Contaminant Species Research Articles

PV Silicon Recovery for Lithium Ion Battery Anodes

As solar photovoltaic (PV) devices across the globe reach the end of their approximately 30-year lifetimes, an emerging challenge is how to handle the waste from large volumes of end-of-life (EOL) PV modules. It is projected that the cumulative mass of EOL PV modules could be up to 8 million tonnes (Mt) by 2030 so recovery of high value materials from these EOL modules through a cost efficient recycling process would minimize environmental impacts compared to disposing them in landfills[1]. A typical recycling process for EOL PV modules involves mechanical disassembly, separation of the tempered cover glass and silicon wafer followed by purification and recovery of other constituents such as Pb or Ag with the goal of reinstating the recovered materials as a PV module. However, since new module prices continue to decline and the recovered PV modules typically have a shorter lifetime and lower efficiency, the economic value of using the recovered PV materials to manufacture a new PV module is uncertain[2]. Since silicon, particularly boron-doped, is a promising candidate for next-generation anodes for lithium-ion batteries (LIB), recovering the silicon from PV modules for use in LIB anodes could be an attractive alternative. A ball milling process was developed at Oak Ridge National Laboratory to prepare ball milled silicon from washed silicon boules as well as EOL PV modules sourced from a commercial PV module recycler. In this talk we will be discussing the purification process, contaminant removal requirements and key anode performance metrics of recycled PV silicon materials. Organic acid washing with and without microwave-treatment as the heat source was conducted on ball milled boron-doped silicon and reference undoped silicon. The organic acid washing was conducted several times and followed by centrifugation and drying to attempt to remove unwanted contaminant species and compared to a single step microwave-assisted process. The initial carbon species present after ball milling the silicon remained on the ball milled silicon based on FTIR data and the structure of the ball milled silicon was unchanged based on XRD analysis. Elemental analysis and half cells tests were conducted to observe the effect of boron-doping and contaminants inherent to the EoL PV Si material with pristine boron-doped silicon showing noticeably better performance than non-doped ball milled silicon or contaminated silicon PV silicon. Determining the maximum amount of each potential contaminant from PV panels will help facilitate these materials being introduced into local supply chains as a silicon precursor material for more highly engineered silicon anode materials. IRENA, I.-P., End-of-Life Management: Solar Photovoltaic Panels 2016: International Renewable Energy Agency and International Energy Agency Photovoltaic Power Systems.A. Wade, P.S., K. Drozdiak, E. Brutsch. Beyond Waste – The Fate of End-of-Life Photovoltaic Panels from Large Scale PV Installations in the EU. The Socio-Economic Benefits of High Value Recycling Compared to Re-Use. in 33rd European Photovoltaic Solar Energy Conference and Exhibition. 2017.

Active Quantum Biomaterials-Enhanced Microrobots for Food Safety.

Timely disruptive tools for the detection of pathogens in foods are needed to face global health and economic challenges. Herein, the utilization of quantum biomaterials-enhanced microrobots (QBEMRs) as autonomous mobile sensors designed for the precise detection of endotoxins originating from Salmonella enterica (S. enterica) as an indicator species for food-borne contamination globally is presented. A fluorescent molecule-labeled affinity peptide functions as a specific probe, is quenched upon binding to the surface of QBEMRs. Owing to its selective affinity for endotoxin, in the presence of S. enterica the fluorescence is restored and easy to observe and quantifies optical color change to indicate the presence of Salmonella. The devised approach is designed to achieve highly sensitive detection of the S. enterica serovar Typhimurium endotoxin with exquisite selectivity through the utilization of QBEMRs. Notably, no fluorescence signal is observed in the presence of endotoxins bearing similar structural characteristics, highlighting the selectivity of the approach during food sample analysis. Technically, the strategy is implemented in microplate readers to extend microrobots-based approaches to the routine laboratory. This new platform can providefast and anticipated results in food safety.

Unraveling the complex dynamics of temporal moments for multispecies contaminant transport in saturated porous media: A global sensitivity analysis approach

In this study, we focus on the application of global sensitivity analysis (GSA) to gain insight into the influence of model parameters on the outputs of multispecies contaminant transport model. In this context, employing GSA methods (Morris and FAST) allows us to comprehend the relative significance of each input parameter in the model. We specifically analyzed the effects of model parameters on the concentration breakthrough curves and associated temporal moments of concentration of contaminant species. The spatial variability of sensitivity indexes from Morris and FAST methods for parent and daughter contaminant species is also investigated. We represent uncertainties of longitudinal dispersivity, porosity, first-order degradation constants of parent and daughter contaminant species, and sorption distribution coefficient of parent species into the coupled multispecies contaminant transport model and GSA framework. Our results show a complex interplay between different model parameters and their varying influences on different output metrics. The ranking of parameters based on GSA shows that (i) the contaminant mass recovery of final daughter species of three species chain reaction is governed by the first-order degradation coefficient of parent and first daughter species; (ii) dispersivity and porosity are critical parameters that govern the mean residence time and variance of breakthrough curve of final daughter species; (iii) the coefficient of skewness is more sensitive to dispersivity, sorption distribution coefficient, and first-order degradation coefficient of parent species as compared to other model parameters. The variation in the sensitivity indices among contaminant species and with travel distance is observed. This study highlights the significance of global sensitivity analysis when simulating the multiple species contaminants in saturated porous media.

LSTAR — An isobar separator for expanding radioactive ion beam production at the Cyclotron Institute, Texas A&M University

A new isobar separator, LSTAR (Light-ion guide Separator for Texas A&M’s Radioactive ion beams), has been designed to purify the exotic beams produced by a He-driven light-ion guide (He-LIG) system at Texas A&M University, primarily for the TAMUTRAP experiment. The main purpose of TAMUTRAP is to probe for physics beyond the standard model by searching for possible scalar or tensor currents in the weak interaction using nuclear β decay. The proton-rich isotopes of interest for this program will be produced at low yields, requiring efficient reduction of contaminant species to avoid overloading of TAMUTRAP’s radiofrequency quadrupole cooler-buncher. The layout, ion-optics, and specifications of LSTAR will be presented.

Automated Identification of Outgassed Chemical Species Using Mass Spectrometry for Scientific Space Missions

Current and planned space exploration and life detection missions such as NASA Jet Propulsion Laboratory’s Mars 2020, Mars Sample Return, and Europa Clipper require record-low contamination levels. In this work, we develop a novel automated outgassing contamination species identification method using mass spectrometry data. Thanks to the existing knowledge of ASTM-E1559 and direct analysis in real-time mass spectrometry material testing methods, we improved species outgassing deconvolution and physical characterization techniques. We developed a brand-new combined approach that leverages both tests’ complementary insights into contaminants’ chemical identities. Namely, we rely on the Dromey–Foyster algorithm and the Seven Golden Rules of mass spectrometry analysis to narrow down the probable identified molecules by a factor of 10 compared to the sole use of ASTM-E1559. Furthermore, thanks to recent advances in machine learning spectral analysis, we developed a composite spectral score that ranks all candidate contaminants based on their similarity to the measurements. Ultimately, we validated an automated species identification algorithm on samples of NuSil CV4-2946, Dacron, and a spacecraft cable component. The techniques established in this work enable accurate estimations of outgassed contaminant species’ chemical structure, leading to a comprehensive understanding of the effects of outgassing on scientific objectives.

Detection Limits of Insect Fragments in Spiked Whole Wheat Flour Using Multiplex Polymerase Chain Reaction (PCR)

The need for a sensitive molecular method to detect specific species of insect contaminants in food products remains a significant challenge in the food industry. This study evaluated the detection limit of a multiplex end-point PCR assay for detecting insects in food. The assay amplifies two fragments of the cytochrome oxidase subunit I gene (COI-Fa and COI-Fb) and one fragment of the protein-coding wingless (wg) gene found in insects. Five insect species, comprising three vectors of foodborne pathogens (the housefly, Musca domestica, the American cockroach, Periplaneta americana, and the pharaoh ant, Monomorium pharaonis) and two storage insect pests (the red flour beetle, Tribolium castaneum and the Indian meal moth, Plodia interpunctella), were spiked separately and in combination at levels of 1, 0.1, 0.01, and 0.001% in whole wheat flour. At spike levels greater than 0.01%, amplicon bands of expected sizes were seen in 100% of samples containing fragments from distinct insect species. At least 25% of spiked samples at the lowest spike level had amplicon bands, except for samples spiked with M. domestica. Results showed an 18.9% probability (with 11.3% and 30% lower and upper confidence limits, respectively) of detecting insect fragments at the lowest spike level (0.001%, corresponding to 3–22 fragments), which is far below the FDA’s regulatory level of less than 75 fragments per 50 g of wheat flour. The intensity of amplicon bands in the gel images was higher at higher spike levels. However, this method is not quantitative enough to extrapolate the intensity of the amplicon bands to the number of insect fragments present in a sample. This multiplex assay was also evaluated in a variety of market food samples derived from plants and animals, showing its potential use in various food types. Overall, the sensitivity and specificity of this molecular approach suggest that it could be used in the future as a screening tool for detecting insect contaminants in food.

Experimental and theoretical investigation of the treatment of Cu-rich Acid Mine Drainage using iron oxide magnetic nanoparticles

Acid Mine Drainage (AMD) is a significant environmental problem in the mining industry due to its high concentration of hazardous metals and metalloids, sulfate compounds, and low pH levels. Despite the attention that iron oxide magnetic nanoparticles (MNP) have received for AMD remediation, there is still a lack of understanding of the physicochemical mechanisms behind their non-specific adsorption, particularly in distinct variations of AMD, such as Cu-rich AMD. In this study, we synthesized, characterized, and applied MNP to the two-step treatment of Cu-rich AMD. The chemical and physical properties of the MNP and magnetically separated sludges after AMD treatment are characterized. Additionally, the chemical species adsorbed onto the MNP, the oxidation state of the resultant sludge after Cu-rich AMD treatment, and the short-range ordering of metal contaminant species on the surface of the MNP are identified. Finally, first-principles calculations using Density Functional Theory were conducted to understand how different Cu ion species adsorb to the MNP surface depending on the pH of the Cu-rich AMD. The bonding between MNP and Cu species occurs primarily through metal cation-oxygen bonds on the surface of MNP, and this bonding is influenced by the pH of the solution. A combination of experimental and theoretical approaches was the key to arrive at this conclusion. This information can aid in the comprehension of how metal contaminants adhere to the surfaces of MNP and in the precise engineering of these nanoparticles.

Recognition of screening out hierarchical toxic contaminants tuned by quantified pseudo-components from complex engineering co-combustion

Co-combustion of industrial and municipal solid wastes has emerged as the most promising disposal technology, yet its effect on unknown contaminants generation remains rarely revealed due to waste complexity. Hence, six batches of large-scale engineering experiments were designed in an incinerator of 650 t/d, which overcame the inauthenticity and deviation of laboratory tests. 953–1772 non-targeted compounds were screened in fly ash. Targeting the impact of co-combustion, a pseudo-component matrix model was innovatively integrated to quantitatively extract nine components from complex wastes grouped into biomass and plastic. Thus, the influence was evaluated across eight dimensions, covering molecular characteristics and toxicity. The effect of co-combustion with biomass pseudo-components was insignificant. However, co-combustion with high ratios of plastic pseudo-components induced higher potential risks, significantly promoting the formation of unsaturated hydrocarbons, highly unsaturated compounds (DBE≥15), and cyclic compounds by 19 %− 49 %, 17 %− 31 %, and 7 %− 27 %, respectively. Especially, blending with high ratios of PET plastic pseudo-components produced more species of contaminants. Unique 2 Level I toxicants, bromomethyl benzene and benzofuran-2-carbaldehyde, as well as 4 Level II toxicants, were locked, receiving no concern in previous combustion. The results highlighted risks during high proportion plastics co-combustion, which can help pollution reduction by tuning source wastes to enable healthy co-combustion.

Flow cytometry: Unravelling the real antimicrobial and antibiofilm efficacy of natural bioactive compounds

Flow cytometry (FCM) provides unique information on bacterial viability and physiology, allowing a real-time early warning antimicrobial and antibiofilm monitoring system for preventing the spread risk of foodborne disease. The present work used a combined culture-based and FCM approach to assess the in vitro efficacy of essential oils (EOs) from condiment plants commonly used in Mediterranean Europe (i.e., thyme EO, oregano EO, basil EO, and lemon EO) against planktonic and sessile cells of food-pathogenic Listeria monocytogenes 56 LY, and contaminant and alterative species Escherichia coli ATCC 25922 and Pseudomonas fluorescens ATCC 13525. Evaluation of the bacterial response to the increasing concentrations of natural compounds posed FCM as a crucial technique for the quantification of the live/dead, and viable but non-culturable (VBNC) cells when antimicrobial agents exert no real bactericidal action. Furthermore, the FCM results displayed higher numbers of viable bacteria expressed as Active Fluorescent Units (AFUs) with a greater level of repeatability compared with outcomes of the plate-count method. Overall, accurate counting of viable microbial cells is a critically important parameter in food microbiology, and flow cytometry provides an innovative approach with high-throughput potential for applications in the food industry as “flow microbiology”.

Molecular Identification and Subtype Analysis of Blastocystis sp. Isolates from Wild Mussels (Mytilus edulis) in Northern France.

Blastocystis sp. is the most common single-celled eukaryote colonizing the human gastrointestinal tract worldwide. Because of the proven zoonotic potential of this protozoan, sustained research is therefore focused on identifying various reservoirs of transmission to humans, and in particular animal sources. Numerous groups of animals are considered to be such reservoirs due to their handling or consumption. However, some of them, including mollusks, remain underexplored. Therefore, a molecular epidemiological survey conducted in wild mussels was carried out in Northern France (Hauts-de-France region) to evaluate the frequency and subtypes (STs) distribution of Blastocystis sp. in these bivalve mollusks. For this purpose, 100 mussels (Mytilus edulis) were randomly collected in two sampling sites (Wimereux and Dannes) located in the vicinity of Boulogne-sur-Mer. The gills and gastrointestinal tract of each mussel were screened for the presence of Blastocystis sp. by real-time polymerase chain reaction (qPCR) assay followed by direct sequencing of positive PCR products and subtyping through phylogenetic analysis. In parallel, sequences of potential representative Blastocystis sp. isolates that were previously obtained from temporal surveys of seawater samples at marine stations offshore of Wimereux were integrated in the present analysis. By taking into account the qPCR results from all mussels, the overall prevalence of the parasite was shown to reach 62.0%. In total, more than 55% of the positive samples presented mixed infections. In the remaining mussel samples with a single sequence, various STs including ST3, ST7, ST14, ST23, ST26 and ST44 were reported with varying frequencies. Such distribution of STs coupled with the absence of a predominant ST specific to these bivalves strongly suggested that mussels might not be natural hosts of Blastocystis sp. and might rather be carriers of parasite isolates from both human and animal (bovid and birds) waste. These data from mussels together with the molecular identification of isolates from marine stations were subsequently discussed along with the local geographical context in order to clarify the circulation of this protozoan in this area. The identification of human and animal STs of Blastocystis sp. in mussels emphasized the active circulation of this protozoan in mollusks and suggested a significant environmental contamination of fecal origin. This study has provided new insights into the host/carrier range and transmission of Blastocystis sp. and emphasized its potential as an effective sentinel species for water quality and environmental contamination.

Multiple stressors unpredictably affect primary producers and decomposition in a model freshwater ecosystem

Freshwater ecosystems are affected by various stressors, such as contamination and exotic species, making them amongst the most imperilled biological systems on the planet. In Australia and elsewhere, copper is one of the most common metal contaminants in freshwater systems and the European carp (Cyprinus carpio L.) is one of the most pervasive and widespread invasive fish species. Copper (Cu) and carp can both directly affect primary production and decomposition, which are critical and interrelated nutrient cycling processes and ecosystem services. The aim of this study was to explore the direct and indirect effects of Cu and carp individually, and together on periphyton cover, chlorophyll a concentration, growth of the macrophyte Vallisneria spiralis L., and the decomposition of leaf litter and cotton strips in a controlled, factorial experiment in outdoor experimental ponds. In isolation, Cu reduced macrophyte growth and organic matter decomposition, while chlorophyll a concentrations and periphyton cover remained unchanged, possibly due to the Low-Cu concentrations in the overlying water. Carp addition alone had a direct negative effect on the biomass of aquatic plants outside protective cages, but also increased plant biomass inside the cages, periphyton cover and chlorophyll a concentrations. Leaf litter was more decomposed in the carp only ponds compared to controls, while there was no significant effect on cotton strip decomposition. Aquatic plants were absent in the Cu + carp ponds caused by the combined effects of Cu toxicity, carp disturbance and the increase in turbidity due to carp bioturbation. Increases in periphyton cover in Low-Cu + carp, while absence in the High-Cu + carp ponds, and differences in the decomposition of surface and buried cotton strips were not as predicted, which highlights the need for such studies to understand the complex interactions among stressors for environmental risk assessment.

Incubation period of axenic shiitake (Lentinula edodes L.) blocks

Shiitake mushroom (Lentinula edodes) is the most produced mushroom in the world and has a long incubation period, which precedes the productive phase, being the only mushroom produced in axenic blocks, which, after completing the mycelial colonization, initiates the maturation of the mycelium forming a brown cover. Many producers are told that when they find contaminated blocks in their production, they must discard them immediately. On the other hand, producers report that over the fruiting period, some blocks contaminate more than others. The objective of this work is to identify the best incubation period for productivity and occurrence of contaminants. Incubation periods of 70, 80, 90, 100 and 110 days were tested. Production precocity, productivity and biological efficiency, average number and mass of mushrooms, brown cap formation area, number of points of contamination and identification of contaminant species were evaluated. The results obtained show that the best incubation period was 70 days.

Rapid and sensitive detection of genome contamination at scale with FCS-GX

Assembled genome sequences are being generated at an exponential rate. Here we present FCS-GX, part of NCBI’s Foreign Contamination Screen (FCS) tool suite, optimized to identify and remove contaminant sequences in new genomes. FCS-GX screens most genomes in 0.1–10 min. Testing FCS-GX on artificially fragmented genomes demonstrates high sensitivity and specificity for diverse contaminant species. We used FCS-GX to screen 1.6 million GenBank assemblies and identified 36.8 Gbp of contamination, comprising 0.16% of total bases, with half from 161 assemblies. We updated assemblies in NCBI RefSeq to reduce detected contamination to 0.01% of bases. FCS-GX is available at https://github.com/ncbi/fcs/ or https://doi.org/10.5281/zenodo.10651084.

Computation of Particulate Deposition on Dry Storage Canisters

This paper provides an overview of ongoing work aimed at developing spent nuclear fuel (SNF) canister deposition models. Currently, it is known that stainless steel canisters are susceptible to chloride-induced stress corrosion cracking (CISCC). However, the rate of CISCC degradation and the likelihood that it could lead to a through-wall crack is unknown. While it is currently unknown if there is a threshold chloride surface concentration for CISCC initiation, it can be assumed that the onset and progress of material degradation will depend on the local contaminant concentration, the properties of the contaminant species, and the synergistic effects when multiple contaminants are present. This study uses well-developed computational fluid dynamics and particle tracking tools and applies them to SNF storage to determine the rate of deposition on canisters. Understanding the rate of deposition on SNF canisters could be important for making canister aging management predictions. This study is a part of an ongoing effort funded by the U.S. Department of Energy, Office of Nuclear Energy, Office of Spent Fuel and Waste Science and Technology, which is tasked with doing research relevant to enhancing the technical basis for ensuring the safe extended storage and subsequent transport of SNF. This work is being presented to demonstrate a potentially useful technique for SNF canister vendors, utilities, regulators, and stakeholders to utilize and further develop for their own designs and site-specific studies.

Establishment and comparison of in situ detection models for foodborne pathogen contamination on mutton based on SWIR-HSI.

Rapid and accurate detection of food-borne pathogens on mutton is of great significance to ensure the safety of mutton and its products and the health of consumers. The feasibility of short-wave infrared hyperspectral imaging (SWIR-HSI) in detecting the contamination status and species of Escherichia coli (EC), Staphylococcus aureus (SA) and Salmonella typhimurium (ST) contaminated on mutton was explored. The hyperspectral images of uncontaminated and contaminated mutton samples with different concentrations (108, 107, 106, 105, 104, 103 and 102 CFU/mL) of EC, SA and ST were acquired. The one dimensional convolutional neural network (1D-CNN) model was constructed and the influence of structure hyperparameters on the model was explored. The effects of different spectral preprocessing methods on partial least squares-discriminant analysis (PLS-DA), support vector machine (SVM) and 1D-CNN models were discussed. In addition, the feasibility of using the characteristic wavelength to establish simplified models was explored. The best full band model was the 1D-CNN model with the convolution kernels number of (64, 16) and the activation function of tanh established by the original spectra, and its accuracy of training set, test set and external validation set were 100.00, 92.86 and 97.62%, respectively. The optimal simplified model was genetic algorithm optimization support vector machine (GA-SVM). For discriminating the pathogen species, the accuracies of SVM models established by full band spectra preprocessed by 2D and all 1D-CNN models with the convolution kernel number of (32, 16) and the activation function of tanh were 100.00%. In addition, the accuracies of all simplified models were 100.00% except for the 1D-CNN models. Considering the complexity of features and model calculation, the 1D-CNN models established by original spectra were the optimal models for pathogenic bacteria contamination status and species. The simplified models provide basis for developing multispectral detection instruments. The results proved that SWIR-HSI combined with machine learning and deep learning could accurately detect the foodborne pathogen contamination on mutton, and the performance of deep learning models were better than that of machine learning. This study can promote the application of HSI technology in the detection of foodborne pathogens on meat.

Identification of oil palm tissue culture contaminants by using DNA barcodes: preliminary results

The success of oil palm tissue culture is constrained by the microbes contaminating cultures in the laboratory. Accurate identification of contaminant species leads to the right strategies for solving the contamination problem. This research was done to identify contaminant species at the Indonesian Oil Palm Research Institute Tissue Culture Laboratory at its stages by using DNA barcodes. Bacteria identification was done by 16S rRNA sequencing, while fungi identification was done by ITS region sequencing. Preliminary results showed that bacteria and fungi were identified in the laboratory’s stages of the tissue culture process. Four species were identified in the dark room, two in the light room, and four in the advanced light room. The identified bacteria were Bacillus subtilis, Streptococcus parasuis, Priestia megaterium, and Bacillus sp. The identified fungi were Tritirachium candoliense, Penicillium citrinum, Irpex laceratus, Aspergillus reticulatus, and Perenniporia tephropora. More data is needed to determine the right strategies to control the contamination problem.

Arsenic sorption and oxidation by natural manganese-oxide-enriched soils: Reaction kinetics respond to varying environmental conditions

Manganese-oxides are some of the strongest oxidants and sorbents in the environment, which impact many geochemical processes. However, nearly all our understanding of manganese-oxides’ reaction kinetics is based on laboratory-synthesized minerals. This study quantifies the oxidative kinetics and adsorptive capacity of five soils rich in pedogenic manganese- and iron-oxides through arsenite oxidation batch reactions over a range of pHs and temperatures to mimic diverse environmental conditions. The two A horizons were less reactive and enriched in manganese(IV), compared to the B horizons, particularly the subsoil containing the manganese-rich wad material. The reaction kinetics fit a pseudo-first-order reaction with distinct fast and slow phases. The baseline reactions were pH 7.2 at 23 °C. Adjusting pH to 4.5 or 9.0 increased the reaction rates. Decreasing the temperature to 4.0 °C reduced the reaction kinetics, while raising the temperature to 40 °C increased the arsenite oxidation rate. pH and temperature changes alter the reaction kinetics due to shifts related to the point of zero charge, the total system energy, and surface passivation from adsorbing arsenic and manganese species. Synchrotron X-ray fluorescence mapping indicates arsenic only penetrates the surficial layers of most manganese-oxide-containing nodules found in the soil. After the arsenite oxidation reaction in the pedogenically weathered subsoil, X-ray absorption spectroscopy demonstrates significant differences in the average manganese oxidation number between the nodules’ outer layers compared to the soil matrix and nodule centers. The kinetic and sorption parameters give critical insight into determining the mobility and species of arsenic and other redox-sensitive contaminants in manganese-containing environmental systems over appropriate timescales.

Pharmaceutical residues in stranded dolphins in the Bay of Biscay

There is a growing concern about the presence of pharmaceuticals on the aquatic environment, while the marine environment has been much less investigated than in freshwater. Marine mammals are suitable sentinel species of the marine environment because they often feed at high trophic levels, have unique fat stores and long lifespan. Some small delphinids in particular serve as excellent sentinel species for contamination in the marine environment worldwide. To the best of our knowledge, no pharmaceuticals have been detected or reported in dolphins so far.In the present study, muscle, liver and blubber samples from three common dolphins (Delphinus delphis) and seven striped dolphins (Stenella coeruleoalba) stranded along the Basque Coast (northern Spain) were collected. A total of 95 pharmaceuticals based on detectability and predicted ability to bioaccumulate in fish were included in the liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis.At least one pharmaceutical was found in 70 % of the individuals. Only three of the 95 monitored pharmaceuticals were detected in dolphin's tissues. Very low concentrations (<1 ng/g) of orphenadrine and pizotifen were found in liver and promethazine in blubber.Herein, the gap in the knowledge regarding the study organisms and marine environments with respect to pharmaceutical pollution, which demands further research to understand if pharmaceuticals are a threat for these apex predators, is highlighted and discussed.

Metals and microorganisms in a Maar lake sediment core indicating the anthropogenic impact over last 800 years

A closed Maar lake, receiving mostly atmospheric deposition, offers a unique setting for investigating the impact of human activities on the environment. In this study, we aimed to investigate the historical record of metals in core sediments of Maar Lake in Huguangyan (HGY), Southeast China, and elucidate the possible microbial responses to anthropogenic metal stress. Five stages were divided according to the historical record of metals and corresponding distribution of microbial community, among which Pb and Sn showed a peak value around 1760 CE, indicating the ancient mining and smelting activities. Since the 1980s, a substantial enrichment of metals such as Zn, As, Mo, Cd, Sn, Sb, and Pb was observed, due to the rapid industrial growth in China. In terms of microorganisms, Chloroflexi phylum, particularly dominated by Anaerolineales, showed significant correlations with Pb and Sn, and could potentially serve as indicator species for mining and smelting-related contamination. Desulfarculales and Desulfobacterales were found to be more prevalent in recent period and exhibited positive correlations with anthropogenic metals. Moreover, according to the multivariate regression modeling and variance decomposition analysis, Pb and Sn could regulate Anaerolineales and further pose impact on the carbon cycle; while sulfate-reducing bacteria (SRB) could response to anthropogenic metals and influence sulfur cycle. These findings provide new insights into the interaction between metals and microbial communities over human history.

Duration Effects of Shrimp Paste Storage on ALT of Mold Colonies: Variations by Brand and Pre-Standard Treatment

Shrimp paste is a commonly employed condiment or flavoring in culinary preparations. As a result of the nutrients present in shrimp paste, fungi and other microbial contaminants are able to proliferate and develop on the paste. This study aims as follows: 1) to determine ALT measurements of mold colonies to assess the quality of two brands of pre-treated shrimp paste; and 2) to identify contaminating mold species present in steamed and unsteamed shrimp paste prior to storage. Descriptive quantitative and qualitative research methods were employed within the Biology Department of FMIPA UM's Microbiology Laboratory. A series of three samplings were conducted on treated shrimp paste brands A and B, one week apart between each sampling. A volume of 90 ml of 0.1% peptone water was used to dissolve 10 grams of shrimp paste, resulting in a dilution of 10-1; this process was repeated until the dilution reached 10-5. 0. The surface of PDA (Potato Dextrose Agar) medium was inoculated with 1 ml of suspension from each dilution. The medium was subsequently incubated at a temperature of 25oC for 7x24 hours. The findings of this study indicate the following: 1) At the 28th day of storage, both brands of shrimp paste that underwent treatment with steamed and unsteamed shrimp paste remained of acceptable quality for human consumption. 2) In steamed and unsteamed shrimp paste, thirteen species of mold contaminants were identified: Chrysosporium corda, Cladosporium sphaerospermum, Penicillium frequentans, Penicillium chrysogenum, Rhizoctonia sp1., Aspergillus candidus, Fusarium equeseti, Colletotrichum ti, Moniliella acetobutens, and Rhizoctonia sp3