bluuebunny/crossref_metadata_2025_split huggingface dataset:
Urinary Sodium and Potassium, and Risk of Ischemic and Hemorrhagic Stroke (INTERSTROKE): A Case–Control Study
Authors: Judge Conor , O’Donnell Martin J , Hankey Graeme J , Rangarajan Sumathy , Chin Siu Lim , Rao-Melacini Purnima , Ferguson John , Smyth Andrew , Xavier Denis , Lisheng Liu , Zhang Hongye , Lopez-Jaramillo Patricio , Damasceno Albertino , Langhorne Peter , Rosengren Annika , Dans Antonio L , Elsayed Ahmed , Avezum Alvaro , Mondo Charles , Ryglewicz Danuta , Czlonkowska Anna , Pogosova Nana , Weimar Christian , Diaz Rafael , Yusoff Khalid , Yusufali Afzalhussein , Oguz Aytekin , Wang Xingyu , Lanas Fernando , Ogah Okechukwu S , Ogunniyi Adesola , Iversen Helle K , Malaga German , Rumboldt Zvonko , Oveisgharan Shahram , Al Hussain Fawaz , Yusuf Salim 
Published: November 2020

Abstract

BACKGROUND
Although low sodium intake (&lt;2 g/day) and high potassium intake (&gt;3.5 g/day) are proposed as public health interventions to reduce stroke risk, there is uncertainty about the benefit and feasibility of this combined recommendation on prevention of stroke.

METHODS
We obtained random urine samples from 9,275 cases of acute first stroke and 9,726 matched controls from 27 countries and estimated the 24-hour sodium and potassium excretion, a surrogate for intake, using the Tanaka formula. Using multivariable conditional logistic regression, we determined the associations of estimated 24-hour urinary sodium and potassium excretion with stroke and its subtypes.

RESULTS
Compared with an estimated urinary sodium excretion of 2.8–3.5 g/day (reference), higher (&gt;4.26 g/day) (odds ratio [OR] 1.81; 95% confidence interval [CI], 1.65–2.00) and lower (&lt;2.8 g/day) sodium excretion (OR 1.39; 95% CI, 1.26–1.53) were significantly associated with increased risk of stroke. The stroke risk associated with the highest quartile of sodium intake (sodium excretion &gt;4.26 g/day) was significantly greater (P &lt; 0.001) for intracerebral hemorrhage (ICH) (OR 2.38; 95% CI, 1.93–2.92) than for ischemic stroke (OR 1.67; 95% CI, 1.50–1.87). Urinary potassium was inversely and linearly associated with risk of stroke, and stronger for ischemic stroke than ICH (P = 0.026). In an analysis of combined sodium and potassium excretion, the combination of high potassium intake (&gt;1.58 g/day) and moderate sodium intake (2.8–3.5 g/day) was associated with the lowest risk of stroke.

CONCLUSIONS
The association of sodium intake and stroke is J-shaped, with high sodium intake a stronger risk factor for ICH than ischemic stroke. Our data suggest that moderate sodium intake—rather than low sodium intake—combined with high potassium intake may be associated with the lowest risk of stroke and expected to be a more feasible combined dietary target.
Twenty-Five-Year Changes in Office and Ambulatory Blood Pressure: Results From the Coronary Artery Risk Development in Young Adults (CARDIA) Study
Authors: Bundy Joshua D , Jaeger Byron C , Huffman Mark D , Knox Sarah S , Thomas S Justin , Shimbo Daichi , Booth John N , Lewis Cora E , Edwards Lloyd J , Schwartz Joseph E , Muntner Paul 
Published: November 2020

AbstractBACKGROUNDBlood pressure (BP) measured in the office setting increases from early through later adulthood. However, it is unknown to what extent out-of-office BP derived via ambulatory BP monitoring (ABPM) increases over time, and which participant characteristics and risk factors might contribute to these increases.METHODSWe assessed 25-year change in office- and ABPM-derived BP across sex, race, diabetes mellitus (DM), and body mass index (BMI) subgroups in the Coronary Artery Risk Development in Young Adults study using multivariable-adjusted linear mixed effects models.RESULTSWe included 288 participants who underwent ABPM at the Year 5 Exam (mean [SD] age, 25.1 [3.7]; 45.8% men) and 455 participants who underwent ABPM at the Year 30 Exam (mean [SD] age, 49.5 [3.7]; 42.0% men). Office, daytime, and nighttime systolic BP (SBP) increased 12.8 (95% confidence interval [CI], 7.6–17.9), 14.7 (95% CI, 9.7–19.8), and 16.6 (95% CI, 11.4–21.8) mm Hg, respectively, over 25 years. Office SBP increased 6.5 (95% CI, 2.3–10.6) mm Hg more among black compared with white participants. Daytime SBP increased 6.3 (95% CI, 0.2–12.4) mm Hg more among participants with a BMI ≥25 vs. &lt;25 kg/m2. Nighttime SBP increased 4.7 (95% CI, 0.5–8.9) mm Hg more among black compared with white participants, and 17.3 (95% CI, 7.2–27.4) mm Hg more among participants with vs. without DM.CONCLUSIONSOffice- and ABPM-derived BP increased more from early through middle adulthood among black adults and participants with DM and BMI ≥25 kg/m2.
The Destiny of Multiple Domain Amnesic Mild Cognitive Impairment: Effect of Alternative Neuropsychological Definitions and Their Adjunctive Role in Respect of Memory Impairment
Authors: Piccininni Chiara , Quaranta Davide , Gainotti Guido , Lacidogna Giordano , Guglielmi Valeria , Giovannini Silvia , Marra Camillo 
Published: November 2020

Abstract

Objective
Mild cognitive impairment is the main risk factor of dementia. Previous evidence has claimed that subjects with memory disturbances associated with impairment of other cognitive domains (multiple domain amnesic MCI) are at the highest risk of developing dementia. To date, a shared definition of amnesic MCI multiple domain (aMCI-MD) is still lacking.

Method
163 subjects with aMCI were enrolled and followed-up for 2 years. They underwent a baseline comprehensive neuropsychological battery. The cut-off point for each test was set at 1, 1.5, and 2 SD below the mean obtained in normative studies; aMCI-MD was defined as the occurrence of abnormal scores on at least one, two, or three tests not assessing memory. The Episodic Memory Score (EMS), that measures the severity of memory impairment, was determined. Logistic regressionand Cox’s proportional hazard risk models were carried out. The adjunctive effect of the definitions of aMCI-MD on the severity of memory impairment was assessed.

Results
Fifty-four subjects progressed to dementia. Only restrictive definitions of aMCI-MD (at least three tests below 1.5 SD; at least two tests below 2 SD) predicted conversion to dementia in both logistic regression and survival analysis. None of the conditions showed a significant adjunctive effect on the EMS.

Conclusions
The predictive effect of impairment in tests assessing cognitive domains other than memory depends on its psychometric definition. The use of a restrictive definition would be of some usefulness, but the adjunctive effect of such a definition on an integrated analysis of memory impairment may be questionable.
Flexible habitat choice by aphids exposed to multiple cues reflecting present and future benefits
Authors: Yin Wandong , Xue Qi , Tian Baoliang , Yang Shujian , Li Zhengying , Chen Zhaozhao , Ryan Michael J , Hoffmann Ary A 
Published: November 2020

Abstract
Mothers choose suitable habitats for laying offspring to maximize fitness. Because habitat quality varies in space and time, mothers gather information to choose among available habitats through multiple cues reflecting different aspects of habitat quality at present and in the future. However, it is unclear how females assess and integrate different cues associated with current rewards and future safety to optimize oviposition/larviposition decisions, especially across small spatial scales. Here, we tested the individual and interactive effects of leaf surface, leaf orientation, and leaf bending direction on larviposition site choice and fitness benefits of wheat aphids (Metopolophium dirhodum) within individual leaves. We found that females preferred upper over lower surfaces for gaining current food-related rewards, downward- over upward-facing surfaces for avoiding potential abiotic risks, and sunken over protruding surfaces for avoiding potential biotic risks. When facing conflicting cues during larviposition, females preferred downward-facing/sunken surfaces over upper surfaces, suggesting that females prioritize potential safety at the cost of current rewards during decision making. Most importantly, our combined-cue experiments showed females still assessed secondary cues (i.e., the upper surface) when first-ranked cues (i.e., the downward-facing/sunken surface) are available, even though females only gained relatively small fitness rewards through secondary cues, and females can integrate different cues associated with current rewards and potential safety in a multiplicative way to make flexible and complex larviposition decisions. Overall, our findings provide new insights into how animals collect and process multi-cue information associated with current rewards and potential safety to maximize fitness at small spatial scales.
Target shortage and less explored multiple targeting: hurdles in the development of novel antifungals but overcome/addressed effectively through structural bioinformatics
Authors: Jha Anubhuti , Vimal Archana , Kumar Awanish 
Published: November 2020

Abstract
Billions of people are affected by fungal infection worldwide, which is a major cause of morbidity and mortality in humans. Regardless of development in the field of antifungal therapeutics over the last three decades, multidrug resistance and limited efficacy of available antifungal drugs are very prominent and still a great hurdle in the patient treatment. The current antifungal pipeline is dry, which is needed to be strengthened. Although several strategies have been implemented over time to discover novel promising antifungal leads, but very little emphasis has been given to address the gap of fungal target identification. Undeniably, the need for identifying novel cellular fungal targets is as vital as discovering novel antifungal leads and a structural bioinformatics approach could be an effective strategy in this regard. To address the issue, we have performed in silico screening to identify a few potent multiple targeting ligands and their respective antifungal targets. Thus, we offer a perspective on the phenomena of ‘target shortage’ and least explored ‘multiple targeting’ being the most underrated challenges in antifungal drug discovery. ‘Structural bioinformatics’ could be an effective approach in the recognition of new/innovative antifungal target and identification/development of novel antifungal lead molecule aiming multiple molecular targets of the fungal pathogen.
Pathogenic gene prediction based on network embedding
Authors: Liu Yang , Guo Yuchen , Liu Xiaoyan , Wang Chunyu , Guo Maozu 
Published: November 2020

Abstract
In disease research, the study of gene–disease correlation has always been an important topic. With the emergence of large-scale connected data sets in biology, we use known correlations between the entities, which may be from different sets, to build a biological heterogeneous network and propose a new network embedded representation algorithm to calculate the correlation between disease and genes, using the correlation score to predict pathogenic genes. Then, we conduct several experiments to compare our method to other state-of-the-art methods. The results reveal that our method achieves better performance than the traditional methods.
The impact of structural bioinformatics tools and resources on SARS-CoV-2 research and therapeutic strategies
Authors: Waman Vaishali P , Sen Neeladri , Varadi Mihaly , Daina Antoine , Wodak Shoshana J , Zoete Vincent , Velankar Sameer , Orengo Christine 
Published: November 2020

AbstractSARS-CoV-2 is the causative agent of COVID-19, the ongoing global pandemic. It has posed a worldwide challenge to human health as no effective treatment is currently available to combat the disease. Its severity has led to unprecedented collaborative initiatives for therapeutic solutions against COVID-19. Studies resorting to structure-based drug design for COVID-19 are plethoric and show good promise. Structural biology provides key insights into 3D structures, critical residues/mutations in SARS-CoV-2 proteins, implicated in infectivity, molecular recognition and susceptibility to a broad range of host species. The detailed understanding of viral proteins and their complexes with host receptors and candidate epitope/lead compounds is the key to developing a structure-guided therapeutic design.Since the discovery of SARS-CoV-2, several structures of its proteins have been determined experimentally at an unprecedented speed and deposited in the Protein Data Bank. Further, specialized structural bioinformatics tools and resources have been developed for theoretical models, data on protein dynamics from computer simulations, impact of variants/mutations and molecular therapeutics.Here, we provide an overview of ongoing efforts on developing structural bioinformatics tools and resources for COVID-19 research. We also discuss the impact of these resources and structure-based studies, to understand various aspects of SARS-CoV-2 infection and therapeutic development. These include (i) understanding differences between SARS-CoV-2 and SARS-CoV, leading to increased infectivity of SARS-CoV-2, (ii) deciphering key residues in the SARS-CoV-2 involved in receptor–antibody recognition, (iii) analysis of variants in host proteins that affect host susceptibility to infection and (iv) analyses facilitating structure-based drug and vaccine design against SARS-CoV-2.
Deep inverse reinforcement learning for structural evolution of small molecules
Authors: Agyemang Brighter , Wu Wei-Ping , Addo Daniel , Kpiebaareh Michael Y , Nanor Ebenezer , Roland Haruna Charles 
Published: November 2020

Abstract
The size and quality of chemical libraries to the drug discovery pipeline are crucial for developing new drugs or repurposing existing drugs. Existing techniques such as combinatorial organic synthesis and high-throughput screening usually make the process extraordinarily tough and complicated since the search space of synthetically feasible drugs is exorbitantly huge. While reinforcement learning has been mostly exploited in the literature for generating novel compounds, the requirement of designing a reward function that succinctly represents the learning objective could prove daunting in certain complex domains. Generative adversarial network-based methods also mostly discard the discriminator after training and could be hard to train. In this study, we propose a framework for training a compound generator and learn a transferable reward function based on the entropy maximization inverse reinforcement learning (IRL) paradigm. We show from our experiments that the IRL route offers a rational alternative for generating chemical compounds in domains where reward function engineering may be less appealing or impossible while data exhibiting the desired objective is readily available.
ARBitR: an overlap-aware genome assembly scaffolder for linked reads
Authors: Hiltunen Markus , Ryberg Martin , Johannesson Hanna 
Published: November 2020

Abstract

Summary
Linked genomic sequencing reads contain information that can be used to join sequences together into scaffolds in draft genome assemblies. Existing software for this purpose performs the scaffolding by joining sequences with a gap between them, not considering potential overlaps of contigs. We developed ARBitR to create scaffolds where overlaps are taken into account and show that it can accurately recreate regions where draft assemblies are broken.

Availability and implementation
ARBitR is written and implemented in Python3 for Unix-based operative systems. All source code is available at https://github.com/markhilt/ARBitR under the GNU General Public License v3.

Supplementary information
Supplementary data are available at Bioinformatics online.
eMPRess: a systematic cophylogeny reconciliation tool
Authors: Santichaivekin Santi , Yang Qing , Liu Jingyi , Mawhorter Ross , Jiang Justin , Wesley Trenton , Wu Yi-Chieh , Libeskind-Hadas Ran 
Published: November 2020

Abstract

Summary
We describe eMPRess, a software program for phylogenetic tree reconciliation under the duplication-transfer-loss model that systematically addresses the problems of choosing event costs and selecting representative solutions, enabling users to make more robust inferences.

Availability and implementation
eMPRess is freely available at http://www.cs.hmc.edu/empress.

Supplementary information
Supplementary data are available at Bioinformatics online.
An iterative approach to detect pleiotropy and perform Mendelian Randomization analysis using GWAS summary statistics
Authors: Zhu Xiaofeng , Li Xiaoyin , Xu Rong , Wang Tao 
Published: November 2020

Abstract

Motivation
The overall association evidence of a genetic variant with multiple traits can be evaluated by cross-phenotype association analysis using summary statistics from genome-wide association studies. Further dissecting the association pathways from a variant to multiple traits is important to understand the biological causal relationships among complex traits.

Results
Here, we introduce a flexible and computationally efficient Iterative Mendelian Randomization and Pleiotropy (IMRP) approach to simultaneously search for horizontal pleiotropic variants and estimate causal effect. Extensive simulations and real data applications suggest that IMRP has similar or better performance than existing Mendelian Randomization methods for both causal effect estimation and pleiotropic variant detection. The developed pleiotropy test is further extended to detect colocalization for multiple variants at a locus. IMRP will greatly facilitate our understanding of causal relationships underlying complex traits, in particular, when a large number of genetic instrumental variables are used for evaluating multiple traits.

Availability and implementation
The software IMRP is available at https://github.com/XiaofengZhuCase/IMRP. The simulation codes can be downloaded at http://hal.case.edu/∼xxz10/zhu-web/ under the link: MR Simulations software.

Supplementary information
Supplementary data are available at Bioinformatics online.
Depression, dementia and immune dysregulation
Authors: Hayley Shawn , Hakim Antoine M , Albert Paul R 
Published: November 2020

AbstractMajor depression is a prevalent illness that increases the risk of several neurological conditions. These include stroke, cardiovascular disease, and dementia including Alzheimer’s disease. In this review we ask whether certain types of depression and associated loneliness may be a harbinger of cognitive decline and possibly even dementia. We propose that chronic stress and inflammation combine to compromise vascular and brain function. The resulting increases in proinflammatory cytokines and microglial activation drive brain pathology leading to depression and mild cognitive impairment, which may progress to dementia. We present evidence that by treating the inflammatory changes, depression can be reversed in many cases. Importantly, there is evidence that anti-inflammatory and antidepressant treatments may reduce or prevent dementia in people with depression. Thus, we propose a model in which chronic stress and inflammation combine to increase brain permeability and cytokine production. This leads to microglial activation, white matter damage, neuronal and glial cell loss. This is first manifest as depression and mild cognitive impairment, but can eventually evolve into dementia. Further research may identify clinical subgroups with inflammatory depression at risk for dementia. It would then be possible to address in clinical trials whether effective treatment of the depression can delay the onset of dementia.
Olfactory Dysfunction Predicts the Development of Depression in Older US Adults
Authors: Eliyan Yazan , Wroblewski Kristen E , McClintock Martha K , Pinto Jayant M 
Published: November 2020

AbstractNeuroanatomic connections link the olfactory and limbic systems potentially explaining an association between olfactory dysfunction and depression. Some previous studies have demonstrated that olfactory dysfunction is associated with increased depressive symptoms. However, these studies were cross-sectional and unable to establish which develops first. We used longitudinal data to determine if impaired odor identification increased subsequent depressive symptoms or vice versa. We assessed olfaction and depression in the National Social Life, Health, and Aging Project, a nationally representative, 15-year longitudinal study of older US adults. Olfaction was measured using a validated odor identification test (Sniffin’ Sticks). Depressive symptoms were measured using a modified version of the validated Center for Epidemiological Studies Depression Scale. Multivariable logistic regression models examined the temporal relationships between developing olfactory dysfunction and depression while accounting for demographics, disease comorbidities, alcohol use, smoking, and cognition. Older adults with olfactory dysfunction had concurrent frequent depressive symptoms (odds ratio [OR] = 1.20, 95% confidence interval [CI] = 1.00–1.43). Among healthy adults at baseline, those who had olfactory dysfunction were more likely to develop frequent depressive symptoms 5 or 10 years later (OR = 2.22, 95% CI = 1.13–4.37). Conversely, those with frequent depressive symptoms at baseline were not more likely to develop olfactory dysfunction 5 or 10 years later. We show for the first time that olfactory dysfunction predicts subsequent development of depression in older US adults. These data support screening for depression in older adults with chemosensory impairment and set the stage for disentangling the relationship between olfaction and depression.
Safety and Efficacy of CR6261 in an Influenza A H1N1 Healthy Human Challenge Model
Authors: Han Alison , Czajkowski Lindsay , Rosas Luz Angela , Cervantes-Medina Adriana , Xiao Yongli , Gouzoulis Monica , Lumbard Keith , Hunsberger Sally , Reed Susan , Athota Rani , Baus Holly Ann , Lwin Amy , Sadoff Jerald , Taubenberger Jeffery K , Memoli Matthew J 
Published: November 2020

Abstract

Background
It is imperative to identify new targets for improved vaccines and therapeutics against influenza. One such target is the relatively conserved stalk region of the influenza A hemagglutinin (HA) surface protein.

Methods
We conducted a randomized, double-blind, phase 2, placebo-controlled trial of a monoclonal antibody that targets the HA stalk (CR6261) in a H1N1pdm09 healthy volunteer human challenge model. A single 50 mg/kg dose of CR6261 was infused 24 hours after challenge. The primary efficacy outcome was area under the curve (AUC) of viral RNA detection over time.

Results
Ninety-one healthy volunteers were randomized and underwent influenza challenge; 49 received CR6261 and 42 received placebo. CR6261 had no statistically significant effect on AUC (AUC, 48.56 log [copies/mL] × days, interquartile range [IQR], 202 vs AUC, 25.53 log [copies/mL] × days, IQR, 155; P = .315) and no clinically significant effect on influenza disease measures including number of symptoms, duration of symptoms, or inFLUenza Patient-Reported Outcome (FLU-PRO) scores. Preexisting anti-NA antibody titers were most predictive of reduced influenza disease. CR6261 reached a mean peak serum concentration of 1 × 106 ng/mL 15 minutes after infusion and a mean peak of 5.97 × 102 ng/mL in the nasal mucosa 2–3 days after infusion.

Conclusions
The results of this study suggest that a monoclonal anti-stalk approach to prevent or treat influenza infection may be limited in efficacy. Future approaches should consider including and evaluating anti-stalk antibodies as part of a multifaceted strategy rather than as a stand-alone therapeutic.

Clinical Trials Registration
NCT02371668.