Exploring the Benefits of Nutritional and Chemical Characteristics of Touriga Nacional and Arinto Varieties (Vitis vinifera L.).

Environmental degradation leads to an unsustainable food system. In addition to this issue, the consumption of foods that improve people's health and well-being is recommended. One of the alternatives is undoubtedly the use of by-products of winemaking, namely in the form of grape pomace flour (GPF). To verify the benefits of using the Touriga Nacional and Arinto (Vitis vinifera L.) flour varieties, analytical determinations were made to identify and quantify different components. In terms of nutritional characterization, the Touriga Nacional GPF showed results that indicate better nutritional quality than the Arinto GPF. The Touriga Nacional and Arinto samples had protein contents of 10.13% and 8.38%, polyunsaturated fatty acids of 6.66% and 5.18%, soluble dietary fiber of 14.3% and 1.7%, and insoluble dietary fiber of 55.1% and 46.4%, respectively. The anthocyanins, proanthocyanidins, and flavonols presented in samples were detected by HPLC-DAD/ESI-MS. Atomic absorption spectrometry revealed elevated concentrations of certain elements in Touriga Nacional compared to Arinto, with the former showing higher levels of aluminum (130 mg/kg) and iron (146 mg/kg) against the latter's Al (120 mg/kg) and Fe (112 mg/kg) content. GPF could become a valuable ingredient due to its nutritional quality and high content of various polyphenols.

The Glycan Ectodomain of SARS-CoV-2 Spike Protein Modulates Cytokine Production and Expression of CD206 Mannose Receptor in PBMC Cultures of Pre-COVID-19 Healthy Subjects.

The ability of recombinant, SARS-CoV-2 Spike (S) protein to modulate the production of two COVID-19 relevant, pro-inflammatory cytokines (IL-6 and IFN-γ) in PBMC cultures of healthy, pre-COVID-19 subjects was investigated. We observed that cytokine production was largely and diversely modulated by the S protein depending on antigen or mitogen stimulation, as well as on the protein source, insect (S-in) or human (S-hu) cells. While both proteins co-stimulated cytokine production by polyclonally CD3-activated T cells, PBMC activation by the mitogenic lectin Concanavalin A (Con A) was up-modulated by S-hu protein and down-modulated by S-in protein. These modulatory effects were likely mediated by the S glycans, as demonstrated by direct Con A-S binding experiments and use of yeast mannan as Con A binder. While being ineffective in modulating memory antigenic T cell responses, the S proteins and mannan were able to induce IL-6 production in unstimulated PBMC cultures and upregulate the expression of the mannose receptor (CD206), a marker of anti-inflammatory M2 macrophage. Our data point to a relevant role of N-glycans, particularly N-mannosidic chains, decorating the S protein in the immunomodulatory effects here reported. These novel biological activities of the S glycan ectodomain may add to the comprehension of COVID-19 pathology and immunity to SARS-CoV-2.

Mycobacterium tuberculosis Antigen 85B modifies BCG-induced anti-tuberculosis immunity and favors pathogen survival.

Tuberculosis is one of the deadliest infectious diseases worldwide. Mycobacterium tuberculosis (Mtb) has developed strategies not only to evade from host immunity but also to manipulate it for its survival. We investigated whether Mtb exploited the immunogenicity of Ag85B, one of its major secretory proteins, to redirect host anti-TB immunity to its advantage. We found that administration of Ag85B protein to mice vaccinated with Bacillus Calmette-Guérin (BCG) impaired the protection elicited by vaccination causing a more severe infection when mice were challenged with Mtb. Ag85B administration reduced BCG-induced CD4 T cell activation and IFN-γ, CCL-4 and IL-22 production in response to Mtb-infected cells. On the other hand, it promoted robust Ag85B-responsive IFN-γ-producing CD4 T cells, expansion of a subset of IFN-γ/IL-10-producing CD4+FOXP3+Treg cells, differential activation of IL-17/IL-22 responses and activation of regulatory and exhaustion pathways, including programmed death-ligand 1 expression on macrophages. All this resulted in impaired intracellular Mtb growth control by systemic immunity, both at pre- and post-Mtb challenge. Interestingly, Mtb infection itself generated Ag85B-reactive inflammatory immune cells incapable of clearing Mtb in both unvaccinated and BCG-vaccinated mice. Our data suggest that Mtb can exploit the strong immunogenicity of Ag85B to promote its own survival and spread. Since Ag85B is normally secreted by replicating bacteria and it is commonly found in the lungs of the Mtb-infected host, our findings may advance the understanding on the mechanisms of Mtb pathogenesis and immune evasion.

Assessment and Comparison of Microplastic Contamination in Atlantic Navigation Routes with Known Uncertainty.

Microplastics (MP) have been found in various environments worldwide. However, not many studies focus on the open ocean due to logistical restraints. Between January and May 2020, the NRP Sagres sampled 123 linear paths of subsurface water of the Atlantic Ocean, passing by Cape Verde, the east coast of South America, and the west coast of Africa. The water was sampled through the ship's water system. The membranes were analyzed by the Hydrographic Institute of Portugal and the Norwegian Institute for Water Research by micro-FTIR. The contamination levels were reported with uncertainty, for 99% confidence level (CL), normalized for filtered water volume and the distance traveled during sampling. Uncertainties were calculated through a detailed ″bottom-up″ evaluation. MP were found in about a third of the stations (48 out of 123), and most of those stations (43 out of 48) presented concentrations below 1 m-3 km-1. The sites where higher concentrations were registered were the port of the island of Santiago (Cape Verde) ((5.9 ± 5.2) m-3 km-1), the Guanabara Bay in Rio de Janeiro (Brazil) ((41 ± 27) m-3 km-1), and close to South Africa ((4.9 ± 2.4) m-3 km-1). Most MP found were polyamide, polyester, polyethylene, ethylene vinyl acetate, and poly(methyl methacrylate). The estimated contamination levels cannot be directly compared with information obtained in other studies due to differences in how MP were determined and the unknown uncertainty of their measured values. This article presents a relevant and reliable contribution to understanding the MP distribution in the Atlantic Ocean.

Statistically sound comparison of standardized and simulation methods for oil spill source identification in real spill scenarios.

The comparison of oil patterns of a spill (Sp) and suspected spill source (SS) samples is based on ratios between correlated GC-MS signals of oil-discriminating compounds, i.e., diagnostic ratios (DR). The Student's t statistics (S-t) and a maximum relative difference (SC), proposed in standard methods, have been used for DR comparison due to their simplicity. An alternative methodology based on Monte Carlo Method (MCM) simulations of correlated signals, capable of accurately defining DR comparison criteria, proved that S-t and SC assumptions regarding DR normality and precision are frequently not valid, affecting comparison reliability. The performance of the approaches was accurately compared from independent signals of the same oil sample from a perfect match between Sp and SS. The present study describes the comparison of the approaches in real oil spill scenarios reproduced in International Round Robin Tests. Since as the number of compared DR increases, also rises the probability of not all equivalent DR being actually considered equivalent, the decision of oil pattern equivalence was based on two comparisons of independent sets of Sp and SS signals. The risk of true oil standard equivalency claims is compared for the three oil spill scenarios studied, which are different considering oil types, DR sets and spill weathering. The ability of the approaches to distinguish the Sp sample from an oil sample known not to be the source of the spill was also assessed. The MCM based on two independent DR comparison trials was the only one consistently producing fingerprint comparison risks of correct equivalence claims larger than 98 %. MCM also performed better in distinguishing different oil patterns. It was concluded that comparing >22 DR does not change the risk of correct oil pattern equivalence assessment significantly. The complexity of the MCM approach is overcome by using user-friendly and validated software.

[Autoimmune/inflammatory syndrome induced by adjuvants. Case report]. / Síndrome autoinmunitario/inflamatorio inducido por adyuvantes. Reporte de caso.

Background: The indiscriminate application of substances for aesthetic purposes, such as silicone in breast implants, leads to the production of common local signs such as inflammation, skin irregularities, edema, erythema, vascular neoformations, and ulcers, which can evolve into general symptoms such as fever, asthenia, weakness, arthralgia or activate the immune system abnormally, causing the appearance of autoimmune diseases. This set of signs and symptoms is called adjuvant-induced autoimmune/inflammatory syndrome. Clinical case: We present the case of a 50-year-old woman with a history of silicone-based breast implants who spontaneously developed a hemorrhagic coagulopathy, type A acquired hemophilia was documented, that is, autoantibodies against coagulation factor VIII. Thanks to the work of a multidisciplinary team, it is possible to successfully diagnose and treat the patient with bridging agents, implant removal and management of associated symptoms. Conclusion: the importance of knowing the pathology is recognized, which, although it is rare, when it occurs has a high mortality rate if it is not diagnosed and treated on time.

Introducción: la aplicación de sustancias con fines estéticos de forma indiscriminada, como es el caso de la silicona en los implantes mamarios, llevan a la producción de signos locales comunes como: inflamación, irregularidad en la piel, edema, eritema, neoformaciones vasculares y úlceras, que pueden evolucionar a síntomas generales como la fiebre, astenia, adinamia, artralgias o a activar, de manera anómala, el sistema inmunitario, causando la aparición de enfermedades autoinmunitarias. A este conjunto de signos y síntomas se le denomina síndrome autoinmunitario/inflamatorio inducido por adyuvantes. Caso clínico: presentamos el caso de una mujer de 50 años con antecedente de implantes mamarios a base de silicona que desarrolla, de manera espontánea, una coagulopatía hemorrágica, se documenta hemofilia tipo A adquirida, es decir, autoanticuerpos contra el factor VIII de la coagulación. Gracias al trabajo de un equipo multidisciplinario se consigue diagnosticar y tratar de manera exitosa a la paciente con agentes de puente, remoción de los implantes y manejo de los síntomas asociados. Conclusión: se reconoce la importancia de conocer la patología que, si bien es rara, cuando se presenta tiene alta tasa de mortalidad si no se diagnostica y trata a tiempo.

Determination of microplastic contamination levels and trends in vast oceanic sediment areas with uncertainty.

Small plastic particles, designated as microplastics, are known vehicles of several contaminants desorbed from their surface after being ingested by marine organisms. The monitoring of the levels and trends of microplastics in oceanic areas is essential to identify relevant threats and respective sources whose management should be improved to protect the environmental resources. However, the assessment of contamination trends in large oceanic areas is affected by contamination heterogeneity, sampling representativeness, and the uncertainty of collected sample analyses. Only contamination variations not justifiable by system heterogeneity and their characterisation uncertainty are meaningful and should be taken seriously by the authorities. This work describes a novel methodology for the objective identification of meaningful variation of microplastic contamination in vast oceanic areas by the Monte Carlo simulation of all uncertainty components. This tool was successfully applied to the monitoring of the levels and trends of microplastic contamination in sediments from a 700 km2 oceanic area from 3 km to 20 km offshore Sesimbra and Sines (Portugal). This work allowed concluding that contamination has not varied between 2018 and 2019 (difference of mean total microplastic contamination between -40 kg-1 and 34 kg-1) but that microparticles made of PET are the major type of studied microplastics (in 2019, mean contamination is between 36 kg-1 and 85 kg-1). All assessments were performed for a 99 % confidence level.

Metrologically sound comparison of trace-metal levels in sea cucumber tissues from different species and habitats.

Sea cucumbers are indicators of metal contamination in sea bottoms due to their low mobility and feeding behaviour. Comparing contaminations of specimens from different locations, habitats, and/or organs allows understanding of contamination processes and differences. However, the interpretation of these data is affected by the variability of contamination levels in specimens, the uncertainty of tissue analyses, and the complex correlation of mass fractions estimated by using the same calibration of the used instrumental method of analysis. This work presents a novel tool for the sound comparison of contamination levels of biota where all mentioned factors are considered to produce reliable and undisputable information on the studied system. The Monte Carlo simulation of uncertainty components, affecting the determination of mean contamination levels observed in selected types of tissues, allowed simulating mean contamination differences and determining if these are meaningful. This tool was used to assess the levels of Cd, Cu, Ni and Pb of animals collected in different locations of Sesimbra-Portugal. It was concluded that specimens that selectively consume macroalgae have larger contamination levels than animals feeding on sediment. The gut is the most contaminated organ suggesting intake from feeding is dominant. Three of the analysed animals have Pb mass fractions larger than a maximum admissible value for human consumption of 3 mg kg-1 with a probability larger than 2.5%.

Long-term variation of dissolved metals and metalloid in the waters of an Atlantic mesotidal estuary (Sado Estuary, Portugal).

Estuaries have long been preferred sites of human settlement due to the benefits regarding proximity to fresh water and the ocean. As such, these environments have been subject to increasing anthropogenic pressures, resulting in issues of pollution and contamination. However, since the second half of the 20th century an environmental concern has reflected in the development of legislation, monitoring programmes and measures to diminish and control those impacts. The study presented herein integrates metals and metalloid concentrations from surface water samples obtained in a long-term monitoring programme (1986-2020) conducted in the Sado Estuary. The results obtained show a decrease and stabilisation of the concentrations of elements (between 81 % for Pb and 11 % for As in the average concentrations, between 83 % for Pb and 11 % for Cd in the median concentrations, and an increase of 1 % in the As median values). Nevertheless, high concentrations were still observed in the stations closest to the industrial area and the main freshwater to confluence with the estuary. Despite the efforts in improving the environmental quality of the Sado Estuary, possible effects in native species such as cuttlefishes and oysters are still a possibility, particularly in the stations where higher concentrations were registered, as well as close to nurseries as a result of trace metal transport through currents and tides.

Evaluation of temporal trends and correlations of physical-chemical parameters in vast oceanic areas robust to information uncertainty.

The physical-chemical monitoring of vast oceanic areas aims at assessing the status and evolution of the environmental resource for its exploration, protection and/or better understanding. However, the interpretation of monitoring data is affected by ocean seasonality and heterogeneity, and by the quality of sampling and characterization tools used to study the environment. All these factors contribute to the uncertainty of collected information that should be expressed in determined parameter values or trends. A trend of a studied parameter quantified by values difference is significant if the observed absolute value of the difference is larger than their expanded uncertainty. The correlation of studied parameters, useful for their interpretation, is equality affected by the mentioned sources of uncertainty. This work describes the metrologically sound evaluation of trends and correlations of physicochemical parameters of vast oceanic areas where all uncertainty sources affecting the information are considered by simulating their complex impact by the Monte Carlo Method. The described methodology was successfully used to study the impact of summer upwelling in an 800 km2 coastal area offshore two large cities in Portugal. Nutrients, conductivity, salinity and temperature trends and correlations are distinguished from system heterogeneity, sampling and sample analysis uncertainty for a 99% confidence level.

Increased oyster aquaculture in the Sado Estuary (Portugal): How to ensure ecosystem sustainability?

Aquaculture is one of the fastest growing sectors in the world. However, this may come with a cost, as increasing aquatic production is likely to impose changes in the environment. To ensure ecosystem sustainability, it is essential to think on this larger scale. This study aims to use the Delft3D model suite to evaluate the ecological carrying capacity for bivalve production in the Sado Estuary (Portugal), under present and future conditions (2050). Scenarios for increased oyster production resulted in reductions of chlorophyll a associated with increased nutrient concentrations. In the most extreme production scenario, which considered an increase of 100 ha in production area, a predicted decrease of 90 % in phytoplankton biomass was observed. Climate change (CC) was incorporated as an increase in sea level and water temperature, as well as a reduction in river flow. Under present oyster production conditions, CC revealed contrasting patterns, i.e. an increase in chlorophyll a concentrations and a reduction in nutrients. These results suggest that CC has a positive effect in counteracting the impacts of increased oyster production, however further research is necessary. All scenarios point to reduced dissolved oxygen concentrations, highlighting the need to monitor this parameter. Given the difficulty in defining what are unacceptable impacts to the ecosystem it would be prudent to include a socio-ecological framework in the future, in order to integrate ecosystem services and the perception of local stakeholders.

Optimisation of the uncertainty of oil spill identification from replicate comparative analyses: Comparison of standardised and novel identification methods.

Oil spill identifications involve the comparison of oil fingerprints between the oil spill and suspected oil sources, defined by ratios between the abundances of oil-discriminating compounds, Diagnostic Ratios (DR). The normalised Nordtest and EN 15522-2 methodologies use Student's t statistic (S-t) or a maximum relative difference (SC) to compare mean DR from replicate sample analysis. While the S-t method assumes the normality of DR distribution, the SC method is based on controlled DR dispersion. However, when false, the assumptions and approximations adopted can lead to low true identification rates. This work presents a novel computational tool for the statistically sound oil spill identification that allows following requirements defined by EN 15522-2, the comparison of replicate DR determinations, and the use of different DR sets and formats. The tool uses the Monte Carlo Method (MCM) to describe the probability distribution of the difference of mean DR, allowing estimating the probability of the true acceptance of fingerprints equivalence. The studied methods were applied to the comparison of signals from the same oil and to a real scenario reproduced in an International Round Robin Test. The methods were compared considering the probabilities of true acceptance of oil patterns equivalence based on a single, γ, or various, δ, DR. The MCM method performs identifications with γ equivalent to the defined confidence level for the comparison, P. Since the various DR studied are not perfectly correlated, the δ is below P. The number of replicate analyses performed and the DR considered in the comparison affect identification performance. The S-t produces comparison criteria with a γ lower than P. The SC criteria for duplicate analysis is associated with a δ lower than the obtained by the MCM. A user-friendly MS-Excel spreadsheet is available to perform oil pattern comparisons using various methods and conditions.

Bottom-Up Evaluation of the Uncertainty of the Quantification of Microplastics Contamination in Sediment Samples.

The quantification and comparison of microplastic contamination of sediments are affected by sample heterogeneity and the systematic and random effects affecting sample analysis. The quantification and combination of these components in the measurement uncertainty allows the objective interpretation of analysis results. This work presents the first detailed evaluation of the uncertainty of microplastic contamination quantification in sediments. The random and systematic effects affecting microplastic counts are modeled by the Poisson-lognormal distribution with inputs estimated from duplicate sediment analysis and the analysis of sediments spiked with microparticles. The uncertainty from particle counting was combined with the uncertainty from the determination of the dry mass of the analytical portion by the Monte Carlo method. The developed methodology was implemented in a user-friendly spreadsheet made available as the Supporting Information. The contamination of sediment samples collected in various inland Portuguese waters was determined, ranging from [0; 160] to [361; 2932] kg-1 for a 99% confidence level, and compared by assessing if the difference between contamination levels is equivalent to zero for the same confidence level. Several samples proved to have metrologically different microplastic contamination. This work represents a contribution to the objectivity of the assessment of environmental contamination with microplastics.

Microplastics contamination in sediments from Portuguese inland waters: Physical-chemical characterisation and distribution.

Plastics are the major constituent of waste accumulated in inland waters and subsequently transferred to the ocean. The smaller plastic particles, typically obtained from the fragmentation of larger pieces, are vehicles for food chain accumulation of plastic components and contaminants sorbed to these particles through their ingestion by small organisms. The monitoring of the level and trends of the contamination by microplastics is essential to determine the relevance and potential sources of this contamination necessary to define strategies to reduce this threat. This work presents microplastic contamination levels and trends of sediments of four Portuguese inland waters, namely Ria de Aveiro, Ria Formosa, Mira river, and Mondego river, between 02/2019 and 09/2020. The contamination is classified considering the type of polymer and size, shape, and colour of particles. Polymers are identified by micro-ATR-FTIR with true and false identification rates larger and lower than 95% and 5%, respectively. Duplicate analysis results are used to quantify contamination heterogeneity subsequently applied to assess if a specific contamination trend is not meaningful for a 99% confidence level. The analytical procedure is described in detail to clarify the scope of the analysis. Tests' quality is controlled by following strict quality control measures. Results from sixty-three sediment samples proved the ubiquitous presence of microplastic (MP) in these inland waters with contamination levels ranging between 20 MP kg-1 and 1090 MP kg-1, excluding six samples not contaminated with these particles. Overall, more than 86% of the microplastics were fragments lower than 1000 µm, and 33% were identified as polyethylene or polypropylene. A large diversity of microplastic colours was observed. For the Mondego River and Ria de Aveiro locations monitored for consecutive years, no significant variations of microplastic contamination were observed for a 99% confidence level.

Development and validation of statistically sound criteria for the match of unweathered GC-MS fingerprints in oil spill forensics.

The investigation of an oil spill's origin frequently relies on determining the equivalence of oil component patterns in samples from the contaminated environment and suspected oil source. This comparison benefits if based on the ratio of the abundance of unweathered characteristic components of the oil product, Diagnostic Ratios, DR. Replicate determinations of DR from one sample are used to set limits for the second sample's DR. The composition equivalence of oil patterns in both samples is indicated if all compared DR are statistically equivalent with a high confidence level. Some studies define DR limits assuming their normality and using Student's t statistics (S-t). However, since the ratio of correlated abundances can be not normally distributed, this criterion can drive to more false comparisons than predicted by the test confidence level. This work developed a computational tool for the reliable description of the non-normal distribution of the DR based on the Monte Carlo Method (MCM), aiming to allow the accurate control of the confidence of DR comparison. This work concluded that S-t defines 95% or 98% confidence limits with probabilities of falsely rejecting samples equivalence, φ, that can be up to 4.3% higher than predicted by the confidence level of the S-t test (i.e., 5% and 2%). The fragilities of the S-t limits significantly reduce the probability (1-θ) of two samples with the same oil producing equivalent values of all compared DR. For the studied 69 DR from unweathered components, the (1-θ) for 98% confidence level limits, set by the MCM and S-t from triplicate injections of one sample, are 94.8% and 91.7%, respectively. These values are below the confidence level (P) defined for each DR because DR are correlated with a correlation coefficient lower than 1. The (1-θ) can be increased to above P by using MCM limits and accepting composition equivalence if at least one of two sample extract injections produces values within limits set from the other sample's replicate injection. The validated user-friendly MS-Excel file used to set and access comparison criteria is made available as Supplementary Material and was checked experimentally. However, it is not feasible to estimate model confidence exclusively from experimentation because it would require too much independent analysis.

Tidal variability of water quality parameters in a mesotidal estuary (Sado Estuary, Portugal).

To establish effective water quality monitoring strategies in estuaries, it is imperative to identify and understand the main drivers for the variation of water quality parameters. The tidal effect is an important factor of the daily and fortnightly variability in several estuaries. However, the extent of that influence on the different physicochemical and biological parameters is still overlooked in some estuarine systems, such as the Sado Estuary, a mesotidal estuary located on the west coast of Portugal. The main objective of this study was to determine how the water quality parameters of the Sado Estuary varied with the fortnightly and the semidiurnal tidal variation. To achieve this goal, sampling campaigns were conducted in May/18, Nov/18 and Jun/19, under neap and spring tidal conditions, with data collection over the tidal cycle. Results were observed to be significantly influenced by the tidal variation, in a large area of the estuary. Flood seemed to mitigate possible effects of nutrient enrichment in the water column. Additionally, significant differences were also observed when considering the different sampling stations. Temperature, Suspended Particulate Matter (SPM) and nutrients showed the highest values at low water. Lastly, the implications of the tidal variability in the evaluation of the water quality according to Water Framework Directive were also discussed, highlighting the importance of studying short-time scale variations and the worst-case scenario to ensure water quality is maintained. These findings are relevant for the implementation of regional management plans and to promote sustainable development.

Validated spreadsheet for the identification of PE, PET, PP and PS microplastics by micro-ATR-FTIR spectra with known uncertainty.

The monitoring of microplastics in the environment is crucial to determine the relevance and trends of this contamination necessary to plan environmental protection policies. Monitoring data reliability is essential for this purpose. This work describes a methodology for the reliable identification of the most abundant polymer types in aquatic sediments (polyethylene, PE, polypropylene, PP, polyethylene terephthalate, PET, and polystyrene, PS) by micro-ATR-FTIR. Identifications with true and false result rates greater than 95% and lower than 5% are performed, respectively. The analysis is based on defining spectra requirements regarding characteristic and interfering bands intensity and selecting optimal assessed wavenumber range, signal processing, and algorithm to quantify the match/agreement between particle and reference spectra. It is also defined the minimum match value, P5¼P, for reliable identifications. Examinations are performed in two stages where in the first stage PE and PP, PE&PP, are distinguished from other microplastics by taking the [4000-500] cm-1 spectra and various Match Methods and P5¼P depending on the polymer type. PE and PP are distinguished by quantifying weighted or unweighted Pearson correlation coefficients against a reference spectrum in the [3000-2800] cm-1 range. The defined P5¼P are above the 0.6 value considered in many references that do not quantify identification uncertainty. The MS-Excel files used in method development and validation are made available as Supplementary Material being applicable to other spectral techniques and analytical fields.

Monte Carlo bottom-up evaluation of the uncertainty of complex sample preparation: Elemental determination in sediments.

Many chemical analyses involve a complex sample preparation, and some, based on an instrumental method of analysis such as spectrometric or chromatographic methods, are affected by matrix effects. The objective interpretation of the results of these analyses performed in the framework of a research or a conformity assessment requires quantifying the measurement uncertainty. This work presents a novel methodology for the bottom-up modelling of the performance of complex analytical operations, such as sample digestion or extraction, by the Monte Carlo simulation of their performance independently of the performance of the other analytical steps. The simulation of between-days precision of complex sample preparation and mean measurement error observed from the analysis of various reference materials and their combination with models of instrumental quantification performance allow the detailed modelling of the measurement uncertainty. The developed methodology adapts to the complex distribution of observed measurement performance data avoiding the under evaluation of the measurement uncertainty by assuming the normal distribution of systematic and random effects. The developed methodology was successfully applied to the determination of total or acid-extractable As (following OSPAR or EPA 3051A methods, respectively) in sediments where measurement trueness was assessed from the analysis of one Certified Reference Material and two spiked samples. The evaluated uncertainty is fit for environmental monitoring considering performance criteria defined for Quasimeme proficiency tests. The developed measurement models were successfully cross-validated by randomly extracting data from the validation set subsequently used to check the compatibility between estimated and reference values for 95% or 99% confidence level. The observed success rate of these assessments is compatible with the confidence level of the tests.

Caloric Restriction Promotes Immunometabolic Reprogramming Leading to Protection from Tuberculosis.

There is a strong relationship between metabolic state and susceptibility to Mycobacterium tuberculosis (MTB) infection, with energy metabolism setting the basis for an exaggerated immuno-inflammatory response, which concurs with MTB pathogenesis. Herein, we show that controlled caloric restriction (CR), not leading to malnutrition, protects susceptible DBA/2 mice against pulmonary MTB infection by reducing bacterial load, lung immunopathology, and generation of foam cells, an MTB reservoir in lung granulomas. Mechanistically, CR induced a metabolic shift toward glycolysis, and decreased both fatty acid oxidation and mTOR activity associated with induction of autophagy in immune cells. An integrated multi-omics approach revealed a specific CR-induced metabolomic, transcriptomic, and proteomic signature leading to reduced lung damage and protective remodeling of lung interstitial tightness able to limit MTB spreading. Our data propose CR as a feasible immunometabolic manipulation to control MTB infection, and this approach offers an unexpected strategy to boost immunity against MTB.

Evaluation of seawater composition in a vast area from the Monte Carlo simulation of georeferenced information in a Bayesian framework.

The detection of composition or pollution trends of vast environmental water areas, from a river, lake or sea, requires the determination of the mean concentration of the studied component in the studied area at defined depth in, at least, two occasions. Mean concentration estimates of a large area are robust to system heterogeneity and, if expressed with uncertainty, allow assessing if observed trends are meaningful or can be attributed to the measurement process. Mean concentration values and respective uncertainty are more accurately determined if various samples are collected from the studied area and if samples coordinates are considered. The spatial representation of concentration variation and the subsequent randomization of this model, given coordinates and samples analysis uncertainty, allows an improved characterization of studied area and the optimization of the sampling process. Recently, this evaluation methodology was described and implemented in a user-friendly MS-Excel file. This tool was upgraded to allow determinations close to zero concentration and "bottom-up" uncertainty evaluations of collected samples analysis. Since concentrations cannot be negative, this prior knowledge is merged with the original measurements in a Bayesian uncertainty evaluation that improves studied area description and sampling modelling. The Bayesian assessment avoids the underestimation of concentrations distribution by assuming that negative concentrations are impossible. This tool was successfully applied to the determination of reactive phosphate concentration in a vast ocean area of the Portuguese coast. The new version of the developed tool is made available as Supplementary Material.