Background Air pollution is a major environmental factor threatening respiratory health. Different pollutants exhibit varying degrees of lag effects on respiratory diseases, and synergistic effects may exist among multiple pollutants. There is an urgent need to identify the key air pollutants influencing respiratory diseases and their interactive effects at specific lags. Objective To identify key pollutants affecting hospital admissions for respiratory diseases, to analyze their lag effect characteristics, and to quantify the impact of multi-pollutant synergistic effects on respiratory disease admissions. Methods Daily air pollution data, meteorological data, and respiratory disease hospitalization records were collected from multiple national monitoring stations in Hefei City from 2019 to 2024. A two-stage analytical framework was employed. First, a distributed lag model (DLM) was used to construct pollutant lag matrices, followed by least absolute shrinkage and selection operator (LASSO) regression to select key variables among fine particulate matter (PM_2.5), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), carbon monoxide (CO), and ozone (O₃). Second, a generalized additive model (GAM) was established, incorporating product interaction terms and excess relative risk (ERI) to quantitatively assess synergistic effects among the selected pollutants. Results Through LASSO regression, 24 pollutant lag terms with non-zero coefficients were identified, among which NO₂, PM_2.5, and SO₂ accounted for 66.7% of the total positive effects and exhibited distinct lag patterns. Exposure to NO₂ showed acute risk, with a relative risk of 1.040 (95%CI: 1.023, 1.057) at lag0. Conversely, PM_2.5 and SO₂ exhibited delayed effects, with peak impacts observed at lag7 (RR=1.012, 95%CI: 1.0002, 1.024) and lag3 (RR=1.015, 95%CI: 1.0004, 1.03), respectively. Short-term NO₂ exposure (lag0–1) exhibited a significant positive interaction with medium-term PM_2.5 exposure (lag4–7). When both pollutants coexisted at high exposure levels, the combined health risk exceeded the sum of their independent effects by 4.40%. Stratified analysis showed that the interaction effects of pollutants were higher in females (ERI=5.00%), children (<18 years, ERI=5.50%), and older adults (≥65 years, ERI=3.90%)Conclusion There are significant lag heterogeneity and synergistic mechanisms in the health effects of air pollution in Hefei. It is recommended to implement real-time early warning responses for NO₂, prioritize medium-to-long-term management for PM_2.5 and SO₂, and adopt coordinated emission reduction measures when NO₂ and PM_2.5 concentrations rise simultaneously. Concurrently, enhanced health protection should be provided for sensitive populations such as women, children, and the elderly.

Glycogen synthase 1 (GYS1) is the rate-limiting enzyme responsible for glycogen synthesis in skeletal muscle, heart, brain, and other extrahepatic tissues, playing a central role in systemic energy homeostasis. The human GYS1 gene maps to chromosome 19q13.33, comprises 16 exons, and encodes a 737-amino-acid polypeptide that is highly conserved across mammals. GYS1 activity is subject to multilayered and precisely coordinated regulation. At the transcriptional level, the GYS1 promoter contains a hypoxia response element (HRE) that mediates HIF-1α-dependent induction under low-oxygen conditions, as well as a muscle-specific enhancer harboring MEF2 and MyoD binding sites that confers tissue-restricted expression. At the post-translational level, a hierarchical phosphorylation cascade serves as the primary activity switch: glycogen synthase kinase 3β (GSK3β) sequentially phosphorylates four C-terminal serine residues following casein kinase II priming, while protein kinase A (PKA) and AMP-activated protein kinase (AMPK) provide parallel inhibitory inputs at both N- and C-terminal sites. Dephosphorylation and reactivation are mediated by protein phosphatase 1 (PP1) through tissue-specific glycogen-targeting regulatory subunits such as PPP1R3A and PPP1R3B, which anchor PP1 to glycogen particles and direct its activity toward GYS1. The allosteric activator glucose-6-phosphate (G6P) binds at the dimer interface, simultaneously enhancing catalytic efficiency and promoting dephosphorylation susceptibility, thereby establishing a feed-forward activation loop that couples substrate availability to glycogen synthesis. Beyond phosphorylation, GYS1 is regulated by ubiquitination (mediated by the E3 ligase PJA1), acetylation, O-linked β-N-acetylglucosamine (O-GlcNAc) modification, and SUMOylation, which collectively modulate protein stability, subcellular localization, and protein-protein interactions. Epigenetic mechanisms, including CpG island methylation and histone acetylation dynamics, govern chromatin accessibility at the GYS1 locus, while muscle-specific microRNAs such as miR-1 and miR-206 fine-tune GYS1 expression at the post-transcriptional level. Dysregulation of GYS1 has been identified as a central pathogenic driver in a spectrum of human diseases. In inherited glycogen storage disorders—including Lafora disease, adult polyglucosan body disease (APBD), and Pompe disease—loss of upstream regulatory control leads to GYS1 hyperactivation and the accumulation of structurally abnormal or excessive glycogen, resulting in progressive neurodegeneration, myopathy, and multiorgan dysfunction. In type 2 diabetes mellitus (T2DM), impaired insulin signaling through the PI3K-AKT-GSK3β axis maintains GYS1 in a hyperphosphorylated inactive state in skeletal muscle, compromising postprandial glucose disposal and exacerbating hyperglycemia. In oncology, GYS1 exhibits context-dependent roles across multiple cancer types. In hepatocellular carcinoma, FMO2⁺ cancer-associated fibroblasts stabilize GYS1 by competitively inhibiting PJA1-mediated ubiquitination, and stabilized GYS1 subsequently activates NF‑κB/CCL19 signaling to promote tertiary lymphoid structure formation and enhance anti-PD-1 immunotherapy responsiveness. In clear cell renal cell carcinoma, GYS1 promotes tumor progression through non-canonical NF‑κB pathway activation via the scaffold protein RPS27A. In triple-negative breast cancer, GYS1 has been identified as a trigger of disulfidptosis and an activator of NF-κB signaling through non-enzymatic facilitation of IκBα degradation. In colorectal cancer, mitochondrial fission deficiency drives AMPK-dependent GYS1 upregulation and glycogen accumulation as a compensatory survival mechanism, while in cervical cancer, GYS1-maintained glycogen reserves fuel the pentose phosphate pathway to generate NADPH for ROS clearance, thereby conferring cisplatin resistance in cancer stem cells. Therapeutic strategies targeting GYS1 have gained substantial momentum across these disease contexts. For glycogen storage disorders, antisense oligonucleotides, small interfering RNAs (e.g., ABX1100), and small-molecule inhibitors (e.g., MZ-101) have demonstrated preclinical and early clinical efficacy in reducing pathological glycogen accumulation. For T2DM, pharmacological activation of GYS1 through GSK3β inhibition or enhancement of PP1-mediated dephosphorylation is being explored to restore insulin-stimulated glycogen synthesis. In cancer, GYS1-directed interventions—including targeted silencing to sensitize tumors to chemotherapy and immune microenvironment modulation to enhance immunotherapy—represent emerging precision oncology approaches. This review provides a comprehensive and integrated account of GYS1 gene structure, tissue-specific distribution, regulatory networks, and pathogenic roles in metabolic disorders and malignancies, with the aim of establishing a theoretical framework for the development of GYS1-targeted precision therapies.

Diabetic retinopathy (DR) is one of the most prevalent and vision-threatening microvascular complications of diabetes mellitus, yet its pathogenesis extends far beyond vascular injury alone. As the retina is among the most energy-demanding tissues in the body, its neurons, glial cells, pigment epithelial cells, pericytes, and endothelial cells are highly dependent on mitochondrial oxidative phosphorylation to maintain visual signal transduction, ionic homeostasis, and neurovascular integrity. This review summarizes current evidence indicating that mitochondrial dysfunction is not merely a downstream consequence of chronic hyperglycemia, but a central pathogenic hub that initiates, amplifies, and perpetuates retinal neurovascular degeneration in DR. Persistent hyperglycemia activates multiple abnormal metabolic pathways, including the polyol pathway, hexosamine pathway, protein kinase C signaling, advanced glycation end-product formation, and angiotensin II-related responses. Although these pathways differ mechanistically, they converge on excessive reactive oxygen species (ROS) generation, antioxidant depletion, and mitochondrial injury. Under diabetic stress, electron transport chain overload promotes mitochondrial ROS leakage, damages mitochondrial DNA, disrupts membrane potential, and impairs the transcription of key respiratory chain components. In parallel, mitochondrial quality-control systems become progressively compromised. The balance between fusion and fission shifts toward pathological fragmentation through reduced MFN1/2 and OPA1 activity and enhanced DRP1-mediated fission. Mitochondrial biogenesis is suppressed through inhibition of the AMPK/SIRT1/PGC-1α/NRF1/TFAM axis, while mitophagy changes from an early compensatory response to a later state of autophagic flux blockade and accumulation of dysfunctional mitochondria. Importantly, damaged mitochondria serve as signal amplifiers linking metabolic stress to inflammation and programmed cell death. Mitochondrial ROS, oxidized mitochondrial DNA, calcium overload, cardiolipin exposure, and membrane permeabilization activate interrelated death pathways, including intrinsic apoptosis, ferroptosis, and pyroptosis. Cytochrome C and apoptosis-inducing factor promote caspase-dependent and caspase-independent apoptosis; iron dyshomeostasis, glutathione depletion, GPX4 dysfunction, and lipid peroxidation drive ferroptosis; and mitochondrial danger signals activate the NLRP3 inflammasome and gasdermin-dependent pyroptosis. These pathways jointly damage the retinal neurovascular unit and contribute to pericyte loss, endothelial barrier breakdown, Müller cell dysfunction, retinal ganglion cell apoptosis, retinal pigment epithelial injury, and photoreceptor degeneration. This review also emphasizes the role of epigenetic regulation in stabilizing mitochondrial pathology. DNA methylation, histone modifications, and non-coding RNAs interact to silence mitochondrial protective genes, alter antioxidant responses, and maintain the “metabolic memory” of DR even after glycemic normalization. Therefore, mitochondrial dysfunction should be understood as a dynamic, multidimensional network rather than a single pathological event. Current clinical approaches, such as laser photocoagulation, intravitreal anti-VEGF therapy, and vitrectomy, mainly target advanced vascular lesions and are limited by invasiveness, incomplete responsiveness, recurrence, and potential adverse effects. Therapeutically, strategies targeting mitochondrial ROS, restoring mitochondrial dynamics, enhancing biogenesis, regulating mitophagy, inhibiting inflammasome activation, correcting epigenetic abnormalities, and improving targeted delivery systems show promising potential. However, major translational barriers remain, including retinal cell heterogeneity, stage-specific mitochondrial responses, insufficient organelle-specific drug delivery, and long-term safety concerns. A deeper understanding of mitochondrial regulatory networks may support earlier, more precise, and multi-target interventions for preventing or slowing DR progression.

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.

ObjectiveTo investigate the relationship between periodontitis severity and brain functional indices-amplitude of low-frequency fluctuations （ALFF） and fractional ALFF （fALFF） in cognitively normal middle-aged and older adults， and to examine their associations with cognitive performance. Methods42 cognitively normal middle-aged and older participants were enrolled. Periodontal data—including the number of remaining teeth （NTP）， bleeding on probing positivity rate （BOP%）， probing depth （PD）， and clinical attachment loss （CAL） as well as resting-state functional magnetic resonance imaging data were collected. Participants were divided into a mild periodontitis group and a moderate-to-severe periodontitis group according to periodontitis severity. Group differences in ALFF and fALFF were compared， and correlation analyses were performed. ResultsCompared with the mild periodontitis group， the moderate-to-severe group showed decreased ALFF values in the right lingual gyrus， superior occipital gyrus， paracentral lobule， and in the left calcarine cortex as well as the precentral and postcentral gyri. Decreased fALFF values were observed in the right lingual gyrus， cuneus， and left calcarine cortex. Indicators related to periodontitis progression ［BOP%， PD=4-5 mm （%）， PD≥6 mm （%）， CAL=3-4 mm （%） and CAL≥5 mm （%）］ were negatively correlated with ALFF， fALFF and cognitive performance， whereas indicators reflecting better periodontal function ［PD=1-3 mm （%） and CAL=0-2 mm （%）］ were positively correlated with these measures. ConclusionIn cognitively normal middle-aged and older adults， periodontitis severity is associated with alterations in brain functional activity and cognitive performance.

Purpose To investigate the sex differences of white matter damage in Alzheimer's disease(AD)and their association with cognitive impairment.Materials and Methods This retrospective study included 88 AD patients(48 females),71 amnestic mild cognitive impairment(aMCI)patients(39 females),and 95 healthy controls(63 females)recruited from the Memory Disorder Clinic at the First Affiliated Hospital of Anhui Medical University from September 2017 to July 2024.High-resolution three-dimensional T1 structure images and diffusion tensor imaging images were all obtained from each participant.The mean diffusivity(MD)and fractional anisotropy(FA)values of each white matter region were obtained,and the two-way ANOVA analysis was conducted to investigate brain regions with interaction effects between groups and sexes,those brain regions were then chosen as regions of interest for further correlation analysis with a series of cognitive scale scores.Results In terms of FA values,the right posterior corona radiata,right anterior limb of the internal capsule and left corticospinal tract showed interaction between sexes and cognitive groups(F=4.764,3.812,5.937,all P<0.05).The FA value of AD group was significantly lower than that of healthy control and aMCI group(all P<0.05),but there was no significant difference between healthy control and aMCI group(except the right anterior limb of the internal capsule,P=0.018).In AD group,FA values were significantly higher in women than in men in the previously described brain regions(all P<0.05),while there was no significant difference in FA values between male and female in healthy control and aMCI groups(except the left corticospinal tract,P<0.001).In terms of MD values,the right anterior limb of the internal capsule,right superior corona radiata and left external capsule showed interaction effect between sexes and cognitive groups(F=8.581,3.680,7.218,all P<0.05).The MD value of AD group was significantly higher than that of aMCI group(P<0.001),and aMCI group was higher than that of healthy control group(all P<0.05).In AD group,the MD values in the above brain regions were significantly higher in males than those in females(all P<0.01),while no significant difference was found between males and females in healthy control and aMCI groups(except for the left external capsule,P<0.05).For correlation analysis,the AD group was dimidiated into two groups by sex,the scores of the Montreal cognitive assessment,the Mini Mental state examination and the verbal fluency test of the female patient group were positively correlated with the FA values of the right posterior corona radiate(r=0.372,P=0.009;r=0.345,P=0.016;r=0.383,P=0.007),while the Mini Mental state examination and the verbal fluency test scores of female AD patient group were negatively correlated with the MD values of the right superior corona radiata(r=-0.360,P=0.012;r=-0.360,P=0.003).Conclusion Compared to the healthy control and MCI groups,white matter damage in AD patients shows sex differences and is associated with general cognitive and language functions impairment in female AD patients.

Objective:To establish a stable rat model of sequelae of pelvic inflammatory disease(SPID)with clinical characteristics,and to provide a reliable experimental model for the study of the pharmcological effect and mechanism of SPID.Methods:Twenty-four 7-week-old SD rats were divided into sham operation group,model-A(108 cfu/mL mixed bacterial solution,0.2 mL),model-B(109 cfu/mL mixed bacterial solution 0.2 mL),and model-C(108 cfu/mL E.coli 0.2 mL).The weight of the rat's uterine was weighed and the uterine index was calculated.The automatic hematology analyzer was used to detect the blood routine;hematoxylin-eosin staining(HE)and masson staining were used to detect uterine pathlogical changes in rats.Enzyme-linked immunosorbent assay(ELISA)was used to detect interleukin-1β(IL-1β),interleukin-6(IL-6)and tumor necrosis factor-α(TNF-α)in rat uterine tissue homogenates.Western blot was used to detect the expression of proteins related to NF-κB signaling pathway.Results:Compared with the sham operation group,the uterine index of model-A,model-B,and model-C were significantly increased(P＜0.05,P＜0.01).The levels of WBC and NE in the model-A increased significantly(P＜0.01).The level of LY in model-B decreased significantly(P＜0.01).The levels of IL-1β,TNF-α in model-A,model-B,and model-C were significantly increased(P＜0.01).The levels of IL-6 in model-A and model-B were significantly increased(P＜0.05,P＜0.01).The collagen volume fraction of model-A and model-B were significantly increased(P＜0.01).Mechanism study indicates that the expression levels of p-IKKβ/IKKβ,p-IκBα/IκBα and p-p65/p65 in model-A were significantly increased(P＜0.01),and the expression levels of IκBα/β-actin were significantly decreased(P＜0.01).The expression level of p-IKKβ/IKKβ in model-B was significantly increased(P＜0.01).Conclusions:A stable rat model of SPID that conforms to clinical characteristics can be successfully constructed by combining 0.2 mL of mixed bacterial solution with a concentration of 108 cfu/mL and mechanical injury.This modeling method intervened in the expression of the NF-κB inflammatory signaling pathway.

Objective:To explore the interrelationship between brain functional networks and features in functional magnetic resonance imaging(fMRI)of patients with Alzheimer's disease(AD),and to construct mixed-function networks(MFN),and apply them in machine learning classification models to improve the accuracy of AD classification.Methods:102 AD patients and 227 healthy subjects in the Alzheimer's Neuroimaging Initiative(ADNI)dataset were retrospectively analyzed.The partial correlation brain network of the blood oxygen level dependent(BOLD)signal was calculated and fused with low-frequency wave amplitude(ALFF),fractional low-frequency wave amplitude(fALFF)and local consistency(ReHo)features to construct MFN.Network topology parameters were extracted,and a variety of machine learning classification models were constructed based on MFN topological parameters,accuracy,precision,recall and area under the curve(AUC)were used to evaluate the predictive efficiency of the models.Results:By constructed MFN and calculated intra group to inter group ratio(IIGR),35 features could be obtained from ALFF,fALFF and ReHo feature topological parameter analysis,after rank sum test and FDR correction,there were statistical differences among 28 features(P＜0.05).The classification results show that,all the five classifiers have high classification performance on the test data set.The accuracy,precision and recall rates of random forest(RF),adaptive lifting algorithm(AdaBoost),guided aggregation algorithm(Bagging)and support vector machine(SVM)were all 99.7％,and the AUC values were up to 100％,99.5％,99.1％and 99.5％,respectively.The accuracy(98.5％),precision(98.5％),recall(98.5％),and AUC(99.1％)of the multi-layer perceptron(MLP)were slightly lower than other models,but remained excellent.It was worth noting that RF has the highest AUC value of all models at 100.0％,while Bagging has the lowest AUC value(99.1％)in the integrated approach.The results of performance comparison show that,MFN classification model can significantly improve the recognition and classification of AD disease,and greatly improve the performance of various indicators of the classifier.The results showed that,MFN classification model was superior to intelligent classification based fusion,DBN-based multitask learning,PVT-TSVM,unsupervised learning and clustering,SVM and SVM of degree 3 polynomial kernel function in key indicators such as accuracy(99.13％),AUC(99.42％),recall rate(99.46％)and specificity(99.42％)with plasma proteins,machine learning algorithms.It was further proved that MFN classification model has good generalization ability and robustness in AD disease classification.Conclusion:The AD classification model constructed based on brain mixed function network topology parameters and machine learning can improve the accuracy of AD classification.

Objective:To investigate the effect and mechanism of injectable photopolymerizable porous gelatin methacrylate anhydride (Porous GelMA)/methacrylated silk fibroin (SilMA) composite hydrogel (PSE) loaded with human umbilical cord mesenchymal stem cell-derived exosomes (hUCMSC-Exos) in promoting knee joint cartilage regeneration.Methods:The porous GelMA solution (60 g/L) was mixed with SilMA solution (200 g/L) at a volume ratio of 6∶1 . The mixture was ultraviolet-irradiated for 30 seconds to form a cured Porous GelMA/SilMA hydrogel (P/S6). The hUCMSC-Exos was isolated via differential centrifugation coupled with ultrafiltration and then was incorporated into the Porous GelMA/SilMA composite solution at 200 μg/ml, followed by ultraviolet irradiation for 30 seconds to generate Exos-loaded PSE. Primary rat chondrocytes (P1) were divided into control group, P/S6 group, and PSE group to characterize the porosity, compressive strength, and sustained exosome release kinetics of PSE hydrogel. Chondrocytes were allocated to control group, interleukin-1β (IL-1β) group, P/S6 group, and PSE group, among which the last three groups were preconditioned with 10 ng/ml IL-1β for 24 hours, and then cultured in complete medium, P/S6 extract and PSE extract for 3 days, respectively, to establish in vitro cartilage defect models, while the control group remained untreated. Western blot and qRT-PCR analysis were conducted to quantify the expression levels of antibody to aggrecan core protein (ACAN), sex-determining region Y-box transcription factor 9 (SOX9), matrix metalloproteinase-13 (MMP13) and collagen type II (COL II). Murine monocyte-macrophage leukemia cells (RAW264.7) were divided into control group, P/S6 group, and PSE group, which were then cultured in complete medium, PSE extract, and PSE extract medium for 3 days, respectively. qRT-PCR was employed to detect the expression levels of recombinant arginase-1 protein (ARG1), mannose receptor (CD206), and inducible nitric oxide synthase (iNOS). Transcriptomic sequencing was used to identify differentially expressed genes during PSE-mediated chondrocyte regeneration, followed by functional enrichment analysis of key signaling pathways. Twenty-four SD rats were selected to establish cartilage defect models and assigned to injury control group, P/S6 group, and PSE group according to the random number table (8 rats per group). The right knee joints of the rats were surgically exposed, and cylindrical osteochondral defects (a diameter of 2.0 mm× a depth of 1.0 mm) were surgically created in the center of the femoral trochlear groove using a drill bit. The injury control group received phosphate-buffered saline, while the P/S6 group and PSE group were injected with corresponding hydrogels followed by photo-crosslinking. Incisions then were closed in layers. At 6 and 10 weeks after injury, specimens were harvested for HE staining and safranin O-fast green staining to evaluate cartilage regeneration and immunohistochemistry staining to quantify the positive area fractions for COL II, MMP13, ARG1, and CD206 in the defect areas. Results:PSE hydrogel exhibited compressive strength matching native cartilage (0.41 MPa), high porosity (85%), and sustained exosome release capacity (cumulative release rate of approximately 85% over 14 days). In chondrocyte repair experiments, compared to the IL-1β group, the PSE group demonstrated significantly upregulated expression of anabolic markers of cartilage (COL II expression increased by 2.1-fold, ACAN by 1.8-fold, and SOX9 by 1.5-fold) ( P<0.01) as well as significantly suppressed expression of catabolic markers (MMP13 expression decreased by 52%) ( P<0.01). In macrophage polarization assays, the PSE group exhibited ARG1 expression increased by 68% when compared to the control group ( P<0.01), thus promoting M2 polarization of macrophages. Transcriptomic analysis revealed that PSE enhanced extracellular matrix (ECM) synthesis by activating the phosphatidylinositol 3-kinase/protein kinase B (PI3K/Akt) pathway and ECM-receptor interaction pathway, as well as by suppressing inflammation-related gene expression. Histological evaluation in animal experiments revealed regeneration of hyaline cartilage with smooth, continuous surfaces in the defect areas in the PSE group. At 10 weeks after surgery, the neocartilage-positive area in the PSE group was (9.94±0.26)%, significantly larger than (1.67±0.11)% in the injury control group ( P<0.01). Besides, the CD206? M2 macrophage-positive area reached (14.44±0.23)% in the PSE group, significantly larger than (3.41±0.36)% in the injury control group ( P<0.01). Conclusions:The PSE hydrogel successfully engineered in the study can significantly promote regenerative repair of knee cartilage defects through a dual mechanism of enhanced ECM anabolism and remodeled inflammatory microenvironment. The core mechanisms involve specific activation of the PI3K/Akt pathway (boosting chondrocyte proliferation and survival) and ECM-receptor interaction pathway (driving ECM synthesis and assembly) by exosome-loaded PSE, while effectively polarizing macrophages toward an anti-inflammatory M2 phenotype so as to coordinately regulate cartilage ECM metabolism and suppress inflammatory responses.

Objective To design an integrated device for cleaning,sterilizing and drying the glass graduated pipette with considerations on its characteristics.Methods The integrated device had its shell made of 304 stainless steel and hardware part composed of three modules for control,cleaning and drying.The control module consisted of a human machine interface(HMI)touch screen,a programmable logic controller(PLC),solenoid valves and etc;the cleaning module was made up of an ultrasonic release disk,a heat preservation cylinder,a bracket and etc;the drying module comprised a blower,a heating plate,a heat preservation cylinder and connected pipes.The HMI was developed with the programming language of EasyBuilder,and the PLC control logic was written with SCL high-level programming language.Results The device developed could be used for cleaning,sterilizing and drying the glass graduated pipette,and the pipette could be stored in the device after drying.Conclusion The integrated device developed eliminates manual operation and enhances the efficiency of the cleaning,sterilization and drying of the glass graduated pipette.[Chinese Medical Equipment Journal,2025,46(4):108-112]