Comprehensive hepatotoxicity prediction: ensemble model integrating machine learning and deep learning.

Background: Chemicals may lead to acute liver injuries, posing a serious threat to human health. Achieving the precise safety profile of a compound is challenging due to the complex and expensive testing procedures. In silico approaches will aid in identifying the potential risk of drug candidates in the initial stage of drug development and thus mitigating the developmental cost. Methods: In current studies, QSAR models were developed for hepatotoxicity predictions using the ensemble strategy to integrate machine learning (ML) and deep learning (DL) algorithms using various molecular features. A large dataset of 2588 chemicals and drugs was randomly divided into training (80%) and test (20%) sets, followed by the training of individual base models using diverse machine learning or deep learning based on three different kinds of descriptors and fingerprints. Feature selection approaches were employed to proceed with model optimizations based on the model performance. Hybrid ensemble approaches were further utilized to determine the method with the best performance. Results: The voting ensemble classifier emerged as the optimal model, achieving an excellent prediction accuracy of 80.26%, AUC of 82.84%, and recall of over 93% followed by bagging and stacking ensemble classifiers method. The model was further verified by an external test set, internal 10-fold cross-validation, and rigorous benchmark training, exhibiting much better reliability than the published models. Conclusion: The proposed ensemble model offers a dependable assessment with a good performance for the prediction regarding the risk of chemicals and drugs to induce liver damage.

Facile access to S-aryl/alkyl dithiocarbamates via a three-component reaction under metal-free conditions.

The development of facile and convenient atom-economical methods for the preparation of organosulfur compounds from CS2 is a challenging endeavor. Herein, a one-pot, environmentally friendly method to access S-aryl/alkyl dithiocarbamates has been demonstrated by a three-component coupling involving aryl/alkyl thiols, CS2 and amines in the presence of a common base K2CO3. The transformation process can proceed in an H2O-DMAc (3 : 1) mixed solvent without requiring any catalysts or extensive prefunctionalization of reactants. The protocol is operationally simple and affords dithiocarbamates with various moieties (including aryl, aliphatic, heteroaryl and alkenyl) in good yields.

Moxibustion with seed-size moxa cones alleviates colonic injury in mice with ulcerative colitis by regulating TLR4/MyD88/NF-κB signaling pathway. / 麦粒灸调控TLR4/MyD88/NF-κBä¿¡å·é€šè·¯å‡è½»æºƒç–¡æ€§ç»“è‚ ç‚Žå°é¼ ç»“è‚ æŸä¼¤çš„æœºåˆ¶ç ”ç©¶.

OBJECTIVES: To observe the effect of moxibustion with seed-size moxa cones on the Toll-like receptor 4(TLR4)/myeloid differentiation factor 88(MyD88)/nuclear transcription factor-κB(NF-κB) signaling pathway in mice with ulcerative colitis(UC), so as to explore the therapeutic mechanism of moxibustion with seed-size moxa cones on colonic injury in UC. METHODS: Forty male C57BL/6 mice were randomly divided into blank group, model group, moxibustion group, and western medicine group, with 10 mice in each group. The UC mouse model was established by 3% DSS solution by free drinking for 7 consecutive days. Mice in the moxibustion group were treated with seed-size moxa cones at "Zhongwan"(CV12), "Tianshu"(ST25) and "Shangjuxu"(ST37), 3 moxa cones per point, with each cone applied for approximately 30 s, while mice in the western medicine group were orally administered with 300 mg/kg mesalazine solution, which were both conducted once a day for 7 consecutive days. The general condition of mice was observed every 2 days, and the disease activity index (DAI) score was calculated. HE staining was used to observe the morphology of colonic tissue in mice. ELISA was used to detect the serum interleukin(IL)-1ß, tumor necrosis factor(TNF)-α, IL-6, and IL-8 contents. Immunohistochemistry was used to detect the positive expression of TLR4 and MyD88 in colonic tissue of mice. Real-time fluorescence quantitative PCR was used to detect the expression levels of TLR4, MyD88, and NF-κB p65 mRNAs in colonic tissue. RESULTS: Compared with the blank group, varying degrees of soft or watery stools were observed, colon length and body weight were decreased(P<0.01) in mice of the model group, while DAI score, colon weight index, mucosal damage score, colonic pathological score, serum IL-1ß, TNF-α, IL-6, and IL-8 contents, positive expressions of TLR4 and MyD88, and TLR4, MyD88, and NF-κB p65 mRNA expressions in colonic tissue were increased(P<0.01). Compared with the model group, improved fecal characteristics were observed, colon length and body weight were increased(P<0.01) in mice of the moxibustion group and western medicine group, while DAI scores, colon weight indexes, mucosal damage scores, colonic pathological score, serum contents of IL-1ß, TNF-α, IL-6, and IL-8, positive expressions of TLR4 and MyD88, and TLR4, MyD88, and NF-κB p65 mRNA expressions in colonic tissue were decreased(P<0.01, P<0.05). There was no significant difference in the above indicators between the moxibustion group and the western medicine group. CONCLUSIONS: Moxibustion with seed-size moxa cones may alleviate colonic injury in UC mice by regulating the TLR4/MyD88/NF-κB signaling pathway and reducing the release of inflammatory factors.

Applying Deep Learning with Convolutional Neural Networks to Laryngoscopic Imaging for Automated Segmentation and Classification of Vocal Cord Leukoplakia.

Objectives: Vocal cord leukoplakia is clinically described as a white plaque or patch on the vocal cords observed during macroscopic examination, which does not take into account histological features or prognosis. A clinical challenge in managing vocal cord leukoplakia is to assess the potential malignant transformation of the lesion. This study aims to investigate the potential of deep learning (DL) for the simultaneous segmentation and classification of vocal cord leukoplakia using narrow band imaging (NBI) and white light imaging (WLI). The primary objective is to assess the model's accuracy in detecting and classifying lesions, comparing its performance in WLI and NBI. Methods: We applied DL to segment and classify NBI and WLI of vocal cord leukoplakia, and used pathological diagnosis as the gold standard. Results: The DL model autonomously detected lesions with an average intersection-over-union (IoU) >70%. In classification tasks, the model differentiated between lesions in the surgical group with a sensitivity of 93% and a specificity of 94% for WLI, and a sensitivity of 99% and a specificity of 97% for NBI. In addition, the model achieved a mean average precision of 81% in WLI and 92% in NBI, with an IoU threshold >0.5. Conclusions: The model proposed by us is helpful in assisting in accurate diagnosis of vocal cord leukoplakia from NBI and WLI.

A model based on C-TIRADS combined with SWE for predicting Bethesda I thyroid nodules.

Objectives: This study aimed to explore the performance of a model based on Chinese Thyroid Imaging Reporting and Data Systems (C-TIRADS), clinical characteristics, and shear wave elastography (SWE) for the prediction of Bethesda I thyroid nodules before fine needle aspiration (FNA). Materials and methods: A total of 267 thyroid nodules from 267 patients were enrolled. Ultrasound and SWE were performed for all nodules before FNA. The nodules were scored according to the 2020 C-TIRADS, and the ultrasound and SWE characteristics of Bethesda I and non-I thyroid nodules were compared. The independent predictors were determined by univariate analysis and multivariate logistic regression analysis. A predictive model was established based on independent predictors, and the sensitivity, specificity, and area under the curve (AUC) of the independent predictors were compared with that of the model. Results: Our study found that the maximum diameter of nodules that ranged from 15 to 20 mm, the C-TIRADS category <4C, and E max <52.5 kPa were independent predictors for Bethesda I thyroid nodules. Based on multiple logistic regression, a predictive model was established: Logit (p) = -3.491 + 1.630 × maximum diameter + 1.719 × C-TIRADS category + 1.046 × E max (kPa). The AUC of the model was 0.769 (95% CI: 0.700-0.838), which was significantly higher than that of the independent predictors alone. Conclusion: We developed a predictive model for predicting Bethesda I thyroid nodules. It might be beneficial to the clinical optimization of FNA strategy in advance and to improve the accurate diagnostic rate of the first FNA, reducing repeated FNA.

Transcriptome and proteomic analysis reveal the protective mechanism of acupuncture on reproductive function in mice with asthenospermia.

Acupuncture is an integral component of complementary and alternative medicine that has been reported to enhance sperm motility, improve semen quality, and consequently augment male fertility. However, the precise mechanisms of action and the underlying molecular pathways remain unclear. In the present study, we aimed to elucidate the potential mechanisms through which acupuncture improves reproductive function in a mouse model of cyclophosphamide-induced asthenozoospermia. We collected sperm from the epididymis for semen analysis, collected serum to determine gonadotropin and oxidative stress marker levels, conducted histological examination of testicular tissue using hematoxylin and eosin (HE) and terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) staining, and observed mitochondrial morphology using transmission electron microscopy (TEM). We also assessed oxidative stress levels and total iron content in testicular tissue and validated the proteomic and transcriptomic analysis results of testicular tissue using real-time reverse transcription-quantitative polymerase chain reaction (RT-qPCR), protein imprinting analysis, and immunohistochemistry (IHC). Our results indicate that acupuncture enhances sperm quality in asthenozoospermic mice; increases serum testosterone (T), follicle-stimulating hormone (FSH), and luteinizing hormone (LH) levels; and attenuates oxidative damage, iron accumulation, and mitochondrial injury in mouse testicular tissues. Through protein and transcriptomic analyses, we identified 21 key genes, of which cytochrome b-245 heavy chain (CYBB), glutathione peroxidase 4 (GPX4), acyl-CoA synthetase long-chain family member 1 (ACSL1), and ferritin mitochondria (FTMT) were closely associated with ferroptosis. RT-qPCR, protein imprinting, and immunofluorescence (IF) analyses collectively indicated that acupuncture reduced ACSL1 and CYBB expression, and increased GPX4 and FTMT expression. Overall, the ferroptosis pathway associated with ACSL1/CYBB/FTMT/GPX4 represents a potential strategy through which acupuncture can improve the reproductive function in asthenozoospermic mice.

FGTN: Fragment-based graph transformer network for predicting reproductive toxicity.

Reproductive toxicity is one of the important issues in chemical safety. Traditional laboratory testing methods are costly and time-consuming with raised ethical issues. Only a few in silico models have been reported to predict human reproductive toxicity, but none of them make full use of the topological information of compounds. In addition, most existing atom-based graph neural network methods focus on attributing model predictions to individual nodes or edges rather than chemically meaningful fragments or substructures. In current studies, we develop a novel fragment-based graph transformer network (FGTN) approach to generate the QSAR model of human reproductive toxicity by considering internal topological structure information of compounds. In the FGTN model, the compound is represented by a graph architecture using fragments to be nodes and bonds linking two fragments to be edges. A super molecule-level node is further proposed to connect all fragment nodes by undirected edges, obtaining global molecular features from fragment embeddings. The FGTN model achieved an accuracy (ACC) of 0.861 and an area under the receiver operating characteristic curve (AUC) value of 0.914 on nonredundant blind tests, outperforming traditional fingerprint-based machine learning models and atom-based GCN model. The FGTN model can attribute toxic predictions to fragments, generating specific structural alerts for the positive compound. Moreover, FGTN may also have the capability to distinguish various chemical isomers. We believe that FGTN can be used as a reliable and effective tool for human reproductive toxicity prediction in contribution to the advancement of chemical safety assessment.

Cost-Effectiveness of Varicella Vaccination for 1-4-Year-Olds in Shanghai, China.

INTRODUCTION: Varicella has not yet been included in the National Immunization Program (NIP) in China, and varicella vaccination strategies vary by region. To determine the optimal varicella vaccination strategy in Shanghai, China, the cost-effectiveness and 5-year costs of 5 immunization scenarios were analyzed. METHODS: A static decision tree-Markov model was developed in 2022 to assess the cost-effectiveness and 5-year costs of voluntary and routine varicella vaccination programs in the 2019 birth cohort in Shanghai from a societal perspective. Parameters were collected in 2022 from the varicella surveillance system, a questionnaire survey of 414 guardians of patients with childhood varicella, and semi-structured interviews with 20 experts on varicella outbreaks from different institutions in Shanghai. The outcomes included varicella cases avoided, quality-adjusted life year (QALY) loss, and incremental costs per QALY (ICER). The 5-year costs were compared with local medical expenditures. RESULTS: Among the 5 scenarios, one dose of routine varicella vaccination was the most cost-saving (USD 70.2) and cost-effective (Dominant) with a 5-year immunization expenditure of USD 9.9 million. Two doses of routine varicella vaccination had the highest QALY (29.9), and its ICER (USD 791.9/QALY) was below the willingness-to-pay threshold (USD 5,203-23,767/QALY). The 5-year immunization expenditure was USD 19.8 million. The effectiveness and price of vaccines, vaccination coverage, and per capita income are the 4 main factors that affect ICERs. CONCLUSIONS: In Shanghai, the 2 doses of routine varicella vaccination strategy for 1- and 4-year-olds with a 95% coverage rate was found to be the optimal varicella immunization strategy.

[Effects of Meteorological Conditions in Summer and Early Autumn on PM2.5 and O3 Pollution in Beijing-Tianjin-Hebei and Surrounding Areas].

PM2.5 pollution remains prominent in autumn, whereas O3 pollution gradually manifests in summer. To understand the dual high characteristics and meteorological effects of PM2.5 and O3 in the summer and early autumn of 2021 in the Beijing-Tianjin-Hebei and surrounding areas, the spatiotemporal distribution characteristics of PM2.5 and O3 concentrations, as well as meteorological conditions, subtropical high index, and weather situation in the Beijing-Tianjin-Hebei and surrounding areas were analyzed. The results showed that PM2.5 concentration and DPO3 （O3 daily maximum 8h mean minus O3 concentration at 06：00） from June to September 2021 decreased compared with those in the same period in 2020 and 2022, and high concentrations were mainly occurring in June. The overall PM2.5 concentration and DPO3 showed a gradual decrease from the middle to the north and south, with synchronous spatiotemporal changes. The hourly value of PM2.5 concentration presented a multimodal distribution, reaching the peak at 07：00-10：00 and 22：00-24：00. O3 concentration showed an opposite trend of change with PM2.5 concentration, reaching their peak from 14：00-16：00. When DPO3 and the concentration of PM2.5 were high, the characteristics of near-surface meteorological elements were characterized by temperatures ranging from 24.0-28.0℃, relative humidity concentrated at 58.4%-76.3%, and wind speeds ranging from 1.5-3 m·s-1. There was a high lag correlation between the subtropical high index and DPO3. When the subtropical high was farther and stronger from the Beijing-Tianjin-Hebei and surrounding areas, DPO3 was higher. The major weather patterns with both high PM2.5 and O3 concentrations in the study area were near surface low-pressure front, high-pressure type, and frontal type. The high altitude was controlled by high-pressure ridges, and the subtropical high ridge line was stable between 21°-28°N.

MRI-based machine learning radiomics for prediction of HER2 expression status in breast invasive ductal carcinoma.

Background: Human epidermal growth factor receptor 2 (HER2) is a tumor biomarker with significant prognostic and therapeutic implications for invasive ductal breast carcinoma (IDC). Objective: This study aimed to explore the effectiveness of a multisequence magnetic resonance imaging (MRI)-based machine learning radiomics model in classifying the expression status of HER2, including HER2-positive, HER2-low, and HER2 completely negative (HER2-zero), among patients with IDC. Methods: A total of 402 female patients with IDC confirmed through surgical pathology were enrolled and subsequently divided into a training group (n = 250, center I) and a validation group (n = 152, center II). Radiomics features were extracted from the preoperative MRI. A simulated annealing algorithm was used for key feature selection. Two classification tasks were performed: task 1, the classification of HER2-positive vs. HER2-negative (HER2-low and HER2-zero), and task 2, the classification of HER2-low vs. HER2-zero. Logistic regression, random forest (RF), and support vector machine were conducted to establish radiomics models. The performance of the models was evaluated using the area under the curve (AUC) of the operating characteristics (ROC). Results: In total, 4506 radiomics features were extracted from multisequence MRI. A radiomics model for prediction of expression state of HER2 was successfully developed. Among the three classification algorithms, RF achieved the highest performance in classifying HER2-positive from HER2-negative and HER2-low from HER2-zero, with AUC values of 0.777 and 0.731, respectively. Conclusions: Machine learning-based MRI radiomics may aid in the non-invasive prediction of the different expression status of HER2 in IDC.

The safety and efficacy of indobufen or aspirin combined with clopidogrel in patients with acute myocardial infarction after percutaneous coronary intervention.

Currently, the standard treatment for patients who have undergone percutaneous coronary intervention (PCI) following acute myocardial infarction (MI) involves dual antiplatelet therapy (DAPT) with a combination of aspirin and a potent P2Y12 receptor inhibitor. However, the potential benefits of aspirin were partially constrained by the intolerance of some patients. The safety and efficacy of indobufen, an alternative antiplatelet agents to aspirin, in patients with AMI after PCI are yet to be thoroughly investigated.This retrospective study was conducted at a single center and utilized propensity score matching. The enrollment spanned from January 2019 to June 2022, incorporating patients with AMI after PCI. The participants were categorized into two groups based on discharged prescriptions: the aspirin DAPT group and the indobufen DAPT group. The primary endpoint focused on net adverse clinical event (NACE), defined as a composite outcome, including cardiac death, recurrence of MI, definite or probable stent thrombosis (ST), target lesion revascularization (TLR), ischemic stroke and Bleeding Academic Research Consortium (BARC) criteria type 2, 3, or 5. All the patients underwent a one-year follow-up period.A total of 1451 patients were enrolled in this study, with 258 assigned to the indobufen DAPT group and 1193 to the aspirin DAPT group. Following 1:1 propensity score matching, 224 patients were retained in each group. In the indobufen DAPT group, 58 individuals (25.9%) experienced the primary endpoint within one year, compared to 52 individuals (23.2%) in the aspirin DAPT group (HR 1.128, 95% CI 0.776-1.639, p = .527). Specifically, no significant differences were observed in either the efficacy endpoint (MACCE, 20.1% vs. 14.7%, HR 1.392, 95% CI 0.893-2.170, p = .146) or the safety endpoint (BARC 2,3 or 5, 8.04% vs. 10.30%, HR 0.779, p = .427). These findings remained consistent at 1, 3, or 6 months. Additionally, the incidence of gastrointestinal symptoms were significantly lower in indobufen DAPT group compared to the aspirin DAPT group (7.1% vs. 14.3%, p = .022).Our research reveals that the efficacy and safety of indobufen are comparable to aspirin in Chinese patients with AMI following PCI. Given the potential advantages of indobufen in alleviating gastrointestinal symptoms, we propose it as a viable alternative for individuals intolerant to aspirin.

What is the context? Currently, the standard treatment for patients who have undergone percutaneous coronary intervention following acute myocardial infarction involves dual antiplatelet therapy with a combination of aspirin and a potent P2Y12 receptor inhibitor.However, the potential benefits of aspirin were partially constrained by the intolerance of some patients.The safety and efficacy of indobufen, an alternative antiplatelet agents to aspirin, in patients with AMI after PCI are yet to be thoroughly investigated.What is new? While both American and European clinical guidelines recommend the use of indobufen as an alternative treatment for patients who cannot tolerate aspirin, there exists a limited body of research on this subject.Our research is the first to address this gap by comparing the efficacy and safety of indobufen and aspirin in patients with AMI.Our research reveals that the efficacy and safety of indobufen are comparable to aspirin in Chinese patients with AMI following PCI. Given the potential advantages of indobufen in alleviating gastrointestinal symptoms, we propose it as a viable alternative for individuals intolerant to aspirin.What is the impact? These findings might pave the way for further exploration of alternatives to aspirin in patients with AMI.

Beat-to-Beat Blood Pressure Variability Within 24 Hours of Ischemic Stroke Onset: A Potential Predictor of Functional Prognosis.

BACKGROUND: Beat-to-beat blood pressure variability (BPV) is based on each heartbeat and represents a dynamic equilibrium process modulated by artery and cardiac involvement of pressure-receptive reflexes. To date, there remains a lack of prospective studies illustrating the clinical value of beat-to-beat BPV within 24 hours of acute ischemic stroke onset. METHODS AND RESULTS: This study prospectively monitored beat-to-beat blood pressure and heart rate in patients with acute ischemic stroke within 24 hours of onset using a noninvasive plethysmograph and calculated beat-to-beat BPV, heart rate variability, and the cross-correlation baroreflex sensitivity. A modified Rankin Scale score of ≥2 at 90 days was defined as an unfavorable prognosis. Multivariate logistic regression was performed, and the nomogram model was developed by adding the beat-to-beat BPV to the traditional model for predicting prognosis. Beat-to-beat BPV increased significantly in the unfavorable outcome group (P<0.05) compared with that in the favorable outcome group, whereas no difference was observed in beat-to-beat heart rate variability and cross-correlation baroreflex sensitivity between both groups (P>0.05). Furthermore, beat-to-beat BPV within 24 hours of acute ischemic stroke onset was independently associated with unfavorable outcome at 90 days (P<0.005). The addition of beat-to-beat BPV to the traditional model for predicting prognosis enhanced the area under the receiver operating characteristic curve from 0.816 to 0.830. CONCLUSIONS: Increased beat-to-beat BPV within 24 hours of acute ischemic stroke onset was independently associated with a poor prognosis at 90 days and may be a potential predictor for discriminating unfavorable prognosis.

Evaluation of pre-school pertussis booster vaccination in Shanghai, China: A cost-effectiveness analysis.

BACKGROUND: In recent years, notified pertussis cases have been increasingly documented in China. It raised a new public health concern of potential optimization in immunization strategy. This study was aimed to determine the cost-effectiveness of different immunization strategies against pertussis-containing vaccines for 6-year-old pre-school children in Shanghai. METHODS: A Markov-decision tree model was applied to evaluate two pertussis immunization strategies for 6-year-old pre-school children as following: (1) 1 dose of acellular pertussis (aP) contained vaccine (DTaP or Tdap) booster vaccinated at 6 years of age, and (2) no booster at 6 years of age regimen. Primary outcomes included quality-adjusted life years (QALYs), costs, and incremental cost-utility ratios (ICUR). Sensitivity analyses were performed. The analysis was conducted over a study period of 14 years from a societal perspective. RESULTS: Compared to no booster immunization strategy, administering 1 dose of acellular pertussis (aP) contained vaccine (DTaP or Tdap) booster at 6 years of age, resulted in an average cost reduction of CNY 814.16 (USD 116) per individual, an increase in QALYs by 0.00066, and a rise in per capita net monetary benefit (NMB) by CNY 933.51 (USD 132). The total costs over the study period were reduced by CNY 160.59 million (USD 23 million), utility increased by 130.49 QALYs, and NMB increased by CNY 184.14 million (USD 26 million). CONCLUSIONS: Implementing acellular pertussis booster immunization for 6-year-old pre-school children in Shanghai emerges as a cost-saving immunization strategy, with both cost savings and utility gains.

Prevalence, clinical characteristics, and long-term outcomes of new diabetes diagnosis in elderly patients undergoing percutaneous coronary intervention.

Previous studies have reported associations between newly diagnosed diabetes and poor outcomes after percutaneous coronary intervention (PCI), but there is limited data focusing on elderly patients (age ≥ 65). This study aimed to analyze the prevalence and clinical implications of newly diagnosed diabetes in elderly patients who underwent PCI. From 2004 to 2021, a total of 2456 elderly patients who underwent invasive PCI at Korea University Guro Hospital were prospectively enrolled and followed up for a median of five years. The primary endpoint was five-year major adverse cardiovascular events (MACE). Cox regression was used to evaluate whether newly diagnosed diabetes impacted on long-term clinical outcomes. Newly diagnosed diabetes was presented in approximately 8.1% to 10.9% of elderly patients who underwent PCI. Those who had a new diagnosis of diabetes had a higher risk of MACE than previously known diabetes (25.28% vs. 19.15%, p = 0.039). After adjusting for significant factors, newly diagnosed diabetes remained an independent predictor of MACE (HR [hazard ratio] 1.64, 95% confidence interval [CI] 1.24-2.17, p < 0.001), cardiac death (HR 2.15, 95% CI 1.29-3.59, p = 0.003) and repeat revascularization (HR 1.52, 95% CI 1.09-2.11, p = 0.013), but not for non-fatal myocardial infarction (HR 1.66, 95% CI 0.94-2.12, p = 0.081). Newly diagnosed diabetes was associated with an increased risk of 5-year MACE compared with non-diabetes and previously diagnosed diabetes in elderly patients underwent PCI. More attention should be given to those elderly newly diagnosed diabetes population.

PUM2 promoted osteoarthritis progression through PTEN-mediated chondrocyte ferroptosis by facilitating NEDD4 mRNA degradation.

Osteoarthritis (OA) is a prevalent degenerative joint disease with a lack of effective therapeutic. Chondrocyte ferroptosis contributes to the progression of OA. PUM2 is shown to exacerbate ischemia-reperfusion-induced neuroinflammation by promoting ferroptosis, but its role in OA remains unexplored. Here, primary mouse chondrocytes were stimulated with IL-1ß to mimic OA chondrocyte injury in vitro. And PUM2 was upregulated in OA cartilage tissues and IL-1ß-induced chondrocytes. Silencing PUM2 alleviated IL-1ß-induced chondrocyte inflammation and ECM degradation. Mechanistically, PUM2 facilitated the degradation of NEDD4 mRNA by binding to the 3'UTR of NEDD4 mRNA, which in turn inhibited NEDD4 induced PTEN ubiquitination and degradation. Consistently, NEDD4 silencing reversed the ameliorative effect of PUM2 knockdown on chondrocyte injury, and overexpression of PTEN abolished the improved role of NEDD4 in chondrocyte injury. Moreover, PTEN aggravated IL-1ß-induced ferroptosis in chondrocytes through the Nrf2/HO-1 pathway by increasing the levels of Fe2+, ROS, MDA, and ACSL4 protein, decreasing the activity of SOD and the levels of GSH and GPX4 protein, and aggravating mitochondrial damage. Additionally, destabilized medial meniscus (DMM) were conducted to establish the OA mouse model, and adenovirus-mediated PUM2 shRNA was administered intra-articularly. Silencing PUM2 attenuated OA-induced cartilage damage in vivo. In conclusion, PUM2 promoted OA progression through PTEN-mediated chondrocyte ferroptosis by facilitating NEDD4 mRNA degradation.

[Antioxidative effect of wheat-grain moxibustion on cyclophosphamide-induced liver injury in mice based on Nrf2-Keap1 signaling pathway].

OBJECTIVE: To observe the protective effect of wheat-grain moxibustion on cyclophosphamide (CTX)-induced liver injury in mice, and explore its mechanism based on the nuclear factor E2-related factor 2 (Nrf2)-Kelch-like ECH-associated protein 1 (Keap1) signaling pathway. METHODS: Twenty-four male CD-1 (ICR) mice were randomly divided into a blank group, a model group, and a moxibustion group, with 8 mice in each group. The mice in the model group and the moxibustion group were intraperitoneally injected with CTX (80 mg/kg) to induce liver injury. The mice in the moxibustion group were treated with wheat-grain moxibustion at "Guanyuan" (CV 4) and bilateral "Zusanli" (ST 36) and "Sanyinjiao" (SP 6), with each acupoint being treated by 3 cones, approximately 30 seconds per cone, once daily for 7 days. After intervention, the general condition of the mice was observed; the liver mass was measured and the liver index was calculated; HE staining was used to observe the morphology of the liver, and the liver tissue pathological score was assessed; ELISA was used to detect the serum levels of aspartate aminotransferase (AST), alanine aminotransferase (ALT), glutamate dehydrogenase (GLDH) and the levels of malondialdehyde (MDA), superoxide dismutase (SOD), glutathione peroxidase (GSH-Px) in the liver; Western blot and real-time fluorescence quantitative PCR were used to detect the protein and mRNA expression of Nrf2, Keap1, and quinione acceptor oxidoreductase 1 (NQO1) in the liver. RESULTS: Compared with the blank group, the mice in the model group showed sluggishness, unsteady gait, and decreased body weight; liver index was increased (P<0.01); liver cells were loosely arranged, with a small number of cell swollen and exhibiting balloon-like changes; liver tissue pathological score was increased (P<0.05); the serum levels of AST, ALT, GLDH, and level of MDA in the liver were increased (P<0.05), and the levels of SOD and GSH-Px in the liver were decreased (P<0.05); protein and mRNA expression of Nrf2 and NQO1 in the liver was decreased (P<0.01), protein and mRNA expression of Keap1 in the liver was increased (P<0.01). Compared with the model group, the mice in the moxibustion group showed improvement in general condition; liver index was decreased (P<0.01); liver cell structure was relatively intact and clear, and liver tissue pathological score was decreased (P<0.05); the serum levels of AST, ALT, GLDH, and level of MDA in the liver were decreased (P<0.05), and the levels of SOD and GSH-Px in the liver were increased (P<0.05, P<0.01); protein and mRNA expression of Nrf2 and NQO1 in the liver was increased (P<0.05), protein and mRNA expression of Keap1 in the liver was decreased (P<0.05). CONCLUSION: The wheat-grain moxibustion may alleviate CTX-induced liver injury by activating the Nrf2-Keap1 signaling pathway and enhancing the expression of antioxidative enzyme system in the body.

Incidence rate of occult lymph node metastasis in clinical T1-2N0M0 small cell lung cancer patients and radiomic prediction based on contrast-enhanced CT imaging: a multicenter study : Original research.

BACKGROUND: This study aimed to explore the incidence of occult lymph node metastasis (OLM) in clinical T1 - 2N0M0 (cT1 - 2N0M0) small cell lung cancer (SCLC) patients and develop machine learning prediction models using preoperative intratumoral and peritumoral contrast-enhanced CT-based radiomic data. METHODS: By conducting a retrospective analysis involving 242 eligible patients from 4 centeres, we determined the incidence of OLM in cT1 - 2N0M0 SCLC patients. For each lesion, two ROIs were defined using the gross tumour volume (GTV) and peritumoral volume 15 mm around the tumour (PTV). By extracting a comprehensive set of 1595 enhanced CT-based radiomic features individually from the GTV and PTV, five models were constucted and we rigorously evaluated the model performance using various metrics, including the area under the curve (AUC), accuracy, sensitivity, specificity, calibration curve, and decision curve analysis (DCA). For enhanced clinical applicability, we formulated a nomogram that integrates clinical parameters and the rad_score (GTV and PTV). RESULTS: The initial investigation revealed a 33.9% OLM positivity rate in cT1 - 2N0M0 SCLC patients. Our combined model, which incorporates three radiomic features from the GTV and PTV, along with two clinical parameters (smoking status and shape), exhibited robust predictive capabilities. With a peak AUC value of 0.772 in the external validation cohort, the model outperformed the alternative models. The nomogram significantly enhanced diagnostic precision for radiologists and added substantial value to the clinical decision-making process for cT1 - 2N0M0 SCLC patients. CONCLUSIONS: The incidence of OLM in SCLC patients surpassed that in non-small cell lung cancer patients. The combined model demonstrated a notable generalization effect, effectively distinguishing between positive and negative OLMs in a noninvasive manner, thereby guiding individualized clinical decisions for patients with cT1 - 2N0M0 SCLC.

Vaporization of perfluorocarbon attenuates sea-water-drowning-induced acute lung injury by deactivating the NLRP3 inflammasomes in canines.

Seawater-drowning-induced acute lung injury (SD-ALI) is a life-threatening disorder characterized by increased alveolar-capillary permeability, an excessive inflammatory response, and refractory hypoxemia. Perfluorocarbons (PFCs) are biocompatible compounds that are chemically and biologically inert and lack toxicity as oxygen carriers, which could reduce lung injury in vitro and in vivo. The aim of our study was to explore whether the vaporization of PFCs could reduce the severity of SD-ALI in canines and investigate the underlying mechanisms. Eighteen beagle dogs were randomly divided into three groups: the seawater drowning (SW), perfluorocarbon (PFC), and control groups. The dogs in the SW group were intratracheally administered seawater to establish the animal model. The dogs in the PFC group were treated with vaporized PFCs. Probe-based confocal laser endomicroscopy (pCLE) was performed at 3 h. The blood gas, volume air index (VAI), pathological changes, and wet-to-dry (W/D) lung tissue ratios were assessed. The expression of heme oxygenase-1 (HO-1), nuclear respiratory factor-1 (NRF1), and NOD-like receptor family pyrin domain containing-3 (NLRP3) inflammasomes was determined by means of quantitative real-time polymerase chain reaction (qRT-PCR) and immunological histological chemistry. The SW group showed higher lung injury scores and W/D ratios, and lower VAI compared to the control group, and treatment with PFCs could reverse the change of lung injury score, W/D ratio and VAI. PFCs deactivated NLRP3 inflammasomes and reduced the release of caspase-1, interleukin-1ß (IL-1ß), and interleukin-18 (IL-18) by enhancing the expression of HO-1 and NRF1. Our results suggest that the vaporization of PFCs could attenuate SD-ALI by deactivating NLRP3 inflammasomes via the HO-1/NRF1 pathway.

iDNA-OpenPrompt: OpenPrompt learning model for identifying DNA methylation.

Introduction: DNA methylation is a critical epigenetic modification involving the addition of a methyl group to the DNA molecule, playing a key role in regulating gene expression without changing the DNA sequence. The main difficulty in identifying DNA methylation sites lies in the subtle and complex nature of methylation patterns, which may vary across different tissues, developmental stages, and environmental conditions. Traditional methods for methylation site identification, such as bisulfite sequencing, are typically labor-intensive, costly, and require large amounts of DNA, hindering high-throughput analysis. Moreover, these methods may not always provide the resolution needed to detect methylation at specific sites, especially in genomic regions that are rich in repetitive sequences or have low levels of methylation. Furthermore, current deep learning approaches generally lack sufficient accuracy. Methods: This study introduces the iDNA-OpenPrompt model, leveraging the novel OpenPrompt learning framework. The model combines a prompt template, prompt verbalizer, and Pre-trained Language Model (PLM) to construct the prompt-learning framework for DNA methylation sequences. Moreover, a DNA vocabulary library, BERT tokenizer, and specific label words are also introduced into the model to enable accurate identification of DNA methylation sites. Results and Discussion: An extensive analysis is conducted to evaluate the predictive, reliability, and consistency capabilities of the iDNA-OpenPrompt model. The experimental outcomes, covering 17 benchmark datasets that include various species and three DNA methylation modifications (4mC, 5hmC, 6mA), consistently indicate that our model surpasses outstanding performance and robustness approaches.

Structuring restricted amorphous molecular chains in the reinforced cellulose film by uniaxial stretching.

The construction of the preferred orientation structure by stretching is an efficient strategy to fabricate high-performance cellulose film and it is still an open issue whether crystalline structure or amorphous molecular chain is the key factor in determining the enhanced mechanical performance. Herein, uniaxial stretching with constant width followed by drying in a stretching state was carried out to cellulose hydrogels with physical and chemical double cross-linking networks, achieving high-performance regenerated cellulose films (RCFs) with an impressive tensile strength of 154.5 MPa and an elastic modulus of 5.4 GPa. The hierarchical structure of RCFs during uniaxial stretching and drying was systematically characterized from micro- to nanoscale, including microscopic morphology, crystalline structure as well as relaxation behavior at a molecular level. The two-dimensional correlation spectra of dynamic mechanical analysis and Havriliak-Negami fitting results verified that the enhanced mechanical properties of RCFs were mainly attributed to the stretch-induced tight packing and restricted relaxation of amorphous molecular chains. The new insight concerning the contribution of molecular chains in the amorphous region to the enhancement of mechanical performance for RCFs is expected to provide valuable guidance for designing and fabricating high-performance eco-friendly cellulose-based films.