ObjectiveTo investigate the effects of Scutellariae Radix combined with epidermal growth factor receptor-tyrosine kinase inhibitors （EGFR-TKIs） on cell proliferation， apoptosis， cancer stem cell （CSC） marker expression， and metabolism in non-small cell lung cancer （NSCLC） cells. MethodsThe anti-tumor effects of Scutellariae Radix and EGFR-TKIs （gefitinib or osimertinib） in NSCLC cells were evaluated using the cell counting kit-8 （CCK-8） and Annexin V-FITC/propidium iodide （PI） double staining apoptosis assay. The activity of Scutellariae Radix and EGFR-TKIs in three-dimensional （3D） cultures of NSCLC cells was assessed using the CellTiter-Glo® 3D cell viability assay. The mRNA and protein expression levels of CSC markers， sex determining region y box protein 2 （SOX2） and aldehyde dehydrogenase 1 family member A1 （ALDH1A1）， were detected by quantitative real-time polymerase chain reaction （Real-time PCR） and Western blot， respectively. Changes in intracellular reactive oxygen species （ROS） levels were detected by ROS staining， and the redox ratio was detected by femtosecond laser labeling free imaging （FLI）. ResultsUnder both two-dimensional （2D） and 3D culture conditions， compared with the blank group and EGFR-TKI group， the combination group showed significantly reduced cell viability and increased apoptosis rate （P<0.05）. Compared with the EGFR-TKI group， the mRNA and protein levels of CSC markers were significantly downregulated in the combination group （P<0.05）. Additionally， the redox ratio was significantly elevated （P<0.05）， and ROS levels were also increased in the combination group compared with the EGFR-TKI group. ConclusionIn NSCLC cells， Scutellariae Radix enhances the redox ratio and increases ROS levels， thereby inhibiting the expression of CSC markers and strengthening the anti-tumor effects of EGFR-TKIs. This provides a novel molecular mechanism by which Scutellariae Radix may enhance the sensitivity of targeted therapies.

ObjectiveTransfer RNA-derived fragments (tRFs) are a recently characterized and rapidly expanding class of small non-coding RNAs, typically ranging from 13 to 50 nucleotides in length. They are derived from mature or precursor tRNA molecules through specific cleavage events and have been implicated in a wide range of cellular processes. Increasing evidence indicates that tRFs play important regulatory roles in gene expression, primarily by interacting with target messenger RNAs (mRNAs) to induce transcript degradation, in a manner partially analogous to microRNAs (miRNAs). However, despite their emerging biological relevance and potential roles in disease mechanisms, there remains a significant lack of computational tools capable of systematically predicting the interaction landscape between tRFs and their target mRNAs. Existing databases often rely on limited interaction features and lack the flexibility to accommodate novel or user-defined tRF sequences. The primary goal of this study was to develop a machine learning based prediction algorithm that enables high-throughput, accurate identification of tRF:mRNA binding events, thereby facilitating the functional analysis of tRF regulatory networks. MethodsWe began by assembling a manually curated dataset of 38 687 experimentally verified tRF:mRNA interaction pairs and extracting seven biologically informed features for each pair: (1) AU content of the binding site, (2) site pairing status, (3) binding region location, (4) number of binding sites per mRNA, (5) length of the longest consecutive complementary stretch, (6) total binding region length, and (7) seed sequence complementarity. Using this dataset and feature set, we trained 4 distinct machine learning classifiers—logistic regression, random forest, decision tree, and a multilayer perceptron (MLP)—to compare their ability to discriminate true interactions from non-interactions. Each model’s performance was evaluated using overall accuracy, receiver operating characteristic (ROC) curves, and the corresponding area under the ROC curve (AUC). The MLP consistently achieved the highest AUC among the four, and was therefore selected as the backbone of our prediction framework, which we named tRF Prospect. For biological validation, we retrieved 3 high-throughput RNA-seq datasets from the gene expression omnibus (GEO) in which individual tRFs were overexpressed: AS-tDR-007333 (GSE184690), tRF-3004b (GSE197091), and tRF-20-S998LO9D (GSE208381). Differential expression analysis of each dataset identified genes downregulated upon tRF overexpression, which we designated as putative targets. We then compared the predictions generated by tRF Prospect against those from three established tools—tRFTar, tRForest, and tRFTarget—by quantifying the number of predicted targets for each tRF and assessing concordance with the experimentally derived gene sets. ResultsThe proposed algorithm achieved high predictive accuracy, with an AUC of 0.934. Functional validation was conducted using transcriptome-wide RNA-seq datasets from cells overexpressing specific tRFs, confirming the model’s ability to accurately predict biologically relevant downregulation of mRNA targets. When benchmarked against established tools such as tRFTar, tRForest, and tRFTarget, tRF Prospect consistently demonstrated superior performance, both in terms of predictive precision and sensitivity, as well as in identifying a higher number of true-positive interactions. Moreover, unlike static databases that are limited to precomputed results, tRF Prospect supports real-time prediction for any user-defined tRF sequence, enhancing its applicability in exploratory and hypothesis-driven research. ConclusionThis study introduces tRF Prospect as a powerful and flexible computational tool for investigating tRF:mRNA interactions. By leveraging the predictive strength of deep learning and incorporating a broad spectrum of interaction-relevant features, it addresses key limitations of existing platforms. Specifically, tRF Prospect: (1) expands the range of detectable tRF and target types; (2) improves prediction accuracy through multilayer perceptron model; and (3) allows for dynamic, user-driven analysis beyond database constraints. Although the current version emphasizes miRNA-like repression mechanisms and faces challenges in accurately capturing 5'UTR-associated binding events, it nonetheless provides a critical foundation for future studies aiming to unravel the complex roles of tRFs in gene regulation, cellular function, and disease pathogenesis.

Chronic prostatitis/chronic pelvic pain syndrome (CP/CPPS) is a complex disease that is often accompanied by mental health disorders. However, the potential mechanisms underlying the heterogeneous clinical presentation of CP/CPPS remain uncertain. This study analyzed widely targeted metabolomic data of expressed prostatic secretions (EPS) and plasma to reveal the underlying pathological mechanisms of CP/CPPS. A total of 24 CP/CPPS patients from The Second Nanning People's Hospital (Nanning, China), and 35 asymptomatic control individuals from First Affiliated Hospital of Guangxi Medical University (Nanning, China) were enrolled. The indicators related to CP/CPPS and psychiatric symptoms were recorded. Differential analysis, coexpression network analysis, and correlation analysis were performed to identify metabolites that were specifically altered in patients and associated with various phenotypes of CP/CPPS. The crucial links between EPS and plasma were further investigated. The metabolomic data of EPS from CP/CPPS patients were significantly different from those from control individuals. Pathway analysis revealed dysregulation of amino acid metabolism, lipid metabolism, and the citrate cycle in EPS. The tryptophan metabolic pathway was found to be the most significantly altered pathway associated with distinct CP/CPPS phenotypes. Moreover, the dysregulation of tryptophan and tyrosine metabolism and elevation of oxidative stress-related metabolites in plasma were found to effectively elucidate the development of depression in CP/CPPS. Overall, metabolomic alterations in the EPS and plasma of patients were primarily associated with oxidative damage, energy metabolism abnormalities, neurological impairment, and immune dysregulation. These alterations may be associated with chronic pain, voiding symptoms, reduced fertility, and depression in CP/CPPS. This study provides a local-global perspective for understanding the pathological mechanisms of CP/CPPS and offers potential diagnostic and therapeutic targets.
Humans ; Male ; Prostatitis/blood* ; Adult ; Pelvic Pain/blood* ; Metabolomics ; Prostate/metabolism* ; Middle Aged ; Chronic Pain/blood* ; Metabolome ; Case-Control Studies ; Tryptophan/blood* ; Depression/blood* ; Oxidative Stress/physiology* ; Chronic Disease ; Lipid Metabolism/physiology*

Nonobstructive azoospermia (NOA), one of the most severe types of male infertility, etiology often remains unclear in most cases. Therefore, this study aimed to detect four biallelic detrimental variants (0.5%) in the minichromosome maintenance domain containing 2 ( MCMDC2 ) genes in 768 NOA patients by whole-exome sequencing (WES). Hematoxylin and eosin (H&E) demonstrated that MCMDC2 deleterious variants caused meiotic arrest in three patients (c.1360G>T, c.1956G>T, and c.685C>T) and hypospermatogenesis in one patient (c.94G>T), as further confirmed through immunofluorescence (IF) staining. The single-cell RNA sequencing data indicated that MCMDC2 was substantially expressed during spermatogenesis. The variants were confirmed as deleterious and responsible for patient infertility through bioinformatics and in vitro experimental analyses. The results revealed four MCMDC2 variants related to NOA, which contributes to the current perception of the function of MCMDC2 in male fertility and presents new perspectives on the genetic etiology of NOA.
Humans ; Male ; Azoospermia/genetics* ; Meiosis/genetics* ; Spermatogenesis/genetics* ; Adult ; Exome Sequencing ; Microtubule-Associated Proteins/genetics* ; Alleles ; Infertility, Male/genetics*

OBJECTIVE: To compare the therapeutic efficacy and safety of local anesthesia and spinal anesthesia for the patients with varicocele (VC) who underwent microsurgical varicocelectomy (MV). METHODS: We retrospectively analyzed the data of VC patients who underwent MV treatment at the Andrology Department of the Affiliated Ruikang Hospital of Guangxi University of Chinese Medicine from May 2020 to March 2023. Cases with complete clinical data and follow-up evaluation were selected and divided into a control group (spinal anesthesia) and an observation group (local anesthesia) according to different anesthesia methods. The surgical time (including anesthesia time), visual analogue scale (VAS) score for pain, hospital stay, treatment cost, sperm concentration, forward motile sperm rate, and normal sperm morphology rate after three months of surgery, as well as postoperative complications and recurrence rate were compared between the two groups. RESULTS: A total of 107 eligible cases were included, with 56 cases in the control group and 51 cases in the observation group. There was no significant difference in the VAS score for pain during and after four hours of surgery, as well as postoperative complications, and recurrence rate between the two groups (P> 0.05). There was an significant increase in sperm concentration, forward motile sperm rate, and normal sperm morphology rate in both of two groups after three months of surgery (P<0.05). However, there was no significant difference between the two groups three months after surgery (P>0.05). The surgical time and hospital stay were shorter than those of the control group (P<0.05). And the treatment cost in observation group was lower than that of the control group (P<0.05). CONCLUSION Both local anesthesia and lumbar anesthesia for MV treatment of VC have good efficacy and safety. However, patients treated with MV under local anesthesia for VC have obvious advantages in terms of operation time (including anesthesia time), hospital stay, and treatment cost, which is worthy of clinical promotion and application.
Humans ; Male ; Varicocele/surgery* ; Retrospective Studies ; Microsurgery ; Anesthesia, Spinal ; Adult ; Treatment Outcome ; Anesthesia, Local

OBJECTIVE: Automatic planning is a commonly used alternative to manual planning. This study evaluated the clinical performance of automatic plans available in commercial treatment planning systems for nasopharyngeal carcinoma (NPC) treatment by comparing automatic planning with manual planning. METHODS: A total of 14 patients with nasopharyngeal carcinoma were enrolled in the study. For each patient, three different sets of clinical goals were used to generate three hybrid automatic plans based on 3D dose distribution prediction and three automatic plans based on script, respectively, which were compared with the manual plans used in clinic. RESULTS: The dose coverage performance of the automatic planning based on 3D dose distribution prediction on the planning target volume (PTV) was comparable to that of the manual planning. Automatic planning based on 3D dose prediction achieved the level of manual planning in most organs at risk. However, automatic planning based on scripts did not perform well in the prediction of some organs at risk, especially the parotid gland. CONCLUSION The hybrid automatic plan based on 3D dose distribution prediction can reach the level of manual planning and have good robustness with the change of clinical objective.
Humans ; Nasopharyngeal Neoplasms/radiotherapy* ; Radiotherapy Planning, Computer-Assisted/methods* ; Nasopharyngeal Carcinoma ; Male ; Female ; Middle Aged ; Adult ; Carcinoma ; Radiotherapy Dosage

OBJECTIVES: To investigate the characteristics of immune cell infiltration in tumor samples from Chinese patients with clear cell renal cell carcinoma (ccRCC) and the correlation of immune cell infiltration with tumor stage and response to immunotherapy. METHODS: Tumor samples and clinicopathological data were collected from 154 ccRCC patients treated in Nanfang Hospital, Southern Medical University from October, 2020 to October, 2023. The immune cell types infiltrating the tumor tissues were identified using immunohistochemistry and immunofluorescence staining, and their correlations with the patients' clinicopathological characteristics were analyzed. Patient-derived tumor tissue fragment models (PDTF) models, constructed using tumor tissues from 22 patients, were treated with PD-1 monoclonal antibody, and T cell activation was detected using flow cytometry to assess the patients' responses to immunotherapy. RESULTS: In Chinese ccRCC patients included in this study, CD8⁺ T cells, CD4⁺ T cells, and CD3⁺ T cells were the most abundant in the tumor tissues. Higher infiltration levels of CD3⁺ T cells (P=0.004), PD-1⁺ T cells (P=0.020), CD68⁺ T cells (P=0.049), CD79⁺ T cells (P=0.049), and Tryptase⁺ cells (P=0.049) were all positively correlated with a larger tumor size (≥5 cm). A higher infiltration level of CD4⁺ T cells was associated with a lower tumor stage. Patients with higher International Society of Urological Pathology (ISUP) grades had higher infiltration levels of CD3⁺ T cells (P=0.023), CD8⁺ T cells (P=0.045), PD-1⁺ T cells (P=0.014), CD20⁺ B cells (P=0.020) and CD79⁺ B cells (P=0.049), and lower levels of Tryptase⁺ cells (P=0.001). Patients with abundant infiltrating immune cells tended to have better responses to immunotherapy. CONCLUSIONS The infiltrating immune cells are heterogeneous in Chinese ccRCC patients, and immune cell infiltration characteristics are closely correlated with clinicopathological parameters of the patients.
Humans ; Carcinoma, Renal Cell/pathology* ; Kidney Neoplasms/pathology* ; Immunotherapy ; Male ; Lymphocytes, Tumor-Infiltrating/immunology* ; Female ; Middle Aged ; CD8-Positive T-Lymphocytes/immunology* ; Aged ; T-Lymphocytes/immunology* ; Programmed Cell Death 1 Receptor/immunology* ; Adult ; CD4-Positive T-Lymphocytes/immunology* ; Neoplasm Staging

The gut-brain axis is a bidirectional communication pathway connecting the central nervous system and gastrointestinal tract,playing a key role in the occurrence and development of diseases related to this axis.The vermiform appendix,as a part of the gut that is connected to the cecum,has a unique anatomical location,a rich microbiome,and abundant immune cells.Appendicitis and appendectomy have been found to be associated with the development of diseases related to the gut-brain axis.This review first introduces the anatomy and functions of the vermiform appendix and then expounds the associations of appendicitis and appendectomy with diseases related to the gut-brain axis.Furthermore,this review summarizes and prospects the mechanisms of the vermiform appendix in affecting the occurrence and development of diseases related to the gut-brain axis.
Humans ; Appendix/anatomy & histology* ; Brain ; Appendicitis ; Appendectomy/adverse effects* ; Gastrointestinal Microbiome ; Brain-Gut Axis

Objective To investigate the spatiotemporal distribution characteristics and potential influencing factors of newly diagnosed echinococcosis cases in Qinghai Province from 2016 to 2022, so as to provide insights into the formulation of the echinococcosis control strategy in Qinghai Province. Methods The number of individuals screened for echinococcosis, number of newly diagnosed echinococcosis cases, number of registered dogs and number of stray dogs were captured from the annual reports of echinococcosis control program in Qinghai Province from 2016 to 2022, and the detection of newly diagnosed echinococcosis cases was calculated. The number of populations, precipitation, temperature, wind speed, sunshine hours, average altitude, number of year-end cattle stock, number of year-end sheep stock, gross domestic product (GDP) per capita, and number of village health centers in each county (district) of Qinghai Province were captured from the Qinghai Provincial Statistical Yearbook, and county-level electronic maps in Qinghai Province were downloaded from the National Platform for Common Geospatial Information Services. The software ArcGIS 10.8 was used to map the distribution of newly diagnosed echinococcosis cases in Qinghai Province, and the spatial autocorrelation analysis of newly diagnosed echinococcosis cases was performed. In addition, the spacetime scan analyses of number of individuals screened for echinococcosis, number of newly diagnosed echinococcosis cases and geographical coordinates in Qinghai Province were performed with the software SaTScan 10.1.2, and the spatial stratified heterogeneity of the detection of newly diagnosed echinococcosis cases was investigated with the software GeoDetector. Results A total of 6 569 426 residents were screened for echinococcosis in Qinghai Province from 2016 to 2022, and 5 924 newly diagnosed echinococcosis cases were found. The detection of newly diagnosed echinococcosis cases appeared a tendency towards a decline over years from 2016 to 2022 (χ² = 11.107, P < 0.01), with the highest detection in Guoluo Tibetan Autonomous Prefecture in 2017 (82.12/10⁵). There were spatial clusters in the detection of newly diagnosed echinococcosis cases in Qinghai Province from 2016 to 2018 (Moran’s I = 0.34 to 0.65, all Z values > 1.96, all P values < 0.05), and the distribution of newly diagnosed echinococcosis cases appeared random distribution from 2019 to 2022 (Moran’s I = −0.09 to 0.04, all Z values < 1.96, all P values > 0.05). Local spatial autocorrelation analysis showed high-high clusters and low-low clusters in the detection of new diagnosed echinococcosis cases in Qinghai Province from 2016 to 2022, and space-time scan analysis showed that the first most likely cluster areas of newly diagnosed echinococcosis cases in Qinghai Province from 2016 to 2022 were mainly distributed in Yushu Tibetan Autonomous Prefecture and Guoluo Tibetan Autonomous Prefecture. GeoDetector-based analysis of the driving factors for the spatial stratified heterogeneity of detection of newly diagnosed echinococcosis cases in Qinghai Province showed that average altitude, number of village health centers, number of cattle and sheep stock, GDP per capita, annual average sunshine hours, and annual average temperature had a strong explanatory power for the spatial distribution of newly diagnosed echinococcosis cases, with q values of 0.630, 0.610, 0.600, 0.590, 0.588, 0.537 and 0.526, respectively. Conclusions The detection of newly diagnosed echinococcosis cases appeared a tendency towards a decline in Qinghai Province over years from 2016 to 2022, showing spatial clustering. Targeted control measures are required in cluster areas of newly diagnosed echinococcosis cases for further control of the disease.

ObjectiveTo explore whether miR-375 regulates the malignant characteristics of osteosarcoma (OS) by influencing the expression of MMP13. MethodsPlasmid DNAs and miRNAs were transfected into OS cells and HEK293 cells using Lipofectamine 3000 reagent. Real-time quantitative polymerase chain reaction was performed to measure the expression of miR-375 and MMP13 in OS patients and OS cells. Western blot was performed to analyze the MMP13 protein in the patients with OS and OS cells. The targeting relationship between miR-375 and MMP13 was analyzed by luciferase assay. Migration and invasion were analysed by heal wound and transwell assays, respectively. ResultsmiR-375 expression in OS tissues was lower than that in normal tissues. The expression of MMP13 was upregulated in OS tissues. MMP13 expression was negatively correlated withmiR-375 expression in patients with OS. Migration and invasion were significantly inhibited in OS cells with the miR-375 mimic compared with OS cells with the miRNA control. MMP13 partially reversed the inhibition of migration and invasion induced by miR-375 in the OS cells. ConclusionmiR-375 attenuates migration and invasion by downregulating the expression of MMP13 in OS cells.