Brain’s neural activities encompass both periodic rhythmic oscillations and aperiodic neural fluctuations. Rhythmic oscillations manifest as spectral peaks of neural signals, directly reflecting the synchronized activities of neural populations and closely tied to cognitive and behavioral states. In contrast, aperiodic fluctuations exhibit a power-law decaying spectral trend, revealing the multiscale dynamics of brain neural activity. In recent years, researchers have made notable progress in studying brain aperiodic dynamics. These studies demonstrate that aperiodic activity holds significant physiological relevance, correlating with various physiological states such as external stimuli, drug induction, sleep states, and aging. Aperiodic activity serves as a reflection of the brain’s sensory capacity, consciousness level, and cognitive ability. In clinical research, the aperiodic exponent has emerged as a significant potential biomarker, capable of reflecting the progression and trends of brain diseases while being intricately intertwined with the excitation-inhibition balance of neural system. The physiological mechanisms underlying aperiodic dynamics span multiple neural scales, with activities at the levels of individual neurons, neuronal ensembles, and neural networks collectively influencing the frequency, oscillatory patterns, and spatiotemporal characteristics of aperiodic signals. Aperiodic dynamics currently boasts broad application prospects. It not only provides a novel perspective for investigating brain neural dynamics but also holds immense potential as a neural marker in neuromodulation or brain-computer interface technologies. This paper summarizes methods for extracting characteristic parameters of aperiodic activity, analyzes its physiological relevance and potential as a biomarker in brain diseases, summarizes its physiological mechanisms, and based on these findings, elaborates on the research prospects of aperiodic dynamics.

Alzheimer’s disease (AD) is a central neurodegenerative disease characterized by progressive cognitive decline and memory impairment in clinical. Currently, there are no effective treatments for AD. In recent years, a variety of therapeutic approaches from different perspectives have been explored to treat AD. Although the drug therapies targeted at the clearance of amyloid β-protein (Aβ) had made a breakthrough in clinical trials, there were associated with adverse events. Neuroinflammation plays a crucial role in the onset and progression of AD. Continuous neuroinflammatory was considered to be the third major pathological feature of AD, which could promote the formation of extracellular amyloid plaques and intracellular neurofibrillary tangles. At the same time, these toxic substances could accelerate the development of neuroinflammation, form a vicious cycle, and exacerbate disease progression. Reducing neuroinflammation could break the feedback loop pattern between neuroinflammation, Aβ plaque deposition and Tau tangles, which might be an effective therapeutic strategy for treating AD. Traditional Chinese herbs such as Polygonum multiflorum and Curcuma were utilized in the treatment of AD due to their ability to mitigate neuroinflammation. Non-steroidal anti-inflammatory drugs such as ibuprofen and indomethacin had been shown to reduce the level of inflammasomes in the body, and taking these drugs was associated with a low incidence of AD. Biosynthetic nanomaterials loaded with oxytocin were demonstrated to have the capability to anti-inflammatory and penetrate the blood-brain barrier effectively, and they played an anti-inflammatory role via sustained-releasing oxytocin in the brain. Transplantation of mesenchymal stem cells could reduce neuroinflammation and inhibit the activation of microglia. The secretion of mesenchymal stem cells could not only improve neuroinflammation, but also exert a multi-target comprehensive therapeutic effect, making it potentially more suitable for the treatment of AD. Enhancing the level of TREM2 in microglial cells using gene editing technologies, or application of TREM2 antibodies such as Ab-T1, hT2AB could improve microglial cell function and reduce the level of neuroinflammation, which might be a potential treatment for AD. Probiotic therapy, fecal flora transplantation, antibiotic therapy, and dietary intervention could reshape the composition of the gut microbiota and alleviate neuroinflammation through the gut-brain axis. However, the drugs of sodium oligomannose remain controversial. Both exercise intervention and electromagnetic intervention had the potential to attenuate neuroinflammation, thereby delaying AD process. This article focuses on the role of drug therapy, gene therapy, stem cell therapy, gut microbiota therapy, exercise intervention, and brain stimulation in improving neuroinflammation in recent years, aiming to provide a novel insight for the treatment of AD by intervening neuroinflammation in the future.

Objective:To investigate the role and mechanism of negative pressure wound therapy (NPWT) in a rabbit full-thickness wound model using non-targeted metabolomics.Methods:Eighteen male New Zealand rabbits (11-12 weeks old) were used. Two symmetrical circular full-thickness skin defects were created on the back of each rabbit. The animals were randomly divided into three groups: Control group (no treatment), Saline group (debridement with saline irrigation), and NPWT+ Saline group (saline debridement followed by 2 h of NPWT at -125 mm Hg once daily for two weeks). Wound healing was documented on days 0, 3, 7, 10, and 14. The wound healing rate was calculated as (original area-unhealed area)/original area × 100%. Histopathological changes were evaluated via hematoxylin and eosin (HE) staining. Metabolomic profiling of wound tissues was performed using ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS). Differential metabolites were identified, and pathway enrichment analysis was conducted. Oxidative stress markers, including superoxide dismutase (SOD) and catalase (CAT) activities and malondialdehyde (MDA) content, were measured using commercial kits. Data were analyzed using SPSS 20.0. One-way ANOVA with Tukey’s HSD test or Welch’s ANOVA with Games-Howell test was applied as appropriate.Results:On days 3, 10, and 14, the wound healing rate in the NPWT+ Saline group was significantly higher than that in the Control and Saline groups ( P<0.05). On day 7, the NPWT+ Saline group showed a significantly higher healing rate than the Saline group ( P<0.01), but no significant difference compared with the Control group ( P>0.05). HE staining on day 7 revealed enhanced epithelialization, thicker granulation tissue, higher microvessel density, and more abundant, well-organized collagen in the NPWT+ Saline group. By day 14, all groups had formed relatively continuous epithelial structures. Non-targeted metabolomics identified riboflavin and spermidine as differential metabolites. Pathway analysis highlighted riboflavin metabolism and glutathione metabolism as the most significantly enriched pathways. Compared with the Control and Saline groups, the NPWT+ Saline group exhibited significantly increased CAT and SOD activities ( P<0.05) and decreased MDA content ( P<0.01), indicating reduced oxidative stress. Conclusion:NPWT may promote wound healing by elevating riboflavin and spermidine levels, thereby modulating riboflavin and glutathione metabolism and regulating local redox reactions.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Foodborne illnesses caused by Salmonella pose significant threats to worldwide public health safety.In this study,a rapid method for screening viable Salmonella in oyster sauce and milk was developed by utilizing an electronic microbial growth analyzer(EMGA).Target food samples were diluted 10-fold with RVS broth and loaded into test tubes.Test tubes were positioned in the EMGA to determine the bacterial growth curves and the time required to reach the maximum growth rate(Tmgr).Using Salmonella typhimurium(S.typhimurium)asan model species,there was linear relationship between the logarithmic value of viable bacterial concentration(lgC)and Tmgr over the range of 5×101-5×106 CFU/mL,with a detection limit of 10 CFU/mL.For oyster sauce,the regression equation was Tmgr(min)=-80.775lg[C/(CFU/mL)]+754.96(R2=0.9907),and the recovery rates of S.typhimurium ranged from 95.2%to 119.8%,with relative standard deviations(RSD)ranging from 3.5%to 16.3%.For milk,the regression equation was Tmgr(min)=-71.922 lg[C/(CFU/mL)]+618.65(R2=0.9985),with recovery rates ranging from 98.4%to 110.6%and RSD ranging from 6.4%to 12.8%.The EMGA method required only one portable instrument,and involving only three manual steps,i.e.,dilution,transfer,and insertion.When S.typhimurium contamination reached 106 CFU/mL,the total time consumption,from the unwrapping of samples to the readout of bacterial concentration,was no more than 7 h.When applied to detection of actual oyster sauce and milk samples,the new method demonstrated strong consistency with plate counting results in positive detection rates.This method was superior to the plate counting method,which was generally considered as a gold standard,in terms of accuracy,precision,simplicity and efficiency,representing a promising alternative for the on-site screening and quantification of viable Salmonella in oyster sauce and milk products.

Objective:To evaluate the characteristic manifestations of lumbar fusion following oblique lateral interbody fusion (OLIF), determine the specific incidence of these patterns, and the identify factors associated with fusion characteristics.Methods:This retrospective study analyzed 209 patients who underwent OLIF surgery at Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, between July 2017 and September 2023. The cohort had a mean age of 64.2±9.8 years and included 125 males and 84 females. A total of 338 lumbar segments were assessed, comprising 159 segments treated with stand-alone OLIF (OLIF-SA) and 179 segments treated with OLIF combined with posterior pedicle screw fixation (OLIF-PSF). Inclusion criteria were: patients aged 18-80 years who underwent OLIF with complete radiographic records. Surgical parameters, including fixation method, number of fused segments, surgical approach, and cage dimensions (height and width), were obtained from operative records. Radiographic evaluation included preoperative osteophytes, Hounsfield unit (HU) values of endplates, and cage positioning. Fusion rate, fusion pattern (lateral vs. central), cage subsidence, and related influencing factors were assessed. Clinical outcomes were measured via the Oswestry disability index (ODI) and visual analog scale (VAS) preoperatively, immediately postoperatively, and at 1-year follow-up. Results:The overall fusion rate was 98.2% (332/338), with a non-union rate of 1.8% (6/338). The incidence of lateral fusion was 40.2% (136/338). In the OLIF-SA group, lateral and central fusion rates were 50.3% (80/159) and 49.7% (79/159), respectively, with no cases of non-union. In the OLIF-PSF group, lateral fusion occurred in 31.3% (56/179), central fusion in 65.4% (117/179), and non-union in 3.3% (6/179), with statistically significant differences between groups ( P<0.05). Preoperative osteophytes and higher endplate HU values were significantly associated with lateral fusion ( P<0.05). However, cage dimensions and cage position (anterior-posterior and lateral placement) were not significantly associated with fusion pattern ( P>0.05). Overall, 61.5% (208/338) of segments showed no cage subsidence; 24.5% (83/338) had settling, and 14.0% (47/338) had grade 1 or higher subsidence. Among lateral fusion cases, the rates of no subsidence, anchoring, grade 1, grade 2, and grade 3 subsidence were 67.6%, 21.3%, 7.4%, 3.9%, and 0.7%, respectively. In the central fusion group, these rates were 59.2%, 27.6%, 9.2%, 2.5%, and 1.3%, respectively. In the non-union group, grade 2 and 3 subsidence occurred in 50% (3/6) each, significantly higher than in the other fusion groups ( P<0.05). Post hoc analysis confirmed that grade 2 and 3 subsidence rates were significantly elevated in the non-union group compared to the lateral and central fusion groups, while other subsidence categories showed no significant differences across groups. Clinically, patients showed significant improvements in ODI and VAS scores following surgery ( P<0.05). Conclusions:Lateral fusion occurred in 40.2% of OLIF cases. The OLIF-SA technique, preoperative osteophytes, and elevated preoperative HU values were significantly associated with lateral fusion. In contrast, surgical approach, number of fused segments, cage height, width, and cage positioning did not significantly influence the occurrence of lateral fusion.

Aim To examine the pathogenesis of disul-fide death gene in vascular dementia(VD)by bioin-formatics analysis of disulfide death differentially ex-pressed genes(DEGs)combined with experimental verification.Methods The death DEGs of disulfide were screened and their correlation was analyzed.The VD patients data in the data set were analyzed by clus-tering and typing and gene set variation.The clustering risk of DEGs was tested with a nomogram model,and the optimal learning model was predicted.After the es-tablishment of VD rat model,water maze test,HE stai-ning and RT-qPCR detection were performed to verify the results of health information.Results Four DEGs including SLC7A11 were obtained,which had antago-nistic or synergistic interaction with each other.The genetic data could be divided into two subtypes with significant differences.After typing,VD disulfide DEGs were mainly concentrated in GnRH signaling pathways.The accuracy of the nomogram prediction model was high.Generalized linear was the best ma-chine learning model.Compared with the sham opera-tion group,the escape latency of rats in the model group was prolonged,the number of crossing platforms decreased,the relative mRNA expression levels of Slc3a2 and Slc7a11 decreased,and LRPPRC in-creased.Conclusions SLC7A11 and other disulfide death DEGs and its related GnRH signaling pathway may be an important part of the pathogenesis of VD di-sulfide death.SLC3A2,LRPPRC and SLC7A11 can be used as characteristic genes in the regulation of VD by disulfide death,which may affect VD progression through the regulation of disulfide death.

BACKGROUND: Medical informatics accumulated vast amounts of data for clinical diagnosis and treatment. However, limited access to follow-up data and the difficulty in integrating data across diverse platforms continue to pose significant barriers to clinical research progress. In response, our research team has embarked on the development of a specialized clinical research database for cardiology, thereby establishing a comprehensive digital platform that facilitates both clinical decision-making and research endeavors. METHODS: The database incorporated actual clinical data from patients who received treatment at the Cardiovascular Medicine Department of Chinese PLA General Hospital from 2012 to 2021. It included comprehensive data on patients' basic information, medical history, non-invasive imaging studies, laboratory test results, as well as peri-procedural information related to interventional surgeries, extracted from the Hospital Information System. Additionally, an innovative artificial intelligence (AI)-powered interactive follow-up system had been developed, ensuring that nearly all myocardial infarction patients received at least one post-discharge follow-up, thereby achieving comprehensive data management throughout the entire care continuum for high-risk patients. RESULTS: This database integrates extensive cross-sectional and longitudinal patient data, with a focus on higher-risk acute coronary syndrome patients. It achieves the integration of structured and unstructured clinical data, while innovatively incorporating AI and automatic speech recognition technologies to enhance data integration and workflow efficiency. It creates a comprehensive patient view, thereby improving diagnostic and follow-up quality, and provides high-quality data to support clinical research. Despite limitations in unstructured data standardization and biological sample integrity, the database's development is accompanied by ongoing optimization efforts. CONCLUSION The cardiovascular specialty clinical database is a comprehensive digital archive integrating clinical treatment and research, which facilitates the digital and intelligent transformation of clinical diagnosis and treatment processes. It supports clinical decision-making and offers data support and potential research directions for the specialized management of cardiovascular diseases.

Attention deficit hyperactivity disorder (ADHD), a prevalent neurodevelopmental disorder influenced by both genetic and environmental factors, remains poorly understood regarding how its polygenic risk score (PRS) impacts functional networks and symptomology. This study capitalized on data from 11,430 children in the Adolescent Brain Cognitive Development study to explore the interplay between PRS_ADHD, brain function, and behavioral problems, along with their interactive effects. The results showed that children with a higher PRS_ADHD exhibited more severe attention deficits and rule-breaking problems, and experienced sleep disturbances, particularly in initiating and maintaining sleep. We also identified the central executive network, default mode network, and sensory-motor network as the functional networks most associated with PRS and symptoms in ADHD cases, with potential mediating roles. Particularly, the impact of PRS_ADHD was enhanced in children experiencing heightened sleep disturbances, emphasizing the need for early intervention in sleep issues to potentially mitigate subsequent ADHD symptoms.
Humans ; Attention Deficit Disorder with Hyperactivity/physiopathology* ; Male ; Female ; Sleep Wake Disorders/physiopathology* ; Adolescent ; Child ; Brain/diagnostic imaging* ; Multifactorial Inheritance ; Genetic Predisposition to Disease