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This study investigated the socio-cultural determinants of climate change adaptation and vulnerability among crop farmers in Ondo State, Southwestern Nigeria. The study specifically examined the vulnerability to climate change, determined the factors influencing the level of vulnerability, and determined factors affecting the adaptation to climate change and the vulnerability status of the respondents. Using a multi-stage sampling approach and the Delphi method, 150 respondents were selected from the three Senatorial Zones. Primary data were sourced with the aid of a survey and oral interviews. The collected data were analyzed using the vulnerability index, Ordinal logistic regression, and Heckman probit regression. The findings revealed that the socio-cultural characteristics of respondents contributed to their vulnerability to climate change, as indicated by an average livelihood vulnerability index (LVI) of 0.33. Notably, factors such as water availability and adaptation practices exhibited higher vulnerability indices of 0.49 and 0.42, respectively. The overall LVI and LVI-IPCC averages were 0.35 and 0.02, respectively, highlighting the existence of vulnerability among farming households. The results of ordinal logistic regression revealed that age, marital status, education level, and income from agriculture were statistically significant factors determining the level of vulnerability to climate change in the study area. Consequently, the results of the Heckman two-step regression model revealed that age, marital status, household size, education, religion, belief, family structure, and community teamwork were the significant factors affecting the adaptation and vulnerability to climate change in the area. The policy should be geared towards improving the socio-cultural factors for sustainable livelihoods with an income diversification strategy by the government for crop farmers to cushion the effects of low income realized from farming activities in the area. [ABSTRACT FROM AUTHOR]

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Background: Changes in myelin integrity are associated with the pathophysiology of many neurological diseases, including multiple sclerosis. However, noninvasive measurement of myelin injury and repair remains challenging. Advanced MRI techniques including diffusion tensor imaging (DTI), neurite orientation dispersion and density index (NODDI), and texture analysis have shown promise in quantifying subtle abnormalities in white matter structure.Purpose: To determine whether and how these advanced imaging methods help understand remyelination changes after demyelination using a mouse model.Study Type: Prospective, longitudinal.Animal Model: Demyelination was induced in the thoracic spinal cord of 21 mice using the chemical toxin lysolecithin.Field Strength/sequences: 9.4T ASSESSMENT: Imaging was done at day 7 (demyelination) and days 14 to 35 (ongoing remyelination) postsurgery, followed by histology. Image analysis focused on both lesions and peri-lesional areas where remyelination began. In histology, we quantified the complexity of tissue alignment using angular entropy, in addition to staining area.Statistical Analysis: Two-way analysis of variance was performed for assessing differences between tissue types and across timepoints, followed by post-hoc analysis to correct for multiple comparisons (P < 0.05).Results: All diffusion and texture parameters were worse in lesions than the control tissue (P < 0.05) except orientation dispersion index (ODI) and neurite density index (NDI) over late remyelination. Longitudinally, ODI decreased and NDI increased persistently in both lesions and peri-lesion regions (P < 0.05). Fractional anisotropy showed a mild decrease at day 35 after increase, when lesion texture heterogeneity showed a trend to decrease (P > 0.05). Both lesion size and angular entropy decreased over time, and no change in any measure in the control tissue.Data Conclusion: Diffusion and MRI texture metrics may provide compensatory information on myelin repair and ODI and NDI could be sensitive measures of evolving remyelination, deserving further validation.Level Of Evidence: 1 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;49:1750-1759. [ABSTRACT FROM AUTHOR]