High Throughput Sequencing Identifies MicroRNAs Mediating α-Synuclein Toxicity by Targeting Neuroactive-Ligand Receptor Interaction Pathway in Early Stage of Drosophila Parkinson\u27s Disease Model.

Parkinson\u27s disease (PD) is a prevalent neurodegenerative disorder with pathological features including death of dopaminergic neurons in the substantia nigra and intraneuronal accumulations of Lewy bodies. As the main component of Lewy bodies, α-synuclein is implicated in PD pathogenesis by aggregation into insoluble filaments. However, the detailed mechanisms underlying α-synuclein induced neurotoxicity in PD are still elusive. MicroRNAs are ~20nt small RNA molecules that fine-tune gene expression at posttranscriptional level. A plethora of miRNAs have been found to be dysregulated in the brain and blood cells of PD patients. Nevertheless, the detailed mechanisms and their in vivo functions in PD still need further investigation. By using Drosophila PD model expressing α-synuclein A30P, we examined brain miRNA expression with high-throughput small RNA sequencing technology. We found that five miRNAs (dme-miR-133-3p, dme-miR-137-3p, dme-miR-13b-3p, dme-miR-932-5p, dme-miR-1008-5p) were upregulated in PD flies. Among them, miR-13b, miR-133, miR-137 are brain enriched and highly conserved from Drosophila to humans. KEGG pathway analysis using DIANA miR-Path demonstrated that neuroactive-ligand receptor interaction pathway was most likely affected by these miRNAs. Interestingly, miR-137 was predicted to regulate most of the identified targets in this pathway, including dopamine receptor (DopR, D2R), γ-aminobutyric acid (GABA) receptor (GABA-B-R1, GABA-B-R3) and N-methyl-D-aspartate (NMDA) receptor (Nmdar2). The validation experiments showed that the expression of miR-137 and its targets was negatively correlated in PD flies. Further experiments using luciferase reporter assay confirmed that miR-137 could act on specific sites in 3\u27 UTR region of D2R, Nmdar2 and GABA-B-R3, which downregulated significantly in PD flies. Collectively, our findings indicate that α-synuclein could induce the dysregulation of miRNAs, which target neuroactive ligand-receptor interaction pathway in vivo. We believe it will help us further understand the contribution of miRNAs to α-synuclein neurotoxicity and provide new insights into the pathogenesis driving PD

Nickel-based superalloy architectures with surface mechanical attrition treatment:Compressive properties and collapse behaviour

Surface modifications can introduce natural gradients or structural hierarchy into human-made microlattices, making them simultaneously strong and tough. Herein, we describe our investigations of the mechanical properties and the underlying mechanisms of additively manufactured nickel–chromium superalloy (IN625) microlattices after surface mechanical attrition treatment (SMAT). Our results demonstrated that SMAT increased the yielding strength of these microlattices by more than 64.71% and also triggered a transition in their mechanical behaviour. Two primary failure modes were distinguished: weak global deformation, and layer-by-layer collapse, with the latter enhanced by SMAT. The significantly improved mechanical performance was attributable to the ultrafine and hard graded-nanograin layer induced by SMAT, which effectively leveraged the material and structural effects. These results were further validated by finite element analysis. This work provides insight into collapse behaviour and should facilitate the design of ultralight yet buckling-resistant cellular materials.</p

Crosstalk between the Circadian Clock and Innate Immunity in Arabidopsis

Plants are frequently challenged by various pathogens. The circadian clock, which is the internal time measuring machinery, has been implicated in regulating plant responses to biotic cues. To better understand the role of the circadian clock in defense control, we tested disease resistance with Arabidopsis mutants disrupted in CCA1 and LHY , two key components of the circadian clock. We found that consistent with their contributions to the circadian clock, cca1 and lhy mutants synergistically affect resistance to both bacterial and oomycete pathogens. Disrupting the circadian clock caused by overexpression of CCA1 or LHY also results in severe disease susceptibility. Thus, our data further demonstrate a direct role of the circadian clock mediated by CCA1 and LHY in defense regulation. We also found that CCA1 and LHY act independently of salicylic acid mediated defense but at least through the down- stream target gene GRP7 to regulate both stomata- dependent and -independent pathways. We further show that defense activation by bacterial infection and the treatment with the elicitor flg22 can also feed back to regulate clock activity. Together our study reveals for the first time reciprocal regulation of the circadian clock and plant innate immunity, significantly expanding our view of complex gene networks regulating plant defense responses and development

Crosstalk between the Circadian Clock and Innate Immunity in Arabidopsis

Plants are frequently challenged by various pathogens. The circadian clock, which is the internal time measuring machinery, has been implicated in regulating plant responses to biotic cues. To better understand the role of the circadian clock in defense control, we tested disease resistance with Arabidopsis mutants disrupted in CCA1 and LHY , two key components of the circadian clock. We found that consistent with their contributions to the circadian clock, cca1 and lhy mutants synergistically affect resistance to both bacterial and oomycete pathogens. Disrupting the circadian clock caused by overexpression of CCA1 or LHY also results in severe disease susceptibility. Thus, our data further demonstrate a direct role of the circadian clock mediated by CCA1 and LHY in defense regulation. We also found that CCA1 and LHY act independently of salicylic acid mediated defense but at least through the down- stream target gene GRP7 to regulate both stomata- dependent and -independent pathways. We further show that defense activation by bacterial infection and the treatment with the elicitor flg22 can also feed back to regulate clock activity. Together our study reveals for the first time reciprocal regulation of the circadian clock and plant innate immunity, significantly expanding our view of complex gene networks regulating plant defense responses and development

Stomatal response to decreased relative humidity constrains the acceleration of terrestrial evapotranspiration

Terrestrial evapotranspiration (ET) is thermodynamically expected to increase with increasing atmospheric temperature; however, the actual constraints on the intensification of ET remain uncertain due to a lack of direct observations. Based on the FLUXNET2015 Dataset, we found that relative humidity (RH) is a more important driver of ET than temperature. While actual ET decrease at reduced RH, potential ET increases, consistently with the complementary relationship (CR) framework stating that the fraction of energy not used for actual ET is dissipated as increased sensible heat flux that in turn increases potential ET. In this study, we proposed an improved CR formulation requiring no parameter calibration and assessed its reliability in estimating ET both at site-level with the FLUXNET2015 Dataset and at basin-level. Using the ERA-Interim meteorological dataset for 1979-2017 to calculate ET, we found that the global terrestrial ET showed an increasing trend until 1998, while the trend started to decline afterwards. Such decline was largely associated with a reduced RH, inducing water stress conditions that triggered stomatal closure to conserve water. For the first time, this study quantified the global-scale implications of changes in RH on terrestrial ET, indicating that the temperature-driven acceleration of the terrestrial water cycle will be likely constrained by terrestrial vegetation feedbacks.Peer reviewe

L-Met Activates Arabidopsis GLR Ca2+ Channels Upstream of ROS Production and Regulates Stomatal Movement

Plant glutamate receptor homologs (GLRs) have long been proposed to function as ligand-gated Ca2+ channels, but no in planta evidence has been provided. Here, we present genetic evidence that Arabidopsis GLR3.1 and GLR3.5 form Ca2+ channels activated by L-methionine (L-Met) at physiological concentrations and regulate stomatal apertures and plant growth. The glr3.1/3.5 mutations resulted in a lower cytosolic Ca2+ level, defective Ca2+-induced stomatal closure, and Ca2+-deficient growth disorder, all of which involved L-Met. Patch-clamp analyses of guard cells showed that GLR3.1/3.5 Ca2+ channels are activated specifically by L-Met, with the activation abolished in glr3.1/3.5. Moreover, GLR3.1/3.5 Ca2+ channels are distinct from previously characterized ROS-activated Ca2+ channels and act upstream of ROS, providing Ca2+ transients necessary for the activation of NADPH oxidases. Our data indicate that GLR3.1/3.5 constitute L-Met-activated Ca2+ channels responsible for maintaining basal [Ca2+]cyt, play a pivotal role in plant growth, and act upstream of ROS, thereby regulating stomatal aperture. © 2016 Institute for Basic Science / DGIST1

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

CNN-FWS: A Model for the Diagnosis of Normal and Abnormal ECG with Feature Adaptive

(1) Background and objective: Cardiovascular disease is one of the most common causes of death in today’s world. ECG is crucial in the early detection and prevention of cardiovascular disease. In this study, an improved deep learning method is proposed to diagnose abnormal and normal ECG accurately. (2) Methods: This paper proposes a CNN-FWS that combines three convolutional neural networks (CNN) and recursive feature elimination based on feature weights (FW-RFE), which diagnoses abnormal and normal ECG. F1 score and Recall are used to evaluate the performance. (3) Results: A total of 17,259 records were used in this study, which validated the diagnostic performance of CNN-FWS for normal and abnormal ECG signals in 12 leads. The experimental results show that the F1 score of CNN-FWS is 0.902, and the Recall of CNN-FWS is 0.889. (4) Conclusion: CNN-FWS absorbs the advantages of convolutional neural networks (CNN) to obtain three parts of different spatial information and enrich the learned features. CNN-FWS can select the most relevant features while eliminating unrelated and redundant features by FW-RFE, making the residual features more representative and effective. The method is an end-to-end modeling approach that enables an adaptive feature selection process without human intervention

F-Wave Extraction from Single-Lead Electrocardiogram Signals with Atrial Fibrillation by Utilizing an Optimized Resonance-Based Signal Decomposition Method

(1) Background: A typical cardiac cycle consists of a P-wave, a QRS complex, and a T-wave, and these waves are perfectly shown in electrocardiogram signals (ECG). When atrial fibrillation (AF) occurs, P-waves disappear, and F-waves emerge. F-waves contain information on the cause of atrial fibrillation. Therefore it is essential to extract F-waves from the ECG signal. However, F-waves overlap the QRS complex and T-waves in both the time and frequency domain, causing this matter to be a difficult one. (2) Methods: This paper presents an optimized resonance-based signal decomposition method for detecting F-waves in single-lead ECG signals with atrial fibrillation (AF). It represents the ECG signal utilizing morphological component analysis as a linear combination of a finite number of components selected from the high-resonance and low-resonance dictionaries, respectively. The linear combination of components in the low-resonance dictionary reconstructs the oscillatory part (F-wave) of the ECG signal. In contrast, the linear combination of components in the high-resonance dictionary reconstructs the transient components part (QRST wave). The tunable Q-factor wavelet transform generates the high and low resonance dictionaries, with a high Q-factor producing a high resonance dictionary and a low Q-factor producing a low resonance dictionary. The different Q-factor settings affect the dictionaries’ characteristics, hence the F-wave extraction. A genetic algorithm was used to optimize the Q-factor selection to select the optimal Q-factor. (3) Results: The presented method helps reduce RMSE between the extracted and the simulated F-waves compared to average beat subtraction (ABS) and principal component analysis (PCA). According to the amplitude of the F-wave, RMSE is reduced by 0.24–0.32. Moreover, the dominant frequency of F-waves extracted by the presented method is clearer and more resistant to interference. The presented method outperforms the other two methods, ABS and PCA, in F-wave extraction from AF-ECG signals with the ventricular premature heartbeat. (4) Conclusion: The proposed method can potentially improve the accuracy of F-wave extraction for mobile ECG monitoring equipment, especially those with fewer leads