Research letters

Patients with transfusion-dependent thalassemia are expected to have an unfavorable quality of life due to multiple factors. We studied the quality of life in 72 patients (age 5-39 y) with transfusion-dependent thalassemia in the era of improved care, and assessed different parameters affecting it.     

From the Cover: Algorithms,games, and evolution

Even the most seasoned students of evolution, starting with Darwin himself, have occasionally expressed amazement that the mechanism of natural selection has produced the whole of Life as we see it around us. There is a computational way to articulate the same amazement: “What algorithm could possibly achieve all this in a mere three and a half billion years?” In this paper we propose an answer: We demonstrate that in the regime of weak selection, the standard equations of population genetics describing natural selection in the presence of sex become identical to those of a repeated game between genes played according to multiplicative weight updates (MWUA), an algorithm known in computer science to be surprisingly powerful and versatile. MWUA maximizes a tradeoff between cumulative performance and entropy, which suggests a new view on the maintenance of diversity in evolution.Precisely how does selection change the composition of the gene pool from generation to generation? The field of population genetics has developed a comprehensive mathematical framework for answering this and related questions (1). Our analysis in this paper focuses particularly on the regime of weak selection, now a widely used assumption (2, 3). Weak selection assumes that the differences in fitness between genotypes are small relative to the recombination rate, and consequently, through a result due to Nagylaki et al. (4) (see also ref. 1, section II.6.2), evolution proceeds near linkage equilibrium, a regime where the probability of occurrence of a certain genotype involving various alleles is simply the product of the probabilities of each of its alleles. Based on this result, we show that evolution in the regime of weak selection can be formulated as a repeated game, where the recombining loci are the players, the alleles in those loci are the possible actions or strategies available to each player, and the expected payoff at each generation is the expected fitness of an organism across the genotypes that are present in the population. Moreover, and perhaps most importantly, we show that the equations of population genetic dynamics are mathematically equivalent to positing that each locus selects a probability distribution on alleles according to a particular rule which, in the context of the theory of algorithms, game theory, and machine learning, is known as the multiplicative weight updates algorithm (MWUA). MWUA is known in computer science as a simple but surprisingly powerful algorithm (see ref. 5 for a survey). Moreover, there is a dual view of this algorithm: each locus may be seen as selecting its new allele distribution at each generation so as to maximize a certain convex combination of (i) cumulative expected fitness and (ii) the entropy of its distribution on alleles. This connection between evolution, game theory, and algorithms seems to us rife with productive insights; for example, the dual view just mentioned sheds new light on the maintenance of diversity in evolution.Game theory has been applied to evolutionary theory before, to study the evolution of strategic individual behavior (see, e.g., refs. 6, 7). The connection between game theory and evolution that we point out here is at a different level, and arises not in the analysis of strategic individual behavior, but rather in the analysis of the basic population genetic dynamics in the presence of sexual reproduction. The main ingredients of evolutionary game theory, namely strategic individual behavior and conflict between individuals, are extraneous to our analysis.We now state our assumptions and results. We consider an infinite panmictic population of haplotypes involving several unlinked (i.e., fully recombining) loci, where each locus has several alleles. These assumptions are rather standard in the literature. They are made here to simplify exposition and algebra, and there is no a priori reason to believe that they are essential for the results, beyond making them easily accessible. For example, Nagylaki’s theorem (4), which is the main analytical ingredient of our results, holds even in the presence of diploidy and partial recombination.Nagylaki’s theorem states that weak selection in the presence of sex proceeds near the Wright manifold, where the population genetic dynamics becomes (SI Text)xit+1(j)=1Xtxit(j)(Fit(j)),where xit(j) is the frequency of allele j of locus i in the population at generation t, X is a normalizing constant to keep the frequencies summing to 1, and Fit(j) is the mean fitness at time t among genotypes that contain allele j at locus i (see ref. 4 and SI Text). Under the assumption of weak selection, the fitnesses of all genotypes are close to one another, say within the interval [1 − ε, 1 + ε], and so the fitness of genotype g can be written as F_g = 1 + εΔ_g, where ε is the selection strength, assumed here to be small, and Δ_g ∈ [−1, 1] can be called the differential fitness of the genotype. With this in mind, the equation above can be writtenxit+1(j)=1Xtxit(j)(1+ϵΔit(j)),[1]where Δit(j) is the expected differential fitness among genotypes that contain allele j at locus i (see Fig. 1 for an illustration of population genetics at linkage equilibrium).Open in a separate windowFig. 1.Equations of population genetics formulated in the 1930s constitute the standard mathematical way of understanding evolution of a species by tracking the frequencies of various genotypes in a large population. In the simple example shown here, a haploid organism with two genetic loci A and B has three alleles in each of its two loci named A1, A2, A3 and B1, B2, B3 for a total of nine genotypes. In A we show the fitness of each genotype, that is, its expected number of offspring. The fitness numbers shown in A are all close to each other, reflecting weak selection, where the individual alleles’ contributions to fitness are typically minuscule. Initially, each genotype occurs in the population with some frequency; in this particular example these numbers are initially equal (B); naturally, their sum over all nine genotypes is 1 (frequencies are truncated to the fourth decimal digit). C shows how the genotype frequencies evolve in the next generation: each individual of a given genotype produces a number of offspring that is proportional to its fitness shown in A, and the resulting offspring inherits the alleles of its parents with equal probability (because we are assuming, crucially, sexual reproduction). The genotype frequencies in the next generation are shown in C, calculated through the standard recurrence equations of population genetics. We also show in the margins of the table the allele frequencies, obtained by adding the genotype frequencies along the corresponding row or column. Ten generations later, the frequencies are as shown in D.We now introduce the framework of game theory (see Fig. 2 for an illustration) and the MWUA (SI Text), studied in computer science and machine learning, and rediscovered many times over the past half-century; as a result of these multiple rediscoveries, the algorithm is known with various names across subfields: “the experts algorithm” in the theory of algorithms, “Hannan consistency” in economics, “regret minimization” in game theory, “boosting” and “winnow” in artificial intelligence, etc. Here we state it in connection to games, which is only a small part of its applicability (see SI Text for an introduction to the MWUA in connection to the so-called “experts problem” in computer science).Open in a separate windowFig. 2.A simple coordination game is played by two players: the row player, who chooses a row, and the column player, who chooses a column. After the two players make a choice, they both receive (or both pay, in case of a negative entry) the same amount of money, equal to the number at the chosen row and column (A). Coordination games are the simplest possible kind of a game, one in which the strategic interests of all players are completely aligned—that is to say, there is no conflict at all. They are of interest when it is difficult for the players to know these numbers, or to communicate and agree on a mutually beneficial combination (in this example, third row and second column). Notice that this particular coordination game is closely related to the fitness landscape shown in Fig. 1A: If P is a payoff in this game, the corresponding entry of Fig. 1A is equal to 1 + ε ⋅ P, where ε is a small parameter here taken to be 0.01. Suppose that each of the two players chooses each of the three options with some probability, initially 1/3 for all (B); in game theory such probabilistic play is called a mixed action. How do we expect these probabilities to change over repeated play? One famous recipe is the MWUA, in which a player “boosts” the probability of each option by multiplying it by 1 + εG, where G is the expected amount of money this option is going to win the player in the current round of play, and ε is the same small parameter as above. For example, the second action of the row player has G equal to 2 (the average of 3, −1, and 4), and so the probability of playing the second row will be multiplied by 1.02. Then these weights are “renormalized” so they add up to 1, yielding the marginal probabilities shown in C. The probabilities after 10 such rounds of play are shown in D. Comparing now the numbers in the margins of Figs. 1D and ​and2D,2D, we notice that they are essentially the same. This is what we establish mathematically in this paper: the two processes—repeated coordination games played through multiplicative updates, and evolution under weak selection—are essentially identical. This conclusion is of interest because the MWUA is known in computer science to be surprisingly powerful.A game has several players, and each player i has a set A_i of possible actions. Each player also has a utility, capturing the way whereby her actions and the actions of the other players affect this player’s well-being. Formally the utility of a player is a function that maps each combination of actions by the players to a real number (intuitively denoting the player’s gain, in some monetary unit, if all players choose these particular actions). In general, rather than choosing a single action, a player may instead choose a mixed or randomized action, that is, a probabilistic distribution over her action set. Here we only need to consider coordination games, in which all players have the same utility function—that is, the interests of the players are perfectly aligned, and their only challenge is to coordinate their choices effectively. Coordination games are among the simplest games; the only challenge in such a game is for the players to “agree” on a mutually beneficial action.How do the players choose and adjust their choice of randomized (mixed) actions over repeated play? Assume that at time t, player i has mixed action xit, assigning to each action j ∈ A_i the probability xit(j). The MWUA algorithm (5) adjusts the mixed strategy for player i in the next round of the game according to the following rule:xit+1(j)=1Ztxit(j)(1+ϵuit(j)),[2]where Z^t is a normalizing constant designed to ensure that ∑jxit(j)=1, so xit+1 is a probability distribution; ε is a crucial small positive parameter, and uit(j) denotes the expected utility gained by player i choosing action j in the regime of the mixed actions by the other players effective at time t. This algorithm (i) is known to converge to the min–max actions if the game is two-player zero-sum; (ii) is also shown here to converge to equilibrium for the coordination games of interest in the present paper (SI Text, Corollary 5); (iii) is a general “learning algorithm” that has been shown to be very successful in both theory and practice; and (iv) if, instead of games, it is applied to a large variety of optimization problems, including linear programming, convex programming, and network congestion, it provably converges to the optimum quite fast.It can be now checked that the two processes expressed in Eqs. 1 and 2, evolution under natural selection in the presence of sex and multiplicative weight updates in a coordination game, are mathematically identical (SI Text, Theorem 3). That is, the interaction of weak selection and sex is equivalent to the MWUA in a coordination game between loci in which the common utility is the differential fitness of the organism. The parameter ε in the algorithm, which, when small signifies that the algorithm is taking a “longer-term view” of the process to be solved (SI Text), corresponds to the selection strength in evolution, i.e., the magnitude of the differences between the fitness of various genotypes.The MWUA is known in computer science as an extremely simple and yet unexpectedly successful algorithm, which has surprised us time and again by its prowess in solving sophisticated computational problems such as congestion minimization in networks and convex programming in optimization. The observation that multiplicative weight updates in a coordination game are equivalent to evolution under sex and weak selection makes an informative triple connection between three theoretical fields: evolutionary theory, game theory, and the theory of algorithms–machine learning.So far we have presented the MWUA by “how it works” (informally, it boosts alleles proportionally to how well they do in the current mix). There is an alternative way of understanding the MWUA in terms of “what it is optimizing.” That is, we imagine that the allele frequencies of each locus in each generation are the result of a deliberate optimization by the locus of some quantity, and we wish to determine that quantity.Returning to the game formulation, define Uit(j)=∑τ=0tuiτ(j) to be the cumulative utility obtained by player i by playing strategy j over all t first repetitions of the game, and consider the quantity∑jxit(j)Uit(j)−1ϵ∑jxit(j)ln⁡xit(j).[3]The first term is the current (at time t) expected cumulative utility. The second term of 3 is the entropy (expected negative logarithm) of the probability distribution {x_i(j), j = 1, … |A_i|}, multiplied by a large constant 1/?. Suppose now that player i wished to choose the probabilities of actions xit(j)s with the sole goal of maximizing the quantity 3. This is a relatively easy optimization problem, because the quantity 3 to be maximized is strictly concave, and therefore it has a unique maximum, obtained through the Karush–Kuhn–Tucker conditions of optimality (8) (SI Text, section 4):Uit(j)−1ϵ(1+ln⁡xit(j))+μt=0.[Here μ^t is the Lagrange multiplier associated with the constraint ∑jxit(j)=1 seeking to keep the xit(j)s a probability distribution; see SI Text.] Subtracting this equation from its homolog with t replaced by t + 1, and applying the approximation exp(ϵuit(j))≈(1+ϵuit(j)), we obtain the precise Eq. 2 (the normalization Z^t is obtained from μ^t and μ^t+1; see SI Text for the more detailed derivation).Thus, because Eqs. 1 and 2 are identical, we conclude that, in the weak selection regime, natural selection is tantamount to each locus choosing at each generation its allele frequencies in the population so as to maximize the sum of the expected cumulative differential fitness over the alleles, plus the distribution’s entropy. Note that quantity 3 is maximized by genes, not by individuals, and that, interestingly, it is maximized with respect to current frequencies while being dependent (through U^t) on all past frequencies, and although there is some precedent to the use of “historical fitness” (9), its importance in this context is unexpected.This alternative view of selection provides a new insight into an important question in evolutionary biology, namely: How is genetic diversity maintained in the presence of natural selection (10)? That the MWUA process enhances the entropy of the alleles’ distribution (while at the same time optimizes expected cumulative utility) hints at such a mechanism. In fact, entropy is enhanced inversely proportional to s (the quantity corresponding in the population genetics domain to the parameter ε), the selection strength: The weaker the selection, the more it favors high entropy. Naturally, entropy will eventually vanish when the process quiesces at equilibrium: One allele per locus will eventually be fixed, and in fact this equilibrium may be a local, as opposed to global, fitness maximum. However, we believe that it is interesting and significant that the entropy of the allele distribution is favored by selection in the transient; in any event, mutations, environmental changes, and finite population effects are likely to change the process before equilibrium is reached. This new way of understanding the maintenance of variation in evolution (selection as a tradeoff between fitness and entropy maximization) is quite different from previous hypotheses for the maintenance of variation (e.g., refs. 11, 12). Another rather surprising consequence of this characterization is that, under weak selection, all past generations, no matter how distant, have equal influence on the change in the allele mix of the current generation.Our discussion has focused on the evolution of a fixed set of alleles; that is, we have not discussed mutations. Mutations are, of course, paramount in evolution, as they are the source of genetic diversity, and we believe that introducing mutations to the present analysis is an important research direction. Here we focus on the selection process, which is rigorously shown to be tantamount to a tradeoff, for each locus, between maximizing diversity and maximizing expected cumulative fitness.We can now note a simple yet important point. Because multiplicative weight updates by the loci operate in the presence of sex, the triple connection uncovered in this paper is informative for the “queen of problems in evolutionary biology,” namely the role of sex in evolution (13, 14). The notion that the role of sex is the maintenance of diversity has been critiqued (15), because sex does not always increase diversity, and diversity is not always favorable. The MWUA connection sheds new light on the debate, because sex is shown to lead to a tradeoff between increasing entropy and increasing (cumulative) fitness.The connection between the three fields, evolution, game theory, and learning algorithms, described here was not accessible to the founders of the modern synthesis, and we hope that it expands the mathematical tracks that can be traveled in evolution theory.     

Diarrhoea-related hospitalizations in children before and after implementation of monovalent rotavirus vaccination in Mexico

Objective

To assess, by socioeconomic setting, the effect of nationwide vaccination against species A rotavirus (RVA) on childhood diarrhoea-related hospitalizations in Mexico.

Methods

Data on children younger than 5 years who were hospitalized for diarrhoea in health ministry hospitals between 1 January 2003 and 31 December 2011 were collected from monthly discharge reports. Human development indexes were used to categorize the states where hospitals were located as having generally high, intermediate or low socioeconomic status. Annual rates of hospitalization for diarrhoea – per 10 000 hospitalizations for any cause – were calculated. Administrative data were used to estimate vaccine coverage.

Findings

In the states with high, intermediate and low socioeconomic status, coverage with a two-dose monovalent RVA vaccine – among children younger than 5 years – had reached 93%, 86% and 71%, respectively, by 2010. The corresponding median annual rates of hospitalization for diarrhoea – per 10 000 admissions – fell from 1001, 834 and 1033 in the “prevaccine” period of 2003–2006, to 597, 497 and 705 in the “postvaccine” period from 2008 to 2011, respectively. These decreases correspond to rate reductions of 40% (95% confidence interval, CI: 38–43), 41% (95% CI: 38–43) and 32% (95% CI: 29–34), respectively. Nationwide, RVA vaccination appeared to have averted approximately 16 500 hospitalizations for childhood diarrhoea in each year of the postvaccine period.

Conclusion

Monovalent RVA vaccination has substantially reduced childhood diarrhoea-related hospitalizations for four continuous years in discretely different socioeconomic populations across Mexico.     

Development of a tetra-primer ARMS PCR-based assay for detection of a novel single-nucleotide polymorphism in the 5′ untranslated region of the bovine ITGB6 receptor gene associated with foot-and-mouth disease susceptibility in cattle

ITGB6 is known to be one of the major receptor components involved in host tropism of foot-and-mouth disease (FMD) virus in cattle. A competitive PCR technique called ARMS PCR was adapted to identify a single-nucleotide polymorphism (SNP), G29A, db SNP Id: rs109075046, in the 5′ untranslated region (5′UTR) of the bovine ITGB6 gene. Genotype profiling identified three kinds of genetic variation within the targeted SNP among Frieswal crossbred cattle. The occurrence of FMD in the three genotypes was further evaluated, revealing a clear role in the incidence of FMD in the studied population.     

Detection,removal and prevention of calculus: Literature Review

Dental plaque is considered to be a major etiological factor in the development of periodontal disease. Accordingly, the elimination of supra- and sub-gingival plaque and calculus is the cornerstone of periodontal therapy. Dental calculus is mineralized plaque; because it is porous, it can absorb various toxic products that can damage the periodontal tissues. Hence, calculus should be accurately detected and thoroughly removed for adequate periodontal therapy. Many techniques have been used to identify and remove calculus deposits present on the root surface. The purpose of this review was to compile the various methods and their advantages for the detection and removal of calculus.     

Prevalence of chronic disease in older adults in multitier eye-care facilities in South India: Electronic medical records-driven big data analytics report

Purpose:To study the prevalence of systemic conditions in older adults, either self-reported or discovered during routine eye examinations, at multitier eye-care facilities over the past decade, and to explore their association with vision and common ocular disorders, including cataract, glaucoma, and retinopathy.Methods:Retrospective review of a large data set compiled from the electronic medical records of patients older than 60 years who presented to an eye facility of a multitier ophthalmology network located in 200 different geographical locations that included urban and rural eye-care centers spread across four states in India over a 10-year period.Results:618,096 subjects aged 60 or older were identified as visiting an eye facility over the 10-year study period. The mean age of the study individuals was 67·28 (±6·14) years. A majority of older adults (66·96%) reported being free of systemic illnesses. Patients from lower socioeconomic status had a lower prevalence of chronic systemic disease, but the presenting vision was poorer. Hypertension (21·62%) and diabetes (18·77%) were the most commonly reported chronic conditions in patients who had concomitant systemic illness with visual concerns.Conclusion:The prevalence of chronic systemic illnesses in older adults presenting to multitier eye-care facilities is relatively low, except in those with diabetic retinopathy. These observations suggest a need to include active screening for common chronic diseases in standalone eye-care facilities to achieve a more accurate assessment of chronic disease burden in the older population.     

ZEUS (ZIF-based electrochemical ultrasensitive screening) device for isopentane analytics with focus on lung cancer diagnosis

Breath analytics is currently being explored for the development of point-of-care devices in non-invasive disease detection. It is based on the measurement of volatile organic compounds (VOCs) and gases that are produced by the body because of the metabolic pathways. The levels of these metabolites vary due to alteration in the endogenous oxidative stress-related metabolic pathways and can be correlated to understand the underlying disease condition. The levels of exhaled hydrocarbons in human breath can be used to design a rapid, easy to use method for lung cancer detection. This work outlines the development of an electrochemical sensing platform that can be used for the non-invasive diagnosis of lung cancer by monitoring isopentane levels in breath. This electrochemical sensor platform involves the use of [BMIM]BF₄@ZIF-8 for sensing the target analyte. This synthesized nanocomposite offers advantages for gas sensing applications as it possesses unique properties such as an electrochemically active Room Temperature Ionic Liquid (RTIL) and a crosslinking Metal Organic Framework (MOF) that provides increased surface area for gas absorption. This is the first report of a hydrocarbon-based sensor platform developed for lung cancer diagnosis. The developed sensor platform displays sensitivity and specificity for the detection of isopentane up to 600 parts-per-billion. We performed structural and morphological characterization of the synthesized nanocomposite using various analytical techniques such as PXRD, FESEM, FTIR, and DLS. We further analyzed the electrochemical activity of the synthesized nanocomposite using a standard glassy carbon electrode. The application of the nanocomposite for isopentane sensing was done using a commercially available carbon screen printed electrode. The results so obtained helped in strengthening our hypothesis and serve as a proof-of-concept for the development of a breathomics-enabled electrochemical strategy. We illustrated the specificity of the developed nanocomposite by cross-reactivity studies. We envision that the detection platform will allow sensitive and specific sensing of isopentane levels such that it can used for point of care applications in noninvasive and early diagnosis of lung cancer, thereby leading to its early treatment and decrease in mortality rate.

A novel synthesized [BMIM]BF₄@ZIF-8 nanocomposite for electrochemical sensing of isopentane as a biomarker for lung cancer diagnosis.     

Adenylate cyclase activator forskolin alleviates intracerebroventricular propionic acid-induced mitochondrial dysfunction of autistic rats

Neuronal mitochondrial dysfunction increases inflammatory mediators and leads to free radical generation and anti-oxidant enzymatic alterations,which are major neuropathological hallmarks responsible for autism.Mitochondrial dysfunction in autism is associated with decreased ATP levels due to reduced levels of cyclic adenosine monophosphate.Rat models of autism were established by intracerebroventricular injection of propionic acid.These rat models had memory dysfunction,decreased muscle coordination and gait imbalance.Biochemical estimation of propionic acid-treated rats showed changes in enzyme activity in neuronal mitochondrial electron transport chain complexes and increases in pro-inflammatory cytokines,oxidative stress and lipid biomarkers.Oral administration of 10,20 and 30 mg/kg adenylate cyclase activator forskolin for 15 days reversed these changes in a dose-dependent manner.These findings suggest that forskolin can alleviate neuronal mitochondrial dysfunction and improve neurological symptoms of rats with autism.This study was approved by the RITS/IAEC,SIRSA,HARYANA on March 3,2014(approval No.RITS/IAEC/2014/03/03).     

HIV Transmission Risk Behavior Among HIV-Positive Patients Receiving Antiretroviral Therapy in KwaZulu-Natal,South Africa

The aim of this investigation was to identify factors associated with HIV transmission risk behavior among HIV-positive women and men receiving antiretroviral therapy (ART) in KwaZulu-Natal, South Africa. Across 16 clinics, 1,890 HIV+ patients on ART completed a risk-focused audio computer-assisted self-interview upon enrolling in a prevention-with-positives intervention trial. Results demonstrated that 62 % of HIV-positive patients’ recent unprotected sexual acts involved HIV-negative or HIV status unknown partners. For HIV-positive women, multivariable correlates of unprotected sex with HIV-negative or HIV status unknown partners were indicative of poor HIV prevention-related information and of sexual partnership-associated behavioral skills barriers. For HIV-positive men, multivariable correlates represented motivational barriers, characterized by negative condom attitudes and the experience of depressive symptomatology, as well as possible underlying information deficits. Findings suggest that interventions addressing gender-specific and culturally-relevant information, motivation, and behavioral skills barriers could help reduce HIV transmission risk behavior among HIV-positive South Africans.