bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Radiologic Characteristics and Retinal Thickness Are Correlated With Visual Field Defect in Patients With a Pituitary Mass
Authors: Suh Hiebum , Choi Heeyoung , Jeon Hyeshin 
Published: June 2020

Background:
Investigation of visual field defects (VFDs) is important to decide the treatment and to predict the prognosis in patients with a pituitary mass. The aim of this study was to evaluate the correlation among 2 diagnostic modalities—MRI and optical coherence tomography (OCT)—and VFDs.

Methods:
Consecutive patients who showed the presence of a pituitary mass on MRI and in whom ophthalmic examinations were performed were recruited. Height and volume of the mass, sagittal and coronal displacement of optic chiasm, and the direction of mass expansion were measured. Patients were divided into 2 groups according to the presence (VFD group) or absence of VFDs (no VFDs group [NVFD]). The correlation among MRI parameters, OCT parameters, and VFDs were examined, and the diagnostic values of MRI and OCT and the combined value of the 2 modalities were analyzed.

Results:
Forty-one patients were included. The greatest coefficients of determination were observed between the sagittal displacement and pattern standard deviation (PSD) (R2 = 0.3661, P < 0.001) and between the inferonasal ganglion cell–inner plexiform layer (GCIPL) and PSD (R2 = 0.4079, P < 0.001). The height and the size of the mass in the VFD group were significantly greater as 57% and 148%, respectively, and the VFD group had more severe chiasmal displacement both in the sagittal (165%) and in the coronal (178%) plane (large effect in all). All macular GCIPLs were thinner in the NVFD group (range 9%–26%, large effect), whereas only temporal (25%) and average (11%) values were among peripapillary retinal nerve fiber layers.

Conclusions:
The highest correlations with the degree of the VFD were seen in the sagittal displacement of optic chiasm and the inferonasal GCIPL, and these parameters were correlated concurrently. Both modalities showed a good diagnostic value for discriminating VFDs.
Considerations for the Treatment of Inflammatory Neuro-Ophthalmologic Disorders During the COVID-19 Pandemic
Authors: Martin Paez Yosbelkys , Bennett Jeffrey L. , Subramanian Prem S. , Pelak Victoria S. 
Published: June 2020

Abstract:
The initiation and continuation of immune-based therapies to treat and prevent complications of inflammatory neuro-ophthalmologic disorders during the 2019 novel coronavirus (COVID-19) pandemic is the subject of considerable debate. In each case, a treatment decision must be reached based on best clinical practices for the disorder, patient comorbidities, the current state of knowledge about the pathogenesis and infectivity of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and the utilization of hospital and community resources. Unfortunately, the evidence needed to standardize the decision-making process for each neuro-ophthalmologic disorder is currently absent and is likely to require months or years to develop based on the accrual of robust international data sets. In this article, we review the current understanding of SARS-CoV-2 and COVID-19 complications to provide a framework for approaching the treatment of inflammatory neuro-ophthalmic disorders during the COVID-19 viral pandemic.
CORRELATION BETWEEN EARLY ANTIBIOTIC THERAPY AND IN-HOSPITAL MORTALITY IN PATIENTS WITH COMMUNITY ACQUIRED INFECTION
Authors: Araújo Beatriz , Reis Geovane Rossone , Araújo Isadora , Sales Marcella Soares Carreiro , Silveira Janne Marques 
Published: June 2020

ABSTRACTSepsis is defined as the systemic response to an infectious disease, whether caused by bacteria, viruses, fungi or protozoa. Sepsis has several etiologies according to the worsening of the disease, those of bacterial origin with 70%, of which Gram-negative bacilli are the most frequent, especially in patients with the most severe disease. The most common community infections are respiratory infections, urinary tract infections and skin infections, with elderly individuals and children being more susceptible to complications of the immune system. The objective of this research is to analyze whether the time between hospitalization and the start of antibiotic treatment is directly related to the mortality rate and length of stay. This study was carried out in the form of documentary field research, where data collection was performed using data from the medical records of patients diagnosed with community infection or sepsis. Data collection was carried out from a form where patient identification, age, infectious focus, date and time of admission to the emergency room, date and time of the 1st dose of antibiotic, time interval between admission and antibiotic administration, ICU stay, days of mechanical ventilation and outcome. 34 patients were followed up in the emergency room and in the ICU, with an average age of these patients is 71.4 ± 30 years. This research showed a high mortality rate of the included patients who were diagnosed with community infection.
Opposing Wnt and JAK-STAT signaling gradients define a stem cell domain by regulating spatially patterned cell division and differentiation at two borders
Authors: Melamed David , Kalderon Daniel 
Published: June 2020

AbstractMany adult stem cells are maintained as a community by population asymmetry, wherein stochastic actions of individual cells collectively result in a balance between stem cell division and differentiation. We have used Drosophila Follicle Stem Cells (FSCs) as a paradigm to explore the extracellular niche signals that define a stem cell domain and organize stem cell behavior. FSCs produce transit-amplifying Follicle Cells (FCs) from their posterior face and quiescent Escort Cells (ECs) to their anterior. Here we show that JAK-STAT pathway activity, which declines from posterior to anterior, dictates the pattern of divisions over the FSC and EC domains, promotes more posterior FSC locations and conversion to FCs, while opposing EC production. A Wnt pathway gradient of opposite polarity promotes more anterior FSC locations and EC production and opposes FC production. Promotion of both FSC division and conversion to FCs by JAK-STAT signaling buffers the effects of genetically altered pathway activity on FSC numbers and balances the four-fold higher rate of differentiation at the posterior face of the FSC domain with a higher rate of FSC division in the most posterior layer. However, genetic elimination of Wnt pathway activity exacerbated elevated FC production resulting from increased JAK-STAT pathway activity, leading to rapid FSC depletion despite high rates of division. The two pathways combine to define a stem cell domain through concerted effects on FSC differentiation to ECs (high Wnt, low JAK-STAT) and FCs (low Wnt, high JAK-STAT) at each end of opposing signaling gradients, further enforced by quiescence at the anterior border due to declining JAK-STAT pathway activity.
Coastal winds and larval fish abundance indicate a recruitment mechanism for southeast Australian estuarine fisheries
Authors: Schilling Hayden T. , Hinchliffe Charles , Gillson Jonathan P. , Miskiewicz Anthony , Suthers Iain M. 
Published: June 2020

AbstractCoastal winds transport water masses and larval fish onshore or offshore which may influence estuarine recruitment, yet our understanding of the mechanism underlying this relationship is limited. Here, we combine datasets from a historical database of larval fish off southeast Australia with a high-resolution atmospheric reanalysis model to show that normalised abundance of coastally spawned larvae increased with weak to moderate upwelling favourable winds 14 days prior to sampling. The increase in abundance may reflect increased nutrient and plankton availability for larval fish. Normalised larval abundance decreased following strong upwelling favourable winds but increased after onshore (downwelling favourable) winds, due to wind-driven transport. By combining a commercial estuarine fisheries catch-rate dataset (4 species, 8 estuaries, 10 years) and the high-resolution atmospheric reanalysis model, we show that negative effects of upwelling favourable winds during the spawning period can be detected in lagged estuarine commercial fisheries catch rates (lagged by 2 – 8 years depending on species’ growth rates), potentially representing the same mechanism proposed for larval fish. Upwelling favourable winds in the southeast Australian region have increased since 1850 while onshore winds have decreased, which may reduce larval recruitment to estuaries. Coastal winds are likely an important factor for estuarine recruitment in the southeast Australian region and future research on the estuarine recruitment of fish should incorporate coastal winds.
Deep Learning for Virtual Screening: Five Reasons to Use ROC Cost Functions
Authors: Golkov Vladimir , Becker Alexander , Plop Daniel T. , Čuturilo Daniel , Davoudi Neda , Mendenhall Jeffrey , Moretti Rocco , Meiler Jens , Cremers Daniel 
Published: June 2020

AbstractComputer-aided drug discovery is an essential component of modern drug development. Therein, deep learning has become an important tool for rapid screening of billions of moleculesin silicofor potential hits containing desired chemical features. Despite its importance, substantial challenges persist in training these models, such as severe class imbalance, high decision thresholds, and lack of ground truth labels in some datasets. In this work we argue in favor of directly optimizing the receiver operating characteristic (ROC) in such cases, due to its robustness to class imbalance, its ability to compromise over different decision thresholds, certain freedom to influence the relative weights in this compromise, fidelity to typical benchmarking measures, and equivalence to positive/unlabeled learning. We also propose new training schemes (coherent mini-batch arrangement, and usage of out-of-batch samples) for cost functions based on the ROC, as well as a cost function based on the logAUC metric that facilitates early enrichment (i.e. improves performance at high decision thresholds, as often desired when synthesizing predicted hit compounds). We demonstrate that these approaches outperform standard deep learning approaches on a series of PubChem high-throughput screening datasets that represent realistic and diverse drug discovery campaigns on major drug target families.
Neuroinvasion of SARS-CoV-2 in human and mouse brain
Authors: Song Eric , Zhang Ce , Israelow Benjamin , Lu-Culligan Alice , Prado Alba Vieites , Skriabine Sophie , Lu Peiwen , Weizman Orr-El , Liu Feimei , Dai Yile , Szigeti-Buck Klara , Yasumoto Yuki , Wang Guilin , Castaldi Christopher , Heltke Jaime , Ng Evelyn , Wheeler John , Alfajaro Mia Madel , Levavasseur Etienne , Fontes Benjamin , Ravindra Neal G. , Van Dijk David , Mane Shrikant , Gunel Murat , Ring Aaron , Jaffar Kazmi Syed A. , Zhang Kai , Wilen Craig B , Horvath Tamas L. , Plu Isabelle , Haik Stephane , Thomas Jean-Leon , Louvi Angeliki , Farhadian Shelli F. , Huttner Anita , Seilhean Danielle , Renier Nicolas , Bilguvar Kaya , Iwasaki Akiko 
Published: June 2020

SummaryAlthough COVID-19 is considered to be primarily a respiratory disease, SARS-CoV-2 affects multiple organ systems including the central nervous system (CNS). Yet, there is no consensus whether the virus can infect the brain, or what the consequences of CNS infection are. Here, we used three independent approaches to probe the capacity of SARS-CoV-2 to infect the brain. First, using human brain organoids, we observed clear evidence of infection with accompanying metabolic changes in the infected and neighboring neurons. However, no evidence for the type I interferon responses was detected. We demonstrate that neuronal infection can be prevented either by blocking ACE2 with antibodies or by administering cerebrospinal fluid from a COVID-19 patient. Second, using mice overexpressing human ACE2, we demonstratein vivothat SARS-CoV-2 neuroinvasion, but not respiratory infection, is associated with mortality. Finally, in brain autopsy from patients who died of COVID-19, we detect SARS-CoV-2 in the cortical neurons, and note pathologic features associated with infection with minimal immune cell infiltrates. These results provide evidence for the neuroinvasive capacity of SARS-CoV2, and an unexpected consequence of direct infection of neurons by SARS-CoV-2.
Apple peel and flesh contain pro-neurogenic compounds
Authors: Ichwan Muhammad , Walker Tara L. , Nicola Zeina , Ludwig-Müller Jutta , Böttcher Christoph , Overall Rupert W. , Adusumilli Vijay S , Bulut Merve , Lugo-Hernández Enrique A. , Ramirez-Rodriguez Gerardo , Kempermann Gerd 
Published: June 2020

AbstractAs mammals evolved exposed to particular diets, naturally abundant compounds may have become part of the set of environmental co-determinants that shaped brain structure and function. Here we investigated whether bioactive factors found in apples directly affect hippocampal neural stem cells and promote neurogenesis in the adult mouse. Whereas the consumption of apple juiceper seneither altered adult hippocampal neurogenesis nor improved learning and memory, we did find specific direct effects of apple-derived factors on neural stem cell survival and differentiation. Our results revealed that quercetin, the most abundant flavanol in apple peel, was anti-proliferative at high concentrations but acted pro-neurogenically at low concentrations. This was confirmedin vivo, with intraperitoneally-delivered quercetin promoting survival and neuronal differentiation, without affecting proliferation, likely via the PI3 kinase-Akt and Nrf2-Keap1 pathways, respectively. Using a bio-assay-guided fractionation approach with high-resolution collision induced dissociation mass spectroscopy, we also identified additional pro-neurogenic compounds in apple flesh that were not related to flavonoids. In particular, we found that 3,5-dihydroxybenzoic acid, a weak agonist to the lactate receptor, significantly increased bothin vitroandin vivoneural precursor cell proliferation and neurogenesis. Altogether, this work shows that both flavonoids and 3,5-dihydroxybenzoic acid are pro-neurogenic, not only by activating precursor cell proliferation but also through promoting cell cycle exit, cellular survival, and neuronal differentiation.
rearrvisr: an R package to detect, classify, and visualize genome rearrangements
Authors: Lindtke Dorothea , Yeaman Sam 
Published: June 2020

AbstractThe identification of genome rearrangements is of direct relevance for understanding their potential impacts on evolution and disease. However, available methods that detect or visualize rearrangements from deviations in gene order do not map them onto a genome of interest, complicating downstream analysis. In this work, we presentrearrvisr, an R package that implements a novel algorithm for the identification and classification of rearrangements. In contrast to other software, it projects rearrangements onto a single genome, facilitating the localization of rearranged regions and estimation of their extent. We show that our tool achieves high precision and recall scores on simulated data, and illustrate the utility of our method by applying it to a data set generated from publicly availableDrosophilagenomes. The package is freely available from GitHub (https://github.com/dorolin/rearrvisr) and can be installed directly from R.
Distinct photooxidation-induced cell death pathways lead to selective killing of human breast cancer cells
Authors: dos Santos Ancély F. , Inague Alex , Arini Gabriel S. , Terra Letícia F. , Wailemann Rosangela A.M. , Pimentel André C. , Yoshinaga Marcos Y. , Silva Ricardo R. , Severino Divinomar , de Almeida Daria Raquel Q. , Gomes Vinícius M. , Bruni-Cardoso Alexandre , Terra Walter R. , Miyamoto Sayuri , Baptista Maurício S. , Labriola Leticia 
Published: June 2020

AbstractLack of effective treatments for aggressive breast cancer is still a major global health problem. We previously reported that Photodynamic Therapy using Methylene Blue as photosensitizer (MB-PDT) massively kills metastatic human breast cancer, marginally affecting healthy cells. In this study we aimed to unveil the molecular mechanisms behind MB-PDT effectiveness. Through lipidomic and biochemical approaches we demonstrated that MB-PDT efficiency and specificity relies on polyunsaturated fatty acids-enriched membranes and on the better capacity to deal with photooxidative damage displayed by non-tumorigenic cells. We found out that, in tumorigenic cells, lysosome membrane permeabilization is accompanied by ferroptosis and/or necroptosis. Our results broadened the understanding of MB-PDT-induced photooxidation mechanisms and specificity in breast cancer cells. Therefore, we demonstrated that efficient approaches could be designed on the basis of lipid composition and metabolic features for hard-to-treat cancers. The results further reinforce MB-PDT as a therapeutic strategy for highly aggressive human breast cancer cells.
Swarm Learning as a privacy-preserving machine learning approach for disease classification
Authors: Warnat-Herresthal Stefanie , Schultze Hartmut , Shastry Krishnaprasad Lingadahalli , Manamohan Sathyanarayanan , Mukherjee Saikat , Garg Vishesh , Sarveswara Ravi , Händler Kristian , Pickkers Peter , Aziz N. Ahmad , Ktena Sofia , Siever Christian , Kraut Michael , Desai Milind , Monnet Bruno , Saridaki Maria , Siegel Charles Martin , Drews Anna , Nuesch-Germano Melanie , Theis Heidi , Netea Mihai G. , Theis Fabian , Aschenbrenner Anna C. , Ulas Thomas , Breteler Monique M.B. , Giamarellos-Bourboulis Evangelos J. , Kox Matthijs , Becker Matthias , Cheran Sorin , Woodacre Michael S. , Goh Eng Lim , Schultze Joachim L. ,   German COVID-19 OMICS Initiative (DeCOI)
Published: June 2020

AbstractIdentification of patients with life-threatening diseases including leukemias or infections such as tuberculosis and COVID-19 is an important goal of precision medicine. We recently illustrated that leukemia patients are identified by machine learning (ML) based on their blood transcriptomes. However, there is an increasing divide between what is technically possible and what is allowed because of privacy legislation. To facilitate integration of any omics data from any data owner world-wide without violating privacy laws, we here introduce Swarm Learning (SL), a decentralized machine learning approach uniting edge computing, blockchain-based peer-to-peer networking and coordination as well as privacy protection without the need for a central coordinator thereby going beyond federated learning. Using more than 14,000 blood transcriptomes derived from over 100 individual studies with non-uniform distribution of cases and controls and significant study biases, we illustrate the feasibility of SL to develop disease classifiers based on distributed data for COVID-19, tuberculosis or leukemias that outperform those developed at individual sites. Still, SL completely protects local privacy regulations by design. We propose this approach to noticeably accelerate the introduction of precision medicine.
Order and disorder – an integrative structure of the full-length human growth hormone receptor
Authors: Kassem Noah , Araya-Secchi Raul , Bugge Katrine , Barclay Abigail , Steinocher Helena , Khondker Adree , Lenard Aneta J. , Bürck Jochen , Ulrich Anne S. , Pedersen Martin Cramer , Wang Yong , Rheinstädter Maikel C. , Pedersen Per Amstrup , Lindorff-Larsen Kresten , Arleth Lise , Kragelund Birthe B. 
Published: June 2020

ABSTRACTDespite the many physiological and pathophysiological functions of the human growth hormone receptor (hGHR), a detailed understanding of itsmodus operandiis hindered by the lack of structural information of the entire receptor at the molecular level. Due to its relatively small size (70 kDa) and large content of structural disorder (>50%), this membrane protein falls between the cracks of conventional high-resolution structural biology methods. Here, we study the structure of the full-length hGHR in nanodiscs with small angle-X-ray scattering (SAXS) as the foundation. We developed an approach in which we combined SAXS, X-ray diffraction and NMR spectroscopy obtained on the individual domains and integrated the data through molecular dynamics simulations to interpret SAXS data on the full-length hGHR in nanodiscs. The structure of the hGHR was determined in its monomeric state and provides the first experimental model of any full-length cytokine receptor in a lipid membrane. Combined, our results highlight that the three domains of the hGHR are free to reorient relative to each other, resulting in a broad structural ensemble. Our work exemplifies how integrating experimental data from several techniques computationally, may enable the characterization of otherwise inaccessible structures of membrane proteins with long disordered regions, a widespread phenomenon in biology. To understand orchestration of cellular signaling by disordered chains, the hGHR is archetypal and its structure emphasizes that we need to take a much broader, ensemble view on signaling.
A two-point IC50method for evaluating the biochemical potency of irreversible enzyme inhibitors
Authors: Kuzmič Petr 
Published: June 2020

AbstractIrreversible (covalent) enzyme inhibitors cannot be unambiguously ranked for biochemical potency by using IC50values determined at a single point in time, because the same IC50value could originate either from relatively low initial binding affinity accompanied by high chemical reactivity, or the other way around. To disambiguate the potency ranking of covalent inhibitors, here we describe a data-analytic procedure relying on two separate IC50values, determined at two different reaction times. In the case of covalent inhibitors following the two-step kinetic mechanismE+I⇌E·I→EI, the two IC50values alone can be used to estimate both the inhibition constant (Ki) as a measure of binding affinity and the inactivation rate constant (kinact) as a measure of chemical reactivity. In the case of covalent inhibitors following the one-step kinetic mechanismE+I→EI, a simple algebraic formula can be used to estimate the covalent efficiency constant (kinact/Ki) from a single experimental value of IC50. The two simplifying assumptions underlying the method are (1) zero inhibitor depletion, which implies that the inhibitor concentrations are always significantly higher than the enzyme concentration; and (2) constant reaction rate in the uninhibited control assay. The newly proposed method is validated by using a simulation study involving 64 irreversible inhibitors with covalent efficiency constants spanning seven orders of magnitude.