High Correlation Research Articles

Investigating the Relationship between Urbanization and Air Pollution Using Google Earth Engine Platform: A Case Study of Istanbul

Rapid population growth in megacities such as Istanbul has led to various effects, such as industrialization, urbanization, loss of green areas, increasing vehicle traffic, and higher consumption of fossil fuels. These reasons, along with many other environmental factors, contribute to the rise of air pollution in urban life. This study aimed to examine the relationship between urbanization and air pollution in Istanbul. For this purpose, land cover maps covering Istanbul province were produced using Landsat-5 (TM), Landsat-8 (OLI), and Sentinel-2 (MSI) images for the years 1996 to 2021 at three-year intervals on the Google Earth Engine platform. Land cover for classification purposes was divided into five different classes: forest, water surface, urban area, and bare land, and classified using a random forest machine learning algorithm. To examine the impact of this urban area growth on air pollution, in the second step of the study, the column number density values of Sentinel 5P (TROPOMI) data for SO2, NO2, CO, and O3 gases for 2019, 2020, and 2021 were analyzed. The averages of the data from 39 air pollution monitoring stations across Istanbul were also examined. According to this classification, the urban area expanded from 491 km2 in 1996 to 1222 km2 by 2021. Considering the total surface area of Istanbul province, the urban area, which was 9% in 1996, reached 23% by 2021. The TROPOMI values were calculated as follows: the average column number density values for SO2, NO2, CO, and O3 were 0.0003538 mol/m², 0.0339514 mol/m², 0.0000984 mol/m², and 0.1453515 mol/m², respectively. Similarly, the gas concentrations of SO2, NO2, CO, and O3 measured from the ground stations were calculated as 6.603 µ/m3, 786,815 µ/m3, 43.763 µ/m3 and 45.773 µ/m3, respectively. Correlations between urbanization and TROPOMI values revealed a positive correlation of 0.39, 0.02, and 0.80 for SO2, NO2, and CO gases, while a negative correlation of 0.25 was found for O3 gas. The study also examined correlations between TROPOMI and ground station measurements, resulting in positive correlations of 0.55, 0.66, and 0.16 for SO2, NO2, and CO gases, respectively, while a negative correlation of 0.05 was found for O3 gas. Based on these findings, among the air pollutants studied both through TROPOMI and ground station data, the highest correlation was observed for CO gas.

Effectiveness of Serious Games in Evaluating Cognitive Status of the Elderly: A Systematic Review And Meta-Analysis.

Early diagnosis of mild cognitive impairment (MCI) and Alzheimer's disease (AD) is very important in better management of these diseases, and serious games play an effective role in helping to diagnose these diseases more accurately owing to their innovative features. With respect to the diversity of available games, the purpose of this study was to investigate the effectiveness of using serious games to assess the cognitive status of the elderly at risk of MCI/AD. A systematic review was conducted and the correlation of serious game results with cognitive test scores were extracted from eligible studies for meta-analysis. We analyzed the correlation between the results of serious games with the scores of mini-mental state examination (MMSE), Addenbrooke's Cognitive Examination-revised edition (ACE-R), and Montreal Cognitive Assessment (MoCA) tests to evaluate cognitive status of the elderly at risk of MCI/AD, as well as the cognitive aspects examined by these tests. The random-effects model was used to obtain the overall correlation coefficient to assess the relationship between the results of serious games and the above mentioned paper-and-pencil tests. The correlation of game results with the MMSE, ACE-R, and MoCA was 0.604, 0.682, with 0.682, respectively. The correlation between the results of the games with the score of each cognitive aspect was also calculated. Overall, there is a positive correlation between serious game scores in terms of accurate patients' reactions with the scores of MMSE, ACE-R, and MoCA tests. Among the cognitive aspects, the highest correlation was obtained for fluency (0.591). For abstraction, however, the correlation was the lowest (0.036). In all three tests, the correlation was >0.6 and in cognitive aspects was <0.6. Thus, more studies should be conducted to develop serious games that are more in line with cognitive tests.

Synergistic Mitochondrial Genotoxicity of Carbon Dots and Arsenate in Earthworms Eisenia fetida across Generations: The Critical Role of Binding.

The escalating utilization of carbon dots (CDs) in agriculture raises ecological concerns. However, their combined toxicity with arsenic remains poorly understood. Herein, we investigated the combined mitochondrial genotoxicity of CDs and arsenate at environmentally relevant concentrations across successive earthworm generations. Iron-doped CDs (CDs-Fe) strongly bound to arsenate and arsenite, while nitrogen-doped CDs (CDs-N) exhibited weaker binding. Both CDs enhanced arsenate bioaccumulation without affecting its biotransformation, with most arsenate being reduced to arsenite. CDs-Fe generated significantly more reactive oxygen species than did CDs-N, causing stronger mitochondrial DNA (mtDNA) damage. Arsenate further exacerbated the oxidative mtDNA damage induced by CDs-N, as evidenced by increased reactive oxygen species, elevated 8-oxo-7,8-dihydro-2'-deoxyguanosine (8-OHdG) levels, and a higher correlation between 8-OHdG and mtDNA damage. This was due to arsenic inhibiting the antioxidant enzyme catalase. This exacerbation was negligible with CDs-Fe because their strong binding with arsenic prevented catalase inhibition. Maternal mitochondrial DNA damage was inherited by filial earthworms, which experienced significant weight loss in coexposure groups coupled with mtDNA toxicity. This study reveals the synergistic genotoxicity of CDs and arsenate, suggesting that CDs could disrupt the arsenic biogeochemical cycle, increase arsenate risk to terrestrial animals, and influence ecosystem stability and health through multigenerational impacts.

Local authority variation in special educational needs provision at the start of primary school: observational study of preterm children born in England, 2003-2013

Objective and ApproachWe explored variation in special educational needs (SEN) provision between local authorities (LAs) in England by focussing on children born preterm (24-&lt;37 weeks gestation). We used linked individual-level state-funded hospital and school records from the ECHILD database, alongside publicly available school-level records. LA of child’s residential address (n=150) and recording of SEN provision (split into SEN support and education, health and care plans, EHCPs) were captured at the January school census in year one, when pupils were five/six years old. We fitted multi-level logistic regression models to the child-level records that included a-priori selected child- and LA-level characteristics. ResultsOur population included 226,419 children (45.4% female ; 10.6% with a congenital anomaly) born between 2003-2013 and attending a state-funded primary school. Across LAs, the median prevalence of SEN support and EHCPs recorded in year one was 18.4% (interquartile range 16.4%-20.4%) and 4.2% (3.5%-4.8%), respectively. In the SEN support vs. no SEN provision model, there was very low correlation among children from the same LA (intraclass correlation coefficient (ICC)=0.006 )). There was higher correlation in the EHCP vs. no SEN provision model (ICC=0.032). Of the LA-level characteristics, the percentage of children eligible for free school meals had the greatest impact on the ICC values (reduction of 26.7% in the EHCP model). ConclusionsLess than 1% of the variation in SEN support and approximately 3% of the variation in EHCPs was explained at the LA level. We will extend these models to consider variation at the school level.

The utility of 18F-FDG PET/CT for predicting the pathological response and prognosis to neoadjuvant immunochemotherapy in resectable non-small-cell lung cancer

ObjectiveTo evaluate the potential utility of 18F-FDG PET/CT to assess response to neoadjuvant immunochemotherapy in patients with resectable NSCLC, and the ability to screen patients who may benefit from neoadjuvant immunochemotherapy.MethodsFifty one resectable NSCLC (stage IA–IIIB) patients were analyzed, who received two-three cycles neoadjuvant immunochemotherapy.18F-FDG PET/CT was carried out at baseline(scan-1) and prior to radical resection(scan-2). SULmax, SULpeak, MTV, TLG, T/N ratio, ΔSULmax%,ΔSULpeak%, ΔMTV%, ΔTLG%,ΔT/N ratio% were calculated. 18F-FDG PET/CT responses were classified using PERCIST. We then compared the RECIST 1.1 and PERCIST criteria for response assessment.With surgical pathology of primary lesions as the gold standard, the correlation between metabolic parameters of 18F-FDG PET/CT and major pathologic response (MPR) was analyzed. All metabolic parameters were compared to treatment response and correlated to PFS and OS.ResultsIn total of fifty one patients, MPR was achieved in 25(49%, 25/51) patients after neoadjuvant therapy. The metabolic parameters of Scan-1 were not correlated with MPR.The degree of pathological regression was negatively correlated with SULmax, SULpeak, MTV, TLG, T/N ratio of scan-2, and the percentage changes of the ΔSULmax%, ΔSULpeak%, ΔMTV%,ΔTLG%,ΔT/N ratio% after neoadjuvant therapy (p < 0.05). According to PERCIST, 36 patients (70.6%, 36/51) showed PMR, 12 patients(23.5%, 12/51) had stable metabolic disease(SMD), and 3 patients(5.9%, 3/51) had progressive metabolic disease (PMD). ROC indicated that all of scan-2 metabolic parameters and the percentage changes of metabolic parameters had ability to predict MPR and non-MPR, SULmax and T/N ratio of scan-2 had the best differentiation ability.The accuracy of RECIST 1.1 and PERCIST criteria were no statistical significance(p = 0.91). On univariate analysis, ΔMTV% has the highest correlation with PFS.ConclusionsMetabolic response by 18F-FDG PET/CT can predict MPR to neoadjuvant immunochemotherapy in resectable NSCLC. ΔMTV% was significantly correlated with PFS.

Correlation of anogenital distance from childhood to age 9 years-a prospective population-based birth cohort-the Odense Child Cohort.

Does anogenital distance (AGD) - distance from the anus to the genitals - correlate from infancy (3 months) to the age of 9 years in boys and girls? In boys, AGD correlated from infancy to 9 years of age, whereas in girls, correlations were weaker, especially between infancy and later childhood. AGD is considered a marker for prenatal androgen action. In males, reduced AGD is associated with testicular cancer, infertility, and lower sperm count. In females, AGD is associated with endometriosis and polycystic ovary syndrome. In the Odense Child Cohort, a prospective population-based birth cohort, pregnant women were enrolled in early pregnancy. AGD and BMI were measured repeatedly in children at ages 3 and 18 months, as well as at 3, 5, 7, and 9 years. AGD was measured from the anus to the scrotum (AGDas) and to the penis (AGDap) in 1022 boys, and to the posterior fourchette and the clitoris in 887 girls repeatedly between the age of 3 months to 9 years. In total, 7706 assessments were made. AGD was adjusted for body weight, and SD scores (the difference between individual AGD and the mean of AGD in the population divided by SD of AGD) were calculated for each child. Pearson correlation coefficient (r) of each measurement was performed to investigate whether individual AGD was stable during childhood. Short predictive values at 3 months (20th percentile) to 9 years were investigated using the AUC produced by the receiver operating characteristic curve. In boys, AGD/body size-index SD score correlated significantly between infancy and 9 years, strongest for AGDas (r = 0.540 P > 0.001). In girls, weaker significant correlation coefficients were found between AGD at infancy and 9 years; higher correlation coefficients were found between AGD from 3 to 9 years (P > 0.001). Short AGDas in infancy predicted short AGDas in boys aged 9 years (AUC: 0.767, sensitivity 0.71, specificity 0.71). The predictive values of short infant AGDap, penile width (in boys), and AGD (in girls) concerning short outcomes at 9 years were low. The AGD measurements are less precisely measurable in girls compared to boys, especially in infancy, resulting in less reproducible measurements. Additionally, because AGD is shorter in girls, the same absolute measurement error is relatively more significant, potentially contributing to greater variability and lower reproducibility in girls. This may contribute to the weaker correlations in girls compared to boys. In boys, AGDas, relative to body size, correlated from infancy to 9 years, suggesting that AGD in infancy can be considered a non-invasive marker of later reproductive health. Further follow-up studies are needed to evaluate long-term individual tracking of AGD as well as assessment of childhood AGD as early marker of adult reproductive health. This study was supported by Odense University Hospital, Denmark, the Region of Southern Denmark, the Municipality of Odense, Denmark, the University of Southern Denmark, Odense Patient data Exploratory Network (OPEN), Denmark, the Danish Research Council (4004-00352B_FSS), Novo Nordisk Foundation, Denmark (grant no. NNF19OC0058266 and NNF17OC0029404), Sygeforsikring Danmark (journalnr. 2021-0173), the Collaborative Foundation between Odense University Hospital and Rigshospitalet, and Helsefonden. There is no conflict of interest of any author that could be perceived as prejudicing the impartiality of the research reported. N/A.

Classification of tomato seedling chilling injury based on chlorophyll fluorescence imaging and DBO-BiLSTM

IntroductionTomatoes are sensitive to low temperatures during their growth process, and low temperatures are one of the main environmental limitations affecting plant growth and development in Northeast China. Chlorophyll fluorescence imaging technology is a powerful tool for evaluating the efficiency of plant photosynthesis, which can detect and reflect the effects that plants are subjected to during the low temperature stress stage, including early chilling injury.MethodsThis article primarily utilizes the chlorophyll fluorescence image set of tomato seedlings, applying the dung beetle optimization (DBO) algorithm to enhance the deep learning bidirectional long short term memory (BiLSTM) model, thereby improving the accuracy of classification prediction for chilling injury in tomatoes. Firstly, the proportion of tomato chilling injury areas in chlorophyll fluorescence images was calculated using a threshold segmentation algorithm to classify tomato cold damage into four categories. Then, the features of each type of cold damage image were filtered using SRCC to extract the data with the highest correlation with cold damage. These data served as the training and testing sample set for the BiLSTM model. Finally, DBO algorithm was applied to enhance the deep learning BiLSTM model, and the DBO-BiLSTM model was proposed to improve the prediction performance of tomato seedling category labels.ResultsThe results showed that the DBO-BiLSTM model optimized by DBO achieved an accuracy, precision, recall, and F1 score with an average of over 95%.DiscussionCompared to the original BiLSTM model, these evaluation parameters improved by 9.09%, 7.02%, 9.16%, and 8.68%, respectively. When compared to the commonly used SVM classification model, the evaluation parameters showed an increase of 6.35%, 7.33%, 6.33%, and 6.5%, respectively. This study was expected to detect early chilling injury through chlorophyll fluorescence imaging, achieve automatic classification and labeling of cold damage data, and lay a research foundation for in-depth research on the cold damage resistance of plants themselves and exploring the application of deep learning classification methods in precision agriculture.

Variability in Liver Size Measurements Using Different View Angles in Ultrasound Imaging.

The aim of this study was to compare liver size measurements in different conventional B-mode ultrasound image (US) field views using magnetic resonance imaging (MRI) measurement as a reference. After receiving Institutional Review Board approval and informed consent, three operators measured the largest sagittal and transverse dimensions of adult livers on three US image field views (90°, 120°, and 140°) with a single curvilinear transducer. We analyzed the differences in liver size across three image field views using one-way analysis of variance (ANOVA) and examined the correlations between MRI and ultrasound measurements using Spearman regression. We used 95% Bland-Altman limits of agreement (95% LOA) to analyze the confidence interval for liver size measurements between MRI and US. Intra-observer and inter-observer reliability in measuring liver size were assessed using intraclass correlation coefficient (ICC). Based on sagittal liver length, 28 adult participants (7 men and 21 women, mean age 43 years) were divided into Group 1 (<17 cm, n = 10) or Group 2 (≥17 cm, n = 18). There was a significant difference in the liver size measurements across the three image field views (P < .001) in both groups. The highest correlation in liver size measurements between MRI and US was with ultra-wide-view (R2 = .87 in sagittal; R2 = .79 in transverse). Bland-Altman LOA also indicated good agreement between MRI and ultra-wide-view measurements. Intra-observer and inter-observer reliability in measuring liver size were good (ICC = 0.82-0.98). The study suggests that ultrasound ultra-wide-view provides the most accurate liver size measurement and good intra- and inter-operator reliability.

Tempo-spatial Variations in Nitrogen and Phosphorus Loads in Jianli-Hankou Reach of the Middle Yangtze River During the Past 20 Years

Ammonia nitrogen （NH4+-N） and total phosphorus （TP） were the major control pollutants in the Yangtze River Basin. Based on measured data from 2003 to 2020, the temporal and spatial variations in concentrations and fluxes of NH4+-N and TP in the Jianli to Hankou （JL-HK） reach of the Middle Yangtze River were studied, and the impacts of flow-sediment factors, tributary inflows, and others on variations in NH4+-N and TP fluxes were discussed. The results showed that： ① In recent years, NH4+-N and TP concentrations in the mainstream have declined significantly, with annual NH4+-N and TP concentrations at each monitoring station in 2020 averagely decreasing by 41% and 34% compared to those in 2003, respectively. Spatially, NH4+-N and TP concentrations decreased and then increased along the mainstream. NH4+-N and TP concentrations of tributary inflows, which include the Dongting Lake and Han River, were generally lower than that of the mainstream. The multi-year average values of NH4+-N and TP concentrations were both averaged at 0.12 mg·L-1 in the mainstream and were averaged at 0.11 mg·L-1 and 0.09 mg·L-1 in the tributary inflows. ② The flux differences between the upper and lower sections net of tributary confluences showed that NH4+-N and TP fluxes were lost in the Jianli to Luoshan （JL-LS） sub-reach and increased in the Luoshan to Hankou （LS-HK） sub-reach in most years. NH4+-N and TP fluxes decreased in the JL-LS sub-reach, which was related to the lower NH4+-N and TP concentrations in lateral inflows, such as Dongting Lake, and thus lowered the NH4+-N and TP concentrations in the mainstream. The LS-HK sub-reach showed the opposite trends, and the water and sediment loads increased in this sub-reach. Across the whole JL-HK reach, TP flux as well as water and sediment loads were recharged along the reach, whereas NH4+-N flux was reduced greatly, which could be attributed to the pollution abatement conducted in the Yangtze River Basin, which mainly focused on NH4+-N. ③ The correlation analysis results showed that NH4+-N fluxes had the strongest correlation with NH4+-N concentrations but not significantly correlated with discharges and sediment transport rates, indicating that NH4+-N was mainly controlled by point source pollution in the study reach. TP fluxes had higher correlations with discharges and sediment transport rates in high flow level periods, and the correlations between TP fluxes and TP concentrations were better in low flow level periods, reflecting that point source pollution contributed more to TP in dry seasons compared to flood seasons.

The value of cesarean scar diverticulum in diagnosis of adverse events during dilatation and curettage in patient with cesarean scar pregnancy.

The aim of the present study was to explore the relationship between the size of cesarean scar diverticulum (CSD) measured on preoperative magnetic resonance imaging (MRI) and adverse events during dilatation and curettage (D&C) procedure in patients with cesarean scar pregnancy (CSP). The MRI of 197 CSP patients from October 2019 to August 2023 were retrospectively reviewed. The volume, area, and depth of CSD, residual myometrium thickness (RMT), and gestational sac diameter were recorded and tested for correlation with intraoperative estimated blood loss (EBL), and operation time and for any association with the intraoperative adverse events (intraoperative massive hemorrhage [39 cases] and D&C procedure failure [15 cases]). The Spearman test was used to characterize the correlation between the five MRI variables and both the EBL and operation time. The correlation between the five MRI variables and intraoperative adverse events was evaluated with student's t test and Mann-Whitney U test. Diagnostic power of the MRI variables was evaluated by the area under receiver operating characteristic curve (AUC). The volume, area, and depth of CSD and gestational sac diameter were positively correlated with both EBL and operation time, with the CSD volume having the highest correlation with them (r = 0.543 and 0.461, respectively). Conversely, the RMT displayed a negative correlation with the EBL and operation time. All five MRI variables were significantly associated with both intraoperative massive hemorrhage and D&C failure (all P < 0.001). The CSD volume demonstrated the highest AUC for diagnosing intraoperative massive hemorrhage and D&C failure at 0.893 (95% CI: 0.82-0.92) and 0.901 (95% CI: 0.85-0.94), respectively. The optimal cutoff values for CSD volume in predicting massive hemorrhage and D&C failure were determined to be 5.41 and 8.92 cm3, respectively, with corresponding sensitivities/specificities of 92.31/74.68 and 93.33/82.42, respectively. Quantifying the size of CSD based on preoperative MRI could aid in evaluating risk during D&C in CSP patients, with CSD volume possessing higher diagnostic efficacy than the other four MRI indicators.

Smartphone-Based Assessment of Mobility and Manual Dexterity in Adult People with Spinal Muscular Atrophy.

More responsive, reliable, and clinically valid endpoints of disability are essential to reduce size, duration, and burden of clinical trials in adult persons with spinal muscular atrophy (aPwSMA). The aim is to investigate the feasibility of smartphone-based assessments in aPwSMA and provide evidence on the reliability and construct validity of sensor-derived measures (SDMs) of mobility and manual dexterity collected remotely in aPwSMA. Data were collected from 59 aPwSMA (23 walkers, 20 sitters and 16 non-sitters) and 30 age-matched healthy controls (HC). SDMs were extracted from five smartphone-based tests capturing mobility and manual dexterity, which were administered in-clinic and remotely in daily life for four weeks. Reliability (Intraclass Correlation Coefficients, ICC) and construct validity (ability to discriminate between HC and aPwSMA and correlations with Revised Upper Limb Module, RULM and Hammersmith Functional Scale - Expanded HFMSE) were quantified for all SDMs. The smartphone-based assessments proved feasible, with 92.1% average adherence in aPwSMA. The SDMs allowed to reliably assess both mobility and dexterity (ICC > 0.75 for 14/22 SDMs). Twenty-one out of 22 SDMs significantly discriminated between HC and aPwSMA. The highest correlations with the RULM were observed for SDMs from the manual dexterity tests in both non-sitters (Typing, ρ= 0.78) and sitters (Pinching, ρ= 0.75). In walkers, the highest correlation was between mobility tests and HFMSE (5 U-Turns, ρ= 0.79). This exploratory study provides preliminary evidence for the usability of smartphone-based assessments of mobility and manual dexterity in aPwSMA when deployed remotely in participants' daily life. Reliability and construct validity of SDMs remotely collected in real-life was demonstrated, which is a pre-requisite for their use in longitudinal trials. Additionally, three novel smartphone-based performance outcome assessments were successfully established for aPwSMA. Upon further validation of responsiveness to interventions, this technology holds potential to increase the efficiency of clinical trials in aPwSMA.

Using MRI Texture Analysis Machine Learning Models to Assess Graft Interstitial Fibrosis and Tubular Atrophy in Patients with Transplanted Kidneys

Objective: Interstitial fibrosis/tubular atrophy (IFTA) is a common, irreversible, and progressive form of chronic kidney allograft injury, and it is considered a critical predictor of kidney allograft outcomes. The extent of IFTA is estimated through a graft biopsy, while a non-invasive test is lacking. The aim of this study was to evaluate the feasibility and accuracy of an MRI radiomic-based machine learning (ML) algorithm to estimate the degree of IFTA in a cohort of transplanted patients. Approach: Patients who underwent MRI and renal biopsy within a 6-month interval from 1 January 2012 to 1 March 2021 were included. Stable MRI sequences were selected, and renal parenchyma, renal cortex and medulla were segmented. After image filtering and pre-processing, we computed radiomic features that were subsequently selected through a LASSO algorithm for their highest correlation with the outcome and lowest intercorrelation. Selected features and relevant patients’ clinical data were used to produce ML algorithms using 70% of the study cases for feature selection, model training and validation with a 10-fold cross-validation, and 30% for model testing. Performances were evaluated using AUC with 95% confidence interval. Main results: A total of 70 coupled tests (63 patients, 35.4% females, mean age 52.2 years) were included and subdivided into a wider cohort of 50 for training and a smaller cohort of 20 for testing. For IFTA ≥ 25%, the AUCs in test cohort were 0.60, 0.59, and 0.54 for radiomic features only, clinical variables only, and a combined radiomic–clinical model, respectively. For IFTA ≥ 50%, the AUCs in training cohort were 0.89, 0.84, and 0.96, and in the test cohort, they were 0.82, 0.83, and 0.86, for radiomic features only, clinical variables only, and the combined radiomic–clinical model, respectively. Significance: An ML-based MRI radiomic algorithm showed promising discrimination capacity for IFTA &gt; 50%, especially when combined with clinical variables. These results need to be confirmed in larger cohorts.

Quantitative muscle MRI in sporadic inclusion body myositis (sIBM): A prospective cohort study.

Sporadic inclusion body myositis (sIBM) is the predominant idiopathic inflammatory myopathy (IIM) in older people. Limitations of classical clinical assessments have been discussed as possible explanations for failed clinical trials, underlining the need for more sensitive outcome measures. Quantitative muscle MRI (qMRI) is a promising candidate for evaluating and monitoring sIBM. Longitudinal assessment of qMRI in sIBM patients. We evaluated fifteen lower extremity muscles of 12 sIBM patients (5 females, mean age 69.6, BMI 27.8) and 12 healthy age- and gender-matched controls. Seven patients and matched controls underwent a follow-up evaluation after one year. Clinical assessment included testing for muscle strength with Quick Motor Function Measure (QMFM), IBM functional rating scale (IBM-FRS), and gait analysis (6-minute walking distance). 3T-MRI scans of the lower extremities were performed, including a Dixon-based sequence, T2 mapping and Diffusion Tensor Imaging. The qMRI-values fat-fraction (FF), water T2 relaxation time (wT2), fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (λ1), and radial diffusivity (RD) were analysed. Compared to healthy controls, significant differences for all qMRI parameters averaged over all muscles were found in sIBM using a MANOVA (p < 0.001). In low-fat muscles (FF < 10%), a significant increase of wT2 and FA with an accompanying decrease of MD, λ1, and RD was observed (p≤0.020). The highest correlation with clinical assessments was found for wT2 values in thigh muscles (r≤-0.634). Significant changes of FF (+3.0%), wT2 (+0.6 ms), MD (-0.04 10-3mm2/s), λ1 (-0.05 10-3mm2/s), and RD (-0.03 10-3mm2/s) were observed in the longitudinal evaluation of sIBM patients (p≤0.001). FA showed no significant change (p = 0.242). qMRI metrics correlate with clinical findings and can reflect different ongoing pathophysiological mechanisms. While wT2 is an emerging marker of disease activity, the role of diffusion metrics, possibly reflecting changes in fibre size and intracellular deposits, remains subject to further investigations.

Modeling and Application of Drought Monitoring with Adaptive Spatial Heterogeneity Using Eco–Geographic Zoning: A Case Study of Drought Monitoring in Yunnan Province, China

Drought, characterized by frequent occurrences, an extended duration, and a wide range of destruction, has become one of the natural disasters posing a significant threat to both socioeconomic progress and agricultural livelihoods. Large-scale geographical environments often exhibit obvious spatial heterogeneity, leading to significant spatial differences in drought’s development and outcomes. However, traditional drought monitoring models have not taken into account the impact of regional spatial heterogeneity on drought, resulting in evaluation results that do not match the actual situation. In response to the above-mentioned issues, this study proposes the establishment of ecological–geographic zoning to adapt to the spatially stratified heterogeneous characteristics of large-scale drought monitoring. First, based on the principles of ecological and geographical zoning, an appropriate index system was selected to carry out ecological and geographical zoning for Yunnan Province. Second, based on the zoning results and using data from NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) and the Tropical Rainfall Measuring Mission (TRMM) 3B43, the vegetation condition index (VCI), the temperature condition index (TCI), the precipitation condition index (TRCI), and three topographic factors including the digital elevation model (DEM), slope (SLOPE), and aspect (ASPECT) were selected as model parameters. Multiple linear regression models were then used to establish integrated drought monitoring frameworks at different eco–geographical zoning scales. Finally, the standardized precipitation evapotranspiration index (SPEI) was used to evaluate the monitoring effects of the model, and the spatiotemporal variation patterns and characteristics of winter and spring droughts in Yunnan Province from 2008–2019 were further analyzed. The results show that (1) compared to the traditional non-zonal models, the drought monitoring model constructed based on ecological–geographic zoning has a higher correlation and greater accuracy with the SPEI and (2) Yunnan Province experiences periodic and seasonal drought patterns, with spring being the peak period of drought occurrence and moderate drought and light drought being the main types of drought in Yunnan Province. Therefore, we believe that ecological–geographic zoning can better adapt to geographical spatial heterogeneity characteristics, and the zonal drought monitoring model constructed can more effectively identify the actual occurrence of drought in large regions. This research finding can provide reference for the formulation of drought response policies in large-scale regions.

Segregation GWAS to linearize a non-additive locus with incomplete penetrance: an example of horn status in sheep

BackgroundThe objective of this study was to introduce a genome-wide association study (GWAS) in conjunction with segregation analysis on monogenic categorical traits. Genotype probabilities calculated from phenotypes, mode of inheritance and pedigree information, are expressed as the expected allele count (EAC) (range 0 to 2), and are inherited additively, by definition, unlike the original phenotypes, which are non-additive and could be of incomplete penetrance. The EAC are regressed on the single nucleotide polymorphism (SNP) genotypes, similar to an additive GWAS. In this study, horn phenotypes in Merino sheep are used to illustrate the advantages of using the segregation GWAS, a trait believed to be monogenic, affected by dominance, sex-dependent expression and likely affected by incomplete penetrance. We also used simulation to investigate whether incomplete penetrance can cause prediction errors in Merino sheep for horn status.ResultsEstimated penetrance values differed between the sexes, where males showed almost complete penetrance, especially for horned and polled phenotypes, while females had low penetrance values for the horned status. This suggests that females homozygous for the ‘horned allele’ have a horned phenotype in only 22% of the cases while 78% will be knobbed or have scurs. The GWAS using EAC on 4001 animals and 510,174 SNP genotypes from the Illumina Ovine high-density (600k) chip gave a stronger association compared to using actual phenotypes. The correlation between the EAC and the allele count of the SNP with the highest –log10(p-value) was 0.73 in males and 0.67 in females. Simulations using penetrance values found by the segregation analyses resulted in higher correlations between the EAC and the causative mutation (0.95 for males and 0.89 for females, respectively), suggesting that the most predictive SNP is not in full LD with the causative mutation.ConclusionsOur results show clear differences in penetrance values between males and female Merino sheep for horn status. Segregation analysis for a trait with mutually exclusive phenotypes, non-additive inheritance, and/or incomplete penetrance can lead to considerably more power in a GWAS because the linearized genotype probabilities are additive and can accommodate incomplete penetrance. This method can be extended to any monogenic controlled categorical trait of which the phenotypes are mutually exclusive.

CD24 affects the immunosuppressive effect of tumor-infiltrating cells and tumor resistance in a variety of cancers

BackgroundCluster of differentiation 24 (CD24) is a highly glycosylated glycosylphosphatidylinositol (GPI)-anchored surface protein, expressed in various tumor cells, as a "don't eat me" signaling molecule in tumor immune. This study aimed to investigate the potential features of CD24 in pan-cancer.MethodsThe correlations between 22 immune cells and CD24 expression were using TIMER analysis. R package “ESTIMATE” was used to predict the proportion of immune and stromal cells in pan-cancer. Spearman's correlation analysis was performed to evaluate the relationships between CD24 expression and immune checkpoints, chemokines, mismatch repair, tumor mutation burden and microsatellite instability, and qPCR and western blot were conducted to assess CD24 expression levels in liver hepatocellular carcinoma (LIHC). In addition, loss of function was performed for the biological evaluation of CD24 in LIHC.ResultsCD24 expression was positively correlated with myeloid cells, including neutrophils and myeloid-derived suppressor cells, in various tumors, such as BLCA, HNSC-HPV, HNSC, KICH, KIRC, KIRP, TGCT, THCA, THYM, and UCEC. In contrast, anti-tumor NK cells and NKT cells showed a negative association with CD24 expression in BRCA-Her2, ESCA, HNSC-HPV, KIRC, THCA, and THYM. The top three tumors with the highest correlation between CD24 and ImmuneScore were TGCT, THCA, and SKCM. Functional enrichment analysis revealed CD24 expression was negatively associated with various immune-related pathways. Immune checkpoints and chemokines also exhibited inverse correlations with CD24 in CESC, CHOL, COAD, ESCA, READ, TGCT, and THCA. Additionally, CD24 was overexpressed in most tumors, with high CD24 expression in BRCA, LIHC, and CESC correlating with poor prognosis. The TIDE database indicated tumors with high CD24 expression, particularly melanoma, were less responsive to PD1/PD-L1 immunotherapy. Finally, CD24 knockdown resulted in impaired proliferation and cell cycle progression in LIHC.ConclusionCD24 participates in regulation of immune infiltration, influences patient prognosis and serves as a potential tumor marker.

Predictive modeling of MRR, TWR, and SR in spark-EDM of Al-4.5Cu–SiC using ANN and GEP

In this study, Al-4.5Cu alloy was reinforced with varying weight percentages of SiC particles (2%, 4%, 6%, and 8%) to create metal matrix composites via the stir casting method. The formation of intermetallic compounds was confirmed through energy dispersive spectroscopy and x-ray diffraction analysis. This article compares the performance of Artificial Neural Network (ANN) and Gene Expression Programming (GEP) models in predicting the Metal Removal Rate (MRR), tool wear rate, and surface roughness in the die-sinking electro-discharge machining (EDM) process of the ex-situ developed Al-4.5%Cu–SiC composites. The study considers three machine parameters—pulse on time (TON), pulse off time (TOFF), and current (I)—along with the weight fraction of SiC particles as input variables for the models. Both ANN and GEP models demonstrated high predictive accuracy for the EDM performance metrics, with correlation coefficients (R) ranging from 0.973 68 to 0.980 65 for the ANN model and 0.980 11 to 0.982 59 for the GEP model. Notably, the GEP model exhibited superior predictive capability, as evidenced by its higher correlation coefficients and lower root mean square error, indicating greater effectiveness in predicting the EDM process outcomes than the ANN model.

Effect of Stocking Density on the Growth of the Endangered Amazonian Fish Hypancistrus zebra (Siluriformes: Loricariidae)

ABSTRACTStocking density has a significant influence on animal homeostasis, and so is a crucial factor in the management of organisms in captivity and an important role in ex situ conservation of endangered species. Hypancistrus zebra is an endemic fish species from the Xingu River, Brazil—considered Critically Endangered since the early 2000s due to fishing pressure and, more recently, due to habitat changes resulting from the construction of the Belo Monte Hydroelectric Dam. The implementation of appropriate management in captivity is of utmost importance for its conservation, particularly in enhancing ex situ breeding techniques. This study aimed to evaluate the growth of juvenile H. zebra in aquaria with three different stocking density levels. The juveniles were distributed between three treatments, each with three replicates. We found no correlation between biomass and aquarium volume. The highest correlation coefficients were found between growth rates and densities related to the number of individuals per shelter area. Mortality rate was directly related to the initial number of fish in the aquariums, with larger populations showing higher mortality rates. The treatment with lower stocking density displayed the highest growth rate, while the treatment with higher density had the lowest growth rate, with a 23.38% difference between them.

Architectural Strategies for Fostering Creativity and Enhancing Education for Children with Autism

Students with intellectual disabilities tend to spend most of their time in the classroom. The current research was conducted to create suitable environment for fostering creativity and improving education for children with autism. The type of research was quantitative, and the research data were analyzed using SPSS and AMOS software. specialized questionnaire was designed using expert opinion. The findings showed that, although psychological and biological factors have the highest correlation (T=867), architectural and environmental factors have a greater effect on biological factors (T=0.663) than do psychological factors (T=576). Furthermore, physical, psychological and biological factors having connecting and complementary roles should be considered when improving the quality of education for children with autism. Psychological factors are the influential components, followed by biological needs. Physical variables identified as facilitating psychological and biological needs included the degree of flexibility in quality (light, color and materials) and environmental structure (layout, shape and function).

Coupled model intercomparison project phase 6 (CMIP6) high resolution model intercomparison project (HighResMIP) bias in extreme rainfall drives underestimation of amazonian precipitation

Extreme rainfall events drive the amount and spatial distribution of rainfall in the Amazon and are a key driver of forest dynamics across the basin. This study investigates how the 3-hourly predictions in the High Resolution Model Intercomparison Project (HighResMIP, a component of the recent Coupled Model Intercomparison Project, CMIP6) represent extreme rainfall events at annual, seasonal, and sub-daily time scales. TRMM 3B42 (Tropical Rainfall Measuring Mission) 3 h data were used as observations. Our results showed that eleven out of seventeen HighResMIP models showed the observed association between rainfall and number of extreme events at the annual and seasonal scales. Two models captured the spatial pattern of number of extreme events at the seasonal and annual scales better (higher correlation) than the other models. None of the models captured the sub-daily timing of extreme rainfall, though some reproduced daily totals. Our results suggest that higher model resolution is a crucial factor for capturing extreme rainfall events in the Amazon, but it might not be the sole factor. Improving the representation of Amazon extreme rainfall events in HighResMIP models can help reduce model rainfall biases and uncertainties and enable more reliable assessments of the water cycle and forest dynamics in the Amazon.