Geographically weighted accelerated failure time model for spatial survival data: application to ovarian cancer survival data in New Jersey.

Background: In large multiregional cohort studies, survival data is often collected at small geographical levels (such as counties) and aggregated at larger levels, leading to correlated patterns that are associated with location. Traditional studies typically analyze such data globally or locally by region, often neglecting the spatial information inherent in the data, which can introduce bias in effect estimates and potentially reduce statistical power.

Method: We propose a Geographically Weighted Accelerated Failure Time Model for spatial survival data to investigate spatial heterogeneity.

Lung image segmentation via generative adversarial networks.

Introduction: Lung image segmentation plays an important role in computer-aid pulmonary disease diagnosis and treatment.

Methods: This paper explores the lung CT image segmentation method by generative adversarial networks. We employ a variety of generative adversarial networks and used their capability of image translation to perform image segmentation.

Membrane Damage and Metabolic Disruption as the Mechanisms of Linalool against : An Amino Acid Metabolomics Study.

() is usually detected in low-temperature meat products, and seriously threatens food safety and human health. Therefore, the study investigated the antibacterial mechanism of linalool against from membrane damage and metabolic disruption. Results from field-emission transmission electron microscopy (FETEM) and atomic force microscopy (AFM) showed that linalool damage membrane integrity increases surface shrinkage and roughness.

Structure-activity relationship of dual inhibitors containing maleimide and imidazole motifs against glutaminyl cyclase and glycogen synthase kinase-3β.

Alzheimer's disease (AD) is a major cause of dementia and one of the most common chronic diseases affecting the aging population. Because AD is considered a public health priority, there is a critical need to discover novel and effective agents for the treatment of this condition. In view of the known contribution of up-regulated glutaminyl cyclase (QC) and glycogen synthase kinase-3β (GSK-3β) to the initiation of AD, we previously evaluated a series of dual inhibitors containing maleimide and imidazole motifs as potential anti-AD agents.

High-dimensional mediation analysis for continuous outcome with confounders using overlap weighting method in observational epigenetic study.

Background: Mediation analysis is a powerful tool to identify factors mediating the causal pathway of exposure to health outcomes. Mediation analysis has been extended to study a large number of potential mediators in high-dimensional data settings. The presence of confounding in observational studies is inevitable.

Outlier detection in spatial error models using modified thresholding-based iterative procedure for outlier detection approach.

Background: Outliers, data points that significantly deviate from the norm, can have a substantial impact on statistical inference and provide valuable insights in data analysis. Multiple methods have been developed for outlier detection, however, almost all available approaches fail to consider the spatial dependence and heterogeneity in spatial data. Spatial data has diverse formats and semantics, requiring specialized outlier detection methodology to handle these unique properties.

Developing Deep LSTMs With Later Temporal Attention for Predicting COVID-19 Severity, Clinical Outcome, and Antibody Level by Screening Serological Indicators Over Time.

Objective: The clinical course of COVID-19, as well as the immunological reaction, is notable for its extreme variability. Identifying the main associated factors might help understand the disease progression and physiological status of COVID-19 patients. The dynamic changes of the antibody against Spike protein are crucial for understanding the immune response.

Monocular BEV Perception of Road Scenes via Front-to-Top View Projection.

HD map reconstruction is crucial for autonomous driving. LiDAR-based methods are limited due to expensive sensors and time-consuming computation. Camera-based methods usually need to perform road segmentation and view transformation separately, which often causes distortion and missing content.

Healthy life expectancy for 202 countries up to 2030: Projections with a Bayesian model ensemble.

Background: Healthy life expectancy (HLE) projections are required for optimising social and health service management in the future. Existing studies on the topic were usually conducted by selecting a single model for analysis. We thus aimed to use an ensembled model to project the future HLE for 202 countries/region.

Discovery of potential scaffolds for glutaminyl cyclase inhibitors: Virtual screening, synthesis, and evaluation.

Glutaminyl cyclase (QC) plays a crucial role in the early stages of Alzheimer's disease (AD), thus inhibition of QC may be a promising strategy for the treatment of early AD. Therefore, QC inhibitors with novel chemical scaffolds may contribute to the development of additional anti-AD agents. We conducted a virtual screening of 3 million compounds from the Chemdiv and Enamine databases, to discover potential scaffolds for QC inhibitors.

Explainable Machine Learning with Pairwise Interactions for Predicting Conversion from Mild Cognitive Impairment to Alzheimer's Disease Utilizing Multi-Modalities Data.

Background: Predicting cognition decline in patients with mild cognitive impairment (MCI) is crucial for identifying high-risk individuals and implementing effective management. To improve predicting MCI-to-AD conversion, it is necessary to consider various factors using explainable machine learning (XAI) models which provide interpretability while maintaining predictive accuracy. This study used the Explainable Boosting Machine (EBM) model with multimodal features to predict the conversion of MCI to AD during different follow-up periods while providing interpretability.

Instrumental variable-based high-dimensional mediation analysis with unmeasured confounders for survival data in the observational epigenetic study.

High dimensional mediation analysis is frequently conducted to explore the role of epigenetic modifiers between exposure and health outcome. However, the issue of high dimensional mediation analysis with unmeasured confounders for survival analysis in observational study has not been well solved. In this study, we proposed an instrumental variable based approach for high dimensional mediation analysis with unmeasured confounders in survival analysis for epigenetic study.

Predicting Six-Month Re-Admission Risk in Heart Failure Patients Using Multiple Machine Learning Methods: A Study Based on the Chinese Heart Failure Population Database.

Since most patients with heart failure are re-admitted to the hospital, accurately identifying the risk of re-admission of patients with heart failure is important for clinical decision making and management. This study plans to develop an interpretable predictive model based on a Chinese population for predicting six-month re-admission rates in heart failure patients. Research data were obtained from the PhysioNet portal.

Purification, Characterization and Bioactivity of Different Molecular-Weight Fractions of Polysaccharide Extracted from Litchi Pulp.

Litchi polysaccharides are a kind of macromolecular polymers with various biological activities and a wide range of molecular weights. In this study, two separate fractions, with average molecular weights of 378.67 kDa (67.

ERAP2 as a potential biomarker for predicting gemcitabine response in patients with pancreatic cancer.

Objective: Pancreatic cancer is one of the most malignant tumors, with rapid metastasis, high mortality rate, and difficult early screening. Currently, gemcitabine is a first-line drug for pancreatic cancer patients, but its clinical effect is limited due to drug resistance. It is particularly important to further identify biomarkers associated with gemcitabine resistance to improve the sensitivity of gemcitabine treatment.

Hybrid Cell Membrane-Functionalized Biomimetic Nanoparticles for Targeted Therapy of Osteosarcoma.

Purpose: In order to prepare a biomimetic nano-carrier which has inflammatory chemotaxis, homologous targeting and reduce immune clearance, for targeted chemotherapy of osteosarcoma, we fabricated the paclitaxel-loaded poly(lactic-co-glycolic) acid (PLGA) nanoparticles coated with 143B-RAW hybrid membrane (PTX-PLGA@[143B-RAW] NPs) and evaluate its anti-cancer efficacy in vitro and vivo.

Methods: PTX-PLGA@[143B-RAW] NPs were prepared by the ultrasonic method and were characterized by size, zeta potential, polymer dispersion index (PDI), Coomassie bright blue staining, transmission electron microscopy (TEM) and high performance liquid chromatography (HPLC). Cellular uptake, cell viability assay, flow cytometry and chemotactic effect of PTX-PLGA@[143B-RAW] NPs were evaluated in vitro.

Recent progress of macrophage vesicle-based drug delivery systems.

Nanoparticle drug delivery systems (NDDSs) are promising platforms for efficient delivery of drugs. In the past decades, many nanomedicines have received clinical approval and completed translation. With the rapid advance of nanobiotechnology, natural vectors are emerging as novel strategies to carry and delivery nanoparticles and drugs for biomedical applications.

Comparative evaluation of methods for isolating small extracellular vesicles derived from pancreatic cancer cells.

Background: Small extracellular vesicles (sEVs) are nanosized vesicles involved in cell-to-cell communication. sEVs have been widely studied for clinical applications such as early detection of diseases and as therapeutics. Various methods for sEVs isolation are been using, but different methods may result in different qualities of sEVs and impact downstream analysis and applications.

A Mobile Phone App-Based Tai Chi Training in Parkinson's Disease: Protocol for a Randomized Controlled Study.

With an increasing number of China's aging population, Parkinson's disease (PD) increases year by year. Persons with PD exhibit abnormal balance functions, leading to motor skills difficulties, such as unstable walking or even falling. Therefore, activities of daily living and quality of life are affected.

Repurposing FDA-Approved Compounds for the Discovery of Glutaminyl Cyclase Inhibitors as Drugs Against Alzheimer's Disease.

Alzheimer's disease (AD) is one of the most common neurodegenerative causes of dementia, the pathology of which is still not much clear. It's challenging to discover the disease modifying agents for the prevention and treatment of AD over the years. Emerging evidence has been accumulated to reveal the crucial role of up-regulated glutaminyl cyclase (QC) in the initiation of AD.

Extracellular vesicles derived from different sources of mesenchymal stem cells: therapeutic effects and translational potential.

Mesenchymal stem cells (MSCs) were known to have excellent properties in cell therapy. However, the risk of immune rejection associated with cell transplant therapy hampers its use. Extracellular vesicles secreted by MSCs derived from different sources that contain therapeutic molecules such as RNA and proteins, which is a novel strategy for cell-free therapy.

3,5,4'-Trimethoxy-trans-stilbene loaded microemulsion for cutaneous melanoma therapy by transdermal drug delivery.

For therapy of skin cancer, transdermal administration has been a potential way to enhance chemotherapy. However, the drug delivery efficacy remained unsatisfactory because of the physiological barriers from the skin to the tumor, which hindered the effect of 3,5,4'-trimethoxy-trans-stilbene (BTM), a drug that has toxicity to cancer. Herein, we prepared an oil-in-water (O/W) microemulsion to load BTM (BTM-ME) for transdermal therapy of melanoma.