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.

ObjectiveHepatocellular carcinoma (HCC) represents 90% of all primary liver cancers. The main risk factors associated with HCC include viral hepatitis (B and/or C), alcohol abuse, and metabolic dysfunction-associated steatotic liver disease (MASLD), which progressively advance to liver fibrosis, cirrhosis, and ultimately evolve into HCC. Surgical resection represents the most effective treatment for HCC, while recent advances in immunotherapy, including immune checkpoint inhibitors and adoptive cell therapies, have provided improved treatment prospects for patients with unresectable HCC. However, the complex metabolic heterogeneity of HCC limits the therapeutic efficacy. Metabolic intermediates acyl-CoA not only provide energy and substrates for numerous biochemical reactions but also serve as donors for protein lysine acylation, a major class of post-translational modification (PTM). Therefore, a deeper understanding of the molecular mechanisms underlying protein lysine acylation and hepatocarcinogenesis is urgently needed. MethodsThe levels of protein lysine acylation and silence information regulator 5 (SIRT5) expression levels in clinical HCC samples were analyzed by Western blot. Quantitative malonylome and succinylome of HCC samples were analyzed by antibody-based affinity enrichment coupled with tandem mass spectrometry. The proliferation of HCC cells was analyzed with Cell Counting Kit-8 (CCK-8) assays, the apoptosis was quantified by Annexin V-FITC/propidium iodide (PI) staining coupled with flow cytometry, and the ability of cells to migrate was assayed by Transwell assays. The enzymatic activity of glutathione S-transferase Mu 1 (GSTM1) was quantified. Transgenic mice with hepatic overexpression of SIRT5 were constructed using CRISPR-Cas9, and primary hepatocarcinogenesis was induced by administration of diethylnitrosamine. ResultsWestern blot analysis indicated that the expression level of SIRT5 was elevated in clinical samples from HCC patients, and the levels of lysine malonylation, glutarylation, and succinylation were significantly reduced in HCC tissues. Knockout of SIRT5 in MHCC-97H and MHCC-97L hepatoma cells suppressed cell proliferation, and increased the percentage of apoptotic cells significantly. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the differentially malonylome and succinylome of HCC samples revealed significant enrichment in two major classes of biological processes: core energy metabolism (e.g., glycolysis/gluconeogenesis, tricarboxylic acid metabolic process, fatty acid beta oxidation) and detoxification and oxidative stress response (e.g., response to toxic substance, chemical carcinogenesis, reactive oxygen species (ROS)). SIRT5 removes malonylation from lysine residues in GSTM1 and restores its detoxification activity, which is crucial for the survival of hepatocytes under stressed conditions. More importantly, in vivo experiment indicated that hepatic-specific overexpression of SIRT5 in mice accelerated diethylnitrosamine-induced liver fibrosis and hepatocarcinogenesis, indicating the critical role of SIRT5 in HCC progression. ConclusionThis study highlights the previously unrecognized SIRT5-GSTM1 axis as a key regulator in hepatocarcinogenesis, and suggests a potential target for the treatment of patients with HCC.

Sarcopenia, an age-related degenerative skeletal muscle disorder characterized by progressive loss of muscle mass, diminished strength, and impaired physical function, poses substantial challenges to global healthy aging initiatives. The pathogenesis of this condition is fundamentally rooted in mitochondrial dysfunction, manifested through defective energy metabolism, disrupted redox equilibrium, imbalanced dynamics, and compromised organelle quality control. This comprehensive review elucidates the central role of exercise-induced mitochondrial hormesis as a critical adaptive mechanism counteracting sarcopenia. Mitohormesis represents an evolutionarily conserved stress response wherein sublethal mitochondrial perturbations, particularly transient low-dose reactive oxygen species (ROS) generated during muscle contraction, activate cytoprotective signaling cascades rather than inflicting macromolecular damage. The mechanistic foundation of this process involves ROS functioning as essential signaling molecules that activate the Keap1 nuclear factor erythroid 2 related factor 2 (Nrf2) antioxidant response element pathway. This activation drives transcriptional upregulation of phase II detoxifying enzymes including superoxide dismutase (SOD) and glutathione peroxidase (GPx), thereby enhancing cellular redox buffering capacity. Crucially, Nrf2 engages in bidirectional molecular crosstalk with peroxisome proliferator activated receptor gamma coactivator 1 alpha (PGC-1α), the principal regulator orchestrating mitochondrial biogenesis through coordinated induction of nuclear respiratory factors 1 and 2 (NRF1/2) along with mitochondrial transcription factor A (Tfam), collectively facilitating mitochondrial DNA replication and respiratory complex assembly. Concurrently, exercise-induced alterations in cellular energy status, specifically diminished ATP to AMP ratios, potently activate AMP activated protein kinase (AMPK). This energy-sensing kinase phosphorylates PGC-1α while concomitantly stimulating NAD dependent deacetylase sirtuin 1 (SIRT1) activity, which further potentiates PGC-1α function through post-translational deacetylation. The integrated AMPK/PGC-1α/SIRT1 axis coordinates mitochondrial biogenesis, optimizes network architecture through regulation of fusion proteins mitofusin 1 (Mfn1), mitofusin 2 (Mfn2) and optic atrophy protein 1 (OPA1), and enhances clearance of damaged organelles via selective activation of mitophagy receptors BCL2 interacting protein 3 (Bnip1) and FUN14 domain containing 1 (FNDC1). Exercise further stimulates the mitochondrial unfolded protein response (UPRmt), increasing molecular chaperones such as heat shock protein 60 (HSP60) and HSP10 to preserve proteostasis. Within the mitochondrial matrix, SIRT3 fine-tunes metabolic flux through deacetylation of electron transport chain components, improving phosphorylation efficiency while attenuating pathological ROS emission. Distinct exercise modalities differentially engage these pathways. Aerobic endurance training primarily activates AMPK/PGC-1α signaling and UPRmt to expand mitochondrial volume and oxidative capacity. Resistance training exploits mechanical tension to acutely stimulate mechanistic target of rapamycin complex 1 (mTORC1) mediated protein synthesis while modulating dynamin related protein 1 (Drp1) phosphorylation dynamics to support mitochondrial network reorganization. High intensity interval training generates potent metabolic oscillations that rapidly amplify AMPK/PGC-1α and Nrf2 activation, demonstrating particular efficacy in insulin-resistant phenotypes. Strategically designed concurrent training regimens synergistically integrate these adaptations. Mitochondrial-nuclear communication through tricarboxylic acid cycle metabolites and mitochondrially derived peptides such as mitochondrial open reading frame of 12s rRNA-c (MOTS-c) coordinates systemic metabolic reprogramming, with exercise-responsive myokines including fibroblast growth factor 21 (FGF-21) mediating inter-tissue signaling to reduce inflammation and enhance insulin sensitivity. This integrated framework provides the scientific foundation for precision exercise interventions targeting mitochondrial pathophysiology in sarcopenia, incorporating biomarker monitoring and exploring pharmacological potentiators including nicotinamide riboside and MOTS-c mimetics. Future investigations should delineate temporal dynamics of mitohormesis signaling and epigenetic regulation to optimize therapeutic approaches for age-related muscle decline.

Objective To evaluate the changes in postoperative plasma β-endorphin(β-EP)levels in patients who had received perioperative electroacupuncture(EA)treatment in 10 randomized controlled trials(RCTs)and examine the impact of EA on postoperative pain.Methods This meta-analysis evaluated the changes in plasma β-EP levels and visual analog scale(VAS)12,24 and 48 hours after surgery in patients receiving perioperative EA.It also assessed the changes in plasma serotonin(5-hydroxytryptamine,5-HT)and prostaglandin E2(PGE2)levels at 24 hours postsurgery.A comprehensive search was conducted in the China National Knowledge Infrastructure(CNKI),Wanfang,Chongqing VIP database,Chinese Biomedical Database(CBM),Web of Science,and PubMed databases.RCTs on perioperative EA and β-EP published from the inception of the websites up to July 25,2023,were retrieved.Effect size aggregation,literature quality assessment,and bias analysis were performed using RevMan 5.3 software,and sensitivity analysis was conducted via R 4.3.1.Results A total of 10 RCTs involving 706 patients were included.EA in conjunction with conventional anesthesia significantly increased plasma β-EP levels at 12 hours postsurgery[standard mean difference(SMD)=2.79,95%CI(1.85,3.72),Z=5.81,P＜0.00001],24hours postsurgery[SMD=1.87,95%CI(0.9,2.83),Z=3.79,P=0.0001],and 48 hours postsurgery[SMD=2.02,95%CI(1.49,2.54),Z=7.50,P＜0.00001].EA reduced plasma PGE2 levels at 24 hours postsurgery and plasma 5-HT levels at 24 hours postsurgery,and the VAS at 12,24 and 48 hours after surgery also decreased.Conclusion These findings suggest that perioperative EA markedly elevates plasma β-EP levels,reduces pain-inducing factors in plasma,and effectively alleviates acute postoperative pain.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

AIM To explore the clinical effects of Jiawei Yanghe Decoction combined with Budesonide and Formoterol Fumarate Powder for Inhalation on patients with mild to moderate bronchial asthma in chronic and persistent period.METHODS One hundred and eighteen patients were randomly assigned into control group(59 cases)for 4-week administration of Budesonide and Formoterol Fumarate Powder for Inhalation,and observation group(59 cases)for 4-week administration of both Jiawei Yanghe Decoction and Budesonide and Formoterol Fumarate Powder for Inhalation.The changes in clinical effects,ACT score,bronchial asthma control rate,pulmonary function indices(FEV1,PEF,FEV1％,PEF％),inflammatory indices(EOS,EOS％,FeNO),TCM syndrome score and incidence of adverse reactions were detected.RESULTS The observation group demonstrated higher total effective rate than the control group(P＜0.05).After the treatment,the two groups displayed increased bronchial asthma control rate,ACT score,PEF(P＜0.05),and decreased TCM syndrome score(P＜0.05),especially for the observation group(P＜0.05);the observation group exhibited increased FEV1,FEV1％,PEF％(P＜0.05),among which FEV1,PEF％were higher than those in the control group(P＜0.05);the observation group showed decreased inflammatory indices(P＜0.05),among which FeNO was lower than that in the control group(P＜0.05).No significant difference in incidence of adverse reactions was found between the two groups(P＞0.05).CONCLUSION For the patients with mild to moderate bronchial asthma in chronic and persistent period,Jiawei Yanghe Decoction combined with Budesonide and Formoterol Fumarate Powder for Inhalation can safely and effectively alleviate clinical symptoms,improve pulmonary functions,airway inflammatory reactions,and enhance bronchial asthma control rate.

Laccase is a type of polyphenol oxidase that can catalyze the oxidation of various substances,including phenols,aromatic amines,and catecholamines.It has been widely utilized in pollutant degradation and analytical applications.However,the high cost of preparation of natural laccase and its susceptibility to environmental factors,which can lead to denaturation and inactivation,limit its practical applications.Nanozymes,which are nanomaterials that exhibit enzyme-like properties,offer advantages such as easy preparation,adjustable activity,and exceptional stability.Currently,many types of nanozymes have been developed.Inspired by the coordination of Cu2+with amino acids in the active site of natural laccase,researchers have employed coordination synthetic strategies to prepare laccase-like nanozymes.The metal nodes in these laccase-like nanozymes include copper,manganese,and cerium,while the ligands involve a variety of chemicals like nucleotides,amino acids,polypeptides,and aromatic acids.By manipulating factors such as the metal-to-ligand ratio,reducing capacity of ligands,buffer solutions,chloride ions,bromine ions,the catalytic activity of laccase-like nanozymes can be finely tuned.In this paper,laccase-like nanozymes developed through coordination strategies were categorized and summarized,along with review of their analytical applications in detection of phenolic compounds,disease biomarkers,antibiotics,pesticides,sulfur-containing pollutants,and time-temperature indicators.Furthermore,the challenges currently faced in the research of laccase-like nanozymes and future research directions were discussed.

Gender recognition based on the analysis of fingerprint residue can assist investigators in narrowing down the scope of investigation and play an important role in the field of criminal investigation.This study established a quantitative analysis method for lipid substances in fingerprints based on gas chromatography-mass spectrometry(GC-MS).Fatty acids in fingerprints were methylated using sulfuric acid methanol derivatization reagent(7%,V/V),the extraction reagent was dichloromethane-methanol(1∶1,V/V)solution,the reaction temperature was 70℃and the heating time was 45 min.Quantitative analysis of the relative content of 23 kinds of fatty acids and squalene in fingerprints residue by different genders was conducted,and orthogonal partial least squares-discriminant analysis(OPLS-DA)was used to reduce the dimensionality of the quantitative results.A total of 13 kinds of components in the fingerprints were selected to maximize the difference in relative content between male and female fingerprints.Three machine learning models,including binary logistic regression(BLR),support vector machine(SVM)and random forest(RF),were further used as feature variables to classify the gender of fingerprints.The classification performance of each model was compared through five indicators,and it was found that the most suitable model for binary classification of fingerprint gender was SVM model.The results showed that the SVM fingerprint residual gender binary classification model established based on the relative content data of 13 kinds of lipid substances in fingerprints achieved a classification accuracy of 90%and an area under the receiver operating characteristic curve(AUC)value of 0.98.This study provided a new research method for detecting lipid components in fingerprints and a methodological basis for gender recognition of fingerprints.

Objective To explore the correlation between the actual age and the pulp chamber volume(PCV)and pulp dentinal index(PDI)of the right first molars based on cone beam computed tomog-raphy(CBCT)technology,and to construct an accurate and convenient model for age estimation.Methods CBCT image data of 1 857 Han adults(883 males and 974 females)from the Department of Stomatology,Affiliated Hospital of North Sichuan Medical College were collected.The data were di-vided into training and validation sets at a ratio of 8∶2.A total of 1 485 training samples were used to construct the age estimation model,and 372 samples were used to validate the accuracy of the model.The Mimics 21.0 software was used to measure the PCV and calculate the PDI of the right first molars.Their correlations with age and the differences between different sexes and tooth positions were analyzed.Results Both the PCV and the PDI of the first molars showed strong negative correla-tions with the actual age(r values ranged from 0.82 to 0.89).The differences in PCV and PDI be-tween different sexes and tooth positions were statistically significant(P<0.05).The age estimation model based on PDI was superior to that based on PCV.The model based on the PDI values of the two right first molars(y=73.72-44.15 x3-28.27 x4,where x3 and x4 are the PDI values of the right maxil-lary and mandibular first molars,respectively)was the best,with the R2 of 0.79 and the mean abso-lute error of 4.90 years.Conclusion Both PCV and PDI of the first molars are effective indicators for age estimation.The age estimation model based on the PDI is more convenient and accurate than that based on the PCV,providing a more effective method for age estimation in forensic practice.