Cheminformatics-based identification of phosphorylated RET tyrosine kinase inhibitors for human cancer.

Background: Rearranged during transfection (RET), an oncogenic protein, is associated with various cancers, including non-small-cell lung cancer (NSCLC), papillary thyroid cancer (PTC), pancreatic cancer, medullary thyroid cancer (MTC), breast cancer, and colorectal cancer. Dysregulation of RET contributes to cancer development, highlighting the importance of identifying lead compounds targeting this protein due to its pivotal role in cancer progression. Therefore, this study aims to discover effective lead compounds targeting RET across different cancer types and evaluate their potential to inhibit cancer progression. Methods: This study used a range of computational techniques, including Phase database creation, high-throughput virtual screening (HTVS), molecular docking, molecular mechanics with generalized Born surface area (MM-GBSA) solvation, assessment of pharmacokinetic (PK) properties, and molecular dynamics (MD) simulations, to identify potential lead compounds targeting RET. Results: Initially, a high-throughput virtual screening of the ZINC database identified 2,550 compounds from a pool of 170,269. Subsequent molecular docking studies revealed 10 compounds with promising negative binding scores ranging from -8.458 to -7.791 kcal/mol. MM-GBSA analysis further confirmed the potential of four compounds to exhibit negative binding scores. MD simulations demonstrated the stability of CID 95842900, CID 137030374, CID 124958150, and CID 110126793 with the target receptors. Conclusion: These findings suggest that these selected four compounds have the potential to inhibit phosphorylated RET (pRET) tyrosine kinase activity and may represent promising candidates for the treatment of various cancers.

Assessing the Correlation of Periodontal Inflamed Surface Area (PISA) With Systemic Inflammatory Markers.

Background Periodontitis has a vital role in eliciting a cross-reactivity or systemic inflammatory response, making periodontal inflamed surface area (PISA) a primary contributor to the inflammatory burden posed by periodontitis. PISA helps in the quantification of the amount of inflamed periodontal tissue. However, the existing literature data concerning PISA as an indicator of inflammatory burden are scarce, with limited research on the relationship between systemic inflammatory markers and PISA. Aim The present clinic-hematological cross-sectional study aimed to correlate PISA with systemic inflammatory markers. The study also aimed to assess serum concentrations of inflammatory markers such as erythrocyte sedimentation rates (ESR), C-reactive protein (CRP), and peripheral blood markers such as neutrophils and monocytes and to correlate these markers with PISA. Methods The study assessed 62 subjects, who were divided into two groups of 31 subjects, each following bleeding on probing (BOP) criteria. Group I consisted of subjects with generalized chronic gingivitis, and Group II included subjects with generalized chronic periodontitis. In two groups, BOP, probing pocket depth, clinical attachment level, and gingival recession were assessed along with PISA by a custom-made R function derived from a pre-existing, freely available MS Excel spreadsheet (Microsoft Corporation, Redmond, Washington). The results of the assessment were then compared. Results A statistically highly significant positive correlation was seen in PISA and CRP with a correlation coefficient of 0.4875 and p-value of 0.000059. A similar statistically significant positive correlation was seen in ESR and PISA with a correlation coefficient of 0.4089 and p-value of 0.000968. A statistically non-significant correlation was seen in neutrophils and PISA with p=0.576018. However, a moderate and positive statistically significant association was seen in monocyte and PISA with a correlation coefficient of 0.3258 and p-value of 0.009956. Conclusions The present study concludes that most of the common systemic inflammatory markers have a positive correlation with PISA. However, more studies are required to establish this correlation.

The impact of obesity on body surface area adjusted estimated glomerular filtration rate in patients with chronic kidney disease.

BACKGROUND: Assessment of kidney function is necessary for prescribing renally excreted drugs. The estimated glomerular filtration rate (eGFR) routinely reported by laboratories is indexed to a body surface area (BSA) of 1.73 m2. In obese patients, the indexed eGFR may underestimate directly measured GFR. AIMS: To determine the prevalence of obesity in patients with chronic kidney disease (CKD) and examine the effect of adjusting the indexed eGFR for patient BSA (deindexing) across CKD Stages 2-5. METHODS: We conducted a cross-sectional study of 575 adults with stable CKD from two general nephrology clinics over 6 months. Dialysis and kidney transplant patients were excluded. We used four equations (Mosteller, Dubois, Haycock and Schlich) to determine BSA based on actual body weight and applied Bland-Altman plots and piecewise linear regression to examine the relationship between deindexed and indexed eGFR. RESULTS: The median age was 68 years (58% male). The prevalence of overweight and obesity was 31% and 47% respectively. Mean body mass index was 29.7 kg/m2. The Schlich equation for BSA produced the smallest adjustment in eGFR, while the Haycock equation produced the largest adjustment. Males experienced the largest change in eGFR from deindexing because of larger BSAs. Although bias became increasingly positive with higher eGFR, the linear regression stratified by CKD stage indicated that deindexing had little impact with eGFR <45 mL/min/1.73 m2. CONCLUSIONS: In CKD, deindexing the Chronic Kidney Disease Epidemiology Collaboration eGFR may not be necessary when the eGFR is <45 mL/min/1.73 m2, particularly if the patient is female.

Hierarchical Y Zeolite-Based Catalysts for VGO Cracking: Impact of Carbonaceous Species on Catalyst Acidity and Specific Surface Area.

The performance of catalysts prepared from hierarchical Y zeolites has been studied during the conversion of vacuum gas oil (VGO) into higher-value products. Two different catalysts have been studied: CatY.0.00 was obtained from the standard zeolite (Y-0.00-M: without alkaline treatment) and CatY.0.20 was prepared from the desilicated zeolite (Y-0-20-M: treated with 0.20 M NaOH). The cracking tests were carried out in a microactivity test (MAT) unit with a fixed-bed reactor at 550 °C in the 20-50 s reaction time range, with a catalyst mass of 3 g and a mass flow rate of VGO of 2.0 g/min. The products obtained were grouped according to their boiling point range in dry gas (DG), liquefied petroleum gas (LPG), naphtha, and coke. The results showed a greater conversion and selectivity to gasoline with the CatY.0.20 catalyst, along with improved quality (RON) of the C5-C12 cut. Conversely, the CatY.0.00 catalyst (obtained from the Y-0.00-M zeolite) showed greater selectivity to gases (DG and LPG), attributable to the electronic confinement effect within the microporous channels of the zeolite. The nature of coke has been studied using different analysis techniques and the impact on the catalysts by comparing the properties of the fresh and deactivated catalysts. The coke deposited on the catalyst surfaces was responsible for the loss of activity; however, the CatY.0.20 catalyst showed greater resistance to deactivation by coke, despite showing the highest selectivity. Given that the reaction occurs in the acid sites of the zeolite and not in the matrix, the increased degree of mesoporosity of the zeolite in the CatY.0.20 catalyst facilitated the outward diffusion of products from the zeolitic channels to the matrix, thereby preserving greater activity.

Cardiac output in patients with small annuli undergoing transcatheter aortic valve implantation with self-expanding versus balloon expandable valve (COPS-TAVI).

BACKGROUND: There is limited data on cardiac output in patients with small aortic annuli undergoing trans-catheter aortic valve implantation (TAVI) according to the implanted platform of balloon-expandable (BEV) compared to self-expanding valves (SEV). METHODS: This is a retrospective analysis of consecutive patients with severe aortic stenosis and small annuli who underwent successful TAVI. Cardiac output was measured using echocardiography within 4 weeks following TAVI. Data were recorded and analysed by an experienced operator who was not aware of the type of the implanted valve. RESULTS: 138 patients were included in the analysis, of whom 57 % underwent TAVI with BEV. Clinical and echocardiographic characteristics were comparable between the two platforms, except for more frequent previous cardiac surgery and smaller indexed aortic valve in the BEV group. There was no relationship between computed tomography-derived aortic annulus area and cardiac output post TAVI. When compared to patients who underwent TAVI with BEV, those with SEV had larger cardiac output [mean difference - 0.50 l/min, 95 % CI (-0.99, -0.01)] and cardiac index [mean difference - 0.20 l/min/m2, 95 % CI (-0.47, 0.07)], although the latter did not reach statistical significance. Unlike patients with small body surface area, in those with large body surface area both cardiac output and cardiac index were statistically larger in patients who underwent SEV compared to BEV. CONCLUSION: Cardiac output, as measured by echocardiography, was larger in patients with small annuli who underwent TAVI procedure with SEV compared to BEV. Such difference was more evident in patients with large body surface area.

Geometric relationship between the projected surface area and mass of a plastic particle.

The quantification of the mass of meso/microplastic (MMP) particles is crucial for assessing the global inventory of ocean plastics and assessing environmental and human health risks. Herein, linear regression models between mass and projected surface area on a log scale were established by directly measuring the masses of 4390 MMP particles collected at 35 sites in 17 Japanese rivers with an ultramicrobalance. The linear regression models estimated mass concentrations more accurately than any previous method based on geometric volume assuming several three-dimensional shapes. Additionally, linear regression models were quite reasonable for determining the geometric relationships of idealized cuboid particles. The slope of the linear regression models was dependent on the three-dimensional shapes of the particles, and their intercept was determined according to their third dimension. Moreover, the third dimension led to uncertainty in the mass estimation of particles; thus, the accuracies of the previous methods were relatively poor. Nevertheless, two limitations for mass measurement by linear regression models were identified, which determined the size range of the MMP particles on the projected surface area (ranging from 10-4 mm2 to 102 mm2) that is applicable for mass estimation of the particles collected from riverine and marine environments. Our results could be used to accurately estimate the mass concentrations in aquatic environments and provide insights into the geometric relationships between the mass and size of MMP particles.

Border row effects improved the spatial distributions of maize and peanut roots in an intercropping system, associated with improved yield.

Background: Border row effects impact the ecosystem functions of intercropping systems, with high direct interactions between neighboring row crops in light, water, and nutrients. However, previous studies have mostly focused on aboveground, whereas the effects of intercropping on the spatial distribution of the root system are poorly understood. Field experiments and planting box experiments were combined to explore the yield, dry matter accumulation, and spatial distribution of root morphological indexes, such as root length density (RLD), root surface area density (RSAD), specific root length (SRL), and root diameter (RD), of maize and peanut and interspecific interactions at different soil depths in an intercropping system. Results: In the field experiments, the yield of intercropped maize significantly increased by 33.45%; however, the yield of intercropped peanut significantly decreased by 13.40%. The land equivalent ratio (LER) of the maize-peanut intercropping system was greater than 1, and the advantage of intercropping was significant. Maize was highly competitive (A = 0.94, CR=1.54), and the yield advantage is mainly attributed to maize. Intercropped maize had higher RLD, RSAD, and SRL than sole maize, and intercropped peanut had lower RLD, RSAD, and SRL than sole peanut. In the interspecific interaction zone, the increase in RLD, RSAD, SRL, and RD of intercropped maize was greater than that of intercropped peanut, and maize showed greater root morphological plasticity than peanut. A random forest model determined that RSAD significantly impacted yield at 15-60 cm, while SRL had a significant impact at 30-60 cm. Structural equation modeling revealed that root morphology indicators had a greater effect on yield at 30-45 cm, with interactions between indicators being more pronounced at this depth. Conclusion: These results show that border-row effects mediate the plasticity of root morphology, which could enhance resource use and increase productivity. Therefore, selecting optimal intercropping species and developing sustainable intercropping production systems is of great significance.

Fluorine-18 FDG PET/CT and New NIMS Grading System for Chemotherapy Response in Breast Cancer.

Background: Positron emission tomography with computed tomography (PET-CT) using fluorine 18-fluorodeoxyglucose (F-18 FDG) is increasingly used to stage patients with locally advanced breast cancer and for assessing treatment response after neoadjuvant chemotherapy (NACT). Aims and Objectives: The aim of the study was to assess the correlation between PET-CT parameters and pathologic response of breast primary after NACT in breast cancer patients and to devise a grading system called NIMS grading system for response assessment using PET quantitative parameters. Materials and Methods: 55 patients who underwent F-18 FDG PET-CT before starting the therapy and again after completion of therapy were identified and included in the study. The clinical data and the histopathologic findings were recorded. All the patients received chemotherapy followed by surgery with axillary lymph node dissection. The PET-CT results were interpreted both qualitatively by visual analysis and quantitatively by estimating maximum Standardized uptake values(SUVmax) and other parameters - SUVmean, SUL, SUVBSA, Metabolic tumor volume (MTV) and Total lesion glycolysis (TLG). Results: The sensitivity and specificity of F-18 FDG PET-CT to detect the residual disease after neoadjuvant chemotherapy was 75.6% & 92.8% respectively. Differences between complete response and residual disease were significant for ΔSUVmax(p=0.005), ΔSUVmean(p=0.006), ΔSUL (0.005) and ΔSUVBSA(0.004), while ΔMTV and ΔTLG were not significantly different between the two groups. The new NIMS grading system included scoring of ΔSUVmax, ΔSUVBSA, ΔTLG and ΔMTV on scale of 1 to 4 and correlated well with PERCIST criteria. Conclusion: F-18 FDG PET-CT had a good accuracy in the detection of residual disease after completion of NACT. Pre chemotherapy PET-CT is not adequate to predict the response of primary tumour to chemotherapy. However, changes in the values of various PET-CT parameters are a sensitive tool to assess the response to chemotherapy. The new grading system is easy to use and showed good correlation to PERCIST.

A convenient calf proportion index calculator for survival prediction in overweight and obese patients with cancer.

OBJECTIVE: This study aimed to define the calf proportion index (CPI) and investigate its association with malnutrition and survival in overweight and obese patients with cancer. METHODS: This multicenter observational cohort study included 3499 patients diagnosed with cancer, including 3145 overweight and 354 obese individuals. The CPI was defined as the ratio of the cross-sectional area of the calf circumference (CC) to the body surface area (BSA). A CPI calculator that automatically calculated the CPI and survival probability based on the patient's sex, height, weight, and CC was developed. RESULTS: During a median follow-up of 44.1 months, 935 deaths were recorded. Receiver operating characteristic curves revealed that the CPI was better than CC and BSA as a predictor of survival, with AUCs for the 3-year mortality rate were 0.574, 0.553 and 0.529, respectively. In overweight and obese patients with cancer, the optimal CPI cut-off value was 0.65 % for men and 0.57 % for women. The Kaplan-Meier curve revealed that patients with a low CPI had lower survival. After adjusting confounding factors, a low CPI was an independent risk factor for overweight (hazard ratio [HR]: 1.29, 95 % confidence interval [CI]: 1.11-1.51, P < 0.001) and obesity (HR: 1.92, 95 % CI: 1.20-3.09, P = 0.007) in patients with cancer. The CPI exhibited significant prognostic value in patients with lung and digestive system cancers. The risk of malnutrition was significantly higher in patients with a low CPI (HR: 1.25, 95 % CI: 1.04-1.50, P = 0.019). CONCLUSIONS: The CPI is a useful prognostic indicator in overweight and obese patients with cancer, especially in obese patients.

Constant surface area-to-volume ratio during cell growth as a design principle in mammalian cells.

All cells are subject to geometric constraints, such as surface area-to-volume (SA/V) ratio, that impact cell functions and force biological adaptations. Like the SA/V ratio of a sphere, it is generally assumed that the SA/V ratio of cells decreases as cell size increases. Here, we investigate this in near-spherical mammalian cells using single-cell measurements of cell mass and surface proteins, as well as imaging of plasma membrane morphology. We find that the SA/V ratio remains surprisingly constant as cells grow larger. This observation is largely independent of the cell cycle and the amount of cell growth. Consequently, cell growth results in increased plasma membrane folding, which simplifies cellular design by ensuring sufficient membrane area for cell division, nutrient uptake and deformation at all cell sizes.

Harnessing photocatalytic activity of mesoporous graphitic carbon nitride decorated by copper single-atom catalysts for oxidative dehydrogenation of N-heterocycles.

This work describes the application of Cu single-atom catalysts (SACs) for photocatalytic oxidative dehydrogenation of N-heterocyclic amines to the respective N-heteroaromatics through environmentally benign and sustainable pathways. The mesoporous graphitic carbon nitride (mpg-C3N4), prepared by the one-step pyrolysis method, possesses a lightweight material with a high surface area (95 m2 g-1) and an average pore diameter (3.6 nm). A simple microwave-assisted preparation method was employed to decorate Cu single-atom over mpg-C3N4 support. The Cu single-atom decorated on mpg-C3N4 support (Cu@mpg-C3N4) is characterized by various characterization techniques, including XRD, UV-visible spectrophotometry, HRTEM, HAADF-STEM with elemental mapping, AC-STEM, ICP-OES, XANES, EXAFS, and BET surface area. These characterization studies confirmed that the Cu@mpg-C3N4 catalyst exhibited high surface area, mesoporous nature, medium band gap, and low metal loading. The as-synthesized and well-characterized Cu@mpg-C3N4 single-atom photocatalyst is then evaluated for its efficacy in converting N-heterocycles into corresponding N-heteroaromatic compounds with excellent conversion and selectivity (>99 %). This transformation is achieved using water as a green solvent and a 30 W white light as a visible light source, demonstrating the catalyst's potential for sustainable and environmentally benign reactions.

Validation of IGA*BSA in Assessing Disease Severity and Response in Patients with Atopic Dermatitis: A Retrospective Cohort Study in China.

Background: Accurate evaluation of atopic dermatitis (AD) severity is crucial to determine and adjust treatment options. Previous studies have found the product of Investigator's Global Assessment (IGA) and affected body surface area (BSA) to be a simple tool, which requires further verification. Objective: To determine the validity of IGA*BSA in assessing the severity of AD across all age, sex, BMI and disease severity groups. Method: We performed a retrospective study of AD using data from a national cohort (China Type II Inflammatory Skin Disease Clinical Research and Standardized Diagnosis and Treatment Project). Results: Overall, 3051 participants were included in the final analysis. IGA*BSA correlated better with objective measures than with subjective measures. IGA*BSA significantly correlated with Eczema Area and Severity Index (EASI) (r = 0.81), which was stronger than either IGA or BSA alone with EASI, regardless of age, sex, Body Mass Index (BMI), and disease severity groups. Besides, IGA*BSA mild, moderate, and severe groups were associated with significantly higher scores of other assessments and had moderate to fair concordance with other assessments severity strata. At follow-up, the concordance of improvement between IGA*BSA 50/75/90 and EASI 50/75/90 was observed (ĸ = 0.65, 0.62, 0.58, respectively). Conclusion: IGA*BSA appears to be a valid objective assessment of AD severity and improvement over time across all age, sex, BMI, and disease severity subgroups in the clinical practice.

AI-assisted deep learning segmentation and quantitative analysis of X-ray microtomography data from biomass ashes.

X-ray microtomography is a non-destructive method that allows for detailed three-dimensional visualisation of the internal microstructure of materials. In the context of using phosphorus-rich residual streams in combustion for further ash recycling, physical properties of ash particles can play a crucial role in ensuring effective nutrient return and sustainable practices. In previous work, parameters such as surface area, porosity, and pore size distribution, were determined for ash particles. However, the image analysis involved binary segmentation followed by time-consuming manual corrections. The current work presents a method to implement deep learning segmentation and an approach for quantitative analysis of morphology, porosity, and internal microstructure. Deep learning segmentation was applied to microtomography data. The model, with U-Net architecture, was trained using manual input and algorithm prediction.•The trained and validated deep learning model could accurately segment material (ash) and air (pores and background) for these heterogeneous particles.•Quantitative analysis was performed for the segmented data on porosity, open pore volume, pore size distribution, sphericity, particle wall thickness and specific surface area.•Material features with similar intensities but different patterns, intensity variations in the background and artefacts could not be separated by manual segmentation - this challenge was resolved using the deep learning approach.

Investigation of the Compressive Strength and Void Analysis of Cement Pastes with Superabsorbent Polymer.

This study aimed to experimentally investigate the compressive strength and air voids of cement pastes with varying dosages of Superabsorbent Polymer (SAP) and water-to-cement (w/c) ratios. Cement pastes were prepared using three different w/c ratios of 0.4, 0.5, and 0.6, along with different dosages of SAP ranging from 0.2% to 0.5% by weight of cement. Additionally, SAP was introduced in two forms: dry and wet. After casting the cubes, two distinct curing conditions were employed: curing at a temperature of 20 °C with a Relative Humidity (RH) of 60% (Curing 1), and water curing (Curing 2). The results revealed that the addition of SAP increased early strength when subjected to Curing 1, followed by a decrease in later strength. On the other hand, samples with SAP and water curing exhibited higher strength compared to those without SAP, especially with w/c ratios of 0.4 and 0.5. However, at a w/c ratio of 0.6, nearly all samples showed a reduction in strength compared to those without SAP. Furthermore, air void analysis was performed on all samples cured for 28 days using an image analysis technique. The samples containing wet SAP resulted in a higher total air content compared to the samples with dry SAP. Additionally, the incorporation of wet SAP in cement paste led to lower specific surface areas and a higher spacing factor than the samples with dry SAP. These findings suggest that the clumping of wet SAP particles during presoaking resulted in coarser air voids compared to the samples containing dry SAP.

Predicting and refining acid modifications of biochar based on machine learning and bibliometric analysis: Specific surface area, average pore size, and total pore volume.

Acid-modified biochar is a modified biochar material with convenient preparation, high specific surface area, and rich pore structure. It has great potential for application in the heavy metal remediation, soil amendments, and carrying catalysts. Specific surface area (SSA), average pore size (APS), and total pore volume (TPV) are the key properties that determine its adsorption capacity, reactivity, and water holding capacity, and an intensive study of these properties is essential to optimize the performance of biochar. But the complex interactions among the preparation conditions obstruct finding the optimal modification strategy. This study collected dataset through bibliometric analysis and used four typical machine learning models to predict the SSA, APS, and TPV of acid-modified biochar. The results showed that the extreme gradient boosting (XGB) was optimal for the test results (SSA R2 = 0.92, APS R2 = 0.87, TPV R2 = 0.96). The model interpretation revealed that the modification conditions were the major factors affecting SSA and TPV, and the pyrolysis conditions were the major factors affecting APS. Based on the XGB model, the modification conditions of biochar were optimized, which revealed the ideal preparation conditions for producing the optimal biochar (SSA = 727.02 m2/g, APS = 5.34 nm, TPV = 0.68 cm3/g). Moreover, the biochar produced under specific conditions verified the generalization ability of the XGB model (R2 = 0.99, RMSE = 12.355). This study provides guidance for optimizing the preparation strategy of acid-modified biochar and promotes its potentiality for industrial application.

A Novel Approach for Preparing Sepiolite Micron Powder Based on Steam Pressure Changes.

As a common method for preparing micron powder in industrial operations, the mechanical extrusion method simply pursues the particle size without considering the microstructure characteristics of sepiolite, which leads to problems such as bundles of sepiolite not being effectively dispersed, and thus the disruption of fibers is inevitably caused. In this work, a new micronization method for disaggregating these bundles while preserving the original structural integrity of the fibers is proposed based on steam pressure changes. The effects of steam pressure changes on the particle size distribution, microstructure, and properties of treated sepiolite are studied using X-ray fluorescence spectrometer (XRF), X-ray diffractometer (XRD), Field Emission Scanning Electron Microscopy (FESEM), Transmission Electron Microscopy (TEM), and a specific surface area and aperture analyzer (BET). The experimental results show that the particle size of sepiolite powder depends greatly on steam pressure, and sepiolite powder with mass ratio of 91.6% and a particle size D97 of 21.27 µm is obtained at a steam pressure of 0.6 MPa. Compared to the sepiolite after mechanical extrusion, the sepiolite treated with steam pressure changes can maintain the integrity of its crystalline structure. The specific surface area of sepiolite enhanced from 80.15 m2 g-1 to 141.63 m2 g-1 as the steam pressure increased from 0.1 to 0.6 MPa, which is about 1.6 times that of the sample treated with mechanical extrusion.

Alveolar Microdynamics during Tidal Ventilation in Live Animals Imaged by SPring-8 Synchrotron.

It is self-evident that our chests expand and contract during breathing but, surprisingly, exactly how individual alveoli change shape over the respiratory cycle is still a matter of debate. Some argue that all the alveoli expand and contract rhythmically. Others claim that the lung volume change is due to groups of alveoli collapsing and reopening during ventilation. Although this question might seem to be an insignificant detail for healthy individuals, it might be a matter of life and death for patients with compromised lungs. Past analyses were based on static post-mortem preparations primarily due to technological limitations, and therefore, by definition, incapable of providing dynamic information. In contrast, this study provides the first comprehensive dynamic data on how the shape of the alveoli changes, and, further, provides valuable insights into the optimal lung volume for efficient gas exchange. It is concluded that alveolar micro-dynamics is nonlinear; and at medium lung volume, alveoli expand more than the ducts.

Enhancing the properties of swelling soils with lime, fly ash, and expanded polystyrene -A review.

This paper discusses efforts made by past researchers to steady the expansive (problematic) soils using mechanical and chemical techniques - specifically with EPS beads, lime and fly ash. Administering swelling of problematic soils is critical for civil engineers to prevent structural distress. This paper summarizes studies on reduction of swelling potential using EPS, lime and fly ash individually. Chemical stabilization with lime and fly ash are conventional methods for expansive soil stabilization, with known merits and demerits. This paper explores the suitability of different materials under various conditions and stabilization mechanisms, including cation exchange, flocculation, and pozzolanic reactions. The degree of stabilization is influenced by various factors such as the type and amount of additives, soil mineralogy, curing temperature, moisture content during molding, and the presence of nano-silica, organic matter, and sulfates. Additionally, expanded polystyrene (EPS) improves structural integrity by compressing when surrounded clay swells, reducing overall swelling. Thus, EPS addresses limitations of chemicals by mechanical means. Combining EPS, lime and fly ash creates a customized system promoting efficient, long-lasting, cost-effective and eco-friendly soil stabilization. Chemicals address EPS limitations like poor stabilization. This paper benefits civil engineers seeking to control expansive soil swelling and prevent structural distress. It indicates potential of an EPS-lime-fly ash system and concludes by identifying research gaps for further work on such combinatorial stabilizer systems.

Macrostructural Brain Morphology as Moderator of the Relationship Between Pandemic-Related Stress and Internalizing Symptomology During COVID-19 in High-Risk Adolescents.

BACKGROUND: According to person-by-environment models, individual differences in traits may moderate the association between stressors and the development of psychopathology; however, findings in the literature have been inconsistent and little literature has examined adolescent brain structure as a moderator of the effects of stress on adolescent internalizing symptoms. The COVID-19 pandemic presented a unique opportunity to examine the associations between stress, brain structure, and psychopathology. Given links of cortical morphology with adolescent depression and anxiety, the present study investigated whether cortical morphology moderates the relationship between stress from the COVID-19 pandemic on the development of internalizing symptoms in familial high-risk adolescents. METHODS: Prior to the COVID-19 pandemic, 72 adolescents (27M) completed a measure of depressive and anxiety symptoms and underwent magnetic resonance imaging. T1-weighted images were acquired to assess cortical thickness and surface area. Approximately 6-8 months after COVID-19 was declared a global pandemic, adolescents reported their depressive and anxiety symptoms and pandemic-related stress. RESULTS: Adjusting for pre-pandemic depressive and anxiety symptoms and stress, increased pandemic-related stress was associated with increased depressive but not anxiety symptoms. This relationship was moderated by cortical thickness and surface area in the anterior cingulate and cortical thickness in the medial orbitofrontal cortex such that increased stress was only associated with increased depressive and anxiety symptoms among adolescents with lower cortical surface area and higher cortical thickness in these regions. CONCLUSIONS: Results further our understanding of neural vulnerabilities to the associations between stress and internalizing symptoms in general, and during the COVID-19 pandemic in particular.

Cellular uptake of allicin in the hCMEC/D3 human brain endothelial cells: exploring blood-brain barrier penetration in an in vitro model.

Background: Allicin, a bioactive compound derived from garlic (Allium sativum), demonstrates antibacterial activity against a broad spectrum of bacteria including the most common meningitis pathogens. In order to advocate for allicin as a potential therapeutic candidate for bacterial meningitis, the present study aimed to assess the ability of allicin to cross the blood-brain barrier (BBB) using an in vitro model. Methods: The cell viability of the human brain endothelial cell line hCMEC/D3 after incubation with various concentrations of allicin was investigated using an MTT assay at 3 and 24 h. Additionally, reactive oxygen species (ROS) production of allicin-treated hCMEC/D3 cells was examined at 3 h. The concentrations of allicin that were not toxic to the cells, as determined by the MTT assay, and did not significantly increase ROS generation, were then used to investigate allicin's ability to traverse the in vitro BBB model for 3 h. High-performance liquid chromatography (HPLC) analysis was utilized to examine the allicin concentration capable of passing the in vitro BBB model. The cellular uptake experiments were subsequently performed to observe the uptake of allicin into hCMEC/D3 cells. The pkCSM online tool was used to predict the absorption, distribution, metabolism, excretion, and pharmacokinetic properties of allicin and S-allylmercaptoglutathione (GSSA). Results: The results from MTT assay indicated that the highest non-toxicity concentration of allicin on hCMEC/D3 cells was 5 µg/ml at 3 h and 2 µg/ml at 24 h. Allicin significantly enhanced ROS production of hCMEC/D3 cells at 10 µg/ml at 3 h. After applying the non-toxicity concentrations of allicin (0.5-5 µg/ml) to the in vitro BBB model for 3 h, allicin was not detectable in both apical and basolateral chambers in the presence of hCMEC/D3 cells. On the contrary, allicin was detected in both chambers in the absence of the cells. The results from cellular uptake experiments at 3 h revealed that hCMEC/D3 cells at 1 × 104 cells could uptake allicin at concentrations of 0.5, 1, and 2 µg/ml. Moreover, allicin uptake of hCMEC/D3 cells was proportional to the cell number, and the cells at 5 × 104 could completely uptake allicin at a concentration of 5 µg/ml within 0.5 h. The topological polar surface area (TPSA) predicting for allicin was determined to be 62.082 Å2, indicating its potential ability to cross the BBB. Additionally, the calculated logBB value surpassing 0.3 suggests that the compound may exhibit ease of penetration through the BBB. Conclusion: The present results suggested that allicin was rapidly taken up by hCMEC/D3 cells in vitro BBB model. The prediction results of allicin's distribution patterns suggested that the compound possesses the capability to enter the brain.