Objective:To study the relationship between urinary arsenic methylation metabolism patterns and skin keratinization and pigmentation abnormalities in population exposed to arsenic through drinking water.Methods:Using a cross-sectional study method, a survey on endemic arsenic poisoning was conducted among permanent residents of drinking water endemic arsenic poisoning areas in Bayannur City, Inner Mongolia Autonomous Region in 2004 (before water improvement). In 2017 (after water improvement), 71 arsenic exposed individuals were followed up as survey subjects. According to the "Diagnosis of Endemic Arsenism" (WS/T 211-2015), the clinical grading of skin injuries (skin keratinization, pigmentation abnormalities) in the survey subjects was evaluated. Urine samples were collected for detection of arsenic methylation metabolite levels by high-performance liquid chromatography inductively coupled plasma mass spectrometry and calibrated with urinary creatinine. The changes and amplitudes of urinary arsenic methylation indicators before and after water improvement were calculated and analyzed according to the outcome of skin keratinization and pigmentation abnormalities which were divided into reduced, unchanged, and added groups.Results:(1) The changes in urinary total arsenic (TAs), inorganic arsenic (iAs), monomethyl arsenic (MMA), and dimethyl arsenic (DMA) levels in different outcome groups of skin keratinization were compared, and the differences were statistically significant ( H = 9.08, 8.77, 9.28, 8.57, P < 0.05). The changes in urinary TAs, iAs, MMA, DMA levels, iAs percentage (iAs%), DMA percentage (DMA%), and primary methylation index (PMI) in different outcome groups of skin pigmentation abnormalities were compared, and the differences were statistically significant ( H = 8.04, 10.67, 8.29, 9.14, 6.30, 9.10, 7.20, P < 0.05). (2) The comparison of amplitudes in urinary TAs, iAs, MMA, and DMA levels in different outcome groups of skin keratinization showed statistically significant differences ( H = 6.92, 7.34, 6.66, 6.16, P < 0.05). The amplitudes in urinary iAs level, iAs%, DMA%, and PMI in different outcome groups of skin pigmentation abnormalities were compared, and the differences were statistically significant ( H = 7.94, 7.61, 9.95, 7.22, P < 0.05). Conclusion:The changes pattern of urinary TAs, iAs, MMA, DMA, iAs%, DMA%, and PMI in population exposed to arsenic through drinking water is related to the transformation of skin keratinization and pigmentation abnormalities.

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 establish a reliable prediction model for radiation pneumonitis(RP)based on multi-regional radiomics analysis of localizable CT images.Methods A retrospective analysis was conducted on 185 patients who received radiotherapy from January 2021 to June 2023 in the Department of Radiotherapy,Xuzhou Cancer Hospital.Patients were classified as having RP or not based on imaging combined with clinical diagnosis.Three regions of interest(ROI)were defined in the localizable CT images:Lung,Lung-PTV and PTV,and their radiomics features were extracted.After feature screening using methods such as Mann-Whitney Utest,recursive feature elimination,and Lasso,a prediction model was established using support vector machine classification algorithm.The model performance was validated using 6 evaluation metrics:the area under the receiver operating characteristic curve(AUC),accuracy,specificity,sensitivity,positive predictive value,and negative predictive value.Results The prediction model consisted of 7 radiomics features.The clinical model of target-to-lung ratio,PTV model,Lung model,and Lung-PTV model achieved AUC values of 0.535,0.801,0.672,and 0.706 in the test set,respectively.The AUC value and accuracy of PTV model reached 0.843 and 0.775 in the training set,while 0.801 and 0.750 in the test set.PTV model was superior to Lung model,Lung-PTV model,and clinical model in predictive performance.The AUC values of the combined PTV+(Lung-PTV)model in the training and test sets were 0.867 and 0.806,respectively,higher than those of PTV model and Lung-PTV model.Conclusion The predictive ability of the prediction models constructed from radiomics features in different ROI for symptomatic RP varies.The radiomics prediction model using PTV as ROI exhibits superior predictive performance,and the combined multi-regional radiomics model can further improve the predictive ability for RP.

Objective To establish a reliable prediction model for radiation pneumonitis(RP)based on multi-regional radiomics analysis of localizable CT images.Methods A retrospective analysis was conducted on 185 patients who received radiotherapy from January 2021 to June 2023 in the Department of Radiotherapy,Xuzhou Cancer Hospital.Patients were classified as having RP or not based on imaging combined with clinical diagnosis.Three regions of interest(ROI)were defined in the localizable CT images:Lung,Lung-PTV and PTV,and their radiomics features were extracted.After feature screening using methods such as Mann-Whitney Utest,recursive feature elimination,and Lasso,a prediction model was established using support vector machine classification algorithm.The model performance was validated using 6 evaluation metrics:the area under the receiver operating characteristic curve(AUC),accuracy,specificity,sensitivity,positive predictive value,and negative predictive value.Results The prediction model consisted of 7 radiomics features.The clinical model of target-to-lung ratio,PTV model,Lung model,and Lung-PTV model achieved AUC values of 0.535,0.801,0.672,and 0.706 in the test set,respectively.The AUC value and accuracy of PTV model reached 0.843 and 0.775 in the training set,while 0.801 and 0.750 in the test set.PTV model was superior to Lung model,Lung-PTV model,and clinical model in predictive performance.The AUC values of the combined PTV+(Lung-PTV)model in the training and test sets were 0.867 and 0.806,respectively,higher than those of PTV model and Lung-PTV model.Conclusion The predictive ability of the prediction models constructed from radiomics features in different ROI for symptomatic RP varies.The radiomics prediction model using PTV as ROI exhibits superior predictive performance,and the combined multi-regional radiomics model can further improve the predictive ability for RP.

Attention-deficit/hyperactivity disorder(ADHD)is a common behavioral disorder in children and has significant non-specific symptoms.The specific pathogenesis of ADHD remains unclear.Chinese medicine has a unique advantage in treating this disease.The"qi cycle in round"theory is a unique diagnosis and treatment system constructed by Huang Yuanyu,a Qing Dynasty physician,through systematic integration and innovative development of the theoretical framework of traditional Chinese medicine,which is widely used in clinical practice.Based on the"qi cycle in round"theory,the pathogenesis of ADHD in children was discussed,and the abnormal middle qi was proposed as the root cause of the disease,with hyperactivity of the liver,lung depletion,and fire as the key contributing factors.Guided by the"qi cycle in round"theory in the treatment of ADHD in children,the approach focuses on restoring and balancing central qi.It emphasized the understanding of the overall changes in the spleen,stomach,lungs,liver,heart,kidney,and other viscera,along with the movement of qi.Treatment focuses on methods such as lifting clear yang,reducing stomach turbidity,softening the liver and quenching the wind,suppressing the lungs and reducing the inversion,and reducing the fire and returning to the yuan.These interventions aim to promote the smooth circulation of the qi circulation from multiple perspectives,thereby facilitating recovery.

Objective To construct an evaluation index system for new quality productive forces in health,providing a quantifiable reference for assessing the development of new quality productive forces in the healthcare sector.Methods Prelimi-nary indicators were screened through literature research.The Delphi expert consultation method was then used to optimize and adjust the indicator framework.Finally,the analytic hierarchy process(AHP)was applied to determine the weights of each indi-cator,ultimately establishing the evaluation index system.Results The constructed evaluation index system for new quality pro-ductive forces in health includes 6 first-level indicators,12 second-level indicators,and 27 third-level indicators.Conclusion The evaluation index system for new quality productive forces in health,based on factor resource allocation,is scientifically and reasonably designed.It can provide a theoretical basis and reference for the assessment of new quality productive forces in health-care at the national,provincial,and municipal levels.

Objective To study the expression of N6-methyladenosine(m6A)methyltransferase-like protein 16(METTL16),Ankyrin repeat and SOCS box containing protein 4(ASB13)in elderly breast cancer tissues and their relationship with clinicopathological features and prognosis.Methods 124 elderly patients with breast cancer diagnosed and treated in the Zibo 148 Hospital from January 2019 to January 2021 were selected.Immunohistochemistry(IHC)was used to detect the expression of METTL16 and ASB13 proteins in tissues.Real time fluorescence quantitative PCR(RT-qPCR)was used to detect the expression of METTL16 mRNA and ASB13 mRNA in tissues.Pearson correlation was used for correlation analysis.Survival analysis used Kaplan-Meier curves and Log Rank tests to compare the prognostic differences among patients with different METTL16 and ASB13 expression levels.COX regression analysis was used to analyze the prognostic factors of elderly patients with breast cancer.Results The positive rate of METTL16 in cancer tissue(70.97%)was higher than that in adjacent tissues(8.06%),while the positive rate of ASB13(22.58%)was lower than that in adjacent tissues(72.58%),the differences were statistically significant(χ2=102.642,62.146,all P<0.001).METTL16 mRNA,Snail mRNA and N-cadherin(N-cd)mRNA were higher in cancer tissues than in adjacent tissues,while ASB13 mRNA was lower in adjacent tissues,the differences were statistically significant(t=40.498～48.624,all P<0.001).METTL16 mRNA was positively correlated with Snail mRNA and N-cd mRNA in cancer tissue(r=0.712,0.669,all P<0.001),while ASB13 mRNA was negatively correlated with Snail mRNA and N-cd mRNA(r=-0.734,-0.759,all P<0.001).Compared with TNM stage Ⅰ-Ⅱ and patients with high to medium differentiation,patients with TNM stage Ⅲ and low differentiation had higher positive rate of METTL16 in cancer tissue and lower positive rate of ASB13,the differences were statistically significant(χ2=5.340～10.370,all P<0.05).The 3-year progression free survival rate(73.86%)of the METTL16 positive group was lower than that of the METTL16 negative group(88.89%),the 3-year progression free survival rate(92.86%)of the ASB13 positive group was higher than that of the ASB13 negative group(73.96%),and the differences were statistically significant(Log Rank χ2=4.483,4.882,all P<0.005).METTL16 positive,TNM stage Ⅲ,poor differentiation were risk factors affecting the prognosis of elderly breast cancer,and ASB13 positive was protective factors(Wald χ2=5.056～9.267,all P<0.001).Conclusion METTL16 expression is up-regulated and ASB13 expression is down-regulated in elderly breast cancer,both of which are related to the expression of invasion and metastasis genes,and are new prognostic markers for elderly breast cancer.

Objective:To investigate the influencing factors of adult dental fluorosis in drinking water-borne endemic fluorosis areas of Inner Mongolia Autonomous Region.Methods:A case-control study was conducted in January 2024 to select adult fluorosis patients (case group) and healthy individuals (control group) from the drinking water-borne endemic fluorosis areas in Helinger County, Hohhot City, Inner Mongolia Autonomous Region as the survey subjects. Urine samples were collected to determine urinary fluoride concentration. A questionnaire survey was conducted. SPSS 25.0 software was used for χ 2 test and multivariate logistic regression analysis. Restricted cubic spline (RCS) was used to analyze the association between urinary fluoride concentration and the risk of dental fluorosis in adults. Results:A total of 161 individuals were included in the survey, including 100 in the case group and 61 in the control group. The results of univariate analysis showed that there were statistically significant differences in the distribution of gender, smoking, and urinary fluoride concentration between the case group and the control group (χ 2 = 7.54, 5.02, 9.69, P < 0.05). The results of multivariate logistic regression analysis indicated that gender ( OR = 0.36, 95% CI: 0.18 - 0.73, P = 0.005) and urinary fluoride concentration ( OR = 3.08, 95% CI: 1.46 - 6.67, P = 0.003) were the influencing factors of adult fluorosis. RCS analysis showed a significant linear dose-response relationship between the risk of dental fluorosis and urinary fluoride concentration ( Poverall trend = 0.001, Pnonlinear = 0.071). When the urinary fluoride concentration was greater than 1.57 mg/L, the risk of dental fluorosis increased with the increase of urinary fluoride concentration. Conclusion:Gender and urinary fluoride concentration are the risk factors of dental fluorosis in adults in drinking water-borne endemic fluorosis areas of Inner Mongolia Autonomous Region.

The radiation-free and unmarked body surface monitoring technology is developed for reducing the additional radiation dose generated by positioning error verification during radiotherapy positioning,and further reducing the positioning error and monitoring the displacement deviation of patients during radiotherapy in real time.At present,the widely used optical surface guided radiotherapy technology is also a type of radiotherapy guided by body surface monitoring.The system mainly uses optical imaging equipment as a tool to complete body surface scanning,three-dimensional reconstruction,real-time monitoring,etc.,thereby assisting doctors to carry out radiotherapy more accurately.Herein the study elaborates on the methods,technologies and research results of guided radiotherapy from the aspects of body surface markers,three-dimensional surface imaging systems and mobile devices,and provides prospects for future researches.

Objective:To quantitatively detect plasma ceramide (Cer) levels using high-performance liquid chromatography tandem mass spectrometry (LC-MS/MS) and analyze plasma ceramide levels in homozygous familial hypercholesterolemia (HoFH) patients.Methods:A case-control study was conducted. Plasma samples were collected from 70 healthy individuals who underwent physical examinations at the Health Check-Up Center of Suzhou Municipal Hospital between October 2023 and December 2023, as well as from 34 HoFH patients (including 11 patients with concomitant coronary artery disease) who were treated in the Cardiology Department of the same hospital during the same period. Deuterated isotopes were used as internal standards, and a Phenomenex Kinetex C18 column (2.1×100 mm, 2.6 μm) was employed for separation. An LC-MS/MS method was developed using an AB Sciex 6500+triple quadrupole mass spectrometer for the detection of ceramides, followed by method validation. Additionally, the differences in ceramide levels among healthy individuals, HoFH patients, and HoFH patients with concomitant coronary artery disease were compared. Receiver operating characteristic (ROC) curves were used to evaluate the diagnostic value of various ceramides for HoFH.Results:A method for the quantification of 9 plasma ceramides was established, showing excellent linearity ( r>0.99), precision (1.8%-11.0%), and recovery rates (89.9%-114.7%), meeting the requirements for detection. Compared to the control group, the HoFH group exhibited significantly higher levels of Cer(d18∶1/14∶0), Cer(d18∶1/16∶0), Cer (d18∶1/18∶0), Cer (d18∶1/18∶1), Cer (d18∶1/20∶0), Cer(d18∶1/22∶0), Cer(d18∶1/24∶0), and Cer(d18∶1/24∶1) ( P<0.05). ROC curve analysis revealed that Cer(d18∶1/18∶0) had the highest diagnostic value for HoFH, with an area under the curve (AUC) of 0.83, a cutoff value of 64.6 ng/ml, and sensitivity and specificity of 82.4% and 87.1%, respectively. In HoFH patients complicated with coronary artery disease, the plasma ceramide levels of Cer(d18∶1/18∶0) [(155.7±25.1) ng/ml vs (103.0±11.1) ng/ml, P=0.03] and the ratio of Cer (d18∶1/18∶0) to Cer(d18∶1/24∶0) (0.077±0.012 vs 0.048±0.006, P=0.03) were significantly higher than in HoFH patients without coronary artery disease. Conclusion:A quantitative LC-MS/MS method was developed for detecting ceramides in human plasma, which shows potential diagnostic value for patients with HoFH.