Regional Mean Values Research Articles

Does geographical location impact educational disparities among Ecuadorians? A novel two-stage inequality decomposition method

The aim of this paper is to assess the extent of educational disparities among Ecuadorians attributed to their geographical location. For this purpose, a novel two-stage hierarchical decomposition of inequality for the half of the square of the coefficient of variation is introduced. This method, an extension of the one-stage (within/between) decomposition, is applicable to variables that can take the value zero, such as the ‘years of schooling’ variable. Using microdata bases from Ecuador’s National Survey of Employment, Unemployment and Underemployment (encompassing all twenty-four provinces and four regions in 2014 and 2021), we estimated the ‘years of schooling’ for individuals aged 24 and over, determining provincial, regional and national mean values. The proposed method allows the identification of the extent to which educational disparities among Ecuadorians (total inequality) can be attributed to differences between provinces and regions (spatial inequality), and the extent to which such educational inequality is due to variations among individuals within provinces. Moreover, it measures the educational inequality within each province and evaluates the contribution of each province to intra-provincial inequality. The results indicate that, although spatial inequality increased between the study years, total educational inequality decreased. This is because the contribution of spatial inequality to total inequality was practically negligible compared to the influence of disparities among individuals within provinces. Consequently, the reduction in the intra-provincial inequality is the reason for the decrease in educational differences among Ecuadorians. The findings potentially reflect individual-focused policies, socioeconomic features of Ecuador’s provinces and align with the official educational statistics.

APOE4 Carriers with Perivascular Spaces Exhibit Altered Cerebral Blood Flow

AbstractBackgroundPerivascular spaces (PVS) are fluid‐filled spaces surrounding arterioles, capillaries and venules in the brain, which support metabolic waste clearance. Enlarged PVS are associated with increased dementia risk. Changes in arterial pulsatility are hypothesized to be associated with accumulation of toxic solutes and PVS widening. However, few prior studies have examined whether cerebral blood flow (CBF) is linked to PVS.MethodIndependently living older adults (N = 60, mean age = 68.1 years; SD = 7.5; age range 55‐88 years; 30.0% male) free of dementia or clinical stroke were recruited from the community and underwent brain MRI and venipuncture. Pseudo‐continuous arterial spin labeling was utilized to determine CBF in gray matter CBF (mL/100g tissue/min). Regional mean values were determined for regions of interest. PVS were qualitatively scored in the basal ganglia (BG), and centrum semiovale (CS). APOE genotyping was conducted on the blood cell pellet fraction.ResultAfter accounting for age and sex, multiple linear regression analysis revealed a significant negative association between BG‐PVS and CBF in the left inferior occipital gyrus (B = ‐.07, 95% CI (‐.13, ‐.01), p = .022), right inferior occipital gyrus (B = ‐.06, 95% CI (‐.12, ‐.001), p = .048), left middle occipital gyrus (B = ‐.05, 95% CI (‐.10, ‐.001), p = .047), right middle occipital gyrus (B = ‐.08, 95% CI (‐.13, ‐.02), p = .007), and right inferior temporal gyrus (B = ‐.05, 95% CI (‐.09, ‐.01), p = .025) as well as a positive association in the left precuneus (B = .05, 95% CI (.01, .08), p = .022). When stratified by APOE4 status, all associations were significant only in APOE4 carriers. CS‐PVS were not associated with CBF.ConclusionThese findings indicate altered CBF in older adults with BG‐PVS but not CS‐PVS. Resting CBF was altered in specific brain regions, predominantly in APOE4 carriers. APOE4 is known to convey both vascular risk and risk for Alzheimer’s disease (AD). Additional longitudinal studies are warranted to explore the association between PVS and CBF in individuals at risk for dementia to further understand vascular contributions to the development of AD and other dementias.

APOE4 Carriers with Perivascular Spaces Exhibit Altered Cerebral Blood Flow

AbstractBackgroundPerivascular spaces (PVS) are fluid‐filled spaces surrounding arterioles, capillaries and venules in the brain, which support metabolic waste clearance. Enlarged PVS are associated with increased dementia risk. Changes in arterial pulsatility are hypothesized to be associated with accumulation of toxic solutes and PVS widening. However, few prior studies have examined whether cerebral blood flow (CBF) is linked to PVS.MethodIndependently living older adults (N = 60, mean age = 68.1 years; SD = 7.5; age range 55‐88 years; 30.0% male) free of dementia or clinical stroke were recruited from the community and underwent brain MRI and venipuncture. Pseudo‐continuous arterial spin labeling was utilized to determine CBF in gray matter CBF (mL/100g tissue/min). Regional mean values were determined for regions of interest. PVS were qualitatively scored in the basal ganglia (BG), and centrum semiovale (CS). APOE genotyping was conducted on the blood cell pellet fraction.ResultAfter accounting for age and sex, multiple linear regression analysis revealed a significant negative association between BG‐PVS and CBF in the left inferior occipital gyrus (B = ‐.07, 95% CI (‐.13, ‐.01), p = .022), right inferior occipital gyrus (B = ‐.06, 95% CI (‐.12, ‐.001), p = .048), left middle occipital gyrus (B = ‐.05, 95% CI (‐.10, ‐.001), p = .047), right middle occipital gyrus (B = ‐.08, 95% CI (‐.13, ‐.02), p = .007), and right inferior temporal gyrus (B = ‐.05, 95% CI (‐.09, ‐.01), p = .025) as well as a positive association in the left precuneus (B = .05, 95% CI (.01, .08), p = .022). When stratified by APOE4 status, all associations were significant only in APOE4 carriers. CS‐PVS were not associated with CBF.ConclusionThese findings indicate altered CBF in older adults with BG‐PVS but not CS‐PVS. Resting CBF was altered in specific brain regions, predominantly in APOE4 carriers. APOE4 is known to convey both vascular risk and risk for Alzheimer’s disease (AD). Additional longitudinal studies are warranted to explore the association between PVS and CBF in individuals at risk for dementia to further understand vascular contributions to the development of AD and other dementias.

Audit&Feedback in emergency care: a pre-post intervention study in Lazio (Italy)

Abstract Background Within EASY-NET Italian Programme (NET-2016-02364191), we evaluated the effectiveness of a structured Audit & Feedback (A&F) intervention in improving care quality for ST Elevation Myocardial Infarction (STEMI). Methods A&F intervention involved sending periodic reports via e-mail to participating hospitals in Lazio Region (about 5 million inhabitans). Volume, process and outcome indicators were calculated by hospital through Health Information System, compared with regional mean and target values. Health managers and clinicians were feedback recipients. Study design: pre-post intervention with control group (web-based regional periodic publication of indicators). Proportion of STEMI treated within 90 minutes with Percutaneous Transluminal Coronary Angioplasty (PTCA) was calculated in 2021 (pre) and in 2022 (post). Patients level adjusted Difference-in-Difference model (DID, 95% CI) was applied. Stepwise procedure identified individual (e.g. age, sex, clinical conditions) and hospital (e.g. hospital type) covariates entering in the model. Results A total of 19 hospitals were evaluated, 8 as controls. The number of analysed STEMI was 5084 (2651 in 2022) of which 3272 (1731 in 2022) in exposed hospitals. Overall, mean age 66 years, males 74.7%. Proportion treated with PTCA within 90 minutes in 2021 was 55.1% in exposed hospitals, and 57.9% in controls; in 2022 60.0% in exposed hospitals 66.4% in controls. Adjusted percentage difference in post/pre change between exposed and non-exposed hospitals was not significant in univariate and multivariate model (-3.6%, p = 0.218 and -4.4% p = 0.126). Conclusions These results cannot demonstrate a difference between exposed and not exposed hospitals. Possible explanations could be the short follow-up evaluated and the influence of covid-19 pandemic. In fact, several hospitals in both exposed and control group still had entire hospital wards dedicated to covid-19 management in 2021. Key messages • A&F methodology designed and implemented in EASY-NET project represents a challenging instrument to promote quality of care. • Monitoring hospital performance through periodical reporting allows continuous quality improvement.

Multi-decadal analysis of past winter temperature, precipitation and snow cover data in the European Alps from reanalyses, climate models and observational datasets

Abstract. Assessing past distributions, variability and trends in the mountain snow cover and its first-order drivers, temperature and precipitation, is key for a wide range of studies and applications. In this study, we compare the results of various modeling systems (global and regional reanalyses ERA5, ERA5-Land, ERA5-Crocus, CERRA-Land, UERRA MESCAN-SURFEX and MTMSI and regional climate model simulations CNRM-ALADIN and CNRM-AROME driven by the global reanalysis ERA-Interim) against observational references (in situ, gridded observational datasets and satellite observations) across the European Alps from 1950 to 2020. The comparisons are performed in terms of monthly and seasonal snow cover variables (snow depth and snow cover duration) and their main atmospherical drivers (near-surface temperature and precipitation). We assess multi-annual averages of regional and subregional mean values, their interannual variations, and trends over various timescales, mainly for the winter period (from November through April). ERA5, ERA5-Crocus, MESCAN-SURFEX, CERRA-Land and MTMSI offer a satisfying description of the monthly snow evolution. However, a spatial comparison against satellite observation indicates that all datasets overestimate the snow cover duration, especially the melt-out date. CNRM-AROME and CNRM-ALADIN simulations and ERA5-Land exhibit an overestimation of the snow accumulation during winter, increasing with elevations. The analysis of the interannual variability and trends indicates that modeling snow cover dynamics remains complex across multiple scales and that none of the models evaluated here fully succeed to reproduce this compared to observational reference datasets. Indeed, while most of the evaluated model outputs perform well at representing the interannual to multi-decadal winter temperature and precipitation variability, they often fail to address the variability in the snow depth and snow cover duration. We discuss several artifacts potentially responsible for incorrect long-term climate trends in several reanalysis products (ERA5 and MESCAN-SURFEX), which we attribute primarily to the heterogeneities of the observation datasets assimilated. Nevertheless, many of the considered datasets in this study exhibit past trends in line with the current state of knowledge. Based on these datasets, over the last 50 years (1968–2017) at a regional scale, the European Alps have experienced a winter warming of 0.3 to 0.4 ∘C per decade, stronger at lower elevations, and a small reduction in winter precipitation, homogeneous with elevation. The decline in the winter snow depth and snow cover duration ranges from −7 % to −15 % per decade and from −5 to −7 d per decade, respectively, both showing a larger decrease at low and intermediate elevations. Overall, we show that no modeling strategy outperforms all others within our sample and that upstream choices (horizontal resolution, heterogeneity of the observations used for data assimilation in reanalyses, coupling between surface and atmosphere, level of complexity, configuration of the snow scheme, etc.) have great consequences on the quality of the datasets and their potential use. Despite their limitations, in many cases they can be used to characterize the main features of the mountain snow cover for a range of applications.

Natural radioactivity of groundwater in Vendian deposits in St. Petersburg Region

The study is focused on the hydrogeological conditions and the chemistry of groundwater of the Vendian aquifer in the western part of the Leningrad oblast (Karelian Isthmus and the area near Sosnovy Bor town) and St. Petersburg City, where groundwater features higher radioactivity, but nevertheless it is used for drinking water supply. Data on the radiological characteristics, which have been determined in the estimation of the quality of groundwater used for drinking are generalized and analyzed. These characteristics include the gross alpha and gross beta activity and the specific activity of natural radionuclides 222Rn, 226Ra, 228Ra, 210Pb, 210Po, 238U, and 234U. The data were subjected to statistical and correlation analysis to determine the hygienic criteria for the use of groundwater of this aquifer for drinking water supply and to study the sources and the processes of formation of the natural radiological background. Groundwater quality standards were shown to be exceeded in the majority of the analyzed wells. The brackish water in the southern, deeper, part of the aquifer system was shown to have higher radioactivity and relatively high concentrations of 226Ra, 228Ra, 210Pb, and 210Po, compared with fresh water in the northern part of the territory, of which higher, though nonuniform, 222Rn activity is typical. Relationships between the radiation characteristics of groundwater are considered along with the causes of formation of groundwater radionuclide composition as a result of the higher radioactivity of the host deposits and the chemistry of groundwater; changes in the radiological and hydrochemical background groundwater characteristics from the north to the south are characterized in accordance with the subsidence of the aquifer system and an increase in the stagnation of the hydrochemical regime. The analysis of the well-known relationship between the concentrations of radium isotopes in groundwater, uranium and thorium isotopes in the host rocks, and groundwater residence time in the aquifer, along with the comparison of the available field data with calculation results, suggested the conclusion that the concentration of uranium in the water-bearing rocks in the major portion of the area under consideration is higher than its regional mean values.

A quantitative clinical evaluation of simultaneous reconstruction of attenuation and activity in time-of-flight PET

BackgroundThe maximum likelihood activity and attenuation (MLAA) reconstruction algorithm has been proposed to jointly estimate tracer activity and attenuation at the same time, and proven to be a promising solution to the CT attenuation correction (CT-AC) artifacts in PET images. This study aimed to perform a quantitative evaluation and clinical validation of the MLAA method.MethodsA uniform cylinder phantom filled with 18F-FDG solution was scanned to optimize the reconstruction parameters for the implemented MLAA algorithm. 67 patients who underwent whole-body 18F-FDG PET/CT scan were retrospectively recruited. PET images were reconstructed using MLAA and clinical standard OSEM algorithm with CT-AC (CT-OSEM). The mean and maximum standardized uptake values (SUVmean and SUVmax) in regions of interest (ROIs) of organs, high uptake lesions and areas affected by metal implants and respiration motion artifacts were quantitatively analyzed.ResultsIn quantitative analysis, SUVs in patient’s organ ROIs between two methods showed R2 ranging from 0.91 to 0.98 and k ranging from 0.90 to 1.06, and the average SUVmax and SUVmean differences between two methods were within 10% range, except for the lung ROI, which was 10.5% and 16.73% respectively. The average SUVmax and SUVmean differences of a total of 117 high uptake lesions were 7.25% and 7.10% respectively. 20 patients were identified to have apparent respiration motion artifacts in the liver in CT-OSEM images, and the SUVs differences between two methods measured at dome of the liver were significantly larger than measured at middle part of the liver. 10 regions with obvious metal artifacts were identified in CT-OSEM images and the average SUVmean and SUVmax differences in metal implants affected regions were reported to be 52.90% and 56.20% respectively.ConclusionsPET images reconstructed using MLAA are clinically acceptable in terms of image quality as well as quantification and it is a useful tool in clinical practice, especially when CT-AC may cause respiration motion and metal artifacts. Moreover, this study also provides technical reference and data support for the future iteration and development of PET reconstruction technology of SUV accurate quantification.

Brain computed tomography perfusion analysis in HIV-seropositive adults with and without neurocognitive impairment in Nigeria: outcomes and challenges of a pilot study.

the significance of cerebrovascular disease in HIV-associated neurocognitive disorder (HAND) in a homogeneous black population has not yet been determined. This incident case-control study used CT perfusion imaging to quantify and compare regional cerebral blood flow parameters in neuro-cognitively impaired and unimpaired HIV+ participants of the Ibadan Cohort on Neuro AIDS (ICON) in Nigeria. this was an incident case-control study consisting of twenty-seven HIV+ adults, classified based on Frascati criteria into neurocognitive impaired (n=18) and unimpaired (n=9) groups, who had brain computed tomographic perfusion (CTP) with a 64-slice Toshiba T scanner. The standard deviation (SD) of regional mean transit time (MTT), cerebral blood flow (CBF), and cerebral blood volume (CBV) values were calculated for bilateral basal ganglia (BG), frontal, parietal, temporal, and occipital regions from CT perfusion maps. The regional mean values and variability (SD) in the CTP measures were compared in the groups using an independent student t-test. differentially higher variability in the bilateral CBF measures in the parietal (right; OR = 1.14, x̄ =5.61, p=0.041, CI=0.27-11.35/left; OR = 1.16, x̄=7.01, p=0.03, CI=5.6-13.47) and time to peak (TTP) measures in the basal ganglia (right; OR = 3.78, x̄=0.88, p=0.032, CI=0.081-1.67/left; OR = 2.44, x̄=1.48, p=0.020, CI=0.26-2.71) and occipital (right; OR = 2.18, x̄=1.32, p=0.018, CI=0.25-2.38/left; OR = 1.93, x̄=1.08, p=0.034, CI=0.086-2.06) regions were observed in the cognitively impaired group compared to the unimpaired group. the study evidence suggests that alterations in cerebral perfusion implicated in HIV-associated neurocognitive disorder may be possibly demonstrated using CTP, a readily available resource in most African countries saddled with the highest burden of HIV.

Differential vulnerability of hippocampal microstructure in 5xFAD mouse model of Alzheimer’s Disease: A dMRI study

AbstractBackgroundHippocampal subfields exhibit differential vulnerabilities to Alzheimer’s disease (AD) associated pathologies. These pathological processes extensively attenuate the structural and functional interconnectivities of the subfields. Abnormal accumulation of beta‐amyloid (Aβ) is considered a primary hallmark of AD. Histopathological studies suggest region‐specific accumulation of Aβ in hippocampal subfields. The aim of the current study is to understand the subfield‐specific in‐vivo microstructural changes in hippocampus due to Aβ load in 2.5 months old 5xFAD mouse model of AD.MethodTwo and a half month old male 5xFAD and age‐matched littermate controls were used in this study. DWI and anatomical images were acquired on a horizontal bore 9.4T Biospec micro‐MRI system equipped with a H1 cryogenic surface coil. 2D T2‐weighted anatomical images were acquired using the following parameters: TE/TR=43.67/7500 ms, voxel size=117x117x250 µm3 and number of slices=20. DWIs were acquired using multi‐shot dual‐spin‐echo EPI sequence using following parameters: TE/TR=34.78/3000 ms, voxel size=117x117x250 µm3, number of slices=20, 3 b‐values (650, 1200 and 2500) s/mm2, 5 b0 per shell, 12 diffusion encoding direction for b=650, 60 for b=1200 and 80 for b=2500 s/mm2. T2‐W images were nonlinearly registered to Badhwar hippocampal atlas. Hippocampal subfields (CA1, CA2, CA3, DG and Subiculum) in atlas space were transformed to individual T2W space and then linearly transformed to DWI space. Multi‐compartment microstructural imaging was performed using Cortical‐NODDI. Volume fraction of isotropic water diffusivity (VFISO) and intracellular volume fraction (VFIC) maps were calculated. The regional mean values (VFIC and VFISO) of individual subfields were extracted and used in general linear model for group‐comparisons.ResultThe results of the study suggest group‐level differences between control and 5xFAD mice in cornu ammonis regions. Compared to 5xFAD, VFIC in littermate control mice was significantly higher in CA1 (p<0.05; d=1.47), CA2 (p<0.05; d=1.11) and CA3 (p<0.05; d=1.54). VFISO in DG was significantly lower in littermate control compared to 5xFAD mice (p<0.05; d=1.31).ConclusionThe study demonstrates the importance of utilizing tissue‐specific microstructural imaging in detecting Aβ associated microstructural alterations in multiple hippocampal subfields. This study demonstrates that Aβ alters the hippocampal microstructure. study also suggests on the differential effect of Aβ pathology on hippocampal microstructure.

Towards accurate partial volume correction in 99mTc oncology SPECT: perturbation for case-specific resolution estimation

BackgroundCurrently, there is no consensus on the optimal partial volume correction (PVC) algorithm for oncology imaging. Several existing PVC methods require knowledge of the reconstructed resolution, usually as the point spread function (PSF)—often assumed to be spatially invariant. However, this is not the case for SPECT imaging. This work aimed to assess the accuracy of SPECT quantification when PVC is applied using a case-specific PSF.MethodsSimulations of SPECT ^{99{mathrm{m}}}Tc imaging were performed for a range of activity distributions, including those replicating typical clinical oncology studies. Gaussian PSFs in reconstructed images were estimated using perturbation with a small point source. Estimates of the PSF were made in situations which could be encountered in a patient study, including; different positions in the field of view, different lesion shapes, sizes and contrasts, noise-free and noisy data. Ground truth images were convolved with the perturbation-estimated PSF, and with a PSF reflecting the resolution at the centre of the field of view. Both were compared with reconstructed images and the root-mean-square error calculated to assess the accuracy of the estimated PSF. PVC was applied using Single Target Correction, incorporating the perturbation-estimated PSF. Corrected regional mean values were assessed for quantitative accuracy.ResultsPerturbation-estimated PSF values demonstrated dependence on the position in the Field of View and the number of OSEM iterations. A lower root mean squared error was observed when convolution of the ground truth image was performed with the perturbation-estimated PSF, compared with convolution using a different PSF. Regional mean values following PVC using the perturbation-estimated PSF were more accurate than uncorrected data, or data corrected with PVC using an unsuitable PSF. This was the case for both simple and anthropomorphic phantoms. For the simple phantom, regional mean values were within 0.7% of the ground truth values. Accuracy improved after 5 or more OSEM iterations (10 subsets). For the anthropomorphic phantoms, post-correction regional mean values were within 1.6% of the ground truth values for noise-free uniform lesions.ConclusionPerturbation using a simulated point source could potentially improve quantitative SPECT accuracy via the application of PVC, provided that sufficient reconstruction iterations are used.

Alcohol dependence inpatients classification with GLM and hierarchical clustering integration using fMRI data of alcohol multiple scenario cues.

Alterations in brain reactions to alcohol-related cues are a neurobiological characteristic of alcohol dependence (AD) and a prospective target for achieving substantial treatment effects. However, a robust prediction of the differences in inpatients' brain responses to alcohol cues during the treatment process is still required. This study offers a data-driven approach for classifying AD inpatients undertaking alcohol treatment protocols based on their brain responses to alcohol imagery with and without drinking actions. The brain activity of thirty inpatients with AD undergoing treatment was scanned using functional magnetic resonance imaging (fMRI) while seeing alcohol and matched non-alcohol images. The mean values of brain regions of interest (ROI) for alcohol-related brain responses were obtained using general linear modeling (GLM) and subjected to hierarchical clustering analysis. The proposed classification technique identified two distinct subgroups of inpatients. For the two types of cues, subgroup one exhibited significant activation in a wide range of brain regions, while subgroup two showed mainly decreased activation. The proposed technique may aid in detecting the vulnerability of the classified inpatient subgroups, which can suggest allocating the inpatients in the classified subgroups to more effective therapies and developing prognostic future relapse markers in AD.

Right Cortical Infarction and a Reduction in Putamen Volume May Be Correlated with Empathy in Patients after Subacute Ischemic Stroke-A Multimodal Magnetic Resonance Imaging Study.

Empathy has not been well studied in patients following ischemic stroke. We aimed to evaluate the relationships of multimodal neuroimaging parameters with the impairment of empathy in patients who had experienced subacute ischemic stroke. Patients who had experienced a first-event acute ischemic stroke were recruited, and we assessed their empathy using the Chinese version of the Empathy Quotient (EQ) 3 months after the index stroke. Multimodal magnetic resonance imaging (MRI) was conducted in all the participants to identify acute infarction and assess brain volumes, white matter integrity, and other preexisting abnormalities. We quantified the brain volumes of various subcortical structures, the ventricles, and cortical lobar atrophy. The microstructural integrity of the white matter was reflected in the mean fractional anisotropy (FA) and mean diffusivity (MD), and the regional mean values of FA and MD were quantified after mapping using the ICBM_DTI_81 Atlas. Twenty-three (56.1%) men and 18 (43.9%) women (mean age: 61.73 years, range: 41–77 years) were included. The median National Institutes of Health Stroke Scale (NIHSS) score at discharge was 1 (range: 0–4). On univariate analysis, the EQ was correlated with right cortical infarction (r = −0.39, p = 0.012), putamen volume (r = 0.382, p = 0.014), right putamen volume (r = 0.338, p = 0.031), and the FA value of the right sagittal stratum. EQ did not correlated with the MD value in any region of interest or pre-existing brain abnormalities. Multiple stepwise linear regression models were used to identify factors associated with EQ. After adjusting for age and the NIHSS score on admission, the frequency of right cortical infarcts negatively correlated with EQ (standardized β = −0.358, 95% confidence interval =−0.708 to −0.076, p = 0.016), and the putamen volume positively correlated with EQ (standardized β = 0.328, 95% confidence interval =0.044 to 0.676, p = 0.027). In conclusion, in patients who have experienced subacute ischemic stroke, right cortical infarction and a smaller putamen volume are associated with the impairment of empathy.

A Remote-Sensing Ecological Index Approach for Restoration Assessment of Rare-Earth Elements Mining

In order to meet the requirements for comprehensive and multidimensional generalization of ecological management effectiveness evaluation indexes in the context of ecological restoration advocating comprehensive management by multiple means, this paper explores the rationality of using RSEI as an ecological management effectiveness evaluation index to adapt to the systematic transformation of the management goal of abandoned mine restoration from ecological restoration to regional socioeconomic sustainable development. Based on Landsat-8 image data, the remote sensing ecological index (RSEI) was used to evaluate the dynamic changes and spatial and temporal differences of the ecological environment in the study area under the long-term multimeans comprehensive management. The RSEI is suitable for evaluating the effectiveness of comprehensive ecological management in mining areas with a large amount of bare soil. The regional RSEI mean value increased by 0.029 in the early stage and 0.051 in the later stage by fragmentation management, indicating a better effect of multimeans comprehensive management. The remote sensing ecological index can objectively reflect the difference of spatial distribution characteristics of ecological environment in the four “Ecological+” governance regions. It can both objectively reflect the ecological status of the study area and reflect the differentiated spatial distribution characteristics of the ecological environment in different treatment areas, which is of long-term practical significance to the ecological construction of the study area. This study provides a theoretical reference for ecological assessment of complex situation under difficult site conditions.

Post-Radiotherapy PET Image Outcome Prediction by Deep Learning Under Biological Model Guidance: A Feasibility Study of Oropharyngeal Cancer Application.

PurposeTo develop a method of biologically guided deep learning for post-radiation 18FDG-PET image outcome prediction based on pre-radiation images and radiotherapy dose information.MethodsBased on the classic reaction–diffusion mechanism, a novel biological model was proposed using a partial differential equation that incorporates spatial radiation dose distribution as a patient-specific treatment information variable. A 7-layer encoder–decoder-based convolutional neural network (CNN) was designed and trained to learn the proposed biological model. As such, the model could generate post-radiation 18FDG-PET image outcome predictions with breakdown biological components for enhanced explainability. The proposed method was developed using 64 oropharyngeal patients with paired 18FDG-PET studies before and after 20-Gy delivery (2 Gy/day fraction) by intensity-modulated radiotherapy (IMRT). In a two-branch deep learning execution, the proposed CNN learns specific terms in the biological model from paired 18FDG-PET images and spatial dose distribution in one branch, and the biological model generates post-20-Gy 18FDG-PET image prediction in the other branch. As in 2D execution, 718/233/230 axial slices from 38/13/13 patients were used for training/validation/independent test. The prediction image results in test cases were compared with the ground-truth results quantitatively.ResultsThe proposed method successfully generated post-20-Gy 18FDG-PET image outcome prediction with breakdown illustrations of biological model components. Standardized uptake value (SUV) mean values in 18FDG high-uptake regions of predicted images (2.45 ± 0.25) were similar to ground-truth results (2.51 ± 0.33). In 2D-based Gamma analysis, the median/mean Gamma Index (<1) passing rate of test images was 96.5%/92.8% using the 5%/5 mm criterion; such result was improved to 99.9%/99.6% when 10%/10 mm was adopted.ConclusionThe developed biologically guided deep learning method achieved post-20-Gy 18FDG-PET image outcome predictions in good agreement with ground-truth results. With the breakdown biological modeling components, the outcome image predictions could be used in adaptive radiotherapy decision-making to optimize personalized plans for the best outcome in the future.

High helium reservoirs in the Four Corners area of the Colorado Plateau, USA

Radiogenic 4He is naturally produced in Earth's crust due to alpha decay of Uranium (U) and Thorium (Th). Helium has unique thermodynamic properties required for the medical imaging industry, aerospace and other fields of high-tech manufacturing, and currently is in increasingly high demand. Despite its economic value, the mechanisms of helium migration and retention in sedimentary basins remain poorly understood.Oil and gas fields with economic helium (>0.3%) concentrations have been discovered in Paleozoic intervals in the Colorado Plateau, southwestern USA. Here we report new noble gas isotope and abundance data for gas samples (n = 31), from actively producing Paleozoic formations within five fields: Ratherford, Tocito Dome, Navajo Springs, Pinta Dome, and Dineh-Bi-Keyah. Helium concentrations range from 0.01% to 7.9% with varying amounts of liquid and gaseous hydrocarbons, N2, and CO2. We present multi-stage gas, water, and oil equilibration models to account for the observed noble gas elemental and isotopic signatures. Oil-dominated systems are explained by a closed system oil/water equilibration and subsequent admixture of air. He-rich dry gas samples exhibit uniform 4He/N2 ratios consistent with the regional mean values, suggesting a common crustal source and no subsequent fractionation. In contrast, air-derived 20Ne/36Ar ratios are highly fractionated. These observations are consistent with a tectonically controlled crustal gas release from the basement, groundwater saturation with 4He and N2, and subsequent degassing. Extensive gas-water interaction (i.e., migration) leads to extreme fractionation of 20Ne/36Ar, but does not affect 4He/N2 due to water saturation with crustal gases released from the basement.We show the volume of rock required to have produced helium in the reservoir to be significantly larger than the current reservoir volume immediately beneath the field. Therefore, the reservoir helium concentration cannot be sourced by in-reservoir decay of U and Th and instead requires a process to incorporate exogenous sources of helium in the reservoir without significant dilution from hydrocarbons. For helium-rich fields, excess helium is sourced from the Precambrian granitic basement likely utilizing a large area beneath the field area (i.e., crustal gas mobilization and transport via fracture zones), consistent with the degree of water contact. Deep crustal faults in the Precambrian basement are in close proximity to the high helium fields, indicating that these structures are potentially serving as primary migration conduits via advective fluid flow.

Modeled approaches to estimating blue carbon accumulation with mangrove restoration to support a blue carbon accounting method for Australia

AbstractThe development and refinement of methods for estimating organic carbon accumulation in biomass and soils during mangrove restoration and rehabilitation can encourage uptake of restoration projects for their ecosystem services, including those of climate change mitigation, or blue carbon. To support the development of a blue carbon method for Australia under the Emission Reduction Fund scheme we investigated; (1) whether carbon accumulation data from natural mangroves could be used to estimate carbon accumulation during restoration; (2) modeling mangrove biomass accumulation; and (3) how modeled carbon accumulation could be achieved over heterogeneous sites. First, we assessed carbon accumulation in soil and biomass pools from the global literature, finding that estimating carbon accumulation using data from natural mangroves provided similar estimates as those for restored or rehabilitated mangroves. We assessed mangrove biomass accumulation from global chronosequence studies, which we used to develop regional models for estimating biomass accumulation with restoration in Australia using values from local natural mangroves. Estimating biomass carbon accumulation using site‐based means of stand biomass provided similar estimates as values estimated through use of regional means values stratified by elevation; and reduced overestimates of biomass carbon accumulation that were based on regional mean values. Modeling soil carbon accumulation over environmentally heterogeneous project sites can apply a similar approach, stratifying over variation in site elevation. Our analysis provides a strategy for modeling blue carbon pools for an Australian blue carbon method that accommodates regional differences and is based on data from natural mangroves.

Instability of remote sensing based ecological index (RSEI) and its improvement for time series analysis

With the rapid development of remote sensing technology, the monitoring of land surface ecological status (LSES) based on remote sensing has made remarkable progress, which has a positive contribution on improving the regional ecological environment and promoting the realization of Sustainable Development Goals (SDGs). Among them, the proposed Remote Sensing-based Ecological Index (RSEI) becomes the most widely used model in the current application of remote sensing-based LSES monitoring due to its complete derived from remote sensing images and no subjective intervention. RSEI is not flawless either, and it still suffers from some uncertainties in its application in multiple scenarios. However, compared to the extensive applied research, work on the instability assessment and improvement of RSEI is particularly scarce and urgently needed. Therefore, in this paper, we analyzed the possible instabilities in the RSEI calculation process and proposed various inversion models to evaluate their accuracy and stability in time-series LSES monitoring. The results indicated that the existing normalized RSEI is relatively stable for the characterization of single-phase LSES, however, there is a high risk in the time-series analysis or cross-regional comparison due to the interference of component extremes. The standard deviation discretized DRSEIs proposed in this paper perform better in both single-phase and long-term dynamics LSES assessments and are more consistent with the real land cover changes. Also, compared with the approach that measures LSES dynamics using time-series regional RSEI mean values, the DRSEIs change detection results can reveal the spatial heterogeneity of regional LSES dynamics more effectively and provide a finer reference for the formulation and implementation of ecological protection policies.

Radiomics Analysis of Magnetic Resonance Proton Density Fat Fraction for the Diagnosis of Hepatic Steatosis in Patients With Suspected Non-Alcoholic Fatty Liver Disease.

This study aimed to assess the diagnostic feasibility of radiomics analysis based on magnetic resonance (MR)-proton density fat fraction (PDFF) for grading hepatic steatosis in patients with suspected non-alcoholic fatty liver disease (NAFLD). This retrospective study included 106 patients with suspected NAFLD who underwent a hepatic parenchymal biopsy. MR-PDFF and MR spectroscopy were performed on all patients using a 3.0-T scanner. Following whole-volume segmentation of the MR-PDFF images, 833 radiomic features were analyzed using a commercial program. Radiologic features were analyzed, including median and mean values of the multiple regions of interest and variable clinical features. A random forest regressor was used to extract the important radiomic, radiologic, and clinical features. The model was trained using 20 repeated 10-fold cross-validations to classify the NAFLD steatosis grade. The area under the receiver operating characteristic curve (AUROC) was evaluated using a classifier to diagnose steatosis grades. The levels of pathological hepatic steatosis were classified as low-grade steatosis (grade, 0-1; n = 82) and high-grade steatosis (grade, 2-3; n = 24). Fifteen important features were extracted from the radiomic analysis, with the three most important being wavelet-LLL neighboring gray tone difference matrix coarseness, original first-order mean, and 90th percentile. The MR spectroscopy mean value was extracted as a more important feature than the MR-PDFF mean or median in radiologic measures. Alanine aminotransferase has been identified as the most important clinical feature. The AUROC of the classifier using radiomics was comparable to that of radiologic measures (0.94 ± 0.09 and 0.96 ± 0.08, respectively). MR-PDFF-derived radiomics may provide a comparable alternative for grading hepatic steatosis in patients with suspected NAFLD.

Nitrous oxide emissions from agricultural soils challenge climate sustainability in the US Corn Belt

Agricultural landscapes are the largest source of anthropogenic nitrous oxide (N2O) emissions, but their specific sources and magnitudes remain contested. In the US Corn Belt, a globally important N2O source, in-field soil emissions were reportedly too small to account for N2O measured in the regional atmosphere, and disproportionately high N2O emissions from intermittent streams have been invoked to explain the discrepancy. We collected 3 y of high-frequency (4-h) measurements across a topographic gradient, including a very poorly drained (intermittently flooded) depression and adjacent upland soils. Mean annual N2O emissions from this corn-soybean rotation (7.8 kg of N2O-N ha-1⋅y-1) were similar to a previous regional top-down estimate, regardless of landscape position. Synthesizing other Corn Belt studies, we found mean emissions of 5.6 kg of N2O-N ha-1⋅y-1 from soils with similar drainage to our transect (moderately well-drained to very poorly drained), which collectively comprise 60% of corn-soybean-cultivated soils. In contrast, strictly well-drained soils averaged only 2.3 kg of N2O-N ha-1⋅y-1 Our results imply that in-field N2O emissions from soils with moderately to severely impaired drainage are similar to regional mean values and that N2O emissions from well-drained soils are not representative of the broader Corn Belt. On the basis of carbon dioxide equivalents, the warming effect of direct N2O emissions from our transect was twofold greater than optimistic soil carbon gains achievable from agricultural practice changes. Despite the recent focus on soil carbon sequestration, addressing N2O emissions from wet Corn Belt soils may have greater leverage in achieving climate sustainability.

Vertical Mixing and Heat Fluxes Conditioned by a Seismically Imaged Oceanic Front

The southwest Atlantic gyre connects several distinct water masses, which means that this oceanic region is characterized by a complex frontal system and enhanced water mass modification. Despite its significance, the distribution and variability of vertical mixing rates have yet to be determined for this system. Specifically, potential conditioning of mixing rates by frontal structures, in this location and elsewhere, is poorly understood. Here, we analyze vertical seismic (i.e., acoustic) sections from a three-dimensional survey that straddles a major front along the northern portion of the Brazil-Falkland Confluence. Hydrographic analyses constrain the structure and properties of water masses. By spectrally analyzing seismic reflectivity, we calculate spatial and temporal distributions of the dissipation rate of turbulent kinetic energy, ε, of diapycnal mixing rate, K, and of vertical diffusive heat flux, FH. We show that estimates of ε, K, and FH are elevated compared to regional and global mean values. Notably, cross-sectional mean estimates vary little over a 6 week period whilst smaller scale thermohaline structures appear to have a spatially localized effect upon ε, K, and FH. In contrast, a mesoscale front modifies ε and K to a depth of 1 km, across a region of O(100) km. This front clearly enhances mixing rates, both adjacent to its surface outcrop and beneath the mixed layer, whilst also locally suppressing ε and K to a depth of 1 km. As a result, estimates of FH increase by a factor of two in the vicinity of the surface outcrop of the front. Our results yield estimates of ε, K and FH that can be attributed to identifiable thermohaline structures and they show that fronts can play a significant role in water mass modification to depths of 1 km.