STARComm Scalably Detects Emergent Modules of Spatial Cell-Cell Communication in Inflammation and Cancer.

Unlabelled: In humans, cell-cell communication orchestrates tissue organization, immune coordination, and repair, yet spatially mapping these interactions remains a challenge for biology. We introduce STARComm, a scalable-interpretable computational method that identifies Multicellular Communication Interaction Modules (MCIMs) by detecting spatially co-located receptor-ligand activity from high-plex spatial transcriptomics in 2D and 3D. Applied to an atlas of >14million cells across 8 cancers, STARComm revealed 24 conserved and tumor-specific MCIMs, including a fibro-immune module with targetable axes linked to immune exclusion and immunotherapy resistance.

CD38 Endothelial Remodeling Defines Spatially Diverse Vasculopathy Programs in Rapidly Advancing Oral Inflammation.

Oral inflammatory diseases affect nearly half of the global population. Among them, newly defined peri-implantitis and high-grade periodontitis represent rapidly advancing inflammatory disease types, marked by relatively rapid tissue destruction. Despite their prevalence, the cell mechanisms and spatial architecture driving this severity remain poorly understood.

Deconvolution of cell types and states in spatial multiomics utilizing TACIT.

Identifying cell types and states remains a time-consuming, error-prone challenge for spatial biology. While deep learning increasingly plays a role, it is difficult to generalize due to variability at the level of cells, neighborhoods, and niches in health and disease. To address this, we develop TACIT, an unsupervised algorithm for cell annotation using predefined signatures that operates without training data.

Spatial Deconvolution of Cell Types and Cell States at Scale Utilizing TACIT.

Identifying cell types and states remains a time-consuming, error-prone challenge for spatial biology. While deep learning is increasingly used, it is difficult to generalize due to variability at the level of cells, neighborhoods, and niches in health and disease. To address this, we developed TACIT, an unsupervised algorithm for cell annotation using predefined signatures that operates without training data.

Spatial Deconvolution of Cell Types and Cell States at Scale Utilizing TACIT.

Identifying cell types and states remains a time-consuming and error-prone challenge for spatial biology. While deep learning is increasingly used, it is difficult to generalize due to variability at the level of cells, neighborhoods, and niches in health and disease. To address this, we developed TACIT, an unsupervised algorithm for cell annotation using predefined signatures that operates without training data, using unbiased thresholding to distinguish positive cells from background, focusing on relevant markers to identify ambiguous cells in multiomic assays.

A comparison of severity of illness between the SARS-CoV-2 Omicron variant and Delta variant.

Background: The COVID-19 pandemic has disproportionally affected traditionally marginalized groups. Both the Delta and Omicron variants raised concern amongst public health officials due to potentially higher infectivity rates and disease severity than prior variants. This study sought to compare disease severity between adults infected with the Omicron variant and adults infected with the Delta variant who presented to the Emergency Department at an academic, safety-net hospital in Virginia.

Prevalence and impact of metabolic syndrome on in-hospital outcomes in patients with acute myocardial infarction: A perspective from a developing country.

Acute myocardial infarction (AMI) often suffers from a high prevalence of metabolic syndrome (MetS). However, few studies in developing countries have focused on the effect of MetS on in-hospital outcomes in patients with AMI. We analyzed 199 patients with AMI who underwent primary percutaneous coronary intervention.

Prediction of obstructive coronary artery disease in patients undergoing heart valve surgery: A cross-sectional study in a tertiary care hospital.

Estimating the probability of obstructive coronary artery disease in patients undergoing noncoronary cardiac surgery should be considered compulsory. Our study sought to evaluate the prevalence of obstructive coronary artery disease in patients undergoing valvular heart surgery and to utilize predictive methodology of concomitant obstructive coronary artery disease in these patients. The retrospective study cohort was derived from a tertiary care hospital registry of patients undergoing coronary angiogram prior to valvular heart operations.

The global response: How cities and provinces around the globe tackled Covid-19 outbreaks in 2021.

Background: Tackling the spread of COVID-19 remains a crucial part of ending the pandemic. Its highly contagious nature and constant evolution coupled with a relative lack of immunity make the virus difficult to control. For this, various strategies have been proposed and adopted including limiting contact, social isolation, vaccination, contact tracing, etc.

Predicting Anxiety and Depression Among Patients With COVID-19 in Concentrated Isolation at Medical Camps in Vietnam: A Descriptive Cross-Sectional Study.

Introduction: This study aims to assess the requirement for anxiety and depression treatment for patients with coronavirus disease 2019 (COVID-19) in medical camps in Bac Giang province, Vietnam. This information can help improve the government policy to reduce anxiety and depression in patients with COVID-19.

Methods: A total of patients with 427 COVID-19 participated in the survey conducted from 5 to 15 June 2021 in Bac Giang province.

Chest X-ray Severity Score as a Putative Predictor of Clinical Outcome in Hospitalized Patients: An Experience From a Vietnamese COVID-19 Field Hospital.

Background Through the coronavirus disease 2019 (COVID-19) pandemic, portable radiography was particularly useful for assessing and monitoring the COVID-19 disease in Vietnamese field hospitals. It provides a convenient and precise picture of the progression of the disease. The purpose of this study was to evaluate the predictive value of chest radiograph reporting systems (Brixia and total severity score (TSS)) and the National Early Warning Score (NEWS) clinical score in a group of hospitalized patients with COVID-19.

The effects of the COVID-19 lockdown on patients with chronic cardiovascular disease in Vietnam.

Introduction: We evaluated the impact of the lockdown policy during the COVID-19 pandemic on cardiovascular outpatients of a cardiology clinic in Vietnam from April to June 2020. We estimated the occurrence of different cardiovascular problems in general and the stability of blood pressure.

Methodology: During the Covid-19 outbreak in Vietnam, we conducted a cross-sectional study to evaluate its impact on blood pressure stability of hypertensive patients treated as outpatients at the clinic of the University Medical Center (UMC), Ho Chi Minh City.