bluuebunny/crossref_metadata_2025_split huggingface dataset:
Differentiation of Epileptic and Psychogenic Nonepileptic Seizures Using Single-Channel Surface Electromyography
Authors: Husain Aatif M. , Towne Alan R. , Chen David K. , Whitmire Luke E. , Voyles Shannon R. , Cardenas Damon P. 
Published: June 2020

Purpose:
Epileptic seizures (ES) and psychogenic nonepileptic seizures (PNES) are difficult to differentiate when based on a patient's self-reported symptoms. This study proposes review of objective data captured by a surface electromyography (sEMG) wearable device for classification of events as ES or PNES. This may help clinicians accurately identify ES and PNES.

Methods:
Seventy-one subjects were prospectively enrolled across epilepsy monitoring units at VA Epilepsy Centers of Excellence. Subjects were concomitantly monitored using video EEG and a wearable sEMG epilepsy monitor, the Sensing Portable sEmg Analysis Characterization (SPEAC) System. Three epileptologists independently classified ES and PNES that contained upper extremity motor activity based on video EEG. The sEMG data from those events were automatically processed to provide a seizure score for event classification. After brief training (60 minutes), the sEMG data were reviewed by a separate group of four epileptologists to independently classify events as ES or PNES.

Results:
According to video EEG review, 17 subjects experienced 34 events (15 ES and 19 PNES with upper extremity motor activity). The automated process correctly classified 87% of ES (positive predictive value = 88%, negative predictive value = 76%) and 79% of PNES, and the expert reviewers correctly classified 77% of ES (positive predictive value = 94%, negative predictive value = 84%) and 96% of PNES. The automated process and the expert reviewers correctly classified 100% of tonic–clonic seizures as ES, and 71 and 50%, respectively, of non-tonic–clonic ES.

Conclusions:
Automated and expert review, particularly in combination, of sEMG captured by a wearable seizure monitor (SPEAC System) may be able to differentiate ES (especially tonic–clonic) and PNES with upper extremity motor activity.
Cyclic Alternating Pattern Analysis in Periodic Leg Movements in Sleep in Patients With Obstructive Sleep Apnea Syndrome Before and After Positive Airway Pressure Treatment
Authors: Benbir Senel Gulcin , Ozcelik Emel Ur , Karadeniz Derya 
Published: June 2020

Purpose:
Cyclic alternating pattern (CAP) is known to increase in many conditions of sleep disruption and sleep disorders, including obstructive sleep apnea syndrome and periodic limb movements in sleep (PLMS). Periodic limb movements in sleep associated with obstructive sleep apnea syndrome may vanish after positive airway pressure treatment, may persist, or emerge at treatment night. Here, the authors aimed to investigate the underlying pathophysiology of nonvanishing, vanishing, or newly emergent PLMS.

Methods:
The authors designed a prospective study and included 10 patients with nonvanishing PLMS during positive airway pressure therapy, 10 patients with vanishing PLMS, 10 patients with newly emergent PLMS, and 10 patients without PLMS at both nights. The CAP analysis was performed in detail at diagnostic polysomnography recording and at positive airway pressure titration. The changes in CAP parameters were evaluated in regard to nonvanishing, vanishing, or newly emergent PLMS.

Results:
Periodic limb movements in sleep related to A1 subtype of CAP were observed to decrease under positive airway pressure titration more than PLMS related to A3 subtype of CAP. The A3 subtype of CAP was higher in patients with vanishing PLMS than those with newly emergent PLMS. The newly emergent PLMS were mostly related to A1 subtype of CAP compared with A3 subtype of CAP.

Conclusions:
This study showed that vanishing, nonvanishing, or newly emerging PLMS may indeed represent different underlying pathophysiology. The authors suggest that organization of sleep and preservation of ultradian rhythms during titration may determine whether PLMS will be vanished or persist. Newly emergent PLMS may probably arise from a separate central generator by the activation of higher cortical areas.
Insular Magnetoencephalography Dipole Clusters in Patients With Refractory Focal Epilepsy
Authors: Chourasia Nitish , Quach Michael , Gavvala Jay 
Published: June 2020

Purpose:
The clinical significance of magnetoencephalography (MEG) dipole clusters in the insular region in patients with focal epilepsy, when present in conjunction with MEG dipole clusters in other regions of the brain is not known.

Methods:
All patients (adult and pediatric) with MEG dipole clusters involving the insula were retrospectively evaluated. Patients who underwent any form of surgical intervention were included in the study. Data obtained included age, sex, seizure characteristics, MRI brain, EEG, MEG, intracranial EEG, type of intervention, and seizure outcomes.

Results:
Twenty-four patients (12 adults and 12 pediatric) were included. Eight patients had one staged intervention and 16 had intracranial evaluation. Ten of 11 patients (91%) with insular coverage by stereotactic EEG had interictal insular spikes, and 5 of 11 patients (45%) had ictal onset from the insula. Combined Engel (I & II) outcomes were seen in five patients with resections/ablations involving the insula MEG dipole clusters as compared with eight patients where the insular MEG dipole clusters were not resected/ablated.

Conclusions:
Insular MEG dipole clusters identified on surface MEG correlated with interictal spikes in intracranial stereotactic electrode contacts in the insula. The presence of insular MEG dipole clusters, however, does not definitively imply a primary insular onset epilepsy.
The impact of the undetected COVID-19 cases on its transmission dynamics
Authors: Saha Sujata , Saha Sumanta 
Published: June 2020

AbstractObjectiveThe COVID-19 pandemic is currently ongoing. Presently, due to the unavailability of a definitive vaccine to decrease its acquiring, it’s essential to understand its transmissibility in the community by undetected cases to control its transmission. This study aims to study this context using mathematical modelling.MethodsA COVID-19 transmission model was framed that estimated the basic reproduction number (R0, a measurement of disease risk) using the next-generation method. It explored the contribution of exposed and infected (detected and undetected) individuals, and environmental pathogen to the overall risk of infection spreading, utilizing the publicly reported data of this infection in Maharashtra between March 22, 2020, and May 4, 2020. A sensitivity analysis was performed to study the effect of a rising number of undetected cases to R0.ResultsThe estimated basic reproduction number is R0 = 4.63, which increases rapidly with the rise in the undetected COVID-19 cases. Although the exposed individuals made the largest contribution to infection transmission (R1 = 2.42), the contaminated environment also played a significant role.ConclusionsIt is crucial to identify the individuals exposed and infected to COVID-19 disease and isolate them to control its transmission. The awareness of the role of fomites in infection transmission is also important in this regard.
Psychological consequences of the Flint Water Crisis: A systematic review
Authors: Brooks Samantha K. , Patel Sonny S. 
Published: June 2020

AbstractGiven the COVID-19 outbreak, these unprecedented times pose many urgent dilemmas about how to support the mental health of communities. The goal of this research is to summarize existing literature on the mental health impact of the recent Flint Water Crisis. In March 2020, we searched five databases for literature exploring the psychological consequences of the crisis. Main findings were extracted. 132 citations were screened and eleven included in the review. Results suggest a negative psychological effect caused by the water crisis, including anxiety and health worries, exacerbated by lowered trust in public health officials, uncertainty about the long-term impacts of the crisis, financial hardships, stigma, and difficulties seeking help. There was evidence that concerns about tap water continued even after the state of emergency was lifted. With a possible compounded effect to residents of Flint with the recent COVID-19 pandemic, the results highlight the need for more resources for psychological health interventions in Flint as well as a need for local governments and health authorities to regain the trust of those affected by the Flint Water Crisis.
Development and application of Pandemic Projection Measures (PPM) for forecasting the COVID-19 outbreak
Authors: Chang Shu-Ren 
Published: June 2020

AbstractThis study aims to provide an accessible and dynamic estimate method to project the Covid-19 trend and hopefully it will help inform policymakers to allocate the needed medical equipment and supplies for saving more lives. A set of newly developed Pandemic Projection Measures (PPM) had been successfully applied to project daily new cases across countries. During the development, numerous trial and error iterations had been performed and then improved with live data. The procedures and computations for the PPM including Uphill Index (UHI), Downhill Indices (DHI), and Error Band Projection (EBP) estimates were explained and discussed along with graphical projections. The PPM was computed with daily live data for the USA, four U.S. states (Illinois, Massachusetts, New Jersey, and New York), France, Italy, Spain, Germany, and China. The results indicated that with the PPM estimations, the daily projections for the future trend were robust to reflect the most plausibility, since the PPM can be updated frequently. With the most up-to-date predictions, governments should be able to monitor the values of UHI and DHI for making a better decision for “flattening the curve”. Based on the empirical data, policymakers should pay more attentions for the following two scenarios: a) When expecting an apex of the outbreak, the UHI is higher than 1.20; and b) After passing a peak day, the DHI is still larger than 0.925. The applications of the PPM estimates are not designed for a one-time projection rather than updated frequently to improve the prediction precisions. With the same concepts from the PPM computations, the peak day and the number of new deaths could be predictable if more data are collected. Like many country leaders saying, “We will win the battle of coronavirus pandemic”, the author hopes to use this easily applicable estimate method to save more lives and to win. The results, currently presented with the data on April 16 and 17, 2020, were only used to explain how to apply the PPM estimates for predictions. The outdated results should not be used to compared with today’s outbreak trend.
Using newspapers obituaries to nowcast daily mortality: evidence from the Italian COVID-19 hot-spots
Authors: Buonanno Paolo , Puca Marcello 
Published: June 2020

AbstractReal-time tracking of infectious disease outbreaks helps policymakers to make timely data-driven decisions. Official mortality data, whenever available, may be incomplete and published with a substantial delay. We report the results of using newspapers obituaries to nowcast the mortality levels observed in Italy during the COVID-19 outbreak between February 24, 2020 and April 15, 2020. We find that the mortality levels predicted using newspapers obituaries outperforms forecasts based on past mortality according to several performance metrics, making obituaries a potentially powerful alternative source of information to deal with real-time tracking of infectious disease outbreaks.
Elucidating the genetic risk of obesity through the human blood plasma proteome
Authors: Zaghlool Shaza B. , Sharma Sapna , Molnar Megan , Matías‐García Pamela R. , Elhadad Mohamed A. , Waldenberger Melanie , Peters Annette , Rathmann Wolfgang , Graumann Johannes , Gieger Christian , Grallert Harald , Suhre Karsten 
Published: June 2020

ABSTRACTObesity is affecting an increasing number of individuals worldwide, but the complex interplay between genetic, environmental and lifestyle factors that control body weight is still poorly understood. Blood circulating protein are confounded readouts of the biological processes that occur in different tissues and organs of the human body. Many proteins have been linked to complex disorders and are also under substantial genetic control. Here, we investigate the associations between over 1,000 blood circulating proteins and body mass index (BMI) in three studies, including over 4,600 participants. We show that BMI is associated with widespread changes in the plasma proteome. We report 152 protein associations with BMI that replicate in at least one other study. 24 proteins also associate with a genome‐wide polygenic score (GPS) for BMI. These proteins are involved in lipid metabolism and inflammatory pathways impacting clinically relevant pathways of adiposity. Mendelian randomization suggests a bi‐directional causal relationship of BMI with three proteins (LEPR, IGFBP1, and WFIKKN2), a protein‐to‐BMI relationship for three proteins (AGER, DPT, and CTSA), and a BMI‐to‐protein relationship for 21 other proteins. Combined with animal model and tissue‐specific gene expression data, our findings suggest potential therapeutic targets and further elucidate the biological role of these proteins in pathologies associated with obesity.
Using generalised dissimilarity modelling and targeted field surveys to gap-fill an ecosystem surveillance network
Authors: Guerin Greg R. , Williams Kristen J. , Leitch Emrys , Lowe Andrew J. , Sparrow Ben 
Published: June 2020

AbstractWhen considering which sites or land parcels complement existing conservation or monitoring networks, there are many strategies for optimising ecological coverage in the absence of ground observations. However, such optimisation is often implemented theoretically in conservation prioritisation frameworks and real-world implementation is rarely assessed, particularly for networks of monitoring sites.We assessed the performance of adding new survey sites informed by predictive modelling in gap-filling the ecological coverage of the Terrestrial Ecosystem Research Network’s (TERN) continental network of ecosystem surveillance plots, Ausplots. Using plant cover observations from 531 sites, we constructed a generalised dissimilarity model (GDM) in which species composition was predicted by environmental parameters. We combined predicted nearest-neighbour ecological distances for locations across Australia with practical considerations to select regions for gap-filling surveys of 181 new plots across 18 trips. We tracked the drop in mean nearest-neighbour distances in GDM space, and increases in the actual sampling of ecological space through cumulative multivariate dispersion.GDM explained 34% of deviance in species compositional turnover and retained geographic distance, soil P, aridity, actual evapotranspiration and rainfall seasonality among 17 significant predictors.Key bioregions highlighted as gaps included Cape York Peninsula, Brigalow Belt South, South Eastern Queensland, Gascoyne and Dampierland.We targeted identified gap regions for surveys in addition to opportunistic or project-based gap-filling over two years. Approximately 20% of the land area of Australia received increased servicing of biological representation, corresponding to a drop in mean nearest-neighbour ecological distances from 0.38 to 0.33 in units of compositional dissimilarity. The gain in sampled ecological space was 172% that from the previous 181 plots. Notable gaps were filled in northern and south-east Queensland, north-east New South Wales and northern Western Australia.Biological scaling of environmental variables through GDM supports practical sampling decisions for ecosystem monitoring networks. Optimising putative survey locations via ecological distance to a nearest neighbour rather than to all existing sites is useful when the aim is to increase representation of habitats rather than sampling evennessper se. Iterations between modelled gaps and field campaigns provide a pragmatic compromise between theoretical optima and real-world decision-making.
The Guaymas Basin Subseafloor Sedimentary Archaeome Reflects Complex Environmental Histories
Authors: Ramírez Gustavo A. , McKay Luke J. , Fields Matthew W. , Buckley Andrew , Mortera Carlos , Hensen Christian , Ravelo Ana Christina , Teske Andreas P. 
Published: June 2020

AbstractWe explore archaeal distribution and environmental niche differentiation in sedimentary subseafloor habitats of Guaymas Basin and the adjacent Sonora Margin, located in the Gulf of California, México. Specifically, we survey diverse subseafloor habitats on the Guaymas Basin flanking regions that are extending from the spreading center, termed here “off-axis” sites. Sampling locations include (i) control sediments without hydrothermal or seep influence, (ii) Sonora Margin sediments underlying oxygen minimum zone water, (iii) compacted, highly reduced sediments from a pressure ridge with numerous seeps at the base of the Sonora Margin, and (iv) sediments impacted by hydrothermal circulation at the off-axis Ringvent site. Generally, archaeal 16S rRNA gene datasets are largely comprised of Bathyarchaeal lineages, members of the Hadesarchaea, MBG-D, TMEG, and ANME-1 groups. The most frequently observed 25 OTUs belong to members of these lineages, and correspond to approx. 40 to 80% of the sequence dataset in each sediment sample. Differential distribution patterns of these archaeal groups in downcore sediments uniquely characterize each major sedimentary environment. Variations in archaeal community composition reflect locally specific environmental challenges throughout the greater Guaymas Basin area. Background sediments are divided into surface and subsurface niches, reflecting increased selection of the archaeal community downcore. In sum, the environmental setting and history of a particular site, not isolated biogeochemical properties out of context, control the subseafloor archaeal communities in Guaymas Basin and Sonora Margin sediments.
The neural representation of force across grasp types in motor cortex of humans with tetraplegia
Authors: Rastogi Anisha , Willett Francis R. , Abreu Jessica , Crowder Douglas C. , Murphy Brian A. , Memberg William D. , Vargas-Irwin Carlos E. , Miller Jonathan P. , Sweet Jennifer , Walter Benjamin L. , Rezaii Paymon G. , Stavisky Sergey D. , Hochberg Leigh R. , Shenoy Krishna V. , Henderson Jaimie M. , Kirsch Robert F. , Ajiboye A. Bolu 
Published: June 2020

AbstractIntracortical brain-computer interfaces (iBCIs) have the potential to restore hand grasping and object interaction to individuals with tetraplegia. Optimal grasping and object interaction require simultaneous production of both force and grasp outputs. However, since overlapping neural populations are modulated by both parameters, grasp type could affect how well forces are decoded from motor cortex in a closed-loop force iBCI. Therefore, this work quantified the neural representation and offline decoding performance of discrete hand grasps and force levels in two participants with tetraplegia. Participants attempted to produce three discrete forces (light, medium, hard) using up to five hand grasp configurations. A two-way Welch ANOVA was implemented on multiunit neural features to assess their modulation toforceandgrasp. Demixed principal component analysis was used to assess for population-level tuning to force and grasp and to predict these parameters from neural activity. Three major findings emerged from this work: 1) Force information was neurally represented and could be decoded across multiple hand grasps (and, in one participant, across attempted elbow extension as well); 2) Grasp type affected force representation within multi-unit neural features and offline force classification accuracy; and 3) Grasp was classified more accurately and had greater population-level representation than force. These findings suggest that force and grasp have both independent and interacting representations within cortex, and that incorporating force control into real-time iBCI systems is feasible across multiple hand grasps if the decoder also accounts for grasp type.Significance StatementIntracortical brain-computer interfaces (iBCIs) have emerged as a promising technology to potentially restore hand grasping and object interaction in people with tetraplegia. This study is among the first to quantify the degree to which hand grasp affects force-related – orkinetic– neural activity and decoding performance in individuals with tetraplegia. The study results enhance our overall understanding of how the brain encodes kinetic parameters across varying kinematic behaviors -- and in particular, the degree to which these parameters have independent versus interacting neural representations. Such investigations are a critical first step to incorporating force control into human-operated iBCI systems, which would move the technology towards restoring more functional and naturalistic tasks.
Scalable, continuous evolution for the generation of diverse enzyme variants encompassing promiscuous activities
Authors: Rix Gordon , Watkins-Dulaney Ella J. , Almhjell Patrick J. , Boville Christina E. , Arnold Frances H. , Liu Chang C. 
Published: June 2020

AbstractEnzyme orthologs sharing identical primary functions can have different promiscuous activities. While it is possible to mine this natural diversity to obtain useful biocatalysts, generating comparably rich ortholog diversity is difficult, as it is the product of deep evolutionary processes occurring in a multitude of separate species and populations. Here, we take a first step in recapitulating the depth and scale of natural ortholog evolution on laboratory timescales. Using a continuous directed evolution platform called OrthoRep, we rapidly evolved theThermotoga maritimatryptophan synthase β-subunit (TmTrpB) through multi-mutation pathways in many independent replicates, selecting only onTmTrpB’s primary activity (synthesizing L-tryptophan from indole and L-serine). We find that the resulting sequence-diverseTmTrpB variants span a range of substrate profiles useful in industrial biocatalysis and suggest that the depth and scale of evolution that OrthoRep affords will be generally valuable in enzyme engineering and the evolution of new biomolecular functions.
Leveraging non-structural data to predict structures of protein–ligand complexes
Authors: Paggi Joseph M. , Belk Julia A. , Hollingsworth Scott A. , Villanueva Nicolas , Powers Alexander S. , Clark Mary J. , Chemparathy Augustine G. , Tynan Jonathan E. , Lau Thomas K. , Sunahara Roger K. , Dror Ron O. 
Published: June 2020

AbstractOver the past fifty years, tremendous effort has been devoted to computational methods for predicting properties of ligands that bind macromolecular targets, a problem critical to rational drug design. Such methods generally fall into two categories: physics-based methods, which directly model ligand interactions with the target given the target’s three-dimensional (3D) structure, and ligand-based methods, which predict ligand properties given experimental measurements for similar ligands. Here we present a rigorous statistical framework to combine these two sources of information. We develop a method to predict a ligand’s pose—the 3D structure of the ligand bound to its protein target—that leverages a widely available source of information: a list of other ligands that are known to bind the same target but for which no 3D structure is available. This combination of physics-based and ligand-based modeling improves upon state-of-the-art pose prediction accuracy across all major families of drug targets. As an illustrative application, we predict binding poses of antipsychotics and validate the results experimentally. Our statistical framework and results suggest broad opportunities to predict diverse ligand properties using machine learning methods that draw on physical modeling and ligand data simultaneously.