Achondroplasia (ACH) is a common inherited skeletal dysplasia (inherited dwarfism) that compromises quality of life across the lifespan. In 2021, vosoritide became the first approved precision therapy for ACH and is now available in more than 40 countries. Compared with prior symptomatic measures, vosoritide has demonstrated favorable efficacy and a reassuring safety profile. Nevertheless, existing international ACH guidelines largely emphasize complication management and symptomatic care, and there is no unified consensus on pharmacologic therapy. To address this gap, an international expert group developed the International Consensus Guidelines for the Implementation and Monitoring of Vosoritide Therapy in Patients with Achondroplasia providing systematic recommendations that span the continuum of care - from initial patient contact and pre-treatment assessment to medication counseling, injection training, and long-term outcome monitoring. These recommendations complement and refine current management and nursing protocols for individuals with ACH and offer practical guidance for clinicians across diverse regions. This article highlights key elements of the guideline to provide evidence-based support and clinical direction for healthcare professionals in China treating children with ACH using vosoritide.
Humans ; Achondroplasia/drug therapy* ; Consensus ; Practice Guidelines as Topic ; Child

Objective To explore the pathogenesis and prognostic factors of liposarcoma in the head and neck region, and simultaneously analyze the efficacy of different treatment regimens. Methods A retrospective analysis was performed on all patients with primary untreated head and neck liposarcoma who were diagnosed and underwent surgical treatment at our hospital from January 2008 to January 2024. All patients were monitored during follow-up, and their prognoses were analyzed using SPSS software. Results A total of 30 patients were included in the study. Liposarcoma accounted for up to 60% of the cases in the orbit, while the remaining liposarcomas were primarily located in various interspaces of the neck. Dedifferentiated liposarcoma was the most common type, comprising 33%, while myxoid pleomorphic liposarcoma was the rarest at 4%. The tumor pathological type (P<0.001) and Ki67 (P=0.014) significantly affected the tumor control rate. However, an analysis of disease-specific survival rates revealed no significant differences across various factors (all P>0.05). Conclusion The prognosis of head and neck liposarcoma is better compared to that of liposarcomas in other parts of the body. However, myxoid pleomorphic liposarcoma, pleomorphic fat sarcoma, and high Ki67 levels are indicators of poor prognosis. Additionally, postoperative adjuvant radiotherapy does not significantly enhance disease-specific survival rates.

Objective:Using resting-state functional magnetic resonance imaging (rs-fMRI), we explored the changes in dynamic functional network connections (dFNC) in the brains of patients with first-episode schizophrenia (SZ) and evaluated the potential clinical value of dFNC changes in combination with a machine learning model.Methods:Clinical data of 50 patients with schizophrenia (schizophrenia group), 29 males and 21 females, aged 18-47 (28.3±7.2) years, who attended the psychiatric department of the Second Affiliated Hospital of Xinxiang Medical College from January 2022 to August 2023, were retrospectively included. In the same period, 50 healthy controls matched for age and education (healthy control group) were recruited, of which 24 were male and 26 were female, aged 18-48 (28.0±6.9) years. The rs-fMRI imaging data were acquired for each subject. The dFNC cluster analysis was performed based on independent component analysis, and the differences between groups with different state FNC matrices were statistically analyzed. The dataset samples were divided into a training set (35 SZ patients and 35 healthy controls) and a validation set (15 SZ patients and 15 healthy controls) in a 7∶3 ratio. A machine learning classification model was constructed based on the dFNC matri. The performance of the model for distinguishing between schizophrenia and healthy controls was assessed by five-fold cross-validation using accuracy (ACC), recall (REC), F1 score, and area under curve (AUC) metrics of the working characteristics of the subjects.Results:Five network functional connectivity states were obtained by dFNC cluster analysis. Patients with first SZ showed a wide range of high connectivity and low connectivity changes on the neural dynamic functional networks, as shown by increased dynamic connectivity within the visual network (VIS) in state 1 (weak connectivity); The dynamic connectivity between executive control network (ECN) and VIS, frontal parietal network (FPN) and VIS decreases at state 3 (strong connectivity); The dynamic connectivity between default mode network (DMN) and FPN, DMN and ventral attention network (VAN) decreases at state 4 (weak connectivity). The machine learning results show that the classification model constructed by the dFNC matrix combined with SVM in state 3 (strongly connected) in the validation set obtains the best classification results (ACC=0.938; REC=0.938; F1=0.937; AUC=0.984), and the overall average classification ACC of the five states reaches 0.751, and AUC reaches 0.784.Conclusion:Patients with first-episode SZ have some brain functional network connectivity abnormalities, and a machine learning model based on dFNC features has high classification performance in distinguishing first-episode SZ from HC.

Objective To compare regression models for age estimation constructed based on the Pulp Dentinal Index(PDI)of the first permanent molars and explore a more accurate and applicable novel method.Methods A total of 900 Cone Beam Computed Tomography(CBCT)image datasets from adult Han Chinese individuals(455 males and 445 females)residing in Sichuan province,China,were collected from the Affiliated Hospital of North Sichuan Medical College.The PDI of the first permanent molars were measured using Mimics software.Regression analysis was performed with age as the dependent variable and PDI as the independent variable to establish and validate the optimal mathematical model for age estimation.Results Strong correlations were observed between the PDI of all four first permanent molars and age,with the correlation being stronger for maxillary teeth compared to mandibular teeth,and the highest correlation found in the left maxillary first molar among females(r=0.881).Significant differences in PDI were identified between maxillary and mandibular positions as well as between genders(P＜0.05),but not between left and right positions(P＞0.05).Among the 11 mathematical models constructed,the cubic regression model outperformed others,with the left maxillary first molar model demonstrating the best performance(Age=73.93-70.79x-68.75x2+94.33x3),yielding a mean absolute error(MAE)of 4.88 years.Conclusion Among the 11 regression models constructed in this study based on CBCT-measured PDI values of the first permanent molars,the cubic regression model exhibited the highest accuracy,with an MAE of 4.88 years.

Objective:To investigate the role of the CD38/p53/ME1 axis in regulating T cell mitochondrial function and senescence during HIV infection.Methods:The expression of CD38 on T cells was examined in HIV-infected individuals receiving antiretroviral therapy(ART), untreated HIV-infected individuals, and HIV-negative healthy controls. Flow cytometry was used to compare senescence markers and mitochondrial function between CD38 + and CD38 - T cells. Malic enzyme 1(ME1) mRNA levels were measured by qRT-PCR in T cells treated with the CD38 inhibitor 78c. Mitochondrial function and senescence were assessed in T cells treated with an ME1 inhibitor. The regulatory mechanism of CD38-mediated ME1 downregulation was further explored. Results:Compared to healthy controls, T cells from HIV-infected individuals exhibited significantly elevated CD38 expression, which persisted despite ART. CD38 + T cells showed increased senescence (CD28 -CD57 + subset) and mitochondrial dysfunction[depolarization and reactive oxygen species(ROS) accumulation]. CD38 inhibition upregulated ME1 mRNA level ( P<0.05). ME1 suppression led to mitochondrial impairment (reduced membrane potential and elevated ROS) and senescence in T cells. Mechanistically, CD38 depletion increased NAD + levels and SIRT1 activity, while SIRT1/p53 inhibition rescued ME1 expression, suggesting CD38 regulates ME1 via the NAD + /SIRT1/p53 axis. Conclusions:The CD38/p53/ME1 axis drives T cell senescence in HIV infection by disrupting mitochondrial function. Targeting this pathway may ameliorate CD38-associated T cell dysfunction and immune aging.

AIM To study the chemical constituents from Commelina communis L.METHODS The 95％ethanol extract from C.Communis was isolated and purified by activated charcoal,silica gel,Sephadex LH-20,and HPLC,then the structures of obtained compounds were identified by physicochemical properties and spectral data.RESULTS Seventeen compounds were isolated and identified as p-hydroxyl ethyl cinnamate(1),p-hydroxybenzaldehyde(2),vanillin(3),4-hydroxy-2,3-dimethyl-2-nonen-4-olide(4),hemeratrol A(5),chakyunglupulin B(6),chakyunglupulin A(7),2-(2-hydroxyethyl)-3-methylfumaric acid(8),N-cis-feruloyl tyramine(9),N-trans-coumaroyltyramine(10),5,6,7,3',4',5'-hexamethoxyflavone(11),N-trans-sinapoyltyramine(12),dihydro-feruloyltyramine(13),N-trans-feruloyltyramine(14),2-phenylethanol-β-D-glucoside(15),quercetin-3-O-β-D-glucoside(16),and isorhamnetin-3-O-β-D-glucopyranoside(17).CONCLUSION Compounds 4-8,10 and 11 are isolated from Commelina genus for the first time,and 1,9,12-15 are first isolated from this plant.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

OBJECTIVES: Accurate identification of risk factors for precocious puberty is essential for clinical diagnosis and management, yet the performance of natural language processing methods applied to unstructured electronic medical record (EMR) data remains to be fully evaluated. This study aims to assess the performance of a prompt engineering method for extracting individual risk factors of precocious puberty from EMRs. METHODS: Based on the capacity and role-insight-statement-personality-experiment (CRISPE) prompt framework, both simple and optimized prompts were designed to guide the large language model GLM-4-9B in extracting 10 types of risk factors for precocious puberty from 653 EMRs. Accuracy, precision, recall, and F1-score were used as evaluation metrics for the information extraction task. RESULTS: Under simple and optimized prompt conditions, the overall accuracy, precision, recall, and F1-score of the model were 84.18%, 98.09%, 81.99%, and 89.32% versus 97.15%, 98.31%, 98.16%, and 98.23%, respectively. The optimized prompts achieved more stable performance across age (<9 years vs ≥9 years) and visit-time (<2023 vs ≥2023) subgroups compared with simple prompts. The accuracy range for extracting each risk factor was 60.03%-97.24%, while with optimized prompts, the range improved to 92.19%-99.85%. The largest performance improvement occurred for "beverage intake" (60.03% vs 92.19%), and the smallest for "maternal age of menarche" (97.24% vs 99.23%). In comparing distributions among simple prompts, optimized prompts, and ground truth, statistically significant differences were observed for snack intake, beverage intake, soy milk intake, honey intake, supplement use, tonic use, sleep quality, and sleeping with the light on (all P<0.001), while exercise (P=0.966) and maternal menarche age (P=0.952) showed no significant differences. CONCLUSIONS Compared with simple prompts, optimized prompts substantially improved the extraction performance of individual risk factors for precocious puberty from EMRs, underscoring the critical role of prompt engineering in enhancing large language model performance.
Humans ; Puberty, Precocious/epidemiology* ; Risk Factors ; Electronic Health Records ; Female ; Child ; Natural Language Processing