Proportion Of Class Research Articles

Dynamics of HLA and angiotensin II type 1 receptor antibodies during pregnancy

BackgroundAlloantibodies, especially anti-human leukocyte antigen antibodies (HLA antibodies), and autoantibodies, as angiotensin II type 1 receptor antibodies (AT1R antibodies), may complicate the access and the course of transplantation. Pregnancy is a known source of HLA antibodies, with most studies evaluating pregnancy-induced sensitization by complement-dependent cytotoxicity assays, mainly after childbirth. AT1R antibodies have been evaluated in the context of preeclampsia. We aimed to evaluate pregnancy as a natural source of HLA antibodies and AT1R antibodies, their dynamics along gestation and the potential factors involved in antibody appearance. MethodsSerum samples from pregnant women were collected during the three trimesters of pregnancy (1T, 2T, 3T). Presence of HLA antibodies was assessed by screening beads on Luminex and AT1R antibodies by ELISA. ResultsA cohort of 138 pregnant women were included. Samples from all were tested in 1T, 127 in 2T and 102 in 3T. HLA antibodies increased from 29.7 % (1T) to 38.2 % (3T). AT1R antibodies were stable around 30 % along pregnancy. Up to 43.2 % multiparous women had HLA antibodies, with a similar proportion of class I and class II antibodies. In primiparous women HLA antibodies increased along pregnancy (from 17.6 % to 34.1 %), with predominance of class II HLA antibodies. AT1R antibodies were not different in primiparous and multiparous women. ConclusionsPregnancy is a relevant source of HLA antibodies sensitization, but not of AT1R antibodies. HLA antibodies increased clearly in primiparous women with predominance of class II. The use of newer solid-phase techniques on Luminex evidence a higher degree of HLA sensitization during pregnancy.

Dietary polyphenol intake in the Canadian population: Findings from the 2015 Canadian Community Health Survey-Nutrition.

This study aimed to estimate usual polyphenol intake among Canadians using the nationally representative 2015 Canadian Community Health Survey-Nutrition and to explore the main dietary contributors to polyphenol intake and the sociodemographic and lifestyle factors that may impact polyphenol intake. Dietary information was collected from 19,409 respondents using 24-h dietary recalls. The polyphenol content of foods was estimated using the Phenol-Explorer Database (version 3.6). Daily intake values for total polyphenols (adjusted to energy intake), main classes, and subclasses were calculated for each respondent and dietary recall. Usual intake was estimated by age/sex groups and by sociodemographic and lifestyle characteristics independently for adults and children using the National Cancer Institute method. Given-day arithmetic mean polyphenol intakes and mean proportions of main classes contributing to sum total polyphenol intakes were explored. Population proportions were used to determine dietary contributors. Usual total polyphenol intake was 1119.3mg/1000kcal/day (95% CI: 1090.5, 1148.1) for adults ≥ 19years and 473.0mg/1000kcal/day (95% CI: 454.9, 491.0) for children 2‒18years. Generally, total polyphenol intakes differed by age, sex, ethnicity, and household education status and were higher among coffee and tea consumers. Most polyphenols came from flavonoids (40.0%) and phenolic acids (49.8%), with children consuming more flavonoids and other polyphenols and adults more phenolic acids. The top food contributors to polyphenol intake were coffee (26.8%), tea (8.9%), fruit juice (4.2%), banana (4.1%), and apple (3.8%). Usual intake of total polyphenols among Canadians differed primarily by age. Non-alcoholic beverages were top contributors to total polyphenol intake.

Effect of elevated temperature on concrete incorporating zeolite, silica fume and fly ash as replacement for cement

In this study, the effect of utilizing zeolite and industrial by-products, silica fume, and Class C fly ash, as partial replacement for cement is investigated at room and elevated temperatures of 200°C, 400°C, and 600°C. Four different high-strength concrete mixes of M50 concrete grade with varying proportions of zeolite, silica fume, and Class C fly ash are tested and observed for workability, compressive strength, and microstructural characteristics using Scanning Electron Microscope analysis, and the optimum mix has arrived. The results indicate that the addition of zeolite, silica fume, and fly ash resulted in lesser early-age strength development but the strength after 28 days of curing is found satisfactory and the desired target strength is achieved. Temperature rise resulted in degradation of concrete properties for both conventional and optimum mix but the concrete cubes with 10% of zeolite, 7.5% of silica fume, and 10% of fly ash have higher retainment of strength at elevated temperatures compared with conventional mix. The results from the microstructural study are found to correlate with strength test results. Incorporation of 10% zeolite, 7.5% silica fume, and 10% fly ash improved mechanical and microstructural characteristics at room and elevated temperature, however, the replacement is effective for 28 days of curing.

An automated method for tendon image segmentation on ultrasound using grey-level co-occurrence matrix features and hidden Gaussian Markov random fields

Background:Despite knowledge of qualitative changes that occur on ultrasound in tendinopathy, there is currently no objective and reliable means to quantify the severity or prognosis of tendinopathy on ultrasound. Objective:The primary objective of this study is to produce a quantitative and automated means of inferring potential structural changes in tendinopathy by developing and implementing an algorithm which performs a texture based segmentation of tendon ultrasound (US) images. Method:A model-based segmentation approach is used which combines Gaussian mixture models, Markov random field theory and grey-level co-occurrence (GLCM) features. The algorithm is trained and tested on 49 longitudinal B-mode ultrasound images of the Achilles tendons which are labelled as tendinopathic (24) or healthy (25). Hyperparameters are tuned, using a training set of 25 images, to optimise a decision tree based classification of the images from texture class proportions. We segment and classify the remaining test images using the decision tree. Results:Our approach successfully detects a difference in the texture profiles of tendinopathic and healthy tendons, with 22/24 of the test images accurately classified based on a simple texture proportion cut-off threshold. Results for the tendinopathic images are also collated to gain insight into the topology of structural changes that occur with tendinopathy. It is evident that distinct textures, which are predominantly present in tendinopathic tendons, appear most commonly near the transverse boundary of the tendon, though there was a large variability among diseased tendons. Conclusion:The GLCM based segmentation of tendons under ultrasound resulted in distinct segmentations between healthy and tendinopathic tendons and provides a potential tool to objectively quantify damage in tendinopathy.

A systematic review and meta-analysis of sex differences in clinical outcomes of hypertrophic cardiomyopathy.

Hypertrophic cardiomyopathy (HCM) is recognized as the most prevalent form of genetic cardiomyopathy, and recent investigations have shed light on the existence of sex disparities in terms of clinical presentation, disease progression, and outcomes. This study aimed to systematically review the literature and perform a meta-analysis to comprehensively compare the clinical outcomes between female and male patients with HCM. A thorough search was conducted in databases including PubMed, Embase, Cochrane Library, and Web of Science, encompassing literature from inception until June 2023. The primary endpoints examined were: (1) all-cause mortality; (2) an arrhythmic endpoint comprising sudden cardiac death (SCD), sustained ventricular tachycardia, ventricular fibrillation, or aborted SCD; and (3) a composite endpoint incorporating either (1) or (2), in addition to hospitalization for heart failure or cardiac transplantation. Pooled estimates were derived using a random-effects meta-analysis model. The analysis encompassed a total of 29 observational studies, involving 44,677 patients diagnosed with HCM, of which 16,807 were female. Baseline characteristics revealed that the female group exhibited an advanced age [55.66 ± 0.04 years vs. 50.38 ± 0.03 years, pooled mean difference (MD) = 0.31, 95% CI: 0.22-0.40, p = 0.000, I2 = 88.89%], a higher proportion of New York Heart Association class III/IV patients [pooled odds ratio (OR) = 1.94, 95% CI: 1.55-2.43, p = 0.000, I2 = 85.92%], and a greater prevalence of left ventricular outflow tract gradient greater than or equal to 30 mmHg (pooled OR = 1.48, 95% CI: 1.27-1.73, p = 0.000, I2 = 68.88%) compared to the male group. The female group were more likely to have a positive genetic test (pooled OR = 1.27, 95% CI: 1.08-1.48, p = 0.000, I2 = 42.74%) and to carry the myosin heavy chain beta 7 mutation (pooled OR = 1.26, 95% CI: 1.04-1.54, p = 0.020, I2 = 0.00%) compared to the male group. Female sex exhibited a significant association with increased risks of all-cause mortality (pooled OR = 1.62, 95% CI: 1.38-1.89, p = 0.000, I2 = 72.78%) and the composite endpoint (pooled OR = 1.47, 95% CI: 1.20-1.79, p = 0.000, I2 = 84.96%), while no substantial difference was observed in the arrhythmic endpoint (pooled OR = 1.08, 95% CI: 0.87-1.34, p = 0.490, I2 = 55.48%). The present findings suggest that female patients with HCM tend to experience poorer clinical outcomes. It is imperative to critically reevaluate disease definitions and enhance awareness to mitigate delays in the diagnosis and treatment of HCM in women, thereby fostering equitable healthcare practices. https://www.crd.york.ac.uk/, PROSPERO (CRD42023431881).

Influence of Maceration Solvent on Chemical Composition of Gemmotherapy Macerates—A Case Study on Olea europaea Young Shoots

Gemmotherapy, a natural therapy based on bud macerates, has recently gained importance in the field of food supplements. However, two coexisting extraction methods employ a glycerin-based solvent, either in a binary or ternary solvent mixture. The absence of an official method for bud preparation leads to non-standardized bud macerates. Given this context, this study aimed to (i) assess the influence of solvent composition on the chemical profile of olive young shoot macerates obtained using glycerin-based solvents or using different solvent extractions and (ii) to compare the two coexisting traditional bud extraction methods described by Dr Pol Henry and by the European Pharmacopoeia. A comprehensive phytochemical analysis of all macerates was conducted using HPLC-DAD-ELSD-MS2, identifying 50 metabolites divided into 7 classes through dereplication. The extracts obtained with the solvent described by the European Pharmacopoeia (ethanol/glycerin) and by Dr Pol Henry (water/ethanol/glycerin) appeared to be the most diversified in terms of metabolite distribution and possessed higher rates of secondary metabolites. These observations reinforce the interest in a glycerin-based solvent mixture for bud extraction in gemmotherapy. In addition, the difference in composition between the two traditional solvents was highlighted. Indeed, iridoids were predominant in both macerates, representing about 50% of the chemical composition, but differences were observed from one macerate to another regarding the proportions of the other chemical classes. This emphasizes the necessity for standardized gemmotherapy macerates.

Detecting land use land cover using supervised maximum likelihood algorithm on spatiotemporal imagery in Samarinda, Indonesia

Land use change commonly has an impact on urban areas. The land use and land cover (LULC) model should be used to address land problems. Land conversion is inextricably linked to Samarinda, Indonesia, the administrative center of the province of East Kalimantan. Additionally, this city serves as the new capital city’s Ibu Kota Nusantara-specific buffer zone. The current study aims to find and assess Samarinda City’s LULC. A supervised maximum likelihood technique was used to extract this data from spatiotemporal images. Both spatial and non-spatial data about changes in LULC are used in this study. The imagery data for the Samarinda region includes Landsat 5, 7, and 9 images from 1994 to 2022, along with administrative maps and GPS measurement data enabling on-the-ground checkpoints. Before classification analysis, radiometric and atmospheric correction, cropping, and layer stacking procedures were used to treat the image data. In supervised classification, the maximum likelihood method is applied to the four land classes of uncultivated vegetation, cultivated vegetation, waterbodies, and land with buildings. The research result indicates that the number of uncultivated land classes decreased by 6.38 percent and the percentage of cultivated land decreased by 5.52 percent, according to the study’s findings. On the other hand, the proportion of water bodies increased by 2.39 percent, and the proportion of built-up land classes increased by 9.51 percent. The overall and kappa accuracy test’s average value is 97.67%, higher than the required minimum of 75%.

Evolution of chlorinated paraffin and olefin fingerprints in sewage sludge from 1993 to 2020 of a Swiss municipal wastewater treatment plant

Exposure of humans to chlorinated paraffins (CPs) and chlorinated olefins (COs) can occur via contact with CP-containing plastic materials. Such plastic materials can contain short-chain CPs (SCCPs), which are regulated as persistent organic pollutants (POPs) under the Stockholm Convention since 2017. Municipal wastewater treatment plants (WWTP) collect effluents of thousands of households and their sludge is a marker for CP exposure. We investigated digested sewage sludge collected in the years 1993, 2002, 2007, 2012, and 2020 from a Swiss WWTP serving between 20000 and 23000 inhabitants. A liquid chromatography mass spectrometry (R > 100000) method, in combination with an atmospheric pressure chemical ionization source (LC-APCI-MS), was used to detect mass spectra of CPs and olefinic side products. A R-based automated spectra evaluation routine (RASER) was applied to search for ∼23000 ions whereof ∼6000 ions could be assigned to CPs, chlorinated mono- (COs), di- (CdiOs) and tri-olefins (CtriOs). Up to 230 CP-, 120 CO-, 50 CdiO- and 20 CtriO-homologues could be identified in sludge. Characteristic fingerprints were deduced describing C- and Cl-homologue distributions, chlorine- (nCl) and carbon- (nC) numbers of CPs and COs. In addition, proportions of saturated and unsaturated material were determined together with proportions of different chain length classes including short- (SC), medium- (MC), long- (LC) and very long-chain (vLC) material. A substantial reduction of SCCPs of 84% was observed from 1993 to 2020. Respective levels of MCCPs, LCCPs and vLCCPs decreased by 61, 69 and 58%. These trends confirm that banned SCCPs and non-regulated CPs are present in WWTP sludge and higher-chlorinated SCCPs were replaced by lower chlorinated MCCPs. Combining high-resolution mass spectrometry with a selective and fast data evaluation method can produce characteristic fingerprints of sewage sludge describing the long-term trends in a WWTP catchment area.

Estimate of the Vulnerability to Erosion of the Soils in the State of Paraíba

This work estimated the degree of vulnerability to soil erosion (GVES) based on the relationship between the natural erosion potential (PNE) and the soil loss tolerance limit (LTP), applied to the State of Paraíba using geoprocessing techniques for modeling the data based on information contained in the representative profiles of the Soil Bulletins of the State of Paraíba and the Agricultural Zoning of the State of Paraíba and on rainfall and altitude data. The results showed that the use of geoprocessing and kriging techniques allowed estimating and mapping the degree of vulnerability to soil erosion. The K Factor, even appearing in the very high class observed by the R and S Factors, leading the LTP to the Degree of Vulnerability to Soil Erosion (GVES) to present itself in good proportion in the middle class, smoothing the result. Despite its limitations, the information generated in this study of the knowledge of the spatial variability of vulnerability can be used in decision-making and serve as support for conservation planning, thus being able to develop strategies for management and conservation of soil and water. The distribution was symmetrical, the kurtosis indicated a platykurtic distribution, where the greatest variations in amplitude and irregular distribution were present in the variables Factor K and LTP. The greatest regularity was in Factor R, in which the Shapiro-Wilk test showed the smallest difference between them. It could be said that there is similarity and agreement between the tests used in this work and led to accept the normality of the data.

Comparison of Methotrexate Maintenance Versus Autologous Stem Cell Transplant Consolidation after High-Dose Methotrexate-Based Induction Therapy in Primary Central Nervous System Lymphoma

Background: Primary central nervous system lymphoma (PCNSL) is a rare form of non-Hodgkin lymphoma with historically poor outcomes. Induction therapy with high-dose methotrexate (HD-MTX)-based regimens followed by consolidation with autologous stem cell transplant (auto-SCT) has become the mainstay of treatment with overall response rates (ORR) of 69-87% and two-year overall survival (OS) of 66-70% reported in prospective clinical trials. Limited data are available regarding a maintenance approach with single-agent HD-MTX, particularly in patients who are not auto-SCT candidates. Herein, we describe a comparison of outcomes in patients with PCNSL who underwent HD-MTX-based induction followed by either HD-MTX maintenance or auto-SCT consolidation at Mayo Clinic, Rochester. Methods: Patients with a diagnosis of PCNSL who received HD-MTX as part of induction therapy at Mayo Clinic between October 2010 and June 2022 were identified. Patients with prior or concurrent diagnosis of systemic lymphoma were excluded. Primary endpoints were progression-free survival (PFS) defined as time from post-induction treatment initiation to relapse, progression, or death due to any cause; and OS defined as time from post-induction treatment initiation to death due to any cause. We compared baseline characteristics by post-induction therapy using descriptive statistics. The primary endpoints PFS and OS were evaluated using Kaplan-Meier curves and compared by risk scores using a log-rank test. Results: A total of 148 patients were identified (51% female, 95% white) with median age at diagnosis of 66 years (range 29-85), with 48 patients (32%) age > 70. Most patients had multifocal disease (n=89, 60%) and deep brain involvement (n=100, 70%) at diagnosis. Few had vitreoretinal (n=15, 10%) or CSF involvement (n=9, 6%) at diagnosis. Using the Memorial Sloan Kettering (MSKCC) prognostic score for PCNSL, 35 patients (26%) scored class 3 (poor prognosis), 85 (62%) scored class 2, and 17 (12%) scored class 1. In total, 117 patients (79%) received methotrexate, rituximab, and temozolomide (MRT) induction therapy, and the remaining 31 patients (21%) received methotrexate and rituximab (MR) induction therapy (Table 1). A total of 70 patients (47%) underwent consolidation with auto-SCT and 37 patients (25%) received maintenance methotrexate. The patients who received maintenance methotrexate had higher median age of 72 versus 62 years, higher proportion of patients older than 70 (54% versus 16%, p<0.001), higher proportion of MSKCC prognostic score class 3 patients (33% versus 17%, p=0.026), and trend towards higher proportion of patients ECOG 2 or higher (41% versus 29%, p=0.109). A higher proportion of patients who underwent auto-SCT received MRT (vs MR) induction (n=64, 91%) compared to those who received maintenance methotrexate (n=24, 65%, p=0.004) (Table 1). The median follow-up for all patients was 4.5 years. At 1-, 3-, and 5-years post-induction treatment initiation, the PFS in the auto-SCT cohort was 85.8% (95% CI 77.7-94.9), 81.0% (95% CI 72.0-91.0), and 74.6% (95% CI 63.3-87.9), respectively; and the PFS in the HD-MTX maintenance cohort was 88.6% (95% CI 78.7-99.8), 72.6% (95% CI 58.8-89.8), and 72.6% (95% CI 58.8-89.8), respectively. At the same time points, the OS in the auto-SCT cohort was 94.0% (95% CI 88.4-99.9), 81.3% (95% CI 71.8-92.0), and 76.0% (95% CI 65.0-89.0), respectively; and the OS in the HD-MTX maintenance cohort was 94.3% (95% CI 86.9-100.0), 87.5% (76.8-99.8%), and 82.4% (69.0-98.4), respectively. Overall, there was no significant difference in PFS (p=0.64) or OS (p=0.95) based on post-induction treatment (Figure 1). Conclusions: Our study demonstrates comparable outcomes in PCNSL between a post-induction treatment approach with maintenance HD-MTX and consolidation auto-SCT, even though baseline characteristics indicate that patients who went on to receive auto-SCT were younger and had overall better performance status. This suggests that maintenance HD-MTX is a reasonable, time-limited strategy for patients with PCNSL responding to initial induction therapy, particularly in patients who are not candidates for auto-SCT.

Role of magnetic resonance imaging in characterization of cystic renal lesions based on Bosniak classification version 2019

BackgroundIn 2019, the Bosniak classification system for cystic renal lesions underwent modifications aimed at addressing the limitations of the original classification.ResultsThe revised 2019 version demonstrated notable differences from its predecessor. Specifically, it showed an increased proportion of class IIF cystic lesions (31% compared to 16.7%) and a decreased proportion of class III cystic lesions (27.4% compared to 45.2%). Additionally, the malignancy rate for class III cystic renal lesions was lower in the 2019 version (37.8% vs. 42.2%). When it came to diagnosing malignancies, the 2019 version exhibited higher specificity (74.4% compared to 41.03%) while maintaining a comparable sensitivity (97.8% vs. 100%) compared to the original Bosniak system.ConclusionsThe Bosniak 2019 version demonstrated enhanced specificity and diagnostic accuracy for malignancies in comparison to the original Bosniak system, all while maintaining an equivalent sensitivity.

Untangling the impacts of land cover representation and resampling in distributed hydrological model predictions

Accurate land cover information is essential for hydrometeorological modeling, as it defines parameters governing land-atmosphere-vegetation interactions, water partitioning, and routing. This study presents a controlled sensitivity analysis that evaluated the impact of land cover resampling methods on hydrologic simulations within the WRF-Hydro/NWM framework. The choice of resampling algorithms affected simulations but was generally limited to arid environments, catchments featuring minor land cover classes with high hydrologic impact, or low-flow predictions. We tested two distinct spatial aspects: areal proportions of land cover classes and spatial patterns in land cover. Areal proportions influenced vertical hydrologic fluxes at the catchment scale and subsequently affected streamflow characteristics. In contrast, spatial arrangement alone had a marginal impact on vertical fluxes but could still induce limited alterations in streamflow characteristics through routing processes. These results suggest that spatially distributed land cover, as used in physics-based model structures, has a limited impact on watershed-scale hydrologic simulations.

Differential patterns of lifestyle behaviors among low- and high-income postmenopausal women in Korea: a latent class analysis

BackgroundHealthy lifestyle behaviors among postmenopausal women are important to prevent chronic diseases and improve health later in life. Heterogeneous lifestyle patterns may exist among postmenopausal women, and socioeconomic status (SES) is a critical determinant of lifestyle behaviors. However, little is known about distinct SES-specific patterns of lifestyle behaviors among postmenopausal women. Thus, this study used latent class analysis to identify subgroups of postmenopausal women with different health behaviors according to income and to examine the predictors of income-specific subgroups.MethodsWe analyzed nationally representative data from the Eighth Korea National Health and Nutrition Examination Survey, collected in 2019 and 2020. We used nine lifestyles (i.e., current smoking and drinking, high-risk drinking, walking, muscle-strengthening exercise, sleep, vegetable and fruit intakes, and weight control efforts). We conducted a multiple-group latent class analysis using monthly household income as a proxy for SES. The monthly household income variable was calculated by standardizing monthly household income by the number of family members and then divided into quintiles. We classified the participants into low- (i.e., Q1 and Q2) and high-income (i.e., Q3, Q4, and Q5) groups.ResultsAlthough the three-class models best fit the data of low- and high-income groups, we found differential patterns by income: (a) for low-income group, “relatively healthy (RH),” “lowest physical activity, insufficient fruit intake, and no intention to control weight,” and “high-risk drinking and insufficient fruit intake” classes and (b) for high-income group, “RH,” “lowest physical activity,” “high-risk drinking and insufficient fruit intake and sleep” classes. The proportion of the RH class was largest in both groups. However, lifestyle patterns in low-income group showed multiple and unhealthy characteristics than those in high-income group.ConclusionsThis study suggests that different underlying lifestyle patterns exist in postmenopausal women with low- and high-income. To promote healthy behaviors among postmenopausal women, health professionals should develop and apply lifestyle interventions tailored to lifestyle pattern characteristics according to income.

Analysis of heterogeneous vehicular traffic: Using proportional densities

This paper presents a multi-class Aw–Rascle (AR) model with area occupancy expressed in terms of vehicle class proportions. Two vehicle classes that is; cars and motorcycles are considered based on an assumption that proportions of these form total traffic density. Qualitative properties of the proposed equilibrium velocity are established. Conditions under which the proposed model is stable are determined by linear stability analysis. To compute numerical flux, the model is decomposed by original Roe decomposition, where Roe matrix, averaged data variables and wave strengths are explicitly derived. The Roe matrix is shown to be hyperbolic, consistent and conservative. From the numerical results, the effect of proportional densities on the flow of vehicle classes is determined. Results obtained remain within limits therefore, the proposed model is realistic.

NIMG-12. SPATIALLY MAPPING TREATMENT-EFFECT IN RECURRENT GLIOMA WITH PHYSIOLOGIC MRI AND DEEP LEARNING

Abstract INTRODUCTION Discriminating between glioma tumor recurrence (rTumor) and treatment-induced effects (TxE) from chemo and radiotherapy using MRI is an ongoing challenge in neuro-oncology. Although deep learning has been used to characterize suspicious lesions, these models typically do not account for lesions that are comprised of mixtures of rTumor and TxE components. We hypothesize that using an approach that includes using tissue samples with known location on MRI, incorporating perfusion-weighted and diffusion-weighted with anatomical MRI, self-supervised pretraining, and a novel ensembling strategy will improve performance and attain spatial maps of rTumor and TxE for determining subsequent treatment. METHODS Using 218 pathology confirmed tissue samples with coordinates on multi-parametric MRI from 111 patients with suspected tumor progression, we developed a deep learning approach to spatially map intratumoral regions of rTumor and TxE. Our model leveraged 10mm isotropic cubes centered on the tissue sample coordinates that includes Diffusion-Weighted and Dynamic Susceptibility-Contrast Perfusion MRI and large amounts of pathologically unlabeled data from the lesion in self-supervised pretraining. The multiple networks of the ensemble were generated through repeated constrained cross validation (RC-CV) which enabled unique repetitions of training with more variation in class proportions. RESULTS Our best classifier performed with a RC-CV/test AUROC of 0.85/0.81 and was able to generate maps of tumor probability as well as ensenble variance and uncertainty. Ensemble variance was significantly higher in prediction failures of rTumor (P=.006) and epistemic uncertainty was significantly higher (P=.002) in prediction failures of TxE in training. Test Performance dropped by 14.7% when removing self-supervised pretraining, 21.3% when removing physiological imaging contrasts, and 1.2% when ensembling across standard 4-fold CV. CONCLUSION The AUROC of .81 supports the feasibility of discriminating between TxE and rTumor within a single lesion non-invasively. Physiologic MRI, pretraining on pathology unlabeled data, and ensembling networks, improve performance and help characterize model failures.

Moderate-to-vigorous intensity physical activity levels of children with intellectual disability during physical education classes.

Physical education (PE) class is an excellent way to improve moderate-to-vigorous intensity physical activity (MVPA). Increasing number of research has explored the children's PA based on movement during PE classes, but data for children with intellectual disability (ID) is still lacking. The purpose of this study was to investigate the current status of MVPA levels of children with ID during PE classes in China, as well as differences of MVPA levels according to gender and grade. Accelerometers were used to record MVPA levels of fifty-three children with severe ID from 9 to 16 years of age (mean age: 12.60 ± 1.66 years) during standard PE classes. The mean time spent in MVPA during PE classes was 8.00 ± 2.10 min, meaning only 22.88% of PE class time was spent in MVPA. As grade levels progresses, time spent in MVPA during PE classes tended to decrease; the fourth-grade children tended to spend more time in MVPA during PE classes compared with the fifth-grade and the sixth-grade (9.15 vs. 7.61 vs. 7.25 min, all p < 0.05). Boys spend significantly more time in MVPA during PE classes than girls; both in the entire sample (9.20 vs. 5.70 min) as well as in each grade (9.76 vs. 6.09 min, 9.35 vs. 5.68 min, 8.31 vs. 5.59 min, all p < 0.05). Findings from this study indicate that the proportion of PE class spent in the MVPA of children with ID was lower than the 50% recommended by the U.S. Department of Health and Human Services (DHHS) and U.K. Association for Physical Education (AfPE). And the amount of MVPA participation varied by the grade and gender as well as by the activity performed. Therefore, in order to help children with ID achieve MVPA goals, educators need to reevaluate the PE curriculum as well as take due consideration of grade and gender when devising new content.

Synthetically induced Arabidopsis thaliana autotetraploids provide insights into the analysis of meiotic mutants with altered crossover frequency.

Mutations affecting crossover (CO) frequency and distribution lead to the presence of univalents during meiosis, giving rise to aneuploid gametes and sterility. These mutations may have a different effect after chromosome doubling. The combination of altered ploidy and mutations could be potentially useful to gain new insights into the mechanisms and regulation of meiotic recombination; however, studies using autopolyploid meiotic mutants are scarce. Here, we have analyzed the cytogenetic consequences in colchicine-induced autotetraploids (colchiploids) from different Arabidopsis mutants with an altered CO frequency. We have found that there are three types of mutants: mutants in which chiasma frequency is doubled after chromosome duplication (zip4, mus81), as in the control; mutants in which polyploidy leads to a higher-than-expected increase in chiasma frequency (asy1, mer3, hei10, and mlh3); and mutants in which the rise in chiasma frequency produced by the presence of two extrachromosomal sets is less than doubled (msh5, fancm). In addition, the proportion of class I/class II COs varies after chromosome duplication in the control. The results obtained reveal the potential of colchiploid meiotic mutants for better understanding of the function of key proteins during plant meiosis. This is especially relevant considering that most crops are polyploids.

News-On-Clix: Enrich Multi-Category News Aggregation with Fake News Detector to Curb Spreading of Misinformation

In the era of Technology &amp; Information, with rapid grow in number of social media platforms &amp; user’s using them, the information which is being produced to each &amp; every user is very important and sensitive as it can lead to various serious consequences. Misinformation is spread intentionally to disturb the harmony and peace also they hide their anonymity which gives them the advantage to do it on large scale. Our model contrasts from other models in-terms of imbalanced data which leads to skewed class proportions creating uneven curve distribution as well as offers a news classification on various domains such as Politics, Sports, Entertainment, Business, Health, etc. “Fake news can imply things like- a mistake, intentional misleading, twisting a new story, or a complete lie”, also panic which was created during the Covid-19 pandemic is not less. Hence our project aims to focus on identifying fake news using the fake news detector so that people who want to have a reality check on specific news of any related topic can verify and get to know whether the information spreading is true or false

Do we really need dice? The hidden region-size biases of segmentation losses

Most segmentation losses are arguably variants of the Cross-Entropy (CE) or Dice losses. On the surface, these two categories of losses (i.e., distribution based vs. geometry based) seem unrelated, and there is no clear consensus as to which category is a better choice, with varying performances for each across different benchmarks and applications. Furthermore, it is widely argued within the medical-imaging community that Dice and CE are complementary, which has motivated the use of compound CE-Dice losses. In this work, we provide a theoretical analysis, which shows that CE and Dice share a much deeper connection than previously thought. First, we show that, from a constrained-optimization perspective, they both decompose into two components, i.e., a similar ground-truth matching term, which pushes the predicted foreground regions towards the ground-truth, and a region-size penalty term imposing different biases on the size (or proportion) of the predicted regions. Then, we provide bound relationships and an information-theoretic analysis, which uncover hidden region-size biases: Dice has an intrinsic bias towards specific extremely imbalanced solutions, whereas CE implicitly encourages the ground-truth region proportions. Our theoretical results explain the wide experimental evidence in the medical-imaging literature, whereby Dice losses bring improvements for imbalanced segmentation. It also explains why CE dominates natural-image problems with diverse class proportions, in which case Dice might have difficulty adapting to different region-size distributions. Based on our theoretical analysis, we propose a principled and simple solution, which enables to control explicitly the region-size bias. The proposed method integrates CE with explicit terms based on L1 or the KL divergence, which encourage segmenting region proportions to match target class proportions, thereby mitigating class imbalance but without losing generality. Comprehensive experiments and ablation studies over different losses and applications validate our theoretical analysis, as well as the effectiveness of explicit and simple region-size terms. The code is available at https://github.com/by-liu/SegLossBias .

Chemical elucidation of recycled plastic pyrolysis oils by means of GC×GC-PI-TOF-MS and GC-VUV

Detailed chemical characterization of the composition of pyrolysis oils produced from plastics is a mandatory step in understanding the recycling process. Even though the chemical composition of pyrolysis plastic waste oils shows similarities with fossil-based oils, e.g. PIONA related compounds, the relative proportions of the chemical classes are significantly different, resulting in important changes in the global properties of these fluids. In this context, an analytical method based on comprehensive two-dimensional gas chromatography (GC×GC), coupled with photoionization (PI) – time-of-flight mass spectrometry (TOF MS) was developed to obtain a detailed chemical characterization of plastic pyrolysis-oil. A group-type analysis was achieved thanks to the detection of molecular ions by soft ionization PI-TOF MS. Moreover, olefins were successfully distinguished from naphthenes by in-depth consideration of MS spectra, even though such compounds elute very close in the 2D chromatographic separation space. A part of the olefins identified by PI was further confirmed by GC coupled to vacuum ultraviolet detection (VUV) since olefins VUV spectra differ from other compounds. The overall combination of the entire set of data of this multi-modal approach was valuable in studying the pyrolyzed plastic oil composition. It was furthermore applied to monitor the efficiency of upgrading processes that were applied to the oils to remove specific contaminants such as the diolefins. This approach has the potential to support the production of plastic pyrolysis oils that could efficiently be reintroduced in the market to sustain economic circularity needs.