Probing the Interaction between Individual Metal Nanocrystals and Two-Dimensional Metal Oxides via Electron Energy Loss Spectroscopy.

Metal nanoparticles can photosensitize two-dimensional metal oxides, facilitating their electrical connection to devices and enhancing their abilities in catalysis and sensing. In this study, we investigated how individual silver nanoparticles interact with two-dimensional tin oxide and antimony-doped indium oxide using electron energy loss spectroscopy (EELS). The measurement of the spectral line width of the longitudinal plasmon resonance of the nanoparticles in absence and presence of 2D materials allowed us to quantify the contribution of chemical interface damping to the line width. Our analysis reveals that a stronger interaction (damping) occurs with 2D antimony-doped indium oxide due to its highly homogeneous surface. The results of this study offer new insight into the interaction between metal nanoparticles and 2D materials.

The temporal specificity of BOLD fMRI is systematically related to anatomical and vascular features of the human brain.

The ability to detect fast responses with functional MRI depends on the speed of hemodynamic responses to neural activity, because hemodynamic responses act as a temporal low-pass filter smoothing out rapid changes. However, hemodynamic responses (their shape and timing) are highly variable across the brain and across stimuli. This heterogeneity of responses implies that the temporal specificity of fMRI signals, or the ability of fMRI to preserve fast information, should also vary substantially across the cortex. In this work we investigated how local differences in hemodynamic response timing impact the temporal specificity of fMRI. We conducted our research using ultra-high field (7T) fMRI at high spatiotemporal resolution, using the primary visual cortex (V1) as a model area for investigation. We used visual stimuli oscillating at slow and fast frequencies to probe the temporal specificity of individual voxels. As expected, we identified substantial variability in temporal specificity, with some voxels preserving their responses to fast neural activity more effectively than others. We investigated which voxels had the highest temporal specificity and related those to anatomical and vascular features of V1. We found that low temporal specificity is only weakly explained by the presence of large veins or cerebral cortical depth. Notably, however, temporal specificity depended strongly on a voxel's position along the anterior-posterior anatomical axis of V1, with voxels within the calcarine sulcus being capable of preserving close to 25% of their amplitude as the frequency of stimulation increased from 0.05-Hz to 0.20-Hz, and voxels nearest to the occipital pole preserving less than 18%. These results indicate that detection biases in high-resolution fMRI will depend on the anatomical and vascular features of the area being imaged, and that these biases will differ depending on the timing of the underlying neuronal activity. Importantly, this spatial heterogeneity of temporal specificity suggests that it could be exploited to achieve higher specificity in some locations, and that tailored data analysis strategies may help improve the detection and interpretation of fast fMRI responses.

Resting-state fMRI signals contain spectral signatures of local hemodynamic response timing.

Functional magnetic resonance imaging (fMRI) has proven to be a powerful tool for noninvasively measuring human brain activity; yet, thus far, fMRI has been relatively limited in its temporal resolution. A key challenge is understanding the relationship between neural activity and the blood-oxygenation-level-dependent (BOLD) signal obtained from fMRI, generally modeled by the hemodynamic response function (HRF). The timing of the HRF varies across the brain and individuals, confounding our ability to make inferences about the timing of the underlying neural processes. Here, we show that resting-state fMRI signals contain information about HRF temporal dynamics that can be leveraged to understand and characterize variations in HRF timing across both cortical and subcortical regions. We found that the frequency spectrum of resting-state fMRI signals significantly differs between voxels with fast versus slow HRFs in human visual cortex. These spectral differences extended to subcortex as well, revealing significantly faster hemodynamic timing in the lateral geniculate nucleus of the thalamus. Ultimately, our results demonstrate that the temporal properties of the HRF impact the spectral content of resting-state fMRI signals and enable voxel-wise characterization of relative hemodynamic response timing. Furthermore, our results show that caution should be used in studies of resting-state fMRI spectral properties, because differences in fMRI frequency content can arise from purely vascular origins. This finding provides new insight into the temporal properties of fMRI signals across voxels, which is crucial for accurate fMRI analyses, and enhances the ability of fast fMRI to identify and track fast neural dynamics.

Functional magnetic resonance imaging (fMRI) is a tool that can be used to non-invasively measure the activity of the human brain. Active parts of the brain require more oxygen, which increases blood flow to these areas. fMRI can detect these changes, and its signal reflects the coupling between brain activity and changes in blood flow. The mechanism that couples brain activity to blood flow is known as the 'hemodynamic response', and its timing varies across the brain. Therefore, to interpret fMRI signals correctly and use them to measure underlying brain activity, it is necessary to understand how the response changes across the brain. Current methods for probing hemodynamic response variation are either limited to specific brain regions or require patients to hold their breath ­ something not all groups of patients can do. To solve this problem, Bailes et al. investigated whether resting-state fMRI signals contain information about how the hemodynamic response changes across the brain. This information could then be used to better infer brain activity from fMRI measurements. The experiments showed that resting-state fMRI signals can be used to characterize and predict the timing of the hemodynamic response. Specifically, the frequencies in resting-state fMRI signals are impacted by changes in the hemodynamic response and can therefore be used to predict hemodynamic timing. Additionally, Bailes et al. showed that these predictions are better than those obtained in experiments requiring patients to hold their breath, which is the current gold standard. The findings also demonstrate that the information from the frequencies of resting-state fMRI signals should be interpreted carefully, as differences in these frequencies can have a non-neural origin. Bailes et al. propose a highly generalizable approach for mapping and predicting variations of the hemodynamic response across the whole brain. These findings provide insights into the time-related properties of fMRI signals that are crucial for accurate analyses. This will be of particular importance as the field moves towards fMRI studies focused on rapid neural dynamics and higher-level cognition.

Solution processed bismuth oxyiodide (BiOI) thin films and solar cells.

Post transition metal chalcohalides are an emerging class of semiconductor materials for optoelectronic applications. Within this class, bismuth oxyiodide (BiOI) is of particular interest due to its high environmental stability, low toxicity, and defect tolerance considered typical of 'ns2' materials. Here we fabricate BiOI thin films using a solution-processed method that affords pin-hole free highly pure films without any residual carbon or other contaminant species. Based on these films, solution processed all-inorganic solar cells with an architecture ITO/NiOx/BiOI/ZnO/Al are fabricated for the first time. Additional device improvements are realised by templating BiOI thin film growth to attain efficiencies that rival some of the best vacuum deposited devices. The BiOI thin films and devices outlined here are an excellent platform for the further development of solution processed bismuth chalcohalide optoelectronic devices.

Photoinitiated Energy Transfer in Porous-Cage-Stabilised Silver Nanoparticles.

We report a new composite material consisting of silver nanoparticles decorated with three-dimensional molecular organic cages based on light-absorbing porphyrins. The porphyrin cages serve to both stabilize the particles and allow diffusion and trapping of small molecules close to the metallic surface. Combining these two photoactive components results in a Fano-resonant interaction between the porphyrin Soret band and the nanoparticle-localised surface-plasmon resonance. Time-resolved spectroscopy revealed the silver nanoparticles transfer up to 37 % of their excited-state energy to the stabilising layer of porphyrin cages. These unusual photophysics cause a 2-fold current increase in photoelectrochemical water-splitting measurements. The composite structure provides a compelling proof of concept for advanced photosensitiser systems with intrinsic porosity for photocatalytic and sensing applications.

Molecular Energy Transfer under the Strong Light-Matter Interaction Regime.

Research into strong light-matter interactions continues to fascinate, being spurred on by unforeseen and often spectacular experimental observations. Properties that were considered to depend exclusively on material composition have been found to be drastically altered when a material is placed inside a resonant optical cavity. This is nowhere more the case than in the field of intermolecular energy transfer, where polaritonic states formed as a result of strong light-matter interactions have been shown to promote energy transfer over distances vastly exceeding conventional limits. In this review, we provide the reader with a succinct account of the fundamental concepts of intermolecular energy transfer, and how they are modified by strong light-matter interactions. We also summarize recent experimental advances in the area, including in optoelectronic device contexts, and highlight both the potential and challenges that remain in this exciting field of research going forward.

Key role of PIN1 in telomere maintenance and oncogenic behavior in a human glioblastoma model.

PIN1 is the only known enzyme capable of recognizing and isomerizing the phosphorylated Serine/Threonine­Proline motif. Through this mechanism, PIN1 controls diverse cellular functions, including telomere maintenance. Both PIN1 overexpression and its involvement in oncogenic pathways are involved in several cancer types, including glioblastoma (GBM), a lethal disease with poor therapeutic resources. However, knowledge of the role of PIN1 in GBM is limited. Thus, the present work aimed to study the role of PIN1 as a telomere/telomerase regulator and its contribution to tumor biology. PIN1 knockout (KO) LN­229 cell variant using CRISPR/Cas9 was developed and compared with PIN1 LN­229 expressing cells. To study the effect of PIN1 absence, status of NF­κB pathway was evaluated by luciferase reporter gene assay and quantitative PCR. Results revealed that PIN1 deletion in GBM cells diminished the active levels of NF­κB and decrease the transcription of il­8 and htert genes. Then, telomere/telomerase related processes were studied by RQ­TRAP assay and telomere length determination by qPCR, obtaining a reduction both in telomerase activity as in telomere length in PIN1 KO cells. In addition, measurement of SA ß­galactosidase and caspase­3 activities revealed that loss of PIN1 triggers senescence and apoptosis. Finally, migration, cell cycle progression and tumorigenicity were studied by flow cytometry/western blot, Transwell assay and in vivo experiments, respectively. PIN1 deletion decreased migration as well as cell cycle progression by increasing doubling time and also resulted in the loss of LN­229 cell ability to form tumors in mice. These results highlight the role of PIN1 in telomere homeostasis and GBM progression, which supports PIN1 as a potential molecular target for the development of novel therapeutic agents for GBM treatment.

Photoactive p-Type Spinel CuGa2O4 Nanocrystals.

Herein we report the synthesis and characterization of spinel copper gallate (CuGa2O4) nanocrystals (NCs) with an average size of 3.7 nm via a heat-up colloidal reaction. CuGa2O4 NCs have a band gap of ∼2.5 eV and marked p-type character, in agreement with ab initio simulations. These novel NCs are demonstrated to be photoactive, generating a clear and reproducible photocurrent under blue light irradiation when deposited as thin films. Crucially, the ability to adjust the Cu/Ga ratio within the NCs, and the effect of this on the optical and electronic properties of the NCs, was also demonstrated. These results position CuGa2O4 NCs as a novel material for optoelectronic applications, including hole transport and light harvesting.

Optimal Geometry for Plasmonic Hot-Carrier Extraction in Metal-Semiconductor Nanocrystals.

Plasmon-induced energy and charge transfer from metal nanostructures hold great potential for harvesting solar energy. Presently, the efficiencies of charge-carrier extraction are still low due to the competitive ultrafast mechanisms of plasmon relaxation. Using single-particle electron energy loss spectroscopy, we correlate the geometrical and compositional details of individual nanostructures to their carrier extraction efficiencies. By removing ensemble effects, we are able to show a direct structure-function relationship that permits the rational design of the most efficient metal-semiconductor nanostructures for energy harvesting applications. In particular, by developing a hybrid system comprising Au nanorods with epitaxially grown CdSe tips, we are able to control and enhance charge extraction. We show that optimal structures can have efficiencies as high as 45%. The quality of the Au-CdSe interface and the dimensions of the Au rod and CdSe tip are shown to be critical for achieving these high efficiencies of chemical interface damping.

Resting-state fMRI signals contain spectral signatures of local hemodynamic response timing.

Functional magnetic resonance imaging (fMRI) has proven to be a powerful tool for noninvasively measuring human brain activity; yet, thus far, fMRI has been relatively limited in its temporal resolution. A key challenge is understanding the relationship between neural activity and the blood-oxygenation-level-dependent (BOLD) signal obtained from fMRI, generally modeled by the hemodynamic response function (HRF). The timing of the HRF varies across the brain and individuals, confounding our ability to make inferences about the timing of the underlying neural processes. Here we show that resting-state fMRI signals contain information about HRF temporal dynamics that can be leveraged to understand and characterize variations in HRF timing across both cortical and subcortical regions. We found that the frequency spectrum of resting-state fMRI signals significantly differs between voxels with fast versus slow HRFs in human visual cortex. These spectral differences extended to subcortex as well, revealing significantly faster hemodynamic timing in the lateral geniculate nucleus of the thalamus. Ultimately, our results demonstrate that the temporal properties of the HRF impact the spectral content of resting-state fMRI signals and enable voxel-wise characterization of relative hemodynamic response timing. Furthermore, our results show that caution should be used in studies of resting-state fMRI spectral properties, as differences can arise from purely vascular origins. This finding provides new insight into the temporal properties of fMRI signals across voxels, which is crucial for accurate fMRI analyses, and enhances the ability of fast fMRI to identify and track fast neural dynamics.

A comparison of multiband and multiband multiecho gradient-echo EPI for task fMRI at 3 T.

A multiband (MB) echo-planar imaging (EPI) sequence is compared to a multiband multiecho (MBME) EPI protocol to investigate differences in sensitivity for task functional magnetic resonance imaging (fMRI) at 3 T. Multiecho sampling improves sensitivity in areas where single-echo-EPI suffers from dropouts. However, It requires in-plane acceleration to reduce the echo train length, limiting the slice acceleration factor and the temporal and spatial resolution Data were acquired for both protocols in two sessions 24 h apart using an adapted color-word interference Stroop task. Besides protocol comparison statistically, we performed test-retest reliability across sessions for different protocols and denoising methods. We evaluated the sensitivity of two different echo-combination strategies for MBME-EPI. We examined the performance of three different data denoising approaches: "Standard," "AROMA," and "FIX" for MB and MBME, and assessed whether a specific method is preferable. We consider using an appropriate autoregressive model order within the general linear model framework to correct TR differences between the protocols. The comparison between protocols and denoising methods showed at group level significantly higher mean z-scores and the number of active voxels for MBME in the motor, subcortical and medial frontal cortices. When comparing different echo combinations, our results suggest that a contrast-to-noise ratio weighted echo combination improves sensitivity in MBME compared to simple echo-summation. This study indicates that MBME can be a preferred protocol in task fMRI at spatial resolution (≥2 mm), primarily in medial prefrontal and subcortical areas.

Preclinical Efficacy and Toxicology Evaluation of RAC1 Inhibitor 1A-116 in Human Glioblastoma Models.

Malignant gliomas are the most common primary central nervous system tumor in adults. Despite current therapeutics, these tumors are associated with poor prognosis and a median survival of 16 to 19 months. This highlights the need for innovative treatments for this incurable disease. Rac1 has long been associated with tumor progression and plays a key role in glioma's infiltrative and invasive nature. The aim of this study is to evaluate the 1A-116 molecule, a Rac1 inhibitor, as targeted therapy for this aggressive disease. We found that targeting Rac1 inhibits cell proliferation and cell cycle progression using different in vitro human glioblastoma models. Additionally, we evaluated 1A-116 in vivo, showing a favorable toxicological profile. Using in silico tools, 1A-116 is also predicted to penetrate the blood-brain barrier and present a favorable metabolic fate. In line with these results, 1A-116 i.p daily treatment resulted in a dose-dependent antitumor effect in an orthotopic IDH-wt glioma model. Altogether, our study provides a strong potential for clinical translation of 1A-116 as a signal transduction-based precision therapy for glioma and also increases the evidence of Rac1 as a key molecular target.

A temporal sequence of thalamic activity unfolds at transitions in behavioral arousal state.

Awakening from sleep reflects a profound transformation in neural activity and behavior. The thalamus is a key controller of arousal state, but whether its diverse nuclei exhibit coordinated or distinct activity at transitions in behavioral arousal state is unknown. Using fast fMRI at ultra-high field (7 Tesla), we measured sub-second activity across thalamocortical networks and within nine thalamic nuclei to delineate these dynamics during spontaneous transitions in behavioral arousal state. We discovered a stereotyped sequence of activity across thalamic nuclei and cingulate cortex that preceded behavioral arousal after a period of inactivity, followed by widespread deactivation. These thalamic dynamics were linked to whether participants subsequently fell back into unresponsiveness, with unified thalamic activation reflecting maintenance of behavior. These results provide an outline of the complex interactions across thalamocortical circuits that orchestrate behavioral arousal state transitions, and additionally, demonstrate that fast fMRI can resolve sub-second subcortical dynamics in the human brain.

Reinterpreting the Fate of Iridium(III) Photocatalysts─Screening a Combinatorial Library to Explore Light-Driven Side-Reactions.

Photoredox catalysts are primarily selected based on ground and excited state properties, but their activity is also intrinsically tied to the nature of their reduced (or oxidized) intermediates. Catalyst reactivity often necessitates an inherent instability, thus these intermediates represent a mechanistic turning point that affords either product formation or side-reactions. In this work, we explore the scope of a previously demonstrated side-reaction that partially saturates one pyridine ring of the ancillary ligand in heteroleptic iridium(III) complexes. Using high-throughput synthesis and screening under photochemical conditions, we identified different chemical pathways, ultimately governed by ligand composition. The ancillary ligand was the key factor that determined photochemical stability. Following photoinitiated electron transfer from a sacrificial tertiary amine, the reduced intermediate of complexes containing 1,10-phenanthroline derivatives exhibited long-term stability. In contrast, complexes containing 2,2'-bipyridines were highly susceptible to hydrogen atom transfer and ancillary ligand modification. Detailed characterization of selected complexes before and after transformation showed differing effects on the ground and excited state reduction potentials dependent on the nature of the cyclometalating ligands and excited states. The implications of catalyst stability and reactivity in chemical synthesis was demonstrated in a model photoredox reaction.

Rational design of PIN1 inhibitors for cancer treatment based on conformational diversity analysis and docking based virtual screening.

The parvulin PIN1 (peptidyl-prolyl cis-trans isomerase NIMA-interacting 1), is the only enzyme capable of isomerizing prolines of phospho-Serine/Threonine-Proline motifs. PIN1 binds to a subset of proteins and plays an essential role in regulating protein function post-phosphorylation control. Furthermore, the activity of PIN1 regulates the outcome of the signalling of proline-directed kinases (e.g. MAPK, CDK, or GSK3) and thus regulates cell proliferation and cell survival. For these reasons, PIN1 inhibitors are interesting since they may have therapeutic implications for cancer. Several authors have already reported that the non-structural point mutation Trp34Ala prevents PIN1 from interacting with its downstream effector proteins. In this work, we characterized PIN1 structurally, intending to explore new inhibition targets for the rational design of pharmacological activity compounds. Through a conformational diversity analysis of PIN1, we identified and characterized a highly specific druggable pocket around the residue Trp34. This pocket was used in a high-throughput docking screening of 450,000 drug-like compounds, and the top 10 were selected for re-docking studies on the previously used conformers. Finally, we evaluated the binding of each compound by thermal shift assay and found four molecules with a high affinity for PIN1 and potential inhibitory activity. Through this strategy, we achieved novel drug candidates with the ability to interfere with the phosphorylation-dependent actions of PIN1 and with potential applications in the treatment of cancer.Communicated by Ramaswamy H. Sarma.

Near-Perfect Absorption of Light by Coherent Plasmon-Exciton States.

We experimentally demonstrate and theoretically study the formation of coherent plasmon-exciton states which exhibit absorption of >90% of the incident light (at resonance) and cancellation of absorption. These coherent states result from the interaction between a material supporting an electronic excitation and a plasmonic structure capable of (near) perfect absorption of light. We illustrate the potential implications of these coherent states by measuring the charge separation attainable after photoexcitation. Our study opens the prospect for realizing devices that exploit coherent effects in applications.

New inhibitor targeting Acyl-CoA synthetase 4 reduces breast and prostate tumor growth, therapeutic resistance and steroidogenesis.

Acyl-CoA synthetase 4 (ACSL4) is an isoenzyme of the fatty acid ligase-coenzyme-A family taking part in arachidonic acid metabolism and steroidogenesis. ACSL4 is involved in the development of tumor aggressiveness in breast and prostate tumors through the regulation of various signal transduction pathways. Here, a bioinformatics analysis shows that the ACSL4 gene expression and proteomic signatures obtained using a cell model was also observed in tumor samples from breast and cancer patients. A well-validated ACSL4 inhibitor, however, has not been reported hindering the full exploration of this promising target and its therapeutic application on cancer and steroidogenesis inhibition. In this study, ACSL4 inhibitor PRGL493 was identified using a homology model for ACSL4 and docking based virtual screening. PRGL493 was then chemically characterized through nuclear magnetic resonance and mass spectroscopy. The inhibitory activity was demonstrated through the inhibition of arachidonic acid transformation into arachidonoyl-CoA using the recombinant enzyme and cellular models. The compound blocked cell proliferation and tumor growth in both breast and prostate cellular and animal models and sensitized tumor cells to chemotherapeutic and hormonal treatment. Moreover, PGRL493 inhibited de novo steroid synthesis in testis and adrenal cells, in a mouse model and in prostate tumor cells. This work provides proof of concept for the potential application of PGRL493 in clinical practice. Also, these findings may prove key to therapies aiming at the control of tumor growth and drug resistance in tumors which express ACSL4 and depend on steroid synthesis.

Orientation-Dependent Soft Plasmonics of Gold Nanobipyramid Plasmene Nanosheets.

In parallel to the burgeoning field of soft electronics, soft plasmonics focuses on the design and fabrication of plasmonic structures supported on elastomers and to understand how their properties respond to mechanical deformations. Here, we report on a partial ligand-stripping strategy to fabricate elastomer-supported gold nanobipyramid (NBP) plasmene nanosheets. Unlike spherelike building blocks, NBP-building blocks display complex orientation-dependent plasmonic responses to external strains. By collecting polarized plasmonic resonance spectra in conjunction with electrostatic eigenmode modeling, we reveal simultaneous changes in interparticle spacing and spatial orientations of NBP building blocks under mechanical strains. Such changes are directly related to initial NBP packing orders. Further analysis of strain sensitivities for various NBP plasmenes indicated that plasmonic spectra of ∼45° oriented samples are mostly susceptible to strain at acute polarized angles. The results presented may enable novel applications in future soft optoelectronic devices in sensing, encryption, and data storage.

Self-Assembly of Plasmonic Near-Perfect Absorbers of Light: The Effect of Particle Size.

Structures capable of perfect light absorption promise technological advancements in varied applications, including sensing, optoelectronics, and photocatalysis. While it is possible to realize such structures by placing a monolayer of metal nanostructures above a reflecting surface, there remains limited studies on what effect particle size plays on their capacity to absorb light. Here, we fabricate near-perfect absorbers using colloidal Au nanoparticles, via their electrostatic self-assembly on a TiO2 film supported by a gold mirror. This method enables the control of interparticle spacing, thus minimizing reflection to achieve optimal absorption. Slightly altering the nanoparticle size in these structures reveals significant changes in the spectral separation of hybrid optical modes. We rationalize this observation by interpreting data with a coupled-mode theory that provides a thorough basis for creating functional absorbers using complex colloids and outlines the key considerations for achieving a broadened spectral response.

Analysis of task-based functional MRI data preprocessed with fMRIPrep.

Functional magnetic resonance imaging (fMRI) is a standard tool to investigate the neural correlates of cognition. fMRI noninvasively measures brain activity, allowing identification of patterns evoked by tasks performed during scanning. Despite the long history of this technique, the idiosyncrasies of each dataset have led to the use of ad-hoc preprocessing protocols customized for nearly every different study. This approach is time consuming, error prone and unsuitable for combining datasets from many sources. Here we showcase fMRIPrep (http://fmriprep.org), a robust tool to prepare human fMRI data for statistical analysis. This software instrument addresses the reproducibility concerns of the established protocols for fMRI preprocessing. By leveraging the Brain Imaging Data Structure to standardize both the input datasets (MRI data as stored by the scanner) and the outputs (data ready for modeling and analysis), fMRIPrep is capable of preprocessing a diversity of datasets without manual intervention. In support of the growing popularity of fMRIPrep, this protocol describes how to integrate the tool in a task-based fMRI investigation workflow.