PLA plastic particles disrupt bile acid metabolism leading to hepatic inflammatory injury in male mice.

Microplastics, such as polylactic acid (PLA), are ubiquitous environmental pollutants with unclear implications for health impact. This study aims to elucidate the mechanisms of PLA-induced inflammatory liver injury, focusing on disturbance of bile acid metabolism. The in vitro PLA exposure experiment was conducted using HepG2 cells to assess cell viability, cytokine secretion, and effects on bile acid metabolism. In vivo, male C57BL/6 J mice were exposed to PLA for ten days continuously, liver function and histopathological assessment were evaluated after the mice sacrificed. Molecular analyses including quantitative reverse transcription polymerase chain reaction (RT-qPCR) and Western blotting, were applied to evaluate the expression of bile acid metabolizing enzymes and transporters. PLA exposure resulted in decreased cell viability in HepG2 cells, increased inflammation and altered bile acid metabolism. In mice, PLA exposure resulted in decreased body weight and food intake, impaired liver function, increased hepatic inflammation, altered bile acid profiles, and dysregulated expression of bile acid metabolic pathways. PLA exposure disrupts bile acid metabolism through inhibition of the CYP7A1 enzyme and activation of the FGF-JNK/ERK signaling pathway, contributing to liver injury. These findings highlight the potential hepatotoxic effects of environmentally friendly plastics PLA and underscore the need for further research on their biological impact.

Tethered cord syndrome from pediatric and adult perspectives: a comprehensive systematic review of 6135 cases.

OBJECTIVE: This study aimed to investigate the differences in clinical features, diagnostic examination, treatment, and pathological results between adult-onset and pediatric-onset tethered cord syndrome (TCS). METHODS: The authors searched the PubMed, Embase, and Cochrane Library databases through January 2023 for reports on TCS, extracting information on clinical features, imaging data, treatment modalities, prognosis, and pathological research results. A total of 6135 cases from 246 articles were included in the analysis. This review was conducted in accordance with the 2020 PRISMA guidelines and registered on PROSPERO. RESULTS: The most common adult clinical manifestations were pain, urinary symptoms, and numbness; in children, they were urinary symptoms, skin lesions, bowel symptoms, and unspecific motor deficits. Surgical treatment was the primary approach for both adults and children, with a higher clinical improvement rate observed in adults. However, adults also had a higher rate of surgical complications than children. TCS pathological studies have not yet identified the differences between adults and children, and the pathogenesis of adult-onset TCS requires further investigation. CONCLUSIONS: Adult-onset and pediatric-onset TCS exhibit certain differences in clinical characteristics, diagnostic examinations, and treatments. However, significant differences have not been found in current pathological studies between adults and children. Systematic review registration no.: CRD42023479450 (www.crd.york.ac.uk/prospero).

Nicotine promotes Staphylococcus aureus-induced osteomyelitis by activating the Nrf2/Slc7a11 signaling axis.

Although smoking is a significant risk factor for osteomyelitis, there is limited experimental evidence that nicotine, a key tobacco constituent, is associated with this condition, leaving its mechanistic implications uncharacterized. This study revealed that nicotine promotes Staphylococcus aureus-induced osteomyelitis by increasing Nrf2 and Slc7a11 expression in vivo and in vitro. Inhibition of Slc7a11 using Erastin augmented bacterial phagocytosis/killing capabilities and fortified antimicrobial responses in an osteomyelitis model. Moreover, untargeted metabolomic analysis demonstrated that Erastin mitigated the effects of nicotine on S. aureus-induced osteomyelitis by altering glutamate/glutathione metabolism. These findings suggest that nicotine aggravates S. aureus-induced osteomyelitis by activating the Nrf2/Slc7a11 signaling pathway and that Slc7a11 inhibition can counteract the detrimental health effects of nicotine.

Association between the stress-hyperglycemia ratio and all-cause mortality in community-dwelling populations: An analysis of the National Health and Nutrition Examination Survey (NHANES) 1999-2014.

BACKGROUND: Reportedly, the stress-hyperglycemia ratio (SHR) is closely associated with poor prognosis in patients with severe acute disease. However, the community-dwelling may also be in a state of stress due to environmental exposure. Our study aimed to explore the association between SHR and all-cause mortality in the community-dwelling population. METHODS: A total of 18 480 participants were included out of 82 091 from the NHANES 1999-2014 survey. The Kaplan-Meier survival analyses were used to assess the disparities in survival rates based on SHR, and the log-rank test was employed to investigate the distinctions between groups. The multivariate Cox regression analysis and restricted cubic spline (RCS) analysis were performed to assess the association of SHR with all-cause mortality. A subgroup analysis was also conducted. RESULTS: A total of 3188 deaths occurred during a median follow-up period of 11.0 (7.7; 15.4) years. The highest risk for all-cause mortality was observed when SHR≤ 0.843 or SHR ≥0.986 (log-rank p < .001). After adjusting for the confounding factors, compared with subjects in the second SHR quartile (Q2), participants in the highest (Q4, adjusted hazard ratio [HR] 1.49, 95% confidence interval [CI] 1.28-1.73) and lowest quartiles (Q1, adjusted HR 1.37, 95% CI 1.16-1.60) have a higher probability of all-cause death. The RCS observed a dose-response U-shaped association between SHR and all-cause mortality. The U-shaped association between SHR and all-cause mortality was similar across subgroup analysis. CONCLUSIONS: The SHR was significantly associated with all-cause mortality in the community-dwelling population, and the relationship was U-shaped.

Efficacy and safety of total glucosides of paeony in the treatment of recurrent aphthous ulcers: a systematic review and meta-analysis.

Background: Recurrent aphthous ulcer (RAU) had high prevalence and lacked widely recognized treatment. Total glucosides of paeony (TGP) was used in the treatment of RAU in recent years. This study was to summarize the efficacy and safety of TGP in the treatment of RAU. Methods: We searched eight commonly used databases for relevant studies that published before 1 November 2023. Primary outcome was visual analogue scale (VAS). Secondary outcomes included overall response rate, significant response rate, ulcer healing time, interval, number of ulcers, and serum inflammatory factors. We conducted the meta-analysis, assessed risk of bias and the confidence of the evidence, by using Stata 15.0, Review Manager 5.4, and Gradepro. Results: Nine randomized controlled trials (RCTs) encompassing 883 patients with RAU were included in the final analysis. The VAS in the TGP group was lower than that in the control group (MD = -1.18, 95% CI = -1.58 to -0.78, p < 0.001, moderate-certainty evidence), subgroup analysis suggested longer (>8 weeks) medication and observation led to a more significant reduction in pain (p = 0.02). Moreover, TGP had higher overall response rate (RR = 1.18, 95% CI = 1.04 to 1.33, p = 0.008, very low-certainty evidence) and significant response rate (RR = 1.72, 95% CI = 1.38 to 2.14, p < 0.001, very low-certainty evidence), accelerated ulcer healing (MD = -1.79, 95% CI = -2.67 to -0.91, p < 0.001, low-certainty evidence), and extended intervals (MD = 23.60, 95% CI = 14.17 to 33.03, p < 0.001, very low-certainty evidence). The efficacy of TGP in reducing the number of ulcers showed no significant difference compared to the control group (MD = -1.66, 95% CI = -3.60 to 0.28, p = 0.09, low-certainty evidence). Moreover, TGP treatment was associated with a higher incidence of abdominal symptoms (RR = 3.27, 95% CI = 1.62 to 6.60, p < 0.001). Conclusion: TGP appears to hold promise as a widely-used clinical therapeutic option for treating RAU. Nevertheless, further rigorous studies of high quality are required to validate its effectiveness. Systematic Review Registration: https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=471154, Identifier CRD42023471154.

Differences in the response of normal oral mucosa, oral leukoplakia, oral squamous cell carcinoma-derived mesenchymal stem cells, and epithelial cells to photodynamic therapy.

OBJECTIVE: The objective of this study is to investigate the variances in transcriptome gene expression of normal oral mucosa-derived mesenchymal stem cell (OM-MSC), oral leukoplakia-derived MSC (OLK-MSC) and oral squamous cell carcinoma-derived MSC(OSCC-MSC). as Additionally, the study aims to compare the in vitro proliferation, migration, invasion ability, and response to photodynamic therapy (PDT) of these three MSC, HOK, DOK, leuk1, and Cal27 cell lines. METHODS: HOK, DOK, leuk1, Cal27 cells were cultured in vitro. 3 MSC cells were obtained from OM, OLK, OSCC tissue (n = 3) and identified through flow cytometry. They were also cultured in vitro for osteogenic and lipogenic-induced differentiation. Based on the Illumina HiSeq high-throughput sequencing platform, OM-MSC, OLK-MSC, OSCC-MSC (n = 3) were subjected to transcriptome sequencing, functional annotation, and enrichment analysis of differentially expressed genes and related genes. CCK8 assay, wound healing assay, and transwell assay were performed to compare the proliferation, migration, and invasion of the seven types of cells. The 7 cells were incubated with 0, 0.125 mM, 0.25 mM, 0.5 mM, 1 mM, and 2 mM of the photosensitizer (5-aminolevulinic acid, 5-ALA) in vitro. Subsequently, they were irradiated with a 150 mM, 635 nm laser for 1 min, and the cell activity was detected using the CCK8 assay after 24 h. The mitochondrial changes in the 7 cells before and after the treatment of PDT were detected using the JC-10 probe, and the changes in ATP content were measured before and after the PDT treatment. RESULTS: OM-MSC, OLK-MSC, and OSCC-MSC expressed positive MSC surface markers. After osteogenic and lipogenic-induced differentiation culture, stained calcium nodules and lipid droplets were visible, meeting the identification criteria of MSC. Pathway enrichment analysis revealed that the differentially expressed genes (DEGs) of OSCC-MSC compared to OLK-MSC were primarily associated with the PI3K-Akt signaling pathway and tumor-related pathways. OSCC-MSC exhibited stronger migratory and invasive abilities compared to Cal27. The IC50 values required for OM, OLK, and OSCC-derived MSC were lower than those required for epithelial cells treated with PDT, which were 1.396 mM, 0.9063 mM, and 2.924 mM, respectively. Cell membrane and mitochondrial disruption were observed in seven types of cells after 24 h of PDT treatment. However, HOK, DOK, leuk1, and Cal27 cells had an ATP content increased. CONCLUSIONS: OLK, OSCC epithelial cells require higher concentrations of 5-ALA for PDT treatment than MSC of the same tissue origin. The concentration of 5-ALA required increases with increasing cell malignancy. Differences in the response of epithelial cells and MSC to PDT treatment may have varying impacts on OLK recurrence and malignancy.

SGLMDA: A Subgraph Learning-based Method for miRNA-disease Association Prediction.

MicroRNAs (miRNA) are endogenous non-coding RNAs, typically around 23 nucleotides in length. Many miRNAs have been founded to play crucial roles in gene regulation though post-transcriptional repression in animals. Existing studies suggest that the dysregulation of miRNA is closely associated with many human diseases. Discovering novel associations between miRNAs and diseases is essential for advancing our understanding of disease pathogenesis at molecular level. However, experimental validation is time-consuming and expensive. To address this challenge, numerous computational methods have been proposed for predicting miRNA-disease associations. Unfortunately, most existing methods face difficulties when applied to large-scale miRNA-disease complex networks. In this paper, we present a novel subgraph learning method named SGLMDA for predicting miRNA-disease associations. For miRNA-disease pairs, SGLMDA samples K-hop subgraphs from the global heterogeneous miRNA-disease graph. It then introduces a novel subgraph representation algorithm based on Graph Neural Network (GNN) for feature extraction and prediction. Extensive experiments conducted on benchmark datasets demonstrate that SGLMDA can effectively and robustly predict potential miRNA-disease associations. Compared to other state-of-the-art methods, SGLMDA achieves superior prediction performance in terms of Area Under the Curve (AUC) and Average Precision (AP) values during 5-fold Cross-Validation (5CV) on benchmark datasets such as HMDD v2.0 and HMDD v3.2. Additionally, case studies on Colon Neoplasms and Triple-Negative Breast Cancer (TNBC) further underscore the predictive power of SGLMDA. The dataset and source code of SGLMDA are available at https://github.com/cunmeiji/SGLMDA.

Association of Pre-PCI Blood Pressure and No-Reflow in Patients with Acute ST-Elevation Coronary Infarction.

Background: Previous studies have established blood pressure (BP) as a pivotal factor influencing no-reflow following primary percutaneous coronary intervention (PCI) in patients with ST-elevation acute coronary infarction (STEMI). However, no relevant study has been conducted to investigate the optimal range of BP associated with the lowest risk of no-reflow among STEMI patients so far. Therefore, our objective was to evaluate the association between pre-PCI BP and the occurrence of no-reflow in patients with STEMI. Method: We included 1025 STEMI patients undergoing primary PCI. The BP pre-PCI was categorized into 20-mmHg increments. Logistic models were employed to assess the association of no-reflow with systolic blood pressure (SBP) or diastolic blood pressure (DBP). Three sensitivity analyses were conducted to further confirm the robustness of the association between blood pressure and no-reflow. Results: SBP or DBP exhibited a U-shaped curve association with no-reflow. No-reflow was higher in patients with lower SBP (<100 mmHg) (adjusted hazard ratio (OR) 3.64, 95% confidence interval (CI) 1.84,7.21; p < 0.001) and lower DBP (<60 mmHg) (OR 3.28, 95% CI 1.63,6.49; p < 0.001) [reference: 120 ≤SBP <140; 80 ≤DBP <100 mmHg], respectively. Furthermore, no-reflow was higher in patients with higher SBP (≥160 mmHg) (OR 2.07, 95% CI 1.27,3.36; p = 0.003) and DBP (≥100 mmHg) (OR 3.36, 95% CI 2.07,5.46; p < 0.001), respectively. The results of sensitivity analyses were consistent with the above findings. Conclusion: Maintaining a pre-PCI SBP within the range of 120 to 140 mmHg and a DBP within the range of 80 to 100 mmHg may be confer benefits to patients with STEMI in no-reflow.

A Prediction Model Based on Systemic Immune-Inflammatory Index Combined with Other Predictors for Major Adverse Cardiovascular Events in Acute Myocardial Infarction Patients.

Objective: To evaluate the prognostic value of the systemic immune-inflammatory index (SII) for predicting in-hospital major adverse cardiovascular events (MACEs) in patients with acute myocardial infarction (AMI) and establish a relevant nomogram. Methods: This study included 954 AMI patients. We examined three inflammatory factors (SII, platelet to lymphocyte ratio (PLR) and neutrophil to lymphocyte ratio (NLR)) to see which one predicts in-hospital MACEs better. The predictors were subsequently screened using bidirectional stepwise regression method, and a MACE nomogram was constructed via logistic regression analysis. The predictive value of the model was evaluated using the area under the curve (AUC), sensitivity and specificity. In addition, the clinical utility of the nomogram was evaluated using decision curve analysis. We also compared the nomogram with the Global Registry of Acute Coronary Events (GRACE) scoring system. Results: 334 (35.0%) patients had MACEs. The SII (AUC =0.684) had a greater predictive value for in-hospital MACEs in AMI patients than the PLR (AUC =0.597, P<0.001) or NLR (AUC=0.654, P=0.01). The area under the curve (AUC) of the SII-based multivariable model for predicting MACEs, which was based on the SII, Killip classification, left ventricular ejection fraction, age, urea nitrogen (BUN) concentration and electrocardiogram-based diagnosis, was 0.862 (95% CI: 0.833-0.891). Decision curve and calibration curve analysis revealed that SII-based multivariable model demonstrated a good fit and calibration and provided positive net benefits than the model without SII. The predictive value of the SII-based multivariable model was greater than that of the GRACE scoring system (P<0.001). Conclusion: SII is a promising, reliable biomarker for identifying AMI patients at high risk of in-hospital MACEs, and SII-based multivariable model may serve as a quick and easy tool to identify these patients.

Cadherin-responsive hydrogel combined with dental pulp stem cells and fibroblast growth factor 21 promotes diabetic scald repair via regulating epithelial-mesenchymal transition and necroptosis.

Diabetes causes a loss of sensation in the skin, so diabetics are prone to burns when using heating devices. Diabetic scalded skin is often difficult to heal due to the microenvironment of high glucose, high oxidation, and low blood perfusion. The treatment of diabetic scald mainly focuses on three aspects: 1) promote the formation of the epithelium; 2) promote angiogenesis; and 3) maintain intracellular homeostasis. In response to these three major repair factors, we developed a cadherin-responsive hydrogel combined with FGF21 and dental pulp stem cells (DPSCs) to accelerate epithelial formation by recruiting cadherin to the epidermis and promoting the transformation of N cadherin to E cadherin; promoting angiogenesis to increase wound blood perfusion; regulating the stability of lysosomal and activating autophagy to maintain intracellular homeostasis in order to comprehensively advance the recovery of diabetic scald.

SATCount: A scale-aware transformer-based class-agnostic counting framework.

This paper studies the class-agnostic counting problem, which aims to count objects regardless of their class, and relies only on a limited number of exemplar objects. Existing methods usually extract visual features from query and exemplar images, compute similarity between them using convolution operations, and finally use this information to estimate object counts. However, these approaches often overlook the scale information of the exemplar objects, leading to lower counting accuracy for objects with multi-scale characteristics. Additionally, convolution operations are local linear matching processes that may result in a loss of semantic information, which can limit the performance of the counting algorithm. To address these issues, we devise a new scale-aware transformer-based feature fusion module that integrates visual and scale information of exemplar objects and models similarity between samples and queries using cross-attention. Finally, we propose an object counting algorithm based on a feature extraction backbone, a feature fusion module and a density map regression head, called SATCount. Our experiments on the FSC-147 and the CARPK demonstrate that our model outperforms the state-of-the-art methods.

Development and validation of an immune-related gene prognostic index for lung adenocarcinoma.

Background: Lung cancer is the most common malignant tumor in the world, and its prognosis is still not optimistic. The aim of this study was to establish an immune-related gene (IRG) prognostic index (IRGPI) for lung adenocarcinoma (LUAD) based on IRGs, and to explore the prognosis, molecular and immune features, and response to immune checkpoint inhibitor (ICI) therapy in IRGPI-classified different subgroups of LUAD. Methods: Based on the LUAD transcriptome RNA-sequencing data in TCGA database, the differentially expressed genes (DEGs) were selected. Subsequently, DEGs were intersected with IRGs to obtain differentially expressed immune-related genes (DEIRGs). Weighted gene co-expression network analysis (WGCNA) identified hub genes in DEIRGs. Finally, univariate and multivariate Cox regression analyses were used to build an IRGPI model. Subsequently, TCGA patients were divided into high- and low-risk groups, and the survival of patients in different groups was further analyzed. Besides, we validated the molecular and immune characteristics, relationship with immune checkpoints, angiogenesis-related genes, and immune subtypes distribution in different subgroups. Meanwhile, we further validated the response to ICI therapy in different subgroups. Results: The IRGPI was constructed based on 13 DEIRGs. Compared with the low-risk group, overall survival (OS) was lower in the high-risk group, and the high-risk score was independently associated with poorer OS. Besides, the high-risk score was associated with cell cycle pathway, high mutation rate of TP53 and KRAS, high infiltration of M0 macrophages, and immunosuppressive state, and these patients had poorer prognosis but the TIDE score of the high-risk group was lower than that of the other group, which means that the high-risk group could benefit more from ICI treatment. In contrast, the low-risk score was related to low mutation rate of TP53 and KRAS, high infiltration of plasma cells, and immunoactive state, and these patients had better prognosis but the low-risk group less benefit from ICI treatment based on the results of TIDE score. Conclusions: IRGPI is a prospective biomarker based on IRGs that can distinguish high- and low-risk groups to predict patient prognosis, help characterize the tumor immune microenvironment, and evaluate the benefit of ICI therapy in LUAD.

Glycyrrhetinic Acid Receptor-Mediated Zeolitic Imidazolate Framework-8 Loaded Doxorubicin as a Nanotherapeutic System for Liver Cancer Treatment.

In this study, we designed and developed a DOX nanodrug delivery system (PEG-GA@ZIF-8@DOX) using ZIF-8 as the carrier and glycyrrhetinic acid (GA) as the targeting ligand. We confirmed that DOX was loaded and PEG-GA was successfully modified on the surface of the nanoparticles. The in vitro release profile of the system was investigated at pH 5.0 and 7.4. The cellular uptake, in vitro cytotoxicity, and lysosomal escape characteristics were examined using HepG2 cells. We established an H22 tumor-bearing mouse model and evaluated the in vivo antitumor activity. The results showed that the system had a uniform nanomorphology. The drug loading capacity was 11.22 ± 0.87%. In acidic conditions (pH 5.0), the final release rate of DOX was 57.73%, while at pH 7.4, it was 25.12%. GA-mediated targeting facilitated the uptake of DOX by the HepG2 cells. PEG-GA@ZIF-8@DOX could escape from the lysosomes and release the drug in the cytoplasm, thus exerting its antitumor effect. When the in vivo efficacy was analyzed, we found that the tumor inhibition rate of PEG-GA@ZIF-8@DOX was 67.64%; it also alleviated the loss of the body weight of the treated mice. This drug delivery system significantly enhanced the antitumor effect of doxorubicin in vitro and in vivo, while mitigating its toxic side effects.

Gas Evolution Principle during Gas Drainage from a Drill Hole along the Coal Seam and Reasonable Borehole Layout Spacing.

The efficiency of coal seam gas drainage can be further improved by the accurate mastery of the gas evolution principle during gas drainage from the drill hole along the coal seam and reasonable optimization of borehole layout spacing. Based on the actual geological conditions of the no. 2 coal seam in a coal mine in Guizhou, China, and relevant control equations, a fluid-structure interaction model of gas drainage from a drill hole along the coal seam was established in this paper. Besides, numerical simulation research on the gas evolution principle during gas drainage along the coal seam and optimization of the borehole layout spacing was carried out with the COMSOL simulation software; and these were verified in combination with the project site. The results showed that in the early stage of gas drainage the gas pressure in the area near the drill holes decreased significantly. As the gas drainage went on, the degree of influence decreased gradually. During the gas drainage from adjacent drill holes, the gas pressure in the coal body between the holes decreased rapidly, and the migration was obvious. With the increase of the spacing between the drill holes, the drainage superposition effect between these holes gradually decreased until the influence area around a single hole is independently distributed in a circle-like shape, indicating that the optimization and the reasonable spacing of the drill holes are directly related to the effect of the gas drainage. With the increase of drilling spacing, the superposition effect of extraction between the holes gradually decreased until the influence area around a single hole is independently distributed in the shape of a circle, indicating that the optimization of drilling spacing is directly related to the effect of gas drainage. The results of numerical simulation were verified by analyzing the three-dimensional map of the gas pressure during the period of gas drainage at the project site and by comparing and examining the rational borehole layout spacing of the drill hole along the coal seam. The results of this study can be used to determine the spacing of gas extraction boreholes and improve the efficiency of gas extraction in the no. 2 coal seam of a coal mine in Guizhou, China, as well as to provide a reference for the gas pressure evolution, velocity field distribution, the prediction of effective drainage area, and the selection of rational borehole layout spacing during gas drainage.

Molecular subtyping based on immune cell marker genes predicts prognosis and therapeutic response in patients with lung adenocarcinoma.

OBJECTIVE: Lung adenocarcinoma (LA) is one of the most common malignancies and is responsible for the greatest number of tumor-related deaths. Our research aimed to explore the molecular subtype signatures of LA to clarify the correlation among the immune microenvironment, clinical outcomes, and therapeutic response. METHODS: The LA immune cell marker genes (LICMGs) identified by single-cell RNA sequencing (scRNA-seq) analysis were used to discriminate the molecular subtypes and homologous immune and metabolic traits of GSE72094 LA cases. In addition, the model-building genes were identified from 1441 LICMGs by Cox-regression analysis, and a LA immune difference score (LIDscore) was developed to quantify individual differences in each patient, thereby predicting prognosis and susceptibility to immunotherapy and chemotherapy of LA patients. RESULTS: Patients of the GSE72094 cohort were divided into two distinct molecular subtypes based on LICMGs: immune activating subtype (Cluster-C1) and metabolically activating subtype (cluster-C2). The two molecular subtypes have distinct characteristics regarding prognosis, clinicopathology, genomics, immune microenvironment, and response to immunotherapy. Among the LICMGs, LGR4, GOLM1, CYP24A1, SFTPB, COL1A1, HLA-DQA1, MS4A7, PPARG, and IL7R were enrolled to construct a LIDscore model. Low-LIDscore patients had a higher survival rate due to abundant immune cell infiltration, activated immunity, and lower genetic variation, but probably the higher levels of Treg cells in the immune microenvironment lead to immune cell dysfunction and promote tumor immune escape, thus decreasing the responsiveness to immunotherapy compared with that of the high-LIDscore patients. Overall, high-LIDscore patients had a higher responsiveness to immunotherapy and a higher sensitivity to chemotherapy than the low-LIDscore group. CONCLUSIONS: Molecular subtypes based on LICMGs provided a promising strategy for predicting patient prognosis, biological characteristics, and immune microenvironment features. In addition, they helped identify the patients most likely to benefit from immunotherapy and chemotherapy.

Uric Acid Mitigates Cognitive Deficits via TFEB-Mediated Microglial Autophagy in Mice Models of Alzheimer's Disease.

Clinical trials have demonstrated the potential neuroprotective effects of uric acid (UA) in Alzheimer's disease (AD). However, the specific mechanism underlying the neuroprotective effect of UA remains unclear. In the present study, we investigated the neuroprotective effect and underlying mechanism of UA in AD mouse models. Various behavioral tests including an elevated plus maze, Barnes maze, and Morris water maze were conducted to evaluate the impact of UA on cognitive function in ß-amyloid (Aß) microinjection and APP23/PS45 double transgenic mice models of AD. Immunohistochemical staining was employed to visualize pathological changes in the brains of AD model mice. Western blotting and immunofluorescence techniques were used to assess levels of autophagy-related proteins and transcription factor EB (TFEB)-related signaling pathways. BV2 cells were used to investigate the association between UA and microglial autophagy. We reported that UA treatment significantly alleviated memory decline in Aß-induced AD model mice and APP23/PS45 double transgenic AD model mice. Furthermore, UA activated microglia and upregulated the autophagy-related proteins such as LC3II/I ratio, Beclin-1, and LAMP1 in the hippocampus of AD model mice. Similarly, UA protected BV2 cells from Aß toxicity by upregulating the expressions of Beclin-1, LAMP1, and the LC3II/I ratio, whereas genetic inhibition of TFEB completely abolished these protective effects. Our results indicate that UA may serve as a novel activator of TFEB to induce microglia autophagy and facilitate Aß degradation, thereby improving cognitive function in AD model mice. Therefore, these findings suggest that UA may be a novel therapeutic agent for AD treatment.

An End-to-End Deep Hybrid Autoencoder Based Method for Single-Cell RNA-Seq Data Analysis.

Single-cell RNA sequencing technology provides powerful support for researchers to understand the complex mechanisms of cells at the single-cell level. Due to the high sparsity, technical noise, and computational complexity of single-cell transcriptome data, the existing data analysis methods are unable to effectively extract the fine-grained characteristics of scRNA-seq data, resulting in inaccurately analyze the heterogeneity of the individual cell from a great quantity of cell mixtures. To address these shortcomings, we proposed an end-to-end analysis method called dhaSCA, which integrates the Graph convolutional neural network (GCN) feature learning and downstream tasks such as classification and imputation into a unified deep learning manner. dhaSCA uses hybrid GCN-MLP deep autoencoder and to capture structural information between cells, and learn the low dimensional cell representation. It also introduces downstream tasks as constraints to guide the model to learn more accurate cell features. We conducted various experiments to evaluate the performance of dhaSCA based on eight real RNA-Seq datasets, including classification, imputation, clustering, and visualization. The results show that dhaSCA outperforms other state-of-the-art methods in these downstream tasks. Therefore, dhaSCA is able to obtain a richer representation of cells, and provides strong support for efficient analysis of single-cell data.

scGCC: Graph Contrastive Clustering With Neighborhood Augmentations for scRNA-Seq Data Analysis.

Single-cell RNA sequencing (scRNA-seq) has rapidly emerged as a powerful technique for analyzing cellular heterogeneity at the individual cell level. In the analysis of scRNA-seq data, cell clustering is a critical step in downstream analysis, as it enables the identification of cell types and the discovery of novel cell subtypes. However, the characteristics of scRNA-seq data, such as high dimensionality and sparsity, dropout events and batch effects, present significant computational challenges for clustering analysis. In this study, we propose scGCC, a novel graph self-supervised contrastive learning model, to address the challenges faced in scRNA-seq data analysis. scGCC comprises two main components: a representation learning module and a clustering module. The scRNA-seq data is first fed into a representation learning module for training, which is then used for data classification through a clustering module. scGCC can learn low-dimensional denoised embeddings, which is advantageous for our clustering task. We introduce Graph Attention Networks (GAT) for cell representation learning, which enables better feature extraction and improved clustering accuracy. Additionally, we propose five data augmentation methods to improve clustering performance by increasing data diversity and reducing overfitting. These methods enhance the robustness of clustering results. Our experimental study on 14 real-world datasets has demonstrated that our model achieves extraordinary accuracy and robustness. We also perform downstream tasks, including batch effect removal, trajectory inference, and marker genes analysis, to verify the biological effectiveness of our model.

Efficacy and safety of total glucosides of paeony in the treatment of recurrent aphthous ulcers: a single-center, double-blind, randomized, placebo-controlled clinical trial.

Introduction: There has been a lack of treatments available to lower the frequency of recurrent aphthous ulcers (RAUs) until now. Total glucosides of paeony (TGP) is a botanical drug extracted from the dried roots of Paeonia lactiflora Pall. [Ranunculaceae; Paeoniae Radix Alba]. This study aims to evaluate the efficacy and safety of TGP in the treatment of RAU. Methods: This study was registered with the Chinese Clinical Trial Registry (ChiCTR1900025623). Patients were randomly assigned to the TGP or placebo group and treated with 1.8 g/day for 24 weeks. Participants were observed for a total of 36 weeks and were asked to record ulcer severity, medication, and adverse reactions in the form of diaries or apps every day. The primary outcome was the monthly ulcer-free interval. Results: A total of 79 individuals were enrolled, with 40 assigned to the TGP group and 39 to the placebo group. The dropout rate was 18.18%. In the TGP group, the monthly ulcer-free interval was significantly longer than baseline (median, 9.6 days) since weeks 13-24 (median, 18.5 days) (p < 0.05), and after discontinuation, it was further prolonged (median, 24.7 days) than in weeks 13-24 (p < 0.05). In addition, the monthly ulcer-free interval was longer in the TGP group than in the placebo group (median, 15.9 days) at weeks 25-36 (p < 0.001). There were better improvements in the monthly number of ulcers and monthly area of ulcers, and visual analog scoring in the TGP group at weeks 25-36 (p < 0.001). Conclusion: TGP had a good long-term therapeutic effect on RAU with frequent occurrence. Systematic Review Registration: www.chictr.org.cn, identifier ChiCTR1900025623.