Hepatoprotective effect of Cassia obtusifolia seed extract and constituents against oxidative damage induced by tert‐butyl hydroperoxide in human hepatic HepG2 cells

The aim of the present study was to investigate the hepatoprotective effects of different soluble fractions of methanolic derived Cassia obtusifolia seeds extract (COE) and its active components in tert‐butyl hydroperoxide (t‐BHP)‐induced oxidative stress in HepG2 cells. Among the tested fractions, the ethyl acetate (EtOAc) fraction was the most active hepatoprotective fraction. From the active EtOAc fraction, six anthraquinones (alaternin, emodin, aloe emodin, 2‐hydroxyemodin 1‐methyl ether, chryso‐obtusin‐2‐O‐β‐d ‐glucoside, and questin) and one naphthopyrone glycoside (cassiaside) were isolated. The cytotoxic effect in 200 µM t‐BHP‐induced HepG2 cells was inhibited by COE and their bioactive compounds. The protective effect of COE in 200 µM t‐BHP‐induced HepG2 cells may be associated with positive regulation of glutathione (GSH) and decreased in reactive oxygen species (ROS) formation of their bioactive compounds. The increased ROS and decreased GSH levels observed in t‐BHP‐treated HepG2 cells were ameliorated by pretreatment with cassiaside, alaternin, and aloe emodin, indicating that the hepatoprotective effects of these major constituents are mediated by induction of cellular defense against oxidative stress. Overall, COE displayed a significant cytoprotective effect against oxidative stress, which may most likely be because of active compounds like cassiaside, alaternin, and aloe emodin in COE, which leads to maintenance of the normal redox status of cells.

Practical applications

The dried and roasted seeds of Cassia obtusifolia are commonly consumed as brew tea and medicinal foods in Korea. The seeds have multiple therapeutic actions related to the treatment of liver disease, dementia, diabetes, eye inflammation, photophobia and lacrimation, dysentery, headache, as well as dizziness. The present study demonstrates the hepatoprotective effect through prevention of oxidative stress, suggesting that C. obtusifolia and its constituents may have beneficial effects in preventing hepatic diseases.     

Incidence of aflatoxin M1 in human breast milk in Tehran, Iran

This study examined the exposure of infants to aflatoxin M1 (AFM1) and of lactating mothers to aflatoxin B1 (AFB1), using AFM1 in breast milk as a biomarker for exposure to AFB1. An enzyme-linked immunosorbent assay (ELISA) was modified for the analysis of AFM1 in breast milk samples from 160 women in Tehran, Iran. AFM1 was detected in 157 samples by average concentration of 8.2 ± 5.1 ng/kg (range 0.3–26.7 ng/kg).The concentration of AFM1 in one sample was higher than the maximum tolerance limit accepted by European Union and USA (25 ng/kg), but in 55 samples was higher than the maximum concentration recommended by Australia and Switzerland (10 ng/kg).Logistic regression Analysis failed to show significant correlation between AFM1 and gestational age, education, postnatal age, gender, nationality, clinical condition, the number of family member, the number of children, type and amount of dairy consumption, vegetable, fruits, oil and meat. But it was significant relation to the cereal consumption, also to the height at birth.     

Variation in the Optical Properties of the SiC-SiO<Subscript>2</Subscript> Composite Antireflection Layer in Crystalline Silicon Solar Cells by Annealing

This study showed the effects of annealing on a sol–gel-derived SiC-SiO₂ composite antireflection (AR) layer and investigated the optical and photovoltaic properties of crystalline silicon (Si) solar cells. The SiC-SiO₂ composite AR coating showed a considerable decrease in reflectance from 7.18% to 3.23% at varying annealing temperatures of 450–800°C. The refractive indices of the SiC-SiO₂ composite AR layer were tuned from 2.06 to 2.45 with the increase in annealing temperature. The analysis of the current density–voltage characteristics indicated that the energy conversion efficiencies of the fabricated Si solar cells gradually increased from 16.99% to 17.73% with increasing annealing temperatures of 450–800°C. The annealing of the SiC-SiO₂ composite AR layer in Si solar cells was crucial to improving the optical, morphological, and photovoltaic properties.     

Brain Tumor Auto-Segmentation on Multimodal Imaging Modalities Using Deep Neural Network

Due to the difficulties of brain tumor segmentation, this paper proposes a strategy for extracting brain tumors from three-dimensional Magnetic Resonance Image (MRI) and Computed Tomography (CT) scans utilizing 3D U-Net Design and ResNet50, taken after by conventional classification strategies. In this inquire, the ResNet50 picked up accuracy with 98.96%, and the 3D U-Net scored 97.99% among the different methods of deep learning. It is to be mentioned that traditional Convolutional Neural Network (CNN) gives 97.90% accuracy on top of the 3D MRI. In expansion, the image fusion approach combines the multimodal images and makes a fused image to extricate more highlights from the medical images. Other than that, we have identified the loss function by utilizing several dice measurements approach and received Dice Result on top of a specific test case. The average mean score of dice coefficient and soft dice loss for three test cases was 0.0980. At the same time, for two test cases, the sensitivity and specification were recorded to be 0.0211 and 0.5867 using patch level predictions. On the other hand, a software integration pipeline was integrated to deploy the concentrated model into the webserver for accessing it from the software system using the Representational state transfer (REST) API. Eventually, the suggested models were validated through the Area Under the Curve–Receiver Characteristic Operator (AUC–ROC) curve and Confusion Matrix and compared with the existing research articles to understand the underlying problem. Through Comparative Analysis, we have extracted meaningful insights regarding brain tumour segmentation and figured out potential gaps. Nevertheless, the proposed model can be adjustable in daily life and the healthcare domain to identify the infected regions and cancer of the brain through various imaging modalities.     

An experimental design-based evaluation of sensitivities of MEPDG prediction: investigating main and interaction effects

The mechanistic–empirical pavement design guide (MEPDG) uses mechanistic–empirical models by analysing the impacts of traffic, climate, materials and pavement structure to predict performances of pavement. The MEPDG software uses a three-level hierarchical input to predict performance in terms of terminal International Roughness Index, permanent deformation, total cracking (reflective and alligator), asphalt concrete (AC) thermal fracture, AC bottom-up fatigue cracking and AC top-down fatigue cracking. However, these inputs with different levels of accuracy may have significant impact on performance prediction. This study focuses on the sensitivity of the inputs of MEPDG distresses to identify the effect of the accuracy level of inputs based on experimental design. A local sensitivity analysis is carried out to identify the main effect of inputs considering them as independent variables. Interaction effects are also analysed based on random combination of the inputs. Sensitive input variables and their combinations are evaluated through a multiple regression analysis for respective distresses.     

A novel aqueous micellar two-phase system composed of surfactant and mannitol for purification of polygalacturonase enzyme from Durio zibethinus Murray and recycling phase components

A novel aqueous micellar two-phase system composed of surfactant and mannitol was employed for the first time to purify polygalacturonase from Durio zibethinus Murray. The influences of different parameters such as type of surfactants, composition of surfactant/mannitol, pH and crude load on polygalacturonase partitioning were investigated. The results indicated that the polygalacturonase was recovered in 25% Tween 80 and 22% mannitol, at 68.2% of Tie line length, crude load of 30% at pH 5.0. The enzyme was successfully recovered with a high purification factor of 16.1 and yield of 97.3% while phase components were also recovered and recycled above 95%.     

TiO2/Si nanowires hybrid system for efficient photocatalytic degradation of organic dye

Herein, titanium dioxide (TiO₂)-coated vertically aligned silicon nanowires (SiNWs/TiO₂) were fabricated and evaluated for photocatalytic degradation of organic dyes. Aligned SiNWs arrays were prepared by facile metal-assisted chemical-etching process with varying the etching time that was followed by TiO₂ nanoparticles coating using sputtering technique. The TiO₂ film crystallized in pure anatase phase with an average crystalline size of 50 nm, as was elucidated with X-ray diffraction studies. SEM analysis showed nanowires with varying lengths from 2.5 to 13.5 µm and confirmed the homogenous surface decoration with TiO₂. The homogeneous distribution of TiO₂ nanoparticles on nanowires was co-evidenced with Energy-Dispersive X-ray spectroscopy (EDX) and Raman spectra analysis. The developed SiNWs/TiO₂ was exploited for photocatalytic degradation of methylene blue; the role of hydrogen peroxide was also elucidated. The highest photocatalytic efficiency of 96% was achieved for SiNWs/TiO₂ with optimum nanowire length of 3.5 μm. The developed photocatalyst was found to be almost stable even after 190 days (~?5 months) and could be used as reusable and easily removable photocatalysts. The current study highlighted the SiNWs/TiO₂/H₂O₂ system as excellent candidate for water remediation applications.

     

Enhanced Photocatalytic Performance of Zinc Ferrite Nanocomposites for Degrading Methylene Blue: Effect of Nickel Doping Concentration

Journal of Inorganic and Organometallic Polymers and Materials - In the present work, undoped and nickel doped zinc ferrite (ZnFe2?xNixO4) nano-composites were synthesized using a facile...     

An Ultrasensitive Silicon Photonic Ion Sensor Enabled by 2D Plasmonic Molybdenum Oxide

Silicon photonics has demonstrated great potential in ultrasensitive biochemical sensing. However, it is challenging for such sensors to detect small ions which are also of great importance in many biochemical processes. A silicon photonic ion sensor enabled by an ionic dopant–driven plasmonic material is introduced here. The sensor consists of a microring resonator (MRR) coupled with a 2D restacked layer of near‐infrared plasmonic molybdenum oxide. When the 2D plasmonic layer interacts with ions from the environment, a strong change in the refractive index results in a shift in the MRR resonance wavelength and simultaneously the alteration of plasmonic absorption leads to the modulation of MRR transmission power, hence generating dual sensing outputs which is unique to other optical ion sensors. Proof‐of‐concept via a pH sensing model is demonstrated, showing up to 7 orders improvement in sensitivity per unit area across the range from 1 to 13 compared to those of other optical pH sensors. This platform offers the unique potential for ultrasensitive and robust measurement of changes in ionic environment, generating new modalities for on‐chip chemical sensors in the micro/nanoscale.     

Application of marble powder as a potential green adsorbent for miniaturized solid phase extraction of polycyclic aromatic hydrocarbons from water samples

ABSTRACT

In this study, marble powder was evaluated as a cheap, easy to prepare and efficient green sorbent for miniaturized solid phase extraction of polycyclic aromatic hydrocarbons (PAHs) and determination by high performance liquid chromatography with UV detection. Under the optimized experimental conditions, wide linear dynamic ranges were achieved in the range of 0.1–200 μg L^?1, with correlation coefficient higher than 0.996. The limits of detection and quantification for target analytes could reach 16.3–120.2 and 54.3–398 ng L^?1, respectively. The method precision based on obtained RSD values in the range of 4.9–7.9% (n = 8) was very satisfactory.