Molecular Physics Research Articles

Animal Models of Human Disease

The use of animal models of human disease is critical for furthering our understanding of disease mechanisms, for the discovery of novel targets for treatment, and for translational research. This Special Topic entitled “Animal Models of Human Disease” aimed to collect state-of-the-art primary research studies and review articles from international experts and leading groups using animal models to study human diseases. Submissions were welcomed on a wide range of animal models and pathologies, including infectious disease, acute injury, regeneration, cancer, autoimmunity, degenerative and chronic disease. Seven participating MDPI journals supported the Special Topic, namely: Biomedicines, Cells, Current Issues in Molecular Biology, Diagnostics, Genes, the International Journal of Molecular Sciences, and the International Journal of Translational Medicine. In total, 46 papers were published in this Special Topic, with 37 full length original research papers, 2 research communications and 7 reviews. These contributions cover a wide range of clinically relevant, translatable, and comparative animal models, as well as furthering understanding of fundamental sciences, covering topics on physiological processes, on degenerative, inflammatory, infectious, autoimmune, neurological, metabolic, heamatological, hormonal and mitochondrial disorders, developmental processes and diseases, cardiology, cancer, trauma, stress, and ageing.

Investigating the magneto-transport and thermal properties of 2D electron systems under the influence of the Aharonov–Bohm field and Eckart potential interaction

The Eckart potential is a well-known potential model with applications cutting across chemical physics and related areas. It is often used to evaluate quantum mechanical tunneling corrections in order to obtain chemical rate constants. To this end, this study focused on extensively examining the effects of perturbations on the magnetic and thermal properties of the Eckart potential. In the presence of magnetic and Aharonov–Bohm fields with Eckart potential, the Schrödinger equation is solved using the functional analysis approach (FAA). The energy equation and wave function are obtained analytically. The energy equation is used to derive expressions for the thermo-magnetic properties of the Eckart potential. An extensive analysis of the effect of these fields and potential parameters on the wave function is presented. In several configurations of the analysis, we observe that the system exhibits a diamagnetic behavior,and the specific heat capacity agree with the Dulong–Petit law. The results of this study are valuable in areas such as molecular physics and condensed matter physics, amongst others.

Comparative analysis of computational based motif refinement methods

Finding patterns in DNA sequences, a challenging task in molecular biology and computer science, plays a crucial role in understanding gene expression and transcription regulation. This article explores various computational methods for identifying transcription factor binding sites TFBS and regulatory motifs in DNA sequences. We discuss the significance of these motifs in gene expression and disease susceptibility research. The article categorizes motif discovery algorithms into enumerative, probabilistic, combinatorial, and nature-inspired approaches, highlighting their strengths and limitations. It emphasizes the need for a comprehensive motif discovery tool that can handle diverse motif types, perform global searches efficiently, and reduce user-defined parameters.

The database of spectroscopic constants of diatomic molecules (DSCDM): A dynamic and user-friendly interface for molecular physics and spectroscopy

We present the database of spectroscopic constants of diatomic molecules (DSCDM), a website dedicated to the spectroscopic constants of ground and excited states of diatomics (https://dscdm.physics.stonybrook.edu). The database can be improved based on community feedback: the community as contributors may upload new data. Additionally, it counts on an Application Programming Interface (API) for molecular spectroscopy data retrieval to make the search process more efficient. On the other hand, the website presents a machine learning predictor of spectroscopic constants based on atomic properties and a new plotting tool to study the statistical distribution of spectroscopic constants.

Bridging Molecular and Clinical Sciences to Achieve the Best Treatment of Enterococcus faecalis Endocarditis.

Enterococcus faecalis (E. faecalis) is a commensal bacterium that causes various infections in surgical sites, the urinary tract, and blood. The bacterium is becoming a significant concern because it tends to affect the elderly population, which has a high prevalence of undiagnosed degenerative valvular disease and is often subjected to invasive procedures and implanted medical devices. The bacterium's actions are influenced by specific characteristics like pili activity and biofilm formation. This resistance significantly impedes the effectiveness of numerous antibiotic therapies, particularly in cases of endocarditis. While current guidelines recommend antimicrobial therapy, the emergence of resistant strains has introduced complexity in managing these patients, especially with the increasing use of transcatheter therapies for those who are not suitable for surgery. Presentations of the condition are often varied and associated with generalised symptoms, which may pose a diagnostic challenge. We share our encounter with a case study that concerns an octogenarian who had a TAVI valve and developed endocarditis. We also conducted a literature review to identify the essential treatment algorithms for such cases.

X-ray induced Coulomb explosion imaging of transient excited-state structural rearrangements in CS2

Structural imaging of transient excited-state species is a key goal of molecular physics, promising to unveil rich information about the dynamics underpinning photochemical transformations. However, separating the electronic and nuclear contributions to the spectroscopic observables is challenging, and typically requires the application of high-level theory. Here, we employ site-selective ionisation via ultrashort soft X-ray pulses and time-resolved Coulomb explosion imaging to interrogate structural dynamics of the ultraviolet photochemistry of carbon disulfide. This prototypical system exhibits the complex motifs of polyatomic photochemistry, including strong non-adiabatic couplings, vibrational mode couplings, and intersystem crossing. Immediately following photoexcitation, we observe Coulomb explosion signatures of highly bent and stretched excited-state geometries involved in the photodissociation. Aided by a model to interpret such changes, we build a comprehensive picture of the photoinduced nuclear dynamics that follows initial bending and stretching motions, as the reaction proceeds towards photodissociation.

Scalable photonic integrated circuits for high-fidelity light control

Advances in laser technology have driven discoveries in atomic, molecular, and optical (AMO) physics and emerging applications, from quantum computers with cold atoms or ions, to quantum networks with solid-state color centers. This progress is motivating the development of a new generation of optical control systems that can manipulate the light field with high fidelity at wavelengths relevant for AMO applications. These systems are characterized by criteria: (C1) operation at a design wavelength of choice in the visible (VIS) or near-infrared (IR) spectrum, (C2) a scalable platform that can support large channel counts, (C3) high-intensity modulation extinction and (C4) repeatability compatible with low gate errors, and (C5) fast switching times. Here, we provide a pathway to address these challenges by introducing an atom control architecture based on VIS-IR photonic integrated circuit (PIC) technology. Based on a complementary metal–oxide–semiconductor fabrication process, this atom-control PIC (APIC) technology can meet system requirements (C1)–(C5). As a proof of concept, we demonstrate a 16-channel silicon-nitride-based APIC with (5.8±0.4)ns response times and >30dB extinction ratio at a wavelength of 780 nm.

GeoT: A Geometry-Aware Transformer for Reliable Molecular Property Prediction and Chemically Interpretable Representation Learning.

In recent years, molecular representation learning has emerged as a key area of focus in various chemical tasks. However, many existing models fail to fully consider the geometric information on molecular structures, resulting in less intuitive representations. Moreover, the widely used message passing mechanism is limited to providing the interpretation of experimental results from a chemical perspective. To address these challenges, we introduce a novel transformer-based framework for molecular representation learning, named the geometry-aware transformer (GeoT). The GeoT learns molecular graph structures through attention-based mechanisms specifically designed to offer reliable interpretability as well as molecular property prediction. Consequently, the GeoT can generate attention maps of the interatomic relationships associated with training objectives. In addition, the GeoT demonstrates performance comparable to that of MPNN-based models while achieving reduced computational complexity. Our comprehensive experiments, including an empirical simulation, reveal that the GeoT effectively learns chemical insights into molecular structures, bridging the gap between artificial intelligence and molecular sciences.

Global trends and hotspots of treatment for nonalcoholic fatty liver disease: A bibliometric and visualization analysis (2010-2023).

Nonalcoholic fatty liver disease (NAFLD) is chronic, with its progression leading to liver fibrosis and end-stage cirrhosis. Although NAFLD is increasingly common, no treatment guideline has been established. Many mechanistic studies and drug trials have been conducted for new drug development to treat NAFLD. An up-to-date overview on the knowledge structure of NAFLD through bibliometrics, focusing on research hotspots, is necessary to reveal the rational and timely directions of development in this field. To research the latest literature and determine the current trends in treatment for NAFLD. Publications related to treatment for NAFLD were searched on the Web of Science Core Collection database, from 2010 to 2023. VOSviewers, CiteSpace, and R package "bibliometrix" were used to conduct this bibliometric analysis. The key information was extracted, and the results of the cluster analysis were based on network data for generating and investigating maps for country, institution, journal, and author. Historiography analysis, bursts and cluster analysis, co-occurrence analysis, and trend topic revealed the knowledge structure and research hotspots in this field. GraphPad Prism 9.5.1.733 and Microsoft Office Excel 2019 were used for data analysis and visualization. In total, 10829 articles from 120 countries (led by China and the United States) and 8785 institutions were included. The number of publications related to treatment for NAFLD increased annually. While China produced the most publications, the United States was the most cited country, and the United Kingdom collaborated the most from an international standpoint. The University of California-San Diego, Shanghai Jiao Tong University, and Shanghai University of Traditional Chinese Medicine produced the most publications of all the research institutions. The International Journal of Molecular Sciences was the most frequent journal out of the 1523 total journals, and Hepatology was the most cited and co-cited journal. Sanyal AJ was the most cited author, the most co-cited author was Younossi ZM, and the most influential author was Loomba R. The most studied topics included the epidemiology and mechanism of NAFLD, the development of accurate diagnosis, the precise management of patients with NAFLD, and the associated metabolic comorbidities. The major cluster topics were "emerging drug," "glucagon-like peptide-1 receptor agonist," "metabolic dysfunction-associated fatty liver disease," "gut microbiota," and "glucose metabolism." The bibliometric study identified recent research frontiers and hot directions, which can provide a valuable reference for scholars researching treatments for NAFLD.

Trends in research of exosomes associated with breast cancer over the past decade: a scientometric analysis.

Breast cancer remains a significant global health challenge, accounting for 2.3 million new cases in 2020 and ranking as the most prevalent cancer by incidence and the fourth in cancer-related mortality worldwide. In China, breast cancer also rapidly increases incidence and burden. The research of exosomes in breast cancer has attracted more and more attention and has a rapid development. Recognizing the pivotal role of exosomes in breast cancer research, we have undertaken a comprehensive scientometric analysis of pertinent scholarly articles published over the past decade to elucidate the current research landscape for researchers. In this study, we gathered all pertinent publications from the Web of Science. Biblioshiny (a web interface for Bibliometrix), VOSviewer software, and CiteSpace software were used to analyze the information on publications, including global trends, countries, institutions, journals, authors, keywords, and citations. A total of 1,239 articles and 625 review articles were retrieved. The annual global publication output has an increased trend in recent decades overall. China contributed the most articles. The publications of the USA had the most total link strength. Nanjing Medical University had the most total link strength. The most relevant source was the International Journal of Molecular Sciences. Tang JH contributed the most articles and had the highest H-index, G-index, and total link strength. The most cited document was "Tumor exosome integrins determine organotropic metastasis", with 2730 citations. The basic themes included "exosomes", "expression", "cells", "identification", "biomarkers", and "serum". The keyword "membrane vesicle" had the strongest bursts. The keywords "target", "biology", "suppressor cell", "molecular mechanism", "tumor progression", "inhibitor", and "model" appeared as prominent focal points in current research and active areas of exploration. Over the past decade, exosome research in breast cancer has undergone a discernible evolution, shifting from broader investigations of exosome roles to focused exploration of specific pathways relevant to breast cancer. Notably, the emphasis has extended to the clinical application of exosomes as biomarkers and potential therapeutic agents in breast cancer treatment.

Laboratory equipment for practice learning in the framework of educational course “Molecular Physics and Thermodynamics”

This article presents laboratory equipment for practice learning of physics specialties students in the framework of educational course “Molecular Physics and Thermodynamics”. The presented laboratory equipment allows measuring the temperature dependence of the thermal conductivity coefficient of molecular liquids under atmospheric pressure and saturated vapors pressure in the temperature range from 150K to 400K. A general scheme of the developed experimental setup for measuring the thermal conductivity of liquids by the steady-state method under isobaric condition has been described. The created laboratory setup uses general design solutions of the coaxial cylinder method, preserving its features and measurement precision in general. The measurements are carried out on coaxial-geometry cell under atmospheric pressure. A modified heat potentiometer method with one thermometer was used, which allowed us to minimize the error in the estimation of the thermal conductivity coefficient due to the uncontrollable heat flows and different calibration of thermometers. The total systematic error in the measurement of the molecular liquids thermal conductivity does not exceed 3%. The procedures for direct measurement and calculation of the thermal conductivity coefficient of molecular liquids using the developed laboratory equipment are described.

Epitope-Based IgE Assays and Their Role in Providing Diagnosis and Prognosis of Food Allergy.

With advances in molecular and computational science, epitope-specific IgE antibody profiling has been developed and recently brought into clinical practice. Epitope-based testing detects IgE antibodies that directly bind to antigenic sites of an allergen, providing increased resolution specificity and fewer false-positive results for diagnosing food allergy. Epitope-binding profiles may also serve as prognostic markers of food allergy and help predict quantities of allergen that would provoke a reaction (ie, eliciting dose, possible severity of a reaction after allergen ingestion, and outcomes of treatment options such as oral immunotherapy [OIT]). Future studies are under way to discover additional applications of epitope-specific antibodies for multiple food allergens.

A scalable scanning transfer cavity laser stabilization scheme based on the Red Pitaya STEMlab platform.

Many experiments in atomic and molecular physics require simultaneous frequency stabilization of multiple lasers. We present a stabilization scheme based on a scanning transfer cavity lock that is simple, stable, and easily scalable to many lasers at minimal cost. The scheme is based on the Red Pitaya STEMlab platform, with custom software developed and implemented to achieve up to 100 Hz bandwidth. As an example demonstration, we realize simultaneous stabilization of up to four lasers and a reduction of long-term drifts to well below 1 MHz/h. This meets typical requirements, e.g., for experiments on laser cooling of molecules.

Albertson (Alb) spectral radii and Albertson (Alb) energies of graph operation.

The sum of the absolute eigenvalues of the adjacency matrix make up graph energy. The greatest absolute eigenvalue of the adjacency matrix is represented by the spectral radius of the graph. Both molecular computing and computer science have uses for graph energies and spectral radii. The Albertson (Alb) energies and spectral radii of generalized splitting and shadow graphs constructed on any regular graph is the main focus of this study. The only thing that may be disputed is the comparison of the (Alb) energies and (Alb) spectral radii of the newly formed graphs to those of the base graph. By concentrating on splitting and shadow graph, we compute new correlations between the Alb energies and spectral radius of the new graph and the prior graph.

Development of zero-noise extrapolated projective quantum algorithm for accurate evaluation of molecular energetics in noisy quantum devices.

The recently developed Projective Quantum Eigensolver (PQE) offers an elegant procedure to evaluate the ground state energies of molecular systems in quantum computers. However, the noise in available quantum hardware can result in significant errors in computed outcomes, limiting the realization of quantum advantage. Although PQE comes equipped with some degree of inherent noise resilience, any practical implementation with apposite accuracy would require additional routines to eliminate or mitigate the errors further. In this work, we propose a way to enhance the efficiency of PQE by developing an optimal framework for introducing Zero Noise Extrapolation (ZNE) in the nonlinear iterative procedure that outlines the PQE, leading to the formulation of ZNE-PQE. Moreover, we perform a detailed analysis of how various components involved in it affect the accuracy and efficiency of the reciprocated energy convergence trajectory. Additionally, we investigate the underlying mechanism that leads to the improvements observed in ZNE-PQE over conventional PQE by performing a comparative analysis of their residue normlandscape. This approach is expected to facilitate practical applications of quantum computing in fields related to molecular sciences, where it is essential to determine molecular energies accurately.

Bridging organic, molecular, macromolecular, supramolecular and biological sciences to create functions via fluorine chemistry and fluorinated reagents

After a brief introduction highlighting the challenges of fluorine chemistry and the latest developments in the field, this Perspective will discuss how a combination of fluorine and fluorous chemistry together with fluorinated reagents helped to bridge between organic, molecular, macromolecular, supramolecular and biological sciences to create functions in the laboratory of the corresponding author. The reactivity of fluoride as a leaving group is best illustrated by SNAr reactions when it helped to demonstrate single electron transfer-mediated side reactions and through molecular design replaced activated aryl fluorides with aryl chlorides in the synthesis of poly(etherketone)s. Subsequently it was demonstrated how Ni(II) sigma complexes provided an orthogonal approach to the Suzuki-type cross-coupling of arylfluorides, other halides and all aryl C–O based electrophiles. Fluorinated reagents facilitated cylotrimetrization vs cyclotetramerization of bis(methoxy)benzyl chloride and alcohol and the synthesis of the simplest molecular liquid crystals. Triflic acid, methyl triflate facilitated the most tolerant living polymerizations including of cyclic siloxanes, functional vinyl ethers and oxazolines to generate self-organizable dendronized polymers while fluorine, trifluoromethyl and trifluoromethoxy groups facilitated disassembly and reassembly of liquid crystal polyethers and poly(p-phenylenes). Fluorinated stereocenters accessed the first heterochiral recognition in side-chain liquid crystal poly(vinyl ether)s and their model compounds. Alkali metal triflates mediated self-organization of supramolecular nonfluorinated and fluorinated self-assembling minidendrons, dendrons, dendrimers and self-organizable dendronized polymers. The role of fluorinated alkyl groups and of alkali metal triflates in the self-assembly, disassembly and isomorphic replacement analysis, of supramolecular helical columns, of the assembly of helical cogwheel coat and of spherical supramolecular dendrimers forming Frank-Kasper periodic and quasiperiodic arrays was highlighted. A brief discussion of fluorinated amino acids, peptides and peptoids and their potential role in the self-assembly and functions resulted from dendritic dipeptides followed by a discussion of semifluorinated amphiphilic Janus dendrimers as models of biological membranes, including for cell fusion and fission, concludes this Perspective.

Decoding the key compounds responsible for the empty cup aroma of soy sauce aroma type baijiu

The empty cup aroma in soy sauce aroma type baijiu (SSB) is distinct, but the specific compounds responsible for its unique aroma remain unknown. The aroma characteristics of SSB and the empty cup were investigated using molecular sensory science. Fifty-three and 27 aroma active compounds were identified in SSB and empty cup aroma, respectively. AEDA of the empty cup showed ethyl 3-phenylpropanoate, phenylethyl alcohol, sotolon, p-cresol, and 2,3-dimethyl-5-ethyl pyrazine could be the most important aroma contributors to the empty cup aroma due to their high FD values. Sotolon, characterized by its seasoning-like and herbal aroma, was identified as a crucial aroma compound for the empty cup aroma for the first time. Lactic acid was found to decrease the olfactory threshold of sotolon markedly in both 53% ethanol water solution and empty cup, promoting the contribution of sotolon to the empty cup aroma.

Unveiling improval changes in fried chicken flavor by glucose-curing treatment based on molecular sensory science

To gain insight into the improved flavor changes, the volatile flavor composition of fried chicken with glucose curing (500 mg/100 g meat) (FCWG), exhibiting the strongest meaty and roasted aromas, and that without curing (FCWOG) were comparatively analyzed. Solvent-assisted flavor evaporation combined with gas chromatography–mass spectrometry (GC–MS) and aroma extract dilution analysis by gas chromatography–olfactometry (GC–O), accurate quantitation, and odor-activity values (OAVs) calculation were performed. Both GC–MS or GC–O results revealed that levels of most aroma compounds were increased by the glucose-curing treatment. GC–MS results suggested that the glucose-curing treatment caused increased formation of the flavors via the Maillard reaction and lipid degradation, while the lipid degradation pathway was modified. In addition, GC–O results indicated a higher increase in the formation of the aroma compounds via the Maillard reaction by the glucose-curing treatment. Furthermore, quantitation and odor active values (OAVs) calculation showed glucose-curing had increased formation of the key odorants (OAV ≥ 1) (e.g., bis(2-methyl-3-furyl)disulfide, 2-acetylthiophene, 2-acetylthiazole, (E,E)− 2,4-decadienal, and methional), of which 2-acetylthiophene, bis(2-methyl-3-furyl)disulfide, and (E,E)− 2,4-decadienal are vital in fried chicken flavor. The results can provide guidance for improving fried chicken flavor by marination.

Short Sequence Aligner Benchmarking for Chromatin Research.

Much of today's molecular science revolves around next-generation sequencing. Frequently, the first step in analyzing such data is aligning sequencing reads to a reference genome. This step is often taken for granted, but any analysis downstream of the alignment will be affected by the aligner's ability to correctly map sequences. In most cases, for research into chromatin structure and nucleosome positioning, ATAC-seq, ChIP-seq, and MNase-seq experiments use short read lengths. How well aligners manage these reads is critical. Most aligner programs will output mapped reads and unmapped reads. However, from a biological point of view, reads will fall into one of three categories: correctly mapped, incorrectly mapped, and unmapped. While increased sequencing depth can often compensate for unmapped reads, incorrectly and correctly mapped reads appear algorithmically identical but can produce biologically significant alterations in the results. For this reason, we are benchmarking various alignment programs to determine their propensity to incorrectly map short reads. As short-read alignment is an important step in ATAC-seq, ChIP-seq, and MNase-seq experiments, caution should be taken in mapping reads to ensure that the most accurate conclusions can be made from the data generated. Our analysis is intended to help investigators new to the field pick the alignment program best suited for their experimental conditions. In general, the aligners we tested performed well. BWA, Bowtie2, and Chromap were all exceptionally accurate, and we recommend using them. Furthermore, we show that longer read lengths do in fact lead to more accurate mappings.

Simple Model of Liquid Water Dynamics.

We develop an analytical statistical-mechanical model to study the dynamic properties of liquid water. In this two-dimensional model, neighboring waters can interact through a hydrogen bond, a van der Waals contact, or an ice-like cage structure or have no interaction. We calculate the diffusion coefficient, viscosity, and thermal conductivity versus temperature and pressure. The trends follow those seen in the water experiments. The model explains that in warm water, heating drives faster diffusion but less interaction, so the viscosity and conductivity decrease. Cooling cold water causes poorer energy exchange because water's ice-like cages are big and immobile and collide infrequently. The main antagonism in water dynamics is not between vdW and H bonds, but it is an interplay between both those pair interactions, multibody cages, and no interaction. The value of this simple model is that it is analytical, so calculations are immediate, and it gives interpretations based on molecular physics.