OBJECTIVE: The relationship between fish consumption and stroke is inconsistent, and it is uncertain whether this association varies across predicted stroke risks. METHODS: A cohort study comprising 95,800 participants from the Prediction for Atherosclerotic Cardiovascular Disease Risk in China project was conducted. A standardized questionnaire was used to collect data on fish consumption. Participants were stratified into low- and moderate-to-high-risk categories based on their 10-year stroke risk prediction scores. Hazard ratios ( HRs) and 95% confidence intervals ( CIs) were estimated using Cox proportional hazard models and additive interaction by relative excess risk due to interaction (RERI), attributable proportion (AP), and synergy index (SI). RESULTS: During 703,869 person-years of follow-up, 2,773 incident stroke events were identified. Higher fish consumption was associated with a lower risk of stroke, particularly among moderate-to-high-risk individuals ( HR = 0.53, 95% CI: 0.47-0.60) than among low-risk individuals ( HR = 0.64, 95% CI: 0.49-0.85). A significant additive interaction between fish consumption and predicted stroke risk was observed (RERI = 4.08, 95% CI: 2.80-5.36; SI = 1.64, 95% CI: 1.42-1.89; AP = 0.36, 95% CI: 0.28-0.43). CONCLUSION Higher fish consumption was associated with a lower risk of stroke, and this beneficial association was more pronounced in individuals with moderate-to-high stroke risk.
Humans ; China/epidemiology* ; Male ; Female ; Stroke/etiology* ; Middle Aged ; Prospective Studies ; Incidence ; Aged ; Animals ; Fishes ; Risk Factors ; Diet ; Seafood ; Adult ; Cohort Studies

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Objective:To evaluate the value of ultrasound radiomics combined with machine learning for early diagnosis of seronegative Hashimoto’s thyroiditis (SN-HT) .Methods:This retrospective study included 164 patients from Liaoning Provincial People’s Hospital , Lixin County People’s Hospital, Linghai Dalinghe Hospital, Fengcheng Phoenix Hospital, who underwent thyroidectomy for solitary nodules with normal thyroid function between Nov. 2016 and Jan. 2024. Postoperative pathology confirmed Hashimoto’s thyroiditis (HT) in some cases, who were further categorized into antibody-positive and antibody-negative groups based on serum antibody status. Patients without Hashimoto’s thyroiditis served as the control group. A total of 298 ultrasound images were analyzed. Radiomics features were extracted from hypoechoic non-nodular areas within 0.5 cm surrounding the tumor. Two senior pathologists and two senior ultrasound physicians independently assessed lymphocytic infiltration, eosinophilic changes of follicular epithelium, and the proportion of hypoechoic areas in pathology and ultrasound images, respectively. A machine learning model, CCH-NET, was developed using linear regression and t-distributed stochastic neighbor embedding (t-SNE) techniques. The dataset was divided into a training set (80%) and a validation set (20%) to compare the diagnostic accuracy of CCH-NET with that of senior ultrasound physicians. Results:In internal validation, CCH-NET achieved a diagnostic accuracy of 88.89% for both antibody-positive and antibody-negative groups, significantly higher than the 66.67% accuracy of senior ultrasound physicians ( P<0.01). In external validation, CCH-NET achieved 75.00% and 66.67% accuracy for the two groups, compared to 50.00% by senior ultrasound physicians. For the control group, both methods achieved 93.33% accuracy. The AUC of CCH-NET was 0.848, outperforming senior ultrasound physicians (0.681) ,demonstrating superior diagnostic performance. Conclusion:The radiomics-based CCH-NET model, using non-nodular hypoechoic areas as a specific indicator, can accurately identify early SN-HT in euthyroid patients. It significantly outperforms senior ultrasound physicians, improving diagnostic accuracy and reducing missed diagnoses.

Objective:To evaluate the value of ultrasound radiomics combined with machine learning for early diagnosis of seronegative Hashimoto’s thyroiditis (SN-HT) .Methods:This retrospective study included 164 patients from Liaoning Provincial People’s Hospital , Lixin County People’s Hospital, Linghai Dalinghe Hospital, Fengcheng Phoenix Hospital, who underwent thyroidectomy for solitary nodules with normal thyroid function between Nov. 2016 and Jan. 2024. Postoperative pathology confirmed Hashimoto’s thyroiditis (HT) in some cases, who were further categorized into antibody-positive and antibody-negative groups based on serum antibody status. Patients without Hashimoto’s thyroiditis served as the control group. A total of 298 ultrasound images were analyzed. Radiomics features were extracted from hypoechoic non-nodular areas within 0.5 cm surrounding the tumor. Two senior pathologists and two senior ultrasound physicians independently assessed lymphocytic infiltration, eosinophilic changes of follicular epithelium, and the proportion of hypoechoic areas in pathology and ultrasound images, respectively. A machine learning model, CCH-NET, was developed using linear regression and t-distributed stochastic neighbor embedding (t-SNE) techniques. The dataset was divided into a training set (80%) and a validation set (20%) to compare the diagnostic accuracy of CCH-NET with that of senior ultrasound physicians. Results:In internal validation, CCH-NET achieved a diagnostic accuracy of 88.89% for both antibody-positive and antibody-negative groups, significantly higher than the 66.67% accuracy of senior ultrasound physicians ( P<0.01). In external validation, CCH-NET achieved 75.00% and 66.67% accuracy for the two groups, compared to 50.00% by senior ultrasound physicians. For the control group, both methods achieved 93.33% accuracy. The AUC of CCH-NET was 0.848, outperforming senior ultrasound physicians (0.681) ,demonstrating superior diagnostic performance. Conclusion:The radiomics-based CCH-NET model, using non-nodular hypoechoic areas as a specific indicator, can accurately identify early SN-HT in euthyroid patients. It significantly outperforms senior ultrasound physicians, improving diagnostic accuracy and reducing missed diagnoses.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Aim To explore the potential genes and mechanism of alisol B in the treatment of non-small cell lung cancer(NSCLC).Methods The proliferation and migration of NSCLC cells were detected by CCK-8 and Transwell.Genes of NSCLC and alisol B were col-lected through TCGA and compound gene prediction database,and their intersection genes were obtained.The network of protein-protein interaction(PPI)was constructed by using String database,and the top 20 key nodes were screened out,and the prognosis-related proteins related to the prognosis of NSCLC were screened out by using R language,and the intersection of them was obtained.The potential mechanism of ali-sol B on NSCLC was explored by KEGG and GO en-richment analysis and the relationship between related genes and immune cells,which was verified by cell-lev-el experiments.Results Alisol B inhibited the cell activity and migration ability of NSCLC cells.Five im-portant genes were identified by network pharmacologi-cal analysis:CCNE1,CDK1,COL1A1,COL1A2 and COL3A1.The results of cell experiment showed that al-isol B down-regulated the expression of Cyclin E1,CDK1 and COL1A2 in NSCLC cells.In addition,alisol B could inhibit the expression of COL1A2 and M2 macrophage marker CD206 in macrophages.Conclu-sions Alisol B may inhibit the proliferation of tumor cells by down-regulating CDK1 and Cyclin E1,and may affect the function of macrophages by inhibiting COL1A2,thus regulating the tumor immune microenvi-ronment and inhibiting NSCLC.

Objective To construct a UNet fusing patch attention(PA-UNet)model,and to observe its value for segmenting knee cartilage on MRI.Methods Slice and preprocessing were performed on knee MRI selected from Osteoarthritis Initiative-Zuse Institute Berlin dataset.Taken UNet as the backbone network,a PA-UNet model was constructed based on patch attention mechanism.The effect of PA-UNet model and other models for segmenting both femoral cartilage and tibial cartilage were compared by subjective and objective evaluations.Ablation experiments based on UNet,UNet based on SE with layers 2-4(UNet+SE),+UNet,++UNet,+++UNet,+U-Net+,++U-Net++and PA-UNet models were performed to observe the effect of models for segmenting knee cartilage.Results PA-UNet could accurately segment femoral and tibial cartilage in all simple,medium and difficult samples,which had better segmenting effect on small structures than SegNet,UNet and DeepLabv3+models.The Dice similarity coefficient(DSC)and intersection over union of PA-UNet model for segmenting femoral and tibial cartilage were both higher,while Hausdorff distance of PA-UNet model was lower than those of UNet,DeepLabv3+,SA-UNet,RA UNet and SegNet models.DSC of PA-UNet model for segmenting femoral cartilage and tibial cartilage was 88.97％and 82.72％,respectively,both higher than those of UNet,UNet+SE,+UNet,++UNet,++UNet,+UNet+and++UNet++models.Conclusion PA-UNet could segment knee cartilage completely on MRI,especially for small structures.

Objective To explore the toxicity of Polygonum multiflorum alcohol extract on 3D hepatospheres.Methods Variations in culture conditions and cell ratios were implemented,followed by the assessment of cell sphere diameter,density,and roundness,aiming to explore the optimal culture conditions.The 3D hepatocyte spheres were divided into control group and experimental-L,-M,-H groups.The experimental-L,-M,-H groups were treated with 0.25,1.00 and 2.50 mg·mL-1 Polygounm multiforum alcohol extract,and the control group was given the same amount of culture medium.The cell viability of the cell spheroids was tested by CellTiter-Glo reagent,the expression level of liver function related genes was detected by fluorescent quantitative polymerase chain reaction(RT-qRCR).The toxicity of cell spheres was detected by double fluorescent staining of living and dead cells.Results The ideal culture condition of cell sphere was 500 cells per micropore,and the cell ratio was HepG2-Huvec-LX-2=8∶1∶1.It displayed the values of 0.91±0.07 for circularity,0.91±0.02 for firmness,1.12±0.14 for aspect ratio,and(170.97±14.79)μm for diameter.On the 3rd,7th,10th and 14th days,the expression levels of albumin(ALB)mRNA were 1.00±0.02,0.96±0.02,0.54±0.07,0.52±0.07,and the expression levels of cytochrome P450 1A2(CYP1A2)mRNA were 1.00±0.10,2.15±0.16,2.45±0.33,1.30±0.03,respectively.The expression levels of multidrug resistance protein 2(MPR2)in the control group and the experimental-L,-M,-H groups were 1.00±0.31,1.38±0.24,1.48±0.06 and 1.90±0.08,respectively;spheroid viability were(98.19±0.49)％,(88.53±0.90)％,(71.60±2.91)％and(56.65±5.41)％.There were statistically significant differences in the above indexes between the experimental-L,-M,-H groups and the control group(all P＜0.05).Conclusion The established hepatocyte sphere co-culture model showed varying degrees of expression of phase Ⅰ/Ⅱ drug metabolism enzymes,transporters,and liver cell specific marker molecule albumin and can be used to evaluate the toxicity of multiflorum multiflorum,which provides further reference for the clinical application of multiflorum multiflorum.

Objective:To explore any effect of repeated transcranial magnetic stimulation (rTMS) on the upper limb motor function and cerebral cortex activation of stroke survivors.Methods:Sixty stroke survivors were randomly divided into an intervention group and a control group, each of 30. In addition to routine rehabilitation training (including drug therapy, comprehensive hemiplegic limb training and physical factor therapy), the intervention group received 15 minutes of rTMS daily, five days a week for 4 weeks while the control group was given false rTMS. Upper limb motor function was evaluated before and after the treatment using the Fugl Meyer upper limb motor function rating scale (FMA-UE). Functional near-infrared spectroscopy was used to detect and compare the activation (β values) of the prefrontal cortex, the motor cortex and the primary somatosensory cortex in the 2 groups. The correlation between the FMA-UE scores and the β values was quantified.Results:①There was no significant difference in the average FMA-UE scores between the two groups before the treatment. Afterward, though both groups′ average scores had increased significantly, there was significantly greater improvement in the treatment group. ②There was also no significant difference in average β value between the two groups before the experiment, but afterward the average βs of channels 27 and 13 in the intervention group were significantly higher than in the control group. Moreover, in patients with lesion in the left brain, the β-values of CH27 and CH13 were also significantly higher than the control group ( P<0.05). ③The FMA-UE scores of the intervention group were moderately correlated with the CH27 and CH13 β values, but those of the control group were only weakly correlated with the β values of CH27. Conclusion:Transcranial magnetic stimulation activates a lesioned left brain region, improving upper limb motor function. The improvement is correlated with the activation of the left prefrontal cortex and the left primary somatosensory cortex.