Sanggenol L Alleviates Rotenone-induced Parkinson's Disease and Inhibits Mitochondrial Complex I by Apoptosis Via P13K/AKT/mTOR Signalling.

Background: Parkinson's disease (PD) is the age-associated, second most advanced neurodegenerative illness. Rotenone is an extensively used pesticide to study PD pathology and inhibits mitochondrial complex I. Reports indicate that rotenone exerts neurotoxicity by its capability to produce reactive oxygen species (ROS), which eventually leads to neuronal apoptosis.

Environmentally friendly synthesis of gelatin hydrogel nanoparticles for gastric cancer treatment, bisphenol A sensing and nursing applications: Fabrication, characterization and ANN modeling.

This study presents a dual application approach for the environmentally friendly synthesis of gelatin hydrogel nanoparticles with potential applications in gastric cancer treatment, bisphenol A (BPA) sensing, and nursing. Gelatin hydrogel nanoparticles were synthesized using a green and freeze-drying method, avoiding the use of toxic chemicals and solvents. The nanoparticles showed excellent biocompatibility and promising potential for drug delivery system (DDS) in gastric cancer treatment.

Mediated Targeting // to Accelerate Thyroid Stimulating Hormone-Induced Hepatic Steatosis.

Purpose: Thyroid-stimulating hormone (TSH) has been identified as an independent risk factor for non-alcoholic fatty liver disease (NAFLD), TSH binds to the TSH receptor (TSHR) to exert its function. However, the underlying mechanisms by which TSHR influences NAFLD development remain unclear. This study investigates the role of in NAFLD progression.

Changes in immune status of circulating NK cells in patients with latent tuberculosis infection.

Introduction: The presence of patients with latent tuberculosis infection (LTBI) has fueled the tuberculosis pandemic. We aimed to investigate the immune status of NK cells in LTBI patients.

Material And Methods: Twenty-one LTBI patients, 25 active pulmonary tuberculosis (APTB) patients and 25 healthy controls (HCs) participated in our research.

TCD-Guided management in carotid endarterectomy: a retrospective study.

BACKGROUNDː: Stroke, primarily resulting from ischemic conditions, is the foremost cause of mortality and long-term impairment and is frequently associated with narrowing of the carotid arteries. Although carotid endarterectomy (CEA) is the treatment of choice, it carries the risk of cerebral ischemia and reduced blood flow. Transcranial Doppler (TCD) ultrasound offers a nonintrusive method to assess cerebral blood circulation during CEA, potentially enhancing surgical outcomes.

Robot-Assisted Ocular Tumour Radiotherapy Positioning and Tracking System.

Background: Precise dose position distribution is crucial for ocular proton therapy.

Methods: A non-invasive eye positioning and tracking system with novel structure is designed to reduce eye movement and facilitate precise dose by guiding the direction of patients' gaze. The system helps to achieve gaze guidance by controlling the light source fixed on two turntables above the patient's face.

Enhancing prostate cancer segmentation on multiparametric magnetic resonance imaging with background information and gland masks.

Background: The landscape of prostate cancer (PCa) segmentation within multiparametric magnetic resonance imaging (MP-MRI) was fragmented, with a noticeable lack of consensus on incorporating background details, culminating in inconsistent segmentation outputs. Given the complex and heterogeneous nature of PCa, conventional imaging segmentation algorithms frequently fell short, prompting the need for specialized research and refinement.

Purpose: This study sought to dissect and compare various segmentation methods, emphasizing the role of background information and gland masks in achieving superior PCa segmentation.

Automated Cerebrovascular Segmentation and Visualization of Intracranial Time-of-Flight Magnetic Resonance Angiography Based on Deep Learning.

Time-of-flight magnetic resonance angiography (TOF-MRA) is a non-contrast technique used to visualize neurovascular. However, manual reconstruction of the volume render (VR) by radiologists is time-consuming and labor-intensive. Deep learning-based (DL-based) vessel segmentation technology may provide intelligent automation workflow.

Robot-assisted system for non-invasive wide-range flexible eye positioning and tracking in particle radiotherapy.

Particle (proton, carbon ion, or others) radiotherapy for ocular tumors is highly dependent on precise dose distribution, and any misalignment can result in severe complications. The proposed eye positioning and tracking system (EPTS) was designed to non-invasively position eyeballs and is reproducible enough to ensure accurate dose distribution by guiding gaze direction and tracking eye motion. Eye positioning was performed by guiding the gaze direction with separately controlled light sources.

[An early warning model for sepsis complicated with acute respiratory distress syndrome based on synthetic minority oversampling technique algorithm].

Objective: To explore the independent risk factors of acute respiratory distress syndrome (ARDS) in patients with sepsis, establish an early warning model, and verify the predictive value of the model based on synthetic minority oversampling technique (SMOTE) algorithm.

Methods: A retrospective case-control study was conducted. 566 patients with sepsis who were admitted to Jinan People's Hospital from October 2016 to October 2022 were enrolled.

Prognostic value and drug sensitivity of F‑box and leucine‑rich repeat protein 6 in glioma.

Gliomas are highly malignant and invasive tumors lacking clear boundaries. Previous bioinformatics and experimental analyses have indicated that F-box and leucine-rich repeat protein 6 (FBXL6), a protein crucial for the cell cycle and tumorigenesis, is highly expressed in certain types of tumors. The high expression level of FBXL6 is reported to promote tumor growth and adversely affect patient survival.

Automatic assessment of DWI-ASPECTS for acute ischemic stroke based on deep learning.

Background: Alberta Stroke Program Early Computed Tomography Score (ASPECTS) is a standardized semi-quantitative method for early ischemic changes in acute ischemic stroke.

Purpose: However, ASPECTS is still affected by expert experience and inconsistent results between readers in clinical. This study aims to propose an automatic ASPECTS scoring model based on diffusion-weighted imaging (DWI) mode to help clinicians make accurate treatment plans.

The role of hydrogen in the prevention and treatment of coronary atherosclerotic heart disease.

Coronary atherosclerotic heart disease (CHD) is a primary cardiovascular disease caused by atherosclerosis (AS), which is characterized by chronic inflammation and lipid oxidative deposition. Molecular hydrogen (H) is an effective anti-inflammatory agent and has potential to ameliorate glycolipid metabolism disorders, which is believed to exert beneficial effects on the prevention and treatment of CHD. It is suggested that H reduces inflammation in CHD by regulating multiple pathways, including NF-κB inflammatory pathway, pyroptosis, mitophagy, endoplasmic reticulum (ER) stress, and Nrf2 antioxidant pathway.

Serum iron element: A novel biomarker for predicting PD-1 immunotherapy efficacy.

This study aims to explore the relationship between serum iron by inductively coupled plasma-mass spectrometry (ICP-MS) and the efficacy of immune checkpoint inhibitors (ICIs) and potential mechanism. Totally 113 patients from 233 patients with advanced metastatic lung cancer, esophageal cancer, gastric cancer and colorectal cancer who treated with immunotherapy in Shandong Provincial Hospital were divided into training group (n=68) and validation group (n=45), whose patients were divided into clinical benefit response (CBR) and non-clinical benefit (NCB) by RECIST (v1.1) respectively.

Feature Fusion for Multi-Coil Compressed MR Image Reconstruction.

Magnetic resonance imaging (MRI) occupies a pivotal position within contemporary diagnostic imaging modalities, offering non-invasive and radiation-free scanning. Despite its significance, MRI's principal limitation is the protracted data acquisition time, which hampers broader practical application. Promising deep learning (DL) methods for undersampled magnetic resonance (MR) image reconstruction outperform the traditional approaches in terms of speed and image quality.

Development and internal validation of a clinical prediction model for spontaneous abortion risk in early pregnancy.

Objective: This study aimed to develop and internally validate a prediction model for estimating the risk of spontaneous abortion in early pregnancy.

Methods: This prospective cohort study included 9,895 pregnant women who received prenatal care at a maternal health facility in China from January 2021 to December 2022. Data on demographics, medical history, lifestyle factors, and mental health were collected.

CircTMEM87A promotes the tumorigenesis of gastric cancer by regulating the miR-1276/SLC7A11 axis.

Background: Gastric cancer (GC) is a common malignancy with high incidence and mortality, and its pathogenesis involves the regulation of circular RNAs (circRNAs). However, the molecular mechanism of circTMEM87A in GC malignant progression is uncertain.

Methods: Quantitative real-time polymerase chain reaction (qRT-PCR) was performed to detect the expressions of circTMEM87A, miR-1276, and solute carrier family 7 membrane 11 (SLC7A11).

A deep learning and radiomics based Alberta stroke program early CT score method on CTA to evaluate acute ischemic stroke.

Background: Alberta stroke program early CT score (ASPECTS) is a semi-quantitative evaluation method used to evaluate early ischemic changes in patients with acute ischemic stroke, which can guide physicians in treatment decisions and prognostic judgments.

Objective: We propose a method combining deep learning and radiomics to alleviate the problem of large inter-observer variance in ASPECTS faced by physicians and assist them to improve the accuracy and comprehensiveness of the ASPECTS.

Methods: Our study used a brain region segmentation method based on an improved encoding-decoding network.

Joint two-stage convolutional neural networks for intracranial aneurysms detection on 3D TOF-MRA.

. This study aims to develop a three-dimensional convolutional neural network utilizing computer-aided diagnostic technology to facilitate the detection of intracranial aneurysms and automatically assess their location and extent, thereby enhancing the efficiency of radiologists, and streamlining clinical workflows..

Identification of lymph node metastasis in pre-operation cervical cancer patients by weakly supervised deep learning from histopathological whole-slide biopsy images.

Background: Lymph node metastasis (LNM) significantly impacts the prognosis of individuals diagnosed with cervical cancer, as it is closely linked to disease recurrence and mortality, thereby impacting therapeutic schedule choices for patients. However, accurately predicting LNM prior to treatment remains challenging. Consequently, this study seeks to utilize digital pathological features extracted from histopathological slides of primary cervical cancer patients to preoperatively predict the presence of LNM.

Knockdown of circEXOC6 inhibits cell progression and glycolysis by sponging miR-433-3p and mediating FZD6 in glioma.

Background: The effect of circular RNA in many human cancers is widely studied. Nevertheless, their specific biological functions and mechanisms in glioma remain unclear.

Methods: CircEXOC6, miR-433-3p, and frizzled class receptor 6 (FZD6) mRNA expression levels were measured by quantitative reverse transcription polymerase chain reaction assay.