Forging a path toward a more sustainable laboratory.

Scientific discovery has advanced human society in countless ways, but research requires the expenditure of energy and resources. This Scientific Life article details one laboratory's efforts to reduce the environmental impact of wet-lab research and provides a series of resources to improve lab sustainability.

Needs for a conceptual bridge between biological domestication and early food globalization.

The past 15 y has seen much development in documentation of domestication of plants and animals as gradual traditions spanning millennia. There has also been considerable momentum in understanding the dispersals of major domesticated taxa across continents spanning thousands of miles. The two processes are often considered within different theoretical strains. What is missing from our repertoire of explanations is a conceptual bridge between the protracted process over millennia and the multiregional, globally dispersed nature of domestication. The evidence reviewed in this paper bears upon how we conceptualize domestication as an episode or a process. By bringing together the topics of crop domestication and crop movement, those complex, protracted, and continuous outcomes come more clearly into view.

Uncovering social and environmental factors that increase the burden of climate-sensitive diarrheal infections on children.

Climate-sensitive infectious diseases are an issue of growing concern due to global warming and the related increase in the incidence of extreme weather and climate events. Diarrhea, which is strongly associated with climatic factors, remains among the leading causes of child death globally, disproportionately affecting populations in low- and middle-income countries (LMICs). We use survey data for 51 LMICs between 2000 and 2019 in combination with gridded climate data to estimate the association between precipitation shocks and reported symptoms of diarrheal illness in young children. We account for differences in exposure risk by climate type and explore the modifying role of various social factors. We find that droughts are positively associated with diarrhea in the tropical savanna regions, particularly during the dry season and dry-to-wet and wet-to-dry transition seasons. In the humid subtropical regions, we find that heavy precipitation events are associated with increased risk of diarrhea during the dry season and the transition from dry-to-wet season. Our analysis of effect modifiers highlights certain social vulnerabilities that exacerbate these associations in the two climate zones and present opportunities for public health intervention. For example, we show that stool disposal practices, child feeding practices, and immunizing against the rotavirus modify the association between drought and diarrhea in the tropical savanna regions. In the humid subtropical regions, household's source of water and water disinfection practices modify the association between heavy precipitation and diarrhea. The evidence of effect modification varies depending on the type and duration of the precipitation shock.

Open practices in our science and our courtrooms.

Advocates of transparency in science often point to the benefits of open practices for the scientific process. Here, we focus on a possibly underappreciated effect of standards for transparency: their influence on non-scientific decisions. As a case study, we consider the current state of probabilistic genotyping software in forensics.

The five pillars of computational reproducibility: bioinformatics and beyond.

Computational reproducibility is a simple premise in theory, but is difficult to achieve in practice. Building upon past efforts and proposals to maximize reproducibility and rigor in bioinformatics, we present a framework called the five pillars of reproducible computational research. These include (1) literate programming, (2) code version control and sharing, (3) compute environment control, (4) persistent data sharing and (5) documentation. These practices will ensure that computational research work can be reproduced quickly and easily, long into the future. This guide is designed for bioinformatics data analysts and bioinformaticians in training, but should be relevant to other domains of study.

Critical assessment of variant prioritization methods for rare disease diagnosis within the rare genomes project.

BACKGROUND: A major obstacle faced by families with rare diseases is obtaining a genetic diagnosis. The average "diagnostic odyssey" lasts over five years and causal variants are identified in under 50%, even when capturing variants genome-wide. To aid in the interpretation and prioritization of the vast number of variants detected, computational methods are proliferating. Knowing which tools are most effective remains unclear. To evaluate the performance of computational methods, and to encourage innovation in method development, we designed a Critical Assessment of Genome Interpretation (CAGI) community challenge to place variant prioritization models head-to-head in a real-life clinical diagnostic setting. METHODS: We utilized genome sequencing (GS) data from families sequenced in the Rare Genomes Project (RGP), a direct-to-participant research study on the utility of GS for rare disease diagnosis and gene discovery. Challenge predictors were provided with a dataset of variant calls and phenotype terms from 175 RGP individuals (65 families), including 35 solved training set families with causal variants specified, and 30 unlabeled test set families (14 solved, 16 unsolved). We tasked teams to identify causal variants in as many families as possible. Predictors submitted variant predictions with estimated probability of causal relationship (EPCR) values. Model performance was determined by two metrics, a weighted score based on the rank position of causal variants, and the maximum F-measure, based on precision and recall of causal variants across all EPCR values. RESULTS: Sixteen teams submitted predictions from 52 models, some with manual review incorporated. Top performers recalled causal variants in up to 13 of 14 solved families within the top 5 ranked variants. Newly discovered diagnostic variants were returned to two previously unsolved families following confirmatory RNA sequencing, and two novel disease gene candidates were entered into Matchmaker Exchange. In one example, RNA sequencing demonstrated aberrant splicing due to a deep intronic indel in ASNS, identified in trans with a frameshift variant in an unsolved proband with phenotypes consistent with asparagine synthetase deficiency. CONCLUSIONS: Model methodology and performance was highly variable. Models weighing call quality, allele frequency, predicted deleteriousness, segregation, and phenotype were effective in identifying causal variants, and models open to phenotype expansion and non-coding variants were able to capture more difficult diagnoses and discover new diagnoses. Overall, computational models can significantly aid variant prioritization. For use in diagnostics, detailed review and conservative assessment of prioritized variants against established criteria is needed.

Encouraging voluntary government action via a solar-friendly designation program to promote solar energy in the United States.

SignificanceDue to market and system failures, policies and programs at the local level are needed to accelerate the renewable energy transition. A voluntary environmental program (VEP), such as SolSmart, can encourage local governments to adopt solar-friendly best practices. Unlike previous research, this study uses a national sample, more recent data, and a matched control group for difference-in-differences estimation to quantify the causal impact of a VEP in the public, rather than private, sector. We offer empirical evidence that SolSmart increased installed solar capacity and, with less statistical significance, the number of solar installations. The results inform the design of sustainability-focused VEPs and future research to understand the causal pathways between local governments' voluntary actions and solar market development.

Persistent soil carbon enhanced in Mollisols by well-managed grasslands but not annual grain or dairy forage cropping systems.

Intensive crop production on grassland-derived Mollisols has liberated massive amounts of carbon (C) to the atmosphere. Whether minimizing soil disturbance, diversifying crop rotations, or re-establishing perennial grasslands and integrating livestock can slow or reverse this trend remains highly uncertain. We investigated how these management practices affected soil organic carbon (SOC) accrual and distribution between particulate (POM) and mineral-associated (MAOM) organic matter in a 29-y-old field experiment in the North Central United States and assessed how soil microbial traits were related to these changes. Compared to conventional continuous maize monocropping with annual tillage, systems with reduced tillage, diversified crop rotations with cover crops and legumes, or manure addition did not increase total SOC storage or MAOM-C, whereas perennial pastures managed with rotational grazing accumulated more SOC and MAOM-C (18 to 29% higher) than all annual cropping systems after 29 y of management. These results align with a meta-analysis of data from published studies comparing the efficacy of soil health management practices in annual cropping systems on Mollisols worldwide. Incorporating legumes and manure into annual cropping systems enhanced POM-C, microbial biomass, and microbial C-use efficiency but did not significantly increase microbial necromass accumulation, MAOM-C, or total SOC storage. Diverse, rotationally grazed pasture management has the potential to increase persistent soil C on Mollisols, highlighting the key role of well-managed grasslands in climate-smart agriculture.

Synthesis and Assembly of Virtual Collaborations.

The interplay between academics and society within the environment of the COVID-19 pandemic has impacted on scientists across the world, prompting reevaluation of how virtual toolboxes can be used to support responsible collaborative research practices. We provide awareness of virtual resources and activities that enable scientific discovery using safe and efficient practices.

Establishing Personalized Blood Protein Reference Ranges Using Noninvasive Microsampling and Targeted Proteomics: Implications for Antidoping Strategies.

To prevent doping practices in sports, the World Anti-Doping Agency implemented the Athlete Biological Passport (ABP) program, monitoring biological variables over time to indirectly reveal the effects of doping rather than detect the doping substance or the method itself. In the context of this program, a highly multiplexed mass spectrometry-based proteomics assay for 319 peptides corresponding to 250 proteins was developed, including proteins associated with blood-doping practices. "Baseline" expression profiles of these potential biomarkers in capillary blood (dried blood spots (DBS)) were established using multiple reaction monitoring (MRM). Combining DBS microsampling with highly multiplexed MRM assays is the best-suited technology to enhance the effectiveness of the ABP program, as it represents a cost-effective and robust alternative analytical method with high specificity and selectivity of targets in the attomole range. DBS data were collected from 10 healthy athlete volunteers over a period of 140 days (28 time points per participant). These comprehensive findings provide a personalized targeted blood proteome "fingerprint" showcasing that the targeted proteome is unique to an individual and likely comparable to a DNA fingerprint. The results can serve as a baseline for future studies investigating doping-related perturbations.

Plant-Derived Compounds: A Promising Tool for Dental Caries Prevention.

There is a growing shift from the use of conventional pharmaceutical oral care products to the use of herbal extracts and traditional remedies in dental caries prevention. This is attributed to the potential environmental and health implications of contemporary oral products. This comprehensive review aims at the analysis of plant-derived compounds as preventive modalities in dental caries research. It focuses on data collected from 2019 until recently, trying to emphasize current trends in this topic. The research findings suggest that several plant-derived compounds, either aqueous or ethanolic, exhibit notable antibacterial effects against Streptococcus mutans and other bacteria related to dental caries, with some extracts demonstrating an efficacy comparable to that of chlorhexidine. Furthermore, in vivo studies using plant-derived compounds incorporated in food derivatives, such as lollipops, have shown promising results by significantly reducing Streptococcus mutans in high-risk caries children. In vitro studies on plant-derived compounds have revealed bactericidal and bacteriostatic activity against S. mutans, suggesting their potential use as dental caries preventive agents. Medicinal plants, plant-derived phytochemicals, essential oils, and other food compounds have exhibited promising antimicrobial activity against oral pathogens, either by their anti-adhesion activity, the inhibition of extracellular microbial enzymes, or their direct action on microbial species and acid production. However, further research is needed to assess their antimicrobial activity and to evaluate the cytotoxicity and safety profiles of these plant-derived compounds before their widespread clinical use can be recommended.

Consensus recommendations for improving the cancer clinical trial matching environment.

Enrollment in cancer clinical trials cannot occur without first successfully identifying trials for which patients are a match based on their clinical characteristics. A lack of onsite matching trials has been identified as the single largest barrier preventing patients from participating in clinical trials. The site-agnostic cancer clinical trial matching environment is a mix of public and private tools and infrastructure that are not designed to work together to facilitate trial matching in an efficient manner. To identify policy and infrastructure solutions that could enable more effective and more frequent use of third-party site-agnostic matching, the American Cancer Society Cancer Action Network held a summit to examine challenges and propose consensus recommendations that could address those challenges. At this 2019 summit, stakeholders in this field examined these barriers and challenges and made a number of policy and infrastructure recommendations to improve the ability of this environment to work in a more coordinated and efficient manner.

Provider motivations and barriers to cancer clinical trial screening, referral, and operations: Findings from a survey.

BACKGROUND: Provider and institutional practices have been shown to have a large impact on cancer clinical trial enrollment. Understanding provider perspectives on screening for trial eligibility is necessary to improve enrollment. METHODS: A questionnaire about incentives, barriers, process tools, and infrastructure related to opening trials and referring patients to onsite and offsite trials was administered to diverse stakeholders, including professional societies, advocacy organizations, and industry networks. Descriptive statistics were used to summarize findings. RESULTS: Overall, 693 responses were received, primarily from physicians (42.7%) and nurses (35.6%) employed at hospital health systems (43.7%) and academic centers (36.5%). Approximately half (49.2%) screened all patients for onsite clinical trials with screening typically done by manual chart review (81.9%). The greatest incentive reported for offering trials was providing the best treatment options for patients (67.7%). Contracting and paperwork (48.5%) were the greatest barriers to opening more onsite trials. Offsite referrals were rare. CONCLUSIONS: Screening for trial eligibility is a largely manual and ad hoc process, with screening and referral to offsite trials occurring infrequently. Administrative and infrastructure barriers commonly prevent sites from opening more onsite trials. These findings suggest that automated trial screening tools built into workflows that screen in a site-agnostic manner could result in more frequent trial eligibility screening, especially for offsite trials. With recent momentum, in part in response to the COVID-19 pandemic, to improve clinical trial efficiencies and broaden access and participant diversity, implementing tools to improve screening and referral processes is timely and essential. PLAIN LANGUAGE SUMMARY: There are many factors that contribute to low adult enrollment in cancer clinical trials, but previous research has indicated that provider and institutional barriers are the largest contributors to low cancer clinical trial enrollment. In this survey, we sought to gain insight into cancer clinical trial enrollment practices from the perspective of health care providers such as physicians and nurses. We found that only approximately half of respondents indicated their institution systematically screens their patients for clinical trials and this process is manual and time consuming. Furthermore, we found that providers infrequently search for and refer patients to clinical trials at other sites. Creating better screening methods could improve enrollment in clinical trials.

Is there an association between endometriosis and subsequent breast cancer? A retrospective cohort study from Germany.

PURPOSE: Given the relatively high incidence of both endometriosis and breast cancer, investigating the potential connection between these gynecological diseases is of substantial clinical significance. However, there is no clear consensus in the literature on the extent to which the risk of breast cancer is increased in patients with endometriosis. Therefore, we conducted a large-scale observational study investigating the association between endometriosis and breast cancer risk. METHODS: This study included women aged ≥ 18 years with an initial endometriosis diagnosis from one of 315 office-based gynecologists in Germany between January 2005 and December 2021. Non-endometriosis patients were matched 1:1 to patients with endometriosis based on age, index year, average yearly consultation frequency, and predefined co-diagnoses within 12 months before or on the index date, including obesity and benign breast disorders. The association between endometriosis and the 10-year incidence of breast cancer was studied using Kaplan-Meier curves and log-rank tests. Finally, a univariable Cox regression analysis was conducted to assess the association between endometriosis and breast cancer. RESULTS: Over a follow-up period of up to 10 years, no significant difference was observed between the endometriosis (2.4%) and the matched non-endometriosis group (2.5%) with regard to breast cancer diagnoses. Furthermore, the regression analysis revealed no significant association between endometriosis and subsequent breast cancer. CONCLUSION: In summary, our comprehensive 10-year study involving a substantial sample of women indicates that endometriosis is not significantly associated with an increased risk of subsequent breast cancer.

Evidence for Policies and Practices to Address Global Food Insecurity.

Food insecurity affects an estimated 691-783 million people globally and is disproportionately high in Africa and Asia. It arises from poverty, armed conflict, and climate change, among other demographic and globalization forces. This review summarizes evidence for policies and practices across five elements of the agrifood system framework and identifies gaps that inform an agenda for future research. Under availability, imbalanced agriculture policies protect primarily staple food producers, and there is limited evidence on food security impacts for smallholder and women food producers. Evidence supports the use of cash transfers and food aid for affordability and school feeding for multiple benefits. Food-based dietary guidelines can improve the nutritional quality of dietary patterns, yet they may not reflect the latest evidence or food supplies. Evidence from the newer food environment elements, promotion and sustainability, while relatively minimal, provides insight into achieving long-term impacts. To eliminate hunger, our global community should embrace integrated approaches and bring evidence-based policies and practices to scale.

KDOQI Commentary on the KDIGO 2022 Update to the Clinical Practice Guideline for Diabetes Management in CKD.

The Kidney Disease: Improving Global Outcomes (KDIGO) guideline for diabetes management in chronic kidney disease (CKD) was updated in 2022, just 2 years after the previous update. The need for this rapid update is reflective of the recent and unprecedented positive results of numerous clinical trials aimed at reducing kidney and cardiovascular morbidity and mortality in people with diabetes. The Kidney Disease Outcomes Quality Initiative (KDOQI) work group for diabetes in CKD, convened by the National Kidney Foundation, provides herein a commentary on these changes, particularly the implications for health care in the United States. Changes to the KDIGO guideline mirror the evolution of sodium/glucose cotransporter 2 (SGLT2) inhibitors and glucagon-like peptide 1 receptor agonists from purely antihyperglycemic agents to cardiorenal-metabolic therapeutics, and the lower estimated glomerular filtration rate of≥20mL/min/1.73m2 for SGLT2 inhibitor initiation. New data have also brought the addition of the first-in-class, Federal Drug Administration-approved nonsteroidal mineralocorticoid receptor antagonist finerenone as an agent to reduce cardiorenal end points. While there has been significant progress in innovation, there remain serious challenges to implementation, particularly in the United States where inequities in insurance coverage and high costs limit their use, particularly in vulnerable populations, ultimately widening health care disparities.

Enhancing current guidance for psoriatic arthritis and its comorbidities: recommendations from an expert consensus panel.

OBJECTIVES: Existing guidelines for psoriatic arthritis (PsA) cover many aspects of management. Some gaps remain relating to routine practice application. An expert group aimed to enhance current guidance and develop recommendations for clinical practice that are complementary to existing guidelines. METHODS: A steering committee comprising experienced, research-active clinicians in rheumatology, dermatology and primary care agreed on themes and relevant questions. A targeted literature review of PubMed and Embase following a PICO framework was conducted. At a second meeting, recommendations were drafted and subsequently an extended faculty comprising rheumatologists, dermatologists, primary care clinicians, specialist nurses, allied health professionals, non-clinical academic participants and members of the Brit-PACT patient group, was recruited. Consensus was achieved via an online voting platform when 75% of respondents agreed in the range of 7-9 on a 9-point scale. RESULTS: The guidance comprised 34 statements covering four PsA themes. Diagnosis focused on strategies to identify PsA early and refer appropriately, assessment of diagnostic indicators, use of screening tools and use of imaging. Disease assessment centred on holistic consideration of disease activity, physical functioning and impact from a patient perspective, and on how to implement shared decision-making. For comorbidities, recommendations included specific guidance for high-impact conditions such as depression and obesity. Management statements (which excluded extant guidance on pharmacological therapies) covered multidisciplinary team working, implementation of lifestyle modifications and treat-to-target strategies. Minimising corticosteroid use was recommended where feasible. CONCLUSION: The consensus group have made evidence-based best practice recommendations for the management of PsA to enhance the existing guidelines.

Perspective: use and reuse of NMR-based metabolomics data: what works and what remains challenging.

BACKGROUND: The National Cancer Institute issued a Request for Information (RFI; NOT-CA-23-007) in October 2022, soliciting input on using and reusing metabolomics data. This RFI aimed to gather input on best practices for metabolomics data storage, management, and use/reuse. AIM OF REVIEW: The nuclear magnetic resonance (NMR) Interest Group within the Metabolomics Association of North America (MANA) prepared a set of recommendations regarding the deposition, archiving, use, and reuse of NMR-based and, to a lesser extent, mass spectrometry (MS)-based metabolomics datasets. These recommendations were built on the collective experiences of metabolomics researchers within MANA who are generating, handling, and analyzing diverse metabolomics datasets spanning experimental (sample handling and preparation, NMR/MS metabolomics data acquisition, processing, and spectral analyses) to computational (automation of spectral processing, univariate and multivariate statistical analysis, metabolite prediction and identification, multi-omics data integration, etc.) studies. KEY SCIENTIFIC CONCEPTS OF REVIEW: We provide a synopsis of our collective view regarding the use and reuse of metabolomics data and articulate several recommendations regarding best practices, which are aimed at encouraging researchers to strengthen efforts toward maximizing the utility of metabolomics data, multi-omics data integration, and enhancing the overall scientific impact of metabolomics studies.

Transparency in Cognitive Training Meta-analyses: A Meta-review.

Meta-analyses often present flexibility regarding their inclusion criteria, outcomes of interest, statistical analyses, and assessments of the primary studies. For this reason, it is necessary to transparently report all the information that could impact the results. In this meta-review, we aimed to assess the transparency of meta-analyses that examined the benefits of cognitive training, given the ongoing controversy that exists in this field. Ninety-seven meta-analytic reviews were included, which examined a wide range of populations with different clinical conditions and ages. Regarding the reporting, information about the search of the studies, screening procedure, or data collection was detailed by most reviews. However, authors usually failed to report other aspects such as the specific meta-analytic parameters, the formula used to compute the effect sizes, or the data from primary studies that were used to compute the effect sizes. Although some of these practices have improved over the years, others remained the same. Moreover, examining the eligibility criteria of the reviews revealed a great heterogeneity in aspects such as the training duration, age cut-offs, or study designs that were considered. Preregistered meta-analyses often specified poorly how they would deal with the multiplicity of data or assess publication bias in their protocols, and some contained non-disclosed deviations in their eligibility criteria or outcomes of interests. The findings shown here, although they do not question the benefits of cognitive training, illustrate important aspects that future reviews must consider.

Net greenhouse gas balance in U.S. croplands: How can soils be part of the climate solution?

Agricultural soils play a dual role in regulating the Earth's climate by releasing or sequestering carbon dioxide (CO2 ) in soil organic carbon (SOC) and emitting non-CO2 greenhouse gases (GHGs) such as nitrous oxide (N2 O) and methane (CH4 ). To understand how agricultural soils can play a role in climate solutions requires a comprehensive assessment of net soil GHG balance (i.e., sum of SOC-sequestered CO2 and non-CO2 GHG emissions) and the underlying controls. Herein, we used a model-data integration approach to understand and quantify how natural and anthropogenic factors have affected the magnitude and spatiotemporal variations of the net soil GHG balance in U.S. croplands during 1960-2018. Specifically, we used the dynamic land ecosystem model for regional simulations and used field observations of SOC sequestration rates and N2 O and CH4 emissions to calibrate, validate, and corroborate model simulations. Results show that U.S. agricultural soils sequestered 13.2 ± 1.16 $$ 13.2\pm 1.16 $$ Tg CO2 -C year-1 in SOC (at a depth of 3.5 m) during 1960-2018 and emitted 0.39 ± 0.02 $$ 0.39\pm 0.02 $$ Tg N2 O-N year-1 and 0.21 ± 0.01 $$ 0.21\pm 0.01 $$ Tg CH4 -C year-1 , respectively. Based on the GWP100 metric (global warming potential on a 100-year time horizon), the estimated national net GHG emission rate from agricultural soils was 122.3 ± 11.46 $$ 122.3\pm 11.46 $$ Tg CO2 -eq year-1 , with the largest contribution from N2 O emissions. The sequestered SOC offset ~28% of the climate-warming effects resulting from non-CO2 GHG emissions, and this offsetting effect increased over time. Increased nitrogen fertilizer use was the dominant factor contributing to the increase in net GHG emissions during 1960-2018, explaining ~47% of total changes. In contrast, reduced cropland area, the adoption of agricultural conservation practices (e.g., reduced tillage), and rising atmospheric CO2 levels attenuated net GHG emissions from U.S. croplands. Improving management practices to mitigate N2 O emissions represents the biggest opportunity for achieving net-zero emissions in U.S. croplands. Our study highlights the importance of concurrently quantifying SOC-sequestered CO2 and non-CO2 GHG emissions for developing effective agricultural climate change mitigation measures.