Objective: To systematically review the development and changes in mental health policies within the National Outline for Children s Development in China from 1992 to 2030, providing a reference basis for future formulation of mental health policies among children and adolescent in China. Methods: Based on the four editions of the National Outline for Children s Development in China across different periods from 1992 to 2030, word frequency analysis was used to reveal shifts in policy priorities, and an internationally recognized framework for adolescent health policy analysis was applied to conduct a textual review. Results: Word frequency analysis revealed that the term "psychological" appeared 6 times in the National Outline for Children s Development in China (2001-2010) but increased to 20 times in the National Outline for Children s Development in China (2021-2030) (abbreviated as the National Outline of 2021), while the term "health" rose from 4 times in the National Outline for Children s Development Plan in China in the 1990s to 68 times in the National Outline of 2021. The scope of mental health policy interventions expanded to encompass five key areas:health, safety, education, welfare and legal protection. Textual analysis highlighted that the policies of the National Outline for Children s Development in China were demand driven, prioritized vulnerable groups and continuously broadened their coverage, emphasizing sustainability and appropriateness, and monitoring/evaluation mechanisms. By 2023, 42.3% of primary schools and 64.8% of secondary schools employed full time mental health education teachers. However, the National Outline for Children s Development in China lacked direct evidence of children and adolescents participation in policy formulation, and publicly available mental health data disaggregated by age and gender remained limited. Conclusion Mental health policies of children and adolescents in China have evolved from nonexistence to gradual refinement, yet institutionalized channels for youth involvement in policy development and evaluation remain insufficient, and transparency in age and gender specific mental health data needs improvement.

OBJECTIVES: To investigate the effect of interferon-λ1 (IFN-λ1) on glucocorticoid (GC) resistance in human bronchial epithelial cells (HBECs) stimulated by respiratory syncytial virus (RSV). METHODS: HBECs were divided into five groups: control, dexamethasone, IFN-λ1, RSV, and RSV+IFN-λ1. CCK-8 assay was used to measure the effect of different concentrations of IFN-λ1 on the viability of HBECs, and the sensitivity of HBECs to dexamethasone was measured in each group. Quantitative real-time PCR was used to measure the mRNA expression levels of p38 mitogen-activated protein kinase (p38 MAPK), glucocorticoid receptor (GR), and MAPK phosphatase-1 (MKP-1). Western blot was used to measure the protein expression level of GR in cell nucleus and cytoplasm, and the nuclear/cytoplasmic ratio of GR was calculated. RESULTS: At 24 and 72 hours, the proliferation activity of HBECs increased with the increase in IFN-λ1 concentration in a dose- and time-dependent manner (P˂0.05). Compared with the RSV group, the RSV+IFN-λ1 group had significant reductions in the half-maximal inhibitory concentration of dexamethasone and the mRNA expression level of p38 MAPK (P<0.05), as well as significant increases in the mRNA expression levels of GR and MKP-1, the level of GR in cell nucleus and cytoplasm, and the nuclear/cytoplasmic GR ratio (P<0.05). CONCLUSIONS IFN-λ1 can inhibit the p38 MAPK pathway by upregulating MKP-1, promote the nuclear translocation of GR, and thus ameliorate GC resistance in HBECs.
Humans ; p38 Mitogen-Activated Protein Kinases/genetics* ; Glucocorticoids/pharmacology* ; Receptors, Glucocorticoid/analysis* ; Dual Specificity Phosphatase 1/physiology* ; Dexamethasone/pharmacology* ; Drug Resistance/drug effects* ; Respiratory Syncytial Viruses ; Interferons/pharmacology* ; MAP Kinase Signaling System/drug effects* ; Epithelial Cells/drug effects* ; Signal Transduction/drug effects* ; Cells, Cultured

OBJECTIVES: To study the clinical and genetic characteristics of children with congenital adrenal hyperplasia (CAH). METHODS: Clinical data, laboratory findings, and genetic test results of 63 children diagnosed with CAH at Henan Children's Hospital from January 2017 to December 2024 were retrospectively reviewed. RESULTS: Of the 63 patients, the mean age at the first visit was (21 ± 14) days; 29 (46%) were of male sex and 34 (54%) were of female sex. The predominant clinical manifestations were poor weight gain or weight loss (92%, 58/63), poor feeding (84%, 53/63), skin hyperpigmentation (83%, 52/63), and female external genital anomalies (100%, 34/34). Laboratory abnormalities included hyponatremia (87%, 55/63), hyperkalemia (68%, 43/63), metabolic acidosis (68%, 43/63), and markedly elevated 17-hydroxyprogesterone (92%, 58/63), testosterone (89%, 56/63), and adrenocorticotropic hormone (81%, 51/63). Among 49 patients who underwent genetic testing, CYP21A2 variants were identified in 90% (44/49), with c.293-13A/C>G (33%, 30/91) and large deletions/gene conversions (29%, 26/91) being the most frequent; STAR (8%, 4/49) and HSD3B2 (2%, 1/49) variants were also detected. Following hormone replacement therapy, electrolyte disturbances were corrected in 57 cases, with significant reductions in 17-hydroxyprogesterone, adrenocorticotropic hormone, and testosterone levels (P<0.001). CONCLUSIONS CAH presenting in neonates or young infants is characterized by electrolyte imbalance, external genital anomalies, and abnormal hormone levels. Genetic testing enables definitive subtype classification; in CYP21A2-related CAH, c.293-13A/C>G is a hotspot variant. These findings underscore the clinical value of genetic testing for early diagnosis and genetic counseling in CAH. Citation:Chinese Journal of Contemporary Pediatrics, 2025, 27(11): 1367-1372.
Humans ; Adrenal Hyperplasia, Congenital/diagnosis* ; Male ; Female ; Retrospective Studies ; Infant ; Infant, Newborn

Hepatic stellate cells (HSCs) are the primary fibrogenic cells in the liver, and their activation plays a crucial role in the development and progression of hepatic fibrosis. Here, we report that retinoid X receptor-alpha (RXRα), a unique member of the nuclear receptor superfamily, is a key modulator of HSC activation and liver fibrosis. RXRα exerts its effects by modulating calcium/calmodulin-dependent protein kinase kinase β (CaMKKβ)-mediated activation of AMP-activated protein kinase-alpha (AMPKα). In addition, we demonstrate that K-80003, which binds RXRα by a unique mechanism, effectively suppresses HSC activation, proliferation, and migration, thereby inhibiting liver fibrosis in the CCl₄ and amylin liver NASH (AMLN) diet animal models. The effect is mediated by AMPKα activation, promoting mitophagy in HSCs. Mechanistically, K-80003 activates AMPKα by inducing RXRα to form condensates with CaMKKβ and AMPKα via a two-phase process. The formation of RXRα condensates is driven by its N-terminal intrinsic disorder region and requires phosphorylation by CaMKKβ. Our results reveal a crucial role of RXRα in liver fibrosis regulation through modulating mitochondrial activities in HSCs. Furthermore, they suggest that K-80003 and related RXRα modulators hold promise as therapeutic agents for fibrosis-related diseases.

Traditional development of small protein scaffolds has relied on display technologies and mutation-based engineering, which limit sequence and functional diversity, thereby constraining their therapeutic and application potential. Protein design tools have significantly advanced the creation of novel protein sequences, structures, and functions. However, further improvements in design strategies are still needed to more efficiently optimize the functional performance of protein-based drugs and enhance their druggability. Here, we extended an evolution-based design protocol to create a novel minibinder, BindHer, against the human epidermal growth factor receptor 2 (HER2). It not only exhibits super stability and binding selectivity but also demonstrates remarkable properties in tissue specificity. Radiolabeling experiments with ^99mTc, ⁶⁸Ga, and ¹⁸F revealed that BindHer efficiently targets tumors in HER2-positive breast cancer mouse models, with minimal nonspecific liver absorption, outperforming scaffolds designed through traditional engineering. These findings highlight a new rational approach to automated protein design, offering significant potential for large-scale applications in therapeutic mini-protein development.

Objective To understand the infectious pathogen characteristics and drug sensitivity of hospitalized patients in the respiratory intensive care unit (RICU) of Renmin Hospital of Wuhan University. Methods Bacterial culture samples sent to the RICU of our hospital from January 2020 to December 2022 were retrospectively analyzed. The bacterial types were identified by Bruker mass spectrometer, and the Phoenix 100 was used for drug sensitivity analysis. The antimicrobial susceptibility was analyzed by WHONET 5.6 software. Results A total of 1 157 strains of bacteria were isolated, including 878 strains of Gram-negative bacteria (75.89%) and 279 strains of Gram-positive bacteria (24.11%). The top five with the highest detection rate were Acinetobacter baumannii (25.50%), Pseudomonas aeruginosa (18.76%), Klebsiella pneumoniae (13.83%), Staphylococcus aureus (6.57%) and Escherichia coli (5.70%). Among them, Acinetobacter baumannii was extremely drug-resistant, only showing relatively high sensitivity to colistin, minocycline, and tigecycline. Staphylococcus aureus accounted for the highest proportion of Gram-positive bacteria (6.57%), with methicillin-resistant Staphylococcus (MRSA) showing a continuous increase. Conclusion In the past three years, Gram-negative bacteria have been the main pathogenic bacteria detected in the respiratory intensive care unit of our hospital. The main bacteria are Acinetobacter baumannii, Pseudomonas aeruginosa, and Klebsiella pneumoniae, which have a high resistance rate to various antibiotics. Therefore, clinical monitoring of resistant strains in RICU should be strengthened to facilitate rational use of antibiotics and improve antibacterial effect.

Objective To investigate the trends of major thyroid function indices in Chinese adolescent females at different ages and the differences from adult reference intervals.Methods A total of 791 female students from 4 junior high schools were enrolled in the study by selecting one junior high school in each of the following locations:Minhang District of Shanghai,Haimen City of Jiangsu Province,Yuhuan City of Zhejiang Province,and Deqing County of Zhejiang Province from Oct to Nov 2017 and from Jan to Mar 2019.The subjects were subjected to physical examination as well as thyroid hormone levels;and the Pubertal Developmental Events Self-Assessment Scale(PDS)was used to evaluate the staging of pubertal development.Follow-ups were conducted after 2 years,with the same survey content.Thyroid function levels were assessed in 5 age groups between 11 to 15 years old,95%CI were calculated,and mixed linear models were used to analyze the effects of age and pubertal developmental stage on hormone levels.Results The reference intervals for thyroid stimulating hormone(TSH),free triiodothyronine(FT3)and free thyroxine(FT4)in adolescent females differed significantly from those of adults,with misclassification rates ranging from 2.98%to 5.17%.Statistically significant differences were found for age,pubertal development staging,and the interaction of age and pubertal staging after correcting for BMI,waist circumference(all P<0.05).TSH levels were more affected by age before the completion of pubertal development,the level of the 12-year-old group was higher than that of the 11-year-old group(P=0.001 2)and the 13-year-old group(P<0.000 1);FT3 levels showed greater variability with age during late pubertal stage,with levels significantly higher at 13 years of age than at 11 and 12 years of age(P<0.0001),and gradually decreasing after 13 years of age(P<0.000 1).In contrast,FT4 levels were generally less affected by age between 11 and 15 years of age,with levels slightly higher at 13-15 years of age than at 11-12 years of age(P<0.000 1).Conclusion The levels of TSH,FT3,and FT4,as indicators of thyroid function in adolescent females,differ significantly from those of adults,and are differently affected by age and the stages of pubertal development;further refinement of the reference intervals for age-and pubertal-development-specific thyroid indicators is necessary.

Objective To construct trajectory models of care-seeking patterns for type 2 diabetes mellitus(T2DM)patients,analyze the influencing factors of different trajectories,and explore the fasting blood glucose control levels of T2DM patients with different trajectories.Methods A retrospective cohort study was carried out on 18088 T2DM patients who had health records and been involved in the diabetic management in Community Health Service Center of Minhang District,Shanghai from 2006 to 2009.Starting from Jan 1,2010,participants were followed up until Dec 31,2019,with complete follow-up information.Group-based trajectory modelling(GBTM)was employed to identify and construct the fluctuation trajectory of fasting blood glucose in the patients.Bayesian information criterion(BIC),average posterior probability(AvePP)and other evaluation indicators were used to select the optimum subgroup number model.Then the differences in demographic characteristics,health status,family history,fasting blood glucose,BMI,etc were compared among different categories.Multinational logistic regression model was constructed to explore the influencing factors of different fluctuation trajectories.Cox regression analysis was used to examine the relationship between the long-term trajectories of care-seeking patterns and fasting blood glucose control level.Results Using GBTM analysis,we constructed the optimal Model 4 to categorize 18088 T2DM patients with community health records into five distinct trajectory subgroups:continuous non-attendance group(22.29%),low-level increasing group(15.09%),high-level slowly decreasing group(14.18%),high-level rapidly decreasing group(14.90%),and continuous regular attendance group(33.54%).With the continuous regular attendance group serving as the reference,gender,age,place of residence,baseline comorbidity of hypertension,baseline fasting plasma glucose level,and BMI were found to influence the community attendance trajectories of T2DM patients(P<0.05).After adjusting for confounding factors,Cox regression analysis revealed that compared to the continuous non-attendance group,the low-level increasing group,high-level slowly decreasing group,and continuous regular attendance group had better glycemic control,with HRs of 0.37(95%CI:0.34-0.39),0.72(95%CI:0.67-0.78),and 0.78(95%CI:0.73-0.84),respectively.The glycemic control level in the high-level rapidly decreasing group was comparable,with an HR of 1.06(95%CI:0.99-1.12).Conclusion Based on the optimal model,the community medical treatment trajectories of T2DM patients showed different dynamic characteristics.Factors such as gender,residence,hypertension,and weight loss may influence these varying trajectories.Regular community visits and follow-up may help control blood glucose levels.

Objective:To develop a simple, rapid, and convenient analysis method for the identification of breast cancer and its molecular sub-types.Methods:A laser confocal Raman spectrometer was used to collect Raman spectrograms of normal breast cells and different molecular sub-types of breast cancer cells, and assign the material origin of the Raman spectral peaks. First, Savitzky-Golay smoothing (with a window size of 9) was selected to perform smoothing and denoising on the Raman spectrogram. Subsequently, an iterative adaptive weighted penalty least squares method was employed for baseline correction, and principal component analysis was used to eliminate outliers. The recognition model of normal breast cells and breast cancer cells and the recognition model of different molecular sub-types of breast cancer cells were established by using three algorithms with different principles, including partial least squares discriminant analysis (PLS-DA), K-nearest neighbor (KNN), and support vector machine (SVM).Results:The Raman spectrogram and Raman peak shifts of normal breast cells and breast cancer cells were similar, but there were significant differences in intensity. The results of the machine learning models showed that the recognition accuracy of PLS-DA and SVM algorithms for distinguishing between normal breast cells and breast cancer cells was above 92.03% and 90.67%, respectively. The recognition accuracy of PLS-DA and SVM algorithms for different molecular sub-types of breast cancer cells was (83.66 ± 2.77)% and (90.55 ± 0.06)%, respectively.Conclusions:The combination of Raman spectroscopy and machine learning algorithms can achieve accurate identification of normal breast cells, breast cancer cells, and different molecular sub-types of breast cancer cells.