Abstract: Objective　To evaluate the potential transmission risk of schistosomiasis in Yunnan Province, and to provide strategic basis for the prevention and control. Methods　Based on the prevalence of schistosomiasis, the social and environmental factors that may lead to the epidemic, 1-3 villages from 3 provincial-level and 15 county-level counties (cities and districts) were selected as the evaluated villages in 2021. The risk of schistosomiasis spread was analyzed comprehensively by consulting, reviewing and collecting routine surveillance data of schistosomiasis in the villages, combined with snail and wild feces survey. The risk level was evaluated for the positive snails, positive wild feces, resident infection, average density of live snails and snail frame occurrence rate. Results　Totally 7 snail counties schistosomiasis transmission was blocked of 18 epidemic counties and the rest were eliminated counties. A total of 152 447 snail frames were investigated and 3 043 frames with snails, 15 895 snails were captured and included 15 727 live snails in the 32 evaluated villages. The total area of snail was 58.87 hm2 and the area of reoccurrence was 34.19 hm2 with snail frame occurrence rate of 2.00% and average density of live snails 0.103 2/0.11 m2, and no positive snails were found by loop-mediated isothermal amplification (LAMP) assay. A total of 1 374 wild feces were collected in 27 evaluated villages of 14 epidemic counties, mainly from cattle, dogs, sheep, equine animals, pigs and so on, all of which were negative. According to the risk assessment of epidemic spread, Yongle Village and Yongsheng Village in Eryuan County, Zhiming Village in Chuxiong City were Ⅱ risk, and the rest were Ⅲ risk. Conclusions　Although the risk of transmission is low in Yunnan Province, the risk of transmission and spread still exists. It is necessary to strengthen the risk monitoring, control of snail and effective management of livestock to prevent the rebound of the epidemic.

OBJECTIVES: To investigate the risk factors for neonatal asphyxia in Hubei Enshi Tujia and Miao Autonomous Prefecture and establish a nomogram model for predicting the risk of neonatal asphyxia. METHODS: A retrospective study was conducted with 613 cases of neonatal asphyxia treated in 20 cooperative hospitals in Enshi Tujia and Miao Autonomous Prefecture from January to December 2019 as the asphyxia group, and 988 randomly selected non-asphyxia neonates born and admitted to the neonatology department of these hospitals during the same period as the control group. Univariate and multivariate analyses were used to identify risk factors for neonatal asphyxia. R software (4.2.2) was used to establish a nomogram model. Receiver operator characteristic curve, calibration curve, and decision curve analysis were used to assess the discrimination, calibration, and clinical usefulness of the model for predicting the risk of neonatal asphyxia, respectively. RESULTS: Multivariate logistic regression analysis showed that minority (Tujia), male sex, premature birth, congenital malformations, abnormal fetal position, intrauterine distress, maternal occupation as a farmer, education level below high school, fewer than 9 prenatal check-ups, threatened abortion, abnormal umbilical cord, abnormal amniotic fluid, placenta previa, abruptio placentae, emergency caesarean section, and assisted delivery were independent risk factors for neonatal asphyxia (P<0.05). The area under the curve of the model for predicting the risk of neonatal asphyxia based on these risk factors was 0.748 (95%CI: 0.723-0.772). The calibration curve indicated high accuracy of the model for predicting the risk of neonatal asphyxia. The decision curve analysis showed that the model could provide a higher net benefit for neonates at risk of asphyxia. CONCLUSIONS The risk factors for neonatal asphyxia in Hubei Enshi Tujia and Miao Autonomous Prefecture are multifactorial, and the nomogram model based on these factors has good value in predicting the risk of neonatal asphyxia, which can help clinicians identify neonates at high risk of asphyxia early, and reduce the incidence of neonatal asphyxia.
Infant, Newborn ; Humans ; Male ; Pregnancy ; Female ; Nomograms ; Retrospective Studies ; Cesarean Section ; Risk Factors ; Asphyxia Neonatorum/etiology*

Objective: To explore the association between cardiometabolic diseases (CMD) and quality of life, the association between CMD and perceived stress, and the mediation effect of perceived stress on the association between CMD and quality of life, and to provide evidence for the prevention and treatment of CMD and the improvement of quality of life in these patients. Methods: This is a cross-sectional study. Data were collected by the employees' physical examination of a company in Xi'an in 2021. Multiple linear regression models were used to analyze the association between the status of CMD (divided into three categories: no CMD, presence of one kind of CMD, and with≥2 kinds of CMD (≥2 kinds of CMD were defined as cardiometabolic multimorbidity (CMM)), quality of life, and perceived stress. Mediation analysis with a multi-categorical independent variable was conducted to determine the mediation effect of perceived stress on the association between CMD and quality of life. Results: Among all 4 272 participants, 1 457 (34.1%) participants had one kind of CMD and 677 (15.8%) participants had CMM. The average scores for quality of life and perceived stress were (57.5±15.7) and (16.9±7.9), respectively. Compared with participants without CMD, after adjusting for demographic and lifestyle factors, no statistically significant associations were observed between one kind of CMD and perceived stress or quality of life (both P>0.05). Perceived stress did not mediate the association between one kind of CMD and quality of life. However, participants with CMM had lower quality of life and higher perceived stress than participants without CMD. The relative total effect coefficient c (95%CI) and the relative direct effect coefficient c' (95%CI) between CMM and quality of life were -3.71 (-5.04--2.37) and -2.52 (-3.81--1.24) (both P<0.05), respectively. The relative indirect effect coefficient a₂b (95%CI) of perceived stress on the association between CMM and quality of life was -1.18 (-1.62--0.77) (P<0.05). The mediation effect size was 31.8%. Conclusions: CMM is negatively associated with quality of life and positively associated with perceived stress. Perceived stress partially mediates the association between CMM and quality of life. Our results suggest that, in addition to preventing and treating CMM actively, efforts should be taken to relieve the perceived stress of people with CMM to improve their quality of life.
Humans ; Quality of Life ; Cross-Sectional Studies ; Cardiovascular Diseases/complications* ; Stress, Psychological

Objective: To understand the distribution characteristics of age of Alzheimer's disease (AD) onset and influencing factors. Methods: Based on the follow-up data of Alzheimer's Disease Neuroimaging Initiative from 2005 to 2022, participants with normal cognition (CN) or mild cognitive impairment (MCI) at baseline survey, and those with progression to AD during follow-up period were selected as study subjects. Univariate analysis and multiple linear regression analysis were performed to explore the associations of gender, race, number of ApoE ε4 genes carried, family history, years of education and marital status with the age of AD onset. Results: A total of 405 participants, with an average age of (74.0±6.9) years at baseline survey, progressed to AD during follow up period. The age of AD onset was (76.6±7.5) years, and age of onset in men was about 1.9 years later than women. Multiple linear regression analysis showed that for each increase in ApoE ε4 gene number, the age of AD onset was about 0.344 years earlier. The age of AD onset was 4.007 years earlier for those with MCI at baseline survey compared with those with CN. Years of education were not significantly associated with the age of onset of AD (P>0.05). Conclusion: Those who carry ApoE ε4 gene, and have MCI at baseline survey might have earlier age of AD onset.
Aged ; Aged, 80 and over ; Female ; Humans ; Male ; Alzheimer Disease/genetics* ; Apolipoprotein E4/genetics* ; Cognition ; Cognition Disorders ; Cognitive Dysfunction/genetics*

OBJECTIVE: This study was aimed at investigating the carrier rate of, and molecular variation in, α- and β-globin gene mutations in Hunan Province. METHODS: We recruited 25,946 individuals attending premarital screening from 42 districts and counties in all 14 cities of Hunan Province. Hematological screening was performed, and molecular parameters were assessed. RESULTS: The overall carrier rate of thalassemia was 7.1%, including 4.83% for α-thalassemia, 2.15% for β-thalassemia, and 0.12% for both α- and β-thalassemia. The highest carrier rate of thalassemia was in Yongzhou (14.57%). The most abundant genotype of α-thalassemia and β-thalassemia was -α ^3.7/αα (50.23%) and β ^IVS-II-654/β ^N (28.23%), respectively. Four α-globin mutations [CD108 (ACC>AAC), CAP +29 (G>C), Hb Agrinio and Hb Cervantes] and six β-globin mutations [CAP +8 (C>T), IVS-II-848 (C>T), -56 (G>C), beta nt-77 (G>C), codon 20/21 (-TGGA) and Hb Knossos] had not previously been identified in China. Furthermore, this study provides the first report of the carrier rates of abnormal hemoglobin variants and α-globin triplication in Hunan Province, which were 0.49% and 1.99%, respectively. CONCLUSION Our study demonstrates the high complexity and diversity of thalassemia gene mutations in the Hunan population. The results should facilitate genetic counselling and the prevention of severe thalassemia in this region.
Humans ; beta-Thalassemia/genetics* ; alpha-Thalassemia/genetics* ; Hemoglobinopathies/genetics* ; China/epidemiology* ; High-Throughput Nucleotide Sequencing

The approach combining disease, syndrome, and symptom was employed to investigate the characteristic changes of blood stasis syndrome in a rat model of steroid-induced osteonecrosis of the femoral head(SONFH) during disease onset and progression. Seventy-two male SD rats were randomized into a healthy control group and a model group. The rat model of SONFH was established by injection of lipopolysaccharide(LPS) in the tail vein at a dose of 20 μg·kg~(-1)·d~(-1) on days 1 and 2 and gluteal intramuscular injection of methylprednisolone sodium succinate(MPS) at a dose of 40 mg·kg~(-1)·d~(-1) on days 3-5, while the healthy control group received an equal volume of saline. The mechanical pain test, tongue color RGB technique, gait detection, open field test, and inclined plane test were employed to assess hip pain, tongue color, limping, joint activity, and lower limb strength, respectively, at different time points within 21 weeks of modeling. At weeks 2, 4, 8, 12, 16, and 21 after modeling, histopathological changes of the femoral head were observed by hematoxylin-eosin(HE) staining and micro-CT scanning; four coagulation items were measured by rotational thromboelastometry; and enzyme-linked immunosorbent assay(ELISA) was employed to determine the levels of six blood lipids, vascular endothelial growth factor(VEGF), endothelin-1(ET-1), nitric oxide(NO), tissue-type plasminogen activator(t-PA), plasminogen activator inhibitor factor-1(PAI-1), bone gla protein(BGP), alkaline phosphatase(ALP), receptor activator of nuclear factor-κB(RANKL), osteoprotegerin(OPG), and tartrate-resistant acid phosphatase 5b(TRAP5b) in the serum, as well as the levels of 6-keto-prostaglandin 1α(6-keto-PGF1α) and thromboxane B2(TXB2) in the plasma. The results demonstrated that the pathological alterations in the SONFH rats were severer over time. The bone trabecular area ratio, adipocyte number, empty lacuna rate, bone mineral density(BMD), bone volume/tissue volume(BV/TV), trabecular thickness(Tb.Th), trabecular number(Tb.N), bone surface area/bone volume(BS/BV), and trabecular separation(Tb.Sp) all significantly increased or decreased over the modeling time after week 4. Compared with the healthy control group, the mechanical pain threshold, gait swing speed, stride, standing time, and walking cycle of SONFH rats changed significantly within 21 weeks after modeling, with the greatest difference observed 12 weeks after modeling. The time spent in the central zone, rearing score, and maximum tilt angle in the open field test of SONFH rats also changed significantly over the modeling time. Compared with the healthy control group, the R, G, and B values of the tongue color of the model rats decreased significantly, with the greatest difference observed 11 weeks after modeling. The levels of total cholesterol(TC), total triglycerides(TG), low-density lipoprotein-cholesterol(LDL-C), and apoprotein B(ApoB) in the SONFH rats changed significantly 4 and 8 weeks after modeling. The levels of VEGF, ET-1, NO, t-PA, PAI-1, 6-keto-PGF1α, TXB2, four coagulation items, and TXB2/6-keto-PGF1α ratio in the serum of SONFH rats changed significantly 4-16 weeks after modeling, with the greatest differences observed 12 weeks after modeling. The levels of BGP, TRAP5b, RANKL, OPG, and RANKL/OPG ratio in the serum of SONFH rats changed significantly 8-21 weeks after modeling. During the entire onset and progression of SONFH in rats, the blood stasis syndrome characteristics such as hyperalgesia, tongue color darkening, gait abnormalities, platelet, vascular, and coagulation dysfunctions were observed, which gradually worsened and then gradually alleviated in the disease course(2-21 weeks), with the most notable differences occurred around 12 weeks after modeling.
Rats ; Male ; Animals ; Femur Head/pathology* ; Plasminogen Activator Inhibitor 1/adverse effects* ; Vascular Endothelial Growth Factor A ; Femur Head Necrosis/pathology* ; Rats, Sprague-Dawley ; Steroids ; Pain ; Cholesterol

OBJECTIVES: To investigate the efficacy and required indicators of Children Neuropsychological and Behavioral Scale-Revision 2016 (CNBS-R2016) in the differential diagnosis of autism spectrum disorder (ASD) and global developmental delay (GDD). METHODS: A total of 277 children with ASD and 415 children with GDD, aged 18-48 months, were enrolled as subjects. CNBS-R2016 was used to assess the developmental levels of six domains, i.e., gross motor, fine motor, adaptive ability, language, social behavior, and warning behavior, and a total of 13 indicators on intelligence age and developmental quotient (DQ) were obtained as the input features. Five commonly used machine learning classifiers were used for training to calculate the classification accuracy, sensitivity, and specificity of each classifier. RESULTS: DQ of warning behavior was selected as the first feature in all five classifiers, and the use of this indicator alone had a classification accuracy of 78.90%. When the DQ of warning behavior was used in combination with the intelligence age of warning behavior, gross motor, and language, it had the highest classification accuracy of 86.71%. CONCLUSIONS Machine learning combined with CNBS-R2016 can effectively distinguish children with ASD from those with GDD. The DQ of warning behavior plays an important role in machine learning, and its combination with other features can improve classification accuracy, providing a basis for the efficient and accurate differential diagnosis of ASD and GDD in clinical practice.
Child ; Humans ; Autism Spectrum Disorder/psychology* ; Diagnosis, Differential ; Machine Learning ; Social Behavior

In this study, the ovarian surgery (ovariectomy, OVX) was used to establish the osteoporosis mice model of primary menstruation, in order to evaluate the protective effects and mechanisms of Zhibai Dihuang decotion on postmenopausal osteoporosis (PMOP). The animal experimental protocol has been reviewed and approved by Laboratory Animal Ethics Committee of Jinan University (number: 20210315-03), in compliance with the Institutional Animal Care Guidelines. C57BL/6 mice were divided into five groups, including Sham group, OVX group, low (32 g·kg^-1·day^-1) and high dose (64 g·kg^-1·day^-1) of Zhibai Dihuang decotion groups, positive drug group (alendronate, 9.9 mg·kg^-1·q3d). After modeling, mice were given medication intervention for 8 weeks, and then femoral and tibial tissues were taken to detect indicators such as bone microstructure, bone resorption, and oxidative stress. The experimental results showed that after Zhibai Dihuang decotion administration, the bone microstructure damage caused by OVX surgery was alleviated, and the relevant parameters bone mineral density (BMD), bone volume/total volume (BV/TV), trabecular number (Tb. N) and connectivity density (Conn. D) both significantly increased. At the same time, the number of TRAP positive osteoclasts decreased significantly, and the levels of proteins and genes related to osteoclast differentiation decreased, indicating that Zhibai Dihuang decoction could inhibit the increased activity of osteoclast caused by OVX. Afterwards, network pharmacology was used to construct the active compound action target network of Zhibai Dihuang decotion, and it was found that the target genes of its active ingredients were closely related to the oxidative stress pathway. Finally, the detection results of oxidative stress levels in bone tissues showed that after treatment with Zhibai Dihuang decotion, the levels of oxidative stress products 4-hydroxynonenal (4-HNE) and malondialdehyde (MDA) in bone tissues of mice significantly decreased, while the levels of antioxidant stress substance L-glutathione (GSH) increased. These above results indicated that Zhibai Dihuang decotion can regulate the level of oxidative stress in the body and inhibit osteoclast activity, which played a therapeutic role in PMOP, as well as provided theoretical basis for the prevention and treatment of PMOP with traditional Chinese medicine.

Objective To investigate the status of glycemic control and influencing factors among male and female elderly diabetic patients in Wuhan. Methods The cluster sampling method was used to select 5 441 patients with type 2 diabetes mellitus who participated in the elderly physical examination from January to December 2018 in 6 administrative districts of Wuhan City. The effects of different social-demographic characteristics, different behavioral lifestyle, and different health-related variables on the glycemic control rates among male and female elderly diabetic patients were analyzed. Binary logistic regression was employed to analyze the influencing factors among those people. Results The glycemic control rate of elderly diabetic patients in Wuhan was 54.29%, including 53.25% in males and 55.06% in females. Multivariate unconditional logistic regression analysis showed that living in remote urban areas, central obesity, and elevated TG were the risk factors for blood glucose control in male patients, while having weekly exercise routine of walking was the protective factor. Similarly, having weekly exercise routine of walking was the protective factor in female patients, but living in rural area, long duration of diabetes, and elevated TG and TC were the risk factors for controlling blood glucose level in female patients. Conclusion There is little difference in blood glucose control level between male and female elderly diabetic patients in Wuhan, but there are certain differences in influencing factors. Targeted diabetes control measures should be formulated according to the different influencing factors of elderly diabetic patients of different genders.

Objective: To construct and compare the dynamic prediction models of the risk of mild cognitive impairment (MCI) in the elderly based on six different cognitive function scales. Methods: Based on longitudinal data from the Alzheimer's Disease Neuroimaging Initiative from 2005 to 2020, Mini-mental state examination (MMSE), functional activities questionnaire (FAQ), Alzheimer's disease assessment scale-cognitive (ADAS-Cog) 11, ADAS-Cog13, ADAS delayed word recall (ADASQ4), and Rey auditory verbal learning test (RAVLT)_immediate were used as longitudinal cognitive function evaluation indicators to assess the longitudinal changes in cognitive function. The joint model was used to analyze association between indicators variation trajectory and survival outcome MCI, and construct the risk prediction model of MCI in the elderly, the linear mixed model was constructed the longitudinal sub-model which described the evolution of a repeated measure over time, a proportional hazards model was constructed the survival sub-model, and the two sub-models were connected through the correlation parameter (α). The areas under the receiver operator characteristic curve (AUC) were used to evaluate the predictive efficacy of the model in the follow-up period of (t, t+Δt). The starting point t was selected at the 30^th, 42^nd, and 54^th month, and the Δt was selected as 15 and 21 months. Based on the prediction model, an example of the research object was selected for dynamic individual predictions of the risk of MCI. Results: Finally, 544 older adults (aged 60 years and above) with normal baseline cognitive status were included, of which 119 cases (21.9%) had MCI during the follow-up process were regarded as the case group, and 425 cases remained normal as the control group. The joint model suggests that the longitudinal trajectories of the six evaluation indicators are all related to the risk of MCI (P<0.001). The risk of MCI decreased by 32.3% (HR=0.677, 95%CI: 0.541-0.846) and 10.8% (HR=0.892, 95%CI: 0.865-0.919) for each one-point increase of MMSE and RAVLT_immediate longitudinal scores. The risk of MCI increased by 53.2% (HR=1.532, 95%CI: 1.393-1.686), 36.2% (HR=1.362, 95%CI: 1.268-1.462), 23.2% (HR=1.232, 95%CI: 1.181-1.285), and 85.1% (HR=1.851, 95%CI:1.629-2.104) for each one-point increase of FAQ, ADAS-Cog11, ADAS-Cog13, and ADASQ4 longitudinal scores. AUC results show that RAVLT_immediate (0.760 2) and ADASQ4 (0.755 8) have higher average prediction efficiency, followed by ADAS-Cog13 (0.743 7), ADAS-Cog11 (0.715 3), FAQ (0.700 8) and MMSE (0.629 5). ADASQ4 joint model was used to provide a dynamic individual prediction of the risk of MCI. The average probability of MCI after five years of follow-up and ten years of follow-up in the example individuals were 8% and 40%, respectively. Conclusions: The RAVLT_immediate and ADASQ4 scales, which are only for memory tests, have high accuracy in predicting the risk of MCI. Using the RAVLT_immediate and ADASQ4 scales as longitudinal cognitive function evaluation indicators to construct a joint model, the results can provide a basis for realizing MCI risk prediction for the elderly.
Aged ; Alzheimer Disease/psychology* ; Cognition ; Cognitive Dysfunction/epidemiology* ; Humans ; Middle Aged ; Neuropsychological Tests ; Risk Factors