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"Islam, Mohammad"
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Adolescent motherhood in Bangladesh: Trends and determinants
While studies on fertility and contraceptives issues are available, until recently adolescent motherhood has not received enough attention among policy makers in understanding adolescent motherhood in Bangladesh. We aimed to examine the trends and determinants of adolescent motherhood among women aged 15-49 years.
For trend analysis we used all the 7 waves of Bangladesh Demographic and Health Survey (BDHS, 1993-2014) data but for multivariate analysis 4 waves of BDHS (2004-2014). Two separate analyses were carried out on ever married women aged 15-49: (1) teenage girls aged 15-19 and (2) adult women aged 20 and above.
The prevalence of adolescent motherhood had declined to a slower pace from 1993 to2014 (from 33.0% to 30.8%). Lower spousal age gap and higher education were found to be associated with lower likelihood of adolescent motherhood both among teenage girls [OR 0.447 (0.374-0.533)] and adult women [OR 0.451 (0.420-0.484)]. Teenage girls in the poorest wealth quintile [OR 1.712 [1.350-2.173] were more likely to experience adolescent motherhood than the richest wealth quintile. Teenage girls who had no education were found to have 2.76 times higher odds of adolescent motherhood than their counterparts who had higher than secondary education. Concerning the time effect, the odds of adolescent motherhood among adult women was found to decline overtime.
Despite substantial decrease in total fertility rate in Bangladesh adolescent motherhood is still highly prevalent though declining from 1993 to 2014. Social policies including those addressing poverty, ensuring greater emphasis on education for women; and adolescent mothers in rural areas are needed.
Journal Article
Knowledge, attitudes, and practices toward the novel coronavirus among Bangladeshis: Implications for mitigation measures
The current novel coronavirus (nCoV) pandemic, COVID-19, was first reported in December 2019 in Wuhan, China, and has spread globally, causing startling loss of life, stalling the global economy, and disrupting social life. One of the challenges to contain COVID-19 is convincing people to adopt personal hygiene, social distancing, and self-quarantine practices that are related to knowledge, attitudes, and practices (KAP) of the residents of respective countries. Bangladesh, a densely populated country with a fast-growing economy and moderate literacy rate, has shown many hiccups in its efforts to implement COVID-19 policies. Understanding KAP may help policy makers produce informed decisions. This study assessed KAP in relation to COVID-19 in Bangladesh. An online survey using a pre-tested questionnaire conducted in late March 2020 attained 1,837 responses across Bangladesh. Ultimately, 1,589 completed responses were included in a statistical analysis to calculate KAP scores and their interrelations with sociodemographic variables. The overall KAP was poor, with only 33% of the participants demonstrating good knowledge, whereas 52.4% and 44.8% of the subjects showed good attitudes and practices, respectively. Sociodemographic factors had strong bearings on the KAP scores. Significantly higher KAP scores were evident in females over males, among aged 45 years and older over younger participants, and among retired workers and homemakers over students and public service employees. This study indicated a panic fuelled by poor understanding of COVID-19 associated facts and the need for the government to ensure more granular and targeted awareness campaigns in a transparent and factual manner to foster public confidence and ensure more meaningful public participation in mitigation measures. This study provides a KAP baseline regarding COVID-19 among Bangladeshis.
Journal Article
Stem Cell Transplantation Therapy and Neurological Disorders: Current Status and Future Perspectives
Neurodegenerative diseases are a global health issue with inadequate therapeutic options and an inability to restore the damaged nervous system. With advances in technology, health scientists continue to identify new approaches to the treatment of neurodegenerative diseases. Lost or injured neurons and glial cells can lead to the development of several neurological diseases, including Parkinson’s disease, stroke, and multiple sclerosis. In recent years, neurons and glial cells have successfully been generated from stem cells in the laboratory utilizing cell culture technologies, fueling efforts to develop stem cell-based transplantation therapies for human patients. When a stem cell divides, each new cell has the potential to either remain a stem cell or differentiate into a germ cell with specialized characteristics, such as muscle cells, red blood cells, or brain cells. Although several obstacles remain before stem cells can be used for clinical applications, including some potential disadvantages that must be overcome, this cellular development represents a potential pathway through which patients may eventually achieve the ability to live more normal lives. In this review, we summarize the stem cell-based therapies that have been explored for various neurological disorders, discuss the potential advantages and drawbacks of these therapies, and examine future directions for this field.
Journal Article
Ultra-compact quintuple-band terahertz metamaterial biosensor for enhanced blood cancer diagnostics
Cancer and its diverse variations pose one of the most significant threats to human health and well-being. One of the most aggressive forms is blood cancer, originating from bone marrow cells and disrupting the production of normal blood cells. The incidence of blood cancer is steadily increasing, driven by both genetic and environmental factors. Therefore, early detection is crucial as it enhances treatment outcomes and improves success rates. However, accurate diagnosis is challenging due to the inherent similarities between normal and cancerous cells. Although various techniques are available for blood cancer identification, high-frequency imaging techniques have recently shown promise, particularly for real-time monitoring. Notably, terahertz (THz) frequencies offer unique advantages for biomedical applications. This research proposes an innovative terahertz metamaterial-based biosensor for high-efficacy blood cancer detection. The proposed structure is ultra-compact and operates across five bands within the range of 0.6 to 1.2 THz. It is constructed using a polyethylene terephthalate (PET) dielectric layer and two aluminum (Al) layers, with the top layer serving as a base for the THz-range resonator. Careful design, architectural arrangement, and optimization of the geometry parameters allow for achieving nearly perfect absorption rates (>95%) across all operating bands. The properties of the proposed sensor are extensively evaluated through full-wave electromagnetic (EM) analysis, which includes assessing the refractive index and the distribution of the electric field at individual working frequencies. The suitability for blood cancer diagnosis has been validated by integrating the sensor into a microwave imaging (MWI) system and conducting comprehensive simulation studies. These studies underscore the device’s capability to detect abnormalities, particularly in distinguishing between healthy and cancerous cells. Benchmarking against state-of-the-art biosensors in recent literature indicates that the proposed sensor is highly competitive in terms of major performance indicators while maintaining a compact size.
Journal Article
Variable selection strategies and its importance in clinical prediction modelling
Clinical prediction models are used frequently in clinical practice to identify patients who are at risk of developing an adverse outcome so that preventive measures can be initiated. A prediction model can be developed in a number of ways; however, an appropriate variable selection strategy needs to be followed in all cases. Our purpose is to introduce readers to the concept of variable selection in prediction modelling, including the importance of variable selection and variable reduction strategies. We will discuss the various variable selection techniques that can be applied during prediction model building (backward elimination, forward selection, stepwise selection and all possible subset selection), and the stopping rule/selection criteria in variable selection (p values, Akaike information criterion, Bayesian information criterion and Mallows’ Cp statistic). This paper focuses on the importance of including appropriate variables, following the proper steps, and adopting the proper methods when selecting variables for prediction models.
Journal Article
Evaluation of serum amino acids and non-enzymatic antioxidants in drug-naïve first-episode major depressive disorder
Background
The alterations of biological markers are thought to be effective tools to understand the pathophysiology and management of major depressive disorder (MDD). A lot of researches has implied many markers for depression, but any of them fully discovered the association between the markers and depression. The present study investigated the serum levels of amino acids and non-enzymatic antioxidants in major depression, and also explained their association with depression.
Methods
This study examined 247 MDD patients and 248 healthy controls (HCs) matched by age and sex. The Hamilton Depression Rating Scale (Ham-D) was used to all the participants to measure the severity of depression. Quantification of serum amino acids, vitamin A and E were carried out using the HPLC system whereas vitamin C levels were measured by UV-spectrophotometer. All the statistical analysis was performed by SPSS statistical software (version 23.0). The independent sample t-test, the Mann-Whitney U test, and the Fisher’s exact test were applied to detect the group differences where a Bonferroni correction applied to the
p
value.
Results
It was observed that serum levels of four amino acids (methionine, phenylalanine, tryptophan, and tyrosine) along with three non-enzymatic antioxidants (vitamin A, E, and C) were significantly dropped in MDD patients compared to HCs (Cohen’s d (d): − 0.45, − 0.50, − 0.68, − 0.21, − 0.27, − 0.65, and − 0.24, respectively). Furthermore, Ham-D scores of cases were negatively correlated with serum levels of methionine (
r
= − 0.155,
p
= 0.015) and tyrosine (
r
= − 0.172,
p
= 0.007).
Conclusion
The present study suggests that lowered serum methionine, phenylalanine, tryptophan, tyrosine, and non-enzymatic antioxidants are associated with depression. The reduction of these parameters in MDD patients may be the consequence, and not the cause, of major depression.
Journal Article
Perfect metamaterial absorber with high fractional bandwidth for solar energy harvesting
A new perfect metamaterial absorber (PMA) with high fractional bandwidth (FBW) is examined and verified for solar energy harvesting. Solar cells based on perfect metamaterial give a chance to increase the efficiency of the system by intensifying the solar electromagnetic wave that incident on the device. The designed structure is mostly offered in the visible frequency range so as to exploit the solar's energy efficiently. Parametric investigations with regard to the measurements of the design structure are fulfilled to characterize the absorber. The finite-difference time-domain (FDTD) method-based CST simulator was used to keep the pattern parameters and absorbance analysis. The metamaterial shows almost 99.96% and 99.60% perfect absorption at 523.84 THz and 674.12 THz resonance frequencies. Moreover, absorption's FBW is studied, and 39.22% FBW is found. The results confirm that the designed PMA can attain very high absorption peak at two modes such as transverse electric (TE) and transverse magnetic (TM) mode. Other than the numerical outcomes demonstrated that the suggested configuration was also polarization angle insensitive. In addition, the change of absorbance of the structure has provided a new kind of sensor applications in these frequency ranges. Therefore, the suggested metamaterial absorber offers perfect absorption for visible frequency ranges and can be used for renewable solar energy harvesting applications.
Journal Article
Design and validation of ultra-compact metamaterial-based biosensor for non-invasive cervical cancer diagnosis in terahertz regime
Cervical cancer belongs to the most dangerous types of cancers posing considerable threat to women’s survival. It is most often diagnosed in the advanced stages as precancerous lesions are often symptom-free and difficult to identify. Microwave imaging, especially in terahertz (THz) range, is a convenient and noninvasive cancer detection tool. It enables characterization of biological tissues and discrimination between healthy and malignant ones. This study presents a novel triple-band biosensor based on metamaterials (MTMs). By leveraging unique properties of MTMs, the proposed biosensor operates as a perfect absorber. It exploits resonant modes in the THz spectrum to achieve remarkable sensitivity. Meticulous selection of the sensor geometry and dimensions enables efficient miniaturization. Meanwhile, utilization of frequency-domain data to detect refractive index changes improves resolution of cancerous tissue identification. Extensive numerical investigations corroborate its ability to carry out reliable early-stage cervical cancer diagnosis. This includes identification of the spatial extent of the malignant tissue. Excellent electrical properties of the sensor are accompanied by its compact size, which is highly desirable for non-invasive and portable applications.
Journal Article
A Negative Index Metamaterial-Inspired UWB Antenna with an Integration of Complementary SRR and CLS Unit Cells for Microwave Imaging Sensor Applications
This paper presents a negative index metamaterial incorporated UWB antenna with an integration of complementary SRR (split-ring resonator) and CLS (capacitive loaded strip) unit cells for microwave imaging sensor applications. This metamaterial UWB antenna sensor consists of four unit cells along one axis, where each unit cell incorporates a complementary SRR and CLS pair. This integration enables a design layout that allows both a negative value of permittivity and a negative value of permeability simultaneous, resulting in a durable negative index to enhance the antenna sensor performance for microwave imaging sensor applications. The proposed MTM antenna sensor was designed and fabricated on an FR4 substrate having a thickness of 1.6 mm and a dielectric constant of 4.6. The electrical dimensions of this antenna sensor are 0.20 λ × 0.29 λ at a lower frequency of 3.1 GHz. This antenna sensor achieves a 131.5% bandwidth (VSWR < 2) covering the frequency bands from 3.1 GHz to more than 15 GHz with a maximum gain of 6.57 dBi. High fidelity factor and gain, smooth surface-current distribution and nearly omni-directional radiation patterns with low cross-polarization confirm that the proposed negative index UWB antenna is a promising entrant in the field of microwave imaging sensors.
Journal Article