Development, External Validation, and Visualization of Machine Learning Models for Predicting Occurrence of Acute Kidney Injury after Cardiac Surgery.

Background: Cardiac surgery-associated acute kidney injury (CSA-AKI) is a major complication that results in short- and long-term mortality among patients. Here, we adopted machine learning algorithms to build prediction models with the overarching goal of identifying patients who are at a high risk of such unfavorable kidney outcomes.

Methods: A total of 1686 patients (development cohort) and 422 patients (validation cohort), with 126 pre- and intra-operative variables, were recruited from the First Medical Centre and the Sixth Medical Centre of Chinese PLA General Hospital in Beijing, China, respectively.

Nomograms Predict PFS and OS for SCLC Patients After Standardized Treatment: A Real-World Study.

Purpose: This study aims to investigate the process of small cell lung cancer (SCLC) patients from achieving optimal efficacy to experiencing disease progression until death. It examines the predictive value of the treatment response on progression free survival (PFS) and overall survival (OS) of SCLC patients.

Patients And Methods: We conducted a retrospective analysis on 136 SCLC patients diagnosed from 1992 to 2018.

Deep learning for head and neck semi-supervised semantic segmentation.

. Radiation therapy (RT) represents a prevalent therapeutic modality for head and neck (H&N) cancer. A crucial phase in RT planning involves the precise delineation of organs-at-risks (OARs), employing computed tomography (CT) scans.

Attention Connect Network for Liver Tumor Segmentation from CT and MRI Images.

Currently, the incidence of liver cancer is on the rise annually. Precise identification of liver tumors is crucial for clinicians to strategize the treatment and combat liver cancer. Thus far, liver tumor contours have been derived through labor-intensive and subjective manual labeling.

A real-world study of immune checkpoint inhibitors in advanced triple-negative breast cancer.

Background: Triple-negative breast cancer (TNBC) is the most aggressive type of breast cancer. Immune checkpoint inhibitors (ICIs) have been widely used to treat various tumors and have changed the landscape of tumor management, but the data from real-world studies of ICIs for TNBC treatment remain limited. The aim of this study was to evaluate the efficacy of ICIs in the treatment of patients with advanced TNBC in a real-world setting and to explore possible correlates.

Relationship Between MUC4 Variants and Metastatic Recurrence in Colorectal Cancer.

Background: Recurrent metastasis after radical resection in patients of colorectal cancer (CRC) is a great challenge for the world, in which genomic alterations play a major role in tumorigenesis. MUC4 plays a significant role in recurrence and metastasis in tumor. This study is aimed at exploring the association between MUC4 variants and metastatic recurrence of CRC.

The upregulation of immune checkpoints after photodynamic therapy reducing immune effect for treating breast cancer.

The immune effect induced by photodynamic therapy (PDT) has a limited effect on breast tumor. This study hypothesized that suppressive immune checkpoints on T cells might upregulate after PDT, which may reduce the antitumor effect of PDT for treating breast tumor. This study explored the alteration of immune checkpoint for the first time.

Magnetic Resonance Diffusion Tensor Imaging Characterize the Hepatic Ischemia-Reperfusion Injury in an Animal Study.

Background: Hepatic ischemia-reperfusion (I/R) injury is the main cause of morbidity and mortality after hepatectomy; thus, new methods for reducing I/R injury are required. The aim of this study is to evaluate changes in the average apparent diffusion coefficient (ADC) and fractional anisotropy (FA) in rabbits with partial hepatic I/R injury with magnetic resonance diffusion tensor imaging (DTI).

Methods: The left lobe of the rabbit liver underwent 60 minutes of ischemia followed by 0.

Plasma exosomal hsa_circ_0079439 as a novel biomarker for early detection of gastric cancer.

Background: Due to the poor prognosis of gastric cancer (GC), early detection methods are urgently needed. Plasma exosomal circular RNAs (circRNAs) have been suggested as novel biomarkers for GC.

Aim: To identify a novel biomarker for early detection of GC.

Nomogram for predicting survival in patients with advanced hepatocellular carcinoma treated with PD-1 inhibitors: incorporating pre-treatment and post-treatment clinical parameters.

Background: Immunotherapy has transformed cancer treatment patterns for advanced hepatocellular carcinoma (aHCC) in recent years. Therefore, the identification of predictive biomarkers has important clinical implications.

Methods: We collected medical records from 117 aHCC patients treated with anti-PD-1 antibody.

The Significance of Neutrophil Extracellular Traps in Colorectal Cancer and Beyond: From Bench to Bedside.

Neutrophil extracellular traps (NETs), products of neutrophil death when exposed to certain stimuli, were first proposed as a type of response to bacterial infection in infectious diseases. Since then, extensive studies have discovered its involvement in other non-infectious inflammatory diseases including thromboembolism, autoimmune diseases, and cancer. Colorectal cancer (CRC) is one of the most common malignancies in the world.

Development of machine learning models for mortality risk prediction after cardiac surgery.

Background: We developed machine learning models that combine preoperative and intraoperative risk factors to predict mortality after cardiac surgery.

Methods: Machine learning involving random forest, neural network, support vector machine, and gradient boosting machine was developed and compared with the risk scores of EuroSCORE I and II, Society of Thoracic Surgeons (STS), as well as a logistic regression model. Clinical data were collected from patients undergoing adult cardiac surgery at the First Medical Centre of Chinese PLA General Hospital between December 2008 and December 2017.

Self-eating and Heart: The Emerging Roles of Autophagy in Calcific Aortic Valve Disease.

Autophagy is a self-degradative pathway by which subcellular elements are broken down intracellularly to maintain cellular homeostasis. Cardiac autophagy commonly decreases with aging and is accompanied by the accumulation of misfolded proteins and dysfunctional organelles, which are undesirable to the cell. Reduction of autophagy over time leads to aging-related cardiac dysfunction and is inversely related to longevity.

Case Report: Pseudoprogression With Nivolumab and Bevacizumab Followed by Recurrent Immune-Related Pneumonitis in Urothelial Carcinoma With Lung Metastasis.

Background: Combination therapy with immune checkpoint inhibitors (ICIs) and antiangiogenic agents is generally effective and well tolerated and might be effective for metastatic urothelial carcinoma (UC). However, ICI treatment is often associated with unique responses, such as pseudoprogression and ICI-related pneumonitis (CIP), which may influence clinical decision making and affect treatment. Although there have been many studies on the mechanism of pseudoprogression and CIP, the characteristics and relationship of these special events in a clinical setting remain rarely reported.