Objective To compare the clinical efficacy of neuroendoscope-assisted evacuation and navigation-assisted puncture drainage in treating thalamic hemorrhage breaking into the ventricle. Methods A retrospective analysis was conducted on the clinical data of 93 patients with thalamic hemorrhage breaking into the ventricle at Taihe Hospital of Wannan Medical College between January 2022 and February 2024. The patients received neuroendoscope-assisted removal of thalamic hematoma combined with contralateral extraventricular drainage (n＝44, neuroendoscope group) and navigation-assisted thalamic hematoma puncture drainage combined with contralateral extraventricular drainage (n＝49, navigation group), respectively. The treatment efficacy, surgical situation, and prognosis between the two groups were compared. Results The neuroendoscope group had longer operation duration, more intraoperative blood loss, higher hospitalization costs than the navigation group (P＜0.05). The neuroendoscope group had higher hematoma clearance rate 3rd after surgery and shorter length of stay than the navigation group (P＜0.05). There was no significant difference in the incidence of intracranial infection after surgery between the two groups. The neuroendoscope group had higher Glasgow coma scale (GCS) score at 1 week after surgery and Glasgow outcome scale (GOS) score at 3 months after surgery (P＜0.01). Conclusions Compared with navigation-assisted puncture, neuroendoscope-assisted evacuation can improve the thalamic hemorrhage clearance rate, shorten the length of stay, and improve the prognosis of patients.

ObjectiveTo investigate the functional role and underlying molecular mechanisms of fumarylacetoacetate hydrolase （FAH） in the progression of glioblastoma （GBM）. MethodsDifferential expression analysis was performed on the TCGA-GBM， GSE4290， and GSE116520 datasets. Weighted gene co-expression network analysis （WGCNA） was used to identify key modules， and Cox regression and risk modeling were used to screen prognostic genes. Immune infiltration analysis of prognostic genes was carried out by using single-cell RNA sequencing panels. The clinical expression signature of FAH in GBM was analyzed in the TCGA and HPA databases. The functional role of FAH was validated by in vitro and in vivo experiments， and pathway analysis was performed to explore the underlying mechanisms. ResultsA total of 152 overlapping genes were identified across the three GBM datasets （P<0.05）. WGCNA revealed that the turquoise module was most strongly associated with tumor purity， stromal score， immune score， and ESTIMATE score （P<0.001）. Compared with normal tissues， three prognostic genes （CTSD， FAH， and THBD） were upregulated in GBM and correlated with immune infiltration （P<0.05）. FAH mRNA and protein levels were elevated in GBM tissues relative to normal tissues， and its expression was significantly associated with age stratification and TP53 mutation （P<0.05）. CCK-8 assay results showed that， compared with the shNC group， the proliferative activity of GBM cells in the shFAH group was reduced （P<0.001）. Transwell migration and invasion assays demonstrated that， relative to the shNC group， the numbers of migrated and invaded cells in the shFAH group decreased （P<0.05）. Western blot analysis revealed that the protein expression levels of PI3K， p-AKT， and p-mTOR in the shFAH group decreased compared with those in the shNC group （P<0.05）. In vivo subcutaneous xenograft experiments further confirmed that tumor volume and weight significantly decreased in the shFAH group compared with the shNC group （P<0.001）. ConclusionFAH promotes GBM progression by activating the PI3K/AKT/mTOR signaling pathway and may serve as a potential therapeutic target for GBM.

ObjectiveTo investigate the molecular mechanisms related to angiogenesis during the development and progression of diabetic retinopathy （DR）. MethodsAngiogenesis-related genes were obtained from the Gencard website and intersected with differentially expressed genes from DR datasets （GSE60436 and GSE94019）. Functional enrichment and protein-protein interaction （PPI） networks were then used to screen candidate genes and evaluate their diagnostic value. Gene set enrichment analysis （GSEA） was used to explore potential pathways underlying candidate genes， and immune infiltration analysis revealed associations between candidate genes and immune cells. Cellular experiments were conducted to validate the role of fibronectin 1 （FN1） in human retinal microvascular endothelial cells （HRMECs） under high glucose （HG） conditions. ResultsA total of 237 differentially expressed genes related to angiogenesis were identified， enriched in pathways such as phosphoinositide 3-kinase/protein kinase B signaling pathway （PI3K-Akt）， tumor suppressor protein 53 （P53）， tumor necrosis factor （TNF）， and Janus kinase （JAK）/signal transducer and activator of transcription signaling pathway （STAT）. Among them， collagen type I alpha 1 chain （COL1A1）， COL1A2， FN1， TNF， and tumor protein p53 （TP53） were key genes with high diagnostic value. GSEA indicated that these genes were involved in multiple signaling pathways， including P53. CIBERSORTx analysis revealed significant associations with the infiltration of multiple immune cells. HG treatment led to the upregulation of FN1. In HG-induced HRMECs， compared with the si-NC control group， si-FN1 significantly reduced cell proliferation， migration， and tube formation， while P53 protein expression was increased. ConclusionThis study reveals the important role of FN1 in angiogenesis in DR and suggests that it may be a potential diagnostic and therapeutic target.

This study utilized data from the non-communicable diseases (NCDs) Progress Monitor Reports (2015, 2017, 2020, 2022) released by World Health Organization (WHO) to analyze the implementation of NCDs prevention and control policies in China from 2014 to 2021 through descriptive statistical method, aiming to provide evidence for strengthening national NCDs strategies. The analysis focuses on WHO-recommended ‘best buys’ policies for NCDs prevention and control, covering 10 categories (18 interventions): national NCDs targets, mortality data, risk factor surveys, national integrated NCDs policies/strategies/action plans, tobacco demand-reduction measures, harmful use of alcohol reduction measures, unhealthy diet reduction policies, physical activity campaigns, national clinical guidelines for cancer/CVD/diabetes/CRD management, and drug therapy/counselling for cardiovascular diseases. In accordance with the WHO′s NCDs progress monitor scoring methodology, policies are assigned 1.0 point for full implementation, 0.5 points for partial implementation, and 0 points for non-implementation or missing data, with a maximum total score of 18.0 points. The analytical metrics encompass the policy implementation score, implementation rate, and period-on-period implementation growth rate. The results showed that China′s total policy implementation scores for NCDs prevention and control in 2014, 2016, 2019, and 2021 were consistently higher than the global average (8.5, 10.5, 9.5, 9.5 vs 6.7, 8.3, 8.6, 8.6). From 2014 to 2021, the total score increased by 1.0 point, and the implementation rate improved by 8.9%. From 2014 to 2016, China′s total policy implementation score rose from 8.5 to 10.5, primarily driven by improvements in tobacco tax increases and unhealthy diet reduction measures (salt reduction, restrictions on high-fat foods, and regulation of breast-milk substitute sales). However, this progress was partially offset by a decline in scores for physical activity campaigns. From 2016 to 2019, the total score decreased to 9.5, largely due to lower scores in harmful use of alcohol reduction measures (alcohol taxation and advertising bans). From 2019 to 2021, the total score remained stable, with increases in marketing to children restrictions balanced by declines in scores for drug therapy/counselling for cardiovascular diseases. In 2021, China′s total policy implementation score (9.5) exceeded the global average (8.6) but fell below the G20 average (11.2). Significant gaps remained compared to top-performing G20 countries such as Turkey (16.5), particularly in tobacco control and restrictions on harmful alcohol use. In conclusion, from 2014 to 2021, China′s total policy implementation score for NCDs prevention and control consistently exceeded the global average, demonstrating an upward trend, and various NCDs prevention and control policies have been continuously improved.

This study utilized data from the non-communicable diseases (NCDs) Progress Monitor Reports (2015, 2017, 2020, 2022) released by World Health Organization (WHO) to analyze the implementation of NCDs prevention and control policies in China from 2014 to 2021 through descriptive statistical method, aiming to provide evidence for strengthening national NCDs strategies. The analysis focuses on WHO-recommended ‘best buys’ policies for NCDs prevention and control, covering 10 categories (18 interventions): national NCDs targets, mortality data, risk factor surveys, national integrated NCDs policies/strategies/action plans, tobacco demand-reduction measures, harmful use of alcohol reduction measures, unhealthy diet reduction policies, physical activity campaigns, national clinical guidelines for cancer/CVD/diabetes/CRD management, and drug therapy/counselling for cardiovascular diseases. In accordance with the WHO′s NCDs progress monitor scoring methodology, policies are assigned 1.0 point for full implementation, 0.5 points for partial implementation, and 0 points for non-implementation or missing data, with a maximum total score of 18.0 points. The analytical metrics encompass the policy implementation score, implementation rate, and period-on-period implementation growth rate. The results showed that China′s total policy implementation scores for NCDs prevention and control in 2014, 2016, 2019, and 2021 were consistently higher than the global average (8.5, 10.5, 9.5, 9.5 vs 6.7, 8.3, 8.6, 8.6). From 2014 to 2021, the total score increased by 1.0 point, and the implementation rate improved by 8.9%. From 2014 to 2016, China′s total policy implementation score rose from 8.5 to 10.5, primarily driven by improvements in tobacco tax increases and unhealthy diet reduction measures (salt reduction, restrictions on high-fat foods, and regulation of breast-milk substitute sales). However, this progress was partially offset by a decline in scores for physical activity campaigns. From 2016 to 2019, the total score decreased to 9.5, largely due to lower scores in harmful use of alcohol reduction measures (alcohol taxation and advertising bans). From 2019 to 2021, the total score remained stable, with increases in marketing to children restrictions balanced by declines in scores for drug therapy/counselling for cardiovascular diseases. In 2021, China′s total policy implementation score (9.5) exceeded the global average (8.6) but fell below the G20 average (11.2). Significant gaps remained compared to top-performing G20 countries such as Turkey (16.5), particularly in tobacco control and restrictions on harmful alcohol use. In conclusion, from 2014 to 2021, China′s total policy implementation score for NCDs prevention and control consistently exceeded the global average, demonstrating an upward trend, and various NCDs prevention and control policies have been continuously improved.

AIM: To investigate the change trend of angle Kappa after intraocular lens(IOL)implantation in cataract patients and its relationship with IOL stability.METHODS: A total of 120 patients(120 eyes)with cataract who received IOL implantation in our hospital from February 2023 to January 2024 were selected as the research objects, including 56 left eyes and 64 right eyes. The results of ophthalmic examination, the distribution of angle Kappa, the changes of angle Kappa and the stability of IOL at different time points before and after operation were compared. Pearson correlation analysis and multiple linear regression analysis were used to analyze the correlation between IOL rotational stability and ophthalmic examination indexes. Multiple linear regression analysis was used to analyze the correlation between angle Kappa and IOL stability.RESULTS: After surgery, angle Kappa decreased and the degree of decrease decreased gradually(all P<0.05), and the IOL rotation degree also decreased gradually(P<0.05). The degree of IOL rotation at 2 mo after surgery was positively correlated with axial length(AL), lens thickness(LT), horizontal keratometer(K1), vertical keratometer(K2), pupil diameter(PD)and angle Kappa at 1 d after surgery(all P<0.05), and negatively correlated with anterior chamber depth(ACD)at 1 d after surgery(all P<0.05). AL, ACD, PD and angle Kappa had significant effects on IOL rotation degree(all P<0.05). With the increase of angle Kappa, the degree of IOL rotation gradually increased, that is, the stability of IOL gradually decreased(P<0.05).CONCLUSION: Angle Kappa decreased significantly after IOL implantation in cataract patients, and then tended to be stable. The stability of IOL decreased with the increase of angle Kappa.

AIM: To investigate the change trend of angle Kappa after intraocular lens(IOL)implantation in cataract patients and its relationship with IOL stability.METHODS: A total of 120 patients(120 eyes)with cataract who received IOL implantation in our hospital from February 2023 to January 2024 were selected as the research objects, including 56 left eyes and 64 right eyes. The results of ophthalmic examination, the distribution of angle Kappa, the changes of angle Kappa and the stability of IOL at different time points before and after operation were compared. Pearson correlation analysis and multiple linear regression analysis were used to analyze the correlation between IOL rotational stability and ophthalmic examination indexes. Multiple linear regression analysis was used to analyze the correlation between angle Kappa and IOL stability.RESULTS: After surgery, angle Kappa decreased and the degree of decrease decreased gradually(all P<0.05), and the IOL rotation degree also decreased gradually(P<0.05). The degree of IOL rotation at 2 mo after surgery was positively correlated with axial length(AL), lens thickness(LT), horizontal keratometer(K1), vertical keratometer(K2), pupil diameter(PD)and angle Kappa at 1 d after surgery(all P<0.05), and negatively correlated with anterior chamber depth(ACD)at 1 d after surgery(all P<0.05). AL, ACD, PD and angle Kappa had significant effects on IOL rotation degree(all P<0.05). With the increase of angle Kappa, the degree of IOL rotation gradually increased, that is, the stability of IOL gradually decreased(P<0.05).CONCLUSION: Angle Kappa decreased significantly after IOL implantation in cataract patients, and then tended to be stable. The stability of IOL decreased with the increase of angle Kappa.

Objective : To investigate the effect of laminarin(LAM) on nonproliferative diabetes retinopathy by high throughput sequencing(RNA-seq). Methods : The diabetes model was established by intraperitoneal injection of streptozotocin(STZ), and the effect of LAM on diabetic mice was observed.C57BL/6 mice were randomly divided into three groups: Control group, Model group, and LAM group, with 8 mice in each group. After 8 weeks of modeling, the LAM group received a 4-week intraperitoneal injection of LAM treatment. Changes in blood glucose and body weight of the three groups of mice were recorded, HE staining was performed to examine retinal lesions, and RNA-seq was used to identify differentially expressed genes(DEGs) in diabetic retinopathy(DR) under the action of STZ and LAM. Results : STZ successfully established the model of DR, and LAM reduced the blood sugar in diabetic mice to a certain extent and improved the pathological morphology of retinal structural looseness in diabetic mice. After RNA-seq analysis of DEGs, it was found that there were a total of 214 DEGs in the retina of the Model group mice compared to the Control group. Enrichment analysis revealed that DR could exacerbate the lesions through the PI3K Akt signaling pathway. There were a total of 42 DEGs in the retina of the Model group and LAM group mice, and enrichment showed that LAM improved the lesions through the neutrophil extracellular trap pathway. Early growth response factor 1(Egr1), FBJ osteosarcoma oncogene(Fos), nuclear receptor subfamily 4A member 1(Nr4a1), and salt-induced kinase 1(Sik1) were regulated by STZ, and LAM significantly regulated their expression, which might be closely related to LAM′s treatment of diabetic retinopathy. Conclusion DEGs can exacerbate the severity of diabetic retinopathyviathe PI3K-Akt signaling pathway. LAM can mitigate diabetic retinopathyviathe neutrophil extracellular trap pathway. Egr1, Fos, Nr4a1, and Sik1 are key genes involved in LAM treatment of STZ-induced DR.

BackgroundSchizophrenia is a highly heterogeneous disease with different clinical subtypes. Artificial intelligence technology represented by deep learning models has provided considerable benefits for the electroencephalogram （EEG）-based schizophrenia diagnosis， treatment and research， however， to date little research has been conducted regarding any of these benefits among Chinese schizophrenic patients. ObjectiveTo investigate the application of deep learning techniques utilizing EEG parameters for the diagnosis of first-episode schizophrenia and grading of EEG abnormalities in patients， with the aim of contributing to improved clinical diagnosis and treatment strategies for the disorder. MethodsFrom January 2020 to January 2023， a total of 130 patients with first-episode schizophrenia who met the diagnostic criteria of International Classification of Diseases， tenth edition （ICD-10）， and attended at the Third People's Hospital of Fuyang， along with 150 health checkup examinees， were enrolled. All of them underwent EEG examination. An optimized long short-term memory （LSTM） deep learning model was developed utilizing EEG signals. Ten-fold cross-validation method was employed to evaluate the model's performance. The dataset was then split into two components： a training set （90%） for LSTM model development and a test set （10%） for validation. The accuracy， recall rate， precision， F1-score， schizophrenia diagnosis and EEG abnormality grading were used as evaluation indicators， and the results of the proposed model were compared to the assessments made by experienced psychiatrists. ResultsFor schizophrenia diagnosis， the modeling group achieved the following performance metrics： precision （94.40±3.03）%， recall rate （94.30±3.23）%， accuracy （94.60±2.22）%， and F1-score （94.20±2.20）%. In the validation group， the corresponding metrics were precision （90.90±2.85）%， recall rate （92.20±1.14）%， accuracy （92.20±1.69）%， and F1-score （91.50±1.78）%. Statistical analysis revealed no significant differences between the LSTM diagnostic model and the experienced psychiatrists in terms of precision， recall rate， accuracy， and F1-score for schizophrenia diagnosis （χ²=1.500， 0.750， 2.722， 1.056， P>0.05）. The modeling group demonstrated an accuracy rate of （91.71±1.73）% in grading EEG abnormalities. For Grade 1 abnormalities， the modeling group reported a precision of （96.40±2.39）%， a recall rate of （94.77±1.40）%， and an F1-score of （95.55±1.14）%. In the case of Grade 2 abnormalities， the precision was （85.89±2.04）%， the recall rate was （88.10±6.18）%， and the F1-score was （87.06±3.12）%. For the more severe Grade 3 abnormalities， the modeling group's precision was （79.61±7.33）%， the recall rate was （81.79±9.87）%， and the F1-score was （80.41±6.79）%. Additionally， the validation group exhibited an accuracy rate of （85.61±6.16）%. The precision， recall rate， and F1-score for Grade 1 abnormalities were （91.43±6.25）%， （92.64±9.65）% and （91.56±4.83）%， respectively. For Grade 2 abnormalities， these metrics were （71.17±19.02）%， （77.64±17.24）% and （71.88±11.33）%. In the case of Grade 3 abnormalities， the precision was （90.00±21.08）%， the recall rate was （80.00±25.82）%， and the F1-score was （81.67±19.95）%. There was no significant difference in the accuracy， recall， accuracy and F1 value between LSTM model and senior doctors in evaluating the abnormal degree of EEG in schizophrenia （χ²=0.098， 0.036， 0.020， 0.336， P>0.05）. The LSTM model takes less time to diagnose schizophrenia and EEG abnormalities than senior doctors， and the differences were statistically significant （t=57.147， 43.104， P<0.01）. ConclusionThe study utilizes an EEG-based LSTM deep learning model for diagnosing first-episode schizophrenia and grading EEG abnormalities， and the model not only matches the performance of experienced psychiatrists but also significantly reduces the time required for diagnosis.

To analyze the clinical characteristics of acute diquat poisoning complicated by central nervous system injury (CNSI) and identify early risk factors, aiming to provide a theoretical basis for reducing mortality in diquat poisoning with CNSI.