Search results for: Ajoy Roychoudhury
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5

Search results for: Ajoy Roychoudhury

5 Mycophenolate Mofetil Increases Mucin Expression in Primary Cultures of Oral Mucosal Epithelial Cells for Application in Limbal Stem Cell Deficiency

Authors: Sandeep Kumar Agrawal, Aditi Bhattacharya, Janvie Manhas, Krushna Bhatt, Yatin Kholakiya, Nupur Khera, Ajoy Roychoudhury, Sudip Sen

Abstract:

Autologous cultured explants of human oral mucosal epithelial cells (OMEC) are a potential therapeutic modality for limbal stem cell deficiency (LSCD). Injury or inflammation of the ocular surface in the form of burns, chemicals, Stevens Johnson syndrome, ocular cicatricial pemphigoid etc. can lead to destruction and deficiency of limbal stem cells. LSCD manifests in the form of severe ocular surface diseases (OSD) characterized by persistent and recurrent epithelial defects, conjuntivalisation and neovascularisation of the corneal surface, scarring and ultimately opacity and blindness. Most of the cases of OSD are associated with severe dry eye pertaining to diminished mucin and aqueous secretion. Mycophenolate mofetil (MMF) has been shown to upregulate the mucin expression in conjunctival goblet cells in vitro. The aim of this study was to evaluate the effects of MMF on mucin expression in primary cultures of oral mucosal epithelial cells. With institutional ethics committee approval and written informed consent, thirty oral mucosal epithelial tissue samples were obtained from patients undergoing oral surgery for non-malignant conditions. OMEC were grown on human amniotic membrane (HAM, obtained from expecting mothers undergoing elective caesarean section) scaffold for 2 weeks in growth media containing DMEM & Ham’s F12 (1:1) with 10% FBS and growth factors. In vitro dosage of MMF was standardised by MTT assay. Analysis of stem cell markers was done using RT-PCR while mucin mRNA expression was quantified using RT-PCR and q-PCR before and after treating cultured OMEC with graded concentrations of MMF for 24 hours. Protein expression was validated using immunocytochemistry. Morphological studies revealed a confluent sheet of proliferating, stratified oral mucosal epithelial cells growing over the surface of HAM scaffold. The presence of progenitor stem cell markers (p63, p75, β1-Integrin and ABCG2) and cell surface associated mucins (MUC1, MUC15 and MUC16) were elucidated by RT-PCR. The mucin mRNA expression was found to be upregulated in MMF treated primary cultures of OMEC, compared to untreated controls as quantified by q-PCR with β-actin as internal reference gene. Increased MUC1 protein expression was validated by immunocytochemistry on representative samples. Our findings conclude that OMEC have the ability to form a multi-layered confluent sheet on the surface of HAM similar to a cornea, which is important for the reconstruction of the damaged ocular surface. Cultured OMEC has stem cell properties as demonstrated by stem cell markers. MMF can be a novel enhancer of mucin production in OMEC. It has the potential to improve dry eye in patients undergoing OMEC transplantation for bilateral OSD. Further clinical trials are required to establish the role of MMF in patients undergoing OMEC transplantation.

Keywords: limbal stem cell deficiency, mycophenolate mofetil, mucin, ocular surface disease

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4 A Machine Learning Based Method to Detect System Failure in Resource Constrained Environment

Authors: Payel Datta, Abhishek Das, Abhishek Roychoudhury, Dhiman Chattopadhyay, Tanushyam Chattopadhyay

Abstract:

Machine learning (ML) and deep learning (DL) is most predominantly used in image/video processing, natural language processing (NLP), audio and speech recognition but not that much used in system performance evaluation. In this paper, authors are going to describe the architecture of an abstraction layer constructed using ML/DL to detect the system failure. This proposed system is used to detect the system failure by evaluating the performance metrics of an IoT service deployment under constrained infrastructure environment. This system has been tested on the manually annotated data set containing different metrics of the system, like number of threads, throughput, average response time, CPU usage, memory usage, network input/output captured in different hardware environments like edge (atom based gateway) and cloud (AWS EC2). The main challenge of developing such system is that the accuracy of classification should be 100% as the error in the system has an impact on the degradation of the service performance and thus consequently affect the reliability and high availability which is mandatory for an IoT system. Proposed ML/DL classifiers work with 100% accuracy for the data set of nearly 4,000 samples captured within the organization.

Keywords: machine learning, system performance, performance metrics, IoT, edge

Procedia PDF Downloads 163
3 Prediction of Unsteady Heat Transfer over Square Cylinder in the Presence of Nanofluid by Using ANN

Authors: Ajoy Kumar Das, Prasenjit Dey

Abstract:

Heat transfer due to forced convection of copper water based nanofluid has been predicted by Artificial Neural network (ANN). The present nanofluid is formed by mixing copper nano particles in water and the volume fractions are considered here are 0% to 15% and the Reynolds number are kept constant at 100. The back propagation algorithm is used to train the network. The present ANN is trained by the input and output data which has been obtained from the numerical simulation, performed in finite volume based Computational Fluid Dynamics (CFD) commercial software Ansys Fluent. The numerical simulation based results are compared with the back propagation based ANN results. It is found that the forced convection heat transfer of water based nanofluid can be predicted correctly by ANN. It is also observed that the back propagation ANN can predict the heat transfer characteristics of nanofluid very quickly compared to standard CFD method.

Keywords: forced convection, square cylinder, nanofluid, neural network

Procedia PDF Downloads 294
2 Person-Led Organizations Nurture Bullying Behavior: A Qualitative Study

Authors: Shreya Mishra, Manosi Chaudhuri, Ajoy K. Dey

Abstract:

Workplace bullying is a social phenomenon which has proved to be hazardous not only for employees’ well-being but also organizations. Despite being prevalent across geographical boundaries, Indian organizations have failed to acknowledge its vices. This paper aims to understand targets’ perception on what makes bullying nurture in organizations. The paper suggests that person-led Indian work settings give birth to bullying behavior as it lacks professional acumen and systems. An analysis of 13 in-depth interviews of employees from the organized sector suggests that organizations, where decision making lies with single individual, may be a hub of hostile behavior due to the culture which promotes ‘yesmanship’, ‘authoritarianism’ and/or blind belief of leaders on certain set of employees. The study used constructivist grounded theory approach, and the data was analyzed using R Based Qualitative Data Analysis (RQDA) software. Respondents reported that bullying behavior is taken lightly by the management with 'just ignore it' attitude. According to the respondents, the behavior prolong as the perpetrator have a direct approach to the top authority. The study concludes that person-led organizations may create a family-like environment which is favored by employees; however, authoritative leaders are unable to gain the trust of employees. Also, employees who are close to the leader may either be a perpetrator or a target of bullying. It is recommended that leaders in such organizations need to acknowledge the presence of bullying which affects an employees’ commitment towards their job and/or organization. They need to have an assertive check on individuals who hide behind ‘yesman’ attitude. This may help employees feel safe in such work settings.

Keywords: constructivist grounded theory, person-led organization, RQDA, workplace bullying

Procedia PDF Downloads 173
1 Green Synthesis of Silver and Silver-Gold Alloy Nanoparticle Using Cyanobacteria as Bioreagent

Authors: Piya Roychoudhury, Ruma Pal

Abstract:

Cyanobacteria, commonly known as blue green algae were found to be an effective bioreagent for nanoparticle synthesis. Nowadays silver nanoparticles (AgNPs) are very popular due to their antimicrobial and anti-proliferative activity. To exploit these characters in different biotechnological fields, it is very essential to synthesize more stable, non-toxic nano-silver. For this reason silver-gold alloy (Ag-AuNPs) nanoparticles are of great interest as they are more stable, harder and more effective than single metal nanoparticles. In the present communication we described a simple technique for rapid synthesis of biocompatible AgNP and Ag-AuNP employing cyanobacteria, Leptolyngbya and Lyngbya respectively. For synthesis of AgNP the biomass of Leptolyngbya valderiana (200 mg Fresh weight) was exposed to 9 mM AgNO3 solution (pH 4). For synthesis of Ag-AuNP Lyngbya majuscula (200 mg Fresh weight) was exposed to equimolar solution of hydrogen tetra-auro chlorate and silver nitrate (1mM, pH 4). After 72 hrs of exposure thallus of Leptolyngyba turned brown in color and filaments of Lyngbya turned pink in color that indicated synthesis of nanoparticles. The produced particles were extracted from the cyanobacterial biomass using nano-capping agent, sodium citrate. Firstly, extracted brown and pink suspensions were taken for Energy Dispersive X-ray (EDAX) analysis to confirm the presence of silver in brown suspension and presence of both gold and silver in pink suspension. Extracted nanoparticles showed a distinct single plasmon band (AgNP at 411 nm; Ag-Au NP at 481 nm) in Uv-vis spectroscopy. It was revealed from Transmission electron microscopy (TEM) that all the synthesized particles were spherical in nature with a size range of ~2-25 nm. In X-ray powder diffraction (XRD) analysis four intense peaks appeared at 38.2°, 44.5°, 64.8°and 77.8° which confirmed the crystallographic nature of synthesized particles. Presence of different functional groups viz. N-H, C=C, C–O, C=O on the surface of nanoparticles were recorded by Fourier transform infrared spectroscopy (FTIR). Scanning Electron microscopy (SEM) images showed the surface topography of metal treated filaments of cyanobacteria. The stability of the particles was observed by Zeta potential study. Antibiotic property of synthesized particles was tested by Agar well diffusion method against gram negative bacteria Pseudomonas aeruginosa. Overall, this green-technique requires low energy, less manufacturing cost and produces rapidly eco-friendly metal nanoparticles.

Keywords: cyanobacteria, silver nanoparticles, silver-gold alloy nanoparticles, spectroscopy

Procedia PDF Downloads 285