OBJECTIVE To investigate the effect of Huangqin decoction （HQD）-based self-assembled nanoparticles （SAN） co-loaded with terbinafine （TBF） （TBF-HQD-SAN NPs） on the transdermal absorption of TBF. METHODS High-speed centrifugation combined with dialysis was used to separate HQD-SAN， and TBF-HQD-SAN NPs were obtained by loading TBF using the ultrasound magnetic stirring method； the particle size distribution， Zeta potential and polydispersity index （PDI） of the nanoparticle were characterized， and the encapsulation efficiency （EE） and drug loading （DL） of TBF were determined； using in vitro and in vivo transdermal experiments， the differences in transdermal performance between TBF-HQD-SAN NPs and TBF raw materials， as well as TBF and HQD-SAN physical mixture （TBF-HQD-SAN PM）， were compared and analyzed. RESULTS TBF- HQD-SAN NPs were spherical with a particle size of （177.60±2.57） nm， a PDI of 0.197 4±0.007 9， and a Zeta potential of （－14.63±0.85） mV. The EE and DL of TBF were （99.49±0.71）% and （3.22±0.10）% ， respectively. In vitro transdermal experiments， compared with TBF raw materials， the steady-state permeation rate （Jss） and skin retention of TBF-HQD-SAN NPs increased by 3.34 times and 27.56 times， respectively （P＜0.05）； compared with TBF-HQD-SAN PM， its Jss and skinretention were increased by 2.04 times and 7.44 times， respectively （P＜0.05）. In vivo transdermal experiments 69号） showed that， the area under the drug-time curve and the maximum concentration of TBF-HQD-SAN NPs increased by 2.13 times and 2.06 times respectively compared to TBF raw materials， and increased by 1.59 times and 1.65 times respectively compared to TBF-HQD-SAN PM （P＜0.05）. CONCLUSIONS TBF-HQD-SAN NPs can significantly enhance the in vitro and in vivo transdermal absorption efficiency and skin retention of TBF.

Objective: To analyze the trajectory of dietary behaviors among middle school students in Jiading District, Shanghai, from 2021 to 2023, and longitudinally verify their association with anxiety and depression symptoms, aiming to provide scientific evidence for promoting the mental health of adolescents. Methods: The data were sourced from the National Monitoring and Intervention Project on Common Diseases and Health Impact Factors of students in Jiading District, Shanghai. A total of 1 217 middle school students who participated in at least two surveys from 2021 to 2023 were selected as the research objects, and group-based trajectory model was constructed to identify their dietary behavior scores trajectories. Modified Poisson regression was used to investigate the impact of dietary behavior scores trajectories on anxiety and depression, while Logistic regression was employed to explore the association between trajectories and changes in depression score levels. Results: The dietary behavior scores trajectories of middle school students were divided into three groups: Persistent Healthy Dietary Behavior (9.5%), Persistent Relatively Unhealthy Dietary Behavior (85.0%), and Persistent Very Unhealthy Dietary Behavior (5.5%). Students who perceived their academic performance as poor and whose parents had a cultural level of high school or below had a significantly lower proportion in the Persistent Healthy Dietary Behavior group compared to students with other characteristics ( χ 2=12.87, 8.69, 6.50, P <0.05). Compared with the Persistent Healthy Dietary Behavior group, the risk of anxiety symptoms in middle school students in the Persistent Very Unhealthy Dietary Behavior group was significantly increased ( aRR=3.04, 95%CI =1.15-8.02); Persistent Relatively Unhealthy Dietary Behavior and Persistent Very Unhealthy Dietary Behavior increased the risk of depressive symptoms ( aRR = 1.80 , 2.45, respectively), and were positively correlated with the increase in depression scores ( aOR =1.70, 2.24) ( P <0.05). Conclusions The dietary behavior of middle school students have not changed significantly in the past three years, with persistent unhealthy dietary behavior being the most common. Unhealthy dietary behaviors are positively correlated with the risk of anxiety and depressive symptoms and an increase in depression scores.

Background: Psychological test reports are essential in assessing intellectual functioning, aiding in diagnosing and treating intellectual disability (ID) and attention-deficit/ hyperactivity disorder (ADHD). However, these reports can have several problems because they are diverse, unstructured, subjective, and involve human errors. Additionally, physicians often do not read the entire report, and the number of reports is lower than that of diagnoses. Methods: We developed explainable predictive models for classifying IDs and ADHDs based on written reports to address these issues. The reports of 1,475 patients with IDs and ADHDs who underwent intelligence tests were used for the models. These models were developed by analyzing reports using natural language processing (NLP) and incorporating the physician’s diagnosis for each report. We selected n-gram features from the models’ results by extracting important features using SHapley Additive exPlanations and permutation importance to make the models explainable. Developing the n-gram feature-based original text search system compensated for the lack of human readability caused by NLP and enabled the reconstruction of human-readable texts from the selected n-gram features. Results: The maximum model accuracy was 0.92, and the 80 human-readable texts were restored from four models. Conclusion The results showed that the models could accurately classify IDs and ADHDs, even with a few reports. The models were also able to explain their predictions. The explainability-enhanced model can help physicians understand the classification process of IDs and ADHDs and provide evidence-based insights.

Background: Psychological test reports are essential in assessing intellectual functioning, aiding in diagnosing and treating intellectual disability (ID) and attention-deficit/ hyperactivity disorder (ADHD). However, these reports can have several problems because they are diverse, unstructured, subjective, and involve human errors. Additionally, physicians often do not read the entire report, and the number of reports is lower than that of diagnoses. Methods: We developed explainable predictive models for classifying IDs and ADHDs based on written reports to address these issues. The reports of 1,475 patients with IDs and ADHDs who underwent intelligence tests were used for the models. These models were developed by analyzing reports using natural language processing (NLP) and incorporating the physician’s diagnosis for each report. We selected n-gram features from the models’ results by extracting important features using SHapley Additive exPlanations and permutation importance to make the models explainable. Developing the n-gram feature-based original text search system compensated for the lack of human readability caused by NLP and enabled the reconstruction of human-readable texts from the selected n-gram features. Results: The maximum model accuracy was 0.92, and the 80 human-readable texts were restored from four models. Conclusion The results showed that the models could accurately classify IDs and ADHDs, even with a few reports. The models were also able to explain their predictions. The explainability-enhanced model can help physicians understand the classification process of IDs and ADHDs and provide evidence-based insights.

Background: Psychological test reports are essential in assessing intellectual functioning, aiding in diagnosing and treating intellectual disability (ID) and attention-deficit/ hyperactivity disorder (ADHD). However, these reports can have several problems because they are diverse, unstructured, subjective, and involve human errors. Additionally, physicians often do not read the entire report, and the number of reports is lower than that of diagnoses. Methods: We developed explainable predictive models for classifying IDs and ADHDs based on written reports to address these issues. The reports of 1,475 patients with IDs and ADHDs who underwent intelligence tests were used for the models. These models were developed by analyzing reports using natural language processing (NLP) and incorporating the physician’s diagnosis for each report. We selected n-gram features from the models’ results by extracting important features using SHapley Additive exPlanations and permutation importance to make the models explainable. Developing the n-gram feature-based original text search system compensated for the lack of human readability caused by NLP and enabled the reconstruction of human-readable texts from the selected n-gram features. Results: The maximum model accuracy was 0.92, and the 80 human-readable texts were restored from four models. Conclusion The results showed that the models could accurately classify IDs and ADHDs, even with a few reports. The models were also able to explain their predictions. The explainability-enhanced model can help physicians understand the classification process of IDs and ADHDs and provide evidence-based insights.

Background: Psychological test reports are essential in assessing intellectual functioning, aiding in diagnosing and treating intellectual disability (ID) and attention-deficit/ hyperactivity disorder (ADHD). However, these reports can have several problems because they are diverse, unstructured, subjective, and involve human errors. Additionally, physicians often do not read the entire report, and the number of reports is lower than that of diagnoses. Methods: We developed explainable predictive models for classifying IDs and ADHDs based on written reports to address these issues. The reports of 1,475 patients with IDs and ADHDs who underwent intelligence tests were used for the models. These models were developed by analyzing reports using natural language processing (NLP) and incorporating the physician’s diagnosis for each report. We selected n-gram features from the models’ results by extracting important features using SHapley Additive exPlanations and permutation importance to make the models explainable. Developing the n-gram feature-based original text search system compensated for the lack of human readability caused by NLP and enabled the reconstruction of human-readable texts from the selected n-gram features. Results: The maximum model accuracy was 0.92, and the 80 human-readable texts were restored from four models. Conclusion The results showed that the models could accurately classify IDs and ADHDs, even with a few reports. The models were also able to explain their predictions. The explainability-enhanced model can help physicians understand the classification process of IDs and ADHDs and provide evidence-based insights.

Low-intensity pulsed ultrasound (LIPUS) is a non-invasive sonodynamic therapy that has been approved by the U.S. Food and Drug Administration for clinical use. Clinical trials have demonstrated that LIPUS ameliorates mild-to-moderate erectile dysfunction without adverse events. Histological analysis of the corpus cavernosum suggests that the therapeutic benefits of LIPUS may be attributed to alleviation of fibrosis, enhanced neovascularization, and promotion of innervation. Further investigations have revealed that LIPUS facilitates cavernous tissue repair through non-thermal mechanisms, including a cavitation effect, acoustic streaming, mass transfer enhancement, and direct mechanical stimulation. Mechanobiological transduction triggers molecular signaling cascades within endogenous cavernous cells, thereby stimulating cell proliferation, angiogenesis, extracellular matrix remodeling, and stem cell differentiation. Although LIPUS has the potential to induce cavernous rehabilitation in the treatment of erectile dysfunction, further investigations are necessary to elucidate the mechanisms via which LIPUS regulates each type of cavernous cell to determine the optimal parameters for this innovative therapy.
Male ; Humans ; Erectile Dysfunction/therapy* ; Ultrasonic Therapy/methods* ; Penis/pathology* ; Ultrasonic Waves

Patients with Noonan syndrome (NS) are born with normal or slightly lower body length and weight compared to the normal ranges. However, their height gradually falls behind that of the general population, leading to growth retardation and delayed puberty. In China, the incidence of short stature in patients with NS is approximately 65%. Short stature in these patients arises from multiple causes, including feeding difficulties in infancy, comorbidities such as congenital heart disease, genetic heterogeneity, and disorders of the growth hormone/insulin-like growth factor-1 axis. Growth hormone is commonly used to alleviate symptoms of short stature. This article reviews the growth and development patterns at different stages of NS, analyzes the causes of short stature, and summarizes the latest advances in treatment to provide new insights for the diagnosis and management of short stature in patients with NS.
Noonan Syndrome/complications* ; Humans ; Body Height ; Growth Disorders/therapy*

OBJECTIVES: To assess the preliminary efficacy and safety of a dose-intensified C5VD regimen (cisplatin, 5-fluorouracil, vincristine, and doxorubicin) in children with locally advanced hepatoblastoma. METHODS: This prospective study enrolled 24 children with newly diagnosed, locally advanced hepatoblastoma who received the dose-intensified C5VD regimen at Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, and Shanghai Children's Hospital between January 2020 and December 2023. Clinical characteristics, treatment outcomes, and chemotherapy-related toxicities were analyzed. RESULTS: Of the 24 patients, 13 were male and 11 were female, with a median age at diagnosis of 18.7 months (range: 3.5-79.4 months). All patients achieved complete macroscopic resection of hepatic lesions without liver transplantation. Serum alpha-fetoprotein levels decreased significantly after two chemotherapy cycles. During a median follow-up of 38.4 months (range: 15.8-50.7 months), all patients maintained continuous complete remission, with 3-year event-free survival and overall survival rates of 100%. Across 144 chemotherapy cycles, the incidence rates of grade 3-4 neutropenia, thrombocytopenia, and infections were 97%, 77%, and 71%, respectively; no treatment-related deaths occurred. Notably, 5 patients (21%) developed Brock grade ≥3 hearing loss, of whom 1 required a hearing aid. CONCLUSIONS The dose-intensified C5VD regimen demonstrates significant efficacy with an overall favorable safety profile in the treatment of newly diagnosed, locally advanced pediatric hepatoblastoma. Grade 3-4 myelosuppression and infection are the predominant toxicities. However, high‑dose cisplatin-induced ototoxicity remains a concern, highlighting the need for improved otoprotective strategies.
Humans ; Hepatoblastoma/pathology* ; Male ; Female ; Infant ; Liver Neoplasms/pathology* ; Antineoplastic Combined Chemotherapy Protocols/therapeutic use* ; Child, Preschool ; Prospective Studies ; Doxorubicin/adverse effects* ; Child ; Cisplatin/adverse effects* ; Vincristine/adverse effects* ; Fluorouracil/adverse effects*

OBJECTIVES: To study genotype-phenotype correlations in children with FGFR3 variants and to improve clinical recognition of related disorders. METHODS: Clinical data of 95 patients aged 0-18 years harboring FGFR3 variants, confirmed by whole‑exome sequencing at Shanghai Children's Medical Center from January 2012 to December 2023, were retrospectively reviewed. Detailed phenotypic characterization was performed for 22 patients with achondroplasia (ACH) and 10 with hypochondroplasia (HCH). RESULTS: Among the 95 patients, 52 (55%) had ACH, 24 (25%) had HCH, 9 (9%) had thanatophoric dysplasia, 3 (3%) had syndromic skeletal dysplasia, 2 (2%) had severe achondroplasia with developmental delay and acanthosis nigricans, and 5 (5%) remained unclassified. A previously unreported FGFR3 variant, c.1663G>T, was identified. All 22 ACH patients presented with disproportionate short stature accompanied by limb dysplasia, commonly with macrocephaly, a depressed nasal bridge, bowed legs, and frontal bossing; complications were present in 17 (77%). The 10 HCH patients predominantly exhibited disproportionate short stature with limb dysplasia and depressed nasal bridge. CONCLUSIONS ACH is the most frequent phenotype associated with FGFR3 variants, and missense variants constitute the predominant variant type. The degree of FGFR3 activation appears to correlate with the clinical severity of skeletal dysplasia.
Humans ; Receptor, Fibroblast Growth Factor, Type 3/genetics* ; Child ; Male ; Child, Preschool ; Female ; Infant ; Adolescent ; Dwarfism/genetics* ; Achondroplasia/genetics* ; Lordosis/genetics* ; Infant, Newborn ; Retrospective Studies ; Genetic Association Studies ; Bone and Bones/abnormalities* ; Phenotype ; Limb Deformities, Congenital