Comparison of the therapeutic effects of three minimally invasive approaches for laparoscopic cholecystectomy combined with common bile duct exploration-- a 5-year retrospective analysis.

OBJECTIVE: The aim of this retrospective study was to explore the indications for three minimally invasive approaches-T-tube external drainage, double J-tube internal drainage, and primary closure-in laparoscopic cholecystectomy combined with common bile duct exploration. METHODS: Three hundred eighty-nine patients with common bile duct stones who were treated at the Second People's Hospital of Hefei between February 2018 and January 2023 were retrospectively included. Patients were divided into three groups based on the surgical approach used: the T-tube drainage group, the double J-tube internal drainage group, and the primary closure group. General data, including sex, age, and BMI, were compared among the three groups preoperatively. Surgical time, length of hospital stay, pain scores, and other aspects were compared among the three groups. Differences in liver function, inflammatory factors, and postoperative complications were also compared among the three groups. RESULTS: There were no significant differences among the three groups in terms of sex, age, BMI, or other general data preoperatively (P > 0.05). There were significant differences between the primary closure group and the T-tube drainage group in terms of surgical time and pain scores (P < 0.05). The primary closure group and double J-tube drainage group differed from the T-tube drainage group in terms of length of hospital stay, hospitalization expenses, and time to passage of gas (P <0.05). Among the three groups, there were no statistically significant differences in inflammatory factors or liver function, TBIL, AST, ALP, ALT, GGT, CRP, or IL-6, before surgery or on the third day after surgery (P > 0.05). However, on the third day after surgery, liver function in all three groups was significantly lower than that before surgery (P<0.05). In all three groups, the levels of CRP and IL-6 were significantly lower than their preoperative levels. The primary closure group had significantly lower CRP and IL-6 levels than did the T-tube drainage group (P < 0.05). The primary closure group differed from the T-tube drainage group in terms of the incidences of bile leakage and electrolyte imbalance (P < 0.05). The double J-tube drainage group differed from the T-tube drainage group in terms of the tube dislodgement rate (P < 0.05). CONCLUSION: Although primary closure of the bile ducts has clear advantages in terms of length of hospital stay and hospitalization expenses, it is associated with a higher incidence of postoperative complications, particularly bile leakage. T-tube drainage and double J-tube internal drainage also have their own advantages. The specific surgical approach should be selected based on the preoperative assessment, indications, and other factors to reduce the occurrence of postoperative complications.

Salvage surgery and conversion surgery for patients with non-small cell lung cancer: A narrative review.

Non-small cell lung cancer (NSCLC) remains the leading cause of cancer-related deaths. With the development of screening, patient selection and treatment strategies, patients' survival outcomes and living quality significantly improved. However, some patients still have local recurrence or residual tumors after receiving definitive therapies. Salvage surgery has been regarded as an effective option for recurrent or residual NSCLC, but its effectiveness remains undetermined. Furthermore, conversion surgery is a special type of salvage surgery for tumors converted from "initially unresectable" to "potentially resectable" status due to a favorable response to systemic treatments. Although conversion surgery is a promising curative procedure for advanced NSCLC, its concept and clinical value remain unfamiliar to clinicians. In this narrative review, we provided an overview of the safety and efficacy of salvage surgery, especially salvage surgery after sublobar resection in early-stage NSCLC. More importantly, we highlighted the concept and value of conversion surgery after systemic treatment in advanced NSCLC to gain some insights into its role in the treatment of lung cancer.

A comparative study of sampling methods in the detection of esophageal cancer-related microbiota.

Esophageal cancer (EC) is a multifaceted disease. Our understanding of the involvement of esophageal microbiota in its pathogenesis and progression is limited, which is due to the lack of proper endoscopic sampling methods. Hereby, we conducted a comparative analysis of paired samples obtained through endoscopic brushing and cytosponge, aiming at assessing the feasibility of using cytosponge as a minimally invasive sampling way for studying esophageal microbiota. Our findings suggest that cytosponge sampling yielded significantly superior community richness and diversity compared to endoscopic brushing in both controls (non-cancerous) and EC individuals. The analysis of beta-diversity revealed distinct microbial community pattern in the genus diversity between the two sampling methods, underscoring the importance of selecting appropriate sampling methods to effectively characterize the esophageal microbiota. Specifically, Lactococcus and Serratia showed higher abundance in the samples collected by endoscopic brushing, while Alloprevotella and Leptotrichia were more enriched in the samples collected by cytosponge. These differences in dominant microbes were associated with metabolic pathways that particularly were related to host inflammation, such as pyruvate and glucose metabolisms. Notably, the phylogenetic levels of the microbiota indicated varied explanatory power for different detection purposes. This study underscores the substantial impact of sampling method selection on the acquisition of esophageal microbiota associated with the EC development, encompassing considerations of both abundance and diversity. This highlights the significance of selecting an appropriate sampling method for investigating the esophageal microbial status and studying the micro-environment in EC-related individuals. IMPORTANCE: This study addresses a critical issue in esophageal cancer study by comparing two different sampling methods, endoscopic brushing and cytosponge, for investigating the esophageal microbiota. Our work highlights the suitability of the cytosponge technique as a minimally invasive sampling method for studying the esophageal microbiota and emphasizes the importance of selecting an appropriate sampling method to characterize the microbial community. Our findings have significant implications for advancing the understanding of the role of the esophageal microbiota in cancer development and will inform future research and clinical approaches in this field.

Survival outcomes and prognostic factors of advanced gastrointestinal stromal tumors: in the era of multiple tyrosine kinase inhibitors.

Background: Tyrosine kinase inhibitors (TKIs) have shown great efficacy in the treatment of advanced gastrointestinal stromal tumors (GISTs), significantly prolonging the survival of patients. In the era of imatinib, a few studies reported some prognostic factors for patients with advanced GISTs, such as age, sex, performance status, diameter of the largest lesions, KIT exon mutations, and some hematological examination results. However, with the advent of more TKIs, the prognostic factors for patients with advanced GISTs have not been fully understood in the era of multiple TKIs. In this study, we aimed to identify independent prognostic factors associated with the survival of patients diagnosed with advanced GISTs. Methods: Data on clinicopathologic characteristics, treatment approaches, and survival were retrospectively collected for patients with primary unresectable or recurrent GISTs treated from January 2010 to July 2023 at the First Affiliated Hospital of Chongqing Medical University, China. Univariable and multivariable Cox proportional hazards regression models were used to identify independent prognostic factors of survival. Results: A total of 194 patients were included in the analysis. The median follow-up duration was 59.9 months (range, 2.7-141.7 months). The median overall survival (mOS) in this cohort was 76.5 months (95% confidence interval, 63.4 to 89.6 months). All patients received TKI therapy during the follow-up period, and 56.2% received two or more types of TKIs. In multivariable Cox analysis, younger age, a single lesion at enrollment, no previous use of TKIs, smaller tumor burden, good Eastern Cooperative Oncology Group performance status (ECOG PS ≤1), and lesions limited to the liver were independent prognostic factors for better survival. Conclusions: We found that a single lesion at enrollment, no previous use of TKIs, a smaller tumor burden, and lesions limited to the liver were associated with better survival. Drug resistance is a severe challenge for advanced GISTs, and several factors mentioned above may be correlated with the development of drug resistance, leading to the poor survival of patients.

Finite-Time Stabilization of Inertial Memristive Neural Networks via Nonreduced Order Method.

This article investigates the finite-time stabilization problem of inertial memristive neural networks (IMNNs) with bounded and unbounded time-varying delays, respectively. To simplify the theoretical derivation, the nonreduced order method is utilized for constructing appropriate comparison functions and designing a discontinuous state feedback controller. Then, based on the controller, the state of IMNNs can directly converge to 0 in finite time. Several criteria for finite-time stabilization of IMNNs are obtained and the setting time is estimated. Compared with previous studies, the requirement of differentiability of time delay is eliminated. Finally, numerical examples illustrate the usefulness of the analysis results in this article.

Resection of the tumor in the trigone of the lateral ventricle via the contralateral posterior interhemispheric transfalcine transprecuneus approach with multi-modern neurosurgery technology: a case report.

Choroid plexus papilloma (CPP) is a rare benign intracranial tumor origin that predominantly manifests in the lateral ventricle in children, accounting for 0.3%-0.6% of all primary intracranial tumors. It is extremely rare to have the CPP in the trigone of the lateral ventricle through the contralateral posterior interhemispheric transfalcine transprecuneus approach (PITTA). Herein, we report this rare case. A 7-year-old girl presented with headache. Magnetic resonance imaging of the brain showed periatrial lesions, and histopathological examination confirmed CPP (WHO grade I). The contralateral PITTA is a safe, effective, reasonable, and appropriate for some lesions in the trigone of the lateral ventricle. It provides a wider surgical angle (especially for the lateral extension) and reduces the risk of disturbance of the optic radiation compared with the conventional approaches. The use of multiple modern neurosurgical techniques, including interventional embolization, intraoperative navigation, microscope, and electrophysiological monitoring, make the procedure much easier and more accurate, and the neuroendoscope adds to the visualization of the microscope and can reduce surgical complications.

Cuproptosis-Related Genes as Prognostic Biomarkers for Sepsis: Insights into Immune Function and Personalized Immunotherapy.

Background: This study aimed to discover diagnostic and prognostic biomarkers for sepsis immunotherapy through analyzing the novel cellular death process, cuproptosis. Methods: We used transcriptome data from sepsis patients to identify key cuproptosis-related genes (CuRGs). We created a predictive model and used the CIBERSORT algorithm to observe the link between these genes and the septic immune microenvironment. We segregated sepsis patients into three subgroups, comparing immune function, immune cell infiltration, and differential analysis. Single-cell sequencing and real-time quantitative PCR were used to view the regulatory effect of CuRGs on the immune microenvironment and compare the mRNA levels of these genes in sepsis patients and healthy controls. We established a sepsis forecast model adapted to heart rate, body temperature, white blood cell count, and cuproptosis key genes. This was followed by a drug sensitivity analysis of cuproptosis key genes. Results: Our results filtered three key genes (LIAS, PDHB, PDHA1) that impact sepsis prognosis. We noticed that the high-risk group had poorer immune cell function and lesser immune cell infiltration. We also discovered a significant connection between CuRGs and immune cell infiltration in sepsis. Through consensus clustering, sepsis patients were classified into three subgroups. The best immune functionality and prognosis was observed in subgroup B. Single-cell sequencing exposed that the key genes manage the immune microenvironment by affecting T cell activation. The qPCR results highlighted substantial mRNA level reduction of the three key genes in the SP compared to the HC. The prediction model, which combines CuRGs and traditional diagnostic indicators, performed better in accuracy than the other markers. The drug sensitivity analysis listed bisphenol A as highly sensitive to all the key genes. Conclusion: Our study suggests these CuRGs may offer substantial potential for sepsis prognosis prediction and personalized immunotherapy.

Prediction of tumor regression grade in far-advanced gastric cancer after preoperative immuno-chemotherapy using dual-energy CT-derived extracellular volume fraction.

OBJECTIVES: This study examines the effectiveness of dual-energy CT (DECT) delayed-phase extracellular volume (ECV) fraction in predicting tumor regression grade (TRG) in far-advanced gastric cancer (FAGC) patients receiving preoperative immuno-chemotherapy. MATERIALS AND METHODS: A retrospective analysis was performed on far-advanced gastric adenocarcinoma patients treated with preoperative immuno-chemotherapy at our institution from August 2019 to March 2023. Patients were categorized based on their TRG into pathological complete response (pCR) and non-pCR groups. ECV was determined using the delayed-phase iodine maps. In addition, tumor iodine densities and standardized iodine ratios were meticulously analyzed using the triple-phase enhanced iodine maps. Univariate analysis with five-fold cross-validation and Spearman correlation determined DECT parameters and clinical indicators association with pCR. The predictive accuracy of these parameters for pCR was evaluated using a weighted logistic regression model with five-fold cross-validation. RESULTS: Of the 88 patients enrolled (mean age 60.8 ± 11.1 years, 63 males), 21 (23.9%) achieved pCR. Univariate analysis indicated ECV's significant role in differentiating between pCR and non-pCR groups (average p value = 0.021). In the logistic regression model, ECV independently predicted pCR with an average odds ratio of 0.911 (95% confidence interval, 0.798-0.994). The model, incorporating ECV, tumor area, and IDAV (the relative change rate of iodine density from venous phase to arterial phase), showed an average area under curves (AUCs) of 0.780 (0.770-0.791) and 0.766 (0.731-0.800) for the training and validation sets, respectively, in predicting pCR. CONCLUSION: DECT-derived ECV fraction is a valuable predictor of TRG in FAGC patients undergoing preoperative immuno-chemotherapy. CLINICAL RELEVANCE STATEMENT: This study demonstrates that DECT-derived extracellular volume fraction is a reliable predictor for pathological complete response in far-advanced gastric cancer patients receiving preoperative immuno-chemotherapy, offering a noninvasive tool for identifying potential treatment beneficiaries.

Active on-site calibration technology of current transformer based on non-rated frequency current injection.

This paper proposes an active on-site calibration method through background current cancellation and non-rated current injection. It can measure the error of the current transformer in service from 1% to 120% rated current percentage without power supply interruption. In order to establish the error relationship between rated frequency and arbitrary frequency, a theoretical analysis of current transformer calibration at the arbitrary frequency has been developed by means of the equivalent circuit. It describes a method to determine the phase angle and ratio errors of the measuring transformers at arbitrary frequencies on the basis of the calibrated error values at rated frequency. To prove the theoretical analysis, an experimental validation was carried out. The experimental results demonstrate that this active onsite calibration is a valid tool for the evaluation of current transformer performances. The calibration results showed that, for both cases (non-rated frequency calibration and mixing frequency calibration), the difference between mean ratio error and rated frequency ratio error was lower than 0.01%, and the difference between mean phase error and rated frequency phase error was lower than 1', which meets the requirement of the 0.2 accuracy class calibration.

Molecular separation-assisted label-free SERS combined with machine learning for nasopharyngeal cancer screening and radiotherapy resistance prediction.

Nasopharyngeal cancer (NPC) is a malignant tumor with high prevalence in Southeast Asia and highly invasive and metastatic characteristics. Radiotherapy is the primary strategy for NPC treatment, however there is still lack of effect method for predicting the radioresistance that is the main reason for treatment failure. Herein, the molecular profiles of patient plasma from NPC with radiotherapy sensitivity and resistance groups as well as healthy group, respectively, were explored by label-free surface enhanced Raman spectroscopy (SERS) based on surface plasmon resonance for the first time. Especially, the components with different molecular weight sizes were analyzed via the separation process, helping to avoid the possible missing of diagnostic information due to the competitive adsorption. Following that, robust machine learning algorithm based on principal component analysis and linear discriminant analysis (PCA-LDA) was employed to extract the feature of blood-SERS data and establish an effective predictive model with the accuracy of 96.7% for identifying the radiotherapy resistance subjects from sensitivity ones, and 100% for identifying the NPC subjects from healthy ones. This work demonstrates the potential of molecular separation-assisted label-free SERS combined with machine learning for NPC screening and treatment strategy guidance in clinical scenario.

Co-colonization of different species harboring KPC or NDM carbapenemase in the same host gut: insight of resistance evolution by horizontal gene transfer.

Introduction: The dissemination of carbapenem-resistant Enterobacteriales (CRE) in nosocomial settings is primarily associated with the horizontal transfer of plasmids. However, limited research has focused on the in-host transferability of carbapenem resistance. In this study, ten isolates were collected from gut specimens of five individuals, each hosting two different species, including Escherichia coli, Klebsiella pneumoniae, Klebsiella aerogenes, Enterobacter cloacae, or Citrobacter koseri. Methods: Species identification and antimicrobial susceptibility were determined by MALDI-TOF MS and broth microdilution method. Carbapenemase genes were detected and localized using PCR, S1-PFGE and southern blot. The transferability of carbapenemase genes between species was investigated through filter mating experiments, and the genetic contexts of the plasmids were analyzed using whole genome sequencing. Results and discussion: Our results revealed that each of the ten isolates harbored a carbapenemase gene, including bla NDM-5, bla NDM-1, or bla KPC-2, on a plasmid. Five different plasmids were successfully transferred to recipient cells of E. coli, K. pneumoniae or A. baumannii by transconjugation. The genetic contexts of the carbapenemase gene were remarkably similar between the two CRE isolates from each individual. This study highlights the potential for interspecies plasmid transmission in human gut, emphasizing the colonization of CRE as a significant risk factor for the dissemination of carbapenemase genes within the host. These findings underscore the need for appropriate intestinal CRE screening and colonization prevention.

Investigating the features of risky driving behaviors on expressway diverge area based on conflict and modeling analysis.

Driving behaviors are important cause of expressway crash. In this study, method based on modified time-to-collision (MTTC) to identify risky driving behaviors on an expressway diverge area is proposed, thus investigating the impact of velocity and acceleration features of risky driving behavior. Firstly, MTTC is applied to judge whether the behavior is risky. Then, the relationships between velocity, acceleration and different driving behavior on the expressway diverge area were fit by binary logistic regression models (BLR) with L2 regularization and random forests (RF) models, and the models were interpreted by feature importance plots and partial dependency plots. The results show that the AUC metric of 4 RF models for 4 types of driving behaviors, namely, left lane change, right lane change, acceleration and deceleration, are 0.932, 0.845, 0.846 and 0.860 separately. The interpretation of models demonstrates that velocity and absolute value of acceleration greatly affect the risk of the driving behaviors. Different driving behaviors with a certain acceleration have a range of safety speed range. The range will get narrower with the growth of maximum absolute value of acceleration rate, and will be nearly non-exist when the acceleration is over 5 m/s2. In conclusion, this study provided a methodology to measure the risk of driving behaviors and establish a model to recognize of risky driving behaviors. The results can lay the foundation for making countermeasures to prevent risky driving behaviors by managing the vehicle speed.

Electronic Structure Modification of MnO2 Nanosheet Arrays with Enhanced Water Oxidation Activity and Stability by Nitrogen Plasma.

The strategic design of catalysts for the oxygen evolution reaction (OER) is crucial in tackling the substantial energy demands associated with hydrogen production in electrolytic water splitting. Despite extensive research on birnessite (δ-MnO2) manganese oxides to enhance catalytic activity by modulating Mn3+ species, the ongoing challenge is to simultaneously stabilize Mn3+ while improving overall activity. Herein, oxygen (O) vacancies and nitrogen (N) doping have been simultaneously introduced into the MnO2 through a simple nitrogen plasma approach, resulting in efficient OER performance. The optimized N-MnO2v electrocatalyst exhibits outstanding OER activity in alkaline electrolyte, reducing the overpotential by nearly 160 mV compared to pure pristine MnO2 (from 476 to 312 mV) at 10 mA cm-2, and a small Tafel slope of 89 mV dec-1. Moreover, it demonstrates excellent durability over a 122 h stability test. The introduction of O vacancies and incorporation of N not only fine-tune the electronic structure of MnO2, increasing the Mn3+ content to enhance overall activity, but also play a crucial role in stabilizing Mn3+, thereby leading to exceptional stability over time. Subsequently, density functional theory calculations validate the optimized electronic structure of MnO2 achieved through the two engineering methods, effectively lowering the intermediate adsorption free energy barrier. Our synergistic approach, utilizing nitrogen plasma treatment, opens a pathway to concurrently enhance the activity and stability of OER electrocatalysts, applicable not only to Mn-based but also to other transition metal oxides.

Comprehensive investigation in oncogenic functions and immunological roles of NCBP2 and its validation in prostate cancer.

BACKGROUND: Nuclear cap-binding protein 2 (NCBP2), as the component of the cap-binding complex, participates in a number of biological processes, including pre-mRNA splicing, transcript export, translation regulation and other gene expression steps. However, the role of NCBP2 on the tumor cells and immune microenvironment remains unclear. To systematically analyze and validate functions of NCBP2, we performed a pan-cancer analysis using multiple approaches. METHODS: The data in this study were derived from sequencing, mutation, and methylation data in the TCGA cohort, normal sample sequencing data in the GTEx project, and cell line expression profile data in the CCLE database. RESULTS: Survival analyses including the Cox proportional-hazards model and log-rank test revealed the poor prognostic role of NCBP2 in multiple tumors. We further validated the oncogenic ability of NCBP2 in prostate cancer cell lines, organoids and tumor-bearing mice. A negative correlation was observed between NCBP2 expression and immune score by the ESTIMATE algorithm. Simultaneously, the NCBP2-induced immunosuppressive microenvironment might be related to the decline in CD8+T cells and the increase in regulatory T cells and neutrophils, examined by flow cytometry experiments for NCBP2 overexpressed tumor-bearing mice. CONCLUSION: This research offered strong proof supporting NCBP2 as the prognostic marker and the therapeutic target in the future.

Multimodal frontal neuroimaging markers predict longitudinal craving reduction in abstinent individuals with heroin use disorder.

The variation in improvement among individuals with addiction after abstinence is a critical issue. Here, we aimed to identify robust multimodal markers associated with high response to 8-month abstinence in the individuals with heroin use disorder (HUD) and explore whether the identified markers could be generalized to the individuals with methamphetamine use disorder (MUD). According to the median of craving changes, 53 individuals with HUD with 8-month abstinence were divided into two groups: higher craving reduction and lower craving reduction. At baseline, clinical variables, cortical thickness and subcortical volume, fractional anisotropy (FA) of fibers and resting-state functional connectivity (RSFC) were extracted. Different strategies (single metric, multimodal neuroimaging fusion and multimodal neuroimaging-clinical data fusion) were used to identify reliable features for discriminating the individuals with HUD with higher craving reduction from those with lower reduction. The generalization ability of the identified features was validated in the 21 individuals with MUD. Multimodal neuroimaging-clinical fusion features with best performance was achieved an 87.1 ± 3.89% average accuracy in individuals with HUD, with a moderate accuracy of 66.7% when generalizing to individuals with MUD. The multimodal neuroimaging features, primarily converging in frontal regions (e.g., the left superior frontal (LSF) thickness, FA of the LSF-occipital tract, and RSFC of left middle frontal-right superior temporal lobe), collectively contributed to prediction alongside dosage and attention impulsiveness. In this study, we identified the validated multimodal frontal neuroimaging markers associated with higher response to long-term abstinence and revealed insights for the neural mechanisms of addiction abstinence, contributing to clinical strategies and treatment for addiction.

Machine Learning-Based Design of Superhard High-Entropy Nitride Coatings.

Limited by the inefficiency of the conventional trial-and-error method and the boundless compositional design space of high-entropy alloys (HEAs), accelerating the discovery of superior-performing high-entropy nitride (HEN) coatings remains a formidable challenge. Herein, the superhard HEN coatings were designed and prepared using the rapidly developing data-driven model machine learning (ML). A database containing hardness and different features of HEN coatings was established and categorized into four subsets covering the information on composition, composition-physical descriptors, composition-technique parameters, and composition-physical descriptors-technique parameters. Feature engineering was employed to reduce dimensionality and interpret the impact of features on the evolution of hardness. Both root mean squared error (RMSE) and decision coefficient (R2) were applied to assess the predictive accuracy of ML models with different subsets, proportions of test set, and algorithms. The model with best predicted performance was used to explore superhard HEN coatings in a predefined virtual space. Among the generated 5-/6-/7-/8-component (excluding N) systems, the coating possessing highest hardness was individually selected for further preparation. Four newly prepared coatings achieved the superhard level with an average prediction error of 7.83%. The morphology, chemical composition, structure, and hardness of the newly prepared coatings were discussed. The nanocrystal-amorphous nanocomposite structure of the novel AlCrNbSiTiN coating with the highest hardness of 45.77 GPa was revealed. The results demonstrated that ML can effectively guide the design and composition optimization of superb-performance protective HEN coatings.

Surface Cleaning of Oil Contaminants Using Bulk Nanobubbles.

The removal of oil from solid surfaces, such as textiles and plates, remains a challenge due to the strong binding affinity of the oil. Conventional methods for surface cleaning often require surfactants and mechanical abrasion to enhance the cleaning process. However, in excess, these can pose adverse effects on the environment and to the material. This study investigated how bulk nanobubble water can clean oil microdroplets deposited on surfaces like glass coverslips and dishes. Microscopy imaging and further image analysis clearly revealed that these microdroplets detached from both hydrophobic and hydrophilic surfaces when washed with bulk nanobubble water within a fluidic microchannel. Oil contaminant cleaning was also conducted in water as mobile phase to mimic the circumstances that occur in a dishwasher and washing machine. Cleaning on a larger scale also proved very successful in the removal of oil from a porcelain bowl. These results indicate that nanobubble water can easily remove oil contaminants from glass and porcelain surfaces without the assistance of surfactants. This is in stark contrast to negligible results obtained with a control solution without nanobubbles. This study indicates that nanobubble technology is an innovative, low-cost, eco-friendly approach for oil removal, demonstrating its potential for broad practical applications.

Cerebral venous sinus thrombosis accompanied by cerebral venous infarction and multiorgan dysfunction after wasp stings, A case report.

Introduction: The high incidence of wasp stings have been causing a variety of injuries in China, but systemic complications are rarely reported. Case presentation: A 59-year-old man was severely attacked by wasps. He developed an acute onset of right hemiplegia and chest distress and was admitted to our emergency department 13 hours after being attacked. Various abnormal signals were found by biochemical tests. Magnetic resonance venography of head demonstrated that the superior sagittal sinus was not visible, indicating cerebral venous sinus thrombosis. Magnetic resonance imaging showed abnormal signals in the left frontal lobe, parietal lobe, and thalamus, indicating venous cerebral infarction and hemorrhage, coupled with subarachnoid hemorrhage. The patient was diagnosed with a rare combination of cerebral venous sinus thrombosis, cerebral venous infarction, and multi-organ dysfunction following hornet stings. After undergoing systematic treatment including blood perfusion, blood dialysis, anti-inflammatory hormone therapy, antiallergic medication, antibiotic use, and anticoagulation treatment, the patient showed significant improvement in limb muscle strength and dizziness symptoms. However, the patient developed irreversible kidney damage and is currently dependent on renal replacement therapy. Conclusions: This case highlights the serious systemic consequences that can occur following multiple wasp stings, including rare complications such as venous sinus thrombosis leading to cerebral infarction and renal failure. Early intervention with blood perfusion, hemodialysis, and plasmapheresis, in addition to general treatment, may help prevent permanent organ damage in patients with a large number of wasp stings.

Identifying autophagy-related mRNAs and potential ceRNA networks in meniscus degeneration based on RNA sequencing and experimental validation.

Purpose: The intimate connection between long noncoding RNA (lncRNA) and autophagy has been established in cartilage degeneration. However, their roles in meniscal degeneration remain ambiguous. This study aimed to identify the key autophagy-related lncRNA and its associated regulatory network in meniscal degeneration in the context of osteoarthritis (OA). Methods: RNA sequencing was performed to identify differentially expressed lncRNAs (DELs) and mRNAs (DEMs), which were then conducted to enrichment analyses using the DAVID database and Metascape. Autophagy-related DEMs were identified by combining DEMs with data from the Human Autophagy Database. Three databases were used to predict miRNA, and the DIANA LncBase Predicted database was utilized to predict miRNA-lncRNA interactions. Based on these predictions, comprehensive competitive endogenous RNA (ceRNA) network were constructed. The expression levels of the classical autophagy markers and autophagy-related ceRNA network were validated. Additionally, Gene Set Enrichment Analysis (GSEA) was performed using autophagy-related DEMs. Results: 310 DELs and 320 DEMs were identified, with five upregulated and one downregulated autophagy-related DEMs. Through reverse prediction of miRNA, paired miRNA-lncRNA interactions, and verification using RT-qPCR, two lncRNAs (PCAT19, CLIP1-AS1), two miRNA (has-miR-3680-3p and has-miR-4795-3p) and two mRNAs (BAG3 and HSP90AB1) were included in the constructed ceRNA regulatory networks. GSEA indicated that the increased expression of autophagy-related mRNAs inhibited glycosaminoglycan biosynthesis in the degenerative meniscus. Conclusion: This study presented the first construction of regulatory ceRNA network involving autophagy-related lncRNA-miRNA-mRNA interactions in OA meniscus. These findings offered valuable insights into the mechanisms underlying meniscal degeneration and provided potential targets for therapeutic intervention.

Versatile Framework for Drug-Target Interaction Prediction by Considering Domain-Specific Features.

Predicting drug-target interactions (DTIs) is one of the crucial tasks in drug discovery, but traditional wet-lab experiments are costly and time-consuming. Recently, deep learning has emerged as a promising tool for accelerating DTI prediction due to its powerful performance. However, the models trained on limited known DTI data struggle to generalize effectively to novel drug-target pairs. In this work, we propose a strategy to train an ensemble of models by capturing both domain-generic and domain-specific features (E-DIS) to learn diverse domain features and adapt them to out-of-distribution data. Multiple experts were trained on different domains to capture and align domain-specific information from various distributions without accessing any data from unseen domains. E-DIS provides a comprehensive representation of proteins and ligands by capturing diverse features. Experimental results on four benchmark data sets in both in-domain and cross-domain settings demonstrated that E-DIS significantly improved model performance and domain generalization compared to existing methods. Our approach presents a significant advancement in DTI prediction by combining domain-generic and domain-specific features, enhancing the generalization ability of the DTI prediction model.