bluuebunny/crossref_metadata_2025_split huggingface dataset:
How to design optimal eDNA sampling strategies for biomonitoring in river networks
Authors: Carraro Luca , Stauffer Julian B. , Altermatt Florian 
Published: May 2020

AbstractThe current biodiversity crisis calls for appropriate and timely methods to assess state and change of bio-diversity. In this respect, environmental DNA (eDNA) is a highly promising tool, especially for aquatic ecosystems. While initial eDNA studies assessed biodiversity at a few sites, technology now allows analyses of samples from many points at a time. However, the selection of these sites has been mostly motivated on an ad-hoc basis, and it is unclear where to position sampling sites in a river network to most effectively sample biodiversity. To this end, hydrology-based models might offer a unique guidance on where to sample eDNA to reconstruct the spatial patterns of taxon density based on eDNA data collected across a watershed.Here, we performed computer simulations to identify best-practice criteria for the choice of positioning of eDNA sampling sites in river networks. To do so, we combined a hydrology-based eDNA transport model with a virtual river network reproducing the scaling features of real rivers. In particular, we conducted simulations investigating scenarios of different number and location of eDNA sampling sites in a riverine network, different spatial taxon distributions, and different eDNA measurement errors.We identified best practices for sampling site selection for taxa that have a scattered versus an even distribution across the network. We observed that, due to hydrological controls, non-uniform patterns of eDNA concentration arise even if the taxon distribution is uniform and decay is neglected. We also found that uncertainties in eDNA concentration estimates do not necessarily hamper model predictions. Knowledge of eDNA decay rates improves model predictions, highlighting the need for empirical estimates of these rates under relevant environmental conditions. Our simulations help define strategies for the design of eDNA sampling campaigns in river networks, and can guide the sampling effort of field ecologists and environmental authorities.
Population coding in the cerebellum and its implications for learning from error
Authors: Shadmehr Reza 
Published: May 2020

AbstractThe cerebellum resembles a feedforward, three-layer network of neurons in which the “hidden layer” consists of Purkinje cells (P-cells), and the output layer consists of deep cerebellar nucleus (DCN) neurons. However, unlike an artificial network, P-cells are grouped into small populations that converge onto single DCN neurons. Why are the P-cells organized in this way, and what is the membership criterion of each population? To consider these questions, in this review I apply elementary mathematics from machine learning and assume that the output of each DCN neuron is a prediction that is compared to the actual observation, resulting in an error signal that originates in the inferior olive. This signal is sent to P-cells via climbing fibers that produce complex spikes. The same error signal from the olive must also guide learning in the DCN neurons, yet the olivary projections to the DCN are weak, particularly in adulthood. However, P-cells that form a population exhibit a special property: they can synchronize their complex spikes, which in turn suppresses activity of the DCN neuron that produced the erroneous output. Viewed in the framework of machine learning, it appears that the olive organizes the P-cells into populations so that through complex spike synchrony each population can act as a surrogate teacher for the DCN neuron it projects to. This error-dependent grouping of P-cells into populations gives rise to a number of remarkable features of behavior, including multiple timescales of learning, protection from erasure, and spontaneous recovery of memory.
Larvicidal activity ofAzadirachta indica, Melaleuca alternifolia, andCarapa guianensisoil compounds and Carica papaya fermented extract onAedes aegyptiLarvicidal activity of oil compounds onAedes aegypti
Authors: Torres Sandra M. , Lima Luis A.R. , Lima Maria do Carmo A. , Alves Lêucio C. , Júnior Valdemiro A.S. 
Published: May 2020

AbstractThe aim of this study was to evaluate the structural changes ofAedes aegyptilarvae submitted to treatment with a product based onAzadirachta indica, Melaleuca alternifolia, Carapa guianensisoils andCarica papayafermented extract. The larvae were exposed for 24h to the experimental groups: product formulated in concentrations of 50% (G1), 25% (G2), and 12.5% (G3); and negative control groups based on water (CN1) and dimethyl sulfoxide (CN2). By the end of the experimental period, some larvae were fixed in 4% buffered glutaraldehyde solution to be processed for optical microscopy. Larvae exposed to G2 and G3 presented more structural damage of the mesentery, Malpighi tubules and nerve ganglia. We conclude that the product formulated in 12.5% and 25% concentrations can be used in the population control of the 3rd larvae stage ofAedes aegyptiby causing lethal injuries and avoiding the larvae development.
HAND2 is a novel obesity-linked adipogenic transcription factor regulated by glucocorticoid signaling
Authors: Giroud Maude , Tsokanos Foivos-Filippos , Caratti Giorgio , Khani Sajjad , Vogl Elena Sophie , Imler Martin , Glantschnig Christina , Gil-Lozano Manuel , Kotschi Stefan , Hass Daniela , Khan Asrar Ali , Garcia Marcos Rios , Mattijssen Frits , Maida Adriano , Tews Daniel , Fischer-Posovszky Pamela , Feuchtinger Annette , Virtanen Kirsi A. , Beckers Johannes , Wabitsch Martin , Blüher Matthias , Tuckerman Jan , Scheideler Marcel , Bartelt Alexander , Herzig Stephan 
Published: May 2020

AbstractAdipocytes are critical cornerstones of energy metabolism. While obesity-induced adipocyte dysfunction is associated with insulin resistance and systemic metabolic disturbances, adipogenesis, the formation of new adipocytes and healthy adipose tissue expansion are associated with metabolic benefits. Understanding the molecular mechanisms governing adipogenesis is of great clinical potential to efficiently restore metabolic health in obesity. Here we show that Heart- and neural crest derivatives-expressed protein 2 (HAND2) is an obesity-linked adipocyte transcription factor regulated by glucocorticoids and required for adipocyte differentiationin vitro. In a large cohort of humans with obesity, white adipose tissue (WAT)HAND2expression was correlated to body-mass-index (BMI). TheHAND2gene was enriched in white adipocytes, induced early in differentiation and responded to dexamethasone, a typical glucocorticoid receptor (GR, encoded byNR3C1) agonist. Silencing ofNR3C1in human multipotent adipose-derived stem cells (hMADS) or deletion of GR in a transgenic conditional mouse model results in diminishedHAND2expression, establishing that adipocyte HAND2 is regulated by glucocorticoids via GRin vitroandin vivo. Using a combinatorial RNAseq approach we identified gene clusters regulated by the GR-HAND2 pathway. Interestingly, silencing ofHAND2impaired adipocyte differentiation in hMADS and primary mouse adipocytes. However, a conditional adipocyteHand2deletion mouse model using Cre under control of theAdipoqpromoter did not mirror these effects on adipose tissue differentiation, indicating that Hand2 was required at stages prior toAdipoqexpression. In summary, our study identifies HAND2 as a novel obesity-linked adipocyte transcription factor, highlighting new mechanisms of GR-dependent adipogenesis in human and mice.
Using Conditional Generative Adversarial Networks to Boost the Performance of Machine Learning in Microbiome Datasets
Authors: Reiman Derek , Dai Yang 
Published: May 2020

AbstractThe microbiome of the human body has been shown to have profound effects on physiological regulation and disease pathogenesis. However, association analysis based on statistical modeling of microbiome data has continued to be a challenge due to inherent noise, complexity of the data, and high cost of collecting large number of samples. To address this challenge, we employed a deep learning framework to construct a data-driven simulation of microbiome data using a conditional generative adversarial network. Conditional generative adversarial networks train two models against each other while leveraging side information learn from a given dataset to compute larger simulated datasets that are representative of the original dataset. In our study, we used a cohorts of patients with inflammatory bowel disease to show that not only can the generative adversarial network generate samples representative of the original data based on multiple diversity metrics, but also that training machine learning models on the synthetic samples can improve disease prediction through data augmentation. In addition, we also show that the synthetic samples generated by this cohort can boost disease prediction of a different external cohort.
Mitochondrial Enzymes of the Urea Cycle Cluster at the Inner Mitochondrial Membrane
Authors: Haskins Nantaporn , Bhuvanendran Shivaprasad , Gams Anna , Kanholm Tomas , Kocher Kristen M. , LoTempio Jonathan , Krohmaly Kylie I. , Sohai Danielle , Stearrett Nathan , Bonner Erin , Tuchman Mendel , Morizono Hiroki , Jaiswal Jyoti K. , Caldovic Ljubica 
Published: May 2020

AbstractMitochondrial enzymes involved in energy transformation are organized into multiprotein complexes that channel the reaction intermediates for efficient ATP production. Three of the mammalian urea cycle enzymes: N-acetylglutamate synthase (NAGS), carbamylphosphate synthetase 1 (CPS1), and ornithine transcarbamylase (OTC) reside in the mitochondria. Urea cycle is required to convert ammonia into urea and protect the brain from ammonia toxicity. Urea cycle intermediates are tightly channeled in and out of mitochondria, indicating that efficient activity of these enzymes relies upon their coordinated interaction with each other perhaps in a multiprotein complex. This view is supported by mutations in surface residues of the urea cycle proteins that impair urea genesis in the patients but do not affect protein stability or catalytic activity. Further, we find one third of the NAGS, CPS1 and OTC proteins in liver mitochondria can associate with the inner mitochondrial membrane (IMM), and co-immunoprecipitate. Ourin silicoanalysis of vertebrate NAGS proteins, the least abundant of the urea cycle enzymes, identified a region we call ‘variable segment’ present only in the mammalian NAGS protein. We experimentally confirmed that NAGS variable segment mediates the interaction of NAGS with CPS1. Use of Gated-Stimulation Emission Depletion (gSTED) super resolution microscopy showed that in situ, NAGS, CPS1 and OTC are organized into clusters. These results are consistent with mitochondrial urea cycle proteins forming a cluster instead of functioning either independently or in a rigid multienzyme complex.
Time between milestone events in the Alzheimer’s disease amyloid cascade
Authors: Insel Philip S. , Donohue Michael C. , Berron David , Hansson Oskar , Mattsson-Carlgren Niklas 
Published: May 2020

AbstractObjectiveEstimate the time-course of the spread of key pathological markers and the onset of cognitive dysfunction in Alzheimer’s disease.MethodsIn a cohort of 336 older adults, ranging in cognitive functioning, we estimated the time of initial changes of Aβ, tau, and decreases in cognition with respect to the time of Aβ-positivity.ResultsSmall effect sizes of change in CSF Aβ42 and regional Aβ PET were estimated to occur several decades before Aβ-positivity. Increases in CSF tau occurred 11-12 years before Aβ-positivity. Temporoparietal tau PET showed increases 4-5 years before Aβ-positivity. Subtle cognitive dysfunction was observed 7-9 years before Aβ-positivity.ConclusionsIncreases in tau and cognitive dysfunction occur years before the presence of significant Aβ. Explicit estimates of the time for these events provide a clearer picture of the time course of the amyloid cascade and identify potential windows for specific treatments.
AHLF: ad hoc learning of peptide fragmentation from mass spectra enables an interpretable detection of phosphorylated and cross-linked peptides
Authors: Altenburg Tom , Giese Sven , Wang Shengbo , Muth Thilo , Renard Bernhard Y. 
Published: May 2020

AbstractMass spectrometry-based proteomics provides a holistic snapshot of the entire protein set of a living cell on a molecular level. Currently, only a few deep learning approaches that involve peptide fragmentation spectra, which represent partial sequence information of proteins, exist. Commonly, these approaches lack the ability to characterize less studied or even unknown patterns in spectra because of their use of explicit domain knowledge. To elevate unrestricted learning from spectra, we introduce AHLF, a deep learning model that is end-to-end trained on 19.2 million spectra from multiple phosphoproteomic data sets. AHLF is interpretable and we show that peak-level feature importances and pairwise interactions between peaks are in line with corresponding peptide fragments. We demonstrate our approach by detecting post-translational modifications, specifically protein phosphorylation based on only the fragmentation spectrum without a database search. AHLF increases the area under the receiver operating characteristic curve (AUC) by an average of 9.4% on recent phosphoproteomic data compared to the current-state-of-the-art on this task. To show the broad applicability of AHLF we use transfer learning to also detect cross-linked peptides, as used in protein structure analysis, with an AUC of up to 94%. We expect our approach to directly apply to cell signaling and structural biology which use phosphoproteomic and cross-linking data, but in principal any mass spectrometry based study can benefit from an interpretable, end-to-end trained model like AHLF.Availabilityhttps://gitlab.com/dacs-hpi/ahlfContactbernhard.renard@hpi.de
The transmission-blocking effects antimalarial drugs revisited: mosquito fitness costs and sporontocidal effects of artesunate and sulfadoxine-pyrimethamine
Authors: Villa M , Buysse M , Berthomieu A , Rivero A 
Published: May 2020

AbstractAssays used to evaluate the transmission-blocking activity of antimalarial drugs are largely focused on their potential to inhibit or reduce the infectivity of gametocytes, the blood stages of the parasite that are responsible for the onward transmission to the mosquito vector. For this purpose, the drug is administered concomitantly with the gametocyte-infected blood, and the results are evaluated as the % reduction in the number of oocysts in the mosquito midgut.We report the results of a series of experiments that explore the transmission blocking potential of two key antimalarial drugs, artesunate (AS) and sulfadoxine-pyrimethamine (SP), when administered to mosquitoes already infected from a previous blood meal. For this purpose, uninfected mosquitoes and mosquitoes carrying a 6-day oldPlasmodium relictuminfection (early oocyst stages) are allowed to feed either on a drug-treated or an untreated host in a fully factorial experiment. This protocol allows us to bypass the gametocyte stages and establish whether the drugs are able to arrest the ongoing development of oocysts and sporozoites, as would be the case when a mosquito takes a post-infection treated blood meal. In a separate experiment, we also explore whether a drug-treated blood meal impacts key life history traits of the mosquito relevant for transmission, and if this depends on their infection status.Our results show that feeding on an AS- or SP-treated host has no epidemiologically relevant effects on the fitness of infected or uninfected mosquitoes. In contrast, when infected mosquitoes feed on an SP-treated host, we observe both a significant increase in the number of oocysts in the midgut, and a drastic decrease in both sporozoite prevalence (−30%) and burden (−80%) compared to the untreated controls. We discuss the potential mechanisms underlying these seemingly contradictory results and contend that, provided the results are translatable to human malaria, the potential epidemiological and evolutionary consequences of the current preventive use of SP in malaria-endemic countries could be substantial.
Development of a diamide resistance diagnostic method using LAMP based on a resistance-specific indel in ryanodine receptors forSpodoptera exigua(Lepidoptera: Noctuidae)
Authors: Kim Juil , Nam Hwa Yeun , Kwon Min , Choi Ji Hye , Cho Sun Ran , Kim Gil-Hah 
Published: May 2020

AbstractRecently, resistance to diamide insecticides (IRAC group 28) has been reported in various lepidopteran pests, includingSpodoptera exigua. In the present study, susceptibility of six field populations was evaluated to two diamide insecticides: chlorantraniliprole and flubendiamide. The bioassay test for resistance revealed a high level of diamide resistance and helped to select a diamide resistant (Di-R) strain, whose LC50 values against chlorantraniliprole and flubendiamide were 28,950- and 135,286-fold higher, respectively, than those of susceptible strains. In the ryanodine receptor, instead of the G4946E mutation, one of the well-known diamide resistance mechanisms, we found a I4790M mutation and identified the resistance allele-specific indel linked to it. Resistance allele diagnostic primers were designed using this distinct region and applied in loop-mediated isothermal amplification (LAMP) and general PCR. LAMP accurately detected the specific indel when conducted for 2 h at temperature range from 63 °C to 65 °C and using four LAMP primers; its efficiency was further amplified by an additional loop primer. A broad range of DNA concentrations was workable in the LAMP assay, with the minimum detectable DNA concentration of 100 pg. The new DNA releasing method used for the LAMP assay consisted of 5 min of incubation of a larva or adult tissue at 95°C. The entire diagnostic process, which included the DNA releasing technique and LAMP, lasted only 100 min. This simple and accurate LAMP assay can be applied to monitor diamide resistance and for integrated resistance management ofS. exiguain the field.
Laboratory evolution of multipleE. colistrains reveals unifying principles of adaptation but diversity in driving genotypes
Authors: Kavvas Erol S. , Antoniewicz Maciek , Long Christopher , Ding Yang , Monk Jonathan M. , Palsson Bernhard O. , Feist Adam M. 
Published: May 2020

AbstractFitness landscapes are a central concept in evolutionary biology and have been thoroughly detailed in terms of genotypes. However, our understanding of the selected metabolic and gene expression adaptations, and their dependence on genetic background, remains limited. Here, we reveal multi-scale adaptation principles in theE. colispecies by taking multi-omics measurements of six different strains throughout their adaptive evolution to glucose minimal media. Statistics and matrix factorization is applied to yield four key results. First, analysis of the metabolic and physiological data shows evolutionary convergence in growth rate, glucose uptake rate, glycolytic ATP and NADH production but divergence in NADPH production strategies. Second, factorization-based analysis of the transcriptome revealed six conserved transcriptomic adaptations describing increased expression of ribosome and amino acid biosynthetic genes and decreased expression of stress response and structural genes. Third, correlation analysis identifies five tradeoffs underlying the transcriptomic profiles. Fourth, statistical tests leveraging ALE design identify four mutation-flux correlates and eight mutation-transcriptomic correlates that link mutations to systems level adaptation principles. Our total results reveal the dominant metabolic and regulatory constraints governingE. coligrowth adaptation that either distinguish strains or are conserved principles.
Chemical probe-based Nanopore Sequencing to Selectively Assess the RNA modifications
Authors: Ramasamy Soundhar , Sahayasheela Vinodh J , Yu Zutao , Hidaka Takuya , Cai Li , Sugiyama Hiroshi , Pandian Ganesh N. 
Published: May 2020

AbstractCurrent methods to identify RNA modifications with short-read sequencing are laborious and direct RNA sequencing gets proclaimed as the viable alternative. Herein, we harness the selective reactivity of the acrylonitrile towards the Inosine (I)and pseudouridine (Ψ) modifications and developed a chemical probe-based direct RNA sequencing method. We first demonstrated that the chemical probe-induced differential signature profile using nanopore sequencing could facilitate the selective assessment ofIandΨin thein vitrosynthesized RNA. Furthermore, we verified theIandΨmodification with single-nucleotide resolution using RNA derived from mouse brain without the need for a null dataset using knockouts. Our chemical probe-based nanopore sequencing strategy can be extended to profile multiple RNA modifications on a single RNA and may facilitate the diagnosis of disease-associated epitranscriptome markers by generating a comparative dataset in clinical scenarios.Abstract Figure
A single master regulator controls asexual cell cycle division patterns inToxoplasma gondii
Authors: Khelifa Asma S. , Sanchez Guillen Cecilia , Lesage Kevin M. , Huot Ludovic , Pericard Pierre , Barois Nicolas , Touzet Helene , Marot Guillemette , Gissot Mathieu 
Published: May 2020

ABSTRACTAll apicomplexan parasites have complex life cycles exhibiting division characterized by a tightly regulated cell cycle control, resulting in the emergence of daughter parasites in possession of a single nucleus and a complete set of organelles. Apicomplexa have evolved efficient and distinctive strategies for intracellular replication where the timing of emergence of the daughter cells, a process termed “budding”, is a decisive element. However, the molecular mechanisms that provide the proper timing of parasite budding remain unknown. UsingToxoplasma gondiias a model Apicomplexa, we identified a master regulator that controls the timing of the budding process. We show that an ApiAP2 transcription factor, TgAP2IX-5, controls cell cycle events downstream of centrosome duplication including organelle division and segregation. TgAP2IX-5 binds to the promoter of hundreds of genes and controls the activation of the budding-specific cell cycle expression program. We show that TgAP2IX-5 regulates the expression of specific transcription factors that are necessary for the completion of the budding cycle. TgAP2IX-5 acts as a licensing factor that ensures that asexual proliferation continues by promoting the inhibition of the differentiation pathway at each round of the cell cycle. Therefore, TgAP2IX-5 is a master regulator that controls both cell cycle and developmental pathways.