Significant Correlation Coefficients Research Articles

Revealing the Hidden Consequences of Increased Soil Moisture Storage in Greening Drylands

Vegetation primarily draws water from soil moisture (SM), with restoration in drylands often reducing SM storage (SMS). However, anomalies have been detected in the Beijing–Tianjin Sand Source Region (BTSSR) of China via the Global Land Data Assimilation System (GLDAS) and Gravity Recovery and Climate Experiment (GRACE). This study quantified the sources of increased SMS in drylands to elucidate the effects of vegetation restoration on SMS. The results indicated the following: (1) In vegetated drylands, 46.2% experienced a significant increase in SMS while 53.8% remained stable; both were positively correlated with the normalised difference vegetation index (NDVI). (2) The increase in SMS was accompanied by a decrease in groundwater storage (GWS), as indicated by the significant correlation coefficients of −0.710 and −0.569 for SMS and GWS, respectively. Furthermore, GWS served as the primary source of water for vegetation. (3) The results of the redundancy analysis (RDA) indicated that the initial vegetation, the driver of the observed trend of increased SMS and decreased GWS, accounted for 50.3% of the variability in water storage. Therefore, to sustain dryland ecosystems, we recommend that future vegetation restoration projects give due consideration to the water balance while concurrently strengthening the dynamic monitoring of SMS and GWS.

Multi-omics strategy reveals potential role of antimicrobial resistance and virulence factor genes responsible for Simmental diarrheic calves caused by Escherichia coli.

Escherichia coli (E. coli) is reported to be an important pathogen associated with calf diarrhea. Antibiotic resistance genes (ARGs) and virulence factor genes (VFGs) pose a considerable threat to both animal and human health. However, little is known about the characterization of ARGs and VFGs presented in the gut microbiota of diarrheic calves caused by E. coli. In this study, we used multi-omics strategy to analyze the ARG and VFG profiles of Simmental calves with diarrhea caused by E. coli K99. We found that gut bacterial composition and their microbiome metabolic functions varied greatly in diarrheic calves compared to healthy calves. In total, 175 ARGs were identified, and diarrheal calves showed a significantly higher diversity and abundance of ARGs than healthy calves. Simmental calves with diarrhea showed higher association of VFGs with pili function, curli assembly, and ferrienterobactin transport of E. coli. Co-occurrence patterns based on Pearson correlation analysis revealed that E. coli had a highly significant (P < 0.0001) correlation coefficient (>0.8) with 16 ARGs and 7 VFGs. Metabolomics analysis showed that differentially expressed metabolites in Simmental calves with diarrhea displayed a high correlation with the aforementioned ARGs and VFGs. Phylotype analysis of E. coli genomes showed that the predominant phylogroup B1 in diarrheic Simmental calves was associated with 10 ARGs and 3 VFGs. These findings provide an overview of the diversity and abundance of the gut microbiota in diarrheic calves caused by E. coli and pave the way for further studies on the mechanisms of antibiotic resistance and virulence in the calves affected with diarrhea.IMPORTANCESimmental is a well-recognized beef cattle breed worldwide. They also suffer significant economic losses due to diarrhea. In this study, fecal metagenomic analysis was applied to characterize the antibiotic resistance gene (ARG) and virulence factor gene (VFG) profiles of diarrheic Simmental calves. We identified key ARGs and VFGs correlated with Escherichia coli isolated from Simmental calves. Additionally, metabolomics analysis showed that differentially expressed metabolites in Simmental calves with diarrhea displayed a high correlation with the aforementioned ARGs and VFGs. Our findings provide an insight into the diversity and abundance of the gut microbiota in diarrheic calves caused by Escherichia coli and pave the way for further studies on the mechanisms of antibiotic resistance and virulence in the diarrheal calves from cattle hosts.

Development and preliminary validation of a questionnaire for assessing fitness centers

This manuscript comprehensively examines the development and preliminary validation of a questionnaire designed to assess fitness centers. The study aims to address existing gaps in the literature by providing a standardized tool for evaluating the quality of fitness facilities. The study aims to design, validate, and present a preliminary assessment instrument tailored specifically for fitness centers, encompassing various aspects such as program offerings, facility conditions, and staff competencies. The research methods involved the identification of key indicators affecting fitness center services, followed by the generation and validation of questionnaire items through a rigorous statistical analysis. The research subjects consisted of 119 fitness enthusiasts from Angeles City, Philippines, who actively participated in the validation process. The instruments used in data processing included Likert-style rating scales and statistical methods such as Point Biserial Correlation and t-tests. The analysis of data utilized in data processing led to the retention of 59 questionnaire items, demonstrating significant correlation coefficients. The study's results highlight the reliability and validity of the developed questionnaire as a valuable tool for assessing fitness centers, providing insights into client needs and areas for improvement. In conclusion, the preliminary validation of the questionnaire serves as a crucial step towards enhancing the quality and standards of fitness center services, benefiting both managers and regulatory authorities in ensuring the provision of safe and effective fitness facilities.

An accurate snow cover product for the Moroccan Atlas Mountains: Optimization of the MODIS NDSI index threshold and development of snow fraction estimation models

In semi-arid Mediterranean areas, a significant proportion of the population living downstream depends on water resources from snowmelt and precipitation as their main source of water. Consequently, snow-covered mountain regions can be considered as a vital water tower, providing a steady supply of water, and contributing significantly to streamflow and groundwater recharge. Given the scarcity of ground-based hydroclimatic measurements, remote sensing could be an effective technique for mapping and monitoring snow cover. This study evaluates the last version of MODIS (version 6, called V6) snow cover product, optimizing the NDSI threshold for accurate snow cover mapping and developing models for local fractional snow cover estimation in the southern Mediterranean region, particularly in the Moroccan Atlas Mountains. For this purpose, 448 Sentinel-2 (S2) scenes from six different regions across the Atlas Range were used to adjust the NDSI threshold and to develop FSC estimation models. In addition, a total of 8419 MOD10A1 images from March 2000 to June 2023, and 7561 MYD10A1 images from September 2002 to June 2023, were processed to improve cloud filtering and to develop a highly accurate daily snow cover product suitable for the Moroccan Atlas Mountains. The cloud correction approach significantly reduced the number of cloud-covered pixels, from 25.7% to 0.4% after filtering. Two schemes for selecting the MODIS NDSI threshold were tested: (1) the global reference of 0.4 and (2) the locally optimal threshold of 0.2. The average snow cover estimation errors using the optimal and global NDSI thresholds for Terra are an average overestimation of 0.34% and a significant underestimation of 6.13%, respectively. For Aqua, the corresponding errors are an overestimation of 1.4% and an underestimation of 6.8%. Thus, the optimal NDSI threshold of 0.2 could be more appropriate than the threshold of 0.4 for use in the southern Mediterranean region. The new FSC estimation models developed showed satisfactory performance with significant correlation coefficients (mean of 0.85 for Terra and 0.83 for Aqua), and with low RMSE and MAE values (mean of 0.17 and 0.12 for Terra and mean of 0.19 and 0.14 for Aqua) when comparing FSC derived from high-resolution S2 data with predicted FSC from MODIS NDSI. The daily snow cover product developed was compared with the high-resolution snow maps obtained from S2 satellite imagery in different regions of the Moroccan Atlas. On average, the product showed a mean correlation coefficient of 0.96, a mean absolute error of 0.22%, and a mean reasonable negative bias of −0.17%. This research concludes that the enhanced daily snow cover product could improve the understanding of spatiotemporal dynamics of snow extent and, therefore, contribute to quantifying the snowmelt contribution to the water budget through modeling approaches in the southern Mediterranean region.

Contagion and linkages across international currencies

This paper examines dynamic linkages among international currencies in the face of several turmoil episodes including the global financial crisis (GFC), eurozone sovereign debt crisis (ESDC) and the recent COVID-19 pandemic. We utilize weekly data from August 2005 till December 2022. Our empirical strategy consists of identification of crisis periods using a Markov-switching VAR, followed by estimation of the dynamic conditional correlations using an ADCC-GARCH model and testing for the impact of the crises using a regression model with robust standard errors. We compare impact of the episodes on the dynamic correlations across the currency pairs. Our findings suggest that correlation between developed economy exchange rates increased significantly during these episodes implying existence of a contagion effect. While significant negative correlation coefficients were observed across all pairs with Japanese Yen during GFC and ESDC, indicating flight to quality. We analyse factors that may be responsible for changes in co-movement of the currencies during the study period and find that financial stress, emergence of the pandemic and geo-political risk have a significant role to play.

Hepatitis C virus core antigen: A diagnostic and treatmentmonitoring marker of hepatitis C virus in Indian population.

The diagnosis and treatment monitoring of hepatitis C is quite challenging. The screening test, i.e. antibody assay, is unable to detect acute cases, while the gold standard hepatitis C virus (HCV) reverse transcriptase polymerase chain reaction (RTPCR) assay is not feasible in resource-limited countries such as India due to high cost and infrastructure requirement. European Association for the Study of the Liver and World Health Organization have approved a new marker, i.e. HCV core antigen (HCVcAg) assay, as an alternative to molecular assay. In this study, we have evaluated HCVcAg assay for diagnosis and treatment monitoring follow-up in Indian population infected with hepatitis C. Blood specimen of 90 clinically suspected cases of acute hepatitis C were tested simultaneously for anti-HCV antibody assay via ELISA (enzyme-linked immunoassay), HCVcAg assay by chemiluminescence immune assay (CLIA) and HCV RTPCR VL (viral load) assay. Thirty-four HCV RTPCR positive patients were further enrolled in treatment monitoring group whose blood samples were tested at thebeginning of treatment, twoweeks, fourweeks and 12weeks via HCV core Ag assay and HCV RTPCR Viral Load assay. Considering HCV RTPCR as gold standard, diagnostic performance of HCV core Ag assay and anti-HCV antibody assay was evaluated. The sensitivity and specificity of HCV core Ag assay were higher than that of anti-HCV Antibody assay, i.e. 88.3% and 100% vs. 23.3% and 83.3%, respectively. The overall diagnostic accuracy of HCV core Ag assay was 92.20%. Among treatment follow-up group, HCV core Ag levels correlated well with HCV viral load levels, at the beginning of treatment (baseline) till 12weeks showing highly significant Spearman rank correlation coefficient of > 0.9 with HCV viral load levels. HCV core Ag assay is a cost-effective, practically feasible substitute of HCV RTPCR viral load assay for diagnosis as well as long duration treatment monitoring of hepatitis C infection in resource-limited settings.

Sensitivity analysis on stormwater management response to land cover dynamics and urban expansion of developing City in Lake Hawassa watershed, Ethiopia

AbstractHawassa is a rapidly developing city in Lake Hawassa watershed of Ethiopia. Analyzing the effect of land cover dynamics on surface runoff remains imperative to adaptive urban stormwater management. This study quantified spatial variation of land cover and sensitivity of stormwater management response. Historical 30 years of daily annual rainfall, three satellite imageries, DEM, and hydrological soil group data were analyzed. A statistical‐based combined approach of geospatial techniques and Soil Conservation Service‐Curve Number (SCS‐CN) model was employed. CN and surface runoff depth for the delineated urban watersheds were determined. The result revealed that the built‐up area increased by 30.9 km2, where the rate varies spatially. The variation of impervious land cover explains 58.6% of change in CN with coefficient of 0.352. While CN is inversely correlated with agricultural and vegetation land cover variations. The finding suggests CN explains 96.78% of the change in surface runoff with a significant correlation coefficient of 3.91. The proposed integrated model approach justifies the potential to reorganize the relationship between the spatial effect of land cover variation on surface runoff at the urban watersheds. Thus, suitable local‐specific solutions can be devised for effective management of flood risk and optimize the drainage system of urban areas.

Estimation of Correlation Coefficient Analysis for Yield and Component Traits in Field Pea (Pisum sativum L.)

The present investigation entitled “Estimation of Correlation Coefficient Analysis for Yield and Component Traits in field pea (Pisum sativum L.)” for 10 characters. The experiment comprising of 23 genotypes of pea were grown in a Randomized Block Design (RBD), with three replications at Research Farm, Department of Genetics &amp; Plant Breeding, Post Graduate College, Ghazipur, during rabi season of 2017-2018, plant to plant and row to row distance was kept 10 cm and 45 cm, respectively. The maximum positive and significant phenotypic correlation coefficient (0.834) was found between seed yield per plant, biological yield per plant. Positive and significant correlations were observed between seed yield per plant and number of pods per plant, plant height. Positive and significant correlations were also recorded between biological yield per plant and plant height, number of pods per plant. Similarly number of pods per plant had positive and significant correlation with plant height.

Abstract LB386: Weakly-supervised prediction of tumor infiltrating lymphocytes per high power field from colorectal cancer histopathology slides using regression transformers

Abstract Tumor infiltrating lymphocytes (TILs)-based biomarkers have emerged as a robust method for predicting treatment efficacy and outcome in colorectal cancer (CRC). However, the quantification of TILs remains a strenuous task for pathologists and is susceptible to inter-pathologist variations. Deep learning (DL) can predict cancer biomarkers directly from routine hematoxylin and eosin (H&amp;E) pathology slides, enabling the automated and consistent quantification of TILs for clinical decision-making. Our study focuses on the prediction of TILs per high-power field (HPF) on two large cohorts of CRC patients. We developed a weakly-supervised, transformer-based deep regression model to predict TILs per HPF from routine H&amp;E-stained histology slides. We trained the model using 5-fold cross-validation on a large cohort of CRC patients (n=1,738), and validated its performance on an external cohort of CRC patients (n=223). The model was evaluated using the Pearson’s correlation coefficient r. Moreover, pathologist-determined TILs per HPF was categorized into low (&amp;lt;2) and high (≥2), enabling evaluation via the area under the receiver operating characteristic curve (AUROC). Our model achieved a significant correlation coefficient of 0.60 (p&amp;lt;0.0001) for the predicted TILs per HPF in the holdout test sets of the internal cohort, and a significant correlation coefficient of 0.57 (p&amp;lt;0.0001) on the external validation cohort. Using the thresholds for low and high TILs per HPF, we found that the model accurately predicted the presence of high TILs per HPF in both the internal and external test cohorts, yielding AUROCs of 0.76 and 0.81, respectively. These findings underscore the efficacy of our deep learning model in predicting TILs per HPF from routine pathology slides. This approach holds promise for cost-effective, efficient and uniform quantification of TILs per HPF in CRC, potentially across various cancer types. Citation Format: Omar S. El Nahhas, Joseph D. Bonner, Joel K. Greenson, Daniel B. Schmolze, Lawrence Shaktah, Jonathan Salazar, Lorena Reynaga, Sidney Lindsey, Jenny Lu, Victor Moreno, Stephanie L. Schmit, Ya-Yu Tsai, Stanley R. Hamilton, Gad Rennert, Jakob N. Kather, Stephen B. Gruber. Weakly-supervised prediction of tumor infiltrating lymphocytes per high power field from colorectal cancer histopathology slides using regression transformers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB386.

Relationships Between Executive Functions and Computational Thinking

Addressing cognitive disparities has become a paramount concern in computational thinking (CT) education. The intricate and nuanced relationships between CT and cognitive variations emphasize the needs to accommodate diverse cognitive profiles when fostering CT skills, recognizing that these cognitive functions can manifest as either strengths or limitations in different students. Consequently, understanding the connections between students’ cognitive functions and CT skills assumes pivotal importance in the design of personalized instructional strategies for CT. Despite a general consideration of learning variability in CT education, empirical insights exploring the correlation between cognitive skills and CT competencies remain notably scarce. This study endeavors to bridge this research gap by investigating the links between executive functions and CT skills, as well as the associations between their sub-dimensions. The results reveal a statistically significant correlation coefficient of 0.452 between these two domains, underscoring the notable connection between executive functions and CT abilities. Furthermore, the sub-dimensional analysis offers a comprehensive understanding of how specific executive functions uniquely contribute to certain CT skills. In light of these findings, this research offers a promising pathway for the development of tailored CT education programs that can cater to the unique needs of each individual, ultimately facilitating inclusive CT programs and making significant contributions to broaden STEM education and future workforce.

Влияние природных и антропогенных факторов на формирование микроэлементного состава буроземов острова Рейнеке

The role of natural and anthropogenic factors in the formation of the microelement composition of the brown soils of the Reinecke Island is considered. Analysis of the concentration coefficients of heavy metals in the island brown soils showed that during soil formation, active accumulation occurs in the surface horizons of Zn, Cu, Cd and Co. The research results indicate the prevailing influence of soil formation features on the content and distribution of heavy metals in areas remote from the coast. As we approach the coastal zone, beloved by tourists for recreation, the content of Zn, Cu, Cd increases significantly in the surface layer of the island&amp;#x27;s brown soils, which is probably due to the local anthropogenic impact that takes place there. The data on the profile distribution of heavy metals in the studied brown soils reflect the intensity of the processes of humus formation occurring in the profile of brown soils and indicate the affinity of Pb, Cd to organic complexes. This is confirmed by the presence of significant positive correlation coefficients between organic matter and Pb and Cd content. The role of physical indicators of borozems on the fixation of a number of heavy metals in their profile is also noted. Quantitative indicators of Cr and Ni content are most determined by the distribution of the silty fraction. High values of the correlation coefficient between pH, the sum of exchange bases and the Mn content may indicate the influence of acid-base properties on its accumulation in the soil profile. Manganese hydroxide plays an important role in fixing Co in the brown soils of the island. The correlation between Co and Mn is estimated as noticeable.

Towards urban wind utilization: The spatial characteristics of wind energy in urban areas

Urban wind energy is gaining increasing recognition for its environmentally friendly nature, particularly in the context of energy shortages. Predicting wind speed in urban environments is challenging due to the varying roughness and drag caused by obstacles on the ground. The complexity of urban morphology significantly disrupts the wind field and hampers the utilization of wind energy. This study aimed to investigate the diverse impacts of highly heterogeneous urban environment on the urban wind energy by innovatively establishing spatially varying power law wind profiles. Firstly, long-term LIDAR observations were conducted to measure the vertical wind profile in the study area. Then, a high-resolution LCZ map was created and integrated into the Weather Research and Forecasting (WRF) model to reproduce the urban wind field, which was validated using the observational data. Finally, the spatial characteristics of the urban wind field and wind energy were analyzed based on 3 representative points and the urban LCZ categories. The results show that the average power law exponents of each LCZ classification ranges from 0.29 to 0.75, with the average power law exponent of the high-volume building area being larger than 0.6. The highest wind power density in the study area can reach 343.3W/m2 at 200m height. Further, significant negative correlation coefficients were found between wind power density and building height, as well as building density, with values of approximately −0.6 and −0.35, respectively. Overall, the high-volume-ratio built-up areas with higher roughness had a notable impact on the wind speed by increasing the power law exponents. These spatially varying wind profiles are expected to provide technical support for the utilization of urban wind energy.

Insights into the phytochemical composition and antioxidant potential of the Tunisian Ceratonia siliqua L.

Carob (Ceratonia siliqua L.) corresponds to an evergreen leguminous tree (Fabaceae family). The high phenolic content of numerous parts of carob has been deeply associated with several nutritional and functional benefits. The aim of this study was to investigate the physicochemical properties of ground carob pods and seeds, the effect of different extraction procedures as well a comprehensive phytochemical characterization of hydro-methanolic extracts (80/20 v/v) of pods and seeds by HPLC-DAD ESI-Q-TOF-MS/MS. Additionally, their antioxidant activity was evaluated using in vitro assays.The results showed thatthe dry matter (DM) values were 88.09% for pods and 89.10% for seeds, protein contents were 0.41 g/100 g DM for pods and 0.88 g/100 g DM for seedsand total sugars contents were 0.35 g/100 DM for pods and 26.70 g/100 g DM for seeds. Furthermore, the oil holding capacities (OHC) were 10.43 g/g for pods and 7.53 g/g for seeds, while the water holding capacities were 8.46 g/g for pods and 2.59 g/g for seeds.The hydro-methanolic extracts of both pods and seeds showed the presence of 53 secondary bioactive metabolites belonging to various classes(flavonoids, phenolic acids, tannins and non-phenolic compounds). The antioxidant activities were evidenced in DPPH (22.24 mg/ml for pods and 26.37 mg/ml for seeds), ABTS (198.50 mmol Eq Trolox/100 g for pods and 201.04 mmol Eq Trolox/100 g for seeds) and FRAP (0.39 mmol Eq Trolox/100 g for pods and 0.53 mmol Eq Trolox/100 g for seeds).Moreover,high significant (p ≤ 0.01) correlation coefficients were found between the antioxidant activity estimated by the DPPH method and total phenols (r = 0.943), orthodiphenols (r = 0.996), flavonoids (r = 0.880) and flavonols (r = 0.982). Nevertheless, lower correlations were detected with ABTS and FRAP methods.These results demonstrated that carob parts displayed an interesting potential that can be of interest for further valorizations as a natural antioxidant with multiple applications, namely functional food ingredients or prevention of many health problems.

Studying the estimates of gamma distribution parameters

The main goal of the work is to obtain additional information about the experimentally obtained sample with a previously known theoretical distribution, the point estimates of the parameters of which are considered known. At the same time, the laws of distribution of these parameters remain unknown, whereas they could provide a researcher with additional information about both the material and technological processes. Hence, it is necessary to obtain an additional number of samples, which is not always possible experimentally. Here we used data on the service life of cutters (GOST 11.011–83 «Rules for determining estimates and confidence limits for gamma distribution parameters») as an experimental sample. The experimental sample contains the results of 50 measurements. The mean was 57.88 hours CI [50.74:65.01]. The confidence probability is taken to be 0.95. Bootstrap was used as a way to obtain additional samples. The universal mathematical package MATLAB is used in the study. Bootstrap allows generation of a large number of samples that require certain selection rules to be applied to them. The first obvious requirement is the significance of the correlation coefficient of the generated sample with the original one. Even at this stage, the bootstrap showed certain limitations in performing the task set in the study. For 1000 samples generated by the standard bootstrap routine, the mean for the population of all mean bootstrap samples was 57.80 hours, and the confidence interval was [50.59:58.08]. The result is good. Though the nonparametric hypothesis regarding an agreement between the bootstrap samples for the gamma distribution and the parameters characteristic of the original experimentally obtained sample was not rejected, the statistically significant correlation coefficient was observed only for 29 bootstrap samples. As a result of meeting these obvious requirements, less than 3% of the generated bootstrap samples remained for further consideration. This fact requires the introduction of additional conditions when using the bootstrap to obtain samples that are close to the original experimental sample, which can be rather specific. To determine the parameters of the gamma distribution for bootstrap samples, the method of moments and the one-step method were used.

Abstract 6191: Simultaneous prediction of tumor microenvironment biomarkers from pathology slides using multi-task deep regression

Abstract Understanding the Tumor Microenvironment (TME) is crucial for tailoring personalized cancer treatments and improving patient outcomes. Using deep learning, we can predict properties of the TME from standard Hematoxylin and Eosin (H&amp;E) stained slides, including specific gene expression signatures. While past models were limited to single signature predictions, we explore the potential of multi-task deep learning to identify multiple biomarkers at once, allowing more complex relationships and interactions to be modeled simultaneously. Our study focuses on the prediction of expression patterns of tumor, stromal, and immune cells in breast cancer (BC). We developed a multi-task transformer-based deep regression model, trained in a weakly-supervised setting, to predict biomarkers in the TME from routine H&amp;E-stained pathology slides of a BC cohort (n=876). The performance was evaluated using Pearson’s correlation coefficient (r) and spatial heatmaps generated via gradient-weighted class activation mapping. Our model achieved a significant correlation coefficient above 0.40 (p&amp;lt;0.0001) for all predicted TME biomarkers in the holdout test set (n=176). This includes the biomarkers lymphocyte infiltrating signature score (r=0.46, p&amp;lt;0.0001), tumor infiltrating lymphocyte regional fraction (r=0.48, p&amp;lt;0.0001), leukocyte fraction (r=0.43, p&amp;lt;0.0001), stromal fraction (r=0.42, p&amp;lt;0.0001), and tumor cell proliferation (r=0.47, p&amp;lt;0.0001). Notably, the model's heatmaps highlighted the pertinent cells and histological characteristics for its predictions. These data show that our deep learning model accurately predicts multiple TME biomarkers concurrently from routine pathology slides. This approach offers a promising avenue for cost-effective and efficient biomarker quantification in the TME, with potential applicability across various cancer types. Citation Format: Omar S. El Nahhas, Marta Ligero, Jakob N. Kather. Simultaneous prediction of tumor microenvironment biomarkers from pathology slides using multi-task deep regression [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6191.

Adsorption of Methylene Blue Dye and Analysis of Two Clays: A Study of Kinetics, Thermodynamics, and Modeling with DFT, MD, and MC Simulations.

The purpose of this research was to learn more about the primary and secondary properties of Moroccan natural clay in an effort to better investigate innovative adsorbents and gain access to an ideal adsorption system. Scanning electron microscopy coupled with energy-dispersive X-ray spectroscopy analysis (SEM-EDX) and X-ray fluorescence were employed for identification. SEM revealed clay grains, including tiny particles and unevenly shaped sticks. First- and second-order rate laws, representing two distinct kinetic models, were applied in the kinetic approach. Adsorption of dye MB onto natural clay was studied, and the results agreed with the 2 s order model. The significant correlation coefficients support the inference that the adsorption process was governed by the Langmuir model. Subsequent DFT analyses demonstrated that the methylene blue dye's HOMO and LUMO surfaces are dispersed across most of the dye's components, pointing to a strong interaction with the clay. To determine how the dye might be adsorbed onto the clay, we employed quantum descriptors to locate its most nucleophilic and electrophilic centers. Endothermic reactions are evident during the MB adsorption process on clay, as indicated by the positive values of ΔH0 and ΔS0 (70.49 kJ mol-1of RC and 84.19 kJ mol-1 of OC and 10.45 J mol-1 K-1 of RC and 12.68 mol-1 K-1 of OC, respectively). Additionally dye molecules on the adsorbent exhibit a higher order of distribution than in the solution, indicating that the adsorption process is spontaneous.

Plasma metabolomics identifies S-adenosylmethionine as a biomarker and potential therapeutic target for vascular aging in older adult males

Brachial-ankle pulse wave velocity (baPWV) is a noninvasive index of vascular aging. However, the metabolic profile underlying vascular aging has not yet been fully elucidated. The current study aimed to identify circulating markers of vascular aging as assessed by baPWV and to elucidate its mechanism from a metabolomic perspective in older adults. A total of 60 and 61 Chinese male participants aged ≥80 years were recruited to the metabolome and validation cohorts, respectively. The baPWV of participants was measured using an automatic waveform analyzer. Plasma metabolic profile was investigated using ultra-performance liquid chromatography coupled with triple quadrupole linear ion trap tandem mass spectrometry. Orthogonal partial least squares (OPLS) regression modeling established the association between metabolic profile and baPWV to determine important metabolites predictive of vascular aging. Additionally, an enzyme-linked immunosorbent assay was employed to validate the metabolites in plasma and culture media of vascular smooth muscle cells in vitro. OPLS modeling identified 14 and 22 metabolites inversely and positively associated with baPWV, respectively. These 36 biomarkers were significantly enriched in seven metabolite sets, especially in cysteine and methionine metabolism (p <0.05). Notably, among metabolites involved in cysteine and methionine metabolism, S-adenosylmethionine (SAM) level was inversely related to baPWV, with a significant correlation coefficient in the OPLS model (p <0.05). Furthermore, the relationship between SAM and vascular aging was reconfirmed in an independent cohort and at the cellular level in vitro. SAM was independently associated with baPWV after adjustments for clinical covariates (β = −0.448, p <0.001) in the validation cohort. In summary, plasma metabolomics identified an inverse correlation between SAM and baPWV in older males. SAM has the potential to be a novel biomarker and therapeutic target for vascular aging.

Air Quality Changes under the Influence of Cut-Off Lows and Omega Blocking Patterns and Associated Health Risks in a Coastal Mediterranean Region: Case of Bizerte, Northern Tunisia

The study of the daily and diurnal variability of NO, NO2, surface O3 and PM10 was carried out in urban Bizerte (Northern Tunisia), from January to March, 2013. The main results showed three distinct periods depending on multi-scale sources and meteorology. The first period, (≈20% of total cases) influenced by moderately stable conditions, was characterized by a slight excess of NO due to traffic emissions. The second period, (≈ 60% of total cases) associated with moderately unstable conditions, was devoid of any significant impact of sources. The third period, (≈ 20% of total cases) distinguished by noteworthy excess of O3 and PM10, was attributed to a marked effect of succeeding Cut-off lows and Omega blocking patterns. Under these conditions, the scatter plots of NO, NO2, and O3 versus NOx for daytime and nighttime showed good polynomial fit curves with high R2 values for NO and NO2 only. Under both moderately unstable and stable conditions, significant negative correlation coefficients between O3 and NOx were found to be 0.53 (p < 0.05) and 0.50 (p < 0.05) for daytime and nighttime, respectively. Under Cut-off lows and Omega, an absence of any significant correlations between O3 and NOx was noticed. Under Cut-off lows, the good linear regression fits between OX (=O3 + NO2) and NOx illustrated high NOx independent contributions, possibly attributed to the biogenic VOCs effect. The investigation of the air quality index (AQI) for NO2, PM10 and O3 (running 8-h mean) highlighted the significant effect of both O3 and PM10 only under Cut-off lows and Omega which were retraced by poor to very poor air quality categories.

Drought Dynamics in the Nile River Basin: Meteorological, Agricultural, and Groundwater Drought Propagation

The Nile River Basin (NRB) has experienced a notable rise in drought episodes in recent decades. The propagation of meteorological, agricultural, and groundwater drought dynamics in the NRB was investigated in this study. The following drought indices examined the correlation and propagation among meteorological, agricultural, and groundwater droughts. These are the standardized precipitation evapotranspiration index (SPEI), soil moisture index, Gravity Recovery and Climate Experiment, and GRACE Follow-On (GRACE/GRACE-FO)-derived groundwater drought index (GGDI). These droughts were comprehensively evaluated in the NRB from 2003 to 2022. The cross-wavelet transform approach highlighted the links between droughts. The following are the key findings: (1) In the NRB, the cross-wavelet energy spectrum of wavelet coherence can indicate the internal connection between meteorological versus (vs.) agricultural and agricultural versus (vs.) groundwater drought. The time scale with the most significant correlation coefficient is the drought propagation time. (2) The El Niño–Southern Oscillation (ENSO) correlated with agricultural and groundwater drought much more than the Indian Ocean Dipole (IOD), demonstrating that ENSO has an important impact on drought advancement. (3) The R2 values were 0.68 for GGDI vs. standardized soil moisture index (SSI), 0.71 for Blue Nile Region (BNR) GGDI vs. SSI, and 0.55 for SSI vs. Standardized Precipitation Evapotranspiration Index (SPEI). Similarly, in the Lake Victoria Region (LVR), GGDI vs. SSI was 0.51 and SSI vs. SPEI was 0.55, but in the Bahr-el-Ghazal Region (BER), GGDI vs. SSI was 0.61 and SSI vs. SPEI was 0.27 during the whole research period with varied lag durations ranging from 1 to 6 months. Thus, the propagation of drought (i.e., meteorological, agricultural, and groundwater drought) dynamics has the potential to reshape our understanding of drought evolution, which could lead to early drought forecasting across the NRB and similar climatic regions.

33 An evaluation of Oklahoma beef producer decision factors regarding the implementation of calf best management practices

Abstract Oklahoma State Ag Economics and Animal Science Specialists implement the Oklahoma Beef Management and Marketing Survey approximately every 5 yr. Data from the 2017 survey indicated that 82% of producers practiced castration, 87% dewormed, 75% trained calves to feed bunks, 63% weaned calves for a minimum of 45 days, and 49% administered two rounds of respiratory vaccinations (Barnes et al., 2023). Using data from the 2017 survey, the objectives of this study were to evaluate incentives and constraints to producer implementation of calf best management practices and to analyze relationships between individual management practices and marketing calves at weaning ( &amp;lt; 30 d weaned) or following a weaning period (≥ 30 d weaned). Management practices evaluated included castration, deworming, feed bunk training, a minimum 45-d weaning period, and the administration of two rounds of respiratory vaccines. A total of 1,495 surveys were returned. When asked to indicate management incentives (why the practice was implemented), n = 1,375, n = 1,348, n = 1,070, n = 937, and n = 937 responses were recorded regarding castration, deworming, bunk training, 45-d weaning period, and respiratory vaccination, respectively. Survey data indicated 30%, 17%, 18%, 21%, and 21% of respondents felt that buyers paid a premium for the practices of castration, deworming, bunk training, 45-d weaning period, and respiratory vaccination, respectively. Survey responses illustrated that 22% and 19% of producers felt that deworming and bunk training, respectively, improved calf marketability. A total of 12% of respondents indicated that announcing days weaned and vaccination history at the time of sale improved calf value. When asked to indicate constraints to implementing management practices, n = 211, n = 277, n = 258, n = 388, and n = 542 responses were recorded regarding castration, deworming, bunk training, 45-d weaning period, and respiratory vaccination, respectively. According to survey results 15%, 26%, 20%, 17%, and 25% of producers felt that castration, deworming, bunk training, 45-d weaning period, or administering respiratory vaccinations, respectively, provided no benefit to their operations. Data illustrated that 7%, 9%, 10%, 9%, and 9% of respondents were unaware of any added value for the practices of castration, deworming, bunk training, 45-d weaning period, and administering respiratory vaccines. Relationships between the management practices of castration, deworming, and providing respiratory vaccines and the decision to market calves at weaning or post-weaning were evaluated. Data indicated weak significant negative correlation coefficients of -0.25, -0.28, and -0.21 for castration, deworming, and respiratory vaccines, respectively, and marketing at weaning. Conversely, weak significant positive correlations of 0.25, 0.30, and 0.25, respectively, were observed for castration, deworming, and respiratory vaccines with marketing post-weaning. A substantial percentage of producers subscribed to calf best management practices. However, because the observed correlation coefficients were weaker than expected producer education regarding optimal marketing strategies may lead to an improvement in capturing market premiums related to management practices.