LIVIVO - The Search Portal for Life Sciences

zur deutschen Oberfläche wechseln
Advanced search

Search results

Result 1 - 10 of total 33

Search options

  1. Article ; Online: Structural Perspectives in the Development of Novel EGFR Inhibitors for the Treatment of NSCLC.

    Makhija, Rahul / Sharma, Anushka / Dubey, Rahul / Asati, Vivek

    Mini reviews in medicinal chemistry

    2024  

    Abstract: Non-small cell Lung cancer (NSCLC) is the most common type of lung cancer, which is caused by high consumption of tobacco and smoking. It is an epithelial lung cancer that affects about 2.2 million people across the globe, according to International ... ...

    Abstract Non-small cell Lung cancer (NSCLC) is the most common type of lung cancer, which is caused by high consumption of tobacco and smoking. It is an epithelial lung cancer that affects about 2.2 million people across the globe, according to International Agency for Research on Cancer (IARC). Non-small cell lung cancer is a malignant tumor caused by EGFR mutation that occurs in the in-frame deletion of exon 19 and L858R point mutation in exon 21. Presently, clinically available inhibitors of EGFR (including erlotinib, lapatinib, gefitinib, selumetinib, etc.) are not specific and responsible for undesirable adverse effects. Moreover, to solve this problem search for newer EGFR inhibitors is the utmost need for the treatment and/or management of increasing lung cancer burden. The discovery of therapeutic agents that inhibit the specific target in tumorous cells, such as EGFR, is one of the successful strategies in treating many cancer therapies, including lung cancer. The exhaustive literature survey (2018-2023) has shown the importance of medicinally privileged pyrimidine derivatives together, fused and/or clubbed with other heterocyclic rings to design and develop novel EGFR inhibitors. Pyrimidine derivatives substituted with phenylamine, indole, pyrrole, piperazine, pyrazole, thiophene, pyridine and quinazoline derivatives substituted with phenylamine, pyrimidine, morpholine, pyrrole, dioxane, acrylamide, indole, pyridine, furan, pyrimidine, pyrazole etc. are privileged heterocyclic rings shown promising activity by inhibiting EGFR and TKIs. The present review summarizes the structure-activity relationship (SAR) and enzyme inhibitory activity, including IC50 values, percentage inhibition, and kinetic studies of potential compounds from various literature. The review also includes various aspects of molecular docking studies with compounds under clinical trials and patents filed on pyrimidine-based EGFR inhibitors in treating non-small cell lung cancer. The present review may benefit the medicinal chemist for developing novel compounds such as EGFR inhibitors.
    Language English
    Publishing date 2024-04-04
    Publishing country Netherlands
    Document type Journal Article
    ZDB-ID 2104081-3
    ISSN 1875-5607 ; 1389-5575
    ISSN (online) 1875-5607
    ISSN 1389-5575
    DOI 10.2174/0113895575296174240323172754
    Database MEDical Literature Analysis and Retrieval System OnLINE

    More links

    Kategorien

  2. Book ; Online: Power Quality Event Recognition and Classification Using an Online Sequential Extreme Learning Machine Network based on Wavelets

    Dubey, Rahul Kumar

    2022  

    Abstract: Reduced system dependability and higher maintenance costs may be the consequence of poor electric power quality, which can disturb normal equipment performance, speed up aging, and even cause outright failures. This study implements and tests a prototype ...

    Abstract Reduced system dependability and higher maintenance costs may be the consequence of poor electric power quality, which can disturb normal equipment performance, speed up aging, and even cause outright failures. This study implements and tests a prototype of an Online Sequential Extreme Learning Machine (OS-ELM) classifier based on wavelets for detecting power quality problems under transient conditions. In order to create the classifier, the OSELM-network model and the discrete wavelet transform (DWT) method are combined. First, discrete wavelet transform (DWT) multi-resolution analysis (MRA) was used to extract characteristics of the distorted signal at various resolutions. The OSELM then sorts the retrieved data by transient duration and energy features to determine the kind of disturbance. The suggested approach requires less memory space and processing time since it can minimize a large quantity of the distorted signal's characteristics without changing the signal's original quality. Several types of transient events were used to demonstrate the classifier's ability to detect and categorize various types of power disturbances, including sags, swells, momentary interruptions, oscillatory transients, harmonics, notches, spikes, flickers, sag swell, sag mi, sag harm, swell trans, sag spike, and swell spike.
    Keywords Electrical Engineering and Systems Science - Signal Processing ; Computer Science - Artificial Intelligence ; Computer Science - Machine Learning
    Subject code 006
    Publishing date 2022-12-27
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    More links

    Kategorien

  3. Article ; Online: Optimization of Extraction Conditions using Response Surface Methodology and HPTLC Fingerprinting Analysis of Indian Propolis

    Sankaran, Sandeep / Dubey, Rahul / Lohidasan, Sathiyanarayanan

    Journal of Biologically Active Products from Nature. 2023 Jan. 02, v. 13, no. 1 p.76-93

    2023  

    Abstract: The potential of Indian propolis as a suitable therapeutic agent is still to be explored to the fullest. As variation in the chemical composition across different geographical regions has been a major concern, it is, therefore, worthwhile to ... ...

    Abstract The potential of Indian propolis as a suitable therapeutic agent is still to be explored to the fullest. As variation in the chemical composition across different geographical regions has been a major concern, it is, therefore, worthwhile to systematically investigate, and assess the quality of Indian propolis and set nationalized standards. The propolis collected from three different regions were authenticated for the major plant source, followed by the evaluation of physicochemical properties. Different extraction methods were compared, with their influence on balsam content, polyphenol, and flavonoid content. The sample coded HAR using ultrasonication gave the highest extraction yield of 71.87%. Further, the process variables in the ultrasonication method (i.e. Amplitude, extraction time, the concentration of ethanol) at three levels were optimized using the Box-Behnken response design. The model was found significant with the concentration of ethanol having a maximum influence on the responses. The model was successfully verified by setting the amplitude at 48%, extraction time to 5.6 mins, and ethanol concentration to 87% v/v. The extraction efficiency of 83.86±1.17% was achieved with a substantial diminution of extraction time. The total phenolic, total flavonol, and total flavanone content of the optimized batch were 28.74±0.13 mgGAE/g, 4.66±0.78 mgQE/g, and 3.16±0.14 mgPE/g of propolis respectively. Further HPTLC fingerprint image of the optimized extract revealed the presence of quercetin, p-coumaric acid, kaempferol, chrysin, pinocembrin, and galangin.
    Keywords chemical composition ; chrysin ; ethanol ; experimental design ; flavanones ; kaempferol ; models ; p-coumaric acid ; polyphenols ; propolis ; quercetin ; response surface methodology ; therapeutics ; ultrasonic treatment ; Extraction ; HPTLC
    Language English
    Dates of publication 2023-0102
    Size p. 76-93.
    Publishing place Taylor & Francis
    Document type Article ; Online
    ISSN 2231-1874
    DOI 10.1080/22311866.2023.2185681
    Database NAL-Catalogue (AGRICOLA)

    More links

    Kategorien

  4. Article ; Online: Deciphering the multi-functional role of Indian propolis for the management of Alzheimer's disease by integrating LC-MS/MS, network pharmacology, molecular docking, and in-vitro studies.

    Sankaran, Sandeep / Dubey, Rahul / Gomatam, Anish / Chakor, Rishikesh / Kshirsagar, Ashwini / Lohidasan, Sathiyanarayanan

    Molecular diversity

    2024  

    Abstract: The conventional one-drug-one-disease theory has lost its sheen in multigenic diseases such as Alzheimer's disease (AD). Propolis, a honeybee-derived product has ethnopharmacological evidence of antioxidant, anti-inflammatory, antimicrobial and ... ...

    Abstract The conventional one-drug-one-disease theory has lost its sheen in multigenic diseases such as Alzheimer's disease (AD). Propolis, a honeybee-derived product has ethnopharmacological evidence of antioxidant, anti-inflammatory, antimicrobial and neuroprotective properties. However, the chemical composition is complex and highly variable geographically. So, to leverage the potential of propolis as an effective treatment modality, it is essential to understand the role of each phytochemical in the AD pathophysiology. Therefore, the present study was aimed at investigating the anti-Alzheimer effect of bioactive in Indian propolis (IP) by combining LC-MS/MS fingerprinting, with network-based analysis and experimental validation. First, phytoconstituents in IP extract were identified using an in-house LC-MS/MS method. The drug likeness and toxicity were assessed, followed by identification of AD targets. The constituent-target-gene network was then constructed along with protein-protein interactions, gene pathway, ontology, and enrichment analysis. LC-MS/MS analysis identified 16 known metabolites with druggable properties except for luteolin-5-methyl ether. The network pharmacology-based analysis revealed that the hit propolis constituents were majorly flavonoids, whereas the main AD-associated targets were MAOB, ESR1, BACE1, AChE, CDK5, GSK3β, and PTGS2. A total of 18 gene pathways were identified to be associated, with the pathways related to AD among the topmost enriched. Molecular docking analysis against top AD targets resulted in suitable binding interactions at the active site of target proteins. Further, the protective role of IP in AD was confirmed with cell-line studies on PC-12, in situ AChE inhibition, and antioxidant assays.
    Language English
    Publishing date 2024-03-11
    Publishing country Netherlands
    Document type Journal Article
    ZDB-ID 1376507-3
    ISSN 1573-501X ; 1381-1991
    ISSN (online) 1573-501X
    ISSN 1381-1991
    DOI 10.1007/s11030-024-10818-8
    Database MEDical Literature Analysis and Retrieval System OnLINE

    More links

    Kategorien

  5. Article ; Online: Assessment of structural and activity-related contributions of various PIM-1 kinase inhibitors in the treatment of leukemia and prostate cancer.

    Sharma, Anushka / Dubey, Rahul / Asati, Vikas / Baweja, Gurkaran Singh / Gupta, Shankar / Asati, Vivek

    Molecular diversity

    2024  

    Abstract: One of the most perilous illnesses in the world is cancer. The cancer may be associated with the mutation of different genes inside the body. The PIM kinase, also known as the serine/threonine kinase, plays a critical role in the biology of different ... ...

    Abstract One of the most perilous illnesses in the world is cancer. The cancer may be associated with the mutation of different genes inside the body. The PIM kinase, also known as the serine/threonine kinase, plays a critical role in the biology of different kinds of cancer. They are widely distributed and associated with several biological processes, including cell division, proliferation, and death. Aberration of PIM-1 kinase is found in varieties of cancer. Prostate cancer and leukemia can both be effectively treated with PIM-1 kinase inhibitors. There are several potent compounds that have been explored in this review based on heterocyclic compounds for the treatment of prostate cancer and leukemia that have strong effects on the suppression of PIM-1 kinase. The present review summarizes the PIM-1 kinase pathway, their inhibitors under clinical trial, related patents, and SAR studies of several monocyclic, bicyclic, and polycyclic compounds. The study related to their molecular interactions with receptors is also included in the present manuscript. The study may be beneficial to scientists for the development of novel compounds as PIM-1 inhibitors in the treatment of prostate cancer and leukemia.
    Language English
    Publishing date 2024-04-20
    Publishing country Netherlands
    Document type Journal Article ; Review
    ZDB-ID 1376507-3
    ISSN 1573-501X ; 1381-1991
    ISSN (online) 1573-501X
    ISSN 1381-1991
    DOI 10.1007/s11030-023-10795-4
    Database MEDical Literature Analysis and Retrieval System OnLINE

    More links

    Kategorien

  6. Article ; Online: A comprehensive review of small molecules targeting PI3K pathway: Exploring the structural development for the treatment of breast cancer.

    Dubey, Rahul / Sharma, Anushka / Gupta, Shankar / Gupta, G D / Asati, Vivek

    Bioorganic chemistry

    2023  Volume 143, Page(s) 107077

    Abstract: Cancer stands as one of the deadliest diseases, ranking second in terms of its global impact. Despite the presence of numerous compelling theories concerning its origins, none have succeeded in fully elucidating the intricate nature of this ailment. ... ...

    Abstract Cancer stands as one of the deadliest diseases, ranking second in terms of its global impact. Despite the presence of numerous compelling theories concerning its origins, none have succeeded in fully elucidating the intricate nature of this ailment. Among the prevailing concerns in today's world, breast cancer proliferation remains a significant issue, particularly affecting females. The abnormal proliferation of the PI3K pathway emerges as a prominent driver of breast cancer, underscoring its role in cellular survival and proliferation. Consequently, targeting this pathway has emerged as a leading strategy in breast cancer therapeutics. Within this context, the present article explores the current landscape of anti-tumour drug development, focusing on structural activity relationships (SAR) in PI3K targeting breast cancer treatment. Notably, certain moieties like triazines, pyrimidine, quinazoline, quinoline, and pyridoxine have been explored as potential PI3K inhibitors for combating breast cancer. Various heterocyclic small molecules are undergoing clinical trials, such as Alpelisib, the first orally available FDA-approved drug targeting PI3K; others include buparlisib, pictilisib, and taselisib, which inhibit class I PI3K. These drugs are used for the treatment of breast cancer but still have various side effects with their high cost. Therefore, the primary goal of this review is to include all current advances in the development of anticancer medicines that target PI3K over-activation in the treatment of breast cancer.
    MeSH term(s) Female ; Humans ; Antineoplastic Agents/chemistry ; Antineoplastic Agents/pharmacology ; Antineoplastic Combined Chemotherapy Protocols/therapeutic use ; Breast Neoplasms/drug therapy ; Phosphatidylinositol 3-Kinases/drug effects ; Phosphoinositide-3 Kinase Inhibitors/pharmacology
    Chemical Substances Antineoplastic Agents ; Phosphatidylinositol 3-Kinases (EC 2.7.1.-) ; Phosphoinositide-3 Kinase Inhibitors ; Alpelisib (08W5N2C97Q) ; NVP-BKM120 ; 2-(1H-indazol-4-yl)-6-(4-methanesulfonylpiperazin-1-ylmethyl)-4-morpholin-4-ylthieno(3,2-d)pyrimidine ; 2-(3-(2-(1-isopropyl-3-methyl-1H-1,2-4-triazol-5-yl)-5,6-dihydrobenzo(f)imidazo(1,2-d)(1,4)oxazepin-9-yl)-1H-pyrazol-1-yl)-2-methylpropanamide
    Language English
    Publishing date 2023-12-30
    Publishing country United States
    Document type Journal Article ; Review
    ZDB-ID 120080-x
    ISSN 1090-2120 ; 0045-2068
    ISSN (online) 1090-2120
    ISSN 0045-2068
    DOI 10.1016/j.bioorg.2023.107077
    Database MEDical Literature Analysis and Retrieval System OnLINE

    More links

    Kategorien

  7. Book ; Online: VORRT-COLREGs

    Dubey, Rahul / Louis, Sushil J

    A Hybrid Velocity Obstacles and RRT Based COLREGs-Compliant Path Planner for Autonomous Surface Vessels

    2021  

    Abstract: This paper presents VORRT-COLREGs, a hybrid technique that combines velocity obstacles (VO) and rapidly-exploring random trees (RRT) to generate safe trajectories for autonomous surface vessels (ASVs) while following nautical rules of the road. RRT ... ...

    Abstract This paper presents VORRT-COLREGs, a hybrid technique that combines velocity obstacles (VO) and rapidly-exploring random trees (RRT) to generate safe trajectories for autonomous surface vessels (ASVs) while following nautical rules of the road. RRT generates a set of way points and the velocity obstacles method ensures safe travel between way points. We also ensure that the actions of ASVs do not violate maritime collision guidelines. Earlier work has used RRT and VO separately to generate paths for ASVs. However, RRT does not handle highly dynamic situations well and and VO seems most suitable as a local path planner. Combining both approaches, VORRT-COLREGs is a global path planner that uses a joint forward simulation to ensure that generated paths remain valid and collision free as the situation changes. Experiments were conducted in different types of collision scenarios and with different numbers of ASVs. Results show that VORRT-COLREGS generated collision regulations (COLREGs) complaint paths in open ocean scenarios. Furthermore, VORRT-COLREGS successfully generated compliant paths within traffic separation schemes. These results show the applicability of our technique for generating paths for ASVs in different collision scenarios. To the best of our knowledge, this is the first work that combines velocity obstacles and RRT to produce safe and COLREGs complaint path for ASVs.

    Comment: Accepted in IEEE OCEANS 2021
    Keywords Computer Science - Robotics ; Computer Science - Artificial Intelligence
    Subject code 629
    Publishing date 2021-09-02
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    More links

    Kategorien

  8. Book ; Online: The Integrity of Machine Learning Algorithms against Software Defect Prediction

    and, Param Khakhar / Dubey, Rahul Kumar

    2020  

    Abstract: The increased computerization in recent years has resulted in the production of a variety of different software, however measures need to be taken to ensure that the produced software isn't defective. Many researchers have worked in this area and have ... ...

    Abstract The increased computerization in recent years has resulted in the production of a variety of different software, however measures need to be taken to ensure that the produced software isn't defective. Many researchers have worked in this area and have developed different Machine Learning-based approaches that predict whether the software is defective or not. This issue can't be resolved simply by using different conventional classifiers because the dataset is highly imbalanced i.e the number of defective samples detected is extremely less as compared to the number of non-defective samples. Therefore, to address this issue, certain sophisticated methods are required. The different methods developed by the researchers can be broadly classified into Resampling based methods, Cost-sensitive learning-based methods, and Ensemble Learning. Among these methods. This report analyses the performance of the Online Sequential Extreme Learning Machine (OS-ELM) proposed by Liang et.al. against several classifiers such as Logistic Regression, Support Vector Machine, Random Forest, and Na\"ive Bayes after oversampling the data. OS-ELM trains faster than conventional deep neural networks and it always converges to the globally optimal solution. A comparison is performed on the original dataset as well as the over-sampled data set. The oversampling technique used is Cluster-based Over-Sampling with Noise Filtering. This technique is better than several state-of-the-art techniques for oversampling. The analysis is carried out on 3 projects KC1, PC4 and PC3 carried out by the NASA group. The metrics used for measurement are recall and balanced accuracy. The results are higher for OS-ELM as compared to other classifiers in both scenarios.

    Comment: 7 pages, 4 figures
    Keywords Computer Science - Software Engineering ; Computer Science - Machine Learning ; Statistics - Machine Learning
    Subject code 006
    Publishing date 2020-09-05
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    More links

    Kategorien

  9. Book ; Online: Meta-Embeddings for Natural Language Inference and Semantic Similarity tasks

    R, Shree Charran / Dubey, Rahul Kumar

    2020  

    Abstract: Word Representations form the core component for almost all advanced Natural Language Processing (NLP) applications such as text mining, question-answering, and text summarization, etc. Over the last two decades, immense research is conducted to come up ... ...

    Abstract Word Representations form the core component for almost all advanced Natural Language Processing (NLP) applications such as text mining, question-answering, and text summarization, etc. Over the last two decades, immense research is conducted to come up with one single model to solve all major NLP tasks. The major problem currently is that there are a plethora of choices for different NLP tasks. Thus for NLP practitioners, the task of choosing the right model to be used itself becomes a challenge. Thus combining multiple pre-trained word embeddings and forming meta embeddings has become a viable approach to improve tackle NLP tasks. Meta embedding learning is a process of producing a single word embedding from a given set of pre-trained input word embeddings. In this paper, we propose to use Meta Embedding derived from few State-of-the-Art (SOTA) models to efficiently tackle mainstream NLP tasks like classification, semantic relatedness, and text similarity. We have compared both ensemble and dynamic variants to identify an efficient approach. The results obtained show that even the best State-of-the-Art models can be bettered. Thus showing us that meta-embeddings can be used for several NLP tasks by harnessing the power of several individual representations.
    Keywords Computer Science - Computation and Language ; Computer Science - Artificial Intelligence ; Computer Science - Information Retrieval ; Computer Science - Machine Learning
    Subject code 006
    Publishing date 2020-12-01
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    More links

    Kategorien

  10. Book ; Online: Deep Learning Based Hybrid Models for Prediction of COVID-19 using Chest X-Ray

    R, Shree Charran / Dubey, Rahul Kumar

    2020  

    Abstract: COVID-19 has ended up being the greatest pandemic to come to pass for on humanity in the last century. It has influenced all parts of present day life. The best way to confine its spread is the early and exact finding of infected patients. Clinical ... ...

    Abstract COVID-19 has ended up being the greatest pandemic to come to pass for on humanity in the last century. It has influenced all parts of present day life. The best way to confine its spread is the early and exact finding of infected patients. Clinical imaging strategies like Chest X-ray imaging helps specialists to assess the degree of spread of infection. In any case, the way that COVID-19 side effects imitate those of conventional Pneumonia brings few issues utilizing of Chest Xrays for its prediction accurately. In this investigation, we attempt to assemble 4 ways to deal with characterize between COVID-19 Pneumonia, NON-COVID-19 Pneumonia, and an Healthy- Normal Chest X-Ray images. Considering the low accessibility of genuine named Chest X-Ray images, we incorporated combinations of pre-trained models and data augmentation methods to improve the quality of predictions. Our best model has achieved an accuracy of 99.5216%. More importantly, the hybrid did not predict a False Negative Normal (i.e. infected case predicted as normal) making it the most attractive feature of the study.
    Keywords covid19
    Publisher Institute of Electrical and Electronics Engineers (IEEE)
    Publishing country us
    Document type Book ; Online
    DOI 10.36227/techrxiv.12839204
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    More links

    Kategorien

To top