bluuebunny/crossref_metadata_2025_split huggingface dataset:
Critical strategies for implementing supported employment
Authors: Becker Deborah R. , Baker Stephen R. , Carlson Linda , Flint Laura , Howell Ruth , Lindsay Shannon , Moore Michael , Reeder Steven , Drake Robert E. 
Published: November 2024

Objective: This paper provides a review of experiences by six states and the District of Columbia in disseminating an evidence-based practice, supported employment (SE). Each jurisdiction had unique strengths and barriers to overcome to effectively implement supported employment services for people with severe mental illness. Methods: Using a case study approach seven jurisdictions report special aspects surrounding the implementation of evidence-based supported employment. Results: Diverse strategies were used to augment implementation of supported employment services: a) Instituting state-level administrative procedures and reconfiguration of local staffing to enhance collaboration between mental health and vocational rehabilitation; b) Promoting SE services through the media, on-line training, and training by early adopters; c) Hiring benefits specialists; d) Teaching outcome-based supervision; and e) Building capacity for supported employment fidelity reviews. Conclusions: Dissemination of evidenced-based supported employment was enhanced when six states and the District of Columbia addressed special aspects. Supported employment implementation included different pathways to good employment outcomes.
Assessment of working conditions and implementation of changes	among employees with spinal cord lesion – A case series
Authors: Sandsjö Leif , Valtonen Kirsi , Grundell Lena Olsson , Karlsson Ann-Katrin , Viikari-Juntura Eira 
Published: November 2024

The objective of this study was to identify work situations of concern, implement changes, and evaluate how these changes affect working conditions in a group of employees with traumatic spinal cord injury (SCI) and meningomyelocele (MMC). Six persons with traumatic SCI and one with MMC were visited by an ergonomist at their workplace and assessed regarding accessibility and physical workload factors, especially risk factors for neck/shoulder disorders. The working conditions were documented by means of video, questionnaires, and the ergonomist's own observations. From situations identified, including the participant's own reporting of problematic situations, possible changes were discussed and implemented if feasible. All participants were offered to take part in a myofeedback intervention, aiming at reducing muscle load of the neck and shoulder muscles. A remodelling of the workplace to get better access to items and tools was carried out in five out of seven cases. After these changes, the number of identified situations of concern was reduced. The relative rest time (RRT) improved in the neck and shoulder after the intervention in the four participants that completed the myofeedback training. This study demonstrates that the working conditions of persons with spinal cord lesion (SCL) can be improved by an ergonomic intervention.
Commentary: Access to Virtual Care Matters: The Problem with Giving to Some and Not All
Authors: Chung-Lee Leinic , Catallo Cristina , Fredericks Suzanne 
Published: November 2024

<p> </p>
<p>Expedited in the midst of the COVID-19 pandemic, virtualization of healthcare is becoming an inevitable norm. While this conveys hope for improving health systems performance, inequitable access could result in consequences that intensify health disparities and increase the burden on the health system. Nurse leaders are optimally positioned to tactfully influence policy directions on virtual care and shape a comprehensive research agenda that includes virtual nursing care in all domains of practice. With virtual care advancing into the mainstream, it is time to mind the health equity gap and co-design virtualized care that ensures the needs of all are met.</p>
Deep Learning Based Clustering of Gene Expression Data in Cancer Patients using Variational Autoencoder Model
Authors: Mehmood Zunaira , Sharma Divya 
Published: November 2024

Background: High mortality associated with cancer presents challenges in both diagnosis and treatment. Deep learning-based clustering analysis provides a powerful tool for identifying molecular subtypes within cancer enabling personalized treatment strategies.
Objectives: This project has two objectives: (1) to cluster gene expression data for cancer patients into unique subtypes to uncover novel biological insights and improve patient outcomes; (2) to identify unique molecular signatures driving each cluster.
Methods: GDC Pan-Cancer data, consisting of 33 tumor types with 11,506 samples and 32,967 gene expression features, from TCGA repository was used. Outliers were identified using interquartile criterion, and replaced using multiple imputation by chained equations. A variational autoencoder (VAE) model was used to extract latent representations within the gene expression data. These latent features were then utilized in K-Means clustering to identify distinct clusters based on similarity in gene expression profiles. Survival rate and median survival time for each cluster were computed, and statistical tests were used to determine the significance of the observed differences. Finally, gene signatures for individual clusters were developed using standardized mean difference (SMD) analysis, determining features significant in one cluster vs the others (p<0.05).
Results: Survival rates vary significantly across clusters (p<0.05). Clustering helped identify clusters with low survival rates. Subsequently, distinct gene signatures identified for each cluster helped determine molecular mechanisms driving survival outcomes.
Conclusion: A deep learning-based model efficiently groups cancer patients, revealing unique molecular signatures within each subgroup. Screening and prioritizing treatment for patients in subgroups with lower survival rates could enhance patient management.
Risk Factors Associated with Mood Disorders in Canada
Authors: Jiang Yuchen , Nisenbaum Rosane 
Published: November 2024

Background: Mental health presents a profound challenge globally, affecting around 970 million individuals. In Canada, mental disorders significantly impact the well-being of society and individuals, with one in three Canadians expected to face a mental problem during their lifetime. However, the utilization of mental health services is low, and a large proportion of the population does not have access to effective care.

Objectives: This study was designed to identify key sociodemographic, clinical, and lifestyle factors associated with the prevalence of mood disorders among Canadians, thereby aiding in the development of targeted interventions.

Methods: Utilizing data from the Canadian Community Health Survey 2017-2018, multivariable logistic regression analysis was performed, incorporating the sampling weights to make the inference representative of the Canadian population. Bootstrap weighting was applied to the multivariable associations to ensure robust variance estimates.

Results: Females (OR, 1.98; 95% CI, 1.86-2.16) and individuals with higher obesity levels (pre-obesity: OR, 1.05; 95% CI, 1.04-1.05; obesity class 3: OR, 2.37; 95% CI, 1.88-3.00) were more likely to experience mood disorders. Conversely, higher income levels (>$80,000: OR, 0.57; 95% CI, 0.49-0.66; $60,000-$79,999: OR, 0.66; 95% CI, 0.56-0.77) and immigrant status (OR, 0.49; 95% CI, 0.43-0.56) were linked to a lower prevalence of mood disorders. Being unmarried was also associated with lower odds of mood disorders. Furthermore, additional factors such as higher education, increased life stress, and smoking were found to significantly influence the prevalence of mood disorders.

Conclusions: The prevalence of mood disorders in Canada is influenced by various factors, with significant gender disparities. These findings can assist policymakers and healthcare professionals in developing targeted interventions and allocating resources effectively to meet the specific needs of at-risk populations. Future research is necessary to address these determinants.
Metabolic pathways from the gut metatranscriptome are associated with COPD and respiratory function in lung cancer patients
Authors: Dora David , Revisnyei Peter , Mihucz Anna , Kiraly Peter , Szklenarik György , Dulka Edit , Galffy Gabriella , Lohinai Zoltan 
Published: November 2024

IntroductionChanges in the human gut microbiome have been linked to various chronic diseases, including chronic obstructive pulmonary disease (COPD). While substantial knowledge is available on the genomic features of fecal communities, little is known about the microbiome’s transcriptional activity. Here, we analyzed the metatranscriptomic (MTR) abundance of MetaCyc pathways, SuperPathways, and protein domain families (PFAM) represented by the gut microbiome in a cohort of non-small cell lung cancer (NSCLC) patients with- or without COPD comorbidity.MethodsFecal samples of 40 NSCLC patients with- or without COPD comorbidity were collected at the time of diagnosis. Data was preprocessed using the Metaphlan3/Humann3 pipeline and BioCyc© to identify metabolic SuperPathways. LEfSe analysis was conducted on Pathway- and PFAM abundance data to determine COPD- and non-COPD-related clusters.ResultsKey genera Streptococcus, Escherichia, Gemella, and Lactobacillus were significantly more active transcriptionally compared to their metagenomic presence. LEfSe analysis identified 11 MetaCyc pathways that were significantly overrepresented in patients with- and without COPD comorbidity. According to Spearman’s rank correlation, Smoking PY showed a significant negative correlation with Glycolysis IV, Purine Ribonucleoside Degradation and Glycogen Biosynthesis I, and a significant positive correlation with Superpathway of Ac-CoA Biosynthesis and Glyoxylate cycle, whereas forced expiratory volume in the first second (FEV1) showed a significant negative correlation with Glycolysis IV and a significant positive correlation with Glycogen Biosynthesis I. Furthermore, COPD patients showed a significantly increased MTR abundance in ~60% of SuperPathways, indicating a universally increased MTR activity in this condition. FEV1 showed a significant correlation with SuperPathways Carbohydrate degradation, Glycan biosynthesis, and Glycolysis. Taxonomic analysis suggested a more prominent MTR activity from multiple Streptococcus species, Enterococcus (E.) faecalis, E. faecium and Escherichia (E.) coli than expected from their metagenomic abundance. Multiple protein domain families (PFAMs) were identified as more associated with COPD, E. faecium, E.coli, and Streptococcus salivarius, contributing the most to these PFAMs.ConclusionMetatranscriptome analysis identified COPD-related subsets of lung cancer with potential therapeutic relevance.
Early coronary angiography in patients with myocardial infarction without ST elevation after out-of-hospital cardiac arrest: a systematic review and meta-analysis
Authors: Ahmed Warda , Ejaz Arooba , Arshad Muhammad Sameer , Mubeen Manahil , Ahmed Aymen , Siddiqui Asad Ali , Tharwani Zoaib Habib , Deepak F. N. U. , Kumar Prince , Shahid Izza , Memon Muhammad Mustafa 
Published: November 2024

BackgroundEarly coronary angiography (CAG) in post-cardiac arrest patients without ST-segment elevation is a topic of debate. This meta-analysis aimed to assess its impact on outcomes.MethodsA search of Medline and Cochrane up to February 2023 was conducted to identify randomized controlled trials and observational studies comparing patients undergoing early CAG vs. delayed/no CAG after experiencing out-of-hospital cardiac arrest. A random-effects model pooled odds ratios (ORs) with 95% confidence intervals (CIs). Meta-regression explored factors modifying effect sizes.ResultsWe identified 16 studies (7 RCTs, 9 observational studies) involving 4,737 patients. Early CAG significantly reduced long-term mortality [OR: 0.66 (0.51–0.85)], and increased favorable cerebral performance category (CPC) 1–2 at discharge [OR: 1.49 (1.09–2.03)]. Observational study subgroup showed decreased short-term mortality, long-term mortality, and CPC 1–2 at discharge, unlike RCT subgroup. Meta-regression revealed type 2 diabetes mellitus and follow-up time influencing short-term mortality and CPC 1–2 at discharge, respectively.ConclusionEarly CAG in post-cardiac arrest patients without ST elevation is associated with long-term clinical benefits, particularly evident in observational studies. Interpretation should be cautious.
Case Report: Restrictive cardiomyopathy due to a rare mutation in troponin I gene (TNNI3) in a patient
Authors: Deng Lili , Luo Liming , Zhang Min , Guo Cheng , Liu Kai 
Published: November 2024

BackgroundRestrictive cardiomyopathy (RCM) is a rare cardiomyopathy often characterized by normal or reduced ventricular chamber volume and bi-atrial enlargement, caused mainly by mutations in the myonodal gene. It has a low incidence, non-specific clinical manifestations, rapid progression, and lack of specific treatment, with heart transplantation usually being the ultimate treatment.Methods and resultsThis case reports a case of a 2-year-2-month-old boy located in Yunnan Province, China, who was admitted to the hospital with a 2-month history of orofacial bruising, aggravated by a 1-week history of bilateral eyelid swelling. After admission, electrocardiogram showed bi-atrial enlargement, echocardiography suggested bi-atrial enlargement with right and left ventricular diastolic hypoplasia, and cardiac magnetic resonance showed bi-atrial dilatation and possible localized myocardial fibrosis. A de novo heterozygous mutation (c.574C &gt; T, p.Arg192Cys) in the TNNI3gene was identified by whole exome sequencing and verified by Sanger sequencing. The patient’s family opted for conservative treatment after diagnosis, but the patient died suddenly 2 months after diagnosis.ConclusionThis study identified a case of RCM due to TNNI3 mutation, emphasizing the importance of cardiac MRI and genetic testing in the clinical diagnosis of RCM and the need for heart transplantation. The study also revealed the possible heterogeneity of TNNI3 mutations across ethnic and geographic backgrounds, suggesting that long-term studies of genetic mutations should be strengthened in the future to promote the development of precision treatment strategies for cardiomyopathy.
Transcatheter intervention of modified Blalock–Taussig shunts in patients with hypoplastic left heart syndrome undergoing stage 1 palliation
Authors: Mini Nathalie , Schneider Martin B. E. , Mikus Marian 
Published: November 2024

BackgroundWhile several studies have explored the outcomes of transcatheter interventions for modified Blalock–Taussig shunts (MBTSs) in a broad range of congenital heart diseases, none have specifically examined the interventions in patients with hypoplastic left heart syndrome (HLHS) who underwent Norwood palliation (NP).MethodsThis retrospective study was conducted between 2020 and 2024, when 24 urgent interventions were performed on 17 patients at our center. We recorded several key outcomes, including early and late intervention-related complications, the need for reintervention, the interval between the NP and the first intervention, shunt patency following the intervention, associated morbidities, and thrombosis-related sudden events. Additionally, during follow-up, we documented the outcomes for patients who underwent the Glenn procedure and those who were palliated, including late death.ResultsThe median age and weight at the time of intervention were 88 days (range: 15–300 days) and 5 kg (range: 2.6–7.6 kg), respectively. The median interval between the Norwood procedure and the transcatheter intervention was 61 days (7–160 days), with median shunt patency lasting 62 days (1–150 days). Notably, there were no intervention-related complications or deaths. In-stent thrombosis, a late complication, occurred in four patients; two of these had impaired anticoagulation, including extracorporeal membrane oxygenation (ECMO)-related causes, while the other two, who were on aspirin, had multiple stents within the shunt, one of whom experienced sudden death. Six patients required seven reinterventions: four due to shunt obstruction or restenosis and two to delay surgery or provide palliation for patients unfit for surgery, aiding in pulmonary development.ConclusionThe transcatheter intervention of the MBTSs in patients with HLHS undergoing NP is considered both safe and potentially life-saving in emergent situations. This approach may facilitate improved pulmonary development, postpone the need for subsequent surgeries, and provide medium-term palliative care for critically ill patients. However, managing late complications such as stent thrombosis remains a significant challenge. Our findings indicate that risk factors for shunt thrombosis include using ECMO therapy, underlying coagulation disorders, impaired lymphatic drainage, requiring multiple stents within the shunt, and a prior history of thrombosis before intervention. Dual antiplatelet therapy is recommended to alleviate the risk of thrombotic events in this population.
Efficient out-of-distribution detection via layer-adaptive scoring and early stopping
Authors: Wang Haoliang , Zhao Chen , Chen Feng 
Published: November 2024

IntroductionMulti-layer aggregation is key to the success of out-of-distribution (OOD) detection in deep neural networks. Moreover, in real-time systems, the efficiency of OOD detection is equally important as its effectiveness.MethodsWe propose a novel early stopping OOD detection framework for deep neural networks. By attaching multiple OOD detectors to the intermediate layers, this framework can detect OODs early to save computational cost. Additionally, through a layer-adaptive scoring function, it can adaptively select the optimal layer for each OOD based on its complexity, thereby improving OOD detection accuracy.ResultsExtensive experiments demonstrate that our proposed framework is robust against OODs of varying complexity. Adopting the early stopping strategy can increase OOD detection efficiency by up to 99.1% while maintaining superior accuracy.DiscussionOODs of varying complexity are better detected at different layers. Leveraging the intrinsic characteristics of inputs encoded in the intermediate latent space is important for achieving high OOD detection accuracy. Our proposed framework, incorporating early stopping, significantly enhances OOD detection efficiency without compromising accuracy, making it practical for real-time applications.
Learning English as a second language with artificial intelligence for prospective teachers: a systematic review
Authors: Peña-Acuña Beatriz , Corga Fernandes Durão Rosana 
Published: November 2024

IntroductionArtificial intelligence is revolutionizing English language teaching with personalized assessments and advanced tools, though more studies are needed on its effectiveness and equitable accessibility.MethodA systematic literature review (SLR) was conducted using articles from Web of Science, Scopus, and ERIC to establish theoretical foundations.ResultsAI in learning English as a second language offers personalized tools such as chatbots, pronunciation improvement apps, and platforms that adapt content according to student progress.DiscussionThe study highlights how AI is revolutionizing English learning by personalizing lessons, improving pronunciation, and promoting cultural understanding.
18F-AlF-NOTA-octreotide PET/CT and 3D printing technology for precision diagnosis and treatment of phosphaturic mesenchymal tumors in patients with tumor-induced osteomalacia: two case reports
Authors: Zhao Gang , Guan Lijuan , Zhang Yongqiang , Shi Xingzhen , Luo Wenming , Yang Maiqing , Wang Qi , Liu Zhen , Liu Yongqiang , Ding Xiaolei , Zhao Jie 
Published: November 2024

ObjectiveThis study aims to report the application of 18F-AlF-NOTA-Octreotide PET/CT and 3D printing technology in the diagnosis and treatment of phosphaturic mesenchymal tumors (PMT) in patients with tumor-induced osteomalacia (TIO).Case presentationA 68-year-old male patient (Case 1) was admitted to the Weifang People’s Hospital in August 2022 with complaints of “persistent pain in the bilateral flank and lumbosacral region”. 18F-AlF-NOTA-Octreotide PET/CT showed high octreotide expression in the left femoral region. A 48-year-old male patient (Case 2) was admitted to the Weifang People’s Hospital in November 2022, complaining of “pain in the lumbar region and ribs”. 18F-AlF-NOTA-Octreotide PET/CT showed high octreotide expression in the pancreatic uncinate process and the left acetabulum. They were diagnosed with hypophosphatemic osteomalacia, with a strong consideration of an underlying neuroendocrine tumor. Preoperative design of 3D virtual surgery, CAD/CAM, and 3D printing technology were used to customize the digital surgical guide plates, and the surgery was carried out. They were both finally confirmed as phosphateuric mesenchymal tumors (PMT) based on postoperative pathology and immunohistochemistry results. Both patients experienced substantial relief from their clinical manifestations after surgery.Conclusion18F-AlF-NOTA-Octreotide PET/CT may be a precise diagnostic method for TIO, while 3D printing technology may serve as an effective and dependable adjunct for the treatment of PMT in patients with TIO.
Interplay between lipid profile and anthropometric measures as indicators of cardiometabolic risk in women with polycystic ovary syndrome
Authors: Jabczyk Marzena , Nowak Justyna , Jagielski Paweł , Hudzik Bartosz , Borszcz Jakub , Zubelewicz-Szkodzińska Barbara 
Published: November 2024

ObjectivesPolycystic ovary syndrome (PCOS) is a complex endocrine disorder that often coexists with cardiometabolic risk factors. Women with PCOS have a two-fold increased risk of developing type 2 diabetes and substantially elevated risk for cardiovascular disease (CVD) events later in life. PCOS patients may require more comprehensive metabolic screening to identify populations at higher risk of developing CVD and dyslipidemia. It is recommended to evaluate lipid profile, glucose tolerance and of women with PCOS every 2-3 years. Simple, short, and easy methods for the assessment of CVD risk in women with PCOS may be useful tools for implementing CVD prevention strategies by doctors or nutritionists. The aim of this study was to investigate the usefulness of anthropometric indices in the assessment of cardiometabolic risk based on lipid profile in patients with PCOS.Material and methodsThe study involved 49 of Caucasian women aged 18-39 who were diagnosed with PCOS based on the Rotterdam criteria and divided into two groups with normal lipid profile (N=14) and dyslipidemia (N=35). Biochemical parameters were tested in the morning while fasting. Anthropometric parameters such as Body Mass Index (BMI), Body Adiposity Index (BAI), Waist-to-Hip Ratio (WHR), and Waist-to-Height Ratio (WHtR) were calculated, while the Percent of Body Fat was measured using a body analyzer.ResultsThe study demonstrated that women with dyslipidemia were older than the control group, 33 years (27-37) vs 24 years (21-26), p&lt;0.01. Neither BMI nor BAI (%) correlated with total cholesterol (p=0.63 and p=0.27). Other lipid parameters, such as serum HDL cholesterol (R=-0.68, p&lt;0.01; R=-0.58, p&lt;0.01), LDL cholesterol (R=0.34, p=0.02; R=0.37, p=0.01), non-HDL cholesterol (R=0.40, p&lt;0.01; R=0.42, p&lt;0.01), and triglycerides (R=0.56, p&lt;0.01; R=0.51, p&lt;0.01) correlated with BMI and BAI (%). ROC analysis demonstrated a high predictive value for age in identifying dyslipidemia. ROC analysis demonstrated poor predictive value for BMI, BAI, WHR, WHtR in identifying dyslipidemia.ConclusionsAnalysis of simple and rapid parameters used to assess body fat, such as BMI, BAI, WHR, and WHtR, has shown that they are poor predictors of dyslipidemia in women with PCOS. In young women with PCOS, age appears to be a more reliable predictor of dyslipidemia.