ObjectiveTaking the cuproptosis/oxidative stress pathway as the entry point， this study investigated the effect and mechanism of Liangyi Paste on hepatic lipid deposition in naturally aged mice fed with a high-fat diet. MethodsAfter adaptive feeding， 80 ten-week-old male C57BL/6 mice were used. Thirty of them were randomly divided into three groups （10 mice per group）： The 12-month-old control group （12MCON）， the 15-month-old control group （15MCON）， and the 15-month-old group with a high-fat diet （15MHFD）. The 12MCON and 15MCON groups were continuously fed a standard diet， while the 15MHFD group started receiving a high-fat diet at 12 months of age. Tissue samples were collected at the corresponding time points for each group. The remaining 50 mice were randomly divided into five groups （10 mice per group）： the 20-month-old control group （20MCON）， the model group， and the low-， medium-， and high-dose Liangyi Paste groups （2.91 ， 5.82 ， 11.64 g·kg^-1·d^-1， respectively）. The 20MCON group was continuously fed a standard diet， while the other groups started receiving a high-fat diet at 15 months of age. At 18 months of age， the Liangyi Paste groups were administered the corresponding doses of Liangyi Paste by gavage， while the 20MCON and model groups were given an equal volume of saline by gavage. After 8 weeks of continuous gavage （when the mice reached 20 months of age）， tissue samples were collected. Hepatic TG levels were measured using assay kits； liver histology and lipid deposition were observed via hematoxylin-eosin （HE） and oil red O staining； reactive oxygen species （ROS） were detected by enzyme-linked immunosorbent assay （ELISA）； Cu²⁺， superoxide dismutase （SOD）， and malondialdehyde （MDA） levels were measured by colorimetry； mRNA and protein expression of genes related to cuproptosis and oxidative stress pathways were analyzed by Real-time polymerase chain reaction（Real-time PCR） and Wes automated protein expression system. ResultsCompared with 12MCON， the 15MCON group showed significantly increased hepatic TG， Cu²⁺， ROS， and MDA levels （P<0.01）， decreased SOD （P<0.01）， hepatocyte swelling， and disordered arrangement. The mRNA and protein levels of ferredoxin 1 （FDX1）， dihydrolipoamide S-acetyltransferase （DLAT）， heat shock protein 70 （HSP70）， dihydrolipoamide dehydrogenase （DLD）， pyruvate dehydrogenase E1 subunit-β （PDHB）， nuclear factor erythroid 2-related factor 2 （Nrf2）， and peroxisome proliferator-activated receptor γ （PPARγ） were significantly elevated （P<0.05， P<0.01）. Compared with 15MCON group， the 15MHFD and 20MCON groups exhibited further increases in TG， Cu²⁺， ROS， and MDA （P<0.01）， reduced SOD （P<0.01）， and aggravated hepatocyte swelling and disorder. There were increased lipid droplets with mild vacuolization in the 15MHFD group， and no significant lipid deposition was observed in the 20MCON group. FDX1， DLAT， HSP70， DLD， PDHB， Nrf2， and PPARγ mRNA and protein levels were significantly increased （P<0.05， P<0.01）. Compared with 20MCON group， the model group demonstrated markedly elevated TG， Cu²⁺， ROS， and MDA （P<0.01）， reduced SOD （P<0.01）， severe hepatic steatosis， and upregulated expression of FDX1， DLAT， HSP70， DLD， PDHB， Nrf2， and PPARγ mRNA and proteins （P<0.05， P<0.01）. All abnormalities were significantly reversed after Liangyi Paste treatment. ConclusionLiangyi paste can ameliorate hepatic lipid deposition in naturally aged mice with a high-fat diet by modulating the cuproptosis/oxidative stress pathway.

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.

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.

Objective To explore the value of deep learning image reconstruction(DLIR)algorithm to improve the quality of low keV monochromatic portal vein images of energy spectrum CT.Methods Fifty patients who underwent enhanced upper abdominal energy spectrum CT scan were selected.Mixed-model adaptive statistical iterative reconstruction-Veo(50%ASIR-V)algorithm and high-deep learning image reconstruction(DLIR-H)algorithm were used to obtain monochromatic images at 40-70 keV(with intervals of 10 keV).The CT and standard deviation(SD)values of the portal vein trunk,left and right branches,and erector spinae muscle were measured in the transverse position,and the signal-to-noise ratio(SNR)and portal vein contrast-to-noise ratio(CNR)were calculated for objective evaluation.The portal vein image quality between the two algorithms and different energy was subjectively scored by two physicians.Results In terms of objective evaluation:compared with 50%ASIR-V,the CNR and SNR of portal vein in monochromatic DLIR-H images at the same keV between 40-70 keV energy levels were increased while the SD value was decreased(P＜0.05),and the CT value was unchanged;there was no statistical difference in the magnitude of change in CNR between the two algorithms at different energy levels(P＞0.05);there was a statistically significant difference in the magnitude of change in SNR and SD value(P＜0.05)and the magnitude of change was the largest at 40 keV;comparison between different energy levels of DLIR-H,the CNR and SD value of 40 keV DLIR-H were the highest(P＜0.05),and there was no significant difference in the SNR(P＞0.05).In terms of subjective evaluation:there was no significant difference between the subjective scores of the two algorithms at the same keV from 40-70 keV(P＞0.05),and the two reconstruction algorithms at 40 keV and 50 keV had the highest subjective scores between different keV.Conclusion The DLIR algorithm can reduce the noise of low keV monochromatic images,improve the image quality of portal vein.

Objective To explore the value of deep learning image reconstruction(DLIR)algorithm to improve the quality of low keV monochromatic portal vein images of energy spectrum CT.Methods Fifty patients who underwent enhanced upper abdominal energy spectrum CT scan were selected.Mixed-model adaptive statistical iterative reconstruction-Veo(50%ASIR-V)algorithm and high-deep learning image reconstruction(DLIR-H)algorithm were used to obtain monochromatic images at 40-70 keV(with intervals of 10 keV).The CT and standard deviation(SD)values of the portal vein trunk,left and right branches,and erector spinae muscle were measured in the transverse position,and the signal-to-noise ratio(SNR)and portal vein contrast-to-noise ratio(CNR)were calculated for objective evaluation.The portal vein image quality between the two algorithms and different energy was subjectively scored by two physicians.Results In terms of objective evaluation:compared with 50%ASIR-V,the CNR and SNR of portal vein in monochromatic DLIR-H images at the same keV between 40-70 keV energy levels were increased while the SD value was decreased(P＜0.05),and the CT value was unchanged;there was no statistical difference in the magnitude of change in CNR between the two algorithms at different energy levels(P＞0.05);there was a statistically significant difference in the magnitude of change in SNR and SD value(P＜0.05)and the magnitude of change was the largest at 40 keV;comparison between different energy levels of DLIR-H,the CNR and SD value of 40 keV DLIR-H were the highest(P＜0.05),and there was no significant difference in the SNR(P＞0.05).In terms of subjective evaluation:there was no significant difference between the subjective scores of the two algorithms at the same keV from 40-70 keV(P＞0.05),and the two reconstruction algorithms at 40 keV and 50 keV had the highest subjective scores between different keV.Conclusion The DLIR algorithm can reduce the noise of low keV monochromatic images,improve the image quality of portal vein.

BACKGROUND:Knee finite element modelling can provide insight into knee mechanics,but its complex image segmentation is more difficult for researchers.With the development of deep learning techniques,deep learning techniques have been widely used in knee joint finite element modelling.OBJECTIVE:To replace the manual segmentation step in finite element modelling of the knee joint by using 3D Swin UNETR in combination with a semi-automatic segmentation technique for statistical shape models.METHODS:Manual(artificial)knee joint finite element model was developed based on MR and semi-automatic knee joint finite element model was developed based on 3D Swin UNETR+statistical shape model segmentation.The same loads and boundary conditions were applied to both models.Validation was performed by calculating the Dice similarity coefficient,mean distance,and comparing the peak equivalent stresses,maximum principal stresses,and maximum shear stresses of the two models.RESULTS AND CONCLUSION:(1)The Dice similarity coefficients of the manual and semi-automatic segmented femur and tibia were more than 98％,and the average distances were less than or equal to(0.35±0.08)mm.(2)With the longitudinal load of 750 N and 10 Nm internal overturning moment applied to the femur tip of both manual and semi-automatic finite element models,the peak equivalent stress,maximum principal stress,and maximum shear stresses of meniscus in manual finite element model were 14.12,18.54,and 7.35 MPa;peak equivalent force,maximum principal stress,and maximum shear stress of femoral cartilage were 2.22,2.15,and 1.18 MPa;peak equivalent force,maximum principal stress,and maximum shear stress of tibial cartilage were 2.50,1.91,and 1.41 MPa;semi-automatic finite element model of meniscus:peak equivalent force,maximum principal stress,and maximum shear stress were 14.93,18.53,and 7.75 MPa.The peak equivalent force,maximum principal stress,and maximum shear stress of femoral cartilage were 2.26,2.18,and 1.20 MPa;the peak equivalent stress,maximum principal stress,and maximum shear stress of tibial cartilage were 2.60,1.91,and 1.46 MPa.The peak equivalent stress,maximum principal stress,and maximum shear stress of manual and semi-automatic finite element models were basically consistent,with no significant difference(P＞0.05).(3)The semi-automatic segmentation technique proposed in this study can replace manual segmentation in creating accurate finite element models of the knee joint.

The long non-coding RNA KCNQ1OT1 plays an important role in promoting the occurrence and development of various cancers.However,there is currently no systematic analysis of KCNQ1OT1 in pan cancer.To elucidate the value of KCNQ1OT1 in tumor diagnosis and prognosis,this study analyzed its expression levels in pan-cancer tissues and its impact on patient prognosis.By analyzing the regulatory mechanism of KCNQ1OT1 in gastric cancer,new molecular targets may be found for the diagnosis and treatment of gastric cancer.Using Sangerbox 3.0,ACLBI and UALCAN databases,we found the expres-sion levels of KCNQ1OT1 were increased in 7 tumor tissues types(P＜0.05).We found KCNQ1OT1 ex-pression was correlated with poor prognosis in many tumor types using Sangerbox 3.0 database.We used R software to analyze the differential genes between the high and low expression groups of KCNQ1OT1 in gastric cancer patients(P＜0.05,|log2FoldChange|＞1).The GO and KEGG enrichment analysis showed that KCNQ1OT1 was involved in the glutamine metabolism of gastric cancer.The cell counting and Western blot detection showed that knocking down KCNQ1OT1 significantly reduced the gastric canc-er cell activity,SLC1A5 expression level and SLC1A5-mediated glutamine transport process(P＜0.01).Bioinformatics,RNA immunoprecipitation and dual luciferase analysis confirmed that KCNQ1OT1 com-petitively bind to miR-138-5p to promote the expression of SLC1A5.Finally,ChIP-seq data was used to detect the high H3K27ac signaling at the gene locus of KCNQ1OT1,and ChIP-qPCR was used to verify that P300-mediated enhancer activity regulated the high expression of KCNQ1OT1 in gastric cancer.KC-NQ1OT1 can serve as an independent diagnostic biomarker and prognostic predictor in various tumors.Targeting the KCNQ1OT1/miR-138-5p/SLC1A5 signaling axis to regulate glutamine metabolism may pro-vide new strategies and molecular targets for the treatment of gastric cancer.

Objective To investigate whether Danlou tablet-containing serum ameliorates lipid deposition in HepG2 cells by regulating oxidative stress.Methods Optimal treatment conditions,including concentration and exposure time of Danlou tablet and concentration of oleic acid,were determined,and their effects on cell viability were assessed using the CCK-8 assay.An in vitro model of lipid depo-sition was established by inducing HepG2 cells with oleic acid.HepG2 cells were divided into control,model(treated with oleic acid),and Danlou tablet groups(treated with oleic acid and Danlou tablet).Intracellular lipid droplets were visualized using oil red O staining.Lipid content including non-esterified fatty acid(NEFA)and triglyceride(TG),as well as oxidative stress markers in the cell supernatant,were quantified by enzyme-linked immunosorbent assay.Ultimately,reactive oxygen species(ROS)levels were measured using a fluores-cent probe.Results The optimal conditions were 10％Danlou tablet,24-hour treatment,and 800 μmol/L oleic acid.Compared with the control group,the model group exhibited significantly increased lipid droplet number and size,elevated supernatant levels of NEFA,TG,malondialdehyde,cyclooxygenase-2,and ROS(P＜0.01),and decreased levels of catalase and superoxide dismutase(P＜0.01).Compared with the model group,the Danlou tablet group showed reduced lipid deposition and oxidative stress markers,and increased antioxidant enzyme activity.Conclusion Danlou tablet may ameliorate oleic acid-induced lipid deposition in HepG2 cells by regulating oxidative stress response.

Objective To explore the value of deep learning image reconstruction(DLIR)combined with"three low(low radiation dose,low contrast dose,and low contrast injection rate)techniques"of spectrum CT with low keV in optimizing the image quality of portal vein for liver cirrhosis.Methods Sixty patients with liver cirrhosis who underwent computed tomography portal venography(CTPV)were selected and randomly divided into standard protocol group(group A,n=30)and"three-low"protocol group(group B,n=30).The group A with 120 kVp,contrast dose of 1.4 mL/kg,injection rate of 4.0-5.0 mL/s,and reconstructed 50%adaptive statistical iterative reconstruction-Veo(ASIR-V)image.The group B with 80 kVp/140 kVp double instantaneous switching gemstone spectral imaging(GSI)scan,contrast dose of 1.0 mL/kg,injection rate of 3.0-3.5 mL/s,and reconstructed 40 keV DLIR-M and DLIR-H images.The quality of portal vein images,effective dose(ED),contrast dose and injection rate were compared between the two groups.Results The ED of(4.10±1.56)mSv in group B was lower than that of(7.88±1.08)mSv in group A(P<0.001),and the contrast dose of(67.26±8.74)mL in group B was lower than that of(99.12±8.84)mL in group A(P<0.001).The injection rate of 3.0-3.5 mL/s in group B was reduced by 25%-30%compared with group A.Group B had the greatest contrast-to-noise ratio(CNR)and signal-to-noise ratio(SNR)of portal vein in the 40 keV DLIR-H.The subjective image quality scores were in good agreement between the two physicians(Kappa value>0.75).The subjective DLIR score in group B was higher than that in group A.Conclusion DLIR combined with"three low techniques"spectrum CT with low keV can improve the image quality of portal vein in liver cirrhosis patients.

AIM:This study aims to investigate the effects of baicalin on the hypoxia-inducible factor-1α(HIF-1α)/solute carrier family 7 member 11(SLC7A11)/glutathione peroxidase 4(GPX4)axis and the ferroptosis induced by oxidized low-density lipoprotein(ox-LDL)in RAW264.7 macrophage-derived foam cells.METHODS:RAW264.7 cells were categorized into five groups:control,ox-LDL,baicalin+ox-LDL,ferrostatin-1(Fer-1;ferroptosis inhibitor)+ox-LDL,and baicalin+Fer-1+ox-LDL.To induce foam cell formation,RAW264.7 macrophages were exposed to 100 μg/mL ox-LDL for 24 h.Oil red O staining was employed to visualize lipid droplet formation in each group.The ultrastructure of the mitochondria was examined using transmission electron microscopy.Fluorescence microscopy was utilized to assess the fluorescence intensity of intracellular reactive oxygen species(ROS),lipid peroxides,and Fe2+.A colorimetric assay facilitated the measurement of malondialdehyde(MDA)and glutathione(GSH)levels.Additionally,Western blot analy-sis was conducted to quantify protein levels of HIF-1α,SLC7A11,and GPX4.RESULTS:The model group exhibited foam cell formation,abundant lipid droplets,significant swelling of mitochondrial structures,and observable shortening or disappearance of cristae.There was a marked increase in intracellular fluorescence intensity of ROS,lipid peroxides,and Fe2+,alongside elevated MDA levels and decreased GSH levels.HIF-1α protein expression was significantly increased,while SLC7A11 and GPX4 protein expressions were notably decreased(P<0.05).In comparison to the model group,both the baicalin+ox-LDL and Fer-1+ox-LDL groups demonstrated a significant reduction in lipid droplets,improved mitochon-drial structures,decreased fluorescence intensity of ROS,lipid peroxides,and Fe2+,as well as lower MDA levels and higher GSH levels.Additionally,HIF-1α expression significantly decreased,while SLC7A11 and GPX4 expressions sig-nificantly increased(P<0.05).Furthermore,the baicalin+Fer-1+ox-LDL group showed a more pronounced reduction in lipid droplets,near-normal mitochondrial structures,lower fluorescence intensity of ROS,lipid peroxides,and Fe2+,de-creased MDA levels,and increased GSH levels compared to the baicalin+ox-LDL group;HIF-1α,SLC7A11,and GPX4 protein expressions were also significantly reduced(P<0.05).CONCLUSION:Baicalin modulates the HIF-1α/SLC7A11/GPX4 axis,thereby inhibiting ox-LDL-induced ferroptosis in macrophage-derived foam cells.