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BackgroundThe influence of atrial fibrillation (AF) and blood pressure (BP) on brain lesions and cognitive function is unclear. We aimed to investigate the association of BP with different types of brain lesions and cognitive decline in patients with AF.MethodsOverall, 1,213 AF patients underwent standardized brain magnetic resonance imaging at baseline and after 2 years, as well as yearly neurocognitive testing. BP was measured at baseline and categorized according to guidelines. New lesions were defined as new or enlarged brain lesions after 2 years. We defined cognitive decline using three different neurocognitive tests. Logistic and Cox regression analyses were performed to examine the associations of BP with new brain lesions and cognitive decline.ResultsThe mean age was 71 ± 8.4 years, 74% were male and mean BP was 135 ± 18/79 ± 12 mmHg. New ischemic lesions and white matter lesions were found in 5.4% and 18.4%, respectively. After multivariable adjustment, BP was not associated with the presence of new brain lesions after 2 years. There was no association between BP and cognitive decline over a median follow-up of 6 years when using the Montreal Cognitive Assessment or Digit Symbol Substitution Test. However, BP categories were inversely associated with cognitive decline using the Semantic Fluency Test, with the strongest association in patients with hypertension grade 1 [Hazard Ratio (95% Confidence Interval) 0.57(0.42 to 0.77)], compared to patients with optimal BP (p for linear trend: 0.025).ConclusionsIn a large cohort of AF patients, there was no association between BP and incidence of brain lesions after 2 years. Also, there was no consistent association between BP and cognitive decline over a follow-up of 6 years. Clinical Trial Registrationhttps://clinicaltrials.gov/study/NCT02105844, Identifier (NCT02105844).

Chronic total occlusions (CTOs) represent the most complex subset of coronary artery disease and therefore careful planning of CTO percutaneous coronary recanalization (PCI) strategy is of paramount importance aiming to achieve procedural success, and improve patient's safety and post CTO PCI outcomes. Intravascular imaging has an essential role in facilitating CTO PCΙ. First, intravascular ultrasound (IVUS), due to its higher penetration depth compared to optical coherence tomography (OCT), and the additional capacity of real-time imaging without need for contrast injection is considered the preferred imaging modality for CTO PCI. Secondly, IVUS can be used to resolve proximal cap ambiguity, facilitate wire re-entry when dissection and re-entry strategies are applied and most importantly to guide stent deployment and optimization post implantation. The role of OCT during CTO PCI is currently limited to stent sizing and optimization, however, due to its high spatial resolution, OCT is ideal for detecting stent edge dissections and strut malapposition. In this review, we describe the use of intravascular imaging for lesion crossing, plaque characterization and wire tracking, extra- or intra-plaque, and stent sizing and optimization during CTO PCI and summarize the findings of the major studies in this field.

BackgroundLongitudinal association studies of atrial fibrillation (AF) and cognitive functions have shown an unclear role of AF-type and often differ in methodological aspects. We therefore aim to investigate longitudinal changes in cognitive functions in association with AF-type (non-paroxysmal vs. paroxysmal) and comorbidities in the Swiss-AF cohort.MethodsSeven cognitive measures were administered up to five times between 2014 and 2022. Age-education standardized scores were calculated and association between longitudinal change in scores and baseline AF-type investigated using linear mixed-effects models. Associations between AF-type and time to cognitive drop, an observed score of at least one standard deviation below individual's age-education standardized cognitive scores at baseline, were studied using Cox proportional hazard models of each cognitive test, censoring patients at their last measurement. Models were adjusted for baseline covariates.Results2,415 AF patients (mean age 73.2 years; 1,080 paroxysmal, 1,335 non-paroxysmal AF) participated in this Swiss multicenter prospective cohort study. Mean cognitive scores increased longitudinally (median follow-up 3.97 years). Non-paroxysmal AF patients showed smaller longitudinal increases in Digit Symbol Substitution Test (DSST), Cognitive Construct Score (CoCo)and Trail Making Test part B (TMT-B) scores vs. paroxysmal AF patients. Diabetes, history of stroke/TIA and depression were associated with worse performance on all cognitive tests. No differences in time to cognitive drop were observed between AF-types in any cognitive test.ConclusionThis study indicated preserved cognitive functioning in AF patients, best explained by practice effects. Smaller practice effects were found in non-paroxysmal AF patients in the DSST, TMT-B and the CoCo and could indicate a marker of subtle cognitive decline. As diabetes, history of stroke/TIA and depression—but not AF-type—were associated with cognitive drop, more attention should be given to risk factors and underlying mechanisms of AF.

Inherited Arrhythmia Syndromes (IAS) including long QT and Brugada Syndrome, are characterized by life-threatening arrhythmias in the absence of apparent structural heart disease and are caused by pathogenic variants in genes encoding cardiac ion channels or associated proteins. Studies of large pedigrees of families affected by IAS have demonstrated incomplete penetrance and variable expressivity. Biological sex is one of several factors that have been recognized to modulate disease severity in IAS. There is a growing body of evidence linking sex hormones to the susceptibility to arrhythmias, yet, many sex-specific disease aspects remain underrecognized as female sex and women with IAS are underinvestigated and findings from male-predominant cohorts are often generalized to both sexes with minimal to no consideration of relevant sex-associated differences in prevalence, disease manifestations and outcome. In this review, we highlight current knowledge of sex-related biological differences in normal cardiac electrophysiology and sex-associated factors that influence IAS phenotypes.

Since the first groundbreaking procedure in 2002, transcatheter aortic valve implantation (TAVI) has revolutionized the management of aortic stenosis (AS). Through striking developments in pertinent equipment and techniques, TAVI has now become the leading therapeutic strategy for aortic valve replacement in patients with severe symptomatic AS. The procedure streamlining from routine use of conscious sedation to a single arterial access approach, the newly adapted implantation techniques, and the introduction of novel technologies such as intravascular lithotripsy and the refinement of valve-bioprosthesis devices along with the accumulating experience have resulted in a dramatic reduction of complications and have improved associated outcomes that are now considered comparable or even superior to surgical aortic valve replacement (SAVR). These advances have opened the road to the use of TAVI in younger and lower-risk patients and up-to-date data from landmark studies have now established the outstanding efficacy and safety of TAVI in patients with low-surgical risk impelling the most recent ESC guidelines to propose TAVI, as the main therapeutic strategy for patients with AS aged 75 years or older. In this article, we aim to summarize the most recent advances and the current clinical aspects involving the use of TAVI, and we also attempt to highlight impending concerns that need to be further addressed.

BackgroundRoutine coronary artery disease (CAD) secondary prevention strategies target standard modifiable cardiovascular risk factors (SMuRFs), which include: diabetes mellitus, dyslipidemia, hypertension, and smoking. However, a significant proportion of patients with acute coronary syndrome (ACS) present without any SMuRFs. The angiographic severity of disease in this population has not yet been investigated.MethodsAfter propensity score matching of patients without SMuRFs and patients with ≥1 SMuRFs (ratio 1:3), we used zero-inflated negative binomial regression modeling to investigate the relationship of SMuRF-less status with the angiographic severity of CAD, as measured by the SYNTAX score. Survival analysis was performed to investigate differences in all-cause mortality at 30 days and at the end of follow-up period.ResultsWe analyzed 534 patients presenting with ACS who underwent coronary angiography. Of them, 56 (10.5%) presented without any SMuRF. After propensity score matching, the median SYNTAX score was 13.8 (IQR 0–22.1) in 56 SMuRF-less patients and 14 (IQR 5–25) in 166 patients with ≥1 SMuRFs. SMuRF-less status was associated with increased odds of zero SYNTAX score [zero-part model: odds ratio = 2.11, 95% confidence interval (CI): 1.03–4.33], but not with decreased SYNTAX score among patients with non-zero SYNTAX score (count-part model: incidence rate ratio = 0.99, 95% CI: 0.79–1.24); the overall distribution of the SYNTAX score was similar between the two groups (p = 0.26). The 30-day risk for all-cause mortality was higher for SMuRF-less patients compared to patients with ≥1 SMuRFs [hazard ratio (HR) = 3.58, 95% CI: 1.30–9.88]; however, the all-cause mortality risk was not different between the two groups over a median 1.7-year follow-up (HR = 1.72, 95% CI: 0.83–3.57).ConclusionAmong patients with ACS, the absence of SMuRFs is associated with increased odds for non-obstructive CAD and with increased short-term mortality rates.

Despite the enormous success of artificial neural networks (ANNs) in many disciplines, the characterization of their computations and the origin of key properties such as generalization and robustness remain open questions. Recent literature suggests that robust networks with good generalization properties tend to be biased toward processing low frequencies in images. To explore the frequency bias hypothesis further, we develop an algorithm that allows us to learn modulatory masks highlighting the essential input frequencies needed for preserving a trained network's performance. We achieve this by imposing invariance in the loss with respect to such modulations in the input frequencies. We first use our method to test the low-frequency preference hypothesis of adversarially trained or data-augmented networks. Our results suggest that adversarially robust networks indeed exhibit a low-frequency bias but we find this bias is also dependent on directions in frequency space. However, this is not necessarily true for other types of data augmentation. Our results also indicate that the essential frequencies in question are effectively the ones used to achieve generalization in the first place. Surprisingly, images seen through these modulatory masks are not recognizable and resemble texture-like patterns.

BackgroundThe relationship between inflammation and corrected QT (QTc) interval prolongation is currently not well defined in patients with COVID-19.ObjectiveThis study aimed to assess the effect of marked interval changes in the inflammatory marker C-reactive protein (CRP) on QTc interval in patients hospitalized with COVID-19.MethodsIn this retrospective cohort study of hospitalized adult patients admitted with COVID-19 infection, we identified 85 patients who had markedly elevated CRP levels and serial measurements of an ECG and CRP during the same admission. We compared mean QTc interval duration, and other clinical and ECG characteristics between times when CRP values were high and low. We performed mixed-effects linear regression analysis to identify associations between CRP levels and QTc interval in univariable and adjusted models.ResultsMean age was 58 ± 16 years, of which 39% were women, 41% were Black, and 25% were White. On average, the QTc interval calculated via the Bazett formula was 15 ms higher when the CRP values were “high” vs. “low” [447 ms (IQR 427–472 ms) and 432 ms (IQR 412–452 ms), respectively]. A 100 mg/L increase in CRP was associated with a 1.5 ms increase in QTc interval [β coefficient 0.15, 95% CI (0.06–0.24). In a fully adjusted model for sociodemographic, ECG, and clinical factors, the association remained significant (β coefficient 0.14, 95% CI 0.05–0.23).ConclusionAn interval QTc interval prolongation is observed with a marked elevation in CRP levels in patients with COVID-19.

Pharmaceutical production quality has recently been a focus for improvement through incorporation of end-to-end continuous processing. Enzymatic ß-lactam antibiotic synthesis has been one focus for continuous manufacturing, and α-amino ester hydrolases (AEHs) are currently being explored for use in the synthesis of cephalexin due to their high reactivity and selectivity. In this study, several reactors were simulated to determine how reactor type and configuration impacts reactant conversion, fractional yield toward cephalexin, and volumetric productivity for AEH-catalyzed cephalexin synthesis. The primary reactor configurations studied are single reactors including a continuous stirred-tank reactor (CSTR) and plug flow reactor (PFR) as well as two CSTRS and a CSTR + PFR in series. Substrate concentrations fed to the reactors as well as enzyme concentration in the reactor were varied. The presence of substrate inhibition was found to have a negative impact on all reactor configurations studied. No reactor configuration simultaneously allowed high substrate conversion, high fractional yield, and high productivity; however, a single PFR was found to enable the highest substrate conversion with higher fractional yields than all other reactor configurations, by minimizing substrate inhibition. Finally, to further demonstrate the impact of substrate inhibition, an AEH engineered to improve substrate inhibition was simulated and Pareto optimal fronts for a CSTR catalyzed with the current AEH were compared to Pareto fronts for the improved AEH. Overall, reduced substrate inhibition would allow for high substrate conversion, fractional yield, and productivity with only a single CSTR.

Plant tetrapyrrole biosynthesis (TPS) provides the indispensable chlorophyll (Chl) and heme molecules in photosynthetic organisms. Post-translational mechanisms control the enzymes to ensure a balanced flow of intermediates in the pathway and synthesis of appropriate amounts of both endproducts. One of the critical regulators of TPS is GENOMES UNCOUPLED 4 (GUN4). GUN4 interacts with magnesium chelatase (MgCh), and its binding of the catalytic substrate and product of the MgCh reaction stimulates the insertion of Mg2+ into protoporphyrin IX. Despite numerous in vitro studies, knowledge about the in vivo function of the GUN4:porphyrin interaction for the whole TPS pathway, particularly in plants, is still limited. To address this, we focused on two highly conserved amino acids crucial for porphyrin-binding to GUN4 and analyzed GUN4-F191A, R211A, and R211E substitution mutants in vitro and in vivo. Our analysis confirmed the importance of these amino acids for porphyrin-binding and the stimulation of plant MgCh by GUN4 in vitro. Expression of porphyrin-binding deficient F191A, R211A, and R211E in the Arabidopsis gun4-2 knockout mutant background revealed that, unlike in cyanobacteria and green algae, GUN4:porphyrin interactions did not affect the stability of GUN4 or other Arabidopsis TPS pathway enzymes in vivo. In addition, although they shared diminished porphyrin-binding and MgCh activation in vitro, expression of the different GUN4 mutants in gun4-2 had divergent effects on the TPS and the accumulation of Chl and Chl-binding proteins. For instance, expression of R211E, but not R211A, induced a substantial decrease of ALA synthesis rate, lower TPS intermediate and Chl level, and strongly impaired accumulation of photosynthetic complexes compared to wild-type plants. Furthermore, the presence of R211E led to significant growth retardation and paler leaves compared to GUN4 knockdown mutants, indicating that the exchange of R211 to glutamate compromised TPS and Chl accumulation more substantially than the almost complete lack of GUN4. Extensive in vivo analysis of GUN4 point mutants suggested that F191 and R211 might also play a role beyond porphyrin-binding.

Our study aims to develop a data-driven framework utilizing heterogenous electronic medical and clinical records and advanced Machine Learning (ML) approaches for: (i) the identification of critical risk factors affecting the complexity of Coronary Artery Disease (CAD), as assessed via the SYNTAX score; and (ii) the development of ML prediction models for accurate estimation of the expected SYNTAX score. We propose a two-part modeling technique separating the process into two distinct phases: (a) a binary classification task for predicting, whether a patient is more likely to present with a non-zero SYNTAX score; and (b) a regression task to predict the expected SYNTAX score accountable to individual patients with a non-zero SYNTAX score. The framework is based on data collected from the GESS trial (NCT03150680) comprising electronic medical and clinical records for 303 adult patients with suspected CAD, having undergone invasive coronary angiography in AHEPA University Hospital of Thessaloniki, Greece. The deployment of the proposed approach demonstrated that atherogenic index of plasma levels, diabetes mellitus and hypertension can be considered as important risk factors for discriminating patients into zero- and non-zero SYNTAX score groups, whereas diastolic and systolic arterial blood pressure, peripheral vascular disease and body mass index can be considered as significant risk factors for providing an accurate estimation of the expected SYNTAX score, given that a patient belongs to the non-zero SYNTAX score group. The experimental findings utilizing the identified set of important risk factors indicate a sufficient prediction performance for the Support Vector Machine model (classification task) with an F-measure score of ~0.71 and the Support Vector Regression model (regression task) with a median absolute error value of ~6.5. The proposed data-driven framework described herein present evidence of the prediction capacity and the potential clinical usefulness of the developed risk-stratification models. However, further experimentation in a larger clinical setting is needed to ensure the practical utility of the presented models in a way to contribute to a more personalized management and counseling of CAD patients.

Both aortic aneurysm and dissection are life threatening pathologies. In the lack of a conservative medical treatment, the only therapy consists of modifying cardiovascular risk factors and either surgical or endovascular treatment. Like many other cardiovascular diseases, in particular atherosclerosis, aortic aneurysm and dissection have a strong inflammatory phenotype. Inflammasomes are part of the innate immune system. Upon stimulation they form multi protein complexes resulting mainly in activation of interleukin-1β and other cytokines. Considering the gathering evidence, that inflammasomes are decisively involved in the emergence and progression of aortic diseases, inflammasome targeted therapy provides a promising new treatment approach. A systematic review following the PRISMA guidelines on the current preclinical data regarding the potential role of inflammasome targeted drug therapy as novel treatment option for aortic aneurysms and dissections was performed. Included were all rodent models of aortic disease (aortic aneurysm and dissection) evaluating a drug therapy with direct or indirect inhibition of inflammasomes and a suitable control group with the use of the same aortic model without the inflammasome targeted therapy. Primary and secondary outcomes were incidence of aortic disease, aortic rupture, aortic related death, and the maximum aortic diameter. The literature search of MEDLINE (via PubMed), the Web of Science, EMBASE and the Cochrane Central Registry of Registered Trials (CENTRAL) resulted in 8,137 hits. Of these, four studies met the inclusion criteria and were therefore eligible for data analysis. In all of them, targeting of the NOD-, LRR- and pyrin domain-containing protein 3 (NLRP3) inflammasome effectively reduced the incidence of aortic disease and aortic rupture, and additionally reduced destruction of the aortic wall. Treatment strategies aiming at other inflammasomes could not be identified. In conclusion, inflammasome targeted therapies, more precisely targeting the NLRP3 inflammasome, have shown promising results in rodent models and deserve further investigation in preclinical research to potentially translate them into clinical research for the treatment of human patients with aortic disease. Regarding other inflammasomes, more preclinical research is needed to investigate their role in the pathophysiology of aortic disease.Protocol Registration: PROSPERO 2021 CRD42021279893, https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021279893

Background: Angiographic detection of thrombus in STEMI is associated with adverse outcomes. However, routine thrombus aspiration failed to demonstrate the anticipated benefit. Hence, management of high coronary thrombus burden remains challenging. We sought to assess for the first time extracted thrombotic material characteristics utilizing micro-computed tomography (micro-CT).Methods: One hundred thirteen STEMI patients undergoing thrombus aspiration were enrolled. Micro-CT was undertaken to quantify retrieved thrombus volume, surface, and density. Correlation of these indices with angiographic and electrocardiographic outcomes was performed.Results: Mean aspirated thrombus volume, surface, and density (±standard deviation) were 15.71 ± 20.10 mm3, 302.89 ± 692.54 mm2, and 3139.04 ± 901.88 Hounsfield units, respectively. Aspirated volume and surface were significantly higher (p < 0.001) in patients with higher angiographic thrombus burden. After multivariable analysis, independent predictors for thrombus volume were reference vessel diameter (RVD) (p = 0.011), right coronary artery (RCA) (p = 0.039), and smoking (p = 0.027), whereas RVD (p = 0.018) and RCA (p = 0.019) were predictive for thrombus surface. Thrombus volume and surface were independently associated with distal embolization (p = 0.007 and p = 0.028, respectively), no-reflow phenomenon (p = 0.002 and p = 0.006, respectively), and angiographically evident residual thrombus (p = 0.007 and p = 0.002, respectively). Higher thrombus density was correlated with worse pre-procedural TIMI flow (p < 0.001). Patients with higher aspirated volume and surface developed less ST resolution (p = 0.042 and p = 0.023, respectively).Conclusions: Angiographic outcomes linked with worse prognosis were more frequent among patients with larger extracted thrombus. Despite retrieving larger thrombus load in these patients, current thrombectomy devices fail to deal with thrombotic material adequately. Further studies of novel thrombus aspiration technologies are warranted to improve patient outcomes.Clinical Trial Registration: QUEST-STEMI trial ClinicalTrials.gov number: NCT03429608 Date of registration: February 12, 2018. The study was prospectively registered.

As an integral part of patient care, nursing is required to constantly adapt to changes in the healthcare system, as well as the wider financial and societal environment. Among the key factors driving these changes is the aging of population. Combined with an existing shortage of nursing and caregiving professionals, accommodating for the patients and elderly needs within hospitals, elderly-care facilities and at a home setting, becomes a societal challenge. Amongst the technological solutions that have evolved in response to these developments, nursing and assistive robotics claim a pivotal role. The objective of the present study is to provide an overview of today's landscape in nursing and assistive robotics, highlighting the benefits associated with adopting such solutions in standard clinical practice. At the same time, to identify existing challenges and limitations that essentially outline the area's future directions. Beyond technological innovation, the manuscript also investigates the end-users' angle, being a crucial parameter in the success of robotics solutions operating within a healthcare environment. In this direction, the results of a survey designed to capture the nursing professionals' perspective toward more informed robotics design and development are presented.

Viral carrier transport efficiency of gene delivery is high, depending on the type of vector. However, viral delivery poses significant safety concerns such as inefficient/unpredictable reprogramming outcomes, genomic integration, as well as unwarranted immune responses and toxicity. Thus, non-viral gene delivery methods are more feasible for translation as these allow safer delivery of genes and can modulate gene expression transiently both in vivo, ex vivo, and in vitro. Based on current studies, the efficiency of these technologies appears to be more limited, but they are appealing for clinical translation. This review presents a summary of recent advancements in orthopedics, where primarily bone and joints from the musculoskeletal apparatus were targeted. In connective tissues, which are known to have a poor healing capacity, and have a relatively low cell-density, i.e., articular cartilage, bone, and the intervertebral disk (IVD) several approaches have recently been undertaken. We provide a brief overview of the existing technologies, using nano-spheres/engineered vesicles, lipofection, and in vivo electroporation. Here, delivery for microRNA (miRNA), and silencing RNA (siRNA) and DNA plasmids will be discussed. Recent studies will be summarized that aimed to improve regeneration of these tissues, involving the delivery of bone morphogenic proteins (BMPs), such as BMP2 for improvement of bone healing. For articular cartilage/osteochondral junction, non-viral methods concentrate on targeted delivery to chondrocytes or MSCs for tissue engineering-based approaches. For the IVD, growth factors such as GDF5 or GDF6 or developmental transcription factors such as Brachyury or FOXF1 seem to be of high clinical interest. However, the most efficient method of gene transfer is still elusive, as several preclinical studies have reported many different non-viral methods and clinical translation of these techniques still needs to be validated. Here we discuss the non-viral methods applied for bone and joint and propose methods that can be promising in clinical use.

Bacterial metabolites represent an invaluable source of bioactive molecules which can be used as such or serve as chemical frameworks for developing new antimicrobial compounds for various applications including crop protection against pathogens. Prodiginines are tripyrrolic, red-colored compounds produced by many bacterial species. Recently, due to the use of chemical-, bio-, or mutasynthesis, a novel group of prodiginines was generated. In our study, we perform different assays to evaluate the effects of prodigiosin and five derivatives on nematodes and plant pathogenic fungi as well as on plant development. Our results showed that prodigiosin and the derivatives were active against the bacterial feeding nematode Caenorhabditis elegans in a concentration- and derivative-dependent manner while a direct effect on infective juveniles of the plant parasitic nematode Heterodera schachtii was observed for prodigiosin only. All compounds were found to be active against the plant pathogenic fungi Phoma lingam and Sclerotinia sclerotiorum. Efficacy varied depending on compound concentration and chemical structure. We observed that prodigiosin (1), the 12 ring- 9, and hexenol 10 derivatives are neutral or even positive for growth of Arabidopsis thaliana depending on the applied compound concentration, whereas other derivatives appear to be suppressive. Our infection assays revealed that the total number of developed H. schachtii individuals on A. thaliana was decreased to 50% in the presence of compounds 1 or 9. Furthermore, female nematodes and their associated syncytia were smaller in size. Prodiginines seem to indirectly inhibit H. schachtii parasitism of the plant. Further research is needed to elucidate their mode of action. Our results indicate that prodiginines are promising metabolites that have the potential to be developed into novel antinematodal and antifungal agents.

Pelage luminance has been found in many mammalian systems to follow patterns predicted by Gloger’s rule where darker colored animals are associated with environments that are warmer and more moist. Sciurids have one of the greatest diversities of color patterns and hues among mammalian families. We have used comparative methods to investigate whether the luminance of dorsal pelage in 137 species across Sciuridae conforms to prediction of Gloger’s rule and other background matching expectations. We found using phylogenetic multiple regression, as well as univariate regression, that Sciurids generally conform to the expectations of Gloger’s rule. Darker species are associated with environments with higher primary productivity, higher temperature, higher humidity, and lower solar radiation. Moreover, in support of the predictions of background matching, darker squirrel species were associated with environments with greater soil carbon content and higher fire frequency. Our macroevolutionary study sheds some light on selective pressures that are driving the evolution of coloration in Sciurids, but more comparative research is needed to fully understand other selective pressures that have led to the wide diversity of color patterns and hues.

Raanes et al. [1] revised the iterative ensemble smoother of Chen and Oliver [2, 3], denoted Ensemble Randomized Maximum Likelihood (EnRML), using the property that the EnRML solution is contained in the ensemble subspace. They analyzed EnRML and demonstrated how to implement the method without the use of expensive pseudo inversions of the low-rank state covariance matrix or the ensemble-anomaly matrix. The new algorithm produces the same result, realization by realization, as the original EnRML method. However, the new formulation is simpler to implement, numerically stable, and computationally more efficient. The purpose of this document is to present a simple derivation of the new algorithm and demonstrate its practical implementation and use for reservoir history matching. An additional focus is to customize the algorithm to be suitable for big-data assimilation of measurements with correlated errors. The computational cost of the resulting “ensemble sub-space” algorithm is linear in both the dimension of the state space and the number of measurements, also when the measurements have correlated errors. The final algorithm is implemented in the Ensemble Reservoir Tool (ERT) for running and conditioning ensembles of reservoir models. Several verification experiments are presented.

For several decades, Drosophila has been widely used as a suitable model organism to study the fundamental processes of associative olfactory learning and memory. More recently, this condition also became true for the Drosophila larva, which has become a focus for learning and memory studies based on a number of technical advances in the field of anatomical, molecular, and neuronal analyses. The ongoing efforts should be mentioned to reconstruct the complete connectome of the larval brain featuring a total of about 10,000 neurons and the development of neurogenic tools that allow individual manipulation of each neuron. By contrast, standardized behavioral assays that are commonly used to analyze learning and memory in Drosophila larvae exhibit no such technical development. Most commonly, a simple assay with Petri dishes and odor containers is used; in this method, the animals must be manually transferred in several steps. The behavioral approach is therefore labor-intensive and limits the capacity to conduct large-scale genetic screenings in small laboratories. To circumvent these limitations, we introduce a training device called the Maggot Instructor. This device allows automatic training up to 10 groups of larvae in parallel. To achieve such goal, we used fully automated, computer-controlled optogenetic activation of single olfactory neurons in combination with the application of electric shocks. We showed that Drosophila larvae trained with the Maggot Instructor establish an odor-specific memory, which is independent of handling and non-associative effects. The Maggot Instructor will allow to investigate the large collections of genetically modified larvae in a short period and with minimal human resources. Therefore, the Maggot Instructor should be able to help extensive behavioral experiments in Drosophila larvae to keep up with the current technical advancements. In the longer term, this condition will lead to a better understanding of how learning and memory are organized at the cellular, synaptic, and molecular levels in Drosophila larvae.

Great progress has been made towards understanding the properties of single neurons, yet the principles underlying interactions between neurons remain poorly understood. Given that connectivity in the neocortex is locally dense through both horizontal and vertical con-nections, it is of particular importance to characterize the activity structure of local popula-tions of neurons arranged in three dimensions. However, techniques for simultaneously measuring microcircuit activity are lacking. We developed an in vivo 3D high-speed, ran-dom-access two-photon microscope that is capable of simultaneous 3D motion tracking. This allows imaging from hundreds of neurons at several hundred Hz, while monitoring tissue movement. Given that motion will induce common artifacts across the population, accurate motion tracking is absolutely necessary for studying population activity with ran-dom-access based imaging methods. We demonstrate the potential of this imaging tech-nique by measuring the correlation structure of large populations of nearby neurons in the mouse visual cortex, and find that the microcircuit correlation structure is stimulus-dependent. Three-dimensional random access multiphoton imaging with concurrent mo-tion tracking provides a novel powerful method to characterize the microcircuit activity in vivo.

The fruit fly Drosophila melanogaster represents a key model organism for analyzing how neuronal circuits regulate behavior. The mushroom body in the central brain is a particularly prominent brain region that has been intensely studied in several insect species and been implicated in a variety of behaviors, e.g., associative learning, locomotor activity and sleep. Drosophila melanogaster offers the advantage that transgenes can be easily expressed in neuronal subpopulations, e.g., in intrinsic mushroom body neurons (Kenyon cells). A number of transgenes has been described and engineered to visualize the anatomy of neurons, to monitor physiological parameters of neuronal activity, and to manipulate neuronal function artificially. To target the expression of these transgenes selectively to specific neurons several sophisticated bi- or even multipartite transcription systems have been invented. However, the number of transgenes that can be combined in the genome of an individual fly is limited in practice. To facilitate the analysis of the mushroom body we provide a compilation of transgenic fruit flies that express transgenes under direct control of the Kenyon-cell specific promoter, mb247. The transgenes expressed are fluorescence reporters to analyze neuroanatomical aspects of the mushroom body, proteins to restrict ectopic gene expression to mushroom bodies, or fluorescent sensors to monitor physiological parameters of neuronal activity of Kenyon cells. Some of the transgenic animals compiled here have been published already, whereas others are novel and characterized here for the first time. Overall, the collection of transgenic flies expressing sensor and reporter genes in Kenyon cells facilitates combinations with binary transcription systems and might, ultimately, advance the physiological analysis of mushroom body function.

Extra-cellular voltage fluctuations (local field potentials; LFPs) reflecting neural mass action are ubiquitous across species and brain regions. Numerous studies have characterized the properties of LFP signals in the cortex to study sensory and motor computations as well as cognitive processes like attention, perception and memory. In addition, its extracranial counterpart – the electroencelphalogram (EEG) – is widely used in clinical applications. However, the link between LFP signals and the underlying activity of local populations of neurons remains largely elusive. Here, we review recent work elucidating the relationship between spiking activity of local neural populations and LFP signals. We focus on oscillations in the gamma-band (30-90Hz) of the local field potential in the primary visual cortex (V1) of the macaque that dominate during visual stimulation. Given that in area V1 much is known about the properties of single neurons and the cortical architecture, it provides an excellent opportunity to study the mechanisms underlying the generation of the local field potential.

In the face of uncontrollable complexity, the concept of a rational design of the organization is being replaced by the notion of an open future that is inherently unpredictable and unplanable. In rapidly changing environments, organizations and leaders are confronted with a constant stream of irritations and unexpected developments, that require ongoing attention. This prompts the question of whether the conceptualization of digital transformation as a paradigm shift also implies the need for new forms of leadership. The article analyzes the discourse on digital leadership and assesses the extent to which this concept relativizes leadership in the context of the evolution of leadership theory, which is characterized by a persistent process of modification and relativization of preceding concepts. Leadership concepts are not only responsive to general needs, but also vary according to specific contexts, such as non-profit leadership or leadership in social welfare organizations and meta-organizations. Results of a discourse analysis, which underscore the significance of adopting a complexity theory perspective on digital leadership, will therefore be contrasted with the initial findings of an empirical study on digitization in such meta-organizations. This allows for a discussion of the general findings on the revitalization of leadership, which will serve as a paradigmatic example of the previously developed context. The article concludes with implications for further theory development with the aim of making a specific contribution to organization-sensitive digitization research. The findings of the empirical study indicate the significance of employing informal structures and a heightened emphasis on subjectivity within meta-organizations, as opposed to the formal structures of organizations. The concept of digital leadership does not signify the obsolescence of traditional leadership; rather, it can be conceptualized as an advanced form of unheroic leadership within the context of external and internal complexity.

This study investigates the dynamic interactions between physiological systems during competitive gaming, utilizing a Network Physiology approach. By examining the physiological responses of a gamer with attention-deficit/hyperactivity disorder playing a real-time strategy game, we explore the relationships and temporal lag effects between pupil dilation, skin temperature, and heart rate. Our findings highlight the interconnectedness of these physiological systems and demonstrate how different physiological states are associated with unique patterns of network interactions. The study employs the concept of Time Delay Stability towards a deeper understanding of the complex dynamics involved. This research contributes to the growing field of Network Physiology by offering new insights into the physiological underpinnings of competitive gaming, potentially informing targeted training and recovery protocols for eSports athletes.

IntroductionThe severity of Coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is often dictated by a range of comorbidities. A considerable literature suggests iron deficiency and iron overload may contribute to increased infection, inflammation and disease severity, although direct causal relationships have been difficult to establish.MethodsHere we generate iron deficient and iron loaded C57BL/6 J mice by feeding standard low and high iron diets, with mice on a normal iron diet representing controls. All mice were infected with a primary SARS-CoV-2 omicron XBB isolate and lung inflammatory responses were analyzed by histology, immunohistochemistry and RNA-Seq.ResultsCompared with controls, iron deficient mice showed no significant changes in lung viral loads or histopathology, whereas, iron loaded mice showed slightly, but significantly, reduced lung viral loads and histopathology. Transcriptional changes were modest, but illustrated widespread dysregulation of inflammation signatures for both iron deficient vs. controls, and iron loaded vs. controls. Some of these changes could be associated with detrimental outcomes, whereas others would be viewed as beneficial.DiscussionDiet-associated iron deficiency or overload thus induced modest modulations of inflammatory signatures, but no significant histopathologically detectable disease exacerbations.

PurposeThe natural history in unselected cohorts of patients with pheochromocytoma/ paraganglioma (PPGL) followed for a period >10 years remains limited. We aimed to describe baseline characteristics and outcome of a large cohort and to identify predictors of shorter survival.MethodsThis retrospective single-center study included 303 patients with newly diagnosed PPGL from 1968 to December 31, 2023, in 199 prospectively supplemented since July 2020. Mean follow-up was 11.4 (range 0.3-50) years, germline genetic analyses were available in 92.1%. The main outcome measures were overall (OAS), disease-specific (DSS), recurrence-free (RFS) survival and predictors of shorter survival evaluated in patients with metastases at first diagnosis (n=12), metastatic (n=24) and nonmetastatic (n=33) recurrences and without evidence of PPGL after first surgery (n=234).ResultsAge at study begin was 49.4 ± 16.3 years. There were 72 (23.8%) deaths, 15 (5.0%), 29 (9.6%) and 28 (9.2%) due to PPGL, cardiovascular disease (CVD) and malignant or other diseases, respectively. Median OAS, DSS1 (tumor-related) and DSS2 (DSS1 and death caused by CVD) were 4.8, 5.9 and 5.2 years (patients with metastases at first diagnosis), 21.2, 21.2 and 19.9 years, and 38.0, undefined and 38.0 years (patients with metastatic and with nonmetastatic recurrences, respectively). Major adverse cardiovascular events (MACE) preceded the first diagnosis in 15% (n=44). Shorter DSS2 correlated with older age (P ≤ 0.001), male sex (P ≤ 0.02), MACE (P ≤ 0.01) and primary metastases (P

Sorption is a key process to understand the environmental fate of pollutants on soils, conduct preliminary risk assessments and fill information gaps. Quantitative Structure-Activity Relationships (QSAR) and Pedotransfer Functions (PTF) are the most common approaches used in the literature to predict sorption. Both models use different outcomes and follow different simplification strategies to represent data. However, the impact of those differences on the interpretation of sorption trends and application of models for regulatory purposes is not well understood. We conducted a systematic review to contextualize the requirements for developing, interpreting, and applying predictive models in different scenarios of environmental concern by using pesticides as a globally relevant organic pollutant model. We found disagreements between predictive model assumptions and empirical information from the literature that affect their reliability and suitability. Additionally, we found that both model procedures are complementary and can improve each other by combining the data treatment and statistical validation applied in PTF and QSAR models, respectively. Our results expose how relevant the methodological and environmental conditions and the sources of variability studied experimentally are to connect the representational value of data with the applicability domain of predictive models for scientific and regulatory decisions. We propose a set of empirical correlations to unify the sorption mechanisms within the dataset with the selection of a proper kind of model, solving apparent incompatibilities between both models, and between model assumptions and empirical knowledge. The application of our proposal should improve the representativity and quality of predictive models by adding explicit conditions and requirements for data treatment, selection of outcomes and predictor variables (molecular descriptors versus soil properties, or both), and an expanded applicability domain for pollutant-soil interactions in specific environmental conditions, helping the decision-making process in regard to both scientific and regulatory concerns (in the following, the scientific and regulatory dimensions).

IntroductionThe aim of this study was to analyze age-associated myocardial injury and clinical outcome after non-ST-elevation myocardial infarction (NSTEMI).MethodsThis prospective, multicenter study consists of 440 patients with NSTEMI enrolled at 7 centers. All patients were treated with primary percutaneous coronary intervention and underwent cardiac magnetic resonance (CMR) imaging 1–10 days after study inclusion. CMR parameters of myocardial injury and clinical outcome were evaluated by creating 2 subgroups:

BackgroundFood plays a dual role in promoting human health and environmental sustainability. Yet, current food systems jeopardize both. Food waste poses a major global challenge due to its significant economic, social, and environmental impacts. Healthcare facilities generate the largest amounts of food waste compared to other forms of catering provision. Food waste correlates with environmental unsustainability and diminished patient satisfaction, compounding the prevalent challenge of hospital malnutrition and contributing to suboptimal patient outcomes.Materials and methodsIn a three-year interventional study (2020-2022) at a psychiatric tertiary care center, we assessed and mitigated food waste using evidence-based measures. We conducted systematic food wastage audits over three years (2020-2022) in May and June, each lasting four weeks. Costs were analyzed comprehensively, covering food, staff, infrastructure, and disposal. Environmental impact was assessed using Umweltbelastungspunkte (UBP) and CO2e/kg emissions, alongside water usage (H2O - l/kg).ResultsEconomic losses due to food wastage were substantial, primarily from untouched plates and partially consumed dinners, prompting meal planning adjustments. Despite a >3% increase in meals served, both food waste mass and costs decreased by nearly 6%. Environmental impact indicators showed a reduction >20%. Vegetables, salad, and fruits constituted a significant portion of waste. Overproduction minimally contributed to waste, validating portion control efficacy.ConclusionOur study highlights significant economic and environmental losses due to hospital food waste, emphasizing the importance of resource efficiency. The strategies outlined offer promising avenues for enhanced efficiency. The decrease in food waste observed over the three-year period underscores the potential for improvement.

Introduction: We performed an exposure-based Next Generation Risk Assessment case read-across study using New Approach Methodologies (NAMs) to determine the highest safe concentration of daidzein in a body lotion, based on its similarities with its structural analogue, genistein. Two assumptions were: (1) daidzein is a new chemical and its dietary intake omitted; (2) only in vitro data were used for daidzein, while in vitro and legacy in vivo data for genistein were considered.Methods: The 10-step tiered approach evaluating systemic toxicity included toxicokinetics NAMs: PBPK models and in vitro biokinetics measurements in cells used for toxicogenomics and toxicodynamic NAMs: pharmacology profiling (i.e., interaction with molecular targets), toxicogenomics and EATS assays (endocrine disruption endpoints). Whole body rat and human PBPK models were used to convert external doses of genistein to plasma concentrations and in vitro Points of Departure (PoD) to external doses. The PBPK human dermal module was refined using in vitro human skin metabolism and penetration data.Results: The most relevant endpoint for daidzein was from the ERα assay (Lowest Observed Effective Concentration was 100 ± 0.0 nM), which was converted to an in vitro PoD of 33 nM. After application of a safety factor of 3.3 for intra-individual variability, the safe concentration of daidzein was estimated to be 10 nM. This was extrapolated to an external dose of 0.5 μg/cm2 for a body lotion and face cream, equating to a concentration of 0.1%.Discussion: When in vitro PoD of 33 nM for daidzein was converted to an external oral dose in rats, the value correlated with the in vivo NOAEL. This increased confidence that the rat oral PBPK model provided accurate estimates of internal and external exposure and that the in vitro PoD was relevant in the safety assessment of both chemicals. When plasma concentrations estimated from applications of 0.1% and 0.02% daidzein were used to calculate bioactivity exposure ratios, values were >1, indicating a good margin between exposure and concentrations causing adverse effects. In conclusion, this case study highlights the use of NAMs in a 10-step tiered workflow to conclude that the highest safe concentration of daidzein in a body lotion is 0.1%.

ObjectivesTo date there is no universally accepted model that describes the development of substance related addictive behavior. In order to address this gap, the study sought to examine whether the association between primary emotions and the inclination toward addictive behavior is mediated by an anxious attachment style.MethodsThe total sample consisted of 900 German speaking non-clinical adults (age: M = 27; SD = 9.60; 71.6% female). Structural Equation Modeling (SEM) was applied to examine the connection between the primary emotions (SADNESS and ANGER), and the latent variables attachment anxiety and symptoms of addictive behavior.ResultsSubstance use symptomatology was correlated with higher attachment anxiety (r = 0.15), SADNESS (r = 0.15), and ANGER (r = 0.11). The effect of SADNESS on addictive behavior is mediated by attachment anxiety (p

BackgroundIndividuals with anxiety disorders (ADs) often display hypervigilance to threat information, although this response may be less pronounced following psychotherapy. This study aims to investigate the unconscious recognition performance of facial expressions in patients with panic disorder (PD) post-treatment, shedding light on alterations in their emotional processing biases.MethodsPatients with PD (n=34) after (exposure-based) cognitive behavior therapy and healthy controls (n=43) performed a subliminal affective recognition task. Emotional facial expressions (fearful, happy, or mirrored) were displayed for 33 ms and backwardly masked by a neutral face. Participants completed a forced choice task to discriminate the briefly presented facial stimulus and an uncovered condition where only the neutral mask was shown. We conducted a secondary analysis to compare groups based on their four possible response types under the four stimulus conditions and examined the correlation of the false alarm rate for fear responses to non-fearful (happy, mirrored, and uncovered) stimuli with clinical anxiety symptoms.ResultsThe patient group showed a unique selection pattern in response to happy expressions, with significantly more correct “happy” responses compared to controls. Additionally, lower severity of anxiety symptoms after psychotherapy was associated with a decreased false fear response rate with non-threat presentations.ConclusionThese data suggest that patients with PD exhibited a “happy-face recognition advantage” after psychotherapy. Less symptoms after treatment were related to a reduced fear bias. Thus, a differential facial emotion detection task could be a suitable tool to monitor response patterns and biases in individuals with ADs in the context of psychotherapy.

Plant tetrapyrrole biosynthesis (TPS) provides the indispensable chlorophyll (Chl) and heme molecules in photosynthetic organisms. Post-translational mechanisms control the enzymes to ensure a balanced flow of intermediates in the pathway and synthesis of appropriate amounts of both endproducts. One of the critical regulators of TPS is GENOMES UNCOUPLED 4 (GUN4). GUN4 interacts with magnesium chelatase (MgCh), and its binding of the catalytic substrate and product of the MgCh reaction stimulates the insertion of Mg2+ into protoporphyrin IX. Despite numerous in vitro studies, knowledge about the in vivo function of the GUN4:porphyrin interaction for the whole TPS pathway, particularly in plants, is still limited. To address this, we focused on two highly conserved amino acids crucial for porphyrin-binding to GUN4 and analyzed GUN4-F191A, R211A, and R211E substitution mutants in vitro and in vivo. Our analysis confirmed the importance of these amino acids for porphyrin-binding and the stimulation of plant MgCh by GUN4 in vitro. Expression of porphyrin-binding deficient F191A, R211A, and R211E in the Arabidopsis gun4-2 knockout mutant background revealed that, unlike in cyanobacteria and green algae, GUN4:porphyrin interactions did not affect the stability of GUN4 or other Arabidopsis TPS pathway enzymes in vivo. In addition, although they shared diminished porphyrin-binding and MgCh activation in vitro, expression of the different GUN4 mutants in gun4-2 had divergent effects on the TPS and the accumulation of Chl and Chl-binding proteins. For instance, expression of R211E, but not R211A, induced a substantial decrease of ALA synthesis rate, lower TPS intermediate and Chl level, and strongly impaired accumulation of photosynthetic complexes compared to wild-type plants. Furthermore, the presence of R211E led to significant growth retardation and paler leaves compared to GUN4 knockdown mutants, indicating that the exchange of R211 to glutamate compromised TPS and Chl accumulation more substantially than the almost complete lack of GUN4. Extensive in vivo analysis of GUN4 point mutants suggested that F191 and R211 might also play a role beyond porphyrin-binding. [ABSTRACT FROM AUTHOR]

BackgroundMental health problems are prevalent among people with diabetes, yet often under-diagnosed. Smart sensing, utilizing passively collected digital markers through digital devices, is an innovative diagnostic approach that can support mental health screening and intervention. However, the acceptance of this technology remains unclear. Grounded on the Unified Theory of Acceptance and Use of Technology (UTAUT), this study aimed to investigate (1) the acceptance of smart sensing in a diabetes sample, (2) the determinants of acceptance, and (3) the effectiveness of an acceptance facilitating intervention (AFI).MethodsA total of N = 132 participants with diabetes were randomized to an intervention group (IG) or a control group (CG). The IG received a video-based AFI on smart sensing and the CG received an educational video on mindfulness. Acceptance and its potential determinants were assessed through an online questionnaire as a single post-measurement. The self-reported behavioral intention, interest in using a smart sensing application and installation of a smart sensing application were assessed as outcomes. The data were analyzed using latent structural equation modeling and t-tests.ResultsThe acceptance of smart sensing at baseline was average (M = 12.64, SD = 4.24) with 27.8% showing low, 40.3% moderate, and 31.9% high acceptance. Performance expectancy (γ = 0.64, p

Most drugs that target the complement system are designed to inhibit the complement pathway at either the proximal or terminal levels. The use of a natural complement regulator such as factor H (FH) could provide a superior treatment option by restoring the balance of an overactive complement system while preserving its normal physiological functions. Until now, the systemic treatment of complement-associated disorders with FH has been deemed unfeasible, primarily due to high production costs, risks related to FH purified from donors’ blood, and the challenging expression of recombinant FH in different host systems. We recently demonstrated that a moss-based expression system can produce high yields of properly folded, fully functional, recombinant FH. However, the half-life of the initial variant (CPV-101) was relatively short. Here we show that the same polypeptide with modified glycosylation (CPV-104) achieves a pharmacokinetic profile comparable to that of native FH derived from human serum. The treatment of FH-deficient mice with CPV-104 significantly improved important efficacy parameters such as the normalization of serum C3 levels and the rapid degradation of C3 deposits in the kidney compared to treatment with CPV-101. Furthermore, CPV-104 showed comparable functionality to serum-derived FH in vitro, as well as similar performance in ex vivo assays involving samples from patients with atypical hemolytic uremic syndrome, C3 glomerulopathy and paroxysomal nocturnal hematuria. CPV-104 – the human FH analog expressed in moss – will therefore allow the treatment of complement-associated human diseases by rebalancing instead of inhibiting the complement cascade.

IntroductionGlobal microplastic (MP) pollution is now well recognized, with humans and animals consuming and inhaling MPs on a daily basis, with a growing body of concern surrounding the potential impacts on human health.MethodsUsing a mouse model of mild COVID-19, we describe herein the effects of azide-free 1 μm polystyrene MP beads, co-delivered into lungs with a SARS-CoV-2 omicron BA.5 inoculum. The effect of MPs on the host response to SARS-CoV-2 infection was analysed using histopathology and RNA-Seq at 2 and 6 days post-infection (dpi).ResultsAlthough infection reduced clearance of MPs from the lung, virus titres and viral RNA levels were not significantly affected by MPs, and overt MP-associated clinical or histopathological changes were not observed. However, RNA-Seq of infected lungs revealed that MP exposure suppressed innate immune responses at 2 dpi and increased pro-inflammatory signatures at 6 dpi. The cytokine profile at 6 dpi showed a significant correlation with the ‘cytokine release syndrome’ signature observed in some COVID-19 patients.DiscussionThe findings are consistent with the recent finding that MPs can inhibit phagocytosis of apoptotic cells via binding of Tim4. They also add to a growing body of literature suggesting that MPs can dysregulate inflammatory processes in specific disease settings.

Introduction: In this article, we revisit the pitch-angle scattering equation describing the propagation of energetic particles through magnetized plasma. In this case, solar energetic particles and cosmic rays interact with magnetohydrodynamic turbulence and experience stochastic changes in the pitch-angle. Since this happens over an extended period of time, a pitch-angle isotropization process occurs, leading to parallel spatial diffusion. This process is described well by the pitch-angle scattering equation. However, the latter equation is difficult to solve analytically even when considering special cases for the scattering coefficient.Methods: In the past, a so-called subspace approximation was proposed, which has important applications in the theory of perpendicular diffusion. Alternatively, an approach based on the telegraph equation (also known as telegrapher’s equation) has been developed. We show that two-dimensional subspace approximation and the description based on the telegraph equation are equivalent. However, it is also shown that the obtained distribution functions contain artifacts and inaccuracies that cannot be found in the numerical solution to the problem. Therefore, an N-dimensional subspace approximation is proposed corresponding to a semi-analytical/semi-numerical approach. This is a useful alternative compared to standard numerical solvers.Results and Discussion: Depending on the application, the N-dimensional subspace approximation can be orders of magnitude faster. Furthermore, the method can easily be modified so that it can be used for any pitch-angle scattering equation.

ObjectivePatients with cancer experience significant psychosocial distress. Stressors include interpersonal difficulties like loneliness, isolation, thwarted belongingness, communication impediments, and conflicts. Interventions are required that address their specific psychosocial needs. Interpersonal Psychotherapy (IPT) is a promising concept for the treatment of psychosocial distress associated with cancer because it addresses patients’ interactions and role transformations. This review aims to provide an overview of the current evidence regarding interventions for patients with cancer based on IPT.MethodsA systematic review following PRISM guidelines was conducted, including randomized controlled trials of IPT-based interventions in patients with cancer, assessing effects on distress, depression, and anxiety.ResultsEight studies were included, sampling 390 patients in total. Seven out of eight studies assessed exclusively women with breast cancer. Two studies described IPT interventions and showed stronger improvement in depression and anxiety compared to TAU and equal improvement in depression compared to other psychotherapy interventions. Six studies described remote Interpersonal Counselling (IPC). One found remote IPC to be superior to control conditions regarding depression, and one found remote IPC to be superior to attention control, but not active control conditions. No study found remote IPC to be superior to control conditions regarding distress.DiscussionThere are few randomized controlled trials of IPT for patients with cancer. Results regarding depression and anxiety are promising for in-person IPT, but mixed for remote IPC.ConclusionThe review suggests in-person IPT, but not remote IPC, may yield benefits for patients with cancer. Research on the subject is scarce, and to inform implementation of IPT interventions, research with diverse groups of patients with cancer is required.Systematic trial registrationPROSPERO, Identifier CRD42023410687.

ObjectivesPrimary emotion traits and attachment patterns, have been linked to various mental disorders. This study aims to shed more light on the less studied relationship with eating disorder (ED) symptoms.MethodsA total of 921 non-clinical subjects (69.9% females) were assessed for primary emotions traits (B-ANPS-GL), attachment insecurity (ECR-RD8), and eating disorder pathology (EDE-Q8). A theoretically derived model was evaluated by means of a path analysis with attachment anxiety as assumed mediator variable.ResultsGlobal problematic eating behavior showed negative correlations with the positive emotions PLAY, CARE, and LUST (r = −0.10 to −0.24), positive correlations with the negative primary emotions ANGER, FEAR, and SADNESS (r = 0.12–0.27), as well as with attachment anxiety (r = 0.22, all p < 0.01). Path analyses revealed direct effects between eating behavior pathology with LUST (β = −0.07 to −0.15) and FEAR (β = 0.12–0.19; all p < 0.05). The association of SADNESS and Weight (β = 0.05) and Shape Concern (β = 0.06, p < 0.001) was fully mediated by attachment anxiety. Overall, the path model explained 17% of the variance for attachment anxiety and 6% of the Restraint, 13% for Eating, 10% for Weight and 14% for Shape Concern Subscales.DiscussionThe findings shed light on the multifactorial relationship between affective traits, attachment security, and eating disorder pathology. In line with previous research, the results emphasize the role of attachment and affective functioning in ED symptoms.

During the last decade, the application of strontium isotope analysis (87Sr/86Sr) has increased rapidly. The understanding of the strontium isoscape and the construction of a strontium isotope baseline in southern Scandinavia are biased toward Denmark and southwestern to eastern Scania. We report the results of new baseline samples in Halland and the Bjäre Peninsula, adding to the rich strontium isotope library that exists for southern Scandinavia. We add nuance to the previous divisions of Scania, in which the Bjäre Peninsula is not well represented. The results show that the Bjäre Peninsula is characterized by relatively low 87Sr/86Sr values gathered in the preliminary baseline 0.7100 ± 0.0024 (2σ, n = 8), similar to that of southwest Scania and Zealand in Denmark. There is a greater variation and higher values among the Halland samples. Together with previously published faunal samples, a preliminary 87Sr/86Sr baseline for Halland is 0.7122 ± 0.0055 (2σ, n = 24). We apply these baseline results to archaeological cases, both human and animal, from recent excavations in the Bjäre Peninsula. The results imply that there was a certain degree of mobility and interaction across the landscape in this region of southern Scandinavia in prehistory.

A profound knowledge of pollutant emissions and transport processes is essential to better assess the impact on local air quality, which ultimately affects human health. This is of special importance in the proximity of airports, as flight activities are a major source of ultrafine aerosol particles (UFP) that are associated with adverse health effects. A quantification of the aerosol population in the horizontal and in particular in the vertical distribution has not been sufficiently characterized so far, but is of crucial relevance, as the atmospheric boundary layer (ABL) is strongly interacting with aerosols. For this purpose, the fixed-wing research drone called ALADINA (Application of Light-weight Aircraft for Detecting in-situ Aerosol) was operated at a distance of approximately 4 km downwind of the German airport Berlin Brandenburg (BER) on October 11–19, 2021. During the investigation period, 140 vertical profiles of different meteorological parameters and aerosol particle sizes were obtained on six measurement days between the surface and up to a maximum altitude of 750 m above ground level (a.g.l.). The investigations indicate several features: The stability of the ABL is a key characteristic for the vertical distribution of aerosol population with highest concentrations close to ground. Inversion layers further enhance horizontal transport so that airport pollutants can be moved to a further distance away. The airborne observations of total particle number concentration (TNC) coincide with ground-based data from fix-point sites. They show a high variability depending on the distance to the plume as well as upwind position and highest concentrations of TNC related to rush hours of airport operations.

Like other infections, a SARS-CoV-2 infection can also trigger Post-Acute Infection Syndromes (PAIS), which often progress into myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). ME/CFS, characterized by post-exercise malaise (PEM), is a severe multisystemic disease for which specific diagnostic markers or therapeutic concepts have not been established. Despite numerous indications of post-infectious neurological, immunological, endocrinal, and metabolic deviations, the exact causes and pathophysiology remain unclear. To date, there is a paucity of data, that changes in the composition and function of the gastrointestinal microbiota have emerged as a potential influencing variable associated with immunological and inflammatory pathways, shifts in ME/CFS. It is postulated that this dysbiosis may lead to intestinal barrier dysfunction, translocation of microbial components with increased oxidative stress, and the development or progression of ME/CFS. In this review, we detailed discuss the findings regarding alterations in the gastrointestinal microbiota and its microbial mediators in ME/CFS. When viewed critically, there is currently no evidence indicating causality between changes in the microbiota and the development of ME/CFS. Most studies describe associations within poorly defined patient populations, often combining various clinical presentations, such as irritable bowel syndrome and fatigue associated with ME/CFS. Nevertheless, drawing on analogies with other gastrointestinal diseases, there is potential to develop strategies aimed at modulating the gut microbiota and/or its metabolites as potential treatments for ME/CFS and other PAIS. These strategies should be further investigated in clinical trials.

BackgroundDeep sternal wound infection (DSWI) remains a serious complication after coronary artery bypass grafting (CABG). We herein aimed to stratify diabetic patients who underwent CABG using bilateral internal mammary artery (BIMA) for levels of glycated hemoglobin A1C (HbA1c) and compare postoperative outcomes.MethodsBetween January 2010 and August 2020, 4,186 consecutive patients underwent isolated CABG at our center. In 3,229 patients, preoperative HbA1c levels were available. Primary endpoints were wound healing disorder (WHD), DSWI, and 30-day mortality. Patients were stratified according to preoperative HbA1c levels. Patients were further divided into subgroups according to utilization of BIMA.ResultsAfter adjustment, no differences in mortality and stroke rates were seen between group 1 (HbA1c