ObjectiveFunctional near-infrared spectroscopy (fNIRS), a novel non-invasive technique for monitoring cerebral activity, can be integrated with upper limb rehabilitation robots to facilitate the real-time assessment of neurological rehabilitation outcomes. The rehabilitation robot is designed with 3 training modes: passive, active, and resistance. Among these, the resistance mode has been demonstrated to yield superior rehabilitative outcomes for patients with a certain level of muscle strength. The control modes in the resistance mode can be categorized into dynamic and static control. However, the effects of different control modes in the resistance mode on the motor function of patients with upper limb hemiplegia in stroke remain unclear. Furthermore, the effects of force, an important parameter of different control modes, on the activation of brain regions have rarely been reported. This study investigates the effects of dynamic and static resistance modes under varying resistance levels on cerebral functional alterations during motor rehabilitation in post-stroke patients. MethodsA cohort of 20 stroke patients with upper limb dysfunction was enrolled in the study, completing preparatory adaptive training followed by 3 intensity-level tasks across 2 motor paradigms. The bilateral prefrontal cortices (PFC), bilateral primary motor cortices (M1), bilateral primary somatosensory cortices (S1), and bilateral premotor and supplementary motor cortices (PM) were examined in both the resting and motor training states. The lateralization index (LI), phase locking value (PLV), network metrics were employed to examine cortical activation patterns and topological properties of brain connectivity. ResultsThe data indicated that both dynamic and static modes resulted in significantly greater activation of the contralateral M1 area and the ipsilateral PM area when compared to the resting state. The static patterns demonstrated a more pronounced activation in the contralateral M1 in comparison to the dynamic patterns. The results of brain network analysis revealed significant differences between the dynamic and resting states in the contralateral PFC area and contralateral M1 area (F=4.709, P=0.038), as well as in the contralateral PM area and ipsilateral M1 area (F=4.218, P=0.049). Moreover, the findings indicated a positive correlation between the activation of the M1 region and the increase in force in the dynamic mode, which was reversed in the static mode. ConclusionBoth dynamic and static resistance training modes have been demonstrated to activate the corresponding brain functional regions. Dynamic resistance modes elicit greater oxygen changes and connectivity to the region of interest (ROI) than static resistance modes. Furthermore, the effects of increasing force differ between the two modes. In patients who have suffered a stroke, dynamic modes may have a more pronounced effect on the activation of exercise-related functional brain regions.

Background Occupational disease diagnosis appraisal is an appeal procedure initiated when a party disagrees with the occupational disease diagnosis conclusion. It is a legal procedure to safeguard the health rights of employees and the legitimate rights and interests of employers. Objective To analyze the data of occupational disease diagnosis appraisal in Shanghai, identify existing problems, and provide suggestions for improving. Methods Statistical analysis was conducted on basic situation, characteristics of workers and employers, disease classification, and consistency between diagnosis and appraisal conclusions of all occupational disease diagnosis appraisal cases from 2012 to 2024. All diagnosis conclusions were named in accordance with the Classified Catalogue of Occupational Diseases included employers were classified according to the Measures for the Statistical Classification of Large, Medium, Small and Micro Enterprises" and the Notice on Adjusting the Provisions for Classifying Enterprise Registration Types; industry classification followed the Industrial Classification for National Economic Activities (GB/T 4754-2017). Results From 2012 to 2024, a total of 260 cases of occupational diseases diagnosis appraisal were closed. The main diagnosis were 138 cases of ear, nose, throat, and oral diseases (53.1%), chemical poisoning (18.8%), and pneumoconiosis and other respiratory diseases (16.2%). The proportion of ear, nose, throat, and oral diseases gradually increased (2022 excluded). The incidence of annual municipal and provincial cases decreased by 76.3% and 85.0% respectively (2024 vs 2012). The consistency rate of conclusions between appraisal and diagnosis gradually increased. The total consistency rates between final appraisals and diagnostic conclusions were 81.5%, and 79.7%, 87.8%, 100.0%, 85.0% for ear, nose, throat, and oral diseases, chemical poisoning, and pneumoconiosis and other respiratory system diseases, respectively. Specifically, the consistency rates were 80.1% and 80.0% for noise-induced deafness and chronic benzene poisoning. In terms of inconsistency reasons, "inconsistent interpretation of standards and excessive discretion in standard application" accounted for 43.8%, followed by "failure to correctly apply standards" (31.3%) and and "discrepancies in occupational exposure history recognition" (15.6%). Conclusion The revisions and improvements of the legal system for occupational disease diagnosis appraisal have played a positive role in improving the consistency of conclusions between appraisal and diagnosis of occupational diseases in Shanghai. It is suggested to further strengthening the publicity and training of occupational disease diagnosis standards to improve the quality of occupational disease diagnosis.

Medical institutions, with their clinical practice foundation and abundant human use experience data, have become important carriers for the inheritance and innovation of traditional Chinese medicine(TCM) and the "cradles" of the preparation of new TCM. To effectively promote the transformation of new TCM originating from the TCM clinical practice in medical institutions and establish an effective evaluation index system for the transformation of new TCM conforming to the characteristics of TCM, consensus experts adopted the literature research, questionnaire survey, Delphi method, etc. By focusing on the policy and technical evaluation of new TCM originating from the TCM clinical practice in medical institutions, a comprehensive evaluation from the dimensions of drug safety, efficacy, feasibility, and characteristic advantages was conducted, thus forming a comprehensive evaluation system with four primary indicators and 37 secondary indicators. The expert consensus reached aims to encourage medical institutions at all levels to continuously improve the high-quality research and development and transformation of new TCM originating from the TCM clinical practice in medical institutions and targeted at clinical needs, so as to provide a decision-making basis for the preparation, selection, cultivation, and transformation of new TCM for medical institutions, improve the development efficiency of new TCM, and precisely respond to the public medication needs.
Medicine, Chinese Traditional/standards* ; Humans ; Consensus ; Drugs, Chinese Herbal/therapeutic use* ; Surveys and Questionnaires

The study investigated the intrinsic changes in material basis of Angelicae Sinensis Radix during wine processing by headspace-gas chromatography-ion mobility spectrometry(HS-GC-IMS), headspace-solid phase microextraction-gas chromatography-mass spectrometry(HS-SPME-GC-MS), and ultra-high performance liquid chromatography-quadrupole-orbitrap mass spectrometry(UPLC-Q-Orbitrap-MS) combined with chemometrics. HS-GC-IMS fingerprints of Angelicae Sinensis Radix before and after wine processing were established to analyze the variation trends of volatile components and characterize volatile small-molecule substances before and after processing. Principal component analysis(PCA) and orthogonal partial least squares-discriminant analysis(OPLS-DA) were employed for differentiation and difference analysis. A total of 89 volatile components in Angelicae Sinensis Radix were identified by HS-GC-IMS, including 14 unsaturated hydrocarbons, 16 aldehydes, 13 ketones, 9 alcohols, 16 esters, 6 organic acids, and 15 other compounds. HS-SPME-GC-MS detected 118 volatile components, comprising 42 unsaturated hydrocarbons, 11 aromatic compounds, 30 alcohols, 8 alkanes, 6 organic acids, 4 ketones, 7 aldehydes, 5 esters, and 5 other volatile compounds. UPLC-Q-Orbitrap-MS identified 76 non-volatile compounds. PCA revealed distinct clusters of raw and wine-processed Angelicae Sinensis Radix samples across the three detection methods. Both PCA and OPLS-DA effectively discriminated between the two groups, and 145 compounds(VIP>1) were identified as critical markers for evaluating processing quality, including 4-methyl-3-penten-2-one, ethyl 2-methylpentanoate, and 2,4-dimethyl-1,3-dioxolane detected by HS-GC-IMS, angelic acid, β-pinene, and germacrene B detected by HS-SPME-GC-MS, and L-tryptophan, licoricone, and angenomalin detected by UPLC-Q-Orbitrap-MS. In conclusion, the integration of the three detection methods with chemometrics elucidates the differences in the chemical material basis between raw and wine-processed Angelicae Sinensis Radix, providing a scientific foundation for understanding the processing mechanisms and clinical applications of wine-processed Angelicae Sinensis Radix.
Wine/analysis* ; Gas Chromatography-Mass Spectrometry/methods* ; Chromatography, High Pressure Liquid/methods* ; Angelica sinensis/chemistry* ; Solid Phase Microextraction/methods* ; Drugs, Chinese Herbal/isolation & purification* ; Chemometrics ; Volatile Organic Compounds/chemistry* ; Principal Component Analysis ; Ion Mobility Spectrometry/methods*

Accumulating evidence has demonstrated that nucleic acid-based therapies are promising for atherosclerosis. However, nearly all nucleic acid delivery systems developed for atherosclerosis necessitate injection, which results in rapid elimination and poor patient compliance. Consequently, oral delivery strategies capable of targeting atherosclerotic plaques are imperative for nucleic acid therapeutics. Herein we report the development of yeast-derived capsules (YCs) packaging an antisense oligonucleotide (AM33) targeting microRNA-33 (miR-33) for the oral treatment of atherosclerosis. YCs provide stability for AM33, preventing its premature release in the gastrointestinal tract. AM33-containing YCs, defined as YAM33, showed high transfection in macrophages, thus promoting cholesterol efflux and inhibiting foam cell formation by regulating the target genes/proteins of miR-33. Orally delivered YAM33 effectively accumulated within atherosclerotic plaques in ApoE ^-/- mice, primarily by transepithelial absorption via M cells in Peyer's patches and subsequent translocation via macrophages through the lymphatic system. Inhibition of miR-33 by oral YAM33 significantly delayed the progression of atherosclerosis. Moreover, oral treatment with YCs co-delivering AM33 and atorvastatin afforded significantly enhanced anti-atherosclerotic effects. Our findings suggest that yeast-based microcapsules represent an effective carrier for oral delivery of nucleic acids, either alone or in combination with existing drugs, offering a promising approach for precision therapy of atherosclerotic diseases.

Objective To explore the therapeutic mechanism of Euonymus alatus for diabetic kidney disease(DKD).Methods TCMSP,PubChem and Swiss Target Prediction databases were used to obtain the active ingredients in Euonymus alatus and their targets.GEO database and R language were used to analyze the differentially expressed genes in DKD.The therapeutic targets of DKD were obtained using GeneCards,DisGeNet,OMIM and TTD databases.The protein-protein interaction network and the"drug-component-target-disease"network were constructed for analyzing the topological properties of the core targets,which were functionally annotated using GO and KEGG pathway enrichment analyses.Molecular docking was performed for the core targets and the main pharmacologically active components,and the results were verified in db/db mice.Results Analysis of GSE96804,GSE30528 and GSE30529 datasets(including 60 DKD patients and 45 normal samples)identified 111 differentially expressed genes in DKD.Network pharmacology analysis obtained 161 intersecting genes between the target genes of Euonymus alatus and DKD,including the key core target genes SRC,EGFR,and AKT1.The core active ingredients of Euonymus alatus were quercetin,kaempferol,diosmetin,and naringenin,which were associated with responses to xenobiotic stimulionus and protein phosphorylation and regulated EGFR tyrosine kinase inhibitor resistance pathways.Molecular docking suggested good binding activities of the core active components of Euonymus alatus with the core targets.In db/db mouse models of DKD,treatment with Euonymus alatus obviously ameliorated kidney pathologies,significantly inhibited renal expressions of SRC,EGFR and AKT1,and delayed the progression of DKD.Conclusion Euonymus alatus contains multiple active ingredients such as quercetin,kakaferol,diosmetin,naringenin,which regulate the expressions of SRC,EGFR,and AKT1 to affect the EGFR tyrosine kinase inhibitor resistance signaling pathway to delay the progression of DKD.

Objective To explore the therapeutic mechanism of Euonymus alatus for diabetic kidney disease(DKD).Methods TCMSP,PubChem and Swiss Target Prediction databases were used to obtain the active ingredients in Euonymus alatus and their targets.GEO database and R language were used to analyze the differentially expressed genes in DKD.The therapeutic targets of DKD were obtained using GeneCards,DisGeNet,OMIM and TTD databases.The protein-protein interaction network and the"drug-component-target-disease"network were constructed for analyzing the topological properties of the core targets,which were functionally annotated using GO and KEGG pathway enrichment analyses.Molecular docking was performed for the core targets and the main pharmacologically active components,and the results were verified in db/db mice.Results Analysis of GSE96804,GSE30528 and GSE30529 datasets(including 60 DKD patients and 45 normal samples)identified 111 differentially expressed genes in DKD.Network pharmacology analysis obtained 161 intersecting genes between the target genes of Euonymus alatus and DKD,including the key core target genes SRC,EGFR,and AKT1.The core active ingredients of Euonymus alatus were quercetin,kaempferol,diosmetin,and naringenin,which were associated with responses to xenobiotic stimulionus and protein phosphorylation and regulated EGFR tyrosine kinase inhibitor resistance pathways.Molecular docking suggested good binding activities of the core active components of Euonymus alatus with the core targets.In db/db mouse models of DKD,treatment with Euonymus alatus obviously ameliorated kidney pathologies,significantly inhibited renal expressions of SRC,EGFR and AKT1,and delayed the progression of DKD.Conclusion Euonymus alatus contains multiple active ingredients such as quercetin,kakaferol,diosmetin,naringenin,which regulate the expressions of SRC,EGFR,and AKT1 to affect the EGFR tyrosine kinase inhibitor resistance signaling pathway to delay the progression of DKD.

Objective To explore the value of deep learning models in predicting axillary lymph node(ALN)metastasis of breast cancer based on intratumoral and peritumoral dynamic contrast-enhanced magnetic resonance imaging(DCE-MRI).Methods A retrospective analysis was conducted on cases from Tianjin Medical University Cancer Hospital and Laoshan Branch of Affiliated Hospital of Qingdao University,involving a total of 850 lesions in 850 patients.The region of interest within the tumor was delineated at the largest area of the lesion on the first enhancement images and automatically expanded by 3 mm and 6 mm in a conformal fashion.Deep learning prediction models based on ResNet50 were developed via intratumoral,peritumoral,and intratumoral combined peritumoral models,respectively,and a comprehensive prediction model was developed by integrating semantic features of imaging reports.Cases from Tianjin Medical University Cancer Hospital were randomly divided into training and test cohorts in a 7∶3 ratio,while cases from Laoshan Branch of Affiliated Hospital of Qingdao University served as the external validation cohort.The area under the curve(AUC),accuracy,sensitivity,specificity,F1-score,and Brier-score were calculated,respectively.Results The model incorporating intratumoral,peritumoral(3 mm),and semantic features demonstrated the highest performance,with AUC of 0.801[95％confidence interval(CI)0.765-0.845],0.781(95％CI 0.745-0.817),and 0.752(95％CI 0.700-0.793)in the training cohort,test cohort,and external validation cohort,respectively,and there was no significant difference in AUC between combined model and intratumoral/peritumoral model,respectively,but it demonstrated the higher sensitivity and F1-score,and the lower Brier-score.Conclusion Incorporating peritumoral images into the conventional model based on intratumoral images enhanced the predictive ability of ALN metastasis in breast cancer.

Objective To investigate the incidence rate,clinical characteristics,and prognosis of neonatal stroke in Shenzhen,China.Methods Led by Shenzhen Children's Hospital,the Shenzhen Neonatal Data Collaboration Network organized 21 institutions to collect 36 cases of neonatal stroke from January 2020 to December 2022.The incidence,clinical characteristics,treatment,and prognosis of neonatal stroke in Shenzhen were analyzed.Results The incidence rate of neonatal stroke in 21 hospitals from 2020 to 2022 was 1/15 137,1/6 060,and 1/7 704,respectively.Ischemic stroke accounted for 75％(27/36);boys accounted for 64％(23/36).Among the 36 neonates,31(86％)had disease onset within 3 days after birth,and 19(53％)had convulsion as the initial presentation.Cerebral MRI showed that 22 neonates(61％)had left cerebral infarction and 13(36％)had basal ganglia infarction.Magnetic resonance angiography was performed for 12 neonates,among whom 9(75％)had involvement of the middle cerebral artery.Electroencephalography was performed for 29 neonates,with sharp waves in 21 neonates(72％)and seizures in 10 neonates(34％).Symptomatic/supportive treatment varied across different hospitals.Neonatal Behavioral Neurological Assessment was performed for 12 neonates(33％,12/36),with a mean score of(32±4)points.The prognosis of 27 neonates was followed up to around 12 months of age,with 44％(12/27)of the neonates having a good prognosis.Conclusions Ischemic stroke is the main type of neonatal stroke,often with convulsions as the initial presentation,involvement of the middle cerebral artery,sharp waves on electroencephalography,and a relatively low neurodevelopment score.Symptomatic/supportive treatment is the main treatment method,and some neonates tend to have a poor prognosis.

Objective: To describe the clinical features, causal agent and transmission mode of a fever outbreak in a school in Shanghai. Methods: Field epidemiological approaches including case definition development, searching for contacts, distribution of diseases description, environmental sampling and laboratory testing. Results: A total of 16 influenza like cases were included, all concentrated in the one class of grade two, including 15 students and 1 teacher. Among student cases, the incidence rate was 36.59% (15/41), the average age was 7.4 years, the incidence rate was 36.84%(7/19) for boys, 36.36%(8/22) for girls. The clinical course was 5-15 days, with the median of 9 days, and 18.75%(3/16) of the cases stayed studying while sick. The nasopharyngeal swab specimens in 16 cases all tested positive for influenza B, of which 11 tested positive for mycoplasma pneumoniae and 1 case also tested positive for coronavirus OC43. Body temperature, number of mononuclear cells, and treatment time of patients infected with Influenza B and mycoplasma pneumoniae were higher than those of patients infected with influenza B alone( P <0.05). The outbreak lasted for 12 days, all sick students were treated and discharged from hospital, with no severe cases or death, and the outbreak was effectively controlled. Conclusion This campus cluster outbreak caused by influenza B and mycoplasma pneumoniae. Patients with influenza B with mycoplasma pneumoniae have severe symptoms and a long course of illness, suggesting the importance of early management of the epidemic.