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AbstractStriking examples of local adaptation at fine geographic scales are increasingly being documented in natural populations. However, the relative contributions made by natural selection, phenotype-dependent dispersal (when individuals disperse with respect to a habitat preference), and mate preference in generating and maintaining microgeographic adaptation and divergence are not well studied. Here, we develop quantitative genetics models and individual-based simulations (IBSs) to uncover the evolutionary forces that possibly drive microgeographic divergence. We also perform Bayesian estimation of the parameters in our IBS using empirical data on habitat-specific variation in bill morphology in the island scrub-jay (Aphelocoma insularis) to apply our models to a natural system. We find that natural selection and phenotype-dependent dispersal can generate the patterns of divergence we observe in the island scrub-jay. However, mate preference for a mate with similar bill morphology, even though observed in the species, does not play a significant role in driving divergence. Our modeling approach provides insights into phenotypic evolution occurring over small spatial scales relative to dispersal ranges, suggesting that adaptive divergence at microgeographic scales may be common across a wider range of taxa than previously thought. Our quantitative genetic models help to inform future theoretical and empirical work to determine how selection, habitat preference, and mate preference contribute to local adaptation and microgeographic divergence.
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Ecossistema , Seleção Genética , Humanos , Teorema de Bayes , Fenótipo , Variação GenéticaRESUMO
INTRODUCTION: Adverse birth outcomes particularly preterm births and congenital anomalies, are the leading causes of infant mortality globally, and the burden is highest in developing countries. We set out to determine the frequency of adverse birth outcomes and the risk factors associated with such outcomes in a cohort of pregnant women in Kenya. METHODS: From October 2017 to July 2019, pregnant women < 28 weeks gestation were enrolled and followed up until delivery in three hospitals in coastal Kenya. Newborns were examined at delivery. Among women with birth outcome data, we assessed the frequency of congenital anomalies defined as gastroschisis, umbilical hernia, limb abnormalities and Trisomy 21, and adverse birth outcomes, defined as either stillbirth, miscarriage, preterm birth, small for gestational age, or microcephaly. We used log-binomial regression to identify maternal characteristics associated with the presence of at least one adverse outcome. RESULTS: Among the 2312 women enrolled, 1916 (82.9%) had birth outcome data. Overall, 402/1916 (20.9%; 95% confidence interval (CI): 19.1-22.8) pregnancies had adverse birth outcomes. Specifically, 66/1916 (3.4%; 95% CI: 2.7-4.4) were stillbirths, 34/1916 (1.8%; 95% CI: 1.2-2.4) were miscarriages and 23/1816 (1.2%; 95% CI: 0.8-1.9) had congenital anomalies. Among the participants with anthropometric measurements data, 142/1200 (11.8%; 95% CI: 10.1 - 13.8) were small for gestational age and among the participants with ultrasound records, 143/1711 (8.4%; 95% CI: 7.1-9.8) were preterm. Febrile illnesses in current pregnancy (adjusted risk ratio (aRR): 1.7; 95% CI: 1.1-2.8), a history of poor birth outcomes in prior pregnancy (aRR: 1.8; 95% CI: 1.3-2.4) and high blood pressure in pregnancy (aRR: 3.9, 95% CI: (1.7-9.2) were independently associated with adverse birth outcomes in a model that included age, education, human immunodeficiency virus status and high blood pressure at enrolment. CONCLUSION: We found similar rates of overall adverse birth outcomes, congenital anomalies, and small for gestational age but higher rates of stillbirths and lower rates of prematurity compared to the rates that have been reported in the sub-Saharan Africa region. However, the rates of adverse birth outcomes in this study were comparable to other studies conducted in Kenya. Febrile illnesses during the current pregnancy, previous history of poor birth outcomes and high blood pressure in pregnancy are predictive of an increased risk of adverse birth outcomes.
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Aborto Espontâneo , Hipertensão , Complicações na Gravidez , Nascimento Prematuro , Gravidez , Recém-Nascido , Feminino , Humanos , Natimorto/epidemiologia , Resultado da Gravidez/epidemiologia , Gestantes , Quênia/epidemiologia , Nascimento Prematuro/epidemiologia , Complicações na Gravidez/epidemiologia , Fatores de Risco , Aborto Espontâneo/epidemiologia , Retardo do Crescimento FetalRESUMO
BACKGROUND: Subfertility is a major issue facing the dairy industry as the average US Holstein cow conception rate (CCR) is approximately 35%. The genetics underlying the physiological processes responsible for CCR, the proportion of cows able to conceive and maintain a pregnancy at each breeding, are not well characterized. The objectives of this study were to identify loci, positional candidate genes, and transcription factor binding sites (TFBS) associated with CCR and determine if there was a genetic correlation between CCR and milk production in primiparous Holstein cows. Cows were bred via artificial insemination (AI) at either observed estrus or timed AI and pregnancy status was determined at day 35 post-insemination. Additive, dominant, and recessive efficient mixed model association expedited (EMMAX) models were used in two genome-wide association analyses (GWAA). One GWAA focused on CCR at first service (CCR1) comparing cows that conceived and maintained pregnancy to day 35 after the first AI (n = 494) to those that were open after the first AI (n = 538). The second GWAA investigated loci associated with the number of times bred (TBRD) required for conception in cows that either conceived after the first AI (n = 494) or repeated services (n = 472). RESULTS: The CCR1 GWAA identified 123, 198, and 76 loci associated (P < 5 × 10- 08) in additive, dominant, and recessive models, respectively. The TBRD GWAA identified 66, 95, and 33 loci associated (P < 5 × 10- 08) in additive, dominant, and recessive models, respectively. Four of the top five loci were shared in CCR1 and TBRD for each GWAA model. Many of the associated loci harbored positional candidate genes and TFBS with putative functional relevance to fertility. Thirty-six of the loci were validated in previous GWAA studies across multiple breeds. None of the CCR1 or TBRD associated loci were associated with milk production, nor was their significance with phenotypic and genetic correlations to 305-day milk production. CONCLUSIONS: The identification and validation of loci, positional candidate genes, and TFBS associated with CCR1 and TBRD can be utilized to improve, and further characterize the processes involved in cattle fertility.
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Bovinos/genética , Loci Gênicos , Animais , Sítios de Ligação , Feminino , Fertilização/genética , Estudo de Associação Genômica Ampla , Leite , Polimorfismo de Nucleotídeo Único , Fatores de Transcrição/metabolismoRESUMO
COVID-19 has presented hospitals with unique challenges. A SHEA Research Network survey showed that 40% reported "limited" or worse levels of personal protective equipment (PPE), and 13% were self-producing PPE to address those deficits, including 3D-printed items. However, we do not know how efficiently, if at all, 3D-printed materials can be disinfected. Additionally, two filaments, PLACTIVE and BIOGUARD, claim to be antimicrobial; they use copper nanocomposites and silver ions to reduce bacterial populations. We assess how PLACTIVE and BIOGUARD may be contaminated and how well they reduce contamination, and how readily Polylactic Acid (PLA), a standard 3D-printed material, may be disinfected. 3D-printed materials, including PLACTIVE and BIOGUARD, are readily contaminated with bacteria that are common in hospitals and can sustain that contamination. Our findings reveal that the levels of contamination on PLACTIVE and BIOGUARD can vary under specific conditions such as layer height or bacterial contact time, sometimes surpassing or falling short of PLA. However, disinfected disks had lower overall CFU averages than those that were not, but the level of disinfection was variable, and bacterial populations recovered hours after disinfection application. Proper disinfection and using appropriate 3D-printed materials are essential to limit bacterial contamination. 3D printers and their products can be invaluable for hospitals, especially when supplies are low, and healthcare worker safety is paramount. Environmental services should be made aware of the presence of antimicrobial 3D-printed materials, and patients should be discouraged from printing their own items for use in hospital environments.
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Prior studies suggest that population heterogeneity in SARS-CoV-2 (COVID-19) transmission plays an important role in epidemic dynamics. During the fall of 2020, many US universities and the surrounding communities experienced an increase in reported incidence of SARS-CoV-2 infections, with a high disease burden among students. We explore the transmission dynamics of an outbreak of SARS-CoV-2 among university students, how it impacted the non-student population via cross-transmission, and how it could influence pandemic planning and response. Using surveillance data of reported SARS-CoV-2 cases, we developed a two-population SEIR model to estimate transmission parameters and evaluate how these subpopulations interacted during the 2020 Fall semester. We estimated the transmission rate among the university students (ßU) and community residents (ßC), as well as the rate of cross-transmission between the two subpopulations (ßM) using particle Markov Chain Monte Carlo (pMCMC) simulation-based methods. We found that both populations were more likely to interact with others in their population and that cross-transmission was minimal. The cross-transmission estimate (ßM) was considerably smaller [0.04 × 10-5 (95% CI: 0.00 × 10-5, 0.15 × 10-5)] compared to the community estimate (ßC) at 2.09 × 10-5 (95% CI: 1.12 × 10-5, 2.90 × 10-5) and university estimate (ßU) at 27.92 × 10-5 (95% CI: 19.97 × 10-5, 39.15 × 10-5). The higher within population transmission rates among the university and the community (698 and 52 times higher, respectively) when compared to the cross-transmission rate, suggests that these two populations did not transmit between each other heavily, despite their geographic overlap. During the first wave of the pandemic, two distinct epidemics occurred among two subpopulations within a relatively small US county population where university students accounted for roughly 41% of the total population. Transmission parameter estimates varied substantially with minimal or no cross-transmission between the subpopulations. Assumptions that county-level and other small populations are well-mixed during a respiratory viral pandemic should be reconsidered. More granular models reflecting overlapping subpopulations may assist with better-targeted interventions for local public health and healthcare facilities.
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Background: Recent epidemiology of Rift Valley fever (RVF) disease in Africa suggests growing frequency and expanding geographic range of small disease clusters in regions that previously had not reported the disease. We investigated factors associated with the phenomenon by characterizing recent RVF disease events in East Africa. Methods: Data on 100 disease events (2008 - 2022) from Kenya, Uganda, and Tanzania were obtained from public databases and institutions, and modeled against possible geo-ecological risk factors of occurrence including altitude, soil type, rainfall/precipitation, temperature, normalized difference vegetation index (NDVI), livestock production system, land-use change, and long-term climatic variations. Decadal climatic variations between 1980-2022 were evaluated for association with the changing disease pattern. Results: Of 100 events, 91% were small RVF clusters with a median of one human (IQR, 1-3) and 3 livestock cases (IQR, 2-7). These clusters exhibited minimal human mortality (IQR 0-1), and occurred primarily in highlands (67%), with 35% reported in areas that had never reported RVF disease. Multivariate regression analysis of geo-ecological variables showed a positive correlation between occurrence and increasing temperature and rainfall. A 1oC increase in temperature and 1-unit increase in NDVI, 1-3 months prior were associated with increased RVF incidence rate ratios (IRR) of 1.20 (95% CI 1.1,1.2) and 9.88 (95% CI 0.85, 119.52), respectively. Long-term climatic trends showed significant decadal increase in annual mean temperature (0.12 to 0.3oC/decade, P<0.05), associated with decreasing rainfall in arid and semi-arid lowlands but increasing rainfall trends in highlands (P<0.05). These hotter and wetter highlands showed increasing frequency of RVF clusters, accounting for 76% and 43% in Uganda and Kenya, respectively. Conclusion: These findings demonstrate the changing epidemiology of RVF disease. The widening geographic range of disease is associated with climatic variations, with the likely impact of wider dispersal of virus to new areas of endemicity and future epidemics. Key questions: What is already known on this topic?: Rift Valley fever is recognized for its association with heavy rainfall, flooding, and El Niño rains in the East African region. A growing body of recent studies has highlighted a shifting landscape of the disease, marked by an expanding geographic range and an increasing number of small RVF clusters.What this study adds: This study challenges previous beliefs about RVF, revealing that it predominantly occurs in small clusters rather than large outbreaks, and its association with El Niño is not as pronounced as previously thought. Over 65% of these clusters are concentrated in the highlands of Kenya and Uganda, with 35% occurring in previously unaffected regions, accompanied by an increase in temperature and total rainfall between 1980 and 2022, along with a rise in the annual number of rainy days. Notably, the observed rainfall increases are particularly significant during the short-rains season (October-December), aligning with a secondary peak in RVF incidence. In contrast, the lowlands of East Africa, where typical RVF epidemics occur, display smaller and more varied trends in annual rainfall.How this study might affect research, practice, or policy: The worldwide consequence of the expanding RVF cluster is the broader dispersion of the virus, leading to the establishment of new regions with virus endemicity. This escalation heightens the risk of more extensive extreme-weather-associated RVF epidemics in the future. Global public health institutions must persist in developing preparedness and response strategies for such scenarios. This involves the creation and approval of human RVF vaccines and therapeutics, coupled with a rapid distribution plan through regional banks.
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BACKGROUND: Recent epidemiology of Rift Valley fever (RVF) disease in Africa suggests growing frequency and expanding geographic range of small disease clusters in regions that previously had not reported the disease. We investigated factors associated with the phenomenon by characterising recent RVF disease events in East Africa. METHODS: Data on 100 disease events (2008-2022) from Kenya, Uganda and Tanzania were obtained from public databases and institutions, and modelled against possible geoecological risk factors of occurrence including altitude, soil type, rainfall/precipitation, temperature, normalised difference vegetation index (NDVI), livestock production system, land-use change and long-term climatic variations. Decadal climatic variations between 1980 and 2022 were evaluated for association with the changing disease pattern. RESULTS: Of 100 events, 91% were small RVF clusters with a median of one human (IQR, 1-3) and three livestock cases (IQR, 2-7). These clusters exhibited minimal human mortality (IQR, 0-1), and occurred primarily in highlands (67%), with 35% reported in areas that had never reported RVF disease. Multivariate regression analysis of geoecological variables showed a positive correlation between occurrence and increasing temperature and rainfall. A 1°C increase in temperature and a 1-unit increase in NDVI, one months prior were associated with increased RVF incidence rate ratios of 1.20 (95% CI 1.1, 1.2) and 1.93 (95% CI 1.01, 3.71), respectively. Long-term climatic trends showed a significant decadal increase in annual mean temperature (0.12-0.3°C/decade, p<0.05), associated with decreasing rainfall in arid and semi-arid lowlands but increasing rainfall trends in highlands (p<0.05). These hotter and wetter highlands showed increasing frequency of RVF clusters, accounting for 76% and 43% in Uganda and Kenya, respectively. CONCLUSION: These findings demonstrate the changing epidemiology of RVF disease. The widening geographic range of disease is associated with climatic variations, with the likely impact of wider dispersal of virus to new areas of endemicity and future epidemics.
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Mudança Climática , Febre do Vale de Rift , Febre do Vale de Rift/epidemiologia , Humanos , Animais , África Oriental/epidemiologia , Gado , Fatores de Risco , Uganda/epidemiologia , Análise por Conglomerados , Surtos de Doenças , Quênia/epidemiologiaRESUMO
Background: Pregnancy is associated with a higher risk of adverse symptoms and outcomes for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection for both mother and neonate. Antibodies can provide protection against SARS-CoV-2 infection and are induced in pregnant women after vaccination or infection. Passive transfer of these antibodies from mother to fetus in utero may provide protection to the neonate against infection. However, it is unclear whether the magnitude or quality and kinetics of maternally derived fetal antibodies differs in the context of maternal infection or vaccination. Objective: We aimed to determine whether antibodies transferred from maternal to fetus differed in quality or quantity between infection- or vaccination-induced humoral immune responses. Methods: We evaluated 93 paired maternal and neonatal umbilical cord blood plasma samples collected between October 2020 and February 2022 from a birth cohort of pregnant women from New Orleans, Louisiana, with histories of SARS-CoV-2 infection and/or vaccination. Plasma was profiled for the levels of spike-specific antibodies and induction of antiviral humoral immune functions, including neutralization and Fc-mediated innate immune effector functions. Responses were compared between 4 groups according to maternal infection and vaccination. Results: We found that SARS-CoV-2 vaccination or infection during pregnancy increased the levels of antiviral antibodies compared to naive subjects. Vaccinated mothers and cord samples had the highest anti-spike antibody levels and antiviral function independent of the time of vaccination during pregnancy. Conclusions: These results show that the most effective passive transfer of functional antibodies against SARS-CoV-2 in utero is achieved through vaccination, highlighting the importance of vaccination in pregnant women.
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Purpose of Review: Preparing for pandemics requires a degree of interdisciplinary work that is challenging under the current paradigm. This review summarizes the challenges faced by the field of pandemic science and proposes how to address them. Recent Findings: The structure of current siloed systems of research organizations hinders effective interdisciplinary pandemic research. Moreover, effective pandemic preparedness requires stakeholders in public policy and health to interact and integrate new findings rapidly, relying on a robust, responsive, and productive research domain. Neither of these requirements are well supported under the current system. Summary: We propose a new paradigm for pandemic preparedness wherein interdisciplinary research and close collaboration with public policy and health practitioners can improve our ability to prevent, detect, and treat pandemics through tighter integration among domains, rapid and accurate integration, and translation of science to public policy, outreach and education, and improved venues and incentives for sustainable and robust interdisciplinary work.
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A number of key processes in evolution are driven by individuals preferring mates with particular phenotypes. However, despite long-standing interest, it is difficult to quantify the strength of mate preference from phenotypic observations in nature in a way that connects directly to key parameters in theoretical models. To bridge the gap between mathematical models and empirical data, we develop a novel maximum likelihood-based method to estimate the strength and form of mate preference, where preference depends on traits expressed in both males and females. Using simulated data, we demonstrate that our method accurately infers model parameters, including the strength of mate preference and the optimal offset match between trait values in mated pairs when model assumptions are satisfied. Applying our method to two previous studies of assortative mating in marine gastropods and the European common frog, we support previous findings, but also give additional insight into the role of mate preference in each system. Our method can be generalized to a variety of plant and animal taxa that exhibit mating preferences to facilitate the testing of evolutionary hypotheses and link empirical data to theoretical models of assortative mating, sexual selection, and speciation.
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Preferência de Acasalamento Animal , Animais , Feminino , Humanos , Funções Verossimilhança , Masculino , Fenótipo , ReproduçãoRESUMO
Although inbreeding depression affects survival, fitness and population viability, the extent of inbreeding depression in wild populations remains unclear. We examined inbreeding depression in the small, isolated National Bison Range (NBR), MT, pronghorn (Antilocapra americana) population following a bottleneck. We have studied the National Bison Range pronghorn extensively since 1981, and we have detailed birth, survival and mate choice data. We genotyped all animals in the population between 1999 and 2010 at 19 microsatellite loci, assigned paternities to all fawns based on genotype and constructed a genetic-based pedigree to calculate inbreeding coefficients (f). We found an increase in the frequency of inbreeding following the bottleneck. We detected evidence of inbreeding depression on fawn survival to weaning, birth mass, foot length and condition. We estimated the number of diploid lethal equivalents on survival to weaning as 24.17-28.72. Standardized heterozygosity (H) had a relatively small influence on survival, mass, length and condition compared with f, and H was not correlated with f. We conclude that for pronghorn, H was not a good predictor of pedigree-estimates of f.