Search

Your search keyword '"Showkat Mir"' showing total 9 results
Start Over Author "Showkat Mir"
9 results on '"Showkat Mir"'

2. Biopesticides Handbook

Author

Leo M.L. Nollet, Showkat Mir, Leo M.L. Nollet, and Showkat Mir

Subjects
Natural pesticides
Abstract

Biopesticides have a great influence in sustainable agriculture, and their use in commercial farming ensures environmental protection, qualitative products, and effective use of resources. The second edition of Biopesticides Handbook is fully updated and includes five new chapters on microbial, biochemical, and RNAi pesticides. It details the benefits of biopesticides along the food chain, offering a full spectrum of the range of organisms and organic products that may be used in the biological control of pests. It discusses the uses and abuses of biopesticides, their positive and negative consequences, as well as more recent advances and the best mode of action to improve environmental safety.FEATURES Thoroughly updated, this edition explores not only the benefits but also all aspects of biopesticides Includes new chapters on the uses of biochemical and microbial pesticides and plant-incorporated protectants Discusses the new field of RNAi pesticides Provides information on insect growth regulators and allelochemicals Introduces a new chapter on the uses of biopesticides in food and medicinal crops This book is intended for professionals, researchers, academics, and postgraduate students with experience in fields such as chemistry, biochemistry, environmental sciences, ecology, and agriculture, as well as those invested in the supply chain of agricultural products, such as farmers, growers, and other stakeholders.

Published
2024

3. Molecular Modeling of Novel Fluorophoric Thiazolo- [2, 3-B] Quinazolinones to Study Epidermal Growth Factor Receptor Tyrosine Kinase Inhibition Potency

Author

Binata Nayak, Mukesh Kumar Raval, Ajay Kumar Behera, Iswar Baitharu, Pranab Kishor Mohapatra, Prajna Mohanta, Kumar Sambhav Chopdar, Ganesh Chandra Dash, and Showkat Mir

Abstract

Epidermal growth factor receptor tyrosine kinase (EGFR-TK) is one of the key regulators that exhibit pivotal role in proliferation of cancer cell. Quinazolinones are studiedly widely as effective EGFR-TK inhibitor because of their higher affinity to bind with adenosine triphosphate (ATP) binding site of receptor tyrosine kinases. However, their toxicity due to non-specific binding to tyrosine kinase in non-cancerous normally dividing cells of the body limits its applicability as a cancer therapeutics. In the present investigation a series of thirty-four novel synthesized thiazolo- [2, 3-b] quinazolinones were studied in silico as EGFR-TK inhibitors. All the thirty-four compounds were screened against EGFR-TK domain using multiple software’s (AutoDock Vina, Argus Lab, YASARA, and MOE). The interactions of the ligands with amino acid residues, namely, Lys721, Met769 and Asp831 of the active site were through the functional groups on aryl substituents at position 3 and 5 of the thiazolo- [2, 3-b] quinazolinone scaffold. The methyl substituents at position 8 of the ligands had prominent hydrophobic interactions in the active site cavity of EGFR-TK domain. The compounds 5ab, 5aq, and 5bq were predicted to be non-toxic and drug-like by in silico ADMET investigations. These compounds were considered for further investigation due to their non-toxicity and higher docking score ranking in different docking methods. The molecular dynamics (MD) simulation for 100 ns of docked complexes revealed the stability of these compounds. The binding free energy determined using Molecular Mechanics Generalized Born Model and Solvent Accessibility (MM-GBSA) method indicate that thiazolo- [2, 3-b] quinazolinone has high inhibitory efficacy similar to the standard drug, erlotinib (5ab - 22.45, 5aq -22.23, 5bq -20.76, and erlotinib -24.11 kcal/mol). In silico studies and MD simulations indicated that compounds (5ab, 5aq and 5bq) could be potential EGFR-TK inhibitors and require further validation as cancer therapeutics using carcinoma cell lines.

Published
2021
Full Text
View/download PDF

4. Chemical Methods for Control of Mosquito Vector

Author

Ajay Kumar Behera, Iswar Baitharu, Sabita Shroff, Binata Naik, and Showkat Mir

Subjects
Transmission (medicine), Yellow fever, medicine.disease, medicine.disease_cause, Filariasis, Dengue fever, Mosquito control, Geography, Vector (epidemiology), Environmental health, parasitic diseases, medicine, Chikungunya, Malaria
Abstract

Vector-borne diseases take a big toll of life each year in most of the tropical and subtropical countries including India. Among the number of insect species that act as a vector, mosquitos play a critical role in the transmission of numerous deadly diseases. Some of the major mosquito-borne diseases that incur a great economic loss to the public include malaria, yellow fever, dengue fever, chikungunya, filariasis, and encephalitis. Malaria alone affects some 3.2 billion people living in 117 endemic countries and has been reported to cause over 1 million deaths annually. As per the Indian Council of Medical Research report, ~1000 people lose their lives each year due to malaria infection out of 2 million confirmed cases. However, WHO reports estimate much higher annual death in India of about 15 million confirmed cases and 20,000 deaths. As per WHO reports, India is the major hub of malaria infection contributing 77% of total malaria in Southeast Asia. Worldwide death toll because of these vector-borne diseases especially that transmitted by a mosquito is very high in low-income countries despite the availability of effective curative measures. Controlling and managing the mosquito population below the economic injury level is the most preferred preventive strategies in vector-borne disease control. Initially, environmental management was the major tool in eradicating mosquito populations in a locality which though was sustainable barely effective in controlling the mosquito population in various set up resulting in epidemics. The necessity to have an effective and rapid vector control measure was achieved with the discovery of DDT during World War II that was miraculous in eliminating the mosquito population rapidly. The use of chemicals in vector control progressed rapidly thereafter resulting in the development of several classes of chemicals in the market. Some of these chemicals are natural such as pyrethrin, however, most of them are synthetic chemicals that are non-biodegradable and have severe negative environmental impacts. The use of chemicals based on synthetic insecticides is the first line control measure for mosquitoes all over the world now. However, the development of resistance against these insecticides in the mosquito population has recently forced the scientists and clinicians to look for effective alternatives that could offer lasting solutions to this age-old long battle against insects. The present chapter attempts to give an overview of the chemicals species used for mosquito control and their impact on health and the environment.

Published
2020
Full Text
View/download PDF

5. Brachial artery pseudo-aneurysm in intravenous drug abuser: a rare case report

Author

Showkat Mir, Naveed Nabi, and Firdous A Beigh

Subjects
medicine.medical_specialty, Intravenous drug, business.industry, medicine.artery, Rare case, medicine, Brachial artery, Pseudo aneurysm, business, Surgery
Abstract

Brachial artery pseudo-aneurysm (BAP) is a rare entity because pseudo-aneurysms are common in lower limbs.1 Usual causes of BAP are humeral fractures, iatrogenic causes (repeated punctures for sample collection, following construction of Brachio-cephalic fistula) or some genetic causes like Ehler Danlos syndrome (EDS). This case has been reported to highlight the importance of considering all the differential diagnosis while evaluation of an upper limb swelling especially in the cubital fossa and due consideration of history of any IV drug abuse.

Published
2019
Full Text
View/download PDF

6. Machine learning driven prediction of cerebrospinal fluid rhinorrhoea following endonasal skull base surgery: A multicentre prospective observational study

Author

CRANIAL Consortium, Adrito Das, Danyal Z. Khan, Danail Stoyanov, Hani J. Marcus, Soham Bandyopadhyay, Benjamin E. Schroeder, Vikesh Patel, Alice O’Donnell, Neurology and Neurosurgery Interest Group, British Neurosurgical Trainee Research Collaborative, Anastasios Giamouriadis, Pragnesh Bhatt, Bhaskar Ram, Adithya Varma, Philip Weir, Brendan Hanna, Theodore C. Hirst, Patrick McAleavey, Alessandro Paluzzi, Georgios Tsermoulas, Shahzada Ahmed, Wai Cheong Soon, Yasir Arafat Chowdhury, Suhaib Abualsaud, Shumail Mahmood, Paresh Naik, Zohra Haiderkhan, Rafid Al-Mahfoudh, Andrea Perera, Mircea Rus, Adam Williams, Charles Hand, Kumar Abhinav, Cristina Cernei, Aiman Dilnawaz, Richard Mannion, Thomas Santarius, James Tysome, Rishi Sharma, Angelos G. Kolias, Neil Donnelly, Ashwin Venkatesh, Caroline Hayhurst, Amr Mohamed, Benjamin Stew, Joseph Merola, Setthasorn Zhi Yang, Mahmoud Kamel, Mohammad Habibullah Khan, Sahibzada Abrar, Christopher Mckeon, Daniel McSweeney, Mohsen Javadpour, Peter Lacy, Daniel Murray, Elena Roman, Kismet Hossain-Ibrahim, David Bennett, Nathan McSorley, Adam Hounat, Patrick Statham, Mark Hughes, Alhafidz Hamdan, Caroline Scott, Jigi Moudgil-Joshi, Anuj Bahl, Anna Bjornson, Daniel Gatt, Nick Phillips, Neeraj Kalra, Melissa Bautista, Seerat Shirazi, Catherine E. Gilkes, Christopher P. Millward, Ahmad MS. Ali, Dimitris Paraskevopoulos, Jarnail Bal, Samir Matloob, Rhannon Lobo, Nigel Mendoza, Ramesh Nair, Arthur Dalton, Adarsh Nadig, Lucas Hernandez, Nick Thomas, Eleni Maratos, Jonathan Shapey, Sinan Al-Barazi, Asfand Baig Mirza, Mohamed Okasha, Prabhjot Singh Malhotra, Razna Ahmed, Neil L. Dorward, Joan Grieve, Parag Sayal, David Choi, Ivan Cabrilo, Hugo Layard Horsfall, Jonathan Pollock, Alireza Shoakazemi, Oscar Maccormac, Guru N K. Amirthalingam, Andrew Martin, Simon Stapleton, Florence Hogg, Daniel Richardson, Kanna Gnanalingham, Omar Pathmanaban, Daniel M. Fountain, Raj Bhalla, Cathal J. Hannan, Annabel Chadwick, Alistair Jenkins, Claire Nicholson, Syed Shumon, Mohamed Youssef, Callum Allison, Graham Dow, Iain Robertson, Laurence Johann Glancz, Murugan Sitaraman, Ashwin Kumaria, Ananyo Bagchi, Simon Cudlip, Jane Halliday, Rory J. Piper, Alexandros Boukas, Meriem Amarouche, Damjan Veljanoski, Samiul Muquit, Ellie Edlmann, Haritha Maripi, Yi Wang, Mehnaz Hossain, Andrew Alalade, Syed Maroof, Pradnya Patkar, Saurabh Sinha, Showkat Mirz, Duncan Henderson, Mohammad Saud Khan, Nijaguna Mathad, Jonathan Hempenstall, Difei Wang, Pavan Marwaha, Simon Shaw, Georgios Solomou, and Alina Shrestha

Subjects
cerebrospinal fluid leak, cerebrospinal fluid rhinorrhoea, CSF, endoscopic endonasal, skull base surgery, machine learning - ML, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

BackgroundCerebrospinal fluid rhinorrhoea (CSFR) is a common complication following endonasal skull base surgery, a technique that is fundamental to the treatment of pituitary adenomas and many other skull base tumours. The CRANIAL study explored CSFR incidence and related risk factors, particularly skull base repair techniques, via a multicentre prospective observational study. We sought to use machine learning to leverage this complex multicentre dataset for CSFR prediction and risk factor analysis.MethodsA dataset of 865 cases - 725 transsphenoidal approach (TSA) and 140 expanded endonasal approach (EEA) - with cerebrospinal fluid rhinorrhoea as the primary outcome, was used. Relevant variables were extracted from the data, and prediction variables were divided into two categories, preoperative risk factors; and repair techniques, with 6 and 11 variables respectively. Three types of machine learning models were developed in order to predict CSFR: logistic regression (LR); decision tree (DT); and neural network (NN). Models were validated using 5-fold cross-validation, compared via their area under the curve (AUC) evaluation metric, and key prediction variables were identified using their Shapley additive explanations (SHAP) score.ResultsCSFR rates were 3.9% (28/725) for the transsphenoidal approach and 7.1% (10/140) for the expanded endonasal approach. NNs outperformed LR and DT for CSFR prediction, with a mean AUC of 0.80 (0.70-0.90) for TSA and 0.78 (0.60-0.96) for EEA, when all risk factor and intraoperative repair data were integrated into the model. The presence of intraoperative CSF leak was the most prominent risk factor for CSFR. Elevated BMI and revision surgery were also associated with CSFR for the transsphenoidal approach. CSF diversion and gasket sealing appear to be strong predictors of the absence of CSFR for both approaches.ConclusionNeural networks are effective at predicting CSFR and uncovering key CSFR predictors in patients following endonasal skull base surgery, outperforming traditional statistical methods. These models will be improved further with larger and more granular datasets, improved NN architecture, and external validation. In the future, such predictive models could be used to assist surgical decision-making and support more individualised patient counselling.

Published
2023
Full Text
View/download PDF

7. CSF rhinorrhoea after endonasal intervention to the skull base (CRANIAL): A multicentre prospective observational study

Author

CRANIAL Consortium, Danyal Z Khan, Hani J Marcus, Soham Bandyopadhyay, Benjamin E Schroeder, Vikesh Patel, Alice O’Donnell, Neurology and Neurosurgery Interest Group, British Neurosurgical Trainee Research Collaborative, Anastasios Giamouriadis, Pragnesh Bhatt, Bhaskar Ram, Adithya Varma, Philip Weir, Brendan Hanna, Theodore C Hirst, Patrick McAleavey, Alessandro Paluzzi, Georgios Tsermoulas, Shahzada Ahmed, Wai Cheong Soon, Yasir Arafat Chowdhury, Suhaib Abualsaud, Shumail Mahmood, Paresh Naik, Zohra Haiderkhan, Rafid Al-Mahfoudh, Andrea Perera, Mircea Rus, Adam Williams, Charles Hand, Kumar Abhinav, Cristina Cernei, Aiman Dilnawaz, Richard Mannion, Thomas Santarius, James Tysome, Rishi Sharma, Angelos G Kolias, Neil Donnelly, Ashwin Venkatesh, Caroline Hayhurst, Amr Mohamed, Benjamin Stew, Joseph Merola, Setthasorn Zhi Yang Ooi, Mahmoud Kamel, Mohammad Habibullah Khan, Sahibzada Abrar, Christopher Mckeon, Daniel McSweeney, Mohsen Javadpour, Peter Lacy, Daniel Murray, Elena Roman, Kismet Hossain-Ibrahim, Peter Ross, David Bennett, Nathan McSorley, Adam Hounat, Patrick Statham, Mark Hughes, Alhafidz Hamdan, Caroline Scott, Jigi Moudgil-Joshi, Anuj Bahl, Anna Bjornson, Daniel Gatt, Nick Phillips, Neeraj Kalra, Melissa Bautista, Seerat Shirazi, Catherine E Gilkes, Christopher P Millward, Ahmad MS Ali, Dimitris Paraskevopoulos, Jarnail Bal, Samir Matloob, Rhannon Lobo, Nigel Mendoza, Ramesh Nair, Arthur Dalton, Adarsh Nadig, Lucas Hernandez, Nick Thomas, Eleni Maratos, Jonathan Shapey, Sinan Al-Barazi, Asfand Baig Mirza, Mohamed Okasha, Prabhjot Singh Malhotra, Razna Ahmed, Neil L Dorward, Joan Grieve, Parag Sayal, David Choi, Ivan Cabrilo, Hugo Layard Horsfall, Jonathan Pollock, Alireza Shoakazemi, Oscar Maccormac, Guru N K Amirthalingam, Andrew Martin, Simon Stapleton, Florence Hogg, Daniel Richardson, Kanna Gnanalingham, Omar Pathmanaban, Daniel M Fountain, Raj Bhalla, Cathal J Hannan, Annabel Chadwick, Alistair Jenkins, Claire Nicholson, Syed Shumon, Mohamed Youssef, Callum Allison, Graham Dow, Iain Robertson, Laurence Johann Glancz, Murugan Sitaraman, Ashwin Kumaria, Ananyo Bagchi, Simon Cudlip, Jane Halliday, Rory J Piper, Alexandros Boukas, Meriem Amarouche, Damjan Veljanoski, Samiul Muquit, Ellie Edlmann, Haritha Maripi, Yi Wang, Mehnaz Hossain, Andrew Alalade, Syed Maroof, Pradnya Patkar, Saurabh Sinha, Showkat Mirza, Duncan Henderson, Mohammad Saud Khan, Nijaguna Mathad, Jonathan Hempenstall, Difei Wang, Department of Neurosurgery, Pavan Marwaha, Simon Shaw, Georgios Solomou, Alina Shrestha, Andrew Fraser, Theodore Hirst, Yasir Chowdhury, Sobiya Bilal, Jack Wildman, Priya Babu, Cian Carey, Renitha Reddi Bathuni, Joseph Nathaniel Brennan, Howra Ktayen, Sandhya T Trichinopoly, Danyal Khan, Seun Sobawale, Amir Suliman, Rory Piper, Will Owen, Afaq Sartaj, Edward Goacher, Euan Strachan, and Giorgios Solomou

Subjects
cerebrospinal fluid rhinorrhoea, CSF, EEA, endoscopic endonasal, cerebrospinal fluid leak, skull base surgery, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

ObjectiveDespite progress in endonasal skull-base neurosurgery, cerebrospinal fluid (CSF) rhinorrhoea remains common and significant. The CRANIAL study sought to determine 1) the scope of skull-base repair methods used, and 2) corresponding rates of postoperative CSF rhinorrhoea in the endonasal transsphenoidal approach (TSA) and the expanded endonasal approach (EEA) for skull-base tumors.MethodsA prospective observational cohort study of 30 centres performing endonasal skull-base neurosurgery in the UK and Ireland (representing 91% of adult units). Patients were identified for 6 months and followed up for 6 months. Data collection and analysis was guided by our published protocol and pilot studies. Descriptive statistics, univariate and multivariable logistic regression models were used for analysis.ResultsA total of 866 patients were included - 726 TSA (84%) and 140 EEA (16%). There was significant heterogeneity in repair protocols across centres. In TSA cases, nasal packing (519/726, 72%), tissue glues (474/726, 65%) and hemostatic agents (439/726, 61%) were the most common skull base repair techniques. Comparatively, pedicled flaps (90/140, 64%), CSF diversion (38/140, 27%), buttresses (17/140, 12%) and gasket sealing (11/140, 9%) were more commonly used in EEA cases. CSF rhinorrhoea (biochemically confirmed or requiring re-operation) occurred in 3.9% of TSA (28/726) and 7.1% of EEA (10/140) cases. A significant number of patients with CSF rhinorrhoea (15/38, 39%) occurred when no intraoperative CSF leak was reported. On multivariate analysis, there may be marginal benefits with using tissue glues in TSA (OR: 0.2, CI: 0.1-0.7, p

Published
2023
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results