Hyperoside Protects Against Pressure Overload-Induced Cardiac Remodeling via the AKT Signaling Pathway

Background/Aims: Cardiac hypertrophy is a major predisposing factor for heart failure and sudden cardiac death. Hyperoside (Hyp), a flavonoid isolated from Rhododendron ponticum L., is a primary component of Chinese traditional patent medicines. Numerous studies have shown that Hyp exerts marked anti-viral, anti-inflammatory, anti-oxidant, anti-cancer, anti-ischemic, and particularly cardio-protective effects. However, the effects of Hyp on cardiac hypertrophy have not been explored. The aims of this study were to determine whether Hyp could protect against cardiac remodeling and to clarify the potential molecular mechanisms. Methods: Neonatal rat cardiac myocytes were isolated and treated with different concentrations of Hyp, then cultured with angiotensin II for 48 h. Mice were subjected to either aortic banding or sham surgery (control group). One week after surgery, the mice were treated with Hyp (20 mg/kg/day) or vehicle by oral gavage for 7 weeks. Hypertrophy was evaluated by assessing morphological changes, echocardiographic parameters, histology, and biomarkers. Results: Hyp pretreatment suppressed angiotensin II-induced hypertrophy in cardiomyocytes. Hyp exerted no basal effects but attenuated cardiac hypertrophy and dysfunction, fibrosis, inflammation, and oxidative stress induced by pressure overload. Both in vivo and in vitro experiments demonstrated that the effect of Hyp on cardiac hypertrophy was mediated by blocking activation of the AKT signaling pathway. Conclusion: Hyp improves cardiac function and prevents the development of cardiac hypertrophy via AKT signaling. Our results suggest a protective effect of Hyp on pressure overload-induced cardiac remodeling. Taken together, Hyp may have a role in the pharmacological therapy of cardiac hypertrophy

AI of Brain and Cognitive Sciences: From the Perspective of First Principles

Nowadays, we have witnessed the great success of AI in various applications, including image classification, game playing, protein structure analysis, language translation, and content generation. Despite these powerful applications, there are still many tasks in our daily life that are rather simple to humans but pose great challenges to AI. These include image and language understanding, few-shot learning, abstract concepts, and low-energy cost computing. Thus, learning from the brain is still a promising way that can shed light on the development of next-generation AI. The brain is arguably the only known intelligent machine in the universe, which is the product of evolution for animals surviving in the natural environment. At the behavior level, psychology and cognitive sciences have demonstrated that human and animal brains can execute very intelligent high-level cognitive functions. At the structure level, cognitive and computational neurosciences have unveiled that the brain has extremely complicated but elegant network forms to support its functions. Over years, people are gathering knowledge about the structure and functions of the brain, and this process is accelerating recently along with the initiation of giant brain projects worldwide. Here, we argue that the general principles of brain functions are the most valuable things to inspire the development of AI. These general principles are the standard rules of the brain extracting, representing, manipulating, and retrieving information, and here we call them the first principles of the brain. This paper collects six such first principles. They are attractor network, criticality, random network, sparse coding, relational memory, and perceptual learning. On each topic, we review its biological background, fundamental property, potential application to AI, and future development.Comment: 59 pages, 5 figures, review articl

Combination of Neutrophil Count and Gensini Score as a Prognostic Marker in Patients with ACS and Uncontrolled T2DM Undergoing PCI

Background: Several biomarkers have been studied as prognostic indicators among people with diabetes and coronary artery disease (CAD). The purpose of this study was to determine the prognostic value of neutrophil counts and the Gensini score in patients with diabetes and ACS undergoing percutaneous coronary intervention (PCI). Methods: A total of 694 people with ACS and T2DM who simultaneously had elevated HBA1c received PCI. Spearman rank correlation estimates were used for correlation evaluation. Multivariate Cox regression and Kaplan-Meier analysis were used to identify characteristics associated with major adverse cardiovascular and cerebrovascular events (MACCEs) and patient survival. The effects of single- and multi-factor indices on MACCEs were evaluated through receiver operating characteristic curve analysis. Results: The Gensini score and neutrophil count significantly differed between the MACCE and non-MACCE groups among patients receiving PCI who had concomitant ACS and T2DM with elevated HBA1c (P<0.001). The Gensini score and neutrophil count were strongly associated with MACCEs (log-rank, P<0.001). The Gensini score and neutrophil count, alone or in combination, were predictors of MACCEs, according to multivariate Cox regression analysis (adjusted hazard ratio [HR], 1.005; 95% confidence interval [CI], 1.002–1.008; P=0.002; adjusted HR, 1.512; 95% CI, 1.005–2.274; P=0.047, respectively). The Gensini score was strongly associated with neutrophil count (variance inflation factor ≥ 5). Area under the curve analysis revealed that the combination of multivariate factors predicted the occurrence of MACCEs better than any single variable. Conclusion: In patients with T2DM and ACS with elevated HBA1c who underwent PCI, both the Gensini score and neutrophil count were independent predictors of outcomes. The combination of both predictors has a higher predictability

Association between plasma trimethylamine N -oxide and neoatherosclerosis in patients with very late stent thrombosis

Abstract(#br)Background(#br)Trimethylamine N -oxide (TMAO) has been shown to promote the development of atherosclerosis. However, the relationship between plasma TMAO and neoatherosclerosis, an important underlying mechanism of very late stent thrombosis (VLST), is unknown.(#br)Methods(#br)This post hoc study investigated the association between TMAO and neoatherosclerosis in two independent cohorts. These included a control group of 50 healthy volunteers and a study cohort of 50 patients with VLST who presented with ST-segment elevation myocardial infarction and underwent optical coherence tomography examination. Of the 50 patients with VLST, 23 had neoatherosclerosis and 27 did not have neoatherosclerosis. Patients with neoatherosclerosis were further divided into two subgroups, including 14 patients with plaque rupture and 9 without plaque rupture.(#br)Results(#br)The plasma TMAO levels, detected using mass spectrometry, were significantly higher in patients with VLST than in healthy individuals (median [interquartile range]: 2.50 [1.67-3.84] vs. 1.32 [0.86-2.44] μM; P < 0.001). Among the VLST patients, the plasma TMAO levels were significantly higher in patients with neoatherosclerosis than in those without neoatherosclerosis (3.69 [2.46-5.29] vs. 1.96 [1.39-2.80] μM; P<0.001). In addition, in patients with neoatherosclerosis, patients with plaque rupture had significantly higher plasma TMAO concentrations than those without plaque rupture (4.51 [3.41-5.85] vs. 2.46 [2.05-3.55] μM; P=0.005). Multivariate analysis indicated that TMAO was an independent predictor of neoatherosclerosis (odds ratio 3.41; 95% confidence interval: 1.59-7.30; P=0.002). Moreover, the area under the receiver operating characteristic curve for TMAO, differentiated by neoatherosclerosis, was 0.85.(#br)Conclusions(#br)Plasma TMAO was significantly correlated with neoatherosclerosis and plaque rupture in patients with VLST

Diabetes increases mortality after myocardial infarction by oxidizing CaMKII

Diabetes increases oxidant stress and doubles the risk of dying after myocardial infarction, but the mechanisms underlying increased mortality are unknown. Mice with streptozotocin-induced diabetes developed profound heart rate slowing and doubled mortality compared with controls after myocardial infarction. Oxidized Ca(2+)/calmodulin-dependent protein kinase II (ox-CaMKII) was significantly increased in pacemaker tissues from diabetic patients compared with that in nondiabetic patients after myocardial infarction. Streptozotocin-treated mice had increased pacemaker cell ox-CaMKII and apoptosis, which were further enhanced by myocardial infarction. We developed a knockin mouse model of oxidation-resistant CaMKIIδ (MM-VV), the isoform associated with cardiovascular disease. Streptozotocin-treated MM-VV mice and WT mice infused with MitoTEMPO, a mitochondrial targeted antioxidant, expressed significantly less ox-CaMKII, exhibited increased pacemaker cell survival, maintained normal heart rates, and were resistant to diabetes-attributable mortality after myocardial infarction. Our findings suggest that activation of a mitochondrial/ox-CaMKII pathway contributes to increased sudden death in diabetic patients after myocardial infarction

Multicenter validation of the value of BASFI and BASDAI in Chinese ankylosing spondylitis and undifferentiated spondyloarthropathy patients

The objectives of this study were to evaluate the reliability of Bath ankylosing spondylitis functional index (BASFI) and Bath ankylosing spondylitis disease activity index (BASDAI) in Chinese ankylosing spondylitis (AS) and undifferentiated spondyloarthropathy (USpA) patients. 664 AS patients by the revised New York criteria for AS and 252 USpA patients by the European Spondyloarthropathy Study Group criteria were enrolled. BASDAI and BASFI questionnaires were translated into Chinese. Participants were required to fill in BASFI and BASDAI questionnaires again after 24 h. Moreover, BASDAI and BASFI were compared in AS patients receiving Enbrel or infliximab before and after treatment. For AS group, BASDAI ICC: 0.9502 (95% CI: 0.9330–0.9502, α = 0.9702), BASFI ICC: 0.9587 (95% CI: 0.9521–0.9645, α = 0.9789). For USpA group, BASDAI ICC: 0.9530 (95% CI: 0.9402–0.9632, α = 0.9760), BASFI ICC: 0.9900 (95% CI: 0.9871–0.9922, α = 0.9950). In the AS group, disease duration, occipital wall distance, modified Schober test, chest expansion, ESR, and CRP showed significant correlation with BASDAI and BASFI (all P < 0.01). In the USpA group, onset age, ESR, and CRP were significantly correlated with BASDAI (all P < 0.05), while modified Schober test, ESR, and CRP were significantly associated with BASFI (all P < 0.05). The change in BASDAI and BASFI via Enbrel or infliximab treatment showed a significant positive correlation (P < 0.01). The two instruments have good reliability and reference value regarding the evaluation of patient’s condition and anti-TNF-α treatment response

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Defogging lens design for infrared laser active imaging by orbital angular momentum meta-surface

Imaging in scattering media has been a big problem, as the ballistic light carrying object information is swamped by background noise, thus degrading the imaging quality. In addressing this issue, active illumination imaging technology has various advantages over passive imaging since it can introduce several controllable parameters, such as polarization, coded aperture, and so on. Here, we actively introduce orbital angular momentum into the scattering imaging, which can effectively enhance the mid/high frequency components of the object. Then, it is fused with the low-quality image obtained by traditional imaging, which can effectively enhance the visualization. Compared with the results of direct imaging, the signal-to-noise ratio is improved by up to 250%–300%, and the image contrast is improved by up to 300%–400%. This method may find applications in foggy environments for autonomous driving, lidar, and machine vision

Multi-View Information Fusion Fault Diagnosis Method Based on Attention Mechanism and Convolutional Neural Network

Multi-view information fusion can provide more accurate, complete and reliable data descriptions for monitoring objects, effectively improve the limitations and unreliability of single-view data. Existing multi-view information fusion based on deep learning mostly focuses on the feature level and decision level, with large information loss, and does not distinguish the view weight in the fusion process. To this end, a multi-view data level information fusion model CAM_MCFCNN with view weight was proposed based on a channel attention mechanism and convolutional neural network. The model used the channel characteristics to implement multi-view information fusion at the data level stage, which made the fusion position and mode more natural and reduced the loss of information. A multi-channel fusion convolutional neural network was used for feature learning. In addition, the channel attention mechanism was used to learn the view weight, so that the algorithm could pay more attention to the views that contribute more to the fault identification task during the training process, and more reasonably integrate the information of different views. The proposed method was verified by the data of the planetary gearbox experimental platform. The multi-view data and single-view data were used as the input of the CAM_MCFCNN model and single-channel CNN model respectively for comparison. The average accuracy of CAM_MCFCNN on three constant-speed datasets reached 99.95%, 99.87% and 99.92%, which was an improvement of 0.95%, 2.25%, and 0.04%, compared with the single view with the highest diagnostic accuracy, respectively. When facing limited samples, CAM_MCFCNN had similar performance. Finally, compared with different multi-view information fusion algorithms, CAM_MCFCNN showed better stability and higher accuracy. The experimental results showed that the proposed method had better performance, higher diagnostic accuracy and was more reliable, compared with other methods