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Molecular biomarkers that predict disease progression might promote drug development and therapeutic strategies in aggressive cancers, such as gastric cancer (GC). High-throughput mRNA sequencing (RNA-seq) revealed that collagen type X alpha 1 (COL10A1) is a disease progression-associated gene. Analysis of 103 GC patients showed that high COL10A1 mRNA expression was associated with GC metastasis and reduced survival. We analyzed the COL10A1 promoter using the UCSC genome website and JASPAR database, and we found potential SOX9 binding site. Here, we demonstrated that SOX9 and COL10A1 were both up-regulated in GC. We observed a positive correlation between the expression patterns of SOX9 and COL10A1 in GC cells and tissues. The results of electrophoretic mobility shift assay (EMSA), chromatin immunoprecipitation (ChIP) assay and promoter reporter indicated that SOX9 could directly bind to the COL10A1 gene promoter and activate its transcription. Biological function experiments showed that COL10A1 regulated the migration and invasion of GC cells. Knockdown COL10A1 inhibited lung and abdominal cavity metastasis in a nude mouse model. Moreover, transforming growth factor-β1 (TGF-β1) treatment up-regulated the phosphorylation of Smad2 and increased SOX9 and COL10A1 expression. COL10A1 was confirmed to be a potential inducer of epithelial-to-mesenchymal transition (EMT). SOX9 was essential for COL10A1-mediated EMT, and cell migration, invasion and metastasis. Co-expression of SOX9 and COL10A1 was associated with tumor progression and was strongly predictive of overall survival in GC patients. In summary, this study elucidated the mechanistic link between COL10A1 and the TGF-β1-SOX9 axis. These findings indicated that COL10A1 might play a crucial role in GC progression and serve as a potential biomarker and therapeutic target in GC patients.

Type 2 diabetes affects the central nervous system, yet the role of glymphatic dysfunction remains unclear. This study investigated alterations in the DTI-ALPS index in T2DM patients and its associations with cognitive function, white matter integrity, and hippocampal morphology. 74 T2DM patients and 32 healthy controls underwent brain T1-weighted and diffusion tensor imaging. The DTI-ALPS index, white matter microstructure, and hippocampal subregion volumes were quantified. Correlation and mediation analyses assessed relationships between the DTI-ALPS index and cognitive assessments, clinical indicators, white matter microstructures, and hippocampus subregions. T2DM patients exhibited reduced DTI-ALPS index and fractional anisotropy, increased axial diffusivity, and decreased global network efficiency. Furthermore, both betweenness centrality and degree centrality in the right superior frontal gyrus were significantly reduced. Hippocampal subfield volumes were significantly reduced. The DTI-ALPS index correlated positively with HDL and MMSE scores, but negatively with fasting blood glucose (FBG). Mediation analysis showed that the DTI-ALPS index partially mediated the relationship between fasting glucose and cognition. T2DM is linked to glymphatic dysfunction, white matter damage, and hippocampal atrophy, contributing to cognitive decline. The DTI-ALPS index may serve as a sensitive biomarker for early glymphatic impairment, emphasizing the role of metabolic clearance dysfunction in diabetes-related cognitive deterioration. Trial registration Chinese Clinical Trial Registry (ChiCTR1900024109) on June 26, 2019.

Peritoneal metastasis predicts poor prognosis of gastric cancer (GC) patients, and the underlying mechanisms are poorly understood. The 2-DIGE, MALDI-TOF/TOF MS and single-cell transcriptome were used to detect differentially expressed proteins among normal gastric mucosa, primary GC and peritoneal metastatic tissues. Lentiviruses carrying shRNA and transcription activator-like effector nuclease technology were used to knock down myosin heavy chain 9 (MYH9) expression in GC cell lines. Immunofluorescence, immune transmission electron microscopy, chromatin fractionation, co-immunoprecipitation, and assays for chromatin immunoprecipitation, dual luciferase reporter, agarose-oligonucleotide pull-down, flow cytometry and cell anoikis were performed to uncover nuclear MYH9-induced β-catenin ( ) transcription . Nude mice and conditional transgenic mice were used to investigate the findings . We observed that MYH9 was upregulated in metastatic GC tissues and was associated with a poor prognosis of GC patients. Mechanistically, we confirmed that MYH9 was mainly localized in the GC cell nuclei by four potential nuclear localization signals. Nuclear MYH9 bound to the promoter through its DNA-binding domain, and interacted with myosin light chain 9, β-actin and RNA polymerase II to promote transcription, which conferred resistance to anoikis in GC cells and . Staurosporine reduced nuclear MYH9 S1943 phosphorylation to inhibit transcription, Wnt/β-catenin signaling activation and GC progression in both orthotropic xenograft GC nude mouse and transgenic GC mouse models. This study identified that nuclear MYH9-induced CTNNB1 expression promotes GC metastasis, which could be inhibited by staurosporine, indicating a novel therapy for GC peritoneal metastasis.

Objective Lung cancer remains the leading cause of cancer-related deaths worldwide, and lymphovascular invasion (LVI) is an important pathological indicator affecting the prognosis of lung cancer patients. Traditional imaging techniques face challenges in effectively and accurately predicting vascular invasion, but integrating clinical indicators with radiomics features is expected to improve the non-invasive preoperative prediction of LVI, providing valuable reference for clinical treatment decisions. This study aimed to investigate the clinical value of predicting LVI in patients with invasive lung adenocarcinoma (LUAD) based on the intratumoral and peritumoral CT radiomics models. Patients and methods The 384 patients with invasive LUAD from Institution 1 were randomly divided into training ( n  = 268) and internal validation ( n  = 116) sets with a ratio of 7:3, and 251 patients from Institution 2 were used as the external validation set. Altogether, 1226 features were extracted from the tumor gross (GT), gross tumor and peritumor (GPT), and peritumor(PT), respectively. Clinical independent predictors for LVI in patients with invasive LUAD were screened using univariate and multivariate logistic regression analysis, a combined model that included clinical predictors and optimal Radscore was constructed, and a nomogram was drawn. All cases were diagnosed using histopathological examination results as the gold standard. Results The GPT model showed better predictive efficacy than the GT and PT models, with the area under the curve (AUC) of 0.83, 0.79, and 0.75 in the training, internal validation, and external validation sets, respectively. In the clinical model, the preoperative carcinoembryonic antigen (CEA) level, tumor diameter, and spiculation were the independent predictors. The combined model containing the independent predictors and the GPT-Radscore significantly predicted LVI in patients with invasive LUAD, with AUCs of 0.84, 0.82, and 0.77 in the three cohorts, respectively. Conclusion The CT scan-based radiomics model which including intratumoral and peritumoral radiomics features could effectively predict LVI in LUAD patients, and the predictive efficacy were further improved by combining clinically independent predictors. This study holded significant clinical importance, as it provided a non-invasive biomarker for the preoperative prediction of LVI status in lung cancer patients, thereby identifying subgroups with poor prognosis. It demonstrated great potential for risk stratification and guiding personalized treatment strategies in clinical practice.

Reactive thiols of proteinaceous cysteines are vital to cell biology by serving as sensor, effector and buffer of environmental redox fluctuations. Being the major source, as well as the prime target, of reactive oxygen species (ROS), mitochondria confront great challenges in preserving their thiol pool. Here we show that ROS modulator 1 (ROMO1), a small inner mitochondrial membrane protein, plays a role in protecting the mitochondrial cysteinome. ROMO1 is redox sensitive and reactive and overexpression can prevent deleterious oxidation of proteinaceous thiols. ROMO1 upregulation leads to a reductive shift of the mitochondrial cysteinome, exerting beneficial effects on mitochondria, such as promoting energy metabolism and Ca 2+ uniport while inhibiting vicious membrane permeability transition. Importantly, ROMO1 overexpression reverses mitochondrial cysteinome oxidations in multiple organs and slows functional decline in aged male mice. These findings unravel a redox regulatory mechanism of the mitochondrial cysteinome and mark ROMO1 as a potential target for combating oxidative stress and improving healthspan. As a major source of reactive oxygen species, mitochondria face a challenge to maintain their redox state. Here the authors show that ROMO1 overexpression prevents deleterious oxidation of the mitochondrial cysteinome and exerts beneficial effects on mitochondrial function.

Backgroud Lymphovascular invasion (LVI) was histological factor that was closely related to prognosis of lung adenocarcinoma (LAC).The primary aim was to investigate the value of a nomogram incorporating clinical and computed tomography (CT) factors to predict LVI in LAC, and validating the predictive efficacy of a clinical model for LVI in patients with lung adenocarcinoma with lesions ≤ 3 cm. Methods A total of 450 patients with LAC were retrospectively enrolled. Clinical data and CT features were analyzed to identify independent predictors of LVI. A nomogram incorporating the independent predictors of LVI was built. The performance of the nomogram was evaluated by assessing its discriminative ability and clinical utility.We took 321 patients with tumours ≤ 3 cm in diameter to continue constructing the clinical prediction model, which was labelled subgroup clinical model. Results Carcinoembryonic antigen (CEA) level, maximum tumor diameter, spiculation, and vacuole sign were independent predictors of LVI. The LVI prediction nomogram showed good discrimination in the training set [area under the curve (AUC), 0.800] and the test set (AUC, 0.790), the subgroup clinical model also owned the stable predictive efficacy for preoperative prediction of LVI in lung adenocarcinoma patients, and both training and test set AUC reached 0.740. Conclusions The nomogram developed in this study could predict the risk of LVI in LAC patients, facilitate individualized risk-stratification, and help inform treatment decision-makin, and the subgroup clinical model also had good predictive performance for lung cancer patients with lesion ≤ 3 cm in diameter.

Real-time monitoring of the laser paint removal process is critical to realize a good cleaning effect without causing damages to the base. Acoustic signals when the laser pulse continuously acts at one point were studied through an experiment. Results show that peak values and maximum frequency component of acoustic signals decreased to a stable value with paint removal, reflecting the cleaning process. According to an experimental study on cleaning acoustic signals during laser scanning, the cleaning process is divided into paint removal, clean finished, and excessive cleaning according to the damages threshold. The acoustic signals of the different processes were analyzed. Results show that variations of frequency components could reflect the paint removal process more accurately than time-domain signals. Extracting characteristic parameters of the maximum frequency component, spectrum, spectrum centroid amplitude, and spectrum centroid frequency from the frequency domain; introducing in the discriminant analysis; and establishing a Bayesian discriminant model according to cleaning characteristics can realize the quantitative discrimination of the paint removal process.

In response to the insufficient detection capability of laser paint stripping effects for a single modality and the high operational and cost requirements of existing multi-monitoring technologies, a method is proposed to integrate visual and auditory signals for evaluating laser paint stripping effects. Utilizing wavelet packet transformation for a more detailed understanding of the variations in paint-stripping sound signals, more representative energy features are extracted. The EfficientNetv2 network, optimized with an attention mechanism, further enhances the focus on crucial features. The image feature vectors are concatenated with the energy features extracted from the sound signals, forming a new and more informative feature vector for paint stripping effect discrimination. Experimental results demonstrate that the multi-feature fusion detection algorithm significantly improves the accuracy of paint stripping effect discrimination, reaching 98.7%. The 98.9% F1-Score and the smoothly converging loss curve also indicate the algorithm's effective control over category imbalance and training stability. This research is of paramount importance for improving the evaluation of laser cleaning technology effects and provides insights into multi-modal feature fusion for other relevant fields of study.

The rising incidence of clear cell renal cell carcinoma (ccRCC) with current treatments offering limited survival benefits and a poor prognosis. Mitochondrial abnormalities impact tumor immunity, progression, and metastasis, and the role of mitochondrial energy metabolism-related genes (MMRGs) in ccRCC remains largely unexplored. This study analyzed TCGA-KIRC, GSE159115, and GSE29609 datasets to identify differentially expressed (DE) MMRGs and their functions. It used LASSO and Cox models to select prognostic MMRGs for model building, created a nomogram (based on independent factors) in TCGA-KIRC (evaluated via calibration and ROC curves), and conducted GSEA, immune cell correlation analyses, TF-miRNA-mRNA network studies, qRT-PCR (ccRCC vs. controls), and WB (RIPA) for biomarker validation. A study of 103 DE-MMRGs highlighted their link to fatty acid metabolism and peroxisome proliferator-activated receptor (PPAR) signaling. Machine learning assessed the prognostic potential of these DE-MMRGs, which yielded a risk model based on six key biomarkers. The constructed prognostic model exhibited outstanding performance in both training and validation sets. This study also explored immune cell relevance and regulatory networks and elucidated complex mitochondrial-tumor interactions. The validation of predictive biomarker expression in clinical samples underscored their role in refining prognostic assessment and therapeutic strategies for ccRCC. In this study, six mitochondrial energy metabolism-related prognosis biomarkers ( COX7B, PPARGC1B, NDUFA11, PFKFB4, NDUFV2, and NDUFA7 ) were screened. A risk model was developed to provide a new reference for the prognosis of ccRCC patients.

Background The combination of PD-1/PD-L1 monoclonal antibodies and chemotherapy has established a new standard of care for the first-line treatment of patients with unresectable locally advanced or metastatic gastric cancer (GC) and gastro-oesophageal junction adenocarcinoma. However, peritoneal metastasis represents a distinct pattern of dissemination in GC, typically associated with a poor prognosis. Whether the combination regimen improves survival for patients with concomitant peritoneal metastasis remains controversial. This study aims to evaluate the efficacy and safety of toripalimab (an anti-PD-1 monoclonal antibody) combined with FLOT chemotherapy as conversion therapy in these patients. Methods In this single-arm, open-label, phase II trial conducted in China, we enrolled patients aged 18–80 years with laparoscopically proven gastric cancer and peritoneal metastasis. Patients received toripalimab (3 mg/kg) plus FLOT chemotherapy (docetaxel 50 mg/m 2 ; oxaliplatin 85 mg/m 2 ; leucovorin 200 mg/m 2 , 5-FU 2600 mg/m 2 ) every 14 days for up to 4 cycles, followed by surgical resection. Patients who underwent surgery subsequently received 4 cycles of adjuvant treatment. The primary endpoint was the R0 resection conversion rate. The secondary endpoints included progression-free survival (PFS), overall survival (OS) and safety. Results Between April 2021 and April 2023, 24 patients were screened, 20 of whom were included in this analysis. The median follow-up was 10.8 months. The objective response rate (ORR) was 35% and the disease control rate (DCR) was 80%. The R0 resection conversion rate after treatment was 25% (5/20), 40% (2/5) participants achieved TRG1 and 60% (3/5) participants achieved TRG2. The median PFS and OS were 6.5 and 10.8 months, respectively. Grade 3–4 treatment-related adverse events (TRAEs) occurred in 35% of participants. Conclusions Toripalimab combined with FLOT chemotherapy demonstrated potential conversion efficacy in the treatment of gastric cancer with peritoneal metastasis. Clinical trial information ClinicalTrials.gov (NCT04886193). Date of registration: 13 May 2021.