A Systematic Survey of the Optimal Strategy for Dealing With Missing Binary Outcomes in Simulation Studies of Randomized Controlled Trials.

Aim: To summarize the optimal strategies for dealing with missing binary outcome data (MBOD) in randomized controlled trials (RCTs) as informed by simulation studies, and to summarize the quality of reporting in these studies.

Methods: To identify simulation studies comparing at least two strategies to deal with MBOD and evaluating their performance (bias, coverage and power), we searched MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials via Ovid, Web of Science, and JSTOR from their inception up to December 20, 2023. We evaluated reporting quality using established criteria for simulation studies in medical statistics.

Optical characteristics and formation mechanism of haze events in Qingdao, a coastal city in China.

During the field campaign conducted in Qingdao, Shandong Province, from December 2019 to January 2020, six significant haze episodes occurred. To investigate the optical characteristics and formation mechanisms of haze in this region, we utilized an optical particle counter to measure the size distribution of aerosol particles. The results showed that the average Angström exponent value during the campaign was 1.

Molecular surveillance-informed personalized multidisciplinary therapy achieves prolonged survival in a patient with Lynch syndrome-associated colorectal cancer: A case report.

Background: Lynch syndrome (LS), an autosomal dominant genetic disorder, is distinguished by germline mutations in the DNA mismatch repair genes, including . These mutations confer an elevated risk for the development of colorectal cancer (CRC) and an array of other malignancies. Timely detection, facilitated by genetic profiling and stringent molecular surveillance, is crucial.

Therapeutic effects of self-assembled berberine-glycyrrhizic acid and matrine-glycyrrhizic acid complexes from Qingchang Wenzhong decoction on DSS-induced ulcerative colitis: Mechanisms of anti-inflammatory action.

Ethnopharmacological Relevance: Qingchang Wenzhong Decoction (QCWZD), a traditional Chinese medicine (TCM) formula, has been clinically utilized for ulcerative colitis (UC) treatment due to its anti-inflammatory and intestinal barrier-protective effects. However, the mechanisms by which its naturally self-assembled supramolecular complexes, formed during aqueous decoction, contribute to therapeutic outcomes remain underexplored, representing a critical gap in understanding TCM's holistic pharmacology.

Aim Of The Study: This study sought to elucidate the self-assembly mechanisms underlying QCWZD's therapeutic effects, with a focus on characterizing the anti-inflammatory properties of its naturally self-assembled complexes formed during decoction and their role in UC intervention.

Geospatially enhanced convolutional neural network for HY-2B scatterometer-based marine wind field retrieval.

Precise monitoring of sea surface wind fields is imperative for understanding ocean-atmosphere interactions and extreme weather evolution, where spaceborne scatterometers provide unique observational capabilities but face inherent limitations in accuracy and efficiency using the geophysical model function (GMF). We developed convolutional neural network-based models (CNN-WSPD and CNN-WDIR respectively for sea surface wind speed and direction retrievals) integrating HY-2B scatterometer data and ECMWF reanalysis with geographical coordinates. The innovation lies in embedding positional features into multi-angle backscatter processing, enhancing physical consistency across diverse marine environments.

Coded-mask-based wavefront sensing technique for APS nanofocusing beamline diagnostics.

We extend our recently developed coded-mask wavefront sensing technique to enable single-shot measurements of nanofocused x-ray beams. This method accurately reconstructs the focal beam profile by backpropagating the wavefront measured downstream of the beam focus. To validate its performance, we benchmarked it against the conventional fluorescence wire scan method, successfully measuring ∼120 nm focal spots at the 28-ID-B beamline of the Advanced Photon Source using a polymeric compound refractive lens.

Review on research methods of the surface urban heat island effect based on CNKI bibliometrics.

The urban heat island (UHI) effect is an increasingly prominent local climate issue in the process of global urbanization, significantly impacting human settlement health and energy consumption. Based on the China National Knowledge Infrastructure (CNKI) database, we searched and analyzed Chinese journal articles on the surface urban heat island (SUHI) effect published during 1980 and 2024. Using CiteSpace software, we conducted a visual analysis of publication trends and keywords to systematically summarize the research advances.

In-situ X-ray scattering observation of colloidal epitaxy at the gas-liquid-solid interface.

The convective self-assembly of dip-coating is a long-established technique widely employed in scientific and industrial applications. Despite its apparent importance, many of the fundamental aspects remain unknown, particularly the exact assembling mechanism and its relationship with evaporation kinetics and fluid dynamics. Here, we perform the in-situ small-angle X-ray scattering study of the real-time convective self-assembly of colloidal particles inside a meniscus.

Hyperbolic vision language representation learning on chest radiology images.

Given the visual-semantic hierarchy between images and texts, hyperbolic embeddings have been employed for visual-semantic representation learning, leveraging the advantages of hierarchy modeling in hyperbolic space. This approach demonstrates notable advantages in zero-shot learning tasks. However, unlike general image-text alignment tasks, textual data in the medical domain often comprises complex sentences describing various conditions or diseases, posing challenges for vision language models to comprehend free-text medical reports.

Synergistic governance of urban heat islands, energy consumption, carbon emissions, and air pollution in China: Evidence from a Spatial Durbin Model.

Advancing the synergistic governance of urban heat island (UHI), energy consumption (EC), CO emissions and air pollution (collectively referred to as heat-energy-carbon-pollution, HECP) is essential for China's green transition. This study examined five representative indicators of HECP-namely, urban heat island intensity (UHII), EC, CO emissions, PM and O concentrations-using panel data from 269 prefecture-level cities in China from 2005 to 2020. The Spatial Durbin Model (SDM) was employed to identify the key drivers of HECP governance at both national and regional levels.

[Regulatory roles of JAZ in the growth and development of horticultural plants].

Jasmonic acid (JA) is a common plant hormone with regulatory effects on plant growth and development. The jasmonate ZIM-domain (JAZ) proteins (JAZs), as key regulators in the JA signaling pathway, are involved in multiple biological processes such as anthocyanin accumulation, flowering time modulation, and secondary metabolite synthesis in plants. JAZs are essential components of many regulatory signaling networks.

Emerging strategies to overcome PARP inhibitors' resistance in ovarian cancer.

The utilization of PARP inhibitors (PARPis) has significantly improved the prognosis for ovarian cancer patients. However, as the use of PARPis increases, the issue of PARPi resistance has become more prominent. Prolonged usage of PARPis can lead to the development of resistance in ovarian cancer, often mediated by mechanisms such as homologous recombination (HR) recovery, ultimately resulting in cancer relapse.

Identifying causal relationships between 35 blood and urine biomarkers and urologic cancers: MR-meta combined with Bayesian colocalization Mendelian randomization analysis.

Background: Blood and urine biomarkers have been associated with urologic tumors, but their causal relationship with urologic tumors is unclear.

Methods: We performed a bidirectional Mendelian randomization (MR) analysis of the association between 35 blood and urine biomarkers and urological tumors in our discovery cohort. A Bayesian weighting approach was used to validate the positive results identified in the discovery cohort, and steiger filtering analysis was used to distinguish causality from reverse causality.

Construction and validation of a machine learning-based immune-related prognostic model for glioma.

Background: Glioma stands as the most prevalent primary brain tumor found within the central nervous system, characterized by high invasiveness and treatment resistance. Although immunotherapy has shown potential in various tumors, it still faces challenges in gliomas. This study seeks to develop and validate a prognostic model for glioma based on immune-related genes, to provide new tools for precision medicine.

Health risk assessment of municipal solid waste incineration emissions based on regression analysis.

This study examined the potential health risks posed by the operation of 96 waste-to-energy (WtE) plants in 30 cities in the Bohai Rim of China. Utilizing a sophisticated simulation approach, the Weather Research and Forecasting (WRF) model coupled with the California Puff (CALPUFF) model, we obtained the spatial distribution of pollutants emitted by WtE plants in the atmosphere. Hazard indices (HI) and cancer risks (CR) were calculated for each plant using the United States Environmental Protection Agency's recommended methodologies.

CNDP1 Suppresses the Malignant Behavior of Hepatoma Cell Restricting PI3K-AKT-mTOR Activation.

Introduction: Hepatocellular carcinoma (HCC) is a global health problem with increasing morbidity and mortality, and exploring the diagnosis and treatment of HCC at the gene level has become a research hotspot in recent years. As the rate-limiting enzyme of carnosine hydrolysis, CNDP1 participates in the progress of many diseases, but its function in HCC has not been fully elucidated.

Methods: This study firstly screened differentially expressed genes from the biochip related to HCC by bioinformatic analysis, and CNDP1 was finally selected for in-depth study.

Opportunity Analysis of Phosphorus Recovery from Municipal Wastewater for Cropland Based on the Simulated Vehicle Transport Distance in the Yangtze River Delta, China.

With the rapid depletion of phosphate rocks and increasing agricultural demand, establishing a phosphorus (P) flow "loop" rather than a one-way trajectory between cropland and urban areas was imperative. Recovering P from municipal wastewater stood as a viable strategy to mitigate reliance on traditional P-containing chemical fertilizer. This study analyzed the intricate relationships between the potentials of P recovery from municipal wastewater and the P demand of croplands in the populated Yangtze River Delta (YRD), China.

Road defect detection based on improved YOLOv8s model.

Road defect detection is critical step for road maintenance periodic inspection. Current methodologies exhibit drawbacks such as low detection accuracy, slow detection speed, and the inability to support edge deployment and real-time detection. To solve this issue, we introduce an improved YOLOv8 road defect detection model.

Gastric Cancer Assembloids Derived from Patient-Derived Xenografts: A Preclinical Model for Therapeutic Drug Screening.

The construction of reliable preclinical models is crucial for understanding the molecular mechanisms involved in gastric cancer and for advancing precision medicine. Currently, existing in vitro tumor models often do not accurately replicate the human gastric cancer environment and are unsuitable for high-throughput therapeutic drug screening. In this study, droplet microfluidic technology is employed to create novel gastric cancer assembloids by encapsulating patient-derived xenograft gastric cancer cells and patient stromal cells in Gelatin methacryloyl (GelMA)-Gelatin-Matrigel microgels.

X-ray optics for the cavity-based X-ray free-electron laser.

A cavity-based X-ray free-electron laser (CBXFEL) is a possible future direction in the development of fully coherent X-ray sources. CBXFELs consist of a low-emittance electron source, a magnet system with several undulators and chicanes, and an X-ray cavity. The X-ray cavity stores and circulates X-ray pulses for repeated FEL interactions with electron pulses until the FEL reaches saturation.

Depth-Guided Bilateral Grid Feature Fusion Network for Dehazing.

In adverse foggy weather conditions, images captured are adversely affected by natural environmental factors, resulting in reduced image contrast and diminished visibility. Traditional image dehazing methods typically rely on prior knowledge, but their efficacy diminishes in practical, complex environments. Deep learning methods have shown promise in single-image dehazing tasks, but often struggle to fully leverage depth and edge information, leading to blurred edges and incomplete dehazing effects.

Robot-assisted minimally invasive esophagectomy versus minimally invasive esophagectomy for thoracic lymph node dissection in patients with squamous cell carcinoma: a retrospective comparative cohort study.

Background: In Asia, esophageal squamous cell carcinoma (ESCC) accounts for more than 90% of esophageal cancer cases and can be treated with minimally invasive esophagectomy (MIE); however, MIE has certain technical limitations in resecting lymph nodes. The advantages of robot-assisted minimally invasive esophagectomy (RAMIE) surgery, such as the high-definition three-dimensional (3D) vision and the presence of the EndoWrist, facilitates movement in challenging anatomical regions. However, few studies have compared the postoperative outcomes between RAMIE with MIE for the lymph node dissection of patients with ESCC.

ClinicalRisk: A New Therapy-related Clinical Trial Dataset for Predicting Trial Status and Failure Reasons.

Clinical trials aim to study new tests and evaluate their effects on human health outcomes, which has a huge market size. However, carrying out clinical trials is expensive and time-consuming and often ends in no results. It will revolutionize clinical practice if we can develop an effective model to automatically estimate the status of a clinical trial and find out possible failure reasons.