Printable functionally graded tibial implant for TAR: FE study comparing implant materials, FGM properties, and implant designs.

Tibial implants with functionally graded material (FGM) for total ankle replacement (TAR) can provide stiffness similar to the host tibia bone. The FGM implants with low stiffness reduce stress shielding but may increase implant-bone micromotion. A trade-off between stress shielding and implant-bone micromotion is required if FGMs are to substitute traditionally used Ti and CoCr metal implants. The FGM properties such as material gradation law and volume fraction index may influence the performance of FGM implants. Along with the FGM properties, the design of FGM implants may also have a role to play. The objective of this study was to examine FGM tibial implants for TAR, by comparing implant materials, FGM properties, and implant designs. For this purpose, finite element analysis (FEA) was conducted on 3D FE models of the intact and the implanted tibia bone. The tibial implants were composed of CoCr and Ti, besides them, the FGM of Ti and HA was developed. The FGM implants were modelled using exponential, power, and sigmoid laws. Additionally, for power and sigmoid laws, different volume fraction indices were taken. The effect of implant design was observed by using keel type and stem type TAR fixation designs. The results indicated that FGM implants are better than traditional metal implants. The power law is most suitable for developing FGM implants because it reduces stress shielding. For both power law and sigmoid law, low values of the volume fraction index are preferrable. Therefore, FGM implant developed using power law with 0.1 vol fraction index is ideal with the lowest stress shielding and marginally increased implant-bone micromotion. FGM implants are more useful for keel type fixation design than stem type design. To conclude, with FGMs the major complication of stress shielding can be solved and the longevity and durability of TAR implants can be enhanced.

Repurposing of antimycobacterium drugs for COVID-19 treatment by targeting SARS CoV-2 main protease: An in-silico perspective.

The global mortality rate has been significantly impacted by the COVID-19 pandemic, caused by the SARS CoV-2 virus. Although the pursuit for a potent antiviral is still in progress, experimental therapies based on repurposing of existing drugs is being attempted. One important therapeutic target for COVID-19 is the main protease (Mpro) that cleaves the viral polyprotein in its replication process. Recently minocycline, an antimycobacterium drug, has been successfully implemented for the treatment of COVID-19 patients. But it's mode of action is still far from clear. Furthermore, it remains unresolved whether alternative antimycobacterium drugs can effectively regulate SARS CoV-2 by inhibiting the enzymatic activity of Mpro. To comprehend these facets, eight well-established antimycobacterium drugs were put through molecular docking experiments. Four of the antimycobacterium drugs (minocycline, rifampicin, clofazimine and ofloxacin) were selected by comparing their binding affinities towards Mpro. All of the four drugs interacted with both the catalytic residues of Mpro (His41 and Cys145). Additionally, molecular dynamics experiments demonstrated that the Mpro-minocyline complex has enhanced stability, experiences reduced conformational fluctuations and greater compactness than other three Mpro-antimycobacterium and Mpro-N3/lopinavir complexes. This research furnishes evidences for implementation of minocycline against SARS CoV-2. In addition, our findings also indicate other three antimycobacterium/antituberculosis drugs (rifampicin, clofazimine and ofloxacin) could potentially be evaluated for COVID-19 therapy.

Assessment of bone ingrowth around beaded coated tibial implant for total ankle replacement using mechanoregulatory algorithm.

The long-term performance of porous coated tibial implants for total ankle replacement (TAR) primarily depends on the extent of bone ingrowth at the bone-implant interface. Although attempts were made for primary fixation for immediate post-operative stability, no investigation was conducted on secondary fixation. The aim of this study is to assess bone ingrowth around the porous beaded coated tibial implant for TAR using a mechanoregulatory algorithm. A realistic macroscale finite element (FE) model of the implanted tibia was developed based on computer tomography (CT) data to assess implant-bone micromotions and coupled with microscale FE models of the implant-bone interface to predict bone ingrowth around tibial implant for TAR. The macroscale FE model was subjected to three near physiological loading conditions to evaluate the site-specific implant-bone micromotion, which were then incorporated into the corresponding microscale model to mimic the near physiological loading conditions. Results of the study demonstrated that the implant experienced tangential micromotion ranged from 0 to 71 µm with a mean of 3.871 µm. Tissue differentiation results revealed that bone ingrowth across the implant ranged from 44 to 96 %, with a mean of around 70 %. The average Young's modulus of the inter-bead tissue layer varied from 1444 to 4180 MPa around the different regions of the implant. The analysis postulates that when peak micromotion touches 30 µm around different regions of the implant, it leads to pronounced fibrous tissues on the implant surface. The highest amount of bone ingrowth was observed in the central regions, and poor bone ingrowth was seen in the anterior parts of the implant, which indicate improper osseointegration around this region. This macro-micro mechanical FE framework can be extended to improve the implant design to enhance the bone ingrowth and in future to develop porous lattice-structured implants to predict and enhance osseointegration around the implant.

A numerical investigation for the development of functionally graded Ti/HA tibial implant for total ankle replacement: Influence of material gradation law and volume fraction index.

Stress shielding is one of the major concerns for total ankle replacement implants nowadays, because it is responsible for implant-induced bone resorption. The bone resorption contributes to the aseptic loosening and failure of ankle implants in later stages. To reduce the stress shielding, improvements can be made in the implant material by decreasing the elastic mismatch between the implant and the tibia bone. This study proposes a new functionally graded material (FGM) based tibial implant for minimizing the problem of stress shielding. Three-dimensional finite element (FE) models of the intact tibia and the implanted tibiae were created to study the influence of material gradation law and volume fraction index on stress shielding and implant-bone micromotion. Different implant materials were considered that is, cobalt-chromium, titanium (Ti), and FGM with Ti at the bottom and hydroxyapatite (HA) at the top. The FE models of FGM implants were generated by using different volume fractions and the rule of mixtures. The rule of mixtures was used to calculate the FGM properties based on the local volume fraction. The volume fraction was defined by using exponential, power, and sigmoid laws. For the power and sigmoid law varying volume fraction indices (0.1, 0.2, 0.5, 1, 2, and 5) were considered. The geometry resembling STAR® ankle system tibial implant was considered for the present study. The results indicate that FGMs lower stress shielding but also marginally increase implant-bone micromotion; however, the values were within the acceptable limit for bone ingrowth. It is observed that the material gradation law and volume fraction index influence the performance of FGM tibial implants. The tibial implant composed of FGM using power law with a volume fraction index of 0.1 was the preferred option because it showed the least stress shielding.

Influence of obesity on load-transfer mechanism, contact mechanics, and longevity of cemented acetabular cup.

Objective: This investigation aimed to assess the impact of obesity on the load-transfer mechanism, longevity, and contact mechanics of cemented acetabular cups. Methods: Three obesity scenarios were considered: obese case-I (100-110 kg), obese case-II (120-130 kg), and obese case-III (140-150 kg). Utilising six finite element models, the effects of different bodyweights on load transfer, contact mechanics, and cup longevity during normal walking conditions were assessed. Muscle forces and hip joint reaction forces were adjusted and linearly calibrated based on obesity cases. Results: Elevated stresses in cortical and cancellous bones, as well as the cement mantle, were observed in obese cases, suggesting a heightened risk of loosening and failure of the cemented fixation of the acetabular cup. Additionally, increased contact pressure and micromotion between articulating surfaces were noted in obese individuals, with a gradual escalation from obese case-I to obese case-III. Conclusions: These findings highlight the significant negative impact of obesity on the performance of cemented acetabular cups, emphasizing the importance of considering bodyweight variations in the design and assessment of orthopaedic implants for optimal functionality and durability.

A macro-micro FE and ANN framework to assess site-specific bone ingrowth around the porous beaded-coated implant: an example with BOX® tibial implant for total ankle replacement.

The use of mechanoregulatory schemes based on finite element (FE) analysis for the evaluation of bone ingrowth around porous surfaces is a viable approach but requires significant computational time and effort. The aim of this study is to develop a combined macro-micro FE and artificial neural network (ANN) framework for rapid and accurate prediction of the site-specific bone ingrowth around the porous beaded-coated tibial implant for total ankle replacement (TAR). A macroscale FE model of the implanted tibia was developed based on CT data. Subsequently, a microscale FE model of the implant-bone interface was created for performing bone ingrowth simulations using mechanoregulatory algorithms. An ANN was trained for rapid and accurate prediction of bone ingrowth. The results predicted by ANN are well comparable to FE-predicted results. Predicted site-specific bone ingrowth using ANN around the implant ranges from 43.04 to 98.24%, with a mean bone ingrowth of around 74.24%. Results suggested that the central region exhibited the highest bone ingrowth, which is also well corroborated with the recent explanted study on BOX®. The proposed methodology has the potential to simulate bone ingrowth rapidly and effectively at any given site over any implant surface.

The role of the depth of resection of the distal tibia on biomechanical performance of the tibial component for TAR: A finite element analysis with three implant designs.

The depth of resection of the tibia bone in total ankle replacement (TAR) may influence implant-bone micromotion and stress shielding. High implant-bone micromotion and stress-shielding lead to aseptic loosening of the tibial component for TAR. The aim was to improve the outcomes of the different designs of TAR (STAR, Mobility, and Salto) with the variation of the depth of resection of the distal tibia bone. Finite element (FE) models of the implanted tibia with the depth of resection varying from 6 mm to 16 mm and of the intact tibia was prepared. The value of micromotion increased as the depth of resection increased. The micromotion increased in the proximal anterior-posterior portion of the pegs for STAR, the posterior part of the stem for Mobility, and the proximal lateral portion of the keel for Salto with the increase in the depth of resection. Whereas, the stresses (von Mises) decreased in some regions and increased in some regions depending upon the implant design. But overall stresses decreased in the tibia bone. Furthermore, the mean stress shielding increased in all the designs as the depth of resection increased. This in silico study indicated that the depth of resection should be given more importance during TAR surgery. The ideal depth of resection should be minimum i.e., 6 mm based on this FE study.

Single-tier point-of-care serodiagnosis of Lyme disease.

Point-of-care (POC) serological testing provides actionable information for several difficult to diagnose illnesses, empowering distributed health systems. Accessible and adaptable diagnostic platforms that can assay the repertoire of antibodies formed against pathogens are essential to drive early detection and improve patient outcomes. Here, we report a POC serologic test for Lyme disease (LD), leveraging synthetic peptides tuned to be highly specific to the LD antibody repertoire across patients and compatible with a paper-based platform for rapid, reliable, and cost-effective diagnosis. A subset of antigenic epitopes conserved across Borrelia burgdorferi genospecies and targeted by IgG and IgM antibodies, were selected based on their seroreactivity to develop a multiplexed panel for a single-step measurement of combined IgM and IgG antibodies from LD patient sera. Multiple peptide epitopes, when combined synergistically using a machine learning-based diagnostic model, yielded a high sensitivity without any loss in specificity. We blindly tested the platform with samples from the U.S. Centers for Disease Control & Prevention (CDC) LD repository and achieved a sensitivity and specificity matching the lab-based two-tier results with a single POC test, correctly discriminating cross-reactive look-alike diseases. This computational LD diagnostic test can potentially replace the cumbersome two-tier testing paradigm, improving diagnosis and enabling earlier effective treatment of LD patients while also facilitating immune monitoring and surveillance of the disease in the community.

A new mathematical model of compressive stress-strain behaviour of low viscosity and high viscosity bone cement with different strain rates.

A new mathematical model of compressive stress-strain behaviour of low viscosity (LV) and high viscosity (HV) bone cement has been proposed to capture large uniaxial deformation under constant applied strain rate by incorporating three-term power law. The modeling capacity of the proposed model has been validated using uniaxial compressive test under eight different low strain rates ranging from 1.39 × 10-4 s-1 to 3.53 × 10-2 s-1 for low viscosity and high viscosity bone cement. The well agreement between the model and experimental response suggests that the proposed model can successfully predict rate dependent deformation behavior for Poly(methyl methacrylate) (PMMA) bone cement. Additionally, the proposed model was compared with the generalized Maxwell viscoelastic model and found to be in good agreement. The comparison of compressive responses over low strain rates for LV and HV bone cement reveals their rate-dependent compressive yield stress behaviour along with a higher value of compressive yield stress of LV bone cement compared to HV bone cement. For example, at the strain rate of 1.39 × 10-4 s-1 the mean value of compressive yield stress of LV bone cement was found to be 64.46 MPa, whereas for HV bone cement it was 54.00 MPa. Moreover, the modeling of experimental compressive yield stress with the Ree-Eyring molecular theory suggests that the variation of yield stress of PMMA bone cement can be predicted using two processes Ree-Eyring theory. The proposed constitutive model might be useful to characterize large deformation behaviour with high accuracy for PMMA bone cement. Finally, both variants of PMMA bone cement also exhibit ductile-like compressive behaviour below the strain rate of 2.1 × 10-2 s-1, whereas above this threshold strain rate, brittle-like compressive failure behavior is observed.

A combined FE-hybrid MCDM framework for improving the performance of the conical stem tibial design for TAR with the addition of pegs.

BACKGROUND AND OBJECTIVES: The conical stemmed design of the tibial component for total ankle replacement (TAR) (example Mobility design) uses a single intramedullary stem for primary fixation. Tibial component loosening is a common mode of failure for TAR. Primary causes of loosening are lack of bone ingrowth due to excessive micromotion at the implant-bone interface and bone resorption due to stress shielding after implantation. The fixation feature of the conical stemmed design can be modified with the addition of small pegs to avoid loosening. The aim of the study is to select the improved design for conical stemmed TAR using a combined Finite Element (FE) hybrid Multi-Criteria Decision-Making (MCDM) framework. METHODS: The geometry and material properties of the bone for FE modeling were extracted from the CT data. Thirty-two design alternatives with varying pegs in number (one, two, four, eight), location (anterior, posterior, medial, lateral, anterior-posterior, medial-lateral, equally spaced), and height (5 mm, 4 mm, 3 mm, 2 mm) were prepared. All models were analyzed for dorsiflexion, neutral, and plantarflexion loading. The proximal part of the tibia was fixed. The implant-bone interface coefficient of friction was taken as 0.5. The implant-bone micromotion, stress shielding, volume of bone resection, and surgical simplicity were the important criteria considered for evaluating the performance of TAR. The designs were compared using a hybrid MCDM method of WASPAS, TOPSIS, EDAS, and VIKOR. The weight calculations were based on fuzzy AHP and the final ranks on the Degree of Membership method. RESULTS: The addition of pegs decreased the mean implant-bone micromotions and increased stress shielding. There was a marginal decrease in micromotion and a marginal increase in stress shielding when the peg heights were increased. The results of hybrid MCDM indicated that the most preferable alternative designs were two pegs of 4 mm height in the AP direction to the main stem, two pegs of 4 mm height in the ML direction, and one peg of 3 mm height in the A direction. CONCLUSIONS: Outcomes of this study suggest that the addition of pegs can reduce the implant-bone micromotions. Modified three designs would be useful by considering implant-bone micromotions, stress shielding, volume of bone resection, and surgical simplicity.

Deep Learning-Enabled Multiplexed Point-of-Care Sensor using a Paper-Based Fluorescence Vertical Flow Assay.

Multiplexed computational sensing with a point-of-care serodiagnosis assay to simultaneously quantify three biomarkers of acute cardiac injury is demonstrated. This point-of-care sensor includes a paper-based fluorescence vertical flow assay (fxVFA) processed by a low-cost mobile reader, which quantifies the target biomarkers through trained neural networks, all within <15 min of test time using 50 µL of serum sample per patient. This fxVFA platform is validated using human serum samples to quantify three cardiac biomarkers, i.e., myoglobin, creatine kinase-MB, and heart-type fatty acid binding protein, achieving less than 0.52 ng mL-1 limit-of-detection for all three biomarkers with minimal cross-reactivity. Biomarker concentration quantification using the fxVFA that is coupled to neural network-based inference is blindly tested using 46 individually activated cartridges, which shows a high correlation with the ground truth concentrations for all three biomarkers achieving >0.9 linearity and <15% coefficient of variation. The competitive performance of this multiplexed computational fxVFA along with its inexpensive paper-based design and handheld footprint makes it a promising point-of-care sensor platform that can expand access to diagnostics in resource-limited settings.

Automated Quantification of Inflamed Lung Regions in Chest CT by UNet++ and SegCaps: A Comparative Analysis in COVID-19 Cases.

During the current COVID-19 pandemic, a high volume of lung imaging has been generated in the aid of the treating clinician. Importantly, lung inflammation severity, associated with the disease outcome, needs to be precisely quantified. Producing consistent and accurate reporting in high-demand scenarios can be a challenge that can compromise patient care with significant inter- or intra-observer variability in quantifying lung inflammation in a chest CT scan. In this backdrop, automated segmentation has recently been attempted using UNet++, a convolutional neural network (CNN), and results comparable to manual methods have been reported. In this paper, we hypothesize that the desired task can be performed with comparable efficiency using capsule networks with fewer parameters that make use of an advanced vector representation of information and dynamic routing. In this paper, we validate this hypothesis using SegCaps, a capsule network, by direct comparison, individual comparison with CT severity score, and comparing the relative effect on a ML(machine learning)-based prognosis model developed elsewhere. We further provide a scenario, where a combination of UNet++ and SegCaps achieves improved performance compared to individual models.

Single-cell sorting based on secreted products for functionally defined cell therapies.

Cell therapies have emerged as a promising new class of "living" therapeutics over the last decade and have been particularly successful for treating hematological malignancies. Increasingly, cellular therapeutics are being developed with the aim of treating almost any disease, from solid tumors and autoimmune disorders to fibrosis, neurodegenerative disorders and even aging itself. However, their therapeutic potential has remained limited due to the fundamental differences in how molecular and cellular therapies function. While the structure of a molecular therapeutic is directly linked to biological function, cells with the same genetic blueprint can have vastly different functional properties (e.g., secretion, proliferation, cell killing, migration). Although there exists a vast array of analytical and preparative separation approaches for molecules, the functional differences among cells are exacerbated by a lack of functional potency-based sorting approaches. In this context, we describe the need for next-generation single-cell profiling microtechnologies that allow the direct evaluation and sorting of single cells based on functional properties, with a focus on secreted molecules, which are critical for the in vivo efficacy of current cell therapies. We first define three critical processes for single-cell secretion-based profiling technology: (1) partitioning individual cells into uniform compartments; (2) accumulating secretions and labeling via reporter molecules; and (3) measuring the signal associated with the reporter and, if sorting, triggering a sorting event based on these reporter signals. We summarize recent academic and commercial technologies for functional single-cell analysis in addition to sorting and industrial applications of these technologies. These approaches fall into three categories: microchamber, microfluidic droplet, and lab-on-a-particle technologies. Finally, we outline a number of unmet needs in terms of the discovery, design and manufacturing of cellular therapeutics and how the next generation of single-cell functional screening technologies could allow the realization of robust cellular therapeutics for all patients.

Biomechanical performance of the cemented acetabular cup with combined effects of bone quality, implant material combinations and bodyweight.

GRAPHICAL ABSTRACT: [Formula: see text].

Identification of Alkaloids from Terminalia chebula as Potent SARS- CoV-2 Main Protease Inhibitors: An In Silico Perspective.

Natural compounds in medicinal plants are best remedies for different diseases and are important to develop new drugs. This work was dedicated to understand the role of different natural compounds of Terminalia Chebula, a well-known herbal plant, in the treating of Covid 19. In this article, we have investigated interactions of such natural compounds from Terminalia Chebula with the main protease (Mpro) of the SARS-CoV-2, which is a key component for cleavage of viral polyprotein, and an important target for the development of drugs towards COVID-19. We have performed molecular docking study on 22 different molecules of Terminalia Chebula and proposed that 7 of the natural compounds (triterpenoids and sterols) interacts with a comparable or stronger interactions than the inhibitor N3. Molecular dynamics simulations (100 ns) revealed that 7 Mpro-Terminalia Chebula complexes are stable, conformationally less fluctuated, slightly less compact, and marginally expanded than ligand-free conformation of Mpro. The intermolecular H-bonding and detailed MM/PBSA and MM-GBSA analysis showed Daucosterol interaction to be the most strong, whereas comparable interactions were observed for Arjunetin, Maslinic acid, and Bellericoside. Our study suggested that these natural compounds can act as potent Mpro inhibitors for SARS-CoV-2, and may evolve as promising anti-COVID-19 drugs in the near future.

Biomechanical analysis of three popular tibial designs for TAR with different implant-bone interfacial conditions and bone qualities: A finite element study.

BACKGROUND: The long-term success of total ankle replacement (TAR) depends on both bone ingrowth and remodelling. The extreme values of implant-bone micromotion hinder bone ingrowth. Whereas, bone resorption due to bone remodelling is triggered by stress shielding. This study aims to investigate the biomechanical performance of three popular tibial designs (STAR, Salto and Mobility) for TAR with different implant-bone interfacial conditions and bone qualities. METHODS: In this study, CT data were used for the geometric modelling of bone. The cancellous bone was considered to be heterogeneous with location-based properties. Total 48 Finite Element (FE) models were prepared i.e., 45 implanted and 3 intact. For the three designs, three bone qualities were considered. For each bone quality, five implant-bone interface coefficients of friction were considered (0.1 to 0.5). The proximal part of the tibia was fully constrained and dorsiflexion loading condition was applied. RESULTS: There was a reduction in micromotion as the coefficient of friction increased and increase in micromotion as the bone quality reduced. The effect of implant-bone coefficient of friction was trivial on tibial stress (von Mises stress) however, bone quality and implant design was considerable. Stress shielding was seen in all the models and it increased when the bone quality degraded. CONCLUSIONS: This study establishes the effect of the implant-bone interfacial condition, bone quality and implant design on implant-bone micromotion and bone stress. For long-term fixation of the tibial component, due attention should be given while selecting the tibial component design for TAR, especially for STAR and Mobility design.

Adsorptive colorimetric determination of chromium(VI) ions at ultratrace levels using amine functionalized mesoporous silica.

There is an urgent need for a rapid, affordable and sensitive analytical method for periodic monitoring of heavy metals in water bodies. Herein, we report for the first time a versatile method for ultratrace level metal detection based on colorimetric sensing. The method integrates preconcentration using a nanomaterial with a colorimetric assay performed directly on the metal-enriched nanomaterial surface. This method circumvents the need for tedious sample pre-processing steps and the complex development of colorimetric probes, thereby reducing the complexity of the analytical procedure. The efficacy of the proposed method was demonstrated for chromium(VI) ions detection in water samples. Amine functionalized mesoporous silica (AMS) obtained from a one-pot synthesis was utilized as a pre-concentration material. The structural and chemical analysis of AMS was conducted to confirm its physico-chemical properties. The pre-concentration conditions were optimized to maximise the colorimetric signal. AMS exhibited a discernible colour change from white to purple (visible to the naked eye) for trace Cr(VI) ions concentration as low as 0.5 µg L-1. This method shows high selectivity for Cr(VI) ions with no colorimetric signal from other metal ions. We believe our method of analysis has a high scope for de-centralized monitoring of organic/inorganic pollutants in resource-constrained settings.

A review on experimental and numerical investigations of cortical bone fracture.

This paper comprehensively reviews the various experimental and numerical techniques, which were considered to determine the fracture characteristics of the cortical bone. This study also provides some recommendations along with the critical review, which would be beneficial for future research of fracture analysis of cortical bone. Cortical bone fractures due to sports activities, climbing, running, and engagement in transport or industrial accidents. Individuals having different diseases are also at high risk of cortical bone fracture. It has been observed that osteon orientation influences cortical bone fracture toughness and fracture mechanisms. Apart from this, recent studies indicate that fracture parameters of cortical bone also depend on many factors such as age, sex, temperature, osteoporosis, orientation, location, loading condition, strain rate, and storage facility, etc. The cortical bone regains its fracture toughness due to various toughening mechanisms. Owing to these factors, several experimental, clinical, and numerical investigations have been carried out to determine the fracture parameters of the cortical bone. Cortical bone is the dense outer surface of the bone and contributes to 80%-82% of the skeleton mass. Cortical bone experiences load far exceeding body weight due to muscle contraction and the dynamics of motion. It is very important to know the fracture pattern, direction of fracture, location of the fracture, and toughening mechanism of cortical bone. A basic understanding of the different factors that affect the fracture parameters and fracture mechanisms of the cortical bone is necessary to prevent the failure and fracture of cortical bone. This review has summarized the advancement considered in the various experimental techniques and numerical methods to get complete information about the fracture mechanisms of cortical bone.

Potential therapeutic use of corticosteroids as SARS CoV-2 main protease inhibitors: a computational study.

The outbreak of COVID-19, caused by severe acute respiratory syndrome coronavirus 2 (SARS CoV-2), represents a pandemic threat to global public health. To date, ∼530,000 people died of this disease worldwide. Presently, researchers/clinicians are adopting the drug repurposing strategy to combat this disease. It has also been observed that some repurposed anti-viral drugs may serve as potent inhibitors of SARS CoV-2 Mpro, a key component of viral replication. Apart from these anti-viral drugs, recently dexamethasone (an important corticosteroid) is effectively used to treat COVID-19 patients. However, the mechanism behind the mode of its action is not so clear. Additionally, the effect of other well-known corticosteroids to control this disease by inhibiting the proteolytic activity of Mpro is ambiguous. In this study, we have adopted computational approaches to understand these aspects. Six well-known corticosteroids (cortisone, hydrocortisone, prednisolone, methylprednisolone, betamethasone and dexamethasone) and two repurposed drugs (darunavir and lopinavir) against COVID-19 were subjected for molecular docking studies. Two of them (betamethasone and dexamethasone) were selected by comparing their binding affinities with selected repurposed drugs toward Mpro. Betamethasone and dexamethasone interacted with both the catalytic residues of Mpro (His41 and Cys145). Molecular dynamics studies further revealed that these two Mpro-corticosteroid complexes are more stable, experience less conformational fluctuations and more compact than Mpro-darunavir/lopinavir complexes. These findings were additionally validated by MM-GBSA analysis. This study provides corroboration for execution of anti-COVID-19 activity of dexamethasone. Our study also emphasizes on the use of another important corticosteroid (betamethasone) as potential therapeutic agent for COVID-19 treatment.