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Most animals are complex multicellular organisms that require a mechanism for transporting nutrients throughout their bodies and removing waste products. The circulatory system has evolved over time from simple diffusion through cells in the early evolution of animals to a complex network of blood vessels that reach all parts of the human body. This extensive network supplies the cells, tissues, and organs with oxygen and nutrients, and removes carbon dioxide and waste, which are byproducts of respiration.
At the core of the human circulatory system is the heart. The size of a clenched fist, the human heart is protected beneath the rib cage. Made of specialized and unique cardiac muscle, it pumps blood throughout the body and to the heart itself. Heart contractions are driven by intrinsic electrical impulses that the brain and endocrine hormones help to regulate. Understanding the heart’s basic anatomy and function is important to understanding the body’s circulatory and respiratory systems.
Gas exchange is one essential function of the circulatory system. A circulatory system is not needed in organisms with no specialized respiratory organs because oxygen and carbon dioxide diffuse directly between their body tissues and the external environment. However, in organisms that possess lungs and gills, oxygen must be transported from these specialized respiratory organs to the body tissues via a circulatory system. Therefore, circulatory systems have had to evolve to accommodate the great diversity of body sizes and body types present among animals.
40.0: Prelude to the Circulatory System - Biology
Figure 1. The major human arteries and veins are shown. (credit: modification of work by Mariana Ruiz Villareal)
The blood from the heart is carried through the body by a complex network of blood vessels (Figure 1). Arteries take blood away from the heart. The main artery is the aorta that branches into major arteries that take blood to different limbs and organs. These major arteries include the carotid artery that takes blood to the brain, the brachial arteries that take blood to the arms, and the thoracic artery that takes blood to the thorax and then into the hepatic, renal, and gastric arteries for the liver, kidney, and stomach, respectively. The iliac artery takes blood to the lower limbs. The major arteries diverge into minor arteries, and then smaller vessels called arterioles, to reach more deeply into the muscles and organs of the body.
Arterioles diverge into capillary beds. Capillary beds contain a large number (10 to 100) of capillaries that branch among the cells and tissues of the body. Capillaries are narrow-diameter tubes that can fit red blood cells through in single file and are the sites for the exchange of nutrients, waste, and oxygen with tissues at the cellular level. Fluid also crosses into the interstitial space from the capillaries. The capillaries converge again into venules that connect to minor veins that finally connect to major veins that take blood high in carbon dioxide back to the heart. Veins are blood vessels that bring blood back to the heart. The major veins drain blood from the same organs and limbs that the major arteries supply. Fluid is also brought back to the heart via the lymphatic system.
The structure of the different types of blood vessels reflects their function or layers. There are three distinct layers, or tunics, that form the walls of blood vessels (Figure 2). The first tunic is a smooth, inner lining of endothelial cells that are in contact with the red blood cells. The endothelial tunic is continuous with the endocardium of the heart. In capillaries, this single layer of cells is the location of diffusion of oxygen and carbon dioxide between the endothelial cells and red blood cells, as well as the exchange site via endocytosis and exocytosis. The movement of materials at the site of capillaries is regulated by vasoconstriction, narrowing of the blood vessels, and vasodilation, widening of the blood vessels this is important in the overall regulation of blood pressure.
Figure 2. Arteries and veins consist of three layers: an outer tunica externa, a middle tunica media, and an inner tunica intima. Capillaries consist of a single layer of epithelial cells, the tunica intima. (credit: modification of work by NCI, NIH)
Veins and arteries both have two further tunics that surround the endothelium: the middle tunic is composed of smooth muscle and the outermost layer is connective tissue (collagen and elastic fibers). The elastic connective tissue stretches and supports the blood vessels, and the smooth muscle layer helps regulate blood flow by altering vascular resistance through vasoconstriction and vasodilation. The arteries have thicker smooth muscle and connective tissue than the veins to accommodate the higher pressure and speed of freshly pumped blood. The veins are thinner walled as the pressure and rate of flow are much lower. In addition, veins are structurally different than arteries in that veins have valves to prevent the backflow of blood. Because veins have to work against gravity to get blood back to the heart, contraction of skeletal muscle assists with the flow of blood back to the heart.
Links and Resources
ABPI Heart and circulation web site
This web site has been written specifically for key stage 4 students. It covers the following:
&bull The need for a transport system
&bull The circulatory system
&bull The heart
&bull The blood vessels
&bull The blood and blood clotting
&bull Blood pressure
&bull Cardiovascular disease
&bull Prevention and treatment of cardiovascular disease
Each section contains brief self-test questions.
The web site can be used to allow students to learn independently and could be part of a &lsquoflipped classroom&rsquo approach. This is where students learn content away from the classroom and then use teacher contact time to check understanding, go over misconceptions or tackle questions on the topic.
When using the web site, it is a good idea to give students specific tasks to address. These could include:
&bull What materials does blood transport throughout the body. Why do these materials need to be carried?
&bull Describe the role of each of the components in the blood.
&bull Compare and contrast the structures and functions of arteries, veins and capillaries.
&bull Explain why humans have a double circulatory system.
&bull Describe the structure of the heart.
&bull Describe the sequence of events in a cardiac cycle (heartbeat).
&bull How does the pressure change in each of the chambers during one heartbeat?
&bull Describe blood clotting and how this helps to prevent disease.
&bull Suggest ways that a person could help reduce their risk of having a heart attack.
Let's Dissect - the Heart
This video is a detailed and fairly graphic account of the dissection of a pig&rsquos heart. The dissection, and accompanying commentary, shows all of the main features of the heart. It should be shown after students have been made aware of the heart structure.
Dissection is a sensitive issue. It is worth telling students about the video and any dissection the lesson before it is due to take place. In that way, students with real concerns can talk to you and alternative self-study away from the laboratory can be organised if necessary.
Reassure students that the heart is from a pig and that the animal was not killed for the purpose of the dissection but would have been killed for food production.
The first few minutes of the video clip show the heart connected to a set of lungs. This is good to see but looks quite bloody. You may want to preview this section to see that it is suitable for your students. If in doubt, advance the video to 54seconds where the heart is cleaned up and the anatomy is being described.
The video can be the prelude for an actual dissection of a hearts obtained from the butchers. Take care to be sensitive to cultural objections to using materials from pigs or cows. Discussing this with students prior to the lesson is recommended. In certain circumstances you may want to inform parents in advance of the class. It is worth, have an alternative activity prepared for students who do not wish to take part or watch a dissection.
Remember to consider the sensible precautions for using scissors or scalpels and it is advisable to use cutting boards. Supplying students with disposable gloves can encourage them to use fingers, or glass rods, to explore heart chambers and blood vessels.
Challenge students to find the different chambers and major blood vessels (often the atria are missing as they have been chopped off during butchery of the carcass).
It is worth showing students the coronary arteries that supply the cardiac muscle. Show how small they are and note that these are the vessels that, if blocked, cause a heart attack. Remind students of the link between excess fat in the diet and blocked arteries causing a heart attack.
Links and Resources
ABPI interactive website *suitable for home teaching*
This interactive website has a number of sections which are relevant to this topic area of GCSE Biology, these include: &bull
- The need for a transport system
- The circulatory system
- The heart
- The blood vessels
- The blood and blood clotting
- Blood pressure
- Cardiovascular disease
- Prevention and treatment of cardiovascular disease.
In each section there is information and a brief self-test quiz. These sections could be used for independent learning/homework activities. Different students could be asked to complete specific tasks to answer in class having worked through the website for homework , tasks could include:
- What materials does blood transport throughout the body.
- Why do these materials need to be carried?
- Describe the role of each of the components in the blood.
- Compare and contrast the structures and functions of arteries, veins and capillaries.
- Explain why humans have a double circulatory system.
- Describe the structure of the heart.
- Describe the sequence of events in a cardiac cycle (heartbeat).
- How does the pressure change in each of the chambers during one heartbeat?
- Describe blood clotting and how this helps to prevent disease.
- Suggest ways that a person could help reduce their risk of having a heart attack
Cardiovascular System *suitable for home teaching*
This is a three page summary sheet on the cardiovascular system. The resource provides details of the functions and key mechanisms involved in the cardiovascular system. It explains the role of the cardiovascular system in homeostasis and describes atherosclerosis and the role of aspirin in managing heart attacks.
This is a clear concise summary with some good illustrations. Although originally designed for use with post 16 students it would be useful for higher ability students.
Students could work in pairs, read through the article and then prepare 5 questions to challenge each other with. the questions should be answered without reference to the summary sheet
On the nature of biological "systems"
A 'system' in biology is any interconnected, interacting, coordinated and hierarchical assembly of biological components or elements—an organized assemblage with identifiable behavior. For example, the vertebrate body is an assembly of diverse, interacting organs, among other components, behaving to survive and reproduce. The mitochondria of cells comprise a system for converting food energy into a general-use molecule for energizing biochemical reactions. Each component in a biological system interacts in some way(s) with one or more components in the system--a dynamical assembly of components. In a cell, proteins are the products of genes, but they also interact with genes, affecting their expression, as well as interacting with other proteins. Systems can exhibit behaviors that are characteristic of the system-as-a-whole (see below), but which are not shared by any of its components (so-called emergent behaviors). A tree fruits, for example, because its dynamically interacting components enable it to, but no single component of a tree can.
Subsystems consist of smaller (less complex) systems embedded in a larger (more complex) system, and constitute at least part of the components or elements of the larger system. Whether a systems biologist treats a given assembly of components as a subsystem or as a system depends on the 'level' at which she focuses her attention. If she focuses her research at the level of a whole vertebrate organism, for example, she treats its organs as subsystems. If she focuses her research at the level of the heart, she treats the heart's interacting components as a system, while recognizing that the heart remains part of a larger system (the circulatory system).
Even the larger systems, such as the vertebrate body system, are components or elements of even larger systems, a species of vertebrates, say, where individual members of the species interact with each other, as components, to generate a set of behaviors or properties characteristic of the species but not of its individual members. The flocking behavior of birds illustrates a species behavior--technically the behavior of a deme. One bird cannot flock. Reproduction among sexually reproducing species requires the emergent behavior of two individuals.
When trying to understand biological systems, systems biologists need not treat the components or elements of a system (or subsystem) exclusively as discrete or concrete objects or entities (e.g., molecules, organelles, cells, etc.), but may also treat them as abstracted concepts of organizational collections or activity patterns of those entities (e.g., networks), which admit of study by graphical, mathematical, computational and statistical tools. Those include such concepts as circuits, networks and modules. Such concepts have a way of appearing less abstract or hypothetical as biologists more fully define them in terms of structure and coordinated dynamical interactions predict systems behavior from them using quantitative models and relate them functionally in the larger systems embedding them. Indeed, Bruggeman and Westerhoff  remark that the advances in molecular biology and mathematical modeling have ". shifted the focus of research from molecules to networks. ", citing Barabasi and Otvai's review  underscoring the importance of networks in understanding the organization of cells.
'Complex' vs. 'Complicated'
Systems biologists distinguish between the complex and the complicated. A complicated system need not qualify as complex. It may have many parts, intricately interconnected, but no one part may play a critical role in the system's operation, each part more or less independent. A 1000-piece assembled jigsaw puzzle may represents a complicated scene, but a missing piece hardly affects the visual result. A biological cell with a missing chromosome, however, becomes seriously dysfunctional. John H. Miller, professor of economics and social sciences at Carnegie Mellon University, and Scott E. Page, professor of complex systems, political science, and economics at the University of Michigan, express the difference as follows:
We would, however, like to make a distinction between complicated worlds and complex ones. In a complicated world, the various elements that make up the system maintain a degree of independence from one another. Thus, removing one such element (which reduces the level of complication) does not fundamentally alter the system’s behavior apart from that which directly resulted from the piece that was removed. Complexity arises when the dependencies among the elements become important. In such a system, removing one such element destroys system behavior to an extent that goes well beyond what is embodied by the particular element that is removed. 
Networks  ‘re-present’ or 'abstract' a system as an assemblage of 'nodes’ and ‘interactions’ among the nodes (also referred to as ‘edges’ or ‘arrows’ or ‘links’). In a spoken sentence, for example, words and phrases make up the nodes, and the interconnections of syntax (subject-to-predicate, preposition-to-object of preposition, etc.) make up the links. Molecular networks in cells represent specific functions in the cell molecules make up the nodes, and their interactions with other nodes make up the edges or arrows. Networks accept inputs of one kind and return outputs of a different kind.
One finds networks everywhere in biology, from intracellular signaling pathways, to intraspecies networks, to ecosystems. Humans deliberately construct social networks of individuals working (more or less) to a common purpose, such as the U.S. Congress they also construct networks of electronic parts to produce, for example, mobile phones and networks of sentences and paragraphs to express messages, including this article. Researchers view the World Wide Web as a network, and study its characteristics and dynamics.  
According to Alon, "The cell can be viewed as an overlay of at least three types of networks, which describes protein-protein, protein-DNA, and protein-metabolite interactions."  Alon notes that cellular networks, like many human engineered networks, show 'modularity', 'robustness', and 'motifs':
- Modules are subnetworks with a specific function and which connect with other modules often only at one input node and one output node. Modularity facilitates evolutionary adaptation to changing environments, for to produce an adaptation, evolution need tinker with just a few modules rather than with the whole system. Evolution can sometimes 'exapt' existing modules for new functions that contribute to reproductive fitness. For example, the swim bladder purportedly evolved as an adaptation for control of buoyancy later exapted as a respiratory organ in various groups of fish. 
- Robustness describes how a network is able to maintain its functionality despite environmental perturbations that affect the components. Robustness also reduces the range of network types that researchers must consider, because only certain types of networks are robust.
- Network motifs offer economy of network design, as the same circuit can have many different uses in cellular regulation, as in the case of autoregulatory circuits and feedforward loops. Nature selects motifs in part for their ability to make networks robust, so systems use motifs that work well over and over again in many different networks.  In several well-studied biological networks, the abundance of network motifs — small subnetworks — correlates with the degree of robustness.  Networks, like those in cells and those in neural networks in the brain,  use motifs as basic building blocks, like multicellular organisms use cells as basic building blocks. Motifs offer biologists a level of simplicity of biological functionality for their efforts to model the dynamics of organized hierarchies of networks. 
The view of the cell as an overlay of mathematically-definable (in principle) dynamic networks can reveal how a living system can exist as an improbable, intricate, self-orchestrated dance of molecules.  The 'overlay of networks' view also suggests how the concept of self-organized networks can extend to all higher levels of living systems.
Biological system behaviors typically perform one or more evolution-informed functions (e.g., growth), so unraveling the evolutionary history of the networks in a biological system contributes importantly in explaining it. Evolutionary history requires knowledge of the mechanisms of both generation and selection.
Examples of biological systems
Examples of biological systems (subsystems) include:
- the biosphere
- ecosystems (e.g., a forest)
- demes (e.g., a local population of a species)
- organisms (e.g., humans bacteria)
- organs (e.g., brain the vascular endothelium)
- cells (e.g., epithelial cell)
- metabolic pathways (e.g., glycolysis)
- cellular organelles (e.g., mitochondria)
- genomes (e.g., the entire complement of DNA in an organism, as the ’mouse genome')
- gene complexes (e.g., co-expressing genes)
- genes (e.g., protein blueprints)
In the context of high adult mortality and an immense impact on the health burden of Zambia, a decomposition analysis of age- and cause-specific mortality in age group 15–59 was performed to determine the contributions to the gap in life expectancy at birth between males and females. Previous studies on decomposition have examined income groups, ethnicity, and regional differences’ contributions to gaps in life expectancy, but not the adult mortality age group 15–59. These studies focus on developed countries and few on developing countries. Arriaga’s decomposition method was applied to 2010 census and 2010–2012 sample vital registration with verbal autopsy survey (SAVVY) data to decompose contributions of age- and cause-specific adult mortality to the gap in life expectancy at birth between males and females. The decomposition analysis revealed that mortality was higher among males than females and concentrated in age groups 20–49. Age- and cause-specific adult mortality contributed positively, 50% of the years to the gap in life expectancy at birth between males and females. Major cause-specific mortality contributors to the gap in life expectancy were infectious and parasitic diseases (1.17 years, 26.3%), accidents and injuries (0.54 years, 12.2%), suicide and violence (0.30 years, 6.8%). Female HIV mortality offset male mortality. Neoplasms deaths among females contributed negatively to the gap in life expectancy (-0.22 years, -5.4%). Accidents, injuries, suicide, and violence are emerging major causes of death in age group 20–49 in Zambia which health policy and programmes should target.
40.0: Prelude to the Circulatory System - Biology
Available studies in the literature on the selenium levels in Alzheimer's disease (AD) are inconsistent with some studies reporting its decrease in the circulation, while others reported an increase or no change as compared to controls.
The objective of this study was to perform a meta-analysis of circulatory (plasma/serum and blood), erythrocyte and cerebrospinal fluid (CSF) selenium levels in AD compared controls. We also performed a meta-analysis of the correlation coefficients (r) to demonstrate the associations between selenium and glutathione peroxidase (GPx) in AD patients.
All major databases were searched for eligible studies. We included 12 case–control/observational studies reporting selenium concentrations in AD and controls. Pooled-overall effect size as standardized mean difference (SMD) and pooled r-values were generated using Review Manager 5.3 and MedCalc 15.8 software.
Random-effects meta-analysis indicated a decrease in circulatory (SMD = −0.44), erythrocellular (SMD = −0.52) and CSF (SMD = −0.14) selenium levels in AD patients compared to controls. Stratified meta-analysis demonstrated that the selenium levels were decreased in both the subgroups with (SMD = −0.55) and without (SMD = −0.37) age matching between AD and controls. Our results also demonstrated a direct association between decreased selenium levels and GPx in AD.
This meta-analysis suggests that circulatory selenium concentration is significantly lower in AD patients compared to controls and this decrease in selenium is directly correlated with an important antioxidant enzyme, the GPx, in AD.
The deadly spike protein, take two
About three weeks ago, antivaxxers started pointing to a study from the Salk Institute as yet more “proof” that the spike protein used in COVID-19 vaccines is toxic and deadly. For instance, behold Alex Berenson, the “pandemic’s wrongest man“, crowing about the study:
As smoking guns go, this study is high-caliber. @UCSanDiego and Chinese researchers showed that the #SARSCoV2 spike protein – the one the vaccines make you produce – can all by itself cause major damage to the walls of blood vessels. pic.twitter.com/Fk5DNZugzH
&mdash Alex Berenson (@AlexBerenson) May 2, 2021
I was amused when I saw these Tweets to see Berenson use a term like “off-target effects” as if he actually knows what it means.
It turns out that this study on a preprint server has been published in Circulation Research . It also turns out—surprise! surprise!—to definitely not to be “smoking gun” evidence for Berenson’s claims. Unlike the case of many papers cherry picked by antivaxxers to support their claims, it’s not that the paper is horrible, either. It’s not. It’s pretty decent, actually, at least as a preliminary, primarily observational study. Even more amusing, in it the authors expressly describe how their work actually demonstrates why vaccines that use spike protein as the antigen are so effective, and the Salk Institute press release even includes a disclaimer that the spike proteins made in cells by SARS-CoV-2 “behave very differently than those safely encoded by vaccines”.
Let’s look at the paper itself. The first thing that those of you with access to the paper will notice is how short it is: Three pages, one figure. That’s because it’s not a full research paper, but rather a research letter. As a result, there’s no detailed Methods section, and the results are very briefly described (much too briefly, for my liking). To be honest, for some of the experiments, due to the brevity of the paper, I had a bit of a hard time making heads or tails of what, exactly, the investigators did. I’ll do my best trying to explain, however.
In brief, the researchers used a “pseudovirus” that was surrounded by a “crown” of spike protein, like the coronavirus, but did not contain actual virus, dubbed Pseu-Spike by the authors. What is a pseudovirus? A reasonable question. In brief, a pseudovirus is a construct that has the external proteins of the virus of interest. There are a variety of pseudoviruses now, as described in this article in The Scientist :
Among these, researchers turned to models of the pathogen such as pseudoviruses and chimeric viruses that can be studied safely in labs with lower biosafety level (BSL) clearance than required for studying the wildtype version, in an effort to expand the study of the novel coronavirus. Pseudoviruses don’t replicate, rendering them harmless, but by replacing their surface envelope proteins with those of SARS-CoV-2, researchers can glean insights into the ways the pathogen infects cells.
Pseudoviruses were first developed in the 1960s, after scientists began studying a vesicular stomatitis virus (VSV) isolated from cattle. In addition to replicating well in culture, they later learned that its surface protein, VSV-G, facilitates entry into all eukaryotic cells, making the virus a useful vector not only as a pseudovirus but as a ferry to deliver DNA into cells for therapeutic purposes. The first Ebola vaccine was developed using a VSV platform, and more recently, the virus has been engineered to seek out and destroy cancer cells.
HIV-based platforms, which came about in the 1980s, have since replaced VSV as the most common model for developing both pseudo- and chimeric viruses. Unlike VSV’s negative-strand RNA genome that must be transcribed once inside the cell, HIV’s positive-strand RNA genome can instantly begin translation, making pseudoviruses based on HIV faster to produce. HIV-based model viruses have now been used in many of the same applications as VSV, with scientists applying them to the study of diseases such as AIDS, SARS, MERS, and influenza.
Also, compared with natural virus, a pseudovirus can only infect cells in a single round, has broad host range, high titer, and is not easily inactivated by serum complement.
Unfortunately, it is not clear from the paper which of these platforms was used to produce the pseudovirus in the experiments or how that pseudovirus was developed and produced. This is the sort of information that a full-length research paper would describe in the Methods section and it’s important information for determining whether the pseudovirus used was likely to be a good model. In another issue with this paper, the authors also do not describe the “mock virus” that they used as a control or how it was constructed. As a result, I find it very difficult to interpret their results. In fairness, some of this confusion might be because I am not highly knowledgeable about this particular system and don’t have the background knowledge about methodology that the authors clearly assume that the reader possesses. On the other hand, in a paper this in a journal like Circulation Research , which is not a virology journal, and particularly given that this is a paper that was likely to make the news and be misused by antivaxxers after its release, explanatory details that allow scientists from other fields with knowledge of molecular biology (but who are not experts in this field) to understand what was done are critical. A Research Letter does not accomplish this.
My concerns aside, let’s look at the experiments. The authors took pseudovirus or mock virus and instilled it into the tracheas of Syrian hamsters, three animals per experimental group. Another aspect of this study caught my eye, namely the amount of virus used, 5 x 10 8 pfu. For those of you not knowing what “pfu” stands for, it stands for “plaque-forming units.” Basically it’s a measure of the number of viable virus particles, virus particles that can infect cells and cause a plaque on a confluent layer of cells. That’s half a billion particles, far, far more of a viral challenge than the amount of virus launching any “natural” infection by SARs-CoV-2.
Using what is a highly artificial system, the authors compared the levels of a whole slate of protein markers related to cell signaling and oxidative stress in the mock- and Pseu-Spike-treated hamsters, as well as the histology of the lungs. I won’t go into detail about all of the markers examined, but rather will step back to take a longer view because it is not important for a lay person to understand all the phosphorylation of this protein or ubiquitination of that protein measured. (It’s also easy to get lost in the weeds of a study like this.) As stated, the authors found signs of inflammation in the alveoli (air sacs) of the Pseu-Spike-treated lungs, including thickened walls and inflammatory cells. They measured the levels of various proteins they deemed relevant:
AMPK (AMP-activated protein kinase) phosphorylates ACE2 Ser-680, MDM2 (murine double minute 2) ubiquitinates ACE2 Lys-788, and crosstalk between AMPK and MDM2 determines the ACE2 level.4 In the damaged lungs, levels of pAMPK (phospho-AMPK), pACE2 (phospho-ACE2), and ACE2 decreased but those of MDM2 increased (Figure [B], i). Furthermore, complementary increased and decreased phosphorylation of eNOS (endothelial NO synthase) Thr-494 and Ser-1176 indicated impaired eNOS activity. These changes of pACE2, ACE2, MDM2 expression, and AMPK activity in endothelium were recapitulated by in vitro experiments using pulmonary arterial ECs infected with Pseu-Spike which was rescued by treatment with N-acetyl-L-cysteine, a reactive oxygen species inhibitor (Figure [B], ii).
Translation: Compared to mock virus, Pseu-Spike altered signaling due to the ACE2 receptor, which is not surprising given that it’s been known for a year now that spike protein latches onto the ACE2 receptor in order to get SARS-CoV-2 into the cell. As a result, there was a lower level of ACE2 in the hamster lung tissue treated with Pseu-Spike, although looking at the Western blots in Figure 1B I am not particularly impressed by the magnitude of the decrease in protein level.
Also observed in the Pseu-Spike-treated hamster lung was decreased activity of eNOS, an enzyme that generates nitric oxide, as well as damage to the mitochondria, the “power plants” of the cell. The authors also did the same experiments in cell culture alone using pulmonary vascular endothelial cells (the cells the line the inside of the arteries in the lung), reporting that they recapitulated their findings, although they used spike protein at a rather high concentration (4 μg/ml). They also tested whether similar changes occurred in vascular endothelial cells genetically engineered to make a more stable and less stable version of ACE2. They did, although this is only suggestive, not slam dunk evidence, that it is the spike protein-induced degradation of ACE2 that results in these intracellular changes. The authors also reported that in pulmonary arteries isolated from the hamsters vasodilation induced by a drug called nitroprusside was not affected by Pseu-Spike, but the vasodilation caused by acetylcholine was impaired. Nitroprusside works by breaking down in the presence of oxyhemoglobin to produce, among other things, nitric oxide, while acetylcholine binds to specific protein receptors on the cell surface.
To be honest, I’ve never been a fan of papers this short (e.g., some Nature or Science papers, which can be even shorter than this) because I can never quite figure out what the authors did this is one of the rare cases of a paper that to me screams out for an online Supplemental Data and Supplemental Figures section, and I say this as someone who generally detests the trend in scientific publications to dump all sorts of data into supplemental sections.
Let’s, for the sake of argument, take the results at face value and assume that this study shows what the authors say it shows, namely that spike protein damages endothelium, “manifested by impaired mitochondrial function and eNOS activity”. and can cause oxidative stress that destabilizes the ACE2 receptor, leading to lower levels of the receptor. The authors themselves note that by decreasing the level of ACE2, spike protein could actually decrease the infectivity of SARs-CoV-2, given that the coronavirus needs to bind to ACE2 to get into cells, while speculating that the dysfunction of endothelial cells could result in endotheliitis, or inflammation of the endothelium that more than makes up for the decreased infectivity.
But here’s the kicker, taken right from the final paragraph of the paper:
Collectively, our results suggest that the S protein-exerted EC damage overrides the decreased virus infectivity. This conclusion suggests that vaccination-generated antibody and/or exogenous antibody against S protein not only protects the host from SARS-CoV-2 infectivity but also inhibits S protein imposed endothelial injury.
In other words, the vaccine could be protective not just against infection by SARS-CoV-2 but also against endothelial injury from the spike protein.
I just want to reiterate again that this is a contrived system. It’s far from a worthless system, as pseudovirus systems have value in studying the role of spike protein in the pathogenesis of COVID-19. However, given the crapton of pseudovirus used in this hamster model, I really question any relevance of this system to vaccine safety issues with respect to mRNA- or adenovirus-based vaccines that produce the spike protein as an antigen. Why? The mRNA or adenovirus from the vaccines does not distribute extensively given that it’s an intramuscular injection, and the spike protein is highly unlikely to attain concentrations in the circulation anywhere near the high levels produced by the model used in these experiments. Moreover, the spike protein from the vaccine is not attached in a crown-like array on a virus particle (or pseudovirus particle), but rather exists as naked single protein molecules, and, as has been described before, it’s unclear that in this form spike protein, compared to the “crown of spikes” that gives coronaviruses their name, is anywhere near as effective at causing these downstream effects in cells. Add to that the fact that mRNA, even the modified mRNA in the vaccine, doesn’t hang around very long and therefore doesn’t generate spike protein for very long. (Doubters should consider this: Why do the mRNA vaccines both require a second dose 3-4 weeks after the first dose if, as many antivaxxers claim, the vaccines crank out spike protein indefinitely?)
Indeed, one of the authors pointed out this very issue and took antivaxxers to task for misusing their study:
i’m going to give a full response asap. but quickly for the record:
1) the (relatively) small amount of spike protein produced by the mRNA vaccine would not be nearly enough to do any damage
2) i happily got the mRNA vaccine, FWIW
3) i encourage everyone to get it
&mdash Uri Manor (@manorlaboratory) May 2, 2021
very important: while the mRNA codes for spike protein, the transfected cells degrade it and only present small chunks via MHC-I on their surfaces. the amount of full length spike protein entering circulation must be *infinitesimal*. this video explains: https://t.co/H7NyBHoVtD
&mdash Uri Manor (@manorlaboratory) May 2, 2021
a couple prelim responses to anti-vaxxers misrepresenting these findings (here: https://t.co/qMhHyNyRR1). tldr: mRNA vaccine is waaaaay safer than COVID19 and everyone should get it – I did and everyone in my family did as well! Our paper just shows this disease really sucks. https://t.co/1t6SuUXZ5B
&mdash Uri Manor (@manorlaboratory) May 2, 2021
Since I first discovered this study, it’s just amused me how obvious it is that the antivaxxers citing this study have obviously not actually read the study itself, nor have they considered the background science and knowledge behind the study. They’ve just read the press release. What do you expect, though? They’re antivaxxers. This study by Uri Manor’s laboratory is interesting and potentially important because it begins to elucidate the role of the spike protein itself in the pathophysiology of SARS-CoV-2 infection and how the spike protein alone can cause damage, but it does not in any way suggest that spike protein made by a COVID-19 vaccine is in any way toxic at the concentrations it’s produced, much less that it’s in any way “shed” or that the “shed” spike protein can cause disease or miscarriages in the unvaccinated who encounter the vaccinated.
Which brings me to the last of the three studies, which was published late last week.
Previously, Kuakini Honolulu Heart Program researchers reported that occupational exposure to pesticides was significantly associated with total mortality. The current study examines occupational exposure to pesticides in relation to incident cardiovascular disease, defined as coronary heart disease or cerebrovascular accident.
Methods and Results
With the Occupational Safety Health Administration exposure scale used as an estimate of exposure, statistical analyses were performed on a cohort of 7557 Japanese‐American men from the Kuakini Honolulu Heart Program. Hazard ratios for cardiovascular disease incidence were calculated for various levels of pesticide exposure using Cox proportional hazards models. In the first 10 years of follow‐up, a positive association was observed between age‐adjusted cardiovascular disease incidence and high levels of pesticide exposure (hazard ratio=1.46, 95% CI =1.10‐1.95, P=0.009). This relationship remained significant after adjustment for other cardiovascular disease risk factors (hazard ratio=1.42, 95% CI =1.05‐1.92, P=0.021). No significant association for coronary heart disease or cerebrovascular accident incidence with pesticide exposure was observed when examined separately, possibly due to a smaller number of events.
These findings suggest that occupational exposure to pesticides may play a role in the development of cardiovascular diseases. The results are novel, as the association between occupational exposure to pesticides and cardiovascular disease incidence has not been examined previously in this unique cohort.
What Is New?
This is the longest longitudinal study of chronic occupational pesticide exposure and its association with cardiovascular diseases, taking into account epidemiologic risk factors for cardiovascular diseases.
High level of occupational pesticide exposure is associated with 10‐year incidence of cardiovascular diseases.
What Are the Clinical Implications?
Health care providers need to be aware of pesticide exposure occupational health risks, especially in the agricultural population.
Long‐ and short‐term chemical exposures, especially to pesticides, need to be documented in individual medical records.
Farm and agricultural workers need to wear personal protective equipment and have their health monitored for cardiovascular disease outcomes.
According to the World Health Organization, cardiovascular diseases (CVD) were the number 1 cause of death worldwide and accounted for 31% of all deaths annually. 1 Although there are many contributing causes to heart disease, pesticide exposure is associated with increased mortality and may exert some of its effects via the cardiovascular system. 2
Pesticides have been shown to be associated with CVD in other studies, especially in subjects wearing little or no proper personal protective equipment. For example, factory workers involved with phenoxy herbicides and chlorophenol production were found to have an increased incidence of circulatory diseases, including ischemic heart disease and diabetes mellitus. 3
Agrochemical products are associated with development of myocardial infarction, congestive heart failure, stroke, arrhythmia, and sudden death. 2 A study of chlorophenoxy and phenoxy pesticide manufacturing workers found that hypertension was associated with a positive family history but not occupational exposure. 4
According to the Hawaii Department of Agriculture in 1969, common pesticides in Hawaii consisted of several classes of organophosphates, organochlorines, insecticides, fumigants, and herbicides. 5 Although pesticides were used as chemical warfare agents during World War I and World War II, they were not used commercially until 1945. 6 Most of these chemicals have since been banned, such as chlordane, DDT, dieldrin, heptachlor, hexachlorobenzene, and toxaphene, as they are persistent organic pollutants. Pesticides, depending on their solubility, undergo degradation into different metabolites but may persist for decades. 7 The jobs that have been associated with pesticide exposure are either agricultural or industrial. These jobs include pesticide applicators, craftsmen, landscapers, forestry workers, factory workers, pesticide manufacturing workers, aircraft mechanics, jet fuel refinery workers, and agricultural workers.
In the Kuakini Honolulu Heart Program (HHP) longitudinal cohort, there have been multiple studies of occupational exposures and association with various diseases such as cancer 8 , 9 and Parkinson disease 5 however, CVD incidence in association with pesticide exposure has not been evaluated previously. One particularly interesting study was the assessment of occupational exposure to chemicals (pesticides, metals, and solvents) in relation to total mortality from circulatory diseases, respiratory diseases, and cancer by Charles et al. 9 The causes of death in this cohort were 28.3% from circulatory disease, 32.4% from cancer, 8% from respiratory disease, 13.1% from a combination of diabetes mellitus, digestive disorders, and other diseases, 3.9% from accidental deaths, and 14.4% from undetermined causes. 9 Death from respiratory diseases and all types of cancer were associated with all 3 occupational chemical types, whereas deaths from circulatory diseases were only associated with solvents and pesticides. The mortality analyses were broken down into 5‐year intervals. The 15‐year lag time was found to be the most relevant in relation to circulatory disease mortality from exposure to solvents and pesticides.
Most previous studies examining occupational chemical exposure and cerebrovascular accident (CVA), coronary heart disease (CHD), and CVD have looked at CVD mortality only. 9 , 10 The purpose of this analysis is to determine if there is an association between occupational exposure to pesticides and the incidence of CVD, CHD, and CVA. Our hypothesis is that occupational exposure to pesticides is a risk factor for incident CVD, CHD, and CVA. However, the mechanisms and biochemical pathways by which pesticides cause the development of these circulatory diseases are not yet fully understood.
Materials and Methods
Because of the sensitive nature of the data collected for this study, Health Insurance Portability and Accountability Act (HIPAA) regulations, and institutional review board approval, requests for limited access of the Kaukini Honolulu Heart Program data set may be possible for purposes of reproducing the results or replicating the procedures, with special requirements to address these confidentiality issues.
Study Design and Population
The Kuakini HHP was originally established in 1965 to study CVD in a cohort of middle‐aged Japanese‐American men living on the island of Oahu, Hawaii. The Kuakini HHP enrolled 8006 participants out of 11 000 possible candidates from a listing of World War II Selective Service records. 11 Participants were born between 1900 and 1919 either in Japan or Hawaii. Therefore, at the beginning of this study, the population consisted of either Japanese immigrants or second‐generation Japanese‐American men between the ages of 45 and 68 years. 5 , 9 , 10 , 12
Occupational data were collected by self‐report at the baseline exam (1965‐1968) and were available for 7994 individuals. Occupations were categorized according to the US Bureau of the Census definitions. This cohort has undergone multiple examinations and had surveillance for all mortality and some morbidity outcomes. Data on incident CVD were available through December 1999, for up to 34 years of follow‐up. All prevalent cases of CVD (CHD or CVA) at baseline were excluded, leaving an analytic sample of 7557 participants. The Institutional Review Board of Kuakini Medical Center approved this study, and participants or proxy informants gave written informed consent at each examination. These analyses were also approved by the Institutional Review Board of the University of Hawaii at Manoa (CHS# 23491).
Predictor Variables: Occupational Exposure
The Occupational Safety and Health Administration scale was created and coded by industrial hygienists at the National Institute of Occupational Safety and Health for permissible exposure limits in relation to chemical exposures and duration of primary and current jobs. The Occupational Safety and Health Administration scale was used to assess intensity level of exposure for each occupation reported in the Kuakini HHP cohort and is the same scale used in previous studies of this cohort. 5 , 8 , 9 , 13 Permissible exposure limits determine the maximum amount of chemical exposure a person can be exposed to over a time‐weighted average. The time‐weighted average is the average amount of exposure over a specific period, usually an 8‐hour workday or a 40‐hour work week. 13 Intensity scores for metals, pesticides, and solvents served as independent variables based on industry and agricultural occupational exposure variables and time variables (years worked and an individual's age during that job) and were used to measure total occupational chemical exposure. 13 Four categories were defined: no exposure (0), low exposure (1), medium exposure (2), and high exposure (3). According to Kashon and Burchfiel, 3 parameters were taken into account in identifying exposure to pesticides, metals, and solvents these were (1) if exposure of any kind occurred, (2) an estimate of the magnitude/duration of the exposure, and (3) the particular timing of the exposure. 13 Details about how the Occupational Safety and Health Administration scale was created have been previously described. 13
Outcome Variables: Incident CVD, CHD, and CVA
Longitudinal follow‐up for CHD and CVA incidence was based on a hospital surveillance system, review of death records, periodic examinations, and an autopsy study. Details of the surveillance methods have been described elsewhere. 14 The follow‐up for this report includes incident cases of CHD, CVA, and CVD (defined as either CHD or CVA), after the baseline examination (1965‐1968), through 1999, or a total follow‐up of up to 34 years.
The risk factors included age (in years), systolic blood pressure (SBP), diastolic blood pressure (DBP), smoking, total cholesterol (mg/dL), triglycerides (mg/dL), physical activity, alcohol intake (oz/mo), glucose (mg/dL), body mass index, and education (percentage who graduated from high school). These covariates were measured at examinations during different phases of the study, as reported by Charles et al. Level of education, smoking, and alcohol consumption were self‐reported. One of the main goals of the Kuakini HHP was to study risk factors for the development of CVD. Methods for the baseline examinations have been reported elsewhere. 15
The mean values and standard deviations of the covariates at baseline were compared according to disease status, that is, those who developed incident CVD and those who did not, using general linear models. Baseline covariates were also compared according to levels of exposure to pesticides (no exposure, low to moderate exposure, and high exposure) using general linear models. Rates of cardiovascular disease incidence were calculated per 1000 person‐years, for the first 10 years of follow‐up separately, and for the overall 34‐year follow‐up period, first without adjustment and then after adjustment for age.
Cox proportional hazard models were used to calculate hazard ratios for CVD incidence in the high‐exposure and low‐ and moderate‐exposure pesticide groups, using the no‐exposure group as reference and adjusting for baseline risk factors. Adjustments for risk factors were evaluated in various models. For example, SBP and body mass index were removed from the model to determine whether there were any effects mediated by these known risk factors. SBP (rather than SBP and DBP) was included as a covariate in the Cox models (to avoid problems with colinearity because SBP and DBP are often associated). All statistical analyses were conducted using SAS version 9.4 (SAS Institute Inc, Cary, NC).
Table 1 compares baseline CVD risk factors in participants who developed incident CVD over the follow‐up period with those who remained free of CVD. Those who developed incident CVD were significantly older (P=0.0038), and had higher levels of body mass index (P<0.0001), SBP (P<0.0001), DBP (P<0.0001), total cholesterol (P<0.0001), triglycerides (P<0.0001), nonfasting glucose (P<0.0001), and smoking pack‐years (P=0.0269). Those who developed incident CVD had significantly lower alcohol consumption (P=0.0004). There were no significant associations with the physical activity index (P=0.1389) or education (P=0.422).
Table 1. Baseline Cardiovascular Disease Risk Factors by Disease Status (Incident CVD), Kuakini Honolulu Heart Program
Values are means±SD. CVD indicates cardiovascular disease.
Table 2 compares baseline CVD risk factors in those with no exposure, low to moderate exposure, and high exposure to pesticides. Occupational exposure to pesticides at baseline was significantly associated with older age (P for trend<0.0001), higher physical activity index (P for trend<0.0001), and lower nonfasting triglycerides (P for trend 0.0063). There were significant inverse associations with alcohol intake (P for trend=0.0002) and education (P for trend<0.0001). Associations between pesticide groups and DBP were mixed, without a clear trend. No significant associations were observed for body mass index (P for trend=0.1717), SBP (P for trend=0.8243), total cholesterol (P for trend=0.5799), nonfasting glucose (P for trend=0.6308), or pack‐years smoking (P for trend=0.0962).
Table 2. Baseline CVD Risk Factors by Levels of Pesticide Exposure, Kuakini Honolulu Heart Program
CVD indicates cardiovascular disease.
Table 3 displays unadjusted and age‐adjusted incidence rates of CVD per 1000 person‐years follow‐up by levels of pesticide exposure (none, low‐moderate, and high), stratified for the first 10 years of follow‐up, and for the total follow‐up period of 34 years. The number of subjects in each group is shown. The highest CVD incidence rates observed during the 10‐ and 34‐year follow‐up periods were in the group with highest exposure to pesticides. It was interesting to note that there appeared to be a lower risk of incident CVD among those with low to moderate levels of exposure, compared to those with no exposure, but this protective effect was not statistically significant.
Table 3. Incidence Rates of Cardiovascular Disease by Pesticide Groups, Kuakini Honolulu Heart Program
Incidence rates per 1000 person‐y. CVD indicates cardiovascular disease.
Table 4 displays the Cox regression models for 10‐year CVD incidence, comparing those with high and low‐moderate levels of exposure to pesticides with those with no exposure (reference group). There was no significant increase in incident CVD in the low‐ to moderate‐exposure group. High levels of pesticide exposure were found to be significantly associated with incident CVD in all models except for the model adjusted only for age.
Table 4. Hazard Ratios From Cox Proportional Hazards Models and 95% CI for the First 10‐Year Follow‐Up Period, Kuakini Honolulu Heart Program
Risk factors include age, body mass index (BMI), systolic blood pressure (SBP), total cholesterol, nonfasting triglycerides, nonfasting glucose, physical activity index, pack‐years smoking, alcohol intake, percentage with high school education.
In addition, we also explored possible interaction effects between each of the variables in the Cox models, including CVD risk factor levels with pesticide levels. We did not find significant interaction effects (data not shown). Also, there were no significant associations for pesticide exposure with incident CVD over 34 years of follow‐up (data not shown).
Figure 1 is a forest plot of the data from Table 4 to display the results in a more visual way.
Figure 1. Cardiovascular disease hazard ratios from Cox proportional hazards models for the first 10 years of follow‐up and 95% CIs, Kuakini Honolulu Heart Program. Risk factors include age, body mass index ( BMI ), systolic blood pressure ( SBP ), total cholesterol, nonfasting triglycerides, nonfasting glucose, physical activity index, pack‐years smoking, alcohol intake, and percentage with high school education. Yellow squares represent hazard ratios with 95% CIs for low to moderate pesticide exposure. Green triangles represent hazard ratios with 95% CIs for high pesticide exposure.
Figure 2 shows Kaplan‐Meier curves for survival free of incident CVD over the follow‐up period of 34 years by the 3 pesticide exposure groups. In the first 10 years of follow‐up, the group with high exposure to pesticides had the highest incidence of cardiovascular diseases, followed by those with no exposure to pesticides (largest group), and then by the group with low‐moderate exposure. It appears that differentiation between the exposure groups was greatest at 10 years of follow‐up.
Figure 2. Kaplan‐Meier curves for survival free of incident cardiovascular disease for 3 pesticide‐exposure groups, Kuakini Honolulu Heart Program. X‐axis is exposure time (years). Y‐axis is survival free of incident cardiovascular disease.
It is important to note that we also separately examined the outcomes of incident CHD and CVA and did not find significant associations, probably due to the smaller number of outcomes with inadequate power to detect differences (data not shown).
In the current study a high level of pesticide exposure in the first 10 years of follow‐up was found to be significantly associated with CVD incidence after adjustment for all relevant risk factors. In this comprehensive investigation we did not find any association in follow‐up periods >10 years and up to 34 years after exposure. A possible explanation for this observation is that other risk factors associated with aging may mask the effects of toxic pesticide exposure later in life. A study of pesticide factory workers and sprayers of TCDD (tetrachlorodibenzo‐p‐dioxin) reported that the highest susceptibility for developing circulatory diseases occurs 10 to 19 years after exposure to pesticides. 3 According to Charles et al, the greatest correlation with chemical exposure (pesticides, metals, and solvents) and total mortality was found 15 years before death in the Kuakini HHP cohort. The Charles et al 9 study focused on all‐cause and cause‐specific mortality and did not explore CVD incidence.
The current study found that those in the high‐pesticide‐exposure group had a higher physical activity index than the other groups. This would be consistent with participants in this study, especially those in manual labor jobs, exhibiting a healthy worker effect due to higher levels of physical activity, which may lower the incidence of CVD overall, and this could have attenuated the effect of pesticides on CVD incidence.
We also found that CVD incidence was not associated with low to moderate levels of exposure to pesticides in unadjusted and adjusted models. In fact, our results found nonsignificant trends that suggest low to moderate levels of pesticide exposure may be protective for incident CVD. This could potentially be due to the hormesis principle, which argues that low‐dose exposures to some toxic agents may be protective in some individuals and may stimulate homeostasis of the organism. 15 It is thought that low‐dose exposure at nontoxic levels causes stimulation of protective enzymes, which provide enhanced protection against occasional exposure to higher, more toxic levels. 16 Examples of hormesis include nutrition, essential vitamins, exercise, sun exposure, calorie restriction, intermittent fasting, pharmaceutical agents, alcohol, and chemicals (basically anything that puts low amounts of stress on the system. 17 , 18 , 19 , 20 The benefits of hormesis are limited to the organism's biological plasticity and are thought to be an evolutionary advantage to how the organism's cells adapt to changes in their environment. 20
A specific example of the hormesis principle is the effect of moderate alcohol consumption and CVD. The plasma prooxidant activity appears to be due to ethanol metabolism, whereas the antioxidant activity may be due to the absorption of polyphenols in the beverage. 21 Many studies have shown a protective effect of moderate alcohol consumption, but alcohol becomes harmful when consumed in larger quantities. 18 , 20 , 21
In 1965, when the study began, proper personal protective equipment for the use of pesticides was not required. Typical routes of pesticide exposure would have been absorption, inhalation, and ingestion. In addition, different occupational exposures may have had a synergistic effect due to exposure to a combination of pesticide chemical classes. Pesticide exposure has previously been linked to development of Alzheimer disease, dementia, cancer, and Parkinson disease in the Kuakini HHP studies. 5 A study published in 2015 found an association among hypertension, pesticide exposure, and cognitive decline. 22 Previous studies have determined that plantation employees in Hawaii participating in the Kuakini HHP were exposed to organochlorines, organophosphates, and synthetic herbicides. 5 , 9 , 13 Agricultural work would not be the only occupation in which pesticide exposure could occur, as scientists developing agricultural chemicals and technicians in chemical companies would also have occupational chemical exposure.
Based on previous studies, pesticide exposures associated with the development of incident CVD and CHD have been attributed to organophosphates, organochlorines, and herbicides. 23 , 24 , 25 , 26 , 27 In previous agricultural studies, pesticide exposure was associated with an increase in hypertension, which is also associated with CVD and other diseases. 28 , 29 , 30 , 31 Polychlorinated dibenzodioxins and polychlorinated dibenzofurans were found to cause hypertension only in women but not in men. 28 PCBs (polychlorinated biphenyls) and chemicals similar to dioxin cause hypertension in men. 28 In addition, diazoxonase, used by mosquito sprayers, was found to be associated with increased rates of hypertension. 26 The current study adjusted for SBP at baseline to avoid confounding and also conducted analyses without adjusting for SBP to determine if it was a mediating factor and found no effect.
Hung et al 32 reported an association between long‐term effects of acute organophosphate poisoning and the development of CVD including arrhythmias, coronary artery disease, and congestive heart failure in middle‐aged men. They suggested that the underlying mechanism leading to CVD in younger people was the disruption in autonomic function due to the organophosphates’ effect on the neurotransmitter that controls cardiac muscles, inducing oxidative stress. 32 The acetylcholinesterase enzyme and its neurotransmitter aid in controlling the function of all muscles (skeletal, smooth, and cardiac). Pesticide interference with neurotransmitters is a reasonable explanation because many pesticides are neurotoxic. The Hung et al 32 study also reported that the association of organophosphate exposure with CVD was masked by other risk factors as the cohort aged. Individuals heavily exposed to organophosphates had permanent electrocardiographic changes after controls for age and smoking were taken into account. 25
The effects of TCDD exposure on serum lipoproteins were still found 20 years after chronic exposure to high dosages in farm workers in the Czech Republic, where exposure was shown to play a role in the development of atherosclerosis and high blood pressure. 33 High pesticide exposure affects cells in the liver, leading to oxidative stress and hyperlipidemia and ultimately to cardiovascular morbidity. 34 The parent compounds and their metabolites resulting from chronic or acute pesticide poisoning may linger in the body decades after exposure, as some pesticides, such as TCDD, have long half‐lives.
With respect to lipoprotein biomarkers, PCBs and organochlorine exposures have been found to be associated with an increased risk of CVD by reducing arylesterase activity of HDL. 35 PCB decreases the PON1 gene activity, which in turn impairs HDL function, thus affecting cholesterol production. 35 The PCBs also prevent the oxidization of low‐density lipoproteins.
Wafa et al 36 suggested that the inactivation of the PON1 gene causes a decrease in HDL production. Some of the functions of the PON1 gene include reducing oxidative stress, lipid metabolism, and production of HDL. The PON gene product also reduces inflammation and rids the body of pesticides. 32 , 36 , 37 , 38 , 39 Genetic polymorphisms of the PON1 gene affect production of metabolic enzymes, especially those that aid in the production of cholesterol and neurotransmitters. The PON genes code for enzymes related to both cholesterol production and the breakdown of neurotransmitters. The ability of the PON1 gene to rid the body of pesticides and metals is polymorphism dependent and has been identified in the Turkish population. 37 , 40 Some PON1 gene alleles are better than others at ridding the body of toxins, and other alleles make subjects more susceptible to developing coronary artery disease. Different populations carry different variants of the PON1, PON2, and PON3 genes. High pesticide exposures lead to cytogenetic effects in the PON genes. 39 The PON1 gene is associated with vascular diseases. 41 According to Costa et al, 41 the PON1 gene aids HDL via high‐affinity reabsorption to leave the liver with assistance from apolipoproteins and phospholipids. A study conducted in the Kuakini HHP cohort found that apolipoproteins predict CHD only for those with low concentrations of HDL. 42 Japanese people have polymorphisms that include PON1 584A>G and 172T>A. 43 To better understand susceptibility from occupational pesticide exposure, gene‐gene and gene‐environment interactions need to be further investigated. Agirbasli et al 37 suggest that diseases dealing with the circulatory system should assess multiple gene‐gene interactions and their cellular pathways and the environment‐gene impact.
The current study has some limitations. One limitation is that the specific pesticides that each participant was exposed to are not known. However, as previously mentioned, documentation by the Hawaii Department of Agriculture from 1969 lists organophosphates, organochlorines, insecticides, and herbicides as being commonly used in agricultural work at that time. 5 , 44 Another limitation is that the group with a moderate intensity of exposure to pesticides had a small sample size so it was combined with the low‐pesticide‐exposure group, which also contained a small number of subjects. Most participants were in the “no exposure” group. Participants exposed to pesticides were exposed to a wide range of chemical types and classes as well as to other potentially toxic agents. Future studies should look at the combination of both pesticide and solvent occupational exposures in relation to development of CVD. Those 2 chemical types were associated with higher mortality from CVD in a previous study of the same cohort. 9 Workers on the job could be potentially exposed to multiple chemicals every day depending on the type of labor and task involved. Another limitation of this study is that, although we were able to adjust for major CVD risk factors, we were unable to adjust for all possible risk factors. The project does not include many of the risk factors identified since the study started in 1965, when many other CVD risk factors were unknown. The data on pesticide exposure were based on self‐report, and this is always subject to memory bias: the exposure information was collected at the beginning of the study before the outcome of CVD occurred, so this would be a nondifferential misclassification bias that would bias toward the null. This study may also have limited generalizability because the study population included only men of Japanese ancestry.
Study strengths include a large sample size and a wealth of information from previous studies published from the same cohort. Another strength of this study is the fact that the cohort was limited to men because some pesticides affect men in a different way than women, and some do not affect women at all. 24 Another advantage is that our study population consisted of individuals from the same ethnic group. This is a highly homogeneous group and allows for fewer genetic influences.
Multiple risk factors contribute to the development of cardiovascular diseases, including chemical exposure to pesticides from occupational factors. Although the sample size for the high‐pesticide‐exposure group in our cohort was small compared to the unexposed group, high pesticide exposure was still independently associated with the risk of developing incident CVD. Employees can still have effects related to exposure to chemicals years after their exposure because the pesticides have a long half‐life. By investigating different lag times after exposure, we estimate that the maximum effect of exposure was seen within 10 years.
This study provides valuable insight into chemical occupational exposure and incident cardiovascular diseases and is consistent with the study by Hung et al 32 from Taiwan that suggests that acute high dosages of pesticides may contribute to the development of CVD.
Future studies of genetic polymorphisms of the PON1, ‐2, and ‐3 genes and of gene‐ environment interactions need to be further explored in our cohort, as well as others, to determine if there is an association between pesticide exposure and oxidative stress. Some polymorphisms of the PON1 gene have stronger associations with cardiovascular diseases than others consequently identification of the impacts and mechanisms of specific polymorphisms is needed.
The findings of this research provide insight into the harmful effects of pesticides on the cardiovascular system and confirm a positive association between high levels of pesticide exposure and CVD incidence. These data could be helpful in identifying groups of subjects, such as those involved in agriculture and the manufacturing of pesticides, who may be at higher risk of developing CVD. In addition, they highlight the importance of measures adopted by the National Institute of Occupational Safety and Health, such as protective gear to limit occupational exposure to pesticides, to reduce the increased risk of developing CVD and other diseases associated with pesticide exposure.
Sources of Funding
This study was supported by the National Institutes of Health (National Institute on Aging contract N01AG42149, grant 1R01AG1715501A1, grant U54MD007601, and grant U54MD007584). It was also supported by the National Heart, Lung, and Blood Institute contract N01HC05102, and a National Institute of Neurological Disorders and Stroke grant (1R01NS4126501), and by the National Institute for Occupational Safety and Health (Contract HELD0080060). The findings and conclusions in this article are those of the authors and do not necessarily represent the views of the federal government.
3 points. This corresponds to a >20% increased risk of mortality in that section of the SOFA score scale . A similar observation of increased EMR was observed when comparing SAVE scores at conversion to admission RESP scores (although the SAVE and RESP scores are not interchangeable, both scores consider “0 points” as an EMR of 50%, and a score >0 indicates a higher chance for survival and vice versa). Thus, we found that converted patients had a temporal trajectory of both increased SOFA score and EMR obtained from RESP and SAVE scores between admission and conversion. This suggests that temporal trajectories of these scores, as well as daily echocardiography, could be used for early identification of patients who require conversion. Thereby avoiding an emergent conversion with fully developed circulatory shock or cardiac arrest.
To understand antiseptics , one should first understand the root of the word. Consider the word “ sepsis,” which is a medical term meaning there are microorganisms alive in the blood and/or the tissues of the body. If a person is septic, then he is in big trouble because the infection is often global, meaning it is throughout the body, having been carried by the circulatory system. Sepsis must be treated very quickly and aggressively. “Aseptic” simply means “not septic.” It is sometimes used as an adjective to imply the prevention of sepsis. Consider the physician who is about to perform a procedure. The doctor will wash his hands very well. He may place a drape over parts of the patient that are near the area to be worked on. If the procedure is a surgery, the doctor will cover his hair and mouth and wear a gown that has been sterilized. These measures are known as aseptic technique. Similarly, when biotechnologists work with cells, we do so in a biological safety cabinet because it prevents room air from delivering dust, lint, spores, or what-have-you into the cell medium with which we are working. In addition, a person performing cell culture in a biosafety cabinet will not move his hands or arms over what is being worked upon, including any open containers, because particles can fall off of the lab coat, the skin, or possibly the gloves. The prevention of sepsis—the prevention of bacteria growing in our cell cultures, in our mice, or in our patients—is known as aseptic technique. Antiseptics are chemicals applied to body surfaces to destroy or inhibit the growth of vegetative pathogens. Their use is similar to disinfecting the skin. An example of sanitizing your skin would be washing your hands under a faucet using regular hand soap. You would be removing a great deal of bacteria. The use of an antiseptic would be different—perhaps using a hand soap with triclosan or swabbing the skin with an alcohol. Disinfectants and antiseptics are different. Disinfectants are used on inanimate surfaces, and antiseptics are for body surfaces like your skin. Disinfectants can potentially be harsher than antiseptics because one does not have to worry about the preservation of living tissue.
To extend our discussion, what would be the result of sterilizing your finger? Killing every cell in your finger! Your cells are microorganisms too, so to sterilize any part of your body would essentially mean to kill it.
Hydrogen peroxide is a very effective antimicrobial. In fact, what you buy from the store—3%—is very effective, killing a broad spectrum of microbes within 10-15 s. It is used as both a disinfectant and an antiseptic. However, it is not the best agent to put onto a healing wound because it can damage your own cells. Hydrogen peroxide works by making hydroxyl oxygen radicals, which can oxidize DNA, RNA, proteins, and membrane lipids. H2O2 will serve to help clean a fresh wound by killing microbes. When you first get an open wound, you should clean out any debris, which includes dead cells, tissue, dirt, and what-have-you. One could wash the wound with hydrogen peroxide. However, after the healing process begins, hydrogen peroxide will take away the body’s work in wound healing. At the end of the day, you may have grown fresh granulation tissue to cover the wound. You wouldn’t want to strip that away by killing those cells. The healing process is complex, and what might work well on day 0 might not be the best agent on day 2.