Quantitative Analysis Of Distribution Research Articles

324 (PB104) - Quantitative analysis of EGFR expression and distribution upon drug treatment in colorectal organoid models

Background: Human organoids are patient-derived tissues that can be expanded in vitro by stimulating the (cancer) stem cells with WNT pathway activators, treatment with differentiation inhibitors and by providing growth factors in an extracellular matrix environment. These organoids form three-dimensional (3D) multicellular structures that polarize and self-organize and express relevant disease-related markers, which makes an organoid biobank ideal for testing the efficacy and mode of action of compounds and antibodies across a diverse patient population. Here, our colorectal organoid biobank and high content imaging platform were used to characterize EGFR dynamics upon drug treatment. Methods: An established biobank of normal colon and colorectal cancer organoid models was characterized for its sensitivity to the growth factor EGF, EGFR-inhibitors (Cetuximab), and standard-of-care compounds. To study the distribution of the EGF receptor, antibodies followed by immunofluorescence staining were used to detect the localization and distribution upon growth factor stimulation. (Inducible) knockdown organoid models with shRNA constructs targeting EGFR were generated to validate the findings. Results: The 3D organoid screening and our proprietary image analysis platform allows the in-depth detection and distinction of growth factor responses that not necessarily only relate to proliferation. By making use of this system, the sensitivity of organoid models to EGF stimulation that are independent of EGF for their outgrowth could be determined. By combining the detection of the target, EGFR, with the detection of targeting EGFR-inhibitory antibodies by immunofluorescence followed by image analysis, the redistribution of the receptor upon EGF-stimulation and in response to antibody exposure could be visualized and quantified. This revealed that EGFR is internalized in the first hours upon EGF stimulation. Along with making use of (inducible) knockdown organoids, it also revealed that different EGFR-targeting antibodies have different effects on the redistribution, internalization, and degradation of EGFR. Conclusions: The high content imaging platform in combination with high throughput screening in 3D-cultured organoid models allows compound and antibody testing in physiologically relevant patient-derived models to not only study the sensitivity to novel compounds, but also for patient stratification and to study the mode of action or understand the underlying relevant biology. The outcome of this work demonstrated that organoids are versatile, multicellular structures that are highly suitable for studying the expression and redistribution of disease-relevant targets. No conflict of interest.

Quantitative analysis of respiratory viral distribution in forensic autopsy cases

Respiratory viruses can cause fatal systemic infections; therefore, post-mortem diagnosis is essential in forensic autopsy cases. However, little is known regarding the distribution of respiratory viruses in the body. In this study, we investigated the anatomical distribution of respiratory viruses in 48 forensic autopsy cases suspected of viral infections at our institute. Fast Track Diagnostics (FTD) Respiratory Pathogens 21 was used as a screening test for 20 respiratory viruses in nasopharyngeal swabs. In cases with positive results for virus detection by the screening test, the detected viruses were quantified in body fluid and organ specimens by virus-specific real-time reverse transcription polymerase chain reaction (RT-PCR) and digital PCR. Viruses were detected in 33 cases, with the viral distribution and load differing among the cases. Since various respiratory viruses were detected from the nasopharyngeal swab and its viral load was higher than those of other body fluid specimens, the nasopharyngeal swab was suggested as a useful specimen for the post-mortem detection of respiratory viruses. Viruses were detected in almost all specimens including the serum in six cases. Considering the viral distribution in the body, pathological findings, and ante-mortem symptoms, these cases were presumed to be systemically infected, having died in the acute infection phase. In conclusion, the anatomical distribution of respiratory viruses can help indicate ante-mortem systemic conditions and the cause of death.

Quantitative Distribution Characterization and Correlation Study of Composition, Structure and Hardness of Rim Region in Railway Wheel.

The railway wheel is the key component of high-speed railway train. To assure the safety in service, higher requirements are put forward in this study for the composition, microstructure uniformity, and comprehensive properties of wheel materials. In this paper, the high throughput quantitative distribution characterization methods of composition, microstructure, inclusions and Vickers hardness of high-speed railway wheel materials based on the spark source original position analysis technique, high throughput scanning electron microscope (SEM) combined with image batch processing technology, and automatic two-dimensional quantitative distribution analysis technique of inclusions and micro hardness have been studied. The distribution trend of the content of nine elements, size and quantity of sulfides and oxides, ferrite area fraction, and Vickers hardness from the wheel tread surface to the radial depth of about 50 mm below the surface has been discussed. The influence of inclusions distribution on the element segregation and the effect of rim-chilling process with different water spraying angle on the distribution of microstructure and micro hardness have been investigated. It was found that unsynchronized cooling on both sides of the rim altered the phase behavior of ferrite and pearlite and obvious inhomogeneity distribution of ferrite appeared, which led to the asymmetrical Vickers hardness in areas near or away from the flange. Based on the quantitative characterization of area fraction and micro hardness on the same location of wheel rim, a statistical mapping relationship between ferrite area fraction and Vickers hardness was established.

A Geometry Optimization of Spiral Grain Selector During Directional Solidification of Nickel‐Based Superalloy

A spiral grain selector with excellent geometric parameters can ensure qualified single-crystal (SX) is selected while decreasing lesser thermal gradient (G) during casting of SX nickel-based superalloy . In this paper, three configurations of spiral grain selectors with different height of starter block (H = 18, 25, 35 mm) and same spiral passage are adopted. Based on the quantitative analysis of orientation distribution of grains in starter block, it is found that the deviation of <001> oriented grains in the projection zone of spiral passage inlet (circle with a diameter of 4 mm) are smaller than grains of overall cross-section (circle with a diameter of 10 mm), which verify that starter block with smaller diameter have better optimization effect of grain orientation. Moreover, the average deviation of <001> oriented grains decreases to a range of 6.6–10.8° when the height of starter block is 18–27 mm, and SX selection is completed on the position of less than half turn in spiral passage regardless of the number of grains in the inlet position. Finally, a modified spiral grain selector is designed from the perspective of practical production, of which total height is reduced by at least 15 mm, and can decrease lesser G at some extent during casting .

Quantitative analysis of spatial distribution of lymphocytes in hepatocellular carcinoma: A biomarker correlated with survival and gene expression in cancer immune system.

4119 Background: Tumor microenvironment (TME) is known to impact prognosis in hepatocellular carcinoma (HCC). Although digital pathology and artificial intelligence have been adopted in modern medicine and oncology, few quantitative biomarkers have been identified to predict the prognosis and guide treatment for HCC via an automated analysis of TME at the cellular level. Methods: Histopathological images and clinical data of 365 cases with HCC were obtained from TCGA (The Cancer Genome Atlas), and 60 of HCC pathology images and cancer lesion annotations were collected from PAIP2019 [1]. DenseNet-based HCC segmentation model (F1-score, 0.904) and Hover-Net-based cell detection model (F1-score, 0.914) were developed using PAIP2019 and MoNuSac datasets, respectively [2,3,4]. Each histopathology image of TME was segmented via the segmentation model into two areas: 1) non-tumoral regions that include the stroma; 2) tumoral regions where HCC cells are concentrated. The cell detection model recognized individual cells on images, specified lymphocytes, and calculated ratios of lymphocyte to total cell count (RLTCC) in segmented regions. RLTCC was then correlated with clinical survival outcomes, HCC primary risk factors, and RNA expression profiles. Results: RLTCC in tumoral regions was not significantly associated with prognosis. Patient groups with higher RLTCC in non-tumoral regions (RLTCC in NT) showed better overall survival (OS) than those with lower RLTCC in NT regardless of HCC risk factors (median OS 45.7 vs 18.6 months; log hazard ratio of -1.6 ± 1.1, p=0.006). These patients had significantly enriched expression of genes (p&lt;0.05) related to cancer antigen presentation (higher gene expression by +33.7%), recognition of cancer cells by T-cell (+32.0%), T-cell priming and activation (+32.2%), immune cell localization to tumors (+31.9%), and killing of cancer cells (+24.7%). Those with HCC etiology of hepatitis B and C had more patients in the higher RLTCC in NT (17/21 patients, 81.0%; 23/29, 79.3%, respectively). In comparison, those with alcohol consumption showed equal distribution (26/53, 49.1%). The RLTCC in NT in hepatitis B/C groups was statistically higher than alcohol consumption group (p&lt;0.05). Conclusions: A digital prognostic biomarker, RLTCC in NT of TME was identified as a significant prognostic indicator, and it was shown to correlate with RNA gene expression related to T-cell mediated cancer immunity. A retrospective analysis of clinical response from systemic therapy in relation to digital biomarkers is underway and will be reported.

Computational prediction of the long-term behavior of the femoral density after THR using the Silent Hip stem

Aseptic loosening due to the progressive periprosthetic bone resorption following total hip replacement is a crucial concern, that causes complications and failure of the arthroplasty surgery. The mismatch in stiffness between the hip implant and the surrounding femoral bone is one of the key factors leading to bone density resorption. This paper aimed to investigate the long-term response of the femoral bone after THR using the Silent Hip stem. For this purpose, a validated thermodynamic-based computational model was used to compute the change in bone density before and after THR. This model incorporated essential factors involved in bone remodeling process, such as mechanical loading, and biochemical affinities. The results of the numerical simulations using 3D finite element analysis were analyzed in five zones of interest qualitatively and quantitatively. Bone density predictions showed notable bone resorption in cervical areas, specifically in zone 1 and zone 5 of −18.7% and −14%, respectively. Conversely, bone formation was observed in the greater trochanter area (zone 2) of +25%. Stress shielding seemed to occur at cervical area due to the reduction in the mechanical loading in this region. Based on the quantitative analysis of the bone density distribution throughout the femoral bone, it appears that the Silent Hip stem achieved less bone resorption compared to conventional hip stem designs reported in the literature, which could be used for active patients.

Quantitative analysis of regional distribution of tau pathology with 11C-PBB3-PET in a clinical setting.

PurposeThe recent developments of tau-positron emission tomography (tau-PET) enable in vivo assessment of neuropathological tau aggregates. Among the tau-specific tracers, the application of 11C-pyridinyl-butadienyl-benzothiazole 3 (11C-PBB3) in PET shows high sensitivity to Alzheimer disease (AD)-related tau deposition. The current study investigates the regional tau load in patients within the AD continuum, biomarker-negative individuals (BN) and patients with suspected non-AD pathophysiology (SNAP) using 11C-PBB3-PET.Materials and methodsA total of 23 memory clinic outpatients with recent decline of episodic memory were examined using 11C-PBB3-PET. Pittsburg compound B (11C-PIB) PET was available for 17, 18F-flurodeoxyglucose (18F-FDG) PET for 16, and cerebrospinal fluid (CSF) protein levels for 11 patients. CSF biomarkers were considered abnormal based on Aβ42 (< 600 ng/L) and t-tau (> 450 ng/L). The PET biomarkers were classified as positive or negative using statistical parametric mapping (SPM) analysis and visual assessment. Using the amyloid/tau/neurodegeneration (A/T/N) scheme, patients were grouped as within the AD continuum, SNAP, and BN based on amyloid and neurodegeneration status. The 11C-PBB3 load detected by PET was compared among the groups using both atlas-based and voxel-wise analyses.ResultsSeven patients were identified as within the AD continuum, 10 SNAP and 6 BN. In voxel-wise analysis, significantly higher 11C-PBB3 binding was observed in the AD continuum group compared to the BN patients in the cingulate gyrus, tempo-parieto-occipital junction and frontal lobe. Compared to the SNAP group, patients within the AD continuum had a considerably increased 11C-PBB3 uptake in the posterior cingulate cortex. There was no significant difference between SNAP and BN groups. The atlas-based analysis supported the outcome of the voxel-wise quantification analysis.ConclusionOur results suggest that 11C-PBB3-PET can effectively analyze regional tau load and has the potential to differentiate patients in the AD continuum group from the BN and SNAP group.

Sealing mechanism study of laryngeal mask airways via 3D modelling and finite element analysis

Proper sealing of laryngeal mask airways (LMAs) is critical for airway management in clinical use. Understanding the sealing mechanism can significantly help front-line anaesthetists to reduce the incidence of adverse events. However, anaesthetists, who may not have the most substantial engineering backgrounds, lack intuitive ways to develop an understanding of the LMA sealing mechanism effectively. The paper aims to study the LMA-pharynx sealing mechanisms from the perspective of front-line anaesthetists. We use a computer-aided 3D modelling technique to visualise the LMA—pharynx interactions, which helps anaesthetists identify the critical areas of complications. Furthermore, we conduct a quantitative pressure distribution analysis of the LMA-pharynx contacting surface using the finite element analysis technique, which helps further understand the sealing mechanics in those areas. We present two cases studies based on one male volunteer, aged 50, inserted with a ProSeal LMA. In the first case, a relatively low cuff pressure (CP) was applied to simulate the clinical circumstances in which complications related to air leakage are most likely to happen; in the second case, we increase the CP to a relatively high value to simulate the scenarios with an increased risk of complications related to high mucosal pressure. The experiments suggest the follows: (1) Sore throat complications related to high mucosal pressure is most likely to occur in the hypopharynx with a high CP setting, particularly in the areas where the cricoid cartilage presses the mucosa. (2) The narrow hyoid bone super horn width likely causes LMA insertion difficulties. (3) Insufficient CP will significantly increase the risk of air leakage in the oropharynx. A complete sealing pressure line in the contacting surface will be formed with sufficient CP, thereby preventing the air leakage into the oral.

Online data sharing with virtual social interactions favor scientific and educational successes in a biodiversity citizen science project

ABSTRACT Given the diversity of biodiversity citizen science projects' design and objectives, a major challenge is to better understand the factors influencing their successes. We study an online communication space where participants to a participative biodiversity monitoring program share their data and freely interact. A quantitative analysis of the comments' distribution among participants reveals the multiplicity of epistemic and social roles they endorse: helping collective identification of plants and insects, moderating the respect of the scientific protocol, or maintaining community's life. By building a typology of these comments, we show how this space of discussion favors exchanges and reflections about esthetical, interpersonal, biological and methodological aspects. We argue that the existence of such spaces favors all together the production of high-quality data, science learning, and individual commitment towards environmental issues. Maybe more importantly, they allow citizens to build and strengthen collective epistemic and affective relationships with science.

Optimum Multiparameter Analysis of Water Mass Structure off Western Guangdong during Spring Monsoon Transition

Water masses and their variability play vital roles in regulating ocean circulation, material exchanges and biogeochemical processes. However, there is still a lack of quantitative analysis of water mass distributions in coastal waters of the South China Sea. Here, two oceanographic cruise observations in April and May 2016 are used to quantify water mass distributions, pathways and mixture, and their intraseasonal variability off western Guangdong during the spring monsoon transition. Temperature and salinity observations qualitatively reveal that there are three types of water masses: the Pearl River diluted water (PRDW, salinity (S) = 22 psu, potential temperature (θ) = 25 °C), the South China Sea surface water (SCSSW, S = 34 psu, θ = 28 °C) and the South China Sea subsurface water mass (SCSSUW, S = 34.5 psu, θ = 17 °C). Their relative contributions and intraseasonal variability are quantified using the Optimum Multiparameter (OMP) method. The PRDW is largely confined to the upper 10 m layer in shallow nearshore waters (depths &lt; 30 m), with a maximum contribution &gt;90% near the Pearl River Estuary. The SCSSW mainly dominates the rest of the surface layer above 20 m, with a contribution &gt;50% in offshore regions. The layer below 20 m is primarily composed of ~60% SCSSW and ~40% SCSSUW. A comparison between the two different observations suggests that the PRDW tends to expand southwestward and the SCSSUW spreads offshore, whereas the SCSSW moves landward and is situated underneath the surface fresh PRDW. These characteristics are very likely associated with the wind transition from weak southeasterly in April to strong northeasterly in May, which enhances the southwestward coastal current and the onshore surface Ekman transport from offshore waters.

Total Water Column Analysis Shows the Importance of a Single Species in Subsurface Chlorophyll Maximum Thin Layers in Stratified Waters

Marine phytoplankton form the base of marine food webs and are the driving force of the marine carbon cycle, so understanding the dynamics of their blooms is critical. While near-surface marine productivity (&amp;lt;10 m water depths) is extensively documented, that of the subsurface is less well characterised. Increasing evidence of the importance of subsurface chlorophyll maxima (SCM) and climatically driven increases in stratification of surface waters that promote SCM development call for improved sampling of the subsurface. To address this, we targeted the summer stratified waters of the Western English Channel, part of the NW European shelf seas, where SCM are commonly developed. In situ holography was applied to undertake the highest ever resolution, total water column, quantitative analysis of microplankton distribution, and demonstrated the importance of a SCM, co-located with the thermocline, dominated by a single species, the dinoflagellate Ceratium fusus. This species was dominant in the SCM over a wide area of the NW European shelf in the June/July 2015 study period and comprised up to 85% of the SCM biomass. Analysis of similarity and multivariate non-metric multidimensional scaling showed the phytoplankton community of the SCM to be statistically distinct from those of the surface and deep waters. Holography also revealed a fine scale layering of taxa at different levels within the SCM, likely reflecting ecological differences. Some taxa followed the peak abundance of C. fusus, while others reached maximum abundances immediately below or above the C. fusus maximum, suggesting the possible operation of exclusion mechanisms. Additionally, the detection of abundant aggregates located only within and beneath the SCM demonstrates the potential importance of this deep production for the export of carbon to the sea floor. Some predictions of phytoplankton productivity propose a shift to smaller cells in the more stratified oceans of the future resulting in declining production and export. Results presented here, however, contribute to a growing body of evidence that suggests, on the contrary, that key species among the larger celled/colonial, SCM-adapted diatoms and dinoflagellates may instead be selected in stratified conditions, driving increased production and export.

Quantitative Analysis of Droplet Size Distribution in Plant Protection Spray Based on Machine Learning Method

Spray droplet size is the main factor affecting the deposition uniformity on a target crop. Studying the influence of multiple factors on the droplet size distribution as well as the evaluation method is of great significance for improving the utilization of pesticides. In this paper, volume median diameter (VMD) and relative span (RS) were selected to evaluate the droplet size distribution under different hollow cone nozzles, flow rates and spatial positions, and the quantitative models of VMD and RS were established based on machine learning methods. The results showed that support vector regression (SVR) had excellent results for VMD (Rc = 0.9974, Rp = 0.9929), while multi-layer perceptron (MLP) had the best effect for RS (Rc = 0.9504, Rp = 0.9537). The correlation coefficient of the prediction set is higher than 0.95, showing the excellent ability of machine learning on predicting the droplet size distribution. In addition, the visualization images of the droplet size distribution were obtained based on the optimal models, which provided intuitive guidance for realizing the uniform distribution of pesticide deposition. In conclusion, this study provides a novel and feasible method for quantitative evaluation of droplet size distribution and offers a theoretical basis for further determining appropriate operation parameters according to the optimal droplet size.

High-efficiency utilization of Tb in enhancing the coercivity of Nd-Fe-B magnets by multicomponent Tb70−xPrxCu10Al10Zn10 (x = 0–30) film diffusion

The effect of multicomponent Tb70−xPrxCu10Al10Zn10 (x = 0–30) film diffusion on microstructure and magnetic properties of sintered Nd-Fe-B magnets was investigated in this paper through magnetron sputtering system. The coercivity increased significantly from 11.5 kOe to 17.5 kOe, 18.8 kOe, 19.8 kOe, and 17.8 kOe for the processed samples by Tb40Pr30Cu10Al10Zn10, Tb60Pr10Cu10Al10Zn10, Tb70Cu10Al10Zn10 and Tb, respectively. The remanence and the maximum magnetic energy product of multicomponent film diffused magnets were all higher than those of Tb diffused magnet. Particularly, compared with Tb diffused magnet, the ΔHcj/wt%Tb (the coercivity enhancement per wt% Tb usage) of Tb40Pr30Cu10Al10Zn10, Tb60Pr10Cu10Al10Zn10 and Tb70Cu10Al10Zn10 diffused samples increased by 105%, 63.4% and 57.5%, respectively. It is obviously that the Tb utilization in multicomponent diffusion sources has a higher efficiency in coercivity enhancement. The quantitative analysis of Tb distribution was characterized for comparison. The extra addition of Cu/Al/Zn elements in Tb70Cu10Al10Zn10 diffusion source would enter into the rare earth-rich (RE-rich) grain boundary phases, and an easy diffusion channel was formed to promote the infiltration of Tb element. The results show that improved distribution uniformity of the Tb-rich shell, deeper shell-core structure and the increased local grain boundary phases are the key factors for the significant enhancement of coercivity in multicomponent diffusion magnet. In addition, on one hand, the easily combination of Tb and Cu/Al/Zn elements effectively prevented Tb from entering the main phases. On the other hand, the thinner shell-core structure was observed due to the uniform distribution of Tb in Tb70Cu10Al10Zn10 diffused magnet. These two factors jointly lead to the increase of remanence. This work puts forward that using multicomponent alloy as diffusion sources provides a composition diversity and cost-effective way to enhance the magnetic properties of sintered Nd-Fe-B magnets, while reducing the consumption of Tb.

X-ray scattering as an effective tool for characterizing liquid metal composite morphology.

Quantitative analysis of particle size and size distribution is crucial in establishing structure-property relationships of composite materials. An emerging soft composite architecture involves dispersing droplets of liquid metal throughout an elastomer, enabling synergistic properties of metals and soft polymers. The structure of these materials is typically characterized through real-space microscopy and image analysis; however, these techniques rely on magnified images that may not represent the global-averaged size and distribution of the droplets. In this study, we utilize ultra-small angle X-ray scattering (USAXS) as a reciprocal-space characterization technique that yields global-averaged dimensions of eutectic gallium indium (EGaIn) alloy soft composites. The Unified fit and Monte Carlo scattering methods are applied to determine the particle size and size distributions of the liquid metal droplets in the composites and are shown to be in excellent agreement with results from real-space image analysis. Additionally, all methods indicate that the droplets are getting larger as they are introduced into composites, suggesting that the droplets are agglomerating or possibly coalescing during dispersion. This work demonstrates the viability of X-ray scattering to elucidate structural information about liquid metal droplets for material development for applications in soft robotics, soft electronics, and multifunctional materials.

A novel method for measuring and evaluating spatial distribution of straw incorporated by rotary tillage

AbstractStraw incorporation after tillage plays an essential role in soil organic matter and fertility. Despite the importance of understanding the effect of tillage on straw distribution in the soil, an accurate method to measure and evaluate the spatial distribution of straw has not been developed. In this work, we proposed a method for quantifying straw distribution in soil following tillage. The approach uses a straw spatial coordinate digitizer, Pro/Engineer drawing software, and MATLAB visualization software. Straw of four different lengths was mixed into soil by a rotary tillage. Results indicated that the uniformity of straw spatial distribution decreased with the increase of straw length. T50 (50‐mm straw length) had the greatest uniformity. As a result, it is recommended that straw be cut to 50 mm or shorter. This work offers a new insight into the quantitative analysis of straw spatial distribution in soil.

Numerical Study of Microplastic Dispersal in Simulated Coastal Waters Using CFD Approach

Microplastics are accumulated in coastal regions due to human activity. Although limited data from beach surveys show an increase in microplastics in marine habitats, continuous monitoring is required on microplastics loading and distribution in the marine environment. In this study, CFD numerical simulations using VOF and Airy wave models coupled with DPM were carried out to investigate the effects of various variables on microplastics motion and distribution in a simulated coastal marine environment. PET, PU, and PP microplastic particles were released from the oceanside to investigate the effects of microplastic type, size, and shape with two different ocean–water flow velocities and temperature conditions. Particle position data from their tracking were used to determine the effect of each variable on the spatial distribution of particles. The quantitative analysis of vertical and horizontal distribution of microplastics particles revealed that, with low water velocity, most of the large denser spherical PET and PU microplastics would sink towards the bottom and settle at the ocean floor, while most of the small non-spherical particles would float near the surface and travel towards the shoreline. For lighter PP microplastics, larger spherical particles would float more readily than denser spherical ones. Large spherical and smaller non-spherical PP particles travel farthest reporting to the shoreline. Increasing the oceanwater velocity altered the distribution patterns in which lighter PP particles, almost independent of shape and size, travel swiftly to the shoreline together with smaller non-spherical denser microplastics. Lastly, the simulation results revealed that the oceanwater temperature did not play any significant role in the spatial distribution of microplastic particles.

Identifying promising anticancer Sulforaphane derivatives using QSAR, Docking, and ADME studies

In cruciferous vegetables such as broccoli, sulfur-rich isothiocyanates, most notably sulforaphane (SFN), has shown anti-cancer properties, including cell cycle regulation, inducing apoptosis, and metastasis. Sulforaphane is a natural antioxidant that regulates several signal transduction pathways controlling oxidative stress, cellular defense, and cardiovascular disease. This paper attempts to elucidate the most drug-like SFN derivative through computational methods, including molecular docking, Quantitative Structure-Activity Relationship (QSAR), and absorption, distribution, metabolism, and excretion (ADME) analysis. From our studies, we can conclude that phenylethyl isothiocyanate (PEITC) has the most therapeutic potential out of a small set of 7 SFN derivatives. It is a confirmed lead-like compound by testing QSAR descriptors, notably the Dragon consensus drug-like score and lead-like score 2. PEITC also proves to be the most bioavailable derivative, as it is predicted to have high gastrointestinal absorption (GIA) and blood-brain barrier (BBB) permeability. In addition, it is in the optimal range for 5 out of 6 bioavailability properties proposed by the Abbot Bioavailability Score1. Lastly, from docking studies, PEITC had the highest average binding affinity overall, meaning that it holds a vital role in cancer prevention through molecular mechanisms.

Quantitative analysis of spatial distribution of land surface temperature (LST) in relation Ecohydrological, terrain and socio- economic factors based on Landsat data in mountainous area

Land surface temperature (LST) is considered as one of the most significantly effective factors on the regional climate and ecology, playing an important role in connecting surface energy and water exchange. In mountainous regions, LST reveals lots of inconsistencies due to the effect of such factors as topography, vegetation, solar radiation, etc. We sought to investigate the the temporal and spatial variation LST in different years and its relationship with effective factors in 5 dimensions using Multiple statistical methods, the sepidan region in northwest Iran. The multi-factorial land use, topographic (elevation, slope, aspect), biophysical indices (normalized difference vegetation index (NDVI), normalized difference moisture index (NDMI), normalized difference built up index (NDBI), and modified of normalized difference water index (MNDWI)), socio-economic (fossil fuel CO 2 emissions (FFCOE) and road density(RD)), and climate (temperature and solar radiation) was studied in the current research. To this end, Images of July 1998 and 2017 were extracted from Thematic Mapper (TM5) and Operational Land Imager/Thermal infrared sensors (OLI/TIRS8). Moreover, ordinary least squares regression (OLS), Best subset regression, and Hierarchical Partitioning Analysis (HP) were used to investigate the relationship between LST and relevant effective factors. The results indicated that the temperature range varied from 10 to 53 °C in the time period mentioned. The highest amount of LST was observed in barren land use and the lowest one was found in garden lands. An negative correlation was found between LST and elevation. On the other hand, the highest value of the Laps rate of surface temperature was observed in the southern aspects and the lowest one was observed in the western aspects. Furthermore, the highest and lowest values of lase rate were found in slopes less than 10°, and in 50 to 60-degree slopes, respectively. The results of the OLS correlation indicated a negative correlation between LST and NDVI, NDMI, and MNDWI, and a positive correlation of LST with climatic and socio-economic indicators. LST’s highest and lowest correlations were found to be with vegetation (R 2 = 0.95) and road density (R 2 = 0.1). Finally, while in 1998 temperature and vegetation were identified as the most influential factors on LST, it was the elevation that was found to be the most effective factor on LST in 2017 with the effective rate of 82.72%. This study offers a valuable viewpoint on the temporal and spatial variations of LST, their complexity, and the environmental factors that affect them. The viewpoint could, therefore, be used for prospective studies on the analysis of the ecosystem's reaction to climate changes.

Quantitative analysis of size and regional distribution of corpora amylacea in the hippocampal formation of obstructive sleep apnoea patients

Corpora amylacea (CoA) are spherical aggregates of glucose polymers and proteins within the periventricular, perivascular and subpial regions of the cerebral cortex and the hippocampal cornu ammonis (CA) subfields. The present study quantified the distribution of CoA in autopsied hippocampi of patients with obstructive sleep apnoea (OSA) using ethanolamine-induced fluorescence. CoA were observed in 29 of 30 patients (96.7%). They were most abundant in periventricular regions (wall of lateral ventricle, alveus, fimbria and CA4), rarely found in the CA3 and CA1, and undetectable in the CA2 or subiculum. A spatiotemporal sequence of CoA deposition was postulated, beginning in the fimbria and progressively spreading around the subpial layer until they extended medially to the wall of the lateral ventricle and laterally to the collateral sulcus. This ranked CoA sequence was positively correlated with CoA packing density (count and area fraction) and negatively correlated with CoA minimum diameters (p < 0.05). Although this sequence was not correlated with age or body mass index (BMI), age was positively correlated with the mean and maximum diameters of CoA. These findings support the view that the spatiotemporal sequence of CoA deposition is independent of age, and that CoA become larger due to the accretion of new material over time.

Quantitative Analysis of Concentration Distribution in Non-Evaporative Diesel Spray with Laser Induced Fluorescence Method

Quantitative Analysis of Concentration Distribution in Non-Evaporative Diesel Spray with Laser Induced Fluorescence Method