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Article ; Online: Epigenetic Features in Newborns Associated with Preadolescence Lung Function and Asthma Acquisition during Adolescence.

Abrar, Mohammad Nahian Ferdous / Jiang, Yu / Zhang, Hongmei / Li, Liang / Arshad, Hasan

Epigenomes

2024 Volume 8, Issue 2

Abstract: The association between newborn DNA methylation (DNAm) and asthma acquisition (AA) during adolescence has been suggested. Lung function (LF) has been shown to be associated with asthma risk and its severity. However, the role of LF in the associations ... ...

Abstract	The association between newborn DNA methylation (DNAm) and asthma acquisition (AA) during adolescence has been suggested. Lung function (LF) has been shown to be associated with asthma risk and its severity. However, the role of LF in the associations between DNAm and AA is unclear, and it is also unknown whether the association between DNAm and AA is consistent with that between DNAm and LF. We address this question through assessing newborn epigenetic features of preadolescence LF and of AA during adolescence, along with their biological pathways and processes. Our study's primary medical significance lies in advancing the understanding of asthma's early life origins. By investigating epigenetic markers in newborns and their association with lung function in preadolescence, we aim to uncover potential early biomarkers of asthma risk. This could facilitate earlier detection and intervention strategies. Additionally, exploring biological pathways linking early lung function to later asthma development can offer insights into the disease's pathogenesis, potentially leading to novel therapeutic targets. Methods: The study was based on the Isle of Wight Birth cohort (IOWBC). Female subjects with DNAm data at birth and with no asthma at age 10 years were included (n = 249). The R package ttScreening was applied to identify CpGs potentially associated with AA from 10 to 18 years and with LF at age 10 (FEV1, FVC, and FEV1/FVC), respectively. Agreement in identified CpGs between AA and LF was examined, along with their biological pathways and processes via the R function gometh. We tested the findings in an independent cohort, the Avon Longitudinal Study of Parents and Children (ALSPAC), to examine overall replicability. Results: In IOWBC, 292 CpGs were detected with DNAm associated with AA and 1517 unique CpGs for LF (514 for FEV1, 436 for FVC, 408 for FEV1/FVC), with one overlapping CpG, cg23642632 ( Conclusions: The present study suggests that FEV1, FVC, and FEV1/FVC (as objective measures of LF) and AA (incidence of asthma) are likely to have their own specific epigenetic features and biological pathways at birth. More replications are desirable to fully understand the complexity between DNAm, lung function, and asthma acquisition.
Language	English
Publishing date	2024-03-22
Publishing country	Switzerland
Document type	Journal Article
ISSN	2075-4655
ISSN (online)	2075-4655
DOI	10.3390/epigenomes8020012
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Article ; Online: Risk factors for maxillary impacted canine-linked severe lateral incisor root resorption.

Kumar, Mukesh / Goyal, Manish / Kaur, Amandeep / Abrar, Mohammad

American journal of orthodontics and dentofacial orthopedics : official publication of the American Association of Orthodontists, its constituent societies, and the American Board of Orthodontics

2021 Volume 159, Issue 4, Page(s) 409–410

MeSH term(s)	Cone-Beam Computed Tomography ; Cuspid/diagnostic imaging ; Humans ; Incisor ; Risk Factors ; Root Resorption/diagnostic imaging ; Root Resorption/etiology ; Tooth, Impacted/diagnostic imaging
Language	English
Publishing date	2021-04-01
Publishing country	United States
Document type	Letter ; Comment
ZDB-ID	356699-7
ISSN	1097-6752 ; 0889-5406 ; 0002-9416
ISSN (online)	1097-6752
ISSN	0889-5406 ; 0002-9416
DOI	10.1016/j.ajodo.2020.11.014
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Article: Brain Tumor Segmentation from MRI Images Using Handcrafted Convolutional Neural Network.

Ullah, Faizan / Nadeem, Muhammad / Abrar, Mohammad / Al-Razgan, Muna / Alfakih, Taha / Amin, Farhan / Salam, Abdu

Diagnostics (Basel, Switzerland)

2023 Volume 13, Issue 16

Abstract: Brain tumor segmentation from magnetic resonance imaging (MRI) scans is critical for the diagnosis, treatment planning, and monitoring of therapeutic outcomes. Thus, this research introduces a novel hybrid approach that combines handcrafted features with ...

Abstract	Brain tumor segmentation from magnetic resonance imaging (MRI) scans is critical for the diagnosis, treatment planning, and monitoring of therapeutic outcomes. Thus, this research introduces a novel hybrid approach that combines handcrafted features with convolutional neural networks (CNNs) to enhance the performance of brain tumor segmentation. In this study, handcrafted features were extracted from MRI scans that included intensity-based, texture-based, and shape-based features. In parallel, a unique CNN architecture was developed and trained to detect the features from the data automatically. The proposed hybrid method was combined with the handcrafted features and the features identified by CNN in different pathways to a new CNN. In this study, the Brain Tumor Segmentation (BraTS) challenge dataset was used to measure the performance using a variety of assessment measures, for instance, segmentation accuracy, dice score, sensitivity, and specificity. The achieved results showed that our proposed approach outperformed the traditional handcrafted feature-based and individual CNN-based methods used for brain tumor segmentation. In addition, the incorporation of handcrafted features enhanced the performance of CNN, yielding a more robust and generalizable solution. This research has significant potential for real-world clinical applications where precise and efficient brain tumor segmentation is essential. Future research directions include investigating alternative feature fusion techniques and incorporating additional imaging modalities to further improve the proposed method's performance.
Language	English
Publishing date	2023-08-11
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2662336-5
ISSN	2075-4418
ISSN	2075-4418
DOI	10.3390/diagnostics13162650
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Article ; Online: Survival Prediction of Children Undergoing Hematopoietic Stem Cell Transplantation Using Different Machine Learning Classifiers by Performing Chi-Square Test and Hyperparameter Optimization: A Retrospective Analysis.

Ratul, Ishrak Jahan / Wani, Ummay Habiba / Nishat, Mirza Muntasir / Al-Monsur, Abdullah / Ar-Rafi, Abrar Mohammad / Faisal, Fahim / Kabir, Mohammad Ridwan

Computational and mathematical methods in medicine

2022 Volume 2022, Page(s) 9391136

Abstract: Bone marrow transplant (BMT) is an effective surgical treatment for bone marrow-related disorders. However, several associated risk factors can impair long-term survival after BMT. Machine learning (ML) technologies have been proven useful in survival ... ...

Abstract	Bone marrow transplant (BMT) is an effective surgical treatment for bone marrow-related disorders. However, several associated risk factors can impair long-term survival after BMT. Machine learning (ML) technologies have been proven useful in survival prediction of BMT receivers along with the influences that limit their resilience. In this study, an efficient classification model predicting the survival of children undergoing BMT is presented using a public dataset. Several supervised ML methods were investigated in this regard with an 80-20 train-test split ratio. To ensure prediction with minimal time and resources, only the top 11 out of the 59 dataset features were considered using Chi-square feature selection method. Furthermore, hyperparameter optimization (HPO) using the grid search cross-validation (GSCV) technique was adopted to increase the accuracy of prediction. Four experiments were conducted utilizing a combination of default and optimized hyperparameters on the original and reduced datasets. Our investigation revealed that the top 11 features of HPO had the same prediction accuracy (94.73%) as the entire dataset with default parameters, however, requiring minimal time and resources. Hence, the proposed approach may aid in the development of a computer-aided diagnostic system with satisfactory accuracy and minimal computation time by utilizing medical data records.
MeSH term(s)	Chi-Square Distribution ; Child ; Hematopoietic Stem Cell Transplantation ; Humans ; Machine Learning ; Retrospective Studies ; Supervised Machine Learning
Language	English
Publishing date	2022-09-25
Publishing country	United States
Document type	Journal Article
ZDB-ID	2252430-7
ISSN	1748-6718 ; 1748-670X ; 1027-3662
ISSN (online)	1748-6718
ISSN	1748-670X ; 1027-3662
DOI	10.1155/2022/9391136
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Article ; Online: Predictors of Poor Response and Adverse Events Following Botulinum Toxin-A for Refractory Idiopathic Overactive Bladder.

Abrar, Mohammad / Stroman, Luke / Malde, Sachin / Solomon, Eskinder / Sahai, Arun

Urology

2019 Volume 135, Page(s) 32–37

Abstract: Objective: To ascertain whether a poor response and adverse events (voiding dysfunction and urinary tract infection) were predictable for first time botulinum toxin-A (BTX-A) injections in a patient cohort of refractory idiopathic overactive bladder ... ...

Abstract	Objective: To ascertain whether a poor response and adverse events (voiding dysfunction and urinary tract infection) were predictable for first time botulinum toxin-A (BTX-A) injections in a patient cohort of refractory idiopathic overactive bladder with detrusor overactivity. Methods: Patients who received BTX-A injections for the first time between the dates of March 2004-August 2017 were analyzed in this single center study. Urogenital Distress Inventory short form (UDI-6) questionnaires were collected both preinjection and postinjection prospectively. A poor response was defined as a decrease of less than 16.7 on the UDI-6 questionnaire. Additional information was gathered from patient records in a retrospective fashion. Predictors of poor response, voiding dysfunction, and UTI were analyzed with multivariate logistic regression analysis. Results: Seventy-four patients were analyzed. The only predictor of poor response was male gender (OR, 5.45; 95% CI 1.83-16.47; P = .002). Lower maximum urinary flow rates (OR, 0.91; 95% CI, 0.83-0.99; P = .023), male gender (OR, 5.14; 95% CI 1.41-18.72; P = .013), and hysterectomy in females (OR, 4.55; 95% CI, 1.09-18.87; P = .038) were predictors of clean intermittent self catheterisation (CISC). There was an increased risk of UTIs in patients who performed CISC (OR, 5.26; 95% CI 1.38-20.0; P = .015). Conclusion: Male gender was associated with a poor response to BTX-A injections and increased risk of CISC. Lower maximum urinary flow rates and women with hysterectomies were at increased risk of requiring CISC postinjection. Performing CISC was associated with increased risk of UTI. These factors could be helpful when counselling or selecting patients.
MeSH term(s)	Administration, Intravesical ; Botulinum Toxins, Type A/administration & dosage ; Botulinum Toxins, Type A/adverse effects ; Female ; Humans ; Injections, Intramuscular/methods ; Intermittent Urethral Catheterization/adverse effects ; Intermittent Urethral Catheterization/methods ; Intermittent Urethral Catheterization/statistics & numerical data ; Male ; Middle Aged ; Neuromuscular Agents/administration & dosage ; Neuromuscular Agents/adverse effects ; Prognosis ; Retrospective Studies ; Self Care/methods ; Self Care/statistics & numerical data ; Sex Factors ; Surveys and Questionnaires ; Treatment Outcome ; Urinary Bladder/drug effects ; Urinary Bladder/physiopathology ; Urinary Bladder, Overactive/diagnosis ; Urinary Bladder, Overactive/physiopathology ; Urinary Bladder, Overactive/therapy ; Urinary Tract Infections/epidemiology ; Urinary Tract Infections/etiology ; Urination Disorders/diagnosis ; Urination Disorders/epidemiology ; Urination Disorders/etiology
Chemical Substances	Neuromuscular Agents ; Botulinum Toxins, Type A (EC 3.4.24.69)
Language	English
Publishing date	2019-10-15
Publishing country	United States
Document type	Journal Article
ZDB-ID	192062-5
ISSN	1527-9995 ; 0090-4295
ISSN (online)	1527-9995
ISSN	0090-4295
DOI	10.1016/j.urology.2019.08.054
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Zs.A 1142: Show issues			Location: Je nach Verfügbarkeit (siehe Angabe bei Bestand) bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular Jg. 1995 - 2021: Lesesall (1.OG) ab Jg. 2022: Lesesaal (EG)
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Article: Exploring the natural products chemical space through a molecular search to discover potential inhibitors that target the hypoxia-inducible factor (HIF) prolyl hydroxylase domain (PHD).

Sayaf, Abrar Mohammad / Ullah Khalid, Saif / Hameed, Jawad Ahmed / Alshammari, Abdulrahman / Khan, Abbas / Mohammad, Anwar / Alghamdi, Saeed / Wei, Dong-Qing / Yeoh, KarKheng

Frontiers in pharmacology

2023 Volume 14, Page(s) 1202128

Abstract: Introduction: ...

Abstract	Introduction:
Language	English
Publishing date	2023-08-21
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2587355-6
ISSN	1663-9812
ISSN	1663-9812
DOI	10.3389/fphar.2023.1202128
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Article ; Online: Predictors of Poor Response and Adverse Events Following Botulinum Toxin A for Refractory Idiopathic Overactive Bladder: A Systematic Review.

Abrar, Mohammad / Pindoria, Nisha / Malde, Sachin / Chancellor, Michael / DeRidder, Dirk / Sahai, Arun

European urology focus

2020 Volume 7, Issue 6, Page(s) 1448–1467

Abstract: Context: Botulinum toxin A (BTX-A) injections are effective in managing refractory overactive bladder (OAB). However, some patients exhibit a poor response and/or experience adverse events (AEs) such as voiding dysfunction necessitating clean ... ...

Abstract	Context: Botulinum toxin A (BTX-A) injections are effective in managing refractory overactive bladder (OAB). However, some patients exhibit a poor response and/or experience adverse events (AEs) such as voiding dysfunction necessitating clean intermittent self-catheterisation (CISC) and urinary tract infections (UTIs). Objective: To systematically evaluate whether poor response/AEs to BTX-A for idiopathic OAB are predictable. Evidence acquisition: MEDLINE, EMBASE, and Google Scholar database were searched in March 2020. Studies reporting predictive factors for poor response or AEs were included. Two reviewers independently screened articles, searched references, and extracted data. Risk of bias (Quality in Prognosis Studies [QUIPS]) and quality of evidence (Grading of Recommendations Assessment, Development and Evaluation [GRADE]) tools were utilised. Evidence synthesis: Of 1579 articles, 17 met the inclusion criteria. These were cohort studies with predominantly level 3 evidence. Factors including male gender, frailty, comorbidity, increasing age, smoking, baseline leakage episodes, and various urodynamic parameters (bladder outlet obstruction index [BOOI], high pretreatment maximum detrusor pressure, and poor bladder compliance) were proposed as predictors of nonresponse. In predicting CISC use, male gender, comorbidity, increasing age, number of vaginal deliveries, hysterectomy, and urodynamic parameters (bladder capacity, postvoid residual volume, projected isovolumetric pressure value, bladder contractility index, and BOOI) were implicated. Female gender, males with their prostates in situ, and CISC were suggested to increase UTIs after BTX-A. Conclusions: This review has identified factors that may predict poor response/AEs following bladder BTX-A and help in counselling of patients. Overall, the quality of individual studies included was poor, limiting the certainty of evidence reported. Larger-scale, better-designed trials with uniform definitions of poor response are required to confirm these preliminary findings. Patient summary: This review assessed whether we could predict poor response or side effects to bladder botulinum toxin A injections in managing overactive bladder. Many different factors based on the patient, medical conditions, previous surgery, and pretreatment investigations were identified. However, the quality of included studies was generally poor, limiting their conclusions.
MeSH term(s)	Botulinum Toxins, Type A/adverse effects ; Female ; Humans ; Male ; Neuromuscular Agents/adverse effects ; Urinary Bladder Neck Obstruction ; Urinary Bladder, Neurogenic/drug therapy ; Urinary Bladder, Overactive/drug therapy ; Urinary Tract Infections/drug therapy ; Urodynamics/physiology
Chemical Substances	Neuromuscular Agents ; Botulinum Toxins, Type A (EC 3.4.24.69)
Language	English
Publishing date	2020-06-29
Publishing country	Netherlands
Document type	Journal Article ; Review ; Systematic Review
ISSN	2405-4569
ISSN (online)	2405-4569
DOI	10.1016/j.euf.2020.06.013
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Article ; Online: Pharmacotherapeutic Potential of Natural Products to Target the SARS-CoV-2 PLpro Using Molecular Screening and Simulation Approaches.

Sayaf, Abrar Mohammad / Ahmad, Hassaan / Aslam, Muhammad Ammar / Ghani, Sidra Abdul / Bano, Saira / Yousafi, Qudsia / Suleman, Muhammad / Khan, Abbas / Yeoh, Kar Kheng / Wei, Dong-Qing

Applied biochemistry and biotechnology

2023 Volume 195, Issue 11, Page(s) 6959–6978

Abstract: Because of the essential role of PLpro in the regulation of replication and dysregulation of the host immune sensing, it is considered a therapeutic target for novel drug development. To reduce the risk of immune evasion and vaccine effectiveness, small ... ...

Abstract	Because of the essential role of PLpro in the regulation of replication and dysregulation of the host immune sensing, it is considered a therapeutic target for novel drug development. To reduce the risk of immune evasion and vaccine effectiveness, small molecular therapeutics are the best complementary approach. Hence, we used a structure-based drug-designing approach to identify potential small molecular inhibitors for PLpro of SARS-CoV-2. Initial scoring and re-scoring of the best hits revealed that three compounds NPC320891 (2,2-Dihydroxyindene-1,3-Dione), NPC474594 (Isonarciclasine), and NPC474595 (7-Deoxyisonarciclasine) exhibit higher docking scores than the control GRL0617. Investigation of the binding modes revealed that alongside the essential contacts, i.e., Asp164, Glu167, Tyr264, and Gln269, these molecules also target Lys157 and Tyr268 residues in the active site. Moreover, molecular simulation demonstrated that the reported top hits also possess stable dynamics and structural packing. Furthermore, the residues' flexibility revealed that all the complexes demonstrated higher flexibility in the regions 120-140, 160-180, and 205-215. The 120-140 and 160-180 lie in the finger region of PLpro, which may open/close during the simulation to cover the active site and push the ligand inside. In addition, the total binding free energy was reported to be - 32.65 ± 0.17 kcal/mol for the GRL0617-PLpro, for the NPC320891-PLpro complex, the TBE was - 35.58 ± 0.14 kcal/mol, for the NPC474594-PLpro, the TBE was - 43.72 ± 0.22 kcal/mol, while for NPC474595-PLpro complex, the TBE was calculated to be - 41.61 ± 0.20 kcal/mol, respectively. Clustering of the protein's motion and FEL further revealed that in NPC474594 and NPC474595 complexes, the drug was seen to have moved inside the binding cavity along with the loop in the palm region harboring the catalytic triad, thus justifying the higher binding of these two molecules particularly. In conclusion, the overall results reflect favorable binding of the identified hits strongly than the control drug, thus demanding in vitro and in vivo validation for clinical purposes.
MeSH term(s)	Humans ; Biological Products/pharmacology ; Biological Products/therapeutic use ; COVID-19 ; SARS-CoV-2 ; Aniline Compounds ; Molecular Docking Simulation ; Molecular Dynamics Simulation
Chemical Substances	Biological Products ; 5-amino-2-methyl-N-((R)-1-(1-naphthyl)ethyl)benzamide ; Aniline Compounds
Language	English
Publishing date	2023-03-24
Publishing country	United States
Document type	Journal Article
ZDB-ID	392344-7
ISSN	1559-0291 ; 0273-2289
ISSN (online)	1559-0291
ISSN	0273-2289
DOI	10.1007/s12010-023-04466-1
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Article: Deep GRU-CNN Model for COVID-19 Detection From Chest X-Rays Data.

Shah, Pir Masoom / Ullah, Faizan / Shah, Dilawar / Gani, Abdullah / Maple, Carsten / Wang, Yulin / Shahid / Abrar, Mohammad / Islam, Saif Ul

IEEE access : practical innovations, open solutions

2021 Volume 10, Page(s) 35094–35105

Abstract: In the current era, data is growing exponentially due to advancements in smart devices. Data scientists apply a variety of learning-based techniques to identify underlying patterns in the medical data to address various health-related issues. In this ... ...

Abstract	In the current era, data is growing exponentially due to advancements in smart devices. Data scientists apply a variety of learning-based techniques to identify underlying patterns in the medical data to address various health-related issues. In this context, automated disease detection has now become a central concern in medical science. Such approaches can reduce the mortality rate through accurate and timely diagnosis. COVID-19 is a modern virus that has spread all over the world and is affecting millions of people. Many countries are facing a shortage of testing kits, vaccines, and other resources due to significant and rapid growth in cases. In order to accelerate the testing process, scientists around the world have sought to create novel methods for the detection of the virus. In this paper, we propose a hybrid deep learning model based on a convolutional neural network (CNN) and gated recurrent unit (GRU) to detect the viral disease from chest X-rays (CXRs). In the proposed model, a CNN is used to extract features, and a GRU is used as a classifier. The model has been trained on 424 CXR images with 3 classes (COVID-19, Pneumonia, and Normal). The proposed model achieves encouraging results of 0.96, 0.96, and 0.95 in terms of precision, recall, and f1-score, respectively. These findings indicate how deep learning can significantly contribute to the early detection of COVID-19 in patients through the analysis of X-ray scans. Such indications can pave the way to mitigate the impact of the disease. We believe that this model can be an effective tool for medical practitioners for early diagnosis.
Language	English
Publishing date	2021-05-05
Publishing country	United States
Document type	Journal Article
ZDB-ID	2687964-5
ISSN	2169-3536
ISSN	2169-3536
DOI	10.1109/ACCESS.2021.3077592
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Article: Blocking key mutated hotspot residues in the RBD of the omicron variant (B.1.1.529) with medicinal compounds to disrupt the RBD-hACE2 complex using molecular screening and simulation approaches

Khan, Abbas / Randhawa, AsfandYar Waheed / Balouch, Ali Raza / Mukhtar, Naila / Sayaf, Abrar Mohammad / Suleman, Muhammad / Khan, Taimoor / Ali, Shahid / Ali, Syed Shujait / Wang, Yanjing / Mohammad, Anwar / Wei, Dong-Qing

RSC advances. 2022 Mar. 04, v. 12, no. 12

2022

Abstract: A new variant of SARS-CoV-2 known as the omicron variant (B.1.1.529) reported in South Africa with 30 mutations in the whole spike protein, among which 15 mutations are in the receptor-binding domain, is continuously spreading exponentially around the ... ...

Abstract	A new variant of SARS-CoV-2 known as the omicron variant (B.1.1.529) reported in South Africa with 30 mutations in the whole spike protein, among which 15 mutations are in the receptor-binding domain, is continuously spreading exponentially around the world. The omicron variant is reported to be highly contagious with antibody-escaping activity. The emergence of antibody-escaping variants is alarming, and thus the quick discovery of small molecule inhibitors is needed. Hence, the current study uses computational drug screening and molecular dynamics simulation approaches (replicated) to identify novel drugs that can inhibit the binding of the receptor-binding domain (RBD) with hACE2. Screening of the North African, East African and North-East African medicinal compound databases by employing a multi-step screening approach revealed four compounds, namely (−)-pipoxide (C1), 2-(p-hydroxybenzyl) benzofuran-6-ol (C2), 1-(4-hydroxy-3-methoxyphenyl)-2-{4-[(E)-3-hydroxy-1-propenyl]-2-methoxyphenoxy}-1,3-propanediol (C3), and Rhein (C4), with excellent anti-viral properties against the RBD of the omicron variant. Investigation of the dynamics demonstrates stable behavior, good residue flexibility profiles, and structural compactness. Validation of the top hits using computational bioactivity analysis, binding free energy calculations and dissociation constant (KD) analysis also indicated the anti-viral properties of these compounds. In conclusion, this study will help in the design and discovery of novel drug therapeutics, which may be used against the emerging omicron variant of SARS-CoV-2.
Keywords	Gibbs free energy ; Severe acute respiratory syndrome coronavirus 2 ; dissociation ; drug therapy ; drugs ; molecular dynamics ; South Africa
Language	English
Dates of publication	2022-0304
Size	p. 7318-7327.
Publishing place	The Royal Society of Chemistry
Document type	Article
ISSN	2046-2069
DOI	10.1039/d2ra00277a
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