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Abstract The health of honey bee queens is crucial for colony success, particularly during stressful periods like overwintering. To accompany a previous longitudinal study of colony and worker health, we explored niche-specific gut microbiota, host gene expression, and pathogen prevalence in honey bee queens overwintering in a warm southern climate. We found differential gene expression and bacterial abundance with respect to various pathogens throughout the season. Biologically older queens had larger microbiotas, particularly enriched in Bombella and Bifidobacterium. Both Deformed Wing Virus A and B subtypes were highest in the fat body tissue in January, correlating with colony Varroa levels, and Deformed Wing Virus titers in workers. High viral titers in queens were associated with decreased vitellogenin expression, suggesting a potential trade-off between immune function and reproductive capacity. Additionally, we found a complex and dynamic relationship between these viral loads and immune gene expression, indicating a possible breakdown in the coordinated immune response as the season progressed. Our study also revealed a potential link between Nosema and Melissococcus plutonius infections in queens, demonstrating that seasonal opportunism is not confined to just workers. Overall, our findings highlight the intricate interplay between pathogens, metabolic state, and immune response in honey bee queens. Combined with worker and colony-level metrics from the same colonies, our findings illustrate the social aspect of queen health and resilience over the winter dearth.

The microbiome of the honey bee worker hindgut has been explored thoroughly with culturing and next-generation sequencing revealing both composition and function. However, less effort has been devoted to the aerobic social niches associated with the hive environment and colony process. We performed a meta-analysis of 3,800+ publicly available 16S rRNA gene sequence libraries examining the hypothesis of a native aerobic microbiota associated with social interaction and colony resources. We selected high-throughput studies to represent tissue-specific samples, including nine distinct aerobic niches throughout the colony and hive, defined by social nutrient processing. These included queen and worker gut tissues, foregut, midgut, ileum, rectum, mouthparts, worker social glands, developing larvae, and secreted and stored nutrition. We found that the aerobic mouthparts, foregut and midgut niches of queens and workers share a significant portion of their microbiome with that of larval rearing and nutrient secretion and storage, defining the microbiota of the social resource niche. Characterized by species dominance and rapid growth, the social resource microbiota functions primarily in disease prevention at both the individual and colony level and may also function in social communication and gut microbiome resilience. Defining the microbiota of social function contributes to a systems-level understanding of host–microbial interactions in the honey bee.

Abstract Probiotics are widely used in agriculture including commercial beekeeping, but there is little evidence supporting their effectiveness. Antibiotic treatments can greatly distort the gut microbiome, reducing its protective abilities and facilitating the growth of antibiotic resistant pathogens. Commercial beekeepers regularly apply antibiotics to combat bacterial infections, often followed by an application of non-native probiotics advertised to ease the impact of antibiotic-induced gut dysbiosis. We tested whether probiotics affect the gut microbiome or disease prevalence, or rescue the negative effects of antibiotic induced gut dysbiosis. We found no difference in the gut microbiome or disease markers by probiotic application or antibiotic recovery associated with probiotic treatment. A colony-level application of the antibiotics oxytetracycline and tylosin produced an immediate decrease in gut microbiome size, and over the longer-term, very different and persistent dysbiotic effects on the composition and membership of the hindgut microbiome. Our results demonstrate the lack of probiotic effect or antibiotic rescue, detail the duration and character of dysbiotic states resulting from different antibiotics, and highlight the importance of the gut microbiome for honeybee health.

Substance use disorders contribute to considerable U.S. morbidity and mortality. While effective pharmacotherapy options are available to treat opioid and alcohol use disorders, for a variety of reasons, many patients lack access to treatment or may be reluctant to seek care due to concerns such as perceived stigma or a current lack of desire to completely curtail their substance use. Furthermore, treatment options are limited for patients with stimulant or polysubstance use disorders. Thus, there is considerable need to expand the substance use disorder harm reduction armamentarium. Kratom (Mitragyna speciosa Korth.) is an herbal substance that can produce both opioid and stimulant-like effects, and its use in the US is growing. Though there are concerns regarding adverse effects, dependence risk, and limited regulation of its manufacturing and sale, the pharmacology of kratom and early preclinical studies suggest a potential role as a harm reduction agent for various substance use disorders, and it has historically been used in Southeast Asia for such purposes. The goal of this review is to describe kratom’s history of use, pharmacology, and early pre-clinical and observational research regarding its therapeutic potential in opioid use disorder, as well as alcohol, stimulant, and polysubstance use disorders, while also highlighting current concerns around its use, existing gaps in the literature, and directions for future research.

Classification of sheep behaviour from a sequence of tri-axial accelerometer data has the potential to enhance sheep management. Sheep behaviour is inherently imbalanced (e.g., more ruminating than walking) resulting in underperforming classification for the minority activities which hold importance. Existing works have not addressed class imbalance and use traditional machine learning techniques, e.g., Random Forest (RF). We investigated Deep Learning (DL) models, namely, Long Short Term Memory (LSTM) and Bidirectional LSTM (BLSTM), appropriate for sequential data, from imbalanced data. Two data sets were collected in normal grazing conditions using jaw-mounted and ear-mounted sensors. Novel to this study, alongside typical single classes, e.g., walking, depending on the behaviours, data samples were labelled with compound classes, e.g., walking_grazing. The number of steps a sheep performed in the observed 10 s time window was also recorded and incorporated in the models. We designed several multi-class classification studies with imbalance being addressed using synthetic data. DL models achieved superior performance to traditional ML models, especially with augmented data (e.g., 4-Class + Steps: LSTM 88.0%, RF 82.5%). DL methods showed superior generalisability on unseen sheep (i.e., F1-score: BLSTM 0.84, LSTM 0.83, RF 0.65). LSTM, BLSTM and RF achieved sub-millisecond average inference time, making them suitable for real-time applications. The results demonstrate the effectiveness of DL models for sheep behaviour classification in grazing conditions. The results also demonstrate the DL techniques can generalise across different sheep. The study presents a strong foundation of the development of such models for real-time animal monitoring.

Abstract Twentieth century industrial whaling pushed several species to the brink of extinction, with fin whales being the most impacted. However, a small, resident population in the Gulf of California was not targeted by whaling. Here, we analyzed 50 whole-genomes from the Eastern North Pacific (ENP) and Gulf of California (GOC) fin whale populations to investigate their demographic history and the genomic effects of natural and human-induced bottlenecks. We show that the two populations diverged ~16,000 years ago, after which the ENP population expanded and then suffered a 99% reduction in effective size during the whaling period. In contrast, the GOC population remained small and isolated, receiving less than one migrant per generation. However, this low level of migration has been crucial for maintaining its viability. Our study exposes the severity of whaling, emphasizes the importance of migration, and demonstrates the use of genome-based analyses and simulations to inform conservation strategies.

Abstract Clinical phenotyping is often a foundational requirement for obtaining datasets necessary for the development of digital health applications. Traditionally done via manual abstraction, this task is often a bottleneck in development due to time and cost requirements, therefore raising significant interest in accomplishing this task via in-silico means. Nevertheless, current in-silico phenotyping development tends to be focused on a single phenotyping task resulting in a dearth of reusable tools supporting cross-task generalizable in-silico phenotyping. In addition, in-silico phenotyping remains largely inaccessible for a substantial portion of potentially interested users. Here, we highlight the barriers to the usage of in-silico phenotyping and potential solutions in the form of a framework of several desiderata as observed during our implementation of such tasks. In addition, we introduce an example implementation of said framework as a software application, with a focus on ease of adoption, cross-task reusability, and facilitating the clinical phenotyping algorithm development process.

Abstract Severe outbreaks and deaths have been linked to the emergence and global spread of fluoroquinolone-resistant Clostridioides difficile over the past two decades. At the same time, metronidazole, a nitro-containing antibiotic, has shown decreasing clinical efficacy in treating C. difficile infection (CDI). Most metronidazole-resistant C. difficile exhibit an unusual resistance phenotype that can only be detected in susceptibility tests using molecularly intact heme. Here, we describe the mechanism underlying this trait. We find that most metronidazole-resistant C. difficile strains carry a T-to-G mutation (which we term PnimB G ) in the promoter of gene nimB, resulting in constitutive transcription. Silencing or deleting nimB eliminates metronidazole resistance. NimB is related to Nim proteins that are known to confer resistance to nitroimidazoles. We show that NimB is a heme-dependent flavin enzyme that degrades nitroimidazoles to amines lacking antimicrobial activity. Furthermore, occurrence of the PnimB G mutation is associated with a Thr82Ile substitution in DNA gyrase that confers fluoroquinolone resistance in epidemic strains. Our findings suggest that the pandemic of fluoroquinolone-resistant C. difficile occurring over the past few decades has also been characterized by widespread resistance to metronidazole.

Introduction: Second-generation antipsychotics (SGA) are associated with misuse potential; however, there are limited data describing the prevalence and characteristics of this misuse. This study was conducted to identify and describe quetiapine and olanzapine misuse among US adults. Methods: This cross-sectional survey questionnaire was conducted online using Qualtrics research panel aggregator service to identify a quota-based sample of respondents constructed to mimic the general US population aged 18 to 59 years, with regards to gender, geographic region, ethnicity, income, and education level. Misuse was defined as using quetiapine or olanzapine for treatment outside of medical recommendations, for reasons other than a diagnosed medical condition, or obtaining without a prescription. A logistic regression was used to identify factors associated with SGA misuse, incorporating relevant covariates. Results: Among 1843 total respondents, 229 had a history of quetiapine or olanzapine use. Misuse prevalence was estimated to be 6.3% (95% CI: 5.2, 7.5%). Although most respondents (?70%) using quetiapine or olanzapine reported doing so to treat a diagnosed medical condition, those misusing them most commonly did so because prescribed medications failed to relieve their symptoms. Misuse was commonly reported (?50%) concomitantly with opioids, benzodiazepines, or alcohol. Factors significantly associated with quetiapine or olanzapine misuse included employment (OR = 4.64), previous substance use disorder treatment (OR = 2.48), and having riskier attitudes toward medication misuse (OR = 1.23). Discussion: Misuse of quetiapine and olanzapine, while fairly limited in prevalence, appears to be primarily associated with under-treatment of existing medical conditions.

Abstract As essential pollinators of ecosystems and agriculture, honey bees (Apis mellifera) are host to a variety of pathogens that result in colony loss. Two highly prevalent larval diseases are European foulbrood (EFB) attributed to the bacterium Melissococcus plutonius, and Varroosis wherein larvae can be afflicted by one or more paralytic viruses. Here we used high-throughput sequencing and qPCR to detail microbial succession of larval development from six diseased, and one disease-free apiary. The disease-free larval microbiome revealed a variety of disease-associated bacteria in early larval instars, but later developmental stages were dominated by beneficial symbionts. Microbial succession associated with EFB pathology differed by apiary, characterized by associations with various gram-positive bacteria. At one apiary, diseased larvae were uniquely described as “melting and deflated”, symptoms associated with Varroosis. We found that Acute Bee Paralysis Virus (ABPV) levels were significantly associated with these symptoms, and various gram-negative bacteria became opportunistic in the guts of ABPV afflicted larvae. Perhaps contributing to disease progression, the ABPV associated microbiome was significantly depleted of gram-positive bacteria, a likely result of recent antibiotic application. Our results contribute to the understanding of brood disease diagnosis and treatment, a growing problem for beekeeping and agriculture worldwide.

We present a framework that couples a high-fidelity compositional reservoir simulator with Bayesian optimization (BO) for injection well scheduling optimization in geological carbon sequestration. This work represents one of the first at tempts to apply BO and high-fidelity physics models to geological carbon storage. The implicit parallel accurate reservoir simulator (IPARS) is utilized to accurately capture the underlying physical processes during CO2 sequestration. IPARS provides a framework for several flow and mechanics models and thus supports both stand-alone and coupled simulations. In this work, we use the compositional flow module to simulate the geological carbon storage process. The compositional flow model, which includes a hysteretic three-phase relative permeability model, accounts for three major CO2 trapping mechanisms: structural trapping, residual gas trapping, and solubility trapping. Furthermore, IPARS is coupled to the International Business Machines (IBM) Corporation Bayesian Optimization Accelerator (BOA) for parallel optimizations of CO2 injection strategies during field-scale CO2 sequestration. BO builds a probabilistic surrogate for the objective function using a Bayesian machine learning algorithm—the Gaussian process regression, and then uses an acquisition function that leverages the uncertainty in the surrogate to decide where to sample. The IBM BOA addresses the three weaknesses of standard BO that limits its scalability in that IBM BOA supports parallel (batch) executions, scales better for high-dimensional problems, and is more robust to initializations. We demonstrate these merits by applying the algorithm in the optimization of the CO2 injection schedule in the Cranfield site in Mississippi, USA, using field data. The optimized injection schedule achieves 16% more gas storage volume and 56% less water/surfactant usage compared with the baseline. The performance of BO is compared with that of a genetic algorithm (GA) and a covariance matrix adaptation (CMA)-evolution strategy (ES). The results demonstrate the superior performance of BO, in that it achieves a competitive objective function value with over 60% fewer forward model evaluations.

Abstract Winter forage dearth is a major contributor to honey bee colony loss and can influence disease susceptibility. Honey bees possess a secretory head gland that interfaces with the social environment on many levels. During winter or forage dearth, colonies produce a long-lived (diutinus) worker phenotype that survives until environmental conditions improve. We used a known-age worker cohort to investigate microbiome integrity and social gene expression of workers in early and late winter. We provide additional context by contrasting host-microbial interactions from warm outdoor and cold indoor environments. Our results provide novel evidence that social immune gene expression is associated with worker longevity, and highlight the midgut as a target of opportunistic disease during winter. Host microbial interactions suggest opportunistic disease progression and resistance in long-lived workers, but susceptibility to opportunistic disease in younger workers that emerged during the winter, including increases in Enterobacteriaceae, fungal load and non-core bacterial abundance. The results are consistent with increased social immunity, including host associations with the social microbiota, and a social immune response by long-lived workers to combat microbial opportunism. The cost/benefit ratio associated with limited expression of the diutinus phenotype may be a strong determinant of colony survival during winter forage dearth.

The genus Quercus (oaks) has diversified into over 450 species which often play dominant roles in the ecosystems in which they occur. Here the authors present a genome and methylome for a California endemic oak, Quercus lobata, and describe features relevant to its evolutionary success.

Honey bee colonies maintain viable queens in part through communication with Queen Mandibular Pheromone (QMP), a mixture that signals the queen's presence and reproductive quality to workers. In turn, workers are thought to provide retinue queen care or replace queens partially based on QMP profiles. We examined the effects of seasonal dearth (overwintering in a warm subtropical location) on queen-worker interactions. Retinue worker responses to continuously ovipositing queens were considered in view of QMP signaling and queen reproductive quality. QMP signaling was estimated from QMP residues recovered from nest worker bodies, which is the primary mode of QMP transfer from the queen to the colony at large. QMP residues varied seasonally but not at all with queen reproductive quality (spermatheca sperm storage, ovary protein and lipid contents). 9-HDA and 9-ODA were lower in January than other months. HOB decreased from July to January, while HVA, a component associated with mated queens, increased sharply in January. Despite these seasonal signaling differences, retinue workers attended queens at similar levels through the months. In terms of reproductive quality, queens did not differ over the months in matedness (spermatheca sperm storage) or physiological age (protein carbonyl content), but varied in nutrient allocation to reproductive and non-reproductive tissues. Queen ovaries contained more protein in September than in November, and more lipid in July and September than in November and January. Queen fat bodies had more protein in July than September or November, but less lipid in July and September than November or January. Retinue worker responses did not vary with seasonal QMP changes, but reflected overall continuous brood rearing efforts and queen matedness throughout the year. The absence of seasonal differences in worker responses to QMP should be considered in the broader context of continuous reproductive efforts in warm subtropical colonies.

Honey bees exhibit an elaborate social structure based in part on an age-related division of labor. Young workers perform tasks inside the hive, while older workers forage outside the hive, tasks associated with distinct diets and metabolism. Critical to colony fitness, the work force can respond rapidly to changes in the environment or colony demography and assume emergency tasks, resulting in young foragers or old nurses. We hypothesized that both task and age affect the gut microbiota consistent with changes to host diet and physiology. We performed two experiments inducing precocious foragers and reverted nurses, then quantified tissue-specific gut microbiota and host metabolic state associated with nutrition, immunity and oxidative stress. In the precocious forager experiment, both age and ontogeny explained differences in midgut and ileum microbiota, but host gene expression was best explained by an interaction of these factors. Precocious foragers were nutritionally deficient, and incurred higher levels of oxidative damage relative to age-matched nurses. In the oldest workers, reverted nurses, the oxidative damage associated with age and past foraging was compensated by high Vitellogenin expression, which exceeded that of young nurses. Host-microbial interactions were evident throughout the dataset, highlighted by an age-based increase of Gilliamella abundance and diversity concurrent with increased carbonyl accumulation and CuZnSOD expression. The results in general contribute to an understanding of ecological succession of the worker gut microbiota, defining the species-level transition from nurse to forager.

Coronavirus disease has disproportionately affected persons in congregate settings and high-density workplaces. To determine more about the transmission patterns of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in these settings, we performed whole-genome sequencing and phylogenetic analysis on 319 (14.4%) samples from 2,222 SARS-CoV-2–positive persons associated with 8 outbreaks in Minnesota, USA, during March–June 2020. Sequencing indicated that virus spread in 3 long-term care facilities and 2 correctional facilities was associated with a single genetic sequence and that in a fourth long-term care facility, outbreak cases were associated with 2 distinct sequences. In contrast, cases associated with outbreaks in 2 meat-processing plants were associated with multiple SARS-CoV-2 sequences. These results suggest that a single introduction of SARS-CoV-2 into a facility can result in a widespread outbreak. Early identification and cohorting (segregating) of virus-positive persons in these settings, along with continued vigilance with infection prevention and control measures, is imperative.

Introduction: Gabapentin and pregabalin (gabapentinoids) can be given with opioids for opioid-sparing and adjuvant analgesic effects. In the context of certain comorbidities and high dosages, coadministration of these agents can lead to respiratory depression or oversedation, necessitating naloxone administration. Methods: A retrospective chart review from January 2015 to December 2017 was conducted to include patients who received naloxone and opioids with or without gabapentinoids. Exclusion criteria included pregnancy or having received naloxone in the emergency department, intensive care, or pediatrics units. The primary outcome was to characterize differences between groups regarding comorbidities, history of renal or hepatic dysfunction, history of SUD, opioid tolerance, initiation and dose appropriateness of gabapentinoids, and dose intensity of gabapentinoids and opioids. Secondary outcomes were concomitant CNS depressant use and naloxone episodes for documented respiratory depression. Results: Of 126 patients who met inclusion criteria, 36 received opioids and gabapentinoids (gabapentinoid group) and 90 received opioids alone (nongabapentinoid group). There were 136 naloxone episodes between the 2 groups. More than 50% of the naloxone episodes in the gabapentinoid group involved opioids of at least 90 oral morphine mg equivalents. Respiratory depression accounted for 39% and 15.8% of the naloxone episodes in the gabapentinoid and nongabapentinoid groups, respectively. Discussion: There may be increased naloxone episodes among patients receiving opioids and gabapentinoids. Future studies are needed to evaluate the incremental risk of respiratory depression and oversedation as it pertains to concomitant medication administration and patient-specific factors.

ABSTRACT The highly social honey bee has dense populations but a significantly reduced repertoire of immune genes relative to solitary species, suggesting a greater reliance on social immunity. Here we investigate immune gene expression and gut microbial succession in queens during colony introduction. Recently mated queens were placed into an active colony or a storage hive for multiple queens: a queen-bank. Feeding intensity, social context, and metabolic demand differ greatly between the two environments. After 3 weeks, we examined gene expression associated with oxidative stress and immunity and performed high-throughput sequencing of the queen gut microbiome across four alimentary tract niches. Microbiota and gene expression in the queen hindgut differed by time, queen breeder source, and metabolic environment. In the ileum, upregulation of most immune and oxidative stress genes occurred regardless of treatment conditions, suggesting postmating effects on gut gene expression. Counterintuitively, queens exposed to the more social colony environment contained significantly less bacterial diversity indicative of social immune factors shaping the queens microbiome. Queen bank queens resembled much older queens with decreased Alpha 2.1, greater abundance of Lactobacillus firm5 and Bifidobacterium in the hindgut, and significantly larger ileum microbiotas, dominated by blooms of Snodgrassella alvi. Combined with earlier findings, we conclude that the queen gut microbiota experiences an extended period of microbial succession associated with queen breeder source, postmating development, and colony assimilation. IMPORTANCE In modern agriculture, honey bee queen failure is repeatedly cited as one of the major reasons for yearly colony loss. Here we discovered that the honey bee queen gut microbiota alters according to early social environment and is strongly tied to the identity of the queen breeder. Like human examples, this early life variation appears to set the trajectory for ecological succession associated with social assimilation and queen productivity. The high metabolic demand of natural colony assimilation is associated with less bacterial diversity, a smaller hindgut microbiome, and a downregulation of genes that control pathogens and oxidative stress. Queens placed in less social environments with low metabolic demand (queen banks) developed a gut microbiota that resembled much older queens that produce fewer eggs. The queens key reproductive role in the colony may rely in part on a gut microbiome shaped by social immunity and the early queen rearing environment.

Abstract Background Cardiac metastasis due to colon cancer is extraordinarily uncommon. Given the rarity of diagnosis, there is paucity of evidence and hence, no established guidelines for evaluation or clinical management strategy. Clinical presentation We present the case of a 59 year old male with a previously treated colonic carcinoma who presented with new onset exertional dyspnea. He was noted to be having a right atrial mass on an echocardiogram performed at his cardiologist’s office. Further workup with CT angiogram of the chest confirmed a right atrial mass measuring 4.0 cm. Serum CEA was normal. Biopsies of the right atrial mass demonstrated metastatic moderately differentiated colonic adenocarcinoma. Mismatch repair protein expression analysis by immunohistochemistry showed no loss of MLH1, MSH2, MSH6 or PMS2 expression. Next generation sequencing for RAS and BRAF mutations was negative. Patient received treatment with FOLFIRINOX/ bevacizumab with noted reduction in size of mass. Conclusion To the best of our knowledge, this is the first report of next generation sequencing results available on a biopsy of metastatic colorectal cancer to the heart with the largest literature review of 31 reported cases of metastatic colorectal cancer to the heart. It will help direct clinical management and also adds evidence to the potential efficacy of treatment of this rare aggressive disease with chemotherapy in combination with VEGF inhibitors.

Abstract The alkylating agent, temozolomide (TMZ), is the most commonly used chemotherapeutic for the treatment of glioblastoma (GBM). The anti-glioma effect of TMZ involves a complex response that includes G2-M cell cycle arrest and cyclin-dependent kinase 1 (CDK1) activation. While CDK1 phosphorylation is a well-described consequence of TMZ treatment, we find that TMZ also robustly induces CDK1 expression. Analysis of this pathway demonstrates that CDK1 is regulated by NF-κB via a putative κB-site in its proximal promoter. CDK1 was induced in a manner dependent on mature p50 and the atypical inhibitor κB protein, BCL-3. Treatment with TMZ induced binding of NF-κB to the κB-site as assessed by gel shift analysis and chromatin immunoprecipitation. Examination of a CDK1 promoter-reporter demonstrated the functional relevance of the κB-site and underlined the requirement of p50 and BCL-3 for activation. Targeted knockdown of CDK1 or chemical inhibition with the selective CDK1 inhibitor, RO-3306, potentiated the cytotoxic effect of TMZ. These results identify CDK1 as an NF-κB target gene regulated by p50 and BCL-3 and suggest that targeting CDK1 may be a strategy to improve the efficacy of TMZ against GBM.

Abstract Human‐driven habitat fragmentation and loss have led to a proliferation of small and isolated plant and animal populations with high risk of extinction. One of the main threats to extinction in these populations is inbreeding depression, which is primarily caused by recessive deleterious mutations becoming homozygous due to inbreeding. The typical approach for managing these populations is to maintain high genetic diversity, increasingly by translocating individuals from large populations to initiate a “genetic rescue.” However, the limitations of this approach have recently been highlighted by the demise of the gray wolf population on Isle Royale, which declined to the brink of extinction soon after the arrival of a migrant from the large mainland wolf population. Here, we use a novel population genetic simulation framework to investigate the role of genetic diversity, deleterious variation, and demographic history in mediating extinction risk due to inbreeding depression in small populations. We show that, under realistic models of dominance, large populations harbor high levels of recessive strongly deleterious variation due to these mutations being hidden from selection in the heterozygous state. As a result, when large populations contract, they experience a substantially elevated risk of extinction after these strongly deleterious mutations are exposed by inbreeding. Moreover, we demonstrate that, although genetic rescue is broadly effective as a means to reduce extinction risk, its effectiveness can be greatly increased by drawing migrants from small or moderate‐sized source populations rather than large source populations due to smaller populations harboring lower levels of recessive strongly deleterious variation. Our findings challenge the traditional conservation paradigm that focuses on maximizing genetic diversity in small populations in favor of a view that emphasizes minimizing strongly deleterious variation. These insights have important implications for managing small and isolated populations in the increasingly fragmented landscape of the Anthropocene.

The small animal imaging Digital Imaging and Communications in Medicine (DICOM) acquisition context structured report (SR) was developed to incorporate pre-clinical data in an established DICOM format for rapid queries and comparison of clinical and non-clinical datasets. Established terminologies (i.e., anesthesia, mouse model nomenclature, veterinary definitions, NCI Metathesaurus) were utilized to assist in defining terms implemented in pre-clinical imaging and new codes were added to integrate the specific small animal procedures and handling processes, such as housing, biosafety level, and pre-imaging rodent preparation. In addition to the standard DICOM fields, the small animal SR includes fields specific to small animal imaging such as tumor graft (i.e., melanoma), tissue of origin, mouse strain, and exogenous material, including the date and site of injection. Additionally, the mapping and harmonization developed by the Mouse-Human Anatomy Project were implemented to assist co-clinical research by providing cross-reference human-to-mouse anatomies. Furthermore, since small animal imaging performs multi-mouse imaging for high throughput, and queries for co-clinical research requires a one-to-one relation, an imaging splitting routine was developed, new Unique Identifiers (UID’s) were created, and the original patient name and ID were saved for reference to the original dataset. We report the implementation of the small animal SR using MRI datasets (as an example) of patient-derived xenograft mouse models and uploaded to The Cancer Imaging Archive (TCIA) for public dissemination, and also implemented this on PET/CT datasets. The small animal SR enhancement provides researchers the ability to query any DICOM modality pre-clinical and clinical datasets using standard vocabularies and enhances co-clinical studies.

Genome-wide maps of evolutionary constraint and large-scale compendia of epigenomic and transcription factor data provide complementary information for genome annotation. Here, the authors develop the Constrained Non-Exonic Predictor (CNEP) that enables better understanding of their relationship.

Honey bee colonies are resource rich and densely populated, generating a constant battle to control microbial growth. Honey is relatively sterile in comparison with beebread: a food storage medium comprising pollen mixed with honey and worker head-gland secretions. Within colonies, the microbes that dominate aerobic niches are abundant throughout social resource space including stored pollen, honey, royal jelly, and the anterior gut segments and mouthparts of both queens and workers. Here, we identify and discuss the microbial load in stored pollen associated with non-Nosema fungi (primarily yeast) and bacteria. We also measured abiotic changes associated with pollen storage and used culturing and qPCR of both fungi and bacteria to investigate changes in stored pollen microbiology by both storage time and season. Over the first week of pollen storage, pH and water availability decreased significantly. Following an initial drop in microbial abundance at day one, both yeasts and bacteria multiply rapidly during day two. Both types of microbes then decline at 3–7 days, but the highly osmotolerant yeasts persist longer than the bacteria. Based on measures of absolute abundance, bacteria and yeast are controlled by similar factors during pollen storage. This work contributes to our understanding of host–microbial interactions in the honey bee gut and colony and the effect of pollen storage on microbial growth, nutrition, and bee health.

Quantitative trait loci (QTL) analysis could help to identify suitable molecular markers for marker-assisted breeding (MAB). A mapping population of 124 F5:7recombinant inbred lines derived from the cross ‘TAM 112’/‘TAM 111’ was grown under 28 diverse environments and evaluated for grain yield, test weight, heading date, and plant height. The objective of this study was to detect QTL conferring grain yield and agronomic traits from multiple mega-environments. Through a linkage map with 5,948 single nucleotide polymorphisms (SNPs), 51 QTL were consistently identified in two or more environments or analyses. Ten QTL linked to two or more traits were also identified on chromosomes 1A, 1D, 4B, 4D, 6A, 7B, and 7D. Those QTL explained up to 13.3% of additive phenotypic variations with the additive logarithm of odds (LOD(A)) scores up to 11.2. The additive effect increased yield up to 8.16 and 6.57 g m−2 and increased test weight by 2.14 and 3.47 kg m−3 with favorable alleles from TAM 111 and TAM 112, respectively. Seven major QTL for yield and six for TW with one in common were of our interest on MAB as they explained 5% or more phenotypic variations through additive effects. This study confirmed previously identified loci and identified new QTL and the favorable alleles for improving grain yield and agronomic traits.

Ancient human migrations led to the settlement of population groups in varied environmental contexts worldwide. The extent to which adaptation to local environments has shaped human genetic diversity is a longstanding question in human evolution. Recent studies have suggested that introgression of archaic alleles in the genome of modern humans may have contributed to adaptation to environmental pressures such as pathogen exposure. Functional genomic studies have demonstrated that variation in gene expression across individuals and in response to environmental perturbations is a main mechanism underlying complex trait variation. We considered gene expression response to in vitro treatments as a molecular phenotype to identify genes and regulatory variants that may have played an important role in adaptations to local environments. We investigated if Neanderthal introgression in the human genome may contribute to the transcriptional response to environmental perturbations. To this end we used eQTLs for genes differentially expressed in a panel of 52 cellular environments, resulting from 5 cell types and 26 treatments, including hormones, vitamins, drugs, and environmental contaminants. We found that SNPs with introgressed Neanderthal alleles (N-SNPs) disrupt binding of transcription factors important for environmental responses, including ionizing radiation and hypoxia, and for glucose metabolism. We identified an enrichment for N-SNPs among eQTLs for genes differentially expressed in response to 8 treatments, including glucocorticoids, caffeine, and vitamin D. Using Massively Parallel Reporter Assays (MPRA) data, we validated the regulatory function of 21 introgressed Neanderthal variants in the human genome, corresponding to 8 eQTLs regulating 15 genes that respond to environmental perturbations. These findings expand the set of environments where archaic introgression may have contributed to adaptations to local environments in modern humans and provide experimental validation for the regulatory function of introgressed variants.

Evolutionary forces like Hill-Robertson interference and negative epistasis can lead to deleterious mutations being found on distinct haplotypes. However, the extent to which these forces depend on the selection and dominance coefficients of deleterious mutations and shape genome-wide patterns of linkage disequilibrium (LD) in natural populations with complex demographic histories has not been tested. In this study, we first used forward-in-time simulations to predict how negative selection impacts LD. Under models where deleterious mutations have additive effects on fitness, deleterious variants less than 10 kb apart tend to be carried on different haplotypes relative to pairs of synonymous SNPs. In contrast, for recessive mutations, there is no consistent ordering of how selection coefficients affect LD decay, due to the complex interplay of different evolutionary effects. We then examined empirical data of modern humans from the 1000 Genomes Project. LD between derived alleles at nonsynonymous SNPs is lower compared to pairs of derived synonymous variants, suggesting that nonsynonymous derived alleles tend to occur on different haplotypes more than synonymous variants. This result holds when controlling for potential confounding factors by matching SNPs for frequency in the sample (allele count), physical distance, magnitude of background selection, and genetic distance between pairs of variants. Lastly, we introduce a new statistic HR(j) which allows us to detect interference using unphased genotypes. Application of this approach to high-coverage human genome sequences confirms our finding that nonsynonymous derived alleles tend to be located on different haplotypes more often than are synonymous derived alleles. Our findings suggest that interference may play a pervasive role in shaping patterns of LD between deleterious variants in the human genome, and consequently influences genome-wide patterns of LD.

Abstract Background Evaluating the strength of the small muscles of the foot may be useful in a variety of clinical applications but is challenging from a methodology standpoint. Previous efforts have focused primarily on the functional movement of toe flexion, but clear methodology guidelines are lacking. A novel foot doming test has also been proposed, but not fully evaluated. The purposes of the present study were to assess the repeatability and comparability of several functional foot strength assessment techniques. Methods Forty healthy volunteers were evaluated across two testing days, with a two-week doming motion practice period between them. Seven different measurements were taken using a custom toe flexion dynamometer (seated), custom doming dynamometer (standing), and a pressure mat (standing). Measurements from the doming dynamometer were evaluated for reliability (ICCs) and a learning effect (paired t-tests), while measurements from the toe flexion dynamometer and pressure mat were evaluated for reliability and comparability (correlations). Electromyography was also used to descriptively assess the extent of muscle isolation in all measurements. Results Doming showed excellent within-session reliability (ICCs > 0.944), but a clear learning effect was present, with strength (p 0.945). Seated toe flexion tests using the dynamometer were moderately correlated to standing toe flexion tests on a pressure mat (r > 0.54); however, there were some differences in muscle activity. The former may better isolate the toe flexors, while the latter appeared to be more functional for many pathologies. On the pressure mat, reciprocal motion appeared to display slightly greater forces and reliability than isolated toe flexion. Conclusions This study further refines potential methodology for foot strength testing. These devices and protocols can be duplicated in the clinic to evaluate and monitor rehabilitation progress in clinical populations associated with foot muscle weakness.

Grain sorghum (Sorghum bicolor L.) is a major dryland crop in the Texas High Plains. Currently, drought and infestation by the sugarcane aphid (SCA, Melanaphis sacchari) are the two major challenges to grain sorghum production in the area. A 2-year field study was conducted to investigate the effect of planting date (PD) and hybrid selection on yield, evapotranspiration (ET), water use efficiency (WUE), and SCA infestation. Five sorghum hybrids (86P20, SP-31A15, AG1201, AG1203, and DKS37-07) were grown on two planting dates (PD1—early May; PD2—late June) under dryland conditions. Insecticides were not used. There were significant differences in grain yield, WUE, evapotranspiration (ET), and SCA population between two PDs and among hybrids. For PD1, SCA infestation occurred after sorghum reached physiological maturity in 2017. Although SCA infestation was observed during late grain filling in 2018, SCA populations were low and did not affect yield. For PD2, SCA was present before anthesis in both years and significantly affected grain yield. Even with heavy SCA infestation in PD2, the grain yield was higher in PD2 than in PD1 due to timely precipitation. Among hybrids, AG1203, 86P20 and DK37-07 performed better with higher yield and less SCA infestation in PD2. Grain yield was more related to seeds per plant than to kernel weight and harvest index.

[This corrects the article DOI: 10.1371/journal.pone.0175933.].

The explosion in population genomic data demands ever more complex modes of analysis, and increasingly, these analyses depend on sophisticated simulations. Recent advances in population genetic simulation have made it possible to simulate large and complex models, but specifying such models for a particular simulation engine remains a difficult and error-prone task. Computational genetics researchers currently re-implement simulation models independently, leading to inconsistency and duplication of effort. This situation presents a major barrier to empirical researchers seeking to use simulations for power analyses of upcoming studies or sanity checks on existing genomic data. Population genetics, as a field, also lacks standard benchmarks by which new tools for inference might be measured. Here, we describe a new resource, stdpopsim, that attempts to rectify this situation. Stdpopsim is a community-driven open source project, which provides easy access to a growing catalog of published simulation models from a range of organisms and supports multiple simulation engine backends. This resource is available as a well-documented python library with a simple command-line interface. We share some examples demonstrating how stdpopsim can be used to systematically compare demographic inference methods, and we encourage a broader community of developers to contribute to this growing resource.

Background: As opioid-related overdose deaths climb in the U.S., risk reduction measures are increasingly important. One such measure recommended involves provision of proactive substance use counseling regarding the risks of opioid analgesics. This is particularly important in patients at increased risk of overdose, such as those with substance use disorders (SUD) or those receiving concomitant medications that further increase the overdose risk (eg, benzodiazepines, gabapentinoids, or Z-hypnotics). However, previous research regarding the likelihood that such counseling is provided during outpatient prescriber visits is lacking. Objectives: To determine the percentage of U.S. ambulatory care visits in which patients taking prescription opioids received substance use counseling, and whether counseling was more common in patients with concomitant GABAergic medication(s) (benzodiazepine, gabapentinoid or Z-hypnotic) or substance use disorder (SUD) diagnosis. Methods: A cross-sectional analysis was conducted of all patients aged ⩾18 years identified as having a prescription opioid on their medication list within the 2014-2015 National Ambulatory Medical Care Survey data. Results: Among 162.7 million visits in which patients were taking opioid medication(s), substance use counseling was provided in 2.4%. During visits for patients receiving opioid(s) plus GABAergic(s), substance use counseling was marginally more common (3.1% versus 2.0%, P < .0001). Substance use counseling was also more common among visits for patients taking opioid(s) with SUD (18.9% versus 1.5%, P < .0001). Among visits in which a patient was diagnosed with SUD and taking opioid(s) plus GABAergic(s), counseling was more common (23.1% versus 1.4%, P < .0001) compared to patients taking opioid(s) plus GABAergic(s) without SUD. Conclusions: Among national ambulatory care visits in the United States, substance use counseling is provided infrequently for patients taking opioids, even when significant risk factors are present. Increasing patient education may help reduce opioid-related overdose mortality.