Direct Photocatalytic Methane Oxidation to Formaldehyde by N Doping Co-Decorated Mixed Crystal TiO2.

In this paper, N-doped TiO2 mixed crystals are prepared via direct calcination of TiN for highly selective oxidation of CH4 to HCHO at room temperature. The structures of the prepared TiO2 samples are characterized to be N-doped TiO2 of anatase and rutile mixed crystals. The crystal structures of TiO2 samples are determined by XRD spectra and Raman spectra, while N doping is demonstrated by TEM mapping, ONH inorganic element analysis, and high-resolution XPS results. Significantly, the production rate of HCHO is as high as 23.5 mmol·g-1·h-1 with a selectivity over 90%. Mechanism studies reveal that H2O is the main oxygen source and acts through the formation of ·OH. DFT calculations indicate that the construction of a mixed crystal structure and N-doping modification mainly act by increasing the adsorption capacity of H2O. An efficient photocatalyst was prepared by us to convert CH4 to HCHO with high yield and selectivity, greatly promoting the development of the photocatalytic CH4 conversion study.

Phenanthroline-functionalized donor-acceptor covalent organic frameworks as photo-responsive nanozymes for visual colorimetric detection of isoniazid.

Development of metal-free nanozymes has raised concern for their extensive applications in photocatalysis and sensing fields. As novel metal-free nanomaterials, covalent organic frameworks (COFs) have engendered intense interest in the construction of nanozymes due to their structural controllability and molecular functionality. The formation of the molecular arrangement by embedding orderly donor-acceptors (D-A) linked in the framework topology to modulate material properties for highly efficient enzyme mimicking activity is of importance but challenging. Here, a strong D-A type of COF was designed and synthesized by integrating electron donor units (pyrene) and electron acceptor units (phenanthroline), named Py-PD COF. Using experiments and theoretical calculations, the introduction of a phenanthroline ring endowed the Py-PD COF with a narrowed band gap, and efficient charge transfer and separation. Further, the Py-PD COF exhibited a superior light-responsive oxidase-mimicking characteristic under visible light irradiation, which could catalyze the oxidation of 3,3',5,5-tetramethylbenzidine (TMB) and give the corresponding evolution of color. The nanoenzymatic activity of the Py-PD COF was light-regulated, which offers a fascinating advantage because of its high efficiency and spatial controllability. Based on previously mentioned characteristics, an "on-off" sensing platform for the colorimetric analysis of isoniazid (INH) could be constructed with a good linear relationship (2-100 µM) and a low limit of detection (1.26 µM). This research shows that not only is Py-PD COF an environmentally friendly compound for the colorimetric detection of INH, but it is also capable of providing the interesting D-A type COF-based material for designing an excellent nanozyme.

The CDE region of feline Calicivirus VP1 protein is a potential candidate subunit vaccine.

BACKGROUND: Feline calicivirus (FCV) infection causes severe upper respiratory disease in cats, but there are no effective vaccines available for preventing FCV infection. Subunit vaccines have the advantages of safety, low cost and excellent immunogenicity, but no FCV subunit vaccine is currently available. The CDE protein is the dominant neutralizing epitope region of the main antigenic structural protein of FCV, VP1. Therefore, this study evaluated the effectiveness of the CDE region as a truncated FCV VP1 protein in preventing FCV infection to provide a strategy for developing potential FCV subunit vaccines. RESULTS: Through the prediction of FCV VP1 epitopes, we found that the E region is the dominant neutralizing epitope region. By analysing the spatial structure of VP1 protein, 13 amino acid sites in the CD and E regions were found to form hydrogen bonding interactions. The results show the presence of these interaction forces supports the E region, helping improve the stability and expression level of the soluble E protein. Therefore, we selected the CDE protein as the immunogen for the immunization of felines. After immunization with the CDE protein, we found significant stimulation of IgG, IgA and neutralizing antibody production in serum and swab samples, and the cytokine TNF-α levels and the numbers of CD4+ T lymphocytes were increased. Moreover, a viral challenge trial indicated that the protection generated by the CDE subunit vaccine significantly reduced the incidence of disease in animals. CONCLUSIONS: For the first time, we studied the efficacy of the CDE protein, which is the dominant neutralizing epitope region of the FCV VP1 protein, in preventing FCV infection. We revealed that the CDE protein can significantly activate humoral, mucosal and cellular immunity, and the resulting protective effect can significantly reduce the incidence of animal disease. The CDE region of the FCV capsid is easy to produce and has high stability and excellent immunogenicity, which makes it a candidate for low-cost vaccines.

Calculating Pairwise Similarity of Polymer Ensembles via Earth Mover's Distance.

Synthetic polymers, in contrast to small molecules and deterministic biomacromolecules, are typically ensembles composed of polymer chains with varying numbers, lengths, sequences, chemistry, and topologies. While numerous approaches exist for measuring pairwise similarity among small molecules and sequence-defined biomacromolecules, accurately determining the pairwise similarity between two polymer ensembles remains challenging. This work proposes the earth mover's distance (EMD) metric to calculate the pairwise similarity score between two polymer ensembles. EMD offers a greater resolution of chemical differences between polymer ensembles than the averaging method and provides a quantitative numeric value representing the pairwise similarity between polymer ensembles in alignment with chemical intuition. The EMD approach for assessing polymer similarity enhances the development of accurate chemical search algorithms within polymer databases and can improve machine learning techniques for polymer design, optimization, and property prediction.

Drug screening identified that handelin inhibits feline calicivirus infection by inhibiting HSP70 expression in vitro.

Feline calicivirus (FCV) is considered one of the major pathogens of cats worldwide and causes upper respiratory tract disease in all cats. In some cats, infection is by a highly virulent strain of FCV (vs.-FCV), which can cause severe and fatal systemic disease symptoms. At present, few antiviral drugs are approved for clinical treatment against FCV. Therefore, there is an imminent need for effective FCV antiviral agents. Here, we used observed a cytopathic effect (CPE) assay to screen 1746 traditional Chinese medicine monomer compounds and found one that can effectively inhibit FCV replication, namely, handelin, with an effective concentration (EC50) value of approximately 2.5 µM. Further study showed that handelin inhibits FCV replication via interference with heat shock protein 70 (HSP70), which is a crucial host factor and plays a positive role in regulating viral replication. Moreover, handelin and HSP70 inhibitors have broad-spectrum antiviral activity. These findings indicate that handelin is a potential candidate for the treatment of FCV infection and that HSP70 may be an important drug target.

Alternaria TeA toxin activates a chloroplast retrograde signaling pathway to facilitate JA-dependent pathogenicity.

The chloroplast is a critical battleground in the arms race between plants and pathogens. Among microbe-secreted mycotoxins, tenuazonic acid (TeA), produced by the genus Alternaria and other phytopathogenic fungi, inhibits photosynthesis, leading to a burst of photosynthetic singlet oxygen (1O2) that is implicated in damage and chloroplast-to-nucleus retrograde signaling. Despite the significant crop damage caused by Alternaria pathogens, our understanding of the molecular mechanism by which TeA promotes pathogenicity and cognate plant defense responses remains fragmentary. We now reveal that A. alternata induces necrotrophic foliar lesions by harnessing EXECUTER1 (EX1)/EX2-mediated chloroplast-to-nucleus retrograde signaling activated by TeA toxin-derived photosynthetic 1O2 in Arabidopsis thaliana. Mutation of the 1O2-sensitive EX1-W643 residue or complete deletion of the EX1 singlet oxygen sensor domain compromises expression of 1O2-responsive nuclear genes and foliar lesions. We also found that TeA toxin rapidly induces nuclear genes implicated in jasmonic acid (JA) synthesis and signaling, and EX1-mediated retrograde signaling appears to be critical for establishing a signaling cascade from 1O2 to JA. The present study sheds new light on the foliar pathogenicity of A. alternata, during which EX1-dependent 1O2 signaling induces JA-dependent foliar cell death.

14 examples of how LLMs can transform materials science and chemistry: a reflection on a large language model hackathon.

Large-language models (LLMs) such as GPT-4 caught the interest of many scientists. Recent studies suggested that these models could be useful in chemistry and materials science. To explore these possibilities, we organized a hackathon. This article chronicles the projects built as part of this hackathon. Participants employed LLMs for various applications, including predicting properties of molecules and materials, designing novel interfaces for tools, extracting knowledge from unstructured data, and developing new educational applications. The diverse topics and the fact that working prototypes could be generated in less than two days highlight that LLMs will profoundly impact the future of our fields. The rich collection of ideas and projects also indicates that the applications of LLMs are not limited to materials science and chemistry but offer potential benefits to a wide range of scientific disciplines.

Generalizing factors of COVID-19 vaccine attitudes in different regions: A summary generation and topic modeling approach.

Objective: The goal of this study is to use summary generation and topic modeling to identify factors contributing to vaccine attitudes for three different vaccine brands, with the aim of generalizing these factors across different regions. Methods: A total of 5562 tweets about three vaccine brands (Sinovac, AstraZeneca, and Pfizer) were collected from 14 December 2020 to 30 December 2021. BERTopic clustering is used to group the tweets into topics, and then contrastive learning (CL) is adopted to generate summaries of each topic. The main content of each topic is generalized into three factors that contribute to vaccine attitudes: vaccine-related factors, health system-related factors, and individual social attributes. Results: BERTopic clustering outperforms Latent Dirichlet Allocation clustering in our analysis. It can also be found that using CL for summary generation helped to better model the topics, particularly at the center-point of the clustering. Our model identifies three main factors contributing to vaccine attitudes that are consistent across different regions. Conclusions: Our study demonstrates the effectiveness of deep learning methods for identifying factors contributing to vaccine attitudes in different regions. By determining these factors, policymakers and medical institutions can develop more effective strategies for addressing concerns related to the vaccination process.

Paper-based sensor based on lead-free manganese halide for the determination of water content in organic solvents.

A highly stable and luminescent lead-free manganese(II) halide hybrid MnBr4(TMN)2 (C34H42Br4MnN4) was designed and synthesized by introducing a large cationic organic spacer. The MnBr4(TMN)2 displays high luminescence with quantum yields up to 77% and possesses turn-off fluorescence behavior (Ex/Em=365/546 nm) for water. These properties make the MnBr4(TMN)2 a promising candidate as an alternative indicator for the detection of water with potential applications for the fabrication of LEDs. Herein, a paper-based sensor based on MnBr4(TMN)2 is described for the determination of water content in organic solvents. The mechanism of water sensing can be tentatively explained by fluorescence quenching originating from the destruction of water due to the Mn-Br bonds of MnBr4(TMN)2. The MnBr4(TMN)2-based paper sensor exhibits an excellent discrimination ability of water content in the range 0-25.0% with a detection limit of 0.27%. Satisfactory recoveries (94.91±4.09% to 103.23±2.38%) are obtained in spiked ethanol solvent samples, which demonstrate that the MnBr4(TMN)2-based paper sensor is capable of detecting water content in real ethanol solvent samples.

Quantity and location of aortic valve calcification predicts paravalvular leakage after transcatheter aortic valve replacement: a systematic review and meta-analysis.

Introduction: Transcatheter aortic valve replacement (TAVR) is the first-line treatment for patients with moderate-to-high surgical risk of severe aortic stenosis. Paravalvular leakage (PVL) is a serious complication of TAVR, and aortic valve calcification contributes to the occurrence of PVL. This study aimed to investigate the effect of location and quantity of calcification in the aortic valve complex (AVC) and left ventricular outflow tract (LVOT) on PVL after TAVR. Method: We performed a systematic review and meta-analysis to evaluate the effect of quantity and location of aortic valve calcification on PVL after TAVR using observational studies from PubMed and EMBASE databases from inception to February 16, 2022. Results: Twenty-four observational studies with 6,846 patients were included in the analysis. A high quantity of calcium was observed in 29.6% of the patients; they showed a higher risk of significant PVL. There was heterogeneity between studies (I2 = 15%). In the subgroup analysis, PVL after TAVR was associated with the quantity of aortic valve calcification, especially those located in the LVOT, valve leaflets, and the device landing zone. A high quantity of calcium was associated with PVL, regardless of expandable types or MDCT thresholds used. However, for valves with sealing skirt, the amount of calcium has no significant effect on the incidence of PVL. Conclusion: Our study elucidated the effect of aortic valve calcification on PVL and showed that the quantity and location of aortic valve calcification can help predict PVL. Furthermore, our results provide a reference for the selection of MDCT thresholds before TAVR. We also showed that balloon-expandable valves may not be effective in patients with high calcification, and valves with sealing skirts instead of those without sealing skirts should be applied more to prevent PVL from happening. Systematic Review Registration: https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=354630, identifier: CRD42022354630.

Griseofulvin Inhibits Root Growth by Targeting Microtubule-Associated Proteins Rather Tubulins in Arabidopsis.

Griseofulvin was considered an effective agent for cancer therapy in past decades. Although the negative effects of griseofulvin on microtubule stability are known, the exact target and mechanism of action in plants remain unclear. Here, we used trifluralin, a well-known herbicide targeting microtubules, as a reference and revealed the differences in root tip morphology, reactive oxygen species production (ROS), microtubule dynamics, and transcriptome analysis between Arabidopsis treated with griseofulvin and trifluralin to elucidate the mechanism of root growth inhibition by griseofulvin. Like trifluralin, griseofulvin inhibited root growth and caused significant swelling of the root tip due to cell death induced by ROS. However, the presence of griseofulvin and trifluralin caused cell swelling in the transition zone (TZ) and meristematic zone (MZ) of root tips, respectively. Further observations revealed that griseofulvin first destroyed cortical microtubules in the cells of the TZ and early elongation zone (EZ) and then gradually affected the cells of other zones. The first target of trifluralin is the microtubules in the root MZ cells. Transcriptome analysis showed that griseofulvin mainly affected the expression of microtubule-associated protein (MAP) genes rather than tubulin genes, whereas trifluralin significantly suppressed the expression of αß-tubulin genes. Finally, it was proposed that griseofulvin could first reduce the expression of MAP genes, meanwhile increasing the expression of auxin and ethylene-related genes to disrupt microtubule alignment in root tip TZ and early EZ cells, induce dramatic ROS production, and cause severe cell death, eventually leading to cell swelling in the corresponding zones and inhibition of root growth.

Transfer Learning Facilitates the Prediction of Polymer-Surface Adhesion Strength.

Machine learning (ML) accelerates the exploration of material properties and their links to the structure of the underlying molecules. In previous work [Shi et al. ACS Applied Materials & Interfaces 2022, 14, 37161-37169.], ML models were applied to predict the adhesive free energy of polymer-surface interactions with high accuracy from the knowledge of the sequence data, demonstrating successes in inverse-design of polymer sequence for known surface compositions. While the method was shown to be successful in designing polymers for a known surface, extensive data sets were needed for each specific surface in order to train the surrogate models. Ideally, one should be able to infer information about similar surfaces without having to regenerate a full complement of adhesion data for each new case. In the current work, we demonstrate a transfer learning (TL) technique using a deep neural network to improve the accuracy of ML models trained on small data sets by pretraining on a larger database from a related system and fine-tuning the weights of all layers with a small amount of additional data. The shared knowledge from the pretrained model facilitates the prediction accuracy significantly on small data sets. We also explore the limits of database size on accuracy and the optimal tuning of network architecture and parameters for our learning tasks. While applied to a relatively simple coarse-grained (CG) polymer model, the general lessons of this study apply to detailed modeling studies and the broader problems of inverse materials design.

Sarcopenia is an independent risk factor for all-cause mortality rate in patients with diabetic foot ulcers.

Objective: This study aimed to determine whether sarcopenia affects the all-cause mortality rate of patients with diabetic foot ulcers (DFUs). Research design and methods: The clinic-based observational study included 217 patients treated at the Department of Endocrinology, the First Affiliated Hospital of Chongqing Medical University during a 4-year period. All subjects underwent dual-energy X-ray absorptiometry to determine their body composition during hospitalization. Diagnosis of sarcopenia was based on the Baumgartner diagnostic criteria. Patients were followed up regularly by phone calls until April 1, 2019, and their survival status was recorded.Univariate and multivariate Cox risk ratio regression models were used to analyze factors influencing the all-cause mortality rate of patients with DFUs. Results: Of the 217 patients, 158 people survived (82.7%), 33 died (17.3%), and 26 were lost to follow-up. The median follow-up time was 23 (Range 11-34) months. The majority of patients were male (68.6%), with a mean age of 67.29 ± 11.14 years. The 5-year survival rate was 68.3% and 45.9% for all study patients (n = 217) and sarcopenia patients (n = 81), respectively. Multivariate Cox risk regression model showed that age (HR 1.042[95%CI:1.006, 1.078], P = 0.021), sarcopenia (HR 5.051[95%CI:1.968, 12.961], P = 0.001), and serum creatinine (HR 1.007[95%CI: 1.003, 1.010], P < 0.001) were independent risk factors for all-cause mortality rate of patients with DFUs. Kaplan-Meier survival curve indicated that the survival rate of patients with sarcopenia was significantly lower than non-sarcopenia patients (P < 0.001). Conclusions: Sarcopenia is an independent risk factor for all-cause mortality of patients with DFUs and hence an important prognostic factor for patients with DFUs. Active prevention and improvement of sarcopenia can potentially improve the survival outcomes of this patient population.

Immune evasion strategy involving propionylation by the KSHV interferon regulatory factor 1 (vIRF1).

Post-translational modifications (PTMs) are essential for host antiviral immune response and viral immune evasion. Among a set of novel acylations, lysine propionylation (Kpr) has been detected in both histone and non-histone proteins. However, whether protein propionylation occurs in any viral proteins and whether such modifications regulate viral immune evasion remain elusive. Here, we show that Kaposi's sarcoma-associated herpesvirus (KSHV)-encoded viral interferon regulatory factor 1 (vIRF1) can be propionylated in lysine residues, which is required for effective inhibition of IFN-ß production and antiviral signaling. Mechanistically, vIRF1 promotes its own propionylation by blocking SIRT6's interaction with ubiquitin-specific peptidase 10 (USP10) leading to its degradation via a ubiquitin-proteasome pathway. Furthermore, vIRF1 propionylation is required for its function to block IRF3-CBP/p300 recruitment and repress the STING DNA sensing pathway. A SIRT6-specific activator, UBCS039, rescues propionylated vIRF1-mediated repression of IFN-ß signaling. These results reveal a novel mechanism of viral evasion of innate immunity through propionylation of a viral protein. The findings suggest that enzymes involved in viral propionylation could be potential targets for preventing viral infections.

Ependymal polarity defects coupled with disorganized ciliary beating drive abnormal cerebrospinal fluid flow and spine curvature in zebrafish.

Idiopathic scoliosis (IS) is the most common spinal deformity diagnosed in childhood or early adolescence, while the underlying pathogenesis of this serious condition remains largely unknown. Here, we report zebrafish ccdc57 mutants exhibiting scoliosis during late development, similar to that observed in human adolescent idiopathic scoliosis (AIS). Zebrafish ccdc57 mutants developed hydrocephalus due to cerebrospinal fluid (CSF) flow defects caused by uncoordinated cilia beating in ependymal cells. Mechanistically, Ccdc57 localizes to ciliary basal bodies and controls the planar polarity of ependymal cells through regulating the organization of microtubule networks and proper positioning of basal bodies. Interestingly, ependymal cell polarity defects were first observed in ccdc57 mutants at approximately 17 days postfertilization, the same time when scoliosis became apparent and prior to multiciliated ependymal cell maturation. We further showed that mutant spinal cord exhibited altered expression pattern of the Urotensin neuropeptides, in consistent with the curvature of the spine. Strikingly, human IS patients also displayed abnormal Urotensin signaling in paraspinal muscles. Altogether, our data suggest that ependymal polarity defects are one of the earliest sign of scoliosis in zebrafish and disclose the essential and conserved roles of Urotensin signaling during scoliosis progression.

Effects of Mycotoxin Fumagillin, Mevastatin, Radicicol, and Wortmannin on Photosynthesis of Chlamydomonas reinhardtii.

Mycotoxins are one of the most important sources for the discovery of new pesticides and drugs because of their chemical structural diversity and fascinating bioactivity as well as unique novel targets. Here, the effects of four mycotoxins, fumagillin, mevastatin, radicicol, and wortmannin, on photosynthesis were investigated to identify their precise sites of action on the photosynthetic apparatus of Chlamydomonas reinhardtii. Our results showed that these four mycotoxins have multiple targets, acting mainly on photosystem II (PSII). Their mode of action is similar to that of diuron, inhibiting electron flow beyond the primary quinone electron acceptor (QA) by binding to the secondary quinone electron acceptor (QB) site of the D1 protein, thereby affecting photosynthesis. The results of PSII oxygen evolution rate and chlorophyll (Chl) a fluorescence imaging suggested that fumagillin strongly inhibited overall PSII activity; the other three toxins also exhibited a negative influence at the high concentration. Chl a fluorescence kinetics and the JIP test showed that the inhibition of electron transport beyond QA was the most significant feature of the four mycotoxins. Fumagillin decreased the rate of O2 evolution by interrupting electron transfer on the PSII acceptor side, and had multiple negative effects on the primary photochemical reaction and PSII antenna size. Mevastatin caused a decrease in photosynthetic activity, mainly due to the inhibition of electron transport. Both radicicol and wortmannin decreased photosynthetic efficiency, mainly by inhibiting the electron transport efficiency of the PSII acceptor side and the activity of the PSII reaction centers. In addition, radicicol reduced the primary photochemical reaction efficiency and antenna size. The simulated molecular model of the four mycotoxins' binding to C. reinhardtii D1 protein indicated that the residue D1-Phe265 is their common site at the QB site. This is a novel target site different from those of commercial PSII herbicides. Thus, the interesting effects of the four mycotoxins on PSII suggested that they provide new ideas for the design of novel and efficient herbicide molecules.

Effect of Mycotoxin Cytochalasin A on Photosystem II in Ageratina adenophora.

Biological herbicides have received much attention due to their abundant resources, low development cost, unique targets and environmental friendliness. This study reveals some interesting effects of mycotoxin cytochalasin A (CA) on photosystem II (PSII). Our results suggested that CA causes leaf lesions on Ageratina adenophora due to its multiple effects on PSII. At a half-inhibitory concentration of 58.5 µΜ (I50, 58.5 µΜ), the rate of O2 evolution of PSII was significantly inhibited by CA. This indicates that CA possesses excellent phytotoxicity and exhibits potential herbicidal activity. Based on the increase in the J-step of the chlorophyll fluorescence rise OJIP curve and the analysis of some JIP-test parameters, similar to the classical herbicide diuron, CA interrupted PSII electron transfer beyond QA at the acceptor side, leading to damage to the PSII antenna structure and inactivation of reaction centers. Molecular docking model of CA and D1 protein of A. adenophora further suggests that CA directly targets the QB site of D1 protein. The potential hydrogen bonds are formed between CA and residues D1-His215, D1-Ala263 and D1-Ser264, respectively. The binding of CA to residue D1-Ala263 is novel. Thus, CA is a new natural PSII inhibitor. These results clarify the mode of action of CA in photosynthesis, providing valuable information and potential implications for the design of novel bioherbicides.

Mediating pathways of neuroticism and social anxiety in the relationship between childhood trauma and the fear of missing out among Chinese college students.

Recent research has identified various risk factors for fear of missing out. However, studies on the potential influence of childhood trauma on the fear of missing out remain scarce, and little is known regarding the mediating mechanisms underlying this relationship. In this study, we examine the predictive role of childhood trauma on the fear of missing out among college students and investigate whether neuroticism and social anxiety mediate the relationship between childhood trauma and the fear of missing out. A sample of 1,266 Chinese college students completed questionnaires regarding childhood trauma, neuroticism, social anxiety, and the fear of missing out. The results indicated that (a) childhood trauma is positively associated with the fear of missing out, (b) both neuroticism and social anxiety mediate the relationship between childhood trauma and the fear of missing out, and (c) neuroticism and social anxiety sequentially mediate the relationship between childhood trauma and the fear of missing out. These findings have crucial implications for the prevention and intervention of the fear of missing out among college students.

Predicting Adhesive Free Energies of Polymer-Surface Interactions with Machine Learning.

Polymer-surface interactions are crucial to many biological processes and industrial applications. Here we propose a machine learning method to connect a model polymer's sequence with its adhesion to decorated surfaces. We simulate the adhesive free energies of 20000 unique coarse-grained one-dimensional polymer sequences interacting with functionalized surfaces and build support vector regression models that demonstrate inexpensive and reliable prediction of the adhesive free energy as a function of sequence. Our work highlights the promising integration of coarse-grained simulation with data-driven machine learning methods for the design of functional polymers and represents an important step toward linking polymer compositions with polymer-surface interactions.

Free-Energy Landscape and Isomerization Rates of Au4 Clusters at Finite Temperatures.

In metallic nanoparticles, the geometry of atomic positions controls the particle's electronic band structure, polarizability, and catalytic properties. Analyzing the structural properties is a complex problem; the structure of an assembled cluster changes from moment to moment due to thermal fluctuations. Conventional structural analyses based on spectroscopy or diffraction cannot determine the instantaneous structure exactly and can merely provide an averaged structure. Molecular simulations offer an opportunity to examine the assembly and evolution of metallic clusters, as the preferred assemblies and conformations can easily be visualized and explored. Here, we utilize the adaptive biasing force algorithm applied to first-principles molecular dynamics to demonstrate the exploration of a relatively simple system, which permits a comprehensive study of the small metal cluster Au4 in both neutral and charged configurations. Our simulation work offers a quantitative understanding of these clusters' dynamic structure, which is significant for single-site catalytic reactions on metal clusters and provides a starting point for a detailed quantitative understanding of more complex pure metal and alloy clusters' dynamic properties.