Real-time automated behavioural monitoring of mussels during contaminant exposures using an improved microcontroller-based device

Comparative Investigation of the Spectroscopic Behavior Based on High-Concentrated Solution in Nitrogen and Air Atmospheres

In order to accurately obtain photometric information of high concentration SO42- and other substances in the process industry, the spectroscopy behavior of SO42-, S2-, Ni2+ and Cu2+ in air and nitrogen atmosphere was compared based on the UV-visible spectrophotometer with a nitrogen replacing the oxygen. Different from Ni2+ and Cu2+, the accuracy of SO42- and S2- in the ultraviolet region was effectively improved by using a nitrogen atmosphere (P detection results were regressed within the limited standard range, RE < 5%). The nitrogen atmosphere suppressed the additional light attenuation caused by its absorption of ultraviolet rays by isolating oxygen and was also reflected in the decrease in the degree of red shift of the characteristic wavelength for SO42- with increasing concentration. Therefore, the detection results of SO42- showed an effective improvement in sensitivity. Nevertheless, according to the complementary experimental results and theoretical calculations, in addition to oxygen absorption, the low detection accuracy of SO42- high concentration is also attributed to the reduction of the energy required for electronic excitation per unit group caused by the interaction between SO42- groups, resulting in a deviation of the C-A curve from linearity at high concentrations. The influence of this intermolecular force on the detection results is far more important than oxygen absorption. The research can provide reliable theoretical guidance and technical support for the pollution-free direct measurement of high-concentration solutions in the process industry and promote the sustainable development of the process industry.

Using valve gape analysis to compare sensitivity of native Mytilus edulis to invasive Magallana gigas when exposed to heavy metal contamination

Coastal ecosystems are ecologically and economically important but are under increasing pressure from numerous anthropogenic sources of stress. Both heavy metal pollution and invasive species pose major environmental concerns that can have significant impacts on marine organisms. It is likely that many stresses will occur simultaneously, resulting in potential cumulative ecological effects. The aim of this study was to compare the relative resilience of an invasive oyster Magallana gigas and a native mussel Mytilus edulis to heavy metal pollution, utilising their valve gape response as an indicator. The gape activity of bivalves has been utilised to monitor a range of potential impacts, including for example oil spills, increased turbidity, eutrophication, heavy metal contamination etc. In this study, Hall effect sensors were used on both the native blue mussel (M. edulis) and the pacific oyster (M. gigas), invasive to Ireland. Mussels were shown to be more responsive to pollution events than oysters, where all heavy metals tested (copper, cadmium, zinc, lead) had an effect on transition frequency though significant differences were only observed for lead and cadmium (Control; > Copper, p = 0.0003; >lead, p = 0.0002; >Cadmium, p = 0.0001). Cadmium had an apparent effect on mussels with specimens from this treatment remaining closed for an average of 45.3% of the time. Similarly, significant effects on the duration of time mussels spent fully open was observed when treated with lead and cadmium (Control; > lead, p = 0.03, > cadmium, p = 0.02). In contrast, oysters displayed no significant difference for any treatment for number of gapes, or duration spent open or closed. Though there was an effect of both zinc and copper on the amount of time spent closed, with averages of 63.2 and 68.7% respectively. This indicates oysters may be potentially more resilient to such pollution events; further boosting their competitive advantage. Future mesocosm or field studies are required to quantify this relative resilience.

The molecular mechanisms of cuproptosis and its relevance to cardiovascular disease

Recently, cuproptosis has been demonstrated to be a new non-apototic cell death mode that is characterized by copper dependence and the regulation of mitochondrial respiration. Cuproptosis is distinct from known cell death modes such as apoptosis, necrosis, pyroptosis, or ferroptosis. Excessive copper induces cuproptosis by promoting protein toxic stress reactions via copper-dependent anomalous oligomerization of lipoylation proteins in the tricarboxylic acid (TCA) cycle and reducing iron-sulfur cluster protein levels. Ferredoxin1 (FDX1) promotes dihydrolipoyl transacetylase (DLAT) lipoacylation and abates iron-sulfur cluster proteins by reducing Cu²⁺ to Cu⁺, inducing cell death. Copper homeostasis depends on the copper transporter, and disturbances to this homeostasis cause cuproptosis. Recent evidence has shown that cuproptosis plays a significant role in the occurrence and development of many cardiovascular diseases, such as myocardial ischemia/reperfusion (I/R) injury, heart failure, atherosclerosis, and arrhythmias. Copper chelators, such as ammonium tetrathiomolybdate(VI) and DL-Penicillamine, may ease the above cardiovascular diseases by inhibiting the cuproptosis pathway. Oxidative phosphorylation inhibitors may inhibit cuproptosis by inhibiting protein stress response. In conclusion, cuproptosis plays an essential role in cardiovascular disease pathogenesis. Inhibition of cardiovascular cuproptosis is expected to become a potential treatment. Here, we will thoroughly review the molecular mechanisms involved in cuproptosis and its significance in cardiovascular disease.

Single and combined potential of polystyrene microparticles and fluoranthene in the induction of DNA damage in haemocytes of Mediterranean mussel (Mytilus galloprovincialis)

In this study, the possible 'vector effect' within the exposure of Mediterranean mussels (Mytilus galloprovincialis) to polystyrene microplastics with adsorbed fluoranthene was investigated by applying the multibiomarker approach. The major focus was placed on genotoxicological endpoints as to our knowledge there are no literature data on the genotoxicity of polystyrene microparticles alone or with adsorbed fluoranthene in the selected experimental organisms. DNA damage was assessed in haemocytes by comet assay and micronucleus test. For the assessment of neurotoxicity, acetylcholinesterase activity was measured in gills. Glutathione S-transferase was assessed in gills and hepatopancreas since these enzymes are induced for biotransformation and excretion of lipophilic compounds such as hydrocarbons. Finally, differences in physiological response within the exposure to polystyrene particles, fluoranthene, or particles with adsorbed fluoranthene were assessed by the variation of heart rate patterns studied by the noninvasive laser fibre-optic method. The uniform response of individual biomarkers within the exposure groups was not recorded. There was no clear pattern in variation of acetylcholinesterase or glutathione S-transferase activity which could be attributed to the treatment. Exposure to polystyrene increased DNA damage which was detected by the comet assay but was not confirmed by micronucleus formation. Data of genotoxicity assays indicated differential responses among the groups exposed to fluoranthene alone and fluoranthene adsorbed to polystyrene. Change in the heart rate patterns within the studied groups supports the concept of the Trojan horse effect within the exposure to polystyrene particles with adsorbed fluoranthene.

Elucidating the consequences of the co-exposure of microplastics jointly to other pollutants in bivalves: A review

The marine environment has numerous impacts related to anthropogenic activities including pollution. Abundances of microplastics (MPs) and other pollutants are continuously increasing in the marine environment, resulting in a complex mixture of contaminants affecting biota. In order to understand the consequences, a review of studies analyzing combined effects of MPs and other types of pollutants in bivalves has been conducted as species in this group have been considered as sentinel and bioindicators. Regarding studies reviewed, histological analyses give evidence that MPs can be located in the haemolymph, gills and gonads, as well as in digestive glands in the intestinal lumen, epithelium and tubules, demonstrating that the entire body of bivalves is affected by MPs. Moreover, DNA strand breaks represent the most relevant form of damage caused by the enhanced production of reactive oxygen species in response to MPs exposure. The role of MPs as vectors of pollutants and the ability of polymers to adsorb different compounds have also been considered in this review highlighting a high variability of results. In this sense, toxic impacts associated to MPs exposure were found to significantly increase with the co-presence of antibiotics or petroleum hydrocarbons amongst other pollutants. In addition, bioaccumulation processes of pollutants (PAHs, metals and others) have been affected by the co-presence with MPs. Histological, genetic and physiological alterations are the most reported damages, and the degree of harm seems to be correlated with the concentration and size of MP and with the type of pollutant.

Socioeconomic Appraisal of an Early Prevention System against Toxic Conditions in Mussel Aquaculture

Simple Summary

In order to mitigate the destructive effects of the occurrence of toxic conditions on mussel farming, an automated early prevention system against such conditions was installed. The analysis in this paper demonstrates that the investment is highly profitable and can contribute to achieving broader socioeconomic benefits at the local and regional level.

Abstract

This paper examines the financial viability and potential socioeconomic effects of introducing and operating an automated, remote-controlled management system for mussel farms which uses probes of temperature, dissolved oxygen, and conductivity associated with prediction software to demonstrate the potential need for mussel movement between marine areas. This system provides an early warning to farmers regarding the presence of toxins in aquatic ecosystems, thus contributing to saving mussel production and avoidikng significant economic losses. The analysis combines two established methodological tools in agricultural economics (linear programming and cost-benefit analysis) and provides estimates of the Net Present Value of the investment under two scenarios—one reflecting the existing situation and one a possible future situation where the mussel production system is expanded. The results of the analysis reveal the mid- and long-term effects of using the automated system, both of which demonstrate that the system is economically viable even if it contributes to saving mussel production from toxicity occurrence for only one year during its period of operation. The annual gross margin in the first scenario was €386,069 but almost tripled in the second scenario (€1,154,649). In addition, the future development and expansion of the mussel sector will likely be based on larger farms with an entrepreneurial and exporting orientation where risk mitigation systems, such as the one appraised in this paper, can play an important role.

IR-Based Novel Device for Real-Time Online Acquisition of Fish Heart ECG Signals

We developed an infrared (IR)-based real-time online monitoring device (US Patent No: US 10,571,448 B2) to quantify heart electrocardiogram (ECG) signals to assess the water quality based on physiological changes in fish. The device is compact, allowing us to monitor cardiac function for an extended period (from 7 to 30 days depending on the rechargeable battery capacity) without function injury and disturbance of swimming activity. The electrode samples and the biopotential amplifier and microcontroller process the cardiac-electrical signals. An infrared transceiver transmits denoised electrocardiac signals to complete the signal transmission. The infrared receiver array and biomedical acquisition signal processing system send signals to the computer. The software in the computer processes the data in real time. We quantified ECG indexes (P-wave, Q-wave, R-wave, S-wave, T-wave, PR-interval, QRS-complex, and QT-interval) of carp precisely and incessantly under the different experimental setup (CuSO₄ and deltamethrin). The ECG cue responses were chemical-specific based on CuSO₄ and deltamethrin exposures. This study provides an additional technology for noninvasive water quality surveillance.

A Low-Cost Multi-Sensor Data Acquisition System for Fault Detection in Fused Deposition Modelling

Fused deposition modelling (FDM)-based 3D printing is a trending technology in the era of Industry 4.0 that manufactures products in layer-by-layer form. It shows remarkable benefits such as rapid prototyping, cost-effectiveness, flexibility, and a sustainable manufacturing approach. Along with such advantages, a few defects occur in FDM products during the printing stage. Diagnosing defects occurring during 3D printing is a challenging task. Proper data acquisition and monitoring systems need to be developed for effective fault diagnosis. In this paper, the authors proposed a low-cost multi-sensor data acquisition system (DAQ) for detecting various faults in 3D printed products. The data acquisition system was developed using an Arduino micro-controller that collects real-time multi-sensor signals using vibration, current, and sound sensors. The different types of fault conditions are referred to introduce various defects in 3D products to analyze the effect of the fault conditions on the captured sensor data. Time and frequency domain analyses were performed on captured data to create feature vectors by selecting the chi-square method, and the most significant features were selected to train the CNN model. The K-means cluster algorithm was used for data clustering purposes, and the bell curve or normal distribution curve was used to define individual sensor threshold values under normal conditions. The CNN model was used to classify the normal and fault condition data, which gave an accuracy of around 94%, by evaluating the model performance based on recall, precision, and F1 score.