ABSTRACT
Research on astronaut health and model organisms have revealed six features of spaceflight biology that guide our current understanding of fundamental molecular changes that occur during space travel. The features include oxidative stress, DNA damage, mitochondrial dysregulation, epigenetic changes (including gene regulation), telomere length alterations, and microbiome shifts. Here we review the known hazards of human spaceflight, how spaceflight affects living systems through these six fundamental features, and the associated health risks of space exploration. We also discuss the essential issues related to the health and safety of astronauts involved in future missions, especially planned long-duration and Martian missions.
Subject(s)
Extraterrestrial Environment , Space Flight , Astronauts , Health , Humans , Microbiota , Risk FactorsABSTRACT
Plants are expected to play a critical role in the biological life support systems of crewed spaceflight missions, including in the context of upcoming missions targeting the Moon and Mars. Therefore, understanding the response of plants to spaceflight is essential for improving the selection and engineering of plants and spaceflight conditions. In particular, understanding the root-tip's response to spaceflight is of importance as it is the center of orchestrating the development of the root, the primary organ for the absorption of nutrients and anchorage. GLDS-120 is a pioneering study by Paul et al. that used transcriptomics to evaluate the spaceflight response of the root-tip of the model plant Arabidopsis thaliana in dark and light through separate analyses of three genotype groups (Wassilewskija, Columbia-0, and Columbia-0 PhyD) and comparison of genotype responses. Here, we provide a complementary analysis of this dataset through a combined analysis of all samples while controlling for the genotypes in a paired analysis. We identified a robust transcriptional response to spaceflight with 622 DEGs in light and 200 DEGs in dark conditions. Gene enrichment analysis identified 37 and 13 significantly enriched terms from biological processes in light and dark conditions, respectively. Prominent enrichment for hypoxia-related terms in both conditions suggests hypoxia is a key stressor for root development during spaceflight. Additional enriched terms in light conditions include the circadian cycle, light response, and terms for the metabolism of flavonoid and indole-containing compounds. These results further our understanding of plants' responses to the spaceflight environment.
Subject(s)
Arabidopsis , Gene Expression Regulation, Plant , Space Flight , Arabidopsis/genetics , Arabidopsis/physiology , Arabidopsis/growth & development , Genotype , Gene Expression Profiling , Meristem/genetics , Meristem/growth & development , Meristem/radiation effects , Plant Roots/genetics , Plant Roots/growth & development , Plant Roots/radiation effects , Transcriptome , Light , Arabidopsis Proteins/genetics , Arabidopsis Proteins/metabolismABSTRACT
An ergonomics assessment of the physical risk factors in the workplace is instrumental in predicting and preventing musculoskeletal disorders (MSDs). Using Artificial Intelligence (AI) has become increasingly popular for ergonomics assessments because of the time savings and improved accuracy. However, most of the effort in this area starts and ends with producing risk scores, without providing guidance to reduce the risk. This paper proposes a holistic job improvement process that performs automatic root cause analysis and control recommendations for reducing MSD risk. We apply deep learning-based Natural Language Processing (NLP) techniques such as Part of Speech (PoS) tagging and dependency parsing on textual descriptions of the physical actions performed in the job (e.g. pushing) along with the object (e.g. cart) being acted upon. The action-object inferences provide the entry point to an expert-based Machine Learning (ML) system that automatically identifies the targeted work-related causes (e.g. cart movement forces are too high, due to caster size too small) of the identified MSD risk (e.g. excessive shoulder forces). The proposed framework utilises the root causes identified to recommend control strategies (e.g. provide larger diameter casters, minimum diameter 8" or 203 mm) most likely to mitigate risk, resulting in a more efficient and effective job improvement process.
We propose an ergonomics framework that identifies the root causes of MSD risk and recommends control actions. A key insight exploited using artificial intelligence is that when the estimated risk is high for a body joint, the actions of the worker in question and the associated objects constitute valuable information.
ABSTRACT
A plant's oxygen supply can vary from normal (normoxia) to total depletion (anoxia). Tolerance to anoxia is relevant to wetland species, rice (Oryza sativa) cultivation, and submergence tolerance of crops. Decoding and transmitting calcium (Ca) signals may be an important component to anoxia tolerance; however, the contribution of intracellular Ca transporters to this process is poorly understood. Four functional cation/proton exchangers (CAX1-4) in Arabidopsis (Arabidopsis thaliana) help regulate Ca homeostasis around the vacuole. Our results demonstrate that cax1 mutants are more tolerant to both anoxic conditions and submergence. Using phenotypic measurements, RNA-sequencing, and proteomic approaches, we identified cax1-mediated anoxia changes that phenocopy changes present in anoxia-tolerant crops: altered metabolic processes, diminished reactive oxygen species production post anoxia, and altered hormone signaling. Comparing wild-type and cax1 expressing genetically encoded Ca indicators demonstrated altered cytosolic Ca signals in cax1 during reoxygenation. Anoxia-induced Ca signals around the plant vacuole are involved in the control of numerous signaling events related to adaptation to low oxygen stress. This work suggests that cax1 anoxia response pathway could be engineered to circumvent the adverse effects of flooding that impair production agriculture.
Subject(s)
Arabidopsis , Cation Transport Proteins , Humans , Vacuoles/metabolism , Calcium/metabolism , Antiporters/metabolism , Protons , Proteomics , Cation Transport Proteins/metabolism , Arabidopsis/metabolism , Hypoxia/genetics , Hypoxia/metabolism , Oxygen/metabolismABSTRACT
We consider estimator and model choice when estimating abundance from capture-recapture data. Our work is motivated by a mark-recapture distance sampling example, where model and estimator choice led to unexpectedly large disparities in the estimates. To understand these differences, we look at three estimation strategies (maximum likelihood estimation, conditional maximum likelihood estimation, and Bayesian estimation) for both binomial and Poisson models. We show that assuming the data have a binomial or multinomial distribution introduces implicit and unnoticed assumptions that are not addressed when fitting with maximum likelihood estimation. This can have an important effect in finite samples, particularly if our data arise from multiple populations. We relate these results to those of restricted maximum likelihood in linear mixed effects models.
Subject(s)
Models, Statistical , Population Density , Bayes Theorem , Linear Models , Likelihood FunctionsABSTRACT
Root elongation depends on the action of the gibberellin (GA) growth hormones, which promote cell production in the root meristem and cell expansion in the elongation zone. Sites of GA biosynthesis in the roots of 7-d-old Arabidopsis thaliana seedlings were investigated using tissue-specific GA inactivation in wild-type (Col-0) or rescue of GA-deficient dwarf mutants. Tissue-specific GA depletion was achieved by ectopic expression of the GA-inactivating enzyme AtGA2ox2, which is specific for C19 -GAs, and AtGA2ox7, which acts on C20 -GA precursors. In addition, tissue-specific rescue of ga20ox triple and ga3ox double mutants was shown. Furthermore, GUS reporter lines for major GA20ox, GA3ox and GA2ox genes were used to observe their expression domains in the root. The effects of expressing these constructs on the lengths of the root apical meristem and cortical cells in the elongation zone confirmed that roots are autonomous for GA biosynthesis, which occurs in multiple tissues, with the endodermis a major site of synthesis. The results are consistent with the early stages of GA biosynthesis within the root occurring in the meristematic region and indicate that the penultimate step of GA biosynthesis, GA 20-oxidation, is required in both the meristem and elongation zone.
Subject(s)
Arabidopsis Proteins , Arabidopsis , Arabidopsis/genetics , Arabidopsis/metabolism , Arabidopsis Proteins/genetics , Arabidopsis Proteins/metabolism , Gene Expression Regulation, Plant , Gibberellins , Meristem/metabolismABSTRACT
Microgravity is known to affect the organization of the cytoskeleton, cell and nuclear morphology and to elicit differential expression of genes associated with the cytoskeleton, focal adhesions and the extracellular matrix. Although the nucleus is mechanically connected to the cytoskeleton through the Linker of Nucleoskeleton and Cytoskeleton (LINC) complex, the role of this group of proteins in these responses to microgravity has yet to be defined. In our study, we used a simulated microgravity device, a 3-D clinostat (Gravite), to investigate whether the LINC complex mediates cellular responses to the simulated microgravity environment. We show that nuclear shape and differential gene expression are both responsive to simulated microgravity in a LINC-dependent manner and that this response changes with the duration of exposure to simulated microgravity. These LINC-dependent genes likely represent elements normally regulated by the mechanical forces imposed by gravity on Earth.
Subject(s)
Cell Nucleus/physiology , Cytoskeleton/physiology , Gene Expression/physiology , Nuclear Matrix/physiology , Cell Line , Extracellular Matrix/physiology , Focal Adhesions/physiology , Humans , Weightlessness , Weightlessness Simulation/methodsABSTRACT
PREMISE OF THE STUDY: Spaceflight provides a unique environment in which to dissect plant stress response behaviors and to reveal potentially novel pathways triggered in space. We therefore analyzed the transcriptomes of Arabidopsis thaliana plants grown on board the International Space Station to find the molecular fingerprints of these space-related response networks. METHODS: Four ecotypes (Col-0, Ws-2, Ler-0 and Cvi-0) were grown on orbit and then their patterns of transcript abundance compared to ground-based controls using RNA sequencing. KEY RESULTS: Transcripts from heat-shock proteins were upregulated in all ecotypes in spaceflight, whereas peroxidase transcripts were downregulated. Among the shared and ecotype-specific changes, gene classes related to oxidative stress and hypoxia were detected. These spaceflight transcriptional response signatures could be partly mimicked on Earth by a low oxygen environment and more fully by oxidative stress (H2 O2 ) treatments. CONCLUSIONS: These results suggest that the spaceflight environment is associated with oxidative stress potentially triggered, in part, by hypoxic response. Further, a shared spaceflight response may be through the induction of molecular chaperones (such as heat shock proteins) that help protect cellular machinery from the effects of oxidative damage. In addition, this research emphasizes the importance of considering the effects of natural variation when designing and interpreting changes associated with spaceflight experiments.
Subject(s)
Arabidopsis/metabolism , Oxidative Stress , Space Flight , Transcriptome , Ecotype , Gene Expression Regulation, Plant , Heat-Shock Response , Peroxidase/metabolismABSTRACT
RATIONALE: Stable isotope ratios can provide a 'fingerprint' to enable differentiation of sources of monofluoroacetate (MFA), hence providing a means to eliminate potential sources of MFA in a blackmail case involving the contamination of milk. METHODS: The stable isotopic compositions (δ2 H, δ13 C and δ18 O values) of a library of 43 samples of MFA were determined and multivariate models constructed to differentiate samples of different composition. The data from the MFA library were compared with those obtained from MFA extracted from contaminated milk powder (the case samples). The isotopic composition of the extracted samples was measured on dichloroaniline derivatives. RESULTS: A wide range of values was found for δ2 H, δ13 C and δ18 O of the MFA samples, much greater than the analytical repeatability between subsamples. Stable isotope data, therefore, provide a means of distinguishing samples of MFA. Of the 43 MFA samples tested, all but 6 could be eliminated as potential sources of the contamination, i.e. they had a distinctly different isotopic composition such that they must have had different histories and/or origins. CONCLUSIONS: Stable isotope measurements of bulk and derivatized MFA provide an effective means of discriminating MFA samples. Three of the library samples that could not be differentiated from the case samples were directly connected to the suspect, and this evidence contributed to the suspect's admission of guilt.
ABSTRACT
Article impact statement: New collaborations with accounting research can improve conservation impact of ecosystem-based information systems.
Subject(s)
Conservation of Natural Resources , EcosystemABSTRACT
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ABSTRACT
N-mixture models provide an appealing alternative to mark-recapture models, in that they allow for estimation of detection probability and population size from count data, without requiring that individual animals be identified. There is, however, a cost to using the N-mixture models: inference is very sensitive to the model's assumptions. We consider the effects of three violations of assumptions that might reasonably be expected in practice: double counting, unmodeled variation in population size over time, and unmodeled variation in detection probability over time. These three examples show that small violations of assumptions can lead to large biases in estimation. The violations of assumptions we consider are not only small qualitatively, but are also small in the sense that they are unlikely to be detected using goodness-of-fit tests. In cases where reliable estimates of population size are needed, we encourage investigators to allocate resources to acquiring additional data, such as recaptures of marked individuals, for estimation of detection probabilities.
Subject(s)
Models, Statistical , Animals , Bias , Population Density , ProbabilityABSTRACT
The standard approach to fitting capture-recapture data collected in continuous time involves arbitrarily forcing the data into a series of distinct discrete capture sessions. We show how continuous-time models can be fitted as easily as discrete-time alternatives. The likelihood is factored so that efficient Markov chain Monte Carlo algorithms can be implemented for Bayesian estimation, available online in the R package ctime. We consider goodness-of-fit tests for behavior and heterogeneity effects as well as implementing models that allow for such effects.
Subject(s)
Likelihood Functions , Models, Statistical , Algorithms , Bayes Theorem , Markov Chains , Monte Carlo Method , Poisson Distribution , Time FactorsABSTRACT
N-mixture models describe count data replicated in time and across sites in terms of abundance N and detectability p. They are popular because they allow inference about N while controlling for factors that influence p without the need for marking animals. Using a capture-recapture perspective, we show that the loss of information that results from not marking animals is critical, making reliable statistical modeling of N and p problematic using just count data. One cannot reliably fit a model in which the detection probabilities are distinct among repeat visits as this model is overspecified. This makes uncontrolled variation in p problematic. By counter example, we show that even if p is constant after adjusting for covariate effects (the "constant p" assumption) scientifically plausible alternative models in which N (or its expectation) is non-identifiable or does not even exist as a parameter, lead to data that are practically indistinguishable from data generated under an N-mixture model. This is particularly the case for sparse data as is commonly seen in applications. We conclude that under the constant p assumption reliable inference is only possible for relative abundance in the absence of questionable and/or untestable assumptions or with better quality data than seen in typical applications. Relative abundance models for counts can be readily fitted using Poisson regression in standard software such as R and are sufficiently flexible to allow controlling for p through the use covariates while simultaneously modeling variation in relative abundance. If users require estimates of absolute abundance, they should collect auxiliary data that help with estimation of p.
Subject(s)
Animal Distribution , Models, Statistical , Animals , Linear Models , Population Density , Population DynamicsABSTRACT
BACKGROUND: One of the functions of the reformed Cancer Drugs Fund in England is as a managed access fund, providing conditional funding for cancer drugs where there is uncertainty in the economic case, and where that uncertainty can be addressed by data collection during two years' use in the NHS. Our study characterises likely sources of such uncertainty, through a review of recent NICE Technology Appraisals. METHODS: Discussions of uncertainty in NICE Appraisal Committees were extracted from published Single Technology Appraisals of cancer drugs, 2014-2016, and categorised inductively. The location of the comments within the structured Appraisal document was used as a proxy for the degree of concern shown by the Committee. RESULTS: Twenty-nine appraisals were analysed, of which 23 (79%) were recommended for funding. Six main sources of uncertainty were identified. Immaturity of survival data, and issues relating to comparators, were common sources of uncertainty regardless of degree of concern. Uncertainties relating to quality of life, and the patient population in the trial, were discussed frequently but rarely occurred in the more uncertain appraisals. Concerns with trial design, and cost uncertainty, were less common, but a high proportion contributed to the most uncertain appraisals. Funding decisions were not driven by uncertainty in the evidence base, but by the expected cost per QALY relative to acceptance thresholds, and the resultant level of uncertainty in the decision. CONCLUSIONS: The reformed CDF is an improvement on its predecessor. However the main types of uncertainty seen in recent cancer appraisals will not readily be resolved solely by 2 years' RWD collection in the reformed CDF; where there are no ongoing trials to provide longer-term data, randomised trials rather than RWD may be needed to fully resolve questions of relative efficacy. Other types of uncertainty, and concerns with generalisability, may be more amenable to the RWD approach, and it is these that we expect to be the focus of data collection arrangements in the reformed CDF.
Subject(s)
Antineoplastic Agents/economics , Neoplasms/economics , Uncertainty , Advisory Committees , Antineoplastic Agents/therapeutic use , Clinical Trials as Topic/economics , Cost-Benefit Analysis , Drug Approval/economics , Drug Costs , England , Financial Management , Humans , Neoplasms/drug therapy , Quality of Life , Quality-Adjusted Life Years , Sample Size , Technology Assessment, Biomedical/economicsABSTRACT
BACKGROUND: The Scottish Medicines Consortium evaluates new drugs for use in the National Health Service in Scotland. Reforms in 2014 to their evaluation process aimed to increase patient access to new drugs for end-of-life or rare conditions; the changes include additional steps in the process to gain further information from patients and clinicians, and for revised commercial agreements. This study examines the extent of any impact of the reforms on funding decisions. METHOD: Data on the Scottish Medicines Consortium's funding decisions during 24 months post-reform were extracted from published Advice, for descriptive statistics and thematic analysis. Comparison data were extracted for the 24 months pre-reform. Data on decisions for England by the National Institute for Clinical and Health Excellence for the same drugs were extracted from published Technology Appraisals. RESULTS: The new process was used by 90% (53/59) of cancer submissions. It is triggered if the initial advice is not to recommend, and this risk-of-rejection level is higher than in the pre-period. Thirty-eight cancer drugs obtained some level of funding through the new process, but there was no significant difference in the distribution of decision types compared to the pre-reform period. Thematic analysis of patient and clinician input showed no clear relationship between issues raised and funding decision. Differences between SMC's and NICE's definitions of End-of-Life did not fully explain differences in funding decisions. CONCLUSIONS: The Scottish Medicines Consortium's reforms have allowed funding of up to 38 cancer drugs that might previously have been rejected. However, the contribution of specific elements of the reforms to the final decision is unclear. The process could be improved by increased transparency in how the non-quantitative inputs influence decisions. Some disparities in funding decisions between England and Scotland are likely to remain despite recent process convergence.
Subject(s)
Antineoplastic Agents , Delivery of Health Care/economics , Financing, Organized , National Health Programs/economics , Neoplasms/drug therapy , Rare Diseases/drug therapy , Terminal Care/economics , Antineoplastic Agents/economics , Antineoplastic Agents/therapeutic use , Cost-Benefit Analysis , Decision Making , Humans , Neoplasms/economics , Rare Diseases/economics , ScotlandABSTRACT
Distinct phylogenetic lineages of Mycobacterium tuberculosis (MTB) cause disease in patients of particular genetic ancestry, and elicit different patterns of cytokine and chemokine secretion when cultured with human macrophages in vitro. Circulating and antigen-stimulated concentrations of these inflammatory mediators might therefore be expected to vary significantly between tuberculosis patients of different ethnic origin. Studies to characterise such variation, and to determine whether it relates to host or bacillary factors, have not been conducted. We therefore compared circulating and antigen-stimulated concentrations of 43 inflammatory mediators and 14 haematological parameters (inflammatory profile) in 45 pulmonary tuberculosis patients of African ancestry vs. 83 patients of Eurasian ancestry in London, UK, and investigated the influence of bacillary and host genotype on these profiles. Despite having similar demographic and clinical characteristics, patients of differing ancestry exhibited distinct inflammatory profiles at presentation: those of African ancestry had lower neutrophil counts, lower serum concentrations of CCL2, CCL11 and vitamin D binding protein (DBP) but higher serum CCL5 concentrations and higher antigen-stimulated IL-1 receptor antagonist and IL-12 secretion. These differences associated with ethnic variation in host DBP genotype, but not with ethnic variation in MTB strain. Ethnic differences in inflammatory profile became more marked following initiation of antimicrobial therapy, and immunological correlates of speed of elimination of MTB from the sputum differed between patients of African vs. Eurasian ancestry. Our study demonstrates a hitherto unappreciated degree of ethnic heterogeneity in inflammatory profile in tuberculosis patients that associates primarily with ethnic variation in host, rather than bacillary, genotype. Candidate immunodiagnostics and immunological biomarkers of response to antimicrobial therapy should be derived and validated in tuberculosis patients of different ethnic origin.