Bioinformatics Evaluation of Plant Chlorophyllase, the Key Enzyme in Chlorophyll Degradation

Background and Objective: Chlorophyllase catalyzes the hydrolysis of chlorophylls to chlorophyllide and phytol. Recently, several applications including removal of chlorophylls from vegetable oils, use in laundry detergents and production of chlorophyllides have been described for chlorophyllase. However, there is little information about the biochemical characteristics of chlorophyllases.Material and Methods: 35 chlorophyllase protein sequences were obtained from the National Centre for Biotechnology Information database. All of the sequences were analyzed using bioinformatics tools for their conserved domain, phylogenetic relationships and biochemical characteristics.Results and Conclusion: The overall domain architecture of chlorophyllases consisted of the esterases/lipases superfamily domain over their full length and the alpha/beta hydrolase family domain over the middle part of their sequences. Plant chlorophyllases could be classified into 4 clades. Molecular weight and pI of the chlorophyllases ranged 32.65-37.77 kDa and 4.80-8.97, respectively. The most stable chlorophyllase is probably obtained from Malus domestica. Chlorophyllases form Solanum pennellii, Triticum aestivum, Triticum urartu, Arabidopsis lyrata, Pachira macrocarpa, Prunus mume and Malus domestica were predicted to be soluble upon overexpression in Escherichia coli, Beta vulgaris and Chenopodium album chlorophyllases were predicted to form no disulfide bond. Chlorophyllases from Jatropha curcas, Amborella trichopod, Setaria italica, Piper betle, Triticum urartu and Arabidopsis thaliana were predicted to be in non-N-glycosylated form.Conflict of interest: The authors declare no conflict of interest

The Effect of Soft and Rigid Cervical Collars on Head and Neck Immobilization in Healthy Subjects

Study DesignWhiplash injury is a prevalent and often destructive injury of the cervical column, which can lead to serious neck pain. Many approaches have been suggested for the treatment of whiplash injury, including anti-inflammatory drugs, manipulation, supervised exercise, and cervical collars. Cervical collars are generally divided into two groups: soft and rigid collars.PurposeThe present study aimed to compare the effect of soft and rigid cervical collars on immobilizing head and neck motion.Overview of LiteratureMany studies have investigated the effect of collars on neck motion. Rigid collars have been shown to provide more immobilization in the sagittal and transverse planes compared with soft collars. However, according to some studies, soft and rigid collars provide the same range of motion in the frontal plane.MethodsTwenty-nine healthy subjects aged 18–26 participated in this study. Data were collected using a three-dimensional motion analysis system and six infrared cameras. Eight markers, weighing 4.4 g and thickened 2 cm2 were used to record kinematic data. According to the normality of the data, a paired t-test was used for statistical analyses. The level of significance was set at α=0.01.ResultsAll motion significantly decreased when subjects used soft collars (p<0.01). According to the obtained data, flexion and lateral rotation experienced the maximum (39%) and minimum (11%) immobilization in all six motions using soft collars. Rigid collars caused maximum immobilization in flexion (59%) and minimum immobilization in the lateral rotation (18%) and limited all motion much more than the soft collar.ConclusionsThis study showed that different cervical collars have different effects on neck motion. Rigid and soft cervical collars used in the present study limited the neck motion in both directions. Rigid collars contributed to significantly more immobilization in all directions

A systematic review of variables used to assess clinically acceptable alignment of unilateral transtibial amputees in the literature.

Prosthetic alignment is a subjective concept which lacks reliability. The outcome responsiveness to prosthetic alignment quality could help to improve subjective and instrument assisted prosthetic alignment. This study was aimed to review variables used to assess clinically acceptable alignment in the literature. The search was done in some databases including: Google Scholar, PubMed, EBSCO, EMBASE, ISI Web of Knowledge and Scopus. The first selection criterion was based on abstracts and titles to address the research questions of interest. The American Academy of Orthotics and Prosthetics checklists were used for paper risk of bias assessment. A total of 25 studies were included in this study. Twenty-four studies revealed the critics of standing position or walking to locate clinically acceptable alignment, only one study measured outcomes in both situations. A total of 253 adults with transtibial amputations and mean age of 48.71 years participated in included studies. The confidence level of included studies was low to moderate, and before-after trial was the most common study design (n = 19). The joint angle, load line location with respect to joints and center of pressure-related parameters were reported as sensitive outcomes to prosthetic alignment quality in standing posture. The amount of forces at various parts of gait cycle and time of events were sensitive to prosthetic alignment quality during walking. Standing balance and posture and temporal parameters of walking could help to locate clinically acceptable alignment.N/

Observation of Plasmonics Talbot effect in graphene nanostructures

Abstract We report on the theoretical models of the plasmoincs Talbot effect in graphene nanostructure. The Talbot effect for the plasmonics applications in the IR range is theoretically studied and the respective Talbot effect for the novel advanced plasmonics structures are numerically investigated for the first time. It is shown that the metamaterial structures with periodic grating configuration represents a complex three-dimensional lattice of beamlet-like graphene plasmonics devices. The calculated results agree well with the experimental ones. The results obtained can be used to create and optimize the structures considering diffraction limit for a wide range of application areas. Effective focusing of plasmonic waves with exact focal spots and a subwavelength full width at half maximum can be obtained by using periodic graphene grating

Numerical Modeling of a Nanostructure Gas Sensor Based on Plasmonic Effect

In the present paper, a nanostructure plasmonic gas sensor based on ringresonator structure at the wavelength range of 0.6-0.9 μm is presented. The plasmonicmaterials/SiO2 with the advantage of high mobility and low loss is utilized as a substratefor structure to obtain some appropriate characteristics for the sensing Performanceparameters. To evaluate the proposed sensor and calculation of performance parametersincluding figure of merit and sensitivity, the effect of the different gas including CarbonDioxide (CO2), Acetonitrile (C2H3N), Carbon disulfide, and Sarin are considered. Forthis purpose 3D-FDTD method is considered. Our calculations show that by couplingbetween the incident waves and the surface plasmons of the structure, a hightransmission ratio of 0.8 and relatively low insertion loss of 6 dB around the wavelengthinterval of 0.6-0.9 μm are achievable. Furthermore, the calculated sensitivity and figureof merit are 28 and 8.75, respectively. This provides a path for development of nanoscalepractical on-chip applications such as plasmonic memory devices

Numerical Modeling of a Metamaterial Biosensor for Cancer Tissues Detection

In this paper, the numerical design and simulate a biosensor to detect tumors and cancerous tissues by using metamaterial structures in the microwave regime are presented. The presented structure consists of a microstrip transmission line and a split ring resonator (SRR) that form a bandpass filter and has a unique resonance frequency. Given that cancerous tissues have larger volumes of water than healthy tissues. As a result, they have a higher dielectric coefficient and conductivity which use for healthy tissues detection. By placing biological samples on SRR, its dielectric constant changes, therefore, the resonance frequency of the system changes. We can measure the types of biological tissues by measuring these changes. We used the Debye model to simulate the muscles. Also, the benefits of this biosensor are easy to use and operation, but they have lower sensitivity than terahertz biosensors. The minimum resolution for samples under test in this biosensor is 10 MHz

Meticulous research for design of plasmonics sensors for cancer detection and food contaminants analysis via machine learning and artificial intelligence

Abstract Cancer is one of the leading causes of death worldwide, making early detection and accurate diagnosis critical for effective treatment and improved patient outcomes. In recent years, machine learning (ML) has emerged as a powerful tool for cancer detection, enabling the development of innovative algorithms that can analyze vast amounts of data and provide accurate predictions. This review paper aims to provide a comprehensive overview of the various ML algorithms and techniques employed for cancer detection, highlighting recent advancements, challenges, and future directions in this field. The main challenge is finding a safe, auditable and reliable analysis method for fundamental scientific publication. Food contaminant analysis is a process of testing food products to identify and quantify the presence of harmful substances or contaminants. These substances can include bacteria, viruses, toxins, pesticides, heavy metals, allergens, and other chemical residues. Machine learning (ML) and artificial intelligence (A.I) proposed as a promising method that possesses excellent potential to extract information with high validity that may be overlooked with conventional analysis techniques and for its capability in a wide range of investigations. A.I technology used in meta-optics can develop optical devices and systems to a higher level in future. Furthermore (M.L.) and (A.I.) play key roles as a health Approach for nano materials NMs safety assessment in environment and human health research. Beside, benefits of ML in design of plasmonic sensors for different applications with improved resolution and detection are convinced