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Abstract Developing high-performance nanomedicines to enhance antitumor efficacy remains a hot point in the field of biomedicine. In this study, we designed a versatile nanocomposite (FeS₂@COF-HA/AIPH) integrating covalent organic frameworks (COF) functionalized with pyrite (FeS₂) for synergistic photothermal (PTT), chemodynamic (CDT), thermodynamic (TDT) therapies, and immunotherapy. The superior photothermal effects and catalytic capabilities of FeS₂@COF enabled a minimally invasive PTT/CDT combination. The nanoplatform, with its mesoporous structure, also served as a drug delivery system, encapsulating the thermos-decomposable initiator AIPH. The hyaluronic acid (HA) coating not only improved tumor-targeting efficiency but also prevented nonspecific AIPH release. Under near-infrared (NIR) irradiation, the localized hyperthermia triggered AIPH decomposition, generating toxic alkyl radicals (•R) for TDT, further enhancing CDT efficiency. The combination of PTT, CDT, TDT, and immunotherapy led to potent antitumor effects with minimal systemic toxicity, both in vitro and in vivo. Notably, the nanoplatform effectively reprogrammed tumor-associated macrophages (TAMs) from an M2 to M1 phenotype, boosting antitumor immunity. This multifunctional platform thus offers a promising strategy for integrated PTT, CDT, TDT, and immune activation in tumor therapy.

IntroductionIt has been found that programmed cell death protein-1 (PD-1) or its ligand PD-L1 may play an important role in the onset and progression of coronary heart disease (CHD). Thus, we conducted this mendelian randomization analysis (MR) to estimate the causal relationship between PD-1/PD-L1 and 5 specific CHDs (chronic ischemic heart disease, acute myocardial infarction, angina pectoris, coronary atherosclerosis, and unstable angina pectoris), complemented by gene set enrichment analysis (GSEA) for further validation.MethodsPublicly available summary-level data were attained from the UK Biobank with genetic instruments obtained from the largest available, nonoverlapping genome-wide association studies (GWAS). Our analysis involved various approaches including inverse variance-weighted meta-analysis, alternative techniques like weighted median, MR-Egger, MR-multipotency residuals and outliers detection (PRESSO), along with multiple sensitivity assessments such as MR-Egger intercept test, Cochran's Q test, and leave-one-out sensitivity analysis to evaluate and exclude any anomalies.ResultsGene expression profile (GSE71226) was obtained from Gene Expression Omnibus (GEO) database for GSEA. IVW analysis showed a causal association between PD-1 and chronic ischemic heart disease (OR, 0.997; 95%CI, 0.995-0.999; P, 0.009), chronic ischemic heart disease and PD-1 (beta, −3.1; 95%CI, −6.017 to −0.183; P, 0.037), chronic ischemic heart disease and PD-L1 (beta, −3.269; 95%CI, −6.197 to −0.341; P, 0.029). No significant causal relationship was found between PD-1/PD-L1 and other 4 CHDs. The accuracy and robustness of these findings were confirmed by sensitivity tests. GSEA found that the KEGG pathway and related core genes of “PD-L1 expression and PD-1 checkpoint pathway in cancer” pathway were downregulated in CHD.DiscussionThis study provided evidence of a bidirectional causal relationship between PD-1 and chronic ischemic heart disease and a protective association between chronic ischemic heart disease and PD-L1.

Oriental Pied-Hornbills (Anthracoceros albirostris) disappeared from Singapore in the 1800s but were returned in the 2000s through a combination of active reintroduction and recolonization. Since then, they have multiplied and even thrived in Singapore, spreading throughout much of the country. Singapore is extremely urban and densely populated, and here we examine where hornbills have been seen as a function of land-use. We combine citizen science data from eBird and iNaturalist with GIS information to model hornbill occurrence. We find that vegetation with no canopy, marshy habitat, and built-up areas have strong positive effects on the probability of hornbill sightings. We interpret our results with respect to larger regional patterns.

BackgroundIn Malaysia, an increase in non-carbapenemase-producing carbapenem-resistant Klebsiella pneumoniae (NC-CRKP) has been observed over the years. Previously, four NC-CRKP with increased susceptibility to ciprofloxacin in the presence of phenylalanine-arginine β-naphthylamide (PAβN) were identified. However, no contribution of the PAβN-inhibited efflux pump to carbapenem resistance was observed. All four NC-CRKP harboured non-carbapenemase β-lactamase, with two also exhibiting porin loss. In this study, we further investigated the genomic features and resistance mechanisms of these four isolates.MethodsAll four NC-CRKP were subjected to whole-genome sequencing, followed by comparative genomic and phylogenetic analyses.ResultsMulti-locus sequence typing (MLST) analysis divided the four NC-CRKP into different sequence types: ST392, ST45, ST14, and ST5947. Neither major nor rare carbapenemase genes were detected. Given the presence of non-carbapenemase β-lactamase in all isolates, we further investigated the potential mechanisms of resistance by identifying related chromosomal mutations. Deletion mutation was detected in the cation efflux system protein CusF. Insertion mutation was identified in the nickel/cobalt efflux protein RcnA. Missense mutation of ompK36 porin was detected in two isolates, while the loss of ompK36 porin was observed in another two isolates.ConclusionsThis study revealed that NC-CRKP may confer carbapenem resistance through a combination of non-carbapenemase β-lactamase and potential chromosomal mutations including missense mutation or loss of ompK36 porin and/or a frameshift missense mutation in efflux pump systems, such as cation efflux system protein CusF and nickel/cobalt efflux protein RcnA. Our findings highlighted the significance of implementing whole-genome sequencing into clinical practice to promote the surveillance of carbapenem resistance mechanisms among NC-CRKP.

Abstract Background Epilepsy is a chronic neurological disorder that is more likely to be diagnosed in children. The main treatment involves long-term use of anti-epileptic drugs and above all, home care is of great importance. As there has not been a widely accepted home care protocols, simulating a home care environment is necessary for caregivers to develop skills of proper home care. This study aims to evaluate the effectiveness of a simulation training of family management style (STOFMS) for parents of children with epilepsy in China. Methods A randomized controlled trial was conducted on 463 children with epilepsy and their families. They were recruited from March 2020 to November 2022 and randomly assigned to the STOFMS group or the conventional group in a 1:1 ratio. Scores of family management measures, 8-item of Morisky Medication Adherence and epilepsy clinical symptom of both groups were collected at three points of time: within 24 h after admission (T0), 3 months after discharge (T1), and 6 months after discharge (T2). Changes due to intervention were compared across groups by repeated-measures ANOVA. The study report followed the CONSORT 2010 checklist. Results There were statistically significant differences between the two groups at T2. A considerable increase over the baseline was observed in the total management level score and subscale scores in the STOFMS group at T1, compared with essentially no change in the control group. In terms of medication adherence, the STOFMS group performance improved greatly at T1 and T2 compared with the control group. The same result was also found in clinical efficacy at T2 (p

Abstract Genome-wide sequencing and genetic matchmaker services are propelling a new era of genotype-driven ascertainment of novel genetic conditions. The degree to which reported phenotype data in discovery-focused studies address informational priorities for clinicians and families is unclear. We identified reports published from 2017 to 2021 in 10 genetics journals of novel Mendelian disorders. We adjudicated the quality and detail of the phenotype data via 46 questions pertaining to six priority domains: (I) Development, cognition, and mental health; (II) Feeding and growth; (III) Medication use and treatment history; (IV) Pain, sleep, and quality of life; (V) Adulthood; and (VI) Epilepsy. For a subset of articles, all subsequent published follow-up case descriptions were identified and assessed in a similar manner. A modified Delphi approach was used to develop consensus reporting guidelines, with input from content experts across four countries. In total, 200 of 3243 screened publications met inclusion criteria. Relevant phenotypic details across each of the 6 domains were rated superficial or deficient in >87% of papers. For example, less than 10% of publications provided details regarding neuropsychiatric diagnoses and “behavioural issues”, or about the type/nature of feeding problems. Follow-up reports (n = 95) rarely contributed this additional phenotype data. In summary, phenotype information relevant to clinical management, genetic counselling, and the stated priorities of patients and families is lacking for many newly described genetic diseases. The PHELIX (PHEnotype LIsting fiX) reporting guideline checklists were developed to improve phenotype reporting in the genomic era.

Inflammatory diseases compromise a clinically common and diverse group of conditions, causing detrimental effects on body functions. Gasdermins (GSDM) are pore-forming proteins, playing pivotal roles in modulating inflammation. Belonging to the GSDM family, gasdermin D (GSDMD) actively mediates the pathogenesis of inflammatory diseases by mechanistically regulating different forms of cell death, particularly pyroptosis, and cytokine release, in an inflammasome-dependent manner. Aberrant activation of GSDMD in different types of cells, such as immune cells, cardiovascular cells, pancreatic cells and hepatocytes, critically contributes to the persistent inflammation in different tissues and organs. The contributory role of GSDMD has been implicated in diabetes mellitus, liver diseases, cardiovascular diseases, neurodegenerative diseases, and inflammatory bowel disease (IBD). Clinically, alterations in GSDMD levels are potentially indicative to the occurrence and severity of diseases. GSDMD inhibition might represent an attractive therapeutic direction to counteract the progression of inflammatory diseases, whereas a number of GSDMD inhibitors have been shown to restrain GSDMD-mediated pyroptosis through different mechanisms. This review discusses the current understanding and future perspectives on the role of GSDMD in the development of inflammatory diseases, as well as the clinical insights of GSDMD alterations, and therapeutic potential of GSDMD inhibitors against inflammatory diseases. Further investigation on the comprehensive role of GSDM shall deepen our understanding towards inflammation, opening up more diagnostic and therapeutic opportunities against inflammatory diseases.

The nested subtype of urothelial carcinoma (NS-UC), a rare and aggressive bladder cancer, mimics benign bladder lesions but behaves like high-grade urothelial carcinomas. The author reported a rare case of NS-UC, initially presenting with inguinal lymph node metastasis. The tumor cells of NS-UC exhibit minimal cellular atypia, forming small nests, while the tumor cells of lymph node metastatic carcinoma show greater cellular atypia with diverse structures. Immunohistochemistry is helpful in determining the origin of lymph node metastatic carcinoma. NS-UC often presents morphologically similar to benign lesions, which should be given sufficient attention.

Abstract We examined the remains of an individual who was unearthed from the Tuchengzi site and was believed to be from the Warring States period in China. The remains exhibited segmental femoral fracture. We aimed to deduce the cause of fracture, medical interventions, healing process, and motion behavior after fracture healing using several techniques, including macroscopic observation, computed tomography (CT), and finite element analysis. Based on the morphology of the long bones, it appeared that the individual was male. The fractures resulted in an adduction angle of 5.47° and an anterior flexion angle of 21.34° in the proximal femur, while the femoral neck anteversion angle had been replaced by a retroversion angle of 10.74°. Additionally, the distal femur formed an abnormal anterior convex angle of 144.60°. CT revealed mature callus formation and visible trabecular bundles. The finite element analysis indicated that the maximum von Mises stress in the femur was 17.44 MPa during standing and 96.46 MPa during walking. We suggest that medical practitioners in the Warring States period possessed a good knowledge of thigh anatomy, enabling them to perform fracture reduction and fixation. Reasonable medical intervention facilitated fracture healing and load recovery. Satisfactory fracture healing ensured that the individual could engage in normal standing and walking activities after rehabilitation.

Abstract Ageing is a crucial risk factor for Alzheimer’s disease (AD) and is characterised by systemic changes in both intracellular and extracellular microenvironments that affect the entire body instead of a single organ. Understanding the specific mechanisms underlying the role of ageing in disease development can facilitate the treatment of ageing-related diseases, such as AD. Signs of brain ageing have been observed in both AD patients and animal models. Alleviating the pathological changes caused by brain ageing can dramatically ameliorate the amyloid beta- and tau-induced neuropathological and memory impairments, indicating that ageing plays a crucial role in the pathophysiological process of AD. In this review, we summarize the impact of several age-related factors on AD and propose that preventing pathological changes caused by brain ageing is a promising strategy for improving cognitive health.

The aviation industry is a key market that promote additive manufacturing (AM) technology since there are huge demands for precision manufacture of high-value complex structural parts and repair of local defects. Extensive research has been conducted on AM process, characterization, and fatigue evaluation of titanium alloy, but there are rare comprehensive reviews on fatigue evaluation methods used for AM aero-engine blades. Rigorous tests, evaluation, and certification are necessary before AM technology is applied in aero-engine blade repair, although it has shown great advantages in different engineering fields. This paper introduces the application of AM technology in the manufacturing and repair of aero-engine titanium alloy blades, summarizes the key factors affecting the fatigue performance of AM titanium alloys, thoroughly discusses the fatigue mechanism, research methods, and process optimizations of AM parts, and compares the differences among several prediction models in fatigue evaluation of AM titanium alloys.Abbreviations: FOD: foreign object damage; LCF: low cycle fatigue; HCF: high cycle fatigue; LSP: laser shock peening; SP: shot peening; LP: low-pressure; HAZ: heat affected zone; AM: additive manufacturing; LAM: laser additive manufacturing; DED: directed energy deposition; PBF: powder bed fusion; LPBF: laser powder bed fusion; EPBF: electron beam powder bed fusion; LMD: laser metal deposition; LCD: laser cladding deposition; LENS: laser engineered net shaping; SLM: selective laser melting; EBM: electron beam melting; SEBM: selective electron beam melting; SLS: selective laser sintering; DMLS: direct Metal Laser Sintering; DMD-L: direct metal deposition by laser; DMD-P: direct metal deposition by plasma arc; LS: laser sintering; AB: as-built; LOF: lack of fusion; EVS: extreme value statistics; LEVD: largest extreme value distribution; VED: volumetric energy density; PD: probabilistic distribution; MRO: maintenance, repair & operations; STA: solution treatment & aging; BUS: broken-up structure; HIP: hot isostatic pressing; M&P: machining and polishing; SR: stress relief; AN: annealing; DAN: double annealing; PBG: prior β grain; TCT: thermochemical treatment; AC: air cooling; SMAT: surface mechanical attrition treatment; CT: computer tomography; SEM: scanning electron microscope; FCG: fatigue crack propagation; FCGR: fatigue crack propagation rate; SIF: stress intensity factor; EIFS: equivalent initial defect size; LEFM: linear elastic fracture mechanics; ML: machine learning; ANN: artificial neural network; FNN: feed forward neural network; CNN: convolutional neural network; PINN: physics-informed neural network; PPgNN: probabilistic physics-guided neural network; ANFS: adaptive network-based fuzzy system; SVM: support vector machine; SVR: support vector regression; RF: random forest; CDM: continuum damage mechanics.IMPACT STATEMENT The fatigue performance of additively manufactured titanium alloys is influenced by a combination of microstructure, defects, surface roughness, and residual stresses. In the context of fatigue assessment, the role of defects is typically prioritized.

Agricultural soil is the main source of greenhouse gas emissions, among which carbon dioxide (CO2) is an important greenhouse gas, impacting the global climate. In China, as a large rice-producing country, carbon sequestration and CO2 mitigation in paddy soil are crucial for the mitigation of global climate change. While biochar has been widely used in the mitigation of soil greenhouse gas emissions, the application site of biochar, i.e., whether or not it is the same as its feedstocks, may generate different effects on soil CO2 emissions due to the differences in the element and nutrient concentrations in its feedstocks, especially when applied in fertilized soil. In order to explore the effects of biochar application with different feedstocks on the mitigation of CO2 emissions from paddy soil, this experiment took paddy soil in a red soil area as the research object, using rice straw and Camellia oleifera fruit shell as raw materials to produce biochar (adding an amount of 40 g kg−1 soil) and urea as an external nitrogen source (adding an amount of 200 mg kg−1 soil). The effects of two different types of biochar derived from feedstocks with different producing origins on the CO2 emissions from paddy soil were studied via laboratory control incubation studies. The results showed that (1) the effects of rice straw biochar addition on the soil pH, NO3−-N and total available nitrogen (AN) content were significantly higher than those of Camellia oleifera fruit shell biochar (the scale of the increase was higher by 6.40%, 579.7% and 180.1%, respectively). (2) The CO2 emission rate and cumulative emissions of soil supplemented with rice straw biochar were significantly lower than in that supplemented with Camellia oleifera fruit shell biochar (decreases of 28.0% and 27.5%, respectively). Our findings suggest that the efficiency of emission mitigation of rice straw biochar is better than that of Camellia oleifera fruit shell applied to paddy soil. While future studies considering more types of greenhouse gases will be necessary to expand these findings, this study indicates that biochar prepared from in situ feedstock can be used to reduce greenhouse gas emissions in rice fields, so as to ensure sustainable development and achieve energy conservation and emission reduction goals. This study will benefit future agricultural practices when choosing biochar as a greenhouse gas mitigation strategy in the context of global warming, as well as other global changes following global warming, caused by elevated atmospheric greenhouse gases.

IntroductionStaphylococcus aureus, is a pathogen commonly encountered in both community and hospital settings. Patients receiving hemodialysis treatment face an elevated risk of vascular access infections (VAIs) particularly Staphylococcus aureus, infection. This heightened risk is attributed to the characteristics of Staphylococcus aureus, , enabling it to adhere to suitable surfaces and form biofilms, thereby rendering it resistant to external interventions and complicating treatment efforts.MethodsTherefore this study utilized PCR and microtiter dish biofilm formation assay to determine the difference in the virulence genes and biofilm formation among in our study collected of 103 Staphylococcus aureus, isolates from hemodialysis patients utilizing arteriovenous grafts (AVGs), tunneled cuffed catheters (TCCs), and arteriovenous fistulas (AVFs) during November 2013 to December 2021.ResultsOur findings revealed that both MRSA and MSSA isolates exhibited strong biofilm production capabilities. Additionally, we confirmed the presence of agr types and virulence genes through PCR analysis. The majority of the collected isolates were identified as agr type I. However, agr type II isolates displayed a higher average number of virulence genes, with MRSA isolates exhibiting a variety of virulence genes. Notably, combinations of biofilm-associated genes, such as eno−clfA−clfB−fib−icaA−icaD and eno−clfA−clfB−fib−fnbB−icaA−icaD, were prevalent among Staphylococcus aureus, isolates obtained from vascular access infections.DiscussionThese insights contribute to a better understanding of the molecular characteristics associated with Staphylococcus aureus, infections in hemodialysis patients and provided more targeted and effective treatment approaches.

Abstract Energy metabolism is a highly conserved process that balances generation of cellular energy and maintenance of redox homeostasis. It consists of five interconnected pathways: glycolysis, tricarboxylic acid cycle, pentose phosphate, trans-sulfuration, and NAD+ biosynthesis pathways. Environmental stress rewires cellular energy metabolism. Type-2 diabetes is a well-studied energy metabolism rewiring state in human pancreatic β-cells where glucose metabolism is uncoupled from insulin secretion. The two-spotted spider mite, Tetranychus urticae (Koch), exhibits a remarkable ability to adapt to environmental stress. Upon transfer to unfavourable plant hosts, mites experience extreme xenobiotic stress that dramatically affects their survivorship and fecundity. However, within 25 generations, mites adapt to the xenobiotic stress and restore their fitness. Mites’ ability to withstand long-term xenobiotic stress raises a question of their energy metabolism states during host adaptation. Here, we compared the transcriptional responses of five energy metabolism pathways between host-adapted and non-adapted mites while using responses in human pancreatic islet donors to model these pathways under stress. We found that non-adapted mites and human pancreatic β-cells responded in a similar manner to host plant transfer and diabetogenic stress respectively, where redox homeostasis maintenance was favoured over energy generation. Remarkably, we found that upon host-adaptation, mite energy metabolic states were restored to normal. These findings suggest that genes involved in energy metabolism can serve as molecular markers for mite host-adaptation.

Abstract Background To investigate the prevalence of euthyroid sick syndrome (ESS) and to evaluate the outcomes and risk factors associated with ESS among hospitalized patients with diabetic ketosis (DK) or diabetic ketoacidosis (DKA). Methods Laboratory and clinical data of 396 adult hospitalized DK/DKA patients with or without ESS were collected and analyzed. Spearman linear analysis and multivariable logistic regression analyses were used to evaluate correlated factors of thyroid hormones and risk factors of ESS. Results Most of the individuals were diagnosed with type 2 diabetes (359/396, 90.7%). The prevalence of ESS was 57.8% (229/396). Patients in ESS group were older and had a longer course of diabetes. Levels of thyroid hormones, serum lipids, and parameters reflecting acidosis were significantly decreased in ESS group. The proportion of patients with infection, acute renal injury and DKA was significantly higher in ESS group than in control group, accompanied by longer hospitalization stay and higher hospitalization costs. Free triiodothyronine positively correlates with albumin, eGFR, parameters reflecting acidosis and lipid profiles (All P

Abstract Objective To report a rare gastroblastoma; discuss its clinical features, histopathological morphology, diagnosis, differential diagnosis, treatment, and prognosis; and so as to improve the understanding on this disease and provide reference for its diagnosis, treatment, and prognosis. Methods The diagnosis and treatment, imaging examination, pathological, and genetic data of a 19-year-old young female patient with gastroblastoma were analyzed retrospectively, and the relevant literature was reviewed and summarized. Results The patient was found to have a “gastrointestinal stromal tumor” for 3 days by physical examination in another hospital. Abdominal CT and MRI considered “solid pseudopapilloma of pancreas” and clinically planned to perform “radical pancreatoduodenectomy.” During the operation, the tumor was observed to bulge from the posterior wall of the gastric antrum, and the root was located in the gastric antrum, so it was changed to “partial gastrectomy + Ronx-y gastrojejunal anastomosis.” The postoperative pathology showed that the tumor was bi-differentiated between gastric epithelium and mesenchymal. Combined with the results of IHC and the opinions of several consultation units, the diagnosis of gastric blastoma (low-grade malignancy) was supported. However, the fracture rearrangement of GLI1 and EWSR1 genes was not detected by FISH. After 19 months of follow-up, no signs of tumor recurrence and metastasis were found. Conclusion Combined with existing literature reports, gastroblastoma occurs in young people, equally in men and women, and tends to occur in the gastric antrum. The biological behavior of the tumor tends to be inert, and the prognosis of most cases is good. Postoperative pathology and IHC are reliable methods for the diagnosis of gastric blastoma, and surgical resection of the lesion is the preferred treatment.

Abstract Background The objective of this study was to examine the relationship of mental health status between self-poisoning suicide patients and their family members, and it also sought to identify potential patient’s risk and parental factors for the prediction of suicide attempt, anxiety, and depression. Methods In this study, 151 poisoned patients were prospectively included, and they were matched 1:1 with 151 family members. We gathered information on patient’s and their matched family member’s demographics, lifestyle choices, mental health status, level of intimacy, and history of psychiatry disease. The relationship of patient’s and their family member’s mental health state was investigated using a correlation matrix. Multivariable analyses (multiple logistic regression) were conducted among patients and their matched family members, to identify potential risk factors for self-poisoning suicide, anxiety, and depression. Results Of the total patients, 67.55% (102/151) attempted self-poisoning suicide. Poisoned patients had more severe anxiety and depression symptoms than their matched family members, and this difference was even more pronounced among patients with self-poisoning suicide. Generalized anxiety disorder-7 (GAD-7) score for family members was significantly and favorably correlated with patient’s GAD-7 score after eliminating non-suicide patients and their matched family members. The patient health questionnaire-9 (PHQ-9) score showed a similar pattern, and the family member’s PHQ-9 score was strongly and favorably associated with patient’s PHQ-9 and Beck hopelessness scale-20 (BHS-20) score. Multivariable analysis showed that married marital status (P = 0.038), quitting smoking (P = 0.003), sedentary time of 1 to 6 h (P = 0.013), and participation in a sports more than five times per week (P = 0.046) were all significantly associated with a lower risk of suicide by self-poisoning, while a more serious anxiety state (P = 0.001) was significantly associated with a higher risk of self-poisoning suicide. Multivariable analysis demonstrated that, specifically among self-poisoning suicide patients, married marital status (P = 0.011) and no history of psychiatry disease (P

Abstract Introduction Total hip arthroplasty for poliomyelitis sequelae could be a technical challenge due to the higher risk for prosthetic dislocation and degenerative changes in the affected limbs. This study aimed to analyse the mid-term outcomes of primary total hip arthroplasty on the affected hip with standard prosthesis. Materials and Methods From January 2008 to January 2018, 32 patients with poliomyelitis sequelae underwent total hip arthroplasty on the affected hip with standard prosthesis. Clinical and radiographical outcomes, complications, and prosthesis survival rates were evaluated. Results After a mean follow-up of 7.9 (4.4–13.1) years, the Harris Hip Score, University of California Los Angeles activity level rating, and 12-item Short Form Health Survey Questionnaire scale score significantly improved. The abduction and flexion motions of the hip joint improved dramatically, and the visual analogue scale pain score decreased significantly. The leg length discrepancy was effectively corrected. During the follow-up, one patient experienced prosthetic dislocation, one underwent revision surgery due to acetabular component loosening, two had osteolysis, four had heterotopic ossification, two experienced transient sciatic nerve palsy, and one had intermuscular vein thrombosis. The prosthesis survival rate was 96.9% at 5 years postoperatively. No periprosthetic infection occurred. Conclusion Total hip arthroplasty with standard prosthesis could be an effective treatment for hip arthropathy on the affected hip of patients with poliomyelitis sequelae, resulting in good clinical outcomes and few complications. Constrained liner and dual mobility articulation are not recommended unless the hip muscle strength of the abductor is

Background The high burden of extended-spectrum beta-lactamase-producing (ESBL)-producing Enterobacterales worldwide, especially in the densely populated South East Asia poses a significant threat to the global transmission of antibiotic resistance. Molecular surveillance of ESBL-producing pathogens in this region is vital for understanding the local epidemiology, informing treatment choices, and addressing the regional and global implications of antibiotic resistance. Methods Therefore, an inventory surveillance of the ESBL-Escherichia coli (ESBL-EC) isolates responsible for infections in Malaysian hospitals was conducted. Additionally, the in vitro efficacy of flomoxef and other established antibiotics against ESBL-EC was evaluated. Results A total of 127 non-repetitive ESBL-EC strains isolated from clinical samples were collected during a multicentre study performed in five representative Malaysian hospitals. Of all the isolates, 33.9% were isolated from surgical site infections and 85.8% were hospital-acquired infections. High rates of resistance to cefotaxime (100%), cefepime (100%), aztreonam (100%) and trimethoprim-sulfamethoxazole (100%) were observed based on the broth microdilution test. Carbapenems remained the most effective antibiotics against the ESBL-EC, followed by flomoxef. Antibiotic resistance genes were identified by PCR. The blaCTX-M-1 was the most prevalent ESBL gene, with 28 isolates (22%) harbouring blaCTX-M-1 only, 27 isolates (21.3%) co-harbouring blaCTX-M-1 and blaTEM, and ten isolates (7.9%) co-harbouring blaCTX-M-1, blaTEM and blaSHV. A generalised linear model showed significant antibacterial activity of imipenem against different types of infection. Besides carbapenems, this study also demonstrated a satisfactory antibacterial activity of flomoxef (81.9%) on ESBL-EC, regardless of the types of ESBL genes.

Abstract Since venous reflux is difficult to quantify, triggered angiography non-contrast-enhanced (TRANCE)-magnetic resonance imaging (MRI) is a novel tool for objectively evaluating venous diseases in the lower extremities without using contrast media. This study included 26 pre-intervention patients with superficial venous reflux in the lower extremities and 15 healthy volunteers. The quantitative flow (QFlow) analyzed the phase shift information from the pixels within the region of interest from MRI. The fast and simple radial basis function neural network (RBFNN) learning model is constructed by determining the parameters of the radial basis function and the weights of the neural network. The input parameters were the variables generated through QFlow, while the output variables were morbid limbs with venous reflux and normal limb classification. The stroke volume, forward flow volume, absolute stroke volume, mean flux, stroke distance, and mean velocity of greater saphenous veins from QFlow analysis could be used to discriminate the morbid limbs of pre-intervention patients and normal limbs of healthy controls. The neural network successfully classified the morbid and normal limbs with an accuracy of 90.24% in the training stage. The classification of venous reflux using the RBFNN model may assist physicians in clinical settings.

Abstract Objective This study aimed to investigate the changes in perceived public stigma (PPS) towards psychosis, and endorsement of medication treatment between 2009 to 2018 in the Hong Kong Chinese population.The role of education level on the changes in PPS and endorsement of medication treatment for psychosis was also examined. Methods Telephone survey of the general population was conducted in 2009, 2014, and 2018. PPS was assessed using the revised Link’s Perceived Discrimination-Devaluation Scale. Endorsement of medication was measured using an item asking if individuals with psychosis requires medication to manage their symptoms. Education level was separated into three categories (primary, secondary, and tertiary) for analysis. Factorial analysis of covariance was used to examine the main effects of survey year, education and endorsement of medication on stigma, and the interaction between survey year and education level, and survey year and endorsement of medication on PPS. Results 1016, 1018, and 1514 respondents completed the surveys in 2009, 2014, and 2018, respectively. PPS was found to be stable across the three public surveys. Endorsement of medication treatment was associated with higher PPS. An interaction effect between survey year and education level onPPS was observed. PPS was significantly lower and fewer respondents endorsed medication treatment in 2018 in the tertiary education group than in previous years. Conclusion Current findings suggest that a targeted approach may be required for different education groups when developing anti-stigma public campaigns. Inclusion of other aspects of knowledge about psychosis may also be useful in reduction of PPS.

BackgroundMedical disputes are a global public health issue that is receiving increasing attention. However, studies investigating the relationship between hospital legal construction and medical disputes are scarce. The development of a multicenter model incorporating machine learning (ML) techniques for the individualized prediction of medical disputes would be beneficial for medical workers. ObjectiveThis study aimed to identify predictors related to medical disputes from the perspective of hospital legal construction and the use of ML techniques to build models for predicting the risk of medical disputes. MethodsThis study enrolled 38,053 medical workers from 130 tertiary hospitals in Hunan province, China. The participants were randomly divided into a training cohort (34,286/38,053, 90.1%) and an internal validation cohort (3767/38,053, 9.9%). Medical workers from 87 tertiary hospitals in Beijing were included in an external validation cohort (26,285/26,285, 100%). This study used logistic regression and 5 ML techniques: decision tree, random forest, support vector machine, gradient boosting decision tree (GBDT), and deep neural network. In total, 12 metrics, including discrimination and calibration, were used for performance evaluation. A scoring system was developed to select the optimal model. Shapley additive explanations was used to generate the importance coefficients for characteristics. To promote the clinical practice of our proposed optimal model, reclassification of patients was performed, and a web-based app for medical dispute prediction was created, which can be easily accessed by the public. ResultsMedical disputes occurred among 46.06% (17,527/38,053) of the medical workers in Hunan province, China. Among the 26 clinical characteristics, multivariate analysis demonstrated that 18 characteristics were significantly associated with medical disputes, and these characteristics were used for ML model development. Among the ML techniques, GBDT was identified as the optimal model, demonstrating the lowest Brier score (0.205), highest area under the receiver operating characteristic curve (0.738, 95% CI 0.722-0.754), and the largest discrimination slope (0.172) and Youden index (1.355). In addition, it achieved the highest metrics score (63 points), followed by deep neural network (46 points) and random forest (45 points), in the internal validation set. In the external validation set, GBDT still performed comparably, achieving the second highest metrics score (52 points). The high-risk group had more than twice the odds of experiencing medical disputes compared with the low-risk group. ConclusionsWe established a prediction model to stratify medical workers into different risk groups for encountering medical disputes. Among the 5 ML models, GBDT demonstrated the optimal comprehensive performance and was used to construct the web-based app. Our proposed model can serve as a useful tool for identifying medical workers at high risk of medical disputes. We believe that preventive strategies should be implemented for the high-risk group.

PurposeThe risk of cardiovascular disease (CVD) mortality in patients with localized prostate cancer (PCa) by risk stratification remains unclear. The aim of this study was to determine the risk of CVD death in patients with localized PCa by risk stratification.Patients and methodsPopulation-based study of 340,806 cases in the Surveillance, Epidemiology, and End Results (SEER) database diagnosed with localized PCa between 2004 and 2016. The proportion of deaths identifies the primary cause of death, the competing risk model identifies the interaction between CVD and PCa, and the standardized mortality rate (SMR) quantifies the risk of CVD death in patients with PCa.ResultsCVD-related death was the leading cause of death in patients with localized PCa, and cumulative CVD-related death also surpassed PCa almost as soon as PCa was diagnosed in the low- and intermediate-risk groups. However, in the high-risk group, CVD surpassed PCa approximately 90 months later. Patients with localized PCa have a higher risk of CVD-related death compared to the general population and the risk increases steadily with survival (SMR = 4.8, 95% CI 4.6–5.1 to SMR = 13.6, 95% CI 12.8–14.5).ConclusionsCVD-related death is a major competing risk in patients with localized PCa, and cumulative CVD mortality increases steadily with survival time and exceeds PCa in all three stratifications (low, intermediate, and high risk). Patients with localized PCa have a higher CVD-related death than the general population. Management of patients with localized PCa requires attention to both the primary cancer and CVD.

Abstract Pure titanium is widely used in clinical implants, but its bioinert properties (poor strength and mediocre effect on bone healing) limit its use under load‐bearing conditions. Modeling on the structure of collagen fibrils and specific nanocrystal plane arrangement of hydroxyapatite in the natural bone, a new type of titanium (Ti) with a highly aligned fibrous‐grained (FG) microstructure is constructed. The improved attributes of FG Ti include high strength (≈950 MPa), outstanding affinity to new bone growth, and tight bone‐implant contact. The bone‐mimicking fibrous grains induce an aligned surface topological structure conducive to forming close contact with osteoblasts and promotes the expression of osteogenic genes. Concurrently, the predominant Ti(0002) crystal plane of FG Ti induces the formation of hydrophilic anatase titanium oxide layers, which accelerate biomineralization. In conclusion, this bioinspired FG Ti not only proves to show mechanical and bone‐regenerative improvements but it also provides a new strategy for the future design of metallic biomaterials.

Efforts have been made to alleviate plenty of various environmental issues and economic backwardness of elementary and secondary schools in rural China. In this paper, a multiple-perspective assessment framework was applied to evaluate the performance of three eco-campus systems. A set of emergy analysis, life cycle assessment, economic and social analysis indicators of the integrated framework were quantified and analyzed in detail. The results showed that the “Toilet-Biogas-Vegetables” mode (ESI=3.23) had the best sustainability in terms of comprehensive performance, followed by the “Grass-Goats&Toilet-Biogas-Fruits” mode (ESI=1.62) and the “Pigs&Toilet-Biogas-Vegetables” mode (ESI=0.82). In terms of environmental impact, the XDZS has the highest greenhouse gas emission reduction potential, reaching 26.44 ton in total. However, compared to common biogas integrated ecosystems, the three systems have some similarities in many aspects, such as appreciable resource recycling, net carbon sink, energy conservation, and economic feasibility. In this case, the combination of emergy synthesis, life cycle assessment, economic and social analysis provided a better insight into the comprehensive properties of rural campuses and thus could help us make a better environment for all the students and faculty.

BackgroundPrevious studies focused on the impact of cardiovascular diseases (CVD) risk factors in breast cancer patients with chemotherapy (CT) or radiotherapy (RT). This study aimed to identify the impact of tumor characteristics on CVD death in these patients.MethodsData of female breast cancer patients with CT or RT between 2004 and 2016 were included. The risk factors of CVD death were identified using Cox regression analyses. A nomogram was constructed to evaluate the predicted value of tumor characteristics, and then validated by the concordance indexes (C-index) and calibration curves.ResultA total of 28,539 patients were included with an average follow-up of 6.1 years. Tumor size > 45 mm (adjusted HR = 1.431, 95% CI = 1.116–1.836, P = 0.005), regional (adjusted HR = 1.278, 95% CI = 1.048–1.560, P = 0.015) and distant stage (adjusted HR = 2.240, 95% CI = 1.444–3.474, P

The study of circulating cells in the blood stream is critical, as it covers many fields of biomedicine, including immunology, cell biology, oncology, and reproductive medicine. In-vivo flow cytometry (IVFC) is a new tool to monitor and count cells in real time for long durations in their native biological environment. This review describes two main categories of IVFC, i.e., labeled and label-free IVFC. It focuses on label-free IVFC and introduces its technological development and related biological applications. Because cell recognition is the basis of flow cytometry counting, this review also describes various methods for the classification of unlabeled cells, including the latest machine learning-based technologies.

PurposeSuicide is a global concern, especially among young people. Suicide prediction models have the potential to make it easier to identify patients who are at a high risk of suicide, but they have very little predictive power when there is a positive value for suicide mortality. Therefore, the aim of the study is to uncover potential risk factors associated with suicide by self-poisoning and further to provide a trustworthy nomogram to predict self-poisoning suicide among poisoned patients.MethodsThis study prospectively enrolled 237 patients who were treated for poisoning at the Fifth Medical Center of PLA General Hospital (Beijing) between May 2021 and May 2022. Patient's basic characteristics, daily activities, mental health status, and history of psychological illnesses were gathered to examine their predictive power for self-poisoning suicide. On developing a prediction model, patients were split 8:2 into a training (n = 196) group and a validation (n = 41) group at random via computer. The training group worked on model development, while the validation group worked on model validation. In this study, the Hosmer and Lemeshow test, accuracy, and area under the curve were the primary evaluation criteria. Shapley Additive exPlanations (SHAP) was determined to evaluate feature importance. To make the prediction model easy for researchers to utilize, it was presented in nomogram format. Two risk groups of patients were identified based on the ideal cut-off value.ResultsOf all poisoned patients, 64.6% committed suicide by self-poisoning. With regard to self-poisoning attempted suicide, multivariate analysis demonstrated that female gender, smoking, generalized anxiety disorder-7 (GAD-7), and beck hopelessness scale-20 (BHS-20) were significant risk factors, whereas married status, relatively higher education level, a sedentary time of 1–3 h per day, higher sport frequency per week, higher monthly income were significant protective features. The nomogram contained each of the aforementioned nine features. In the training group, the area under curve (AUC) of the nomogram was up to 0.938 (0.904–0.972), whereas in the validation group, it reached a maximum of 0.974 (0.937–1.000). Corresponding accuracy rates were up to 0.883 and 0.927, respectively, and the P-values for the Hosmer and Lemeshow test were 0.178 and 0.346, respectively. SHAP demonstrated that the top three most important features were BHS-20, GAD-7, and marital status. Based on the best cut-off value of the nomogram (40%), patients in the high-risk group had a nearly six-time larger likelihood of committing suicide by self-poisoning than patients in the low-risk group (88.68 vs. 15.38%, P < 0.001). The dynamic nomogram was made available at the following address: https://xiaobo.shinyapps.io/Nomogramselfpoisoningsuicide/.ConclusionsThis study proposes a prediction model to stratify patients at a high risk of suicide by self-poisoning and to guide individual preventive strategies. Patients in the high-risk group require further mental health counseling to alleviate anxiety and hopelessness, healthy lifestyle like quitting smoking and exercising more, and restriction of access to poison and psychiatric drugs.

With the continuous development of synthetic aperture radar (SAR) systems, multipolarization information has been increasingly applied to numerous fields, and automatic target recognition (ATR) in polarimetric SAR (POLSAR) has been recognized as vital problem. The SAR recognition methods can primarily fall into handcrafted feature-based algorithms and deep learning algorithms. The former exhibits excellent interpretability but insufficient generalization; the latter achieves stronger representational ability but relies on a considerable number of samples. To solve above problems, a feature fusion framework is proposed in this article based on monogenic signal and complex-valued nonlocal network (CVNLNet) for POLSAR target recognition. The proposed feature fusion framework effectively uses the complementarity of handcrafted features and deep features, while making up for the disadvantages of single feature-based methods. First, a Mono-BOVW model is proposed based on monogenic signal and bag-of-visual-words (BOVW) model to extract handcrafted features, which can more fully mine the information covered in POLSAR data in multiscale space. Moreover, CVNLNet is built for deep feature extraction to use both the amplitude and phase covered in POLSAR data. Next, a kernel discrimination correlation analysis algorithm is proposed to jointly analyze and transform the two features, so as to remove redundant information while retaining effective and discriminative information. Experiments on the MSTAR dataset and the GOTCHA dataset show that the proposed framework has superior performance on single polarimetric and fully polarimetric datasets.

Objectives: Carbapenem-resistant Enterobacteriaceae (CRE) is a multidrug-resistant gram-negative bacteria (MDR-GNB) that is rapidly emerging as a life-threatening nosocomial disease in many countries. We sought to identify the risk factors associated with mortality for carriage of CRE in patients at a tertiary-care teaching hospital. Methods: A retrospective observational study was conducted between January 2020 to December 2021 in a tertiary-care teaching healthcare facility, University Malaya Medical Centre in Malaysia. The study included all inpatients aged ≥18 years who had a CRE infection or were colonized during the study period. The genotype was identified by polymerase chain reaction (PCR). Statistical analysis of data including a multivariate logistic regression analysis was conducted using SPSS version 23.0 software. Results: In total, 176 cases of CRE (130 infection and 46 colonized) were identified, and the mortality rate was 31.8%. The main sources of CRE were rectal swab (61.9%), blood (11.9%), and respiratory sources (11.9%). Klebsiella pneumoniae (55.7%) was the predominant species, followed by Escherichia coli (21.6%). Among the isolates, 17.7% were non–CPE-CRE and 82.3% were CPE-CRE: NDM (69.3%) and OXA (10.8%). In multivariate analysis, the factors associated with mortality were older age (OR, 1.040; 95% CI, 1.012–1.069), longer length of stay (OR, 0.974; 95% CI, 0.955–0.994), use of central venous catheter (OR, 0.287; 95% CI, 0.094–0.878), and arterial lines (OR, 0.292; 95% CI, 0.095–0.891). Conclusion: Patients with CRE had a high mortality rate. Older age, longer duration of stay, indwelling CVC and arterial line were independent risk factors for death. Infection prevention and control measures to reduce CRE, such as active surveillance, contact precautions, compliance to intravenous catheter care bundles, healthcare worker education, and hand hygiene adherence, should be implemented.

Objectives: Influenza vaccination is encouraged for all healthcare workers (HCWs) to reduce the risk of acquiring the infection and onward transmission to colleagues and patients during the influenza season. Thus, vaccination was introduced at Singapore General Hospital (SGH) in 2007 and has been offered to all HCWs at no cost. The HCW influenza vaccination program is conducted annually in October and biannually during years with vaccine mismatch. However, influenza vaccine uptake remained low among HCWs. We sought to determine the impact of the coronavirus disease 2019 (COVID-19) pandemic on influenza vaccine uptake among HCWs. Methods: At SGH, 2 methods of vaccine delivery are offered: centralized (1-month drop-in system during office hours) and decentralized (administered by vaccination teams in offices or ward staff in inpatient locations). In the 4-year study period between 2018 and 2021, 6 influenza vaccination exercise campaigns were conducted during 8 influenza seasons. During each exercise, ~9,000 HCWs were eligible for vaccination. Results: Prior to the COVID-19 pandemic, vaccine uptake in the Southern Hemisphere was 77.6% (6,964 of 8,977) in 2018 and 84.2% (7,296 of 8,670) in 2019. During the COVID-19 pandemic in 2020, vaccine uptake in the Southern Hemisphere increased by 10% to 94.1% (8,361 of 8,889). In the Northern Hemisphere, vaccine uptake was 79.2% (7,114 of 8,977) in 2018, and this increased by 17.9% to 97.1% (8,926 of 9,194) during the COVID-19 pandemic in 2020. During the 2021 Southern Hemisphere influenza season, no vaccination program was conducted because the risk of influenza was considered low due to the closure of international borders and the implementation of public health measures. In addition, priority was given to COVID-19 vaccination efforts. Conclusions: Increased uptake of the influenza vaccination was observed during the COVID-19 pandemic. Anxiety created by the respiratory disease pandemic and debate surrounding vaccines likely contributed to increased awareness and uptake in influenza vaccine among HCWs.

Objectives: Surgical-site infections (SSIs) cause significant increases in mortality, morbidity, and prolonged hospitalization after cesarean deliveries. We assessed the effectiveness of the implementation of an SSI bundle in reducing postoperative infections in cesarean deliveries in a tertiary-care teaching hospital in Malaysia. Method: We conducted a quality-improvement study on all women who underwent labor and scheduled cesarean sections at the University Malaya Medical Center (UMMC) between May and December 2020. The preintervention period was May–June 2020 and the postintervention period was September–December 2020. Patients were followed for 90 days after their operation. Before the intervention, SSI rates and compliance with prevention practices were documented. A multidisciplinary team was formed, and education regarding the elements of the SSI prevention bundle was conducted before they were implemented. The care bundle focused on monitoring compliance with preoperative bathing, contact time for skin preparation, hair management, and antibiotics prophylaxis given within 60 minutes prior to incision, as well as patient education. Result: With the implementation of the SSI bundle, we observed a significant reduction in the SSI rate by 50%, from 7 per 100 procedures to 2 per 100 procedures. Compared with the preintervention period, overall compliance with bundle elements improved greatly for preoperative bathing (0 vs 95.7%) and contact time for skin preparation (0 vs 98.8%). In the postintervention period, the method of hair removal was documented, compared to no documentation during the preintervention period. The administration of prophylactic antibiotics within 60 minutes prior incision decreased from 99% to 92.3%. Conclusion: Implementation of an SSI prevention bundle successfully reduced the rate of SSI after cesarean section. The SSI prevention bundle together with improvements by multidisciplinary teams and a good patient-safety culture helped reduce SSI rates. Patient education on pre- and postoperative infection prevention also played an important role in reducing this infection rate.

PurposeUsing an ensemble machine learning technique that incorporates the results of multiple machine learning algorithms, the study’s objective is to build a reliable model to predict the early mortality among hepatocellular carcinoma (HCC) patients with bone metastases.MethodsWe extracted a cohort of 124,770 patients with a diagnosis of hepatocellular carcinoma from the Surveillance, Epidemiology, and End Results (SEER) program and enrolled a cohort of 1897 patients who were diagnosed as having bone metastases. Patients with a survival time of 3 months or less were considered to have had early death. To compare patients with and without early mortality, subgroup analysis was used. Patients were randomly divided into two groups: a training cohort (n = 1509, 80%) and an internal testing cohort (n = 388, 20%). In the training cohort, five machine learning techniques were employed to train and optimize models for predicting early mortality, and an ensemble machine learning technique was used to generate risk probability in a way of soft voting, and it was able to combine the results from the multiply machine learning algorithms. The study employed both internal and external validations, and the key performance indicators included the area under the receiver operating characteristic curve (AUROC), Brier score, and calibration curve. Patients from two tertiary hospitals were chosen as the external testing cohorts (n = 98). Feature importance and reclassification were both operated in the study.ResultsThe early mortality was 55.5% (1052/1897). Eleven clinical characteristics were included as input features of machine learning models: sex (p = 0.019), marital status (p = 0.004), tumor stage (p = 0.025), node stage (p = 0.001), fibrosis score (p = 0.040), AFP level (p = 0.032), tumor size (p = 0.001), lung metastases (p < 0.001), cancer-directed surgery (p < 0.001), radiation (p < 0.001), and chemotherapy (p < 0.001). Application of the ensemble model in the internal testing population yielded an AUROC of 0.779 (95% confidence interval [CI]: 0.727–0.820), which was the largest AUROC among all models. Additionally, the ensemble model (0.191) outperformed the other five machine learning models in terms of Brier score. In terms of decision curves, the ensemble model also showed favorable clinical usefulness. External validation showed similar results; with an AUROC of 0.764 and Brier score of 0.195, the prediction performance was further improved after revision of the model. Feature importance demonstrated that the top three most crucial features were chemotherapy, radiation, and lung metastases based on the ensemble model. Reclassification of patients revealed a substantial difference in the two risk groups’ actual probabilities of early mortality (74.38% vs. 31.35%, p < 0.001). Patients in the high-risk group had significantly shorter survival time than patients in the low-risk group (p < 0.001), according to the Kaplan–Meier survival curve.ConclusionsThe ensemble machine learning model exhibits promising prediction performance for early mortality among HCC patients with bone metastases. With the aid of routinely accessible clinical characteristics, this model can be a trustworthy prognostic tool to predict the early death of those patients and facilitate clinical decision-making.

Chronic pain is one of the most common clinical syndromes affecting patients’ quality of life. Regulating the transition from acute to chronic pain is a novel therapeutic strategy for chronic pain that presents a major clinical challenge. However, the mechanism underlying pain transitions remains poorly understood. A rat hyperalgesic priming (HP) model, which mimics pain transition, was established decades ago. Here, this HP model and RNA sequencing (RNA-seq) were used to study the potential role of neuroinflammation in pain transition. In this study, HP model rats developed prolonged hyperalgesia in the hind paw after carrageenan (Car) and PGE2 injection, accompanied by obvious satellite glial cell (SGC) activation in the dorsal root ganglion (DRG), as indicated by upregulation of GFAP. RNA-Seq identified a total of differentially expressed genes in the ipsilateral DRG in HP model rats. The expression of several representative genes was confirmed by real-time quantitative PCR (qPCR). Functional analysis of the differentially expressed genes indicated that genes related to the inflammatory and neuroinflammatory response showed the most significant changes in expression. We further found that the expression of the chemokine CXCL1 was significantly upregulated in the rat DRG. Pharmacological blockade of CXCL1 reduced protein kinase C epsilon overproduction as well as hyperalgesia in HP rats but did not prevent the upregulation of GFAP in the DRG. These results reveal that neuroinflammatory responses are involved in pain transition and may be the source of chronic pain. The chemokine CXCL1 in the DRG is a pivotal contributor to chronic pain and pain transition in HP model rats. Thus, our study provides a putative novel target for the development of effective therapeutics to prevent pain transition.

Abstract Background Poor mental health was reported among medical graduate students in some studies. Identification of risk factors for predicting the mental health is capable of reducing psychological distress among medical graduate students. Therefore, the aim of the study was to identify potential risk factors relating to mental health and further create a novel prediction model to calculate the risk of mental distress among medical graduate students. Methods This study collected and analyzed 1079 medical graduate students via an online questionnaire. Included participants were randomly classified into a training group and a validation group. A model was developed in the training group and validation of the model was performed in the validation group. The predictive performance of the model was assessed using the discrimination and calibration. Results One thousand and fifteen participants were enrolled and then randomly divided into the training group (n = 508) and the validation group (n = 507). The prevalence of severe mental distress was 14.96% in the training group, and 16.77% in the validation group. The model was developed using the six variables, including the year of study, type of student, daily research time, monthly income, scientific learning style, and feeling of time stress. The area under the receiver operating characteristic curve (AUROC) and calibration slope for the model were 0.70 and 0.90 (95% CI: 0.65 ~ 1.15) in the training group, respectively, and 0.66 and 0.80 (95% CI, 0.51 ~ 1.09) in the validation group, respectively. Conclusions The study identified six risk factors for predicting anxiety and depression and successfully created a prediction model. The model may be a useful tool that can identify the mental status among medical graduate students. Trial registration No. ChiCTR2000039574 , prospectively registered on 1 November 2020.

Abstract Studies on the development of central nervous system (CNS) primarily rely on the use of specific molecular markers for different types of neural cells. S100B is widely being used as a specific marker for astrocytes in the CNS. However, the specificity of its expression in astrocyte lineage has not been systematically investigated and thus has remained a lingering issue. In this study, we provide several lines of molecular and genetic evidences that S100B is expressed in both protoplasmic astrocytes and myelinating oligodendrocytes. In the developing spinal cord, S100B is first expressed in the ventral neuroepithelial cells, and later in ALDH1L1+/GS+ astrocytes in the gray matter. Meanwhile, nearly all the S100B+ cells in the white matter are SOX10+/MYRF+ oligodendrocytes. Consistent with this observation, S100B expression is selectively lost in the white matter in Olig2-null mutants in which oligodendrocyte progenitor cells (OPCs) are not produced, and dramatically reduced in Myrf-conditional knockout mutants in which OPCs fail to differentiate. Similar expression patterns of S100B are observed in the developing forebrain. Based on these molecular and genetic studies, we conclude that S100B is not a specific marker for astrocyte lineage; instead, it marks protoplasmic astrocytes in the gray matter and differentiating oligodendrocytes.

Dislocation is the primary carrier for accommodating plastic deformation in metals. It is generally envisaged that metals with low initial dislocation density have high strain-to-failure and good formability, and vice versa. However, contrary to most metals, body-centered-cubic pure tungsten becomes brittle after reducing its dislocation density by recrystallization, while its formability increases after heavy deformation. To elucidate the mechanism of this counterintuitive mechanical behavior, by combining ex-situ indentation tests and dislocation reconstruction techniques, we find that tungsten’s deformation and failure processes are accompanied by the formation of a specific dislocation pattern. Dislocation networks are governed by a mechanism similar to the weaving process of the spider’s orb web. After heavy deformation, subgrains are generated due to the weaving process. The recurring weaving of dislocations reduces the mean free path for crack propagation, which is considered as the main reason for the increased formability of tungsten after deformation.

Overfishing has significantly decreased global shark populations, with some species experiencing reductions of approximately 70% over the last 50 years. Singapore is a major shark fin transhipment hub that helps to satisfy the global demand for shark fins, which are considered status symbols and reputed to have medicinal value in Asian culture. Despite the recognised and urgent need to better protect shark populations, the success of such efforts has been limited by the difficulties associated with visually identifying the species of shark from which the fins originated. In this study, we collected 451 shark fin tissue samples from a variety of local retail markets in Singapore. Using DNA barcoding techniques, we amplified a 350 base pair fragment of the mitochondrial cytochrome c oxidase subunit I (COI) gene from each to identify the species sold in Singapore. We identified 22 shark species, of which 17 are categorised as Threatened (Critically Endangered, Endangered or Vulnerable) under the IUCN Red List. Six of these species are also listed on Appendix II of the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES).

BackgroundMedical disputes are common in hospitals and a major challenge for the operations of medical institutions. However, few studies have looked into the association between medical disputes and hospital legal constructions. The purpose of the study was to investigate the relationship between hospital legal constructions and medical disputes, and it also aimed to develop a nomogram to estimate the likelihood of medical disputes.MethodsBetween July and September 2021, 2,716 administrators from 130 hospitals were enrolled for analysis. The study collected seventeen variables for examination. To establish a nomogram, administrators were randomly split into a training group (n = 1,358) and a validation group (n = 1,358) with a 50:50 ratio. The nomogram was developed using data from participants in the training group, and it was validated in the validation group. The nomogram contained significant variables that were linked to medical disputes and were identified by multivariate analysis. The nomogram's predictive performance was assessed utilizing discriminative and calibrating ability. A web calculator was developed to be conducive to model utility.ResultsMedical disputes were observed in 41.53% (1,128/2,716) of participants. Five characteristics, including male gender, higher professional ranks, longer length of service, worse understanding of the hospital charters, and worse construction status of hospital rule of law, were significantly associated with more medical disputes based on the multivariate analysis. As a result, these variables were included in the nomogram development. The AUROC was 0.67 [95% confident interval (CI): 0.64–0.70] in the training group and 0.68 (95% CI: 0.66–0.71) in the validation group. The corresponding calibration slopes were 1.00 and 1.05, respectively, and intercepts were 0.00 and −0.06, respectively. Three risk groups were created among the participants: Those in the high-risk group experienced medical disputes 2.83 times more frequently than those in the low-risk group (P < 0.001).ConclusionMedical dispute is prevailing among hospital administrators, and it can be reduced by the effective constructions of hospital rule of law. This study proposes a novel nomogram to estimate the likelihood of medical disputes specifically among administrators in tertiary hospitals, and a web calculator can be available at https://ymgarden.shinyapps.io/Predictionofmedicaldisputes/.

Background and Objectives: This study was conducted to investigate whether Pseudomonas aeruginosa (PA) infections of arteriovenous grafts (AVGs) recur more frequently than other bacterial infections following treatment with revision. Materials and Methods: Operative procedures, including total excision, subtotal excision, and revision, were performed on 60 patients to treat 65 AVG infections. Final outcomes were classified as no infection recurrence, infection recurrence, and death without prior recurrence. In the competing risk setting, the cumulative incidence was estimated using the cumulative incidence function and Gray’s test, and the associations between outcomes and different variables were estimated using a subdistribution hazard (SDH) model. Results: Comparing AVG infections with and without recurrence, PA infection was not associated with a higher risk of infection recurrence (p = 0.13); however, the first operative procedure type was associated with infection recurrence (p = 0.04). AVGs with PA infection were associated with a higher total number of surgical interventions (p < 0.05) than AVGs without PA infection. Regarding the cumulative incidences of outcomes, for AVGs treated with subtotal excision or revision, the cumulative incidence of recurrent infection was 3.3-fold higher for those with PA infection than without one year after the first surgery. However, when AVGs were treated with revision alone, the cumulative incidence was 4.1-fold. After excluding AVGs treated with total excision, the SDH model was applied, obtaining a hazard ratio for infection recurrence of 16.05 (p = 0.02) for AVGs with PA infection compared with AVGs without PA infection. No other variables were significantly associated with infection recurrence. Conclusions: For subtotal resection and revision, AVGs infected with PA had a higher recurrence rate than those infected with other species. However, revision surgery may aggravate the recurrence rate.

Abstract Background The programmed death 1 (PD-1)/programmed death-ligand 1 (PD-L1) have shown positive efficacy in several solid cancers due to their targeted antitumour effects. However, the frequency and clinical implication value in prostate cancer still remain unclear. Methods The PD-1/PD-L1 expression was detected by immunohistochemical (IHC) analysis in 96 retrospectively collected cases of prostatic cancer and 44 controls of benign prostatic hyperplasia (BPH). Its correlation with clinicopathological features including age, PSA level, Gleason score, lymph node metastasis, clinical T stage and risk factor grade in prostate cancer was also assessed. Results The PD-L1-positive expression was significantly higher in cancer cases compared with benign tissues, whereas no difference in PD-1 positive expression was found. Moreover, the PD-L1 expression in tumour cells or lymphocytes was associated with Gleason score, but not related to age, preoperative PSA level, clinical T-stage, lymph node metastasis and grade of risk factors. In addition, no association between the positive expression of PD-1 and PD-L1 in tumour cells and lymphocytes was found. Conclusions The expression of PD-L1 not PD-1 is highly prevalent in prostate cancer. PD-L1 is closely related to Gleason score and may be a co-factor associated with the progression of prostate cancer.

Abstract Background Euglycaemic ketoacidosis (EKA) is an infrequent but serious condition which usually follows a period of starvation, severe vomiting or illness in individuals with or without diabetes. Ketoacidosis is associated with materno-fetal morbidity and mortality necessitating prompt diagnosis and management. Physiological increases in insulin resistance render pregnancy a diabetogenic state with increased susceptibility to ketosis. COVID-19 is associated with worse clinical outcomes in patients with diabetes and is an independent risk factor for ketoacidosis in normoglycaemic individuals. Case presentations We describe two cases of SARS-CoV-2 positive pregnant women presenting with normoglycaemic metabolic ketoacidosis. Both cases were associated with maternal and fetal compromise, requiring aggressive fluid and insulin resuscitation and early delivery. Conclusion We discuss possible physiology and propose a management strategy for euglycaemic ketoacidosis in pregnancy.

The aim of this study was to develop and validate a prediction model to evaluate the risk of poor sleep quality. We performed a cross-sectional study and enrolled 1,928 college students from five universities between September and November 2021. The quality of sleep was evaluated using the Chinese version of the Pittsburgh Sleep Quality Index (PSQI). Participants were divided into a training (n = 1,555) group and a validation (n = 373) group. The training group was used to establish the model, and the validation group was used to validate the predictive effectiveness of the model. The risk classification of all participants was performed based on the optimal threshold of the model. Of all enrolled participants, 45.07% (869/1,928) had poor sleep quality (PSQI score ≧ 6 points). Multivariate analysis showed that factors such as older age, a higher grade, previous smoking, drinking, midday rest, chronic disease, anxiety, and stress were significantly associated with a higher rate of poor sleep quality, while preference for vegetables was significantly associated with better sleep quality, and all these variables were included to develop the prediction model. The area under the curve (AUC) was 0.765 [95% confidence interval (CI): 0.742–0.789] in the training group and 0.715 (95% CI: 0.664–0.766) in the validation group. Corresponding discrimination slopes were 0.207 and 0.167, respectively, and Brier scores were 0.195 and 0.221, respectively. Calibration curves showed favorable matched consistency between the predicted and actual probability of poor sleep quality in both groups. Based on the optimal threshold, the actual probability of poor sleep quality was 29.03% (317/1,092) in the low-risk group and 66.03% (552/836) in the high-risk group (P < 0.001). A nomogram was presented to calculate the probability of poor sleep quality to promote the applicationof the model. The prediction model can be a helpful tool to stratify sleep quality, especially among university students. Some intervention measures or preventive strategies to quit smoking and drinking, eat more vegetables, avoid midday rest, treat chronic disease, and alleviate anxiety and stress may be considerably beneficial in improving sleep quality.

Thrombocytopenia can cause substantial morbidity and mortality in critically ill patients. There are multiple etiology factors and various mechanisms associated with thrombocytopenia, of which drug-induced thrombocytopenia (DITP) deserves attention. Herein, we describe a case of severe thrombocytopenia during intensive care unit (ICU) hospitalization that was likely to be associated with vancomycin. By revealing the process of identifying this case of DITP and reviewing relevant clinical studies, a risk alert of vancomycin-related severe hematotoxicity should be considered.

IntroductionDietary vitamin A concentrations correlate with depression. Zinc has been reported to be associated with lower depression. In addition, zinc is an important cofactor in the activation of vitamin A. However, there are few studies investigating relationships between of dietary zinc intake, dietary vitamin A intake and depression.Materials and MethodsThe data for this study came from the National Health and Nutrition Examination Survey (NHANES) from 2005 to 2018 and involved 70,190 participants. We stratified participants by recommended dietary zinc intake (recommended dietary zinc intake for women: 8 mg/day, recommended dietary zinc intake for men: 11 mg/day). We further assessed the association between vitamin A and depression in participants with low and high zinc intake (interaction test) using univariate logistic regression of intake participants.ResultIn the female population we grouped the population into low and high zinc intake groups using the recommended dietary zinc intake of 8 (mg/day), with an increase in total vitamin A, the risk of depression was significantly lower in the low zinc intake group (OR: 0.85 95 CI: 0.76–0.96), while the risk of depression was increased in the high zinc intake group (OR: 1.05 95 CI: 0.95 to 1.17). Thus, in the female population, there was a significant interaction between insufficient vitamin an intake and depression (interaction likelihood ratio test of p = 0.011). In the male population we grouped the population by the recommended dietary zinc intake of 11(mg/day). Again, the population was divided into two groups with low and high zinc intake, however we did not find significant results for the interaction (p = 0.743 for the interaction likelihood ratio test).ConclusionOur findings suggest that zinc intake may influence the relationship between dietary vitamin A and depression. Of course, our findings require further randomized controlled trials to enhance the credibility.

Abstract Background Individuals with psychiatric disorders are often unwilling to seek help or often follow treatment regimens, fearing public stigma. This study identified the sociodemographic correlates of public stigma while accounting for mental health literacy and life satisfaction. Methods This study analysed data for 1514 individuals who participated in a population-based random telephone survey conducted in 2018. Sociodemographic characteristics included gender, age, education level, and occupation. Data on public stigma, mental health literacy, and life satisfaction were also collected. Multiple linear regression was conducted to examine the effects of sociodemographic characteristics on public stigma. A moderation analysis was performed to investigate the role of age and education in the relationship between mental health literacy and public stigma. Results Sociodemographic characteristics, such as female gender, older age, lower education, and occupation (particularly retired and homemakers), were associated with a higher public stigma. The association between public stigma and mental health literacy was the most significant among individuals aged 50 years and above with lower education levels. Conclusions This study showed that certain population subgroups, based on their sociodemographic profile, have a higher stigma about mental illnesses. Understanding the differential effects of sociodemographic factors on public stigma is imperative to developing effective anti-stigma campaigns.

Abstract Background The deployment of antimicrobial stewardship (AMS) teams to deal with the COVID-19 pandemic can lead to a loss of developed frameworks, best practices and leadership resulting in adverse impact on antimicrobial prescribing and resistance. We aim to investigate effects of reduction in AMS resources during the COVID-19 pandemic on antimicrobial prescribing. Methods One of 5 full-time equivalent AMS pharmacists was deployed to support pandemic work and AMS rounds with infectious disease physicians were reduced from 5 to 2 times a week. A survey in acute inpatients was conducted using the Global Point Prevalence Survey methodology in July 2020 and compared with those in 2015 and 2017–2019. Results The prevalence of antimicrobial prescribing (55% in 2015 to 49% in 2019 and 47% in 2020, p = 0.02) and antibacterials (54% in 2015 to 45% in 2019 and 42% in 2020, p