bluuebunny/crossref_metadata_2025_split huggingface dataset:
A deep network-based model of hippocampal memory functions under normal and Alzheimer’s disease conditions
Authors: Kanagamani Tamizharasan , Chakravarthy V. Srinivasa , Ravindran Balaraman 
Published: February 2021

AbstractWe present a deep network-based model of the associative memory functions of the hippocampus. The proposed network architecture has two key modules: 1) an autoencoder module which represents the forward and backward projections of the cortico-hippocampal projections and 2) a module that computes familiarity of the stimulus and implements hill-climbing over the familiarity which represents the dynamics of the loops within the hippocampus. The proposed network is used in two simulation studies. In the first part of the study, the network is used to simulate image pattern completion by autoassociation under normal conditions. In the second part of the study, the proposed network is extended to a heteroassociative memory and is used to simulate picture naming task in normal and Alzheimer’s disease (AD) conditions. The network is trained on pictures and names of digits from 0 – 9. The encoder layer of the network is partly damaged to simulate AD conditions. As in case of AD patients, under moderate damage condition, the network recalls superordinate words (“odd” instead of “nine”). Under severe damage conditions, the network shows a null response (“I don’t know”). Neurobiological plausibility of the model is extensively discussed.
Neural mechanism underlying task-specific enhancement of motor learning by concurrent transcranial direct current stimulation
Authors: Wang Ying , Wang Jixian , Zhang Qing-fang , Xiao Ke-wei , Wang Liang , Yu Qing-ping , Xie Qing , Poo Mu-ming , Wen Yunqing 
Published: February 2021

ABSTRACTThe optimal protocol for neuromodulation by transcranial direct current stimulation (tDCS) remains unclear. Using rotarod paradigm, we found that mouse motor learning was enhanced by anodal tDCS (3.2 mA/cm2) during but not before or after task performance. Dual-task experiments showed that motor learning enhancement was specific to the task accompanied by concurrent anodal tDCS. Studies using stroke model mice induced by middle cerebral artery occlusion (MCAO) showed that concurrent anodal tDCS restored motor learning capability in a task-specific manner. Transcranialin vivocalcium imaging further showed that anodal and cathodal tDCS elevated and suppressed neuronal activity in the primary motor cortex (M1), respectively. Anodal tDCS specifically promoted the activity of task-related M1 neurons during task performance, suggesting that elevated Hebbian synaptic potentiation in task-activated circuits accounts for motor learning enhancement. Thus, application of tDCS concurrent with the targeted behavioral dysfunction could represent a more effective approach for treating brain disorders.
The Reactobiome Unravels a New Paradigm in Human Gut Microbiome Metabolism
Authors: Bidkhori Gholamreza , Lee Sunjae , Edwards Lindsey A. , Chatelier Emmanuelle Le , Almeida Mathieu , Ezzamouri Bouchra , Onate Florian Plaza , Ponte Nicolas , Shawcross Debbie L. , Proctor Gordon , Nielsen Lars , Nielsen Jens , Uhlen Mathias , Ehrlich Stanislav Dusko , Shoaie Saeed 
Published: February 2021

AbstractChanges in microbial metabolism have been used as the main approach to assess function and elucidate environmental and host-microbiome interactions. This can be hampered by uncharacterised metagenome species and lack of metabolic annotation. To address this, we present a comprehensive computational platform for population stratification based on microbiome composition, the underlying metabolic potential and generation of metagenome species and community level metabolic models. We revisit the concepts of enterotype and microbiome richness introducing the reactobiome as a stratification method to unravel the metabolic features of the human gut microbiome. The reactobiome encapsulates resilience and microbiome dysbiosis at a functional level. We describe five reactotypes in healthy populations from 16 countries, with specific amino acid, carbohydrate and xenobiotic metabolic features. The validity of the approach was tested to unravel host-microbiome and environmental interactions by applying the reactobiome analysis on a one-year Swedish longitudinal cohort, integrating gut metagenomics, plasma metabolomics and clinical data.
Transmembrane protein 97 is a potential synaptic amyloid beta receptor in human Alzheimer’s disease
Authors: Colom-Cadena Martí , Toombs Jamie , Simzer Elizabeth , Tulloch Jane , Jackson Rosemary J , Catterson James H , Rose Jamie , Waybright Lora , Caggiano Anthony O , Davies Caitlin , Hooley Monique , Dunnett Sophie , Tempelaar Robert , Tzioras Makis , Hamby Mary E , Izzo Nicholas J , Catalano Susan M. , Smith Colin , Dando Owen , Spires-Jones Tara L. 
Published: February 2021

AbstractSynapse loss correlates with cognitive decline in Alzheimer’s disease, and soluble oligomeric amyloid beta is implicated in synaptic dysfunction and loss. An important knowledge gap is the lack of understanding of how amyloid beta leads to synapse degeneration. In particular, there has been difficulty in determining whether there is a synaptic receptor that binds amyloid beta and mediates toxicity. While many candidates have been observed in model systems, their relevance to human AD brain remains unknown. This is in part due to methodological limitations preventing visualization of amyloid beta binding at individual synapses. To overcome this limitation, we combined two high resolution microscopy techniques: array tomography and Förster resonance energy transfer (FRET) to image over 1 million individual synaptic terminals in temporal cortex from AD (n=9) and age matched control cases (n=6). Within postsynaptic densities, amyloid beta generates a FRET signal with transmembrane protein 97, cellular prion protein, and postsynaptic density 95. Transmembrane protein 97 is also present in a higher proportion of postsynapses in Alzheimer’s brain compared to controls. Further, we inhibited amyloid beta / transmembrane protein 97 interaction in a mouse model of amyloidopathy by treating with the an allosteric modulator CT1812 or vehicle. CT1812 drug concentration correlated negatively with synaptic FRET signal between transmembrane protein 97 and amyloid beta. In human induced pluripotent stem cell derived neurons challenged with human Alzheimer’s brain homogenate, transmembrane protein 97 and amyloid beta are present in synapses. Transcriptional changes are induced by Aβ including changes in genes involved in neurodegeneration and neuroinflammation. CT1812 treatment of these neurons caused changes in gene sets involved in synaptic function. These data support a role for transmembrane protein 97 in the synaptic binding of amyloid beta in human Alzheimer’s disease brain where it may mediate synaptotoxicity.
Complementary Maps for Location and Environmental Structure in CA1 and Subiculum
Authors: Olson Jacob M , Johnson Alexander B , Chang Lillian , Tao Emily L , Wang Xuefei , Nitz Douglas A 
Published: February 2021

AbstractThe dorsal subiculum lies among a network of interconnected brain regions that collectively map multiple spatial and orientational relationships between an organism and the boundaries and pathways composing its environment. A unique role of the subiculum in spatial information processing has yet to be defined despite reports of small neuron subpopulations that encode relationships to specific boundaries, axes of travel, or locations. We examined the activity patterns among populations of subiculum neurons during performance of a spatial working memory task performed within a complex network of interconnected pathways. Compared to neurons in hippocampal sub-region CA1, a major source of its afferents, subiculum neurons were far more likely to exhibit multiple firing fields at locations that were analogous with respect to path structure and function. Subiculum neuron populations were also found to exhibit a greater dynamic range in scale of spatial representation and for persistent patterns of spiking activity to be aligned to transitions between maze segments. Together, the findings indicate that the subiculum plays a unique role in spatial mapping, one that complements the location-specific firing of CA1 neurons with the encoding of emergent and recurring structural features of a complex path network.
Quality control strategies for brain MRI segmentation and parcellation: practical approaches and recommendations - insights from The Maastricht Study
Authors: Sánchez Jennifer Monereo , de Jong Joost J.A. , Drenthen Gerhard S. , Beran Magdalena , Backes Walter H. , Stehouwer Coen D.A. , Schram Miranda T. , Linden David E.J. , Jansen Jacobus. F.A. 
Published: February 2021

ABSTRACTBackgroundQuality control of brain segmentation is a fundamental step to ensure data quality. Manual quality control is the current gold standard, despite unfeasible in large neuroimaging samples. Several options for automated quality control have been proposed, providing potential time efficient and reproducible alternatives. However, those have never been compared side to side, which prevents to reach consensus in the appropriate QC strategy to use. This study aims to elucidate the changes manual editing of brain segmentations produce in morphological estimates, and to analyze and compare the effects of different quality control strategies in the reduction of the measurement error.MethodsWe used structural MR images from 259 participants of The Maastricht Study. Morphological estimates were automatically extracted using FreeSurfer 6.0. A subsample of the brain segmentations with inaccuracies was manually edited, and morphological estimates were compared before and after editing. In parallel, 11 quality control strategies were applied to the full sample. Those included: a manual strategy, manual-QC, in which images were visually inspected and manually edited; five automated strategies where outliers were excluded based on the tools MRIQC and Qoala-T, and the metrics morphological global measures, Euler numbers and Contrast-to-Noise ratio; and five semi-automated strategies, were the outliers detected through the mentioned tools and metrics were not excluded, but visually inspected and manually edited. We used a regression of morphological brain measures against age as a test case to compare the changes in relative unexplained variance that each quality control strategy produces, using the reduction of relative unexplained variance as a measure of increase in quality.ResultsManually editing brain surfaces produced changes particularly high in subcortical brain volumes and moderate in cortical surface area, thickness and hippocampal volumes. The exclusion of outliers based on Euler numbers yielded a larger reduction of relative unexplained variance for measurements of cortical area, subcortical volumes and hippocampal subfields, while manual editing of brain segmentations performed best for cortical thickness. MRIQC produced a lower, but consistent for all types of measures, reduction in relative unexplained variance. Unexpectedly, the exclusion of outliers based on global morphological measures produced an increase of relative unexplained variance, potentially removing more morphological information than noise from the sample.ConclusionOverall, the automatic exclusion of outliers based on Euler numbers or MRIQC are reliable and time efficient quality control strategies that can be applied in large neuroimaging cohorts.
OmicsTIDE: Interactive Exploration of Trends in Multi-Omics Data
Authors: Harbig Theresa , Fratte Julian , Krone Michael , Nieselt Kay 
Published: February 2021

AbstractMotivationThe increasing amount of data produced by omics technologies has significantly improved the understanding of how biological information is transferred across different omics layers and to which extent it is involved in the manifestation of a given phenotype. Besides data-driven analysis strategies, interactive visualization tools have been developed to make the analysis in the multi-omics field more transparent. However, most state-of-the-art tools do not reconstruct the impact of a given omics layer on the final integration result. In general, the amount of omics data analyses strategies and the fields of applications lack a clearer classification of the different approaches.ResultsWe developed a classification for omics data focusing on different aspects of multi-omics data sets, such as data type and experimental design. Based on this classification we developed the Omics Trend-comparing Interactive Data Explorer (OmicsTIDE), an interactive visualization tool developed to address the limitations of current visualization approaches in the multi-omics field. The tool consists of an automated part that clusters omics data to determine trends and an interactive visualization. The trends are visualized as profile plots and are connected by a Sankey diagram that allows an interactive pairwise trend comparison to discover concordant and discordant trends. Moreover, large-scale omics data sets are broken down into small subsets of concordant and discordant regulatory trends within few analysis steps. We demonstrate the interactive analysis usingOmicsTIDEwith two case studies focusing on different types of experimental designs.AvailabilityOmicsTIDEis a web tool and available viahttp://tuevis.informatik.uni-tuebingen.de/Contactkay.nieselt@uni-tuebingen.de
Associations of weather fronts with pig reproduction and mortality
Authors: Reibling Tamás , Hagstrand Linnea , Maróti-Agóts Ákos , Barcza Zoltán , Solymosi Norbert 
Published: February 2021

ABSTRACTFarmers and practising veterinarians have long suspected the impact of weather fronts on production and animal health. A common impression is that sows will farrow earlier in connection with a cold front. There might be a correlation between daily mortality and the occurrence of a strong atmospheric front. Population-based quantitative studies on weather fronts’ effects on animal health and production are very sparse in the scientific literature. In this study, the associations between the weather fronts and daily farrowing incidence, the pregnancy length and the daily death incidence were analysed. The results show that cold front increased the odds of more than daily six farrowings on the day of the front (with at least 3°C cooling OR: 4.79, 95%CI: 1.08-21.21, p=0.039). On the day of the front, with at least 3°C temperature change both the cold and the warm front increased the odds of the farrowing on the day ≥ 118th day of the gestation (OR: 3.10, 95%CI: 1.04-9.30, p=0.43 and OR: 4.39, 95%CI: 1.73-11.15, p=0.002, respectively). On the day after the day of front, the odds of farrowing on the ≤ 113th day of gestation are increased, if the temperature decrease was at least 2°C the OR: 2.30 (95%CI: 1.04-5.06, p=0.039). On the day after the warm front with at least 1°C temperature increase the odds of more than daily three deaths is increased (OR: 5.44, 95%CI: 1.23-24.05, p=0.025).
Wrinkle force microscopy: a new machine learning based approach to predict cell mechanics from images
Authors: Li Honghan , Matsunaga Daiki , Matsui Tsubasa S. , Aosaki Hiroki , Inoue Koki , Doostmohammadi Amin , Deguchi Shinji 
Published: February 2021

Combining experiments with artificial intelligence algorithms, we propose a new machine learning based approach to extract the cellular force distributions from the microscope images. The full process can be divided into three steps. First, we culture the cells on a special substrate allowing to measure both the cellular traction force on the substrate and the corresponding substrate wrinkles simultaneously. The cellular forces are obtained using the traction force microscopy (TFM), at the same time that cell-generated contractile forces wrinkle their underlying substrate. Second, the wrinkle positions are extracted from the microscope images. Third, we train the machine learning system with GAN (generative adversarial network) by using sets of corresponding two images, the traction field and the input images (raw microscope images or extracted wrinkle images), as the training data. The network understands the way to convert the input images of the substrate wrinkles to the traction distribution from the training. After sufficient training, the network is utilized to predict the cellular forces just from the input images. Our system provides a powerful tool to evaluate the cellular forces efficiently because the forces can be predicted just by observing the cells under the microscope, which is a way simpler method compared to the TFM experiment. Additionally, the machine learning based approach presented here has the profound potential for being applied to diverse cellular assays for studying mechanobiology of cells.Significance StatementCell-generated forces are indispensable determinants of fundamental cell functions such as motility and cell division. As such, quantifying how the forces change upon perturbations to the cells such as gene mutations and drug administration is of profound importance. Here we present a novel machine learning based system that allows for efficient estimations of the forces that are determined only by “observing” microscope images. Given that the cellular traction forces are regulated downstream of diverse signaling pathways, our system – that helps significantly improve the throughput of the measurements – presents a new, high throughput platform for real time analysis of the effects of a massive number of genetic and molecular perturbations on the forces and resulting cell mechanics.
Cubam receptor-mediated endocytosis in hindgut-derived pseudoplacenta of a viviparous teleost Xenotoca eiseni
Authors: Iida Atsuo , Sano Kaori , Inokuchi Mayu , Nomura Jumpei , Suzuki Takayuki , Kuriki Mao , Sogabe Maina , Susaki Daichi , Tonosaki Kaoru , Kinoshita Tetsu , Hondo Eiichi 
Published: February 2021

AbstractNutrient transfer from mother to the embryo is essential for reproduction in viviparous animals. In the viviparous teleost Xenotoca eiseni belonging to the family Goodeidae, the intraovarian embryo intakes the maternal component secreted into the ovarian fluid via the trophotaenia. Our previous study reported that the epithelial layer cells of the trophotaenia incorporate a maternal protein via vesicle trafficking. However, the molecules responsible for the absorption were still elusive. Here, we focused on Cubam (Cubilin-Amnionless) as a receptor involved in the absorption, and cathepsin L as a functional protease in the vesicles. Our results indicated that the Cubam receptor is distributed in the apical surface of the trophotaenia epithelium and then is taken into the intracellular vesicles. The trophotaenia possesses acidic organelles in epithelial layer cells and cathepsin L-dependent proteolysis activity. This evidence does not conflict with our hypothesis that receptor-mediated endocytosis and proteolysis play roles in maternal macromolecule absorption via the trohotaenia in viviparous teleosts. Such nutrient absorption involving endocytosis is not a specific trait in viviparous fish. Similar processes have been reported in the larval stage of oviparous fish or the suckling stage of viviparous mammals. Our findings suggest that the viviparous teleost acquired trophotaenia-based viviparity from a modification of the intestinal absorption system common in vertebrates. This is a fundamental study to understand the strategic variation of the reproductive system in vertebrates.Summary statementHere, we report that an endocytic pathway is a candidate for nutrient absorption in pseudoplacenta of a viviparous teleost. The trait may have developed from common intestinal mechanism among vertebrates.
Verapamil/Curcumin treatment attenuates the behavioral alterations observed in Williams Syndrome mice by regulation of MAPK pathway and Microglia overexpression
Authors: Ortiz-Romero Paula , Egea Gustavo , Pérez-Jurado Luis A , Campuzano Victoria 
Published: February 2021

AbstractWilliams-Beuren syndrome (WBS) is a rare neurodevelopmental disorder characterized by a distinctive cognitive phenotype for which there currently are not any effective treatments. We investigated the progression of behavioral deficits present in CD (complete deletion) mice, a rodent model of WBS, after chronic treatment with curcumin, verapamil and a combination of both. These compounds have been proven to have beneficial effects over different cognitive aspects of various murine models and thus, may have neuroprotective effects in WBS. Treatment was administered orally dissolved in drinking water. A set of behavioral tests demonstrated the efficiency of combinatorial treatment. Some histological and molecular analyses were performed to analyze the effects of treatment and its underlying mechanism in CD mice. Behavioral improvement correlates with the molecular recovery of several affected pathways regarding MAPK signaling, in tight relation with the control of synaptic transmission. Moreover, CD mice showed an increased activated microglia density in different brain regions, which was prevented by treatment. Therefore, results show that treatment prevented behavioral deficits by recovering altered gene expression in cortex of CD mice, reducing activated microglia and normalizingBdnfexpression levels. These findings unravel the mechanisms underlying the beneficial effects of this novel treatment on behavioral deficits observed in CD mice, and suggest that the combination of curcumin and verapamil could be a potential candidate to treat the cognitive impairments in WBS patients.
Metabolomic profiling of pancreatic adenocarcinoma reveals fundamental clinical features
Authors: Kaoutari Abdessamad El , Fraunhoffer Nicolas A , Hoare Owen , Teyssedou Carlos , Soubeyran Philippe , Gayet Odile , Roques Julie , Lomberk Gwen , Urrutia Raul , Dusetti Nelson , Iovanna Juan 
Published: February 2021

AbstractIn this study, we perform the metabolomics profiling of 77 PDAC patient-derived tumor xenografts (PDTX) to investigate the relationship of metabolic profiles with overall survival (OS) in PDAC patients, tumor phenotypes and resistance to five anticancer drugs (gemcitabine, oxaliplatin, docetaxel, SN-38 and 5-Fluorouracil). We identified a metabolic signature that was able to predict the clinical outcome of PDAC patients (p < 0.001, HR=2.68 [95% CI: 1.5-4.9]). The correlation analysis showed that this metabolomic signature was significantly correlated with the PDAC molecular gradient (PAMG) (R = 0.44 and p < 0.001) indicating significant association to the transcriptomic phenotypes of tumors. Resistance score established, based on growth rate inhibition metrics using 35 PDTX-derived primary cells, allowed to identify several metabolites related to drug resistance which was globally accompanied by accumulation of several diacy-phospholipids and decrease in lysophospholipids. Interestingly, targeting glycerophospholipid synthesis improved sensitivity to the three tested cytotoxic drugs indicating that interfering with metabolism could be a promising therapeutic strategy to overcome the challenging resistance of PDAC.Short abstractTargeting metabolism of cancer cells gives a precious opportunity to overcome challenges related to the high mortality and chemoresistance in PDAC.Metabolic profiling of PDAC patient-derived tumor xenografts used in this study allowed highlighting the strong link between metabolism and both clinical outcome of the patients and chemoresistance.Metabolic signature was able to discriminate between good and bad prognosis groups of patients based on their level of key metabolites.Identification of key metabolic markers associated to chemoresistance allowed to improve sensitivity to anticancer drugs.These results provide new insights to help to predict patient survival and elaborate new combinatory therapies against chemoresistance in PDAC patients attesting of the important clinical value of this work.