Towards a scalable bioprocess for rAAV production using a HeLa stable cell line.

The majority of recombinant adeno-associated viruses (rAAV) approved for clinical use or in clinical trials areproduced by transient transfection using the HEK293 cell line. However, this platform has several manufacturing bottlenecks at commercial scales namely, low product quality (full to empty capsid ratio <20% in most rAAV serotypes), lower productivities obtained after scale-up and the high cost of raw materials, in particular of Good Manufacturing Practice grade plasmid DNA required for transfection. The HeLa-based stable cell line rAAV production system provides a robust and scalable alternative to transient transfection systems. Nevertheless, the time required to generate the producer cell lines combined with the complexity of rAAV production and purification processes still pose several barriers to the use of this platform as a suitable alternative to the HEK293 transient transfection. In this work we streamlined the cell line development and bioprocessing for the HeLaS3-based production of rAAV. By exploring this optimized approach, producer cell lines were generated in 3-4 months, and presented rAAV2 volumetric production (bulk) > 3 × 1011 vg/mL and full to empty capsids ratio (>70%) at 2 L bioreactor scale. Moreover, the established downstream process, based on ion exchange and affinity-based chromatography, efficiently eliminated process related impurities, including the Adenovirus 5 helper virus required for production with a log reduction value of 9. Overall, we developed a time-efficient and robust rAAV bioprocess using a stable producer cell line achieving purified rAAV2 yields > 1 × 1011 vg/mL. This optimized platform may address manufacturing challenges for rAAV based medicines.

Extending AAV Packaging Cargo through Dual Co-Transduction: Efficient Protein Trans-Splicing at Low Vector Doses.

Adeno-associated viral (AAV) vectors represent one of the leading platforms for gene delivery. Nevertheless, their small packaging capacity restricts their use for diseases requiring large-gene delivery. To overcome this, dual-AAV vector systems that rely on protein trans-splicing were developed, with the split-intein Npu DnaE among the most-used. However, the reconstitution efficiency of Npu DnaE is still insufficient, requiring higher vector doses. In this work, two split-inteins, Cfa and Gp41-1, with reportedly superior trans-splicing were evaluated in comparison with Npu DnaE by transient transfections and dual-AAV in vitro co-transductions. Both Cfa and Gp41-1 split-inteins enabled reconstitution rates that were over two-fold higher than Npu DnaE and 100% of protein reconstitution. The impact of different vector preparation qualities in split-intein performances was also evaluated in co-transduction assays. Higher-quality preparations increased split-inteins' performances by three-fold when compared to low-quality preparations (60-75% vs. 20-30% full particles, respectively). Low-quality vector preparations were observed to limit split-gene reconstitutions by inhibiting co-transduction. We show that combining superior split-inteins with higher-quality vector preparations allowed vector doses to be decreased while maintaining high trans-splicing rates. These results show the potential of more-efficient protein-trans-splicing strategies in dual-AAV vector co-transduction, allowing the extension of its use to the delivery of larger therapeutic genes.

Development of versatile affinity-based system for one step purification process: Case of Group A Streptococcus vaccine.

Affinity capture is one of the most attractive strategies for simplifying downstream processing. Although it is a key mainstream approach for antibody purification, the same is not true for other biologics such as vaccines, mainly due to the lack of suitable affinity material. In this study, a novel custom affinity system is introduced permitting widespread adoption of affinity capture for the purification of biologics beyond antibodies. This is illustrated here by the development of a one-step purification process of a mutant form of streptolysin O (SLO), a vaccine candidate against Streptococcus pyogenes infection. The system consists of the association of custom ligands based on the Nanofitin protein scaffold, with Eshmuno® industry-grade chromatography medium. The Nanofitins were selected for their specificity to the target product. The newly developed affinity medium was used at different column sizes to monitor scalability from process development (1 ml) and robustness verification (5 ml) to pilot (133 ml) and technical (469 ml) runs. The single-step affinity purification consistently delivered high purity product (above > 90%) and improved performances compared with the current three-step process: reduced process time and footprint (3 to 1 step) and increased product yields (0.31 g vs. 0.04 g of SLO per kg of harvest broth). The custom affinity system herein described can potentially be applied to any biologic for which a specific Nanofitin is identified, thus establishing a platform with a strong impact on the manufacturing of vaccines and other biological targets.

Bottom-Up Evaluation of the Uncertainty of the Quantification of Microplastics Contamination in Sediment Samples.

The quantification and comparison of microplastic contamination of sediments are affected by sample heterogeneity and the systematic and random effects affecting sample analysis. The quantification and combination of these components in the measurement uncertainty allows the objective interpretation of analysis results. This work presents the first detailed evaluation of the uncertainty of microplastic contamination quantification in sediments. The random and systematic effects affecting microplastic counts are modeled by the Poisson-lognormal distribution with inputs estimated from duplicate sediment analysis and the analysis of sediments spiked with microparticles. The uncertainty from particle counting was combined with the uncertainty from the determination of the dry mass of the analytical portion by the Monte Carlo method. The developed methodology was implemented in a user-friendly spreadsheet made available as the Supporting Information. The contamination of sediment samples collected in various inland Portuguese waters was determined, ranging from [0; 160] to [361; 2932] kg-1 for a 99% confidence level, and compared by assessing if the difference between contamination levels is equivalent to zero for the same confidence level. Several samples proved to have metrologically different microplastic contamination. This work represents a contribution to the objectivity of the assessment of environmental contamination with microplastics.

Downstream processing for influenza vaccines and candidates: An update.

Seasonal and pandemic influenza outbreaks present severe health and economic burdens. To overcome limitations on influenza vaccines' availability and effectiveness, researchers chase universal vaccines providing broad, long-lasting protection against multiple influenza subtypes, and including pandemic ones. Novel influenza vaccine designs are under development, in clinical trials, or reaching the market, namely inactivated, or live-attenuated virus, virus-like particles, or recombinant antigens, searching for improved effectiveness; all these bring downstream processing (DSP) new challenges. Having to deal with new influenza strains, including pandemics, requires shorter development time, driving the development of faster bioprocesses. To cope with better upstream processes, new regulatory demands for quality and safety, and cost reduction requirements, new unit operations and integrated processes are increasing DSP efficiency for novel vaccine formats. This review covers recent advances in DSP strategies of different influenza vaccine formats. Focus is given to the improvements on relevant state-of-the-art unit operations, from harvest and clarification to purification steps, ending with sterile filtration and formulation. The development of more efficient unit operations to cope with biophysical properties of the new candidates is discussed: emphasis is given to the design of new stationary phases, 3D printing approaches, and continuous processing tools, such as continuous chromatography. The impact of the production platforms and vaccine designs on the downstream operations for the different influenza vaccine formats approved for this season are highlighted.

Oncolytic virus purification with periodic counter-current chromatography.

Virus-based biologicals are one of the most promising biopharmaceuticals of the 21st century medicine and play a significant role in the development of innovative therapeutic, prophylactic, and clinical applications. Oncolytic virus manufacturing scale can range from 5 L in research and development up to 50 L for clinical studies and reach hundreds of liters for commercial scale. The inherent productivity and high integration potential of periodic counter-current chromatography (PCC) offer a transversal solution to decrease equipment footprint and the reduction of several non-value-added unit operations. We report on the design of an efficient PCC process applied to the intermediate purification of oncolytic adenovirus. The developed ion-exchange chromatographic purification method was carried out using a four-column setup for three different scenarios: (i) variation in the feedstock, (ii) potential use of a post-load washing step to improve virus recovery, and (iii) stability during extended operation. Obtained virus recoveries (57%-86%) and impurity reductions (>80% DNA, and >70% total protein) match or overcome batch purification. Regarding process stability and automation, our results show that not only the dynamic control strategy used is able to suppress perturbations in the sample inlet but also allows for unattended operation in the case of ion exchange capture.

Measurement uncertainty for the potency estimation by rapid microbiological methods (RMMs) with correlated data.

Recently, rapid microbiological methods (RMM) have often been used to determinate the potency of antibiotic drugs. Since all the standard and sample preparations are assayed into the same analytical conditions, it is expected that the correlations among the inhibitions zone sizes are not negligible. However, the procedures adopted in uncertainty estimations do not consider the correlation of data. The aim of this work was to study the impact of the correlation of data in the measurement uncertainty and, consequently, in the risk of false conformity decisions. RMM for the determination of the potency of cephalosporin antibiotics in pharmaceutical products were performed using an agar diffusion method. The shared analytical effects on inhibition resulted in correlation of data, which significantly decreased the combined measurement uncertainties, and therefore, the risk of false conformity decisions. Due to the lognormal distribution of potency values, measurement uncertainties were reported as a multiplicative uncertainty factor (UF). A MS-Excel spreadsheet is provided as supplementary material and may be used to estimate the measurement uncertainty and the risk of false conformity decisions for results obtained from RMM.

An electrostatic and probabilistic simulation model to describe neurosecretion at the synaptic scale.

A hybrid simulation model (macro-molecular dynamics and Monte Carlo method) is proposed to reproduce neurosecretion and exocytosis. A theory has been developed for vesicular dynamics based on quasi-static electric interactions and a simple transition-state model for the vesicular fusion. Under the non-equilibrium electric conditions in an electrolytic fluid, it is considered that the motion of each synaptic vesicle is influenced by electrostatic forces exerted by the membranes of the synaptic bouton, other vesicles, the intracellular and intravesicular fluids, and external elements to the neuron. In addition, friction between each vesicle and its surrounding intracellular fluid is included in the theory, resulting in a drift type movement. To validate the vesicle equations of motion, a molecular dynamics method has been implemented, where the synaptic pool was replaced by a straight angle parallelepiped, the vesicles were represented by spheres and the fusion between each vesicle and the presynaptic membrane was simulated by a Monte Carlo type probabilistic change of state. Density profiles showing clusters of preferential activity as well as fusion distributions similar to the Poisson distributions associated with miniature end-plate potentials were obtained in the simulations.

Early miR-155 upregulation contributes to neuroinflammation in Alzheimer's disease triple transgenic mouse model.

MicroRNAs (miRNAs) have emerged as a class of small, endogenous, regulatory RNAs that exhibit the ability to epigenetically modulate the translation of mRNAs into proteins. This feature enables them to control cell phenotypes and, consequently, modify cell function in a disease context. The role of inflammatory miRNAs in Alzheimer's disease (AD) and their ability to modulate glia responses are now beginning to be explored. In this study, we propose to disclose the functional role of miR-155, one of the most well studied immune-related miRNAs in AD-associated neuroinflammatory events, employing the 3xTg AD animal model. A strong upregulation of miR-155 levels was observed in the brain of 12-month-old 3xTg AD animals. This event occurred simultaneously with an increase of microglia and astrocyte activation, and before the appearance of extracellular Aß aggregates, suggesting that less complex Aß species, such as Aß oligomers may contribute to early neuroinflammation. In addition, we investigated the contribution of miR-155 and the c-Jun transcription factor to the molecular mechanisms that underlie Aß-mediated activation of glial cells. Our results suggest early miR-155 and c-Jun upregulation in the 3xTg AD mice, as well as in Aß-activated microglia and astrocytes, thus contributing to the production of inflammatory mediators such as IL-6 and IFN-ß. This effect is associated with a miR-155-dependent decrease of suppressor of cytokine signaling 1. Furthermore, since c-Jun silencing decreases the levels of miR-155 in Aß-activated microglia and astrocytes, we propose that miR-155 targeting can constitute an interesting and promising approach to control neuroinflammation in AD.

Computational modeling of peripheral pain: a commentary.

This commentary is intended to find possible explanations for the low impact of computational modeling on pain research. We discuss the main strategies that have been used in building computational models for the study of pain. The analysis suggests that traditional models lack biological plausibility at some levels, they do not provide clinically relevant results, and they cannot capture the stochastic character of neural dynamics. On this basis, we provide some suggestions that may be useful in building computational models of pain with a wider range of applications.

Simplified and Detailed Evaluation of the Uncertainty of the Measurement of Microbiological Contamination of Pharmaceutical Products.

BACKGROUND: The control of the microbial contamination of pharmaceutical products, PP, is crucial to ensure their safety and efficacy. The validity of the monitoring of such contamination depends on the uncertainty of this quantification. Highly uncertain quantifications due to the variability of determinations or the magnitude of systematic effects affecting microbial growth or other analytical operations make analysis unfit for the intended use. The quantification of the measurement uncertainty expressing the combined effects of all random and systematic effects affecting the analysis allows the sound decision about quantification adequacy for their intended use. The complexity of the quantification of microbial analysis uncertainty led to the development of simplified ways of performing this evaluation. OBJECTIVE: This work assesses the adequacy of the simplified quantification of the uncertainty of the determination of the microbial contamination of PP by log transforming microbial count and dilution factor of the test sample whose uncertainty is combined in a log scale using the uncertainty propagation law. METHODS: This assessment is performed by a parallel novel bottom-up and accurate evaluation of microbial analysis uncertainty involving the Monte Carlo Method simulation of the Poisson log-normal distribution of counts and of the normally distributed measured volumes involved in the analysis. Systematic effects are assessed and corrected on results to compensate for their impact on the determinations. Poisson regression is used to predict precision affecting determinations on unknown test samples. RESULTS AND CONCLUSION: This work concludes that triplicate determinations are required to produce results with adequately low uncertainty and that simplified uncertainty quantification underevaluate or overevaluate the uncertainty from determinations based on low or high colonies numbers, respectively. Therefore, detailed uncertainty evaluations are advised for determinations between 50% and 200% of PP's maximum admissible contamination value.

Evaluation of temporal trends and correlations of physical-chemical parameters in vast oceanic areas robust to information uncertainty.

The physical-chemical monitoring of vast oceanic areas aims at assessing the status and evolution of the environmental resource for its exploration, protection and/or better understanding. However, the interpretation of monitoring data is affected by ocean seasonality and heterogeneity, and by the quality of sampling and characterization tools used to study the environment. All these factors contribute to the uncertainty of collected information that should be expressed in determined parameter values or trends. A trend of a studied parameter quantified by values difference is significant if the observed absolute value of the difference is larger than their expanded uncertainty. The correlation of studied parameters, useful for their interpretation, is equality affected by the mentioned sources of uncertainty. This work describes the metrologically sound evaluation of trends and correlations of physicochemical parameters of vast oceanic areas where all uncertainty sources affecting the information are considered by simulating their complex impact by the Monte Carlo Method. The described methodology was successfully used to study the impact of summer upwelling in an 800 km2 coastal area offshore two large cities in Portugal. Nutrients, conductivity, salinity and temperature trends and correlations are distinguished from system heterogeneity, sampling and sample analysis uncertainty for a 99% confidence level.

Bottom-up uncertainty evaluation of complex measurements from correlated performance data: Determination of total Cr in yeast by ICP-MS after acid digestion.

The objective interpretation of a measurement result requires knowing the associated uncertainty. The cost-effective collection of measurement performance data on the same day produces correlated values that can affect measurement uncertainty evaluation. This work describes a novel methodology for the bottom-up evaluation of measurements based on complex sample pretreatment and the instrumental quantification of the prepared sample applicable to correlated inputs. The numerical Kragten method is used to combine the uncertainty components shared in various analyte recovery determinations. The developed methodology was applied to the determination of total chromium in yeast samples by ICP-MS after microwave-assisted acid digestion. The developed analysis of yeast samples is fit for monitoring the contamination of this product since it is associated with a relative expanded uncertainty, U', lower than 20%, ranging from 8.4% to 10.0% in determinations of Cr between 0.125 mg/kg and 305.5 mg/kg. Duplicate analyses are adequate for reference materials production (U' < 7%).

Determination of microplastic contamination levels and trends in vast oceanic sediment areas with uncertainty.

Small plastic particles, designated as microplastics, are known vehicles of several contaminants desorbed from their surface after being ingested by marine organisms. The monitoring of the levels and trends of microplastics in oceanic areas is essential to identify relevant threats and respective sources whose management should be improved to protect the environmental resources. However, the assessment of contamination trends in large oceanic areas is affected by contamination heterogeneity, sampling representativeness, and the uncertainty of collected sample analyses. Only contamination variations not justifiable by system heterogeneity and their characterisation uncertainty are meaningful and should be taken seriously by the authorities. This work describes a novel methodology for the objective identification of meaningful variation of microplastic contamination in vast oceanic areas by the Monte Carlo simulation of all uncertainty components. This tool was successfully applied to the monitoring of the levels and trends of microplastic contamination in sediments from a 700 km2 oceanic area from 3 km to 20 km offshore Sesimbra and Sines (Portugal). This work allowed concluding that contamination has not varied between 2018 and 2019 (difference of mean total microplastic contamination between -40 kg-1 and 34 kg-1) but that microparticles made of PET are the major type of studied microplastics (in 2019, mean contamination is between 36 kg-1 and 85 kg-1). All assessments were performed for a 99 % confidence level.

Statistically sound comparison of standardized and simulation methods for oil spill source identification in real spill scenarios.

The comparison of oil patterns of a spill (Sp) and suspected spill source (SS) samples is based on ratios between correlated GC-MS signals of oil-discriminating compounds, i.e., diagnostic ratios (DR). The Student's t statistics (S-t) and a maximum relative difference (SC), proposed in standard methods, have been used for DR comparison due to their simplicity. An alternative methodology based on Monte Carlo Method (MCM) simulations of correlated signals, capable of accurately defining DR comparison criteria, proved that S-t and SC assumptions regarding DR normality and precision are frequently not valid, affecting comparison reliability. The performance of the approaches was accurately compared from independent signals of the same oil sample from a perfect match between Sp and SS. The present study describes the comparison of the approaches in real oil spill scenarios reproduced in International Round Robin Tests. Since as the number of compared DR increases, also rises the probability of not all equivalent DR being actually considered equivalent, the decision of oil pattern equivalence was based on two comparisons of independent sets of Sp and SS signals. The risk of true oil standard equivalency claims is compared for the three oil spill scenarios studied, which are different considering oil types, DR sets and spill weathering. The ability of the approaches to distinguish the Sp sample from an oil sample known not to be the source of the spill was also assessed. The MCM based on two independent DR comparison trials was the only one consistently producing fingerprint comparison risks of correct equivalence claims larger than 98 %. MCM also performed better in distinguishing different oil patterns. It was concluded that comparing >22 DR does not change the risk of correct oil pattern equivalence assessment significantly. The complexity of the MCM approach is overcome by using user-friendly and validated software.

Metrologically sound comparison of trace-metal levels in sea cucumber tissues from different species and habitats.

Sea cucumbers are indicators of metal contamination in sea bottoms due to their low mobility and feeding behaviour. Comparing contaminations of specimens from different locations, habitats, and/or organs allows understanding of contamination processes and differences. However, the interpretation of these data is affected by the variability of contamination levels in specimens, the uncertainty of tissue analyses, and the complex correlation of mass fractions estimated by using the same calibration of the used instrumental method of analysis. This work presents a novel tool for the sound comparison of contamination levels of biota where all mentioned factors are considered to produce reliable and undisputable information on the studied system. The Monte Carlo simulation of uncertainty components, affecting the determination of mean contamination levels observed in selected types of tissues, allowed simulating mean contamination differences and determining if these are meaningful. This tool was used to assess the levels of Cd, Cu, Ni and Pb of animals collected in different locations of Sesimbra-Portugal. It was concluded that specimens that selectively consume macroalgae have larger contamination levels than animals feeding on sediment. The gut is the most contaminated organ suggesting intake from feeding is dominant. Three of the analysed animals have Pb mass fractions larger than a maximum admissible value for human consumption of 3 mg kg-1 with a probability larger than 2.5%.

Efficient adeno-associated virus serotype 5 capture with affinity functionalized nanofiber adsorbents.

Adeno-associated viruses (AAVs) are one of the most promising tools for gene therapy applications. These vectors are purified using affinity and ion exchange chromatography, typically using packed beds of resin adsorbents. This leads to diffusion and pressure drop limitations that affect process productivity. Due to their high surface area and porosity, electrospun nanofiber adsorbents offer mass transfer and flow rate advantages over conventional chromatographic media. The present work investigated the use of affinity cellulose-based nanofiber adsorbents for adeno-associated virus serotype 5 (AAV5) capture, evaluating dynamic binding capacity, pressure drop, and AAV5 recovery at residence times (RT) less than 5 s. The dynamic binding capacity was found to be residence time-dependent, but nevertheless higher than 1.0 × 1014 TP mL-1 (RT = 1.6 s), with a pressure drop variation of 0.14 MPa obtained after loading more than 2,000 column volumes of clarified AAV5 feedstock. The single affinity chromatography purification step using these new affinity adsorbents resulted in 80% virus recovery, with the removal of impurities comparable to that of bead-based affinity adsorbents. The high binding capacity, virus recovery and reduced pressure drop observed at residence times in the sub-minute range can potentially eliminate the need for prior concentration steps, thereby reducing the overall number of unit operations, process time and costs.

Development and validation of statistically sound criteria for the match of unweathered GC-MS fingerprints in oil spill forensics.

The investigation of an oil spill's origin frequently relies on determining the equivalence of oil component patterns in samples from the contaminated environment and suspected oil source. This comparison benefits if based on the ratio of the abundance of unweathered characteristic components of the oil product, Diagnostic Ratios, DR. Replicate determinations of DR from one sample are used to set limits for the second sample's DR. The composition equivalence of oil patterns in both samples is indicated if all compared DR are statistically equivalent with a high confidence level. Some studies define DR limits assuming their normality and using Student's t statistics (S-t). However, since the ratio of correlated abundances can be not normally distributed, this criterion can drive to more false comparisons than predicted by the test confidence level. This work developed a computational tool for the reliable description of the non-normal distribution of the DR based on the Monte Carlo Method (MCM), aiming to allow the accurate control of the confidence of DR comparison. This work concluded that S-t defines 95% or 98% confidence limits with probabilities of falsely rejecting samples equivalence, φ, that can be up to 4.3% higher than predicted by the confidence level of the S-t test (i.e., 5% and 2%). The fragilities of the S-t limits significantly reduce the probability (1-θ) of two samples with the same oil producing equivalent values of all compared DR. For the studied 69 DR from unweathered components, the (1-θ) for 98% confidence level limits, set by the MCM and S-t from triplicate injections of one sample, are 94.8% and 91.7%, respectively. These values are below the confidence level (P) defined for each DR because DR are correlated with a correlation coefficient lower than 1. The (1-θ) can be increased to above P by using MCM limits and accepting composition equivalence if at least one of two sample extract injections produces values within limits set from the other sample's replicate injection. The validated user-friendly MS-Excel file used to set and access comparison criteria is made available as Supplementary Material and was checked experimentally. However, it is not feasible to estimate model confidence exclusively from experimentation because it would require too much independent analysis.

Optimisation of the uncertainty of oil spill identification from replicate comparative analyses: Comparison of standardised and novel identification methods.

Oil spill identifications involve the comparison of oil fingerprints between the oil spill and suspected oil sources, defined by ratios between the abundances of oil-discriminating compounds, Diagnostic Ratios (DR). The normalised Nordtest and EN 15522-2 methodologies use Student's t statistic (S-t) or a maximum relative difference (SC) to compare mean DR from replicate sample analysis. While the S-t method assumes the normality of DR distribution, the SC method is based on controlled DR dispersion. However, when false, the assumptions and approximations adopted can lead to low true identification rates. This work presents a novel computational tool for the statistically sound oil spill identification that allows following requirements defined by EN 15522-2, the comparison of replicate DR determinations, and the use of different DR sets and formats. The tool uses the Monte Carlo Method (MCM) to describe the probability distribution of the difference of mean DR, allowing estimating the probability of the true acceptance of fingerprints equivalence. The studied methods were applied to the comparison of signals from the same oil and to a real scenario reproduced in an International Round Robin Test. The methods were compared considering the probabilities of true acceptance of oil patterns equivalence based on a single, γ, or various, δ, DR. The MCM method performs identifications with γ equivalent to the defined confidence level for the comparison, P. Since the various DR studied are not perfectly correlated, the δ is below P. The number of replicate analyses performed and the DR considered in the comparison affect identification performance. The S-t produces comparison criteria with a γ lower than P. The SC criteria for duplicate analysis is associated with a δ lower than the obtained by the MCM. A user-friendly MS-Excel spreadsheet is available to perform oil pattern comparisons using various methods and conditions.

Microplastics contamination in sediments from Portuguese inland waters: Physical-chemical characterisation and distribution.

Plastics are the major constituent of waste accumulated in inland waters and subsequently transferred to the ocean. The smaller plastic particles, typically obtained from the fragmentation of larger pieces, are vehicles for food chain accumulation of plastic components and contaminants sorbed to these particles through their ingestion by small organisms. The monitoring of the level and trends of the contamination by microplastics is essential to determine the relevance and potential sources of this contamination necessary to define strategies to reduce this threat. This work presents microplastic contamination levels and trends of sediments of four Portuguese inland waters, namely Ria de Aveiro, Ria Formosa, Mira river, and Mondego river, between 02/2019 and 09/2020. The contamination is classified considering the type of polymer and size, shape, and colour of particles. Polymers are identified by micro-ATR-FTIR with true and false identification rates larger and lower than 95% and 5%, respectively. Duplicate analysis results are used to quantify contamination heterogeneity subsequently applied to assess if a specific contamination trend is not meaningful for a 99% confidence level. The analytical procedure is described in detail to clarify the scope of the analysis. Tests' quality is controlled by following strict quality control measures. Results from sixty-three sediment samples proved the ubiquitous presence of microplastic (MP) in these inland waters with contamination levels ranging between 20 MP kg-1 and 1090 MP kg-1, excluding six samples not contaminated with these particles. Overall, more than 86% of the microplastics were fragments lower than 1000 µm, and 33% were identified as polyethylene or polypropylene. A large diversity of microplastic colours was observed. For the Mondego River and Ria de Aveiro locations monitored for consecutive years, no significant variations of microplastic contamination were observed for a 99% confidence level.