Precision classification and quantitative analysis of bacteria biomarkers via surface-enhanced Raman spectroscopy and machine learning

The SERS spectra of six bacterial biomarkers, 2,3-DHBA, 2,5-DHBA, Pyocyanin, lipoteichoic acid (LTA), Enterobactin, and β-carotene, of various concentrations, were obtained from silver nanorod array substrates, and the spectral peaks and the corresponding vibrational modes were identified to classify different spectra. The spectral variations in three different concentration regions due to various reasons have imposed a challenge to use classic calibration curve methods to quantify the concentration of biomarkers. Depending on baseline removal strategy, i.e., local or global baseline removal, the calibration curve differed significantly. With the aid of convolutional neural network (CNN), a two-step process was established to classify and quantify biomarker solutions based on SERS spectra: using a specific CNN model, a remarkable differentiation and classification accuracy of 99.99 % for all six biomarkers regardless of the concentration can be achieved. After classification, six regression CNN models were established to predict the concentration of biomarkers, with coefficient of determination R2 > 0.97 and mean absolute error (MAE) < 0.27. The feature of important calculations indicates the high classification and quantification accuracies were due to the intrinsic spectral features in SERS spectra. This study showcases the synergistic potential of SERS and advanced machine learning algorithms and holds significant promise for bacterial infection diagnostics.

Plasmon-driven substitution of 4-mercaptophenylboronic acid to 4-nitrothiophenol monitored by surface-enhanced Raman spectroscopy

Plasmon-driven reactions on plasmonic nanoparticles (NPs) occur under significantly different conditions from those of classical organic synthesis and provide a promising pathway for enhancing the efficiency of various chemical processes. However, these reactions can also have undesirable effects, such as 4-mercaptophenylboronic acid (MPBA) deboronation. MPBA chemisorbs well to Ag NPs through its thiol group and can subsequently bind to diols, enabling the detection of various biological structures by surface-enhanced Raman scattering (SERS), but not upon its deboronation. To avoid this reaction, we investigated the experimental conditions of MPBA deboronation on Ag NPs by SERS. Our results showed that the level of deboronation strongly depends on both the morphology of the system and the excitation laser wavelength and power. In addition, we detected not only the expected products, namely thiophenol and biphenyl-4,4-dithiol, but also 4-nitrothiophenol (NTP). The crucial reagent for NTP formation was an oxidation product of hydroxylamine hydrochloride, the reduction agent used in Ag NP synthesis. Ultimately, this reaction was replicated by adding NaNO2 to the system, and its progress was monitored as a function of the laser power, thereby identifying a new reaction of plasmon-driven -B(OH)2 substitution for -NO2.

Plasmonics nanorod biosensor for in situ intracellular detection of gene expression biomarkers in intact plant systems

The intracellular developmental processes in plants, particularly concerning lignin polymer formation and biomass production are regulated by microRNAs (miRNAs). MiRNAs including miR397b are important for developing efficient and cost-effective biofuels. However, traditional methods of monitoring miRNA expression, like PCR, are time-consuming, require sample extraction, and lack spatial and temporal resolution, especially in real-world conditions. We present a novel approach using plasmonics nanosensing to monitor miRNA activity within living plant cells without sample extraction. Plasmonic biosensors using surface-enhanced Raman scattering (SERS) detection offer high sensitivity and precise molecular information. We used the Inverse Molecular Sentinel (iMS) biosensor on unique silver-coated gold nanorods (AuNR@Ag) with a high-aspect ratio to penetrate plant cell walls for detecting miR397b within intact living plant cells. MiR397b overexpression has shown promise in reducing lignin content. Thus, monitoring miR397b is essential for cost-effective biofuel generation. This study demonstrates the infiltration of nanorod iMS biosensors and detection of non-native miRNA 397b within plant cells for the first time. The investigation successfully demonstrates the localization of nanorod iMS biosensors through TEM and XRF-based elemental mapping for miRNA detection within plant cells of Nicotiana benthamiana. The study integrates shifted-excitation Raman difference spectroscopy (SERDS) to decrease background interference and enhance target signal extraction. In vivo SERDS testing confirms the dynamic detection of miR397b in Arabidopsis thaliana leaves after infiltration with iMS nanorods and miR397b target. This proof-of-concept study is an important stepping stone towards spatially resolved, intracellular miRNA mapping to monitor biomarkers and biological pathways for developing efficient renewable biofuel sources.

Aquaporin-0-protein interactions elucidated by crosslinking mass spectrometry

Aquaporin-0 (AQP0) constitutes 50 % of the lens membrane proteome and plays important roles in lens fiber cell adhesion, water permeability, and lens transparency. Previous work has shown that specific proteins, such as calmodulin (CaM), interact with AQP0 to modulate its water permeability; however, these studies often used AQP0 peptides, rather than full-length protein, to probe these interactions. Furthermore, the specific regions of interaction of several known AQP0 interacting partners, i.e. αA and αB-crystallins, and phakinin (CP49) remain unknown. The purpose of this study was to use crosslinking mass spectrometry (XL-MS) to identify interacting proteins with full-length AQP0 in crude lens cortical membrane fractions and to determine the specific protein regions of interaction. Our results demonstrate, for the first time, that the AQP0 N-terminus can engage in protein interactions. Specific regions of interaction are elucidated for several AQP0 interacting partners including phakinin, α-crystallin, connexin-46, and connexin-50. In addition, two new interacting partners, vimentin and connexin-46, were identified.

Inside of the burst-phase intermediate of a protein folding. Hydration of hydrophobic groups

The thermal effect of the formation of the "burst-phase" folding intermediate has been studied using a titration calorimeter. It is shown that, unlike the total thermal effect of native structure formation, it can be both positive and negative depending on the temperature. The reasons for this paradoxical behavior are analyzed. A conclusion is drawn about the leading role of dehydration of non-polar groups in the first stage of folding.

Rapid detection of tebuconazole based on hydrogel SERS chips

Tebuconazole is one of the most commonly used fungicides in agricultural production, that has the merits of highly effectiveness, broad spectrum and systemic function. Excessive tebuconazole may pose a great threat to human and animal health. Traditional detection techniques for tebuconazole usually have limitations such as expensive equipment, poor antibody stability, and time-consuming procedures. Herein, a sensitive sensor is developed for the rapid detection of tebuconazole based on hydrogel surface-enhanced Raman scattering (SERS) chips. Aggregated Ag nanoparticles (a-AgNPs) with tunable localized surface plasmon resonance (LSPR) wavelength are in-situ synthesized in polyvinyl alcohol (PVA) solution for preparing hydrogel SERS chips. Three hydrogel SERS chips are obtained to match the three commonly used laser wavelengths. On the basis, a match laser wavelength is selected according to the energy levels of tebuconazole and the Fermi level of a-AgNPs to gain a strong chemical enhancement. At the same time, the chip with a corresponding LSPR wavelength to the laser is applied to obtain a strong electromagnetic enhancement. Thus, highly sensitive SERS signal of tebuconazole is obtained. Furthermore, the obtained hydrogel SERS chips have good repeatability, outstanding reproducibility and strong anti-interference ability, and show outstanding reliability in practical applications. As a result, the SERS chips offer a reliable and convenient platform for the quick detection of tebuconazole in foods. The detection limit is as low as 1 ppb, and the recoveries is distributed in the range of 94.66-106.70 %. This work would promote greatly the application of SERS in small molecule detection.

Fourier transform-based post-processing drift compensation and calibration method for scanning probe microscopy

Scanning probe microscopy (SPM) is ubiquitous in nanoscale science allowing the observation of features in real space down to the angstrom resolution. The scanning nature of SPM, wherein a sharp tip rasters the surface during which a physical setpoint is maintained via a control feedback loop, often implies that the image is subject to drift effects, leading to distortion of the resulting image. While there are in-operando methods to compensate for the drift, correcting the residual linear drift in obtained images is often neglected. In this paper, we present a reciprocal space-based technique to compensate the linear drift in atomically-resolved scanning probe microscopy images without distinction of the fast and slow scanning directions; furthermore this method does not require the set of SPM images obtained for the different scanning directions. Instead, the compensation is made possible by the a priori knowledge of the lattice parameters. The method can also be used to characterize and calibrate the SPM instrument.

Understanding the structural dynamics of human islet amyloid polypeptide: Advancements in and applications of ion-mobility mass spectrometry

Human islet amyloid polypeptide (hIAPP) forms amyloid deposits that contribute to β-cell death in pancreatic islets and are considered a hallmark of Type II diabetes Mellitus (T2DM). Evidence suggests that the early oligomers of hIAPP formed during the aggregation process are the primary pathological agent in islet amyloid induced β-cell death. The self-assembly mechanism of hIAPP, however, remains elusive, largely due to limitations in conventional biophysical techniques for probing the distribution or capturing detailed structures of the early, structurally dynamic oligomers. The advent of Ion-mobility Mass Spectrometry (IM-MS) has enabled the characterisation of hIAPP early oligomers in the gas phase, paving the way towards a deeper understanding of the oligomerisation mechanism and the correlation of structural information with the cytotoxicity of the oligomers. The sensitivity and the rapid structural characterisation provided by IM-MS also show promise in screening hIAPP inhibitors, categorising their modes of inhibition through "spectral fingerprints". This review delves into the application of IM-MS to the dissection of the complex steps of hIAPP oligomerisation, examining the inhibitory influence of metal ions, and exploring the characterisation of hetero-oligomerisation with different hIAPP variants. We highlight the potential of IM-MS as a tool for the high-throughput screening of hIAPP inhibitors, and for providing insights into their modes of action. Finally, we discuss advances afforded by recent advancements in tandem IM-MS and the combination of gas phase spectroscopy with IM-MS, which promise to deliver a more sensitive and higher-resolution structural portrait of hIAPP oligomers. Such information may help facilitate a new era of targeted therapeutic strategies for islet amyloidosis in T2DM.

A novel near-infrared polymethine dye biosensor for rapid and selective detection of lithocholic acid

Lithocholic acid (LCA), a secondary bile acid, has emerged as a potential early diagnostic biomarker for various liver diseases. In this study, we introduce a novel near-infrared (NIR) polymethine dye-based biosensor, capable of sensitive and selective detection of LCA in phosphate buffer and artificial urine (AU) solutions. The detection mechanism relies on the formation of J-aggregates resulting from the interplay of 3,3-Diethylthiatricarbocyanine iodide (DiSC2(7)) dye molecules and LCA, which induces a distinctive red shift in both absorption and fluorescence spectra. The biosensor demonstrates a detection limit for LCA of 70 μM in PBS solution (pH 7.4), while in AU solution, it responds to an LCA concentration as low as ∼60 μM. Notably, the proposed biosensor exhibits outstanding selectivity for LCA, effectively distinguishing it from common interferents such as uric acid, ascorbic acid, and glucose. This rapid, straightforward, and cost-effective spectrometer-based method underscores its potential for early diagnosis of liver diseases by monitoring LCA concentrations.

Selective molecular characterization of organic aerosols using in situ laser desorption ionization mass spectrometry

RATIONALE

The sources and chemical compositions of organic aerosol (OA) exert a significant influence on both regional and global atmospheric conditions, thereby having far-reaching implications on environmental chemistry. However, existing mass spectrometry (MS) methods have limitations in characterizing the detailed composition of OA due to selective ionization as well as fractionation during cold-water extraction and solid-phase extraction (SPE).

METHODS

A comprehensive MS study was conducted using aerosol samples collected on dusty, clean, and polluted days. To supplement the data obtained from electrospray ionization (ESI), a strategy for analyzing OAs collected using the quartz fiber filter directly utilizing laser desorption ionization (LDI) was employed. Additionally, the ESI method was conducted to explore suitable approaches for determining various OA compositions from samples collected on dusty, clean, and polluted days.

RESULTS

In situ LDI has the advantages of significantly reducing the sample volume, simplifying sample preparation, and overcoming the problem of overestimating sulfur-containing compounds usually encountered in ESI. It is suitable for the characterization of highly unsaturated and hydrophobic aerosols, such as brown carbon-type compounds with low volatility and high stability, which is supplementary to ESI.

CONCLUSIONS

Compared with other ionization methods, in situ LDI helps provide a complementary description of the molecular compositions of OAs, especially for analyzing OAs in polluted day samples. This method may contribute to a more comprehensive MS analysis of the elusive compositions and sources of OA in the atmosphere.

LC-MS and MALDI-MSI-based metabolomic approaches provide insights into the spatial-temporal metabolite profiles of Tartary buckwheat achene development

Tartary buckwheat, celebrated as the "king of grains" for its flavonoid and phenolic acid richness, has health-promoting properties. Despite significant morphological and metabolic variations in mature achenes, research on their developmental process is limited. Utilizing Liquid chromatography-mass spectrometry and atmospheric pressure matrix-assisted laser desorption/ionization mass spectrometry imaging, we conducted spatial-temporal metabolomics on two cultivars during achene development. Metabolic profiles including 17 phenolic acids and 83 flavonoids are influenced by both varietal distinctions and developmental intricacies. Notably, flavonols, as major flavonoids, accumulated with achene ripening and showed a tissue-specific distribution. Specifically, flavonol glycosides and aglycones concentrated in the embryo, while methylated flavonols and procyanidins in the hull. Black achenes at the green achene stage have higher bioactive compounds and enhanced antioxidant capacity. These findings provide insights into spatial and temporal characteristics of metabolites in Tartary buckwheat achenes and serve as a theoretical guide for selecting optimal resources for food production.

Extended N-centered ensemble density functional theory of double electronic excitations

A recent work (arXiv:2401.04685) has merged N-centered ensembles of neutral and charged electronic ground states with ensembles of neutral ground and excited states, thus providing a general and in-principle exact (so-called extended N-centered) ensemble density functional theory of neutral and charged electronic excitations. This formalism made it possible to revisit the concept of density-functional derivative discontinuity, in the particular case of single excitations from the highest occupied Kohn-Sham (KS) molecular orbital, without invoking the usual "asymptotic behavior of the density" argument. In this work, we address a broader class of excitations, with a particular focus on double excitations. An exact implementation of the theory is presented for the two-electron Hubbard dimer model. A thorough comparison of the true physical ground- and excited-state electronic structures with that of the fictitious ensemble density-functional KS system is also presented. Depending on the choice of the density-functional ensemble as well as the asymmetry of the dimer and the correlation strength, an inversion of states can be observed. In some other cases, the strong mixture of KS states within the true physical system makes the assignment "single excitation" or "double excitation" irrelevant.

Theoretical calculations and experimental verification of carbon dioxide reduction electrocatalyzed by metalloporphyrin

Metal-functionalized porphyrin-like graphene structures are promising electrocatalysts for carbon dioxide reduction reaction (CO2RR) as their metal centers can modulate activity. Yet, the role of metal center of metalloporphyrins (MTPPs) in CO2 reaction activity is still lacking deep understanding. Here, CO2RR mechanism on MTPPs with five different metal centers (M = Fe, Co, Cu, Zn and Ni) are examined by first-principles calculations. The *COOH formation is the rate determined step on the five MTPP structures, and the CoTPP exhibits the best CO2RR activity while ZnTPP and NiTPP are the worst, which is also verified by our experiment. The CO2RR activity is controlled by adsorption states of intermediates (*CO, *COOH), i.e., chemisorption (e.g., on CoTPP) and physisorption (on ZnTPP and NiTPP) of intermediates will lead to good and poor activity, respectively. The deeper the d-band center of the porphyrin ring complexed metal atom, the weaker bonding of MTPP with CO and COOH. Theoretical calculations and experimental results indicate that MTPPs with Co and Fe centers lead to a reduction in the energy barriers for the two uphill reaction steps in the electrocatalytic CO2 reduction process, thereby enhancing CO2 reduction electrocatalytic activity. Faradaic efficiency of CO is correlated with the reaction energy barrier of the first proton-coupled electron reduction process, displaying a strong linear correlation. This work provides a fundamental understanding of MTPPs used as electrocatalysts for CO2RR.

A review on intelligence of cellulose based materials

Cellulose based materials are widely used in various fields such as papermaking, packaging, composite materials, textiles and clothing due to their diverse types, environmental friendliness, natural degradation, high specific strength, and low cost. The intelligence of cellulose based materials will further expand their application fields. This article first gives an in-depth analyzation on the intelligent structural design of these materials according to the two major categories of isotropic and anisotropic, then lists the main preparation methods of cellulose based intelligent materials. Subsequently, this article systematically summarizes the recent intelligent response methods and characteristics of cellulose based materials, and extensively elaborates on the intelligent application of these materials. Finally, the prospects for the intelligence of cellulose based materials are discussed.

A study of particle dry deposition parameterizations in an atmospheric radioactive preparedness model: Application to the Chernobyl case

Parameterization of dry deposition is key for modelling of atmospheric transport and deposition of radioactive particles. Still, very simple parameterizations are often encountered in radioactive preparedness models such as the SNAP model (SNAP=Severe Nuclear Accident Program) of the Norwegian Meteorological Institute. In SNAP a constant dry deposition velocity (=0.2 cm/s) neglecting aerodynamic and surface resistances, is presently used. Therefore, two new dry depositions schemes (the Emerson scheme and the EMEP (European Monitoring and Evaluation Programme) scheme) have been implemented in SNAP to evaluate the benefits of including aerodynamic and surface resistances codes with respect to model prediction skills. The three dry deposition schemes are evaluated using 137Cs total deposition from soil sample data (n = 540) for a 60 km radial zone out from the Chernobyl Nuclear Power Plant (ChNPP) collected during the months after the accident. The present study capitalizes on high resolution meteorological data (2.5 km horizontal resolution), a detailed land-use data set with 273 sub-classes and the hitherto most comprehensive source term description for the Chernobyl accident. Based on our findings it is recommended to replace the present simple SNAP scheme with the Emerson or EMEP dry deposition scheme.

Machine learning for accuracy in density functional approximations

Machine learning techniques have found their way into computational chemistry as indispensable tools to accelerate atomistic simulations and materials design. In addition, machine learning approaches hold the potential to boost the predictive power of computationally efficient electronic structure methods, such as density functional theory, to chemical accuracy and to correct for fundamental errors in density functional approaches. Here, recent progress in applying machine learning to improve the accuracy of density functional and related approximations is reviewed. Promises and challenges in devising machine learning models transferable between different chemistries and materials classes are discussed with the help of examples applying promising models to systems far outside their training sets.

Improving the reliability of machine learned potentials for modeling inhomogeneous liquids

The atomic-scale response of inhomogeneous fluids at interfaces and surrounding solute particles plays a critical role in governing chemical, electrochemical, and biological processes. Classical molecular dynamics simulations have been applied extensively to simulate the response of fluids to inhomogeneities directly, but are limited by the accuracy of the underlying interatomic potentials. Here, we use neural network potentials (NNPs) trained to ab initio simulations to accurately predict the inhomogeneous responses of two distinct fluids: liquid water and molten NaCl. Although NNPs can be readily trained to model complex bulk systems across a range of state points, we show that to appropriately model a fluid's response at an interface, relevant inhomogeneous configurations must be included in the training data. In order to sufficiently sample appropriate configurations of such inhomogeneous fluids, we develop protocols based on molecular dynamics simulations in the presence of external potentials. We demonstrate that NNPs trained on inhomogeneous fluid configurations can more accurately predict several key properties of fluids-including the density response, surface tension and size-dependent cavitation free energies-for liquid water and molten NaCl, compared to both empirical interatomic potentials and NNPs that are not trained on such inhomogeneous configurations. This work therefore provides a first demonstration and framework to extract the response of inhomogeneous fluids from first principles for classical density-functional treatment of fluids free from empirical potentials.

Recent advancements of smartphone-based sensing technology for diagnosis, food safety analysis, and environmental monitoring

The emergence of computationally powerful smartphones, relatively affordable high-resolution camera, drones, and robotic sensors have ushered in a new age of advanced sensible monitoring tools. The present review article investigates the burgeoning smartphone-based sensing paradigms, including surface plasmon resonance (SPR) biosensors, electrochemical biosensors, colorimetric biosensors, and other innovations for modern healthcare. Despite the significant advancements, there are still scarcity of commercially available smart biosensors and hence need to accelerate the rates of technology transfer, application, and user acceptability. The application/necessity of smartphone-based biosensors for Point of Care (POC) testing, such as prognosis, self-diagnosis, monitoring, and treatment selection, have brought remarkable innovations which eventually eliminate sample transportation, sample processing time, and result in rapid findings. Additionally, it articulates recent advances in various smartphone-based multiplexed bio sensors as affordable and portable sensing platforms for point-of-care devices, together with statistics for point-of-care health monitoring and their prospective commercial viability.

Aging of the eye: Lessons from cataracts and age-related macular degeneration

Aging is the greatest risk factor for chronic human diseases, including many eye diseases. Geroscience aims to understand the effects of the aging process on these diseases, including the genetic, molecular, and cellular mechanisms that underlie the increased risk of disease over the lifetime. Understanding of the aging eye increases general knowledge of the cellular physiology impacted by aging processes at various biological extremes. Two major diseases, age-related cataract and age-related macular degeneration (AMD) are caused by dysfunction of the lens and retina, respectively. Lens transparency and light refraction are mediated by lens fiber cells lacking nuclei and other organelles, which provides a unique opportunity to study a single aging hallmark, i.e., loss of proteostasis, within an environment of limited metabolism. In AMD, local dysfunction of the photoreceptors/retinal pigmented epithelium/Bruch's membrane/choriocapillaris complex in the macula leads to the loss of photoreceptors and eventually loss of central vision, and is driven by nearly all the hallmarks of aging and shares features with Alzheimer's disease, Parkinson's disease, cardiovascular disease, and diabetes. The aging eye can function as a model for studying basic mechanisms of aging and, vice versa, well-defined hallmarks of aging can be used as tools to understand age-related eye disease.

Curcumin-derivatives as fluorescence-electrochemical dual probe for ultrasensitive detections of picric acid in aqueous media

We are reporting the two curcumin derivatives, ferrocenyl curcumin (Fc-cur) and 4-nitro-benzylidene curcumin (NBC), as a probe through dual modalities, i.e., fluorescence and electrochemical methods, for the detection of nitro-analytes, such as picric acid (PA). The probes exhibited aggregation-induced enhanced emission (AIEE), and the addition of picric acid (PA) demonstrated good and specific fluorimetric identification of PA in the aggregated state. By using density functional theory (DFT), the mechanism of picric acid's (PA) interactions with the probes was further investigated. DFT studies shows evidence of charge transfer from curcumin derivatives probe to picric acid resulting into the formation of an adduct. The reduction of trinitrophenol (PA) to 2, 4, 6-trinitrosophenol was investigated utilizing a probe-modified glassy carbon electrode (GCE) with a good detection limit of 9.63 ± 0.001 pM and 41.01 ± 0.002 pM, respectively, for Fc-cur@GCE and NBC@GCE, taking into account the redox behavior of the probe. The applicability of the designed sensor has been utilized for real-time application in the estimation of picric acid in several water samples collected from the different source.

Temperature-resilient and sustainable Mn-MOF oxidase-like nanozyme (UoZ-4) for total antioxidant capacity sensing in some citrus fruits: Breaking the temperature barrier

Current nanozyme applications rely heavily on peroxidase-like nanozymes and are limited to a specific temperature range, despite notable advancements in nanozyme development. In this work, we designed novel Mn-based metal organic frameworks (UoZ-4), with excellent oxidase mimic activity towards common substrates. UoZ-4 showed excellent oxidase-like activity (with Km 0.072 mM) in a wide range of temperature, from 10 °C to 100 °C with almost no activity loss, making it a very strong candidate for psychrophilic and thermophilic applications. Ascorbic acid, cysteine, and glutathione could quench the appearance of the blue color of oxTMB, led us to design a visual-based sensing platform for detection of total antioxidant capacity (TAC) in cold, mild and hot conditions. The visual mode successfully assessed TAC in citrus fruits with satisfactory recovery and precisions. Cold/hot adapted and magnetic property will broaden the horizon of nanozyme applications and breaks the notion of the temperature limitation of enzymes.

Surface-enhanced Raman scattering-based identification of breast cancer progression using extracellular vesicles-derived integrin α6β4

Detection of progression is of great importance to breast cancer treatment and can benefit patients. Limited by current detection technologies and biomarkers, early breast cancer progression diagnosis remains challenging. Researchers have found blood extracellular vesicles (EVs)-derived integrin α6β4 directly facilitate progression in breast cancer, enabling cancer detection. However, EVs size and heterogeneity hinder protein detection, masked by abundant background EVs. Hence, novel tools for efficient detection of EVs with high selectivity and low interference are significantly desired. Here, a new silver-coated gold nanorods SERS probe, termed as Au@Ag@IDA-B/4MSTP, based on DNA aptamer was established for the detection of integrin α6β4 derived from EVs. Validation of the Au@Ag@IDA-B/4MSTP probes using cell-culture-derived EVs revealed a LOD of 23 particles/μL for EVs detection. This tool was further confirmed to mimic the real state of cancer with subcutaneous tumor model and lung metastasis model in mice. With 10 μL of blood plasma and simple Raman analysis process, the test achieved 85.7 % sensitivity and 83.3 % specificity. Moreover, our method achieves a simplified approach that expedites the detection process. These results demonstrate the good detection performance of Au@Ag@IDA-B/4MSTP probes for EVs integrin α6β4, and suggest that this non-invasive approach could be a promising tool for early detection of breast cancer progression.

Synechococcus sp. PCC7335 responses to far-red enriched spectra and anoxic/microoxic atmospheres: Potential for astrobiotechnological applications

Recently, cyanobacteria have gained attention in space exploration to support long-term crewed missions via Bioregenerative Life Support Systems. In this frame, cyanobacteria would provide biomass and profitable biomolecules through oxygenic photosynthesis, uptaking CO2, and releasing breathable O2. Their growth potential and organic matter production will depend on their ability to photoacclimate to different light intensities and spectra, maximizing incident light harvesting. Studying cyanobacteria responses to different light regimes will also benefit the broader field of astrobiology, providing data on the possibility of oxygenic photosynthetic life on planets orbiting stars with emission spectra different than the Sun. Here, we tested the acclimation and productivity of Synechococcus sp. PCC7335 (hereafter PCC7335), capable of Far-Red Light Photoacclimation (FaRLiP) and type III chromatic acclimation (CA3), in an anoxic, CO2-enriched atmosphere and under a spectrum simulating the low energetic light regime of an M-dwarf star, also comparable to a subsuperficial environment. When exposed to the light spectrum, with few photons in the visible (VIS) and rich in far-red (FR), PCC7335 did not activate FaRLiP but acclimated only via CA3, achieving a biomass productivity higher than expected, considering the low VIS light availability, and a higher production of phycocyanin, a valuable pigment, with respect to solar light. Its growth or physiological responses of PCC7335 were not affected by the anoxic atmosphere. In these conditions, PCC7335 efficiently produced O2 and scavenged CO2. Results highlight the photosynthetic plasticity of PCC7335, its suitability for astrobiotechnological applications, and the importance to investigate biodiversity of oxygenic photosynthesis for searching life beyond Earth.

Microalgal extracellular polymeric substances (EPS) and their roles in cultivation, biomass harvesting, and bioproducts extraction

Microalgae extracellular polymeric substances (EPS) are complex high-molecular-weight polymers and the physicochemical properties of EPS strongly affect the core features of microalgae cultivation and resource utilization. Revealing the key roles of EPS in microalgae life-cycle processes in an interesting and novelty topic to achieve energy-efficient practical application of microalgae. This review found that EPS showed positive effect in non-gas uptake, extracellular electron transfer, toxicity resistance and heterotrophic symbiosis, but negative impact in gas transfer and light utilization during microalgae cultivation. For biomass harvesting, EPS favored biomass flocculation and large-size cell self-flocculation, but unfavored small size microalgae self-flocculation, membrane filtration, charge neutralization and biomass dewatering. During bioproducts extraction, EPS exhibited positive impact in extractant uptake, but the opposite effect in cellular membrane permeability and cell rupture. Future research on microalgal EPS were also identified, which offer suggestions for comprehensive understanding of microalgal EPS roles in various scenarios.

Vibrational spectroscopy coupled with machine learning sheds light on the cellular effects induced by rationally designed TLR4 agonists

In this work, we present the potential of Fourier transform infrared (FTIR) microspectroscopy to compare on whole cells, in an unbiased and untargeted way, the capacity of bacterial lipopolysaccharide (LPS) and two rationally designed molecules (FP20 and FP20Rha) to activate molecular circuits of innate immunity. These compounds are important drug hits in the development of vaccine adjuvants and tumor immunotherapeutics. The biological assays indicated that FP20Rha was more potent than FP20 in inducing cytokine production in cells and in stimulating IgG antibody production post-vaccination in mice. Accordingly, the overall significant IR spectral changes induced by the treatment with LPS and FP20Rha were similar, lipids and glycans signals being the most diagnostic, while the effect of the less potent molecule FP20 on cells resulted to be closer to control untreated cells. We propose here the use of FTIR spectroscopy supported by artificial intelligence (AI) to achieve a more holistic understanding of the cell response to new drug candidates while screening them in cells.

Emerging trends and future challenges of advanced 2D nanomaterials for combating bacterial resistance

The number of multi-drug-resistant bacteria has increased over the last few decades, which has caused a detrimental impact on public health worldwide. In resolving antibiotic resistance development among different bacterial communities, new antimicrobial agents and nanoparticle-based strategies need to be designed foreseeing the slow discovery of new functioning antibiotics. Advanced research studies have revealed the significant disinfection potential of two-dimensional nanomaterials (2D NMs) to be severed as effective antibacterial agents due to their unique physicochemical properties. This review covers the current research progress of 2D NMs-based antibacterial strategies based on an inclusive explanation of 2D NMs' impact as antibacterial agents, including a detailed introduction to each possible well-known antibacterial mechanism. The impact of the physicochemical properties of 2D NMs on their antibacterial activities has been deliberated while explaining the toxic effects of 2D NMs and discussing their biomedical significance, dysbiosis, and cellular nanotoxicity. Adding to the challenges, we also discussed the major issues regarding the current quality and availability of nanotoxicity data. However, smart advancements are required to fabricate biocompatible 2D antibacterial NMs and exploit their potential to combat bacterial resistance clinically.

Elucidating the roles of electrolytes and hydrogen bonding in the dewetting dynamics of the tear film

This study explores the impact of electrostatic interactions and hydrogen bonding on tear film stability, a crucial factor for ocular surface health. While mucosal and meibomian layers have been extensively studied, the role of electrolytes in the aqueous phase remains unclear. Dry eye syndrome, characterized by insufficient tear quantity or quality, is associated with hyperosmolality, making electrolyte composition an important factor that might impact tear stability. Using a model buffer solution on a silica glass dome, we simulated physiologically relevant tear film conditions. Sodium chloride alone induced premature dewetting through salt crystal nucleation. In contrast, trace amounts of solutes with hydroxyl groups (sodium phosphate dibasic, potassium phosphate monobasic, and glucose) exhibited intriguing phenomena: quasi-stable films, solutal Marangoni-driven fluid influx increasing film thickness, and viscous fingering due to Saffman-Taylor instability. These observations are rationalized by the association of salt solutions with increased surface tension and the propensity of hydroxyl-group-containing solutes to engage in significant hydrogen bonding, altering local viscosity. This creates a viscosity contrast between the bulk buffer solution and the film region. Moreover, these solutes shield the glass dome, counteracting sodium chloride crystallization. These insights not only advance our understanding of tear film mechanics but also pave the way for predictive diagnostics in dry eye syndrome, offering a robust platform for personalized medical interventions based on individual tear film composition.

A Systematic Study of Methyl Carbodithioate Esters as Effective Gold Contact Groups for Single-Molecule Electronics

There are several binding groups used within molecular electronics for anchoring molecules to metal electrodes (e.g., R-SMe, R-NH2, R-CS2 -, R-S-). However, some anchoring groups that bind strongly to electrodes have poor/unknown stability, some have weak electrode coupling, while for some their binding motifs are not well defined. Further binding groups are required to aid molecular design and to achieve a suitable balance in performance across a range of properties. We present an in-depth investigation into the use of carbodithioate esters as contact groups for single-molecule conductance measurements, using scanning tunnelling microscopy break junction measurements (STM-BJ) and detailed surface spectroscopic analysis. We demonstrate that the methyl carbodithioate ester acts as an effective contact for gold electrodes in STM-BJ measurements. Surface enhanced Raman measurements demonstrate that the C=S functionality remains intact when adsorbed on to gold nanoparticles. A gold(I) complex was also synthesised showing a stable C=S→AuI interaction from the ester. Comparison with a benzyl thiomethyl ether demonstrates that the C=S moiety significantly contributes to charge transport in single-molecule junctions. The overall performance of the CS2Me group demonstrates it should be used more extensively and has strong potential for the fabrication of larger area devices with long-term stability.

Time-dependent surface-enhanced Raman scattering: A theoretical approach

A new procedure for computing the time-dependent Raman scattering of molecules in the proximity of plasmonic nanoparticles (NPs) is proposed, drawing inspiration from the pioneering Lee and Heller's theory. This strategy is based on a preliminary simulation of the molecular vibronic wavefunction in the presence of a plasmonic nanostructure and an incident light pulse. Subsequently, the Raman signal is evaluated through an inverse Fourier Transform of the coefficients' dynamics. Employing a multiscale approach, the system is treated by coupling the quantum mechanical description of the molecule with the polarizable continuum model for the NP. This method offers a unique advantage by providing insights into the time evolution of the plasmon-enhanced Raman signal, tracking the dynamics of the incident electric field. It not only provides for the total Raman signal at the process's conclusion but also gives transient information. Importantly, the flexibility of this approach allows for the simulation of various incident electric field profiles, enabling a closer alignment with experimental setups. This adaptability ensures that the method is relevant and applicable to diverse real-world scenarios.

Collision of rare-gas atoms on helium nanodroplets: Theoretical evidence for an efficient coagulation of heavy rare-gas atoms

The coagulation of rare-gas atoms (RG = Ne, Ar, Kr, Xe, and Rn) in helium nanodroplets (HNDs) composed of 1000 atoms is investigated by zero-point averaged dynamics where a He-He pseudopotential is used to make the droplet liquid with proper energies. This method reproduces the qualitative abundances of embedded Arn+1 structures obtained by Time-Dependent Density Functional Theory and Ring Polymer Molecular Dynamics for Ar + ArnHe1000 collisions at realistic projectile speeds and impact parameters. More generally, coagulation is found to be much more efficient for heavy rare-gases (Xe and Rn) than for light ones (Ne and Ar), a behavior mainly attributed to a slower energy dissipation of the projectile in the HND. When coagulation does not occur, the projectile maintains a speed of 10-30 m s-1 within the HND, but its velocity vector is rarely oriented toward the dopant, and the projectile roams in a limited region of the droplet. The structure of embedded RGn+1 clusters does not systematically match their gas-phase global minimum structure, and more than 30% of RGn-RG unbound structures are due to one He atom located in between the projectile and a dopant atom.

Event horizon kinetic Monte Carlo

In this study, we present a novel approach for modeling the dynamics of stochastic processes. The fundamental concept involves constructing a stochastic Markov chain comprising states separated by more than one stochastic event. Initially, the method explores the network of neighboring states connected by stochastic events. This exploration results in a "horizon" of events leading to a set of "boundary" states at the periphery of each local network. Subsequently, the next member in the Markov chain is selected from the "boundary" states based on the probability of reaching each of the "boundary" states for the first time. Meanwhile, the simulation clock is updated according to the time required to reach the boundary for the first time. This can be achieved using an analytical approach, where the probability of reaching each boundary state for the first time is estimated using absorbing conditions for all boundary states in the analytical solution of a master equation describing the local network of states around each current state. The proposed method is demonstrated in modeling the dynamics in networks of stochastic reactions but can be easily applied in any stochastic system whose dynamics can be expressed via the solution of a master equation. It is expected to enhance the efficiency of event-driven Monte Carlo simulations, originally introduced by Gillespie and widely regarded as the gold standard in the field, especially in cases where the presence of events is characterized by different timescales.

Laser pulse induced second- and third-harmonic generation of gold nanorods with real-time time-dependent density functional tight binding (RT-TDDFTB) method

In this study, we investigate second- and third-harmonic generation processes in Au nanorod systems using the real-time time-dependent density functional tight binding method. Our study focuses on the computation of nonlinear signals based on the time dependent dipole response induced by linearly polarized laser pulses interacting with nanoparticles. We systematically explore the influence of various laser parameters, including pump intensity, duration, frequency, and polarization directions, on harmonic generation. We demonstrate all the results using Au nanorod dimer systems arranged in end-to-end configurations, and disrupting the spatial symmetry of regular single nanorod systems is crucial for second-harmonic generation processes. Furthermore, we study the impact of nanorod lengths, which lead to variable plasmon energies, on harmonic generation, and estimates of polarizabilities and hyper-polarizabilities are provided.

Water at the nanoscale: From filling or dewetting hydrophobic pores and carbon nanotubes to "sliding" on graphene

In this work, we study the effect of nanoconfinement on the hydration properties of model hydrophobic pores and carbon nanotubes, determining their wetting propensity and the conditions for geometrically induced dehydration. By employing a recently introduced water structural index, we aim at two main goals: (1) to accurately quantify the local hydrophobicity and predict the drying transitions in such systems, and (2) to provide a molecular rationalization of the wetting process. In this sense, we will further discuss the number and strength of the interactions required by the water molecules to promote wetting. In the case of graphene-like surfaces, an explanation for their unexpectedly significant hydrophilicity will also be provided. On the one hand, the structural index will show that the net attraction to the dense carbon network that a water molecule experiences through several simultaneous weak interactions is sufficient to give rise to hydrophilic behavior. On the other hand, we will show that an additional effect is also at play: the hydrating water molecule is retained on the surface by a smooth exchange of such simultaneous weak interactions, as if "sliding" on graphene.

Harvesting nucleating structures in nanoparticle crystallization: The example of gold, silver, and iron

The thermodynamics and kinetics of nanoparticle crystallization, as opposed to bulk phases, may be influenced by surface and size effects. We investigate the importance of such factors in the crystallization process of gold, silver, and iron nanodroplets using numerical simulations in the form of molecular dynamics combined with path sampling. This modeling strategy is targeted at obtaining representative ensembles of structures located at the transition state of the crystallization process. A structural analysis of the transition state ensembles reveals that both the average size and location of the critical nucleation cluster are influenced by surface and nanoscale size effects. Furthermore, we also show that transition state structures in smaller nanodroplets exhibit a more ordered liquid phase, and differentiating between a well-ordered critical cluster and its surrounding disordered liquid phase becomes less evident. All in all, these findings demonstrate that crystallization mechanisms in nanoparticles go beyond the assumptions of classical nucleation theory.

Twins in rotational spectroscopy: Does a rotational spectrum uniquely identify a molecule?

Rotational spectroscopy is the most accurate method for determining structures of molecules in the gas phase. It is often assumed that a rotational spectrum is a unique "fingerprint" of a molecule. The availability of large molecular databases and the development of artificial intelligence methods for spectroscopy make the testing of this assumption timely. In this paper, we pose the determination of molecular structures from rotational spectra as an inverse problem. Within this framework, we adopt a funnel-based approach to search for molecular twins, which are two or more molecules, which have similar rotational spectra but distinctly different molecular structures. We demonstrate that there are twins within standard levels of computational accuracy by generating rotational constants for many molecules from several large molecular databases, indicating that the inverse problem is ill-posed. However, some twins can be distinguished by increasing the accuracy of the theoretical methods or by performing additional experiments.

Oscillating direct electric current formed by a resonant tunneling diode inside a cavity with periodically oscillating mirrors

A novel phenomenon is described that enables the control of the flux of free electrons through a resonance tunneling diode (RTD) via coupling the RTD to a quantized electromagnetic mode in a dark cavity. As the control parameter, one uses here the distance between the two cavity mirrors (which are set to oscillate in time). The effect is illustrated by carrying out standard scattering calculations of the electron flux. However, the only efficient way to rationalize the phenomenon and to be able to select the proper distance between the two cavity mirrors is to employ non-Hermitian quantum mechanics and the language of discrete resonance poles of the scattering matrix. The demonstrated ability to control the flux of free electrons by using a dark cavity might open a new field of research and development of controllable RTD devices.

Wide-Dynamic-Range Control of Quantum-Electrodynamic Electron Transfer Reactions in the Weak Coupling Regime

Catalyzing reactions effectively by vacuum fluctuations of electromagnetic fields is a significant challenge within the realm of chemistry. As opposed to most studies based on vibrational strong coupling, we introduce an innovative catalytic mechanism driven by weakly coupled polaritonic fields. Through the amalgamation of macroscopic quantum electrodynamics (QED) principles with Marcus electron transfer (ET) theory, we predict that ET reaction rates can be precisely modulated across a wide dynamic range by controlling the size and structure of nanocavities. Compared to QED-driven radiative ET rates in free space, plasmonic cavities induce substantial rate enhancements spanning the range from 103- to 10-fold. By contrast, Fabry-Perot cavities engender rate suppression spanning the range from 10-2- to 10-1-fold. This work overcomes the necessity of using strong light-matter interactions in QED chemistry, opening up a new era of manipulating QED-based chemical reactions in a wide dynamic range.

Exploring the Properties of Curved Lipid Membranes: Comparative Analysis of Atomistic and Coarse-Grained Force Fields

Curvature emerges as a fundamental membrane characteristic crucial for diverse biological processes, including vesicle formation, cell signaling, and membrane trafficking. Increasingly valuable insights into atomistic details governing curvature-dependent membrane properties are provided by computer simulations. Nevertheless, the underlying force field models are conventionally calibrated and tested in relation to experimentally derived parameters of planar bilayers, thereby leaving uncertainties concerning their consistency in reproducing curved lipid systems. In this study we compare the depiction of buckled phosphatidylcholine (POPC) and POPC-cholesterol membranes by four popular force field models. Aside from agreement with respect to general trends in curvature dependence of a number of parameters, we observe a few qualitative differences. Among the most prominent ones is the difference between atomistic and coarse grained force fields in their representation of relative compressibility of the polar headgroup region and hydrophobic lipid core. Through a number of downstream effects, this discrepancy can influence the way in which curvature modulates the behavior of membrane bound proteins depending on the adopted simulation model.

Nonadiabatic Exciton Dynamics and Energy Gradients in the Framework of FMO-LC-TDDFTB

We introduce a novel methodology for simulating the excited-state dynamics of extensive molecular aggregates in the framework of the long-range corrected time-dependent density-functional tight-binding fragment molecular orbital method (FMO-LC-TDDFTB) combined with the mean-field Ehrenfest method. The electronic structure of the system is described in a quasi-diabatic basis composed of locally excited and charge-transfer states of all fragments. In order to carry out nonadiabatic molecular dynamics simulations, we derive and implement the excited-state gradients of the locally excited and charge-transfer states. Subsequently, the accuracy of the analytical excited-state gradients is evaluated. The applicability to the simulation of exciton transport in organic semiconductors is illustrated on a large cluster of anthracene molecules. Additionally, nonadiabatic molecular dynamics simulations of a model system of benzothieno-benzothiophene molecules highlight the method's utility in studying charge-transfer dynamics in organic materials. Our new methodology will facilitate the investigation of excitonic transfer in extensive biological systems, nanomaterials, and other complex molecular systems consisting of thousands of atoms.

The Role of Double Excitations in Exciton Dynamics of Multiazobenzenes: Trisazobenzenophane as a Test Case

Molecular exciton dynamics underlie energy and charge transfer processes in organic multichromophoric systems. A particularly interesting class of the latter is multiphotochromic systems made of molecules capable of photochemical transformations. Exciton dynamics in assemblies of photoswitches have been recently investigated using either the molecular exciton model or supermolecular configuration interaction (CI) singles, both approaches being based on a semiempirical Hamiltonian and combined with surface hopping molecular dynamics. Here, we study how inclusion of double excitations in nonadiabatic dynamics simulations affects exciton dynamics of multiazobenzenes, using trisazobenzenophane as an example. We find that both CI singles and CI singles and doubles yield virtually the same time scale of dynamical exciton localization, ∼50 fs for the studied multiazobenzene. However, inclusion of double excitations considerably affects the excited state lifetimes and isomerization quantum yields.

The BioRECIPE Knowledge Representation Format

The BioRECIPE (Biological system Representation for Evaluation, Curation, Interoperability, Preserving, and Execution) knowledge representation format was introduced to standardize and facilitate human-machine interaction while creating, verifying, evaluating, curating, and expanding executable models of intra- and intercellular signaling. This format allows a human user to easily preview and modify any model component, while it is at the same time readable by machines and can be processed by a suite of model development and analysis tools. The BioRECIPE format is compatible with multiple representation formats, natural language processing tools, modeling tools, and databases that are used by the systems and synthetic biology communities.

Efficient determination of Born-effective charges, LO-TO splitting, and Raman tensors of solids with a real-space atom-centered deep learning approach

We introduce a deep neural network (DNN) framework called theReal-spaceAtomicDecompositionNETwork (radnet), which is capable of making accurate predictions of polarization and of electronic dielectric permittivity tensors in solids and aims to address limitations of previously available machine learning models for Raman predictions in periodic systems. This framework builds on previous, atom-centered approaches while utilizing deep convolutional neural networks. We report excellent accuracies on direct predictions for two prototypical examples: GaAs and BN. We then use automatic differentiation to efficiently calculate the Born-effective charges, longitudinal optical-transverse optical (LO-TO) splitting frequencies, and Raman tensors of these materials. We compute the Raman spectra, and find agreement withab initioresults. Lastly, we explore ways to generalize the predictions of polarization while taking into account periodic boundary conditions and symmetries.

Time-Dependent Multireference Coupled-Cluster Method (TDMRCCM) for the Bath-Dynamics in System-Bath Approach to Nonadiabatic Dynamics

The time-dependent multireference coupled-cluster method (TDMRCCM) fits well in the scheme of the system-bath separation used to study the nonadiabatic dynamics. In TDMRCCM, a projection operator is defined as one that projects the full Hilbert space onto the space spanned by the collection of system degrees of freedom, called the model space. The inverse of this projection operator is a wave operator that acts on the model space and takes its projection back to the full wave function. This wave operator is defined as an exponential of the excitation terms and, hence, can be expanded into a Taylor series, which we have truncated in this work at the second-order of excitations. The attraction of using TDMRCCM for describing the bath dynamics is due to the exponential nature of the ansatz used in the method, which makes it possible for the higher-order excitations to be absorbed by the lower-order terms, even upon truncating the series. This improves the accuracy of the numerical calculations using TDMRCCM as an approximation for the bath-mode dynamics in the system-bath framework for nonadiabatic dynamics. We present the theoretical details of TDMRCCM and the numerical results for implementing this method to study the dynamics in the butatriene cation.

Observation of the Infrared-Induced Structural Change in the Microscopic Hydrogen Bond Network of Phenol-Methanol Cluster Cations in a Cold-Ion Trap

To gain insight into microscopic hydrogen bond networks, we measured ultraviolet photodissociation (UVPD) spectra of the phenol-methanol 1:3 cluster cation, [PhOH(MeOH)3]+ trapped in a variable temperature ion trap. At low temperatures, an isomer with a ring-type hydrogen bond structure dominates, whereas at higher temperatures the chain-type isomers become dominant due to the flexibility of their hydrogen bond structures. We also found a clear temperature dependence of the spectral features, such as band position and width. In addition to the above measurement, we observed the infrared (IR) induced isomerization of [PhOH(MeOH)3]+ to study the dynamical aspects of hydrogen bond networks. We succeeded in observing IR-induced isomerization from the ring to chain forms of [PhOH(MeOH)3]+ at low temperature. The isomerization was clearly identified as a change in the UVPD spectra. The time evolution of the UVPD spectra after IR excitation indicated that the IR-induced isomerization occurs within a nanosecond. The chain-type isomers produced by the IR-induced isomerization are then converted back to the ring-type form by collisions with cold He buffer gas in the trap. This backward isomerization proceeds with a time constant of 100 μs under our experimental conditions. In this study, we evaluated the temperatures of the chain isomers during the backward isomerization on the basis of the spectral features.

Femtosecond Stimulated Raman Spectroscopy of Linear Carotenoids

Femtosecond stimulated Raman spectroscopy (FSRS) and transient absorption data measured in a single experiment are used to determine the vibronic properties of the S1 state of linear carotenoids with different conjugation lengths. The Raman band corresponding to the C═C stretching mode in the S1 state peaks at 1799 cm-1 (neurosporene), 1802 cm-1 (spheroidene), and 1791 cm-1 (lycopene). Contrary to the ground state C═C mode, variation of the C═C stretching mode in the S1 state is small and does not follow a linear dependence on N. The lifetime of the Raman band matches the S1 decays obtained from transient absorption, confirming its S1 state origin. Direct comparison of transient absorption and FSRS signals allowed us to assign Raman signatures of nonrelaxed S1 and S0 states. For lycopene, FSRS data identified a component associated with a downshifted ground state C═C mode, which matches the dynamics of the S* signal observed in transient absorption data.

Novel Inhibitory Site Revealed by Mode of Action on the Metabotropic Glutamate 7 Receptor Venus Flytrap Domain

Metabotropic glutamate (mGlu) receptors play a key role in modulating most synapses in the brain. The mGlu7 receptors inhibit presynaptic neurotransmitter release and offer therapeutic possibilities for post-traumatic stress disorders or epilepsy. Screening campaigns provided mGlu7-specific allosteric modulators as the inhibitor XAP044 (Gee et al. J. Biol. Chem. 2014). In contrast to other mGlu receptor allosteric modulators, XAP044 does not bind in the transmembrane domain but to the extracellular domain of the mGlu7 receptor and not at the orthosteric site. Here, we identified the mode of action of XAP044, combining synthesis of derivatives, modeling and docking experiments, and mutagenesis. We propose a unique mode of action of these inhibitors, preventing the closure of the Venus flytrap agonist binding domain. While acting as a noncompetitive antagonist of L-AP4, XAP044 and derivatives act as apparent competitive antagonists of LSP4-2022. These data revealed more potent XAP044 analogues and new possibilities to target mGluRs.

Active control of plasmon coupling via simple electrochemical surface oxidation/reduction of Au nanoparticle agglomerates

Reversible tuning of plasmon coupling of Au nanoparticle (AuNP) agglomerates containing dimers as the main component was achieved via electrochemical surface oxidation/reduction of the AuNP surface. The system required no reactant except for water and was almost finished within a unit second, which leads to novel active plasmonic devices.

Promotion of Fast and Efficient Singlet Fission Process of PDI Dimers by Selenium Substitution

Singlet fission (SF) is a triplet generation mechanism capable of turning a singlet exciton into two triplet excitons. It has the potential to enhance the power conversion efficiency of single-junction solar cells. Perylene diimides (PDIs) are a class of dye molecules with photovoltaic properties and are beginning to receive more and more attention due to their potential for SF. Here, we report a selenium-substituted PDI dimer, Se-PDI-II, and we studied its SF mechanism by using steady-state, transient absorption, and time-resolved photoluminescence spectroscopy. Compared with the unsubstituted dimer PDI-II, we found that the introduction of selenium atoms can suppress excimer emission during the SF process, showing much higher SF efficiency and triplet yield.

Precision Measurement of the Electron Affinity of Chlorine via High-Resolution Photoelectron Spectroscopy

Chlorine (Cl2) is a diatomic molecule used as an important industrial gas. However, the electron affinity (EA) of Cl2, a fundamental parameter for understanding chemical reactions, has no accurate experimental result available. The latest result of the EA value of Cl2 is 2.50(20) eV reported in 1983. In the present work, we report the precision measurement of the EA of Cl2 with the successive difference method via the high-resolution photoelectron spectroscopy of cryogenically cold chlorine anions Cl2-. The EA of Cl2 is determined to be 19432(9) cm-1 or 2.4093(11) eV.

2D capsid formation within an oscillatory energy landscape: orderly self-assembly depends on the interplay between a dynamic potential and intrinsic relaxation times

Multiple dissipative self-assembly protocols designed to create novel structures or to reduce kinetic traps have recently emerged. Specifically, temporal oscillations of particle interactions have been shown effective at both aims, but investigations thus far have focused on systems of simple colloids or their binary mixtures. In this work, we expand our understanding of the effect of temporally oscillating interactions to a two-dimensional coarse-grained viral capsid-like model that undergoes a self-limited assembly. This model includes multiple intrinsic relaxation times due to the internal structure of the capsid subunits and, under certain interaction regimes, proceeds via a two-step nucleation mechanism. We find that oscillations much faster than the local intrinsic relaxation times can be described via a time averaged inter-particle potential across a wide range of interaction strengths, while oscillations much slower than these relaxation times result in structures that adapt to the attraction strength of the current half-cycle. Interestingly, oscillation periods similar to these relaxation times shift the interaction window over which orderly assembly occurs by enabling error correction during the half-cycles with weaker attractions. Our results provide fundamental insights to non-equilibrium self-assembly on temporally variant energy landscapes.