bluuebunny/crossref_metadata_2025 huggingface dataset:
Development and application of Pandemic Projection Measures (PPM) for forecasting the COVID-19 outbreak
Authors: Chang Shu-Ren
Published: June 2020

This 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 The outdated results should not be used to compared with today’s outbreak trend.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

Real-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

Obesity 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

When 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

We 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

Intracortical 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 Statement

Intracortical 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

Enzyme 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

Over 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.
Structural basis of mechano-chemical coupling by the mitotic kinesin KIF14
Authors: Benoit Matthieu P.M.H. , Asenjo Ana B. , Paydar Mohammadjavad , Dhakal Sabin , Kwok Benjamin H. , Sosa Hernando
Published: June 2020

KIF14 is a mitotic kinesin protein important for cytokinesis. Its overexpression is associated with a variety of cancers and mutations in KIF14 result in cerebral and renal development defects. Like other kinesins, KIF14 contains a highly conserved catalytic motor domain where the energy from ATP hydrolysis is converted to directed movement along microtubules. Although much is known regarding the molecular mechanism of kinesin motility, there is a lack of structural information of kinesin-microtubule interactions at sufficient resolution to unambiguously assess how conformational changes related to ATP hydrolysis, microtubule binding and translocation are coupled. Here we determined the near-atomic resolution cryo-electron microscopy structures of five different KIF14 constructs bound to microtubules in the presence of different nucleotide analogues mimicking distinct steps of the ATPase cycle. Eighteen independent structures together with supporting functional assays provide a comprehensive view of the kinesin conformational changes occurring with microtubule and nucleotide binding. Our data shows that: 1) microtubule binding induces opening of the KIF14 nucleotide binding pocket; 2) AMP-PNP and ADP-AlFxinduce closure of the nucleotide binding pocket in microtubule bound KIF14 and this conformational change is allosterically controlled by the neck-linker domain; 3) the neck-linker domain when undocked prevents the nucleotide-binding-pocket to fully close and dampens ATP hydrolysis; 4) fifteen neck-linker residues are required to assume the docked conformation; 5) the nucleotide analogue ADP-AlFxadopts a distinct configuration in an open nucleotide-binding-pocket; 6) the neck-linker position controls the hydrolysis step rather than nucleotide binding in the KIF14 ATPase cycle; 7) the two motor domains of a KIF14 dimer adopt distinct conformations when simultaneously bound to the microtubule. These observations provide the structural basis for a coordinated chemo-mechanical kinesin plus end translocation model.
Deep learning classification of lipid droplets in quantitative phase images
Authors: Sheneman L. , Stephanopoulos G. , Vasdekis A. E.
Published: June 2020

We report the application of supervised machine learning to the automated classification of lipid droplets in label-free, quantitative-phase images. By comparing various machine learning methods commonly used in biomedical imaging and remote sensing, we found convolutional neural networks to outperform others, both quantitatively and qualitatively. We describe our imaging approach, all implemented machine learning methods, and their performance with respect to computational efficiency, required training resources, and relative method performance measured across multiple metrics. Overall, our results indicate that quantitative-phase imaging coupled to machine learning enables accurate lipid droplet classification in single living cells. As such, the present paradigm presents an excellent alternative of the more common fluorescent and Raman imaging modalities by enabling label-free, ultra-low phototoxicity, and deeper insight into the thermodynamics of metabolism of single cells.

Author Summary

Recently, quantitative-phase imaging (QPI) has demonstrated the ability to elucidate novel parameters of cellular physiology and metabolism without the need for fluorescent staining. Here, we apply label-free, low photo-toxicity QPI to yeast cells in order to identify lipid droplets (LDs), an important organelle with key implications in human health and biofuel development. Because QPI yields low specificity, we explore the use of modern machine learning methods to rapidly identify intracellular LDs with high discriminatory power and accuracy. In recent years, machine learning has demonstrated exceptional abilities to recognize and segment objects in biomedical imaging, remote sensing, and other areas. Trained machine learning classifiers can be combined with QPI within high-throughput analysis pipelines, allowing for efficient and accurate identification and quantification of cellular components. Non-invasive, accurate and high-throughput classification of these organelles will accelerate research and improve our understanding of cellular functions with beneficial applications in biofuels, biomedicine, and more.
A septin GTPase scaffold of dynein-dynactin motors triggers retrograde lysosome transport
Authors: Kesisova Ilona A. , Robinson Benjamin P. , Spiliotis Elias T.
Published: June 2020

The metabolic and signaling functions of lysosomes depend on their intracellular positioning and trafficking, but the underlying mechanisms are little understood. Here, we have discovered a novel septin GTPase-based mechanism for retrograde lysosome transport. We found that septin 9 (SEPT9) associates with lysosomes, promoting the perinuclear localization of lysosomes in a Rab7-independent manner. SEPT9 targeting to mitochondria and peroxisomes is sufficient to recruit dynein and cause perinuclear clustering. We show that SEPT9 interacts with both dynein and dynactin through its GTPase domain and N-terminal extension, respectively. Strikingly, SEPT9 associates preferentially with the dynein intermediate chain (DIC) in its GDP-bound state, which favors dimerization and assembly into septin multimers. In response to oxidative cell stress induced by arsenite, SEPT9 localization to lysosomes is enhanced, promoting the perinuclear clustering of lysosomes. We posit that septins function as GDP-activated scaffolds for the cooperative assembly of dynein-dynactin, providing an alternative mechanism of retrograde lysosome transport at steady state and during cellular adaptation to stress.

The intracellular position of lysosomes is critical for cell metabolism and signaling. Kesisova et al discovered a membrane-associated septin GTPase scaffold of dynein-dynactin that promotes retrograde traffic and perinuclear lysosome clustering at steady state and in response to oxidative stress.
Sex-specific recombination predicts parent of origin for recurrent genomic disorders
Authors: Mosley Trenell , Richard Johnston H. , Cutler David J. , Zwick Michael E. , Mulle Jennifer G.
Published: June 2020

Genomic disorders are caused by structural rearrangements of the genome that generally occur during meiosis1. Often the rearrangements result in large-scale (> 1 kb) copy number variants (CNV; deletions or duplications ≥ 1 kb)2,3. Recurrent pathogenic CNVs harbor similar breakpoints in multiple unrelated individuals and are primarily formed via non-allelic homologous recombination (NAHR)3,4. Several pathogenic NAHR-mediated recurrent CNV loci demonstrate biases for parental origin ofde novoCNVs5–9. However, the mechanism underlying these biases is not well understood. Here we have curated parent of origin data for multiple pathogenic CNV loci and demonstrate a significant association between sex-specific differences in meiotic recombination and parental origin biases at these loci. Our results suggest that parental-origin of CNVs is largely controlled by sex-specific recombination rates and bring into light the need to consider these differences when seeking to determine the factors underlying risk for structural variation.
Test, track, and trace: How is the NHSX Covid app performing in a hospital setting?
Authors: Filer Joshua , Gheorghiu Daniel
Published: June 2020

Objective

To assess the uptake and use of the trial contact tracing app developed by NHSX by healthcare workers.

Design

Cross-sectional study using survey questionnaire.

Setting

Healthcare industry: St Mary’s Hospital, a small NHS district hospital on the Isle of Wight, United Kingdom.

Participants

NHS staff members employed by the Isle of Wight NHS Trust.

Results

Of 3100 eligible staff members, 462 (~15%) responded to the survey. Of the respondents, 90% were aged between 31 and 65, and half had direct patient contact through their job role. Almost three quarters (73%) used social media apps on their smartphones. 421 out of 460 respondents had no trouble downloading and installing the NHSX Covid app on their smartphones. 20% of respondents were left confused by instructions to turn off Bluetooth when wearing PPE. Only 35 people either had to report symptoms or received an alert of contact with a suspected covid case. Of these over 20% were not clear what to do in such a situation.

Conclusions

The trial app has been embraced and adopted well. Many have experienced no problems with it. However, some healthcare workers have been unable to download or install the app due to compatibility issues and some have been left confused by having to turn off Bluetooth whilst wearing PPE.

This raises questions as to the effectiveness of the app for its intended purpose in contact tracing efforts.

Recommendations

We recommend that the wording of alerts and guidance provided by the app be made clearer and more accessible. We also recommend developments to the app to facilitate use by healthcare workers in a clinical setting. We also propose that ‘app instructors’ be made available in hospitals to ensure that patients and staff can access help and advice on use of the app.
It’s the very time to learn a pandemic lesson: why have predictive techniques been ineffective when describing long-term events?
Authors: Kovriguine D. , Nikitenkova S.
Published: June 2020

We have detected a regular component of the monitoring error of officially registered total cases of the spread of the current pandemic. This regular error component explains the reason for the failure of a priori mathematical modelling of probable epidemic events in different countries of the world. Processing statistical data of countries that have reached an epidemic peak has shown that this regular monitoring obeys a simple analytical regularity which allows us to answer the question: is this or that country that has already passed the threshold of the epidemic close to its peak or is still far from it?
The impact of lung function on cardiovascular diseases and cardiovascular risk factors: a two sample bi-directional Mendelian randomization study
Authors: Au Yeung SL , Borges MC , Lawlor DA , Schooling CM
Published: June 2020

Background

Observational studies suggested lung function is inversely associated with cardiovascular disease (CVD) although these studies could be susceptible to residual confounding. We conducted a 2 sample Mendelian randomization study using summary statistics from genome wide association studies (GWAS) to clarify the role of lung function in CVD and its risk factors, and conversely the role of CVD in lung function.

Methods

We obtained genetic instruments for forced expiratory volume in 1 second (FEV1) and forced vital capacity (FVC) from publicly available UK Biobank summary statistics (n = 421,986). We applied these genetic instruments for FEV1 (260) and FVC (320) to publicly available GWAS summary statistics for coronary artery disease (CAD) (n = 184,305), stroke and its subtypes (n = 446,696), atrial fibrillation (n = 1,030,836), and heart failure (n = 977,320) and cardiovascular risk factors. Inverse variance weighting was used to assess the impact of lung function on these outcomes. Sensitivity analyses included MR-Egger, weighted median, MR-PRESSO, and multivariable Mendelian randomization. We also conducted bi-directional Mendelian randomization to assess whether CVD affects lung function.

Results

FEV1 and FVC were inversely associated with CAD (odds ratio (OR) per standard deviation (SD) increase, 0.72 (95% confidence interval (CI) 0.63 to 0.82) and 0.70 (95%CI 0.62 to 0.78)), overall stroke (0.87 (95%CI 0.77 to 0.97), 0.90 (0.82 to 1.00)), ischemic stroke (0.87 (95%CI 0.77 to 0.99), 0.90 (95%CI 0.80 to 1.00)), small vessel stroke (0.78, (95%CI 0.61 to 1.00), 0.74 (95%CI 0.61 to 0.92)), and large artery stroke (0.69 (95%CI 0.54 to 0.89), 0.72 (95%CI 0.57 to 0.91)). FEV1 and FVC were inversely associated with type 2 diabetes (0.75 (95%CI 0.62 to 0.90), 0.67 (95%CI 0.58 to 0.79)) and systolic blood pressure. Sensitivity analyses produced similar direction for most outcomes although the magnitude sometimes differed. Adjusting for height attenuated results for CAD (e.g. OR for 1SD FEV1 0.95 (0.76 to 1.20), but this may reflect weak instrument bias. This adjustment did not attenuate effects for stroke or type 2 diabetes. No strong evidence was observed for CVD affecting lung function.

Conclusion

Higher lung function likely protect against CAD and stroke.
Dynamic functional connectivity analysis reveals transiently increased segregation in patients with severe stroke
Authors: Bonkhoff Anna K. , Schirmer Markus D. , Bretzner Martin , Etherton Mark , Donahue Kathleen , Tuozzo Carissa , Nardin Marco , Giese Anne-Katrin , Wu Ona , Calhoun Vince , Grefkes Christian , Rost Natalia S.
Published: June 2020

Background and Purpose

To explore the whole-brain dynamic functional network connectivity patterns in acute ischemic stroke (AIS) patients and their relation to stroke severity in the short and long term.

Methods

We investigated large-scale dynamic functional network connectivity of 41 AIS patients two to five days after symptom onset. Re-occurring dynamic connectivity configurations were obtained using a sliding window approach and k-means clustering. We evaluated differences in dynamic patterns between three NIHSS-stroke severity defined groups (mildly, moderately, and severely affected patients). Furthermore, we established correlation analyses between dynamic connectivity estimates and AIS severity as well as neurological recovery within the first 90 days after stroke (DNIHSS). Finally, we built Bayesian hierarchical models to predict acute ischemic stroke severity and examine the inter-relation of dynamic connectivity and clinical measures, with an emphasis on white matter hyperintensity lesion load.

Results

We identified three distinct dynamic connectivity configurations in the early post-acute stroke phase. More severely affected patients (NIHSS 10–21) spent significantly more time in a highly segregated dynamic connectivity configuration that was characterized by particularly strong connectivity (three-level ANOVA: p<0.05, post hoc t-tests: p<0.05, FDR-corrected for multiple comparisons). Recovery, as indexed by the realized change of the NIHSS over time, was significantly linked to the acute dynamic connectivity between bilateral intraparietal lobule and left angular gyrus (Pearson’s r = –0.68, p<0.05, FDR-corrected). Increasing dwell times, particularly those in a very segregated connectivity configuration, predicted higher acute stroke severity in our Bayesian modelling framework.

Conclusions

Our findings demonstrate transiently increased segregation between multiple functional domains in case of severe AIS. Dynamic connectivity involving default mode network components significantly correlated with recovery in the first three months post-stroke.
Genetic variants of PIEZO1 associate with COVID-19 fatality
Authors: Cheng C.W. , Deivasikamani V. , Ludlow M.J. , De Vecchis D. , Kalli A.C. , Beech D.J. , Sukumar P.
Published: June 2020

Fatality from coronavirus disease 19 (COVID-19) is a major problem globally and so identification of its underlying molecular mechanisms would be helpful. The combination of COVID-19 clinical data and genome sequence information is providing a potential route to such mechanisms. Here we took a candidate gene approach to UK Biobank data based on the suggested roles of endothelium and membrane proteins in COVID-19. We focussed on the PIEZO1 gene, which encodes a non-selective cation channel that mediates endothelial responses to blood flow. The analysis suggests 3 missense PIEZO1 single nucleotide polymorphisms (SNPs) associated with COVID-19 fatality independently of risk factors. All of them affect amino acids in the proximal N-terminus of PIEZO1, which is an unexplored region of the protein. By using molecular modelling we predict location of all 3 amino acids to a common outward-facing structure of unknown functional significance at the tips of the PIEZO1 propeller blades. Through genome sequence analysis we show that these SNPs vary in prevalence with ethnicity and that the most significant SNP (rs7184427) varies between 65 to 90% even though the reference amino acid is evolutionarily conserved. The data suggest PIEZO1 as a contributor to COVID-19 fatality and factor in ethnic susceptibility.
Monocyte Subsets with High Osteoclastogenic Potential and Their Epigenetic Regulation Orchestrated by IRF8
Authors: Das Amitabh , Wang Xiaobei , Kang Jessica , Coulter Alyssa , Shetty Amol C. , Bachu Mahesh , Brooks Stephen R. , Dell’Orso Stefania , Foster Brian L. , Fan Xiaoxuan , Ozato Keiko , Somerman Martha J. , Thumbigere-Math Vivek
Published: June 2020

Osteoclasts (OCs) are bone resorbing cells formed by the serial fusion of monocytes. In mice and humans, three distinct subsets of monocytes exist; however, it is unclear if all of them exhibit osteoclastogenic potential. Here we show that in wild-type mice, Ly6Chiand Ly6Cintmonocytes are the primary source of OC formation when compared to Ly6C−monocytes. Their osteoclastogenic potential is dictated by increased expression of signaling receptors and activation of pre-established transcripts, as well as de novo gain in enhancer activity and promoter changes. In the absence of IRF8, a transcription factor important for myelopoiesis and osteoclastogenesis, all three monocyte subsets are programmed to display higher osteoclastogenic potential. Enhanced NFATc1 nuclear translocation and amplified transcriptomic and epigenetic changes initiated at early developmental stages direct the increased osteoclastogenesis inIrf8deficient mice. Collectively, our study provides novel insights into the transcription factors and activecis-regulatory elements that regulate OC differentiation.
EarlyC. elegansembryos modulate cell division timing to compensate for, and survive, the discordant conditions of a severe temperature gradient
Authors: Terry Eric , Birsoy Bilge , Bothman David , Sigurdson Marin , Joshi Pradeep M. , Meinhart Carl , Rothman Joel H.
Published: June 2020

Despite a constant barrage of intrinsic and environmental noise, embryogenesis is remarkably reliable, suggesting the existence of systems that ensure faithful execution of this complex process. We report that earlyC. elegansembryos, which normally show a highly reproducible lineage and cellular geometry, can compensate for deviations imposed by the discordant conditions of a steep temperature gradient generated in a microfluidic device starting at the two-cell stage. Embryos can survive a gradient of up to 7.5°C across the 50-micron axis through at least three rounds of division. This response is orientation-dependent: survival is higher when the normally faster-dividing anterior daughter of the zygote, AB, but not its sister, the posterior P1, is warmer. We find that temperature-dependent cellular division rates in the early embryo can be effectively modeled by a modification of the Arrhenius equation. Further, both cells respond to the gradient by dramatically reducing division rates compared to the predicted rates for the temperature experienced by the cell even though the temperature extremes are well within the range for normal development. This finding suggests that embryos may sense discordance and slow development in response. We found that in the cohort of surviving embryos, the cell on the warmer side at the two-cell stage shows a greater average decrease in expected division rate than that on the cooler side, thereby preserving the normal cellular geometry of the embryo under the discordant conditions. A diminished average slow-down response correlated with lethality, presumably owing to disruption of normal division order and developmental fidelity. Remarkably, some inviable embryos in which the canonical division order was reversed nonetheless proceeded through relatively normal morphogenesis, suggesting a subsequent compensation mechanism independent of cell division control. These findings provide evidence for a previously unrecognized process inC. elegansembryos that may serve to compensate for deviations imposed by aberrant environmental conditions, thereby resulting in a high-fidelity output.
Systematic interrogation of mutation groupings reveals divergent downstream expression programs within key cancer genes
Authors: Grzadkowski Michal R. , Manning Hannah , Somers Julia , Demir Emek
Published: June 2020

Genes implicated in tumorigenesis often exhibit diverse sets of genomic variants in the tumor cohorts within which they are frequently mutated. We sought to identify the downstream expression effects of these perturbations and to find whether or not this heterogeneity at the genomic level is reflected in a corresponding heterogeneity at the transcriptomic level. Applying a novel hierarchical framework for organizing the mutations present in a cohort along with machine learning pipelines trained on sample expression profiles we systematically interrogated the signatures associated with combinations of perturbations recurrent in cancer. This allowed us to catalogue the mutations with discernible downstream expression effects across a number of tumor cohorts as well as to uncover and characterize a multitude of cases where subsets of a genes mutations are clearly divergent in their function from the remaining mutations of the gene.
Membrane potential regulates Hedgehog signaling and compartment boundary maintenance in theDrosophilawing disc
Authors: Emmons-Bell Maya , Yasutomi Riku , Hariharan Iswar K.
Published: June 2020

TheDrosophilawing imaginal disc is composed of two lineage-restricted populations of cells separated by a smooth boundary. Hedgehog (Hh) from posterior cells activates a signaling pathway in anterior cells near the boundary which is necessary for boundary maintenance. Here, we show that membrane potential is patterned in the wing disc. Anterior cells near the boundary, where Hh signaling is most active, are more depolarized than posterior cells across the boundary. Elevated expression of the ENaC channel Ripped Pocket (Rpk), observed in these anterior cells, requires Hh. Antagonizing Rpk reduces depolarization and disrupts the compartment boundary. Using genetic and optogenetic manipulations, we show that membrane depolarization promotes membrane localization of Smoothened and augments Hh signaling. Thus, membrane depolarization and Hh-dependent signaling mutually reinforce each other in this region. Finally, clones of depolarized cells survive preferentially in the anterior compartment and clones of hyperpolarized cells survive preferentially in the posterior compartment.
A physiological role for GABAAreceptor desensitization – induction of long-term potentiation at inhibitory synapses
Authors: Field Martin , Thomas Philip , Smart Trevor G
Published: June 2020

GABAAreceptors (GABAARs) are pentameric ligand-gated ion channels distributed throughout the brain where they mediate synaptic and tonic inhibition. Following activation, these receptors undergo desensitization which involves entry into long-lived agonist-bound closed states. Although the kinetic effects of this state are recognised and its structural basis has been uncovered, the physiological impact of desensitization on inhibitory neurotransmission remains unknown. Here we describe an enduring new form of long-term potentiation at inhibitory synapses that elevates synaptic current amplitude for 24 hrs following desensitization of GABAARs in response to prolonged agonist exposure or allosteric modulation. Using receptor mutants and allosteric modulators we demonstrate that desensitization of GABAARs facilitates their phosphorylation by PKC, which increases the number of receptors at inhibitory synapses. These observations provide a new physiological relevance to the desensitized state of GABAARs, acting as a signal to regulate the efficacy of inhibitory synapses during prolonged periods of inhibitory neurotransmission.
Magnetosomes could be protective shields against metal stress in magnetotactic bacteria
Authors: Muñoz D. , Marcano L. , Martín-Rodríguez R. , Simonelli L. , Serrano A. , García-Prieto A. , Fdez-Gubieda M.L. , Muela A.
Published: June 2020

Magnetotactic bacteria are aquatic microorganisms with the ability to biomineralise membrane-enclosed magnetic nanoparticles, called magnetosomes. These magnetosomes are arranged into a chain that behaves as a magnetic compass, allowing the bacteria to align in and navigate along the Earth’s magnetic field lines. According to the magneto-aerotactic hypothesis, the purpose of producing magnetosomes is to provide the bacteria with a more efficient movement within the stratified water column, in search of the optimal positions that satisfy their nutritional requirements. However, magnetosomes could have other physiological roles, as proposed in this work. Here we analyse the role of magnetosomes in the tolerance ofMagnetospirillum gryphiswaldenseMSR-1 to transition metals (Co, Mn, Ni, Zn, Cu). By exposing bacterial populations with and without magnetosomes to increasing concentrations of metals in the growth medium, we observe that the tolerance is significantly higher when bacteria have magnetosomes. The resistance mechanisms triggered in magnetosome-bearing bacteria under metal stress have been investigated by means of x-ray absorption near edge spectroscopy (XANES). XANES experiments were performed both on magnetosomes isolated from the bacteria and on the whole bacteria, aimed to assess whether bacteria use magnetosomes as metal storages, or whether they incorporate the excess metal in other cell compartments. Our findings reveal that the tolerance mechanisms are metal-specific: Mn, Zn and Cu are incorporated in both the magnetosomes and other cell compartments; Co is only incorporated in the magnetosomes, and Ni is incorporated in other cell compartments. In the case of Co, Zn and Mn, the metal is integrated in the magnetosome magnetite mineral core.
Paleoclimate and current climate collectively shape the phylogenetic and functional diversity of trees worldwide
Authors: Guo Wen-Yong , Serra-Diaz Josep M. , Schrodt Franziska , Eiserhardt Wolf L. , Maitner Brian S. , Merow Cory , Violle Cyrille , Blach-Overgaard Anne , Zhang Jian , Anand Madhur , Belluau Michaël , Bruun Hans Henrik , Byun Chaeho , Catford Jane A. , Cerabolini Bruno E. L. , Chacón-Madrigal Eduardo , Ciccarelli Daniela , Cornelissen Johannes H. C. , Dang-Le Anh Tuan , de Frutos Angel , Dias Arildo S. , Giroldo Aelton B. , Gutiérrez Alvaro G. , Hattingh Wesley , He Tianhua , Hietz Peter , Hough-Snee Nate , Jansen Steven , Kattge Jens , Klein Tamir , Komac Benjamin , Kraft Nathan , Kramer Koen , Lavorel Sandra , Lusk Christopher H. , Martin Adam R. , Mencuccini Maurizio , Michaletz Sean T. , Minden Vanessa , Mori Akira S. , Niinemets Ülo , Onoda Yusuke , Onstein Renske E. , Peñuelas Josep , Pillar Valério D. , Pisek Jan , Pound Matthew J. , Robroek Bjorn J.M. , Schamp Brandon , Slot Martijn , Sosinski Ênio , Soudzilovskaia Nadejda A. , Thiffault Nelson , van Bodegom Peter , van der Plas Fons , Wright Ian J. , Zheng Jingming , Enquist Brian J. , Svenning Jens-Christian
Published: June 2020

Trees are of vital importance for ecosystem functioning and services at local to global scales, yet we still lack a detailed overview of the global patterns of tree diversity and the underlying drivers, particularly the imprint of paleoclimate. Here, we present the high-resolution (110 km) worldwide mapping of tree species richness, functional and phylogenetic diversities based on ∼7 million quality-assessed occurrences for 46,752 tree species (80.5% of the estimated total number of tree species), and subsequent assessments of the influence of paleo-climate legacies on these patterns. All three tree diversity dimensions exhibited the expected latitudinal decline. Contemporary climate emerged as the strongest driver of all diversity patterns, with Pleistocene and deeper-time (>107years) paleoclimate as important co-determinants, and, notably, with past cold and drought stress being linked to reduced current diversity. These findings demonstrate that tree diversity is affected by paleoclimate millions of years back in time and highlight the potential for tree diversity losses from future climate change.
Development and application of a metabolomic tool to assess exposure of an estuarine amphipod to pollutants in the environment
Authors: Yanagihara Miina , Nakajima Fumiyuki , Tobino Tomohiro
Published: June 2020

Identifying substances in sediment that cause adverse effects on benthic organisms has been implemented as an effective source-control strategy. However, the identification of such substances is difficult due to the complicated interactions between liquid and solid phases and organisms. Metabolomic approaches have been utilized to assess the effects of toxicants on various organisms; however, the relationships between the toxicants and metabolomic profiles have not been generalized, and it makes impractical to identify major toxicants from metabolomic information. In this study, we used partial least squares discriminant analysis (PLS-DA) to investigate these relationships. The objective of this study was to construct PLS-DA models using the metabolomic profiles of the benthic amphipodGrandidierella japonicato assess the exposure effects of target toxicants and to demonstrate the utility of these models to assess the effects of chemicals in environmental samples. The PLS-DA models were constructed from the metabolomic profiles ofG. japonicato discriminate the exposure ofG. japonicato chromium, nickel, copper, zinc, cadmium, fluoranthene, nicotine, and osmotic stress. The models had high predictive power for the presumptive exposure to each chemical and were able to detect exposures in mixed chemical samples. These results suggest that the metabolomic responses can provide important information for the assessment of chemical effects on organisms. We applied the models to the metabolomic profiles ofG. japonicaexposed to river sediment and road dust, and the results demonstrated the applicability of the models. The control groups were not classified as exposure groups, and no samples were presumed to belong to any exposure group. These results suggest that the target chemicals were not toxic in the samples and conditions we investigated. This study demonstrates a method to assess the relationships between chemical exposure and metabolomic responses. To the best our knowledge, this is the first study to apply metabolomics for identification of toxicants.
Structural basis for neutralization of SARS-CoV-2 and SARS-CoV by a potent therapeutic antibody
Authors: Lv Zhe , Deng Yong-Qiang , Ye Qing , Cao Lei , Sun Chun-Yun , Fan Changfa , Huang Weijin , Sun Shihui , Sun Yao , Zhu Ling , Chen Qi , Wang Nan , Nie Jianhui , Cui Zhen , Zhu Dandan , Shaw Neil , Li Xiao-Feng , Li Qianqian , Xie Liangzhi , Wang Youchun , Rao Zihe , Qin Cheng-Feng , Wang Xiangxi
Published: June 2020

The COVID-19 pandemic caused by the SARS-CoV-2 virus has resulted in an unprecedented public health crisis. There are no approved vaccines or therapeutics for treating COVID-19. Here we reported a humanized monoclonal antibody, H014, efficiently neutralizes SARS-CoV-2 and SARS-CoV pseudoviruses as well as authentic SARS-CoV-2 at nM level by engaging the S receptor binding domain (RBD). Importantly, H014 administration reduced SARS-CoV-2 titers in the infected lungs and prevented pulmonary pathology in hACE2 mouse model. Cryo-EM characterization of the SARS-CoV-2 S trimer in complex with the H014 Fab fragment unveiled a novel conformational epitope, which is only accessible when the RBD is in open conformation. Biochemical, cellular, virological and structural studies demonstrated that H014 prevents attachment of SARS-CoV-2 to its host cell receptors. Epitope analysis of available neutralizing antibodies against SARS-CoV and SARS-CoV-2 uncover broad cross-protective epitopes. Our results highlight a key role for antibody-based therapeutic interventions in the treatment of COVID-19.

One sentence summary

A potent neutralizing antibody conferred protection against SARS-CoV-2 in an hACE2 humanized mouse model by sterically blocking the interaction of the virus with its receptor.