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BACKGROUND:The authors previously reported that inhaled xenon combined with hypothermia attenuates brain white matter injury in comatose survivors of out-of-hospital cardiac arrest (OHCA). OBJECTIVES:A pre-defined secondary objective was to assess the effect of inhaled xenon on myocardial ischemic damage in the same study population. METHODS:A total of 110 comatose patients who had experienced OHCA from a cardiac cause were randomized to receive either inhaled xenon (40% end-tidal concentration) combined with hypothermia (33°C) for 24 h (n = 55; xenon group) or hypothermia treatment alone (n = 55; control group). Troponin-T levels were measured at hospital admission, and at 24 h, 48 h, and 72 h post-cardiac arrest. All available cases were analyzed for troponin-T release. RESULTS:Troponin-T measurements were available from 54 xenon patients and 54 control patients. The baseline characteristics did not differ significantly between the groups. After adjustments for age, sex, study site, primary coronary percutaneous intervention (PCI), and norepinephrine dose, the mean ± SD post-arrival incremental change of the ln-transformed troponin-T at 72 h was 0.79 ± 1.54 in the xenon group and 1.56 ± 1.38 in the control group (adjusted mean difference -0.66; 95% confidence interval: -1.16 to -0.16; p = 0.01). The effect of xenon on the change in the troponin-T values did not differ in patients with or without PCI or in those with a diagnosis of ST-segment elevation myocardial infarction (group by PCI or ST-segment elevation myocardial infarction interaction effect; p = 0.86 and p = 0.71, respectively). CONCLUSIONS:Among comatose survivors of OHCA, in comparison with hypothermia alone, inhaled xenon combined with hypothermia suggested a less severe myocardial injury as demonstrated by the significantly reduced release of troponin-T.

TEMPO was selected in 2012 by NASA as the first Earth Venture Instrument, for launch between 2018 and 2021. It will measure atmospheric pollution for greater North America from space using ultraviolet and visible spectroscopy. TEMPO observes from Mexico City, Cuba, and the Bahamas to the Canadian oil sands, and from the Atlantic to the Pacific, hourly and at high spatial resolution (~2.1 km N/S×4.4 km E/W at 36.5°N, 100°W). TEMPO provides a tropospheric measurement suite that includes the key elements of tropospheric air pollution chemistry, as well as contributing to carbon cycle knowledge. Measurements are made hourly from geostationary (GEO) orbit, to capture the high variability present in the diurnal cycle of emissions and chemistry that are unobservable from current low-Earth orbit (LEO) satellites that measure once per day. The small product spatial footprint resolves pollution sources at sub-urban scale. Together, this temporal and spatial resolution improves emission inventories, monitors population exposure, and enables effective emission-control strategies. TEMPO takes advantage of a commercial GEO host spacecraft to provide a modest cost mission that measures the spectra required to retrieve ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2), formaldehyde (H2CO), glyoxal (C2H2O2), bromine monoxide (BrO), IO (iodine monoxide),water vapor, aerosols, cloud parameters, ultraviolet radiation, and foliage properties. TEMPO thus measures the major elements, directly or by proxy, in the tropospheric O3 chemistry cycle. Multi-spectral observations provide sensitivity to O3 in the lowermost troposphere, substantially reducing uncertainty in air quality predictions. TEMPO quantifies and tracks the evolution of aerosol loading. It provides these near-real-time air quality products that will be made publicly available. TEMPO will launch at a prime time to be the North American component of the global geostationary constellation of pollution monitoring together with the European Sentinel-4 (S4) and Korean Geostationary Environment Monitoring Spectrometer (GEMS) instruments.

Abstract Background The objective was to build a novel method for automated image analysis to locate and quantify the number of cytokeratin 7 (K7)-positive hepatocytes reflecting cholestasis by applying deep learning neural networks (AI model) in a cohort of 210 liver specimens. We aimed to study the correlation between the AI model’s results and disease progression. The cohort of liver biopsies which served as a model of chronic cholestatic liver disease comprised of patients diagnosed with primary sclerosing cholangitis (PSC). Methods In a cohort of patients with PSC identified from the PSC registry of the University Hospital of Helsinki, their K7-stained liver biopsy specimens were scored by a pathologist (human K7 score) and then digitally analyzed for K7-positive hepatocytes (K7%area). The digital analysis was by a K7-AI model created in an Aiforia Technologies cloud platform. For validation, values were human K7 score, stage of disease (Metavir and Nakunuma fibrosis score), and plasma liver enzymes indicating clinical cholestasis, all subjected to correlation analysis. Results The K7-AI model results (K7%area) correlated with the human K7 score (0.896; p

Satellite-based aerosol retrievals provide a timely view of atmospheric aerosol properties, having a crucial role in the subsequent estimation of air quality indicators, atmospherically corrected satellite data products, and climate applications. However, current aerosol data products based on satellite data often have relatively large biases compared to accurate ground-based measurements and distinct uncertainty levels associated with them. These biases and uncertainties are often caused by oversimplified assumptions and approximations used in the retrieval algorithms due to unknown surface reflectance or fixed aerosol models. Moreover, the retrieval algorithms do not usually take advantage of all the possible observational data collected by the satellite instruments and may, for example, leave some spectral bands unused. The improvement and the re-processing of the past and current operational satellite data retrieval algorithms would become tedious and computationally expensive. To overcome this burden, we have developed a model-enforced post-process correction approach to correct the existing operational satellite aerosol data products. Our approach combines the existing satellite aerosol retrievals and a post-processing step carried out with a machine-learning-based correction model for the approximation error in the retrieval. The developed approach allows for the utilization of auxiliary data sources, such as meteorological information, or additional observations such as spectral bands unused by the original retrieval algorithm. The post-process correction model can learn to correct for the biases and uncertainties in the original retrieval algorithms. As the correction is carried out as a post-processing step, it allows for computationally efficient re-processing of existing satellite aerosol datasets without fully re-processing the much larger original radiance data. We demonstrate with over-land aerosol optical depth (AOD) and Ångström exponent (AE) data from the Moderate Imaging Spectroradiometer (MODIS) of the Aqua satellite that our approach can significantly improve the accuracy of the satellite aerosol data products and reduce the associated uncertainties. For instance, in our evaluation, the number of AOD samples within the MODIS Dark Target expected error envelope increased from 63 % to 85 % when the post-process correction was applied. In addition to method description and accuracy results, we also give recommendations for validating machine-learning-based satellite data products.

The new platforms for Earth observation from space are characterized by measurements made at great spatial and temporal resolutions. While this abundance of information makes it possible to detect and study localized phenomena, it may be difficult to manage this large amount of data for the study of global and large-scale phenomena. A particularly significant example is the use by assimilation systems of Level 2 products that represent gas profiles in the atmosphere. The models on which assimilation systems are based are discretized on spatial grids with horizontal dimensions of the order of tens of kilometres in which tens or hundreds of measurements may fall in the future. A simple procedure to overcome this problem is to extract a subset of the original measurements, but this involves a loss of information. Another option is the use of simple averages of the profiles, but this approach also has some limitations that we will discuss in the paper. A more advanced solution is to resort to the so-called fusion algorithms, capable of compressing the size of the dataset while limiting the information loss. A novel data fusion method, the Complete Data Fusion algorithm, was recently developed to merge a set of retrieved products in a single product a posteriori. In the present paper, we apply the Complete Data Fusion method to ozone profile measurements simulated in the thermal infrared and ultraviolet bands in a realistic scenario. Following this, the fused products are compared with the input profiles; comparisons show that the output products of data fusion have smaller total errors and higher information contents in general. The comparisons of the fused products with the fusing products are presented both at single fusion grid box scale and with a statistical analysis of the results obtained on large sets of fusion grid boxes of the same size. We also evaluate the grid box size impact, showing that the Complete Data Fusion method can be used with different grid box sizes even if this possibility is connected to the natural variability of the considered atmospheric molecule.

Adolescents with high-functioning Autism Spectrum Disorder (HFASD) experience difficulties with socio-emotional adjustment, including compromised friendships, feelings of loneliness, and depression. Using a sample of 127 adolescents with HFASD and their parents, this study is first to examine: (1) relations between organized activity (OA) involvement and adjustment and (2) whether these relations were moderated by social impairment and executive functions. Results indicated that greater intensity, breadth, and academic OA involvement were associated with fewer depressive symptoms. OA intensity was also associated with less loneliness. For adolescents with better emotional control, greater intensity was associated with better friendship quality. Results suggest that for adolescents with HFASD, more involvement in OA is associated with better socio-emotional adjustment even after accounting for risk factors.

The aim of this study is to assess the influence of living in nursing homes on COVID-19-related mortality, and to calculate the real specific mortality rate caused by COVID-19 among people older than 20 years of age in the Balaguer Primary Care Centre Health Area during the first wave of the pandemic. We conducted an observational study based on a database generated between March and May 2020, analysing COVID-19-related mortality as a dependent variable, and including different independent variables, such as living in a nursing home or in the community (outside nursing homes), age, sex, symptoms, pre-existing conditions, and hospital admission. To evaluate the associations between the independent variables and mortality, we calculated the absolute and relative frequencies, and performed a chi-square test. To avoid the impact of the age variable on mortality and to assess the influence of the “living in a nursing home” variable, we established comparisons between infected population groups over 69 years of age (in nursing homes and outside nursing homes). Living in a nursing home was associated with a higher incidence of COVID-19 infection, but not with higher mortality in patients over 69 years of age (p = 0.614). The real specific mortality rate caused by COVID-19 was 2.270/00. In the study of the entire sample, all the comorbidities studied were associated with higher mortality; however, the comorbidities were not associated with higher mortality in the infected nursing home patients group, nor in the infected community patients over 69 years of age group (except for neoplasm history in this last group). Finally, hospital admission was not associated with lower mortality in nursing home patients, nor in community patients over 69 years of age.

This study investigated the influence of photoperiod (day length) on the efficacy of grape seed proanthocyanidin extract (GSPE) in mitigating metabolic disorders in obese rats fed a cafeteria diet. Rats were exposed to standard (L12), long (L18), or short (L6) photoperiods and treated with GSPE or vehicle. In the standard photoperiod, GSPE reduced body weight gain (50.5%), total cholesterol (37%), and triglycerides (34.8%), while increasing the expression of hepatic metabolic genes. In the long photoperiod, GSPE tended to decrease body weight gain, increased testosterone levels (68.3%), decreased liver weight (12.4%), and decreased reverse serum amino acids. In the short photoperiod, GSPE reduced glycemia (~10%) and lowered triglyceride levels (38.5%), with effects modified by diet. The standard photoperiod showed the greatest efficacy against metabolic syndrome-associated diseases. The study showed how day length affects GSPE's benefits and underscores considering biological rhythms in metabolic disease therapies. [ABSTRACT FROM AUTHOR]

Purpose: Out-of-hospital cardiac arrest (OHCA) carries a relatively poor prognosis and requires multimodal prognostication to guide clinical decisions. Identification of previously unrecognized metabolic routes associated with patient outcome may contribute to future biomarker discovery. In OHCA, inhaled xenon elicits neuro- and cardioprotection. However, the metabolic effects remain unknown. Materials and methods: In this post-hoc study of the randomised, 2-group, single-blind, phase 2 Xe-Hypotheca trial, 110 OHCA survivors were randomised 1:1 to receive targeted temperature management (TTM) at 33°C with or without inhaled xenon during 24 h. Blood samples for nuclear magnetic resonance spectroscopy metabolic profiling were drawn upon admission, at 24 and 72 h. Results: At 24 h, increased lactate, adjusted hazard-ratio 2.25, 95% CI [1.53; 3.30], p<0.001, and decreased branched-chain amino acids (BCAA) leucine 0.64 [0.5; 0.82], p = 0.007, and valine 0.37 [0.22; 0.63], p = 0.003, associated with 6-month mortality. At 72 h, increased lactate 2.77 [1.76; 4.36], p<0.001, and alanine 2.43 [1.56; 3.78], p = 0.001, and decreased small HDL cholesterol ester content (S-HDL-CE) 0.36 [0.19; 0.68], p = 0.021, associated with mortality. No difference was observed between xenon and control groups. Conclusions: In OHCA patients receiving TTM with or without xenon, high lactate and alanine and decreased BCAAs and S-HDL-CE associated with increased mortality. It remains to be established whether current observations on BCAAs, and possibly alanine and lactate, could reflect neural damage via their roles in the metabolism of the neurotransmitter glutamate. Xenon did not significantly alter the measured metabolic profile, a potentially beneficial attribute in the context of compromised ICU patients. Trial registration: Trial Registry number: ClinicalTrials.gov Identifier: NCT00879892. [ABSTRACT FROM AUTHOR]

Long-term statistics of atmospheric aerosol and especially cloud scavenging were studied at the Puijo measurement station in Kuopio, Finland, during October 2010–November 2014. Aerosol size distributions, scattering coefficients at three different wavelengths (450, 550, and 700 nm), and absorption coefficient at wavelength 637 nm were measured with a special inlet system to sample interstitial and total aerosol in clouds. On average, accumulation mode particle concentration was found to be correlated with temperature with the lowest average concentrations of 200 cm−3 around 0 ∘C increasing to 800 cm−3 at 20 ∘C. The scavenging efficiencies of both scattering and absorbing material were observed to have a slightly positive temperature correlation in in-cloud measurements. At 0 ∘C, the scavenging efficiencies of scattering and absorbing material were 0.85 and 0.55 with slopes of 0.005 and 0.003 ∘C−1, respectively. Scavenging efficiencies were also studied as a function of the diameter at which half of the particles are activated into cloud droplets. This analysis indicated that there is a higher fraction of absorbing material, typically black carbon, in smaller sizes so that at least 20 %–30 % of interstitial particles within clouds consist of absorbing material. In addition, the PM1 inlet revealed that approximately 20 % of absorbing material was observed to reside in particles with ambient diameter larger than ∼ 1 µm at relative humidity below 90 %. Similarly, 40 % of scattering material was seen to be in particles larger than 1 µm. Altogether, this dataset provides information on the size-dependent aerosol composition and in-cloud scavenging of different types of aerosol. The dataset can be useful in evaluating how well the size-dependent aerosol composition is simulated in global aerosol models and how well these models capture the in-cloud scavenging of different types of aerosol in stratus clouds.

The Twomey effect describes the radiative forcing associated with a change in cloud albedo due to an increase in anthropogenic aerosol emissions. It is driven by the perturbation in cloud droplet number concentration (ΔNd, ant) in liquid-water clouds and is currently understood to exert a cooling effect on climate. The Twomey effect is the key driver in the effective radiative forcing due to aerosol–cloud interactions, but rapid adjustments also contribute. These adjustments are essentially the responses of cloud fraction and liquid water path to ΔNd, ant and thus scale approximately with it. While the fundamental physics of the influence of added aerosol particles on the droplet concentration (Nd) is well described by established theory at the particle scale (micrometres), how this relationship is expressed at the large-scale (hundreds of kilometres) perturbation, ΔNd, ant, remains uncertain. The discrepancy between process understanding at particle scale and insufficient quantification at the climate-relevant large scale is caused by co-variability of aerosol particles and updraught velocity and by droplet sink processes. These operate at scales on the order of tens of metres at which only localised observations are available and at which no approach yet exists to quantify the anthropogenic perturbation. Different atmospheric models suggest diverse magnitudes of the Twomey effect even when applying the same anthropogenic aerosol emission perturbation. Thus, observational data are needed to quantify and constrain the Twomey effect. At the global scale, this means satellite data. There are four key uncertainties in determining ΔNd, ant, namely the quantification of (i) the cloud-active aerosol – the cloud condensation nuclei (CCN) concentrations at or above cloud base, (ii) Nd, (iii) the statistical approach for inferring the sensitivity of Nd to aerosol particles from the satellite data and (iv) uncertainty in the anthropogenic perturbation to CCN concentrations, which is not easily accessible from observational data. This review discusses deficiencies of current approaches for the different aspects of the problem and proposes several ways forward: in terms of CCN, retrievals of optical quantities such as aerosol optical depth suffer from a lack of vertical resolution, size and hygroscopicity information, non-direct relation to the concentration of aerosols, difficulty to quantify it within or below clouds, and the problem of insufficient sensitivity at low concentrations, in addition to retrieval errors. A future path forward can include utilising co-located polarimeter and lidar instruments, ideally including high-spectral-resolution lidar capability at two wavelengths to maximise vertically resolved size distribution information content. In terms of Nd, a key problem is the lack of operational retrievals of this quantity and the inaccuracy of the retrieval especially in broken-cloud regimes. As for the Nd-to-CCN sensitivity, key issues are the updraught distributions and the role of Nd sink processes, for which empirical assessments for specific cloud regimes are currently the best solutions. These considerations point to the conclusion that past studies using existing approaches have likely underestimated the true sensitivity and, thus, the radiative forcing due to the Twomey effect.

The TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5 Precursor (S5P) satellite was launched on 13 October 2017 to provide the atmospheric composition for atmosphere and climate research. The S5P is a Sun-synchronous polar-orbiting satellite providing global daily coverage. The TROPOMI swath is 2600 km wide, and the ground resolution for most data products is 7.2×3.5 km2 (5.6×3.5 km2 since 6 August 2019) at nadir. The Finnish Meteorological Institute (FMI) is responsible for the development of the TROPOMI UV algorithm and the processing of the TROPOMI surface ultraviolet (UV) radiation product which includes 36 UV parameters in total. Ground-based data from 25 sites located in arctic, subarctic, temperate, equatorial and Antarctic areas were used for validation of the TROPOMI overpass irradiance at 305, 310, 324 and 380 nm, overpass erythemally weighted dose rate/UV index, and erythemally weighted daily dose for the period from 1 January 2018 to 31 August 2019. The validation results showed that for most sites 60 %–80 % of TROPOMI data was within ±20 % of ground-based data for snow-free surface conditions. The median relative differences to ground-based measurements of TROPOMI snow-free surface daily doses were within ±10 % and ±5 % at two-thirds and at half of the sites, respectively. At several sites more than 90 % of cloud-free TROPOMI data was within ±20 % of ground-based measurements. Generally median relative differences between TROPOMI data and ground-based measurements were a little biased towards negative values (i.e. satellite data < ground-based measurement), but at high latitudes where non-homogeneous topography and albedo or snow conditions occurred, the negative bias was exceptionally high: from −30 % to −65 %. Positive biases of 10 %–15 % were also found for mountainous sites due to challenging topography. The TROPOMI surface UV radiation product includes quality flags to detect increased uncertainties in the data due to heterogeneous surface albedo and rough terrain, which can be used to filter the data retrieved under challenging conditions.

Parvoviruses are single-stranded DNA viruses, infecting many animals from insects to humans. Human parvovirus B19 (B19V) causes erythema infectiosum, arthropathy, anemia, and fetal death, and human bocavirus (HBoV) 1 causes respiratory tract infections, while HBoV2-4 are enteric. Parvoviral genomes can persist in diverse non-permissive tissues after acute infection, but the host-cell tropism and the impact of their tissue persistence are poorly studied. We searched for parvoviral DNA in a total of 427 intestinal biopsy specimens, as paired disease-affected and healthy mucosa, obtained from 130 patients with malignancy, ulcerative colitis (UC), or adenomas, and in similar intestinal segments from 55 healthy subjects. Only three (1.6%) individuals exhibited intestinal HBoV DNA (one each of HBoV1, 2, and 3). Conversely, B19V DNA persisted frequently in the intestine, with 50, 47, 31, and 27% detection rates in the patients with malignancy, UC, or adenomas, and in the healthy subjects, respectively. Intra-individually, B19V DNA persisted significantly more often in the healthy intestinal segments than in the inflamed colons of UC patients. The highest loads of B19V DNA were seen in the ileum and colon specimens of two healthy individuals. With dual-RNAscope in situ hybridization and immunohistochemistry assays, we located the B19V persistence sites of these intestines in mucosal B cells of lymphoid follicles and vascular endothelial cells. Viral messenger RNA transcription remained, however, undetected. RNA sequencing (RNA-seq) identified 272 differentially expressed cellular genes between B19V DNA-positive and -negative healthy ileum biopsy specimens. Pathway enrichment analysis revealed that B19V persistence activated the intestinal cell viability and inhibited apoptosis. Lifelong B19V DNA persistence thus modulates host gene expression, which may lead to clinical outcomes.

Abstract Fish scales are among the structural materials in nature that are inspiring the design and development of “next‐generation” engineering materials. Fish scales possess a mineralization gradient that divides their thickness into three unique regions, each containing characteristic structures and properties. Here, experiments and complementary numerical modeling are performed to understand the importance of the different geometrical and mechanical parameters affecting the structural behavior of fish scales. Numerical modeling results showed that the stiffness and work to fracture of the scales in flexure are dependent on the amplitude and wavelength of the limiting layer profile. Furthermore, the mechanical response in bending of the scales can be effectively tuned by the suture profile location within the limiting layer thickness. These results highlight the opportunity to tailor the mechanical response of flexible composite laminates through the architecture of the layers and their interfaces to effectively control the protecto‐flexibility. Key Points This work combines the disciplines of structural biology, materials science and mechanical engineering to identify the key contributions of the microstructure to the inherent protecto‐flexibility of fish scales, a class of natural dermal armor. The interdisciplinary approach enables an identification of how nature adjusts specific morphological parameters to modulate both flexiblity and protection from physical threats.

ImportanceEvidence from preclinical models indicates that xenon gas can prevent the development of cerebral damage after acute global hypoxic-ischemic brain injury but, thus far, these putative neuroprotective properties have not been reported in human studies.ObjectiveTo determine the effect of inhaled xenon on ischemic white matter damage assessed with magnetic resonance imaging (MRI).Design, setting, and participantsA randomized single-blind phase 2 clinical drug trial conducted between August 2009 and March 2015 at 2 multipurpose intensive care units in Finland. One hundred ten comatose patients (aged 24-76 years) who had experienced out-of-hospital cardiac arrest were randomized.InterventionsPatients were randomly assigned to receive either inhaled xenon combined with hypothermia (33°C) for 24 hours (n = 55 in the xenon group) or hypothermia treatment alone (n = 55 in the control group).Main outcomes and measuresThe primary end point was cerebral white matter damage as evaluated by fractional anisotropy from diffusion tensor MRI scheduled to be performed between 36 and 52 hours after cardiac arrest. Secondary end points included neurological outcome assessed using the modified Rankin Scale (score 0 [no symptoms] through 6 [death]) and mortality at 6 months.ResultsAmong the 110 randomized patients (mean age, 61.5 years; 80 men [72.7%]), all completed the study. There were MRI data from 97 patients (88.2%) a median of 53 hours (interquartile range [IQR], 47-64 hours) after cardiac arrest. The mean global fractional anisotropy values were 0.433 (SD, 0.028) in the xenon group and 0.419 (SD, 0.033) in the control group. The age-, sex-, and site-adjusted mean global fractional anisotropy value was 3.8% higher (95% CI, 1.1%-6.4%) in the xenon group (adjusted mean difference, 0.016 [95% CI, 0.005-0.027], P = .006). At 6 months, 75 patients (68.2%) were alive. Secondary end points at 6 months did not reveal statistically significant differences between the groups. In ordinal analysis of the modified Rankin Scale, the median (IQR) value was 1 (1-6) in the xenon group and 1 (0-6) in the control group (median difference, 0 [95% CI, 0-0]; P = .68). The 6-month mortality rate was 27.3% (15/55) in the xenon group and 34.5% (19/55) in the control group (adjusted hazard ratio, 0.49 [95% CI, 0.23-1.01]; P = .053).Conclusions and relevanceAmong comatose survivors of out-of-hospital cardiac arrest, inhaled xenon combined with hypothermia compared with hypothermia alone resulted in less white matter damage as measured by fractional anisotropy of diffusion tensor MRI. However, there was no statistically significant difference in neurological outcomes or mortality at 6 months. These preliminary findings require further evaluation in an adequately powered clinical trial designed to assess clinical outcomes associated with inhaled xenon among survivors of out-of-hospital cardiac arrest.Trial registrationclinicaltrials.gov Identifier: NCT00879892.