Registered at the UMIN (University Hospital Medical Information Network) Clinical Trials Registry with study number UMIN000008343.

A major obstacle to improving prognoses in ovarian cancer is the lack of effective screening methods for early detection. Circulating microRNAs (miRNAs) have been recognized as promising biomarkers that could lead to clinical applications. Here, to develop an optimal detection method, we use microarrays to obtain comprehensive miRNA profiles from 4046 serum samples, including 428 patients with ovarian tumors. A diagnostic model based on expression levels of ten miRNAs is constructed in the discovery set. Validation in an independent cohort reveals that the model is very accurate (sensitivity, 0.99; specificity, 1.00), and the diagnostic accuracy is maintained even in early-stage ovarian cancers. Furthermore, we construct two additional models, each using 9–10 serum miRNAs, aimed at discriminating ovarian cancers from the other types of solid tumors or benign ovarian tumors. Our findings provide robust evidence that the serum miRNA profile represents a promising diagnostic biomarker for ovarian cancer.

No abstract

Contract farming (CF) has long been practiced but is becoming increasingly common in both developed and developing countries with the heightened interest of consumers in food safety and quality. Under CF, farmers and buyers make advance agreements on volume, quality, time of delivery, use of inputs, and price or pricing formula. This article critically reviews the literature on CF to assess how it contributes to improving production efficiency and income of farmers in general and of small-scale farmers in particular. Although our review focuses on literature in developing countries because of its predominance, we refer to literature in developed countries (primarily the United States) to gain a deeper understanding of the impacts of CF. We find that although CF contributes to the improvement of farmers' income by introducing new crops and production methods, there is room for strengthening its effects on poverty reduction through policy.

Given the stagnant agricultural productivity and persistent food insecurity in low‐income countries—notably in sub‐Saharan Africa (SSA)—there has been continued interest in the adoption of new technology and its impact on productivity in these regions. To increase crop yields and sustain yield gains, recent case studies of technology adoption unanimously recommend the adoption of integrated farm management systems, particularly in SSA. On the other hand, there have been increasing numbers of studies on social network or farmer‐to‐farmer technology extension. These studies explore more efficient extension systems than traditional public‐sector extension approaches. This article reviews both recent case studies of technology adoption and its productivity impacts as well as studies on agricultural extension to identify common findings, shortcomings, and major remaining issues.