bluuebunny/crossref_metadata_2025_split huggingface dataset:
Brain Data Standards - A method for building data-driven cell-type ontologies
Authors: Tan Shawn Zheng Kai , Kir Huseyin , Aevermann Brian D. , Gillespie Tom , Harris Nomi , Hawrylycz Michael , Jorstad Nik , Lein Ed , Matentzoglu Nicolas , Miller Jeremy A. , Mollenkopf Tyler S. , Mungall Christopher J. , Ray Patrick L. , Sanchez Raymond E. A. , Staats Brian , Vermillion Jim , Yadav Ambika , Zhang Yun , Scheuermann Richard H. , Osumi-Sutherland David 
Published: October 2021

AbstractLarge-scale single-cell ‘omics profiling is revolutionising our understanding of cell types in complex organs like the brain, where it is being used to define a complete catalogue of cell types, something that traditional methods struggle with due to the diversity and complexity of the brain. But this poses a problem. How do we organise such a catalogue - providing a standard way to refer to the cell types discovered, linking their classification and properties to supporting data? Cell ontologies provide a solution to recording definitions, classifications, and properties of cell types and provide standard identifiers for annotation, but they currently do not support the data driven cell type definitions and classifications needed for multi-modal single cell ‘omics profiling.Here we describe the construction and application of a semi-automated, data-linked extension to the Cell Ontology that represents cell types in the Primary Motor Cortex of humans, mice and marmosets. The methods and resulting ontology are designed to be scalable and applicable to similar whole brain atlases currently in preparation.
Confirmation of fishers’ local ecological knowledge of ciguatoxic fish species and ciguatera-prone hotspot areas in Puerto Rico using harmful benthic algae surveys and fish toxicity testing
Authors: Raab Henry , Luczkovich Joe , Pozo Miguel Del , Griffith David , Grace-McCaskey Cindy , Litaker Wayne 
Published: October 2021

AbstractCiguatoxin fish poisoning (CFP) is caused by the consumption of tropical and subtropical fishes and other marine species with high levels of ciguatoxin (CTX) in their tissues. CTX is a polycyclic neurotoxin produced by single-celled, photosynthetic dinoflagellates in the Gambierdiscus and Fukuyoa genera which are found in close association with benthic autotrophs. CTX enters the food web when these dinoflagellates are inadvertently consumed by herbivores grazing on their preferred substrates. The toxin biomagnifies up the food chain to the top predators and if humans consume seafood with high levels of CTX it can cause a variety of flu-like symptoms. The best way to avoid CFP is to avoid toxic fishes. However, CTX is undetectable by physical inspection. This study investigated local fishers’ knowledge of ciguatera hotspots and coldspots along Puerto Rican coral reefs using toxic-dinoflagellate cell counts and by estimating fish toxicity in those sites using a cell-based Neuro-2a cytotoxicity assay. The fishers identified regions of high and low risk for CFP based on their local ecological knowledge (LEK) which were deemed hotspots and coldspots, respectively. There is a 35-fold difference in dinoflagellate cell counts of low-toxicity Gambierdiscus species in samples in the identified hotspot compared to the coldspot. Also, higher trophic level fishes (>3.4 ETL) had higher median estimates of CTX in their tissues at the hotspot than the same species in the coldspot. This study shows the effectiveness of LEK in identifying potential problem areas for ciguatera.
Distinct competitive impacts of palatability of taste stimuli on sampling dynamics during a preference test
Authors: Ballintyn Benjamin , Ksander John , Katz Donald , Miller Paul 
Published: October 2021

AbstractFood or taste preference tests are analogous to naturalistic decisions in which the animal selects which stimuli to sample and for how long to sample them. The data acquired in such tests, the relative amounts of the alternative stimuli that are sampled and consumed, indicate the preference for each. While such preferences are typically recorded as a single quantity, an analysis of the ongoing sampling dynamics producing the preference can reveal otherwise hidden aspects of the decision-making process that depend on its underlying neural circuit mechanisms. Here, we perform a dynamic analysis of two factors that give rise to preferences in a two-alternative task, namely the distribution of durations of sampling bouts of each stimulus and the likelihood of returning to the same stimulus or switching to the alternative—i. e., the transition probability—following each bout. The results of our analysis support a specific computational model of decision-making whereby an exponential distribution of bout durations has a mean that is positively correlated with the palatability of that stimulus, but also negatively correlated with the palatability of the alternative. This impact of the alternative stimulus on the distribution of bout durations decays over a timescale of tens of seconds, even though the memory of the alternative stimulus lasts far longer—long enough to impact the transition probabilities upon ending bouts. Together, our findings support a state-transition model for bout durations and suggest a separate memory mechanism for stimulus-selection.
Reverse engineering of metacognition
Authors: Guggenmos Matthias 
Published: October 2021

AbstractThe human ability to introspect on thoughts, perceptions or actions − metacognitive ability − has become a focal topic of both cognitive basic and clinical research. At the same time it has become increasingly clear that currently available quantitative tools are limited in their ability to make unconfounded inferences about metacognition. As a step forward, the present work introduces a comprehensive modeling framework of metacognition that allows for inferences about metacognitive noise and metacognitive biases during the readout of decision values or at the confidence reporting stage. The model assumes that confidence results from a continuous but noisy and potentially biased transformation of decision values, described by a confidence link function. A canonical set of metacognitive noise distributions is introduced which differ, amongst others, in their predictions about metacognitive sign flips of decision values. Successful recovery of model parameters is demonstrated, and the model is validated on an empirical data set. In particular, it is shown that metacognitive noise and bias parameters correlate with conventional behavioral measures. Crucially, in contrast to these conventional measures, metacognitive noise parameters inferred from the model are shown to be independent of performance. This work is accompanied by a toolbox (ReMeta) that allows researchers to estimate key parameters of metacognition in confidence datasets.
Structural basis of mitochondrial protein import by the TIM complex
Authors: Sim Sue Im , Chen Yuanyuan , Park Eunyong 
Published: October 2021

AbstractMitochondria import nearly all their ∼1,000–2,000 constituent proteins from the cytosol across their double membrane envelope. Genetic and biochemical studies have shown that the conserved protein translocase, termed the TIM complex (also known as TIM23 complex), mediates import of presequence-containing proteins into the mitochondrial matrix and inner membrane. Among ∼10 different subunits of the complex, the essential multi-pass membrane protein Tim23, together with the evolutionarily related protein Tim17, has long been postulated to form a protein-conducting channel. However, the mechanism of TIM-mediated protein import remains uncertain due to a lack of structural information on the complex. Here, we have determined the cryo-EM structure of the core TIM complex (Tim17–Tim23–Tim44) from Saccharomyces cerevisiae. We show that, contrary to the prevailing model, Tim23 and Tim17 do not form a water-filled channel, but instead have separate, lipid-exposed concave cavities that face in opposite directions. Remarkably, our data suggest that the cavity of Tim17 itself forms the protein translocation path whereas Tim23 plays a structural role. We also show how the Tim17–Tim23 heterodimer associates with the scaffold protein Tim44 and J-domain proteins to mediate Hsp70-driven polypeptide transport into the matrix. Our work provides the structural foundation to understand the mechanism of TIM-mediated protein import and sorting, a central pathway in mitochondrial biogenesis.
A Novel Activation Maximization-based Approach for Insight into Electrophysiology Classifiers
Authors: Ellis Charles A. , Sendi Mohammad S.E. , Miller Robyn , Calhoun Vince 
Published: October 2021

AbstractSpectral analysis remains a hallmark approach for gaining insight into electrophysiology modalities like electroencephalography (EEG). As the field of deep learning has progressed, more studies have begun to train deep learning classifiers on raw EEG data, which presents unique problems for explainability. A growing number of studies have presented explainability approaches that provide insight into the spectral features learned by deep learning classifiers. However, existing approaches only attribute importance to different frequency bands. Most of the methods cannot provide insight into the actual spectral values or the relationship between spectral features that models have learned. Here, we present a novel adaptation of activation maximization for electrophysiology time-series that generates samples that indicate the features learned by classifiers by optimizing their spectral content. We evaluate our approach within the context of EEG sleep stage classification with a convolutional neural network, and we find that our approach is able to identify spectral patterns known to be associated with each sleep stage. We also find surprising results suggesting that our classifier may have prioritized the use of eye and motion artifact when identifying Awake samples. Our approach is the first adaptation of activation maximization to the domain of raw electrophysiology classification. Additionally, our approach has implications for explaining any classifier trained on highly dynamic, long time-series.
Deep learning redesign of PETase for practical PET degrading applications
Authors: Lu Hongyuan , Diaz Daniel J. , Czarnecki Natalie J. , Zhu Congzhi , Kim Wantae , Shroff Raghav , Acosta Daniel J. , Alexander Brad , Cole Hannah , Zhang Yan Jessie , Lynd Nathaniel , Ellington Andrew D. , Alper Hal S. 
Published: October 2021

AbstractPlastic waste poses an ecological challenge1. While current plastic waste management largely relies on unsustainable, energy-intensive, or even hazardous physicochemical and mechanical processes, enzymatic degradation offers a green and sustainable route for plastic waste recycling2. Poly(ethylene terephthalate) (PET) has been extensively used in packaging and for the manufacture of fabrics and single-used containers, accounting for 12% of global solid waste3. The practical application of PET hydrolases has been hampered by their lack of robustness and the requirement for high processing temperatures. Here, we use a structure-based, deep learning algorithm to engineer an extremely robust and highly active PET hydrolase. Our best resulting mutant (FAST-PETase: Functional, Active, Stable, and Tolerant PETase) exhibits superior PET-hydrolytic activity relative to both wild-type and engineered alternatives, (including a leaf-branch compost cutinase and its mutant4) and possesses enhanced thermostability and pH tolerance. We demonstrate that whole, untreated, post-consumer PET from 51 different plastic products can all be completely degraded by FAST-PETase within one week, and in as little as 24 hours at 50 °C. Finally, we demonstrate two paths for closed-loop PET recycling and valorization. First, we re-synthesize virgin PET from the monomers recovered after enzymatic depolymerization. Second, we enable in situ microbially-enabled valorization using a Pseudomonas strain together with FAST-PETase to degrade PET and utilize the evolved monomers as a carbon source for growth and polyhydroxyalkanoate production. Collectively, our results demonstrate the substantial improvements enabled by deep learning and a viable route for enzymatic plastic recycling at the industrial scale.
TRAIP regulates DNA double-strand break-induced ATM activation
Authors: Gleich Tobias , Quadroni Manfredo , Yigit Gökhan , Wollnik Bernd , Huber Marcel , Pich Christine , Hohl Daniel 
Published: October 2021

ABSTRACTDNA double-strand breaks (DSBs) affect cell survival and genomic integrity. They are repaired by a highly coordinated process called the DNA damage response. Here, we report that the ubiquitously expressed nucleolar E3 ubiquitin ligase TRAF-interacting protein (TRAIP), previously shown to regulate the spindle assembly checkpoint, has an essential role during the DNA damage response. A biotinylation proximity screening assay (BioID) identified Ku80, Ku70, SMARCA5 (SNF2H) and DNA-PKcs as novel TRAIP interactors. Co-immunoprecipitations demonstrated that the interaction of TRAIP with Ku80 was transiently increased while the one with SMARCA5 was strongly decreased after treatment of HeLa cells with neocarzinostatin (NCS). Treatment of fibroblasts from a microcephalic primordial dwarfism patient carrying a hypomorphic TRAIP mutation or shRNA-mediated knockdown of TRAIP in HeLa cells with NCS impaired the activation of ataxia-telangiectasia mutated (ATM), a protein kinase crucial for the DNA damage response. As consequence, the maintenance of γH2AX and Chk2-T68 phosphorylation, two downstream targets of ATM, was significantly abrogated after NCS-inflicted DSBs. DNA repair assays showed that TRAIP inhibits incorrect end utilization during non-homologous end joining. These observations highlight TRAIP as novel regulator of ATM activity in DNA damage signaling.
Effects of forest disturbance and regeneration on tree species composition and traits in DR Congo
Authors: Depecker Jonas , Asimonyio Anio Justin , Miteho Ronald , Hatangi Yves , Kambale Jean-Léon , Verleysen Lauren , Stoffelen Piet , Janssens Steven B. , Dhed’a Benoit , Vandelook Filip , Honnay Olivier 
Published: October 2021

ABSTRACTDespite their key role in biodiversity conservation, forests of the Congo Basin are increasingly threatened by human activities. Whereas deforestation is very conspicuous, it remains challenging to monitor the impact of forest degradation under a more or less intact canopy. Likewise, the outcomes of forest regeneration following agricultural abandonment remain poorly studied in the Congo Basin. Here, we surveyed 125 vegetation quadrats across 25 forest inventory plots in the Yangambi region, and based on historical land-use maps. We aimed to assess both the impact of anthropogenic disturbance and forest recovery on tree species diversity, tree functional traits, community composition, canopy cover, and forest structure, as compared to undisturbed old-growth forest. We found that undisturbed old-growth forest harboured more tree individuals, particularly individuals with a smaller diameter, as well as species with a higher wood density when compared to both disturbed old-growth and regrowth forest. Moreover, species diversity was highest in disturbed old-growth forest. Tree species composition was significantly different between undisturbed old-growth forest and the other two forest categories. Our findings indicate that anthropogenic disturbance results in a degraded forest structure and may reduce the forest’s ability to store carbon. Whereas species diversity recovered 60 years after agricultural abandonment, species composition remained different from undisturbed old-growth forest. Our study illustrates the need for more extensive vegetation surveys in the Congo Basin in order to quantify the effects of human disturbance under a closed canopy.
Whole genome sequence analysis of blood lipid levels in >66,000 individuals
Authors: Selvaraj Margaret Sunitha , Li Xihao , Li Zilin , Pampana Akhil , Zhang David Y , Park Joseph , Aslibekyan Stella , Bis Joshua C , Brody Jennifer A , Cade Brian E , Chuang Lee-Ming , Chung Ren-Hua , Curran Joanne E , Fuentes Lisa de las , de Vries Paul S , Duggirala Ravindranath , Freedman Barry I , Graff Mariaelisa , Guo Xiuqing , Heard-Costa Nancy , Hidalgo Bertha , Hwu Chii-Min , Irvin Marguerite R , Kelly Tanika N , Kral Brian G , Lange Leslie , Li Xiaohui , Lisa Martin , Lubitz Steven A , Manichaikul Ani W , Michael Preuss , Montasser May E , Morrison Alanna C , Naseri Take , O’Connell Jeffrey R , Palmer Nicholette D , Peyser Patricia A , Reupena Muagututia S , Smith Jennifer A , Sun Xiao , Taylor Kent D , Tracy Russell P , Tsai Michael Y , Wang Zhe , Wang Yuxuan , Wei Bao , Wilkins John T , Yanek Lisa R , Zhao Wei , Arnett Donna K , Blangero John , Boerwinkle Eric , Bowden Donald W , Chen Yii-Der Ida , Correa Adolfo , Cupples L Adrienne , Dutcher Susan K , Ellinor Patrick T , Fornage Myriam , Gabriel Stacey , Germer Soren , Gibbs Richard , He Jiang , Kaplan Robert C , Kardia Sharon LR , Kim Ryan , Kooperberg Charles , Loos Ruth J. F. , Martinez Karine , Mathias Rasika A , McGarvey Stephen T , Mitchell Braxton D , Nickerson Deborah , North Kari E , Psaty Bruce M , Redline Susan , Reiner Alexander P , Vasan Ramachandran S , Rich Stephen S , Willer Cristen , Rotter Jerome I , Rader Daniel J , Lin Xihong ,   NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, Peloso Gina M , Natarajan Pradeep 
Published: October 2021

AbstractPlasma lipids are heritable modifiable causal factors for coronary artery disease, the leading cause of death globally. Despite the well-described monogenic and polygenic bases of dyslipidemia, limitations remain in discovery of lipid-associated alleles using whole genome sequencing, partly due to limited sample sizes, ancestral diversity, and interpretation of potential clinical significance. Increasingly larger whole genome sequence datasets with plasma lipids coupled with methodologic advances enable us to more fully catalog the allelic spectrum for lipids. Here, among 66,329 ancestrally diverse (56% non-European ancestry) participants, we associate 428M variants from deep-coverage whole genome sequences with plasma lipids. Approximately 400M of these variants were not studied in prior lipids genetic analyses. We find multiple lipid-related genes strongly associated with plasma lipids through analysis of common and rare coding variants. We additionally discover several significantly associated rare non-coding variants largely at Mendelian lipid genes. Notably, we detect rareLDLRintronic variants associated with markedly increased LDL-C, similar to rareLDLRexonic variants. In conclusion, we conducted a systematic whole genome scan for plasma lipids expanding the alleles linked to lipids for multiple ancestries and characterize a clinically-relevant rare non-coding variant model for lipids.
Mechanisms and physiological function of daily haemoglobin oxidation rhythms in red blood cells
Authors: Beale Andrew D. , Hayter Edward A. , Crosby Priya , Valekunja Utham K. , Edgar Rachel S. , Chesham Johanna E. , Maywood Elizabeth S. , Labeed Fatima H. , Reddy Akhilesh B. , Wright Kenneth P. , Lilley Kathryn S. , Bechtold David A. , Hastings Michael H. , O’Neill John S. 
Published: October 2021

AbstractCellular circadian rhythms confer temporal organisation upon physiology that is fundamental to human health. Rhythms are present in red blood cells (RBCs), the most abundant cell type in the body, but their physiological function is poorly understood. Here, we present a novel biochemical assay for haemoglobin (Hb) oxidation status which relies on a redox-sensitive covalent haem-Hb linkage that forms during SDS-mediated cell lysis. Formation of this linkage is lowest when ferrous Hb is oxidised, in the form of ferric metHb. Daily haemoglobin oxidation rhythms are observed in RBCs culturedin vitroor taken from freely behaving mice or humans exhibit and are unaffected by mutations that affect circadian rhythms in nucleated cells. These rhythms correlate with daily rhythms in core body temperature, with temperature lowest when metHb levels are highest. Raising metHb levels with dietary sodium nitrite can further decrease daytime core body temperature in mice via NO signaling. These results extend our molecular understanding of RBC circadian rhythms and suggest they contribute to the regulation of body temperature.
JIP3 regulates bi-directional organelle transport in neurons through its interaction with dynein and kinesin-1
Authors: Celestino Ricardo , Gama José B. , Castro-Rodrigues Artur F. , Barbosa Daniel J. , d’Amico Ennio A. , Musacchio Andrea , Carvalho Ana Xavier , Morais-Cabral João H. , Gassmann Reto 
Published: October 2021

SUMMARYThe conserved MAP kinase and motor scaffold JIP3 prevents excess lysosome accumulation in axons of vertebrates and invertebrates. Whether and how JIP3’s interaction with dynein and kinesin-1 contributes to this critical organelle clearance function is unclear. Using purified recombinant human proteins, we show that dynein light intermediate chain (DLIC) binds to the N-terminal RH1 domain of JIP3, its paralog JIP4, and the lysosomal adaptor RILP. A point mutation in a hydrophobic pocket of the RH1 domain, previously shown to abrogate RILPL2 binding to myosin Va, abrogates the binding of JIP3/4 and RILP to DLIC without perturbing the interaction between the JIP3 RH1 domain and kinesin heavy chain. Characterization of this separation-of-function mutation in Caenorhabditis elegans shows that JIP3–bound dynein is required for organelle clearance in the anterior process of touch receptor neurons. Unlike JIP3 null mutants, JIP3 that cannot bind DLIC causes prominent accumulation of endo-lysosomal organelles at the neurite tip, which is rescued by a disease-associated point mutation in JIP3’s leucine zipper that abrogates kinesin light chain binding. These results highlight that RH1 domains are interaction hubs for cytoskeletal motors and suggest that JIP3–bound dynein and kinesin-1 participate in bi-directional organelle transport.
Single cell micro-pillar-based characterization of endothelial and fibroblast cell mechanics
Authors: Eckert Julia , Abouleila Yasmine , Schmidt Thomas , Mashaghi Alireza 
Published: October 2021

AbstractMechanotransduction, the ability of cells to sense and respond to the mechanical cues from their microenvironment, plays an important role in numerous cellular processes, ranging from cell migration to differentiation. Several techniques have been developed to investigate the underlying mechanisms of mechanotransduction, in particular, force measurement-based techniques. However, we still lack basic single cell quantitative comparison on the mechanical properties of commonly used cell types, such as endothelial and fibroblast cells. Such information is critical to provide a precedent for studying complex tissues and organs that consist of various cell types. In this short communication, we report on the mechanical characterization of the commonly used endothelial and fibroblast cells at the single cell level. Using a micropillar-based assay, we measured the traction force profiles of these cells. Our study showcases differences between the two cell types in their traction force distribution and morphology. The results reported can be used as a reference and to lay the groundwork for future analysis of numerous disease models involving these cells.