Deep Learning Algorithms Improve Automated Identification of Chagas Disease Vectors

This is a pre-copyedited, author-produced version of an article accepted for publication in Journal of Medical Entomology following peer review. The version of record is available online at: https;//doi.org/https://doi.org/10.1093/jme/tjz065Vector-borne Chagas disease is endemic to the Americas and imposes significant economic and social burdens on public health. In a previous contribution, we presented an automated identification system that was able to discriminate among 12 Mexican and 39 Brazilian triatomine (Hemiptera: Reduviidae) species from digital images. To explore the same data more deeply using machine-learning approaches, hoping for improvements in classification, we employed TensorFlow, an open-source software platform for a deep learning algorithm. We trained the algorithm based on 405 images for Mexican triatomine species and 1,584 images for Brazilian triatomine species. Our system achieved 83.0 and 86.7% correct identification rates across all Mexican and Brazilian species, respectively, an improvement over comparable rates from statistical classifiers (80.3 and 83.9%, respectively). Incorporating distributional information to reduce numbers of species in analyses improved identification rates to 95.8% for Mexican species and 98.9% for Brazilian species. Given the ‘taxonomic impediment’ and difficulties in providing entomological expertise necessary to control such diseases, automating the identification process offers a potential partial solution to crucial challenges

The present universe in the Einstein frame, metric-affine R+1/R gravity

We study the present, flat isotropic universe in 1/R-modified gravity. We use the Palatini (metric-affine) variational principle and the Einstein (metric-compatible connected) conformal frame. We show that the energy density scaling deviates from the usual scaling for nonrelativistic matter, and the largest deviation occurs in the present epoch. We find that the current deceleration parameter derived from the apparent matter density parameter is consistent with observations. There is also a small overlap between the predicted and observed values for the redshift derivative of the deceleration parameter. The predicted redshift of the deceleration-to-acceleration transition agrees with that in the \Lambda-CDM model but it is larger than the value estimated from SNIa observations.Comment: 11 pages; published versio

The cosmic snap parameter in f(R) gravity

We derive the expression for the snap parameter in f(R) gravity. We use the Palatini variational principle to obtain the field equations and regard the Einstein conformal frame as physical. We predict the present-day value of the snap parameter for the particular case f(R)=R-const/R, which is the simplest f(R) model explaining the current acceleration of the universe.Comment: 9 pages; published versio

Acceleration of the universe in the Einstein frame of a metric-affine f(R) gravity

We show that inflation and current cosmic acceleration can be generated by a metric-affine f(R) gravity formulated in the Einstein conformal frame, if the gravitational Lagrangian L(R) contains both positive and negative powers of the curvature scalar R. In this frame, we give the equations for the expansion of the homogeneous and isotropic matter-dominated universe in the case L(R)=R+{R^3}/{\beta^2}-{\alpha^2}/{3R}, where \alpha and \beta are constants. We also show that gravitational effects of matter in such a universe at very late stages of its expansion are weakened by a factor that tends to 3/4, and the energy density of matter \epsilon scales the same way as in the \Lambda-CDM model only when \kappa*\epsilon<<\alpha.Comment: 12 pages; published versio

A Sudden Gravitational Transition

We investigate the properties of a cosmological scenario which undergoes a gravitational phase transition at late times. In this scenario, the Universe evolves according to general relativity in the standard, hot Big Bang picture until a redshift z \lesssim 1. Non-perturbative phenomena associated with a minimally-coupled scalar field catalyzes a transition, whereby an order parameter consisting of curvature quantities such as R^2, R_{ab}R^{ab}, R_{abcd}R^{abcd} acquires a constant expectation value. The ensuing cosmic acceleration appears driven by a dark-energy component with an equation-of-state w < -1. We evaluate the constraints from type 1a supernovae, the cosmic microwave background, and other cosmological observations. We find that a range of models making a sharp transition to cosmic acceleration are consistent with observations.Comment: 8 pages, 8 figures; added reference

f(R) Gravity and scalar-tensor theory

In the present paper we will investigate the relation between scalar-tensor theory and $f(R)$ theories of gravity. Such studies have been performed in the past for the metric formalism of $f(R)$ gravity; here we will consider mainly the Palatini formalism, where the metric and the connections are treated as independent quantities. We will try to investigate under which circumstances $f(R)$ theories of gravity are equivalent to scalar-tensor theory and examine the implications of this equivalence, when it exists.Comment: minor changes to match published version, references adde

Consistent modified gravity: dark energy, acceleration and the absence of cosmic doomsday

We discuss the modified gravity which includes negative and positive powers of the curvature and which provides the gravitational dark energy. It is shown that in GR plus the term containing negative power of the curvature the cosmic speed-up may be achieved, while the effective phantom phase (with $w$ less than -1) follows when such term contains the fractional positive power of the curvature. The minimal coupling with matter makes the situation more interesting: even 1/R theory coupled with the usual ideal fliud may describe the (effective phantom) dark energy. The account of $R^2$ term (consistent modified gravity) may help to escape of cosmic doomsday.Comment: LaTeX file, 9 pages, based on the talk given by S.D. Odintsov (Int. Conference Mathematical Methods in Physics, Rio de Janeiro, Augest, 2004), to appear in CQG, Letter

Automated identification of insect vectors of Chagas disease in Brazil and Mexico: the Virtual Vector Lab

Identification of arthropods important in disease transmission is a crucial, yet difficult, task that can demand considerable training and experience. An important case in point is that of the 150+ species of Triatominae, vectors of Trypanosoma cruzi, causative agent of Chagas disease across the Americas. We present a fully automated system that is able to identify triatomine bugs from Mexico and Brazil with an accuracy consistently above 80%, and with considerable potential for further improvement. The system processes digital photographs from a photo apparatus into landmarks, and uses ratios of measurements among those landmarks, as well as (in a preliminary exploration) two measurements that approximate aspects of coloration, as the basis for classification. This project has thus produced a working prototype that achieves reasonably robust correct identification rates, although many more developments can and will be added, and—more broadly—the project illustrates the value of multidisciplinary collaborations in resolving difficult and complex challenges

Interplay in the Selection of Fluoroquinolone Resistance and Bacterial Fitness

Fluoroquinolones are antibacterial drugs that inhibit DNA Gyrase and Topoisomerase IV. These essential enzymes facilitate chromosome replication and RNA transcription by regulating chromosome supercoiling. High-level resistance to fluoroquinolones in E. coli requires the accumulation of multiple mutations, including those that alter target genes and genes regulating drug efflux. Previous studies have shown some drug-resistance mutations reduce bacterial fitness, leading to the selection of fitness-compensatory mutations. The impact of fluoroquinolone-resistance on bacterial fitness was analyzed in constructed isogenic strains carrying up to 5 resistance mutations. Some mutations significantly decreased bacterial fitness both in vitro and in vivo. We identified low-fitness triple-mutants where the acquisition of a fourth resistance mutation significantly increased fitness in vitro and in vivo while at the same time dramatically decreasing drug susceptibility. The largest effect occurred with the addition of a parC mutation (Topoisomerase IV) to a low-fitness strain carrying resistance mutations in gyrA (DNA Gyrase) and marR (drug efflux regulation). Increased fitness was accompanied by a significant change in the level of gyrA promoter activity as measured in an assay of DNA supercoiling. In selection and competition experiments made in the absence of drug, parC mutants that improved fitness and reduced susceptibility were selected. These data suggest that natural selection for improved growth in bacteria with low-level resistance to fluoroquinolones could in some cases select for further reductions in drug susceptibility. Thus, increased resistance to fluoroquinolones could be selected even in the absence of further exposure to the drug