Department of Biomedical Engineering

Indian Institute of Technology Hyderabad (IITH) is a premier institute of science and technology established in 2008. IITH has been consistently ranked in the&nbsp;<a href="https://iith.ac.in/reports/" rel="noopener noreferrer">top 10 institutes</a>&nbsp;in India for Engineering&nbsp;<a href="https://www.nirfindia.org/2021/EngineeringRanking.html" rel="noopener noreferrer" target="_blank">according to NIRF</a>&nbsp;making it one of the most coveted schools for science and technology in the country.

IITH offers&nbsp;<a href="https://iith.ac.in/academics/under-graduate/">undergraduate programs</a>&nbsp;in all the classical engineering disciplines, applied sciences, design, as well as several modern interdisciplinary areas. Students are given a flexibility to explore a broad set of areas, and potentially pursue a minor or double major in a discipline that is not their own. Students who wish to seek a deeper understanding of their own discipline are strongly encouraged to get involved in cutting-edge research with the help of a faculty to mentor them, and earn an Honors in their own field.

The very foundation of IIT Hyderabad is based on&nbsp;<a href="https://iith.ac.in/research/">research and innovation</a>. The vibrant research culture is evident from the number of patents and publications that IITH produces consistently every year. IITH offers&nbsp;<a href="https://iith.ac.in/academics/programmes-offered/">graduate programs</a>&nbsp;at both a masters, and a doctoral level, in several diverse areas. There are separate programs for technology, design, science, and liberal arts. The&nbsp;<a href="https://iith.ac.in/academics/post-graduate/">MTech program</a>&nbsp;is offered in various modes and durations to cater to the ever-growing need of postgraduate level professionals in the country.

IITH encourages and supports&nbsp;<a href="https://iic-iith.netlify.app/index.html" rel="noopener noreferrer" target="_blank">innovation and entrepreneurship</a>&nbsp;at every stage. The minor program in entrepreneurship is open to all students of IITH, and many of the courses are offered by industrialists who are entrepreneurs themselves. There are various&nbsp;<a href="https://iith.ac.in/research/centres-incubators/">innovation centers and incubators</a>&nbsp;that promote entrepreneurship and help mentor young innovators. IITH has been very successful in building tie-ups with leading academic institutions around the globe.

IITH enjoys a very special relationship with Japanese universities and industries that goes beyond academic and research collaborations. In fact, some of the iconic buildings in IITH campus will carry the signature of Japanese architecture.

IITH creates a unique holistic ecosystem for education that offers interactive learning, a very flexible academic structure, cutting-edge research, strong industry collaboration, and entrepreneurship. This is an environment which enables students and faculty to translate their dreams into realities.

IIT Hyderabad

Abstract: Nanohybrids using biocompatible and biodegradable materials are explored for their photothermal mediated theranostic applications. These hybrids are so chosen that they are biocompatible and biodegradable. Gold-based different nanosystems have NIR absorption which is highly favored for PTT, but they are limited by their toxicity, stability, and clearance. To overcome these challenges, we have demonstrated thermosensitive liposome-gold hybrid nanosystem for photothermal therapy and its clearance in vivo for the first time. We have also explored the possibility of using the same hybrid as drug (curcumin) carrier for triggered delivery and were successful in using curcumin as an adjuvant to PTT. Thermoresponsive polymers coated with gold for photothermal therapy and X-ray imaging of deep seated tumors has been evaluated. Fluorescent Poly (ethylene glycol) encapsulated metal nanoparticles were also synthesized and their application for cancer theranostics has been explored. Biodegradable and biocompatible polymer (PLGA) and liposomes loaded with anticancer plant fraction and a NIR dye showed synergistic photo-chemo therapy against cancer in-vitro & in-vivo. The intracellular changes with PTT and the mechanistic action of anti-cancer agent were explored in detail. Graphic abstract: [Figure not available: see fulltext.] © 2021, Indian National Science Academy.

World University root node

Proceedings of the Indian National Science Academy

Biodegradable/disintegrable nanohybrids for photothermal theranostics

Decellularized extracellular matrix is a tissue-specific biomaterial that recapitulates the complexity of the inherent tissue environment to elicit cellular response. Here, a multi-material decellularized liver (dLM)-based bioink with gelatin is developed and polyethylene glycol crosslinking is used to enhance the viscoelasticity of the dLM. We evaluated the necessity of a post-printing secondary cross-linker mushroom tyrosinase to improve robustness and long term stability. We further demonstrate it's biocompatibility using liver specific gene analysis of HepG2 cells. © 2021 MicroTAS 2021 - 25th International Conference on Miniaturized Systems for Chemistry and Life Sciences. All rights reserved.

MicroTAS 2021 - 25th International Conference on Miniaturized Systems for Chemistry and Life Sciences

A TUNABLE DECELLULARIZED LIVER-BASED HYBRID BIOINK

Costumes of a civilization are studied as a means of understanding people, their thinking, tastes, and culture. However, the subjective ‘feel’ of costume due to their interaction with human body is an important personal aspect of costumes that has not been studied. We hypothesize that this aspect can explain the motivation behind features of costumes that change or remain immutable over time. We propose a novel numerical encoding of costumes based on the interaction of costumes with human anatomy. Using methods from machine classification on a set of costumes from ancient to contemporary periods, we show that costumes of different epochs and cultures are separable in the two dimensional principal component space. We use the Eigen costumes to analyze the immutable similarity in Indic costumes through the ages and the contrasting features between Indic and non-Indic. We further dwell into primary sources to demonstrate that these characteristic features of Indic costumes were very likely considered and deliberate choices motivated by yoga in order to induce beneficial effects on prāṇa. We hope that this work will be a small first step for an alternate way of deriving insights into sartorial trends in various archeological specimen using methods from life sciences and computation. © 2021 The Authors. Archaeometry © 2021 University of Oxford

Archaeometry

Indian Costumes through the Ages: Insights into Sartorial Choices Using Mathematical Biology

3D printing has emerged as a promising fabrication technique for microfluidic devices, overcoming some of the challenges associated with conventional soft lithography. Filament-based polymer extrusion (popularly known as fused deposition modeling (FDM)) is one of the most accessible 3D printing techniques available, offering a wide range of low-cost thermoplastic polymer materials for microfluidic device fabrication. However, low optical transparency is one of the significant limitations of extrusion-based microfluidic devices, rendering them unsuitable for cell culture-related biological applications. Moreover, previously reported extrusion-based devices were largely dependent on fluorescent dyes for cell imaging because of their poor transparency. First, we aim to improve the optical transparency of FDM-based microfluidic devices to enable bright-field microscopy of cells. This is achieved using (1) transparent polymer filament materials such as poly(ethylene terephthalate) glycol (PETg), (2) optimized 3D printing process parameters, and (3) a hybrid approach by integrating 3D printed microfluidic devices with cast poly(dimethylsiloxane) (PDMS) blocks. We begin by optimizing four essential 3D printing process parameters (layer height, printing speed, cooling fan speed, and extrusion flow), affecting the overall transparency of 3D printed devices. Optimized parameters produce exceptional optical transparency close to 80% in 3D printed PETg devices. Next, we demonstrate the potential of FDM-based 3D printing to fabricate transparent micromixing devices with complex planar and nonplanar channel networks. Most importantly, cells cultured on native 3D printed PETg surfaces show excellent cell attachment, spreading, and proliferation during 3 days of culture without extracellular matrix coating or surface treatment. Next, we introduce L929 cells inside hybrid PETg-PDMS biomicrofluidic devices as a proof of concept. We demonstrate that 3D printed hybrid biomicrofluidic devices promote cell adhesion, allow bright-field microscopy, and maintain high cell viability for 3 days. Finally, we demonstrate the applicability of the proposed fabrication approach for developing 3D printed microfluidic devices from other FDM-compatible transparent polymers such as polylactic acid (PLA) and poly(methyl methacrylate) (PMMA). ©

ACS Biomaterials Science and Engineering

Facile Route for 3D Printing of Transparent PETg-Based Hybrid Biomicrofluidic Devices Promoting Cell Adhesion

In this study, an attempt has been made to differentiate Alzheimer's Disease (AD) stages in structural Magnetic Resonance (MR) images using single inception module network. For this, T1-weighted MR brain images of AD, mild cognitive impairment and Normal Controls (NC) are obtained from a public database. From the images, significant features are extracted and classified using an inception module network. The performance of the model is computed and analyzed for different input image sizes. Results show that the single inception module is able to classify AD stages using MR images. The end-to-end network differentiates AD from NC with 85% precision. The model is found to be effective for varied sizes of input images. Since the proposed approach is able to categorize AD stages, single inception module networks could be used for the automated AD diagnosis with minimum medical expertise. © 2021 European Federation for Medical Informatics (EFMI) and IOS Press. © 2021 European Federation for Medical Informatics (EFMI) and IOS Press. All rights reserved.

Public Health and Informatics: Proceedings of MIE 2021

Differentiation of Alzheimer conditions in MR brain images using a single inception module network

Electroencephalography (EEG) based emotion recognition is a widely preferred technique due to its noninvasiveness. Also, frontal region-specific EEG signals have been associated with emotional processing. Feature reductionbased optimized machine learning methods can improve the automated analysis of frontal EEG signals. In this work, an attempt is made to classify emotional states using entropybased features and Bayesian optimized random forest. For this, the EEG signals of prefrontal and frontal regions (Fp1, Fp2, Fz, F3, and F4) are obtained from an online public database. The signals are decomposed into five frequency bands, namely delta (1-4 Hz), theta (4-8 Hz), alpha (8-13 Hz), beta (14-30 Hz), and gamma (30-45 Hz). Three entropy features, namely Dispersion Entropy (DE), Sample Entropy (SE), and Permutation Entropy (PE), are extracted and are dimensionally reduced using Principal Component Analysis (PCA). Further, the reduced features are applied to the Bayesian optimized random forest for the classification. The results show that the DE in the gamma band and SE in the alpha band exhibit a statistically significant (p < 0.05) difference for classifying arousal and valence emotional states. The selected features from PCA yield an F-measure of 73.24% for arousal and 46.98% for valence emotional states. Further, the combination of all features yields a higher F-measure of 48.13% for valence emotional states. The proposed method is capable of handling multicomponent variations of frontal region-specific EEG signals. Particularly the combination of selected features could be useful to characterize arousal and valence emotional states. © 2021 by Walter de Gruyter Berlin/Boston.

Fulltext

Current Directions in Biomedical Engineering

EEG based emotion recognition using entropy features and Bayesian optimized random forest

Background: Data quality assessment is important but complex and task dependent. Identifying suitable measurement methods and reference ranges for assessing their results is challenging. Manually inspecting the measurement results and current data driven approaches for learning which results indicate data quality issues have considerable limitations, e.g. to identify task dependent thresholds for measurement results that indicate data quality issues. Objectives: To explore the applicability and potential benefits of a data driven approach to learn task dependent knowledge about suitable measurement methods and assessment of their results. Such knowledge could be useful for others to determine whether a local data stock is suitable for a given task. Methods: We started by creating artificial data with previously defined data quality issues and applied a set of generic measurement methods on this data (e.g. a method to count the number of values in a certain variable or the mean value of the values). We trained decision trees on exported measurement methods’ results and corresponding outcome data (data that indicated the data’s suitability for a use case). For evaluation, we derived rules for potential measurement methods and reference values from the decision trees and compared these regarding their coverage of the true data quality issues artificially created in the dataset. Three researchers independently derived these rules. One with knowledge about present data quality issues and two without. Results: Our self-trained decision trees were able to indicate rules for 12 of 19 previously defined data quality issues. Learned knowledge about measurement methods and their assessment was complementary to manual interpretation of measurement methods’ results. Conclusions: Our data driven approach derives sensible knowledge for task dependent data quality assessment and complements other current approaches. Based on labeled measurement methods’ results as training data, our approach successfully suggested applicable rules for checking data quality characteristics that determine whether a dataset is suitable for a given task. © 2021, The Author(s).

BMC Medical Informatics and Decision Making

A data driven learning approach for the assessment of data quality

A sand bath assisted strategy for the synthesis of fluorescent carbon dots (CDs) using citrus fruit peels as a renewable green resource is reported in this work. The CDs were synthesized without any alkaline or acidic environment. The synthesized CDs were characterized by various spectroscopic and microscopy techniques. The CDs exhibited excellent water solubility and superior optical properties like excitation dependent emission, and multicolor fluorescence. In addition, the CDs have exhibited remarkable free radical scavenging activity (EC50: 4.7382 μg ml−1).The CDs were highly biocompatible and showed lower toxicity. The CDs when modified with folic acid have shown a significant potential as biological labels for cellular imaging at multiple excitations. Synthesis of CDs from natural fruit peels as an excellent carbon source for versatile applications has been demonstrated. © 2020 Elsevier B.V.

Colloids and Surfaces B: Biointerfaces

Sand bath assisted green synthesis of carbon dots from citrus fruit peels for free radical scavenging and cell imaging

Photodynamic/photothermal therapy (PDT/PTT) that deploys a near-infrared responsive nanosystem is emerging to be a promising modality in cancer treatment. It is highly desirable to have a multifunctional nanosystem that can be used for efficient tumor targeting and inhibiting metastasis/recurrence of cancer. In the current study, self-assembled chlorophyll-rich fluorosomes derived fromSpinacia oleraceawere developed. These fluorosomes were co-assembled on a polydopamine core, forming camouflaged nanoparticles (SPoD NPs). The SPoD NPs exhibited a commingled PDT/PTT (i.e., interdependent PTT and PDT) that inhibited both normoxic and hypoxic cancer cell growth. These nanoparticles showed stealth properties with enhanced physiological stability and passive tumor targeting. SPoD NPs also exhibited tumor suppression by synergistic PTT and PDT. It also prevented lung metastasis and splenomegaly in tumor-bearing Balb/c mice. Interestingly, treatment with SPoD NPs also caused the suppression of secondary tumors by eliciting an anti-tumor immune response. In conclusion, a co-assembled multifunctional nanosystem derived fromS. oleraceashowed enhanced stability and tumor-targeting efficacy, resulting in a commingled PDT/PTT effect. © 2021 American Chemical Society

Biomacromolecules

Self-Assembled Fluorosome-Polydopamine Complex for Efficient Tumor Targeting and Commingled Photodynamic/Photothermal Therapy of Triple-Negative Breast Cancer

Flavonoids have various medicinal properties such as anti-inflammatory, anti-oxidant, anti-cancer, antiviral. Yet, the fluorescent properties of flavonoids are less explored and termed as autofluorescence in general. This study investigates the fluorescence properties of Isoliquiritigenin (ISL) in various alkaline conditions. The maximum fluorescence emission was obtained at pH 12 on excitation wavelength of 440 nm. Theoretical and experimental investigation on the shift in UV–Vis absorbance spectra, upon the variation in pH, performed, indicated deprotonation as the cause. PEG-based stable liposome carrier, with an internal alkaline environment (LIP-ISL-NaOH) that aids in flavonoid fluorescence, was synthesized using a modified thin-film hydration method. The hydrodynamic size of the liposome synthesized was in the range of 50–70 nm. PEG, on the addition, found maintaining the alkaline environment in the internal chamber of the lipo-polymer system, helps the LIP-ISLNaOH nanosystem to exhibit fluorescence irrespective of the suspension pH. Further, reducing property of ISL was used for the synthesis of Au nanoclusters to achieve theranostic nature. © 2021 Elsevier B.V.