Large Discrepancies Research Articles

Evaluating Chemical Transport and Machine Learning Models for Wildfire Smoke PM2.5: Implications for Assessment of Health Impacts.

Growing wildfire smoke represents a substantial threat to air quality and human health. However, the impact of wildfire smoke on human health remains imprecisely understood due to uncertainties in both the measurement of exposure of population to wildfire smoke and dose-response functions linking exposure to health. Here, we compare daily wildfire smoke-related surface fine particulate matter (PM2.5) concentrations estimated using three approaches, including two chemical transport models (CTMs): GEOS-Chem and the Community Multiscale Air Quality (CMAQ) and one machine learning (ML) model over the contiguous US in 2020, a historically active fire year. In the western US, compared against surface PM2.5 measurements from the US Environmental Protection Agency (EPA) and PurpleAir sensors, we find that CTMs overestimate PM2.5 concentrations during extreme smoke episodes by up to 3-5 fold, while ML estimates are largely consistent with surface measurements. However, in the eastern US, where smoke levels were much lower in 2020, CTMs show modestly better agreement with surface measurements. We develop a calibration framework that integrates CTM- and ML-based approaches to yield estimates of smoke PM2.5 concentrations that outperform individual approach. When combining the estimated smoke PM2.5 concentrations with county-level mortality rates, we find consistent effects of low-level smoke on mortality but large discrepancies in effects of high-level smoke exposure across different methods. Our research highlights the differences across estimation methods for understanding the health impacts of wildfire smoke and demonstrates the importance of bench-marking estimates with available surface measurements.

Spectrophotometric and calculative determination methods of textile color-difference threshold considering the observing condition

Purpose This study aims to investigate the varying color-difference thresholds for textiles under various illuminants. Design/methodology/approach To determine color-difference thresholds, 108 fabric samples with widely ranging colors were spectrophotometrically measured and visually assessed under four illumination conditions (correlated color temperatures of 2,856 K and 6,504 K; illuminances of 100 lx and 2,000 lx). Findings The mean spectrophotometric color-difference threshold (solely based on the textile’s physical color attributes in machine vision) was 4.22 ΔE*ab; thus, a mechanically measured color difference between two textiles (regardless of illuminant) of less than 4.22 ΔE*ab indicated individuals’ inability to differentiate between two textiles. The calculated color-difference thresholds, which reflected the color differences perceived by people considering textiles’ physical color attributes and the environmental factors in which they were observed, were higher than the spectrophotometric thresholds. This meant that under various illuminants, people had greater difficulty perceiving color differences than mechanically measured spectrophotometric thresholds. Particularly, larger discrepancies between the two threshold types occurred under reddish illuminants of 2,856 K than under bluish-white illuminants of 6,504 K. Furthermore, the extent to which people perceived color differences as distinct from actual differences under illumination was larger for greenish-blue textiles than for textiles of other hues. Originality/value The determined spectrophotometric and calculative color-difference thresholds for textiles can help fashion companies predict consumers’ perceptions of the colors of their textile products under various illuminants and, accordingly, appropriately plan colors of products and create standards for color quality control.

AED-PADA:Improving Generalizability of Adversarial Example Detection via Principal Adversarial Domain Adaptation

Adversarial example detection, which can be conveniently applied in many scenarios, is important in the area of adversarial defense. Unfortunately, existing detection methods suffer from poor generalization performance, because their training process usually relies on the examples generated from a single known adversarial attack and there exists a large discrepancy between the training and unseen testing adversarial examples. To address this issue, we propose a novel method, named Adversarial Example Detection via Principal Adversarial Domain Adaptation (AED-PADA). Specifically, our approach identifies the Principal Adversarial Domains (PADs), i.e., a combination of features of the adversarial examples generated by different attacks, which possesses a large portion of the entire adversarial feature space. Subsequently, we pioneer to exploit Multi-source Unsupervised Domain Adaptation in adversarial example detection, with PADs as the source domains. Experimental results demonstrate the superior generalization ability of our proposed AED-PADA. Note that this superiority is particularly achieved in challenging scenarios characterized by employing the minimal magnitude constraint for the perturbations.

Reconstruction of Historical Site-Scale Dust Optical Depth (DOD) Time Series from Surface Dust Records and Satellite Retrievals in Northern China: Application to the Evaluation of DOD in CMIP6 Historical Simulations

Abstract The biases generated by state-of-the-art climate models in simulating dust optical depth (DOD) remain to be detailed. Here, a site-scale DOD dataset in March–August over northern China (NC) during 1980–2001 was reconstructed using the empirical relationship between MODIS-retrieved DOD and dust-event frequencies during 2001–21. Then, through the combined use of MODIS-based and reconstructed DOD, we evaluated the reproducibility of DOD from 10 models participating in phase 6 of the Coupled Model Intercomparison Project (CMIP6) for the historical period (1980–2001 and 2002–14) and under different Shared Socioeconomic Pathways (SSPs) during 2015–21. The results demonstrate that CMIP6 models and multimodel ensemble mean (MEM) are capable of capturing the spatial pattern of DOD, but with considerable uncertainty and intermodel variability in magnitude. Regionally averaged DOD is underestimated by 56.09% during 1980–2001 and overestimated by 30.97% during 2002–14 in MEM over NC. Simultaneously, the intermodel standard deviations are greater than MEM during 2002–14, suggesting large discrepancies among individual models. Very few models accurately capture the trends in DOD, which can mainly be attributed to the different trends in simulated wind speed (WS), soil moisture, and vegetation cover, and their contributions to dust evolution. Under four SSPs, despite the best correlation between SSP1-2.6-modeled and MODIS DOD over Gobi Desert (GD), overestimation of DOD is still observed. More models under SSP1-2.6 capture the positive DOD trend, mainly attributable to positive changes in simulated WS over GD.

Validation of ERA5-Land-based reconstructed air temperature and near-surface ground temperature on James Ross Island

ABSTRACT This study evaluates the accuracy of ERA5-Land reanalysis products by comparing them with continuous data from James Ross Island, Antarctic Peninsula. ERA5-Land shows lower variability in air and ground temperatures than measurements from three automatic weather stations (AWSs) on James Ross Island: Johann Gregor Mendel (AWS-JGM), Abernethy Flats (AWS-AF), and Johnson Mesa (AWS-JM). Differences in mean annual air temperature (MAAT) and mean annual ground temperature at 5 cm depth (MAGT5) are noted between ERA5-Land and AWSs for the periods 2007/08-2020/21 and 2011/12-2020/21. Strong correlations (0.88–0.92) exist between ERA5-Land and AWSs, with the highest coefficients and lowest RMSE values for AWS-JM (2.7 °C for AT and 4.9 °C for GT5). Validation statistics reveal seasonal variations in ERA5-Land temperature bias with larger discrepancies in summer and low differences in winter. ERA5-Land’s snow depth estimation indicates unrealistic permanent snow cover between 3–24 meters, affecting ground temperature bias and underestimation. Despite its benefits, ERA5-Land’s inaccuracies in ground temperature data limit its direct use for permafrost research. Corrections were applied to enhance the use of ERA5-Land data for detailed permafrost studies in the JRI area.

Parental vaccine hesitancy toward routine childhood immunizations and COVID-19 vaccines in Japan: A cross-sectional study

BackgroundThis study aimed to elucidate the prevalence and characteristics of parental vaccine hesitancy towards routine infant immunizations and COVID-19 vaccines in Japan.MethodsA web-based survey was conducted among 3,227 parents of children aged 0–11 years to assess vaccine-related hesitancy for routine infant immunizations and COVID-19 vaccines for children using the Parent Attitudes about Childhood Vaccines (PACV) questionnaire. Data were collected from January 18 to 25, 2023. Covariates included demographic characteristics, economic status, COVID-19 infection status, decisional conflict scale, and the fear of COVID-19 Scale.ResultsVaccine hesitancy was found to be 52.4% for routine infant immunizations and 73% for COVID-19 vaccines. Significant differences in parental attitudes were observed between general childhood vaccines and COVID-19 vaccines for 12 out of 13 PACV survey items. The COVID-19 vaccines showed higher hesitancy rates in 10 items; largest discrepancies were noticed in schedule adherence (22.5% vs 61%), overall hesitancy (40% vs 55.1%), and trust in pediatric doctors (37.2% vs 53.6%). Safety concerns were high for both vaccine types, exceeding 50%. Multivariable analysis identified decisional conflict (RR: 1.01 95% CI: 1.00–1.02) and COVID-19-related fear (RR: 1.04, 95% CI: 1.02–1.05) as hesitancy predictors for routine immunizations.ConclusionVaccine-related hesitancy for COVID-19 was significantly higher than that for routine immunizations, with decisional conflict emerging as a primary predictor for both. Fear of COVID-19 was associated with routine immunization-related hesitancy. These findings provide critical insights for future pandemic preparedness and vaccine acceptance strategies, highlighting the importance of strengthening trust between healthcare providers and parents, providing clear and reliable information, and implementing decision support tools.

A universal scaling for the length scales of shock-induced separation

Experiments of transitional shock wave–boundary layer interactions (SBLIs) over 6 $^\circ$ and 10 $^\circ$ compression ramps were performed at Mach number 1.65. The unit Reynolds number was varied by a factor of two between 5.6 million per metre and 11 million per metre. Schlieren flow visualization was performed, and mean flow measurements were made using Pitot probes. Free interaction theory was verified from pressure measurements for all operating conditions. A new non-dimensional parameter was developed for scaling the strength of the imposed shock, which was based on the pressure required to separate a boundary layer. The validity of this new scaling was supported by the reconciliation of large discrepancies in a diverse collection of experimental results on the length scales of transitional interactions. This non-dimensional scaling was also applied to turbulent interactions, where different models were used to determine the pressure required to separate a turbulent boundary layer. Finally, a direct comparison between transitional and turbulent SBLIs was made, which revealed new insights into the evolution of length scales based on the state of the boundary layer.

Evaluation of chemical kinetic models for simulations of hydrogen detonations by comparison with experimental data

Two-dimensional numerical simulations of a weakly unstable detonation mixture 2H2+O2+3.76Ar at 20kPa and 295K were performed using our validated OpenFOAM solver based on reacting-PimpleCentralFoam. This study compared the detonation dynamics obtained with four chemical models, namely Hong 2011, Burke 2012, Mével 2014, and FFCM-2 with recently obtained experimental results. The experimental–numerical comparisons were performed in threefold: (i) quantitative comparisons of the cell sizes (λ) and their distributions (2σ/λ); (ii) qualitative comparisons of the detonation structure based on simultaneous planar laser-induced fluorescence of both nitric oxide (NO-PLIF) and OH radical (OH-PLIF); (iii) qualitative and quantitative comparisons of the detonation dynamics based on combined Rayleigh scattering and NO-PLIF measurements. The simulations conducted with Hong 2011’s, Burke 2012’s, and FFCM-2’s models satisfactorily reproduced the average cell size (within 10%), while it was 1.5 times smaller with Mével 2014’s model. The opposite trends were observed in cell size distributions (2σ/λ) with satisfactory predictions from Mével 2014’s model (within 25%) and almost no cell size variations (2σ/λ<0.1) for the other models. By comparing the simultaneous NO- and OH-PLIF imaging, the simulations conducted with FFCM-2’s and Mével 2014’s models qualitatively reproduced the reaction zone structure, while more discrepancies were obtained with Hong 2011’s and Burke 2012’s models. Quantitatively, simulations conducted with FFCM-2’s and Mével 2014’s models presented the lowest discrepancy (below two-fold) at reproducing the induction zone dynamics along the cellular cycle, while large discrepancies (approximately three-fold) were observed with Hong 2011’s and Burke 2012’s models. Chemical timescale analyses evidenced the relation between the faster reaction timescales of Mével 2014’s model and the ability to reproduce the experimental variability on both λ and Δi. These detailed comparisons emphasized the importance of the chemical model selection and the need for combined experimental measurements to both validate chemical models and achieve predictive detonation simulations.

Experimental study on the interfacial bond behavior of UHPC filled circular stainless steel tubes

As the interfacial bond property is of great significance to derive the composite action between stainless steel tube and UHPC for the Ultra-High Performance Concrete Filled Stainless Steel Tubular (UHPCFSST) columns, the push-out tests were conducted in this program, which includes 8 specimens having different stainless steel tube diameter and tube thickness. Based on the test results, the damage patterns and the full range load-slip curves are analyzed in detail, and the interfacial bond stress constitutes at different loading stages were also identified and evaluated. On top of that, the longitudinal strain of the stainless steel tube was analyzed based on elastic theory to derive the non-dimensional bond stress distribution law along the steel-concrete interface. The comparison between test results and the predictions from current code specification or the available empirical formulas indicate a large discrepancy and inconsistency. Therefore, the bond strength and corresponding slippage value of UHPCFSST columns were predicted by a new equation based on regression analysis. The research discovery obtained from this study provides theoretical significance and practical value for improving the design theory and application of UHPCFSST columns in practical engineering.

Boosting Alkaline Hydrogen Oxidation Kinetics through Interfacial Environments Induced Surface Migration of Adsorbed Hydroxyl

AbstractConstructing bifunctional sites through heterojunction engineering to accelerate water formation has become a pivotal strategy to improve the alkaline hydrogen oxidation reaction (HOR) kinetics, which is mainly focused on the synergistic effect of neighboring sites and the energetics of the surface reaction steps. However, the roles of the surface migration of key intermediates that go beyond the bifunctional mechanism limited to neighboring atoms have usually been ignored. Using the heterostructured Ni3C−Ni catalyst as a model, we found that the rapid surface migration of OHad species from the positively charged Ni3C to the negatively charged Ni component played a decisive role in facilitating water formation. Such unprecedented surface migration of OHad is induced by the large discrepancy between the local surface charge densities and interfacial environments of the Ni3C and Ni components under operating conditions. Benefiting from this, the resultant Ni3C−Ni exhibited outstanding mass activity for the alkaline HOR, which was approximately 19‐fold and 21‐fold higher than those of Ni and Ni3C, respectively. These findings not only provide novel insights into the alkaline HOR mechanism of heterostructured catalysts but also open new avenues for developing advanced electrocatalysts for alkaline fuel cells.

Boosting Alkaline Hydrogen Oxidation Kinetics through Interfacial Environments Induced Surface Migration of Adsorbed Hydroxyl.

Constructing bifunctional sites through heterojunction engineering to accelerate water formation has become a pivotal strategy to improve the alkaline hydrogen oxidation reaction (HOR) kinetics, which is mainly focused on the synergistic effect of neighboring sites and the energetics of the surface reaction steps. However, the roles of the surface migration of key intermediates that go beyond the bifunctional mechanism limited to neighboring atoms have usually been ignored. Using the heterostructured Ni3C-Ni catalyst as a model, we found that the rapid surface migration of OHad species from the positively charged Ni3C to the negatively charged Ni component played a decisive role in facilitating water formation. Such unprecedented surface migration of OHad is induced by the large discrepancy between the local surface charge densities and interfacial environments of the Ni3C and Ni components under operating conditions. Benefiting from this, the resultant Ni3C-Ni exhibited outstanding mass activity for the alkaline HOR, which was approximately 19-fold and 21-fold higher than those of Ni and Ni3C, respectively. These findings not only provide novel insights into the alkaline HOR mechanism of heterostructured catalysts but also open new avenues for developing advanced electrocatalysts for alkaline fuel cells.

Development of age-specific population-based paediatric computational phantoms for image-based data mining and other radiotherapy applications

Objective.Computational anatomical models have many applications in paediatric radiotherapy. Age-specific computational anatomical models were historically developed to represent average and/or healthy individuals, where cancer patients may present with anatomical variations caused by the disease and/or treatment effects. We developed RT-PAL, a library of computational age-specific voxelized anatomical models tailored to represent the paediatric radiotherapy population.Approach.Data from patients undergoing craniospinal irradiation (CSI) were used (n = 74, median age 7.3y, range: 1-17y). The RT-PAL phantoms were generated using groupwise deformable image registration to spatially normalize and average a sub-set of twenty clinical CTs and contours (n = 74, median age 7.7y, range: 3-14 y). To assess their anatomical and age-dependency plausibility, the RT-PAL models were compared against clinical cancer patient data and two healthy population based libraries of phantoms: the International Commission on Radiological Protection (ICRP) pediatric reference computational phantoms (n = 8, median age 7.5y, range: 1-15y) and a range of 4D paediatric extended cardiac torso (XCAT) phantoms (n = 75, median age 9.1y, range: 1-18y). For each dataset, nineteen organs were segmented on all age models to determine their volume. Each set was evaluated through a linear fit of organ volume with age, where comparisons were made relative to the linear fit of the clinical data.Main Results.Overall good anatomical plausibility was found for the RT-PAL phantoms. The age-dependency reported was comparable to both the clinical data and other phantoms, demonstrating their efficacy as a library of age-specific phantoms. Larger discrepancies with the clinical, ICRP and XCAT organ data were attributable to differences in organ filling, segmentation strategy and age distribution of the datasets, limitations of RT-PAL generation methodology, and/or possible anatomical differences between healthy and cancer populations.Significance.The RT-PAL models showed potential in representing the paediatric radiotherapy cohort, who are most likely to benefit from dedicated, age-specific anatomical phantoms.

Heterogeneous marine environments diversify microbial-driven polymetallic nodule formation in the South China Sea

Most studies on the genesis of polymetallic nodules suggested that nodules in the South China Sea (SCS) are hydrogenetic; however, the complexity and the heterogeneity in hydrology and geochemistry of the SCS might cause different processes of nodule formation, impacting their application and economic value. Microbial-mediated ferromanganese deposition is an important process in nodule formation, but the related microbial potentials are still unclear in the SCS. In this study, we sampled in three typical regions (A, B, and C) of the SCS enriched with polymetallic nodules. Firstly, we investigated environmental and microbial characteristics of the water columns to determine the heterogeneity of upper seawater that directly influenced deep-sea environments. Then, microbial compositions and structures in sediment cores, overlying waters, and nodules (inside and outside) collected within the same region were analyzed for inferring features of nodule environments. Microbial interactions between nodules and surrounding environments were estimated with collinear network analysis. The microbial evidence indicated that geochemical characteristics in deep sea of the SCS that were key to the polymetallic nodule formation were severely affected by organic matter flux from upper water column. The sediment in region A was sub-oxic due to the large input of terrigenous and phytoplankton-derived organic matter, potentially enhancing the overflow of reduced metals from the porewater. The intense microbial interaction between nodules and surface sediment reinforced the origin of metals for the ferromanganese deposition from the sediment (diagenetic type). Contrarily, the sediments in regions B and C were relatively rich in oxygen, and metal ions could be majorly supplied from seawater (hydrogenetic type). The large discrepancy in microbial communities between nodule inside and remaining samples suggested that nodules experienced a long-term formation process, consistent with the feature of hydrogenetic nodules. Overall, distributions and interactions of microbial communities in nodules and surrounding environments significantly contributed to the nodule formation in the SCS by manipulating biogeochemical processes that eventually determined the source and the fate of metal ions.

Analysis of Serial Foot Radiographs to Determine Foot Height Multipliers.

The multiplier method is an arithmetic calculation that estimates the amount of growth remaining until skeletal maturity. When predicting lower limb length discrepancy, differences in foot height are added to femur and tibia discrepancies. Foot height multipliers have not been calculated using radiographic measurements, so it is unclear whether foot height develops at the same pace as the femur and tibia. This study used serial images to calculate foot height multipliers and compared them to published lower limb and foot length multipliers. The Bolton Brush radiograph collection was used to measure foot height on the lateral foot view. Multipliers were calculated for ages with at least 10 serial study visits. 212 patients (2195 radiographs) were included in the study (102 female, 110 male patients). Foot height multipliers were calculated for ages 0 to 17 years (females) and 0 to 18 years (males). Multipliers decreased with age, but qualitatively plateau at age 13 (females) and age 15 (males). Lower extremity multipliers have a more dramatic growth curve, indicating comparatively greater lower extremity growth after birth. However, when comparing the limb length discrepancy calculation using the lower extremity multiplier versus the foot height multiplier for the foot portion, the difference was negligible. This paper provides a database of foot height multipliers. Foot height seems to grow on a different trajectory than other lower limb components, confirming that one should consider separate multiplier values. The difference created by the foot height multiplier versus the lower extremity multiplier appears to be modest. Separate use of the foot height multiplier may only be necessary for young children with large foot height discrepancies, but further study to confirm the lack of impact of the foot height multiplier on limb length discrepancy calculations is needed. Our data were derived from normal children, so it is unknown if the presence of a talo-calcaneal coalition would affect foot height on the involved side. Level III-retrospective comparative study.

Influence of Finishing Process Parameters of HDF Boards on Selected Properties of Coatings in Modern UV Lines and Their Relation to Energy Consumption.

This study analyzes the influence of energy generated by emitters on the adhesive properties of varnish coatings in multilayer UV systems. The experimental material, in the form of a cell board finished with UV varnish products, was prepared on a prototype line under the conditions of Borne Furniture in Gorzów Wielkopolski. The roughness and wettability were measured using a OneAttension tensiometer integrated with a topographic module, taking into account the Wenzel coefficient. The adhesion of the examined systems was verified using the PositiTest AT-A automatic pull-off device. Energy consumption by the prototype production line was compared to the standard line, utilizing mercury emitters and mercury emitters with added gallium. Energy consumption was calculated for selected variants. The influence of the Wenzel coefficient on the wettability angle was observed. Significant differences between contact angles (CA and CAc) were noted for coatings formed with sealers (stages I and II). The largest discrepancies, reaching up to 30 degrees, were recorded at the lowest UVA and UVV doses of 26 mJ/cm2. In adhesion tests, values below 1 MPa were obtained. Insufficient energy doses in the curing process of UV systems led to delamination between the coatings. Five variants were selected where delamination within the substrate predominated (˃90% A) and were characterized by the lowest energy consumption in the processes. Topographic images helped identify the presence of various surface microstructures at different stages of the production cycle. The greatest energy savings, up to 50%, were achieved in stages III and IV of the technological process.

Multicolor luminescence and high efficient optical thermometric performance of Eu3+ and Sm3+ in self-activated Na2LuMg2V3O12 garnet

To develop efficient luminescence and optical thermometry materials for color display and non-contact temperature measurement, novel RE3+ (RE = Eu, Sm) doped self-activated Na2LuMg2V3O12 phosphors were prepared by a typical solid-state reaction method. Their crystal structure, morphology, multi-color luminescence and temperature sensing properties were elaborately investigated. Under UV light excitation, an intense and broad green-yellow emission band from VO43– group is observed in the Na2LuMg2V3O12 matrix, indicating its potential application in solid state lighting. After the incorporation of Eu3+ and Sm3+ ions, efficient energy transfer (ET) from VO43– group to Eu3+/Sm3+ ions occurs and the emission color of the samples can be readily tuned among different color ranges. Besides, based on the change of luminescence intensity and lifetimes of VO43– group in Na2LuMg2V3O12:Eu3+ and Na2LuMg2V3O12:Sm3+, the ET efficiency was analyzed and the mechanism is illustrated. Finally, large discrepancy between the thermal stability of VO43– group and Eu3+/Sm3+ ions are observed in the temperature-dependent emission spectra of Na2LuMg2V3O12:Eu3+ and Na2LuMg2V3O12:Sm3+. By taking advantage of the luminescence intensity ratio (LIR) between VO43– group and Eu3+/Sm3+ ions in Na2LuMg2V3O12:0.01Eu3+ and Na2LuMg2V3O12:0.07Sm3+, two new types of optical thermometry mediums were designed and their basic temperature sensing parameters were calculated.

Microanastomosis in large discrepancies: a novel training model

Microanastomosis in large discrepancies: a novel training model

Unveiling the origin of XMM-Newton soft proton flares

Context. Low-energy (&lt; 300 keV) protons entering the field of view of the XMM-Newton telescope scatter with the X-ray mirror surface and might reach the X-ray detectors on the focal plane. They manifest in the form of a sudden increase in the rates, usually referred to as soft proton flares. By knowing the conversion factor between the soft proton energy and the deposited charge on the detector, it is possible to derive the incoming flux and to study the environment of the Earth magnetosphere at different distances, given the wide and elliptical XMM-Newton orbit. Thanks to detailed Geant4 simulations, we were able to build specific soft proton response matrices for MOS and PN. Aims. In this second paper, we present the results of testing these matrices with real data for the first time, while also exploring the seasonal and solar activity effect on the proton environment. The selected spectra are relative to 55 simultaneous MOS and PN observations with flares raised in four different temporal windows: December-January and July-August of 2001-2002 (solar maximum) and 2019-2020 (solar minimum). Methods. We selected and extracted the flare mean spectra and count rates in the 2–11.5 keV energy range for the four epochs. After investigating the rate variations among the MOS1, MOS2, and PN instruments, we fit the X-ray spectra using XSPEC and the proton response matrices. The best-fitting parameters derived for the three instruments were compared in order to obtain the systematic errors. Results. There is no seasonal or solar activity effect on the soft proton mean count rates, but we find large discrepancies in the instrument cross-correlations across the 20 years of satellite operations. In 2001-2002, after a few years of operation, the MOS1 and MOS2 rates are similar, and about 20% with regard to the PN ones. After 20 years, PN does not present any variation in its response, while MOS1 suffers a reduction of ∼30%, in addition to the 30% loss due to the damage of two CCDs, and MOS2 is affected by an even worse degradation (70%). The main result of the spectral analysis is that the physical model representative of the proton spectra at the input of the telescope is a power law. However, a second and phenomenological component is necessary to take into account imprecision in the generation of the matrices at softer (&lt; 5 keV) energies. This component contributes for 21% for the MOS and 5% for the PN to the total flux in the 2–5 keV energy range. Conclusions. This study, which is the first application of the soft proton response matrices to real data, shows coherent results between detectors and allows us to estimate systematic uncertainties in the measured spectra of 3% between the two MOS detectors and of 24% between MOS and PN, together with a systematic in the input flux of about a factor of two. They are all likely due to uncertainties in the proton transmission models, with the presence of additional passive material in front of the front-illuminated MOS, and element deposition on its electrode structure across the mission life. Dedicated studies and laboratory measurements are required for improving the accuracy of the proton response files.

Deciphering Proteomic Expression in Inflammatory Disorders: A Mass Spectrometry Exploration Comparing Infectious, Noninfectious, and Traumatic Brain Injuries in Human Cerebrospinal Fluid.

The central nervous system (CNS) evokes a complex inflammatory response to injury. Inflammatory cascades are present in traumatic, infectious, and noninfectious disorders affecting the brain. It contains a mixture of pro- and anti-inflammatory reactions involving well-known proteins, but also numerous proteins less explored in these processes. The aim of this study was to explore the distinct inflammatory response in traumatic brain injury (TBI) compared with other CNS injuries by utilization of mass-spectrometry. In total, 56 patients had their cerebrospinal fluid (CSF) analyzed with the use of mass-spectrometry. Among these, CSF was collected via an external ventricular drain (EVD) from n = 21 patients with acute TBI. The resulting protein findings were then compared with CSF obtained by lumbar puncture from n = 14 patients with noninfectious CNS disorders comprising relapsing-remitting multiple sclerosis, anti-N-methyl-d-aspartate-receptor encephalitis, acute disseminated encephalomyelitis, and n = 14 patients with progressive multifocal leukoencephalopathy, herpes simplex encephalitis, and other types of viral meningitis. We also utilized n = 7 healthy controls (HCs). In the comparison between TBI and noninfectious inflammatory CNS disorders, concentrations of 55 proteins significantly differed between the groups. Among them, 23 and 32 proteins were up- and downregulated, respectively, in the TBI group. No proteins were uniquely identified in either group. In the comparison of TBI and HC, 51 proteins were significantly different, with 24 and 27 proteins being up- and downregulated, respectively, in TBI. Two proteins (fibrinogen gamma chain and transketolase) were uniquely identified in all samples of the TBI group. Also in the last comparison, TBI versus infectious inflammatory CNS disorders, 51 proteins differed between the two groups, with 19 and 32 proteins being up- and downregulated, respectively, in TBI, and no unique proteins being identified. Due to large discrepancies between the groups compared, the following proteins were selected for further deeper analysis among those being differentially regulated: APOE, CFB, CHGA, CHI3L1, C3, FCGBP, FGA, GSN, IGFBP7, LRG1, SERPINA3, SOD3, and TTR. We found distinct proteomic profiles in the CSF of TBI patients compared with HC and different disease controls, indicating a specific interplay between inflammatory factors, metabolic response, and cell integrity. In relation to primarily infectious or inflammatory disorders, unique inflammatory pathways seem to be engaged, and could potentially serve as future treatment targets.

Identification of new phenotypes in type 2 diabetes with acute myocardial infarction: toward a precision medicine?

Abstract Background Type 2 diabetes mellitus (T2DM) is a highly heterogeneous entity, with multiple subgroups differing by clinic presentation, disease progression and risk of complications such as myocardial infarction (MI). A new T2DM phenotyping classification has been recently proposed to help to improve treatment tailoring and target early treatments, and we aimed to identify the prevalence and characteristics of the new phenotypes. Methods All consecutive adults with a history T2DM hospitalized in a french Coronary Intensive Care Unit for an acute MI between February 1st, 2021 and January 31st, 2023 were included. Clusters were based on six variables (glutamate decarboxylase antibodies, age at diagnosis, BMI, HbA1c, and homoeostatic model assessment 2 estimates of β-cell function and insulin resistance). We stratified patients into five subgroups : 1/ SAID=severe autoimmune diabetes; 2/ SIDD=severe insulin-deficient diabetes; 3/ SIRD=severe insulin-resistant diabetes; 4/ MOD=mild obesity-related diabetes; and 5/ MARD=mild age-related diabetes. Results Among the 266 patients included, characteristics according to diabetes phenotypes are summarized in the Table. Conclusions Our prospective study showed that in real-world T2DM patients with acute MI, unclassical phenotypes, i.e. hyperinsulinaemic and insulinopaenic were common. Given the large discrepancies in characteristics, our findings suggest the relevance of the new substratification. However, its clinical utlity and translation in tailored treatment strategies and prognosis remains to be determined.Table.