Intra- and interspecific diversity in a tropical plant clade alter herbivory and ecosystem resilience.

Declines in biodiversity generated by anthropogenic stressors at both species and population levels can alter emergent processes instrumental to ecosystem function and resilience. As such, understanding the role of biodiversity in ecosystem function and its response to climate perturbation is increasingly important, especially in tropical systems where responses to changes in biodiversity are less predictable and more challenging to assess experimentally. Using large-scale transplant experiments conducted at five neotropical sites, we documented the impacts of changes in intraspecific and interspecific plant richness in the genus Piper on insect herbivory, insect richness, and ecosystem resilience to perturbations in water availability. We found that reductions of both intraspecific and interspecific Piper diversity had measurable and site-specific effects on herbivory, herbivorous insect richness, and plant mortality. The responses of these ecosystem-relevant processes to reduced intraspecific Piper richness were often similar in magnitude to the effects of reduced interspecific richness. Increased water availability reduced herbivory by 4.2% overall, and the response of herbivorous insect richness and herbivory to water availability were altered by both intra- and interspecific richness in a site-dependent manner. Our results underscore the role of intraspecific and interspecific richness as foundations of ecosystem function and the importance of community and location-specific contingencies in controlling function in complex tropical systems.

Colorimetric Scale for Skin of Color: A Practical Classification Scale for the Clinical Assessment, Dermatology Management, and Forensic Evaluation of Individuals With Skin of Color.

Skin of color refers to individuals whose skin color ranges from very light beige to very dark brown. Anthropologists and sociologists have previously recognized the importance of an objective classification of skin color for individuals with skin of color that does not include race and ethnicity. Since 1975, dermatologists have used the Fitzpatrick classification of sun-reactive skin types to categorize patients with skin of color; this classification was established for psoriasis patients participating in using oral methoxsalen and phototherapy clinical trial to determine the initial ultraviolet A dose. The Fitzpatrick classification merely classifies individuals as white, brown, and black; the individuals with white skin are further divided into four groups based on their burning or tanning capacity. This classification system does not provide reliable information with regard to the risk of skin cancer for individuals with darker skin color and does not aid in the evaluation of medical conditions with cutaneous involvement or assessment of appropriate cosmetic interventions for aesthetic management. Many clinicians, including forensic pathologists, incorporate the patient's race or ethnicity in their medical evaluation to describe the individual's skin color. Established scales for skin of color either include white skin color, or include 10 or more color types, or include both. We introduce a simple and rapidly performed scale that is not based on race or ethnicity to categorize persons with skin of color. The colorimetric scale ranges from very light beige to very dark brown and does not include white skin. The scale has five colors ranging from lightest (skin color type 1) to darkest (skin color type 5): very light beige (skin color type 1), light brown (skin color type 2), medium brown (skin color type 3), dark brown (skin color type 4), and very dark brown (skin color type 5); an individual with white skin would have a skin color type 0 in this classification of patient skin color. In conclusion, a scale that is not based on race or ethnicity is useful for categorizing individuals with skin of color not only for sociologists but also for clinicians who treat these patients. This colorimetric scale will be helpful for dermatologists to categorize persons with skin of color to predict their risk for developing skin cancer and to assessing appropriate cosmetic procedures and devices for these patients. In addition, the colorimetric scale will be useful for not only forensic pathologists but also other clinicians to provide a non-racial and non-ethnic designation of skin color type for their patients.

Facing the flames: insect responses to megafires and changing fire regimes.

The rise of megafires and extreme fire behaviors poses a significant threat to insect populations, affecting their survival and postfire recolonization. Megafires threaten the entire insect communities by changing fire regimes and habitats. These fires are now burning non-fire-prone ecosystems, endangering non-fire-adapted insects and habitats. While implementing prescribed burn programs can reduce the chances of megafires from developing, some megafires will be unpreventable. Land managers can mitigate the fire impacts by creating refugia and promoting heterogeneity in burn severity through fire control measures. Last, these post-megafire landscapes can provide an opportunity to restore historical fire regimes through subsequent prescribed burn management. This will revitalize ecosystems, benefit insects, and reduce the likelihood of future megafires and subsequent insect loss.

WITHDRAWN: I feel your pain: Higher empathy is associated with higher posterior default mode network activity.

The authors discovered an error in the primary analysis and have withdrawn the results from this version of the investigation.

Multiple and contrasting pressures determine intraspecific phytochemical variation in a tropical shrub.

Intraspecific phytochemical variation across a landscape can cascade up trophic levels, potentially mediating the composition of entire insect communities. Surprisingly, we have little understanding of the processes that regulate and maintain phytochemical variation within species, likely because these processes are complex and operate simultaneously both temporally and spatially. To assess how phytochemistry varies within species, we tested the degree to which resource availability, contrasting soil type, and herbivory generate intraspecific chemical variation in growth and defense of the tropical shrub, Piper imperiale (Piperaceae). We quantified changes in both growth (e.g., nutritional protein, above- and below-ground biomass) and defense (e.g., imide chemicals) of individual plants using a well-replicated fully factorial shade-house experiment in Costa Rica. We found that plants grown in high light, nutrient- and richer old alluvial soil had increased biomass. High light was also important for increasing foliar protein. Thus, investment into growth was determined by resource availability and soil composition. Surprisingly, we found that chemical defenses decreased in response to herbivory. We also found that changes in plant protein were more plastic compared to plant defense, indicating that constitutive defenses may be relatively fixed, and thus an adaptation to chronic herbivory that is common in tropical forests. We demonstrate that intraspecific phytochemical variation of P. imperiale is shaped by resource availability from light and soil type. Because environmental heterogeneity occurs over small spatial scales (tens of meters), herbivores may be faced with a complex phytochemical landscape that may regulate how much damage any individual plant sustains.

The relationship between ratings of perceived exertion (RPE) and relative strength for a fatiguing dynamic upper extremity task: A consideration of multiple cycles and conditions.

The goal of this study was to evaluate the relationship between ratings of perceived exertion (RPE) and relative strength with respect to baseline for a fatiguing free dynamic task targeting the upper extremity, namely simulated order picking, and determine whether the relationship remains the same for different conditions (i.e., pace and weight) and with fatigue. Fourteen participants (seven males, seven females) performed four sessions that included two 45-min work periods separated by 15 min of rest. The work periods involved picking weighted bottles from shoulder height and packaging them at waist height for four combinations of bottle mass and picking rate: 2.5 kg-15 bottles per minute (bpm), 2.5 kg-10 bpm, 2.5 kg-5 bpm, and 1.5 kg-15 bpm. Participants reported their RPEs every 5 min and performed a maximum isometric shoulder flexion exertion every 9 min. Pearson product-moment correlation was used to evaluate the linear relationship between RPE and relative strength for each subject and work period. Then, the effects of condition and work period on the average relationship were assessed using a repeated-measures analysis of variance (ANOVA). For the first 45-min period, there were no significantly different correlations between RPE and relative strength across conditions (average r = -0.62 (standard deviation = 0.38); p = 0.57). There was a significant decrease in average correlation for the second work period (r = -0.39 (0.53)). These results suggest that individual subjective responses consistently increase while relative strength declines when starting from a non-fatigued state. However, correlations are weaker when re-engaging in work following incomplete recovery. Thus, starting fatigue levels should be accounted for when considering the expected relationship between RPE and relative strength.

Food insecurity and disasters: predicting disparities in total and first-time food pantry visits during the COVID-19 pandemic.

In the U.S. state of Arizona, nearly one-third of households experienced food insecurity during the COVID-19 pandemic, an increase from one-fourth of households before the pandemic. Previous research on food insecurity in the wake of natural and human-instigated disasters demonstrates that groups vulnerable to food insecurity before a disaster are more susceptible to food insecurity during and after that disaster; however, less is known about whether this relationship also holds true during health-related disasters, such as the COVID-19 pandemic. We explore how the COVID-19 pandemic influenced urban food insecurity patterns by analyzing the socio-demographic characteristics of food pantry clients in Maricopa County, Arizona. Using data from Phoenix Rescue Mission (PRM), a local non-profit food service provider, two binomial logistic regression models compare the socio-demographic composition of total and first-time food pantry users before and during the pandemic. In addition to an overall increase in food pantry usage during the pandemic, we find that, while certain socio-demographic groups historically vulnerable to food insecurity experienced the predicted uptick in insecurity during the pandemic, other socio-demographic disparities were attenuated. These somewhat disparate findings illustrate the complex relationship between disasters and food insecurity in an urban context, offering several avenues for future research. Supplementary Information: The online version contains supplementary material available at 10.1007/s12571-022-01336-2.

Functional ANOVA for Upper Extremity Fatigue Analysis during Dynamic Order Picking.

OCCUPATIONAL APPLICATIONSMusculoskeletal disorders are prevalent among warehouse workers who engage in repetitive and dynamic tasks. To prevent such injuries, it is vital to identify the factors that influence fatigue in the upper extremities during these repetitive activities. Our study reveals that task factors, namely the bottle mass and picking rate, significantly influence upper extremity fatigue. In most cases, the fatigue indicator is a functional variable, meaning that the fatigue score or measurement is a curve captured over time, which could be modeled as a function. In this study, we demonstrate that functional data analysis tools, such as functional analysis of variance (FANOVA), prove more effective than traditional methods in specifying how task factors contribute to the development of fatigue in the upper extremities. Furthermore, since there are inherent differences among workers that could affect their fatigue development process, the data heterogeneity could be tackled by employing clustering methods.

Background: Preventing musculoskeletal disorders is a paramount safety concern for industries, with order pickers in warehouses being particularly vulnerable due to their repetitive and dynamic tasks. Understanding the factors contributing to upper-extremity fatigue in such settings is crucial. Purpose: This paper investigates the impact of task-related factors on two upper-extremity fatigue indicators: ratings of perceived fatigue and relative muscle strength. Several statistical approaches were used and compared in terms of their capability in eliciting these effects. Methods: Simulated over-shoulder, order-picking lab experiments were conducted under different combinations of two bottle loads and three picking paces. Fourteen participants, evenly distributed between genders, completed the experiment. A FANOVA was executed as the principal analytical approach, considering the functional nature of the two fatigue indicators measured over the work period. To underscore the benefits of considering the whole functional curve instead of discrete variables, we also conducted repeated-measures and two-way ANOVA as benchmark analyses. Results: FANOVA outcomes affirmed that both task factors (load and pace) significantly influenced both fatigue indicators. The FANOVA method identified larger effect sizes (0.11< ηp2 < 0.19) for both task factors compared to the conventional methods (0< ηp2 < 0.11), supporting the efficacy of FANOVA in identifying the importance of these factors. Conclusions: The FANOVA approach proved effective in detecting the impact of task factors on fatigue indicators, yielding superior results compared to conventional benchmark methods. To address participant heterogeneity, functional clustering and gender-based clustering were introduced into the FANOVA framework, both effectively mitigating this challenge. Notably, FANOVA with functional clusters had superior performance compared to the one with gender clustering, suggesting functional clustering as a more suitable method in overcoming participant heterogeneity.

A hydrodynamic model-based approach to assess sampling approaches for dissolved oxygen criteria in the Chesapeake Bay.

Technological advances in water quality measurement systems have provided the potential to expand high-frequency observations into coastal monitoring programs. However, with limited resources for monitoring budgets in natural waters that exhibit high temporal and spatial variability in water quality, there is a need to identify the locations and time periods where these new technologies can be deployed for maximum efficacy. To advance the capacity to make quantitative and objective decisions on the selection of monitoring locations and sampling frequency, we combined high-resolution numerical model simulations and multi-frequency water quality measurements to conduct a power analysis comparing alternative sampling designs in the assessment of water quality in the Chesapeake Bay. Specifically, we evaluated candidate monitoring networks that deployed both conventional long-term fixed station monitoring in deep channel areas and short-term continuous monitoring technologies in near-shore, shallow areas to assess 30-day dissolved oxygen criteria in two Bay tributaries. We conducted a cumulative frequency diagrams analysis to quantify the accuracy of each monitoring scheme in evaluating compliance with respect to the model. We used a Monte Carlo simulation to incorporate the spatial and temporal uncertainty of criteria failure. We found that additional long-term biweekly channel and short-term continuous shallow sampling efforts can lead to statistically unbiased and improved assessments at local spatial extents (less than 0.2 proportion of the assessed water body), especially when additional sampling is added at stations representing hypoxic water areas. Stations that represented seaward regions of the tributaries were more valuable in maintaining unbiased assessments of dissolved oxygen criteria attainment. This analysis highlights the importance of statistical evaluation of ongoing monitoring programs and suggests an approach to identify efficient deployments of monitoring resources and to improve assessment of other water quality metrics in estuarine ecosystems.

Adjustments in Shoulder and Back Kinematics during Repetitive Palletizing Tasks.

Repetitive task performance is a leading cause of musculoskeletal injuries among order-picking workers in warehouses. The repetition of lifting tasks increases the risk of back and shoulder injuries among these workers. While lifting in this industry is composed of loaded and unloaded picking and placing, the existing literature does not address the separate analysis of the biomechanics of the back and shoulder for these events. To that end, we investigated the kinematics of the back and shoulder movements of nine healthy male participants who performed three sessions of a simulated de/palletization task. Their back and shoulder kinematics were sensed using an optical motion capture system to determine the back inclination and shoulder flexion. Comparison of the kinematics between the first and last sessions indicated statistically significant changes in the timings, angles, coordination between the back and shoulder, and moments around the shoulder (p<0.05). The majority of the significant changes were observed during the loaded events, which confirms the importance of the separation of these events for biomechanical analysis. This finding suggests that focusing worker evaluation on the loaded periods can provide important information to detect kinematic changes that may affect musculoskeletal injury risk.

Climate change winners and losers among North American bumblebees.

Mounting evidence suggests that climate change, agricultural intensification and disease are impacting bumblebee health and contributing to species' declines. Identifying how these factors impact insect communities at large spatial and temporal scales is difficult, partly because species may respond in different ways. Further, the necessary data must span large spatial and temporal scales, which usually means they comprise aggregated, presence-only records collected using numerous methods (e.g. diversity surveys, educational collections, citizen-science projects, standardized ecological surveys). Here, we use occupancy models, which explicitly correct for biases in the species observation process, to quantify the effect of changes in temperature, precipitation and floral resources on bumblebee site occupancy over the past 12 decades in North America. We find no evidence of genus-wide declines in site occupancy, but do find that occupancy is strongly related to temperature, and is only weakly related to precipitation or floral resources. We also find that more species are likely to be climate change 'losers' than 'winners' and that this effect is primarily associated with changing temperature. Importantly, all trends were highly species-specific, highlighting that genus or community-wide measures may not reflect diverse species-specific patterns that are critical in guiding allocation of conservation resources.

The chemical ecology of tropical forest diversity: Environmental variation, chemical similarity, herbivory, and richness.

Species richness in tropical forests is correlated with other dimensions of diversity, including the diversity of plant-herbivore interactions and the phytochemical diversity that influences those interactions. Understanding the complexity of plant chemistry and the importance of phytochemical diversity for plant-insect interactions and overall forest richness has been enhanced significantly by the application of metabolomics to natural systems. The present work used proton nuclear magnetic resonance spectroscopy (1 H-NMR) profiling of crude leaf extracts to study phytochemical similarity and diversity among Piper plants growing naturally in the Atlantic Rainforest of Brazil. Spectral profile similarity and chemical diversity were quantified to examine the relationship between metrics of phytochemical diversity, specialist and generalist herbivory, and understory plant richness. Herbivory increased with understory species richness, while generalist herbivory increased and specialist herbivory decreased with the diversity of Piper leaf material available. Specialist herbivory increased when conspecific host plants were more spectroscopically dissimilar. Spectral similarity was lower among individuals of common species, and they were also more spectrally diverse, indicating phytochemical diversity is beneficial to plants. Canopy openness and soil nutrients also influenced chemistry and herbivory. The complex relationships uncovered in this study add information to our growing understanding of the importance of phytochemical diversity for plant-insect interactions and tropical plant species richness.

A data analytic end-to-end framework for the automated quantification of ergonomic risk factors across multiple tasks using a single wearable sensor.

Existing ergonomic risk assessment tools require monitoring of multiple risk factors. To eliminate the direct observation, we investigated the effectiveness of an end-to-end framework that works with the data from a single wearable sensor. The framework is used to identify the performed task as the major contextual risk factor, and then estimate the task duration and number of repetitions as two main indicators of task intensity. For evaluation of the framework, we recruited 37 participants to complete 10 simulated work tasks in a laboratory setting. In testing, we achieved an average accuracy of 92% for task identification, 7.3% error in estimation of task duration, and 7.1% error for counting the number of task repetitions. Moreover, we showed the utility of the framework outputs in two ergonomic tools to estimate the risk of injury. Overall, we indicated the feasibility of using data from wearable sensors to automate the ergonomic risk assessment in workplaces.

Mobile Pantries Can Serve the Most Food Insecure Populations.

Purpose: Food insecurity is an urgent crisis in the United States, with one in nine people lacking a consistent source of the food necessary for an active and healthy lifestyle. This crisis is particularly dire in Maricopa County, Arizona, where 1 in 5 children experience food insecurity, and >1 in 10 residents experience poverty. Mobile food pantries offer an additional resource to address food insecurity; however, there is minimal knowledge about how communities utilize these food distributors. Background: Research on the elderly (people >60 years) and immigrant populations shows that these populations are especially vulnerable to food insecurity. The risk these groups face is compounded in Maricopa County, the 15th largest county in the country with minimal public transit to extant resources. Mobile food pantries offer one solution to this issue, bringing groceries and other important items directly to communities. Methods: This study utilizes data from a food pantry called "Phoenix Rescue Mission" (PRM) on food insecure people's use of PRM's mobile and brick-and-mortar pantries, as well as census data. Using GIS mapping and a multinomial logistic regression model, this research identifies how different demographic groups engage with PRM's brick-and-mortar or mobile pantries. Results: Findings indicate that people aged 60-80 years and immigrant people of color are more likely to use both mobile and brick-and-mortar pantries. Conclusions: This research suggests that mobile pantries can reach the most food insecure populations and local nonprofits and governments can consider implementing mobile pantries to reach food insecure communities.

Memory Gaps in America: Mutational and Immunoinformatic Analysis of Evolving SARS-CoV-2 Variants of Concern and Interest.

The perpetuation of the SARS-CoV-2 pandemic has permitted the continued evolution of mutations, many of which appear to promote infectivity, transmission, and immune evasion. Critically, several derivative lineages defined as variants of concern (VOCs) and variants of interest (VOIs) have emerged in the last year that possess a constellation of highly adaptive mutations that have resulted in unprecedented propagation. To better understand the significance of these mutations, we analyzed their molecular and immunological consequences against the immunogenetic profile of the United States population using immunoinformatics to analyze in silico data. Our findings indicate that several evolving mutations in the VOCs and VOIs appear to confer immune evasion properties leading to antigenic drift, specifically for Ab-mediated and Th cell-mediated immune recognition, whereas mutations leading to evasion from innate immune mechanisms are less common in the more successful VOC strains compared with the VOIs. Importantly, several of these mutations raise concerns for the effectiveness of anamnestic responses achieved through natural infection and vaccination as well as for the utility of Ab-based therapeutic interventions. The emergence of such adaptations underscores the need for vaccine enhancements as well as the continued need to for preventative hygiene measures to help minimize transmission.

Advancing precision medicine for acute respiratory distress syndrome.

Acute respiratory distress syndrome (ARDS) is a heterogeneous clinical syndrome. Understanding of the complex pathways involved in lung injury pathogenesis, resolution, and repair has grown considerably in recent decades. Nevertheless, to date, only therapies targeting ventilation-induced lung injury have consistently proven beneficial, and despite these gains, ARDS morbidity and mortality remain high. Many candidate therapies with promise in preclinical studies have been ineffective in human trials, probably at least in part due to clinical and biological heterogeneity that modifies treatment responsiveness in human ARDS. A precision medicine approach to ARDS seeks to better account for this heterogeneity by matching therapies to subgroups of patients that are anticipated to be most likely to benefit, which initially might be identified in part by assessing for heterogeneity of treatment effect in clinical trials. In October 2019, the US National Heart, Lung, and Blood Institute convened a workshop of multidisciplinary experts to explore research opportunities and challenges for accelerating precision medicine in ARDS. Topics of discussion included the rationale and challenges for a precision medicine approach in ARDS, the roles of preclinical ARDS models in precision medicine, essential features of cohort studies to advance precision medicine, and novel approaches to clinical trials to support development and validation of a precision medicine strategy. In this Position Paper, we summarise workshop discussions, recommendations, and unresolved questions for advancing precision medicine in ARDS. Although the workshop took place before the COVID-19 pandemic began, the pandemic has highlighted the urgent need for precision therapies for ARDS as the global scientific community grapples with many of the key concepts, innovations, and challenges discussed at this workshop.

Neuroinflammation: Breaking barriers and bridging gaps.

Neurons are the cells of the nervous system and are responsible for every thought, movement and perception. Immune cells are the cells of the immune system, constantly protecting from foreign pathogens. Understanding the interaction between the two systems is especially important in disease states such as autoimmune or neurodegenerative disease. Unfortunately, this interaction is typically detrimental to the host. However, recent efforts have focused on how neurons and immune cells interact, either directly or indirectly, following traumatic injury to the nervous system. The outcome of this interaction can be beneficial - leading to successful neural repair, or detrimental - leading to functional deficits, depending on where the injury occurs. This review will discuss our understanding of neuron-immune cell interactions after traumatic injury to both the peripheral and central nervous system.

The Chesapeake Bay Program Modeling System: Overview and Recommendations for Future Development.

The Chesapeake Bay is the largest, most productive, and most biologically diverse estuary in the continental United States providing crucial habitat and natural resources for culturally and economically important species. Pressures from human population growth and associated development and agricultural intensification have led to excessive nutrient and sediment inputs entering the Bay, negatively affecting the health of the Bay ecosystem and the economic services it provides. The Chesapeake Bay Program (CBP) is a unique program formally created in 1983 as a multi-stakeholder partnership to guide and foster restoration of the Chesapeake Bay and its watershed. Since its inception, the CBP Partnership has been developing, updating, and applying a complex linked modeling system of watershed, airshed, and estuary models as a planning tool to inform strategic management decisions and Bay restoration efforts. This paper provides a description of the 2017 CBP Modeling System and the higher trophic level models developed by the NOAA Chesapeake Bay Office, along with specific recommendations that emerged from a 2018 workshop designed to inform future model development. Recommendations highlight the need for simulation of watershed inputs, conditions, processes, and practices at higher resolution to provide improved information to guide local nutrient and sediment management plans. More explicit and extensive modeling of connectivity between watershed landforms and estuary sub-areas, estuarine hydrodynamics, watershed and estuarine water quality, the estuarine-watershed socioecological system, and living resources will be important to broaden and improve characterization of responses to targeted nutrient and sediment load reductions. Finally, the value and importance of maintaining effective collaborations among jurisdictional managers, scientists, modelers, support staff, and stakeholder communities is emphasized. An open collaborative and transparent process has been a key element of successes to date and is vitally important as the CBP Partnership moves forward with modeling system improvements that help stakeholders evolve new knowledge, improve management strategies, and better communicate outcomes.