Background: and Purpose Therapeutic target selection in noninvasive brain stimulation for poststroke motor recovery typically relies on the interhemispheric inhibition model, which is effective for mildly affected patients but offers limited benefits for severely affected individuals. The mechanisms governing recovery from moderate-to-severe stroke remain poorly understood, which hinders the development of targeted interventions. Methods: We analyzed resting-state functional magnetic resonance imaging data from patients with unilateral subcortical stroke and moderate-to-severe upper limb deficits, both pre- and postintervention, along with data from healthy controls. We developed a novel dynamic lag analysis method for identifying recovery-related homotopic sensorimotor regions with altered interhemispheric interactions. To further uncover the global reorganization pathway, we developed dynamic lateralization approaches to detect large-scale functional connectivity (FC) alterations associated with the identified regions in transient lateralization states. Results: Dynamic time-lag analysis revealed significantly reduced synchronized states in the homotopic dorsal premotor cortex (PMd) post-intervention compared with pre-intervention, which correlated with motor recovery. Further dynamic lateralization analysis revealed a prolonged segregation state in patients, characterized by weakened interhemispheric and strengthened intrahemispheric interactions. In this state, patients showed decreased FC in the ipsilesional PMd and increased FC in the contralesional PMd with bilateral subcortical networks. These recoveryrelated alterations were absent in the traditional static analysis. Conclusions Dynamic analyses targeting interhemispheric interactions are valuable for understanding neural reorganization after stroke. The diminished interactions between the homotopic PMd indicate a compensatory mechanism. Importantly, a state-dependent compensatory pathway was identified, wherein the contralesional PMd assumes the functions of the ipsilesional PMd through enhanced interactions with subcortical structures, potentially guiding more effective interventions.

Objective:To investigate the impact of frailty on post-stroke depression (PSD) in patients with acute ischemic stroke and to identify risk factors for PSD in order to construct a risk prediction model.Methods:A convenience sampling method was used to recruit a total of 450 patients with acute ischemic stroke who were treated in the Department of Neurology at the Affiliated Hospital of Jining Medical University from March 2023 to April 2024. Data were collected using the Edmonton Frail Scale, Hamilton Depression Rating Scale, Barthel Index (Activities of Daily Living, ADL), Pittsburgh Sleep Quality Index, and Morse Fall Scale. Binary logistic regression analysis was performed to explore the impact of frailty on PSD and to identify other risk factors. Based on the results, a predictive model was developed.Results:A total of 450 questionnaires were distributed, with 412 valid responses returned, yielding a valid response rate of 91.56%. The incidence of PSD among the 412 patients was 45.63% (188/412). Binary Logistic regression analysis showed that frailty, sleep disturbance, C-reactive protein (CRP), and ADL score were the influencing factors for PSD in patients with acute ischemic stroke ( P<0.05). These factors were incorporated into the predictive model, and a risk nomogram was constructed. The area under the curve of the model was 0.764 [95% CI (0.716, 0.811) ], indicating good discriminative ability. Internal validation of the nomogram using the Hosmer-Lemeshow goodness-of-fit test showed χ 2=5.883, P=0.66 ( P>0.05), suggesting good calibration of the model. Conclusions:Frailty increases the risk of post-stroke depression in patients with acute ischemic stroke. Sleep disturbance, CRP level, and ADL score are important screening indicators for PSD risk. Targeted assessment and early intervention are recommended to reduce the likelihood of PSD.

Objective To assess the exposure levels of heavy metals,including lead,arsenic,mercury,and cadmium,in the local population in Sichuan and Chongqing,China,to compare and analyze the differences in reference intervals(RIs)obtained from direct and indirect sampling methods,and to explore the interchangeability and limitations of these two sampling methods.Methods RIs were obtained by the direct sampling method and the indirect sampling method.In the direct sample method,the levels of blood arsenic,urinary cadmium,urinary mercury,and blood lead levels of 5562 healthy participants aged 22-50 years in Sichuan and Chongqing,China were measured by atomic absorption spectrometry and inductively coupled plasma-mass spectrometry.Using the human biomonitoring(HBM)data,we established RIs for the population by a nonparametric method.On the other hand,in the indirect sampling method,RIs were established via a nonparametric method based on data from the laboratory information system(LIS)of a local hospital after stratifying healthy individuals using a Gaussian mixture model(GMM).Comparative analysis of the RIs derived from the two sampling methods were then conducted.Results The RI for blood arsenic was 0.11-1.3 μmol/L.The RI for urinary cadmium was 0.51-2.80 μmol/mol creatine for adults aged 22 to under 43 years and 0.66-2.96 μmol/mol creatine for adults aged 43-50 years.The RI for urinary mercury was 0.12-1.10 μmol/mol creatine.The RI for blood lead was 14.00-47.00 pg/L for adults aged 22 to under 41 year,16.00-53.38 pg/L for males aged 41-50 year,and 15.00-51.02 pg/L for females aged 41-50 year.Most of the RIs established by the direct sampling method had a narrower range compared to those established by the indirect sampling method,and the RIs established by both sampling methods were partially biased.Conclusions The RIs for blood arsenic,urine cadmium,urine mercury,and blood lead in healthy individuals aged 22-50 years in Sichuan and Chongqing,China were established using both direct and indirect sampling methods,which contributes to a better understanding of environmental exposure to metals in the general population and provides a reference for metal poisoning.For data from the same lab,the GMM-based indirect sampling method demonstrated relatively consistent performance in establishing RIs compared with the direct sampling method.

Objective:To investigate the impact of frailty on post-stroke depression (PSD) in patients with acute ischemic stroke and to identify risk factors for PSD in order to construct a risk prediction model.Methods:A convenience sampling method was used to recruit a total of 450 patients with acute ischemic stroke who were treated in the Department of Neurology at the Affiliated Hospital of Jining Medical University from March 2023 to April 2024. Data were collected using the Edmonton Frail Scale, Hamilton Depression Rating Scale, Barthel Index (Activities of Daily Living, ADL), Pittsburgh Sleep Quality Index, and Morse Fall Scale. Binary logistic regression analysis was performed to explore the impact of frailty on PSD and to identify other risk factors. Based on the results, a predictive model was developed.Results:A total of 450 questionnaires were distributed, with 412 valid responses returned, yielding a valid response rate of 91.56%. The incidence of PSD among the 412 patients was 45.63% (188/412). Binary Logistic regression analysis showed that frailty, sleep disturbance, C-reactive protein (CRP), and ADL score were the influencing factors for PSD in patients with acute ischemic stroke ( P<0.05). These factors were incorporated into the predictive model, and a risk nomogram was constructed. The area under the curve of the model was 0.764 [95% CI (0.716, 0.811) ], indicating good discriminative ability. Internal validation of the nomogram using the Hosmer-Lemeshow goodness-of-fit test showed χ 2=5.883, P=0.66 ( P>0.05), suggesting good calibration of the model. Conclusions:Frailty increases the risk of post-stroke depression in patients with acute ischemic stroke. Sleep disturbance, CRP level, and ADL score are important screening indicators for PSD risk. Targeted assessment and early intervention are recommended to reduce the likelihood of PSD.

Objective:To explore the diagnostic value of whole blood cell parameters logistic regression model for radiation injury on radiation workers by comparing the differences of whole blood cell parameters between occupational radiation injury population and occupational health examination population.Methods:In February 2023, 184 radiation workers who received occupational health examinations in our hospital and occurrenced chromosome aberration from July 2021 to July 2022 were retrospectively selected as the radiation injury group. And other 184 radiation workers encountered in the same period without chromosome aberration occurrence were selected as the control group. Collected whole blood cell parameters from two groups of research subjects, conducted comparative analysis, constructed a logistic regression model, and evaluated the diagnostic value of the logistic regression model for radiation injury on radiation workers by receiver operating characteristic curve (ROC) and area under curve (AUC) . In addition, with the same standard, 60 radiation workers with chromosome aberration and 60 radiation workers without chromosome aberration from August 2022 to January 2023 were included in the validation queue to validate the logistic regression model.Results:Neu_X, Neu_Y, Neu_Z, Lym_X, Lym_Y, Lym_Z, Mon_X, Mon_Y, Mon_Z, Micro, MCHC in the radiation injury group were significantly higher than those in the control group, and the difference was statistically significant ( P<0.05) . And MCV and Macro in the radiation injury group were lower than those in the control group, and the difference was statistically significant ( P<0.05) . Moreover, logistic regression analysis showed that Lym_X, Lym_Y, Lym_Z, MCHC, Micro were all independent risk factors for diagnosing radiation injury on radiation workers ( OR=1.08、1.02、0.99、1.06、51.32, P<0.05) . ROC curve analysis showed that the AUC, sensitivity, specificity, and accuracy of the logistic regression model based by Lym_X, Lym_Y, Lym_Z, MCHC and Micro in diagnosing radiation injury on radiation workers were 0.80, 85.9%, 65.8% and 75.9% respectively. The validation queue verified the logistic regression model and the AUC, sensitivity, specificity, and accuracy of the logistic regression model were 0.80, 81.7%, 71.7% and 76.7% respectively, the model fitted well. Conclusion:Radiation damage can cause changes in multiple whole blood cell parameters of radiation workers. The logistic regression model based by Lym_X, Lym_Y, Lym_Z, MCHC and Micro showed good diagnosis ability and can be used for the screening of radiation injury on radiation workers.

Objective:To explore the diagnostic value of whole blood cell parameters logistic regression model for radiation injury on radiation workers by comparing the differences of whole blood cell parameters between occupational radiation injury population and occupational health examination population.Methods:In February 2023, 184 radiation workers who received occupational health examinations in our hospital and occurrenced chromosome aberration from July 2021 to July 2022 were retrospectively selected as the radiation injury group. And other 184 radiation workers encountered in the same period without chromosome aberration occurrence were selected as the control group. Collected whole blood cell parameters from two groups of research subjects, conducted comparative analysis, constructed a logistic regression model, and evaluated the diagnostic value of the logistic regression model for radiation injury on radiation workers by receiver operating characteristic curve (ROC) and area under curve (AUC) . In addition, with the same standard, 60 radiation workers with chromosome aberration and 60 radiation workers without chromosome aberration from August 2022 to January 2023 were included in the validation queue to validate the logistic regression model.Results:Neu_X, Neu_Y, Neu_Z, Lym_X, Lym_Y, Lym_Z, Mon_X, Mon_Y, Mon_Z, Micro, MCHC in the radiation injury group were significantly higher than those in the control group, and the difference was statistically significant ( P<0.05) . And MCV and Macro in the radiation injury group were lower than those in the control group, and the difference was statistically significant ( P<0.05) . Moreover, logistic regression analysis showed that Lym_X, Lym_Y, Lym_Z, MCHC, Micro were all independent risk factors for diagnosing radiation injury on radiation workers ( OR=1.08、1.02、0.99、1.06、51.32, P<0.05) . ROC curve analysis showed that the AUC, sensitivity, specificity, and accuracy of the logistic regression model based by Lym_X, Lym_Y, Lym_Z, MCHC and Micro in diagnosing radiation injury on radiation workers were 0.80, 85.9%, 65.8% and 75.9% respectively. The validation queue verified the logistic regression model and the AUC, sensitivity, specificity, and accuracy of the logistic regression model were 0.80, 81.7%, 71.7% and 76.7% respectively, the model fitted well. Conclusion:Radiation damage can cause changes in multiple whole blood cell parameters of radiation workers. The logistic regression model based by Lym_X, Lym_Y, Lym_Z, MCHC and Micro showed good diagnosis ability and can be used for the screening of radiation injury on radiation workers.

From October 2021 to February 2023, we retrospectively analyzed the clinical and laboratory data of six patients (three male and three female, median age: 54 years, age range: 29-73 years) with mast cell leukemia (MCL) diagnosed in the First Affiliated Hospital of Soochow University (The Mastocytosis Collaborative Network of China). All patients had acute MCL, with at least one C-finding present. The main clinical presentations were hypoalbuminemia ( n=4), fatigue ( n=3), fever ( n=2), abdominal discomfort ( n=2), osteolytic lesions ( n=2), dizziness ( n=1), skin flushing ( n=1), and weight loss ( n=1). Splenomegaly and lymphadenopathy were noted in six and three patients, respectively. Six patients were strongly positive for CD117, five were positive for CD30 and CD25, and four were positive for CD2. Four patients had a normal karyotype and two patients had an abnormal karyotype. Gene mutations were detected in 4/6 cases. The median serum tryptase level was 24.9 (range: 20.1-171.9) μg/L. Two patients were treated with venetoclax and azacitidine for induction (one patient achieved partial remission by combination with afatinib, while there was no remission after combination with dasatinib in the other patient). Two patients did not achieve complete remission despite treatment with cladribine and imatinib, respectively. One patient treated with interferon combined with glucocorticoids was lost to follow-up, and one patient abandoned treatment. The follow-up time ranged from 1.1 to 21.7 months. Three patients died and two survived. Overall, MCL is a rare subtype of systemic mastocytosis with heterogeneous clinical course, and these patients have poor outcome. A better understanding of the clinical characteristics, treatment, and prognosis of MCL is urgently needed.

【Objective】 To genetically analyze the D^el sample from a blood donor in Jiangyin and make clear the molecular basis of the serological phenotype. 【Methods】 The EDTA anticoagulant blood were collected: buffy coat were used for nucleic acid extract and cDNA analysis; red blood cells for serological test. Tube method and microcolumn gel were used for serological test. Genotyping kit were used for exon analysis. Gene mutation was analyzed using the sequence analyzer. 【Results】 Serological analysis demonstrated the sample′s RhD phenotype was D^el. The phenotype of RhCE was CCEe. Real-time fluorescence quota PCR result demonstrated the existence of all exones. Weak D15 and RHD^* DEL1 [RHD(1227G>A)], which had a high frequency of occurrence in China, were excluded according to real-time fluorescence quota PCR result. Sequence analyzing result verified RHD(28C>T) SNP mutation in cDNA. The genotype of this sample was RHD^*01 W. 61[RHD(28C>T)]. 【Conclusion】 A weak D61 was found among blood donors in our city, Jiangyin.

Objective To investigate the relationship between disrupted corticospinal tract (CST) and motor recovery after stroke by using diffusion tensor tracking (DTT). Methods From March, 2012 to June, 2013, 15 chronic stroke patients with left subcortical lesions and 15 age- and sex- matched healthy subjects were performed diffusion tensor imaging (DTI) examination. The CST was tracked by DTT technique, and the damaged values of the CST caused by the stroke lesions were quantified using a CST template generated from healthy controls. Furthermore, the correlations of the damaged values of the CST with Fugl-Meyer Assessment (FMA) were performed. Results The range of the damaged values of CST in stroke patients was 0.00% to 29.6%. There were very strong negative correlation between the damaged values of the CST and FMA scores (the wrist, r = -0.660; hand, r = -0.813; wrist plus hand, r = -0.795, respectively, P < 0.01). It also showed strong negative correlation between the damaged values of the CST and FMA scores (upper limb, r = -0.614; upper limb plus lower limb, r = -0.563, respectively, P < 0.05). Whereas, there was no correlation between the damaged values of the CST and FMA scores of lower limb (r = -0.270, P = 0.331). In addition, the lesion volumes of stroke and FMA scores were not significantly correlated (P > 0.05). Conclusion The severity of motor deficit after stroke was closely related to the overlap of lesions with CST. The damaged values of the CST based on DTT may be used as a potential biomarker to assess motor impairments of upper limbs, especially hand and wrist in stroke patients.

Precision medicine emerges as a new approach that takes into account individual variability. Successful realization of precision medicine requires disease models that are able to incorporate personalized disease information and recapitulate disease development processes at the molecular, cellular and organ levels. With recent development in stem cell field, a variety of tissue organoids can be derived from patient specific pluripotent stem cells and adult stem cells. In combination with the state-of-the-art genome editing tools, organoids can be further engineered to mimic disease-relevant genetic and epigenetic status of a patient. This has therefore enabled a rapid expansion of sophisticated in vitro disease models, offering a unique system for fundamental and biomedical research as well as the development of personalized medicine. Here we summarize some of the latest advances and future perspectives in engineering stem cell organoids for human disease modeling.
Animals ; Biomedical Research ; Gene Editing ; methods ; Humans ; Models, Biological ; Organoids ; metabolism ; Pluripotent Stem Cells ; metabolism ; Precision Medicine ; methods