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Background: Catch-up growth issues among children born small for gestational age (SGA) present a substantial public health challenge. Prenatal exposure to heavy metals can cause adverse effects on birth weight. However, comprehensive studies on the accurate assessment of individual blood concentrations of heavy metals and their effect on the failure to achieve catch-up growth remain unavailable.

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The bidirectional fluxes of cadmium and calcium across the plasma membrane were assessed and compared in subapical maize root segments. This homogeneous material provides a simplified system for investigating ion fluxes in whole organs. The kinetic profile of cadmium influx was characterized by a combination of a saturable rectangular hyperbola ( = 30.

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Delving into the molecular initiating event of cadmium toxification via the dose-dependent functional genomics approach in Saccharomyces cerevisiae.

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April 2023

State Key Laboratory of Pollution Control & Resource Reuse, School of the Environment, Nanjing University, 163 Xianlin Ave., Nanjing, Jiangsu, 210023, China.

Determining dose-response relationship is essential for comprehensively revealing chemical-caused effects on organisms. However, uncertainty and complexity of gene/protein interactions cause the inability of traditional toxicogenomic methods (e.g.

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Multiple effects of the PHO91 gene knockout in Ogataea parapolymorpha.

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Federal Research Center "Pushchino Scientific Center for Biological Research of the Russian Academy of Sciences", Skryabin Institute of Biochemistry and Physiology of Microorganisms, Pushchino, Russian Federation.

Pho91 is a vacuolar phosphate transporter that exports phosphate from the vacuolar lumen to the cytosol in yeast cells. In this study, we have demonstrated the pleiotropic effects of the PHO91 gene knockout in the methylotrophic yeast Ogataea parapolymorpha (Hansenula polymorpha, Ogataea angusta). The content of both acid-soluble and acid-insoluble inorganic polyphosphate (polyP) in the ∆pho91 cells was slightly higher compared to the strain with wild-type PHO91, when the cells were cultivated on glucose.

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Article Synopsis
  • The study addresses the challenge of mapping soil heavy metal pollution and introduces a hybrid machine learning method using random forest and fuzzy c-means to identify risk zones based on 577 soil samples and 12 environmental factors.
  • Results show that random forest outperforms multiple linear regression in predicting various heavy metals, with notable high concentrations in the north central region for metals like Cd, Cr, Hg, Pb, and Zn.
  • The research identified four risk zones and emphasized targeted control strategies, particularly in the high-risk zone, such as regulating industrial discharges and remediating contaminated soils.
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