Proxy failure in academia: More than just another example.

Proxy failure in academia has progressed much ahead of what John et al. describe. We see advanced phenomena such as proxy complimentarity in which different players push each others' proxy failures; proxy exploitation in which external agents exploit players' proxies and predatory proxies that devour the goal itself. Academics need to avoid proxy failures by designing behaviorally sound systems.

Epidemiology: Gray immunity model gives qualitatively different predictions.

Compartmental models that dynamically divide the host population into categories such as susceptible, infected, and immune constitute the mainstream of epidemiological modelling. Effectively, such models treat infection and immunity as binary variables. We constructed an individual-based stochastic model that considers immunity as a continuous variable and incorporates factors that bring about small changes in immunity. The small immunity effects (SIE) comprise cross-immunity by other infections, small increments in immunity by subclinical exposures, and slow decay in the absence of repeated exposure. The model makes qualitatively different epidemiological predictions, including repeated waves without the need for new variants, dwarf peaks (peak and decline of a wave much before reaching herd immunity threshold), symmetry in upward and downward slopes of a wave, endemic state, new surges after variable and unpredictable gaps, and new surges after vaccinating majority of the population. In effect, the SIE model raises alternative possible causes of universally observed dwarf and symmetric peaks and repeated surges, observed particularly well during the COVID-19 pandemic. We also suggest testable predictions to differentiate between the alternative causes for repeated waves. The model further shows complex interactions of different interventions that can be synergistic as well as antagonistic. It also suggests that interventions that are beneficial in the short run could also be hazardous in the long run.

Tradition-invention dichotomy and optimization in the field of science.

The central idea of the bifocal stance theory (BST) by Jagiello et al. has substantial relevance to scientific research. Both tradition-following and exploration-innovation are important in science and researchers subconsciously try to optimize their strategies. We outline three important dimensions of this optimization and argue that attempts to understand this complex process can help us design better science education, research training, investigation, and science publication.

The ratio versus difference optimization and its implications for optimality theory.

Among the classical models of optimization, some models maximize the ratio of returns to investment and others maximize the difference between returns and investment. However, an understanding of under what conditions the ratio or the difference approaches are appropriate is still fragmentary. Under specific contexts, it has been stated that when the investable amount, but not the opportunity for investment, is perceived to be limiting, a ratio optimum is appropriate, whereas a difference optimum is appropriate when the opportunity for investment, but not the investable amount, is perceived to be limiting. The question is important because the strategies indicated by ratio optimum can be substantially different than the ones suggested by difference optimum. We make a general case here to examine and expand this principle and apply it to many evolutionary ecological problems including parental investment, offspring quality-quantity trade-off, nectar production, pollinator behavior viral burst size, and intracellular protein handling. We show that the ratio-difference distinction in optimization models resolves many long-standing debates and conundrums in evolution and behavior.

Phylogenetic diversity and activity screening of cultivable Actinobacteria isolated from marine sponges and associated environments from the western coast of India.

The phylogenetic diversity of cultivable actinobacteria isolated from sponges (Haliclona spp.) and associated intertidal zone environments along the northern parts of the western coast of India were studied using 16S rRNA gene sequences. A subset of randomly selected actinobacterial cultures were screened for three activities, namely predatory behaviour, antibacterial activity and enzyme inhibition. We recovered 237 isolates from the phylum Actinobacteria belonging to 19 families and 28 genera, which could be attributed to 95 putative species using maximum-likelihood partition and 100 putative species using Bayesian partition in Poisson tree processes. Although the trends in the discovery of actinobacterial genera isolated from sponges were consistent with previous studies from different study areas, we provide the first report of nine actinobacterial species from sponges. We observed widespread non-obligate epibiotic predatory behaviour in eight actinobacterial genera and we provide the first report of predatory activity in Brevibacterium , Glutamicibacter , Micromonospora , Nocardiopsis , Rhodococcus and Rothia . Sponge-associated actinobacteria showed significantly more predatory behaviour than environmental isolates. While antibacterial activity by actinobacterial isolates mainly affected Gram-positive target bacteria with little or no effect on Gram-negative bacteria, predation targeted both Gram-positive and Gram-negative prey with equal propensity. Actinobacterial isolates from both sponges and associated environments produced inhibitors of serine proteases and angiotensin-converting enzyme. Predatory behaviour was strongly associated with inhibition of trypsin and chymotrypsin. Our study suggests that the sponges and associated environments of the western coast of India are rich in actinobacterial diversity, with widespread predatory activity, antibacterial activity and production of enzyme inhibitors. Understanding the diversity and associations among various actinobacterial activities - with each other and the source of isolation - can provide new insights into marine microbial ecology and provide opportunities to isolate novel therapeutic agents.

Evaluating alternative hypotheses to explain the downward trend in the indices of the COVID-19 pandemic death rate.

BACKGROUND: In the ongoing Covid-19 pandemic, in the global data on the case fatality ratio (CFR) and other indices reflecting death rate, there is a consistent downward trend from mid-April to mid-November. The downward trend can be an illusion caused by biases and limitations of data or it could faithfully reflect a declining death rate. A variety of explanations for this trend are possible, but a systematic analysis of the testable predictions of the alternative hypotheses has not yet been attempted. METHODOLOGY: We state six testable alternative hypotheses, analyze their testable predictions using public domain data and evaluate their relative contributions to the downward trend. RESULTS: We show that a decline in the death rate is real; changing age structure of the infected population and evolution of the virus towards reduced virulence are the most supported hypotheses and together contribute to major part of the trend. The testable predictions from other explanations including altered testing efficiency, time lag, improved treatment protocols and herd immunity are not consistently supported, or do not appear to make a major contribution to this trend although they may influence some other patterns of the epidemic. CONCLUSION: The fatality of the infection showed a robust declining time trend between mid April to mid November. Changing age class of the infected and decreasing virulence of the pathogen were found to be the strongest contributors to the trend.

Combining payment for crop damages and reward for productivity to address wildlife conflict.

Conflict caused by wild herbivores damaging crops is an almost universal problem in conservation. We designed and implemented a game-theory-based system for supporting farmers whose crops were being heavily damaged by wild herbivores. In this community-operated system, farmers self-report their production, which is endorsed by neighboring farmers. The average deficit in production is compensated for by a payment that is directly proportional to the average deficit in production of the group and to the individual farmer's productivity. As a result, farmers are compensated for the average damage (support) and rewarded for individual productivity (reward) (i.e., support cum reward [SuR]). The design of the game is such that only honest reporting gives maximum returns. Farmers who underreport receive less payment because the SuR amount is proportionate to their self-reported productivity. The endorsing farmers, in their own self-interest, prevent overreporting. The system involves multiple game situations, the combined result of which is a stable strategy based on honesty and hard work. In 2 villages along the western boundary of Tadoba Andhari Tiger Reserve in central India, we tested the system with 75 farmers over 6 crop seasons. After a few initial attempts to cheat, honesty prevailed throughout the group. Average crop productivity increased 2.5-fold, in spite of damage, owing to increased effort by farmers. Apart from wildlife conflict resolution, the model offers a promising alternative to crop insurance and a potential behavioral green revolution in agriculture.

Combinación entre el Pago por Daños a Cultivos y la Recompensa por Productividad para Abordar el Conflicto con la Fauna Resumen El conflicto causado por herbívoros silvestres que dañan los cultivos es casi un problema universal para la conservación. Diseñamos e implementamos un sistema basado en la teoría de juegos para apoyar a los agricultores cuyos cultivos estuvieran siendo dañados considerablemente por los herbívoros silvestres. En este sistema operado comunitariamente, los agricultores reportan por sí mismos su producción, la cual es endosada por los agricultores vecinos. El déficit promedio en la producción se compensa con un pago que es directamente proporcional al déficit promedio en la producción del grupo y a la productividad individual del agricultor. Como resultado, los agricultores son compensados por el daño promedio (apoyo) y recompensados por la productividad individual (recompensa) (es decir, apoyo con recompensa [SuR]). El diseño del juego es tal que solamente la declaración honesta otorga la máxima ganancia. Los agricultores que declaren menos de lo dañado reciben menor pago porque la cantidad SuR es proporcional a su productividad auto declarada. Los agricultores que los endosan, por interés propio, previenen que haya declaraciones por encima de lo realmente producido. El sistema involucra varias situaciones de juego, cuyo resultado combinado es una estrategia estable basada en la honestidad y el trabajo duro. En dos aldeas ubicadas a lo largo de la frontera occidental de la Reserva de Tigres Tadoba Andhari en el centro de la India, pusimos a prueba este sistema con 75 agricultores durante seis temporadas de cultivo. Después de algunos intentos iniciales por hacer trampa, la honestidad prevaleció en todo el grupo. La productividad promedio de cultivos incrementó 2.5 veces su cantidad inicial a pesar del daño, esto debido al incremento en el esfuerzo de los agricultores. Además de la solución del conflicto con la fauna, el modelo ofrece una alternativa prometedora al aseguramiento de cultivos y una potencial revolución verde en el comportamiento agrícola.

A multidimensional functional fitness score has a stronger association with type 2 diabetes than obesity parameters in cross sectional data.

OBJECTIVES: We examine here the association of multidimensional functional fitness with type 2 diabetes mellitus (T2DM) as compared to anthropometric indices of obesity such as body mass index (BMI) and waist to hip ratio (WHR) in a sample of Indian population. RESEARCH DESIGN AND METHOD: We analysed retrospective data of 663 volunteer participants (285 males and 378 females between age 28 and 84), from an exercise clinic in which every participant was required to undergo a health related physical fitness (HRPF) assessment consisting of 15 different tasks examining 8 different aspects of functional fitness. RESULTS: The odds of being diabetic in the highest quartile of BMI were not significantly higher than that in the lowest quartile in either of the sexes. The odds of being a diabetic in the highest WHR quartile were significantly greater than the lowest quartile in females (OR = 4.54 (1.95, 10.61) as well as in males (OR = 3.81 (1.75, 8.3). In both sexes the odds of being a diabetic were significantly greater in the lowest quartile of HRPF score than the highest (males OR = 10.52 (4.21, 26.13); females OR = 10.50 (3.53, 31.35)). After removing confounding, the predictive power of HRPF was significantly greater than that of WHR. HRPF was negatively correlated with WHR, however for individuals that had contradicting HRPF and WHR based predictions, HRPF was the stronger predictor of T2DM. CONCLUSION: The association of multidimensional functional fitness score with type 2 diabetes was significantly stronger than obesity parameters in a cross sectional self-selected sample from an Indian city.

Driver versus navigator causation in biology: the case of insulin and fasting glucose.

BACKGROUND: In biomedicine, inferring causal relation from experimental intervention or perturbation is believed to be a more reliable approach than inferring causation from cross-sectional correlation. However, we point out here that even in interventional inference there are logical traps. In homeostatic systems, causality in a steady state can be qualitatively different from that in a perturbed state. On a broader scale there is a need to differentiate driver causality from navigator causality. A driver is essential for reaching a destination but may not have any role in deciding the destination. A navigator on the other hand has a role in deciding the destination and the path but may not be able to drive the system to the destination. The failure to differentiate between types of causalities is likely to have resulted into many misinterpretations in physiology and biomedicine. METHODS: We illustrate this by critically re-examining a specific case of the causal role of insulin in glucose homeostasis using five different approaches (1) Systematic review of tissue specific insulin receptor knock-outs, (2) Systematic review of insulin suppression and insulin enhancement experiments, (3) Differentiating steady state and post-meal state glucose levels in streptozotocin treated rats in primary experiments, (4) Mathematical and theoretical considerations and (5) Glucose-insulin relationship in human epidemiological data. RESULTS: All the approaches converge on the inference that although insulin action hastens the return to a steady state after a glucose load, there is no evidence that insulin action determines the steady state level of glucose. Insulin, unlike the popular belief in medicine, appears to be a driver but not a navigator for steady state glucose level. It is quite likely therefore that the current line of clinical action in the field of type 2 diabetes has limited success largely because it is based on a misinterpretation of glucose-insulin relationship. The insulin-glucose example suggests that we may have to carefully re-examine causal inferences from perturbation experiments and set up revised norms for experimental design for causal inference.

Geriatric infections: Decreased immunity or evolved opportunists?

In host-parasite co-evolution, parasites are assumed to have an advantage owing to their shorter generation time. Evolution of pathogens within the lifetime of a host individual is implicated as a strong selective force in the evolution of sex and aging in the host. However, this assumption or its testable predictions have not been examined empirically. We classified infectious bacteria and viruses into those that can have continued longterm existence on the host body (group 1) versus those that have only a short-term interaction during an active infection (group 2). We surveyed the literature for age-specific incidence data about infections from both the groups. The age trends of the two groups show contrasting patterns. The incidence of infections by all group 1 pathogens showed a 2.28- to 28-fold increase in older ages. In group 2, 6 out of the 9 pathogens showed a significant declining trend in incidence with age. In both groups, there was greater mortality or morbidity among the infected in the old-age classes. These patterns are better explained by pathogen evolution than by age-related decline in immunity.

Context-dependent selection as the keystone in the somatic evolution of cancer.

Somatic evolution of cancer involves a series of mutations, and attendant changes, in one or more clones of cells. A "bad luck" type model assumes chance accumulation of mutations. The clonal expansion model assumes, on the other hand, that any mutation leading to partial loss of regulation of cell proliferation will give a selective advantage to the mutant. However, a number of experiments show that an intermediate pre-cancer mutant has only a conditional selective advantage. Given that tissue microenvironmental conditions differ across individuals, this selective advantage to a mutant could be widely distributed over the population. We evaluate three models, namely "bad luck", context-independent, and context-dependent selection, in a comparative framework, on their ability to predict patterns in total incidence, age-specific incidence, stem cell number-incidence relationship and other known phenomena associated with cancers. Results show that among the factors considered in the model, context dependence is necessary and sufficient to explain observed epidemiological patterns, and that cancer evolution is largely selection-limited, rather than mutation-limited. A wide range of physiological, genetic and behavioural factors influence the tissue micro-environment, and could therefore be the source of this context dependence in somatic evolution of cancer. The identification and targeting of these micro-environmental factors that influence the dynamics of selection offer new possibilities for cancer prevention.

Foraging theory and the propensity to be obese: an alternative to thrift.

The evolutionary origin of obesity is classically believed to be genetic or developmentally induced thrift, as an adaptation to ancestral feast and famine conditions. However, recently the thrift family of hypotheses have attracted serious criticism necessitating alternative thinking. Optimization of foraging behaviour is an important aspect of behavioural evolution. For a species evolved for optimizing nutritional benefits against predation or other foraging risks, reduction in foraging risk below a threshold dramatically increases the steady-state body weight. In modern life where feeding is detached from foraging, the behavioural regulation mechanisms are likely to fail resulting into escalation of adiposity. At a proximate level the signalling pathways for foraging optimization involve fear induced signal molecules in the brain including Cocaine and Amphetamine Regulated Transcript (CART) interacting with adiposity signals such as leptin. While leptin promotes the expression of the fear peptides, the fear peptides promote anorectic action of leptin. This interaction promotes foraging drive and risk tolerance when the stored energy is low and suppresses hunger and foraging drive when the perceived risk is high. The ecological model of foraging optimization and the molecular model of interaction of these peptides converge in the outcome that the steady state adiposity is an inverse square root function of foraging risk. The foraging optimization model is independent of thrift or insurance hypotheses, but not mutually exclusive. We review existing evidence and suggest testable predictions of the model. Understanding obesity simultaneously at proximate and ultimate levels is likely to suggest effective means to curb the obesity epidemic.

Inferring causal pathways among three or more variables from steady-state correlations in a homeostatic system.

Cross-sectional correlations between two variables have limited implications for causality. We examine here whether it is possible to make causal inferences from steady-state data in a homeostatic system with three or more inter-correlated variables. Every putative pathway between three variables makes a set of differential predictions that can be tested with steady state data. For example, among 3 variables, A, B and C, the coefficient of determination, [Formula: see text] is predicted by the product of [Formula: see text] and [Formula: see text] for some pathways, but not for others. Residuals from a regression line are independent of residuals from another regression for some pathways, but positively or negatively correlated for certain other pathways. Different pathways therefore have different prediction signatures, which can be used to accept or reject plausible pathways using appropriate null hypotheses. The type 2 error reduces with sample size but the nature of this relationship is different for different predictions. We apply these principles to test the classical pathway leading to a hyperinsulinemic normoglycemic insulin-resistant, or pre-diabetic, state using four different sets of epidemiological data. Currently, a set of indices called HOMA-IR and HOMA-ß are used to represent insulin resistance and glucose-stimulated insulin response by ß cells respectively. Our analysis shows that if we assume the HOMA indices to be faithful indicators, the classical pathway must in turn be rejected. In effect, among the populations sampled, the classical pathway and faithfulness of the HOMA indices cannot be simultaneously true. The principles and example shows that it is possible to infer causal pathways from cross sectional correlational data on three or more correlated variables.

Blind fish: An eye opener.

Lay Summary: Different species of vertebrates have conditions similar to human obesity, insulin resistance and type 2 diabetes. Increasing number of studies are now revealing that the causes and interrelationships between these states are substantially different in different species. Comparative physiology may turn out to be an eye opener for evolutionary theories of diabetes. Obesity induced insulin resistance is believed to be central to type 2 diabetes. Recent work on Mexican cavefish, Astyanax mexicanus, has revealed a hyperglycemic phenotype similar to human type 2 diabetes but here insulin resistance is the cause of obesity rather than an effect. Instead of developing diabetic complications, the hyperglycemic fish lead a healthy and long life. In addition to fish, insulin resistance in hibernating bears, dolphins, horses, bonnet macaques and chimpanzees demonstrate that the relationship between diet, obesity, insulin sensitivity and diabetes is widely different in different species. Evolutionary hypotheses about type 2 diabetes should explain these differences.

Isolation and structure elucidation of halymeniaol, a new antimalarial sterol derivative from the red alga Halymenia floresii.

A new mono-hydroxy acetylated sterol derivative: 12ß-hydroxy-3ß, 15α, 16ß-triacetoxy-cholest-5-en-7-one (halymeniaol) (1), and cholesterol (2) were isolated from the marine red alga Halymenia floresii. The structure of the compound 1 (halymeniaol) was established from its spectral data, derived from HRMS/MS and 2D NMR. Compound 1 exhibited growth inhibitory activity against chloroquine-resistant Plasmodium falciparum 3D7 strain with an IC50 of 3.0 µM.

Bi-stability in type 2 diabetes mellitus multi-organ signalling network.

Type 2 diabetes mellitus (T2DM) is believed to be irreversible although no component of the pathophysiology is irreversible. We show here with a network model that the apparent irreversibility is contributed by the structure of the network of inter-organ signalling. A network model comprising all known inter-organ signals in T2DM showed bi-stability with one insulin sensitive and one insulin resistant attractor. The bi-stability was made robust by multiple positive feedback loops suggesting an evolved allostatic system rather than a homeostatic system. In the absence of the complete network, impaired insulin signalling alone failed to give a stable insulin resistant or hyperglycemic state. The model made a number of correlational predictions many of which were validated by empirical data. The current treatment practice targeting obesity, insulin resistance, beta cell function and normalization of plasma glucose failed to reverse T2DM in the model. However certain behavioural and neuro-endocrine interventions ensured a reversal. These results suggest novel prevention and treatment approaches which need to be tested empirically.

Social behavioural epistemology and the scientific community.

The progress of science is influenced substantially by social behaviour of and social interactions within the scientific community. Similar to innovations in primate groups, the social acceptance of an innovation depends not only upon the relevance of the innovation but also on the social dominance and connectedness of the innovator. There are a number of parallels between many well-known phenomena in behavioural evolution and various behavioural traits observed in the scientific community. It would be useful, therefore, to use principles of behavioural evolution as hypotheses to study the social behaviour of the scientific community. I argue in this paper that a systematic study of social behavioural epistemology is likely to boost the progress of science by addressing several prevalent biases and other problems in scientific communication and by facilitating appropriate acceptance/rejection of novel concepts.

What to expect from an evolutionary hypothesis for a human disease: The case of type 2 diabetes.

Evolutionary medicine has a promise to bring in a conceptual revolution in medicine. However, as yet the field does not have the same theoretical rigour as that of many other fields in evolutionary studies. We discuss here with reference to type 2 diabetes mellitus (T2DM) what role an evolutionary hypothesis should play in the development of thinking in medicine. Starting with the thrifty gene hypothesis, evolutionary thinking in T2DM has undergone several transitions, modifications and refinements of the thrift family of hypotheses. In addition alternative hypotheses independent of thrift are also suggested. However, most hypotheses look at partial pictures; make selective use of supportive data ignoring inconvenient truths. Most hypotheses look at a superficial picture and avoid getting into the intricacies of underlying molecular, neuronal and physiological processes. Very few hypotheses have suggested clinical implications and none of them have been tested with randomized clinical trials. In the meanwhile the concepts in the pathophysiology of T2DM are undergoing radical changes and evolutionary hypotheses need to take them into account. We suggest an approach and a set of criteria to evaluate the relative merits of the alternative hypotheses. A number of hypotheses are likely to fail when critically evaluated against these criteria. It is possible that more than one selective process are at work in the evolution of propensity to T2DM, but the intercompatibility of the alternative selective forces and their relative contribution needs to be examined. The approach we describe could potentially lead to a sound evolutionary theory that is clinically useful and testable by randomized controlled clinical trials.

Assessment of Crop Damage by Protected Wild Mammalian Herbivores on the Western Boundary of Tadoba-Andhari Tiger Reserve (TATR), Central India.

Crop raiding by wild herbivores close to an area of protected wildlife is a serious problem that can potentially undermine conservation efforts. Since there is orders of magnitude difference between farmers' perception of damage and the compensation given by the government, an objective and realistic estimate of damage was found essential. We employed four different approaches to estimate the extent of and patterns in crop damage by wild herbivores along the western boundary of Tadoba-Andhari Tiger Reserve in the state of Maharashtra, central India. These approaches highlight different aspects of the problem but converge on an estimated damage of over 50% for the fields adjacent to the forest, gradually reducing in intensity with distance. We found that the visual damage assessment method currently employed by the government for paying compensation to farmers was uncorrelated to and grossly underestimated actual damage. The findings necessitate a radical rethinking of policies to assess, mitigate as well as compensate for crop damage caused by protected wildlife species.