Influence of Implementing Inquiry-based Instruction on Science Learning Motivation and Interest: A Perspective of Comparison

AbstractThe purpose of this study was to explore the influence of implementing inquiry-based instruction on science-learning motivation and interest. The participants included students from three high schools located north, west, and south of Taiwan.The results showed that after participating in the implementation of inquiry-based instruction, science learning motivation and interest were both increased. Among them, School A achieved the best learning effect. Significant variation was observed in terms of self-efficacy and performance goals with regard to learning motivation; considerable differences in learning interests were also seen with respect to attitude towards science, learning atmosphere, learning difficulties, and learning commitment

Comorbidity and dementia: A nationwide survey in Taiwan

Background Comorbid medical diseases are highly prevalent in the geriatric population, imposing hardship on healthcare services for demented individuals. Dementia also complicates clinical care for other co-existing medical conditions. This study investigated the comorbidities associated with dementia in the elderly population aged 65 years and over in Taiwan. Methods We conducted a nationwide, population-based, cross-sectional survey; participants were selected by computerized random sampling from all 19 Taiwan counties between December 2011 and March 2013. After exclusion of incomplete or erroneous data, 8,456 subjects were enrolled. Of them, 6,183 were cognitively normal (control group), 1,576 had mild cognitive impairment (MCI), and 697 had dementia. We collected information about types of comorbidities (i.e., vascular risk factors, lung diseases, liver diseases, gastrointestinal diseases, and cancers), Charlson comorbidity index score, and demographic variables to compare subjects with normal cognition, MCI, and dementia. Results Regardless of the cognitive condition, over 60% of the individuals in each group had at least one comorbid disease. The proportion of subjects possessing at least three comorbidities was higher in those with cognitive impairment (MCI 20.9%, dementia 27.3%) than in control group (15%). Hypertension and diabetes mellitus were the most common comorbidities. The mean number of comorbidities and Charlson comorbidity index score were greater in MCI and dementia groups than in control group. Logistic regression demonstrated that the comorbidities significantly associated with MCI and dementia were cerebrovascular disease (OR 3.35, CI 2.62–4.28), cirrhosis (OR 3.29, CI 1.29–8.41), asthma (OR 1.56, CI 1.07–2.27), and diabetes mellitus (OR 1.24, CI 1.07–1.44). Conclusion Multiple medical comorbid diseases are common in older adults, especially in those with cognitive impairment. Cerebrovascular disease, cirrhosis, asthma, and diabetes mellitus are important contributors to cognitive deterioration in the elderly. Efforts to lower cumulative medical burden in the geriatric population may benefit cognitive function

Comorbidity and dementia: A nationwide survey in Taiwan

Background Comorbid medical diseases are highly prevalent in the geriatric population, imposing hardship on healthcare services for demented individuals. Dementia also complicates clinical care for other co-existing medical conditions. This study investigated the comorbidities associated with dementia in the elderly population aged 65 years and over in Taiwan. Methods We conducted a nationwide, population-based, cross-sectional survey; participants were selected by computerized random sampling from all 19 Taiwan counties between December 2011 and March 2013. After exclusion of incomplete or erroneous data, 8,456 subjects were enrolled. Of them, 6,183 were cognitively normal (control group), 1,576 had mild cognitive impairment (MCI), and 697 had dementia. We collected information about types of comorbidities (i.e., vascular risk factors, lung diseases, liver diseases, gastrointestinal diseases, and cancers), Charlson comorbidity index score, and demographic variables to compare subjects with normal cognition, MCI, and dementia. Results Regardless of the cognitive condition, over 60% of the individuals in each group had at least one comorbid disease. The proportion of subjects possessing at least three comorbidities was higher in those with cognitive impairment (MCI 20.9%, dementia 27.3%) than in control group (15%). Hypertension and diabetes mellitus were the most common comorbidities. The mean number of comorbidities and Charlson comorbidity index score were greater in MCI and dementia groups than in control group. Logistic regression demonstrated that the comorbidities significantly associated with MCI and dementia were cerebrovascular disease (OR 3.35, CI 2.62–4.28), cirrhosis (OR 3.29, CI 1.29–8.41), asthma (OR 1.56, CI 1.07–2.27), and diabetes mellitus (OR 1.24, CI 1.07–1.44). Conclusion Multiple medical comorbid diseases are common in older adults, especially in those with cognitive impairment. Cerebrovascular disease, cirrhosis, asthma, and diabetes mellitus are important contributors to cognitive deterioration in the elderly. Efforts to lower cumulative medical burden in the geriatric population may benefit cognitive function

Visually Relating Gene Expression and in vivo DNA Binding Data

Gene expression and in vivo DNA binding data provide important information for understanding gene regulatory networks: in vivo DNA binding data indicate genomic regions where transcription factors are bound, and expression data show the output resulting from this binding. Thus, there must be functional relationships between these two types of data. While visualization and data analysis tools exist for each data type alone, there is a lack of tools that can easily explore the relationship between them. We propose an approach that uses the average expression driven by multiple of ciscontrol regions to visually relate gene expression and in vivo DNA binding data. We demonstrate the utility of this tool with examples from the network controlling early Drosophila development. The results obtained support the idea that the level of occupancy of a transcription factor on DNA strongly determines the degree to which the factor regulates a target gene, and in some cases also controls whether the regulation is positive or negative

Muscle Contraction and Force: the Importance of an Ancillary Network, Nutrient Supply and Waste Removal

Muscle contraction studies often focus solely on myofibres and the proteins known to be involved in the processes of sarcomere shortening and cross-bridge cycling, but skeletal muscle also comprises a very elaborate ancillary network of capillaries, which not only play a vital role in terms of nutrient delivery and waste product removal, but are also tethered to surrounding fibres by collagen ”wires”. This paper therefore addresses aspects of the ancillary network of skeletal muscle at both a microscopic and functional level in order to better understand its role holistically as a considerable contributor to force transfer within muscular tissue

Mechanism of Regulation of Big-Conductance Ca2+-Activated K+ Channels by mTOR Complex 2 in Podocytes

Podocytes, dynamic polarized cells wrapped around glomerular capillaries, are an essential component of the glomerular filtration barrier. BK channels consist of one of the slit diaphragm (SD) proteins in podocytes, interact with the actin cytoskeleton, and play vital roles in glomerular filtration. Mechanistic target of rapamycin (mTOR) complexes regulate expression of SD proteins, as well as cytoskeleton structure, in podocytes. However, whether mTOR complexes regulate podocyte BK channels is still unclear. Here, we investigated the mechanism of mTOR complex regulation of BK channels via real-time PCR, western blot, immunofluorescence, and patch clamping. Inhibiting mTORC1 with rapamycin or downregulating Raptor had no significant effect on BK channel mRNA and protein levels and bioactivity. However, the dual inhibitor of mTORC1 and mTORC2 AZD8055 and short hairpin RNA targeting Rictor downregulated BK channel mRNA and protein levels and bioactivity. In addition, MK2206, GF109203X, and GSK650394, which are inhibitors of Akt, PKCα, and SGK1, respectively, were employed to test the downstream signaling pathway of mTORC2. MK2206 and GF109203X had no effect on BK channel protein levels. MK2206 caused an obvious decrease in the current density of the BK channels. Moreover, GSK650394 downregulated the BK channel protein and mRNA levels. These results indicate mTORC2 not only regulates the distribution of BK channels through Akt, but also modulates BK channel protein expression via SGK1 in podocytes

A forward-backward fragment assembling algorithm for the identification of genomic amplification and deletion breakpoints using high-density single nucleotide polymorphism (SNP) array

<p>Abstract</p> <p>Background</p> <p>DNA copy number aberration (CNA) is one of the key characteristics of cancer cells. Recent studies demonstrated the feasibility of utilizing high density single nucleotide polymorphism (SNP) genotyping arrays to detect CNA. Compared with the two-color array-based comparative genomic hybridization (array-CGH), the SNP arrays offer much higher probe density and lower signal-to-noise ratio at the single SNP level. To accurately identify small segments of CNA from SNP array data, segmentation methods that are sensitive to CNA while resistant to noise are required.</p> <p>Results</p> <p>We have developed a highly sensitive algorithm for the edge detection of copy number data which is especially suitable for the SNP array-based copy number data. The method consists of an over-sensitive edge-detection step and a test-based forward-backward edge selection step.</p> <p>Conclusion</p> <p>Using simulations constructed from real experimental data, the method shows high sensitivity and specificity in detecting small copy number changes in focused regions. The method is implemented in an R package FASeg, which includes data processing and visualization utilities, as well as libraries for processing Affymetrix SNP array data.</p

Writing in Britain and Ireland, c. 400 to c. 800

No abstract available

Tissue-specific gene expression templates for accurate molecular characterization of the normal physiological states of multiple human tissues with implication in development and cancer studies

<p>Abstract</p> <p>Background</p> <p>To elucidate the molecular complications in many complex diseases, we argue for the priority to construct a model representing the normal physiological state of a cell/tissue.</p> <p>Results</p> <p>By analyzing three independent microarray datasets on normal human tissues, we established a quantitative molecular model GET, which consists of 24 tissue-specific <it>G</it>ene <it>E</it>xpression <it>T</it>emplates constructed from a set of 56 genes, for predicting 24 distinct tissue types under disease-free condition. 99.2% correctness was reached when a large-scale validation was performed on 61 new datasets to test the tissue-prediction power of GET. Network analysis based on molecular interactions suggests a potential role of these 56 genes in tissue differentiation and carcinogenesis.</p> <p>Applying GET to transcriptomic datasets produced from tissue development studies the results correlated well with developmental stages. Cancerous tissues and cell lines yielded significantly lower correlation with GET than the normal tissues. GET distinguished melanoma from normal skin tissue or benign skin tumor with 96% sensitivity and 89% specificity.</p> <p>Conclusions</p> <p>These results strongly suggest that a normal tissue or cell may uphold its normal functioning and morphology by maintaining specific chemical stoichiometry among genes. The state of stoichiometry can be depicted by a compact set of representative genes such as the 56 genes obtained here. A significant deviation from normal stoichiometry may result in malfunction or abnormal growth of the cells.</p