bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comparative and phylogenetic analysis of the complete chloroplast genomes of 10 Artemisia selengensis resources based on high-throughput sequencing
Authors: Wang Yuhang , Wei Qingying , Xue Tianyuan , He Sixiao , Fang Jiao , Zeng Changli 
Published: June 2024

Abstract
Background
Artemisia selengensis, classified within the genus Artemisia of the Asteraceae family, is a perennial herb recognized for its dual utility in culinary and medicinal domains. There are few studies on the chloroplast genome of A. selengensis, and the phylogeographic classification is vague, which makes phylogenetic analysis and evolutionary studies very difficult.

Results
The chloroplast genomes of 10 A. selengensis in this study were highly conserved in terms of gene content, gene order, and gene intron number. The genome lengths ranged from 151,148 to 151,257 bp and were typical of a quadripartite structure with a total GC content of approximately 37.5%. The chloroplast genomes of all species encode 133 genes, including 88 protein-coding genes, 37 tRNA genes, and 8 rRNA genes. Due to the contraction and expansion of the inverted repeats (IR), the overlap of ycf1 and ndhF genes occurred at the inverted repeats B (IRB) and short single copy sequence (SSC) boundaries. According to a codon use study, the frequent base in the chloroplast genome of A. selengensis’ third codon position was A/T. The number of SSR repeats was 42–44, most of which were single nucleotide A/T repeats. Sequence alignment analysis of the chloroplast genome showed that variable regions were mainly distributed in single copy regions, nucleotide diversity values of 0 to 0.009 were calculated by sliding window analysis, 8 mutation hotspot regions were detected, and coding regions were more conserved than non-coding regions. Analysis of non-synonymous substitution (Ka) and synonymous substitution (Ks) revealed that accD, rps12, petB, and atpF genes were affected by positive selection and no genes were affected by neutral selection. Based on the findings of the phylogenetic analysis, Artemisia selengensis was sister to the genus Artemisia Chrysanthemum and formed a monophyletic group with other Artemisia genera.

Conclusions
In this research, the present study systematically compared the chloroplast genomic features of A. selengensis and provided important information for the study of the chloroplast genome of A. selengensis and the evolutionary relationships among Asteraceae species.
Genome-wide characterization, functional analysis, and expression profiling of the Aux/IAA gene family in spinach
Authors: Imani Asl Erfan , Soorni Aboozar , Mehrabi Rahim 
Published: June 2024

Abstract
Background
The auxin/indole-3-acetic acid (Aux/IAA) gene family is a crucial element of the auxin signaling pathway, significantly influencing plant growth and development. Hence, we conducted a comprehensive investigation of Aux/IAAs gene family using the Sp75 and Monoe-Viroflay genomes in spinach.

Results
A total of 24 definitive Aux/IAA genes were identified, exhibiting diverse attributes in terms of amino acid length, molecular weight, and isoelectric points. This diversity underscores potential specific roles within the family, such as growth regulation and stress response. Structural analysis revealed significant variations in gene length and molecular weight. These variations indicate distinct roles within the Aux/IAA gene family. Chromosomal distribution analysis exhibited a dispersed pattern, with chromosomes 4 and 1 hosting the highest and lowest numbers of Aux/IAA genes, respectively. Phylogenetic analysis grouped the identified genes into distinct clades, revealing potential evolutionary relationships. Notably, the phylogenetic tree highlighted specific gene clusters suggesting shared genetic ancestry and potential functional synergies within spinach. Expression analysis under NAA treatment unveiled gene-specific and time-dependent responses, with certain genes exhibiting distinct temporal expression patterns. Specifically, SpoIAA5 displayed a substantial increase at 2 h post-NAA treatment, while SpoIAA7 and SpoIAA9 demonstrated continuous rises, peaking at the 4-hour time point.

Conclusions
These observations indicate a complex interplay of gene-specific and temporal regulation in response to auxin. Moreover, the comparison with other plant species emphasized both shared characteristics and unique features in Aux/IAA gene numbers, providing insights into the evolutionary dynamics of this gene family. This comprehensive characterization of Aux/IAA genes in spinach not only establishes the foundation for understanding their specific functions in spinach development but also provides a valuable resource for experimental validation and further exploration of their roles in the intricate network of auxin signaling pathways.
Integrated metabolomic and transcriptomic analysis reveals the regulatory mechanisms of flavonoid and alkaloid biosynthesis in the new and old leaves of Murraya tetramera Huang
Authors: Zhou Tao , Xing Qinqin , Bu Jiahao , Han Wenjun , Shen Zhiguo 
Published: June 2024

Abstract
Background
Murraya tetramera Huang is a traditional Chinese woody medicine. Its leaves contain flavonoids, alkaloids, and other active compounds, which have anti-inflammatory and analgesic effects, as well as hypoglycemic and lipid-lowering effects, and anti-tumor effects. There are significant differences in the content of flavonoids and alkaloids in leaves during different growth cycles, but the synthesis mechanism is still unclear.

Results
In April 2021, new leaves (one month old) and old leaves (one and a half years old) of M. tetramera were used as experimental materials to systematically analyze the changes in differentially expressed genes (DEGs) and differentially accumulated metabolites (DAMs) with transcriptomics and metabolomics technology. This was done to identify the signaling pathways of flavonoid and alkaloid synthesis. The results showed that the contents of total alkaloids and flavonoids in old leaves were significantly higher than those in new leaves. Thirteen flavonoid compounds, three isoflavone compounds, and nineteen alkaloid compounds were identified, and 125 and 48 DEGs related to flavonoid and alkaloid synthesis were found, respectively. By constructing the KEGG (Kyoto Encyclopedia of Genes and Genomes) network of DEGs and DAMs, it was shown that the molecular mechanism of flavonoid biosynthesis in M. tetramera mainly focuses on the “flavonoid biosynthetic pathway” and the “flavonoid and flavonol biosynthetic pathway”. Among them, p-Coumaryl alcohol, Sinapyl alcohol, Phloretin, and Isoquercitrin were significantly accumulated in old leaves, the up-regulated expression of CCR (cinnamoyl-CoA reductase) might promote the accumulation of p-Coumaryl alcohol, upregulation of F5H (ferulate-5-hydroxylase) might promote Sinapyl alcohol accumulation. Alkaloids, including indole alkaloids, pyridine alkaloids, imidazole alkaloids, and quinoline alkaloids, were significantly accumulated in old leaves, and a total of 29 genes were associated with these substances.

Conclusions
These data are helpful to better understand the biosynthesis of flavonoids and alkaloids in M. tetramera and provide a scientific basis for the development of medicinal components in M. tetramera.
Low Hartmann’s procedure versus abdominoperineal resection for rectal cancer, a propensity score matching cohort study
Authors: Zhang Xubing , Liu Shaojun , Liu Liu , Zhu Zhiqiang 
Published: June 2024

Abstract
Background
This study aimed to compare low Hartmann’s procedure (LHP) with abdominoperineal resection (APR) for rectal cancer (RC) regarding postoperative complications.

Method
RC patients receiving radical LHP or APR from 2015 to 2019 in our center were retrospectively enrolled. Patients’ demographic and surgical information was collected and analyzed. Propensity score matching (PSM) was used to balance the baseline information. The primary outcome was the incidence of major complications. All the statistical analysis was performed by SPSS 22.0 and R.

Results
342 individuals were primarily included and 134 remained after PSM with a 1:2 ratio (50 in LHP and 84 in APR). Patients in the LHP group were associated with higher tumor height (P < 0.001). No significant difference was observed between the two groups for the incidence of major complications (6.0% vs. 1.2%, P = 0.290), and severe pelvic abscess (2% vs. 0%, P = 0.373). However, the occurrence rate of minor complications was significantly higher in the LHP group (52% vs. 21.4%, P < 0.001), and the difference mainly lay in abdominal wound infection (10% vs. 0%, P = 0.006) and bowel obstruction (16% vs. 4.8%, P = 0.028). LHP was not the independent risk factor of pelvic abscess in the multivariate analysis.

Conclusion
Our data demonstrated a comparable incidence of major complications between LHP and APR. LHP was still a reliable alternative in selected RC patients when primary anastomosis was not recommended.
Mental health and quality of life in patients with chronic liver disease: a single-center structural equation model
Authors: Jafree Sara Rizvi , Naveed Ammara , Ahsan Humna , Burhan Syeda Khadija , Khan Masha Asad , Khawar Amna , Fischer Florian 
Published: June 2024

Abstract
Background
Chronic liver disease (CLD) is one of the leading disease burdens in Pakistan. Until now, there has only been limited focus in the country on providing health services through tertiary services in urban cities, whereas there is almost no research in Pakistan on the mental health and quality of life of CLD patients. This study aimed to understand which predictors influence the mental health and quality of life of CLD patients in order to advise better policy protection.

Methods
Data was collected from CLD patients at the Pakistan Kidney and Liver Institute and Research Centre, Lahore, Pakistan. A total of 850 respondents were part of the final sample. The age of respondents ranged from 18 to 79 years and included the following diagnosis: (i) Chronic Viral Hepatitis (n = 271), (ii) Cirrhosis (n = 259), (iii) Hepatocellular Carcinoma (n = 193), and (iv) Non-viral Liver Disease (n = 127).

Results
Mean results reveal that females as well as illiterate patients need more support for mental health and communication with their physician; whereas men need more support to develop coping strategies. Structural equation modelling results reveal that the severity of symptoms (β = 0.24, p < 0.001), coping strategies (β=-0.51, p < 0.001), and doctor communication (β=-0.35, p < 0.001) predict mental health. Quality of life is associated with the severity of symptoms (β=-0.36, p < 0.001), coping strategies (β = 0.26, p < 0.05), and doctor communication (β = 0.09, p < 0.05).

Conclusions
A ‘bio-psycho-social-spiritual’ model is recommended for Pakistan’s CLD patients which includes the integration of social officers to provide support in four key areas to secure mental health and quality of life of patients.
Prevalence and associated risk factors of sarcopenia in community-dwelling older adults in Pakistan: a cross-sectional study
Authors: Altaf Shafaq , Malmir Kazem , Mir Syed Mohsen , Olyaei Gholam Reza , Aftab Anam , Rajput Tausif Ahmed 
Published: June 2024

Abstract
Background
Advancements in medical facilities have led to an increase in global life expectancy, emphasizing the need to address age-related health issues. Sarcopenia, characterized by muscle mass loss, poses significant challenges for older adults. Despite a higher prevalence in Asian populations, there is a remarkable absence of studies addressing sarcopenia among the older adults in Pakistan. This research aims to determine sarcopenia prevalence, identify risk factors, and explore gender- and age-specific patterns among older adults in Pakistan.

Methods
A cross-sectional study involving 142 participants (65 males, 77 females) aged 60 and above was conducted using DEXA scans. Over a six-month period from January to June 2023, data were collected from the Islamabad Diagnostic Centre. This comprehensive dataset covered anthropometric measurements, body composition details, and health parameters. Statistical analyses, including logistic regression, were employed to examine the associations between sarcopenia and various factors.

Results
Sarcopenia manifested in 47.18% of the older adult population (n = 142), with a distribution of 39 males (60%) and 28 females (36.36%). The investigation unveiled a compelling correlation between underweight status and sarcopenia across genders. Indeed, males exhibited a significant negative correlation between skeletal muscle mass index and age, whereas females did not show a statistically significant association. Males presented higher odds of sarcopenia in comparison to females (Odds Ratio [OR] = 2.63, 95% Confidence Interval [CI]: 1.33–5.18, p = 0.005). Age (OR = 1.12, 95% CI: 1.02–1.22, p = 0.014), lower BMI (OR = 0.35, 95% CI: 0.20–0.60, p < 0.001), and reduced body fat percentage (OR = 1.75, 95% CI: 1.31–2.33, p < 0.001) emerged as significant contributors to sarcopenia. These detailed gender-specific findings emphasize the importance of customizing intervention strategies to address gender disparities in sarcopenia risk factors.

Conclusion
This study highlights the significant prevalence of sarcopenia among older adults in Pakistan, with distinct gender and age-related patterns observed. The overall prevalence of sarcopenia was found to be 47.18%, with higher rates among males compared to females. Age emerged as a significant risk factor, with each additional year increasing the odds of sarcopenia. Furthermore, weight, BMI, lean mass, and total body fat demonstrated important associations with sarcopenia prevalence, highlighting the multifaceted nature of this condition. The practical implications of this study emphasize the need for targeted screening programs and personalized interventions to mitigate sarcopenia’s impact, informing healthcare policies and public health strategies in Pakistan.
Development and validation of a social alienation predictive model for older maintenance hemodialysis patients based on latent profile analysis—a cross-sectional study
Authors: Wang Guannan , Dong Jing , Zhu Na , Zhu Yiping 
Published: June 2024

Abstract
Background
Social alienation refers to the state of feeling isolated, helpless, and unsatisfied due to maintaining distance from others or avoiding social interaction and activities. This phenomenon is caused by a lack of social skills, social anxiety, physical health problems, and other reasons. Older maintenance hemodialysis patients are exposed to a higher risk of social alienation. However, previous studies have been performed using the total score of the scale, which does not allow the identification of the characteristics of various patient groups with different levels of social alienation. In contrast, latent profile analysis can classify individuals into different categories based on continuous observational indicators, which improves accuracy and provides a more objective assessment by accounting for the uncertainty of variables. Given the concealed nature of social alienation and the differences in characteristics and treatment measures between different profiles, developing a predictive model for social alienation in older maintenance hemodialysis patients holds significance.

Objective
To explore the latent profile analysis of social alienation in older maintenance hemodialysis patients and to develop and validate a predictive model for social alienation in this population.

Methods
A total of 350 older maintenance hemodialysis patients were selected as the study subjects using convenience sampling. A cross-sectional survey was conducted using a general information questionnaire, the Generalized Alienation Scale, and the Self-Perceived Burden Scale. Based on the results of the Generalized Alienation Scale, a latent profile analysis was performed, followed by univariate analysis and multinomial logistic regression to develop a predictive model. The effectiveness of the predictive model was evaluated in terms of its authenticity, reliability, and predictive ability.

Results
Three hundred nineteen valid questionnaires were collected. The social alienation of older maintenance hemodialysis patients based on latent profile analysis were divided into three profiles, which were named the low/medium/high-symptom groups, comprising 21%, 38.9%, and 40.1% of participants, respectively. Based on male, monthly social activity hours, Age-Adjusted Charlson Comorbidity Index, dialysis age, and Self-Perceived Burden Scale, a predictive model of social alienation for older maintenance hemodialysis patients was developed, and the Hosmer–Lemeshow tests showed no statistical significance (P > 0.05). The model has high predictive efficiency in authenticity, reliability and predictability.

Conclusion
Older maintenance hemodialysis patients exhibited moderate to high levels of social alienation. The latent profile analysis based method was used to divide patients into low/medium/high-symptom profiles, and the predictive model demonstrates excellent authenticity, reliability, and predictability.
The impact of colistin-based regimens on mortality compared to other antimicrobials in patients with carbapenem-resistant Enterobacterales bacteremia in South African hospitals: a cross-sectional study
Authors: Ngoma Nqobile , Perovic Olga , de Voux Alex , Musekiwa Alfred , Shuping Liliwe ,   for GERMS-SA
Published: June 2024

Abstract
Background
Treatment of carbapenem-resistant Enterobacterales (CRE) infections in low-resource settings is challenging particularly due to limited treatment options. Colistin is the mainstay drug for treatment; however, nephrotoxicity and neurotoxicity make this drug less desirable. Thus, mortality may be higher among patients treated with alternative antimicrobials that are potentially less efficacious than colistin. We assessed mortality in patients with CRE bacteremia treated with colistin-based therapy compared to colistin-sparing therapy.

Methods
We conducted a cross-sectional study using secondary data from a South African national laboratory-based CRE bacteremia surveillance system from January 2015 to December 2020. Patients hospitalized at surveillance sentinel sites with CRE isolated from blood cultures were included. Multivariable logistic regression modeling, with multiple imputations to account for missing data, was conducted to determine the association between in-hospital mortality and colistin-based therapy versus colistin-sparing therapy.

Results
We included 1 607 case-patients with a median age of 29 years (interquartile range [IQR], 0–52 years) and 53% (857/1 607) male. Klebsiella pneumoniae caused most of the infections (82%, n=1 247), and the most common carbapenemase genes detected were blaOXA-48-like (61%, n=551), and blaNDM (37%, n=333). The overall in-hospital mortality was 31% (504/1 607). Patients treated with colistin-based combination therapy had a lower case fatality ratio (29% [152/521]) compared to those treated with colistin-sparing therapy 32% [352/1 086]) (p=0.18). In our imputed model, compared to colistin-sparing therapy, colistin-based therapy was associated with similar odds of mortality (adjusted odds ratio [aOR] 1.02; 95% confidence interval [CI] 0.78-1.33, p=0.873).

Conclusion
In our resource-limited setting, the mortality risk in patients treated with colistin-based therapy was comparable to that of patients treated with colistin-sparing therapy. Given the challenges with colistin treatment and the increasing resistance to alternative agents, further investigations into the benefit of newer antimicrobials for managing CRE infections are needed.
Spatial and geometric learning for classification of breast tumors from multi-center ultrasound images: a hybrid learning approach
Authors: Ru Jintao , Zhu Zili , Shi Jialin 
Published: June 2024

Abstract
Background
Breast cancer is the most common cancer among women, and ultrasound is a usual tool for early screening. Nowadays, deep learning technique is applied as an auxiliary tool to provide the predictive results for doctors to decide whether to make further examinations or treatments. This study aimed to develop a hybrid learning approach for breast ultrasound classification by extracting more potential features from local and multi-center ultrasound data.

Methods
We proposed a hybrid learning approach to classify the breast tumors into benign and malignant. Three multi-center datasets (BUSI, BUS, OASBUD) were used to pretrain a model by federated learning, then every dataset was fine-tuned at local. The proposed model consisted of a convolutional neural network (CNN) and a graph neural network (GNN), aiming to extract features from images at a spatial level and from graphs at a geometric level. The input images are small-sized and free from pixel-level labels, and the input graphs are generated automatically in an unsupervised manner, which saves the costs of labor and memory space.

Results
The classification AUCROC of our proposed method is 0.911, 0.871 and 0.767 for BUSI, BUS and OASBUD. The balanced accuracy is 87.6%, 85.2% and 61.4% respectively. The results show that our method outperforms conventional methods.

Conclusions
Our hybrid approach can learn the inter-feature among multi-center data and the intra-feature of local data. It shows potential in aiding doctors for breast tumor classification in ultrasound at an early stage.
A miRNA-disease association prediction model based on tree-path global feature extraction and fully connected artificial neural network with multi-head self-attention mechanism
Authors: Biyu Hou , Mengshan Li , Yuxin Hou , Ming Zeng , Nan Wang , Lixin Guan 
Published: June 2024

Abstract
Background
MicroRNAs (miRNAs) emerge in various organisms, ranging from viruses to humans, and play crucial regulatory roles within cells, participating in a variety of biological processes. In numerous prediction methods for miRNA-disease associations, the issue of over-dependence on both similarity measurement data and the association matrix still hasn’t been improved. In this paper, a miRNA-Disease association prediction model (called TP-MDA) based on tree path global feature extraction and fully connected artificial neural network (FANN) with multi-head self-attention mechanism is proposed. The TP-MDA model utilizes an association tree structure to represent the data relationships, multi-head self-attention mechanism for extracting feature vectors, and fully connected artificial neural network with 5-fold cross-validation for model training.

Results
The experimental results indicate that the TP-MDA model outperforms the other comparative models, AUC is 0.9714. In the case studies of miRNAs associated with colorectal cancer and lung cancer, among the top 15 miRNAs predicted by the model, 12 in colorectal cancer and 15 in lung cancer were validated respectively, the accuracy is as high as 0.9227.

Conclusions
The model proposed in this paper can accurately predict the miRNA-disease association, and can serve as a valuable reference for data mining and association prediction in the fields of life sciences, biology, and disease genetics, among others.

Graphical Abstract