Sex-specific associations of environmental exposures with prevalent diabetes and obesity - Results from the KORA Fit study.

Promising evidence suggests a link between environmental factors, particularly air pollution, and diabetes and obesity. However, it is still unclear whether men and women are equally susceptible to environmental exposures. Therefore, we aimed to assess sex-specific long-term effects of environmental exposures on metabolic diseases. We analyzed cross-sectional data from 3,034 participants (53.7% female, aged 53-74 years) from the KORA Fit study (2018/19), a German population-based cohort. Environmental exposures, including annual averages of air pollutants [nitrogen oxides (NO2, NOx), ozone, particulate matter of different diameters (PM10, PMcoarse, PM2.5), PM2.5abs, particle number concentration], air temperature and surrounding greenness, were assessed at participants' residences. We evaluated sex-specific associations of environmental exposures with prevalent diabetes, obesity, body-mass-index (BMI) and waist circumference using logistic or linear regression models with an interaction term for sex, adjusted for age, lifestyle factors and education. Further effect modification, in particular by urbanization, was assessed in sex-stratified analyses. Higher annual averages of air pollution, air temperature and greenness at residence were associated with diabetes prevalence in men (NO2: Odds Ratio (OR) per interquartile range increase in exposure: 1.49 [95% confidence interval (CI): 1.13, 1.95], air temperature: OR: 1.48 [95%-CI: 1.15, 1.90]; greenness: OR: 0.78 [95%-CI: 0.59, 1.01]) but not in women. Conversely, higher levels of air pollution, temperature and lack of greenness were associated with lower obesity prevalence and BMI in women. After including an interaction term for urbanization, only higher greenness was associated with higher BMI in rural women, whereas higher air pollution was associated with higher BMI in urban men. To conclude, we observed sex-specific associations of environmental exposures with metabolic diseases. An additional interaction between environmental exposures and urbanization on obesity suggests a higher susceptibility to air pollution among urban men, and higher susceptibility to greenness among rural women, which needs corroboration in future studies.

Improved daily estimates of relative humidity at high resolution across Germany: A random forest approach.

The lack of readily available methods for estimating high-resolution near-surface relative humidity (RH) and the incapability of weather stations to fully capture the spatiotemporal variability can lead to exposure misclassification in studies of environmental epidemiology. We therefore aimed to predict German-wide 1 × 1 km daily mean RH during 2000-2021. RH observations, longitude and latitude, modelled air temperature, precipitation and wind speed as well as remote sensing information on topographic elevation, vegetation, and the true color band composite were incorporated in a Random Forest (RF) model, in addition to date for capturing the temporal variations of the response-explanatory variables relationship. The model achieved high accuracy (R2 = 0.83) and low errors (Root Mean Square Error (RMSE) of 5.07%, Mean Absolute Percentage Error (MAPE) of 5.19% and Mean Percentage Error (MPE) of - 0.53%), calculated via ten-fold cross-validation. A comparison of our RH predictions with measurements from a dense monitoring network in the city of Augsburg, South Germany confirmed the good performance (R2 ≥ 0.86, RMSE ≤ 5.45%, MAPE ≤ 5.59%, MPE ≤ 3.11%). The model displayed high German-wide RH (22y-average of 79.00%) and high spatial variability across the country, exceeding 12% on yearly averages. Our findings indicate that the proposed RF model is suitable for estimating RH for a whole country in high-resolution and provide a reliable RH dataset for epidemiological analyses and other environmental research purposes.

High-resolution spatiotemporal modeling of daily near-surface air temperature in Germany over the period 2000-2020.

The commonly used weather stations cannot fully capture the spatiotemporal variability of near-surface air temperature (Tair), leading to exposure misclassification and biased health effect estimates. We aimed to improve the spatiotemporal coverage of Tair data in Germany by using multi-stage modeling to estimate daily 1 × 1 km minimum (Tmin), mean (Tmean), maximum (Tmax) Tair and diurnal Tair range during 2000-2020. We used weather station Tair observations, satellite-based land surface temperature (LST), elevation, vegetation and various land use predictors. In the first stage, we built a linear mixed model with daily random intercepts and slopes for LST adjusted for several spatial predictors to estimate Tair from cells with both Tair and LST available. In the second stage, we used this model to predict Tair for cells with only LST available. In the third stage, we regressed the second stage predictions against interpolated Tair values to obtain Tair countrywide. All models achieved high accuracy (0.91 ≤ R2 ≤ 0.98) and low errors (1.03 °C ≤ Root Mean Square Error (RMSE) ≤ 2.02 °C). Validation with external data confirmed the good performance, locally, i.e., in Augsburg for all models (0.74 ≤ R2 ≤ 0.99, 0.87 °C ≤ RMSE ≤ 2.05 °C) and countrywide, for the Tmean model (0.71 ≤ R2 ≤ 0.99, 0.79 °C ≤ RMSE ≤ 1.19 °C). Annual Tmean averages ranged from 8.56 °C to 10.42 °C with the years beyond 2016 being constantly hotter than the 21-year average. The spatial variability within Germany exceeded 15 °C annually on average following patterns including mountains, rivers and urbanization. Using a case study, we showed that modeling leads to broader Tair variability representation for exposure assessment of participants in health cohorts. Our results indicate the proposed models as suitable for estimating nationwide Tair at high resolution. Our product is critical for temperature-based epidemiological studies and is also available for other research purposes.

The association of COVID-19 incidence with temperature, humidity, and UV radiation - A global multi-city analysis.

BACKGROUND AND AIM: The associations between COVID-19 transmission and meteorological factors are scientifically debated. Several studies have been conducted worldwide, with inconsistent findings. However, often these studies had methodological issues, e.g., did not exclude important confounding factors, or had limited geographic or temporal resolution. Our aim was to quantify associations between temporal variations in COVID-19 incidence and meteorological variables globally. METHODS: We analysed data from 455 cities across 20 countries from 3 February to 31 October 2020. We used a time-series analysis that assumes a quasi-Poisson distribution of the cases and incorporates distributed lag non-linear modelling for the exposure associations at the city-level while considering effects of autocorrelation, long-term trends, and day of the week. The confounding by governmental measures was accounted for by incorporating the Oxford Governmental Stringency Index. The effects of daily mean air temperature, relative and absolute humidity, and UV radiation were estimated by applying a meta-regression of local estimates with multi-level random effects for location, country, and climatic zone. RESULTS: We found that air temperature and absolute humidity influenced the spread of COVID-19 over a lag period of 15 days. Pooling the estimates globally showed that overall low temperatures (7.5 °C compared to 17.0 °C) and low absolute humidity (6.0 g/m3 compared to 11.0 g/m3) were associated with higher COVID-19 incidence (RR temp =1.33 with 95%CI: 1.08; 1.64 and RR AH =1.33 with 95%CI: 1.12; 1.57). RH revealed no significant trend and for UV some evidence of a positive association was found. These results were robust to sensitivity analysis. However, the study results also emphasise the heterogeneity of these associations in different countries. CONCLUSION: Globally, our results suggest that comparatively low temperatures and low absolute humidity were associated with increased risks of COVID-19 incidence. However, this study underlines regional heterogeneity of weather-related effects on COVID-19 transmission.

The Impact of the COVID-19 Pandemic on Self-Reported Health.

BACKGROUND: The pandemic caused by the coronavirus SARS-CoV-2 and the countermeasures taken to protect the public are having a substantial effect on the health of the population. In Germany, nationwide protective measures to halt the spread of the virus were implemented in mid-March for 6 weeks. METHODS: In May, the impact of the pandemic was assessed in the German National Cohort (NAKO). A total of 113 928 men and women aged 20 to 74 years at the time of the baseline examination conducted 1 to 5 years earlier (53%) answered, within a 30-day period, a follow-up questionnaire on SARS-CoV-2 test status, COVID-19- associated symptoms, and self-perceived health status. RESULTS: The self-reported SARS-CoV-2 test frequency among the probands was 4.6%, and 344 participants (0.3%) reported a positive test result. Depressive and anxiety-related symptoms increased relative to baseline only in participants under 60 years of age, particularly in young women. The rate of moderate to severe depressive symptoms increased from 6.4% to 8.8%. Perceived stress increased in all age groups and both sexes, especially in the young. The scores for mental state and self-rated health worsened in participants tested for SARS-CoV-2 compared with those who were not tested. In 32% of the participants, however, self-rated health improved. CONCLUSION: The COVID-19 pandemic and the protective measures during the first wave had effects on mental health and on self-rated general health.

Phase Equilibria Modeling with Systematically Coarse-Grained Models-A Comparative Study on State Point Transferability.

Coarse-grained (CG) models for soft matter systems can be parameterized using a variety of approaches. In systematic coarse-graining procedures, effective interactions are calculated using a reference fine-grained simulation. The degree to which thermodynamical and structural properties of the reference system are reproduced depends critically on the coarse-graining method used to parameterize the model. In this article, a comparative study is presented on the capability of different CG models to reproduce vapor-liquid equilibrium thermodynamics of hexane and perfluorohexane systems. CG models are developed using coarse-graining methods based on the reproduction of (a) structure and (b) coupling free energies. Although the structure-based models show an overestimation of the pressure and therefore perform relatively poorly in reproducing the vapor-liquid thermodynamics, it is shown that methods based on coupling free energies, in particular the conditional reversible work method, are capable of better reproducing the vapor-liquid phase diagram of the united-atom reference simulations, while reproducing the liquid structure almost as accurately as the structure-based CG model. This illustrates the state point transferability of the interaction potentials calculated using these methods, as the resulting CG model (which has been parameterized at 300 K) is capable of accurately modeling the thermodynamic properties up to the critical point.

Functionalization Pattern of Graphene Oxide Sheets Controls Entry or Produces Lipid Turmoil in Phospholipid Membranes.

Molecular dynamics, coarse-grained to the level of hydrophobic and hydrophilic interactions, shows that graphene oxide sheets, GOSs, can pierce through the phospholipid membrane and navigate the double layer only if the hydrophilic groups are randomly dispersed in the structure. Their behavior resembles that found in similar calculations for pristine graphene sheets. If the oxidation is located at the edge of the sheets, GOSs hover over the membrane and trigger a major reorganization of the lipids. The reorganization is the largest when the radius of the edge-functionalized sheet is similar to the length of the lipophilic chain of the lipids. In the reorganization, the heads of the lipid chains form dynamical structures that pictorially resemble the swirl of water flowing down a drain. All effects maximize the interaction between hydrophobic moieties on the one hand and lipophilic fragments on the other and are accompanied by a large number of lipid flip-flops. Possible biological consequences are discussed.

Evaluation of mapping schemes for systematic coarse graining of higher alkanes.

A model is introduced to explore the influence of different coarse-grained (CG) resolutions on the structural and thermodynamic properties of higher alkanes. Four different mapping schemes are considered, for which the potentials are derived using the conditional reversible work (CRW) method. The CRW method is a bottom-up coarse-graining procedure, which derives effective pair potentials between nonbonded chemical groups defined by the mapping scheme from the underlying molecular interactions in a quick, inexpensive way. We consider the applicability of CRW for mapping sites including up to four heavy atoms and study the properties of n-dodecane and n-tetracosane in the liquid state. Both chemical and thermodynamic transferability are achieved for high resolution representations. However, the ability of the coarse-grained model to effectively describe the system deteriorates as the size of the mapping is increased and sampling issues arise. By looking at the configuration distributions of the dihedrals in the atomistic sampling runs (gas phase), it is shown that the gauche population is underrepresented. Here we address the problem and propose a viable solution to recover the agreement between atomistic and low resolution coarse-grained representation. All the CRW potentials presented in the paper are reported in tabulated and analytical form.

"Active" drops as phantom models for living cells: a mesoscopic particle-based approach.

Drops and biological cells share some morphological features and visco-elastic properties. The modelling of drops by mesoscopic non-atomistic models has been carried out to a high degree of success in recent years. We extend such treatment and discuss a simple, drop-like model to describe the interactions of the outer layer of cells with the surfaces of materials. Cells are treated as active mechanical objects that are able to generate adhesion forces. They appear with their true size and are made of "parcels of fluids" or beads. The beads are described by (very) few quantities/parameters related to fundamental chemical forces such as hydrophilicity and lipophilicity that represent an average of the properties of a patch of material or an area of the cell(s) surface. The investigation of adhesion dynamics, motion of individual cells, and the collective behavior of clusters of cells on materials is possible. In the simulations, the drops become active soft matter objects and different from regular droplets they do not fuse when in contact, their trajectories are not Brownian, and they can be forced "to secrete" molecules, to name some of the properties targeted by the modeling. The behavior that emerges from the simulations allows ascribing some cell properties to their mechanics, which are related to their biological features.

Graphene can wreak havoc with cell membranes.

Molecular dynamics--coarse grained to the level of hydrophobic and hydrophilic interactions--shows that small hydrophobic graphene sheets pierce through the phospholipid membrane and navigate the double layer, intermediate size sheets pierce the membrane only if a suitable geometric orientation is met, and larger sheets lie mainly flat on the top of the bilayer where they wreak havoc with the membrane and create a patch of upturned phospholipids. The effect arises in order to maximize the interaction between hydrophobic moieties and is quantitatively explained in terms of flip-flops by the analysis of the simulations. Possible severe biological consequences are discussed.

Explaining fullerene dispersion by using micellar solutions.

An effective computational strategy to describe the dispersion of C60 by surfactants is presented. The influence of parameters such as surfactant concentration and molecular length on the final morphology of the system is explored to explain the experimental results and to understand the incorporation of C60 inside micelles. Both neutral and charged amphiphilic molecules are simulated. The long-discussed problem of the location of fullerenes in micelles is addressed and C60 is found in the hydrocarbon-chain region of the micelles. If the available hydrophobic space increases, C60 is localized in the inner part of the micellar core. Short, charged amphiphilic stabilizers are more efficient at dispersing fullerenes monomolecularly. Two different phases of C60 are observed as the C60/surfactant ratio varies. In the first, aggregates of C60 are entrapped inside the micelles, whereas, in the second, colloidal nanoC60 is formed with surfactants adsorbed on the surface.

Stability, dynamics, and lubrication of MoS2 platelets and nanotubes.

A model is introduced to investigate structure, stability, dynamics, and properties of MoS(2). The tribological behavior of the material is obtained from the autocorrelation function, ACF, of the forces, using the Green-Kubo equation, and by the classical Amontons' laws. In the idealized system, i.e. without defects, junctions, vacancies, asperities, and impurities, both models find a superlubrication regime, in agreement with some experiments. In nanotubes, NTs, friction is an order of magnitude lower than in the layered systems. The calculations also show that there is a substantial stabilization, per atom, for the formation of multiwall NTs with at least four walls.

Wrapping nanotubes with micelles, hemimicelles, and cylindrical micelles.

This work uses a simple model based on hydrophobic and hydrophilic forces to investigate the molecular dynamics that lead to the supramolecular self-assembly of surfactants around carbon nanotubes (CNTs). The effects of the concentration and the structure of surfactants are explored. The bead-based mesoscopic description spontaneously develops the several micellar morphologies that are known to wrap and solvate CNTs.