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  1. Book ; Online ; E-Book: Application of nanoparticles in tissue engineering

    Afaq, Sarah / Malik, Arshi / Tarique, Mohammed

    2022  

    Author's details edited by Sarah Afaq, Arshi Malik, Mohammed Tarique
    Keywords Nanoparticles ; Nanopartícules ; Enginyeria de teixits
    Subject code 730
    Language English
    Size 1 online resource (134 pages)
    Publisher Springer
    Publishing place Singapore
    Document type Book ; Online ; E-Book
    Remark Zugriff für angemeldete ZB MED-Nutzerinnen und -Nutzer
    ISBN 981-16-6198-7 ; 9789811661976 ; 978-981-16-6198-3 ; 9811661979
    Database ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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  2. Book ; Online ; E-Book: Nanomedicine for cancer diagnosis and therapy

    Tarique, Mohammed / Afaq, Sarah / Malik, Arshi

    2021  

    Author's details Arshi Malik, Sarah Afaq and Mohammed Tarique (editors)
    Keywords Nanomedicine ; Cancer/Treatment/Technological innovations ; Nanomedicina ; Oncologia ; Terapèutica
    Subject code 616.994075
    Language English
    Size 1 online resource (251 pages)
    Publisher Springer
    Publishing place Gateway East, Singapore
    Document type Book ; Online ; E-Book
    Remark Zugriff für angemeldete ZB MED-Nutzerinnen und -Nutzer
    ISBN 981-15-7564-9 ; 981-15-7563-0 ; 978-981-15-7564-8 ; 978-981-15-7563-1
    Database ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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  3. Article ; Online: A study of using cough sounds and deep neural networks for the early detection of Covid-19.

    Islam, Rumana / Abdel-Raheem, Esam / Tarique, Mohammed

    Biomedical engineering advances

    2022  Volume 3, Page(s) 100025

    Abstract: The current clinical diagnosis of COVID-19 requires person-to-person contact, needs variable time to produce results, and is expensive. It is even inaccessible to the general population in some developing countries due to insufficient healthcare ... ...

    Abstract The current clinical diagnosis of COVID-19 requires person-to-person contact, needs variable time to produce results, and is expensive. It is even inaccessible to the general population in some developing countries due to insufficient healthcare facilities. Hence, a low-cost, quick, and easily accessible solution for COVID-19 diagnosis is vital. This paper presents a study that involves developing an algorithm for automated and noninvasive diagnosis of COVID-19 using cough sound samples and a deep neural network. The cough sounds provide essential information about the behavior of glottis under different respiratory pathological conditions. Hence, the characteristics of cough sounds can identify respiratory diseases like COVID-19. The proposed algorithm consists of three main steps (a) extraction of acoustic features from the cough sound samples, (b) formation of a feature vector, and (c) classification of the cough sound samples using a deep neural network. The output from the proposed system provides a COVID-19 likelihood diagnosis. In this work, we consider three acoustic feature vectors, namely (a) time-domain, (b) frequency-domain, and (c) mixed-domain (i.e., a combination of features in both time-domain and frequency-domain). The performance of the proposed algorithm is evaluated using cough sound samples collected from healthy and COVID-19 patients. The results show that the proposed algorithm automatically detects COVID-19 cough sound samples with an overall accuracy of 89.2%, 97.5%, and 93.8% using time-domain, frequency-domain, and mixed-domain feature vectors, respectively. The proposed algorithm, coupled with its high accuracy, demonstrates that it can be used for quick identification or early screening of COVID-19. We also compare our results with that of some state-of-the-art works.
    Language English
    Publishing date 2022-01-06
    Publishing country United States
    Document type Journal Article
    ISSN 2667-0992
    ISSN (online) 2667-0992
    DOI 10.1016/j.bea.2022.100025
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Performances of Orthogonal Wavelet Division Multiplex (OWDM) System Under AWGN, Rayleigh and Ricean Channel Conditions

    Mohammed Tarique

    International Journal of Computer Networks & Communications , Vol 8, Iss 3, Pp 93-

    2016  Volume 105

    Abstract: Orthogonal Wavelet Division Multiplexing (OWDM) has been considered as an alternative of Orthogonal Frequency Division Multiplexing (OFDM) in the recent years. OWDM has lower computational complexity and higher flexibility compared to its OFDM ... ...

    Abstract Orthogonal Wavelet Division Multiplexing (OWDM) has been considered as an alternative of Orthogonal Frequency Division Multiplexing (OFDM) in the recent years. OWDM has lower computational complexity and higher flexibility compared to its OFDM counterpart. The core component of OWDM is wavelet. Wavelet has been a much investigated and applied topic in digital image processing for a long time. Recently, it has drawn considerable attention of the researchers working in communication field. In this work we investigate the performances of OWDM under different channel conditions. We consider three channel conditions namely Additive White Gaussian Noise (AWGN), Rayleigh, Ricean, and frequency selective. We consider a number of wavelets namely Haar, Daubechies, Biorthogonal, Reverse Biorthogonal, Coiflets, and Symlets in OWDM design. For system model we choose Digital Video Broadcasting-Terrestrial (DVB-T). Originally DVB-T system was designed based on OFDM. In this work we use OWDM instead. The simulation results show OWDM outperforms OFDM in terms of bit error rate (BER), noise resiliency, and peak-to-average ration. The results also show that the Haar wavelet based OWDM outperforms other wavelets based OWDM system under all three considered three channel conditions.
    Keywords Digital Video Broadcasting ; OWDM ; wavelets ; AWGN ; multipath ; Rayleigh ; Ricean ; frequency selective ; Electronic computers. Computer science ; QA75.5-76.95 ; Instruments and machines ; QA71-90 ; Mathematics ; QA1-939 ; Science ; Q
    Subject code 003
    Language English
    Publishing date 2016-05-01T00:00:00Z
    Publisher Academy & Industry Research Collaboration Center (AIRCC)
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  5. Article ; Online: Bioactive properties and gut microbiota modulation by date seed polysaccharides extracted using ultrasound-assisted deep eutectic solvent.

    Subhash, Athira Jayasree / Bamigbade, Gafar Babatunde / Tarique, Mohammed / Al-Ramadi, Basel / Abu-Jdayil, Basim / Kamal-Eldin, Afaf / Nyström, Laura / Ayyash, Mutamed

    Food chemistry: X

    2024  Volume 22, Page(s) 101354

    Abstract: Polysaccharides are abundant macromolecules. The study extracted date seed polysaccharides (UPS) using ultrasound-assisted deep eutectic solvent extraction to valorize date seeds. UPS were subjected to comprehensive characterization and evaluation of ... ...

    Abstract Polysaccharides are abundant macromolecules. The study extracted date seed polysaccharides (UPS) using ultrasound-assisted deep eutectic solvent extraction to valorize date seeds. UPS were subjected to comprehensive characterization and evaluation of their bioactivity, prebiotic properties, and their potential to modulate the gut microbiome. Characterization revealed UPS's heteropolysaccharide composition with galactose, mannose, fructose, glucose, and galacturonic acid respectively in 66.1, 13.3, 9.9, 5.4, and 5.1%. UPS showed a concentration-dependent increase of radical scavenging and antioxidant activities, evidenced by FRAP, TAC, and RP assays. They also displayed antimicrobial efficacy against
    Language English
    Publishing date 2024-04-03
    Publishing country Netherlands
    Document type Journal Article
    ISSN 2590-1575
    ISSN (online) 2590-1575
    DOI 10.1016/j.fochx.2024.101354
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article ; Online: A Novel Pathological Voice Identification Technique through Simulated Cochlear Implant Processing Systems

    Rumana Islam / Esam Abdel-Raheem / Mohammed Tarique

    Applied Sciences, Vol 12, Iss 2398, p

    2022  Volume 2398

    Abstract: This paper presents a pathological voice identification system employing signal processing techniques through cochlear implant models. The fundamentals of the biological process for speech perception are investigated to develop this technique. Two ... ...

    Abstract This paper presents a pathological voice identification system employing signal processing techniques through cochlear implant models. The fundamentals of the biological process for speech perception are investigated to develop this technique. Two cochlear implant models are considered in this work: one uses a conventional bank of bandpass filters, and the other one uses a bank of optimized gammatone filters. The critical center frequencies of those filters are selected to mimic the human cochlear vibration patterns caused by audio signals. The proposed system processes the speech samples and applies a CNN for final pathological voice identification. The results show that the two proposed models adopting bandpass and gammatone filterbanks can discriminate the pathological voices from healthy ones, resulting in F1 scores of 77.6% and 78.7%, respectively, with speech samples. The obtained results of this work are also compared with those of other related published works.
    Keywords bandpass ; cochlear implants ; classifier ; deep learning ; filterbank ; gammatone ; 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 2022-02-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  7. Article ; Online: Voice pathology detection using convolutional neural networks with electroglottographic (EGG) and speech signals

    Rumana Islam / Esam Abdel-Raheem / Mohammed Tarique

    Computer Methods and Programs in Biomedicine Update, Vol 2, Iss , Pp 100074- (2022)

    2022  

    Abstract: This paper presents a convolutional neural network (CNN) based automated noninvasive voice pathology detection system. The proposed system functions in two steps. First, it discriminates pathological voices from healthy ones, and then, it classifies the ... ...

    Abstract This paper presents a convolutional neural network (CNN) based automated noninvasive voice pathology detection system. The proposed system functions in two steps. First, it discriminates pathological voices from healthy ones, and then, it classifies the discriminated pathological voices into one of the three pathologies. Two CNNs are used for these purposes; one works as a binary classifier to identify pathological voices. The other one works as a multiclass classifier for categorizing the voice pathologies. This work investigates the effectiveness of electroglottographic (EGG) and speech signals to detect and classify pathological voices using sustained vowel ('/a/') samples. EGG signals can assess the vibratory pattern of the vocal folds during voiced sound. On the other hand, the speech signals add spectral color to the EGG signals. Hence, their contributions for pathology identification and segregation differ, as demonstrated in this work. The Saarbrücken Voice Database (SVD) is used in this investigation. The results show that the proposed system achieves a higher accuracy (more than 9%) in identifying pathological voices from healthy ones with speech signals than EGG signals. However, categorizing pathological voices into different pathology types demonstrates higher accuracy (more than 12%) with EGG signals than speech signals. A comparative performance analysis of the proposed system is presented with these two signals in terms of clinical and statistical measures. The obtained results of this work are also compared with those of other related published works.
    Keywords Classifier ; Deep learning ; EGG ; Pathology detection ; Speech ; Voice generation ; Computer applications to medicine. Medical informatics ; R858-859.7
    Subject code 410
    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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  8. Article ; Online: Potential of green-synthesized ZnO NPs against human ovarian teratocarcinoma: an in vitro study.

    Khan, Mohd Shahnawaz / Altwaijry, Nojood / Jabir, Nasimudeen R / Alamri, Abdulaziz Mohammed / Tarique, Mohammad / Khan, Azhar U

    Molecular biology reports

    2023  Volume 50, Issue 5, Page(s) 4447–4457

    Abstract: Background: Ovarian cancer leads to devastating outcomes, and its treatment is highly challenging. At present, there is a lack of clinical symptoms, well-known sensitivity biomarkers, and patients are diagnosed at an advanced stage. Currently, available ...

    Abstract Background: Ovarian cancer leads to devastating outcomes, and its treatment is highly challenging. At present, there is a lack of clinical symptoms, well-known sensitivity biomarkers, and patients are diagnosed at an advanced stage. Currently, available therapeutics against ovarian cancer are inefficient, costly, and associated with severe side effects. The present study evaluated the anticancer potential of zinc oxide nanoparticles (ZnO NPs) that were successfully biosynthesized in an ecofriendly mode using pumpkin seed extracts.
    Methods and results: The anticancer potential of the biosynthesized ZnO NPs was assessed using an in vitro human ovarian teratocarcinoma cell line (PA-1) by well-known assays such as MTT assay, morphological alterations, induction of apoptosis, measurement of reactive oxygen species (ROS) production, and inhibition of cell adhesion/migration. The biogenic ZnO NPs exerted a high level of cytotoxicity against PA-1 cells. Furthermore, the ZnO NPs inhibited cellular adhesion and migration but induced ROS production and cell death through programmed cell death.
    Conclusion: The aforementioned anticancer properties highlight the therapeutic utility of ZnO NPs in ovarian cancer treatment. However, further research is recommended to envisage their mechanism of action in different cancer models and validation in a suitable in vivo system.
    MeSH term(s) Female ; Humans ; Zinc Oxide/pharmacology ; Reactive Oxygen Species/metabolism ; Teratocarcinoma ; Nanoparticles ; Ovarian Neoplasms/drug therapy ; Metal Nanoparticles
    Chemical Substances Zinc Oxide (SOI2LOH54Z) ; Reactive Oxygen Species
    Language English
    Publishing date 2023-04-04
    Publishing country Netherlands
    Document type Journal Article
    ZDB-ID 186544-4
    ISSN 1573-4978 ; 0301-4851
    ISSN (online) 1573-4978
    ISSN 0301-4851
    DOI 10.1007/s11033-023-08367-8
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    In stock of ZB MED Cologne/Königswinter

    Zs.A 1140: Show issues Location:
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    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (1.OG)
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  9. Article ; Online: An Update on Genetic Predisposition for Prostate Cancer: Perspectives and Prospects.

    Ellatif, Mohamd Abd / Gamal, Basiouny El / Musaam, Adel Osman / Malik, Arshi / Tarique, Mohammed

    Cellular and molecular biology (Noisy-le-Grand, France)

    2023  Volume 69, Issue 2, Page(s) 1–7

    Abstract: Prostate cancer (PC) is a heterogeneous disease that kills a significant number of people all over the world. It is the most common cancer in men, especially in the western world, and causes morbidity and mortality. There are several important risk ... ...

    Abstract Prostate cancer (PC) is a heterogeneous disease that kills a significant number of people all over the world. It is the most common cancer in men, especially in the western world, and causes morbidity and mortality. There are several important risk factors known for PC like age, ethnicity, and inherited genetic variants which contribute significantly. The current research studies are endeavoring to identify genetic markers for PC and to understand underlying molecular mechanisms, so that new diagnostic and screening tests based on genetics can be developed for PC. The present review discusses candidate genes such as HOXB13, BRCA1, BRCA2, ATM, MMR gene, RAD51C, CHECK2, etc., and family-based linkage studies which defined the location of loci on chromosomal regions like 1q24-25, 1q42-43, Xq27-28, 1p36, 20q13, 17q21. Furthermore, the major part of the review focuses on important PC susceptible loci (8q24, 10q11, 17q12, 17q24, and 19q13, etc.) and risk variants identified by population-based genome-wide association studies (GWAS).
    MeSH term(s) Male ; Humans ; Genetic Predisposition to Disease ; Genome-Wide Association Study ; Prostatic Neoplasms/genetics ; Ethnicity
    Language English
    Publishing date 2023-02-28
    Publishing country France
    Document type Review ; Journal Article
    ZDB-ID 1161779-2
    ISSN 1165-158X ; 0145-5680
    ISSN (online) 1165-158X
    ISSN 0145-5680
    DOI 10.14715/cmb/2023.69.2.1
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    Zs.A 3812: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (2.OG)
    ab Jg. 2022: Lesesaal (EG)

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  10. Article ; Online: Exopolysaccharides from

    Tarique, Mohammed / Ali, Abdelmoneim H / Kizhakkayil, Jaleel / Liu, Shao-Quan / Oz, Fatih / Dertli, Enes / Kamal-Eldin, Afaf / Ayyash, Mutamed

    Food chemistry: X

    2023  Volume 21, Page(s) 101073

    Abstract: Exopolysaccharides (EPSs) are carbohydrate polymers that can be produced from probiotic bacteria. This study characterized the EPSs ... ...

    Abstract Exopolysaccharides (EPSs) are carbohydrate polymers that can be produced from probiotic bacteria. This study characterized the EPSs from
    Language English
    Publishing date 2023-12-15
    Publishing country Netherlands
    Document type Journal Article
    ISSN 2590-1575
    ISSN (online) 2590-1575
    DOI 10.1016/j.fochx.2023.101073
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