bluuebunny/crossref_metadata_2025_split huggingface dataset:
Identification of a Candidate Risk Model Based on Cancer- Associated Fibroblasts-Related Gene Signature Predicting the Prognosis in Hepatocellular Carcinoma
Authors: Dai Bin , Wang Wei , Li Yanan , Zhou Chen , Ran Jun , Shang Runze , Xia Hui 
Published: December 2024

Abstract

Background
Cancer-associated fibroblasts (CAFs) play vital roles in HCC initiation and progression via multicellular, stromal-dependent manners. Despite their acknowledged significance, the comprehensive role of CAFs-related gene signatures in HCC and their prognostic implications remain underexplored. Here, we constructed a prognostic signature based on CAFs-related differentially expressed genes in HCC.
Methods
We conducted a comprehensive analysis using RNA sequencing data from the TCGA database and a validation cohort from the ICGC database. Differential gene expression analysis identified CAF-related genes associated with HCC prognosis. A gene signature was developed using LASSO and Cox regression analyses, and its prognostic value was evaluated through Kaplan-Meier (K-M) survival analyses and receiver operating characteristic curve (ROC) analysis. The signature's association with immune cell infiltration, chemotherapeutic response, and functional enrichment was also investigated.
Results
In total 256 differentially expressed CAFs-related genes were identified between CAFs high and low samples. After systematic analysis, a prognostic signature including 23 genes (MYH11, RAMP3, RCAN2, CLEC3B, KLF2, HTRA3, VCAN, MARVELD1, PRSS23, IL7R, IL33, MSC, SERPINE2, CRYAB, SPINT1, HGFAC, IGLL5, SLC22A1, CTAG2, CXCL8, ADH1C, PEG10, AKR1B10) were constructed. The K-M and ROC analysis demonstrated the robust predictive potential of our risk model for HCC patients. The univariate/multivariate Cox regression analyses furtherly confirmed the risk model was an independent prognostic factor of HCC in both testing and validation cohort. Moreover, the response to chemotherapy and the stromal score were differed significantly between the high- and low-risk groups. Finally, the signaling pathways enriched in high-risk group are mainly associated with HCC progression.
Conclusions
CAFs-related gene signature model shows good predictive potential with respect to prognosis of HCC patients.
Impact of lung-resident Mesenchymal Stem Cells on Epithelial Wound Healing in Idiopathic Pulmonary Fibrosis
Authors: Martin-Medina Aina , Truyols-Vives Joan , Jahn Andreas , Rio Carlos , Montes Ana , Molina-Molina Maria , Elowson Linda , Westergren-Thorsson Gunilla , Mercader-Barceló Josep , Sala-Llinàs Ernest 
Published: December 2024

Abstract

Aberrant repair processes in lung alveolar epithelial cells (AEC) are hallmarks of the initiation and progression of idiopathic pulmonary fibrosis (IPF), a lethal interstitial lung disease with very limited therapeutic options and no current means to reverse or improve lung function. Lung-resident mesenchymal stem cells (LRMSC) are expected to repair and regenerate tissue; however, they have recently been reported to be altered in IPF, thereby promoting disease pathogenesis. Although IPF LRMSC closely interact with alveolar epithelial cells (AEC), the involvement of IPF LRMSC in restoring the epithelial lung barrier has not been studied in detail. Here, we compared the proliferation capacity of LRMSC from IPF patients and control subjects via molecular and functional assays and investigated the induction of in vitro epithelial wound closure in both direct and indirect cell cocultures. All setups were tested under normal and profibrotic conditions upon stimulation of LRMSC with TGF-β. IPF LRMSC were less proliferative than controls under profibrotic conditions. LRMSC enhanced wound closure in direct coculture with AEC, however, the ability of LRMSC to regenerate scratched AEC monolayers through only their secreted factors was reduced in IPF donors. Moreover, profibrotic stimulation of LRMSC with TGF-β further potentiated AEC wound closure, but this effect was delayed in IPF donors compared with controls. This study demonstrated that LRMSC mediate epithelial wound closure under fibrotic conditions; however, their potential is impaired in IPF LRMSC, especially in terms of their paracrine function.
Recurrent Headaches in a Child with Tuberculous Meningitis: Unmasking Slit Ventricle Syndrome
Authors: Li Yiyuan , Zhu YU , Guo Qin 
Published: December 2024

Abstract

Background
Slit ventricle syndrome (SVS) is a severe and potentially life-threatening complication associated with chronic overdrainage of cerebrospinal fluid. However, its clinical manifestations and imaging characteristics are often overlooked due to insufficient awareness among clinicians..
Case Presentation
We report the case of a pediatric patient diagnosed with tuberculous meningitis, who received standard anti-tuberculosis treatment and underwent ventriculoperitoneal shunting for hydrocephalus. Four years after completing treatment, the patient presented with recurrent headaches, which were eventually diagnosed as SVS. The patient's condition improved following an upward adjustment of the shunt valve pressure.
Conclusion
This case highlights the critical need for heightened awareness of SVS among pediatric specialists. Early recognition and timely intervention are crucial for optimizing clinical outcomes in patients with a history of shunt surgery and hydrocephalus.
Extensor Mechanism Injuries after Primary Total Knee Arthroplasty
Authors: Jajou Lawrence , Golasa Brian , McCall Daniel 
Published: December 2024

Abstract

Background: Extensor mechanism injuries after total knee arthroplasty (TKA) continue to be a difficult complication to treat and can be associated with devastating outcomes. This study attempts to review the prevalence, treatment types, and outcomes of extensor mechanism injuries after total knee arthroplasty within a cohort of patients.
Methods: Using a clinical research database, a retrospective cohort study was performed via chart review of patients who underwent a total knee arthroplasty over the course of 7 years from 7 hospitals within the same hospital system. The charts were then screened for subsequent operative repair of the ipsilateral extensor mechanism at a later date. Patient characteristics, implants, type of extensor mechanism injury, fixation type, subsequent surgeries were evaluated.
Results: Of the 6064 total knee arthroplasties, 104 patients with 105 (1.73%) knees went on to have extensor mechanism injuries. Quadriceps tendon injuries were the most common, followed by patellar tendon, and then patella fractures. Median time to injury was 70 days. Patients requiring additional surgery beyond initial repair of extensor mechanism injury was 47.6% (50/105). Additionally, 33% (35/105) went on to have revision of component(s) and 17.1% (18-105) received treatment for prosthetic joint infection.
Conclusions: While overall rare, extensor mechanism injuries after total knee arthroplasty can pose serious complications beyond initial repair, including need for additional surgery, infection, revision, and even amputation. Careful consideration should be taken by the treating surgeon when faced with these injuries to avoid further complications.
A novel KRAS Exon 2 drop-off Digital PCR Assay for Mutation Detection in Cell- free DNA of Cancer Patients
Authors: Nard Bianca Addamo-De , Geissmann Meret , Akhoundova Dilara , Pistoni Clelia , Brezina Tomas , Zoche Martin , Weber Achim , Hussung Saskia , Fritsch Ralph 
Published: December 2024

Abstract

Background: KRAS exon 2 mutations are highly prevalent in human malignancies, making them attractive targets for detection and monitoring in cell-free DNA (cfDNA) of cancer patients. Drop-off assays designed for digital polymerase chain reaction (ddPCR drop-off) span entire mutational hotspots and detect any mutated allele within the covered region, overcoming a major limitation of mutation-specific ddPCR assays. We therefore set out to develop a novel KRAS codon 12/13 ddPCR drop-off assay for the robust, highly sensitive and specific detection of KRAS exon 2 hotspot mutations in cfDNA.
Methods: We designed, optimized and extensively validated a KRAS codon 12/13 ddPCR drop-off ssay. We compared assay performance to a commercially available KRAS multiplex assay. For clinical validation, we analyzed plasma samples collected from patients with KRAS-mutated gastrointestinal malignancies.
Results: Limit of detection of the newly established ddPCR drop-off assay was 0.57 copies/µL, limit of blank was 0.13 copies/µ. The inter-assay precision (r2) was 0.9096. Our newly developed KRAS ddPCR drop-off assay accurately identified single nucleotide variants in 35/36 (97.2%) of circulating tumor-positive samples from the patient validation cohort. Assay cross-validation showed that the newly established KRAS codon 12/13 ddPCR drop-off assay outperformed a commercially available KRAS multiplex ddPCR assay in terms of specificity . Moreover, the newly developed assay proved to be suitable for multiplexing with mutation-specific probes.
Conclusion: We developed and clinically validated a highly accurate ddPCR drop-off assay for KRAS exon 2 hot-spot detection in cfDNA with broad applicability for clinic and research.
An Intelligent CDS (Clinical Decision Support) Framework using Machine Learning Algorithms for Parkinson Disease Detection
Authors: Mukherjee Rajendrani , Dwivedi Rahul , Jana Nanda Dulal , Chatterjee Rajdeep , Ghosh Subhayu , Dey Ankika , NA Draksha , Lemos Bernardo , Mallik Saurav , Shah Mohd Asif 
Published: December 2024

Abstract

Parkinson’s disease is a progressive neurodegenerative disorder characterized by the gradual onset of symptoms, complicating early diagnosis. Traditionally, neurologists diagnose Parkinson’s through patient medical history reviews and repeated scans, while body movement analysts focus on evaluating physical movements. Recent studies suggest that speech alterations can serve as quantifiable markers for early Parkinson’s detection. This paper introduces a novel and robust framework that leverages the Multiple Feature Evaluation Approach (MFEA), the Synthetic Minority Oversampling Technique (SMOTE), and Neural Networks for the early detection of Parkinson’s disease. A new algorithm, termed Multi-Agent MFEA, is proposed within this framework, which is further developed into an intelligent system called iCDS (Intelligent Clinical Decision Support). The effectiveness of this system is validated using a speech dataset from the UCI Machine Learning Repository. Comparative analysis shows that the iCDS framework, equipped with MFEA, outperforms traditional feature selection methods (such as Mutual Information Gain and Recursive Feature Elimination) and classifiers (including Naive Bayes, KNN, and SVM) in multiple aspects. The study’s findings have the potential to aid both patients and medical professionals in making timely decisions and improving medical support. The development of Clinical Decision Support (CDS) systems has made early detection of Parkinson’s disease more feasible, and this research substantiates that advancement.
Prevalence and Distribution of Respiratory Pathogens in Paediatric Acute Respiratory Infections After the Cessation of Strict Non-Pharmaceutical Interventions in Putian, China.
Authors: Zhu Jinwei , Wu Suqing , Chen Yan , Zheng Liping 
Published: December 2024

Abstract

Background
Acute respiratory infections (ARIs) are a significant cause of morbidity in children. This study aimed to investigate the prevalence and distribution of respiratory pathogens in paediatric ARIs in Putian, China, following the cessation of strict non-pharmaceutical interventions (NPIs).
Methods
A total of 3,790 paediatric patients with suspected ARIs were included in the study. Nasopharyngeal swabs were collected and analyzed using RT-PCR to identify 13 common respiratory tract pathogens. Statistical analyses were performed to examine the distribution of pathogens among patients stratified by sex, age, and season.
Results
The overall pathogen positivity rate was 78.9%. No significant difference in detection rates was observed between males (79.7%) and females (77.9%). The highest positivity rate was found in the school-age group, with elevated rates noted during autumn and winter. Among the positive cases, 81.9% had a single pathogen, with Mycoplasma pneumoniae (Mp) being the most common (33.6%), followed by Human rhinovirus (HRV) and Human respiratory syncytial virus (HRSV). Age-dependent distribution indicated that Influenza A (InfA) was more prevalent in preschool and school-age children, whereas HRSV was most prevalent in infants. Temporal distribution showed that InfA peaked in spring, while Mp, Human metapneumovirus (HMPV), and Human adenovirus (HADV) were most common in winter. Co-infections were more frequent in autumn and winter, with the HRV + Mp co-infection being the most prevalent pattern.
Conclusion
The prevalence of respiratory pathogens in children with ARI has returned to pre-COVID-19 pandemic levels following the discontinuation of stringent NPIs. Additionally, the epidemiology of certain pathogens has shifted from traditional patterns. These findings underscore the dynamic nature of respiratory pathogen distribution and highlight the necessity for ongoing surveillance to inform effective treatment and prevention strategies for ARIs in children.
The role of left atrio-ventricular coupling index and left atrial ejection fraction in predicting onset of atrial fibrillation and adverse cardiac events in hypertrophic cardiomyopathy
Authors: Parisi Francesca , Franca Eluisa La , Pistelli Lorenzo , Gentile Giovanni , Bellavia Diego , Nuzzi Vincenzo , Manca Paolo , Mulè Massimiliano , Zito Concetta , Bella Gianluca Di , Carerj Scipione , Cipriani Manlio , Faletra Francesco F. 
Published: December 2024

Abstract

Background
In recent years, several indexes have been proposed to predict atrial fibrillation (AF) in hypertrophic cardiomyopathy (HCM) patients, but with limited accuracy. This study aims to assess the role of new echocardiographic parameters in predicting AF onset. Additionally, the relationship of these parameters with major adverse cardiovascular outcomes (cardiovascular death and heart transplant) has been also investigated.
Methods
Clinical and imaging data from 141 patients with HCM and without history of AF have been retrospectively analyzed over 5 years period. Patients who developed AF during the study were compared to those who did not. Main parameters analyzed included end-diastolic left atrial volume (LAVmin), end-systolic volume (LAVmax), left atrial ejection fraction (LAEF), left atrioventricular coupling index (LACI), and left atrial diameter (LAD). The standardization of echocardiographic measurements has been assessed using cardiac magnetic resonance (CMR) as a reference.
Results
Thirty-five patients developed AF at mean time of 4 years from the baseline evaluation. HCM-AF group had significantly higher values of LACI, LAD, and LAVmin. A LACI > 43% on echocardiography, and LACI > 44% on CMR showed the best performance in identifying patients who would develop AF. In a multivariate analysis, an echocardiographic LAEF < 43% was independently associated with the occurences of AF (OR 4.5, 95% CI 1.4–13.7). Eleven patients met the composite outcome of cardiovascular death or heart transplant; and a LACI > 60% was associated with this outcome.
Conclusion
In HCM patients, both LACI and LAEF were significantly associated with the occurrence of AF over a 4 years period, demonstrating higher sensitivity and specificity compared to other tools. LACI > 60% showed to be associated with the occurrence of cardiovascular death or heart transplant in HCM patients.
Risk of falls in patients with arthritis: results from the China Health and Retirement Longitudinal Study (CHARLS)
Authors: Zhong zhongci , Chen Jiayi , Hua Chenfeng , Hu Xinlan , Qiu Xiaoqiao , Che Yizhang , Sun Shanghui , Zhan Ling , Bi yin , Zheng Chenxiao , Dong Lijuan 
Published: December 2024

Abstract

Background
Arthritis is a common chronic disease often accompanied by pain and activity limitation, which significantly affects the quality of life of older adults and may increase the risk of falls. This study aimed to clarify the association between arthritis and fall risk and its influencing factors.
Methods
Data from the China Health and Retirement Longitudinal Study (CHARLS) were compared between participants with and without arthritis. The effect of arthritis on the incidence of falls was assessed by propensity score matching (PSM) method, adjusting for potential confounders, and using multiple statistical models (e.g., multivariate logistic regression and inverse probability weighting model) to calculate the odds ratio (OR) for falls and its 95% confidence interval (95% CI).
Results
A total of 9553 subjects were included, and the overall incidence of falls was 40.7%. The China Health and Retirement Longitudinal Study (CHARLS) data China Health and Retirement Longitudinal Study (CHARLS) data rate for patients with arthritis was 25.6%, whereas the incidence of falls in patients without arthritis was 22.0%. Multivariate analysis showed that the ratio of falls in arthritis patients was 0.90 (95% CI: 0.82 to 0.99, P = 0.042). Subgroup and sensitivity analyses showed that the results were stable and reliable.
Conclusions
This study confirms the significance of fall risk in patients with arthritis and suggests the development of fall prevention strategies for patients with arthritis to improve their health outcomes.
The Impact of the Inflation Reduction Act on Investment in Innovative Medicines: A Project- Level Analysis
Authors: Xie Richard Z. , Cameron Tess , Kolchinsky Peter 
Published: December 2024

Abstract

The impact of Medicare’s price negotiation on long-term pharmaceutical innovation and patient welfare remains one of the most widely debated topics across stakeholder groups.
Existing policy simulations have tried to assess the policy impacts on innovation based on either empirical estimates of elasticity of innovation from the literature or structural models estimating the joint distribution of expected revenue and expected costs at key stages of pharmaceutical development.
Since investors exert significant influence on investment programs that companies advance in the real world, a program-level analysis of how investors make their investment decisions can inform the key assumptions for policy simulations and generate more realistic insights.
Using an illustrative case example based on a marketed small-molecule drug indicated for cardiovascular diseases, we constructed a net present value (NPV) model to examine how Medicare price negotiation will impact discounted value and investment decisions at six key timepoints of new drug development.
Our analyses showed that IRA would lead to a 40% reduction in the NPV at the time of launch. The reduction was greater in earlier stages of development due to expected dilution and discounting, resulting in discontinuing this project at earlier decision points.
The case study demonstrated that the negative impacts of price negotiation at nine years were more pronounced for small-molecule assets in the earlier stages of development (e.g., preclinical or Phase 1) than those in the later stages, implying a possibly much larger impact on innovation than suggested by existing empirical literature and observed in the short term.
New machine-learning models outperform conventional risk assessment tools in gastrointestinal bleeding
Authors: Boros Eszter , Prószéky Kristóf Gergely , Molontay Roland , Pintér József , Vörhendi Nóra , Simon Orsolya Anna , Teutsch Brigitta , Pálinkás Dániel , Frim Levente , Tari Edina , Gagyi Endre Botond , Szabó Imre , Hágendorn Roland , Vincze Áron , Izbéki Ferenc , Abonyi-Tóth Zsolt , Szentesi Andrea , Vass Vivien , Hegyi Péter , Erőss Bálint 
Published: December 2024

Abstract

Rapid and accurate identification of high-risk acute gastrointestinal bleeding (GIB) patients is essential. We developed two machine-learning (ML) models to calculate the risk of in-hospital mortality in patients admitted due to overt GIB. We analyzed the prospective, multicenter Hungarian GIB Registry's data. The predictive performance of XGBoost and CatBoost machine-learning algorithms with the Glasgow-Blatchford (GBS) and pre-endoscopic Rockall scores were compared. We evaluated our models using five-fold cross-validation, and performance was measured by area under receiver operating characteristic curve (AUC) analysis with 95% confidence intervals (CI). Overall, we included 1,021 patients in the analysis. In-hospital death occurred in 108 cases. The XGBoost and the CatBoost model identified patients who died with an AUC of 0.84 (CI:0.76–0.90; 0.77–0.90; respectively) in the internal validation set, whereas the GBS and pre-endoscopic Rockall clinical scoring system's performance was significantly lower, AUC values of 0.68 (CI:0.62–0.74) and 0.62 (CI:0.56–0.67), respectively. The XGBoost model had a specificity of 0.96 (CI:0.92–0.98) at a sensitivity of 0.25 (CI:0.10–0.43) compared with the CatBoost model, which had a specificity of 0.74 (CI:0.66–0.83) at a sensitivity of 0.78 (CI:0.57–0.95). XGBoost and the CatBoost model identified patients with high mortality risk better than GBS and pre-endoscopic Rockall scores.
Application of Terahertz-combined Infrared Technology to the Restoration Testing of Ancient City Walls
Authors: Meng Tianhua , Xu Shixiang , Ren Jianguang , Yang Chunhua , Liu Hongmei , Li Wenyu , Li Bangquan , Hu Weidong 
Published: December 2024

Abstract

A comprehensive study of the three sections of the Desheng Fortress was conducted using terahertz time-domain spectroscopy (THz-TDS) and infrared thermal imaging technology. The results demonstrated significant differences in both THz spectra and infrared thermal images among the well-preserved unrepaired wall, adobe brick laying repaired wall, and traditionally layer-by-layer ramming repaired wall. Samples extracted from the traditional layer-by-layer ramming repaired wall had consistent THz time-domain delay values, absorption coefficients, and refractive indexes with those of the well-preserved wall but slightly higher values for the adobe brick laying repaired wall. Infrared thermal imaging demonstrated that the areas restored by layer-by-layer ramming exhibited greater uniformity with fewer instances of cracks, capillary phenomena, or biological diseases. Therefore, it can be concluded that restoration methods involving layer-by-layer ramming are more effective in reinstating the Desheng Fortress to its original state. The repair effect of the city wall can be accurately and quantitatively evaluated by combining infrared thermograph detection of the city wall area with terahertz spectroscopy measurement of fixed-point samples. Additionally, this approach enabled precise identification of deterioration and diseases in city walls.