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.

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.

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.

Background and aims The mechanism of cholestatic liver injury (CLI) is unclear, and effective therapies are lacking. While peroxisome proliferator-activated receptor alpha (PPARα) agonists show potential hepatoprotective effect and pyroptosis is implicated in hepatocellular damage, how PPARα activation mitigates lithocholic acid (LCA)-induced pyroptosis remains unknown. Methods The hepatoprotective effect of PPARα agonists was evaluated in a mouse model of intrahepatic cholestasis induced by LCA. Liver injury was assessed via serum biochemistry, hematoxylin and eosin and TUNEL staining, and electron microscopy. Pyroptosis pathways were analyzed using real-time quantitative polymerase chain reaction, Western blot, and co-immunoprecipitation. Results Combined morphological, histopathological, and biochemical analyses confirmed that PPARα activation protects against CLI. Compared with LCA treatment alone, PPARα activation significantly attenuated the elevation of serum lactate dehydrogenase (LDH), the increased TUNEL-positive cells, and the formation of hepatocyte membrane pores. Mechanistically, PPARα activation suppressed both NOD-like receptor protein 3 (NLRP3) inflammasome-mediated pyroptosis and apoptosis protease-activating factor-1 (APAF-1)/CASPASE-3/GSDME-mediated pyroptosis. Furthermore, PPARα agonist pretreatment inhibited activation of the nuclear factor-kappa B (NF-κB) and forkhead box O1 (FOXO1) signaling pathways. Conclusions PPARα protects against LCA-induced CLI by inhibiting both NLRP3 inflammasome-mediated pyroptosis associated with NF-κB and APAF-1/CASPASE-3/GSDME-mediated pyroptosis associated with the FOXO1 signaling pathway.

ObjectiveTo investigate the mechanism underlying the effects of three formulas of the method of warming Yang and relieving depression on anxiety- and depression-like behaviors in the mice subjected to a two-hit paradigm of maternal separation （MS） combined with restraint stress （RS）. MethodsNeonatal mice were randomly assigned into the following groups： Blank control， MS alone， model （MS+RS）， warming Yang （WY，5.85 g·kg^-1）， relieving depression （RD，12.03 g·kg^-1）， warming Yang and relieving depression （WYRD，16.71 g·kg^-1）， and fluoxetine groups （2.6 mg·kg^-1）. MS was conducted on postnatal day 5 （PD5）. Weaning and preventive drug administration were carried out on PD21， and restraint stress was applied on PD90. Anxiety- and depression-like behaviors were assessed using the open field test （OFT）， the elevated zero maze test and tail suspension test （TST）. High-performance liquid chromatography with electrochemical detection （HPLC-ECD） was employed to measure the levels of neurotransmitters， including 5-hydroxytryptamine （5-HT） and dopamine （DA）， in the hippocampus. Real-time quantitative polymerase chain reaction （Real-time PCR） was used to detect the mRNA expression levels of 5-HT_1A receptor （5-HT_1AR）， serotonin transporter （SERT）， monoamine oxidase A （MAOA）， glucocorticoid receptor （GR）， adrenocorticotropic hormone （ACTH）， corticotropin-releasing hormone （CRH）， brain-derived neurotrophic factor （BDNF）， and tyrosine kinase receptor B （TrkB）. Immunohistochemistry （IHC） was applied to assess the protein expression levels of 5-HT_1AR， 5-HT_2A receptor （5-HT_2AR）， 5-HT_2C receptor （5-HT_2CR）， GR， and CRH receptor 1 （CRHR1）. The protein expression levels of BDNF and TrkB in the hippocampus were measured using the fully automated protein expression analysis system （Simple Wes）. ResultsIn the behavioral tests， compared with the blank control group， the model group exhibited significant increases in locomotor distance and central area crossings （P<0.05， P<0.01）in OFT， as well as a significant increase in immobility time in the TST （P<0.05）. Compared with the model group， the RD， WYRD， and fluoxetine groups all showed significantly reduced central area crossings （P<0.05， P<0.01）. Regarding neurotransmitter levels， compared with the blank control group， the model group had significantly decreased hippocampal epinephrine （E） and dopamine （DA） content （P<0.05， P<0.01）. Compared with the MS group， the model group showed significant decreases in hippocampal norepinephrine （NE）， E， and 5-HT content （P<0.05， P<0.01）. Compared with the model group， the WY group decreased hippocampal NE， DA， and 5-HT content （P<0.01）， while the RD， WYRD， and fluoxetine groups exhibited significantly increased hippocampal E content （P<0.01）. At the molecular level， compared with the blank control and MS groups， the model group showed significant increases in mRNA levels of 5-HT_1AR， SERT， MAOA， ACTH， and CRH （P<0.01）， and significant decreases in mRNA levels of tryptophan hydroxylase （TPH）， GR， BDNF， and TrkB （P<0.01）. Protein expression of 5-HT_1AR， 5-HT_2AR， and 5-HT_2CR was also significantly elevated （P<0.05， P<0.01） in the model group. Compared with the model group， the RD group showed significant decreases in SERT， MAOA， and CRH mRNA （P<0.05， P<0.01）， significant increases in TPH， BDNF， and TrkB mRNA （P<0.01）， significantly reduced protein expression of 5-HT_1AR， 5-HT_2AR， and 5-HT_2CR （P<0.05）， and significantly increased GR protein expression. The WY group showed a significant increase in ACTH mRNA expression （P<0.01）. The fluoxetine group exhibited significant decreases in MAOA and CRH mRNA （P<0.05， P<0.01）， significant increases in TPH， BDNF， and TrkB mRNA （P<0.01）， significantly reduced 5-HT_2AR protein expression （P<0.01）， and significantly increased GR protein expression（P<0.05）. ConclusionThe method of warming Yang and relieving depression can ameliorate anxiety- and depression-like behaviors in two-hit mice. Its mechanism may be associated with the BDNF/TrkB signaling pathway， as well as the HPA axis and serotonergic system.

Objective: To determine the potential genetic causal relationship between sleep related phenotypes and female pubertal onset using the two sample Mendelian randomization approach. Methods: Genetic instrumental variables for sleep and age at menarche were sourced from FinnGen, IEU Open GWAS and GWAS Catalog three publicly available Genome Wide Association Study databases. Causal effects were estimated using the inverse variance weighted method, supplemented by sensitivity analyses and tests for heterogeneity, pleiotropy, and direction. Results: Genetically predicted sleep duration was positively associated with age at menarche ( β =0.61, 95% CI =0.30-0.91, P <0.01). Conversely, overall sleep problems ( β =-0.13, 95% CI =-0.20 to -0.07 ), two specific types of sleep disorders (sleep apnea: β =-0.10, 95% CI =-0.16 to -0.03; insomnia: β =-0.40, 95% CI = -0.69 to -0.11) were causally associated with earlier age at menarche (all P <0.01). Sensitivity analyses confirmed the robustness of these findings with consistent effect directions and no evidence of significant directional pleiotropy. Conclusions The study reveales a genetic causal relationship between sleep and pubertal onset. Adequate sleep duration appears to have a protective effect. These findings suggest that sleep may have a critical regulatory role in the initiation of pubertal development.

Objective To compare the effects of different doses of budesonide and formoterol fumarate powder for inhalation combined with montelukast sodium tablet in the treatment of cough variant asthma(CVA)and the improvement of airway function and inflammatory factors.Methods Elderly patients with cough variant asthma were randomly divided into group A and group B.Both groups of patients received budesonide and formoterol fumarate powder for inhalation combined with montelukast sodium tablet.Group A was given budesonide and formoterol fumarate powder for inhalation(Ⅱ),2 inhalation per time,twice a day;Group B was given budesonide and formoterol fumarate powder for inhalation,4 inhalation per time,twice a day;budesonide fumatrol inhalation powder mist for continuous treatment for 6 months,and montelukast sodium tablet 10 mg once a day for at least 3 months.The nighttime cough scores of the two groups were compared before treatment and after treatment.The percentage of forced expiratory volume in one second(FEV1)in the predicted value,the maximum mid expiratory flow(MMEF),the fractional exhaled nitric oxide(FeNO),interleukin-5(IL-5)and eosinophils were compared between the two groups.The incidence of adverse drug reactions and the recurrence rate within 1 year were compared between the two groups.Results A total of 45 cases were enrolled in both the group A and the group B.At 9 months after treatment,the nocturnal cough scores of the group A and the group B were(0.93±0.42)and(0.65±0.29)points,respectively;the percentage of FEV1 in the predicted value were(97.75±9.67)％and(100.93±11.06)％,respectively;the MMEF values were(2.81±1.04)and(3.08±1.09)L·s-1,respectively;the FeNO values were(18.94±9.75)and(15.94±7.96)ppb,respectively;the IL-5 levels were(10.88±7.06)and(8.11±5.56)pg·mL-1,respectively.The above indicators in group B showed statistically significant differences compared to group A(all P＜0.05).The total incidence of adverse drug reactions in group A and group B were 8.89％(5 cases/45 cases)and 13.33％(6 cases/45 cases),respectively.The recurrence rates was 15.56％(7 cases/45 cases)and 13.33％(6 cases/45 cases),respectively.There was no statistically significant difference in the above indicators between group B and group A(all P＞0.05).Conclusion For elderly patients with CVA,higher dose of budesonide and formoterol fumarate powder for inhalation combined with montelukast sodium tablet can better improve cough symptoms,reduce the level of airway hyperresponsiveness and inflammatory factors,reduce the recurrence rate,and the patients are well tolerated.

Objective To investigate the distribution and antimicrobial resistance profiles of clinically isolated Haemophilus influenzae and Moraxella catarrhalis in hospitals across China from 2015 to 2021,and provide evidence for rational use of antimicrobial agents.Methods Data of H.influenzae and M.catarrhalis strains isolated from 2015 to 2021 in CHINET program were collected for analysis,and antimicrobial susceptibility testing was performed by disc diffusion method or automated systems according to the uniform protocol of CHINET.The results were interpreted according to the CLSI breakpoints in 2022.Beta-lactamases was detected by using nitrocefin disk.Results From 2015 to 2021,a total of 43 642 strains of Haemophilus species were isolated,accounting for 2.91％of the total clinical isolates and 4.07％of Gram-negative bacteria in CHINET program.Among the 40 437 strains of H.influenzae,66.89％were isolated from children and 33.11％were isolated from adults.More than 90％of the H.influenzae strains were isolated from respiratory tract specimens.The prevalence of β-lactamase was 53.79％in H.influenzae strains.The H.influenzae strains isolated from children showed higher resistance rate than the strains isolated from adults.Overall,779 strains of H.influenzae did not produce β-lactamase but were resistant to ampicillin(BLNAR).Beta-lactamase-producing strains showed significantly higher resistance rates to these antimicrobial agents than the β-lactamase-nonproducing strains.Of the 16 191 M.catarrhalis strains,80.06％were isolated from children and 19.94％isolated from adults.M.catarrhalis strains were mostly susceptible to both amoxicillin-clavulanic acid and cefuroxime,evidenced by resistance rate lower than 2.0％.Conclusions The emergence of antibiotic-resistant H.influenzae due to β-lactamase production poses a challenge for clinical anti-infective treatment.Therefore,it is very important to implement antibiotic resistance surveillance for H.influenzae and guide rational antibiotic use.All local clinical microbiology laboratories should actively improve antibiotic susceptibility testing and strengthen antibiotic resistance surveillance for H.influenzae.

Objective:To explore the influence of artificial intelligence(AI)-assisted compressive sensing(ACS)technique with different acceleration factors on the image quality and scan time of three dimensional time-of-flight magnetic resonance angiography(3D-TOF-MRA)for brain.Methods:Thirty participants who underwent brain magnetic resonance imaging(MRI)at Tongzhou Branch of Beijing Friendship Hospital were recruited.All subjects underwent imaging scans about four different parameters:a non-accelerated technique(control group),ACS technique integrated with acceleration factor of 4.03(ACS4 group),ACS technique integrated with acceleration factor of 5.02(ACS5 group),and ACS technique integrated with acceleration factor of 6.06(ACS6 group).The image clarity,ranking of imaging capabilities of distal branch blood vessels and the ratio of pseudo-stenosis were qualitatively analyzed.The signal-to-noise ratio(SNR),contrast-to-noise ratio(CNR),edge sharpness,and scan time were quantitatively analyzed.Results:There was not difference in vessel clarity among three ACS groups at the proximal and middle intracranial segments.For distal segments of blood vessel,the ACS4 group[3.0(3.0,3.0)]and ACS5 group[3.0(3.0,3.0)]were better than ACS6[2.5(2.0,3.0)](q=29.800,27.500,P<0.05).The imaging capabilities of distal-branch vessel of ACS4 group and ACS5 group were better than ACS6 group.There was no stenosis in the proximal and middle segments of the images of the three ACS group,and there were no stenosis in the images of distal vessels of ACS4 group and ACS5 group.A total of 5 cases were pseudo-stenosis in the distal vessels of ACS6 group.Compared with the control group,the incidence of pseudo-stenosis in the distal vessels of ACS6 group was 16.7%.The SNR and CNR values of quantitative analysis for proximal vessels in ACS6 group were higher than them in ACS4 group(q=27.800,26.200,P<0.05),and there was not significant difference in them among ACS4 group,ACS6 group and ACS5 group(P>0.05).The differences of SNR and CNR values in the middle and distal segments of blood vessels among different groups were not significant(P>0.05).There was not significant difference in the edge sharpness of blood vessels among ACS4 group,ACS5 group,and ACS6 group(P>0.05),while all of them were higher than those of control group,and the differences were significant(q=48.150,53.367,44.883,P<0.001).Compared with control group,the scan-time of ACS4 group was reduced by 55.19%,and that of ACS5 group was reduced by 64.07%,and that of ACS6 group was reduced by 70%.Conclusion:ACS technique can accelerate the imaging speed of brain 3D-TOF-MRA and ensure image quality.It is clinically recommended to set the ACS acceleration factor as 5.02 to undergo brain 3D-TOF-MRA scans.