Noncovalent synthesis of homo and hetero-architectures of supramolecular polymers via secondary nucleation.

The synthesis of supramolecular polymers with controlled architecture is a grand challenge in supramolecular chemistry. Although living supramolecular polymerization via primary nucleation has been extensively studied for controlling the supramolecular polymerization of small molecules, the resulting supramolecular polymers have typically exhibited one-dimensional morphology. In this report, we present the synthesis of intriguing supramolecular polymer architectures through a secondary nucleation event, a mechanism well-established in protein aggregation and the crystallization of small molecules. To achieve this, we choose perylene diimide with 2-ethylhexyl chains at the imide position as they are capable of forming dormant monomers in solution. Activating these dormant monomers via mechanical stimuli and hetero-seeding using propoxyethyl perylene diimide seeds, secondary nucleation event takes over, leading to the formation of three-dimensional spherical spherulites and scarf-like supramolecular polymer heterostructures, respectively. Therefore, the results presented in this study propose a simple molecular design for synthesizing well-defined supramolecular polymer architectures via secondary nucleation.

Effect of rheological models on pulsatile hemodynamics in a multiply afflicted descending human aortic network.

In the cardiovascular diseased (CVD) conditions, it is essential to choose a suitable rheological model for capturing the correct physics behind the hemodynamic in the multiply afflicted diseased arterial network. This study investigates the effect of blood rheology on hemodynamics in a blood vessel with abdominal aortic aneurysm (AAA) and right internal iliac stenosis (RIIAS). A model with AAA and RIIAS is reconstructed from a human subject's computed tomography (CT) data. Localized mesh generation and pulsatile inflow condition are considered. Non-Newtonian models such as the Power-law, Carreau, Cross, and Herschel Berkley models are used in simulations. The outcome from a validated computational model is compared with the Newtonian model to identify the suitable model for dealing with pathological complications under consideration. The capabilities and significance of various rheological models are also examined via Wall Pressure (WP), Wall Shear Stress (WSS), velocity, Global non-Newtonian importance factor (IG), Vorticity Streamlines, and Swirling Strength. It is noted that during the entire cardiac cycle, the IG factor of the cross model is found to be relatively more significant. Power Law depicts larger IG factor during peak systole and early diastole. Also, the cross model depicts larger WSS, WPS, swirling strength distribution and vorticity during the peak systolic and diastolic phases It is noted that IG ∼0.02 is an appropriate non-Newtonian blood activity cut-off value in the descending abdominal artery having AAA and RIIAS. The critical important WSS values are in the range of 0-9 Pa which is stated in WSS contour plot.

Transparent Superhydrophobic Coatings of Silica Nanoparticles Using Functionalized Polyurethanes.

Superhydrophobic coatings are essential to prepare water-repellent surfaces, self-cleaning materials, etc. Silica nano-materials are often immobilized to different surfaces for imparting super-hydrophobicity. Direct coating of silica-nanoparticles is often challenging since it can easily be peeled off under different environments. Herein, we reported the use of properly functionalized polyurethanes to facilitate the strong binding of silica-nanoparticles to surfaces. The alkyne terminal polyurethane was synthesized by step-growth polymerization while click-reactions facilitated to post-functionalization using phenyl moiety and were characterized by 1 H, 13 C nuclear magnetic resonance (NMR) spectroscopies, and 1 H spin-lattice relaxation times (T1 s). Upon functionalization, the glass transition temperature (Tg) increased due to enhanced interchain interactions. Moreover, additives like di(propyleneglycol)dibenzoate showed a substantial plasticizing effect to compensate for the increase in Tg, an important parameter for low-temperature applications. NMR signatures the spatial interactions between various protons of grafted silica-nanoparticles and phenyl triazole functionalized polyurethanes, thus indicating the usefulness of polyurethanes to bind silica-nanoparticles. After coating functionalized silica-nanoparticles to leather using functionalized polyurethanes, a contact angle value of more than 157° was observed with retention of grain patterns of leather due to transparency. We anticipate the results to help design varieties of materials with superhydrophobicity where the structural integrity of the surfaces is retained.

TrGANet: Transforming 3T to 7T dMRI using Trapezoidal Rule and Graph based Attention Modules.

Diffusion MRI (dMRI) is a non-invasive tool for assessing the white matter region of the brain by approximating the fiber streamlines, structural connectivity, and estimation of microstructure. This modality can yield useful information for diagnosing several mental diseases as well as for surgical planning. The higher angular resolution diffusion imaging (HARDI) technique is helpful in obtaining more robust fiber tracts by getting a good approximation of regions where fibers cross. Moreover, HARDI is more sensitive to tissue changes and can accurately represent anatomical details in the human brain at higher magnetic strengths. In other words, magnetic strengths affect the quality of the image, and hence high magnetic strength has good tissue contrast with better spatial resolution. However, a higher magnetic strength scanner (like 7T) is costly and unaffordable to most hospitals. Hence, in this work, we have proposed a novel CNN architecture for the transformation of 3T to 7T dMRI. Additionally, we have also reconstructed the multi-shell multi-tissue fiber orientation distribution function (MSMT fODF) at 7T from single-shell 3T. The proposed architecture consists of a CNN-based ODE solver utilizing the Trapezoidal rule and graph-based attention layer alongwith L1 and total variation loss. Finally, the model has been validated on the HCP data set quantitatively and qualitatively.

Undersampled single-shell to MSMT fODF reconstruction using CNN-based ODE solver.

BACKGROUND AND OBJECTIVE: Diffusion MRI (dMRI) has been considered one of the most popular non-invasive techniques for studying the human brain's white matter (WM). dMRI is used to delineate the brain's microstructure by approximating the WM region's fiber tracts. The achieved fiber tracts can be utilized to assess mental diseases like Multiple sclerosis, ADHD, Seizures, Intellectual disability, and others. New techniques such as high angular resolution diffusion-weighted imaging (HARDI) have been developed, providing precise fiber directions, and overcoming the limitation of traditional DTI. Unlike Single-shell, Multi-shell HARDI provides tissue fractions for white matter, gray matter, and cerebrospinal fluid, resulting in a Multi-shell Multi-tissue fiber orientation distribution function (MSMT fODF). This MSMT fODF comes up with more precise fiber directions than a Single-shell, which helps to get correct fiber tracts. In addition, various multi-compartment diffusion models, including as CHARMED and NODDI, have been developed to describe the brain tissue microstructural information. This type of model requires multi-shell data to obtain more specific tissue microstructural information. However, a major concern with multi-shell is that it takes a longer scanning time restricting its use in clinical applications. In addition, most of the existing dMRI scanners with low gradient strengths commonly acquire a single b-value (shell) upto b=1000s/mm2 due to SNR (Signal-to-noise ratio) reasons and severe imaging artifacts. METHODS: To address this issue, we propose a CNN-based ordinary differential equations solver for the reconstruction of MSMT fODF from under-sampled and fully sampled Single-shell (b=1000s/mm2) dMRI. The proposed architecture consists of CNN-based Adams-Bash-forth and Runge-Kutta modules along with two loss functions, including L1 and total variation. RESULTS: We have shown quantitative results and visualization of fODF, fiber tracts, and structural connectivity for several brain regions on the publicly available HCP dataset. In addition, the obtained angular correlation coefficients for white matter and full brain are high, showing the proposed network's utility.Finally, we have also demonstrated the effect of noise by adjusting SNR from 5 to 50 and observed the network robustness. CONCLUSION: We can conclude that our model can accurately predict MSMT fODF from under-sampled or fully sampled Single-shell dMRI volumes.

The pulsatile 3D-Hemodynamics in a doubly afflicted human descending abdominal artery with iliac branching.

The study of patient-specific human arterial flow dynamics is well known to face challenges like a) apt geometric modelling, b) bifurcation zone meshing, and c) capturing the hemodynamic prone to variations with multiple disease complications. Due to aneurysms and stenosis in the same arterial network, the blood flow dynamics get affected, which needs to be explored. This study develops a new protocol for accurate geometric modelling, bifurcation zone meshing and numerically investigates the arterial network with abdominal aortic aneurysms (AAA) and right internal iliac stenosis (RIIAS). A realistic arterial model is reconstructed from the computed tomography (CT) data of a human subject. To understand the combined effect of the aneurysm and aortoiliac occlusive diseases in a patient, an arterial network with AAA, RIIAS, multiple branches tapering, and curvature has been considered. Clinically significant pulsatile blood flow simulations have been carried out to trace the alteration in the flow dynamics with multiple pathological complications under consideration. The transient blood flow dynamics are investigated via wall shear stress, wall pressure, velocity contour, streamlines, vorticity, and swirling strength. During the systolic deceleration phase, the rhythmic nested rapid secondary oscillatory WSS, adverse pressure gradients, high WSS, and high WP bands are noticed. Also, the above studies will help researchers, clinicians, and doctors understand the influence of morphological changes on hemodynamics in cardiovascular studies.

Chemical Communication in Artificial Cells: Basic Concepts, Design and Challenges.

In the past decade, the focus of bottom-up synthetic biology has shifted from the design of complex artificial cell architectures to the design of interactions between artificial cells mediated by physical and chemical cues. Engineering communication between artificial cells is crucial for the realization of coordinated dynamic behaviours in artificial cell populations, which would have implications for biotechnology, advanced colloidal materials and regenerative medicine. In this review, we focus our discussion on molecular communication between artificial cells. We cover basic concepts such as the importance of compartmentalization, the metabolic machinery driving signaling across cell boundaries and the different modes of communication used. The various studies in artificial cell signaling have been classified based on the distance between sender and receiver cells, just like in biology into autocrine, juxtacrine, paracrine and endocrine signaling. Emerging tools available for the design of dynamic and adaptive signaling are highlighted and some recent advances of signaling-enabled collective behaviours, such as quorum sensing, travelling pulses and predator-prey behaviour, are also discussed.

VRfRNet: Volumetric ROI fODF reconstruction network for estimation of multi-tissue constrained spherical deconvolution with only single shell dMRI.

Diffusion MRI (dMRI) is one of the most popular techniques for studying the brain structure, mainly the white matter region. Among several sampling methods in dMRI, the high angular resolution diffusion imaging (HARDI) technique has attracted researchers due to its more accurate fiber orientation estimation. However, the current single-shell HARDI makes the intravoxel structure challenging to estimate accurately. While multi-shell acquisition can address this problem, it takes a longer scanning time, restricting its use in clinical applications. In addition, most existing dMRI scanners with low gradient-strengths often acquire single-shell up to b=1000s/mm2 because of signal-to-noise ratio issues and severe image artefacts. Hence, we propose a novel generative adversarial network, VRfRNet, for the reconstruction of multi-shell multi-tissue fiber orientation distribution function from single-shell HARDI volumes. Such a transformation learning is performed in the spherical harmonics (SH) space, as raw input HARDI volume is transformed to SH coefficients to soften gradient directions. The proposed VRfRNet consists of several modules, such as multi-context feature enrichment module, feature level attention, and softmax level attention. In addition, three loss functions have been used to optimize network learning, including L1, adversarial, and total variation. The network is trained and tested using standard qualitative and quantitative performance metrics on the publicly available HCP data-set.

Cardiac electro-mechanical activity in a deforming human cardiac tissue: modeling, existence-uniqueness, finite element computation and application to multiple ischemic disease.

In this study, the cardiac electro-mechanical model in a deforming domain is taken with the addition of mechanical feedback and stretch-activated channel current coupled with the ten Tusscher human ventricular cell level model that results in a coupled PDE-ODE system. The existence and uniqueness of such a coupled system in a deforming domain is proved. At first, the existence of a solution is proved in the deformed domain. The local existence of the solution is proved using the regularization and the Faedo-Galerkin technique. Then, the global existence is proved using the energy estimates in appropriate Banach spaces, Gronwall lemma, and the compactness procedure. The existence of the solution in an undeformed domain is proved using the lower semi-continuity of the norms. Uniqueness is proved using Young's inequality, Gronwall lemma, and the Cauchy-Schwartz inequality. For the application purpose, this model is applied to understand the electro-mechanical activity in ischemic cardiac tissue. It also takes care of the development of active tension, conductive, convective, and ionic feedback. The Second Piola-Kirchoff stress tensor arising in Lagrangian mapping between reference and moving frames is taken as a combination of active, passive, and volumetric components. We investigated the effect of varying strength of hyperkalemia and hypoxia, in the ischemic subregions of human cardiac tissue with local multiple ischemic subregions, on the electro-mechanical activity of healthy and ischemic zones. This system is solved numerically using the [Formula: see text] finite element method in space and the implicit-explicit Euler method in time. Discontinuities arising with the modeled multiple ischemic regions are treated to the desired order of accuracy by a simple regularization technique using the interpolating polynomials. We examined the cardiac electro-mechanical activity for several cases in multiple hyperkalemic and hypoxic human cardiac tissue. We concluded that local multiple ischemic subregions severely affect the cardiac electro-mechanical activity more, in terms of action potential (v) and mechanical parameters, intracellular calcium ion concentration [Formula: see text], active tension ([Formula: see text]), stretch ([Formula: see text]) and stretch rate ([Formula: see text]), of a healthy cell in its vicinity, compared to a single Hyperkalemic or Hypoxic subregion. The four moderate hypoxically generated ischemic subregions affect the waveform of the stretch along the fiber and the stretch rate more than a single severe ischemic subregion.

Mutual Information Regularized Feature-Level Frankenstein for Discriminative Recognition.

Deep learning recognition approaches can potentially perform better if we can extract a discriminative representation that controllably separates nuisance factors. In this paper, we propose a novel approach to explicitly enforce the extracted discriminative representation d, extracted latent variation l (e,g., background, unlabeled nuisance attributes), and semantic variation label vector s (e.g., labeled expressions/pose) to be independent and complementary to each other. We can cast this problem as an adversarial game in the latent space of an auto-encoder. Specifically, with the to-be-disentangled s, we propose to equip an end-to-end conditional adversarial network with the ability to decompose an input sample into d and l. However, we argue that maximizing the cross-entropy loss of semantic variation prediction from d is not sufficient to remove the impact of s from d, and that the uniform-target and entropy regularization are necessary. A collaborative mutual information regularization framework is further proposed to avoid unstable adversarial training. It is able to minimize the differentiable mutual information between the variables to enforce independence. The proposed discriminative representation inherits the desired tolerance property guided by prior knowledge of the task. Our proposed framework achieves top performance on diverse recognition tasks, including digits classification, large-scale face recognition on LFW and IJB-A datasets, and face recognition tolerant to changes in lighting, makeup, disguise, etc.

Development and Validation of Chemometrics-Assisted Green UPLC-MS/MS Bioanalytical Method for Simultaneous Estimation of Capecitabine and Lapatinib in Rat Plasma.

A chemometrics-oriented green ultra-performance liquid chromatography-mass spectrometry/mass spectrometry method was developed and validated for the first-time simultaneous estimation of capecitabine (CAP) and lapatinib (LPB) along with imatinib (as internal standard (IS)) in rat plasma. Analytes were extracted using ethyl acetate as the liquid-liquid extraction media. In the pre-development phase, principles of analytical eco-scale were used to confirm method greenness. Subsequently, vital method variables, influencing method robustness and performance, were optimized using a chemometrics-based quality-by-design approach. Chromatography was achieved on a BEH C18 (100 × 2.1 mm, 1.7 µm) using isocratic flow (0.5 mL.min-1) of mobile phase acetonitrile (0.1% formic acid):0.002 M ammonium acetate in water as the mobile phase. The mass spectrometric detections were carried out in multiple reaction monitoring modes with precursor-to-product ion transitions with m/z 360.037 → 244.076 for CAP, m/z 581.431 → 365.047 LPB and m/z 494.526 → 394.141 for IS. The bioanalytical method validation studies were performed, ensuring regulatory compliance. Linearity (r2> 0.99) over analyte concentrations ranging from 5 and 40 ng.mL-1 was observed, while acceptable values were obtained for all other validation parameters. In a nutshell, a robust and green bioanalytical method was developed and applied for the simultaneous estimation of two anticancer agents from rat plasma.

Delay in puberty is dependent on heat shock protein B1 expression in native cross layers of Punjab under heat stress.

Small heat shock protein B1 (HspB1) has been reported to play an essential role in thermotolerance. This study aimed to determine a correlation (if any) between HspB1 expression and age at first egg lay (puberty) in a native cross-layer poultry of Punjab under heat stress. Forty native cross-layer birds were reared in two different seasons, viz. summer (THI was more than 27), classified as the heat-stressed group (n = 20) and winter season (THI was less than 21), classified as the control group (n = 20). Blood was collected from both the groups of birds in their 15th week of age and at puberty. Serum catalase and superoxide dismutase activities, reduced glutathione and corticosterone concentration and lipid peroxidation were measured to assess the oxidative stress in both the groups of birds. The serum antioxidants significantly decreased whilst corticosterone levels and lipid peroxidation significantly elevated in birds in response to summer heat stress. Moreover, in summer season, the activities of the antioxidant enzymes further decreased and lipid peroxidation further increased significantly in birds from their pre-pubertal stage to puberty, which was not observed during the winter season. A clone of chicken HspB1 in BL21 (DE3) cells was revived, and recombinant HspB1 was purified using Ni-NTA agarose column. Serum HspB1 concentration was estimated in different groups of birds by indirect ELISA that has been standardized using the recombinant chicken HspB1. Compared to the control, birds under heat stress had significantly higher serum HspB1 levels. The delay in puberty of all the heat-stressed birds was significantly associated with the increase in their serum HspB1 levels. Taken together, the expression of HspB1 was found to be associated with age at puberty in the native cross poultry layers of Punjab.

Chemical-mediated translocation in protocell-based microactuators.

Artificial cell-like communities participate in diverse modes of chemical interaction but exhibit minimal interfacing with their local environment. Here we develop an interactive microsystem based on the immobilization of a population of enzyme-active semipermeable proteinosomes within a helical hydrogel filament to implement signal-induced movement. We attach large single-polynucleotide/peptide microcapsules at one or both ends of the helical protocell filament to produce free-standing soft microactuators that sense and process chemical signals to perform mechanical work. Different modes of translocation are achieved by synergistic or antagonistic enzyme reactions located within the helical connector or inside the attached microcapsule loads. Mounting the microactuators on a ratchet-like surface produces a directional push-pull movement. Our methodology opens up a route to protocell-based chemical systems capable of utilizing mechanical work and provides a step towards the engineering of soft microscale objects with increased levels of operational autonomy.

Interaction between sodium dodecylsulfate (SDS) and pluronic L61 in aqueous medium: assessment of the nature and morphology of the formed mixed aggregates by NMR, EPR, SANS and FF-TEM measurements.

The interaction of copolymer L61 i.e., (EO)2(PO)32(EO)2 (where EO and PO are ethylene and propylene oxides, respectively) with surfactant SDS (sodium dodecylsulfate) in relation to their self-aggregation, dynamics and microstructures has been physicochemically studied in detail employing the Nuclear Magnetic Resonance (NMR), Electron Paramagnetic Resonance (EPR), Small-Angle Neutron Scattering (SANS), and Freeze-Fracture Transmission Electron Microscopy (FF-TEM) methods. The NMR self-diffusion study indicated a synergistic interaction between SDS and L61 forming L61-SDS mixed complex aggregates, and deuterium (2H) NMR pointed out the nonspherical nature of these aggregates with increasing [L61]. EPR spectral analysis of the motional parameters of 5-doxyl steraric acid (5-DSA) as a spin probe provided information on the microviscosity of the local environment of the L61-SDS complex aggregates. SANS probed the geometrical aspects of the SDS-L61 assemblies as a function of both [L61] and [SDS]. Progressive evolution of the mixed-aggregate geometries from globular to prolate ellipsoids with axial ratios ranging from 2 to 10 with increasing [L61] was found. Such morphological changes were further corroborated with the results of 2H NMR and FF-TEM measurements. The strategy of the measurements, and data analysis for a concerted conclusion have been presented.

Determining Cost-Optimal Next-Generation Sequencing Panels for Rare Disease and Pharmacogenomics Testing.

BACKGROUND: Multi-gene panel sequencing using next-generation sequencing (NGS) methods is a key tool for genomic medicine. However, with an estimated 140 000 genomic tests available, current system inefficiencies result in high genetic-testing costs. Reduced testing costs are needed to expand the availability of genomic medicine. One solution to improve efficiency and lower costs is to calculate the most cost-effective set of panels for a typical pattern of test requests. METHODS: We compiled rare diseases, associated genes, point prevalence, and test-order frequencies from a representative laboratory. We then modeled the costs of the relevant steps in the NGS process in detail. Using a simulated annealing-based optimization procedure, we determined panel sets that were more cost-optimal than whole exome sequencing (WES) or clinical exome sequencing (CES). Finally, we repeated this methodology to cost-optimize pharmacogenomics (PGx) testing. RESULTS: For rare disease testing, we show that an optimal choice of 4-6 panels, uniquely covering genes that comprise 95% of the total prevalence of monogenic diseases, saves $257-304 per sample compared with WES, and $66-135 per sample compared with CES. For PGx, we show that the optimal multipanel solution saves $6-7 (27%-40%) over a single panel covering all relevant gene-drug associations. CONCLUSIONS: Laboratories can reduce costs using the proposed method to obtain and run a cost-optimal set of panels for specific test requests. In addition, payers can use this method to inform reimbursement policy.

Exposures to 2,4-Dichlorophenoxyacetic acid with or without endotoxin upregulate small cell lung cancer pathway.

BACKGROUND: Pesticide residues in food and environment along with airborne contaminants such as endotoxins pose health risk. Although herbicide 2,4-Dichlorophenoxyacetic acid (2,4-D) has been associated with increased risk of lung cancers such as small cell lung cancer (SCLC) among agricultural workers, there are no data on the SCLC signaling pathway upon 2,4-D exposure without LPS or in combination with endotoxin. METHODS: We exposed Swiss albino mice (N = 48) orally to high (9.58 mg kg- 1) and low (5.12 mg kg- 1) dosages of 2,4-D dissolved in corn oil for 90 days followed by E. coli lipopolysaccharide (LPS) or normal saline solution (80 µl/animal). Lung samples and broncho-alveolar fluid (BALF) were subjected to Total histological score (THS) and total leucocyte count (TLC) and differential leucocytes count (DLC) analyses, respectively. We used microarray and bioinformatics tools for transcriptomic analyses and differentially expressed genes were analyzed to predict the top canonical pathways followed by validation of selected genes by qRT-PCR and immunohistochemistry. RESULTS: Total histological score (THS) along with BALF analyses showed lung inflammation following long term dietary exposure to high or low doses of 2,4-D individually or in combination with LPS. Microarray analysis revealed exposure to high dose of 2,4-D without or with LPS upregulated 2178 and 2142 and downregulated 1965 and 1719 genes, respectively (p < 0.05; minimum cut off 1.5 log fold change). The low dose without or with LPS upregulated 2133 and 2054 and downregulated 1838 and 1625 genes, respectively. Bioinformatics analysis showed SCLC as topmost dysregulated pathway along with differential expression of Itgb1, NF-κB1, p53, Cdk6 and Apaf1. Immunohistological and quantitative real time PCR (qRT-PCR) analyses also supported the transcriptomic data. CONCLUSIONS: Taken together, the data show exposures to high and low dose of 2,4-D with/without LPS induced lung inflammation and altered pulmonary transcriptome profile with the involvement of the SCLC pathway. The data from the study provide the insights of the potential damage on lungs caused by 2,4-D and help to better understand the mechanism of this complex relation.

Drug Repurposing Strategy (DRS): Emerging Approach to Identify Potential Therapeutics for Treatment of Novel Coronavirus Infection.

Drug repurposing is also termed as drug repositioning or therapeutic switching. This method is applied to identify the novel therapeutic agents from the existing FDA approved clinically used drug molecules. It is considered as an efficient approach to develop drug candidates with new pharmacological activities or therapeutic properties. As the drug discovery is a costly, time-consuming, laborious, and highly risk process, the novel approach of drug repositioning is employed to increases the success rate of drug development. This strategy is more advantageous over traditional drug discovery process in terms of reducing duration of drug development, low-cost, highly efficient and minimum risk of failure. In addition to this, World health organization declared Coronavirus disease (COVID-19) as pandemic globally on February 11, 2020. Currently, there is an urgent need to develop suitable therapeutic agents for the prevention of the outbreak of COVID-19. So, various investigations were carried out to design novel drug molecules by utilizing different approaches of drug repurposing to identify drug substances for treatment of COVID-19, which can act as significant inhibitors against viral proteins. It has been reported that COVID-19 can infect human respiratory system by entering into the alveoli of lung via respiratory tract. So, the infection occurs due to specific interaction or binding of spike protein with angiotensin converting enzyme-2 (ACE-2) receptor. Hence, drug repurposing strategy is utilized to identify suitable drugs by virtual screening of drug libraries. This approach helps to determine the binding interaction of drug candidates with target protein of coronavirus by using computational tools such as molecular similarity and homology modeling etc. For predicting the drug-receptor interactions and binding affinity, molecular docking study and binding free energy calculations are also performed. The methodologies involved in drug repurposing can be categorized into three groups such as drug-oriented, target-oriented and disease or therapy-oriented depending on the information available related to quality and quantity of the physico-chemical, biological, pharmacological, toxicological and pharmacokinetic property of drug molecules. This review focuses on drug repurposing strategy applied for existing drugs including Remdesivir, Favipiravir, Ribavirin, Baraticinib, Tocilizumab, Chloroquine, Hydroxychloroquine, Prulifloxacin, Carfilzomib, Bictegravir, Nelfinavir, Tegobuvir and Glucocorticoids etc to determine their effectiveness toward the treatment of COVID-19.

Expression of recombinant DnaK of Brucella abortus and its evaluation as immuno-modulator.

Heat shock proteins are molecular chaperones that are immunogens as well as potent inducers of an antigen-specific immunological response. In this study, we aimed to evaluate if co-immunization of Brucella rOmp22 and rDnaK proteins had boosted immunogenic activity as compared to rOmp22 immunization alone in mice. For this, gene-encoding DnaK of B. abortus was cloned, expressed in E. coli and purified using Ni-NTA agarose. Immuno-modulatory effect of rDnaK protein was evaluated in mice when co-immunized with Brucella rOmp22. Four groups of mice (n = 6 per group) were used in the study. The control group was immunized with rOmp22 alone, while rOmp22 emulsified with conventional adjuvants (Freund's complete and incomplete adjuvants) and rOmp22 mixed with rDnaK were injected to group I and group II in mice, respectively. Group III mice were immunized with rDnaK alone. IgG class switching (IgG1 and IgG2a) response to immunization was assessed by enzyme-linked immunosorbent assay and expression of IL-4 and IL-12 mRNA was assessed by real-time PCR to evaluate the immune response in mice. The ratio of IgG1-IgG2a was less than 1 in mice co-immunized with rOmp22 and rDnaK, indicating that the immune response was directed towards CMI arm in this group of mice. Moreover, IL-12 mRNA expression was also up-regulated to a greater extent in mice co-immunized with rOmp22 and rDnaK as compared to those immunized with rOmp22 along with the conventional adjuvants, or rOmp22 alone. Our data suggest that rDnaK could be responsible for modulating the immune response, specifically the CMI response.