1,721,075 research outputs found
Estimation of Child Undernutrition at Disaggregated Administrative Tiers of a North-Eastern District of Bangladesh:An Application of Small Area Estimation Method
No full textChildren of Sunamganj district located in the north-eastern part of Bangladesh are highly vulnerable to undernutrition and chronic food insecurity due to its geographic location, long-time waterlog, frequent flash floods, and underdeveloped infrastructure. In this study, child undernutrition indicators stunting and underweight are estimated at district, sub-district (Upzila) and union level administrative tiers of Sunamganj district employing the World Bank small area estimation (SAE) method to a Sunamganj household level survey data collected in 2018 and the census 2011 data of Sunamganj. District level prevalence of stunting and underweight are estimated as about 48.5% (95% CI: 45.3-51.7%) and 37.0% (95% CI: 34.6-39.8%) based on the SAE method. At upzila level, stunting varied from 41.0% to 54.9% and underweight varied from 24.0% to 53.4%; while the indicators varied over 19.5-59.7% and 20.2-56.8% respectively at union level. A significant number of unions are found as hotspots of higher underweight and stunting over the north, north-eastern and north-western parts of Sunamganj. Though the southern part of Sunamganj was homogeneous in the upzila level maps of stunting and underweight; significant number of heterogeneous unions are found in the union-level maps. The upzilas belong to the northern part particularly closer to the Indian border and haor areas are mostly vulnerable to stunting and underweight. The study findings on disaggregate level prevalence of stunting and underweight might help the concerned government and non-government organizations to prepare and implement aid-related programs on public health and nutrition
Using a Spatial Farm Microsimulation Model for Australia to Estimate the Impact of an External Shock on Farmer Incomes
No full textA greater uncertainty in climate conditions in Australia and external price shocks in commodity prices has posed a real question for communities on the impact of these external factors on farmers. Spatial microsimulation models are ideal for understanding the spatial impacts of various external shocks, including changes in commodity prices; changes in climate conditions; and changes in Government policy. This study demonstrates the building of a spatial microsimulation model to identify farmer financial stress in the Australian State of Victoria, and then shows how this model can be used to estimate the impact of an external shock such as a drop in the price of milk. The model is estimated for the Australian State of Victoria
Collagen and Chitin from Marine Resources and Their Interdisciplinary Applications
No full textMarine collagen and chitin exhibit significant applicative potential in the fields of drug discovery, drug delivery, wound healing, tissue engineering, antiaging, agriculture, and the environment. These two biopolymers also exhibit similar hierarchical structural organizations. After cellulose, chitin is the second most important natural polymer in the world, and has been identified in bacteria, fungi, plants, and marine invertebrates. Chitin can also be enzymatically deacetylated to chitosan, a more flexible and soluble biopolymer. As mentioned above, it has many applications, including in the biomedical, environmental, and agricultural sectors. Similarly, nature is a source of massive quantities of collagen, especially in marine organisms. It is the main fibrous structural protein in the extracellular matrix and connective tissue of animals. It contributes greatly to the development of products for biotechnology and medical applications.
On Propensity Score Methodology
No full textIn an observational study, researchers are constantly required to distinguish the effects caused by the assignment of treatment. Propensity score methodology is one way to determine the effects of, and their probabilities, given a vector of observed covariates, which is particularly popular in the fields of medical, pharmaceutical and social sciences. However, there are mixed views for the best methodologies to use and an overall understanding of the propensity score methodology. Also, there is minimal literature for propensity score methods being used within the broader scientific community. Propensity score methodology can be suited to determine effects caused by, not only treatment of pharmaceutical medication, but for “treatment” of some external event, proposed event or interaction within the wider community. For example, the effect on a regional community due to business closure, or a road by-pass would be a reasonable case of how propensity score methods can be further used within the wider scientific community
Determining Risk Factors of Antenatal Care Attendance and its Frequency in Bangladesh:An Application of Count Regression Analysis
No full textStandard Poisson and negative binomial regression models are the common count regression analysis tools for modelling the number of antenatal care (ANC) visits. Two-part (zero and count) models like zero-inflated and hurdle regression models are recommended for modelling ANC visits with excess zeros. The intra-cluster correlation (ICC) can be accounted by incorporating clusterspecific random intercepts in the corresponding standard and two-part models. The existence of excess zeros in the distribution of ANC visits in Bangladesh raises the issue of identifying a proper count regression model for the number of ANC visits covering the issues of overdispersion, zero-inflation, and ICC in determining the risk factors of ANC use and its frequency. The data have been extracted from the 2014 Bangladesh Demographic and Health Survey. The hurdle negative binomial regression model with cluster-specific random effects at both zero- and count- parts is found as the best fitted model. Women who have poor education status, live in poor households, have less access to mass media, and belong to Sylhet and Chittagong divisions are less likely to use prenatal care and to have more ANC visits. In addition, women who live in rural areas, depend on other family members’ decision for taking health care, and have unintended pregnancies had lower tendency to more ANC visits. The findings recommend incorporation of random community effects along with overdispersion and zero-inflation in modelling the ANC data of Bangladesh, and model selection should be model-driven rather than data-driven since practically assumption of structural zeros is tough to meet
Marine Skeletal Biopolymers and Proteins, and Their Biomedical Application
Full text linkThis book covers recent trends in all aspects of basic and applied scientific research on marine skeletal proteins and biopolymers (e.g., chitin, collagen), and their derivatives. Some recent innovations of marine proteins have been incorporated in this book that could be potentially applied in scientific and industrial research. Due to their broad array of biological functions in biopolymer- and protein-based drugs, such as anticancer, antimicrobial, bone tissue regeneration, antioxidant, and anti-aging functions, bioactive skeletal proteins and biopolymers have recently attracted a great amount of interest in the pharmaceutical, nutraceutical, and cosmeceutical industries (including anti-aging drugs)
Chitin and Collagen: Isolation, Purification, Characterization, and Applications
No full textThis reprint includes recent trends in all aspects of applied scientific research on chitin and collagen, including isolation, purification, and characterization. A few recent innovations in chitin and collagen have been incorporated into this reprint. These innovations could potentially be applied in various scientific and industrial research. Due to its broad array of biological functions such as anticancer, antimicrobial, bone tissue regeneration, antioxidant, and anti-aging activities, collagen has recently attracted vast interest in the pharmaceutical, nutraceutical, and cosmeceutical industries. Similarly, chitin and chitin-derived chitosan have many applications, including in the medical, environmental, and agricultural sectors
Identification of exosomal proteins in primary human bronchial tracheal epithelial cell HBTE and the H358, THP1 and MCF7 cell lines
Full text linkBackground: Early detection of cancer is of paramount importance for successful treatment. Unfortunately, this is currently complex and time consuming. New sources of biomarkers are needed to improve. Exosomes are nano sized extracellular vesicles released by almost all cells have gained much interest as a cancer biomarker source due to their ability to transfer genetic materials, stability and ease of availability.
Aims: The aim of this study is to investigate the potentials of exosomes as a source of biomarkers of cancer in general and lung cancer in particular. To achieve this, exosomes from three difference cancer cell lines (lung cancer H358, leukaemia THP1 and breast cancer MCF7) and a primary lung cell HBTE were isolated and their protein contents were analysed to establish whether cancer specific proteins are present.
Methods and Materials: Exosomes were isolated and characterized by scanning (SEM) and transmission electron microscopy (TEM), dynamic light scattering (DLS) and Western Blot analysis. The exosome number and protein profile were analysed at different cellular growth stages using Exo-Elisa based on exosomal marker CD63 and mass spectrometry (MS) respectively. LC-MS based proteomic approach has been used to compare the proteomic profile of exosomes from three cancer cells. Finally, comparative proteomic study and gene expression analysis were carried out between exosomes from lung cancer cell (H358) and its counterpart normal cell (HBTE)
Results and Discussions: Successful isolation of exosomes from H358, THP1 and MCF7 was confirmed based on their size distribution (ranging from 96.54±28.53nm to 128.06±17.74nm) and by the presence of exosomal markers (CD63, CD81, CD9 and Hsp70). The number of exosomes released/cell was shown to increase with time ranging from 14500 on day 1 to 18000 at day 15. Interestingly, MS analysis revealed that, alpha-2-macroglobulin (A2M) and pregnancy zone protein was present only in stationary phase indicative of the oxidative stress.
Comparative proteomic study by LC-MS identified a total of 613 proteins commonly found across three cell lines. A large proportion of membranous proteins were identified including integrins, catenins, cadherins, and cathepsins. Most of which are involved in molecular signalling, cellular growth and transport, supporting the role of exosomes in cellular communication. Several adhesion molecules such as integrins, laminlins, catenins as well as cadherins and cathepsins were also identified as differentially expressed between different types of cancer derived exosomes.
Proteomic profiling of HBTE cell derived exosomes revealed 1011 proteins which only partially overlapped with those identified in H358 exosomes. A total of 205 proteins were specific for the cancerous lung cell line derived exosomes. Of particular interest was the identification of CTNNB1, an adhesion molecule known to be present in several other lung cancers, making it an ideal candidate for biomarker for non-small cell lung cancer, bronchioalveloar carcinoma. Gene expression analysis revealed that this protein is expressed at cellular level in both cancerous and normal lung cells, albeit found in a significantly higher level in H358 (p≤0.05).
Conclusion: This is the first report to show successful isolation and characterization of exosomes from H358 and HBTE. Comparative proteomic analysis of the newly isolated exosomes not only revealed that exosomes are a good source of lung cancer biomarkers but identified a potential candidate. CTNNB1 was selectively found in lung cancer cell derived exosomes but not in the counterpart normal cell (HBTE) and was selected for further investigation
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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