bluuebunny/crossref_metadata_2025_split huggingface dataset:
HSPA4 upregulation induces immune evasion via ALKBH5/CD58 axis in gastric cancer
Authors: Suo Daqin , Gao Xiaoling , Chen Qingyun , Zeng Tingting , Zhan Jiarong , Li Guanghui , Zheng Yinli , Zhu Senlin , Yun Jingping , Guan Xin-Yuan , Li Yan 
Published: April 2024

Abstract
Introduction
Gastric cancer (GC) is one of the leading causes of cancer-related death worldwide. Recently, targeted therapies including PD1 (programmed cell death 1) antibodies have been used in advanced GC patients. However, identifying new biomarker for immunotherapy is still urgently needed. The objective of this study is to unveil the immune evasion mechanism of GC cells and identify new biomarkers for immune checkpoint blockade therapy in patients with GC.

Methods
Coimmunoprecipitation and meRIP were performed to investigate the mechanism of immune evasion of GC cells. Cocuture system was established to evaluate the cytotoxicity of cocultured CD8+ T cells. The clinical significance of HSPA4 upregulation was analyzed by multiplex fluorescent immunohistochemistry staining in GC tumor tissues.

Results
Histone acetylation causes HSPA4 upregulation in GC tumor tissues. HSPA4 upregulation increases the protein stability of m6A demethylase ALKBH5. ALKBH5 decreases CD58 in GC cells through m6A methylation regulation. The cytotoxicity of CD8+ T cells are impaired and PD1/PDL1 axis is activated when CD8+ T cells are cocultured with HSPA4 overexpressed GC cells. HSPA4 upregulation is associated with worse 5-year overall survival of GC patients receiving only surgery. It is an independent prognosis factor for worse survival of GC patients. In GC patients receiving the combined chemotherapy with anti-PD1 immunotherapy, HSPA4 upregulation is observed in responders compared with non-responders.

Conclusion
HSPA4 upregulation causes the decrease of CD58 in GC cells via HSPA4/ALKBH5/CD58 axis, followed by PD1/PDL1 activation and impairment of CD8+ T cell’s cytotoxicity, finally induces immune evasion of GC cells. HSPA4 upregulation is associated with worse overall survival of GC patients with only surgery. Meanwhile, HSPA4 upregulation predicts for better response in GC patients receiving the combined immunotherapy.
Association of congenital heart disease and neurodevelopmental disorders: an observational and Mendelian randomization study
Authors: Liu Zhi-yuan , Wang Qiong-qiong , Pang Xian-yong , Huang Xiao-bi , Yang Gui-ming , Zhao Sheng 
Published: April 2024

Abstract
Background
This study aims to thoroughly study the connection between congenital heart disease (CHD) and neurodevelopmental disorders (NDDs) through observational and Mendelian randomization (MR) designs.

Methods
This observational study uses data from the National Survey of Children’s Health (2020–2021). Multivariable logistic regression and propensity score matching (PSM) were performed to analyze the association. PSM was used to minimize bias for covariates such as age, race, gender, maternal age, birth weight, concussion or brain injury, preterm birth, cerebral palsy, Down syndrome, and other inherited conditions. In MR analyses, inverse variance-weighted measures, weighted median, and MR-Egger were employed to calculate causal effects.

Results
A total of 85,314 children aged 0–17 were analyzed in this study. In regression analysis, CHD (p = 0.04), the current heart condition (p = 0.03), and the severity of current heart condition (p < 0.05) had a suggestive association with speech or language disorders. The severity of current heart condition (p = 0.08) has a potential statistically significant association with attention deficit hyperactivity disorder(ADHD). In PSM samples, ADHD(p = 0.003), intellectual disability(p = 0.012), and speech or language disorders(p < 0.001) were all significantly associated with CHD. The severity of current heart condition (p < 0.001) also had a significant association with autism. MR analysis did not find causality between genetically proxied congenital cardiac malformations and the risk of NDDs.

Conclusions
Our study shows that children with CHD have an increased risk of developing NDDs. Heart conditions currently and severity of current heart conditions were also significantly associated with these NDDs. In the future, we need to try more methods to clarify the causal relationship between CHD and NDDs.
Epidemiology of respiratory syncytial virus in a large pediatric hospital in Central Italy and development of a forecasting model to predict the seasonal peak
Authors: Cutrera Renato , Ciofi degli Atti Marta Luisa , Dotta Andrea , D’Amore Carmen , Ravà Lucilla , Perno Carlo Federico , Villani Alberto 
Published: April 2024

Abstract
Background
Respiratory Syncytial Virus (RSV) is responsible for the majority of acute lower respiratory infections in infants and can affect also older age groups. Restrictions linked to the emergence of the SARS-CoV-2 pandemic and their subsequent lifting caused a change in the dynamics of RSV circulation. It is therefore fundamental to monitor RSV seasonal trends and to be able to predict its seasonal peak to be prepared to the next RSV epidemics.

Methods
We performed a retrospective descriptive study on laboratory-confirmed RSV infections from Bambino Gesù Children’s Hospital in Rome from 1st January 2018 to 31st December 2022. Data on RSV-positive respiratory samples (n = 3,536) and RSV-confirmed hospitalizations (n = 1,895) on patients aged 0–18 years were analyzed. In addition to this, a SARIMA (Seasonal AutoRegressive Integrated Moving Average) forecasting model was developed to predict the next peak of RSV.

Results
Findings show that, after the 2020 SARS-CoV-2 pandemic season, where RSV circulation was almost absent, RSV infections presented with an increased and anticipated peak compared to pre-pandemic seasons. While mostly targeting infants below 1 year of age, there was a proportional increase in RSV infections and hospitalizations in older age groups in the post-pandemic period. A forecasting model built using RSV weekly data from 2018 to 2022 predicted the RSV peaks of 2023, showing a reasonable level of accuracy (MAPE 33%). Additional analysis indicated that the peak of RSV cases is expected to be reached after 4–5 weeks from case doubling.

Conclusion
Our study provides epidemiological evidence on the dynamics of RSV circulation before and after the COVID-19 pandemic. Our findings highlight the potential of combining surveillance and forecasting to promote preparedness for the next RSV epidemics.
Clinical factors associated with patterns of endocrine therapy adherence in premenopausal breast cancer patients
Authors: Woolpert Kirsten M. , Schmidt Julie A. , Ahern Thomas P. , Hjorth Cathrine F. , Farkas Dóra K. , Ejlertsen Bent , Collin Lindsay J. , Lash Timothy L. , Cronin-Fenton Deirdre P. 
Published: April 2024

Abstract
Introduction
Patients with hormone receptor positive breast cancer are recommended at least five years of adjuvant endocrine therapy, but adherence to this treatment is often suboptimal. We investigated longitudinal trends in adjuvant endocrine therapy (AET) adherence among premenopausal breast cancer patients and identified clinical characteristics, including baseline comorbidities and non-cancer chronic medication use, associated with AET adherence.

Methods
We included stage I–III premenopausal breast cancer patients diagnosed during 2002–2011 and registered in the Danish Breast Cancer Group clinical database who initiated AET. We used group-based trajectory modeling to describe AET adherence patterns. We also linked patients to Danish population-based registries and fit multinomial logistic models to compute odds ratios (ORs) and 95% confidence intervals (95% CIs) associating clinical characteristics with AET adherence patterns.

Results
We identified three adherence patterns among 4,353 women—high adherers (57%), slow decliners (36%), and rapid decliners (6.9%). Women with stage I disease (vs. stage II; OR: 1.9, 95% CI 1.5, 2.5), without chemotherapy (vs. chemotherapy; OR: 4.3, 95% CI 3.0, 6.1), with prevalent comorbid disease (Charlson Comorbidity Index score ≥ 1 vs. 0; OR: 1.6, 95% CI 1.1, 2.3), and with a history of chronic non-cancer medication use (vs. none; OR: 1.3, 95% CI 1.0, 1.8) were more likely to be rapid decliners compared with high adherers.

Conclusions
Women with stage I cancer, no chemotherapy, higher comorbidity burden, and history of chronic non-cancer medication use were less likely to adhere to AET. Taking steps to promote adherence in these groups of women may reduce their risk of recurrence.
scifi-ATAC-seq: massive-scale single-cell chromatin accessibility sequencing using combinatorial fluidic indexing
Authors: Zhang Xuan , Marand Alexandre P. , Yan Haidong , Schmitz Robert J. 
Published: April 2024

AbstractSingle-cell ATAC-seq has emerged as a powerful approach for revealing candidate cis-regulatory elements genome-wide at cell-type resolution. However, current single-cell methods suffer from limited throughput and high costs. Here, we present a novel technique called scifi-ATAC-seq, single-cell combinatorial fluidic indexing ATAC-sequencing, which combines a barcoded Tn5 pre-indexing step with droplet-based single-cell ATAC-seq using the 10X Genomics platform. With scifi-ATAC-seq, up to 200,000 nuclei across multiple samples can be indexed in a single emulsion reaction, representing an approximately 20-fold increase in throughput compared to the standard 10X Genomics workflow.
A comprehensive benchmark of graph-based genetic variant genotyping algorithms on plant genomes for creating an accurate ensemble pipeline
Authors: Du Ze-Zhen , He Jia-Bao , Jiao Wen-Biao 
Published: April 2024

Abstract
Background
Although sequencing technologies have boosted the measurement of the genomic diversity of plant crops, it remains challenging to accurately genotype millions of genetic variants, especially structural variations, with only short reads. In recent years, many graph-based variation genotyping methods have been developed to address this issue and tested for human genomes. However, their performance in plant genomes remains largely elusive. Furthermore, pipelines integrating the advantages of current genotyping methods might be required, considering the different complexity of plant genomes.

Results
Here we comprehensively evaluate eight such genotypers in different scenarios in terms of variant type and size, sequencing parameters, genomic context, and complexity, as well as graph size, using both simulated and real data sets from representative plant genomes. Our evaluation reveals that there are still great challenges to applying existing methods to plants, such as excessive repeats and variants or high resource consumption. Therefore, we propose a pipeline called Ensemble Variant Genotyper (EVG) that can achieve better genotyping performance in almost all experimental scenarios and comparably higher genotyping recall and precision even using 5× reads. Furthermore, we demonstrate that EVG is more robust with an increasing number of graphed genomes, especially for insertions and deletions.

Conclusions
Our study will provide new insights into the development and application of graph-based genotyping algorithms. We conclude that EVG provides an accurate, unbiased, and cost-effective way for genotyping both small and large variations and will be potentially used in population-scale genotyping for large, repetitive, and heterozygous plant genomes.
Anopheles aquatic development kinetic and adults’ longevity through different seasons in laboratory and semi-field conditions in Burkina Faso
Authors: Djègbè Nicaise D. C. , Da Dari F. , Somé Bernard M. , Paré Lawata Inès G. , Cissé Fatoumata , Mamai Wadaka , Mouline Karine , Sawadogo Simon P. , Challenger Joseph D. , Churcher Thomas S. , Dabiré Roch K. 
Published: April 2024

A﻿bstract
Background
Anopheles mosquitoes are ectothermic and involved in numerous pathogen transmissions. Their life history traits are influenced by several environmental factors such as temperature, relative humidity and photoperiodicity. Despite extensive investigations of these environmental conditions on vector population ecology, their impact on the different life stages of Anopheles at different seasons in the year remains poorly explored. This study reports the potential impact of these abiotic factors on the immature and adult stages of Anopheles gambiae sensu lato during different seasons.

Methods
Environmental conditions were simulated in the laboratory using incubators to mimic the environmental conditions of two important periods of the year in Burkina Faso: the peak of rainy season (August) and the onset of dry season (December). Eggs from wild An. coluzzii and An. gambiae s.l. were reared separately under each environmental condition. For Anopheles coluzzii or An. gambiae s.l., eggs were equally divided into two groups assigned to the two experimental conditions. Four replicates were carried out for this experiment. Then, egg hatching rate, pupation rate, larval development time, larva-to-pupae development time, adult emergence dynamics and longevity of Anopheles were evaluated. Also, pupae-to-adult development time from wild L3 and L4 Anopheles larvae was estimated under semi-field conditions in December.

Results
A better egg hatching rate was recorded overall with conditions mimicking the onset of the dry season compared to the peak of the rainy season. Larval development time and longevity of An. gambiae s.l. female were significantly longer at the onset of the dry season compared than at the peak of the rainy season. Adult emergence was spread over 48 and 96 h at the peak of the rainy season and onset of dry season conditions respectively. This 96h duration in the controlled conditions of December was also observed in the semi-field conditions in December.

Conclusions
The impact of temperature and relative humidity on immature stages and longevity of An. gambiae s.l. adult females differed under both conditions. These findings contribute to a better understanding of vector population dynamics throughout different seasons of the year and may facilitate tailoring of control strategies.

Graphical Abstract
Geospatial evaluation of radiologic access in Rwanda
Authors: Liu Rui Han , Lindeborg Michael , Ncogoza Isaie , Nyiraneza Sabine E. , Barrera Keisha J. , Shaye David A. 
Published: April 2024

Abstract
Background
Rwanda has aimed to rebuild its health care system since the Rwandan genocide against the Tutsis in 1994, though one of the challenges has been a scarcity of radiologic resources.

Objective
To assess the location and accessibility of radiologic facilities in Rwanda using geospatial mapping and population-based data.

Methods
A cross-sectional study was conducted in May 2023 using location and radiologic modality data provided by the Department of Radiology at the University Teaching Hospital of Kigali and the WorldPop database, a publicly available database providing open-access geospatial population data. Radiologic equipment included magnetic resonance (MR), computed tomography (CT), positron emission tomography (PET), radiotherapy, X-ray, mammography, and fluoroscopy machines. Geospatial analysis was performed using ArcGIS Pro 2.8.6 software.

Results
Fifty-six radiologic facilities were identified, including 5 MR, 7 CT, 1 radiotherapy, 52 X-ray, 5 mammography, 5 fluoroscopy, and 0 PET machines. There were 0.4 MR, 0.5 CT, 0 PET, 0.1 radiotherapy, 3.9 X-ray, 0.4 mammography, and 0.4 fluoroscopy units per 1 million people.

Conclusion
Rwanda is one of the countries with the lowest radiologic access in East Africa; however, there is evidence of progress, particularly in more advanced diagnostic imaging techniques such as computed tomography and magnetic resonance imaging.

Critical relevance statement
This study provides a 10-year update on current radiologic resources and access in Rwanda, identifying areas of progress and ongoing scarcity, serving as a guide for future direction of growth.

Key points
• As Rwanda works on rebuilding its health care system, this study provides an assessment of the current radiologic resources within the country.
• There is less than one radiologic unit for every million of the Rwandan population for every imaging modality other than X-ray.
• While radiologic access in Rwanda lags behind that of its neighbors, there has been growth focused on advanced imaging modalities and the training of human resources.

Graphical Abstract
Swine acute diarrhea syndrome coronavirus Nsp1 suppresses IFN-λ1 production by degrading IRF1 via ubiquitin–proteasome pathway
Authors: Zhong Chunhui , She Gaoli , Zhao Yukun , Liu Yufang , Li Jingmin , Wei Xiaona , Chen Zexin , Zhao Keyu , Zhao Zhiqing , Xu Zhichao , Zhang Hao , Cao Yongchang , Xue Chunyi 
Published: April 2024

AbstractSwine acute diarrhea syndrome coronavirus (SADS-CoV) is a novel porcine enteric coronavirus that causes acute watery diarrhea, vomiting, and dehydration in newborn piglets. The type III interferon (IFN-λ) response serves as the primary defense against viruses that replicate in intestinal epithelial cells. However, there is currently no information available on how SADS-CoV modulates the production of IFN-λ. In this study, we utilized IPI-FX cells (a cell line of porcine ileum epithelium) as an in vitro model to investigate the potential immune evasion strategies employed by SADS-CoV against the IFN-λ response. Our results showed that SADS-CoV infection suppressed the production of IFN-λ1 induced by poly(I:C). Through screening SADS-CoV-encoded proteins, nsp1, nsp5, nsp10, nsp12, nsp16, E, S1, and S2 were identified as antagonists of IFN-λ1 production. Specifically, SADS-CoV nsp1 impeded the activation of the IFN-λ1 promoter mediated by MAVS, TBK1, IKKε, and IRF1. Both SADS-CoV and nsp1 obstructed poly(I:C)-induced nuclear translocation of IRF1. Moreover, SADS-CoV nsp1 degraded IRF1 via the ubiquitin-mediated proteasome pathway without interacting with it. Overall, our study provides the first evidence that SADS-CoV inhibits the type III IFN response, shedding light on the molecular mechanisms employed by SADS-CoV to evade the host immune response.
Traffic prediction for diverse edge IoT data using graph network
Authors: Shen Tao , Zhang Lu , Geng Renkang , Li Shuai , Sun Bin 
Published: April 2024

AbstractMore researchers are proposing artificial intelligence algorithms for Internet of Things (IoT) devices and applying them to themes such as smart cities and smart transportation. In recent years, relevant research has mainly focused on data processing and algorithm modeling, and most have shown good prediction results. However, many algorithmic models often adjust parameters for the corresponding datasets, so the robustness of the models is weak. When different types of data face other model parameters, the prediction performance often varies a lot. Thus, this work starts from the perspective of data processing and algorithm models. Taking traffic data as an example, we first propose a new data processing method that processes traffic data with different attributes and characteristics into a dataset that is more common for most models. Then we will compare different types of datasets from the perspective of multiple model parameters, and further analyze the precautions and changing trends of different traffic data in machine learning. Finally, different types of data and ranges of model parameters are explored, together with possible reasons for fluctuations in forecast results when data parameters change.
Patient and pharmacist perspectives on opioid misuse screening and brief interventions in community pharmacies
Authors: Rao Deepika , Ford James H. , Shiyanbola Olayinka O. 
Published: April 2024

Abstract
Background
Pharmacy-based screening and brief interventions (SBI) offer opportunities to identify opioid misuse and opioid safety risks and provide brief interventions that do not overly burden pharmacists. Currently, such interventions are being developed without patient input and in-depth contextual data and insufficient translation into practice. The purpose of this study is to qualitatively explore and compare patient and pharmacist perceptions and needs regarding a pharmacy-based opioid misuse SBI and to identify relevant SBI features and future implementation strategies.

Methods
Using the Consolidated Framework for Implementation Research, we conducted semi-structured interviews with 8 patients and 11 pharmacists, to explore needs and barriers to participating in a pharmacy-based SBI. We recruited a purposive sample of English-speaking patients prescribed opioids for chronic or acute pain and pharmacists practicing in varied pharmacies (small independent, large-chain, specialty retail) settings. We used an inductive content analysis approach to analyze patient interview data. Then through a template analysis approach involving comparison of pharmacist and patient themes, we developed strategies for SBI implementation.

Results
Most patient participants were white, older, described living in suburban areas, and were long-term opioid users. We identified template themes related to individual, interpersonal, intervention, and implementation factors and inferred applications for SBI design or potential SBI implementation strategies. We found that patients needed education on opioid safety and general opioid use, regardless of opioid use behaviors. Pharmacists described needing patient-centered training, protocols, and scripts to provide SBI. A short-self-reported screening and brief interventions including counseling, naloxone, and involving prescribers were discussed by both groups.

Conclusions
Through this implementation-focused qualitative study, we identified patient needs such as opioid safety education delivered in a private and convenient format and pharmacist needs including training, workflow integration, protocols, and a time-efficient intervention for effective pharmacy-based SBI. Alternate formats of SBI using digital health technologies may be needed for effective implementation. Our findings can be used to develop patient-centered pharmacy-based SBI that can be implemented within actual pharmacy practice.
Phase diagram and density of SiO2–H2O fluid across critical conditions
Authors: Gao Hui , Li Guoge , Zhang Zhigang 
Published: April 2024

AbstractThe SiO2–H2O binary system serves as a basis for understanding complex silicate-water systems. In this study, based on limited existing experimental data of solubility, we propose a new thermodynamic model for SiO2–H2O fluid by modifying the traditional non-random two-liquid model with a simplified polymerization reaction. This model is applicable from 773 K to the anhydrous quartz melting temperature and from 0.5 GPa to at least 2 GPa across the critical conditions. It can predict solid–liquid equilibrium and vapor–liquid equilibrium in good agreement with available experiments. The upper critical endpoint of the SiO2–H2O system is predicted to be at ~ 1.14 ± 0.18 GPa and 1344 ± 87 K. With the new model, we obtain a quantitative three-dimensional pressure–temperature–composition phase diagram of the SiO2–H2O fluid, which greatly facilitates the understanding of the complex phase behavior of this binary around the upper critical endpoint. In addition, since the model is based on the Gibbs free energy foundation, we further discuss the derived density variations of SiO2–H2O fluid along with its complex phase changes in typical geochemical processes.