Disclosing the impact of metformin and methotrexate in adjuvant arthritis in female rats: molecular docking and biochemical insights on visfatin.

Rheumatoid arthritis (RA) is one of the most common systemic autoimmune inflammatory diseases, with a progressive etiology that results in serious complications and a higher chance of early death. Visfatin, an adipokine, is correlated with disease pathologic features and becomes a key biomarker and therapeutic target for RA. This study aimed to evaluate the anti-arthritic activity of metformin (an antidiabetic drug with anti-inflammatory activities) and methotrexate (the first choice for disease-modifying antirheumatic drugs in RA, with diverse adverse effects) in complete Freund's adjuvant (CFA)-induced arthritis in female rats.

Establishing a preoperative predictive model for gallbladder adenoma and cholesterol polyps based on machine learning: a multicentre retrospective study.

Background: With the rising diagnostic rate of gallbladder polypoid lesions (GPLs), differentiating benign cholesterol polyps from gallbladder adenomas with a higher preoperative malignancy risk is crucial. This study aimed to establish a preoperative prediction model capable of accurately distinguishing between gallbladder adenomas and cholesterol polyps using machine learning algorithms.

Materials And Methods: We retrospectively analysed the patients' clinical baseline data, serological indicators, and ultrasound imaging data.

Evaluating the Potential of Quantitative Susceptibility Mapping for Detecting Iron Deposition of Renal Fibrosis in a Rabbit Model.

Background: As ferroptosis is a key factor in renal fibrosis (RF), iron deposition monitoring may help evaluating RF. The capability of quantitative susceptibility mapping (QSM) for detecting iron deposition in RF remains uncertain.

Purpose: To investigate the potential of QSM to detect iron deposition in RF.

F-18 FDG PET/CT based Preoperative Machine Learning Prediction Models for Evaluating Regional Lymph Node Metastasis Status of Patients with Colon Cancer.

Objective: This study aimed to develop a simple machine-learning model incorporating lymph node metastasis status with F-18 Fluorodeoxyglucose positron emission tomography/computed tomography (FDG PET/CT) and clinical information for predicting regional lymph node metastasis in patients with colon cancer.

Methods: This retrospective study included 193 patients diagnosed with colon cancer between January 2014 and December 2017. All patients underwent F-18 FDG PET/CT and blood test before surgery.

Identification of ubiquitination-related key biomarkers and immune infiltration in Crohn's disease by bioinformatics analysis and machine learning.

Crohn's disease (CD) is a chronic inflammatory bowel disease with an unknown etiology. Ubiquitination plays a significant role in the pathogenesis of CD. This study aimed to explore the functional roles of ubiquitination-related genes in CD.

Deep learning uncovers histological patterns of YAP1/TEAD activity related to disease aggressiveness in cancer patients.

Over the last decade, Hippo signaling has emerged as a major tumor-suppressing pathway. Its dysregulation is associated with abnormal expression of and -family genes. Recent works have highlighted the role of YAP1/TEAD activity in several cancers and its potential therapeutic implications.

Comprehensive Sepsis Risk Prediction in Leukemia Using a Random Forest Model and Restricted Cubic Spline Analysis.

Background: Sepsis is a severe complication in leukemia patients, contributing to high mortality rates. Identifying early predictors of sepsis is crucial for timely intervention. This study aimed to develop and validate a predictive model for sepsis risk in leukemia patients using machine learning techniques.

Research on noise-induced hearing loss based on functional and structural MRI using machine learning methods.

Noise-induced hearing loss (NIHL) is a common occupational condition. The aim of this study was to develop a classification model for NIHL on the basis of both functional magnetic resonance imaging (fMRI) and structural magnetic resonance imaging (sMRI) by applying machine learning methods. fMRI indices such as the amplitude of low-frequency fluctuation (ALFF), fractional amplitude of low-frequency fluctuation (fALFF), regional homogeneity (ReHo), degree of centrality (DC), and sMRI indices such as gray matter volume (GMV), white matter volume (WMV), and cortical thickness were extracted from each brain region.

SERT-Deficient Mice Fed Western Diet Reveal Altered Metabolic and Pro-Inflammatory Responses of the Liver: A Link to Abnormal Behaviors.

Background: The inheritance of the short allele, encoding the serotonin transporter (SERT) in humans, increases susceptibility to neuropsychiatric and metabolic disorders, with aging and female sex further exacerbating these conditions. Both central and peripheral mechanisms of the compromised serotonin (5-HT) system play crucial roles in this context. Previous studies on SERT-deficient (Sert) mice, which model human SERT deficiency, have demonstrated emotional and metabolic disturbances, exacerbated by exposure to a high-fat Western diet (WD).

Real-World Impact of Olaparib Exposure in Advanced Pancreatic Cancer Patients Harboring Germline BRCA1-2 Pathogenic Variants.

Introduction: Pancreatic cancer arising in the context of BRCA predisposition may benefit from poly(ADP-ribose) polymerase inhibitors. We analyzed real-world data on the impact of olaparib on survival in metastatic pancreatic cancer patients harboring germline BRCA mutations in Italy, where olaparib is not reimbursed for this indication.

Methods: Clinico/pathological data of pancreatic cancer patients with documented BRCA1-2 germline pathogenic variants who had received first-line chemotherapy for metastatic disease were collected from 23 Italian oncology departments and the impact of olaparib exposure on overall survival (OS) was analyzed.

Retinal Protection of New Nutraceutical Formulation.

Retinal ganglion cell (RGC) protection represents an unmet need in glaucoma. This study assessed the neuroprotective, antioxidant, and anti-inflammatory effect of a new nutraceutical formulation named Epicolin, based on citicoline, homotaurine, epigallocatechin-3-gallate, forskolin, and vitamins, through in vitro and in vivo studies. The neuroprotective effect of Epicolin or its single components, and Epicolin compared to an untreated control and two marketed formulations [Formulation G (FG) and N (FN)], was evaluated in neuroblastoma cells (SH-SY5Y) challenged with staurosporine.

Cellular Senescence in Hepatocellular Carcinoma: Immune Microenvironment Insights via Machine Learning and In Vitro Experiments.

Hepatocellular carcinoma (HCC), a leading liver tumor globally, is influenced by diverse risk factors. Cellular senescence, marked by permanent cell cycle arrest, plays a crucial role in cancer biology, but its markers and roles in the HCC immune microenvironment remain unclear. Three machine learning methods, namely k nearest neighbor (KNN), support vector machine (SVM), and random forest (RF), are utilized to identify eight key HCC cell senescence markers (HCC-CSMs).

Unveiling the Mechanisms of a Remission in Major Depressive Disorder (MDD)-like Syndrome: The Role of Hippocampal Palmitoyltransferase Expression and Stress Susceptibility.

Post-translational modifications of proteins via palmitoylation, a thioester linkage of a 16-carbon fatty acid to a cysteine residue, reversibly increases their affinity for cholesterol-rich lipid rafts in membranes, changing their function. Little is known about how altered palmitoylation affects function at the systemic level and contributes to CNS pathology. However, recent studies suggested a role for the downregulation of palmitoyl acetyltransferase (DHHC) 21 gene expression in the development of Major Depressive Disorder (MDD)-like syndrome.

Plasma levels of glial fibrillary acidic protein and neurofilament light chain in patients with chronic migraine: a multicenter case-control study.

Objective: Plasma glial fibrillary acidic protein (pGFAP) and plasma neurofilament light chain (pNfL) levels reflect astrocyte activation and neuronal damage, respectively. Whether these phenomena play a role in migraine is unknown. This study aimed to compare pGFAP and pNfL levels in patients with chronic migraine (CM) and age-matched controls and to analyze their relation with clinical features.

Fast Hadamard-Encoded 7T Spectroscopic Imaging of Human Brain.

: The increased SNR available at 7T combined with fast readout trajectories enables accelerated spectroscopic imaging acquisitions for clinical applications. In this report, we evaluate the performance of a Hadamard slice encoding strategy with a 2D rosette trajectory for multi-slice fast spectroscopic imaging at 7T. : Moderate-TE (~40 ms) spin echo and J-refocused polarization transfer sequences were acquired with simultaneous Hadamard multi-slice excitations and rosette in-plane encoding.

Characterization and Machine Learning-Driven Property Prediction of a Novel Hybrid Hydrogel Bioink Considering Extrusion-Based 3D Bioprinting.

The field of tissue engineering has made significant advancements with extrusion-based bioprinting, which uses shear forces to create intricate tissue structures. However, the success of this method heavily relies on the rheological properties of bioinks. Most bioinks use shear-thinning.

Taba Binary, Multinomial, and Ordinal Regression Models: New Machine Learning Methods for Classification.

The classification methods of machine learning have been widely used in almost every discipline. A new classification method, called Taba regression, was introduced for analyzing binary, multinomial, and ordinal outcomes. To evaluate the performance of Taba regression, liver cirrhosis data obtained from a Mayo Clinic study were analyzed.

Anti-arthritic Effects of Undifferentiated and Chondrogenic Differentiated MSCs in MIA-induced Osteoarthritis in Wistar Rats: Involvement of Oxidative Stress and Immune Modulation.

Introduction: Osteoarthritis (OA) is a degenerative joint disease that can affect the many tissues of the joint. There are no officially recognized disease-modifying therapies for clinical use at this time probably due to a lack of complete comprehension of the pathogenesis of the disease. In recent years, emerging regenerative therapy and treatments with stem cells both undifferentiated and differentiated cells have gained much attention as they can efficiently promote tissue repair and regeneration.

Hip Arthroscopy and Its Impact on Performance in National Hockey League Players Using Team-Based Advanced Performance Statistics.

Background: Ice hockey players have a high rate of hip pathology, which can lead to hip arthroscopy. Previous studies have not utilized team-based advanced performance statistics in the setting of hip arthroscopy in National Hockey League (NHL) players.

Purpose/hypothesis: The purpose of this study was to use team-based advanced performance statistics to evaluate postoperative performance after hip arthroscopy in NHL players in comparison with their preoperative performance and matched controls of uninjured skaters.

An early lung cancer diagnosis model for non-smokers incorporating ct imaging analysis and circulating genetically abnormal cells (CACs).

Background: An increase in the prevalence of lung cancer that is not smoking-related has been noticed in recent years. Unfortunately, these patients are not included in low dose computer tomography (LDCT) screening programs and are not actually considered in early diagnosis. Therefore, improved early diagnosis methods are urgently needed for non-smokers.

Periodically poled aluminum scandium nitride bulk acoustic wave resonators and filters for communications in the 6G era.

Bulk Acoustic Wave (BAW) filters find applications in radio frequency (RF) communication systems for Wi-Fi, 3G, 4G, and 5G networks. In the beyond-5G (potential 6G) era, high-frequency bands (>8 GHz) are expected to require resonators with high-quality factor (Q) and electromechanical coupling ( ) to form filters with low insertion loss and high selectivity. However, both the Q and of resonator devices formed in traditional uniform polarization piezoelectric films of aluminum nitride (AlN) and aluminum scandium nitride (AlScN) decrease when scaled beyond 8 GHz.

Mineral Stress Drives Loss of Heterochromatin: An Early Harbinger of Vascular Inflammaging and Calcification.

Background: Vascular calcification is a detrimental aging pathology markedly accelerated in patients with chronic kidney disease. Prelamin A is a biomarker of vascular smooth muscle cell aging that accelerates calcification however the mechanisms remain undefined.

Methods: Vascular smooth muscle cells were transduced with prelamin A using an adenoviral vector and epigenetic modifications were monitored using immunofluorescence and targeted polymerase chain reaction array.

Gossypin Ameliorates Collagen-Induced Arthritic Rats by Inhibiting Angiogenesis, Inflammation and Oxidative Stress.

Background: Rheumatoid arthritis (RA) is a long-term inflammatory autoimmune disease that damages cartilage and synovial membranes while also affecting bones and joints. The aim of the current study was to investigate the antiarthritic effect of gossypin against collagen-induced arthritis (CIA) in rats.

Methods: Intraperitoneal administration of Type II collagen (2 mg/mL) was used to induce arthritis in the rats, followed by oral administration of gossypin (5, 10 and 15 mg/kg) for 28 days.

Programmable wave-based analog computing machine: a metastructure that designs metastructures.

The ability to perform mathematical computations using metastructures is an emergent paradigm that carries the potential of wave-based analog computing to the realm of near-speed-of-light, low-loss, compact devices. We theoretically introduce and experimentally verify the concept of a reconfigurable metastructure that performs analog complex mathematical computations using electromagnetic waves. Reconfigurable, RF-based components endow our device with the ability to perform stationary and non-stationary iterative algorithms.