Atherosclerosis （AS） is a chronic and inflammatory vascular disease. Macrophages are common immune cells and play an important role in the development of AS. In recent years， research has found that the formation of AS plaques is closely related to pathological and physiological processes such as macrophage polarization， energy metabolism， and lipid phagocytosis. This review aims to summarize the mechanism of macrophages in the development of AS， and to explore potential therapeutic methods for delaying AS by regulating macrophages， providing new ideas for the treatment and research of AS.

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.

p21 (encoded by the CDKN1A gene) is a critical cell cycle regulatory protein endowed with versatile biological functions. In various sex hormone-related cancers, p21 exhibits a paradoxical dual role, capable of both inhibiting tumorigenesis and promoting cancer progression, exerting dual, often opposing, effects on cellular fate that are dictated by the specific context. The clinical targeting of p21 remains elusive, largely due to its functionally pleiotropic and context-dependent nature within intricate regulatory networks. During the initial, hormone-dependent phase of cancers like breast and prostate cancer, p21 expression and activity are largely governed by the transcriptional programs of estrogen or androgen receptor signaling. This hormonal regulation contributes to the control of tumor cell proliferation and underpins the initial efficacy of endocrine therapies. In contrast, as these diseases advance to late stages or evolve into non-hormone-dependent subtypes—exemplified by castration-resistant prostate cancer (CRPC) and specific forms of triple-negative breast cancer (TNBC)—these conventional hormonal control mechanisms often become dysfunctional or are entirely bypassed. This fundamental transition creates a critical therapeutic void, highlighting the urgent need to identify and exploit alternative molecular pathways to effectively target p21’s function. Promising strategies may include the precise modulation of its upstream transcriptional regulators, downstream effector proteins, or the intersecting parallel signaling networks that critically influence its activity. This review provides a systematic synthesis of the intricate and interconnected mechanisms that underpin the dual effects of p21 in sex hormone-related tumors. These mechanisms are categorized into three core, interrelated functional domains. (1) cell cycle regulation: p21 executes its canonical tumor-suppressive role by binding to and inhibiting cyclin-dependent kinases (CDKs) and by directly interacting with proliferating cell nuclear antigen (PCNA), thereby inducing cell cycle arrest, predominantly at the G1/S checkpoint; (2) apoptosis modulation: p21 exerts a highly context-dependent influence on programmed cell death, functioning either as a pro-apoptotic agent under severe genotoxic stress or as a pro-survival factor by inhibiting apoptosis through interactions with proteins like Bcl-2; (3) hormonal and signaling crosstalk: p21 is an integral node within broader cellular networks, engaging in direct physical interactions with hormone receptors(e.g., AR, ER) and participating in complex feedback loops with key oncogenic pathways, including PI3K/AKT, MAPK/ERK, and p53. Critically, the role of p21 is not static but highly dynamic. It can undergo a functional switch from tumor-suppressive to tumor-promoting in response to therapeutic pressures, metabolic alterations, or evolving tumor microenvironment cues. These adaptive shifts are frequently implicated in the development of therapy resistance and disease recurrence, particularly in advanced, hormone-resistant cancers. By synthesizing these insights, this review aims to establish a coherent theoretical framework to guide the future development of novel therapeutic strategies that target the p21 pathway. It underscores the necessity of moving beyond a simplistic, binary view of p21 and emphasizes the forthcoming challenges, such as the discovery of reliable biomarkers to predict its functional state and the rational design of context-specific pharmacological modulators to selectively harness its therapeutic potential.

In this study,a sensitive lateral flow immunoassay(LFIA)platform based on carbon dots-mesoporous silica nanocomposite(CD-MSNs)fluorescent probes was constructed for high-performance detection of inflammatory marker interleukin-6(IL-6).Green fluorescent carbon dots(CDs)were prepared by hydrothermal method with 3,9-perylenic acid and 3-aminopropyltriethoxysilane(APTES)as raw materials,and highly fluorescent CD-MSNs composites were then constructed by encapsulating the prepared CDs in mesoporous silica nanoparticles(MSNs).Fluorescent probes were prepared by covalent coupling of CD-MSNs with IL-6 antibody.Fluorescent immunochromatographic test strips were constructed by spraying IL-6 capture antibody and goat anti-mouse IgG on nitrocellulose membrane as detection line(T-line)and quality control line(C-line),respectively.The fluorescence immunoassay analyzer was used to quantitatively detect the fluorescence intensity of T-line,and the experimental results showed that the LFIA platform based on this probe had a good linear relationship in IL-6 concentration range of 102-106 pg/mL,and the detection limit was 64 pg/mL,which was two orders of magnitude more sensitive than that of the traditional colloidal gold test strips.This method effectively solved the issue of insufficient sensitivity of traditional LFIA technique,and provided a rapid and highly sensitive detection method for early diagnosis of inflammatory diseases.

Lentiviral vectors(LVs)are key gene delivery tools for integrating target genes into the host genome,but they may also pose risks of insertional mutagenesis.The vector copy number(VCN)in cells is critical for determining the safety of gene modification.However,the reliability and accuracy of its quantification process are influenced by multiple factors.Developing cell reference materials with specific vector copy numbers represents a viable approach to enhance the reliability and consistency of measurement results,enabling quality control of the quantification process and traceability of outcomes.However,the preparation of such reference materials faces challenges in cell sample design,preparation protocols,and advanced quantification techniques.In this study,T lymphocyte cell line Jurkat-based reference materials with LV gene copy numbers of 1 and 2 copy/cell were developed.A high-precision duplex digital polymerase chain reaction(dPCR)method was established to quantify the LV gene and endogenous genes simultaneously.Additionally,the results of dPCR were cross-validated through next-generation sequencing and flow cytometric analysis.Ultimately,confocal microscopy characterization results showed that the developed cell reference materials had intact morphology.The quantification result of VCN-1 was(1.07±0.11)copy/cell,and that of VCN-2 was(2.09±0.21)copy/cell.These cell reference materials demonstrated compliance with stability and homogeneity requirements,and could be applied for quality control throughout the VCN measurement workflow and metrological traceability,improving the accuracy,comparability,and validity of copy number measurements.

Given the increasing concern regarding antibacterial resistance, the antimicrobial properties of naphthoquinones have recently attracted significant attention. While 1,4-naphthoquinone and its derivatives have been extensively studied, the antibacterial properties of 5,8-dihydroxy-1,4-naphthoquinone derivatives remain relatively unexplored. This study presents a comprehensive in vitro and in vivo analysis of the antibacterial activity of 35 naturally sourced and chemically synthesized derivatives of 5,8-dihydroxy-1,4-naphthoquinone. Kirby-Bauer antibiotic testing identified three compounds with activity against methicillin-resistant Staphylococcus aureus (MRSA), with one compound (PNP-02) demonstrating activity comparable to vancomycin in minimum inhibitory concentration, minimum bactericidal concentration (MBC), and time-kill assays. Microscopic and biochemical analyses revealed that PNP-02 adversely affects the cell wall and cell membrane of MRSA. Mechanistic investigations, including proteomic sequencing analyses, Western blotting, and RT-qPCR assays, indicated that PNP-02 compromises cell membrane integrity by inhibiting arginine biosynthesis and pyrimidine metabolism pathways, thereby increasing membrane permeability and inducing bacterial death. In an in vivo mouse model of skin wound healing, PNP-02 exhibited antibacterial efficacy similar to vancomycin. The compound demonstrated low toxicity to cultured human cells and in hemolysis assays and remained stable during serum incubation. These findings suggest that PNP-02 possesses promising bioactivity against MRSA and represents a potential novel antibacterial agent.
Methicillin-Resistant Staphylococcus aureus/genetics* ; Anti-Bacterial Agents/chemistry* ; Naphthoquinones/administration & dosage* ; Animals ; Microbial Sensitivity Tests ; Mice ; Humans ; Staphylococcal Infections/microbiology* ; Molecular Structure

Inflammatory response,immunosuppression,and drug sensitivity have been reported to have a significant correlation with the disulfidptosis levels in cancer patients.However,the value of disulfidpto-sis in colorectal cancer therapy remains unclear.Therefore,we classified the CRC cells into different cell types using single-cell sequencing data and cell-specific markers and analyzed their relationship with the cell disulfidptosis level.We found that the high disulfidptosis regions were concentrated in epithelial-like CRC cells.Further exploration using the disulfidptosis and programmed cell death 1 inhibitor therapy treated differential expression genes indicated that CRC patients with high disulfidptosis levels exhibited a lower risk profile and increased sensitivity to immunotherapy.By using the spatial transcriptomic analy-sis,we found that ubiquinol-cytochrome c reductase core protein 1(UQCRC1),a disulfidptosis-related gene,is highly expressed in epithelial-like CRC cells and co-localized with immune-infiltrated tumor re-gions.Additional bioinformatic analyses and experimental validation further confirmed that UQCRC1 was downregulated in CRC tissues.Overexpression of UQCRC1 suppressed CRC cell proliferation and migra-tion.These findings indicate that UQCRC1 is a potential target for CRC diagnosis and treatment.

Copy number variation encompassing SNP plays an important role in IVD and precision medi-cine.As the most commonly used method,FISH could not overcome the probe cross-reactivity which is common when to detect SNP.Here we developed a quantitative and qualitative method on copy number variation encompassing SNP.In this study,the rs76711854 was used as an example to establish a quanti-tative method by advantage of probe cross-reactivity.The fragment encompassing rs76711854 and its downstream to 9 514 bp were amplified by PCR.The allelic genotypes were verified by Sanger sequen-cing.Different probes with or without cross-reactivity to be used via quantitative real-time PCR and digit-al PCR.The different clusters(2D)and fluorescence intensity layers(1D)exist by adding probe with cross-reactivity.The A/G ratio measured by digital PCR is 2︰1,which is verified by probe targeting to the SNP.The copy-number variant exists in the 9kb-long fragment upstream to the SNP of prostate cancer cell line but not in human endometrial adenocarcinoma cell line Ishikawa.The data suggest that there is a multi-copy variation at this locus in DU145 cells.The method applied here is based on one single cross-reactivity probe via digital PCR.