ObjectiveTreadmill exercise intervention was evaluated for its effects on addictive behavior, learning and memory, and hippocampal neuroinflammation in methamphetamine (MA)-addicted mice, and transcriptomic screening was performed to identify candidate molecules involved in exercise-mediated attenuation of MA-related neuronal injury. MethodsTwo-month-old male C57BL/6 mice were randomly assigned to four groups: control (C), exercise control (CE), methamphetamine (M), and methamphetamine plus exercise (ME). Mice in the M and ME groups received intraperitoneal injections of MA (1 mg/kg) once daily for 7 consecutive days to establish the addiction model, whereas mice in the C and CE groups received equal volumes of saline. Subsequently, mice in the CE and ME groups underwent treadmill exercise at 12 m/min for 60 min/d for 2 weeks. Conditioned place preference (CPP), the Y-maze, and the Morris water maze (MWM) were used to assess addictive behavior, spatial recognition memory, and spatial learning and memory, respectively. Hippocampal neuronal ultrastructure was examined by transmission electron microscopy (TEM), and microglia-related responses were evaluated by immunofluorescence staining for ionized calcium-binding adapter molecule 1 (Iba-1) in the hippocampal CA1 region. Previously generated and publicly available RNA-seq data from brain tissue of the C, M, and ME groups were reanalyzed, with three biological samples per group. Differentially expressed genes (DEGs) were re-screened using the criteria of P<0.05 and fold change>1.5 or <0.67, followed by gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. NLR family CARD domain containing 5 (Nlrc5) was further validated by reverse transcription-quantitative polymerase chain reaction (RT-qPCR), and Western blot was used to determine the protein expression of NLRC5, nuclear factor kappa B (NF‑κB), interleukin-1β (IL-1β), postsynaptic density-95 (PSD-95), and synaptophysin. ResultsTreadmill exercise significantly attenuated MA-induced conditioned place preference and improved learning and memory performance in both the Y-maze and MWM tests. Exercise increased exploration time and distance in the novel arm of the Y-maze, shortened escape latency, and increased the number of platform crossings in the MWM. Average swimming speed during the probe trial did not differ significantly among groups, suggesting that the MWM differences were not attributable to obvious differences in swimming performance. TEM revealed that MA exposure induced mitochondrial swelling, disrupted cristae, reduced organelle abundance, and nuclear envelope abnormalities in hippocampal neurons, whereas these ultrastructural changes were alleviated after exercise. Immunofluorescence staining showed that MA increased Iba-1 fluorescence intensity in the hippocampal CA1 region, while treadmill exercise significantly reduced this change. Transcriptomic analysis identified 160 DEGs associated with MA exposure and 58 DEGs associated with exercise intervention, with 9 overlapping DEGs. KEGG enrichment analysis showed that MA-related DEGs were enriched in the NOD-like receptor signaling pathway. Among the overlapping DEGs, Nlrc5, which was downregulated after MA exposure and restored following exercise intervention, was selected as a candidate gene for further validation. RT-qPCR confirmed that treadmill exercise reversed the MA-induced decrease in Nlrc5 mRNA expression. Western blot analysis further showed that treadmill exercise increased NLRC5, PSD-95, and synaptophysin protein expression while reducing NF-κB and IL-1β expression. ConclusionTwo weeks of treadmill exercise attenuated MA-induced conditioned place preference and ameliorated learning and memory impairment, alleviated hippocampal neuroinflammation and neuronal ultrastructural damage, and restored the expression of synapse-related proteins. Transcriptomic screening combined with molecular validation demonstrated that exercise intervention was accompanied by restoration of NLRC5 expression, reduced NF‑κB and IL-1β expression, and increased PSD-95 and synaptophysin expression. These findings suggest that NLRC5 may represent a candidate molecule involved in exercise-mediated amelioration of MA-related neuronal injury. However, the present results mainly demonstrate coordinated changes in NLRC5 expression, inflammatory indicators, and cognitive outcomes rather than a direct causal relationship, and the specific role of NLRC5 requires further functional validation.

Traditional mass measurement methods are not applicable in microgravity environments,and the main challenge for in-orbit body mass measurement technology based on inertial principles is to address the random errors brought about by the weightless environment.These include additional torques due to shifts in the center of mass,nonlinear accelerations due to non-rigid human bodies,mechanical energy consumption due to organ vibrations,and random vibrations of the measurement device itself.To address the above difficulties,the project proposes a technical scheme based on the principle of linear acceleration,designs and constructs a ground-specific air-floating experimental and simulation platform,studies key data such as motion trajectory,acceleration change,and vibration frequency amplitude during the mass measurement process,and simulates the changes in the center of mass and random vibrations of the human body in a weightless environment.The project has designed an adjustable posture bracket to adapt to changes in the center of mass,enhance body restraint,and greatly reduce shaking;it has also developed an integrated four-bar linkage motion guidance mechanism,high-precision integrated photoelectric distance measurement,and modular motion constant force measurement device to ensure the accurate measurement of acceleration and constant force data.The product has undergone simulation calculations,ground human applicability tests,and in-orbit applicability verification in the space station.Ground test results show that the device achieves a body mass measurement accuracy better than 0.5%,and the dispersion is better than 0.38%;after flight mission verification and evaluation,the in-orbit body mass measurement dispersion is less than 0.4%,which is superior to the SLAMMD,a mass measurement device of the same principle on the International Space Station,and is at the forefront internationally,achieving accurate body mass measurement.

Rodent models play a crucial role in research on human periodontal diseases,providing key evidence for investigation into the pathological mechanisms of periodontal bone defects.Relevant research in the field involves gene expression,inflammatory regulation mechanisms,host-microbial interactions,as well as disease resolution and healing processes.Research methodology in the field falls under 2 categories-periodontal inflammation models and surgical defect models.The former simulates periodontal defects by inducing periodontal diseases,while the latter constructs clinically simulated periodontal defects through surgical removal of periodontal tissue.However,the currently available animal models of periodontitis face challenges in simultaneously capturing the disease complexity,tracking dynamic repair processes,and meeting translational needs.Herein,we reviewed and summarized the methods and characteristics of periodontal disease modeling in recent years.We proposed the establishment of a multimodal assessment framework integrating technologies such as spatial transcriptomics,single-cell sequencing,and in vivo fluorescence imaging,which may serve as a critical pathway for overcoming existing research challenges.

Knee osteoarthritis(KOA)is a chronic degenerative joint disease,which poses a major challenge particularly among the elderly population due to its high incidence and high disability.Imaging examination has been used commonly to diagnose KOA.However,it faces imitations in predicting disease progression due to the lack of prior information and constraints in manpower and time.With the rapid evolution of big data and computational technologies,artificial intelligence(AI)is progressively integrating into various healthcare domains.Therefore,the integration of artificial intelligence(AI)into healthcare holds promise for revolutionizing KOA diagnosis and treatment.AI-assisted diagnostic models have demonstrated the potential to automate diagnosis,classify disease severity,and predict disease progression with improved efficiency and accuracy.In addition,these models provide personalized diagnosis and treatment options,as well as accurate disease progression risk assessment.Despite these promising outcomes,challenges such as high costs associated with data annotation and limitations in model generalization capabilities persist.This paper reviews recent advancements in AI applications and summarizes the potential value of utilizing AI applications for KOA.To further enhance the utilization of AI in KOA management to overcome current limitations,future efforts should focus on standardizing clinical sample databases,optimizing AI algorithms,and enhancing external verification sets.

This study aimed to compare the ameliorative effects of Lycii Fructus and Chrysanthemi Flos at different ratios on retinal damage in mice and to elucidate the underlying mechanisms. A retinal injury model was established by intraperitoneal injection of sodium iodate(NaIO_3) solution. The mice were divided into the following groups: blank group, model group, positive drug(AREDS 2) group, low-and high-dose groups of Lycii Fructus and Chrysanthemi Flos at 1∶1, low-and high-dose groups at 3∶1, and low-and high-dose groups at 1∶3. Administration was carried out 15 days after modeling. The visual acuity of the mice was assessed using the black-and-white box test. The fundus was observed using an optical coherence tomography device, and retinal thickness was measured. HE staining was used to observe the morphology and pathological changes of the retina. The levels of oxidative factors in serum and ocular tissues were measured using assay kits. The levels of inflammatory factors in serum and ocular tissues were detected by enzyme-linked immunosorbent assay(ELISA), and the expression of Nrf2, HO-1, and NF-κB proteins in ocular tissues was analyzed by Western blot. The results showed that after administration of Lycii Fructus and Chrysanthemi Flos at different ratios, the model group showed improved retinal thinning and disordered arrangement of retinal layers, elevated content of SOD and GSH in the serum and ocular tissues, and reduced levels of MDA, TNF-α, IL-1β, and IL-6. Lycii Fructus and Chrysanthemi Flos at 1∶1 and 1∶3 showed better improvement effects. The combination significantly upregulated the expression levels of Nrf2 and HO-1 and downregulated the expression of NF-κB p65. These results indicate that Lycii Fructus and Chrysanthemi Flos at different ratios can improve retinal damage, reduce oxidative stress, and alleviate inflammation in both the body and ocular tissues of mice. The mechanism may be related to the regulation of the Nrf2/HO-1 and NF-κB signaling pathways in ocular tissues. These findings provide a theoretical basis for the clinical application of Lycii Fructus and Chrysanthemi Flos in the treatment of dry age-related macular degeneration.
Animals ; Mice ; Retina/injuries* ; Male ; Lycium/chemistry* ; Drugs, Chinese Herbal/administration & dosage* ; Chrysanthemum/chemistry* ; NF-kappa B/genetics* ; Humans ; Retinal Diseases/metabolism* ; NF-E2-Related Factor 2/metabolism* ; Oxidative Stress/drug effects* ; Flowers/chemistry* ; Heme Oxygenase-1/genetics*

The holistic view is the key in the study of traditional Chinese medicine(TCM). The component structure theory is based on the holistic view to investigate the correlation between material basis and efficiency, which enriches the holistic "component-effect" research of TCM. Gintonin is a newly isolated non-saponin component of ginseng. Compared to ginsenosides, gintonin has many different pharmacological activities, and it provides new knowledge for the holistic research of ginseng. Thus, taking the discovery of gintonin from ginseng as an example, this paper explored the linkage between ginsenosides and gintonin from the perspective of "component-effect" correlations and systematically sorted out the similarities and differences between them in terms of structural characteristics, modes of action, and pharmacological activities. Starting from the collaborative interaction of TCM compounds, the study discussed the application and value of the holistic view in TCM "component-effect" research in the light of the component structure theory to provide new thoughts for the development of modern TCM research.
Panax/chemistry* ; Drugs, Chinese Herbal/pharmacology* ; Medicine, Chinese Traditional ; Humans ; Ginsenosides/pharmacology* ; Animals

Objective:To investigate the clinical characteristics and independent risk factors of severe disease in patients with anti-nuclear matrix protein (NXP) 2 antibody-positive juvenile dermatomyositis (JDM).Methods:A retrospective cohort study was conducted, including 219 anti-NXP2 antibody-positive JDM patients admitted to 23 children′s hospitals across China from July 2011 to July 2023. Patients were classified into severe and non-severe groups based on classification criteria for severe dermatomyositis. Demographic characteristics, clinical manifestations, and laboratory parameters were compared between the 2 groups using independent sample t-test, Mann-Whitney U test, or χ2 test. Univariate and multivariate Logistic regression analyses were performed to identify risk factors for severe disease. The receiver operating characteristic curve was employed to calculate optimal cut-off values. Results:Among the 219 patients, 108 were male and 111 were female, with an age at onset of 6.3 (3.5, 9.4) years. The severe group comprised 69 patients, and the non-severe group 150 patients. The severe group had significantly higher rates of fever, heliotrope rash, subcutaneous edema, periorbital edema, anti-Ro52 antibody positivity, as well as elevated levels of ferritin-to-albumin ratio (FAR), creatine kinase (CK), aspartate aminotransferase (AST), and lactate dehydrogenase (LDH) (all P<0.05). Multivariate analysis identified anti-Ro52 antibody positivity ( OR=13.26, 95% CI 1.37-128.29) and elevated FAR ( OR=1.90, 95% CI 1.09-2.31) as independent risk factors for severe anti-NXP2 antibody-positive JDM (both P<0.05). Receiver operating characteristic curve analysis revealed that a FAR cutoff value of 6.82 predicted severe disease with an area under the curve of 0.87 (95% CI 0.81-0.94, P<0.001), sensitivity of 0.85, and specificity of 0.70. All patients received glucocorticoid therapy, and the severe group received higher proportions of steroid pulse therapy, cyclophosphamide, mycophenolate mofetil, intravenous immunoglobulin, biologics, and adjuvant treatments compared to the non-severe group (all P<0.05). In terms of outcomes, 2 patients (2.9%) in the severe group died (due to neurological involvement and intestinal perforation, respectively), while the remaining patients achieved complete clinical response or remission. All patients in the non-severe group achieved remission. Conclusions:The primary clinical features of anti-NXP2 antibody-positive JDM included fever, heliotrope rash, subcutaneous edema, periorbital edema, anti-Ro52 antibody positivity, and elevated levels of CK, AST, LDH, and FAR. Furthermore, anti-Ro52 antibody positivity and a FAR>6.82 were identified as independent risk factors.

Microplastics are widely present in various environments such as water bodies,land,and atmosphere,which pose threats to the ecological environment and human health through transmission and accumulation in the food chain.The existing detection techniques for microplastics face challenges such as complex preparation procedure of samples,low efficiency in processing large batches of samples,and difficulties in handling complex samples.Therefore,there is an urgent need for rapid and efficient detection techniques suitable for complex microplastics samples in the field of environmental monitoring.Raman spectroscopy,known for its advantages such as rapidity,accuracy,high sensitivity,non-destructiveness,and non-contact,demonstrates great application potential in detection of microplastics.Deep learning,an artificial intelligence method known for its large-scale data processing,nonlinear modeling and automatic feature extraction capabilities,is receiving increasing attention in the analysis of Raman spectroscopy signals.The application of deep learning-based Raman spectroscopy has significantly improved performance indicators such as detection efficiency and accuracy.This article introduced the existing Raman enhancement techniques,summarized the deep learning methods applied in Raman spectroscopy signal analysis,reviewed the recent research and application progress of deep learning-based Raman spectroscopy in detection of microplastics,and finally discussed the challenges and future prospects of deep learning-based Raman spectroscopy in detection of microplastics.

A pair of positively charged stable isotope labelling agents,4-((2,5-dioxocyclopentyloxy)carbonyl)-N,N,N-trimethylnaphthalen-1-aminium iodide(DPTNA)and its deuterated counterpart d3-DPTNA,were designed and synthesized,which were applied to pre-column labelling of alkylphenols to enhance the sensitivity and accuracy of liquid chromatography-tandem mass spectrometry(LC-MS/MS).By crosslinking covalent organic framework(COF)with hydrophilic sodium alginate and Ca2+in the presence of pore forming agent NH4HCO3 and surfactant P123,abundant of"gas pocket"were created before and during the beads formation process,and high porous COF beads with macroporous and open structure were achieved after removal of gas.Compared with traditional powdered adsorbents,COF beads demonstrated superior operability and recyclability.The proposed method was applied to analysis of alkylphenols in water samples with method LODs of 0.25-0.50 ng/L,while the method LOQs were in the range of 0.80-1.52 ng/L,and recoveries ranged from 92.2%to 98.3%.The proposed method could be well applied to the simultaneous enrichment and analysis of alkylphenols in water samples.