Metabolic associated fatty liver disease (MAFLD) is fundamentally driven by an imbalance in hepatic fatty-acid flux: the influx of fatty acids exceeds the liver’s capacity for disposal, resulting in excessive hepatic lipid accumulation, predominantly in the form of triglycerides (TGs). The occurrence and progression of MAFLD depend on disordered regulation across multiple metabolic steps, including fatty-acid uptake, de novo lipogenesis (DNL), fatty-acid oxidation (FAO), and very low-density lipoprotein (VLDL) export. Forkhead box protein O1 (FOXO1) is a key transcriptional regulator within the hepatic network coordinating glucose and lipid metabolism. Under metabolic stress and insulin resistance (IR), FOXO1 expression is frequently increased, whereas its inhibitory phosphorylation is reduced. These changes enhance FOXO1 nuclear localization and transcriptional activity, thereby reprogramming the expression of genes related to metabolism in the liver. Because hepatic lipid deposition is the central pathological feature of MAFLD, the functional status of FOXO1 directly influences hepatic lipid homeostasis. Growing evidence suggests that FOXO1 can exert bidirectional, environment-dependent effects on hepatic lipid accumulation; however, the molecular basis for this functional switch remains incompletely understood. This review systematically summarizes the biological functions and regulatory mechanisms of FOXO1 and its roles in hepatic lipid metabolism, with a particular focus on its crosstalk with insulin signaling. FOXO1 expression is shaped by RNA modifications and epigenetic regulation mediated by non-coding RNAs. Its transcriptional output is precisely governed by post-translational modifications—such as phosphorylation and acetylation—as well as by coordinated nucleocytoplasmic shuttling. Notably, these regulatory patterns vary markedly across nutritional states, degrees of insulin resistance, and stages of disease. In the fed state, insulin/IGF-1 signaling activates the PI3K-AKT pathway, promoting the inhibitory phosphorylation of FOXO1 and facilitating additional modifications, including acetylation, methylation, and ubiquitination. Together, these events drive FOXO1 export from the nucleus and dampen its transcriptional activity, suppressing gluconeogenesis and constraining lipogenic programs. Conversely, during fasting or when insulin signaling is weakened, FOXO1 inhibition is relieved. FOXO1 accumulates in the nucleus, binds to DNA, and regulates the transcription of downstream target genes. Mechanistically, FOXO1 can aggravate hepatic lipid accumulation by activating genes involved in TG synthesis while repressing FAO-related pathways, thereby favoring storage over oxidation. However, under specific conditions, FOXO1 may also alleviate the hepatic lipid burden by promoting TG hydrolysis and enhancing VLDL secretion, thereby reducing the net hepatic lipid load. In addition, lipotoxic signals mediated by ceramides and diacylglycerols (Cer/DAG) activate atypical protein kinase C (aPKC), further exacerbating the disruption of the AKT-FOXO1 axis. This vicious cycle ultimately produces a metabolic paradox in which increased hepatic glucose output coexists with persistent, insulin-independent lipogenesis, accelerating MAFLD progression. Importantly, FOXO1 regulation is not uniform: during early metabolic overload, insulin-mediated suppression may remain effective, whereas in advanced insulin resistance, the loss of AKT control permits sustained FOXO1 activity. Such stage-dependent dynamics may help explain why FOXO1 can either promote steatosis or, in certain contexts, support programs that facilitate lipid turnover. Accordingly, interventions should be liver-specific and tuned to the disease stage, aiming to curb maladaptive FOXO1 signaling while preserving its capacity to promote triglyceride hydrolysis and VLDL secretion when advantageous. Overall, this review offers an important perspective on MAFLD pathogenesis, emphasizing FOXO1 as a potential therapeutic target and providing a theoretical basis for developing liver-specific, disease-course-dependent precision interventions.

ObjectiveIn traditional Chinese medicine (TCM), the foundational doctrine that the eyes reflect the essence of the internal viscera establishes ocular observation as a cornerstone of diagnostic practice. Specifically, the morphological characteristics and coloration variations of the scleral microvasculature serve as critical clinical indicators for assessing the dynamic balance of Qi and Blood, as well as the pathological status of internal organs. Historically, however, TCM eye diagnosis has relied predominantly on the subjective clinical experience and visual acuity of individual practitioners, leading to inherent challenges in standardization and reproducibility. While automated computer-aided diagnostic systems offer a promising solution, existing vessel segmentation algorithms encounter significant domain-specific bottlenecks when applied to scleral imagery. These challenges primarily stem from the highly reflective and moist nature of the ocular surface, which generates severe reflective interference. Furthermore, the inherent low contrast of fine capillary networks against complex background textures, compounded by non-uniform illumination, frequently results in high false-positive rates, misdetections, and severe vessel fragmentation. To address these critical limitations and advance the objective quantification of TCM diagnostics, this paper proposes a novel, highly robust sclera vessel segmentation framework that innovatively integrates Frangi-Sato dual-filter adaptive enhancement with pixel-level reflection detection. MethodsThe proposed methodology systematically addresses the segmentation pipeline through three synergistic stages. First, to overcome the structural limitations of single-filter approaches, a multi-scale weighted fusion strategy is meticulously designed to harness the complementary extraction capabilities of both Frangi and Sato filters. This adaptive enhancement optimally balances the preservation of main vessel trunk continuity with the heightened sensitivity required for delineating delicate, low-contrast peripheral capillaries. Second, to tackle the persistent issue of reflective highlights, a sophisticated multi-feature synergistic reflection detection module is introduced. By jointly analyzing local information entropy, gradient field variations, and intensity statistical distributions, this module achieves precise, pixel-level identification and elimination of reflective artifacts without compromising the underlying vascular structures. Finally, a dual-level adaptive thresholding strategy, featuring an innovative “core protection” mechanism, is implemented. This critical step effectively suppresses complex background noise while rigorously preserving the structural and topological integrity of the intricate vessel network, preventing the structural breaks often seen in conventional binarization methods. ResultsThe efficacy of the proposed framework was rigorously evaluated using both self-constructed clinical datasets specifically acquired for TCM research and standardized public datasets. Extensive experimental results demonstrate that the proposed method consistently outperforms state-of-the-art traditional approaches and contemporary deep learning models. Specifically, the proposed method achieves a Dice similarity coefficient of approximately 0.71 on the private clinical dataset, and secures the best performance across the majority of quantitative metrics on both datasets. Notably, the framework exhibits exceptional robustness and generalization capabilities in highly challenging scenarios characterized by intense reflective interference, low signal-to-noise ratios, and cross-domain image variations. ConclusionThis study successfully realizes the high-integrity, automated segmentation of scleral vessel networks under complex clinical imaging conditions. By overcoming the fundamental algorithmic challenges of reflection interference and micro-vessel loss, the proposed methodology provides potential support for the digitization, objective standardization, and intelligent advancement of modern TCM eye diagnosis systems.

ObjectiveIn traditional Chinese medicine (TCM), the foundational doctrine that the eyes reflect the essence of the internal viscera establishes ocular observation as a cornerstone of diagnostic practice. Specifically, the morphological characteristics and coloration variations of the scleral microvasculature serve as critical clinical indicators for assessing the dynamic balance of Qi and Blood, as well as the pathological status of internal organs. Historically, however, TCM eye diagnosis has relied predominantly on the subjective clinical experience and visual acuity of individual practitioners, leading to inherent challenges in standardization and reproducibility. While automated computer-aided diagnostic systems offer a promising solution, existing vessel segmentation algorithms encounter significant domain-specific bottlenecks when applied to scleral imagery. These challenges primarily stem from the highly reflective and moist nature of the ocular surface, which generates severe reflective interference. Furthermore, the inherent low contrast of fine capillary networks against complex background textures, compounded by non-uniform illumination, frequently results in high false-positive rates, misdetections, and severe vessel fragmentation. To address these critical limitations and advance the objective quantification of TCM diagnostics, this paper proposes a novel, highly robust sclera vessel segmentation framework that innovatively integrates Frangi-Sato dual-filter adaptive enhancement with pixel-level reflection detection. MethodsThe proposed methodology systematically addresses the segmentation pipeline through three synergistic stages. First, to overcome the structural limitations of single-filter approaches, a multi-scale weighted fusion strategy is meticulously designed to harness the complementary extraction capabilities of both Frangi and Sato filters. This adaptive enhancement optimally balances the preservation of main vessel trunk continuity with the heightened sensitivity required for delineating delicate, low-contrast peripheral capillaries. Second, to tackle the persistent issue of reflective highlights, a sophisticated multi-feature synergistic reflection detection module is introduced. By jointly analyzing local information entropy, gradient field variations, and intensity statistical distributions, this module achieves precise, pixel-level identification and elimination of reflective artifacts without compromising the underlying vascular structures. Finally, a dual-level adaptive thresholding strategy, featuring an innovative “core protection” mechanism, is implemented. This critical step effectively suppresses complex background noise while rigorously preserving the structural and topological integrity of the intricate vessel network, preventing the structural breaks often seen in conventional binarization methods. ResultsThe efficacy of the proposed framework was rigorously evaluated using both self-constructed clinical datasets specifically acquired for TCM research and standardized public datasets. Extensive experimental results demonstrate that the proposed method consistently outperforms state-of-the-art traditional approaches and contemporary deep learning models. Specifically, the proposed method achieves a Dice similarity coefficient of approximately 0.71 on the private clinical dataset, and secures the best performance across the majority of quantitative metrics on both datasets. Notably, the framework exhibits exceptional robustness and generalization capabilities in highly challenging scenarios characterized by intense reflective interference, low signal-to-noise ratios, and cross-domain image variations. ConclusionThis study successfully realizes the high-integrity, automated segmentation of scleral vessel networks under complex clinical imaging conditions. By overcoming the fundamental algorithmic challenges of reflection interference and micro-vessel loss, the proposed methodology provides potential support for the digitization, objective standardization, and intelligent advancement of modern TCM eye diagnosis systems.

Aim Mouse model of myocardial hypertro-phy was established via intraperitoneal injection of iso-proterenol(ISO)in mice.This approach allows for an in-depth investigation into the pharmacological effects and mechanisms of action of emodin,offering novel in-sights and directions for the improvement of myocardial hypertrophy.Methods The mice were randomly di-vided into the following groups:control group(CON),emodin group(EMO),MAPK activator control group(EMO+Ani),model group(ISO),treatment group(ISO+EMO),and activator intervention group(ISO+EMO+Ani).After treatment with emodin and inter-vention with MAPK activator,the heart weight ratio and cardiac size of each group were observed.Hematoxy-lin-eosin(HE)staining was used to observe the patho-logical changes in cardiac tissue,and kits were utilized to measure the levels of GSH,LDH,and MDA in the serum.Western blot was employed to detect the protein expression levels of inflammatory and oxidative factors,as well as p-p38,p-ERK,p38,and ERK in cardiac tis-sue.Results Emodin can significantly inhibit the production of myocardial inflammatory and oxidative factors induced by ISO,thereby effectively alleviating the degree of myocardial hypertrophy and fibrosis.Af-ter the p38/ERK signaling pathway was specifically ac-tivated by farnesol,the improvement effect of emodin on myocardial hypertrophy was weakened.Further comparison revealed that,compared with the myocardi-al hypertrophy pathological model group,the pathologi-cal protein expression levels in the farnesol-treated group showed no significant difference,and were even higher in some indicators.Conclusion Emodin can effectively inhibit the release of inflammatory factors and improve the state of oxidative stress by modulating the p38/ERK signaling pathway,thereby exerting an ameliorative effect on myocardial hypertrophy.

Objective To observe the association between afterschool physical exercise and sleep quality among preschool children,and to explore the proper afterschool physical exercise model for better sleep quality.Methods A cross-sectional study was conducted.From Apr to Jun 2024,a total of 1 430 children from three public kindergartens in Minhang district were enrolled to participate in the survey.Parents were invited to complete the basic sociodemographic information,afterschool physical exercise information and the Children's Sleep Habits Questionnaire.One-way ANOVA and linear mixed effects models were used to explore the relationship between afterschool exercise and sleep quality.Results A total of 1 430 questionnaires were sent out and 1 384 were recovered with a recovery rate of 96.78%.Among them 1 366 were valid,with an effective rate of 95.52%.The average age of the children was(5.19±0.87)years old with gender ration of 1.07∶1(male:female).The prevalence of poor sleep quality was 80.60%(regarding a CSHQ total score>41 as cutoff).A one-way ANOVA indicated that time on afterschool physical exercise was significantly associated with sleep duration,Night waking,and sleep onset delay(P<0.05).After adjusting for age,gender,the only child or not,main caregiver,and parental education and occupation,linear mixed effects models showed that engaging in afterschool physical activity for at least 180 mins per week has a statistically significant predictive effect on sleep duration scores(β=-0.50,z=-4.52,95%CI:-0.72,-0.28,P<0.001),night waking scores(β=-0.16,z=-2.34,95%CI:-0.29,-0.02,P=0.020),and sleep onset delay scores(β=-0.14,z=-2.35,95%CI:-0.26,-0.02,P=0.019).Conclusion Afterschool exercise was significantly associated with sleep quality among preschool children in Minhang district of Shanghai.The time≥180 min on afterschool exercise per week in preschool children was significantly positively associated with maintaining sleep duration,reducing night wakings and shortening the latency to fall asleep.The habit of afterschool exercise and the time on afterschool exercise should be emphasized by parents and the society to improve sleep quality among preschool children.

AIM To evaluate the quality of Tibetan medicine"Sangdi"based on HPLC fingerprints combined with chemometrics.METHODS The analysis was performed on a 30 ℃ thermostatic Welch Ultimate AQ-C18 column(250 mm × 4.6 mm,5 μm),with the mobile phase comprising of acetonitrile-0.2％phosphoric acid flowing at 1 mL/min in a gradient elution manner,and the detection wavelength was set at 245 nm,after which cluster analysis,principal component analysis and orthogonal partial least squares discriminant analysis were performed,the contents of gentiopicroside,sweroside,mangiferin,isoorientin,8-hydroxy-1,3,5-trimethoxyxanthone(R2)and 1,8-dihydroxy-3,7-dimethoxyxanthone(R3)were determined.RESULTS There were 18 common peaks in the fingerprints for 15 batches of samples with the similarities of more than 0.90.Six constituents showed good linear relationships within their own ranges(R 2 ≥ 0.999 2),whose average recoveries were 96.93％-103.58％with the RSDs of 0.82％-2.9％.Various batches of samples were clustered into 2 categories,4 principal components demonstrated the accumulative variance contribution rate of 86.404％,mangiferin,gentiopicroside and isoorientin were taken as quality difference markers.CONCLUSION This stable,reliable and reproducibe method can provide a reference for the comprehensive quality evaluation of"Sangdi".

Liposomes serve as critical carriers for drugs and vaccines,with their biological effects influenced by their size.The microfluidic method,renowned for its precise control,reproducibility,and scalability,has been widely employed for liposome preparation.Although some studies have explored factors affecting liposomal size in microfluidic processes,most focus on small-sized liposomes,predominantly through experimental data analysis.However,the production of larger liposomes,which are equally significant,remains underexplored.In this work,we thoroughly investigate multiple variables influencing liposome size during microfluidic preparation and develop a machine learning(ML)model capable of accurately predicting liposomal size.Experimental validation was conducted using a staggered herringbone micromixer(SHM)chip.Our findings reveal that most investigated variables significantly influence liposomal size,often interrelating in complex ways.We evaluated the predictive performance of several widely-used ML algorithms,including ensemble methods,through cross-validation(CV)for both lipo-some size and polydispersity index(PDI).A standalone dataset was experimentally validated to assess the accuracy of the ML predictions,with results indicating that ensemble algorithms provided the most reliable predictions.Specifically,gradient boosting was selected for size prediction,while random forest was employed for PDI prediction.We successfully produced uniform large(600 nm)and small(100 nm)liposomes using the optimised experimental conditions derived from the ML models.In conclusion,this study presents a robust methodology that enables precise control over liposome size distribution,of-fering valuable insights for medicinal research applications.

OBJECTIVE: To explore the impact of age on the genetic variant spectrum and prognosis of patients with previously untreated Diffuse large B-cell lymphoma (DLBCL). METHODS: A retrospective analysis was conducted on the clinical data and follow-up information of 254 previously untreated DLBCL patients from 14 hospitals in the Jiangsu Cooperative Lymphoma Group (JCLG) enrolled from July 2018 and July 2023. Following extraction of DNA from tumor tissue samples, next-generation sequencing (NGS) technique was employed to analyze the genetic variant spectrum of the DLBCL patients, with an evaluation of the relationship between age and genetic variants as well as prognosis. This study was approved by the Medical Ethics Committee of the Affiliated Hospital of Nantong University (Ethics No.: 2023-K048-01). RESULTS: The median age of the 254 DLBCL patients was 62 years old, with 55% of patients aged 60 years or above. Clinical evaluation showed that younger (< 60 years) patients had higher complete response (CR) (70% vs. 59%), and objective response rate (ORR) (88% vs. 79%) than older patients, though the difference between the two groups was not statistically. Survival analysis indicated that both the five-year overall survival (OS) (82.7% vs. 71.7%, P = 0.006) and progression-free survival (PFS) (70.6% vs. 50.2%, P < 0.05) rates were significantly higher in younger patients. NGS showed that 99.6% of the patients harbored genetic variants, with PIM1, KMT2D, TP53, MYD88, and CD79B being the most common genes. Age significantly affected the variant frequency of certain genes, with MYC variants serving an adverse prognostic factor for OS in younger patients (P = 0.002), while TP53 (P = 0.024) and BCL2 (P = 0.002) variants significantly impacted OS in older patients. Prognostic analysis identified age ≥ 60 years (HR = 3.439, 95%CI: 1.318~9.874), presence of B symptoms (HR = 2.871, 95%CI = 1.133~7.307), and elevated lactate dehydrogenase (HR = 3.528, 95%CI = 1.231~10.66) as independent adverse prognostic factors. CONCLUSION Age, genetic variants, and clinical factors may significantly affect the prognosis of the DLBCL patients. Younger patients have better survival compared to older patients. Variants of the MYC, BCL2, and TP53 genes are closely associated with poor prognosis.
Humans ; Lymphoma, Large B-Cell, Diffuse/diagnosis* ; Middle Aged ; Female ; Male ; Retrospective Studies ; Aged ; Prognosis ; Adult ; Aged, 80 and over ; High-Throughput Nucleotide Sequencing ; Young Adult ; Adolescent ; Genetic Variation

AIM To evaluate the quality of Tibetan medicine"Sangdi"based on HPLC fingerprints combined with chemometrics.METHODS The analysis was performed on a 30 ℃ thermostatic Welch Ultimate AQ-C18 column(250 mm × 4.6 mm,5 μm),with the mobile phase comprising of acetonitrile-0.2％phosphoric acid flowing at 1 mL/min in a gradient elution manner,and the detection wavelength was set at 245 nm,after which cluster analysis,principal component analysis and orthogonal partial least squares discriminant analysis were performed,the contents of gentiopicroside,sweroside,mangiferin,isoorientin,8-hydroxy-1,3,5-trimethoxyxanthone(R2)and 1,8-dihydroxy-3,7-dimethoxyxanthone(R3)were determined.RESULTS There were 18 common peaks in the fingerprints for 15 batches of samples with the similarities of more than 0.90.Six constituents showed good linear relationships within their own ranges(R 2 ≥ 0.999 2),whose average recoveries were 96.93％-103.58％with the RSDs of 0.82％-2.9％.Various batches of samples were clustered into 2 categories,4 principal components demonstrated the accumulative variance contribution rate of 86.404％,mangiferin,gentiopicroside and isoorientin were taken as quality difference markers.CONCLUSION This stable,reliable and reproducibe method can provide a reference for the comprehensive quality evaluation of"Sangdi".

AIM To explore the relieving effect of Er Miao Wan on atopic dermatitis in mice.METHODS In vivo experiment:BALB/c mice were randomly divided into normal group,model group,dexamethasone group(2 mg/kg)and high,medium and low dose groups of Er Miao Wan(4.68,2.34 and 1.17 g/kg).The mouse model of atopic dermatitis was established by repeatedly smearing DNCB solution,and the model was given orally for 21 days.The skin lesion condition on the back of mice,ear swelling degree,and the weight difference between ear lobes were observed and recorded.HE staining was used to observe the histopathological changes in the skin lesion tissues of mice.Toluidine blue(TB)staining was used to observe the infiltration of mast cells in skin lesions.The expression of macrophage marker F4/80 in skin lesions was detected by IHC.The serum levels of TSLP,IL-4,IL-5 and total IgE were detected by ELISA.In vitro experiment:RAW264.7 cells in logarithmic growth period were given 400,200 and 100 μg/mL Er Miao Wan for intervention.Cell proliferation was detected by CCK-8 method.NO level in cell supernatant was detected by Griess method.TNF-α,IL-1 β and IL-6 levels in cell supernatant were detected by ELISA method.The expressions of proteins related to the MAPK/NF-κB signaling pathway in cells was detected by Western blot.RESULTS In vivo experiment:Compared with the model group,the scores of back skin lesions,the swelling degree of right ear and the weight difference between left and right ear pieces in the high-dose group of Er Miao Wan decreased(P＜0.05,P＜0.01),the thickness of skin lesions decreased,the infiltration of mast cells and macrophages decreased(P＜0.05,P＜0.01),and the inflammatory factors TSLP,IL-4,IL-5 and total IgE levels in serum decreased(P＜0.05,P＜0.01),and the expression of F4/80 in the skin lesions decreased(P＜0.01).In vitro experiment:Compared with the model group,the levels of NO,TNF-α,IL-1 β and IL-6 in Er Miao Wan 400 and 200 μg/mL groups decreased(P＜0.05,P＜0.01),and the phosphorylation levels of P38,JNK and P65 proteins decreased(P＜0.05,P＜0.01).CONCLUSION Er Miao Wan can alleviate skin lesion inflammation in DNCB-induced atopic dermatitis mice,and its mechanism may be related to inhibiting the activation of MAPK/NF-κB signaling pathway of macrophage,reducing macrophage infiltration and reducing Th2 cytokines.