ObjectiveTo explore the effect of precocious puberty on glucose metabolism and lipid metabolism in female rats. MethodsSixty two-day-old female rats were randomly divided into 2 groups. When aged 5 days， the precocious puberty group and normal group were given a single subcutaneous injection of danazol and solvent soybean oil respectively. The vaginal opening of rats was monitored from their 21 days of age. After 12 hours of fasting， all successful modeling rats were randomly executed within 3 days after vaginal opening， when aged 7 and 12 weeks. Then we measured the rats’ body weight and length， determined the concentrations of glucose， insulin， blood lipids， estradiol， leptin and adiponectin with enzyme-linked immunosorbent assay and observed the pathological changes of perirenal fat， uterus and ovary. ResultsFor body weight and length， rats in the precocious puberty group were smaller than those in the normal group within 3 days after vaginal opening， but which did not affect their subsequent growth and development， and there was no significant difference between the two groups at 7 and 12 weeks of age. Within 3 days after vaginal opening， insulin levels had significant difference between the two groups （P = 0.001）， the precocious group showed hyperinsulinemia and increased number of perirenal adipocytes. At three execution times， no significant difference was noted in estradiol， leptin and adiponectin levels between the two groups. The same was true in the ratios of ovary or uterus to body weight between the two groups. ConclusionsPrecocious puberty makes earlier onset of pubertal development and allows body maladaptation to the sudden changes of the internal environment. However， the changes due to precocious puberty are temporary and reversible， and they may become normal in adulthood.

Objective To summarize and analyze the clinical phenotypes,hereditary features and treatment and follow-up strategies of different hereditary pheochromocytoma/paragangliomas(PCC/PGL)and related syndromes.Methods Forty-four clinically diagnosed PCC/PGL patients admitted in our hospital from January 2000 to August 2022 were enrolled,and the clinical data of them and their family members were collected.Second-generation sequencing was performed on 43 patients for genetic detection,and Sanger sequencing was applied to verify the mutation of the probands and family members.Results There were 15 patients diagnosed with hereditary PCC/PGL,including 7 cases of von Hippel-Lindau(VHL)syndrome,3 cases of multiple endocrine neoplasia type 2(MEN2),and 5 cases of familial paraganglioma syndrome.Seven VHL syndrome families were diagnosed as VHL2A(c.500G＞A),VHL2B(c.239G＞T and c.444_457del),and VHL2C(c.293A＞G)according to their clinical manifestations.All probands received surgical treatment,and 2 cases of recurrent PCC and the patients with multiple renal cancer also received targeted therapy with sunitinib.Three MEN2 families carried c.1901G＞C,c.1832G＞A,and c.1901G＞A missense mutations,respectively,and were diagnosed with MEN2A clinically.All of them underwent adrenalectomy and thyroidectomy,including one for preventive thyroidectomy.Among the 5 familial paraganglioma syndrome families,4 patients carried SDHB mutations(SDHB:c.343C＞T,c.541-2A＞G,c.575G＞A,c.268C＞T)and 1 patient carried an SDHD mutation(SDHD:c.337_340del).Sporadic retroperitoneal PGL were most common.Conclusion More than 1/3 of PCC/PGL patients carry germline gene mutations,showing obvious genotype-phenotype correlation.Genetic diagnosis technology plays an important guidance role for clinical precision treatment and follow-up,and genetic counseling.

Cognitive dysfunction is the impairment of higher brain functions.Cognitive impairment caused by neuropsychiatric diseases has caused serious impact on patients'quality of life and the outcome of the disease.The transcranial alternating current stimulation(tACS)improves cognitive function by modulating neural oscillations of specific frequencies,affecting the release of neurotransmitters such as serotonin and dopamine,and enhancing local and distal synchronization of brain networks.Specific frequencies of tACS can improve the cognitive impairment caused by Alzheimer disease(AD),schizophrenia,and depression,among which the gamma and theta frequencies of tACS have the most significant effects on cognitive function.tACS has high safety and low operational difficulty,and has great potential to improve cognitive function.

Objective:To detect the status of PIK3CA in triple-negative breast cancer (TNBC) , and to analyze the relationships between PIK3CA mutation and clinical features and its impact on prognosis.Methods:From January 1, 2016 to December 31, 2018, 50 patients with primary TNBC admitted to Xinxiang Central Hospital of Henan Province were collected. The PIK3CA mutation status was detected, and the relationships between PIK3CA mutation and clinical characteristics of patients with TNBC and its impact on prognosis were analyzed.Results:PIK3CA gene mutation was detected in 9 of 50 TNBC patients, with a mutation frequency of 18.0%. H1047R mutation was found in 4 cases, E545K mutation in 3 cases and E542K mutation in 2 cases. PIK3CA gene mutation was not associated with age ( χ2=3.55, P=0.060) , tumor location ( χ2=1.01, P=0.315) , tumor size ( χ2<0.01, P>0.999) , lymph node status ( χ2=0.76, P=0.385) , clinical stage ( χ2=0.65, P=0.420) , Ki-67 value ( χ2<0.01, P>0.999) , P53 status ( χ2=0.02, P=0.894) and human epidermal growth factor receptor-2 (HER-2) status ( χ2=1.65, P=0.200) . Prognostic analysis showed that 3-year disease-free survival rates of wild-type PIK3CA patients was significantly higher than that of mutant PIK3CA patients (80.5% vs. 11.1%, χ2=28.23, P<0.001) . Conclusion:The frequency of PIK3CA gene mutation is higher in TNBC patients. There is no correlation between PIK3CA mutation and clinicopathologic features in TNBC patients. PIK3CA gene mutation may be significantly associated with poor prognosis of TNBC patients.

Abstract: Objective To analyze the resistance and spatial distribution of Mycobacterium tuberculosis (MTB) to six commonly used anti-tuberculosis drugs in Qinghai Province from 2016 to 2019, so as to provide a reference for tuberculosis treatment and drug-resistant tuberculosis control. Methods A total of 1 182 identified strains of Mycobacterium tuberculosis in Qinghai Province from 2016 to 2019 were collected, and 6 anti-tuberculosis drugs were subjected to drug susceptibility tests and strain confirmed by the proportional method. By means of ArcMap10.7 and SaTScan10.1 software, map visualization, spatial autocorrelation analysis and spatial scanning of MTB drug resistance were performed to identify MTB drug resistance clusters in Qinghai Province. Results From 2016 to 2019, the total drug resistance (TDR) rate of 1 182 Mycobacterium tuberculosis strains in Qinghai Province was 23.77% (281/1 182), with a mono-resistance (MR) rate of 11.08% (131/1 182), a poly-resistance (PDR) rate of 3.89% (46/1 182), a multi-drug resistance (MDR) rate of 8.80% (104/1 182), and an extensive drug resistance (XDR) rate of 0.85% (10/1 182). The rates of MDR, XDR and TDR all showed a decreasing trend year by year (P<0.01). The drug resistance spectrum displayed 21 combinations. The TDR rate and MDR rate in the retreatment patients were higher than those of the initial treated patients, and the difference was statistically significant (χ2 TDR=22.784, χ2MDR=45.082, P<0.01). In terms of demographic characteristics, the TDR rate in males was higher than that in females, and the middle-aged group was higher than other age groups, and the differences were statistically significant (χ2=7.541, 10.825, P<0.05). The results of global spatial autocorrelation analysis showed that there was no statistical significance in the autocorrelation and obvious spatial clustering of MTB drug resistance in Qinghai Province from 2016 to 2019 (P>0.05), which indicated a random distribution. The results of spatiotemporal scanning showed that there was a kind of clustering area, but the clustering effect was not significant (P>0.05), indicating a random distribution. Conclusions The TDR of MTB in Qinghai Province from 2016 to 2019 showed a downward trend year by year. In comparison with the national average, the rate of multi-drug resistance and extensive drug resistance was still high, and most of the multi-drug resistance resulted from rifampicin and isoniazid. The drugresistant population mainly consisted of retreatment, males, and young and middle-aged pop

ObjectiveTo explore the relationship between the intestinal flora and the impairment of liver and kidney in HIV-infected men who have heterosexual sex with healthy women. MethodsFecal samples from 41 HIV-infected heterosexual men who have sex with women （PMSW） and 43 age- and BMI-matched healthy heterosexual men who have sex with women （NMSW） were collected and subjected to 16S rDNA sequencing. The blood levels of AST， ALT， TBIL， UREA， Cr， UA， β2-MG and other liver and kidney function indicators were measured. Bioinformatics methods were used to analyze the characteristics of the intestinal flora of the patients in these two groups， to compare the differential bacteria strains， and to analyze their correlation with liver and kidney function indicators. ResultsIn comparison with NMSW， the alpha diversity of intestinal flora was decreased in PMSW， and the beta diversity analysis showed significant differences in flora characteristics between the two groups （P<0.05）. The abundance of Clostridium， Phylum thick-walled， Trichosporon， and Clostridium tumefaciens decreased but Fusobacteriota increased （LDA score >4）. The comparison of liver and kidney function indexes revealed that AST， β2-MG levels were higher in PMSW than in NMSW， while TBIL was lower in PMSW than in NMSW. The number of patients with abnormal β2-MG was much higher in PMSW than in NMSW， and the difference was statistically significant （P<0.001）. It was also found that AST was negatively correlated with Clostridium （P<0.05）； TBIL was negatively correlated with Clostridium and positively correlated with Phylum thick-walled and Trichosporon （P<0.05）. β2-MG was negatively correlated with Phylum thick-walled， Clostridium， Trichosporon and Rumenococcus （P<0.05） and positively correlated with Clostridium （P<0.05）. ConclusionIn PMSW group， the alpha diversity of the flora is decreased. AST and β2-MG levels are increased， and TBIL level is decreased. These changes were significantly correlated with different strains of bacteria in the intestinal flora.

Objective:To summarize the clinical and genetic features of 7 patients with a mild form of Geleophysic dysplasia type 2(GD2)/Acromicric dysplasia(AD) induced by fibrillin 1(FBN1) gene mutation from one Chinese family.Methods:A Chinese pedigree of mild GD2/AD treated at the Pediatric Endocrinology Department at the First Affiliated Hospital of Sun Yat-sen University between August 2017 and May 2022 was collected. Whole-exome genetic sequencing of the FBN1 gene were performed to establish the diagnosis. Additionally, a literature review was further conducted.Results:In this family, among 13 individuals spanning three generations, there were 7 affected cases, including 1 adult female, 1 adult male, and 5 children. All individuals exhibited postnatal growth failure, severe disproportionate short stature, and lacked typical facial features. Exome sequencing and Sanger sequencing confirmed the presence of a heterozygous missense mutation c. 5099A>G(p.Tyr1700Cys) in exon 42 of the FBNI gene in 6 affected individuals(Ⅱ-1, Ⅲ-1 to Ⅲ-5), which was identified as a pathogenic mutation. This mutation was previously reported in a Chinese classical achondroplasia(AD) family. Based on comprehensive genetic analysis, clinical features, and multisystem evaluation, 3 cases were diagnosed with mild type 2 growth hormone deficiency(GD2), and 4 cases were diagnosed with mild AD. Recombinant human growth hormone(rhGH; 1.1-1.4 IU·kg -1·week -1) was applied to all the 5 children, and additional gonadotropin releasing hormone analogue(GnRHa) was administered to the 2 girls in late puberty, resulting in certain growth-promoting effect. Conclusions:The c. 5099A>G(p.Tyr1700Cys) mutation not only leads to the classical type of achondroplasia(AD) as reported in the literature but also causes the non-classical GD2 or AD(mild GD2/AD). Further research is warranted to investigate the long-term therapeutic effects of rhGH treatment.

Objective: The study aims to explore the epidemiological characteristics of tuberculosis among students in Qinghai Province, to provide scientific basis for the prevention and control of students tuberculosis. Methods: Data on tuberculosis among students from 2016 to 2019 in Qinghai province were collected and epidemiological characteristics were analyzed, the spatial distribution map were drawn by using ArcMap 10.8. Results: During 2016-2019, there were 2 691 reported cases of tuberculosis among students in Qinghai Province the reporting rate were 46.10/10 5, 68.50/10 5, 73.49/10 5, 85.96/10 5, increased year by year( χ 2=116.45, P <0.01). With a high incidence from March to September each year. The tuberculosis patients were mainly aged 18 years and above, with more reported female cases than male cases and more Tibetan cases. Most of students tuberculosis cases were reported in southern Qinghai, especially in Yushu and Guoluo areas, and sharp increase was observed in Xining during 2018 to 2019. Conclusion Students tuberculosis in Qinghai is still serious. Schools should strengthen education on tuberculosis prevention, especially those in southern Qinghai and Xining.

Objective: To preliminarily analyze the prediction efficiency of multimodal MRI-based radiomics model for preoperative glioma IDH1 gene expression type. Methods: The MRI data of 108 surgery-proven glioma patients from May 2015 to January 2019 were retrospectively analyzed, and the MRI data included axial T₁WI,T₂WI,fluid attenuated inversion recovery (FLAIR),DWI imaging and enhanced T₁WI sequence.Forty-seven cases were IDH1 mutant type, and 61 cases were IDH1 wild type. All patients were divided into training and validation groups according to the 7∶3 ratio of the random forest model. Seventy-three cases were in training group, and 35 cases were in validation group. Independent predictors of IDH1 mutation were screened by univariate analysis combined with multivariate logistic regression analysis (P<0.05) in order to construct a random forest diagnosis model of general clinical information and conventional MRI morphological features.General clinical information and conventional MRI morphological features included gender, age, umbers of cases of left and right hemispheres, location of tumors, maximum diameter of tumors, peritumoral edema, intratumoral cystic degeneration, enhancement and ADC value of tumors. The ROI was manually outlined by MaZda software in the most obvious level of 5 sequences of tumor mass and the radiomics features were extracted, including the gray-level co-occurrence matrix(GLCM), the run-length matrix(RUN), the absolute gradient(GRA),the auto-regressive model(ARM) and wavelets transform(WAV). The least absolute shrinkage and selection operator (LASSO)regression were used to select image radiomics features with a method of 10 fold cross -validation and to reduce the dimensions. The screened image radiomics labels were combined with the conventional morphological feature independent predictors to construct a multimodal MRI-based random forest model, and the validation data set was used to evaluate the accuracy and diagnostic efficiency of each model. The sensitivity and specificity of conventional MRI morphological feature model and multimodal MRI-based radiomics prediction model were evaluated dynamically by drawing ROC curves, and the prediction efficiency of the two models was quantified by using AUC statistical indicators. The model classification error rate under different outcomes and the classification error rate of out of bag(OOB)were used to evaluate the stability of the multimodal MRI-based random forest model. The contribution rate of each variable to the model was reflected by the characteristic variables importance assessment map. Results: Univariate regression analysis of the conventional MRI morphological characteristics showed that peritumoral edema, cystic degeneration and enhancement were the three independent predictors of IDH1 gene expression (P<0.01). LASSO algorithm and 10-fold cross-validation identified six robust radiomic features including high frequency coefficients of wavelet transform (WavEnHH_s-4) of T₂WI, S(4,4) inverse difference of gray uniformity measurement (InvDfMom),S(5,0) Entropy (entropy),WavEnHH_s-4 of T₁WI enhancement, S(1,1) InvDfMom,S(1, -1) Entropy Difference (DifEntrp)of Flair.The error rate of classification for different outcomes and classification error rate of random forest OOB data of multimodal MRI radiomics diagnosis model finally stabilized at 10%. The results of Characteristic Variable Importance Assessment Map: Mean Decrease Accuracy and Mean Decrease Gini index were consistent, which showed that besides three conventional MRI morphological predictors peritumoral edema, enhancement and cystic degeneration, the radiomics labels also played a key role in the model. The results of ROC curve showed that the accuracy, specificity, sensitivity and AUC of conventional MRI morphological feature model were 82.7%, 68.4%, 90.9% and 0.835, respectively, and those of multimodal MRI-based radiomics model were 88.5%, 89.5%, 87.8% and 0.956 respectively. Conclusion Multimodal MRI-based radiomics random forest model can improve the predictive efficiency of preoperative glioma IDH1 gene expression type more quantitatively.

Objective To preliminarily analyze the prediction efficiency of multimodal MRI?based radiomics model for preoperative glioma IDH1 gene expression type. Methods The MRI data of 108 surgery?proven glioma patients from May 2015 to January 2019 were retrospectively analyzed, and the MRI data included axial T1WI,T2WI,fluid attenuated inversion recovery (FLAIR),DWI imaging and enhanced T1WI sequence.Forty-seven cases were IDH1 mutant type, and 61 cases were IDH1 wild type. All patients were divided into training and validation groups according to the 7∶3 ratio of the random forest model. Seventy-three cases were in training group, and 35 cases were in validation group. Independent predictors of IDH1 mutation were screened by univariate analysis combined with multivariate logistic regression analysis (P<0.05) in order to construct a random forest diagnosis model of general clinical information and conventional MRI morphological features.General clinical information and conventional MRI morphological features included gender, age, umbers of cases of left and right hemispheres, location of tumors, maximum diameter of tumors, peritumoral edema, intratumoral cystic degeneration, enhancement and ADC value of tumors. The ROI was manually outlined by MaZda software in the most obvious level of 5 sequences of tumor mass and the radiomics features were extracted, including the gray?level co?occurrence matrix(GLCM), the run?length matrix(RUN), the absolute gradient(GRA),the auto?regressive model(ARM) and wavelets transform (WAV). The least absolute shrinkage and selection operator (LASSO)regression were used to select image radiomics features with a method of 10 fold cross?validation and to reduce the dimensions. The screened image radiomics labels were combined with the conventional morphological feature independent predictors to construct a multimodal MRI?based random forest model, and the validation data set was used to evaluate the accuracy and diagnostic efficiency of each model. The sensitivity and specificity of conventional MRI morphological feature model and multimodal MRI?based radiomics prediction model were evaluated dynamically by drawing ROC curves, and the prediction efficiency of the two models was quantified by using AUC statistical indicators. The model classification error rate under different outcomes and the classification error rate of out of bag(OOB)were used to evaluate the stability of the multimodal MRI?based random forest model. The contribution rate of each variable to the model was reflected by the characteristic variables importance assessment map. Results Univariate regression analysis of the conventional MRI morphological characteristics showed that peritumoral edema, cystic degeneration and enhancement were the three independent predictors of IDH1 gene expression (P<0.01). LASSO algorithm and 10?fold cross?validation identified six robust radiomic features including high frequency coefficients of wavelet transform (WavEnHH_s?4) of T2WI, S(4, 4) inverse difference of gray uniformity measurement (InvDfMom), S(5, 0) Entropy (entropy), WavEnHH_s?4 of T1WI enhancement, S(1, 1) InvDfMom, S(1, -1) Entropy Difference (DifEntrp)of Flair.The error rate of classification for different outcomes and classification error rate of random forest OOB data of multimodal MRI radiomics diagnosis model finally stabilized at 10%. The results of Characteristic Variable Importance Assessment Map: Mean Decrease Accuracy and Mean Decrease Gini index were consistent, which showed that besides three conventional MRI morphological predictors peritumoral edema, enhancement and cystic degeneration, the radiomics labels also played a key role in the model. The results of ROC curve showed that the accuracy, specificity,sensitivity and AUC of conventional MRI morphological feature model were 82.7%, 68.4%, 90.9% and 0.835, respectively, and those of multimodal MRI?based radiomics model were 88.5%, 89.5%, 87.8% and 0.956 respectively. Conclusion Multimodal MRI?based radiomics random forest model can improve the predictive efficiency of preoperative glioma IDH1 gene expression type more quantitatively.