13 research outputs found
Socioeconomic impacts of innovative dairy supply chain practices. The case of the Laiterie du Berger in the Senegalese Sahel
This study analyzes the Laiterie Du Berger (LDB)'s milk supply chain and its contribution to strengthening the food security and socioeconomic resources of Senegalese Sahelian pastoral households. Porter's value chain model is used to characterize the innovations introduced by the LDB dairy in its milk inbound logistics and supplier relationships. A socioeconomic food security index and qualitative data are used to assess the dairy's supply chain's contribution to strengthen smallholder households' livelihoods. Data for this research were obtained through individual surveys, focus groups and in-depth interviews of LDB managers and milk suppliers. Results show that milk income contributes significantly to household food security. Suppliers who stabilize their dairy income between rainy and dry seasons, diversify income sources and have larger herds are more likely to remain food secure. The LDB innovations contribute by helping herders access biophysical and economic resources, leading to better livestock feed and household food security. (Résumé d'auteur
AUT772813_Supplementary_material – Supplemental material for Prenatal and perinatal risk factors and the clinical implications on autism spectrum disorder
<p>Supplemental material, AUT772813_Supplementary_material for Prenatal and perinatal risk
factors and the clinical implications on autism spectrum disorder by Yi-Ling Chien,
Miao-Chun Chou, Wen-Jiun Chou, Yu-Yu Wu, Wen-Che Tsai, Yen-Nan Chiu and Susan Shur-Fen Gau
in Autism</p
Legislative Documents
Also, variously referred to as: Senate bills; Senate documents; Senate legislative documents; legislative documents; and General Court documents
AUT772813_Lay_Abstract – Supplemental material for Prenatal and perinatal risk factors and the clinical implications on autism spectrum disorder
<p>Supplemental material, AUT772813_Lay_Abstract for Prenatal and perinatal risk factors and
the clinical implications on autism spectrum disorder by Yi-Ling Chien, Miao-Chun Chou,
Wen-Jiun Chou, Yu-Yu Wu, Wen-Che Tsai, Yen-Nan Chiu and Susan Shur-Fen Gau in Autism</p
Table_3_Blood-Bourne MicroRNA Biomarker Evaluation in Attention-Deficit/Hyperactivity Disorder of Han Chinese Individuals: An Exploratory Study.xls
<p>Background: Attention-deficit/hyperactivity disorder (ADHD) is a highly genetic neurodevelopmental disorder, and its dysregulation of gene expression involves microRNAs (miRNAs). The purpose of this study was to identify potential miRNAs biomarkers and then use these biomarkers to establish a diagnostic panel for ADHD.</p><p>Design and methods: RNA samples from white blood cells (WBCs) of five ADHD patients and five healthy controls were combined to create one pooled patient library and one control library. We identified 20 candidate miRNAs with the next-generation sequencing (NGS) technique (Illumina). Blood samples were then collected from a Training Set (68 patients and 54 controls) and a Testing Set (20 patients and 20 controls) to identify the expression profiles of these miRNAs with real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR). We used receiver operating characteristic (ROC) curves and the area under the curve (AUC) to evaluate both the specificity and sensitivity of the probability score yielded by the support vector machine (SVM) model.</p><p>Results: We identified 13 miRNAs as potential ADHD biomarkers. The ΔCt values of these miRNAs in the Training Set were integrated to create a biomarker model using the SVM algorithm, which demonstrated good validity in differentiating ADHD patients from control subjects (sensitivity: 86.8%, specificity: 88.9%, AUC: 0.94, p < 0.001). The results of the blind testing showed that 85% of the subjects in the Testing Set were correctly classified using the SVM model alignment (AUC: 0.91, p < 0.001). The discriminative validity is not influenced by patients' age or gender, indicating both the robustness and the reliability of the SVM classification model.</p><p>Conclusion: As measured in peripheral blood, miRNA-based biomarkers can aid in the differentiation of ADHD in clinical settings. Additional studies are needed in the future to clarify the ADHD-associated gene functions and biological mechanisms modulated by miRNAs.</p
Image_1_Blood-Bourne MicroRNA Biomarker Evaluation in Attention-Deficit/Hyperactivity Disorder of Han Chinese Individuals: An Exploratory Study.tif
<p>Background: Attention-deficit/hyperactivity disorder (ADHD) is a highly genetic neurodevelopmental disorder, and its dysregulation of gene expression involves microRNAs (miRNAs). The purpose of this study was to identify potential miRNAs biomarkers and then use these biomarkers to establish a diagnostic panel for ADHD.</p><p>Design and methods: RNA samples from white blood cells (WBCs) of five ADHD patients and five healthy controls were combined to create one pooled patient library and one control library. We identified 20 candidate miRNAs with the next-generation sequencing (NGS) technique (Illumina). Blood samples were then collected from a Training Set (68 patients and 54 controls) and a Testing Set (20 patients and 20 controls) to identify the expression profiles of these miRNAs with real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR). We used receiver operating characteristic (ROC) curves and the area under the curve (AUC) to evaluate both the specificity and sensitivity of the probability score yielded by the support vector machine (SVM) model.</p><p>Results: We identified 13 miRNAs as potential ADHD biomarkers. The ΔCt values of these miRNAs in the Training Set were integrated to create a biomarker model using the SVM algorithm, which demonstrated good validity in differentiating ADHD patients from control subjects (sensitivity: 86.8%, specificity: 88.9%, AUC: 0.94, p < 0.001). The results of the blind testing showed that 85% of the subjects in the Testing Set were correctly classified using the SVM model alignment (AUC: 0.91, p < 0.001). The discriminative validity is not influenced by patients' age or gender, indicating both the robustness and the reliability of the SVM classification model.</p><p>Conclusion: As measured in peripheral blood, miRNA-based biomarkers can aid in the differentiation of ADHD in clinical settings. Additional studies are needed in the future to clarify the ADHD-associated gene functions and biological mechanisms modulated by miRNAs.</p
Table_4_Blood-Bourne MicroRNA Biomarker Evaluation in Attention-Deficit/Hyperactivity Disorder of Han Chinese Individuals: An Exploratory Study.doc
<p>Background: Attention-deficit/hyperactivity disorder (ADHD) is a highly genetic neurodevelopmental disorder, and its dysregulation of gene expression involves microRNAs (miRNAs). The purpose of this study was to identify potential miRNAs biomarkers and then use these biomarkers to establish a diagnostic panel for ADHD.</p><p>Design and methods: RNA samples from white blood cells (WBCs) of five ADHD patients and five healthy controls were combined to create one pooled patient library and one control library. We identified 20 candidate miRNAs with the next-generation sequencing (NGS) technique (Illumina). Blood samples were then collected from a Training Set (68 patients and 54 controls) and a Testing Set (20 patients and 20 controls) to identify the expression profiles of these miRNAs with real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR). We used receiver operating characteristic (ROC) curves and the area under the curve (AUC) to evaluate both the specificity and sensitivity of the probability score yielded by the support vector machine (SVM) model.</p><p>Results: We identified 13 miRNAs as potential ADHD biomarkers. The ΔCt values of these miRNAs in the Training Set were integrated to create a biomarker model using the SVM algorithm, which demonstrated good validity in differentiating ADHD patients from control subjects (sensitivity: 86.8%, specificity: 88.9%, AUC: 0.94, p < 0.001). The results of the blind testing showed that 85% of the subjects in the Testing Set were correctly classified using the SVM model alignment (AUC: 0.91, p < 0.001). The discriminative validity is not influenced by patients' age or gender, indicating both the robustness and the reliability of the SVM classification model.</p><p>Conclusion: As measured in peripheral blood, miRNA-based biomarkers can aid in the differentiation of ADHD in clinical settings. Additional studies are needed in the future to clarify the ADHD-associated gene functions and biological mechanisms modulated by miRNAs.</p
Genome-Wide Association Study for Autism Spectrum Disorder in Taiwanese Han Population
<div><p>Background</p><p>Autism spectrum disorder (ASD) is a neurodevelopmental disorder with strong genetic components. Several recent genome-wide association (GWA) studies in Caucasian samples have reported a number of gene regions and loci correlated with the risk of ASD—albeit with very little consensus across studies.</p><p>Methods</p><p>A two-stage GWA study was employed to identify common genetic variants for ASD in the Taiwanese Han population. The discovery stage included 315 patients with ASD and 1,115 healthy controls, using the Affymetrix SNP array 6.0 platform for genotyping. Several gene regions were then selected for fine-mapping and top markers were examined in extended samples. Single marker, haplotype, gene-based, and pathway analyses were conducted for associations.</p><p>Results</p><p>Seven SNPs had p-values ranging from 3.4~9.9*10<sup>−6</sup>, but none reached the genome-wide significant level. Five of them were mapped to three known genes (<i>OR2M4</i>, <i>STYK1</i>, and <i>MNT</i>) with significant empirical gene-based p-values in <i>OR2M4</i> (p = 3.4*10<sup>−5</sup>) and <i>MNT</i> (p = 0.0008). Results of the fine-mapping study showed single-marker associations in the <i>GLIS1</i> (rs12082358 and rs12080993) and <i>NAALADL2</i> (rs3914502 and rs2222447) genes, and gene-based associations for the <i>OR2M3-OR2T5</i> (olfactory receptor genes, p = 0.02), and <i>GLIPR1/KRR1</i> gene regions (p = 0.015). Pathway analyses revealed important pathways for ASD, such as olfactory and G protein–coupled receptors signaling pathways.</p><p>Conclusions</p><p>We reported Taiwanese Han specific susceptibility genes and variants for ASD. However, further replication in other Asian populations is warranted to validate our findings. Investigation in the biological functions of our reported genetic variants might also allow for better understanding on the underlying pathogenesis of autism.</p></div
Manhattan plot of genome-wide association analysis.
<p>Results of genome-wide association analysis (–log<sub>10</sub>P) are shown in chromosomal order for 546,171 SNPs that were tested for association in the initial sample of 315 ASD cases and 1115 controls. The horizontal line indicates a P-value of 10<sup>−5</sup>.</p
Pathway annotation for significant genes from gene-based association analyses in the GWA study of autism.
<p>Note: FDR (False Discovery Rate)</p><p>Pathway annotation for significant genes from gene-based association analyses in the GWA study of autism.</p