bluuebunny/crossref_metadata_2025_split huggingface dataset:
Toward a standard pathological and molecular characterization of recurrent glioma in adults: a Response Assessment in Neuro-Oncology effort
Authors: Haider Ali S , van den Bent Martin , Wen Patrick Y , Vogelbaum Michael A , Chang Susan , Canoll Peter D , Horbinski Craig M , Huse Jason T 
Published: December 2019

AbstractRegardless of subtype, diffuse gliomas of adulthood are characterized by inexorable progression through treatment. Cancer recurrence in the context of therapy is by no means unique to gliomas. For many tumors residing outside the central nervous system (CNS), tissue-based analyses are routinely employed to document the molecular and cellular features of disease recurrence. Such interventions are inconsistently applied for gliomas, however, and lack rigorous standardization when they are. While many of the reasons underlying these discrepancies reflect pragmatic realities inherent to CNS disease, the suboptimal employment of histological and molecular assessment at recurrence nevertheless represents a missed opportunity to proactively guide patient management and increase knowledge. Herein, we address this quandary by pairing a succinct description of the histological, biological, and molecular characteristics of recurrent glioma with recommendations for how to better standardize and implement quality pathological assessment into patient management. We hope this review will prompt thoughtful revision of standard operating procedures to maximize the utility of glioma re-biopsy.
Irregular sleep and event schedules are associated with poorer self-reported well-being in US college students
Authors: Fischer Dorothee , McHill Andrew W , Sano Akane , Picard Rosalind W , Barger Laura K , Czeisler Charles A , Klerman Elizabeth B , Phillips Andrew J K 
Published: December 2019

Abstract

Study Objectives
Sleep regularity, in addition to duration and timing, is predictive of daily variations in well-being. One possible contributor to changes in these sleep dimensions are early morning scheduled events. We applied a composite metric—the Composite Phase Deviation (CPD)—to assess mistiming and irregularity of both sleep and event schedules to examine their relationship with self-reported well-being in US college students.

Methods
Daily well-being, actigraphy, and timing of sleep and first scheduled events (academic/exercise/other) were collected for approximately 30 days from 223 US college students (37% females) between 2013 and 2016. Participants rated well-being daily upon awakening on five scales: Sleepy–Alert, Sad–Happy, Sluggish–Energetic, Sick–Healthy, and Stressed–Calm. A longitudinal growth model with time-varying covariates was used to assess relationships between sleep variables (i.e. CPDSleep, sleep duration, and midsleep time) and daily and average well-being. Cluster analysis was used to examine relationships between CPD for sleep vs. event schedules.

Results
CPD for sleep was a significant predictor of average well-being (e.g. Stressed–Calm: b = −6.3, p &lt; 0.01), whereas sleep duration was a significant predictor of daily well-being (Stressed–Calm, b = 1.0, p &lt; 0.001). Although cluster analysis revealed no systematic relationship between CPD for sleep vs. event schedules (i.e. more mistimed/irregular events were not associated with more mistimed/irregular sleep), they interacted upon well-being: the poorest well-being was reported by students for whom both sleep and event schedules were mistimed and irregular.

Conclusions
Sleep regularity and duration may be risk factors for lower well-being in college students. Stabilizing sleep and/or event schedules may help improve well-being.

Clinical Trial Registration
NCT02846077.
Informing Pharmacokinetic Models with Physiological Data: Oral Population Modeling of L-Serine in Humans
Authors: Bosley J. R. , Björnson Elias , Zhang Cheng , Turkez Hasan , Nielsen Jens , Uhlen Mathias , Boren Jan , Mardinoglu Adil 
Published: December 2019

AbstractTo determine how to set optimal oral L-serine (serine) dose levels for a clinical trial, existing literature was surveyed. Data sufficient to set the dose was inadequate, and so a (n=10) Phase I-A calibration trial was performed, administering serine with and without other oral agents. We analyzed the trial and the literature data using pharmacokinetic (PK) modeling and statistical analysis. The therapeutic goal is to modulate specific serine-related metabolic pathways in the liver using the lowest possible dose which gives the desired effect since the upper bound was expected to be limited by toxicity. In this paper, we first review relevant literature, describe the calibration trial and resulting data, and present the results of modeling from the trial. Serine is a non-essential amino acid that is nonetheless present at a base level in blood from both dietary sources and endogenous production. Serine is consumed by several pathways. A standard PK approach, in which a common model structure was selected using a fit to data, yielded a model with a single central compartment corresponding to plasma, clearance from that compartment, and an endogenous source of serine. The lack of intravenous data normally prevents independent determination of bioavailability and volume of distribution, however, under some assumptions about endogenous synthesis and use, values could be estimated. The model was poorly conditioned but did give consistent estimates. To improve conditioning, a parametric structure was changed to estimate ratios (bioavailability over volume, for example). Model fit quality was improved and the uncertainty in estimated parameters was reduced. Because of the particular interest in the fate of serine, the model was used to estimate whether serine is consumed in the gut, absorbed by the liver, or entered the blood in either a free state, or in a protein- or tissue-bound state that is not measured by our assay. The PK model structure was set up to represent relevant physiology, and this quantitative systems biology approach allowed a broader set of physiological data to be used to narrow parameter and prediction confidence intervals, and to better understand the biological meaning of the data. The model results allowed us to determine the optimal human dose for future trials, including a trial design component including IV and tracer studies. A key contribution is that we were able to use human physiological data from the literature to inform the PK model and to set reasonable bounds on parameters, and to improve model conditioning. Leveraging literature data produced a more predictive, useful model.
Precision Multiparameter Tracking of Inflammation on Timescales of Hours to Years Using Serial Dried Blood Spots
Authors: Anderson N. Leigh , Razavi Morteza , Pope Matthew E. , Yip Richard , Cameron L. C. , Bassini-Cameron Adriana , Pearson Terry W. 
Published: December 2019

AbstractHigh-frequency longitudinal tracking of inflammation using dried blood microsamples provides a new window for personalized monitoring of infections, chronic inflammatory disease, and clinical trials of anti-inflammatory drugs. Using 1,662 dried blood spot samples collected by 16 subjects over periods of weeks to years, we studied the behavior of 12 acute phase response (APR) and related proteins in inflammation events correlated with infection, vaccination, surgery, intense exercise and Crohn’s disease. Proteins were measured using SISCAPA mass spectrometry and normalized to constant plasma volume using low-variance proteins, generating high precision within-person biomarker trajectories with well-characterized personal baselines. The results shed new light on the dynamic regulation of APR proteins and offer a new approach to visualization of multidimensional inflammation trajectories.
Risk of schizophrenia and bipolar disorder in patients with multiple sclerosis: record-linkage studies
Authors: Meier Ute-Christiane , Ramagopalan Sreeram V , Goldacre Michael J , Goldacre Raph 
Published: December 2019

AbstractBackgroundThe epidemiology of psychiatric comorbidity in multiple sclerosis (MS) remains poorly understood.ObjectiveWe aimed to determine the risk of schizophrenia and bipolar disorder in MS patients.Material and MethodsRetrospective cohort analyses were performed using an all-England national linked Hospital Episode Statistics (HES) dataset (1999-2016) and to determine whether schizophrenia or bipolar disorder are more commonly diagnosed subsequently in people with MS (n=128,194), and whether MS is more commonly diagnosed subsequently in people with schizophrenia (n=384,188) or bipolar disorder (n=203,592), than would be expected when compared with a reference cohort (∼15 million people) after adjusting for age and other factors. Adjusted hazard ratios (aHRs) were calculated using Cox proportional hazards models.ResultsFindings were dependent on whether the index and subsequent diagnoses were selected as the primary reason for hospital admission or were taken from anywhere on the hospital record. When searching for diagnoses anywhere on the hospital record, there was a significantly elevated risk of subsequent schizophrenia (aHR 1.51, 95% confidence interval (CI) 1.40 to 1.60) and of bipolar disorder (aHR 1.14, 95% CI 1.04 to 1.24) in people with prior-recorded MS and of subsequent MS in people with prior-recorded schizophrenia (aHR 1.26, 1.15-1.37) or bipolar disorder (aHR 1.73, 1.57-1.91), but most of these associations were reduced to null when analyses were confined to diagnoses recorded as the primary reason for admission.ConclusionFurther research is needed to investigate the potential association between MS and schizophrenia and/or bipolar disorder as it may shed light on underlying pathophysiology and help identify potential shared risk factors.
What is the best evidence for graft choice in ACL reconstruction? Protocol for a systematic review and network meta-analysis
Authors: Habibi Junaid , Zakharia Alexander , Woolnough Taylor , Axelrod Daniel , de SA Darren 
Published: December 2019

ABSTRACTIntroductionAnterior cruciate ligament (ACL) reconstruction is one of the most commonly performed sports medicine procedures. A variety of grafts are currently used for reconstruction, including both allograft and autograft. Despite numerous meta-analyses, there exists no high-quality quantitative synthesis of all randomized controlled trial (RCT) data on graft choice.ObjectiveTo identify the optimal graft choice for ACL reconstruction by performing the first systematic review and network meta-analysis (NMA) to include both functional outcomes and complications.MethodsMultiple digital databases including MEDLINE, Embase, and CENTRAL will be searched independently and in duplicate for RCTs randomizing graft choice in ACL reconstruction in skeletally mature patients. A Bayesian framework with a random-effects model will be used for NMA. Surface under the cumulative ranking curve (SUCRA) values will be used to generate a rank list for each outcome. Results will be reported as mean differences (MD) (or standardized mean difference, if necessary) or relative risk (RR) with 95% credible intervals (CI). Comparisons will be inferred to be statistically significant if the 95% CI of MD does not cross zero or if the 95% CI of relative risk does not cross one. Studies will be assessed for quality using the Cochrane risk of bias assessment tool. Quality of evidence for each network comparison will be determined as per the Grades of Recommendation, Assessment, Development and Evaluation (GRADE) approach for network meta-analyses. This NMA will be reported according to the PRISMA extension statement for network meta-analysesOutcomes of interestFunctional outcomes of interest including range of motion, return to activity/sport, and IKDC, Lysholm, Tegner, ACL-QOL, and KOOS scores. Persistent laxity as measured by Lachman, Pivot-shift, side-to-side, and measured laxity (e.g. KT-1000) will also be analyzed. Complications (e.g. infection, graft failure, donor site pain), tunnel osteolysis, and failure (including but not limited to graft rupture and/or persistent laxity) will be compared between grafts.Relevance/ImpactThis NMA will be the first high-quality syntheses of all randomized evidence regarding graft choice in ACL reconstruction. As the first analysis to compare all major graft choices independently, it will be used to inform surgeon-patient decision making. It has the reasonable possibility of changing clinical practice.
Clustering of susceptible individuals within households can drive an outbreak: an individual-based model exploration
Authors: Kuylen Elise , Willem Lander , Broeckhove Jan , Beutels Philippe , Hens Niel 
Published: December 2019

ABSTRACTWhen estimating important measures such as the herd immunity threshold, and the corresponding efforts required to eliminate measles, it is often assumed that susceptible individuals are uniformly distributed throughout populations. However, unvaccinated individuals may be clustered in a variety of ways, including by geographic location, by age, in schools, or in households. Here, we investigate to which extent different levels of within-household clustering of susceptible individuals may impact the risk and persistence of measles outbreaks. To this end, we apply an individual-based model, Stride, to a population of 600,000 individuals, using data from Flanders, Belgium. We compare realistic scenarios regarding the distribution of susceptible individuals within households in terms of their impact on epidemiological measures for outbreak risk and persistence. We find that higher levels of within-household clustering of susceptible individuals increase the risk, size and persistence of measles outbreaks. Ignoring within-household clustering thus leads to underestimations of measles elimination and outbreak mitigation efforts.
Probability waves: pattern-based p-value correction in mass univariate analysis between two event-related potential waves
Authors: Abramov Dimitri Marques 
Published: December 2019

AbstractBackgroundMethods for p-value correction are criticized for either increasing Type II error or improperly reducing Type I error. This problem is worse when dealing with hundreds or thousands of paired comparisons between waves or images which are performed point-to-point. This text considers patterns in probability vectors resulting from multiple point-to-point comparisons between two ERP waves (mass univariate analysis) to correct p-values. These patterns (probability waves) mirror ERP waveshapes and might be indicators of consistency in statistical differences.New methodIn order to compute and analyze these patterns, we convoluted the decimal logarithm of the probability vector (p’) using a Gaussian vector with size compatible to the ERP periods observed. For verify consistency of this method, we also calculated mean amplitudes of late ERPs from Pz (P300 wave) and O1 electrodes in two samples, respectively of typical and ADHD subjects.Resultsthe present method reduces the range of p’-values that did not show covariance with neighbors (that is, that are likely random differences, type I errors), while preserving the amplitude of probability waves, in accordance to difference between respective mean amplitudes.Comparison with existing methodsthe positive-FDR resulted in a different profile of corrected p-values, which is not consistent with expected results or differences between mean amplitudes of the analyzed ERPs.Conclusionthe present new method seems to be biological and statistically more suitable to correct p-values in mass univariate analysis of ERP waves.
Honeybees adjust colour preferences in response to concurrent social information from conspecifics and heterospecifics
Authors: Romero-González José E , Solvi Cwyn , Chittka Lars 
Published: December 2019

AbstractBees efficiently learn asocial and social cues to optimise foraging from fluctuating floral resources. However, it remains unclear how bees respond to divergent sources of social information, and whether such social cues might modify bees’ natural preferences for non-social cues (e.g. flower colour), hence affecting foraging decisions. Here, we investigated honeybees’ (Apis mellifera) inspection and choices of unfamiliar flowers based on both natural colour preferences and simultaneous foraging information from conspecifics and heterospecifics. Individual honeybees’ preferences for flowers were recorded when the reward levels of a learned flower type had declined and novel-coloured flowers were available where they would find either no social information or one conspecific and one heterospecific (Bombus terrestris), each foraging from a different coloured flower (magenta or yellow). Honeybees showed a natural preference for magenta flowers. Honeybees modified their inspection of both types of flowers in response to conspecific and heterospecific social information. The presence of either demonstrator on the less-preferred yellow flower increased honeybees’ inspection of yellow flowers. Conspecific social information influenced observers’ foraging choices of yellow flowers, thus outweighing their original preference for magenta flowers. This effect was not elicited by heterospecific social information. Our results indicate that flower colour preferences of honeybees are rapidly adjusted in response to conspecific social information, which in turn is preferred over heterospecific information, possibly favouring the transmission of adaptive foraging information within species.
Detection for suspected Genetically Modified Maize and Soybean crops in the selcted places of Ethiopia using PCR machine
Authors: Admas Adugnaw , Melese Smegnew , Genetu Amare 
Published: December 2019

AbstractDetection of genetically modified organisms (GMOs) in crops is an important issue for all the subjects involved in seed quality control and customer’s right. Due to the increasing number of GMOs research and development activity in the globe during the past few years, it has become necessary to screen and regulate highely practiced GMO crops. In this study, following the extraction of genomic DNA from agriculture farming land and commercial areas collected samples that suspected for GMOs such as Soybean and maize crops, the recombinant DNA target sequences were targeted to detect for transgene such as CaMV35s gene using thermal cycler Polymerase Chain Reaction (PCR). In addition, for positive control taxone specficInvertaseandLectinegene of maize and soybean have done. Based on the gel electrophoresis results,Invertase and Lectinegene events were detected in all maize and soybean samples respectively. How ever, fortunately in all collected samples of maize and soybean in different places of the countery trans-genes were not detected. Finally, this reserch result concludes that in the studied area soybean and maize crops are GMO free.
Cortical control of virtual self-motion using task-specific subspaces
Authors: Schroeder Karen E , Perkins Sean M , Wang Qi , Churchland Mark M 
Published: December 2019

AbstractBrain-machine interfaces (BMIs) for reaching have enjoyed continued performance improvements, yet there remains significant need for BMIs that control other movement classes. Recent scientific findings suggest that the intrinsic covariance structure of neural activity depends strongly on movement class, potentially necessitating different decode algorithms across classes. To address this, we developed a self-motion BMI based on cortical activity as monkeys performed non-reaching arm movements: cycling a hand-held pedal to progress along a virtual track. Unlike during reaching, we found no high-variance dimensions that directly correlated with to-be-decoded variables. Yet we could decode a single variable – self-motion – by non-linearly leveraging structure that spanned many high-variance neural dimensions. Resulting online BMI-control success rates approached those during manual control. These findings make two broad points regarding how to build decode algorithms that harmonize with the empirical structure of neural activity in motor cortex. First, even when decoding from the same cortical region (e.g., arm-related motor cortex) different movement classes may need to employ very different strategies. Although correlations between neural activity and hand velocity are prominent during reaching tasks, they are not a fundamental property of motor cortex and cannot be counted on to be present in general. Second, although one generally desires a low-dimensional readout, it can be beneficial to leverage a multi-dimensional high-variance subspace. Fully embracing this approach requires highly non-linear approaches tailored to the task at hand, but can produce near-native levels of performance.Significance StatementMany BMI decoders have been constructed for controlling movements normally performed with the arm. Yet it is unclear how these will function beyond the reach-like scenarios where they were developed. Existing decoders implicitly assume that neural covariance structure, and correlations with to-be-decoded kinematic variables, will be largely preserved across tasks. We find that the correlation between neural activity and hand kinematics, a feature typically exploited when decoding reach-like movements, is essentially absent during another task performed with the arm: cycling through a virtual environment. Nevertheless, the use of a different strategy, one focused on leveraging the highest-variance neural signals, supported high performance real-time BMI control.
Functional genomics of the parasitic habits of blowflies and botflies
Authors: Cardoso Gisele Antoniazzi , Deszo Marina , Torres Tatiana Teixeira 
Published: December 2019

AbstractInfestation by dipterous larvae – myiasis - is a major problem for livestock industries worldwide and can cause severe economic losses. The Oestroidea superfamily is an interesting model to study the evolution of myiasis-causing flies because of the diversity of parasitism strategies among closely-related species. These flies are saprophagous, obligate parasites, or facultative parasites and can be subdivided into cutaneous, nasopharyngeal, traumatic, and furuncular. We expect that closely-related species have genetic differences that lead to the diverse parasitic strategies. To identify genes with such differences, we used gene expression and coding sequence data from five species (Cochliomyia hominivorax, Chrysomya megacephala, Lucilia cuprina, Dermatobia hominis, andOestrus ovis). We tested whether 1,287 orthologs have different expression and evolutionary constraints under different scenarios. We found two up-regulated genes; one in species causing cutaneous myiasis that is involved in iron transportation/metabolization (ferritin), and another in species causing traumatic myiasis that responds to reduced oxygen levels (anoxia up-regulated-like). Our evolutionary analysis showed a similar result. In theCh. hominivoraxbranch, we found one gene with the same function as ferritin that may be evolving under positive selection, spook. This is the first step towards understanding origins and evolution of parasitic strategy diversity in Oestroidea.