Variety Of Interactions Research Articles

Uncovering bacterial-mammalian cell interactions via single-cell tracking

BackgroundThe interactions between bacterial pathogens and host cells are characterized by a multitude of complexities, leading to a wide range of heterogeneous outcomes. Despite extensive research, we still have a limited understanding of how bacterial motility in complex environments impacts their ability to tolerate antibiotics and adhere to mammalian cell surfaces. The challenge lies in unraveling the complexity of these interactions and developing quantitative microscopy approaches to predict the behavior of bacterial populations.ResultsTo address this challenge, we directed our efforts towards Pseudomonas aeruginosa, a pathogenic bacterium known for producing thick films in the lungs of cystic fibrosis patients, and Escherichia coli, used as a proof of concept to develop and demonstrate our single-cell tracking approaches. Our results revealed that P. aeruginosa exhibits diverse and complex interactions on mammalian cell surfaces, such as adhesion, rotational motion, and swimming, unlike the less interactive behavior of Escherichia coli. Our analysis indicated that P. aeruginosa demonstrated lower mean-squared displacement (MSD) values and greater adherence to mammalian cells compared to E. coli, which showed higher MSD slopes and less frequent adherence. Genetic mutations in membrane proteins of P. aeruginosa resulted in altered displacement patterns and reduced adhesion, with the ΔfliD mutant displaying a more Gaussian displacement distribution and significantly less adherence to mammalian cells. Adhesion and tolerance mechanisms are diverse and complex, potentially involving distinct pathways; however, our findings highlight the therapeutic potential of targeting the fliD gene (encoding a critical flagellum protein), as its deletion not only reduced adherence but also antibiotic tolerance.ConclusionsOverall, our findings underscore the importance of single cell tracking in accurately assessing bacterial behavior over short time periods and highlight its significant potential in guiding effective intervention strategies.

Prediction of antibody-antigen interaction based on backbone aware with invariant point attention.

Antibodies play a crucial role in disease treatment, leveraging their ability to selectively interact with the specific antigen. However, screening antibody gene sequences for target antigens via biological experiments is extremely time-consuming and labor-intensive. Several computational methods have been developed to predict antibody-antigen interaction while suffering from the lack of characterizing the underlying structure of the antibody. Beneficial from the recent breakthroughs in deep learning for antibody structure prediction, we propose a novel neural network architecture to predict antibody-antigen interaction. We first introduce AbAgIPA: an antibody structure prediction network to obtain the antibody backbone structure, where the structural features of antibodies and antigens are encoded into representation vectors according to the amino acid physicochemical features and Invariant Point Attention (IPA) computation methods. Finally, the antibody-antigen interaction is predicted by global max pooling, feature concatenation, and a fully connected layer. We evaluated our method on antigen diversity and antigen-specific antibody-antigen interaction datasets. Additionally, our model exhibits a commendable level of interpretability, essential for understanding underlying interaction mechanisms. Quantitative experimental results demonstrate that the new neural network architecture significantly outperforms the best sequence-based methods as well as the methods based on residue contact maps and graph convolution networks (GCNs). The source code is freely available on GitHub at https://github.com/gmthu66/AbAgIPA .

An advanced sensitive detection method for internal and external exposures assessment of para-phenylenediamines and their quinone derivatives based on hierarchical pore-structured nitro-microporous organic networks

para-Phenylenediamines (PPDs) and their quinone derivatives (PPD-Qs) are emerging pollutants that are associated with neurotoxicity, reproductive toxicity, and genetic toxicity, raising significant public health concerns globally. In this study, a novel hierarchical pore-structured nitro-microporous organic networks (NO2-MONs) characterized by multiple adsorption interactions and rapid mass transfer rates was synthesized. Model fitting and adsorption experiments confirmed diverse interaction mechanisms, including pore effects, hydrogen bonding, π-π stacking, and hydrophobic interactions. Utilizing these advantages, NO2-MONs-coated solid-phase microextraction fibers facilitated the effective extraction of trace PPDs and PPD-Qs. Subsequently, a highly sensitive analytical approach was developed for detecting trace amounts of PPDs and PPD-Qs using GC-MS/MS analysis. This method significantly improved upon existing techniques, addressing the low accuracy associated with current semi-quantitative methods and enhancing sensitivity by two orders of magnitude. Notably, the achieved detection limits ranged from 0.38 to 2.6 pg mL−1, with recovery rates between 75.7 % and 117.5 % (RSD ≤ 9.8 %). This proposed approach provides technical support for investigating concentration-dose-effect relationships related to the environmental presence of PPDs and PDD-Qs, facilitating the development of relevant regulatory standards.

Glacier retreat decreases mutualistic network robustness over spacetime

Glaciers are retreating worldwide at an ever‐increasing rate, exposing new ice‐free areas to ecological succession. This process leads to changes in biodiversity and potentially to novel species interactions. However, we still have a limited understanding of how glacier retreat influences species interaction networks, particularly the structure and robustness of mutualistic networks. After reconstructing plant–pollinator networks along a 140‐years chronosequence on a glacier foreland, we address the effects of glacier retreat on network structure and robustness. Our results show that the prevalence of different network motifs changes over spacetime, leading to a decrease of network robustness. With glacier retreat, mutualistic networks shift from highly connected with diverse specialist interactions to loosely connected with few generalist interactions. Furthermore, despite the turnover of plant species, we find that species structural roles remain constant over spacetime while depending on species identity. Our findings suggest that glacier retreat reshuffles mutualistic networks with motifs posing low robustness, leading to increased fragility. Understanding the assembly and breaking down of species interaction networks provides novel insights into the development and stability of novel, post‐glacial ecological systems facing glacier extinction.

Efficient All‐Polymer Solar Cells Enabled by a Novel Medium Bandgap Guest Acceptor

Comprehensive SummaryNear‐infrared (NIR)‐absorbing polymerized small molecule acceptors (PSMAs) based on a Y‐series backbone (such as PY‐IT) have been widely developed to fabricate efficient all‐polymer solar cells (all‐PSCs). However, medium‐bandgap PSMAs are often overlooked, while they as the third component can be expected to boost power conversion efficiencies (PCEs) of all‐PSCs, mainly due to their up‐shifted lowest unoccupied molecular orbital (LUMO) energy level, complimentary absorption, and diverse intermolecular interaction compared to the NIR‐absorbing host acceptor. Herein, an IDIC‐series medium‐bandgap PSMA (P‐ITTC) is developed and introduced as the third component into D18/PY‐IT host, which can not only form complementary absorption and cascade energy level, but also finely optimize active layer morphology. Therefore, compared to the D18/PY‐IT based parental all‐PSCs, the ternary all‐PSCs based on D18/PY‐IT:P‐ITTC obtain an increased exciton dissociation, charge transport, carrier lifetime, as well as suppressed charge recombination and energy loss. As a result, the ternary all‐PSCs achieve a high PCE of 17.64% with a photovoltage of 0.96 V, both of which are among the top values in layer‐by‐layer typed all‐PSCs. This work provides a method for the design and selection of the medium‐bandgap third component to fabricate efficient all‐PSCs.

Deradicalization Through Multicultural Islamic Religious Education at The Islamic University

In the context of preventing radicalism, it is important to research educational institutions that have implemented multicultural Islamic education. This article explains how deradicalization is pursued through Multicultural Islamic Education at Universitas Islam Malang (UNISMA. This research uses a qualitative method with a phenomenological approach to understand the role of Islamic religious education in shaping students' multicultural attitudes. Data were collected through observations, interviews with 15 alumni from three cohorts, and documentation, focusing on the integration of multiculturalism concepts in the course materials. The findings indicate that the Multicultural PAI doctoral program at UNISMA significantly contributes to preventing radicalism by promoting tolerance and inclusive religious education. The program encompasses both theological and socio-cultural aspects, which help transform students' mindsets to become more open and reinforce the values of Bhinneka Tunggal Ika and Pancasila within the framework of Islamic education. The curriculum serves as a deradicalization tool by deepening the understanding of diversity and encouraging positive interactions within and between religious communities. However, its effectiveness is influenced by students' subjective factors, such as their attitudes, and external factors like the sociopolitical context. Further research is needed to assess the program's long-term impact and refine the curriculum based on student feedback.

Review of Yu–Shiba–Rusinov bound state in quantum impurity structures: basic principle and current progress

Abstract Magnetic impurities connected to superconductors reservoir result in bound states within the superconducting gap, so called Yu–Shiba–Rusinov (YSR) state. In the past few years, this field has gained much attention since it is crucial for engineering novel superconducting many-body states, with the perspective of manufacturing Majorana Fermions. The underlying physical picture of YSR state depends closely on the form of the impurities connected to the leads, the manner in which the impurities are organized, and also the diverse local interactions, which is always disclosed with the aid of quantum impurity models. This article provides a comprehensive overview of the progress achieved by previous studies, focusing on the issues demonstrated by quantum impurity structures. The physical mechanisms and the related phenomena assisted by different interactions are discussed in detail. Furthermore, a comprehensive overview of recent experimental achievements is presented, using various metal phthalocyanine molecules as illustrative examples, thereby establishing a robust foundation for future inquiries in this domain.

Habitat Fragmentation Affects Richness—A View Through a Metacommunity Lens

Habitat fragmentation is often assumed to negatively impact species diversity because smaller, more isolated populations on smaller habitat patches are at a higher extinction risk. However, some empirical and theoretical studies suggest that landscapes with numerous small habitat patches may support higher species richness, although the circumstances remain elusive. We used an agent-based metacommunity model to investigate this and simulate landscapes of the same total area but diverse patch sizes. Our model, as generic and unbiased by specific assumptions as possible, aimed to explore which circumstances may be more conducive to supporting higher biodiversity. To this end, most parameters and behaviors were random. The model included generalized species traits, dispersal, and interactions to explore species richness dynamics in fragmented landscapes of distinct patch sizes. Our results show that landscapes with many small patches maintain higher species richness than those with fewer large patches. Moreover, the relationship between patch connectivity and species richness is more pronounced in landscapes with smaller patches. High connectivity in these landscapes may support species diversity by preventing local extinctions and facilitating recolonization. In contrast, connectivity is less significant in large-patch landscapes, where generalist species dominate. The findings highlight the complex interplay between patch size quality, connectivity, species traits, and diverse interactions among species in determining species richness. We suggest the patterns produced by the model represent null predictions and may be useful as a reference for a diversity of more specialized questions and predictions. These insights may also have specific implications for conservation strategies, suggesting that maintaining a mosaic of small, well-connected patches could enhance biodiversity in fragmented landscapes.

Online Media Use and COVID-19 Vaccination in Real-World Personal Networks: Quantitative Study.

Most studies assessing the impact of online media and social media use on COVID-19 vaccine hesitancy predominantly rely on survey data, which often fail to capture the clustering of health opinions and behaviors within real-world networks. In contrast, research using social network analysis aims to uncover the diverse communities and discourse themes related to vaccine support and hesitancy within social media platforms. Despite these advancements, there is a gap in the literature on how a person's social circle affects vaccine acceptance, wherein an important part of social influence stems from offline interactions. We aimed to examine how online media consumption influences vaccination decisions within real-world social networks by analyzing unique quantitative network data collected from Romania, an Eastern European state and member of the European Union. We conducted 83 face-to-face interviews with participants from a living lab in Lerești, a small rural community in Romania, using a personal network analysis framework. This approach involved gathering data on both the respondents and individuals within their social circles (referred to as alters). After excluding cases with missing data, our analysis proceeded with 73% (61/83) of the complete personal networks. To examine the hierarchical structure of alters nested within ego networks, we used a mixed multilevel logistic regression model with random intercepts. The model aimed to predict vaccination status among alters, with the focal independent variable being the respondents' preferred source of health and prevention information. This variable was categorized into 3 types: traditional media, online media (including social media), and a combination of both, with traditional media as the reference category. In this study, we analyzed 61 personal networks, encompassing between 15 and 25 alters each, totaling 1280 alters with valid data across all variables of interest. Our primary findings indicate that alters within personal networks, whose respondents rely solely on online media for health information, exhibit lower vaccination rates (odds ratio [OR] 0.37, 95% CI 0.15-0.92; P=.03). Conversely, the transition from exclusive traditional media use to a combination of both traditional and online media does not significantly impact vaccination rate odds (OR 0.75, 95% CI 0.32-1.78; P=.52). In addition, our analysis revealed that alters in personal networks of respondents who received the vaccine are more likely to have received the vaccine themselves (OR 3.75, 95% CI 1.79-7.85; P<.001). Real-world networks combine diverse human interactions and attributes along with consequences on health opinions and behaviors. As individuals' vaccination status is influenced by how their social alters use online media and vaccination behavior, further insights are needed to create tailored communication campaigns and interventions regarding vaccination in areas with low levels of digital health literacy and vaccination rates, as Romania exposes.

Metagenomic characterization of viruses and mobile genetic elements associated with the DPANN archaeal superphylum.

The archaeal superphylum DPANN (an acronym formed from the initials of the first five phyla discovered: Diapherotrites, Parvarchaeota, Aenigmarchaeota, Nanohaloarchaeota and Nanoarchaeota) is a group of ultrasmall symbionts able to survive in extreme ecosystems. The diversity and dynamics between DPANN archaea and their virome remain largely unknown. Here we use a metagenomic clustered regularly interspaced short palindromic repeats (CRISPR) screening approach to identify 97 globally distributed, non-redundant viruses and unclassified mobile genetic elements predicted to infect hosts across 8 DPANN phyla, including 7 viral groups not previously characterized. Genomic analysis suggests a diversity of viral morphologies including head-tailed, tailless icosahedral and spindle-shaped viruses with the potential to establish lytic, chronic or lysogenic infections. We also find evidence of a virally encoded Cas12f1 protein (probably originating from uncultured DPANN archaea) and a mini-CRISPR array, which could play a role in modulating host metabolism. Many metagenomes have virus-to-host ratios >10, indicating that DPANN viruses play an important role in controlling host populations. Overall, our study illuminates the underexplored diversity, functional repertoires and host interactions of the DPANN virome.

Surface microlayer-mediated virome dissemination in the Central Arctic

BackgroundAquatic viruses act as key players in shaping microbial communities. In polar environments, they face significant challenges such as limited host availability and harsh conditions. However, due to the restricted accessibility of these ecosystems, our understanding of viral diversity, abundance, adaptations, and host interactions remains limited.ResultsTo fill this knowledge gap, we studied viruses from atmosphere-close aquatic ecosystems in the Central Arctic and Northern Greenland. Aquatic samples for virus-host analysis were collected from ~60 cm depth and the submillimeter surface microlayer (SML) during the Synoptic Arctic Survey 2021 on icebreaker Oden in the Arctic summer. Water was sampled from a melt pond and open water before undergoing size-fractioned filtration, followed by genome-resolved metagenomic and cultivation investigations. The prokaryotic diversity in the melt pond was considerably lower compared to that of open water. The melt pond was dominated by a Flavobacterium sp. and Aquiluna sp., the latter having a relatively small genome size of 1.2 Mb and the metabolic potential to generate ATP using the phosphate acetyltransferase-acetate kinase pathway. Viral diversity on the host fraction (0.2–5 µm) of the melt pond was strikingly limited compared to that of open water. From the 1154 viral operational taxonomic units (vOTUs), of which two-thirds were predicted bacteriophages, 17.2% encoded for auxiliary metabolic genes (AMGs) with metabolic functions. Some AMGs like glycerol-3-phosphate cytidylyltransferase and ice-binding like proteins might serve to provide cryoprotection for the host. Prophages were often associated with SML genomes, and two active prophages of new viral genera from the Arctic SML strain Leeuwenhoekiella aequorea Arc30 were induced. We found evidence that vOTU abundance in the SML compared to that of ~60 cm depth was more positively correlated with the distribution of a vOTU across five different Arctic stations.ConclusionsThe results indicate that viruses employ elaborate strategies to endure in extreme, host-limited environments. Moreover, our observations suggest that the immediate air-sea interface serves as a platform for viral distribution in the Central Arctic.Dvb_jZZ1H7pg55rxrDSVb2Video

Hierarchical assembly of Ag40 nanowheel ranging from building blocks to diverse superstructure regulation

Achieving precise and controllable hierarchical self-assembly of functional nanoclusters within crystal lattices to create distinct architectures is of immense significance, yet it creates considerable challenges. Here we successfully synthesized a silver nanowheel Ag40, along with its optically pure enantiomers S-/R-Ag40. Each species possesses an internal nanospace and exhibits host-guest interactions. These structures are constructed from primary building blocks (Ag9). By manipulating the surface anions and guest molecules, the nanowheels function as secondary building blocks, spontaneously organizing into complex double- and triple-helical crystalline superstructures or one-dimensional chains {Ag41}n through conformational matching and diverse noncovalent interactions. Moreover, we demonstrate that the water-mediated complex specifically assembled with uridine monophosphate nucleotides, resulting in chiral assemblies of Ag40 that exhibit chiroptical activity for specific recognition. Our findings provide insights into the efficient construction of assemblies with hollow frameworks and propose strategies for superstructure engineering by manipulating surface motifs.

Expanding the Toolbox of Oxidants: Controllable Etching of Ultrasmall Au Nanoparticles toward Tailorable NIR-II Luminescence and Ligand-Mediated Biodistribution and Clearance.

Oxidant-driven and controllable etching of small-sized nanoparticles (NPs, d < 3 nm) and tailorable modulation of their optical properties are challenging due to the high reactivity and complicated surface chemistry. Herein, we present a facile strategy for highly controllable oxidative etching of ultrasmall AuNPs and tailorable modulation of luminescence. The proper choice of a moderate oxidant, ClO-, could not only selectively etch the Au(I)-thiolate motifs from the nanoparticle surface at the subnanometer scale but also retained a stable metallic core structure without aggregation, which impressively prompted the wide-range luminescent switching from the visible to second near-infrared (NIR-II) region. The resultant oxidized AuNPs displayed highly luminescent NIR-II emission with a quantum yield of 3.0%, excellent monodispersed stability, ideal biocompatibility, and tunable shielding effects against protein adsorption. With those outstanding features, oxidized AuNPs could be utilized as nanoprobes for long-lasting and in vivo bioimaging of associated metabolic behaviors with distinguishable organ-specific targeting capabilities and ligand-mediated kinetics in nanoparticle clearance. These findings expand the toolbox of oxidants for the controllable synthesis of NIR-II nanoprobes and open up a path for exploring diverse ligand interactions on ultrasmall AuNPs with organs or tissues that might advance their monitoring applications for a wide range of clinically important diseases.

Geographical variation, socioeconomic inequalities of low birth weight, and its relationship with maternal dietary diversity: Insights from the maternal infant and young child nutrition programme in Bangladesh.

Globally, every year, 20 million neonates are born with weights below 2500 g and are considered low birth weight (LBW). About 90% of these births occur in low- and middle-income countries. Information regarding the geographical variation, socioeconomic inequalities of LBW neonates, and the relationship between maternal inadequate dietary diversity and LBW is limited in rural areas of Bangladesh. We aimed to explore the geographical disparities and socioeconomic inequalities in the prevalence of LBW and its association with inadequate maternal dietary diversity. We extracted data from a large-scale evaluation programme conducted as a part of the maternal infant and young child nutrition phase two in Bangladesh, implemented by BRAC. We used the concentration index (CIX) to measure the socioeconomic inequalities of LBW. We performed a cluster-adjusted multiple logistic regression analysis to determine the association between LBW and maternal dietary diversity. A total of 4651 children aged <5 years with their mother's information were included. The overall prevalence of LBW was 13.5%. About 16% of mothers living in the poorest wealth quintile gave birth to LBW babies, whereas 10% of mothers living in the richest households gave birth to LBW babies. The CIX exhibited LBW babies were more prevalent among the socioeconomically worst-off (poorest) group (CIX = -0.08), indicating mothers of the poorest households are vulnerable to giving birth to normal-weight babies. An adjusted multiple logistic regression model indicated that mothers with inadequate dietary diversity had higher odds (adjusted odds ratio (AOR) = 1.27; 95% confidence interval (CI) = 1.04, 1.54) of giving birth to LBW babies. Notably, in the interaction of mothers' age and dietary diversity, we found that adolescent mothers (aged ≤ 19 years) with inadequate dietary diversity had 2.56 times (AOR = 2.56; 95% CI = 1.14, 5.76) higher odds of giving birth to LBW babies compared to adult mothers (aged >19 years) who consumed diversified foods. Intervention strategies for reducing LBW prevalence should target the poorest households. Also, interventions for improving the dietary diversity of adolescent pregnant mothers are expected to reduce the number of LBW babies from the rural areas of Bangladesh.

Supradecoration induced novel Properties: A comparative study of Ferrocene and Ferrocenyl α-aminophosphonate

Decorating chemical motifs with appropriate functional groups capable of supramolecular interactions hold key in modulating these novel systems for targeted applications. This work by means of a comparative study of Ferrocene and Ferrocenyl α- aminophosphonate highlight supradecoration induced multi paradigm properties across materials to medicine. The observed results indicate an increase in crystal framework energy with induction of mechanochromism and aggregation-induced emission in case of Ferrocenyl-α-amino phosphonate as novel supra decorated Ferrocene motif. Comparative BSA and BLC studies indicated improved biocompatibility with enhancement of catalase enzyme activity in case of Ferrocenyl-α- aminophosphonate compared to pristine Ferrocene. The relative quantification of intermolecular non covalent interactions of Ferrocene and Ferrocenyl-α- aminophosphonate evaluated using Quantum crystallographic methods and non-covalent interaction analysis were used to corroborate the supramodulation effects. The observed influence of Ferrocenyl α-aminophosphonate on the enzymatic activity of catalase was also examined using a comparative molecular docking analysis. The docking results corroborated influence of supradecoration on binding affinity and binding site, which are vital for designing ligands of enhanced catalase activity and also helpful in prediction of newer regulatory sites on enzyme. Taken together this work signifies how supra decoration of Ferrocene motif with functionalities capable of diverse intermolecular non-covalent interactions modulate molecular properties for newer applications.

Recent Advances of Exosomes Derived from Skeletal Muscle and Crosstalk with Other Tissues.

Skeletal muscle plays a crucial role in movement, metabolism, and energy homeostasis. As the most metabolically active endocrine organ in the body, it has recently attracted widespread attention. Skeletal muscle possesses the ability to release adipocytokines, bioactive peptides, small molecular metabolites, nucleotides, and other myogenic cell factors; some of which have been shown to be encapsulated within small vesicles, particularly exosomes. These skeletal muscle exosomes (SKM-Exos) are released into the bloodstream and subsequently interact with receptor cell membranes to modulate the physiological and pathological characteristics of various tissues. Therefore, SKM-Exos may facilitate diverse interactions between skeletal muscle and other tissues while also serving as biomarkers that reflect the physiological and pathological states of muscle function. This review delves into the pivotal role and intricate molecular mechanisms of SKM-Exos and its derived miRNAs in the maturation and rejuvenation of skeletal muscle, along with their intercellular signaling dynamics and physiological significance in interfacing with other tissues.

Detection of serum alterations in polysubstance use patients by FT-Raman spectroscopy

Substance use disorders pose significant health risks and treatment challenges due to the diverse interactions between substances and their impact on physical and mental health. The chemical effects of multiple substance use on bodily fluids are not yet fully understood. Therefore, this study aimed to investigate the chemical changes induced by a combination of substances compared to a control group. Analysis of FT-Raman spectra revealed structural alterations in the amide III, I, and C = O functional groups of lipids in subjects treated with opioids, alcohol and cannabis (polysubstance group). These changes were evident in the form of peak shifts compared to the control group. Additionally, an imbalance in the amide-lipid ratio was observed, indicating perturbations in serum protein and lipid levels. Furthermore, a 2D plot of two-track two-dimensional correlation spectra (2T2D-COS) demonstrated a shift towards dominance of lipid vibrations in the polysubstance use groups, contrasting with the predominance of the amide fraction in the control group. This observation suggests distinct molecular changes induced by multiple substance use, potentially contributing to the pathophysiology of substance use disorders. Principal Component Analysis (PCA) was utilized to visualize the data structure and identify outliers. Subsequently, Partial Least Squares Discriminant Analysis (PLS-DA) was employed to classify the polysubstance use and control groups. The PLS-DA model demonstrated high classification accuracy, achieving 100.00 % in the training dataset and 94.74 % in the test dataset. Furthermore, receiver operating characteristic (ROC) analysis yielded perfect AUC values of 1.00 for both the training and test sets, underscoring the robustness of the classification model.This study highlights the quantitative and qualitative changes in serum protein and lipid levels induced by polysubstance use groups, as evidenced by FT-Raman spectroscopy. The findings underscore the importance of understanding the chemical effects of polysubstance use on bodily fluids for improved diagnosis and treatment of substance use disorders. Moreover, the successful classification of spectral data using machine learning techniques emphasizes the potential of these approaches in clinical applications for substance abuse monitoring and management.

Conformational Selection of α-Synuclein Tetramers at Biological Interfaces.

Controlling the polymorphic assemblies of α-synuclein (αS) oligomers is crucial to reroute toxic protein aggregation implicated in Parkinson's disease (PD). One potential mediator is the interaction of αS tetramers with cell membranes, which may regulate the dynamic balance between aggregation-prone disordered monomers and aggregation-resistant helical tetramers. Here, we model diverse tetramer-cell interactions and compare the structure-function relations at the supramolecular-biological interface with available experimental data. The models predict preferential interaction of compact αS tetramers with highly charged membrane surfaces, which may further stabilize this aggregation-resistant conformer. On moderately charged membranes, extended structures are preferred. In addition to surface charge, curvature influences tetramer thermodynamic stability and aggregation, with potential for selective isolation of tetramers via regio-specific interactions with strongly negatively charged micelles that screen further aggregation. Our modeling data set highlights diverse beneficial nano-bio interactions to redirect biomolecule assembly, supporting new therapeutic approaches for PD based on lipid-mediated conformational selection and inhibition.

Epigenetic Regulation in Insect-Microbe Interactions.

Insects have evolved diverse interactions with a variety of microbes, such as pathogenic fungi, bacteria, and viruses. The immune responses of insect hosts, along with the dynamic infection process of microbes in response to the changing host environment and defenses, require rapid and fine-tuned regulation of gene expression programs. Epigenetic mechanisms, including DNA methylation, histone modifications, and noncoding RNA regulation, play important roles in regulating the expression of genes involved in insect immunity and microbial pathogenicity. This review highlights recent discoveries and insights into epigenetic regulatory mechanisms that modulate insect-microbe interactions. A deeper understanding of these regulatory mechanisms underlying insect-microbe interactions holds promise for the development of novel strategies for biological control of insect pests and mitigation of vector-borne diseases.

Impact of Black Swan Events on Ethereum blockchain ERC20 token transaction networks

The Ethereum blockchain and its ERC20 token standard have revolutionized the landscape of digital assets and decentralized applications. ERC20 tokens are programmable and interoperable tokens, enabling various applications and token economies. Transaction graphs, representing the flow of the value between wallets within the Ethereum network, have played a crucial role in understanding the system’s dynamics, such as token transfers and the behavior of traders. Here, we explore the evolution of daily transaction graphs of ERC20 token transactions, which sheds light on the trader’s behavior during the Black Swan Events – 2018 crypto crash and the COVID-19 pandemic. By using the tools from network science and differential geometry, we analyze 0.98 billion of ERC20 token transaction data from November 2015 to January 2023. Our analysis reveals an increase in diverse interaction among the traders and a greater adoption of ERC20 tokens in a maturing Ethereum ERC20 financial ecosystem after the Crypto Crash 2018 and the COVID-19 pandemic. Before the crash and the COVID-19 pandemic, most traders interacted with other traders in an isolated or restricted manner, with each trader focusing solely on either buying or selling activities. However, after the crash and during the pandemic, most traders diversely interacted among themselves by participating in both buying and selling activities. In addition, we observe no significant negative impact of the COVID-19 pandemic on user behavior in the financial ecosystem.