Atherosclerosis (AS), the primary pathological contributor to cardiovascular diseases (CVDs), has increasingly affected younger populations due to modern dietary habits and sedentary lifestyles. Current diagnostic modalities, including ultrasound, MRI, and CT, primarily identify advanced lesions and inadequately evaluate plaque vulnerability, thereby hindering early detection. Conventional treatments, which involve long-term medications associated with side effects such as hepatic injury and surgical interventions that carry risks of restenosis and hemorrhage, underscore the urgent need for non-invasive, cost-effective early diagnostic methods and targeted therapies. Gut microbiota metabolites are pivotal in AS pathogenesis, with trimethylamine N-oxide (TMAO) and short-chain fatty acids (SCFAs) serving as functionally opposing biomarkers. TMAO is produced when gut bacteria, specifically Firmicutes and Proteobacteria, metabolize dietary choline and carnitine into trimethylamine (TMA), which the liver subsequently converts to TMAO via flavin-containing monooxygenase 3 (FMO3); TMAO is then excreted in urine. Variability in TMAO levels is influenced by marine food consumption and FMO3 modulation, which can be affected by genetics, age, and diet. Mechanistically, TMAO exacerbates AS by disrupting cholesterol metabolism, inducing endothelial dysfunction through the elevation of reactive oxygen species (ROS) and pro-inflammatory cytokines such as IL-6, and reducing nitric oxide levels. Additionally, TMAO activates NF-κB and NLRP3 pathways while enhancing platelet reactivity. Clinically, elevated TMAO levels correlate with early AS and serve as predictors of mortality in patients with stable coronary artery disease (CAD) and acute coronary syndrome (ACS), as well as major adverse cardiovascular events (MACE) in stroke patients. Conversely, SCFAs—namely acetate, propionate, and butyrate—are produced by gut bacteria such as Akkermansia muciniphila and Faecalibacterium prausnitzii through the fermentation of dietary fiber. These metabolites exert anti-AS effects: acetate aids in maintaining metabolic homeostasis; propionate protects endothelial function and reduces plaque area; and butyrate fortifies intestinal barriers while suppressing inflammation. Furthermore, SCFAs cross-regulate bile acid metabolism, thereby influencing TMAO levels, and antagonize the pro-inflammatory and lipid-disrupting effects of TMAO. The use of TMAO and SCFAs as standalone biomarkers is constrained by limitations. TMAO lacks specificity, while SCFA levels fluctuate based on gut microbiota and dietary intake. Traditional AS risk assessment tools, which include clinical indicators, imaging techniques, and single biomarkers such as CRP, LDL-C, and ASCVD scores, overlook gut metabolism and demonstrate inadequate performance in younger populations. This review advocates for an “antagonistic-complementary” combined strategy: utilizing acetate and TMAO for early AS, propionate and TMAO for progressive AS, and butyrate and TMAO for advanced AS, addressing endothelial dysfunction, lipid deposition, and plaque stability/thrombosis risk, respectively. For clinical application, standardization of detection methods is crucial; liquid chromatography-mass spectrometry (LC-MS) is the gold standard, necessitating a unified sample pretreatment protocol, such as extraction with 1% formic acid in methanol. Additionally, dried blood spots (DBS) facilitate non-invasive testing, provided that dietary controls are implemented prior to detection, including a 12-hour fast and avoidance of high-choline and high-fiber foods. Existing challenges encompass the absence of standardized systems, limited large-scale validation, and ambiguous interactions with conditions such as hypertension. The authors’ team has previously established connections between gut metabolites and AS, including the reduction of TMAO as a preventive measure for AS, thereby reinforcing this proposed strategy. Future research should prioritize standardization, the development of machine learning-optimized models, validation of interventions, and the exploration of multi-omics-based “gut microbiota-metabolite-vascular” networks. In conclusion, the combined detection of TMAO and SCFAs offers a novel framework for AS risk assessment, facilitating early diagnosis and targeted interventions while enhancing the integration of gut metabolism into cardiovascular disease management.

Atherosclerosis (AS), the primary pathological contributor to cardiovascular diseases (CVDs), has increasingly affected younger populations due to modern dietary habits and sedentary lifestyles. Current diagnostic modalities, including ultrasound, MRI, and CT, primarily identify advanced lesions and inadequately evaluate plaque vulnerability, thereby hindering early detection. Conventional treatments, which involve long-term medications associated with side effects such as hepatic injury and surgical interventions that carry risks of restenosis and hemorrhage, underscore the urgent need for non-invasive, cost-effective early diagnostic methods and targeted therapies. Gut microbiota metabolites are pivotal in AS pathogenesis, with trimethylamine N-oxide (TMAO) and short-chain fatty acids (SCFAs) serving as functionally opposing biomarkers. TMAO is produced when gut bacteria, specifically Firmicutes and Proteobacteria, metabolize dietary choline and carnitine into trimethylamine (TMA), which the liver subsequently converts to TMAO via flavin-containing monooxygenase 3 (FMO3); TMAO is then excreted in urine. Variability in TMAO levels is influenced by marine food consumption and FMO3 modulation, which can be affected by genetics, age, and diet. Mechanistically, TMAO exacerbates AS by disrupting cholesterol metabolism, inducing endothelial dysfunction through the elevation of reactive oxygen species (ROS) and pro-inflammatory cytokines such as IL-6, and reducing nitric oxide levels. Additionally, TMAO activates NF-κB and NLRP3 pathways while enhancing platelet reactivity. Clinically, elevated TMAO levels correlate with early AS and serve as predictors of mortality in patients with stable coronary artery disease (CAD) and acute coronary syndrome (ACS), as well as major adverse cardiovascular events (MACE) in stroke patients. Conversely, SCFAs—namely acetate, propionate, and butyrate—are produced by gut bacteria such as Akkermansia muciniphila and Faecalibacterium prausnitzii through the fermentation of dietary fiber. These metabolites exert anti-AS effects: acetate aids in maintaining metabolic homeostasis; propionate protects endothelial function and reduces plaque area; and butyrate fortifies intestinal barriers while suppressing inflammation. Furthermore, SCFAs cross-regulate bile acid metabolism, thereby influencing TMAO levels, and antagonize the pro-inflammatory and lipid-disrupting effects of TMAO. The use of TMAO and SCFAs as standalone biomarkers is constrained by limitations. TMAO lacks specificity, while SCFA levels fluctuate based on gut microbiota and dietary intake. Traditional AS risk assessment tools, which include clinical indicators, imaging techniques, and single biomarkers such as CRP, LDL-C, and ASCVD scores, overlook gut metabolism and demonstrate inadequate performance in younger populations. This review advocates for an “antagonistic-complementary” combined strategy: utilizing acetate and TMAO for early AS, propionate and TMAO for progressive AS, and butyrate and TMAO for advanced AS, addressing endothelial dysfunction, lipid deposition, and plaque stability/thrombosis risk, respectively. For clinical application, standardization of detection methods is crucial; liquid chromatography-mass spectrometry (LC-MS) is the gold standard, necessitating a unified sample pretreatment protocol, such as extraction with 1% formic acid in methanol. Additionally, dried blood spots (DBS) facilitate non-invasive testing, provided that dietary controls are implemented prior to detection, including a 12-hour fast and avoidance of high-choline and high-fiber foods. Existing challenges encompass the absence of standardized systems, limited large-scale validation, and ambiguous interactions with conditions such as hypertension. The authors’ team has previously established connections between gut metabolites and AS, including the reduction of TMAO as a preventive measure for AS, thereby reinforcing this proposed strategy. Future research should prioritize standardization, the development of machine learning-optimized models, validation of interventions, and the exploration of multi-omics-based “gut microbiota-metabolite-vascular” networks. In conclusion, the combined detection of TMAO and SCFAs offers a novel framework for AS risk assessment, facilitating early diagnosis and targeted interventions while enhancing the integration of gut metabolism into cardiovascular disease management.

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.

ObjectiveThis study aims to explore the potential of different orders of magnitude single-nucleotide polymorphism (SNP) locus combinations for predicting distant kinship relationships. A high-density SNP locus set was constructed, and a comprehensive assessment of its inference capability was conducted. MethodsFirstly, we selected three commercial chip panels, CGA (Chinese genotyping array, Illumina), GSA (Global screening array, Illumina), Affy (23MF_V2 high-density SNP array, Affymetrix) and merged them after quality control, forming a high-density SNP locus panel(1 180 k). Secondly, we selected 161 samples and collected their peripheral blood samples by using whole-genome sequencing technology. Within this sample population, the levels of kinship relationships fully covered the range from level 1 to level 9, and the number of kinship pairs at each level was consistently maintained at over 50 pairs. From 161 samples data of whole-genome sequencing, the 1 180 k locus set was extracted, which is referred to as the high-density SNP locus set in the following text. The kinship inference was conducted using the identity-by-descent (IBD) algorithm with the selected optimal parameters. To comprehensively evaluate the performance of the high-density SNP locus set in kinship inference, we compared it with the three commercial chip panels, the intersection of these three chip loci, and the control sets constructed by randomly reducing the number of the high-density SNP locus set. Based on the changes in the IBD lengths, as well as the dynamic trends in prediction accuracy, we conducted a scientific assessment of the kinship inference capability of the high-density SNP locus set. ResultsAfter screening, a set of 1 184 334 autosomal SNPs was obtained. During the process of screening the optimal IBD length threshold, the result revealed that 0 cM, 1 cM, and 2 cM all demonstrated good applicability. However, to avoid the issue of a large amount of redundant information caused by setting a too low IBD length threshold, this study ultimately selected 2 cM as the optimal threshold. Compared with the average results of three chip panels, the high-density SNP locus set increased the total IBD length and the average IBD length across levels 1-9; the accuracy of the confidence interval for level 8 was 70.97%, which represented a 3.50% improvement; the average confidence interval accuracy for levels 1-8 was 91.39%, representing a 1.00% increase; and the false negative rates at levels 8 and 9 were reduced by 2.42% and 6.76%, respectively. The system efficacy of the high-density SNP locus set for kinship inference of first to eighth degree relationships reached 98.91%. Through random reduction of the high-density SNP locus set results, it is found that increasing the number of SNPs with the panel, the detection efficiency of IBD length showed a significant upward trend. At the same time, the overall trend in the accuracy of kinship relationship prediction as well as the confidence interval accuracy also indicated that both metrics steadily increased with the addition of more loci. ConclusionThe results show that the high-density SNPs panel significantly enhances the efficacy of distant kinship inference, accurately covering kinship degrees, with the average confidence interval accuracy for first to eighth degree relationships stably above 90%. The study finds that increasing the number of SNPs panel can improve the ability to predict distant kinship.

Dietary interventions such as fasting are gaining increasing attention for their synergistic effects in anti-tumor therapy, yet the precise underlying mechanisms remain incompletely understood. Recent research has unveiled a novel mode of cell death named “mitoxyperilysis”, providing a fresh perspective on the molecular mechanisms by which fasting may interfere with tumor treatment. This form of death is primarily triggered by the synergy between metabolic dysfunction and innate immune activation. Its mechanism involves the mTORC2 signaling pathway mediating prolonged abnormal contact between damaged mitochondria and the plasma membrane. This leads to massive local release of reactive oxygen species (ROS), which further induces lipid peroxidation of the plasma membrane, ultimately resulting in the physical rupture and death of the cell. The most significant distinction between mitoxyperilysis and classical cell death pathways lies in its independence from caspases and GSDMD. This comment aims to systematically elucidate the process, molecular mechanisms, and differences from other classical cell death pathways of mitoxyperilysis, while also exploring its potential for clinical translation in oncological diseases. Targeting induction of mitoxyperilysis may enhance the efficacy of existing anti-tumor drugs and overcome chemotherapy resistance. However, intervention protocols require further optimization to achieve an optimal balance between safety and therapeutic effectiveness in clinical application.

Objective To systematically review the studies on predictive models for delayed graft function (DGF) after kidney transplantation. Methods Databases including China Biology Medicine Database, China National Knowledge Infrastructure, Wanfang Database, VIP Database, PubMed, Web of Science and CINAHL were searched to collect studies on predictive models for DGF after kidney transplantation published from the establishment of each database to June 29, 2025. Two researchers screened the literatures according to the inclusion and exclusion criteria, evaluated the quality of the literatures using the prediction model risk of bias assessment tool (PROBAST), and conducted a meta-analysis of the common predictors of the models using R software. Results A total of 12 literatures were included, involving 14 predictive models with sample sizes ranging from 103 to 24 653 cases. Donor serum creatinine level, cold ischemia time, donor age and donor body mass index were the top four common predictors. All the predictive models were at high risk of bias and low in applicability. The results of meta-analysis showed that abnormal donor body mass index, advanced donor age, prolonged cold ischemia time and elevated donor serum creatinine level were all associated with an increased risk of DGF after transplantation (all P<0.01), but there was high heterogeneity among the studies. Fixed-effect model and random-effect model were used to re-pool the effect sizes separately. The results indicated that the fixed-effect model and random-effect model had good consistency in terms of donor body mass index, donor age and cold ischemia time, while there was a significant difference in the effect sizes of the two models for donor serum creatinine level. Conclusions The predictive models for DGF risk after kidney transplantation have good predictive performance, but the overall risk of bias is high. In the future, large-sample, multicenter and high-quality prospective clinical studies should be carried out to optimize the predictive models, so as to improve their predictive ability and clinical application value.

Objective To investigate the therapeutic effect of Huangkui capsules on targeted drug-related proteinuria in patients with hepatocellular carcinoma (HCC). Methods A retrospective analysis was conducted on clinical data of HCC patients with targeted drug-related proteinuria from June 2023 to December 2024 at Zhongshan Hospital, Fudan University. According to the treatment plan, patients were divided into the conventional treatment group and the Huangkui combination treatment group (Huangkui capsules combined with conventional treatment), and the clinical efficacy between the two groups was compared. The logistic regression analysis was used to identify the main factors affecting treatment efficacy. Results The Huangkui combination treatment group (n＝29) showed a significantly higher overall effective rate (79.3% vs 42.3%, P＝0.005), and an earlier proteinuria improvement (median time: 3 months vs 6 months, P＝0.008) than the conventional treatment group (n＝26) . The multivariate logistic regression analysis showed angiotensin-converting enzyme inhibitor (ACEI) or angiotensin Ⅱ receptor blocker (ARB) using (OR＝0.190, 95%CI 0.045-0.808, P＝0.025), targeted drug adjustment (OR＝0.132, 95%CI 0.030-0.581, P＝0.007), and Huangkui capsules using (OR＝0.168, 95%CI 0.039-0.730, P＝0.017) were protective factors for treatment efficacy of targeted drug-related proteinuria. Conclusions On the basis of conventional treatment, additive treatment with Huangkui capsules can alleviate targeted drug-related proteinuria faster and more effectively in HCC patients.

A 42-year-old male with chest tightness and dyspnea was admitted to the hospital. Chest CT indicated diffuse interstitial lung infiltration. Despite receiving anti-infective therapy, glucocorticoid therapy, and immunosuppressive agents, the patient developed refractory hypoxaemia. Endotracheal intubation and invasive mechanical ventilation failed to improve oxygenation. Therefore the patient was diagnosed with rapidly progressive interstitial lung disease (RP-ILD) accompanied by type Ⅰ respiratory failure. Veno-venous (VV) extracorporeal membrane oxygenation (ECMO) was initiated, and oxygenation improved in this patient. The patient subsequently underwent bilateral lung transplantation with veno-arterio-venous (VAV) ECMO support. ECMO machine was withdrawn on day 1, and extubation was achieved on day 9 after surgery. Histopathology revealed fibrotic nonspecific interstitial pneumonia (NSIP) with hyaline membrane formation. The patient developed ICU-acquired myasthenia and received early rehabilitation, with gradual recovery of muscle strength. During follow-up, graft lung function remained stable. This case demonstrates that ECMO can serve as a bridge to lung transplantation in RP-ILD patients.

ObjectiveTo evaluate the effect of Ningying Formula （宁瘿方） combined with low-dose antithyroid drugs （ATDs） on the relapse risk for patients with Graves' hyperthyroidism （GH） during the remission phase， and to analyze the related factors between GH relapse and thyrotropin receptor antibody （TRAb） negativity， so as to provide evidence for the standardized management of GH in remission stage. MethodsA single-center retrospective cohort study was conducted， including 269 GH patients in the remission stage. After propensity score matching （PSM）， 102 matched pairs （204 patients） were established. The control group received low-dose ATDs as maintenance therapy， while the exposure group received the core Ningying Formula in addition to low-dose ATDs. The primary outcome was the GH recurrence rate； the secondary outcome was the thyrotropin receptor antibody （TRAb） negativity rate （TRAb＜1.75 IU/L）. Safety outcomes included treatment-related adverse events. Differences between groups were assessed using Cox regression models and Kaplan-Meier curves， with sensitivity analysis performed using inverse probability of treatment weighting （IPTW）. ResultsThe median follow-up in the matched cohort was 28.07 months. Regarding the GH recurrence outcome， the recurrence rate in the exposure group （18/102， 17.6%） was significantly lower than that in the control group （31/102， 30.4%； χ²=4.539， P=0.033）； regarding the TRAb negativity outcome， the TRAb negativity rate in the exposure group （50/102， 49.0%） was significantly higher than that in the control group （23/102， 22.5%； χ²=15.551， P＜0.001）. Multivariate Cox regression analysis for recurrence showed that Ningying Formula treatment reduced the risk of recurrence ［HR=0.324， 95%CI（0.170， 0.617）， P＜0.001］. Male ［HR=2.209， 95%CI（1.079， 4.520）， P=0.030］， higher initial TRAb level ［per 1 IU/L increase： HR=1.033， 95%CI（1.003， 1.064）， P=0.032］， and larger thyroid volume ［per 1 ml increase： HR=1.045， 95%CI（1.003， 1.088）， P=0.035］ were identified as independent risk factors for recurrence； multivariate Cox regression analysis for TRAb negativity indicated that Ningying Formula treatment promoted TRAb negativity ［HR=1.826， 95%CI（1.091， 3.056）， P=0.022］， while a higher initial TRAb level was associated with a lower probability of negativity ［HR=0.974， 95%CI（0.950， 0.998）， P=0.032］. Survival analysis showed significant differences in relapse rate between groups （Log-Rank P=0.003） and in TRAb outcomes （Log-Rank P=0.034）. The incidence of treatment-related adverse events was similar between groups （P=0.757）. The IPTW sensitivity analysis was consistent with the primary analysis， indicating robust results. ConclusionThe Ningying Formula combined with low-dose ATDs can significantly reduce the risk of recurrence and can improve the TRAb negativity rate in GH patients during the remission stage， without increasing common adverse events， making it an optional strategy for reducing relapse risk during remission. Male gender， higher baseline TRAb level， and larger thyroid volume indicate a higher risk of recurrence， warranting focused follow-up and stratified management.

ObjectiveTo investigate the possible mechanism of Jishe Qushi Capsule （脊蛇祛湿胶囊， JQC） in treating rheumatoid arthritis （RA） from the perspective of macrophage polarization mediated by neutrophil extracellular traps （NETs）. MethodsTwenty-four female SD rats were randomly divided into four groups， blank control group， model group， JQC group， and peptidylarginine deiminase 4 （PAD4） inhibitor group with 6 rats in each group. All groups but the blank control group were subjected to the induction of collagen-induced arthritis （CIA）. After successful model establishment， rats in the JQC group received intragastric administration of JQC 1.47 g/kg daily； rats in the PAD4 inhibitor group received intraperitoneal injections of the PAD4 inhibitor 4 mg/kg weekly. Rats in the blank， model， and PAD4 inhibitor groups received 2 ml of pure water daily by gavage. All treatments lasted 4 weeks. Joint lesions of each group were assessed on day 7， 14， 21， 28， and 35 after model establishment， and arthritis index （AI） scores were recorded. At 24 h after the final administration， histopathology of knee joints， including HE staining， safranin O-fast green staining， and TRAP staining， was performed. Flow cytometry was used to detect the counts of M1 and M2 macrophages in peripheral blood. ELISA was used to determine serum levels of TRACP， NETs， TNF-α， IL-1β， and iNOS. Western Blotting and qRT-PCR were used to measure MPO， NE， RANKL， OPG， and p65 protein and mRNA expression in knee cartilage tissue. ResultsCompared with the blank control group， the model group showed increased AI scores （P＜0.05）， marked synovial inflammatory infiltration， angiogenesis， and bone-cartilage destruction， increased TRAP-positive osteoclasts， increased M1 macrophages and decreased M2 macrophages， elevated serum TRACP， NETs， TNF-α， IL-1β， and iNOS （P＜0.05）， elevated MPO， NE， RANKL， and p65 protein/mRNA expression and decreased OPG protein/mRNA expression in knee cartilage tissue （P＜0.05）. Compared with the model group， the JQC group exhibited improved synovial inflammation， angiogenesis， and bone-cartilage damage， reduced AI scores on day 21， 28， and 35， decreased osteoclast counts， decreased M1 macrophages and increased M2 macrophages， reduced serum TRACP， NETs， TNF-α， IL-1β， and iNOS （P＜0.05）， decreased MPO， NE， RANKL， and p65 protein/mRNA expression and increased OPG expression （P＜0.05）. Compared with the PAD4 inhibitor group， the JQC group showed significantly lower AI scores， reduced M1 macrophages， increased M2 macrophages （P＜0.05）， reduced serum TRACP， TNF-α， IL-1β， and iNOS， decreased MPO， RANKL， and p65 expression， and increased OPG levels （P＜0.05）. ConclusionThe therapeutic mechanism of JQC for RA may involve inhibition of NETs formation， downregulation of the RANKL/NF-κB signaling pathway， and regulation of macrophage M1/M2 polarization imbalance， thereby suppressing osteoclastogenesis and inflammatory bone destruction.