bluuebunny/crossref_metadata_2025 huggingface dataset:
Predicting atmospheric optical properties for radiative transfer computations using neural networks
Authors: Veerman Menno A. , Pincus Robert , Stoffer Robin , van Leeuwen Caspar M. , Podareanu Damian , van Heerwaarden Chiel C.
Published: February 2021

The radiative transfer equations are well known, but radiation parametrizations in atmospheric models are computationally expensive. A promising tool for accelerating parametrizations is the use of machine learning techniques. In this study, we develop a machine learning-based parametrization for the gaseous optical properties by training neural networks to emulate a modern radiation parametrization (RRTMGP). To minimize computa- tional costs, we reduce the range of atmospheric conditions for which the neural networks are applicable and use machine-specific optimized BLAS functions to accelerate matrix computations. To generate training data, we use a set of randomly perturbed atmospheric profiles and calculate optical properties using RRTMGP. Predicted optical properties are highly accurate and the resulting radiative fluxes have average errors within 0.5 W m
−2
compared to RRTMGP. Our neural network-based gas optics parametrization is up to four times faster than RRTMGP, depending on the size of the neural networks. We further test the trade-off between speed and accuracy by training neural networks for the narrow range of atmospheric conditions of a single large-eddy simulation, so smaller and therefore faster networks can achieve a desired accuracy. We conclude that our machine learning-based parametrization can speed-up radiative transfer computations while retaining high accuracy.

This article is part of the theme issue ‘Machine learning for weather and climate modelling’.
Can deep learning beat numerical weather prediction?
Authors: Schultz M. G. , Betancourt C. , Gong B. , Kleinert F. , Langguth M. , Leufen L. H. , Mozaffari A. , Stadtler S.
Published: February 2021

The recent hype about artificial intelligence has sparked renewed interest in applying the successful deep learning (DL) methods for image recognition, speech recognition, robotics, strategic games and other application areas to the field of meteorology. There is some evidence that better weather forecasts can be produced by introducing big data mining and neural networks into the weather prediction workflow. Here, we discuss the question of whether it is possible to completely replace the current numerical weather models and data assimilation systems with DL approaches. This discussion entails a review of state-of-the-art machine learning concepts and their applicability to weather data with its pertinent statistical properties. We think that it is not inconceivable that numerical weather models may one day become obsolete, but a number of fundamental breakthroughs are needed before this goal comes into reach.

This article is part of the theme issue ‘Machine learning for weather and climate modelling’.
Machine learning for weather and climate are worlds apart
Authors: Watson-Parris D.
Published: February 2021

Modern weather and climate models share a common heritage and often even components; however, they are used in different ways to answer fundamentally different questions. As such, attempts to emulate them using machine learning should reflect this. While the use of machine learning to emulate weather forecast models is a relatively new endeavour, there is a rich history of climate model emulation. This is primarily because while weather modelling is an initial condition problem, which intimately depends on the current state of the atmosphere, climate modelling is predominantly a boundary condition problem. To emulate the response of the climate to different drivers therefore, representation of the full dynamical evolution of the atmosphere is neither necessary, or in many cases, desirable. Climate scientists are typically interested in different questions also. Indeed emulating the steady-state climate response has been possible for many years and provides significant speed increases that allow solving inverse problems for e.g. parameter estimation. Nevertheless, the large datasets, non-linear relationships and limited training data make climate a domain which is rich in interesting machine learning challenges. Here, I seek to set out the current state of climate model emulation and demonstrate how, despite some challenges, recent advances in machine learning provide new opportunities for creating useful statistical models of the climate.

This article is part of the theme issue ‘Machine learning for weather and climate modelling’.
A framework for probabilistic weather forecast post-processing across models and lead times using machine learning
Authors: Kirkwood Charlie , Economou Theo , Odbert Henry , Pugeault Nicolas
Published: February 2021

Forecasting the weather is an increasingly data-intensive exercise. Numerical weather prediction (NWP) models are becoming more complex, with higher resolutions, and there are increasing numbers of different models in operation. While the forecasting skill of NWP models continues to improve, the number and complexity of these models poses a new challenge for the operational meteorologist: how should the information from all available models, each with their own unique biases and limitations, be combined in order to provide stakeholders with well-calibrated probabilistic forecasts to use in decision making? In this paper, we use a road surface temperature example to demonstrate a three-stage framework that uses machine learning to bridge the gap between sets of separate forecasts from NWP models and the ‘ideal’ forecast for decision support: probabilities of future weather outcomes. First, we use quantile regression forests to learn the error profile of each numerical model, and use these to apply empirically derived probability distributions to forecasts. Second, we combine these probabilistic forecasts using quantile averaging. Third, we interpolate between the aggregate quantiles in order to generate a full predictive distribution, which we demonstrate has properties suitable for decision support. Our results suggest that this approach provides an effective and operationally viable framework for the cohesive post-processing of weather forecasts across multiple models and lead times to produce a well-calibrated probabilistic output.

This article is part of the theme issue ‘Machine learning for weather and climate modelling’.
Relation of inflammatory marker trajectories with frailty and aging in a 20-year longitudinal study
Authors: Samson Leonard Daniël , Buisman Anne-Marie , Ferreira José A. , Picavet H. Susan J. , Verschuren W. M. Monique , Boots A. Mieke H. , Engelfriet Peter
Published: February 2021

Little is known about the development of low-grade inflammation with age and its relationship with the onset of frailty. In this exploratory study, we investigated 18 inflammatory markers measured in blood of 144 individuals aged 65-75 years at study endpoint, collected over 20 years at five-year intervals. IFNγ-induced markers and platelet activation markers changed in synchrony over time. Chronically elevated levels of IL-6-related markers, such as CRP and sIL-6R, were associated with frailty and becoming frail over time, poorer lung function, or less physical strength. Overweight was a possible driver of these associations. More and stronger associations were detected in women, such as between increasing sCD14 levels and frailty, indicating possible monocyte overactivation. Multivariate prediction of frailty showed low accuracy but confirmed the main results. In summary, we documented 20-year temporal changes of inflammatory markers in an aging population, and related these to clinically relevant health outcomes.
Summary of the Effects of Exercise Therapy in Non-Communicable Diseases: Clinically Relevant Evidence from Meta-Analyses of Randomized Controlled Trials
Authors: Kujala Urho M
Published: February 2021

There is strong evidence that exercise therapy leads to better measured and self-reported physical fitness and function in patients with chronic diseases, along with improvements in body composition. The evidence for other health benefits has not been summarized as systematically across different chronic diseases. Given the volume of research that has appeared in the past decade, this review of meta-analyses of randomized controlled trials (RCTs) in patients with specific chronic diseases summarizes the evidence regarding exercise therapy for various outcomes to help practitioners in prescribing exercise therapy for their patients. Meta-analyses published before Jan 1, 2021, based on at least four RCTs, and investigating the effect of exercise therapy on the same outcome among patients with a specific chronic disease were screened. These meta-analyses show that, in addition to improvements in fitness and function, various cardio-metabolic risk factor levels are improved in most of the common cardio-metabolic diseases, pain is reduced in musculoskeletal diseases, mood (depression and anxiety) and health-related quality of life are improved in various disease categories, and disease-specific indicators of disease progression are improved for conditions such as type 2 diabetes, hypertension, coronary heart disease, heart failure, claudication, chronic obstructive pulmonary disease, rheumatoid arthritis, fibromyalgia, depression, anxiety, and schizophrenia. Physicians should consider prescribing exercise to their patients with chronic disease conditions to improve their physical fitness, mood, and health-related quality of life and to slow down the progression of disease. This improves a patient's possibility to enjoy an active and independent life.
Potential Association of Mitochondrial Haplogroups and A8860G Mutation with Breast Cancer Risk
Authors: Fadhl Han N. Mohammed , Abdulkarim Farhad M.
Published: February 2021

The last decade has witnessed great progresses regarding the molecular basis of breast cancer with discovery of different nuclear susceptibility genes; in addition investigations and researches regarding mitochondrial DNA (mtDNA) mutations in breast cancer have been started. Mitochondrial haplogroup determinants (single nucleotide polymorphism SNP) and somatic mitochondrial mutations have recently been studied as possible risk factors for carcinogenic processes in different tissues, hence in order to identify breast cancer related SNPs and haplogroups among the population of Sulaimaniyah city/Iraq, the entire mitochondrial genome of 20-breast cancer samples and comparable controls were sequenced. Haplogrep 2.0 was used for haplogroup identification; Chi-square and Fishers exact test were applied to assess relational significance. HV haplogroup in the cancer samples appeared to be a risk factor for breast cancer compared to the most common H haplogroup in control samples with a p-values of 0.002 and 0.006 respectively and an Odd Ratio (OR) = 28.00. Besides, SNP (A8860G) was also identified as a risk factor for breast cancer as compared to other randomly selected SNPs (A750G, A1438G and C7028T) with p values □0.05 and OR >1.
Comparison of SARS-CoV-2 viral load in saliva samples in symptomatic and asymptomatic cases
Authors: Bhatta Anuja , Henkhaus Rebecca , Fehling Heather L.
Published: February 2021

SARS-CoV-2 infections can be symptomatic as well as asymptomatic. In this study, we analyzed 460,814 saliva samples collected from July 2020 to January 2021 for a SARS-CoV-2-specific gene target using the FDA EUA test, CRL Rapid Response™, based on reverse transcription polymerase chain reaction (RT-PCR). We measured SARS-CoV-2 viral loads using cycle threshold (Ct) values. A total of 17,813 samples tested positive for COVID-19 using self-collected saliva samples. The Ct values ranged from 11 to 40, 91.3% distributed between 22 to 38 Ct. We then compared Ct values for symptomatic and asymptomatic cases for all positive saliva samples. A total of 8,706 cases were symptomatic with an average Ct value of 29.24, and 9,107 cases were asymptomatic with an average Ct value of 30.99. Hence, SARS-CoV-2 viral loads (Ct) in saliva samples for both symptomatic and asymptomatic cases are similar.
Detection of Antibiotic-Resistant Bacteria, Resistance Determinants, and Mobile Elements in Surface Waters in Lebanon
Authors: Moussa Jennifer , Abboud Edmond , Tokajian Sima
Published: February 2021

The prevalence of antibiotic-resistant bacteria in surface water in Lebanon is a growing concern and understanding the mechanisms of the spread of resistance determinants is essential. We aimed at studying the occurrence of resistant organisms and determinants in surface water sources in Lebanon and understanding their mobilization and transmission. Water samples were collected from five major rivers in Lebanon. 91 isolates were recovered out of which 25 were multidrug-resistant (MDR) and accordingly were further characterized. Escherichia coli and Klebsiella pneumoniae were the most commonly identified MDR isolates. Conjugation assays coupled with in silico plasmid analysis were performed and validated using PCR-based replicon typing (PBRT) to identify and confirm incompatibility groups and the localization of β-lactamase encoding genes. E. coli EC23 carried a blaNDM-5 gene on a conjugative, multireplicon plasmid, while blaCTX-M-15 and blaTEM-1B were detected in the majority of the MDR isolates. Different ST types were identified including the highly virulent E. coli ST131. Our results showed a common occurrence of bacterial contaminants in surface water and an increase in the risk for the dissemination of resistance determinants exacerbated with the ongoing intensified population mobility in Lebanon and the widespread lack of wastewater treatment.
The impact of armed conflict on the epidemiological situation of Coronavirus disease (COVID-19) in Libya, Syria, and Yemen
Authors: Daw Mohamed A
Published: February 2021

Background

Since the Arab uprising 2011, Libya, Syria, and Yemen have gone through a major armed conflict. This resulted in a high rate of mortality, injury, and population displacement with a collapse of the health care system. Furthermore, it was complicated by the emergence of, COVID-19 as a global pandemic which made the population of these countries strive under unusual conditions to tackle both the pandemic and the ongoing wars. The objectives of this study were to determine the impacts and influence of armed conflicts on the epidemiology of Novel Coronavirus (SARS-CoV-2) within these war-torn countries and outline the needed strategies to combat the spread of the pandemic and its upcoming consequences.

Methods

The official and public data regarding the dynamics of armed conflict and the spread, of SARS-COV-19 in Libya, Syria, and Yemen were collected from all available sources. Starting from the early emergence of the COVID-19 in each country until the end of December 2020. Datasets were analyzed through a set of statistical techniques and the weekly resolved data were used to probe the link between the intensity levels of the armed conflict and the spread of the pandemic.

Results

Data indicated that there is an increase in the intensity of violence levels at an early stage from March to August reached up to two folds in the three countries particularly in Libya. In this violent period, few cases of COVID-19 were reported ranging from 5-53 cases/day. From September to December, a significant decline in the level of the armed conflict was accompanied by steep upsurges in the number of reported COVID-19 cases reached up to 500 cases/day. The highest accumulative cases of COVID-19 were reported in Libya, Syria, and Yemen respectively.

Conclusions

Our analysis demonstrates that the armed conflict has provided an opportunity for SARS-COV-19 to spread. At the early weeks of the pandemic that coincided with high levels of the armed conflict few cases were officially reported indicating a vast undercount, which may suggest a hidden mitigating spread at an early stage. Then the pandemic increased immensely as the armed conflict decline to reach the highest by December. A full-blown transmission of the COVID-19 pandemic in these countries is expected. Therefore, urgent national and international strategies should be implemented to combat the pandemic and its upcoming consequences.
Typical somatomotor physiology of the hand is preserved in a patient with an amputated arm
Authors: van den Boom Max , Miller Kai J. , Gregg Nicholas M. , Ojeda Gabriela , Lee Kendall H. , Richner Thomas J. , Ramsey Nick F. , Worrell Greg A. , Hermes Dora
Published: February 2021

Electrophysiological signals in the human motor system may change in different ways after deafferentation, with some studies emphasizing reorganization while others propose retained physiology. Understanding whether motor electrophysiology is retained over longer periods of time can be invaluable for patients with paralysis (e.g. ALS or brainstem stroke) when signals from sensorimotor areas may be used for communication or control over neural prosthetic devices. In addition, a maintained electrophysiology can potentially benefit the treatment of phantom limb pains through prolonged use of these signals in a brain-machine interface (BCI).

Here, we were presented with the unique opportunity to investigate the physiology of the sensorimotor cortex in a patient with an amputated arm using electrocorticographic (ECoG) measurements. While implanted with an ECoG grid for clinical evaluation of electrical stimulation for phantom limb pain, the patient performed attempted finger movements with the contralateral (lost) hand and executed finger movements with the ipsilateral (healthy) hand.

The electrophysiology of the sensorimotor cortex contralateral to the amputated hand remained very similar to that of hand movement in healthy people, with a spatially focused increase of high-frequency band (65-175Hz; HFB) power over the hand region and a distributed decrease in low-frequency band (15-28Hz; LFB) power. The representation of the three different fingers (thumb, index and little) remained intact and HFB patterns could be decoded using support vector learning at single-trial classification accuracies of >90%, based on the first 1-3s of the HFB response. These results demonstrate that hand representations are largely retained in the motor cortex. The intact physiological response of the amputated hand, the high distinguishability of the fingers and fast temporal peak are encouraging for neural prosthetic devices that target the sensorimotor cortex.
Trade-offs between antiseptic cytotoxicity and efficacy in a humanex vivowound contamination model
Authors: Cheong J. Z. Alex , Liu Aiping , Rust Clayton J. , Kalan Lindsay R. , Gibson Angela L. F.
Published: February 2021

Wound cleansing agents are routine in wound care, even in the absence of signs of infection. Antiseptic activity prevents contaminating microbes from establishing an infection while also raising concerns of cytotoxicity and delayed wound healing. Here, we used anex vivohuman skin excisional wound model to evaluate the cytotoxicity of five clinically-used wound cleaning agents (saline, povidone iodine, Dove® soap, Dial® soap, and chlorhexidine gluconate). We established a wound contamination model using ∼100 cells ofPseudomonas aeruginosaper wound to evaluate antiseptic efficacy and microbial biofilm spatial organization. We found that Dial® soap and chlorhexidine gluconate significantly reduced metabolic activity of the biopsies, while all treatments except saline affected local cellular viability. Within the contamination model, only chlorhexidine gluconate treatment resulted in significantly lowerP. aeruginosacounts at 24 hours post-treatment, driven by sub-limit-of-detection counts immediately post-treatment. Later applications of chlorhexidine gluconate had no effects on microbial growth, with microscopy showing extensive surface colonization of the wound bed. We present a clinically-relevant model for evaluating antiseptic cytotoxicity and efficacy, with the ability to resolve spatial localization and temporal dynamics of tissue viability and microbial growth.
Comparison of library preparation and sequencing depths for direct sequencing ofBordetella pertussispositive samples
Authors: Fong Winkie , Pey Keenan , Rockett Rebecca , Sadsad Rosemarie , Sintchenko Vitali , Timms Verlaine
Published: February 2021

Whooping cough, or pertussis, is a highly transmissible respiratory infection caused byBordetella pertussis. Due to the high burden of pertussis, vaccine programmes were introduced internationally and in Australia since the 1950s. This has resulted in a significant decrease of pertussis infections. However, since the 1990s the number of pertussis notifications has increased considerably. Currently circulatingB. pertussisstrains differ in vaccine antigen composition compared to strains that circulated in the pre-vaccination era. These genetic differences are thought to contribute, in part, to the re-emergence of pertussis in Australia and around the world. Whole genome sequencing (WGS) can resolve minute differences in circulating strains and provides unparalleled resolution of vaccine antigens. This high-resolution snapshot can provide clues that enable more targeted public health interventions. However, pertussis is primarily diagnosed with culture-independent diagnostic assays which offer fast turnaround result times and reduced laboratory costs, eliminating the need to culture isolates. Current WGS methods require a cultured isolate, resulting in an absence ofB. pertussisgenome sequences in the post vaccination era. This scarcity has, in turn, limited understanding of currently circulating strains and respective vaccine antigen compositions.

Recent advancements of WGS technologies have allowed direct sequencing of clinical specimens without the need for a cultured isolate. However, recovering reliable sequence data from clinical samples of low bacterial load infections such asB. pertussisis a pressing challenge. We sought to increase the yield ofB. pertussissequences direct from a clinical sample by evaluating widely available WGS library preparation methods.

We report that the Illumina DNA prep library preparation kit combined with deep sequencing allowed the detection of important surveillance information such as allelic variations in theB. pertussisvaccine antigens. Further, our method generates high coverage over the 23S ribosomal RNA ofB. pertussisenabling macrolide resistance to be easily determined. Overall, this method can improve surveillance ofB. pertussis, by monitoring changes in vaccine antigens, detecting antimicrobial resistance and guiding Public Health control interventions.
Microbiota-derived metabolites inhibitSalmonellavirulent subpopulation development by acting on single-cell behaviors
Authors: Hockenberry Alyson M , Micali Gabriele , Takács Gabriella , Weng Jessica , Hardt Wolf-Dietrich , Ackermann Martin
Published: February 2021

Salmonella spp.expressSalmonellapathogenicity island 1 (SPI-1) genes to mediate the initial phase of interaction with host cells. Prior studies indicate short-chain fatty acids, microbial metabolites at high concentrations in the gastrointestinal tract, limit SPI-1 gene expression. A number of reports show only a subset ofSalmonellacells in a population express these genes, suggesting short-chain fatty acids could decrease SPI-1 population-level expression by acting on per-cell expression and/or the proportion of expressing cells. Here, we combine single-cell, theoretical, and molecular approaches to address the effect of short-chain fatty acids on SPI-1 expression. Our results show short-chain fatty acids do not repress SPI-1 expression by individual cells. Rather, these compounds act to selectively slow the growth of SPI-1 expressing cells, ultimately decreasing their frequency in the population. Further experiments indicate slowed growth arises from short-chain fatty acid-mediated depletion of the proton motive force. By influencing the SPI-1 cell-type proportions, our findings imply gut microbial metabolites act on cooperation between the two cell-types and ultimately influenceSalmonella’s capacity to establish within a host.

Significance Statement

Emergence of distinct cell-types in populations of genetically identical bacteria is common. Furthermore, it is becoming increasingly clear that cooperation between cell-types can be beneficial. This is the case duringSalmonellainfection, in which cooperation between inflammation-inducing virulent and fast-growing avirulent cell-types occurs during infection to aid in colonization of the host gut. Here, we show gut microbiota-derived metabolites slow growth by the virulent cell-type. Our study implies microbial metabolites shape cooperative interactions between the virulent and avirulent cell types, a finding that can help explain the wide array of clinical manifestations ofSalmonellainfection.
Quantifying and Mitigating Motor Phenotypes Induced by Antisense Oligonucleotides in the Central Nervous System
Authors: Moazami Michael P. , Rembetsy-Brown Julia M. , Wang Feng , Krishnamurthy Pranathi Meda , Weiss Alexandra , Marosfoi Miklos , King Robert M. , Motwani Mona , Gray-Edwards Heather , Fitzgerald Katherine A. , Brown Robert H. , Watts Jonathan K.
Published: February 2021

Antisense oligonucleotides (ASOs) are emerging as a promising class of therapeutics for neurological diseases. When injected directly into the cerebrospinal fluid, ASOs distribute broadly across brain regions and exert long-lasting therapeutic effects. However, many phosphorothioate (PS)-modified gapmer ASOs show transient motor phenotypes when injected into the cerebrospinal fluid, ranging from reduced motor activity to ataxia or acute seizure-like phenotypes. The effect of sugar and phosphate modifications on these phenotypes has not previously been systematically studied. Using a behavioral scoring assay customized to reflect the timing and nature of these effects, we show that both sugar and phosphate modifications influence acute motor phenotypes. Among sugar analogues, PS-DNA induces the strongest motor phenotype while 2’-substituted RNA modifications improve the tolerability of PS-ASOs. This helps explain why gapmer ASOs have been more challenging to develop clinically relative to steric blocker ASOs, which have a reduced tendency to induce these effects. Reducing the PS content of gapmer ASOs, which contain a stretch of PS-DNA, improves their toxicity profile, but in some cases also reduces their efficacy or duration of effect. Reducing PS content improved the acute tolerability of ASOs in both mice and sheep. We show that this acute toxicity is not mediated by the major nucleic acid sensing innate immune pathways. Formulating ASOs with calcium ions before injecting into the CNS further improved their tolerability, but through a mechanism at least partially distinct from the reduction of PS content. Overall, our work identifies and quantifies an understudied aspect of oligonucleotide toxicology in the CNS, explores its mechanism, and presents platform-level medicinal chemistry approaches that improve tolerability of this class of compounds.
What are housekeeping genes?
Authors: Joshi Chintan J. , Ke Wenfan , Drangowska-Way Anna , O’Rourke Eyleen J. , Lewis Nathan E.
Published: February 2021

The concept of “housekeeping genes” has been used for four decades but remains loosely defined. Housekeeping genes are commonly described as “essential for cellular existence regardless of their specific function in the tissue or organism”, and “stably expressed irrespective of tissue type, developmental stage, cell cycle state, or external signal”. However, experimental support for the tenet that gene essentiality is linked to stable expression across cell types, conditions, and organisms has been limited. Here we use genome-scale functional genomic screens, bulk and single-cell sequencing technologies to test this link and optimize a quantitative and experimentally validated definition of housekeeping gene. Using the optimized definition, we identify, characterize, and provide as resources, housekeeping gene lists extracted from several human datasets, and 12 other animal species that include primates, chicken, andC. elegans. We find that stably expressed genes are not necessarily essential, and that the individual genes that are essential and stably expressed can considerably differ across organisms; yet the pathways enriched among these genes are conserved. Further, the level of conservation of housekeeping genes across the analyzed organisms captures their taxonomic groups, showing evolutionary relevance for our definition. Therefore, we here present a quantitative and experimentally validated definition of housekeeping genes that can contribute to better understanding of their unique biological and evolutionary characteristics.
Calling differential DNA methylation at cell-type resolution: addressing misconceptions and best practices
Authors: Rahmani Elior , Jew Brandon , Schweiger Regev , Rhead Brooke , Criswell Lindsey A. , Barcellos Lisa F. , Eskin Eleazar , Rosset Saharon , Sankararaman Sriram , Halperin Eran
Published: February 2021

We benchmarked two approaches for the detection of cell-type-specific differential DNA methylation: Tensor Composition Analysis (TCA) and a regression model with interaction terms (CellDMC). Our experiments alongside rigorous mathematical explanations show that TCA is superior over CellDMC, thus resolving recent criticisms suggested by Jing et al. Following misconceptions by Jing and colleagues with modelling cell-type-specificity and the application of TCA, we further discuss best practices for performing association studies at cell-type resolution. The scripts for reproducing all of our results and figures are publicly available at github.com/cozygene/CellTypeSpecificMethylationAnalysis.
Spatially Interacting Phosphorylation Sites and Mutations in Cancer
Authors: Huang Kuan-lin , Scott Adam D. , Zhou Daniel Cui , Wang Liang-Bo , Weerasinghe Amila , Elmas Abdulkadir , Liu Ruiyang , Wu Yige , Wendl Michael C. , Wyczalkowski Matthew A. , Baral Jessika , Sengupta Sohini , Lai Chin-Wen , Ruggles Kelly , Payne Samuel H. , Raphael Benjamin , Fenyö David , Chen Ken , Mills Gordon , Ding Li
Published: February 2021

Advances in mass-spectrometry have generated increasingly large-scale proteomics datasets containing tens of thousands of phosphorylation sites (phosphosites) that require prioritization. We develop a bioinformatics tool called HotPho and systematically discover 3D co-clustering of phosphosites and cancer mutations on protein structures. HotPho identifies 474 such hybrid clusters containing 1,255 co-clustering phosphosites, including RET p.S904/Y928, the conserved HRAS/KRAS p.Y96, and IDH1 p.Y139/IDH2 p.Y179 that are adjacent to recurrent mutations on protein structures not found by linear proximity approaches. Hybrid clusters, enriched in histone and kinase domains, frequently include expression-associated mutations experimentally shown as activating and conferring genetic dependency. Approximately 300 co-clustering phosphosites are verified in patient samples of 5 cancer types or previously implicated in cancer, including CTNNB1 p.S29/Y30, EGFR p.S720, MAPK1 p.S142, and PTPN12 p.S275. In summary, systematic 3D clustering analysis highlights nearly 3,000 likely functional mutations and over 1,000 cancer phosphosites for downstream investigation and evaluation of potential clinical relevance.
Unravelling processes between phenotypic plasticity and population dynamics in migratory birds
Authors: Liu Jin , Lei Weipan , Mo Xunqiang , Hassell Chris J. , Zhang Zhengwang , Coulson Tim
Published: February 2021

Populations can rapidly respond to environmental change via adaptive phenotypic plasticity, which can also modify interactions between individuals and their environment, affecting population dynamics. Bird migration is a highly plastic resource-tracking strategy in seasonal environments. However, the link between the population dynamics of migratory birds and migration strategy plasticity is not well understood.

The quality of staging habitats affects individuals’ migration timing and energy budgets in the course of migration, and can consequently affect individuals’ breeding and overwintering performance, and impact population dynamics. Given staging habitats being lost in many parts of the world, our goal is to investigate responses of individual migration strategies and population dynamics in the face of loss of staging habitat, and to identify the key processes connecting them.

We started by constructed and analysed a general full-annual-cycle individual-based model with a stylized migratory population to generate hypotheses on how changes in the size of staging habitat might drive changes in individual stopover duration and population dynamics, and to identify the key processes connecting them. Next, through the interrogation of census data, we tested these hypotheses by analysing population trends and stopover duration of migratory waterbirds experiencing loss of staging habitat.

We found empirical support for our modelling-identified hypotheses: the loss of staging habitat generates plasticity in migration strategies, with individuals remaining on the staging habitat for longer to obtain food due to a reduction in per capita food availability. The subsequent increasing population density on the staging habitat has knock on effects on population dynamics in the breeding and overwintering stage.

Our results demonstrate how environmental change that impacts one energetically costly life history stage in migratory birds can have population dynamics impacts across the entire annual cycle via phenotypic plasticity.
The hippocampus shows an own-age bias during unfamiliar face viewing
Authors: Koen Joshua D. , Hauck Nedra , Rugg Michael D.
Published: February 2021

The present study investigated the neural correlates of the own-age bias for face recognition in a repetition suppression paradigm. Healthy young and older adults viewed upright and inverted unfamiliar faces. Some of the upright faces were repeated following one of two delays (lag 0 or lag 11). Repetition suppression effects were observed in bilateral fusiform cortex. However, there were no significant effects indicating an own-age bias in repetition suppression. The absence of these effects is arguably inconsistent with perceptual expertise accounts of own-age biases in face processing. By contrast, the right anterior hippocampus showed an own-age bias (greater activity for own-than other-age faces) when viewing an unfamiliar face for the first time. Given the importance of the hippocampus for episodic memory encoding, we conjecture that the increased hippocampal activity for own-age relative to other-age faces reflects differential engagement of neural processes supporting the episodic encoding of faces and might provide insight into the neural underpinnings of own-age biases in face recognition memory.
A new field instrument for leaf volatiles reveals an unexpected vertical profile of isoprenoid emission capacities in a tropical forest
Authors: Taylor Tyeen C. , Wisniewski Wit T. , Alves Eliane G. , de Oliveira Raimundo C. , Saleska Scott R.
Published: February 2021

Both plant physiology and atmospheric chemistry are substantially altered by the emission of volatile isoprenoids (VI), such as isoprene and monoterpenes, from plant leaves. Yet, since gaining scientific attention in the 1950’s, empirical research on leaf VI has been largely confined to laboratory experiments and atmospheric observations. Here, we introduce a new field instrument designed to bridge the scales from leaf to atmosphere, by enabling precision VI detection in real time from plants in their natural ecological setting. With a field campaign in the Brazilian Amazon, we reveal an unexpected distribution of leaf emission capacities (EC) across the vertical axis of the forest canopy, with EC peaking in the mid-canopy instead of the sun-exposed canopy surface, and high emissions occurring in understory specialist species. Compared to the simple interpretation that VI protect leaves from heat stress at the hot canopy surface, our results encourage a more nuanced view of the adaptive role of VI in plants. We infer that forest emissions to the atmosphere depend on the dynamic microenvironments imposed by canopy structure, and not simply on canopy surface conditions. We provide a new emissions inventory from 51 tropical tree species, revealing moderate consistency in EC within taxonomic groups. Our self-contained, portable instrument provides real-time detection and live measurement feedback with precision and detection limits better than 0.5 nmol m-2leafs-1. We call the instrument ‘PORCO’ based on the gas detection method: photoionization of organic compounds. We provide a thorough validation of PORCO and demonstrate its capacity to detect ecologically driven variation in leaf emission rates and thus accelerate a nascent field of science: the ecology and ecophysiology of plant volatiles.

Type of paper

Method
AAV-MediatedIn VivoCAR Gene Therapy for Targeting Human T Cell Leukemia
Authors: Nawaz Waqas , Huang Bilian , Xu Shijie , Li Yanlei , Zhu Linjing , Wu Zhiwei , Wu Xilin
Published: February 2021

Chimeric antigen receptor (CAR) T cell therapy is the most active field in immuno-oncology and brings substantial benefit to patients with B cell malignancies. However, the complex procedure for CAR T cell generation hampers its widespread applications. Here, we describe a novel approach in which human CAR T cells can be generated within the host upon injecting an Adeno-associated virus (AAV)vector carrying the CAR gene, which we call AAV delivering CAR gene therapy (ACG). Upon single infusion into a humanized NCG tumor mouse model of human T cell leukemia, AAV generates sufficient numbers of potentin vivoCAR cells, resulting in tumor regression; these in vivo generated CAR cells produce antitumor immunological characteristics. This instantaneous generation ofin vivoCAR T cells may bypass the need for patient lymphodepletion, as well as theex vivoprocesses of traditional CAR T cell production, which may make CAR therapy simpler and less expensive. It may allow the development of intricate, individualized treatments in the form of on-demand and diverse therapies.

Significance Statement

AAV can generate enough CAR cells within the host. That act as a living drug, distributed throughout the body, and persist for weeks, with the ability to recognize and destroy tumor cells.
Identification of salt tolerant genotypes in wheat using stress tolerance indices
Authors: Bakhshi Behnam , Taghi Tabatabaei Seyed Mohammad , Naroui Rad Mohammad Reza , Masoudi Bahram
Published: February 2021

Salinity is one of the most important causes of yield loss in agricultural products, especially wheat. Wheat cultivation, on the other hand, is carried out on a wide range of agricultural land in saline lands. Therefore, wheat breeding for tolerance to salinity can be an effective way to improve yield and yield stability under these conditions. In this study, twenty wheat genotypes were studied in a randomized complete block design with three replications in two normal and salinity stress conditions in order to identify suitable indices of wheat stress tolerance and also to identify genotypes tolerant to salinity stress. Genotypes were evaluated based on tolerance index (TOL), stress tolerance index (STI), mean productivity (MP), susceptibility to stress (SSI), geometric mean productivity (GMP), harmonic mean productivity (HM), yield stability (YS) and yield index (YS). The results showed that MP, GMP, HM and STI indices are suitable indices because of their positive and highly significant correlation with yield in both normal and salinity stress conditions and it was found that these indices were suitable tools to achieve high yield genotypes in both environments. The results also showed that genotypes 10, 4, 9, 3 and 8 are resistant to salt stress with acceptable yield. Genotypes 5, 11, 12, 14, 16, 17, 18 and 20 were also identified as the most susceptible genotypes.
Nutrient copper signaling promotes protein turnover by allosteric activation of ubiquitin E2D conjugases
Authors: Opazo C.M. , Lotan A. , Xiao Z. , Zhang B. , Greenough M.A. , Lim C.M. , Trytell H. , Ramírez A. , Ukuwela A.A. , Mawal C.H. , McKenna J. , Saunders D.N. , Burke R. , Gooley P.R. , Bush A.I.
Published: February 2021

Nutrient copper supply is critical for cell growth and differentiation, and its disturbance is associated with major pathologies including cancer and neurodegeneration. Although increasing copper bioavailability in late Precambrian facilitated emergence of novel cuproproteins, their intricate regulation by this essential trace element remains largely cryptic. We found that subtle rises in cellular copper strikingly increase polyubiquitination and accelerate protein degradation within 30 minutes in numerous mammalian cell lines. We track this surprising observation to allostery induced in the UBE2D ubiquitin conjugase clade through a conserved CXXXC sub-femtomolar-affinity Cu+binding motif. Thus, physiologic fluctuation in cytoplasmic Cu+is coupled to the prompt degradation of UBE2D protein targets, including p53. InDrosophilaharboring a larval-lethal knockdown of the nearly identical fly orthologue UbcD1, complementation with human UBE2D2 restored near-normal development, but mutation of its CXXXC Cu+binding motif profoundly disrupted organogenesis. Nutrient Cu+emerges as a trophic allosteric modulator of UBE2D activity through a structural motif whose evolution coincides with animal multicellularity.

One Sentence Summary

Modulation of nutrient copper impacts protein turnover and animal morphogenesis through conserved allostery of ubiquitin E2D conjugases.

Hilights

Nutrient copper supply is critical for cell growth and differentiation

The E2D clade of ubiquitin conjugases contains a sub-femtomolar-affinity Cu+binding motif

Allosteric activation by Cu+markedly accelerates protein polyubiquitination

This sensor couples physiologic fluctuations in cytoplasmic Cu+with the degradation rate of E2D targets, including p53

This metazoan signaling mechanism is critical fordrosophilamorphogenesis

In Brief

Conserved allostery of ubiquitin E2D conjugases links nutrient copper signaling to protein degradation and animal morphogenesis.

Abstract Figure

Graphical Abstract
Phyletic distribution and diversification of the Phage Shock Protein stress response system in bacteria and archaea
Authors: Popp Philipp F. , Gumerov Vadim M. , Andrianova Ekaterina P. , Bewersdorf Lisa , Mascher Thorsten , Zhulin Igor B. , Wolf Diana
Published: February 2021

The bacterial cell envelope is an essential structure that protects the cell from environmental threats, while simultaneously serving as communication interface and diffusion barrier. Therefore, maintaining cell envelope integrity is of vital importance for all microorganisms. Not surprisingly, evolution has shaped conserved protection networks that connect stress perception, transmembrane signal transduction and mediation of cellular responses upon cell envelope stress. The phage shock protein (PSP) stress response is one of such conserved protection networks. Most of the knowledge about the Psp response comes from studies in the Gram-negative model bacterium,Escherichia coliwhere the Psp system consists of several well-defined protein components. Homologous systems were identified in representatives of Proteobacteria, Actinobacteria, and Firmicutes; however, the Psp system distribution in the microbial world remains largely unknown. By carrying out a large-scale, unbiased comparative genomics analysis, we found components of the Psp system in many bacterial and archaeal phyla and demonstrated that the PSP system deviates dramatically from the proteobacterial prototype. Two of its core proteins, PspA and PspC, have been integrated in various (often phylum-specifically) conserved protein networks during evolution. Based on protein sequence and gene neighborhood analyses ofpspAandpspChomologs, we built a natural classification system of PSP networks in bacteria and archaea. We performed a comprehensivein vivoprotein interaction screen for the PSP network newly identified in the Gram-positive model organismBacillus subtilisand found a strong interconnected PSP response system, illustrating the validity of our approach. Our study highlights the diversity of PSP organization and function across many bacterial and archaeal phyla and will serve as foundation for future studies of this envelope stress response beyond model organisms.
The genome of the CTG(Ser1) yeast Scheffersomyces stipitisis plastic
Authors: Estevez Samuel Vega , Armitage Andrew , Bates Helen J. , Harrison Richard J. , Buscaino Alessia
Published: February 2021

Microorganisms need to adapt to environmental changes, and genome plasticity can lead to rapid adaptation to hostile environments by increasing genetic diversity. Here, we investigate genome plasticity in the CTG(Ser1) yeastScheffersomyces stipitis, an organism with an enormous potential for second-generation biofuel production. We demonstrate thatS. stipitishas an intrinsically plastic genome and that differentS. stipitisisolates have genomes with distinct chromosome organisation. Real-time evolution experiments show thatS. stipitisgenome plasticity is common and rapid as extensive genomic changes with fitness benefits are detected followingin vitroevolution experiments. Hybrid MinION Nanopore and Illumina genome sequencing identifies retrotransposons as major drivers of genome diversity. Indeed, the number and position of retrotransposons is different in differentS. stipitisisolates, and retrotransposon-rich regions of the genome are sites of chromosome rearrangements. Our findings provide important insights into the adaptation strategies of the CTG (Ser1) yeast clade and have critical implications in the development of second-generation biofuels. These data highlight that genome plasticity is an essential factor to be considered for the development of sustainableS. stipitisplatforms for second-generation biofuels production.
Clinical and Genetic insights in a tertiary care center cohort of patients with bicuspid aortic valve
Authors: Théron Alexis , Touil Anissa , Résseguier Noémie , Collod-Beroud Gwenaelle , Norscini Giulia , Simoni Anne-Sophie , Odelin Gaёlle , Collart Frédéric , Zaffran Stéphane , Avierinos Jean-François
Published: February 2021

BACKGROUND

to describe spectrum of valve function in bicuspid aortic valve (BAV) patients referred to a tertiary care center and to investigate genetic pathways associated with valve degeneration.

METHODS

All consecutive patients with BAV were prospectively included from 2014 to 2018. BAV was defined according to embryologic and Sievers classifications. Clinical and echo variables were compared according to aortic valve function. Aortic valve tissues were collected from BAV patients (n=15) operated for severe aortic stenosis (AS-BAV, n=7) or aortic regurgitation (AR-BAV, n=8). RT-qPCR was performed to compare gene expression level in AS-BAV, AR-BAV and controls corresponding to healthy tricuspid aortic valves collected on human heart explant immediately after transplantation (n=5).

RESULTS

Out of 223 adults with BAV, mean age 53±17 years, 83% had left-right coronary cusps fusion, 80% Sievers type 1 BAV and 49% aortopathy. Twenty-four patients had normal valve function, 66 patients had AS-BAV, 91 patients had AR-BAV and 40 patient had AR+AS BAV. BAV phenotype did not predict neither AS-BAV nor AR-BAV (all p>0.1). By multivariable analysis, age >50 (41.6[10.3-248.2],p<0.001) and presence of raphe(12.8[2.4-87.4],p<0.001) were significantly associated with AS-BAV and male gender of AR-BAV(5[1.6-16.4], p=0.005). RT-qPCR revealed overexpression ofRUNX2in AS-BAV (17.67±1.83 vs 3.25±0.93, p=0.04), and overexpression ofCOL1A1(4.01±0.6vs2.25±0.5,p=0.03) andFLNA(23.31±7.5vs1.97±0.3,p=0.03) in AR-BAV.

CONCLUSIONS

This prospective study confirmed high prevalence of valve dysfunction at first diagnosis of BAV in a referred population. Clinical and echo variables are poorly associated with BAV dysfunction. The leaking or stenotic processes could be both supported by dysregulation of specific genetic pathways