Background MicroRNAs (miRNAs) emerge in various organisms, ranging from viruses to humans, and play crucial regulatory roles within cells, participating in a variety of biological processes. In ...numerous prediction methods for miRNA-disease associations, the issue of over-dependence on both similarity measurement data and the association matrix still hasn't been improved. In this paper, a miRNA-Disease association prediction model (called TP-MDA) based on tree path global feature extraction and fully connected artificial neural network (FANN) with multi-head self-attention mechanism is proposed. The TP-MDA model utilizes an association tree structure to represent the data relationships, multi-head self-attention mechanism for extracting feature vectors, and fully connected artificial neural network with 5-fold cross-validation for model training. Results The experimental results indicate that the TP-MDA model outperforms the other comparative models, AUC is 0.9714. In the case studies of miRNAs associated with colorectal cancer and lung cancer, among the top 15 miRNAs predicted by the model, 12 in colorectal cancer and 15 in lung cancer were validated respectively, the accuracy is as high as 0.9227. Conclusions The model proposed in this paper can accurately predict the miRNA-disease association, and can serve as a valuable reference for data mining and association prediction in the fields of life sciences, biology, and disease genetics, among others. Graphical Keywords: Association tree, Multi-head self-attention mechanism, miRNA-disease association, Deep learning, Cancer
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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Baicalein is the main active compound of Scutellaria baicalensis Georgi, a medicinal herb with multiple pharmacological activities, including the broad anti-virus effects. In this ...paper, the preclinical study of baicalein on the treatment of COVID-19 was performed. Results showed that baicalein inhibited cell damage induced by SARS-CoV-2 and improved the morphology of Vero E6 cells at a concentration of 0.1 μM and above. The effective concentration could be reached after oral administration of 200 mg/kg crystal form β of baicalein in rats. Furthermore, baicalein significantly inhibited the body weight loss, the replication of the virus, and relieved the lesions of lung tissue in hACE2 transgenic mice infected with SARS-CoV-2. In LPS-induced acute lung injury of mice, baicalein improved the respiratory function, inhibited inflammatory cell infiltration in the lung, and decreased the levels of IL-1β and TNF-α in serum. In conclusion, oral administration of crystal form β of baicalein could reach its effective concentration against SARS-CoV-2. Baicalein could inhibit SARS-CoV-2-induced injury both in vitro and in vivo. Therefore, baicalein might be a promising therapeutic drug for the treatment of COVID-19.
In complex urban traffic scenarios, autonomous vehicles face significant challenges in adapting to diverse and dynamic traffic conditions. Reward-based reinforcement learning has emerged as an ...effective approach to tackle these challenges. This paper presents a novel method that combines deep reinforcement learning with automotive dynamics systems. Building upon the Double Deep Q-learning algorithm, our approach integrates a Recurrent Neural Network with Gated Recurrent Units to enhance the environmental exploration capabilities of autonomous vehicles. To obtain more precise reward values, we introduce a trajectory tracking algorithm based on a combination of proportional-integral-derivative control and feedforward control within the automotive dynamics system. The proportional-integral-derivative controller is utilized for longitudinal control, while the Error-Optimized feedforward controller enhances lateral control, thereby improving trajectory tracking accuracy. Finally, extensive simulation experiments are conducted to evaluate the proposed method, comparing it against other baseline methods in terms of vehicle following and lane-changing scenarios. The results demonstrate that our approach significantly improves both the reward values and control performance of the algorithm.
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•Novel DDQN_PID_LEO algorithm: DDQN, PID, and lateral control fusion.•Realistic traffic simulations in UE4 for dynamic scenarios.•Enhanced vehicle control with minimized lateral errors.•DDQN reinforcement learning for rewarding collision avoidance.
Abstract
Endoplasmic reticulum (ER) stress is a cellular state that results from the overload of unfolded/misfolded protein in the ER that, if not resolved properly, can lead to cell death. Both ...acute lung infections and chronic lung diseases have been found related to ER stress. Yet no study has been presented integrating metabolomic and transcriptomic data from total lung in interpreting the pathogenic state of ER stress. Total mouse lungs were used to perform LC–MS and RNA sequencing in relevance to ER stress. Untargeted metabolomics revealed 16 metabolites of aberrant levels with statistical significance while transcriptomics revealed 1593 genes abnormally expressed. Enrichment results demonstrated the injury ER stress inflicted upon lung through the alteration of multiple critical pathways involving energy expenditure, signal transduction, and redox homeostasis. Ultimately, we have presented p-cresol sulfate (PCS) and trimethylamine N-oxide (TMAO) as two potential ER stress biomarkers. Glutathione metabolism stood out in both omics as a notably altered pathway that believed to take important roles in maintaining the redox homeostasis in the cells critical for the development and relief of ER stress, in consistence with the existing reports.
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•Puerarin ameliorates muscle wasting in type 1 diabetic rats.•Puerarin improves skeletal muscle weight and strength in type 1 diabetic rats.•Puerarin promotes transformation of muscle ...fiber types from slow-twitch to fast-twitch in type 1 diabetic rats.•Puerarin activates Akt/mTOR while inhibites autophagy in skeletal muscle.
Puerarin is an isoflavonoid extracted from Pueraria lobate with extensive pharmacological effects in traditional Chinese medicine. The evidence implicates that puerarin mitigates hyperglycemia and various relevant complications. Here, the effect of puerarin on skeletal muscle wasting induced by type 1 diabetes (T1D) was explored. Streptozotocin (STZ)-induced T1D male Sprague Dawley (SD) rats were used in this study. Muscle strength, weight and size were measured. L6 rat skeletal muscle cells were applied for in vitro study. Our results showed that eight-week oral puerarin administration (100 mg/kg) increased muscle strengths and weights accompanied by enhanced skeletal muscle cross-sectional areas in diabetic rats. Simultaneously, puerarin also reduced expressions of several muscle wasting marker genes including F-box only protein 32 (Atrogin-1) and muscle-specific RING-finger 1 (Murf-1) in diabetic group both in vitro and in vivo. Transformation from type I fibers (slow muscle) to type II fibers (fast muscle) were also observed under puerarin administration in diabetic rats. Puerarin promoted Akt/mTOR while inhibited LC3/p62 signaling pathway in skeletal muscle cells. In conclusion, our study showed that puerarin mitigated skeletal muscle wasting in T1D rats and closely related with Akt/mTOR activation and autophagy inhibition. Whether this effect in murine applies to humans remains to be determined.
Background/Aims: Glomerular endothelium dysfunction leads to the progression of renal architectonic and functional abnormalities in early-stage diabetic nephropathy (DN). Advanced glycation end ...products (AGEs) and receptor for AGEs (RAGE) are proved to play important roles in diabetic nephropathy. This study investigated the role of Salvianolic acid A (SalA) on early-stage DN and its possible underlying mechanism. Methods: In vitro AGEs formation and breaking rate were measured to illustrate the effect of SalA on AGEs. Type 2 diabetic nephropathy rats were induced by high-fat diet and low-dose streptozocin (STZ). After eight-week treatment with SalA 1 mg/kg/day, 24h-urine protein, creatinine clearance was tested and renal structural injury was assessed by PAS and PASM staining. Primary glomerular endothelial cell permeability was evaluated after exposed to AGEs. AGEs-induced RhoA/ROCK and subsequently activated disarrange of cytoskeleton were assessed by western blot and immunofluorescence. Results: Biochemical assay and histological examination demonstrated that SalA markedly reduced endothelium loss and glomerular hyperfiltration, suppressed glomerular hypertrophy and mesangial matrix expansion, eventually reduced urinary albumin and ameliorated renal function. Further investigation suggested that SalA exerted its renoprotective effects through inhibiting AGE-RAGE signaling. It not only inhibited formation of AGEs and increased its breaking in vitro, but also reduced AGEs accumulation in vivo and downregulated RAGE expression. SalA restored glomerular endothelial permeability through suppressing AGEs-induced rearrangement of actin cytoskeleton via AGE-RAGE-RhoA/ ROCK pathway. Moreover, SalA attenuated oxidative stress induced by AGEs, subsequently alleviated inflammation and restored the disturbed autophagy in glomerular endothelial cell and diabetic rats via AGE-RAGE-Nox4 axis. Conclusion: Our study indicated that SalA restored glomerular endothelial function and alleviated renal structural deterioration through inhibiting AGE-RAGE, thus effectively ameliorated early-stage diabetic nephropathy. SalA might be a promising therapeutic agent for the treatment of diabetic nephropathy.
Long non-coding RNAs (lncRNAs) have been shown to play a regulatory role in various processes of human diseases. However, lncRNA experiments are inefficient, time-consuming and highly subjective, so ...that the number of experimentally verified associations between lncRNA and diseases is limited. In the era of big data, numerous machine learning methods have been proposed to predict the potential association between lncRNA and diseases, but the characteristics of the associated data were seldom explored. In these methods, negative samples are randomly selected for model training and the model is prone to learn the potential positive association error, thus affecting the prediction accuracy. In this paper, we proposed a cyclic optimization model of predicting lncRNA-disease associations (COPTLDA in short). In COPTLDA, the two-step training strategy is adopted to search for the samples with the greater probability of being negative examples from unlabeled samples and the determined samples are treated as negative samples, which are combined together with known positive samples to train the model. The searching and training steps are repeated until the best model is obtained as the final prediction model. In order to evaluate the performance of the model, 30% of the known positive samples are used to calculate the model accuracy and 10% of positive samples are used to calculate the recall rate of the model. The sampling strategy used in this paper can improve the accuracy and the AUC value reaches 0.9348. The results of case studies showed that the model could predict the potential associations between lncRNA and malignant tumors such as colorectal cancer, gastric cancer, and breast cancer. The predicted top 20 associated lncRNAs included 10 colorectal cancer lncRNAs, 2 gastric cancer lncRNAs, and 8 breast cancer lncRNAs.
Systemic lupus erythaematosus (SLE) is a chronic multi-system autoimmune disease with a high prevalence of kidney and cardiovascular complications. Considering that Rho-associated ...coiled-coil-containing protein kinases (ROCKs) play important roles in SLE, inflammation, and cardiovascular disease, we hypothesized that coptisine, which has been found to inhibit ROCKs, may have an effect on SLE. The effect of coptisine was assessed in female BALB/c mice intraperitoneally injected with 0.5 mL of pristane. Serum autoantibodies were tested every month, blood pressure was measured every 2 months, and serum inflammatory markers, spleen pathologic characteristics, renal injury and vascular function were observed at 6 months. The results showed that coptisine decreased the levels of serum autoantibodies and serum inflammatory markers in the SLE mice, improved the pathologic characteristics of the spleen, and simultaneously improved renal injury, decreased inflammatory responses in the kidneys, reduced blood pressure, and improved vascular endothelial function. Western blot assays revealed that inhibiting the activation of the NF-κB and Rho/ROCK signalling pathways and downstream signalling molecules might be the potential mechanisms of the effects of coptisine. Our findings suggest that therapy with coptisine may be a strategy for preventing SLE and ameliorating associated kidney and cardiovascular complications.
Metabolic changes associated with diabetes are reported to lead to the onset of early-stage diabetic nephropathy (DN). Furthermore, lipotoxicity is implicated in renal dysfunction. Most studies of DN ...have focused on a single or limited number of lipids, and the lipidome of the kidney during early-stage DN remains to be elucidated. In the present study, we aimed to comprehensively identify lipid abnormalities during early-stage DN; to this end, we established an early-stage DN rat model by feeding a high-sucrose and high-fat diet combined with administration of low-dose streptozotocin. Using a high-coverage, targeted lipidomic approach, we established the lipid profile, comprising 437 lipid species and 25 lipid classes, of the kidney cortex in normal rats and the DN rat model. Our findings additionally confirmed that the DN rat model had been successfully established. We observed distinct lipidomic signatures in the DN kidney, with characteristic alterations in side chain composition and degree of unsaturation. Glyceride lipids, especially cholesteryl esters, showed a significant increase in the DN kidney cortex. The levels of most phospholipids exhibited a decline, except those of phospholipids with side chain of 36:1. Furthermore, the levels of lyso-phospholipids and sphingolipids, including ceramide and its derivatives, were dramatically elevated in the present DN rat model. Our findings, which provide a comprehensive lipidome of the kidney cortex in rats with DN, are expected to be useful for the identification of pathologically relevant lipid species in DN. Furthermore, the results represent novel insights into the mechanistic basis of DN.
Natural products have been the main sources of new drugs. The different strategies have been developed to find the new drugs based on natural products. The traditional and ethic medicines have ...provided information on the therapeutic effects and resulted in some notable drug discovery of natural products. The special activities of the medicine plants such as the side effects have inspired scientists to develop the novel small molecular. The microorganisms and the endogenous active substances from human or animal also become the important approaches to the drug discovery. The tremendous progress in technology led to the new strategies in drug discovery from natural products. The bioinformation and artificial intelligence have facilitated the research and development of natural products. We will provide a scene of strategies and technologies for drug discovery from natural products in this review.
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