bluuebunny/crossref_metadata_2025 huggingface dataset:
Cross-sectional and longitudinal associations between self-esteem and BMI depends on baseline BMI category in a population-based study
Authors: Robert Margaux , Allès Benjamin , Gisch Ulrike A. , Shankland Rebecca , Hercberg Serge , Touvier Mathilde , Leys Christophe , Péneau Sandrine
Published: January 2024

Background

Some studies have reported associations between self-esteem and weight status, but longitudinal data on adults remain scarce. The aim of this population-based study was to analyze the cross-sectional and longitudinal association between self-esteem and body mass index (BMI) and to investigate whether baseline BMI has an impact on this association.

Methods

In 2016, 29,735 participants aged ≥ 18 years in the NutriNet-Santé cohort completed the Rosenberg Self-Esteem Scale. BMI was self-reported yearly over a 4-year period. Association between self-esteem and BMI was assessed using mixed models and logistic regressions. Analyses were stratified by BMI (categorical) at baseline and adjusted on sociodemographic and lifestyle characteristics.

Results

At baseline, higher self-esteem was associated with higher BMI in normal weight individuals(p = 0.32), and with lower BMI in obese class II and III individuals (p = 0.13). In addition, higher baseline self-esteem was associated with BMI increase over time in normal weight individuals (p = 0.15). Among normal weight individuals, those with higher self-esteem were less likely to show a decrease in their BMI (p = 0.005), while no association was observed with BMI increase (p = 0.81).

Discussion

Our findings suggest that the association between self-esteem and BMI depends on the initial category of BMI, with a negligible effect of self-esteem.
Higher insoluble fiber intake is associated with a lower risk of prostate cancer: results from the PLCO cohort
Authors: Shen Yang , Yuan Qinbo , Shi Minhong , Luo Banxin
Published: January 2024

Studies regarding the relationship between fiber intake and prostate cancer (PCa) have conflicting results. Therefore, this study examined the relationship between fiber intake and the risk of PCa by using data from Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial. A total of 54,336 participants in the United States, consisting of 6,414 patients with PCa, were included in this study. Multivariate Cox regression models were applied to estimate adjusted hazard ratios (aHRs) and corresponding 95% confidence intervals (CIs). Compared with individuals in the lowest quartile, individuals in the highest quartile of insoluble fiber intake had a significantly lower risk of PCa (aHR, 0.87; 95% CI, 0.78–0.98). By contrast, no significant associations were detected between total fiber intake (aHR, 0.90; 95% CI, 0.80–1.01) or soluble fiber intake (aHR, 0.90; 95% CI, 0.80–1.02). Subgroup analyses showed that insoluble fiber was related to a decreased risk of PCa in subjects with the following characteristics: age > 65 years, nonsmoking or former smokers, education level ≤ high school, non-Hispanic white ethnicity, or without a family history of PCa. In addition, significant combined effects of insoluble fiber intake, age and family history of PCa on the risk of PCa were observed, but no combined effects of smoking status and insoluble fiber intake were observed. In addition, total fiber, insoluble fiber, and soluble fiber intake had no influence on the mortality of PCa patients. These results show that all 3 measures of fiber suggest a protective association, but insoluble fiber may have a stronger association with the risk of PCa. Future studies are warranted to further investigate these relationships.
Effects and mechanisms of Porphyromonas gingivalis outer membrane vesicles induced cardiovascular injury
Authors: Guo Jianbin , Lin Kaijin , Wang Siyi , He Xiaozhen , Huang Zhen , Zheng Minqian
Published: January 2024

Background

The outer membrane vesicles (OMVs) derived fromPorphyromonas gingivalis(P. gingivalis) have long been acknowledged for their crucial role in the initiation of periodontitis. However, the implications ofP. gingivalisOMVs in the context of cardiovascular disease (CVD) remain incompletely understood. This study aimed to clarify both the impact and the underlying mechanisms through whichP.gingivalisOMVs contribute to the propagation of distal cardiovascular inflammation and trauma.

Methods

In this study, various concentrations (0, 1.25, 2.5, and 4.5 µg/µL) ofP. gingivalisOMVs were microinjected into the common cardinal vein of zebrafish larvae at 48 h post-fertilization (hpf) to assess changes in cardiovascular injury and inflammatory response. Zebrafish larvae from both the PBS and the 2.5 µg/µL injection cohorts were harvested at 30 h post-injection (hpi) for transcriptional analysis. Real-time quantitative PCR (RT-qPCR) was employed to evaluate relative gene expression.

Results

These findings demonstrated thatP. gingivalisOMVs induced pericardial enlargement in zebrafish larvae, caused vascular damage, increased neutrophil counts, and activated inflammatory pathways. Transcriptomic analysis further revealed the involvement of the immune response and the extracellular matrix (ECM)-receptor interaction signaling pathway in this process.

Conclusion

This study illuminated potential mechanisms through whichP. gingivalisOMVs contribute to CVD. It accentuated their involvement in distal cardiovascular inflammation and emphasizes the need for further research to comprehensively grasp the connection between periodontitis and CVD.
Development and application of Chinese medical ontology for diabetes mellitus
Authors: Hu Jie , Huang Zixian , Ge Xuewen , Shen Yulin , Xu Yihan , Zhang Zirui , Zhou Guangyin , Wang Junjie , Lu Shan , Yu Yun , Wan Cheng , Zhang Xin , Huang Ruochen , Liu Yun , Cheng Gong
Published: January 2024

Objective

To develop a Chinese Diabetes Mellitus Ontology (CDMO) and explore methods for constructing high-quality Chinese biomedical ontologies.

Materials and methods

We used various data sources, including Chinese clinical practice guidelines, expert consensus, literature, and hospital information system database schema, to build the CDMO. We combined top-down and bottom-up strategies and integrated text mining and cross-lingual ontology mapping. The ontology was validated by clinical experts and ontology development tools, and its application was validated through clinical decision support and Chinese natural language medical question answering.

Results

The current CDMO consists of 3,752 classes, 182 fine-grained object properties with hierarchical relationships, 108 annotation properties, and over 12,000 mappings to other well-known medical ontologies in English. Based on the CDMO and clinical practice guidelines, we developed 200 rules for diabetes diagnosis, treatment, diet, and medication recommendations using the Semantic Web Rule Language. By injecting ontology knowledge, CDMO enhances the performance of the T5 model on a real-world Chinese medical question answering dataset related to diabetes.

Conclusion

CDMO has fine-grained semantic relationships and extensive annotation information, providing a foundation for medical artificial intelligence applications in Chinese contexts, including the construction of medical knowledge graphs, clinical decision support systems, and automated medical question answering. Furthermore, the development process incorporated natural language processing and cross-lingual ontology mapping to improve the quality of the ontology and improved development efficiency. This workflow offers a methodological reference for the efficient development of other high-quality Chinese as well as non-English medical ontologies.
Daly/Cost comparison in the management of peripheral arterial disease at 17 Belgian hospitals
Authors: Rondelet Benoît , Dehanne Fabian , Van Den Bulcke Julie , Martins Dimitri , Belhaj Asmae , Libert Benoît , Leclercq Pol , Pirson Magali
Published: January 2024

Objective

Peripheral arterial disease (PAD) is a manifestation of atherosclerosis that affects the lower extremities and afflicts more than 200 million people worldwide. Because of limited resources, the need to provide quality care associated with cost control is essential for health policies. Our study concerns an interhospital comparison among seventeen Belgian hospitals that integrates the weighting of quality indicators and the costs of care, from the hospital perspective, for a patient with this pathology in 2018.

Methods

The disability-adjusted life years (DALYs) were calculated by adding the number of years of life lost due to premature death and the number of years of life lost due to disability for each in-hospital stay. The DALY impact was interpreted according to patient safety indicators. We compared the hospitals using the adjusted values ​​of costs and DALYs for their case mix index, obtained by relating the observed value to the predicted value obtained by linear regression.

Results

We studied 2,437 patients and recorded a total of 560.1 DALYs in hospitals. The in-hospital cost average [standard deviation (SD)] was €8,673 (€10,893). Our model identified the hospitals whose observed values were higher than predicted; six needed to reduce the costs and impacts of DALYs, six needed to improve one of the two factors, and four seemed to have good results. The average cost (SD) for the worst performing hospitals amounted to €27,803 (€28,358).

Conclusions

Studying the costs of treatment according to patient safety indicators permits us to evaluate the entire chain of care using a comparable unit of measurement.
Pulse wave-based evaluation of the blood-supply capability of patients with heart failure via machine learning
Authors: Wang Sirui , Ono Ryohei , Wu Dandan , Aoki Kaoruko , Kato Hirotoshi , Iwahana Togo , Okada Sho , Kobayashi Yoshio , Liu Hao
Published: January 2024

Pulse wave, as a message carrier in the cardiovascular system (CVS), enables inferring CVS conditions while diagnosing cardiovascular diseases (CVDs). Heart failure (HF) is a major CVD, typically requiring expensive and time-consuming treatments for health monitoring and disease deterioration; it would be an effective and patient-friendly tool to facilitate rapid and precise non-invasive evaluation of the heart’s blood-supply capability by means of powerful feature-abstraction capability of machine learning (ML) based on pulse wave, which remains untouched yet. Here we present an ML-based methodology, which is verified to accurately evaluate the blood-supply capability of patients with HF based on clinical data of 237 patients, enabling fast prediction of five representative cardiovascular function parameters comprising left ventricular ejection fraction (LVEF), left ventricular end-diastolic diameter (LVDd), left ventricular end-systolic diameter (LVDs), left atrial dimension (LAD), and peripheral oxygen saturation (SpO2). Two ML networks were employed and optimized based on high-quality pulse wave datasets, and they were validated consistently through statistical analysis based on the summary independent-samplest-test (p > 0.05), the Bland–Altman analysis with clinical measurements, and the error-function analysis. It is proven that evaluation of the SpO2, LAD, and LVDd performance can be achieved with the maximum error < 15%. While our findings thus demonstrate the potential of pulse wave-based, non-invasive evaluation of the blood-supply capability of patients with HF, they also set the stage for further refinements in health monitoring and deterioration prevention applications.
Multimodal diagnosis model of Alzheimer’s disease based on improved Transformer
Authors: Tang Yan , Xiong Xing , Tong Gan , Yang Yuan , Zhang Hao
Published: January 2024

Purpose

Recent technological advancements in data acquisition tools allowed neuroscientists to acquire different modality data to diagnosis Alzheimer’s disease (AD). However, how to fuse these enormous amount different modality data to improve recognizing rate and find significance brain regions is still challenging.

Methods

The algorithm used multimodal medical images [structural magnetic resonance imaging (sMRI) and positron emission tomography (PET)] as experimental data. Deep feature representations of sMRI and PET images are extracted by 3D convolution neural network (3DCNN). An improved Transformer is then used to progressively learn global correlation information among features. Finally, the information from different modalities is fused for identification. A model-based visualization method is used to explain the decisions of the model and identify brain regions related to AD.

Results

The model attained a noteworthy classification accuracy of 98.1% for Alzheimer’s disease (AD) using the Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset. Upon examining the visualization results, distinct brain regions associated with AD diagnosis were observed across different image modalities. Notably, the left parahippocampal region emerged consistently as a prominent and significant brain area.

Conclusions

A large number of comparative experiments have been carried out for the model, and the experimental results verify the reliability of the model. In addition, the model adopts a visualization analysis method based on the characteristics of the model, which improves the interpretability of the model. Some disease-related brain regions were found in the visualization results, which provides reliable information for AD clinical research.
A district-level geospatial analysis of anaemia prevalence among rural men in India, 2019-21
Authors: Singh Aditya , Ram Sumit , Chandra Rakesh , Tanti Arabindo , Singh Shivani , Kundu Ananya
Published: January 2024

Background

Despite its considerable impact on health and productivity, anemia among men has received limited attention. In a country as diverse as India, characterized by extensive geographic variations, there is a pressing need to investigate the nuanced spatial patterns of anemia prevalence among men. The identification of specific hotspots holds critical implications for policymaking, especially in rural areas, where a substantial portion of India’s population resides.

Methods

The study conducted an analysis on a sample of 61,481 rural men from 707 districts of India, utilizing data from the National Family Health Survey-5 (2019-21). Various analytical techniques, including Moran’s I, univariate LISA (Local Indicators of Spatial Association), bivariate LISA, and spatial regression models such as SLM (Spatial Lag Model), and SEM (Spatial Error Model) were employed to examine the geographic patterns and spatial correlates of anaemia prevalence in the study population.

Results

In rural India, three out of every ten men were found to be anemic. The univariate Moran’s I value for anaemia was 0.66, indicating a substantial degree of spatial autocorrelation in anaemia prevalence across the districts in India. Cluster and outlier analysis identified five prominent ‘hotspots’ of anaemia prevalence across 97 districts, primarily concentrated in the eastern region (encompassing West Bengal, Jharkhand, and Odisha), the Dandakaranya region, the Madhya Pradesh-Maharashtra border, lower Assam, and select districts in Jammu and Kashmir. The results of SLM revealed significant positive association between anaemia prevalence at the district-level and several key factors including a higher proportion of Scheduled Tribes, men in the 49–54 years age group, men with limited or no formal education, individuals of the Muslim faith, economically disadvantaged men, and those who reported alcohol consumption.

Conclusions

Substantial spatial heterogeneity in anaemia prevalence among men in rural India suggests the need for region-specific targeted interventions to reduce the burden of anaemia among men in rural India and enhance the overall health of this population.
New immunotherapy approaches for colorectal cancer: focusing on CAR-T cell, BiTE, and oncolytic viruses
Authors: Kamrani Amin , Nasiri Hadi , Hassanzadeh Ali , Ahmadian Heris Javad , Mohammadinasab Reza , Sadeghvand Shahram , Sadeghi Mohammadreza , Valedkarimi Zahra , Hosseinzadeh Ramin , Shomali Navid , Akbari Morteza
Published: January 2024

Colorectal cancer is one of the most common causes of mortality worldwide. There are several potential risk factors responsible for the initiation and progression of colorectal cancer, including age, family history, a history of inflammatory bowel disease, and lifestyle factors such as physical activity and diet. For decades, there has been a vast amount of study on treatment approaches for colorectal cancer, which has led to conventional therapies such as chemotherapy, surgery, etc. Considering the high prevalence and incidence rate, scholars believe there is an urgent need for an alternative, more efficacious treatment with fewer adverse effects than the abovementioned treatments. Immunotherapy has emerged as a potential treatment alternative in a few years and has become one of the fastest-evolving therapeutic methods. Immunotherapy works by activating or enhancing the immune system’s power to identify and attack cancerous cells. This review summarizes the most crucial new immunotherapy methods under investigation for colorectal cancer treatment, including Immune checkpoint inhibitors, CAR-T cell therapy, BiTEs, Tumor-infiltrating lymphocytes, and Oncolytic virus therapy. Furthermore, this study discusses the application of combination therapy, precision medicine, biomarker discovery, overcoming resistance, and immune-related adverse effects.
Faecalibacterium prausnitzii as a potential Antiatherosclerotic microbe
Authors: Yang Hai-Tao , Jiang Zhi-hui , Yang Yi , Wu Ting-Ting , Zheng Ying-Ying , Ma Yi-Tong , Xie Xiang
Published: January 2024

Background

The gut microbiota plays a crucial role in coronary artery disease (CAD) development, but limited attention has been given to the role of the microbiota in preventing this disease. This study aimed to identify key biomarkers using metagenomics and untargeted metabolomics and verify their associations with atherosclerosis.

Methods

A total of 371 participants, including individuals with various CAD types and CAD-free controls, were enrolled. Subsequently, significant markers were identified in the stool samples through gut metagenomic sequencing and untargeted metabolomics. In vivo and in vitro experiments were performed to investigate the mechanisms underlying the association between these markers and atherosclerosis.

Results

Faecal omics sequencing revealed that individuals with a substantial presence of Faecalibacterium prausnitzii had the lowest incidence of CAD across diverse CAD groups and control subjects. A random forest model confirmed the significant relationship between F. prausnitzii and CAD incidence. Notably, F. prausnitzii emerged as a robust, independent CAD predictor. Furthermore, our findings indicated the potential of the gut microbiota and gut metabolites to predict CAD occurrence and progression, potentially impacting amino acid and vitamin metabolism. F. prausnitzii mitigated inflammation and exhibited an antiatherosclerotic effect on ApoE−/− mice after gavage. This effect was attributed to reduced intestinal LPS synthesis and reinforced mechanical and mucosal barriers, leading to decreased plasma LPS levels and an antiatherosclerotic outcome.

Conclusions

Sequencing of the samples revealed a previously unknown link between specific gut microbiota and atherosclerosis. Treatment with F. prausnitzii may help prevent CAD by inhibiting atherosclerosis.
Establishment and analysis of a novel diagnostic model for systemic juvenile idiopathic arthritis based on machine learning
Authors: Ding Pan , Du Yi , Jiang Xinyue , Chen Huajian , Huang Li
Published: January 2024

Background

Systemic juvenile idiopathic arthritis (SJIA) is a form of childhood arthritis with clinical features such as fever, lymphadenopathy, arthritis, rash, and serositis. It seriously affects the growth and development of children and has a high rate of disability and mortality. SJIA may result from genetic, infectious, or autoimmune factors since the precise source of the disease is unknown. Our study aims to develop a genetic-based diagnostic model to explore the identification of SJIA at the genetic level.

Methods

The gene expression dataset of peripheral blood mononuclear cell (PBMC) samples from SJIA was collected from the Gene Expression Omnibus (GEO) database. Then, three GEO datasets (GSE11907-GPL96, GSE8650-GPL96 and GSE13501) were merged and used as a training dataset, which included 125 SJIA samples and 92 health samples. GSE7753 was used as a validation dataset. The limma method was used to screen differentially expressed genes (DEGs). Feature selection was performed using Lasso, random forest (RF)-recursive feature elimination (RFE) and RF classifier.

Results

We finally identified 4 key genes (ALDH1A1, CEACAM1, YBX3 and SLC6A8) that were essential to distinguish SJIA from healthy samples. And we combined the 4 key genes and performed a grid search as well as 10-fold cross-validation with 5 repetitions to finally identify the RF model with optimal mtry. The mean area under the curve (AUC) value for 5-fold cross-validation was greater than 0.95. The model’s performance was then assessed once more using the validation dataset, and an AUC value of 0.990 was obtained. All of the above AUC values demonstrated the strong robustness of the SJIA diagnostic model.

Conclusions

We successfully developed a new SJIA diagnostic model that can be used for a novel aid in the identification of SJIA. In addition, the identification of 4 key genes that may serve as potential biomarkers for SJIA provides new insights to further understand the mechanisms of SJIA.
N6-methyladenosine modification positively regulate Japanese encephalitis virus replication
Authors: Yao Min , Cheng Zhirong , Li Xueyun , Li Yuexiang , Ye Wei , Zhang Hui , Liu He , Zhang Liang , Lei Yingfeng , Zhang Fanglin , Lv Xin
Published: January 2024

N6-methyladenosine (m6A) is present in diverse viral RNA and plays important regulatory roles in virus replication and host antiviral innate immunity. However, the role of m6A in regulating JEV replication has not been investigated. Here, we show that the JEV genome contains m6A modification upon infection of mouse neuroblast cells (neuro2a). JEV infection results in a decrease in the expression of m6A writer METTL3 in mouse brain tissue. METTL3 knockdown by siRNA leads to a substantial decrease in JEV replication and the production of progeny viruses at 48 hpi. Mechanically, JEV triggered a considerable increase in the innate immune response of METTL3 knockdown neuro2a cells compared to the control cells. Our study has revealed the distinctive m6A signatures of both the virus and host in neuro2a cells infected with JEV, illustrating the positive role of m6A modification in JEV infection. Our study further enhances understanding of the role of m6A modification in Flaviviridae viruses.
Correlation analysis of hepatic steatosis and hepatitis B virus: a cross-sectional study
Authors: Yi Sitong , Ren Guanghui , Zhu Ying , Cong Qingwei
Published: January 2024

Background

The co-occurrence of chronic hepatitis B (CHB) and metabolic dysfunction-associated fatty liver disease (MAFLD) has drawn considerable attention due to its impact on disease outcomes. This study aimed to investigate the association between hepatic steatosis and hepatitis B virus (HBV) and analyzed the influence of hepatic steatosis on hepatitis B virology in patients with CHB.

Methods

In this cross-sectional study, 272 patients infected with HBV who were treatment-naïve or had ceased antiviral treatment for > 6 months were categorized into the CHB group (n = 128) and CHB + MAFLD group (n = 144). Furthermore, based on whether HBV DNA was higher than 2000 IU/mL, patients were categorized into the high-level HBV DNA group (n = 129) and the low-level HBV DNA group (n = 143). The impact of hepatic steatosis on hepatitis B virology was analyzed within the CHB cohort. Multivariate logistic regression analysis was employed to identify independent factors influencing pre-genomic RNA (pgRNA) levels below the lower limit of detection (LLD) in patients with CHB.

Results

Among the 272 patients, compared with CHB group, HBV DNA levels (4.11 vs. 3.62 log10 IU/mL, P = 0.045), hepatitis B surface antigen (HBsAg) levels (3.52 vs. 3.20 log10 IU/mL, P = 0.008) and the hepatitis B e antigen (HBeAg) positive rate (33.6% vs. 22.2%, P = 0.036) were significantly decreased in the CHB + MAFLD group; In 143 low-level HBV DNA patients, the CHB + MAFLD group exhibited decreased levels of pgRNA and HBsAg compared to the CHB group. However, in 129 high-level HBV DNA patients, a more significant decrease was observed in pgRNA (3.85 vs 3.35 log10 copies/mL, P = 0.044) and HBsAg (3.85 vs 3.59 log10 IU/mL, P = 0.033); Spearman correlation analysis revealed a negative correlation between hepatic steatosis and pgRNA (r =  − 0.529, P < 0.001), HBV DNA (r =  − 0.456, P < 0.001), HBsAg (r =  − 0.465, P < 0.001) and HBeAg (r =  − 0.339, P < 0.001) levels; Multivariate logistic regression analysis identified HBV DNA (odds ratio [OR] = 0.283, P < 0.001), HBsAg (OR = 0.300, P < 0.001), and controlled attenuation parameter (CAP) values (OR = 1.013, P = 0.038) as independent factors influencing pgRNA levels below the LLD in patients with CHB.

Conclusions

This study establishes a negative correlation between hepatic steatosis and hepatitis B virology, demonstrating decreased HBV expression in patients with CHB + MAFLD.
Epithelioid angiomyolipoma of the liver in a patient with Li-Fraumeni syndrome: a case report
Authors: Yang Yaewon , Lee Jisun , Woo Chang Gok , Lee Ok-Jun , Son Seung-Myoung
Published: January 2024

Background

Epithelioid angiomyolipoma (EAML) is a rare variant of angiomyolipoma that predominantly consists of epithelioid cells and belongs to the perivascular epithelioid cell neoplasm (PEComa) family. The majority of EAMLs arise in the kidneys, and primary hepatic EAML appears to be much less common than renal EAML. Most PEComas arise sporadically, but may be associated with tuberous sclerosis complex (TSC), an autosomal dominant genetic disorder characterized by germline mutations in the TSC1 or TSC2 genes. However, PEComas have previously been reported in five patients with Li-Fraumeni syndrome (LFS), which is an inherited cancer susceptibility disorder resulting from germline mutations in the TP53 tumor suppressor gene.

Case presentation

We report a 49-year-old female patient with hepatic EAML and pancreatic cancer. Because she had previously been diagnosed with bilateral breast cancer at the age of 30, we performed a comprehensive genetic analysis to identify genetic alterations associated with any cancer predisposition syndrome. Whole-exome sequencing of a blood sample identified a heterozygous germline variant of TP53 (NM_000546.5):c.708C>A, and targeted next-generation sequencing of liver EAML and pancreatic cancer tissue samples demonstrated the same TP53 (NM_000546.5):c.708C>A variant in both. This, plus the patient’s history of early-onset breast cancer, met the 2015 version of the Chompret criteria for diagnosis of LFS.

Conclusions

There have been very few case reports regarding the presence of PEComa in LFS, and to the best of our knowledge, this is the first report of EAML of the liver in a patient with LFS.
Physical activity, recreational screen time, and depressive symptoms among Chinese children and adolescents: a three-wave cross-lagged study during the COVID-19 pandemic
Authors: Liu Yujie , Zhang Erliang , Li Huilun , Ge Xin , Hu Fan , Cai Yong , Xiang Mi
Published: January 2024

Background

Longitudinal evidence is lacking on the interplay between lifestyle behaviors and depressive symptoms, especially in the context of the COVID-19 pandemic. This study investigated the changes in physical activity and recreational screen time during the pandemic, along with their reciprocal associations with depressive symptoms among children and adolescents.

Methods

The public health emergency due to the pandemic started in January 2023 and lasted for two months in Shanghai, China. A three-wave longitudinal study was conducted among 1,666 children and adolescents (6–18 years) in January, March, and July 2023. Moderate-to-vigorous intensity physical activity (MVPA), recreational screen time, and depressive symptoms were measured using self-reported questionnaires. Random-intercept cross-lagged panel models were constructed to examine the bidirectional associations between physical activity and recreational screen time with depressive symptoms.

Results

Children and adolescents experienced a significant decrease in MVPA and a substantial increase in recreational screen time during the pandemic, which failed to return to pre-pandemic levels post-pandemic. Pre-pandemic MVPA was negatively associated with subsequent depressive symptoms (β = -0.147). Conversely, pre-pandemic depressive symptoms were positively associated with subsequent recreational screen time (β = 0.085), which in turn predicted heightened post-pandemic depressive symptoms (β = 0.076). When stratified by age, significant associations were found in adolescents but not children.

Conclusions

Sustained unhealthy changes in physical activity and recreational screen time were observed during the COVID-19 pandemic among children and adolescents. This study elucidates a potential reciprocal relationship between lifestyle behaviors and mental well-being. Effective interventions are emphasized to counter the negative impacts of insufficient physical activity and excessive screen use on the mental health of children and adolescents.
Compact CRISPR genetic screens enabled by improved guide RNA library cloning
Authors: Heo Seok-Jin , Enriquez Lauren D. , Federman Scot , Chang Amy Y. , Mace Rachel , Shevade Kaivalya , Nguyen Phuong , Litterman Adam J. , Shafer Shawn , Przybyla Laralynne , Chow Eric D.
Published: January 2024

CRISPR genome editing approaches theoretically enable researchers to define the function of each human gene in specific cell types, but challenges remain to efficiently perform genetic perturbations in relevant models. In this work, we develop a library cloning protocol that increases sgRNA uniformity and greatly reduces bias in existing genome-wide libraries. We demonstrate that our libraries can achieve equivalent or better statistical power compared to previously reported screens using an order of magnitude fewer cells. This improved cloning protocol enables genome-scale CRISPR screens in technically challenging cell models and screen formats.
DeepVelo: deep learning extends RNA velocity to multi-lineage systems with cell-specific kinetics
Authors: Cui Haotian , Maan Hassaan , Vladoiu Maria C. , Zhang Jiao , Taylor Michael D. , Wang Bo
Published: January 2024

Existing RNA velocity estimation methods strongly rely on predefined dynamics and cell-agnostic constant transcriptional kinetic rates, assumptions often violated in complex and heterogeneous single-cell RNA sequencing (scRNA-seq) data. Using a graph convolution network, DeepVelo overcomes these limitations by generalizing RNA velocity to cell populations containing time-dependent kinetics and multiple lineages. DeepVelo infers time-varying cellular rates of transcription, splicing, and degradation, recovers each cell’s stage in the differentiation process, and detects functionally relevant driver genes regulating these processes. Application to various developmental and pathogenic processes demonstrates DeepVelo’s capacity to study complex differentiation and lineage decision events in heterogeneous scRNA-seq data.
Robotic versus Electromagnetic bronchoscopy for pulmonary LesIon AssessmeNT: the RELIANT pragmatic randomized trial
Authors: Paez Rafael , Lentz Robert J. , Salmon Cristina , Siemann Justin K. , Low See-Wei , Casey Jonathan D. , Chen Heidi , Chen Sheau-Chiann , Avasarala Sameer , Shojaee Samira , Rickman Otis B. , Lindsell Christopher J. , Gatto Cheryl L. , Rice Todd W. , Maldonado Fabien ,   for the Vanderbilt Learning Healthcare System Platform Investigators
Published: January 2024

Background

Robotic-assisted bronchoscopy has recently emerged as an alternative to electromagnetic navigational bronchoscopy for the evaluation of peripheral pulmonary lesions. While robotic-assisted bronchoscopy is proposed to have several advantages, such as an easier learning curve, it is unclear if it has comparable diagnostic utility as electromagnetic navigational bronchoscopy.

Methods

Robotic versus Electromagnetic bronchoscopy for pulmonary LesIon AssessmeNT (RELIANT) is an investigator-initiated, single-center, open label, noninferiority, cluster randomized controlled trial conducted in two operating rooms at Vanderbilt University Medical Center. Each operating room (OR) is assigned to either robotic-assisted or electromagnetic navigational bronchoscopy each morning, with each OR day considered one cluster. All patients undergoing diagnostic bronchoscopy for evaluation of a peripheral pulmonary lesion in one of the two operating rooms are eligible. Schedulers, patients, and proceduralists are blinded to daily group allocations until randomization is revealed for each operating room each morning. The primary endpoint is the diagnostic yield defined as the proportion of cases yielding lesional tissue. Secondary and safety endpoints include procedure duration and procedural complications. Enrolment began on March 6, 2023, and will continue until 202 clusters have been accrued, with expected enrolment of approximately 400 patients by the time of completion in March of 2024.

Discussion

RELIANT is a pragmatic randomized controlled trial that will compare the diagnostic yield of the two most commonly used bronchoscopic approaches for sampling peripheral pulmonary lesions. This will be the first known cluster randomized pragmatic trial in the interventional pulmonology field and the first randomized controlled trial of robotic-assisted bronchoscopy.

Trial registration

ClinicalTrials.gov registration (NCT05705544) on January 30, 2023.
Lignin impairs Cel7A degradation of in vitro lignified cellulose by impeding enzyme movement and not by acting as a sink
Authors: Haviland Zachary K. , Nong Daguan , Zexer Nerya , Tien Ming , Anderson Charles T. , Hancock William O.
Published: January 2024

Background

Cellulose degradation by cellulases has been studied for decades due to the potential of using lignocellulosic biomass as a sustainable source of bioethanol. In plant cell walls, cellulose is bonded together and strengthened by the polyphenolic polymer, lignin. Because lignin is tightly linked to cellulose and is not digestible by cellulases, is thought to play a dominant role in limiting the efficient enzymatic degradation of plant biomass. Removal of lignin via pretreatments currently limits the cost-efficient production of ethanol from cellulose, motivating the need for a better understanding of how lignin inhibits cellulase-catalyzed degradation of lignocellulose. Work to date using bulk assays has suggested three possible inhibition mechanisms: lignin blocks access of the enzyme to cellulose, lignin impedes progress of the enzyme along cellulose, or lignin binds cellulases directly and acts as a sink.

Results

We used single-molecule fluorescence microscopy to investigate the nanoscale dynamics of Cel7A from Trichoderma reesei, as it binds to and moves along purified bacterial cellulose in vitro. Lignified cellulose was generated by polymerizing coniferyl alcohol onto purified bacterial cellulose, and the degree of lignin incorporation into the cellulose meshwork was analyzed by optical and electron microscopy. We found that Cel7A preferentially bound to regions of cellulose where lignin was absent, and that in regions of high lignin density, Cel7A binding was inhibited. With increasing degrees of lignification, there was a decrease in the fraction of Cel7A that moved along cellulose rather than statically binding. Furthermore, with increasing lignification, the velocity of processive Cel7A movement decreased, as did the distance that individual Cel7A molecules moved during processive runs.

Conclusions

In an in vitro system that mimics lignified cellulose in plant cell walls, lignin did not act as a sink to sequester Cel7A and prevent it from interacting with cellulose. Instead, lignin both blocked access of Cel7A to cellulose and impeded the processive movement of Cel7A along cellulose. This work implies that strategies for improving biofuel production efficiency should target weakening interactions between lignin and cellulose surface, and further suggest that nonspecific adsorption of Cel7A to lignin is likely not a dominant mechanism of inhibition.
A novel avian intestinal epithelial cell line: its characterization and exploration as an in vitro infection culture model for Eimeria species
Authors: Chen Huifang , Li Juan , Pan Xiaoting , Hu Zhichao , Cai Jianfeng , Xia Zijie , Qi Nanshan , Liao Shenquan , Spritzer Zachary , Bai Yinshan , Sun Mingfei
Published: January 2024

Background

The gastrointestinal epithelium plays an important role in directing recognition by the immune system, and epithelial cells provide the host's front line of defense against microorganisms. However, it is difficult to cultivate avian intestinal epithelial cells in vitro for lengthy periods, and the lack of available cell lines limits the research on avian intestinal diseases and nutritional regulation. Chicken coccidiosis is a serious intestinal disease that causes significant economic losses in the poultry industry. In vitro, some cell line models are beneficial for the development of Eimeria species; however, only partial reproduction can be achieved. Therefore, we sought to develop a new model with both the natural host and epithelial cell phenotypes.

Methods

In this study, we use the SV40 large T antigen (SV40T) gene to generate an immortalized cell line. Single-cell screening technology was used to sort positive cell clusters with epithelial characteristics for passage. Polymerase chain reaction (PCR) identification, immunofluorescence detection, and bulk RNA sequencing analysis and validation were used to check the expression of epithelial cell markers and characterize the avian intestinal epithelial cell line (AIEC). AIECs were infected with sporozoites, and their ability to support the in vitro endogenous development of Eimeria tenella was assessed.

Results

This novel AIEC consistently expressed intestinal epithelial markers. Transcriptome assays revealed the upregulation of genes associated with proliferation and downregulation of genes associated with apoptosis. We sought to compare E. tenella infection between an existing fibroblast cell line (DF-1) and several passages of AIEC and found that the invasion efficiency was significantly increased relative to that of chicken fibroblast cell lines.

Conclusions

An AIEC will serve as a better in vitro research model, especially in the study of Eimeria species development and the mechanisms of parasite–host interactions. Using AIEC helps us understand the involvement of intestinal epithelial cells in the digestive tract and the immune defense of the chickens, which will contribute to the epithelial innate defense against microbial infection in the gastrointestinal tract.

Graphical Abstract
A monoclonal antibody collection for C. difficile typing ?
Authors: Hunault Lise , England Patrick , Barbut Frédéric , Iannascoli Bruno , Godon Ophélie , Déjardin François , Thomas Christophe , Dupuy Bruno , Guo Chunguang , Macdonald Lynn , Gorochov Guy , Sterlin Delphine , Bruhns Pierre
Published: January 2024

Clostridioides difficile is the leading cause of antibiotic-associated diarrhea and pseudomembranous colitis in adults. Various C. difficile strains circulate currently, associated with different outcomes and antibiotic resistance profiles. However, most studies still focus on the reference strain 630 that does not circulate anymore, partly due to the lack of immunological tools to study current clinically important C. difficile PCR ribotypes. The goal of this study was to generate monoclonal antibodies recognizing various epidemic ribotypes of C. difficile. To do so, we immunized mice expressing human variable antibody genes with the Low Molecular Weight (LMW) subunit of the surface layer protein SlpA from various C. difficile strains. Monoclonal antibodies purified from hybridomas bound LMW with high-affinity and whole bacteria from current C. difficile ribotypes with different cross-specificities. This first collection of anti-C. difficile mAbs represent valuable tools for basic and clinical research.
Approximation by bivariate Bernstein–Kantorovich–Stancu operators that reproduce exponential functions
Authors: Su Lian-Ta , Kanat Kadir , Sofyalioğlu Aksoy Melek , Kisakol Merve
Published: January 2024

In this study, we construct a Stancu-type generalization of bivariate Bernstein–Kantorovich operators that reproduce exponential functions. Then, we investigate some approximation results for these operators. We use test functions to prove a Korovkin-type convergence theorem. Then, we show the rate of convergence by the modulus of continuity and give a Voronovskaya-type theorem. We give a covergence comparison about bivariate Bernstein–Kantorovich–Stancu operators and their exponential form.
Norwegian “dugnad” as a rhetorical device in public health communication during the COVID-19 pandemic. A qualitative study from immigrant’s perspectives
Authors: Herrero-Arias Raquel , Halbostad Irina Vladimirovna , Diaz Esperanza
Published: January 2024

Background

During the COVID-19 pandemic, the Norwegian government appealed to the term “national dugnad” in the communication of containment measures as a call for collective action to fight the spread of infection. “Dugnad” is traditionally associated with solidarity, social responsibility, and a communal spirit in the form of volunteer work carried out by a local community. Although the word “dugnad” is difficult to translate to other languages, it was used as a rhetorical device by the government to communicate health-related information during the pandemic. This study aims to explore how immigrants understood and related to the term “dugnad” as used in the context of the COVID-19 pandemic in Norway.

Methods

We conducted 55 semi-structured interviews in 2020 with immigrants from Poland (10), Syria (15), Somalia (10), Sri Lanka (10), and Chile (10). Interviews were conducted in participants’ mother-tongues. We used systematic text condensation following Malterud’s four steps to analyze the data.

Results

The results are organized into three themes corresponding to: (1) meaning making of the term “dugnad”; (2) attitudes towards the term “dugnad”; and (3) reactions to the use of “dugnad” in a public health context. Overall, participants were familiar with the term “dugnad” and positively associated it with volunteering, unity, and a sense of community. However, we found a variety of reactions towards using this term in a public health context, ranging from agreement to disagreement and irritation.

Conclusion

Health communication during pandemics is crucial for maximizing compliance and gaining control of disease spread. In multicultural societies, governments and authorities should be aware of the linguistic and cultural barriers to public health communication if they are to effectively reach the entire population. The use of culturally specific concepts in this context, specially as rhetorical devices, may hinder effective health communication and increase health inequalities.
Buprenorphine misinformation and willingness to treat patients with opioid use disorder among primary care-aligned health care professionals
Authors: Franz Berkeley , Dhanani Lindsay Y. , Hall O. Trent , Brook Daniel L. , Fenstemaker Cheyenne , Simon Janet E. , Miller William C.
Published: January 2024

Background

Buprenorphine is a highly effective medication for opioid use disorder that is underused by health care professionals (HCPs). Medications for opioid use disorder (MOUD) misinformation may be an important barrier to buprenorphine access, but most implementation strategies have aimed to reduce negative attitudes towards patients with opioid use disorder (OUD) rather than misinformation specific to buprenorphine use. In this study, we assessed the degree to which HCPs endorsed misinformation related to buprenorphine, and whether this is associated with willingness to provide care to patients with OUD.

Methods

In September-December of 2022, we surveyed HCPs practicing in Ohio (n = 409). Our primary outcomes included a previously validated 5-item measure of HCP willingness to treat patients with OUD, and three other measures of willingness. Our key independent variable was a study-developed 5-item measure of endorsement of misinformation related to buprenorphine, which assessed beliefs in buprenorphine’s efficacy in managing withdrawal symptoms and reducing overdose deaths as well as beliefs about the role of buprenorphine in achieving remission. We computed descriptive and bivariable statistics and fit regression models predicting each outcome of interest.

Results

On average, HCPs scored 2.34 out of 5.00 (SD = 0.80) on the composite measure of buprenorphine misinformation. 48.41% of participants endorsed at least one piece of misinformation. The most endorsed items were that buprenorphine is ineffective at reducing overdose deaths (M = 2.75, SD =0 .98), and that its use substitutes one drug for another (M = 2.41, SD = 1.25). HCP endorsement of buprenorphine misinformation significantly and negatively predicted willingness to work with patients with OUD (b = − 0.34; 95% CI − 0.46, − 0.21); intentions to increase time spent with this patient population (b = − 0.36; 95% CI − 5.86, − 1.28); receipt of an X-waiver (OR = 0.54, 95% CI 0.38, 0.77); and intention to get an X-waiver (OR: 0.56; 95% CI: 0.33−0.94).

Conclusions

Misinformation is common among HCPs and associated with lower willingness to treat patients with OUD. Implementation strategies to increase MOUD use among HCPs should specifically counter misinformation related to buprenorphine.

Clinical Trial Registration: Clinicaltrials.gov, NCT05505227. Registered 17 August 2022, https://clinicaltrials.gov/ct2/show/NCT05505227
The fusion of multi-omics profile and multimodal EEG data contributes to the personalized diagnostic strategy for neurocognitive disorders
Authors: Han Yan , Zeng Xinglin , Hua Lin , Quan Xingping , Chen Ying , Zhou Manfei , Chuang Yaochen , Li Yang , Wang Shengpeng , Shen Xu , Wei Lai , Yuan Zhen , Zhao Yonghua
Published: January 2024

Background

The increasing prevalence of neurocognitive disorders (NCDs) in the aging population worldwide has become a significant concern due to subjectivity of evaluations and the lack of precise diagnostic methods and specific indicators. Developing personalized diagnostic strategies for NCDs has therefore become a priority.

Results

Multimodal electroencephalography (EEG) data of a matched cohort of normal aging (NA) and NCDs seniors were recorded, and their faecal samples and urine exosomes were collected to identify multi-omics signatures and metabolic pathways in NCDs by integrating metagenomics, proteomics, and metabolomics analysis. Additionally, experimental verification of multi-omics signatures was carried out in aged mice using faecal microbiota transplantation (FMT). We found that NCDs seniors had low EEG power spectral density and identified specific microbiota, including Ruminococcus gnavus, Enterocloster bolteae, Lachnoclostridium sp. YL 32, and metabolites, including L-tryptophan, L-glutamic acid, gamma-aminobutyric acid (GABA), and fatty acid esters of hydroxy fatty acids (FAHFAs), as well as disturbed biosynthesis of aromatic amino acids and TCA cycle dysfunction, validated in aged mice. Finally, we employed a support vector machine (SVM) algorithm to construct a machine learning model to classify NA and NCDs groups based on the fusion of EEG data and multi-omics profiles and the model demonstrated 92.69% accuracy in classifying NA and NCDs groups.

Conclusions

Our study highlights the potential of multi-omics profiling and EEG data fusion in personalized diagnosis of NCDs, with the potential to improve diagnostic precision and provide insights into the underlying mechanisms of NCDs.