Machine and Deep Learning Methods for Predicting 3D Genome Organization.

Three-dimensional (3D) chromatin interactions, such as enhancer-promoter interactions (EPIs), loops, topologically associating domains (TADs), and A/B compartments, play critical roles in a wide range of cellular processes by regulating gene expression. Recent development of chromatin conformation capture technologies has enabled genome-wide profiling of various 3D structures, even with single cells. However, current catalogs of 3D structures remain incomplete and unreliable due to differences in technology, tools, and low data resolution. Machine learning methods have emerged as an alternative to obtain missing 3D interactions and/or improve resolution. Such methods frequently use genome annotation data (ChIP-seq, DNAse-seq, etc.), DNA sequencing information (k-mers and transcription factor binding site (TFBS) motifs), and other genomic properties to learn the associations between genomic features and chromatin interactions. In this review, we discuss computational tools for predicting three types of 3D interactions (EPIs, chromatin interactions, and TAD boundaries) and analyze their pros and cons. We also point out obstacles to the computational prediction of 3D interactions and suggest future research directions.

Sequence Design for RNA-RNA Interactions.

The design of RNA sequences with desired structural properties presents a challenging computational problem with promising applications in biotechnology and biomedicine. Most regulatory RNAs function by forming RNA-RNA interactions, e.g., in order to regulate mRNA expression. It is therefore natural to consider problems where a sequence is designed to form a desired RNA-RNA interaction and switch between structures upon binding. This contribution demonstrates the use of the Infrared framework to design interacting sequences. Specifically, we consider the regulation of the rpoS mRNA by the sRNA DsrA and design artificial 5 ' UTRs that place a downstream protein coding gene under control of DsrA. The design process is explained step by step in a Jupyter notebook, accompanied by Python code. The text discusses setting up design constraints for sampling sequences in Infrared, computing quality measures, constructing a suitable cost function, as well as the optimization procedure. We show that not only thermodynamic but also kinetic folding features can be relevant. Kinetics of interaction formation can be estimated efficiently using the RRIkinDP tool, and the chapter explains how to include kinetic folding features from RRIkinDP directly in the cost function. The protocol implemented in our Jupyter notebook can easily be extended to consider additional requirements or adapted to novel design scenarios.

Anion-binding-induced selective aggregation and self-degradation: Influence of positional isomerism on the anion selectivity and mode of binding of an imine-based receptor.

Imine based positional isomers (8E)-N-(4-((E)-(perfluorophenylimino)methyl)benzylidene)-2,3,4,5,6-pentafluorobenzenamine, L and (10E)-N-(3-(E-Perfluorophenylimino)methyl)benzylidene)-2,3,4,5,6-pentafluorobenzenamine, L1 have been designed, and synthesized by functionalizing two electron deficient aromatic moieties at the para-para'/ortho-ortho' positions in the phenyl core of the L and L1 respectively. The responses of L and L1 towards various anionic species are examined. The positional isomers L and L1 differs not only by showing distinguishable color change upon addition of anions but also differentiates themselves by the way of self-assembling together upon binding with cyanide anion. The naked-eye colorimetric experiments, UV-Vis, Nuclear Magnetic Resonance, and Infra-Red spectroscopic analyses reveal that the isomer L binds fluoride anion through 2:1 stoichiometry ratio. Unlike fluoride complex, the isomer L form aggregates while binding with cyanide ion. On the other hand, isomer L1 does not show any instant color change upon additions of any anion. Interestingly, after thirty minutes, only the color of the cyanide complex is turned into dark brown. While analyzing the spectroscopic results of cyanide complex of L1, it is found that the cyanide complex begins to decompose and finally it is completely decomposed within 30 min. This unprecedented phenomenon about the colorimetric sensing of cyanide and destruction of cyanide complex with respect to time has not been reported in the literature yet. To the best of our knowledge this is the first example of study of sensing controlling the selectivity, mode of binding, self-aggregating and degradation properties of anionic complexes under the influence of positional isomeric effects. This present investigation provides simple and effective strategy to construct the sensor molecules with tunable binding properties in terms of easy to prepare as well as easy to use as a colorimetric sensor. _____________________________________________________________________________________________________.

Carbonyl stretching band in amides as Lorentz oscillator. Insights into anharmonicity and local environment in the liquid phase from NIR and MIR spectra of N-methylformamide and di-N,N-methylformamide.

We investigated the anharmonicity and intermolecular interactions of N-methylformamide (NMF) and di-N,N-methylformamide (DMF) in the neat liquid phase with particular interest in the amide bands. The vibrational spectra, complex refractive index, and complex electric permittivity were determined in in the mid- (MIR) and near-infrared (NIR) regions (11,500-560 cm-1; 870-17857 nm). Dispersion analysis was based on the Classical Damped Harmonic Oscillator (CDHO) and simultaneous modelling of the real and imaginary components of the spectra. This data delivered insights into the vibrational energy dissipation and self-association in liquid amides. Identification of the MIR and NIR bands was based on anharmonic GVPT2//B3LYP/6-311++G(d,p) calculations. DMF and NMF follow distinct self-association, evidenced in the MIR fingerprint by the two components of the νCO, the analog of the Amide I band. These conclusions are supported by the structural information derived from the NIR spectra. Furthermore, the contribution of overtones and combination bands in the MIR spectra of amides was examined. The conclusions on molecular interactions and structural dynamics of NMF and DMF contribute to a deeper understanding of the effects of changes in the local environment of the amide group.

Artificial chemotaxis under electrodiffusiophoresis.

HYPOTHESIS: Through a large parameter space, electric fields can tune colloidal interactions and forces leading to diverse static and dynamical structures. So far, however, field-driven interactions have been limited to dipole-dipole and hydrodynamic contributions. Nonetheless, in this work, we propose that under the right conditions, electric fields can also induce interactions based on local chemical fields and diffusiophoretic flows. EXPERIMENTS: Herein, we present a strategy to generate and measure 3D chemical gradients under electric fields. In this approach, faradaic reactions at electrodes induce global pH gradients that drive long-range transport through electrodiffusiophoresis. Simultaneously, the electric field induces local pH gradients by driving the particle's double layer far from equilibrium. FINDINGS: As a result, while global pH gradients lead to 2D focusing away from electrodes, local pH gradients induce aggregation in the third dimension. Evidence points to a mechanism of interaction based on diffusiophoresis. Interparticle interactions display a strong dependence on surface chemistry, zeta potential and diameter of particles. Furthermore, pH gradients can be readily tuned by adjusting the voltage and frequency of the electric field. For large Péclet numbers, we observed a collective chemotactic-like collapse of particles. Remarkably, such collapse occurs without reactions at a particle's surface. By mixing particles with different sizes, we also demonstrate, through experiments and Brownian dynamics simulations, the emergence of non-reciprocal interactions, where small particles are more drawn towards large ones.

Lipidic drug delivery systems are responsive to the human microbiome.

In vitro and in vivo tests for therapeutic agents are typically conducted in sterile environments, but many target areas for drug delivery are home to thousands of microbial species. Here, we examine the behaviour of lipidic nanomaterials after exposure to representative strains of four bacterial species found in the gastrointestinal tract and skin. Small angle X-ray scattering measurements show that the nanostructure of monoolein cubic and inverse hexagonal phases are transformed, respectively, into inverse hexagonal and inverse micellar cubic phases upon exposure to a strain of live Staphylococcus aureus often present on skin and mucosa. Further investigation demonstrates that enzymatic hydrolysis and cell membrane lipid transfer are both likely responsible for this effect. The structural responses to S. aureus are rapid and significantly reduce the rate of drug release from monoolein-based nanomaterials. These findings are the first to demonstrate how a key species in the live human microbiome can trigger changes in the structure and drug release properties of lipidic nanomaterials. The effect appears to be strain specific, varies from patient to patient and body region to body region, and is anticipated to affect the bioapplication of monoglyceride-based formulations.

Electronic regulation of hcp-Ru by d-d orbital coupling for robust electrocatalytic hydrogen oxidation in alkaline electrolytes.

Bimetallic alloys hold exceptional promise as candidate materials because they offer a diverse parameter space for optimizing electronic structures and catalytic sites. Herein, we fabricate ruthenium-cobalt alloy nanoparticles uniformly dispersed within hollow mesoporous carbon spheres (hcp-RuCo@C) via impregnation and pyrolysis strategies. The intriguing hollow mesopore structure of hcp-RuCo@C facilitates efficient contact between active sites and reactants, thereby accelerating hydrogen oxidation reaction (HOR) kinetics. As anticipated, the hcp-RuCo@C showcases remarkable exchange current density and mass activity of 3.73 mA cm-2 and 2.8 mA µgRu-1, respectively, surpassing those of commercial Pt/C and documented Ru-based electrocatalysts. Notably, hcp-RuCo@C demonstrates robust resistance to 1000 ppm CO, a trait lacking in Pt/C catalysts. Comprehensive experimental results reveal that the alloying-induced d-d electronic interactions between Ru and Co species significantly optimizes hydrogen binding energy (HBE) and hydroxide binding energy (OHBE). This optimization promotes the vital Volmer step, ameliorating the alkaline HOR properties of hcp-RuCo@C.

Supervised Chromatin Loop Detection Using Peakachu Version 2.

Peakachu is a supervised-learning-based approach that identifies chromatin loops from chromatin contact data. Here, we present Peakachu version 2, an updated version that significantly improves extensibility, usability, and computational efficiency compared to its predecessor. It features pretrained models tailored for a wide range of experimental platforms, such as Hi-C, Micro-C, ChIA-PET, HiChIP, HiCAR, and TrAC-loop. This chapter offers a step-by-step tutorial guiding users through the process of training Peakachu models from scratch and utilizing pretrained models to predict chromatin loops across various platforms.

Integrative Modeling of 3D Genome Organization by Bayesian Molecular Dynamics Simulations with Hi-C Metainference.

Polymer modeling has been playing an increasingly important role in complementing 3D genome experiments, both to aid their interpretation and to reveal the underlying molecular mechanisms. This chapter illustrates an application of Hi-C metainference, a Bayesian approach to explore the 3D organization of a target genomic region by integrating experimental contact frequencies into a prior model of chromatin. The method reconstructs the conformational ensemble of the target locus by combining molecular dynamics simulation and Monte Carlo sampling from the posterior probability distribution given the data. Using prior chromatin models at both 1 kb and nucleosome resolution, we apply this approach to a 30 kb locus of mouse embryonic stem cells consisting of two well-defined domains linking several gene promoters together. Retaining the advantages of both physics-based and data-driven strategies, Hi-C metainference can provide an experimentally consistent representation of the system while at the same time retaining molecular details necessary to derive physical insights.

Application of FTIR two-dimensional correlation spectroscopy (2D-COS) analysis in characterizing environmental behaviors of microplastics: A systematic review.

Microplastics (MPs) are ubiquitous in the environment, continuously undergo aging processes and release toxic chemical substances. Understanding the environmental behaviors of MPs is critical to accurately evaluate their long-term ecological risk. Generalized two-dimensional correlation spectroscopy (2D-COS) is a powerful tool for MPs studies, which can dig more comprehensive information hiding in the conventional one-dimensional spectra, such as infrared (IR) and Raman spectra. The recent applications of 2D-COS in analyzing the behaviors and fates of MPs in the environment, including their aging processes, and interactions with natural organic matter (NOM) or other chemical substances, were summarized systematically. The main requirements and limitations of current approaches for exploring these processes are discussed, and the corresponding strategies to address these limitations and drawbacks are proposed as well. Finally, new trends of 2D-COS are prospected for analyzing the properties and behaviors of MPs in both natural and artificial environmental processes.

Ampullaviruses: From Extreme Environments to Biotechnological Innovation.

Ampullaviruses are unique among viruses. They live in extreme environments and have special bottle-shaped architecture. These features make them useful tools for biotechnology. These viruses have compact genomes. They encode a range of enzymes and proteins. Their natural environment highlights their suitability for industrial applications. Ongoing research explores ways in which these viruses can improve enzyme stability. They are also employed in the creation of new biosensors and the development of new bioremediation techniques. High coinfection rates and the ecology of ampullaviruses at larger scales can also reveal new viral vectors. They can also help improve phage therapy. Here, we have explored the structure and function of ampullaviruses. We have focused on their use in biotechnology. We have also identified their characteristics that could prove to be useful. We have also pointed out key knowledge gaps and bridging them could further extend the biotechnological uses.

The Changing Phases of Bromopentafluorobenzene.

As part of a much larger study on non-covalent interactions in binary adducts, we have explored the solid-state structures of bromopentafluorobenzene (C6F5Br) using differential scanning calorimetry (DSC), variable-temperature powder X-ray diffraction (VT-PXRD), and single-crystal X-ray diffraction (SXD). DSC data initially indicated a single solid-state phase below the freezing point, but revealed additional weak transitions upon heating. The crystal structures of three solid-state phases have been solved. The SXD data showed that phases I and IV are centrosymmetric, whilst phase II is polar. However, the structure of phase III remains elusive due to the changing phase behaviour of C6F5Br that is determined as much as by kinetics as thermodynamics. The results underline the need for multiple analytical techniques to study non-covalent interactions and offer valuable data for refining computational models in crystal structure prediction and machine learning. A comparison with the iodinated counterpart is also made.

Effect of Danhong injection on pharmacokinetics and pharmacodynamics of rivaroxaban in rats.

BACKGROUND AND OBJECTIVES: Rivaroxaban is often used in combination with DHI to treat thromboembolic disease. Whether the combination causing HDIs is still unknown. The purpose of this study was to evaluate effects of DHI on pharmacokinetics and pharmacodynamics of rivaroxaban in rats and effects on CYP3A2. METHODS: Plasma concentration of rivaroxaban with or without DHI was determined by HPLC. Pharmacokinetics parameters were calculated. Effect of DHI on pharmacodynamics of rivaroxaban was investigated by APTT, PT, TT, FIB, INR, length of tail thrombosis, vWF, t-PA, PAI-1, IL-1ß, TNF-α and histopathological sections. Effect of DHI on CYP3A2 in rats was investigated by probe drug method. RESULTS: Cmax and AUC of rivaroxaban increased significantly in combination group (P < 0.05). APTT, PT, INR and TT increased (P < 0.05), length of tail thrombosis, FIB, vWF, PAI-1, IL-1ß and TNF-α of combination group decreased significantly (P < 0.05) compared with rivaroxaban or DHI alone. Histopathologic section of tail thrombus had significant improvement. Cmax and AUC of dapsone increased (P < 0.05) in DHI group. CONCLUSION: In summary, DHI is an inhibitor of CYP3A2 and could significantly affect pharmacokinetics and pharmacodynamic of rivaroxaban, enhance anticoagulant and antithrombotic efficacy in rats. However, the combination of rivaroxaban and DHI might lead to potential HDIs. The dosage of rivaroxaban should be adjusted in clinical.

Decoding the genetic landscape of autism: A comprehensive review.

BACKGROUND: Autism spectrum disorder (ASD) is a complex neurodevelopmental condition characterized by heterogeneous symptoms and genetic underpinnings. Recent advancements in genetic and epigenetic research have provided insights into the intricate mechanisms contributing to ASD, influencing both diagnosis and therapeutic strategies. AIM: To explore the genetic architecture of ASD, elucidate mechanistic insights into genetic mutations, and examine gene-environment interactions. METHODS: A comprehensive systematic review was conducted, integrating findings from studies on genetic variations, epigenetic mechanisms (such as DNA methylation and histone modifications), and emerging technologies [including Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-Cas9 and single-cell RNA sequencing]. Relevant articles were identified through systematic searches of databases such as PubMed and Google Scholar. RESULTS: Genetic studies have identified numerous risk genes and mutations associated with ASD, yet many cases remain unexplained by known factors, suggesting undiscovered genetic components. Mechanistic insights into how these genetic mutations impact neural development and brain connectivity are still evolving. Epigenetic modifications, particularly DNA methylation and non-coding RNAs, also play significant roles in ASD pathogenesis. Emerging technologies like CRISPR-Cas9 and advanced bioinformatics are advancing our understanding by enabling precise genetic editing and analysis of complex genomic data. CONCLUSION: Continued research into the genetic and epigenetic underpinnings of ASD is crucial for developing personalized and effective treatments. Collaborative efforts integrating multidisciplinary expertise and international collaborations are essential to address the complexity of ASD and translate genetic discoveries into clinical practice. Addressing unresolved questions and ethical considerations surrounding genetic research will pave the way for improved diagnostic tools and targeted therapies, ultimately enhancing outcomes for individuals affected by ASD.

Rhabdomyolysis associated with concomitant use of colchicine and statins in the real world: identifying the likelihood of drug-drug interactions through the FDA adverse event reporting system.

Background: Currently, there remains substantial controversy in research regarding whether the concomitant use of colchicine and statins increases the occurrence of rhabdomyolysis, warranting further substantiation. Objective: This study aimed to identify the likelihood drug-drug interactions (DDIs) for the co-administration of colchicine and statins resulting in rhabdomyolysis. Methods: A disproportionality analysis was conducted by using data sourced from the US Food and Drug Administration Adverse Event Reporting System (FAERS) to detect rhabdomyolysis signals associated with the combined use of colchicine and statins. The association between (colchicine/statins/colchicine and statins) and rhabdomyolysis were evaluated using information component (IC). DDI signals were calculated based on the Ω shrinkage measure and Bayesian confidence propagation neural network (BCPNN) method. Furthermore, stratification was performed based on colchicine and individual statins agents. Results: In total, 11,119 reports of rhabdomyolysis were identified in the FAERS database, 255 (2.29%) involved both colchicine and statins. Our analysis showed potential DDI signals of rhabdomyolysis (Ω025 = 1.17) among individuals concurrent use of colchicine and statins. Moreover, further drug-specific analysis suggests DDI signals in the colchicine-atorvastatin pair (Ω025 = 1.12), and colchicine-rosuvastatin pair (Ω025 = 1.05), along with a higher proportion of rhabdomyolysis (IC025 = 5.20) and (IC025 = 4.26), respectively. Conclusion: The findings suggest that concomitant use of colchicine and statins may increase the risk of rhabdomyolysis, particularly when combined with atorvastatin or rosuvastatin. Therefore, healthcare professionals should pay special attention to life-threatening AE such as rhabdomyolysis, when co-prescribing colchicine statins.

Patient-based multilevel transcriptome exploration highlights relevant chemokines and chemokine receptor axes in glioblastoma.

Chemokines and their receptors form a complex interaction network, crucial for precise leukocyte positioning and trafficking. In cancer, they promote malignant cell proliferation and survival but are also critical for immune cell infiltration in the tumor microenvironment. Glioblastoma (GBM) is the most common and lethal brain tumor, characterized by an immunosuppressive TME, with restricted immune cell infiltration. A better understanding of chemokine-receptor interactions is therefore essential for improving tumor immunogenicity. In this study, we assessed the expression of all human chemokines in adult-type diffuse gliomas, with particular focus on GBM, based on patient-derived samples. Publicly available bulk RNA sequencing datasets allowed us to identify the chemokines most abundantly expressed in GBM, with regard to disease severity and across different tumor subregions. To gain insight into the chemokines-receptor network at the single cell resolution, we explored GBmap, a curated resource integrating multiple scRNAseq datasets from different published studies. Our study constitutes the first patient-based handbook highlighting the relevant chemokine-receptor crosstalks, which are of significant interest in the perspective of a therapeutic modulation of the TME in GBM.

Preferential Formation of Three-layered Host-Guest Complexes of a Planar Dinuclear Metallohost with Alkali Metal Ions.

We synthesized a planar macrocyclic dinuclear nickel(II) metallohost from the corresponding macrocyclic imine ligand containing two N2O2 chelate coordination sites and an O6 cation binding site like 18-crown-6 as well as peripheral hexyl groups. Due to the lipophilic nature of the hexyl groups, the metallohost was soluble in less polar media where its interaction with alkali metal ions was enhanced. The binding studies by NMR spectroscopy clearly showed its strong tendency to form multi-layered structures. The metallohost formed 2:1 and 1:1 (host/guest) complexes with Na+ with the two-step binding constants of logK1 = 6.6 and logK2 = 3.0. In contrast, its complexation with larger alkali metal ions (K+, Rb+, Cs+) preferentially gave 3:2 (host/guest) complexes when 2/3 equiv of the guest was present. The three-layered structures of these 3:2 complexes were well characterized by mass spectrometry and 2D COSY/ROESY experiments as well as DFT calculations, elucidating their unique structural feature with three chemically different environments due to the oppositely curved two [Ni(saloph)] moieties of the metallohost. Therefore, the three-layered structures were preferentially formed when larger alkali metal ions (K+, Rb+, Cs+) were complexed with the metallohost.

A density functional benchmark for dehydrogenation and dehalogenation reactions on coinage metal surfaces.

The on-surface synthesis of low-dimensional organic nanostructures has been extensively investigated through both experimental and theoretical methods, particularly by density functional theory (DFT). However, the complex mixture of interactions often poses challenges within the DFT framework, and there is a knowledge-gap regarding how the choice of DFT approach affects the computed results. Here, five different approaches including vdW interactions, i.e., PBE+D3, PBE+vdWsurf, rev-vdW-DF2, r2SCAN+rVV10 and BEEF-vdW, are employed to describe three prototypical on-surface reactions; dehydrogenation of benzene, debromination of bromobenzene, and deiodination of iodobenzene on the (111) facets of the coinage metals. Overall, rev-vdW-DF2 outperforms the other methods in describing benzene adsorption, whereas BEEF-vdW falls short. For dehydrogenation and debromination on Cu(111), all functionals except BEEF-vdW give reasonable activation energies compared to experiments. A similar trend is observed for Ag(111) and Au(111), with BEEF-vdW yielding significantly higher activation and reaction energies. For dehalogenation, all the five vdW approaches correctly capture the reactivity trend - Cu(111) > Ag(111) > Au(111) - and the expected hierarchy between bromobenzene desorption and carbon- bromine activation. Only BEEF-vdW fails to predict the faster kinetics of deiodination than the iodobenzene desorption. Our work forms a basis for evaluating density functionals in describing chemical reactions on surfaces.

Long-term monitoring of a population of greater horseshoe bat emphasises the importance of a pest beetle prey on demographic trends.

The global decline in insect biomass has far-reaching implications for terrestrial and freshwater food webs, impacting species reliant on insects as a crucial component of their diet. This issue extends to species traditionally considered agricultural pests, such as the common cockchafer Melolontha melolontha. In the race to combat cockchafers through collection, insecticide use, and other control methods, the repercussions of their numerical fluctuations on predators, including species of high conservation importance like bats, have been largely overlooked. Drawing on 31-years of monitoring data for a greater horseshoe bat Rhinolophus ferrumequinum population in the Aosta Valley (Western Italian Alps), we investigated whether annual fluctuations in bat counts are influenced by cockchafer availability and weather conditions. Despite an overall positive trend in bat abundance, we observed pronounced annual fluctuations, mostly driven by cockchafer availability rather than variations in temperature and precipitation. Furthermore, we found a significant association between cockchafer availability and the median date of birth and birth rate of bats. Births occurred approximately 5 days earlier in cockchafer flight years, with earlier births also linked to warmer spring temperatures and higher numbers of warm days in April. Moreover, the ratio pups/older bats was 0.56 in cockchafer flight years, compared to 0.47 in other years. Our results underscore the importance of considering predator-prey dynamics when examining the long-term population trends of species of conservation concern. We recommend implementing restrictions on the use of chemicals and other potentially harmful practices that may diminish prey abundance or quality, including that of species considered as agricultural pests. In designing conservation strategies, a delicate balance should be struck between the current interests of farmers and the overarching goal of preserving biodiversity against potential future threats.