Numerical analysis of scaffold degradation in cryogenic environment: impact of cell migration and cell apoptosis.

The analysis of degradation in the presence of cell death and migration is a critical aspect of research in various biological fields, such as tissue engineering, regenerative medicine, and disease pathology. In present study, numerical study of degradation of scaffold were performed in present of cells, cell apoptosis and cell migration. A poly electrolyte complex (PEC) silk fibroin scaffold was used for degradation study. Degradation study in the presence of cells and migration were performed at fixed pH concentration 7.2. Similarly, degradation study of scaffold were performed at different pH cell apoptosis. A transient analysis of scaffold was evaluated in COMSOL 5.5 in presence of cryogenic temperature at different temperature gradient. The parameters; temperature, stress, strain tensor and deformation gradient associated with the degradation of polyelectrolyte complex scaffold were evaluated. Result shows that in both geometries minimum temperature had been achieved as 230.051 K at point P4 in series view and parallel view and at a point P3 for cell migration study for -5 k min-1and -1 k min-1, respectively. The maximum stress had been generated for 5.57 × 107N m-2for the temperature gradient of -2 K min-1at T cycle in the case of cell migration study. In contrast in series view the maximum stress 2.9 × 107 N m-2were observed at P4 which was higher as compare to P3. Similarly, for a parallel view, maximum stress (3.93 × 107 N m-2) was obtained for point P3. It had been observed that the maximum strain tensor 5.21 × 10-3, 5.15 × 10-3and 5.26 × 10-3was generated in series view at 230 k on a point P3 for - 1, -2 and -5 K min-1, respectively. Similarly, the maximum strain tensor 8.16 × 10-3, 8.09 × 10-3and 8.09 × 10-3was generated in parallel view at 230 k on a point P3 for -1, -2 and -5 K min-1, respectively. In the presence of cells, at a point P4 for temperature gradient of -1 and -2 K min-1, it had been closed to the scaffold wall, which had a different temperature profile than the point P3 and scaffold comes to the contact with the cells. The analysis of PEC scaffold degradation in the presence of cells, including cell apoptosis and migration, offers significant insights into the relationship between scaffold properties, cell behaviour, and tissue regeneration.

Hybrid computational model depicts the contribution of non-significant lobes of human brain during the perception of emotional stimuli.

Emotions are synchronizing responses of human brain while executing cognitive tasks. Earlier studies had revealed strong correlation between specific lobes of the brain to different types of emotional valence. In the current study, a comprehensive three-dimensional mapping of human brain for executing emotion specific tasks had been formulated. A hybrid computational machine learning model customized from Custom Weight Allocation Model (CWAM) and defined as Custom Rank Allocation Model (CRAM). This regression-based hybrid computational model computes the allocated tasks to different lobes of the brain during their respective executive stage. Event Related Potentials (ERP) were obtained with significant effect at P1, P2, P3, N170, N2, and N4. These ERPs were configured at Pz, Cz, F3, and T8 regions of the brain with maximal responses; while regions like Cz, C4 and F4 were also found to make effective contributions to elevate the responses of the brain, and thus these regions were configured as augmented source regions of the brain. In another circumstance of frequent -deviant - equal (FDE) presentation of the emotional stimuli, it was observed that the brain channels C3, C4, P3, P4, O1, O2, and Oz were contributing their emotional quotient to the overall response of the brain regions; whereas, the interaction effect was found presentable at O2, Oz, P3, P4, T8 and C3 regions of brain. The proposed computational model had identified the potential neural pathways during the execution of emotional task.

Investigation of frequency components embedded in EEG recordings underlying neuronal mechanism of cognitive control and attentional functions.

Attentional cognitive control regulates the perception to enhance human behaviour. The current study examines the atltentional mechanisms in terms of time and frequency of EEG signals. The cognitive load is higher for processing local attentional stimulus, thereby demanding higher response time (RT) with low response accuracy (RA). On the other hand, the global attentional mechanisms broadly promote the perception while demanding a low cognitive load with faster RT and high RA. Attentional mechanisms refer to perceptual systems that afford and allocate the adaptive behaviours for prioritizing the processing of relevant stimuli based on the local and global features. The early sensory component of C1, which was associated with the local attentional mechanism, showed higher amplitudes than the global attentional mechanisms in parieto-occipital regions. Further, the local attentional mechanisms were also sustained in N2 and P3 components increasing higher amplitude in the left and right hemispheric sides of temporal regions (T7 and T8). Theta band frequency had shown higher power spectrum density (PSD) values while processing local attentional mechanisms. However, the significance of other frequency bands was noticeably minute. Hence, integrating the attentional mechanisms in terms of ERP and frequency signatures, a hybrid custom weight allocation model (CWAM) was built to assess and predict the contribution of insignificant channels to significant ones. The CWAM model was formulated based on the computational linear regression derivatives. All the derivatives are computationally derived the significant score while channelizing the hierarchical performance of each channel with respect to the frequent and deviant occurrences of global-local stimulus. This model enables us to configure the neural dynamicity of cognitive allocation of resources within the different locations of the human brain while processing the attentional stimulus. CWAM is reported to be the first model to evaluate the performance of the non-significant channels for enhancing the response of significant channels. The findings of the CWAM model suggest that the brain's performance may be determined by the underlying contribution of the non-significant channels. Supplementary Information: The online version contains supplementary material available at 10.1007/s11571-022-09888-x.

Influence of Non-Newtonian Viscosity on Flow Structures and Wall Deformation in Compliant Serpentine Microchannels: A Numerical Study.

The viscosity of fluid plays a major role in the flow dynamics of microchannels. Viscous drag and shear forces are the primary tractions for microfluidic fluid flow. Capillary blood vessels with a few microns diameter are impacted by the rheology of blood flowing through their conduits. Hence, regenerated capillaries should be able to withstand such impacts. Consequently, there is a need to understand the flow physics of culture media through the lumen of the substrate as it is one of the vital promoting factors for vasculogenesis under optimal shear conditions at the endothelial lining of the regenerated vessel. Simultaneously, considering the diffusive role of capillaries for ion exchange with the surrounding tissue, capillaries have been found to reorient themselves in serpentine form for modulating the flow conditions while developing sustainable shear stress. In the current study, S-shaped (S1) and delta-shaped (S2) serpentine models of capillaries were considered to evaluate the shear stress distribution and the oscillatory shear index (OSI) and relative residual time (RRT) of the derivatives throughout the channel (due to the phenomena of near-wall stress fluctuation), along with the influence of culture media rheology on wall stress parameters. The non-Newtonian power-law formulation was implemented for defining rheological viscosity of the culture media. The flow actuation of the media was considered to be sinusoidal and physiological, realizing the pulsatile blood flow behavior in the circulatory network. A distinct difference in shear stress distributions was observed in both the serpentine models. The S1 model showed higher change in shear stress in comparison to the S2 model. Furthermore, the non-Newtonian viscosity formulation was found to produce more sustainable shear stress near the serpentine walls compared to the Newtonian formulation fluid, emphasizing the influence of rheology on stress generation. Further, cell viability improved in the bending regions of serpentine channels compared to the long run section of the same channel.

Processing of attentional and emotional stimuli depends on retrospective response of foot pressure: Conceptualizing neuron-cognitive distribution in human brain.

Cognitive function of human brain requires temporal execution of emotional or attentional tasks, or their inter-dependence influences. Smooth execution of such tasks requires spontaneous distribution of cognitive load at specific regions of brain based on its classification. A strong connectivity between peripheral sensors and central nervous system is thought to assist the cognitive load distribution effectively. Novelty of current study evaluates the modulation of foot pressure and its mapping with distributed cognitive load while executing attentional biased emotional tasks. Emotional stimulus in form of happy and sad faces with attentional paradigm drawn on them were used in the study. Behavioral results were measured with respect to the analysis of response time (RT) and response accuracy (%). Neurological signals were acquired using 10-channel EEG data acquisition system, whereas, another 6 channels were used to measure foot pressure in the left and right feet at three different locations of foot. Acquired signals were further analyzed in time and frequency domains to interpret the cognitive load distribution, and the influence of foot pressure on distribution of cognitive loads. We found that the foot pressure accelerated the response accuracy rate in attending the local scope of attention, which was not in the case of global scope of attention. This means that the global attention does not require any pressure from peripheral sensory neurons. Our event related potential (ERP) results revealed that the early sensory negative N100 characterized the processing of global scope of attention coupled with high-foot pressure. However, the late positive peak of P300 and P600 associated with local scope of attention along with high-foot pressure. The global scope of attention with low-foot pressure modulates delta and theta oscillations. These results largely contribute to the literature on cognitive neuroscience of attention and it corelation with the peripheral sensory foot pressure.

Evaluation of heat transfer in porous scaffolds under cryogenic treatment: a numerical study.

The present work had evaluated the effect of cryogenic treatment (233 K) on the degradation of polymeric biomaterial using a numerical model. The study on effect of cryogenic temperature on mechanical properties of cell-seeded biomaterials is very limited. However, no study had reported material degradation evaluation. Different structures of silk-fibroin-poly-electrolyte complex (SFPEC) scaffolds had been designed by varying hole distance and hole diameter, with reference to existing literature. The size of scaffolds were maintained at 5 [Formula: see text] 5 mm2. Current study evaluates the effect of cryogenic temperature on mechanical properties (corelated to degradation) of scaffold. Six parameters related to scaffold degradation: heat transfer, deformation gradient, stress, strain, strain tensor, and displacement gradient were analyzed for three different cooling rates (- 5 K/min, - 2 K/min, and - 1 K/min). Scaffold degradation had been evaluated in the presence of water and four different concentrations of cryoprotectant solution. Heat distribution at various points (points_base, point_wall and point_core) on the region of interest (ROI) was found similar for different cooling rates of the system. Thermal stress was found developing proportional to cooling rate, which leads to minimal variation in thermal stress over time. Strain tensor was found gradually decreasing due to attenuating response of deformation gradient. In addition to that, dipping down of cryogenic temperature had prohibited the movement of molecules in the crystalline structure which had restricting the displacement gradient. It was found that uniform distribution of desired heat at different cooling rates has the ability to minimize the responses of other scaffold degradation parameters. It was found that the rates of change in stress, strain, and strain tensor were minimal at different concentrations of cryoprotectant. The present study had predicted the degradation behavior of PEC scaffold under cryogenic temperature on the basis of explicit mechanical properties.

Numerical and Experimental Analysis of Shear Stress Influence on Cellular Viability in Serpentine Vascular Channels.

3D bioprinting has emerged as a tool for developing in vitro tissue models for studying disease progression and drug development. The objective of the current study was to evaluate the influence of flow driven shear stress on the viability of cultured cells inside the luminal wall of a serpentine network. Fluid-structure interaction was modeled using COMSOL Multiphysics for representing the elasticity of the serpentine wall. Experimental analysis of the serpentine model was performed on the basis of a desirable inlet flow boundary condition for which the most homogeneously distributed wall shear stress had been obtained from numerical study. A blend of Gelatin-methacryloyl (GelMA) and PEGDA200 PhotoInk was used as a bioink for printing the serpentine network, while facilitating cell growth within the pores of the gelatin substrate. Human umbilical vein endothelial cells were seeded into the channels of the network to simulate the blood vessels. A Live-Dead assay was performed over a period of 14 days to observe the cellular viability in the printed vascular channels. It was observed that cell viability increases when the seeded cells were exposed to the evenly distributed shear stresses at an input flow rate of 4.62 mm/min of the culture media, similar to that predicted in the numerical model with the same inlet boundary condition. It leads to recruitment of a large number of focal adhesion point nodes on cellular membrane, emphasizing the influence of such phenomena on promoting cellular morphologies.

Metallic ion-based graphene oxide functionalized silk fibroin-based dressing promotes wound healing via improved bactericidal outcomes and faster re-epithelization.

An ideal wound dressing material should enhance the wound healing process and must avoid bacterial contamination. In this study, the synergistic effect of graphene oxide (GO), silver (Ag) and magnesium (Mg) based silk electrospun nanofibrous film on wound healing was evaluated. It reports the influence of essential elements Mg and Ag during the skin regeneration process. Silver and magnesium nanoparticles were doped in graphene oxide. The goal of the present study was to fabricate an electrospun nanofibrous patch with nanoscale fillers to improve the wound recuperation manner and decrease the recuperation time to forestall microorganism infections and improve cellular behavior. Doping was done to insert Ag+and Mg2+ions in the crystal lattice of GO to overcome the disadvantage of aggregation of Ag and Mg nanoparticles. In this study, Mg2+and Ag+ions doped GO functionalized silk fibroin/PVA dressing material was prepared using the electrospinning technique. It was found that, Mg-GO@NSF/PVA and Ag/Mg-GO@NSF/PVA film possess good cytocompatibility, low hemolytic effect and effective antibacterial and anti-biofilm activities. Furthermore, their improved hydrophilicity and mid-range water vapor transmission rate allow them to be a suitable wound dressing material. Tensile strength of the composite silk film were enhanced relatively to silk/PVA film. The effect of prepared film on wound repair were investigated in excision rat model. It indicates, the wound covered with Ag/Mg-GO@NSF/PVA film showed the highest wound contraction rate and re-epithelization, allowing faster repair of wound sites. In conclusion, the development of metallic ions doped GO based silk fibroin/PVA is a promising approach towards development of antibiotic free wound dressing material. It prevents anti-biofilm formation and also provides adequate therapeutic effects for accelerating wound healing.

Fibroblast Derived Skin Wound Healing Modeling on Chip under the Influence of Micro-Capillary Shear Stress.

Fibroblast cell migration plays a crucial role in the wound-healing process. Hence, its quantitative investigation is important to understand the mechanism of the wound-healing process. The dynamic nature of the wound-healing process can be easily implemented using a microfluidic-based wound-healing assay. This work presented the use of a microfluidics device to simulate traumatic wounds on fibroblast cell monolayers by utilizing trypsin flow and PDMS barrier. In this study, a microfluidic chip with a transparent silk film is reported. The placement of film provides 3D cell culture conditions that mimic a 3D extracellular matrix (ECM) like environment and allows real-time monitoring of cells. A numerical study was conducted to evaluate the influence of dynamic medium-induced shear stress on the base and wall of the microchannel. This could facilitate the optimization of the inlet flow conditions of the media in the channel. At the same time, it could help in identifying stress spots in the channel. The scaffolds were placed in those spots for evaluating the influence of shear forces on the migratory behavior of fibroblast cells. The in vitro microfluidic assembly was then evaluated for cell migration under the influence of external shear forces during the wound-healing phenomena. A faster wound healing was obtained at the end of 24 h of the creation of the wound in the presence of optimal shear stress. On increasing the shear stress beyond a threshold limit, it dissociates fibroblast cells from the surface of the substrate, thereby decelerating the wound-healing process. The above phenomena were transformed in both coplanar microfluidics surfaces (by realizing in the multichannel interlinked model) and transitional microfluidics channels (by realizing in the sandwich model).

Neurocognitive functions of prosocial and unsocial incongruency information during language comprehension: evidence from time-frequency analysis of EEG signals.

This study examined neurocognitive mechanisms of prosocial and antisocial congruency in English sentences by conducting an electroencephalography experiment. Participants performed a judgment task whether prosocial and unsocial/antisocial nominal words were congruent or incongruent with the upcoming prosocial and antisocial verbal category of words in sentences (e.g., he established a friendship with others because he wanted to terrorize people). We found that the antisocial sentences were processed in the early P1, whereas prosocial sentences were processed in late P3. The negative deflection of N400 was higher for incongruent than congruent trials in the temporal regions of the brain. Further, the early suppression of antisocial sentences increased the brain oscillation of delta, theta, and beta-band activities in the temporal and frontal regions of the brain. The power spectrum density (PSD) of theta-band frequency was higher for incongruent than congruent trials in the parietal regions of the brain. These results suggest that the antisocial content of language is recognized very rapidly, and the time-course of processing underlies the congruent and incongruent sentences between prosocial and unsocial words in sentences. The current investigation contributes to the recognition of neural signatures of prosocial language that plays a significant role in developing the survival strategies, interpersonal communications, and wellbeing of humans.

From 3D printing to 3D bioprinting: the material properties of polymeric material and its derived bioink for achieving tissue specific architectures.

The application of 3D printing technologies fields for biological tissues, organs, and cells in the context of medical and biotechnology applications requires a significant amount of innovation in a narrow printability range. 3D bioprinting is one such way of addressing critical design challenges in tissue engineering. In a more general sense, 3D printing has become essential in customized implant designing, faithful reproduction of microenvironmental niches, sustainable development of implants, in the capacity to address issues of effective cellular integration, and long-term stability of the cellular constructs in tissue engineering. This review covers various aspects of 3D bioprinting, describes the current state-of-the-art solutions for all aforementioned critical issues, and includes various illustrative representations of technologies supporting the development of phases of 3D bioprinting. It also demonstrates several bio-inks and their properties crucial for being used for 3D printing applications. The review focus on bringing together different examples and current trends in tissue engineering applications, including bone, cartilage, muscles, neuron, skin, esophagus, trachea, tympanic membrane, cornea, blood vessel, immune system, and tumor models utilizing 3D printing technology and to provide an outlook of the future potentials and barriers.

3D bioprinting in tissue engineering and regenerative medicine.

This review paper is primarily focused on bioprinting technology for biomedical applications. Bioprinting can be utilized for fabrication of wide range of tissue, based on which this chapter describes in detail its application in tissue regeneration. Further, the difficulties and potential in developing a construct for tissue regeneration are discussed herein. In this review paper, application of 3D bioprinting in tissue regeneration will be discussed in depth.

Six artificial intelligence paradigms for tissue characterisation and classification of non-COVID-19 pneumonia against COVID-19 pneumonia in computed tomography lungs.

BACKGROUND: COVID-19 pandemic has currently no vaccines. Thus, the only feasible solution for prevention relies on the detection of COVID-19-positive cases through quick and accurate testing. Since artificial intelligence (AI) offers the powerful mechanism to automatically extract the tissue features and characterise the disease, we therefore hypothesise that AI-based strategies can provide quick detection and classification, especially for radiological computed tomography (CT) lung scans. METHODOLOGY: Six models, two traditional machine learning (ML)-based (k-NN and RF), two transfer learning (TL)-based (VGG19 and InceptionV3), and the last two were our custom-designed deep learning (DL) models (CNN and iCNN), were developed for classification between COVID pneumonia (CoP) and non-COVID pneumonia (NCoP). K10 cross-validation (90% training: 10% testing) protocol on an Italian cohort of 100 CoP and 30 NCoP patients was used for performance evaluation and bispectrum analysis for CT lung characterisation. RESULTS: Using K10 protocol, our results showed the accuracy in the order of DL > TL > ML, ranging the six accuracies for k-NN, RF, VGG19, IV3, CNN, iCNN as 74.58 ± 2.44%, 96.84 ± 2.6, 94.84 ± 2.85%, 99.53 ± 0.75%, 99.53 ± 1.05%, and 99.69 ± 0.66%, respectively. The corresponding AUCs were 0.74, 0.94, 0.96, 0.99, 0.99, and 0.99 (p-values < 0.0001), respectively. Our Bispectrum-based characterisation system suggested CoP can be separated against NCoP using AI models. COVID risk severity stratification also showed a high correlation of 0.7270 (p < 0.0001) with clinical scores such as ground-glass opacities (GGO), further validating our AI models. CONCLUSIONS: We prove our hypothesis by demonstrating that all the six AI models successfully classified CoP against NCoP due to the strong presence of contrasting features such as ground-glass opacities (GGO), consolidations, and pleural effusion in CoP patients. Further, our online system takes < 2 s for inference.

A narrative review on characterization of acute respiratory distress syndrome in COVID-19-infected lungs using artificial intelligence.

COVID-19 has infected 77.4 million people worldwide and has caused 1.7 million fatalities as of December 21, 2020. The primary cause of death due to COVID-19 is Acute Respiratory Distress Syndrome (ARDS). According to the World Health Organization (WHO), people who are at least 60 years old or have comorbidities that have primarily been targeted are at the highest risk from SARS-CoV-2. Medical imaging provides a non-invasive, touch-free, and relatively safer alternative tool for diagnosis during the current ongoing pandemic. Artificial intelligence (AI) scientists are developing several intelligent computer-aided diagnosis (CAD) tools in multiple imaging modalities, i.e., lung computed tomography (CT), chest X-rays, and lung ultrasounds. These AI tools assist the pulmonary and critical care clinicians through (a) faster detection of the presence of a virus, (b) classifying pneumonia types, and (c) measuring the severity of viral damage in COVID-19-infected patients. Thus, it is of the utmost importance to fully understand the requirements of for a fast and successful, and timely lung scans analysis. This narrative review first presents the pathological layout of the lungs in the COVID-19 scenario, followed by understanding and then explains the comorbid statistical distributions in the ARDS framework. The novelty of this review is the approach to classifying the AI models as per the by school of thought (SoTs), exhibiting based on segregation of techniques and their characteristics. The study also discusses the identification of AI models and its extension from non-ARDS lungs (pre-COVID-19) to ARDS lungs (post-COVID-19). Furthermore, it also presents AI workflow considerations of for medical imaging modalities in the COVID-19 framework. Finally, clinical AI design considerations will be discussed. We conclude that the design of the current existing AI models can be improved by considering comorbidity as an independent factor. Furthermore, ARDS post-processing clinical systems must involve include (i) the clinical validation and verification of AI-models, (ii) reliability and stability criteria, and (iii) easily adaptable, and (iv) generalization assessments of AI systems for their use in pulmonary, critical care, and radiological settings.

Bone regeneration in rat using polycaprolactone/gelatin/epinephrine scaffold.

Solid supports like the extracellular matrix network are necessary for bone cell attachment and start healing in the damaged bone. Scaffolds which are made of different materials are widely used as a supportive structure in bone tissue engineering. In the current study, a 3D polycaprolactone/gelatin bone scaffold was developed by blending electrospinning and freeze-drying techniques for bone tissue engineering. To improve the efficiency of the scaffold, different concentrations of epinephrine (EP) due to its effect on bone healing were loaded. Fabricated scaffolds were characterized by different tests such as surface morphology, FTIR, porosity, compressive strength, water contact angle, and degradation rate. The interaction between prepared scaffolds and blood and cells was evaluated by hemolysis, and MTT test, respectively, and bone healing was evaluated by a rat calvaria defect model. Based on the results, the porosity of scaffolds was about 75% and by adding EP, mechanical strength decreased while due to the hydrophilic properties of it, degradation rate increased. In vivo and in vitro studies showed the best cell proliferation and bone healing were in PCL/gelatin/EP1% treated group. These results showed the positive effect of fabricated scaffold on osteogenesis and bone healing and the possibility of using it in clinical trials.

Evaluation of silk-based bioink during pre and post 3D bioprinting: A review.

During past few decades, the demand for the replacement of damaged organs is increasing consistently. This is due to the advancement in tissue engineering, which opens the possibility of regeneration of damaged organs or tissues into functional parts with the help of 3D bioprinting. Bioprinting technology presents an excellent potential to develop complex structures with precise control over cell suspension and structure. A brief description of different types of 3D bioprinting techniques, including inkjet-based, laser-based, and extrusion-based bioprinting is presented here. Due to innate advantageous features like tunable biodegradability, biocompatibility, elasticity and mechanical robustness, silk has carved a niche in the realm of tissue engineering. In this review article, the focus is to highlight the possible approach of exploring silk as bioink for fabrication of bioprinted implants using 3D bioprinting. This review discusses different type of degumming, dissolution techniques for extraction of proteins from different sources of silk. Different recently reported 3D bioprinting techniques suitable for silk-based bioink are further elaborated. Postprinting characterization of resultant scaffolds are also describe here. However, there is an astounding progress in 3D bioprinting technology, still there is a need to develop further the current bioprinting technology to make it suitable for generation of heterogeneous tissue construct. The possibility of utilizing the adhesive property of sericin to consider it as bioink is elaborated.

A tailored polylactic acid/polycaprolactone biodegradable and bioactive 3D porous scaffold containing gelatin nanofibers and Taurine for bone regeneration.

The focus of the current study was to develop a functional and bioactive scaffold through the combination of 3D polylactic acid (PLA)/polycaprolactone (PCL) with gelatin nanofibers (GNFs) and Taurine (Tau) for bone defect regeneration. GNFs were fabricated via electrospinning dispersed in PLA/PCL polymer solution, Tau with different concentrations was added, and the polymer solution converted into a 3D and porous scaffold via the thermally-induced phase separation technique. The characterization results showed that the scaffolds have interconnected pores with the porosity of up to 90%. Moreover, Tau increased the wettability and weight loss rate, while compromised the compressive strengths. The scaffolds were hemo- and cytocompatible and supported cell viability and proliferation. The in vivo studies showed that the defects treated with scaffolds filled with new bone. The computed tomography (CT) imaging and histopathological observation revealed that the PLA/PCL/Gel/Tau 10% provided the highest new bone formation, angiogenesis, and woven bone among the treatment groups. Our finding illustrated that the fabricated scaffold was able to regenerate bone within the defect and can be considered as the effective scaffold for bone tissue engineering application.

Prediction of stenosis behaviour in artery by neural network and multiple linear regressions.

Blood flow analysis in the artery is a paramount study in the field of arterial stenosis evaluation. Studies conducted so far have reported the analysis of blood flow parameters using different techniques, but the regression analysis is not adequately used. Artificial neural network is a nonlinear and nonparametric approach. It uses back-propagation algorithm for regression analysis, which is effective as compared to statistical model that requires a higher domain of statistics for prediction. In our manuscript, twofold analyses of data are done. First phase involves the determination of blood flow parameters using physiological flow pulse generator. The second phase includes regression modelling. The inputs to the model were axial length from stenosis, radial distance, inlet velocity, mean pressure, density, viscosity, time, and degree of blockage. Output included dependent variables in the form of output as mean velocity, root-mean-square (RMS) velocity, turbulent intensity, mean frequency, RMS frequency, frequency of turbulent intensity, gate time mean, gate time RMS. The temperature, density, and viscosity conditions were kept constant for various degrees of blockages. It was followed by regression analysis of variables using conventional statistical and neural network approach. The result shows that the neural network model is more appropriate, because value of percentage of response variation of dependent variable is almost approaching unity as compared to statistical analysis.

Integration of cardiovascular risk assessment with COVID-19 using artificial intelligence.

Artificial Intelligence (AI), in general, refers to the machines (or computers) that mimic "cognitive" functions that we associate with our mind, such as "learning" and "solving problem". New biomarkers derived from medical imaging are being discovered and are then fused with non-imaging biomarkers (such as office, laboratory, physiological, genetic, epidemiological, and clinical-based biomarkers) in a big data framework, to develop AI systems. These systems can support risk prediction and monitoring. This perspective narrative shows the powerful methods of AI for tracking cardiovascular risks. We conclude that AI could potentially become an integral part of the COVID-19 disease management system. Countries, large and small, should join hands with the WHO in building biobanks for scientists around the world to build AI-based platforms for tracking the cardiovascular risk assessment during COVID-19 times and long-term follow-up of the survivors.