ZRT/IRT-like Protein 14 (ZIP14) Promotes the Cellular Assimilation of Iron from Transferrin

ZIP14 is a transmembrane metal ion transporter that is abundantly expressed in the liver, heart, and pancreas. Previous studies of HEK 293 cells and the hepatocyte cell lines AML12 and HepG2 established that ZIP14 mediates the uptake of non-transferrin-bound iron, a form of iron that appears in the plasma during pathologic iron overload. In this study we investigated the role of ZIP14 in the cellular assimilation of iron from transferrin, the circulating plasma protein that normally delivers iron to cells by receptor-mediated endocytosis. We also determined the subcellular localization of ZIP14 in HepG2 cells. We found that overexpression of ZIP14 in HEK 293T cells increased the assimilation of iron from transferrin without increasing levels of transferrin receptor 1 or the uptake of transferrin. To allow for highly specific and sensitive detection of endogenous ZIP14 in HepG2 cells, we used a targeted knock-in approach to generate a cell line expressing a FLAG-tagged ZIP14 allele. Confocal microscopic analysis of these cells detected ZIP14 at the plasma membrane and in endosomes containing internalized transferrin. HepG2 cells in which endogenous ZIP14 was suppressed by siRNA assimilated 50% less iron from transferrin compared with controls. The uptake of transferrin, however, was unaffected. We also found that ZIP14 can mediate the transport of iron at pH 6.5, the pH at which iron dissociates from transferrin within the endosome. These results suggest that endosomal ZIP14 participates in the cellular assimilation of iron from transferrin, thus identifying a potentially new role for ZIP14 in iron metabolism.     

Potassium uptake by platelets from Down's syndrome and normal subjects

Potassium uptake was studied in Down's syndrome (D.S.) platelets to determine if the Na⁺/K⁺ ATPase mediated movement of this ion was decreased compared to normal platelets. Total uptake of ⁴²K was 1.58±0.16 μmoles/hr/10⁹ normal platelets but was decreased to 1.06±0.06 μmoles/hr/10⁹ D.S. platelets (p<.001). Na⁺/K⁺ ATPase mediated (ouabain sensitive) K⁺ uptake was 0.87±0.05 μmoles/hr/10⁹ normal platelets but only 0.54±0.04 μmoles/hr/10⁹ in D.S. platelets (p<.001). As the Na⁺/K⁺ ATPase mediated outward movement of Na⁺ is decreased in D.S. platelets, the present work demonstrates that bidirectional functional imparrment of the Na⁺/K⁺ ATPase pump is present in D.S. platelets.     

Modulation of the transferrin receptor during DMSO-induced differentiation in HL-60 cells

When HL-60 cells are induced to differentiate by dimethyl sulfoxide along a granulocytic pathway there is a fivefold decrease in the total number of transferrin receptors within 3 days, as compared to untreated cells. This decrease is due primarily to a rapid decline in the synthesis of the receptor rather than an increase in the degradation of the receptor. The decrease in transferrin receptor synthesis is a specific and early event that precedes the cessation of cell proliferation, differentiation, and the decrease in total protein synthesis.     

Ferristatin II Promotes Degradation of Transferrin Receptor-1 In Vitro and In Vivo

Previous studies have shown that the small molecule iron transport inhibitor ferristatin (NSC30611) acts by down-regulating transferrin receptor-1 (TfR1) via receptor degradation. In this investigation, we show that another small molecule, ferristatin II (NSC8679), acts in a similar manner to degrade the receptor through a nystatin-sensitive lipid raft pathway. Structural domains of the receptor necessary for interactions with the clathrin pathway do not appear to be necessary for ferristatin II induced degradation of TfR1. While TfR1 constitutively traffics through clathrin-mediated endocytosis, with or without ligand, the presence of Tf blocked ferristatin II induced degradation of TfR1. This effect of Tf was lost in a ligand binding receptor mutant G647A TfR1, suggesting that Tf binding to its receptor interferes with the drug’s activity. Rats treated with ferristatin II have lower TfR1 in liver. These effects are associated with reduced intestinal ⁵⁹Fe uptake, lower serum iron and transferrin saturation, but no change in liver non-heme iron stores. The observed hypoferremia promoted by degradation of TfR1 by ferristatin II appears to be due to induced hepcidin gene expression.     

早期液体复苏对感染性休克患者血流动力学的影响

目的：早期液体复苏对感染性休克患者血流动力学的影响。方法：选取2012年2月-2013年2月我院ICU收治的26例感染性休克患者作为研究对象,随机分为对照组和试验组,各13例。两组患者均采用PICCO监测,并根据早期复苏目标导向（Earlygoaldirectedtherapy,EGDT）进行早期液体复苏治疗。对照组和试验组复苏液分别为林格液和6％羟乙基淀粉130／0．4氯化钠溶液。分别于复苏开始时（Oh）、8h和24h收集患者的血流动力学参数。结果：两组患者CO及PAWP水平均随着时间的延长下降,而CI、CVP及SVR水平均随着时间的增加上升。除对照组CI外,与开始复苏（oh）相比较试验组和对照组的C0、CI、CVP、SVR及PAWP与开始复苏（O小时）相比较均有显著差异（P值均〈0．05）。经重复测量资料的．方差分析进行比较发现,与对照组相比较,试验组CVP和SVR上升水平及PAWP下降水平明显,差异具有统计学意义（P值均〈0．05）。结论：感染性休克患者使用6％羟乙基淀粉130／0．4氯化钠溶液进行复苏,能更好的改善患者的血流动力学指标。     

Relationship among Medical Student Resilience,Educational Environment and Quality of Life

Context

Resilience is a capacity to face and overcome adversities, with personal transformation and growth. In medical education, it is critical to understand the determinants of a positive, developmental reaction in the face of stressful, emotionally demanding situations. We studied the association among resilience, quality of life (QoL) and educational environment perceptions in medical students.

Methods

We evaluated data from a random sample of 1,350 medical students from 22 Brazilian medical schools. Information from participants included the Wagnild and Young’s resilience scale (RS-14), the Dundee Ready Educational Environment Measure (DREEM), the World Health Organization Quality of Life questionnaire – short form (WHOQOL-BREF), the Beck Depression Inventory (BDI) and the State-Trait Anxiety Inventory (STAI).

Results

Full multiple linear regression models were adjusted for sex, age, year of medical course, presence of a BDI score ≥ 14 and STAI state or anxiety scores ≥ 50. Compared to those with very high resilience levels, individuals with very low resilience had worse QoL, measured by overall (β=-0.89; 95% confidence interval =-1.21 to -0.56) and medical-school related (β=-0.85; 95%CI=-1.25 to -0.45) QoL scores, environment (β=-6.48; 95%CI=-10.01 to -2.95), psychological (β=-22.89; 95%CI=-25.70 to -20.07), social relationships (β=-14.28; 95%CI=-19.07 to -9.49), and physical health (β=-10.74; 95%CI=-14.07 to -7.42) WHOQOL-BREF domain scores. They also had a worse educational environment perception, measured by global DREEM score (β=-31.42; 95%CI=-37.86 to -24.98), learning (β=-7.32; 95%CI=-9.23 to -5.41), teachers (β=-5.37; 95%CI=-7.16 to -3.58), academic self-perception (β=-7.33; 95%CI=-8.53 to -6.12), atmosphere (β=-8.29; 95%CI=-10.13 to -6.44) and social self-perception (β=-3.12; 95%CI=-4.11 to -2.12) DREEM domain scores. We also observed a dose-response pattern across resilience level groups for most measurements.

Conclusions

Medical students with higher resilience levels had a better quality of life and a better perception of educational environment. Developing resilience may become an important strategy to minimize emotional distress and enhance medical training.     

Validated predictive modelling of the environmental resistome

Multi-drug-resistant bacteria pose a significant threat to public health. The role of the environment in the overall rise in antibiotic-resistant infections and risk to humans is largely unknown. This study aimed to evaluate drivers of antibiotic-resistance levels across the River Thames catchment, model key biotic, spatial and chemical variables and produce predictive models for future risk assessment. Sediment samples from 13 sites across the River Thames basin were taken at four time points across 2011 and 2012. Samples were analysed for class 1 integron prevalence and enumeration of third-generation cephalosporin-resistant bacteria. Class 1 integron prevalence was validated as a molecular marker of antibiotic resistance; levels of resistance showed significant geospatial and temporal variation. The main explanatory variables of resistance levels at each sample site were the number, proximity, size and type of surrounding wastewater-treatment plants. Model 1 revealed treatment plants accounted for 49.5% of the variance in resistance levels. Other contributing factors were extent of different surrounding land cover types (for example, Neutral Grassland), temporal patterns and prior rainfall; when modelling all variables the resulting model (Model 2) could explain 82.9% of variations in resistance levels in the whole catchment. Chemical analyses correlated with key indicators of treatment plant effluent and a model (Model 3) was generated based on water quality parameters (contaminant and macro- and micro-nutrient levels). Model 2 was beta tested on independent sites and explained over 78% of the variation in integron prevalence showing a significant predictive ability. We believe all models in this study are highly useful tools for informing and prioritising mitigation strategies to reduce the environmental resistome.