Platinum speciation in the presence of natural organic matter in a simplified freshwater medium investigated using HPSEC-ICP-MS.

Environmental context Platinum is a metal of emerging concern in ecotoxicology, mainly due to its dissemination in the environment through the abrasion of car catalysts. However, its aqueous speciation in natural waters remains poorly known, and its binding to organic matter may modify its effects on organisms. Experimental measurements revealed the complex chemistry of Pt, low complexation and very slow kinetics. The use of PtII would be recommended for chronic exposure experiments. Rationale It is a common consensus that the free ion concentration of a metal in an aqueous medium can be a good indicator of its toxicity. In this context, the ability to determine metal speciation is of paramount importance to evaluate possible effect on aquatic ecosystems. Although speciation can be predicted for well-studied metals, the task is difficult when little information on thermodynamic constants is available, as is the case for platinum. It is then necessary to turn to experimental methods. Methodology For this purpose, a high-performance size exclusion liquid chromatography method coupled with inductively coupled plasma–mass spectrometry for online metal detection was used. In a synthetic freshwater medium, we first explored the inorganic speciation of platinum (added as PtIV) at pH 5 and 6, and using three equilibration periods (4 min, 48 h and 1 week). We then tested two different conditions with freshwater natural organic matter (NOM) from four different origins, both expected to provide different levels of complexation: low (pH = 5; [NOM] = 3 mg C L−1) and high (pH = 6; [NOM] = 10 mg C L−1). Results Several inorganic forms of platinum (PtII and PtIV) were identified, with good separation and repeatability. In the absence of NOM, dissociation of [PtIVCl6]2− complexes was clearly more important at pH 5 than at pH 6. Also, [PtIVCl6]2− persisted over time, even after 1 week, even though this redox form is believed to be unstable in these conditions, suggesting that thermodynamic equilibrium was not reached. Discussion Weak complexation by NOM was observed, and the initial form of [PtIVCl6]2− persisted. However, the presence of NOM resulted in the formation of additional Pt inorganic species. These unidentified peaks, which were relatively more abundant at high NOM levels, were interpreted as intermediate species between [PtIVCl6]2− and Pt–MON complexes

Machine learning and statistical approaches for wind speed estimation at partially sampled and unsampled locations; review and open questions.

Wind resource assessment (WRA) depends on the availability of accurate, long-term wind speed data. In locations where such data is limited (partially sampled locations, PSL) or completely missing (unsampled locations, USL), various physical, statistical, and machine-learning methods have been developed to address these gaps. This paper presents a comprehensive and up-to-date review of statistical and machine-learning methods for estimating long-term wind speed at PSLs and USLs. It was found that the “Measure Correlate Predict” (MCP) is still the method of choice for estimation at PSL. However, this approach has evolved with the adoption of machine learning, especially Artificial Neural Networks, and reanalysis wind data as the reference site. In general, reanalysis datasets have seen growing adoption for WRA at both PSLs and USLs due to their global coverage, high temporal resolution, and demonstrated accuracy. At USLs, uncorrected and bias-corrected reanalysis wind speed data are used for WRA, with the Global Wind Atlas predominantly used to correct reanalysis wind speed data. There is also a growing effort to develop machine learning models, including deep learning models for reanalysis bias correction at USLs using explanatory variables derived from high-resolution topographic and land use datasets. Challenges to estimating long-term wind speed at PSLs and USLs are identified and discussed: data uncertainties, disparity in the accuracy of reanalysis wind data, model transferability, and nonstationary conditions. Finally, recommendations for future research and development directions are presented, including techniques that consider documented non-stationarity in wind speed data

Brain penetration of peripheral extracellular vesicles from Alzheimer's patients and induction of microglia activation

Alzheimer's disease (AD) is an age-related neurodegenerative pathology. Brain-derived extracellular vesicles (EVs) have been demonstrated to be implicated in AD pathogenesis by facilitating the propagation of Tau, amyloid-β and inflammatory cytokines. However, the impact of peripheral EVs (pEVs) in AD pathogenesis remains poorly investigated. The objective of our study was to compare the passage of pEVs from adults, cognitively healthy elderly, and AD patients through the blood-brain barrier (BBB), to evaluate their uptake in the brain and to assess their impact on the microglia activity using in vitro and in vivo models. To this end, pEVs were enriched, characterized, and fluorescently labelled. The passage of pEVs through the endothelial bEnd.3 cells was studied in a Transwell device with either neuronal or microglia cells seeded at the bottom of the well. Following the internalization of pEVs from AD patients, microglia adopted an amoeboid morphology and released a heightened level of pro-inflammatory cytokine IL-6. To further assess their in vivo transport across the BBB, pEVs were injected into the blood circulation of 2-days post-fertilization Tg(flk1:EGFP) zebrafish. The biodistribution of pEVs was monitored at 1 and 24 h post-injection using confocal microscopy. We demonstrated that pEVs traverse the BBB by transcytosis and subsequently diffuse progressively into the brain. pEVs were then internalized by neuronal and radial glial cells as seen in Tg(huc:EGFP) and Tg(gfap:EGFP) zebrafish, respectively. Additional experiments were performed with the intrahippocampal injection of pEVs in the mouse, indicating their spreading throughout the brain and their uptake by neuronal and glial cells. These findings contribute to novel insights into the fate of pEVs following their passage through the BBB in vitro and in vivo, and demonstrate for the first time that pEVs from AD patients affect microglia activity. This suggests a potential mechanism through which peripheral tissue cues may contribute to AD pathogenesis.</br

Environmental DNA (eDNA) Quantitative Polymerase Chain Reaction‐Based Assays for Surveying 125 Taxa of Importance to North America.

Timely and accurate assessment of the presence of at‐risk or invasive species is critical for effective responses to climate change and human impacts. For example, at‐risk species are often difficult to find, while invasive species are often well established before their infiltration is detected using conventional surveying methods. However, all organisms release genetic material such as DNA into their surroundings, leaving traces of themselves that can be detected using environmental DNA (eDNA) methods. These approaches are powerful tools in the conservation toolbox, as they are transforming how risk assessments and the evaluation of mitigation and remediation effectiveness are done. Despite this, poorly performing tools hinder broad adoption of eDNA‐based detection methods, due in part to their associated high false negatives and false positives that can impair effective management decision‐making. iTrackDNA is a multi‐year, large‐scale applied research project that is addressing these concerns with researchers and end users from various sectors across North America. It is building end‐user capacity through innovative, accessible, socially responsible genomics‐based analytical eDNA tools for effective decision‐making by publishing 125 quantitative real‐time polymerase chain reaction (qPCR) primer/probe sets designed to detect key invertebrates, fish, amphibians, birds, reptiles, and mammals in coastal and inland ecosystems important to North America, with an emphasis on Canada. These 125 assays were designed to meet or exceed the new Canadian Standards Association (CSA) consensus‐based and multi‐stakeholder national standards for eDNA (CSA W214:21 and CSA W219:23). Herein, we describe how we applied eDNA assay design and validation approaches across a wide range of animal taxa to achieve compliance

Compound thermal indices for two species of salmonids.

Water temperature is a determinant variable for the overall health of the river ecosystem and aquatic biota, particularly for cold-water fish. Therefore, the characterization of river temperature is essential for the management of thermal habitats. However, currently, river thermal regime characterization is often achieved by calculating numerous thermal indices that are not often related to cold-water fish physiological requirements and thermal preferences. In this study, we developed a compound thermal index (CTI) based on a methodology used to calculate the water quality index (WQI) in Canada. CTI is composed of specific indicators related to the thermal tolerance thresholds for different life stages for two cold-water species (Atlantic salmon and brook trout), providing a simplified measure of the quality of the thermal habitat for these species. CTI was determined in two salmon/trout rivers in Québec, Canada (Ouelle and Ste-Marguerite). The results showed that (i) CTI allowed the characterization and classification of thermal habitat quality; (ii) the thermal habitat degradation was primarily influenced by climate conditions, particularly during warm and dry years with high temperatures and low precipitations; (iii) the improved thermal habitat quality was associated with air temperature and precipitation values close to seasonal normals; (iv) cold tributaries provided excellent thermal habitats

Nesquehonite Precipitation Kinetics in an MSMPR Crystallizer of the MgO–CO₂–H₂O System Issued from Activated Serpentine Carbonation.

For the first time, continuous nesquehonite precipitation was investigated. The context of this study is indirect aqueous carbonation. The precipitation was operated in a mixed suspension-mixed product removal (MSMPR) crystallizer. The investigated temperature was 40 °C, but the study also covered 50, 60, and 65 °C for comparison purposes. In a continuous mode, the nesquehonite grains obtained are a perfect spherical assemblage of needles instead of the individual needles usually obtained in batch mode. During precipitations in the MSMPR crystallizer, growth dispersion was noticed when supersaturation values were greater than 20. Growth dispersion is attributed to the high density of dislocation screw sites induced by high supersaturation. Meanwhile, for the idealized MSMPR tests, the linear growth rate varied from 1.11 × 10–8 to 2.22 × 10–7 m·s–1. Volumetric growth rates varied from 5.13 × 10–17 to 2.63 × 10–15 m3·s–1. Primary nucleation varied from 8.06 × 1004 and 7.02 × 1005 number·m–3·s–1. Finally, the agglomeration kernel varied from 3.38 × 10–11 to 6.94 × 10–8 m3·number–1·s–1. The growth of the crystals is a limited transport growth. It is also found that agglomeration suppresses primary nucleation. In addition, agglomeration is negatively affected by high solid density due to attrition

Real-Time Moving Vehicle Counting and Speed Estimation Toward Efficient Traffic Surveillance.

This paper presents a Spatial-Temporal Diagram (STD) algorithm for real-time vehicle counting and speed estimation in camera-based traffic surveillance. The algorithm consists of four main steps: STD graph generation highlighting vehicles as peaks, graph refinement using Gaussian Mixture Model likelihood optimization, peak detection through RANdom SAmple Consensus model fitting, and traffic parameter computation. Testing on over 11 million video frames from diverse sources, including 511 highway cameras, NVIDIA AI City Challenge, and Next Generation Simulation datasets, demonstrated the algorithm’s robustness across varying illumination, weather conditions, and road infrastructures. The algorithm achieved average accuracies of 95.4%, 96.9%, and 96.1% for Precision, Recall, and F1-Score, respectively, outperforming traditional deep learning methods while requiring less computational resources

Implementation of an adaptive laboratory evolution strategy for improved production of valuable microbial secondary metabolites

Microbial surface-active agents, such as rhamnolipids, represent an attractive substitute for synthetic surfactants. However, current production bioprocesses are generally inefficient. Adaptive laboratory evolution strategies could offer a promising avenue to improve secondary metabolites production. In the bacterium Burkholderia thailandensis, the social behaviour called swarming motility relies on biosynthesis of rhamnolipids. Since experimental swarming requires lower agar concentrations, we hypothesized that augmenting the agar concentration would constrain the cells to produce more rhamnolipids. Consecutive rounds of B. thailandensis cultivation on swarming media performed with increasing agar concentrations enhanced rhamnolipid production by the evolved populations, with a correlation between rhamnolipid production and agar concentrations. Whole-genome sequencing of superior producing evoluants revealed inactivating mutations in qsmR, which codes for a transcriptional regulator not known to influence rhamnolipid production. Results indicate that QsmR represses rhamnolipid biosynthetic genes transcription. The developed directed evolution strategy could be used to improve biosurfactant yields with other producing bacteria. </br

Bacterial protein secretion systems: Mechanisms, functions, and roles in virulence

Bacterial secretion systems are molecular nanomachines that mediate host-pathogen interactions, antibiotic resistance, and bacterial survival in diverse environments. This review offers a comprehensive overview of the major bacterial protein transport systems, including conserved export pathways (Sec and Tat) and specialized multi-component secretion machineries (type I-XI). These systems mediate the secretion of diverse substrates, such as toxins, adhesins, and enzymes, essential for bacterial virulence, immune evasion, and interbacterial competition. Special emphasis has been given to the injectisome-like secretion systems because of their effective functions in host manipulation, immune evasion, and interbacterial competition. Moreover, recently described T9SS to T11SS are addressed in detail to understand their evolutionary adaptation and biological functions. This review also discusses how environmental cues and stress responses regulate secretion systems, with special emphasis on their relevance to bacterial survival, fitness, and pathogenesis. Despite major advances, the use of multiple secretion systems and full functionality of T11SS in bacterial communities are not well understood. Elucidation of the molecular mechanisms of bacterial secretion can change the face of strategies against infections, preserving beneficial microbiota. Future research should focus on deciphering the regulatory networks controlling secretion systems, particularly the interplay between stress response pathways and secretion activity. </br

Immunological and Toxicological Assessment of Triterpenoid Saponins Bearing Lewis-X- and QS-21-Based Trisaccharides

The search for safer and more effective vaccine adjuvants has intensified in recent years, with triterpenoid saponins like QS-21 and its analogues emerging as promising candidates. We report the synthesis of a novel QS-21 analogue featuring betulinic acid as aglycone, a lupane-type triterpenoid with low toxicity derived from white birch bark. Two convergent synthetic routes, involving different protecting groups and glycosyl donors (bromide and trichloroacetimidate), were optimized to construct the QS-21-based linear trisaccharide motif critical for adjuvant activity. This strategy also enabled efficient preparation of the structurally similar echinocystic acid analogue reported by Gin. The immunological and toxicological profiles of these chimeric saponins, along with Lewis-X-containing and rhamnose-modified derivatives, were evaluated in C57BL/6 wild-type and hDC-SIGN transgenic mice. While the synthetic saponins exhibited low toxicity in vitro and in vivo, replacing echinocystic acid with betulinic acid reduced immunogenicity when tested with ovalbumin as a model antigen compared to alhydrogel and QS-21. These findings provide a foundation for developing saponin-based adjuvants and demonstrate the utility of advanced glycosylation strategies for synthesizing complex unnatural triterpenoid saponins.</br