Investigating parental perceptions of respiratory syncytial virus (RSV) and attitudes to RSV vaccine in Jiangsu, China: Insights from a cross-section study.

Introduction: Our study aimed to assess parents' perceptions of respiratory syncytial virus (RSV) and their attitudes towards the RSV vaccine in China.

Method: The cross-section study was performed between August 21 and November 15, 2023, in Jiangsu province, eastern China. We collected socio-demographics, awareness, knowledge, perceptions of susceptibility and severity of RSV, and attitudes towards RSV vaccine using online survey questionnaire from parents of child aged ≤14 years old.

Discovery of 5-Nitro--(3-(trifluoromethyl)phenyl) Pyridin-2-amine as a Novel Pure Androgen Receptor Antagonist against Antiandrogen Resistance.

The transformation of clinical androgen receptor (AR) antagonists into agonists driven by AR mutations poses a significant challenge in treating prostate cancer (PCa). Novel anti-AR therapeutics combating mutation-induced resistance are required. Herein, by combining structure-based virtual screening and biological evaluation, a high-affinity agonist was first discovered.

HPV vaccination strategy for 14-year-old females and economic returns for cervical cancer prevention in Wuxi City, China: a cost effectiveness analysis.

Background: Since December 2021, Wuxi, China has offered a two-dose human papillomavirus (HPV) vaccination to 14-year-old females for free. This study evaluated the costs and benefits of this vaccination scheduled in the Expanded Program on Immunization in Wuxi from the perspective of the cities' demographic characteristics, economic development, and policy support.

Methods: The model-based economic evaluation used TreeAge Pro software to construct a decision tree-Markov model for the vaccination strategy in which 100,000 14-year-old females received two doses of bivalent HPV vaccine or no vaccination.

GhEXL3 participates in brassinosteroids regulation of fiber elongation in Gossypium hirsutum.

Cotton fiber (Gossypium hirsutum) serves as an ideal model for investigating the molecular mechanisms of plant cell elongation at the single-cell level. Brassinosteroids (BRs) play a crucial role in regulating plant growth and development. However, the mechanism by which BR influences cotton fiber elongation remains incompletely understood.

COVID-19 vaccination and concerns regarding vaccine hesitancy after the termination of the zero-COVID policy in China: A nationwide cross-sectional study.

COVID-19 vaccine hesitancy remains prevalent globally. However, national data on this issue in the general population after the termination of the zero-COVID policy in China are limited. In March 2023, we conducted a nationwide cross-sectional survey among Chinese adults using a self-administered questionnaire.

The role of apparent diffusion coefficient in the grading of adult isocitrate dehydrogenase-mutant astrocytomas: relationship with the Ki-67 proliferation index.

Background: The grading of adult isocitrate dehydrogenase (IDH)-mutant astrocytomas is a crucial prognostic factor.

Purpose: To investigate the value of conventional magnetic resonance imaging (MRI) features and apparent diffusion coefficient (ADC) in the grading of adult IDH-mutant astrocytomas, and to analyze the correlation between ADC and the Ki-67 proliferation index.

Material And Methods: The clinical and MRI data of 82 patients with adult IDH-mutant astrocytoma who underwent surgical resection and molecular genetic testing with IDH and 1p/19q were retrospectively analyzed.

TMBstable: a variant caller controls performance variation across heterogeneous sequencing samples.

In cancer genomics, variant calling has advanced, but traditional mean accuracy evaluations are inadequate for biomarkers like tumor mutation burden, which vary significantly across samples, affecting immunotherapy patient selection and threshold settings. In this study, we introduce TMBstable, an innovative method that dynamically selects optimal variant calling strategies for specific genomic regions using a meta-learning framework, distinguishing it from traditional callers with uniform sample-wide strategies. The process begins with segmenting the sample into windows and extracting meta-features for clustering, followed by using a pre-trained meta-model to select suitable algorithms for each cluster, thereby addressing strategy-sample mismatches, reducing performance fluctuations and ensuring consistent performance across various samples.

Data-driven prediction of colonization outcomes for complex microbial communities.

Microbial interactions can lead to different colonization outcomes of exogenous species, be they pathogenic or beneficial in nature. Predicting the colonization of exogenous species in complex communities remains a fundamental challenge in microbial ecology, mainly due to our limited knowledge of the diverse mechanisms governing microbial dynamics. Here, we propose a data-driven approach independent of any dynamics model to predict colonization outcomes of exogenous species from the baseline compositions of microbial communities.

Perceptions about respiratory syncytial virus (RSV) and attitudes toward the RSV vaccine among the general public in China: A cross-sectional survey.

Our study aims to assess the public's perceptions of respiratory syncytial virus (RSV) and attitudes toward the RSV vaccine and to identify associated factors in China. A nationwide cross-sectional survey conducted using an online platform between August 16 and September 14, 2023. Questions related to socio-demographics, awareness, knowledge, perceptions of susceptibility and severity of RSV, and attitudes toward the RSV vaccine were included in the questionnaire.

Predicting metabolomic profiles from microbial composition through neural ordinary differential equations.

Characterizing the metabolic profile of a microbial community is crucial for understanding its biological function and its impact on the host or environment. Metabolomics experiments directly measuring these profiles are difficult and expensive, while sequencing methods quantifying the species composition of microbial communities are well-developed and relatively cost-effective. Computational methods that are capable of predicting metabolomic profiles from microbial compositions can save considerable efforts needed for metabolomic profiling experimentally.

Identifying keystone species in microbial communities using deep learning.

Previous studies suggested that microbial communities can harbour keystone species whose removal can cause a dramatic shift in microbiome structure and functioning. Yet, an efficient method to systematically identify keystone species in microbial communities is still lacking. Here we propose a data-driven keystone species identification (DKI) framework based on deep learning to resolve this challenge.

Assessing vaccine effectiveness for varicella in Wuxi, China: a time-series analysis.

Objective: The varicella vaccine is not included in the national childhood immunization schedules in China. Varicella epidemics and outbreaks are frequently reported, and the evidence for the effectiveness of the varicella vaccine remains unclear. The aim of this study was to investigate varicella vaccine effectiveness in Wuxi, China.

Nutritional redundancy in the human diet and its application in phenotype association studies.

Studying human dietary intake may help us identify effective measures to treat or prevent many chronic diseases whose natural histories are influenced by nutritional factors. Here, by examining five cohorts with dietary intake data collected on different time scales, we show that the food intake profile varies substantially across individuals and over time, while the nutritional intake profile appears fairly stable. We refer to this phenomenon as 'nutritional redundancy' and attribute it to the nested structure of the food-nutrient network.

The relationship between geometry and hemodynamics of the stenotic carotid artery based on computational fluid dynamics.

Objective: The purpose of this work was to investigate the relationship between the geometric factors and the hemodynamics of the stenotic carotid artery.

Methods: We retrospectively reviewed data of patients with carotid stenosis (40%-95%). The Navier-Stokes equations were solved using ANSYS CFX 18.

OCRFinder: a noise-tolerance machine learning method for accurately estimating open chromatin regions.

Open chromatin regions are the genomic regions associated with basic cellular physiological activities, while chromatin accessibility is reported to affect gene expressions and functions. A basic computational problem is to efficiently estimate open chromatin regions, which could facilitate both genomic and epigenetic studies. Currently, ATAC-seq and cfDNA-seq (plasma cell-free DNA sequencing) are two popular strategies to detect OCRs.

Data-driven prediction of colonization outcomes for complex microbial communities.

Complex microbial interactions can lead to different colonization outcomes of exogenous species, be they pathogenic or beneficial in nature. Predicting the colonization of exogenous species in complex communities remains a fundamental challenge in microbial ecology, mainly due to our limited knowledge of the diverse physical, biochemical, and ecological processes governing microbial dynamics. Here, we proposed a data-driven approach independent of any dynamics model to predict colonization outcomes of exogenous species from the baseline compositions of microbial communities.

Functional characterization of TBL genes revealed the role of GhTBL7 and GhTBL58 in cotton fiber elongation.

TBL (Trichome Birefringence Like) gene family members are involved in trichome initiation and xylan acetylation in several plant species. In our research, we identified 102 TBLs from G. hirsutum.

Identifying chronic obstructive pulmonary disease from integrative omics and clustering in lung tissue.

Background: Chronic obstructive pulmonary disease (COPD) is a highly morbid and heterogenous disease. While COPD is defined by spirometry, many COPD characteristics are seen in cigarette smokers with normal spirometry. The extent to which COPD and COPD heterogeneity is captured in omics of lung tissue is not known.

Identifying keystone species in microbial communities using deep learning.

Previous studies suggested that microbial communities harbor keystone species whose removal can cause a dramatic shift in microbiome structure and functioning. Yet, an efficient method to systematically identify keystone species in microbial communities is still lacking. This is mainly due to our limited knowledge of microbial dynamics and the experimental and ethical difficulties of manipulating microbial communities.