1.Anti-central-fatigue effect of maca via mitochondrial biogenesis via the AMPK/SIRT1/PGC-1α pathway in rats
Wenhuan YAO ; Wen ZHOU ; Yaxuan LI ; Ziyao LI ; Jing ZHANG ; Shibo LYU ; Hui LI
Chinese Journal of Comparative Medicine 2025;35(7):36-43
Objective To examine the anti-central-fatigue function of maca and its underlying mechanism.Methods Forty Sprague-Dawley rats were divided randomly into a negative control group,model control group,and low-,medium-,and high-dose maca groups(0.6,1.2,and 2.4 g/kg·body weight).Rats in all groups except the negative control group were subjected to multi-factor stimulation,including cold-water swimming,sleep deprivation,restraining,and tail-clamping,to establish central fatigue rat models.Rats in the low-,medium-,and high-dose maca groups received 0.6,1.2,or 2.4 g/kg maca,respectively,by gavage for 35 days.Behavioral testing was carried out using the Morris water-maze,sucrose-preference,and tail-suspension tests.Markers of oxidative stress in the hippocampus,including superoxide dismutase(SOD),malondialdehyde(MDA),and catalase(CAT),were detected using test kits.Proteins connected with the AMP-activated protein kinase(AMPK)/sirtuin 1(SIRT1)/peroxisome proliferator-activated receptor γ coactivator 1-α(PGC-1α)signaling pathway in the hippocampus were detected by Western blot.Results Rats in the low-,medium-,and high-dose maca groups spent significantly more time in the target quadrant compared with the model control group(P<0.05 or P<0.01),but there was no significant dose-effect relationship.Rats in the medium-and high-dose maca groups showed decreased escape latency(P<0.05),increased time crossing the platform location(P<0.05),increased sucrose preference(P<0.05),decreased tail suspension time(P<0.05),increased the activities of CAT(P<0.01)and SOD(P<0.05),and decreased MDA content(P<0.01).Rats in the low-,medium-,and high-dose maca groups also showed significantly increased protein expression levels of AMPK and nuclear respiratory factor 1(P<0.01 or P<0.05),but no significant dose-effect relationship was observed.Rats in the medium-and high-dose maca groups showed increased protein expression of PGC-1α(P<0.05 or P<0.01),and rats in the high-dose maca group showed increased protein expression of SIRT1 and mitochondrial transcription factor A(P<0.05 or P<0.01).Conclusions Maca can improve the indicators of central fatigue in rats,determined by behavioral testing and oxidative stress-related factors.The underlying mechanism may be related to its regulatory effects on the AMPK/SIRT1/PGC-1α signaling pathway.
2.Anti-central-fatigue effect of maca via mitochondrial biogenesis via the AMPK/SIRT1/PGC-1α pathway in rats
Wenhuan YAO ; Wen ZHOU ; Yaxuan LI ; Ziyao LI ; Jing ZHANG ; Shibo LYU ; Hui LI
Chinese Journal of Comparative Medicine 2025;35(7):36-43
Objective To examine the anti-central-fatigue function of maca and its underlying mechanism.Methods Forty Sprague-Dawley rats were divided randomly into a negative control group,model control group,and low-,medium-,and high-dose maca groups(0.6,1.2,and 2.4 g/kg·body weight).Rats in all groups except the negative control group were subjected to multi-factor stimulation,including cold-water swimming,sleep deprivation,restraining,and tail-clamping,to establish central fatigue rat models.Rats in the low-,medium-,and high-dose maca groups received 0.6,1.2,or 2.4 g/kg maca,respectively,by gavage for 35 days.Behavioral testing was carried out using the Morris water-maze,sucrose-preference,and tail-suspension tests.Markers of oxidative stress in the hippocampus,including superoxide dismutase(SOD),malondialdehyde(MDA),and catalase(CAT),were detected using test kits.Proteins connected with the AMP-activated protein kinase(AMPK)/sirtuin 1(SIRT1)/peroxisome proliferator-activated receptor γ coactivator 1-α(PGC-1α)signaling pathway in the hippocampus were detected by Western blot.Results Rats in the low-,medium-,and high-dose maca groups spent significantly more time in the target quadrant compared with the model control group(P<0.05 or P<0.01),but there was no significant dose-effect relationship.Rats in the medium-and high-dose maca groups showed decreased escape latency(P<0.05),increased time crossing the platform location(P<0.05),increased sucrose preference(P<0.05),decreased tail suspension time(P<0.05),increased the activities of CAT(P<0.01)and SOD(P<0.05),and decreased MDA content(P<0.01).Rats in the low-,medium-,and high-dose maca groups also showed significantly increased protein expression levels of AMPK and nuclear respiratory factor 1(P<0.01 or P<0.05),but no significant dose-effect relationship was observed.Rats in the medium-and high-dose maca groups showed increased protein expression of PGC-1α(P<0.05 or P<0.01),and rats in the high-dose maca group showed increased protein expression of SIRT1 and mitochondrial transcription factor A(P<0.05 or P<0.01).Conclusions Maca can improve the indicators of central fatigue in rats,determined by behavioral testing and oxidative stress-related factors.The underlying mechanism may be related to its regulatory effects on the AMPK/SIRT1/PGC-1α signaling pathway.
3.Decision tree-enabled establishment and validation of intelligent verification rules for blood analysis results
Linlin QU ; Xu ZHAO ; Liang HE ; Yehui TAN ; Yingtong LI ; Xianqiu CHEN ; Zongxing YANG ; Yue CAI ; Beiying AN ; Dan LI ; Jin LIANG ; Bing HE ; Qiuwen SUN ; Yibo ZHANG ; Xin LYU ; Shibo XIONG ; Wei XU
Chinese Journal of Laboratory Medicine 2024;47(5):536-542
Objective:To establish a set of artificial intelligence (AI) verification rules for blood routine analysis.Methods:Blood routine analysis data of 18 474 hospitalized patients from the First Hospital of Jilin University during August 1st to 31st, 2019, were collected as training group for establishment of the AI verification rules,and the corresponding patient age, microscopic examination results, and clinical diagnosis information were collected. 92 laboratory parameters, including blood analysis report parameters, research parameters and alarm information, were used as candidate conditions for AI audit rules; manual verification combining microscopy was considered as standard, marked whether it was passed or blocked. Using decision tree algorithm, AI audit rules are initially established through high-intensity, multi-round and five-fold cross-validation and AI verification rules were optimized by setting important mandatory cases. The performance of AI verification rules was evaluated by comparing the false negative rate, precision rate, recall rate, F1 score, and pass rate with that of the current autoverification rules using Chi-square test. Another cohort of blood routine analysis data of 12 475 hospitalized patients in the First Hospital of Jilin University during November 1sr to 31st, 2023, were collected as validation group for validation of AI verification rules, which underwent simulated verification via the preliminary AI rules, thus performance of AI rules were analyzed by the above indicators. Results:AI verification rules consist of 15 rules and 17 parameters and do distinguish numeric and morphological abnormalities. Compared with auto-verification rules, the true positive rate, the false positive rate, the true negative rate, the false negative rate, the pass rate, the accuracy, the precision rate, the recall rate and F1 score of AI rules in training group were 22.7%, 1.6%, 74.5%, 1.3%, 75.7%, 97.2%, 93.5%, 94.7%, 94.1, respectively.All of them were better than auto-verification rules, and the difference was statistically significant ( P<0.001), and with no important case missed. In validation group, the true positive rate, the false positive rate, the true negative rate, the false negative rate, the pass rate, the accuracy, the precision rate, the recall rate and F1 score were 19.2%, 8.2%, 70.1%, 2.5%, 72.6%, 89.2%, 70.0%, 88.3%, 78.1, respectively, Compared with the auto-verification rules, The false negative rate was lower, the false positive rate and the recall rate were slightly higher, and the difference was statistically significant ( P<0.001). Conclusion:A set of the AI verification rules are established and verified by using decision tree algorithm of machine learning, which can identify, intercept and prompt abnormal results stably, and is moresimple, highly efficient and more accurate in the report of blood analysis test results compared with auto-vefication.
4. Analysis on the exposure level and geographic distribution trend of toxicological indicators in rural drinking water, Shandong Province, in 2015
Feng SHI ; Shibo LYU ; Fanling KONG ; Xuting YANG ; Jingyang ZHOU
Chinese Journal of Preventive Medicine 2017;51(9):843-847
Objective:
To analyze the exposure level and the geographical distribution trend of toxicological indicators of rural drinking water in Shandong Province.
Methods:
The drawing method was used to randomly select no less than 60% villages and towns from 137 counties (cities, districts) of 17 cities in Shandong Province in 2015, and then 1-3 rural centralized water supply units were selected according to the circumstance of rural centralized water supply units in each village and town. In total, 735 villages and towns, 1 473 rural centralized water supply units were selected, and 1 473 water samples were collected. The water treatment process, water supply population and other circumstances of the rural centralized water supply units were investigated, the water quality was monitored, the content of toxicological indicators of drinking water in different areas was compared, and the trend surface isogram of excessive toxicological indicators was drawn.
Results:
The qualified rate of toxicological indicators in 1 473 water samples was 83.64% (

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