Effects of amphibian genetic diversity on ecological communities.

The amount of genetic diversity within a population can affect ecological processes at population, community, and ecosystem levels. However, the magnitude, consistency, and scope of these effects are largely unknown. To investigate these issues, we conducted two experiments manipulating the amount of genetic diversity and environmental factors in larval amphibians. The first experiment manipulated wood frog genetic diversity, the presence or absence of caged predators, and competition from leopard frogs to test whether these factors affected survival, growth, and morphology of wood frogs and leopard frogs. The second experiment manipulated wood frog genetic diversity, the presence or absence of uncaged predators, and resource abundance to test whether these factors affected wood frog traits (survival, morphology, growth, development, and behavior) and other components of the ecological community (zooplankton abundance, phytoplankton, periphyton, and bacterial community structure). Genetic diversity did not affect wood frog survival, growth, and development in either experiment. However, genetic diversity did affect the mean morphology of wood frog tadpoles in the first experiment and the abundance and distribution of zooplankton in the second experiment. It did not affect phytoplankton abundance, periphyton abundance, or bacterial community structure. While effect sizes (Cohen's d) of genetic diversity were approximately half those of environment treatments, the greatest effect sizes were for interaction effects between genetic diversity and environment. Our results indicate that genetic diversity can have a large effect on ecological processes, but the direction of those effects is highly dependent upon environmental conditions, and not easily predicted from simple measures of traits.

Predicted mechanistic impacts of human protein missense variants.

Genome sequencing efforts have led to the discovery of tens of millions of protein missense variants found in the human population with the majority of these having no annotated role and some likely contributing to trait variation and disease. Sequence-based artificial intelligence approaches have become highly accurate at predicting variants that are detrimental to the function of proteins but they do not inform on mechanisms of disruption. Here we combined sequence and structure-based methods to perform proteome-wide prediction of deleterious variants with information on their impact on protein stability, protein-protein interactions and small-molecule binding pockets. AlphaFold2 structures were used to predict approximately 100,000 small-molecule binding pockets and stability changes for over 200 million variants. To inform on protein-protein interfaces we used AlphaFold2 to predict structures for nearly 500,000 protein complexes. We illustrate the value of mechanism-aware variant effect predictions to study the relation between protein stability and abundance and the structural properties of interfaces underlying trans protein quantitative trait loci (pQTLs). We characterised the distribution of mechanistic impacts of protein variants found in patients and experimentally studied example disease linked variants in FGFR1.

The Frequency of Neuropsychiatric Sequelae After Traumatic Brain Injury in the Global South: A systematic review and meta-analysis.

This study aimed to assess the prevalence of neuropsychiatric sequelae following traumatic brain injury (TBI) among the Western Asian, South Asian and African regions of the global south. All studies on psychiatric disturbances or cognitive impairment following TBI conducted (until August 2021) in the 83 countries that constitute the aforementioned regions were reviewed; 6 databases were selected for the literature search. After evaluating the articles using the Joanna Briggs Institute guidelines, the random effects model was used to estimate the prevalence of depression, anxiety, post-traumatic stress disorder (PTSD), TBI-related sleep disturbance (TBI-SD), obsessive-compulsive disorder (OCD) and cognitive impairment. Of 56 non-duplicated studies identified in the initial search, 27 were eligible for systematic review and 23 for meta-analysis. The pooled prevalence of depression in 1,882 samples was 35.35%, that of anxiety in 1,211 samples was 28.64%, that of PTSD in 426 samples was 19.94%, that of OCD in 313 samples was 19.48%, that of TBI-SD in 562 samples was 26.67% and that of cognitive impairment in 941 samples was 49.10%. To date, this is the first critical review to examine the spectrum of post-TBI neuropsychiatric sequelae in the specified regions. Although existing studies lack homogeneous data due to variability in the diagnostic tools and outcome measures utilised, the reported prevalence rates are significant and comparable to statistics from the global north.

Nonclassical Crystallization Processes of Single-Crystalline Two-Dimensional Covalent Organic Frameworks.

Controlling the two-dimensional polymerization processes of two-dimensional covalent organic frameworks (2D COFs) is essential to fully realizing their distinct properties. Although most 2D COFs have been isolated as polycrystalline aggregates with only nanometer-scale crystalline domains, we have identified rapid, solvothermal conditions that provide micrometer-scale and larger single-crystal 2D polymers for a few 2D COFs. Yet it remains unclear why certain conditions produce far larger 2D polymers than others, which hinders generalizing these findings. The guiding principles for controlled two-dimensional polymerization in solution remain unclear. Here, we study the crystallization processes of both single-crystalline and polycrystalline 2D COFs using ultrasmall-angle X-ray scattering (USAXS) for the first time, through which we characterized COF formation conditions with scattering data collected every few seconds. In situ USAXS experiments revealed distinct growth mechanisms between single-crystalline and polycrystalline COFs and suggested a nonclassical particle fusion-based growth model for single-crystalline COFs that results in faceted, hexagonal particles. These findings were corroborated by in situ wide-angle X-ray scattering (WAXS) experiments and scanning electron microscopy (SEM). In contrast, polymerizations that provide polycrystalline COFs evolve as spherical aggregates that do not fuse in the same way. These insights into how micrometer-sized, crystalline 2D polymers are formed in solution point a way forward to establishing a robust connection between the 2D polymer structure and designed properties by controlling their polymerization processes.

Effects of the nematode Litylenchus crenatae subsp. mccannii and beech leaf disease on leaf fungal and bacterial communities on Fagus grandifolia (American beech).

Beech leaf disease (BLD) is a newly emerging disease in North America that affects American beech (Fagus grandifolia). It is increasingly recognized that BLD is caused by a subspecies of the anguinid nematode Litylenchus crenatae subsp. mccannii (hereafter L. crenatae), which is likely native to East Asia. How nematode infestation of leaves affects the leaf microbiome and whether changes in the microbiome could contribute to BLD symptoms remain uncertain. In this study, we examined bacterial and fungal communities associated with the leaves of F. grandifolia across nine sites in Ohio and Pennsylvania that were either symptomatic or asymptomatic for BLD and used qPCR to measure relative nematode infestation levels. We found significantly higher levels of infestation at sites visibly symptomatic for BLD. Low levels of nematode infestation were also observed at asymptomatic sites, which suggests that nematodes can be present without visible symptoms evident. Bacterial and fungal communities were significantly affected by sampling site and symptomology, but only fungal communities were affected by nematode presence alone. We found many significant indicators of both bacteria and fungi related to symptoms of BLD, with taxa generally occurring in both asymptomatic and symptomatic leaves, suggesting that microbes are not responsible for BLD but could act as opportunistic pathogens. Of particular interest was the fungal genus Erysiphe, which is common in the Fagaceae and is reported to overwinter in buds-a strategy consistent with L. crenatae. The specific role microbes play in opportunistic infection of leaves affected by L. crenatae will require additional study. IMPORTANCE: Beech leaf disease (BLD) is an emerging threat to American beech (Fagus grandifolia) and has spread quickly throughout the northeastern United States and into southern Canada. This disease leads to disfigurement of leaves and is marked by characteristic dark, interveinal banding, followed by leaf curling and drop in more advanced stages. BLD tends to especially affect understory leaves, which can lead to substantial thinning of the forest understory where F. grandifolia is a dominant tree species. Understanding the cause of BLD is necessary to employ management strategies that protect F. grandifolia and the forests where it is a foundation tree species. Current research has confirmed that the foliar nematode Litylenchus crenatae subsp. mccannii is required for BLD, but whether other organisms are involved is currently unknown. Here, we present a study that investigated leaf-associated fungi and bacteria of F. grandifolia to understand more about how microorganisms may contribute to BLD.

ProtVar: mapping and contextualizing human missense variation.

Genomic variation can impact normal biological function in complex ways and so understanding variant effects requires a broad range of data to be coherently assimilated. Whilst the volume of human variant data and relevant annotations has increased, the corresponding increase in the breadth of participating fields, standards and versioning mean that moving between genomic, coding, protein and structure positions is increasingly complex. In turn this makes investigating variants in diverse formats and assimilating annotations from different resources challenging. ProtVar addresses these issues to facilitate the contextualization and interpretation of human missense variation with unparalleled flexibility and ease of accessibility for use by the broadest range of researchers. By precalculating all possible variants in the human proteome it offers near instantaneous mapping between all relevant data types. It also combines data and analyses from a plethora of resources to bring together genomic, protein sequence and function annotations as well as structural insights and predictions to better understand the likely effect of missense variation in humans. It is offered as an intuitive web server https://www.ebi.ac.uk/protvar where data can be explored and downloaded, and can be accessed programmatically via an API.

Neurophysiological and imaging biomarkers of lower motor neuron dysfunction in motor neuron diseases/amyotrophic lateral sclerosis: IFCN handbook chapter.

This chapter discusses comprehensive neurophysiological biomarkers utilised in motor neuron disease (MND) and, in particular, its commonest form, amyotrophic lateral sclerosis (ALS). These encompass the conventional techniques including nerve conduction studies (NCS), needle and high-density surface electromyography (EMG) and H-reflex studies as well as novel techniques. In the last two decades, new methods of assessing the loss of motor units in a muscle have been developed, that are more convenient than earlier methods of motor unit number estimation (MUNE),and may use either electrical stimulation (e.g. MScanFit MUNE) or voluntary activation (MUNIX). Electrical impedance myography (EIM) is another novel approach for the evaluation that relies upon the application and measurement of high-frequency, low-intensity electrical current. Nerve excitability techniques (NET) also provide insights into the function of an axon and reflect the changes in resting membrane potential, ion channel dysfunction and the structural integrity of the axon and myelin sheath. Furthermore, imaging ultrasound techniques as well as magnetic resonance imaging are capable of detecting the constituents of morphological changes in the nerve and muscle. The chapter provides a critical description of the ability of each technique to provide neurophysiological insight into the complex pathophysiology of MND/ALS. However, it is important to recognise the strengths and limitations of each approach in order to clarify utility. These neurophysiological biomarkers have demonstrated reliability, specificity and provide additional information to validate and assess lower motor neuron dysfunction. Their use has expanded the knowledge about MND/ALS and enhanced our understanding of the relationship between motor units, axons, reflexes and other neural circuits in relation to clinical features of patients with MND/ALS at different stages of the disease. Taken together, the ultimate goal is to aid early diagnosis, distinguish potential disease mimics, monitor and stage disease progression, quantify response to treatment and develop potential therapeutic interventions.

Six-Month Pilot Testing of a Digital Health Tool to Support Effective Self-Care in People With Heart Failure: Mixed Methods Study.

BACKGROUND: Digital tools may support people to self-manage their heart failure (HF). Having previously outlined the human-centered design development of a digital tool to support self-care of HF, the next step was to pilot the tool over a period of time to establish people's acceptance of it in practice. OBJECTIVE: This study aims to conduct an observational pilot study to examine the usability, adherence, and feasibility of a digital health tool for HF within the Irish health care system. METHODS: A total of 19 participants with HF were provided with a digital tool comprising a mobile app and the Fitbit Charge 4 and Aria Air smart scales for a period of 6 months. Changes to their self-care were assessed before and after the study with the 9-item European HF Self-care Behavior Scale (EHFScBS) and the Minnesota Living with HF Questionnaire (MLwHFQ) using a Wilcoxon signed rank test. After the study, 3 usability questionnaires were implemented and descriptively analyzed: the System Usability Scale (SUS), Wearable Technology Motivation Scale (WTMS), and Comfort Rating Scale (CRS). Participants also undertook a semistructured interview regarding their experiences with the digital tool. Interviews were analyzed deductively using the Theoretical Domains Framework. RESULTS: Participants wore their devices for an average of 86.2% of the days in the 6-month testing period ranging from 40.6% to 98%. Although improvements in the EHFScBS and MLwHFQ were seen, these changes were not significant (P=.10 and P=.70, respectively, where P>.03, after a Bonferroni correction). SUS results suggest that the usability of this system was not acceptable with a median score of 58.8 (IQR 55.0-60.0; range 45.0-67.5). Participants demonstrated a strong motivation to use the system according to the WTMS (median 6.0, IQR 5.0-7.0; range 1.0-7.0), whereas the Fitbit was considered very comfortable as demonstrated by the low CRS results (median 0.0, IQR 0.0-0.0; range 0.0-2.0). According to participant interviews, the digital tool supported self-management through increased knowledge, improved awareness, decision-making, and confidence in their own data, and improving their social support through a feeling of comfort in being watched. CONCLUSIONS: The digital health tool demonstrated high levels of adherence and acceptance among participants. Although the SUS results suggest low usability, this may be explained by participants uncertainty that they were using it fully, rather than it being unusable, especially given the experiences documented in their interviews. The digital tool targeted key self-management behaviors and feelings of social support. However, a number of changes to the tool, and the health service, are required before it can be implemented at scale. A full-scale feasibility trial conducted at a wider level is required to fully determine its potential effectiveness and wider implementation needs.

Machine learning models help differentiate between causes of recurrent spontaneous vertigo.

BACKGROUND: Vestibular migraine (VM) and Menière's disease (MD) are two common causes of recurrent spontaneous vertigo. Using history, video-nystagmography and audiovestibular tests, we developed machine learning models to separate these two disorders. METHODS: We recruited patients with VM or MD from a neurology outpatient facility. One hundred features from six "feature subsets": history, acute video-nystagmography and four laboratory tests (video head impulse test, vestibular-evoked myogenic potentials, caloric testing and audiogram) were used. We applied ten machine learning algorithms to develop classification models. Modelling was performed using three "tiers" of data availability to simulate three clinical settings. "Tier 1" used all available data to simulate the neuro-otology clinic, "Tier 2" used only history, audiogram and caloric test data, representing the general neurology clinic, and "Tier 3" used history alone as occurs in primary care. Model performance was evaluated using tenfold cross-validation. RESULTS: Data from 160 patients with VM and 114 with MD were used for model development. All models effectively separated the two disorders for all three tiers, with accuracies of 85.77-97.81%. The best performing algorithms (AdaBoost and Random Forest) yielded accuracies of 97.81% (95% CI 95.24-99.60), 94.53% (91.09-99.52%) and 92.34% (92.28-96.76%) for tiers 1, 2 and 3. The best feature subset combination was history, acute video-nystagmography, video head impulse test and caloric testing, and the best single feature subset was history. CONCLUSIONS: Machine learning models can accurately differentiate between VM and MD and are promising tools to assist diagnosis by medical practitioners with diverse levels of expertise and resources.

Assessment of the antigenic evolution of a clade 6B.1 human H1N1pdm influenza virus revealed differences between ferret and human convalescent sera.

BACKGROUND: Influenza viruses continually acquire mutations in the antigenic epitopes of their major viral antigen, the surface glycoprotein haemagglutinin (HA), allowing evasion from immunity in humans induced upon prior influenza virus infections or vaccinations. Consequently, the influenza strains used for vaccine production must be updated frequently. METHODS: To better understand the antigenic evolution of influenza viruses, we introduced random mutations into the HA head region (where the immunodominant epitopes are located) of a pandemic H1N1 (H1N1pdm) virus from 2015 and incubated it with various human sera collected in 2015-2016. Mutants not neutralized by the human sera were sequenced and further characterized for their haemagglutination inhibition (HI) titers with human sera and with ferret sera raised to H1N1pdm viruses from 2009 to 2015. FINDINGS: The largest antigenic changes were conferred by mutations at HA amino acid position 187; interestingly, these antigenic changes were recognized by human, but not by ferret serum. H1N1pdm viruses with amino acid changes at position 187 were very rare until the end of 2018, but have become more frequent since; in fact, the D187A amino acid change is one of the defining changes of clade 6B.1A.5a.1 viruses, which emerged in 2019. INTERPRETATION: Our findings indicate that amino acid substitutions in H1N1pdm epitopes may be recognized by human sera, but not by homologous ferret sera. FUNDING: This project was supported by funding from the NIAID-funded Center for Research on Influenza Pathogenesis (CRIP, HHSN272201400008C).

A foundational atlas of autism protein interactions reveals molecular convergence.

Translating high-confidence (hc) autism spectrum disorder (ASD) genes into viable treatment targets remains elusive. We constructed a foundational protein-protein interaction (PPI) network in HEK293T cells involving 100 hcASD risk genes, revealing over 1,800 PPIs (87% novel). Interactors, expressed in the human brain and enriched for ASD but not schizophrenia genetic risk, converged on protein complexes involved in neurogenesis, tubulin biology, transcriptional regulation, and chromatin modification. A PPI map of 54 patient-derived missense variants identified differential physical interactions, and we leveraged AlphaFold-Multimer predictions to prioritize direct PPIs and specific variants for interrogation in Xenopus tropicalis and human forebrain organoids. A mutation in the transcription factor FOXP1 led to reconfiguration of DNA binding sites and altered development of deep cortical layer neurons in forebrain organoids. This work offers new insights into molecular mechanisms underlying ASD and describes a powerful platform to develop and test therapeutic strategies for many genetically-defined conditions.

2D Covalent Organic Framework Membranes for Liquid-Phase Molecular Separations: State of the Field, Common Pitfalls, and Future Opportunities.

2D covalent organic frameworks (2D COFs) are attractive candidates for next-generation membranes due to their robust linkages and uniform, tunable pores. Many publications have claimed to achieve selective molecular transport through COF pores, but reported performance metrics for similar networks vary dramatically, and in several cases the reported experiments are inadequate to support such conclusions. These issues require a reevaluation of the literature. Published examples of 2D COF membranes for liquid-phase separations can be broadly divided into two categories, each with common performance characteristics: polycrystalline COF films (most >1 µm thick) and weakly crystalline or amorphous films (most <500 nm thick). Neither category has demonstrated consistent relationships between the designed COF pore structure and separation performance, suggesting that these imperfect materials do not sieve molecules through uniform pores. In this perspective, rigorous practices for evaluating COF membrane structures and separation performance are described, which will facilitate their development toward molecularly precise membranes capable of performing previously unrealized chemical separations. In the absence of this more rigorous standard of proof, reports of COF-based membranes should be treated with skepticism. As methods to control 2D polymerization improve, precise 2D polymer membranes may exhibit exquisite and energy efficient performance relevant for contemporary separation challenges.

Interannual variation in spring weather conditions as a driver of spring wildflower coverage: a 15-year perspective from an old-growth temperate forest.

Spring ephemerals are wildflowers found in temperate deciduous forests that typically display aboveground shoots for a period of 2 months or less. Early spring, before the canopy leaves out, marks the beginning of the aboveground growth period where ephemerals acquire nutrients and resources via aboveground tissues. Several studies have shown that spring ephemeral reproduction is affected by spring temperature, but few have looked at how weather conditions of the current and previous seasons, including precipitation and temperature, influence aboveground growth. Here, we examine the response of a spring ephemeral community in a temperate hardwood forest to weather conditions during their current and previous growing seasons. For 15 years we estimated percent cover of each species within our community. We highlighted five dominant spring ephemerals within this community: wild leek (Allium tricoccum), cutleaf toothwort (Cardamine concatenata), spring beauty (Claytonia virginica), squirrel corn (Dicentra canadensis) and trout lily (Erythronium americanum). We compared changes in cover on both a community and species level from 1 year to the next with average precipitation and temperature of the year of measurement as well as the year prior. We found precipitation and temperature influence a change in cover at the community and species level, but the strength of that influence varies by species. There were few significant correlations between plant cover in the current year and temperature and precipitation in the 30 days preceding measurement. However, we found significant correlations between plant cover and precipitation and temperature during the previous spring; precipitation and cover change were positively correlated, whereas temperature and cover change were negatively correlated. Overall, cooler, wetter springs lead to an increase in aboveground cover the next year. Learning how individual species within a forest plant community respond to weather conditions is a crucial part of understanding how plant communities will respond to climate change.

Comparison of three-weekly and six-weekly pembrolizumab United Kingdom prescribing practice for advanced and resected melanoma.

BACKGROUND: Pembrolizumab is approved for the treatment of advanced and resected melanoma and was originally licensed as a three-weekly infusion (Q3W). In April 2019, a six-weekly infusion schedule (Q6W) was also approved. We retrospectively reviewed pembrolizumab prescribing for patients with melanoma across multiple United Kingdom (UK) centres to compare the safety and efficacy of Q6W with Q3W in real-world clinical practice. METHODS: Case notes for melanoma patients treated with pembrolizumab between April 2019 and August 2020 at eight UK centres were reviewed. Prespecified baseline characteristics of the Q3W and Q6W cohorts were compared, as well as toxicity and efficacy outcomes. Prescribers were surveyed about their prescribing practice. RESULTS: Two hundred seventy-seven patients were included: 116 commenced Q3W and 161 commenced Q6W pembrolizumab. The proportion of Q6W prescriptions varied by the centre (range 32-88%). Patient factors associated with an increased likelihood of receiving Q3W over Q6W were preexisting autoimmune comorbidity (odds ratio [OR] 0.33; 95% confidence interval [CI] 0.12-0.82) and treatment for advanced (versus resected) disease (OR 0.54; 95%CI 0.33-0.90). Toxicity outcomes were broadly similar for Q6W and Q3W: 14.9% versus 15.5% ≥ grade 3 Common Terminology Criteria for Adverse Events. Estimated 12-month recurrence-free survival for adjuvantly treated patients was 78.9% for Q6W and 74.2% for Q3W (hazard ratio [HR] 0.93; 95%CI 0.50-1.73). Estimated 12-month progression-free survival for advanced patients was 41.8% for Q6W and 55.9% for Q3W (HR 1.21, 95%CI 0.67-2.18). CONCLUSIONS: Q6W is an appropriate option for administering pembrolizumab, given the opportunity to reduce the health service resource burden.

Antigenic mapping of the hemagglutinin of the H9 subtype influenza A viruses using sera from Japanese quail (Coturnix c. japonica).

IMPORTANCE: Determining the relevant amino acids involved in antigenic drift on the surface protein hemagglutinin (HA) is critical to understand influenza virus evolution and efficient assessment of vaccine strains relative to current circulating strains. We used antigenic cartography to generate an antigenic map of the H9 hemagglutinin (HA) using sera produced in one of the most relevant minor poultry species, Japanese quail. Key antigenic positions were identified and tested to confirm their impact on the antigenic profile. This work provides a better understanding of the antigenic diversity of the H9 HA as it relates to reactivity to quail sera and will facilitate a rational approach for selecting more efficacious vaccines against poultry-origin H9 influenza viruses in minor poultry species.

Tuning Crystallinity and Stacking of Two-Dimensional Covalent Organic Frameworks through Side-Chain Interactions.

Two-dimensional covalent organic frameworks (2D COFs) form as layered 2D polymers whose sheets stack through high-surface-area, noncovalent interactions that can give rise to different interlayer arrangements. Manipulating the stacking of 2D COFs is crucial since it dictates the effective size and shape of the pores as well as the specific interactions between functional aromatic systems in adjacent layers, both of which will strongly influence the emergent properties of 2D COFs. However, principles for tuning layer stacking are not yet well understood, and many 2D COFs are disordered in the stacking direction. Here, we investigate effects of pendant chain length through a series of 2D imine-linked COFs functionalized with n-alkyloxy chains varying in length from one carbon (C1 COF) to 11 carbons (C11 COF). This series reveals previously unrecognized and unanticipated trends in both the stacking geometry and crystallinity. C1 COF adopts an averaged eclipsed geometry with no apparent offset between layers. In contrast, all subsequent chain lengths lead to some degree of unidirectional slip stacking. As pendant chain length is increased, trends show average layer offset increasing to a maximum of 2.07 Å in C5 COF and then decreasing as chain length is extended through C11 COF. Counterintuitively, shorter chains (C2-C4) give rise to lower yields of weakly crystalline materials, while longer chains (C6-C9) produce greater yields of highly crystalline materials, as confirmed by powder X-ray diffraction and scanning electron microscopy. Molecular dynamics simulations corroborate these observations, suggesting that long alkyl chains can interact favorably to promote the self-assembly of sheets. In situ proton NMR spectroscopy provides insights into the reaction equilibrium as well as the relationship between low COF yields and low crystallinity. These results provide fundamental insights into principles of supramolecular assembly in 2D COFs, demonstrating an opportunity for harnessing favorable side-chain interactions to produce highly crystalline materials.

Characterization of A/H7 influenza virus global antigenic diversity and key determinants in the hemagglutinin globular head mediating A/H7N9 antigenic evolution.

IMPORTANCE: A/H7 avian influenza viruses cause outbreaks in poultry globally, resulting in outbreaks with significant socio-economical impact and zoonotic risks. Occasionally, poultry vaccination programs have been implemented to reduce the burden of these viruses, which might result in an increased immune pressure accelerating antigenic evolution. In fact, evidence for antigenic diversification of A/H7 influenza viruses exists, posing challenges to pandemic preparedness and the design of vaccination strategies efficacious against drifted variants. Here, we performed a comprehensive analysis of the global antigenic diversity of A/H7 influenza viruses and identified the main substitutions in the hemagglutinin responsible for antigenic evolution in A/H7N9 viruses isolated between 2013 and 2019. The A/H7 antigenic map and knowledge of the molecular determinants of their antigenic evolution add value to A/H7 influenza virus surveillance programs, the design of vaccines and vaccination strategies, and pandemic preparedness.

Development of Primers Specific for Detection of Litylenchus crenatae, the Causal Agent of Beech Leaf Disease, in Plant Tissue.

Beech leaf disease (BLD), an emerging threat to American beech (Fagus grandifolia) in the northern United States and Canada, was recently confirmed to be caused by the nematode Litylenchus crenatae subsp. mccannii (hereafter L. crenatae). Consequently, there is a need for a rapid, sensitive, and accurate method for detecting L. crenatae for both diagnostic as well as control purposes. This research developed a new set of DNA primers that specifically amplify L. crenatae and allow for accurate detection of the nematode in plant tissue. These primers have also been used in quantitative PCR (qPCR) to determine relative differences in gene copy number between samples. This primer set provides an improved, effective tool for monitoring and detecting L. crenatae in temperate tree leaf tissue which is necessary to understand the spread of this emerging forest pest and to develop management strategies.

Synthesis, Hole Doping, and Electrical Properties of a Semiconducting Azatriangulene-Based Covalent Organic Framework.

Two-dimensional covalent organic frameworks (2D COFs) containing heterotriangulenes have been theoretically identified as semiconductors with tunable, Dirac-cone-like band structures, which are expected to afford high charge-carrier mobilities ideal for next-generation flexible electronics. However, few bulk syntheses of these materials have been reported, and existing synthetic methods provide limited control of network purity and morphology. Here, we report transimination reactions between benzophenone-imine-protected azatriangulenes (OTPA) and benzodithiophene dialdehydes (BDT), which afforded a new semiconducting COF network, OTPA-BDT. The COFs were prepared as both polycrystalline powders and thin films with controlled crystallite orientation. The azatriangulene nodes are readily oxidized to stable radical cations upon exposure to an appropriate p-type dopant, tris(4-bromophenyl)ammoniumyl hexachloroantimonate, after which the network's crystallinity and orientation are maintained. Oriented, hole-doped OTPA-BDT COF films exhibit electrical conductivities of up to 1.2 × 10-1 S cm-1, which are among the highest reported for imine-linked 2D COFs to date.

Beech Leaf Disease Severity Affects Ectomycorrhizal Colonization and Fungal Taxa Composition.

Beech leaf disease (BLD) is an emerging forest infestation affecting beech trees (Fagus spp.) in the midwestern and northeastern United States and southeastern Canada. BLD is attributed to the newly recognized nematode Litylenchus crenatae subsp. mccannii. First described in Lake County, Ohio, BLD leads to the disfigurement of leaves, canopy loss, and eventual tree mortality. Canopy loss limits photosynthetic capacity, likely impacting tree allocation to belowground carbon storage. Ectomycorrhizal fungi are root symbionts, which rely on the photosynthesis of autotrophs for nutrition and growth. Because BLD limits tree photosynthetic capacity, ECM fungi may receive less carbohydrates when associating with severely affected trees compared with trees without BLD symptoms. We sampled root fragments from cultivated F. grandifolia sourced from two provenances (Michigan and Maine) at two timepoints (fall 2020 and spring 2021) to test whether BLD symptom severity alters colonization by ectomycorrhizal fungi and fungal community composition. The studied trees are part of a long-term beech bark disease resistance plantation at the Holden Arboretum. We sampled from replicates across three levels of BLD symptom severity and compared fungal colonization via visual scoring of ectomycorrhizal root tip abundance. Effects of BLD on fungal communities were determined through high-throughput sequencing. We found that ectomycorrhizal root tip abundance was significantly reduced on the roots of individuals of the poor canopy condition resulting from BLD, but only in the fall 2020 collection. We found significantly more ectomycorrhizal root tips from root fragments collected in fall 2020 than in spring 2021, suggesting a seasonal effect. Community composition of ectomycorrhizal fungi was not impacted by tree condition but did vary between provenances. We found significant species level responses of ectomycorrhizal fungi between levels of both provenance and tree condition. Of the taxa analyzed, two zOTUs had significantly lower abundance in high-symptomatology trees compared with low-symptomatology trees. These results provide the first indication of a belowground effect of BLD on ectomycorrhizal fungi and contribute further evidence to the role of these root symbionts in studies of tree disease and forest pathology.