ObjectiveThis paper aims to find the identified and validated clinical biomarker data building upon a clinical study of early-phase phase Ⅱ and investigate the correlation analysis of Huanglian Jiedu Wan on syndrome improvement and clinical biomarkers in the treatment of "excess heat-toxicity" based on a machine learning model. Additionally， the effective prediction of clinical biomarker values for the main symptoms of the "excess heat-toxicity" syndrome was assessed. MethodsA total of 229 patients meeting the inclusion criteria for "excess heat-toxicity" syndrome were randomly divided into the Huanglian Jiedu Wan group and the placebo group. Syndrome score transition matrices were constructed for the Huanglian Jiedu Wan group and the placebo group based on three main symptoms of "excess heat-toxicity" syndrome， such as oral ulcers， sore throat， and gum swelling and pain. Data from the patients with these three syndromes were also integrated for an overall analysis. The corresponding syndrome score transition matrices were further constructed to visualize symptom change trends of the patients in the two groups via heatmaps. Based on the identified and validated clinical biomarkers related to inflammation， oxidative stress， and energy metabolism in the early phase， Spearman correlation analysis was employed to analyze and evaluate the associations between clinical biomarkers and syndrome improvement. Key clinical biomarkers reflecting the effect of Huanglian Jiedu Wan were screened through the comparison of differences between groups. An extreme gradient boosting （XGBoost） algorithm was used to develop a prediction model for main symptom classification， with classification performance evaluated through 10-fold cross-validation. Feature importance analysis was applied to identify variables with the greatest contribution to the prediction result. ResultsThe syndrome transition matrix results indicated that the Huanglian Jiedu Wan group showed a superior effect to the placebo group in improving oral ulcers， sore throat， and overall symptoms， with significant effects observed especially in sore throat and overall symptom analyses （P<0.01）. Spearman correlation analysis revealed that several clinical biomarkers positively correlated with "excess heat-toxicity" syndrome and its main symptom improvement， were also called "heat-related biomarkers"， including succinic acid， α-ketoglutaric acid， glycine， lactic acid， adenosine monophosphate （AMP）， tumor necrosis factor-α （TNF-α）， interferon-γ （IFN-γ）， interleukin-1β （IL-1β）， interleukin-4 （IL-4）， interleukin-6 （IL-6）， interleukin-8 （IL-8）， interleukin-10 （IL-10）， and so on. Conversely， clinical biomarkers negatively correlated with symptom severity， were also called "heat-clearing related biomarkers" after administration of Huanglian Jiedu Wan， including malic acid， fumaric acid， cis-aconitic acid， adrenocorticotropic hormone （ACTH）， IL-1β， IL-4， IL-8， succinic acid， and citric acid. The XGBoost classification model using all 52 biomarkers as variables achieved an average test accuracy of 0.754 and an average F1 score of 0.777. Feature importance analysis identified the scores of glutamic acid in saliva and IL-6 were the highest in all the variables， with importance scores of 0.081 and 0.080， respectively. After screening out 14 key variables and optimizing the parameters， model performance improved to an average accuracy of 0.758 and an F1 score of 0.798. Feature importance analysis further determined that the glutamic acid in saliva and IL-6 showed obvious changes after screening the variables， confirming the good syndrome prediction ability of the model constructed by these key clinical biomarkers. ConclusionThis study systematically elucidates the correlation between syndrome improvement and clinical biomarkers of Huanglian Jiedu Wan in the treatment of "excess heat-toxicity" syndrome. An XGBoost classification model based on key clinical biomarkers is successfully established， achieving effective prediction of the symptoms related to the "excess heat-toxicity" syndrome such as oral ulcers and sore throat and providing a new insight for objective identification of traditional Chinese medicine syndromes.

ObjectiveThis paper aims to find the identified and validated clinical biomarker data building upon a clinical study of early-phase phase Ⅱ and investigate the correlation analysis of Huanglian Jiedu Wan on syndrome improvement and clinical biomarkers in the treatment of "excess heat-toxicity" based on a machine learning model. Additionally， the effective prediction of clinical biomarker values for the main symptoms of the "excess heat-toxicity" syndrome was assessed. MethodsA total of 229 patients meeting the inclusion criteria for "excess heat-toxicity" syndrome were randomly divided into the Huanglian Jiedu Wan group and the placebo group. Syndrome score transition matrices were constructed for the Huanglian Jiedu Wan group and the placebo group based on three main symptoms of "excess heat-toxicity" syndrome， such as oral ulcers， sore throat， and gum swelling and pain. Data from the patients with these three syndromes were also integrated for an overall analysis. The corresponding syndrome score transition matrices were further constructed to visualize symptom change trends of the patients in the two groups via heatmaps. Based on the identified and validated clinical biomarkers related to inflammation， oxidative stress， and energy metabolism in the early phase， Spearman correlation analysis was employed to analyze and evaluate the associations between clinical biomarkers and syndrome improvement. Key clinical biomarkers reflecting the effect of Huanglian Jiedu Wan were screened through the comparison of differences between groups. An extreme gradient boosting （XGBoost） algorithm was used to develop a prediction model for main symptom classification， with classification performance evaluated through 10-fold cross-validation. Feature importance analysis was applied to identify variables with the greatest contribution to the prediction result. ResultsThe syndrome transition matrix results indicated that the Huanglian Jiedu Wan group showed a superior effect to the placebo group in improving oral ulcers， sore throat， and overall symptoms， with significant effects observed especially in sore throat and overall symptom analyses （P<0.01）. Spearman correlation analysis revealed that several clinical biomarkers positively correlated with "excess heat-toxicity" syndrome and its main symptom improvement， were also called "heat-related biomarkers"， including succinic acid， α-ketoglutaric acid， glycine， lactic acid， adenosine monophosphate （AMP）， tumor necrosis factor-α （TNF-α）， interferon-γ （IFN-γ）， interleukin-1β （IL-1β）， interleukin-4 （IL-4）， interleukin-6 （IL-6）， interleukin-8 （IL-8）， interleukin-10 （IL-10）， and so on. Conversely， clinical biomarkers negatively correlated with symptom severity， were also called "heat-clearing related biomarkers" after administration of Huanglian Jiedu Wan， including malic acid， fumaric acid， cis-aconitic acid， adrenocorticotropic hormone （ACTH）， IL-1β， IL-4， IL-8， succinic acid， and citric acid. The XGBoost classification model using all 52 biomarkers as variables achieved an average test accuracy of 0.754 and an average F1 score of 0.777. Feature importance analysis identified the scores of glutamic acid in saliva and IL-6 were the highest in all the variables， with importance scores of 0.081 and 0.080， respectively. After screening out 14 key variables and optimizing the parameters， model performance improved to an average accuracy of 0.758 and an F1 score of 0.798. Feature importance analysis further determined that the glutamic acid in saliva and IL-6 showed obvious changes after screening the variables， confirming the good syndrome prediction ability of the model constructed by these key clinical biomarkers. ConclusionThis study systematically elucidates the correlation between syndrome improvement and clinical biomarkers of Huanglian Jiedu Wan in the treatment of "excess heat-toxicity" syndrome. An XGBoost classification model based on key clinical biomarkers is successfully established， achieving effective prediction of the symptoms related to the "excess heat-toxicity" syndrome such as oral ulcers and sore throat and providing a new insight for objective identification of traditional Chinese medicine syndromes.

Olfactory receptors (ORs) form the largest superfamily of G protein-coupled receptors (GPCRs). Traditionally recognized for their role in the nasal olfactory epithelium, where they mediate the sense of smell, accumulating evidence has firmly established their ectopic expression in non-olfactory tissues, including the intestine, lungs, and kidneys. The intestine, as the primary site for nutrient digestion and absorption, harbors a highly complex chemical environment. To adapt to this environment, the gut employs a sophisticated network of “chemosensors” to monitor luminal contents and maintain homeostasis. Among these sensors, intestinal ORs have emerged as crucial functional components, serving as a molecular bridge that connects environmental chemical signals—such as food-derived odorants—to specific physiological responses. This discovery has significantly deepened our understanding of how dietary flavors and compounds influence intestinal physiology at the molecular level. This review systematically summarizes the expression profiles, ligand classification, and biological functions of ORs within the gastrointestinal tract. Studies indicate that intestinal ORs exhibit distinct spatial distribution patterns across different gut segments and display cell-type specificity, particularly within enterocytes and enteroendocrine cells. These receptors function as versatile sensors capable of recognizing a wide variety of ligands, including exogenous dietary components, gut microbiota metabolites such as short-chain fatty acids, and endogenous small molecules like azelaic acid. Upon activation by specific ligands, intestinal ORs trigger intracellular signaling cascades, primarily involving the AC-cAMP-PKA pathway or calcium influx channels. A major focus of this review is to elucidate the molecular mechanisms by which these receptors regulate the secretion of gut hormones. Activation of specific ORs in enteroendocrine cells has been shown to stimulate the release of hormones such as glucagon-like peptide-1 (GLP-1), peptide YY (PYY), and serotonin (5-HT), thereby modulating systemic energy metabolism, glucose homeostasis, and gastrointestinal motility. Furthermore, the review addresses the critical roles of ORs in immune regulation and pathology. Evidence suggests that specific ORs contribute to the maintenance of intestinal immune homeostasis and may offer protection against inflammation. Beyond their involvement in inflammatory responses, ORs such as Olfr78 have been shown to regulate the differentiation and function of intestinal endocrine cells. Similarly, Olfr544 has been demonstrated to alleviate intestinal inflammation by remodeling the gut microbiome and metabolome. These findings collectively suggest that specific ORs hold promise as therapeutic targets for mitigating intestinal inflammation and maintaining gut homeostasis. Additionally, the review explores the emerging role of ORs in cancer. Although OR expression is often downregulated in tumor tissues compared to normal mucosa, activation of specific ORs by certain ligands can inhibit tumor cell proliferation and migration and induce apoptosis via pathways such as MEK/ERK and p38 MAPK. Conversely, other receptors, such as OR7C1, may serve as biomarkers for cancer-initiating cells. In conclusion, intestinal ORs represent a vital component of the gut’s sensory network. The review also discusses the translational potential of these findings. By elucidating the precise pairing relationships between dietary components and specific ORs, novel therapeutic strategies could be developed. Intestinal ORs may thus emerge as promising targets for nutritional and pharmacological interventions in metabolic diseases, inflammatory bowel diseases, and malignancies.

Background: Patients with coarctation of the aorta (CoA) and an interrupted aortic arch (IAA) may present with small mitral valves (MVs) and a reduced left ventricular (LV) volume. Biventricular repair (BVR) in these patients is dependent on adequate size of the left cardiac structures.Purpose: This study evaluated the impact of the hemodynamic characteristics of atrial septal defects (ASDs) on MV growth following surgical repair. Methods: We retrospectively reviewed the data of patients diagnosed with CoA or IAA between 2007 and 2024. The z score for MV size measured 6 months postoperatively (Z2) was compared with the preoperative MV size (Z1). The factors associated with MV growth were also studied. Results: A total of 161 patients with CoA or IAA were included. Transthoracic echocardiography was used to assess the MV and LV dimensions preoperatively and 6 months postoperatively. Of the cohort, 155 (96.3%) underwent initial BVR and 6 underwent single-ventricle palliation. MV z scores significantly increased following BVR (mean change: +0.45±1.35; P<0.001) but decreased after single-ventricle repair (-0.56±0.49, P=0.04). Multivariate analysis identified the initial MV z score and ASD pressure gradient as independent predictors of MV growth (R2=0.39). Conclusion Annular growth of the MV was not observed in patients who underwent single-ventricle palliation. In contrast, among patients who achieved BVR, those with a small preoperative MV annulus and low ASD pressure gradient demonstrated subsequent catch-up MV growth, suggesting that adequate left-sided preload is essential for MV development.

Objective To provide a scientific basis for vector prevention and control in port areas, vector monitoring has been conducted continuously to characterize the composition, density, and seasonal fluctuations of vectors across 21 port-areas of Shandong province from 2017 to 2023. Methods In accordance with the Regional Vector Monitoring Plan for Frontier Ports, vector surveillance of mosquitoes, flies, cockroaches, rodents, and other disease vectors was performed. Data were analyzed to describe vector community composition and identify seasonal fluctuations. Results A total of 601 rodents belonging to 1 family, 4 genera, and 4 species were captured. Three dominant rodent species inhabit port areas. In addition, 88 104 mosquitoes were captured and classified into 3 subfamilies, 4 genera, and 12 species; 38 959 flies were trapped and classified into 8 families,31 genera, and 51 species, including 9 dominant fly species in port-areas; and 54 672 captured cockroaches were classified into 2 families,4 genera, and 4 species, with Blattella germanica as the dominant species. Conclusions Significant vector community changes(P＜0.005)have been identified after the epidemic. To improve the pertinence and efficacy of port health quarantine work, continuous and strong attention should be paid to vector compositions and population densities at Shandong ports.

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 mRNA expression profile and clinical significance of the RAB24 gene in hepatocellular carcinoma （HCC） based on multi-source database including The Cancer Genome Atlas （TCGA） and clinical cohort validation. MethodsData from TCGA （n=424） were utilized to evaluate the prognostic value of RAB24 expression via Kaplan-Meier analysis and Cox regression models. An independent clinical cohort comprising 90 HCC and 30 paracancerous tissues was established to validate protein expression and histopathological features through immunohistochemistry （IHC） and routine histological staining. The TIMER database was employed to analyze the association between RAB24 and the tumor microenvironment （TME）. Furthermore， integrated with LinkedOmics， GSEA and GSVA algorithms were used to quantitatively characterize the core molecular pathways regulated by RAB24. ResultsThe mRNA expression level of RAB24 in HCC was significantly higher than that in non-tumor liver tissues （P<0.05）. Kaplan-Meier analysis revealed that the overall survival （OS） of patients in the RAB24 low-expression group was significantly longer compared to the high-expression group （HR=1.570， Log-rank P=0.01）. Cox proportional hazards regression analysis demonstrated that RAB24 expression （HR=1.480， P=0.028）， T stage （HR=2.949， P<0.001）， M stage （HR=4.077， P=0.017）， and tumor residual status （HR=2.317， P<0.001） were independent prognostic factors for HCC. RAB24 expression was highly correlated with alpha-fetoprotein （AFP） levels and immune infiltration levels （P<0.01）， and showed a significant， low-level positive correlation with the TP53 gene （Rho=0.31， P<0.01）. Quantitative analysis of the RAB24 protein in clinical samples validated that RAB24 expression in HCC tissues was significantly elevated compared to non-tumor liver tissues （P<0.05）. TIMER analysis confirmed that RAB24 expression was highly associated with the infiltration of multiple immune cells （such as B cells and NK cells）， as well as stromal and tumor purity scores in tumor tissues （P<0.01）. GSEA/GSVA enrichment revealed that the P53， MYC， and mTORC1 signaling pathways were activated in the RAB24 high-expression group； correlation analysis confirmed that the RAB24 expression level exhibited a significant， low-level positive correlation with the ribosome pathway activity score （r=0.23， P<0.01）. ConclusionsThe RAB24 gene， as a poor prognostic factor for HCC patients， is a potential biomarker for HCC diagnosis， treatment and prognosis. The study is expected to lay a theoretical foundation for the precise diagnosis and treatment of clinical HCC.

ObjectiveTo explore the possible mechanisms of Wenyang Huazhuo Formula （温阳化浊方， WHF） in improving reproductive aging from the perspective of the ovarian mechanical microenvironment. MethodsThe experiment included five groups， 3-month group （20 female mice at 3 months of age）， 6-month group （20 female mice at 6 months of age）， 6-month + WHF group （20 female mice at 5 months of age treated with WHF）， 9-month group （20 female mice at 9 months of age）， and 9-month + WHF group （20 female mice at 8 months of age treated with WHF）. The 6-month + WHF group and 9-month + WHF group were orally administered WHF 41.2 g/（kg·d） once daily for 4 consecutive weeks. The other three groups received no intervention. Reproductive hormone levels were measured by ELISA. HE staining was used to count the numbers of various stages of follicles. Ovarian hyaluronic acid （HA） content and collagen fiber content were measured to evaluate the ovarian mechanical microenvironment. Superovulation was performed to observe the number of eggs obtained， as well as the number of offspring and birth weight to assess fertility. The in vitro fertilization and blastocyst culture of oocytes from female offspring in each group were observed to evaluate the effect of WHF on offspring reproductive potential. ResultsCompared with the 3-month group， the 6-month group and 9-month group showed significantly decreased serum levels of gonadotropin-releasing hormone （GnRH）， follicle-stimulating hormone （FSH）， and luteinizing hormone （LH）， decreased ovarian collagen content， and reduced numbers of primordial and secondary follicles. In contrast， the numbers of primary follicles， antral follicles， and atretic follicles increased. The levels of anti-Müllerian hormone （AMH）， ovarian HA content， and the fertilization rate， cleavage rate， and blastocyst formation rate of oocytes from offspring were significantly lower （P＜0.05）. Compared with the 6-month group， the 6-month + WHF group showed significantly reduced serum levels of GnRH， FSH， and LH， with a significant decrease in primary follicles， antral follicles， and atretic follicles as well as increase of AMH levels， ovarian HA content， number of primordial and secondary follicle， egg count， and offspring birth weight （P＜0.05）. Compared with the 9-month group， the 9-month + WHF group exhibited reduced GnRH， FSH， and collagen fiber content， as well as reduced number of primary follicles， antral follicles， and atretic follicles. However， AMH levels， ovarian HA content， number of primordial and secondary follicle， egg count， offspring numbers， birth weight， fertilization rate， cleavage rate， and blastocyst formation rate of oocytes from offspring all significantly increased （P＜0.05）. ConclusionWHF can significantly improve the ovarian reserve， fertility， and reproductive potential in offspring during reproductive mid-life and late-life stages. Its effect may be related to the remodeling of the mechanical microenvironment of aging ovaries. Moreover， the effect on the mechanical microenvironment remodeling of late-stage ovaries and the improvement of the offspring reproductive potential is more significant.

Aim To investigate the therapeutic effects of corylifol A(CYA)on Lewis lung carcinoma(LLC)cachexia mice and its ameliorating effects on myotube atrophy induced by LLC cell-conditioned medium(LLC CM)in vitro,and to explore the mechanisms.Methods The cancer cachexia was induced by subcu-taneous inoculation of LLC cells to C57BL/6J mice.The effects of CYA(10,20 mg·kg-1·d-1,i.p.)on the cachexia symptoms and survival time of cachexia mice were observed.The effects of 2.5 or 5 μmol·L-1 CYA on myotube atrophy of C2C12 induced by LLC CM were observed.The effects of CYA on its pos-sible target the serine/threonine-protein kinase TAO1(TAOK1)and downstream signaling pathways were detected using Western blot.The influence of TAOK1 knockout on the ameliorating effects of CYA on myo-tube atrophy was observed.Results CYA could sig-nificantly prolong the survival time of tumor-bearing mice and ameliorate the muscle atrophy associated with LLC.The effects of CYA on myotube atrophy are relat-ed to its regulation of TAOK1.The effects of CYA could be reduced by knockout of TAOK1.Conclusions CYA improves the survival of LLC cachexia mice and ameliorates the related skeletal muscle atrophy.The mechanism of CYA is related to its inhibition on TAOK1 and downstream signaling pathways.

AIM To optimize the cellulase-assisted ultrasound extraction process for total flavonoids from Plumbago zeylanica L.,and to evaluate their anti-oxidant activity.METHODS With extraction time,liquid-solid ratio,cellulase addition amount,extraction temperature and ultrasonic power as influencing factors,extraction rate of total flavonoids as an evaluation index,the extraction process was optimized by response surface method on the basis of single factor test.Subsequently,The scavenging rates of extract on DPPH,ABTS and OH free radicals were determined.RESULTS The optimal conditions were determined to be 34∶1 for liquid-solid ratio,3％for cellulase addition amount,51 ℃ for extraction temperature,38 min for extraction time,and 400 W for ultrasonic power,the extraction rate of total flavonoids was(33.411±0.97)％.The IC50 values of three free radicals were 0.13,0.042,3.29 mg/mL,respectively.CONCLUSION This reasonable and reliable method can be used for the cellulase-assisted ultrasound extraction of total flavonoids from P.zeylanica with strong anti-oxidant activity.