Objective To explore the clinical feasibility of predicting ischemic penumbra(IP)in patients with acute cerebral infarction based on multiparameter magnetic resonance imaging(MRI)radiomics and deep learning.Methods A total of 105 patients with acute cerebral infarction treated at our hospital between January 2020 and January 2024 were divided into non-IP(n=36)and IP(n=69)groups according to the results of MRI diffusion-weighted imaging(DWI).The clinical data of the two groups were collected,and multipa-rameter MRI radiomics features were screened.Clinical,radiomics,and deep learning models were constructed,and their distinguishing powers were evaluated.A fused model was constructed,and the receiver operating characteristic(ROC),calibration,and clinical decision curves were used to evaluate the predictive efficacy of the four models.Results Increases in the admission National Institutes of Health Stroke Scale(NIHSS)score,anisotropy score(FA),apparent diffusion coefficient(ADC),average diffusion coefficient(DCavg),and N-acetyl aspartate(NAA)were protective factors for IP.An increase in the lactic acid(Lac)level was a risk factor for IP(P<0.05).Of the six considered deep learning models,the support vector machine model performed the best,with an accuracy of 0.952(100/105),sensi-tivity of 0.957(66/69),and specificity of 0.944(34/36).These three models can distinguish the patients with IP.The four models exhibited high differentiation,accuracy,and effectiveness;the prediction efficiency of the fused model was the highest.Conclusion The fused model based on clinical features,multiparameter MRI radiomics,and deep learning accurately predicts IP in patients with acute cerebral infarction and can be used to provide personalized prediction results.

Objective:To investigate the views of doctors on the incidence and treatment tactics of mild progression after epithelial growth factor receptor tyrosine kinase inhibitor(EGFR-TKI)treatment in lung adenocarcinoma and provide suggestions to optimize the counter-measure strategies.Methods:Convenience sampling was used to conduct an online questionnaire survey for doctors specializing in onco-logy and respiratory diseases.Results:584 valid questionnaires were collected,and all the doctors expressed concerns regarding mild tumor progression after EGFR-TKI treatment.The coping strategies included maintaining the original TKI treatment,adding other treatments to the original TKI,changing the regimen,and performing secondary tissue biopsy,among which,most doctors chose to add other treatments to the original TKI.Conclusions:Doctors have noticed the enlargement of target lesions in still stable disease(SD)and most frequently chose to add other treatments to the original TKI as a coping strategy.This finding can provide a reference for framing future guidelines for large sample prospective clinical studies that are needed to find the most effective synergistic treatment options.

In terms of the complexity of the"left"and"right"concepts,these directional terms not only indicate spatial orientation but also embody hierarchical order,official titles,systemic imbalances,and temporal sequences.This study explains the medical theory of"liver is born on the left and lung is hidden on the right,"and reveals its implications for ascending and descending of qi movement pathways,sequential patterns,non-equilibrium states,and the centrality of the middle,thus linking the connotation of this theory and its application.In view of this,the theory of"liver is born on the left and lung is hidden on the right"can be used in the clinical diagnosis and treatment of qi-blood-body fluid and emotional diseases,and guides disease prevention and treatment,as well as enhances the subjective initiative of health maintenance and longevity.This study not only deepens the modern interpretation of the classical theory but also provides novel perspectives for its application in disease prevention and treatment.

Based on the Delphi method, this study conducted an expert questionnaire survey on the diagnostic criteria of edema in TCM by integrating preliminary literature research, aiming to further standardize the revision of Edema diagnosis in Criteria of Diagnosis and Therapeutic Effect of Diseases and Syndromes in Traditional Chinese Medicine (ZY/T001.1－94). Relevant literature on TCM edema was comprehensively retrieved from CNKI, Wanfang Data, VIP and CBM from 1994 to July 1, 2021. The content extracted from the literature was integrated with the diagnostic criteria outlined in the 1994 Criteria of Diagnosis and Therapeutic Effect of Diseases and Syndromes in Traditional Chinese Medicine to establish the questionnaire item pool; two rounds of Delphi expert surveys were conducted to identify content requiring revisions. Subsequently, the degree of concentration and coordination of the expert opinions were analyzed to determine items for inclusion in the revised draft. Ultimately, the finalized revised diagnostic criteria for edema were developed through expert panel discussions. Results showed expert participation rates of 84.21% and 78.13% in respective survey rounds. The progressive increase in Kendall's coefficient of concordance (Kendall's W=0.169 in Round 1 to Kendall's W=0.368 in Round 2) quantitatively validated enhanced expert consensus (both the degree of concentration and coordination) and systematic alignment of revision proposals for diagnostic items. The study findings demonstrated an urgent need for improving the diagnostic criteria section of the the 1994 Criteria of Diagnosis and Therapeutic Effect of Diseases and Syndromes in Traditional Chinese Medicine, and the proposed revisions would be expected to enhance the applicability and specificity of edema diagnostic standards in clinical practice.

T-cell acute lymphoblastic leukemia (T-ALL) is a highly aggressive hematologic malignancy with a poor prognosis, despite advancements in treatment. Many patients struggle with relapse or refractory disease. Investigating the role of the super-enhancer (SE) regulated gene ubiquitin-specific protease 20 (USP20) in T-ALL could enhance targeted therapies and improve clinical outcomes. Analysis of histone H3 lysine 27 acetylation (H3K27ac) chromatin immunoprecipitation sequencing (ChIP-seq) data from six T-ALL cell lines and seven pediatric samples identified USP20 as an SE-regulated driver gene. Utilizing the Cancer Cell Line Encyclopedia (CCLE) and BloodSpot databases, it was found that USP20 is specifically highly expressed in T-ALL. Knocking down USP20 with short hairpin RNA (shRNA) increased apoptosis and inhibited proliferation in T-ALL cells. In vivo studies showed that USP20 knockdown reduced tumor growth and improved survival. The USP20 inhibitor GSK2643943A demonstrated similar anti-tumor effects. Mass spectrometry, RNA-Seq, and immunoprecipitation revealed that USP20 interacted with hypoxia-inducible factor 1 subunit alpha (HIF1A) and stabilized it by deubiquitination. Cleavage under targets and tagmentation (CUT&Tag) results indicated that USP20 co-localized with HIF1A, jointly modulating target genes in T-ALL. This study identifies USP20 as a therapeutic target in T-ALL and suggests GSK2643943A as a potential treatment strategy.

Objective To explore the clinical feasibility of predicting ischemic penumbra(IP)in patients with acute cerebral infarction based on multiparameter magnetic resonance imaging(MRI)radiomics and deep learning.Methods A total of 105 patients with acute cerebral infarction treated at our hospital between January 2020 and January 2024 were divided into non-IP(n=36)and IP(n=69)groups according to the results of MRI diffusion-weighted imaging(DWI).The clinical data of the two groups were collected,and multipa-rameter MRI radiomics features were screened.Clinical,radiomics,and deep learning models were constructed,and their distinguishing powers were evaluated.A fused model was constructed,and the receiver operating characteristic(ROC),calibration,and clinical decision curves were used to evaluate the predictive efficacy of the four models.Results Increases in the admission National Institutes of Health Stroke Scale(NIHSS)score,anisotropy score(FA),apparent diffusion coefficient(ADC),average diffusion coefficient(DCavg),and N-acetyl aspartate(NAA)were protective factors for IP.An increase in the lactic acid(Lac)level was a risk factor for IP(P<0.05).Of the six considered deep learning models,the support vector machine model performed the best,with an accuracy of 0.952(100/105),sensi-tivity of 0.957(66/69),and specificity of 0.944(34/36).These three models can distinguish the patients with IP.The four models exhibited high differentiation,accuracy,and effectiveness;the prediction efficiency of the fused model was the highest.Conclusion The fused model based on clinical features,multiparameter MRI radiomics,and deep learning accurately predicts IP in patients with acute cerebral infarction and can be used to provide personalized prediction results.

Objective:To explore the significance of any correlation between the cost of the rehabilitation provided to stroke survivors during their hospitalization and the functional levels attained, and to analyze factors influencing that correlation.Methods:The International Classification of Functioning, Disability and Health Rehabilitation Set (ICF-RS) was used to evaluate the functioning of 304 stroke survivors on their days of hospital admission and discharge, as well as on their 10th day in hospital. The cost of their rehabilitation was computed, and demographic and clinical data were collected. A generalized estimation equation was used to analyze the changes in dysfunction with time and its risk factors. The relationship between functional levels and rehabilitation cost and its influencing factors were analyzed.Results:Length of stay, age≥60 and hemorrhagic stroke were significant risk factors for greater dysfunction among the stroke survivors. On the 10th day in hospital and the day before discharge (the 18th day), the frequency of severe dysfunction had decreased. The significant predictors of increased cost were severe or moderate dysfunction, the stage of stroke (sub-acute stage), and non-first rehabilitation.Conclusion:Functional level is a useful predictor of rehabilitation cost. It is influenced by the stage of stroke and non-first rehabilitation.

In terms of the complexity of the"left"and"right"concepts,these directional terms not only indicate spatial orientation but also embody hierarchical order,official titles,systemic imbalances,and temporal sequences.This study explains the medical theory of"liver is born on the left and lung is hidden on the right,"and reveals its implications for ascending and descending of qi movement pathways,sequential patterns,non-equilibrium states,and the centrality of the middle,thus linking the connotation of this theory and its application.In view of this,the theory of"liver is born on the left and lung is hidden on the right"can be used in the clinical diagnosis and treatment of qi-blood-body fluid and emotional diseases,and guides disease prevention and treatment,as well as enhances the subjective initiative of health maintenance and longevity.This study not only deepens the modern interpretation of the classical theory but also provides novel perspectives for its application in disease prevention and treatment.

Objective:To explore the significance of any correlation between the cost of the rehabilitation provided to stroke survivors during their hospitalization and the functional levels attained, and to analyze factors influencing that correlation.Methods:The International Classification of Functioning, Disability and Health Rehabilitation Set (ICF-RS) was used to evaluate the functioning of 304 stroke survivors on their days of hospital admission and discharge, as well as on their 10th day in hospital. The cost of their rehabilitation was computed, and demographic and clinical data were collected. A generalized estimation equation was used to analyze the changes in dysfunction with time and its risk factors. The relationship between functional levels and rehabilitation cost and its influencing factors were analyzed.Results:Length of stay, age≥60 and hemorrhagic stroke were significant risk factors for greater dysfunction among the stroke survivors. On the 10th day in hospital and the day before discharge (the 18th day), the frequency of severe dysfunction had decreased. The significant predictors of increased cost were severe or moderate dysfunction, the stage of stroke (sub-acute stage), and non-first rehabilitation.Conclusion:Functional level is a useful predictor of rehabilitation cost. It is influenced by the stage of stroke and non-first rehabilitation.

Objective:To investigate the views of doctors on the incidence and treatment tactics of mild progression after epithelial growth factor receptor tyrosine kinase inhibitor(EGFR-TKI)treatment in lung adenocarcinoma and provide suggestions to optimize the counter-measure strategies.Methods:Convenience sampling was used to conduct an online questionnaire survey for doctors specializing in onco-logy and respiratory diseases.Results:584 valid questionnaires were collected,and all the doctors expressed concerns regarding mild tumor progression after EGFR-TKI treatment.The coping strategies included maintaining the original TKI treatment,adding other treatments to the original TKI,changing the regimen,and performing secondary tissue biopsy,among which,most doctors chose to add other treatments to the original TKI.Conclusions:Doctors have noticed the enlargement of target lesions in still stable disease(SD)and most frequently chose to add other treatments to the original TKI as a coping strategy.This finding can provide a reference for framing future guidelines for large sample prospective clinical studies that are needed to find the most effective synergistic treatment options.