Bailing capsule alleviates autoimmune thyroiditis regulating peroxisome proliferator-activated receptor signaling pathway: a multi-omics analysis.

Objective: To investigate the efficacy and potential mechanism of Bailing capsule (, BL) anti-autoimmune thyroiditis (AIT).

Methods: Based on the AIT rat model, the effect of BL in alleviating AIT was evaluated by detecting serum thyroid index free triiodothyronine (FT3), free thyroxine (FT4), thyroid-stimulating hormone (TSH), thyroglobulin antibody (TGAb), thyroid peroxidase antibody (TPOAb), and inflammatory factors Interferon-gamma (IFN-γ), Interleukin-4, -10, and -12 (IL-4, IL-10, and IL-12) as well as thyroid tissue Hematoxylin-eosin (HE) staining and ultrastructure observation. The mechanism of BL was explored by combining transcriptome and proteome analysis, and further verified by Western blot (WB).

Dissecting the cell microenvironment of ovarian endometrioma through single-cell RNA sequencing.

Ovarian endometrioma (OE), also known as "chocolate cysts," is a cystic mass that develops in the ovaries due to endometriosis and is a common gynecological condition characterized by the growth of endometrial tissue outside the uterus, leading to symptoms such as dysmenorrhea, pelvic pain, and infertility. However, the precise molecular and cellular mechanisms driving this pathophysiology remain largely unknown, posing challenges for diagnosis and treatment. Here, we employed integrated single-cell transcriptomic profiling of over 52,000 individual cells from endometrial tissues of OE patients and healthy donors and identified twelve major cell populations.

AOPPs induces EMT and fibrosis by activating oxidative stress through ERK/p38 MAPK signaling pathway in endometriosis.

Epithelial-mesenchymal transition (EMT) is known to play a crucial role in the development of endometriosis (EMs). However, the exact mechanisms involved in EMT regulation in EMs are not well understood. In this study, we performed comprehensive research using clinical samples, single-cell sequencing, and in vivo/in vitro models to investigate the effects of advanced oxidation protein products (AOPPs) on EMT and the underlying mechanisms in EMs.

A Single-Cell Transcriptome Profiling of Triptolide-Induced Nephrotoxicity in Mice.

Triptolide (TP), an active component isolated from the traditional Chinese herb Tripterygium wilfordii Hook F (TWHF), shows great promise for treating inflammation-related diseases. However, its potential nephrotoxic effects remain concerning. The mechanism underlying TP-induced nephrotoxicity is inadequately elucidated, particularly at single-cell resolution.

Assessing lateral femoral condyle cartilage prior to medial UKA: MRI vs. Valgus stress radiograph.

Background: The cartilage quality of the lateral compartment needs to be clarified prior to medial unicompartmental knee arthroplasty (UKA). Valgus stress radiograph has been recommended as the preferred tool. Some studies also show that magnetic resonance imaging (MRI) has a higher diagnostic value.

Single-cell RNA transcriptome landscape of murine liver following systemic administration of mesoporous silica nanoparticles.

Due to the unique physicochemical properties, mesoporous silica nanoparticles (MONs) have been widely utilized in biomedical fields for drug delivery, gene therapy, disease diagnosis and imaging. With the extensive applications and large-scale production of MONs, the potential effects of MONs on human health are gaining increased attention. To better understand the cellular and molecular mechanisms underlying the effects of MONs on the mouse liver, we profiled the transcriptome of 63,783 single cells from mouse livers following weekly intravenous administration of MONs for 2 weeks.

Improved YOLOv5 infrared tank target detection method under ground background.

The detection precision of infrared seeker directly affects the guidance precision of infrared guidance system. To solve the problem of low target detection accuracy caused by the change of imaging scale, complex ground background and inconspicuous infrared target characteristics when infrared image seeker detects ground tank targets. In this paper, a You Only Look Once, Transform Head Squeeze-and-Excitation (YOLOv5s-THSE) model is proposed based on the YOLOv5s model.

Single-cell transcriptome analysis reveals liver injury induced by glyphosate in mice.

Background: Glyphosate (GLY), as the active ingredient of the most widely used herbicide worldwide, is commonly detected in the environment and living organisms, including humans. Its toxicity and carcinogenicity in mammals remain controversial. Several studies have demonstrated the hepatotoxicity of GLY; however, the underlying cellular and molecular mechanisms are still largely unknown.

Staged open reduction and internal fixation with double-locking plates to treat bilateral distal femur periprosthetic fractures after total knee arthroplasty: A case report.

Background: The incidence of periprosthetic fractures after total knee arthroplasty (TKA) increases in parallel with the number of procedures. Comminuted fractures along the primary fracture line extending to the edge of the prosthesis are challenging, and bilateral fractures are rarely reported, especially with open injuries.

Case Presentation: A 65-year-old female had undergone bilateral TKA in our hospital 5 years before admission.

SILAC-based chemoproteomics reveals a neoligan analogue as an anti-inflammatory agent targeting IRGM to ameliorate cytokine storm.

Cytokine storm is a key feature of sepsis and severe stage of COVID-19, and the immunosuppression after excessive immune activation is a substantial hazard to human life. Both pathogen-associated molecular patterns (PAMPs) and damage-associated molecular patterns (DAMPs) are recognized by various pattern recognition receptors (PRRs), which lead to the immune response. A number of neolignan analogues were synthesized in this work and showed powerful anti-inflammation properties linked to the response to innate and adaptive immunity, as well as NP-7 showed considerable anti-inflammatory activity at 100 nM.

Liq_ccRCC: Identification of Clear Cell Renal Cell Carcinoma Based on the Integration of Clinical Liquid Indices.

Currently, preoperative diagnosis and differentiation of renal clear cell carcinoma and other subtypes remain a serious challenge for doctors. The liquid biopsy technique and artificial intelligence have inspired the pursuit of distinguishing clear cell renal cell carcinoma using clinically available test data. In this work, a method called liq_ccRCC based on the integration of clinical blood and urine indices through machine learning approaches was successfully designed to achieve this goal.

ABCModeller: an automatic data mining tool based on a consistent voting method with a user-friendly graphical interface.

In order to extract useful information from a huge amount of biological data nowadays, simple and convenient tools are urgently needed for data analysis and modeling. In this paper, an automatic data mining tool, termed as ABCModeller (Automatic Binary Classification Modeller), with a user-friendly graphical interface was developed here, which includes automated functions as data preprocessing, significant feature extraction, classification modeling, model evaluation and prediction. In order to enhance the generalization ability of the final model, a consistent voting method was built here in this tool with the utilization of three popular machine-learning algorithms, as artificial neural network, support vector machine and random forest.

GCdiscrimination: identification of gastric cancer based on a milliliter of blood.

Gastric cancer (GC) continues to be one of the major causes of cancer deaths worldwide. Meanwhile, liquid biopsies have received extensive attention in the screening and detection of cancer along with better understanding and clinical practice of biomarkers. In this work, 58 routine blood biochemical indices were tentatively used as integrated markers, which further expanded the scope of liquid biopsies and a discrimination system for GC consisting of 17 top-ranked indices, elaborated by random forest method was constructed to assist in preliminary assessment prior to histological and gastroscopic diagnosis based on the test data of a total of 2951 samples.

ATBdiscrimination: An in Silico Tool for Identification of Active Tuberculosis Disease Based on Routine Blood Test and T-SPOT.TB Detection Results.

Tuberculosis remains one of the deadliest infectious diseases worldwide. Only 5-15% of people infected with develop active TB disease (ATB), while others remain latently infected (LTBI) during their lifetime, which has a completely different clinical treatment schedule. However, most current clinical diagnostic methods are based on the immune response of infections and cannot distinguish ATB from LTBIs.

A Machine Learning Method for Identifying Lung Cancer Based on Routine Blood Indices: Qualitative Feasibility Study.

Background: Liquid biopsies based on blood samples have been widely accepted as a diagnostic and monitoring tool for cancers, but extremely high sensitivity is frequently needed due to the very low levels of the specially selected DNA, RNA, or protein biomarkers that are released into blood. However, routine blood indices tests are frequently ordered by physicians, as they are easy to perform and are cost effective. In addition, machine learning is broadly accepted for its ability to decipher complicated connections between multiple sets of test data and diseases.