Liumotang comes from the Yuan dynasty's Effective Prescription Handed Down for Generations of Physicians. It is composed of six medicinal materials： Arecae Semen， Aquilariae Lignum Resinatum， Aucklandiae Radix， Linderae Radix， Rhei Radix et Rhizoma， and Aurantii Fructus. It is a classical formula for treating abdominal pain due to Qi stagnation and constipation accompanied by heat. This study systematically collated the records of Liumotang in ancient medical books and modern clinical literature and conducted in-depth analysis and textual research on its formula source， main diseases， composition， dosage， medical books， container capacity， processing， preparation method， usage， drug basis， formula meaning， and other key information， so as to provide a powerful reference for the development and clinical application of compound preparations of the classical formula Liumotang. The results show that Liumotang was first seen in Effective Prescription Handed Down for Generations of Physicians， and many medical books of the past dynasties have imitated this. In terms of drug basis， the dried and mature seeds of the palm plant Areca catechu， resin-containing wood of the Daphneaceae plant Aquilaria sinensis， the dried roots of the Asteraceae plant woody Aucklandia lappa， the dried tuber root of the Lauraceae plant Lindera aggregata， the dried roots and rhizomes of the knotweed plant， R. palmatum， R.tangutikum， and R. officinale， and the dried and unripe fruits of the citrus genus C. aurantium and its cultivated varieties from the family Rutaceae were selected. In terms of dosage， through the textual research on bowls in the Ming and Qing dynasties， combined with the conversion of medicines and bowl capacity in the Qing dynasty， it was estimated that the dosage of each drug in the Yuan dynasty was 10.86 g. In the Ming and Qing dynasties， the dosage of drugs was mostly equal， but the dosage of drugs was somewhat different. In terms of processing， preparation method， and usage， in the medical books of the past dynasties， the processing of drugs has slightly changed， but raw drugs are used in all preparations. The preparation method and usage did not change much during the Yuan， Ming， and Qing dynasties， except for certain differences in dosage. In terms of syndrome， Liumotang was first used to treat abdominal pain due to Qi stagnation and constipation accompanied by heat. Medical books of the past dynasties often omit the symptoms of heat. In modern clinical practice， Liumotang is mainly used in the digestive system and urinary system diseases and is mostly used to treat constipation-predominant irritable bowel syndrome， biliary reflux gastritis， functional constipation， slow transit constipation， and other diseases， with no adverse reactions found yet. The above results provide a reliable scientific basis for the development and clinical treatment of Liumotang compound preparations.

OBJECTIVE: To assess the independent and combined effects of air pollutants, meteorological factors, and greenspace exposure on new tuberculosis (TB) cases. METHODS: TB case data from Shanghai (2013-2018) were obtained from the Shanghai Center for Disease Control and Prevention. Environmental data on air pollutants, meteorological variables, and greenspace exposure were obtained from the National Tibetan Plateau Data Center. We employed a distributed-lag nonlinear model to assess the effects of these environmental factors on TB cases. RESULTS: Increased TB risk was linked to PM _2.5, PM ₁₀, and rainfall, whereas NO ₂, SO ₂, and air pressure were associated with a reduced risk. Specifically, the strongest cumulative effects occurred at various lags: PM _2.5 ( RR = 1.166, 95% CI: 1.026-1.325) at 0-19 weeks; PM ₁₀ ( RR = 1.167, 95% CI: 1.028-1.324) at 0-18 weeks; NO ₂ ( RR = 0.968, 95% CI: 0.938-0.999) at 0-1 weeks; SO ₂ ( RR = 0.945, 95% CI: 0.894-0.999) at 0-2 weeks; air pressure ( RR = 0.604, 95% CI: 0.447-0.816) at 0-8 weeks; and rainfall ( RR = 1.404, 95% CI: 1.076-1.833) at 0-22 weeks. Green space exposure did not significantly impact TB cases. Additionally, low temperatures amplified the effect of PM _2.5 on TB. CONCLUSION Exposure to PM _2.5, PM ₁₀, and rainfall increased the risk of TB, highlighting the need to address air pollutants for the prevention of TB in Shanghai.
China/epidemiology* ; Humans ; Air Pollutants/analysis* ; Tuberculosis/epidemiology* ; Incidence ; Meteorological Concepts ; Particulate Matter/adverse effects* ; Environmental Exposure ; Male ; Female ; Adult ; Air Pollution ; Middle Aged

Objective:To investigate the associations of onset age, diabetes duration, and glycated hemoglobin (HbA1c) levels with ischemic stroke risk in type 2 diabetes patients.Methods:The participants were from Comprehensive Research on the Prevention and Control of the Diabetes in Jiangsu Province. The study used data from baseline survey from December 2013 to January 2014 and follow-up until December 31, 2021. After excluding the participants who had been diagnosed with stroke at baseline survey and those with incomplete information on onset age, diabetes duration, and HbA1c level, a total of 17 576 type 2 diabetes patients were included. Cox proportional hazard model was used to calculate the hazard ratio ( HR) and 95% CI of onset age, diabetes duration, and HbA1c level for ischemic stroke. Results:During the median follow-up time of 8.02 years, 2 622 ischemic stroke cases were registered. Multivariate Cox proportional risk regression model showed that a 5-year increase in type 2 diabetes onset age was significantly associated with a 5% decreased risk for ischemic stroke ( HR=0.95, 95% CI: 0.92-0.99). A 5-year increase in diabetes duration was associated with a 5% increased risk for ischemic stroke ( HR=1.05, 95% CI: 1.02-1.10). Higher HbA1c (per 1 standard deviation increase: HR=1.17, 95% CI: 1.13-1.21) was associated with an increased risk for ischemic stroke. Conclusion:The earlier onset age of diabetes, longer diabetes duration, and high levels of HbA1c are associated with an increased risk for ischemic stroke in type 2 diabetes patients.

To investigate the associations of serum gamma-glutamyl transferase (GGT) levels with the risk of cardiovascular disease (CVD) and its subtypes in patients with type 2 diabetes mellitus (T2DM) in Jiangsu Province.Methods:The participants were enrolled in the Comprehensive Research project regarding 'Prevention and Control of Diabetes' in Jiangsu Province. The baseline survey was conducted from 2013 to 2014, and follow-up until December 31, 2021. After excluding the participants who self-reported with chronic liver disease/stroke/coronary heart disease at baseline survey and those with incomplete information on GGT, a total of 16 147 T2DM patients were included in the final analysis. Cox proportional hazard regression models were used to calculate the hazard ratio ( HR) and their 95% CI of GGT for CVD, myocardial infarction, and stroke. Restricted cubic spline models were applied to analyze the dose-response relationship between GGT and the risk of CVD and its subtypes. Results:During the median follow-up time of 8.02 years, 2 860 CVD cases were registered, including 196 cases of myocardial infarction and 2 730 cases of stroke. Multivariate Cox proportional risk regression model indicated that compared to the lowest serum GGT level group, the highest GGT level group had a 24% increased risk of CVD ( HR=1.24, 95% CI: 1.09-1.41) and a 23% increased risk of stroke ( HR=1.23, 95% CI: 1.08-1.40). The restricted cubic spline model showed a nonlinear dose-response relationship between GGT and the risk of CVD, myocardial infarction, and stroke in T2DM patients. Conclusions:High levels of GGT may be associated with an increased risk of cardiovascular disease in T2DM patients, which needs further exploration and validation in future clinical practice.

Objective:To study the alveolar bone remodeling of maxillary anterior teeth after extraction treatment and 2-year recovery period in adolescent patients with maxillary anterior arch protrusion.Methods:15 adolescent patients with maxillary anterior arch protru-sion were included,2 maxillary first premolars were extracted and implant anchorage combined with sliding method were used to close the extraction gap.CBCT images were taken before treatment(T0),after treatment(T1)and 2 years of recorvery period(T2),respectively.After multi-plane reconstruction with Dophin Imaging,the alveolar bone area(ABA)changes of maxillary central incisor,lateral incisor and canine at cementoenamel junction(CEJ-3 mm),root neck,central part,and root tip were measured and recorded as TAC,TA1,TA2 and TA3 respectively.The labial palatal alveolar crest to CEJ bone height(BH)of each tooth was recorded as BCL,BCP respectively.The data were analyzed by IBM SPSS statistics 25.0.Results:In T0-T2 phase,TA1 of each tooth was reduced.In T0-T1 phase,the horizontal adsorption of teeth was significantly correlated with ΔBCP,followed by ΔTA3.In T0-T2 phase,ΔBCP,ΔTA2,ΔTA3 and the horizontal adsorption of teeth showed low negative correlation.In T0-T1 phase,the vertical reduction of teeth was significantly positively correlated with ΔTAC,followed by low correlation with ΔTA3 and ΔTA1.Conclusion:In the treatment of anterior arch protrusion after extraction correction in adolescent patients the more the vertical reduction and horizontal adsorption of teeth in the treatment phase,the more the alveolar bone thickness and height around the tooth root in the maintenance phase,which were significantly positively correlated.Reasonable control of the vertical move-ment of teeth in the alveolar bone can improve the periodontal condition around the teeth to a certain extent.

Objective To explore the relationship between serum ferritin levels and body fat distribution in patients with type 2 diabetes mellitus(T2DM).Methods A retrospective analysis was conducted on 151 patients with T2DM who were hospitalized in the Department of Endocrinology of the First Hospital of Lanzhou University from June to November 2020,and all the patients were divided into high serum ferritin(n=50)and normal serum ferritin(n=101)groups according to their serum ferritin levels.The visceral fat area(VFA),subcutaneous fat area(SFA),liver fat,height,weight and waist circumference(WC)were measured,as well as blood glucose,lipid indexes,body mass index(BMI)and visceral adiposity index(VAI)were also calculated.t-test or nonparametric test was used to compare the differences between the two groups,and the relationship between serum ferritin levels and body fat distribution was analyzed by Pearson or Spearman correlation analysis,multiple linear regression and logistic regression.Results The VAI and WC were significantly higher in high serum ferritin group[3.13(2.16,4.58)and(96.66±7.78)cm]than in normal serum ferritin group[2.66(1.66,3.81)and(91.96±9.75)cm,P<0.05].The prevalence of central obesity and dyslipidemia was higher in high serum ferritin group(88.0%and 90.0%)than in normal serum ferritin group(68.3%and 75.2%);and the composition ratios of poor glycemic control and insulin resistance(96.0%and 62.0%)were also higher than in normal serum ferritin group(78.2%and 40.6%)(P<0.05),there were no statistically significant differences in BMI,VFA,and SFA levels,as well as antidiabetic drug use and chronic complications of diabetes mellitus between the two groups(P>0.05).Serum ferritin levels in T2DM patients were positively correlated with VAI,WC,triglyceride(TG),fasting blood glucose(FPG),HbA1c,dyslipidemia and serum creatinine(r=0.171,0.207,0.187,0.243,0.270,0.162,0.162;P<0.05),and negatively correlated with age,sex and diabetes course(r=-0.191,-0.434,-0.352;P<0.05).Multivariate linear regression analysis showed that in male T2DM patients,duration of diabetes and FPG were risk factors for increased levels of serum ferritin.However,WC and VAI did not significantly affect serum ferritin levels.In female patients with T2DM,the course of diabetes,TG and VAI were the factors influencing serum ferritin(P<0.05).Conclusion Dyslipidemia and visceral fat accumulation are risk factors for elevated serum ferritin levels in female T 2DM patients.

Background/Aims: Despite the high efficacy of direct-acting antivirals (DAAs), approximately 1–3% of hepatitis C virus (HCV) patients fail to achieve a sustained virological response. We conducted a nationwide study to investigate risk factors associated with DAA treatment failure. Machine-learning algorithms have been applied to discriminate subjects who may fail to respond to DAA therapy. Methods: We analyzed the Taiwan HCV Registry Program database to explore predictors of DAA failure in HCV patients. Fifty-five host and virological features were assessed using multivariate logistic regression, decision tree, random forest, eXtreme Gradient Boosting (XGBoost), and artificial neural network. The primary outcome was undetectable HCV RNA at 12 weeks after the end of treatment. Results: The training (n=23,955) and validation (n=10,346) datasets had similar baseline demographics, with an overall DAA failure rate of 1.6% (n=538). Multivariate logistic regression analysis revealed that liver cirrhosis, hepatocellular carcinoma, poor DAA adherence, and higher hemoglobin A1c were significantly associated with virological failure. XGBoost outperformed the other algorithms and logistic regression models, with an area under the receiver operating characteristic curve of 1.000 in the training dataset and 0.803 in the validation dataset. The top five predictors of treatment failure were HCV RNA, body mass index, α-fetoprotein, platelets, and FIB-4 index. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the XGBoost model (cutoff value=0.5) were 99.5%, 69.7%, 99.9%, 97.4%, and 99.5%, respectively, for the entire dataset. Conclusions Machine learning algorithms effectively provide risk stratification for DAA failure and additional information on the factors associated with DAA failure.

In recent years, the prevalence of gestational diabetes mellitus (GDM) has significantly increased, leading to various adverse outcomes for mothers and their offspring. Early diagnosis and good blood glucose control can significantly improve pregnancy outcomes. Currently, the diagnosis of GDM mainly relies on the oral glucose tolerance test (OGTT), but there are many limitations in clinical application. The new biological marker glycosylated CD59 is a glycosylation product of complement regulatory proteins that can stably exist in body fluids and is linearly related to blood glucose levels, which has the advantages of simple testing and good reproducibility, and has been developed into a stable reagent kit. It has shown good value in the early diagnosis, standard diagnosis, and prediction of pregnancy outcomes of GDM.

Objective To investigate the impact of the Shared Medical Appointment (SMA) model on blood glucose levels and self-management behaviors in patients with gestational diabetes mellitus (GDM). Methods A total of 87 pregnant women diagnosed with GDM at the Obstetrics and Gynecology and Endocrinology Outpatient Departments of the Affiliated Suqian Hospital of Xuzhou Medical University from October 2021 to October 2022 were enrolled and divided into treatment group (n=44) and control group (n=43). The treatment group received SMA-based GDM management, while the control group underwent routine outpatient follow-up. Baseline data, flash glucose monitoring (FGM)-related indicators before and after treatment, and self-management behavior scale scores were compared between the two groups. Results No statistically significant differences were observed between the two groups in age, body mass index (BMI), systolic blood pressure (SBP), diastolic blood pressure (DBP), fasting blood glucose (FBG), blood urea nitrogen (BUN), creatinine (Cr), uric acid (UA), triglycerides (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and glycated hemoglobin (HbA1c) (P>0.05). After treatment, the time in range (TIR) of glucose was higher in the treatment group than that in the control group, while mean amplitude of glycemic excursions (MAGE), standard deviation of blood glucose (SDBG), coefficient of variation (CV), and mean blood glucose (MBG) were lower in the treatment group (P < 0.05). Within the treatment group, post-treatment TIR was higher, and MAGE, CV, SDBG, and MBG were lower than pre-treatment levels (P < 0.05). In the control group, post-treatment TIR was higher, and SDBG and MBG were lower than pre-treatment levels (P < 0.05). After treatment, the total score and scores for dietary management, exercise management, medication management, and blood glucose monitoring management in the self-management behavior scale were significantly higher in the treatment group than in the control group (P < 0.05). In the treatment group, post-treatment scores for all self-management behaviors were higher than pre-treatment levels, while post-treatment total scores and scores for medication management and blood glucose monitoring management in the control group were higher than pre-treatment levels (P < 0.05). Conclusion SMA management model can comprehensively improve blood glucose levels and enhance self-management behavior capabilities in GDM patients.

BACKGROUND: The benefits of healthy lifestyles are well recognized. However, the extent to which improving unhealthy lifestyles reduces cardiovascular disease (CVD) risk needs to be discussed. We evaluated the impact of lifestyle improvement on CVD incidence using data from the China-PAR project (Prediction for Atherosclerotic Cardiovascular Disease Risk in China). METHODS: A total of 12,588 participants free of CVD were followed up for three visits after the baseline examination. Changes in four lifestyle factors (LFs) (smoking, diet, physical activity, and alcohol consumption) were assessed through questionnaires from the baseline to the first follow-up visit. Cox proportional hazard models were used to estimate hazard ratios (HRs) and corresponding 95% confidence intervals (CIs). The risk advancement periods (RAPs: the age difference between exposed and unexposed participants reaching the same incident CVD risk) and population-attributable risk percentage (PAR%) were also calculated. RESULTS: A total of 909 incident CVD cases occurred over a median follow-up of 11.14 years. Compared with maintaining 0-1 healthy LFs, maintaining 3-4 healthy LFs was associated with a 40% risk reduction of incident CVD (HR = 0.60, 95% CI: 0.45-0.79) and delayed CVD risk by 6.31 years (RAP: -6.31 [-9.92, -2.70] years). The PAR% of maintaining 3-4 unhealthy LFs was 22.0% compared to maintaining 0-1 unhealthy LFs. Besides, compared with maintaining two healthy LFs, improving healthy LFs from 2 to 3-4 was associated with a 23% lower risk of CVD (HR = 0.77, 95% CI: 0.60-0.98). CONCLUSIONS Long-term sustenance of healthy lifestyles or improving unhealthy lifestyles can reduce and delay CVD risk.