Prediction of strawberry yield based on receptacle detection and Bayesian inference

The receptacle of strawberry is a more direct part than the flower for predicting yield as they eventually become fruits. Thus, we tried to predict the yield by combining an AI technique for receptacle detection in images and statistical analysis on the relationship between the number of receptacles detected and the strawberry yield over a period of time. Five major cultivars were cultivated to consider the cultivar characteristics and environmental factors for two years were collected to consider the climate difference. Faster R–CNN based object detector was used to estimate the number of receptacles per strawberry plant in given two-dimensional images, which achieved a mAP of 0.6587 for our dataset. However, not all receptacles appear on the two-dimensional images, and Bayesian analysis was used to model the uncertainty associated with the number of receptacles missed by the AI. After estimating the probability of fruiting per receptacle, prediction models for the total strawberry yield at the end of harvest season were evaluated. Even though the detection accuracy was not perfect, the results indicated that counting the receptacles by object detection and estimating the probability of fruiting per receptacle by Bayesian modeling are more useful for predicting the total yield per plant than knowing its cumulative yield during the first month

TCF/β-catenin plays an important role in HCCR-1 oncogene expression

<p>Abstract</p> <p>Background</p> <p>Oncogene <it>HCCR-1 </it>functions as a negative regulator of the p53 and contributes to tumorigenesis of various human tissues. However, it is unknown how <it>HCCR-1 </it>contributes to the cellular and biochemical mechanisms of human tumorigenesis.</p> <p>Results</p> <p>In this study, we showed how the expression of <it>HCCR-1 </it>is modulated. The luciferase activity assay indicated that the <it>HCCR-1 </it>5'-flanking region at positions -166 to +30 plays an important role in <it>HCCR-1 </it>promoter activity. Computational analysis of this region identified two consensus sequences for the T-cell factor (TCF) located at -26 to -4 (Tcf1) and -136 to -114 (Tcf2). Mutation at the Tcf1 site led to a dramatic decrease in promoter activity. Mobility shift assays (EMSA) revealed that nuclear proteins bind to the Tcf1 site, but not to the Tcf2 site. LiCl, Wnt signal activator by GSK-3β inhibition, significantly increased reporter activities in wild-type Tcf1-containing constructs, but were without effect in mutant Tcf1-containing constructs in HEK/293 cells. In addition, endogenous <it>HCCR-1 </it>expression was also increased by treatment with GSK-3β inhibitor, LiCl or AR-A014418 in HEK/293 and K562 cells. Finally, we also observed that the transcription factor, TCF, and its cofactor, β-catenin, bound to the Tcf1 site.</p> <p>Conclusion</p> <p>These findings suggest that the Tcf1 site on the <it>HCCR-1 </it>promoter is a major element regulating <it>HCCR-1 </it>expression and abnormal stimulation of this site may induce various human cancers.</p

Anatomical evaluation of CT-MRI combined femoral model

<p>Abstract</p> <p>Background</p> <p>Both CT and MRI are complementary to each other in that CT can produce a distinct contour of bones, and MRI can show the shape of both ligaments and bones. It will be ideal to build a CT-MRI combined model to take advantage of complementary information of each modality. This study evaluated the accuracy of the combined femoral model in terms of anatomical inspection.</p> <p>Methods</p> <p>Six normal porcine femora (180 ± 10 days, 3 lefts and 3 rights) with ball markers were scanned by CT and MRI. The 3D/3D registration was performed by two methods, i.e. the landmark-based 3 points-to-3 points and the surface matching using the iterative closest point (ICP) algorithm. The matching accuracy of the combined model was evaluated with statistical global deviation and locally measure anatomical contour-based deviation. Statistical analysis to assess any significant difference between accuracies of those two methods was performed using univariate repeated measures ANOVA with the Turkey post hoc test.</p> <p>Results</p> <p>This study revealed that the local 2D contour-based measurement of matching deviation was 0.5 ± 0.3 mm in the femoral condyle, and in the middle femoral shaft. The global 3D contour matching deviation of the landmark-based matching was 1.1 ± 0.3 mm, but local 2D contour deviation through anatomical inspection was much larger as much as 3.0 ± 1.8 mm.</p> <p>Conclusion</p> <p>Even with human-factor derived errors accumulated from segmentation of MRI images, and limited image quality, the matching accuracy of CT-&-MRI combined 3D models was 0.5 ± 0.3 mm in terms of local anatomical inspection.</p

Ultra-Processed Food Consumption and Obesity in Korean Adults

Background This study aimed to investigate the association between consumption of ultra-processed foods (UPF) and obesity in Korean adults. Methods We included the Cardiovascular and Metabolic Diseases Etiology Research Center cohort study baseline data of adults aged 30 to 64 years who completed a validated food frequency questionnaire. UPF was defined using the NOVA food classification. Multivariable linear and logistic regression analyses were performed to assess the association of dietary energy contribution of UPF with obesity indicators (body mass index [BMI], obesity, waist circumference [WC], and abdominal obesity). Results Consumption of UPF accounted for 17.9% of total energy intake and obesity and abdominal obesity prevalence was 35.4% and 30.2%, respectively. Compared with those in the lowest quartile of UPF consumption, adults in the highest quartile had greater BMI (β=0.36; 95% confidence interval [CI], 0.15 to 0.56), WC (β=1.03; 95% CI, 0.46 to 1.60), higher odds of having obesity (odds ratio [OR], 1.24; 95% CI, 1.07 to 1.45), and abdominal obesity (OR, 1.34; 95% CI, 1.14 to 1.57), after adjusting for sociodemographic characteristics, health-related behaviors, and family history of diseases. Dose-response associations between UPF consumption and obesity indicators were consistently found (all P trend <0.01). However, the strength of association was halved for all obesity indicators after further adjustments for total energy intake and overall diet quality score, and the trend toward association for obesity and WC disappeared. Conclusion Our finding supports the evidence that consumption of UPF is positively associated with obesity among Korean adults

Estimation of utility weights for human papilloma virus-related health states according to disease severity

Scenarios for the different HPV-related health states. (DOCX 38 kb

Fibrinogen gamma-A chain precursor in CSF: a candidate biomarker for Alzheimer's disease

<p>Abstract</p> <p>Background</p> <p>Cerebrospinal fluid (CSF) may be valuable for exploring protein markers for the diagnosis of Alzheimer's disease (AD). The prospect of early detection and treatment, to slow progression, holds hope for aging populations with increased average lifespan. The aim of the present study was to investigate candidate CSF biological markers in patients with mild cognitive impairment (MCI) and AD and compare them with age-matched normal control subjects.</p> <p>Methods</p> <p>We applied proteomics approaches to analyze CSF samples derived from 27 patients with AD, 3 subjects with MCI and 30 controls. The AD group was subdivided into three groups by clinical severity according to clinical dementia rating (CDR), a well known clinical scale for dementia.</p> <p>Results</p> <p>We demonstrated an elevated level of fibrinogen gamma-A chain precursor protein in CSF from patients with mild cognitive impairment and AD compared to the age-matched normal subjects. Moreover, its expression was more prominent in the AD group than in the MCI and correlated with disease severity and progression. In contrast, fibrinogen gamma-A chain precursor protein was detected very low in the age-matched normal group.</p> <p>Conclusion</p> <p>These findings suggest that the CSF level of fibrinogen gamma-A chain precursor may be a candidate biomarker for AD.</p