Regulation of senescence-associated secretory phenotypes in osteoarthritis by cytosolic UDP-GlcNAc retention and O-GlcNAcylation.

UDP-GlcNAc serves as a building block for glycosaminoglycan (GAG) chains in cartilage proteoglycans and simultaneously acts as a substrate for O-GlcNAcylation. Here, we show that transporters for UDP-GlcNAc to the endoplasmic reticulum (ER) and Golgi are significantly downregulated in osteoarthritic cartilage, leading to increased cytosolic UDP-GlcNAc and O-GlcNAcylation in chondrocytes. Mechanistically, upregulated O-GlcNAcylation governs the senescence-associated secretory phenotype (SASP) by stabilizing GATA4 via O-GlcNAcylation at S406, which compromises its degradation by p62-mediated selective autophagy.

Privacy-Preserving Prediction of Postoperative Mortality in Multi-Institutional Data: Development and Usability Study.

Background: To circumvent regulatory barriers that limit medical data exchange due to personal information security concerns, we use homomorphic encryption (HE) technology, enabling computation on encrypted data and enhancing privacy.

Objective: This study explores whether using HE to integrate encrypted multi-institutional data enhances predictive power in research, focusing on the integration feasibility across institutions and determining the optimal size of hospital data sets for improved prediction models.

Methods: We used data from 341,007 individuals aged 18 years and older who underwent noncardiac surgeries across 3 medical institutions.

Multicentre validation of a machine learning model for predicting respiratory failure after noncardiac surgery.

Background: Postoperative respiratory failure is a serious complication that could benefit from early accurate identification of high-risk patients. We developed and validated a machine learning model to predict postoperative respiratory failure, defined as prolonged (>48 h) mechanical ventilation or reintubation after surgery.

Methods: Easily extractable electronic health record (EHR) variables that do not require subjective assessment by clinicians were used.

Predisposal of Interferon Regulatory Factor 1 Deficiency to Accumulate DNA Damage and Promote Osteoarthritis Development in Cartilage.

Objective: Interferon regulatory factor 1 (IRF1) is a transcriptional regulator conventionally associated with immunomodulation. Recent molecular analyses mapping DNA binding sites of IRF1 have suggested its potential function in DNA repair. However, the physiologic significance of this noncanonical function remains unexplored.

Hunting for the vulnerability in chondrosarcoma by tracing metabolic and genetic links.

In this Backstory, we narrate our journey in establishing a multidisciplinary team for sarcoma research and uncovering vulnerabilities in chondrosarcoma cells associated with their NAD dependencies for survival. Our findings hold promise for exploitation, yielding a synergistic cytotoxic effect when combined with systemic therapy.

Decoupling NAD metabolic dependency in chondrosarcoma by targeting the SIRT1-HIF-2α axis.

Chondrosarcomas represent the second most common primary bone malignancy. Despite the vulnerability of chondrosarcoma cells to nicotinamide adenine dinucleotide (NAD) depletion, targeting the NAD synthesis pathway remains challenging due to broad implications in biological processes. Here, we establish SIRT1 as a central mediator reinforcing the dependency of chondrosarcoma cells on NAD metabolism via HIF-2α-mediated transcriptional reprogramming.

Sarcoma Immunotherapy: Confronting Present Hurdles and Unveiling Upcoming Opportunities.

Sarcomas are rare and heterogeneous mesenchymal neoplasms originating from the bone or soft tissues, which pose significant treatment challenges. The current standard treatment for sarcomas consists of surgical resection, often combined with chemo- and radiotherapy; however, local recurrence and metastasis remain significant concerns. Although immunotherapy has demonstrated promise in improving long-term survival rates for certain cancers, sarcomas are generally considered to be relatively less immunogenic than other tumors, presenting substantial challenges for effective immunotherapy.

Causal relationship between particulate matter 2.5 and diabetes: two sample Mendelian randomization.

Backgrounds: Many studies have shown particulate matter has emerged as one of the major environmental risk factors for diabetes; however, studies on the causal relationship between particulate matter 2.5 (PM) and diabetes based on genetic approaches are scarce. The study estimated the causal relationship between diabetes and PM using two sample mendelian randomization (TSMR).

The effect of residential greenness during pregnancy on infant neurodevelopment using propensity score weighting: A prospective mother-infant paired cohort study.

Background: While prior studies have suggested an association between green spaces and infant neurodevelopment, the causal effect of green space exposure during pregnancy has not been fully investigated. This study aimed to identify with causal inference the effect of exposure to residential greenness during pregnancy on infants' mental-psychomotor development and the role of maternal education in modifying this association.

Methods: We prospectively collected data of pregnant women and their infants from Mothers and Children Environmental Health cohort study.

COVID-19, maternal, and neonatal outcomes: National Mother-Child Cohort (NMCC) of K-COV-N cohort in South Korea.

Throughout the COVID-19 pandemic, pregnant women have been classified as a vulnerable population. However, the evidence on the effect of infection during pregnancy on maternal and neonatal outcomes is still uncertain, and related research comprising a large population of pregnant women in Asian countries is limited. We constructed a national cohort including mothers and children (369,887 pairs) registered in the Prevention Agency-COVID-19-National Health Insurance Service (COV-N), from January 1, 2020 to March 31, 2022.

Multi-center validation of machine learning model for preoperative prediction of postoperative mortality.

Accurate prediction of postoperative mortality is important for not only successful postoperative patient care but also for information-based shared decision-making with patients and efficient allocation of medical resources. This study aimed to create a machine-learning prediction model for 30-day mortality after a non-cardiac surgery that adapts to the manageable amount of clinical information as input features and is validated against multi-centered rather than single-centered data. Data were collected from 454,404 patients over 18 years of age who underwent non-cardiac surgeries from four independent institutions.

A COVID-19 mortality prediction model for Korean patients using nationwide Korean disease control and prevention agency database.

The experience of the early nationwide COVID-19 pandemic in South Korea led to an early shortage of medical resources. For efficient resource allocation, accurate prediction of the prognosis or mortality of confirmed patients is essential. Therefore, the aim of this study was to develop an accurate model for predicting COVID-19 mortality using epidemiolocal and clinical variables and for identifying a high-risk group of confirmed patients.

ANNO: A General Annotation Tool for Bilingual Clinical Note Information Extraction.

Objective: This study was conducted to develop a generalizable annotation tool for bilingual complex clinical text annotation, which led to the design and development of a clinical text annotation tool, ANNO.

Methods: We designed ANNO to enable human annotators to support the annotation of information in clinical documents efficiently and accurately. First, annotations for different classes (word or phrase types) can be tagged according to the type of word using the dictionary function.

Reducing severe cutaneous adverse and type B adverse drug reactions using pre-stored human leukocyte antigen genotypes.

Background: Several type B adverse drug reactions (ADRs), especially severe cutaneous adverse reactions (SCARs), are associated with particular human leukocyte antigen (HLA) genotypes. However, pre-stored HLA information obtained from other clinical workups has not been used to prevent ADRs. We aimed to simulate the preemptive use of pre-stored HLA information in electronic medical records to evaluate whether this information can prevent ADRs.

Mortality Risk within 14 Days after Coronavirus Disease 2019 Diagnosis in Dementia Patients: A Nationwide Analysis.

Introduction: The study evaluated the increased mortality risk within 14 days of coronavirus disease 2019 (COVID-19) diagnosis in dementia patients.

Methods: This retrospective study was conducted from February to April 2020 using the COVID-19 patients' database from the Korea Disease Control and Prevention Agency. The risk factors for early death within 14 days were determined using generalized logistic regression performed in a stepwise manner.

CTRP3 exacerbates tendinopathy by dysregulating tendon stem cell differentiation and altering extracellular matrix composition.

Tendinopathy, the most common disorder affecting tendons, is characterized by chronic disorganization of the tendon matrix, which leads to tendon tear and rupture. The goal was to identify a rational molecular target whose blockade can serve as a potential therapeutic intervention for tendinopathy. We identified C1q/TNF-related protein-3 (CTRP3) as a markedly up-regulated cytokine in human and rodent tendinopathy.

Comprehensive DNA repair gene expression analysis and its prognostic significance in acute myeloid leukemia.

Background: Deficiency in DNA damage response (DDR) pathway and accumulation of DNA damage increases mutation rates resulting in genomic instability and eventually increases the risk of cancer. The aim of our study was to investigate expressions of DNA repair genes as new prognostic biomarkers in acute myeloid leukemia (AML).

Methods: We utilized The Cancer Genome Atlas AML project (TCGA-LAML cohort, 15 acute promyelocytic leukemia (APL) and 155 non-APL AML) for the expression data of DNA repair genes.

Time-sequential change in immune-related gene expression after irradiation in glioblastoma: next-generation sequencing analysis.

The time-sequential change in immune-related gene expression of the glioblastoma cell line after irradiation was evaluated to speculate the effect of combined immunotherapy with radiotherapy. The U373 MG glioblastoma cell line was irradiated with 6 Gy single dose. Next-generation sequencing (NGS) transcriptome data was generated before irradiation (control), and at 6, 24, and 48 h post-irradiation.

Identification of synthetic chemosensitivity genes paired with BRAF for BRAF/MAPK inhibitors.

Molecular-targeted approaches are important for personalised cancer treatment, which requires knowledge regarding drug target specificity. Here, we used the synthetic lethality concept to identify candidate gene pairs with synergistic effects on drug responses. A synergistic chemo-sensitivity response was identified if a drug had a significantly lower half-maximal inhibitory concentration (IC) in cell lines with a pair of mutated genes compared with those in other cell lines (wild-type or one mutated gene).

A system-level approach identifies HIF-2α as a critical regulator of chondrosarcoma progression.

Chondrosarcomas, malignant cartilaginous neoplasms, are capable of transitioning to highly aggressive, metastatic, and treatment-refractory states, resulting in significant patient mortality. Here, we aim to uncover the transcriptional program directing such tumor progression in chondrosarcomas. We conduct weighted correlation network analysis to extract a characteristic gene module underlying chondrosarcoma malignancy.

Immune expression signatures as candidate prognostic biomarkers of age and gender survival differences in cutaneous melanoma.

This study aims to investigate the difference of gene expression and its prognostic significance in younger women with melanoma. Significantly upregulated genes in tumors compared to normal skin tissues were extracted. Among these genes, genes that significantly affected survival according to expression level were selected, and pathway annotation was performed.

Increasing incidence and improving survival of oral tongue squamous cell carcinoma.

We evaluated changes in incidence, relative survival (RS), and conditional survival (CS) of head and neck squamous cell carcinoma (HNSCC), focusing on oral tongue squamous cell carcinoma (OTSCC). Data of 74 680 HNSCC patients from 1976 to 2015 were obtained from the Surveillance, Epidemiology, and End Results database. Five anatomical sites and their subsites were analyzed.

Extracting Structured Genotype Information from Free-Text HLA Reports Using a Rule-Based Approach.

Background: Human leukocyte antigen (HLA) typing is important for transplant patients to prevent a severe mismatch reaction, and the result can also support the diagnosis of various disease or prediction of drug side effects. However, such secondary applications of HLA typing results are limited because they are typically provided in free-text format or PDFs on electronic medical records. We here propose a method to convert HLA genotype information stored in an unstructured format into a reusable structured format by extracting serotype/allele information.

Targeted next-generation DNA sequencing identifies Notch signaling pathway mutation as a predictor of radiation response.

Identifying the association between somatic mutations and the radiation response of tumor is essential for understanding the mechanisms and practicing personalized radiotherapy. The present study aimed to discover specific genes or pathways that are associated with radiation response using targeted next-generation DNA sequencing. Fifty-five patients with various solid tumors whose specimen were sequenced using institutional panel which includes 148 cancer-related genes and received radiotherapy for a measurable tumor were analyzed.