Miracle-dz/UniFAR-FTUs huggingface dataset:
Hemoproteins in Design of Biofuel Cells

Direct electron transfer (DET) is a unique feature of some enzymes. The possibility of DET between enzymes and the electrode surface could pave the way for superior reagentless, noncompartmentised, mediator‐free biofuel cells, as it obviates the need for mediators and allows an efficient transduction of the electrical current. DET is highly beneficial in the development of enzymatic and microbial biofuel cells. In this review article, hemoproteins, which are able to directly transfer electrons to the surfaces of conducting supports, are briefly overviewed and characterised. The main focus is laid on the application of heme‐c containing enzymes in biofuel cell design. Some historical steps and recent developments in biofuel cell design are presented in this article. Various designs of biofuel cells are overviewed. Possible applications of biofuel cells are presented and/or predicted and discussed. Problems and challenges in biofuel cell design and application are identified while possible directions to solve recent problems in biofuel cell development are discussed. The application of enzymatic biofuel cells as model systems and tools for advanced study of bioelectronics' properties of enzymes is predicted.
What The Brain Does As We Speak

Language is a defining human behavior and is dependent on networks interactions amongst broadly distributed neuronal substrates. Transient dynamics between language regions that underpin speech production have long been postulated, yet have proven challenging to evaluate empirically. We used direct intracranial recordings during single word production to create a finely resolved spatiotemporal atlas (134 patients, 25810 electrodes, 40278 words) of the entire language-dominant cortex and used this to derive single-trial state-space sequences of network motifs. We derived 5 discrete neural states during the production of each word, distinguished by unique patterns of distributed cortical interaction. This interactive model was significantly better than a model of the same design but lacking interactions between regions in explaining observed activity. Our results eschew strict functional attribution to localized cortical populations, supporting instead the idea that cognitive processes are better explained by distributed metastable network states.
AlnC: An extensive database of long non-coding RNAs in angiosperms

Long non-coding RNAs (lncRNAs) play a major role in diverse biological processes that are contemplated to have diverse regulatory roles in plants. While lncRNAs have been described and annotated in major plant species, many of plant species lack annotated lncRNAs despite the availability of transcriptome data in public repositories. In this study, we have identified and annotated the lncRNAs in the transcriptomic data from the 1000 plant genome project (1KP), and developed a user-friendly, open-access database called AlnC. This can be used for the exploration of lncRNAs in 682 Angiosperm plants. The current version of AlnC offers 10,855,598 annotated lncRNA transcripts across 809 sample tissues of diverse flowering plants. To enhance the AlnC interface, we have provided the features for browsing, searching and downloading of lncRNA data, interactive graphics, and online BLAST service. In addition to these information, each lncRNA record is annotated with possible Short open reading frames (e.g. sORFs) to facilitate the study of peptides encoded within lncRNAs. With this user-friendly interface, we assume that AlnC will serve as a rich source of lncRNAs that will contribute to small-and large-scale studies in a wide range of flowering plants.
Repurposing of synaptonemal complex proteins for kinetochores in Kinetoplastida

Chromosome segregation in eukaryotes is driven by a macromolecular protein complex called the kinetochore that connects centromeric DNA to microtubules of the spindle apparatus. Kinetochores in well-studied model eukaryotes consist of a core set of proteins that are broadly conserved among distant eukaryotic phyla. In contrast, unicellular flagellates of the class Kinetoplastida have a unique set of kinetochore components. The evolutionary origin and history of these kinetochores remains unknown. Here, we report evidence of homology between three kinetoplastid kinetochore proteins KKT16–18 and axial element components of the synaptonemal complex, such as the SYCP2:SYCP3 multimers found in vertebrates. The synaptonemal complex is a zipper-like structure that assembles between homologous chromosomes during meiosis to promote recombination. Using a sensitive homology detection protocol, we identify divergent orthologues of SYCP2:SYCP3 in most eukaryotic supergroups including other experimentally established axial element components, such as Red1 and Rec10 in budding and fission yeast, and the ASY3:ASY4 multimers in land plants. These searches also identify KKT16–18 as part of this rapidly evolving protein family. The widespread presence of the SYCP2-3 gene family in extant eukaryotes suggests that the synaptonemal complex was likely present in the last eukaryotic common ancestor. We found at least twelve independent duplications of the SYCP2-3 gene family throughout the eukaryotic tree of life, providing opportunities for new functional complexes to arise, including KKT16–18 in Trypanosoma brucei. We propose that kinetoplastids evolved their unique kinetochore system by repurposing meiotic components of the chromosome synapsis and homologous recombination machinery that were already present in early eukaryotes.
INCORPORATING A DYNAMIC GENE-BASED PROCESS MODULE INTO A CROP SIMULATION MODEL

Dynamic crop simulation models are tools that predict plant phenotype grown in specific environments for genotypes using genotype-specific parameters (GSPs), often referred to as “genetic coefficients. ” These GSPs are estimated using phenotypic observations and may not represent “true” genetic information. Instead, estimating GSPs requires experiments to measure phenotypic responses when new cultivars are released. The goal of this study was to evaluate a new approach that incorporates a dynamic gene-based module for simulating time-to-flowering for common bean (Phaseolus vulgaris L.) into an existing dynamic crop model. A multi-environment study conducted in 2011 and 2012 included 187 recombinant inbred lines (RILs) from a bi-parental bean family to measure the effects of quantitative trait loci (QTL), environment (E), and QTL×E interactions across five sites. The dynamic mixed linear model from Vallejos et al. (2020) was modified in this study to create a dynamic module that was then integrated into the CSM-CROPGRO-Drybean model. This new hybrid crop model, with the gene-based flowering module replacing the original flowering component, requires allelic makeup of each genotype being simulated and daily E data. The hybrid model was compared to the original CSM model using the same E data and previously estimated GSPs to simulate time-to-flower. The integrated gene-based module simulated days of first flower agreed closely with observed values (root mean square error of 2.73 days and model efficiency of 0.90) across the five locations and 187 genotypes. The hybrid model with its gene-based module also described most of the G, E and G×E effects on time-to-flower and was able to predict final yield and other outputs simulated by the original CSM. These results provide the first evidence that dynamic crop simulation models can be transformed into gene-based models by replacing an existing process module with a gene-based module for simulating the same process.
14-3-3ζ-depletion impairs mammary gland development in the mouse

The 14-3-3 family of proteins have roles in regulating several key cellular processes. While their significant structural and functional homology had informed the idea that these proteins acted redundantly, it is now becoming clear that individual family members may have tissue and context specific functions, highlighting the need for a more nuanced understanding of these important proteins. Here, we demonstrate that mice deficient in 14-3-3ζ exhibit developmental defects of the mammary epithelium, associated with dysregulation of key transcription factors involved in the maintenance of mammary stem cell populations. We believe that this model will be prove useful for investigating the role of 14-3-3ζ in the maintenance of mammary stem cell populations and elucidating the transcriptional networks driving specification of the mammary epithelium.
Somatosensory innervation of healthy human oral tissues

The oral somatosensory system relays essential information about mechanical stimuli to enable oral functions such as feeding and speech. The neurochemical and anatomical diversity of sensory neurons across oral cavity sites have not been systematically compared. To address this gap, we analyzed healthy human tongue and hard palate innervation. Biopsies were collected from 12 volunteers and underwent multiplex fluorescent immunohistochemistry (≥2 specimens per marker/structure). Afferents were analyzed for markers of neurons (βIII tubulin), myelinated afferents (neurofilament heavy, NFH), and Merkel cells and taste cells (keratin 20, K20). Hard-palate innervation included Meissner’s corpuscles, glomerular endings, Merkel cell-neurite complexes, and free nerve endings. The organization of these somatosensory endings is reminiscent of fingertips, suggesting that the hard palate is equipped with a rich repertoire of sensory neurons for pressure sensing and spatial localization of mechanical inputs, which are essential for speech production and feeding. Likewise, the tongue is innervated by afferents that impart it with exquisite acuity and detection of moving stimuli that support flavor construction and speech. Filiform papillae contain end bulbs of Krause, as well as endings that have not been previously reported, including subepithelial neuronal densities, and NFH+ neurons innervating basal epithelium. Fungiform papillae had Meissner’s corpuscles and densities of NFH+ intraepithelial neurons surrounding taste buds. The differing compositions of sensory endings within filiform and fungiform papillae suggest that these structures have distinct roles in mechanosensation. Collectively, this study has identified previously undescribed afferent endings in human oral tissues and provides an anatomical framework for understanding oral mechanosensory functions.
The Case for Retaining Natural Language Descriptions of Phenotypes in Plant Databases and a Web Application as Proof of Concept

Similarities in phenotypic descriptions can be indicative of shared genetics, metabolism, and stress responses, to name a few. Finding and measuring similarity across descriptions of phenotype is not straightforward, with previous successes in computation requiring a great deal of expert data curation. Natural language processing of free text descriptions of phenotype is often less resource intensive than applying expert curation. It is therefore critical to understand the performance of natural language processing techniques for organizing and analyzing biological datasets and for enabling biological discovery. For predicting similar phenotypes, a wide variety of approaches from the natural language processing domain perform as well as curation-based methods. These computational approaches also show promise both for helping curators organize and work with large datasets and for enabling researchers to explore relationships among available phenotype descriptions. Here we generate networks of phenotype similarity and share a web application for querying a dataset of associated plant genes using these text mining approaches. Example situations and species for which application of these techniques is most useful are discussed. Database URLs The database and analytical tool called QuOATS are available at https://quoats.dill-picl.org/. Code for the web application is available at https://git.io/Jtv9J. Datasets are available for direct access via https://zenodo.org/record/7947342#. ZGwAKOzMK3I. The code for the analyses performed for the publication is available at https://github.com/Dill-PICL/Plant-data and https://github.com/Dill-PICL/NLP-Plant-Phenotypes.
Improving deep learning-based protein distance prediction in CASP14

Accurate prediction of residue-residue distances is important for protein structure prediction. We developed several protein distance predictors based on a deep learning distance prediction method and blindly tested them in the 14th Critical Assessment of Protein Structure Prediction (CASP14). The prediction method uses deep residual neural networks with the channel-wise attention mechanism to classify the distance between every two residues into multiple distance intervals. The input features for the deep learning method include co-evolutionary features as well as other sequence-based features derived from multiple sequence alignments (MSAs). Three alignment methods are used with multiple protein sequence/profile databases to generate MSAs for input feature generation. Based on different configurations and training strategies of the deep learning method, five MULTICOM distance predictors were created to participate in the CASP14 experiment. Benchmarked on 37 hard CASP14 domains, the best performing MULTICOM predictor is ranked 5th out of 30 automated CASP14 distance prediction servers in terms of precision of top L/5 long-range contact predictions (i.e. classifying distances between two residues into two categories: in contact (< 8 Angstrom) and not in contact otherwise) and performs better than the best CASP13 distance prediction method. The best performing MULTICOM predictor is also ranked 6th among automated server predictors in classifying inter-residue distances into 10 distance intervals defined by CASP14 according to the F1 measure. The results show that the quality and depth of MSAs depend on alignment methods and sequence databases and have a significant impact on the accuracy of distance prediction. Using larger training datasets and multiple complementary features improves prediction accuracy. However, the number of effective sequences in MSAs is only a weak indicator of the quality of MSAs and the accuracy of predicted distance maps. In contrast, there is a strong correlation between the accuracy of contact/distance predictions and the average probability of the predicted contacts, which can therefore be more effectively used to estimate the confidence of distance predictions and select predicted distance maps.
Multi-modal artificial dura for simultaneous large-scale optical access and large-scale electrophysiology in non-human primate cortex

Objective. Non-human primates (NHPs) are critical for development of translational neural technologies because of their neurological and neuroanatomical similarities to humans. Large-scale neural interfaces in NHPs with multiple modalities for stimulation and data collection poise us to unveil network-scale dynamics of both healthy and unhealthy neural systems. We aim to develop a large-scale multi-modal interface for NHPs for the purpose of studying large-scale neural phenomena including neural disease, damage, and recovery. Approach. We present a multi-modal artificial dura (MMAD) composed of flexible conductive traces printed into transparent medical grade polymer. Our MMAD provides simultaneous neurophysiological recordings and optical access to large areas of the cortex (∼3 cm2) and is designed to mitigate photo-induced electrical artifacts. The MMAD is the centerpiece of the interfaces we have designed to support electrocorticographic recording and stimulation, cortical imaging, and optogenetic experiments, all at the large-scales afforded by the brains of NHPs. We performed electrical and optical experiments bench-side and in vivo with macaques to validate the utility of our MMAD. Main results. Using our MMAD we present large-scale electrocorticography from sensorimotor cortex of three macaques. Furthermore, we validated surface electrical stimulation in one of our animals. Our bench-side testing showed up to 90% reduction of photo-induced artifacts with our MMAD. The transparency of our MMAD was confirmed both via bench-side testing (87% transmittance) and via in vivo imaging of blood flow from the underlying microvasculature using optical coherence tomography angiography. Significance. Our results indicate that our MMAD supports large-scale electrocorticography, large-scale cortical imaging, and, by extension, large-scale optical stimulation. The MMAD prepares the way for both acute and long-term chronic experiments with complimentary data collection and stimulation modalities. When paired with the complex behaviors and cognitive abilities of NHPs, these assets prepare us to study large-scale neural phenomena including neural disease, damage, and recovery.
Targeting interleukin-1 for reversing fat browning and muscle wasting in infantile nephropathic cystinosis

Background Ctns−/− mice, a mouse model of infantile nephropathic cystinosis, exhibit hypermetabolism with adipose tissue browning and profound muscle wasting. Inflammatory cytokines such as IL-1 trigger inflammatory cascades and play an important role in the pathogenesis of cachexia. Anakinra is an FDA-approved IL-1 receptor antagonist that blocks IL-1 signaling and may provide targeted novel therapy. Methods Ctns−/− mice were bred to Il6 −/− and Il1β −/− mice. Ctns−/− mice and wild type control were treated with anakinra (2.5 mg.kg.day, IP) or saline as vehicle for 6 weeks. We quantitated total fat mass and studied expression of molecules regulating adipose tissue browning. We measured gastrocnemius weight, total lean mass content, muscle function (grip strength and rotarod activity), muscle fiber size, muscle fatty infiltration and expression of molecules regulating muscle metabolism. We also evaluated the effects of anakinra on the muscle transcriptome. Results Il-1β deficiency or treatment with anakinra normalized food intake and weight gain, fat and lean mass content, metabolic rate and muscle function in Ctns−/− mice. Anakinra also diminished molecular perturbations of energy homeostasis in adipose tissue and muscle, specifically, aberrant expression of beige adipose cell biomarkers (UCP-1, CD137, Tmem26 and Tbx1) and molecules implicated in adipocyte tissue browning (Cox2/Pgf2α, Tlr2, Myd88 and Traf6) in inguinal white adipose tissue in Ctns−/− mice. Moreover, anakinra normalized gastrocnemius weight and fiber size as well as attenuated muscle fat infiltration in Ctns−/− mice. This was accompanied by correction of the increased muscle wasting signaling pathways (increased protein content of ERK1/2, JNK, p38 MAPK and NF-κB p65 and gene expression of Atrogin-1 and Myostatin) and the decreased myogenesis process (decreased gene expression of MyoD and Myogenin) in gastrocnemius of Ctns−/− mice. Finally, anakinra normalized or attenuated 12 of those top 20 differentially expressed muscle genes in Ctns−/− mice. Conclusions Anakinra attenuates adipose tissue browning and muscle wasting in Ctns−/− mice. IL-1 receptor blockade may represent a novel targeted treatment for cachexia in patients with infantile nephropathic cystinosis.
hC9ORF78 localizes to kinetochores and is required for proper chromosome segregation

C9ORF78 is a poorly characterized protein found in diverse eukaryotes. Previous work indicated overexpression of hC9ORF78 (aka HCA59) in malignant tissues indicating a possible involvement in growth regulatory pathways. Additional studies in fission yeast and humans uncover a potential function in regulating the spliceosome. In studies of GFP-tagged hC9ORF78 we observed a dramatic reduction in protein abundance in cells grown to confluence and/or deprived of serum growth factors. Serum stimulation induced synchronous re-expression of the protein in HeLa cells. This effect was also observed with the endogenous protein. Overexpressing either E2F1 or N-Myc resulted in elevated hC9ORF78 expression potentially explaining the serum-dependent upregulation of the protein. Immunofluorescence analysis indicates that hC9ORF78 localizes to nuclei in interphase but does not appear to concentrate in speckles as would be expected for a splicing protein. Surprisingly, a subpopulation of hC9ORF78 co-localizes with ACA, Mad1 and Hec1 in mitotic cells suggesting that this protein may associate with kinetochores or centromeres. Furthermore, knocking-down hC9ORF78 caused mis-alignment of chromosomes in mitosis. These studies uncover novel mitotic function and subcellular localization of cancer antigen hC9ORF78. SUMMARY STATEMENT hC9ORF78 regulates chromosome segregation.
TRNP1 sequence, function and regulation co-evolve with cortical folding in mammals

Genomes can be seen as notebooks of evolution that contain unique information on successful genetic experiments (Wright 2001). This allows to identify conserved genomic sequences (Zoonomia Consortium 2020) and is very useful e.g. for finding disease-associated variants (Kircher et al. 2014). Additional information from genome comparisons across species can be leveraged when considering phenotypic variance across species. Here, we exemplify this principle in a cross-species association study by testing whether structural or regulatory changes in TRNP1 correlate with changes in brain size and cortical folding in mammals. We find that the rate of TRNP1 protein evolution (ω) correlates best with the rate of cortical folding and that TRNP1 proteins from species with more cortical folding induce higher proliferation rates in neural stem cells from murine cerebral cortex. Furthermore, we compare the activity of putative cis-regulatory elements of TRNP1 in a massively parallel reporter assay and identify one element that correlates with cortical folding in Old World Monkeys and Apes. Our analyses indicate that coding and regulatory changes in TRNP1 modulated its activity to adjust cortical folding during mammalian evolution and exemplify how evolutionary information can be leveraged by cross-species association studies.
The anterior cingulate cortex and its role in controlling contextual fear memory to predatory threats

Predator exposure is a life-threatening experience and elicits learned fear responses to the context in which the predator was encountered. The anterior cingulate area (ACA) occupies a pivotal position in a cortical network responsive to predatory threats, and it exerts a critical role in processing fear memory. Ours results revealed that the ACA is involved in both the acquisition and expression of contextual fear to predatory threat. Overall, the ACA can provide predictive relationships between the context and the predator threat and influences fear memory acquisition through projections to the basolateral amygdala and perirhinal region and the expression of contextual fear through projections to the dorsolateral periaqueductal gray. Our results expand previous studies based on classical fear conditioning and open interesting perspectives for understanding how the ACA is involved in processing contextual fear memory to ethologic threatening conditions that entrain specific medial hypothalamic fear circuits (i.e., predator- and conspecific-responsive circuits).