bluuebunny/crossref_metadata_2025_split huggingface dataset:
Integrating protein copy numbers with interaction networks to quantify stoichiometry in mammalian endocytosis
Authors: Duan Daisy , Hanson Meretta , Holland David O. , Johnson Margaret E 
Published: October 2020

AbstractProteins that drive processes like clathrin-mediated endocytosis (CME) are expressed at various copy numbers within a cell, from hundreds (e.g. auxilin) to millions (e.g. clathrin). Between cell types with identical genomes, copy numbers further vary significantly both in absolute and relative abundance. These variations contain essential information about each protein’s function, but how significant are these variations and how can they be quantified to infer useful functional behavior? Here, we address this by quantifying the stoichiometry of proteins involved in the CME network. We find robust trends across three cell types in proteins that are sub- vs super-stoichiometric in terms of protein function, network topology (e.g. hubs), and abundance. To perform this analysis, we first constructed the interface resolved network of 82 proteins involved in CME in mammals, plus lipid and cargo binding partners, totaling over 600 specific binding interactions. Our model solves for stoichiometric balance by optimizing each copy of a protein interface to match up to its partner interfaces, keeping the optimized copies as close as possible to observed copies. We find highly expressed, structure-forming proteins such as actin and clathrin do tend to be super-stoichiometric, or in excess of their partners, but they are not the most extreme cases. We test sensitivity of network stoichiometry to protein removal and find that hub proteins tend to be less sensitive to removal of any single partner, thus acting as buffers that compensate dosage changes. As expected, tightly coupled protein pairs (e.g.CAPZA2 and CAPZB) are strongly correlated. Unexpectedly, removal of functionally similar cargo adaptor proteins produces widely variable levels of disruption to the network stoichiometry. Our results predict that knockdown of the adaptor protein DAB2 will globally impact the stoichiometry of most other cargo adaptor proteins in Hela cells, with significantly less impact in fibroblast cells. This inexpensive analysis can be applied to any protein network, synthesizing disparate sources of biological data into a relatively simple and intuitive model of binding stoichiometry that can aid in dynamical modeling and experimental design.
Sodium channel toxin-resistance mutations do not govern batrachotoxin (BTX) autoresistance in poison birds and frogs
Authors: Abderemane-Ali Fayal , Rossen Nathan D. , Kobiela Megan E. , Craig Robert A. , Garrison Catherine E. , O’Connell Lauren A. , Du Bois J. , Dumbacher John P. , Minor Daniel L. 
Published: October 2020

AbstractPoisonous organisms carry small molecule toxins that alter voltage-gated sodium channel (Na✓) function. Among these, batrachotoxin (BTX) fromPitohuitoxic birds andPhyllobatespoison frogs, stands out because of its lethality and unusual effects on Navfunction. How these toxin-bearing organisms avoid autointoxication remains poorly understood. In poison frogs, a NavDIVS6 pore-forming helix N→T mutation has been proposed as the BTX resistance mechanism. Here, we show that this variant is absent fromPitohuiand poison frog Navs, incurs a strong cost that compromises channel function, and fails to produce BTX-resistant channels when tested in the context of poison frog Navs. We further show that captive-raised poison frogs are BTX resistant, even though they bear BTX-sensitive Navs. Hence, our data refute the hypothesis that BTX autoresistance is rooted in Navmutations and instead suggest that more generalizable mechanisms such as toxin sequestration act to protect BTX-bearing species from autointoxication.
Genetic Circuits Combined with Machine Learning Provides Fast Responding Living Sensors
Authors: Saltepe Behide , Bozkurt Eray Ulaş , Güngen Murat Alp , Çiçek A. Ercüment , Şeker Urartu Özgür Şafak 
Published: October 2020

AbstractWhole cell biosensors (WCBs) have become prominent in many fields from environmental analysis to biomedical diagnostics thanks to advanced genetic circuit design principles. Despite increasing demand on cost effective and easy-to-use assessment methods, a considerable amount of WCBs retains certain drawbacks such as long response time, low precision and accuracy. Furthermore, the output signal level does not correspond to a specific analyte concentration value but shows comparative quantification. Here, we utilized a neural network-based architecture to improve the aforementioned features of WCBs and engineered a gold sensing WCB which has a long response time (18 h). Two Long-Short Term-Memory (LSTM)-based networks were integrated to assess both ON/OFF and concentration dependent states of the sensor output, respectively. We demonstrated that binary (ON/OFF) network was able to distinguish between ON/OFF states as early as 30 min with 78% accuracy and over 98% in 3 h. Furthermore, when analyzed in analog manner, we demonstrated that network can classify the raw fluorescence data into pre-defined analyte concentration groups with high precision (82%) in 3 h. This approach can be applied to a wide range of WCBs and improve rapidness, simplicity and accuracy which are the main challenges in synthetic biology enabled biosensing.
Transcriptional profiling reveals conserved and species-specific plant defense responses during the interaction of the early divergent plantPhyscomitrium patenswithBotrytis cinerea
Authors: Reboledo Guillermo , Agorio Astrid , Vignale Lucía , Batista-García Ramón Alberto , De León Inés Ponce 
Published: October 2020

AbstractBryophytes were among the first plants that colonized earth and they evolved key defense mechanisms to counteract microbial pathogens present in the new environment. Although great advances have been made on pathogen perception and subsequent defense activation in angiosperms, limited information is available in early divergent land plants. In this study, a transcriptomic approach uncovered the molecular mechanisms underlying the defense response of the bryophytePhyscomitrium patensagainst the important plant pathogenBotrytis cinerea. A total of 3.072 differentially expressed genes were significantly affected duringB. cinereainfection, including genes encoding proteins with known function in angiosperm immunity and involved in pathogen perception, signaling, transcription, hormonal signaling, metabolic pathways such as shikimate and phenylpropanoid, and proteins with diverse role in defense against biotic stress. Similarly as in other plants,B. cinereainfection leads to downregulation of genes involved in photosynthesis and cell cycle progression. These results highlight the existence of evolutionary conserved defense responses to pathogens throughout the green plant lineage, suggesting that they were probably present in the common ancestors of land plants. Moreover, several genes acquired by horizontal transfer from prokaryotes and fungi, and a high number ofP. patens-specific orphan genes were differentially expressed duringB. cinereainfection, indicating that they are part of the moss immune response and probably played an ancestral role related to effective adaptation mechanisms to cope with pathogen invasion during the conquest of land.Key MessageEvolutionary conserved defense mechanisms present in extant bryophytes and angiosperms, as well as moss-specific defenses are part of the immune response of the early divergent land plantPhyscomitrium patens.
Molecular portraits of cell cycle checkpoint kinases in cancer evolution, progression, and treatment responsiveness
Authors: Oropeza E , Seker S , Carrel S , Mazumder A , Jimenez A , VandenHeuvel SN , Noltensmeyer DA , Punturi NB , Lei JT , Lim B , Raghavan S , Bainbridge MN , Haricharan S 
Published: October 2020

AbstractCell cycle dysregulation is prerequisite for cancer formation. However, it is unknown whether the mode of dysregulation affects disease characteristics. Here, we conduct comprehensive analyses of cell cycle checkpoint dysregulation events in breast cancer using patient data complemented by experimental investigations in multiple model systems: genetically-engineered mice, patient-derived xenografts, biomatrices, and cell lines. We find thatATMmutation predisposes the diagnosis of primary estrogen receptor (ER)+/human epidermal growth factor (HER)2- cancer in older women. Conversely, CHK2 dysregulation induces formation of metastatic, premenopausal ER+/HER2- breast cancer (p=0.001) that is treatment-resistant (HR=6.15, p=0.01). Lastly, while mutations inATRalone are rare,ATR/TP53co-mutation is 12-fold enriched over expected in ER+/HER2- disease (p=0.002) and associates with metastatic progression (HR=2.01, p=0.006). Concordantly, ATR dysregulation induces metastatic phenotypes inTP53mutant, but not wild-type, cells. These results newly identify a role for distinct cell cycle dysregulation events in determining cancer subtype, metastatic potential, and treatment responsiveness.Statement of SignificanceThese findings reframe the paradigm of cancer classification by demonstrating that cell cycle dysregulation decisions during malignant transformation can causally direct the type of cancer that evolves, its metastatic potential, and treatment responsiveness. These results provide rationale for delineating mode of checkpoint kinase dysregulation to improve diagnostic and therapeutic choices.
Unsupervised Learning of Brain State Dynamics during Emotion Imagery using High-Density EEG
Authors: Hsu Sheng-Hsiou , Lin Yayu , Onton Julie , Jung Tzyy-Ping , Makeig Scott 
Published: October 2020

AbstractHere we assume that emotional states correspond to functional dynamic states of brain and body, and attempt to characterize the appearance of these states in high-density scalp electroencephalographic (EEG) recordings acquired from 31 participants during 1-2 hour sessions, each including fifteen 3-5 min periods of self-induced emotion imagination using the method of guided imagery. EEG offers an objective and high-resolution measurement of whatever portion of cortical electrical dynamics is resolvable from scalp recordings. Despite preliminary progress in EEG-based emotion decoding using supervised machine learning methods, few studies have applied data-driven, unsupervised decomposition approaches to investigate the underlying EEG dynamics by characterizing brain temporal dynamics during emotional experience. This study applies an unsupervised approach – adaptive mixture independent component analysis (adaptive mixture ICA, AMICA) that learns a set of ICA models each accounted for portions of a given multi-channel EEG recording. We demonstrate that 20-model AMICA decomposition can identify distinct EEG patterns or dynamic states active during each of the fifteen emotion-imagery periods. The transition in EEG patterns revealed the time-courses of brain-state dynamics during emotional imagery. These time-courses varied across emotions: “grief” and “happiness” showed more abrupt transitions while “contentment” was nearly indistinguishable from the preceding rest period. The spatial distributions of independent components (ICs) of the AMICA models showed higher similarity within-subject across emotions than within-emotion across subjects. No significant differences in IC distributions were found between positive and negative emotions. However, significant changes in IC distributions during emotional imagery compared to rest were identified in brain areas such as the left prefrontal cortex, the posterior cingulate cortex, the motor cortex, and the visual cortex. The study demonstrates the feasibility of AMICA in modeling high-density and nonstationary EEG and its utility in providing data-driven insights into brain state dynamics during self-paced emotional experiences, which have been difficult to measure. This approach can advance our understanding of highly dynamical emotional processes and improve the performance of EEG-based emotion decoding for affective computing and human-computer interaction.
A Python-based optimization framework for high-performance genomics
Authors: Shajii Ariya , Numanagić Ibrahim , Leighton Alexander T. , Greenyer Haley , Amarasinghe Saman , Berger Bonnie 
Published: October 2020

AbstractExponentially-growing next-generation sequencing data requires high-performance tools and algorithms. Nevertheless, the implementation of high-performance computational genomics software is inaccessible to many scientists because it requires extensive knowledge of low-level software optimization techniques, forcing scientists to resort to high-level software alternatives that are less efficient. Here, we introduce Seq—a Python-based optimization framework that combines the power and usability of high-level languages like Python with the performance of low-level languages like C or C++. Seq allows for shorter, simpler code, is readily usable by a novice programmer, and obtains significant performance improvements over existing languages and frameworks. We showcase and evaluate Seq by implementing seven standard, widely-used applications from all stages of the genomics analysis pipeline, including genome index construction, finding maximal exact matches, long-read alignment and haplotype phasing, and demonstrate its implementations are up to an order of magnitude faster than existing hand-optimized implementations, with just a fraction of the code. By enabling researchers of all backgrounds to easily implement high-performance analysis tools, Seq further opens the door to the democratization and scalability of computational genomics.
Fluid Intelligence and Time Management and Artificial Neural Networks
Authors: Tiitto Markus Ville , Lodder Robert A. 
Published: October 2020

AbstractAttention deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterized by inattention, hyperactivity, and impulsivity. Our lab is currently conducting a pilot study to assess the effects of the online game Minecraft as a therapeutic video game (TVG) to train executive function deficits in children with ADHD. The effect of the TVG intervention in combination with stimulants is being investigated to develop a drug-device combination therapy that can address both the dopaminergic dysfunction and executive function deficits present in ADHD. Although the results of this study will be used to guide the clinical development process, additional guidance for the optimization of the executive function training activities will be provided by a computational model of executive functions built with artificial neural networks (ANNs). This model uses ANNs to complete virtual tasks resembling the executive function training activities that the study subjects practice in the Minecraft world, and the schedule of virtual tasks that result in maximum improvements in ANN performance on these tasks will be investigated as a method to inform the selection of training regimens in future clinical studies. This study first proposes the use of recurrent neural networks to model the fluid intelligence executive function. This model is then combined with a previously developed model using convolutional neural networks to model working memory and prepotent impulsivity to produce virtual “subjects” who complete a computational simulation of a Time Management task that requires the use of both of these executive functions to complete. The capability of this model to produce groups of virtual “subjects” with significantly different levels of performance on the Time Management task is demonstrated.
Value Shapes Abstraction During Learning
Authors: Cortese Aurelio , Yamamoto Asuka , Hashemzadeh Maryam , Sepulveda Pradyumna , Kawato Mitsuo , De Martino Benedetto 
Published: October 2020

ABSTRACTThe human brain excels at constructing and using abstractions, such as rules, or concepts. Here, in two fMRI experiments, we demonstrate a mechanism of abstraction built upon the valuation of sensory features. Human volunteers learned novel association rules linking simple visual features. Mixture-of-experts reinforcement learning algorithms revealed that, with learning, high-value abstract representations increasingly guided participants’ behaviour, resulting in better choices and higher subjective confidence. We also found that the brain area computing value signals - the ventromedial prefrontal cortex – prioritized and selected latent task elements during abstraction, both locally and through its connection to the visual cortex. Such coding scheme predicts a causal role for valuation: in a second experiment, we used multivoxel neural reinforcement to test for the causality of feature valuation in the sensory cortex as a mechanism of abstraction. Tagging the neural representation of a task’s feature with rewards evoked abstraction-based decisions. Together, these findings provide a new interpretation of value as a goal-dependent, key factor in forging abstract representations.
Allosteric regulation in CRISPR/Cas1-Cas2 protospacer acquisition mediated by DNA in association with Cas2
Authors: Long Chunhong , Dai Liqiang , E Chao , Da Lin-Tai , Yu Jin 
Published: October 2020

ABSTRACTCas1 and Cas2 are highly conserved proteins across CRISPR-Cas systems and play a significant role in protospacer acquisition. Here we study the protospacer (or ps) DNA binding, recognition, and response to cleavage on the protospacer-adjacent-motif complementary sequence or PAMc by Cas1-Cas2, implementing all-atom molecular dynamics simulations. First, we noticed that two active sites of Cas1&1’ bind asymmetrically to two identical PAMc in the simulation. For psDNA containing only one PAMc to be recognized, it is then found that the non-PAMc association site remains destabilized until after the bound PAMc being cleaved. Thus, correlation appears to exist between the two active sites, which can be allosterically mediated by psDNA and Cas2&2’ in bridging. To substantiate such findings, we further simulated Cas1-Cas2 in complex with synthesized psDNA sequences psL and psH, which have been measured with low and high efficiency in acquisition, respectively. Notably, such inter-site correlation becomes largely enhanced for Cas1-Cas2 in complex with psH, and remains low with psL. Hence, our studies demonstrate that PAMc recognition and cleavage in one active site of Cas1-Cas2 allosterically regulates non-PAMc association/reaction in the other site, and such allosteric regulation is mediated by non-catalytic Cas 2 and DNA protospacer in acquisition.
Father-child dyads exhibit unique inter-subject synchronisation during co-viewing of animation video stimuli
Authors: Azhari Atiqah , Bizzego Andrea , Esposito Gianluca 
Published: October 2020

ABSTRACTInter-subject synchronisation reflects the entrainment of two individuals to each other’s brain signals during passive joint tasks. Within the parent-child dyad, the temporal coordination of signals indicates an attunement to each other’s emotional states. Despite the ubiquity with which parents and their children watch screen media together, no study has investigated intersubject synchronisation in father-child dyads during such a co-viewing activity. The present study examined whether father-child dyads would exhibit unique inter-subject synchronisation during co-viewing of narrative visual scenes that is unique to the dyad and hence would not be observed in control dyads (i.e. randomly paired signals). Hyperscanning fNIRS was used to record the prefrontal cortex (PFC) signals of 29 fathers and their preschool-aged children (11 girls, 18 boys) as each pair engaged in a typical activity of watching children’s shows together. Three 1-min video clips from “Brave”, “Peppa Pig” and “The Incredibles” were presented to each dyad and children’s ratings of video positivity and familiarity were obtained afterwards. PFC activity was analysed according to four clusters: medial left, medial right, frontal left and frontal right clusters. Results from synchrony analyses demonstrated that true father-child dyads showed significantly greater inter-subject synchronisation than control dyads, especially in the medial left cluster during the emotionally arousing conflict scene. Dyads with older fathers displayed less synchrony and older fathers, compared to younger ones, were also found to exhibit greater activity in the frontal right cluster. These findings point to a unique inter-subject synchronisation that exists in father-child relationships during shared co-viewing of narrative scenes which could be potentially modulated by parental age.
Primary cilia formation does not rely on WNT/β-catenin signaling
Authors: Bernatik Ondrej , Paclikova Petra , Kotrbova Anna , Bryja Vitezslav , Cajanek Lukas 
Published: October 2020

Primary cilia act as crucial regulators of embryo development and tissue homeostasis. They are instrumental for modulation of several signaling pathways, including Hedgehog, WNT, and TGF-β. However gaps exist in our understanding of how cilia formation and function is regulated.Recent work has implicated WNT/β-catenin signaling pathway in the regulation of ciliogenesis, yet the results are conflicting. One model suggests that WNT/β-catenin signaling negatively regulates cilia formation, possibly via effects on cell cycle. In contrast second model proposes a positive role of WNT/β-catenin signaling on cilia formation, mediated by the re-arrangement of centriolar satellites in response to phosphorylation of the key component of WNT/β-catenin pathway, β-catenin.To clarify these discrepancies, we investigated possible regulation of primary cilia by the WNT/β-catenin pathway in cell lines (RPE-1, NIH3T3, HEK293) commonly used to study ciliogenesis. We used WNT3a to activate or LGK974 to block the pathway, and examined initiation of ciliogenesis, cilium length, and percentage of ciliated cells. We show that the treatment by WNT3a has no- or lesser inhibitory effect on cilia formation. Importantly, the inhibition of secretion of endogenous WNT ligands using LGK974 blocks WNT signaling but does not affect ciliogenesis. Finally, using knock-out cells for key WNT pathway components, namely DVL1/2/3, LRP5/6 or AXIN1/2 we show that neither activation nor deactivation of the WNT/β-catenin pathway affects the process of ciliogenesis.These results suggest that WNT/β-catenin-mediated signaling is not generally required for efficient cilia formation. In fact, activation of the WNT/β-catenin pathway in some systems seems to moderately suppress ciliogenesis.