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In this study, the polyphenols composition and antioxidant properties of 12 blue highland barley varieties planted on the Qinghai-Tibet Plateau area were measured. The contents of the free, bound and total phenolic acids varied between 166.20–237.60, 170.10–240.75 and 336.29–453.94 mg of gallic acid equivalents per 100 g of dry weight (DW) blue highland barley grains, while the free and bound phenolic acids accounted for 50.09% and 49.91% of the total phenolic acids, respectively. The contents of the free, bound and total flavones varied among 20.61–25.59, 14.91–22.38 and 37.91–47.98 mg of catechin equivalents per 100 g of dry weight (DW) of blue highland barley grains, while the free and bound flavones accounted for 55.90% and 44.10% of the total flavones, respectively. The prominent phenolic compounds in the blue hulless barley grains were gallic acid, benzoic acid, syringic acid, 4-coumaric acid, naringenin, hesperidin, rutin, (+)-catechin and quercetin. Among these, protocatechuic acid, chlorogenic acid and (+)-catechin were the major phenolic compounds in the free phenolics extract. The most abundant bound phenolics were gallic acid, benzoic acid, syringic acid, 4-coumaric acid, benzoic acid, dimethoxybenzoic acid, naringenin, hesperidin, quercetin and rutin. The average contribution of the bound phenolic extract to the DPPH• free radical scavenging capacity was higher than 86%, that of free phenolic extract to the ABTS•+ free radical scavenging capacity was higher than 79%, and that of free phenolic (53%) to the FRAP antioxidant activity was equivalent to that of the bound phenol extract (47%). In addition, the planting environment exerts a very important influence on the polyphenol composition, content and antioxidant activity of blue highland barley. The correlation analysis showed that 2,4-hydroxybenzoic acid and protocatechuic acid were the main contributors to the DPPH• and ABTS•+ free radical scavenging capacity in the free phenolic extract, while chlorogenic acid, vanillic acid, ferulic acid and quercetin were the main contributors to the free radical scavenging capacity in the bound phenol extract. The study results show that the blue highland barley grains have rich phenolic compounds and high antioxidant activity, as well as significant varietal differences. The free and bound phenolic extracts in the blue hulless barley grains have an equivalent proportion in the total phenol, and co-exist in two forms. They can be used as a potential valuable source of natural antioxidants, and can aid in enhancing the development and daily consumption of foods relating to blue highland barley.

Background Metabolic reprogramming and epigenetic alterations contribute to the aggressiveness of pancreatic ductal adenocarcinoma (PDAC). Lactate-dependent histone modification is a new type of histone mark, which links glycolysis metabolite to the epigenetic process of lactylation. However, the role of histone lactylation in PDAC remains unclear. Methods The level of histone lactylation in PDAC was identified by western blot and immunohistochemistry, and its relationship with the overall survival was evaluated using a Kaplan-Meier survival plot. The participation of histone lactylation in the growth and progression of PDAC was confirmed through inhibition of histone lactylation by glycolysis inhibitors or lactate dehydrogenase A ( LDHA ) knockdown both in vitro and in vivo. The potential writers and erasers of histone lactylation in PDAC were identified by western blot and functional experiments. The potential target genes of H3K18 lactylation (H3K18la) were screened by CUT&Tag and RNA-seq analyses. The candidate target genes TTK protein kinase ( TTK ) and BUB1 mitotic checkpoint serine/threonine kinase B ( BUB1B ) were validated through ChIP-qPCR, RT-qPCR and western blot analyses. Next, the effects of these two genes in PDAC were confirmed by knockdown or overexpression. The interaction between TTK and LDHA was identified by Co-IP assay. Results Histone lactylation, especially H3K18la level was elevated in PDAC, and the high level of H3K18la was associated with poor prognosis. The suppression of glycolytic activity by different kinds of inhibitors or LDHA knockdown contributed to the anti-tumor effects of PDAC in vitro and in vivo. E1A binding protein p300 (P300) and histone deacetylase 2 were the potential writer and eraser of histone lactylation in PDAC cells, respectively. H3K18la was enriched at the promoters and activated the transcription of mitotic checkpoint regulators TTK and BUB1B . Interestingly, TTK and BUB1B could elevate the expression of P300 which in turn increased glycolysis. Moreover, TTK phosphorylated LDHA at tyrosine 239 (Y239) and activated LDHA, and subsequently upregulated lactate and H3K18la levels. Conclusions The glycolysis-H3K18la-TTK/BUB1B positive feedback loop exacerbates dysfunction in PDAC. These findings delivered a new exploration and significant inter-relationship between lactate metabolic reprogramming and epigenetic regulation, which might pave the way toward novel lactylation treatment strategies in PDAC therapy.

Due to advances in semiconductor processing technologies, each slice of a semiconductor is becoming denser and more complex, which can increase the number of surface defects. These defects should be caught early and correctly classified in order help identify the causes of these defects in the process and eventually help to improve the yield. In today’s semiconductor industry, visible surface defects are still being inspected manually, which may result in erroneous classification when the inspectors become tired or lose objectivity. This paper presents a vision-based machine-learning-based method to classify visible surface defects on semiconductor wafers. The proposed method uses deep learning convolutional neural networks to identify and classify four types of surface defects: center, local, random, and scrape. Experiments were performed to determine its accuracy. The experimental results showed that this method alone, without additional refinement, could reach a top accuracy in the range of 98% to 99%. Its performance in wafer-defect classification shows superior performance compared to other machine-learning methods investigated in the experiments.

Drug-induced cardiotoxicity arises primarily when a compound alters the electrophysiological properties of cardiomyocytes. Features of intracellular action potentials (iAPs) are powerful biomarkers that predict proarrhythmic risks. In the last decade, a number of vertical nanoelectrodes have been demonstrated to achieve parallel and minimally-invasive iAP recordings. However, the large variability in success rate and signal strength have hindered nanoelectrodes from being broadly adopted for proarrhythmia drug assessment. In this work, we develop vertically-aligned nanocrown electrodes that are mechanically robust and achieve > 99% success rates in obtaining intracellular access through electroporation. We validate the accuracy of nanocrown electrode recordings by simultaneous patch clamp recording from the same cell. Finally, we demonstrate that nanocrown electrodes enable prolonged iAP recording for continual monitoring of the same cells upon the sequential addition of four incremental drug doses. Our technology development provides an advancement towards establishing an iAP screening assay for preclinical evaluation of drug-induced arrhythmogenicity. Nanoelectrodes for measuring intracellular action potentials suffer from issues with success rate, signal strength and fabrication. Here, the authors report on a scalable technique which creates robust nanocrown electrodes with high success rates by electroporation and demonstrate the advance towards preclinical drug evaluation.

Melittin is a prototype of the ubiquitous antimicrobial peptides that induce pores in membranes. It is commonly used as a molecular device for membrane permeabilization. Even at concentrations in the nanomolar range, melittin can induce transient pores that allow transmembrane conduction of atomic ions but not leakage of glucose or larger molecules. At micromolar concentrations, melittin induces stable pores allowing transmembrane leakage of molecules up to tens of kilodaltons, corresponding to its antimicrobial activities. Despite extensive studies, aspects of the molecular mechanism for pore formation remain unclear. To clarify the mechanism, one must know the states of the melittin-bound membrane before and after the process. By correlating experiments using giant unilamellar vesicles with those of peptide-lipid multilayers, we found that melittin bound on the vesicle translocated and redistributed to both sides of the membrane before the formation of stable pores. Furthermore, stable pores are formed only above a critical peptide-to-lipid ratio. The initial states for transient and stable pores are different, which implies different mechanisms at low and high peptide concentrations. To determine the lipidie structure of the pore, the pores in peptide-lipid multilayers were induced to form a lattice and examined by anomalous X-ray diffraction. The electron density distribution of lipid labels shows that the pore is formed by merging of two interfaces through a hole. The molecular property of melittin is such that it adsorbs strongly to the bilayer interface. Pore formation can be viewed as the bilayer adopting a lipid configuration to accommodate its excessive interfacial area.

Clinical observations have shown that cases of stroke or thromboembolism are not uncommon even in the absence of atrial fibrillation, suggesting that atrial fibrillation is a delayed marker of atrial thrombus formation. Atrial cardiomyopathy (ACM) is a pathophysiological concept characterized by atrial substrate and functional abnormalities closely associated with atrial myopathy, atrial enlargement, and impaired ventricular diastolic function. It is an independent factor for thromboembolic stroke, increasing the risk of serious complications such as atrial fibrillation, heart failure, and sudden cardiac death. ACM is likely to be a potential cause of embolic stroke, especially cryptogenic stroke, and early identification of patients at high thromboembolic risk is essential to guide anticoagulation therapy. Although the pathogenesis of ACM has not been fully elucidated, prospective mechanism-based studies have revealed the important role of activated cardiac immune cells along with inflammatory responses, oxidative stress, and other factors in its progression. Exploring the role of immune regulation in the pathogenesis of ACM provides new insights into the underlying mechanisms of cerebrovascular events of cardiac thromboembolic origin. This review summarizes the mechanisms by which immune regulation is involved in the progression of ACM and provides useful insights for future clinical diagnosis and treatment.

Long QT syndrome (LQTS) is a detrimental arrhythmia syndrome mainly caused by dysregulated expression or aberrant function of ion channels. The major clinical symptoms of ventricular arrhythmia, palpitations and syncope vary among LQTS subtypes. Susceptibility to malignant arrhythmia is a result of delayed repolarisation of the cardiomyocyte action potential (AP). There are 17 distinct subtypes of LQTS linked to 15 autosomal dominant genes with monogenic mutations. However, due to the presence of modifier genes, the identical mutation may result in completely different clinical manifestations in different carriers. In this review, we describe the roles of various ion channels in orchestrating APs and discuss molecular aetiologies of various types of LQTS. We highlight the usage of patient-specific induced pluripotent stem cell (iPSC) models in characterising fundamental mechanisms associated with LQTS. To mitigate the outcomes of LQTS, treatment strategies are initially focused on small molecules targeting ion channel activities. Next-generation treatments will reap the benefits from development of LQTS patient-specific iPSC platform, which is bolstered by the state-of-the-art technologies including whole-genome sequencing, CRISPR genome editing and machine learning. Deep phenotyping and high-throughput drug testing using LQTS patient-specific cardiomyocytes herald the upcoming precision medicine in LQTS.

Conventional technologies for virtual and augmented reality simulate interactive experiences through visual and auditory stimuli. A technology that adds sensations of touch could find uses in areas from gaming to prosthetic feedback. Skin-integrated wireless touch-based interfaces.

Due to the strong infectivity of COVID-19, it spread all over the world in about three months and thus has been studied from different aspects including its source of infection, pathological characteristics, diagnostic technology and treatment. Yet, the influences of control strategies on the transmission dynamics of COVID-19 are far from being well understood. In order to reveal the mechanisms of disease spread, we present dynamical models to show the propagation of COVID-19 in Wuhan. Based on mathematical analysis and data analysis, we systematically explore the effects of lockdown and medical resources on the COVID-19 transmission in Wuhan. It is found that the later lockdown is adopted by Wuhan, the fewer people will be infected in Wuhan, and nevertheless it will have an impact on other cities in China and even the world. Moreover, the richer the medical resources, the higher the peak of new infection, but the smaller the final scale. These findings well indicate that the control measures taken by the Chinese government are correct and timely.

Recognizing why an infant cries is challenging as babies cannot communicate verbally with others to express their wishes or needs. This leads to difficulties for parents in identifying the needs and the health of their infants. This study used deep learning (DL) algorithms such as the convolutional neural network (CNN) and long short-term memory (LSTM) to recognize infants’ necessities such as hunger/thirst, need for a diaper change, emotional needs (e.g., need for touch/holding), and pain caused by medical treatment (e.g., injection). The classical artificial neural network (ANN) was also used for comparison. The inputs of ANN, CNN, and LSTM were the features extracted from 1607 10 s audio recordings of infants using mel-frequency cepstral coefficients (MFCC). Results showed that CNN and LSTM both provided decent performance, around 95% in accuracy, precision, and recall, in differentiating healthy and sick infants. For recognizing infants’ specific needs, CNN reached up to 60% accuracy, outperforming LSTM and ANN in almost all measures. These results could be applied as indicators for future applications to help parents understand their infant’s condition and needs.