Characterization of small-scale dairy farms and its relation to water use efficiency in the Mexicali Valley, Mexico.

A survey was completed to determine water use by small-scale dairy farms in Mexicali Valley of Mexico and to associate it with dairy production parameters. Mexicali Valley surrounds the capital city of the state Baja California, Mexicali. Sixty-one smallholders were interviewed in person in this rural area of northwestern Mexico. On average, small dairy holders had more than 20 years of experience and were ~ 55 years of age; people working on their farms are especially relatives. A low percentage was literate (20%), and they belong to a local dairy association. Milk yield/cow/year does not reach 4000 kg of milk and 75% of producers do not follow a defined management program for their cattle. Hand-milking is still practiced by 27% of the producers, and there is a general lack of infrastructure to maintain milk in a refrigerated state so that there is a very high risk of zoonotic diseases. Water use efficiency (WUE) was linearly correlated (P < 0.05) with total irrigated area, but not with animal production parameters. Regression equations constructed to explain WUE exhibited low adjustment, and WUE was not associated (P > 0.05) with milk yield. Small dairy producers in Mexicali Valley are in a generally poor situation with low water use practices; however, required more government support to increase their benefits from this livestock activity.

Metabolomic profile of neuroendocrine tumors identifies methionine, porphyrin, and tryptophan metabolisms as key dysregulated pathways associated with patient survival.

OBJECTIVE: Metabolic profiling is a valuable tool to characterize tumor biology but remains largely unexplored in neuroendocrine tumors (NETs). Our aim was to comprehensively assess the metabolomic profile of NETs and identify novel prognostic biomarkers and dysregulated molecular pathways. DESIGN AND METHODS: Multiplatform untargeted metabolomic profiling (GC-MS, CE-MS, and LC-MS) was performed in plasma from 77 patients with G1-2 extra-pancreatic NETs enrolled in the AXINET trial (NCT01744249) (study cohort) and from 68 non-cancer individuals (control). The prognostic value of each differential metabolite (n = 155) in NET patients (P < .05) was analyzed by univariate and multivariate analyses adjusted for multiple testing and other confounding factors. Related pathways were explored by Metabolite Set Enrichment Analysis (MSEA) and Metabolite Pathway Analysis (MPA). RESULTS: Thirty-four metabolites were significantly associated with progression-free survival (PFS) (n = 16) and/or overall survival (OS) (n = 27). Thirteen metabolites remained significant independent prognostic factors in multivariate analysis, 3 of them with a significant impact on both PFS and OS. Unsupervised clustering of these 3 metabolites stratified patients in 3 distinct prognostic groups (1-year PFS of 71.1%, 47.7%, and 15.4% (P = .012); 5-year OS of 69.7%, 32.5%, and 27.7% (P = .003), respectively). The MSEA and MPA of the 13-metablolite signature identified methionine, porphyrin, and tryptophan metabolisms as the 3 most relevant dysregulated pathways associated with the prognosis of NETs. CONCLUSIONS: We identified a metabolomic signature that improves prognostic stratification of NET patients beyond classical prognostic factors for clinical decisions. The enriched metabolic pathways identified reveal novel tumor vulnerabilities that may foster the development of new therapeutic strategies for these patients.