Ticagrelor versus clopidogrel in reducing inflammatory cell infiltration of thrombus aspirated in patients with ST-elevation myocardial infarction.

BACKGROUND: Ticagrelor provides more rapid, potent, and consistent anti-platelet efficacy than clopidogrel. This randomized trial aimed to evaluate the anti-inflammation effects of ticagrelor versus clopidogrel on thrombus aspirated from the ST-elevation myocardial infarction (STEMI) patients. METHOD: A total of 98 patients with STEMI and intended percutaneous coronary intervention (PCI) were randomly assigned to receive clopidogrel (600-mg loading dose) or ticagrelor (180-mg loading dose), of whom 55 with large thrombus burden underwent thrombus aspiration during PCI. Thrombus specimens were successfully aspirated from 49 patients. Finally, 24 patients in the clopidogrel group and 23 in the ticagrelor group completed the study. Inflammatory cells within thrombi were assessed by hematoxylin-eosin and immunohistochemistry stainings. RESULTS: Compared with the clopidogrel group, the number of total inflammatory cells per mm2 thrombus area in the ticagrelor group was decreased by 28% (P = 0.009). The numbers of neutrophils and myeloperoxidase-positive cells per mm2 thrombus area in the ticagrelor group were respectively decreased by 35% (P = 0.016) and 28% (P = 0.047), as compared with those in the clopidogrel group. Moreover, ticagrelor treatment reduced the ratio of monocytes number higher than 250 per mm2 thrombus area compared with clopidogrel treatment (4% versus 29%, P = 0.048). CONCLUSION: In patients with undergoing PCI for STEMI, the loading dose ticagrelor regimen was associated with a reduction in inflammatory cell infiltration within thrombus compared with the loading dose clopidogrel regimen.

Effects of ticagrelor monotherapy vs. clopidogrel monotherapy on platelet reactivity: a randomized, crossover clinical study (SINGLE study).

Increasing clinical trials demonstrated that the discontinuation of aspirin while maintaining a P2Y12 inhibitor monotherapy could decrease the risk of bleeding without losing the antithrombotic effect. However, no data are available on the platelet reactivity of patients undergoing ticagrelor monotherapy vs. clopidogrel. Therefore, we performed this study to observe the efficacy of ticagrelor monotherapy vs. clopidogrel in Chinese patients with chronic coronary syndrome. This randomized, single-blinded, crossover trial enrolled 50 patients who were administered with ticagrelor (90 mg twice daily for 2 weeks) or clopidogrel (75 mg once daily for 2 weeks). Followed by a 2-week washout period, the two groups of patients underwent a crossover trial. Light transmission aggregometry (LTA) and thromboelastography (TEG) assays were used to test platelet reactivity. The platelet aggregation rate (PAgR) of ADP and AA was significantly lower with ticagrelor than clopidogrel (PAgR of ADP, 27.30% (7.30%-42.635%) vs. 35.55% (12.03%-69.25%), P = .0254; PAgR of AA, 77.80% (21.60%-86.43%) vs. 83.10% (67.13%-87.20%), P = .0400). There was no significant difference in PAgR of collagen and epinephrine between the two groups. The TEG assay showed that ADP and AA, which induced the inhibition of platelet aggregation, were significantly higher in the ticagrelor group than those in the clopidogrel group [ADP%, 69.00% (59.68%-88.95%) vs. 60.55% (35.98%-78.35%), P = .0020; AA%, 53.65% (22.75%-79.28%) vs. 15.15% (5.75%-70.25%), P = .0127]. High on-treatment platelet reactivity (HTPR) on ADP was 2.17% with ticagrelor and 19.57% with clopidogrel. HTPR on AA was 50.00% with ticagrelor and 69.57% with clopidogrel. Ticagrelor and clopidogrel caused the inhibition of ADP and AA-induced platelet aggregation. Moreover, ticagrelor monotherapy had a stronger inhibitory effect than clopidogrel monotherapy (except on collagen and epinephrine).

Efficacy and safety of different ticagrelor regimens versus clopidogrel in patients with coronary artery disease: a retrospective multicenter study (SUPERIOR).

Current guidelines favor dual anti-platelet therapy with ticagrelor 90 mg BID (T90BID) over clopidogrel 75 mg QD (C75QD) in addition to aspirin for acute coronary syndrome. However, an increased risk of ticagrelor-related adverse events prompted the evaluation of low-dose regimens. This study (NCT03381742) retrospectively analyzed the data from 11 hospitals on 3,043 patients with coronary artery disease, who received C75QD, T90BID, ticagrelor 45 mg BID (T45BID), or ticagrelor 90 mg QD (T90QD). Compared with C75QD, both T45BID and T90QD showed significantly higher inhibition of platelet aggregation (P < .0001) and lower platelet-fibrin clot strength (P < .0001) induced by adenosine diphosphate. Furthermore, compared with T90BID, two low-dose regimens had a much lower minor bleeding rate and a significantly higher proportion of patients within the therapeutic window for P2Y12 receptor reactivity. There were no significant differences between T45BID and T90QD in the trough plasma concentrations of ticagrelor and its active metabolite. Similar efficacy and safety outcomes were observed in the propensity score-matched analysis. In conclusion, the low-dose ticagrelor regimen, either T45BID or T90QD, may provide a more attractive benefit-risk profile than C75QD or T90BID.

Atorvastatin Attenuates Cold-Induced Hypertension by Preventing Gut Barrier Injury.

Chronic exposure to cold causes arterial hypertension [cold-induce hypertension (CIH)]. Emerging data have indicated that gut barrier dysfunction is involved in the pathogenesis of hypertension. In this study, we explored the effect of gut barrier dysfunction on vascular inflammation induced by cold exposure and the therapeutic effect of atorvastatin in a CIH rat model. The CIH was established by cold exposure for 2 weeks. Two groups of Sprague Dawley rats were exposed to moderate cold (4 ± 1°C), whereas the control group was maintained at room temperature (23 ± 1°C) (10 rats/group). The 2 groups received atorvastatin or vehicle at the beginning of cold exposure, respectively, for 2 weeks. Cold exposure increased mean arterial pressure compared with room temperature group, indicating that animals developed arterial hypertension. Cold exposure induced vascular dysfunction due to decreasing phosphorylated endothelial nitric oxide synthase protein expression in aorta, and these were blunted by atorvastatin. Cold exposure increased the levels of gut-derived inflammatory cytokines, tumor necrosis factor-α, and interleukin-6 production in aorta and resulted in vascular inflammation, whereas atorvastatin prevented these effects. Cold exposure also increased gut permeability, inhibited tight junction protein expression in proximal colon, and resulted in gut barrier dysfunction. Interestingly, atorvastatin eliminated increasing gut permeability, decreasing tight junction protein expression, and gut pathology and reversed gut barrier dysfunction. Atorvastatin attenuated CIH and improved gut barrier function; the beneficial effects might be via inhibiting gut-derived inflammatory cytokines and reversing cold-induced vascular inflammation, suggesting that gut barrier dysfunction may be involved in the pathogenesis of CIH.

Effects of different doses of ticagrelor on platelet aggregation and endothelial function in diabetic patients with stable coronary artery disease.

We performed this study to observe the effects of different doses of ticagrelor and standard-dose clopidogrel on platelet reactivity and endothelial function in diabetic patients with stable coronary artery disease (CAD). Sixty type 2 diabetic patients were assigned to one-quarter standard-dose ticagrelor, half standard-dose ticagrelor, standard-dose ticagrelor and standard-dose clopidogrel groups. Light transmission aggregometry (LTA) and VerifyNow assay were used to measure platelet function. Endothelial function was assessed by measurement of flow-mediated vasodilation (FMD) and plasma von Willebrand factor (VWF) levels were detected. Enzyme-linked immunosorbent assay (ELISA) examined the Interleukin-8(IL-8) and IL-10. The results suggested that the one-quarter dose (34.0%± 14.7%), half-dose (26.9%± 11.6%) and standard-dose (17.3%± 10.3%) ticagrelor showed lower platelet aggregation rate than clopidogrel (52.8%± 18.3%; P ï¼œ0.0001). PRU values in three ticagrelor groups were lower than that in clopidogrel group (102 (76-184)；75 (33-88)；38 (11-52) versus 194 (138-271) and；P ï¼œ0.0001). FMD levels were higher in ticagrelor groups compared with baseline levels while lower in clopidogrel group after treatment. However, no significant differences were found in the percentage increase in the FMD between ticagrelor groups and clopidogrel group. The levels of VWF after treatment were lower than the baseline levels, but there was no statistically significant difference between ticagrelor group and clopidogrel group after treatment. The concentration of IL-8 and IL-10 were decreased in patients with half and standard-dose ticagrelor group. In conclusion, one-quarter standard-dose ticagrelor produced similar inhibitory effects on platelet aggregation as standard-dose clopidogrel in diabetic patients with stable CAD. The half standard-dose ticagrelor had a similar inhibitory effect on platelet inhibition as standard-dose ticagrelor, which was stronger than that of clopidogrel. Moreover, the half-dose ticagrelor had equal protection of endothelial function and inhibition of inflammatory factor as standard-dose ticagrelor.

Metoprolol has a similar therapeutic effect as amlodipine on BP lowering in hypertensive patients with obstructive sleep apnea.

PURPOSE: ß-Blocker use has been controversial for a long time in the management of hypertensive patients with obstructive sleep apnea (OSA). The aim of present study was to compare the effects of metoprolol on BP lowering with amlodipine in hypertensive OSA patients. METHODS: Hypertensive subjects with OSA were randomly assigned to metoprolol and amlodipine groups, receiving 12 weeks of oral either metoprolol (47.5 mg once daily) or amlodipine (5 mg once daily) treatment. At baseline and after the 12-week treatment period, 24-h ambulatory blood pressure monitoring was performed in both groups. RESULTS: Both of metoprolol and amlodipine treatments significantly lowered 24-h blood pressure (BP) (from 143/88 to 132.3/81.6 mmHg; from 141.3/84.5 to 133.7/80.8 mmHg), daytime BP (from 146/90.2 to 136.4/84.6 mmHg; from 145.1/87.6 to 138.2/84.1 mmHg), and nighttime BP (from 139.1/83.9 to 125.7/76.2 mmHg; from 134.5/78.5 to 125.8/74.1 mmHg) (all P < 0.05). But there were no significant differences between the groups in BP variability (P > 0.05). Besides, metoprolol significantly reduced daytime heart rate (HR) (P < 0.05), while 24-h and nighttime HR values had no remarkable changes compared with baseline (P > 0.05). CONCLUSIONS: Metoprolol had similar therapeutic effects on BP lowering as amlodipine and could not decrease HR during the nighttime in hypertensive patients with OSA.

(-)-Epicatechin Suppresses Angiotensin II-induced Cardiac Hypertrophy via the Activation of the SP1/SIRT1 Signaling Pathway.

BACKGROUND/AIMS: Flavonol (-)-epicatechin (EPI) is present in high amounts in cocoa and tea products, and has been shown to exert beneficial effects on the cardiovascular system. However, the precise mechanism of EPI on cardiomyocyte hypertrophy has not yet been determined. In this study, we examined whether EPI could inhibit cardiac hypertrophy. METHODS: We utilised cultured neonatal mouse cardiomyocytes and mice for immunofluorescence, immunochemistry, qRT-PCR, and western blot analyses. RESULTS: 1µM EPI significantly inhibited 1µM angiotensin II (Ang II)-induced increase of cardiomyocyte size, as well as the mRNA and protein levels of ANP, BNP and ß-MHC in vitro. The effects of EPI were accompanied with an up-regulation of SP1 and SIRT1, and were abolished by SP1 inhibition. Up-regulation of SP1 could block Ang II-induced increase in cardiomyocyte size, as well as the mRNA and protein levels of ANP, BNP and ß-MHC, and increase the protein levels of SIRT1 in vitro. Moreover, 1 mg/kg body weight/day EPI significantly inhibited mouse cardiac hypertrophy induced by Ang II, which could be eliminated by SP1 inhibition in vivo. CONCLUSION: Our data indicated that EPI inhibited AngII-induced cardiac hypertrophy by activating the SP1/SIRT1 signaling pathway.

The ß3 Adrenergic Receptor Agonist BRL37344 Exacerbates Atrial Structural Remodeling Through iNOS Uncoupling in Canine Models of Atrial Fibrillation.

BACKGROUND/AIMS: The role of the ß3-adrenergic receptor (ß3-AR) agonist BRL37344 in atrial fibrillation (AF) structural remodeling and the underlying mechanisms as a therapeutic target were investigated. METHODS: Four groups of dogs were evaluated: sham, pacing, ß3-AR agonist BRL37344 (ß3-AGO), and ß3-AR antagonist L748337 (ß3-ANT) groups. Dogs in the pacing, ß3-AGO and ß3-ANT groups were subjected to rapid atrial pacing for four weeks. Atrial structure and function, AF inducibility and duration, atrial myocyte apoptosis and interstitial fibrosis were assessed. Atrial superoxide anions were evaluated by fluorescence microscopy and colorimetric assays. Cardiac nitrate+nitrite levels were used to assess nitric oxide (NO) production. Protein and mRNA expression of ß3-AR, neuronal NO synthase (nNOS), inducible NO synthase (iNOS), endothelial NO synthase (eNOS) and guanosine triphosphate cyclohydrolase-1 (GCH-1) as well as tetrahydrobiopterin (BH4) levels were measured. RESULTS: ß3-AR was up-regulated in AF. Stimulation of ß3-AR significantly increased atrial myocyte apoptosis, fibrosis and atrial dilatation, resulting in increased AF induction and prolonged duration. These effects were attenuated by ß3-ANT. Moreover, ß3-AGO reduced BH4 and NO production and increased superoxide production, which was inhibited by the specific iNOS inhibitor, 1400w ß3-AGO also increased iNOS but decreased eNOS and had no effect on nNOS expression in AF. CONCLUSIONS: ß3-AR stimulation resulted in atrial structural remodeling by increasing iNOS uncoupling and related oxidative stress. ß3-AR up-regulation and iNOS uncoupling might be underlying AF therapeutic targets.

Hydrogen sulfide reduces serum triglyceride by activating liver autophagy via the AMPK-mTOR pathway.

Autophagy plays an important role in liver triglyceride (TG) metabolism. Inhibition of autophagy could reduce the clearance of TG in the liver. Hydrogen sulfide (H2S) is a potent stimulator of autophagic flux. Recent studies showed H2S is protective against hypertriglyceridemia (HTG) and noalcoholic fatty liver disease (NAFLD), while the mechanism remains to be explored. Here, we tested the hypothesis that H2S reduces serum TG level and ameliorates NAFLD by stimulating liver autophagic flux by the AMPK-mTOR pathway. The level of serum H2S in patients with HTG was lower than that of control subjects. Sodium hydrosulfide (NaHS, H2S donor) markedly reduced serum TG levels of male C57BL/6 mice fed a high-fat diet (HFD), which was abolished by coadministration of chloroquine (CQ), an inhibitor of autophagic flux. In HFD mice, administration of NaSH increased the LC3BII-to-LC3BI ratio and decreased the p62 protein level. Meanwhile, NaSH increased the phosphorylation of AMPK and thus reduced the phosphorylation of mTOR in a Western blot study. In cultured LO2 cells, high-fat treatment reduced the ratio of LC3BII to LC3BI and the phosphorylation of AMPK, which were reversed by the coadministration of NaSH. Knockdown of AMPK by siRNA in LO2 cells blocked the autophagic enhancing effects of NaSH. The same qualitative effect was observed in AMPKα2(-/-) mice. These results for the first time demonstrated that H2S could reduce serum TG level and ameliorate NAFLD by activating liver autophagy via the AMPK-mTOR pathway.

PRFold-TNN: Protein Fold Recognition With an Ensemble Feature Selection Method Using PageRank Algorithm Based on Transformer.

Understanding the tertiary structures of proteins is of great benefit to function in many aspects of human life. Protein fold recognition is a vital and salient means to know protein structure. Until now, researchers have successively proposed a variety of methods to realize protein fold recognition, but the novel and effective computational method is still needed to handle this problem with the continuous updating of protein structure databases. In this study, we develop a new protein structure dataset named AT and propose the PRFold-TNN model for protein fold recognition. Firstly, different types of feature extraction methods including AAC, HMM, HMM-Bigram and ACC are selected to extract corresponding features for protein sequences. Then an ensemble feature selection method based on PageRank algorithm integrating various tree-based algorithms is used to screen the fusion features. Ultimately, the classifier based on the Transformer model achieves the final prediction. Experiments show that the prediction accuracy is 86.27% on the AT dataset and 88.91% on the independent test set, indicating that the model can demonstrate superior performance and generalization ability in the problem of protein fold recognition. Furthermore, we also carry out research on the DD, EDD and TG benchmark datasets, and make them achieve prediction accuracy of 88.41%, 97.91% and 95.16%, which are at least 3.0%, 0.8% and 2.5% higher than those of the state-of-the-art methods. It can be concluded that the PRFold-TNN model is more prominent.

GSB: GNGS and SAG-BiGRU network for malware dynamic detection.

With the rapid development of the Internet, the continuous increase of malware and its variants have brought greatly challenges for cyber security. Due to the imbalance of the data distribution, the research on malware detection focuses on the accuracy of the whole data sample, while ignoring the detection rate of the minority categories' malware. In the dataset sample, the normal data samples account for the majority, while the attacks' malware accounts for the minority. However, the minority categories' attacks will bring great losses to countries, enterprises, or individuals. For solving the problem, this study proposed the GNGS algorithm to construct a new balance dataset for the model algorithm to pay more attention to the feature learning of the minority attacks' malware to improve the detection rate of attacks' malware. The traditional malware detection method is highly dependent on professional knowledge and static analysis, so we used the Self-Attention with Gate mechanism (SAG) based on the Transformer to carry out feature extraction between the local and global features and filter irrelevant noise information, then extracted the long-distance dependency temporal sequence features by the BiGRU network, and obtained the classification results through the SoftMax classifier. In the study, we used the Alibaba Cloud dataset for malware multi-classification. Compared the GSB deep learning network model with other current studies, the experimental results showed that the Gaussian noise generation strategy (GNGS) could solve the unbalanced distribution of minority categories' malware and the SAG-BiGRU algorithm obtained the accuracy rate of 88.7% on the eight-classification, which has better performance than other existing algorithms, and the GSB model also has a good effect on the NSL-KDD dataset, which showed the GSB model is effective for other network intrusion detection.

ResCNNT-fold: Combining residual convolutional neural network and Transformer for protein fold recognition from language model embeddings.

A comprehensive understanding of protein functions holds significant promise for disease research and drug development, and proteins with analogous tertiary structures tend to exhibit similar functions. Protein fold recognition stands as a classical approach in the realm of protein structure investigation. Despite significant advancements made by researchers in this field, the continuous updating of protein databases presents an ongoing challenge in accurately identifying protein fold types. In this study, we introduce a predictor, ResCNNT-fold, for protein fold recognition and employ the LE dataset for testing purpose. ResCNNT-fold leverages a pre-trained language model to obtain embedding representations for protein sequences, which are then processed by the ResCNNT feature extractor, a combination of residual convolutional neural network and Transformer, to derive fold-specific features. Subsequently, the query protein is paired with each protein whose structure is known in the template dataset. For each pair, the similarity score of their fold-specific features is calculated. Ultimately, the query protein is identified as the fold type of the template protein in the pair with the highest similarity score. To further validate the utility and efficacy of the proposed ResCNNT-fold predictor, we conduct a 2-fold cross-validation experiment on the fold level of the LE dataset. Remarkably, this rigorous evaluation yields an exceptional accuracy of 91.57%, which surpasses the best result among other state-of-the-art protein fold recognition methods by an approximate margin of 10%. The excellent performance unequivocally underscores the compelling advantages inherent to our proposed ResCNNT-fold predictor in the realm of protein fold recognition. The source code and data of ResCNNT-fold can be downloaded from https://github.com/Bioinformatics-Laboratory/ResCNNT-fold.

Network pharmacology-based approach to investigate the molecular targets of essential oil obtained from lavender for treating breast cancer.

Lavender essential oil (LEO) is known for its medicinal use in the development of pharmaceuticals. Further investigations were demonstrated that LEO has many biological properties including apoptosis. However, The anti-breast cancer activity and mechanism of LEO are still unclear. we aim to elucidate the elusive anti-breast cancer activity and mechanism of LEO by unveiling the intricate molecular targets that it engages with, thereby priming it for effective therapeutic intervention against breast carcinoma. In this paper, we extracted LEO from lavender and analyzed it's chemical constituents by using hydro-distillation and gas chromatography-mass spectrometry (GS-MS/MS) method, respectively. The active components against breast cancer and it's molecular targets were selected and biological process, molecular function, cellular component and involving pathways were evaluated via network pharmacology approach. Cell viability, apoptosis and cell cycle assay were used to evaluate anti-breast cancer effect of LEO. Employing the western blotting method to validate target protein expression following LEO treatment in vitro. We found the 21 effective components and 213 drug-disease common targets of LEO. Amoung them, 7 active components and 19 targets were identified as potential therapeutic targets. Gene ontology results revealed that the drug-disease common targets of LEO were mainly distributed in membrane region, involved in peptide-tyrosine phosphorylation, and primarily associated with protein tyrosine kinase. We also found that drug-disease common targets might contribute to the regulation of PI3K-AKT signaling pathway by using KEGG pathway analysis. Besides, our study demonstrated reduced cell viability, induced apoptosis in MCF-7 and MDA-MB-231 treated with LEO while cell cycle arrest was not altered. The AKT1 expression down-regulated while PIK3CA expression was increased in both cell lines. Our findings indicate that LEO has the ability to induce apoptosis by modulating the expression of PI3K-AKT signaling pathway in these cell lines.

Vericiguat reduces electrical and structural remodeling in a rabbit model of atrial fibrillation.

Purpose: The molecular etiology of atrial fibrillation (AF) and its treatment are poorly understood. AF involves both electrical and structural features. Vericiguat can ameliorate cardiac remodeling in heart failure. The effects of vericiguat on AF, however, are unclear. Here, the actions of vericiguat on atrial structural and electrical remodeling in AF and its possible mechanisms were investigated. Methods and Results: Thirty-six rabbits were randomly allocated to four groups, namely, sham, RAP (pacing with 600 beats/min over three weeks), vericiguat-treated (three weeks' pacing plus daily oral dose of 1.5 mg/kg of vericiguat), and vericiguat-treated only. HL-1 cells received rapid pacing with or without vericiguat. Parameters including electrophysiology, echocardiography, histology, Ca2+ levels, and ICaL density, as well as levels of TRPC6, CaN, NFAT4, p-NFAT4, Cav1.2, collagen I, collagen III, and ST2 were measured. Significant changes of above proteins expression level, circulating biochemical indices, Ca2+ concentrations, and ICaL density in both animals and cell models, these effects were significantly restored by vericiguat. Vericiguat also reversed the enlarged atrium and significantly reduced myocardial fibrosis, together with preventing reduced atrial effective refractory periods (AERPs) and AF induction rate. Conclusion: Vericiguat thus ameliorated AF-associated structural and electrical remodeling. These findings suggest the potential of vericiguat for treating AF.

Upregulation of ß3-adrenergic receptors contributes to atrial structural remodeling in rapid pacing induced atrial fibrillation canines.

Accumulating evidence suggests that the adrenergic receptors (ARs) play an important role in cardiac diseases. The expression of ß3-AR has been recently demonstrated in atria, however, its role in atrial structural remodeling of atrial fibrillation (AF) is unclear. Therefore, the present study was designed to investigate the role of ß3-AR in atrial structural remodeling in AF and to clarify its possible mechanisms. Twenty-eight dogs were randomly divided into sham, pacing, ß3-AR agonist (BRL37344) and ß3-AR antagonist (L748337) groups. AF was induced by rapid atrial pacing at 600 beats per minute for 3 weeks and evaluated by determining the ultrastructure and function of atria. The expression of ß3-AR and p38 mitogen-activated protein kinase (MAPK) was examined by western blot, immunohistochemistry and real-time RT-PCR. Additionally, the extent of oxidative stress was tested. We found the atrial enlargement and dysfunction in pacing group. Moreover, atrial interstitial fibrosis, apoptosis and oxidative stress were increased and the levels of ß3-AR and phosphorylated p38 MAPK were increased after pacing. Activation of ß3-AR exacerbated the pathologic changes and oxidative stress, which were effectively inhibited by L748337. We concluded that ß3-AR was upregulated in paced atria, which contributed to oxidative stress and exacerbated atrial structural remodeling by regulating p38 MAPK. Our study provides novel insights into the pharmacological role of ß3-AR in AF.

ASFold-DNN: Protein Fold Recognition Based on Evolutionary Features With Variable Parameters Using Full Connected Neural Network.

Protein fold recognition contribute to comprehend the function of proteins, which is of great help to the gene therapy of diseases and the development of new drugs. Researchers have been working in this direction and have made considerable achievements, but challenges still exist on low sequence similarity datasets. In this study, we propose the ASFold-DNN framework for protein fold recognition research. Above all, four groups of evolutionary features are extracted from the primary structures of proteins, and a preliminary selection of variable parameter is made for two groups of features including ACC _HMM and SXG _HMM, respectively. Then several feature selection algorithms are selected for comparison and the best feature selection scheme is obtained by changing their internal threshold values. Finally, multiple hyper-parameters of Full Connected Neural Network are fully optimized to construct the best model. DD, EDD and TG datasets with low sequence similarities are chosen to evaluate the performance of the models constructed by the framework, and the final prediction accuracy are 85.28, 95.00 and 88.84 percent, respectively. Furthermore, the ASTRAL186 and LE datasets are introduced to further verify the generalization ability of our proposed framework. Comprehensive experimental results prove that the ASFold-DNN framework is more prominent than the state-of-the-art studies on protein fold recognition. The source code and data of ASFold-DNN can be downloaded from https://github.com/Bioinformatics-Laboratory/project/tree/master/ASFold.

Effects of Sacubitril/Valsartan on the Expression of CaMKII/Cav1.2 in Atrial Fibrillation Stimulation Rabbit Model.

Methods: Overall, 18 rabbits were randomly divided into control, pacing (600 beats/min), and pacing+sac/val groups. The rabbits in the pacing+sac/val cohort received oral sac/val (10 mg/kg twice daily) across the 21-day investigation period. After three weeks, the atrial effective refractory period (AERP) and AF induction rate were compared. HL-1 cultures were exposed to fast pacing (24 h) with and without LBQ657 (active sacubitril form)/valsartan. Western blots were used for detecting Cav1.2 and CaMKII expression within atrial muscles of the rabbits and HL-1 cultures of AF model. Results: In comparison to the sham cohort, the AF induction rate was markedly increased together with AERP reduction within pacing cohort. Such changes were markedly rescued through sac/val treatment in pacing+sac/val cohort. The proteomic expression profiles of CaMKII and Cav1.2 showed that the CaMKII expression was markedly upregulated, while Cav1.2 expression was downregulated in the pacing cohort. Importantly, these effects were absent in pacing+sac/val cohort. Conclusion: Results of this study show that sac/val treatment regulates the expression of CaMKII/Cav1.2 and could alter this pathway in atrial rapid electrical stimulation models. Therefore, this investigation could contribute to a novel strategy in AF therapeutics in clinical settings.

Functional Evaluation of Intermediate Coronary Lesions with Integrated Computed Tomography Angiography and Invasive Angiography in Patients with Stable Coronary Artery Disease.

Background and objectives: The hemodynamic evaluation of coronary stenoses undergoes a transition from wire-based invasive measurements to image-based computational assessments. However, fractional flow reserve (FFR) values derived from coronary CT angiography (CCTA) and angiography-based quantitative flow ratio have certain limitations in accuracy and efficiency, preventing their widespread use in routine practice. Hence, we aimed to investigate the diagnostic performance of FFR derived from the integration of CCTA and invasive angiography (FFRCT-angio) with artificial intelligence assistance in patients with stable coronary artery disease (CAD). Methods: Forty stable CAD patients with 67 target vessels (50%-90% diameter stenosis) were included in this single-center retrospective study. All patients underwent CCTA followed by coronary angiography with FFR measurement within 30 days. Both CCTA and angiographic images were combined to generate a three-dimensional reconstruction of the coronary arteries using artificial intelligence. Subsequently, functional assessment was performed through a deep learning algorithm. FFR was used as the reference. Results: FFRCT-angio values were significantly correlated with FFR values (r = 0.81, P < 0.001, Spearman analysis). Per-vessel diagnostic accuracy of FFRCT-angio was 92.54%. Sensitivity and specificity in identifying ischemic lesions were 100% and 88.10%, respectively. Positive predictive value and negative predictive value were 83.33% and 100%, respectively. Moreover, the diagnostic performance of FFRCT-angio was satisfactory in different target vessels and different segment lesions. Conclusions: FFRCT-angio exhibits excellent diagnostic performance of identifying ischemic lesions in patients with stable CAD. Combining CCTA and angiographic imaging, FFRCT-angio may represent an effective and practical alternative to invasive FFR in selected patients.

Structural protein fold recognition based on secondary structure and evolutionary information using machine learning algorithms.

Understanding the function of protein is conducive to research in advanced fields such as gene therapy of diseases, the development and design of new drugs, etc. The prerequisite for understanding the function of a protein is to determine its tertiary structure. The realization of protein structure classification is indispensable for this problem and fold recognition is a commonly used method of protein structure classification. Protein sequences of 40% identity in the ASTRAL protein classification database are used for fold recognition research in current work to predict 27 folding types which mostly belong to four protein structural classes: α, ß, α/ß and α + ß. We extract features from primary structure of protein using methods covering DSSP, PSSM and HMM which are based on secondary structure and evolutionary information to convert protein sequences into feature vectors that can be recognized by machine learning algorithm and utilize the combination of LightGBM feature selection algorithm and incremental feature selection method (IFS) to find the optimal classifiers respectively constructed by machine learning algorithms on the basis of tree structure including Random Forest, XGBoost and LightGBM. Bayesian optimization method is used for hyper-parameter adjustment of machine learning algorithms to make the accuracy of fold recognition reach as high as 93.45% at last. The result obtained by the model we propose is outstanding in the study of protein fold recognition.

BERT-m7G: A Transformer Architecture Based on BERT and Stacking Ensemble to Identify RNA N7-Methylguanosine Sites from Sequence Information.

As one of the most prevalent posttranscriptional modifications of RNA, N7-methylguanosine (m7G) plays an essential role in the regulation of gene expression. Accurate identification of m7G sites in the transcriptome is invaluable for better revealing their potential functional mechanisms. Although high-throughput experimental methods can locate m7G sites precisely, they are overpriced and time-consuming. Hence, it is imperative to design an efficient computational method that can accurately identify the m7G sites. In this study, we propose a novel method via incorporating BERT-based multilingual model in bioinformatics to represent the information of RNA sequences. Firstly, we treat RNA sequences as natural sentences and then employ bidirectional encoder representations from transformers (BERT) model to transform them into fixed-length numerical matrices. Secondly, a feature selection scheme based on the elastic net method is constructed to eliminate redundant features and retain important features. Finally, the selected feature subset is input into a stacking ensemble classifier to predict m7G sites, and the hyperparameters of the classifier are tuned with tree-structured Parzen estimator (TPE) approach. By 10-fold cross-validation, the performance of BERT-m7G is measured with an ACC of 95.48% and an MCC of 0.9100. The experimental results indicate that the proposed method significantly outperforms state-of-the-art prediction methods in the identification of m7G modifications.