Patients with Takayasu arteritis combined with aortic valve disease often have a poor prognosis following surgical valve replacement, frequently encountering complications such as perivalvular leakage, valve detachment, and anastomotic aneurysm. This article presents a high-risk case wherein severe aortic valve insufficiency associated with Takayasu arteritis was successfully managed through transcatheter aortic valve implantation via the transapical approach. The patient had satisfactory valve function with no complications observed during the six-month postoperative follow-up. This case provides a minimally invasive and feasible alternative for the clinical management of such high-risk patients.

In recent years， repetitive transcranial magnetic stimulation （rTMS） has garnered significant attention as a therapeutic approach for sleep disorders in the elderly. However， the prevailing rTMS protocols are predominantly developed based on normative neurophysiological data derived from young adults and fail to incorporate individualized parameters tailored to the brain characteristics of the elderly. To address this gap， the consensus development group synthesized the latest evidence from 2010 to 2025 and established a standardized rTMS protocol specifically for elderly patients with sleep disorders. Adhering to the Appraisal of Guidelines for Research and Evaluation II （AGREE II） framework， systematically screened randomized controlled trials （RCTs） and systematic reviews regarding rTMS in the treatment of sleep disorders across various conditions. Meanwhile， the Grading of Recommendations Assessment， Development and Evaluation （GRADE） system was employed to rigorously grade the quality of evidence and the strength of recommendations. This consensus guideline delineates precise rTMS protocols for the management of sleep disorders in the elderly， highlights the adjustment of stimulation intensity according to scalp-cortex distance recommends either MRI‑guided neuronavigation or the Beam F3/F4 heuristic approach for accurate target localization， thereby providing precise rTMS intervention protocol for sleep disorders in the elderly， aiming to enhance clinical efficacy while ensuring treatment safety. ［Funded by National Key Research and Development Program （number， 2023YFC3603200）； General Program of Shenzhen Science and Technology Innovation Commission （number， JCYJ20240813112859008， JCYJ20240813112900002）； Youth Program of Shenzhen Kangning Hospital （number， KN2023A004）； www.guidelines-registry.cn number， PREPARE-2026CN530］

ObjectiveTo investigate the novel post-translational modifications (PTMs) of SnRK2.6, a central component in the abscisic acid (ABA) signaling pathway, such as SUMOylation, and to establish a foundation for revealing the physiological functions and molecular mechanisms of SnRK2.6 regulated by these new modifications. MethodsThe interaction between SnRK2.6 and the SUMO E3 ligase SIZ1, as well as members of the SUMO protease family, was examined using yeast two-hybrid and in vitro pull-down assays. An in vitro SUMOylation system in Escherichia coli was utilized to determine whether SnRK2.6 undergoes SUMOylation. Mass spectrometry, combined with site-directed mutagenesis of candidate lysine residues, was employed to identify potential SUMOylation sites on SnRK2.6. In vitro de-SUMOylation assays were performed to assess whether SUMO proteases interacting with SnRK2.6 could catalyze the removal of SUMO moieties from modified SnRK2.6. The protein stability of SnRK2.6 was assessed in a cell-free degradation assay using bacterial-purified SnRK2.6 incubated with total protein extracts from Col and siz1 mutant seedlings. To dissect the genetic relationship between SnRK2.6 and SIZ1, stomatal aperture assays were performed under ABA treatment using snrk2.6, siz1, and snrk2.6 siz1 double mutant plants. ResultsSnRK2.6 physically interacts with SIZ1 and the SUMO protease ESD4, with the binding domains localized to the C-terminal region of SIZ1 and the N-terminal region of ESD4, respectively. SnRK2.6 was found to be SUMOylated, exhibiting two distinct high-molecular-mass bands ranging from 70 to 100 ku, indicative of modified forms. Bioinformatics analysis predicted four putative SUMOylation sites on lysine residues K57, K63, K142, and K190. Mass spectrometry identified three SUMOylation sites on K63, K142, and K174. However, individual or combinatorial point mutations on these sites had minimal impact on the pattern or intensity of SUMOylation signals, suggesting that these residues may not be responsible for the SUMOylation on SnRK2.6. Instead, such mutations only weaken the protein stability or accelerate the protein mobility of SnRK2.6. Therefore, the exact SUMOylation sites on SnRK2.6 remain unidentified. In de-SUMOylation experiments, incubation of GST-ESD4 with SUMOylated SnRK2.6 for 1-2 h led to the near-complete disappearance of both SUMOylated bands. In contrast, neither the GST control nor the catalytically inactive mutant GST-ESD4^C448S exhibited any de-SUMOylation activity. In protein turnover experiments, SnRK2.6 exhibited markedly enhanced half-life in siz1 compared with Col, indicating that SIZ1-dependent SUMOylation promotes SnRK2.6 turnover. Phenotypically, snrk2.6 mutants were completely insensitive to ABA-induced stomatal closure; siz1 mutants displayed pronounced hypersensitivity; and the snrk2.6 siz1 double mutant phenocopied snrk2.6—showing no significant response to ABA beyond that of the snrk2.6 mutant. These data indicate that SIZ1 acts as a negative regulator of ABA-triggered stomatal closure and SnRK2.6 functions as a positive regulator, and the inhibitory activity of SIZ1 is strictly dependent on SnRK2.6, placing SnRK2.6 genetically upstream of SIZ1 in the ABA signaling pathway. ConclusionSnRK2.6 undergoes SUMOylation, although the specific SUMOylation sites have not been defined. SnRK2.6 is dynamically regulated by reversible SUMOylation—catalyzed by SIZ1 and reversed by ESD4—which controls its protein stability. SUMOylation acts as a destabilizing signal for SnRK2.6, and SIZ1 exerts its negative effect on ABA-triggered stomatal closure probably through promoting SnRK2.6 degradation via SUMOylation. These findings uncover SUMOylation as a critical regulatory layer fine-tuning SnRK2.6 abundance in ABA signaling.

Liver cancer (LC) remains one of the most prevalent tumors globally. Despite considerable advancements in its clinical treatment in recent years, the global burden of this disease is projected to increase. According to World Health Organization statistics, the number of LC deaths worldwide in 2022 was 760,000, ranking third among all cancers. Therefore, there is an urgent need to delve deeper into the realms of LC diagnosis, prognosis, and treatment. Proteomics, as an emerging technology leveraging mass spectrometry (MS)-based protein identification, liquid chromatography separation, and bioinformatics-driven data integration, enables the systematic characterization of proteome dynamics to address critical challenges in LC research. These challenges include the discovery of diagnostic and prognostic biomarkers as well as therapeutic targets. By scrutinizing the expression of specific proteins in both normal and cancerous tissues through high-throughput protein microarrays, researchers can uncover novel biomarkers. The use of these biomarkers alone or in combination with established ones holds the potential to significantly advance the fields of LC diagnosis, prognosis, and treatment. In general, the application of proteomics has significantly promoted the development of LC research. In this review, we summarized the latest advancements in the application of proteomics in LC, with a particular focus on diagnosis, prognosis, and treatment. We also concluded selected protein markers, aiming to offer guidance for further applications and present additional therapeutic targets for LC.

ObjectiveTo investigate the distribution characteristics and correlation of paired oral and esophageal microbiota in patients with esophageal squamous cell carcinoma （ESCC）. MethodsA total of 46 pathologically confirmed ESCC patients were enrolled， and oral swabs and cancerous tissue samples were collected. The microbial composition was analyzed using 16S rRNA gene sequencing， and bioinformatics methods were employed to compare the microbiota diversity， compositional differences， and correlations between the two sites. ResultsThe Alpha diversity of the oral microbiota in ESCC patients was significantly higher than that of their esophageal microbiota， though the overall community structure was similar between the two sites. LEfSe analysis revealed that Spirochaetes， Prevotella， Catonella， Enterococcus， Fusobacterium periodonticum， Veillonella parvula， Capnocytophaga sputigena， and Neisseria subflava were significantly enriched in ESCC tumor tissues. In contrast， Actinobacteria， Proteobacteria， Streptococcus， Neisseria， Haemophilus， Streptococcus mitis， Haemophilus parainfluenzae， Porphyromonas gingivalis， Haemophilus haemolyticus， and Prevotella tannerae were significantly enriched in the oral cavity. Correlation analysis demonstrated significant associations between the two sites at taxonomic levels such as Spirochaetes， Treponema， Granulicatella elegans， Neisseria macacae， Treponema amylovorum， Fusobacterium periodonticum， and Neisseria meningitidis （P<0.05）. ConclusionThe oral and esophageal microbiota in ESCC patients exhibit both distinct differences and similarities. Oral microbiota may influence the esophageal microenvironment through migration or local immune modulation.

Patients with lung cancer experience a heavy symptom burden during the perioperative period, which seriously affects their recovery and quality of life. Traditional symptom management models rely mainly on scheduled ward rounds during hospitalization and outpatient follow-up after discharge. However, they have limitations such as delayed symptom recognition, lack of post-discharge monitoring, and non-quantitative symptom assessment, which often lead to delayed interventions and low patient satisfaction. In recent years, the symptom management model based on electronic patient-reported outcomes (ePRO) has been increasingly valued in clinical practice. Existing high-level evidence from both domestic and international studies indicates that, through proactive monitoring, real-time alerts, and remote interventions, this model enables dynamic and continuous symptom management and helps improve patient recovery and healthcare experience. As a supplement to routine medical care, the ePRO-based symptom management model aims to enhance the quality of care rather than replace existing medical processes. To promote the standardized application of this model in perioperative lung cancer care, this consensus integrates domestic and international evidence. After multiple rounds of voting by more than 50 experts, it formulates 12 consensus statements covering the three core components, symptom monitoring, alerting, and intervention, to provide scientific and practical recommendations for clinical practice.

Objective To analyze the predictive value of the combined application of triglyceride-glucose index (TyG) and triglyceride-glucose-body mass index (TyG-BMI) for the severity of coronary artery lesions in postmenopausal patients with coronary heart disease (CHD). Methods Menopausal women who were diagnosed by coronary angiography and received treatment in the cardiovascular department were selected as the research subjects. According to the Gensini score, the patients were divided into a moderate group (n=151) and a severe group (n=203). The clinical indexes of the two groups were compared and ROC analysis was used to predict the efficacy. Results The BMI, age, hypertension rate, WBC, PLT, NEUT, TC, TG, LCI, TyG, and TyG‑BMI in the severe group were significantly higher than those in the moderate group, while ALB was significantly lower than that in the moderate group (P<0.05). Multivariate logistic regression showed that age, hypertension, WBC, TyG, and TyG‑BMI were independent risk factors for severe coronary artery disease in postmenopausal women (P<0.05). ROC curve analysis showed that the AUC of TyG was 0.745, the AUC of TyG‑BMI was 0.797, and the AUC of TyG combined with TyG‑BMI was 0.803, all showing good predictive performance. Conclusion TyG and TyG‑BMI are effective indicators for predicting the severity of coronary artery disease in postmenopausal CHD patients. The combination of the two can further improve predictive efficacy, providing a simple and economical reference for early clinical risk stratification.

T-cell acute lymphoblastic leukemia (T-ALL) is a highly aggressive hematologic malignancy with a poor prognosis, despite advancements in treatment. Many patients struggle with relapse or refractory disease. Investigating the role of the super-enhancer (SE) regulated gene ubiquitin-specific protease 20 (USP20) in T-ALL could enhance targeted therapies and improve clinical outcomes. Analysis of histone H3 lysine 27 acetylation (H3K27ac) chromatin immunoprecipitation sequencing (ChIP-seq) data from six T-ALL cell lines and seven pediatric samples identified USP20 as an SE-regulated driver gene. Utilizing the Cancer Cell Line Encyclopedia (CCLE) and BloodSpot databases, it was found that USP20 is specifically highly expressed in T-ALL. Knocking down USP20 with short hairpin RNA (shRNA) increased apoptosis and inhibited proliferation in T-ALL cells. In vivo studies showed that USP20 knockdown reduced tumor growth and improved survival. The USP20 inhibitor GSK2643943A demonstrated similar anti-tumor effects. Mass spectrometry, RNA-Seq, and immunoprecipitation revealed that USP20 interacted with hypoxia-inducible factor 1 subunit alpha (HIF1A) and stabilized it by deubiquitination. Cleavage under targets and tagmentation (CUT&Tag) results indicated that USP20 co-localized with HIF1A, jointly modulating target genes in T-ALL. This study identifies USP20 as a therapeutic target in T-ALL and suggests GSK2643943A as a potential treatment strategy.

Type 2 diabetes (T2D) is an independent risk factor for cognitive impairment. The dysregulation of hypoxia inducible factor (HIF) signaling in T2D patients results in impaired adaptive responses to hypoxia, thereby accelerating the progression of complications. However, limited knowledge is available regarding its precise function in diabetes-associated cognitive impairment (DACI). Here, elevated HIF-1α levels were observed in brain endothelial cells (ECs) of db/db mice. Functionally, brain ECs-specific knockdown of H if1 a significantly ameliorated T2D-induced memory loss and neuronal damage. Glycolysis in brain ECs was inhibited in this process, as indicated by RNA-seq, leading to decreased hippocampal lactate production through reduced LDHA expression. Notably, T2D patients showed increased cerebrospinal fluid lactate levels, which were strongly associated with their cognitive dysfunction. Intrahippocampal injection of lactate accelerated cognitive dysfunction and impaired adult hippocampal neurogenesis (AHN) in db/db mice. Conversely, reducing hippocampal lactate levels through the intrahippocampal injection of oxamate delayed the onset of memory deficits. Furthermore, asiatic acid was discovered to protect db/db mice from cognitive impairment by decreasing brain endothelial HIF-1α expression and subsequently reducing hippocampal lactate-induced AHN damage. Overall, this study elucidates the inhibiting role played by endothelial HIF-1α-driven lactate in AHN and highlights a potential tactic of targeting HIF-1α in brain ECs for treating cognitive impairment.