Factors influencing user's health information discernment abilities in online health communities: based on SEM and fsQCA.

Introduction: Online health communities have become the main source for people to obtain health information. However, the existence of poor-quality health information, misinformation, and rumors in online health communities increases the challenges in governing information quality. It not only affects users' health decisions but also undermines social stability.

Identifying Key Genes as Progression Indicators of Prostate Cancer with Castration Resistance Based on Dynamic Network Biomarker Algorithm and Weighted Gene Correlation Network Analysis.

Androgen deprivation therapy (ADT) is the mainstay of treatment for prostate cancer, yet dynamic molecular changes from hormone-sensitive to castration-resistant states in patients treated with ADT remain unclear. In this study, we combined the dynamic network biomarker (DNB) method and the weighted gene co-expression network analysis (WGCNA) to identify key genes associated with the progression to a castration-resistant state in prostate cancer via the integration of single-cell and bulk RNA sequencing data. Based on the gene expression profiles of CRPC in the GEO dataset, the DNB method was used to clarify the condition of epithelial cells and find out the most significant transition signal DNB modules and genes included.

Prediction of mortality events of patients with acute heart failure in intensive care unit based on deep neural network.

Background: Acute heart failure (AHF) in the intensive care unit (ICU) is characterized by its criticality, rapid progression, complex and changeable condition, and its pathophysiological process involves the interaction of multiple organs and systems. This makes it difficult to predict in-hospital mortality events comprehensively and accurately. Traditional analysis methods based on statistics and machine learning suffer from insufficient model performance, poor accuracy caused by prior dependence, and difficulty in adequately considering the complex relationships between multiple risk factors.

Dual Sulfone-Bridged Triphenylamine Heteroaromatics for High-Performance Blue Organic Electroluminescence.

Polycyclic heteroaromatics (PHAs) are a highly versatile class of functional materials, especially applicable as efficient luminophores in organic light-emitting diodes (OLEDs). Those constructed by tethered phenyl surrounding the main group center attract extensive attention due to their excellent OLED device performance. However, the development of such a class of emitters is often limited to boron, nitrogen-doped π-conjugated heterocycles.

Scientific misconduct responsibility attribution: An empirical study on byline position and team identity in Chinese medical papers.

Objective: The primary objective of this inquiry was to explore the nexus between authorship attribution in medical literature and accountability for scientific impropriety while assessing the influence of authorial multiplicity on the severity of sanctions imposed.

Methods: Probit regression models were employed to scrutinize the impact of authorship on assuming accountability for scientific misconduct, and unordered multinomial logistic regression models were used to examine the influence of authorship and the number of bylines on the severity of punitive measures.

Results: First authors and corresponding authors were significantly more likely to be liable for scientific misconduct than other authors and were more likely to be penalized particularly severely.

Difference in Rumor Dissemination and Debunking Before and After the Relaxation of COVID-19 Prevention and Control Measures in China: Infodemiology Study.

Background: The information epidemic emerged along with the COVID-19 pandemic. While controlling the spread of COVID-19, the secondary harm of epidemic rumors to social order cannot be ignored.

Objective: The objective of this paper was to understand the characteristics of rumor dissemination before and after the pandemic and the corresponding rumor management and debunking mechanisms.

Correction: Knowledge and Practices Regarding Human Papillomavirus and Cervical Cancer Screening Among Women in Low-Income Areas of China: A Cross-Sectional Study.

[This corrects the article DOI: 10.7759/cureus.55930.

Correction: Prevalence of High-Risk Human Papillomavirus Infection, Associated Risk Factors, and Relationship With Cervical Precancerous Lesions in Perimenopausal and Older Women in an Area With High Cervical Cancer Incidence in China.

[This corrects the article DOI: 10.7759/cureus.58081.

Prevalence of High-Risk Human Papillomavirus Infection, Associated Risk Factors, and Relationship With Cervical Precancerous Lesions in Perimenopausal and Older Women in an Area With High Cervical Cancer Incidence in China.

Purpose This study delves into the epidemiology of high-risk human papillomavirus (HR-HPV) infection and its link to precancerous lesions among perimenopausal (40-59 years) and elderly (60-65 years) women in a Chinese county with a notably high incidence of cervical cancer. By uniquely focusing on these age groups in underdeveloped regions, the research aims to offer novel strategies for the management and prevention of cervical cancer. It seeks to inform targeted interventions and public health policies that could significantly benefit women at heightened risk for HPV, addressing a critical gap in current prevention efforts in economically disadvantaged communities.

Knowledge and Practices Regarding Human Papillomavirus and Cervical Cancer Screening Among Women in Low-Income Areas of China: A Cross-Sectional Study.

Background: Persistent human papillomavirus (HPV) infection is the primary cause of cervical cancer. However, this can be prevented through vaccination and screening. This study aimed to clarify the relationship between behavior, knowledge, and attitude toward cervical cancer and regular screening and HPV infection among women in Lueyang County.

A novel approach to study multi-domain motions in JAK1's activation mechanism based on energy landscape.

The family of Janus Kinases (JAKs) associated with the JAK-signal transducers and activators of transcription signaling pathway plays a vital role in the regulation of various cellular processes. The conformational change of JAKs is the fundamental steps for activation, affecting multiple intracellular signaling pathways. However, the transitional process from inactive to active kinase is still a mystery.

A study on the factors influencing the intention to receive booster shots of the COVID-19 vaccine in China based on the information frame effect.

Introduction: In the response to and prevention and control of the Novel coronavirus pneumonia, the COVID-19 vaccine does not provide lifelong immunity, and it is therefore important to increase the rate of booster shots of the COVID-19 vaccine. In the field of information health science, research has found that information frames have an impact in changing individual attitudes and health behaviors.

Objective: This study focuses on the effects of different influencing factors on the public's willingness to receive the booster shots of the COVID-19 vaccine under two information frameworks.

Deep-qGFP: A Generalist Deep Learning Assisted Pipeline for Accurate Quantification of Green Fluorescent Protein Labeled Biological Samples in Microreactors.

Absolute quantification of biological samples provides precise numerical expression levels, enhancing accuracy, and performance for rare templates. Current methodologies, however, face challenges-flow cytometers are costly and complex, whereas fluorescence imaging, relying on software or manual counting, is time-consuming and error-prone. It is presented that Deep-qGFP, a deep learning-aided pipeline for the automated detection and classification of green fluorescent protein (GFP) labeled microreactors, enables real-time absolute quantification.

Deep Learning to Predict the Cell Proliferation and Prognosis of Non-Small Cell Lung Cancer Based on FDG-PET/CT Images.

(1) Background: Cell proliferation (Ki-67) has important clinical value in the treatment and prognosis of non-small cell lung cancer (NSCLC). However, current detection methods for Ki-67 are invasive and can lead to incorrect results. This study aimed to explore a deep learning classification model for the prediction of Ki-67 and the prognosis of NSCLC based on FDG-PET/CT images.

Macrocyclic Engineering of Thermally Activated Delayed Fluorescent Emitters for High-Efficiency Organic Light-Emitting Diodes.

Several thermally activated delayed fluorescence (TADF) materials have been studied and developed to realize high-performance organic light-emitting diodes (OLEDs). However, TADF macrocycles have not been sufficiently investigated owing to the synthetic challenges, resulting in limited exploration of their luminescent properties and the corresponding highly efficient OLEDs. In this study, a series of TADF macrocycles is synthesized using a modularly tunable strategy by introducing xanthones as acceptors and phenylamine derivatives as donors.

Photoinduced Radical Persistent Luminescence in Semialiphatic Polyimide System with Temperature and Humidity Resistance.

Organic persistent luminescence (pL) systems with photoresponsive dynamic features have valuable applications in the fields of data encryption, anticounterfeiting, and bioimaging. Photoinduced radical luminescent materials have a unique luminous mechanism with the potential to achieve dynamic pL. It is extremely challenging to obtain radical pL under ambient conditions; on account of it, it is unstable in air.

Identification of a CircRNA-miRNA-mRNA Network and Integrated Analysis of Immune Infiltration in Oral Squamous Cell Carcinoma.

Oral squamous cell carcinoma (OSCC) is a highly invasive type of head and neck cancer. Circular RNA (circRNA) acts as a competing endogenous RNA (ceRNA) and involves in pathogenesis of many diseases. However, the circRNA-miRNA-mRNA network and relationship between ceRNA and immune infiltration in OSCC remain unknown.

High-efficiency blue-emission crystalline organic light-emitting diodes sensitized by "hot exciton" fluorescent nanoaggregates.

Sensitizing fluorescent materials is an effective way to maximally use excitons and obtain high-efficiency blue organic light-emitting diodes (OLEDs). However, it is a persistent challenge for present amorphous thin-film OLEDs to improve photon emission under low driving voltage, severely impeding the development of OLED technology. Here, we propose a novel OLED architecture consisting of a crystalline host matrix (CHM) and embedded "hot exciton" nanoaggregates (HENAs), which effectively sensitize blue dopant (D) emission.

An Efficient Blue-Emission Crystalline Thin-Film OLED Sensitized by "Hot Exciton" Fluorescent Dopant.

Crystalline thin-film organic light-emitting diodes (C-OLEDs) can achieve a large light emission and a low Joule-heat loss under low driving voltage due to the high carrier mobility of the crystalline thin films. However, it is urgent for the C-OLEDs to improve their external quantum efficiency (EQE). Here, a novel strategy is proposed using a doped "hot exciton" material to sensitize a high PLQY blue emitter in C-OLEDs.

Research on the influencing factors of users' information processing in online health communities based on heuristic-systematic model.

With the rapid development of the Internet and the normalization of COVID-19 epidemic prevention and control, Online health communities (OHCs) have gradually become one of the important ways for people to obtain health information, and users have to go through a series of information processing when facing the massive amount of data. Understanding the factors influencing user information processing is necessary to promote users' health literacy, health knowledge popularization and health behavior shaping. Based on the Heuristic-Systematic Model (HSM), Information Ecology Theory, Privacy Trade-Off and Self-Efficacy Theory, we constructed a model of factors influencing user information processing in online health communities.

Photo-controllable Luminescence from Radicals Leading to Ratiometric Emission Switching via Dynamic Intermolecular Coupling.

The development of photoinduced luminescent radicals with dynamic emission color is still challenging. Herein we report a novel molecular radical system (TBIQ) that shows photo-controllable luminescence, leading to a wide range of ratiometric color changes via light excitation. The conjugated skeleton of TBIQ is decorated with steric-demanding tertiary butyl groups that enable appropriate intermolecular interaction to make dynamic intermolecular coupling possible for controllable behaviors.

The Development and Preliminary Application of the Chinese Version of the COVID-19 Vaccine Literacy Scale.

(1) Background: Vaccine literacy (VL) of the public is crucial to deal with anti-vaccination rhetoric. This study aims to (1) develop a Chinese COVID-19 Vaccine Literacy Scale and examine the factor structure and psychometric characteristics, and (2) explore the association between COVID-19 VL and sociodemographic characteristics and other variables; (2) Methods: An online cross-sectional survey was conducted among 362 Chinese residents from 23 May 2022 to 31 May 2022 using snowball sampling; (3) Results: Exploratory and confirmatory factor analysis indicated that the scale of 15 items, consisting of three factors, functional, interactive and critical vaccine literacy, explained 63.3% of the total variance.