Endovascular treatment vs drug therapy alone in patients with mild ischemic stroke and large infarct cores

BACKGROUND Treatment decision making is strictly associated with the outcomes in patients with ischemic stroke who show a large core infarct.Medical care alone may result in suboptimal treatment efficacy,and endovascular treatment may be accompanied by safety issues.Whether endovascular treatment is superior to medical care is not well investigated in the clinical studies.AIM To investigate the efficacy of endovascular treatment and drug therapy alone in mild ischemic stroke patients with large infarct cores.METHODS Fifty patients with mild ischemic stroke and 50 patients with acute ischemic stroke caused by anterior large vessel occlusion were selected at the First Affiliated Hospital of Hebei North University between January 2021 and December 2021.Patients were divided into an endovascular therapy group and a drug therapy group according to different treatment methods.In the endovascular therapy group,there were 28 patients with minor stroke and 22 patients with large infarct cores.The drug therapy group had 22 patients with minor stroke and 28 patients with large infarct cores.The National Institutes of Health Stroke Scale(NIHSS) scores were collected and compared between the two groups immediately after the operation and 24 h and 7 d after the operation.The modified Rankin scale(m RS) and/or activity of daily living were assessed at hospital discharge.RESULTS There was no significant difference in NIHSS scores between the two groups before the operation(P > 0.05).NIHSS scores were lower in the endovascular therapy group than in the drug therapy group at 24 h and 7 d after the operation and at hospital discharge(all P < 0.05).The incidence of early neurologic deterioration was significantly lower in the endovascular therapy group than in the drug therapy group(P < 0.05).At hospital discharge,the m RS score was lower in the endovascular treatment group than in the drug therapy group,and the activity of daily living score was better in the endovascular treatment group than in the drug therapy group(all P < 0.05).During a follow-up of 3 mo,17 patients(34.0%) had good prognosis(m RS ≤ 2),33 patients(66.0%) had poor prognosis(m RS > 2),and 11 patients(22.0%) died.In the medical treatment group,16 patients(m RS ≤ 2) had good prognosis(32.0%),34 patients(m RS > 2) had poor prognosis(68.0%),and 14 patients(28.0%) died.There was no significant difference in prognosis and mortality between the two groups(P > 0.05).CONCLUSION Endovascular therapy can improve NIHSS score and m RS score in patients with mild ischemic stroke and large infarct cores.It is suitable for clinical application.

Low-grade fever during COVID-19 convalescence:A report of 3 cases

BACKGROUND Low-grade fever during convalescence is an atypical symptom of coronavirus disease 2019(COVID-19).Reports of such cases are rare,and the mechanism and outcome of low-grade fever during COVID-19 convalescence are not completely clear.We report 3 cases with low-grade fever during COVID-19 convalescence and highlight the main clinical,radiographic,and laboratory characteristics,thereby increasing the level of expertise in the clinical management of COVID-19 during convalescence and facilitating individualized decision-making.CASE SUMMARY We describe 3 patients with COVID-19,two females aged 62 and 66 years and a male 55 years,who had low-grade fever during COVID-19 convalescence.All 3 patients had no other discomfort or comorbidities during low-grade process.Lesions on computed tomography in all 3 patients had resolved during this period.Two patients tested negative on two consecutive severe acute respiratory syndrome coronavirus 2 tests with an interval of at least 24 h between tests.Body temperature in all 3 patients returned to normal after several days without treatment,and fever recurrence was not observed.CONCLUSION Enhancing the knowledge of low-grade fever during COVID-19 convalescence may increase the expertise in the delivery of optimal healthcare services.

Co-expression Network Analysis Identifies Fourteen Hub Genes Associated with Prognosis in Clear Cell Renal Cell Carcinoma

Summary:Renal cancer is a common genitourinary malignance,of which clear cell renal cell carcinoma(ccRCC)has high aggressiveness and leads to most cancer-related deaths.Identification of sensitive and reliable biomarkers for predicting tumorigenesis and progression has great significance in guiding the diagnosis and treatment of ccRCC.Here,we identified 2397 common difTerentially expressed genes(DEGs)using paired normal and tumor ccRCC tissues from GSE53757 and The Cancer Genome Atlas(TCGA).Then,we performed weighted gene co-expression network analysis and protein-protein interaction network analysis,17 candidate hub genes were identified.These candidate hub genes were further validated in GSE36895 and Oncomine database and 14 real hub genes were identified.All the hub genes were up-regulated and significantly positively correlated with pathological stage and histologic grade of ccRCC.Survival analysis showed that the higher expression level of each hub gene tended to predict a worse clinical outcome.ROC analysis showed that all the hub genes can accurately distinguish between tumor and normal samples,and between early stage and advanced stage ccRCC.Moreover,all the hub genes were positively associated with distant metastasis,lymph node infiltration,tumor recurrence and the expression of MKi67,suggesting these genes might promote tumor proliferation,invasion and metastasis.Furthermore,the functional annotation demonstrated that most genes were enriched in cell-cycle related biological function.In summary,our study identified 14 potential biomarkers for predicting tumorigenesis and progression,which might contribute to early diagnosis,prognosis prediction and therapeutic intervention.

PanGu Drug Model: learn a molecule like a human

Dear Editor,Recent achievements in large-scale pre-trained models like GPT-3 and PanGu-α have demonstrated astounding performances in many downstream tasks of natural language processing (NLP),confirming AI to be user-oriented for even industrial applications.Deep learning has been recognized as the most promising technology for pharmaceuticals,a powerful molecule pre-trained model that could economize researchers’tons of time.For the strategic application of AI capabilities to the drug discovery field,we pre-trained a model called PanGu Drug Model with 1.7 billion small molecules from ZINC20 (Irwin et al.,2020),DrugSpaceX(Yang et al.,2021),and UniChem (Chambers et al.,2013).

Facing small and biased data dilemma in drug discovery with enhanced federated learning approaches

Artificial intelligence(AI)models usually require large amounts of high-quality training data,which is in striking contrast to the situation of small and biased data faced by current drug discovery pipelines.The concept of federated learning has been proposed to utilize distributed data from different sources without leaking sensitive information of the data.This emerging decentralized machine learning paradigm is expected to dramatically improve the success rate of AI-powered drug discovery.Here,we simulated the federated learning process with different property and activity datasets from different sources,among which overlapping molecules with high or low biases exist in the recorded values.Beyond the benefit of gaining more data,we also demonstrated that federated training has a regularization effect superior to centralized training on the pooled datasets with high biases.Moreover,different network architectures for clients and aggregation algorithms for coordinators have been compared on the performance of federated learning,where personalized federated learning shows promising results.Our work demonstrates the applicability of federated learning in predicting drug-related properties and highlights its promising role in addressing the small and biased data dilemma in drug discovery.

Comparative study of material point method and upper bound limit analysis in slope stability analysis

The upper bound limit analysis(UBLA)is one of the key research directions in geotechnical engineering and is widely used in engineering practice.UBLA assumes that the slip surface with the minimum factor of safety(FSmin)is the critical slip surface,and then applies it to slope stability analysis.However,the hypothesis of UBLA has not been systematically verified,which may be due to the fact that the traditional numerical method is difficult to simulate the large deformation.In this study,in order to systematically verify the assumption of UBLA,material point method(MPM),which is suitable to simulate the large deformation of continuous media,is used to simulate the whole process of the slope failure,including the large-scale transportation and deposition of soil mass after slope failure.And a series of comparative studies are conducted on the stability of cohesive slopes using UBLA and MPM.The proposed study indicated that the slope angle,internal friction angle and cohesion have a remarkable effect on the slip surface of the cohesive slope.Also,for stable slopes,the calculation results of the two are relatively close.However,for unstable slopes,the slider volume determined by the UBLA is much smaller than the slider volume determined by the MPM.In other words,for unstable slopes,the critical slip surface of UBLA is very different from the slip surface when the slope failure occurs,and when the UBLA is applied to the stability analysis of unstable slope,it will lead to extremely unfavorable results.

GOLM1 suppresses autophagy-mediated anti-tumor immunity in hepatocellular carcinoma

Dear Editor,Immune-mediated tumor elimination depends on the production of cytokines and the recruitment of immune cells in the tumor microenvironment.Cell death-related signals such as ATP release from tumor cells are crucial for the activation of downstream immune responses.^(1)GOLM1,also known as GOLPH2 and GP73 as a Golgi transmembrane protein involved in the transport of protein cargo through the Golgi apparatus has been extensively studied in various cancers for its multifunctional roles in promoting cancer proliferation and metastasis through the AKT/mTOR pathway.