bluuebunny/crossref_metadata_2025 huggingface dataset:
RangeShiftR: an R package for individual-based simulation of spatial eco-evolutionary dynamics and species’ responses to environmental change
Authors: Malchow Anne-Kathleen , Bocedi Greta , Palmer Stephen C. F. , Travis Justin M. J. , Zurell Damaris
Published: November 2020

Reliably modelling the demographic and distributional responses of a species to environmental changes can be crucial for successful conservation and management planning. Process-based models have the potential to achieve this goal, but so far they remain underused for predictions of species’ distributions. Individual-based models offer the additional capability to model inter-individual variation and evolutionary dynamics and thus capture adaptive responses.

We present RangeShiftR, an R package that provides flexible and fast simulations of spatial eco-evolutionary dynamics and species’ responses to environmental changes. It implements the individual-based simulation software RangeShifter for the widely used statistical programming platform R. The package features additional auxiliary functions to support model specification and analysis of results. We provide an outline of the package’s functionality, describe the underlying model structure with its main components and present a short example.

RangeShiftR offers substantial model complexity, especially for the demographic and dispersal processes. It comes with comprehensive documentation and elaborate tutorials to provide a low entry level. Thanks to the implementation of the core code in C++, the computations are fast. The complete source code is published under a public licence, making adaptations and contributions feasible.

The RangeShiftR package facilitates the application of individual-based and mechanistic modelling to eco-evolutionary questions by operating a flexible and powerful simulation model from R. It allows effortless interoperation with existing packages to create streamlined workflows that can include data preparation, integrated model specification, and results analysis. Moreover, the implementation in R strengthens the potential for coupling RangeShiftR with other models.
Midbrain and lateral nucleus accumbens dopamine depletion affects free-choice high-fat high-sugar diet preference in male rats
Authors: Joshi Anil , Faivre Fanny , la Fleur Susanne Eva , Barrot Michel
Published: November 2020

Dopamine influences food intake behavior. Reciprocally, food intake, especially of palatable dietary items, can modulate dopamine-related brain circuitries. Among these reciprocal impacts, it has been observed that an increased intake of dietary fat results in blunted dopamine signaling and, to compensate this lowered dopamine function, caloric intake may subsequently increase. To determine how dopamine regulates food preference we did 6-hydroxydopamine (6-OHDA) lesions, depleting dopamine in specific brain regions in male Sprague Dawley rats. The food preference was assessed by providing the rats with free choice access to control diet, fat, 20% sucrose and tap water. Rats with midbrain lesions targeting the substantia nigra (which is also a model of Parkinson’s disease) consumed fewer calories, as reflected by a decrease in control diet intake, but they surprisingly displayed an increase in fat intake, without change in the sucrose solution intake compared to sham animals. To determine which of the midbrain dopamine projections may contribute to this effect, we next compared the impact of 6-OHDA lesions of terminal fields, targeting the dorsal striatum, the lateral nucleus accumbens and the medial nucleus accumbens. We found that 6-OHDA lesion of the lateral nucleus accumbens, but not of the dorsal striatum or the medial nucleus accumbens, led to increased fat intake. These findings indicate a role for lateral nucleus accumbens dopamine in regulating food preference, in particularly the intake of fat.

HIGHLIGHTS

Dopamine influences fat intake

Animal model of Parkinson’s disease display lower kcal intake but increased fat choice

Dopamine depletion in the lateral nucleus accumbens favors fat intake
Artificial Joint Speed Feedback for Myoelectric Prosthesis Controls
Authors: Earley Eric J. , Johnson Reva E. , Sensinger Jonathon W. , Hargrove Levi J.
Published: November 2020

I.

Accurate control of human limbs involves both feedforward and feedback signals. For prosthetic arms, feedforward control is commonly accomplished by recording myoelectric signals from the residual limb to predict the user’s intent, but augmented feedback signals are not explicitly provided in commercial devices. Previous studies have demonstrated inconsistent results when artificial feedback was provided in the presence of vision. We hypothesized that negligible benefits in past studies may have been due to artificial feedback with low precision compared to vision, which results in heavy reliance on vision during reaching tasks. Furthermore, we anticipated more reliable benefits from artificial feedback when providing information that vision estimates with high uncertainty – joint speed. In this study, we test an artificial sensory feedback system providing joint speed information and how it impacts performance and adaptation during a hybrid positional-and-myoelectric ballistic reaching task. We found modest improvement in overall reaching errors after perturbed control, and that high prosthesis control noise was compensated for by strategic overreaching with the positional control and underreaching with the myoelectric control. These results provide insights into the relevant factors influencing the improvements conferred by artificial sensory feedback.
U-Net Model for Brain Extraction: Trained on Humans for Transfer to Non-human Primates
Authors: Wang Xindi , Li Xin-Hui , Cho Jae Wook , Russ Brian E. , Rajamani Nanditha , Omelchenko Alisa , Ai Lei , Korchmaros Annachiara , Sawiak Stephen , Benn R. Austin , Garcia-Saldivar Pamela , Wang Zheng , Kalin Ned H. , Schroeder Charles E. , Craddock R. Cameron , Fox Andrew S. , Evans Alan C. , Messinger Adam , Milham Michael P. , Xu Ting
Published: November 2020

Brain extraction (a.k.a. skull stripping) is a fundamental step in the neuroimaging pipeline as it can affect the accuracy of downstream preprocess such as image registration, tissue classification, etc. Most brain extraction tools have been designed for and applied to human data and are often challenged by non-human primates (NHP) data. Amongst recent attempts to improve performance on NHP data, deep learning models appear to outperform the traditional tools. However, given the minimal sample size of most NHP studies and notable variations in data quality, the deep learning models are very rarely applied to multi-site samples in NHP imaging. To overcome this challenge, we used a transfer-learning framework that leverages a large human imaging dataset to pretrain a convolutional neural network (i.e. U-Net Model), and then transferred this to NHP data using a small NHP training sample. The resulting transfer-learning model converged faster and achieved more accurate performance than a similar U-Net Model trained exclusively on NHP samples. We improved the generalizability of the model by upgrading the transfer-learned model using additional training datasets from multiple research sites in the Primate Data-Exchange (PRIME-DE) consortium. Our final model outperformed brain extraction routines from popular MRI packages (AFNI, FSL, and FreeSurfer) across a heterogeneous sample from multiple sites in the PRIME-DE with less computational cost (20s~10min). We also demonstrated the transfer-learning process enables the macaque model to be updated for use with scans from chimpanzees, marmosets, and other mammals (e.g. pig). Our model, code, and the skull-stripped mask repository of 136 macaque monkeys are publicly available for unrestricted use by the neuroimaging community athttps://github.com/HumanBrainED/NHP-BrainExtraction.
The road to sorghum domestication: evidence from nucleotide diversity and gene expression patterns
Authors: Burgarella Concetta , Berger Angélique , Glémin Sylvain , David Jacques , Terrier Nancy , Deu Monique , Pot David
Published: November 2020

Native African cereals (sorghum, millets) ensure food security to millions of low-income people from low fertility and drought-prone regions of Africa and Asia. In spite of their agronomic importance, the genetic bases of their phenotype and adaptations are still not well understood. Here we focus onSorghum bicolor, which is the fifth cereal worldwide for grain production and constitutes the staple food for around 500 million people. We leverage transcriptomic resources to address the adaptive consequences of the domestication process. Gene expression and nucleotide variability were analyzed in 11 domesticated and 9 wild accessions. We documented a downregulation of expression and a reduction of diversity both in nucleotide polymorphism (30%) and gene expression levels (18%) in domesticated sorghum. These findings at the genome-wide level support the occurrence of a genetic bottleneck in the domestication history of sorghum, although several genes showed also patterns consistent with the action of selection. Nine hundred and forty-nine genes were significantly differentially expressed between wild and domesticated gene pools. Their functional annotation points to metabolic pathways most likely contributing to the sorghum domestication syndrome, such as photosynthesis and auxin metabolism. Coexpression network analyses revealed 21 clusters of genes sharing similar expression patterns. Four clusters (totalizing 2449 genes) were significantly enriched in differentially expressed genes between the wild and domesticated pools and two were also enriched in domestication and improvement genes previously identified in sorghum. These findings reinforce the evidence that domestication and improvement do not only affect the behaviors of a few genes but led to a large rewiring of the transcriptome during the domestication event and the improvement process. Overall, these analyses pave the way towards the identification of key domestication genes valuable for genetic resources characterization and breeding purposes.
The role of macrophage scavenger receptor 1 (Msr1) in prion pathogenesis
Authors: Li Bei , Chen Meiling , Aguzzi Adriano , Zhu Caihong
Published: November 2020

The progression of prion diseases is accompanied by the accumulation of prions in the brain. Ablation of microglia enhances prion accumulation and accelerates disease progression, suggesting that microglia play a neuroprotective role by clearing prions. However, the mechanisms underlying the phagocytosis and clearance of prion are largely unknown. The macrophage scavenger receptor 1 (Msr1) is an important phagocytic receptor expressed by microglia in the brain, and is involved in the uptake and clearance of soluble amyloid-β. We therefore asked whether Msr1 might play a role in prion clearance, and assessed the scavenger function of Msr1 in prion pathogenesis. We found that Msr1 expression was upregulated in prion-infected mouse brains. However, Msr1 deficiency did not change prion disease progression or lesion patterns. Prion deposition in Msr1 deficient mice was similar to their wild type littermates. In addition, prion-induced neuroinflammation was not affected by Msr1 ablation. We conclude that Msr1 does not play a major role in prion pathogenesis.
Long-term stability of avalanche scaling and integrative network organization in prefrontal and premotor cortex
Authors: Miller Stephanie R. , Yu Shan , Pajevic Sinisa , Plenz Dietmar
Published: November 2020

Ongoing neuronal activity in the cortex establishes functional networks of synchronization that reflect normal and pathological brain function. The reconstruction of these networks typically suffers from the use of indirect measures of neuronal activity at low spatiotemporal resolution and a lack of longitudinal tracking. Accordingly, the precise nature of the underlying synchronization dynamics and its translation into robust graph theoretical markers are not well characterized. Here, we studied the stability of cortical dynamics and reconstructed functional networks over many weeks in prefrontal and premotor cortex of awake nonhuman primates. We monitored neuronal population activity directly in the ongoing local field potential (LFP) at high spatial and temporal resolution using chronically implanted high-density microelectrode arrays. Ongoing activity was composed of neuronal avalanches exhibiting stable, inverted parabolic profiles with the collapse exponent of 2 in line with a critical branching process. Avalanche-based functional networks, reconstructed using a Normalized Count estimator, revealed robust integrative properties characterized by high neighborhood overlap between strongly connected nodes and robustness to weak-link pruning. “Entropy of mixing” analysis demonstrated progressive link reorganization over weeks. The long-term stability of avalanche scaling and integrative network organization should support the development of robust biomarkers to characterize normal and abnormal brain function.
HTTsilencing delays onset and slows progression of Huntington’s disease like phenotype: Monitoring with a novel neurovascular biomarker
Authors: Liu Hongshuai , Zhang Chuangchuang , Xu Jiadi , Jin Jing , Cheng Liam , Wu Qian , Wei Zhiliang , Liu Peiying , Lu Hanzhang , van Zijl Peter C. M. , Ross Christopher A. , Hua Jun , Duan Wenzhen
Published: November 2020

Huntington’s disease (HD) is a dominantly inherited, fatal neurodegenerative disorder caused by a CAG expansion in theHuntingtin(HTT) gene, coding for pathologic mutant HTT protein (mHTT). Because of its gain-of-function mechanism and monogenic etiology, strategies to lower HTT are being actively investigated as disease-modifying therapies. Most approaches are currently targeted at the manifest HD stage, when clinical outcomes are used to evaluate the effectiveness of therapy. However, as almost 50% of striatal volume has been lost at the time of onset of manifest HD it would be preferable to begin therapy in the premanifest period. An unmet challenge is how to evaluate therapeutic efficacy before the presence of clinical symptoms as outcome measures. To address this, we have been developing more sensitive biomarkers such as functional neuroimaging with the goal of identifying noninvasive biomarkers that provide insight into the best time to introduce HTT-lowering treatment. In this study, we mapped the temporal trajectories of arteriolar cerebral blood volumes (CBVa) using inflow-based vascular-space-occupancy (iVASO) MRI technique in an HD mouse model. Significantly elevated CBVa was evident in premanifest zQ175 HD mice prior to motor deficits and striatal atrophy, recapitulating altered CBVa in human premanifest HD. CRISPR/Cas9-mediated non-allele-specificHTTsilencing in striatal neurons restored altered CBVa in premanifest zQ175 mice, delayed onset of striatal atrophy, and slowed the progression of motor phenotype and brain pathology. This study showed the potential of CBVa as a noninvasive fMRI biomarker for premanifest HD clinical trials and demonstrates long-term benefits of introducing an HTT lowering treatment in the premanifest HD.
Complex trait–environment relationships underlie the structure of Wisconsin forest plant communities
Authors: Rolhauser Andres G. , Waller Donald M. , Tucker Caroline M.
Published: November 2020

Plant species shift in abundance as environmental conditions change because traits adapt species to particular conditions. As a result, trait values shift along environmental gradients—the so-called trait–environment relationships. These relationships are often assessed by regressing community-weighted mean (CWM) traits on environmental gradients. Such regressions (CWMr) assume that local communities exhibit centered optimum trait–abundance relationships and that traits are not independent from one another. However, the shape of trait–abundance relationships can vary widely along environmental gradients—reflecting the interaction between traits and gradients—and traits are usually interrelated. Accounting for these complexities should improve our ability to accurately describe trait–environment relationships. We tested these ideas by analyzing how abundances of 185 herbaceous understory species distributed among 189 forested sites in Wisconsin, USA, varied in response to four functional traits (vegetative height-VH, leaf size-LS, leaf mass per area-LMA, and leaf carbon content) and six soil and climate variables. A generalized linear mixed model (GLMM) allowed us to assess how the shape of trait–abundance relationships changed along environmental gradients for the 24 trait–environment combinations simultaneously. We then compared the resulting trait–environment relationships to those estimated via CWMr. The GLMM identified five significant trait–environment relationships that together explained ∼40% of variation in species abundances across sites. Temperature played important roles with warmer and more seasonal sites favoring taller plants. Soil texture and temperature seasonality affected LS and LMA more modestly; these seasonality effects declined at more seasonal sites. Only some traits under certain conditions showed centered optimum trait– abundance relationships. Concomitantly, CWMr identified 17 significant trait–environment relationships including effects of temperature, precipitation, and soil on LMA as often reported in other studies. Despite this overidentification, CWMr failed to detect significant temperature-seasonality effects found in the GLMM. Modeling the complexity of how traits and environments interact to affect plant abundance allows us to identify and rank key trait– environment relationships. Although the GLMM model was more complex compared to single CWM regressions, it identified a simpler hierarchy of trait–environment relationships that accurately and reliably predicted responses of forest understory species to gradients in environmental conditions.
Universal annotation of the human genome through integration of over a thousand epigenomic datasets
Authors: Vu Ha , Ernst Jason
Published: November 2020

Background

Genome-wide maps of chromatin marks such as histone modifications and open chromatin sites provide valuable information for annotating the non-coding genome, including identifying regulatory elements. Computational approaches such as ChromHMM have been applied to discover and annotate chromatin states defined by combinatorial and spatial patterns of chromatin marks within the same cell type. An alternative ‘stacked modeling’ approach was previously suggested, where chromatin states are defined jointly from datasets of multiple cell types to produce a single universal genome annotation based on all datasets. Despite its potential benefits for applications that are not specific to one cell type, such an approach was previously applied only for small-scale specialized purposes. Large-scale applications of stacked modeling have previously posed scalability challenges.

Results

Using a version of ChromHMM enhanced for large-scale applications, we applied the stacked modeling approach to produce a universal chromatin state annotation of the human genome using over 1000 datasets from more than 100 cell types, with the learned model denoted as the full-stack model. The full-stack model states show distinct enrichments for external genomic annotations, which we used in characterizing each state. Compared to per-cell-type annotations, the full-stack annotations directly differentiate constitutive from cell type specific activity and is more predictive of locations of external genomic annotations.

Conclusions

The full-stack ChromHMM model provides a universal chromatin state annotation of the genome and a unified global view of over 1000 datasets. We expect this to be a useful resource that complements existing per-cell-type annotations for studying the non-coding human genome.
Evaluating the Effects of Propiconazole on Hard Fescue (Festuca brevipila) via RNA sequencing and Liquid Chromatography–Mass Spectrometry
Authors: Qiu Yinjie , Petrella Dominic , Sessoms Florence , Yang Ya , Esler Mark , Hirsch Cory D. , Heineck Garett , Hegeman Adrian , Watkins Eric
Published: November 2020

Propiconazole is often used to remove fungal endophytes from turfgrass to study the effects ofEpichloëendophytes. However, besides a fungicidal effect, propiconazole can bind to the genes in the cytochrome P450 family and affect the biosynthesis of brassinosteroids. For this reason, outside of fungicidal application, propiconazole has also been used as plant growth regulator. In this study, we used a combination of RNA sequencing and liquid chromatography–mass spectrometry (LC-MS) to study how hard fescue (Festuca brevipila) responded to the high dose of propiconazole treatment. To test the long-term effect of the heavy use of propiconazole on plants, we inoculated withMicrodochium nivale(causal agent of pink snow mold) half year post the last fungicide application. Propiconazole-treated plants showed enhanced pink snow mold resistance. This study suggested that the high dose use of propiconazole fungicide resulted in phenotypic and physiological changes in the plant such as slow growth and change in disease resistance. Genes and pathways affected by propiconazole identified in this study provide turfgrass breeders new information for genetic improvement of hard fescue and also provide turfgrass management new ways to control turfgrass diseases.
Human methylome variation across Infinium 450K data on the Gene Expression Omnibus
Authors: Maden Sean K. , Thompson Reid F. , Hansen Kasper D. , Nellore Abhinav
Published: November 2020

While DNA methylation (DNAm) is the most-studied epigenetic mark, few recent studies probe the breadth of publicly available DNAm array samples. We collectively analyzed 35,360 Illumina Infinium HumanMethylation450K DNAm array samples published on the Gene Expression Omnibus (GEO). We learned a controlled vocabulary of sample labels by applying regular expressions to metadata and used existing models to predict various sample properties including epigenetic age. We found approximately two-thirds of samples were from blood, one-quarter were from brain, and one-third were from cancer patients. 19% of samples failed at least one of Illumina’s 17 prescribed quality assessments; signal distributions across samples suggest modifying manufacturer-recommended thresholds for failure would make these assessments more informative. We further analyzed DNAm variances in seven tissues (adipose, nasal, blood, brain, buccal, sperm, and liver) and characterized specific probes distinguishing them. Finally, we compiled DNAm array data and metadata, including our learned and predicted sample labels, into database files accessible via therecountmethylationR/Bioconductor companion package. Its vignettes walk the user through some analyses contained in this paper.
A network modelling approach to assess non-pharmaceutical disease controls in a worker population: An application to SARS-CoV-2
Authors: Hill Edward M. , Atkins Benjamin D. , Keeling Matt J. , Dyson Louise , Tildesley Michael J.
Published: November 2020

Background

As part of a concerted pandemic response to protect public health, businesses can enact non-pharmaceutical controls to minimise exposure to pathogens in workplaces and premises open to the public. Amendments to working practices can lead to the amount, duration and/or proximity of interactions being changed, ultimately altering the dynamics of disease spread. These modifications could be specific to the type of business being operated.

Methods

We use a data-driven approach to parameterise an individual-based network model for transmission of SARS-CoV-2 amongst the working population, stratified into work sectors. The network is comprised of layered contacts to consider the risk of spread in multiple encounter settings (workplaces, households, social and other). We analyse several interventions targeted towards working practices: mandating a fraction of the population to work from home; using temporally asynchronous work patterns; and introducing measures to create ‘COVID-secure’ workplaces. We also assess the general role of adherence to (or effectiveness of) isolation and test and trace measures and demonstrate the impact of all these interventions across a variety of relevant metrics.

Results

The progress of the epidemic can be significantly hindered by instructing a significant proportion of the workforce to work from home. Furthermore, if required to be present at the workplace, asynchronous work patterns can help to reduce infections when compared with scenarios where all workers work on the same days, particularly for longer working weeks. When assessing COVID-secure workplace measures, we found that smaller work teams and a greater reduction in transmission risk reduced the probability of large, prolonged outbreaks. Finally, following isolation guidance and engaging with contact tracing without other measures is an effective tool to curb transmission, but is highly sensitive to adherence levels.

Conclusions

In the absence of sufficient adherence to non-pharmaceutical interventions, our results indicate a high likelihood of SARS-CoV-2 spreading widely throughout a worker population. Given the heterogeneity of demographic attributes across worker roles, in addition to the individual nature of controls such as contact tracing, we demonstrate the utility of a network model approach to investigate workplace-targeted intervention strategies and the role of test, trace and isolation in tackling disease spread.
CLINICAL APPLICATIONS OF MACHINE LEARNING ON COVID-19: THE USE OF A DECISION TREE ALGORITHM FOR THE ASSESSMENT OF PERCEIVED STRESS IN MEXICAN HEALTHCARE PROFESSIONALS
Authors: Delgado-Gallegos Juan Luis , Avilés-Rodriguez Gener , Padilla-Rivas Gerardo R. , Ángeles Cosio-León María De los , Franco-Villareal Héctor , Zuñiga-Violante Erika , Romo-Cardenas Gerardo Salvador , Islas Jose Francisco
Published: November 2020

Stress and anxiety have shown to be indirect effects of the COVID-19 pandemic, therefore managing stress becomes essential. One of the most affected populations by the pandemic are healthcare professionals. Thus, it is paramount to understand and categorize their perceived levels of stress, as it can be a detonating factor leading to mental illness. In our study, we used a machine learning prediction model to help measure perceived stress; a C5.0 decision tree algorithm was used to analyze and classify datasets obtained from healthcare professionals of the northeast region of Mexico. Our analysis showed that 6 out of 102 instances were incorrectly classified. Missing two cases for mild, three for moderate and 1 for severe (accuracy of 94.1%), statistical correlation analysis was performed to ensure integrity of the method, in addition we concluded that severe stress cases can be related mostly to high levels of Xenophobia and Compulsive stress.
Inward and outward effectiveness of cloth masks, a surgical mask, and a face shield
Authors: Pan Jin , Harb Charbel , Leng Weinan , Marr Linsey C.
Published: November 2020

We evaluated the effectiveness of 11 face coverings for material filtration efficiency, inward protection efficiency on a manikin, and outward protection efficiency on a manikin. At the most penetrating particle size, the vacuum bag, microfiber cloth, and surgical mask had material filtration efficiencies >50%, while the other materials had much lower filtration efficiencies. However, these efficiencies increased rapidly with particle size, and many materials had efficiencies >50% at 2 μm and >75% at 5 μm. The vacuum bag performed best, with efficiencies of 54-96% for all three metrics, depending on particle size. The thin acrylic and face shield performed worst. Inward protection efficiency and outward protection efficiency were similar for many masks; the two efficiencies diverged for stiffer materials and those worn more loosely (e.g., bandana) or more tightly (e.g., wrapped around the head) compared to a standard earloop mask. Discrepancies between material filtration efficiency and inward/outward protection efficiency indicated that the fit of the mask was important. We calculated that the particle size most likely to deposit in the respiratory tract when wearing a mask is ∼2 μm. Based on these findings, we recommend a three-layer mask consisting of outer layers of a flexible, tightly woven fabric and an inner layer consisting of a material designed to filter out particles. This combination should produce an overall efficiency of >70% at the most penetrating particle size and >90% for particles 1 μm and larger if the mask fits well.
Assortative social mixing and sex disparities in tuberculosis burden
Authors: Shaweno Debebe , Horton Katherine , Hayes Richard , Dodd Peter J.
Published: November 2020

Globally, men have higher tuberculosis (TB) burden but the mechanisms underlying this sex disparity are not fully understood. Recent surveys of social mixing patterns have established moderate preferential within-sex mixing in many settings. This assortative mixing could amplify differences from other causes. We explored the impact of assortative mixing and factors differentially affecting disease progression and detection using a sex-stratified deterministic TB transmission model. We explored the influence of assortativity at disease-free and endemic equilibria, finding stronger effects during invasion and on increasing male:female prevalence (M:F) ratios than overall prevalence. Variance-based sensitivity analysis of endemic equilibria identified differential progression as the most important driver of M:F ratio uncertainty. We fitted our model to prevalence and notification data in examplar settings within a fully Bayesian framework. For our high M:F setting, random mixing reduced equilibrium M:F ratios by 12%(95%CrI 0 - 30%). Equalizing male case detection there led to a 20% (95%CrI 11 - 31%) reduction in M:F ratio over 10 years - insufficient to eliminate sex disparities. However, this potentially achievable improvement was associated with a meaningful 8%(95%CrI 4 - 14%) reduction in total TB prevalence over this time frame.
Acute nasal dryness in COVID-19
Authors: Navarra Jordi , Ruiz-Ceamanos Alba , Moreno Juan José , García-Basterrechea José María , de Haro-Licer Josep , Sinnett Scott , Spence Charles , Gallardo-Pujol David
Published: November 2020

One of the entry routes of SARS-CoV-2 is the nasal epithelium. Although mounting evidence suggests the presence of olfactory dysfunction, and even anosmia, in patients with COVID-19, it is not clear whether these patients also suffer from other “nasal” symptoms that may influence their olfaction. A group of 35 patients with COVID-19 (and a control group matched in gender and age) were surveyed about the presence of a variety of nasal symptoms that may be associated to drastic perturbations experienced in the nasal cavity (e.g., “excessive dryness” and/or a continual sensation of having had a “nasal douche”). We used a cross-sectional, retrospective survey, targeted at the general population by means of non-quoted, non-random, snowball sampling. Symptoms were assessed with absence/presence responses. The possible association between two continuously distributed latent variables from categorical variables was estimated by means of polychoric correlations. More than 68% of the patients reported at least one “nasal” symptom. The clinical group also experienced “a strange sensation in the nose” and having excessive nasal dryness significantly more often than the control group. Fifty-two percent of the patients (but only 3% of the control group) reported a constant sensation of having had a strong nasal douche. Nasal symptoms predominantly co-occurred with anosmia/hyposmia, and ageusia/hypogeusia, appeared principally before or during the other symptoms of COVID-19, and lasted for twelve days, in average. The presence of these nasal symptoms, and their early occurrence, could potentially facilitate early diagnosis of COVID-19 and initial social distancing efforts.
IMPACT OF THE CORONAVIRUS DISEASE 2019 PANDEMIC ON SURGICAL VOLUME IN JAPAN: A COHORT STUDY USING ADMINISTRATIVE DATA
Authors: Okuno Takuya , Takada Daisuke , Jung-ho Shin , Morishita Tetsuji , Itoshima Hisashi , Kunisawa Susumu , Imanaka Yuichi
Published: November 2020

Background

Internationally, the Coronavirus Disease (COVID-19) pandemic has caused unprecedented challenges for surgical staff to minimise the exposure to COVID-19 or save medical resources without harmful outcomes for patients, in accordance with the statement of each surgical society. However, no research has empirically validated declines in Japanese surgical volume or compared decrease rates of surgeries during the COVID-19 pandemic.

Material and Methods

We extracted 672,772 available cases of patients aged > 15 years who were discharged between July 1, 2018, and June 30, 2020. After categorisation of surgery, we calculated descriptive statistics to compare the year-over-year trend and conducted interrupted time series analysis to validate the decline.

Results

The year-over-year trend of all eight surgical categories decreased from April 2020 and reached a minimum in May 2020 (May: abdominal, 68.4%; thoracic, 85.8%; genitourinary, 78.6%; cardiovascular, 90.8%; neurosurgical, 69.1%; orthopaedic, 62.4%; ophthalmologic, 52.0%; ear/nose/throat, 27.3%). Interrupted time series analysis showed no significant trends in oncological and critical benign surgeries.

Conclusion

We demonstrated and validated a trend of reduction in surgical volume in Japan using administrative data applying interrupted time series analyses. Low priority surgeries, as categorised by the statement of each society, showed obvious and statistically significant declines in case volume during the COVID-19 pandemic.
The detection and stability of the SARS-CoV-2 RNA biomarkers in wastewater influent in Helsinki, Finland
Authors: Hokajärvi Anna-Maria , Rytkönen Annastiina , Tiwari Ananda , Kauppinen Ari , Oikarinen Sami , Lehto Kirsi-Maarit , Kankaanpää Aino , Gunnar Teemu , Al-Hello Haider , Blomqvist Soile , Miettinen Ilkka T. , Savolainen-Kopra Carita , Pitkänen Tarja
Published: November 2020

Wastewater-based surveillance of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is used to monitor the population-level prevalence of the COVID-19 disease. In many cases, due to lockdowns or analytical delays, the analysis of wastewater samples might only be possible after prolonged storage. In this study, the effect of storage conditions on the RNA copy numbers of the SARS-CoV-2 virus in wastewater influent was studied and compared to the persistence of norovirus over time at 4°C, −20°C, and −75°C using the reverse-transcription quantitative PCR (RT-qPCR) assays E-Sarbeco, N2, and norovirus GII. For the first time in Finland, the presence of SARS-CoV-2 RNA was tested in 24 h composite influent wastewater samples collected from Viikinmäki wastewater treatment plant, Helsinki, Finland. The detected and quantified SARS-CoV-2 RNA copy numbers of the wastewater sample aliquots taken during 19–20 April 2020 and stored for 29, 64, and 84 days remained surprisingly stable. In the stored samples, the SARS betacoronavirus and SARS-CoV-2 copy numbers, but not the norovirus GII copy numbers, seemed slightly higher when analyzed from the pre-centrifuged pellet—that is, the particulate matter of the influent—as compared with the supernatant (i.e., water fraction) used for ultrafiltration, although the difference was not statistically significant. Furthermore, when wastewater was spiked with SARS-CoV-2, linear decay at 4°C was observed on the first 28 days, while no decay was visible within 58 days at −20°C or −75°C. In conclusion, freezing temperatures should be used for storage when immediate SARS-CoV-2 RNA analysis from the wastewater influent is not possible. Analysis of the particulate matter of the sample, in addition to the water fraction, can improve the detection frequency.
Association of plasma proteins with rate of cognitive decline and dementia: 20-year follow-up of the Whitehall II and ARIC cohort studies
Authors: Lindbohm Joni V. , Mars Nina , Walker Keenan A. , Singh-Manoux Archana , Livingston Gill , Brunner Eric J. , Sipilä Pyry N. , Saksela Kalle , Ferrie Jane E. , Lovering Ruth , Williams Stephen A. , Hingorani Aroon D. , Gottesman Rebecca F. , Zetterberg Henrik , Kivimäki Mika
Published: November 2020

The role of circulating proteins in Alzheimer’s disease and related dementias is unknown. Using a follow-up of two decades, 4953 plasma proteins, and discovery (Whitehall II) and replication cohort (ARIC), we examined plasma proteins associated with cognitive decline rate and dementia. After replication and adjustment for known dementia risk factors, fifteen proteins were associated with cognitive decline rate and dementia. None of these were amyloid, tau, or neurofilament-related proteins. Currently approved medications can target five of the proteins. The results support systemic pathogenesis of dementias, may aid in early diagnosis, and suggest potential targets for drug development.
The effects of developmental trauma on reinforcement learning and its relationship to psychotic experiences: a behavioural study
Authors: Rezaie Rowan , Modaffar Mustapha , Jung Paul , Hindocha Chandni , Bisby James A , Bloomfield Michael A P
Published: November 2020

Background

Developmental psychological trauma can impact several key neurocognitive domains, including reward processing, and is associated with increased risk of psychosis in adulthood. Aberrant reinforcement learning (RL), an important component of reward processing, has been implicated in the pathophysiology of psychosis by altering information processing through changes in hierarchical predictive coding. We therefore sought to investigate RL in survivors of developmental trauma and its relationship to psychotic experiences.

Methods

We recruited two groups of adults, one with self-reported exposure to multiple forms of developmental trauma (n=115), and a control group without any known history of maltreatment (n=85). Participants completed measures of psychotic experiences (Community Assessment of Psychic Experiences) and undertook a probabilistic selection task designed to assess RL from positive versus negative outcomes. We analysed group differences for main effects and investigated relationships between developmental trauma, RL and psychotic experiences using regression modelling and mediation analysis.

Results

Developmental trauma was associated with psychotic experiences (adjusted R2=0.41,p=0.004) and impaired RL (Fdf=6.291,89,p=0.014). Impaired RL mediated the association between developmental trauma and psychotic experiences (indirect effectβ= 0.60, 95% CI, 0.01–1.36).

Conclusions

Our findings implicate aberrant RL as a possible mechanism through which developmental trauma may increase risk of psychosis. Further research is therefore warranted to understand the specific processes that characterise these putative trauma-induced vulnerability mechanisms and how they may contribute to the development of psychopathology.
Modeling and Sensitivity Analysis of Coronavirus Disease (COVID-19) Outbreak Prediction
Authors: Sedaghat Ahmad , Abbas Oloomi Seyed Amir , Malayer Mahdi Ashtian , Band Shahab S. , Mosavi Amir , Nadai Laszlo
Published: November 2020

Susceptible-infectious-recovered-deceased (SIRD) model is an essential model for outbreak prediction. This paper evaluates the performance of the SIRD model for the outbreak of COVID-19 in Kuwait, which initiated on 24 February 2020 by five patients in Kuwait. This paper investigates the sensitivity of the SIRD model for the development of COVID-19 in Kuwait based on the duration of the progressed days of data. For Kuwait, we have fitted the SIRD model to COVID-19 data for 20, 40, 60, 80, 100, and 116 days of data and assessed the sensitivity of the model with the number of days of data. The parameters of the SIRD model are obtained using an optimization algorithm (lsqcurvefit) in MATLAB. The total population of 50,000 is equally applied for all Kuwait time intervals. Results of the SIRD model indicate that after 40 days, the peak infectious day can be adequately predicted. Although error percentage from sensitivity analysis suggests that different exposed population sizes are not correctly predicted. SIRD type models are too simple to robustly capture all features of COVID-19, and more precise methods are needed to tackle the correct trends of a pandemic.
Assessment of COVID-19 vaccine acceptance among healthcare workers in Los Angeles
Authors: Gadoth Adva , Halbrook Megan , Martin-Blais Rachel , Gray Ashley , Tobin Nicole H. , Ferbas Kathie G. , Aldrovandi Grace M. , Rimoin Anne W.
Published: November 2020

Importance

Healthcare workers (HCW) are slated to be early recipients of SARS-CoV-2 vaccines due to increased risk of exposure to patients with COVID-19, and will be tasked with administering approved vaccines to the general population. As lynchpins of the vaccination effort, HCWs’ opinions of a vaccine’s safety and efficacy may affect both public perception and uptake of the vaccine. Therefore, it is crucial to understand and address potential hesitancy prior to vaccine administration.

Objective

To understand healthcare workers’ attitudes about vaccine safety, efficacy, and acceptability in the context of the COVID-19 pandemic, including acceptance of a novel coronavirus vaccine.

Design, Setting, Participants

A cross-sectional survey was distributed to participants enrolled in a longitudinal cohort study surveilling SARS-CoV-2 infection among 1,093 volunteer sampled University of California, Los Angeles (UCLA) Health System employees. Surveys were completed online between September 24 and October 16, 2020. In total, 609 participants completed this supplemental survey.

Results

We averaged a 9-statement Likert scale matrix scored from 1 (“strongly disagree”) to 5 (“strongly agree”) and found respondents overwhelmingly confident about vaccine safety (4.47); effectiveness (4.44); importance, self-protection, and community health (4.67). Notably, 47.3% of respondents reported unwillingness to participate in a coronavirus vaccine trial, and most (66.5%) intend to delay vaccination. The odds of reporting intent to delay coronavirus vaccine uptake were 4.15 times higher among nurses, 2.45 times higher among other personnel with patient contact roles, and 2.15 times higher among those without patient contact compared to doctors. Evolving SARS-CoV-2 science (76.0%), current political climate (57.6%), and fast-tracked vaccine development timeline (83.4%) were cited as primary variables impacting HCW decisions to undergo vaccination. Of note, these results were obtained prior to release of Phase III data from companies manufacturing vaccines in the U.S.

Conclusions and Relevance

Despite overall confidence in vaccines, a majority of HCW expressed concerns over a novel coronavirus vaccine. A large proportion plan to delay vaccine uptake due to concerns about expedited development, emerging scientific discoveries, and the political climate. Forthcoming vaccination campaigns must address these unique points of coronavirus vaccine hesitancy in order to achieve adequate vaccine coverage.
The loops of the N-SH2 binding cleft do not serve as allosteric switch in SHP2 activation
Authors: Anselmi Massimiliano , Hub Jochen S
Published: November 2020

The Src homology-2 domain containing phosphatase SHP2 is a critical regulator of signal transduction, being implicated in cell growth and differentiation. Activating mutations cause developmental disorders and act as oncogenic drivers in hematologic cancers. SHP2 is activated by phosphopeptide binding to the N-SH2 domain, triggering the release of N-SH2 from the catalytic PTP domain. Based on early crystallographic data, it has been widely accepted that opening of the binding cleft of N-SH2 serves as the key "allosteric switch" driving SHP2 activation. To test the putative coupling between binding cleft opening and SHP2 activation as assumed by the "allosteric switch" model, we critically reviewed structural data of SHP2 and we used extensive molecular dynamics (MD) simulation and free energy calculations of isolated N-SH2 in solution, SHP2 in solution, and SHP2 in a crystal environment. Our results demonstrate that the binding cleft in N-SH2 is constitutively flexible and open in solution, and that a closed cleft found in certain structures is a consequence of crystal contacts. The degree of opening of the binding cleft has only a negligible effect on the free energy of SHP2 activation. Instead, SHP2 activation is greatly favored by the opening of the central β-sheet of N-SH2. We conclude that opening of the N-SH2 binding cleft is not the key allosteric switch triggering SHP2 activation.
Characterization of the first cultured free-living representative of Candidatus Izimaplasma uncovers its unique biology
Authors: Zheng Rikuan , Liu Rui , Shan Yeqi , Cai Ruining , Liu Ge , Sun Chaomin
Published: November 2020

Candidatus Izimaplasma, an intermediate in the reductive evolution from Firmicutes to Mollicutes, was proposed to represent a novel class of free-living wall-less bacteria within the phylum Tenericutes found in deep-sea methane seeps. Unfortunately, the paucity of marine isolates currently available has limited further insights into their physiological and metabolic features as well as ecological roles. Here, we present a detailed description of the phenotypic traits, genomic data and central metabolisms tested in both laboratorial and deep-sea environments of the novel strain zrk13, which allows for the first time the reconstruction of the metabolic potential and lifestyle of a member of the tentatively defined Candidatus Izimaplasma. On the basis of the description of strain zrk13, the novel species and genus Xianfuyuplasma coldseepsis is proposed. Notably, DNA degradation driven by X. coldseepsis zrk13 was detected in both laboratorial and in situ conditions, strongly indicating it is indeed a key DNA degrader. Moreover, the putative genes determining degradation broadly distribute in the genomes of other Izimaplasma members. Given extracellular DNA is a particularly crucial phosphorus as well as nitrogen and carbon source for microorganisms in the seafloor, Izimaplasma bacteria are thought to be important contributors to the biogeochemical cycling in the deep ocean.
Adherent cell remodeling on micropatterns is modulated by Piezo1 channels
Authors: Jetta Deekshitha , Fard Mohammad Reza Bahrani , Sachs Frederick , Munechika Katie , Hua Susan Z.
Published: November 2020

Adherent cells utilize local environmental cues to make decisions on their growth and movement. We have previously shown that HEK293 cells grown on the fibronectin stripe patterns were elongated. Here we show that Piezo1 function is involved in cell spreading. Inhibiting the Rho-ROCK pathway also reversibly inhibited cell extension indicating that myosin contractility is involved. Piezo1 expressing HEK cells plated on fibronectin stripes elongated, while a knockout of Piezo1 eliminated elongation. Inhibiting Piezo1 conductance using GsMTx4 or Gd3+blocked cell spreading, but the cells grew thin tail-like extensions along the patterns. Images of GFP-tagged Piezo1 showed plaques of Piezo1 moving to the extrusion edges, co-localized with focal adhesions. Surprisingly, in non-spreading cells Piezo1 was located primarily on the nuclear envelope. The growth of thin extrusion tails did not occur in Piezo1 knockout cells suggesting that Piezo1 may have functions besides acting as a cation channel.