Association between Heavy Metals and Rare Earth Elements with Acute Ischemic Stroke: A Case-Control Study Conducted in the Canary Islands (Spain)
Abstract
:1. Introduction
2. Patients and Methods
2.1. Study Design and Participants
2.2. Selection of Elements and Sample Preparation
2.3. Analytical Procedure
2.4. Statistical Analysis
3. Results and Discussion
3.1. Clinical Characteristics of Cases and Controls
3.2. ATSDR’s Priority Elements in Stroke
3.3. REEs and Other Inorganic Elements in Stroke
3.4. Strengths and Limitations of the Study
4. Conclusions
Supplementary Materials
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
- WSO. Global Stroke Fact Sheet. 2016. Available online: https://www.world-stroke.org/assets/downloads/WSO_Global_Stroke_Fact_Sheet.pdf (accessed on 20 August 2020).
- Guzik, A.; Bushnell, C. Stroke Epidemiology and Risk Factor Management. Continuum. (Minneap. Minn.) 2017, 23, 15–39. [Google Scholar] [CrossRef] [PubMed]
- SCS. Guía de Atención al Ictus; Asistenciales, D.G.d.P., Ed.; Servicio Canario de la Salud (SCS): Canary Islands, Spain, 2013. [Google Scholar]
- Thrift, A.G.; Thayabaranathan, T.; Howard, G.; Howard, V.J.; Rothwell, P.M.; Feigin, V.L.; Norrving, B.; Donnan, G.A.; Cadilhac, A.D. Global stroke statistics. Int. J. Stroke 2017, 12, 13–32. [Google Scholar] [CrossRef] [PubMed]
- Johnson, W.; Onuma, O.; Owolabi, M.; Sachdev, S. Stroke: A global response is needed. Bull. World Health Organ. 2016, 94, 634. [Google Scholar] [CrossRef] [PubMed]
- SNS. Estrategia en Ictus del Sistema Nacional de Salud; Ministerio de Sanidad y Política Social: Madrid, Spain, 2009. [Google Scholar]
- Boehme, A.K.; Esenwa, C.; Elkind, M.S. Stroke Risk Factors, Genetics, and Prevention. Circ. Res. 2017, 120, 472–495. [Google Scholar] [CrossRef] [PubMed]
- Shah, A.S.; Lee, K.K.; McAllister, D.A.; Hunter, A.; Nair, H.; Whiteley, W.; Langrish, J.P.; Newby, D.E.; Mills, N.L. Short term exposure to air pollution and stroke: Systematic review and meta-analysis. BMJ 2015, 350, h1295. [Google Scholar] [CrossRef] [Green Version]
- Lee, D.H.; Lind, P.M.; Jacobs, D.R., Jr.; Salihovic, S.; van Bavel, B.; Lind, L. Background exposure to persistent organic pollutants predicts stroke in the elderly. Environ. Int. 2012, 47, 115–120. [Google Scholar] [CrossRef]
- Lim, J.E.; Lee, S.; Jee, S.H. Serum persistent organic pollutants levels and stroke risk. Environ. Pollut. 2018, 233, 855–861. [Google Scholar] [CrossRef]
- Henriquez-Hernandez, L.A.; Luzardo, O.P.; Zumbado, M.; Camacho, M.; Serra-Majem, L.; Alvarez-Leon, E.E.; Boada, L.D. Blood pressure in relation to contamination by polychlorobiphenyls and organochlorine pesticides: Results from a population-based study in the Canary Islands (Spain). Environ. Res. 2014, 135, 48–54. [Google Scholar] [CrossRef]
- Henriquez-Hernandez, L.A.; Luzardo, O.P.; Zumbado, M.; Serra-Majem, L.; Valeron, P.F.; Camacho, M.; Alvarez-Perez, J.; Salas-Salvado, J.; Boada, L.D. Determinants of increasing serum POPs in a population at high risk for cardiovascular disease. Results from the PREDIMED-CANARIAS study. Environ. Res. 2017, 156, 477–484. [Google Scholar] [CrossRef]
- Henriquez-Hernandez, L.A.; Luzardo, O.P.; Valeron, P.F.; Zumbado, M.; Serra-Majem, L.; Camacho, M.; Gonzalez-Antuna, A.; Boada, L.D. Persistent organic pollutants and risk of diabetes and obesity on healthy adults: Results from a cross-sectional study in Spain. Sci. Total Environ. 2017, 607–608, 1096–1102. [Google Scholar] [CrossRef]
- Hussain, M.; Mumtaz, S. E-waste: Impacts, issues and management strategies. Rev. Environ. Health 2014, 29, 53–58. [Google Scholar] [CrossRef] [PubMed]
- Tansel, B. From electronic consumer products to e-wastes: Global outlook, waste quantities, recycling challenges. Environ. Int. 2017, 98, 35–45. [Google Scholar] [CrossRef] [PubMed]
- Bozlaker, A.; Prospero, J.M.; Fraser, M.P.; Chellam, S. Quantifying the contribution of long-range Saharan dust transport on particulate matter concentrations in Houston, Texas, using detailed elemental analysis. Environ. Sci. Technol. 2013, 47, 10179–10187. [Google Scholar] [CrossRef] [PubMed]
- Pagano, G.; Aliberti, F.; Guida, M.; Oral, R.; Siciliano, A.; Trifuoggi, M.; Tommasi, F. Rare earth elements in human and animal health: State of art and research priorities. Environ. Res. 2015, 142, 215–220. [Google Scholar] [CrossRef] [PubMed]
- Gaman, L.; Radoi, M.P.; Delia, C.E.; Luzardo, O.P.; Zumbado, M.; Rodriguez-Hernandez, A.; Stoian, I.; Gilca, M.; Boada, L.D.; Henriquez-Hernandez, L.A. Concentration of heavy metals and rare earth elements in patients with brain tumours: Analysis in tumour tissue, non-tumour tissue, and blood. Int. J. Environ. Health Res. 2019, 1–14. [Google Scholar] [CrossRef] [PubMed]
- Henriquez-Hernandez, L.A.; Boada, L.D.; Carranza, C.; Perez-Arellano, J.L.; Gonzalez-Antuna, A.; Camacho, M.; Almeida-Gonzalez, M.; Zumbado, M.; Luzardo, O.P. Blood levels of toxic metals and rare earth elements commonly found in e-waste may exert subtle effects on hemoglobin concentration in sub-Saharan immigrants. Environ. Int. 2017, 109, 20–28. [Google Scholar] [CrossRef] [PubMed]
- Cabrera-Rodriguez, R.; Luzardo, O.P.; Gonzalez-Antuna, A.; Boada, L.D.; Almeida-Gonzalez, M.; Camacho, M.; Zumbado, M.; Acosta-Dacal, A.C.; Rial-Berriel, C.; Henriquez-Hernandez, L.A. Occurrence of 44 elements in human cord blood and their association with growth indicators in newborns. Environ. Int. 2018, 116, 43–51. [Google Scholar] [CrossRef]
- Pagano, G.; Guida, M.; Tommasi, F.; Oral, R. Health effects and toxicity mechanisms of rare earth elements-Knowledge gaps and research prospects. Ecotoxicol. Environ. Saf. 2015, 115, 40–48. [Google Scholar] [CrossRef]
- Tsinovoi, C.L.; Xun, P.; McClure, L.A.; Carioni, V.M.O.; Brockman, J.D.; Cai, J.; Guallar, E.; Cushman, M.; Unverzagt, F.W.; Howard, V.J.; et al. Arsenic Exposure in Relation to Ischemic Stroke: The Reasons for Geographic and Racial Differences in Stroke Study. Stroke 2018, 49, 19–26. [Google Scholar] [CrossRef]
- Moon, K.A.; Oberoi, S.; Barchowsky, A.; Chen, Y.; Guallar, E.; Nachman, K.E.; Rahman, M.; Sohel, N.; D’Ippoliti, D.; Wade, T.J.; et al. A dose-response meta-analysis of chronic arsenic exposure and incident cardiovascular disease. Int. J. Epidemiol. 2017, 46, 1924–1939. [Google Scholar] [CrossRef] [Green Version]
- Steenland, K.; Barry, V.; Anttila, A.; Sallmen, M.; McElvenny, D.; Todd, A.C.; Straif, K. A cohort mortality study of lead-exposed workers in the USA, Finland and the UK. Occup. Environ. Med. 2017, 74, 785–791. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Chiou, H.Y.; Huang, W.I.; Su, C.L.; Chang, S.F.; Hsu, Y.H.; Chen, C.J. Dose-response relationship between prevalence of cerebrovascular disease and ingested inorganic arsenic. Stroke 1997, 28, 1717–1723. [Google Scholar] [CrossRef] [PubMed]
- Tchounwou, P.B.; Yedjou, C.G.; Patlolla, A.K.; Sutton, D.J. Heavy metal toxicity and the environment. Exp. Suppl. 2012, 101, 133–164. [Google Scholar] [PubMed] [Green Version]
- Cid-Ruzafa, J.; Damian-Moreno, J. Disability evaluation: Barthel’s index. Rev. Esp. Salud. Publica 1997, 71, 127–137. [Google Scholar] [CrossRef] [PubMed]
- ATSDR. Agency for Toxic Substances and Disease Registry. 2018. Available online: https://www.atsdr.cdc.gov/ (accessed on 27 January 2020).
- Gonzalez-Antuna, A.; Camacho, M.; Henriquez-Hernandez, L.A.; Boada, L.D.; Almeida-Gonzalez, M.; Zumbado, M.; Luzardo, O.P. Simultaneous quantification of 49 elements associated to e-waste in human blood by ICP-MS for routine analysis. MethodsX 2017, 4, 328–334. [Google Scholar] [CrossRef]
- Lubin, J.H.; Colt, J.S.; Camann, D.; Davis, S.; Cerhan, J.R.; Severson, R.K.; Bernstein, L.; Hartge, P. Epidemiologic evaluation of measurement data in the presence of detection limits. Environ. Health Perspect. 2004, 112, 1691–1696. [Google Scholar] [CrossRef]
- Orozco-Beltran, D.; Sanchez, E.; Garrido, A.; Quesada, J.A.; Carratala-Munuera, M.C.; Gil-Guillen, V.F. Trends in Mortality From Diabetes Mellitus in Spain: 1998–2013. Rev. Esp. Cardiol. (Engl. Ed.) 2017, 70, 433–443. [Google Scholar] [CrossRef]
- Wolf, P.A.; D’Agostino, R.B.; Belanger, A.J.; Kannel, W.B. Probability of stroke: A risk profile from the Framingham Study. Stroke 1991, 22, 312–318. [Google Scholar] [CrossRef] [Green Version]
- Musa, K.I.; Keegan, T.J. The change of Barthel Index scores from the time of discharge until 3-month post-discharge among acute stroke patients in Malaysia: A random intercept model. PLoS ONE 2018, 13, e0208594. [Google Scholar] [CrossRef] [Green Version]
- Furst, A. Can nutrition affect chemical toxicity? Int. J. Toxicol. 2002, 21, 419–424. [Google Scholar] [CrossRef]
- Starling, P.; Charlton, K.; McMahon, A.T.; Lucas, C. Fish intake during pregnancy and foetal neurodevelopment—A systematic review of the evidence. Nutrients 2015, 7, 2001–2014. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Zumbado, M.; Luzardo, O.P.; Rodriguez-Hernandez, A.; Boada, L.D.; Henriquez-Hernandez, L.A. Differential exposure to 33 toxic elements through cigarette smoking, based on the type of tobacco and rolling paper used. Environ. Res. 2019, 169, 368–376. [Google Scholar] [CrossRef] [PubMed]
- Badea, M.; Luzardo, O.P.; Gonzalez-Antuna, A.; Zumbado, M.; Rogozea, L.; Floroian, L.; Alexandrescu, D.; Moga, M.; Gaman, L.; Radoi, M.; et al. Body burden of toxic metals and rare earth elements in non-smokers, cigarette smokers and electronic cigarette users. Environ. Res. 2018, 166, 269–275. [Google Scholar] [CrossRef] [PubMed]
- Mezynska, M.; Brzoska, M.M. Environmental exposure to cadmium-a risk for health of the general population in industrialized countries and preventive strategies. Environ. Sci. Pollut. Res. Int. 2018, 25, 3211–3232. [Google Scholar] [CrossRef] [PubMed]
- Lin, C.H.; Hsu, Y.T.; Yen, C.C.; Chen, H.H.; Tseng, C.J.; Lo, Y.K.; Chan, J.Y.H. Association between heavy metal levels and acute ischemic stroke. J. Biomed. Sci. 2018, 25, 49. [Google Scholar] [CrossRef] [PubMed]
- Wang, B.; Zhu, Y.; Pang, Y.; Xie, J.; Hao, Y.; Yan, H.; Li, Z.; Ye, R. Indoor air pollution affects hypertension risk in rural women in Northern China by interfering with the uptake of metal elements: A preliminary cross-sectional study. Environ. Pollut. 2018, 240, 267–272. [Google Scholar] [CrossRef]
- Chowdhury, R.; Ramond, A.; O’Keeffe, L.M.; Shahzad, S.; Kunutsor, S.K.; Muka, T.; Gregson, J.; Willeit, P.; Warnakula, S.; Khan, H.; et al. Environmental toxic metal contaminants and risk of cardiovascular disease: Systematic review and meta-analysis. BMJ 2018, 362, k3310. [Google Scholar] [CrossRef] [Green Version]
- Wen, Y.; Huang, S.; Zhang, Y.; Zhang, H.; Zhou, L.; Li, D.; Xie, C.; Lv, Z.; Guo, Y.; Ke, Y.; et al. Associations of multiple plasma metals with the risk of ischemic stroke: A case-control study. Environ. Int. 2019, 125, 125–134. [Google Scholar] [CrossRef]
- Wang, W.; Liu, C.; Ying, Z.; Lei, X.; Wang, C.; Huo, J.; Zhao, Q.; Zhang, Y.; Duan, Y.; Chen, R.; et al. Particulate air pollution and ischemic stroke hospitalization: How the associations vary by constituents in Shanghai, China. Sci. Total Environ. 2019, 695, 133780. [Google Scholar] [CrossRef]
- Saravanabhavan, G.; Werry, K.; Walker, M.; Haines, D.; Malowany, M.; Khoury, C. Human biomonitoring reference values for metals and trace elements in blood and urine derived from the Canadian Health Measures Survey 2007–2013. Int. J. Hyg. Environ. Health 2017, 220, 189–200. [Google Scholar] [CrossRef] [Green Version]
- Henriquez-Hernandez, L.A.; Romero, D.; Gonzalez-Antuna, A.; Gonzalez-Alzaga, B.; Zumbado, M.; Boada, L.D.; Hernandez, A.F.; Lopez-Flores, I.; Luzardo, O.P.; Lacasana, M. Biomonitoring of 45 inorganic elements measured in plasma from Spanish subjects: A cross-sectional study in Andalusian population. Sci. Total Environ. 2020, 706, 135750. [Google Scholar] [CrossRef] [PubMed]
- Xiao, L.; Wei, F.; Zhou, Y.; Anderson, G.J.; Frazer, D.M.; Lim, Y.C.; Liu, T.; Xiao, Y. Dihydrolipoic Acid-Gold Nanoclusters Regulate Microglial Polarization and Have the Potential to Alter Neurogenesis. Nano Lett. 2020, 20, 478–495. [Google Scholar] [CrossRef] [PubMed]
- Estevez, A.Y.; Pritchard, S.; Harper, K.; Aston, J.W.; Lynch, A.; Lucky, J.J.; Ludington, J.S.; Chatani, P.; Mosenthal, W.P.; Leiter, J.C.; et al. Neuroprotective mechanisms of cerium oxide nanoparticles in a mouse hippocampal brain slice model of ischemia. Free Radic. Biol. Med. 2011, 51, 1155–1163. [Google Scholar] [CrossRef] [PubMed]
- Kim, C.K.; Kim, T.; Choi, I.Y.; Soh, M.; Kim, D.; Kim, Y.J.; Jang, H.; Yang, H.S.; Kim, J.Y.; Park, H.K.; et al. Ceria nanoparticles that can protect against ischemic stroke. Angew. Chem. Int. Ed. Engl. 2012, 51, 11039–11043. [Google Scholar] [CrossRef]
- Zhou, D.; Fang, T.; Lu, L.Q.; Yi, L. Neuroprotective potential of cerium oxide nanoparticles for focal cerebral ischemic stroke. J. Huazhong Univ. Sci. Technolog. Med. Sci. 2016, 36, 480–486. [Google Scholar] [CrossRef]
- Hou, Q.; Huang, L.; Ge, X.; Yang, A.; Luo, X.; Huang, S.; Xiao, Y.; Jiang, C.; Li, L.; Pan, Z.; et al. Associations between multiple serum metal exposures and low birth weight infants in Chinese pregnant women: A nested case-control study. Chemosphere 2019, 231, 225–232. [Google Scholar] [CrossRef]
Cases N (%) | Controls N (%) | p-Value | |
---|---|---|---|
All participants | 92 (52.6) | 83 (47.4) | |
Gender | |||
Male | 47 (51.1) | 43 (51.8) | 0.924 a |
Female | 45 (48.9) | 40 (48.2) | |
Age (years) | |||
Mean ± SD | 64.1 ± 12.7 | 61.7 ± 14.8 | 0.472 b |
Median | 64 | 65 | |
Range | 34–87 | 33–86 | |
Smoker (yes) | 31 (33.7) | 14 (16.9) | 0.015 a |
Diabetes (yes) | 25 (27.2) | 29 (34.9) | 0.326 a |
Arterial hypertension (yes) | 61 (66.3) | 28 (33.7) | ˂0.0001 a |
Dyslipidemia (yes) | 61 (66.3) | 30 (36.1) | ˂0.0001 a |
Coronary cardiopathy (yes) | 30 (32.6) | 13 (15.7) | 0.013 a |
Barthel index | |||
Mean ± SD | 67.2 ± 32.7 | 93.2 ± 16.9 c | ˂0.0001 b |
Median | 75 | 100 | |
0–60 (severe dependence) | 38 (41.3) | 9 (11.0) | ˂0.0001 a |
61–90 (moderate dependence) | 20 (21.7) | 6 (7.3) | |
>90 (poor dependence/Independence) | 34 (37.0) | 67 (81.7) |
Controls (n = 83) | Cases (n = 92) | ||||||
---|---|---|---|---|---|---|---|
Frequency of Detection (%) | Median | (p5th–p95th) | Frequency of Detection (%) | Median | (p5th–p95th) | p-Value b | |
Ag (silver) | 79.5 | 0.006 | (0–0.37) | 80.4 | 0.064 | (0–0.29) | 0.429 |
As (arsenic) | 100 | 1.69 | (0.45–7.74) | 100 | 1.61 | (0.38–5.50) | 0.546 |
Ba (barium) | 100 | 207.0 | (111.9–669.3) | 100 | 173.5 | (96.3–324.8) | ˂0.0001 |
Be (beryllium) | 8.4 | 0.002 | (0–0.20) | 12.0 | 0.005 | (0–0.57) | 0.006 |
Cd (cadmium) | 100 | 0.25 | (0.09–1.32) | 100 | 0.26 | (0.12–1.06) | 0.359 |
Co (cobalt) | 97.6 | 0.19 | (0.11–0.38) | 100 | 0.19 | (0.11–0.45) | 0.742 |
Cu (copper) c,d | 100 | 0.60 | (0.42–0.89) | 100 | 0.62 | (0.49–0.80) | 0.293 |
Hg (mercury) | 98.8 | 3.74 | (1.01–17.4) | 100 | 3.65 | (0.92–11.9) | 0.793 |
Mn (manganese) c | 96.4 | 8.48 | (0.16–14.5) | 97.8 | 7.85 | (4.55–16.8) | 0.591 |
Ni (nickel) | 92.8 | 1.08 | (0.048–52.6) | 93.5 | 0.98 | (0.052–76.5) | 0.534 |
Pb (lead) | 100 | 9.03 | (4.21–20.0) | 100 | 11.2 | (4.01–25.3) | 0.011 |
Pd (palladium) | 19.3 | 0.002 | (0–0.083) | 9.8 | 0.004 | (0–0.25) | 0.352 |
Se (selenium) c | 100 | 126.1 | (73.0–205.3) | 100 | 128.3 | (79.6–169.2) | 0.589 |
Sb (antimony) | 33.7 | 0.027 | (0.003–1.14) | 26.1 | 0.022 | (0.002–1.31) | 0.151 |
Sr (strontium) | 100 | 16.6 | (11.2–25.0) | 100 | 15.4 | (9.93–28.7) | 0.101 |
Th (thorium) | 92.8 | 0.071 | (0.001–0.22) | 89.1 | 0.061 | (0.001–0.12) | 0.082 |
U (uranium) | 100 | 0.082 | (0.051–0.21) | 100 | 0.072 | (0.037–0.16) | 0.024 |
V (vanadium) | 59.0 | 0.011 | (0.001–0.44) | 35.9 | 0.008 | (0–0.56) | 0.221 |
Zn (zinc) c,d | 100 | 5.13 | (3.7–8.06) | 100 | 5.29 | (3.77–6.53) | 0.652 |
Element | Odds Ratio | 95% CI | p-Value a |
---|---|---|---|
Univariate analyses | |||
Ba (barium) | 0.34 | (0.19–0.60) | <0.001 |
Pb (lead) | 1.65 | (1.09–2.50) | 0.019 |
Au (gold) | 0.81 | (0.70–0.95) | 0.007 |
Ce (cerium) | 0.61 | (0.42–0.90) | 0.012 |
Ga (gallium) | 0.64 | (0.46–0.88) | 0.007 |
Multivariate analyses | |||
Ba (barium) | 0.28 | (0.15–0.55) | <0.001 |
Pb (lead) | 1.91 | (1.20–3.04) | 0.006 |
Au (gold) | 0.81 | (0.69–0.95) | 0.011 |
Ce (cerium) | 0.50 | (0.31–0.78) | 0.003 |
Ga (gallium) | 0.58 | (0.40–0.86) | 0.006 |
Controls (n = 83) | Cases (n = 92) | ||||||
---|---|---|---|---|---|---|---|
Frequency of Detection (%) | Median | (p5th–p95th) | Frequency of Detection (%) | Median | (p5th–p95th) | p-Value b | |
Au (gold) | 57.8 | 0.013 | (0.001–0.80) | 30.4 | 0.007 | (0–0.28) | 0.001 |
Bi (bismuth) | 86.7 | 0.11 | (0.001–0.33) | 63.0 | 0.085 | (0–0.16) | 0.001 |
Ce (cerium) | 100 | 18.0 | (8.02–81.7) | 100 | 15.0 | (7.23–47.2) | 0.010 |
Dy (dysprosium) | 86.7 | 0.017 | (0–0.062) | 84.8 | 0.018 | (0–0.037) | 0.459 |
Er (erbium) | 57.8 | 0.002 | (0–0.027) | 41.3 | 0 | (0–0.015) | 0.806 |
Eu (europium) | 45.8 | 0 | (0–0.022) | 58.7 | 0.007 | (0–0.017) | 0.047 |
Fe (iron) c,d | 100 | 275.5 | (187.6–427.6) | 100 | 277.8 | (203.4–357.9) | 0.860 |
Ga (gallium) | 100 | 0.61 | (0.27–4.47) | 100 | 0.49 | (0.20–1.58) | 0.014 |
Gd (gadolinium) | 69.9 | 0.036 | (0–0.15) | 63.0 | 0.032 | (0–0.089) | 0.207 |
Ho (holmium) | 26.5 | 0 | (0–0.010) | 43.5 | 0 | (0–0.007) | 0.079 |
In (indium) | 20.5 | 0 | (0–0.035) | 64.1 | 0.001 | (0–0.040) | 0.000 |
La (lanthanum) | 47.0 | 0.010 | (0.002–0.30) | 22.8 | 0.007 | (0–0.28) | 0.002 |
Lu (lutetium) | 12.0 | 0 | (0–0.003) | 7.6 | 0 | (0–0.002) | 0.425 |
Nb (niobium) | 49.4 | 0.014 | (0.001–0.58) | 29.3 | 0.011 | (0.001–0.57) | 0.159 |
Nd (neodymium) | 53.0 | 0.006 | (0.001–0.28) | 50.0 | 0.005 | (0.001–0.22) | 0.275 |
Os (osmium) | 81.9 | 0.002 | (0–0.023) | 66.3 | 0.001 | (0–0.053) | 0.000 |
Pr (praseodymium) | 48.2 | 0.001 | (0–0.070) | 50.0 | 0.002 | (0–0.051) | 0.727 |
Pt (platinum) | 30.1 | 0 | (0–0.014) | 45.7 | 0 | (0–0.010) | 0.001 |
Ru (ruthenium) | 60.2 | 0.001 | (0–0.002) | 22.8 | 0 | (0–0.002) | 0.000 |
Sm (samarium) | 83.1 | 0.001 | (0–0.067) | 79.3 | 0.001 | (0–0.045) | 0.109 |
Sn (tin) | 54.2 | 0.17 | (0.017–4.16) | 42.4 | 0.11 | (0.018–8.58) | 0.680 |
Ta (tantalum) | 9.6 | 0.003 | (0.001–0.28) | 8.7 | 0.004 | (0.001–0.35) | 0.107 |
Tb (terbium) | 22.9 | 0 | (0–0.014) | 8.7 | 0 | (0–0.009) | 0.410 |
Tm (thulium) | 3.6 | 0 | (0–0.003) | 19.6 | 0 | (0–0.003) | 0.009 |
Y (yttrium) | 54.2 | 0.004 | (0–0.26) | 56.5 | 0.004 | (0–0.17) | 0.756 |
Yb (ytterbium) | 19.3 | 0 | (0–0.015) | 26.1 | 0 | (0–0.012) | 0.001 |
© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Medina-Estévez, F.; Zumbado, M.; Luzardo, O.P.; Rodríguez-Hernández, Á.; Boada, L.D.; Fernández-Fuertes, F.; Santandreu-Jimenez, M.E.; Henríquez-Hernández, L.A. Association between Heavy Metals and Rare Earth Elements with Acute Ischemic Stroke: A Case-Control Study Conducted in the Canary Islands (Spain). Toxics 2020, 8, 66. https://doi.org/10.3390/toxics8030066
Medina-Estévez F, Zumbado M, Luzardo OP, Rodríguez-Hernández Á, Boada LD, Fernández-Fuertes F, Santandreu-Jimenez ME, Henríquez-Hernández LA. Association between Heavy Metals and Rare Earth Elements with Acute Ischemic Stroke: A Case-Control Study Conducted in the Canary Islands (Spain). Toxics. 2020; 8(3):66. https://doi.org/10.3390/toxics8030066
Chicago/Turabian StyleMedina-Estévez, Florián, Manuel Zumbado, Octavio P. Luzardo, Ángel Rodríguez-Hernández, Luis D. Boada, Fernando Fernández-Fuertes, María Elvira Santandreu-Jimenez, and Luis Alberto Henríquez-Hernández. 2020. "Association between Heavy Metals and Rare Earth Elements with Acute Ischemic Stroke: A Case-Control Study Conducted in the Canary Islands (Spain)" Toxics 8, no. 3: 66. https://doi.org/10.3390/toxics8030066
APA StyleMedina-Estévez, F., Zumbado, M., Luzardo, O. P., Rodríguez-Hernández, Á., Boada, L. D., Fernández-Fuertes, F., Santandreu-Jimenez, M. E., & Henríquez-Hernández, L. A. (2020). Association between Heavy Metals and Rare Earth Elements with Acute Ischemic Stroke: A Case-Control Study Conducted in the Canary Islands (Spain). Toxics, 8(3), 66. https://doi.org/10.3390/toxics8030066