bluuebunny/crossref_metadata_2025_split huggingface dataset:
Treatment of Mixed Azo Dyes in an Aerobic Sequential Batch Reactor and Toxicity Assessment using Vigna radiata
Authors: Vidhya T Akshaya , Gayathri K Veena , Kathawala Tasneem M 
Published: July 2019

AbstractAzo dyes are the most widely used dyes in the textile industry due to their stability buttheir redundancy to degradation is of major concern, particularly to aquatic ecosystems.Unbound dye is let out in the effluent which not only adds to pollution but its toxic metabolites are known to be carcinogenic leading to severe cases of disease. Biological degradation and toxicity removal has been shown to be an easy and effective process for treating textile effluents. In the present study, a laboratory scale aerobic sequential batch reactor (SBR) was designed and operated for the analysis of degradation of mixed reactive azo dyes. Biological degradation was carried out by activated sludge process at an alkaline pH (8.5). Reactive Brown, Reactive Black and Reactive Red dyes were used in the study at a concentration of 100, 500 and 1000 mg/L in synthetic waste water. The effect of increasing dye concentration on the decolorization efficiency, COD and BOD removal along with chloride, hardness, TDS, MLSS and MLVSS was monitored. The COD removal increased from 34% to 61.15% and then dropped to 21.16% at the highest used concentration. The BOD removal decreased from 63% to 55.55% to 28.14% with increasing dye concentration. In order to remove the residual dye from the effluent, a biosorption experiment was also conducted using dried activated sludge (DAS). The DAS successfully removed more than 0.300 mg of dyes by absorption within 2 hours. A toxicity assessment was carried out by mean of a phytotoxicity test on Vigna radiate where the percentage of germination was used to detect toxic effects of untreated dye containing wastewater on plant growth. The treated wastewater showed 100% germination compared to 70% in untreated wastewater containing 100 mg/L mixed dyes confirming the efficacy of the treatment.
Evaluation of domain adaptation approaches for robust classification of heterogeneous biological data sets
Authors: Schneider Michael , Wang Lichao , Marr Carsten 
Published: July 2019

AbstractMost machine learning algorithms require that training data are identically distributed to ensure effective learning. In biological studies, however, even small variations in the experimental setup can lead to substantial deviations. Domain adaptation offers tools to deal with this problem. It is particularly useful for cases where only a small amount of training data is available in the domain of interest, while a large amount of training data is available in a different, but relevant domain.We investigated to what extent domain adaptation was able to improve prediction accuracy for complex biological data. To that end, we used simulated data and time-lapse movies of differentiating blood stem cells in different cell cycle stages from multiple experiments and compared three commonly used domain adaptation approaches. EasyAdapt, a simple technique of structured pooling of related data sets, was able to improve accuracy when classifying the simulated data and cell cycle stages from microscopic images. Meanwhile, the technique proved robust to the potential negative impact on the classification accuracy that is common in other techniques that build models with heterogeneous data. Despite its implementation simplicity, EasyAdapt consistently produced more accurate predictions compared to conventional techniques.Domain adaptation is therefore able to substantially reduce the amount of work required to create a large amount of annotated training data in the domain of interest necessary whenever the domain changes even a little, which is common not only in biological experiments, but universally exists in almost all data collection routines.
Community attitudes on genetic research of gender identity, sexual orientation, and mental health
Authors: Thomas Taylor R. , Hofammann Dabney , McKenna Brooke G. , van der Miesen Anna I.R. , Stokes Mark A. , Daniolos Peter , Michaelson Jacob J. 
Published: July 2019

ABSTRACTBiological sex is an important factor in mental health, and a non-binary view of how variation in sex and gender influence mental health represents a new research frontier that may yield new insights. The recent acceleration of research into sexual orientation, gender identity, and mental health has generally been conducted without sufficient understanding of the opinions of sexual and gender minorities (SGM) toward this research. We surveyed 768 individuals, with an enrichment of LGBTQ+ stakeholders, for their opinions regarding genetic research of SGM and mental health. We found that the key predictors of attitudes toward genetic research specifically on SGM are 1) general attitudes toward genetic and mental health research 2) tolerance of SGM and associated behaviors 3) non-cisgender stakeholder status and 4) age of the respondent. Non-heterosexual stakeholder status was significantly associated with increased willingness to participate in genetic research if a biological basis for gender identity were discovered. We also found that non-stakeholders with a low tolerance for SGM indicated their SGM views would be positively updated if science showed a biological basis for their behaviors and identities. These findings represent an important first step in understanding and engaging the LGBTQ+ stakeholder community in the context of genetic research.
TRIBES: A user-friendly pipeline for relatedness detection and disease gene discovery
Authors: Twine Natalie A. , Szul Piotr , Henden Lyndal , McCann Emily P. , Blair Ian P. , Williams Kelly L. , Bauer Denis C. 
Published: July 2019

AbstractSummaryTRIBES is a user-friendly pipeline for relatedness detection in genomic data. TRIBES is the first tool which is both accurate up to 7th degree relatives (e.g. third cousins) and combines essential data processing steps into a single user-friendly pipeline. Furthermore, using a proof-of-principle cohort comprising amyotrophic lateral sclerosis cases with known relationship structures and a known causal mutation in SOD1, we demonstrated that TRIBES can successfully uncover disease susceptibility loci. TRIBES has multiple applications in addition to disease gene mapping, including sample quality control in genome wide association studies and avoiding consanguineous unions in family planning.AvailabilityTRIBES is freely available on GitHub: https://github.com/aehrc/TRIBES/Contactnatalie.twine@csiro.auSupplementary informationXXXX
Independent evolution of polymerization in the Actin ATPase clan regulates hexokinase activity
Authors: Stoddard Patrick R , Lynch Eric M. , Farrell Daniel P. , Justman Quincey A. , Dosey Annie M. , DiMaio Frank , Williams Tom A. , Kollman Justin M. , Murray Andrew W. , Garner Ethan C. 
Published: July 2019

AbstractThe actin protein fold is found in cytoskeletal polymers, chaperones, and various metabolic enzymes. Many actin-fold proteins, like the carbohydrate kinases, do not polymerize. We find that Glk1, aSaccharomyces cerevisiaeglucokinase, forms two-stranded filaments with unique ultrastructure, distinct from that of cytoskeletal polymers. In cells, Glk1 polymerizes upon sugar addition and depolymerizes upon sugar withdrawal. Glk1 polymerization inhibits its enzymatic activity, thus the Glk1 monomer-polymer equilibrium sets a maximum rate of glucose phosphorylation regardless of Glk1 concentration. A mutation eliminating Glk1 polymerization alleviates concentration-dependent enzyme inhibition, causing glucokinase activity to become unconstrained. Polymerization-based regulation of Glk1 activity serves an important functionin vivo: yeast containing non-polymerizing Glk1 are less fit when growing on sugars and more likely to die when refed glucose. Glucokinase polymerization arose within the ascomycete fungi and is conserved across a group of divergent (150-200 mya) yeast. We show that Glk1 polymerization arose independently from other actin-related filaments and allows yeast to rapidly modulate glucokinase activity as nutrient availability changes.One-sentence summaryYeast glucokinase activity is limited by its polymerization, which is critical for cell viability during glucose refeeding.
Impact of Měnglà virus proteins on human and bat innate immune pathways
Authors: Williams Caroline G. , Gibbons Joyce Sweeney , Keiffer Timothy R. , Luthra Priya , Edwards Megan R. , Basler Christopher F. 
Published: July 2019

AbstractMěnglà virus (MLAV), identified inRousettusbats, is a phylogenetically distinct member of the familyFiloviridae. Because filoviruses Ebola virus (EBOV) and Marburg virus (MARV) modulate host innate immune pathways, MLAV VP35, VP40 and VP24 proteins were compared with their EBOV and MARV homologs for innate immune pathway modulation. In human andRousettuscells, MLAV VP35 behaved like EBOV and MARV VP35s, inhibiting virus-induced activation of the interferon (IFN)-β promoter. MLAV VP35 inhibited IRF3 phosphorylation and interacted with PACT, a host protein engaged by EBOV VP35 to inhibit RIG-I signaling. MLAV VP35 also inhibited PKR activation. MLAV VP40 was demonstrated to inhibit type I IFN induced gene expression in human and bat cells. It blocked STAT1 tyrosine phosphorylation induced either by type I IFN or over-expressed Jak1, paralleling MARV VP40. MLAV VP40 also inhibited virus-induced IFNβ promoter activation, a property shared by MARV VP40 and EBOV VP24. The inhibition of IFN induction was preserved in the presence of a Jak kinase inhibitor, demonstrating that inhibition of Jak-STAT signaling is not sufficient to explain inhibition of IFNβ promoter activation. MLAV VP24 did not inhibit IFN-induced gene expression or bind karyopherin α5, properties of EBOV VP24. MLAV VP24 also differed from MARV VP24 in that it failed to interact with Keap1 or activate an antioxidant response element reporter gene, due to the absence of a Keap1-binding motif. These studies demonstrate similarities between MLAV and MARV in how they suppress IFN responses and differences in how MLAV VP24 interacts with host pathways.ImportanceEBOV and MARV, members of the familyFiloviridae, are highly pathogenic zoonotic viruses that cause severe disease in humans. Both viruses use several mechanisms to modulate the host innate immune response, and these likely contribute to severity of disease. Here, we demonstrate that MLAV, a filovirus newly discovered in a bat, suppresses antiviral type I interferon responses in both human and bat cells. Inhibitory activities are possessed by MLAV VP35 and VP40, which parallels how MARV blocks IFN responses. However, whereas MARV activates cellular antioxidant responses through an interaction between its VP24 protein and host protein Keap1, MLAV VP24 lacks a Keap1 binding motif and fails to activate this cytoprotective response. These data indicate that MLAV possesses immune suppressing functions that could facilitate human infection. They also demonstrate key differences in MLAV versus either EBOV or MARV engagement of host signaling pathways.
Exploitation of local and global information in predictive processing
Authors: Kluger Daniel S. , Broers Nico , Roehe Marlen A. , Wurm Moritz F. , Busch Niko A. , Schubotz Ricarda I. 
Published: July 2019

AbstractWhile prediction errors have been established to instigate learning through model adaptation, recent studies have stressed the role of model-compliant events in predictive processing. Specifically, so-called checkpoints have been suggested to be sampled for model evaluation, particularly in uncertain contexts.Using electroencephalography (EEG), the present study aimed to investigate the interplay of such global information and local adjustment cues prompting on-line adjustments of expectations. Within a stream of single digits, participants were to detect ordered sequences (i.e., 3-4-5-6-7) that had a regular length of five digits and were occasionally extended to seven digits. Across experimental blocks, these extensions were either rare (low irreducible uncertainty) or frequent (high uncertainty) and could be unexpected or indicated by incidental colour cues.Exploitation of local cue information was reflected in significant decoding of cues vs non-informative analogues using multivariate pattern classification. Modulation of checkpoint processing as a function of global uncertainty was likewise reflected in significant decoding of high vs low uncertainty checkpoints. In line with previous results, both analyses comprised the P3b time frame as an index of excess model-compliant information sampled from probabilistic events.Accounting for cue information, an N400 component was revealed as the correlate of locally unexpected (vs expected) outcomes, reflecting effortful integration of incongruous information. Finally, we compared the fit of a global model (disregarding local adjustments) and a local model (including local adjustments) using representational similarity analysis (RSA). RSA revealed a better fit for the global model, underscoring the precedence of global reference frames in hierarchical predictive processing.
An ultrasensitive fiveplex activity assay for cellular kinases
Authors: Smolko Christian M. , Janes Kevin A. 
Published: July 2019

ABSTRACTProtein kinases are enzymes whose abundance, protein-protein interactions, and posttranslational modifications together determine net signaling activity in cells. Large-scale data on cellular kinase activity are limited, because existing assays are cumbersome, poorly sensitive, low throughput, and restricted to measuring one kinase at a time. Here, we surmount the conventional hurdles of activity measurement with a multiplexing approach that leverages the selectivity of individual kinase-substrate pairs. We demonstrate proof of concept by designing an assay that jointly measures activity of five pleiotropic signaling kinases: Akt, IκB kinase (IKK), c-jun N-terminal kinase (JNK), mitogen-activated protein kinase (MAPK)-extracellular regulated kinase kinase (MEK), and MAPK-activated protein kinase-2 (MK2). The assay operates in a 96-well format and specifically measures endogenous kinase activation with coefficients of variation less than 20%. Multiplex tracking of kinase-substrate pairs reduces input requirements by 25-fold, with ~75 μg of cellular extract sufficient for fiveplex activity profiling. We applied the assay to monitor kinase signaling during coxsackievirus B3 infection of two different host-cell types and identified multiple differences in pathway dynamics and coordination that warrant future study. Because the Akt–IKK–JNK–MEK–MK2 pathways regulate many important cellular functions, the fiveplex assay should find applications in inflammation, environmental-stress, and cancer research.
Detecting GPCR Complexes in Postmortem Human Brain with Proximity Ligation Assay and A Bayesian Classifier
Authors: Zhu Ying , Mészáros József , Walle Roman , Fan Rongxi , Sun Ziyi , Dwork Andrew J. , Trifilieff Pierre , Javitch Jonathan A. 
Published: July 2019

AbstractDespite the general controversy regarding the existence and physiological relevance of Class A GPCR dimerization, there is substantial evidence for functional interactions between dopamine D2 receptor (D2R) and adenosine A2A receptor (A2AR). A2AR-D2R complexes have been detected in rodent brains by proximity ligation assay (PLA), but their existence in the human brain is yet to be demonstrated. In this study, we used brightfield PLA, combined with a systematic sampling and a parameter-free naïve Bayesian classifier, and demonstrated proximity between D2R and A2AR in the adult human ventral striatum, consistent with their colocalization within complexes and the possible existence of D2R-A2AR heteromers. These methods are applicable to the quantitative analysis of proximity of two proteins and the expression of individual proteins.Method SummaryBrightfield proximity ligation assay (PLA) was used to assess the expression of G protein-coupled receptors and their proximity in postmortem adult human brains. A novel automated machine learning method (Bayesian Optimized PLA Signal Sorting) was developed to automatically quantify brightfield PLA data.
Exploring Perceptual Illusions in Deep Neural Networks
Authors: Ward Emily J. 
Published: July 2019

AbstractPerceptual illusions—discrepancies between what exists externally and what we actually see—reveal a great deal about how the perceptual system functions. Rather than failures of perception, illusions expose automatic computations and biases in visual processing that help make better decisions from visual information to achieve our perceptual goals. Recognizing objects is one such perceptual goal that is shared between humans and certain Deep Convolutional Neural Networks, which can reach human-level performance. Do neural networks trained exclusively for object recognition “perceive” visual illusions, simply as a result of solving this one perceptual problem? Here, I showed four classic illusions to humans and a pre-trained neural network to see if the network exhibits similar perceptual biases. I found that deep neural networks trained exclusively for object recognition exhibit the Müller-Lyer illusion, but not other illusions. This result shows that some perceptual computations that are similar to humans’ may come “for free” in a system with perceptual goals similar to humans’.
Systems-level analysis identifies key regulators driving epileptogenesis in temporal lobe epilepsy
Authors: Fu Yingxue , Guo Zihu , Wu Ziyin , Chen Liyang , Ma Yaohua , Wang Zhenzhong , Xiao Wei , Wang Yonghua 
Published: July 2019

AbstractTemporal lobe epilepsy (TLE) is the most prevalent and often devastating form of epilepsy. The molecular mechanism underlying the development of TLE remains largely unknown, which hinders the discovery of effective anti-epileptogenic drugs. In this study, we built a systems-level analytic framework which integrates gene meta-signatures, gene coexpression network and cellular regulatory network to unveil the evolution landscape of epileptogenic process and to identify key regulators that govern the transition between different epileptogenesis stages. The time-specific hippocampal transcriptomic profiles from five independent rodent TLE models were grouped into acute, latent and chronic stages of epileptogenesis, and were utilized for generating stage-specific gene expression signatures. 13 cell-type specific functional modules were identified from the epilepsy-context coexpression network, and five of them were significantly associated with the entire epileptogenic process. By inferring the differential protein activity of gene regulators in each stage, 265 key regulators underlying epileptogenesis were obtained. Among them, 122 regulators were demonstrated being associated with high seizure frequency and/or hippocampal sclerosis in human TLE patients. Importantly, we discovered four new gene regulators (ANXA5, FAM107A, SEPT2 and SPARC) whose upregulation may drive the process of epileptogenesis and further lead to chronic recurrent seizures or hippocampal sclerosis. Our findings provide a landscape of the gene network dynamics underlying epileptogenesis and uncovered candidate regulators that may serve as potential targets for future anti-epileptogenic therapy development.
Risk of Seizures Induced by Intracranial Research Stimulation: Analysis of 770 Stimulation Sessions
Authors: Goldstein Hannah E. , Smith Elliot H. , Gross Robert E. , Jobst Barbara C. , Lega Bradley C. , Sperling Michael R. , Worrell Gregory A. , Zaghloul Kareem A. , Wanda Paul A. , Kahana Michael J. , Rizzuto Daniel S. , Schevon Catherine A. , McKhann Guy M. , Sheth Sameer A. 
Published: July 2019

AbstractBackgroundPatients with medically refractory epilepsy often undergo intracranial electroencephalography (iEEG) monitoring to identify a seizure focus and determine their candidacy for surgical intervention. This clinically necessary monitoring period provides an increasingly utilized research opportunity to study human neurophysiology, however, ethical concerns demand a thorough appreciation of the associated risks.ObjectiveWe measured the incidence of research stimulation-associated seizures in a large multi-institutional study on brain stimulation’s effect on memory in order to determine if brain stimulation was statistically associated with seizure incidence, and identify potential risk factors for stimulation-associated seizures.Methods188 subjects undergoing iEEG monitoring across 10 institutions participated in 770 research stimulation sessions over 3.5 years. Seizures within 30 minutes of a stimulation session were included in our retrospective analysis. We analyzed stimulation parameters, seizure incidence, and typical seizure patterns, to assess the likelihood that recorded seizures were stimulation-induced, rather than events that occurred by chance in epilepsy patients prone to seizing.ResultsIn total, 14 seizures were included in our analysis. All events were single seizures, and no adverse events occurred. The mean amplitude of seizure-associated stimulation did not differ significantly from the mean amplitude delivered in sessions without seizures.In order to determine the likelihood that seizures were stimulation induced, we used three sets of analyses: Visual iEEG analysis, statistical frequency, and power analyses. We determined that three of the 14 seizures were likely stimulation-induced, five were possibly stimulation-induced, and six were unlikely stimulation-induced. Overall, we estimate a rate of stimulation-induced seizures between 0.39% and 1.82% of sessions.ConclusionsThe rarity of stimulation-associated seizures, and that none added morbidity or affected the clinical course of any patient, are important findings for understanding the feasibility and safety of intracranial stimulation for research purposes.
Mebendazole for Differentiation Therapy of Acute Myeloid Leukemia Identified by a Lineage Maturation Index
Authors: Li Yulin , Thomas Daniel , Deutzmann Anja , Majeti Ravindra , Felsher Dean W. , Dill David L. 
Published: July 2019

AbstractAccurate assessment of changes in cellular differentiation status in response to drug treatments or genetic perturbations is crucial for understanding tumorigenesis and developing novel therapeutics for human cancer. We have developed a novel computational approach, the Lineage Maturation Index (LMI), to define the changes in differentiation state of hematopoietic malignancies based on their gene expression profiles. We have confirmed that the LMI approach can detect known changes of differentiation state in both normal and malignant hematopoietic cells. To discover novel differentiation therapies, we applied this approach to analyze the gene expression profiles of HL-60 leukemia cells treated with a small molecule drug library. Among multiple drugs that significantly increased the LMIs, we identified mebendazole, an anti-helminthic clinically used for decades with no known significant toxicity. We tested the differentiation activity of mebendazole using primary leukemia blast cells isolated from human acute myeloid leukemia (AML) patients. We determined that treatment with mebendazole induces dramatic differentiation of leukemia blast cells as shown by cellular morphology and cell surface markers. Furthermore, mebendazole treatment significantly extended the survival of leukemia-bearing mice in a xenograft model. These findings suggest that mebendazole may be utilized as a low toxicity therapeutic for human acute myeloid leukemia and confirm the LMI approach as a robust tool for the discovery of novel differentiation therapies for cancer.