bluuebunny/crossref_metadata_2025_split huggingface dataset:
A self-controlled case series study to measure the risk of SARS-CoV-2 infection associated with attendance at sporting and cultural events: the UK Events Research Programme events
Authors: Douglas Ian J. , Peh Jerlyn , Mansfield Kathryn E. , Trelfa Anna , Fowler Tom , Boulter Matthew , Cleary Paul , Smith Jenifer , Edmunds W. John 
Published: March 2024

Abstract
Background
In 2021, whilst societies were emerging from major social restrictions during the SARS-CoV-2 pandemic, the UK government instigated an Events Research Programme to examine the risk of COVID-19 transmission from attendance at cultural events and explore ways to enable people to attend a range of events whilst minimising risk of transmission. We aimed to measure any impact on risk of COVID-19 transmission from attendance at events held at or close to commercially viable capacity using routinely collected data.

Methods
Data were obtained on attendees at Phase 3 Events Research Programme events, for which some infection risk mitigation measures were in place (i.e. evidence of vaccination or a negative lateral flow test). Attendance data were linked with COVID-19 test result data from the UK Test and Trace system. Using a self-controlled case series design, we measured the within person incidence rate ratio for testing positive for COVID-19, comparing the rate in days 3 to 9 following event attendance (high risk period) with days 1 and 2 and 10–16 (baseline period). Rate ratios were adjusted for estimates of underlying regional COVID-19 prevalence to account for population level fluctuations in infection risk, and events were grouped into broadly similar types.

Results
From attendance data available for 188,851 attendees, 3357 people tested positive for COVID-19 during the observation period. After accounting for total testing trends over the period, incidence rate ratios and 95% confidence intervals for positive tests were 1.16 (0.53–2.57) for indoor seated events, 1.12 (0.95–1.30) for mainly outdoor seated events, 0.65 (0.51–0.83) for mainly outdoor partially seated events, and 1.70 (1.52–1.89) for mainly outdoor unseated multi-day events.

Conclusions
For the majority of event types studied in the third phase of the UK Events Research Programme, we found no evidence of an increased risk of COVID-19 transmission associated with event attendance. However, we found a 70% increased risk of infection associated with attendance at mainly outdoor unseated multi-day events. We have also demonstrated a novel use for self-controlled case series methodology in monitoring infection risk associated with event attendance.
Coexistence of blaIMP−4 and blaSFO−1 in an IncHI5B plasmid harbored by tigecycline-non-susceptible Klebsiella variicola strain
Authors: Chen Hui , Xu Hao , Liu Ruishan , Shen Jian , Zheng Beiwen , Li Lanjuan 
Published: March 2024

Abstract
Background
Klebsiella variicola is considered a newly emerging human pathogen. Clinical isolates of carbapenemase and broad-spectrum β-lactamase-producing K. variicola remain relatively uncommon. A strain of K. variicola 4253 was isolated from a clinical sample, and was identified to carry the blaIMP−4 and blaSFO−1 genes. This study aims to discern its antibiotic resistance phenotype and genomic characteristics.

Methods
Species identification was conducted using MALDI-TOF/MS. PCR identification confirmed the presence of the blaIMP−4 and blaSFO−1 genes. Antibiotic resistance phenotype and genomic characteristics were detected by antimicrobial susceptibility testing and whole-genome sequencing. Plasmid characterization was carried out through S1-PFGE, conjugation experiments, Southern blot, and comparative genomic analysis.

Results
K. variicola 4253 belonged to ST347, and demonstrated resistance to broad-spectrum β-lactamase drugs and tigecycline while being insensitive to imipenem and meropenem. The blaIMP−4 and blaSFO−1 genes harbored on the plasmid p4253-imp. The replicon type of p4253-imp was identified as IncHI5B, representing a multidrug-resistant plasmid capable of horizontal transfer and mediating the dissemination of drug resistance. The blaIMP−4 gene was located on the In809-like integrative element (Intl1-blaIMP−4-aacA4-catB3), which circulates in Acinetobacter and Enterobacteriaceae.

Conclusions
This study reports the presence of a strain of K. variicola, which is insensitive to tigecycline, carrying a plasmid harboring blaIMP−4 and blaSFO−1. It is highly likely that the strain acquired this plasmid through horizontal transfer. The blaIMP−4 array (Intl1-blaIMP−4-aacA4-catB3) is also mobile in Acinetobacter and Enterobacteriaceae. So it is essential to enhance clinical awareness and conduct epidemiological surveillance on multidrug-resistant K. variicola, conjugative plasmids carrying blaIMP−4, and the In809 integrative element.
Nanoplastics causes heart aging/myocardial cell senescence through the Ca2+/mtDNA/cGAS-STING signaling cascade
Authors: Wang Kaihao , Du Yipeng , Li Peixin , Guan Chang , Zhou Min , Wu Lanlan , Liu Zengfu , Huang Zheng 
Published: March 2024

Abstract
Background
Nanoplastics (NPs) are now a new class of pollutants widely present in the soil, atmosphere, freshwater and marine environments. Nanoplastics can rapidly penetrate cell membranes and accumulate in human tissues and organs, thus posing a potential threat to human health. The heart is the main power source of the body. But up to now, the toxicological effects of long-term exposure to nanoplastics on the heart has not been revealed yet.

Results
We evaluated the effects of long term exposure of nanoplastics on cardiac cell/tissue in vitro and in vivo model. Furthermore, we explored the molecular mechanism by which nanoplastics exposure causes myocardial cell senescence. Immunohistochemistry, indirect immunofluorescence and ELISA were performed to detect the effects of nanoplastics on heart aging. We found that nanoplastics were able to induce significant cardiac aging through a series of biochemical assays in vivo. In vitro, the effects of nanoplastics on cardiac cell were investigated, and found that nanoplastics were able to internalize into cardiomyocytes in time and dose-dependant manner. Further biochemical analysis showed that nanoplastics induces cardiomyocytes senescence by detecting a series of senescence marker molecules. Molecular mechanism research shows that nanoplastics may cause mitochondrial destabilization by inducing oxidative stress, which leads to the leakage of mtDNA from mitochondria into the cytoplasm, and then cytoplasm-localized mt-DNA activates the cGAS-STING signaling pathway and promotes inflammation response, ultimately inducing cardiomyocytes senescence.

Conclusions
In this work, we found that nanoplastics exposure induces premature aging of heart. Current research also reveals the molecular mechanism by which nanoplastics induces cardiomyocyte senescence. This study laid the foundation for further studying the potential harm of nanoplastics exposure on heart.

Graphical abstract
Unraveling the genetic variations underlying virulence disparities among SARS-CoV-2 strains across global regions: insights from Pakistan
Authors: Jabeen Momina , Shoukat Shifa , Shireen Huma , Bao Yiming , Khan Abbas , Abbasi Amir Ali 
Published: March 2024

AbstractOver the course of the COVID-19 pandemic, several SARS-CoV-2 variants have emerged that may exhibit different etiological effects such as enhanced transmissibility and infectivity. However, genetic variations that reduce virulence and deteriorate viral fitness have not yet been thoroughly investigated. The present study sought to evaluate the effects of viral genetic makeup on COVID-19 epidemiology in Pakistan, where the infectivity and mortality rate was comparatively lower than other countries during the first pandemic wave. For this purpose, we focused on the comparative analyses of 7096 amino-acid long polyprotein pp1ab. Comparative sequence analysis of 203 SARS-CoV-2 genomes, sampled from Pakistan during the first wave of the pandemic revealed 179 amino acid substitutions in pp1ab. Within this set, 38 substitutions were identified within the Nsp3 region of the pp1ab polyprotein. Structural and biophysical analysis of proteins revealed that amino acid variations within Nsp3’s macrodomains induced conformational changes and modified protein-ligand interactions, consequently diminishing the virulence and fitness of SARS-CoV-2. Additionally, the epistatic effects resulting from evolutionary substitutions in SARS-CoV-2 proteins may have unnoticed implications for reducing disease burden. In light of these findings, further characterization of such deleterious SARS-CoV-2 mutations will not only aid in identifying potential therapeutic targets but will also provide a roadmap for maintaining vigilance against the genetic variability of diverse SARS-CoV-2 strains circulating globally. Furthermore, these insights empower us to more effectively manage and respond to potential viral-based pandemic outbreaks of a similar nature in the future.
Exploration of newly synthesized azo-thiohydantoins as the potential alkaline phosphatase inhibitors via advanced biochemical characterization and molecular modeling approaches
Authors: Attaullah Hafiz Muhammad , Ejaz Syeda Abida , Channar Pervaiz Ali , Saeed Aamer , Ujan Rabail , Zargar Seema , Channar Sajid Ali , Sahito Reshma , Wani Tanveer A. , Abbas Qamar 
Published: March 2024

AbstractIn the current study, Azo-Thiohydantoins derivatives were synthesized and characterized by using various spectroscopic techniques including FTIR, 1H-NMR, 13C-NMR, elemental and HRMS analysis. The compounds were evaluated for alkaline phosphatase activity and it was observed that among all the synthesized compounds, derivative 7e exhibited substantial inhibitory activity (IC50 = 0.308 ± 0.065 µM), surpassing the standard inhibitor (L–Phenyl alanine, IC50 = 80.2 ± 1.1 µM). Along with this, these derivatives were comprehensively examined regarding the electronic properties and reactivity of the synthesized compounds using Density Functional Theory (DFT) calculations, where the results were found very promising and the synthesized compound were found stable. After that, SwissADME evaluations highlighted compounds for their favorable physicochemical properties, including solubility and drug-likeness. Molecular docking exhibited the strong binding affinities of 7f and 7e derivatives with intestinal alkaline phosphatase (IAP), further supported by Molecular Dynamics (MD) simulations. This comprehensive integration of experimental and computational approaches sheds the light on the potential therapeutic applications of the synthesized compounds. By providing a detailed investigation of these aspects, this research opens the avenues for the development of novel pharmacologically active compounds with diverse applications.
Circulating cell-free DNA as a biomarker for diagnosis of Schistosomiasis japonica
Authors: Zhang Yu , Liu Rangjiao , Li Junhui , Ma Hongchang , Bao Wenjuan , Jiang Jie , Guo Chen , Tan Deyong , Cheng Xing , Dai Lizhong , Ming Yingzi 
Published: March 2024

Abstract
Background
Schistosomiasis, a neglected tropical disease, remains an important public health problem. Although there are various methods for diagnosing schistosomiasis, many limitations still exist. Early diagnosis and treatment of schistosomiasis can significantly improve survival and prognosis of patients.

Methodology
Circulating cell-free (cf)DNA has been widely used in the diagnosis of various diseases. In our study, we evaluated the diagnostic value of circulating cfDNA for schistosomiasis caused by Schistosoma japonicum. We focused on the tandem sequences and mitochondrial genes of S. japonicum to identify highly sensitive and specific targets for diagnosis of Schistosomiasis japonica.

Results
Through data screening and analysis, we ultimately identified four specific tandem sequences (TD-1, TD-2, TD-3. and TD-4) and six mitochondrial genes (COX1(1), COX1(2), CYTB, ATP6, COX3, and ND5). We designed specific primers to detect the amount of circulating cfDNA in S. japonicum-infected mouse and chronic schistosomiasis patients. Our results showed that the number of tandem sequences was significantly higher than that of the mitochondrial genes. A S. japonicum infection model in mice suggested that infection of S. japonicum can be diagnosed by detecting circulating cfDNA as early as the first week. We measured the expression levels of circulating cfDNA (TD-1, TD-2, and TD-3) at different time points and found that TD-3 expression was significantly higher than that of TD-1 or TD-2. We also infected mice with different quantities of cercariae (20 s and 80 s). The level of cfDNA (TD-3) in the 80 s infection group was significantly higher than in the 20 s infection group. Additionally, cfDNA (TD-3) levels increased after egg deposition. Meanwhile, we tested 42 patients with chronic Schistosomiasis japonica and circulating cfDNA (TD-3) was detected in nine patients.

Conclusions
We have screened highly sensitive targets for the diagnosis of Schistosomiasis japonica, and the detection of circulating cfDNA is a rapid and effective method for the diagnosis of Schistosomiasis japonica. The levels of cfDNA is correlated with cercariae infection severity. Early detection and diagnosis of schistosomiasis is crucial for patient treatment and improving prognosis.

Graphical Abstract
Association between insulin receptor substrate 1 gene polymorphism rs1801278 and gestational diabetes mellitus: an updated meta- analysis
Authors: Shen Lili , Liu Junli , Zhao Xiaolei , Wang Aiqin , Hu Xiaomei 
Published: March 2024

Abstract
Objectives
we performed this meta- analysis to investigate the impact of insulin receptor substrate 1 (IRS1) gene rs1801278 on susceptibility to gestational diabetes mellitus (GDM).

Methods
The pooled odds ratio (OR) and 95% confidence interval (95% CI) were calculated, and p value is used to determine statistical significance. Sensitivity analysis was performed under three models (dominant, recessive and allele model), and the pooled ORs and 95%CI were calculated. Funnel plots and Begger’s regression test were employed to test the publication bias.

Results
The meta-analysis included 4777 participants (2116 cases and 2661 controls). The IRS1 rs1801278 (C/T) were not significant associated with GDM risk under the dominant and allele models, OR (95%CI) = 1.22 (0.88–1.70) and 1.24 (0.91–1.68), respectively (both p values were more than 0.05). But we also found the IRS1 rs1801278 (C/T) were significant associated with GDM risk under the recessive model, OR (95%CI) = 0.37 (0.16–0.86), p = 0.030. Our results showed that none of the studies affected the quality of the pooled OR. We also found no significant publication bias existed in this meta study for three genetic models, PTT + CT vs. CC = 0.445; PCC+CT vs. TT= 0.095; PC vs. T = 0.697.

Conclusion
this meta-analysis indicated that IRS1 rs1801278 (C/T) was associated with the GDM risk under the recessive model but was not associated with the GDM risk under dominant and allele models.
The evolving role of social media in enhancing quality of life: a global perspective across 10 countries
Authors: Marzo Roy Rillera , Jun Chen Hana W. , Ahmad Absar , Thew Hui Zhu , Choy Ja Shen , Ng Chee Han , Chew Chen Loong Alyx , Heidler Petra , King Isabel , Shrestha Rajeev , Rahman Farzana , Rana Jehan Akhter , Khoshtaria Tornike , Matin Arian , Todua Nugzar , Küçük Biçer Burcu , Faller Erwin , Tudy Randy A. , Baldonado Aries , Penamante Criselle Angeline , Bahari Rafidah , Younus Delan Ameen , Ismail Zjwan Mohammed , Lotfizadeh Masoud , Hassan Shehu Muhammad , Iliya Rahamatu Shamsiyyah , Inyang Asari E. , Maung Maung Theingi , Oo Win Myint , Myint Ohnmar , Khadka Anil , Acharya Swosti , Aye Soe Soe , Naing Thein Win , Win Myat Thida , Kyaw Ye Wint , Thapa Pramila Pudasaini , Khanal Josana , Bhattacharya Sudip , Abid Khadijah , Fahlevi Mochammad , Aljuaid Mohammed , El-Abasir Radwa Abdullah , Elsayed Mohamed E. G. 
Published: March 2024

Abstract
Background
Excessive or inappropriate use of social media has been linked to disruptions in regular work, well-being, mental health, and overall reduction of quality of life. However, a limited number of studies documenting the impact of social media on health-related quality of life (HRQoL) are available globally.

Aim
This study aimed to explore the perceived social media needs and their impact on the quality of life among the adult population of various selected countries.

Methodology
A cross-sectional, quantitative design and analytical study utilized an online survey disseminated from November to December 2021.

Results
A total of 6689 respondents from ten countries participated in the study. The largest number of respondents was from Malaysia (23.9%), followed by Bangladesh (15.5%), Georgia (14.8%), and Turkey (12.2%). The prevalence of social media users was over 90% in Austria, Georgia, Myanmar, Nigeria, and the Philippines. The majority of social media users were from the 18–24 age group. Multiple regression analysis showed that higher education level was positively correlated with all four domains of WHOQoL. In addition, the psychological health domain of quality of life was positively associated in all countries. Predictors among Social Media Needs, Affective Needs (β = -0.07), and Social Integrative Needs (β = 0.09) were significantly associated with psychological health.

Conclusion
The study illuminates the positive correlation between higher education levels and improved life quality among social media users, highlighting an opportunity for policymakers to craft education-focused initiatives that enhance well-being. The findings call for strategic interventions to safeguard the mental health of the global social media populace, particularly those at educational and health disadvantages.
Assessing the impact of COVID-19 on self-reported levels of depression during the pandemic relative to pre-pandemic among Canadian adults
Authors: Elamoshy Rasha , Farag Marwa , Geda Nigatu , Feng Cindy 
Published: March 2024

Abstract
Objectives
This study aims to assess the impact of COVID-19 related risk factors on self-reported increases in depression among Canadian adults during the pandemic compared to pre-pandemic levels. We aim to investigate the interactive effects of stressors, including social isolation, financial stress, and fear of catching COVID-19, on mental health outcomes. Our study aims to provide insights for the development of prevention and intervention strategies to address the mental health effects of the pandemic by examining the psychological changes attributable to the pandemic and its impact.

Methods
This study used data collected from the Mental Health Research Canada online survey during the third wave of COVID-19 (April 20–28, 2021). The study examined the impact of COVID-19 related factors, including social isolation, financial concerns, fear of catching COVID-19, and concerns about paying bills, on self-reported increases in depression. Multivariable logistic regression models were utilized to examine these associations, with adjustments made for potential confounding variables. All statistical analysis was performed using SAS V9.4 (SAS Institute Inc., Cary, NC, USA).

Results
Participants reporting social isolation, financial concerns, and fear of catching COVID-19 were more likely to report increased depression. An interaction was observed between concerns for paying bills and catching COVID-19 in relation to depression (p = 0.0085). In other words, the effect of concerns about paying bills on depression was stronger for individuals who also had a fear of catching COVID-19, and vice versa. Young adults, females, patients with pre-existing depression, and residents of certain provinces reported higher levels of depression during COVID-19.

Conclusion
Our study underscores the significant impact of the COVID-19 pandemic on mental health, particularly among certain demographic groups. It emphasizes the need for depression screening and increased support for mental health during the pandemic, with a focus on mitigating financial burdens and reducing negative psychological impacts of social isolation. Our findings highlight the complex interplay between different stressors and the need to consider this when designing interventions to support mental health during times of crisis.
Predicting sepsis in-hospital mortality with machine learning: a multi-center study using clinical and inflammatory biomarkers
Authors: Zhang Guyu , Shao Fei , Yuan Wei , Wu Junyuan , Qi Xuan , Gao Jie , Shao Rui , Tang Ziren , Wang Tao 
Published: March 2024

AbstractBackgroundThis study aimed to develop and validate an interpretable machine-learning model that utilizes clinical features and inflammatory biomarkers to predict the risk of in-hospital mortality in critically ill patients suffering from sepsis.MethodsWe enrolled all patients diagnosed with sepsis in the Medical Information Mart for Intensive Care IV (MIMIC-IV, v.2.0), eICU Collaborative Research Care (eICU-CRD 2.0), and the Amsterdam University Medical Centers databases (AmsterdamUMCdb 1.0.2). LASSO regression was employed for feature selection. Seven machine-learning methods were applied to develop prognostic models. The optimal model was chosen based on its accuracy, F1 score and area under curve (AUC) in the validation cohort. Moreover, we utilized the SHapley Additive exPlanations (SHAP) method to elucidate the effects of the features attributed to the model and analyze how individual features affect the model’s output. Finally, Spearman correlation analysis examined the associations among continuous predictor variables. Restricted cubic splines (RCS) explored potential non-linear relationships between continuous risk factors and in-hospital mortality.Results3535 patients with sepsis were eligible for participation in this study. The median age of the participants was 66 years (IQR, 55–77 years), and 56% were male. After selection, 12 of the 45 clinical parameters collected on the first day after ICU admission remained associated with prognosis and were used to develop machine-learning models. Among seven constructed models, the eXtreme Gradient Boosting (XGBoost) model achieved the best performance, with an AUC of 0.94 and an F1 score of 0.937 in the validation cohort. Feature importance analysis revealed that Age, AST, invasive ventilation treatment, and serum urea nitrogen (BUN) were the top four features of the XGBoost model with the most significant impact. Inflammatory biomarkers may have prognostic value. Furthermore, SHAP force analysis illustrated how the constructed model visualized the prediction of the model.ConclusionsThis study demonstrated the potential of machine-learning approaches for early prediction of outcomes in patients with sepsis. The SHAP method could improve the interoperability of machine-learning models and help clinicians better understand the reasoning behind the outcome.