Predicting the Site-Specific Toxicity of Metals to Fishes Using a New Machine Learning-Based Approach.

Fishes of various trophic levels play an important role in the stability and balance of aquatic ecosystems. Metal contaminants can impair the survival and population fitness of fish at elevated concentrations. When universal water quality criteria (WQC) of metals are adopted to protect different species in different geographic regions, they may not adequately protect all fish due to a lack of consideration for site-specific environmental conditions and species assemblages.

Nanobubble and Slow-Release Hydrogen Delivery Methods for Interfacial Remediation of Copper-Induced Toxicity in Aquatic Environments.

Heavy metal pollution poses a serious threat to aquatic environments, requiring effective strategies to mitigate its harmful effects. Hydrogen molecules have shown potential in alleviating oxidative stress caused by heavy metals; however, delivering hydrogen in water remains challenging. In this study, four hydrogen delivery methods, namely, hydrogen water without nanobubbles (NBs), hydrogen NB water, nanosilicon, and sodium alginate-coated nanosilicon gel microspheres, were evaluated for their ability to protect zebrafish embryos from copper ion-induced toxicity.

Metal-based nanoparticles in natural aquatic environments: concentrations, toxic effects and kinetic processes.

Metal-based nanoparticles (MNPs) are widely used in many aspects of production and life, resulting in their detection in various types of aquatic environments globally with mass concentrations mostly in the range of ng/L-μg/L. Therefore, more attention should be paid to considering realistic situations and exposure scenarios at environmentally relevant MNPs concentrations. With the support of new technology and methods, the environmental concentration distribution of MNPs in the aquatic environment was investigated and sorted out.

Pollutant distribution in vertebrates across scales: Organs, cells, and organelles.

Pollutant accumulation patterns are essential for understanding their toxicity mechanisms and health risks. Accurately identifying pollutant accumulation sites and toxicity targets requires an integrated understanding of their distribution across multiple scales. This review systematically examines recent advances in the multi-scale distribution of environmental pollutants in vertebrates, spanning organ, cellular, and subcellular levels.

Decorative cosmetics and skin care products contribute significantly to short-chain perfluoroalkyl carboxylates exposure.

Research on dermal exposure of per- and polyfluoroalkyl substances (PFAS) in personal care products is limited. Here, we investigated the permeation of 14 PFAS using in vitro 3D-human skin equivalents (3D-HSE). Results revealed that perfluorobutanoic acid (PFBA) exhibited the highest cumulative permeation, while perfluorotetradecanoic acid (PFTeDA) showed the lowest.

Binding of per- and polyfluoroalkyl substances with liver and serum proteins in rats: implications for physiologically based pharmacokinetic modelling.

Understanding the binding between per- and polyfluoroalkyl substances (PFAS) and proteins is essential for elucidating their toxicokinetics and tissue distribution. Here, we quantified the binding affinities of 14 PFAS to rat liver fatty acid-binding protein (rL-FABP) and rat serum albumin (RSA). Results showed that PFAS exhibit strong binding affinities (K) to the rL-FABP (10 ∼ 10 M), particularly among medium- to long-chain perfluorinated carboxylic acids (PFCAs).

Methodological Study on Determination of Recombinant Adeno-Associated Virus Particle Titer Through Size Exclusion Chromatography with Multiangle Light Scattering and Collaborative Calibration of Standard Substances.

Adeno-associated virus (AAV) is a promising gene therapy vector due to its high transduction efficiency, low pathogenicity, low immunogenicity, and the ability to mediate the long-term stable expression of exogenous genes. The viral particle titer is an essential quality attribute of recombinant adeno-associated virus (rAAV) gene therapy products. Multiangle light scattering (MALS) is an important means of directly measuring the absolute molecular weight and distribution of macromolecular drugs.

Removal of Nickel-Citrate by KOH-Modified Arundo donax L. Biochar: Critical Role of Persistent Free Radicals.

Removal of heavy metal complexes (HMCs) from wastewater poses significant challenges to waste water treatment due to the inherent stability of these compounds. In this study, KOH modified Arundo donax L. leaves biochar was developed, which demonstrated a remarkable capacity for nickel-citrate (Ni-Cit) removal.

Modelling the size distribution and bioaccumulation of gold nanoparticles under mixture exposure.

To assess the bioaccumulation and toxicity of nanoparticles (NPs), analyzing and modelling the relationship between the size distribution of NPs in organisms and the exposure particle size distribution represents an important challenge. Previous studies mostly focused on the NPs with single size. However, the size distribution of NPs is wide and variable in the natural environment.

Mitigating environmental toxicity with hydrogen nanobubbles: A mitochondrial function-based approach to ecological restoration.

In biological systems, nanobubbles (NBs) effectively enhance hydrogen molecule retention and scavenging reactive oxygen species (ROS), but the underlying mechanisms remain elusive. To investigate this, we prepared hydrogen NB water samples with consistent dissolved hydrogen levels but varying NB densities to explore their physicochemical properties and effects on green algae (Chlorella vulgaris) under oxidative stress induced by copper ions (Cu) and cadmium ions (Cd). The results indicated a strong correlation between the hydrogen NB number density and the 25 % inhibitory concentration of Cu over 24 h, with ROS removal efficiency increased with the NB number density.

Using the super-learner to predict the chemical acute toxicity on rats.

With the rapid increase in the number of commercial chemicals, testing methods regarding on median lethal dose (LD) relying animal experiments face challenges such as high costs and ethical concerns. Classical quantitative structure-activity relationship models relying on single algorithm always lack interpretability and precision, given the complexity of the mechanisms underlying acute toxicity. To address these issues, this study has developed a predictive framework using an ensemble learning model based on Super-learner.

Application of Machine Learning in Nanotoxicology: A Critical Review and Perspective.

The massive production and application of nanomaterials (NMs) have raised concerns about the potential adverse effects of NMs on human health and the environment. Evaluating the adverse effects of NMs by laboratory methods is expensive, time-consuming, and often fails to keep pace with the invention of new materials. Therefore, methods that utilize machine learning techniques to predict the toxicity potentials of NMs are a promising alternative approach if regulatory confidence in them can be enhanced.

Alleviative effects of C fullerene nanoparticles on arsenate transformation and toxicity to Danio rerio.

Widely-used C fullerene nanoparticles (C) result in their release into the aquatic environment, which may affect the distribution and toxicity of pollutants such as arsenic (As), to aquatic organism. In this study, arsenate (As(V)) accumulation, speciation and subcellular distribution was determined in Danio rerio (zebrafish) intestine, head and muscle tissues in the presence of C. Meanwhile we compared how single-walled carbon nanotubes (SWCNTs), multi-walled carbon nanotubes (MWCNTs), graphene oxide (GO) and graphene (GN) nanoparticles alter the behaviors of As(V).

Hydrogen nanobubbles and oxidative windows: Investigating how varying hydrogen concentrations influence seed germination and stress defense.

The hydrogen molecule can effectively regulate plant growth and development, improving plant resistance to abiotic stresses. However, studies regarding the optimal concentration of hydrogen and the associated mechanisms of action in organisms are lacking. This study showed that the maximum germination rate of radish seeds decreased from 90 % to 50 % under the stress of cadmium ions (Cd), and hydrogen nanobubble (NB) water significantly alleviated the stress effect of Cd on radish seed germination.

Strong cation-exchange combined with mass spectrometry reveals the glycoform heterogeneity of sialylated glycoproteins.

Sialylation is an important modification of proteins, related to protein life and bioactivity. However, the evaluation of sialylation is only based on the average molecular composition by peptide mapping and glycan profiling because sialylated proteins are usually too heterogeneous to obtain good quality mass spectra by conventional intact mass analysis methods. In this study, a simple strong cation exchange-mass spectroscopy (SCX-MS) method was developed for intact mass analysis of sialylated glycoproteins.

Methodological Validation of Sedimentation Velocity Analytical Ultracentrifugation Method for Adeno-Associated Virus and Collaborative Calibration of System Suitability Substance.

Currently, adeno-associated virus (AAV) is one of the primary gene delivery vectors in gene therapy, facilitating long-term gene expression. Despite being imperative, it is incredibly challenging to precisely assess AAV particle distribution according to the sedimentation coefficient and identify impurities related to capsid structures. This study performed the systematic methodological validation of quantifying the AAV empty and full capsid ratio.

Generation and utilization of endostatin-sensitive cell lines for assessing the biological activity of endostatin.

Recombinant proteins are gaining increasing popularity for treating human diseases. The clinical effectiveness of recombinant proteins is directly related to their biological activity, which is an important indicator in drug development and quality control. However, certain recombinant proteins have unclear or complex signal pathways, making detecting their activity in vitro difficult.

Aging effects of titanium dioxide on Cu toxicity to Daphnia magna: Exploring molecular docking and significance of surface properties.

Cosmetics and personal care products containing titanium dioxide nanoparticles (TiO NPs) may enter aquatic environments, where the surface coatings of TiO NPs may change with aging due to environmental factors such as light, and potentially affect their bioaccumulation and toxicity. This study examined how aging impacted the physicochemical properties of three commercially available TiO NPs and subsequent influence on the bioaccumulation and toxicity of copper (Cu) in Daphnia magna (D. magna).

Investigating spectroscopic and copper binding characteristics of dissolved organic matter in wastewater using EEMs with two-dimensional Savitzky-Golay second-order differentiation-PARAFAC.

Dissolved organic matter (DOM) in wastewater interacts with heavy metal particles in aquatic environments, which changes their dynamics and bioavailability. For quantifying the DOM, an excitation-emission matrix (EEM) paired alongside parallel factor analysis (PARAFAC) is typically employed. However, a drawback of PARAFAC has been revealed in recent studies, i.

[Application of automatic injection device based on automatic hemostasis in injection of radiopharmaceutical bolus injection].

In clinical practice, radiopharmaceutical dynamic imaging technology requires the bolus injection method to complete injection. Due to the failure rate and radiation damage of manual injection, even experienced technicians still bear a lot of psychological burden. This study combined the advantages and disadvantages of various manual injection modes to develop the radiopharmaceutical bolus injector, and explored the application of automatic injection in the field of bolus injection from four aspects: radiation protection, occlusion response, sterility of injection process and effect of bolus injection.

Integrating ultra-high-performance liquid chromatography tandem mass spectrometry and imaged capillary isoelectric focusing for in-depth characterization of complex fusion proteins.

Rationale: Fc-fusion proteins represent a successful class of biopharmaceutical products, which combine the tailored pharmacological properties of biological ligands with the multiple functions of the fragment crystallizable domain of immunoglobulins. There is great diversity in terms of possible biological ligands creating highly diverse structures, therefore the analytical characterization of fusion proteins is far more complex than that of monoclonal antibodies and requires the use and development of additional product-specific methods over conventional generic/platform methods.

Methods: Employing etanercept analogues as studied fusion proteins, the Orbitrap mass analyzer with ultra-high performance liquid chromatography (UHPLC-MS) and imaged capillary isoelectric focusing (icIEF) were utilized for the in-depth fusion protein characterization.

Using Machine Learning to Predict Adverse Effects of Metallic Nanomaterials to Various Aquatic Organisms.

The wide production and use of metallic nanomaterials (MNMs) leads to increased emissions into the aquatic environments and induces high potential risks. Experimentally evaluating the (eco)toxicity of MNMs is time-consuming and expensive due to the multiple environmental factors, the complexity of material properties, and the species diversity. Machine learning (ML) models provide an option to deal with heterogeneous data sets and complex relationships.

Water Quality Criteria and Ecological Risk Assessment of Typical Transition Metals in South Asia.

Transition metal pollution in rivers in South Asia is more serious than in other regions because of the lack of adequate freshwater management measures. Water quality criteria (WQC) for South Asia is urgently needed to protect regional aquatic environments because of the occurrence of transboundary rivers. The present study established non-parametric kernel density estimation species sensitivity distribution (NPKDE-SSD) models and then derived the acceptable hazardous concentration for protection of 95% of all aquatic species (HC5) and WQC of six typical transition metals in South Asia.

Nano-TiO modifies heavy metal bioaccumulation in Daphnia magna: A model study.

Due to special properties, nano-TiO will interact with heavy metals and other pollutants in water, thus affecting the environmental behavior and ecotoxicity of these pollutants. However, the exact manner in which nano-TiO affects the bioaccumulation mechanisms of heavy metals is still unclear now. In the present study, quantitative structure bioaccumulation relationship (QSBAR) models were established to explore the relationships between physicochemical parameters of heavy metals and their accumulation in Daphnia magna in the absence and presence of nano-TiO at low metal exposure concentrations.