Sweat Rate, Sweat Sodium Losses, and Body Composition in Professional Male Soccer Players in Southwest Colombia.

Background and Objective: Dehydration and hyperhydration impact athletes' performance. Exploring the fluid balance concerning body composition might help estimate individual hydration requirements. This area of research, particularly regarding sodium losses, has been relatively understudied. We evaluated the sweat rate (SR), sweat sodium losses, and their relationship with body composition in professional soccer players in Cali, Colombia. Materials and Methods: Thirty-two male players, aged 24.3 (±5.2) years, from the Colombian main soccer league, underwent high-intensity training at 32 °C (with a relative humidity of 79%). The outcome variables included SR, calculated using weight loss and fluid intake; forearm sweat sodium concentration (FSCC), measured through the direct ion-selective electrode method; and estimated the predicted whole sweat sodium loss (PWSSL) in mmol. Predictor variables (body mass, fat, and muscle masses) were estimated using the Deborah Kerr anthropometry method. The association between predictors and outcomes was assessed using linear regression. Results: The mean FSCC, PWSSL, and SR were 26.7 ± 11.3 mmol/L, 43 ± 15.9 mmol/L, and 1.7 ± 0.5 L/h, respectively. Body mass positively predicted FSCC in unadjusted and age/fat-mass-adjusted models [Beta 1.28, 95% confidence interval (CI) 0.39-2.18, p = 0.006], and continued related to FSCC after adjustment for muscle mass with marginal significance [Beta 0.85, 95% CI -0.02 to 1.73, p = 0.056]. Muscle mass was associated with the PWSSL in unadjusted and age/fat-mass-adjusted models [Beta 2.42, 95% CI 0.58-4.26, p = 0.012] and sustained an association with marginal statistical significance after adjustment for body mass [Beta 1.86, 95% CI -0.35 to 4.09, p = 0.097]. Conclusions: Under hot tropical weather conditions, FSCC was relatively low among the players. Body mass was better associated with the FSSC, and muscle mass better related to the PWSSL. Body and muscle masses could be regarded as potential factors to be explored in the estimation of individual sodium needs. However, further studies are required to validate and contrast our findings.

Biogeography of microbial communities in high-latitude ecosystems: Contrasting drivers for methanogens, methanotrophs and global prokaryotes.

Methane-cycling is becoming more important in high-latitude ecosystems as global warming makes permafrost organic carbon increasingly available. We explored 387 samples from three high-latitudes regions (Siberia, Alaska and Patagonia) focusing on mineral/organic soils (wetlands, peatlands, forest), lake/pond sediment and water. Physicochemical, climatic and geographic variables were integrated with 16S rDNA amplicon sequences to determine the structure of the overall microbial communities and of specific methanogenic and methanotrophic guilds. Physicochemistry (especially pH) explained the largest proportion of variation in guild composition, confirming species sorting (i.e., environmental filtering) as a key mechanism in microbial assembly. Geographic distance impacted more strongly beta diversity for (i) methanogens and methanotrophs than the overall prokaryotes and, (ii) the sediment habitat, suggesting that dispersal limitation contributed to shape the communities of methane-cycling microorganisms. Bioindicator taxa characterising different ecological niches (i.e., specific combinations of geographic, climatic and physicochemical variables) were identified, highlighting the importance of Methanoregula as generalist methanogens. Methylocystis and Methylocapsa were key methanotrophs in low pH niches while Methylobacter and Methylomonadaceae in neutral environments. This work gives insight into the present and projected distribution of methane-cycling microbes at high latitudes under climate change predictions, which is crucial for constraining their impact on greenhouse gas budgets.

Continuous Measurement of Diffusive and Ebullitive Fluxes of Methane in Aquatic Ecosystems by an Open Dynamic Chamber Method.

An open dynamic chamber for the continuous monitoring of diffusive and ebullitive fluxes of methane (CH4) in aquatic ecosystems was designed and developed. This method is based on a standard floating chamber in which a well-defined carrier gas flows. The concentration of CH4 is measured continuously at the outlet of the chamber, and the flux is determined from a mass balance equation. The method was carefully tested in a laboratory and was subsequently applied to two lakes, in Mexico, with contrasting trophic states. We show here that the method allows for the continuous quantification of CH4 diffusive flux higher than 25 × 10-6 g m-2 h-1, the determination of ebullitive flux, and the individual characterization of bubbles larger than 1.50-1.72 mm in diameter. The method was also applied to determine carbon dioxide emissions (CO2). In that case, the method was less sensitive but allowed for the characterization of diffusive fluxes higher than 10 mg CO2 m-2 h-1 and of bubbles larger than 5.3-8.4 mm in diameter. This high-throughput method can be adapted to any gas detector at low cost, making it a convenient tool to better constrain greenhouse gas emission from freshwater ecosystems.

An Associative Memory Approach to Healthcare Monitoring and Decision Making.

The rapid proliferation of connectivity, availability of ubiquitous computing, miniaturization of sensors and communication technology, have changed healthcare in all its areas, creating the well-known healthcare paradigm of e-Health. In this paper, an embedded system capable of monitoring, learning and classifying biometric signals is presented. The machine learning model is based on associative memories to predict the presence or absence of coronary artery disease in patients. Classification accuracy, sensitivity and specificity results show that the performance of our proposal exceeds the performance achieved by each of the fifty widely known algorithms against which it was compared.

In situ measurement of dissolved methane and carbon dioxide in freshwater ecosystems by off-axis integrated cavity output spectroscopy.

A novel low-cost method for the combined, real-time, and in situ determination of dissolved methane and carbon dioxide concentrations in freshwater ecosystems was designed and developed. This method is based on the continuous sampling of water from a freshwater ecosystem to a gas/liquid exchange membrane. Dissolved gas is transferred through the membrane to a continuous flow of high purity nitrogen, which is then measured by an off-axis integrated cavity output spectrometer (OA-ICOS). This method, called M-ICOS, was carefully tested in a laboratory and was subsequently applied to four lakes in Mexico and Alaska with contrasting climates, ecologies, and morphologies. The M-ICOS method allowed for the determination of dissolved methane and carbon dioxide concentrations with a frequency of 1 Hz and with a method detection limit of 2.76 × 10(-10) mol L(-1) for methane and 1.5 × 10(-7) mol L(-1) for carbon dioxide. These detection limits are below saturated concentrations with respect to the atmosphere and significantly lower than the minimum concentrations previously reported in lakes. The method is easily operable by a single person from a small boat, and the small size of the suction probe allows the determination of dissolved gases with a minimized impact on shallow freshwater ecosystems.

Linking chemical contamination to biological effects in coastal pollution monitoring.

To establish the connection between pollutant levels and their harmful effects on living resources, coastal monitoring programmes have incorporated biological tools, such as the scope for growth (SFG) in marine mussels and benthic macrofauna community indices. Although the relation between oxygen-depleting anthropogenic inputs and the alteration of benthic communities is well described, the effects of chemical pollutants are unknown because they are not expected to favour any particular taxa. In this study, the combined efforts of five research teams involved in the investigative monitoring of marine pollution allowed the generation of a multiyear data set for Ría de Vigo (NW Iberian Peninsula). Multivariate analysis of these data allowed the identification of the chemical-matrix combinations responsible for most of the variability among sites and the construction of a chemical pollution index (CPI) that significantly (P < 0.01) correlated with biological effects at both the individual and the community levels. We report a consistent reduction in the physiological fitness of local populations of mussels as chemical pollution increases. The energy balance was more sensitive to pollution than individual physiological rates, but the reduction in the SFG was primarily due to significantly decreased clearance rates. We also found a decrease in benthic macrofauna diversity as chemical pollution increases. This diversity reduction resulted not from altered evenness, as the classic paradigm might suggest, but from a loss of species richness.

A combined microbial and biogeochemical dataset from high-latitude ecosystems with respect to methane cycle.

High latitudes are experiencing intense ecosystem changes with climate warming. The underlying methane (CH4) cycling dynamics remain unresolved, despite its crucial climatic feedback. Atmospheric CH4 emissions are heterogeneous, resulting from local geochemical drivers, global climatic factors, and microbial production/consumption balance. Holistic studies are mandatory to capture CH4 cycling complexity. Here, we report a large set of integrated microbial and biogeochemical data from 387 samples, using a concerted sampling strategy and experimental protocols. The study followed international standards to ensure inter-comparisons of data amongst three high-latitude regions: Alaska, Siberia, and Patagonia. The dataset encompasses different representative environmental features (e.g. lake, wetland, tundra, forest soil) of these high-latitude sites and their respective heterogeneity (e.g. characteristic microtopographic patterns). The data included physicochemical parameters, greenhouse gas concentrations and emissions, organic matter characterization, trace elements and nutrients, isotopes, microbial quantification and composition. This dataset addresses the need for a robust physicochemical framework to conduct and contextualize future research on the interactions between climate change, biogeochemical cycles and microbial communities at high-latitudes.

Integrative assessment of ecological responses and chemical contamination of urban wastewater outfalls on soft bottom sediments of an estuarine system.

Sewage outfalls are one of the main anthropogenic impacts to coastal systems. Linking the chemical analysis in sediment, and changes in the ecological responses is one of the main tasks in ecosystem assessment for the protection of the marine environment. A three-tiered approach to evaluate the impact of the sewage of a recently built and obsolete Urban Waste Water Treatment Plants (UWWTPs) was performed. The sewage from each UWWTP differentially affected surrounding sediments. Macrobenthic community changes were influenced by the chemical composition in the sediments but also by grain size and organic matter. Abundance of the different families of the macrobenthic communities were correlated with most of the chemicals analyzed. On the contrary, toxicity bioassays were correlated with Zn and PCB concentrations but not with environmental variables. The toxicity tests linked the effect of chemical contamination on macrobenthic communities. A joint assessment of both chemical concentrations and their ecological effects is recommended.

NanoChest-Net: A Simple Convolutional Network for Radiological Studies Classification.

The new coronavirus disease (COVID-19), pneumonia, tuberculosis, and breast cancer have one thing in common: these diseases can be diagnosed using radiological studies such as X-rays images. With radiological studies and technology, computer-aided diagnosis (CAD) results in a very useful technique to analyze and detect abnormalities using the images generated by X-ray machines. Some deep-learning techniques such as a convolutional neural network (CNN) can help physicians to obtain an effective pre-diagnosis. However, popular CNNs are enormous models and need a huge amount of data to obtain good results. In this paper, we introduce NanoChest-net, which is a small but effective CNN model that can be used to classify among different diseases using images from radiological studies. NanoChest-net proves to be effective in classifying among different diseases such as tuberculosis, pneumonia, and COVID-19. In two of the five datasets used in the experiments, NanoChest-net obtained the best results, while on the remaining datasets our model proved to be as good as baseline models from the state of the art such as the ResNet50, Xception, and DenseNet121. In addition, NanoChest-net is useful to classify radiological studies on the same level as state-of-the-art algorithms with the advantage that it does not require a large number of operations.

Objective classification of psychomotor laparoscopic skills of surgeons based on three different approaches.

BACKGROUND: The determination of surgeons' psychomotor skills in minimally invasive surgery techniques is one of the major concerns of the programs of surgical training in several hospitals. Therefore, it is important to assess and classify objectively the level of experience of surgeons and residents during their training process. The aim of this study was to investigate three classification methods for establishing automatically the level of surgical competence of the surgeons based on their psychomotor laparoscopic skills. METHODS: A total of 43 participants, divided into an experienced surgeons group with ten experts (> 100 laparoscopic procedures performed) and non-experienced surgeons group with 24 residents and nine medical students (< 10 laparoscopic procedures performed), performed three tasks in the EndoViS training system. Motion data of the instruments were captured with a video-tracking system built into the EndoViS simulator and analyzed using 13 motion analysis parameters (MAPs). Radial basis function networks (RBFNets), K-star (K*), and random forest (RF) were used for classifying surgeons based on the MAPs' scores of all participants. The performance of the three classifiers was examined using hold-out and leave-one-out validation techniques. RESULTS: For all three tasks, the K-star method was superior in terms of accuracy and AUC in both validation techniques. The mean accuracy of the classifiers was 93.33% for K-star, 87.58% for RBFNets, and 84.85% for RF in hold-out validation, and 91.47% for K-star, 89.92% for RBFNets, and 83.72% for RF in leave-one-out cross-validation. CONCLUSIONS: The three proposed methods demonstrated high performance in the classification of laparoscopic surgeons, according to their level of psychomotor skills. Together with motion analysis and three laparoscopic tasks of the Fundamental Laparoscopic Surgery Program, these classifiers provide a means for objectively classifying surgical competence of the surgeons for existing laparoscopic box trainers.

Sub-oxycline methane oxidation can fully uptake CH4 produced in sediments: case study of a lake in Siberia.

It is commonly assumed that methane (CH4) released by lakes into the atmosphere is mainly produced in anoxic sediment and transported by diffusion or ebullition through the water column to the surface of the lake. In contrast to that prevailing idea, it has been gradually established that the epilimnetic CH4 does not originate exclusively from sediments but is also locally produced or laterally transported from the littoral zone. Therefore, CH4 cycling in the epilimnion and the hypolimnion might not be as closely linked as previously thought. We utilized a high-resolution method used to determine dissolved CH4 concentration to analyze a Siberian lake in which epilimnetic and hypolimnetic CH4 cycles were fully segregated by a section of the water column where CH4 was not detected. This layer, with no detected CH4, was well below the oxycline and the photic zone and thus assumed to be anaerobic. However, on the basis of a diffusion-reaction model, molecular biology, and stable isotope analyses, we determined that this layer takes up all the CH4 produced in the sediments and the deepest section of the hypolimnion. We concluded that there was no CH4 exchange between the hypolimnion (dominated by methanotrophy and methanogenesis) and the epilimnion (dominated by methane lateral transport and/or oxic production), resulting in a vertically segregated lake internal CH4 cycle.

Methane dynamics in the subsaline ponds of the Chihuahuan Desert: A first assessment.

The Cuatro Cienegas Basin (CCB) in the Chihuahuan desert is characterized by the presence of over 500 ponds located in an endorheic basin. These ponds are subsaline ecosystems characterized by a low productivity and a particularly high sulfate concentration, comparable to marine environments. This study focused on assessing the main physicochemical parameters in these ponds along with the characterization of the CH4 dynamics through the determination of fluxes, dissolved CH4 concentrations, and net methanotrophic and methanogenic activity. Despite a sulfate concentration ranging from 1.06 to 4.73 g L-1, the studied ponds showed moderate but clear CH4 production and emission, which suggests that methanogenesis is not completely outcompeted by sulfate reduction. CH4 fluxes ranged from 0.12 to 0.98 mg m-2 d-1, which falls within the higher range of marine emissions and within the lower range reported for coastal saline lagoons and saline ponds. During summer, significant CH4 production in the oxic water column was observed. In addition to CH4, CO2 fluxes were determined at levels from 0.2 to 53 g m-2 d-1, which is within the range recorded for saline lakes in other parts of the world. Our results provide additional evidence that subsaline/saline aquatic ecosystems play an important role in the emission of greenhouse gases to the atmosphere.

Toxicity and phototoxicity of water-accommodated fraction obtained from Prestige fuel oil and Marine fuel oil evaluated by marine bioassays.

Acute toxicity and phototoxicity of heavy fuel oil extracted directly from the sunken tanker Prestige in comparison to a standard Marine fuel oil were evaluated by obtaining the water-accommodated fraction (WAF) and using mussel Mytilus galloprovincialis and sea urchin Paracentrotus lividus embryogenesis bioassays, and copepod Acartia tonsa and fish Cyprinodon variegatus survival bioassays. Aromatic hydrocarbon (AH) levels in WAF were measured by gas chromatography. Prestige WAF was not phototoxic, its median effective concentrations (EC50) were 13% and 10% WAF for mussel and sea urchin respectively, and maximum lethal threshold concentrations (MLTC) were 12% and 50% for copepod and fish respectively. Marine WAF resulted phototoxic for mussel bioassay. EC50s of Marine WAF were 50% for sea urchin in both treatments and 20% for mussel under illumination. Undiluted Marine WAF only caused a 20% decrease in mussel normal larvae. Similar sensitivities were found among sea urchins, mussels and copepods, whilst fish were less sensitive. Unlike Marine WAF, Prestige WAF showed EC50 values at dilutions below 20%, and its toxicity was independent of lighting conditions. The differences in toxicity between both kinds of fuel could not be explained on the basis of total AH content.

Ecotoxicological evaluation of polycyclic aromatic hydrocarbons using marine invertebrate embryo-larval bioassays.

The toxicity of polycyclic aromatic hydrocarbons (PAHs) was determined using mussel, sea-urchin and ascidian embryo-larval bioassays. Fluorescent light exposure enhanced phenanthrene, fluoranthene, pyrene and hydroxypyrene toxicity in comparison with dark conditions, but not naphthalene and fluorene toxicity. The toxicity of PAHs was inversely related to their K(OW) values following QSAR models derived for baseline toxicity of general narcotics, whereas the obtained regression using toxicity data from photoactivated PAHs significantly departed from the general narcosis model. Also, the mixture toxicity of five PAHs to the larval growth of the sea-urchin was compared with predictions derived from the concentration addition concept, indicating less than additive effects. Finally, we compared our toxicity data with worst-case environmental concentrations in order to provide a preliminary estimate of the risk to the marine environment. Naphthalene, fluorene and pyrene are not considered to pose a risk to sea-urchin, mussel or ascidian larvae, whilst phenanthrene and fluoranthene may pose a risk for mussel and sea-urchin. Moreover, a higher risk for those species is expected when we consider the photoactivation of the PAHs.

[Human T-lymphotropic virus (HTLV I/II) seroprevalence amongst blood-donors in a hospital Bogotá, Colombia,between 1999 and 2004]. / Seroprevalencia de Anticuerpos para Virus Linfotrópicos Humanos (HTLV I/II) en donantes de sangre de una Clínica de Bogotá, Colombia. 1999-2004.

OBJECTIVE: This study was aimed at determining anti-human T-lymphotropic virus I/II (HTLV I/II) seroprevalence amongst blood-donors at the Clínica Reina Sofía in Bogotá, Colombia between 1999 and 2004. METHODS: All people donating blood at the Clínica Reina Sofía were selected for anti-HTLV I/II testing; a survey was carried out which focused on risk factors. All blood donations were screened by using enzyme immunolinked assay (ELISA); repeatedly reactive serum samples were confirmed as being HTLV I or HTLV II by using Western blot (WB). RESULTS: 8,913 blood donors, 5,883 (66 %) males and 3,030 (34 %) females having a mean age of 37 were included in the study; 26 (0,3 %) were repeatedly reactive in ELISA tests, 6 (0,07 %) of whom were confirmed by using Western blot (WB). Our findings revealed 0,07 % HTLV seroprevalence amongst blood-donors, in line with other European and South-American countries. CONCLUSION: Although our findings suggest low HTLV I/II seroprevalence, blood-donors should be routinely screened to minimise transmission due to occult HTLV I/II infection in Colombia.

Initial report on methane and carbon dioxide emission dynamics from sub-Antarctic freshwater ecosystems: A seasonal study of a lake and a reservoir.

The sub-Antarctic Magellanic ecoregion is a part of the world where ecosystems have been understudied and where the CH4 cycling and emissions in lakes has not ever been reported. To fill that knowledge gap, a lake and a reservoir located at 53°S were selected and studied during three campaigns equally distributed over one year. Among the parameters measured were CH4 and CO2 emissions, as well their dissolved concentrations in the water column, which were determined with high spatial resolution. No ebullition was observed and the CH4 flux ranged from 0.0094 to 4.47mmolm-2d-1 while the CO2 flux ranged from -22.95 to 35.68mmolm-2d-1. Dissolved CH4 concentrations varied over more than four orders of magnitude (0.025-128.75µmolL-1), and the dissolved carbon dioxide ranged from below the detection limit of our method (i.e., 0.15µmolL-1) to 379.09µmolL-1. The high spatial resolution of the methods used enabled the construction of bathymetric maps, surface contour maps of CH4 and CO2 fluxes, and transect contour maps of dissolved oxygen, temperature, and dissolved greenhouse gases. Overall, both lakes were net greenhouse gas producers and were not significantly different from temperate lakes located at a similar northern latitudes (53°N), except that ebullition was never observed in the studied sub-Antarctic lakes.

Anodic stripping voltammetry measures copper bioavailability for sea urchin larvae in the presence of fulvic acids.

Copper speciation in the presence of fulvic acids (FAs) was studied in chemically defined seawater by square wave anodic stripping voltammetry (SQWASV). A simple complexation model assuming a single type of ligand and a 1:1 reaction stoichiometry successfully explained the measured data. A conditional stability constant of 5.80 +/- 0.07 and a complexing capacity of 610 +/- 80 micromol Cu/g FAs were obtained. This conditional stability constant would correspond to 7.23 on a free copper ion basis. The complexation kinetics was easily followed by anodic stripping voltammetry (ASV) measurements, and complexation equilibria were not reached until approximately 12 h. Coupled to speciation studies, the toxicity of copper in the presence of FAs was studied with the sea urchin Paracentrotus lividus embryogenesis bioassay. A clear protective effect of FAs was observed on Cu toxicity, and this effect could be accurately explained by SQWASV Cu speciation measurements. Additional experiments in the presence of high Cu and FA concentrations were performed, and no extra toxicity of Cu-FA complexes was observed. These results are in agreement with metal bioavailability models and also underline the usefulness of ASV for determining copper bioavailability in the presence of natural organic matter.

Evaluation of artificially-weathered standard fuel oil toxicity by marine invertebrate embryogenesis bioassays.

wWeathering of petroleum spilled in the marine environment may not only change its physical and chemical properties but also its effects on the marine ecosystem. The objective of this study was to evaluate the toxicity of the water-accommodated fraction (WAF) obtained from a standard fuel oil following an environmentally realistic simulated weathering process for a period of 80 d. Experimental flasks with 40 g L(-1) of fuel oil were incubated at 18°C with a 14 h light:10 h dark photoperiod and a photosynthetically active radiation (PAR) intensity of 70 µE m(-2) s(-1). Samples were taken at four weathering periods: 24 h, 7, 21 and 80 d. WAF toxicity was tested using the sea urchin (Paracentrotus lividus) and mussel (Mytilus galloprovincialis) embryo-larval bioassays and the aromatic hydrocarbons levels (AH) in the WAF were measured by gas chromatography/mass spectrometry. In contrast with the classic assumption of toxicity decrease with oil weathering, the present study shows a progressive increase in WAF toxicity with weathering, being the EC(50) after 80d eightfold lower than the EC(50) at day 1, whereas AH concentration slightly decreased. In the long term, inoculation of WAF with bacteria from a hydrocarbon chronically-polluted harbor slightly reduced toxicity. The differences in toxicity between fresh and weathered fuels could not be explained on the basis of the total AH content and the formation of oxidized derivatives is suggested to explain this toxicity increase.

Water characterization in three industrialized harbours (Vigo, Bilbao and Pasajes) in north coast of Spain.

Total dissolved Cu, Zn, Pb and Cd concentrations, speciation, fluorescence of organic matter and toxicity for sea urchin development have been studied during three years in water samples of three of the most industrialized harbours in North Coast of Spain: Vigo, Bilbao and Pasajes. Total metal concentrations were below 0.4 nM for Cd and generally below 2 nM for Pb. Zn and Cu levels were higher (2.8-9 nM Cu and 15-234 nM Zn) and denoted an anthropogenic enrichment. Ligand concentrations were usually between 50 and 200 nM for Cu and between 6 and 80 for Pb and Zn. Organic matter and speciation analysis yielded complementary information to characterize the samples, but no correlation was present between the parameters calculated by both methods. Samples were tested for toxicity with sea urchin embryo bioassay and three samples were toxic but the toxicity could not be explained with the metal levels here measured.

An associative memory approach to medical decision support systems.

Classification is one of the key issues in medical diagnosis. In this paper, a novel approach to perform pattern classification tasks is presented. This model is called Associative Memory based Classifier (AMBC). Throughout the experimental phase, the proposed algorithm is applied to help diagnose diseases; particularly, it is applied in the diagnosis of seven different problems in the medical field. The performance of the proposed model is validated by comparing classification accuracy of AMBC against the performance achieved by other twenty well known algorithms. Experimental results have shown that AMBC achieved the best performance in three of the seven pattern classification problems in the medical field. Similarly, it should be noted that our proposal achieved the best classification accuracy averaged over all datasets.