Adipose ZFP36 protects against diet-induced obesity and insulin resistance.

Aims: Obesity, as a worldwide healthcare problem, has become more prevalent. ZFP36 is a well-known RNA-binding protein and involved in the posttranscriptional regulation of many physiological processes. Whether the adipose ZFP36 plays a role in obesity and insulin resistance remains unclear.

Complement Factor H Promotes the Growth of Lung Adenocarcinoma Cells through the JAK2/STAT3 Signaling Pathway.

Background: Over 50% of lung adenocarcinoma patients have high levels of complement factor H (CFH) expression. Previous studies have reported that CFH inhibits the migration of endothelial cells. In this study, we investigated the mechanism by which CFH affects lung adenocarcinoma development via phosphorylation of STAT3.

Targeting uric acid: a promising intervention against oxidative stress and neuroinflammation in neurodegenerative diseases.

Oxidative stress and neuroinflammation are recognized as key factors in the development of neurodegenerative diseases, yet effective interventions and biomarkers to address oxidative stress and neuroinflammation in these conditions are limited. Uric acid (UA), traditionally associated with gout, is now gaining prominence as a potential target in neurodegenerative diseases. Soluble UA stands out as one of the most vital antioxidant compounds produced by the human body, accounting for up to 55% of the extracellular capacity to neutralize free radicals.

Lactamase β reprograms lipid metabolism to inhibit the progression of endometrial cancer through attenuating MDM2-mediated p53 ubiquitination and degradation.

Background: Lactamase β (LACTB) inhibits the metastasis and progression of multiple malignant tumors. However, little is known about its role in endometrial cancer (EC). Our study aimed to investigate the function and potential molecular mechanism of LACTB in modulating EC progression.

Noninvasive assessment of hepatic steatosis grades by ultrasound derived fat fraction in metabolic dysfunction associated steatotic liver disease.

To evaluate the diagnostic performance of ultrasound-derived fat fraction (UDFF) and clinical prediction models in assessing hepatic steatosis grades in MASLD patients, with liver biopsy as reference standard.A total of 85 obese patients who were found to have fatty liver by B-mode ultrasound and underwent UDFF measurement, with liver biopsy available, were enrolled. The diagnostic performance of UDFF, clinical prediction models including fatty liver index (FLI), hepatic steatosis index (HSI), ZheJiang University index (ZJU index) and lipid accumulation product (LAP) for hepatic steatosis was assessed.

Fuzhisan ameliorates cognitive ability in Alzheimer's disease by p62 and related autophagy regulatory pathways.

Background: Maintaining autophagic homeostasis has been proved to play an important role in Alzheimer's disease.

Object: The aim of this study was to investigate the effect of Fuzhisan(FZS) on autophagic function in Alzheimer's disease and to elucidate its potential mechanism through the P62 regulatory pathways.

Methods: FZS was extracted by water extraction-rotary evaporation method.

Analysis of Factors Related to Throat Soreness After Painless Gastroscopy: A Single-Center Study.

Introduction: Throat soreness is a frequently encountered yet often underappreciated complication in patients undergoing gastroscopy. Few studies have explicitly explored the relationship between gastroscopy and throat soreness. This study aimed to review demographic data, summarize the characteristics, and investigate the influencing factors of throat soreness following gastroscopy.

Initial investigation into patellofemoral morphology in hemophilic arthritis patients.

Background: Hemophilic arthritis (HA) is associated with significant changes in the morphology of mature knee joints due to abnormal growth plate development. Previous studies have established marked distinctions between the femur and tibia of subjects with Haemophilia and those with osteoarthritis (OA). This study explored the morphological characteristics of the patella and patellofemoral joint in subjects with Haemophilia.

Deep learning radiomics on grayscale ultrasound images assists in diagnosing benign and malignant of BI-RADS 4 lesions.

This study aimed to explore a deep learning radiomics (DLR) model based on grayscale ultrasound images to assist radiologists in distinguishing between benign breast lesions (BBL) and malignant breast lesions (MBL). A total of 382 patients with breast lesions were included, comprising 183 benign lesions and 199 malignant lesions that were collected and confirmed through clinical pathology or biopsy. The enrolled patients were randomly allocated into two groups: a training cohort and an independent test cohort, maintaining a ratio of 7:3.

Effect of perioperative dexmedetomidine on recovery of postoperative gastrointestinal function in patients with general anesthesia: a systematic review and meta-analysis.

Background: There is controversy surrounding the influence of dexmedetomidine on the recovery of postoperative gastrointestinal dysfunction in patients under general anesthesia. The main purpose of this meta-analysis is to evaluate the effect of dexmedetomidine administration during the perioperative period on the recovery of gastrointestinal function in patients under general anesthesia.

Methods: A systematic review and meta-analysis with trial sequential analysis was performed to identify randomized controlled trials comparing dexmedetomidine administration with placebo for the recovery of gastrointestinal function.

Nervonic acid alleviates radiation-induced early phase lung inflammation by targeting macrophages activation in mice.

Background: Patients receiving chest radiation therapy, or exposed to high radiation levels due to accidental nuclear leakage are at risk of radiation-induced lung injury (RILI). In innate immunity, macrophages not only exhibit certain radiation tolerance but also play an important regulatory role in the whole pathological process. Nervonic acid (NA), a long-chain unsaturated fatty acid found in nerve tissue, plays a pivotal role in maintaining normal tissue growth and repair.

Review of clinical and imaging findings in autoimmune glial fibrillary acidic protein astrocytopathy to aid in early diagnosis.

Objective: Autoimmune glial fibrillary acidic protein astrocytopathy (GFAP-A) is a novel steroid sensitive autoimmune disease, without a diagnostic consensus. The purpose of this study was to improve early GFAP-A diagnosis by increasing awareness of key clinical characteristics and imaging manifestations.

Methods: Medical records of 13 patients with anti-GFAP antibodies in serum or cerebrospinal fluid (CSF) were reviewed for cross-sectional and longitudinal analysis of clinical and magnetic resonance imaging (MRI) findings.

Clinical features, risk factors, outcomes, and prediction model for intrahepatic and perihepatic abscess following hepatectomy for hepatocellular carcinoma.

Background: Intrahepatic and perihepatic abscess (IPHA) is a severe yet understudied complication that can occur after hepatectomy. This multicenter study aimed to elucidate the clinical features, risk factors, and outcomes of IPHA after hepatectomy for hepatocellular carcinoma (HCC), and to develop a novel prediction model for personalized risk assessment.

Methods: This was a multicenter cohort study of HCC patients who underwent curative-intent hepatectomy.

Identification of targets and comparative study of administration methods for the lipid-lowering effects of fucoidan from Saccharina japonica.

The lipid-lowering activity of fucoidan has been widely reported, but the exploration of its mechanisms is relatively limited, and studies on its direct targets are even scarcer. Additionally, it is unclear whether different administration methods affect the lipid-lowering activity of fucoidan. In current study, we used fucoidan derived from Saccharina japonica (SJF) to investigate its targets.

The impact of glucose metabolism on inflammatory processes in sepsis-induced acute lung injury.

Acute lung injury (ALI) is a prevalent and critical complication of sepsis, marked by high incidence and mortality rates, with its pathogenesis still not being fully elucidated. Recent research has revealed a significant correlation between the metabolic reprogramming of glucose and sepsis-associated ALI (S-ALI). Throughout the course of S-ALI, immune cells, including macrophages and dendritic cells, undergo metabolic shifts to accommodate the intricate demands of immune function that emerge as sepsis advances.

Regulation of macrophage polarization and pyroptosis by 4-methylcatechol alleviates collagen-induced arthritis via Nrf2/HO-1 and NF-κB/NLRP3 signaling pathways.

Rheumatoid arthritis (RA) is a chronic inflammatory disease that leads to joint deformity and ultimately disability. The metabolite of quercetin, 4-Methylcatechol (4-MC), has been acknowledged for its anti-inflammatory and antioxidant properties; however, the protective effects of 4-MC on RA and its underlying mechanisms remain incompletely elucidated. In a collagen-induced arthritis (CIA) model, we observed that 4-MC effectively mitigated joint inflammation and bone destruction in CIA mice.

Image quality assessment of artificial intelligence iterative reconstruction for low dose unenhanced abdomen: comparison with hybrid iterative reconstruction.

Objectives: To assess the impact of artificial intelligence iterative reconstruction algorithms (AIIR) on image quality with phantom and clinical studies.

Methods: The phantom images were reconstructed with the hybrid iterative algorithm (HIR: Karl 3D-3, 5, 7, 9) and AIIR (grades 1-5) algorithm. Noise power spectra (NPS), task transfer functions (TTF) were measured, and additionally sharpness was assessed using a "blur metric" procedure.

Vessel wall MRI evaluation for the safety of endovascular recanalization of non-acute intracranial anterior circulation artery occlusions.

Background: Vessel wall MRI (VWMRI) can reveal the morphological features of intracranial artery occlusion (ICAO). This study aimed to investigate the imaging features of ICAO on VWMRI and explore their correlation with perioperative complications of endovascular recanalization for non-acute ICAO.

Methods: The study retrospectively included consecutive patients with recurrent ischemic stroke due to non-acute ICAO in the anterior circulation who underwent preoperative VWMRI evaluation and endovascular recanalization.

Automatic pituitary adenoma segmentation and identification of cavernous sinus invasion via multitask learning.

Aim: This study aimed to develop a multitask deep learning model for pituitary macroadenoma (PMA) segmentation and identification of cavernous sinus (CS) invasion.

Materials And Methods: A total of 926 patients with PMAs (n=816 from Institution 1 for model training and n=110 from Institution 2 for model validation) were included. Manual segmentation for tumor and bilateral internal carotid arteries was conducted on coronal contrast-enhanced T1-weighted imaging images using ITK-SNAP.

Neuroticism and cerebral small vessel disease: A genetic correlation and Mendelian randomization analysis.

Objectives: The association of neuroticism and cerebral small vessel disease (CSVD) development remains unclear. In this study, we used Mendelian randomization (MR) to explore the potential role of neuroticism in CSVD development.

Methods: We collected data on ischemic stroke (IS); small vessel stroke (SVS); three neuroimaging markers altered in CSVD, including white matter hyperintensity (WMH), fractional anisotropy (FA), and mean diffusivity (MD); and three neuroticism clusters, including depressed affect, worry, sensitivity to environmental stress and adversity (SESA), from large-scale genome-wide association studies (GWAS).

Predicting molecular subtypes of breast cancer based on multi-parametric MRI dataset using deep learning method.

Purpose: To develop a multi-parametric MRI model for the prediction of molecular subtypes of breast cancer using five types of breast cancer preoperative MRI images.

Methods: In this study, we retrospectively analyzed clinical data and five types of MRI images (FS-T1WI, T2WI, Contrast-enhanced T1-weighted imaging (T1-C), DWI, and ADC) from 325 patients with pathologically confirmed breast cancer. Using the five types of MRI images as inputs to the ResNeXt50 model respectively, five base models were constructed, and then the outputs of the five base models were fused using an ensemble learning approach to develop a multi-parametric MRI model.