bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mass photometric detection and quantification of nanoscale α-synuclein phase separation
Authors: Ray Soumik , Mason Thomas O. , Boyens-Thiele Lars , Jahnke Nadin , Buell Alexander K. 
Published: May 2022

Abstractα-Synuclein (α-Syn) liquid-liquid phase separation (LLPS) leads to irreversible amyloid fibril formation associated with Parkinson’s disease pathogenesis. Critical concentrations of α-Syn LLPS are relatively high under physiological solution conditions. Moreover, α-Syn exhibits delayed LLPS kinetics under certain conditions which deviates from the behaviour predicted by classical homogeneous nucleation theory. In the current body of work, using interferometric light scattering (iSCAT), also known as mass photometry, we experimentally probe that α-Syn can form nanoscale phase separated assemblies/clusters, containing tens to hundreds of molecules— both above and below the critical LLPS concentration down to physiologically relevant scales. The formation of these clusters is instantaneous, even under conditions where the formation of microscopically visible droplets takes several days. However, they account for a very small volume fraction below saturation concentration. The slow growth of the nanoclusters can be attributed to a kinetic barrier which can be overcome by increasing the solution temperature to just below the droplet melting point. We provide reasons for caution in quantifying dilute phase concentrations for α-Syn LLPS samples containing nanoscale droplets—which can only be separated using ultracentrifugation. In addition, we also delineate that the presence of certain surfaces facilitates α-Syn droplet nucleation under conditions of delayed kinetics but is not a mandatory prerequisite for nanocluster formation. Taken together, our findings reveal that phase separation of α-Syn occurs at a wider range of solution conditions than predicted so far and provides an important step towards understanding α-Syn LLPS within physiological scales.Abstract Figure
Quantum CART(qCART), apiggyBac-basedsystem for development and production of virus-free multiplex CAR-T cell therapy
Authors: Chen Yi-Chun , Hua Wei-Kai , Hsu Jeff C. , Chang Peter S. , Wen Kuo-Lan Karen , Huang Yi-Wun , Tsai Jui-Cheng , Kao Yi-Hsin , Wu Pei-Hua , Wang Po-Nan , Chen Ke-Fan , Liao Wan-Ting , Wu Sareina Chiung-Yuan 
Published: May 2022

AbstractChimeric antigen receptor T (CAR-T) cell therapy has the potential to transform cancer treatment. However, CAR-T therapy application is currently limited to certain types of relapsed/refractory B cell lymphomas. To unlock the full potential of CAR-T therapy, technologic breakthroughs will be needed in multiple areas, including optimization of autologous CAR-T development, shortening the innovation cycle, and further manufacturing advancement of next-generation CAR-T therapies. Here, we established a simple and robust virus-free multiplexQuantum CART™system that seamlessly and synergistically integrates four platforms: 1.GTailor™for rapid identification of lead CAR construct design, 2.Quantum Nufect™for effective but gentle electroporation-based gene delivery, 3.Quantum pBac™, featuring a virus-free transposon-based vector with large payload capacity and integration profile similar to retrovirus, and 4.iCellar™for robust and high-quality CAR+T memory stem cell expansion. This robust, virus-free multiplexQuantum CART™system is expected to unleash the full potential of CAR-T therapy for treating diseases.
Neurotransmitter content heterogeneity within an interneuron class shapes inhibitory transmission at a central synapse
Authors: Dumontier Dimitri , Mailhes-Hamon Caroline , Supplisson Stéphane , Dieudonné Stéphane 
Published: May 2022

AbstractNeurotransmitter content is deemed the most basic defining criterion for neuronal classes, contrasting with the intercellular heterogeneity of many other molecular and functional features. Here we show, in the adult mouse brain, that neurotransmitter content variegation within a neuronal class is a component of its functional heterogeneity. Most Golgi cells (GoCs), the well-defined class of cerebellar interneurons inhibiting granule cells (GrCs), contain cytosolic glycine, accumulated by the neuronal transporter GlyT2, and GABA in various proportions. To assess the functional consequence of this neurotransmitter variation, we paired GrCs recordings with optogenetic stimulations of single GoCs, which preserve the intracellular transmitter mixture. We show that the strength and decay kinetics of GrCs IPSCs, which are entirely mediated by GABAA receptors are negatively correlated to the presynaptic expression of GlyT2 by GoCs. We isolate a slow spillover component of GrCs inhibition that is also affected by the expression of GlyT2, leading to a 56 % decrease in relative charge. Acute manipulations of cytosolic GABA and glycine supply recapitulate the modulation of IPSC charge, supporting the hypothesis that presynaptic loading of glycine negatively impact the GABAergic transmission in mixed interneurons through a competition for vesicular filling. Our results suggest that heterogeneity of neurotransmitter supply within the GoC class may provide a presynaptic mechanism to tune the gain of the stereotypic granular layer microcircuit, thereby expanding the realm of possible dynamic behavior.
Cell detoxification of secondary metabolites by P4-ATPase mediated vesicle transport
Authors: Li Yujie , Ren Hui , Wang Fanlong , Chen Jianjun , Ma Lian , Chen Yang , Li Xianbi , Fan Yanhua , Jin Dan , Hou Lei , Zhou Yonghong , Keyhani Nemat O. , Pei Yan 
Published: May 2022

AbstractMechanisms for cellular detoxification of drug compounds are of significant interest in human health. Cyclosporine A (CsA) and tacrolimus (FK506) are widely known antifungal and immunosuppressive microbial natural products. However, both compounds can result in significant side effects when used as immunosuppressants. The insect pathogenic fungusBeauveria bassianashows resistance to CsA and FK506. However, the mechanisms underlying the resistance have remained unknown. Here, we identify a P4-ATPase gene,BbCRPA, from the fungus, which confers resistanceviaa unique vesicle mediated transport pathway that targets the compounds into detoxifying vacuoles. Interestingly, the expression ofBbCRPAin plants promotes resistance to the phytopathogenic fungusVerticillium dahliae viadetoxification of the mycotoxin cinnamyl acetate using a similar pathway. Our data reveal a new function for a subclass of P4-ATPases in cell detoxification. The P4-ATPases conferred cross-species resistance can be exploited for plant disease control and human health protection.
Regional context for balancing sagebrush- and woodland-dependent songbird needs with targeted pinyon-juniper management in the sagebrush biome
Authors: Tack Jason D. , Smith Joseph T. , Doherty Kevin E. , Donnelly Patrick J. , Maestas Jeremy D. , Allred Brady W. , Reinhardt Jason , Morford Scott L. , Naugle David E. 
Published: May 2022

AbstractTree expansion among historic grassland and shrubland systems is a global phenomenon, which results in dramatic influences on ecosystem processes and wildlife populations. In the western US, pinyon-juniper woodlands have expanded by as much as six-fold among sagebrush steppe landscapes since the late nineteenth century, with demonstrated negative impacts to the behavior, demography, and population dynamics of species that rely on intact sagebrush rangelands. Notably, greater sage-grouse (Centrocercus urophasianus) are unable to tolerate even low conifer cover, which can result in population declines and local extirpation. Removing expanding conifer cover has been demonstrated to increase sage grouse population growth rates and sagebrush-obligate songbird abundance. However, advances in restoring sagebrush habitats have been met with concern about unintended impacts to species that rely on conifer woodlands, notably the pinyon jay (Gymnorhinus cyanocephalus) whose population declines are distinctive among birds breeding in pinyon-juniper woodlands. We modeled indices to abundance in relation to multi-scale habitat features for nine songbirds reliant on both sagebrush and pinyon-juniper woodlands for breeding. Findings demonstrate that targeted sage grouse habitat restoration under the Sage Grouse Initiative is not at odds with protection of pinyon jay populations. Rather, conifer management has largely occurred in the northern sagebrush ecosystem where models suggest that past cuts likely benefit Brewer’s sparrow and sage thrasher while avoiding pinyon jay habitat. Extending our spatial modeling further south beyond the sagebrush biome could better equip conservationists with more comprehensive decision-support, particularly where pinyon jays face additional pressures of drought-induced tree mortality.
The Colon Mucosal Sialylglycome Is Redox-Regulated by the Golgi Enzyme QSOX1
Authors: Ilani Tal , Reznik Nava , Yeshaya Noa , Feldman Tal , Vilela Patrick , Lansky Zipora , Javitt Gabriel , Shemesh Michal , Brenner Ori , Elkis Yoav , Varsano Neta , Murray Nathan , Azadi Parastoo , Jaramillo Ana M. , Evans Christopher M. , Fass Deborah 
Published: May 2022

AbstractMucus shields the intestinal epithelium from pathogens and provides a supportive environment for commensal bacteria. Mucus is composed of enormous, heavily glycosylated proteins called mucins, which become disulfide crosslinked in a multi-step biosynthetic pathway culminating in the Golgi apparatus and secretory granules of goblet cells. We observed that knockout mice lacking the Golgi-localized disulfide catalyst QSOX1 produced poorly protective colon mucus, were hypersensitive to induced colitis, and had an altered microbiome. The initial hypothesis arising from these observations was that QSOX1 catalyzes disulfide crosslinking of mucins. Contrary to this hypothesis, the disulfide-mediated polymerization of mucins and related glycoproteins proceeded normally without QSOX1. Instead, we found that QSOX1 forms regulatory disulfides in Golgi glycosyltransferases and thereby promotes effective sialylation of the colon glycome. Our findings reveal that enzymatic control of Golgi redox state impacts glycan elaboration in goblet cells, and that this pathway is crucial for maintaining mucosal function.
Right inferior frontal cortex damage impairs the initiation of inhibitory control, but not its implementation
Authors: Choo Yoojeong , Matzke Dora , Bowren Mark D. , Tranel Daniel , Wessel Jan R. 
Published: May 2022

AbstractInhibitory control is one of the most important control functions in the human brain. Much of our understanding of its neural basis comes from seminal work showing that lesions to the right inferior frontal cortex (rIFC) increase stop-signal reaction time (SSRT), a latent variable that expresses the speed of inhibitory control. However, recent work has identified substantial limitations of the SSRT method. Notably, SSRT is confounded by trigger failures: stop-signal trials in which inhibitory control was never initiated. Such trials inflate SSRT, but are typically indicative of attentional, rather than inhibitory deficits. Here, we used hierarchical Bayesian modeling to identify stop-signal trigger failures in human rIFC lesion patients, non-rIFC lesion patients, and healthy comparisons. Furthermore, we measured scalp-EEG to detect β-bursts, a neurophysiological index of inhibitory control. rIFC lesion patients showed a more than five-fold increase in trigger failure trials and did not exhibit the typical increase of stop-related frontal β- bursts. However, on trials in which such β-bursts did occur, rIFC patients showed the typical subsequent upregulation of β over sensorimotor areas, indicating that their ability to implement inhibitory control, once triggered, is intact. These findings suggest that the role of rIFC in inhibitory control has to be fundamentally reinterpreted.
Describing Inhibitor Specificity for the Amino Acid Transporter LAT1 from Metainference Simulations
Authors: Hutchinson Keino , Silva Dina Buitrago , Bohlke Joshua , Clausen Chase , Thomas Allen A. , Bonomi Massimiliano , Schlessinger Avner 
Published: May 2022

ABSTRACTThe human L-type amino acid transporter 1 (LAT1; SLC7A5) is a membrane transporter of amino acids, thyroid hormones, and drugs such as the Parkinson’s disease drug L-Dopa. LAT1 is found in the blood-brain-barrier (BBB), testis, bone marrow, and placenta, and its dysregulation has been associated with various neurological diseases such as autism and epilepsy as well as cancer. In this study, we combine metainference molecular dynamics (MD) simulations, molecular docking, and experimental testing, to characterize LAT1-inhibitor interactions. We first conducted a series of molecular docking experiments to identify the most relevant interactions between LAT1’s substrate binding site and ligan ds, including both inhibitors and substrates. We then performed metainference MD simulations using cryo-EM structures in different conformations of LAT1 with the electron density map as a spatial restraint, to explore the inherent heterogeneity in the structures. We analyzed the LAT1 substrate binding site to map important LAT1-ligand interactions as well as newly described druggable pockets. Finally, this analysis guided the discovery of previously unknown LAT1 ligands using virtual screening and cellular uptake experiments. Our results improve our understanding of LAT1-inhibitor recognition, providing a framework for rational design of future lead compounds targeting this key drug target.Statement of SignificanceLAT1 is a membrane transporter of amino acids, thyroid hormones, and therapeutic drugs, that is primarily found in the BBB and placenta, as well as in tumor cells of several cancer types. We combine metainference MD simulations, molecular docking, and experimental testing, to characterize LAT1-inhibitor interactions. Our computational analysis predicts S66, G67, F252, G255, Y259, W405 are critical residues for inhibitor binding and druggable sub-pockets in the outward-occluded conformation that are ideal for LAT1 inhibitor discovery. Using virtual screening and functional testing, we discovered multiple LAT1 inhibitors with diverse scaffolds and binding modes. Our results improve our understanding of LAT1’s structure and function, providing a framework for development of future therapeutics targeting LAT1 and other SLC transporters.
HSP90-CDC37-PP5 forms a structural platform for kinase dephosphorylation
Authors: Oberoi Jasmeen , Aran-Guiu Xavi , Outwin Emily A. , Schellenberger Pascale , Roumeliotis Theodoros I. , Choudhary Jyoti S. , Pearl Laurence H. 
Published: May 2022

ABSTRACTActivation of client protein kinases by the HSP90 molecular chaperone system is affected by phosphorylation at multiple sites on HSP90, on the kinase specific co-chaperone CDC37, and the kinase client itself. Removal of regulatory phosphorylation from client kinases and their release from the HSP90-CDC37 system depends on a Ser/Thr phosphatase PP5, which associates with HSP90 via its N-terminal TPR domain. Here we present the cryoEM structure of the oncogenic protein kinase client BRAFV600E bound to HSP90-CDC37, showing how the V600E mutation favours BRAF association with HSP90-CDC37. Structures of HSP90-CDC37-BRAFV600E complexes with PP5, in autoinhibited and activated conformations, together with proteomic analysis of its phosphatase activity, reveal how PP5 is activated by recruitment to HSP90 complexes to comprehensively dephosphorylate client proteins.
Principled feature attribution for unsupervised gene expression analysis
Authors: Janizek Joseph D. , Spiro Anna , Celik Safiye , Blue Ben W. , Russell Josh C. , Lee Ting-I , Kaeberlin Matt , Lee Su-In 
Published: May 2022

AbstractAs interest in unsupervised deep learning models for the analysis of gene expression data has grown, an increasing number of methods have been developed to make these deep learning models more interpretable. These methods can be separated into two groups: (1)post hocanalyses of black box models through feature attribution methods and (2) approaches to build inherently interpretable models through biologically-constrained architectures. In this work, we argue that these approaches are not mutually exclusive, but can in fact be usefully combined. We propose a novel unsupervised pathway attribution method, which better identifies major sources of transcriptomic variation than prior methods when combined with biologically-constrained neural network models. We demonstrate how principled feature attributions aid in the analysis of a variety of single cell datasets. Finally, we apply our approach to a large dataset of post-mortem brain samples from patients with Alzheimer’s disease, and show that it identifies Mitochondrial Respiratory Complex I as an important factor in this disease.
A model of decentralized vision in the sea urchinDiadema africanum
Authors: Li Tianshu , Kirwan John , Arnone Maria Ina , Nilsson Dan-Eric , La Camera Giancarlo 
Published: May 2022

AbstractSea urchins can detect light and move in relation to luminous stimuli despite lacking eyes. They presumably detect light through photoreceptor cells distributed on their body surface. However, there is currently no mechanistic explanation of how these animals can process light to detect visual stimuli and produce oriented movement. Here, we present a model of decentralized vision in echinoderms that includes all known processing stages, from photoreceptor cells to radial nerve neurons to neurons contained in the oral nerve ring encircling the mouth of the animals. In the model, light stimuli captured by photoreceptor cells produce neural activity in the radial nerve neurons. In turn, neural activity in the radial nerves is integrated in the oral nerve ring to produce a profile of neural activity reaching spatially across several ambulacra. This neural activity is read out to produce a model of movement. The model captures previously published data on the behavior of sea urchinDiadema africanumprobed with a variety of physical stimuli. The specific pattern of neural connections used in the model makes testable predictions on the properties of single neurons and aggregate neural behavior inDiadema africanumand other echinoderms, offering a potential understanding of the mechanism of visual orientation in these animals.
Selection and validation of reference genes for quantitative real-time polymerase chain reaction in Serratia ureilytica DW2
Authors: Bai Fenglin , Bai Bianxia , Jin Tingting , Zhang Guiping , Ren Jiahong 
Published: May 2022

AbstractSerratia ureilytica DW2 is a highly efficient phosphate-solubilizing bacterium isolated from Codonopsis pilosula rhizosphere soil that can promote the growth of C. pilosula. However, no validated reference genes from the genus Serratia for use in quantitative real-time polymerase chain reaction (RT–qPCR) normalization have been reported. To screen stable reference genes in S. ureilytica DW2, the expression of eight candidate reference genes (16S rRNA, ftsZ, ftsA, mreB, recA, slyD, thiC, and zipA) under different treatment conditions (pH, temperature, culture time, and salt content) was assayed by RT–qPCR. The expression stability of these genes was analyzed with different algorithms (geNorm, NormFinder, and BestKeeper). To verify the reliability of the data, the most stably expressed reference gene was used to quantify expression of the glucose dehydrogenase (gdh) gene under different soluble phosphate levels. The results showed that the zipA and 16S rRNA genes were the most stable reference genes, and the least stable were thiC and recA. The expression of gdh was consistent with the phosphate solubilization ability on plates containing National Botanical Research Institute phosphate (NBRIP) growth medium. Therefore, this study provides a stable and reliable reference gene for Serratia, which is vital for the accurate quantification of functional gene expression in future studies.
On the economic evaluation of online learning in higher education during the COVID-19 pandemic: a willingness-to-accept approach
Authors: del Saz-Salazar Salvador , Gil-Pareja Salvador , García-Grande María José 
Published: May 2022

Purpose
This study, using a contingent valuation approach, aims to shed light on the economic evaluation of online learning during the first wave of the pandemic.

Design/methodology/approach
A sample of 959 higher education students was asked about their willingness-to-accept (WTA) a monetary compensation for the loss of well-being resulting from the unexpected and mandatory transition to the online space. In explaining WTA determinants, the authors test the appropriateness of the double-hurdle model against the alternative of a Tobit model and find that the factors affecting the participation decision are not the same as those that affect the quantity decision.

Findings
Results show that a vast majority of the respondents think that the abrupt transition to online learning is detrimental to them, while those willing to accept a monetary compensation account for 77% of the sample, being the mean WTA between €448 and €595. As expected, WTA decreases with income and age, and it increases if some member of the family unit is unemployed. By aggregating the mean WTA by the population affected, total loss of well-being is obtained.

Originality/value
To the best of the authors’ knowledge, to date, this method has not been used to value online learning in a WTA framework, much less in the particular context of the pandemic. Thus, based on the understanding that the economic evaluation of online learning could be very useful in providing guidance for decision-making, this paper contributes to the literature on the economic evaluation of higher education.
Semisupervised fault diagnosis of aeroengine based on denoising autoencoder and deep belief network
Authors: Lv Defeng , Wang Huawei , Che Changchang 
Published: May 2022

Purpose
The purpose of this study is to analyze the intelligent semisupervised fault diagnosis method of aeroengine.

Design/methodology/approach
A semisupervised fault diagnosis method based on denoising autoencoder (DAE) and deep belief network (DBN) is proposed for aeroengine. Multiple state parameters of aeroengine with long time series are processed to form high-dimensional fault samples and corresponding fault types are taken as sample labels. DAE is applied for unsupervised learning of fault samples, so as to achieve denoised dimension-reduction features. Subsequently, the extracted features and sample labels are put into DBN for supervised learning. Thus, the semisupervised fault diagnosis of aeroengine can be achieved by the combination of unsupervised learning and supervised learning.

Findings
The JT9D aeroengine data set and simulated aeroengine data set are applied to test the effectiveness of the proposed method. The result shows that the semisupervised fault diagnosis method of aeroengine based on DAE and DBN has great robustness and can maintain high accuracy of fault diagnosis under noise interference. Compared with other traditional models and separate deep learning model, the proposed method also has lower error and higher accuracy of fault diagnosis.

Originality/value
Multiple state parameters with long time series are processed to form high-dimensional fault samples. As a typical unsupervised learning, DAE is used to denoise the fault samples and extract dimension-reduction features for future deep learning. Based on supervised learning, DBN is applied to process the extracted features and fault diagnosis of aeroengine with multiple state parameters can be achieved through the pretraining and reverse fine-tuning of restricted Boltzmann machines.