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Identifying genetic variants responsible for phenotypic variation under selective pressure has the potential to enable productive gains in natural resource conservation and management. Despite this potential, identifying adaptive candidate loci is not trivial, and linking genotype to phenotype is a major challenge in contemporary genetics. Many of the population genetic approaches commonly used to identify adaptive candidates will simultaneously detect false positives, particularly in nonmodel species, where experimental evidence is seldom provided for putative roles of the adaptive candidates identified by outlier approaches. In this study, we use outcomes from population genetics, phenotype association, and gene expression analyses as multiple lines of evidence to validate candidate genes. Using lodgepole and jack pine as our nonmodel study species, we analyzed 17 adaptive candidate loci together with 78 putatively neutral loci at 58 locations across Canada (N > 800) to determine whether relationships could be established between these candidate loci and phenotype related to mountain pine beetle susceptibility. We identified two candidate loci that were significant across all population genetic tests, and demonstrated significant changes in transcript abundance in trees subjected to wounding or inoculation with the mountain pine beetle fungal associate Grosmannia clavigera. Both candidates are involved in central physiological processes that are likely to be invoked in a trees response to stress. One of these two candidate loci showed a significant association with mountain pine beetle attack status in lodgepole pine. The spatial distribution of the attack‐associated allele further coincides with other indicators of susceptibility in lodgepole pine. These analyses, in which population genetics was combined with laboratory and field experimental validation approaches, represent first steps toward linking genetic variation to the phenotype of mountain pine beetle susceptibility in lodgepole and jack pine, and provide a roadmap for more comprehensive analyses.

• Renewed interests in the development of bioenergy, biochemicals, and biomaterials have elicited new strategies for engineering the lignin of biomass feedstock plants. This study shows, for the first time, that 3,4-dihydroxybenzoate (DHB) is compatible with the radical coupling reactions that assemble polymeric lignin in plants. • We introduced a bacterial 3-dehydroshikimate dehydratase into hybrid poplar (Populus alba × grandidentata) to divert carbon flux away from the shikimate pathway, which lies upstream of lignin biosynthesis. • Transgenic poplar wood had up to 33% less lignin with p-hydroxyphenyl units comprising as much as 10% of the lignin. Mild alkaline hydrolysis of transgenic wood released fewer ester-linked p-hydroxybenzoate groups than control trees, and revealed the novel incorporation of cell-wall-bound DHB, as well as glycosides of 3,4-dihydroxybenzoic acid (DHBA). Two-dimensional nuclear magnetic resonance (2D-NMR) analysis uncovered DHBA-derived benzodioxane structures suggesting that DHB moieties were integrated into the lignin polymer backbone. In addition, up to 40% more glucose was released from transgenic wood following ionic liquid pretreatment and enzymatic hydrolysis. • This work highlights the potential of diverting carbon flux from the shikimate pathway for lignin engineering and describes a new type of ‘zip-lignin’ derived from the incorporation of DHB into poplar lignin.

Genetic engineering of trees to improve productivity, wood quality, and resistance to biotic and abiotic stresses has been the primary goal of the forest biotechnology community for decades. We review the extensive progress in these areas and their current status with respect to commercial applications. Examples include novel methods for lignin modification, solutions for long-standing problems related to pathogen resistance, modifications to flowering onset and fertility, and drought and freeze tolerance. There have been numerous successful greenhouse and field demonstrations of genetically engineered trees, but commercial application has been severely limited by social and technical considerations. Key social factors are costly and uncertain regulatory hurdles and sweeping market barriers in the form of forest certification systems that disallow genetically modified trees. These factors limit and, in many cases, preclude field research and commercial adoption. Another challenge is the high cost and uncertainty in transformation efficiency that is needed to apply genetic engineering and gene editing methods to most species and genotypes of commercial importance. Recent advances in developmental gene-based transformation systems and gene editing, if combined with regulatory and certification system reform, could provide the foundation for genetic engineering to become a significant tool for coping with the increasing environmental and biological stresses on planted and wild forests.

Advances in detection of genetic material from species in aquatic ecosystems, including environmental DNA (eDNA), have improved species monitoring and management. eDNA from target species can readily move in streams and rivers and the goal is to measure it, and with that infer where and how abundant species are, adding great value to delimiting species invasions, monitoring and protecting rare species, and estimating biodiversity. To date, we lack an integrated framework that identifies environmental factors that control eDNA movement in realistic, complex, and heterogeneous flowing waters. To this end, using an empirical approach and a simple conceptual model, we propose a framework of how eDNA is transported, retained, and resuspended in stream systems. Such an understanding of eDNA dispersal in streams will be essential for designing optimized sampling protocols and subsequently estimating biomass or organismal abundance. We also discuss guiding principles for more effective use of eDNA methods, highlighting the necessity of understanding these parameters for use in future predictive modeling of eDNA transport.

Tulving characterized semantic memory as a vast repository of meaning that underlies language and many other cognitive processes. This perspective on lexical and conceptual knowledge galvanized a new era of research undertaken by numerous fields, each with their own idiosyncratic methods and terminology. For example, “concept” has different meanings in philosophy, linguistics, and psychology. As such, many fundamental constructs used to delineate semantic theories remain underspecified and/or opaque. Weak construct specificity is among the leading causes of the replication crisis now facing psychology and related fields. Term ambiguity hinders cross-disciplinary communication, falsifiability, and incremental theory-building. Numerous cognitive subdisciplines (e.g., vision, affective neuroscience) have recently addressed these limitations via the development of consensus-based guidelines and definitions. The project to follow represents our effort to produce a multidisciplinary semantic glossary consisting of succinct definitions, background, principled dissenting views, ratings of agreement, and subjective confidence for 17 target constructs (e.g., abstractness, abstraction, concreteness, concept, embodied cognition, event semantics, lexical-semantic, modality, representation, semantic control, semantic feature, simulation, semantic distance, semantic dimension) . We discuss potential benefits and pitfalls (e.g., implicit bias, prescriptiveness) of these efforts to specify a common nomenclature that other researchers might index in specifying their own theoretical perspectives (e.g., They said X, but I mean Y).

BackgroundCurrent treatment options for knee osteoarthritis have limited effectiveness and potentially adverse side effects. Massage may offer a safe and effective complement to the management of knee osteoarthritis.ObjectiveExamine effects of whole-body massage on knee osteoarthritis, compared to active control (light-touch) and usual care.DesignMultisite RCT assessing the efficacy of massage compared to light-touch and usual care in adults with knee osteoarthritis, with assessments at baseline and weeks 8, 16, 24, 36, and 52. Subjects in massage or light-touch groups received eight weekly treatments, then were randomized to biweekly intervention or usual care to week 52. The original usual care group continued to week 24. Analysis was performed on an intention-to-treat basis.ParticipantsFive hundred fifty-one screened for eligibility, 222 adults with knee osteoarthritis enrolled, 200 completed 8-week assessments, and 175 completed 52-week assessments.InterventionSixty minutes of protocolized full-body massage or light-touch.Main MeasuresPrimary: Western Ontario and McMaster Universities Arthritis Index. Secondary: visual analog pain scale, PROMIS Pain Interference, knee range of motion, and timed 50-ft walk.Key ResultsAt 8 weeks, massage significantly improved WOMAC Global scores compared to light-touch (− 8.16, 95% CI = − 13.50 to − 2.81) and usual care (− 9.55, 95% CI = − 14.66 to − 4.45). Additionally, massage improved pain, stiffness, and physical function WOMAC subscale scores compared to light-touch (p < 0.001; p = 0.04; p = 0.02, respectively) and usual care (p < 0.001; p = 0.002; p = 0.002; respectively). At 52 weeks, the omnibus test of any group difference in the change in WOMAC Global from baseline to 52 weeks was not significant (p = 0.707, df = 3), indicating no significant difference in change across groups. Adverse events were minimal.ConclusionsEfficacy of symptom relief and safety of weekly massage make it an attractive short-term treatment option for knee osteoarthritis. Longer-term biweekly dose maintained improvement, but did not provide additional benefit beyond usual care post 8-week treatment.Trial Registrationclinicaltrials.gov NCT01537484

Translating a set of disease regions into insight about pathogenic mechanisms requires not only the ability to identify the key disease genes within them, but also the biological relationships among those key genes. Here we describe a statistical method, Gene Relationships Among Implicated Loci (GRAIL), that takes a list of disease regions and automatically assesses the degree of relatedness of implicated genes using 250,000 PubMed abstracts. We first evaluated GRAIL by assessing its ability to identify subsets of highly related genes in common pathways from validated lipid and height SNP associations from recent genome-wide studies. We then tested GRAIL, by assessing its ability to separate true disease regions from many false positive disease regions in two separate practical applications in human genetics. First, we took 74 nominally associated Crohn's disease SNPs and applied GRAIL to identify a subset of 13 SNPs with highly related genes. Of these, ten convincingly validated in follow-up genotyping; genotyping results for the remaining three were inconclusive. Next, we applied GRAIL to 165 rare deletion events seen in schizophrenia cases (less than one-third of which are contributing to disease risk). We demonstrate that GRAIL is able to identify a subset of 16 deletions containing highly related genes; many of these genes are expressed in the central nervous system and play a role in neuronal synapses. GRAIL offers a statistically robust approach to identifying functionally related genes from across multiple disease regions--that likely represent key disease pathways. An online version of this method is available for public use (http://www.broad.mit.edu/mpg/grail/).

The COVID-19 pandemic has disproportionately affected people with diabetes, who are at increased risk of severe COVID-19.* Increases in the number of type 1 diabetes diagnoses (1,2) and increased frequency and severity of diabetic ketoacidosis (DKA) at the time of diabetes diagnosis (3) have been reported in European pediatric populations during the COVID-19 pandemic. In adults, diabetes might be a long-term consequence of SARS-CoV-2 infection (4-7). To evaluate the risk for any new diabetes diagnosis (type 1, type 2, or other diabetes) >30 days after acute infection with SARS-CoV-2 (the virus that causes COVID-19), CDC estimated diabetes incidence among patients aged <18 years (patients) with diagnosed COVID-19 from retrospective cohorts constructed using IQVIA health care claims data from March 1, 2020, through February 26, 2021, and compared it with incidence among patients matched by age and sex 1) who did not receive a COVID-19 diagnosis during the pandemic, or 2) who received a prepandemic non-COVID-19 acute respiratory infection (ARI) diagnosis. Analyses were replicated using a second data source (HealthVerity; March 1, 2020-June 28, 2021) that included patients who had any health care encounter possibly related to COVID-19. Among these patients, diabetes incidence was significantly higher among those with COVID-19 than among those 1) without COVID-19 in both databases (IQVIA: hazard ratio [HR] = 2.66, 95% CI = 1.98-3.56; HealthVerity: HR = 1.31, 95% CI = 1.20-1.44) and 2) with non-COVID-19 ARI in the prepandemic period (IQVIA, HR = 2.16, 95% CI = 1.64-2.86). The observed increased risk for diabetes among persons aged <18 years who had COVID-19 highlights the importance of COVID-19 prevention strategies, including vaccination, for all eligible persons in this age group, in addition to chronic disease prevention and management. The mechanism of how SARS-CoV-2 might lead to incident diabetes is likely complex and could differ by type 1 and type 2 diabetes. Monitoring for long-term consequences, including signs of new diabetes, following SARS-CoV-2 infection is important in this age group.

Although knowledge about the efficacy of behavioral interventions for children with ASD is increasing, studies of effectiveness and transportability to community settings are needed. The current study conducted an effectiveness trial to compare distance learning vs. live instruction for training community-based therapists to implement the Early Start Denver Model. Findings revealed: (a) distance learning and live instruction were equally effective for teaching therapists to both implement the model and to train parents; (b) didactic workshops and team supervision were required to improve therapists’ skill use; (c) significant child gains occurred over time and across teaching modalities; and (d) parents implemented the model more skillfully after coaching. Implications are discussed in relation to the economic and clinical utility of distance learning.