A growing body of research points out that gut microbiota plays a key role in tumor immunotherapy. By optimizing the composition of intestinal microbiota, it is possible to effectively improve immunotherapy resistance and enhance its therapeutic effect. This article comprehensively analyzes the mechanism of intestinal microbiota influencing tumor immunotherapy resistance, expounds the current strategies for targeted regulation of intestinal microbiota, such as traditional Chinese medicine and plant components, fecal microbiota transplantation, probiotics, prebiotics and dietary therapy, and explores the potential mechanisms of these strategies to improve patients' resistance to tumor immunotherapy. At the same time, the article also briefly discusses the prospects and challenges of targeting intestinal microbiota to improve tumor immunotherapy resistance, which provides a reference for related research to help the strategy research of reversing tumor immunotherapy resistance.

RNA modifications constitute a crucial class of post-transcriptional chemical alterations that profoundly influence RNA stability and translational efficiency, thereby shaping cellular protein expression profiles. These diverse chemical marks are ubiquitously involved in key biological processes, including cell proliferation, differentiation, apoptosis, and metastatic potential, and they exert precise regulatory control over these functions. A major advance in the field is the recognition that RNA modifications do not act in isolation. Instead, they participate in complex, dynamic interactions—through synergistic enhancement, antagonism, competitive binding, and functional crosstalk—forming what is now termed the “RNA modification interactome” or “RNA modification interaction network.” The formation and functional operation of this interactome rely on a multilayered regulatory framework orchestrated by RNA-modifying enzymes—commonly referred to as “writers,” “erasers,” and “readers.” These enzymes exhibit hierarchical organization within signaling cascades, often functioning in upstream-downstream sequences and converging at critical regulatory nodes. Their integration is further mediated through shared regulatory elements or the assembly into multi-enzyme complexes. This intricate enzymatic network directly governs and shapes the interdependent relationships among various RNA modifications. This review systematically elucidates the molecular mechanisms underlying both direct and indirect interactions between RNA modifications. Building upon this foundation, we introduce novel quantitative assessment frameworks and predictive disease models designed to leverage these interaction patterns. Importantly, studies across multiple disease contexts have identified core downstream signaling axes driven by specific constellations of interacting RNA modifications. These findings not only deepen our understanding of how RNA modification crosstalk contributes to disease initiation and progression, but also highlight its translational potential. This potential is exemplified by the discovery of diagnostic biomarkers based on interaction signatures and the development of therapeutic strategies targeting pathogenic modification networks. Together, these insights provide a conceptual framework for understanding the dynamic and multidimensional regulatory roles of RNA modifications in cellular systems. In conclusion, the emerging concept of RNA modification crosstalk reveals the extraordinary complexity of post-transcriptional regulation and opens new research avenues. It offers critical insights into the central question of how RNA-modifying enzymes achieve substrate specificity—determining which nucleotides within specific RNA transcripts are selectively modified during defined developmental or pathological stages. Decoding these specificity determinants, shaped in large part by the modification interactome, is essential for fully understanding the biological and pathological significance of the epitranscriptome.

Testicular histology based on testicular biopsy is an important factor for determining appropriate testicular sperm extraction surgery and predicting sperm retrieval outcomes in patients with azoospermia. Therefore, we developed a deep learning (DL) model to establish the associations between testicular grayscale ultrasound images and testicular histology. We retrospectively included two-dimensional testicular grayscale ultrasound from patients with azoospermia (353 men with 4357 images between July 2017 and December 2021 in The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China) to develop a DL model. We obtained testicular histology during conventional testicular sperm extraction. Our DL model was trained based on ultrasound images or fusion data (ultrasound images fused with the corresponding testicular volume) to distinguish spermatozoa presence in pathology (SPP) and spermatozoa absence in pathology (SAP) and to classify maturation arrest (MA) and Sertoli cell-only syndrome (SCOS) in patients with SAP. Areas under the receiver operating characteristic curve (AUCs), accuracy, sensitivity, and specificity were used to analyze model performance. DL based on images achieved an AUC of 0.922 (95% confidence interval [CI]: 0.908-0.935), a sensitivity of 80.9%, a specificity of 84.6%, and an accuracy of 83.5% in predicting SPP (including normal spermatogenesis and hypospermatogenesis) and SAP (including MA and SCOS). In the identification of SCOS and MA, DL on fusion data yielded better diagnostic performance with an AUC of 0.979 (95% CI: 0.969-0.989), a sensitivity of 89.7%, a specificity of 97.1%, and an accuracy of 92.1%. Our study provides a noninvasive method to predict testicular histology for patients with azoospermia, which would avoid unnecessary testicular biopsy.
Humans ; Male ; Azoospermia/diagnostic imaging* ; Deep Learning ; Testis/pathology* ; Retrospective Studies ; Adult ; Ultrasonography/methods* ; Sperm Retrieval ; Sertoli Cell-Only Syndrome/diagnostic imaging*

Intentional tooth replantation (ITR) is an advanced treatment modality and the procedure of last resort for preserving teeth with inaccessible endodontic or resorptive lesions. ITR is defined as the deliberate extraction of a tooth; evaluation of the root surface, endodontic manipulation, and repair; and placement of the tooth back into its original socket. Case reports, case series, cohort studies, and randomized controlled trials have demonstrated the efficacy of ITR in the retention of natural teeth that are untreatable or difficult to manage with root canal treatment or endodontic microsurgery. However, variations in clinical protocols for ITR exist due to the empirical nature of the original protocols and rapid advancements in the field of oral biology and dental materials. This heterogeneity in protocols may cause confusion among dental practitioners; therefore, guidelines and considerations for ITR should be explicated. This expert consensus discusses the biological foundation of ITR, the available clinical protocols and current status of ITR in treating teeth with refractory apical periodontitis or anatomical aberration, and the main complications of this treatment, aiming to refine the clinical management of ITR in accordance with the progress of basic research and clinical studies; the findings suggest that ITR may become a more consistent evidence-based option in dental treatment.
Humans ; Tooth Replantation/methods* ; Consensus ; Periapical Periodontitis/surgery*

Digital technologies have become an integral part of complete denture restoration. With advancement in computer-aided design and computer-aided manufacturing (CAD/CAM), tools such as intraoral scanning, facial scanning, 3D printing, and numerical control machining are reshaping the workflow of complete denture restoration. Unlike conventional methods that rely heavily on clinical experience and manual techniques, digital technologies offer greater precision, predictability, and efficacy. They also streamline the process by reducing the number of patient visits and improving overall comfort. Despite these improvements, the clinical application of digital complete denture restoration still faces challenges that require further standardization. The major issues include appropriate case selection, establishing consistent digital workflows, and evaluating long-term outcomes. To address these challenges and provide clinical guidance for practitioners, this expert consensus outlines the principles, advantages, and limitations of digital complete denture technology. The aim of this review was to offer practical recommendations on indications, clinical procedures and precautions, evaluation metrics, and outcome assessment to support digital restoration of complete denture in clinical practice.
Humans ; Denture, Complete ; Computer-Aided Design ; Denture Design/methods* ; Consensus ; Printing, Three-Dimensional

Objective:To explore the genetic basis of eighteen patients with tetrahydrobiopterin deficiency (BH4D) from Gansu Province.Methods:Eighteen patients diagnosed with BH4D at Gansu Provincial Maternal and Child Health Care Hospital from January 2018 to December 2021 were selected as the study subjects. Whole exome sequencing was carried out, and candidate variants were verified by Sanger sequencing.Results:All of the thirty-six alleles of the eighteen patients were successfully determined by molecular genetic testing. Sixteen patients were found to harbor variants of the PTS gene, and two had harbored variants of the QDPR gene. Ten variants were detected in the PTS gene, with the most common ones being c. 259C>T (34.38%) and c. 286G>A (15.63%). Based on the guidelines from the American College of Medical Genetics and Genomics (ACMG), the c. 259C>T was classified as a pathogenic variant, whilst the c. 286G>A, c. 166G>A, c. 200C>T, c. 272A>G, c. 402A>C, c. 421G>T, c. 84-291A>G and c. 317C>T were classified as likely pathogenic variants. A novel c. 289_290insCTT variant was classified as likely pathogenic (PM1+ PM2_Supporting+ PM3+ PP3+ PP4). The two variants (c.478C>T and c. 665C>T) detected in the QDPR gene were both classified as variants of uncertain significance (PM1+ PM2_Supporting+ PP3+ PP4). Conclusion:Genetic testing has clarified the pathogenic variants in these BH4D patients, which has enabled timely and accurate clinical intervention and treatment, and provided a reference for genetic counseling and reproductive guidance for their families.

Objective To investigate the relationship between single nucleotide polymorphisms(SNPs)in the eNOS gene and genetic susceptibility to systemic lupus erythematosus(SLE)in Hainan.Methods Blood samples were collected from SLE patients(SLE group,n=214)and healthy controls(control group,n=214)from January 2020 to December 2022 at the First Affiliated Hospital of Hainan Medical College and Hainan Provincial People's Hospital.The bases of eNOS gene rs3918188,rs1799983 and rs1007311 loci in each group were detected by SNaPshot sequencing technology.Logistic regression was used to analyze the correlation between genotypes,alleles and gene models(dominant model,recessive model,and overdominant model)of the above 3 target loci of the eNOS gene and genetic susceptibility to SLE.Haplotype analysis was conducted using HaploView 4.2 software to investigate the relationship between haploid and genetic susceptibility to SLE at each site.Results The results of logistic regression analysis revealed that the CC genotype and the C allele at rs3918188 locus were risk factors for genetic susceptibility to SLE(CC vs.AA:OR=2.449,P<0.05;C vs.A:OR=2.133,P<0.001).In recessive model at rs3918188 locus,CC genotype carriers had an increased risk of SLE development compared with AA+AC genotype carriers(OR=2.774,P<0.001).In contrast,in overdominant model at this locus,AC genotype carriers had a decreased risk of SLE occurrence compared with AA+CC genotype carriers(OR=0.385,P<0.001).In addition,polymorphisms of rs1799983 and rs1007311 were not associated with susceptibility to SLE in genotype,allele type and the 3 genetic models(P>0.05).Haplotype analysis revealed a strong linkage disequilibrium between the rs1007311 and rs1799983 loci of the eNOS gene,but no significant correlation was found between haplotype and genetic susceptibility to SLE(P>0.05).Conclusion The CC genotype and C allele at rs3918188 locus of eNOS gene may be risk factors for SLE in Hainan,while the risk of SLE occurrence is reduced in carriers of AC genotype under the overdominant model.

Objective To explore the association between violent behaviors and emotions in individuals with mental disorders,to evaluate the application value of facial expression analysis technology in violence risk assessment of individuals with mental disorders in supervised settings,and to provide a reference for violence risk assessment.Methods Thirty-nine male individuals with mental disorders in supervised settings were selected,the participant risk of violence,cognitive function,psychiatric symptoms and se-verity were assessed using the Modified Overt Aggression Scale (MOAS),the Historical,Clinical,Risk Management-Chinese version(HCR-CV),the Positive and Negative Syndrome Scale (PANSS) and the Brief Psychiatric Rating Scale (BPRS).An emotional arousal was performed on the participants and the intensity of their emotions and facial expression action units was recorded before,during and after the arousal.One-way analysis of variance (ANOVA) was used to compare the differences in the intensity of emotions and facial expression action units before,during and after the arousal.Pearson correlation analysis was used to calculate the correlations between the intensity of the seven basic emo-tional facial expressions and the scores of the assessment scales.Results The intensity difference of sadness,surprise and fear in different time periods was statistically significant (P<0.05).The intensity of the left medial eyebrow lift action unit was found significantly different before and after the emo-tional arousal (P<0.05).The intensity of anger was positively correlated with the Modified Overt Ag-gression Scale score throughout the experiment (P<0.05).Conclusion Eye action units such as eye-brow lifting,eyelid tightening and upper eyelid lifting can be used as effective action units to identify sadness,anger and other negative emotions associated with violent behaviors.Facial expression analysis technology can be used as an auxiliary tool to assess the potential risk of violence in individuals with mental disorders in supervised settings.

AIM:To compare the differences of ocular biometric parameters of age-related cataract between Tibetan and Han ethnic groups, and to analyze the distribution characteristics of ocular biometric parameters in Tibetan cataract patients.METHODS:Retrospective cohort study. A total of 661 patients(1 030 eyes)with age-related cataract confirmed in the hospital between January 2019 and December 2020 were enrolled. The parameters of axial length, anterior chamber depth, keratometry, corneal astigmatism and astigmatic axis were measured by IOL Master 500 in 483 cases(739 eyes)of Tibetan age-related cataract patients and 178 cases(291 eyes)of Han patients.RESULTS:The axial length, anterior chamber depth and corneal astigmatism of the Tibetan patients with age-related cataract were 23.33(22.81, 23.86)mm, 3.04(2.79, 3.30)mm and 0.73(0.47, 1.07)D. The mean keratometry was 43.89±1.35 D. The results indicated that Tibetan cataract patients had shorter axial lengths and smaller keratometry compared to Han patients(all P<0.05). Age in Tibetan patients was negatively correlated with axial length and anterior chamber depth, and positively correlated with keratometry(all P<0.05). Tibetan male patients had longer axial lengths, deeper anterior chambers, and flatter corneas compared to female patients(all P<0.05).CONCLUSION:There were differences in ocular biometric parameters between age-related cataract patients of Tibetan and Han ethnicities. The distribution of ocular biometric parameters in Tibetan cataract patients varied across different age groups and gender groups.

ObjectiveAlthough expression of the TEAD1 protein in preadipocytes has been established, its function remains unclear. In this study, we sought to detect transcripts of TEAD1 in chicken and to examine the effects of this protein on the proliferation, migration, apoptosis, and differentiation of immortalized chicken preadipocyte cell lines (ICP1). MethodsThe full-length sequence of the TEAD1 gene was cloned and the two transcripts were subjected to bioinformatics analysis. The subcellsular localization of TEAD1 transcripts was determined based on indirect immunofluorescence. The effects of TEAD1 transcripts overexpression on the proliferation of ICP1 cells were examined by RT-qPCR, CCK-8, and EdU assays; the effects of TEAD1 transcripts on ICP1 cells migration were examined based on the scratch test; and the effects of TEAD1 transcripts overexpression on ICP1 cells apoptosis were analyzed using apoptosis-Hoechst staining and RT-qPCR. The expression of TEAD1 transcripts in different tissues, cells lines, and ICP1 at different periods of differentiation was analyzed by RT-qPCR. The effects of TEAD1 transcripts overexpression on lipid droplet accumulation and adipogenic-related gene expression in ICP1 cells were analyzed based on Oil Red O and BODIPY staining, RT-qPCR, Western blot, and dual-luciferase reporter gene assays. Finally, the content of triglyceride (TG) was measured in TEAD1 overexpressed ICP1 cells. ResultsThe full-length TEAD1 was cloned and two TEAD1 transcripts were identified. The TEAD1-V1 protein was found to be localized primarily in the cell nucleus, whereas the TEAD1-V2 protein is localized in the cell cytoplasm and nucleus. The overexpression of both TEAD1-V1 and TEAD1-V2 significantly inhibited the proliferation of ICP1 cells. Whereas the overexpression of TEAD1-V1 promoted ICP1 cell migration, the overexpression of TEAD1-V2 had no significant effects on ICP1 migration; the overexpression of both TEAD1-V1 and TEAD1-V2 significantly promoted the apoptosis of ICP1 cells. We found that the different transcripts of TEAD1 have similar expression pattern in different tissues and cells lines. During induced preadipocyte differentiation, the expression of these genes initially declined, although subsequently increased. Overexpression of TEAD1-V1 promoted a significant reduction in lipid droplet formation and inhibited C/EBPα expression during the differentiation of ICP1 cells (P<0.05). However, the overexpression of TEAD1-V2 had no significant effect on lipid droplet accumulation or the expression of adipogenic-related proteins (P>0.05). Overexpression of TEAD1-V1 significantly decreased triglyceride content in ICP1 cells (P<0.05), while overexpression of TEAD1-V2 had no effect on triglyceride content in ICP1 cells (P>0.05). ConclusionIn this study, for the first time, identified two TEAD1 transcripts. Overexpressed transcripts TEAD1-V1 and TEAD1-V2 both inhibited the proliferation of chicken preadipocytes and promoted apoptosis of chicken preadipocytes. TEAD1-V1 inhibited the differentiation of preadipocytes and promoted the migration of preadipocytes, while TEAD1-V2 had no effect on the differentiation and migration of preadipocytes.