Finnsanchez5579

Phenomics technologies allow quantitative assessment of phenotypes across a larger number of plant genotypes compared to traditional phenotyping approaches. The utilization of such technologies has enabled the generation of multidimensional plant traits creating big datasets. However, to harness the power of phenomics technologies, more sophisticated data analysis methods are required. In this study, Aphanomyces root rot (ARR) resistance in 547 lentil accessions and lines was evaluated using Red-Green-Blue (RGB) images of roots. We created a dataset of 6,460 root images that were annotated by a plant breeder based on the disease severity. Two approaches, generalized linear model with elastic net regularization (EN) and convolutional neural network (CNN), were developed to classify disease resistance categories into three classes resistant, partially resistant, and susceptible. The results indicated that the selected image features using EN models were able to classify three disease categories with an accuracy of up to 0.91 ± 0.004 (0.96 ± 0.005 resistant, 0.82 ± 0.009 partially resistant, and 0.92 ± 0.007 susceptible) compared to CNN with an accuracy of about 0.84 ± 0.009 (0.96 ± 0.008 resistant, 0.68 ± 0.026 partially resistant, and 0.83 ± 0.015 susceptible). The resistant class was accurately detected using both classification methods. However, partially resistant class was challenging to detect as the features (data) of the partially resistant class often overlapped with those of resistant and susceptible classes. Collectively, the findings provided insights on the use of phenomics techniques and machine learning approaches to provide quantitative measures of ARR resistance in lentil.Highly processed and energy-dense foods are contributing to the high and rising rates of non-communicable diseases and nutrient deficiencies in Solomon Islands. Non-communicable diseases currently cause 69% of deaths in Solomon Islands, and the rate is rising, fuelled in part by limited health system capacity to treat these conditions. Solomon Islands also has the highest reported undernourishment rate in the Pacific. Recent decades have seen several factors change the food and economic environment in Solomon Islands. Importantly, rural-to-urban migration has caused a disconnect between urban residents and access to land and home gardens. selleck compound This study aimed to examine the complexities of nutritious food access in urban Solomon Islands. Data were collected from 32 women in Honiara, the islands' capital, using a novel survey instrument. There were 3 important findings (1) the dominant influencers of the diet patterns described by participants in this study were food affordability and access to land on which to grow it, (2) all participants experienced food insecurity, and (3) reported diet patterns reflected unhealthy diets which were particularly high in processed and sugary foods. These findings suggest a need for improvements in the food environment in Honiara.The Solomon Islands is currently experiencing a change in disease burdens, from communicable to non-communicable diseases. Obesity is one of the leading non-communicable diseases causing death. Urgent action is needed to decrease the high economic and personal costs associated with obesity. This study proposes to determine behavioral and socioeconomic factors associated with obesity among different sex and age groups in an urban area of the Solomon Islands. In 2016, a cross-sectional study was conducted among adults aged 20 to 80 in Honiara, the capital of the Solomon Islands. Anthropometric measurements and a survey of socioeconomic status (SES) and behavioral status were conducted among 176 participants using a questionnaire. Multiple linear regression analysis was used to identify the socioeconomic factors significantly associated with higher body mass index (BMI) by age group. The study found a high prevalence of overweight (34%) and obesity (48%) in both sexes. Multiple linear regression analysis found that having a high-income level and being married were positively associated with higher BMI among young adults. In the middle age groups, the highest income level was positively associated with higher BMI. Young and middle-aged adults with a high SES might consume higher calorie food, contributing to weight gain, but this needs confirmation. Moreover, getting married might lead to more consistent meals and weight gain among the young age group. These findings suggest that health professionals have to consider the influence of income level and marital status on lifestyle choices when planning interventions that promote healthy lifestyles.

To compare the measurement of glucose uptake in primary invasive breast cancer using simultaneous, time-of-flight breast PET/MRI with prone time-of-flight PET/CT.

In this prospective study, women with biopsy-proven invasive breast cancer undergoing preoperative breast MRI from 2016 to 2018 were eligible. Participants who had fasted underwent prone PET/CT of the breasts approximately 60 minutes after injection of 370 MBq (10 mCi) fluorine 18 fluorodeoxyglucose (

F-FDG) followed by prone PET/MRI using standard clinical breast MRI sequences performed simultaneously with PET acquisition. Volumes of interest were drawn for tumors and contralateral normal breast fibroglandular tissue to calculate standardized uptake values (SUVs). Spearman correlation, Wilcoxon signed ranked test, Mann-Whitney test, and Bland-Altman analyses were performed.

Twenty-three women (mean age, 50 years; range, 33-70 years) were included. Correlation between tumor uptake values measured with PET/MRI and PET/CT was strong (



= 0.95-0.98). No difference existed between modalities for tumor maximum SUV (SUV

) normalized to normal breast tissue SUV

(normSUV

) (

= .58). The least amount of measurement bias was observed with normSUV

, +3.86% (95% limits of agreement -28.92, +36.64).

These results demonstrate measurement agreement between PET/CT, the current reference standard for tumor glucose uptake quantification, and simultaneous time-of-flight breast

F-FDG PET/MRI.

Breast, Comparative Studies, PET/CT, PET/MR

© RSNA, 2021See also the commentary by Mankoff and Surti in this issue.

These results demonstrate measurement agreement between PET/CT, the current reference standard for tumor glucose uptake quantification, and simultaneous time-of-flight breast 18F-FDG PET/MRI.Keywords Breast, Comparative Studies, PET/CT, PET/MR Supplemental material is available for this article. © RSNA, 2021See also the commentary by Mankoff and Surti in this issue.