Beijing Institute of Neurosurgery

SLC26A4 is a major causative gene for hereditary hearing loss, its mutation spectrum shows pronounced population specificity. In Chinese populations, patients predominantly carry biallelic mutations, and compound heterozygous genotypes are prevalent, which results in a wide spectrum of auditory phenotypes. However, how different alleles interact within these contexts to shape phenotypic variability remains poorly understood. We employed cellular and mouse models to explore the allele-specific mechanisms associated with two novel mutations, a frameshift mutation and a missense mutation, in compound heterozygous that share the same splice-site pathogenic allele. In vitro, wild-type (WT) and mutant (c.574delC, c.1211C>A) SLC26A4 constructs were expressed in HeLa cells to assess pendrin localization. Both mutations reduced membrane enrichment and increased intracellular retention. In vivo, compound heterozygous knock-in mouse models (Slc26a4c.574delC/c.919-2A>G and Slc26a4c.1211C>A/c.919-2A>G) were generated using CRISPR/Cas9. The auditory function and cochlear pathology were investigated. Both compound mutants exhibited elevated ABR thresholds, with more severe hearing loss in Slc26a4c.574delC/c.919-2A>G mice. Correspondingly, these mice showed marked hair cell disruption, stereociliary loss, and cochlear structural abnormalities, whereas the Slc26a4c.1211C>A/c.919-2A>G mice displayed milder changes. Transcriptomic profiling examined by bulk RNA-sequencing revealed broader differential expression in Slc26a4c.574delC/c.919-2A>G mice, enriched in structural and developmental pathways, while the missense model showed predominantly immune-related signatures. Our findings demonstrate that allele-specific functional divergence in compound heterozygous SLC26A4 mutations leads to distinct auditory dysfunction, cochlear pathology, and transcriptional programs. These findings provide mechanistic insight into the phenotypic heterogeneity of hearing loss and may indicate future allele-specific interventions or therapeutic strategies.

Osteosarcoma, the most common primary malignant bone tumour, presents significant treatment challenges due to its complex tumour microenvironment and the development of chemoresistance. This study employs single-cell transcriptomics to investigate chemotherapy-induced changes in osteosarcoma at both the cellular and molecular levels. Single-cell RNA sequencing data were analysed to identify cell subpopulations and their responses to chemotherapy. Differential gene expression and pathway enrichment analyses were performed to elucidate chemotherapy-induced changes. Additionally, we developed and validated a predictive model based on pyroptosis-related genes, named Pyroscore, using 101 different machine-learning algorithms. Chemotherapy led to an increased proportion of osteoclasts, endothelial cells, mesenchymal stem cells and pericytes, while decreasing T and NK cells, B cells, chondroblasts, monocytes and macrophages. Chemotherapy markedly upregulates the pyroptosis pathway in tumour cells, suggesting that chemotherapy induces programmed cell death in cancer cells through the activation of pyroptosis. Metabolic pathway analysis revealed significant inhibition of sulphur metabolism, starch and sucrose metabolism, pentose phosphate pathway, inositol phosphate metabolism, nitrogen metabolism and fatty acid metabolism. The Pyroscore model, which incorporates BAK1, CASP1, CASP5 and CASP6, demonstrated robust prognostic value across multiple data sets, with high scores correlating with improved survival outcomes. This study highlights the impact of chemotherapy on osteosarcoma cell subpopulations and the tumour microenvironment. The activation of the pyroptosis pathway and the development of the pyroscore prognostic model provide new insights into the mechanisms of chemotherapy response and potential therapeutic targets. These findings underscore the importance of personalized treatment strategies in improving outcomes for osteosarcoma patients.

Tumor location has been demonstrated to influence the risk of epilepsy in patients with low-grade gliomas (LGGs). However, existing evidence is mainly based on dichotomized analyses, without adequately accounting for seizure frequency. We present a voxel-wise lesion analysis to investigate the potential correlations between the location of tumor and the frequency of seizure occurrence in patients with LGGs. We retrospectively reviewed the clinical information and magnetic resonance images of 352 patients pathologically confirmed with LGGs. Preoperative seizure frequency during the 3 months prior to the primary surgery was classified as daily (≥1/day), weekly (≥1/week), monthly (≥1/month) and rare (<1/month). A voxel-based lesion-symptom mapping analysis was performed to identify the association between tumor location and preoperative seizure frequency. LGGs involving the left primary motor area or right insular and basal ganglia were associated with an increased risk of frequent seizures (≥1/month). A focal aware seizure was more likely to frequently occur compared with a focal to bilateral tonic-clonic seizure caused by LGGs (p < 0.001). Tumors that caused a high seizure frequency were less likely to be completely removed (p = 0.008). Furthermore, preoperative seizure frequency was a significant predictor of seizure outcomes at 6 months after surgery as determined by a univariate analysis (p = 0.002). This study utilized voxel-level neuroimaging analyses to identify the anatomical correlations of seizure frequency in patients with LGGs, providing further insight into seizure risk stratification and potential implications for surgical management.

Background: Chronic rhinitis, including allergic rhinitis (AR) and nonallergic rhinitis (NAR), is frequently influenced by environmental factors such as temperature. This study aimed to investigate the characteristics of temperature-sensitive rhinitis patients and to explore the effects of temperature on nasal symptoms. Methods: A cross-sectional study was conducted from February 2023 to February 2024 at Beijing Tongren Hospital, enrolling 5,595 adult outpatients with chronic rhinitis. Patients were diagnosed with AR or NAR, with AR further classified into seasonal allergic rhinitis (SAR) and perennial allergic rhinitis (PAR). Standardized questionnaires and serum-specific immunoglobulin E testing were performed. Nasal symptoms (congestion, itching, sneezing, and rhinorrhea) were assessed using a visual analogue scale. A generalized linear model with cubic spline functions was used to examine nonlinear associations between ambient temperature and nasal symptoms, adjusting for potential confounders. Associations between temperature sensitivity, symptom severity, and environmental exposures were analyzed. Results: A total of 83.6% of patients with AR and 84.5% of those with NAR reported temperature sensitivity. Patients sensitive to temperature changes had significantly higher nasal symptom scores than those insensitive to temperature changes ( P &lt; 0.001). The proportion of temperature-sensitive individuals increased with the severity of chronic rhinitis symptoms. In SAR, symptoms exhibited an inverted U -shaped relationship with temperature, peaking around 20°C, which corresponded to the pollen peak. In PAR, low-temperature environments (&lt;20°C) aggravated nasal congestion and were the main factor affecting quality of life. Conclusions: Temperature-sensitive rhinitis patients experience more severe nasal symptoms. Low-temperature environments have the greatest impact on patients with PAR, particularly exacerbating symptoms of nasal congestion. Temperature indirectly affects the nasal symptoms in SAR patients by influencing pollen exposure.

Stimulation of the subthalamic nucleus (STN) and globus pallidus internus (GPi) is an effective target for treating blepharospasm-oromandibular dystonia, but the individual optimal remains unclear. Thirteen patients with blepharospasm-oromandibular dystonia were enrolled. Bilateral STN and GPi electrodes were implanted and externalized, and the signal of the two targets was recorded simultaneously. The power spectrum and burst characteristics were analyzed to see how they were related to symptom severity. The 1year follow-up revealed an overall improvement rate of 76.21% ± 12.51%. Those with GPi as final targets showed higher band power and longer average burst duration in the 5.5-12Hz band in the GPi compared to the STN (P < 0.05). Conversely, those with STN as final targets showed higher band power and longer average burst duration in the 6-10Hz band in the STN compared to the GPi (P < 0.05). Exclusion of shorter low-frequency bursts led to higher correlation coefficients with BFMDRS-M scores in both the STN and GPi groups (P < 0.01). Our study suggests that low-frequency oscillatory features may be associated with therapeutic target selection for DBS in blepharospasm-oromandibular dystonia. These findings may help inform target selection strategies and warrant prospective validation for their value in supporting long-term clinical outcomes.

Hypertriglyceridemia (HTG) is a crucial risk factor for cardiovascular disease, metabolic syndrome, and type 2 diabetes. However, its early detection remains challenging due to the dynamic fluctuations in plasma triglyceride levels and their limited utility in predicting long-term dyslipidemia. This study aimed to elucidate the role of asymmetric dimethylguanidino valeric acid (ADGV) in HTG through integrated cohort analyses and mechanistic cellular experiments. Circulating ADGV levels were quantified in a cross-sectional cohort from southern China (n = 588) and assessed its prospective association with incident HTG in an independent prospective cohort from northern China (n = 348, median follow-up: 1.8 years). Hepatocyte experiments were performed to examine biological plausibility and explore potential mechanisms linking ADGV to hepatic triglyceride metabolism. Elevated ADGV levels were significantly associated with increased risk of HTG and remained independently associated after adjustment for age, gender, BMI, eGFR, lifestyle factors, and liver function. Complementary in vitro studies in hepatocytes revealed that ADGV promoted triglyceride accumulation by stimulating de novo fatty acid synthesis, mediated through regulating the expression of key metabolic genes (ACC, CPT1α, and PGC1α). Higher circulating ADGV was independently associated with prevalent and incident hypertriglyceridemia across a cross-sectional cohort and an independent prospective cohort, and hepatocyte experiments support a contributory role of ADGV in hepatic lipogenesis.

BackgroundDynamic metabolic changes may influence outcomes after acute brain injury (ABI), but most ICU studies use only a single triglyceride–glucose (TyG) value. We examined whether ICU TyG trajectories and a cumulative TyG burden provide time-sensitive prognostic information and can be embedded in an interpretable mortality model.MethodsAdults with ABI from three ICU databases (NSICU, MIMIC-IV, eICU) were retrospectively analyzed. TyG trajectories were derived from serial ICU measurements, cumulative exposure was summarized as prespecified threshold-based mean area under the curve (TBM), and in-hospital mortality was evaluated with 7-day time-stratified Cox models. A machine-learning model including TyG trajectory, TBM, and routinely available clinical variables was trained in NSICU and validated in the pooled external cohort.ResultsAmong 4,760 admissions, three trajectories were identified—low–slightly increasing (LSI), moderate–increasing (MI), and persistently high (PH). Mortality did not differ across trajectories during days 0–7, but after day 7 both MI (HR 1.48, 95% CI 1.18–1.86; P < 0.001) and PH (HR 1.51, 95% CI 1.17–1.93; P = 0.001) showed higher in-hospital mortality than LSI. TBM showed a parallel positive association; TBM8p7 remained significant in fully adjusted models (HR 1.42, 95% CI 1.18–1.70; P < 0.001). ExtraTrees was selected for its consistent internal and external validation performance, and model interpretability analyses placed TyG trajectory and TBM8p7 among the next most important predictors alongside SOFA score and vasopressor use.ConclusionIn ICU-treated ABI, TyG is better modeled as a time-aware exposure: trajectory differences become prognostically relevant only after the first week, whereas cumulative TBM8p7 shows a graded, independent association with mortality. Both metrics add risk information beyond conventional severity indicators and can be integrated into an interpretable, externally tested model.

We aimed to construct and validate a radiomics prediction model based on preoperative T2-weighted MRI for prognosis and chemosensitivity prediction in patients with glioma. A total of 576 glioma patients were enrolled in this study. The training and validation group included 324 patients and 127 patients respectively with preoperative MRI image data, tumor transcriptome sequencing data and clinical information. The prospective validation group consisted of 125 patients with preoperative MRI image data and clinical information. The radiomics prediction model was constructed based on the prognostic relevant radiomic features of glioma patients in the training group. The radiomics prediction model was validated inpatients of retrospective and prospective validation groups. Functional annotation of radiomic features was performed by pearson correlation analysis of biological process scores and radiomic features values of patients in the training group and validated by transcriptome sequencing, single cell sequencing, reactive oxygen species detection and endoplasmic reticulum stress detection of tumors of patients in retrospective and prospective validation groups. The radiomics prediction model, which consisted of 17 radiomic features, showed highly predictive stability in overall survival and progression-free survival prediction. Compared with patients who underwent postoperative radiotherapy alone, only patients in the high-risk group benefited from postoperative chemoradiotherapy. The prognostic relevant radiomic features were closely related to immune response, reactive oxygen species metabolism and endoplasmic reticulum stress of glioma cells in silico and in vitro. The radiomics prediction model serves as a non-invasive tool to predict prognosis and temozolomide chemosensitivity of glioma patients based on preoperative T2-weighted MRI.

TLN1, a cytoskeletal protein associated with various tumors, remains inadequately studied in gliomas. In this study, we examined the functional role and mechanisms of TLN1 in glioma pathogenesis. Utilizing public databases, we conducted differential expression, survival (Kaplan-Meier/ROC), and regression analyses, which were subsequently validated with institutional datasets and clinical tissues. In vitro experiments demonstrated that TLN1 knockdown in glioma cells resulted in reduced proliferation (CCK8/EDU), migration and invasion (wound healing/Transwell), and increased apoptosis (AO/EB/flow cytometry); these findings were corroborated by Western blot analyses. Gene Set Enrichment Analysis (GSEA) linked TLN1 to the TGF-beta signaling pathway, a connection further validated by Western blot and in vivo murine models. Both public and institutional data indicated that TLN1 was upregulated in gliomas, with elevated expression correlating with poor prognosis. Furthermore, TLN1 knockdown inhibited glioma growth and progression in vitro and in vivo, primarily through the TGF-beta signaling pathway. Our findings establish TLN1 as an oncogenic driver in gliomas and highlight its potential as a therapeutic target.