bluuebunny/crossref_metadata_2025_split huggingface dataset:
Proteinase-Activated Receptor 1 Inhibition Alleviates Intestinal Fibrosis in Mice with Chronic Colitis
Authors: Song Jia , Guo Jinbo , Sun Donglei , Luo Yuxin , Zhan Rongrong , Li Chenyang , Liang Xiaonan , Yin Fengrong , Zhang Xiaolan 
Published: January 2024

Abstract

Intestinal fibrosis is a serious complication of inflammatory bowel disease (IBD). Proteinase-activated receptor (PAR) 1 is a highly conserved G protein-coupled receptor that is relevant to IBD. We investigated the expression of PAR1 in the progression of intestinal fibrosis in human tissues and mice with chronic enteritis. We acquired intestinal biopsy samples from 6 patients with stenotic UC, 6 patients with stenotic CD, and 6 patients without IBD (control individuals). Biopsy samples were analyzed through histology to test for fibrosis and through immunohistochemistry and RT‒qPCR to measure the levels of PAR1. We studied inflammation and fibrosis severity in intestinal tissues from PAR1–/– mice, and mice were given injections of the PAR1 antagonist; chronic colitis and fibrosis were induced by repetitive administration of DSS. Human intestinal fibroblasts were incubated with thrombin, a PAR1 antagonist, SB-431542 or control medium. The proliferation, activation, migration and collagen synthesis of fibroblasts were detected by CCK8 assay, immunofluorescence cytochemistry, scratch test, transwell assay, western blot, RT‒qPCR and ELISA. Compared with those in mucosal and submucosal biopsy tissue from control individuals, obviously greater levels of collagen deposition were noted in bowel biopsy tissue from patients with fibrostenotic UC or CD. Tissues from patients with fibrostenotic UC or CD had significantly greater levels of PAR1. Mice given injections of a PAR1 antagonist and of PAR1–/– mice exhibited significantly less established fibrosis than mice with chronic colitis. PAR1 inhibition of human intestinal fibroblasts reduced proliferation, differentiation, migration and collagen synthesis. Mechanistically, PAR1 antagonism effectively inhibited the phosphorylation of the Smad2 and Smad3 proteins and the Smad2/3 protein. Compared with those in control individuals, we found enhanced levels of PAR1 in fibrotic bowel tissues from patients with IBD. PAR1 promoted fibrogenesis in fibroblasts. Inhibition or knockout of the PAR1 gene in mice decreases chronic intestinal inflammation and intestinal fibrosis. This research may offer new ideas for the treatment of intestinal fibrosis complicated with chronic intestinal inflammation.
Simple mathematical model for predicting COVID-19 outbreaks in Japan based on epidemic waves with a cyclical trend
Authors: Manabe Hiroki , Manabe Toshie , Honda Yuki , Kawade Yoshihiro , Kambayashi Dan , Manabe Yoshiki , Kudo Koichiro 
Published: January 2024

Abstract

Background
Several models have been used to predict outbreaks during the COVID-19 pandemic, with limited success. We developed a simple mathematical model to accurately predict future epidemic waves.
Methods
We used data from the Ministry of Health, Labour and Welfare - Japan for newly confirmed COVID-19 cases. COVID-19 case data were summarized as weekly data; then, epidemic waves were visualized and identified. The periodicity of COVID-19 in each prefecture of Japan was confirmed using time-series analysis and the autocorrelation coefficient, which was used to investigate the longer-term pattern of COVID-19 cases. Outcomes using the autocorrelation coefficient were visualized via a correlogram to capture the periodicity of the data. An algorithm for a simple prediction model of the seventh COVID-19 wave in Japan comprised three steps. Step 1: machine learning techniques was used to depict the regression lines for each epidemic wave, denoted the “rising trend line”; Step 2: an exponential function with good fit was identified from data of rising straight lines up to the sixth wave and the timing of the rise of the seventh wave and speed of its spread were calculated; Step 3: a logistic function was created using the values calculated in Step 2 as coefficients to predict the seventh wave. The accuracy of the model in predicting the seventh wave was confirmed using data up to the sixth wave.
Results
Up to March 31, 2023, the correlation coefficient value was approximately 0.5, indicating significant periodicity. The spread of COVID-19 in Japan was repeated in a cycle of approximately 140 days. In the predicted seventh wave, although the starting time and peak time of the epidemic were slightly behind, our developed prediction model had a fairly high degree of accuracy.
Conclusion
Our newly developed prediction model based on the rising trend line could predict COVID-19 outbreaks up to a few months in advance with high accuracy. The findings of the present study warrant further investigation regarding application to emerging infectious diseases other than COVID-19 when an epidemic wave has high periodicity.
A Prognostic Signature of Cuproptosis-Related LncRNAs to Predict Survival and Immune Response in Esophageal Cancer
Authors: Wang Xiaofeng , Huang Yiheng , Jing Hui , Yu Zhenjia , Su Liping , Li Hecheng 
Published: January 2024

Abstract
Cuproptosis is a novel copper ion-dependent mode of programmed cell death. Aberrantly expressed lncRNAs are closely associated with the development of esophageal cancer (ESCA), yet the role played by cuproptosis and lncRNAs in ESCA remains unknown. The purpose of the study was to identify a prognostic signature of cuproptosis-related lncRNAs for predicting prognosis and immune response in ESCA. In this study, the transcriptomic and clinical data of ESCA patients were obtained from the TCGA and cuproptosis-related genes were obtained from previously published literatures, from which cuproptosis-related differentially expressed lncRNAs were identified by co-expression analysis. Selected lncRNAs were analyzed with univariate and lasso regression to construct the prognostic signature, of which we assessed the predictive power in terms of overall survival, clinical features, immune infiltration, mutational profiles, efficacy of immunotherapy, and drug sensitivity. We ultimately screened 6 cuproptosis-related prognostic lncRNAs (AC110611.2, AC125437.1, C2orf27A, EWSAT1, GK-IT1 and PRANCR) to construct a novel prognostic signature (CupRLSig) and divided the ESCA patient samples into high- and low- risk groups using the median risk score as a threshold. We demonstrated that the high- and low-risk groups differed in overall survival, clinical parameters, immune infiltration, and drug sensitivity, with the high-risk group having lower survival, more aggressive disease (tumor infiltration depth, lymph node metastasis), immunosuppressive microenvironment (M2 macrophage), and higher tumor immune dysfunction and exclusion (TIDE).The low-risk group was characterized by more antitumor immune cells (neutrophils, T cells) and enhanced immune function (T cell co − stimulation, inflammation promoting), higher tumor mutational load (TMB) and increased drug sensitivity. Gene set enrichment analysis (GSEA) results showed that tumor and immune-related pathways were obviously enriched in the low-risk group. The novel prognostic signature of cuproptosis-related lncRNAs has the potential to predict survival, immune response and drug sensitivity in ESCA, contributing to personalized clinical prediction and treatment.
Pragmatic Nationwide Master Observational Trial Based on Genomic Alterations in Advanced Solid Tumors: KOrean Precision Medicine Networking Group Study of MOlecular profiling guided therapy based on genomic alterations in advanced Solid tumors (KOSMOS)-II Study Protocol KCSG AL-22-09
Authors: Kim Sun Young , Kim Jee Hyun , Kim Tae-Yong , Park Sook Ryun , Yoon Shinkyo , Lee Soohyeon , Lee Se-Hoon , Kim Tae Min , Han Sae-Won , Kim Hye Ryun , Yun Hongseok , Lee Sejoon , Kim Jihun , Choi Yoon-La , Choi Kui Son , Chae Heejung , Ryu Hyewon , Lee Gyeong-Won , Zang Dae Young , Ahn Joong Bae 
Published: January 2024

Abstract

Background: Next-generation sequencing (NGS) has been introduced to many Korean institutions to support molecular diagnostics in cancer since 2017, when it became eligible for reimbursement by the National Health Insurance Service. However, the uptake of molecularly guided treatment (MGT) based on NGS results has been limited because of stringent regulations regarding prescriptions outside of approved indications, a lack of clinical trial opportunities, and limited access to molecular tumor boards (MTB) at most institutions. The KOSMOS-II study was designed to demonstrate the feasibility and effectiveness of MGT, informed by MTBs, using a nationwide precision medicine platform.
Methods: The KOSMOS-II trial is a large-scale nationwide master observational study. It involves a framework for screening patients with metastatic solid tumors for actionable genetic alterations based on local NGS testing. It recommends MGT through a remote and centralized MTB meeting held biweekly. MGT can include one of the following options: Tier 1, the therapeutic use of investigational drugs targeting genetic alterations such as ALK, EGFR, ERBB2, BRAF, FH, ROS1, and RET, or those with high tumor mutational burden; Tier 2, comprising drugs with approved indications or those permitted for treatment outside of the indications approved by the Health Insurance Review and Assessment Service of Korea; Tier 3, involving clinical trials matching the genetic alterations recommended by the MTB. Given the anticipated proportion of patients receiving MGT in the range of 50%±3.25%, this study aims to enroll 1,000 patients. Patients must have progressed to one or more lines of therapy and undergone NGS before enrollment.
Discussion: This pragmatic master protocol provides a mass-screening platform for rare genetic alterations and high-quality real-world data. Collateral clinical trials, translational studies, and clinico-genomic databases will contribute to generating evidence for drug repositioning and the development of new biomarkers.
Trial Registration:NCT05525858
Identification, Heterologous Expression and Characterization of a New Unspecific Peroxygenase from Marasmius fiardii PR-910
Authors: Li Aitao , Fu Xin , Lin Kexin , Zhang Xiaodong , Guo Zhiyong , Kang Lixin 
Published: January 2024

Abstract
Unspecific peroxygenases (UPOs) are glycosylated enzymes that provide an efficient method for oxyfunctionalizing a variety of substrates using only hydrogen peroxide (H2O2) as the oxygen donor. However, their poor heterologous expression has hindered their practical application. Here, a novel UPO from Marasmius fiardii PR910 (MfiUPO) was identified and heterologously expressed in Pichia pastoris. By employing a two-copy expression cassette, the protein titer reached 1.18 g L− 1 in a 5-L bioreactor, marking the highest record. The glycoprotein rMfiUPO exhibited a smeared band in the 40 to 55 kDa range and demonstrated hydroxylation, epoxidation and alcohol oxidation. Moreover, the peroxidative activity was enhanced by 150% after exposure to 50% (v/v) acetone for 40 h. A semi-preparative production of 4-OH-β-ionone on a 100 mL scale resulted in a 54.2% isolated yield with 95% purity. With its high expression level, rMfiUPO is a promising candidate as an excellent parental template for enhancing desirable traits such as increased stability and selectivity through directed evolution, thereby meeting the necessary criteria for practical application.
Ultrasmall Silica Nanoparticles: Synthesis, Functionalization and Biomedical Application
Authors: Cui Feihu , Qu Lishuo , Gong Yao , Xie Yijun , Chang Qing , Celia Christian , Deng Xiaoyong 
Published: January 2024

Abstract
Ultrasmall silica nanoparticles (USNPs) with a size ＜20 nm exhibit unique advantages such as low toxicity, surface modification, and efficient renal clearance, making them highly promising in the fields of bioimaging, disease detection, gene delivery, and drug delivery. In this short review, synthesis, functionalization, and biomedical applications of USNPs are discussed. First, the different synthetic methods for fabricating hollow USNPs and solid USNPs. Then, surface modification methods are described in detail. Finally, the biomedical application progress and toxicity of USNPs encapsulated with fluorescent and drug molecule are discussed.
An ensemble method based on weight voting method for improved prediction of slope stability
Authors: Chen Yumin , Fu Zhongling , Yao Xiaofei , Han Yi , Li Zhenxiong 
Published: January 2024

Abstract
This study proposes a novel ensemble method based on weighted majority voting to evaluate the stability of slope. The ensemble classifier is composed of 5 base classifiers including random forest (namely RF), logistic regression (namely LR), naive Bayes (namely NB), support vector machine (namely SVC) and backpropagation (BP). An integrated approach was developed using 213 slope cases collected from the literature and the performance of the proposed approach was validated. Selection of training parameters was carried out by the definition of safety factor (FS) and the correlation analysis of parameters. Then, a search for the optimal hyperparameters of the base classifiers is performed using a grid search algorithm combined with a five-fold cross-validation. Weights to each base classifier is obtained by the AUC value of the training dataset. To the end, the ensemble method based on weights is established to predict the stability of slopes in this paper. It is demonstrated that the ensemble algorithm is superior to the base classifier with regard to accuracy (ACC), Kappa(K), Precision (P), recall (R), F1 score (F1), and the receiver's operating characteristic curve area under the curve (AUC). Also, the importance scores of training parameters are obtained by the random forest theory.
Tests to Confirm Inherently Safe Commercial Nuclear Reactors
Authors: Dong Zhe , Zhang Zuoyi , Dong Yujie , Li Fu , Huang Xiaojin , Zheng Yanhua , Zhang Han , Chen Zhipeng , Li Xiaowei 
Published: January 2024

Abstract
Nuclear fission energy is one of the firm low-carbon resources containing the cost of deep decar-bonization. Safety is the basis of deploying nuclear power plants near load centers in a large-scale. The safety of inherently safe nuclear reactors is defined to depends solely on the laws of nature. The world’s first demonstration plant of High Temperature Reactor with Pebble-Bed Module (HTR-PM) entered its commercial operation since December 6, 2023. To confirm the existence of inherent safety in a commercial scale, two safety tests were conducted on the two reactor modules of HTR-PM plant, each at a power of 200MWt. During the test, the active power supply was total-ly switched off to see if the decay heat can be removed passively. The responses of nuclear power and temperatures within different reactor structures show that the reactors can be naturally cooled down without active intervention. The results manifest the existence of commercial-scale inherent safety for the first time.
Assessment of genetic diversity of Camellia yuhsienensis based on leaf structure and ISSR markers
Authors: Zou Yuling , Ge Xiaoning , Yan Chao , Zhong Qiuping , Chen Danyang , Chen Zexin , Yuan Yaqi , Guo Hongyan , Zhou Youcheng , Wang Jinfeng , Cao Linqing 
Published: January 2024

Abstract
Genetic diversity of Camellia yuhsienensis was analyzed according to leaf structure and molecular markers to determine genetic relationships and genetic differentiation characteristics among various strains. Leaf structural traits and ISSR molecular markers were selected to study the genetic diversity and cluster analysis of C. yuhsienensis. Twenty-one leaf traits varied to different degrees, and variation coefficients ranged from 6.91–20.45%. They all reached significant or extremely significant levels. Through principal component analysis, the cumulative contribution rate of the first four principal components reached 85.57%, and eight typical leaf characteristics were screened out. Molecular markers revealed that 201 loci were amplified by 10 ISSR primers, and 175 were polymorphic loci with an average polymorphism rate of 87.06%. Nei's Diversity Index and the Shannon diversity index values were 0.2613 and 0.4013, respectively. An ISSR identification card drawn using primer 826 was used to identify 13 C. yuhsienensis. Cluster analysis demonstrated that the clustering results based on leaf structure and molecular markers were generally consistent. Only CL1 and CL2 differed between the two methods, and the ISSR molecular markers detected small variations at the molecular level. Therefore, the clustering was more detailed than that of leaf structural traits. In the two clustering methods, germplasms with higher phloem thickness and main vein bulge and a short diameter of the vascular bundle were clustered into one category, and the specific germplasm LY2 was clustered into another category. Our results provide a theoretical basis for the diversity, germplasm identification, and rational utilization of C. yuhsienensis.
Accelerating the discovery of biodiversity by detecting “new” species based on machine learning method
Authors: Lu Yuanyuan , Li Jing , Zhao Zhengyu , Zhang Yongchao , Tong Yijie , Teng Bei , Liu Ning , Shaw Josh Jenkins , Bai Ming 
Published: January 2024

Abstract
Background
Recently, machine learning (ML) has been widely used in species auto-identification systems for multi-scene applications in biodiversity, while most of the existing ML systems relying on images are limited to identifying the species on which they are trained, and unknown species out of the system are normally incorrectly identified.
Results
Here, we propose a new workflow system based on the ML system and PERMANOVA analysis, named Taichi for the detection and confirmation of unknown species status, stimulated by the traditional biodiversity discovery process. First, we developed a series of high-throughput photography devices that could efficiently obtain aligned multiangle images for ML system training. Then the new analysis workflow was integrated in Python codes based on the convolutional neural networks: MobileNetV2 (selected from four available networks) and further PERMANOVA analysis of euclidean distances to detect 'new' species. Two newly established beetle datasets: Melanopopillia (4 species, 55 specimens, 42 450 images) and Hong Kong beetles (21 species, 206 specimens, 35 450 images) were constructed in this work to demonstrate the Taichi system. The diagnostic information for species is generated from the output results of the ML system (top-1 accuracy rate reached 97.76% and 96.22% respectively) naming as the artificial intelligence (AI) barcode, and extra analysis of AI barcodes could help visualization the diagnostic characters from multiangle images.
Conclusions
By comparing AI barcodes of different specimens outside the system, it is proved that the Taichi workflow can rapidly detect whether the input sample is a known species or possible 'new' species. This workflow provides a newly possible self-extensibility solution for the acceleration of biodiversity discovery. Additionally, it can also drive the development of data mining from the digitization of natural history collections around the world and has great potential to advance the field of biodiversity science.
The relationship between modifiable risk factors and depression in age-specific cancer survivors: Evidence from NHANES
Authors: Qiu Minhao 
Published: January 2024

Abstract
Background: There is limited and inconsistent evidence on whether the modifiable risk factors linked to depression in cancer survivors remain the same across different age groups. We aimed to identify modifiable risk factors that are associated with depression in cancer survivors and determine whether this association varies with age.
Methods: This cross-sectional study analyzed 3,368 participants from the 2007-2018 National Health and Nutrition Examination Survey (NHANES), categorized into adults (20-64 years) and seniors (65 years and above). Cancer survivors were defined as individuals who self-reported having been diagnosed with cancer. Depression was defined as a score of 10 or higher on The Patient Health Questionnaire (PHQ-9). Logistic regression models were used to assess the relationship between modifiable factors and depression.
Results: This analysis included 3,368 participants, 1,332 (39.6%) were aged 20-64, with 205 (15.39%) having depression, and 2,036 (60.4%) were 65 and above, with 121 (5.94%) experiencing depression. Healthcare access (OR: 1.834, 95% CI: 1.145 to 2.937) and insurance (OR: 2.058, 95% CI: 1.393 to 3.039) significantly influenced depression, while mental healthcare (OR: 0.235, 95% CI: 0.176 to 0.314), smoking (OR: 1.694, 95% CI: 1.321 to 2.171), physical activity (OR: 1.588, 95% CI: 1.252 to 2.014), and dietary quality (OR: 1.691, 95% CI: 1.177 to 2.43) were also notable factors. After stratification by age, younger adults (20-64) were more influenced by smoking (OR: 0.709, 95% CI: 0.382 to 1.036) and physical activity (OR: 0.788, 95% CI: 0.468 to 1.108), while older adults (65+) were more affected by insurance (OR: 1.128, 95% CI: 0.159 to 2.096).
Conclusion: The impact of modifiable factors like insurance, smoking, and physical activity varies across age groups, while healthcare access, mental healthcare, and dietary quality remain consistent. The research emphasizes the importance of age-specific mental health support and lifestyle adjustments for cancer survivors.
Effectiveness of an HIV peer support precision matching platform: a randomized controlled trial protocol
Authors: 谢 昕 , Han Shuyu , Wu Yangfeng , Huang Tao , Duan Yi , Li Dongmei , Chen Shuyu , Zhou Bo , Zhang Jiangping , Zhang Lili 
Published: January 2024

Abstract

Background: Peer support is a promising and significant way for people living with HIV (PLWH) to improve their health outcomes. Matching PLWH with HIV peer volunteers can effectively stimulate and mobilize the function of peer support in health management. We developed the online platform Aspark, which features a precision matching function for PLWH and volunteers. This protocol provides a comprehensive overview of the randomized controlled trial design based on Aspark.
Method: A parallel randomized controlled trial using block randomization will be conducted at the Beijing YouAn Home of Loving Care. The intervention group (n = 70) had access to all 12 features of Aspark, including precise volunteer matching, health management tools, drug interaction queries, and medication reminders. The control group (n = 70) had access to two features of informational support on Aspark. The outcomes of both groups will be evaluated at baseline and at 3, 6, 9, and 12 months after platform registration. The primary outcome was perceived social support. The secondary outcomes included mental symptoms, quality of life, self-efficacy, medication adherence, and health behaviors. Linear mixed models or generalized linear mixed models will be applied to test the intervention effects.
Discussion: The Aspark trial is a randomized controlled trial designed to examine the influence of a mobile health (mHealth) application that integrates peer support and precision matchingto strengthen social support for PLWH in China. This trial has the potential to significantly enhance social support for PLWH while also optimizing the delivery of peer support services and fully mobilizing the role of peer support in the overall health management of PLWH.
Clinical registration number: ChiCTR2300077454