bluuebunny/crossref_metadata_2025_split huggingface dataset:
Association between weekend catch-up sleep and high-sensitivity C-reactive protein levels in adults: a population-based study
Authors: Han Kyu-Man , Lee Heon-Jeong , Kim Leen , Yoon Ho-Kyoung 
Published: February 2020

AbstractStudy ObjectivesTo investigate the association between weekend catch-up sleep (WCS) and the levels of high-sensitivity C-reactive protein (hsCRP)—a serum inflammatory maker—in adultsMethodsData of 5,506 adults aged 19 years or older were obtained from the nationwide cross-sectional Korea National Health and Nutrition Examination Surveys conducted in 2016. Serum hsCRP level, weekday and weekend sleep durations, and sociodemographic and health-related characteristics were assessed. Participants whose weekend sleep duration was more than 1 h longer than their weekday sleep duration were included in the WCS group. hsCRP level was categorized into quartiles (i.e. highest, middle-high, middle-low, and lowest). Obesity was defined by body mass index ≥ 25.0 kg/m2.ResultsThe WCS group included 1,901 participants (34.5%). In the logistic regression analysis controlling for all variables, adults in the WCS group were significantly less likely to show the highest hsCRP level (versus the lowest level) compared with those without WCS in the complete sample (adjusted odds ratio = 0.795, 95% confidence interval [CI] = 0.662 to 0.955). In a subgroup analysis, this association was significant only for those with weekday sleep duration of 6 h or lower. Longer WCS (≥3 h) was not associated with hsCRP levels. Non-obese people with WCS demonstrated a lower risk for high hsCRP levels, while there was no significant difference in obese people with WCS.ConclusionsOur findings indicate that WCS may be beneficial for low-grade systemic inflammation in adults, particularly among those with shorter weekday sleep durations. WCS may also interact with obesity.
An unbiased, efficient sleep–wake detection algorithm for a population with sleep disorders: change point decoder
Authors: Cakmak Ayse S , Da Poian Giulia , Willats Adam , Haffar Ammer , Abdulbaki Rami , Ko Yi-An , Shah Amit J , Vaccarino Viola , Bliwise Donald L , Rozell Christopher , Clifford Gari D 
Published: February 2020

Abstract

Study Objectives
The usage of wrist-worn wearables to detect sleep–wake states remains a formidable challenge, particularly among individuals with disordered sleep. We developed a novel and unbiased data-driven method for the detection of sleep–wake and compared its performance with the well-established Oakley algorithm (OA) relative to polysomnography (PSG) in elderly men with disordered sleep.

Methods
Overnight in-lab PSG from 102 participants was compared with accelerometry and photoplethysmography simultaneously collected with a wearable device (Empatica E4). A binary segmentation algorithm was used to detect change points in these signals. A model that estimates sleep or wake states given the changes in these signals was established (change point decoder, CPD). The CPD’s performance was compared with the performance of the OA in relation to PSG.

Results
On the testing set, OA provided sleep accuracy of 0.85, wake accuracy of 0.54, AUC of 0.67, and Kappa of 0.39. Comparable values for CPD were 0.70, 0.74, 0.78, and 0.40. The CPD method had sleep onset latency error of −22.9 min, sleep efficiency error of 2.09%, and underestimated the number of sleep–wake transitions with an error of 64.4. The OA method’s performance was 28.6 min, −0.03%, and −17.2, respectively.

Conclusions
The CPD aggregates information from both cardiac and motion signals for state determination as well as the cross-dimensional influences from these domains. Therefore, CPD classification achieved balanced performance and higher AUC, despite underestimating sleep–wake transitions. The CPD could be used as an alternate framework to investigate sleep–wake dynamics within the conventional time frame of 30-s epochs.
Cerebral grey matter density is associated with neuroreceptor and neurotransporter availability: A combined PET and MRI study
Authors: Manninen Sandra , Karjalainen Tomi , Tuominen Lauri J. , Hietala Jarmo , Kaasinen Valtteri , Joutsa Juho , Rinne Juha , Nummenmaa Lauri 
Published: February 2020

AbstractPositron emission tomography (PET) can be used forin vivomeasurement of specific neuroreceptors and transporters using radioligands, while voxel-based morphometric analysis of magnetic resonance images allows automated estimation of local grey matter densities. However, it is not known how regional neuroreceptor or transporter densities are reflected in grey matter densities. Here, we analyzed brain scans retrospectively from 325 subjects and compared grey matter density estimates with three different neuroreceptors and transporter availabilities. µ-opioid receptors (MORs) were measured with [11C]carfentanil (162 scans), dopamine D2 receptors with [11C]raclopride (91 scans) and serotonin transporters (SERT) with [11C]MADAM (72 scans). The PET data were modelled with simplified reference tissue model. Voxel-wise correlations between binding potential and grey matter density images were computed. Regional binding of all the used radiotracers was associated with grey matter density in region and ligand-specific manner independently of subjects’ age or sex. These data show that grey matter density and MOR and D2R neuroreceptor / SERT availability are correlated, with effect sizes (r2) ranging from 0.04 to 0.69. This suggests that future studies comparing PET outcome measure different groups (such as patients and controls) should take grey matter density differences between the groups into account.
An Evaluation of the Efficacy of Preclinical Models of Lung Cancer Drugs
Authors: Pan Elizabeth , Bogumil David , Cortessis Victoria , Yu Sherrie , Nieva Jorge 
Published: February 2020

AbstractBackgroundPreclinical cell models are the mainstay in the early stages of drug development. We sought to explore the preclinical data that differentiated successful from failed therapeutic agents in lung cancer.Methods134 failed lung cancer drugs and 27 successful lung cancer drugs were identified. Preclinical data were evaluated. The outcome variable for cell model experiments was the half maximal inhibitory concentration (IC50), and for murine model experiments was tumor growth inhibition (TGI). A logistic regression was performed on quartiles (Q) of IC50s and TGIs.ResultsWe compared odds of approval among drugs defined by IC50 and TGI quartile. Compared to drugs with preclinical cell experiments in highest IC50 quartile (Q4, IC50 345.01-100,000nM), those in Q3 differed little, but those in the lower two quartiles had better odds of being approved. However, there was no significant monotonic trend identified (P-trend 0.4). For preclinical murine models, TGI values ranged from −0.3119 to 1.0000, with a tendency for approved drugs to demonstrate poorer inhibition than failed drugs. Analyses comparing success of drugs according to TGI quartile produced interval estimates too wide to be statistically meaningful, although all point estimates accord with drugs in Q2-Q4 (TGI 0.5576-0.7600, 0.7601-0.9364, 0.9365-1.0000) having lower odds of success than those in Q1 (−0.3119-0.5575).ConclusionThere does not appear to be a significant linear trend between preclinical success and drug approval, and therefore published preclinical data does not predict success of therapeutics in lung cancer. Newer models with predictive power would be beneficial to drug development efforts.
DREAM: A Toolbox to Decode Rhythms of the Brain System
Authors: Gong Zhu-Qing , Gao Peng , Jiang Chao , Xing Xiu-Xia , Dong Hao-Ming , White Tonya , Castellanos F. Xavier , Li Hai-Fang , Zuo Xi-Nian 
Published: February 2020

AbstractRhythms of the brain are generated by neural oscillations across multiple frequencies, which can be observed with multiple modalities. Following the natural log linear law of frequency distribution, these oscillations can be decomposed into distinct frequency intervals associated with specific physiological processes. This perspective on neural oscillations has been increasingly applied to study human brain function and related behaviors. In practice, relevant signals are commonly measured as a discrete time series, and thus the sampling period and number of samples determine the number and ranges of decodable frequency intervals. However, these limits have been often ignored by researchers who instead decode measured oscillations into multiple frequency intervals using a fixed sample period and numbers of samples. One reason for such misuse is the lack of an easy-to-use toolbox to implement automatic decomposition of frequency intervals. We report on a toolbox with a graphical user interface for achieving local and remote decoding rhythms of the brain system (DREAM) which is accessible to the public via GitHub. We provide worked examples of DREAM used to investigate frequency-specific performance of both neural (spontaneous brain activity) and neurobehavioral (in-scanner head motion) oscillations. DREAM analyzed the head motion oscillations and found that younger children moved their heads more than older children across all five frequency intervals whereas boys moved more than girls in the age interval from 7 to 9 years. It is interesting that the higher frequency bands contains more head movements, and showed stronger age-motion associations but the weaker sex-motion interactions. Using the fast functional magnetic resonance imaging data from the Human Connectome Project, DREAM mapped the amplitude of these neural oscillations into multiple frequency bands and evaluated their test-retest reliability. A novel result indicated that the higher frequency bands exhibited more reliable amplitude measurements, implying more inter-individual variability of the amplitudes for the higher frequency bands. In summary, these findings demonstrated the applicability of DREAM for frequency-specific human brain mapping as well as the assessments on their measurement reliability and validity.
Distinct neural ensemble response statistics are associated with recognition and discrimination of natural sound textures
Authors: Zhai X. , Khatami F. , Sadeghi M. , He F. , Read H.L. , Stevenson I.H. , Escabí M.A. 
Published: February 2020

ABSTRACTThe perception of sound textures, a class of natural sounds defined by statistical sound structure such as fire wind, and rain, has been proposed to arise through the integration of time-averaged summary statistics. Where and how the auditory system might encode these summary statistics to create internal representations of these stationary sounds, however, is unknown. Here, using natural textures and synthetic variants with reduced statistics, we show that summary statistics modulate the correlations between frequency organized neuron ensembles in the awake rabbit inferior colliculus. These neural ensemble correlation statistics capture high-order sound structure and allow for accurate neural decoding in a single trial recognition task with evidence accumulation times approaching 1 s. In contrast, the average activity across the neural ensemble (neural spectrum) provides a fast (tens of ms) and salient signal that contributes primarily to texture discrimination. Intriguingly, perceptual studies in human listeners reveals analogous trends: the sound spectrum is integrated quickly and serves as salient discrimination cue while high-order sound statistics are integrated slowly and contribute substantially more towards recognition. The findings suggest statistical sound cues such as the sound spectrum and correlation structure are represented by distinct response statistics in auditory midbrain ensembles, and that these neural response statistics may have dissociable roles and time scales for the recognition and discrimination of natural sounds.SIGNIFICANCE STATEMENTBeing able to recognize and discriminate natural sounds, such as from a running stream, a crowd clapping, or ruffling leaves is a critical task of the normal functioning auditory system. Humans can easily perform such tasks, yet they can be particularly difficult for the hearing impaired and they challenge our most sophisticated computer algorithms. This difficulty is attributed to the complex physical structure of such natural sounds and the fact they are not unique: they vary randomly in a statistically defined manner from one excerpt to the other. Here we provide the first evidence, to our knowledge, that the central auditory system is able to encode and utilize statistical sound cues for natural sound recognition and discrimination behaviors.
Does offspring sex ratio differ between urban and forest populations of great tits (Parus major)?
Authors: Ágh Nóra , Pipoly Ivett , Szabó Krisztián , Vincze Ernő , Bókony Veronika , Seress Gábor , Liker András 
Published: February 2020

SummarySince male and female offspring may have different costs and benefits, parents may use sex ratio adjustment to increase their fitness under different environmental conditions. Urban habitats provide poorer conditions for nestling development in many birds. Therefore, we investigated whether great tits (Parus major) produce different brood sex ratios in urban and natural habitats. We determined the sex of nestlings of 126 broods in two urban and two forest habitats between 2012 and 2014 by molecular sexing. We found that brood sex ratio did not differ significantly between urban and forest habitats either at egg-laying or near fledging. Male offspring were larger than females in both habitats. This latter result suggests that male offspring may be more costly to raise than females, yet our findings suggest that urban great tits do not produce more daughters despite the unfavourable breeding conditions. This raises the possibility that other aspects of urban life, such as better post-fledging survival, might favour males and thereby compensate for the extra energetic costs of producing male offspring.
Interaction of intraocular pressure and ganglion cell function in open angle glaucoma
Authors: Al-Nosairy K. O. , Van den Bosch J.J.O.N. , Pennisi V. , Thieme H. , Mansouri K , Choritz L. , Hoffmann M. B. 
Published: February 2020

AbstractPurposeTo test the feasibility of simultaneous steady-state pattern electroretinogram (PERG) and intraocular pressure (IOP) measurements with an IOP sensor and to test a model for IOP manipulation during lateral decubitus positioning (LDP) and its impact on the PERG.DesignA prospective, observational study.Methods15 healthy controls and 15 treated glaucoma patients participated in the study. 8 patients had an intraocular IOP sensor (eyemate-IO®, Implandata Ophthalmic Products GmbH) in the right eye (GLAIMP) and 7 had no sensor and with glaucoma in the left eye. (1) We tested the feasibility of simultaneous IOP and PERG recordings by comparing PERGs with and without simultaneous IOP-read out in GLAIMP. (2) All participants were positioned in the following order: sitting1 (S1), right LDP (LDR), sitting2 (S2), left LDP (LDL) and sitting3 (S3). For each position, PERG amplitudes and IOP were determined with rebound tonometry (Icare® TA01i) in all participants without the IOP sensor.ResultsElectromagnetic intrusions of IOP sensor readout onto steady-state PERG-recordings had, due to different frequency ranges, no relevant effect on PERG amplitudes. IOP and PERG measures were affected by LDP, e.g., IOP was increased during LDRvs S1 in the lower eyes of GLAIMPand controls (P < 0.001 and P < 0.05, respectively) and PERG amplitude was decreased (P < 0.05 and P < 0.01, respectively).ConclusionsDuring LDP, IOP and PERG measurements changed more in the lower eye. IOP changes induced by LDP may be a model for studying the interaction of IOP and ganglion cell function.
Interferon-γ signaling synergizes with LRRK2 in human neurons and microglia
Authors: De Cicco Silvia , Ivanyuk Dina , Haq Wadood , Panagiotakopoulou Vasiliki , Arsić Aleksandra , Schöndorf David , Yu Cong , Perez Maria-Jose , Cassatella Ruggiero Pio , Jakobi Meike , Schneiderhan-Marra Nicole , Nikić-Spiegel Ivana , Gasser Thomas , Deleidi Michela 
Published: February 2020

AbstractIncreasing evidence suggests a role for interferons (IFNs) in neurodegeneration. Parkinson’s disease (PD) associated kinase LRRK2 has been implicated in IFN type II (IFN) response in infections and nigral neuronal loss. However, whether and how LRRK2 synergizes with IFN-γ still remains unclear. Here, we employed dopaminergic (DA) neurons and microglia differentiated from patient induced pluripotent stem cells to unravel the role of IFN-γ in LRRK2-PD. We show that IFN-γ induces LRRK2 expression in both DA neurons and microglial cells. LRRK2-G2019S, the most common PD-associated mutation, sensitizes DA neurons to IFN-γ by decreasing AKT phosphorylation. IFN-γ suppresses NFAT activity in both neurons and microglia and synergistically enhances LRRK2-induced defects of NFAT activation. Furthermore, LRRK2-G2019S negatively regulates NFAT via calcium and microtubule dynamics. Importantly, we uncover functional consequences of the reduction of NFAT activity in both cell types, namely defects of neurite elongation and alteration of microglial activation profile and motility. We propose that synergistic IFN-γ/LRRK2 activation serves as a direct link between inflammation and neurodegeneration in PD.
Csmd2 interacts with Dab1 and is Required in Reelin-Mediated Neuronal Maturation
Authors: Gutierrez Mark A , Dwyer Brett E , Franco Santos J 
Published: February 2020

AbstractReelin is a glycoprotein secreted by Cajal-Retzius cells to regulate development of the cerebral cortex. Reelin binding to its receptors on immature neurons initiates a signaling cascade through the downstream adaptor protein, Dab1. Defects in this signaling mechanism result in perturbed neuronal migration, reductions in dendrite complexity, and deficits in synapse development and function. How Reelin controls neuronal migration and brain lamination have been extensively investigated over the years, but the pathways that regulate dendrite and spine development downstream of Reelin and Dab1 have yet to be fully elucidated. Here, we have identified a novel interaction between Dab1 and Csmd2, a synaptic transmembrane protein required for dendrite and dendritic spine development in forebrain excitatory neurons. We demonstrate that Csmd2 contains an NPxY motif on its intracellular region, through which Dab1 interacts with Csmd2. Interestingly, we find that this NPxY consensus motif is not required for Csmd2 to localize at the postsynaptic densities of spiny neurons. Rather, the introduction of an NPxY mutant form of Csmd2 results in a significant overproduction of immature, filopodia-like dendritic spines in maturing neurons. Moreover, we show that knockdown ofCsmd2mRNA expression in immature developing neurons abolishes the ability of Reelin to promote dendrite elaboration and dendritic spine maturation. This suggests that the Csmd2-Dab1 interaction may be a requirement of Reelin/Dab1 signaling to mediate the structural maturation of neurons. Together, these results point toward a role of Csmd2 in the Reelin/Dab1 signaling axis that promotes the development of dendrites and dendritic spines in maturing neurons.Summary StatementHow Reelin controls neuronal maturation remains to be understood. We demonstrate that the synaptic protein Csmd2 interacts with the Reelin-associated adaptor protein Dab1. We also determine that Reelin requires Csmd2 to regulate structural development and maturation of forebrain neurons.
Learning for angling: an advanced learning capability for avoidance of angling gear in red sea bream juveniles
Authors: Takahashi Kohji , Masuda Reiji 
Published: February 2020

AbstractAngling has been the cause of mortality for fish since ancient. The avoidance learning for angling gear could be considered as a survival strategy against the mortality by angling. Whereas some studies indicated the possibility of avoidance learning for angling gear, most studies investigated the avoidance learning by using groups of fish, in which it is difficult to reveal the process and mechanisms of the learning. The present study elucidated the avoidance learning for angling gear by experiment of single fish in a tank using red sea breamPagrus majorjuveniles. Individuals with only once or twice of experience for angling avoided angling gear while showing the feeding motivation for pellets, representing avoidance learning for the angling gear. Most of the experienced individuals avoided the krill attached with a fishing line, but not krill and pellets near the angling gear. Feeding rate for prey on a fishing line at two month after the angling trial demonstrated that approximately half of fish kept the memory for angling gear. A series of experiment for angling gear elucidated that red sea bream juveniles are equipped with considerable learning capability for angling gear, suggesting a cognitive evolution for angling.
A Prokaryotic Membrane Sculpting BAR Domain Protein
Authors: Phillips Daniel A. , Zacharoff Lori A. , Hampton Cheri M. , Chong Grace W. , Malanoski Anthony P. , Metskas Lauren Ann , Xu Shuai , Bird Lina J. , Eddie Brian J. , Jensen Grant J. , Drummy Lawrence F. , El-Naggar Mohamed Y. , Glaven Sarah M. 
Published: February 2020

AbstractBin/Amphiphysin/RVS (BAR) domain proteins belong to a superfamily of coiled-coil proteins influencing membrane curvature in eukaryotes and are associated with vesicle biogenesis, vesicle-mediated protein trafficking, and intracellular signaling. Here we report the first prokaryotic BAR domain protein, BdpA, fromShewanella oneidensisMR-1, known to produce redox-active membrane vesicles and micrometer-scale outer membrane extensions (OMEs). BdpA is required for uniform size distribution of membrane vesicles and scaffolding OMEs into a consistent diameter and curvature. Cryogenic transmission electron microscopy reveals a strain lacking BdpA produces lobed, disordered OMEs rather than membrane tubes produced by the wild type strain. Overexpression of BdpA promotes OME formation during conditions where they are less common. Heterologous expression results in OME production inMarinobacter atlanticusandEscherichia coli. Based on the ability of BdpA to alter membrane curvaturein vivo, we propose that BdpA and its homologs comprise a newly identified class of prokaryotic BAR (P-BAR) domains.
Degradation of white birch shelterbelts by attack of white-spotted longicorn beetle in central Hokkaido, northern Japan
Authors: Masaka Kazuhiko , Wakita Yohichi , Iwasaki Kenta , Hayamizu Masato 
Published: February 2020

AbstractWidespread decline of white birch shelterbelts was observed in central Hokkaido, northern Japan. Many exit holes bored by adults of the white-spotted longicorn beetle have been found at the bases of the trunks of trees in these stands. The number of adult longicorn beetle exit holes (Nholes) of dead standing trees tended to be greater than that of living trees.Nholestended to increase with increasingDBH, and there was a negative relationship betweenNholesand tree vigor. We found a size-dependent lethal threshold inNholes. A resonance-measurement device (RMD) for diagnosing the level of wood defection inside the trunk was also tested. The RMD examination together with the lethal threshold inNholescan be a useful tool for the diagnosis of white birch trees. We estimatedNholesof dead standing trees with aDBHof 25 cm in each plot (ND25) to compare the severity of infestation among plots. Logistic regression analysis revealed that 50% of stands will be degraded ifND25= 25.0. Thus, the degradation could also be evaluated byNholes.