Gain-of-function and loss-of-function variants in GRIA3 lead to distinct neurodevelopmental phenotypes.

AMPA (α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid) receptors (AMPARs) mediate fast excitatory neurotransmission in the brain. AMPARs form by homo- or heteromeric assembly of subunits encoded by the GRIA1-GRIA4 genes, of which only GRIA3 is X-chromosomal. Increasing numbers of GRIA3 missense variants are reported in patients with neurodevelopmental disorders (NDD), but only a few have been examined functionally. Here, we evaluated the impact on AMPAR function of one frameshift and 43 rare missense GRIA3 variants identified in patients with NDD by electrophysiological assays. Thirty-one variants alter receptor function and show loss-of-function (LoF) or gain-of-function (GoF) properties, whereas 13 appeared neutral. We collected detailed clinical data from 25 patients (from 23 families) harbouring 17 of these variants. All patients had global developmental impairment, mostly moderate (9/25) or severe (12/25). Twelve patients had seizures, including focal motor (6/12), unknown onset motor (4/12), focal impaired awareness (1/12), (atypical) absence (2/12), myoclonic (5/12), and generalized tonic-clonic (1/12) or atonic (1/12) seizures. The epilepsy syndrome was classified as developmental and epileptic encephalopathy in eight patients, developmental encephalopathy without seizures in 13 patients, and intellectual disability with epilepsy in four patients. Limb muscular hypotonia was reported in 13/25, and hypertonia in 10/25. Movement disorders were reported in 14/25, with hyperekplexia or non-epileptic erratic myoclonus being the most prevalent feature (8/25). Correlating receptor functional phenotype with clinical features revealed clinical features for GRIA3-associated NDDs and distinct NDD phenotypes for LoF and GoF variants. GoF variants were associated with more severe outcomes: patients were younger at the time of seizure onset (median age one month), hypertonic, and more often had movement disorders, including hyperekplexia. Patients with LoF variants were older at the time of seizure onset (median age 16 months), hypotonic, and had sleeping disturbances. LoF and GoF variants were disease-causing in both sexes but affected males often carried de novo or hemizygous LoF variants inherited from healthy mothers, whereas all but one affected females had de novo heterozygous GoF variants.

Summary of the first Brazilian Symposium on Human Biometeorology.

This brief background highlights Brazil as a 'climate-health hotspot', i.e. a country where climate affects local populations negatively through multiple pathways (Di Napoli et al. BMC Public Health 22(1):1-8, 2022). Knowledge gaps still need to be filled concerning the various climaterelated dimensions of tourism, vector-borne diseases, mortality and morbidity in urban centers in the country (Krüger et al. Int J Biometeorol 66(7):1297-1315, 2022). Motivated by this, the first Brazilian Symposium on Human Biometeorology (Simpósio Brasileiro de Biometeorologia Humana 2022) was organized and held at the Federal University of Rio Grande do Norte (UFRN) in Natal, northeastern Brazil, between July 4 and 8, 2022. The symposium was organized as a hybrid event by a committee composed of researchers acting in different regions of the country, and who had an ongoing research collaboration on matters related to human biometeorology. The event was partly sponsored by the ISB and partly self-supported by the organizers and institutions involved. The symposium aimed to promote the development of the research area on human biometeorology in Brazil in facing challenges imposed by a globally and locally changing climate. To achieve this, the symposium focused on five main topics of discussion: a) climate-driven diseases; b) thermal comfort, urban and architectural biometeorology; c) atmospheric pollution and health; d) climate change; e) climate, health and climate change. This summary highlights the main findings, future research directions, and policy implications in each topic from the presentations and panel discussions.

The 2020 report of The Lancet Countdown on health and climate change: responding to converging crises.

TRANSLATIONS: For the Chinese, French, German, and Spanish translations of the abstract see Supplementary Materials section.

Tracking the impacts of climate change on human health via indicators: lessons from the Lancet Countdown.

BACKGROUND: In the past decades, climate change has been impacting human lives and health via extreme weather and climate events and alterations in labour capacity, food security, and the prevalence and geographical distribution of infectious diseases across the globe. Climate change and health indicators (CCHIs) are workable tools designed to capture the complex set of interdependent interactions through which climate change is affecting human health. Since 2015, a novel sub-set of CCHIs, focusing on climate change impacts, exposures, and vulnerability indicators (CCIEVIs) has been developed, refined, and integrated by Working Group 1 of the "Lancet Countdown: Tracking Progress on Health and Climate Change", an international collaboration across disciplines that include climate, geography, epidemiology, occupation health, and economics. DISCUSSION: This research in practice article is a reflective narrative documenting how we have developed CCIEVIs as a discrete set of quantifiable indicators that are updated annually to provide the most recent picture of climate change's impacts on human health. In our experience, the main challenge was to define globally relevant indicators that also have local relevance and as such can support decision making across multiple spatial scales. We found a hazard, exposure, and vulnerability framework to be effective in this regard. We here describe how we used such a framework to define CCIEVIs based on both data availability and the indicators' relevance to climate change and human health. We also report on how CCIEVIs have been improved and added to, detailing the underlying data and methods, and in doing so provide the defining quality criteria for Lancet Countdown CCIEVIs. CONCLUSIONS: Our experience shows that CCIEVIs can effectively contribute to a world-wide monitoring system that aims to track, communicate, and harness evidence on climate-induced health impacts towards effective intervention strategies. An ongoing challenge is how to improve CCIEVIs so that the description of the linkages between climate change and human health can become more and more comprehensive.

Evaluation of the ERA5 reanalysis-based Universal Thermal Climate Index on mortality data in Europe.

Air temperature has been the most commonly used exposure metric in assessing relationships between thermal stress and mortality. Lack of the high-quality meteorological station data necessary to adequately characterize the thermal environment has been one of the main limitations for the use of more complex thermal indices. Global climate reanalyses may provide an ideal platform to overcome this limitation and define complex heat and cold stress conditions anywhere in the world. In this study, we explored the potential of the Universal Thermal Climate Index (UTCI) based on ERA5 - the latest global climate reanalysis from the European Centre for Medium-Range Weather Forecasts (ECMWF) - as a health-related tool. Employing a novel ERA5-based thermal comfort dataset ERA5-HEAT, we investigated the relationships between the UTCI and daily mortality data in 21 cities across 9 European countries. We used distributed lag nonlinear models to assess exposure-response relationships between mortality and thermal conditions in individual cities. We then employed meta-regression models to pool the results for each city into four groups according to climate zone. To evaluate the performance of ERA5-based UTCI, we compared its effects on mortality with those for the station-based UTCI data. In order to assess the additional effect of the UTCI, the performance of ERA5-and station-based air temperature (T) was evaluated. Whilst generally similar heat- and cold-effects were observed for the ERA5-and station-based data in most locations, the important role of wind in the UTCI appeared in the results. The largest difference between any two datasets was found in the Southern European group of cities, where the relative risk of mortality at the 1st percentile of daily mean temperature distribution (1.29 and 1.30 according to the ERA5 vs station data, respectively) considerably exceeded the one for the daily mean UTCI (1.19 vs 1.22). These differences were mainly due to the effect of wind in the cold tail of the UTCI distribution. The comparison of exposure-response relationships between ERA5-and station-based data shows that ERA5-based UTCI may be a useful tool for definition of life-threatening thermal conditions in locations where high-quality station data are not available.

Mean radiant temperature from global-scale numerical weather prediction models.

In human biometeorology, the estimation of mean radiant temperature (MRT) is generally considered challenging. This work presents a general framework to compute the MRT at the global scale for a human subject placed in an outdoor environment and irradiated by solar and thermal radiation both directly and diffusely. The proposed framework requires as input radiation fluxes computed by numerical weather prediction (NWP) models and generates as output gridded globe-wide maps of MRT. It also considers changes in the Sun's position affecting radiation components when these are stored by NWP models as an accumulated-over-time quantity. The applicability of the framework was demonstrated using NWP reanalysis radiation data from the European Centre for Medium-Range Weather Forecasts. Mapped distributions of MRT were correspondingly computed at the global scale. Comparison against measurements from radiation monitoring stations showed a good agreement with NWP-based MRT (coefficient of determination greater than 0.88; average bias equal to 0.42 °C) suggesting its potential as a proxy for observations in application studies.

Assessing heat-related health risk in Europe via the Universal Thermal Climate Index (UTCI).

In this work, the potential of the Universal Thermal Climate Index (UTCI) as a heat-related health risk indicator in Europe is demonstrated. The UTCI is a bioclimate index that uses a multi-node human heat balance model to represent the heat stress induced by meteorological conditions to the human body. Using 38 years of meteorological reanalysis data, UTCI maps were computed to assess the thermal bioclimate of Europe for the summer season. Patterns of heat stress conditions and non-thermal stress regions are identified across Europe. An increase in heat stress up to 1 °C is observed during recent decades. Correlation with mortality data from 17 European countries revealed that the relationship between the UTCI and death counts depends on the bioclimate of the country, and death counts increase in conditions of moderate and strong stress, i.e., when UTCI is above 26 and 32 °C. The UTCI's ability to represent mortality patterns is demonstrated for the 2003 European heatwave. These findings confirm the importance of UTCI as a bioclimatic index that is able to both capture the thermal bioclimatic variability of Europe, and relate such variability with the effects it has on human health.

Quantitative Spatiotemporal Chemical Profiling of Individual Lipid Droplets by Hyperspectral CARS Microscopy in Living Human Adipose-Derived Stem Cells.

There is increasing evidence showing that cytosolic lipid droplets, present in all eukaryotic cells, play a key role in many cellular functions. Yet their composition at the individual droplet level and how it evolves over time in living cells is essentially unknown due to the lack of suitable quantitative nondestructive measurement techniques. In this work, we demonstrate the ability of label-free hyperspectral coherent anti-Stokes Raman scattering (CARS) microscopy, together with a quantitative image analysis algorithm developed by us, to quantify the lipid type and content in vol/vol concentration units of individual lipid droplets in living human adipose-derived stem cells during differentiation over 9 days in media supplemented with different fatty acids. Specifically, we investigated the addition of the polyunsaturated linoleic and alpha-linolenic fatty acids into the normal differentiation medium (mostly containing monounsaturated fatty acids). We observe a heterogeneous uptake which is droplet-size dependent, time dependent, and lipid dependent. Cells grown in linoleic-acid-supplemented medium show the largest distribution of lipid content across different droplets at all times during differentiation. When analyzing the average lipid content, we find that adding linoleic or alpha-linolenic fatty acids at day 0 results in uptake of the new lipid components with an exponential time constant of 22 ± 2 h. Conversely, switching lipids at day 3 results in an exponential time constant of 60 ± 5 h. These are unprecedented findings, exemplifying that the quantitative imaging method demonstrated here could open a radically new way of studying and understanding cytosolic lipid droplets in living cells.

Performance Assessment in Fingerprinting and Multi Component Quantitative NMR Analyses.

An interlaboratory comparison (ILC) was organized with the aim to set up quality control indicators suitable for multicomponent quantitative analysis by nuclear magnetic resonance (NMR) spectroscopy. A total of 36 NMR data sets (corresponding to 1260 NMR spectra) were produced by 30 participants using 34 NMR spectrometers. The calibration line method was chosen for the quantification of a five-component model mixture. Results show that quantitative NMR is a robust quantification tool and that 26 out of 36 data sets resulted in statistically equivalent calibration lines for all considered NMR signals. The performance of each laboratory was assessed by means of a new performance index (named Qp-score) which is related to the difference between the experimental and the consensus values of the slope of the calibration lines. Laboratories endowed with a Qp-score falling within the suitable acceptability range are qualified to produce NMR spectra that can be considered statistically equivalent in terms of relative intensities of the signals. In addition, the specific response of nuclei to the experimental excitation/relaxation conditions was addressed by means of the parameter named NR. NR is related to the difference between the theoretical and the consensus slopes of the calibration lines and is specific for each signal produced by a well-defined set of acquisition parameters.

Heat stress in the Caribbean: Climatology, drivers, and trends of human biometeorology indices.

Forty years (1980-2019) of reanalysis data were used to investigate climatology and trends of heat stress in the Caribbean region. Represented via the Universal Thermal Climate Index (UTCI), a multivariate thermophysiological-relevant parameter, the highest heat stress is found to be most frequent and geographically widespread during the rainy season (August, September, and October). UTCI trends indicate an increase of more than 0.2°C·decade-1, with southern Florida and the Lesser Antilles witnessing the greatest upward rates (0.45°C·decade-1). Correlations with climate variables known to induce heat stress reveal that the increase in heat stress is driven by increases in air temperature and radiation, and decreases in wind speed. Conditions of heat danger, as depicted by the heat index (HI), have intensified since 1980 (+1.2°C) and are found to occur simultaneously to conditions of heat stress suggesting a synergy between heat illnesses and physiological responses to heat. This work also includes the analysis of the record-breaking 2020 heat season during which the UTCI and HI achieved above average values, indicating that local populations most likely experienced heat stress and danger higher than the ones they are used to. These findings confirm the gradual intensification of heat stress in the Caribbean and aim to provide a guidance for heat-related policies in the region.

Low-Field Benchtop NMR to Discover Early-Onset Sepsis: A Proof of Concept.

Low-field (LF) benchtop NMR is a new family of instruments available on the market, promising for fast metabolic fingerprinting and targeted quantification of specific metabolites despite a lack of sensitivity and resolution with respect to high-field (HF) instruments. In the present study, we evaluated the possibility to use the urinary metabolic fingerprint generated using a benchtop LF NMR instrument for an early detection of sepsis in preterm newborns, considering a cohort of neonates previously investigated by untargeted metabolomics based on Mass Spectrometry (MS). The classifier obtained behaved similarly to that based on MS, even if different classes of metabolites were taken into account. Indeed, investigating the regions of interest mainly related to the development of sepsis by a HF NMR instrument, we discovered a set of relevant metabolites associated to sepsis. The set included metabolites that were not detected by MS, but that were reported as relevant in other published studies. Moreover, a strong correlation between LF and HF NMR spectra was observed. The high reproducibility of the NMR spectra, the interpretability of the fingerprint in terms of metabolites and the ease of use make LF benchtop NMR instruments promising in discovering early-onset sepsis.

Wet Bulb Globe Temperature: Indicating Extreme Heat Risk on a Global Grid.

The Wet Bulb Globe Temperature (WBGT) is an international standard heat index used by the health, industrial, sports, and climate sectors to assess thermal comfort during heat extremes. Observations of its components, the globe and the wet bulb temperature (WBT), are however sparse. Therefore WBGT is difficult to derive, making it common to rely on approximations, such as the ones developed by Liljegren et al. (2008, https://doi.org/10.1080/15459620802310770, W B G T L i l j e g r e n ) and by the American College of Sports Medicine ( W B G T A C S M 87 ). In this study, a global data set is created by implementing an updated WBGT method using ECMWF ERA5 gridded meteorological variables and is evaluated against existing WBGT methods. The new method, W B G T B r i m i c o m b e , uses globe temperature calculated using mean radiant temperature and is found to be accurate in comparison to W B G T L i l j e g r e n across three heatwave case studies. In addition, it is found that W B G T A C S M 87 is not an adequate approximation of WBGT. Our new method is a candidate for a global forecasting early warning system.

Urine metabolic signature of pancreatic ductal adenocarcinoma by (1)h nuclear magnetic resonance: identification, mapping, and evolution.

Pancreatic ductal adenocarcinoma (PDAC) has a dismal prognosis and is highly chemoresistant. Early detection is the only means to impact long-term survival, but screening methods are lacking. Given the complex and heterogeneous nature of pancreatic cancer, unbiased analytical methods such as metabolomics by nuclear magnetic resonance (NMR) spectroscopy show promise to identify disease-specific molecular fingerprints. NMR profiles constitute a fingerprint of the biofluid, reporting quantitatively on all detectable small biomolecules. NMR spectroscopy was applied to investigate the urine metabolome of PDAC patients (n = 33) and to detect altered metabolic profiles in comparison with healthy matched controls (n = 54). The spectral data were analyzed using multivariate statistical techniques. Statistically significant differences were found between urine metabolomic profiles of PDAC and control individuals (p < 10(-5)). Group discrimination was possible due to average concentration differences of several metabolite signals, pointing to a multimolecular signature of the disease. The robustness of the determined statistical model is confirmed by its predictive performance (sensitivity = 75.8%, specificity = 90.7%). Additionally, the method allowed for a neat separation between spectral profiles of individuals with intermediate and advanced pathologic staging, as well as for the discrimination of samples based on tumor localization. NMR spectroscopy analysis of urinary metabolic profiles proved successful in identifying a complex molecular signature of PDAC. Furthermore, results of a descriptive-level analysis show the possibility to follow disease evolution and to carry out tumor site mapping. Given the high reproducibility and the noninvasive nature of the analytical procedure, the described method bears potential to impact large-scale screening programs.

Feasibility of climate reanalysis data as a proxy for onsite weather measurements in outdoor thermal comfort surveys.

Outdoor thermal comfort (OTC) surveys require synchronous monitoring of meteorological variables for direct comparisons against subjective thermal perception. The Universal Thermal Climate Index (UTCI) is a feasible index as it integrates meteorological conditions as a single value irrespective of urban morphological attributes or biological sex, age and body mass. ERA5-HEAT (Human thErmAl comforT) is a downloadable reanalysis dataset providing hourly grids of UTCI climate records at 0.25° × 0.25° spatial resolution from 1979 to present. We here evaluate for the first time whether it is possible to use ERA5-HEAT data as a proxy for the UTCI measured onsite during OTC surveys. A dataset comprising 1640 survey responses gathered over 14 OTC campaigns in Curitiba, Brazil (25°26'S, 49°16'W) was analysed. We assessed the bias obtained between the Dynamic Thermal Sensation, an index derived from the UTCI, and the thermal sensation reported by survey participants by considering locally measured meteorological variables and ERA5-HEAT reanalysis data. As ERA5-HEAT data are given on an hourly basis, prediction bias can be greatly reduced when accounting for survey responses close to the hour. In terms of seasons, the fall and winter seasons have diminished mean bias, though with larger spread than in summer. In terms of UTCI stress categories, prediction bias is lower for the thermal comfort range. When comparing reanalysis data against WMO station data as proxy candidates for survey field data, the former presented lower bias, less spread in terms of standard deviation and higher correlation to in situ data.

Metabolomics of B to plasma cell differentiation.

When small B lymphocytes bind antigen in the context of suitable signals, a profound geno-proteomic metamorphosis is activated that generates antibody-secreting cells. To study the metabolic changes associated with this differentiation program, we compared the exometabolome of differentiating murine B lymphoma cells and primary B cells by monodimensional proton nuclear magnetic resonance spectroscopy and mass spectrometry coupled to liquid chromatography. Principal component analysis, a multivariate statistical analysis, highlighted metabolic hallmarks of the sequential differentiation phases discriminating between the proliferation and antibody secreting phases and revealing novel metabolic pathways. During proliferation, lactate production increased together with consumption of essential amino acids; massive Ig secretion was paralleled by alanine and glutamate production, glutamine being used as carbon and energy sources. Notably, ethanol and 5'-methylthioadenosine were produced during the last phase of protein secretion and the proliferative burst, respectively. Our metabolomics results are in agreement with previous genoproteomics studies. Thus, metabolic profiling of extracellular medium is a useful tool to characterize the functional state of differentiating B cells and to identify novel underlying metabolic pathways.

Heatwaves, droughts, and fires: Exploring compound and cascading dry hazards at the pan-European scale.

Compound and cascading natural hazards usually cause more severe impacts than any of the single hazard events alone. Despite the significant impacts of compound hazards, many studies have only focused on single hazards. The aim of this paper is to investigate spatio-temporal patterns of compound and cascading hazards using historical data for dry hazards, namely heatwaves, droughts, and fires across Europe. We streamlined a simple methodology to explore the occurrence of such events on a daily basis. Droughts in soil moisture were analyzed using time series of a threshold-based index, obtained from the LISFLOOD hydrological model forced with observations. Heatwave and fire events were analyzed using the ERA5-based temperature and Fire Weather Index datasets. The data used in this study relates to the summer seasons from 1990 to 2018. Our results show that joint dry hazard occurrences were identified in west, central, and east Europe, and with a lower frequency in southern Europe and eastern Scandinavia. Drought plays a substantial role in the occurrence of the compound and cascading events of dry hazards, especially in southern Europe as it drives duration of cascading events. Moreover, drought is the most frequent hazard-precursor in cascading events, followed by compound drought-fire events. Changing the definition of a cascading dry hazard by increasing the number of days without a hazard from 1 to 21 within the event (inter-event criterion), lowers as expected, the maximum number of cascading events from 94 to 42, and extends the maximum average duration of cascading events from 38 to 86 days. We had to use proxy observed data to determine the three selected dry hazards because long time series of reported dry hazards do not exist. A complete and specific database with reported hazards is a prerequisite to obtain a more comprehensive insight into compound and cascading dry hazards.

A community-built calibration system: The case study of quantification of metabolites in grape juice by qNMR spectroscopy.

Nuclear Magnetic Resonance (NMR) is an analytical technique extensively used in almost every chemical laboratory for structural identification. This technique provides statistically equivalent signals in spite of using spectrometer with different hardware features and is successfully used for the traceability and quantification of analytes in food samples. Nevertheless, to date only a few internationally agreed guidelines have been reported on the use of NMR for quantitative analysis. The main goal of the present study is to provide a methodological pipeline to assess the reproducibility of NMR data produced for a given matrix by spectrometers from different manufacturers, with different magnetic field strengths, age and hardware configurations. The results have been analyzed through a sequence of chemometric tests to generate a community-built calibration system which was used to verify the performance of the spectrometers and the reproducibility of the predicted sample concentrations.