Climate Change Impact and Adaptation Assessment on Food Consumption Utilizing a New Scenario Framework

We assessed the impacts of climate change and agricultural autonomous adaptation measures (changes in crop variety and planting dates) on food consumption and risk of hunger considering uncertainties in socioeconomic and climate conditions by using a new scenario framework. We combined a global computable general equilibrium model and a crop model (M-GAEZ), and estimated the impacts through 2050 based on future assumptions of socioeconomic and climate conditions. We used three Shared Socioeconomic Pathways as future population and gross domestic products, four Representative Concentration Pathways as a greenhouse gas emissions constraint, and eight General Circulation Models to estimate climate conditions. We found that (i) the adaptation measures are expected to significantly lower the risk of hunger resulting from climate change under various socioeconomic and climate conditions. (ii) population and economic development had a greater impact than climate conditions for risk of hunger at least throughout 2050, but climate change was projected to have notable impacts, even in the strong emission mitigation scenarios. (iii) The impact on hunger risk varied across regions because levels of calorie intake, climate change impacts and land scarcity varied by region

Socioeconomic factors and future challenges of the goal of limiting the increase in global average temperature to 1.5 °C

<p>The Paris Agreement has confirmed that the ultimate climate policy goal is to hold the increase in the global average temperature to well below 2 °C above pre-industrial levels and to pursue efforts to limit the increase to 1.5 °C. Moving the goal from 2 °C to 1.5 °C calls for much more concerted effort, and presents greater challenges and costs. This study uses an Asia-Pacific Integrated Model/Computable General Equilibrium (AIM/CGE) to evaluate the role of socioeconomic factors (e.g. technological cost and energy demand assumptions) in changing mitigation costs and achieving the 1.5 °C and 2 °C goals, and to identify the channels through which socioeconomic factors affect mitigation costs. Four families of socioeconomic factors were examined, namely low-carbon energy-supply technologies, end-use energy-efficiency improvements, lifestyle changes and biomass-technology promotion (technology cost reduction and social acceptance promotion). The results show that technological improvement in low-carbon energy-supply technologies is the most important factor in reducing mitigation costs. Moreover, under the constraints of the 1.5 °C goal, the relative effectiveness of other socioeconomic factors, such as energy efficiency improvement, lifestyle changes and biomass-related technology promotion, becomes more important in decreasing mitigation cost in the 1.5 °C scenarios than in the 2 °C scenarios.</p

Consequence of Climate Mitigation on the Risk of Hunger

Climate change and mitigation measures have three major impacts on food consumption and the risk of hunger: (1) changes in crop yields caused by climate change; (2) competition for land between food crops and energy crops driven by the use of bioenergy; and (3) costs associated with mitigation measures taken to meet an emissions reduction target that keeps the global average temperature increase to 2 °C. In this study, we combined a global computable general equilibrium model and a crop model (M-GAEZ), and we quantified the three impacts on risk of hunger through 2050 based on the uncertainty range associated with 12 climate models and one economic and demographic scenario. The strong mitigation measures aimed at attaining the 2 °C target reduce the negative effects of climate change on yields but have large negative impacts on the risk of hunger due to mitigation costs in the low-income countries. We also found that in a strongly carbon-constrained world, the change in food consumption resulting from mitigation measures depends more strongly on the change in incomes than the change in food prices

DataSheet_1_A cell-based assay for detection of anti-fibrillarin autoantibodies with performance equivalent to immunoprecipitation.pdf

Anti-fibrillarin autoantibodies are useful for the diagnosis and prognosis of systemic sclerosis (SSc). Anti-fibrillarin produces a clumpy nucleolar pattern in indirect immunofluorescence assay on HEp-2 cells (HEp-2 IFA). Here we develop and validate a reliable cell-based anti-fibrillarin assay (Fibrillarin/CBA) for use in clinical diagnostic laboratories. A TransMembrane Signal was fused to the human fibrillarin gene (TMS-fibrillarin). HEp-2 cells overexpressing transgenic TMS-fibrillarin at the cytoplasmic membrane were used as IFA substrate in the Fibrillarin/CBA. Sixty-two serum samples with nucleolar pattern in the HEp-2 IFA (41 clumpy; 21 homogeneous/punctate) were tested for anti-fibrillarin using Fibrillarin/CBA, immunoprecipitation (IP), line-blot and ELISA. In addition, samples from 106 SSc-patients were evaluated with Fibrillarin/CBA and the results were correlated with disease phenotypes. Thirty-eight of 41 samples with the clumpy nucleolar pattern (92.7%) were positive in the Fibrillarin/CBA, while all 21 samples with other nucleolar patterns were negative. Fibrillarin/CBA results agreed 100% with IP results. Among the 38 Fibrillarin/CBA-positive samples, only 15 (39.5%) and 11 (29%) were positive for anti-fibrillarin in line-blot and ELISA, respectively. Higher frequency of diffuse cutaneous SSc (dcSSc) phenotype (72.7% vs 36.8%; p=0.022), cardiac involvement (36.4% vs 6.5%; p=0.001) and scleroderma renal crisis (18.2% vs 3.3% p = 0.028) was observed in SSc patients with positive compared to negative Fibrillarin/CBA result. Performance of Fibrillarin/CBA in the detection of anti-fibrillarin autoantibodies was comparable to the gold standard IP. Positive Fibrillarin/CBA results correlated with disease phenotypes known to be associated with anti-fibrillarin autoantibodies, underscoring the clinical validation of this novel assay.</p

Microcystic Inner Nuclear Layer Changes and Retinal Nerve Fiber Layer Defects in Eyes with Glaucoma

<div><p>Objective</p><p>To examine microcystic inner nuclear layer (INL) changes in glaucomatous eyes and to determine associated factors.</p><p> Design</p><p>Retrospective, cross-sectional, observational study.</p><p> Methods</p><p>Two hundred seventeen eyes of 133 patients with primary open angle glaucoma (POAG), 41 eyes of 32 patients with preperimetric glaucoma and 181 normal eyes of 117 subjects were ultimately included. Microcystic INL lesions were examined with infrared fundus images and with 19 vertical spectral domain optical coherence tomography (SD-OCT) images in the macular area.</p><p>Results</p><p>Microcystic INL changes were observed in 6.0% of eyes with POAG, but none of the normal eyes or eyes with preperimetric glaucoma showed microcystic INL changes. The proportion of eyes with advanced glaucoma was significantly larger (<i>P</i> = 0.013) in eyes with microcystic lesions than without. The visual field mean deviation (MD) slope was also significantly worse (<i>P</i> = 0.027) in eyes with microcystic lesions. No significant differences were observed in age, sex, refraction, axial length, intraocular pressure, or MD value between eyes with and without microcystic INL lesions. In several cases, microcystic INL lesions occurred along with glaucomatous visual field progression. The retinal nerve fiber layer (RNFL) thickness (<i>P</i> = 0.013) and ganglion cell layer (GCL) + inner plexiform layer thickness (<i>P</i> = 0.023) were significantly lower in areas with microcystic lesions than without. The INL was also significantly thicker (<i>P</i> = 0.002) in areas with microcystic lesions.</p><p>Conclusions</p><p>Microcystic INL lesions in glaucomatous eyes are closely associated with RNFL and GCL thinning and correlated with worse MD slope. These INL lesions may indicate focal and progressive damage in glaucoma.</p></div

The left fundus of a 44-year-old woman with primary open angle glaucoma and microcystic inner nuclear layer (INL) lesions.

<p><b>A,</b> Infrared image shows perimacular hyporeflective patterns in the region with INL microcystic lesions (white arrows). <b>B, C,</b> Fundus (<b>B</b>) and red-free (<b>C</b>) photographs show retinal nerve fiber layer defects (NFLD, white arrows). Disc hemorrhage was also present at the upper NFLD. <b>D,</b> A Spectralis optical coherence tomography (OCT) image along the yellow line in <b>A</b> shows microcystic INL lesions (yellow arrows). The INL is thicker and the retinal nerve fiber and ganglion cell layers are thinner in the microcystic lesion area. This eye had a partial posterior vitreous detachment (white arrows). <b>E,</b> Pattern deviation map from Humphrey Visual Field Analyzer testing (24–2 Swedish interactive threshold algorithm standard program) showing visual field defects. An absolute scotoma at the superonasal test points closest to fixation corresponds to the location of the lower NFLD and microcystic INL lesions. <b>F,</b> Magnified OCT image (yellow box in <b>D</b>).</p

The OCT macular scanning protocol.

<p>The protocol consisted of 19 vertical scan lines (white arrows) over macular area. The scan was centered on the fovea and had a height of 30° and a width of 15°. Each of the 19 line scans was obtained by averaging 50 B-scans.</p

Right fundus of a 29-year-old woman with primary open angle glaucoma and microcystic inner nuclear layer (INL) lesions.

<p><b>A,</b> The infrared image shows a perimacular hyporeflective pattern in the region with INL microcystic changes (white arrow). <b>B,</b> A fundus photograph shows no evident retinal nerve fiber defect (NFLD). <b>C</b>, A red-free photograph shows NFLD in the region of microcystic INL changes (white arrows). <b>D,</b> A Spectralis optical coherence tomography (OCT) image along the yellow arrow in <b>A</b> shows microcystic INL lesions (yellow arrows). The INL is thicker and the retinal nerve fiber and ganglion cell layers are thinner in the region with microcystic lesions. This eye had a partial posterior vitreous detachment, with the vitreous still attached to the retinal surface above the microcystic lesions (white arrows). <b>E,</b> Pattern deviation map from Humphrey Visual Field Analyzer testing (24–2 Swedish interactive threshold algorithm standard program) showed superior visual field defects. An absolute scotoma was present at the superonasal test points closest to the fixation. <b>F,</b> A magnified OCT image (yellow box in <b>D</b>).</p

Comparison of retinal nerve fiber layer (RNFL), ganglion cell complex plus inner plexiform layer (GCC+IPL), inner nuclear layer (INL), and outer retinal thickness between at sites with and without microcystic changes.

<p>Measurements were taken at the opposite and equidistant site from a horizontal line passing through the foveal center (red line in <b>A</b>) for sites with and without INL lesions. <b>A,</b> An infrared fundus image shows measurement points (white arrows). <b>B,</b> A Spectralis optical coherence tomography (OCT) image along the yellow arrow in <b>A</b>. The RNFL (red bars), GCL+IPL (green bars), INL (yellow bars) and outer retinal thickness (brown bars) measured at sites with and without microcystic lesions (white arrows) and are shown in parts in <b>C, D, E</b> and <b>F</b>, respectively.</p

Changes over time in an eye with microcystic inner nuclear layer (INL).

<p>Changes appearing before significant visual field damage occurred. <b>A-D, E-H</b> and <b>I-L</b> show images and testing obtained in December of 2008, 2012, and 2013, respectively. <b>A, E, I,</b> Infrared images showed perimacular hyporeflective patterns (arrow heads) becoming more obvious over time. <b>B, C, F, G, J, K,</b> Spectralis OCT images oriented along arrows in <b>A, E</b> and <b>I</b>. <b>D, H</b> and <b>L,</b> Standard automated perimetry testing results (Humphrey Visual Field Analyzer, 24–2 Swedish interactive threshold algorithm standard program gray scale). Subtle microcystic changes were observed in INL (<b>B, C</b>). It was noticed that localized thinning of retinal nerve fiber layer and ganglion cell layer existed though no severe visual field defects were present (<b>B, C</b> and <b>D</b>). Microcystic changes became more distinct as visual field defects progressed (<b>F, G</b> and <b>H</b>). Microcystic lesion changes became less apparent (<b>F, G, J</b> and <b>K</b>) while the visual field remained stable (<b>H, L</b>).</p