Drug recommendation that aims to provide a prescription for a patient is an essential task in healthcare. Drug molecular graphs provide valuable support for drug recommendation. Existing methods tend to overlook drugs' molecular graphs or use the core substructures of molecular graphs with a rule-based segmentation strategy. However, such methods have several limitations: (1) The rule-based segmentation strategy is inflexible and sub-optimal for extremely complex scenarios. (2) The core substructures derived only consider the drug's chemical characteristics and ignore the patient's health condition. (3) The spurious correlation brought by trivial substructures is disregarded. To address these limitations, we design a novel drug recommendation method from a causal perspective, where a conditional causal representation learner for drug recommendation is proposed. Specifically, we first separate the drug molecular representation into causal and spurious parts depending on various patients' health conditions. Then, we eliminate the spurious correlation caused by the spurious part with causal intervention. Extensive experiments on the MIMIC-III and MIMIC-IV datasets demonstrate that our approach achieves new state-of-the-art performance (e.g., 6.68% Jaccard improvements on MIMIC-III with p-value 0.05).

Introduction: Left ventricular systolic dysfunction (LVSD) is associated with poor health outcomes. Previous study has demonstrated the effectiveness of electromechanical activation time (EMAT) derived from phonocardiography (PCG) and electrocardiography (ECG) signals in identifying LVSD. However, high throughput and well-performed algorithm is needed in automatically detecting LVSD. Hypothesis: An artificial intelligence (AI) algorithm was developed and validated in detecting LVSD. Methods: Using ECG and PCG data collected by wearable patch from 1020 admitted patients in Ruijin hospital, we trained an AI algorithm to detect the LVSD, which was determined by ejection fraction <50% from echocardiogram. A separate 590 patients were taken as independent test set. The AI algorithm followed a two-step detection structure, where the first step is to use LSTM learning to quantify heartbeat and heartbeat interval in ECG, and the second step is to apply convolution neural network (CNN) in estimating optimal EMAT cutoff points in detecting LVSD. To overcome the challenge of multi-modal signal training, we develop an alignment-based contrastive learning approach that generates shared feature space embeddings for ECG and PCG signals. Results: Among training and test sets, 18.2% and 26.1% were LVSD, respectively. The AI algorithm yields an AUROC of 0.92 in detecting LVSD with sensitivity of 85.63%, and specificity of 79.39%. Among the test set, model yielded an AUROC of 0.86, sensitivity of 81.29%, and specificity of 77.13%. Conclusions: A wearable device incorporated with a high performed AI algorithm can be a viable, convenient, cost-effective tool in screening LVSD.

ATP-binding cassette transporter G1 (ABCG1) is a cellular transmembrane protein that transports oxysterol efflux from cells to high-density lipoprotein (HDL) particles in the plasma. Previous studies have demonstrated that an ABCG1 deficiency exerts an antiatherosclerotic function through the effects of oxysterol accumulation in cells to enhance apoptosis and regulate inflammatory processes. However, whether the deficiency of ABCG1 and the corresponding changes in the efflux of oxysterols could take a series of impacts on the proteomic composition of HDL remains unclear. Here, plasma HDL of ABCG1(-/-) mice and their wild-type controls on a normal chow diet (NCD) or a high-fat diet (HFD) were isolated by ultracentrifugation. The proportion of 7-ketocholesterol and the proteomic composition of samples were comparatively analyzed by LC-MS/MS. In NCD-fed mice, lipid metabolism-related protein (arachidonate 12-lipoxygenase) and antioxidative protein (pantetheinase) exhibited increased accumulation, and inflammatory response protein (alpha-1-antitrypsin) was decreased in accumulation in ABCG1(-/-) mice HDL. In HFD-fed mice, fewer proteins were detected than that of NCD-fed mice. The ABCG1(-/-) mice HDL exhibited increased accumulation of lipid metabolism-related proteins (e.g., carboxylesterase 1C, apolipoprotein (apo)C-4) and decreased accumulation of alpha-1-antitrypsin, as well as significantly reduced proportion of 7-ketocholesterol. Additionally, positive correlations were found between 7-ketocholesterol and some essential proteins on HDL, such as alpha-1-antitrypsin, apoA-4, apoB-100, and serum amyloid A (SAA). These results suggest a detrimental impact of oxysterols on HDL composition, which might affect the antiatherosclerotic properties of HDL.

Salt-sensitive hypertension is closely related to inflammation, but the mechanism is barely known. Transmembrane member 16A (TMEM16A) is the Ca2+-activated chloride channel in epithelial cells, smooth muscle cells, and sensory neurons. It can promote inflammatory responses by increasing proinflammatory cytokine release. Here, we identified a positive role of TMEM16A in vascular inflammation. The expression of TMEM16A was increased in high-salt-stimulated vascular smooth muscle cells (VSMCs), whereas inhibiting TMEM16A or silencing TMEM16A with small interfering RNA (siRNA) can abolish this effect in vitro or in vivo. Transcriptome analysis of VSMCs revealed some differential downstream genes of TMEM16A related to inflammation, such as endothelial cell-specific molecule 1 (ESM1) and CXC chemokine ligand 16 (CXCL16). Overexpression of TMEM16A in VSMCs was accompanied by high levels of ESM1, CXCL16, intercellular adhesion molecule-1 (ICAM-1), and vascular adhesion molecule-1 (VCAM-1). We treated VSMCs cultured with high salt and arctigenin (ARC), T16Ainh-A01 (T16), and TMEM16A siRNA (siTMEM16A), leading to greatly decreased ESM1, CXCL16, VCAM-1, and ICAM-1. Beyond that, silencing ESM1, the expression of VCAM-1 and ICAM-1, and CXCL16 was attenuated. In conclusion, our results outlined a signaling scheme that increased TMEM16 protein upregulated ESM1, which possibly activated the CXCL16 pathway and increased VCAM-1 and ICAM-1 expression, which drives VSMC inflammation. Beyond that, arctigenin, as a natural inhibitor of TMEM16A, can reduce the systolic blood pressure (SBP) of salt-sensitive hypertension mice and alleviate vascular inflammation.

The COVID-19 pandemic caused healthcare systems and patients to cancel or postpone healthcare services, particularly preventive care. Many patients still have not received these services raising concerns about the potential for preventable morbidity and mortality. At Sutter Health, a large integrated healthcare system in Northern California, we conducted a population-based email survey in August 2020 to evaluate perceptions and preferences about where, when, and how healthcare is delivered during the COVID-19 pandemic. In total, 3351 patients completed surveys, and 42.6% reported that they would “wait until they felt safe” before receiving a colonoscopy as compared to 22.4% for a mammogram. The doctor's office was the most common preferred location for receiving vaccines/shots (79.9%), though many also reported preferring an outdoor setting or in a car (63.7%). With over 40% of patients reporting that they would “wait until they feel safe” for a colonoscopy, healthcare systems could focus on promoting other evidence-based options such a fecal-occult blood test to ensure timely colon cancer screening.

Abstract Background The morning blood pressure surge (MBPS) is related to an exaggerated risk of cardiovascular diseases and mortality. With increasing attention on circadian change in blood pressure and extensive use of ambulatory blood pressure monitoring (ABPM), chronotherapy that administration of medication according to biological rhythm, is reported to improve cardiovascular outcomes. The aim of this study is to evaluate the influence of chronotherapy of antihypertensive drugs upon MBPS in hypertensive patients. Methods A search strategy was applied in Ovid MEDLINE, EMBASE, Cochrane (Wiley) CENTRAL Register of Controlled Trials, Cochrane Database of Systematic Reviews, and the Chinese Biomedical literature database. No language and date restrictions. Randomized controlled trials (RCT) assessing the efficacy of evening and morning administration of the same medications in adult patients with primary hypertension were included. Results A total of ten trials, comprising 1724 participants with a mean age of 61 and 51% female, were included in this study. Combined analysis observed significant reduction of MBPS (− 5.30 mmHg, 95% CI − 8.80 to − 1.80), night-time SBP (− 2.29 mmHg, 95% CI − 4.43 to − 0.15), night-time DBP (− 1.63 mmHg, 95 %CI − 3.23 to − 0.04) and increase in night blood pressure dipping (3.23%, 95% CI 5.37 to 1.10) in evening dosage compared with traditional morning dosage of blood pressure-lowering drugs. No significant difference was found in the incidence of overall adverse effects (RR 0.65, 95% CI 0.30 to 1.41) and withdrawal due to adverse effects (RR 0.95, 95% CI 0.53 to 1.71). Conclusions Our study suggested that evening administration of antihypertensive medications exerted better blood pressure-lowering effect on MBPS compared with conventional morning dosage. Safety assessment also indicated that the evening regimen did not increase the risk of adverse events. However, endpoint studies need to be carried out to confirm the significance and feasibility of this treatment regimen in clinical practice.

Vascular remodeling is a pathological basis of various disorders. Therefore, it is necessary to understand the occurrence, prevention, and treatment of vascular remodeling. Kruppel-like factor 5 (KLF5) has been identified as a significant factor in cardiovascular diseases during the last two decades. This review provides a mechanism network of function and regulation of KLF5 in vascular remodeling based on newly published data and gives a summary of its potential therapeutic applications. KLF5 modulates numerous biological processes, which play essential parts in the development of vascular remodeling, such as cell proliferation, phenotype switch, extracellular matrix deposition, inflammation, and angiogenesis by altering downstream genes and signaling pathways. Considering its essential functions, KLF5 could be developed as a potent therapeutic target in vascular disorders.

Objective To analyze the adherence to antihypertensive drugs in Chinese patients with hypertension and the factors associated with the drug adherence. Methods The data for this analysis were obtained from the 2014 China Health Insurance Association (CHIRA) database. The study included 64,576 patients aged ≥18 years who were prescribed one of the seven antihypertensive drugs included in the study in their first prescription in 2014 and were observed for ≥180 days. The medicine possession ratio (MPR) was calculated and taken as the measure of treatment adherence. MPR values <0.3, 0.3 to <0.5, 0.5 to <0.8, and ≥0.8 were considered treatment adherence very low, low, intermediate, and high, respectively. Descriptive statistics were used to present baseline data and treatment adherence rate. Multiple regression models were used to determine independent factors which can affect the treatment adherence rate. P-value <0.05 was considered significant. Results Among the study antihypertensive drugs, amlodipine (33.98%), metoprolol (25.04%), and nifedipine (17.15%) were the frequently prescribed drugs. Nifedipine controlled release tablet had the highest MPR (0.61), followed by valsartan (0.53), valsartan/amlodipine fixed-dose combination (0.50), indapamide (0.40), and amlodipine (0.39), whereas benazepril (0.27) and metoprolol (0.19) had the lowest MPR. Higher reimbursement ratio, regular tertiary hospitals visits, lower age, and lower daily medical cost positively affected treatment adherence, whereas longer duration of illness and higher daily average cost affected treatment adherence negatively. Conclusion Our study assessed that prescribing more cost-effective, long-acting antihypertensive drugs, and raising the reimbursement ratio were associated with a better treatment adherence in Chinese patients with hypertension.

Phenotyping electronic health records (EHR)focuses on defining meaningful patient groups (e.g., heart failure group and diabetes group) and identifying the temporal evolution of patients in those groups. Tensor factorization has been an effective tool for phenotyping. Most of the existing works assume either a static patient representation with aggregate data or only model temporal data. However, real EHR data contain both temporal (e.g., longitudinal clinical visits) and static information (e.g., patient demographics), which are difficult to model simultaneously. In this paper, we propose Temporal And Static TEnsor factorization (TASTE) that jointly models both static and temporal information to extract phenotypes.TASTE combines the PARAFAC2 model with non-negative matrix factorization to model a temporal and a static tensor. To fit the proposed model, we transform the original problem into simpler ones which are optimally solved in an alternating fashion. For each of the sub-problems, our proposed mathematical re-formulations lead to efficient sub-problem solvers. Comprehensive experiments on large EHR data from a heart failure (HF) study confirmed that TASTE is up to 14× faster than several baselines and the resulting phenotypes were confirmed to be clinically meaningful by a cardiologist. Using 60 phenotypes extracted by TASTE, a simple logistic regression can achieve the same level of area under the curve (AUC) for HF prediction compared to a deep learning model using recurrent neural networks (RNN) with 345 features.

Background: We determined the impact of data volume and diversity and training conditions on recurrent neural network methods compared with traditional machine learning methods. Methods and Results: Using longitudinal electronic health record data, we assessed the relative performance of machine learning models trained to detect a future diagnosis of heart failure in primary care patients. Model performance was assessed in relation to data parameters defined by the combination of different data domains (data diversity), the number of patient records in the training data set (data quantity), the number of encounters per patient (data density), the prediction window length, and the observation window length (ie, the time period before the prediction window that is the source of features for prediction). Data on 4370 incident heart failure cases and 30 132 group-matched controls were used. Recurrent neural network model performance was superior under a variety of conditions that included (1) when data were less diverse (eg, a single data domain like medication or vital signs) given the same training size; (2) as data quantity increased; (3) as density increased; (4) as the observation window length increased; and (5) as the prediction window length decreased. When all data domains were used, the performance of recurrent neural network models increased in relation to the quantity of data used (ie, up to 100% of the data). When data are sparse (ie, fewer features or low dimension), model performance is lower, but a much smaller training set size is required to achieve optimal performance compared with conditions where data are more diverse and includes more features. Conclusions: Recurrent neural networks are effective for predicting a future diagnosis of heart failure given sufficient training set size. Model performance appears to continue to improve in direct relation to training set size.

IN BRIEF Chronic conditions such as diabetes are largely managed by primary care providers (PCPs), with significant patient self-management. This article describes the development, pilot testing, and fine-tuning of a Web-based digital health solution to help PCPs manage patients with cardiometabolic diseases during routine office encounters. It shows that such products can be successfully integrated into primary care settings when they address important unmet needs and are developed with input from end-users.

Objective: This study was designed to investigate the effects of smoking and smoking cessation on proinflammatory and pro-oxidative properties of low-density lipoprotein (LDL). Methods: This randomized, prospective, and parallel controlled study included seventeen non-smokers and forty long-term smokers, divided randomly into a smoking cessation group (n=20) and smoking continued group (n=20). Measurements of anthropometric data and fasting laboratory tests were carried out before and after smoking cessation. Blood samples for lipoprotein isolation were also collected both at the enrollment (day 0) and at end of the observation (day 90) time points. Low density lipoprotein isolated was used to treat human umbilical vein endothelial cells (HUVECs) in vitro. Inflammatory and oxidative impact of LDL on HUVECs was also measured. Results: Plasma low-density lipoprotein cholesterol (LDL-C) levels of long-term smokers were significantly higher than that of non-smokers (P<0.05). LDL isolated from smokers increased endothelial production of oxidative markers (MDA), acute inflammatory factors (IL-1 beta, TNF-alpha, and MMP-9), and ox-LDL surface receptor (LOX-1), while decreasing endothelial eNOS and NO levels (all P<0.05). Ninety days of smoking cessation partially yet significantly reversed MDA, IL-1 beta, TNF-alpha, MMP-9, and LOX-1 expression (all P<0.05), while decreasing eNOS (P<0.05) levels and trending to increasing NO production. Conclusion: Smoking modified LDL exhibited detrimental effects on vascular endothelium. Smoking cessation, however, significantly alleviated LDL's pro-inflammatory and pro-oxidative effects, compared with non-abstinence, probably playing important roles in preventing atherosclerosis.

Background: Cigarette smoking disturbs plasma lipid level and lipoprotein metabolism; however, the effects of smoking on the functional state of high density lipoprotein (HDL) are still not clear. This study aimed to determine the antioxidant and antichemotactic properties of HDL and HDL-mediated cholesterol efflux in healthy subjects after cigarette smoking. Materials and Methods: Healthy male subjects, including nonsmokers (n = 16) and chronic smokers (n = 8), were enrolled. After smoking 8 cigarettes within 2 hours, plasma HDL was isolated and tested. Copper-induced low density lipoprotein (LDL) oxidation was used to determine the antioxidant ability of HDL. The concentration of serum amyloid A was measured by Enzyme Linked Immunosorbent Assay. Chemotaxis was detected by transwell assay. HDL-mediated cholesterol efflux was measured using fluorescent cholesterol analog. Results: LDL baseline oxidation state was higher in chronic smokers than that in nonsmokers. Meanwhile, HDL-induced cholesterol efflux in macrophages in chronic smokers was significantly enhanced compared with that in nonsmokers. After acute smoking, both the antioxidant and antichemotactic ability of HDL declined in nonsmokers. However, in healthy chronic smokers, the effect of HDL on the susceptibility of LDL to oxidation was compensatorily enhanced. Nevertheless, their bodies were still in a higher oxidation state. Also, acute smoking did not affect HDL-mediated cholesterol efflux significantly in both nonsmokers and chronic smokers. Conclusions Our data suggest that acute smoking attenuates the antioxidant and antichemotactic abilities of HDL in nonsmokers. Chronic smokers are in a higher oxidative state, although the antioxidant function of their HDL is compensatorily enhanced.

Aims: The previous studies on ABCG1 using genetically modified mice showed inconsistent results on atherosclerosis. The aim of this study was to determine whether accurate target knockout of ABCG1 would result in transcriptional changes of other atherosclerosis-related genes. Methods: ABCG1 knockout mouse model was obtained by precise gene targeting without affecting non-target DNA sequences in C57BL/6 background. The wildtype C57BL/6 mice were regarded as control group. 12-week-old male mice were used in current study. We performed whole transcriptome analysis on the peripheral blood mononuclear cells obtained from ABCG1 knockout mice (n = 3) and their wildtype controls (n = 3) by RNA-seq. Results: Compared with wildtype group, 605 genes were modified at the time of ABCG1 knockout and expressed differentially in knockout group, including 306 up-regulated genes and 299 down-regulated genes. 54 genes were associated with metabolism regulation, of which 13 were related to lipid metabolism. We also found some other modified genes in knockout mice involved in cell adhesion, leukocyte transendothelial migration and apoptosis, which might also play roles in the process of atherosclerosis. 7 significantly enriched GO terms and 19 significantly enriched KEGG pathways were identified, involving fatty acid biosynthesis, immune response and intracellular signal transduction. Conclusions: ABCG1 knockout mice exhibited an altered expression of multiple genes related to many aspects of atherosclerosis, which might affect the further studies to insight into the effect of ABCG1 on atherosclerosis with this animal model.

This paper presents a new method, which we call SUSTain, that extends real-valued matrix and tensor factorizations to data where values are integers. Such data are common when the values correspond to event counts or ordinal measures. The conventional approach is to treat integer data as real, and then apply real-valued factorizations. However, doing so fails to preserve important characteristics of the original data, thereby making it hard to interpret the results. Instead, our approach extracts factor values from integer datasets as scores that are constrained to take values from a small integer set. These scores are easy to interpret: a score of zero indicates no feature contribution and higher scores indicate distinct levels of feature importance. At its core, SUSTain relies on: a) a problem partitioning into integer-constrained subproblems, so that they can be optimally solved in an efficient manner; and b) organizing the order of the subproblems' solution, to promote reuse of shared intermediate results. We propose two variants, SUSTain_M and SUSTain_T, to handle both matrix and tensor inputs, respectively. We evaluate SUSTain against several state-of-the-art baselines on both synthetic and real Electronic Health Record (EHR) datasets. Comparing to those baselines, SUSTain shows either significantly better fit or orders of magnitude speedups that achieve a comparable fit (up to 425× faster). We apply SUSTain to EHR datasets to extract patient phenotypes (i.e., clinically meaningful patient clusters). Furthermore, 87% of them were validated as clinically meaningful phenotypes related to heart failure by a cardiologist.

BACKGROUND:Primary care facilities are the base for hypercholesterolemia treatment. However, data regarding the effectiveness of lipid management in primary care are lacking.METHODS AND RESULTS:To evaluate lipid management in the primary care setting in China, we compared patients' characteristics and lipid management outcomes between 6100 outpatients treated at primary care versus 19,217 patients in non-primary settings using data from the DYSlipidemia International Study-China (DYSIS-CHINA). Compared to patients treated at non-primary hospitals, patients who received treatment at primary settings were younger, thinner, and were more likely to be female and to have a family history of premature CVD. Overall, 26.8% of very high-risk and 40.8% of high-risk patients achieved the LDL-C target with primary care treatment, whereas these target rates were 41.2% (p<0.001) and 58.6% (p<0.001), respectively, among patients treated at non-primary hospitals. High-dose statin therapy was underused in primary care patients compared to non-primary hospital patients (p<0.001). Logistic regression analysis showed that female gender, diabetes, and obesity were negative factors, whereas life-style modification and use of high-dose statin (40mg/d simvastatin equivalent) were favorable factors in predicting LDL-C target attainment in the primary care setting.CONCLUSION:Sedentary life style, alcohol drinking, and use of suboptimal statin dosage are key factors that unfavorably affect the LDL-C target rate among patients treated at primary care facilities in China. Sufficient training for primary care physicians regarding proper statin use and support for the combined use of a statin with ezetimibe could promote LDL-C target attainment in primary care.

Introduction: ATP-binding cassette transporter G1(ABCG1)is a transmembrane protein mediated efflux of cellular cholesterol to HDL, which plays a vital part in macrophage lipid homeostasis, but the role of ABCG1 in atherosclerosis still remains controversial. Our previous study demonstrated that human ABCG1 -367 G>A polymorphism in promoter region, which leads to lower ABCG1 protein expression, was associated with a reduced risk of CAD. However, the mechanism behind is not fully understood. Hypothesis: Oxysterols, the oxidized derivatives of cholesterol, whose efflux are mediated by ABCG1, exert cytotoxic effect on macrophage and accelerate cell apoptosis. Low ABCG1 expression induces excess oxysterols accumulation in macrophage, which augments the inflammatory response and accelerates apoptosis. Since defective apoptotic macrophage clearance in late lesions promotes atherosclerosis progression, we hypothesize that macrophage with lower ABCG1 expression may remove apoptotic cells more efficiently, thereby generating an antiatherogenic effect. Methods: To investigate the effect of ABCG1 expression on macrophage, we established ABCG1 knockdown cell line by means of lentivirus mediated shRNA. Apoptosis was determined by flow cytometry (FCM). Fluorescence labeled apoptotic model was generated and macrophage phagocytosis was evaluated. The inflammatory factors level and phagocytosis associated gene expression were measured by ELISA and realtime PCR. Results: Compared with control group, macrophage with lower ABCG1 expression had a higher secretion level of Inflammatory factors, such as TNF-α and IL-1β, showing an increased expression of classic inflammatory M1 phenotype markers,such as CD86 and TGF-β, and a down-regulation of CD163,Arg and IL-6 expression, which are markers of anti-inflammatory M2 phenotype macrophage. The apoptosis was significantly accelerated and the phagocytic clearance was enhanced after ABCG1 expression decreased, which means apoptotic cells could be removed more quickly. Both CD36 and Mertk showed a higher mRNA level in ABCG1 knockdown group. Conclusions: Decreased expression of macrophage ABCG1 may exert antiatherogenic function through accelerating apoptosis and enhancing phagocytosis.

Introduction: We herein describe a patient with chronic disseminated intravascular coagulation (DIC) induced by a giant thrombus in the left atrium.A 63-year-old woman was admitted to our hospital for evaluation of extensive mucocutaneous hemorrhage, especially at the sites of venipuncture, on May 21, 2015. Considering her long history of rheumatic heart disease and atrial fibrillation and her mitral valve replacement performed several years previously, we strongly suspected that the bleeding was closely related to postoperative over-anticoagulation of warfarin. After careful investigation, we found that her coagulopathy was induced by the chronic DIC, which was in turn secondary to a left atrial giant thrombus. This is a rarely reported cause of chronic DIC. Cardiac computed tomography and echocardiography showed apparent biatrial enlargement; the morphology and function of the ventricles were unaffected. After anticoagulant therapy, the bleeding tendency and coagulation index were significantly improved.Conclusion: A left atrial thrombus should be considered as a differential diagnosis of chronic DIC, especially in patients with predisposing heart conditions. Because treatment of the underlying cause is paramount in the management of chronic DIC, this case is of great clinical value.

BACKGROUND:ABCA1 -565C/T gene promoter variants have been associated with the severity of coronary artery disease in Western populations. The purpose of our study was to investigate the association between the -565C/T gene polymorphism and coronary artery disease severity and cholesterol efflux in the Chinese Han population.METHODS:A cohort of 298 acute coronary syndrome (ACS) patients and 541 healthy controls was genotyped using the highly sensitive ligase detection reaction. ABCA1 -565C/T genotype was correlated with the clinical features of 164 acute myocardial infarction (AMI) patients. Monocytes from patients with various -565C/T gene polymorphisms were isolated and differentiated into foam cells by coincubation with [(3)H]-labeled acetyl-low-density lipoprotein cholesterol. ABCA1 mRNA and protein expression levels were evaluated, as well as cellular cholesterol efflux.RESULTS:The frequency of the TT genotype in the -565C/T polymorphism of ACS patients was significantly increased when compared with controls (0.211 vs. 0.162, p<0.05). The TT genotype, but not the CT or CC genotypes, in the -565C/T gene polymorphism correlated with the severity of the coronary lesion observed in AMI patients. Patients with the TT homozygote genotype also exhibited significantly lower cellular cholesterol efflux (TT [6.37%±0.554%]) levels than controls and also had the lowest levels of ABCA1 mRNA and protein expression among the group of variants. In contrast, cholesterol efflux levels in AMI patients with CT [11.35%±3.975%] and CC ([15.32%±6.293%]) genotypes were not significantly different from controls.CONCLUSIONS:Impaired ABCA1-mediated cholesterol efflux in macrophages may be associated with the severity of the coronary lesions in AMI patients with the TT genotype at the -565C/T gene polymorphism.

Objective To investigate the biological function of human lipid transporter gene ABCG1 in THP-1 cell line in the development and progression of atherosclerosis, the lentiviral vector of ABCG1 short hairpin RNA ( shRNA) was constructed and its knockdown effect and function was determined. Methods ABCG1 shRNA was designed and constructed based human ABCG1 cDNA sequence using a lentiviral vector. The expression of ABCG1 was measured by real-time PCR and Western blot, and function was examined by Cholesterol efflux assay. Results Construct of lentiviral vector effectively inhibited ABCG1 mRNA and protein levels and decreased the ABCG1-mediated cholesterol efflux from THP-1-derived macrophages. ( infection group:23. 87% ± 0. 45% vs. control group:30. 57% ± 1. 00%, P﹤0. 001 ) . Conclusions A lentivirus RNA inference vector targeting ABCG1 gene is successfully constructed, which provided THP-1 cell model for further detection of ABCG1 function.