Atherosclerosis (AS) remains the core pathological basis underlying the high incidence and high rates of mortality and disability associated with cardiovascular disease (CVD) worldwide. Its essence is not merely lipid deposition, but rather an immune-mediated disease of the vascular wall characterized by an interplay of lipid metabolism disorders and chronic inflammation, with damage to vascular endothelial cells serving as the initiating event. As the disease progresses, it involves complex synergistic interactions among various cellular components, including endothelial cells, macrophages, and inflammatory cells, ultimately leading to plaque formation, instability, and even fatal thrombotic events. In recent years, the central driving role of lipid metabolic reprogramming in the progression of AS has garnered increasing attention from the scientific community. Among the vast array of lipid molecules, long-chain fatty acids (LCFAs) have become a primary focus of research due to their exceptional physiological functions. Traditional views have primarily emphasized the basic physiological functions of LCFAs: serving as highly efficient energy substrates through mitochondrial β-oxidation and acting as key structural components of cellular phospholipid membranes. However, emerging evidence clearly indicates that the functions of LCFAs extend far beyond those of mere metabolic fuel. They also act as potent bioactive signaling molecules, playing an indispensable multidimensional role in the pathogenesis of AS. Equally noteworthy and representing a paradigm shift in cardiovascular research is the emerging theory of the “gut-heart axis”. This theoretical framework views the human gut microbiota—comprising trillions of microorganisms—as a critical and metabolically active “bioreactor”. A wealth of clinical and multi-cohort epidemiological studies have conclusively demonstrated that imbalances in the composition and function of the gut microbiota are highly correlated with the clinical risk and severity of AS. Within this axis, the gut microbiota serves as the primary processing hub for dietary lipids. It actively participates in the digestion and biochemical remodeling of LCFAs, thereby altering their saturation and chemical structure and generating a wide variety of gut microbial metabolites. The effects of these gut-derived lipid metabolites extend far beyond the local intestinal microenvironment. Upon entering the bloodstream, these circulating microbiota metabolites act as endocrine signals. Given the extreme complexity of the underlying mechanisms, a comprehensive elucidation of the synergistic and bidirectional interactions between LCFAs and the gut microbiota in vascular pathology is particularly urgent. Therefore, this article aims to provide a systematic review of the multidimensional regulatory mechanisms of LCFAs and their associated gut microbiota metabolites in the onset, progression, and clinical manifestations of AS. By thoroughly exploring the interaction patterns within the “LCFAs-gut microbiota-AS” triad, this review seeks to fundamentally expand our understanding of the pathogenesis of CVDs. More importantly, translating these mechanistic insights into clinical practice holds tremendous promise. We hope to provide a solid theoretical foundation for the future development of novel AS prevention and treatment strategies based on non-traditional approaches. These include precision nutritional interventions (i.e., dietary lipid intake plans tailored to an individual’s unique microbiome profile) and targeted microbiome modulation therapies (such as next-generation probiotics, prebiotics, or specific metabolite supplements). Targeting the gut as a “reactor” to treat vascular wall lesions represents a promising direction for future cardiovascular medicine.

Objective The aim of the study is to analyze the incidence patterns and epidemiological characteristics of parasitic and vector-borne diseases in the Minhang and Jinshan districts of Shanghai, and provide evidence-based information for optimizing prevention and control measures. Methods We collected information from epidemic reports and epidemiological investigation forms for cases of parasitic and vector-borne diseases from 2005 to 2024 in Shanghai's Minhang and Jinshan districts. Descriptive epidemiological method were adopted to conduct a comparative analysis of incidence trends, epidemic characteristics, and infection sources. Results A total of 229 cases in 7 categories were reported between 2005 and 2024, with an average annual incidence rate of 0.36/100 000. The average annual incidence rate in Minhang District was significantly higher than that in Jinshan District. The most prevalent diseases were malaria and dengue fever, followed by Japanese encephalitis. Monthly case reports were available, predominantly from June to October, with a peak in July-August. A statistically significant difference was observed between the two districts in case distribution during June-October (P＜0.001), whereas no significant difference was found for July-August (P=0.331). The majority of cases were young men (111/229,48.47%), aged 20-39 years. Migrant workers/farmers constituted the largest occupational group (55/229, 24.02%). Registered residents of other provinces and cities (147/229,64.19%), and the main source of infection was overseas importation (112/229,48.91%). There were no statistically significant differences in gender and household-registration composition between the two districts (P＞0.05). Significant differences existed in age, occupation, and source of infection (P＜0.05). The imported diseases were malaria and dengue fever, with Africa and Southeast Asia being the primary source locations. Malaria was the predominant disease imported from other provinces and cities, with cases having been imported from abroad since 2012. Local infections were mainly Japanese encephalitis, followed by malaria (with the last local case reported in 2010). Cases between 2005 and 2009 were predominantly imported from other provinces and cities. The proportion of cases imported from abroad increased sharply after 2010, particularly in Minhang District. Local infections sometimes arise in Jinshan District, with Japanese encephalitis serving as the primary type. Conclusions Incidence rates of parasitic and vector-borne diseases in Minhang and Jinshan districts have generally remained low. To further reduce this disease burden, it will be necessary to strengthen joint measures for prevention and control, eliminate the environmental risk factors of vector organisms, enhance monitoring and precise control of the environment and inbound personnel to prevent the occurrence and transmission of parasitic and vector-borne diseases.

Tumor angiogenesis is a core pathological driver of malignant growth, invasion, and metastasis, and represents a major obstacle to effective anticancer therapy. Conventional antiangiogenic agents, including neutralizing monoclonal antibodies and small-molecule tyrosine kinase inhibitors, are constrained by drug resistance, on-target toxicity, and the compensatory activation of alternative pro-angiogenic pathways. Targeted protein degradation (TPD) has emerged as a promising strategy that may overcome these limitations. Unlike traditional inhibitors that operate through an occupancy-driven mechanism, degraders function through an event-driven catalytic mechanism in which a single degrader molecule can catalytically promote the ubiquitination and subsequent proteasomal or lysosomal degradation of multiple molecules of the same target protein, thereby eliminating the target protein together with all of its functions rather than merely blocking a single active site. This review systematically delineates the pathophysiological basis of tumor angiogenesis, encompassing the angiogenic switch driven by hypoxia-inducible factor-1α (HIF-1α), the aberrant structural and functional features of the tumor vasculature, and the self-reinforcing vicious cycles that sustain malignant progression. We then categorize the principal TPD modalities, with particular emphasis on proteolysis-targeting chimeras (PROTACs) and lysosome-targeting chimeras (LYTACs), and describe their design principles and mechanisms of action. PROTACs recruit E3 ubiquitin ligases to direct intracellular targets to the ubiquitin-proteasome system for degradation, whereas LYTACs engage lysosome-targeting receptors to route extracellular and membrane proteins to the lysosome, thereby expanding the degradable target space beyond the intracellular proteome. We further summarize recent advances in the application of TPD to antiangiogenic intervention at four distinct levels. First, at the signaling initiation level, degradation of vascular endothelial growth factor (VEGF) and its receptor vascular endothelial growth factor receptor 2 (VEGFR2) by aptamer-engineered PROTACs, antibody-based LYTACs, and small-molecule VEGFR2 degraders blocks the upstream trigger of the angiogenic cascade. Second, at the signal transduction level, degradation of focal adhesion kinase (FAK), B-Raf proto-oncogene serine/threonine kinase (BRAF), phosphodiesterase 4 (PDE4), and bromodomain-containing protein 4 (BRD4) interrupts intracellular signaling cascades and transcriptional responses. Third, at the microenvironment level, degradation of proviral integration site for Moloney murine leukemia virus (PIM) kinases curtails the pro-angiogenic signals secreted by tumor-associated macrophages. Fourth, multi-target synergistic strategies, exemplified by bispecific degraders that simultaneously target human epidermal growth factor receptor 2 (HER2) and VEGF-A, represent a preliminary exploration of cooperative intervention. Representative degraders reviewed herein elicit diverse antiangiogenic phenotypes, ranging from the direct inhibition of endothelial cell proliferation, migration, and tube formation to reductions in microvessel density and the suppression of vasculogenic mimicry. Finally, we discuss the major challenges that remain, including the precise matching of degradation kinetics with the vascular normalization window, target selectivity and tissue specificity, and the activation of compensatory networks and the emergence of resistance. Since the application of TPD in this setting remains at an early stage, the clinical translation of these approaches will require careful optimization of degradation efficiency, spatiotemporal control, and delivery strategies. We also envision future directions toward immunotherapy-based combination regimens and precision-degradation approaches guided by single-cell and spatial transcriptomics. In our view, TPD should not be regarded merely as a substitute for conventional antiangiogenic drugs, but rather as a molecular tool capable of systematically remodeling the tumor vascular microenvironment. When precise control of degradation efficiency and spatiotemporal regulation are integrated with a thorough understanding of the heterogeneity and compensatory capacity of tumor vessels, the full clinical potential of this strategy can be realized.

ObjectiveTransfer RNA-derived fragments (tRFs) are a recently characterized and rapidly expanding class of small non-coding RNAs, typically ranging from 13 to 50 nucleotides in length. They are derived from mature or precursor tRNA molecules through specific cleavage events and have been implicated in a wide range of cellular processes. Increasing evidence indicates that tRFs play important regulatory roles in gene expression, primarily by interacting with target messenger RNAs (mRNAs) to induce transcript degradation, in a manner partially analogous to microRNAs (miRNAs). However, despite their emerging biological relevance and potential roles in disease mechanisms, there remains a significant lack of computational tools capable of systematically predicting the interaction landscape between tRFs and their target mRNAs. Existing databases often rely on limited interaction features and lack the flexibility to accommodate novel or user-defined tRF sequences. The primary goal of this study was to develop a machine learning based prediction algorithm that enables high-throughput, accurate identification of tRF:mRNA binding events, thereby facilitating the functional analysis of tRF regulatory networks. MethodsWe began by assembling a manually curated dataset of 38 687 experimentally verified tRF:mRNA interaction pairs and extracting seven biologically informed features for each pair: (1) AU content of the binding site, (2) site pairing status, (3) binding region location, (4) number of binding sites per mRNA, (5) length of the longest consecutive complementary stretch, (6) total binding region length, and (7) seed sequence complementarity. Using this dataset and feature set, we trained 4 distinct machine learning classifiers—logistic regression, random forest, decision tree, and a multilayer perceptron (MLP)—to compare their ability to discriminate true interactions from non-interactions. Each model’s performance was evaluated using overall accuracy, receiver operating characteristic (ROC) curves, and the corresponding area under the ROC curve (AUC). The MLP consistently achieved the highest AUC among the four, and was therefore selected as the backbone of our prediction framework, which we named tRF Prospect. For biological validation, we retrieved 3 high-throughput RNA-seq datasets from the gene expression omnibus (GEO) in which individual tRFs were overexpressed: AS-tDR-007333 (GSE184690), tRF-3004b (GSE197091), and tRF-20-S998LO9D (GSE208381). Differential expression analysis of each dataset identified genes downregulated upon tRF overexpression, which we designated as putative targets. We then compared the predictions generated by tRF Prospect against those from three established tools—tRFTar, tRForest, and tRFTarget—by quantifying the number of predicted targets for each tRF and assessing concordance with the experimentally derived gene sets. ResultsThe proposed algorithm achieved high predictive accuracy, with an AUC of 0.934. Functional validation was conducted using transcriptome-wide RNA-seq datasets from cells overexpressing specific tRFs, confirming the model’s ability to accurately predict biologically relevant downregulation of mRNA targets. When benchmarked against established tools such as tRFTar, tRForest, and tRFTarget, tRF Prospect consistently demonstrated superior performance, both in terms of predictive precision and sensitivity, as well as in identifying a higher number of true-positive interactions. Moreover, unlike static databases that are limited to precomputed results, tRF Prospect supports real-time prediction for any user-defined tRF sequence, enhancing its applicability in exploratory and hypothesis-driven research. ConclusionThis study introduces tRF Prospect as a powerful and flexible computational tool for investigating tRF:mRNA interactions. By leveraging the predictive strength of deep learning and incorporating a broad spectrum of interaction-relevant features, it addresses key limitations of existing platforms. Specifically, tRF Prospect: (1) expands the range of detectable tRF and target types; (2) improves prediction accuracy through multilayer perceptron model; and (3) allows for dynamic, user-driven analysis beyond database constraints. Although the current version emphasizes miRNA-like repression mechanisms and faces challenges in accurately capturing 5'UTR-associated binding events, it nonetheless provides a critical foundation for future studies aiming to unravel the complex roles of tRFs in gene regulation, cellular function, and disease pathogenesis.

Objective To clarify the risk factors of diaphragmatic dysfunction (DD) after cardiac surgery with extracorporeal circulation. Methods A retrospective analysis was conducted on the data of patients who underwent cardiac surgery with extracorporeal circulation in the Department of Cardiovascular Surgery of Peking University People's Hospital from January 2023 to March 2024. Patients were divided into two groups according to the results of bedside diaphragm ultrasound: a DD group and a control group. The preoperative, intraoperative, and postoperative indicators of the patients were compared and analyzed, and independent risk factors for DD were screened using multivariate logistic regression analysis. Results A total of 281 patients were included, with 32 patients in the DD group, including 23 males and 9 females, with an average age of (64.0±13.5) years. There were 249 patients in the control group, including 189 males and 60 females, with an average age of (58.0±11.2) years. The body mass index of the DD group was lower than that of the control group [(18.4±1.5) kg/m2 vs. (21.9±1.8) kg/m2, P=0.004], and the prevalence of hypertension, chronic obstructive pulmonary disease, heart failure, and renal insufficiency was higher in the DD group (P<0.05). There was no statistical difference in intraoperative indicators (operation method, extracorporeal circulation time, aortic clamping time, and intraoperative nasopharyngeal temperature) between the two groups (P>0.05). In terms of postoperative aspects, the peak postoperative blood glucose in the DD group was significantly higher than that in the control group (P=0.001), and the proportion of patients requiring continuous renal replacement therapy was significantly higher than that in the control group (P=0.001). The postoperative reintubation rate, tracheotomy rate, mechanical ventilation time, and intensive care unit stay time in the DD group were higher or longer than those in the control group (P<0.05). Multivariate logistic regression analysis showed that low body mass index [OR=0.72, 95%CI (0.41, 0.88), P=0.011], preoperative dialysis [OR=2.51, 95%CI (1.89, 4.14), P=0.027], low left ventricular ejection fraction [OR=0.88, 95%CI (0.71, 0.93), P=0.046], and postoperative hyperglycemia [OR=3.27, 95%CI (2.58, 5.32), P=0.009] were independent risk factors for DD. Conclusion The incidence of DD is relatively high after cardiac surgery, and low body mass index, preoperative renal insufficiency requiring dialysis, low left ventricular ejection fraction, and postoperative hyperglycemia are risk factors for DD.

Cardiovascular diseases (CVDs) are the leading cause of death worldwide. Nicotinamide adenine dinucleotide (NAD⁺) is a central and pleiotropic metabolite involved in multiple cellular energy metabolism, such as cell signaling, DNA repair, protein modifications, and so on. Evidence suggests that NAD⁺ levels decline with age, obesity, and hypertension, which are all significant CVD risk factors. In addition, the therapeutic elevation of NAD⁺ levels reduces chronic low-grade inflammation, reactivates autophagy and mitochondrial biogenesis, and enhances antioxidation and metabolism in vascular cells of humans with vascular disorders. In preclinical animal models, NAD⁺ boosting also extends the health span, prevents metabolic syndrome, and decreases blood pressure. Moreover, NAD⁺ storage by genetic, pharmacological, or natural dietary NAD⁺-increasing strategies has recently been shown to be effective in improving the pathophysiology of cardiac and vascular health in different animal models and humans. Here, we discuss NAD⁺-related mechanisms pivotal for vascular health and summarize recent research on NAD⁺ and its association with vascular health and disease, including hypertension, atherosclerosis, and coronary artery disease. This review also assesses various NAD⁺ precursors for their clinical efficacy and the efficiency of NAD⁺ elevation in the prevention or treatment of major CVDs, potentially guiding new therapeutic strategies.
Humans ; Cardiovascular Diseases/physiopathology* ; NAD/metabolism* ; Animals ; Hypertension/metabolism*

This paper aimed to explore the effects of Duzhong Decoction(DZD)-containing serum on the proliferation and osteoblast differentiation of MC3T3-E1 cells through L-type voltage-gated calcium channels(L-VGCCs). L-VGCCs inhibitors, nifedipine and verapamil, were used to block L-VGCCs in osteoblasts. MC3T3-E1 cells were divided into a control group, a low-dose DZD-containing serum(L-DZD) group, a medium-dose DZD-containing serum(M-DZD) group, a high-dose DZD-containing serum(H-DZD) group, a nifedipine group, a H-DZD + nifedipine group, verapamil group, and a H-DZD + verapamil group. The CCK-8 method was used for cell proliferation analysis, alkaline phosphatase(ALP) assay kits for intracellular ALP activity measurement, Western blot for protein expression level in cells, real-time fluorescence quantitative PCR technology for intracellular mRNA expression level determination, fluorescence spectrophotometer for free Ca~(2+) concentration determination in osteoblasts, and alizarin red staining(ARS) for mineralized nodule formation in osteoblasts. The experimental results show that compared to the control group, DZD groups can promote MC3T3-E1 cell proliferation, ALP activity, and mineralized nodule formation, increase intracellular Ca~(2+) concentrations, and upregulate the protein expression of bone morphogenetic protein 2(BMP2), collagen Ⅰ(COL1), α2 subunit protein of L-VGCCs(L-VGCCα2), and the mRNA expression of Runt-related transcription factor 2(RUNX2), and BMP2. After blocking L-VGCCs with nifedipine and verapamil, the intervention effects of DZD-containing serum were inhibited to varying degrees. Both nifedipine and verapamil could inhibit ALP activity, reduce mineralized nodule areas, and downregulate the expression of bone formation-related proteins. Moreover, the effects of DZD-containing serum on increasing MC3T3-E1 cell proliferation, osteoblast differentiation, and Ca~(2+) concentrations, upregulating the mRNA expression of osteoprotegerin(OPG) and protein expression of phosphorylated protein kinase B(p-Akt) and phosphorylated forkhead box protein O1(p-FOXO1), and upregulating phosphatase and tensin homolog(PTEN) expression were reversed by nifedipine. The results indicate that DZD-containing serum can increase the Ca~(2+) concentration in MC3T3-E1 cells to promote bone formation, which may be mediated by L-VGCCs and the PTEN/Akt/FoxO1 signaling pathway, providing a new perspective on the mechanism of DZD in treating osteoporosis.
Animals ; Osteoblasts/metabolism* ; Cell Proliferation/drug effects* ; Cell Differentiation/drug effects* ; Mice ; Drugs, Chinese Herbal/pharmacology* ; Calcium Channels, L-Type/genetics* ; Alkaline Phosphatase/genetics* ; Serum/chemistry* ; Cell Line ; Osteogenesis/drug effects* ; Bone Morphogenetic Protein 2/genetics*

Emodin is a hydroxyanthraquinone compound that is widely distributed and has multiple pharmacological activities, including anti-diarrheal, anti-inflammatory, and liver-protective effects. Research indicates that emodin may be one of the main components responsible for inducing hepatotoxicity. However, studies on the mechanisms of liver injury are relatively limited, particularly those related to bile acids(BAs) metabolism. This study aims to systematically investigate the effects of different dosages of emodin on BAs metabolism, providing a basis for the safe clinical use of traditional Chinese medicine(TCM)containing emodin. First, this study evaluated the safety of repeated administration of different dosages of emodin over a 5-week period, with a particular focus on its impact on the liver. Next, the composition and content of BAs in serum and liver were analyzed. Subsequently, qRT-PCR was used to detect the mRNA expression of nuclear receptors and transporters related to BAs metabolism. The results showed that 1 g·kg~(-1) emodin induced hepatic damage, with bile duct hyperplasia as the primary pathological manifestation. It significantly increased the levels of various BAs in the serum and primary BAs(including taurine-conjugated and free BAs) in the liver. Additionally, it downregulated the mRNA expression of farnesoid X receptor(FXR), retinoid X receptor(RXR), and sodium taurocholate cotransporting polypeptide(NTCP), and upregulated the mRNA expression of cholesterol 7α-hydroxylase(CYP7A1) in the liver. Although 0.01 g·kg~(-1) and 0.03 g·kg~(-1) emodin did not induce obvious liver injury, they significantly increased the level of taurine-conjugated BAs in the liver, suggesting a potential interference with BAs homeostasis. In conclusion, 1 g·kg~(-1) emodin may promote the production of primary BAs in the liver by affecting the FXR-RXR-CYP7A1 pathway, inhibit NTCP expression, and reduce BA reabsorption in the liver, resulting in BA accumulation in the peripheral blood. This disruption of BA homeostasis leads to liver injury. Even doses of emodin close to the clinical dose can also have a certain effect on the homeostasis of BAs. Therefore, when using traditional Chinese medicine or formulas containing emodin in clinical practice, it is necessary to regularly monitor liver function indicators and closely monitor the risk of drug-induced liver injury.
Emodin/administration & dosage* ; Bile Acids and Salts/metabolism* ; Animals ; Male ; Liver/injuries* ; Chemical and Drug Induced Liver Injury/genetics* ; Drugs, Chinese Herbal/adverse effects* ; Humans ; Rats, Sprague-Dawley ; Mice ; Rats

Objective To investigate the genetic differences among different populations based on 13 autosomal STR loci in CODIS core.Methods Data of 13 autosomal STR loci(CSF1PO,FGA,THO1,TPOX,vWA,D3S1358,D5S818,D7S820,D8S1179,D13S317,D16S539,D18S51,D21S11)were collected from 95 populations in scientific journals between 1999 and 2021,soursed from the PubMed database,which had been published.Allele frequencies of loci were sorted out and forensic genetic parameters including gene differentiation coefficient(Gst),total heterozygosity(Ht),subpopula-tion heterozygosity(Hs)values,and Nei's DA genetic distance were calculated.Principal component analysis,phylogenetic tree,and multidimensional scale analysis were conducted to assess population ge-netic structure.Results A total of 265 alleles were detected at the 13 STR loci in these 95 popula-tions.The mean values of Gst,Ht,and Hs were 0.023 247,0.797 915 and 0.779 365.Population genetic analyses reflected significant differences among populations from Asia,Africa and Europe.In Asian populations,there was a certain degree of distinction between mainland and island populations;the Han population showed a certain degree of distinction with surrounding populations in mainland;while within the Han population,there were two distinct clusters formed by the northern Han and the south-ern Han.Conclusion The 13 autosomal STR loci in CODIS core demonstrate potential value for popu-lation identification across different groups,and may be used for the differentiation of ethnic groups,among different continental populations.

Objective To explore the relationship between dynamic contrast-enhanced magnetic resonance imaging(DCE-MRI)and clinical pathological features of invasive breast cancer and lymphovascular invasion(LVI).Methods Imaging and clinical pathological data were retrospectively collected from 508 patients with invasive breast cancer who underwent breast DCE-MRI at the First Medical Center of Chinese PLA General Hospital from January 2019 to August 2021.Patients were divided into the LVI-positive(LVI+)group(n=79)and LVI-negative(LVI-)group(n=429)based on postoperative pathological results.Univariate and multivariate logistic regression analyses were used to identify risk factors for LVI.Results Compared with LVI-group,LVI+group had a higher proportion of patients aged<45 years(44.3%vs.27.0%,P=0.002),non-mass-like enhancement(NME)(31.7%vs.17.7%,P=0.004),Ki-67 expression rate(40.0%vs.30.0%,P<0.001),high Ki-67 expression(94.9%vs.78.1%,P=0.001),Luminal B subtype(76.0%vs.60.1%,P=0.008),and positive axillary lymph nodes rate(72.2%vs.31.5%,P<0.001),while the proportion of Luminal A subtype was lower(2.5%vs.21.5%,P<0.001).Univariate and multivariate logistic regression analyses showed that age≥45 years(OR=0.468,95%CI 0.280-0.783,P=0.004)was an independent protective factor for LVI,while NME(OR=1.987,95%CI 1.126-3.444,P=0.016)was an independent risk factor.Compared with Luminal A subtype,patients with Luminal B subtype(OR=10.482,95%CI 3.164-64.923,P=0.001),HER-2 overexpression subtype(OR=11.571,95%CI 2.755-79.341,P=0.003)and triple-negative subtypes(OR=8.433,95%CI 1.985-57.908,P=0.009)had a higher risk of LVI.Conclusions Age≥45 years is an independent protective factor for LVI,while NME is an independent risk factor.Among molecular subtypes,patients with Luminal B,HER-2 overexpression and triple-negative subtypes have a higher risk of LVI compared with the Luminal A subtype.