Innovative Diagnostic Peptide-Based Technologies for Cancer Diagnosis: Focus on EGFR-Targeting Peptides

Active targeting using biological ligands has emerged as a novel strategy for the targeted delivery of diagnostic agents to tumor cells. Conjugating functional targeting moieties with diagnostic probes can increase their accumulation in tumor cells and tissues, enhancing signal detection and, thus, the sensitivity of diagnosis. Due to their small size, ease of chemical synthesis and site-specific modification, high tissue penetration, low immunogenicity, rapid blood clearance, low cost, and biosafety, peptides offer several advantages over antibodies and proteins in diagnostic applications. Epidermal growth factor receptor (EGFR) is one of the most promising cancer biomarkers for actively targeting diagnostic and therapeutic agents to tumor cells due to its active involvement and overexpression in various cancers. Several peptides for EGFR-targeting have been identified in the last decades, which have been obtained by multiple means including derivation from natural proteins, phage display screening, positional scanning synthetic combinatorial library, and in silico screening. Many studies have used these peptides as a targeting moiety for diagnosing different cancers in vitro, in vivo, and in clinical trials. This review summarizes the progress of EGFR-targeting peptide-based assays in the molecular diagnosis of cancer.     

Simultaneous modification of hydrotalcite–silicate nanolayers as reinforcement of a new polyamide: thermal properties and flammability study

New polyamide/clay–layered double hydroxide nanocomposites (PACLN) were prepared from a synthesized aliphatic–aromatic polyamide (AAPA) and organically modified layered double hydroxide–clay (MLC) nanohybrid. MLC was obtained by simultaneous modification of montmorillonite and hydrotalcite nanolayers with cationic–anionic polyethyleneimine/poly(acrylic acid)-co-poly(2-acrylamido-2-methylpropanesulfonic acid) in an ion-exchange reaction. The analysis results indicated that the modification successfully occurred in MLC with increasing interlayer spacing. PACLN were prepared from AAPA and MLC using the solvent-casting technique. The thermal and combustion properties, morphology and structure of the resulting nanocomposites were studied using thermogravimetric analysis (TGA), microscale combustion calorimetry (MCC), scanning and transmission electron microscopies, Fourier transform infrared spectroscopy and X-ray diffraction. The results indicated that the silicate and hydrotalcite nanosheets were dispersed in the AAPA matrix. In other words, the silicate and hydrotalcite nanosheets were placed in the AAPA matrix as a new two-dimensional rearranged structure by self-assembly. The TGA results of nanocomposites in N₂ environment showed that PACLN is more heat resistant than AAPA. The 5% mass degradation temperature of PACLN containing 5 mass% of MLC was obtained as almost 60 °C more than that of AAPA. According to MCC results, the peaks of heat release rate were reduced from 156 to 91 W g⁻¹ for AAPA containing 5 mass% of MLC. © 2022 Society of Industrial Chemistry.     

Distributed model predictive control of switched nonlinear systems with scheduled mode transitions

A method for the design of distributed model predictive control (DMPC) systems for a class of switched nonlinear systems for which the mode transitions take place according to a prescribed switching schedule is presented. Under appropriate stabilizability assumptions on the existence of a set of feedback controllers that can stabilize the closed‐loop switched, nonlinear system, a cooperative DMPC architecture using Lyapunov‐based model predictive control (MPC) in which the distributed controllers carry out their calculations in parallel and communicate in an iterative fashion to compute their control actions is designed. The proposed DMPC design is applied to a nonlinear chemical process network with scheduled mode transitions and its performance and computational efficiency properties in comparison to a centralized MPC architecture are evaluated through simulations. © 2013 American Institute of Chemical Engineers AIChE J, 59:860‐871, 2013     

Genetic Polymorphisms in the APOA1 Gene and their Relationship with Serum HDL Cholesterol Levels

Low high density lipoprotein cholesterol (HDL-C) is a known risk factor of coronary artery disease. Apolipoprotein A1 (APOA1) is the most abundant component of HDL-C. This study aimed at identifying sequence variations (rare and common) in the APOA1 gene and its association with serum HDL-C levels. This study was conducted from April 2012 to February 2013 on 79 Tehranians (participants of Tehran Lipid and Glucose Study) with extremely low HDL-C (within the 5th percentile) and 63 individuals with extremely high HDL-C (within the 95th percentile) levels. After DNA amplification by PCR, DNA sequencing of all three exons and 700 bps of promoter region of the APOA1 gene was performed. Sequence results were analyzed and interpreted using the appropriate software and variants were identified. After sequencing 42 common and rare variants were identified, 11 of which were known variants and the others had been unreported so far. Of the exonic variants, 11 were missense, 6 were synonymous and 1 was nonsense. There was a significant association between serum HDL-C and variant of rs2070665 as well as variants Chr.11:116707788, Chr.11:116708059, Chr.11:116708036, Chr.11:116707729, rs201148448, Chr.11:116707018, Chr.11:116707801, Chr.11:116708530, Chr.11:116708088, rs121912724 and Chr.11:116706966 (p < 0.001). Variants Chr.11:116707018, rs121912724 and 2070665 were independent predictors of the HDL-C level (p < 0.001). SNP Chr.11:116707018 was the strongest predictor of the HDL-C level (OR 7.527, p < 0.001). This study identified 42 variants in APOA1 gene, 31 of which were new variants. Three variants of rs2070665, rs121912724 and Chr.11:116707018 could predict the HDL-C level independently. Variant rs2070665 was protective against low-HDL-C levels while variants rs121912724 and Chr.11:116707018 were risk factors for that in our population.     

Study of Some Variables Affecting Particle Size and Particle Size Distribution of Suspension Polymerization of Methyl Methacrylate

A laboratory reactor was designed and constructed to study the effect of both speed of agitation and a concentration of suspension stabilizer on particle size and particle size distribution during the suspension polymerization of methyl methacrylate. It was concluded that the average particle size of the prepared polymer powder is directly proportional to the speed of agitation and is inversely proportional to the stabilizer concentration. New empirical equations correlating the average particle size and the particle size distribution (PSD) were derived from the study.     

MODELING OF MEMBRANE FOULING AND FLUX DECLINE IN MICROFILTRATION OF OILY WASTEWATER USING CERAMIC MEMBRANES

One of the major problems in pressure-driven membrane processes is reduction of flux far below the theoretical capacity of the membrane. The results of an experimental study of fouling mechanisms of ceramic membranes in separation of oil from synthesized oily wastewaters are presented. Mullite microfiltration (MF) membranes were synthesized from kaolin clay as MF ceramic membranes. The rejection of total organic carbon (TOC) for the synthetic feeds was found to be more than 94% by these membranes. Hermia's models were used to investigate the fouling mechanisms of membranes. The effect of pressure, cross flow velocity (CFV), temperature, oil concentration, and salt concentration on flux decline were investigated. The results showed that the cake filtration model can well predict the flux decline of mullite ceramic membranes; average error of this model is less than 7%. The results show that by increasing pressure from 0.5 to 4 bar, porosity of the cake layer on the mullite membranes decreases from 25.68% to 14.98%. After the cake filtration model, the intermediate pore blocking model was found to well predict the experimental data with an average error less than 10.5%.     

Mangrove Oyster (Crassostrea belcheri) as a Biomonitor Species for Bioavailability of Polycyclic Aromatic Hydrocarbons (PAHs) from Sediment of the West Coast of Peninsular Malaysia

ABSTRACT

Rapid industrialization and urbanization in the west coast of Peninsular Malaysia has caused increasing pollution particularly of petroleum and petroleum by-products. Surface sediment and mangrove oyster (Crassostrea belcheri) were collected from five mangrove ecosystems in the west coast of Peninsular Malaysia and investigated for bioavailability of polycyclic aromatic hydrocarbons (PAHs). Sampling locations were selected from both remote areas with few or no previous records of petroleum pollution such as Pulau Merambong and polluted areas that are under international attention such as Klang mangrove ecosystem. PAH fractions were obtained through soxhlet extraction and two-step column chromatography and the fractions were injected to gas chromatography-mass spectrometry (GC-MS) for analysis. The concentrations of PAHs ranged from 151 to 4973 ng g^?1 dw in the sediments, while from 309 to 2225 ng g^?1 dw in the oysters. When tested for diagnostic ratios, a predominance of pyrogenic source PAHs was detected in the sediments, whereas PAHs in the oysters had mixed petrogenic and pyrogenic sources. A significant correlation (p < 0.05) was found between high molecular weight (HMW) PAHs in the sediments and oysters and biota accumulation factors (BAFs) of PAHs were approaching or exceeding unity indicating the ability of mangrove oyster in bioaccumulation of PAHs. Overall, this study indicates that mangrove oyster (C. belcheri) can be used as a biomonitor species for PAHs in an aquatic environment.     

Experimental investigation of particle contact time at the wall of gas fluidized beds

The contact time of particles at the walls of gas fluidized beds has been studied using a radioactive particle tracking technique to monitor the position of a radioactive tracer. The solids used were sand or FCC particles fluidized by air at room temperature and atmospheric pressure at various superficial velocities, covering both bubbling and turbulent regimes of fluidization. Based on the analysis of tracer positions, the motion of individual particles near the walls of the fluidized bed was studied. The contact time, contact distance and contact frequency of the particles at the wall were evaluated from these experimental data. It was found that in a bed of sand particles, the mean wall contact time of the fluidized bed of sand particles decreases by increasing the gas velocity in the bubbling and increases in the turbulent fluidization. In other words, the particle-wall contact time is minimum at the onset of turbulent fluidization in the bed of sand particles. However, the mean wall contact time is almost constant in both regimes of fluidization in the bed of FCC particles. All the existing models in the literature predict a decreasing contact time when the gas velocity in the bed is increased. It was also shown that the contact distance increases monotonously by increasing the gas velocity in the bed of sand particles, while it is almost constant for the bed of FCC particles. Contact frequency has a trend similar to that of the contact time for both sand and FCC particles.     

Cell Membrane-Cloaked Nanotherapeutics for Targeted Drug Delivery

Cell membrane cloaking technique is bioinspired nanotechnology that takes advantage of naturally derived design cues for surface modification of nanoparticles. Unlike modification with synthetic materials, cell membranes can replicate complex physicochemical properties and biomimetic functions of the parent cell source. This technique indeed has the potential to greatly augment existing nanotherapeutic platforms. Here, we provide a comprehensive overview of engineered cell membrane-based nanotherapeutics for targeted drug delivery and biomedical applications and discuss the challenges and opportunities of cell membrane cloaking techniques for clinical translation.