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.

Objective To establish a rapid,sensitive,and specific multiplex PCR detection method for the simultaneous detection of Cryptosporidium,Eimeria,and bovine parvovirus.Methods Specific primers targeting the SSU rRNA genes of Cryptosporidium and Eimeria,as well as the VP2 gene of bovine parvovirus were designed and the corresponding recombinant plasmid standards were constructed.To establish the multiplex PCR method,the reaction conditions were optimized using temperature gradient PCR and single-variable control methods.The sensitivity,specificity,reproducibility,and clinical application of the protocol were evaluated.Results The optimal annealing temperature was found to be 60.5℃,and the forward and reverse primer concentrations were determined to be 0.2 μmol/L for Eimeria,and 0.4 μmol/L for Cryptosporidium and bovine parvovirus.The assay demonstrated high sensitivity,with detection limits of 243,260,and 3 110 copies for the recombinant plasmid standards of Cryptosporidium,Eimeria,and bovine parvovirus,respectively.Specificity testing showed no cross-reactivity with ten common bovine pathogens,including Salmonella,bovine viral diarrhea virus,and bovine rotavirus.Consistent intra-and inter-batch results confirmed the strong reproducibility of the method.Clinical application to 81 diarrhea samples from various regions in the Ganzi Prefecture,Sichuan,revealed positivity rates of 18.52%(15/81)for Cryptosporidium,34.57%(28/81)for Eimeria,and 18.52%(15/81)forbovineparvovirus,withamixedinfectionrateof3.7%(3/81).Conclusions Themultiplex PCR method established in this study offers a reliable tool for differential diagnosis and epidemiological investigation of the three common diarrheal pathogens in yaks.

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.

OBJECTIVE: Cigarette smoking exacerbates the progression of pulmonary tuberculosis (TB). The role of tertiary lymphoid structures (TLS) in chronic lung diseases has gained attention; however, it remains unclear whether smoking-exacerbated lung damage in TB is associated with TLS. This study aimed to analyze the characteristics of pulmonary TLS in smokers with TB and to explore the possible role of TLS in smoking-related lung injury in TB. METHODS: Lung tissues from 36 male patients (18 smokers and 18 non-smokers) who underwent surgical resection for pulmonary TB were included in this study. Pathological and immunohistological analyses were conducted to evaluate the quantity of TLS, and chest computed tomography (CT) was used to assess the severity of lung lesions. The correlation between the TLS quantity and TB lesion severity scores was analyzed. The immune cells and chemokines involved in TLS formation were also evaluated and compared between smokers and non-smokers. RESULTS: Smoker patients with TB had significantly higher TLS than non-smokers ( P < 0.001). The TLS quantity in both the lung parenchyma and peribronchial regions correlated with TB lesion severity on chest CT (parenchyma: r = 0.5767; peribronchial: r = 0.7373; both P < 0.001). Immunohistochemical analysis showed increased B cells, T cells, and C-X-C motif chemokine ligand 13 (CXCL13) expression in smoker patients with TB ( P < 0.001). CONCLUSION Smoker TB patients exhibited increased pulmonary TLS, which was associated with exacerbated lung lesions on chest CT, suggesting that cigarette smoking may exacerbate lung damage by promoting TLS formation.
Humans ; Male ; Tuberculosis, Pulmonary/immunology* ; Middle Aged ; Tertiary Lymphoid Structures/pathology* ; Adult ; Lung/pathology* ; Smoking/adverse effects* ; Smokers ; Aged ; Tomography, X-Ray Computed

Nonunion of osteoporotic vertebral fractures (OVF), predominantly affecting the elderly, can lead to intractable pain, vertebral collapse, progressive kyphotic deformity, and neurological impairment, significantly compromising patients′ quality of life. There exists considerable debate on diagnosis and management of OVF, encompassing key issues such as clinical diagnosis and staging criteria for nonunion, surgical indications and procedure selection, and postoperative rehabilitation planning. Currently, there lacks standardized clinical guideline and expert consensus on the diagnosis and management of OVF nonunion in China. To address this gap, Minimally Invasive Surgery Group of Chinese Orthopedic Association, Osteoporosis Committee of Chinese Association of Orthopedic Surgeons, Prevention and Rehabilitation Committee for Osteoporosis of Chinese Association of Rehabilitation Medicine and Minimally Invasive Orthopedic Surgery Branch of China Association for Geriatric Care jointly organized domestic experts in spinal surgery, endocrinology, and rehabilitation to formulate the Clinical guideline for the diagnosis and treatment for nonunion of osteoporotic vertebral fractures ( version 2025), based on existing literature and clinical experience and adhering to principles of scientific rigor and practicality. The guideline provided 13 evidence-based recommendations encompassing diagnosis and treatment of OVF nonunion, aiming to standardize its clinical management.

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.