OBJECTIVE: To develop an objective quantitative evaluative model of manual acupuncture manipulation (MAM) using three-dimensional motion tracking technology and machine learning, so as to provide a new approach to the study on acupuncture and moxibustion education and manipulation standardization. METHODS: A total of 120 undergraduate students in the major of acupuncture-moxibustion and tuina were recruited. The Simi Motion Ver.8.5 motion tracking system was used to collect the data of three types of MAM, balanced reinforcing and reducing by twisting, reinforcing technique by twisting and reducing technique by twisting. Eight quantitative parameters covering movement performance and stability were established. With 5 types of machine learning algorithms (logistic regression, random forest, support vector machine, K-nearest neighbor, and decision tree) adopted, the evaluative model was constructed, and the feature importance analyzed. RESULTS: In the evaluation of different types of MAM, the support vector machine presented the best for the effects of the balanced reinforcing and reducing by twisting, and the reducing by twisting (accuracy rates were both 0.88); and the logistic regression algorithm showed the optimal performance in evaluating the reinforcing by twisting (1.00 of accuracy rate). Feature importance analysis revealed that twisting velocity was the dominant parameter for evaluating the balanced reinforcing-reducing manipulation. The reinforcing and reducing of acupuncture techniques were more dependent on the left-hand twisting parameters and comprehensive performances, respectively. CONCLUSION The objective evaluative model of MAM based on three-dimensional motion tracking technology and machine learning demonstrates a reliable evaluative performance, providing a new technical approach to standardized assessment in acupuncture and moxibustion education.
Humans ; Male ; Acupuncture Therapy/instrumentation* ; Machine Learning ; Female ; Young Adult ; Adult ; Motion

Objective:To study the relationship between the levels of multiple elements in urine and the risk of arsenic poisoning in populations exposed to drinking water arsenic in Inner Mongolia Autonomous Region (Inner Mongolia).Methods:From April 2023 to January 2024, a case-control study method was used to select 128 individuals with a residence time of ≥10 years in drinking water arsenic exposed areas in Inner Mongolia as study subjects. Eighty-one individuals diagnosed with arsenic poisoning were selected as the case group, and 47 healthy individuals were selected as the control group for urine sample collection and questionnaire survey. Inductively coupled plasma mass spectrometry was employed to determine the levels of 10 elements (chromium, manganese, cobalt, nickel, copper, zinc, arsenic, molybdenum, cadmium and lead) in urine. The levels of each element in urine were divided into four groups ( Q1, Q2, Q3, and Q4 groups) based on quartiles. The associations between the levels of various elements in urine and the risk of arsenic poisoning were studied using binary logistic regression model and restricted cubic spline (RCS). Results:The age of the control group and the case group [ M ( Q1, Q3)] were 61 (53, 69) and 61 (56, 67) years old, respectively. There were 19 and 43 males, and 28 and 38 females, respectively. There was no statistically significant differences in age and and gender composition between the two groups ( Z = - 0.39, P = 0.700; χ 2 = 1.91, P = 0.167). The levels of urinary copper and cadmium of the case group were higher than those of the control group, and the differences were statistically significant ( Z = - 2.66, - 2.16, P < 0.05). The results of univariate logistic regression analysis showed that urinary copper was an influencing factor for arsenic poisoning ( P = 0.017). The results of multivariate logistic regression analysis revealed that after adjusting for covariates, urinary copper and arsenic were independent influencing factors of arsenic poisoning ( P < 0.05). Taking Q1 group as a reference, urinary copper in Q3 group [ OR (95% CI) = 8.23 (1.81, 37.39), P = 0.006] increased the risk of arsenic poisoning, while urinary arsenic in Q2, Q3, and Q4 groups [ OR (95% CI) = 0.24 (0.06, 0.92), 0.12 (0.03, 0.53), 0.15 (0.04, 0.63), P < 0.05] decreased the risk of arsenic poisoning. After adjusting for covariates, RCS did not show a dose-response relationship between urinary copper, urinary arsenic, and arsenic poisoning ( P > 0.05). Conclusion:Urinary arsenic and copper are associated with the risk of arsenic poisoning in the drinking water arsenic exposed areas of Inner Mongolia, copper exposure may contribute significantly to arsenic poisoning.

Objective:To analyze the influence factors behind the effective prevention and control of Kashin-Beck disease (KBD) in Tibet Autonomous Region (Tibet).Methods:Based on the data of KBD in Tibet in 2010 and 2015 provided by the Tibet Center for Disease Control and Prevention, the contribution of different prevention and control measures for KBD in Tibet was analyzed from the natural environment and socio-economic aspects (including vegetation coverage, economic level, industrial structure, dietary nutrition, planting structure, land use, aid to Tibet policy and medical care) by using the method of optimal parameters-based geographical detector.Results:There were differences in the explanatory power of various influencing factors on the prevention and control effect of KBD in different periods. In 2010, the proportion of forest area and per capita food consumption of farmers and herdsmen were the dominant factors ( q = 0.482, 0.366, P < 0.05). In 2015, the normalized vegetation index, the proportion of sown area of grain and oil crops, and the proportion of forest area were dominant ( q = 0.378, 0.334, 0.323, P < 0.05). The interaction between various influencing factors was stronger than that of single factor. In 2010, the explanatory power of the interaction between the proportion of forest area and grassland area was the highest ( q = 0.737), followed by the interaction between the proportion of agricultural and animal husbandry output value and the proportion of forest area ( q = 0.688). In 2015, the explanatory power of the interaction between per capita disposable income of farmers and herdsmen and the proportion of agricultural and animal husbandry output value was the highest ( q = 0.844), followed by the interaction between per capita disposable income of farmers and herdsmen and the proportion of arable land area ( q = 0.808). Conclusion:The key to the prevention and control of KBD in Tibet is to improve the economic level, improve the dietary nutrition of residents, adjust the structure of agriculture and animal husbandry and agricultural planting, and change the land use mode.

Objective:To analyze the influence factors behind the effective prevention and control of Kashin-Beck disease (KBD) in Tibet Autonomous Region (Tibet).Methods:Based on the data of KBD in Tibet in 2010 and 2015 provided by the Tibet Center for Disease Control and Prevention, the contribution of different prevention and control measures for KBD in Tibet was analyzed from the natural environment and socio-economic aspects (including vegetation coverage, economic level, industrial structure, dietary nutrition, planting structure, land use, aid to Tibet policy and medical care) by using the method of optimal parameters-based geographical detector.Results:There were differences in the explanatory power of various influencing factors on the prevention and control effect of KBD in different periods. In 2010, the proportion of forest area and per capita food consumption of farmers and herdsmen were the dominant factors ( q = 0.482, 0.366, P < 0.05). In 2015, the normalized vegetation index, the proportion of sown area of grain and oil crops, and the proportion of forest area were dominant ( q = 0.378, 0.334, 0.323, P < 0.05). The interaction between various influencing factors was stronger than that of single factor. In 2010, the explanatory power of the interaction between the proportion of forest area and grassland area was the highest ( q = 0.737), followed by the interaction between the proportion of agricultural and animal husbandry output value and the proportion of forest area ( q = 0.688). In 2015, the explanatory power of the interaction between per capita disposable income of farmers and herdsmen and the proportion of agricultural and animal husbandry output value was the highest ( q = 0.844), followed by the interaction between per capita disposable income of farmers and herdsmen and the proportion of arable land area ( q = 0.808). Conclusion:The key to the prevention and control of KBD in Tibet is to improve the economic level, improve the dietary nutrition of residents, adjust the structure of agriculture and animal husbandry and agricultural planting, and change the land use mode.

Objective:To study the relationship between the levels of multiple elements in urine and the risk of arsenic poisoning in populations exposed to drinking water arsenic in Inner Mongolia Autonomous Region (Inner Mongolia).Methods:From April 2023 to January 2024, a case-control study method was used to select 128 individuals with a residence time of ≥10 years in drinking water arsenic exposed areas in Inner Mongolia as study subjects. Eighty-one individuals diagnosed with arsenic poisoning were selected as the case group, and 47 healthy individuals were selected as the control group for urine sample collection and questionnaire survey. Inductively coupled plasma mass spectrometry was employed to determine the levels of 10 elements (chromium, manganese, cobalt, nickel, copper, zinc, arsenic, molybdenum, cadmium and lead) in urine. The levels of each element in urine were divided into four groups ( Q1, Q2, Q3, and Q4 groups) based on quartiles. The associations between the levels of various elements in urine and the risk of arsenic poisoning were studied using binary logistic regression model and restricted cubic spline (RCS). Results:The age of the control group and the case group [ M ( Q1, Q3)] were 61 (53, 69) and 61 (56, 67) years old, respectively. There were 19 and 43 males, and 28 and 38 females, respectively. There was no statistically significant differences in age and and gender composition between the two groups ( Z = - 0.39, P = 0.700; χ 2 = 1.91, P = 0.167). The levels of urinary copper and cadmium of the case group were higher than those of the control group, and the differences were statistically significant ( Z = - 2.66, - 2.16, P < 0.05). The results of univariate logistic regression analysis showed that urinary copper was an influencing factor for arsenic poisoning ( P = 0.017). The results of multivariate logistic regression analysis revealed that after adjusting for covariates, urinary copper and arsenic were independent influencing factors of arsenic poisoning ( P < 0.05). Taking Q1 group as a reference, urinary copper in Q3 group [ OR (95% CI) = 8.23 (1.81, 37.39), P = 0.006] increased the risk of arsenic poisoning, while urinary arsenic in Q2, Q3, and Q4 groups [ OR (95% CI) = 0.24 (0.06, 0.92), 0.12 (0.03, 0.53), 0.15 (0.04, 0.63), P < 0.05] decreased the risk of arsenic poisoning. After adjusting for covariates, RCS did not show a dose-response relationship between urinary copper, urinary arsenic, and arsenic poisoning ( P > 0.05). Conclusion:Urinary arsenic and copper are associated with the risk of arsenic poisoning in the drinking water arsenic exposed areas of Inner Mongolia, copper exposure may contribute significantly to arsenic poisoning.

Objective To study the relationship between environment selenium distribution characteristic and Kaschin-Beck disease (KBD) in the Yarlung Zangbo River banks and to provide some measures for prevention and control of KBD in the north side of the river bank.Methods Considering the geography and KBD distribution,we made a survey in Xietongmen (KBD area),Lazi and Sajia (non-KBD area) counties in 2013 and 2015.Water,soil,herbage,grain food and children hair samples were collected.Selenium of the samples was measured by hydride generation-atomic fluorescence spectrometry.Results A total of 246 samples of natural soil,cultivated soil,drinking water,food and forage,and 103 samples of children hair were collected.The selenium in natural soil,cultivated soil,herbage,barley,tsampa,self-produced wheat in non-KBD area in the south side of Yarlung Zangbo River bank were significantly higher than those in KBD areas in the north side [mean (μg/kg):288.62 vs 134.90,228.26 vs 160.28,41.85 vs 5.10,13.99 vs 4.02,12.64 vs 8.07,27.44 vs 13.56,U =7,23,0,19,62,0,P ＜ 0.05].Hair selenium in school children in KBD area in the north side was higher than that previously reported,but still significantly lower than that in non-KBD areas in the south side of the river bank [mg/kg:0.221 vs 0.306,U =650,P ＜ 0.01],and about 65.45％ (36/55)of school children in KBD area were at a risk of selenium deficiency in the north of the Yarlung Zangbo River bank.Conclusions The selenium contem in the food chain of soilplants-animals (human being) is significantly lower in KBD area in the north side of Yarlung Zangbo River bank than that in non-KBD areas in the south side.It's still a key factor for the occurrence and prevalence of KBD that low selenium in environment in KBD areas in the north side.