A cost-effective algae-based biosensor for water quality analysis: Development and testing in collaboration with peasant communities

New anthropic potentially harmful compounds are released into the environment everyday. In this context, broad range bioassays have emerged providing economically viable and widely applicable alternatives due to their ability to detect the cumulative toxicity of mixtures of both known and unknown chemicals in a sample, thus allowing direct information about water quality. Here we present a low-cost, wide-range algae-based biosensor that is easy to assemble and operate by untrained users and provides direct readings. It was developed as a request of a peasant social movement organization to assess the toxicity of drinking water in rural communities affected by pesticide spraying. Two fresh water algae strains, Scenedesmus acutus and Pseudokirchneriella subcapitata, were immobilized in alginate beads and tested as bioindicators. After incubation with different pollutants for five days, naked eye analysis by several observers proved to be a successful method to survey algae’s growth and establish the detection limits. Best detection limits were 10 ppm for technical-grade acid glyphosate, 15 ppm for glyphosate-based formulation, 50 ppb for atrazine formulation, 7.5 ppm for copper and 250 ppb for chromium. Absorbance measurements upon algae resuspension validated these results. The developed device was successfully tested in participatory workshops conducted at rural communities. Children, adults and elders with no scientific training were able to build the sensor and interpret the results, thus evaluating the quality of rain and well water used in their communities.Universidad Nacional de Santiago del EsteroConsejo Nacional de Investigaciones Científicas y Técnica

OARSI/OMERACT Initiative to Define States of Severity and Indication for Joint Replacement in Hip and Knee Osteoarthritis. An OMERACT 10 Special Interest Group

To define pain and physical function cutpoints that would, coupled with structural severity, define a surrogate measure of “need for joint replacement surgery,” for use as an outcome measure for potential structure-modifying interventions for osteoarthritis (OA)

Mathematical and Computational Initiatives from the University of Buenos Aires to Contribute to Decision-Making in the Context of COVID-19 in Argentina. REVIEW

With the arrival of the pandemic in Argentina in March 2020, a working group of scientists from two institutes belonging to the Faculty of Exact and Natural Sciences of the University of Buenos Aires and CONICET, together with colleagues from different academic institutions in the country, decided to put forth our experience and knowledge in data science and associated disciplines, towards helping with decision-making in the context of COVID-19. Data analysis within Argentina and other countries, scenario simulation, as well as rapid response projects- mainly in the province of Buenos Aires- were all within the scope of our aim. This review article outlines some of the activities carried out by our team throughout these pandemic months.publishedVersionFil: Arrar, Mehrnoosh. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina.Fil: Arrar, Mehrnoosh. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Cálculo; Argentina.Fil: Arrar, Mehrnoosh. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigación en Ciencias de la Computación; Argentina.Fil: Belloli, Laouen Mayal Louan. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales.; Argentina.Fil: Belloli, Laouen Mayal Louan. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Cálculo; Argentina.Fil: Belloli, Laouen Mayal Louan. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigación en Ciencias de la Computación; Argentina.Fil: Bianco, Ana María. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina.Fil: Bianco, Ana María. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigación en Ciencias de la Computación; Argentina.Fil: Bianco, Ana María. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Cálculo; Argentina.Fil: Boechi, Leonardo. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina.Fil: Boechi, Leonardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigación en Ciencias de la Computación; Argentina.Fil: Boechi, Leonardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Cálculo; Argentina.Fil: Castro, Rodrigo Daniel. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina.Fil: Castro, Rodrigo Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigación en Ciencias de la Computación; Argentina.Fil: Castro, Rodrigo Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Fil: Duran, Guillermo Alfredo. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Calculo; Argentina.Fil: Duran, Guillermo Alfredo. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigación en Ciencias de la Computación; Argentina.Fil: Duran, Guillermo Alfredo. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Cálculo; Argentina.Fil: Etchenique, Roberto Argentino. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina.Fil: Etchenique, Roberto Argentino. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Química, Física de los Materiales, Medioambiente y Energía; Argentina.Fil: Fernández, Natalia Brenda. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina.Fil: Fernández, Natalia Brenda. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Biociencias, Biotecnología y Biología Traslacional; Argentina.Fil: Ferrer, Luciana. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina.Fil: Ferrer, Luciana. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigación en Ciencias de la Computación; Argentina.Fil: Garbervetsky, Diego David. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina.Fil: Garbervetsky, Diego David. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigación en Ciencias de la Computación; Argentina.Fil: Goldsmit, Rodrigo. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina.Fil: Grillo, Carolina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina.Fil: Kamienkowsk, Juan E. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina.Fil: Kamienkowsk, Juan E. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigación en Ciencias de la Computación; Argentina.Fil: Laciana, Pablo. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina.Fil: Laciana, Pablo. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigación en Ciencias de la Computación; Argentina.Fil: Lanzarotti, Esteban. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina.Fil: Lanzarotti, Esteban. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigación en Ciencias de la Computación; Argentina.Fil: Lozano, Mario Enrique. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina.Fil: Lozano, Mario Enrique. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Fil: Maidana, Rodrigo. Universidad Nacional de La Plata. Facultad de Ciencias Exactas; Argentina. esFil: Mendiluce, Mauricio. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina.Fil: Minoldo, Sol. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro de Investigaciones y Estudios sobre Cultura y Sociedad; Argentina.Fil: Pepino, Leonardo Daniel. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina.Fil: Pepino, Leonardo Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigación en Ciencias de la Computación; Argentina.Fil: Pecker Marcosig, Ezequiel. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina.Fil: Pecker Marcosig, Ezequiel. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigación en Ciencias de la Computación; Argentina.Fil: Puerta, Ezequiel. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina.Fil: Puerta, Ezequiel. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigación en Ciencias de la Computación; Argentina.Fil: Quiroga, Rodrigo. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas; Argentina.Fil: Quiroga, Rodrigo. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Físico-química de Córdoba; Argentina.Fil: Solovey, Guillermo. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina.Fil: Solovey, Guillermo. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Calculo; Argentina.Fil: Valdora, Marina Silvia. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina.Fil: Valdora, Marina Silvia. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Calculo; Argentina.Fil: Zapatero, Mariano. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina.Fil: Zapatero, Mariano. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigación en Ciencias de la Computación; Argentina

BeEP Server: using evolutionary information for quality assessment of protein structure models

The BeEP Server is an online resource aimed to help in the endgame of protein structure prediction. It is able to rank submitted structural models of a protein through an explicit use of evolutionary information, a criterion differing from structural or energetic considerations commonly used in other assessment programs. The idea behind BeEP (Best Evolutionary Pattern) is to benefit from the substitution pattern derived from structural constraints present in a set of homologous proteins adopting a given protein conformation. The BeEP method uses a model of protein evolution that takes into account the structure of a protein to build site-specific substitution matrices. The suitability of these substitution matrices is assessed through maximum likelihood calculations from which position-specific and global scores can be derived. These scores estimate how well the structural constraints derived from each structural model are represented in a sequence alignment of homologous proteins. Our assessment on a subset of proteins from the Critical Assessment of techniques for protein Structure Prediction (CASP) experiment has shown that BeEP is capable of discriminating the models and selecting one or more native-like structures. Moreover, BeEP is not explicitly parameterized to find structural similarities between models and given targets, potentially helping to explore the conformational ensemble of the native state

A face detection system based on color and support vector machines

We describe a face detection algorithm, which characterizes and localizes skin regions and eyes in 2D images using color information and Support Vector Machine. The method is scale-independent, works on images of either frontal, rotated faces, with a single person or group of people, and does not require any manual setting or operator intervention. The algorithm can be used in face image database management systems both as a first step of a person identification, and to discriminate the images on the basis of the number of faces in them

An Automatic Feature Based Face Authentication System

In this paper a fully automatic face verification system is presented. A face is characterized by a vector (jet) of coefficients determined applying a bank of Gabor filters in correspondence to 19 facial fiducial points automatically localized. The identity claimed by a subject is accepted or rejected depending on a similarity measure computed among the jet characterizing the subject, and the ones corresponding to the subjects in the gallery. The performance of the system has been quantified according to the Lausanne evaluation protocol for authentication

Genome comparison of two Exiguobacterium strains from high altitude andean lakes with different arsenic resistance: identification and 3D modeling of the Acr3 efflux pump

Arsenic exists in natural systems in a variety of chemical forms, including inorganic arsenite (As [III]) and arsenate (As [V]). The majority of living organisms have evolved various mechanisms to avoid occurrence of arsenic inside the cell due to its toxicity. Common core genes include a transcriptional repressor ArsR, an arsenate reductase ArsC, and arsenite efflux pumps ArsB and Acr3. To understand arsenic resistance we have performed arsenic tolerance studies, genomic and bioinformatic analysis of two Exiguobacterium strains, S17 and N139, from the high-altitude Andean Lakes. In these environments high concentrations of arsenic were described in the water due to a natural geochemical phenomenon, therefore, these strains represent an attractive model system for the study of environmental stress and can be readily cultivated. Our experiments show that S17 has a greater tolerance to arsenite (10 mM) than N139, but similar growth in arsenate (150 mM). We sequenced the genome of the two Exiguobacterium and identified an acr3 gene in S17 as the only difference between both species regarding known arsenic resistance genes. To further understand the Acr3 we modeled the 3D structure and identified the location of relevant residues of this protein. Our model is in agreement with previous experiments and allowed us to identify a region where a relevant cysteine lies. This Acr3 membrane efflux pump, present only in S17, may explain its increased tolerance to As(III) and is the first Acr3-family protein described in Exiguobacterium genus.Fil: Ordoñez, Omar F. Planta Piloto de Procesos Industriales Microbiológicos (PROIMI). Laboratorio de Investigaciones Microbiológicas de Lagunas Andinas (CONICET); Argentina.Fil: Lanzarotti, Esteban. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Física de los Materiales, Medio Ambiente y Energía (INQUIMAE-CONICET); Argentina.Fil: Kurth, Daniel. Planta Piloto de Procesos Industriales Microbiológicos (PROIMI). Laboratorio de Investigaciones Microbiológicas de Lagunas Andinas (CONICET); Argentina.Fil: Cortez, Néstor. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Biología Molecular y Celular de Rosario (IBR-CONICET); Argentina.Fil: Farías, María E. Planta Piloto de Procesos Industriales Microbiológicos (PROIMI). Laboratorio de Investigaciones Microbiológicas de Lagunas Andinas (CONICET); Argentina.Fil: Turjanski, Adrian G. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Física de los Materiales, Medio Ambiente y Energía (INQUIMAE-CONICET); Argentina

Pooled analysis of clinical trial data evaluating the safety and effectiveness of diclofenac epolamine topical patch 1.3% for the treatment of acute ankle sprain

David R Lionberger1, Eric Joussellin2, Jillmarie Yanchick3, Merrell Magelli3,4, Arturo Lanzarotti51Southwest Orthopedic Group, LLP, Houston, TX, USA; 2Institut National du Sport, Paris, France; 3Formerly Alpharma Pharmaceuticals LLC, Piscataway, NJ, USA; 4GTx, Inc., Memphis, TN, USA; 5Institut Biochimique SA, SwitzerlandAbstract: This pooled analysis assessed the efficacy and safety of the diclofenac epolamine topical patch 1.3% (DETP) for the treatment of acute mild-to-moderate ankle sprain. Data from 2 randomized, double-blind, placebo-controlled studies enrolling 274 male and female patients aged 18 to 65 years with acute ankle sprain were pooled and evaluated. The primary end point was pain reduction on movement assessed using a 100 mm visual analog scale (VAS). Safety and tolerability were also assessed. Beginning approximately 3 hours after initial treatment, DETP-treated patients experienced statistically significant and sustained lower mean VAS scores in pain intensity on movement (mean ± SD, 54.1 ± 20.0 mm versus 60.3 ± 16.8 mm) compared with placebo-treated patients, representing a 20% versus 13% reduction in VAS pain scores from baseline (P = 0.012). This statistically significant difference in mean VAS score was maintained through day 7 (9.4 ± 14.4 mm versus 18.4 ± 18.2 mm, P < 0.0001). The DETP and placebo patches were well tolerated. These results further confirm the efficacy and safety of DETP for the treatment of acute pain from ankle sprains.Keywords: soft tissue injury, acute pain, visual analog scale, clinical trial, double-blind, safet