bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Importance of Individual Beliefs in Assessing Treatment Efficacy: Insights from Neurostimulation Studies
Authors: Fassi Luisa , Hochman Shachar , Daskalakis Zafiris J. , Blumberger Daniel M. , Kadosh Roi Cohen 
Published: December 2020

AbstractIn recent years, there has been debate about the effectiveness of treatments from different fields, such as neurostimulation, neurofeedback, brain training, and pharmacotherapy. This debate has been fuelled by contradictory and nuanced experimental findings. Notably, the effectiveness of a given treatment is commonly evaluated by comparing the effect of the active treatment versus the placebo on human health and/or behaviour. However, this approach neglects the individual’s subjective experience of the type of treatment s/he received in establishing treatment efficacy. Here, we show that individual differences insubjective treatment—the thought of receiving the active or placebo condition during an experiment—can explain variability in outcomes better than the actual treatment. We analysed four independent datasets (N=387 participants), including clinical patients and healthy adults from different age groups who were exposed to different neurostimulation treatments (transcranial magnetic stimulation: Study 1 & 2; transcranial direct current stimulation: Study 3 & 4). Our findings show that the inclusion ofsubjective treatmentcan provide a better model fit, either alone or in interaction withobjective treatment(defined as the condition to which participants are assigned in the experiment). These results demonstrate the significant contribution of subjective experience in explaining the variability of clinical, cognitive and behavioural outcomes. We advocate for existing and future studies in clinical and non-clinical research to start accounting for participants’ subjective beliefs and their interplay with objective treatment when assessing the efficacy of treatments. This approach will be crucial in providing a more accurate estimation of the treatment effect and its source, allowing the development of effective and reproducible interventions.Significance statementWe demonstrate that individual differences insubjective treatment—the belief of receiving the active or placebo condition during an experiment—can explain variability in research outcomes better thanobjective treatment, the actual treatment to which participants are assigned. Even though it is a standard practice for intervention studies to collect data onsubjective treatment, its contribution to research outcomes has been overlooked. By demonstrating the explanatory power ofsubjective treatmentbeyondobjective treatmentin four independent datasets, we show its potential to provide further insights into the effectiveness of different interventions. We, therefore, encourage researchers to adopt our approach in existing and new studies, to improve experimental design and ultimately increase the rigour and robustness of clinical and non-clinical interventions.
Somatic Cell Nuclear Transfer Embryos Show Massive Dysregulation of Genes Involved in Transcription Pathways
Authors: Long Chunshen , Li Hanshuang , Li Xinru , Zuo Yongchun 
Published: December 2020

AbstractTranscription is the most fundamental molecular event that occurs with zygotic genome activation (ZGA) during embryo development. However, the potential association between transcription pathways and low cloning efficiency of nuclear transfer (NT) embryos remains elusive. Here, we integrated a series of RNA-seq data on NT embryos to deciphering the molecular barriers of NT embryo development. Comparative transcriptome analysis indicated that incomplete activation of transcription pathways functions as a barrier for NT embryos. Then, the gene regulatory network (GRN) identified that crucial factors responsible for transcription play a coordinated role in epigenome erasure and pluripotency regulation during normal embryo development. But in NT embryos, massive genes involved in transcription pathways were varying degrees of inhibition. Our study therefore provides new insights into understanding the barriers to NT embryo reprogramming.
Using predictive machine learning models for drug response simulation by calibrating patient-specific pathway signatures
Authors: Khatami Sepehr Golriz , Mubeen Sarah , Bharadhwaj Vinay Srinivas , Kodamullil Alpha Tom , Hofmann-Apitius Martin , Domingo-Fernández Daniel 
Published: December 2020

AbstractThe utility of pathway signatures lies in their capability to determine whether a specific pathway or biological process is dysregulated in a given patient. These signatures have been widely used in machine learning (ML) methods for a variety of applications including precision medicine, drug repurposing, and drug discovery. In this work, we leverage highly predictive ML models for drug response simulation in individual patients by calibrating the pathway activity scores of disease samples. Using these ML models and a novel scoring algorithm to modify the signatures of patients, we evaluate whether a given sample that was formerly classified as diseased, could be predicted as normal following drug treatment simulation. We then use this technique as a proxy for the identification of potential drug candidates. Furthermore, we demonstrate the ability of our methodology to successfully identify approved and clinically investigated drugs for three different cancers. We also show how this approach can deconvolute a drugs’ mechanism of action and propose combination therapies. Taken together, our methodology could be promising to support clinical decision-making in personalized medicine by simulating a drugs’ effect on a given patient.
The cellular architecture of memory modules inDrosophilasupports stochastic input integration
Authors: Hafez Omar A. , Escribano Benjamin , Ziegler Rouven L. , Hirtz Jan J. , Niebur Ernst , Pielage Jan 
Published: December 2020

AbstractThe ability to associate neutral stimuli with valence information and to store these associations as memories forms the basis for decision making. To determine the underlying computational principles, we build a realistic computational model of a central decision module within theDrosophilamushroom body (MB), the fly’s center for learning and memory. Our model combines the electron microscopy-based architecture of one MB output neuron (MBON-α3), the synaptic connectivity of its 948 presynaptic Kenyon cells (KCs), and its membrane properties obtained from patch-clamp recordings. We show that this neuron is electrotonically compact and that synaptic input corresponding to simulated odor input robustly drives its spiking behavior. Therefore, sparse innervation by KCs can efficiently control and modulate MBON activity in response to learning with minimal requirements on the specificity of synaptic localization. This architecture allows efficient storage of large numbers of memories using the flexible stochastic connectivity of the circuit.
Grid cell firing fields in a volumetric space
Authors: Grieves Roddy M. , Jedidi-Ayoub Selim , Mishchanchuk Karyna , Liu Anyi , Renaudineau Sophie , Duvelle Éléonore , Jeffery Kate J. 
Published: December 2020

AbstractWe investigated how entorhinal grid cells represent volumetric (three-dimensional) space. On a flat surface, grid cell firing fields are circular and arranged in a close-packed hexagonal array. In three dimensions, theoretical and computational work suggests that the most efficient configuration would be a regular close packing of spherical fields. We report that in rats exploring a cubic lattice, grid cells were spatially stable and maintained normal directional modulation, theta modulation and spike dynamics. However, while the majority of grid fields were spherical, they were irregularly arranged, even when only fields abutting the lower surface (equivalent to the floor) were considered. Thus, grid organization is shaped by the environment’s movement affordances, and may not need to be regular to support spatial computations.One Sentence SummaryIn rats exploring a volumetric space, grid cells are spatially modulated but their firing fields are irregularly arranged.
Suboptimal human inference inverts the bias-variance trade-off for decisions with asymmetric evidence
Authors: Eissa Tahra L , Gold Joshua I , Josić Krešimir , Kilpatrick Zachary P 
Published: December 2020

AbstractSolutions to challenging inference problems are often subject to a fundamental trade-off between bias (being systematically wrong) that is minimized with complex inference strategies and variance (being oversensitive to uncertain observations) that is minimized with simple inference strategies. However, this trade-off is based on the assumption that the strategies being considered are optimal for their given complexity and thus has unclear relevance to the frequently suboptimal inference strategies used by humans. We examined inference problems involving rare, asymmetrically available evidence, which a large population of human subjects solved using a diverse set of strategies that were suboptimal relative to the Bayesian ideal observer. These suboptimal strategies reflected an inversion of the classic bias-variance trade-off: subjects who used more complex, but imperfect, Bayesian-like strategies tended to have lower variance but high bias because of incorrect tuning to latent task features, whereas subjects who used simpler heuristic strategies tended to have higher variance because they operated more directly on the observed samples but displayed weaker, near-normative bias. Our results yield new insights into the principles that govern individual differences in behavior that depends on rare-event inference, and, more generally, about the information-processing trade-offs that are sensitive to not just the complexity, but also the optimality of the inference process.
A Budding Yeast Model for Human Disease Mutations in theEXOSC2Cap Subunit of the RNA Exosome
Authors: Sterrett Maria C. , Enyenihi Liz , Leung Sara W. , Hess Laurie , Strassler Sarah E. , Farchi Daniela , Lee Richard S. , Withers Elise S. , Kremsky Isaac , Baker Richard E. , Basrai Munira A. , van Hoof Ambro , Fasken Milo B. , Corbett Anita H. 
Published: December 2020

AbstractRNA exosomopathies, a growing family of tissue-specific diseases, are linked to missense mutations in genes encoding the structural subunits of the conserved 10-subunit exoribonuclease complex, the RNA exosome. Such mutations in the cap subunit geneEXOSC2cause the novel syndrome SHRF (Short stature,Hearing loss,Retinitis pigmentosa and distinctiveFacies). In contrast, exosomopathy mutations in the cap subunit geneEXOSC3cause pontocerebellar hypoplasia type 1b (PCH1b). Though having strikingly different disease pathologies,EXOSC2andEXOSC3exosomopathy mutations result in amino acid substitutions in similar, conserved domains of the cap subunits, suggesting that these exosomopathy mutations have distinct consequences for RNA exosome function. We generated the firstin vivomodel of the SHRF pathogenic amino acid substitutions using budding yeast by introducing theEXOSC2mutations in the orthologousS. cerevisiaegeneRRP4. The resultingrrp4mutant cells have defects in cell growth and RNA exosome function. We detect significant transcriptomic changes in both coding and non-coding RNAs in therrp4variant,rrp4-G226D, which modelsEXOSC2p.Gly198Asp. Comparing thisrrp4-G226Dmutant to the previously studiedS. cerevisiaemodel ofEXOSC3PCH1b mutation,rrp40-W195R, reveals that these mutants have disparate effects on certain RNA targets, providing the first evidence for different mechanistic consequences of these exosomopathy mutations. Congruently, we detect specific negative genetic interactions between RNA exosome cofactor mutants andrrp4-G226Dbut notrrp40-W195R. These data provide insight into how SHRF mutations could alter the function of the RNA exosome and allow the first direct comparison of exosomopathy mutations that cause distinct pathologies.
Scientific publications and COVID-19 “research pivots” during the pandemic: An initial bibliometric analysis
Authors: Shapira Philip 
Published: December 2020

AbstractAn examination is presented of scientific research publication trends during the global coronavirus (COVID-19) pandemic in 2020. After reviewing the timing of the emergence of the pandemic in 2020 and the growth of governmental responses, available secondary sources are used to highlight impacts of COVID-19 on scientific research. A bibliometric analysis is then undertaken to analyze developments in COVID-19 related scientific publications through to October of 2020 by broad trends, fields, countries, and organizations. Two publication data sources are used: PubMed and the Web of Science.While there has been a massive absolute increase in PubMed and Web of Science papers directly focused on COVID-19 topics, especially in medical, biological science, and public health fields, this is still a relatively small proportion of publication outputs across all fields of science. Using Web of Science publication data, the paper examines the extent to which researchers across all fields of science have pivoted their research outputs to focus on topics related to COVID-19. A COVID-19 research pivot is defined as the extent to which the proportion of output in a particular research field has shifted to a focus on COVID-19 topics in 2020 (to date) compared with 2019. Significant variations are found by specific fields (identified by Web of Science Subject Categories). In a top quintile of fields, not only in medical specialties, biomedical sciences, and public health but also in subjects in social sciences and arts and humanities, there are relatively high to medium research pivots. In lower quintiles, including other subjects in science, social science, and arts and humanities, low to zero COVID-19 research pivoting is identified.In a new Appendix to the paper, an updated analysis is provided through to mid-April 2022.CitationShapira, P. “Scientific publications and COVID-19 “research pivots” during the pandemic: An initial bibliometric analysis,”bioRxiv2020.12.06.413682; doi:https://doi.org/10.1101/2020.12.06.413682Version NotesVersion 1: Original paper, completed on December 6, 2020; posted atbioRxivon December 7, 2020.Version 2: Minor grammar items corrected.Version 3: Updated bibliometric analysis through to mid-April 2022 added on April 29, 2022, as new Appendix 2.
MCOLN1gene-replacement therapy corrects neurologic dysfunction in the mouse model of mucolipidosis IV
Authors: DeRosa Samantha , Salani Monica , Smith Sierra , Sangster Madison , Miller-Browne Victoria , Wassmer Sarah , Xiao Ru , Vandenberghe Luk , Slaugenhaupt Susan , Misko Albert , Grishchuk Yulia 
Published: December 2020

AbstractMucolipidosis IV (MLIV, OMIM 252650) is an orphan disease leading to debilitating psychomotor deficits and vision loss. It is caused by loss-of-function mutations in theMCOLN1gene that encodes thethe lysosomal transient receptor potential channel mucolipin 1 (TRPML1). With no existing therapy, the unmet need in this disease is very high. Here we show that AAV-mediated gene transfer of the humanMCOLN1gene rescues motor function and alleviates brain pathology in theMcoln1−/−MLIV mouse model. Using the AAV-PHP.b vector for initial proof-of-principle experiments in symptomatic mice, we showed long-term reversal of declined motor function and significant delay of paralysis. Next, we designed self-complimentary AAV9 vector for clinical use and showed that its intracerebroventricular administration in post-natal day 1 mice significantly improved motor function and myelination and reduced lysosomal storage load in the MLIV mouse brain. We also showed that CNS targeted gene transfer is necessary to achieve therapeutic efficacy in this disease. Based on our data and general advancements in the gene therapy field, we propose scAAV9-mediated CSF-targetedMCOLN1gene transfer as a therapeutic strategy in MLIV.
Distinctive functional regime of endogenous lncRNAs in dark regions of human genome
Authors: Wang Anyou , Hai Rong 
Published: December 2020

AbstractEukaryotic genomes gradually gain noncoding regions when advancing evolution and human genome actively transcribes >90% of its noncoding regions1, suggesting their criticality in evolutionary human genome. Yet <1% of them have been functionally characterized2, leaving most human genome in dark. Here we systematically decode endogenous lncRNAs located in unannotated regions of human genome and decipher a distinctive functional regime of lncRNAs hidden in massive RNAseq data. LncRNAs divergently distribute across chromosomes, independent of protein-coding regions. Their transcriptions barely initiate on promoters through polymerase II, but mostly on enhancers. Yet conventional enhancer activators(e.g. H3K4me1) only account for a small proportion of lncRNA activation, suggesting alternatively unknown mechanisms initiating the majority of lncRNAs. Meanwhile, lncRNA-self regulation also notably contributes to lncRNA activation. LncRNAs trans-regulate broad bioprocesses, including transcription and RNA processing, cell cycle, respiration, response to stress, chromatin organization, post-translational modification, and development. Overall lncRNAs govern their owned regime distinctive from protein’s.
Cannabinoids modulate food preference and consumption inDrosophila melanogaster
Authors: He Jianzheng , Xien Tan Alice Mei , Ng Si Yun , Yu Fengwei 
Published: December 2020

AbstractCannabinoids have an important role in regulating feeding behaviors via cannabinoid receptors in mammals. Cannabinoids also exhibit potential therapeutic functions inDrosophila melanogaster, or fruit fly that lacks cannabinoid receptors. However, it remains unclear whether cannabinoids affect food consumption and metabolism in a cannabinoid receptors-independent manner in flies. In this study, we systematically investigated pharmacological functions of various cannabinoids in modulating food preference and consumption in flies. We show that flies display preferences for consuming cannabinoids, independent of their sensory functions. Interestingly, phyto- and endo- cannabinoids exhibit an inhibitory effect on food intake. Unexpectedly, the non-selective CB1 receptor antagonist AM251 attenuates the suppression of food intake by endocannabinoids. Moreover, the endocannabinoid anandamide (AEA) and its metabolite inhibit food intake and promote resistance to starvation, possibly through reduced lipid metabolism. Thus, this study has provided insights into a pharmacological role of cannabinoids in feeding behaviors using an adultDrosophilamodel.
Mechanistic basis for ubiquitin modulation of a protein energy landscape
Authors: Carroll Emma C. , Latorraca Naomi R. , Lindner Johanna M. , Maguire Brendan C. , Pelton Jeff G. , Marqusee Susan 
Published: December 2020

AbstractUbiquitin is a common posttranslational modification canonically associated with targeting proteins to the 26S proteasome for degradation and also plays a role in numerous other non-degradative cellular processes. Ubiquitination at certain sites destabilizes the substrate protein, with consequences for proteasomal processing, while ubiquitination at other sites has little energetic effect. How this site specificity—and, by extension, the myriad effects of ubiquitination on substrate proteins—arises remains unknown. Here, we systematically characterize the atomic-level effects of ubiquitination at various sites on a model protein, barstar, using a combination of NMR, hydrogen-deuterium exchange mass spectrometry, and molecular dynamics simulation. We find that, regardless of the site of modification, ubiquitination does not induce large structural rearrangements in the substrate. Destabilizing modifications, however, increase fluctuations from the native state resulting in exposure of the substrate’s C terminus. Both of the sites occur in regions of barstar with relatively high conformational flexibility. Destabilization, however, appears to occur through different thermodynamic mechanisms, involving a reduction in entropy in one case and a loss in enthalpy in another. By contrast, ubiquitination at a non-destabilizing site protects the substrate C terminus through intermittent formation of a structural motif with the last three residues of ubiquitin. Thus, the biophysical effects of ubiquitination at a given site depend greatly on local context. Taken together, our results reveal how a single post-translational modification can generate a broad array of distinct effects, providing a framework to guide the design of proteins and therapeutics with desired degradation and quality-control properties. (248 words)Significance StatementFluctuations on a protein energy landscapes encode the mechanistic basis for vital biological processes not always evident from static structures alone. Ubiquitination, a key posttranslational modification, can affect a protein’s energy landscape with consequences for proteasomal degradation, but the molecular mechanisms driving ubiquitin-induced energetic changes remain elusive. Here, we systematically characterize the energetic effects of ubiquitination at three sites on a model protein. We find that distinct thermodynamic mechanisms can produce the same outcome of ubiquitin-induced destabilization at sensitive sites. At a non-sensitive site, we observe formation of a substrate–ubiquitin interaction that may serve to protect against destabilization. This work will enable development of predictive models of the effect of ubiquitin at any given site on a protein with implications for understanding and engineering regulated ubiquitin signaling and protein quality control in vivo.
Basis for the phototaxis sign reversal in the green algaChlamydomonas reinhardtiistudied by high-speed observation
Authors: Nakajima Masako , Iizuka Kosuke , Takahashi Rina , Ueki Noriko , Isu Atsuko , Yoshimura Kenjiro , Nakagaki Toshiyuki , Hisabori Toru , Sato Katsuhiko , Wakabayashi Ken-ichi 
Published: December 2020

ABSTRACTFor organisms that respond to environmental stimuli using taxes, reversal of the tactic sign should be tightly regulated for survival. The biciliate green algaChlamydomonas reinhardtiiis an excellent model for studying reversal between positive and negative phototaxis.C. reinhardtiicells change swimming direction by modulating the balance of beating forces between their two cilia after photoreception at the eyespot; however, it remains unknown how they reverse phototactic sign. In this study, we observed cells undergoing phototactic turns with a high-speed camera and found that two key factors determine the phototactic sign: which of the two cilia beats more strongly for phototactic turning and when the strong beating starts. The timing of the strong ciliary beating is suggested to be regulated by ROS-regulated switching between the light-on and light-off responses at the eyespot, which leads to the switching between positive and negative phototaxis. This idea is supported by a mathematical model that introduces the timing of the strong ciliary beating after photoreception.