bluuebunny/crossref_metadata_2025_split huggingface dataset:
Leveraging Machine Learning Algorithms for Early Detection and Prognosis of Pediatric Autoimmune Diseases A Comprehensive Data-Driven Approach
Authors: Long Gao , Li Linqiao 
Published: November 2024

Abstract

The early detection and prognosis of pediatric autoimmune diseases are crucial for improving clinical outcomes and patient quality of life. Traditional diagnostic methods often fall short due to the complexity and variability of autoimmune responses in children. This study explores the application of machine learning algorithms in the early detection and prognosis of pediatric autoimmune diseases, leveraging a comprehensive data-driven approach. By integrating various machine learning techniques, including Support Vector Machines (SVM), Random Forests, and Neural Networks, we aim to develop models that can accurately identify early signs of autoimmune diseases and predict their progression. Data for this study were collected from multiple healthcare databases, encompassing a wide range of clinical parameters, patient histories, and biomarker profiles. Preprocessing steps involved data cleaning, normalization, and handling missing values to ensure the robustness of the models. The performance of the machine learning models was evaluated using metrics such as accuracy, precision, recall, and F1-score, with cross-validation techniques employed to validate the results. Our findings demonstrate that machine learning algorithms significantly outperform traditional diagnostic methods in both sensitivity and specificity. The Random Forest algorithm, in particular, showed the highest accuracy in detecting early signs of pediatric autoimmune diseases. Additionally, the models developed provide valuable prognostic insights, aiding healthcare providers in making informed decisions about patient management and treatment plans. The study highlights the potential of machine learning to revolutionize the diagnosis and management of pediatric autoimmune diseases, offering a promising tool for clinicians to enhance early detection and improve patient outcomes. Future research should focus on refining these models and integrating them into clinical practice to fully realize their benefits.
Influence of Fractal Fabric on the Shear Characteristics of Large-Scale Accumulation Bodies
Authors: Huang Yidan , Chen Wentai 
Published: November 2024

Abstract

Large-scale accumulation bodies composed of loose materials are among the theoretical and practical topics of greatest interest to engineers and scientists. Although accumulation bodies have been widely studied across multiple academic disciplines, the impact of particle materials on mechanical properties remains insufficiently explored. The motivation for this study is to investigate the relationship between the fabric characteristics of large-scale accumulation bodies and their shear mechanical properties, field investigations were conducted to obtain particle size distribution characteristics, which led to determining the fractal dimension D as a descriptor of the fabric. For samples with different fractal dimensions, we conducted large direct shear tests and MatDEM numerical simulations. The topological characteristics of the particle contact network during shear were then analysed using a complex network method. The results revealed that the accumulation bodies’ shear strength obtained from both the physical and numerical experiments first increased but then decreased with increasing fractal dimension, following a normal distribution with a mean value of 2.5 and an amplification factor that is proportional to the vertical load. The analysis of complex network parameters also has consistent patterns. On the basis of these experimental results, this study investigates the shear mechanical properties of accumulation bodies from both macroscopic and microscopic perspectives, providing deeper insights into the link between macroscopic responses and the mesoscale structure of force chains, explaining the mechanism by which fractal dimensions affect their shear characteristics and providing new evaluation methods for the utilization and stability assessment of large-scale accumulation materials.
A novel, low-cost clay ceramic membrane for the separation of oil-water emulsions
Authors: Almasri Dema , Manawi Yehia , Makki Suhde , Tasneem Nafia , Simson Simjo , Abdel-Hadi Iman , Agcaoili John , Lawler Jenny , Kochkodan Viktor 
Published: November 2024

Abstract

The development of a facile and efficient method for the fabrication of ceramic membranes fills a vital gap in the ceramic membrane manufacture research field. Ceramic membranes are relatively high in cost due to the cost of raw materials (metal oxides) as well as the energy required during the sintering stage of the fabrication process. In this study, a ceramic membrane made of low-cost halloysite nanotubular (HNT) clay is fabricated through a die press process and sintered at temperatures notably lower than those required of raw materials in commercial membranes. The features of the membrane were evaluated in terms of chemical properties, surface characteristics, hydrophilicity, durability, oil rejection performance, and antifouling properties. The pore size, porosity, and water permeability corresponding to the optimum membrane composition: halloysite: Al2O3: starch as 60:25:15 wt.% were found to be 230 nm, 62.4%, and 1040 LMH/bar, respectively. The membrane demonstrated to be superhydrophilic in air and superoleophobic underwater. The performance tests were conducted with oil emulsions. Oil-water rejection tests were conducted at different concentrations of oil-in-water emulsions (724 and 1014 mg/L) and oil rejection was observed to reach more than 99%. The flux recovery ratio (FRR) of the membrane in the first filtration cycle when treating the lower oil concentration emulsion was 54% greater than the FRR corresponding to the higher oil concentration emulsion. However, in the next filtration cycle, the FRR of the ceramic membrane was 30% greater for the higher oil concentration emulsion which could be attributed to the formation of an oil film, preventing further oil particle penetration in the membrane matrix. The testing with real produced water from gas extraction indicated that the novel HNTs-based ceramic membrane performed well in feed solutions with high total dissolved solids content and can be used for produced water pretreatment before reverse osmosis membranes if the produced water to be desalted. The results from this work show that the developed ceramic membrane is a promising, low-cost alternative to the ones existing in the current market for oily wastewater treatment.
Intrahost dynamics, together with genetic and phenotypic traits predict the success of viral mutations
Authors: Tan Cedric , Escalera-Zamudio Marina , Yavlinksy Alexei , Dorp Lucy van , Balloux Francois 
Published: November 2024

Abstract

Predicting the fitness of mutations in the evolution of pathogens is a long-standing and important, yet largely unsolved problem. In this study, we used SARS-CoV-2 as a model system to explore whether the intrahost diversity of viral infections could provide clues on the relative fitness of single amino acid variants (SAVs). To do so, we analysed ~15 million complete genomes and nearly ~8000 sequencing libraries generated from SARS-CoV-2 infections, which were collected at various timepoints during the COVID-19 pandemic. Across timepoints, we found that many successful SAVs were detected in the intrahost diversity of samples collected prior, with a median of 6-40 months between the initial collection dates of samples and the highest frequency seen for these SAVs. Additionally, we found that the co-occurrence of intrahost SAVs significantly captures genetic linkage patterns observed at the interhost level (Pearson’s r=0.28-0.45, all p<0.0001). Further, we show that machine learning models can learn highly generalisable intrahost, physiochemical and phenotypic patterns to forecast the future fitness of intrahost SAVs (r2=0.48-0.63). Most of these models performed significantly better when considering genetic linkage (r2=0.53-0.68). Overall, our results document the evolutionary forces shaping the fitness of mutations, which may offer potential to forecast the emergence of future variants and ultimately inform the design of vaccine targets.
Spatial and Single-Cell Analyses Reveal the Pro-Invasiveness Role of NUAK1 in Breast Cancer through EMT Regulation
Authors: Wang Jiani , Yang Jiumei , Li Cuicui , Qiu Dongbo , Zhang Baoyu , Zhang Peng 
Published: November 2024

Abstract

Objective
Breast carcinoma is a leading malignancy in women, and the role of Novel (nua) kinase family 1 (NUAK1) in its progression is not well-defined. This study aimed to investigate the biological significance of NUAK1 in breast cancer and its potential as a prognostic marker.
Methods
We assessed the expression levels of NUAK1 in breast cancer tissues and cell lines using RT-qPCR and cultured cell assays. Statistical analysis was conducted to correlate NUAK1 expression levels with clinicopathological features. Survival analysis was performed to determine the prognostic value of NUAK1 in breast cancer. Additionally, Transwell invasion assays and the evaluation of EMT (epithelial-mesenchymal transition)-related proteins were conducted to ascertain the impact of NUAK1 on cellular invasion and EMT. Furthermore, spatial transcriptomic analysis utilizing the CROST dataset and single-cell RNA sequencing data were employed to dissect the expression patterns of NUAK1 and its association with the TME
Results
NUAK1 was found to be upregulated in breast cancer tissues and cell lines compared to non-cancerous controls. High expression of NUAK1 was significantly associated with poorer patient survival and was an independent prognostic factor. Transwell assays demonstrated that NUAK1 overexpression significantly enhanced cellular invasion. Overexpression of NUAK1 also induced EMT, as evidenced by decreased expression of epithelial markers and increased expression of the mesenchymal marker Vimentin. Single-cell analysis across various datasets highlighted NUAK1's expression in endothelial cells and its correlation with the TNM stage. Spatial transcriptomic analysis revealed that NUAK1 expression, particularly in B-Nai cells, was associated with a distinct immune cell landscape and communication patterns within the TME, influencing TGFβ and WNT signaling pathways.
Conclusions
Our findings indicate that NUAK1 is upregulated in breast cancer and serves as an independent prognostic marker. NUAK1 promotes breast cancer cell invasion through the induction of EMT and is implicated in the modulation of the TME. The single-cell analysis and spatial transcriptomic data provide novel insights into the cellular and molecular mechanisms underlying NUAK1's role in breast carcinogenesis, suggesting its potential as a therapeutic target.
Efficacy and safety of targeted immune drugs conversion microwave ablation in the treatment of hepatocellular carcinoma: a retrospective cohort study
Authors: Dai Hongyuan , Lu Ying , Yu Hongli , Zhang Tianlan , Lei Jin , Zhang Linzhi , Hao Qiuyao , Dong Zheng , Lu Yinying 
Published: November 2024

Abstract

Objective
To evaluate the effectiveness and safety of target-immune drug-converted microwave ablation (MWA) companred to MWA alone for treating hepatocellular carcinoma (HCC).
Methods
Retrospectively analyzed the clinical data of 257 patients with hepatocellular carcinoma (HCC) who received either targeted immune drug conversion with microwave ablation (Drug + MWA) or microwave ablation alone (MWA) from January 2022 to March 2023, employing the propensity score matching (PSM) method to mitigate the impact of potential confounding factors. The incidence of perioperative complications was compared between the two groups, and univariate as well as multivariate logistic regression analyses were performed to evaluate these complications. Additionally, Kaplan-Meier curves were utilized to evaluate the tumor control effect between the two groups.
Results
Drug + MWA group and MWA group included 60 patients respectively. The rates of perioperative complications were similar between the two groups (all p > 0.05). Multivariate logistic regression analysis indicated that age and tumor size were positively correlated with the occurrence of perioperative complications associated with MWA (p < 0.05). The most common complications included fever, secondary infection, and electrolyte imbalance, with independent risk factors identified as tumor size, serum albumin, and gender, respectively. Compared to the MWA group, the Drug + MWA group exhibited significantly reduced 1-year intrahepatic tumor progression (1.7% vs. 13.3%, p = 0.015) and local tumor progression rates (1.7% vs. 11.7%, p = 0.028) compared to the MWA group.
Conclusions
Compared with MMW therapy alone, target-immune drug conversion into MWA does not increase the risk of perioperative complications, and has better control over intrahepatic and local tumor progression.
Final-year undergraduate nursing and medical students’ knowledge and perception of, orientation and perceived self-efficacy to provide palliative and end- of-life care. Qualitative findings from a parallel mixed methods study
Authors: Natuhwera Germanus , Ellis Peter , Namisango Eve 
Published: November 2024

Abstract

Introduction: About a decade after the introduction of palliative care teaching for undergraduate nurses and medical students in Uganda, it is unclear to what extent the course impacts students’ understanding and view of and orientates trainees to deliver palliative care end-of-life care.
Aims: To: (1) explore final-year nursing and medical students’ knowledge and perceptions of palliative and end-of-life care, (2) examine students’ orientation and perceived self-efficacy to provide palliative and end-of-life-care.
Design: A multicentre descriptive qualitative study.
Setting/participants: 82 undergraduate nursing and medical students were selected from seven medical and nursing schools in Uganda. Data were collected through 10 face-to-face focus group discussions using an interview guide and analysed using inductive thematic analysis.
Results: Five master themes emerged-: (1) palliative care as a concept with multiple meanings, (2) Misinformation about palliative care, opiates and pain management, (3) Students’ experiences of the course, (4) Dilemmas in knowledge and action, and (5) Palliative and end-of-life care as emotional labour.
Conclusion: Participants generally had inadequate and varied understanding of, and very few demonstrated low willingness and limited confidence to provide, palliative and end-of-life care. They blamed this mainly on the huge emotional labour of palliative/end-of-life care and inadequate teaching and/or limited clinical exposure.
Exploring the Interplay Between Physical Activity, Dietary Patterns, Diabetes, and All-Cause Mortality in the U.S.A. Population, NHANES 2011-2014: A Distributional Data Analysis Perspective.
Authors: Matabuena Marcos , Carreira Anxo , Wagner Robert , Sousa Miguel , Saavedra Miguel , Ghosal Rahul , Onnela JP , Bohn Lucimere 
Published: November 2024

Abstract

Objective: This study investigates the impact of physical activity, measured by accelerometer technology, on the prevalence of type 2 diabetes and related adverse events among U.S.A. adults. Additionally, it examines patient survival in older adults within this cohort.
Methods: The research analyzed a cohort of 5,011 adults from the 2011–2014 National Health and Nutrition Examination Survey (NHANES). Participants' physical activity was assessed using wrist-worn accelerometers, with data analyzed through a novel cluster analysis based on distributional representations to identify digital physical activity phenotypes. Statistical associations between these phenotypes, diabetes prevalence, and all-cause mortality were evaluated using logistic regression and Cox models, adjusting for survey weights and confounding factors such as sex, age, and ethnicity. NHANES data were linked to the National Death Index to perform Cox-survival analysis.
Results: Four physical activity phenotypes were found, highlighting variability in diabetes susceptibility. Phenotype 1, associated with the lowest diabetes prevalence, exhibited the highest levels of moderate to vigorous physical activity (MVPA), averaging 504 minutes weekly—5% of the time. Other phenotypes, characterized by less MVPA (1-3% of the time), showed a 57%-114% higher risk of diabetes compared to phenotype 1. Survival analysis demonstrated association with longer survival between physical activity levels and glucose values, with higher levels of MVPA and lower glucose showing a statistical association with longer survival.
Conclusions: Sedentary behavior significantly increases diabetes risk, particularly in older adults. Higher sedentary behavior, coupled with inadequate proportion of MVPA intensity time, heightens mortality risk, especially when combined with elevated baseline glucose levels.
Increased melanin induces aberrant keratinocyte−melanocyte−basal−fibroblast cell communication and fibrogenesis by inducing iron overload and ferroptosis resistance in keloids
Authors: Shi Xiangguang , Xia Xueyi , Xiao Yang , Zhang Ying , Gong Yiyi , Chen Yahui , Shi Chenyi , Wang Wei , Shi Mengkun , Liu Jianlan , Huang Jia , Liu Mengguo , Wang Jiucun , Wu Wenyu 
Published: November 2024

Abstract

Keloid is a typical skin fibrotic disease with unclear mechanisms and limited therapeutic options. In this study, we found the enriched skin pigmentation-related pathways in the melanocytes of keloid by single-cell RNA-sequence (scRNA-seq) analysis. We further validated increased melanin levels in keloid patients. Additionally, melanin positively correlated with the Keloid Area and Severity Index in keloid. Furthermore, melanocyte-secreted melanin significantly promoted fibroblast proliferation, migration, and collagen synthesis. Mechanically, melanin increased basal cell permeability and inflammation to facilitate its transfer to the dermis, where it further activated fibroblasts by evoking iron overload and ferroptosis resistance. Consistently, iron overload and ferroptosis resistance were validated in primary fibroblasts and skin tissues of keloid patients. Inhibition of iron overload and ferroptosis resistance effectively diminish melanin-induced fibrogenesis. Interestingly, melanin induced iron overload and ferroptosis resistance in melanocytes in an autocrine manner and further stimulated keratinocytes to take up melanin to deepen skin color by upregulating the F2R-like trypsin receptor 1 (F2RL1). In vivo, the delivery of ML329, a micropthalmia-associated transcription factor (MITF) inhibitor, could suppress melanogenesis and alleviate keloid in human keloid-bearing nude mice. Meanwhile, ML329 decreased the iron content and restored the sensitivities of ferroptosis. Collectively, melanin-lowing strategies may appear as a potential new therapeutic target for keloid.
A Case of Digital Vasculitis in Anti-Synthetase Syndrome (Anti-OJ Subtype)
Authors: Ak Deniz , Stratton Richard J. 
Published: November 2024

Abstract

Anti-synthetase syndrome is a rare autoimmune disorder characterised by the presence of autoantibodies against aminoacyl transfer RNA synthetases. We report a unique case of a 54-year-old woman with anti-OJ anti-synthetase syndrome, characterised by the atypical occurrence of digital vasculitis in conjunction with the classic manifestations of anti-synthetase syndrome. Our patient presented with digital vasculitis affecting the right third and fourth fingers, rapidly evolving interstitial lung disease of the organising pneumonia subtype, sub-clinical myositis, arthritis and mechanic's hands. Notably, she had no prior history of Raynaud's phenomenon. Serological tests revealed positive anti-OJ antibodies and weakly positive anti-MI2 antibodies. Our patient's condition was managed with intravenous methylprednisolone then after stepped down to prednisolone and mycophenolate mofetil. Current literature primarily highlights Raynaud's phenomenon and vasculopathy-related ischemia, whether occlusive or non-occlusive in anti-synthetase syndrome. This case study identifies digital vasculitis as a distinctive complication of anti-synthetase syndrome, anti-OJ subtype. It emphasises the importance of recognising vascular complications, including vasculitis, even when classic signs like Raynaud's phenomenon are absent. Further research is crucial to fully understand the range of vascular manifestations associated with anti-synthetase syndrome.
MLKD-CLIP：Multi-layer Feature Knowledge Distillation of CLIP for Open-Vocabulary Action Recognition
Authors: Wang Jingjing , Ye Junyong , Liu Xinyuan , Li Youwei , Xu Guangyi , Zheng Chaoming 
Published: November 2024

Abstract

Open-vocabulary action recognition aims to identify unseen action categories during training, which is crucial for enabling models to address diverse action scenarios and enhancing their generalizability and adaptability to dynamic environments. Large-scale vision-language pre-trained models (such as CLIP) excel in zero-shot image tasks due to their strong generalizability. However, their lack of temporal information hampers direct application to video tasks. Many studies have fine-tuned CLIP on video datasets, but video datasets are much smaller than the pre-training datasets, potentially leading to reduced generalizability and challenges in recognizing unseen actions. To this end, we propose MLKD-CLIP, which uses the frozen CLIP as the teacher and the fine-tuned CLIP as the student to perform multi-layer feature knowledge distillation. Firstly, we introduce a feature fusion module that employs self-attention to merge features from different layers and incorporates a temporal convolution module, enabling the model to maintain the learning of temporal capabilities during the distillation process. Next, we perform layer-wise fusion to combine the multi-layer features of both the teacher and student models, allowing the model to balance their significance in the distillation process. Finally, we distill the fused features, enabling the student model to learn the multi-level features of the teacher model while considering both global representations and local details. Additionally, the classification tasks on video datasets enhance the student model to learn video features. We evaluated the open-vocabulary action recognition capability of MLKD-CLIP on the UCF101, HMDB51, and SSv2 datasets, achieving the best top-1 accuracy compared to popular methods.