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Trends in Analytical Chemistry 169 (2023) 117307
Available online 4 October 2023
0165-9936/© 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Micro(nano)plastics: A review on their interactions with pharmaceuticals
and pesticides
M. Barreto
a
,
*
, I. Lopes
b
, M. Oliveira
b
a
Department of Biology, University of Aveiro, 3810-193, Aveiro, Portugal
b
Centre for Environmental and Marine Studies (CESAM), Department of Biology, University of Aveiro, 3810-193, Aveiro, Portugal
ARTICLE INFO
Keywords:
Micro(nano)plastics
Pharmaceuticals
Pesticides
Co-exposure
Interactions
Research needs
Aquatic organisms
ABSTRACT
This review provides an overview of the current knowledge addressing the interactions between micro(nano)
plastics (MNPs) and pharmaceuticals or pesticides, highlights the main ndings, and outlines research per-
spectives for future investigations. The available studies demonstrated that MNPs can act as pollutant carriers.
The reviewed literature reveals that MNPs inuence the toxicity of pharmaceuticals and pesticides in various
environmental compartments, modulating the toxicity of pharmaceuticals and pesticides, either through
antagonistic or synergistic interactions. MNPs have been shown to mostly confer protective effects against the
toxicity of antibiotics, while exacerbating the toxic effects of certain pesticides. To ensure a more comprehensive
understanding of the interactions between MNPs and pharmaceuticals/pesticides, future research should focus
on several key aspects that include more environmentally relevant scenarios (e.g., concentrations, long-term
exposures), elucidation of the underlying mechanisms of action at molecular and cellular levels,addressing ef-
fects on different species and also considering climate change scenarios.
1. Introduction
Plastics have, since the beginning of its industrial production, been
playing a transformative role in modern society. It is hard to imagine life
without plastics that, due to their shapeability, resistance and low cost,
play a key role in human daily routines as well as in industry [1]. The
production of plastics has seen a signicant rise in recent decades
reaching, in 2021, a global production of 390.70 million tonnes, with
European Union production reaching 29.5 million tonnes [2]. However,
its widespread use has resulted in the generation and environmental
release of a considerable amount of plastic waste with a signicant
impact on ecosystems and potential threat to wildlife.
Although there is a considerable lack of information regarding the
levels of plastic particles found in the environment, estimates of 171
trillion plastic particles adrift in the ocean have been recently presented
[3]. Therefore, plastics are dened as ubiquitous contaminants of
emerging concern due to their persistence in the environment, with
reported bioaccumulation and ability to induce pernicious effects on
organisms [4]. The fate of plastics in the environment is still not well
understood. Nevertheless, under natural conditions, plastic waste is
expected to undergo fragmentation (break down process of large
polymer chains into smaller, but still polymeric fragments) and degra-
dation (chemical transformation, changing its chemical properties),
giving rise to a novel environmental concern – the emergence of
microplastics (plastic particles possessing at least one dimension be-
tween 1 mm and 1000 nm) and nanoplastics (plastic particles smaller
than 1000 nm) [5,6]. There is, however, limited information about the
behaviour of micro(nano)plastics (MNPs) in environmental scenarios,
with a growing research to allow behavioural modelling of MNPs,
especially in aquatic matrices [7]. Nonetheless, predicting the fate of
these particles is challenging, even when their properties are known, as
environmental characteristics of the ecosystems can play a key role in
their environmental fate (e.g., biofouling and agglomeration with
organic matter) [8].
There are numerous reports on the toxicity of MNPs with studies
examining a wide range of endpoints, from molecular to behavioural,
addressing among others, genotoxicity [9–11], oxidative stress [12–15],
neurotransmission [12,16,17], effects on development and reproduction
[18–20], feeding [21,22], predatory performance and efciency [10,23,
24].
MNPs are, however, not absent of interactions with other environ-
mental variables such as contaminants [(e.g., metals [25,26],
* Corresponding author.
E-mail address: marcio.barreto@ua.pt (M. Barreto).
Contents lists available at ScienceDirect
Trends in Analytical Chemistry
journal homepage: www.elsevier.com/locate/trac
https://doi.org/10.1016/j.trac.2023.117307
Received 31 May 2023; Received in revised form 14 September 2023; Accepted 19 September 2023
Trends in Analytical Chemistry 169 (2023) 117307
2
nanomaterials [27,28], pharmaceuticals and personal care products
[29], pesticides [30], hydrophobic pollutants [31]]. MNPs may act as
potential contaminant carriers and promote their incorporation by
biota. This ability often referred as Trojan horse effect, is associated with
sorption events, namely adsorption, where the molecules stay on the
interface between the uid and the solid phases [32,33].
Pharmaceuticals are among the different environmental contami-
nants that may interact with MNPs. These substances contribute to
considerable improvements in the quality of life and expectancy of
modern society. However, the inefciencies of wastewater treatment
plants to manage pharmaceuticals and the active metabolites released
by patients (e.g., through urine), as well as their direct disposal in the
environment, promote their environmental presence [34]. Pesticides are
another important class of environmental contaminants, with known
biological activity. Synthetic or of biological origin, pesticides are
designed to control or eliminate pests that can harm crops, animals, and
humans. They play a signicant role in modern agriculture improving
crop yield, food safety through reduction of possible contamination by
organisms that can cause foodborne illnesses and generate economic
benets promoting increases in agricultural productivity. However,
after application, pesticides can be transported through different pro-
cesses (e.g., runoff, lixiviation, and inltration), reaching surface and
underground waters, where they may pose a great risk to non-target
aquatic organisms [35].
Based on the importance of plastics in today’s society, their ubiqui-
tous distribution in the environment, increasing reports of negative ef-
fects on biota (depending on the size, shape, and polymer type), as well
as the ability of MNPs to modulate the effects of other environmental
contaminants, the number of studies has been increasing in the recent
years. Nevertheless, in an attempt to increase the relevance of the per-
formed studies and to facilitate a better understanding of the risks
associated with the presence of these particles in the environment, it
becomes highly necessary to summarize what is already known about
the interaction with environmental contaminants and what must still be
studied. Therefore, the main objective of this review was to summarize
the available peer-reviewed information about the interaction between
MNPs and pharmaceuticals or pesticides in terms of biological effects to
aquatic organisms, analysing methodological approaches, particle
characterization methods, and identify knowledge gaps in this subject.
2. Methods
In December 2022, a literature search was performed on Scopus
database to retrieve studies addressing the effects of MNPs combined
with pharmaceuticals or pesticides. The literature search was performed
using a combination of words associated with Boolean operators. The
combinations used were: microplastic* AND pharmaceutical* AND ef-
fect NOT soil; microplastic* AND pesticide* AND effect NOT soil;
nanoplastic* AND pharmaceutical AND effect NOT soil; nanoplastic*
AND pesticide* AND effect NOT soil. The combinations were employed
in an all-parameters search to minimize loss of information. Out of 4353
candidate publications analysed, 52 were kept for further analysis after
the titles and abstracts of all the candidate publications were read and
screened for their relevance concerning the research topic of this review,
i.e., the toxicity of pharmaceuticals or pesticides in a mixture with
MNPs, any candidate not concerning toxic effects, as well as in vitro
studies were not considered. The screened publications were summa-
rized in Table A.1-4, retrieving the following criteria for MNPs: (i) type
of polymers tested; (ii) shape and size; (iii) concentrations tested. The
following criteria were used for both pharmaceuticals and pesticides: (i)
pharmaceutical or pesticides classes; (ii) concentrations tested; (iii)
biological model used and (iv) ecotoxicological effects observed in
mixture with MNPs.
In this research, MNPs polymers were classied based on the parent
polymer reported in the literature. These classications included poly-
ethylene (PE), polystyrene (PS), polyvinylchloride (PVC), polylactic acid
(PLA), polyethylene terephthalate (PET), aminoplasts (AP) and not
specied (N/S). PE polymers were grouped in high and low-density PE,
and PS classication included functionalized polymers. Based on size,
particles were classied as microplastics, when having at least one
dimension between 1 mm and 1000 nm, and nanoplastics smaller than
1000 nm (although some authors consider nanoplastics when having at
least one dimension smaller than 100 nm) [36,37].
The pharmaceutical classes presented in this study were based on
their pharmacological effects [38]. Thus, this ranking considered anti-
biotics, non-steroid anti-inammatory drugs (NSAIDs), antidiabetics,
antivirals, anxiolytics, anticonvulsants, antihypertensives, hypolipemic
drugs, contraceptives, antiarrhythmics, antidepressants, cytostatic
drugs, and active metabolites of the aforementioned classes. On the
other hand, pesticides were classied based on their chemical structure
[39–41] and presented as organophosphate pesticides, organochlorine
pesticides, carbamate pesticides, neonicotinoid insecticides, pyrethroid
insecticides, macrocyclic lactone derivate insecticides, triazole fungi-
cides, bipyridyl herbicides and phenylurea class herbicides. The infor-
mation retrieved included organisms from the following phylum:
Arthropoda, Cyanobacteria, Chordata, Chlorophyta, Mollusca,
Proteobacteria.
The ecotoxicological effects were condensed into categories such as
mortality, reproduction, genotoxicity, neurotoxicity, oxidative stress
and damage, behaviour, histological effects, microbiome dysbiosis, and
endocrine disruption. For a better understanding of the interaction be-
tween MNPs and pharmaceuticals or pesticides, effects of individual and
combined effects were analysed, and the interactions were, whenever
possible, categorized as additive (effects are the sum of the effects of
each individual agent in the combination), antagonism (effects corre-
spond to a decrease in the toxicity of one or both chemicals), synergism
(one component enhances the toxicity of the other), potentiation (a non-
toxic component enhances the toxicity of another) or no interaction.
The information in each article was summarized as follows: each
article may include one or more studies, with a study being dened as a
series of observations/measurements of a single group of organisms,
polymer type, shape, size, pharmaceutical or pesticide. Accordingly, the
number of studies generated by an article was based on the number of
elements studied. For example, if an article examined the ecotoxico-
logical effects of the interaction between PS-MPs and sertraline in sh
and microalgae, two studies were considered. Similarly, if an article
examined the ecotoxicological effects of the interaction between both
PS-MPs and NPs and sertraline in sh and microalgae, four studies were
considered. Based on these criteria, a total of 67 studies could be iden-
tied within the 52 peer-reviewed articles.
3. Results and discussion
3.1. Polymer types, shapes, and sizes
PS was the most tested polymer type (64% of the studies), followed
by PVC and PE (15% and 13%, respectively) (Fig. 1). However, PS and
PS-expandable only accounted for a small fraction (5.3%) of the total
plastic produced in 2021. Plastic polymers such as PP (19.3%), PE-LD,
-LLD (14.4%), PE-HD, -MD (12.5%), PET (6.2%), and polyurethane
(5.5%), that according to PlasticEurope’s 2022 report [2], had in 2021
higher global production levels than PS, are still underrepresented in the
selected studies. Biopolymers and co-polymers were almost absent, with
a single study, represented by PLA (1.49%). Although currently bio-
plastics represent a small fraction of the worldwide plastic production
(1.5%), it is in an increasing trend due to the consumer’s demand for
more environmentally friendly and biodegradable alternatives to con-
ventional plastic, as well as the European Union’s efforts to address the
problem of petroleum-based plastics consumption, by promoting a cir-
cular economy and replacing conventional plastics for bioplastics [42,
43]. However, despite the promising nature of these materials, it has
been reported that some of these bioplastics do not degrade, either in
M. Barreto et al.
Trends in Analytical Chemistry 169 (2023) 117307
3
industrial or natural environments. Additionally, MNPs of these poly-
mers may be as toxic as conventional plastics, highlighting the need for
an assessment of the interaction between pharmaceuticals and pesti-
cides also accounting for bioplastics MNPs [44–47].
An analysis of the MPs tested, in terms of shapes, revealed that
spheres were the most tested shape (38.81%), but only in studies with PS
particles, not being commonly used in studies with other polymers. A
similar proportion of studies did not specify the shapes tested. Frag-
ments were the second most tested shape (10.45%), followed by beads
(10.45%), and squares (1.49%) (Fig. 1).
According, to de S´
a et al. [48] MPs collected from eld organisms
mostly comprise bres and fragments (23% and 21% of the studies
summarized, respectively), followed by spheres (11%), lms (8%), and
pellets (4%). This is consistent with reports that identied bres as one
of the most prevalent shapes in both fresh and seawater on a global scale
[49–53]. The performed literature review reveals a knowledge gap
regarding bres, as no reports on bres were found and few reports are
available on fragment particles.
There is a lack of environmental data regarding shape and size of
NPs, that may be associated with technical challenges regarding sam-
pling, extraction, quantication, and characterization of NPs in biolog-
ical samples. Ongoing efforts are focused on optimizing existing
techniques such as nano-Fourier-transform infrared spectroscopy,
Raman spectroscopy using optical tweezers, and tip-enhanced Raman
spectroscopy or developing novel techniques that improve the efciency
of separating, visualizing, and characterizing NPs in environmental
samples [54,55]. Thus, we proceeded to compare our shape and size
ndings with available data on NPs exposures in laboratory assays.
Our analysis of the tested NPs shapes revealed that spherical shapes
were the most prevalent (53.85%), followed by N/S shapes (38.46%)
and squares (7.69%). Publications investigating the effects of laboratory
synthesized NPs exposure have mainly used spherical particles [9,
56–61]. Due to the higher difculty of obtaining NPs resulting from the
degradation of larger particles, with acceptable polydispersity rates that
allow studies of size-specic effects, researchers have been using mon-
odispersed primary NPs or synthesizing their own particles using pub-
lished protocols. However, if we extrapolate what is known about MPs to
NPs, we might hypothesize that spherical shapes are not the most
ecologically relevant shapes to use in ecotoxicological assays, assuming
that most NPs in the environment result from the degradation of MPs.
The obtained data regarding particle sizes are presented in Fig. 2.
Most MPs particles studied were in a size range between 1 and 50
μ
m
(Fig. 2A), while for NPs particles (Fig. 2B) a tendency towards smaller
particles (15–100 nm) and medium-sized particles (500 nm) was
reported.
The results obtained in our literature search are not in agreement
with some available reviews (e.g., [62]), that summarized the sizes of
particles in biological samples in the middle and upper limits of the
micrometric range, with the most abundant sizes ranging between 500
μ
m and over 5 mm. In accordance, de S´
a et al. [48] reviewed that the
most reported sizes of MPs collected from eld animals were in the size
ranges of 800–1600
μ
m and 400–800
μ
m (12% of all studies for both).
However, the same authors also stated limited information in studies
with MPs size range inferior to 50
μ
m, likely related to a limitation in
quantication and characterization techniques. Based on our ndings, a
notable research gap concerning the evaluation of the potential in-
teractions between pharmaceuticals or pesticides and medium-sized
microplastic particles (100–500
μ
m) can be highlighted.
NPs particle size (Fig. 2B) were compared with NPs used in ecotox-
icological assays under laboratory conditions. The ndings of this recent
literature review are in agreement with Gong et al. [63] that reviewed
over 100 studies on the effects of NPs exposure on various organisms.
The authors found that more than half of the studies used NPs in the size
range of 50–100 nm. However, this distribution may be inuenced by
different size range denitions for NPs, such as the range between 1 and
100 nm, which is commonly used for nanomaterials [64]. Nevertheless,
the need for studies using a broader range of sizes is evident, as
demonstrated by our ndings of an absence of studies with NPs between
150-450 and 650–950 nm.
3.1.1. Techniques used for characterization of MNPs
The number of works studying MNPs has been increasing rapidly
during the last years, especially concerning the effects of nanoplastics,
often primary particles purchased or synthesized through replication of
validated protocols both by top-down or bottom-up synthesis. The
Fig. 1. Shapes used in the available studies addressing the combined effects of
micro(nano)plastics and pharmaceuticals or pesticides, per polymer. Each col-
umn presents the total number of studies for each polymer and fractioned by
shape representativity. Plastic types enumerated include PS - Polystyrene; PVC -
Polyvinylchloride; PE - Polyethylene; PET - Polyethylene terephthalate; AP -
Aminoplasts; PLA - Polylactic acid. N/S – Not specied.
Fig. 2. Size distribution of particles used in studies addressing the combined
effects of micro(nano)plastics and pharmaceuticals or pesticides. A) Micro-
plastics size range distribution B) nanoplastics size distribution. The columns
represent the absolute frequency for each bin.
M. Barreto et al.
Trends in Analytical Chemistry 169 (2023) 117307
4
growing concern on the toxicity of MNPs, highlighted the need for
validated guidelines for test material quality control. In an attempt to
address this issue, Kokalj et al. [65] merged existing quality criteria
guidelines for nanomaterials (GUIDEnano and DaNa criteria) and pro-
posed new nanoplastics-specic criteria to assess different parameters
on available MNPs scientic papers. The authors found that particle
characterization-related criteria were often not fullled (e.g.,
morphology, surface charge, crystallinity, size) in the available studies.
To contribute to this effort, we summarized the particle
characterization-related information used in the reviewed scientic
papers (Table A.5).
Our review found that the absence of information regarding particle
characterization was more evident in studies with MPs (34.21%). For
morphological characterization of MPs (e.g., shape and size) the most
applied technique was electron microscopy, such as transmission elec-
tron microscopy (TEM) and scanning electron microscopy (SEM),
whereas to assess chemical composition, Fourier transformed infrared
spectrometry (FTIR) and variations (e.g., Attenuated reection- FTIR),
and Raman spectroscopy were the most applied techniques. Zeta po-
tential is considered a crucial parameter to assess particle stability in
suspension. However, for MPs it was only assessed by 18.42% of the
studies and the only technique applied was electrophoretic light scat-
tering (ELS). Crystal structure, that provides information on the crys-
tallinity, was assessed in a single study, resorting to x-ray diffraction
(XRD).
NPs studies presented a more complete particle characterization,
with only four studies lacking any type of information. Morphology was
assessed with electron microscopy, but also through dynamic light
scattering (DLS) (to determine the hydrodynamic size of the particles in
suspension). However, chemical composition was only assessed in a
single study, but surface charge was assessed in a signicant proportion
of the studies.
MNPs can behave differently depending on the physicochemical
properties of the surrounding environment/test media. Hence, to allow a
better understanding of the risks posed by particles it is crucial to
characterize particles in the different media used in the assays, and at
different time points (e.g., beginning and end of the assay). The
assessment of the hydrodynamic size and surface charge of the particles
in the exposure media were more prevalent for NPs, but only four pre-
sented results at different time points. The development of harmonized
frameworks for the evaluation of the quality of MNPs characterization
should thus be a priority.
3.2. Ecotoxicological research on the effects of combined exposures to
MNPs and pharmaceuticals or pesticides
3.2.1. Organisms tested
It is important to note that toxic effects may differ greatly between
freshwater and seawater organisms and taxonomic groups, due to their
physiological differences.
The studies addressing the combined effects of MNPs with pharma-
ceuticals or pesticides in freshwater compartments rely highly on model
species. Most studies (40.30%) involved sh species, and approximately
half of those (42.86%) used Danio rerio as model species. Small crusta-
ceans, which represent the second most used group of organisms, were
used in 8.96% of the studies, with Daphnia magna being the most used
organism (66.66%).
In assays addressing the marine environment, molluscs and bacteria
were the most representative group of organisms (14.93% and 5.97%,
respectively). Molluscs were mostly represented by two species, Tegil-
larca granosa (50%) and Mytilus galloprovincialis (30%), whereas assays
with bacteria were performed only with organisms from the genus
Shewanella spp. (Fig. 3).
Overall, the data analysis reveals that there are classes of organisms
underrepresented such as insects with aquatic larvae forms, crustaceans,
cyanobacteria, and microalgae. However, there is a lack of
ecotoxicological data for other relevant taxa, such as amphibians, roti-
fers, porifera, cnidarians, among others.
3.2.2. Tested pharmaceuticals and pesticides
A total of 43 studies with MNPs and pharmaceuticals and 24 studies
with MNPs and pesticides were retrieved in the literature search. A
prevalence for MNPs mixtures with antibiotics (48.84%), NSAIDs
(9.30%), and antidepressants (9.30%) is depicted in Fig. 4. Some
pharmaceuticals such as antidepressants, antidiabetics, antiarrhythmics,
antihypertensives, antivirals, anxiolytics, and contraceptives, were only
tested in mixtures with MPs, whereas cytostatic drugs were only tested
in mixtures with NPs.
Concerning antibiotics, the most prevalent class of pharmaceuticals
studied, a variety of antibiotic classes such as uoroquinolones (mainly
represented by ciprooxacin), macrolides, sulphonamides, tetracycline
family, β-lactams, and amphenicols were tested.
NSAIDs were only represented by ibuprofen enantiomers molecules
(e.g., R-ibuprofen; S-ibuprofen; rac-ibuprofen), and antidepressants
were represented by venlafaxine and its active metabolite, O-desme-
thylvenlafaxine, both with its respective enantiomers. In general, be-
sides antibiotics, the pharmaceutical retrieved classes lacked
representativity both in terms of number of articles and pharmaceuticals
diversity within classes. This information highlights the need for further
investigation into the interaction of MNPs with pharmaceutical com-
pounds. According to Organisation for Economic Co-operation and
Development (OECD) [66], member countries have witnessed a signif-
icant increase in the consumption of various pharmaceutical classes
between 2000 and 2019. For instance, the consumption of antihyper-
tensive drugs increased by 65%, while lipid modifying agents (e.g.,
cholesterol-lowering agents) consumption increased four times. The use
of antidiabetics and antidepressant drugs also increased considerably,
doubling over the survey period. Nonetheless, these pharmaceutical
classes are underrepresented in the retrieved studies, supporting the
need for more studies that should consider their toxicity in mixtures with
Fig. 3. Organisms tested in the studies addressing the combined effects of
micro(nano)plastics and pharmaceuticals or pesticides per environment type.
Each bar represents the relative abundance of each group of organisms.
Fig. 4. Representativity of studies addressing pharmaceutical classes in
mixture with micro(nano)plastics. Each bar represents the relative abundance
of each class of pharmaceuticals.
M. Barreto et al.
Trends in Analytical Chemistry 169 (2023) 117307
5
a wider variety of MNPs.
It would also be important to assess the toxicity of mixtures with
different pharmaceuticals within the same class since they can produce
different toxicity effects. For example, Henry et al. [67] assessed the
toxicity of ve serotonin reuptake inhibitors, a class of antidepressants,
and veried that within the same class, pharmaceuticals induced 50% of
mortality in Ceriodaphnia dubia in concentrations from 0.12 (sertraline)
and 3.90 (citalopram) mg L
−1
.
MNPs were predominantly tested in mixtures with organophosphate
pesticides (49.99%), followed by pyrethroid insecticides (12.50%),
neonicotinoid insecticides (8.33%), and carbamate pesticides (8.33%)
(Fig. 5). Studies testing the interaction of pesticides and NPs are limited,
with only three studies, thus highlighting a research gap that must be
addressed. Organophosphate pesticides were highly represented by
chlorpyrifos (66.66%) and glyphosate (16.66%), both widely used in
agriculture systems. Pyrethroid insecticides were the second most tested
class. However, compared to organophosphate pesticides, they were
underrepresented and mainly represented by deltamethrin (75%) and
esfenvalerate (25%). Although neonicotinoid insecticides are among the
most widely used insecticide classes worldwide, they were also under-
represented and only represented by imidacloprid.
According to Food Administration and Organization (FAO) pesticide
use database [68], the use of pesticides has decreased in recent years.
This reported decrease may be associated with the COVID-19 pandemic.
Fungicide use has been increasing but they were generally underrepre-
sented in the retrieved studies, with a single representation of the tri-
azole family. Thus, it becomes highly relevant to evaluate the combined
effects of MNPs with other fungicide families, such as strobilurins and
dithiocarmabates. It should be highlighted that the database referring to
pesticide use are limited to the year 2020, which may limit under-
standing of the environmental relevance of pesticide classes tested in the
selected articles and those widely used in agriculture practices
worldwide.
3.2.3. Biological effects resulting from MNPs interaction with
pharmaceuticals and pesticides
The assessment of the ecological impact resulting from the combined
exposure to pharmaceuticals and pesticides is highly important due to
the notable adsorption patterns observed. The reviewed studies, pre-
sented in Table A.1-2, suggest a higher trend for an antagonistic inter-
action, wherein MNPs conferred protective effects against the toxicity of
pharmaceuticals. MNPs consistently demonstrated an overall protective
effect against the toxicity of antibiotics (the most tested pharmaceutical
class), an effect found in nearly all examined studies. Remarkably, this
antagonistic interaction was observed regardless of the polymer type,
size, or specic antibiotic. For instance, the toxicity of ciprooxacin
towards the seawater bacterium Shewanella spp. was consistently
modulated through antagonism by MPs of four distinct polymers (PLA,
PE, PS, and PVC). These polymers exhibited ameliorative effects in terms
of phosphorus removal inhibition and oxidative stress levels, with the
following order of effectiveness: PS >PLA >PE >PVC [69]. Liu et al.
[70] reported that PS-MPs can alter the toxicity of roxithromycin to the
small crustacean D. magna under chronic exposure, with protective ef-
fects on the maternal generation. However, toxic effects were found in
the rst offspring, while organisms exposed to roxithromycin alone
managed to recover to control levels. Overall, these ndings emphasize
the long-lasting nature of the interaction between MPs and antibiotics,
as well as the potential substantial ecological implications, including
population declines. This interaction was also reported in higher trophic
levels, such as sh and molluscs both in sea and freshwater, mainly for
PS MNPs. For example, PS-MPs had an antagonistic effect on the toxicity
of sulfamethoxazole towards the freshwater sh Oreachromis niloticus,
lowering the oxidative stress and damage caused by the antibiotic [71].
A similar interaction was found between ciprooxacin and PS-MPs, with
MPs mitigating the effects of the antibiotic on acetylcholinesterase ac-
tivity, oxidative stress and damage, and histological damage on the
freshwater mollusc Corbicula uminea [72]. MNPs were also reported to
modulate the toxicity of antibiotics towards seawater sh. For instance,
the presence of PS-NPs had a protective effect against sulfamethazine
effects on the gut microbiome and transcription of oxidative
stress-related genes, in the estuarine sh Oryzias melastigma [73]. On the
other hand, Zhou et al. [74,75] reported a clear synergetic interaction of
two veterinary antibiotics, oxytetracycline and orfenicol, with PS-NPs
towards the immune system of the mollusc Tegillarca granosa, with ef-
fects on total haemocyte count, oxidative stress and damage, upregu-
lation of genes related to antioxidant enzymes and phase two
biotransformation enzymes, genes related to immune system (e.g., ikk
α
,
nfkb and mapk) and apoptosis-related genes (e.g., caspase3). These were
the only studies reporting synergism of MNPs in a mixture with antibi-
otics. Thus, two hypothesis may, in general, explain the antagonism and
synergism effects with different antibiotics: 1) The most tested antibi-
otics are slightly hydrophobic, which potentiates the interaction with
MNPs particles through sorption events and consequently may decrease
the bioavailability of the antibiotics in the medium promoting protective
effects against their toxicity; on the other hand MNPs can promote the
entrance of antibiotics but these may not properly desorb from MNPs,
presenting lower toxicity effects [76,77]. 2) More hydrophilic antibi-
otics, which is the case of oxytetracycline and orfenicol, would likely
be more bioavailable to exert effects in conjunction with MNPs.
On the ip side, the information presented in Table A.3-4 indicates a
potential overall synergism, with MNPs increasing the toxic effects of
pesticides. The primary producer Isochrysis galbana, however, seems
more tolerant to the combined effects of chlorpyrifos and PE-MPs, with
MPs showing a potential protective effect against the pesticide-induced
growth inhibition [78]. The combined effects seem to increase in pri-
mary and secondary consumers, as Felten et al. [79] reported an in-
crease in D. magna mortality and a decrease in the number and quality of
broods when deltamethrin was combined with PE-MPs. On the other
hand, Horton et al. [80] reported no interaction in terms of effects on the
same organism between deltamethrin and PS-MPs, suggesting a possible
tendency of deltamethrin to interact with PE particles. This lack of
interaction was not observed for imidacloprid, reported to reduce
offspring number of Ceriodaphia dubia in mixture with PS-MPs. In sh,
several studies reported synergism in terms of the effects of MNPs and
pesticides. For instance, the presence of PE-MPs aggravated the effects of
glyphosate in terms gut microbiome dysbiosis and histopathological
effects towards Cyprinus carpio [81], while PS-NPs potentiated the
malformation rate of 1,1-Dichloro-2,2-Bis(4-Chlorophenyl)ethylene
(DDE) towards D. rerio [30]. Although knowledge regarding the
adsorption of pesticides to MNPs is limited, the adsorption rate into
PE-MPs can be correlated to the hydrophobicity of the pesticides [82,
83], which may explain the synergistic effect of PE-MPs with a variety of
pesticides.
4. Conclusion and future perspectives
This review shed light on the reported impacts resulting from the
combined exposure to MNPs and pharmaceuticals or pesticides and,
Fig. 5. Representativity of studies addressing pesticide classes in mixture with
micro(nano)plastics. Each bar represents the relative abundance of each class.
M. Barreto et al.
Trends in Analytical Chemistry 169 (2023) 117307
6
revealing intriguing interactions with modulatory effects. The reviewed
studies reported both antagonistic and synergistic effects, highlighting
the complexity and multifaceted nature of these interactions. MNPs
exhibit a protective role by mitigating the toxicity of antibiotics, indi-
cating their potential as modulators of pharmaceutical pollution. How-
ever, studies have demonstrated synergistic effects, wherein MNPs
amplify the adverse effects of pesticides, underscoring their potential as
pollutant carriers. Based on the reviewed data, it appears that environ-
ments contaminated with both pesticides and MNPs could experience
more pronounced impacts. These ndings underscore the necessity for
further comprehensive research to unravel the underlying mechanisms
driving these interactions. It is crucial to elucidate the specic condi-
tions and factors inuencing the observed effects, including the role of
MNPs size, composition, and surface properties. A thorough compre-
hension of the intricate interplay between MNPs and pharmaceuticals/
pesticides is pivotal for effective environmental management strategies
and the preservation of ecosystem integrity. It enables informed
decision-making regarding the regulation, remediation, and mitigation
of MNPs-associated pollution.
Future research efforts should prioritize addressing research gaps to
enhance the understanding and reliable characterization of the risks
associated with co-exposure to MNPs and pharmaceuticals/pesticides,
namely:
•The development of harmonized frameworks for the evaluation of
the quality of MNPs characterization should be prioritized.
•It is highly recommended to assess the interaction with irregularly
shaped MNPs particles.
•Include more environmentally relevant polymers such as PP, PUR
and PET and relevant biopolymers.
•Perform more studies with environmentally relevant concentrations
of both contaminants, especially MNPs which, in high
concentrations, may aggregate and decrease their availability to
interact with pharmaceuticals/pesticides.
•Examine the persistent effects of acute exposures and prolonged,
chronic exposures.
•Understand the impact of abiotic factors on the bioavailability and
toxicity of combined exposures.
CRediT authorship contribution statement
M´
arcio Barreto: Investigation, Writing - original draft, Writing - re-
view & editing. Isabel Lopes: Conceptualization, Investigation, Writing -
review & editing, Supervision. Miguel Oliveira: Conceptualization,
Investigation, Writing - review & editing, Supervision.
Declaration of competing interest
The authors declare that they have no known competing nancial
interests or personal relationships that could have appeared to inuence
the work reported in this paper.
Data availability
Data will be made available on request.
Acknowledgements
This work was developed within the project NanoPlanet (DOI:
10.54499/2022.02340.PTDC), nancially supported by national funds
(OE), through FCT/MCTES. Thanks are also due for the nancial support
to CESAM nanced by national funds through FCT/MCTES (UIDB/
50017/2020, UIDP/50017/2020, LA/P/0094/2020) through strategic
programs.
Appendix
Table A.1
Effects of microplastics on the toxicity of pharmaceuticals.
Group Species Exposure
duration
(hours)
MPs Pharmaceutical Effects of the interaction
b
Ref.
Type (size
μ
m)
a
Tested
Concentrations
Name Tested
Concentrations
Arthropoda (Small
crustaceans)
Artemia salina 48 PVC (n.s) 0.26 mg dm
−3
Carbamazepine 25.16–43.40 mg
dm
−3
↓ Mortality
↑ChE activity
[84]
48 0.26 mg dm
−3
Simvastatin 12.03–52.08 mg
dm
−3
↓ Mortality
- ChE activity
Ceriodaphnia
dubia
168 PS (1) 0.04–2.48
μ
g L
−1
Acyclovir 0.0002–0.0379
μ
g L
−1
↑ offspring reduction
↓ DNA damage
[85]
Daphnia magna 504 PS (5) 2.5
μ
g L
−1
Roxithromycin 0.1–10
μ
g L
−1
F0: Mortality
↓ Number of offspring
- Time for rst brood
↓ Intrinsic rate of
population growth
↓ Velocity and
↓acceleration
-Ingestion and ↓ltration
↓ AChE activity
↓ T-SOD activity
↓ T-AOC content
- MDA content
F1: Mortality
↓ Number of offspring
- Time for rst brood
↓ Intrinsic rate of
population growth
Recovery: Mortality
↑ Number of offspring
↑ Time for rst brood
↓ Intrinsic rate of
population growth
[70]
(continued on next page)
M. Barreto et al.
Trends in Analytical Chemistry 169 (2023) 117307
7
Table A.1 (continued )
Group Species Exposure
duration
(hours)
MPs Pharmaceutical Effects of the interaction
b
Ref.
Type (size
μ
m)
a
Tested
Concentrations
Name Tested
Concentrations
Bacteria Shewanella spp 8 PLA
(28.66)
150–850 mg L
−1
Ciprooxacin 15 mg L
−1
↓ PO
4−
removal
inhibition
↓ SOD activity
[69]
PVC (3.51)
PE (37.87)
PS (45.49)
Chlorophyta Tetraselmis chuii 96 AP (1–5) 1.5 mg L
−1
Procainamide 4.0–256.0 mg
L
−1
↓ Average specic growth
rate
↑ Chlorophyl content
[86]
Doxycycline 4.0–128.0 mg
L
−1
- Average specic growth
rate
↑ Chlorophyl content
Chordata (sh) Danio rerio 336 PVC
(106–150)
5 mg L
−1
Erythromycin 100
μ
g L
−1
↑ Gut microbiome
dysbiosis
[87]
72 and 96 PS (1.11) 25-75 particles
L
−1
Metformin 40
μ
g L
−1
↓ Mortality
↓ Malformation rate
↓ CAT activity
↑ SOD activity
↓ HC content
↓ PC content
↓ MDA content
[88]
N-Guanylurea 200
μ
g L
−1
↓ Mortality
↓ Malformation rate
↓ CAT activity
↑ SOD activity
↓ HC content
↓ PC content
↓ MDA content
Misgurnus
anguillicaudatus
96 PVC (<10) 50 mg L
−1
R-Venlafaxine 10–500
μ
g L
−1
↑ SOD activity
↑ MDA content
[89]
S-Venlafaxine ↑ SOD activity
↑ MDA content
R-O-
Desthylvenlafaxine
↑ SOD activity
- MDA content
S-O-
Desthylvenlafaxine
↑ SOD activity
- MDA content
Oreachromis
niloticus
336 PS (5) 10
μ
g L
−1
Propranolol 50
μ
g L
−1
- AChE activity
- EROD
- BFCOD
↑ SOD activity
- P-gp
↓ MDA content
[71]
Sulfamethoxazole - AChE activity
- EROD
- BFCOD
↓ SOD activity
↑ P-gp
↓ MDA content
Oryzias latipes 288 PS (2) 40
μ
g L
−1
Diazepam 30
μ
g L
−1
Exposure period:
Shoaling behaviour
Recovery period: ↑
Shoaling behaviour
[90]
Oryzias
melastigma
672 PS (2) 2–200
μ
g L
−1
17a-
ethynylestradiol
10 ng L
−1
- Biometric parameters
↑ Plasma E
2
levels
↑ Plasma T levels
↑ E
2
/T ratio
↑ Liver and testes
histological abnormalities
- VTG levels
↑ VTG1 and VTG2 mRNA
levels
↑ CHgH and CHgL mRNA
levels
↑ ER
α
and ERβ mRNA
levels
↑ mGnRH mRNA levels
↑ GnRHR mRNA levels
↑ FSHβ mRNA levels
- LHβ mRNA levels
- GTH
α
mRNA levels
↑ Cyp19a mRNA levels
[91]
Pomatoschistus
microps
96 PE (1–5) 184
μ
g L
−1
Cefalexin 1.3–10 mg L
−1
↑ Post-exposure predatory
behaviour inhibition
[92]
(continued on next page)
M. Barreto et al.
Trends in Analytical Chemistry 169 (2023) 117307
8
Table A.1 (continued )
Group Species Exposure
duration
(hours)
MPs Pharmaceutical Effects of the interaction
b
Ref.
Type (size
μ
m)
a
Tested
Concentrations
Name Tested
Concentrations
- AChE activity
- LPO levels
Cyanobacteria Synechocystis sp. 96 PS (5–50) 5–100 mg L
−1
Ciprooxacin 40
μ
g L
−1
↓ Growth inhibition
↓ ROS levels
↓ Metabolic disorders
(lipids, carbohydrates,
nucleosides)
[93]
Mollusca Corbicula uminea 240 PS (6) 10
μ
g g
−1
Ciprooxacin 0.5–50
μ
g g
−1
↓ AChE activity
↑ SOD and CAT activity
↑ GSH, GSH-Px activity
↓ GST activity
- GR activity
↓ MDA content
↓ Histological damage
- Siphoning behaviour
[72]
Mytilus coruscus 672 PS (4.33) 260 mg L
−1
Carbamazepine 10
μ
g L
−1
↑ Shell regeneration
↑ ATP content
- PFK activity
↑ Ca
2+
-ATPase activity
↑ Intracellular Ca
2+
content
↑ CA content
- BMPR2 content
- CHS mRNA levels
↑ CLP mRNA levels
- CA mRNA levels
↑ BMPR2 mRNA levels
↑ CALM mRNA levels
[94]
Tegillarca granosa 96 PS (30) 1 mg L
−1
17b-estradiol 0.1–1
μ
g L
−1
↓ Total haemocyte count
↓ ROS level
↓ Calcium level
- LZM concentration
↓ LZM activity
↓ TLR4 mRNA levels
↓ TRAF6 mRNA levels
↓ IKK
α
mRNA levels
↓ NFkB mRNA levels
↓ Bcl-2 mRNA levels
↓ Caspase 3 mRNA levels
↓ CALM mRNA levels
[95]
Unio tumidus 335 PET
(100–500)
1 mg L
−1
Ibuprofen 0.8
μ
g L
−1
- Mn-SOD activity
- Zn,Cu-SOD activity
- CAT activity
- LPO content
↑ AChE activity
- PC content
[96]
↓ Antagonistic effect; ↑ Synergistic effect; - No interaction.
a Polystyrene (PS); Polyethylene (PE); High density polyethylene (HDPE); Polyvinyl chloride (PVC); Polyterephthalate (PET); Polylactic acid (PLA); Aminoplast (AP).
b Cholinesterase (ChE); Acetylcholinesterase (AChE); Glutathione (GSH); Glutathione-S-transferase (GST); Glutathione peroxidase (GPx); Glutathione reductase (GR);
Catalase (CAT); Superoxide dismutase (SOD); Total antioxidant content (T-AOC); Malondialdehyde content (MDA); Hydroperoxide content (HC); Protein carbonyl
content (PC); Lipid peroxidation (LPO); Ethoxyresorun-O-deethylase (EROD); Benzyloxy-4-triuoromethylcoumarin-O-debenzyloxylase (BFCOD); Collagen-like
protein (CLP); CHS (Chitin synthase); Bone morphogenetic protein receptor 2 (BMPR2); Carbonic anhydrase (CA); Phosphofructonikase (PFK); Calmodulin
(CALM); Lysozyme (LZM); Toll-like receptor 4 (TLR4); Tumour necrosis associated-receptor factor 6 (TRAF6); Inhibitor of nuclear factor kappa-B kinase subunit
(IKK
α
); Nuclear factor NF-kappa-B p105 subunit (NFkB); Vitellogenin (VTG); Estrogen receptor alfa and beta (ER
α
and β), Choriogenin H and L (CHgH and CHgL);
Luteinizing hormone β (LHβ); Gonadotropin hormone
α
(GTH
α
); Follicle-stimulating hormone β (FSHβ); Gonadotropin-releasing hormone (mGnRH); Gonadotropin-
releasing hormone receptor (GnRHR); Reactive oxygen species (ROS); Total oxidant status (TOS);Glucuronyltransferase (UGT); 2,2-diphenyl-1-picryl-hydrazyl-hy-
drate (DPPH); Aspartate aminotransferase (AST); Alkaline phosphatase (ALP); Creatine phosphokinase (CPK); Alanine aminotransferase (ALT); Lactate dehydroge-
nase (LDH).Heat-shock proteins 70 (hsp70).
Table A.2
Effects of nanoplastics on the toxicity of pharmaceuticals.
Group Species Exposure time
(hours)
NPs Pharmaceutical Effects of the interaction
b
Ref.
Type (size
nm)
a
Tested
Concentration
Name Tested
Concentration
Chlorophyta Chlorella
pyrenoidosa
96 PS (600) 1 mg L
−1
R-Ibuprofen 0.5–100 mg L
−1
↓Mortality
- Chlorophyl content
ROS levels
[82]
(continued on next page)
M. Barreto et al.
Trends in Analytical Chemistry 169 (2023) 117307
9
Table A.2 (continued )
Group Species Exposure time
(hours)
NPs Pharmaceutical Effects of the interaction
b
Ref.
Type (size
nm)
a
Tested
Concentration
Name Tested
Concentration
↓ T-AOC levels
- MDA content
S-Ibuprofen ↓ Mortality
- Chlorophyl content
- ROS levels
↓ T-AOC levels
- MDA content
Rac-Ibuprofen ↓ Mortality
- Chlorophyl content
- ROS levels
↓ T-AOC levels
- MDA content
Chordata
(sh)
Danio rerio 96 PS-COOH
(60)
0.015–1.5 mg
L
−1
Simvastatin 12.5–15
μ
g L
−1
↑ Mortality
- Malformations
↓ Hatchling
↓ Heartbeat
[97]
Oreochromis
niloticus
336 PS (100) 1–100
μ
g L
−1
Roxithromycin 50
μ
g L
−1
↓ AChE activity
- EROD
- BFCOD
↑ SOD activity
↓ MDA content
[60]
Oryzias
melastigma
720 PS (~100) 5 mg g
−1
Sulfamethazine 0.5–5 mg g
−1
↓ Gut microbiome dysbiosis
↓ SOD, CAT and GPx mRNA levels
[73]
Cyanobacteria Synechocystis sp. 96 PS (50) 5–100 mg L
−1
Ciprooxacin 40
μ
g L
−1
↓ Growth inhibition
↓ ROS levels
↓ Metabolic disorders (lipids,
carbohydrates, nucleosides)
[93]
Mollusca Corbicula
uminea
240 PS (80) 1
μ
g L
−1
Ciprooxacin 0.5–50
μ
g L
−1
- AChE activity
↑ SOD and CAT activity
↑ GSH, GPx,
↓ GST activity
- GR activity
- MDA content
↑ Histological damage
↑ Siphoning behaviour
[72]
96 PS (110) 50
μ
g L
−1
Carbamazepine 6.3
μ
g L
−1
- T-AOC
- TOS
↓ Gst mRNA levels
- Hsp70 mRNA levels
- ChE activity
[98]
Tegillarca
granosa
336 PS (500) 260
μ
g L
−1
Florfenicol 42 ng L
−1
↑ Haemocytes total count
↑ Percentage of phagocytosis
↑ ROS levels
↑ MDA content
↑ Haemocyte cell viability
↑ DNA damage
↑ IKK
α
mRNA levels
↑ NFkB mRNA levels
↑ MAPK mRNA levels
↑ Caspase3 mRNA levels
↑ GST mRNA levels
↑ Cyp1a2 mRNA levels
[75]
Oxytetracycline 270 ng L
−1
↑ Haemocytes total count
↑ Percentage of phagocytosis
↑ ROS levels
↑ MDA content
↑ Haemocyte cell viability
↑ DNA damage
↑ Lectin content
- IKK
α
mRNA levels
↑ NFkB mRNA levels
↑ MAPK mRNA levels
↑ Caspase3 mRNA levels
↑ GST mRNA levels
↑ Cyp1a2 mRNA levels
672 PS (500) 260
μ
g L
−1
Florfenicol 42 ng L
−1
↑ GST activity
↑ GST mRNA levels
- UGT mRNA levels
↑ MRP2 mRNA levels
↑ Cyp1a2 mRNA levels
- Cyp2u1 mRNA levels
[74]
Oxytetracycline 270 ng L
−1
- GST activity
↑ GST mRNA levels
(continued on next page)
M. Barreto et al.
Trends in Analytical Chemistry 169 (2023) 117307
10
Table A.2 (continued )
Group Species Exposure time
(hours)
NPs Pharmaceutical Effects of the interaction
b
Ref.
Type (size
nm)
a
Tested
Concentration
Name Tested
Concentration
- UGT mRNA levels
- MRP2 mRNA levels
↑Cyp1a2 mRNA levels
- Cyp2u1 mRNA levels
↓ Antagonistic effect; ↑ Synergistic effect; - No interaction.
a Polystyrene (PS).
b Cholinesterase (ChE); Acetylcholinesterase (AChE); Glutathione (GSH); Glutathione-S-transferase (GST); Glutathione peroxidase (GPx); Glutathione reductase (GR);
Catalase (CAT); Superoxide dismutase (SOD); Total antioxidant content (T-AOC); Malondialdehyde content (MDA); Lipid peroxidation (LPO); Ethoxyresorun-O-
deethylase (EROD); Benzyloxy-4-triuoromethylcoumarin-O-debenzyloxylase (BFCOD); Collagen-like protein (CLP); CHS (Chitin synthase); Bone morphogenetic
protein receptor 2 (BMPR2); Carbonic anhydrase (CA); Phosphofructonikase (PFK); Calmodulin (CALM); Lysozyme (LZM); Toll-like receptor 4 (TLR4); Tumour ne-
crosis associated-receptor factor 6 (TRAF6); Inhibitor of nuclear factor kappa-B kinase subunit (IKK
α
); Mitogen-activated protein kinase (MAPK); Nuclear factor NF-
kappa-B p105 subunit (NFkB); Reactive oxygen species (ROS); Total oxidant status (TOS);Glucuronyltransferase (UGT); 2,2-diphenyl-1-picryl-).Heat-shock proteins 70
(hsp70).
Table A.3
Effects of microplastics on the toxicity of pesticides.
Group Species Exposure
time
(hours)
MPs Pesticide Effects of the interaction
b
Ref.
Type (size
μ
m)
a
Tested
Concentration
Name Tested
Concentration
Arthropoda
(Crustaceans)
Minuca
ecuadoriensis
120 PE (<250) 200 mg L
−1
Malathion 50 mg L
−1
↑ Survival rate [99]
Arthropoda
(Small
crustaceans)
Artemia salina 48 PVC (n.s) 260 mg dm
−3
Chlorpyrifos 2–8 mg dm
−3
↓ Mortality
↑ ChE activity
[84]
Ceriodaphnia
dubia
168 PS (1) 0.04–2.48
μ
g L
−1
Imidacloprid 1.39–1561.1
μ
g L
−1
↑ Percentage of offspring
reduction
-DNA damage
[85]
Daphnia magna 504 PE (1–4) 1–10 mg L
−1
Deltamethrin 40 ng L
−1
↑ Mortality
↑ Number of broods
↑ Number of neonates per
adult
↑ Time for the rst brood
↑ Longevity
[79]
72 PS (1) 300 000 particles
L
−1
Dimethoate 0.15–5 mg L
−1
- Survival rate
- Mobility
[80]
Deltamethrin 0.016–10
μ
g
L
−1
- Survival rate
- Mobility
Arthropoda
(Insects)
Chironomus
riparius
816 PS (1) 14 219 particles
mL
−1
(7.813 ×
10
−9
g mL
−1
)
Esfenvalerate 0.07
μ
g kg
−1
- Survival rate
- Emergence rate
- Sex ratio
- Development time
- Microbiome dysbiosis
[100]
Chlorophyta Isochrysis
galbana
72 PE (<22) 0.5–25 mg L
−1
Chlorpyrifos 2–3 mg L
−1
↓ Cellular inhibition [78]
Chordata (Fish) Cyprinus carpio 1440 PE (8–13) 1.5–4.5 mg L
−1
Glyphosate 5–15 mg L
−1
↑ Histopathological effects
↑ Gut microbiome dysbiosis
[81]
504 PE (n.s) 1–2 mg L
−1
Paraquat 0.2–0.4 mg L
−1
↑ AST, ALP, CPK, ALT and
LDH activities
↑ Glucose levels
↑ Albumin and creatinine
levels
↑ Paraquat toxic effects
[101]
Danio rerio 336 PVC (106–150) 5 mg L
−1
Chlorpyrifos 200
μ
g L
−1
↑ Gut microbiome dysbiosis
↑ Gut CAT activity
↑ Swimming velocity
[87]
PS (5) 500
μ
g L
−1
Chlorpyrifos 20–200
μ
g L
−1
↑ Gut microbiome dysbiosis [102]
504 PS (<100) 1 ×10
6
particles L
-
Chlorpyrifos 10–100 ng L
−1
↓ EROD activity
↓ AChE activity
[103]
96 PS (9–70) 10 mg L
−1
Difenoconazole 1.36–1.74 mg
L
−1
↓ SOD, CAT, GPx activity
↓ MDA content
[104]
96 PET (150) 5–10 mg L
−1
Abamectin 6
μ
g L
−1
↑ Gpx activity
↑ DPPH activity
↑ GSH content
↑ Cyp1a mRNA levels
↑ Vtg mRNA levels
[105]
504 PS (5) 20
μ
g L
−1
Imidacloprid 100
μ
g L
−1
↑ Glycolysis and
gluconeogenesis related
genes mRNA levels
↑ Oxidative stress related
genes mRNA levels
[106]
(continued on next page)
M. Barreto et al.
Trends in Analytical Chemistry 169 (2023) 117307
11
Table A.3 (continued )
Group Species Exposure
time
(hours)
MPs Pesticide Effects of the interaction
b
Ref.
Type (size
μ
m)
a
Tested
Concentration
Name Tested
Concentration
↑ Inammation related genes
mRNA levels
Oncorhynchus
mykiss
96 PS
(21.89–466.70)
30–300
μ
g L
−1
Chlorpyrifos 2–6
μ
g L
−1
↑ Total Fatty acid
composition
↑ Total Amino acid
composition
- Protein content
[105]
96 PS
(21.89–466.70)
30–300
μ
g L
−1
Chlorpyrifos 2–6
μ
g L
−1
↑ Histopathological effects
↑ Histomorphometrical
effects
[107]
Salmo trutta 96 PS (50) 1 ×10
4
particles L
-
Methiocarb 1 mg L
−1
- Hsp70 levels
- SOD activity
- AChE activity
- CbE activity
- LPO levels
[108]
Mollusca Crassostrea gigas 576 HDPE (20–25) 10
μ
g L
−1
Chlortoluron 30
μ
g L
−1
- Valve physiology
↑ Shell formation
[109]
Mytilus
galloprovincialis
504 HDPE (22) 1.5 mm
3
L
−1
Chlorpyrifos 7.6
μ
g L
−1
- Physiological parameters
↑ Energy depletion
(carbohydrates content)
↑ Protease activity
↓ Peroxidase activity
- Lysozyme activity
- Bactericidal activity
[110]
↓ Antagonistic effect; ↑ Synergistic effect; - No interaction.
a Polystyrene (PS); Polyethylene (PE); High density polyethylene (HDPE); Polyvinyl chloride (PVC); Polyterephthalate (PET).
b Cholinesterase (ChE); Acetylcholinesterase (AChE); Glutathione (GSH); Glutathione peroxidase (GPx); Catalase (CAT); Superoxide dismutase (SOD); Malondial-
dehyde content; Lipid peroxidation (LPO); Ethoxyresorun-O-deethylase (EROD); Vitellogenin (VTG); 2,2-diphenyl-1-picryl-hydrazyl-hydrate (DPPH); Aspartate
aminotransferase (AST); Alkaline phosphatase (ALP); Creatine phosphokinase (CPK); Alanine aminotransferase (ALT); Lactate dehydrogenase (LDH).Heat-shock
proteins 70 (hsp70).
Table A.4
Effects of nanoplastics on the toxicity of pesticides.
Group Species Exposure time
(hours)
NPs Pesticide Effects of the interaction Ref.
Type
(size
nm)
a
Tested
Concentration
Name Tested
Concentration
Chordata
(sh)
Danio rerio 96 PS (15) 50 mg L
−1
DDE 100
μ
g L
−1
↑ Pericardial edema area
↑ Oxygen saturation
↑ Locomotor behaviour
↑ Alterations in gene expression
related to cardiovascular system
[30]
96 PS (44) 0.015–1.50 mg
L
−1
Phenmedipham 1–20 mg L
−1
- CAT activity
- GST activity
↑ ChE activity
↓ Locomotor behaviour
[111]
Cyanobacteria Microcystis
aeruginosa
96 PS-NH
2
(200)
5 mg L
−1
Glyphosate 2–20 mg L
−1
↓ Chlorophyll-a content
- Total microcystin content
[112]
↓ Antagonistic effect; ↑ Synergistic effect; - No interaction.
a Polystyrene (PS).
b Cholinesterase (ChE); Glutathione-S-transferase (GST); Catalase (CAT).
Table A.5
Techniques used to characterize micro(nano)plastics.
Polymer
type
Functionalization Size (
μ
m) Morphology
a
Chemical composition
characterization
b
Crystallinity
d
Zeta
Potential
c
Particles characterization in test
medium (timepoints)
Ref.
PVC no 106–150 SEM ATR-FTIR XRD n.d no [87]
PET no 100–500 n.d n.d n.d n.d no [96]
PS no 5. SEM FTIR n.d n.d no [70]
PS no 1.14 CLSM, AFM n.d n.d n.d no [88]
PS no 1 n.d n.d n.d n.d no [85]
PLA no 28.66 LDA n.d n.d ELS no [69]
PVC no 3.51 LDA n.d n.d ELS no
PE no 37.87 LDA n.d n.d ELS no
PS no 45.49 LDA n.d n.d ELS no
PS no 2. n.d n.d n.d n.d no [90]
(continued on next page)
M. Barreto et al.
Trends in Analytical Chemistry 169 (2023) 117307
12
Table A.5 (continued )
Polymer
type
Functionalization Size (
μ
m) Morphology
a
Chemical composition
characterization
b
Crystallinity
d
Zeta
Potential
c
Particles characterization in test
medium (timepoints)
Ref.
PS no 4.33 SEM FTIR, Raman n.d ELS no [94]
PS no 2 SEM, LOM FTIR n.d n.d no [91]
PS no 5–50 SEM, TEM,
DLS
FTIR n.d ELS yes (0h) [113]
PS no 5 SEM FTIR n.d n.d no [71]
PS no 5–50 DLS, TEM n.d n.d ELS yes (0h) [93]
PS no 6 LDA, TEM Raman n.d n.d No [72]
PVC no N/S n.d n.d n.d n.d no [84]
PS no 30 TEM n.d n.d n.d no [95]
AP no 1–5 n.d n.d n.d n.d no [86]
PVC no ≤10 SEM n.d n.d n.d no [89]
PE no 1–5 n.d n.d n.d n.d no [92]
PS no 5 SEM, FM n.d n.d n.d no [102]
PS no ≤100 n.d n.d n.d n.d no [103]
HDPE no ≤22 ECC, LOM n.d n.d n.d no [110]
PE no ≤250 n.d n.d n.d n.d no [99]
PS no 9–70 SEM n.d n.d n.d no [104]
PE no 8–12 SEM FTIR n.d n.d no [81]
PET no 150 n.d n.d n.d n.d no [114]
PS no 21.89–466.70 SEM FTIR n.d n.d no [105]
PS no 1 n.d n.d n.d n.d no [100]
HDPE no 20–25 n.d n.d n.d n.d no [109]
PS no 5 n.d n.d n.d n.d no [106]
PS no 21.89 SEM FTIR n.d n.d no [107]
PS no ≤50 SEM FTIR, Raman, TED-GC-MS n.d n.d no [108]
PE no 1–4 n.d n.d n.d n.d no [79]
PE no ≤22 ECC n.d n.d n.d no [78]
PS no 1 TEM, FC n.d n.d n.d no [80]
PE no N/S n.d n.d n.d n.d no [101]
PS no 50–500 SEM, TEM,
DLS
n.d n.d ELS Yes (0h) [113]
PS no 80 LDA, TEM Raman n.d n.d no [72]
PS no 100 DLS n.d n.d ELS no [73]
PS COOH 60 DLS, TEM,
SEM
n.d n.d ELS yes (0 and 96h) [97]
PS no 50 DLS, TEM n.d n.d ELS yes (0h) [93]
PS no 500 n.d n.d n.d n.d no [75]
PS no 500 n.d n.d n.d n.d no [74]
PS no 600 DLS n.d n.d PALS yes (0, 24, 48, 96h) [83]
PS no 100 SEM n.d n.d n.d no [61]
PS no 110 DLS, TEM n.d n.d ELS yes (0, 6, 24h) [98]
PS no 15 n.d n.d n.d n.d no [30]
PS no 44 DLS n.d n.d ELS yes (0, 96h) [111]
PS -NH
2
200 DLS n.d n.d ELS yes (0h) [112]
Not determined (n.d).
a Scanning electron microscopy (SEM); Transmission electron microscopy (TEM); Laser diffraction analysis (LDA); Dynamic light scattering (DLS); Confocal laser
scanning microscope (CLSM); Atomic force microscope (AFM); Light optical microscope (LOM); electronic coulter counter (ECC); Flowcytometry (FC); Fluorescence
microscope (FM).
b Raman spectroscopy (Raman); Fourier-transform infrared spectroscopy (FTIR); Attenuated-total reection Fourier-transform infrared spectroscopy (ATR-FTIR);
Thermal Extraction-Desorption-Gas chromatography-Mass spectrometer (TED-GC-MS).
c Electrophoretic light scattering (ELS); Phase analysis light scattering (PALS).
d X-ray diffraction (XRD).
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