Miracle-dz/UniFAR-FTUs huggingface dataset:
Cardiac biomarkers: A boon for diagnosis of acute myocardial infarction patients

Acute Myocardial infarction is responsible for substantial mortality and morbidity all over the world. Biomarkers assists in timely diagnosis, prediction and ease clinicians in tailoring appropriate therapy for high-risk patients of acute myocardial infarction. AMI patients can be stratified by symptoms, risk factors and electrocardiogram results but cardiac biomarkers also have significance in diagnosis and prognosis. Presently, troponin is the gold standard biomarker for myocardial insult and is used concurrently with creatine kinase-MB (CK-MB) and myoglobin for a quick and precise diagnosis of acute coronary syndrome (ACS). Novel biomarkers discussed here are Myoglobin, Creatine kinase, Lactate dehydrogenase, Ischaemia modified albumin (IMA), Troponin, Copeptin, Growthdifferentiation factor-15(GDF-15), CD40L, Myeloperoxidase (MPO), ET1/CTproET1, ST2, Circulating microRNA’s, B-type Natriuretic peptide, Mid-regional pro-atrial natriuretic peptide. This review focuses on a variety of promising biomarkers which provide diagnostic and prognostic information of acute myocardial infarction. This may facilitate doctors for appropriate therapy to high-risk patients
Multiple Midfrontal Thetas Revealed by Source Separation of Simultaneous MEG and EEG

Theta-band (∼6 Hz) rhythmic activity within and over the medial PFC (“midfrontal theta”) has been identified as a distinctive signature of “response conflict,” the competition between multiple actions when only one action is goal-relevant. Midfrontal theta is traditionally conceptualized and analyzed under the assumption that it is a unitary signature of conflict that can be uniquely identified at one electrode (typically FCz). Here we recorded simultaneous MEG and EEG (total of 328 sensors) in 9 human subjects (7 female) and applied a feature-guided multivariate source-separation decomposition to determine whether conflict-related midfrontal theta is a unitary or multidimensional feature of the data. For each subject, a generalized eigendecomposition yielded spatial filters (components) that maximized the ratio between theta and broadband activity. Components were retained based on significance thresholding and midfrontal EEG topography. All of the subjects individually exhibited multiple (mean 5.89, SD 2.47) midfrontal components that contributed to sensor-level midfrontal theta power during the task. Component signals were temporally uncorrelated and asynchronous, suggesting that each midfrontal theta component was unique. Our findings call into question the dominant notion that midfrontal theta represents a unitary process. Instead, we suggest that midfrontal theta spans a multidimensional space, indicating multiple origins, but can manifest as a single feature at the sensor level because of signal mixing. SIGNIFICANCE STATEMENT “Midfrontal theta” is a rhythmic electrophysiological signature of the competition between multiple response options. Midfrontal theta is traditionally considered to reflect a single process. However, this assumption could be erroneous because of “mixing” (multiple sources contributing to the activity recorded at a single electrode). We investigated the dimensionality of midfrontal theta by applying advanced multivariate analysis methods to a multimodal MEG/EEG dataset. We identified multiple topographically overlapping neural sources that drove response conflict-related midfrontal theta. Midfrontal theta thus reflects multiple uncorrelated signals that manifest with similar EEG scalp projections. In addition to contributing to the cognitive control literature, we demonstrate both the feasibility and the necessity of signal demixing to understand the narrowband neural dynamics underlying cognitive processes.
Neandertal signatures in modern human mitochondrial genome haplogroups?

Affiliations 1 Department of Neurology and Neurosurgery, Federal University of São Paulo, São Paulo, SP, Brazil, CEP 04039032. 2 Graduate Program in Microbiology and Immunology, Federal University of São Paulo, São Paulo, SP, Brazil, CEP 04039032. 3 Institute for Personalized Medicine, Department of Biochemistry, Pennsylvania State University College of Medicine, 500 University Drive, 17033, Hershey PA, USA. 4 Department of Health Informatics, Federal University of São Paulo, São Paulo, SP, Brazil, CEP 04039032.
Long-term synaptic depression triggers local biogenesis of autophagic vesicles in dendrites and requires autophagic degradation

In neurons, biogenesis of autophagic vesicles (AVs) is spatially confined to the axon tip under baseline conditions. However, it remains unknown whether their biogenesis can be induced in other neuronal compartments following synaptic activity in order to serve local functions. Here, we show that both major types of long-term synaptic depression (LTD), a form of plasticity expressed by the shrinkage and elimination of dendritic spines, trigger the rapid and local biogenesis of AVs in post-synaptic dendrites. In return, autophagy is indispensable for LTD, as either genetic ablation of atg5 in pyramidal neurons or acute pharmacological inhibition of AV biogenesis totally prevents LTD induction. Using quantitative proteomic profiling of purified AVs, we reveal that upon LTD the autophagic cargo is significantly enriched for synaptic proteins, as well as modulators of the actin cytoskeleton and autism-implicated proteins. In line with these findings, a mild autophagy deficit is sufficient to impair behavioral flexibility, a cognitive function that requires efficient LTD. Therefore, local synthesis and assembly of the autophagic machinery in dendrites ensure the elimination of synaptic structures via degradation of their components, facilitating plasticity and associated behaviors. Graphical Abstract In brief Kallergi, Daskalaki and colleagues demonstrate that autophagy is cell autonomously required in pyramidal excitatory neurons for the induction of long-term synaptic depression (LTD). They uncover the novel and local biogenesis of autophagic vesicles (AVs) in dendrites upon LTD, by which post-synaptic components are rapidly accessible on-site for autophagic degradation. Using quantitative proteomics on purified AVs, they reveal that upon LTD the autophagic cargo is enriched in synaptic, cytoskeletal and autism-implicated proteins. Highlights Autophagy is required cell-autonomously in pyramidal neurons for LTD. NMDAR- and mGluR-mediated LTD trigger the local biogenesis of autophagic vesicles in dendrites. Autophagic vesicles sequester primarily synaptic and cytoskeletal cargo upon LTD. Mild impairment in autophagy leads to deficits in cognitive flexibility.
Long-read shotgun metagenome sequencing using PromethION uncovers novel bacteriophages, their abundance, and interaction with host bacterial immunity in the oral microbiota

Bacteriophages (phages), or bacterial viruses, are very diverse and highly abundant worldwide, including human microbiomes. Although a few metagenomic studies have focused on oral phages, they relied on short-read sequencing. Here, we conducted a long-read metagenomic study of human saliva for the first time using PromethION that requires a smaller amount of DNA than PacBio. Our analyses, which integrated both PromethION and HiSeq data of >30 Gb per sample, revealed N50 ranging from 187-345 kb and thousands of contigs with >1 kb accounting for > 99% of all contigs on which 94-96% of HiSeq reads were mapped. We identified hundreds of viral contigs (95 phages and 333 prophages on an average per sample); 0-43.8% and 12.5-56.3% of the “most confident” phages and prophages, respectively, didn’t cluster with those reported previously and were identified as novel. Our integrated analyses identified highly abundant oral phages/prophages, including a novel Streptococcus phage cluster and nine jumbo phages/prophages. Interestingly, 86% of the phage cluster and 67% of the jumbo phages/prophages contained remote homologs of antimicrobial resistance genes, suggesting their potential role as a source of recombination to generate new resistance genes. Pan-genome analysis of the phages/prophages revealed remarkable diversity, identifying 0.3% and 86.4% of the genes as core and singletons, respectively. Functional annotation revealed that the highest fraction of the core genes was enriched in phage morphogenesis, followed by the fraction enriched in host cellular processes. Furthermore, our study suggested that oral phages present in human saliva are under selective pressure for escaping CRISPR immunity. Importance Despite the abundance and grave implications oral bacterial viruses in health and disease, little is known regarding the different groups of oral bacterial viruses, their relative abundances under various conditions, and their activities. We provided answers to these questions for the first time utilizing a recently developed sequencer that can capture and sequence long DNA fragments, including viruses, and requires only a small amount of DNA input, making it suitable for analyzing human oral samples. We identified hundreds of viral sequences, including “jumbo” viruses and a distinctive group of highly abundant oral viruses, which often contained parts of antimicrobial resistance genes; the entire repertoire of these viral genes showed remarkable diversity and supported a recently proposed hypothesis that phages modulate oral microbiota through multiple mechanisms. We also revealed genomic signs of coevolution of viruses and host bacteria that have been missed in large viromic studies in humans.
Integrated Metabolomics, Transcriptomics, and Signal Protein Profile Define the Effector Function and Associated Metabotype of Five Polarized Macrophage Phenotypes

Macrophages (MΦs) display remarkable plasticity and the ability to activate diverse responses to a host of intracellular and external stimuli. Despite extensive characterization of M1 MΦs and a broad set of M2 MΦs, comprehensive characterization of metabolic shifts driving MΦ activation remains. Herein, we utilized an ex vivo model to produce six MΦ functional phenotypes. Isolated CD14+ PBMCs were differentiated into resting M0 MΦs, and then polarized into M1 (IFN-γ/LPS), M2a (IL-4/IL-13), M2b (IC/LPS), M2c (IL-10), and M2d (IL-6/LIF) MΦs. The MΦs were profiled using a bioanalyte matrix of four cell surface markers, ∼50 secreted proteins, ∼800 expressed myeloid genes, and ∼450 identified metabolites relative to M0 MΦs. Signal protein and expressed gene profiles grouped the MΦs into inflammatory (M1 and M2b) and wound resolution (M2a, M2c, and M2d) phenotypes; however, each had a unique metabolic profile. While both M1 and M2b MΦs shared metabotype profiles consistent with an inflammatory signature; key differences were observed in the TCA cycle, FAO and OXPHOS. Additionally, M2a, M2c and M2d MΦs all profiled as tissue repair MΦs; however, metabotype differences were observed in multiple pathways including hexosamine, polyamine, and fatty acid metabolism. These metabolic and other key functional distinctions suggest phagocytic and proliferative functions for M2a MΦs, and angiogenesis and ECM assembly capabilities for M2b, M2c and M2d MΦs. By integrating metabolomics into a systems analysis of MΦ phenotypes, we provide the most comprehensive map of MΦ diversity to date, along with the global metabolic shifts driving MΦ functional plasticity in these phenotypes. Summary Sentence Macrophage functional plasticity of six macrophage phenotypes correlates with unique distinctions in cell-surface marker expression, signal protein secretion, transcriptomics profiles, and metabolic processes.
Implications of simplified linkage equilibrium SNP simulation

In a recent paper published in PNAS (Golan et al. 2014)1, residual maximum likelihood (REML) seriously underestimated genetic variance explained by genome-wide single nucleotide polymorphism when using a case-control design. It was concluded that Haseman–Elston regression (denoted as PCGC in their paper) should be used instead of REML. Their conclusions were based on results from simplified linkage equilibrium SNP simulation (SLES), which the authors acknowledged may be unrealistic. We found that their simulation, SLES, unrealistically inflated the correlation between the eigenvectors of the genomic relationship matrix and disease status to values that are rarely observed in real data analyses. With a more realistic simulation that the authors failed to carry out (as they noted in their paper), we showed that there was no such inflated correlation between the eigenvectors of the genomic relationship matrix and disease status. Because REML uses the eigensystem of covariance structure, the inflated correlation artefactually constrained its estimates. We compared SNP-heritabilities from SLES and a more realistic simulation, showing that there was a substantial difference between the REML estimates from the two simulation strategies. Finally, we presented that there was no difference between REML and PCGC in real data analyses. This pattern from real data results differed strikingly from the pattern in the simulation study of Golan et al.1. One needs to be cautious of results drawn from SLES.
A comparative analysis of Caenorhabditis and Drosophila transcriptional changes in response to pathogen infection

Drosophila melanogaster and Caenorhabditis elegans are well-used invertebrate models for studying the innate immune system. The organisms are susceptible to bacterial pathogens that include Pseudomonas species, (entomophilia – Drosophila) or (aeruginosa – Caenorhabditis), E. faecalis and P. rettgeri, which are or are related to human pathogens. Further, the consequences of exposure to these pathogens, in terms of organismal survival, are roughly equivalent when compared. That is, worms and flies are more susceptible to infection by Pseudomonas than E. faecalis, whereas organismal survival on E. faecalis and P. rettgeri are roughly the same in both. To better understand how these organisms are coordinating their responses to these bacterial pathogens we examined transcriptomes in infected animals. We grouped our analysis based on protein orthology. Of the 3611 pairs analyzed, we found genes whose responses were conserved across the different species at a higher than expected rate for two of the three pathogens. Interestingly within the animals, genes with 1:1 orthologs between species behaved differently. Such genes were more likely to be expressed in D. melanogaster, and less likely to be expressed in C. elegans. From this analysis we found that the gene nucleobindin (nucb-1/NUCB1 in C. elegans and D. melanogaster, respectively) was upregulated in both species in response to Gram negative bacteria. We used RNAi to knock down nucb-1 and found the treated animals were more susceptible to infection by the Gram negative pathogen P. rettgeri than controls. These results provide insight into some of the conserved mechanisms of pathogen defense, but also suggest that these divergent organisms have evolved specific means to orchestrate the defense against pathogens. Article Summary We analyzed transcriptomic data from C. elegans and D. melanogaster to compare the expression of orthologous pairs of genes in response to bacterial pathogens. Our results indicated that only a handful of genes that are orthologous between species are differentially expressed in response to pathogens, but that the pattern of expression was different when comparing one-to-one orthologs versus those that are restricted to one of the two organisms. These results suggest that, although broad patterns of susceptibility to bacterial pathogens are conserved, the regulatory framework by which the organisms fight pathogens is less well conserved. Further our results suggest a more complete analysis of the evolutionary changes in organismal responses to pathogens is required.
Shifts in evolutionary balance of microbial phenotypes under environmental changes

Environmental conditions shape entire communities by driving microbial interactions. These interactions then find their reflection in the evolutionary outcome of microbial competition. In static, homogeneous environments a robust, or evolutionary stable, outcome in microbial communities is reachable, if it exists. However, introducing heterogeneity and time-dependence in microbial ecology leads to stochastic evolutionary outcomes determined by specific environmental changes. We utilise evolutionary game theory to provide insight into phenotypic competition in dynamic environments. We capture these effects in a perturbed evolutionary game describing microbial interactions at a phenotypic level. We show that under regular periodic environmental fluctuations a stable state that preserves dominant phenotypes is reached. However, rapid environmental shifts, especially in a cyclic interactions, can lead to critical shifts in the evolutionary balance among phenotypes. Our analysis suggests that an understanding of the robustness of the systems current state is necessary to understand when system will shift to the new equilibrium. This can be done by understanding the systems overall margin of safety, that is, what level of perturbations it can take before its equilibrium changes. In particular, the extent to which an environmental shift affects the system’s behaviour.
Molecular structure of a prevalent amyloid-β fibril polymorph from Alzheimer's disease brain tissue

Significance Amyloid-β (Aβ) fibrils are the main component of amyloid plaques that develop in brain tissue of Alzheimer’s disease (AD) patients. Aβ fibrils have a variety of molecular structures called polymorphs. Structural variations in Aβ fibrils may contribute to variations in the severity, progression rate, or clinical manifestations of AD. Previous studies, using seeded fibril growth from human cortical tissue and solid-state nuclear magnetic resonance spectroscopy, identified a single most prevalent polymorph for 40-residue Aβ (Aβ40) fibrils in typical AD patients. Here we report the molecular structure of this most prevalent Aβ40 fibril polymorph, determined with electron microscopy methods. Unique structural features of this polymorph may allow the future development of inhibitors and imaging agents with therapeutic and diagnostic value. Amyloid-β (Aβ) fibrils exhibit self-propagating, molecular-level polymorphisms that may contribute to variations in clinical and pathological characteristics of Alzheimer’s disease (AD). We report the molecular structure of a specific fibril polymorph, formed by 40-residue Aβ peptides (Aβ40), that is derived from cortical tissue of an AD patient by seeded fibril growth. The structure is determined from cryogenic electron microscopy (cryoEM) images, supplemented by mass-per-length (MPL) measurements and solid-state NMR (ssNMR) data. Previous ssNMR studies with multiple AD patients had identified this polymorph as the most prevalent brain-derived Aβ40 fibril polymorph from typical AD patients. The structure, which has 2.8-Å resolution according to standard criteria, differs qualitatively from all previously described Aβ fibril structures, both in its molecular conformations and its organization of cross-β subunits. Unique features include twofold screw symmetry about the fibril growth axis, despite an MPL value that indicates three Aβ40 molecules per 4.8-Å β-sheet spacing, a four-layered architecture, and fully extended conformations for molecules in the central two cross-β layers. The cryoEM density, ssNMR data, and MPL data are consistent with β-hairpin conformations for molecules in the outer cross-β layers. Knowledge of this brain-derived fibril structure may contribute to the development of structure-specific amyloid imaging agents and aggregation inhibitors with greater diagnostic and therapeutic utility.
Quantifying and contextualizing the impact of bioRxiv preprints through automated social media audience segmentation

Engagement with scientific manuscripts is frequently facilitated by Twitter and other social media platforms. As such, the demographics of a paper’s social media audience provide a wealth of information about how scholarly research is transmitted, consumed, and interpreted by online communities. By paying attention to public perceptions of their publications, scientists can learn whether their research is stimulating positive scholarly and public thought. They can also become aware of potentially negative patterns of interest from groups that misinterpret their work in harmful ways, either willfully or unintentionally, and devise strategies for altering their messaging to mitigate these impacts. In this study, we collected 331,696 Twitter posts referencing 1,800 highly tweeted bioRxiv preprints and leveraged topic modeling to infer the characteristics of various communities engaging with each preprint on Twitter. We agnostically learned the characteristics of these audience sectors from keywords each user’s followers provide in their Twitter biographies. We estimate that 96% of the preprints analyzed are dominated by academic audiences on Twitter, suggesting that social media attention does not always correspond to greater public exposure. We further demonstrate how our audience segmentation method can quantify the level of interest from non-specialist audience sectors such as mental health advocates, dog lovers, video game developers, vegans, bitcoin investors, conspiracy theorists, journalists, religious groups, and political constituencies. Surprisingly, we also found that 10% of the highly tweeted preprints analyzed have sizable (>5%) audience sectors that are associated with right-wing white nationalist communities. Although none of these preprints intentionally espouse any right-wing extremist messages, cases exist where extremist appropriation comprises more than 50% of the tweets referencing a given preprint. These results present unique opportunities for improving and contextualizing research evaluation as well as shedding light on the unavoidable challenges of scientific discourse afforded by social media.
Establishment of a Pig Influenza Challenge Model for Evaluation of Monoclonal Antibody Delivery Platforms

Monoclonal antibodies are a possible adjunct to vaccination and drugs in treatment of influenza virus infection. However questions remain whether small animal models accurately predict efficacy in humans. We have established the pig, a large natural host animal for influenza, with many physiological similarities to humans, as a robust model for testing monoclonal antibodies. We show that a strongly neutralizing monoclonal antibody (2-12C) against the hemagglutinin head administered prophylactically at 15 mg/kg reduced viral load and lung pathology after pandemic H1N1 influenza challenge. A lower dose of 1 mg/kg of 2-12C or a DNA plasmid encoded version of 2-12C, reduced pathology and viral load in the lungs, but not viral shedding in nasal swabs. We propose that the pig influenza model will be useful for testing candidate monoclonal antibodies and emerging delivery platforms prior to human trials.