BACKGROUND Research has shown that several factors can influence postoperative abnormal liver function;however,most studies on this issue have focused specifically on hepatic and cardiac surgeries,leaving limited rese...BACKGROUND Research has shown that several factors can influence postoperative abnormal liver function;however,most studies on this issue have focused specifically on hepatic and cardiac surgeries,leaving limited research on contributing factors in other types of surgeries.AIM To identify the risk factors for early postoperative abnormal liver function in multiple surgery types and construct a risk prediction model.METHODS This retrospective cohort study involved 3720 surgical patients from 5 surgical departments at Guangdong Provincial Hospital of Traditional Chinese Medicine.Patients were divided into abnormal(n=108)and normal(n=3612)groups based on liver function post-surgery.Univariate analysis and LASSO regression screened variables,followed by logistic regression to identify risk factors.A prediction model was constructed based on the variables selected via logistic re-gression.The goodness-of-fit of the model was evaluated using the Hosm-er–Lemeshow test,while discriminatory ability was measured by the area under the receiver operating characteristic curve.Calibration curves were plotted to visualize the consistency between predicted probabilities and observed outcomes.RESULTS The key factors contributing to abnormal liver function after surgery include elevated aspartate aminotransferase and alanine aminotransferase levels and reduced platelet counts pre-surgery,as well as the sevoflurane use during the procedure,among others.CONCLUSION The above factors collectively represent notable risk factors for postoperative liver function injury,and the prediction model developed based on these factors demonstrates strong predictive efficacy.展开更多
To investigate the correlation between propacetamol and postoperative liver enzyme abnormalities among patients,a retrospective analysis was conducted on inpatients in the thoracic surgery department spanning from Jan...To investigate the correlation between propacetamol and postoperative liver enzyme abnormalities among patients,a retrospective analysis was conducted on inpatients in the thoracic surgery department spanning from January 1 to June 30,2023.Causality assessment regarding propacetamol and postoperative liver enzyme abnormalities was performed using the updated Roussel Uclaf Causality Assessment Method(RUCAM).Furthermore,independent risk factors for liver enzyme abnormalities were identified through both univariate and multivariate analyses,followed by the construction and validation of a clinical nomogram.A total of 247 patients who received propacetamol were ultimately included in the study.Liver enzyme abnormalities post-surgery were more accurately predicted by considering the daily dose of propacetamol and the number of medications(OR(95%CI),4.831(2.797,8.344),P<0.001;10.007(3.878,25.823),P<0.001).A clinical predictive nomogram model was developed,incorporating these two independent risk factors,which exhibited favorable discrimination(AUC(95%CI),0.811(0.750,0.872)),calibration,and decision curve analysis(DCA)demonstrating the highest net benefits across a broad spectrum of threshold probabilities(10%to 90%).The daily dose of propacetamol and the number of medications were found to be independently associated with postoperative liver enzyme abnormalities.This user-friendly nomogram,comprising these two factors,might assist clinicians in assessing the risks of propacetamol-related liver dysfunction following surgery.展开更多
BACKGROUND An echocardiogram is an essential tool in the evaluation of potential kidney transplant recipients(KTRs).Despite cardiac clearance,potential KTRs still have structural and functional abnormalities.Identifyi...BACKGROUND An echocardiogram is an essential tool in the evaluation of potential kidney transplant recipients(KTRs).Despite cardiac clearance,potential KTRs still have structural and functional abnormalities.Identifying the prevalence of these abnormalities and understanding their predictors is vital for optimizing pretransplant risk stratification and improving post-transplant outcomes.AIM To determine the prevalence of left ventricular hypertrophy(LVH),left ventricular systolic dysfunction(LVSD),diastolic dysfunction(DD),pulmonary hypertension(PH),and their predictors,and to assess their impact on graft function in pre-transplant candidates.METHODS The study included all successful transplant candidates older than 14 who had a baseline echocardiogram.Binary logistic regression models were constructed to identify factors associated with LVH,LVSD,DD,and PH.RESULTS Out of 259 patients,LVH was present in 64%(166),12%(31)had LVSD,27.5%(71)had DD,and 66(25.5%)had PH.Independent predictors of LVH included male gender[odds ratio(OR):2.51;95%CI:1.17-5.41 P=0.02],PH(OR=2.07;95%CI:1.11-3.86;P=0.02),DD(OR:2.47;95%CI:1.29-4.73;P=0.006),and dyslipidemia(OR=1.94;95%CI:1.07-3.53;P=0.03).Predictors for LVSD included patients with DD(OR=3.3,95%CI:1.41-7.81;P=0.006)and a family history of coronary artery disease(OR=4.50,95%CI:1.33-15.20;P=0.015).Peritoneal dialysis was an independent predictor for DD(OR=10.03;95%CI:1.71-58.94,P=0.011).The presence of LVH(OR=3.32,95%CI:1.05-10.55,P=0.04)and mild to moderate or moderate to severe mitral regurgitation(OR=4.63,95%CI:1.45-14.78,P=0.01)were significant factors associated with PH.These abnormalities had no significant impact on estimated glomerular filtration at discharge,6 months,1 year,or 2 years post-transplant.CONCLUSION Significant echocardiographic abnormalities persist in a potential transplant candidate despite cardiac clearance,although they don’t affect future graft function.Understanding the risk factors associated with these abnormalities may help clinicians address these factors pre-and post-transplant to achieve better outcomes.展开更多
AIM:To define the prevalence and anatomical patterns of paranasal sinus abnormalities(PSA)in thyroid-associated ophthalmopathy(TAO)and to test the hypothesis that TAO is partially driven by contiguous orbital inflamma...AIM:To define the prevalence and anatomical patterns of paranasal sinus abnormalities(PSA)in thyroid-associated ophthalmopathy(TAO)and to test the hypothesis that TAO is partially driven by contiguous orbital inflammation rather than systemic autoimmunity or generalized orbital pressure.METHODS:Data included ophthalmic assessments and a panel of thyroid function and autoimmune biomarkers.Blinded radiological analysis of orbital computed tomography(CT)scans was performed to quantify sinus abnormalities and extraocular muscles(EOMs)involvement.Patients were categorized into two groups based on CT findings,those with no radiological evidence of sinus abnormalities(non-PSA control group)and those with identifiable PSA.Furthermore,ethmoid sinus mucosal biopsies from a subset of TAO patients and noninflammatory controls were subjected to histopathological analysis.RESULTS:Totally 121 TAO patients(mean age 42.4±12.8y,range 10-78y),male:female=42:79,were included.PSA was identified in 44.6%(n=54)of patients,with a distribution anatomically restricted to the maxillary(50.0%isolated)and ethmoid sinuses(18.5%isolated;29.6%combined).Compared to the non-PSA group(n=67),patients with PSA were significantly older(45.1±11.8 vs 40.3±13.2y;P=0.040)and were more likely to be male(55.6%vs 17.9%;P<0.001).They also had significantly higher proptosis(22.1±3.2 vs 20.7±2.9 mm;P<0.001).Medial/inferior rectus involvement was most frequent(88.4%vs 89.3%).Histopathological analysis of sinus mucosa from PSA patients provided direct evidence of pathology,revealing a dense,chronic lymphoplasmacytic infiltrate and submucosal edema,validating the radiological findings as a true inflammatory process.No significant correlation was found with systemic autoimmune markers,including thyroid-stimulating hormone(TSH)receptor antibodies(TRAb,median 4.86 vs 2.71 IU/L,P=0.104).CONCLUSION:TAO is associated with a high prevalence of PSA in a pattern consistent with the orbital anatomy.The correlation with ipsilateral muscle thickening combined with the lack of association with proptosis laterality or systemic biomarkers lend strong support to a model of contiguous inflammation over systemic autoimmunity,a hypothesis that warrants further validation through longitudinal and mechanistic studies.展开更多
Prenatal exposure to bisphenols and metals has raised significant concerns regarding their potential impact on fetal development,particularly the risk of fetal chromosome numerical abnormalities(CNA).In this case-cont...Prenatal exposure to bisphenols and metals has raised significant concerns regarding their potential impact on fetal development,particularly the risk of fetal chromosome numerical abnormalities(CNA).In this case-control study,we analyzed bisphenol and metal concentrations in amniotic fluid of high-risk pregnant women undergoing amniocentesis.Concentrations of bisphenols and metals were measured using ultra-performance liquid chromatography-tandem mass spectrometry and inductively coupled plasma-mass spectrometry,respectively.Logistic regression and quantile-based g-computation were applied to evaluate individual and combined effects,while dose-response relationships were assessed using restricted cubic splines.Our findings indicated that bisphenol S(BPS),bisphenol Z(BPZ),bisphenol AF(BPAF),antimony(Sb),and vanadium(V)were significantly associated with an increased risk of CNA when analyzed individually,whereas manganese,iron,copper(Cu),nickel(Ni),and zinc(Zn)were significantly and inversely associated with CNA risk.Combined exposure to bisphenol and metal mixtures was associated with an increased risk of CNA in multi-pollutant models.Cu and Ni exhibited a positive additive interaction.Furthermore,BPS,BPZ,and BPAF were individually associated with an increased risk of Down syndrome,while Zn was associated with a decreased risk of Down syndrome.BPS,Sb,V,and Zn were individually associated with an increased risk of Klinefelter syndrome.These findings underscore the potential role of prenatal bisphenol and metal exposure in the pathogenesis of fetal CNA,highlighting both additive and synergistic effects.展开更多
Aiming at the problem of imbalance between detection accuracy and algorithm model lightweight in UAV aerial image target detection algorithm,a lightweight multi-category abnormal behavior detection algorithm based on ...Aiming at the problem of imbalance between detection accuracy and algorithm model lightweight in UAV aerial image target detection algorithm,a lightweight multi-category abnormal behavior detection algorithm based on improved YOLOv11n is designed.By integrating multi-head grouped self-attention mechanism and Partial-Conv,a two-way feature grouping fusion module(DFPF)was designed,which carried out effective channel segmentation and fusion strategies to reduce redundant calculations andmemory access.C3K2 module was improved,and then unstructured pruning and feature distillation technologywere used.The algorithmmodel is lightweight,and the feature extraction ability for airborne visual abnormal behavior targets is strengthened,and the computational efficiency of the model is improved.Finally,we test the generalization of the baseline model and the improved model on the VisDrone2019 dataset.The results show that com-pared with the baseline model,the detection accuracy of the final improved model on the airborne visual abnormal behavior dataset is improved from 90.2% to 94.8%,and the model parameters are reduced by 50.9% to meet the detection requirements of high efficiency and high precision.The detection accuracy of the improved model on the Vis-Drone2019 public dataset is 1.3% higher than that of the baseline model,indicating the effectiveness of the improved method in this paper.展开更多
Nail changes following upper extremity transplantation(UET)cannot be overlooked as they possess diagnostic and prognostic relevance in allotransplantation of upper limbs.This comprehensive review explores nail and nai...Nail changes following upper extremity transplantation(UET)cannot be overlooked as they possess diagnostic and prognostic relevance in allotransplantation of upper limbs.This comprehensive review explores nail and nail bed related changes encountered in UET recipients in the literature.The differential diagnosis of nail abnormalities in UET includes a wide range of systemic,local and iatrogenic conditions other than immune responses to the allograft.It requires interdisciplinary evaluation by primary transplant surgeons,pathologists,dermatologists and immunologists.The possible underlying mechanisms of nail pathology in UET and the management are discussed.It also underscores the importance of onychodystrophy and need for timely intervention and to improve outcomes in UET recipients.展开更多
Advances in optical coherence tomography(OCT)technology allow a clear view of the vitreoretinal interface(VRI).The abnormality of the VRI is one of the common symptoms of high myopia,mainly including posterior vitreou...Advances in optical coherence tomography(OCT)technology allow a clear view of the vitreoretinal interface(VRI).The abnormality of the VRI is one of the common symptoms of high myopia,mainly including posterior vitreous detachment(PVD)and epiretinal membrane(ERM).They can cause severe damage to the structure and function of the retina,leading to permanent vision loss.Therefore,fully automated detection of abnormalities at the VRI is crucial for the management of high myopia.This paper presents a DS-YOLOv7 network aimed at accurately identifying abnormalities,including partial PVD,complete PVD,and ERM from retinal OCT images.Built upon the YOLOv7 network,the proposed model integrates the advanced dynamic snake convolution(DSConv)module to capture the curvilinear characteristics of lesions,and the mixture of attention and convolution(ACMix)module to improve the precision and robustness of feature extraction through effective fusion of self-attention mechanisms and convolution.Moreover,the introduction of the efficient complete intersection-over-union(ECIoU)loss function further enhances the coordinate regression capability of the model.Threefold cross-validation on a dataset with 1973 OCT B-scans from 46 patients shows that the DS-YOLOv7 achieved superior performance in vitreoretinal interface abnormality detection,with mAP@0.5 of 0.714,mAP@0.75 of 0.438,and mAP@0.5:0.95 of 0.424.The proposed model can provide an accurate and efficient diagnostic tool for patients with high myopia.展开更多
To address the issue of abnormal energy consumption fluctuations in the converter steelmaking process,an integrated diagnostic method combining the gray wolf optimization(GWO)algorithm,support vector machine(SVM),and ...To address the issue of abnormal energy consumption fluctuations in the converter steelmaking process,an integrated diagnostic method combining the gray wolf optimization(GWO)algorithm,support vector machine(SVM),and K-means clustering was proposed.Eight input parameters—derived from molten iron conditions and external factors—were selected as feature variables.A GWO-SVM model was developed to accurately predict the energy consumption of individual heats.Based on the prediction results,the mean absolute percentage error and maximum relative error of the test set were employed as criteria to identify heats with abnormal energy usage.For these heats,the K-means clustering algorithm was used to determine benchmark values of influencing factors from similar steel grades,enabling root-cause diagnosis of excessive energy consumption.The proposed method was applied to real production data from a converter in a steel plant.The analysis reveals that heat sample No.44 exhibits abnormal energy consumption,due to gas recovery being 1430.28 kg of standard coal below the benchmark level.A secondary contributing factor is a steam recovery shortfall of 237.99 kg of standard coal.This integrated approach offers a scientifically grounded tool for energy management in converter operations and provides valuable guidance for optimizing process parameters and enhancing energy efficiency.展开更多
Early and accurate detection of bone cancer and marrow cell abnormalities is critical for timely intervention and improved patient outcomes.This paper proposes a novel hybrid deep learning framework that integrates a ...Early and accurate detection of bone cancer and marrow cell abnormalities is critical for timely intervention and improved patient outcomes.This paper proposes a novel hybrid deep learning framework that integrates a Convolutional Neural Network(CNN)with a Bidirectional Long Short-Term Memory(BiLSTM)architecture,optimized using the Firefly Optimization algorithm(FO).The proposed CNN-BiLSTM-FO model is tailored for structured biomedical data,capturing both local patterns and sequential dependencies in diagnostic features,while the Firefly Algorithm fine-tunes key hyperparameters to maximize predictive performance.The approach is evaluated on two benchmark biomedical datasets:one comprising diagnostic data for bone cancer detection and another for identifying marrow cell abnormalities.Experimental results demonstrate that the proposed method outperforms standard deep learning models,including CNN,LSTM,BiLSTM,and CNN-LSTM hybrids,significantly.The CNNBiLSTM-FO model achieves an accuracy of 98.55%for bone cancer detection and 96.04%for marrow abnormality classification.The paper also presents a detailed complexity analysis of the proposed algorithm and compares its performance across multiple evaluation metrics such as precision,recall,F1-score,and AUC.The results confirm the effectiveness of the firefly-based optimization strategy in improving classification accuracy and model robustness.This work introduces a scalable and accurate diagnostic solution that holds strong potential for integration into intelligent clinical decision-support systems.展开更多
Objective: To explore the genotoxic potential and histopathological changes induced in liver, kidney, testis, brain and heart after using the antibiotic drug amoxicillin/clavulanic acid(4:1).Methods: The study include...Objective: To explore the genotoxic potential and histopathological changes induced in liver, kidney, testis, brain and heart after using the antibiotic drug amoxicillin/clavulanic acid(4:1).Methods: The study included chromosomal aberration analysis in bone-marrow and mouse spermatocytes, induction of sperm morphological abnormalities and histopathological changes in different body organs. The drug was administrated orally at a dose of81 mg/kg body weight twice daily(Total = 162 mg/kg/day) for various periods of time equivalent to 625 mg/men(twice daily).Results: The results revealed non-significant chromosomal aberrations induced after treatment with amoxicillin/clavulanic acid(AC) in both bone marrow and mouse spermatocytes after 7 and 10 days treatment. On the other hand, statistically significant percentages of sperm morphological abnormalities were recorded. Such percentage reached 8.10 ± 0.55, 9.86 ± 0.63 and 12.12 ± 0.58 at the three time intervals tested(7, 14 and 35 days after the 1 st treatment respectively)(treatment performed for 5 successive days) compared with 2.78 ± 0.48 for the control. The results also revealed histopathological changes in different body organs after AC treatment which increased with the prolongation of the period of therapy. Congestion of central vain, liver hemorrhage and hydropic changes in hepatocytes were noticed in the liver. Degenerative changes were found in kidney glomerulus and tubules while testis showed atrophy of seminiferous tubules, and reduction of spermatogenesis. AC also induced neurotoxicity and altered brain neurotransmitter levels. Hemorrhage in the myocardium, disruption of cardiac muscle fibers and pyknotic nuclei in cardiomyocytes were recorded as side effects of AC in heart tissue.Conclusions: The results concluded that AC treatment induced sperm morphological abnormalities and histopathological changes in different body organs. Clinicians must be aware of such results while describing the drug.展开更多
Abnormal postoperative neurobehavioral performance(APNP)is a common phenomenon in the early postoperative period.The disturbed homeostatic status of metabolites in the brain after anesthesia and surgery might make a s...Abnormal postoperative neurobehavioral performance(APNP)is a common phenomenon in the early postoperative period.The disturbed homeostatic status of metabolites in the brain after anesthesia and surgery might make a significant contribution to APNP.The dynamic changes of metabolites in different brain regions after anesthesia and surgery,as well as their potential association with APNP are still not well understood.Here,we used a battery of behavioral tests to assess the effects of laparotomy under isoflurane anesthesia in aged mice,and investigated the metabolites in 12 different sub-regions of the brain at different time points using proton nuclear magnetic resonance('H-NMR)spectroscopy.The abnormal neurobehavioral performance occurred at 6 h and/or 9 h,and recovered at 24 h after anesthesia/surgery.Compared with the control group,the altered metabolite of the model group at 6 h was aspartate(Asp),and the difference was mainly displayed in the cortex;while significant changes at 9 h occurred predominantly in the cortex and hippocampus,and the corresponding metabolites were Asp and glutamate(Glu).All changes returned to baseline at 24 h.The altered metabolic changes could have occurred as a result of the acute APNP,and the metabolites Asp and Glu in the cortex and hippocampus could provide preliminary evidence for understanding the APNP process.展开更多
As-forged WSTi6421 titanium alloy billet afterβannealing was investigated.Abnormally coarse grains larger than adjacent grains could be observed in the microstructures,forming abnormal grain structures with uneven si...As-forged WSTi6421 titanium alloy billet afterβannealing was investigated.Abnormally coarse grains larger than adjacent grains could be observed in the microstructures,forming abnormal grain structures with uneven size distribution.Through electron backscattered diffraction(EBSD),the forged microstructure at various locations of as-forged WSTi6421 titanium alloy billet was analyzed,revealing that the strength of theβphase cubic texture generated by forging significantly influences the grain size afterβannealing.Heat treatment experiments were conducted within the temperature range from T_(β)−50°C to T_(β)+10°C to observe the macro-and micro-morphologies.Results show that the cubic texture ofβphase caused by forging impacts the texture of the secondaryαphase,which subsequently influences theβphase formed during the post-βannealing process.Moreover,the pinning effect of the residual primaryαphase plays a crucial role in the growth ofβgrains during theβannealing process.EBSD analysis results suggest that the strength ofβphase with cubic texture formed during forging process impacts the orientation distribution differences ofβgrains afterβannealing.Additionally,the development of grains with large orientations within the cubic texture shows a certain degree of selectivity duringβannealing,which is affected by various factors,including the pinning effect of the primaryαphase,the strength of the matrix cubic texture,and the orientation relationship betweenβgrain and matrix.Comprehensively,the stronger the texture in a certain region,the less likely the large misoriented grains suffering secondary growth,thereby aggregating the difference in microstructure and grain orientation distribution across different regions afterβannealing.展开更多
Objective Rheumatoid arthritis(RA)is a systemic autoimmune disease that affects the small joints of the whole body and degrades the patients’quality of life.Zhengqing Fengtongning(ZF)is a traditional Chinese medicine...Objective Rheumatoid arthritis(RA)is a systemic autoimmune disease that affects the small joints of the whole body and degrades the patients’quality of life.Zhengqing Fengtongning(ZF)is a traditional Chinese medicine preparation used to treat RA.ZF may cause liver injury.In this study,we aimed to develop a prediction model for abnormal liver function caused by ZF.Methods This retrospective study collected data from multiple centers from January 2018 to April 2023.Abnormal liver function was set as the target variable according to the alanine transaminase(ALT)level.Features were screened through univariate analysis and sequential forward selection for modeling.Ten machine learning and deep learning models were compared to find the model that most effectively predicted liver function from the available data.Results This study included 1,913 eligible patients.The LightGBM model exhibited the best performance(accuracy=0.96)out of the 10 learning models.The predictive metrics of the LightGBM model were as follows:precision=0.99,recall rate=0.97,F1_score=0.98,area under the curve(AUC)=0.98,sensitivity=0.97 and specificity=0.85 for predicting ALT<40 U/L;precision=0.60,recall rate=0.83,F1_score=0.70,AUC=0.98,sensitivity=0.83 and specificity=0.97 for predicting 40≤ALT<80 U/L;and precision=0.83,recall rate=0.63,F1_score=0.71,AUC=0.97,sensitivity=0.63 and specificity=1.00 for predicting ALT≥80 U/L.ZF-induced abnormal liver function was found to be associated with high total cholesterol and triglyceride levels,the combination of TNF-αinhibitors,JAK inhibitors,methotrexate+nonsteroidal anti-inflammatory drugs,leflunomide,smoking,older age,and females in middle-age(45-65 years old).Conclusion This study developed a model for predicting ZF-induced abnormal liver function,which may help improve the safety of integrated administration of ZF and Western medicine.展开更多
Male infertility can result from impaired sperm motility caused by multiple morphological abnormalities of the flagella(MMAF).Distinct projections encircling the central microtubules of the spermatozoal axoneme play p...Male infertility can result from impaired sperm motility caused by multiple morphological abnormalities of the flagella(MMAF).Distinct projections encircling the central microtubules of the spermatozoal axoneme play pivotal roles in flagellar bending and spermatozoal movement.Mammalian sperm-associated antigen 17(SPAG17)encodes a conserved axonemal protein of cilia and flagella,forming part of the C1a projection of the central apparatus,with functions related to ciliary/flagellar motility,skeletal growth,and male fertility.This study investigated two novel homozygous SPAG17 mutations(M1:NM_206996.2,c.829+1G>T,p.Asp212_Glu276del;and M2:c.2120del,p.Leu707*)identified in four infertile patients from two consanguineous Pakistani families.These patients displayed the MMAF phenotype confirmed by Papanicolaou staining and scanning electron microscopy assays of spermatozoa.Quantitative real-time polymerase chain reaction(PCR)of patients’spermatozoa also revealed a significant decrease in SPAG17 mRNA expression,and immunofluorescence staining showed the absence of SPAG17 protein signals along the flagella.However,no apparent ciliary-related symptoms or skeletal malformations were observed in the chest X-rays of any of the patients.Transmission electron microscopy of axoneme cross-sections from the patients showed incomplete C1a projection and a higher frequency of missing microtubule doublets 1 and 9 compared with those from fertile controls.Immunofluorescence staining and Western blot analyses of spermatogenesis-associated protein 17(SPATA17),a component of the C1a projection,and sperm-associated antigen 6(SPAG6),a marker of the spring layer,revealed disrupted expression of both proteins in the patients’spermatozoa.Altogether,these findings demonstrated that SPAG17 maintains the integrity of spermatozoal flagellar axoneme,expanding the phenotypic spectrum of SPAG17 mutations in humans.展开更多
The rapid integration of Internet of Things(IoT)technologies is reshaping the global energy landscape by deploying smart meters that enable high-resolution consumption monitoring,two-way communication,and advanced met...The rapid integration of Internet of Things(IoT)technologies is reshaping the global energy landscape by deploying smart meters that enable high-resolution consumption monitoring,two-way communication,and advanced metering infrastructure services.However,this digital transformation also exposes power system to evolving threats,ranging from cyber intrusions and electricity theft to device malfunctions,and the unpredictable nature of these anomalies,coupled with the scarcity of labeled fault data,makes realtime detection exceptionally challenging.To address these difficulties,a real-time decision support framework is presented for smart meter anomality detection that leverages rolling time windows and two self-supervised contrastive learning modules.The first module synthesizes diverse negative samples to overcome the lack of labeled anomalies,while the second captures intrinsic temporal patterns for enhanced contextual discrimination.The end-to-end framework continuously updates its model with rolling updated meter data to deliver timely identification of emerging abnormal behaviors in evolving grids.Extensive evaluations on eight publicly available smart meter datasets over seven diverse abnormal patterns testing demonstrate the effectiveness of the proposed full framework,achieving average recall and F1 score of more than 0.85.展开更多
Cervical cancer is the fourth most common cancer worldwide, accounting for 6.8% of new cancer cases and 8.1% of cancer-related deaths. About 85% of these deaths occurred in low- and middle-income countries. The aim of...Cervical cancer is the fourth most common cancer worldwide, accounting for 6.8% of new cancer cases and 8.1% of cancer-related deaths. About 85% of these deaths occurred in low- and middle-income countries. The aim of this study was to assess the frequency and distribution of the human papillomavirus (HPV) genotypes in women showing cytological abnormalities of the cervix at the Sourô SANOU University Hospital (CHUSS) in Bobo-Dioulasso, Burkina Faso. This is a descriptive study of women recruited at the CHUSS. The cervico-uterine smear examination was carried out at the CHUSS Anatomy and Pathology Department for cervical cancer screening. The data were collected from women with atypical cells on their cervico-uterine smear. Cervicovaginal samples were taken from consenting women and HPV genotyping was performed using the HPV Direct FLOW CHIP kit at CERBA. We obtained approval from the ethics committee. The data were analyzed using the SPSS 26 software. The results of the study showed that 67.79% of the participants were aged between 50 and 65, a group that is particularly vulnerable to persistent infection with high-risk oncogenic HPV genotypes. Of the women screened, 40.7% were HPV positive and 29.2% had multiple infections. The most common genotypes were HPV 35, followed by HPV 18, 52, 58 and 66. These data highlight the need for increased surveillance and targeted prevention strategies among this female population.展开更多
The integration of cloud computing into traditional industrial control systems is accelerating the evolution of Industrial Cyber-Physical System(ICPS),enhancing intelligence and autonomy.However,this transition also e...The integration of cloud computing into traditional industrial control systems is accelerating the evolution of Industrial Cyber-Physical System(ICPS),enhancing intelligence and autonomy.However,this transition also expands the attack surface,introducing critical security vulnerabilities.To address these challenges,this article proposes a hybrid intrusion detection scheme for securing ICPSs that combines system state anomaly and network traffic anomaly detection.Specifically,an improved variation-Bayesian-based noise covariance-adaptive nonlinear Kalman filtering(IVB-NCA-NLKF)method is developed to model nonlinear system dynamics,enabling optimal state estimation in multi-sensor ICPS environments.Intrusions within the physical sensing system are identified by analyzing residual discrepancies between predicted and observed system states.Simultaneously,an adaptive network traffic anomaly detection mechanism is introduced,leveraging learned traffic patterns to detect node-and network-level anomalies through pattern matching.Extensive experiments on a simulated network control system demonstrate that the proposed framework achieves higher detection accuracy(92.14%)with a reduced false alarm rate(0.81%).Moreover,it not only detects known attacks and vulnerabilities but also uncovers stealthy attacks that induce system state deviations,providing a robust and comprehensive security solution for the safety protection of ICPS.展开更多
基金Supported by Guangdong Provincial Hospital of Chinese Medicine Science and Technology Research Special Project,No.YN2023WSSQ01State Key Laboratory of Traditional Chinese Medicine Syndrome.
文摘BACKGROUND Research has shown that several factors can influence postoperative abnormal liver function;however,most studies on this issue have focused specifically on hepatic and cardiac surgeries,leaving limited research on contributing factors in other types of surgeries.AIM To identify the risk factors for early postoperative abnormal liver function in multiple surgery types and construct a risk prediction model.METHODS This retrospective cohort study involved 3720 surgical patients from 5 surgical departments at Guangdong Provincial Hospital of Traditional Chinese Medicine.Patients were divided into abnormal(n=108)and normal(n=3612)groups based on liver function post-surgery.Univariate analysis and LASSO regression screened variables,followed by logistic regression to identify risk factors.A prediction model was constructed based on the variables selected via logistic re-gression.The goodness-of-fit of the model was evaluated using the Hosm-er–Lemeshow test,while discriminatory ability was measured by the area under the receiver operating characteristic curve.Calibration curves were plotted to visualize the consistency between predicted probabilities and observed outcomes.RESULTS The key factors contributing to abnormal liver function after surgery include elevated aspartate aminotransferase and alanine aminotransferase levels and reduced platelet counts pre-surgery,as well as the sevoflurane use during the procedure,among others.CONCLUSION The above factors collectively represent notable risk factors for postoperative liver function injury,and the prediction model developed based on these factors demonstrates strong predictive efficacy.
基金The Medical Education Research Program of Henan Province,China(Grant No.WJLX2023015)and the Chinese International Medical Foundation for Clinical Pharmacy,China(Grant No.Z-2021-46-2101).
文摘To investigate the correlation between propacetamol and postoperative liver enzyme abnormalities among patients,a retrospective analysis was conducted on inpatients in the thoracic surgery department spanning from January 1 to June 30,2023.Causality assessment regarding propacetamol and postoperative liver enzyme abnormalities was performed using the updated Roussel Uclaf Causality Assessment Method(RUCAM).Furthermore,independent risk factors for liver enzyme abnormalities were identified through both univariate and multivariate analyses,followed by the construction and validation of a clinical nomogram.A total of 247 patients who received propacetamol were ultimately included in the study.Liver enzyme abnormalities post-surgery were more accurately predicted by considering the daily dose of propacetamol and the number of medications(OR(95%CI),4.831(2.797,8.344),P<0.001;10.007(3.878,25.823),P<0.001).A clinical predictive nomogram model was developed,incorporating these two independent risk factors,which exhibited favorable discrimination(AUC(95%CI),0.811(0.750,0.872)),calibration,and decision curve analysis(DCA)demonstrating the highest net benefits across a broad spectrum of threshold probabilities(10%to 90%).The daily dose of propacetamol and the number of medications were found to be independently associated with postoperative liver enzyme abnormalities.This user-friendly nomogram,comprising these two factors,might assist clinicians in assessing the risks of propacetamol-related liver dysfunction following surgery.
文摘BACKGROUND An echocardiogram is an essential tool in the evaluation of potential kidney transplant recipients(KTRs).Despite cardiac clearance,potential KTRs still have structural and functional abnormalities.Identifying the prevalence of these abnormalities and understanding their predictors is vital for optimizing pretransplant risk stratification and improving post-transplant outcomes.AIM To determine the prevalence of left ventricular hypertrophy(LVH),left ventricular systolic dysfunction(LVSD),diastolic dysfunction(DD),pulmonary hypertension(PH),and their predictors,and to assess their impact on graft function in pre-transplant candidates.METHODS The study included all successful transplant candidates older than 14 who had a baseline echocardiogram.Binary logistic regression models were constructed to identify factors associated with LVH,LVSD,DD,and PH.RESULTS Out of 259 patients,LVH was present in 64%(166),12%(31)had LVSD,27.5%(71)had DD,and 66(25.5%)had PH.Independent predictors of LVH included male gender[odds ratio(OR):2.51;95%CI:1.17-5.41 P=0.02],PH(OR=2.07;95%CI:1.11-3.86;P=0.02),DD(OR:2.47;95%CI:1.29-4.73;P=0.006),and dyslipidemia(OR=1.94;95%CI:1.07-3.53;P=0.03).Predictors for LVSD included patients with DD(OR=3.3,95%CI:1.41-7.81;P=0.006)and a family history of coronary artery disease(OR=4.50,95%CI:1.33-15.20;P=0.015).Peritoneal dialysis was an independent predictor for DD(OR=10.03;95%CI:1.71-58.94,P=0.011).The presence of LVH(OR=3.32,95%CI:1.05-10.55,P=0.04)and mild to moderate or moderate to severe mitral regurgitation(OR=4.63,95%CI:1.45-14.78,P=0.01)were significant factors associated with PH.These abnormalities had no significant impact on estimated glomerular filtration at discharge,6 months,1 year,or 2 years post-transplant.CONCLUSION Significant echocardiographic abnormalities persist in a potential transplant candidate despite cardiac clearance,although they don’t affect future graft function.Understanding the risk factors associated with these abnormalities may help clinicians address these factors pre-and post-transplant to achieve better outcomes.
基金Supported by The National Natural Science Foundation of China(No.82101180)the Fund for Beijing Science&Technology Development of TCM(No.BJZYYB-2023-17)the Beijing Municipal Natural Science Foundation grant(No.7252093).
文摘AIM:To define the prevalence and anatomical patterns of paranasal sinus abnormalities(PSA)in thyroid-associated ophthalmopathy(TAO)and to test the hypothesis that TAO is partially driven by contiguous orbital inflammation rather than systemic autoimmunity or generalized orbital pressure.METHODS:Data included ophthalmic assessments and a panel of thyroid function and autoimmune biomarkers.Blinded radiological analysis of orbital computed tomography(CT)scans was performed to quantify sinus abnormalities and extraocular muscles(EOMs)involvement.Patients were categorized into two groups based on CT findings,those with no radiological evidence of sinus abnormalities(non-PSA control group)and those with identifiable PSA.Furthermore,ethmoid sinus mucosal biopsies from a subset of TAO patients and noninflammatory controls were subjected to histopathological analysis.RESULTS:Totally 121 TAO patients(mean age 42.4±12.8y,range 10-78y),male:female=42:79,were included.PSA was identified in 44.6%(n=54)of patients,with a distribution anatomically restricted to the maxillary(50.0%isolated)and ethmoid sinuses(18.5%isolated;29.6%combined).Compared to the non-PSA group(n=67),patients with PSA were significantly older(45.1±11.8 vs 40.3±13.2y;P=0.040)and were more likely to be male(55.6%vs 17.9%;P<0.001).They also had significantly higher proptosis(22.1±3.2 vs 20.7±2.9 mm;P<0.001).Medial/inferior rectus involvement was most frequent(88.4%vs 89.3%).Histopathological analysis of sinus mucosa from PSA patients provided direct evidence of pathology,revealing a dense,chronic lymphoplasmacytic infiltrate and submucosal edema,validating the radiological findings as a true inflammatory process.No significant correlation was found with systemic autoimmune markers,including thyroid-stimulating hormone(TSH)receptor antibodies(TRAb,median 4.86 vs 2.71 IU/L,P=0.104).CONCLUSION:TAO is associated with a high prevalence of PSA in a pattern consistent with the orbital anatomy.The correlation with ipsilateral muscle thickening combined with the lack of association with proptosis laterality or systemic biomarkers lend strong support to a model of contiguous inflammation over systemic autoimmunity,a hypothesis that warrants further validation through longitudinal and mechanistic studies.
基金supported by the Key Project of Natural Science Foundation of Tianjin(No.23JCZDJC00330)Tianjin Municipal Education Commission Scientific Research Program(No.2022ZD056).
文摘Prenatal exposure to bisphenols and metals has raised significant concerns regarding their potential impact on fetal development,particularly the risk of fetal chromosome numerical abnormalities(CNA).In this case-control study,we analyzed bisphenol and metal concentrations in amniotic fluid of high-risk pregnant women undergoing amniocentesis.Concentrations of bisphenols and metals were measured using ultra-performance liquid chromatography-tandem mass spectrometry and inductively coupled plasma-mass spectrometry,respectively.Logistic regression and quantile-based g-computation were applied to evaluate individual and combined effects,while dose-response relationships were assessed using restricted cubic splines.Our findings indicated that bisphenol S(BPS),bisphenol Z(BPZ),bisphenol AF(BPAF),antimony(Sb),and vanadium(V)were significantly associated with an increased risk of CNA when analyzed individually,whereas manganese,iron,copper(Cu),nickel(Ni),and zinc(Zn)were significantly and inversely associated with CNA risk.Combined exposure to bisphenol and metal mixtures was associated with an increased risk of CNA in multi-pollutant models.Cu and Ni exhibited a positive additive interaction.Furthermore,BPS,BPZ,and BPAF were individually associated with an increased risk of Down syndrome,while Zn was associated with a decreased risk of Down syndrome.BPS,Sb,V,and Zn were individually associated with an increased risk of Klinefelter syndrome.These findings underscore the potential role of prenatal bisphenol and metal exposure in the pathogenesis of fetal CNA,highlighting both additive and synergistic effects.
基金supported by y the Applied Research Advancement Project in Engineering University of PAP(WYY202304)Research and Innovation Team Project in Engineering University of PAP(KYTD202306)Funding for postgraduate education and teaching.
文摘Aiming at the problem of imbalance between detection accuracy and algorithm model lightweight in UAV aerial image target detection algorithm,a lightweight multi-category abnormal behavior detection algorithm based on improved YOLOv11n is designed.By integrating multi-head grouped self-attention mechanism and Partial-Conv,a two-way feature grouping fusion module(DFPF)was designed,which carried out effective channel segmentation and fusion strategies to reduce redundant calculations andmemory access.C3K2 module was improved,and then unstructured pruning and feature distillation technologywere used.The algorithmmodel is lightweight,and the feature extraction ability for airborne visual abnormal behavior targets is strengthened,and the computational efficiency of the model is improved.Finally,we test the generalization of the baseline model and the improved model on the VisDrone2019 dataset.The results show that com-pared with the baseline model,the detection accuracy of the final improved model on the airborne visual abnormal behavior dataset is improved from 90.2% to 94.8%,and the model parameters are reduced by 50.9% to meet the detection requirements of high efficiency and high precision.The detection accuracy of the improved model on the Vis-Drone2019 public dataset is 1.3% higher than that of the baseline model,indicating the effectiveness of the improved method in this paper.
文摘Nail changes following upper extremity transplantation(UET)cannot be overlooked as they possess diagnostic and prognostic relevance in allotransplantation of upper limbs.This comprehensive review explores nail and nail bed related changes encountered in UET recipients in the literature.The differential diagnosis of nail abnormalities in UET includes a wide range of systemic,local and iatrogenic conditions other than immune responses to the allograft.It requires interdisciplinary evaluation by primary transplant surgeons,pathologists,dermatologists and immunologists.The possible underlying mechanisms of nail pathology in UET and the management are discussed.It also underscores the importance of onychodystrophy and need for timely intervention and to improve outcomes in UET recipients.
基金supported by the National Natural Science Foundation of China(62271337,62371326,and 62371328)the National Key Research and Development Program of China(2019FYC1710204)+1 种基金the National Clinical Key Specialty Construction Project(10000015Z155080000004)the Natural Science Foundation of Jiangsu Province(BK20231310).
文摘Advances in optical coherence tomography(OCT)technology allow a clear view of the vitreoretinal interface(VRI).The abnormality of the VRI is one of the common symptoms of high myopia,mainly including posterior vitreous detachment(PVD)and epiretinal membrane(ERM).They can cause severe damage to the structure and function of the retina,leading to permanent vision loss.Therefore,fully automated detection of abnormalities at the VRI is crucial for the management of high myopia.This paper presents a DS-YOLOv7 network aimed at accurately identifying abnormalities,including partial PVD,complete PVD,and ERM from retinal OCT images.Built upon the YOLOv7 network,the proposed model integrates the advanced dynamic snake convolution(DSConv)module to capture the curvilinear characteristics of lesions,and the mixture of attention and convolution(ACMix)module to improve the precision and robustness of feature extraction through effective fusion of self-attention mechanisms and convolution.Moreover,the introduction of the efficient complete intersection-over-union(ECIoU)loss function further enhances the coordinate regression capability of the model.Threefold cross-validation on a dataset with 1973 OCT B-scans from 46 patients shows that the DS-YOLOv7 achieved superior performance in vitreoretinal interface abnormality detection,with mAP@0.5 of 0.714,mAP@0.75 of 0.438,and mAP@0.5:0.95 of 0.424.The proposed model can provide an accurate and efficient diagnostic tool for patients with high myopia.
基金support from the National Key R&D Program of China(Grant No.2020YFB1711100).
文摘To address the issue of abnormal energy consumption fluctuations in the converter steelmaking process,an integrated diagnostic method combining the gray wolf optimization(GWO)algorithm,support vector machine(SVM),and K-means clustering was proposed.Eight input parameters—derived from molten iron conditions and external factors—were selected as feature variables.A GWO-SVM model was developed to accurately predict the energy consumption of individual heats.Based on the prediction results,the mean absolute percentage error and maximum relative error of the test set were employed as criteria to identify heats with abnormal energy usage.For these heats,the K-means clustering algorithm was used to determine benchmark values of influencing factors from similar steel grades,enabling root-cause diagnosis of excessive energy consumption.The proposed method was applied to real production data from a converter in a steel plant.The analysis reveals that heat sample No.44 exhibits abnormal energy consumption,due to gas recovery being 1430.28 kg of standard coal below the benchmark level.A secondary contributing factor is a steam recovery shortfall of 237.99 kg of standard coal.This integrated approach offers a scientifically grounded tool for energy management in converter operations and provides valuable guidance for optimizing process parameters and enhancing energy efficiency.
文摘Early and accurate detection of bone cancer and marrow cell abnormalities is critical for timely intervention and improved patient outcomes.This paper proposes a novel hybrid deep learning framework that integrates a Convolutional Neural Network(CNN)with a Bidirectional Long Short-Term Memory(BiLSTM)architecture,optimized using the Firefly Optimization algorithm(FO).The proposed CNN-BiLSTM-FO model is tailored for structured biomedical data,capturing both local patterns and sequential dependencies in diagnostic features,while the Firefly Algorithm fine-tunes key hyperparameters to maximize predictive performance.The approach is evaluated on two benchmark biomedical datasets:one comprising diagnostic data for bone cancer detection and another for identifying marrow cell abnormalities.Experimental results demonstrate that the proposed method outperforms standard deep learning models,including CNN,LSTM,BiLSTM,and CNN-LSTM hybrids,significantly.The CNNBiLSTM-FO model achieves an accuracy of 98.55%for bone cancer detection and 96.04%for marrow abnormality classification.The paper also presents a detailed complexity analysis of the proposed algorithm and compares its performance across multiple evaluation metrics such as precision,recall,F1-score,and AUC.The results confirm the effectiveness of the firefly-based optimization strategy in improving classification accuracy and model robustness.This work introduces a scalable and accurate diagnostic solution that holds strong potential for integration into intelligent clinical decision-support systems.
基金supported by the project in National Research Centre under grant number: 10090013, Cairo, Egypt
文摘Objective: To explore the genotoxic potential and histopathological changes induced in liver, kidney, testis, brain and heart after using the antibiotic drug amoxicillin/clavulanic acid(4:1).Methods: The study included chromosomal aberration analysis in bone-marrow and mouse spermatocytes, induction of sperm morphological abnormalities and histopathological changes in different body organs. The drug was administrated orally at a dose of81 mg/kg body weight twice daily(Total = 162 mg/kg/day) for various periods of time equivalent to 625 mg/men(twice daily).Results: The results revealed non-significant chromosomal aberrations induced after treatment with amoxicillin/clavulanic acid(AC) in both bone marrow and mouse spermatocytes after 7 and 10 days treatment. On the other hand, statistically significant percentages of sperm morphological abnormalities were recorded. Such percentage reached 8.10 ± 0.55, 9.86 ± 0.63 and 12.12 ± 0.58 at the three time intervals tested(7, 14 and 35 days after the 1 st treatment respectively)(treatment performed for 5 successive days) compared with 2.78 ± 0.48 for the control. The results also revealed histopathological changes in different body organs after AC treatment which increased with the prolongation of the period of therapy. Congestion of central vain, liver hemorrhage and hydropic changes in hepatocytes were noticed in the liver. Degenerative changes were found in kidney glomerulus and tubules while testis showed atrophy of seminiferous tubules, and reduction of spermatogenesis. AC also induced neurotoxicity and altered brain neurotransmitter levels. Hemorrhage in the myocardium, disruption of cardiac muscle fibers and pyknotic nuclei in cardiomyocytes were recorded as side effects of AC in heart tissue.Conclusions: The results concluded that AC treatment induced sperm morphological abnormalities and histopathological changes in different body organs. Clinicians must be aware of such results while describing the drug.
基金We would like to express our gratitude to Mrs.Pingping An(Wuhan Institute of Physics and Mathematics,Chinese Academy of Sciences)for her help in housing the animals.This work was supported by grants from the National Natural Science Foundation of China(8187051484,8157050329,81600933)the Interdisciplinary Medicine Seed Fund of Peking University(BMU2017MC006)the Youth Innovation Promotion Association of the Chinese Academy of Sciences,China(Y6Y0021004).
文摘Abnormal postoperative neurobehavioral performance(APNP)is a common phenomenon in the early postoperative period.The disturbed homeostatic status of metabolites in the brain after anesthesia and surgery might make a significant contribution to APNP.The dynamic changes of metabolites in different brain regions after anesthesia and surgery,as well as their potential association with APNP are still not well understood.Here,we used a battery of behavioral tests to assess the effects of laparotomy under isoflurane anesthesia in aged mice,and investigated the metabolites in 12 different sub-regions of the brain at different time points using proton nuclear magnetic resonance('H-NMR)spectroscopy.The abnormal neurobehavioral performance occurred at 6 h and/or 9 h,and recovered at 24 h after anesthesia/surgery.Compared with the control group,the altered metabolite of the model group at 6 h was aspartate(Asp),and the difference was mainly displayed in the cortex;while significant changes at 9 h occurred predominantly in the cortex and hippocampus,and the corresponding metabolites were Asp and glutamate(Glu).All changes returned to baseline at 24 h.The altered metabolic changes could have occurred as a result of the acute APNP,and the metabolites Asp and Glu in the cortex and hippocampus could provide preliminary evidence for understanding the APNP process.
基金Key Research and Development Plan of Shaanxi Province(2023-YBGY-493)。
文摘As-forged WSTi6421 titanium alloy billet afterβannealing was investigated.Abnormally coarse grains larger than adjacent grains could be observed in the microstructures,forming abnormal grain structures with uneven size distribution.Through electron backscattered diffraction(EBSD),the forged microstructure at various locations of as-forged WSTi6421 titanium alloy billet was analyzed,revealing that the strength of theβphase cubic texture generated by forging significantly influences the grain size afterβannealing.Heat treatment experiments were conducted within the temperature range from T_(β)−50°C to T_(β)+10°C to observe the macro-and micro-morphologies.Results show that the cubic texture ofβphase caused by forging impacts the texture of the secondaryαphase,which subsequently influences theβphase formed during the post-βannealing process.Moreover,the pinning effect of the residual primaryαphase plays a crucial role in the growth ofβgrains during theβannealing process.EBSD analysis results suggest that the strength ofβphase with cubic texture formed during forging process impacts the orientation distribution differences ofβgrains afterβannealing.Additionally,the development of grains with large orientations within the cubic texture shows a certain degree of selectivity duringβannealing,which is affected by various factors,including the pinning effect of the primaryαphase,the strength of the matrix cubic texture,and the orientation relationship betweenβgrain and matrix.Comprehensively,the stronger the texture in a certain region,the less likely the large misoriented grains suffering secondary growth,thereby aggregating the difference in microstructure and grain orientation distribution across different regions afterβannealing.
基金supported by the Budgeted Fund of Shanghai University of Traditional Chinese Medicine(Natural Science)(No.2021LK037)the Open Project of Qinghai Province Key Laboratory of Tibetan Medicine Pharmacology and Safety Evaluation(No.2021-ZY-03).
文摘Objective Rheumatoid arthritis(RA)is a systemic autoimmune disease that affects the small joints of the whole body and degrades the patients’quality of life.Zhengqing Fengtongning(ZF)is a traditional Chinese medicine preparation used to treat RA.ZF may cause liver injury.In this study,we aimed to develop a prediction model for abnormal liver function caused by ZF.Methods This retrospective study collected data from multiple centers from January 2018 to April 2023.Abnormal liver function was set as the target variable according to the alanine transaminase(ALT)level.Features were screened through univariate analysis and sequential forward selection for modeling.Ten machine learning and deep learning models were compared to find the model that most effectively predicted liver function from the available data.Results This study included 1,913 eligible patients.The LightGBM model exhibited the best performance(accuracy=0.96)out of the 10 learning models.The predictive metrics of the LightGBM model were as follows:precision=0.99,recall rate=0.97,F1_score=0.98,area under the curve(AUC)=0.98,sensitivity=0.97 and specificity=0.85 for predicting ALT<40 U/L;precision=0.60,recall rate=0.83,F1_score=0.70,AUC=0.98,sensitivity=0.83 and specificity=0.97 for predicting 40≤ALT<80 U/L;and precision=0.83,recall rate=0.63,F1_score=0.71,AUC=0.97,sensitivity=0.63 and specificity=1.00 for predicting ALT≥80 U/L.ZF-induced abnormal liver function was found to be associated with high total cholesterol and triglyceride levels,the combination of TNF-αinhibitors,JAK inhibitors,methotrexate+nonsteroidal anti-inflammatory drugs,leflunomide,smoking,older age,and females in middle-age(45-65 years old).Conclusion This study developed a model for predicting ZF-induced abnormal liver function,which may help improve the safety of integrated administration of ZF and Western medicine.
基金supported by the National Natural Science Foundation of China(No.82171599 and No.32270901)the National Key Research and Developmental Program of China(2022YFC2702601 and 2022YFA0806303)the Global Select Project(DJKLX-2022010)of the Institute of Health and Medicine,Hefei Comprehensive National Science Center.
文摘Male infertility can result from impaired sperm motility caused by multiple morphological abnormalities of the flagella(MMAF).Distinct projections encircling the central microtubules of the spermatozoal axoneme play pivotal roles in flagellar bending and spermatozoal movement.Mammalian sperm-associated antigen 17(SPAG17)encodes a conserved axonemal protein of cilia and flagella,forming part of the C1a projection of the central apparatus,with functions related to ciliary/flagellar motility,skeletal growth,and male fertility.This study investigated two novel homozygous SPAG17 mutations(M1:NM_206996.2,c.829+1G>T,p.Asp212_Glu276del;and M2:c.2120del,p.Leu707*)identified in four infertile patients from two consanguineous Pakistani families.These patients displayed the MMAF phenotype confirmed by Papanicolaou staining and scanning electron microscopy assays of spermatozoa.Quantitative real-time polymerase chain reaction(PCR)of patients’spermatozoa also revealed a significant decrease in SPAG17 mRNA expression,and immunofluorescence staining showed the absence of SPAG17 protein signals along the flagella.However,no apparent ciliary-related symptoms or skeletal malformations were observed in the chest X-rays of any of the patients.Transmission electron microscopy of axoneme cross-sections from the patients showed incomplete C1a projection and a higher frequency of missing microtubule doublets 1 and 9 compared with those from fertile controls.Immunofluorescence staining and Western blot analyses of spermatogenesis-associated protein 17(SPATA17),a component of the C1a projection,and sperm-associated antigen 6(SPAG6),a marker of the spring layer,revealed disrupted expression of both proteins in the patients’spermatozoa.Altogether,these findings demonstrated that SPAG17 maintains the integrity of spermatozoal flagellar axoneme,expanding the phenotypic spectrum of SPAG17 mutations in humans.
文摘The rapid integration of Internet of Things(IoT)technologies is reshaping the global energy landscape by deploying smart meters that enable high-resolution consumption monitoring,two-way communication,and advanced metering infrastructure services.However,this digital transformation also exposes power system to evolving threats,ranging from cyber intrusions and electricity theft to device malfunctions,and the unpredictable nature of these anomalies,coupled with the scarcity of labeled fault data,makes realtime detection exceptionally challenging.To address these difficulties,a real-time decision support framework is presented for smart meter anomality detection that leverages rolling time windows and two self-supervised contrastive learning modules.The first module synthesizes diverse negative samples to overcome the lack of labeled anomalies,while the second captures intrinsic temporal patterns for enhanced contextual discrimination.The end-to-end framework continuously updates its model with rolling updated meter data to deliver timely identification of emerging abnormal behaviors in evolving grids.Extensive evaluations on eight publicly available smart meter datasets over seven diverse abnormal patterns testing demonstrate the effectiveness of the proposed full framework,achieving average recall and F1 score of more than 0.85.
文摘Cervical cancer is the fourth most common cancer worldwide, accounting for 6.8% of new cancer cases and 8.1% of cancer-related deaths. About 85% of these deaths occurred in low- and middle-income countries. The aim of this study was to assess the frequency and distribution of the human papillomavirus (HPV) genotypes in women showing cytological abnormalities of the cervix at the Sourô SANOU University Hospital (CHUSS) in Bobo-Dioulasso, Burkina Faso. This is a descriptive study of women recruited at the CHUSS. The cervico-uterine smear examination was carried out at the CHUSS Anatomy and Pathology Department for cervical cancer screening. The data were collected from women with atypical cells on their cervico-uterine smear. Cervicovaginal samples were taken from consenting women and HPV genotyping was performed using the HPV Direct FLOW CHIP kit at CERBA. We obtained approval from the ethics committee. The data were analyzed using the SPSS 26 software. The results of the study showed that 67.79% of the participants were aged between 50 and 65, a group that is particularly vulnerable to persistent infection with high-risk oncogenic HPV genotypes. Of the women screened, 40.7% were HPV positive and 29.2% had multiple infections. The most common genotypes were HPV 35, followed by HPV 18, 52, 58 and 66. These data highlight the need for increased surveillance and targeted prevention strategies among this female population.
基金supported by the National Natural Science Foundation of China(NSFC)under grant No.62371187the Hunan Provincial Natural Science Foundation of China under Grant Nos.2024JJ8309 and 2023JJ50495.
文摘The integration of cloud computing into traditional industrial control systems is accelerating the evolution of Industrial Cyber-Physical System(ICPS),enhancing intelligence and autonomy.However,this transition also expands the attack surface,introducing critical security vulnerabilities.To address these challenges,this article proposes a hybrid intrusion detection scheme for securing ICPSs that combines system state anomaly and network traffic anomaly detection.Specifically,an improved variation-Bayesian-based noise covariance-adaptive nonlinear Kalman filtering(IVB-NCA-NLKF)method is developed to model nonlinear system dynamics,enabling optimal state estimation in multi-sensor ICPS environments.Intrusions within the physical sensing system are identified by analyzing residual discrepancies between predicted and observed system states.Simultaneously,an adaptive network traffic anomaly detection mechanism is introduced,leveraging learned traffic patterns to detect node-and network-level anomalies through pattern matching.Extensive experiments on a simulated network control system demonstrate that the proposed framework achieves higher detection accuracy(92.14%)with a reduced false alarm rate(0.81%).Moreover,it not only detects known attacks and vulnerabilities but also uncovers stealthy attacks that induce system state deviations,providing a robust and comprehensive security solution for the safety protection of ICPS.
