BACKGROUND: As an essential part of health services, rehabilitation is of great significance to improve the health and quality of life of the whole population. Accelerating aging calls for a significant expansion of rehabilitation services in China, but rehabilitation needs remain unclear. We conducted the study to explore the rehabilitation needs in China and project the trend of rehabilitation needs from 2020 to 2034. METHODS: The data of health conditions that might potentially benefit from rehabilitation were obtained from Global Burden of Disease (GBD) study. Estimated annual percentage changes (EAPCs) were calculated to quantify the trends of the age-standardized rates. Projections of rehabilitation needs were made until 2034 using Bayesian age-period-cohort analysis (BAPC). RESULTS: Approximately 460 million persons (33.3% of the total population) need rehabilitation in China, contributing to 63 million years lived with disabilities (YLDs) in 2019. The number of prevalent cases that need rehabilitation increased from around 268 (95% uncertainty interval [UI]: 257-282) million in 1990 to almost 460 (95% UI: 443-479) million in 2019, representing an increase of 71.3%. The highest contribution to the need for rehabilitation was musculoskeletal disorders with about 322 (95% UI: 302-343) million persons in seven aggregate disease and injury categories, and hearing loss with over 95 (95% UI: 84-107) million people among 25 health conditions. Based on the projection results, there will be almost 636 million people (45% of the total population) needing rehabilitation services in China by 2034, representing an increase of 38.3%. The rehabilitation needs of neoplasms, cardiovascular diseases, and neurological disorders are expected to increase significantly from 2019 to 2034, with increases of 102.3%, 88.8% and 73.2%, respectively. CONCLUSIONS The need for rehabilitation in China substantially increased over the last 30 years. It is predicted that over two in five people will require rehabilitation by 2034, thus suggesting the need to develop rehabilitation services that meet individuals' rehabilitation needs.
Humans ; China/epidemiology* ; Global Burden of Disease ; Female ; Male ; Musculoskeletal Diseases/epidemiology* ; Rehabilitation/trends* ; Quality of Life ; Middle Aged ; Aged ; Bayes Theorem

Objective Domestic research institutions and researchers have established a wide variety of animal disease models and accumulated a wealth of specialized, distinctive, and targeted atlas data during the model development process. These atlas data are of great value for development and application. Therefore, it is necessary to develop a professional and complete digital atlas database platform for animal models, which can achieve the open sharing of animal model atlas data and the integration and optimization of atlas resources related to disease animal models held by relevant domestic institutions. Methods Based on the B/S architecture, the authors' institution built a digital atlas database of animal models, using Java as the main development language and Oracle database system along with related auxiliary tools. The database platform ran in a Linux environment and could be accessed by users through a web browser. At present, the data on this platform mainly came from the atlas resources submitted by animal model resource units within Guangdong Province. Results In August 2024, a digital atlas database platform for animal models was constructed based on the classification structure of three dimensions: systemic diseases, animal species, and resource units. This platform provided functions such as collection, management, retrieval, and viewing of atlas data. As of January 2025, four resource units had submitted 61 atlas data entries of animal models to the platform, totalling 610 data items. Conclusion The animal model digital atlas database platform has been constructed and put into preliminary use. Although the amount of data on the platform is still limited, it is capable of integrating and openly sharing animal model atlas data. It is believed that with the continuous enrichment of atlas data in the future, this platform is expected to provide important data support for the development of laboratory animal science and comparative medicine research, thereby promoting the efficient utilization of scientific research resources.

Objective Domestic research institutions and researchers have established a wide variety of animal disease models and accumulated a wealth of specialized, distinctive, and targeted atlas data during the model development process. These atlas data are of great value for development and application. Therefore, it is necessary to develop a professional and complete digital atlas database platform for animal models, which can achieve the open sharing of animal model atlas data and the integration and optimization of atlas resources related to disease animal models held by relevant domestic institutions. Methods Based on the B/S architecture, the authors' institution built a digital atlas database of animal models, using Java as the main development language and Oracle database system along with related auxiliary tools. The database platform ran in a Linux environment and could be accessed by users through a web browser. At present, the data on this platform mainly came from the atlas resources submitted by animal model resource units within Guangdong Province. Results In August 2024, a digital atlas database platform for animal models was constructed based on the classification structure of three dimensions: systemic diseases, animal species, and resource units. This platform provided functions such as collection, management, retrieval, and viewing of atlas data. As of January 2025, four resource units had submitted 61 atlas data entries of animal models to the platform, totalling 610 data items. Conclusion The animal model digital atlas database platform has been constructed and put into preliminary use. Although the amount of data on the platform is still limited, it is capable of integrating and openly sharing animal model atlas data. It is believed that with the continuous enrichment of atlas data in the future, this platform is expected to provide important data support for the development of laboratory animal science and comparative medicine research, thereby promoting the efficient utilization of scientific research resources.

Alzheimer's disease (AD) is characterized by cognitive and functional deterioration, with pathological features such as amyloid-beta (Aβ) aggregates in the extracellular spaces of parenchymal neurons and intracellular neurofibrillary tangles formed by the hyperphosphorylation of tau protein. Despite a thorough investigation, current treatments targeting the reduction of Aβ production, promotion of its clearance, and inhibition of tau protein phosphorylation and aggregation have not met clinical expectations, posing a substantial obstacle in the development of drugs for AD. Recently, artificial intelligence (AI), computational biology (CB), and systems biology (SB) have emerged as promising methodologies in AD research. Their capacity to analyze extensive and varied datasets facilitates the identification of intricate patterns, thereby enriching our comprehension of AD pathology. This paper provides a comprehensive examination of the utilization of AI, CB, and SB in the diagnosis of AD, including the use of imaging omics for early detection, drug discovery methods such as lecanemab, and complementary therapies like phototherapy. This review offers novel perspectives and potential avenues for further research in the realm of translational AD studies.

Magnetic stimulation has made significant strides in the treatment of psychiatric disorders. Nonetheless, current magnetic stimulation techniques lack the precision to accurately modulate specific nuclei and cannot realize deep brain magnetic stimulation. To address this, we utilized superparamagnetic iron oxide nanoparticles as mediators to achieve precise targeting and penetration. We investigated the effects of magnetic fields with varying frequencies on neuronal activity and compared the activation effects on neurons using a 10-Hz precise magneto-stimulation system (pMSS) with repetitive transcranial magnetic stimulation in mice. Oxytocin levels, dendritic morphology and density, and mouse behavior were measured before and after pMSS intervention. Our findings suggest that pMSS can activate oxytocinergic neurons, leading to upregulation of oxytocin secretion and neurite outgrowth. As a result, sociability was rapidly improved after a one-week pMSS treatment regimen. These results demonstrate a promising magneto-stimulation method for regulating neuronal activity in deep brain nuclei and provide a promising therapeutic approach for autism spectrum disorder.
Animals ; Autism Spectrum Disorder/physiopathology* ; Paraventricular Hypothalamic Nucleus/physiology* ; Disease Models, Animal ; Transcranial Magnetic Stimulation/methods* ; Male ; Social Behavior ; Mice ; Oxytocin/metabolism* ; Mice, Inbred C57BL ; Neurons/physiology*

Objective To explore the correlation between the nutritional and immunity score (NIS) based on prealbumin and T lymphocyte count and the prognosis of critically ill patients. Methods A retrospective study was conducted involving patients from the intensive care unit of the First Affiliated Hospital of Zhengzhou University from September 2020 to August 2021. Patients’ basic information, Acute Physiology and Chronic Health Evaluation Ⅱ (APACHE Ⅱ) scores within 24 hours of admission, and relevant biochemical indicators were collected. The primary endpoint was all-cause mortality within 28 days. The optimal cut-off values for prealbumin and T lymphocyte count related to mortality risk were determined using X-tile software. Patients were stratified according to these cut-off values and normal reference ranges, and the NIS was calculated. Univariate and multivariate Cox regression analyses were conducted to evaluate the relationship between NIS and mortality. Results The optimal cut-off value for prealbumin was 110 mg/L, and for T lymphocyte count, it was 455/μL, with NIS scores ranging from 0 to 4. After adjusting for confounding factors, patients with NIS scores of 2 (HR＝1.87, 95%CI 1.19-2.94, P＝0.023), 3 (HR＝2.04, 95%CI 1.20-3.19, P＝0.007), and 4 (HR＝1.68, 95%CI 1.24-3.96, P＝0.005) showed a significantly increased risk of mortality. Conclusions NIS≥2 is associated with an increased risk of death in critically ill patients. NIS can serve as an effective tool for early risk stratification and prognostic assessment in critically ill patients.

Objective This study aimed to investigate the protective effect and mechanism of carvacrol hydrogel on the alveolar bone in rats with periodontitis.Methods A thermosensitive hydrogel supported by carvacrol was pre-pared using poloxamer and hydroxypropyl methyl cellulose as matrix.SD rats were randomly divided into blank group,periodontitis group,blank hydrogel group,and low-,medium-,and high-dose hydrogel groups.The periodonti-tis symptoms and the CT structure of the alveolar bone were observed.The changes in liver,spleen,kidney,and peri-odontal tissues were observed.The related indexes of bone metabolism in serum were detected.The expression of os-teoprotegerin(OPG)and nuclear transcription factor-κB(NF-κB)pathway proteins was determined by Western blot.The levels of inflammatory factors were assessed by quantitative reverse transcription polymerase chain reaction(qRT-PCR).Results Carvacrol hydrogel had good slow release,biocompatibility,and cell adhesion.The periodontitis of rats in the carvacrol hydrogel group was significantly alleviated,the expression of OPG protein in gingival tissue was significantly increased(P<0.01),and the levels of receptor activator of NF-κB ligand(RANKL),receptor activator of NF-κB(RANK),NF-κB protein,and inflammatory factors were significantly decreased(P<0.01).Conclusion Car-vacrol hydrogel can regulate the OPG and NF-κB pathways,reduce alveolar bone absorption,and improve periodontal inflammation.

Objective:To unveil the pathological changes associated with demyelination in schizophre-nia(SZ)and its consequential impact on interstitial fluid(ISF)drainage,and to investigate the thera-peutic efficacy of ursolic acid(UA)in treating demyelination and the ensuing abnormalities in ISF drainage in SZ.Methods:Female C57BL/6J mice,aged 6-8 weeks and weighing(20±2)g,were randomly divided into three groups:control,SZ model,and UA treatment.The control group received intraperitoneal injection(ip)of physiological saline and intragastric administration(ig)of 1％carboxy-methylcellulose sodium(CMC-Na).The SZ model group was subjected to ip injection of 2 mg/kg dizo-cilpine maleate(MK-801)and ig administration of 1％CMC-Na.The UA treatment group underwent ig administration of 25 mg/kg UA and ip injection of 2 mg/kg MK-801.The treatment group received UA pretreatment via ig administration for one week,followed by a two-week drug intervention for all the three groups.Behavioral assessments,including the open field test and prepulse inhibition experiment,were conducted post-modeling.Subsequently,changes in the ISF partition drainage were investigated through fluorescent tracer injection into specific brain regions.Immunofluorescence analysis was employed to examine alterations in aquaporin 4(AQP4)polarity distribution in the brain and changes in protein expres-sion.Myelin reflex imaging using Laser Scanning Confocal Microscopy(LSCM)was utilized to study modifications in myelin within the mouse brain.Quantitative data underwent one-way ANOVA,followed by TukeyHSD for post hoc pairwise comparisons between the groups.Results:The open field test re-vealed a significantly longer total distance[(7 949.39±1 140.55)cm vs.(2 831.01±1 212.72)cm,P＜0.001]and increased central area duration[(88.43±22.06)s vs.(56.85±18.58)s,P=0.011]for the SZ model group compared with the controls.The UA treatment group exhibited signifi-cantly reduced total distance[(2 415.80±646.95)cm vs.(7 949.39±1 140.55)cm,P＜0.001]and increased central area duration[(54.78±11.66)s vs.(88.43±22.06)s,P=0.007]compared with the model group.Prepulse inhibition test results demonstrated a markedly lower inhibition rate of the star-tle reflex in the model group relative to the controls(P＜0.001 for both),with the treatment group dis-playing significant improvement(P＜0.001 for both).Myelin sheath analysis indicated significant demy-elination in the model group,while UA treatment reversed this effect.Fluorescence tracing exhibited a significantly larger tracer diffusion area towards the rostral cortex and reflux area towards the caudal thala-mus in the model group relative to the controls[(13.93±3.35)mm2 vs.(2.79±0.94)mm2,P＜0.001 for diffusion area;(2.48±0.38)mm2 vs.(0.05±0.12)mm2,P＜0.001 for reflux area],with sig-nificant impairment of drainage in brain regions.The treatment group demonstrated significantly reduced tracer diffusion and reflux areas[(7.93±2.48)mm2 vs.(13.93±3.35)mm2,P＜0.001 for diffusion area;(0.50±0.30)mm2 vs.(2.48±0.38)mm2,P＜0.001 for reflux area].Immunofluorescence staining revealed disrupted AQP4 polarity distribution and reduced AQP4 protein expression in the model group compared with the controls[(3 663.88±733.77)μm2 vs.(13 354.92±4 054.05)μm2,P＜0.001].The treatment group exhibited restored AQP4 polarity distribution and elevated AQP4 protein expression[(11 104.68±3 200.04)μm2 vs.(3 663.88±733.77)μm2,P＜0.001].Conclusion:UA intervention ameliorates behavioral performance in SZ mice,Thus alleviating hyperactivity and anxiety symptoms and restoring sensorimotor gating function.The underlying mechanism may involve the improve-ment of demyelination and ISF drainage dysregulation in SZ mice.

Objective To observe the drainage pathways of interstitial fluid(ISF)and substance clearance pattern in rat brain with fluorescence tracing imaging and treacer-based MRI.Methods Thirty-three male SD rats were randomly divided into fluorescence tracing group(F group,n=18)and treacer-based MRI group(MRI group,n=15),then further divided into thalamic,hippocampal and caudate nucleus subgroups,respectively.Evans blue was injected to rats in F group,and cardiac perfusion was performed after injection,then brain tissue was harvested,and frozen sections were made to observe the drainage pathways of IFS in different subgroups.MRI was performed on rats in MRI group before and after injection of gadolinium-diethylenetriamine pentaacetic acid(Gd-DTPA)to observe signal intensity in ROI of brain regions in different subgroups,the signal unit ratio was calculated,and the changing trend was explored.Results ISF in thalamus,hippocampus and caudate nucleus had different dominant drainage pathways,and the time of tracer reached to adjacent brain regions and whole brain in F group were different.In MRI group,within 4 h after injection of Gd-DTPA,there were differences in direction and clearance rate among tracer in thalamus,hippocampus and caudate nucleus,mainly manifesting as the tracer in thalamus and hippocampus drained to the ipsilateral cortex and lateral ventricle,while the tracer in the caudate nucleus diffused to the cortex and midbrain,and there were differences of the peak time of tracer signal among adjacent drainage brain regions.Conclusion Fluorescence and MR dual-mode imaging showed that there were differences in the dominant drainage pathways of IFS and clearance rates of small molecule substances among hypothalamus,hippocampus and caudate nucleus of rats.

Objective To explore the value of artificial intelligence federated learning system based on chest X-ray films for pathogen diagnosis of community-acquired pneumonia(CAP)in children.Methods Totally 900 cases of CAP children from 2 hospitals were retrospectively enrolled,including bacterial,viral and mycoplasma CAP(each n=300),and chest posteroanterior X-ray films were collected.Meanwhile,chest posteroanterior X-ray films of 5856 children from the publicly available dataset GWCMCx were collected,including 4273 CAP images and 1583 healthy chest images.All above 6756 images were divided into training set(n=5359)and validation set(n=1397)at the ratio of 8∶2.Then a pathogen diagnosis model of children CAP was established based on attention mechanism.Binary and ternary diagnostic algorithms were designed,and federated deployment training was performed.The efficacy of this system for pathogen diagnosis of children CAP was analyzed and compared with DenseNet model.Results Based on all data,the accuracy of the obtained artificial intelligence federated learning system model for diagnosing children CAP was 97.00%,with the area under the curve(AUC)of 0.990.Based on hospital data,the AUC of this system using single imaging data and clinical-imaging data for pathogen diagnosis of children CAP was 0.858 and 0.836,respectively,both better than that of DenseNet model(0.740,both P＜0.05).Conclusion The artificial intelligence federated learning system based on chest X-ray films could be used for pathogen diagnosis of children CAP.