The relationship between high-sensitivity C-reactive protein and gallstones: a cross-sectional analysis.

Background And Objective: High-sensitivity C-reactive protein (hs-CRP), a classical indicator of inflammation, holds significant clinical value in various diseases. The relationship between hs-CRP and gallstones, however, remains poorly studied at present. The relationship between hs-CRP and gallstones will be investigated in this study.

Prognostic nutritional index and albuminuria in adults aged 20 years and above: a cross-sectional analysis in the United States.

Background And Objective: Albuminuria is an important early marker of kidney damage and progression of chronic kidney disease and is also linked to several chronic systemic diseases. The Prognostic Nutritional Index (PNI) is widely used in the assessment of multiple diseases. However, research dealing with the relationship between PNI and albuminuria remains scarce.

Prediction of future research trends in bladder urothelial carcinoma: Bibliometric analysis.

Background: Bladder urothelial carcinoma (BLCA) is a prevalent malignant tumor of the urinary system and, ranks 13th worldwide. Its incidence and mortality rates are consistently increasing, posing a significant threat to the physical and mental well-being of patients.

Methods: We conducted a literature search in the field of BLCA from 2010 to 2023 using the Web of Science Core Collection (WoSCC) database.

Salidroside protects RGC from pyroptosis in diabetes-induced retinopathy associated with NLRP3, NFEZL2 and NGKB1, revealed by network pharmacology analysis and experimental validation.

Objective: To investigate the effect of salidroside (SAL) in protecting retinal ganglion cell (RGC) from pyroptosis and explore associated molecular network mechanism in diabetic retinapathy (DR) rats.

Methods: HE, Nissl and immunofluorescence staining were used to observe the retinal morphological change, and the related target genes for salidroside, DR and pyroptosis were downloaded from GeneCard database. Then Venny, PPI, GO, KEGG analysis and molecular docking were used to reveal molecular network mechanism of SAL in inhibiting the pyroptosis of RGC.

Efficacy and safety of antibiotic therapy for post-Lyme disease? A systematic review and network meta-analysis.

Background: At present, the pathogenesis of post-treatment Lyme disease (PTLDS) is not clear, so the treatment scheme of PTLDS, especially antibiotic treatment, is still controversial. This study aims to evaluate the efficacy of antibiotics in the treatment of PTLDS using network meta-analysis (NMA).

Methods: Following PRISMA guidelines, a systematic literature search was conducted on randomized controlled trials in PubMed, EMBASE, Web of Science and Cochrane Library (the literature was published from database inception through December 16, 2022).

Automatic Segmentation of Magnetic Resonance Images of Severe Patients with Advanced Liver Cancer and the Molecular Mechanism of Emodin-Induced Apoptosis of HepG2 Cells under the Deep Learning.

To improve the accuracy of clinical diagnosis of severe patients with advanced liver cancer and enhance the effect of chemotherapy treatment, the U-Net model was optimized by introducing the batch normalization (BN) layer and the dropout layer, and the segmentation training and verification of the optimized model were realized by the magnetic resonance (MR) image data. Subsequently, HepG2 cells were taken as the research objects and treated with 0, 10, 20, 40, 60, 80, and 100 mol/L emodin (EMO), respectively. The methyl thiazolyl tetrazolium (MTT) method was used to explore the changes in cell viability, the acridine orange (AO)/ethidium bromide (EB) and 4',6-diamidino-2-phenylindole (DAPI) were used for staining, the Annexin V fluorescein isothiocyanate (FITC)/propidium iodide (PI) (Annexin V-FITC/PI) was adopted to detect the apoptosis after EMO treatment, and the Western blot (WB) method was used with the purpose of exploring the changes in protein expression levels of PARP, Bcl-2, and p53 in the cells after treatment.

Biomechanical comparison between single-row with triple-loaded suture anchor and suture-bridge double-row rotator cuff repair.

Background: Numerous biomechanical and clinical studies comparing different techniques for rotator cuff repair have been reported, yet universal consensus regarding the superior technique has not achieved. A medially-based single-row with triple-loaded suture anchor (also referred to as the Southern California Orthopedic Institute [SCOI] row) and a suture-bridge double-row (SB-DR) with Push-Locks have been shown to result in comparable improvement in treating rotator cuff tear, yet the biomechanical difference is unknown. The purpose of the current study was to determine whether a SCOI row repair had comparable initial biomechanical properties to a SB-DR repair.

A transcriptional metabolic gene-set based prognostic signature is associated with clinical and mutational features in head and neck squamous cell carcinoma.

Purpose: Head and neck squamous cell carcinoma (HNSCC) is a common cancer with high mortality and poor prognosis partially owing to lack of application of predictive markers. Increasing evidence has suggested that metabolic dysregulation plays an important part in tumorigenesis. We aim to identify a prognostic metabolic pathway (MP) signature in HNSCC.

Application of Machine Learning in Developing a Novelty Five-Pseudogene Signature to Predict Prognosis of Head and Neck Squamous Cell Carcinoma: A New Aspect of "Junk Genes" in Biomedical Practice.

Head and neck squamous cell carcinoma (HNSCC) is the sixth malignancy, which is characterized by poor prognosis or high mortality because of the lack of predicting markers. Aberrant cancer pseudogenes have been found predictive for prognosis. We aim to identify a pseudogene-based prognosis signature for HNSCC by machine learning.

Expression scoring of a small-nucleolar-RNA signature identified by machine learning serves as a prognostic predictor for head and neck cancer.

Head and neck squamous cell carcinoma (HNSCC) is a common malignancy with high mortality and poor prognosis due to a lack of predictive markers. Increasing evidence has demonstrated small nucleolar RNAs (snoRNAs) play an important role in tumorigenesis. The aim of this study was to identify a prognostic snoRNA signature of HNSCC.

Prognostic 4-lncRNA-based risk model predicts survival time of patients with head and neck squamous cell carcinoma.

Head and neck squamous cell carcinoma (HNSCC) is a common malignant disease with high mortality rates. Recently, long non-coding RNAs (lncRNAs) have been demonstrated to participate in a number of important biological functions and could serve as prognostic biomarkers in the field of oncology. Therefore, the present study aimed to identify an lncRNA-based model that was associated with prognosis.

A Four-Pseudogene Classifier Identified by Machine Learning Serves as a Novel Prognostic Marker for Survival of Osteosarcoma.

Osteosarcoma is a common malignancy with high mortality and poor prognosis due to lack of predictive markers. Increasing evidence has demonstrated that pseudogenes, a type of non-coding gene, play an important role in tumorigenesis. The aim of this study was to identify a prognostic pseudogene signature of osteosarcoma by machine learning.

Systematic Profile Analysis of Prognostic Alternative Messenger RNA Splicing Signatures and Splicing Factors in Head and Neck Squamous Cell Carcinoma.

Head and neck squamous cell carcinoma (HNSC) is a common malignancy with high mortality and poor prognosis. Alternative splicing (AS) is a transcriptional regulation mechanism that generates multiple transcripts from same genes, and aberrant AS signatures of cancers can be predictive for prognosis. We identified the survival-related AS events and splicing factors (SFs) from the RNA sequencing data and the corresponding clinical information of an HNSC cohort downloaded from The Cancer Genome Atlas (TCGA) and SpliceSeq.