Arsenic Contamination in Food-chain: Transfer of Arsenic into Food Materials through Groundwater Irrigation

Arsenic contamination in groundwater in Bangladesh has become an additional concern vis-à-vis its use for irrigation purposes. Even if arsenic-safe drinking-water is assured, the question of irrigating soils with arsenic-laden groundwater will continue for years to come. Immediate attention should be given to assess the possibility of accumulating arsenic in soils through irrigation-water and its subsequent entry into the food-chain through various food crops and fodders. With this possibility in mind, arsenic content of 2,500 water, soil and vegetable samples from arsenic-affected and arsenic-unaffected areas were analyzed during 1999–2004. Other sources of foods and fodders were also analyzed. Irrigating a rice field with groundwater containing 0.55 mg/L of arsenic with a water requirement of 1,000 mm results in an estimated addition of 5.5 kg of arsenic per ha per annum. Concentration of arsenic as high as 80 mg per kg of soil was found in an area receiving arsenic-contaminated irrigation. A comparison of results from affected and unaffected areas revealed that some commonly-grown vegetables, which would usually be suitable as good sources of nourishment, accumulate substantially-elevated amounts of arsenic. For example, more than 150 mg/kg of arsenic has been found to be accumulated in arum (kochu) vegetable. Implications of arsenic ingested in vegetables and other food materials are discussed in the paper

Arsenic Contamination in Food-chain: Transfer of Arsenic into Food Materials Through Groundwater Irrigation

Arsenic contamination in groundwater in Bangladesh has become an additional concern vis-\ue0-vis its use for irrigation purposes. Even if arsenic-safe drinking-water is assured, the question of irrigating soils with arsenic-laden groundwater will continue for years to come. Immediate attention should be given to assess the possibility of accumulating arsenic in soils through irrigation-water and its subsequent entry into the food-chain through various food crops and fodders. With this possibility in mind, arsenic content of 2,500 water, soil and vegetable samples from arsenic-affected and arsenic-unaffected areas were analyzed during 1999-2004. Other sources of foods and fodders were also analyzed. Irrigating a rice field with groundwater containing 0.55 mg/L of arsenic with a water requirement of 1,000 mm results in an estimated addition of 5.5 kg of arsenic per ha per annum. Concentration of arsenic as high as 80 mg per kg of soil was found in an area receiving arsenic-contaminated irrigation. A comparison of results from affected and unaffected areas revealed that some commonly-grown vegetables, which would usually be suitable as good sources of nourishment, accumulate substantially-elevated amounts of arsenic. For example, more than 150 mg/kg of arsenic has been found to be accumulated in arum (kochu) vegetable. Implications of arsenic ingested in vegetables and other food materials are discussed in the paper

Positive predictive value of automated database records for diabetic ketoacidosis (DKA) in children and youth exposed to antipsychotic drugs or control medications: a tennessee medicaid study

<p>Abstract</p> <p>Background</p> <p>Diabetic ketoacidosis (DKA) is a potentially life-threatening complication of treatment with some atypical antipsychotic drugs in children and <b>youth</b>. Because drug-associated DKA is rare, large automated health outcomes databases may be a valuable data source for conducting pharmacoepidemiologic studies of DKA associated with exposure to individual antipsychotic drugs. However, no validated computer case definition of DKA exists. We sought to assess the positive predictive value (PPV) of a computer case definition to detect incident cases of DKA, using automated records of Tennessee Medicaid as the data source and medical record confirmation as a "gold standard."</p> <p>Methods</p> <p>The computer case definition of DKA was developed from a retrospective cohort study of antipsychotic-related type 2 diabetes mellitus (1996-2007) in Tennessee Medicaid enrollees, aged 6-24 years. Thirty potential cases with any DKA diagnosis (ICD-9 250.1, ICD-10 E1x.1) were identified from inpatient encounter claims. Medical records were reviewed to determine if they met the clinical definition of DKA.</p> <p>Results</p> <p>Of 30 potential cases, 27 (90%) were successfully abstracted and adjudicated. Of these, 24 cases were confirmed by medical record review (PPV 88.9%, 95% CI 71.9 to 96.1%). Three non-confirmed cases presented acutely with severe hyperglycemia, but had no evidence of acidosis.</p> <p>Conclusions</p> <p>Diabetic ketoacidosis in children and youth can be identified in a computerized Medicaid database using our case definition, which could be useful for automated database studies in which drug-associated DKA is the outcome of interest.</p

The Stem Cell Discovery Engine: an integrated repository and analysis system for cancer stem cell comparisons

Mounting evidence suggests that malignant tumors are initiated and maintained by a subpopulation of cancerous cells with biological properties similar to those of normal stem cells. However, descriptions of stem-like gene and pathway signatures in cancers are inconsistent across experimental systems. Driven by a need to improve our understanding of molecular processes that are common and unique across cancer stem cells (CSCs), we have developed the Stem Cell Discovery Engine (SCDE)—an online database of curated CSC experiments coupled to the Galaxy analytical framework. The SCDE allows users to consistently describe, share and compare CSC data at the gene and pathway level. Our initial focus has been on carefully curating tissue and cancer stem cell-related experiments from blood, intestine and brain to create a high quality resource containing 53 public studies and 1098 assays. The experimental information is captured and stored in the multi-omics Investigation/Study/Assay (ISA-Tab) format and can be queried in the data repository. A linked Galaxy framework provides a comprehensive, flexible environment populated with novel tools for gene list comparisons against molecular signatures in GeneSigDB and MSigDB, curated experiments in the SCDE and pathways in WikiPathways. The SCDE is available at http://discovery.hsci.harvard.edu

Aspiration-based choice

Due to copyright restrictions, the access to the full text of this article is only available via subscription.Numerous studies and experiments suggest that aspirations for desired but perhaps unavailable alternatives influence decisions. A common finding is that an unavailable aspiration steers agents to choose similar available alternatives. We propose and axiomatically characterize a choice theory consistent with this aspirational effect. Similarity is modeled using a subjective metric derived from choice data. This model offers implications for consumer welfare and its distribution between rich and poor when firms compete for aspirational agents, and a novel rationale for sales

Beavers affect carbon biogeochemistry : both short-term and long-term processes are involved.

With the recent population increase in beavers (Castor spp.), a considerable amount of new riparian habitat has been created in the Holarctic. We evaluated how beaver‐induced floods affect carbon (C) dynamics in the beaver ponds and in the water‐atmosphere and riparian zone interfaces. Beaver disturbance affects soil organic C storage by decreasing or increasing it, resulting in a redistribution of C. Upon flooding, the concentration of dissolved organic carbon (DOC) increases in the water. This C can be released into the atmosphere, it can settle down to the bottom sediments, it can be sequestered by vegetation, or it can be transported downstream. The carbon dioxide (CO2) emissions vary between 0.14 and 11.2 g CO2 m−2 day−1, averaging 4.9 CO2 g m−2 day−1. The methane (CH4) emissions vary too, from 27 mg m−2 day−1 to 919 mg m−2 day−1, averaging 222 mg CH4 m−2 day−1. Globally, C emission from beaver ponds in the form of CH4 and CO2 may be 3.33–4.62 Tg (teragram, 1012 g) year−1. The yearly short‐term sedimentation rates in beaver ponds vary between 0.4 and 47 cm year−1, and individual ponds contain 9–6355 m3 of sediment. The approximate global estimate for yearly C sedimentation is 3.8 Tg C; beaver ponds globally contain 380 Tg sedimented C. After being formed, beaver pond deposits can remain for millennia. Both C sequestration and CO2 and CH4 emissions in ponds of various ages should be taken into account when considering the net effect of beavers on the C dynamics. With present estimates, beaver ponds globally range from a sink (−0.47 Tg year−1) to a source (0.82 Tg year−1) of C. More research is needed with continuous flux measurements and from ponds of different ages. Likewise, there is a need for more studies in Eurasia to understand the effect of beaver on C biogeochemistry.Peer reviewe

Systematic review of methods used in meta-analyses where a primary outcome is an adverse or unintended event

addresses: Peninsula College of Medicine and Dentistry, St Luke's Campus, University of Exeter, Exeter, UK. [email protected]: PMCID: PMC3528446types: Journal Article; Research Support, Non-U.S. Gov't© 2012 Warren et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Adverse consequences of medical interventions are a source of concern, but clinical trials may lack power to detect elevated rates of such events, while observational studies have inherent limitations. Meta-analysis allows the combination of individual studies, which can increase power and provide stronger evidence relating to adverse events. However, meta-analysis of adverse events has associated methodological challenges. The aim of this study was to systematically identify and review the methodology used in meta-analyses where a primary outcome is an adverse or unintended event, following a therapeutic intervention