Semaglutide and Postoperative Outcomes in Non-Diabetic Patients Following Body Contouring Surgery.

Background: Semaglutide is a medication used for weight loss in obese patients. Recently, many plastic surgeons have recommended its use of semaglutide following bariatric surgery to increase one's weight loss. However, postoperative complications such as wound dehiscence, delayed healing, and infection pose significant risks.

Evaluation of Accuracy and Engagement of Otolaryngology Educational Videos on Instagram.

To examine the accuracy, engagement, and quality of otolaryngology-related educational videos produced by health care providers on Instagram. A systematic search on Instagram was conducted to identify the top 150 video posts using the hashtags #Otolaryngology, #Otolaryngologist, and #ENTeducation, ranging from September 2020 to January 2024. Posts not related to otolaryngology medical education were excluded from analysis.

Aligning our actions with our words: A systematic review of gender and racial diversity in surgical subspecialties.

Introduction: Persistent racial and gender disparities are prevalent within the higher education and medical training system, notably seen in the underrepresentation of Hispanic or Latinos, Black Americans, and female surgeons compared to their respective population proportions. This study aims to quantify publications addressing ethnic or gender diversity across various surgical specialties, analyze publication trends, and explore specific topics within medical literature.

Database: The Database includes PubMed, Google Scholar, and Scopus.

Unveiling Sex Differences in Pediatric Burns Through the World Health Organization (WHO) Global Burn Registry.

Introduction: Pediatric burns present a significant global health challenge, particularly in low- and middle-income countries (LMICs). Despite this burden, few studies have explored global sex-based differences in pediatric burns. This study aims to describe pediatric burn incidence, burn care facilities' capacities, and burn outcomes with a focus on sex, comparing LMICs to HICs.

Advances in Bone Marrow Evaluation.

Evaluation of bone marrow aspirate smear and trephine biopsy specimens is critical to the diagnosis of benign and malignant hematologic conditions. Digital pathology has the potential to revolutionize bone marrow assessment through implementation of artificial intelligence for assisted and automated evaluation, but there remain many barriers toward this implementation. This article reviews the current state of digital evaluation of bone marrow aspirate smears and trephine biopsies, recent research using machine learning models for automated specimen analysis, an outline of the advantages and barriers facing clinical implementation of artificial intelligence, and a potential vision of artificial intelligence-associated bone marrow evaluation.

The Immunophenotypic Profile of Healthy Human Bone Marrow.

Flow cytometry enables multiparametric characterization of hematopoietic cell immunophenotype. Deviations from normal immunophenotypic patterns comprise a cardinal feature of many hematopoietic neoplasms, underscoring the ongoing essentiality of flow cytometry as a diagnostic tool. However, understanding of aberrant hematopoiesis requires an equal understanding of normal hematopoiesis as a comparator.

Lessons learned: A look back at the performance of nine COVID-19 serologic assays and their proposed utility.

Background: Serologic assays for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been proposed to assist with the acute diagnosis of infection, support epidemiological studies, identify convalescent plasma donors, and evaluate vaccine response.

Methods: We report an evaluation of nine serologic assays: Abbott (AB) and Epitope (EP) IgG and IgM, EUROIMMUN (EU) IgG and IgA, Roche anti-N (RN TOT) and anti-S (RS TOT) total antibody, and DiaSorin (DS) IgG. We evaluated 291 negative controls (NEG CTRL), 91 PCR positive (PCR POS) patients (179 samples), 126 convalescent plasma donors (CPD), 27 healthy vaccinated donors (VD), and 20 allogeneic hematopoietic stem cell transplant (HSCT) recipients (45 samples).

An Automated Pipeline for Differential Cell Counts on Whole-Slide Bone Marrow Aspirate Smears.

The pathologic diagnosis of bone marrow disorders relies in part on the microscopic analysis of bone marrow aspirate (BMA) smears and the manual counting of marrow nucleated cells to obtain a differential cell count (DCC). This manual process has significant limitations, including the analysis of only a small subset of optimal slide areas and nucleated cells, as well as interobserver variability due to differences in cell selection and classification. To address these shortcomings, we developed an automated machine learning-based pipeline for obtaining 11-component DCCs on whole-slide BMAs.

Integration of machine learning and genome-scale metabolic modeling identifies multi-omics biomarkers for radiation resistance.

Resistance to ionizing radiation, a first-line therapy for many cancers, is a major clinical challenge. Personalized prediction of tumor radiosensitivity is not currently implemented clinically due to insufficient accuracy of existing machine learning classifiers. Despite the acknowledged role of tumor metabolism in radiation response, metabolomics data is rarely collected in large multi-omics initiatives such as The Cancer Genome Atlas (TCGA) and consequently omitted from algorithm development.

Personalized Genome-Scale Metabolic Models Identify Targets of Redox Metabolism in Radiation-Resistant Tumors.

Redox cofactor production is integral toward antioxidant generation, clearance of reactive oxygen species, and overall tumor response to ionizing radiation treatment. To identify systems-level alterations in redox metabolism that confer resistance to radiation therapy, we developed a bioinformatics pipeline for integrating multi-omics data into personalized genome-scale flux balance analysis models of 716 radiation-sensitive and 199 radiation-resistant tumors. These models collectively predicted that radiation-resistant tumors reroute metabolic flux to increase mitochondrial NADPH stores and reactive oxygen species (ROS) scavenging.

MTHFD2 Blockade Enhances the Efficacy of β-Lapachone Chemotherapy With Ionizing Radiation in Head and Neck Squamous Cell Cancer.

Head and Neck Squamous Cell Cancer (HNSCC) presents with multiple treatment challenges limiting overall survival rates and affecting patients' quality of life. Amongst these, resistance to radiation therapy constitutes a major clinical problem in HNSCC patients compounded by origin, location, and tumor grade that limit tumor control. While cisplatin is considered the standard radiosensitizing agent for definitive or adjuvant radiotherapy, in recurrent tumors or for palliative care other chemotherapeutics such as the antifolates methotrexate or pemetrexed are also being utilized as radiosensitizers.

An Integrative Gene Expression and Mathematical Flux Balance Analysis Identifies Targetable Redox Vulnerabilities in Melanoma Cells.

Melanomas harboring mutations can be treated with inhibitors (i), but responses are varied and tumor recurrence is inevitable. Here we used an integrative approach of experimentation and mathematical flux balance analyses in -mutated melanoma cells to discover that elevated antioxidant capacity is linked to i sensitivity in melanoma cells. High levels of antioxidant metabolites in cells with reduced i sensitivity confirmed this conclusion.

Peroxiredoxins in Cancer and Response to Radiation Therapies.

Peroxiredoxins have a long-established cellular function as regulators of redox metabolism by catalyzing the reduction of peroxides (e.g., H₂O₂, lipid peroxides) with high catalytic efficiency.

Targeting NAD Metabolism to Enhance Radiation Therapy Responses.

Nicotinamide adenine dinucleotide (NAD) metabolism is integrally connected with the mechanisms of action of radiation therapy and is altered in many radiation-resistant tumors. This makes NAD metabolism an ideal target for therapies that increase radiation sensitivity and improve patient outcomes. This review provides an overview of NAD metabolism in the context of the cellular response to ionizing radiation, as well as current therapies that target NAD metabolism to enhance radiation therapy responses.

Predicting clinical outcomes from large scale cancer genomic profiles with deep survival models.

Translating the vast data generated by genomic platforms into accurate predictions of clinical outcomes is a fundamental challenge in genomic medicine. Many prediction methods face limitations in learning from the high-dimensional profiles generated by these platforms, and rely on experts to hand-select a small number of features for training prediction models. In this paper, we demonstrate how deep learning and Bayesian optimization methods that have been remarkably successful in general high-dimensional prediction tasks can be adapted to the problem of predicting cancer outcomes.

Genome-Scale Modeling of NADPH-Driven β-Lapachone Sensitization in Head and Neck Squamous Cell Carcinoma.

Aims: The purpose of this study was to investigate differential nicotinamide adenine dinucleotide phosphate, reduced (NADPH) production between radiation-sensitive and -resistant head and neck squamous cell carcinoma (HNSCC) cell lines and whether these differences are predictive of sensitivity to the chemotherapeutic β-lapachone.

Results: We have developed a novel human genome-scale metabolic modeling platform that combines transcriptomic, kinetic, thermodynamic, and metabolite concentration data. Upon incorporation of this information into cell line-specific models, we observed that the radiation-resistant HNSCC model redistributed flux through several major NADPH-producing reactions.