Objective To compare the influence between self-monitoring of blood gluocose(SMBG)combined with digital diabetes management and traditional management mode on the related clinical indexes in the patients with type 2 diabetes mellitus(T2DM).Methods A total of 100 patients with T2DM treated in the endocrinology and metabolism outpatient department of this hospital from January 2022 to June 2022 and meeting the inclusion criteria of this study were successively included.They were divided into the experimental group and control group.The experimental group was managed by SMBG combined with digital diabetes man-agement mode,while the control group adopted the traditional management mode,the outpatient clinic follow up once a month.After 6 months of follow-up,fasting blood glucose,glycosylated hemoglobin(HbA1c),low density lipoprotein cholesterol(LDL-C)and urinary microalbumin/creatinine ratio(UACR)were compared between the two groups.Results The FBG,HbA1c,LDL-C,and UACR of the experimental group decreased after intervention when compared with baseline.Compared with the control group,the FBG[8.7(7.7,9.2)mmol/L vs.10.8(8.8,12.7)mmol/L,Z=-4.660,P＜0.001],HbA1c[6.3％(5.3,7.8)％vs.8.5％(7.2,10.0)％,Z=-5.130,P＜0.001],LDL-C[2.6(1.8,3.1)mmol/L vs.3.3(2.6,4.0)mmol/L,Z=-4.112,P＜0.001],UACR[16.1(3.5,46.5)mg/g vs.58.4(11.9,108.0)mg/g,Z=-2.220,P=0.026]for patients in the expriemental group after intervention were significantly decreased.Conclusion SMBG combined with digital diabetes management model can significantly improve the clinical indicators of patients.

Objective To investigate the mechanism of Sini San Formula in the treatment of ulcerative colitis and depression through"homotherapy for heteropathy"based on network pharmacology and molecular docking.Methods The TCMSP database was used to obtain the potential active components and their related targets;GeneCards,CTD,and TTD databases were used to screen the disease-related targets of ulcerative colitis and depression;the intersection of the predicted targets of the active components and the disease-related targets was used to obtain the potential targets(shared targets)for the treatment of ulcerative colitis and depression by Sini San Formula,and Cytoscape 3.7.2 software to construct a"Chinese medicinals-active components-diseases-common targets"network to analyze the core components;importing the common targets into the STRING database,constructing a common protein-protein interaction(PPI)network.The GO function and KEGG pathway enrichment of the shared targets were analyzed by DAVID database,and molecular docking between the core components and the key targets was verified.Results A total of 136 active components of Sini San Formula were obtained,and 220 potential targets of action(shared targets)for the treatment of ulcerative colitis and depression by Sini San Formula,involving 657 biological processes,70 cellular components,147 molecular functions and 133 signaling pathways.The screening yielded core active compounds such as quercetin,kaempferol,lignans,naringenin,7-methoxy-2-methylisoflavone,key target proteins such as JUN,MAPK3,STAT3,AKT1,and MAPK1,as well as signaling pathways such as TNF,IL-17,Th17 cellular differentiation,HIF-1,and Toll-like receptor.Five potential key targets have strong binding activity to quercetin,kaempferol,lignans and naringenin.Conclusion Sini San Formula may act on key targets such as JUN,MAPK3,STAT3,AKT1,MAPK1,etc.through active components such as quercetin,kaempferol,lignocerotonin,naringenin,etc.,and play the role of"homotherapy for heteropathy"for ulcerative colitis and depression through the signaling pathways such as TNF,IL-17,HIF-1,Toll-like receptor and Th17 cell differentiation.

Objective To explore the therapeutic mechanism of Modified Lugen Formula(Phragmitis Rhizoma,Cicadae Periostracum,Batryticatus Bombyx,Lonicerae Japonicae Flos,Glycyrrhiza,Menthae Haplocalycis Herba,Notopterygii Rhizoma et Radix,Puerariae Lobatae Radix,Bupleuri Radix)in treating influenza from the virus-host interaction interface.Methods The phytocompounds were first collected from the HERB database,and then potential active compounds were screened out by Lipinski's rules of five.The targets of active compounds were further predicted through the SwissTargetPrediction platform.Differentially expressed genes(DEGs)were determined from the human H1N1 influenza dataset GSE90732 available in the Gene Expression Omnibus database(GEO).H1N1-Homo sapiens-related protein-protein interactions(PPIs)were gathered from the Pathogen-Host Interaction Search Tool(PHISTO).The above mentioned bioinformatic datasets were integrated.Then a PPI network and a Formula-virus-host interaction network were constructed using Cytoscape.Functional enrichment analyses were performed by using R software.Finally,molecular docking was carried out to evaluate the binding activities between the key compounds and targets.Results A total of 1 252 active compounds,1 415 targets,951 influenza-related DEGs,and 10 142 H1N1-Homo sapiens-related PPIs were obtained.There were 72 intersection targets between the Modified Lugen Formula and influenza.Functional enrichment analyses showed that these targets are closely related to host defense and programmed cell death.The network topological analysis showed that active compounds in the Modified Lugen Formula,such as oleanolic acid,γ-undecalactone,and longispinogenin,regulate viral proteins M2,NA,NS1,and HA and/or the host factors HSP90AA1,NRAS,and ITGB1,thus exert therapeutic effect.Molecular docking results confirmed that these compounds had a good binding ability with the targets.Conclusion Multiple active ingredients in Modified Lugen Formula directly target influenza virus proteins and/or host factors,thereby play an anti-influenza role in multiple dimensions,including inhibiting virus replication,regulating host defense and cell death.This study provides a theoretical basis for further experimental analysis of the action mechanism of the Modified Lugen Formula in treating influenza.

Pregnancy ; Female ; Humans ; Diabetes, Gestational/diagnosis* ; Retrospective Studies ; Prognosis ; Pregnancy Outcome ; Maternal Age

Objective:To explore the optimization of the standardized assessment tool for clinical diagnosis of Chinese developmental dyslexia (DD).Methods:A cross-sectional study was conducted from May to December 2023, in which 130 primary school children in grades 1 to 3 with clinical signs of literacy lag and positive screening results on the screening scales were recruited from the outpatient clinic of Child Health Care Medical Division, Shanghai Children′s Hospital, Shanghai Jiao Tong University School of Medicine. Chinese dyslexia screening behavior checklist for primary students (CDSBC) was used as the screening scales, and supplemented by dyslexia checklist for Chinese children. Referring to the standard procedure of the"expert advice on diagnosis and intervention of Chinese developmental dyslexia", the developmental dyslexia scale for standard mandarin (DDSSM) was used to evaluate the children′s literacy-related cognitive abilities and conduct the diagnostic assessment, and divided the children into learning backward group and the DD group. The t-test and χ2 test were used to compare the differences in the distribution of intelligence, literacy and attention deficit hyperactivity disorder between the two groups. Spearman′s correlation was used to analyze the correlation between the scores for each cognitive ability in the DDSSM and the CDSBC. Results:Of the 130 children, 90 were male, aged (8.3±1.0) years; 40 were female, aged (8.1±0.9) years. A final diagnosis of DD was made in 59 cases, of which 41 were males. There was no statistically significant difference in operational intelligence quotient (101±15 vs.100±15, t=0.53, P>0.05) and statistically significant difference in literacy of DDSSM (32±5 vs.21±4, t=11.56, P<0.001) between the learning backward group and the DD group. Eighteen cases (25.4%) of the learning backward group were children with attention deficit subtype attention deficit hyperactivity disorder (ADHD-I), and 16 cases (27.1%) in DD group, the difference in incidence between the two groups was not statistically significant ( χ2=0.05, P>0.05). There were correlations between the DDSSM (for oral vocabulary, morphological awareness and orthographic awareness) and the CDSBC total score ( r=-0.42, -0.32, -0.35, all P<0.01), but the correlations for visuospatial perception and rapid automatized naming with CDSBC total score were not statistically significant ( r=-0.09 and -0.20,both P>0.05). Conclusion:For literacy-related cognitive abilities, screening scales CDSBC are not sufficiently useful for assessment, so the introduction of standardized assessment tools DDSSM is an optimization of the clinical diagnosis of Chinese DD, which is crucial for achieving accurate diagnosis and intervention.

Objective To explore the association between interpregnancy weight change and the recurrence of gestational diabetes mellitus(GDM).Methods This study included women who had two delivery records and a history of GDM during their previous pregnancy at the Guangdong Women and Children Hospital between January 2017 and July 2022.Interpregnancy weight change was defined as the difference between the prepregnancy BMIs of two consecutive pregnancies.Interpregnancy weight change was categorized into four groups(＜-1,-1 to＜1,1 to＜3,≥3 kg/m2),with the-1 to＜1 kg/m2 group serving as the reference.Logistic regression analyses were used to assess the associations of interpregnancy weight changes with GDM recurrence and changes in glucose values during two consecutive pregnancies.Results Among 703 participants,326 individuals(46.4％)experienced GDM recurrence.Compared with the groups with an interpregnancy BMI change of-1 to＜1 kg/m2,the groups with a BMI change of 1 to＜3 or ≥3 presented an increased risk of GDM recurrence,with odds ratio(OR)[95％confi-dence intervals(CI)]of 2.16(1.52-3.08)and 2.56(1.44-4.56),respectively.The risk of GDM recurrence significantly in-creased with increasing interpregnancy weight gain(P for trend＜0.01).However,there was no significant association between a BMI change＜-1 kg/m2 and GDM recurrence,with an OR(95％CI)of 0.95(0.57-1.57).An increase of 1 kg/m2 in the in-terpregnancy BMI was associated with a higher risk of elevated fasting blood glucose and 1 h plasma glucose,with OR(95％C1)of 1.15(1.05-1.26)and 1.21(1.10-1.33),respectively.Conclusion Women with a history of GDM are at a high risk of GDM recurrence,and interpregnancy weight gain is associated with an increased risk of GDM recurrence.These findings under-score the importance of health education among women with a history of GDM who plan to conceive again and emphasize the im-portance of weight management in reducing the recurrence of GDM.

As a highly malignant gastrointestinal tumor, pancreatic cancer is highly invasive and metastatic, which leads to the low overall survival rate of patients with pancreatic cancer. Studies have shown that long non-coding RNA (lncRNA) is involved in the development, progression, invasion, and metastasis of pancreatic cancer through epigenetic, transcriptional or post-transcriptional regulation. Dysregulated expression of lncRNA is observed in pancreatic cancer and induces epithelial mesenchymal transition (EMT) through specific regulatory mechanisms, thereby causing the changes in the biological behavior of tumor cells. This article reviews the mechanisms of lncRNA in promoting EMT, regulating tumor biological function as competing endogenous RNA, and affecting the development, invasion, and metastasis of pancreatic cancer via multiple pathways by regulating the ferroptosis, autophagy, and exosome of tumor cells, in order to provide a theoretical basis and new targets for the early diagnosis and treatment of pancreatic cancer.

Objective:To investigate changes in the expression of immunohistochemical (IHC) markers and factors associated with the effect of chemotherapy before and after neoadjuvant chemotherapy (NAC).Methods:A retrospective study included 200 breast cancer patients treated with NAC between January 2016 and December 2018. We analyzed the changes in the expression of estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) and Ki-67 in pre- and post-treated samples and the predictive factors of NAC.Results:Among the 200 cases, 16 cases were luminal A, 108 cases were luminal B, 36 cases were HER2 +subtype, and 40 cases were basal-like. Twenty-five patients (12.50%) achieved pathological complete remission (PCR).There were significant differences in PR and Ki-67 before and after NAC but there were no differences in ER and HER2.In univariate analysis, factors associated with PCR were tumor less than 5 cm( P=0.009), non-luminal breast cancer ( P=0.001), ER negative( P=0.001), PR negative ( P=0.029) and HER2 positive( P=0.001). Tumor less than 5 cm [ P=0.020, OR=2.581, 95% CI (1.207, 5.753)], ER negative [ P=0.011, OR=2.264, 95% CI (1.207, 4.248)] and HER2 positive[ P=0.007, OR=2.412, 95% CI (1.275, 4.561)] remained predictive variables in multivariate analysis after correction for the other variables. Conclusions:The expression of Ki-67 decreases after NAC. Negative PR and ER and positive HER2 status are related to the efficacy of pCR for breast cancer, and have guiding significance for the prognosis evaluation of NAC.

Objective:To investigate the value of whole-lesion histogram parameters of apparent diffusion coefficient (ADC) in evaluating and predicting the pathological complete response(PCR) to neoadjuvant chemotherapy (NAC) in different subtypes of breast cancer.Methods:This retrospective study included 117 patients with breast cancer who underwent MRI examination before NAC prior to surgery from January 2016 to December 2017 in the First Affiliated Hospital of Nanjing University. All cases were divided into Luminal B, HER2 positive ( n=21) and triple negative ( n=26) groups. The surgical pathology after chemotherapy was evaluated by Miller-Payne (M-P) system and the patients were divided into PCR group and non-PCR (nPCR) group. Firevoxel software was used to generate the whole-lesion ADC histogram. The parameters included mean (ADC mean), skewness, kurtosis, the minimum (ADC min), the maximum (ADC max), 10th percentile(ADC 10%), 50th percentile (ADC 50%) and 90th percentile (ADC 90%). The two independent samples t test or Mann-Whitney U test was used to compare the differences between PCR and nPCR groups in each subtype. The diagnostic performance of statistically different ADC parameters for predicting PCR was evaluated by receiver operating characteristic (ROC) curve. Results:Kurtosis was significantly higher in PCR group than that in nPCR group in HER2 positive subtype ( P=0.039). It achieved an area under the curve (AUC) of 0.813 with sensitivity of 100% and specificity of 68.7% at the optimal cutoff value (1.861) for differentiating PCR from nPCR cases. In triple negative subtype, ADC mean and ADC 50% were smaller in PCR group than those in nPCR group ( P=0.028,0.013). They achieved AUCs of 0.800, 0.842, respectively. When ADC mean of 1.030×10 -3 mm 2/s and ADC 50% of 0.976×10 -3 mm 2/s were used as cutoff value to differentiate PCR from nPCR, the sensitivities were 75.0%, 80.0% and the specificities were 83.3%, 83.3%, respectively. Conclusion:Kurtosis can predict post-NAC PCR in patients with HER2 positive breast cancer, while ADC 50% has a high value in predicting post NAC PCR of triple negative breast cancer patients.

OBJECTIVE: Identifying Atrial Ventricular Hypertrophy Electrocardiogram (AVH ECG)and diagnosing the classification of theirs automatically. METHODS: The ECG data used in this experiment was collected from the First Affiliated Hospital of China Medical University. CNN are combined with conventional methods and a 10 layers of one dimensional CNN are created in this experiment to extract the features of ECG signals automatically and achieve the function of classifying. ROC, sensitivity and F1-score are used here to evaluate the effects of the model. RESULTS: In the experiment of identifying AVH ECG, the AUC of test dataset is 0.991, while in the experiment of classifying AVH ECG, the maximal F1-score can reach 0.992. CONCLUSIONS The CNN model created in this experiment can achieve the auxiliary diagnosis of AVH ECG.
China ; Electrocardiography ; Heart Atria/pathology* ; Humans ; Hypertrophy ; Neural Networks, Computer