Miracle-dz/UniFAR-FTUs huggingface dataset:
Global Oceanic Eddy Identification: A Deep Learning Method From Argo Profiles and Altimetry Data

The inadequate spatial resolution of altimeter results in low identification efficiency of oceanic eddies, especially for small-scale eddies. It is well known that eddies can not only induce sea surface signal but more importantly have typical vertical structure characteristics. However, although the vertical structure characteristics are usually used for statistical analysis, they are seldom considered in the process of eddy recognition. This study is devoted to identifying eddies from the perspective of their vertical signal derived from the 18-year Argo data. Due to the irregular and noisy profile pattern, the direct identification of eddy core from Argo profile is deemed to be a challenge. With the popularity of artificial intelligence, a new hybrid method that combines the advantages of convolutional neural network (CNN) with extreme gradient boosting (XGBoost) is proposed to extract the representative vertical feature and identify eddy from a profile. First, CNN is employed as a feature extractor to automatically obtain vertical features from the input profile at the bottom of the network. Second, the obtained high-dimensional feature vectors are inputted into the XGBoost model, combined with other profile features for classifying profiles that are outside altimeter-identified eddies (Alt eddy). Finally, extensive experiments are implemented to demonstrate the efficiency of the proposed method. The results show that the classification accuracy of CNN-XGBoost model can reach 98%, and about 36% eddies are recaptured. These eddies, dubbed CNN-XGB eddies, are benchmarked against Alt eddies for the vertical structure and geographical distribution, demonstrating a similar or even stronger vertical signal and a prominent eddy belt in the tropical ocean. Within the proposed theory framework, there are various potentials to obtain a better outlook for eddy identification and in situ float observations.
Characterization of a Plant Nuclear Matrix Constituent Protein in Liverwort

The nuclear lamina (NL) is a complex network of nuclear lamins and lamina-associated nuclear membrane proteins, which scaffold the nucleus to maintain structural integrity. In animals, type V intermediate filaments are the main constituents of NL. Plant genomes do not encode any homologs of these intermediate filaments, yet plant nuclei contain lamina-like structures that are present in their nuclei. In Arabidopsis thaliana, CROWDED NUCLEI (CRWN), which are required for maintaining structural integrity of the nucleus and specific perinuclear chromatin anchoring, are strong candidates for plant lamin proteins. Recent studies revealed additional roles of Arabidopsis Nuclear Matrix Constituent Proteins (NMCPs) in modulating plants’ response to pathogen and abiotic stresses. However, detailed analyses of Arabidopsis NMCP activities are challenging due to the presence of multiple homologs and their functional redundancy. In this study, we investigated the sole NMCP gene in the liverwort Marchantia polymorpha (MpNMCP). We found that MpNMCP proteins preferentially were localized to the nuclear periphery. Using CRISPR/Cas9 techniques, we generated an MpNMCP loss-of-function mutant, which displayed reduced growth rate and curly thallus lobes. At an organelle level, MpNMCP mutants did not show any alteration in nuclear morphology. Transcriptome analyses indicated that MpNMCP was involved in regulating biotic and abiotic stress responses. Additionally, a highly repetitive genomic region on the male sex chromosome, which was preferentially tethered at the nuclear periphery in wild-type thalli, decondensed in the MpNMCP mutants and located in the nuclear interior. This perinuclear chromatin anchoring, however, was not directly controlled by MpNMCP. Altogether, our results unveiled that NMCP in plants have conserved functions in modulating stress responses.
Editorial: Research Collaboration and Networks: Characteristics, Evolution and Trends

In this age of big science, collaboration is increasingly playing an important role in implementing major scientific breakthroughs, solving complex scientific problems, promoting cultural understanding, improving research efficiency, achieving research excellence and knowledge innovation, and sharing scientific and technological resources, etc. (Andrade et al., 2009). Generally speaking, the research network is the manifestation of scientific cooperation. As a popular Research Topic, works on scientific collaboration and network have focused on a variety of terminologies and methods, diverse disciplines and views, different stages and levels, and various factors and challenges (Newman, 2001; Sonnenwald, 2007). This Research Topic aims to discuss novel approaches and new insights to uncover the characteristics of research collaboration networks and to bring new perspectives to understand the nature and trends of scientific collaboration.
MELAS/LS Overlap Syndrome Associated With Mitochondrial DNA Mutations: Clinical, Genetic, and Radiological Studies

Introduction: Mitochondrial diseases are characterized by considerable clinical and genetic heterogeneity. Mitochondrial encephalomyopathy with lactate acidosis and stroke-like episodes (MELAS) and Leigh syndrome (LS) are both established mitochondrial syndromes; sometimes they can overlap. Methods: A retrospective observational cohort study was done to analyze the clinical manifestations, biochemical findings, neuroimaging and genetic data, and disease outcomes of 14 patients with identified MELAS/LS overlap syndrome. Results: A total of 14 patients, 9 males and 5 females, were enrolled. The median age at onset was 14 years, while the average age was 12.6 years. As for clinical features in concordance with MELAS, the top three most common symptoms were seizures, cognitive impairment, and stroke-like episodes (SLE). Brain atrophy was present in seven patients. As for the clinical hallmarks of LS, the top three most common symptoms were ataxia, spastic paraplegia, and bulbar palsy. Patients presented with individual syndrome or overlap syndromes with similar frequency, and the prognosis did not seem to be related to the initial presentation. Thirteen patients were identified with MTND mutations, among which m.13513G>A mutation in the MT-ND5 gene was the most common. Only one patient with m.8344A>G mutation of MTTK gene was found. Discussion: Our study demonstrated that MTND genes are important mutation hot spots in MELAS/LS overlap syndrome. The follow-up is very important for the final diagnosis of overlap syndrome.
Structure-Guided Computational Approaches to Unravel Druggable Proteomic Landscape of Mycobacterium leprae

Leprosy, caused by Mycobacterium leprae (M. leprae), is treated with a multidrug regimen comprising Dapsone, Rifampicin, and Clofazimine. These drugs exhibit bacteriostatic, bactericidal and anti-inflammatory properties, respectively, and control the dissemination of infection in the host. However, the current treatment is not cost-effective, does not favor patient compliance due to its long duration (12 months) and does not protect against the incumbent nerve damage, which is a severe leprosy complication. The chronic infectious peripheral neuropathy associated with the disease is primarily due to the bacterial components infiltrating the Schwann cells that protect neuronal axons, thereby inducing a demyelinating phenotype. There is a need to discover novel/repurposed drugs that can act as short duration and effective alternatives to the existing treatment regimens, preventing nerve damage and consequent disability associated with the disease. Mycobacterium leprae is an obligate pathogen resulting in experimental intractability to cultivate the bacillus in vitro and limiting drug discovery efforts to repositioning screens in mouse footpad models. The dearth of knowledge related to structural proteomics of M. leprae, coupled with emerging antimicrobial resistance to all the three drugs in the multidrug therapy, poses a need for concerted novel drug discovery efforts. A comprehensive understanding of the proteomic landscape of M. leprae is indispensable to unravel druggable targets that are essential for bacterial survival and predilection of human neuronal Schwann cells. Of the 1,614 protein-coding genes in the genome of M. leprae, only 17 protein structures are available in the Protein Data Bank. In this review, we discussed efforts made to model the proteome of M. leprae using a suite of software for protein modeling that has been developed in the Blundell laboratory. Precise template selection by employing sequence-structure homology recognition software, multi-template modeling of the monomeric models and accurate quality assessment are the hallmarks of the modeling process. Tools that map interfaces and enable building of homo-oligomers are discussed in the context of interface stability. Other software is described to determine the druggable proteome by using information related to the chokepoint analysis of the metabolic pathways, gene essentiality, homology to human proteins, functional sites, druggable pockets and fragment hotspot maps.
Qualitative and Quantitative Analysis on Flavonoid Distribution in Different Floral Parts of 42 Hemerocallis Accessions

The Hemerocallis accessions is widely consumed as nutritious vegetable and traditional medicine in eastern Asia and used as an ornamental flower worldwide. Compared with most other horticultural products, its flower is richer in polyphenols, flavonoids, carotenoids, and anthocyanins. Therefore, the flower has strong antioxidant activity that inhibits cancer cell proliferation, which could used for health and pharmaceutical purposes. The flavonoids composition and distribution in the flowers, and the content varied between different accssions is still unclear. In this context, eight flavonols, two flavones, and two anthocyanins were determined in Hemerocallis flower by high-performance liquid chromatography (HPLC) coupled with photodiode array and mass spectrometric detectors. Rutin was the most abundant flavonols and cyanidin 3,5-glucoside and cyanidin 3-rutinoside were the major anthocyanins in Hemerocallis tepals, resulting in flower petal coloration, and their content in the petal was higher than that of the sepal. Hierarchical cluster analysis grouped the 42 accessions into four groups, and they were significantly different (p < 0.05) from each other in the ten significant compounds by One-way ANOVA. Overall, the qualitative and quantitative analysis of flavonoid constituents in six floral parts of 42 Hemerocallis accessions were elucidated, which could be helpful for the food and pharmaceutical industries, and lay the foundation for the Hemerocallis flower color research.
Full Life Cycle Management of Power System Integrated With Renewable Energy: Concepts, Developments and Perspectives

Under high-penetration of renewable energy, power grid is facing with the development problems such as production delay, wind and solar power abandoning. With the continuous growth of renewable energy installation such as wind power, photovoltaic (PV), as well as the increase of power generation capacity, it is urgent to increase peak-load and frequency regulation capacity on a large scale to alleviate the consumption problems caused by large renewable energy integration, and then requires power generation enterprises of peak-load and frequency regulation to increase relevant equipment assets. As a result, peak-load and frequency regulation enterprises must carry out scientific cost management of equipment assets. This paper introduces the concepts, developments and perspectives of life cycle cost (LCC) management of equipment assets in high-penetrated renewable energy power grid, and probes into cost collection and estimation scheme in the process of equipment asset management.
Risks and Prognoses of Alzheimer's Disease and Vascular Dementia in Patients With Insomnia: A Nationwide Population-Based Study

This study aimed to investigate the risk and prognosis of Alzheimer's disease (AD) and vascular dementia (VaD) in patients with insomnia using the National Health Insurance Service database covering the entire population of the Republic of Korea from 2007 to 2014. In total, 2,796,871 patients aged 40 years or older with insomnia were enrolled, and 5,593,742 controls were matched using a Greedy digit match algorithm. Mortality and the rate of admission to a long-term care facility were estimated using multivariable Cox analysis. Of all patients with insomnia, 138,270 (4.94%) and 26,706 (0.96%) were newly diagnosed with AD and VaD, respectively. The incidence rate ratios for AD and VaD were 1.73 and 2.10, respectively, in patients with insomnia compared with those without. Higher mortality rates and long-term care facility admission rates were also observed in patients with dementia in the insomnia group. Known cardiovascular risk factors showed interactions with the effects of insomnia on the risk of AD and VaD. However, the effects of insomnia on the incidence of AD and VaD were consistent between the groups with and without cardiovascular risk factors. Insomnia is a medically modifiable and policy-accessible risk factor and prognostic marker of AD and VaD.
Characterization of Plasma Cell-Free DNA Integrity Using Droplet-Based Digital PCR: Toward the Development of Circulating Tumor DNA-Dedicated Assays

Background: Cellular-cell free-DNA (ccfDNA) is being explored as a diagnostic and prognostic tool for various diseases including cancer. Beyond the evaluation of the ccfDNA mutational status, its fragmentation has been investigated as a potential cancer biomarker in several studies. However, probably due to a lack of standardized procedures dedicated to preanalytical and analytical processing of plasma samples, contradictory results have been published. Methods: ddPCR assays allowing the detection of KRAS wild-type and mutated sequences (KRAS p.G12V, pG12D, and pG13D) were designed to target different fragments sizes. Once validated on fragmented and non-fragmented DNA extracted from cancer cell lines, these assays were used to investigate the influence of the extraction methods on the non-mutated and mutated ccfDNA integrity reflected by the DNA integrity index (DII). The DII was then analyzed in two prospective cohorts of metastatic colorectal cancer patients (RASANC study n = 34; PLACOL study n = 12) and healthy subjects (n = 49). Results and Discussion: Our results demonstrate that ccfDNA is highly fragmented in mCRC patients compared with healthy individuals. These results strongly suggest that the characterization of ccfDNA integrity hold great promise toward the development of a universal biomarker for the follow-up of mCRC patients. Furthermore, they support the importance of standardization of sample handling and processing in such analysis.
MicroRNAs and tRNA-Derived Small Fragments: Key Messengers in Nuclear–Mitochondrial Communication

Mitochondria are not only important as energy suppliers in cells but also participate in other biological processes essential for cell growth and survival. They arose from α-proteobacterial predecessors through endosymbiosis and evolved transferring a large part of their genome to the host cell nucleus. Such a symbiotic relationship has been reinforced over time through increasingly complex signaling mechanisms between the host cell and mitochondria. So far, we do not have a complete view of the mechanisms that allow the mitochondria to communicate their functional status to the nucleus and trigger adaptive and compensatory responses. Recent findings place two classes of small non-coding RNAs (sncRNAs), microRNAs (miRNAs), and tRNA-derived small fragments, in such a scenario, acting as key pieces in the mitochondria–nucleus cross-talk. This review highlights the emerging roles and the interrelation of these sncRNAs in different signaling pathways between mitochondria and the host cell. Moreover, we describe in what way alterations of these complex regulatory mechanisms involving sncRNAs lead to diseases associated with mitochondrial dysfunction. In turn, these discoveries provide novel prognostic biomarker candidates and/or potential therapeutic targets.
K-Domain Technology: Constitutive Expression of a Blueberry Keratin-Like Domain Mimics Expression of Multiple MADS-Box Genes in Enhancing Maize Grain Yield

MADS-box genes are considered as the foundation of all agronomic traits because they play essential roles in almost every aspect of plant reproductive development. Keratin-like (K) domain is a conserved protein domain of tens of MIKC-type MADS-box genes in plants. K-domain technology constitutively expresses a K-domain to mimic expression of the K-domains of other MADS-box genes simultaneously and thus to generate new opportunities for yield enhancement, because the increased K-domains can likely prevent MADS-domain proteins from binding to target DNA. In this study, we evaluated utilizing the K-domain technology to increase maize yield. The K-domain of a blueberry’s SUPPRESSOR of CONSTITUTIVE EXPRESSION OF CONSTANS 1 (VcSOC1K) has similarities to five MADS-box genes in maize. Transgenic maize plants expressing the VcSOC1K showed 13–100% of more grain per plant than the nontransgenic plants in all five experiments conducted under different experimental conditions. Transcriptome comparisons revealed 982 differentially expressed genes (DEGs) in the leaves from 83-day old plants, supporting that the K-domain technology were powerful and multiple functional. The results demonstrated that constitutive expression of the VcSOC1K was very effective to enhance maize grain production. With the potential of mimicking the K-domains of multiple MADS-box genes, the K-domain technology opens a new approach to increase crop yield.
Scalable Declarative HEP Analysis Workflows for Containerised Compute Clouds

We describe a novel approach for experimental High-Energy Physics (HEP) data analyses that is centred around the declarative rather than imperative paradigm when describing analysis computational tasks. The analysis process can be structured in the form of a Directed Acyclic Graph (DAG), where each graph vertex represents a unit of computation with its inputs and outputs, and the graph edges describe the interconnection of various computational steps. We have developed REANA, a platform for reproducible data analyses, that supports several such DAG workflow specifications. The REANA platform parses the analysis workflow and dispatches its computational steps to various supported computing backends (Kubernetes, HTCondor, Slurm). The focus on declarative rather than imperative programming enables researchers to concentrate on the problem domain at hand without having to think about implementation details such as scalable job orchestration. The declarative programming approach is further exemplified by a multi-level job cascading paradigm that was implemented in the Yadage workflow specification language. We present two recent LHC particle physics analyses, ATLAS searches for dark matter and CMS jet energy correction pipelines, where the declarative approach was successfully applied. We argue that the declarative approach to data analyses, combined with recent advancements in container technology, facilitates the portability of computational data analyses to various compute backends, enhancing the reproducibility and the knowledge preservation behind particle physics data analyses.
Integrated Isogenic Human Induced Pluripotent Stem Cell–Based Liver and Heart Microphysiological Systems Predict Unsafe Drug–Drug Interaction

Three-dimensional (3D) microphysiological systems (MPSs) mimicking human organ function in vitro are an emerging alternative to conventional monolayer cell culture and animal models for drug development. Human induced pluripotent stem cells (hiPSCs) have the potential to capture the diversity of human genetics and provide an unlimited supply of cells. Combining hiPSCs with microfluidics technology in MPSs offers new perspectives for drug development. Here, the integration of a newly developed liver MPS with a cardiac MPS—both created with the same hiPSC line—to study drug–drug interaction (DDI) is reported. As a prominent example of clinically relevant DDI, the interaction of the arrhythmogenic gastroprokinetic cisapride with the fungicide ketoconazole was investigated. As seen in patients, metabolic conversion of cisapride to non-arrhythmogenic norcisapride in the liver MPS by the cytochrome P450 enzyme CYP3A4 was inhibited by ketoconazole, leading to arrhythmia in the cardiac MPS. These results establish integration of hiPSC-based liver and cardiac MPSs to facilitate screening for DDI, and thus drug efficacy and toxicity, isogenic in the same genetic background.
The Universally Conserved ATPase YchF Regulates Translation of Leaderless mRNA in Response to Stress Conditions

The universally conserved P-loop GTPases control diverse cellular processes, like signal transduction, ribosome assembly, cell motility, and intracellular transport and translation. YchF belongs to the Obg-family of P-loop GTPases and is one of the least characterized member of this family. It is unique because it preferentially hydrolyses ATP rather than GTP, but its physiological role is largely unknown. Studies in different organisms including humans suggest a possible role of YchF in regulating the cellular adaptation to stress conditions. In the current study, we explored the role of YchF in the model organism Escherichia coli. By western blot and promoter fusion experiments, we demonstrate that YchF levels decrease during stress conditions or when cells enter stationary phase. The decline in YchF levels trigger increased stress resistance and cells lacking YchF are resistant to multiple stress conditions, like oxidative stress, replication stress, or translational stress. By in vivo site directed cross-linking we demonstrate that YchF interacts with the translation initiation factor 3 (IF3) and with multiple ribosomal proteins at the surface of the small ribosomal subunit. The absence of YchF enhances the anti-association activity of IF3, stimulates the translation of leaderless mRNAs, and increases the resistance against the endoribonuclease MazF, which generates leaderless mRNAs during stress conditions. In summary, our data identify YchF as a stress-responsive regulator of leaderless mRNA translation.
Framework for the Classification of Emotions in People With Visual Disabilities Through Brain Signals

Nowadays, the recognition of emotions in people with sensory disabilities still represents a challenge due to the difficulty of generalizing and modeling the set of brain signals. In recent years, the technology that has been used to study a person’s behavior and emotions based on brain signals is the brain–computer interface (BCI). Although previous works have already proposed the classification of emotions in people with sensory disabilities using machine learning techniques, a model of recognition of emotions in people with visual disabilities has not yet been evaluated. Consequently, in this work, the authors present a twofold framework focused on people with visual disabilities. Firstly, auditory stimuli have been used, and a component of acquisition and extraction of brain signals has been defined. Secondly, analysis techniques for the modeling of emotions have been developed, and machine learning models for the classification of emotions have been defined. Based on the results, the algorithm with the best performance in the validation is random forest (RF), with an accuracy of 85 and 88% in the classification for negative and positive emotions, respectively. According to the results, the framework is able to classify positive and negative emotions, but the experimentation performed also shows that the framework performance depends on the number of features in the dataset and the quality of the Electroencephalogram (EEG) signals is a determining factor.