scholarly journals How to get the most bang for your buck: the evolution and physiology of nutrition-dependent resource allocation strategies

2017 ◽  
Author(s):  
Enoch Ng’oma ◽  
Anna M. Perinchery ◽  
Elizabeth G. King
Keyword(s):  
Resource Allocation ◽  
Natural Populations ◽  
Analytical Models ◽  
Major Question ◽  
Proximate Mechanisms ◽  
Level Data ◽  
Flexible Resource ◽  
Empirical Tests ◽  
Underlying Mechanisms ◽  
Allocation Strategies

AbstractAll organisms utilize resources to grow, survive, and reproduce. The supply of these resources varies widely across landscapes and time, imposing ultimate constraints on the maximal trait values for allocation-related traits. In this review, we address three key questions fundamental to our understanding of the evolution of allocation strategies and their underlying mechanisms. First, we ask: how diverse are flexible resource allocation strategies among different organisms? We find there are many, varied, examples of flexible strategies that depend on nutrition. However, this diversity is often ignored in some of the best-known cases of resource allocation shifts, such as the commonly observed pattern of lifespan extension under nutrient limitation. A greater appreciation of the wide variety of flexible allocation strategies leads directly to our second major question: what conditions select for different plastic allocation strategies? Here, we highlight the need for additional models that explicitly consider the evolution of phenotypically plastic allocation strategies and empirical tests of the predictions of those models in natural populations. Finally, we consider the question: what are the underlying mechanisms determining resource allocation strategies? Although evolutionary biologists assume differential allocation of resources is a major factor limiting trait evolution, few proximate mechanisms are known that specifically support the model. We argue that an integrated framework can reconcile evolutionary models with proximate mechanisms that appear at first glance to be in conflict with these models. Overall, we encourage future studies to 1) mimic ecological conditions in which those patterns evolve, and 2) take advantage of the ‘omic’ opportunities to produce multi-level data and analytical models that effectively integrate across physiological and evolutionary theory.

scholarly journals How to get the most bang for your buck: the evolution and physiology of nutrition-dependent resource allocation strategies

2017 ◽  
Vol 284 (1857) ◽  
pp. 20170445 ◽  
Author(s):  
Enoch Ng'oma ◽  
Anna M. Perinchery ◽  
Elizabeth G. King
Keyword(s):  
Resource Allocation ◽  
Natural Populations ◽  
Analytical Models ◽  
Major Question ◽  
Proximate Mechanisms ◽  
Level Data ◽  
Flexible Resource ◽  
Empirical Tests ◽  
Underlying Mechanisms ◽  
Allocation Strategies

All organisms use resources to grow, survive and reproduce. The supply of these resources varies widely across landscapes and time, imposing ultimate constraints on the maximal trait values for allocation-related traits. In this review, we address three key questions fundamental to our understanding of the evolution of allocation strategies and their underlying mechanisms. First, we ask: how diverse are flexible resource allocation strategies among different organisms? We find there are many, varied, examples of flexible strategies that depend on nutrition. However, this diversity is often ignored in some of the best-known cases of resource allocation shifts, such as the commonly observed pattern of lifespan extension under nutrient limitation. A greater appreciation of the wide variety of flexible allocation strategies leads directly to our second major question: what conditions select for different plastic allocation strategies? Here, we highlight the need for additional models that explicitly consider the evolution of phenotypically plastic allocation strategies and empirical tests of the predictions of those models in natural populations. Finally, we consider the question: what are the underlying mechanisms determining resource allocation strategies? Although evolutionary biologists assume differential allocation of resources is a major factor limiting trait evolution, few proximate mechanisms are known that specifically support the model. We argue that an integrated framework can reconcile evolutionary models with proximate mechanisms that appear at first glance to be in conflict with these models. Overall, we encourage future studies to: (i) mimic ecological conditions in which those patterns evolve, and (ii) take advantage of the ‘omic’ opportunities to produce multi-level data and analytical models that effectively integrate across physiological and evolutionary theory.

Integrating Mechanisms and Functions to Understand Behavior

2019 ◽  
pp. xiv-9
Author(s):  
Lisa L. M. Welling ◽  
Todd K. Shackelford
Keyword(s):  
Evolutionary Psychology ◽  
Human Behavior ◽  
Reproductive Behavior ◽  
Affective Behavior ◽  
Behavioral Endocrinology ◽  
Human Psychology ◽  
Proximate Mechanisms ◽  
Underlying Mechanisms ◽  
Influence Behavior ◽  
Evolutionary Perspectives

Evolutionary psychology and behavioral endocrinology provide complementary perspectives on interpreting human behavior and psychology. Hormones can function as underlying mechanisms that influence behavior in functional ways. Understanding these proximate mechanisms can inform ultimate explanations of human psychology. This chapter introduces this edited volume by first discussing evolutionary perspectives in behavioral endocrinology. It then briefly addresses three broad topic areas of behavioral endocrinology: (1) development and survival, (2) reproductive behavior, and (3) social and affective behavior. It provides examples of research within each of these areas and describes potential adaptations. The chapter concludes with a discussion on the importance of integrating mechanisms with function when investigating human behavior and psychology.

scholarly journals Characteristics of intracerebral haemorrhage associated with COVID-19: a systematic review and pooled analysis of individual patient and aggregate data

2021 ◽  
Author(s):  
R. Beyrouti ◽  
J. G. Best ◽  
A. Chandratheva ◽  
R. J. Perry ◽  
D. J. Werring
Keyword(s):  
Intracerebral Haemorrhage ◽  
Pooled Analysis ◽  
Aggregate Data ◽  
High Rate ◽  
Individual Data ◽  
Aggregate Level ◽  
Level Data ◽  
Pooled Prevalence ◽  
Underlying Mechanisms ◽  
Different Characteristics

Abstract Background and purpose There are very few studies of the characteristics and causes of ICH in COVID-19, yet such data are essential to guide clinicians in clinical management, including challenging anticoagulation decisions. We aimed to describe the characteristics of spontaneous symptomatic intracerebral haemorrhage (ICH) associated with COVID-19. Methods We systematically searched PubMed, Embase and the Cochrane Central Database for data from patients with SARS-CoV-2 detected prior to or within 7 days after symptomatic ICH. We did a pooled analysis of individual patient data, then combined data from this pooled analysis with aggregate-level data. Results We included data from 139 patients (98 with individual data and 41 with aggregate-level data). In our pooled individual data analysis, the median age (IQR) was 60 (53–67) years and 64% (95% CI 54–73.7%) were male; 79% (95% CI 70.0–86.9%) had critically severe COVID-19. The pooled prevalence of lobar ICH was 67% (95% CI 56.3–76.0%), and of multifocal ICH was 36% (95% CI 26.4–47.0%). 71% (95% CI 61.0–80.4%) of patients were treated with anticoagulation (58% (95% CI 48–67.8%) therapeutic). The median NIHSS was 28 (IQR 15–28); mortality was 54% (95% CI 43.7–64.2%). Our combined analysis of individual and aggregate data showed similar findings. The pooled incidence of ICH across 12 cohort studies of inpatients with COVID-19 (n = 63,390) was 0.38% (95% CI 0.22–0.58%). Conclusions Our data suggest that ICH associated with COVID-19 has different characteristics compared to ICH not associated with COVID-19, including frequent lobar location and multifocality, a high rate of anticoagulation, and high mortality. These observations suggest different underlying mechanisms of ICH in COVID-19 with potential implications for clinical treatment and trials.

scholarly journals Balancing scarce hospital resources during the COVID-19 pandemic using discrete-event simulation

2021 ◽  
Author(s):  
G.J. Melman ◽  
A.K. Parlikad ◽  
E.A.B. Cameron
Keyword(s):  
Resource Allocation ◽  
Discrete Event Simulation ◽  
Elective Surgery ◽  
Discrete Event ◽  
Specific Patient ◽  
Event Simulation ◽  
The Impact ◽  
Allocation Decisions ◽  
Allocation Strategies ◽  
Resource Allocation Decisions

AbstractCOVID-19 has disrupted healthcare operations and resulted in large-scale cancellations of elective surgery. Hospitals throughout the world made life-altering resource allocation decisions and prioritised the care of COVID-19 patients. Without effective models to evaluate resource allocation strategies encompassing COVID-19 and non-COVID-19 care, hospitals face the risk of making sub-optimal local resource allocation decisions. A discrete-event-simulation model is proposed in this paper to describe COVID-19, elective surgery, and emergency surgery patient flows. COVID-19-specific patient flows and a surgical patient flow network were constructed based on data of 475 COVID-19 patients and 28,831 non-COVID-19 patients in Addenbrooke’s hospital in the UK. The model enabled the evaluation of three resource allocation strategies, for two COVID-19 wave scenarios: proactive cancellation of elective surgery, reactive cancellation of elective surgery, and ring-fencing operating theatre capacity. The results suggest that a ring-fencing strategy outperforms the other strategies, regardless of the COVID-19 scenario, in terms of total direct deaths and the number of surgeries performed. However, this does come at the cost of 50% more critical care rejections. In terms of aggregate hospital performance, a reactive cancellation strategy prioritising COVID-19 is no longer favourable if more than 7.3% of elective surgeries can be considered life-saving. Additionally, the model demonstrates the impact of timely hospital preparation and staff availability, on the ability to treat patients during a pandemic. The model can aid hospitals worldwide during pandemics and disasters, to evaluate their resource allocation strategies and identify the effect of redefining the prioritisation of patients.

Tidal-amplitude rhythms of larval release: variable departure from presumed optimal timing among populations of the mottled shore crab

2010 ◽  
Vol 90 (5) ◽  
pp. 859-865 ◽  
Author(s):  
M. Bueno ◽  
A.A.V. Flores
Keyword(s):  
Comprehensive Evaluation ◽  
Natural Populations ◽  
Wave Action ◽  
Shore Crab ◽  
Optimal Timing ◽  
Rocky Shores ◽  
Tidal Amplitude ◽  
Larval Release ◽  
Underlying Mechanisms ◽  
Release Timing

It is widely assumed that optimal timing of larval release is of major importance to offspring survival, but the extent to which environmental factors entrain synchronous reproductive rhythms in natural populations is not well known. We sampled the broods of ovigerous females of the common shore crab Pachygrapsus transversus at both sheltered and exposed rocky shores interspersed along a 50-km coastline, during four different periods, to better assess inter-population differences of larval release timing and to test for the effect of wave action. Shore-specific patterns were consistent through time. Maximum release fell within 1 day around syzygies on all shores, which matched dates of maximum tidal amplitude. Within this very narrow range, populations at exposed shores anticipated hatching compared to those at sheltered areas, possibly due to mechanical stimulation by wave action. Average departures from syzygial release ranged consistently among shores from 2.4 to 3.3 days, but in this case we found no evidence for the effect of wave exposure. Therefore, processes varying at the scale of a few kilometres affect the precision of semilunar timing and may produce differences in the survival of recently hatched larvae. Understanding the underlying mechanisms causing departures from presumed optimal release timing is thus important for a more comprehensive evaluation of reproductive success of invertebrate populations.

RiRiShun Logistics: Home Appliance Delivery Data for the 2021 Manufacturing & Service Operations Management Data-Driven Research Challenge

2021 ◽  
Author(s):  
Xiaolong Guo ◽  
Yugang Yu ◽  
Gad Allon ◽  
Meiyan Wang ◽  
Zhentai Zhang
Keyword(s):  
Operations Management ◽  
Service Operations ◽  
Optimization Techniques ◽  
Data Driven ◽  
Analytical Models ◽  
Data Set ◽  
Service Operations Management ◽  
Level Data ◽  
Home Appliance ◽  
Research Challenge

To support the 2021 Manufacturing & Service Operations Management (MSOM) Data-Driven Research Challenge, RiRiShun Logistics (a Haier group subsidiary focusing on logistics service for home appliances) provides MSOM members with logistics operational-level data for data-driven research. This paper provides a detailed description of the data associated with over 14 million orders from 149 clients (the consigners) associated with 4.2 million end consumers (the recipients and end users of the appliances) in China, involving 18,000 stock keeping units operated at 103 warehouses. Researchers are welcomed to develop econometric models, data-driven optimization techniques, analytical models, and algorithm designs by using this data set to address questions suggested by company managers.

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