Objective To comparatively analyze the clinical characteristics of primary bilateral macronodular adrenal hyperplasia(PBMAH)and adrenal cortisol-producing Adenoma(CPA),and enhance the understanding of two diseases.Methods The clinical data of 85 PBMAH patients(PBMAH group)and 195 CPA patients(CPA group)diagnosed at Department of Endocrinology,the First Medical Center of Chinese PLA General Hospital,from September 2014 to August 2024 were retrospectively analyzed.The demographic characteristics,comorbidities,biochemical indicators,adrenocorticotropic hormone-cortisol(ACTH-F)levels,and adrenal imaging features and treatment conditions were compared between the two groups.Results(1)General characteristics:Compared with CPA group,PBMAH group had older age at diagnosis and a higher proportion of male patients.(2)Clinical characteristics:Compared with CPA group,PBMAH group had a longer disease duration,a higher proportion of subclinical Cushing's syndrome(CS),and a higher proportion of hypertension,impaired glucose tolerance/diabetes,bone mass reduction or osteoporosis,with higher serum potassium levels,and the differences were statistically significant(P<0.01).(3)Hormone levels:Both PBMAH and CPA groups showed ACTH-F rhythm disorder,significantly increased cortisol levels and suppressed ACTH.Compared with PBMAH group,CPA group had stronger autonomous cortisol secretion ability,manifested by increased midnight serum cortisol(F0:00),16:00 serum cortisol(F16:00),24-hour urinary free cortisol(24 h UFC)levels and lower 8:00 serum ACTH(ACTH8:00)and 16:00 serum ACTH(ACTH16:00)(P<0.01).After low-dose dexamethasone suppression test(LDDST),CPA group showed lower suppression rates of ACTH and cortisol,and higher proportions of paradoxical elevation in serum cortisol and 24 h UFC compared with PBMAH(P<0.01).Conclusions PBMAH has a longer disease course and higher proportions of comorbid metabolic disorders than CPA,mostly manifested as subclinical Cushing's syndrome.CPA has stronger autonomous cortisol secretion ability,with cortisol less likely to be suppressed after LDDST and more obvious paradoxical elevation of cortisol and 24 h UFC.

Objective To investigate the clinical and pathological characteristics of adrenal cortical carcinoma(ACC),compare differences between hypercortisolism and non-functional ACC,and assess the diagnostic value of indicators such as Ki-67 index.Methods The clinical data of 57 ACC patients admitted to the First Medical Center of Chinese PLA General Hospital from January 2015 to March 2025 were retrospectively analyzed.According to the results of endocrine function assessment,47 of these patients were divided into hypercortisolism group(n=19)and non-functional group(n=28).The differences in clinical and pathological characteristics between the two groups were compared,and non-parametric tests and Spearman correlation analysis were used to explore the relationship between Ki-67 index and tumor stage as well as imaging features.Results Among the 57 patients,there were 20 males and 37 females,with a male-to-female ratio of 1:1.85.The age ranged from 16 to 76 years,and the age at diagnosis was(48.7±13.3)years.The tumor diameter was(10.53±4.14)cm.The tumors were located on the right side in 12 cases(21.1%),on the left side in 34 cases(59.6%),and bilaterally in 11 cases(19.3%).Among them,16 cases(28.1%)were complicated with glucose metabolism disorders,31 cases(54.3%)had hypertension,and 20 cases(35.1%)had hypokalemia.According to ENSAT staging,there were 0 cases in stage Ⅰ,15 cases(26.3%)in stage Ⅱ,24 cases(42.1%)in stage Ⅲ,and 18 cases(31.6%)in stage Ⅳ.Endocrine function assessment was completed in 47 of the 57 patients,including 28 cases(59.6%)of non-functional ACC and 19 cases(40.4%)of hypercortisolism(including 1 case of hypercortisolism combined with increased sex hormone secretion).Compared with non-functional group,hypercortisolism group had a significantly higher prevalence of hypertension(P=0.014),later ENSAT stage(P=0.010),and a higher proportion of hypervascularization(P=0.048).The median Ki-67 index was 20%(10%-40%),showing no significant correlation with either the maximum tumor diameter or SUVmax value,but it was related to ENSAT staging,with Ki-67 index in stageⅣ patients being significantly higher than that in stage Ⅱ(P=0.032).Immunohistochemistry results showed that the positive rate of Inhibin-α was 84.8%,and the positive rate of Melan-A was 40.9%.Conclusions ACC is a rare malignant endocrine tumor.ACC patients with hypercortisolism are more likely to be complicated with hypertension,have later staging,and more common hypervascular manifestations.Clinically,their endocrine function should be prioritized for assessment,and more active treatment strategies should be adopted.Diagnosis should be combined with imaging characteristics(such as hypervascularization)and immunohistochemical indicators(Ki-67,Inhibin-α,Melan-A).The significant increase in Ki-67 is in the advanced stage can serve as an important prognostic indicator to guide individualized treatment.

Heart failure(HF)is a cardiovascular disease with a high prevalence and mortality rate worldwide,and despite the widespread use of existing drugs,device intervetions and surgical procedures,the clinical outcomes are still unsatisfactory.The exploration of new methods to treat HF is still an urgent problem.Gene therapy provides a new therapeutic strategy for HF by targeting the regulation of pathogenic genes.This article systematically reviewed the delivery system optimization,key targets and clinical translational challenges of gene therapy for HF,aiming to provide a theoretical basis for the optimization of treatment strategies.

Objective:To explore the interrelationship between brain functional networks and features in functional magnetic resonance imaging(fMRI)of patients with Alzheimer's disease(AD),and to construct mixed-function networks(MFN),and apply them in machine learning classification models to improve the accuracy of AD classification.Methods:102 AD patients and 227 healthy subjects in the Alzheimer's Neuroimaging Initiative(ADNI)dataset were retrospectively analyzed.The partial correlation brain network of the blood oxygen level dependent(BOLD)signal was calculated and fused with low-frequency wave amplitude(ALFF),fractional low-frequency wave amplitude(fALFF)and local consistency(ReHo)features to construct MFN.Network topology parameters were extracted,and a variety of machine learning classification models were constructed based on MFN topological parameters,accuracy,precision,recall and area under the curve(AUC)were used to evaluate the predictive efficiency of the models.Results:By constructed MFN and calculated intra group to inter group ratio(IIGR),35 features could be obtained from ALFF,fALFF and ReHo feature topological parameter analysis,after rank sum test and FDR correction,there were statistical differences among 28 features(P＜0.05).The classification results show that,all the five classifiers have high classification performance on the test data set.The accuracy,precision and recall rates of random forest(RF),adaptive lifting algorithm(AdaBoost),guided aggregation algorithm(Bagging)and support vector machine(SVM)were all 99.7％,and the AUC values were up to 100％,99.5％,99.1％and 99.5％,respectively.The accuracy(98.5％),precision(98.5％),recall(98.5％),and AUC(99.1％)of the multi-layer perceptron(MLP)were slightly lower than other models,but remained excellent.It was worth noting that RF has the highest AUC value of all models at 100.0％,while Bagging has the lowest AUC value(99.1％)in the integrated approach.The results of performance comparison show that,MFN classification model can significantly improve the recognition and classification of AD disease,and greatly improve the performance of various indicators of the classifier.The results showed that,MFN classification model was superior to intelligent classification based fusion,DBN-based multitask learning,PVT-TSVM,unsupervised learning and clustering,SVM and SVM of degree 3 polynomial kernel function in key indicators such as accuracy(99.13％),AUC(99.42％),recall rate(99.46％)and specificity(99.42％)with plasma proteins,machine learning algorithms.It was further proved that MFN classification model has good generalization ability and robustness in AD disease classification.Conclusion:The AD classification model constructed based on brain mixed function network topology parameters and machine learning can improve the accuracy of AD classification.

Objective To investigate the effects of ischemia time and storage periods on RNA quality in fresh-frozen breast cancer(BC)and esophageal cancer(EC)tissue samples in order to establish evidence-based protocols for biobank sample management.Methods The tumor(T)and paired normal(N)tissue samples from 6 cases of BC and 6 cases of EC were collected and cryopreserved in Biobank,Shantou Central Hospital.Mirror paraffin-embedded tissues were simultaneously prepared into sections for morphological analysis.The samples were divided into two groups of<15 min and 15-30 min according to ischemia time,and RNA quality was analyzed at 4 storage periods of 8-10 months(T1),14-16 months(T2),26-28 months(T3)and 38-40 months(T4).Results In 96 analyzed samples,93.8%(90/96)exhibited high quality(RIN≥6),with 89.6%(43/48)in BC and 97.9%(47/48)in EC.Significant differences in RIN were observed between BC group and EC group(8.050 vs.8.600,P=0.009).In EC group,RIN value was significantly negatively correlated with RNA yield(P<0.001).Moreover,RIN values of tumor-normal pairs exhibited markedly significant differences(7.550 vs.9.000,P<0.001).In contrast,no significant difference was detected in BC group(8.200 vs.7.700,P=0.348).Statistical analysis showed that RIN value was positively correlated with 28S/18S(P<0.001),but had no correlation with tumor content(P=0.676)and necrotic content(P=0.055).Neither ischemia time(<15 min vs.15-30 min:8.200 vs.8.300,P=0.932)nor storage periods(T1-T4:8.400,7.700,8.450,8.600,P=0.163)compromised RNA quality.Conclusion Organ origin and tissue type could influence RNA quality of fresh-frozen tissue samples.However,limited ischemia time(≤30 min)and long-term storage period(38-40 months)do not adversely affect RNA quality in fresh-frozen breast cancer and esophageal cancer tissue samples.

Aim To detect the non-coding RNA(ncRNA)expression profile of neuroglioma cells via whole transcriptome sequencing,establish the ceRNA network and reveal the molecular mechanism of ncRNA participating in the inhibition of neuroglioma cell prolif-eration by melatonin.Methods Neuroglioma cells were intervened with by 0,2,4,6 and 8 mmol·L-1 melatonin for 24,48 and 72 h,and the inhibitory effect of melatonin on cell proliferation was detected via CCK-8;after the intervention of 0 and 4 mmol·L-1 melatonin to U251 cells for 24 h,differentially ex-pressed miRNA(DEmiRNA),lncRNA(DElncRNA)and mRNA(DEmRNA)were detected through whole transcriptome sequencing,along with GO and KEGG enrichment analysis of DEmRNA;the ceRNA network was constructed,and the key gene expression of ceR-NA was verified through qRT-PCR.Results Melato-nin exerts a time-dose-dependent inhibitory effect on the proliferation of neuroglioma cells;a total of 5049 DEmRNA,635 DElncRNA and 146 DEmiRNA in 0 and 4 mmol·L-1 melatonin groups were screened out via whole transcriptome sequencing;DEmRNAs were mainly enriched in cancer-related signaling pathways,such as ferroptosis,mTOR signaling pathway,FoxO signaling pathway and cell cycle;the ceRNA network included 4 lncRNAs,3 miRNAs and 48 mRNAs.As verified through real-time PCR,the expressions of hsa-miR-129-5p,hsa-miR-362-5p,LINC00707 and SLC16A1-AS1 of U251 cells were consistent with the sequencing results,and the gene expression of U87 cells was basically consistent with the sequencing re-sults.Conclusions Melatonin affects cancer-related signaling pathways through the differential expression of ncRNA so as to inhibit the proliferation of U251 cells;the ceRNA network composed of LINC00707,SLC16A1-AS1,hsa-miR-129-5p and hsa-miR-362-5p may take a part in the molecular mechanism of melato-nin in inhibiting neuroglioma cell proliferation.

Objective:To compare the accuracy and applicability of three adult height prediction methods based on artificial intelligence-assisted bone age assessment—the Bayley-Pinneau method(BP method), the Tanner-Whitehouse 3 method(TW3 method), and China 05 method—in girls.Methods:This bidirectional cohort study collected clinical data and 690 posteroanterior X-ray images of the left hand from 278 female children who underwent pubertal development assessments at Shenzhen Children′s Hospital between January 2014 and December 2020, with follow-up until adult height was reached. Adult height prediction was performed using BP, TW3, and China 05 methods on artificial intelligence-assisted bone age assessment.Results:The BP and TW3 methods overestimated adult height by(1.7±3.7) cm and(2.6±3.0) cm, respectively, while the China 05 method underestimated adult height by(2.3±3.5) cm. The proportion of PAH within±5 cm of FAH were 80.0% for the TW3 method, 77.0% for the BP method, and 74.2% for the China 05 method, with significant differences among them( P=0.038). Analysis of cases with prediction deviations>10 cm and subgroup comparisons revealed that the TW3 and BP methods were more likely to overestimate adult height in girls aged 6.0-<8.0 years, with delayed bone age, or in the prepubertal stage(all P<0.001). The China 05 method was more prone to underestimate adult height in those with advanced bone age( P<0.001). All three methods showed significantly greater prediction errors(absolute difference between PAH and FAH) in girls with early puberty compared to those with normal pubertal development(all P<0.05). Conclusions:The TW3 and BP methods tend to overestimate adult height in girls, while the China 05 method tends to underestimate it. Caution is warranted when predicting adult height, particularly in girls under 8 years of bone age, with delayed or advanced bone age, and those with early puberty.

Objective:To explore the relationship between urinary cadmium levels and thyroid hormone levels in people aged 40-89 years old in selected areas of China.Methods:Based on the "Investigation of the Impact of Soil Quality of Agricultural Land on Human Health in Typical Areas" project from October 2019 to August 2020, a multi-stage stratified random sampling method was used to include 6 588 middle-aged and older adults aged 40-89. Demographic characteristics, dietary frequency and disease status were collected through the questionnaire and physical examination. Urinary cadmium and urinary creatinine were detected by random midstream urine. Fasting venous blood was collected for the detection of Triiodothyronine (T3) and Thyroxine (T4). The linear mixed effects model was used to explore the association of urine cadmium levels with thyroid hormone levels. Its dose-response relationship was explored by using the restricted cubic spline.Results:The age of the subjects was (63.48±12.18) years, with males accounting for 51.28%. The M ( Q 1,Q 3) of urinary cadmium level, T3 and T4 was 2.48 (1.36, 4.42) μg/g·creatinine, (1.96±0.51) nmol/L and (113.75±29.11) nmol/L, respectively. The linear mixed effects model showed that the changes of T3 and T4 were 0.027 (0.009, 0.044) nmol/L and 2.019 (1.084, 2.953) nmol/L for each one-unit increase (natural logarithm transformed) of urinary cadmium. The restricted cubic spline showed that there was a positive nonlinear association between urinary cadmium and T3 as well as T4 (all Pnonlinear<0.05). Conclusion:In selected areas of China, the urinary cadmium level of middle-aged and older adults aged 40-89 years is positively associated with T3 and T4.

Objective:To systematically evaluate the molecular characteristics and prognostic value of ammonia death-related genes in hepatocellular carcinoma(HCC).Methods:Consensus unsupervised clustering was used to identify ammonia death-related molecular subtypes in HCC samples.Weighted gene co-expression network analysis(WGCNA)was applied to identify gene modules associated with ammonia death.Support vector machine(SVM)and LASSO algorithms were used to screen four hub genes,and a risk score system was constructed based on a LASSO-Cox regression model.The association between the risk model and patient survival,tumor microenvironment,and re-sponse to immunotherapy was further analyzed.Results:Consensus clustering identified two distinct ammonia death-related molecular subtypes(P<0.05).The constructed risk score model showed good predictive performance for overall survival in HCC patients and was closely associated with immune infiltration characteristics of the tumor microenviron-ment and immunotherapy responsiveness(P<0.05).Conclusion:The ammonia death-related risk score model may serve as a novel prognostic biomarker for HCC and provide potential guidance for immunotherapy strategies.

Objective:To systematically evaluate the molecular characteristics and prognostic value of ammonia death-related genes in hepatocellular carcinoma(HCC).Methods:Consensus unsupervised clustering was used to identify ammonia death-related molecular subtypes in HCC samples.Weighted gene co-expression network analysis(WGCNA)was applied to identify gene modules associated with ammonia death.Support vector machine(SVM)and LASSO algorithms were used to screen four hub genes,and a risk score system was constructed based on a LASSO-Cox regression model.The association between the risk model and patient survival,tumor microenvironment,and re-sponse to immunotherapy was further analyzed.Results:Consensus clustering identified two distinct ammonia death-related molecular subtypes(P<0.05).The constructed risk score model showed good predictive performance for overall survival in HCC patients and was closely associated with immune infiltration characteristics of the tumor microenviron-ment and immunotherapy responsiveness(P<0.05).Conclusion:The ammonia death-related risk score model may serve as a novel prognostic biomarker for HCC and provide potential guidance for immunotherapy strategies.