Deep Learning Segmentation of Lower Extremities Radiographs for an Automatic Leg Length Discrepancy Measurement.

Leg length measurement is relevant for the early diagnostic and treatment of discrepancies as they are related with orthopedic and biomechanical changes. Simple radiology constitutes the gold standard on which radiologists perform manual lower limb measurements. It is a simple task but represents an inefficient use of their time, expertise and knowledge that could be spent in more complex labors. In this study, a pipeline for semantic bone segmentation in lower extremities radiographs is proposed. It uses a deep learning U-net model and performs an automatic measurement without consuming physicians' time. A total of 20 radiographs were used to test the methodology proposed obtaining a high overlap between manual and automatic masks with a Dice coefficient value of 0.963. The obtained Spearman's rank correlation coefficient between manual and automatic leg length measurements is statistically different from cero except for the angle of the left mechanical axis. Furthermore, there is no case in which the proposed automatic method makes an absolute error greater than 2 cm in the quantification of leg length discrepancies, being this value the degree of discrepancy from which medical treatment is required.Clinical Relevance- Leg length discrepancy measurements from X-ray images is of vital importance for proper treatment planning. This is a laborious task for radiologists that can be accelerated using deep learning techniques.

Identification of RP1 as the genetic cause of retinitis pigmentosa in a multi-generational pedigree using Extremely Low-Coverage Whole Genome Sequencing (XLC-WGS).

MOTIVATION: Next-generation sequencing (NGS) technologies are decisive for discovering disease-causing variants, although their cost limits their utility in a clinical setting. A cost-mitigating alternative is an extremely low coverage whole-genome sequencing (XLC-WGS). We investigated its use to identify causal variants within a multi-generational pedigree of individuals with retinitis pigmentosa (RP). Causing progressive vision loss, RP is a group of genetically heterogeneous eye disorders with approximately 60 known causal genes. RESULTS: We performed XLC-WGS in seventeen members of this pedigree, including three individuals with a confirmed diagnosis of RP. Sequencing data were processed using Illumina's DRAGEN pipeline and filtered using Illumina's genotype quality score metric (GQX). The resulting variants were analyzed using Expert Variant Interpreter (eVai) from enGenome as a prioritization tool. A nonsense known mutation (c.1625C > G; p.Ser542*) in exon 4 of the RP1 gene emerged as the most likely causal variant. We identified two homozygous carriers of this variant among the three sequenced RP cases and three heterozygous individuals with sufficient coverage of the RP1 locus. Our data show the utility of combining pedigree information with XLC-WGS as a cost-effective approach to identify disease-causing variants.

Gemin5-dependent RNA association with polysomes enables selective translation of ribosomal and histone mRNAs.

Selective translation allows to orchestrate the expression of specific proteins in response to different signals through the concerted action of cis-acting elements and RNA-binding proteins (RBPs). Gemin5 is a ubiquitous RBP involved in snRNP assembly. In addition, Gemin5 regulates translation of different mRNAs through apparently opposite mechanisms of action. Here, we investigated the differential function of Gemin5 in translation by identifying at a genome-wide scale the mRNAs associated with polysomes. Among the mRNAs showing Gemin5-dependent enrichment in polysomal fractions, we identified a selective enhancement of specific transcripts. Comparison of the targets previously identified by CLIP methodologies with the polysome-associated transcripts revealed that only a fraction of the targets was enriched in polysomes. Two different subsets of these mRNAs carry unique cis-acting regulatory elements, the 5' terminal oligopyrimidine tracts (5'TOP) and the histone stem-loop (hSL) structure at the 3' end, respectively, encoding ribosomal proteins and histones. RNA-immunoprecipitation (RIP) showed that ribosomal and histone mRNAs coprecipitate with Gemin5. Furthermore, disruption of the TOP motif impaired Gemin5-RNA interaction, and functional analysis showed that Gemin5 stimulates translation of mRNA reporters bearing an intact TOP motif. Likewise, Gemin5 enhanced hSL-dependent mRNA translation. Thus, Gemin5  promotes polysome association of only a subset of its targets, and as a consequence, it favors translation of the ribosomal and the histone mRNAs. Together, the results presented here unveil Gemin5 as a novel translation regulator of mRNA subsets encoding proteins involved in fundamental cellular processes.

Beneficial and pathogenic plant-microbe interactions during flooding stress.

The number and intensity of flood events will likely increase in the future, raising the risk of flooding stress in terrestrial plants. Understanding flood effects on plant physiology and plant-associated microbes is key to alleviate flooding stress in sensitive species and ecosystems. Reduced oxygen supply is the main constrain to the plant and its associated microbiome. Hypoxic conditions hamper root aerobic respiration and, consequently, hydraulic conductance, nutrient uptake, and plant growth and development. Hypoxia favours the presence of anaerobic microbes in the rhizosphere and roots with potential negative effects to the plant due to their pathogenic behaviour or their soil denitrification ability. Moreover, plant physiological and metabolic changes induced by flooding stress may also cause dysbiotic changes in endosphere and rhizosphere microbial composition. The negative effects of flooding stress on the holobiont (i.e., the host plant and its associated microbiome) can be mitigated once the plant displays adaptive responses to increase oxygen uptake. Stress relief could also arise from the positive effect of certain beneficial microbes, such as mycorrhiza or dark septate endophytes. More research is needed to explore the spiralling, feedback flood responses of plant and microbes if we want to promote plant flood tolerance from a holobiont perspective.

Concurrence of Rheumatoid Arthritis and Ankylosing Spondylitis: Analysis of Seven Cases and Literature Review.

Introduction: The association of rheumatoid arthritis (RA) and ankylosing spondylitis (AS) in a single patient is a rarely described phenomenon. AS and RA are conditions that can have a high impact on the morbidity and mortality of patients. Methods: We described the clinical, epidemiological, analytical, and radiological characteristics of 81 patients with concomitant diagnosis of rheumatoid arthritis (RA) and ankylosing spondylitis (AS). Of these patients, seven were diagnosed at our hospital. A literature review was carried out using Medline, Embase, Scopus, and virtual hospital libraries, including the period from January 1950 to April 2020. Results: Regarding the results, 71% of the patients were men, with a mean age of 53 years (±14.83). RA was the first disease diagnosed in 52% of the cases. Approximately 53% of the patients had rheumatoid nodules, and 83% reported inflammatory lumbar pain during their evaluation. Erosions were observed on radiographs of the hands and/or feet in 85% of the cases, and almost all the patients (80/81) had sacroiliitis on imaging studies. Approximately 92% of the cases were rheumatoid factor (RF) positive and 90% HLA B-27 positive. Conclusions: The coexistence of RA and AS is highly uncommon. With the data obtained in this review, it seems that there exist erosive radiological patterns, positivity for RF, involvement of the axial skeleton, and rheumatoid nodules at a higher frequency than those patients with a single diagnosis of the two entities. More data are needed to corroborate this association.

In vitro Selection of High Affinity DNA and RNA Aptamers that Detect Hepatitis C Virus Core Protein of Genotypes 1 to 4 and Inhibit Virus Production in Cell Culture.

Hepatitis C virus (HCV) core is a highly conserved and multifunctional protein that forms the viral capsid, making it an attractive target for HCV detection and inhibition. Aptamers are in vitro selected, single-stranded nucleic acids (RNA or ssDNA) with growing applicability in viral diagnostics and therapy. We have carried out DNA and RNA in vitro selection against six different variants of HCV core protein: two versions of the full-length protein of genotype 1, and the hydrophilic domain of genotypes 1 to 4. The aptamer populations obtained were analyzed by means of Ultra-Deep Sequencing (UDS), the most abundant sequences were identified and a number of highly represented sequence motifs were unveiled. Affinity (measured as the dissociation constant, Kd) of the most abundant DNA and RNA aptamers were quantified using Enzyme-Linked OligoNucleotide Assay (ELONA)-based methods. Some aptamers with nanomolar or subnanomolar Kd values (as low as 0.4 nM) were the common outcome of DNA and RNA selections against different HCV core variants. They were tested in sandwich and competitive biosensor assays, reaching a limit of detection for HCV core of 2 pM. Additionally, the two most prevalent and high affinity aptamers were assayed in Huh-7.5 reporter cell lines infected with HCV, where they decreased both the viral progeny titer and the extracellular viral RNA level, while increasing the amount of intracellular viral RNA. Our results suggest that these aptamers inhibit HCV capsid assembly and virion formation, thus making them good candidate molecules for the design of novel therapeutic approaches for hepatitis C.

Priming of Plant Defenses against Ophiostoma novo-ulmi by Elm (Ulmus minor Mill.) Fungal Endophytes.

Some fungal endophytes of forest trees are recognized as beneficial symbionts against stresses. In previous works, two elm endophytes from the classes Cystobasidiomycetes and Eurotiomycetes promoted host resistance to abiotic stress, and another elm endophyte from Dothideomycetes enhanced host resistance to Dutch elm disease (DED). Here, we hypothesize that the combined effect of these endophytes activate the plant immune and/or antioxidant system, leading to a defense priming and/or increased oxidative protection when exposed to the DED pathogen Ophiostoma novo-ulmi. To test this hypothesis, the short-term defense gene activation and antioxidant response were evaluated in DED-susceptible (MDV1) and DED-resistant (VAD2 and MDV2.3) Ulmus minor genotypes inoculated with O. novo-ulmi, as well as two weeks earlier with a mixture of the above-mentioned endophytes. Endophyte inoculation induced a generalized transient defense activation mediated primarily by salicylic acid (SA). Subsequent pathogen inoculation resulted in a primed defense response of variable intensity among genotypes. Genotypes MDV1 and VAD2 displayed a defense priming driven by SA, jasmonic acid (JA), and ethylene (ET), causing a reduced pathogen spread in MDV1. Meanwhile, the genotype MDV2.3 showed lower defense priming but a stronger and earlier antioxidant response. The defense priming stimulated by elm fungal endophytes broadens our current knowledge of the ecological functions of endophytic fungi in forest trees and opens new prospects for their use in the biocontrol of plant diseases.

From genotypes to organisms: State-of-the-art and perspectives of a cornerstone in evolutionary dynamics.

Understanding how genotypes map onto phenotypes, fitness, and eventually organisms is arguably the next major missing piece in a fully predictive theory of evolution. We refer to this generally as the problem of the genotype-phenotype map. Though we are still far from achieving a complete picture of these relationships, our current understanding of simpler questions, such as the structure induced in the space of genotypes by sequences mapped to molecular structures, has revealed important facts that deeply affect the dynamical description of evolutionary processes. Empirical evidence supporting the fundamental relevance of features such as phenotypic bias is mounting as well, while the synthesis of conceptual and experimental progress leads to questioning current assumptions on the nature of evolutionary dynamics-cancer progression models or synthetic biology approaches being notable examples. This work delves with a critical and constructive attitude into our current knowledge of how genotypes map onto molecular phenotypes and organismal functions, and discusses theoretical and empirical avenues to broaden and improve this comprehension. As a final goal, this community should aim at deriving an updated picture of evolutionary processes soundly relying on the structural properties of genotype spaces, as revealed by modern techniques of molecular and functional analysis.

MoiRNAiFold: a novel tool for complex in silico RNA design.

Novel tools for in silico design of RNA constructs such as riboregulators are required in order to reduce time and cost to production for the development of diagnostic and therapeutic advances. Here, we present MoiRNAiFold, a versatile and user-friendly tool for de novo synthetic RNA design. MoiRNAiFold is based on Constraint Programming and it includes novel variable types, heuristics and restart strategies for Large Neighborhood Search. Moreover, this software can handle dozens of design constraints and quality measures and improves features for RNA regulation control of gene expression, such as Translation Efficiency calculation. We demonstrate that MoiRNAiFold outperforms any previous software in benchmarking structural RNA puzzles from EteRNA. Importantly, with regard to biologically relevant RNA designs, we focus on RNA riboregulators, demonstrating that the designed RNA sequences are functional both in vitro and in vivo. Overall, we have generated a powerful tool for de novo complex RNA design that we make freely available as a web server (https://moiraibiodesign.com/design/).

Stem endophytes increase root development, photosynthesis, and survival of elm plantlets (Ulmus minor Mill.).

Long-lived trees benefit from fungal symbiotic interactions in the adaptation to constantly changing environments. Previous studies revealed a core fungal endobiome in Ulmus minor which has been suggested to play a critical role in plant functioning. Here, we hypothesized that these core endophytes are involved in abiotic stress tolerance. To test this hypothesis, two core endophytes (Cystobasidiales and Chaetothyriales) were inoculated into in vitro U. minor plantlets, which were further subjected to drought. Given that elm genotypes resistant to Dutch elm disease (DED) tend to show higher abiotic stress tolerance than susceptible ones, we tested the endophyte effect on two DED-resistant and two DED-susceptible genotypes. Drought stress was moderate; endophyte presence attenuated stomata closure in response to drought in one genotype but this stress did not affect plant survival. In comparison, long-term in-vitro culture proved stressful to mock-inoculated plants, especially in DED-susceptible genotypes. Interestingly, no endophyte-inoculated plant died during the experiment, as compared to high mortality in mock-inoculated plants. In surviving plants, endophyte presence stimulated root and shoot growth, photosynthetic rates, antioxidant activity and molecular changes involving auxin-signaling. These changes and the observed endophyte stability in elm tissues throughout the experiment suggest endophytes are potential tools to improve survival and stress tolerance of DED-resistant elms in elm restoration programs.

Concomitant prediction of environmental fate and toxicity of chemical compounds.

The environmental fate of many functional molecules that are produced on a large scale as precursors or as additives to specialty goods (plastics, fibers, construction materials, etc.), let alone those synthesized by the pharmaceutical industry, is generally unknown. Assessing their environmental fate is crucial when taking decisions on the manufacturing, handling, usage, and release of these substances, as is the evaluation of their toxicity in humans and other higher organisms. While this data are often hard to come by, the experimental data already available on the biodegradability and toxicity of many unusual compounds (including genuinely xenobiotic molecules) make it possible to develop machine learning systems to predict these features. As such, we have created a predictor of the "risk" associated with the use and release of any chemical. This new system merges computational methods to predict biodegradability with others that assess biological toxicity. The combined platform, named BiodegPred (https://sysbiol.cnb.csic.es/BiodegPred/), provides an informed prognosis of the chance a given molecule can eventually be catabolized in the biosphere, as well as of its eventual toxicity, all available through a simple web interface. While the platform described does not give much information about specific degradation kinetics or particular biodegradation pathways, BiodegPred has been instrumental in anticipating the probable behavior of a large number of new molecules (e.g. antiviral compounds) for which no biodegradation data previously existed.

Changes in plant function and root mycobiome caused by flood and drought in a riparian tree.

Under increasingly harsh climatic conditions, conservation of threatened species requires integrative studies to understand stress tolerance. Riparian Ulmus minor Mill. populations have been massively reduced by Dutch Elm disease (DED). However, resistant genotypes were selected to restore lost populations. To understand the acclimation mechanisms to the succession of abiotic stresses, ramets of five DED-tolerant U. minor genotypes were subjected to flood and subsequently to drought. Physiological and biochemical responses were evaluated together with shifts in root-fungal assemblages. During both stresses, plants exhibited a decline in leaf net photosynthesis and an increase in percentage loss of stem hydraulic conductivity and in leaf and root proline content. Stomatal closure was produced by chemical signals during flood and hydraulic signals during drought. Despite broad similarities in plant response to both stresses, root-mycobiome shifts were markedly different. The five genotypes were similarly tolerant to moderate drought, however, flood tolerance varied between genotypes. In general, flood did not enhance drought susceptibility due to fast flood recovery, nevertheless, different responses to drought after flood were observed between genotypes. Associations were found between some fungal taxonomic groups and plant functional traits varying with flood and drought (e.g. proline, chlorophyll and starch content) indicating that the thriving of certain taxa depends on host responses to abiotic stress.

Gene expression trade-offs between defence and growth in English elm induced by Ophiostoma novo-ulmi.

Wilt diseases caused by vascular pathogens include some of the most damaging stresses affecting trees. Dutch elm disease (DED), caused by the fungus Ophiostoma novo-ulmi, destroyed most of North American and European elm populations in the 20th century. The highly susceptible English elm, also known as Atinian clone, suffered the highest mortality rates during the last pandemic event, probably due to its lack of genetic diversity. To study the DED pathosystem, we inoculated English elm ramets with O. novo-ulmi and evaluated xylem anatomy, molecular response, and disease symptoms. The high DED susceptibility of the clone was linked to xylem structure. The transcript levels changed significantly for 1,696 genes during O. novo-ulmi invasion. Genes covering different steps of the plant immune system were identified, many of which showed homology with Arabidopsis thaliana genes involved in systemic acquired resistance. Induction of several pathogenesis-related proteins and repression of fasciclin-like arabinogalactan proteins and other cell wall biosynthesis pathways evidence unbalanced costs between growth and defence mechanisms far from the inoculation point. This study sheds light on elm molecular defence mechanisms against DED.

New tools to analyze overlapping coding regions.

BACKGROUND: Retroviruses transcribe messenger RNA for the overlapping Gag and Gag-Pol polyproteins, by using a programmed -1 ribosomal frameshift which requires a slippery sequence and an immediate downstream stem-loop secondary structure, together called frameshift stimulating signal (FSS). It follows that the molecular evolution of this genomic region of HIV-1 is highly constrained, since the retroviral genome must contain a slippery sequence (sequence constraint), code appropriate peptides in reading frames 0 and 1 (coding requirements), and form a thermodynamically stable stem-loop secondary structure (structure requirement). RESULTS: We describe a unique computational tool, RNAsampleCDS, designed to compute the number of RNA sequences that code two (or more) peptides p,q in overlapping reading frames, that are identical (or have BLOSUM/PAM similarity that exceeds a user-specified value) to the input peptides p,q. RNAsampleCDS then samples a user-specified number of messenger RNAs that code such peptides; alternatively, RNAsampleCDS can exactly compute the position-specific scoring matrix and codon usage bias for all such RNA sequences. Our software allows the user to stipulate overlapping coding requirements for all 6 possible reading frames simultaneously, even allowing IUPAC constraints on RNA sequences and fixing GC-content. We generalize the notion of codon preference index (CPI) to overlapping reading frames, and use RNAsampleCDS to generate control sequences required in the computation of CPI. Moreover, by applying RNAsampleCDS, we are able to quantify the extent to which the overlapping coding requirement in HIV-1 [resp. HCV] contribute to the formation of the stem-loop [resp. double stem-loop] secondary structure known as the frameshift stimulating signal. Using our software, we confirm that certain experimentally determined deleterious HCV mutations occur in positions for which our software RNAsampleCDS and RNAiFold both indicate a single possible nucleotide. We generalize the notion of codon preference index (CPI) to overlapping coding regions, and use RNAsampleCDS to generate control sequences required in the computation of CPI for the Gag-Pol overlapping coding region of HIV-1. These applications show that RNAsampleCDS constitutes a unique tool in the software arsenal now available to evolutionary biologists. CONCLUSION: Source code for the programs and additional data are available at http://bioinformatics.bc.edu/clotelab/RNAsampleCDS/ .

RNAdualPF: software to compute the dual partition function with sample applications in molecular evolution theory.

BACKGROUND: RNA inverse folding is the problem of finding one or more sequences that fold into a user-specified target structure s 0, i.e. whose minimum free energy secondary structure is identical to the target s 0. Here we consider the ensemble of all RNA sequences that have low free energy with respect to a given target s 0. RESULTS: We introduce the program RNAdualPF, which computes the dual partition function Z ∗, defined as the sum of Boltzmann factors exp(-E(a,s 0)/RT) of all RNA nucleotide sequences a compatible with target structure s 0. Using RNAdualPF, we efficiently sample RNA sequences that approximately fold into s 0, where additionally the user can specify IUPAC sequence constraints at certain positions, and whether to include dangles (energy terms for stacked, single-stranded nucleotides). Moreover, since we also compute the dual partition function Z ∗(k) over all sequences having GC-content k, the user can require that all sampled sequences have a precise, specified GC-content. Using Z ∗, we compute the dual expected energy 〈E ∗〉, and use it to show that natural RNAs from the Rfam 12.0 database have higher minimum free energy than expected, thus suggesting that functional RNAs are under evolutionary pressure to be only marginally thermodynamically stable. We show that C. elegans precursor microRNA (pre-miRNA) is significantly non-robust with respect to mutations, by comparing the robustness of each wild type pre-miRNA sequence with 2000 [resp. 500] sequences of the same GC-content generated by RNAdualPF, which approximately [resp. exactly] fold into the wild type target structure. We confirm and strengthen earlier findings that precursor microRNAs and bacterial small noncoding RNAs display plasticity, a measure of structural diversity. CONCLUSION: We describe RNAdualPF, which rapidly computes the dual partition function Z ∗ and samples sequences having low energy with respect to a target structure, allowing sequence constraints and specified GC-content. Using different inverse folding software, another group had earlier shown that pre-miRNA is mutationally robust, even controlling for compositional bias. Our opposite conclusion suggests a cautionary note that computationally based insights into molecular evolution may heavily depend on the software used. C/C++-software for RNAdualPF is available at http://bioinformatics.bc.edu/clotelab/RNAdualPF .

RNAiFold2T: Constraint Programming design of thermo-IRES switches.

MOTIVATION: RNA thermometers (RNATs) are cis-regulatory elements that change secondary structure upon temperature shift. Often involved in the regulation of heat shock, cold shock and virulence genes, RNATs constitute an interesting potential resource in synthetic biology, where engineered RNATs could prove to be useful tools in biosensors and conditional gene regulation. RESULTS: Solving the 2-temperature inverse folding problem is critical for RNAT engineering. Here we introduce RNAiFold2T, the first Constraint Programming (CP) and Large Neighborhood Search (LNS) algorithms to solve this problem. Benchmarking tests of RNAiFold2T against existent programs (adaptive walk and genetic algorithm) inverse folding show that our software generates two orders of magnitude more solutions, thus allowing ample exploration of the space of solutions. Subsequently, solutions can be prioritized by computing various measures, including probability of target structure in the ensemble, melting temperature, etc. Using this strategy, we rationally designed two thermosensor internal ribosome entry site (thermo-IRES) elements, whose normalized cap-independent translation efficiency is approximately 50% greater at 42 °C than 30 °C, when tested in reticulocyte lysates. Translation efficiency is lower than that of the wild-type IRES element, which on the other hand is fully resistant to temperature shift-up. This appears to be the first purely computational design of functional RNA thermoswitches, and certainly the first purely computational design of functional thermo-IRES elements. AVAILABILITY: RNAiFold2T is publicly available as part of the new release RNAiFold3.0 at https://github.com/clotelab/RNAiFold and http://bioinformatics.bc.edu/clotelab/RNAiFold, which latter has a web server as well. The software is written in C ++ and uses OR-Tools CP search engine. CONTACT: clote@bc.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Designing synthetic RNAs to determine the relevance of structural motifs in picornavirus IRES elements.

The function of Internal Ribosome Entry Site (IRES) elements is intimately linked to their RNA structure. Viral IRES elements are organized in modular domains consisting of one or more stem-loops that harbor conserved RNA motifs critical for internal initiation of translation. A conserved motif is the pyrimidine-tract located upstream of the functional initiation codon in type I and II picornavirus IRES. By computationally designing synthetic RNAs to fold into a structure that sequesters the polypyrimidine tract in a hairpin, we establish a correlation between predicted inaccessibility of the pyrimidine tract and IRES activity, as determined in both in vitro and in vivo systems. Our data supports the hypothesis that structural sequestration of the pyrimidine-tract within a stable hairpin inactivates IRES activity, since the stronger the stability of the hairpin the higher the inhibition of protein synthesis. Destabilization of the stem-loop immediately upstream of the pyrimidine-tract also decreases IRES activity. Our work introduces a hybrid computational/experimental method to determine the importance of structural motifs for biological function. Specifically, we show the feasibility of using the software RNAiFold to design synthetic RNAs with particular sequence and structural motifs that permit subsequent experimental determination of the importance of such motifs for biological function.

RNA Thermodynamic Structural Entropy.

Conformational entropy for atomic-level, three dimensional biomolecules is known experimentally to play an important role in protein-ligand discrimination, yet reliable computation of entropy remains a difficult problem. Here we describe the first two accurate and efficient algorithms to compute the conformational entropy for RNA secondary structures, with respect to the Turner energy model, where free energy parameters are determined from UV absorption experiments. An algorithm to compute the derivational entropy for RNA secondary structures had previously been introduced, using stochastic context free grammars (SCFGs). However, the numerical value of derivational entropy depends heavily on the chosen context free grammar and on the training set used to estimate rule probabilities. Using data from the Rfam database, we determine that both of our thermodynamic methods, which agree in numerical value, are substantially faster than the SCFG method. Thermodynamic structural entropy is much smaller than derivational entropy, and the correlation between length-normalized thermodynamic entropy and derivational entropy is moderately weak to poor. In applications, we plot the structural entropy as a function of temperature for known thermoswitches, such as the repression of heat shock gene expression (ROSE) element, we determine that the correlation between hammerhead ribozyme cleavage activity and total free energy is improved by including an additional free energy term arising from conformational entropy, and we plot the structural entropy of windows of the HIV-1 genome. Our software RNAentropy can compute structural entropy for any user-specified temperature, and supports both the Turner'99 and Turner'04 energy parameters. It follows that RNAentropy is state-of-the-art software to compute RNA secondary structure conformational entropy. Source code is available at https://github.com/clotelab/RNAentropy/; a full web server is available at http://bioinformatics.bc.edu/clotelab/RNAentropy, including source code and ancillary programs.