Biological Systems Research Articles

Study of lump and periodic waves along with rogue waves and breathers for mathematical modeling of biological dynamical system

Globally, infectious diseases pose a significant threat. Notable cases include influenza, Hepatitis B and HIV. COVID-19, caused by the coronavirus, has been the subject of recent discussion due to its great transmissibility. This study explores the Susceptible–Infectious–Recovered (SIR) epidemic model, explaining several analytical approaches to comprehend the nonlinear incident rates and geographic dispersion. The model investigates phenomena such as M-shaped solitons, homoclinic breather-like solitons, lump waves (LWs), lump solution (LS) with one or two kinks, rogue waves (RWs), periodic waves (PWs) and periodic cross-kink waves. These solutions aid in understanding the disease spread and informing containment strategies by identifying optimal outbreak control methods. This work studies localized wave solutions in nonlinear wave equations, known as soliton solutions including the LS. RWs are characterized by unexpectedly large amplitude and rapid profile changes, drawing attention for their erratic features. PWs exhibit periodic repetitions over time and space. Besides, some type of solitons with special waveforms are the periodic cross-kink, M-shaped and homoclinic breather-like solitons. Graphical representation visualizes the behavior of these effective waves, providing insights into virus spread in specific regions over time. SIR models help identify optimal strategies for controlling outbreaks. The work adds to our understanding of epidemic dynamics by illuminating how the movement of susceptible and infected individuals affects the spread of disease.

Mott memristor based stochastic neurons for probabilistic computing.

Many studies suggest that probabilistic spiking in biological neural systems is beneficial as it aids learning and provides Bayesian inference-like dynamics. If appropriately utilised, noise and stochasticity in nanoscale devices can benefit neuromorphic systems. In this paper, we build stochastic spiking neurons, a stochastic leaky integrate and fire(LIF) neuron and a probabilistic sigmoid neuron, utilising a Mott memristor's inherent stochastic switching dynamics. We demonstrate that the developed LIF neuron is capable of biological neural dynamics. We leverage these characteristics of the proposed LIF neuron by integrating it into a population-coded spiking neural network, thereby showcasing its ability to implement probabilistic learning and inference. We also utilise the probabilistic sigmoid neuron to implement a Spiking Restricted Boltzmann Machine (sRBM) that achieves a software-comparable accuracy of 85.56\%. Unlike CMOS-based probabilistic neurons, our design does not require any external noise sources. The designed neurons are highly energy efficient and ultra-compact, requiring only three components: a resistor, a capacitor and a memristor device.

Recent advances in understanding the neurobiology of pediatric functional neurological disorder.

Functional neurological disorder (FND) is a neuropsychiatric disorder that manifests in a broad array of functional motor, sensory, or cognitive symptoms, which arise from complex interactions between brain, mind, body, and context. Children with FND make up 10%-20% of presentations to neurology services in children's hospitals and up to 20% of adolescents admitted to hospital for the management of intractable seizures. The current review focuses on the neurobiology of pediatric FND. The authors present an overview of the small but growing body of research pertaining to the biological, emotion-processing, cognitive, mental health, physical health, and social system levels. Emerging research suggests that pediatric FND is underpinned by aberrant changes within and between neuron-glial (brain) networks, with a variety of factors - on multiple system levels - contributing to brain network changes. In pediatric practice, adverse childhood experiences (ACEs) are commonly reported, and activation or dysregulation of stress-system components is a frequent finding. Our growing understanding of the neurobiology of pediatric FND has yielded important flow-on effects for assessing and diagnosing FND, for developing targeted treatment interventions, and for improving the treatment outcomes of children and adolescents with FND.

RASP: Optimal Single Puncta Detection in Complex Cellular Backgrounds.

Super-resolution and single-molecule microscopies have been increasingly applied to complex biological systems. A major challenge of these approaches is that fluorescent puncta must be detected in the low signal, high noise, heterogeneous background environments of cells and tissue. We present RASP, Radiality Analysis of Single Puncta, a bioimaging-segmentation method that solves this problem. RASP removes false-positive puncta that other analysis methods detect and detects features over a broad range of spatial scales: from single proteins to complex cell phenotypes. RASP outperforms the state-of-the-art methods in precision and speed using image gradients to separate Gaussian-shaped objects from the background. We demonstrate RASP's power by showing that it can extract spatial correlations between microglia, neurons, and α-synuclein oligomers in the human brain. This sensitive, computationally efficient approach enables fluorescent puncta and cellular features to be distinguished in cellular and tissue environments, with sensitivity down to the level of the single protein. Python and MATLAB codes, enabling users to perform this RASP analysis on their own data, are provided as Supporting Information and links to third-party repositories.

Breathing Planet Earth: Analysis of Keeling’s Data on CO2 and O2 with Respiratory Quotient (RQ), Part II: Energy-Based Global RQ and CO2 Budget

For breathing humans, the respiratory quotient (RQ = CO2 moles released/O2 mols consumed) ranges from 0.7 to 1.0. In Part I, the literature on the RQ was reviewed and Keeling’s data on atmospheric CO2 and O2 concentrations (1991–2018) were used in the estimation of the global RQ as 0.47. A new interpretation of RQGlob is provided in Part II by treating the planet as a “Hypothetical Biological system (HBS)”. The CO2 and O2 balance equations are adopted for estimating (i) energy-based RQGlob(En) and (ii) the CO2 distribution in GT/year and % of CO2 captured by the atmosphere, land, and ocean. The key findings are as follows: (i) The RQGlob(En) is estimated as 0.35 and is relatively constant from 1991 to 2020. The use of RQGlob(En) enables the estimation of CO2 added to the atmosphere from the knowledge of annual fossil fuel (FF) energy data; (ii) The RQ method for the CO2 budget is validated by comparing the annual CO2 distribution results with results from more detailed models; (iii) Explicit relations are presented for CO2 sink in the atmosphere, land, and ocean biomasses, and storage in ocean water from the knowledge of curve fit constants of Keeling’s curves and the RQ of FF and biomasses; (iv) The rate of global average temperature rise (0.27 °C/decade) is predicted using RQGlob,(En) and the annual energy release rate and compared with the literature data; and (v) Earth’s mass loss in GT and O2 in the atmosphere are predicted by extrapolating the curve fit to the year 3700. The effect of RQGlob and RQFF on the econometry and policy issues is briefly discussed.

An easy to use tool for the analysis of subcellular mRNA transcript colocalisation in smFISH data

Single molecule fluorescence in situ hybridisation (smFISH) has become a valuable tool to investigate the mRNA expression of single cells. However, it requires a considerable amount of programming expertise to use currently available open-source analytical software packages to extract and analyse quantitative data about transcript expression. Here, we present FISHtoFigure, a new software tool developed specifically for the analysis of mRNA abundance and co-expression in QuPath-quantified, multi-labelled smFISH data. FISHtoFigure facilitates the automated spatial analysis of transcripts of interest, allowing users to analyse populations of cells positive for specific combinations of mRNA targets without the need for computational image analysis expertise. As a proof of concept and to demonstrate the capabilities of this new research tool, we have validated FISHtoFigure in multiple biological systems. We used FISHtoFigure to identify an upregulation in the expression of Cd4 by T-cells in the spleens of mice infected with influenza A virus, before analysing more complex data showing crosstalk between microglia and regulatory B-cells in the brains of mice infected with Trypanosoma brucei brucei. These analyses demonstrate the ease of analysing cell expression profiles using FISHtoFigure and the value of this new tool in the field of smFISH data analysis.

Global Solution and Stability of a Haptotaxis Mathematical Model for Complex MAP

A critical function of polymeric matrices in biological systems is to exert selective control over the transport of thousands of nanoparticulate species. Utilizing “third-party” molecular anchors to crosslink nanoparticulates to the matrix is an effective strategy, and a trapped nanoparticulate formed a desired complex MAP that is necessary to keep the nanoparticulate immobilized at any given time. In this paper, the global solution and stability of a parabolic–ordinary-parabolic haptotaxis system to complex MAP are studied. First, the existence of a local classical solution to system () has been observed using fixed point argument and parabolic Schauder estimates. Furthermore, some a priori estimates that can raise the regularity estimate of the solution for the relatively complicated first equation of system () from Lρ to L2ρ (ρ≥1) are given; then, the local classic solution can thus extend to the global classic solution when the space dimension N≤3. Lastly, by using various analytical methods, a threshold value ξ00(ξ00<0) is found, such that positive constant steady state (u*,v*,w*) becomes unstable when ξ<ξ00. Our results show that the haptotaxis plays a crucial role in determining the stability to the model (), that is, it can have a destabilizing effect.

Evaluation of the Lipophilicity of Angularly Condensed Diquino- and Quinonaphthothiazines as Potential Candidates for New Drugs.

Lipophilicity is one of the most important properties of compounds required to estimate the absorption, distribution, and transport in biological systems, in addition to solubility, stability, and acid-base nature. It is crucial in predicting the ADME profile of bioactive compounds. The study assessed the usefulness of computational and chromatographic methods (thin-layer chromatography in a reversed-phase system, RP-TLC) for estimating the lipophilicity of 21 newly synthesized compounds belonging to diquinothiazines and quinonaphthiazines. In order to obtain reliable values of the relative lipophilicities of diquinothiazines and quinonaphthiazines, the partition coefficients obtained using different algorithms such as AlogPs, AClogP, AlogP, MLOGP, XLOGP2, XLOGP3, logP, and ClogP were compared with the chromatographic RM0 values of all the tested compounds measured by the experimental RP-TLC method (logPTLC). Additionally, logPTLC values were also correlated with other descriptors, as well as the predicted ADME and drug safety profiling parameters. The linear correlations of logPTLC values of the tested compounds with other calculated molecular descriptors such as molar refractivity, as well as ADME parameters (Caco-2 substrates, P-gp inhibitors, CYP2C19, and CYP3A4) generally show poor predictive power. Therefore, in silico ADME profiling can only be helpful at the initial step of designing these new candidates for drugs. The compliance of all discussed diquinothiazines and naphthoquinothiazines with the rules of Lipiński, Veber, and Egan suggests that the tested pentacyclic phenothiazine analogs have a chance to become therapeutic drugs, especially orally active drugs.

Modeling Zinc Complexes Using Neural Networks.

Understanding the energetic landscapes of large molecules is necessary for the study of chemical and biological systems. Recently, deep learning has greatly accelerated the development of models based on quantum chemistry, making it possible to build potential energy surfaces and explore chemical space. However, most of this work has focused on organic molecules due to the simplicity of their electronic structures as well as the availability of data sets. In this work, we build a deep learning architecture to model the energetics of zinc organometallic complexes. To achieve this, we have compiled a configurationally and conformationally diverse data set of zinc complexes using metadynamics to overcome the limitations of traditional sampling methods. In terms of the neural network potentials, our results indicate that for zinc complexes, partial charges play an important role in modeling the long-range interactions with a neural network. Our developed model outperforms semiempirical methods in predicting the relative energy of zinc conformers, yielding a mean absolute error (MAE) of 1.32 kcal/mol with reference to the double-hybrid PWPB95 method.

Synaptic Plasticity and Visual Memory in a Neuromorphic 2D Memitter Based on WS2 Monolayers

AbstractNeuromorphic computing aims to leverage physical phenomena of adaptive materials for emulating information processing capabilities and effectiveness of biological neuronal circuits. In this framework, memristors (resistors with memory) based on 2D materials are demonstrated for the hardware implementation of highly integrated artificial neural networks. All the works reported thus far exploited electrical properties of 2D materials to emulate neuromorphic functionalities. Here, a 2D memitter (emitter with memory) is reported on that exploits the stimuli‐responsive photoluminescence of a monolayer WS2 for neuromorphic‐type of data processing. A combined experimental and modeling approach reveals that photoluminescent dynamics triggered by optical stimulation emulates Short‐Term synaptic Plasticity and Visual Short‐Term Memory typical of biological systems. While spatio‐temporal processing capabilities of input signals can be used for information processing in the context of reservoir computing, the capability of the 2D memitter of sensing, processing, and memorizing‐forgetting optical inputs in the same physical substrate can be utilized for in‐sensor computing.

Fluorescent Protein-Based Sensors for Detecting Essential Metal Ions across the Tree of Life.

Genetically encoded fluorescent metal ion sensors are powerful tools for elucidating metal dynamics in living systems. Over the last 25 years since the first examples of genetically encoded fluorescent protein-based calcium indicators, this toolbox of probes has expanded to include other essential and non-essential metal ions. Collectively, these tools have illuminated fundamental aspects of metal homeostasis and trafficking that are crucial to fields ranging from neurobiology to human nutrition. Despite these advances, much of the application of metal ion sensors remains limited to mammalian cells and tissues and a limited number of essential metals. Applications beyond mammalian systems and in vivo applications in living organisms have primarily used genetically encoded calcium ion sensors. The aim of this Perspective is to provide, with the support of historical and recent literature, an updated and critical view of the design and use of fluorescent protein-based sensors for detecting essential metal ions in various organisms. We highlight the historical progress and achievements with calcium sensors and discuss more recent advances and opportunities for the detection of other essential metal ions. We also discuss outstanding challenges in the field and directions for future studies, including detecting a wider variety of metal ions, developing and implementing a broader spectral range of sensors for multiplexing experiments, and applying sensors to a wider range of single- and multi-species biological systems.

Engineered and Mimicked Extracellular Nanovesicles for Therapeutic Delivery.

Exosomes are spherical extracellular nanovesicles with an endosomal origin and unilamellar lipid-bilayer structure with sizes ranging from 30 to 100 nm. They contain a large range of proteins, lipids, and nucleic acid species, depending on the state and origin of the extracellular vesicle (EV)-secreting cell. EVs' function is to encapsulate part of the EV-producing cell content, to transport it through biological fluids to a targeted recipient, and to deliver their cargos specifically within the aimed recipient cells. Therefore, exosomes are considered to be potential biological drug-delivery systems that can stably deliver their cargo into targeted cells. Various cell-derived exosomes are produced for medical issues, but their use for therapeutic purposes still faces several problems. Some of these difficulties can be avoided by resorting to hemisynthetic approaches. We highlight here the uses of alternative exosome-mimes involving cell-membrane coatings on artificial nanocarriers or the hybridization between exosomes and liposomes. We also detail the drug-loading strategies deployed to make them drug-carrier systems and summarize the ongoing clinical trials involving exosomes or exosome-like structures. Finally, we summarize the open questions before considering exosome-like disposals for confident therapeutic delivery.

Biosynthesis of vitamin B3 and NAD+ - incubating HepG2 cells with the alkaloid Myosmine.

In the 'kynurenine pathway', it is reported that essential amino acid tryptophan (TRP) forms nicotinic acid (NA, vitamin B3) in biological systems. This pathway is part of the 'de novo pathway' to perform the nicotinamide adenine dinucleotide (NAD+)-biosynthesis. Additionally, biosynthesis of the NAD+ via the 'Preiss-Handler pathway' involves NA and its analogue nicotinamide (NAM) both designated as niacin. Previous attempts were successfully to convert MYO by organic synthesis to NA and assumption was, the alkaloid myosmine (MYO), which is in taken from food, can be converted into NA by biological oxidation. In the present study, incubation of HepG2 cells with MYO yielded NA. Moreover, a significant increase of NAD+ compared to the control has been found. Hence MYO could be assumed to be the hitherto unknown origin of an alternative NA-biosynthesis additionally influencing NAD+-biosynthesis positively. This novel MYO-pathway may open new perspectives to improve knowledge and relevance of NA and NAD+-biosynthesis and bioactivation in cells and moreover in food staples, food and diet. This article is protected by copyright. All rights reserved.

An Expanded Palette of Fluorescent COS/H2S-Releasing Donors for H2S Delivery, Detection, and In Vivo Application.

Hydrogen sulfide (H2S) is an important reactive sulfur species that is involved in many biological functions, and H2S imbalances have been indicated as a potential biomarker for various diseases. Different H2S donors have been developed to deliver H2S directly to biological systems, but few reports include donors with optical responses that allow for tracking of H2S release. Moreover, donor systems that use the same chemistry to deliver H2S across a palette of fluorescent responses remain lacking. Here we report five thiol-activated fluorescence turn-on COS/H2S donors that utilize blue, yellow, orange, red, and near infrared-emitting dyes functionalized with an H2S-releasing sulfenyl thiocarbonate scaffold. Upon treatment with thiols, each donor provides a fluorescence turn-on response (3-310-fold) and high H2S release efficiencies (>60%). Using combined electrode and fluorescence experiments, we directly correlate the measured H2S release with the fluorescence response. All donors are biocompatible and release H2S in live cell environments. In addition, we demonstrate that the NIR donor allows for imaging H2S release in live rats via subcutaneous injection of the donor loaded into an alginate gel, which to the best of our knowledge is the first in vivo tracking of H2S release from a fluorogenic donor in non-transparent organisms.

An Expanded Palette of Fluorescent COS/H2S‐Releasing Donors for H2S Delivery, Detection, and In Vivo Application

Hydrogen sulfide (H2S) is an important reactive sulfur species that is involved in many biological functions, and H2S imbalances have been indicated as a potential biomarker for various diseases. Different H2S donors have been developed to deliver H2S directly to biological systems, but few reports include donors with optical responses that allow for tracking of H2S release. Moreover, donor systems that use the same chemistry to deliver H2S across a palette of fluorescent responses remain lacking. Here we report five thiol‐activated fluorescence turn‐on COS/H2S donors that utilize blue, yellow, orange, red, and near infrared‐emitting dyes functionalized with an H2S‐releasing sulfenyl thiocarbonate scaffold. Upon treatment with thiols, each donor provides a fluorescence turn‐on response (3–310‐fold) and high H2S release efficiencies (>60%). Using combined electrode and fluorescence experiments, we directly correlate the measured H2S release with the fluorescence response. All donors are biocompatible and release H2S in live cell environments. In addition, we demonstrate that the NIR donor allows for imaging H2S release in live rats via subcutaneous injection of the donor loaded into an alginate gel, which to the best of our knowledge is the first in vivo tracking of H2S release from a fluorogenic donor in non‐transparent organisms.

Abstract LB193: Enhanced single cell DNA methylation analysis using combinatorial indexing

Abstract The epigenetic landscape of the human brain undergoes a plethora of changes during malignant transformation. In recent years, DNA methylation-based epigenetic modifications have been widely studied using traditional techniques like bisulfite sequencing and enzymatic methyl sequencing (EM-seq). However, these methods analyze bulk cell populations and lack the granularity of single-cell analysis. Although advances in single-cell analysis have revolutionized our understanding of cellular heterogeneity and functional diversity within complex biological systems, they are still costly, low throughput, and laborious. To address these challenges, ScaleBio has pioneered combinatorial indexing technology, enabling a significant increase in cell throughput. This method utilizes the cell itself as a compartment to perform 2-3 rounds of sequential barcoding in a plate-based workflow, eliminating the need for complex instrumentation. This technology has been successfully adapted to assess DNA methylation at the single-cell level offering a robust, affordable, high-throughput protocol that enhances yield, diversity, and coverage. In this study we used ScaleBio's single-cell methylation kit to investigate DNA methylation patterns during oncogenesis using cancer cells with widespread DNA methylation changes, such as human isocitrate dehydrogenase (IDH) mutant glioma cells at the single-cell level. The IDH gene family, comprising of IDH1, IDH2, and IDH3, encodes enzymes involved in the tricarboxylic acid (TCA) cycle. IDH1/2 mutations are present in over 80% of low-grade gliomas while IDH-mutant gliomas constitute about 1/5th of all adult diffuse gliomas, thus making them one of the most common brain tumor subtypes. As such, IDH mutations have emerged as attractive therapeutic targets for glioma treatment. By uncovering DNA methylation patterns at the single cell level, we provide here an epigenetic map to better understand this complex disease and better inform clinical discoveries. We achieved high cell recovery and robust cytosine coverage throughout our analysis of single cell methylomes isolated from human glioma tumor tissue. Using this data we generated a ranked list of the top hypo- and hypermethylated genomic regions and identified cell type specific clusters seen in different pathological states by looking at Differentially Methylated Regions (DMR) uncovering unique single-cell methylation profiles that may be obscured by bulk or pseudo-bulk analysis. These data show that the ScaleBio single-cell methylation workflow offers increased sensitivity, specificity, and accuracy in identifying DNA methylation sites when compared to other techniques while offering a comprehensive view of methylomes and providing insights into cellular heterogeneity and trajectories. Citation Format: Sanika Khare, Dominic Skinner, Maggie Nakamoto, Hosu Sin, Ashley Woodfin, Eric Pu, Lin Lin, Jason Koth, Beth Walczak. Enhanced single cell DNA methylation analysis using combinatorial indexing [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB193.

Edge-based relative entropy as a sensitive indicator of critical transitions in biological systems

BackgroundDisease progression in biosystems is not always a steady process but is occasionally abrupt. It is important but challenging to signal critical transitions in complex biosystems.MethodsIn this study, based on the theoretical framework of dynamic network biomarkers (DNBs), we propose a model-free method, edge-based relative entropy (ERE), to identify temporal key biomolecular associations/networks that may serve as DNBs and detect early-warning signals of the drastic state transition during disease progression in complex biological systems. Specifically, by combining gene‒gene interaction (edge) information with the relative entropy, the ERE method converts gene expression values into network entropy values, quantifying the dynamic change in a biomolecular network and indicating the qualitative shift in the system state.ResultsThe proposed method was validated using simulated data and real biological datasets of complex diseases. The applications show that for certain diseases, the ERE method helps to reveal so-called “dark genes” that are non-differentially expressed but with high ERE values and of essential importance in both gene regulation and prognosis.ConclusionsThe proposed method effectively identified the critical transition states of complex diseases at the network level. Our study not only identified the critical transition states of various cancers but also provided two types of new prognostic biomarkers, positive and negative edge biomarkers, for further practical application. The method in this study therefore has great potential in personalized disease diagnosis.

A Siderophore Mimicking Gelation Component for Capturing and Self-Separation of Fe(III) from an Aqueous Solution of Mixture of Metal Ions.

The carbohydrazide-based gelation component N2,N4,N6-(1,3,5-triazine-2,4,6-triyl)tris(benzene-1,3,5-tricarbohydrazide) (CBTC) was synthesized and characterized using various spectroscopic tools. CBTC and trimesic acid (TMA) get self-assembled to form metallogel with Fe3+, specifically through various noncovalent interactions in a DMSO and H2O mixture. The self-assembly shows remarkable specificity toward Fe(III) among different transition metal salts. It is pertinent to point out that the binding specificity for Fe3+ can also be found in nature in the form of siderophores, as they are mainly involved in scavenging iron selectively from the surroundings. DFT studies have been used to investigate the possible interaction between the different components of the iron metallogel. To determine the selectivity of CBTC for iron, CBTC, along with trimesic acid, is used to interact with other metal ions, including Fe(III) ions, in a single system. The gelation components CBTC and TMA selectively bind with iron(III), which leads to the formation of metallogel and gets separated as a discrete layer, leaving the other metal ions in the solution. Therefore, CBTC and TMA together show iron-scavenging properties. This selective scavenging property is explored through FE-SEM, XPS, PXRD, IR, and ICP-AES analysis. The FE-SEM analysis shows a flower-petal-like morphology for the Fe(III) metallogel. The resemblance in the CBTC-TMA-Fe metallogel and metallogel obtained from the mixture of different metal salts is established through FE-SEM images and XPS analysis. The release of iron from the metallogel is achieved with the help of ascorbic acid, which converts Fe3+ to Fe2+. In biological systems, iron also gets released similarly from siderophores. This is the first report where the synthesized gelation component CBTC molecule is capable of scavenging out iron in the form of metallogel and self-separating from the aqueous mixture in the presence of various other metal ions.

Visualization of the hepatic and renal cell uptake and trafficking of tetrahedral DNA origami in tumour.

DNA nanostructures, known for their programmability, ease of modification, and favourable biocompatibility, have gained widespread application in the biomedical field. Among them, Tetrahedral DNA Origami (TDOs), as a novel DNA nanostructure, possesses well-defined structures, multiple modification sites, and large cavities, making it a promising drug carrier. However, current understanding of TDOs' interactions with biological systems, particularly with target cells and organs, remains unexplored, limiting its further applications in biomedicine. In this work, we prepared TDOs with an average particle size of 40 nm and labelled them with Cy5 fluorescent molecules. Following intravenous injection in mice, the uptake of TDOs by different types of liver and kidney cells was observed. Results indicated that TDOs accumulate in renal tubules and are metabolized by Kupffer cells, epithelial cells, and hepatocytes in the liver. Additionally, in a tumour-bearing mouse model, TDOs passively targeted tumour tissues and exhibited excellent tumour penetration and retention after rapid metabolism in hepatocytes. Our findings provide crucial insights for the development of TDO-based drug delivery systems.

The influence of cation exchange on the possible mechanism of erionite toxicity: A synchrotron-based micro-X-ray fluorescence study on THP-1-derived macrophages exposed to erionite-Na

Fibrous erionite is the only zeolite classified as Group 1 carcinogen by the International Agency for Research on Cancer (IARC). Carcinogenesis induced by erionite is thought to involve several factors as biopersistence, the iron role and cation exchange processes. To better understand these mechanisms, a detailed investigation at the micro scale was performed, collecting elemental information on iron and cation release and their distribution in biological systems by synchrotron micro-X-ray fluorescence mapping (SR-micro-XRF) and synchrotron micro-X-ray absorption spectroscopy (SR-micro-XANES) at the TwinMic beamline (Elettra synchrotron) and at the ID21 beamline of the European Synchrotron Radiation Facility (ESRF). By microscopy and chemical mapping, highly detailed maps of the chemical and morphological interaction of biological systems with fibres could be produced. In detail, THP-1 cell line derived macrophages, used as in vitro model, were analysed during erionite-Na phagocytosis at different time intervals, after single dose exposure. For comparison, cellular fluorescent probes were also used to evaluate the intracellular free sodium and calcium concentrations. Synchrotron analyses visualised the spatial distribution of both fibre and mineral particle associated metals during the phagocytosis, describing the mechanism of internalisation of erionite-Na and its accessory mineral phases. The intracellular distribution of metals and other cations was mapped to evaluate metal release, speciation changes and/or cation exchange during phagocytosis. The fluorescent probes complemented microchemical data clarifying, and confirming, the cation distribution observed in the SR-micro-XRF maps. The significant cytoplasmic calcium decrease, and the concomitant sodium increase, after the fibre phagocytosis seemed due to activation of plasma membrane cations exchangers triggered by the internalisation while, surprisingly, the ion-exchange capacity of erionite-Na could play a minor role in the disruption of the two cations intracellular homeostasis. These results help to elucidate the role of cations in the toxicity of erionite-treated THP-1 macrophages and add knowledge to its carcinogenicity process.