Miracle-dz/UniFAR-FTUs huggingface dataset:
Assembly of the β4-Integrin Interactome Based on Proximal Biotinylation in the Presence and Absence of Heterodimerization*

This study characterized the β4-integrin interacting proteome using BioID proximity-dependent biotinylation in epithelial MDCK cells. The analysis identified several novel type II hemidesmosome (HD)-associated proteins and revealed potential connecting protein modules that could orchestrate the observed coordinated coassembly of HDs and focal adhesions (FAs). Curiously, unlike the formation of HDs, the assembly of β4-interactome did not depend on α6β4-heterodimerization. Graphical Abstract Highlights This study reports the first proteomic characterization of a type II hemidesmosomal complex. This study characterizes the interactome of β4-integrin in the presence and absence of α6-integrin in a simple epithelial cell model. The assembly of the β4-integrin interacting complex was largely independent of α6-integrin expression. Integrin-mediated laminin adhesions mediate epithelial cell anchorage to basement membranes and are critical regulators of epithelial cell polarity. Integrins assemble large multiprotein complexes that link to the cytoskeleton and convey signals into the cells. Comprehensive proteomic analyses of actin network-linked focal adhesions (FA) have been performed, but the molecular composition of intermediate filament-linked hemidesmosomes (HD) remains incompletely characterized. Here we have used proximity-dependent biotin identification (BioID) technology to label and characterize the interactome of epithelia-specific β4-integrin that, as α6β4-heterodimer, forms the core of HDs. The analysis identified ∼150 proteins that were specifically labeled by BirA-tagged integrin-β4. In addition to known HDs proteins, the interactome revealed proteins that may indirectly link integrin-β4 to actin-connected protein complexes, such as FAs and dystrophin/dystroglycan complexes. The specificity of the screening approach was validated by confirming the HD localization of two candidate β4-interacting proteins, utrophin (UTRN) and ELKS/Rab6-interacting/CAST family member 1 (ERC1). Interestingly, although establishment of functional HDs depends on the formation of α6β4-heterodimers, the assembly of β4-interactome was not strictly dependent on α6-integrin expression. Our survey to the HD interactome sets a precedent for future studies and provides novel insight into the mechanisms of HD assembly and function of the β4-integrin.
Speech Enhancement via Generative Adversarial LSTM Networks

Recently, deep learning techniques have significantly promoted the development of speech enhancement. In this paper, we propose a novel framework to conduct speech enhancement, which is based on the long short-term memory networks (LSTMs) and conditional generative adversarial networks (cGANs). This framework includes a generator (G) and a discriminator (D). G and $D$ are both LSTMs so our method is able to be more suitable for speech enhancement task than previous deep neural network-based methods. In this study, we firstly apply this framework to map the log-power spectral (LPS) of clean speech given the noisy LPS input. In addition, this framework is also used to estimate the ideal Wiener filter by giving the noisy Cepstral input. Experimental results indicate that our strategy can not only improve the quality and intelligibility of noisy speech, but also is competitive to other deep learning-based approaches.
Identification of Core Biomarkers Associated with Outcome in Glioma: Evidence from Bioinformatics Analysis

Glioma is the most common neoplasm of the central nervous system (CNS); the progression and outcomes of which are affected by a complicated network of genes and pathways. We chose a gene expression profile of GSE66354 from GEO database to search core biomarkers during the occurrence and development of glioma. A total of 149 samples, involving 136 glioma and 13 normal brain tissues, were enrolled in this article. 1980 differentially expressed genes (DEGs) including 697 upregulated genes and 1283 downregulated genes between glioma patients and healthy individuals were selected using GeoDiver and GEO2R tool. Then, gene ontology (GO) analysis as well as Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were carried out using the Database for Annotation, Visualization and Integrated Discovery (DAVID). Moreover, Cytoscape with Search Tool for the Retrieval of Interacting Genes (STRING) and Molecular Complex Detection (MCODE) plug-in was employed to imagine protein-protein interaction (PPI) of these DEGs. The upregulated genes were enriched in cell cycle, ECM-receptor interaction, and p53 signaling pathway, while the downregulated genes were enriched in retrograde endocannabinoid signaling, glutamatergic synapse, morphine addiction, GABAergic synapse, and calcium signaling pathway. Subsequently, 4 typical modules were discovered by the PPI network utilizing MCODE software. Besides, 15 hub genes were chosen according to the degree of connectivity, including TP53, CDK1, CCNB1, and CCNB2, the Kaplan-Meier analysis of which was further identified. In conclusion, this bioinformatics analysis indicated that DEGs and core genes, such as TP53, might influence the development of glioma, especially in tumor proliferation, which were expected to be promising biomarkers for diagnosis and treatment of glioma.
SMOS and SMAP Brightness Temperature Assimilation Over the Murrumbidgee Basin

With the launch of the Soil Moisture and Ocean Salinity (SMOS) mission in 2009 and the Soil Moisture Active-Passive (SMAP) mission in 2015, a wealth of L-band brightness temperature (Tb) observations has become available. In this letter, SMOS and SMAP Tbs are assimilated separately into the Community Land Model over the Murrumbidgee basin in south-east Australia from April 2015 to August 2017. To overcome the seasonal Tb observation-minus-forecast biases, Tb anomalies from the seasonal climatology are assimilated. The use of climatologies derived from either SMOS or SMAP observations using either 2 years or 7 years of data yields nearly identical results, highlighting the limited sensitivity to the climatology computation and their interchangeability. The temporal correlation between soil moisture data assimilation results and in situ observations is slightly improved for top-layer soil moisture (+0.04) and for root-zone soil moisture (+0.05). The soil moisture anomaly correlation improves moderately for the top-layer soil moisture (+0.15), with a smaller positive impact on the root zone (+0.05).
Microbiome analysis of Pacific white shrimp gut and rearing water from Malaysia and Vietnam: implications for aquaculture research and management

Aquaculture production of the Pacific white shrimp is the largest in the world for crustacean species. Crucial to the sustainable global production of this important seafood species is a fundamental understanding of the shrimp gut microbiota and its relationship to the microbial ecology of shrimp pond. This is especially true, given the recently recognized role of beneficial microbes in promoting shrimp nutrient intake and in conferring resistance against pathogens. Unfortunately, aquaculture-related microbiome studies are scarce in Southeast Asia countries despite the severe impact of early mortality syndrome outbreaks on shrimp production in the region. In this study, we employed the 16S rRNA amplicon (V3–V4 region) sequencing and amplicon sequence variants (ASV) method to investigate the microbial diversity of shrimp guts and pond water samples collected from aquaculture farms located in Malaysia and Vietnam. Substantial differences in the pond microbiota were observed between countries with the presence and absence of several taxa extending to the family level. Microbial diversity of the shrimp gut was found to be generally lower than that of the pond environments with a few ubiquitous genera representing a majority of the shrimp gut microbial diversity such as Vibrio and Photobacterium, indicating host-specific selection of microbial species. Given the high sequence conservation of the 16S rRNA gene, we assessed its veracity at distinguishing Vibrio species based on nucleotide alignment against type strain reference sequences and demonstrated the utility of ASV approach in uncovering a wider diversity of Vibrio species compared to the conventional OTU clustering approach.
Species- and developmental stage-specific effects of allelopathy and competition of invasive Impatiens glandulifera on co-occurring plants

Background Impacts of invasive species on native communities are often difficult to assess, because they depend on a range of factors, such as species identity and traits. Such context-dependencies are poorly understood yet, but knowledge is required to predict the impact of invasions. Materials and methods We assessed species- and developmental stage-specificity of competitive and allelopathic effects of the invasive plant Impatiens glandulifera on different developmental stages of four native plant species. While some studies have shown a reduction in plant growth caused by I. glandulifera, the magnitude of its impact is ambiguous. For our study we used seedlings and juveniles of I. glandulifera and the native target species Geum urbanum, Filipendula ulmaria, Urtica dioica, and Salix fragilis (seedlings only of the latter), which often co-occur with I. glandulifera in different habitats. Plants were grown in competition with I. glandulifera or treated with I. glandulifera leaf material, or 2-metoxy-1,4-naphtoquinone (2-MNQ), its supposedly main allelochemical. Results and conclusions Overall I. glandulifera had a negative effect on the growth of all target species depending on the species and on the plant’s developmental stage. F. ulmaria was the least affected and U. dioica the most, and seedlings were less affected than juveniles. The species-specific response to I. glandulifera may lead to an altered community composition in the field, while growth reduction of seedlings and juveniles should give I. glandulifera an advantage in cases where plant recruitment is crucial. 2-MNQ led to minor reductions in plant growth, suggesting that it may not be the only allelopathic substance of I. glandulifera. Surprisingly, I. glandulifera was not fully tolerant to 2-MNQ. This autotoxicity could contribute to I. glandulifera population dynamics. We conclude that I. glandulifera reduces the growth of native vegetation and alters early successional stages without fully hindering it.
Semantic perception of curbs beyond traversability for real-world navigation assistance systems

Intelligent Vehicles (IV) and navigational assistance for the Visually Impaired (VI) are becoming highly coupled, both fulfilling safety-critical tasks towards the utopia of all traffic participants. In this paper, the main purpose is to leverage recently emerged methods for self-driving technology, and transfer them to augment perception and aid navigation in ambient assisted living. More precisely, we put forward to seize pixel-wise semantic segmentation to support curb negotiation and traversability awareness, along the pathway of visually impaired individuals. At the crux of our perception unification framework is an effort to attain efficient understanding by proposing a deep architecture built on residual factorized convolution and pyramidical representation. A comprehensive set of experiments demonstrates the accurate scene parsing results with promise of real-time inference speed. Crucially, real-world performance over state-of-art approaches qualifies the proposed framework for assistance when deployed to two wearable navigation systems, including a pair of commercial smart glasses and a prototype of customized device.
Biological characteristics and immunological properties in Muscovy ducks of H5N6 virus-like particles composed of HA-TM/HA-TMH3 and M1

ABSTRACT Highly pathogenic avian influenza viruses (HPAIVs), including H5N6 strains, pose threats to the health of humans and poultry. Waterfowl play a crucial role as a reservoir of HPAIVs. Since current influenza vaccines induce poor antibody titres in waterfowl, there is an urgent need to develop an efficient vaccine against H5N6 infection. In this study, we constructed two H5N6 virus-like particles (VLPs) composed of matrix-1 (M1) and haemagglutinin of wildtype (HA-TM) or haemagglutinin with transmembrane domain replacement (HA-TMH3) (designated as H5N6 VLPs-TM and H5N6 VLPs-TMH3). Biological characteristics of the composed H5N6 VLPs were compared including localization, expression, contents of HA trimers, thermal stability, morphology and immunogenicity in Muscovy ducks. Our results indicate that the H5N6 VLPs-TMH3 contained more HA trimers and presented better thermal stability. Moreover, Muscovy ducks immunized with H5N6 VLPs-TMH3 produced higher titres of HI antibody and IFN-γ compared with those immunized with the same dose of H5N6 VLP-TM, thus providing a promising approach for the development of influenza virus vaccines for waterfowl. RESEARCH HIGHLIGHTS H5N6 VLPs-TMH3 had more HA trimers and resisted higher temperature than H5N6 VLPs-TM H5N6 VLPs-TMH3 induced higher titre of HI than H5N6 VLPs-TM in Muscovy ducks
Direct Energy Transfer Technique Based DC-DC Converter with Distributed MPPT for PV Charging Applications

The solar based charging systems depend on factors like irradiance, temperature, MPPT tracker, etc. Its performance can be improvised by selecting appropriate converter topologies and system's design specifications. While analyzing the Solar irradiance pattern, both uniform and nonuniform (partial) shading conditions need to be considered. Normally, by-pass diodes are used in anti-parallel to the module or panel to protect it from the hot spot effect. Due to partial shading conditions, multiple local Maximum Power Points (MPP's) occur in the Power-Voltage graph, because of by-pass diodes, and only one among them is the global MPP. For best operation of PV, it is to be operated at global MPP. But, at the global MPP, the partial shaded modules/panels are unable to produce the maximum power. To utilize the power produced by each panel/module efficiently, distributed MPPT is used; where each converter is connected to a module/panel and operated at their local MPP's and the output of the converters are connected in series or parallel to meet the desired voltage and current levels respectively. This paper presents the performance of a system under uniform and non-uniform irradiance conditions analyzing stress on the converter and overall system efficiency for conventional Buck-Boost and direct energy transfer based technique with distributed MPPT for PV charging applications. The simulation is carried out using MATLAB/Simulink, and results are presented.
Kernel Ridge Regression with Constraint of Helmholtz Equation for Sound Field Interpolation

Kernel ridge regression with the constraint of the Helmholtz equation for three-dimensional sound field interpolation is proposed. Interpolation of a sound field is formulated as an optimization problem whose objective function to be minimized is a weighted sum of the squared residuals and the squared norm of the interpolating sound field. We show that this problem corresponds to kernel ridge regression and that the reproducing kernel for this problem is given by the zeroth-order spherical Bessel function of the first kind. In this kernel, the physical constraint on the sound fields, i.e., the Helmholtz equation, is taken into consideration, which is a major advantage over other commonly used kernels such as the Gaussian kernel. This advantage is also confirmed by numerical simulations.
Multi-Source Ensemble Learning for the Remote Prediction of Parkinson's Disease in the Presence of Source-Wise Missing Data

As the collection of mobile health data becomes pervasive, missing data can make large portions of datasets inaccessible for analysis. Missing data has shown particularly problematic for remotely diagnosing and monitoring Parkinson's disease (PD) using smartphones. This contribution presents multi-source ensemble learning, a methodology which combines dataset deconstruction with ensemble learning and enables participants with incomplete data (i.e., where not all sensor data is available) to be included in the training of machine learning models and achieves a 100% participant retention rate. We demonstrate the proposed method on a cohort of 1513 participants, 91.2% of which contributed incomplete data in tapping, gait, voice, and/or memory tests. The use of multi-source ensemble learning, alongside convolutional neural networks (CNNs) capitalizing on the amount of available data, increases PD classification accuracy from 73.1% to 82.0% as compared to traditional techniques. The increase in accuracy is found to be partly caused by the use of multi-channel CNNs and partly caused by developing models using the large cohort of participants. Furthermore, through bootstrap sampling we reveal that feature selection is better performed on a large cohort of participants with incomplete data than on a small number of participants with complete data. The proposed method is applicable to a wide range of wearable/remote monitoring datasets that suffer from missing data and contributes to improving the ability to remotely monitor PD via revealing novel methods of accounting for symptom heterogeneity.
Respiratory frequency and tidal volume during exercise: differential control and unbalanced interdependence

Differentiating between respiratory frequency (fR) and tidal volume (VT) may improve our understanding of exercise hyperpnoea because fR and VT seem to be regulated by different inputs. We designed a series of exercise manipulations to improve our understanding of how fR and VT are regulated during exercise. Twelve cyclists performed an incremental test and three randomized experimental sessions in separate visits. In two of the three experimental visits, participants performed a moderate‐intensity sinusoidal test followed, after recovery, by a moderate‐to‐severe‐intensity sinusoidal test. These two visits differed in the period of the sinusoid (2 min vs. 8 min). In the third experimental visit, participants performed a trapezoidal test where the workload was self‐paced in order to match a predefined trapezoidal template of rating of perceived exertion (RPE). The results collectively reveal that fR changes more with RPE than with workload, gas exchange, VT or the amount of muscle activation. However, fR dissociates from RPE during moderate exercise. Both VT and minute ventilation ( V˙E ) showed a similar time course and a large correlation with V˙CO2 in all the tests. Nevertheless, V˙CO2 was associated more with V˙E than with VT because VT seems to adjust continuously on the basis of fR levels to match V˙E with V˙CO2 . The present findings provide novel insight into the differential control of fR and VT – and their unbalanced interdependence – during exercise. The emerging conceptual framework is expected to guide future research on the mechanisms underlying the long‐debated issue of exercise hyperpnoea.
miRNA-21 and miRNA-223 expression signature as a predictor for lymph node metastasis, distant metastasis and survival in kidney renal clear cell carcinoma

Purpose: The aim of this study was to generate a novel miRNA expression signature to effectively assess nodal metastasis, distant metastasis and predict prognosis for patients with kidney renal clear cell carcinoma (KIRC) and explore its potential mechanism of affecting the prognosis. Method: Using expression profiles downloaded from the Cancer Genome Atlas database, we identified multiple miRNAs with differential expression between KIRC and paired normal tissues. The diagnostic values of the differentially expressed miRNAs for nodal metastasis and distant metastasis were evaluated by Receiver Operating Characteristic (ROC) curve analysis. Then, we evaluated the impact of miRNAs on overall survival (OS) by univariate and multivariate COX regression analyzes. This analysis was ultimately used to construct a miRNA signature that effectively assessed nodal metastasis, distant metastasis and predicted prognosis. The functional enrichment analysis of the miRNAs included in the signatures was used to explore its potential molecular mechanism in KIRC. Results: Based on our cutoff criteria (P < 0.05 and |log2FC| > 1.0), we identified 104 differentially expressed microRNAs (miRNAs), including 43 that were up-regulated in KIRC tissues and 61 that were down-regulated. We found 12 miRNAs were potentially diagnostic biomarkers of nodal metastasis and distant metastasis by ROC curve analysis. Two miRNAs (miRNA-21 and miRNA-223) were significant miRNAs independently associated with OS based on Cox univariate and multivariate analysis. We generated a signature index based on expression of these two miRNAs, and the two-miRNA signature is promising as a biomarker for diagnosing nodal metastasis, distant metastasis and predicting 5-year survival rate of KIRC with areas under the curve (AUC)=0.738, 0.659 and 0.731, respectively. Patients were stratified into high-risk and low-risk groups, according to median of the signature prognosis indexes. Patients in the high-risk group had significantly shorter survival times than those in the low-risk group (P = 0.000). The functional enrichment analysis suggested that the target genes of two miRNAs may be involved in various pathways related to cancer, p53 signaling pathway, apoptosis, and MAPK signaling pathway. Conclusion: The two-miRNA signature could assess nodal metastasis, distant metastasis and predict survival of KIRC. As a promising prediction tool, the mechanism of the two miRNAs in KIRC deserves further study.
ANGUSTIFOLIA Regulates Actin Filament Alignment for Nuclear Positioning in Leaves1[OPEN]

In dark-adapted Arabidopsis cells, nuclei position toward the body center of the leaf, a centripetal nuclear positioning process regulated by ANGUSTIFOLIA through the alignment of actin filaments. During dark adaptation, plant nuclei move centripetally toward the midplane of the leaf blade; thus, the nuclei on both the adaxial and abaxial sides become positioned at the inner periclinal walls of cells. This centripetal nuclear positioning implies that a characteristic cell polarity exists within a leaf, but little is known about the mechanism underlying this process. Here, we show that ANGUSTIFOLIA (AN) and ACTIN7 regulate centripetal nuclear positioning in Arabidopsis (Arabidopsis thaliana) leaves. Two mutants defective in the positioning of nuclei in the dark were isolated and designated as unusual nuclear positioning1 (unp1) and unp2. In the dark, nuclei of unp1 were positioned at the anticlinal walls of adaxial and abaxial mesophyll cells and abaxial pavement cells, whereas the nuclei of unp2 were positioned at the anticlinal walls of mesophyll and pavement cells on both the adaxial and abaxial sides. unp1 was caused by a dominant-negative mutation in ACTIN7, and unp2 resulted from a recessive mutation in AN. Actin filaments in unp1 were fragmented and reduced in number, which led to pleiotropic defects in nuclear morphology, cytoplasmic streaming, and plant growth. The mutation in AN caused aberrant positioning of nuclei-associated actin filaments at the anticlinal walls. AN was detected in the cytosol, where it interacted physically with plant-specific dual-specificity tyrosine phosphorylation-regulated kinases (DYRKPs) and itself. The DYRK inhibitor (1Z)-1-(3-ethyl-5-hydroxy-2(3H)-benzothiazolylidene)-2-propanone significantly inhibited dark-induced nuclear positioning. Collectively, these results suggest that the AN-DYRKP complex regulates the alignment of actin filaments during centripetal nuclear positioning in leaf cells.