Objective To investigate the effect of hemoglobin A1c variability on the incidence of malignant tumors in type 2 diabetes mellitus (T2DM) patients, and to provide a reference for the prevention and treatment of diabetes. Methods A retrospective cohort study was used to integrate Shanghai malignant tumor registration information and T2DM patient management information of Minhang Districts in Shanghai. A record linkage was carried out using ID numbers for patients who had been diagnosed through the Cancer Registry System. Average Real Variability（ARV）was used to assess the variability for hemoglobin A1c results, with no less than 3 measurements and no more than 1 follow-up visit per year. Cox proportional hazards regression models and Restricted Cubic Splines (RCS) were used for statistical analysis. ARV was grouped using quartile classification, represented by Q1, Q2, Q3, and Q4, respectively. Cox regression was performed using unadjusted model I and model II adjusted for gender, age, and group. Results A total of 2 762 research subjects were included in the present study, with 45.84% males and 54.16% females. The average age was (63.58±10.11) years, and an average follow-up time was (9.96±3.66) years. Malignant tumor incidence rate was 345.45/100 000 person years. There was statistical significance among different ARV groups (P=0.01). COX regression analysis of model I and model II showed that compared with Q1, the risk of Q4 group was significantly increased, with HRs of 2.72 (1.56-4.74) and 2.68 (1.53-4.68), respectively. The RCS graph's analysis showed that except for the ≥65-year-old group, the risk of tumor incidence gradually increased with the increase of ARV coefficient. Conclusion The variability of hemoglobin A1c is positively associated with the risk of occurrence of malignant tumors in type 2 diabetes patients. It is necessary to strengthen the monitoring of hemoglobin A1c and to reduce the health hazards caused by fluctuations in hemoglobin A1c.

Objective To investigate the effect of hemoglobin A1c variability on the incidence of malignant tumors in type 2 diabetes mellitus (T2DM) patients, and to provide a reference for the prevention and treatment of diabetes. Methods A retrospective cohort study was used to integrate Shanghai malignant tumor registration information and T2DM patient management information of Minhang Districts in Shanghai. A record linkage was carried out using ID numbers for patients who had been diagnosed through the Cancer Registry System. Average Real Variability（ARV）was used to assess the variability for hemoglobin A1c results, with no less than 3 measurements and no more than 1 follow-up visit per year. Cox proportional hazards regression models and Restricted Cubic Splines (RCS) were used for statistical analysis. ARV was grouped using quartile classification, represented by Q1, Q2, Q3, and Q4, respectively. Cox regression was performed using unadjusted model I and model II adjusted for gender, age, and group. Results A total of 2 762 research subjects were included in the present study, with 45.84% males and 54.16% females. The average age was (63.58±10.11) years, and an average follow-up time was (9.96±3.66) years. Malignant tumor incidence rate was 345.45/100 000 person years. There was statistical significance among different ARV groups (P=0.01). COX regression analysis of model I and model II showed that compared with Q1, the risk of Q4 group was significantly increased, with HRs of 2.72 (1.56-4.74) and 2.68 (1.53-4.68), respectively. The RCS graph's analysis showed that except for the ≥65-year-old group, the risk of tumor incidence gradually increased with the increase of ARV coefficient. Conclusion The variability of hemoglobin A1c is positively associated with the risk of occurrence of malignant tumors in type 2 diabetes patients. It is necessary to strengthen the monitoring of hemoglobin A1c and to reduce the health hazards caused by fluctuations in hemoglobin A1c.

Objective·To explore the correlation between body compositions and cardiovascular fitness(CRF)in patients with coronary heart disease(CHD).Methods·The CHD patients(CHD group)who underwent elective percutaneous coronary intervention treatment at Renji Hospital,Shanghai Jiao Tong University School of Medicine from October 2022 to June 2023 as well as healthy people(control group)were selected.All the participants completed cardiopulmonary exercise testing(CPET)to determine CRF and bioelectrical impedance analysis(BIA)to determine body compositions on the same day.Results·A total of 191 patients with coronary heart disease and 188 healthy individuals were included.There was no statistically significant difference in baseline characteristics between the two groups.Compared with the control group,the CRF indicators of the CHD group were significantly reduced(all P<0.05).In terms of body composition indicators,the trunk muscle mass(TMM)of the CHD group was significantly lower than that of the control group(P<0.01),and the trunk fat mass(TFM)was significantly higher than that of the control group(P<0.01).Correlation analysis showed that TMM(R=0.538),lower limbs muscle mass(LMM)(R=0.754),and lower limbs fat mass(LFM)(R=0.593)were positively correlated with peak oxygen uptake per kilogram of bodyweight(VO2peak/kg)in the CHD group(all P<0.01),while TFM(R=-0.563)was negatively correlated with VO2peak/kg(P<0.01).There was no statistically significant correlation between other body composition indicators and VO2peak/kg.According to VO2peak/kg,the CHD patients were divided into low CRF group,medium CRF group,and high CRF group.The results showed that there were statistically significant differences in LMM,TMM,LFM,and TFM among the three groups of patients(all P<0.05).Multiple linear regression analysis suggested that age,gender,TMM,TFM,LMM,and LFM were related factors of VO2peak/kg in the patients with CHD.The VO2peak/kg of CHD patients increased with the increase of TMM,LMM,and LFM and the decrease of age and TFM;the female patients had lower VO2peak/kg compared to the males.Conclusion·The CRF of CHD patients is significantly lower than that of the healthy population,with higher TFM and lower TMM;in the CHD patients,CRF is negatively correlated with TFM and positively correlated with TMM,LMM,and LFM.

Objective·To analyze the differences and classify hypertrophic cardiomyopathy(HCM)patients and healthy controls(HC)using short-axis cine cardiac magnetic resonance(CMR)images-derived radiomics features.Methods·One hundred HCM subjects were included,and fifty HC were randomly selected at 2∶1 ratio during January 2018 to December 2021 in the Department of Cardiology,Renji Hospital,Shanghai Jiao Tong University School of Medicine.The CMR examinations were performed by experienced radiologists on these subjects.CVI 42 post-processing software was used to obtain left ventricular morphology and function measurements,including left ventricular ejection fraction(LVEF),left ventricular end-diastolic volume(LVEDV)and left ventricular end-diastolic mass(LVEDM).The 3D radiomic features of the end-diastolic myocardial region were extracted from short-axis images CMR cine.The distribution of the radiomic features in the two groups was analysed and machine learning models were constructed to classify the two groups.Results·One hundred and seven 3D radiomic features were selected and extracted.After exclusion of highly correlated features,least absolute shrinkage and selection operator(LASSO)was used,and a 5-fold cross-validation was performed.There were still 11 characteristics with non-zero coefficients.The K-best method was used to decide the top 8 features for subsequent analysis.Among them,four features were significantly different between the two groups(all P<0.05).Support vector machine(SVM)and random forest(RF)models were constructed to discriminate the two groups.The results showed that the maximum area under the curve(AUC)for the single-feature model(first order grayscale:entropy)was 0.833(95%CI 0.685?0.968)and the maximum accuracy for the multi-feature model was 83.3%with an AUC of 0.882(95%CI 0.705?0.980).Conclusion·There are significant differences in both left ventricular function and left ventricular morphology between HCM and HC.The 3D myocardial radiomic features of the two groups are also significantly different.Although single feature is able to distinguish the two groups,the combination of multi-features show better classification performance.

AIM To identify the chemical components of Longmu Qingxin Mixture by UPLC-Q-TOF-MS and study its material basis for the treatment of attention deficit hyperactivity disorder.METHODS The sample was detected by mass spectrometry in positive and negative ion mode on a Waters CORTECS? UPLC? T3 chromatographic column.The data were analyzed with Peakview 1.2 software and matched with the Natural Products HR-MS/MS Spectral Library 1.0 database,and the components were identified in combination with literature reports.The material basis of Longmu Qingxin Mixture for the treatment of attention deficit hyperactivity disorder was analysed according to the identified components.RESULTS Forty chemical components were identified,including 11 flavonoids,6 monoterpene glycosides,4 triterpene saponins,3 phenolic acids,6 alkaloids etc.,which mainly derived from Radix Astragali,Radix Paeoniae Alba,Radix Scutellariae,licorice root,Ramulus Uncariae cum,etc.,baicalein,formononetin,astragaloside Ⅳ and rhynchophylline may be the material basis for the therapeutic effect of Longmu Qingxin Mixture.CONCLUSION UPLC-Q-TOF-MS can quickly identify the chemical components of Longmu Qingxin Mixture.Flavonoids,triterpene saponins and alkaloids may be the material basis for Longmu Qingxin Mixture for the treatment of attention deficit hyperactivity disorder,which can provide the basis for its material basis research,quality standard establishment and pharmacological study of the dismantled formula.

Objective To investigate the effect of Alogliptin benzoate on the serum autophagy markers in type 2 diabetes mellitus(T2DM)patients.Methods Eighty newly diagnosed T2DM patients who visited the Department of Endocrinology in Baoding No.1 Central Hospital from December 2021 to October 2022 were randomly divided into a group treated with Metformin(Met group,n=40)and a group treated with Met and Alog(Met+Alog group,n=40).The differences in BMI,WHR,FPG,HbA1c,Atg7 and Beclin-1 between two groups before and after 12 weeks of treatment were compared.Results After treatment,the levels of Atg7 and Beclin-1 increased in both groups(P<0.05),while FPG,HbA1c and HOMA-IR decreased(P<0.05).After treatment,Atg7,Beclin-1 and HDL-C in Met+Alog group were higher than those in Met group(P<0.05).Pearson correlation analysis showed that Atg7 was negatively correlated with BMI,FPG and HbA1c(P<0.05);Beclin-1 was positively correlated with HDL-C(P<0.05),and negatively correlated with BMI,FPG,HbA1c,and TG(P<0.05).Meta linear regression analysis showed that BMI was the influencing factor of Atg7,while BMI and HDL-C were the influencing factors of Beclin-1.Conclusion Alogliptin benzoate may improve islet β cell function by up-regulating the expression of autophagy related factors Atg7 and Beclin-1 in patients with T2DM.

Most patients with differentiated thyroid cancer have a good prognosis after radioiodine-131 therapy,but a small number of patients are insensitive to radioiodine-131 therapy and even continue to develop disease.At present,some targeted drugs can improve progression-free survival in patients with radioactive iodine-refractory differentiated thyroid cancer(RAIR-DTC),such as sorafenib and levatinib,have been approved for the treatment of RAIR-DTC.However,due to the presence of primary and acquired drug resistance,drug efficacy in these patients is unsatisfactory.This review introduces the acquired drug resistance mechanism of sorafenib in the regulation of mitogen-activated protein kinase(MAPK)and phosphatidylinositol-3-kinase(PI3K)pathways and proposes related treatment strategies,in order to provide a reference for similar drug resistance mechanism of sorafenib and effective treatment of RAIR-DTC.

Objective The purpose of this study was to investigate the bacterial communities of biting midges and ticks collected from three sites in the Poyang Lake area,namely,Qunlu Practice Base,Peach Blossom Garden,and Huangtong Animal Husbandry,and whether vectors carry any bacterial pathogens that may cause diseases to humans,to provide scientific basis for prospective pathogen discovery and disease prevention and control. Methods Using a metataxonomics approach in concert with full-length 16S rRNA gene sequencing and operational phylogenetic unit(OPU)analysis,we characterized the species-level microbial community structure of two important vector species,biting midges and ticks,including 33 arthropod samples comprising 3,885 individuals,collected around Poyang Lake. Results A total of 662 OPUs were classified in biting midges,including 195 known species and 373 potentially new species,and 618 OPUs were classified in ticks,including 217 known species and 326 potentially new species.Surprisingly,OPUs with potentially pathogenicity were detected in both arthropod vectors,with 66 known species of biting midges reported to carry potential pathogens,including Asaia lannensis and Rickettsia bellii,compared to 50 in ticks,such as Acinetobacter lwoffii and Staphylococcus sciuri.We found that Proteobacteria was the most dominant group in both midges and ticks.Furthermore,the outcomes demonstrated that the microbiota of midges and ticks tend to be governed by a few highly abundant bacteria.Pantoea sp7 was predominant in biting midges,while Coxiella sp1 was enriched in ticks.Meanwhile,Coxiella spp.,which may be essential for the survival of Haemaphysalis longicornis Neumann,were detected in all tick samples.The identification of dominant species and pathogens of biting midges and ticks in this study serves to broaden our knowledge associated to microbes of arthropod vectors. Conclusion Biting midges and ticks carry large numbers of known and potentially novel bacteria,and carry a wide range of potentially pathogenic bacteria,which may pose a risk of infection to humans and animals.The microbial communities of midges and ticks tend to be dominated by a few highly abundant bacteria.

Antisense oligonucleotides are a type of gene therapy that targets mRNA and inhibits gene expression. They have been applied in the treatment of various diseases, but there are still problems with poor enzyme stability and high dosage in vivo, due to the shortage of appropriate delivery system. Insulin-like growth factor 1 receptor (IGF1R) is a cell surface receptor with tyrosine kinase activity. Its expression is abnormal in a variety of malignant tumors. It mediates the malignant proliferation, migration and invasion of tumor cells through a variety of ways. In this study, an antisense oligonucleotide (ASO, N04) targeting IGF1R mRNA was designed and chemically modified (PS, 2'-OMOE), then neutral cytidine lipid DNCA and cystine backbone cationic lipid CLD (Mix) were used to encapsulate ASOs. The particle size, polymer dispersity index and ζ potential of the formulations were 151 nm, 0.18 and -3.9 mV. The nanoparticles entered liver cancer cells (HepG-2, Huh-7), silenced target mRNA, arrested cell cycle in S phase, promoted apoptosis, and inhibited the proliferation efficiently. These results indicate that Mix/N04_MOE5 has great potential in tumor treatment, which provides a basis for further research on novel agents against hepatocellular carcinoma.

Objective:To comprehensively evaluate the clinical value of Elecsys serum abnormal prothrombin (PIVKA-Ⅱ) test reagent for auxiliary diagnosis of hepatocellular carcinoma (HCC) in the Chinese population.Methods:A multicenter case-control design was used in the study. Samples from patients with first-time confirmed, diagnosed, and untreated HCC, benign liver disease and interfering controls were collected continuously. Elecsys PIVKA-II and alpha-fetoprotein (AFP) were tested for analysis. Various clinical details of the subjects were collected and analyzed. The efficacy of PIVKA-II (21.29 ng/ml) and AFP (400 ng/ml) for HCC diagnosis was calculated at specific positive cut-off values. Statistical analysis was performed using the Kruskal-Wallis test or receiver operating characteristic curve.Results:A total of 448 subjects were eventually enrolled from five centers, including 185 HCC cases. PIVKA-II had a higher diagnostic sensitivity and accuracy than AFP (84.86% vs. 30.81% and 89.01% vs. 63.66%) when the benign liver disease group was used as the control group, while the specificity was slightly lower. A sensitive analysis showed that PIVKA-II had a sensitivity of >80% at this specific positive cut-off value in the subgroup of AFP-negative subjects, patients with different etiologies, and HCC patients with multiple Barcelona Clinic liver cancer stages (including early-stage HCC). At the same time, the PIVKA-II subject had a slightly higher area under the receiver operating characteristic curve than the AFP (0.920 0 vs. 0.880 9).Conclusion:The clinical efficacy of Elecsys PIVKA-Ⅱ is good and stable in the Chinese population. Additionally, it has the clinical potential to improve the current missed diagnosis status of AFP-negative HCC and HCC monitoring at an early stage, as well as the effectiveness of accuracy promotion for HCC auxiliary diagnosis in China.