bluuebunny/crossref_metadata_2025_split huggingface dataset:
Palm-based tocotrienol-rich fraction (TRF) supplementation modulates cardiac sod1 expression, fxr target gene expression, and tauro-conjugated bile acid levels in aleptinemic mice fed a high-fat diet
Authors: Md Shahrulnizam Nur Aliah Natasha , Mohd Efendy Goon Mohd Danial , Ab Rahim Sharaniza , Lew Sook Weih , Sheikh Abdul Kadir Siti Hamimah , Ibrahim Effendi 
Published: February 2024

AbstractTocotrienol-rich fraction (TRF) has been reported to protect the heart from oxidative stress-induced inflammation. It is, however, unclear whether the protective effects of TRF against oxidative stress involve the activation of farnesoid X receptor (fxr), a bile acid receptor, and the regulation of bile acid metabolites. In the current study, we investigated the effects of TRF supplementation on antioxidant activities, expression of fxr and its target genes in cardiac tissue, and serum untargeted metabolomics of high-fat diet-fed mice. Mice were divided into high-fat diet (HFD) with or without TRF supplementation (control) for 6 weeks. At the end of the intervention, body weight (BW), waist circumference (WC), and random blood glucose were measured. Heart tissues were collected, and the gene expression of sod1, sod2, gpx, and fxr and its target genes shp and stat3 was determined. Serum was subjected to untargeted metabolomic analysis using UHPLC-Orbitrap. In comparison to the control, the WC of the TRF-treated group was higher (p >0.05) than that of the HFD-only group, in addition there was no significant difference in weight or random blood glucose level. Downregulation of sod1, sod2, and gpx expression was observed in TRF-treated mice; however, only sod1 was significant when compared to the HFD only group. The expression of cardiac shp (fxr target gene) was significantly upregulated, but stat3 was significantly downregulated in the TRF-treated group compared to the HFD-only group. Biochemical pathways found to be influenced by TRF supplementation include bile acid secretion, primary bile acid biosynthesis, and biotin and cholesterol metabolism. In conclusion, TRF supplementation in HFD-fed mice affects antioxidant activities, and more interestingly, TRF also acts as a signaling molecule that is possibly involved in several bile acid-related biochemical pathways accompanied by an increase in cardiac fxr shp expression. This study provides new insight into TRF in deregulating bile acid receptors and metabolites in high-fat diet-fed mice.
GPAD: a natural language processing-based application to extract the gene-disease association discovery information from OMIM
Authors: Rahit K. M. Tahsin Hassan , Avramovic Vladimir , Chong Jessica X. , Tarailo-Graovac Maja 
Published: February 2024

Abstract
Background
Thousands of genes have been associated with different Mendelian conditions. One of the valuable sources to track these gene-disease associations (GDAs) is the Online Mendelian Inheritance in Man (OMIM) database. However, most of the information in OMIM is textual, and heterogeneous (e.g. summarized by different experts), which complicates automated reading and understanding of the data. Here, we used Natural Language Processing (NLP) to make a tool (Gene-Phenotype Association Discovery (GPAD)) that could syntactically process OMIM text and extract the data of interest.

Results
GPAD applies a series of language-based techniques to the text obtained from OMIM API to extract GDA discovery-related information. GPAD can inform when a particular gene was associated with a specific phenotype, as well as the type of validation—whether through model organisms or cohort-based patient-matching approaches—for such an association. GPAD extracted data was validated with published reports and was compared with large language model. Utilizing GPAD's extracted data, we analysed trends in GDA discoveries, noting a significant increase in their rate after the introduction of exome sequencing, rising from an average of about 150–250 discoveries each year. Contrary to hopes of resolving most GDAs for Mendelian disorders by now, our data indicate a substantial decline in discovery rates over the past five years (2017–2022). This decline appears to be linked to the increasing necessity for larger cohorts to substantiate GDAs. The rising use of zebrafish and Drosophila as model organisms in providing evidential support for GDAs is also observed.

Conclusions
GPAD’s real-time analyzing capacity offers an up-to-date view of GDA discovery and could help in planning and managing the research strategies. In future, this solution can be extended or modified to capture other information in OMIM and scientific literature.
Combined analysis of mRNA and miRNA transcriptomes reveals the regulatory mechanism of Xanthomonas arboricola pv pruni resistance in Prunus persica
Authors: Zhu Pengxiang , Li Haiyan , Lu Tailiang , Liang Ruizheng , Wan Baoxiong 
Published: February 2024

Abstract
Background
Peach bacterial shot hole, caused by Xanthomonas arboricola pv pruni (Xap), is a global bacterial disease that poses a threat to the yield and quality of cultivated peach trees (Prunus persica).

Results
This study compared the mRNA and miRNA profiles of two peach varieties, ‘Yanbao’ (resistant) and ‘Yingzui’ (susceptible), after inoculation with Xap to identify miRNAs and target genes associated with peach tree resistance. mRNA sequencing results revealed that in the S0-vs-S3 comparison group, 1574 genes were upregulated and 3975 genes were downregulated. In the R0-vs-R3 comparison group, 1575 genes were upregulated and 3726 genes were downregulated. Through miRNA sequencing, a total of 112 known miRNAs belonging to 70 miRNA families and 111 new miRNAs were identified. Notably, some miRNAs were exclusively expressed in either resistant or susceptible varieties. Additionally, 59 miRNAs were downregulated and 69 miRNAs were upregulated in the R0-vs-R3 comparison group, while 46 miRNAs were downregulated and 52 miRNAs were upregulated in the S0-vs-S3 comparison group. Joint analysis of mRNA and miRNA identified 79 relationship pairs in the S0-vs-S3 comparison group, consisting of 48 miRNAs and 51 target genes. In the R0-vs-R3 comparison group, there were 58 relationship pairs, comprising 28 miRNAs and 20 target genes. Several target genes related to resistance, such as SPL6, TIFY6B, and Prupe.4G041800_v2.0.a1 (PPO), were identified through literature reports and GO/KEGG enrichment analysis.

Conclusion
In conclusion, this study discovered several candidate genes involved in peach tree resistance by analyzing differential expression of mRNA and miRNA. These findings provide valuable insights into the mechanisms underlying resistance to Xap in peach trees.
Pangenome analysis of Shewanella xiamenensis revealed important genetic traits concerning genetic diversity, pathogenicity and antibiotic resistance
Authors: Wang Haichen , Xia Fengjun , Xia Yubing , Li Jun , Hu Yongmei , Deng Yating , Zou Mingxiang 
Published: February 2024

Abstract
Background
Shewanella xiamenensis, widely distributed in natural environments, has long been considered as opportunistic pathogen. Recently, significant changes in the resistance spectrum have been observed in S. xiamenensis, due to acquired antibiotic resistance genes. Therefore, a pan-genome analysis was conducted to illuminate the genomic changes in S. xiamenensis.

Results
Phylogenetic analysis revealed three major clusters and three singletons, among which close relationship between several strains was discovered, regardless of their host and niches. The “open” genomes with diversity of accessory and strain-specific genomes took advantage towards diversity environments. The purifying selection pressure was the main force on genome evolution, especially in conservative genes. Only 53 gene families were under positive selection pressure. Phenotypic resistance analysis revealed 21 strains were classified as multi-drug resistance (MDR). Ten types of antibiotic resistance genes and two heavy metal resistance operons were discovered in S. xiamenensis. Mobile genetic elements and horizontal gene transfer increased genome diversity and were closely related to MDR strains. S. xiamenensis carried a variety of virulence genes and macromolecular secretion systems, indicating their important roles in pathogenicity and adaptability. Type IV secretion system was discovered in 15 genomes with various sequence structures, indicating it was originated from different donors through horizontal gene transfer.

Conclusions
This study provided with a detailed insight into the changes in the pan-genome of S. xiamenensis, highlighting its capability to acquire new mobile genetic elements and resistance genes for its adaptation to environment and pathogenicity to human and animals.
Phenotypic, molecular, and in silico characterization of coumarin as carbapenemase inhibitor to fight carbapenem-resistant Klebsiella pneumoniae
Authors: Abdel-Halim Mahmoud Saad , El-Ganiny Amira M. , Mansour Basem , Yahya Galal , Latif Hemat K. Abd El , Askoura Momen 
Published: February 2024

Abstract
Background
Carbapenems represent the first line treatment of serious infections caused by drug-resistant Klebsiella pneumoniae. Carbapenem-resistant K. pneumoniae (CRKP) is one of the urgent threats to human health worldwide. The current study aims to evaluate the carbapenemase inhibitory potential of coumarin and to test its ability to restore meropenem activity against CRKP. Disk diffusion method was used to test the antimicrobial susceptibility of K. pneumoniae clinical isolates to various antibiotics. Carbapenemase genes (NDM-1, VIM-2, and OXA-9) were detected using PCR. The effect of sub-MIC of coumarin on CRKP isolates was performed using combined disk assay, enzyme inhibition assay, and checkerboard assay. In addition, qRT-PCR was used to estimate the coumarin effect on expression of carbapenemase genes. Molecular docking was used to confirm the interaction between coumarin and binding sites within three carbapenemases.

Results
K. pneumoniae clinical isolates were found to be multi-drug resistant and showed high resistance to meropenem. All bacterial isolates harbor at least one carbapenemase-encoding gene. Coumarin significantly inhibited carbapenemases in the crude periplasmic extract of CRKP. The checkerboard assay indicated that coumarin-meropenem combination was synergistic exhibiting a fractional inhibitory concentration index ≤ 0.5. In addition, qRT-PCR results revealed that coumarin significantly decreased carbapenemase-genes expression. Molecular docking revealed that the binding energies of coumarin to NDM1, VIM-2, OXA-48 and OXA-9 showed a free binding energy of -7.8757, -7.1532, -6.2064 and − 7.4331 Kcal/mol, respectively.

Conclusion
Coumarin rendered CRKP sensitive to meropenem as evidenced by its inhibitory action on hydrolytic activity and expression of carbapenemases. The current findings suggest that coumarin could be a possible solution to overcome carbapenems resistance in CRKP.
Digital stressors and resources perceived by emergency physicians and associations to their digital stress perception, mental health, job satisfaction and work engagement
Authors: Bernburg Monika , Tell Anika , Groneberg David A. , Mache Stefanie 
Published: February 2024

Abstract
Background
Digital technologies are increasingly being integrated into healthcare settings, including emergency departments, with the potential to improve efficiency and patient care. Although digitalisation promises many benefits, the use of digital technologies can also introduce new stressors and challenges among medical staff, which may result in the development of various negative work and health outcomes. Therefore, this study aims to identify existing digital stressors and resources among emergency physicians, examine associations with various work- and health-related parameters, and finally identify the potential need for preventive measures.

Methods
In this quantitative cross-sectional study, an online questionnaire was used to examine the relationship between digital stressors (technostress creators), digital resources (technostress inhibitors), technostress perception as well as mental health, job satisfaction and work engagement among 204 physicians working in German emergency medicine departments. Data collection lasted from December 2022 to April 2023. Validated scales were used for the questionnaire (e.g. “Technostress”-scale and the Copenhagen Psychosocial Questionnaire (COPSOQ). Descriptive and multiple regression analyses were run to test explorative assumptions.

Results
The study found medium levels of technostress perception among the participating emergency physicians as well as low levels of persisting technostress inhibitors. The queried physicians on average reported medium levels of exhaustion symptoms, high levels of work engagement and job satisfaction. Significant associations between digital stressors and work- as well as health-related outcomes were analyzed.

Conclusion
This study provides a preliminary assessment of the persistence of digital stressors, digital resources and technostress levels, and their potential impact on relevant health and work-related outcomes, among physicians working in German emergency departments. Understanding and mitigating these stressors is essential to promote the well-being of physicians and ensure optimal patient care. As digitisation processes will continue to increase, the need for preventive support measures in dealing with technology stressors is obvious and should be expanded accordingly in the clinics. By integrating such support into everyday hospital life, medical staff in emergency departments can better focus on patient care and mitigate potential stress factors associated with digital technologies.
Change analysis for intermediate disease markers in nutritional epidemiology: a causal inference perspective
Authors: Tang Dan , Hu Yifan , Zhang Ning , Xiao Xiong , Zhao Xing 
Published: February 2024

Abstract
Background
Several approaches are commonly used to estimate the effect of diet on changes of various intermediate disease markers in prospective studies, including “change-score analysis”, “concurrent change-change analysis” and “lagged change-change analysis”. Although empirical evidence suggests that concurrent change-change analysis is most robust, consistent, and biologically plausible, in-depth dissection and comparison of these approaches from a causal inference perspective is lacking. We intend to explicitly elucidate and compare the underlying causal model, causal estimand and interpretation of these approaches, intuitively illustrate it with directed acyclic graph (DAG), and further clarify strengths and limitations of the recommended concurrent change-change analysis through simulations.

Methods
Causal model and DAG are deployed to clarify the causal estimand and interpretation of each approach theoretically. Monte Carlo simulation is used to explore the performance of distinct approaches under different extents of time-invariant heterogeneity and the performance of concurrent change-change analysis when its causal identification assumptions are violated.

Results
Concurrent change-change analysis targets the contemporaneous effect of exposure on outcome (measured at the same survey wave), which is more relevant and plausible in studying the associations of diet and intermediate biomarkers in prospective studies, while change-score analysis and lagged change-change analysis target the effect of exposure on outcome after one-period timespan (typically several years). Concurrent change-change analysis always yields unbiased estimates even with severe unobserved time-invariant confounding, while the other two approaches are always biased even without time-invariant heterogeneity. However, concurrent change-change analysis produces almost linearly increasing estimation bias with violation of its causal identification assumptions becoming more serious.

Conclusions
Concurrent change-change analysis might be the most superior method in studying the diet and intermediate biomarkers in prospective studies, which targets the most plausible estimand and circumvents the bias from unobserved individual heterogeneity. Importantly, careful examination of the vital identification assumptions behind it should be underscored before applying this promising method.
Impact of COVID-19 pandemic on pediatric dental procedures in primary healthcare settings in Piracicaba, Brazil: an ecological study
Authors: Figueiredo dos Santos Rúbia Vanessa , Bado Fernanda Maria Rovai , da Cunha Inara Pereira , de Castro Meneghim Marcelo 
Published: February 2024

AbstractBackgroundThe COVID-19 pandemic brought significant changes to dental care, which may have affected pediatric dental care offered in primary healthcare settings. Therefore, the aim of this study was to analyze the quantity of dental procedures performed in primary healthcare for children aged 6 to 12 years, before and during the COVID-19 pandemic.MethodsThis is an ecological study using data from the health information system of Piracicaba, São Paulo, Brazil. The variables considered were: coverage of first programmed dental consultation, restoration of permanent and deciduous teeth, topical fluoride application (individual per session), emergency care, and deciduous tooth extraction. Two periods were considered: period I (March 1, 2019 to February 29, 2020) and period II (April 1, 2020 to March 31, 2021), before and during the pandemic, respectively. Comparisons between periods were made using the paired nonparametric Wilcoxon test with a significance level of 5%.ResultsThere was an increase in emergency care from 15.4 to 32.4% (p = 0.0095) and a decrease in the number of restorations of deciduous teeth from 32.8 to 20.2% (p = 0.0217). The first programmed consultation showed a decrease of 9.60% (p = 0.0930) in period II.ConclusionsThe COVID-19 pandemic has hindered access to primary dental care for children, impacting the quantity of emergency care, reducing restorations of deciduous teeth, and first programmed dental consultations. These findings highlight the need for strategies to ensure that pediatric dental care is not neglected during pandemics.
Effect of home-based lifestyle interventions on cognition in older adults with mild cognitive impairment: a systematic review
Authors: Zou Cynthia , Amos-Richards Divinity , Jagannathan Ram , Kulshreshtha Ambar 
Published: February 2024

Abstract
Background
Mild Cognitive Impairment (MCI) is frequently a precursor to dementia, affecting aspects of cognition such as language, thinking, or memory. Lifestyle interventions are increasingly studied as potential means to slow the progression from MCI to dementia.

Objective
A systematic review was conducted to investigate the effectiveness of home-based lifestyle interventions in reducing cognitive decline in older adults with MCI.

Methods
A systematic review of randomized controlled trials (RCTs) was conducted to identify home-based lifestyle interventions for individuals with MCI from 1980 to 2023. These interventions were either single-component or multi-component and included diet, physical activity, stress-reduction, or cognitive stimulation treatments to assess their impact on cognition. We performed a comprehensive search in the PubMed, Web of Science, Google Scholar, Embase, and MEDLINE databases.

Results
From 320 abstracts, 20 (6.25%) studies met the criteria for inclusion, with five multi-component and fifteen single-component studies. Eighteen home-based lifestyle interventions for MCI patients were focused on physical activity, diet, and/or cognitive training, while two studies were identified that incorporated stress reduction training as a method to improve cognitive function. Nineteen studies reported significant improvements in cognitive performance between the experimental and control groups post-intervention for at least one aspect of cognition. Four studies reported nonsignificant improvements in cognitive function between the two groups for at least one area of cognition.

Conclusions
Home-based lifestyle interventions have the potential to improve cognition in elderly patients with MCI. However, future RCTs with larger sample sizes and longer intervention durations are needed to confirm these findings.
Exploration of subgroups and predictors of loneliness among older adults in rural China: A latent profile analysis
Authors: Wang Yuecong , Li Shasha , Zou Xiaoyue , Ni Yingyuan , Xu Lijun , Liao Shufang , Cao Lijun , Bao Jianyi , Li Yue , Xi Yingxue 
Published: February 2024

Abstract
Background
Loneliness is a negative emotional state that can lead to physical and mental health problems. This study’s objective was to acquire an in-depth understanding of the heterogeneity and the predictors of loneliness among older adults in rural China and provide valuable references for practical interventions.

Methods
Older rural adults in China (N = 680) were recruited between January and April 2023. Latent profile analysis (LPA) was employed to identify subgroups of loneliness among participants. Single-factor and multinomial logistic regression analyses were conducted to investigate predictors of loneliness.

Results
The loneliness of rural older adults could be divided into three subgroups: low interaction loneliness group (55.0%), moderate emotional loneliness group (31.8%), and high loneliness group (13.2%). The subgroup predictors included age, gender, religious beliefs, marital status, living alone, number of chronic diseases, and smartphone use (P < 0.05).

Conclusion
This study identified a classification pattern for loneliness among older adults in rural areas of China, revealed the characteristics of different demographic variables in loneliness categories, and highlighted the heterogeneity of loneliness in this population. It serves as a theoretical reference for formulating intervention plans aimed at addressing various loneliness categories for local rural older adults.

Clinical trial registration
ChiCTR2300071591.
Automated machine learning for the identification of asymptomatic COVID-19 carriers based on chest CT images
Authors: Yin Minyue , Xu Chao , Zhu Jinzhou , Xue Yuhan , Zhou Yijia , He Yu , Lin Jiaxi , Liu Lu , Gao Jingwen , Liu Xiaolin , Shen Dan , Fu Cuiping 
Published: February 2024

Abstract
Background
Asymptomatic COVID-19 carriers with normal chest computed tomography (CT) scans have perpetuated the ongoing pandemic of this disease. This retrospective study aimed to use automated machine learning (AutoML) to develop a prediction model based on CT characteristics for the identification of asymptomatic carriers.

Methods
Asymptomatic carriers were from Yangzhou Third People’s Hospital from August 1st, 2020, to March 31st, 2021, and the control group included a healthy population from a nonepizootic area with two negative RT‒PCR results within 48 h. All CT images were preprocessed using MATLAB. Model development and validation were conducted in R with the H2O package. The models were built based on six algorithms, e.g., random forest and deep neural network (DNN), and a training set (n = 691). The models were improved by automatically adjusting hyperparameters for an internal validation set (n = 306). The performance of the obtained models was evaluated based on a dataset from Suzhou (n = 178) using the area under the curve (AUC), accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and F1 score.

Results
A total of 1,175 images were preprocessed with high stability. Six models were developed, and the performance of the DNN model ranked first, with an AUC value of 0.898 for the test set. The sensitivity, specificity, PPV, NPV, F1 score and accuracy of the DNN model were 0.820, 0.854, 0.849, 0.826, 0.834 and 0.837, respectively. A plot of a local interpretable model-agnostic explanation demonstrated how different variables worked in identifying asymptomatic carriers.

Conclusions
Our study demonstrates that AutoML models based on CT images can be used to identify asymptomatic carriers. The most promising model for clinical implementation is the DNN-algorithm-based model.