Determinants of female labor force participation: implications for policy in Qatar

The aim of this study was to examine the microlevel factors affecting women’s participation in the Qatar workforce, as the gender gap in employment is still wide, and addressing this issue remains an essential item on the government’s policy agenda. Data were collected via a national telephonic survey of a representative sample of Qatari nationals, chosen using simple random sampling. A regression analysis was performed with women’s employment, individual-level characteristics (e.g., age, education, and marital status), and household-level factors (e.g., number of children below 18 years of age and household monthly income) as the variables. The analytical model highlighted the microlevel predictors at the individual level as well as the public attitudes toward societal obstacles that have adverse effects on female labor force participation. The results revealed several indicators that affect women’s participation in the labor force, including education level, marital status, and age. These constructs were found to have the strongest (direct or indirect) effects in terms of pushing Qatari women into the labor market. The originality of this study lies in its ability to explain how state-directed initiatives can encourage women to participate in the labor market and thus facilitate a rapid increase in the number of employed women in Qatar. A methodological limitation of the cross-sectional survey design used in this study is that it limits the causations between the government interventions and the research outcomes. The findings indicate the need for further improvement in welfare regimes at the intrastate level.The Qatar National Research Fund [OSRA4-0324-19012]. Open Access funding is provided by the Qatar National Library

Molecular aspects in the biosynthesis of diterpene secondary metabolites in stevia rebaudiana and stevia ovata

Table of contents Page Acknowledgements i List of figures vii List of tables ix List of abbreviations xi Introduction 1 Chapter 1: Literature review 5 1.1 Stevia: history of discovery 5 1.2 General features of Stevia rebaudiana and Stevia ovata 6 1.3 Sweet glycosides in Stevia rebaudiana 8 1.3.1 Stevioside 10 1.3.1.1 Pharmaceutical uses of stevioside 10 1.3.1.2 Safety of stevioside 11 1.3.2 Rebaudioside A 12 1.3.2.1 Safety of rebaudioside A 12 1.3.3 Other steviol glycosides 13 1.3.4 Radical scavenging activity of steviol glycosides 13 1.4 Metabolic flux to gibberellins and steviol synthesis pathway 14 1.4.1 Isopentenyl pyrophosphate 14 1.4.2 Geranylgeranyl pyrophospate 18 1.4.3 Ent-kaurenoic acid as a common precursor for gibberellins and steviol 18 1.5 Different gene families involved in the biosynthetic pathway of steviol 20 1.5.1 Terpene cyclases 20 1.5.1.1 Ent-copalyl pyrophosphate synthase 21 1.5.1.2 Ent-kaurene synthase 22 1.5.2 Cytochrome P450 genes 24 1.5.2.1 From ent-kaurene to ent-kaurenoic acid 24 1.5.2.2 The branch point 26 1.5.3 Down-stream genes: UDP-dependent glycosyl transferases 26 1.5.3.1 Classification of SrUDP-dependent glycosyltransferases 28 1.6 Non-sweet glycosides in Stevia ovata 30 Chapter 2: Materials and Methods 33 2.1 Extraction and purification of ent-kaurenoic acid 33 2.1.1 Extraction of the plant material 33 2.1.2 Chromatographic separation and identification of ent-kaurenoic acid 33 2.1.3 Purification of ent-kaurenoic acid 34 2.1.4 Mass spectrometric analysis 34 2.1.5 Nuclear magnetic resonance (NMR) analysis 34 2.2 Cloning of a cytochrome P450 gene as possible candidate for KAHent 36 2.2.1 cDNA cloning and analysis 36 2.2.2 DNA extraction 39 2.3 Transcription pattern of the genes involved in the biosynthesis of steviol glycosides 40 2.3.1 Plant material and growth conditions 40 2.3.2 Steviol glycoside quantification 40 2.3.3 Extraction of RNA and cDNA synthesis 41 2.3.4 Choosing the endogenous control (the housekeeping gene) 41 2.3.5 Primer design 42 2.3.6 Quantification using RT-qPCR 43 2.3.7 Statistical analysis 44 2.4 Molecular analysis in Stevia ovata 44 2.4.1 Growth conditions, plant material and RNA extraction 44 2.4.2 RT-PCR and PCR experiments and cloning 44 2.4.3 RT-qPCR of SoCPSent transcription 50 2.4.4 Gene expression and activity analysis 50 2.4.4.1 Gateway expression system 50 2.4.4.2 Functional assay 53 2.4.4.3 Analysis of geranylgeraniol and copalol 53 Chapter 3: Extraction and purification of ent-kaurenoic acid 55 3.1 Introduction 55 3.2 Results 55 3.2.1 Extraction of ent-kaurenoic acid and preliminary LC-MS analysis 55 3.2.2 Purification of ent-kaurenoic acid 59 3.2.3 Characterization of compounds by EI-MS 61 3.2.3 Characterization of compounds by NMR 66 3.3 Discussion 67 Chapter 4: C-13 hydroxylation of ent-kaurenoic acid to steviol 69 4.1 Introduction 69 4.2 Results 69 4.2.1 cDNA cloning and analysis 69 4.2.2 Detection of the gap at the genomic level 73 4.2.3 Cloning of the whole gene from gDNA 74 4.3 Discussion 75 Chapter 5: Regulation of steviol glycoside biosynthesis by daylength and light 83 5.1 Introduction 83 5.2 Results 83 5.2.1 Steviol glycoside accumulation 83 5.2.2 Analysis of the transcription of the genes 86 5.2.2.1 Transcription pattern of up-stream genes 86 5.2.2.2 Transcription pattern of down-stream genes 94 5.2.3 Statistical analysis 100 5.3 Discussion 103 Chapter 6: Early steps in regulation of the biosynthesis of paniculosides in Stevia ovata 109 6.1 Introduction 109 6.2 Results 109 6.2.1 cDNA cloning and analysis 109 6.2.2 RT-qPCR anaylsis of SoCPSent 111 6.3 Discussion 112 Chapter 7: General conclusion and perspectives 119 Summary 123 Samenvatting 127 References 131 List of publications 153nrpages: 167status: publishe

A case of neonatal osteofibrous dysplasia with novel CDK12 and DDR2 mutations

Osteofibrous dysplasia [OFD] is a rare, benign pediatric fibro-osseous lesion that exclusively arises in the lower limbs. Apart from the limited number of familial OFD cases with MET mutation, no other genetic aberrations have been identified. Herein, we report a case of OFD in a four-month- old girl's leg with novel cyclin-dependent kinase 12 and discoidin domain receptor 2 gene mutations. Further studies to understand their role in the pathogenesis and clinical utility are needed

Machine Learning Models Reveal The Importance of Clinical Biomarkers for the Diagnosis of Alzheimer\u27s Disease

Alzheimer\u27s Disease (AD) is a neurodegenerative disease that causes complications with thinking capability, memory and behavior. AD is a major public health problem among the elderly in developed and developing countries. With the growth of AD around the world, there is a need to further expand our understanding of the roles different clinical measurements can have in the diagnosis of AD. In this work, we propose a machine learning-based technique to distinguish control subjects with no cognitive impairments, AD subjects, and subjects with mild cognitive impairment (MCI), often seen as precursors of AD. We utilized several machine learning (ML) techniques and found that Gradient Boosting Decision Trees achieved the highest performance above 84% classification accuracy. Also, we determined the importance of the features (clinical biomarkers) contributing to the proposed multi-class classification system. Further investigation on the biomarkers will pave the way to introduce better treatment plan for AD patients