Search

IntroductionClinical research in Alzheimer's disease (AD) lacks cohort diversity despite being a global health crisis. The Asian Cohort for Alzheimer's Disease (ACAD) was formed to address underrepresentation of Asians in research, and limited understanding of how genetics and non-genetic/lifestyle factors impact this multi-ethnic population.MethodsThe ACAD started fully recruiting in October 2021 with one central coordination site, eight recruitment sites, and two analysis sites. We developed a comprehensive study protocol for outreach and recruitment, an extensive data collection packet, and a centralized data management system, in English, Chinese, Korean, and Vietnamese.ResultsACAD has recruited 606 participants with an additional 900 expressing interest in enrollment since program inception.DiscussionACAD's traction indicates the feasibility of recruiting Asians for clinical research to enhance understanding of AD risk factors. ACAD will recruit > 5000 participants to identify genetic and non-genetic/lifestyle AD risk factors, establish blood biomarker levels for AD diagnosis, and facilitate clinical trial readiness.HighlightsThe Asian Cohort for Alzheimer's Disease (ACAD) promotes awareness of under-investment in clinical research for Asians. We are recruiting Asian Americans and Canadians for novel insights into Alzheimer's disease. We describe culturally appropriate recruitment strategies and data collection protocol. ACAD addresses challenges of recruitment from heterogeneous Asian subcommunities. We aim to implement a successful recruitment program that enrolls across three Asian subcommunities.

Neurons' primary function is to encode and transmit information in the brain and body. The branching architecture of axons and dendrites must compute, respond and make decisions while obeying the rules of the substrate in which they are enmeshed. Thus, it is important to delineate and understand the principles that govern these branching patterns. Here, we present evidence that asymmetric branching is a key factor in understanding the functional properties of neurons. First, we derive novel predictions for asymmetric scaling exponents that encapsulate branching architecture associated with crucial principles such as conduction time, power minimization and material costs. We compare our predictions with extensive data extracted from images to associate specific principles with specific biophysical functions and cell types. Notably, we find that asymmetric branching models lead to predictions and empirical findings that correspond to different weightings of the importance of maximum, minimum or total path lengths from the soma to the synapses. These different path lengths quantitatively and qualitatively affect energy, time and materials. Moreover, we generally observe that higher degrees of asymmetric branching-potentially arising from extrinsic environmental cues and synaptic plasticity in response to activity-occur closer to the tips than the soma (cell body).

IntroductionFilipino Americans are one of the largest Asian American and Pacific Islander (AAPI) populations in the United States (US). Previous studies suggest that Filipino Americans have one of the highest incidence rates of Alzheimer's disease and related dementias (ADRD) among AAPI subgroups. Despite the expected increase in Filipino Americans with ADRD, no studies to-date have validated neuropsychological measures in the United States for speakers of Tagalog, a major language spoken by Filipino Americans. A significant barrier to dementia care and diagnosis is the lack of linguistically and socioculturally appropriate cognitive tasks for Tagalog speakers. To address this need, we developed and piloted the Cognitive Assessment for Tagalog Speakers (CATS), the first neuropsychological battery for the detection of ADRD in Filipino American Tagalog speakers.MethodsBased on evidence-based neuropsychological batteries, we adapted and constructed de novo tasks to measure performance across 4 main cognitive domains: visual/verbal memory, visuospatial functioning, speech and language, and frontal/executive functioning. Tasks were developed with a team of bilingual English/Tagalog, bicultural Filipino American/Canadian experts, including a neurologist, speech-language pathologist, linguist, and neuropsychologist. We recruited Tagalog-speaking participants of age 50+ through social media advertisements and recruitment registries for this cross-sectional study. We present the CATS design and protocol.ResultsTo-date, the CATS battery has been administered to 26 healthy control participants (age 64.5 ± 7.8 years, 18F/8 M) at an academic institution in Northern California, United States. The development and administration of the CATS battery demonstrated its feasibility but also highlighted the need to consider the effects of bilingualism, language typology, and cultural factors in result interpretation.DiscussionThe CATS battery provides a mechanism for cognitive assessment of Filipino Americans, a population that has been underrepresented in ADRD research. As we move toward the treatment and cure of ADRD, linguistically and socioculturally appropriate cognitive tests become even more important for equitable care.

ObjectivesThis scoping review aims to examine the caregiving experiences of Korean American caregivers of persons with dementia.MethodsA comprehensive electronic search was conducted within 5 databases (PubMed, CINAHL, Web of Science, Embase, PsycINFO-ProQuest) for papers published from 01/01/00 -01/24/22. Seventeen articles met the inclusion criteria. Thematic analysis was used to summarize key findings from these papers.ResultsMost Korean American dementia caregivers were immigrants and wives/daughters/daughters-in-law. Two themes emerged: 1) how Korean American caregivers perceived their caregiving experiences, and 2) how Korean American caregivers perceived their caregiving support services. Korean American caregivers often experience poor mental health and burden. Social support and familism were found to be two of the most important factors that determine their attitudes toward caregiving. Most reported barriers to utilizing public services. Challenges in finding culturally relevant resources were common.ConclusionsDementia caregiving is a significant public health problem facing Korean Americans. Recommendations for future research are provided.

IntroductionClinical research focused on aging, Alzheimer's disease and related dementias (ADRD), and caregiving often does not recruit Asian Americans and Pacific Islanders (AAPIs).MethodsWith funding from the National Institute on Aging, we designed and launched the Collaborative Approach for AAPIs Research and Education (CARE), a research recruitment registry to increase AAPIs' participation in ADRD, aging, and caregiving research. We present the design of this novel recruitment program.ResultsCARE uses community-based participatory research methods that are culturally and linguistically appropriate. Since CARE's launch, it has enrolled >7000 AAPIs in a 1-year period. The majority enrolled in CARE via community organizations and reported never having participated in any kind of research before. CARE also engages researchers by establishing a recruitment referral request protocol.DiscussionCARE provides a promising venue to foster meaningful inclusion of AAPIs who are under-represented in aging and dementia-related research.

Neurons are connected by complex branching processes-axons and dendrites-that process information for organisms to respond to their environment. Classifying neurons according to differences in structure or function is a fundamental part of neuroscience. Here, by constructing biophysical theory and testing against empirical measures of branching structure, we develop a general model that establishes a correspondence between neuron structure and function as mediated by principles such as time or power minimization for information processing as well as spatial constraints for forming connections. We test our predictions for radius scale factors against those extracted from neuronal images, measured for species that range from insects to whales, including data from light and electron microscopy studies. Notably, our findings reveal that the branching of axons and peripheral nervous system neurons is mainly determined by time minimization, while dendritic branching is determined by power minimization. Our model also predicts a quarter-power scaling relationship between conduction time delay and body size.

Reports of escalated discrimination among Asian Americans and Pacific Islanders (AAPIs) due to COVID-19 are alarming, making this a public health priority. However, there are limited empirical studies on the scope and impact of COVID-19-related discrimination among AAPIs. Using the COVID-19 Effects on the Mental and Physical Health of AAPI Survey Study (COMPASS) data (N = 4971; survey period: October 2020-February 2021), which is a U.S.-wide multi-lingual survey, we examined the prevalence of, and factors associated with discrimination experiences attributable to being an AAPI during the COVID-19 pandemic. Overall, 60.7% reported experiencing discrimination; the group prevalence ranged from 80.0% (Hmong) to 40.5% (Native Hawaiians and Pacific Islanders). Multivariable logistic regression models revealed that COVID-19-related factors were associated with many discrimination experiences: having a shelter-in-place order of ≥1 month, living in areas with perceived similar/higher COVID-19 severity, and negative impact in family income/employment due to COVID-19. Additionally, being Asian American (versus Native Hawaiians and Pacific Islanders), females, non-heterosexuals, younger, more severe effect on family income, living in the non-West, and poorer health were significantly correlated with discrimination experiences. Findings may assist in formulating anti-AAPI-discrimination policies and programs at the local, state, and federal levels. Culturally appropriate programs and policies to combat this are urgently needed.

Willingness to get the COVID-19 vaccine is crucial to reduce the current strain on healthcare systems and increase herd immunity, but only 71% of the U.S. public said they would get the vaccine. It remains unclear whether Asian Americans and Pacific Islanders (AAPI), a population with existing inequalities in COVID-19 infection and mortality, are willing to get the vaccine, and the factors associated with vaccine willingness. Given this imperative, we used data from a national, cross-sectional, community-based survey called COVID-19 Effects on the Mental and Physical Health of AAPI Survey Study (COMPASS), an ongoing survey study that is available in English and Asian languages (i.e., Simplified or Traditional Chinese, Korean, Vietnamese) to examine vaccine willingness among AAPI. A total of 1,646 U.S. adult AAPI participants completed the survey. Self-reported vaccine willingness showed the proportion who were "unsure" or "probably/definitely no" to getting the COVID-19 vaccine was 25.4%. The odds for vaccine willingness were significantly lower for were Native Hawaiians and Pacific Islanders (vs. Asian Americans), Korean Americans (vs. Chinese and Vietnamese Americans), women (vs. men), heterosexuals (vs. non-heterosexuals), those aged 30-39 and 50-59 (vs. aged

Willingness to get the COVID-19 vaccine is crucial to reduce the current strain on healthcare systems and increase herd immunity, but only 71% of the U.S. public said they would get the vaccine. It remains unclear whether Asian Americans and Pacific Islanders (AAPI), a population with existing inequalities in COVID-19 infection and mortality, are willing to get the vaccine, and the factors associated with vaccine willingness. Given this imperative, we used data from a national, cross-sectional, community-based survey called COVID-19 Effects on the Mental and Physical Health of AAPI Survey Study (COMPASS), an ongoing survey study that is available in English and Asian languages (i.e., Simplified or Traditional Chinese, Korean, Vietnamese) to examine vaccine willingness among AAPI. A total of 1,646 U.S. adult AAPI participants completed the survey. Self-reported vaccine willingness showed the proportion who were "unsure" or "probably/definitely no" to getting the COVID-19 vaccine was 25.4%. The odds for vaccine willingness were significantly lower for were Native Hawaiians and Pacific Islanders (vs. Asian Americans), Korean Americans (vs. Chinese and Vietnamese Americans), women (vs. men), heterosexuals (vs. non-heterosexuals), those aged 30-39 and 50-59 (vs. aged

Temperature variation-through time and across climatic gradients-affects individuals, populations, and communities. Yet how the thermal response of biological systems is altered by environmental stressors is poorly understood. Here, we quantify two key features-optimal temperature and temperature breadth-to investigate how temperature responses vary in the presence of antibiotics. We use high-throughput screening to measure growth of Escherichia coli under single and pairwise combinations of 12 antibiotics across seven temperatures that range from 22°C to 46°C. We find that antibiotic stress often results in considerable changes in the optimal temperature for growth and a narrower temperature breadth. The direction of the optimal temperature shifts can be explained by the similarities between antibiotic-induced and temperature-induced damage to the physiology of the bacterium. We also find that the effects of pairs of stressors in the temperature response can often be explained by just one antibiotic out of the pair. Our study has implications for a general understanding of how ecological systems adapt and evolve to environmental changes. IMPORTANCE The growth of living organisms varies with temperature. This dependence is described by a temperature response curve that is described by an optimal temperature where growth is maximized and a temperature range (termed breadth) across which the organism can grow. Because an organism's temperature response evolves or acclimates to its environment, it is often assumed to change over only evolutionary or developmental timescales. Counter to this, we show here that antibiotics can quickly (over hours) change the optimal growth temperature and temperature breadth for the bacterium Escherichia coli. Moreover, our results suggest a shared-damage hypothesis: when an antibiotic damages similar cellular components as hot (or cold) temperatures do, this shared damage will combine and compound to more greatly reduce growth when that antibiotic is administered at hot (or cold) temperatures. This hypothesis could potentially also explain how temperature responses are modified by stressors other than antibiotics.

Branching in vascular networks and in overall organismic form is one of the most common and ancient features of multicellular plants, fungi and animals. By combining machine-learning techniques with new theory that relates vascular form to metabolic function, we enable novel classification of diverse branching networks-mouse lung, human head and torso, angiosperm and gymnosperm plants. We find that ratios of limb radii-which dictate essential biologic functions related to resource transport and supply-are best at distinguishing branching networks. We also show how variation in vascular and branching geometry persists despite observing a convergent relationship across organisms for how metabolic rate depends on body mass.

Sleep serves disparate functions, most notably neural repair, metabolite clearance and circuit reorganization. Yet the relative importance remains hotly debated. Here, we create a novel mechanistic framework for understanding and predicting how sleep changes during ontogeny and across phylogeny. We use this theory to quantitatively distinguish between sleep used for neural reorganization versus repair. Our findings reveal an abrupt transition, between 2 and 3 years of age in humans. Specifically, our results show that differences in sleep across phylogeny and during late ontogeny (after 2 or 3 years in humans) are primarily due to sleep functioning for repair or clearance, while changes in sleep during early ontogeny (before 2 or 3 years) primarily support neural reorganization and learning. Moreover, our analysis shows that neuroplastic reorganization occurs primarily in REM sleep but not in NREM. This developmental transition suggests a complex interplay between developmental and evolutionary constraints on sleep.

Understanding how stressors combine to affect population abundances and trajectories is a fundamental ecological problem with increasingly important implications worldwide. Generalisations about interactions among stressors are challenging due to different categorisation methods and how stressors vary across species and systems. Here, we propose using a newly introduced framework to analyse data from the last 25 years on ecological stressor interactions, for example combined effects of temperature, salinity and nutrients on population survival and growth. We contrast our results with the most commonly used existing method - analysis of variance (ANOVA) - and show that ANOVA assumptions are often violated and have inherent limitations for detecting interactions. Moreover, we argue that rescaling - examining relative rather than absolute responses - is critical for ensuring that any interaction measure is independent of the strength of single-stressor effects. In contrast, non-rescaled measures - like ANOVA - find fewer interactions when single-stressor effects are weak. After re-examining 840 two-stressor combinations, we conclude that antagonism and additivity are the most frequent interaction types, in strong contrast to previous reports that synergy dominates yet supportive of more recent studies that find more antagonism. Consequently, measuring and re-assessing the frequency of stressor interaction types is imperative for a better understanding of how stressors affect populations.

Dynamical shifts between the extremes of stability and collapse are hallmarks of ecological systems. These shifts are limited by and change with biodiversity, complexity, and the topology and hierarchy of interactions. Most ecological research has focused on identifying conditions for a system to shift from stability to any degree of instability-species abundances do not return to exact same values after perturbation. Real ecosystems likely have a continuum of shifting between stability and collapse that depends on the specifics of how the interactions are structured, as well as the type and degree of disturbance due to environmental change. Here we map boundaries for the extremes of strict stability and collapse. In between these boundaries, we find an intermediate regime that consists of single-species extinctions, which we call the extinction continuum. We also develop a metric that locates the position of the system within the extinction continuum-thus quantifying proximity to stability or collapse-in terms of ecologically measurable quantities such as growth rates and interaction strengths. Furthermore, we provide analytical and numerical techniques for estimating our new metric. We show that our metric does an excellent job of capturing the system's behaviour in comparison with other existing methods-such as May's stability criteria or critical slowdown. Our metric should thus enable deeper insights about how to classify real systems in terms of their overall dynamics and their limits of stability and collapse.

Spatially continuous data on functional diversity will improve our ability to predict global change impacts on ecosystem properties. We applied methods that combine imaging spectroscopy and foliar traits to estimate remotely sensed functional diversity in tropical forests across an Amazon-to-Andes elevation gradient (215 to 3537 m). We evaluated the scale dependency of community assembly processes and examined whether tropical forest productivity could be predicted by remotely sensed functional diversity. Functional richness of the community decreased with increasing elevation. Scale-dependent signals of trait convergence, consistent with environmental filtering, play an important role in explaining the range of trait variation within each site and along elevation. Single- and multitrait remotely sensed measures of functional diversity were important predictors of variation in rates of net and gross primary productivity. Our findings highlight the potential of remotely sensed functional diversity to inform trait-based ecology and trait diversity-ecosystem function linkages in hyperdiverse tropical forests.

PurposeThe objective of this study was to explore the perspectives of postpartum depression (PPD) and mental health help-seeking behaviors among Chinese American women.Study design and methodsUsing a qualitative design, Chinese American women, who had given birth in the past year, participated in a semistructured interview (English or Mandarin). Depressive symptoms and mental health services questionnaires were also conducted.ResultsAll 15 participants were married and between 29 and 39 years of age. Content analysis revealed two main themes including culture-specific postpartum traditions and mental health help-seeking. Nine reported sadness or PPD symptoms, including three who scored above the cutoff of the Edinburgh Postnatal Depression Scale (EPDS score ≥9) for risk of PPD and others who disclosed such information during the interview. Many women shared that they experienced postpartum depressive symptoms, but some did not believe depression was applicable to Chinese women.Clinical implicationsHealthcare professionals working with Chinese American women must be aware of culture-specific childbearing traditions to promote maternal-infant well-being outcomes.

PurposeThe objective of this study was to explore the perspectives of postpartum depression (PPD) and mental health help-seeking behaviors among Chinese American women.Study design and methodsUsing a qualitative design, Chinese American women, who had given birth in the past year, participated in a semistructured interview (English or Mandarin). Depressive symptoms and mental health services questionnaires were also conducted.ResultsAll 15 participants were married and between 29 and 39 years of age. Content analysis revealed two main themes including culture-specific postpartum traditions and mental health help-seeking. Nine reported sadness or PPD symptoms, including three who scored above the cutoff of the Edinburgh Postnatal Depression Scale (EPDS score ≥9) for risk of PPD and others who disclosed such information during the interview. Many women shared that they experienced postpartum depressive symptoms, but some did not believe depression was applicable to Chinese women.Clinical implicationsHealthcare professionals working with Chinese American women must be aware of culture-specific childbearing traditions to promote maternal-infant well-being outcomes.

Cities, wealth, and earthquakes follow continuous power-law probability distributions such as the Pareto distribution, which are canonically associated with scale-free behavior and self-similarity. However, many self-similar processes manifest as discrete steps that do not produce a continuous scale-free distribution. We construct a discrete power-law distribution that arises naturally from a simple model of hierarchical self-similar processes such as turbulence and vasculature, and we derive the maximum-likelihood estimate (MLE) for its exponent. Our distribution is self-similar, in contrast to previously studied discrete power laws such as the Zipf distribution. We show that the widely used MLE derived from the Pareto distribution leads to inaccurate estimates in systems that lack continuous scale invariance such as branching networks and data subject to logarithmic binning. We apply our MLE to data from bronchial tubes, blood vessels, and earthquakes to produce new estimates of scaling exponents and resolve contradictions among previous studies.

Much ecological research aims to explain how climate impacts biodiversity and ecosystem-level processes through functional traits that link environment with individual performance. However, the specific climatic drivers of functional diversity across space and time remain unclear due largely to limitations in the availability of paired trait and climate data. We compile and analyze a global forest dataset using a method based on abundance-weighted trait moments to assess how climate influences the shapes of whole-community trait distributions. Our approach combines abundance-weighted metrics with diverse climate factors to produce a comprehensive catalog of trait-climate relationships that differ dramatically-27% of significant results change in sign and 71% disagree on sign, significance, or both-from traditional species-weighted methods. We find that (i) functional diversity generally declines with increasing latitude and elevation, (ii) temperature variability and vapor pressure are the strongest drivers of geographic shifts in functional composition and ecological strategies, and (iii) functional composition may currently be shifting over time due to rapid climate warming. Our analysis demonstrates that climate strongly governs functional diversity and provides essential information needed to predict how biodiversity and ecosystem function will respond to climate change.

Environmental factors like temperature, pressure, and pH partly shaped the evolution of life. As life progressed, new stressors (e.g., poisons and antibiotics) arose as part of an arms race among organisms. Here we ask if cells co-opted existing mechanisms to respond to new stressors, or whether new responses evolved de novo. We use a network-clustering approach based purely on phenotypic growth measurements and interactions among the effects of stressors on population growth. We apply this method to two types of stressors-temperature and antibiotics-to discover the extent to which their cellular responses overlap in Escherichia coli. Our clustering reveals that responses to low and high temperatures are clearly separated, and each is grouped with responses to antibiotics that have similar effects to cold or heat, respectively. As further support, we use a library of transcriptional fluorescent reporters to confirm heat-shock and cold-shock genes are induced by antibiotics. We also show strains evolved at high temperatures are more sensitive to antibiotics that mimic the effects of cold. Taken together, our results strongly suggest that temperature stress responses have been co-opted to deal with antibiotic stress.

Animal social groups are complex systems that are likely to exhibit tipping points-which are defined as drastic shifts in the dynamics of systems that arise from small changes in environmental conditions-yet this concept has not been carefully applied to these systems. Here, we summarize the concepts behind tipping points and describe instances in which they are likely to occur in animal societies. We also offer ways in which the study of social tipping points can open up new lines of inquiry in behavioural ecology and generate novel questions, methods, and approaches in animal behaviour and other fields, including community and ecosystem ecology. While some behaviours of living systems are hard to predict, we argue that probing tipping points across animal societies and across tiers of biological organization-populations, communities, ecosystems-may help to reveal principles that transcend traditional disciplinary boundaries.

Antibiotics select for resistant bacteria whose existence and emergence is more likely in populations with high phenotypic and genetic diversity. Identifying the mechanisms that generate this diversity can thus have clinical consequences for drug-resistant pathogens. We show here that intermediate levels of antibiotics are associated with higher levels of phenotypic diversity in size of colony forming units (cfus), within a single bacterial population. We examine experimentally thousands of populations of bacteria subjected to different disturbance levels that are created by varying antibiotic concentrations. Based on colony sizes, we find that intermediate levels of antibiotics always result in the highest phenotypic variation of this trait. This result is supported across bacterial densities and in the presence of three different antibiotics with two different mechanisms of action. Our results suggest intermediate levels of a stressor (as opposed to very low or very high levels) could affect the phenotypic diversity of a population, at least with regards to the single trait measured here. While this study is limited to a single phenotypic trait within a single species, the results suggest examining phenotypic and genetic variation created by disturbances and stressors could be a promising way to understand and limit variation in pathogens.

Interactions and emergent processes are essential for research on complex systems involving many components. Most studies focus solely on pairwise interactions and ignore higher-order interactions among three or more components. To gain deeper insights into higher-order interactions and complex environments, we study antibiotic combinations applied to pathogenic Escherichia coli and obtain unprecedented amounts of detailed data (251 two-drug combinations, 1512 three-drug combinations, 5670 four-drug combinations, and 13608 five-drug combinations). Directly opposite to previous assumptions and reports, we find higher-order interactions increase in frequency with the number of drugs in the bacteria's environment. Specifically, as more drugs are added, we observe an elevated frequency of net synergy (effect greater than expected based on independent individual effects) and also increased instances of emergent antagonism (effect less than expected based on lower-order interaction effects). These findings have implications for the potential efficacy of drug combinations and are crucial for better navigating problems associated with the combinatorial complexity of multi-component systems.

In animals, gas exchange between blood and tissues occurs in narrow vessels, whose diameter is comparable to that of a red blood cell. Red blood cells must deform to squeeze through these narrow vessels, transiently blocking or occluding the vessels they pass through. Although the dynamics of vessel occlusion have been studied extensively, it remains an open question why microvessels need to be so narrow. We study occlusive dynamics within a model microvascular network: the embryonic zebrafish trunk. We show that pressure feedbacks created when red blood cells enter the finest vessels of the trunk act together to uniformly partition red blood cells through the microvasculature. Using mathematical models as well as direct observation, we show that these occlusive feedbacks are tuned throughout the trunk network to prevent the vessels closest to the heart from short-circuiting the network. Thus occlusion is linked with another open question of microvascular function: how are red blood cells delivered at the same rate to each micro-vessel? Our analysis shows that tuning of occlusive feedbacks increase the total dissipation within the network by a factor of 11, showing that uniformity of flows rather than minimization of transport costs may be prioritized by the microvascular network.

BackgroundIn drug-drug interactions, there are surprising cases in which the growth inhibition of bacteria by a single antibiotic decreases when a second antibiotic is added. These interactions are termed suppressive and have been argued to have the potential to limit the evolution of resistance. Nevertheless, little attention has been given to suppressive interactions because clinical studies typically search for increases in killing efficiency and because suppressive interactions are believed to be rare based on pairwise studies.ResultsHere, we quantify the effects of single-, double-, and triple-drug combinations from a set of 14 antibiotics and 3 bacteria strains, totaling 364 unique three-drug combinations per bacteria strain. We find that increasing the number of drugs can increase the prevalence of suppressive interactions: 17% of three-drug combinations are suppressive compared to 5% of two-drug combinations in this study. Most cases of suppression we find (97%) are "hidden" cases for which the triple-drug bacterial growth is less than the single-drug treatments but exceeds that of a pairwise combination.ConclusionsWe find a surprising number of suppressive interactions in higher-order drug combinations. Without examining lower-order (pairwise) bacterial growth, emergent suppressive effects would be missed, potentially affecting our understanding of evolution of resistance and treatment strategies for resistant pathogens. These findings suggest that careful examination of the full factorial of drug combinations is needed to uncover suppressive interactions in higher-order combinations.

Understanding how multiple stressors interact is needed to predict the dynamical outcomes of diverse biological systems, ranging from drug-resistant pathogens that are combated and treated with combination drug therapies to ecosystems impacted by environmental toxicants or disturbances. Nevertheless, extensive studies of higher-order (more than two component) interactions have been lacking. Here, we conduct experiments using 20 three-drug combinations and their effects on the bacterial growth of Escherichia coli We report our measurements of growth rates in single, pairwise and triple-drug combinations. To uncover emergent interactions, we derive a simple framework to calculate expectations for three-way interactions based on the measured impact of each individual stressor and of each pairwise interaction. Using our framework, we find that (i) emergent antagonisms are more common than emergent synergies and (ii) emergent antagonisms are more common and emergent synergies are more rare than would be inferred from measures of net effects that do not disentangle pairwise interactions from three-way interactions.

Modern models that derive allometric relationships between metabolic rate and body mass are based on the architectural design of the cardiovascular system and presume sibling vessels are symmetric in terms of radius, length, flow rate, and pressure. Here, we study the cardiovascular structure of the human head and torso and of a mouse lung based on three-dimensional images processed via our software Angicart. In contrast to modern allometric theories, we find systematic patterns of asymmetry in vascular branching, potentially explaining previously documented mismatches between predictions (power-law or concave curvature) and observed empirical data (convex curvature) for the allometric scaling of metabolic rate. To examine why these systematic asymmetries in vascular branching might arise, we construct a mathematical framework to derive predictions based on local, junction-level optimality principles that have been proposed to be favored in the course of natural selection and development. The two most commonly used principles are material-cost optimizations (construction materials or blood volume) and optimization of efficient flow via minimization of power loss. We show that material-cost optimization solutions match with distributions for asymmetric branching across the whole network but do not match well for individual junctions. Consequently, we also explore random branching that is constrained at scales that range from local (junction-level) to global (whole network). We find that material-cost optimizations are the strongest predictor of vascular branching in the human head and torso, whereas locally or intermediately constrained random branching is comparable to material-cost optimizations for the mouse lung. These differences could be attributable to developmentally-programmed local branching for larger vessels and constrained random branching for smaller vessels.

Cardiovascular networks span the body by branching across many generations of vessels. The resulting structure delivers blood over long distances to supply all cells with oxygen via the relatively short-range process of diffusion at the capillary level. The structural features of the network that accomplish this density and ubiquity of capillaries are often called space-filling. There are multiple strategies to fill a space, but some strategies do not lead to biologically adaptive structures by requiring too much construction material or space, delivering resources too slowly, or using too much power to move blood through the system. We empirically measure the structure of real networks (18 humans and 1 mouse) and compare these observations with predictions of model networks that are space-filling and constrained by a few guiding biological principles. We devise a numerical method that enables the investigation of space-filling strategies and determination of which biological principles influence network structure. Optimization for only a single principle creates unrealistic networks that represent an extreme limit of the possible structures that could be observed in nature. We first study these extreme limits for two competing principles, minimal total material and minimal path lengths. We combine these two principles and enforce various thresholds for balance in the network hierarchy, which provides a novel approach that highlights the tradeoffs faced by biological networks and yields predictions that better match our empirical data.

Interactions among drugs play a critical role in the killing efficacy of multi-drug treatments. Recent advances in theory and experiment for three-drug interactions enable the search for emergent interactions-ones not predictable from pairwise interactions. Previous work has shown it is easier to detect synergies and antagonisms among pairwise interactions when a rescaling method is applied to the interaction metric. However, no study has carefully examined whether new types of normalization might be needed for emergence. Here, we propose several rescaling methods for enhancing the classification of the higher order drug interactions based on our conceptual framework. To choose the rescaling that best separates synergism, antagonism and additivity, we conducted bacterial growth experiments in the presence of single, pairwise and triple-drug combinations among 14 antibiotics. We found one of our rescaling methods is far better at distinguishing synergistic and antagonistic emergent interactions than any of the other methods. Using our new method, we find around 50% of emergent interactions are additive, much less than previous reports of greater than 90% additivity. We conclude that higher order emergent interactions are much more common than previously believed, and we argue these findings for drugs suggest that appropriate rescaling is crucial to infer higher order interactions.

Whether the thermal sensitivity of an organism's traits follows the simple Boltzmann-Arrhenius model remains a contentious issue that centers around consideration of its operational temperature range and whether the sensitivity corresponds to one or a few underlying rate-limiting enzymes. Resolving this issue is crucial, because mechanistic models for temperature dependence of traits are required to predict the biological effects of climate change. Here, by combining theory with data on 1,085 thermal responses from a wide range of traits and organisms, we show that substantial variation in thermal sensitivity (activation energy) estimates can arise simply because of variation in the range of measured temperatures. Furthermore, when thermal responses deviate systematically from the Boltzmann-Arrhenius model, variation in measured temperature ranges across studies can bias estimated activation energy distributions toward higher mean, median, variance, and skewness. Remarkably, this bias alone can yield activation energies that encompass the range expected from biochemical reactions (from ~0.2 to 1.2 eV), making it difficult to establish whether a single activation energy appropriately captures thermal sensitivity. We provide guidelines and a simple equation for partially correcting for such artifacts. Our results have important implications for understanding the mechanistic basis of thermal responses of biological traits and for accurately modeling effects of variation in thermal sensitivity on responses of individuals, populations, and ecological communities to changing climatic temperatures.

Scientists have long sought to understand how vascular networks supply blood and oxygen to cells throughout the body. Recent work focuses on principles that constrain how vessel size changes through branching generations from the aorta to capillaries and uses scaling exponents to quantify these changes. Prominent scaling theories predict that combinations of these exponents explain how metabolic, growth, and other biological rates vary with body size. Nevertheless, direct measurements of individual vessel segments have been limited because existing techniques for measuring vasculature are invasive, time consuming, and technically difficult. We developed software that extracts the length, radius, and connectivity of in vivo vessels from contrast-enhanced 3D Magnetic Resonance Angiography. Using data from 20 human subjects, we calculated scaling exponents by four methods-two derived from local properties of branching junctions and two from whole-network properties. Although these methods are often used interchangeably in the literature, we do not find general agreement between these methods, particularly for vessel lengths. Measurements for length of vessels also diverge from theoretical values, but those for radius show stronger agreement. Our results demonstrate that vascular network models cannot ignore certain complexities of real vascular systems and indicate the need to discover new principles regarding vessel lengths.

Trophic cascades are indirect positive effects of predators on resources via control of intermediate consumers. Larger-bodied predators appear to induce stronger trophic cascades (a greater rebound of resource density toward carrying capacity), but how this happens is unknown because we lack a clear depiction of how the strength of trophic cascades is determined. Using consumer resource models, we first show that the strength of a trophic cascade has an upper limit set by the interaction strength between the basal trophic group and its consumer and that this limit is approached as the interaction strength between the consumer and its predator increases. We then express the strength of a trophic cascade explicitly in terms of predator body size and use two independent parameter sets to calculate how the strength of a trophic cascade depends on predator size. Both parameter sets predict a positive effect of predator size on the strength of a trophic cascade, driven mostly by the body size dependence of the interaction strength between the first two trophic levels. Our results support previous empirical findings and suggest that the loss of larger predators will have greater consequences on trophic control and biomass structure in food webs than the loss of smaller predators.

We demonstrate how path integrals often used in problems of theoreticalphysics can be adapted to provide a machinery for performing Bayesian inferencein function spaces. Such inference comes about naturally in the study ofinverse problems of recovering continuous (infinite dimensional) coefficientfunctions from ordinary or partial differential equations (ODE, PDE), a problemwhich is typically ill-posed. Regularization of these problems using $L^2$function spaces (Tikhonov regularization) is equivalent to Bayesianprobabilistic inference, using a Gaussian prior. The Bayesian interpretation ofinverse problem regularization is useful since it allows one to quantify andcharacterize error and degree of precision in the solution of inverse problems,as well as examine assumptions made in solving the problem -- namely whetherthe subjective choice of regularization is compatible with prior knowledge.Using path-integral formalism, Bayesian inference can be explored throughvarious perturbative techniques, such as the semiclassical approximation, whichwe use in this manuscript. Perturbative path-integral approaches, whileoffering alternatives to computational approaches like Markov-Chain-Monte-Carlo(MCMC), also provide natural starting points for MCMC methods that can be usedto refine approximations. In this manuscript, we illustrate a path-integral formulation for inverseproblems and demonstrate it on an inverse problem in membrane biophysics aswell as inverse problems in potential theories involving the Poisson equation.

Prenatal health care counseling is associated with positive health outcomes for mothers and infants. Moreover, pregnant women are considered a vulnerable population at risk of being victims of intimate partner violence. Pregnancy provides a unique opportunity to identify and refer women experiencing intimate partner violence to community resources; however, in prior research, most women reported that their prenatal care providers did not talk to them about intimate partner violence. Given the importance for providers to offer prenatal health care counseling on intimate partner violence, it is concerning that there is scant knowledge on Asian, Native Hawaiian, and other Pacific Islander mothers' experiences in this area. The study's objectives were (a) to determine the proportion of mothers who received prenatal health care counseling on intimate partner violence; and, (b) to examine racial differences of those who received prenatal health care counseling on intimate partner violence. Hawai'i's Pregnancy Risk Assessment Monitoring System (PRAMS) data from 2004-08 were analyzed for 8,120 mothers with information on receipt of intimate partner violence prenatal health care counseling. Overall, 47.7% of mothers were counseled on intimate partner violence. Compared to Whites, Native Hawaiians, Japanese, Chinese, and Koreans were significantly less likely to report receiving prenatal health care counseling in intimate partner violence, but the opposite association was observed for Samoans. Intimate partner violence continues to be a significant problem for women, thus, this study's findings may be used as important baseline data to measure the progress made given the implementation of the new Guidelines for Women's Preventive Services in intimate partner violence screening and counseling.

Research has documented tobacco-related health disparities by race and gender. Prior research, however, has not examined expectancies about the smoking cessation process (i.e., abstinence-related expectancies) as potential contributors to tobacco-related disparities in special populations. This cross-sectional study compared abstinence-related expectancies between American Indian (n = 87), African American (n = 151), and White (n = 185) smokers, and between women (n = 231) and men (n = 270) smokers. Abstinence-related expectancies also were examined as mediators of race and gender relationships with motivation to quit and abstinence self efficacy. Results indicated that American Indians and African Americans were less likely than Whites to expect withdrawal effects, and more likely to expect that quitting would be unproblematic. African Americans also were less likely than Whites to expect smoking cessation interventions to be effective. Compared with men, women were more likely to expect withdrawal effects and weight gain. These expectancy differences mediated race and gender relationships with motivation to quit and abstinence self-efficacy. Findings emphasize potential mechanisms underlying tobacco-related health disparities among American Indians, African Americans, and women and suggest a number of specific approaches for targeting tobacco dependence interventions to these populations.

The West, Brown, Enquist (WBE) model derives symmetrically self-similar branching to predict metabolic scaling from hydraulic conductance, K, (a metabolism proxy) and tree mass (or volume, V). The original prediction was Kα V(0.75). We ask whether trees differ from WBE symmetry and if it matters for plant function and scaling. We measure tree branching and model how architecture influences K, V, mechanical stability, light interception and metabolic scaling. We quantified branching architecture by measuring the path fraction, Pf : mean/maximum trunk-to-twig pathlength. WBE symmetry produces the maximum, Pf = 1.0. We explored tree morphospace using a probability-based numerical model constrained only by biomechanical principles. Real tree Pf ranged from 0.930 (nearly symmetric) to 0.357 (very asymmetric). At each modeled tree size, a reduction in Pf led to: increased K; decreased V; increased mechanical stability; and decreased light absorption. When Pf was ontogenetically constant, strong asymmetry only slightly steepened metabolic scaling. The Pf ontogeny of real trees, however, was 'U' shaped, resulting in size-dependent metabolic scaling that exceeded 0.75 in small trees before falling below 0.65. Architectural diversity appears to matter considerably for whole-tree hydraulics, mechanics, photosynthesis and potentially metabolic scaling. Optimal architectures likely exist that maximize carbon gain per structural investment.

The mitochondrial inner membrane contains a large protein complex that functions in inner membrane organization and formation of membrane contact sites. The complex was variably named the mitochondrial contact site complex, mitochondrial inner membrane org

The relationships between cellular, structural and dynamical properties of tumors have traditionally been studied separately. Here, we construct a quantitative, predictive theory of solid tumor growth, metabolic rate, vascularization and necrosis that integrates the relationships between these properties. To accomplish this, we develop a comprehensive theory that describes the interface and integration of the tumor vascular network and resource supply with the cardiovascular system of the host. Our theory enables a quantitative understanding of how cells, tissues, and vascular networks act together across multiple scales by building on recent theoretical advances in modeling both healthy vasculature and the detailed processes of angiogenesis and tumor growth. The theory explicitly relates tumor vascularization and growth to metabolic rate, and yields extensive predictions for tumor properties, including growth rates, metabolic rates, degree of necrosis, blood flow rates and vessel sizes. Besides these quantitative predictions, we explain how growth rates depend on capillary density and metabolic rate, and why similar tumors grow slower and occur less frequently in larger animals, shedding light on Peto's paradox. Various implications for potential therapeutic strategies and further research are discussed.

This study seeks to understand how Native Hawaiian (NH) women identified themselves culturally and conceptualized the causes of depression, and whether there was an association between these two constructs. Among the thirty NH women who were interviewed, a quarter had a high degree of depression symptoms, and a majority expressed a strong/shared identification/affinity with their culture. Our findings suggest that social stressors that contribute to the depressive symptoms of NH women could be, in part, linked to acculturation-related factors associated with U.S. occupation of Hawai‘i and their social status as native people. Future research should examine this relationship further.

BackgroundMosquito saliva, consisting of a mixture of dozens of proteins affecting vertebrate hemostasis and having sugar digestive and antimicrobial properties, helps both blood and sugar meal feeding. Culicine and anopheline mosquitoes diverged ~150 MYA, and within the anophelines, the New World species diverged from those of the Old World ~95 MYA. While the sialotranscriptome (from the Greek sialo, saliva) of several species of the Cellia subgenus of Anopheles has been described thoroughly, no detailed analysis of any New World anopheline has been done to date. Here we present and analyze data from a comprehensive salivary gland (SG) transcriptome of the neotropical malaria vector Anopheles darlingi (subgenus Nyssorhynchus).ResultsA total of 2,371 clones randomly selected from an adult female An. darlingi SG cDNA library were sequenced and used to assemble a database that yielded 966 clusters of related sequences, 739 of which were singletons. Primer extension experiments were performed in selected clones to further extend sequence coverage, allowing for the identification of 183 protein sequences, 114 of which code for putative secreted proteins.ConclusionComparative analysis of sialotranscriptomes of An. darlingi and An. gambiae reveals significant divergence of salivary proteins. On average, salivary proteins are only 53% identical, while housekeeping proteins are 86% identical between the two species. Furthermore, An. darlingi proteins were found that match culicine but not anopheline proteins, indicating loss or rapid evolution of these proteins in the old world Cellia subgenus. On the other hand, several well represented salivary protein families in old world anophelines are not expressed in An. darlingi.