Modulation of the electrostatic potential around α-lactalbumin using oligoelectrolyte chains, pH and salt concentration.

In this study, we conducted a comprehensive computational investigation of the interaction between α-lactalbumin, a small globular protein, and strong anionic oligoelectrolyte chains with a polymerization degree from 2 to 9. Both the protein and oligoelectrolyte chains are represented using coarse-grained models, and their properties were calculated by the Monte Carlo method under constant pH conditions. We were able to estimate the effects of this interaction on the electrostatic potential around the protein. At acidic pH, the protein had a net positive charge; therefore, the electrostatic potential around it was also positive. To neutralize or reverse this electrostatic potential, oligoelectrolyte chains with a minimum size of six monomers were necessary. Simultaneously, low salt concentrations were required as elevated salt levels led to a significant attenuation of the electrostatic interactions and the corresponding electrostatic potential.

Environmental pollution by heavy metals within the area influenced by the Tungurahua volcano eruption - Ecuador.

Volcanic eruptions can have long-lasting negative effects on nearby environments and communities, especially those relying on agriculture. The Tungurahua and Sangay volcanoes in Ecuador's highlands pose a significant risk to the region's agricultural economy and inhabitants. The most recent eruption of the Tungurahua volcano spanned from September 1999 to March 2016. Volcanic ash is known to contain both non-essential and essential elements for plant growth, but excessive amounts of the latter can also be toxic and disrupt physiological processes. Additionally, the use of pesticides and fertilizers introduces additional elements to agricultural soils, which can potentially transfer to edible plants and raise health concerns for consumers. Despite this, little is known about the impact of the Tungurahua volcano's latest eruption on soil deposition of micronutrient and heavy metals and their potential transfer to the food chain. To address this knowledge gap, we conducted a study to explore the impact of the Tungurahua volcano's latest eruption on soil deposition of Cd, Cr, Ni, Pb, As, Fe, Cu, Mn, and Zn, as well as the physicochemical characteristics of cultivated and uncultivated soil samples and vegetables in the cantons most affected by volcanic ash. According to our findings, the physicochemical properties, micronutrient, and heavy metal concentrations of both cultivated and uncultivated soils differ and, in some cases, exceeded the maximum limits established, which could affect the health of the soil as well as of human beings through the trophic chain. This study provides valuable information for monitoring the chemical and physical properties of soil and vegetables in areas affected by the Tungurahua volcanic activity and agriculture, aiding in understanding their impact on the environment, agriculture, and potential health risks associated with locally grown crops in rural Ecuadorian communities.

Systematic review and meta-analysis of arsenic concentration in drinking water sources of Iran.

Recent studies have found arsenic contamination of drinking water in some parts of Iran, as in many other countries. Thus, a comprehensive systematic review is necessary to assess the distribution and concentration of arsenic in drinking water sources. For this purpose, articles published from the first identification until December 2023, were retrieved from various national and international databases. Of all the studies examined (11,726), 137 articles were selected for review based on their conceptual relationship to this survey. A review of the extracted studies presented that ICP methods (ICP-MS, ICP-OES, 56%) and atomic absorption spectrophotometry (AAS, 34.1%) were the two most commonly used techniques for the analysis of arsenic in water samples. The order of arsenic content in the defined study areas is descending, as follows: northwest ˃ southeast ˃ southwest ˃ northeast. A review of studies performed in Iran depicted that provinces such as Kurdistan, Azerbaijan, and Kerman have the highest arsenic concentrations in water resources. Accordingly, the maximum concentration of arsenic was reported in Rayen, Kerman, and ranged from < 0.5-25,000 µg/L. The primary cause of elevated arsenic levels in water resources appears to be geologic structure, including volcanic activity, biogeochemical processes, sulfur-bearing volcanic rocks, Jurassic shale, the spatial coincidence of arsenic anomalies in tube wells and springs, and, to some extent, mining activities. The findings of the presented survey indicate that it is essential to take serious measures at the national level to minimize the health risks of arsenic contamination from drinking water consumption.

Linking QKD Testbeds across Europe.

Quantum-key-distribution (QKD) networks are gaining importance and it has become necessary to analyze the most appropriate methods for their long-distance interconnection. In this paper, four different methods of interconnecting remote QKD networks are proposed. The methods are used to link three different QKD testbeds in Europe, located in Berlin, Madrid, and Poznan. Although long-distance QKD links are only emulated, the methods used can serve as a blueprint for the secure interconnection of distant QKD networks in the future. Specifically, the presented approaches combine, in a transparent way, different fiber and satellite physical media, as well as common standards of key delivery interfaces. The testbed interconnections are designed to increase the security by utilizing multipath techniques and multiple hybridizations of QKD and post-quantum cryptography (PQC) algorithms.

Cluster approximation applied to multisite-occupancy adsorption: configurational entropy of the adsorbed phase for dimers and trimers on triangular lattices.

The adsorption of dimers and trimers on triangular lattices is studied by combining theoretical modeling and Monte Carlo (MC) simulations. The thermodynamic process is analyzed through the behavior of the configurational entropy per site of the adsorbed phase as a function of the coverage. MC calculations, supplemented by the thermodynamic integration method, are performed in the grand canonical ensemble. The theoretical model used in the present study is called Cluster Approximation (CA), and it is based on exact calculation of states on finite cells. An efficient algorithm allows us to determine the detailed structure of the configuration space for m = l1 × l2 cells. From there, the thermodynamic properties can be obtained. Five systems are investigated, according to the size and shape of the molecule in the adsorbed state: (i) dimers, (ii) linear trimers, (iii) triangular trimers, (iv) 60°-angular trimers and (v) 120°-angular trimers on triangular lattices. Dimer and trimer are the simplest cases of a polyatomic adsorbate, containing all the properties of the multisite-occupancy adsorption and can be used to model several experimental systems. CA solutions are tested by comparison with MC simulations and previous data in the literature. Special interest is devoted to the calculation of the configurational entropy per site in the limit case of θ → 1 (full coverage), where some exact results are available. The theoretical formalism is also applied to model CH4 and CO2 clathrate hydrates. In these systems, a triangular lattice is used to simulate the substrate, and methane(carbon dioxide) molecules can be well represented by triangular(linear) trimers. The good qualitative agreement between simulation and analytical data supports the validity of the CA scheme to predict the behavior of a wide variety of multisite-adsorption models, for which theoretical solutions are very difficult to obtain.

Prenatal exposure to metal mixtures and lung function in children from the New Hampshire birth cohort study.

Prenatal exposure to metals/metalloids, even at common US population levels, may pose risks to fetal health, and affect children's lung function. Yet, the combined effects of simultaneous prenatal exposures on children's lung function remain largely unexplored. This study analyzed 11 metals (As speciation, Cd, Co, Cu, Mo, Ni, Pb, Sb, Se, Sn, Zn) in maternal urine during weeks 24-28 of gestation and evaluated lung function, including forced vital capacity (FVC) and forced expiratory volume in the first second of expiration (FEV1), in 316 US mother-child pairs at around age 7. We used Bayesian Kernel Machine Regression (BKMR), weighted quantile sum regression (WQSR), and multiple linear regression to examine the association between metal mixture exposure and children's lung function, adjusting for maternal smoking, child age, sex, and height. In BKMR models assessing combined exposure effects, limited evidence of metal non-linearity or interactions was found. Nevertheless, Co, As species, and Pb showed a negative association, while Mo exhibited a positive association with children's FVC and FEV1, with other metals held constant at their medians. The weighted index, from WQSR analysis assessing the cumulative impact of all metals, highlighted prenatal Mo with the highest positive weight, and Co, As, and Sb with the most substantial negative weights on children's FVC and FEV1. Urinary Co and Pb were negatively associated with FVC (ß = -0.09, 95% confidence interval (CI) (-0.18; -0.01) and ß = -0.07, 95% CI (-0.13; 0.00), respectively). Co was also negatively associated with FEV1 (ß = -0.09, 95% CI (-0.18; 0.00). There was a negative association between As and FVC, and a positive association between Mo and both FVC and FEV1, though with wide confidence intervals. Our findings suggest that prenatal trace element exposures may impact children's lung function, emphasizing the importance of reducing toxic exposures and maintaining adequate nutrient levels.

Dietary intake of polychlorinated dibenzo-p-dioxins and furans, adiposity and obesity status.

INTRODUCTION: The principal source of exposure to Polychlorinated dibenzo-p-dioxins and polychlorinated dibenzo-p-furans (PCDD/Fs) in humans comes from food intake. PCDD/Fs, are a family of potential endocrine disruptors and have been associated with different chronic diseases such as diabetes and hypertension. However, studies assessing the relationship between dietary exposure to PCDD/Fs and adiposity or obesity status in a middle-aged population are limited. OBJECTIVE: To assess cross-sectionally and longitudinally the associations between estimated dietary intake (DI) of PCDD/Fs and body mass index (BMI), waist circumference, and the prevalence/incidence of obesity and abdominal obesity in a middle-aged population. METHODS: In 5899 participants aged 55-75 years (48% women) living with overweight/obesity from the PREDIMED-plus cohort, PCDD/Fs DI was estimated using a 143-item validated food-frequency questionnaire, and the levels of food PCDD/F expressed as Toxic Equivalents (TEQ). Consequently, cross-sectional and prospective associations between baseline PCDD/Fs DI (in pgTEQ/week) and adiposity or obesity status were assessed at baseline and after 1-year follow-up using multivariable cox, logistic or linear regression models. RESULTS: Compared to participants in the first PCDD/F DI tertile, those in the highest tertile presented a higher BMI (ß-coefficient [confidence interval]) (0.43kg/m2 [0.22; 0.64]; P-trend <0.001), a higher waist circumference (1.11 cm [0.55; 1.66]; P-trend <0.001), and a higher prevalence of obesity and abdominal obesity (1.05 [1.01; 1.09] and 1.02 [1.00; 1.03]; P-trend = 0.09 and 0.027, respectively). In the prospective analysis, participants in the top PCDD/F DI baseline tertile showed an increase in waist circumference compared with those in the first tertile after 1-year of follow-up (ß-coefficient 0.37 cm [0.06; 0.70]; P-trend = 0.015). CONCLUSION: Higher DI of PCDD/Fs was positively associated with adiposity parameters and obesity status at baseline and with changes in waist circumference after 1-year of follow-up in subjects living with overweight/obesity. Further large prospective studies using a different population with longer follow-up periods are warranted in the future to strengthen our results.

Carbon dioxide (CO2) emissions and adherence to Mediterranean diet in an adult population: the Mediterranean diet index as a pollution level index.

BACKGROUND: Research related to sustainable diets is is highly relevant to provide better understanding of the impact of dietary intake on the health and the environment. AIM: To assess the association between the adherence to an energy-restricted Mediterranean diet and the amount of CO2 emitted in an older adult population. DESIGN AND POPULATION: Using a cross-sectional design, the association between the adherence to an energy-reduced Mediterranean Diet (erMedDiet) score and dietary CO2 emissions in 6646 participants was assessed. METHODS: Food intake and adherence to the erMedDiet was assessed using validated food frequency questionnaire and 17-item Mediterranean questionnaire. Sociodemographic characteristics were documented. Environmental impact was calculated through greenhouse gas emissions estimations, specifically CO2 emissions of each participant diet per day, using a European database. Participants were distributed in quartiles according to their estimated CO2 emissions expressed in kg/day: Q1 (≤2.01 kg CO2), Q2 (2.02-2.34 kg CO2), Q3 (2.35-2.79 kg CO2) and Q4 (≥2.80 kg CO2). RESULTS: More men than women induced higher dietary levels of CO2 emissions. Participants reporting higher consumption of vegetables, fruits, legumes, nuts, whole cereals, preferring white meat, and having less consumption of red meat were mostly emitting less kg of CO2 through diet. Participants with higher adherence to the Mediterranean Diet showed lower odds for dietary CO2 emissions: Q2 (OR 0.87; 95%CI: 0.76-1.00), Q3 (OR 0.69; 95%CI: 0.69-0.79) and Q4 (OR 0.48; 95%CI: 0.42-0.55) vs Q1 (reference). CONCLUSIONS: The Mediterranean diet can be environmentally protective since the higher the adherence to the Mediterranean diet, the lower total dietary CO2 emissions. Mediterranean Diet index may be used as a pollution level index.

Transformers for Multi-Horizon Forecasting in an Industry 4.0 Use Case.

Recently, a novel approach in the field of Industry 4.0 factory operations was proposed for a new generation of automated guided vehicles (AGVs) that are connected to a virtualized programmable logic controller (PLC) via a 5G multi-access edge-computing (MEC) platform to enable remote control. However, this approach faces a critical challenge as the 5G network may encounter communication disruptions that can lead to AGV deviations and, with this, potential safety risks and workplace issues. To mitigate this problem, several works have proposed the use of fixed-horizon forecasting techniques based on deep-learning models that can anticipate AGV trajectory deviations and take corrective maneuvers accordingly. However, these methods have limited prediction flexibility for the AGV operator and are not robust against network instability. To address this limitation, this study proposes a novel approach based on multi-horizon forecasting techniques to predict the deviation of remotely controlled AGVs. As its primary contribution, the work presents two new versions of the state-of-the-art transformer architecture that are well-suited to the multi-horizon prediction problem. We conduct a comprehensive comparison between the proposed models and traditional deep-learning models, such as the long short-term memory (LSTM) neural network, to evaluate the performance and capabilities of the proposed models in relation to traditional deep-learning architectures. The results indicate that (i) the transformer-based models outperform LSTM in both multi-horizon and fixed-horizon scenarios, (ii) the prediction accuracy at a specific time-step of the best multi-horizon forecasting model is very close to that obtained by the best fixed-horizon forecasting model at the same step, (iii) models that use a time-sequence structure in their inputs tend to perform better in multi-horizon scenarios compared to their fixed horizon counterparts and other multi-horizon models that do not consider a time topology in their inputs, and (iv) our experiments showed that the proposed models can perform inference within the required time constraints for real-time decision making.

Dietary Exposure to Toxic Elements and the Health of Young Children: Methodological Considerations and Data Needs.

Concerns have been raised regarding toxic-element (arsenic, cadmium, lead, and mercury) contamination of commercially available infant foods around the world. Young children are vulnerable to the effects of toxic elements, based on higher absorption levels and potentially poorer detoxification capacities. Toxic-element exposures in early life exact high societal costs, but it is unclear how much dietary exposure to these elements contributes to adverse health outcomes. Well-designed epidemiological studies conducted in different geographical and socioeconomic contexts need to estimate dietary toxicant exposure in young children and to determine whether causal links exist between toxicants in children's diets and health outcomes. This commentary outlines the methodological considerations and data needs to advance such research.

Exposure to metal mixture and growth indicators at 4-5 years. A study in the INMA-Asturias cohort.

BACKGROUND: Exposure to toxic and non-toxic metals impacts childhood growth and development, but limited data exists on exposure to metal mixtures. Here, we investigated the effects of exposure to individual metals and a mixture of barium, cadmium, cobalt, lead, molybdenum, zinc, and arsenic on growth indicators in children 4-5 years of age. METHODS: We used urine metal concentrations as biomarkers of exposure in 328 children enrolled in the Spanish INMA-Asturias cohort. Anthropometric measurements (arm, head, and waist circumferences, standing height, and body mass index) and parental sociodemographic variables were collected through face-to-face interviews by trained study staff. Linear regressions were used to estimate the independent effects and were adjusted for each metal in the mixture. We applied Bayesian kernel machine regression to examine non-linear associations and potential interactions. RESULTS: In linear regression, urinary levels of cadmium were associated with reduced arm circumference (ßadjusted = -0.44, 95% confidence interval [CI]: -0.73, -0.15), waist circumference (ßadjusted = -1.29, 95% CI: -2.10, -0.48), and standing height (ßadjusted = -1.09, 95% CI: -1.82, -0.35). Lead and cobalt concentrations were associated with reduced standing height (ßadjusted = -0.64, 95% CI: -1.20, -0.07) and smaller head circumference (ßadjusted = -0.29, 95% CI: -0.49, -0.09), respectively. However, molybdenum was positively associated with head circumference (ßadjusted = 0.22, 95% CI: 0.01, 0.43). BKMR analyses showed strong linear negative associations of cadmium with arm and head circumference and standing height. BKMR analyses also found lead and cobalt in the metal mixture were related to reduce standing height and head circumference, and consistently found molybdenum was related to increased head circumference. CONCLUSION: Our findings suggest that exposure to metal mixtures impacts growth indicators in children.

Serum concentrations of persistent organic pollutants mixture during pregnancy and anogenital distance in 8-year-old children from the INMA-Asturias cohort.

BACKGROUND: During pregnancy, women are commonly exposed to several endocrine-disrupting chemicals, including persistent organic pollutants (POPs). These compounds can transfer to the fetus through the placenta. Prenatal POP exposure is related to altered fetal genital and reproductive tract development. However, the relationship between exposure to POP mixtures and anogenital distance (AGD) is poorly investigated. This study investigated the association between prenatal exposure to POP mixtures and AGD in 8-year-old children. METHODS: Data were collected from the INMA-Asturias cohort. Maternal serum POP concentrations were measured during the first trimester of pregnancy. Anoscrotal distance (AGDAS) and anopenile distance (AGDAP) in males and anofourchetal distance (AGDAF) and anoclitoral distance (AGDAC) in females were recorded in 362 8-years-olds. Conventional linear regression, and the novel weighted quantile sum regression (WQSR) and Bayesian kernel machine regression (BKMR) models were applied to assess the relationships between AGD and POPs exposure stratified by sex. RESULTS: Among males, in the linear regression, b-hexachlorocyclohexane, PCB138, PCB153, and PCB180 were inversely associated with the anogenital index (AGI)AS (-0.06 mm/kg (95% confidence interval [CI]: -0.11, -0.02), -0.07 mm/kg (95% CI: -0.14, -0.01), -0.07 mm/kg (95% CI: -0.13, -0.01), and -0.08 mm/kg (95% CI: -0.14, -0.02), respectively). Among females, polybrominated diphenyl ether (PBDE)47 and PBDE154 were positively associated with increased AGIAF (0.02 mm/kg (95% CI: 0.00, 0.03) and 0.09 mm/kg (95% CI: 0.01, 0.17), respectively). BKMR confirmed these associations. WQSR found a negative combined effect of the POP mixture on AGD, and PCB138, PCB153, and PCB180 (weighted 0.18, 0.13, and 0.09, respectively) were identified as the most impacting chemicals. In females, WQSR found a positive combined effect and determined PBDE47 (weighted 0.35) as the most impacting. CONCLUSIONS: Maternal exposure to a POP mixture was negatively associated with AGD in male children and positively associated with AGD in female children, thus providing evidence of the adverse effects of POPs on genital development.

B5GEMINI: AI-Driven Network Digital Twin.

Network Digital Twin (NDT) is a new technology that builds on the concept of Digital Twins (DT) to create a virtual representation of the physical objects of a telecommunications network. NDT bridges physical and virtual spaces to enable coordination and synchronization of physical parts while eliminating the need to directly interact with them. There is broad consensus that Artificial Intelligence (AI) and Machine Learning (ML) are among the key enablers to this technology. In this work, we present B5GEMINI, which is an NDT for 5G and beyond networks that makes an extensive use of AI and ML. First, we present the infrastructural and architectural components that support B5GEMINI. Next, we explore four paradigmatic applications where AI/ML can leverage B5GEMINI for building new AI-powered applications. In addition, we identify the main components of the AI ecosystem of B5GEMINI, outlining emerging research trends and identifying the open challenges that must be solved along the way. Finally, we present two relevant use cases in the application of NDTs with an extensive use of ML. The first use case lays in the cybersecurity domain and proposes the use of B5GEMINI to facilitate the design of ML-based attack detectors and the second addresses the design of energy efficient ML components and introduces the modular development of NDTs adopting the Digital Map concept as a novelty.

Correction: Vidal et al. From Messengers to Receptors in Psoriasis: The Role of IL-17RA in Disease and Treatment. Int. J. Mol. Sci. 2021, 22, 6740.

In the original publication [...].

Adsorption of interacting particles on bivariate diffusion-limited aggregates.

The adsorption of pairwise interacting particles on fractal surfaces has been studied by grand canonical Monte Carlo simulations. The substrate is built from a mixture of two types of objects: (i) objects with two bonds and (ii) objects with four bonds. These objects move on a square lattice, according to diffusion-limited aggregation (DLA) rules, and stick to each other only if they have a free bond pointing at each other and, of course, are first neighbors of each other. The resulting substrate, which is named as bivariate diffusion-limited aggregate (BDLA), is a fractal structure composed by two bonds units with fraction [Formula: see text] and four bonds units with concentration [Formula: see text]. Different surface morphologies are obtained by varying [Formula: see text] and [Formula: see text]. In the limit case of [Formula: see text] and [Formula: see text], the standard DLA model is recovered. In addition, repulsive lateral interactions between adsorbed particles are considered. Adsorption isotherms and differential heats of adsorption are calculated for different values of the parameters of the system. In the case of high repulsive couplings, a wide variety of structural orderings are observed in the adlayer. The main characteristics of these ordered phases are discussed in terms of the topological properties of the bivariate aggregates.

Order and disorder in the adsorption model of repulsively interacting binary mixtures on triangular lattices: theory and Monte Carlo simulations.

The problem of interacting binary mixtures adsorbed on triangular lattices has been studied by means of ground-state (GS) calculations, Monte Carlo (MC) simulations and exact counting of configurations on finite cells [the so-called cluster-exact approximation (CA)]. We focus on the case of repulsive intraspecies couplings and null interspecies interaction, where a rich variety of ordered phases is found in the adsorbed layer. Each surface structure is separated from a disordered state by a phase transition occurring at a finite temperature. The ordered phases are identified by means of GS analysis, and their dependence on temperature is studied by MC simulations and CA. Total and partial adsorption isotherms are obtained for values of the lateral interactions in the different regions of the phase diagram. MC results are compared with CA calculations. A very good coincidence is obtained between both methods, supporting the validity of the exact counting of states on finite cells as an adequate approach to describe the behavior of multicomponent competitive adsorption with adsorbate-adsorbate interactions.

Toenails as a biomarker of exposure to arsenic: A review.

This systematic review summarizes the current evidence related to the reliability of toenail total arsenic concentrations (thereafter "arsenic") as a biomarker of long-term exposure. Specifically, we reviewed literature on consistency of repeated measures over time, association with other biomarkers and metal concentrations, factors influencing concentrations, and associations with health effects. We identified 129 papers containing quantitative original data on arsenic in toenail samples covering populations from 29 different countries. We observed geographic differences in toenail arsenic concentrations, with highest median or mean concentrations in Asian countries. Arsenic-contaminated drinking water, occupational exposure or living in specific industrial areas were associated with an increased toenail arsenic content. The effects of other potential determinants and sources of arsenic exposure including diet, gender and age on the concentrations in toenails need further investigations. Toenail arsenic was correlated with the concentrations in hair and fingernails, and with urine arsenic mainly among highly exposed populations with a toenail mean or median ≥1 µg/g. Overall, there is a growing body of evidence suggesting that arsenic content from a single toenail sample may reflect long-term internal dose-exposure. Toenail arsenic can serve as a reliable measure of toxic inorganic arsenic exposure in chronic disease research, particularly promising for cancer and cardiovascular conditions.

From Messengers to Receptors in Psoriasis: The Role of IL-17RA in Disease and Treatment.

The paradigm of psoriasis as a Th17-driven disease has evolved in the last years towards a much deeper knowledge of the complex pathways, mechanisms, cells, and messengers involved, highlighting the crucial role played by the IL-17 family of cytokines. All IL-17 isoforms signal through IL-17R. Five subunits of IL-17R have been described to date, which couple to form a homo- or hetero-receptor complex. Characteristically, IL-17RA is a common subunit in all hetero-receptors. IL-17RA has unique structural-containing a SEFIR/TILL domain-and functional-requiring ACT-1 for signaling-properties, enabling Th17 cells to act as a bridge between innate and adaptive immune cells. In psoriasis, IL-17RA plays a key role in pathogenesis based on: (a) IL-17A, IL-17F, and other IL-17 isoforms are involved in disease development; and (b) IL-17RA is essential for signaling of all IL-17 cytokines but IL-17D, whose receptor has not been identified to date. This article reviews current evidence on the biology and role of the IL-17 family of cytokines and receptors, with focus on IL-17RA, in psoriasis and some related comorbidities, and puts them in context with current and upcoming treatments.

Multiple Exclusion Statistics.

A new distribution for systems of particles in equilibrium obeying the exclusion of correlated states is presented following Haldane's state counting. It relies upon an ansatz to deal with the multiple exclusion that takes place when the states accessible to single particles are spatially correlated and it can be simultaneously excluded by more than one particle. Haldane's statistics and Wu's distribution are recovered in the limit of noncorrelated states of the multiple exclusion statistics. In addition, an exclusion spectrum function G(n) is introduced to account for the dependence of the state exclusion on the occupation number n. The results of thermodynamics and state occupation are shown for ideal lattice gases of linear particles of size k (k-mers) where the multiple exclusion occurs. Remarkable agreement is found with grand-canonical Monte Carlo simulations from k=2 to 10 where the multiple exclusion dominates as k increases.

Inorganic arsenic exposure and neuropsychological development of children of 4-5 years of age living in Spain.

Early-life exposure to inorganic arsenic (iAs) may adversely impact health later in life. To date, evidence of iAs adverse effects on children's neurodevelopment comes mainly from populations highly exposed to contaminated water with conflicting results. Little is known about those effects among populations with low iAs exposure from food intake. We investigated the cross-sectional association between exposure to iAs and neurodevelopment scores among children living in Spain whose main route of exposure was diet. Arsenic species concentrations in urine from 400 children was determined, and the sum of urinary iAs, dimethylarsinic acid, and monomethylarsonic acid was used to estimate iAs exposure. The McCarthy Scales of Children's Abilities was used to assess children's neuropsychological development at about 4-5 years of age. The median (interquartile range) of children's sum of urinary iAs, MMA, and DMA was 4.85 (2.74-7.54) µg/L, and in adjusted linear regression analyses the natural logarithm transformed concentrations showed an inverse association with children's motor functions (ß, [95% confidence interval]; global scores (-2.29, [-3.95, -0.63])), gross scores (-1.92, [-3.52, -0.31]) and fine scores (-1.54, [-3.06, -0.03]). In stratified analyses by sex, negative associations were observed with the scores in the quantitative index (-2.59, [-5.36, 0.17]) and working memory function (-2.56, [-5.36, 0.24]) only in boys. Our study suggests that relatively low iAs exposure may impair children's neuropsychological development and that sex-related differences may be present in susceptibility to iAs related effects; however, our findings should be interpreted with caution given the possibility of residual confounding.