and 70.0% (WB-MRI + SD) (difference −4.0%, 95% CI −13.5% to 5.5%; p = 0.344). For inexperienced readers (53 reads, 15 with metastases), per-patient specificity was 76.3% in both groups with sensitivities of 73.3% (WB-MRI + ML) and 60.0% (WB-MRI + SD). Per-site specificity remained high within all sites; above 95% (experienced) or 90% (inexperienced). Per-site sensitivity was highly variable due to the low number of lesions in each site, hampering interpretation. Reading time was lowered under ML by 6.2% (95% CI −22.8% to 10.0%). Read time was primarily influenced by read round with round 2 read times reduced by 32% (95% CI 20.8% to 42.8%) overall with subsequent regression analysis showing a significant effect (p = 0.0281) by using ML in round 2 estimated as 286 seconds (or 11%) quicker. Interobserver variance for experienced readers suggests moderate agreement, Cohen’s κ = 0.64, 95% CI 0.47 to 0.81 (WB-MRI + ML) and Cohen’s κ = 0.66, 95% CI 0.47 to 0.81 (WB-MRI + SD). Conclusion Phase 1 In Phase 1, we developed and evaluated three state-of-the-art algorithms that automatically segment healthy organs and bones in WB-MRI with accuracy comparable to the one achieved manually by clinical experts, using relatively sparse training data. An algorithm based on CNNs and trained using T2w-only images as input performs favourably when compared to CFs or a MA algorithm, trained with either T2w-only images or a combination of imaging inputs (T2w + T1w + DWI). Using multimodal MRI data as input for training did not improve the segmentation performance in this work, but it is anticipated to improve the segmentation performance if more effective WB registration between the various imaging modalities can be performed. This investigation was the first step towards developing robust algorithms for the automatic detection and segmentation of benign and malignant lesions in WB-MRI scans for staging of cancer patients. Phase 2 There were many challenges in training the algorithm for lesion detection, with a very heterogeneous data set, acquired at 16 sites on different machines. The low number of metastatic lesions were scattered through many anatomic sites. Identification of lesions of relatively small volume in relation to the large volume of the WB-MRI required a two-stage approach for lesion detection, with initial organ identification followed by lesion detection. Phase 3 We undertook a robust diagnostic test accuracy study comparing WB-MRI with ML support (index text) with standard WB-MRI, without ML support (comparator test), with paired reads separated by a wash-out period. Although there was no clear statistical difference with or without ML support in terms of diagnostic test accuracy, either in experienced or inexperienced hands, we found that ML reads were likely to be a little shorter in reading time. Implications for health care Machine learning support for image interpretation is a rapidly expanding area of research. With continually increasing demand for diagnostic imaging and a radiology workforce crisis in the NHS, as well as globally, ML techniques may offer support to allow complex imaging modalities, such as WB-MRI, to be ready for translation into clinical care for the benefit of patients. Phase 1 demonstrated that with relatively sparse data, we could develop very successful organ segmentation tools in highly complex data sets and this has many potential future roles. In this study, we used this as a first step prior to lesion detection and this generic method could be applied to a wider range of disease areas, including other tumour types. We found that ML support slightly shorted the reading time, although with no improvement in diagnostic accuracy. However, we have shown that lesion detection using ML is achievable on heterogeneous and complex multiparametric WB-MRI scans. With further model training, we believe that ML support is feasible in the future, with the potential to improve translation of WB-MRI more widely. In addition, many of the techniques that have been developed in the course of the study have the potential to be applied to other areas of diagnostic imaging. Recommendations for future research Future research should investigate: Further improvement in lesion detection accuracy, with evaluation of failure cases for improved model training. Evaluate lesion detection technique on other cancers, notably breast, prostate and myeloma. Further developments in understanding the marrow composition in healthy aging and in metastatic cancer. Developing further understanding and methods to overcome registration challenges between breath-hold and non-breath-hold MRI sequences in order to improve ML tissue characterisation. Study registration This study is registered as ISRCTN23068310. Funding This award was funded by the National Institute for Health and Care Research (NIHR) Efficacy and Mechanism Evaluation (EME) programme (NIHR award ref: 13/122/01) and is published in full in Efficacy and Mechanism Evaluation; Vol. 11, No. 15. See the NIHR Funding and Awards website for further award information.

This comprehensive review aims to delineate the prevailing non-cardiac thoracic injuries occurring in urban environments following initial on-site treatment and subsequent admission to hospital emergency departments. Our study involved a rigorous search within the PubMed database, employing key phrases and their combinations, including "thoracic injury," "thoracic trauma," "haemothorax," "lung contusion," "traumatic pneumothorax," "rib fractures," and "flail chest." We focused on original research articles and reviews. Non-cardiac thoracic injuries exhibit a high prevalence, often affecting poly-trauma patients, and contributing to up to 35% of polytrauma-related fatalities. Furthermore, severe thoracic injuries can result in a substantial 5% mortality rate. This review provides insights into clinical entities such as lung contusion, traumatic haemothorax, pneumothorax, rib fractures, and sternal fractures. Thoracic injuries represent a frequent and significant clinical concern for emergency department physicians and thoracic surgeons, warranting thorough understanding and timely intervention.

Background The risk of recurrence after nephrectomy for primary clear cell renal cell carcinoma (ccRCC) is estimated in daily practice solely based on clinical criteria. The aim of this study was to assess the prognostic relevance of common somatic mutations with respect to tumor aggressiveness and outcomes of ccRCC patients after definitive treatment. Methods Primary tumors from 37 patients with ccRCC who underwent radical nephrectomy were analyzed for presence of somatic mutations using a 15-gene targeted next-generation sequencing (NGS) panel. Associations to histopathologic characteristics and outcomes were investigated in the study cohort (n=37) and validated in The Cancer Genome Atlas (TCGA) ccRCC cohort (n=451). Results VHL was the most frequently mutated gene (51%), followed by PBRM1 (27%), BAP1 (13%), SETD2 (13%), KDM5C (5%), ATM (5%), MTOR (5%), and PTEN (3%). One-third of patients did not have any somatic mutations within the 15-gene panel. The vast majority of tumors harboring no mutations at all or VHL-only mutations (51%) were more frequently of smaller size (pT1-2) and earlier stage (I/II), whereas presence of any other gene mutations in various combinations with or without VHL was enriched in larger (pT3) and higher stage tumors (III) (p=0.02). No recurrences were noted in patients with unmutated tumors or VHL-only mutations as opposed to three relapses in patients with non-VHL somatic mutations (p=0.06). Presence of somatic mutations in PBRM1, BAP1, SETD2, KDM5C, ATM, MTOR, or PTEN genes in 451 TCGA ccRCC patients was associated with a significantly shorter disease-free survival (DFS) compared to those with unaltered tumors (q=0.01). Conclusions Preliminary findings from this ongoing study support the prognostic value of non-VHL mutations including PBRM1, BAP1, SETD2, KDM5C, ATM, MTOR, and PTEN in primary ccRCC tumors as surrogates of earlier recurrence and potential selection for adjuvant immune checkpoint inhibition.

A severe condition of sepsis can be a complication of necrotizing enterocolitis (NEC), which can occur in premature infants and becomes a medical challenge in the neonatal intensive care unit (NICU). It is a multifactorial intestinal disease (can affect both the small and large intestine) that can lead to ischemia of the intestinal tissues that evolves into acute organ necrosis. One of these factors is that different types of nutrition can influence the onset or the progression of the disease. Cow-milk-based infant formulas have been shown to cause it in premature infants more frequently than human milk. Recently, nutrition has been shown to be beneficial after surgery. Several issues still under study, such as the pathogenesis and the insufficient and often difficult therapeutic approach, as well as the lack of a common and effective prevention strategy, make this disease an enigma in daily clinical practice. Recent studies outlined the emerging role of the host immune system and resident gut microbiota, showing their close connection in NEC pathophysiology. In its initial stages, broad-spectrum antibiotics, bowel rest, and breastfeeding are currently used, as well as probiotics to help the development of the intestinal microbiota and its eubiosis. This paper aims to present the current knowledge and potential fields of research in NEC pathophysiology and therapeutic assessment.

Abstract Sensorimotor control of complex, dynamic systems such as humanoids or quadrupedal robots is notoriously difficult. While artificial systems traditionally employ hierarchical optimisation approaches or black-box policies, recent results in systems neuroscience suggest that complex behaviours such as locomotion and reaching are correlated with limit cycles in the primate motor cortex. A recent result suggests that, when applied to a learned latent space, oscillating patterns of activation can be used to control locomotion in a physical robot. While reminiscent of limit cycles observed in primate motor cortex, these dynamics are unsurprising given the cyclic nature of the robot’s behaviour (walking). In this preliminary investigation, we consider how a similar approach extends to a less obviously cyclic behaviour (reaching). This has been explored in prior work using computational simulations. But simulations necessarily make simplifying assumptions that do not necessarily correspond to reality, so do not trivially transfer to real robot platforms. Our primary contribution is to demonstrate that we can infer and control real robot states in a learnt representation using oscillatory dynamics during reaching tasks. We further show that the learned latent representation encodes interpretable movements in the robot’s workspace. Compared to robot locomotion, the dynamics that we observe for reaching are not fully cyclic, as they do not begin and end at the same position of latent space. However, they do begin to trace out the shape of a cycle, and, by construction, they are driven by the same underlying oscillatory mechanics.

Abstract Venous thromboembolism (VTE) is the leading cause of preventable death in hospitalized patients. Artificial intelligence (AI) and machine learning (ML) can support guidelines recommending an individualized approach to risk assessment and prophylaxis. We conducted electronic surveys asking clinician and healthcare informaticians about their perspectives on AI/ML for VTE prevention and management. Of 101 respondents to the informatician survey, most were 40 years or older, male, clinicians and data scientists, and had performed research on AI/ML. Of the 607 US-based respondents to the clinician survey, most were 40 years or younger, female, physicians, and had never used AI to inform clinical practice. Most informaticians agreed that AI/ML can be used to manage VTE (56.0%). Over one-third were concerned that clinicians would not use the technology (38.9%), but the majority of clinicians believed that AI/ML probably or definitely can help with VTE prevention (70.1%). The most common concern in both groups was a perceived lack of transparency (informaticians 54.4%; clinicians 25.4%). These two surveys revealed that key stakeholders are interested in AI/ML for VTE prevention and management, and identified potential barriers to address prior to implementation.

In addition to motor symptoms, neurocognitive impairment (NCI) affects patients with prodromal Parkinson’s disease (PD). NCI in PD ranges from subjective cognitive complaints to dementia. The purpose of this review is to present the available evidence of NCI in PD and highlight the heterogeneity of NCI phenotypes as well as the range of factors that contribute to NCI onset and progression. A review of publications related to NCI in PD up to March 2023 was performed using PubMed/Medline. There is an interconnection between the neurocognitive and motor symptoms of the disease, suggesting a common underlying pathophysiology as well as an interconnection between NCI and non-motor symptoms, such as mood disorders, which may contribute to confounding NCI. Motor and non-motor symptom evaluation could be used prognostically for NCI onset and progression in combination with imaging, laboratory, and genetic data. Additionally, the implications of NCI on the social cognition of afflicted patients warrant its prompt management. The etiology of NCI onset and its progression in PD is multifactorial and its effects are equally grave as the motor effects. This review highlights the importance of the prompt identification of subjective cognitive complaints in PD patients and NCI management.

Abstract Using smartphone-based ecological momentary assessment, this study investigated an association between natural diversity on mental wellbeing. A sample of 1,998 participants completed 41,448 assessments between April 2018 and September 2023. Environments which included a larger range of natural features, such as trees, plants and birdlife (high natural diversity) were associated with greater mental wellbeing than environments including a smaller range of natural features (low natural diversity). There was evidence of a mediating effect of natural diversity on the association between natural environments and mental wellbeing. These results highlight the importance of policies and practices that support richness of biodiversity for public mental health.

Background Older individuals are usually treated as a homogenous group despite evidence that old age consists of distinct subphases. This observational study including 493 older patients aimed to identify differences among age subgroups of older persons. Receiver operating characteristic (ROC) curve analysis was then applied to identify the optimal age cutoff points to distinguish those age groups. Methods Data were collected on the demographics of older patients, their medical and medication histories, dependence on activities of daily living (ADLs), and instrumental activities of daily living (IADLs). Non-parametric tests (Kruskal–Wallis and Mann–Whitney U tests) and ROC curves were used for statistical analysis. Results The 65–79 and ≥80 years of age groups showed distinct frailty status, comorbidity, and dependency in ADLs. The median age to remain completely independent in IADLs was 76–79 years, while the median age for being free from geriatric syndromes was slightly higher (77–80 years) and reached 82 years for the absence of delirium, falls, and swallowing problems. In the ROC analysis, the optimal cutoff ages for the presence of frailty, cognitive impairment, and dependency in ADLs were 80–82 years. Conclusion The 65–79 and ≥80 years of age groups differed significantly in numerous parameters, underscoring the need to address these distinct age groups differently, both for applying medical therapies and interventions, as well as for conducting health research.

Abstract Insect-based diets are gaining interest as potential ingredients in improving poultry gut health. This study assessed the dietary treatment with whole dried Tenebrio molitor larvae (TM) on broiler chickens’ gut microbiota and morphology. 120 Ross-308 broilers received treated diets with 5% (TM5) and 10% (TM10) replacement ratio in a 35-day trial. Intestinal histomorphometry was assessed, as well as claudin-3 expression pattern and ileal and caecal digesta for microbial community diversity. Null hypothesis was tested with two-way ANOVA considering the intestinal segment and diet as main factors. The TM5 group presented higher villi in the duodenum and ileum compared to the other two (P

Abstract Analysis of coupling between the phases and amplitudes of neural oscillations has gained increasing attention as an important mechanism for large-scale brain network dynamics. In Parkinson’s disease (PD), preliminary evidence indicates abnormal beta-phase coupling to gamma-amplitude in different brain areas, including the subthalamic nucleus (STN). We analyzed bilateral STN local field potentials (LFPs) in eight subjects with PD chronically implanted with deep brain stimulation electrodes during upright quiet standing and unperturbed walking. Phase-amplitude coupling (PAC) was computed using the Kullback-Liebler method, based on the modulation index. Neurophysiological recordings were correlated with clinical and kinematic measurements and individual molecular brain imaging studies ([123I]FP-CIT and single-photon emission computed tomography). We showed a dopamine-related increase in subthalamic beta-gamma PAC from standing to walking. Patients with poor PAC modulation and low PAC during walking spent significantly more time in the stance and double support phase of the gait cycle. Our results provide new insights into the subthalamic contribution to human gait and suggest cross-frequency coupling as a gateway mechanism to convey patient-specific information of motor control for human locomotion.

Abstract The bamboo-coral Isidella elongata is a key habitat-forming species in the deep Mediterranean Sea. This alcyonacean is listed as an indicator of Vulnerable Marine Ecosystems (VMEs) and as Critically Endangered due to bottom trawling impacts. In this work, a modeling approach was used to predict and map the habitat suitability of I. elongata in the Mediterranean Sea under current environmental conditions. Occurrence data were modeled as a function of environmental parameters. Using climate change scenarios and fishing effort data, the risk of climate change and fisheries impacts on habitat suitability were estimated, and climate refugia were identified. A drastic loss of habitat is predicted, and climate change scenarios suggest a loss of 60% of suitable habitats by 2100. In the central Mediterranean, climate refugia overlapped with active fishing grounds. This study represents the first attempt to identify hot spots for the protection of soft bottom Vulnerable Marine Ecosystems for the entire Mediterranean Sea, and highlights areas most at risk from trawling. This work is relevant to the objectives of the EU Marine Strategy Framework and Maritime Spatial Planning Directives, the Biodiversity Strategy for 2030 regarding priority areas for conservation.

Abstract A nonlinear system, exhibiting a unique asymptotic behaviour, while being continuously subject to a stimulus from a certain class, is said to suffer from fading memory. This interesting phenomenon was first uncovered in a non-volatile tantalum oxide-based memristor from Hewlett Packard Labs back in 2016 out of a deep numerical investigation of a predictive mathematical description, known as the Strachan model, later corroborated by experimental validation. It was then found out that fading memory is ubiquitous in non-volatile resistance switching memories. A nonlinear system may however also exhibit a local form of fading memory, in case, under an excitation from a given family, it may approach one of a number of distinct attractors, depending upon the initial condition. A recent bifurcation study of the Strachan model revealed how, under specific train stimuli, composed of two square pulses of opposite polarity per cycle, the simplest form of local fading memory affects the transient dynamics of the aforementioned Resistive Random Access Memory cell, which, would asymptotically act as a bistable oscillator. In this manuscript we propose an analytical methodology, based on the application of analysis tools from Nonlinear System Theory to the Strachan model, to craft the properties of a generalised pulse train stimulus in such a way to induce the emergence of complex local fading memory effects in the nano-device, which would consequently display an interesting tuneable multistable oscillatory response, around desired resistance states. The last part of the manuscript discusses a case study, shedding light on a potential application of the local history erase effects, induced in the device via pulse train stimulation, for compensating the unwanted yet unavoidable drifts in its resistance state under power off conditions.

Background: The ASCAPE project aims to improve the health-related quality of life of cancer patients using artificial intelligence (AI)-driven solutions. The current study employs a comprehensive dataset to evaluate sleep and urinary incontinence, thus enabling the development of personalized interventions. Methods: This study focuses on prostate cancer patients eligible for curative treatment with surgery. Forty-two participants were enrolled following their diagnosis and were followed up at baseline and 3, 6, 9, and 12 months after surgical treatment. The data collection process involved a combination of standardized questionnaires and wearable devices, providing a holistic view of patients’ QoL and health outcomes. The dataset is systematically organized and stored in a centralized database, with advanced statistical and AI techniques being employed to reveal correlations, patterns, and predictive markers that can ultimately lead to implementing personalized intervention strategies, ultimately enhancing patient QoL outcomes. Results: The correlation analysis between sleep quality and urinary symptoms post-surgery revealed a moderate positive correlation between baseline insomnia and baseline urinary symptoms (r = 0.407, p = 0.011), a positive correlation between baseline insomnia and urinary symptoms at 3 months (r = 0.321, p = 0.049), and significant correlations between insomnia at 12 months and urinary symptoms at 3 months (r = 0.396, p = 0.014) and at 6 months (r = 0.384, p = 0.017). Furthermore, modeling the relationship between baseline insomnia and baseline urinary symptoms showed that baseline insomnia is significantly associated with baseline urinary symptoms (coef = 0.222, p = 0.036). Conclusions: The investigation of sleep quality and urinary incontinence via data analysis through the ASCAPE project suggests that better sleep quality could improve urinary disorders.

Environmental disasters are extreme environmental processes such as earthquakes, volcanic eruptions, landslides, tsunamis, floods, cyclones, storms, wildfires and droughts that are the consequences of the climate crisis due to human intervention in the environment. Their effects on human health have alarmed the global scientific community. Among them, autoimmune diseases, a heterogeneous group of disorders, have increased dramatically in many parts of the world, likely as a result of changes in our exposure to environmental factors. However, only a limited number of studies have attempted to discover and analyze the complex association between environmental disasters and autoimmune diseases. This narrative review has therefore tried to fill this gap. First of all, the activation pathways of autoimmunity after environmental disasters have been analyzed. It has also been shown that wildfires, earthquakes, desert dust storms and volcanic eruptions may damage human health and induce autoimmune responses to inhaled PM2.5, mainly through oxidative stress pathways, increased pro-inflammatory cytokines and epithelial barrier damage. In addition, it has been shown that heat stress, in addition to increasing pro-inflammatory cytokines, may also disrupt the intestinal barrier, thereby increasing its permeability to toxins and pathogens or inducing epigenetic changes. In addition, toxic volcanic elements may accelerate the progressive destruction of myelin, which may potentially trigger multiple sclerosis. The complex and diverse mechanisms by which vector-borne, water-, food-, and rodent-borne diseases that often follow environmental diseases may also trigger autoimmune responses have also been described. In addition, the association between post-disaster stress and the onset or worsening of autoimmune disease has been demonstrated. Given all of the above, the rapid restoration of post-disaster health services to mitigate the flare-up of autoimmune conditions is critical.

Introduction The treatment of children with pelviureteric junction obstruction (PUJO) has naturally progressed from open, to minimally invasive approaches, including laparoscopic pyeloplasty and robot-assisted laparoscopic pyeloplasty (RALP). The RALP is now considered to be the gold standard for paediatric patients with PUJO, except for smaller infants due to size limitations. Our systematic review aims to synthesise all the available evidence regarding key postoperative outcomes for the three surgical approaches to pyeloplasties in children. Our outcomes of interest include, but are not limited to, the reoperation rate, length of hospital stay and postoperative complications as classified by the Clavien-Dindo grading system. A comprehensive assessment of all three methods in paediatric patients has yet to be conducted in the literature to date.Methods and analysis A systematic search of the MEDLINE, PubMed, EMBASE and Cochrane databases will be conducted. Screening, data extraction, statistical analysis and reporting will be performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Included papers will be full-text manuscripts written between 1947 and March 2024, comparing the outcomes and complications of open, laparoscopic and RALP. Quality and study bias will be assessed using the Newcastle-Ottawa score and, if relevant, the Cochrane risk of bias tool for randomised trials. This present protocol is written in accordance with the PRISMA Protocol 2015 checklist, ensuring that the highest methodological standards are adhered to.Ethics and dissemination No ethical approval shall be required, as this is a review of already published literature. Findings will be disseminated through publications in peer-reviewed journals and presentations at international and national conferences.PROSPERO registration number CRD42023456779.

The aim of this study was to evaluate the effect of starvation and refeeding on the growth and food intake of gilthead seabream (Sparus aurata) and seabass (Dicentrarchus labrax) and on the growth and nitrogen uptake of glasswort (Salicornia europaea) in a polyculture aquaponic system under 12 ppt salinity for 75 days. Nine small-scale autonomous aquaponic systems were used, each containing 10 gilthead seabreams (average weight of 6.33 ± 0.73 g and average length of 5.73 ± 0.72 cm) and 10 seabasses (5.82 ± 0.77 g and 6.35 ± 0.45 cm), as well as five glasswort plants. Three fish feeding treatments were performed, a control (A), in which fish were fed daily until satiation, and two fasting treatments for 4 (B) and 7 days (C). Fish growth performance was significantly lower (p

AIMS OF THE STUDY: Anti-reflux surgery aims to restore the anti-reflux barrier and reduce the retrograde flow of stomach contents. However, traditional surgical techniques generally involve some degree of encircling of the oesophagus, which can result in adverse effects such as dysphagia and the inability to belch or vomit. Based on the first published results, a novel surgical technique – with the RefluxStop™ device – appears promising for treating gastroesophageal reflux disease (GERD) with minimal postoperative dysphagia. This study describes the initial clinical experience with this procedure in a cohort of patients with chronic gastroesophageal reflux disease to evaluate its feasibility and safety in clinical practice. METHODS: This retrospective cohort study examined the first 40 patients who underwent laparoscopic anti-reflux surgery with the RefluxStop™ device at a private hospital in Switzerland. The procedure involves implanting a nonactive device on the outside of the gastric fundus to stabilise a narrow oesophagogastric plication. Feasibility was assessed based on the proportion of patients in whom the device could be successfully implanted, with a discussion of the operative details. Intraoperative and postoperative complications, adverse effects, and changes in gastroesophageal reflux disease-related quality of life (GERD-HRQL questionnaire) are also reported. RESULTS: Between May 2020 and April 2022, 40 patients underwent elective surgery for laparoscopic hiatal hernia repair and RefluxStop™ device implantation. All patients had typical symptoms of gastroesophageal reflux disease, such as heartburn and regurgitation; 20 (50%) had preoperative dysphagia. Laparoscopic surgery was feasible in all patients except one who required laparotomy due to adhesions and associated bleeding when accessing the abdomen. The median operating time was 57.5 minutes (interquartile range = 51.75–64.25 minutes) with no device-related intraoperative or postoperative complications. All patients were imaged one day and three months postoperative, confirming the correct placement of the device. Reflux symptoms (heartburn and acid regurgitation) were significantly improved in all patients at three months (p

BackgroundMultiple sclerosis (MS) is a chronic inflammatory disease affecting the central nervous system, often leading to poor sleep quality and diminished quality of life (QoL) for affected patients. Sleep disturbances in MS do not always correlate linearly with other symptoms such as anxiety, depression, fatigue, or pain. Various approaches, including stress reduction techniques such as mindfulness-based interventions, have been proposed to manage MS-related sleep issues. ObjectiveThe aim of this study was to evaluate the effects of the mindfulness-based body scan technique on sleep quality and QoL in patients with MS using both subjective (questionnaires) and objective (electronic portable device) measures. MethodsA single-case study was performed involving a 31-year-old woman diagnosed with relapsing-remitting MS. The patient practiced the mindfulness-based body scan technique daily before bedtime and outcomes were compared to measures evaluated at baseline. ResultsThe mindfulness-based body scan intervention demonstrated positive effects on both sleep quality and overall QoL. Biometric data revealed a notable dissociation between daily stress levels and sleep quality during the intervention period. Although self-report instruments indicated significant improvement, potential biases were noted. ConclusionsWhile this study is limited to a single patient, the promising outcomes suggest the need for further investigation on a larger scale. These findings underscore the potential benefits of the mindfulness-based body scan technique in managing sleep disturbances and enhancing QoL among patients with MS.

Objective To estimate the cost-effectiveness of craniotomy, compared with decompressive craniectomy (DC) in UK patients undergoing evacuation of acute subdural haematoma (ASDH).Design Economic evaluation undertaken using health resource use and outcome data from the 12-month multicentre, pragmatic, parallel-group, randomised, Randomised Evaluation of Surgery with Craniectomy for Patients Undergoing Evacuation-ASDH trial.Setting UK secondary care.Participants 248 UK patients undergoing surgery for traumatic ASDH were randomised to craniotomy (N=126) or DC (N=122).Interventions Surgical evacuation via craniotomy (bone flap replaced) or DC (bone flap left out with a view to replace later: cranioplasty surgery).Main outcome measures In the base-case analysis, costs were estimated from a National Health Service and Personal Social Services perspective. Outcomes were assessed via the quality-adjusted life-years (QALY) derived from the EuroQoL 5-Dimension 5-Level questionnaire (cost-utility analysis) and the Extended Glasgow Outcome Scale (GOSE) (cost-effectiveness analysis). Multiple imputation and regression analyses were conducted to estimate the mean incremental cost and effect of craniotomy compared with DC. The most cost-effective option was selected, irrespective of the level of statistical significance as is argued by economists.Results In the cost-utility analysis, the mean incremental cost of craniotomy compared with DC was estimated to be −£5520 (95% CI −£18 060 to £7020) with a mean QALY gain of 0.093 (95% CI 0.029 to 0.156). In the cost-effectiveness analysis, the mean incremental cost was estimated to be −£4536 (95% CI −£17 374 to £8301) with an OR of 1.682 (95% CI 0.995 to 2.842) for a favourable outcome on the GOSE.Conclusions In a UK population with traumatic ASDH, craniotomy was estimated to be cost-effective compared with DC: craniotomy was estimated to have a lower mean cost, higher mean QALY gain and higher probability of a more favourable outcome on the GOSE (though not all estimated differences between the two approaches were statistically significant).Ethics Ethical approval for the trial was obtained from the North West—Haydock Research Ethics Committee in the UK on 17 July 2014 (14/NW/1076).Trial registration number ISRCTN87370545.

Abstract Employing Empirical Dynamic Modelling we investigate whether model free methods could be applied in the study of Culex mosquitoes in Northern Greece. Applying Simplex Projection and S-Map algorithms on yearly timeseries of maximum abundances from 2011 to 2020 we successfully predict the decreasing trend in the maximum number of mosquitoes which was observed in the rural area of Thessaloniki during 2021. Leveraging the use of vector correlation metrics we were able to deduce the main environmental factors driving mosquito abundance such as temperature, rain and wind during 2012 and study the causal interaction between neighbouring populations in the industrial area of Thessaloniki between 2019 and 2020. In all three cases a chaotic and non-linear behaviour of the underlying system was observed. Given the health risk associated with the presence of mosquitoes as vectors of viral diseases these results hint to the usefulness of EDM methods in entomological studies as guides for the construction of more accurate and realistic mechanistic models which are indispensable to public health authorities for the design of targeted control strategies and health prevention measures.

Abstract In this commentary, we address a paper published by Johnson et al. by assessing the robustness of their method to discover diagnostic biomarkers in Alzheimer’s disease (AD). In addition, we examine how these newly discovered and previously discovered biomarkers, can play a role in assisting patients with AD and those at risk for developing AD, with an emphasis on the translational hurdles that accompany such discoveries.

Purpose: The purpose of this meta-analysis is to study the impact of varicocele repair in the largest cohort of infertile males with clinical varicocele by including all available studies, with no language restrictions, comparing intra-person conventional semen parameters before and after the repair of varicoceles. Materials and Methods: The meta-analysis was performed according to PRISMA-P and MOOSE guidelines. A systematic search was performed in Scopus, PubMed, Cochrane, and Embase databases. Eligible studies were selected according to the PICOS model (Population: infertile male patients with clinical varicocele; Intervention: varicocele repair; Comparison: intraperson before-after varicocele repair; Outcome: conventional semen parameters; Study type: randomized controlled trials [RCTs], observational and case-control studies). Results: Out of 1,632 screened abstracts, 351 articles (23 RCTs, 292 observational, and 36 case-control studies) were included in the quantitative analysis. The before-and-after analysis showed significant improvements in all semen parameters after varicocele repair (except sperm vitality); semen volume: standardized mean difference (SMD) 0.203, 95% CI: 0.129–0.278; p

Purpose: Sperm DNA fragmentation (SDF) is a functional sperm abnormality that can impact reproductive potential, for which four assays have been described in the recently published sixth edition of the WHO laboratory manual for the examination and processing of human semen. The purpose of this study was to examine the global practices related to the use of SDF assays and investigate the barriers and limitations that clinicians face in incorporating these tests into their practice. Materials and Methods: Clinicians managing male infertility were invited to complete an online survey on practices related to SDF diagnostic and treatment approaches. Their responses related to the technical aspects of SDF testing, current professional society guidelines, and the literature were used to generate expert recommendations via the Delphi method. Finally, challenges related to SDF that the clinicians encounter in their daily practice were captured. Results: The survey was completed by 436 reproductive clinicians. Overall, terminal deoxynucleotidyl transferase deoxyuridine triphosphate Nick-End Labeling (TUNEL) is the most commonly used assay chosen by 28.6%, followed by the sperm chromatin structure assay (24.1%), and the sperm chromatin dispersion (19.1%). The choice of the assay was largely influenced by availability (70% of respondents). A threshold of 30% was the most selected cut-off value for elevated SDF by 33.7% of clinicians. Of respondents, 53.6% recommend SDF testing after 3 to 5 days of abstinence. Although 75.3% believe SDF testing can provide an explanation for many unknown causes of infertility, the main limiting factors selected by respondents are a lack of professional society guideline recommendations (62.7%) and an absence of globally accepted references for SDF interpretation (50.3%). Conclusions: This study represents the largest global survey on the technical aspects of SDF testing as well as the barriers encountered by clinicians. Unified global recommendations regarding clinician implementation and standard laboratory interpretation of SDF testing are crucial.

Georg Bartisch, a 16th century barber surgeon, published in 1583 his treatise entitled "Ophthalmodouleia" (Greek term meaning eye service), a work in German to promote ophthalmology for his countrymen barber surgeons. He did not have an academic education nor knew classical languages, he had used a triplet in terminology by using German, Hellenic and Latin nomination in his anatomical descriptions. Various accurate illustrations and a peculiar system of presentation with flap to liken an in-depth presentation were demonstrated to add prestige in his work. This raises concerns for another medical surgeon to have helped for this publication. Bartisch innovative approaches introduced various surgical tools. Cataract surgery was the epitome of his work. Anatomy of both the eye and the eyelids was there for only to serve the operation. Religion, magic and Galenic views presented barriers for Bartisch's scientific development. However, he is considered as the patron of German School of Ophthalmology.