Development and validation of a multi-parametric MRI deep-learning model for preoperative lymphovascular invasion evaluation in rectal cancer.

Background: Lymphovascular invasion (LVI) is an independent prognostic factor for patients with rectal cancer (RC). Recent studies have shown that deep learning (DL)-based magnetic resonance imaging (MRI) has potential in evaluating the treatment response of RC patients, but the role of MRI-based DL in assessing RC LVI remains unclear. This study sought to develop and validate a DL model to evaluate the LVI status of RC patients preoperatively based on MRI, and to test its performance at an external center.

CP/HA/HGF Conductive Composite Scaffolds with Synergistic Electrical Stimulation for Nerve Regeneration.

The challenge of nerve regeneration stems from the diminished vitality of mature neurons post-injury. The construction of a suitable microenvironment at the injury site to facilitate axonal regeneration is a crucial aspect of nerve injury repair. In this work, a conductive and biocompatible composite material, CP/HA/HGF, is designed by grafting polypyrrole onto chitosan and compounding it with hyaluronic acid and functional short peptides for neural regeneration.

Construction of a prognostic prediction model for colorectal cancer based on 5-year clinical follow-up data.

Colorectal cancer (CRC) is a prevalent malignant tumor that presents significant challenges to both public health and healthcare systems. The aim of this study was to develop a machine learning model based on five years of clinical follow-up data from CRC patients to accurately identify individuals at risk of poor prognosis. This study included 411 CRC patients who underwent surgery at Yixing Hospital and completed the follow-up process.

Clinical Validation of MyProstateScore 2.0 Testing Using First-Catch, Non-DRE Urine.

Purpose: The 18-gene MyProstateScore 2.0 (MPS2) test was previously validated for detection of Grade Group≥2 (GG≥2) prostate cancer using post-digital rectal examination (DRE) urine. To improve ease of testing, we validated MPS2 using first-catch, non-DRE urine.

Preoperative ultrasound risk factors for peripartum hysterectomy among PAS suspected pregnancies.

Objective: This study aimed to identify risk factors for peripartum hysterectomy among pregnancies complicated by suspected Placenta Accreta Spectrum (PAS) in preoperative obstetric imaging screening.

Methods: Data were retrospectively extracted from the Longitudinal Placenta Accreta Spectrum Study (LoPASS), covering pregnancies with PAS from January 2018 to March 2023 at our institute. Patients were divided into Control and Hysterectomy groups based on whether they underwent hysterectomy.