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Article ; Online: Dynamics of a diffusive vaccination model with therapeutic impact and non-linear incidence in epidemiology.

Kamrujjaman, Md / Shahriar Mahmud, Md / Islam, Md Shafiqul

2020 Volume 15, Issue sup1, Page(s) S105–S133

Abstract: In this paper, we study a more general diffusive spatially dependent vaccination model for infectious disease. In our diffusive vaccination model, we consider both therapeutic impact and nonlinear incidence rate. Also, in this model, the number of ... ...

Abstract	In this paper, we study a more general diffusive spatially dependent vaccination model for infectious disease. In our diffusive vaccination model, we consider both therapeutic impact and nonlinear incidence rate. Also, in this model, the number of compartments of susceptible, vaccinated and infectious individuals are considered to be functions of both time and location, where the set of locations (equivalently, spatial habitats) is a subset of
MeSH term(s)	Basic Reproduction Number ; Communicable Diseases/epidemiology ; Diffusion ; Humans ; Incidence ; Models, Biological ; Vaccination
Language	English
Publishing date	2020-11-18
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2274786-2
ISSN	1751-3766 ; 1751-3758
ISSN (online)	1751-3766
ISSN	1751-3758
DOI	10.1080/17513758.2020.1849831
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Dynamics of a diffusive vaccination model with therapeutic impact and non-linear incidence in epidemiology

Md. Kamrujjaman / Md. Shahriar Mahmud / Md. Shafiqul Islam

Journal of Biological Dynamics, Vol 15, Iss S1, Pp S105-S

2021 Volume 133

Abstract	In this paper, we study a more general diffusive spatially dependent vaccination model for infectious disease. In our diffusive vaccination model, we consider both therapeutic impact and nonlinear incidence rate. Also, in this model, the number of compartments of susceptible, vaccinated and infectious individuals are considered to be functions of both time and location, where the set of locations (equivalently, spatial habitats) is a subset of $ \mathbb {R}^n $ with a smooth boundary. Both local and global stability of the model are studied. Our study shows that if the threshold level $ \mathcal {R}_0 \le 1, $ the disease-free equilibrium $ E_0 $ is globally asymptotically stable. On the other hand, if $ \mathcal {R}_0> 1 $ then there exists a unique stable disease equilibrium $ E^* $ . The existence of solutions of the model and uniform persistence results are studied. Finally, using finite difference scheme, we present a number of numerical examples to verify our analytical results. Our results indicate that the global dynamics of the model are completely determined by the threshold value $ \mathcal {R}_0 $ .
Keywords	spatial vaccination model ; nonlinear incidence ; threshold value ; local stability ; global stability ; uniform persistence ; Environmental sciences ; GE1-350 ; Biology (General) ; QH301-705.5
Subject code	612
Language	English
Publishing date	2021-05-01T00:00:00Z
Publisher	Taylor & Francis Group
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: RiIG Modeled WCP Image-Based CNN Architecture and Feature-Based Approach in Breast Tumor Classification from B-Mode Ultrasound

Shahriar Mahmud Kabir / Mohammed I. H. Bhuiyan / Md Sayed Tanveer / ASM Shihavuddin

Applied Sciences, Vol 11, Iss 12138, p

2021 Volume 12138

Abstract: This study presents two new approaches based on Weighted Contourlet Parametric (WCP) images for the classification of breast tumors from B-mode ultrasound images. The Rician Inverse Gaussian (RiIG) distribution is considered for modeling the statistics ... ...

Abstract	This study presents two new approaches based on Weighted Contourlet Parametric (WCP) images for the classification of breast tumors from B-mode ultrasound images. The Rician Inverse Gaussian (RiIG) distribution is considered for modeling the statistics of ultrasound images in the Contourlet transform domain. The WCP images are obtained by weighting the RiIG modeled Contourlet sub-band coefficient images. In the feature-based approach, various geometrical, statistical, and texture features are shown to have low ANOVA p -value, thus indicating a good capacity for class discrimination. Using three publicly available datasets (Mendeley, UDIAT, and BUSI), it is shown that the classical feature-based approach can yield more than 97% accuracy across the datasets for breast tumor classification using WCP images while the custom-made convolutional neural network (CNN) can deliver more than 98% accuracy, sensitivity, specificity, NPV, and PPV values utilizing the same WCP images. Both methods provide superior classification performance, better than those of several existing techniques on the same datasets.
Keywords	deep learning ; machine learning ; convolutional neural network (CNN) ; breast cancer ; contourlet ; B-mode ultrasound ; Technology ; T ; Engineering (General). Civil engineering (General) ; TA1-2040 ; Biology (General) ; QH301-705.5 ; Physics ; QC1-999 ; Chemistry ; QD1-999
Subject code	006
Language	English
Publishing date	2021-12-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Multiomics analysis of altered NRF3 expression reveals poor prognosis in cancer

Md. Morshedul Alam / Kanchan Chakma / Shahriar Mahmud / Mohammad Nazir Hossain / M. Rezaul Karim / Md. Ariful Amin

Informatics in Medicine Unlocked, Vol 29, Iss , Pp 100892- (2022)

2022

Abstract: The alliance of NRF3 expression with human cancer patient survival and the underlying function of this gene in liaison to various cancers progression has not been comprehensively studied. In addition, the molecular mechanism of the NRF3 gene and its ... ...

Abstract	The alliance of NRF3 expression with human cancer patient survival and the underlying function of this gene in liaison to various cancers progression has not been comprehensively studied. In addition, the molecular mechanism of the NRF3 gene and its relationship to cancer patient survival and prognosis are still poorly understood. To elucidate the carcinogenic activity of NRF3, we systematically analyzed the NRF3 expression and its prognostic relevance in diverse cancer patients to decipher the oncogenic function of NRF3. Therefore, we systematically investigated the expression level of NRF3 and its relationship with patient survival as well as the affected pathways in breast, colorectal adenocarcinoma, renal cancer, pancreatic cancer, and thymoma cancer. Relative expression levels of NRF3 were analyzed using the Oncomine, GEPIA2, GENT, UALCAN, cBioPortal, UCSC Xena and The Cancer Genome Atlas (TCGA) databases. Gene copy number of NRF3 was analyzed using cBioPortal, and the subsequent patient prognosis and risk factors were analyzed by obtaining the data from GEPIA2, GENT, and PrognoScan databases. Besides, gene ontology and pathway analysis of co-expressed genes, and transcriptome data analysis were performed using the Enrichr, which revealed NRF3-related pathways in diverse malignancies. Overall, this open database analysis shows a link between NRF3 expression and cancer patient survival and identifies potential NRF3-mediated pathways that could lead to NRF3 being used as a therapeutic target for a variety of human cancers.
Keywords	NRF3 ; Cancer patient ; Poor prognosis ; Patient survival ; Cancer therapeutics ; Computer applications to medicine. Medical informatics ; R858-859.7
Subject code	616
Language	English
Publishing date	2022-01-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: A systemic analysis reveals TRIM24-SMARCC1 dependent poor prognosis of hepatocellular carcinoma

Md Morshedul Alam / Kanchan Chakma / Shahriar Mahmud / Mohammad Nazir Hossain / Tamim Ahsan

Informatics in Medicine Unlocked, Vol 21, Iss , Pp 100467- (2020)

2020

Abstract: The role of TRIM24 in HCC and the mechanisms underlying the dysregulated expression of TRIM24 is poorly understood. Here, we systematically analyzed TRIM24 expression and its prognostic role in HCC using various open databases. More precisely, we found ... ...

Abstract	The role of TRIM24 in HCC and the mechanisms underlying the dysregulated expression of TRIM24 is poorly understood. Here, we systematically analyzed TRIM24 expression and its prognostic role in HCC using various open databases. More precisely, we found an up-regulated gene expression profile of TRIM24 in hepatocellular carcinoma by using Oncomine, cBioPortal, TCGA, and the Human Protein Atlas. The higher expression of TRIM24 is allied with various clinicopathological conditions such as cancer stages, tumor grade, nodal metastasis status, histological subtypes, and also mutant TP53 status based on the TCGA database. In addition to the mRNA expression profile, the correlation between mRNA expression and TRIM24 promoter methylation is entrenched using TCGA datasets from the UALCAN web and subsequently, we examined the liaison of TRIM24 promoter methylation with different clinicopathological conditions in HCC patients. We also clarified a negative correlation of the TRIM24 mRNA expression with antioxidant responsive genes using the TCGA cBioPortal database. Data mining via Kaplan-Meier Plotter and the Human Protein Atlas symbolized a positive tie-up among the higher TRIM24 gene expression, protein expression, and poor survival of HCC patients. Besides, we also identified a highly co-expressed gene, SMARCC1 with TRIM24 in the most predominant correlation fashion in HCC using UALCAN, cBioPortal, UCSC Xena database. Finally, we identified the co-expressed genes with gene oncological features, signaling pathways, and ENCODE ChIP-seq coordination in HCC development. Altogether, this study establishes that elevated TRIM24 expression might accelerate the cancer progression and poor prognosis in HCC patients in a concerted fashion with SMARCC1 expression, which would allow them as a potential therapeutic biomarker in HCC cases.
Keywords	Hepatocellular carcinoma ; TRIM24 ; SMARCC1 ; Poor prognosis ; Computer applications to medicine. Medical informatics ; R858-859.7
Subject code	570
Language	English
Publishing date	2020-01-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: Weighted Contourlet Parametric (WCP) Feature Based Breast Tumor Classification from B-Mode Ultrasound Image

Kabir, Shahriar Mahmud / Tanveer, Md. Sayed / Shihavuddin, ASM / Bhuiyan, Mohammed Imamul Hassan

2021

Abstract: Automated detection of breast tumor in early stages using B-Mode Ultrasound image is crucial for preventing widespread breast cancer specially among women. This paper is primarily focusing on the classification of breast tumors through statistical ... ...

Abstract	Automated detection of breast tumor in early stages using B-Mode Ultrasound image is crucial for preventing widespread breast cancer specially among women. This paper is primarily focusing on the classification of breast tumors through statistical modelling such as Rician inverse Gaussian (RiIG) pdf of contourlet transformed B-Mode image of breast tumors which is not reported yet in other earlier works. The suitability of RiIG distribution in modeling the contourlet coefficients is illustrated and compared with that of Nakagami distribution. The proposed method consists of pre-processing to remove the speckle noise, segmentation of the lesion region, contourlet transform on the B-Mode Ultrasound image and using the corresponding contourlet sub-band coefficients and the RiIG parameters, production of contourlet parametric (CP) images and weighted contourlet parametric (WCP) images. A number of geometrical, statistical, and texture features are calculated from B-Mode and the contourlet parametric images. In order to classify the features, seven different classifiers are employed. The proposed approach is applied to two different datasets (Mendeley Data and Dataset B) those are available publicly. It is shown that with parametric images, accuracies in the range of 94-97% are achieved for different classifiers. Specifically, with the support vector machine and k-nearest-neighbor classifier, very high accuracies of 97.2% and 97.55% can be obtained for the Mendeley Data and Dataset B,respectively, using the weighted contourlet parametric images.The reported classification performance is also compared with that of other works using the datasets employed in this paper. It is seen that the proposed approach using weighted contourlet parametric images can provide a superior performance.
Keywords	Electrical Engineering and Systems Science - Image and Video Processing
Subject code	006
Publishing date	2021-02-11
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Structural and Functional Elucidation of IF-3 Protein of Chloroflexus aurantiacus Involved in Protein Biosynthesis

Abu Saim Mohammad Saikat / Md. Ekhlas Uddin / Tasnim Ahmad / Shahriar Mahmud / Md. Abu Sayeed Imran / Sohel Ahmed / Salem A. Alyami / Mohammad Ali Moni

BioMed Research International, Vol

An In Silico Approach

2021 Volume 2021

Abstract: Chloroflexus aurantiacus is a thermophilic bacterium that produces a multitude of proteins within its genome. Bioinformatics strategies can facilitate comprehending this organism through functional and structural interpretation assessments. This study is ...

Abstract	Chloroflexus aurantiacus is a thermophilic bacterium that produces a multitude of proteins within its genome. Bioinformatics strategies can facilitate comprehending this organism through functional and structural interpretation assessments. This study is aimed at allocating the structure and function through an in silico approach required for bacterial protein biosynthesis. This in silico viewpoint provides copious properties, including the physicochemical properties, subcellular location, three-dimensional structure, protein-protein interactions, and functional elucidation of the protein (WP_012256288.1). The STRING program is utilized for the explication of protein-protein interactions. The in silico investigation documented the protein’s hydrophilic nature with predominantly alpha (α) helices in its secondary structure. The tertiary-structure model of the protein has been shown to exhibit reasonably high consistency based on various quality assessment methods. The functional interpretation suggested that the protein can act as a translation initiation factor, a protein required for translation and protein biosynthesis. Protein-protein interactions also demonstrated high credence that the protein interconnected with 30S ribosomal subunit involved in protein synthesis. This study bioinformatically examined that the protein (WP_012256288.1) is affiliated in protein biosynthesis as a translation initiation factor IF-3 of C. aurantiacus.
Keywords	Medicine ; R
Subject code	612
Language	English
Publishing date	2021-01-01T00:00:00Z
Publisher	Hindawi Limited
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: SARS-CoV-2 and Rohingya Refugee Camp, Bangladesh

Md. Kamrujjaman / Md. Shahriar Mahmud / Shakil Ahmed / Md. Omar Qayum / Mohammad Morshad Alam / Md Nazmul Hassan / Md Rafiul Islam / Kaniz Fatema Nipa / Ummugul Bulut

Biology, Vol 10, Iss 2, p

Uncertainty and How the Government Took Over the Situation

2021 Volume 124

Abstract: Background: Bangladesh hosts more than 800,000 Rohingya refugees from Myanmar. The low health immunity, lifestyle, access to good healthcare services, and social-security cause this population to be at risk of far more direct effects of COVID-19 than the ...

Abstract	Background: Bangladesh hosts more than 800,000 Rohingya refugees from Myanmar. The low health immunity, lifestyle, access to good healthcare services, and social-security cause this population to be at risk of far more direct effects of COVID-19 than the host population. Therefore, evidence-based forecasting of the COVID-19 burden is vital in this regard. In this study, we aimed to forecast the COVID-19 obligation among the Rohingya refugees of Bangladesh to keep up with the disease outbreak’s pace, health needs, and disaster preparedness. Methodology and Findings: To estimate the possible consequences of COVID-19 in the Rohingya camps of Bangladesh, we used a modified Susceptible-Exposed-Infectious-Recovered (SEIR) transmission model. All of the values of different parameters used in this model were from the Bangladesh Government’s database and the relevant emerging literature. We addressed two different scenarios, i.e., the best-fitting model and the good-fitting model with unique consequences of COVID-19. Our best fitting model suggests that there will be reasonable control over the transmission of the COVID-19 disease. At the end of December 2020, there will be only 169 confirmed COVID-19 cases in the Rohingya refugee camps. The average basic reproduction number ( <semantics> R 0 </semantics> ) has been estimated to be 0.7563. Conclusions: Our analysis suggests that, due to the extensive precautions from the Bangladesh government and other humanitarian organizations, the coronavirus disease will be under control if the maintenance continues like this. However, detailed and pragmatic preparedness should be adopted for the worst scenario.
Keywords	COVID-19 ; Rohingya Refugee camp ; mathematical model ; numerical results ; basic reproduction number ; AMS Subject Classication 2010 ; Biology (General) ; QH301-705.5
Subject code	910
Language	English
Publishing date	2021-02-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Coating Efficiency in Preventing Photolytic Degradation of Two Randomly Selected Brands of Metoprolol Tartrate

Md. Anisur Rahman / Mohammed Faisal Bin Karim / Tirtha Nandi / Kazi Imran Adib / Roksana Parvin / Md. Shahriar Mahmud

International Journal of Pharmaceutical Sciences and Drug Research, Vol 8, Iss 2, Pp 83-

2016 Volume 86

Abstract: This research work was carried out to determine whether the film coating is effective to prevent the photolytic degradation of Metoprolol tartrate which is known to have photosensitivity. For this purpose, two randomly selected brands of two different ... ...

Abstract	This research work was carried out to determine whether the film coating is effective to prevent the photolytic degradation of Metoprolol tartrate which is known to have photosensitivity. For this purpose, two randomly selected brands of two different pharmaceutical companies were chosen i.e. Brand A and Brand B. These two brands were exposed to different lighting conditions (normal light, direct sunlight as well as two incandescent lights i.e. 25 watt bulb, 40 watt bulb). Potency tests were performed using UV spectroscopy which showed gradual decline in potency of the tablets under aforesaid lighting conditions and the potency degradations were found 11.48%, 12.92%, 22.62%, 16.87% for Brand A and 14.74%, 14.24%, 10.88%, 18.10% for Brand B under 25 watt bulb, 40 watt bulb, direct sunlight and normal room light respectively. So this study reveals that the both brands containing metoprolol tartrate showed significant light sensitivity even though they are coated and protective opaque packaging is highly recommended for their protection.
Keywords	Metoprolol Tartrate ; Potency ; Light ; Incandescent ; Photolytic Degradation ; Photosensitivity ; opaque packaging ; Therapeutics. Pharmacology ; RM1-950 ; Medicine ; R
Language	English
Publishing date	2016-03-01T00:00:00Z
Publisher	International Journal of Pharmaceutical Sciences and Drug Research
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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