Kernel-based hierarchical structural component models for pathway analysis on survival phenotype.

Background: High-throughput sequencing, particularly RNA-sequencing (RNA-seq), has advanced differential gene expression analysis, revealing pathways involved in various biological conditions. Traditional pathway-based methods generally consider pathways independently, overlooking the correlations among them and ignoring quite a few overlapping biomarkers between pathways. In addition, most pathway-based approaches assume that biomarkers have linear effects on the phenotype of interest.

Association between intraoperative tidal volume and postoperative acute kidney injury in non-cardiac surgical patients using a propensity score-weighted analysis.

Acute kidney injury (AKI) is related to adverse clinical outcomes. Therefore, identifying patients at increased risk of postoperative AKI and proactively providing appropriate care is crucial. However, only a limited number of modifiable risk factors have been recognized to mitigate AKI risk.

Analysis of host factor networks during hepatitis B virus infection in primary human hepatocytes.

Background: Chronic hepatitis B virus (HBV) infection affects around 250 million people worldwide, causing approximately 887,000 deaths annually, primarily owing to cirrhosis and hepatocellular carcinoma (HCC). The current approved treatments for chronic HBV infection, such as interferon and nucleos(t)ide analogs, have certain limitations as they cannot completely eradicate covalently closed circular DNA (cccDNA). Considering that HBV replication relies on host transcription factors, focusing on host factors in the HBV genome may provide insights into new therapeutic targets against HBV.

Intrahepatic IgA complex induces polarization of cancer-associated fibroblasts to matrix phenotypes in the tumor microenvironment of HCC.

Background And Aims: Cancer-associated fibroblasts (CAFs) play key roles in the tumor microenvironment. IgA contributes to inflammation and dismantling antitumor immunity in the human liver. In this study, we aimed to elucidate the effects of the IgA complex on CAFs in Pil Soo Sung the tumor microenvironment of HCC.

Effect of driving pressure-guided positive end-expiratory pressure on postoperative pulmonary complications in patients undergoing laparoscopic or robotic surgery: a randomised controlled trial.

Background: Individualised positive end-expiratory pressure (PEEP) improves respiratory mechanics. However, whether PEEP reduces postoperative pulmonary complications (PPCs) remains unclear. We investigated whether driving pressure-guided PEEP reduces PPCs after laparoscopic/robotic abdominal surgery.

Conization before radical hysterectomy in patients with early-stage cervical cancer: A Korean multicenter study (COBRA-R).

Objective: To investigate the impact of conization on survival outcomes and to identify a specific population that might benefit from conization before radical hysterectomy (RH) in patients with early-stage cervical cancer.

Methods: From six institutions in Korea, we identified node-negative, margin-negative, parametria-negative, 2009 FIGO stage IB1 cervical cancer patients who underwent primary type C RH between 2006 and 2021. The patients were divided into multiple groups based on tumor size, surgical approach, and histology.

Proteomic Discovery of Plasma Protein Biomarkers and Development of Models Predicting Prognosis of High-Grade Serous Ovarian Carcinoma.

Ovarian cancer is one of the most lethal female cancers. For accurate prognosis prediction, this study aimed to investigate novel, blood-based prognostic biomarkers for high-grade serous ovarian carcinoma (HGSOC) using mass spectrometry-based proteomics methods. We conducted label-free liquid chromatography-tandem mass spectrometry using frozen plasma samples obtained from patients with newly diagnosed HGSOC (n = 20).

Development and Validation of 18F-FDG PET/CT-Based Models for Predicting Successful Complete Cytoreduction During Primary Cytoreductive Surgery for Advanced Ovarian cancer.

Purpose: The aim of this study was to develop an 18F-FDG PET/CT-based model to predict complete cytoreduction during primary cytoreductive surgery (CRS) for ovarian cancer (OC).

Patients And Methods: We retrospectively identified patients with stage III-IV OC who underwent primary CRS between June 2013 and February 2020 at 2 tertiary centers. Patients from each hospital were assigned to training and test sets.

Machine learning models to predict the maximum severity of COVID-19 based on initial hospitalization record.

Background: As the worldwide spread of coronavirus disease 2019 (COVID-19) continues for a long time, early prediction of the maximum severity is required for effective treatment of each patient.

Objective: This study aimed to develop predictive models for the maximum severity of hospitalized COVID-19 patients using artificial intelligence (AI)/machine learning (ML) algorithms.

Methods: The medical records of 2,263 COVID-19 patients admitted to 10 hospitals in Daegu, Korea, from February 18, 2020, to May 19, 2020, were comprehensively reviewed.

Kernel-based hierarchical structural component models for pathway analysis.

Motivation: Pathway analyses have led to more insight into the underlying biological functions related to the phenotype of interest in various types of omics data. Pathway-based statistical approaches have been actively developed, but most of them do not consider correlations among pathways. Because it is well known that there are quite a few biomarkers that overlap between pathways, these approaches may provide misleading results.

Clinicopathologic and protein markers distinguishing the "polymerase epsilon exonuclease" from the "copy number low" subtype of endometrial cancer.

Objective: The need to perform genetic sequencing to diagnose the polymerase epsilon exonuclease () subtype of endometrial cancer (EC) hinders the adoption of molecular classification. We investigated clinicopathologic and protein markers that distinguish the from the copy number (CN)-low subtype in EC.

Methods: Ninety-one samples (15 , 76 CN-low) were selected from The Cancer Genome Atlas EC dataset.

Comparisons of survival outcomes between bevacizumab and olaparib in -mutated, platinum-sensitive relapsed ovarian cancer: a Korean Gynecologic Oncology Group study (KGOG 3052).

Objective: To compare survival outcomes between bevacizumab (BEV) and olaparib (OLA) maintenance therapy in -mutated, platinum-sensitive relapsed (PSR) high-grade serous ovarian carcinoma (HGSOC).

Methods: From 10 institutions, we identified HGSOC patients with germline and/or somatic mutations, who experienced platinum-sensitive recurrence between 2013 and 2019, and received second-line platinum-based chemotherapy. Patients were divided into BEV (n=29), OLA (n=83), and non-BEV/non-OLA users (n=36).

Development of Machine Learning Models to Predict Platinum Sensitivity of High-Grade Serous Ovarian Carcinoma.

To support the implementation of individualized disease management, we aimed to develop machine learning models predicting platinum sensitivity in patients with high-grade serous ovarian carcinoma (HGSOC). We reviewed the medical records of 1002 eligible patients. Patients' clinicopathologic characteristics, surgical findings, details of chemotherapy, treatment response, and survival outcomes were collected.

Prediction Models for the Clinical Severity of Patients With COVID-19 in Korea: Retrospective Multicenter Cohort Study.

Background: Limited information is available about the present characteristics and dynamic clinical changes that occur in patients with COVID-19 during the early phase of the illness.

Objective: This study aimed to develop and validate machine learning models based on clinical features to assess the risk of severe disease and triage for COVID-19 patients upon hospital admission.

Methods: This retrospective multicenter cohort study included patients with COVID-19 who were released from quarantine until April 30, 2020, in Korea.

Clinical Characteristics and Outcomes of COVID-19 Cohort Patients in Daegu Metropolitan City Outbreak in 2020.

Background: A coronavirus disease 2019 (COVID-19) outbreak started in February 2020 and was controlled at the end of March 2020 in Daegu, the epicenter of the coronavirus outbreak in Korea. The aim of this study was to describe the clinical course and outcomes of patients with COVID-19 in Daegu.

Methods: In collaboration with Daegu Metropolitan City and Korean Center for Diseases Control, we conducted a retrospective, multicenter cohort study.

Development of Web-Based Nomograms to Predict Treatment Response and Prognosis of Epithelial Ovarian Cancer.

Purpose: Discovery of models predicting the exact prognosis of epithelial ovarian cancer (EOC) is necessary as the first step of implementation of individualized treatment. This study aimed to develop nomograms predicting treatment response and prognosis in EOC.

Materials And Methods: We comprehensively reviewed medical records of 866 patients diagnosed with and treated for EOC at two tertiary institutional hospitals between 2007 and 2016.

Photodynamic therapy by conjugation of cell-penetrating peptide with fluorochrome.

Photodynamic therapy (PDT) is a promising alternative therapy that could be used as an adjunct to chemotherapy and surgery for cancer, and works by destroying tissue with visible light in the presence of a photosensitizer (PS) and oxygen. The PS should restrict tissue destruction only to the tumor and be activated by light of a specific wavelength; both of these properties are required. Arginine-rich peptides, such as cell-penetrating peptides, have membrane-translocating and nuclear-localizing activities, which have led to their application in various drug delivery modalities.