Amity University Mumbai

Inflammatory bowel disease (IBD) is a chronic inflammatory condition of gastrointestinal (GI) tract with dysregulated mucosal immune functions and disturbed commensal ecosystem of the intestinal lumen.IBD is categorized into two major subsets: Crohn's disease (CD) and ulcerative colitis (UC).Though advent of biologics has shifted the treatment with relatively longer remission compared to small molecule pharmaceuticals, patients still suffer from long-term complications.Since gutmicrobiome is now accepted as another human organ holding potential for long-lasting human health, probiotics, and its engineering hold great promises to treat several previously untreatable chronic inflammatory conditions including IBD.Several emerging biological engineering tools have unlimited potential to manipulate probiotic bacterial system.These can produce useful therapeutic biologics with a goal to either ameliorate and/or treat previously untreatable chronic inflammatory conditions.As gut-microbiome is diverse and vary in different ethnic, geographic, and cultural human population, it will be important to develop vision for personalized probiotic treatment and develop the technology thereof to make personalized probiotic options a reality.The aim of this review paper is to present an overview of the current knowledge on both pharmacological and nonpharmacological IBD treatment modalities with a special emphasis on probiotic strains that are developed through the probiotic engineering.These engineered probiotics contain the most anti-inflammatory cytokines found within the human immune response and are currently being used to treat the intestinal inflammation in IBD for the IBD treatment.

The next generation of electronics technology is purely going to be based on wearable sensing systems. Wearable electronic sensors that can operate in a continuous and sustainable manner without the need of an external power sources, are essential for portable and mobile electronic applications. In this review article, the recent progress and advantages of wearable self-powered smart chemical sensors systems for wearable electronics are presented. An overview of various modes of energy conversion and storage technologies for self-powered devices is provided. Self-powered chemical sensors (SPCS) systems with integrated energy units are then discussed, separated as solar cell-based SPCS, triboelectric nano-generators based SPCS, piezoelectric nano-generators based SPCS, energy storage device based SPCS, and thermal energy-based SPCS. Finally, the outlook on future prospects of wearable chemical sensors in self-powered sensing systems is addressed.

Abstract Borophene, the lightest among all Xenes, possesses extreme electronic mobility along with high carrier density and high Young's modulus. To accomplish device‐quality borophene, novel approaches of realization of monolayers need to be urgently explored. In this work, micromechanical exfoliation is discovered to result in mono‐ and few‐layered borophene of device quality. Borophene sheets are successfully fabricated down to monolayer thickness. Distinct crystallographic phases of borophene viz. XRD study reveals crystallographic phase transition from rhombohedral to several other eigen phases of borophene. The role of the destination substrates is held crucial in determining the final phase of the transferred sheet. The exfoliation energy is calculated by density functional theory. Molecular dynamics simulations are used to simulate the exfoliation process. Heterolayers of borophene, with black phosphorene (BP) or with molybdenum disulfide (MoS 2 ) atomic sheets, are found to result in photoexcited coupling quantum states. Gold‐coated borophene bestows promising anchoring capability for surface‐enhanced Raman spectroscopy (SERS). Successful demonstration of the electronic behavior of micromechanically exfoliated borophene and excitonic behavior of borophene‐based heterolayers will guide future generation devices not only in electronics and excitonics, but also in thermal management, electronic packaging, hydrogen storage, hybrid energy storage, and clean energy solutions.

Head and neck squamous cell carcinoma (HNSCC) is the sixth most common non-skin cancer with a tobacco consumption and infection with high-risk human papillomavirus (HPV) being major risk factors. Despite advances in numerous therapy modalities, survival rates for HNSCC have not improved considerably; a vast number of clinical outcomes have demonstrated that a combination strategy (the most well-known docetaxel, cisplatin, and 5-fluorouracil) is the most effective treatment choice. Immunotherapy that targets immunological checkpoints is being tested in a number of clinical trials, either alone or in conjunction with chemotherapeutic or targeted therapeutic drugs. Various monoclonal antibodies, such as cetuximab and bevacizumab, which target the EGFR and VEGFR, respectively, as well as other signaling pathway inhibitors, such as temsirolimus and rapamycin, are also being studied for the treatment of HNSCC. We have reviewed the primary targets in active clinical studies in this study, with a particular focus on the medications and drug targets used.

2-D Ti 3 C 2 T X MXene nanosheets are obtained by etching Ti 3 SiC 2 MAX phase that is synthesized by heating the elemental Ti, Si, and C mixture at high temperature. The electron emission behavior of both Ti 3 C 2 T X MXene and Ti 3 SiC 2 MAX phase is studied. MXene exhibits excellent field emission characteristics with a turn-on field of 4.7 V μm –1, and that for the Ti 3 SiC 2 MAX phase is 6.5 V μm –1 . The turn-on electric field corresponding to an emission current density of 10 μA cm –2 is 5.0 V μm –1 for Ti 3 C 2 T X MXene and 7.5 V μm –1 for the Ti 3 SiC 2 MAX phase. The calculated enhancement factor of MXene nanosheets is ∼4280, which is one of the highest reported enhancement factors to date. In order to get theoretical insight into the field emission properties for Ti 3 C 2 and OH-terminated Ti 3 C 2 MXene in comparison to the Ti 3 SiC 2 MAX phase, we have presented the structure and electronic properties from state of the art density functional theory (DFT) simulations. The interaction of – OH with Ti 3 C 2 involves charge transfer from the “Ti” 3d orbital to −OH. The computed work function follows the trend Ti 3 SiC 2 > Ti 3 C 2 > Ti 3 C 2 /OH, which supports the maximum field emission in −OH-terminated Ti 3 C 2 MXene and the minimum field emission in the Ti 3 SiC 2 MAX phase.

Black phosphorous (BP) has emerged as a potential sensing material due to its exceptional physicochemical properties. The review presents both the theoretical and experimental aspects of the BP-based gas sensors.

Abstract We present the pulse arrival times and high-precision dispersion measure estimates for 14 millisecond pulsars observed simultaneously in the 300 $-$ 500 MHz and 1260 $-$ 1460 MHz frequency bands using the upgraded Giant Metrewave Radio Telescope. The data spans over a baseline of 3.5 years (2018-2021), and is the first official data release made available by the Indian Pulsar Timing Array collaboration. This data release presents a unique opportunity for investigating the interstellar medium effects at low radio frequencies and their impact on the timing precision of pulsar timing array experiments. In addition to the dispersion measure time series and pulse arrival times obtained using both narrowband and wideband timing techniques, we also present the dispersion measure structure function analysis for selected pulsars. Our ongoing investigations regarding the frequency dependence of dispersion measures have been discussed. Based on the preliminary analysis for five millisecond pulsars, we do not find any conclusive evidence of chromaticity in dispersion measures. Data from regular simultaneous two-frequency observations are presented for the first time in this work. This distinctive feature leads us to the highest precision dispersion measure estimates obtained so far for a subset of our sample. Simultaneous multi-band upgraded Giant Metrewave Radio Telescope observations in 300 $-$ 500 MHz and 1260 $-$ 1460 MHz are crucial for high-precision dispersion measure estimation and for the prospect of expanding the overall frequency coverage upon the combination of data from the various Pulsar Timing Array consortia in the near future. Parts of the data presented in this work are expected to be incorporated into the upcoming third data release of the International Pulsar Timing Array.

Ensemble multifeatured deep learning methodology has emerged as a powerful approach to overcome the limitations of single deep learning models in terms of generalization, robustness, and performance. This survey provides an extended review of ensemble multifeatured deep learning models, and their applications, challenges, and future directions. We explore potential applications of these models across various domains, including computer vision, medical imaging, natural language processing, and speech recognition. By combining the strengths of multiple models and features, ensemble multifeatured deep learning models have demonstrated improved performance and adaptability in diverse problem settings. We also discuss the challenges associated with these models, such as model interpretability, computational complexity, ensemble model selection, adversarial robustness, and personalized and federated learning. This survey highlights recent advancements in addressing these challenges and emphasizes the importance of continued research in tackling these issues to enable widespread adoption of ensemble multifeatured deep learning models. It provides an outlook on future research directions, focusing on the development of new algorithms, frameworks, and hardware architectures that can efficiently handle the large-scale computations required by these models. Moreover, it underlines the need for a better understanding of the trade-offs between model complexity, accuracy, and computational resources to optimize the design and deployment of ensemble multifeatured deep learning models.

Two-dimensional transition-metal dichalcogenides (2D-TMDCs) have shown great promise for sustainable energy production via electrocatalytic, photocatalytic, and photovoltaic activities. Here, we report the WS 2 /ZnO (WZO) nano-heterostructures with optimized materials properties for high-performance photoelectrocatalytic activity. WZO nano-heterostructures have shown faster electrocatalytic hydrogen evolution reaction (HER) compared to pristine WS 2 and ZnO owing to the reduced charge transfer resistance and enhanced active area of the catalysts. HER activity has been found to be stable for chrono-amperometry of 25 h and cyclic voltammetry of 2000 cycles. The catalyst has shown visible light-sensitive catalytic activity and a significantly reduced over potential of −182 mV versus RHE (reversible hydrogen electrode) at 10 mA/cm 2 . Additionally, a self-powered and fast photodetection ability with a responsivity of 6.7 mA/W, stability upto 1600 s, and response time of 80 ms has been reported. The maximum photoresponsivity of 1.34 A/W was realized at −250 mV versus RHE. Besides, present findings report the importance of dominating pyroelectricity for photoswitching. Overall, the present findings explored the photo-sensitive 2D-TMDCs as an alternative of noble metals in electrocatalytic activity for clean energy production.

Systems for monitoring air quality are essential for reducing the negative consequences of air pollution, but creating real-time systems encounters several challenges. The accuracy and effectiveness of these systems can be greatly improved by integrating federated learning and multi-access edge computing (MEC) technology. This paper critically reviews the state-of-the-art methodologies for federated learning and MEC-enabled air quality monitoring systems. It discusses the immense benefits of federated learning, including privacy-preserving model training, and MEC, such as reduced latency and improved response times, for air quality monitoring applications. Additionally, it highlights the challenges and requirements for developing and implementing real-time air quality monitoring systems, such as data quality, security, and privacy, as well as the need for interpretable and explainable AI-powered models. By leveraging such advanced techniques and technologies, air monitoring systems can overcome various challenges and deliver accurate, reliable, and timely air quality predictions. Moreover, this article provides an in-depth analysis and assessment of the state-of-the-art techniques and emphasizes the need for further research to develop more practical and affordable AI-powered decentralized systems with improved performance and data quality and security while ensuring the ethical and responsible use of the data to support informed decision making and promote sustainability.

Young age, female sex, absence of comorbidities, and prior infection or vaccination are known epidemiological barriers for contracting the new infection and/or increased disease severity. Demographic trends from the recent coronavirus disease 2019 waves, which are believed to be driven by newer severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants, indicate that the aforementioned epidemiological barriers are being breached and a larger number of younger and healthy individuals are developing severe disease. The new SARS-CoV-2 variants have key mutations that can induce significant changes in the virus-host interactions. Recent studies report that, some of these mutations, singly or in a group, enhance key mechanisms, such as binding of the receptor-binding domain (RBD) of the viral spike protein with the angiotensin-converting enzyme 2 (ACE2) receptor in the host-cells, increase the glycosylation of spike protein at the antigenic sites, and enhance the proteolytic cleavage of the spike protein, thus leading to improved host-cell entry and the replication of the virus. The putative changes in the virus-host interactions imparted by the mutations in the RBD sequence can potentially be the reason behind the breach of the observed epidemiological barriers. Susceptibility for contracting SARS-CoV-2 infection and the disease outcomes are known to be influenced by host-cell expressions of ACE2 and other proteases. The new variants can act more efficiently, and even with the lesser availability of the viral entry-receptor and the associated proteases, can have more efficient host-cell entry and greater replication resulting in high viral loads and prolonged viral shedding, widespread tissue-injury, and severe inflammation leading to increased transmissibility and lethality. Furthermore, the accumulating evidence shows that multiple new variants have reduced neutralization by both, natural and vaccine-acquired antibodies, indicating that repeated and vaccine breakthrough infections may arise as serious health concerns in the ongoing pandemic.

The MoS 2 nanobelts/Carbon hybrid nanostructure was synthesized by the simple hydrothermal method. The MoS 2 nanobelts were distributed in the interlayers of Lemon grass-derived carbon (LG-C), provides the active sites and avoid restacking of the sheets. The structural and morphological characterization of MoS 2 /LG-C and LG-C were performed by Raman spectroscopy, X-ray diffraction, field emission scanning electron microscopy, transmission electron microscopy, and X-ray photoelectron spectroscopy. The electrochemical measurements were studied with cyclic voltammetry, the galvanostatic charge-discharge method, and electrochemical impedance spectroscopy. The specific capacitance of MoS 2 /LG-C and LG-C exhibits 77.5 F g −1 and 30.1 F g −1 at a current density of 0.5 A g −1 . The MoS 2 /LG-C-based supercapacitor provided the maximum power density and energy density of 273.2 W kg −1 and 2.1 Wh kg −1 , respectively. Furthermore, the cyclic stability of MoS 2 /LG-C was tested using charging-discharging up to 3,000 cycles, confirming only a 71.6% capacitance retention at a current density of 3 A g −1 . The result showed that MoS 2 /LG-C is a superior low-cost electrode material that delivered a high electrochemical performance for the next generation of electrochemical energy storage.

In the current decade, nanoparticles are synthesized using solvents that are environmentally friendly. A number of nanoparticles have been synthesized at room temperature using water as a solvent, such as gold (Au) and silver (Ag) nanoparticles. As part of nanotechnology, nanoparticles are synthesized through biological processes. Biological methods are the preferred method for the synthesis of inorganic nanoparticles (AgNPs) as a result of their simple and non-hazardous nature. Nanoparticles of silver are used in a variety of applications, including catalysts, spectrally selective coatings for solar absorption, optical objectives, pharmaceutical constituents, and chemical and biological sensing. Antimicrobial agents are among the top uses of silver nanoparticles. In the current study, silver nanoparticles were biologically manufactured through Madhuca longifolia, and their antibacterial activity against pathogenic microorganisms, anticancer, anti-inflammatory, and antioxidant activities were assessed. UV-Vis spectroscopy, XRD (X-ray diffraction), transmission electron microscopy, Zeta Potential, and FTIR were used to characterize silver nanoparticles. The current work describes a cheap and environmentally friendly method to synthesize silver nanoparticles from silver nitrate solution by using plant crude extract as a reducing agent.

Immune dysregulation is a pivotal factor in the onset and progression of various diseases. In cancer, the immune system's inability to discern and eliminate abnormal cells leads to uncontrolled tumor growth. When faced with resilient pathogens or harmful toxins, the immune system encounters challenges in clearance and neutralization. Achieving a delicate balance of pro‐inflammatory and anti‐inflammatory signals is essential in managing a range of disorders and diseases. Like in other biomedical research domains, nanotechnology has provided innovative approaches for rebalancing host immunity. Among the plethora of nanotechnology‐based interventions, the concept of cell membrane‐coated nanoparticles holds significant potential for immunomodulatory applications owing to their biomimetic properties that allow for precise interaction with the compromised immune system. This review thoroughly examines the potential of novel nanosystems for immune modulation. The exploration covers crucial elements, including the origins and characteristics of cell membranes, the methods employed for their procurement and coating, physicochemical/biological characterization techniques, and enhancement of their therapeutic efficacy via functionalization. Subsequently, case studies‐based analysis of utilizing these bioinspired nanosystems in tackling different conditions caused by immune disturbance has been comprehensively discussed.

Cancer is still one of the world's deadliest health concerns. As per latest statistics, lung, breast, liver, prostate, and cervical cancers are reported topmost worldwide. Although chemotherapy is most widely used methodology to treat cancer, poor pharmacokinetic parameters of anticancer drugs render them less effective. Novel nano-drug delivery systems have the caliber to improve the solubility and biocompatibility of various such chemical compounds. In this regard, cyclodextrins (CD), a group of natural nano-oligosaccharide possessing unique physicochemical characteristics has been highly exploited for drug delivery and other pharmaceutical purposes. Their cup-like structure and amphiphilic nature allows better accumulation of drugs, improved solubility, and stability, whereas CDs supramolecular chemical compatibility renders it to be highly receptive to various kinds of functionalization. Therefore combining physical, chemical, and bio-engineering approaches at nanoscale to specifically target the tumor cells can help in maximizing the tumor damage without harming non-malignant cells. Numerous combinations of CD nanocomposites were developed over the years, which employed photodynamic, photothermal therapy, chemotherapy, and hyperthermia methods, particularly targeting cancer cells. In this review, we discuss the vivid roles of cyclodextrin nanocomposites developed for the treatment and theranostics of most important cancers to highlight its clinical significance and potential as a medical tool.

This review provides the basic working principles of field emission, the advantages of 2D materials and various approaches to further tune the performance for cold field emitter devices.

Abstract This paper highlights unique sites in Ladakh, India, investigated during our 2016 multidisciplinary pathfinding expedition to the region. We summarize our scientific findings and the site's potential to support science exploration, testing of new technologies and science protocols within the framework of astrobiology research. Ladakh has several accessible, diverse, pristine and extreme environments at very high altitudes (3000–5700 m above sea level). These sites include glacial passes, sand dunes, hot springs and saline lake shorelines with periglacial features. We report geological observations and environmental characteristics (of astrobiological significance) along with the development of regolith-landform maps for cold high passes. The effects of the diurnal water cycle on salt deliquescence were studied using the ExoMars Mission instrument mockup: HabitAbility: Brines, Irradiance and Temperature (HABIT). It recorded the existence of an interaction between the diurnal water cycle in the atmosphere and salts in the soil (which can serve as habitable liquid water reservoirs). Life detection assays were also tested to establish the best protocols for biomass measurements in brines, periglacial ice-mud and permafrost melt water environments in the Tso-Kar region. This campaign helped confirm the relevance of clays and brines as interest targets of research on Mars for biomarker preservation and life detection.

Aquatic weeds have posed a challenge in their containment to halt its spread worldwide. When removed from the water systems, huge capital and human resources are diverted for its safe management and disposal. When used as a potential resource, the aquatic weeds can be profitable and beneficial. The contents of carbohydrate, protein and lipids make aquatic weed a potential feedstock in production of biofuels. Lignin and sugar component of aquatic weed could be utilized in production of bio-oil, combustible gases and heat energy using thermo-chemical methods. The sugar portion could be subjected to fermentation to produce bio-ethanol, bio-methanol and bio-butanol. The lipid fraction of the aquatic week could be utilized to produce biodiesel. Bio-methane and bio-hydrogen could also be developed from the biomass of aquatic weed by biological processes. A large-scale production of aquatic weed will be feasible with innovative and cost-effective methods for harvesting, drying, transportation of the aquatic weed to processing sites and conversion to respective biofuels. Process intensification (viz. Microwave and sonication) during pretreatment steps could fasten the decomposition of biomass of aquatic weed.A biorefinery approach where the aquatic biomass could yield biofuel, fertilizer, industrially useful chemicals and remediate the wastewater is ought to make the overall process economical, sustainable and environment friendly. The value-added products (enzymes and polymers) derived from the biomass of the aquatic weeds could strengthen the commerciality of the process. Aquatic macrophytes could further be used in food source for animals, fish, and humans; in paper making and in medicinal applications.

Terrestrial Wireless Sensor Networks (WSNs) are used in military environments for region surveillance, healthcare systems for soldiers, and, smart transport, and logistics, etc. In surveillance applications, the sensor nodes are deployed randomly in the field to observe the events of interest, movement of humans, or vehicles. In these sensor networks, the image or video is captured by the camera module. Many times it becomes difficult to correctly detect the intrusion or anomalous activity in the field because the image being captured maybe not clear enough due to prevailing weather conditions, the amount of light, and other reasons. In this paper, in addition to a WSN Surveillance System for military applications, we have used Convolutional Neural Network (CNN) for analyzing and understanding the content of the captured images and videos. CNN is a deep learning neural network that detects and tracks automatically the important features without any human supervision. The distinctive layers of each class are learned by themselves and have the highest accuracy of prediction. The results of the implementation for four test images captured in different conditions show an accuracy of 92%. The results of the video tracking yield the Object Tracking Efficiency of 80.35%.

Abstract The quest for new functional nanomaterials is one of the defining purposes of nanoscience and nanotechnology. A large number of metal nanoparticles (NPs) are extensively exploited for biomedical applications. Metal NPs, in particular platinum NPs (PtNPs), possess remarkable properties that make them a potential candidate as a diagnostic or therapeutic agent. Due to potential technological interest over the last decade, PtNPs have attracted much attention in the field of anticancer research. PtNPs, when conjugated with many functionalizing agents such as polymers, ligands, drugs, peptides, and surfactants, exhibit improved targeting and reduced cytotoxic effects in various cancers. The PtNPs conjugated with folic acid, graphene oxide, and iron NPs are gained more attention due to their stability, large surface area, and reduced toxicity. To achieve this goal, PtNPs are co‐loaded with drugs or other modalities that offer an opportunity for multimodal activity in the frame of treating cancer types focusing on breast, blood, lung, ovarian, skin, liver, etc. However, a review of PtNPs’ function in diagnosis and treatment is still lacking. In this review, the effectiveness of PtNPs toward inducing and elevating death of the cancerous cells proving its delivery approaches and antitumor nature, concluding with future perspectives, are summarized.