Lovely Professional University

Cancer is an abnormal state of cells where they undergo uncontrolled proliferation and produce aggressive malignancies that causes millions of deaths every year. With the new understanding of the molecular mechanism(s) of disease progression, our knowledge about the disease is snowballing, leading to the evolution of many new therapeutic regimes and their successive trials. In the past few decades, various combinations of therapies have been proposed and are presently employed in the treatment of diverse cancers. Targeted drug therapy, immunotherapy, and personalized medicines are now largely being employed, which were not common a few years back. The field of cancer discoveries and therapeutics are evolving fast as cancer type-specific biomarkers are progressively being identified and several types of cancers are nowadays undergoing systematic therapies, extending patients' disease-free survival thereafter. Although growing evidence shows that a systematic and targeted approach could be the future of cancer medicine, chemotherapy remains a largely opted therapeutic option despite its known side effects on the patient's physical and psychological health. Chemotherapeutic agents/pharmaceuticals served a great purpose over the past few decades and have remained the frontline choice for advanced-stage malignancies where surgery and/or radiation therapy cannot be prescribed due to specific reasons. The present report succinctly reviews the existing and contemporary advancements in chemotherapy and assesses the status of the enrolled drugs/pharmaceuticals; it also comprehensively discusses the emerging role of specific/targeted therapeutic strategies that are presently being employed to achieve better clinical success/survival rate in cancer patients.

The textile sector is 14% of total industrial production in India and contributes to about 4% of the gross domestic product and earns about 27% of India's total foreign exchange. Worldwide, up to 10,000 dyes are available and their annual production is above 7 × 105 metric tons, which are being used not only in textile sector but also applied in paper, food and pharmaceutical industries. Textile industries in India have been consuming more than 100 L of water to process 1 kg of textiles, and have contributed heavily in polluting surface and ground water resources in many regions of the country. The toxic and carcinogenic effect of untreated textile effluent is well understood. The decolorization and detoxification of industrial dye effluents is most important aspect and is major concern to meet environmental regulations. This paper presents a review of literature on the significance of bioremediation technologies over other physico-chemical methods for efficient removal of textile dyes from industrial waste effluents to improve the fragile ecosystems in different regions of the world.The present review paper (a) symbolizes the applications of existing conventional physical and chemical approaches for the decolorization/degradation of textile dyes, (b) describes their merits and demerits, (c) emphasizes on the existing literature on microbial decolorization of textile dyes precisely by using bacteria (aerobic and anaerobic conditions), fungi and algae, and (d) involvement of various enzymes from different biological sources for the decolorization of various textile dyes and their mechanism of action.Over the years, researchers have developed several bioremediation technologies to treat textile effluents, but little effort has been made to put the entire literature review of these technologies in one refereed paper, our review paper is an attempt to compile the existing information on various treatment technologies of textile effluent, so that these technologies can be shared widely for site specific situations.

Emerged in the middle of 20th century, composite materials are now one of the hotspot research topics in the modern technology. Their promising characteristics make them suitable for enormous applications in industrial field such as aerospace, automotive, construction, sports, bio-medical and many others. These materials reveal remarkable structural and mechanical properties such as high strength to weight ratio, resistance to chemicals, fire, corrosion and wear; being economical to manufacture. Herein, an overview of composite materials, their characterization, classification and main advantages linked to physical and mechanical properties based on the recent studies are presented. There, were presented the conventional manufacturing techniques of composite and their applications. It was highlighted the tremendous need to discovery new generation of composites that should incorporate the synthetic or natural materials by implementing new efficient manufacturing processes. In the combination of matrix and reinforcement materials, the use of natural materials as constituent are compulsory in order to obtain a complete material degradable as environmentally friendly.

Pneumonia is among the top diseases which cause most of the deaths all over the world. Virus, bacteria and fungi can all cause pneumonia. However, it is difficult to judge the pneumonia just by looking at chest X-rays. The aim of this study is to simplify the pneumonia detection process for experts as well as for novices. We suggest a novel deep learning framework for the detection of pneumonia using the concept of transfer learning. In this approach, features from images are extracted using different neural network models pretrained on ImageNet, which then are fed into a classifier for prediction. We prepared five different models and analyzed their performance. Thereafter, we proposed an ensemble model that combines outputs from all pretrained models, which outperformed individual models, reaching the state-of-the-art performance in pneumonia recognition. Our ensemble model reached an accuracy of 96.4% with a recall of 99.62% on unseen data from the Guangzhou Women and Children’s Medical Center dataset.

The era of artificial neural network (ANN) began with a simplified application in many fields and remarkable success in pattern recognition (PR) even in manufacturing industries. Although significant progress achieved and surveyed in addressing ANN application to PR challenges, nevertheless, some problems are yet to be resolved like whimsical orientation (the unknown path that cannot be accurately calculated due to its directional position). Other problem includes; object classification, location, scaling, neurons behavior analysis in hidden layers, rule, and template matching. Also, the lack of extant literature on the issues associated with ANN application to PR seems to slow down research focus and progress in the field. Hence, there is a need for state-of-the-art in neural networks application to PR to urgently address the above-highlights problems for more successes. The study furnishes readers with a clearer understanding of the current, and new trend in ANN models that effectively addresses PR challenges to enable research focus and topics. Similarly, the comprehensive review reveals the diverse areas of the success of ANN models and their application to PR. In evaluating the performance of ANN models, some statistical indicators for measuring the performance of the ANN model in many studies were adopted. Such as the use of mean absolute percentage error (MAPE), mean absolute error (MAE), root mean squared error (RMSE), and variance of absolute percentage error (VAPE). The result shows that the current ANN models such as GAN, SAE, DBN, RBM, RNN, RBFN, PNN, CNN, SLP, MLP, MLNN, Reservoir computing, and Transformer models are performing excellently in their application to PR tasks. Therefore, the study recommends the research focus on current models and the development of new models concurrently for more successes in the field.

Plants face a variety of abiotic stresses, which generate reactive oxygen species (ROS), and ultimately obstruct normal growth and development of plants. To prevent cellular damage caused by oxidative stress, plants accumulate certain compatible solutes known as osmolytes to safeguard the cellular machinery. The most common osmolytes that play crucial role in osmoregulation are proline, glycine-betaine, polyamines, and sugars. These compounds stabilize the osmotic differences between surroundings of cell and the cytosol. Besides, they also protect the plant cells from oxidative stress by inhibiting the production of harmful ROS like hydroxyl ions, superoxide ions, hydrogen peroxide, and other free radicals. The accumulation of osmolytes is further modulated by phytohormones like abscisic acid, brassinosteroids, cytokinins, ethylene, jasmonates, and salicylic acid. It is thus important to understand the mechanisms regulating the phytohormone-mediated accumulation of osmolytes in plants during abiotic stresses. In this review, we have discussed the underlying mechanisms of phytohormone-regulated osmolyte accumulation along with their various functions in plants under stress conditions.

Recent scientific studies have established a relationship between the consumption of phytochemicals such as carotenoids, polyphenols, isoprenoids, phytosterols, saponins, dietary fibers, polysaccharides, etc., with health benefits such as prevention of diabetes, obesity, cancer, cardiovascular diseases, etc. This has led to the popularization of phytochemicals. Nowadays, foods containing phytochemicals as a constituent (functional foods) and the concentrated form of phytochemicals (nutraceuticals) are used as a preventive measure or cure for many diseases. The health benefits of these phytochemicals depend on their purity and structural stability. The yield, purity, and structural stability of extracted phytochemicals depend on the matrix in which the phytochemical is present, the method of extraction, the solvent used, the temperature, and the time of extraction.

Additive Manufacturing (AM) has revolutionized the manufacturing industry in several directions. Laser powder bed fusion (LPBF), a powder bed fusion AM process, has been dramatically accepted in various industries due to its versatility with several materials, including alloys. This comprehensive review article primarily explains the basic principle of the LPBF process, scientific and technological progress of several inter-related parameters, feedstock materials, produced properties/defects, and insights of numerical modelling to virtually understand the process behavior. Specific attention has been given to selective laser-meted (LPBFed) properties, driven through the microstructure formations and, thereby, concerning defects. The scope of the post-processing techniques to refine microstructure has also been discussed in this review paper. It has been identified that the defects are vital in LPBF process and are primarily governed by the process parameters. Therefore, a wisely chosen, optimized set of parameters can play a crucial role in minimizing defects considerably. Finally, the numerical modeling discussed in this review paper will help the researchers understand the LPBF process.

Solid lipid nanoparticles (SLNs) are nanocarriers developed as substitute colloidal drug delivery systems parallel to liposomes, lipid emulsions, polymeric nanoparticles, and so forth. Owing to their unique size dependent properties and ability to incorporate drugs, SLNs present an opportunity to build up new therapeutic prototypes for drug delivery and targeting. SLNs hold great potential for attaining the goal of targeted and controlled drug delivery, which currently draws the interest of researchers worldwide. The present review sheds light on different aspects of SLNs including fabrication and characterization techniques, formulation variables, routes of administration, surface modifications, toxicity, and biomedical applications.

The plant-Trichoderma-pathogen triangle is a complicated web of numerous processes. Trichoderma spp. are avirulent opportunistic plant symbionts. In addition to being successful plant symbiotic organisms, Trichoderma spp. also behave as a low cost, effective and ecofriendly biocontrol agent. They can set themselves up in various patho-systems, have minimal impact on the soil equilibrium and do not impair useful organisms that contribute to the control of pathogens. This symbiotic association in plants leads to the acquisition of plant resistance to pathogens, improves developmental processes and yields and promotes absorption of nutrient and fertilizer use efficiency. Among other biocontrol mechanisms, antibiosis, competition and mycoparasitism are among the main features through which microorganisms, including Thrichoderma, react to the presence of other competitive pathogenic organisms, thereby preventing or obstructing their development. Stimulation of every process involves the biosynthesis of targeted metabolites like plant growth regulators, enzymes, siderophores, antibiotics, etc. This review summarizes the biological control activity exerted by Trichoderma spp. and sheds light on the recent progress in pinpointing the ecological significance of Trichoderma at the biochemical and molecular level in the rhizosphere as well as the benefits of symbiosis to the plant host in terms of physiological and biochemical mechanisms. From an applicative point of view, the evidence provided herein strongly supports the possibility to use Trichoderma as a safe, ecofriendly and effective biocontrol agent for different crop species.

The segmentation, detection, and extraction of infected tumor area from magnetic resonance (MR) images are a primary concern but a tedious and time taking task performed by radiologists or clinical experts, and their accuracy depends on their experience only. So, the use of computer aided technology becomes very necessary to overcome these limitations. In this study, to improve the performance and reduce the complexity involves in the medical image segmentation process, we have investigated Berkeley wavelet transformation (BWT) based brain tumor segmentation. Furthermore, to improve the accuracy and quality rate of the support vector machine (SVM) based classifier, relevant features are extracted from each segmented tissue. The experimental results of proposed technique have been evaluated and validated for performance and quality analysis on magnetic resonance brain images, based on accuracy, sensitivity, specificity, and dice similarity index coefficient. The experimental results achieved 96.51% accuracy, 94.2% specificity, and 97.72% sensitivity, demonstrating the effectiveness of the proposed technique for identifying normal and abnormal tissues from brain MR images. The experimental results also obtained an average of 0.82 dice similarity index coefficient, which indicates better overlap between the automated (machines) extracted tumor region with manually extracted tumor region by radiologists. The simulation results prove the significance in terms of quality parameters and accuracy in comparison to state-of-the-art techniques.

Biodegradable polymers have played an important role in the delivery of drugs in a controlled and targeted manner. Polylactic-co-glycolic acid (PLGA) is one of the extensively researched synthetic biodegradable polymers due to its favorable properties. It is also known as a 'Smart Polymer' due to its stimuli sensitive behavior. A wide range of PLGA-based drug delivery systems have been reported for the treatment or diagnosis of various diseases and disorders. The present review provides an overview of the chemistry, physicochemical properties, biodegradation behavior, evaluation parameters and applications of PLGA in drug delivery. Different drug–polymer combinations developed into drug delivery or carrier systems are enumerated and discussed.

Plants are often exposed to unfavorable environmental conditions, for instance abiotic stresses, which dramatically alter distribution of plant species among ecological niches and limit the yields of crop species. Among these, drought stress is one of the most impacting factors which alter seriously the plant physiology, finally leading to the decline of the crop productivity. Drought stress causes in plants a set of morpho-anatomical, physiological and biochemical changes, mainly addressed to limit the loss of water by transpiration with the attempt to increase the plant water use efficiency. The stomata closure, one of the first consistent reactions observed under drought, results in a series of consequent physiological/biochemical adjustments aimed at balancing the photosynthetic process as well as at enhancing the plant defense barriers against drought-promoted stress (e.g., stimulation of antioxidant systems, accumulation of osmolytes and stimulation of aquaporin synthesis), all representing an attempt by the plant to overcome the unfavorable period of limited water availability. In view of the severe changes in water availability imposed by climate change factors and considering the increasing human population, it is therefore of outmost importance to highlight: (i) how plants react to drought; (ii) the mechanisms of tolerance exhibited by some species/cultivars; and (iii) the techniques aimed at increasing the tolerance of crop species against limited water availability. All these aspects are necessary to respond to the continuously increasing demand for food, which unfortunately parallels the loss of arable land due to changes in rainfall dynamics and prolonged period of drought provoked by climate change factors. This review summarizes the most updated findings on the impact of drought stress on plant morphological, biochemical and physiological features and highlights plant mechanisms of tolerance which could be exploited to increase the plant capability to survive under limited water availability. In addition, possible applicative strategies to help the plant in counteracting unfavorable drought periods are also discussed.

In the last few decades, the vast potential of nanomaterials for biomedical and healthcare applications has been extensively investigated. Several case studies demonstrated that nanomaterials can offer solutions to the current challenges of raw materials in the biomedical and healthcare fields. This review describes the different nanoparticles and nanostructured material synthesis approaches and presents some emerging biomedical, healthcare, and agro-food applications. This review focuses on various nanomaterial types (e.g., spherical, nanorods, nanotubes, nanosheets, nanofibers, core-shell, and mesoporous) that can be synthesized from different raw materials and their emerging applications in bioimaging, biosensing, drug delivery, tissue engineering, antimicrobial, and agro-foods. Depending on their morphology (e.g., size, aspect ratio, geometry, porosity), nanomaterials can be used as formulation modifiers, moisturizers, nanofillers, additives, membranes, and films. As toxicological assessment depends on sizes and morphologies, stringent regulation is needed from the testing of efficient nanomaterials dosages. The challenges and perspectives for an industrial breakthrough of nanomaterials are related to the optimization of production and processing conditions.

The correct prediction of heart disease can prevent life threats, and incorrect prediction can prove to be fatal at the same time. In this paper different machine learning algorithms and deep learning are applied to compare the results and analysis of the UCI Machine Learning Heart Disease dataset. The dataset consists of 14 main attributes used for performing the analysis. Various promising results are achieved and are validated using accuracy and confusion matrix. The dataset consists of some irrelevant features which are handled using Isolation Forest, and data are also normalized for getting better results. And how this study can be combined with some multimedia technology like mobile devices is also discussed. Using deep learning approach, 94.2% accuracy was obtained.

The most popular additive manufacturing (AM) technologies to produce titanium alloy parts are electron beam melting (EBM), selective laser melting (SLM) and directed energy deposition (DED). This investigation explores mainly these three techniques and compares these three methods comprehensively in terms of microstructure, tensile properties, porosity, surface roughness and residual stress based on the information available in the literature. It was found that the microstructure is affected by the highest temperature generated and the cooling rate which can be tailored by the input variables of the AM processes. The parts produced from EBM have strength comparable to that of conventionally fabricated counterparts. SLM and DED yield superior strength, which can be up to 25% higher than traditionally manufactured products. Due to the presence of larger tensile residual stress, surface roughness and porosity, AM fabricated parts have lower fatigue life compared to those of from traditional methods. EBM parts have slightly lower fracture toughness (i.e., lower fatigue life) than conventionally produced parts while SLM and DED have significantly lower fracture toughness. Annealing, hot isostatic pressing, stress relief and additional machining processes improve the characteristics of parts produced from AM. Ti–6Al–4V alloy parts fabricated via AM may have limited applications despite the high demands in aerospace or biomedical engineering. Since rapid product development using 3D printers leads to significant cost reductions more recently, it is expected that more opportunities may soon be available for the AM of titanium alloys with newer AM processes such as cold spray additive manufacturing (CSAM) and additive friction stir deposition (AFSD).

The Generative Pre-trained Transformer (GPT) represents a notable breakthrough in the domain of natural language processing, which is propelling us toward the development of machines that can understand and communicate using language in a manner that closely resembles that of humans. GPT is based on the transformer architecture, a deep neural network designed for natural language processing tasks. Due to their impressive performance on natural language processing tasks and ability to effectively converse, GPT have gained significant popularity among researchers and industrial communities, making them one of the most widely used and effective models in natural language processing and related fields, which motivated to conduct this review. This review provides a detailed overview of the GPT, including its architecture, working process, training procedures, enabling technologies, and its impact on various applications. In this review, we also explored the potential challenges and limitations of a GPT. Furthermore, we discuss potential solutions and future directions. Overall, this paper aims to provide a comprehensive understanding of GPT, its enabling technologies, their impact on various applications, emerging challenges, and potential solutions.

Breast cancer is the second leading cause of death for women worldwide. The heterogeneity of this disease presents a big challenge in its therapeutic management. However, recent advances in molecular biology and immunology enable to develop highly targeted therapies for many forms of breast cancer. The primary objective of targeted therapy is to inhibit a specific target/molecule that supports tumor progression. Ak strain transforming, cyclin-dependent kinases, poly (ADP-ribose) polymerase, and different growth factors have emerged as potential therapeutic targets for specific breast cancer subtypes. Many targeted drugs are currently undergoing clinical trials, and some have already received the FDA approval as monotherapy or in combination with other drugs for the treatment of different forms of breast cancer. However, the targeted drugs have yet to achieve therapeutic promise against triple-negative breast cancer (TNBC). In this aspect, immune therapy has come up as a promising therapeutic approach specifically for TNBC patients. Different immunotherapeutic modalities including immune-checkpoint blockade, vaccination, and adoptive cell transfer have been extensively studied in the clinical setting of breast cancer, especially in TNBC patients. The FDA has already approved some immune-checkpoint blockers in combination with chemotherapeutic drugs to treat TNBC and several trials are ongoing. This review provides an overview of clinical developments and recent advancements in targeted therapies and immunotherapies for breast cancer treatment. The successes, challenges, and prospects were critically discussed to portray their profound prospects.

For many years, conventional plastics are manufactured and used for packaging applications in different sectors. As the food industries are increasing, the demand for packaging material is also increasing. Plastics have transformed the food industry to higher levels; however, conventional petroleum-based plastics are non-degradable which has created severe ecological problems to the environment like a threat to aquatic life and degrading air quality. Biodegradable polymers or biopolymers emerged as an alternative approach for many industrial applications to control the risk caused by non-biodegradable plastic. According to the type of starting material, they have been categorized as polymers extracted from biomass, synthesized from monomers, and produced from microorganisms. The quality of biopolymers depends on the physical, mechanical, thermal, and barrier properties. The present review highlights the characteristics of various biopolymers and their blends, comparison of properties between non-biodegradable and biopolymers, the market potential for food packaging applications. The review also emphasizes different commercial forms like films, trays, bags, coatings, and foamed products for application as modified atmosphere packaging, active packaging, and edible packaging. Different issues affecting market growth like harmful products formed during production and consumer perception have also been discussed. Information on biopolymers is widely scattered over many sources, this article aims to provide an overview of biodegradable polymer packages for food applications.

Chromium (Cr) is an element naturally occurring in rocky soils and volcanic dust. It has been classified as a carcinogen agent according to the International Agency for Research on Cancer. Therefore, this metal needs an accurate understanding and thorough investigation in soil-plant systems. Due to its high solubility, Cr (VI) is regarded as a hazardous ion, which contaminates groundwater and can be transferred through the food chain. Cr also negatively impacts the growth of plants by impairing their essential metabolic processes. The toxic effects of Cr are correlated with the generation of reactive oxygen species (ROS), which cause oxidative stress in plants. The current review summarizes the understanding of Cr toxicity in plants via discussing the possible mechanisms involved in its uptake, translocation and sub-cellular distribution, along with its interference with the other plant metabolic processes such as chlorophyll biosynthesis, photosynthesis and plant defensive system.