Microplastics and anthropogenic debris in rainwater from Bahia Blanca, Argentina.

Concern about atmospheric microplastic (MP) contamination has increased in recent years. This study assessed the abundance of airborne anthropogenic particles, including MPs, deposited in rainfall in Bahia Blanca, southwest Buenos Aires, Argentina. Rainwater samples were collected monthly from March to December 2021 using an active wet-only collector consisting of a glass funnel and a PVC pipe that is only open during rain events. Results obtained show that all rain samples contained anthropogenic debris. The term "anthropogenic debris" is used to refer to the total number of particles as not all the particles found could be determined as plastic. Among all the samples, an average deposition of 77 ± 29 items (anthropogenic debris) m-2d-1 was found. The highest deposition was observed in November (148 items m-2d-1) while the lowest was found in March (46 items m-2d-1). Anthropogenic debris ranged in size from 0.1 mm to 3.87 mm with the most abundant particles being smaller than 1 mm (77.8%). The dominant form of particles found were fibers (95%), followed by fragments (3.1%). Blue color predominated (37.2%) in the total number of samples, followed by light blue (23.3%) and black (21.7%). Further, small particles (<2 mm), apparently composed of mineral material and plastic fibers, were recognized. The chemical composition of suspected MPs was examined by Raman microscopy. The analysis of µ-Raman spectra confirmed the presence of polystyrene, polyethylene terephthalate, and polyethylene vinyl acetate fibers and provided evidence of fibers containing industrial additives such as indigo dye. This is the first assessment of MP pollution in rain in Argentina.

Multi-year monitoring of atmospheric dust fall as a sink for lead in an agro-industrial and petrochemical city of Argentina. Geo-accumulation and ecological risk assessment.

A multi-year monitoring data set of potentially harmful elements (PHEs), which are present in the chemical composition of atmospheric settleable particulate matter (SPM) in the urban, industrial and port areas in Bahía Blanca, was studied in order to assess potential ecological risk. The selected PHEs were metal elements of local and regional environmental importance (Cd, Cr, Cu, Ni, Pb, and Zn). Seventeen sampling campaigns were carried out between April 2013 and September 2019. After the microwave-assisted acid digestion of samples, the total contents of the PHEs were determined by ICP-OES. The annual dry deposition rate, the indexes associated with the potential ecological risk (RI) and the degree of geo-accumulation (Igeo) of each PHE were calculated. The results indicated that: (a) there are 3 groups (I, II, III) of PHEs with differentiated concentration levels, ranked I (Pb > Zn > Cu) > II (Cr ≈ Ni) > III (Cd) (p < 0.01) in all the studied areas; (b) the median of the total deposition rate was 1 mg cm-2. month-1 with a significant relative contribution of Pb; (c) a considerable increase in geo-accumulation of Pb indicated that SPM was functioning as a sink for Pb, and also reflected a significant progressive increase in the potential ecological risk in all sites (p < 0.01); and (d) there were chemometrically identified potential sources of Pb, Cu and Zn emissions that would be associated mainly to the resuspension of dust from geogenic, industrial and urban origin, and to a lesser extent, to other gaseous emissions of the industrial sector. This work highlights three major aspects of environmental assessment: (a) the value of continuous monitoring as an important tool to detect long-term trends; (b) the importance of the role of dust fall as a useful environmental indicator of lead geo-accumulation; and (c) the great utility of geo-accumulation and potential ecological risk indices as rapid quantitative assessment tools of environmental pollution.

Microbiological quality and determination of pesticide residues in the lettuce produced in Bahía Blanca's horticultural belt, Argentina.

The aims of this research were 1) to find out the possible microbiological contamination and residues of pesticides (chlorpyrifos and cypermethrin) in lettuce grown in Bahía Blanca's horticultural belt, and bacteriological quality of waters used for irrigation and post-harvest washing, 2) to investigate and compare the internalization capacity of a strain of Escherichia coli isolated from irrigation water with another hospital uropathogenic strain. Some strains of bacteria can internalize into the plant tissue. This capability presents food safety threats as they cannot be removed with standard sanitation practices. To determine bacteriological quality of lettuce, E. coli, Salmonella spp and E. coli O157: H7/NM (n = 10) were investigated. Bacteriological quality of water was determined by quantification of fecal coliforms/100 mL (n = 20). Pesticides were determined by using an improved and validated QuEChERS method combined with GC-MSD. Irrigation water in 19/20 samples did not present health risk. Bacteriological quality of lettuce met demands in 9/10 samples. Pesticides were detected in half of the samples, values exceeding the FAO recommendations. An effort is strongly recommended to implement both, best phytosanitary practices and monitoring programmes. Uropathogenic strain was able to internalize into plant tissue, while the nonpathogenic one was not.

Redes de atención en salud: alcances territoriales y colaboración institucional en el seguimiento de pacientes pediátricos en la Red del Sudeste Bonaerense / Health care networks: territories and institutional collaboration for extended treatments of pediatric patients within Southeastern Metropolitan Area of Buenos Aires

OBJETIVO: Este trabajo presenta el inicio de un proyecto de largo término que analiza la dinámica local de circulación de pacientes y colaboración profesional entre el conjunto de efectores localizados en los partidos de Florencio Varela, Berazategui, Alte. Brown y Quilmes, denominado la Red del Sudeste Bonaerense. Ésta articula efectores de primer, segundo y tercer nivel de atención (169 en total), asiste a 2 millones de personas anualmente en una de las áreas con mayor población del país y con altos niveles de necesidades básicas insatisfechas. METODOLOGÍA: La metodología se plantea desde los métodos mixtos que articulan técnicas cualitativas y cuantitativas para la recolección, procesamiento y análisis de la información de los efectores de la Red, a partir de: registros de pacientes pediátricos, datos epidemiológicos y trabajo de campo etnográfico. Complementariamente, se articulan tres líneas multi-disciplinarias: Análisis de sistemas y servicios de salud en red; Análisis espacial entre centros de salud; Análisis de redes sociales (identifica estructuras y dinámicas de flujo y colaboración). RESULTADOS: Los resultados sugieren: a) la estructura de derivaciones la HEC tiene una forma de "estrella", b) mayor cantidad de derivaciones desde los distritos de la Red del Sudeste que de otros efectores, c) Coeficiente de Jaccard es bajo, d) dificultades en el mecanismo de contra-referencia, e) la estructura de colaboración entre 25 especialidades es un modelo "centro/periferia", f) emergen subgrupos de acuerdo a las patologías derivadas. CONCLUSIÓN: Se concluye con una discusión sobre la importancia de la interacción estructural entre las especialidades para la atención compleja de patologías pediátricas. Finalmente, la centralidad del HEC en la dinámica de derivaciones pediátricas se corresponde con su condición de único efector de tercer nivel de la región, su robusta comunicación con los efectores en el territorio así como por su posicionamiento como referente nacional de derivación por patologías específicas.

OBJECTIVE: This paper presents the beginning of a long-term project that analyses local dynamics of patient transfers and professional collaboration among a formal assistance network of health providers called the "Southeastern Network" localized in four districts in the Metropolitan Area of Buenos Aires: F. Varela, Berazategui, Alte. Brown y Quilmes. This network connects primary, secondary and tertiary care levels (169 in total) and assists over 2 million people annually in the region, one of the most populated and deprived areas in Argentina. METHODS: Methodological strategies point toward a mixed methods approach, which articulates qualitative and quantitative methods for collecting, processing and analyzing the information from the network care providers: patients institutional registers, epidemiological data and ethnographic field work.Additionally, we follow three multi-disciplinary lines: health systems and services analysis, special analysis regarding care providers, Social Network Analysis (identifying structures and dynamics of patients flow and professional collaboration). RESULTS: Suggest: a) the structure of patients' referral is "star" model b) there are more referrals from the Network's districts than from other areas c) Jaccard Coefficient is low, d) there are some difficulties in counter-referral mechanisms e) professional collaboration structure among 25 medical specialties is a "center/periphery" model f) some subgroups emerge from assisting certain pathologies. CONCLUSIONS: We conclude with a discussion on the importance of structural interaction among medical specialties for complex pediatric care. Finally, the centrality of El Cruce Hospital within pediatric referrals in this area correspond to the fact that it is the only tertiary care provider, it maintains robust communications with other care providers and it is positioned as national reference for specific pathologies referral.

Unidad de terapia intensiva pediátrica II: repercusiones en el intercambio asistencial de la Red Pediátrica / Pediatric intensive care unit II: impact on the in-network pediatric health care exchange

INTRODUCCIÓN En el año 2012 como consecuencia de la necesidad asistencial de generar nuevas camas en terapia intensiva pediátrica se creó la Unidad de Cuidados Intensivos pediátricos II (UTIP II) que se dedicó principalmente a la asistencia de pacientes con necesidades especiales de atención médica, con una repercusión en el intercambio asistencial y sus consecuencias indirectas en la red pediátrica no estudiadas hasta la fecha. OBJETIVOS El objetivo de nuestro estudio es analizar las repercusiones en el intercambio asistencial con la red pediátrica en la unidad de terapia intermedia pediátrica (CIPED) como consecuencia de la creación de la UTIP II. METODOS Estudio observacional, retrospectivo realizado en la CIPED del HEC, desde enero de 2009 a diciembre de 2016. Se evaluaron el nᵒ/% de derivaciones aceptadas respecto a las solicitadas, origen de los pacientes (Red/Extrared/HEC), nᵒ de egresos, % de ocupación de camas, giro cama. RESULTADOS Se observa un aumento en los rechazos de solicitudes de ingreso a CIPED a partir de 2013(p de tendencia <0,000001); comparando el período 2009/2012 (pre UTIP 2) con el período 2013/2016 considerando el origen de los pacientes ingresados a CIPED, se observa un aumento en los ingresos directos desde el HEC y un descenso de los ingresos procedentes de los hospitales de la red (p <0,000001) y un porcentaje creciente de pacientes que egresan directamente desde UTIP. El porcentaje de ocupación de cama resulto alto en los tres sectores mientras que el giro cama es bajo, intermedio y alto en la UTIP2, UTIP y CIPED respectivamente. CONCLUSIONES los indicadores evaluados alertan acerca de una disminución en la respuesta a las necesidades asistenciales de la red pediátrica desde la CIPED del HEC y evidencian ineficiencias en el sistema que atentan contra la calidad asistencial y profundización de las relaciones en la red.

INTRODUCTION The Pediatric Intensive Care Unit II (PICU II) was created in 2012,as a result of the health care need to generate new beds in pediatric intensive care. It was devote d mainly to provide care to patients with special health care needs and had an impact on health care exchange and its indirect effects in the pediatric network, which have not been studied to date. Our study aims at examining the impact of creating the PICU II on the health care exchange with the pediatric network in the pediatric intermediate care unit (PIMCU). METHODS Retrospective observational study by the PIMCU of HEC from January 2009 to December 2016. Number/percentage of accepted referrals versus requested referrals, sources of patients' referrals(In-network/ Out-of-network/ HEC), number of discharges, % of bed occupancy and bed turnover rate were evaluated. RESULTS Increased denials in admission requests to the PIMCU are observed from 2013 (P for trend <0.000001). Comparing the 2009/2012 period (pre-PICU 2) with the 2013/2016 period and considering the sources of patients admitted to the PIMCU, increased direct admissions to PIMCU, decreased admissions of patients from in-network hospitals (p <0.000001) and an increased percentage of patients discharged directly from the PICU are observed. Bed occupancy percentage was high in the three sectors while the bed turnover was low, intermediate and high in PICU2, PICU and PIMCU, respectively. CONCLUSIONS Evaluated indicators warn about a diminished response by HEC's PIMCU to pediatric network's healthcare needs and evidence system inefficiencies that target healthcare quality and relationship deepening in the network.

DNA damaging potential of Ganoderma lucidum extracts.

ETHNOPHARMACOLOGICAL RELEVANCE: Ganoderma lucidum (Lingzhi or Reishi) is a medicinal mushroom historically used in Asian countries to treat a wide variety of diseases and prolong life. In the last years, G. lucidum has been internationally recognized as an effective adjuvant in cancer treatment. Among active components, the most recent research indicates that polysaccharides modulate the immune response favoring the recovery from toxicity of chemo and radiotherapy while triterpenes are cytotoxic to tumoral cells mainly by altering gene expression. Beyond this body of evidence on the efficacy of G. lucidum in cancer treatment, it is not yet understood whether these extracts exert the same mechanisms of action than current antitumoral drugs. AIM OF THE STUDY: In this study, we tested the DNA damaging potential of G. lucidum extracts by the ß-galactosidase biochemical prophage induction assay (BIA) using doxorubicin, a DNA intercalating agent, as a positive control. This assay was traditionally used to screen microbial metabolites towards antitumoral agents. Here, we used this bacterial assay for the first time to assess DNA damage of herbal drugs. RESULTS: After a bioguided assay, only a purified fraction of G. lucidum containing a mixture of C16 and C18:1 fatty acids exerted weak activity which could not be attributed to direct interaction with DNA. At the same concentrations, the induction observed for doxorubicin was clearly contrasting. CONCLUSIONS: The micro BIA assay could be successfully used to demonstrate differences in cellular effects between G. lucidum extracts and doxorubicin. These results showed that G. lucidum extracts display weak DNA damaging potential. Since DNA injury promotes aging and cancer, our results substantiate the traditional use of this mushroom to prolong life.

Stroke Onset Time Determination Using MRI Relaxation Times without Non-Ischaemic Reference in A Rat Stroke Model.

BACKGROUND: Objective timing of stroke in emergency departments is expected to improve patient stratification. Magnetic resonance imaging (MRI) relaxations times, T2 and T1ρ , in abnormal diffusion delineated ischaemic tissue were used as proxies of stroke time in a rat model. METHODS: Both 'non-ischaemic reference'-dependent and -independent estimators were generated. Apparent diffusion coefficient (ADC), T2 and T1ρ , were sequentially quantified for up to 6 hours of stroke in rats (n = 8) at 4.7T. The ischaemic lesion was identified as a contiguous collection of voxels with low ADC. T2 and T1ρ in the ischaemic lesion and in the contralateral non-ischaemic brain tissue were determined. Differences in mean MRI relaxation times between ischaemic and non-ischaemic volumes were used to create reference-dependent estimator. For the reference-independent procedure, only the parameters associated with log-logistic fits to the T2 and T1ρ distributions within the ADC-delineated lesions were used for the onset time estimation. RESULT: The reference-independent estimators from T2 and T1ρ data provided stroke onset time with precisions of ±32 and ±27 minutes, respectively. The reference-dependent estimators yielded respective precisions of ±47 and ±54 minutes. CONCLUSIONS: A 'non-ischaemic anatomical reference'-independent estimator for stroke onset time from relaxometric MRI data is shown to yield greater timing precision than previously obtained through reference-dependent procedures.

Fast Unsupervised Bayesian Image Segmentation With Adaptive Spatial Regularisation.

This paper presents a new Bayesian estimation technique for hidden Potts-Markov random fields with unknown regularisation parameters, with application to fast unsupervised K -class image segmentation. The technique is derived by first removing the regularisation parameter from the Bayesian model by marginalisation, followed by a small-variance-asymptotic (SVA) analysis in which the spatial regularisation and the integer-constrained terms of the Potts model are decoupled. The evaluation of this SVA Bayesian estimator is then relaxed into a problem that can be computed efficiently by iteratively solving a convex total-variation denoising problem and a least-squares clustering ( K -means) problem, both of which can be solved straightforwardly, even in high-dimensions, and with parallel computing techniques. This leads to a fast fully unsupervised Bayesian image segmentation methodology in which the strength of the spatial regularisation is adapted automatically to the observed image during the inference procedure, and that can be easily applied in large 2D and 3D scenarios or in applications requiring low computing times. Experimental results on synthetic and real images, as well as extensive comparisons with state-of-the-art algorithms, confirm that the proposed methodology offer extremely fast convergence and produces accurate segmentation results, with the important additional advantage of self-adjusting regularisation parameters.

Collaborative sparse regression using spatially correlated supports--Application to hyperspectral unmixing.

This paper presents a new Bayesian collaborative sparse regression method for linear unmixing of hyperspectral images. Our contribution is twofold; first, we propose a new Bayesian model for structured sparse regression in which the supports of the sparse abundance vectors are a priori spatially correlated across pixels (i.e., materials are spatially organized rather than randomly distributed at a pixel level). This prior information is encoded in the model through a truncated multivariate Ising Markov random field, which also takes into consideration the facts that pixels cannot be empty (i.e., there is at least one material present in each pixel), and that different materials may exhibit different degrees of spatial regularity. Second, we propose an advanced Markov chain Monte Carlo algorithm to estimate the posterior probabilities that materials are present or absent in each pixel, and, conditionally to the maximum marginal a posteriori configuration of the support, compute the minimum mean squared error estimates of the abundance vectors. A remarkable property of this algorithm is that it self-adjusts the values of the parameters of the Markov random field, thus relieving practitioners from setting regularization parameters by cross-validation. The performance of the proposed methodology is finally demonstrated through a series of experiments with synthetic and real data and comparisons with other algorithms from the literature.

Exploiting information geometry to improve the convergence of nonparametric active contours.

This paper presents a fast converging Riemannian steepest descent method for nonparametric statistical active contour models, with application to image segmentation. Unlike other fast algorithms, the proposed method is general and can be applied to any statistical active contour model from the exponential family, which comprises most of the models considered in the literature. This is achieved by first identifying the intrinsic statistical manifold associated with this class of active contours, and then constructing a steepest descent on that manifold. A key contribution of this paper is to derive a general and tractable closed-form analytic expression for the manifold's Riemannian metric tensor, which allows computing discrete gradient flows efficiently. The proposed methodology is demonstrated empirically and compared with other state of the art approaches on several standard test images, a phantom positron-emission-tomography scan and a B-mode echography of in-vivo human dermis.

Quantification of uncertainty in mercury wastewater analysis at different concentration levels and using information from proficiency test with a limited number of participants.

Measurement uncertainty is one of the most required parameters of analytical quality in environmental decision-making. Several approaches have been reported for estimating uncertainty in analytical measurements. The use of proficiency test (PT) is an alternative, not only for assessing the performance of individual analytical laboratories, but also for estimating the concordance of an analytical method and their measurement uncertainties. Here we develop a PT scheme for a limited number of analytical laboratories that took part in the analysis of total mercury in samples with complex matrix (chlor-alkali process wastewater effluent) in absence of references of the highest metrological hierarchy (e.g. primary method, primary CRM). Two in-house reference materials (IHRMs) were prepared at different levels of analyte concentration and the homogeneity required was verified for the intended use. A set of parametric and robust statistical tests were applied to evaluate the assigned values of each IHRM. Metrological compatibility assessment of PT results, evaluation of individual and global performance of the laboratories, and determination of uncertainty of the analytical measurements were evaluated in this restricted study scenario. Between-laboratory differences were found not significant (α=0.05). For both concentration levels we computed a relative standard uncertainty of 30% for the total Hg content.

Estimating the granularity coefficient of a Potts-Markov random field within a Markov chain Monte Carlo algorithm.

This paper addresses the problem of estimating the Potts parameter ß jointly with the unknown parameters of a Bayesian model within a Markov chain Monte Carlo (MCMC) algorithm. Standard MCMC methods cannot be applied to this problem because performing inference on ß requires computing the intractable normalizing constant of the Potts model. In the proposed MCMC method, the estimation of ß is conducted using a likelihood-free Metropolis-Hastings algorithm. Experimental results obtained for synthetic data show that estimating ß jointly with the other unknown parameters leads to estimation results that are as good as those obtained with the actual value of ß. On the other hand, choosing an incorrect value of ß can degrade estimation performance significantly. To illustrate the interest of this method, the proposed algorithm is successfully applied to real bidimensional SAR and tridimensional ultrasound images.

Segmentation of skin lesions in 2-D and 3-D ultrasound images using a spatially coherent generalized Rayleigh mixture model.

This paper addresses the problem of jointly estimating the statistical distribution and segmenting lesions in multiple-tissue high-frequency skin ultrasound images. The distribution of multiple-tissue images is modeled as a spatially coherent finite mixture of heavy-tailed Rayleigh distributions. Spatial coherence inherent to biological tissues is modeled by enforcing local dependence between the mixture components. An original Bayesian algorithm combined with a Markov chain Monte Carlo method is then proposed to jointly estimate the mixture parameters and a label-vector associating each voxel to a tissue. More precisely, a hybrid Metropolis-within-Gibbs sampler is used to draw samples that are asymptotically distributed according to the posterior distribution of the Bayesian model. The Bayesian estimators of the model parameters are then computed from the generated samples. Simulation results are conducted on synthetic data to illustrate the performance of the proposed estimation strategy. The method is then successfully applied to the segmentation of in vivo skin tumors in high-frequency 2-D and 3-D ultrasound images.

Modeling ultrasound echoes in skin tissues using symmetric α-stable processes.

Starting from the widely accepted point-scattering model, this paper establishes, through analytical developments, that ultrasound signals backscattered from skin tissues converge to a complex Levy flight random process with non- Gaussian α-stable statistics. The envelope signal follows a generalized (heavy-tailed) Rayleigh distribution. It is shown that these signal statistics imply that scatterers have heavy-tailed power-law cross sections. This model generalizes the Gaussian framework and provides a formal representation for a new case of non-Gaussian statistics, in which both the number of scatterers and the variance of their cross sections tend to infinity. In addition, analytical expressions are derived to relate the α-stable parameters to scatterer properties. Simulations show that these expressions can be used as rigorous interpretation tools for tissue characterization. Several experimental results supported by excellent goodness-of-fit tests confirm the proposed analytical model. Finally, these fundamental results set the basis for new echography processing methods and quantitative ultrasound characterization tools.

Multi-year monitoring of estuarine sediments as ultimate sink for DDT, HCH, and other organochlorinated pesticides in Argentina.

Forty-nine superficial sediment samples used in this study were collected from eight sites in the Bahia Blanca Estuary, located in the Buenos Aires Province southwest, Argentina, in a period between April 2005 and March 2009, to assess the concentration levels, spatial and seasonal distribution, and putative input sources of 18 selected organochlorine pesticides (OCs), following UNEP-IAEA procedures. Average concentration levels in sediments ranged between 3.54 and 63.79 ng g⁻¹, d.w. (mean = 15.99 ng g⁻¹, d.w.), for ∑OCs, and from nondetectable to 8.03 ng g⁻¹, d.w. (mean = 2.16 ng g⁻¹, d.w.), and from nondetectable to 3.20 ng g⁻¹ (mean = 0.97 ng g⁻¹, d.w.) for hexachlorocyclohexanes (HCHs) and dichlorodiphenyltrichloroethanes (DDTs), respectively. Principal component analysis allowed the classification of sampling sites according to the main OCs inputs over the estuary. In comparison to other worldwide locations and to the world coastal sediment concentrations range, sediment DDTs and HCHs levels were in the low range; on the opposite, ∑OCs average was in the medium range. OCs seasonal distribution was found to be highly correlated with the precipitations seasonality and sowing seasons in the adjacent agriculture fields. In addition, an ecotoxicological risk assessment pointed industrial and agriculture catchment zones with intermediate probability of adverse effects to biota, while the city sewage outfall was classified with none indication of an immediate threat. Data indicated that the estuary sediments were functioning as a sink for persistent OC pesticides (either in use or banned), however, it was found a declining trend on their environmental burden.

An alpha-stable model for ultrasound speckle statistics in skin.

Characterization of biological tissues in ultrasound images is often tackled using empirical pre-Rayleigh distributions. However, the absence of a theoretical explanation to these distributions hinders their improvement and clinical interpretation. This paper presents a novel model that extends classic statistical theories to speckle in biological tissues and explains the existing pre-Rayleigh distributions. Furthermore, statistics derived from the proposed model outperform the state of the art in skin tissue characterization. Finally, promising results in characterization of skin melanoma tumors set the basis for the development of reliable ultrasound-based diagnosis techniques.

Lactante sibilante atípico: consideraciones diagnósticas. Hendidura laríngea / Atypical sibilant lactate: diagnostic considerations. Laryngeal cleft

El síndrome bronquial obstructivo es un motivo de consulta frecuente en la edad pediátrica. En este trabajo se presenta el caso de un paciente con antecedentes de internaciones recurrentes por infecciones respiratorias agudas bajas y trastorno de deglución con diagnóstico de hendidura laríngea. Se realiza una breve descripción de la hendidura laríngea, sus características clínicas, diagnóstico y tratamiento. Se enumeran los diagnósticos diferenciales de los niños con sibilancias atípicas, sus signos y síntomas y su evaluación inicial.