Owing to its inherent advantages—such as being non-destructive, rapid, highly molecule-specific, and minimally interfered with by moisture—Raman spectroscopy has been widely adopted in the fields of skin barrier function assessment, monitoring the transdermal penetration of active cosmetic ingredients, and the identification and quality control of cosmetic products. Despite these strengths, the practical application of this technique faces a significant bottleneck: the strong fluorescence background generated by endogenous skin components and exogenous cosmetic additives. Endogenous skin substances, such as structural proteins (e.g., collagen and elastin), metabolic coenzymes (e.g., nicotinamide adenine dinucleotide), and pigments (e.g., melanin), together with exogenous cosmetic constituents like organic colorants, chemical sunscreens, and fragrances, often possess strong absorption and emission characteristics. When excited by lasers, these components produce a fluorescence background that can be 10⁶ to 10⁸ times stronger than the Raman scattering signals, effectively masking the inherently weak vibrational fingerprint information. In recent years, driven by the rapid development of optoelectronic hardware and artificial intelligence algorithms, fluorescence suppression strategies have evolved from isolated, single-method approaches into comprehensive, multi-level synergistic systems. These systems are categorized into three distinct tiers: sample preparation, signal acquisition, and data processing. At the sample preparation level, techniques such as photobleaching and surface-enhanced Raman spectroscopy (SERS) are employed to eliminate or bypass the generation of fluorescence at the source. At the signal acquisition level, instrumental improvements—including the use of long-wavelength near-infrared excitation (typically 785 nm or 1 064 nm), confocal spatial filtering, and shifted excitation Raman difference spectroscopy (SERDS)— are utilized to physically isolate Raman signals from the fluorescence background. Furthermore, at the data processing level, numerical baseline correction methods such as polynomial fitting, penalized least squares (e.g., airPLS, arPLS), wavelet transform, and derivative algorithms are increasingly integrated into the analytical pipeline to extract Raman spectral features from mixed signals without increasing hardware costs or acquisition time. This review provides a systematic categorization and critical evaluation of these fluorescence suppression methods, detailing their underlying principles, technical advantages, and inherent limitations in diverse experimental setups. By focusing on critical application scenarios—including skin barrier assessment, percutaneous absorption monitoring, the routine quality control of cosmetics, and the emerging field of portable on-site detection—this paper explores the current state of technique selection and optimization. Finally, the article discusses future development trends, emphasizing the necessity of constructing adaptive, tiered suppression strategies, developing intelligent and automated data processing algorithms, and promoting the integration of portable, multi-modal diagnostic devices. The objective of this review is to provide a comprehensive technical reference to facilitate the transition of Raman spectroscopy from a specialized laboratory tool into a routine, robust analytical platform for advancements in skin science and cosmetic research.

Autism spectrum disorder (ASD) is a neurodevelopmental condition with a steadily rising global prevalence, yet effective pharmacological interventions remain notably limited, highlighting an urgent need for safe, accessible, and mechanism-based therapeutic strategies. Physical exercise has emerged as a promising non-pharmacological intervention that ameliorates both core symptoms—social communication deficits and restricted repetitive behaviors—and associated features including cognitive dysfunction and motor impairments, in children and adolescents with ASD. However, the molecular mechanisms mediating these beneficial effects remain incompletely defined, impeding the development of evidence-based exercise prescriptions and biomarker-driven rehabilitation protocols. MicroRNAs (miRNAs) are evolutionarily conserved small non-coding RNAs that post-transcriptionally regulate approximately 60% of protein-coding genes. Within the central nervous system, miRNAs orchestrate diverse neurobiological processes including neural progenitor proliferation, neuronal differentiation, dendritic spine morphogenesis, synaptic plasticity, and neuroinflammatory homeostasis. Notably, miRNAs are remarkably stable in biological fluids and can be packaged into extracellular vesicles, rendering them attractive candidates as both mechanistic mediators and non-invasive peripheral biomarkers. Among the hundreds of miRNAs expressed in the brain, three—miR-132, miR-34a, and miR-146a—have emerged as particularly relevant to ASD pathophysiology. This review focuses on these three miRNAs for the following reasons: miR-132 is a master regulator of activity-dependent synaptic plasticity through its modulation of BDNF/MeCP2/PTEN signaling and has been consistently downregulated in ASD prefrontal cortex; miR-34a functions as a pro-apoptotic factor that suppresses Bcl-2-mediated neuronal survival pathways and is upregulated in ASD cerebellum; and miR-146a serves as a key brake on neuroinflammation via TLR7/IRAK1 signaling and shows region-specific dysregulation in ASD temporal lobe. We first summarize evidence from human post-mortem brain tissues and ASD animal models demonstrating the consistent dysregulation of these three miRNAs. Notably, the pathological consequences of these miRNA alterations—impaired synaptic plasticity, excessive neuronal apoptosis, and sustained neuroinflammation—are interconnected and collectively contribute to the heterogeneous symptomatology of ASD. We then present a synthesis of emerging evidence demonstrating that various exercise modalities, including swimming, treadmill running, and voluntary wheel running, can concurrently reverse these ASD-like behavioral phenotypes and normalize the expression of the three key miRNAs. These data provide the first direct experimental evidence linking exercise-induced miRNA modulation to ASD symptom improvement. On the basis of these findings, we propose an integrative “exercise-miRNA-ASD” framework wherein exercise functions as a multi-targeted modulator—simultaneously enhancing synaptic plasticity, promoting neuronal survival, and attenuating neuroinflammation—through coordinated regulation of the three miRNAs. Importantly, this framework is not merely descriptive but offers testable predictions: exercise-induced miRNA changes should be dose-dependent, show temporal correlation with behavioral improvements, and be blunted by miRNA-specific antagonists or CRISPR/Cas9-mediated knockout. Beyond its specific application to ASD, this framework has broader implications. The miR-132/BDNF, miR-34a/Bcl-2, and miR-146a/TLR7 pathways are not ASD-specific but represent fundamental neural stress and repair mechanisms that are dysregulated across Alzheimer’s disease (AD), traumatic brain injury, Parkinson’s disease (PD), and major depressive disorder. Exercise has been shown to modulate these same miRNAs in several of these conditions, suggesting that the “exercise-miRNA-neural function” axis may represent a conserved neuroprotective mechanism that transcends diagnostic boundaries. Thus, we propose that ASD serves as an ideal model disease for elucidating this universal mechanism, with findings potentially generalizable to other neurological disorders. We also critically evaluate current translational barriers: the near-absence of human clinical trials with serial miRNA profiling; the undefined dose-response relationships between exercise parameters and miRNA expression; the unresolved causality issue (current evidence demonstrates association, not causation); and the uncertain correlation between peripheral exosomal miRNA levels and brain miRNA dynamics. We argue that future research must prioritize CRISPR/Cas9-based miRNA manipulation in animal models combined with longitudinal exercise interventions to establish causality, and that cross-disease validation studies are essential to determine whether exercise-induced miRNA changes represent a shared neuroprotective signature or disease-specific responses. Ultimately, we envision a paradigm where a simple blood test measuring exosomal miR-132, miR-34a, and miR-146a levels could guide personalized exercise prescriptions, enabling precision rehabilitation for individuals with ASD and potentially other neurological conditions.

Metabolic dysfunction-associated fatty liver disease （MAFLD） has become the most common chronic liver disease worldwide. Its pathological process is centered on the “two-hit” theory， with gut-liver axis dysregulation running through the entire disease course from steatosis to liver cirrhosis and even hepatocellular carcinoma， and it forms an extensive cross-system regulatory mechanism with the metabolic， cardiovascular， renal， and psychological and nervous systems through multi-dimensional pathways such as the “gut-liver-brain axis”， the “liver-kidney axis”， and the “liver-heart axis”. Disease progression is not limited to the liver itself， and it also involves functional imbalance of multiple organ systems throughout the body. This article systematically elaborates on the association mechanism of “liver pathological progression-multi-axis regulation-comorbidity occurrence” in MAFLD， proposes synergistic management strategies integrating early screening based on risk stratification， targeted intervention， and multidisciplinary diagnosis and treatment， and analyzes the limitations of current research and future development directions， in order to provide a theoretical basis and practical guidance for precise diagnosis and treatment and individualized management of MAFLD.

With the continuous development of society, a large number of new chemicals are continuously emerging, which presents a challenge to current risk assessment and safety management of chemicals. Traditional toxicology research methods have certain limitations in quickly, efficiently, and accurately assessing the toxicity of many chemicals, and cannot meet the actual needs. In response to this challenge, computational toxicology that use mathematical and computer models to achieve the prediction of chemical toxicity has emerged. In the meantime, as researchers increasingly pay attention to understanding the interaction mechanisms between exogenous chemical substances and the body from the system level, and multiomics technologies develop rapidly such as genomics, transcriptomics, proteomics, and metabolomics, huge amounts of data have been generated, providing rich information resources for studying the interactions between chemical substances and biological molecules. System toxicology and network toxicology have also developed accordingly. Of these, network toxicology can integrate these multiomics data to construct biomolecular networks, and then quickly predict the key toxicological targets and pathways of chemicals at the molecular level. This paper outlined the concept and development of network toxicology, summarized the main methods and supporting tools of network toxicology research, expounded the application status of network toxicology in studying potential toxicity of exogenous chemicals such as agricultural chemicals, environmental pollutants, industrial chemicals, and foodborne chemicals, and analyzed the development prospects and limitations of network toxicology research. This paper aimed to provide a reference for the application of network toxicology in other fields.

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.

Objective To investigate whether the application of automated software for computed tomography angiography(CTA)and computed tomography perfusion imaging(CTP)can improve in-hospital workflow for endovascular treatment(EVT)in acute ischemic stroke patients.Methods We included patients with acute ischemic stroke who received CTA and CTP evaluation followed by EVT through the stroke emergency pathway at the Affiliated Hospital of Southwest Medical University between January 1,2020 and December 30,2022.The patients were divided into two groups:control group and artificial intelligence(Al)group based on whether automated software was used for assessment.The control group consisted of patients who underwent manual post-processing of multimodal imaging before June 2021,while the AI group was composed of patients whose imaging was processed with automated software from July 2021 onwards.The primary outcome was door-to-puncture time(DPT),and the secondary outcome was the 90-day modified Rankin Scale(mRS)score.Results A total of 312 patients were included,with 145 in the control group and 167 in the AI group.The median age of all the patients was 68 years(range:58-74 years),and 55.4％(173 patients)were male.The median National Institutes of Health Stroke Scale(NIHSS)score at presentation was 16 scores(range:12-19 scores).The median DPT was reduced from 110 min(range:80-150 min)before the use of automated software to 95 min(range:65-125 min)after its implementation(P＜0.001).However,there was no significant difference in the proportion of patients achieving functional independence(mRS score of 0-2)between the two groups(39.3％vs.41.3％,P=0.719).Conclusion The application of multimodal CT automated software improves the in-hospital workflow for acute ischemic stroke patients by reducing the time to EVT.However,the software did not significantly impact neurological functional outcomes as measured by the mRS.

Persistent atrial fibrillation and other factors can cause mitral and tricuspid annular dilation and leaflet regurgitation,leading to severe functional mitral and tricuspid regurgitation.Patients often experience significant heart failure symptoms and poor prognosis.For patients with severe mitral or tricuspid regurgitation who are at high risk or contraindicated for surgical procedures,transbronchial repair(TEER)is an important alternative therapy that can effectively reduce valve regurgitation and improve cardiac function;Although there is a lack of large-scale data on atrial functional reflux,existing experience still shows that TEER can significantly reduce reflux and improve patients'quality of life.However,double valve intervention therapy poses challenges,especially when combined with TEER repair,which is technically more complex,time-consuming,and carries higher risks.Foreign data shows that simultaneous or staged double valve intervention can safely improve cardiac function and increase survival rates,but the optimal intervention strategy still needs further research.Due to the fact that tricuspid TEER devices have not yet been launched in China,only staged treatment can be adopted at present.This case report shows a patient with severe atrial functional mitral and tricuspid regurgitation who underwent staged transcatheter edge to edge repair surgery successfully.During a 1-year follow-up,bilateral valve regurgitation continued to improve,indicating that staged repair of bilateral atrioventricular valve regurgitation through the catheter margin is a feasible and effective treatment option.

Objective To compare the effects of different detector combinations of 320-row CT on the image quality and radiation dose of head CT to explore the feasibility of using a wide detector for head CT scanning.Methods Totally 100 patients underwent head CT scanning due to trauma or cerebrovascular disease at some hospital from June to August 2023 were collected prospectively and divided into group A and group B by using block randomization grouping method,with the length of the block group being 2 and 50 patients in each group.In group A,all the detectors had the widths at z-axis direction being 40×0.5 mm and head scanning was completed after multiple exposures;in group B,detector combinations with widths of 280×0.5 mm or 320×0.5 mm were chosen based on the patient's head size in the head-foot direction(z-axis direction),and head scanning was performed with a single-turn exposure.The remaining scanning and image reconstruction parameters in the two groups were kept completely consistent.The head image quality of the 2 groups was evaluated objectively and scored subjectively by 2 radiologists.The volume CT dose index(CTDIvol),dose length product(DLP)and exposure time of the 2 groups were recorded,and the effective dose(ED)was calculated.SPSS 22.0 software was used for statistical analysis.Results In terms of objective evaluation of image quality,at the level of the parietal skull group B had the CT value of gray matter,image noise and contrast to noise ratio(CNR)of the images higher than those of group A,and the differences were statistically significant(all P<0.05);at the level of the posterior skull group B had the CT values of gray and white matter,image noise and air noise lower while CNR higher than those of group A,and the differences were statistically significant(all P<0.05).In terms of subjective scoring of image quality,at the levels of parietal and posterior skull group A behaved better than group B,and the differences were statistically significant(all P<0.05).In group A 5 patients had obvious motion artifacts affecting the diagnosis and the image quality scores not higher than 2,and secondary scanning had to be carried out;In group B all the patients had no obvious motion artifacts and met the diagnosis requirements.When compared with group A Group B had the CTDIvol,DLP,ED and exposure time decreased by 17.44%,17.24%,17.48%and 85.53%,respectively,and the differences were statistically significant(all P<0.05).Conclusion A wide detector gains advantages over a 20 mm detector in image quality when 320-row CT is used for head CT scanning,with the diagnosis requirements satisfied.[Chinese Medical Equipment Journal,2025,46(4):57-62]

Objective To design a high altitude adaptive oxygen generator for the crews to alleviate their high altitude reaction in high altitude environment and meet their requirements for oxygen supply.Methods A high altitude adaptive oxygen generator based on the mature pressure swing adsorption oxygen production method was designed with the key technologies of discharge capacity compensation of air compression pump and airway fusion of molecular sieve tower,which had the components of molecular sieve tower,air compression pump,controller,cooling fan,cooler,solenoid valve,regulator,flow meter and etc.Trials were carried out at the simulated altitude and field plateau environment so as to verify the high altitude adaptive performance of the oxygen generator developed.Results The trial results showed the oxygen generator met the desired objectives and the requirements for oxygen volume fraction in GJB 2799-1996 General specification for medical oxygen generator using molecular sieve method.Conclusion The oxygen generartor provides oxygen supply effectively for vehicle operators in plateau environments or the ones rushing into the plateau.[Chinese Medical Equipment Journal,2025,46(4):29-34]

Persistent atrial fibrillation and other factors can cause mitral and tricuspid annular dilation and leaflet regurgitation,leading to severe functional mitral and tricuspid regurgitation.Patients often experience significant heart failure symptoms and poor prognosis.For patients with severe mitral or tricuspid regurgitation who are at high risk or contraindicated for surgical procedures,transbronchial repair(TEER)is an important alternative therapy that can effectively reduce valve regurgitation and improve cardiac function;Although there is a lack of large-scale data on atrial functional reflux,existing experience still shows that TEER can significantly reduce reflux and improve patients'quality of life.However,double valve intervention therapy poses challenges,especially when combined with TEER repair,which is technically more complex,time-consuming,and carries higher risks.Foreign data shows that simultaneous or staged double valve intervention can safely improve cardiac function and increase survival rates,but the optimal intervention strategy still needs further research.Due to the fact that tricuspid TEER devices have not yet been launched in China,only staged treatment can be adopted at present.This case report shows a patient with severe atrial functional mitral and tricuspid regurgitation who underwent staged transcatheter edge to edge repair surgery successfully.During a 1-year follow-up,bilateral valve regurgitation continued to improve,indicating that staged repair of bilateral atrioventricular valve regurgitation through the catheter margin is a feasible and effective treatment option.