Objective: To evaluate the intervention effectiveness of co-occurrence and prevention for myopia and obesity among primary and secondary school students, so as to provide a scientific basis for the development of comprehensive intervention measures in myopia and obesity. Methods: From September 2022 to September 2023, a cluster random sampling method was used to select 6 primary schools and 6 junior high schools from Tongzhou District, Beijing. Participants were randomly assigned to an intervention group (914 before intervention and 754 after intervention) and a control group (868 before intervention and 652 after intervention), with an expected duration of one academic year. Based on the RE-AIM framework, integrate resources from families, schools, communities, and medical institutions to develop a school-based intervention technology packagefor the co-occurrence and prevention of myopia and obesity in children. The intervention group received intervention according to the comprehensive intervention technology package, while the control group did not receive any intervention measures. Relevant health indicators during the baseline period and after intervention were measured and collected, and groups were compared by Chi quest test, t-test and Wilcoxon rank sum test. Results: After intervention, the uncorrected visual acuity of primary and secondary school students in the intervention group (4.79±0.30) and the control group (4.77±0.33) both decreased compared to those before intervention (4.80±0.30, 4.90±0.32) ( t =-7.00,-5.24); the decrease in uncorrected visual acuity in the intervention group was smaller than that in the control group( t =5.33)( P <0.01). After intervention, body mass index, waist circumference, hip circumference, and body fat percentage of primary and secondary school students in the intervention group decreased compared to those before intervention. However, the changes in these indicators were not statistically significant ( t/Z =-0.03, - 0.36，- 0.30，- 0.01, P >0.05); the above indicators in the control group increased compared to those before intervention, but only hip circumference and body fat percentage showed statistically significant changes ( t/Z =2.17, 2.62, P <0.05). After intervention, both the intervention group and the control group showed increases in systolic and diastolic blood pressure compared to those before intervention(intervention group: t =2.16,5.29; control group: t =6.84,5.07); the intervention group had lower systolic and diastolic blood pressure than the control group( t = -5.27 , -2.08)( P <0.05). After intervention, the intervention and the control groups had statistically significant differences in cognitive accuracy(92.48%, 69.33%) in terms of "outdoor exercise can prevent myopia" and "having 5 servings of adult fist sized vegetables and fruits every day" ( χ 2=6.30, 7.86, P <0.05). There was a statistically significant difference in the proportion of primary and secondary school students in the intervention group (40.98%) and the control group (35.43%) for "who did not drink sugary drinks for every day in the past 7 days" ( χ 2=4.32, P <0.05). After intervention, the intervention group and the control group showed increases in "school outdoor activity duration on school days" and "outdoor activity duration on rest days" compared to those before intervention ( t/Z =-13.32,-9.71;- 2.59，-2.69）；the behavior rate of "visual acuity measurement frequency at least once every 3 months" in the intervention group (46.68%) and the control group (52.76%) increased compared to those before intervention (36.43%, 44.01%), and the increases in the intervention group were greater than that in the control group ( χ 2=17.52,11.08) ( P <0.05). Conclusions Comprehensive intervention measures have significant intervention effects on controlling the occurrence and development of comorbidity of myopia and obesity in children. It could actively promote collaboration and cooperation among families, schools, communities and medical institutions to reduce the occurrence of myopia and obesity among primary and secondary school students.

Objective: Whether elevation in plasma levels of amyloid and tau protein biomarkers are better indicators of cognitive decline than higher baseline levels in patients with amnestic mild cognitive impairment (aMCI) and Alzheimer’s disease (AD) remains understudied. Methods: We included 67 participants with twice testing for AD-related plasma biomarkers via immunomagnetic reduction (IMR) assays (amyloid beta [Aβ]1-40, Aβ1-42, total tau [t-Tau], phosphorylated tau [p-Tau] 181, and alpha-synuclein [α-Syn]) and the Mini-Mental State Examination (MMSE) over a 1-year interval. We examined the correlation between biomarker levels (baseline vs. longitudinal change) and annual changes in the MMSE scores. Receiver operating characteristic curve analysis was conducted to compare the biomarkers. Results: After adjustment, faster cognitive decline was correlated with lower baseline levels of t-Tau (β=0.332, p=0.030) and p-Tau 181 (β=0.369, p=0.015) and rapid elevation of t-Tau (β=-0.330, p=0.030) and p-Tau 181 levels (β=-0.431, p=0.004). However, the levels (baseline and longitudinal changes) of Aβ1-40, Aβ1-42, and α-Syn were not correlated with cognitive decline. aMCI converters had lower baseline levels of p-Tau 181 (p=0.002) but larger annual changes (p=0.001) than aMCI non-converters. The change in p-Tau 181 levels showed better discriminatory capacity than the change in t-Tau levels in terms of identifying AD conversion in patients with aMCI, with an area under curve of 86.7% versus 72.2%. Conclusion We found changes in p-Tau 181 levels may be a suitable biomarker for identifying AD conversion.

Objective: Whether elevation in plasma levels of amyloid and tau protein biomarkers are better indicators of cognitive decline than higher baseline levels in patients with amnestic mild cognitive impairment (aMCI) and Alzheimer’s disease (AD) remains understudied. Methods: We included 67 participants with twice testing for AD-related plasma biomarkers via immunomagnetic reduction (IMR) assays (amyloid beta [Aβ]1-40, Aβ1-42, total tau [t-Tau], phosphorylated tau [p-Tau] 181, and alpha-synuclein [α-Syn]) and the Mini-Mental State Examination (MMSE) over a 1-year interval. We examined the correlation between biomarker levels (baseline vs. longitudinal change) and annual changes in the MMSE scores. Receiver operating characteristic curve analysis was conducted to compare the biomarkers. Results: After adjustment, faster cognitive decline was correlated with lower baseline levels of t-Tau (β=0.332, p=0.030) and p-Tau 181 (β=0.369, p=0.015) and rapid elevation of t-Tau (β=-0.330, p=0.030) and p-Tau 181 levels (β=-0.431, p=0.004). However, the levels (baseline and longitudinal changes) of Aβ1-40, Aβ1-42, and α-Syn were not correlated with cognitive decline. aMCI converters had lower baseline levels of p-Tau 181 (p=0.002) but larger annual changes (p=0.001) than aMCI non-converters. The change in p-Tau 181 levels showed better discriminatory capacity than the change in t-Tau levels in terms of identifying AD conversion in patients with aMCI, with an area under curve of 86.7% versus 72.2%. Conclusion We found changes in p-Tau 181 levels may be a suitable biomarker for identifying AD conversion.

Objective: Whether elevation in plasma levels of amyloid and tau protein biomarkers are better indicators of cognitive decline than higher baseline levels in patients with amnestic mild cognitive impairment (aMCI) and Alzheimer’s disease (AD) remains understudied. Methods: We included 67 participants with twice testing for AD-related plasma biomarkers via immunomagnetic reduction (IMR) assays (amyloid beta [Aβ]1-40, Aβ1-42, total tau [t-Tau], phosphorylated tau [p-Tau] 181, and alpha-synuclein [α-Syn]) and the Mini-Mental State Examination (MMSE) over a 1-year interval. We examined the correlation between biomarker levels (baseline vs. longitudinal change) and annual changes in the MMSE scores. Receiver operating characteristic curve analysis was conducted to compare the biomarkers. Results: After adjustment, faster cognitive decline was correlated with lower baseline levels of t-Tau (β=0.332, p=0.030) and p-Tau 181 (β=0.369, p=0.015) and rapid elevation of t-Tau (β=-0.330, p=0.030) and p-Tau 181 levels (β=-0.431, p=0.004). However, the levels (baseline and longitudinal changes) of Aβ1-40, Aβ1-42, and α-Syn were not correlated with cognitive decline. aMCI converters had lower baseline levels of p-Tau 181 (p=0.002) but larger annual changes (p=0.001) than aMCI non-converters. The change in p-Tau 181 levels showed better discriminatory capacity than the change in t-Tau levels in terms of identifying AD conversion in patients with aMCI, with an area under curve of 86.7% versus 72.2%. Conclusion We found changes in p-Tau 181 levels may be a suitable biomarker for identifying AD conversion.

Objective: Whether elevation in plasma levels of amyloid and tau protein biomarkers are better indicators of cognitive decline than higher baseline levels in patients with amnestic mild cognitive impairment (aMCI) and Alzheimer’s disease (AD) remains understudied. Methods: We included 67 participants with twice testing for AD-related plasma biomarkers via immunomagnetic reduction (IMR) assays (amyloid beta [Aβ]1-40, Aβ1-42, total tau [t-Tau], phosphorylated tau [p-Tau] 181, and alpha-synuclein [α-Syn]) and the Mini-Mental State Examination (MMSE) over a 1-year interval. We examined the correlation between biomarker levels (baseline vs. longitudinal change) and annual changes in the MMSE scores. Receiver operating characteristic curve analysis was conducted to compare the biomarkers. Results: After adjustment, faster cognitive decline was correlated with lower baseline levels of t-Tau (β=0.332, p=0.030) and p-Tau 181 (β=0.369, p=0.015) and rapid elevation of t-Tau (β=-0.330, p=0.030) and p-Tau 181 levels (β=-0.431, p=0.004). However, the levels (baseline and longitudinal changes) of Aβ1-40, Aβ1-42, and α-Syn were not correlated with cognitive decline. aMCI converters had lower baseline levels of p-Tau 181 (p=0.002) but larger annual changes (p=0.001) than aMCI non-converters. The change in p-Tau 181 levels showed better discriminatory capacity than the change in t-Tau levels in terms of identifying AD conversion in patients with aMCI, with an area under curve of 86.7% versus 72.2%. Conclusion We found changes in p-Tau 181 levels may be a suitable biomarker for identifying AD conversion.

Objective: Whether elevation in plasma levels of amyloid and tau protein biomarkers are better indicators of cognitive decline than higher baseline levels in patients with amnestic mild cognitive impairment (aMCI) and Alzheimer’s disease (AD) remains understudied. Methods: We included 67 participants with twice testing for AD-related plasma biomarkers via immunomagnetic reduction (IMR) assays (amyloid beta [Aβ]1-40, Aβ1-42, total tau [t-Tau], phosphorylated tau [p-Tau] 181, and alpha-synuclein [α-Syn]) and the Mini-Mental State Examination (MMSE) over a 1-year interval. We examined the correlation between biomarker levels (baseline vs. longitudinal change) and annual changes in the MMSE scores. Receiver operating characteristic curve analysis was conducted to compare the biomarkers. Results: After adjustment, faster cognitive decline was correlated with lower baseline levels of t-Tau (β=0.332, p=0.030) and p-Tau 181 (β=0.369, p=0.015) and rapid elevation of t-Tau (β=-0.330, p=0.030) and p-Tau 181 levels (β=-0.431, p=0.004). However, the levels (baseline and longitudinal changes) of Aβ1-40, Aβ1-42, and α-Syn were not correlated with cognitive decline. aMCI converters had lower baseline levels of p-Tau 181 (p=0.002) but larger annual changes (p=0.001) than aMCI non-converters. The change in p-Tau 181 levels showed better discriminatory capacity than the change in t-Tau levels in terms of identifying AD conversion in patients with aMCI, with an area under curve of 86.7% versus 72.2%. Conclusion We found changes in p-Tau 181 levels may be a suitable biomarker for identifying AD conversion.

Objective:To investigate the effects of Ziyin Liangxue formula combined with prednisone on immune function and the ST2/IL-33 pathway in mice with immune thrombocytopenia.Methods:In 40 BALB/c mice,32 were constructed as immune thrombocytopenia mouse models by antiplatelet serum injection.After successful modeling,the mice were randomly divided into model group,Ziyin Liangxue formula group(0.2 ml/10 g),prednisone group(0.2 ml/10 g),and Ziyin Liangxue formula+prednisone group(0.2 ml/10 g),8 mice in each group,and the other 8 mice were set as control group.The drugs were administered by gavage at the dose,and the model group and control group were given equal amounts of saline by gavage once a day for 2 weeks of continuous intervention.Blood samples and spleen tissues were collected,the peripheral platelet count was measured by automatic hematology analyzer,the pathological changes in spleen tissue was observed by HE staining,the levels of serum transforming growth factor(TGF)-β,interleukin(IL)-17,and peripheral blood thrombopoietin(TPO)were detected by enzyme-linked immunosorbent assay(ELISA),the expression of IL-33,sST2,and ST2 in spleen tissue was detected by Western blot,and the cell counts of peripheral blood Th17 and Treg were detected by flow cytometry.Results:Compared with the control group,the number of platelets,the level of TPO,TGF-β,and Treg cells were significantly decreased(P＜().05),while the level of IL-17,Thl7 cells,and the expression of IL-33,sST2,and ST2 protein were significantly increased in the model group(P＜0.01).Compared with the model group,the number of platelets,the level of TPO,TGF-β,and Treg cells were significantly increased(P＜0.05),while the level of IL-17,Th17 cells,and the expression of IL-33,sST2,and ST2 protein were significantly decreased in the Ziyin Liangxue formula+prednisone group(P＜0.01).Conclusion:Ziyin Liangxue formula+prednisone can effectively regulate Th17/Treg balance,thus effectively improve immune thrombocytopenia,and the mechanism may be related to the regulation of ST2/IL-33 signaling pathway.