Objective: To characterize longitudinal trajectories of testicular development in boys and breast development in girls, so as to provide reference data for understanding patterns of pubertal sexual maturation. Methods: Based on the Shanghai Pudong New Area Cohort Study on Growth, Development and Health in Children and Adolescents, a baseline survey was conducted in 2020 using a mult stage cluster random sampling method. A total of 2 184 children who completed all follow ups during the primary school period from 13 elementary schools in Pudong New Area,Shanghai,with annual follow ups during 2021-2025. Testicular volume and Tanner stage of breast development were assessed by professional physicians using standardized visual inspection and palpation. The age distribution of testicular volume and breast development was fitted by using cumulative link mixed models and Turnbull s nonparametric maximum likelihood estimation method. Results: Median ages for testicular volumes of 2, 3, 4 and 5 mL in boys were 7.07, 9.24, 10.29, and 11.57 years old, respectively. Median ages for Tanner breast stages Ⅱ, Ⅲ, Ⅳ, and Ⅴ in girls were 8.55 , 10.17, 11.18, and 13.78 years old, respectively. Based on overweight and obesity, stratified analysis showed that earlier pubertal onset among overweight/obesity children, and the key milestones for pubertal initiation were testicular volume reaching 4 mL in boys and breast Tanner II in girls for 10.29, 10.83; 8.18, 9.00 years. Conclusion Overweight and obesity are associated with earlier pubertal initiation,but there are certain gender and developmental stage specific patterns.

ObjectiveTo investigate the present situation of input, output, outcome and impact of all registered community-based rehabilitation stations in Inner Mongolia in China, and analyze how the input predict the output, outcome and impact. MethodsFrom March 1st to April 30th, 2025, a questionnaire survey was conducted on all registered community-based rehabilitation stations in Inner Mongolia, covering four dimensions: input, output, outcome and impact. A total of 1 365 questionnaires were distributed. The input included four items: laws and policies, human resources, equipment and facilities, and rehabilitation information management. The output included two items: technical paths and benefits/effectiveness. The outcome included three items: coverage rates, rehabilitation interventions and functional results. The impact included two items: health and sustainability. Each item contained several questions, all of which were described in a positive way. Each question was scored from one to five. A lower score indicated that the situation of the community-based rehabilitation station was more in line with the content described in the question. Regression analysis was performed using the total score of each item of input dimension as independent variables, and the total scores of the output, outcome and impact dimensions as dependent variables. ResultsA total of 1 262 valid questionnaires were collected. The mean values of input, output, outcome and impact of community-based rehabilitation stations were 1.827 to 1.904, with coefficient of variation of 45.892% to 49.239%. The regression analysis showed that, rehabilitation information management, human resources, and laws and policies significantly predicted the output dimension (R² = 0.910, P < 0.001). Meanwhile, all four items in the input dimension predicted both the outcome (R² = 0.850, P < 0.001) and impact dimensions (R² = 0.833, P < 0.001). ConclusionInput, output, outcome and impact of the community-based rehabilitation stations in Inner Mongolia were generally in line with the content of the questions, although some imbalances were observed. Additionally, the input of community-based rehabilitation stations could significantly predict their output, outcome and impact.

ObjectiveDiscriminating atypical hepatocellular carcinoma (HCC) from other malignancies in liver nodules classified as Liver Imaging Reporting and Data System category M (LR-M) remains a significant diagnostic challenge on conventional ultrasound examination. The LR-M category, originally intended to capture non-HCC malignancies, paradoxically contains up to 63% of atypical HCCs that deviate from classic enhancement patterns, leading to potential misdiagnosis and suboptimal treatment planning. While deep learning has shown promise in HCC diagnosis, most existing models rely exclusively on single-modality ultrasound, overlooking the diagnostic benefits of integrating complementary information from multiple imaging sources. To address this gap, we propose a novel attention-weighted tri-modal ultrasound network (TUS-Net) that integrates contrast-enhanced ultrasound (CEUS), B-mode ultrasound (BUS), and time-intensity curves (TICs) to improve diagnostic accuracy for these clinically challenging lesions. MethodsOur framework incorporates a three-dimensional convolutional neural network (C3D) backbone to extract spatiotemporal features from CEUS videos, capturing dynamic vascular patterns critical for lesion characterization. To effectively fuse complementary modalities, we introduce a dual-channel feature fusion module (DCFFM) that adaptively combines features from CEUS and BUS through channel-wise attention mechanisms, allowing the model to dynamically weigh the contribution of each modality based on diagnostic relevance. Additionally, we propose a temporal intensity feature fusion module (TIFFM) that leverages quantitative hemodynamic information from TICs to guide the model’s attention toward diagnostically critical temporal phases, such as arterial wash-in and portal venous washout. The model is further enhanced by automated lesion localization using YOLOX and class activation mapping for interpretability, ensuring that predictions align with clinically meaningful imaging features. ResultsEvaluated on a tri-modal ultrasound dataset comprising 161 patients with pathologically confirmed LR-M nodules (131 atypical HCC and 30 non-HCC malignancies), our model achieved an accuracy of 86.83%, a sensitivity of 92.50%, a specificity of 75.50%, and an AUC of 89.32% in screening atypical HCC. Compared to single-modality baselines, TUS-Net demonstrated superior specificity, a clinically critical metric given the higher risk associated with misclassifying non-HCC malignancies. Ablation studies confirmed the contribution of each module, with the full model outperforming both standard C3D and 3D ResNet backbones integrated with attention mechanisms. A reader study involving junior and senior radiologists further validated the clinical utility of AI assistance, showing consistent improvements in specificity and inter-reader consistency, particularly for less experienced clinicians. ConclusionThese results surpass existing benchmark models and demonstrate the potential of our approach to enhance diagnostic precision in clinically specific cases. By intelligently fusing multi-modal ultrasound data with attention-guided mechanisms, TUS-Net offers a reliable and interpretable tool that holds promise for improving the non-invasive diagnosis of atypical HCC in challenging LR-M liver nodules.

ObjectiveDiscriminating atypical hepatocellular carcinoma (HCC) from other malignancies in liver nodules classified as Liver Imaging Reporting and Data System category M (LR-M) remains a significant diagnostic challenge on conventional ultrasound examination. The LR-M category, originally intended to capture non-HCC malignancies, paradoxically contains up to 63% of atypical HCCs that deviate from classic enhancement patterns, leading to potential misdiagnosis and suboptimal treatment planning. While deep learning has shown promise in HCC diagnosis, most existing models rely exclusively on single-modality ultrasound, overlooking the diagnostic benefits of integrating complementary information from multiple imaging sources. To address this gap, we propose a novel attention-weighted tri-modal ultrasound network (TUS-Net) that integrates contrast-enhanced ultrasound (CEUS), B-mode ultrasound (BUS), and time-intensity curves (TICs) to improve diagnostic accuracy for these clinically challenging lesions. MethodsOur framework incorporates a three-dimensional convolutional neural network (C3D) backbone to extract spatiotemporal features from CEUS videos, capturing dynamic vascular patterns critical for lesion characterization. To effectively fuse complementary modalities, we introduce a dual-channel feature fusion module (DCFFM) that adaptively combines features from CEUS and BUS through channel-wise attention mechanisms, allowing the model to dynamically weigh the contribution of each modality based on diagnostic relevance. Additionally, we propose a temporal intensity feature fusion module (TIFFM) that leverages quantitative hemodynamic information from TICs to guide the model’s attention toward diagnostically critical temporal phases, such as arterial wash-in and portal venous washout. The model is further enhanced by automated lesion localization using YOLOX and class activation mapping for interpretability, ensuring that predictions align with clinically meaningful imaging features. ResultsEvaluated on a tri-modal ultrasound dataset comprising 161 patients with pathologically confirmed LR-M nodules (131 atypical HCC and 30 non-HCC malignancies), our model achieved an accuracy of 86.83%, a sensitivity of 92.50%, a specificity of 75.50%, and an AUC of 89.32% in screening atypical HCC. Compared to single-modality baselines, TUS-Net demonstrated superior specificity, a clinically critical metric given the higher risk associated with misclassifying non-HCC malignancies. Ablation studies confirmed the contribution of each module, with the full model outperforming both standard C3D and 3D ResNet backbones integrated with attention mechanisms. A reader study involving junior and senior radiologists further validated the clinical utility of AI assistance, showing consistent improvements in specificity and inter-reader consistency, particularly for less experienced clinicians. ConclusionThese results surpass existing benchmark models and demonstrate the potential of our approach to enhance diagnostic precision in clinically specific cases. By intelligently fusing multi-modal ultrasound data with attention-guided mechanisms, TUS-Net offers a reliable and interpretable tool that holds promise for improving the non-invasive diagnosis of atypical HCC in challenging LR-M liver nodules.

The auxin/indole-3-acetic acid (Aux/IAA) gene family is an important regulator for plant growth hormone signaling, involved in plant growth, development, as well as response to environmental stresses. In the present study, we identified SmIAA7 which is potentially associated with Salvia miltiorrhiza leaf development through comparatively analyzed the transcriptome data from different pinnate leaves. SmIAA7 was successfully isolated from S. miltiorrhiza using the specific primers. Then subsequent bioinformatic analysis, prokaryotic expression and purification, subcellular localization, and induction expression analysis under auxin and abiotic stress were performed. The full-length of SmIAA7 contained an ORF of 684 bp encoding a protein of 227 amino acid with a molecular weight of 25.3 kD. Conserved domain analysis showed that SmIAA7 contains the conserved Aux_IAA domain (pfam02309). Sequence analysis and phylogenetic tree analysis results indicated SmIAA7 was phylogenetically close to IAA7 and IAA14 from other plants, suggesting SmIAA7 involved in plant growth and development as well as response to environmental stresses. The prokaryotic expression vector pET28a-SmIAA7 was constructed and SmIAA7 recombinant protein was successfully expressed in E. coli Rosetta (DE3) strain. Subcellular localization experiment demonstrated that SmIAA7 localized in the nucleus of plant cells. Real-time fluorescence quantitative PCR results showed that the expression level of SmIAA7 was upregulated in response to auxin. Drought, low temperature, and salt stress significantly increased the transcript level of SmIAA7 gene. This study lays a foundation for further elucidating the role of SmIAA7 in leaf development, signal transduction, and stress defense in S. miltiorrhiza.

Objective: To analyze respiratory syncytial virus(RSV) outbreaks surveillance results and the epidemiological characteristics in kindergarten and school in Shenzhen during 2017-2023 , so as to provide a scientific reference for control and prevention of RSV. Methods: Epidemiological data and surveillance results of RSV outbreaks in kindergarten and school from 2017 to 2023 were collected for descriptive analyses. Results: A total of 31 RSV outbreaks were identified in kindergarten and school in 2017-2023 in Shenzhen, 346 cases were reported, the average incidence rate was 22.02%. The most annual RSV outbreaks were reported in 2020 with 14 outbreaks, followed by 8 outbreaks in 2023. A total of 64.52% of RSV outbreaks were identified in kindergarten with rest occurring in primary school or middle school. The greatest monthly count of outbreak was 18 (58.06%) in September, followed by 3 outbreaks (9.68%) in March and October. A total of 244 swab samples were collected, 169 samples were positive for respiratory viruses, the positive rate was 69.26%, 121 samples were positive for RSV,from 31 respiratory syncytical virus outbreaks 57 and samples were positive for other respiratory viruses(9 samples were positive for two respiratory viruses). A toral of 14(45.16%) outbreaks are caused by RSV alone, 17 outbreaks (54.84%) were caused by RSV and other respiratory viruses. Conclusions Most RSV outbreaks in kindergarten and school are reported after 2020 in Shenzhen, most RSV outbreaks occur in kindergarten, peak seasons of RSV outbreaks are autumn and spring.

Acute lung injury （ALI） is one of the most common and critical diseases in clinical practice， with extremely high morbidity and mortality， seriously threatening human life and health. The pathogenesis of ALI is complex， in which the inflammatory response is a key factor. Studies have shown that NOD-like receptor protein 3 （NLRP3） inflammasomes are involved in ALI through mechanisms such as inflammation induction， increased microvascular permeability， recruitment of neutrophils， oxidative stress， and pyroptosis， playing a key role in the occurrence and progression of ALI. Therefore， regulating NLRP3 inflammasomes and inhibiting the release of inflammatory factors can alleviate the damage in ALI. At present， ALI is mainly treated by mechanical ventilation and oxygen therapy， which have problems such as high costs and poor prognosis. In recent years， studies have shown that traditional Chinese medicine （TCM） can reduce the inflammatory response and the occurrence of oxidative stress and pyroptosis by regulating the NLRP3 inflammasome， thus alleviating the damage and decreasing the mortality of ALI. Based on the relevant literature in recent years， this article reviews the research progress in TCM treatment of ALI by regulating NLRP3 inflammasomes， discusses how NLRP3 inflammasomes participate in ALI， and summarizes the active ingredients， extracts， and compound prescriptions of TCM that regulate NLRP3 inflammasomes， aiming to provide new ideas for the clinical treatment of ALI and the development of relevant drugs.

Liquiritigenin(LG)is a flavone of pharmacological importance,however,its application potential is severely limited due to its poor water solubility.LG could be disassociated slightly in water to form phenolate anion,therefore,better solubilization effect is expected by inclusion with cationic cyclodextrins(CCDs).In this work,four kinds of CCDs modified with amino groups at the primary face were synthesized,and their solid inclusion complexes with LG were successfully prepared by preparing their saturated solutions.The formation of the solid inclusion complexes was confirmed by scanning electron microscopy(SEM)and powder X-ray diffraction(PXRD),and their supramolecular binding behavior in solution was studied using multiple techniques.A 1∶1 inclusion stoichiometry of inclusion complexation was defined using Job plot by ultraviolet-visible(UV-vis)spectroscopy,and their binding stability constants(Ks)were determined as 2862.77,3494.70,6521.85 and 9599.48 L/mol using UV-vis spectroscopic titration,far more superior to that of nativeβ-CD(Ks=236.79 L/mol).This indicated that the amino side chains on CCDs could actively participate in the inclusion complexation through anion-cation interactions,significantly strengthening the host-guest binding between CCDs and LG.The inclusion modes were further elucidated based on proton and two-dimensional rotating-frame overhauser enhancement spectroscopy(2D-ROESY)nuclear magnetic resonance(NMR)experiments and molecular docking.Water solubility of LG was dramatically promoted up to 4.9 mg/mL,which was 70-fold higher than that of native LG.This study could draw inspiration for the binding and solubilization of phenols such as flavones by design of cationic macrocyclic molecules.

Objective To investigate the predictive value of serum lactate dehydrogenase(LDH)level com-bined with high-throughput sequencing in children with severe Mycoplasma pneumoniae pneumonia(SMPP).Methods The clinical data of 99 children with Mycoplasma pneumoniae pneumonia(MPP)admitted to Hua-zhong University of Science and Technology Union Hospital from October 2023 to March 2024 were retro-spectively analyzed.According to the severity of the disease,the children were divided into mild group(33 ca-ses)and severe group(66 cases).Spearman correlation analysis was used for correlation analysis,Logistic re-gression was used to analyze the influencing factors of SMPP,and the receiver operating characteristic(ROC)curve was used to evaluate the value of LDH in predicting SMPP.Results The level of LDH in the severe group was higher than that in the mild group(P<0.05).The results of high-throughput sequencing showed that the proportions of virulence positive and drug resistance gene A2063G mutation in the severe group were higher than those in the mild group(P<0.05).Multivariate Logistic regression analysis showed that LDH level and drug resistance gene A2063G mutation were related to the SMPP(P<0.05).ROC curve analysis showed that LDH combined with high-throughput sequencing detection of drug resistance gene A2063G muta-tion had a high value in predicting SMPP,and the area under the curve was 0.724.Conclusion Serum LDH combined with high-throughput sequencing detection of drug resistance gene A2063G mutation can be used as an effective indicator to predict SMPP.

Objective:To explore the predictive value of neutrophil-to-lymphocyte ratio (NLR) and tumor necrosis factor -α (TNF-α) level on the therapeutic effect of transcatheter arterial chemoembolization (TACE) combined with microwave ablation in patients with massive liver cancer.Methods:The medical records of 106 patients with massive liver cancer who underwent TACE combined with microwave ablation treatment in the Affiliated Hospital of Weifang Medical University from February 2020 to February 2023 were retrospectively analyzed. The efficacy was evaluated 6 weeks after surgery, and the patients were divided into remission group and non-remission group according to the therapeutic effect. The levels of NLR and TNF-α in the two groups were detected before surgery, 3 days after surgery and 7 days after surgery. Point two column correlation was used to analyze the relationship between the levels of NLR and TNF-α in different time periods and the therapeutic effect of TACE combined with microwave ablation in patients with massive liver cancer. The receiver operator characteristic (ROC) curve was drawn to analyze the predictive value of NLR and TNF-α levels in different time periods for the therapeutic effect of TACE combined with microwave ablation in patients with massive liver cancer.Results:Six weeks after surgery, out of 106 patients with massive liver cancer, 13 achieved complete remission, 48 achieved partial remission, 20 experienced disease progression, and 25 remained stable. The overall remission rate was 57.55% (61/106). Before surgery, the levels of NLR [ (2.26±0.13) vs. (2.43±0.12), t=6.87, P<0.001] and TNF-α [ (36.20±4.38) pg/ml vs. (42.74±5.74) pg/ml, t=6.66, P<0.001] in the remission group ( n=61) were lower than those in the non-remission group ( n=45), with statistically significant differences. At 3 days after surgery, there were no statistically significant difference in the levels of NLR [ (6.16±3.22) vs. (6.22±3.30), t=0.09, P=0.925] or TNF-α [ (48.84±7.22) pg/ml vs. (49.13±7.34) pg/ml, t=0.20, P=0.840] between the remission group and the non-remission group. At 7 days after surgery, the levels of NLR [ (2.60±0.18) vs. (2.82±0.26), t=5.15, P<0.001] and TNF-α [ (38.20±6.30) pg/ml vs. (45.57±5.79) pg/ml, t=6.16, P<0.001] in the remission group were lower than those in the non-remission group, with statistically significant differences. There were statistically significant differences in NLR and TNF-α levels before surgery, 3 days and 7 days after surgery between the remission group and the non-remission group ( F=82.43, P<0.001; F=54.45, P<0.001; F=76.23, P<0.001; F=15.61, P<0.001). Further pair-to-pair comparison showed that the levels of NLR and TNF-α were higher in both groups 3 and 7 days after surgery than before surgery, but the levels of NLR and TNF-α were lower in both groups 7 days after surgery than 3 days after surgery, with statistically significant differences (all P<0.005). Point two column correlation analysis showed that NLR level, TNF-α level and the efficacy of TACE combined with microwave ablation in patients with massive liver cancer were significantly positively correlated before and 7 days after surgery ( r=0.42, P<0.001; r=0.49, P<0.001; r=0.43, P<0.001; r=0.46, P<0.001). ROC curve showed that the area under the curve (AUC) of NLR and TNF-α alone in predicting the efficacy of TACE combined with microwave ablation in patients with massive liver cancer before and 7 days after surgery was 0.750 (95% CI: 0.656-0.844), 0.788 (95% CI: 0.699-0.877), 0.751 (95% CI: 0.652-0.850), 0.788 (95% CI: 0.700-0.876), respectively. The AUC of combined prediction of NLR and TNF-α before and 7 days after surgery were 0.818 (95% CI: 0.736-0.900) and 0.813 (95% CI: 0.730-0.897), respectively. There were no statistically significant differences in the AUC values of NLR and TNF-α alone or in combination for predicting the therapeutic effect of TACE combined with microwave ablation in patients with massive liver cancer before and 7 days after surgery (all P>0.05) . Conclusions:The levels of NLR and TNF-α before and 7 days after surgery are related to the effect of TACE combined with microwave ablation in patients with massive liver cancer, and the combination of NLR and TNF-α levels before and 7 days after surgery has certain value in predicting the effect of TACE combined with microwave ablation in patients with massive liver cancer.