Biolmpacts
Volume:11 Issue: 2, Mar 2021

Although thrombolytic agents have been used for several decades in the treatment of thromboembolic conditions, there is an unmet need for the development of safer thrombolytic agents. The development of new molecules themselves may not be sufficient. This has sparked a growing interest in the design of novel nanoscale drug carrier systems for the delivery of thrombolytic enzymes in an effort to address its fatal side effects. There are numerous proofof-concept reports on such nanoscale systems that seek to capitalize on the pathophysiologic signatures of thrombosis as well as external biochemical/physical triggers. Although there may be a long road ahead before we have such new nanoscale therapeutics on the bedside, hopes remain high.

In recent decades, the growing rate of cancer incidence is a big concern for most societies. Due to the genetic origins of cancer disease, its internal structure is necessary for the study of this disease.

In this research, cancer data are analyzed based on DNA sequences. The transition probability of occurring two pairs of nucleotides in DNA sequences has Markovian property. This property inspires the idea of feature dimension reduction of DNA sequence for overcoming the high computational overhead of genes analysis. This idea is utilized in this research based on the Markovian property of DNA sequences. This mapping decreases feature dimensions and conserves basic properties for discrimination of cancerous and noncancerous genes.

The results showed that a non-linear support vector machine (SVM) classifier with RBF and polynomial kernel functions can discriminate selected cancerous samples from non-cancerous ones. Experimental results based on the 10-fold cross-validation and accuracy metrics verified that the proposed method has low computational overhead and high accuracy.

The proposed algorithm was successfully tested on related research case studies. In general, a combination of proposed Markovian-based feature reduction and non-linear SVM classifier can be considered as one of the best methods for discrimination of cancerous and noncancerous genes.

Riboswitches are short regulatory elements generally found in the untranslated regions of prokaryotes’ mRNAs and classified into several families. Due to the binding possibility between riboswitches and antibiotics, their usage as engineered regulatory elements and also their evolutionary contribution, the need for bioinformatics tools of riboswitch detection is increasing. We have previously introduced an alignment independent algorithm for the identification of frequent sequential blocks in the families of riboswitches. Herein, we report the application of block location-based feature extraction strategy (BLBFE), which uses the locations of detected blocks on riboswitch sequences as features for classification of seed sequences. Besides, monoand dinucleotide frequencies, k-mer, DAC, DCC, DACC, PC-PseDNC-General and SC-PseDNC-General methods as some feature extraction strategies were investigated.

The classifiers of the Decision tree, KNN, LDA, and Naïve Bayes, as well as k-fold crossvalidation, were employed for all methods of feature extraction to compare their performances based on the criteria of accuracy, sensitivity, specificity, and f-score performance measures.

The outcome of the study showed that the BLBFE strategy classified the riboswitches indicating 87.65% average correct classification rate (CCR). Moreover, the performance of the proposed feature extraction method was confirmed with average values of 94.31%, 85.01%, 95.45% and 85.38% for accuracy, sensitivity, specificity, and f-score, respectively.

Our result approved the performance of the BLBFE strategy in the classification and discrimination of the riboswitch groups showing remarkable higher values of CCR, accuracy, sensitivity, specificity and f-score relative to previously studied feature extraction methods.

Cell aggregation of threedimensional (3D) culture systems (the socalled spheroids) are designed as in vitro platform to represent more accurately the in vivo environment for drug discovery by using semi-solid media. The uniform multicellular tumor spheroids can be generated based on the interaction of cells with extracellular matrix (ECM) macromolecules such as collagen and integrin. This study aimed to investigate the possible interactions between the cellulose family and collagen using both in vitro and in silico approaches.

The 3D microtissue of JIMT-1 cells was generated using hanging drop method to study the effects of charge and viscosity of the medium containing cellulose family. To determine the mode of interaction between cellulose derivatives (CDs) and collagen-integrin, docking analysis and molecular simulation were further performed using open source web servers and chemical simulations (GROMACS), respectively.

The results confirmed that the addition of CDs into the 3D medium can promote the formation of solid spheroids, where methylcellulose (MC) yielded uniform spheroids compared to carboxymethyl cellulose (CMC). Moreover, the computational analysis showed that MC interacted with both integrin and collagen, while sodium carboxymethyl cellulose (NaCMC) only interacted with collagen residues. The stated different behaviors in the 3D culture formation and collagen interaction were found in the physicochemical properties of CDs.

Based on in vitro and in silico findings, MC is suggested as an important ECMmimicking entity that can support the semi-solid medium and promote the formation of the uniform spheroid in the 3D culture.

The present study attempts to identify potential targets of H. pylori for novel inhibitors from therapeutic herb, mango ginger (Curcuma amada Roxb.).

Crystal structure of all the selected drug targets obtained from Protein Data Bank (PDB) were subjected to molecular docking against a total of 130 compounds (found to have biological activity against H. pylori) were retrieved from public databases. Compounds with good binding affinity were selected for Prime MM-GBSA rescoring and molecular dynamics (MD) simulation. Final list of compounds were taken for ADMET predictions.

Based on binding affinity denoted by glide score and ligand efficiency, mango ginger compounds were found selective to shikimate kinase and type II dehydroquinase through hydrogen bonding and salt bridge interactions. Stability of the interactions and free energy calculations by Prime MM-GBSA results confirmed the affinity of mango ginger compounds towards both shikimate kinase and type II dehydroquinase. From the above results, 15 compounds were calculated for ADMET parameters, Lipinski’s rule of five, and the results were found promising without any limitations. MD simulations identified gentisic acid as hit compound for shikimate kinase of H. pylori.

Current study could identify the in silico potential of mango ginger compounds against shikimate kinase and type II dehydroquinase targets for H. pylori infections and are suitable for in vitro and in vivo evaluation.

Thalassemia is associated with a genetic decline in the rate of synthesis of one or more types of natural hemoglobin polypeptide chains. One of the major complications in thalassemia patients is alloimmunization, which is antibody production by the patient against transfused red blood cells (RBCs). These RBCs are unknown by the recipient and the formed antibodies against them are called alloantibodies. This study aimed to evaluate the frequency of alloantibodies against RBCs in betathalassemia patients referred to Tehran Regional Blood Transfusion Center.

In this study, antibody screening tests (Dia-cell I, II, and III) were performed on 184 thalassemia patients. An identification test by the Dia panel consisting of 11 different O RBCs groups to examine sera with Dia cells (I, II, or III) was performed.

In our study, males and females patients comprised 66 (35.87%) and 118 (64.13%), respectively, of whom 116 (63%) had alloimmunization. In addition, 68 thalassemia subjects (37%) lacked alloantibodies. Among 184 patients with beta-thalassemia major, anti-K (Kell system), anti-D, and anti-E (Rhesus system) had the most abundant alloantibody variants with an incidence of 24 (13%), 11 (5.98%), and 10 (5.4%), respectively.

Before RBC transfusion, regular RBC antigen phenotypes, as well as problem-solving of alloantibody production by receiving compatible blood for Kell and RH subgroups, are suggested for all cases of transfusion-derived thalassemia.

Krabbe disease (KD) is an autosomal recessive disorder caused by mutations in the galactocerebrosidase (GALC) gene resulting in neuro-inflammation and defective myelination in the central and peripheral nervous systems. Most infantile patients present with clinical features before six months of age and die before two years of age. The only treatment available for presymptomatic or mildly affected individuals is hematopoietic stem cell transplantation (HSCT). In the animal models, combining bone marrow transplantation (BMT) with gene therapy has shown the best results in disease outcome. In this study, we examine the outcome of gene therapy alone.

Twitcher (twi) mice used in the study, have a W339X mutation in the GALC gene. Genotype identification of the mice was performed shortly after birth or post-natal day 1 (PND1), using polymerase chain reaction on the toe clips followed by restriction enzyme digestion and electrophoresis. Eight or nine-day-old affected mice were used for gene therapy treatment alone or combined with BMT. While iv injection of 4 × 1013 gc/kg of body weight of viral vector was used originally, different viral titers were also used without BMT to evaluate their outcomes.

When the standard viral dose was increased four- and ten-fold (4X and 10X) without BMT, the lifespans were increased significantly. Without BMT the affected mice were fertile, had the same weight and appearance as wild type mice and had normal strength and gait. The brains showed no staining for CD68, a marker for activated microglia/macrophages, and less astrogliosis than untreated twi mice.

Our results demonstrate that, it may be possible to treat human KD patients with high dose AAVrh10 without blood stem cell transplantation which would eliminate the side effects of HSCT.

Metabolomic studies on various colorectal cancer (CRC) cell lines have improved our understanding of the biochemical events underlying the disease. However, the metabolic profile dynamics associated with different stages of CRC progression is still lacking. Such information can provide further insights into the pathophysiology and progression of the disease that will prove useful in identifying specific targets for drug designing and therapeutics. Thus, our study aims to characterize the metabolite profiles in the established cell lines corresponding to different stages of CRC.

Metabolite profiling of normal colon cell lines (CCD 841 CoN) and CRC cell lines corresponding to different stages, i.e., SW 1116 (stage A), HT 29 and SW 480 (stage B), HCT 15 and DLD-1 (stage C), and HCT 116 (stage D), was carried out using liquid chromatography-mass spectrometry (LC-MS). Mass Profiler Professional and Metaboanalyst 4.0 software were used for statistical and pathway analysis. METLIN database was used for the identification of metabolites.

We identified 72 differential metabolites compared between CRC cell lines of all the stages and normal colon cells. Principle component analysis and partial least squares discriminant analysis score plot were used to segregate normal and CRC cells, as well as CRC cells in different stages of the disease. Variable importance in projection score identified unique differential metabolites in CRC cells of the different stages. We identified 7 differential metabolites unique to stage A, 3 in stage B, 5 in stage C, and 5 in stage D.

This study highlights the differential metabolite profiling in CRC cell lines corresponding to different stages. The identification of the differential metabolites in CRC cells at individual stages will lead to a better understanding of the pathophysiology of CRC development and progression and, hence, its application in treatment strategies.

The study examined the behavior of vasculature in conditions of eliminated cardiac function using mathematical modeling. In addition, we addressed the question of whether the stretch-recoil capability of veins, at least in part accounts for the slower response to simulated cardiac arrest.

In the first set of computational experiments, blood flow and pressure patterns in veins and arteries during the first few seconds after cardiac arrest were assessed via a validated multi-scale mathematical model of the whole cardiovascular system, comprising cardiac dynamics, arterial and venous blood flow dynamics, and microcirculation. In the second set of experiments, the effects of stretch-recoil zones of venous vessels with different diameters and velocities on blood velocity and dynamic pressure analyzed using computational fluid dynamics (CFD) modeling.

In the first set of experiments, measurement of changes in velocity, dynamic pressure, and fluid flow revealed that the venous system responded to cardiac arrest more slowly compared to the arteries. This disparity might be due to the intrinsic characteristics of the venous system, including stretch-recoil and elastic fiber composition. In the second set of experiments, we attempted to determine the role of the stretch-recoil capability of veins in the slower response to cardiac arrest. During the second set of experiments, we found that this recoil behavior increased dynamic pressure, velocity, and blood flow. The enhancement in dynamic pressure through combining the results from both experiments yielded a 15-40% increase in maximum dynamic pressure due to stretch-recoil, depending on vein diameter under normal conditions.

In the situation of cardiac arrest, the vein geometry changes continue, promoting smooth responses of the venous system. Moreover, the importance of such vein behavior in blood displacement may grow as the pressure on the venous side gradually decreases with time. Our experiments suggest that the driving force for venous return is the pressure difference that remains within the venous system after the energy coming from every ventricular systole spent to overcome the resistance created by arterial and capillary systems.