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OBJECTIVETo evaluate glycemic outcomes in youth (aged 13–25 years) with type 1 diabetes and high-risk glycemic control (HbA1c ≥8.5% [69 mmol/mol]) on multiple daily injection (MDI) therapy after transitioning to advanced hybrid closed loop (AHCL) therapy.RESEARCH DESIGN AND METHODSThis prospective, 3-month, single-arm, dual-center study enrolled 20 participants, and all completed the study.RESULTSHbA1c decreased from 10.5 ± 2.1% (91.2 ± 22.8 mmol/mol) at baseline to 7.6 ± 1.1% (59.7 ± 11.9 mmol/mol), and time spent in target range 70–180 mg/dL (3.9–10.0 mmol/L) increased from 27.6 ± 13.2% at baseline to 66.5 ± 9.8% after 3 months of AHCL. Two episodes of diabetic ketoacidosis attributed to infusion set failure occurred.CONCLUSIONSAHCL has the potential to improve suboptimal glycemia in youth with type 1 diabetes previously on MDI therapy.

Lumateperone is indicated for the treatment of schizophrenia in adults and for depressive episodes associated with bipolar I or II disorder (bipolar depression) in adults, as monotherapy and as adjunctive therapy with lithium or valproate (Calabrese et al., 2021). It is currently under evaluation for the treatment of major depressive disorder (www.ClinicalTrials.gov). Lumateperone acts by selectively modulating serotonin, dopamine, and glutamate neurotransmission in the brain. However, other mechanisms could be involved in the actions of lumateperone, and because of the connection between the immune system and psychiatric health, we hypothesized that lumateperone might improve symptoms of depression, at least in part, by normalizing pathologic inflammation. Here, we show that in male and female C57BL/6 mice subjected to an acute immune challenge, lumateperone reduced aberrantly elevated levels of key proinflammatory cytokines (e.g., IL-1β, IL-6, and TNF-α) in both brain and serum; lumateperone also reduced proinflammatory cytokines in male mice under acute behavioral stress. Further, we demonstrate that lumateperone altered key genes/pathways involved in maintaining tissue integrity and supporting blood–brain barrier function, such as claudin-5 and intercellular adhesion molecule 1. In addition, in acutely stressed male Sprague Dawley rats, lumateperone conferred anxiolytic- and antianhedonic-like properties while enhancing activity in the mammalian target of rapamycin complex 1 pathway in the PFC. Together, our preclinical findings indicate that lumateperone, in addition to its ability to modulate multiple neurotransmitter systems, could also act by reducing the impact of acute inflammatory challenges.SIGNIFICANCE STATEMENTLumateperone is indicated in adults to treat schizophrenia and depressive episodes associated with bipolar I or II disorder, as monotherapy and adjunctive therapy with lithium or valproate. Because aberrant immune system activity is associated with increased depressive symptoms, the relationship between lumateperone and immune function was studied. Here, lumateperone reduced the levels of proinflammatory cytokines that were increased following an immune challenge or stress in mice. Additionally, lumateperone altered genes and pathways that maintain blood–brain barrier integrity, restored an index of blood–brain barrier function, reduced anxiety-like behavior in rodents, and enhanced mammalian target of rapamycin complex 1 pathway signaling in the PFC. These results highlight the anti-inflammatory actions of lumateperone and describe how lumateperone may reduce immune pathophysiology, which is associated with depressive symptoms.

Introduction: Community Engagement and the All of Us Research Program. Community engagement is a proven and effective tool to enhance participation in research by increasing access and awareness of medical studies. Increasing access and awareness of medical studies with an emphasis on populations who have been historically underrepresented in biomedical research (UBR) has also shown to expand the reach of innovative and novel breakthrough therapies in early detection to improve cancer outcomes. To ensure that advances in early detection improve cancer health inequities for all, early engagement has been demonstrated to be critical. Early and ongoing engagement has been at the core of the National Institutes of Health (NIH) All of Us Research Program. All of Us adheres to the community engagement principles of information-sharing, consultation, involvement and collaboration in decision-making, and empowered action in informal groups or through formal partnerships. Since its inception in 2015, the overarching goal of the All of Us community engagement strategy has been to create a program that reflects the needs, preferences, and priorities of individuals in the U.S. inclusive of UBR communities. As such, program participants and partners have been involved in all aspects of the program including governance, oversight, design, conduct, dissemination, and evaluation. All of Us has accomplished unprecedented advances in the inclusion of UBR populations by building the largest, most diverse biomedical resource of its kind: 80% of program participants are from UBR communities covering a broad range of age, social, racial, ethnic, cultural, geographical, and health statuses. Additionally, nearly 50% of participants self-identify as racial and ethnic minorities. This inclusion of diverse communities throughout the program moves us closer to achieving health equity in biomedical research and ensuring more precise care for all. The Role of Early Community Engagement in Mitigating Cancer Disparities. Our ability to have a diverse participant pool is due in large part to intentional and early community engagement efforts together with the creation of an ecosystem built to support community partners. Research shows that community engagement can help mitigate cancer health disparities by increasing communities’ knowledge of the importance of healthy behaviors such as screening, awareness of research, building trust in research, and improving study design and ethics. All of this combined with groundbreaking progress in early cancer detection and available therapies has the potential to transform patient care. Immunotherapy and gene therapy, a better understanding of fertility preservation in cancer treatment, and how artificial intelligence (AI) models can predict patients’ risks of breast cancer are only a few recent and transformative advances that are driving progress against cancer. While these and other advances are promising, many UBR communities have not benefited equally from this progress. Historical, systemic, and structural barriers, such as the digital divide and lack of access to and awareness of clinical trials, are preventing the achievement of equitable advances in precision medicine and cancer research. Early and intentional community engagement efforts must be put in place to ensure that these innovative advances reduce cancer disparities and improve cancer prevention and detection in medically underserved groups. For instance, we must consider the role that "ZNA" (zip code or neighborhood association) or "place and space" has on cancer. We know that ZNA can be just as important in the precision medicine and cancer journey as someone’s DNA. Research has not always been conducted in places where the populations reflect the diversity of the U.S. Most cancer oncology trials and cancer treatment centers may not be accessible to those that carry the greatest burden of disease, which leads to greater disparities. Similarly, researchers play an essential role in community engagement; studies have shown that being engaged by a research team that reflects the diversity of the population being studied leads to greater participation in research, better retention, and adherence to recommendations. Conclusion: These are only a few reasons why engaging UBR communities in the early phases and throughout the duration of research studies is important to identify the right problems, formulate the appropriate questions, and build mutual trust and transparency. Redefining participants’ roles not as “patients” or “subjects” but as true partners will improve health outcomes and better address health care for all, leading us to a future where precision engagement drives research along with rigorous science and where community engagement ensures equity and inclusion in precision medicine for all. Objectives: This presentation will (a) describe how early engagement can lead to mitigation of cancer disparities, (b) discuss best practices of early and intentional community engagement, (c) outline the All of Us engagement ecosystem, and (d) explore the future of engagement in building sustainable, cohesive, and equitable communities. Citation Format: Karriem S. Watson. Early Engagement Equals Early Detection. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr PL03-05.

In the US, newborn screening (NBS) is a unique health program that supports health equity and screens virtually every baby after birth, and has brought timely treatments to babies since the 1960's. With the decreasing cost of sequencing and the improving methods to interpret genetic data, there is an opportunity to add DNA sequencing as a screening method to facilitate the identification of babies with treatable conditions that cannot be identified in any other scalable way, including highly penetrant genetic neurodevelopmental disorders (NDD). However, the lack of effective dietary or drug-based treatments has made it nearly impossible to consider NDDs in the current NBS framework, yet it is anticipated that any treatment will be maximally effective if started early. Hence there is a critical need for large scale pilot studies to assess if and how NDDs can be effectively screened at birth, if parents desire that information, and what impact early diagnosis may have. Here we attempt to provide an overview of the recent advances in NDD treatments, explore the possible framework of setting up a pilot study to genetically screen for NDDs, highlight key technical, practical, and ethical considerations and challenges, and examine the policy and health system implications.

Despite the popularity of feature importance (FI) measures in interpretable machine learning, the statistical adequacy of these methods is rarely discussed. From a statistical perspective, a major distinction is between analysing a variable’s importance before and after adjusting for covariates—i.e., between marginal and conditional measures. Our work draws attention to this rarely acknowledged, yet crucial distinction and showcases its implications. We find that few methods are available for testing conditional FI and practitioners have hitherto been severely restricted in method application due to mismatched data requirements. Most real-world data exhibits complex feature dependencies and incorporates both continuous and categorical features (i.e., mixed data). Both properties are oftentimes neglected by conditional FI measures. To fill this gap, we propose to combine the conditional predictive impact (CPI) framework with sequential knockoff sampling. The CPI enables conditional FI measurement that controls for any feature dependencies by sampling valid knockoffs—hence, generating synthetic data with similar statistical properties—for the data to be analysed. Sequential knockoffs were deliberately designed to handle mixed data and thus allow us to extend the CPI approach to such datasets. We demonstrate through numerous simulations and a real-world example that our proposed workflow controls type I error, achieves high power, and is in-line with results given by other conditional FI measures, whereas marginal FI metrics can result in misleading interpretations. Our findings highlight the necessity of developing statistically adequate, specialized methods for mixed data.

Unsupervised learning algorithms are widely used for many important statistical tasks with numerous applications in science and industry. Yet despite their prevalence, they have attracted remarkably little philosophical scrutiny to date. This stands in stark contrast to supervised and reinforcement learning algorithms, which have been widely studied and critically evaluated, often with an emphasis on ethical concerns. In this article, I analyze three canonical unsupervised learning problems: clustering, abstraction, and generative modeling. I argue that these methods raise unique epistemological and ontological questions, providing data-driven tools for discovering natural kinds and distinguishing essence from contingency. This analysis goes some way toward filling the lacuna in contemporary philosophical discourse on unsupervised learning, as well as bringing conceptual unity to a heterogeneous field more often described by what it is not (i.e., supervised or reinforcement learning) than by what it is. I submit that unsupervised learning is not just a legitimate subject of philosophical inquiry but perhaps the most fundamental branch of all AI. However, an uncritical overreliance on unsupervised methods poses major epistemic and ethical risks. I conclude by advocating for a pragmatic, error-statistical approach that embraces the opportunities and mitigates the challenges posed by this powerful class of algorithms.

ObjectiveTo describe the National Heart Lung and Blood Institute (NHLBI) sponsored Disparities Elimination through Coordinated Interventions to Prevent and Control Heart and Lung Disease (DECIPHeR) Alliance to support late-stage implementation research aimed at reducing disparities in communities with high burdens of cardiovascular and/or pulmonary disease.Study settingNHBLI funded seven DECIPHeR studies and a Coordinating Center. Projects target high-risk diverse populations including racial and ethnic minorities, urban, rural, and low-income communities, disadvantaged children, and persons with serious mental illness. Two projects address multiple cardiovascular risk factors, three focus on hypertension, one on tobacco use, and one on pediatric asthma.Study designThe initial phase supports planning activities for sustainable uptake of evidence-based interventions in targeted communities. The second phase tests late-stage evidence-based implementation strategies.Data collection/extraction methodsNot applicable.Principal findingsWe provide an overview of the DECIPHeR Alliance and individual study designs, populations, and settings, implementation strategies, interventions, and outcomes. We describe the Alliance's organizational structure, designed to promote cross-center partnership and collaboration.ConclusionsThe DECIPHeR Alliance represents an ambitious national effort to develop sustainable implementation of interventions to achieve cardiovascular and pulmonary health equity.

Genomic/precision medicine offers a remarkable opportunity to improve health and address health disparities. Genomic medicine is the study of genes and their interaction with health. Precision medicine is an approach to disease prevention and treatment that considers individual variability in genes, environment and lifestyle. Conclusions from studies lacking diversity may hinder generalizability as genomic variation occurs within and between populations. Historical factors, such as medical mistrust, ethical issues related to decision making, and data sharing pose complex challenges that may further widen inequities in genomic/precision medicine if not appropriately addressed. Although few biomedical studies integrate priorities of community partners into their conceptual framework, effective implementation of genomic/precision medicine research calls for the involvement of diverse stakeholders to expand traditional unidirectional models of engagement in clinical research towards authentic bidirectional collaboration.A multipronged approach was used integrating an evidence-based literature review and best practices in developing and evaluating the engagement of diverse stakeholders in genomic and precision medicine research. This was combined with expert consensus building to adapt a conceptual model from a community engagement framework to addressing genomics to be scalable to engagement science, which is challenging to genomic/precision medicine research.The final enhanced conceptual framework is composed of four overarching dimensions now inclusive of domains in trust, exploitation, discrimination, privacy risk, stigmatization, prior harms/injustices, failure to recognize coexisting governments, intersectionality and research transformation. This conceptual framework proposes effective participant research engagement strategies for upstream relationship building, distinct from downstream recruitment strategies in which the goal is enrolment.To further shape the evolution of genomic/precision medicine research, it is important to leverage existing partnerships, engage participants beyond recruitment and embrace diverse perspectives.In preparation of this manuscript, the perspectives of the community partners on the impact of engaging in genomic/precision medicine research beyond research participation were integrated into this conceptual framework from various guided listening sessions held in diverse communities.

Health plan claims may provide complete longitudinal data for timely, real-world population-level COVID-19 assessment. However, these data often lack laboratory results, the standard for COVID-19 diagnosis.We assessed the validity of ICD-10-CM diagnosis codes for identifying patients hospitalized with COVID-19 in U.S. claims databases, compared to linked laboratory results, among six Food and Drug Administration Sentinel System data partners (two large national insurers, four integrated delivery systems) from February 20-October 17, 2020. We identified patients hospitalized with COVID-19 according to five ICD-10-CM diagnosis code-based algorithms, which included combinations of codes U07.1, B97.29, general coronavirus codes, and diagnosis codes for severe symptoms. We calculated the positive predictive value (PPV) and sensitivity of each algorithm relative to laboratory test results. We stratified results by data source type and across three time periods: February 20-March 31 (Time A), April 1-30 (Time B), May 1-October 17 (Time C).The five algorithms identified between 34 806 and 47 293 patients across the study periods; 23% with known laboratory results contributed to PPV calculations. PPVs were high and similar across algorithms. PPV of U07.1 alone was stable around 93% for integrated delivery systems, but declined over time from 93% to 70% among national insurers. Overall PPV of U07.1 across all data partners was 94.1% (95% CI, 92.3%-95.5%) in Time A and 81.2% (95% CI, 80.1%-82.2%) in Time C. Sensitivity was consistent across algorithms and over time, at 94.9% (95% CI, 94.2%-95.5%).Our results support the use of code U07.1 to identify hospitalized COVID-19 patients in U.S. claims data.

The Winchcombe meteorite fell on 28th February 2021 in Gloucestershire, UK. As the most accurately recorded carbonaceous chondrite fall, the Winchcombe meteorite is an opportunity to link a tangible sample of known chemical constitution to a specific region of the solar system whose chemistry can only be otherwise predicted or observed remotely. Winchcombe is a CM carbonaceous chondrite, a group known for their rich and varied abiotic organic chemistry. The rapid collection of Winchcombe provides an opportunity to study a relatively terrestrial contaminant-limited meteoritic organic assemblage. The majority of the organic matter in CM chondrites is macromolecular in nature and we have performed non-destructive and destructive analyses of Winchcombe by Raman spectroscopy, online pyrolysis-gas chromatography (pyrolysis-GC-MS), and stepped combustion. The Winchcombe pyrolysis products were consistent with a CM chondrite, namely aromatic and polycyclic aromatic hydrocarbons, sulfur-containing units including thiophenes, oxygen containing units such as phenols and furans, and nitrogen-containing units such as pyridine; many substituted/alkylated forms of these units were also present. The presence of phenols in the online pyrolysis products indicated only limited influence from aqueous alteration, which can deplete the phenol precursors in the macromolecule when aqueous alteration is extensive. Raman spectroscopy and stepped combustion also generated responses consistent with a CM chondrite. The pyrolysis-GC-MS data is likely to reflect the more labile and thermally sensitive portions of the macromolecular materials while the Raman and stepped combustion data will also reflect the more refractory and non-pyrolyzable component, hence we accessed the complete macromolecular fraction of the recently fallen Winchcombe meteorite and revealed a chemical constitution that is similar to other meteorites of the CM group.

Six strains, KI11_D11T, KI4_B1, KI11_C11T, KI16_H9T, KI4_A6T and KI3_B9T, were isolated from insects and flowers on Kangaroo Island, South Australia. On the basis of 16S rRNA gene phylogeny, strains KI11_D11T, KI4_B1, KI11_C11T, KI16_H9T, KI4_A6T were found to be closely related to Fructilactobacillus ixorae Ru20-1T. Due to the lack of a whole genome sequence for this species, whole genome sequencing of Fructilactobacillus ixorae Ru20-1T was undertaken. KI3_B9T was found to be closely related to Fructobacillus tropaeoli F214-1T. Utilizing core gene phylogenetics and whole genome analyses, such as determination of AAI, ANI and dDDH, we propose that these six isolates represent five novel species with the names Fructilactobacillus cliffordii (KI11_D11T= LMG 32130T = NBRC 114988T), Fructilactobacillus hinvesii (KI11_C11T = LMG 32129T = NBRC 114987T), Fructilactobacillus myrtifloralis (KI16_H9T= LMG 32131T = NBRC 114989T) Fructilactobacillus carniphilus (KI4_A6T = LMG 32127T = NBRC 114985T) and Fructobacillus americanaquae (KI3_B9T = LMG 32124T = NBRC 114983T). Chemotaxonomic analyses detected no fructophilic characters for these strains of member of the genus Fructilactobacillus . KI3_B9T was found to be obligately fructophilic, similarly to its phylogenetic neighbours in the genus Fructobacillus . This study represents the first isolation, to our knowledge, of novel species in the family Lactobacillaceae from the Australian wild.

Classical novae are shock-powered multi-wavelength transients triggered by a thermonuclear runaway on an accreting white dwarf. V1674 Her is the fastest nova ever recorded (time to declined by two magnitudes is t_2=1.1 d) that challenges our understanding of shock formation in novae. We investigate the physical mechanisms behind nova emission from GeV gamma-rays to cm-band radio using coordinated Fermi-LAT, NuSTAR, Swift and VLA observations supported by optical photometry. Fermi-LAT detected short-lived (18 h) 0.1-100 GeV emission from V1674 Her that appeared 6 h after the eruption began; this was at a level of (1.6 +/- 0.4)x10^-6 photons cm^-2 s^-1. Eleven days later, simultaneous NuSTAR and Swift X-ray observations revealed optically thin thermal plasma shock-heated to kT_shock = 4 keV. The lack of a detectable 6.7 keV Fe K_alpha emission suggests super-solar CNO abundances. The radio emission from V1674 Her was consistent with thermal emission at early times and synchrotron at late times. The radio spectrum steeply rising with frequency may be a result of either free-free absorption of synchrotron and thermal emission by unshocked outer regions of the nova shell or the Razin-Tsytovich effect attenuating synchrotron emission in dense plasma. The development of the shock inside the ejecta is unaffected by the extraordinarily rapid evolution and the intermediate polar host of this nova., 20 pages, 9 figures, 3 tables. Accepted to MNRAS

Organic matter in sediments is dominated by kerogen, a high molecular weight geomacromolecule. Kerogen can be subdivided into Types I to IV that provide paleoenvironmental and petroleum potential information. Kerogen typing can be performed by several chemical methods including elemental analysis (H/C and O/C), FTIR and pyrolysis-gas chromatography techniques. However, kerogens occur naturally within mineral matrices and these can influence the chemical responses. We have examined the effects of a range of minerals (namely kaolinite, lizardite, ripidolite, illite, montmorillonite, haematite, goethite, limonite and magnetite) on the responses of kerogen to pyrolysis-gas chromatography-mass spectrometry. We used aliphatic hydrocarbon containing kerogen Types I and II from Carboniferous Midland Valley shales of Scotland and the Jurassic Oxford Clay of southern England, respectively, as well as a pure synthetic aliphatic polymer, polyethylene. We find that the aliphatic organic matter in Type I kerogens is transformed by interaction with minerals during pyrolysis to give a signal incorrectly suggesting more contributions from land plant-containing kerogens, such as a large number of aromatic molecules. Pyrolysis with goethite, limonite and magnetite leads to almost complete destruction of the organic matter. Hence, the mineral composition of sedimentary rocks during pyrolysis should be considered when assigning kerogen types. Failure to consider the effects of minerals can lead to incorrect assignment of kerogen type and, therefore, erroneous interpretations of paleoenvironments and petroleum potential.

Plantago ovatais cultivated for production of its seed husk (psyllium). When wet, the husk transforms into a mucilage with properties suitable for pharmaceutical industries, utilised in supplements for controlling blood cholesterol levels, and food industries for making gluten-free products. There has been limited success in improving husk quantity and quality through breeding approaches, partly due to the lack of a reference genome. Here we constructed the first chromosome-scale reference assembly ofP. ovatausing a combination of 5.98 million PacBio and 636.5 million Hi-C reads. We also used corrected PacBio reads to estimate genome size and transcripts to generate gene models. The final assembly covers ~ 500 Mb with 99.3% gene set completeness. A total of 97% of the sequences are anchored to four chromosomes with an N50 of ~ 128.87 Mb. TheP. ovatagenome contains 61.90% repeats, where 40.04% are long terminal repeats. We identified 41,820 protein-coding genes, 411 non-coding RNAs, 108 ribosomal RNAs, and 1295 transfer RNAs. This genome will provide a resource for plant breeding programs to, for example, reduce agronomic constraints such as seed shattering, increase psyllium yield and quality, and overcome crop disease susceptibility.

Objective: To evaluate glycemic outcomes in youth (aged 13–25 years) with type 1 diabetes and high-risk glycemic control [HbA1c ≥ 8.5% (69 mmol/mol)] on multiple daily injections (MDI) after transitioning to advanced hybrid closed-loop (AHCL) therapy. Research Design and Methods: This prospective 3-month single-arm, dual-center study enrolled 20 participants, and all completed the study. Results: HbA1c decreased from 10.5 ± 2.1% (91.2 ± 22.8 mmol/mol) at baseline to 7.6 ± 1.1% (59.7 ± 11.9 mmol/mol) and time spent in target range 70–180 mg/dL (3.9–10.0 mmol/L) increased from 27.6 ± 13.2% at baseline, to 66.5 ± 9.8% after 3 months of AHCL. Two episodes of diabetic ketoacidosis attributed to infusion set failure occurred. Conclusions: AHCL has the potential to improve suboptimal glycemia in youth with type 1 diabetes previously on MDI.

The rapid recovery of the Winchcombe meteorite offers a valuable opportunity to study the soluble organic matter (SOM) profile in pristine carbonaceous astromaterials. Our interests in the biologically relevant molecules, amino acids—monomers of protein, and the most prevalent meteoritic organics—polycyclic aromatic hydrocarbons (PAHs) are addressed by analyzing the solvent extracts of a Winchcombe meteorite stone using gas chromatography mass spectrometry. The Winchcombe sample contains an amino acid abundance of ~1132 parts-per-billion that is about 10 times lower than other CM2 meteorites. The detection of terrestrially rare amino acids, including α-aminoisobutyric acid (AIB); isovaline; β-alanine; α-, β-, and γ-amino-n-butyric acids; and 5-aminopentanoic acid, and the racemic enantiomeric ratios (D/L = 1) observed for alanine and isovaline indicate that these amino acids are indigenous to the meteorite and not terrestrial contaminants. The presence of predominantly α-AIB and isovaline is consistent with their formation via the Strecker-cyanohydrin synthetic pathway. The L-enantiomeric excesses in isovaline previously observed for aqueously altered meteorites were viewed as an indicator of parent body aqueous processing; thus, the racemic ratio of isovaline observed for Winchcombe, alongside the overall high free:total amino acid ratio, and the low amino acid concentration suggest that the analyzed stone is derived from a lithology that has experienced brief episode(s) of aqueous alteration. Winchcombe also contains 2- to 6-ring alkylated and nonalkylated PAHs. The low total PAHs abundance (6177 ppb) and high nonalkylated:alkylated ratio are distinct from that observed for heavily aqueously altered CMs. The weak petrographic properties of Winchcombe, as well as the discrepancies observed for the Winchcombe SOM content—a low total amino acid abundance comparable to heavily altered CMs, and yet the high free:total amino acid and nonalkylated:alkylated PAH ratios are on par with the less altered CMs—suggest that Winchcombe could represent a class of weak, poorly lithified meteorite not been previously studied.

Space missions concerned with life detection contain highly sensitive instruments for the detection of organics. Terrestrial contamination can interfere with signals of indigenous organics in samples and has the potential to cause false positive biosignature detections, which may lead to incorrect suggestions of the presence of life elsewhere in the Solar System. This study assessed the capability of solid phase micro extraction (SPME) as a method for monitoring organic contamination encountered by spacecraft hardware during assembly and operation. SPME-gas chromatography-mass spectrometry (SPME-GC-MS) analysis was performed on potential contaminant source materials, which are commonly used in spacecraft construction. The sensitivity of SPME-GC-MS to organics was assessed in the context of contaminants identified in molecular wipes taken from hardware surfaces on the ExoMars Rosalind Franklin rover. SPME was found to be effective at detecting a wide range of common organic contaminants that include aromatic hydrocarbons, non-aromatic hydrocarbons, nitrogen-containing compounds, alcohols and carbonyls. A notable example of correlation of contaminant with source material was the detection of benzenamine compounds in an epoxy adhesive analyzed by SPME-GC-MS and in the ExoMars rover surface wipe samples. The current form of SPME-GC-MS does not enable quantitative evaluation of contaminants, nor is it suitable for the detection of every group of organic molecules relevant to astrobiological contamination concerns, namely, large and/or polar molecules such as amino acids. However, it nonetheless represents an effective new monitoring method for rapid, easy identification of organic contaminants commonly present on spacecraft hardware and could thus be utilized in future space missions as part of their contamination control and mitigation protocols.

Rusts and powdery mildew are diseases that have a major effect on yield loss in barley. Adult Plant Resistance (APR) is a post-seedling resistance mechanism and its expression is influenced by many factors, including host susceptibility and weather conditions, as well as the timing and severity of disease outbreaks. There are two mechanisms associated with APR: non-hypersensitive and minor gene APR. In this study, 431 European barley accessions were evaluated phenotypically over 2 years (2018–2019) under field conditions, scoring APR to powdery mildew (PM), barley brown rust (BBR), and stem rust (SR), and genotypically using DArTseq. Accessions were grouped into sub-collections by cultivation period (group A—cultivated prior 1985, B—cultivated after 1985, and C—Polish landraces) and by European country of origin or European region. GWAS was conducted for PM, BBR, and SR, and scored at the heading (HA) and milky-waxy (MW) seed stages in 2019 and maximum scores across all replicates were obtained 2018–2019. Disease severity was sufficient to differentiate the collection according to cultivation time and country of origin and to determine SNPs. Overall, the GWAS analysis identified 73 marker–trait associations (MTAs) with these traits. For PM resistance, we identified five MTAs at both the HA stage and when considering the maximal disease score across both growth stages and both years. One marker (3432490-28-T/C) was shared between these two traits; it is located on chromosome 4H. For BBR resistance, six MTAs at HA and one MTA at the MW stage in 2019 and seven MTAs, when considering the maximal disease score across both growth stages and both years, were identified. Of the 48 markers identified as being associated with SR resistance, 12 were on chromosome 7H, 1 was in the telomeric region of the short arm, and 7 were in the telomeric region of the long arm. Rpg1 has previously been mapped to 7HS. The results of this study will be used to create a Polish Gene Bank platform for precise breeding programs. The resistant genotypes and MTA markers will serve as a valuable resource for breeding for PM, BBR, and SR resistance in barley.

Salinity tolerance in bread wheat is frequently reported to be associated with low leaf sodium (Na+) concentrations. However, the Portuguese landrace, Mocho de Espiga Branca, accumulates significantly higher leaf Na+ but has comparable salinity tolerance to commercial bread wheat cultivars. To determine the genetic loci associated with the salinity tolerance of this landrace, an F2 mapping population was developed by crossing Mocho de Espiga Branca with the Australian cultivar Gladius. The population was phenotyped for 19 salinity tolerance subtraits using both non-destructive and destructive techniques. Genotyping was performed using genotyping-by-sequencing (GBS). Genomic regions associated with salinity tolerance were detected on chromosomes 1A, 1D, 4B and 5A for the subtraits of relative and absolute growth rate (RGR, AGR respectively), and on chromosome 2A, 2B, 4D and 5D for Na+, potassium (K+) and chloride (Cl−) accumulation. Candidate genes that encode proteins associated with salinity tolerance were identified within the loci including Na+/H+ antiporters, K+ channels, H+-ATPase, calcineurin B-like proteins (CBLs), CBL-interacting protein kinases (CIPKs), calcium dependent protein kinases (CDPKs) and calcium-transporting ATPase. This study provides a new insight into the genetic control of salinity tolerance in a Na+ accumulating bread wheat to assist with the future development of salt tolerant cultivars.

The fungal family Serendipitaceae encompasses root-associated lineages with endophytic, ericoid, orchid, and ectomycorrhizal lifestyles. Switchgrass is an important bioenergy crop for cellulosic ethanol production owing to high biomass production on marginal soils otherwise unfit for food crop cultivation. The aim of this study was to investigate the host plant responses to Serendipita spp. colonization by characterizing the switchgrass root transcriptome during different stages of symbiosis in vitro. For this, we included a native switchgrass strain, Serendipita bescii, and a related strain, S. vermifera, isolated from Australian orchids. Serendipita colonization progresses from thin hyphae that grow between root cells to, finally, the production of large, bulbous hyphae that fill root cells during the later stages of colonization. We report that switchgrass seems to perceive both fungi prior to physical contact, leading to the activation of chemical and structural defense responses and putative host disease resistance genes. Subsequently, the host defense system appears to be quenched and carbohydrate metabolism adjusted, potentially to accommodate the fungal symbiont. In addition, prior to contact, switchgrass exhibited significant increases in root hair density and root surface area. Furthermore, genes involved in phytohormone metabolism such as gibberellin, jasmonic acid, and salicylic acid were activated during different stages of colonization. Both fungal strains induced plant gene expression in a similar manner, indicating a conserved plant response to members of this fungal order. Understanding plant responsiveness to Serendipita spp. will inform our efforts to integrate them into forages and row crops for optimal plant–microbe functioning, thus facilitating low-input, sustainable agricultural practices. [Formula: see text] Copyright © 2021 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .

There is a growing trend for releasing bioinformatics workflows as command line applications. This is a good thing as workflow management systems add both functionality and reliability, while command line interfaces are convenient for end users. Developing command line software in this way is considerably faster. However, there are many potential pitfalls that developers of bioinformatics tools should avoid. We outline ten simple rules for converting workflow manager pipelines into command line applications, and present working examples that also function as templates using the two most popular workflow managers, Snakemake (github.com/beardymcjohnface/Snaketool) and Nextflow (github.com/beardymcjohnface/Nektool).

Life detection missions to the outer solar system are concentrating on the icy moons of Jupiter and Saturn and their inferred subsurface oceans. Access to evidence of habitability, and possibly even life, is facilitated by the ejection of subsurface material in plumes and outgassing fissures. Orbiting spacecraft can intersect the plume material or detect past sputtered remnants of outgassed products and analyze the contents using instruments such as mass spectrometers. Hydrothermalism has been proposed for the subsurface environments of icy moons, and the organic remains of any associated life would be expected to suffer some degradation through hydrothermalism, radiolysis, or spacecraft flyby impact fragmentation. Hydrothermalism is treated here for the first time in the context of the Europa Clipper mission. To assess the influence of hydrothermalism on the ability of orbiting mass spectrometers to detect degrading signals of life, we have subjected Earth microorganisms to laboratory hydrothermal processing. The processed microorganism samples were then analyzed using gas chromatography-mass spectrometry (GC-MS), and mass spectra were generated. Certain compound classes, such as carbohydrates and proteins, are significantly altered by hydrothermal processing, resulting in small one-ring and two-ring aromatic compounds such as indoles and phenols. However, lipid fragments, such as fatty acids, retain their fidelity, and their provenance is easily recognized as biological in origin. Our data indicate that mass spectrometry measurements in the plumes of icy moons, using instruments such as the MAss Spectrometer for Planetary Exploration (MASPEX) onboard the upcoming Europa Clipper mission, can reveal the presence of life even after significant degradation by hydrothermal processing has taken place.