General Trends of Technological Changes in Agriculture

In this article we show that technological development in agriculture exhibits general trends when assessed on a large scale. These trends are generated by changes in the larger socioeconomic context in which the farming system operates. We characterize agricultural performance by land and farm labor productivity and the pattern of use of technological inputs. By means of a cross-sectional analysis of agricultural performance of 20 countries (at the national level), we show that increases in demographic pressure and socioeconomic pressure (increases in average income and labor productivity) in society are the main driving forces of technological development in agriculture. Further, it is shown that the ecological impact of farming (environmental loading) is linked to the particular combination of land productivity and labor productivity at which the agricultural sector operates (through the particular mix and the level of inputs used in agricultural production). Briefly we discuss the role of international trade in agricultural policies and performance. Special attention is given to the situation of Chinese agriculture.     

Conventional and Land-Time Budget Analysis of Rural Villages in Hubei Province,China

Five rural villages in Qianjiang County (Hubei province), PR China, were investigated to collect information on the socioeconomic characteristics relevant to farming system analysis. In each village, 50 households were randomly sampled and household heads interviewed. We first present the results of this conventional survey, which describes these five villages in terms of conventional socioeconomic parameters such as demographic variables, land availability and profiles of land use, time allocation and profiles of working time use, cash flows, and degree of food self-sufficiency. Then we change focus by characterizing household types rather than village types. This is done analyzing the same raw data aggregated at the household level to illustrate the difference of a parallel readings at different hierarchical levels. Finally, we present a new approach to organize the information gathered in the conventional way into “typologies” referring to both household and village level. Such a passage makes possible a multidimensional reading of the system. One key concept of this analysis is the land-time budget (LTB) approach, which is first explained in theoretical terms and then illustrated with examples applied to our data set.     

Genetic Variations of GWAS-Identified Genes and Neuroblastoma Susceptibility: a Replication Study in Southern Chinese Children

Neuroblastoma is one of the most commonly diagnosed solid cancers for children, and genetic factors may play a critical role in neuroblastoma development. Previous genome-wide association studies (GWASs) have identified nine genes associated with neuroblastoma susceptibility in Caucasians. To determine whether genetic variations in these genes are also associated with neuroblastoma susceptibility in Southern Chinese children, we genotyped 25 polymorphisms within these genes by the TaqMan method in 256 cases and 531 controls. Odds ratios (ORs) and 95% confidence intervals (CIs) were used to evaluate the strength of the associations. We performed a meta-analysis to further evaluate the associations. Furthermore, we calculated the area under the receiver-operating characteristic curves (AUC) to assess which gene/genes may better predict neuroblastoma risk. We confirmed that CASC15 rs6939340 A > G, rs4712653 T > C, rs9295536 C > A, LIN28B rs221634 A > T, and LMO1 rs110419 A > G were associated with significantly altered neuroblastoma susceptibility. We also confirmed that rs6939340 A > G (G versus A: OR = 1.30, 95% CI = 1.13-1.50) and rs110419 G > A (A versus G: OR = 1.37, 95% CI = 1.19-1.58) were associated with increased neuroblastoma risk for all subjects. We also found that the combination of polymorphisms in CASC15, LIN28B, and LMO1 may be used to predict neuroblastoma risk (AUC = 0.63, 95% CI = 0.59-0.67). Overall, we verified five GWAS-identified polymorphisms that were associated with neuroblastoma susceptibility alteration for Southern Chinese population; however, these results need further validation in studies with larger sample sizes.     

Combination of Pre-Treatment DWI-Signal Intensity and S-1 Treatment: A Predictor of Survival in Patients with Locally Advanced Pancreatic Cancer Receiving Stereotactic Body Radiation Therapy and Sequential S-1

OBJECTIVE: To identify whether the combination of pre-treatment radiological and clinical factors can predict the overall survival (OS) in patients with locally advanced pancreatic cancer (LAPC) treated with stereotactic body radiation and sequential S-1 (a prodrug of 5-FU combined with two modulators) therapy with improved accuracy compared with that of established clinical and radiologic risk models. METHODS: Patients admitted with LAPC underwent diffusion weighted imaging (DWI) scan at 3.0-T (b = 600 s/mm²). The mean signal intensity (SI_b = 600) of region-of-interest (ROI) was measured. The Log-rank test was done for tumor location, biliary stent, S-1, and other treatments and the Cox regression analysis was done to identify independent prognostic factors for OS. Prediction error curves (PEC) were used to assess potential errors in prediction of survival. The accuracy of prediction was evaluated by Integrated Brier Score (IBS) and C index. RESULTS: 41 patients were included in this study. The median OS was 11.7 months (2.8-23.23 months). The 1-year OS was 46%. Multivariate analysis showed that pre-treatment SI_b = 600 value and administration of S-1 were independent predictors for OS. The performance of pre-treatment SI_b = 600 and S-1 treatment in combination was better than that of SI_b = 600 or S-1 treatment alone. CONCLUSION: The combination of pre-treatment SI_b = 600 and S-1 treatment could predict the OS in patients with LAPC undergoing SBRT and sequential S-1 therapy with improved accuracy compared with that of established clinical and radiologic risk models.     

Clinicopathologic Factors Related to the Histological Tumor Grade of Breast Cancer in Western China: An Epidemiological Multicenter Study of 8619 Female Patients

BACKGROUND AND PURPOSE: Breast cancer is now recognized as a clinically heterogeneous disease with a wide spectrum of epidemiological and clinicopathologic features. We aimed to evaluate whether epidemiological and clinicopathologic features are associated with the histological tumor grade of breast carcinomas in Western China. METHODS: We retrospectively collected data from the Western China Clinical Cooperation Group and assessed associations between clinicopathologic factors and histological tumor grade in 8619 female breast cancer patients. Patients were divided into two groups: Group I (tumor grade I/II) and Group II (tumor grade III). Univariable analysis and multivariable logistic regression models were used to analyze the relationships between clinicopathologic factors and tumor grade. RESULTS: Patients presenting with positive axillary lymph nodes, large tumor size (>2?cm), lymphovascular invasion, hormone receptor negativity, human epidermal growth factor receptor 2 (HER-2) positivity, and triple negativity tended to have an increased risk of a high tumor grade. However, the number of pregnancies or births was inversely correlated with the risk of a high tumor grade. In addition, patients presenting with grade III tumors were more likely to receive aggressive treatment, such as adjuvant chemotherapy, anti–HER-2 therapy, and level III axillary lymph node dissection. CONCLUSIONS: Our results suggested that several clinicopathologic factors were associated with high tumor grade of breast cancer patients in Western China.