Cell-Type-Specific Optical Recording of Membrane Voltage Dynamics in Freely Moving Mice.

Electrophysiological field potential dynamics are of fundamental interest in basic and clinical neuroscience, but how specific cell types shape these dynamics in the live brain is poorly understood. To empower mechanistic studies, we created an optical technique, TEMPO, that records the aggregate trans-membrane voltage dynamics of genetically specified neurons in freely behaving mice. TEMPO has >10-fold greater sensitivity than prior fiber-optic techniques and attains the noise minimum set by quantum mechanical photon shot noise. After validating TEMPO's capacity to track established oscillations in the delta, theta, and gamma frequency bands, we compared the D1- and D2-dopamine-receptor-expressing striatal medium spiny neurons (MSNs), which are interspersed and electrically indistinguishable. Unexpectedly, MSN population dynamics exhibited two distinct coherent states that were commonly indiscernible in electrical recordings and involved synchronized hyperpolarizations across both MSN subtypes. Overall, TEMPO allows the deconstruction of normal and pathologic neurophysiological states into trans-membrane voltage activity patterns of specific cell types.

Identifying properties of pattern completion neurons in a computational model of the visual cortex.

Neural ensembles are found throughout the brain and are believed to underlie diverse cognitive functions including memory and perception. Methods to activate ensembles precisely, reliably, and quickly are needed to further study the ensembles' role in cognitive processes. Previous work has found that ensembles in layer 2/3 of the visual cortex (V1) exhibited pattern completion properties: ensembles containing tens of neurons were activated by stimulation of just two neurons. However, methods that identify pattern completion neurons are underdeveloped. In this study, we optimized the selection of pattern completion neurons in simulated ensembles. We developed a computational model that replicated the connectivity patterns and electrophysiological properties of layer 2/3 of mouse V1. We identified ensembles of excitatory model neurons using K-means clustering. We then stimulated pairs of neurons in identified ensembles while tracking the activity of the entire ensemble. Our analysis of ensemble activity quantified a neuron pair's power to activate an ensemble using a novel metric called pattern completion capability (PCC) based on the mean pre-stimulation voltage across the ensemble. We found that PCC was directly correlated with multiple graph theory parameters, such as degree and closeness centrality. To improve selection of pattern completion neurons in vivo, we computed a novel latency metric that was correlated with PCC and could potentially be estimated from modern physiological recordings. Lastly, we found that stimulation of five neurons could reliably activate ensembles. These findings can help researchers identify pattern completion neurons to stimulate in vivo during behavioral studies to control ensemble activation.

Giant Out-of-Plane Exciton Emission Enhancement in Two-Dimensional Indium Selenide via a Plasmonic Nanocavity.

Out-of-plane (OP) exciton-based emitters in two-dimensional semiconductor materials are attractive candidates for novel photonic applications, such as radially polarized sources, integrated photonic chips, and quantum communications. However, their low quantum efficiency resulting from forbidden transitions limits their practicality. In this work, we achieve a giant enhancement of up to 34000 for OP exciton emission in indium selenide (InSe) via a designed Ag nanocube-over-Au film plasmonic nanocavity. The large photoluminescence enhancement factor (PLEF) is attributed to the induced OP local electric field (Ez) within the nanocavity, which facilitates effective OP exciton-plasmon interaction and subsequent tremendous enhancement. Moreover, the nanoantenna effect resulting from the effective interaction improves the directivity of spontaneous radiation. Our results not only reveal an effective photoluminescence enhancement approach for OP excitons but also present an avenue for designing on-chip photonic devices with an OP dipole orientation.

Void Volume Fraction of Granular Scaffolds.

Void volume fraction (VVF) is a global measurement frequently used to characterize the void space of granular scaffolds, yet there is no gold standard by which to measure VVF in practice. To study the relationship  between VVF and particles of varying size, form, and composition, a library of 3D simulated scaffolds is used. Results reveal that relative to particle count, VVF is a less predictable metric across replicate scaffolds. Simulated scaffolds are used to explores the relationship between microscope magnification and VVF, and recommendations are offered for optimizing the accuracy of approximating VVF using 2D microscope images. Lastly, VVF of hydrogel granular scaffolds is measured while varying four input parameters: image quality, magnification, analysis software, and intensity threshold. Results show that VVF is highly sensitive to these parameters. Overall, random packing produces variation in VVF among granular scaffolds comprising the same particle populations. Furthermore, while VVF is used to compare the porosity of granular materials within a study, VVF is a less reliable metric across studies that use different input parameters. VVF, a global measurement, cannot describe the dimensions of porosity within granular scaffolds, and the work supports the notion that more descriptors are necessary to sufficiently characterize void space.

Ultrafast Internal Exciton Dissociation through Edge States in MoS2 Nanosheets with Diffusion Blocking.

Edge states of two-dimensional transition-metal dichalcogenides (TMDCs) are crucial to quantum circuits and optoelectronics. However, their dynamics are pivotal but remain unclear due to the edge states being obscured by their bulk counterparts. Herein, we study the state-resolved transient absorption spectra of ball-milling-produced MoS2 nanosheets with 10 nm lateral size with highly exposed free edges. Electron energy loss spectroscopy and first-principles calculations confirm that the edge states are located in the range from 1.23 to 1.78 eV. Upon above bandgap excitations, excitons populate and diffuse toward the boundary, where the potential gradient blocks excitons and the edge states are formed through interband transitions within 400 fs. With below bandgap excitations, edge states are slowed down to 1.1 ps due to the weakened valence orbital coupling. These results shed light on the fundamental exciton dissociation processes on the boundary of functionalized TMDCs, enabling the ground work for applications in optoelectronics and light-harvesting.

Engineering rhodopsins' activation spectra using a FRET-based approach.

In the past decade, optogenetics has become a nearly ubiquitous tool in neuroscience because it enables researchers to manipulate neural activity with high temporal resolution and genetic specificity. Rational engineering of optogenetic tools has produced channelrhodopsins with a wide range of kinetics and photocurrent magnitude. Genome mining for previously unidentified species of rhodopsin has uncovered optogenetic tools with diverse spectral sensitivities. However, rational engineering of a rhodopsin has thus far been unable to re-engineer spectral sensitivity while preserving full photocurrent. Here, we developed and characterized ChroME-mTFP, a rhodopsin-fluorescent protein fusion that drives photocurrent through Förster resonance energy transfer (FRET). This FRET-opsin mechanism artificially broadened the activation spectrum of the blue-green-light-activated rhodopsin ChroME by approximately 50 nm, driving higher photocurrent at blue-shifted excitation wavelengths without sacrificing kinetics. The excitation spectra's increase at short wavelengths enabled us to optogenetically excite neurons at lower excitation powers with shorter wavelengths of light. Increasing this rhodopsin's sensitivity to shorter, bluer wavelengths pushes it toward dual-channel, crosstalk-free optogenetic stimulation and imaging with green-light-activated sensors. However, this iteration of FRET-opsin suffers from some imaging-light-induced photocurrent crosstalk from green or yellow light due to maintained, low-efficiency excitation at longer wavelengths.

A kinetic-optimized CoChR variant with enhanced high-frequency spiking fidelity.

Channelrhodopsins are a promising toolset for noninvasive optical manipulation of genetically identifiable neuron populations. Existing channelrhodopsins have generally suffered from a trade-off between two desired properties: fast channel kinetics and large photocurrent. Such a trade-off hinders spatiotemporally precise optogenetic activation during both one-photon and two-photon photostimulation. Furthermore, the simultaneous use of spectrally separated genetically encoded indicators and channelrhodopsins has generally suffered from non-negligible crosstalk in photocurrent or fluorescence. These limitations have hindered crosstalk-free dual-channel experiments needed to establish relationships between multiple neural populations. Recent large-scale transcriptome sequencing revealed one potent optogenetic actuator, the channelrhodopsin from species Chloromonas oogama (CoChR), which possessed high cyan light-driven photocurrent but slow channel kinetics. We rationally designed and engineered a kinetic-optimized CoChR variant that was faster than native CoChR while maintaining large photocurrent amplitude. When expressed in cultured hippocampal pyramidal neurons, our CoChR variant improved high-frequency spiking fidelity under one-photon illumination. Our CoChR variant's blue-shifted excitation spectrum enabled simultaneous cyan photostimulation and red calcium imaging with negligible photocurrent crosstalk.

Kilohertz two-photon brain imaging in awake mice.

Two-photon microscopy is a mainstay technique for imaging in scattering media and normally provides frame-acquisition rates of ~10-30 Hz. To track high-speed phenomena, we created a two-photon microscope with 400 illumination beams that collectively sample 95,000-211,000 µm2 areas at rates up to 1 kHz. Using this microscope, we visualized microcirculatory flow, fast venous constrictions and neuronal Ca2+ spiking with millisecond-scale timing resolution in the brains of awake mice.

Fast and robust active neuron segmentation in two-photon calcium imaging using spatiotemporal deep learning.

Calcium imaging records large-scale neuronal activity with cellular resolution in vivo. Automated, fast, and reliable active neuron segmentation is a critical step in the analysis workflow of utilizing neuronal signals in real-time behavioral studies for discovery of neuronal coding properties. Here, to exploit the full spatiotemporal information in two-photon calcium imaging movies, we propose a 3D convolutional neural network to identify and segment active neurons. By utilizing a variety of two-photon microscopy datasets, we show that our method outperforms state-of-the-art techniques and is on a par with manual segmentation. Furthermore, we demonstrate that the network trained on data recorded at a specific cortical layer can be used to accurately segment active neurons from another layer with different neuron density. Finally, our work documents significant tabulation flaws in one of the most cited and active online scientific challenges in neuron segmentation. As our computationally fast method is an invaluable tool for a large spectrum of real-time optogenetic experiments, we have made our open-source software and carefully annotated dataset freely available online.

Photon-recycling effect in perovskites for photovoltaic applications: a Monte Carlo study.

Photon recycling has been shown to play an important role in the optoelectronic properties and device performance of perovskite solar cells recently. However, there lacks an analytical method to accurately predict the dynamics of charge carriers and photons and the device performance with photon recycling due to the complexity of multiple electron-photon conversion processes involved in photon recycling. We propose a model based on the Monte Carlo simulation method that combines charge carrier diffusion and photon radiation transport to analyze the effects of photon recycling on electron-photon dynamics and device performance of perovskite solar cells. We show that the carrier lifetime can be significantly boosted by photon recycling in the radiative limit, which yields a 37 meV increase in the open-circuit voltage for a 500 nm thick perovskite solar cell. Our results provide insights for the working mechanisms of perovskite solar cells, and the new model can be further applied to other types of solar cells with photon recycling.

Improving FRET dynamic range with bright green and red fluorescent proteins.

A variety of genetically encoded reporters use changes in fluorescence (or Förster) resonance energy transfer (FRET) to report on biochemical processes in living cells. The standard genetically encoded FRET pair consists of CFPs and YFPs, but many CFP-YFP reporters suffer from low FRET dynamic range, phototoxicity from the CFP excitation light and complex photokinetic events such as reversible photobleaching and photoconversion. We engineered two fluorescent proteins, Clover and mRuby2, which are the brightest green and red fluorescent proteins to date and have the highest Förster radius of any ratiometric FRET pair yet described. Replacement of CFP and YFP with these two proteins in reporters of kinase activity, small GTPase activity and transmembrane voltage significantly improves photostability, FRET dynamic range and emission ratio changes. These improvements enhance detection of transient biochemical events such as neuronal action-potential firing and RhoA activation in growth cones.

A Semi-supervised Pipeline for Accurate Neuron Segmentation with Fewer Ground Truth Labels.

Recent advancements in two-photon calcium imaging have enabled scientists to record the activity of thousands of neurons with cellular resolution. This scope of data collection is crucial to understanding the next generation of neuroscience questions, but analyzing these large recordings requires automated methods for neuron segmentation. Supervised methods for neuron segmentation achieve state of-the-art accuracy and speed but currently require large amounts of manually generated ground truth training labels. We reduced the required number of training labels by designing a semi-supervised pipeline. Our pipeline used neural network ensembling to generate pseudolabels to train a single shallow U-Net. We tested our method on three publicly available datasets and compared our performance to three widely used segmentation methods. Our method outperformed other methods when trained on a small number of ground truth labels and could achieve state-of-the-art accuracy after training on approximately a quarter of the number of ground truth labels as supervised methods. When trained on many ground truth labels, our pipeline attained higher accuracy than that of state-of-the-art methods. Overall, our work will help researchers accurately process large neural recordings while minimizing the time and effort needed to generate manual labels.

An immune biomarker associated with EMT serves as a predictor for prognosis and drug response in bladder cancer.

BACKGROUND: Bladder cancer (BLCA), which develops from the upper endometrial of the bladder, is the sixth most prevalent cancer across the globe. WDHD1 (WD repeat and HMG-box DNA binding protein 1 gene) directly affects signaling, the cell cycle, and the development of the cell skeleton. Uncertainty surrounds WDHD1's function in BLCA immunity and prognosis, though. MATERIALS AND METHODS: Using weighed gene co-expression network analysis (WGCNA), initially, we first identified 32 risk factors in genes with differential expression for this investigation. Then, using a variety of bioinformatic techniques and experimental validation, we examined the connections between WDHD1 and BLCA expression, clinical pathological traits, WDHD1-related proteins, upper-skin-intermediate conversion (EMT), immune cell immersion, convergence factors, immune markers, and drug sensitivity. RESULT: The findings demonstrated that we constructed a 32-gene risk-predicting model where WDHD1 was elevated as a representative gene expression in BLCA and related to a range of clinical traits. Furthermore, high WDHD1 expression was a standalone predictor associated with a worse survival rate. The most commonly recruited cells and their evolutionary patterns were highlighted to better comprehend WDHD1's function in cancer. High WDHD1 expression was associated with many aspects of immunology. Finally, the study found that individuals with high expression of WDHD1 were drug-sensitive to four different broad-spectrum anti-cancer drugs. CONCLUSION: These results describe dynamic changes in the tumor microenvironment in BLCA and provide evidence for the hypothesis that WDHD1 is a novel biomarker of tumor development. WDHD1 may therefore be a useful target for the detection and management of BLCA.

PVALB Was Identified as an Independent Prognostic Factor for HCC Closely Related to Immunity, and Its Absence Accelerates Tumor Progression by Regulating NK Cell Infiltration.

Purpose: Hepatocellular carcinoma is the most common primary liver cancer, with poor prognosis. Complex immune microenvironment of the liver is linked to the development of HCC. PVALB is a calcium-binding protein which has been described as a cancer suppressor gene in thyroid cancer and glioma. Nevertheless, the role of PVALB in HCC is unknown. Materials and Methods: We obtained data from TCGA and GSE54236 datasets. MCP-counter, WGCNA and LASSO model were applied to identify PVALB. With UALCAN, MethSurv, and other websites, we probed the expression, methylation and survival of PVALB. LinkedOmics and GSEA were adopted for functional analysis, while TIMER, TISIDB, Kaplan-Meier plotter, TIDE databases were utilized to evaluate the relevance of PVALB to the tumor immune microenvironment and predict immunotherapy efficacy. TargetScan, DIANA, LncRNASNP2 databases and relevant experiments were employed to construct ceRNA network. Finally, molecular docking and drug sensitivity of PVALB were characterized by GeneMANIA, CTD, and so on. Results: PVALB was recognized as a gene associated with HCC and NK cell. Its expression was down-regulated in HCC tissue, which lead to adverse prognosis. Besides, the hypomethylation of PVALB was related to its reduced expression. Notably, PVALB was tightly linked to immune, and its reduced expression attenuated the anticancer effect of NK cells via the Fas/FasL pathway, leading to a adverse outcome. The lnc-YY1AP1-3/hsa-miR-6735-5p/PVALB axis may regulate the PVALB expression. Finally, we found immunotherapy might be a viable treatment option. Conclusion: In a word, PVALB is a prognostic indicator, whose low expression facilitates HCC progression by impacting NK cell infiltration.

LAMP3 is a potent uterine corpus endometrial carcinoma prognostic biomarker associated with immune behavior.

BACKGROUND: Uterine corpus endometrial carcinoma (UCEC) is one of the most common gynecological malignancies and its incidence and mortality continue apace. Lysosome-associated membrane protein 3 (LAMP3) is the third member of the LAMP family and its overexpression has been described to be involved in the progression of breast, ovarian and cervical cancers, but there has been an absence of research focusing on its role in UCEC. METHODS: WGCNA, TIMER, LinkedOmics, GSEA, Cytoscape, Kaplan-Meier plotter, GDC, GeneMANIA, cBioPortal, PDB, RNAinter, miRNet were applied in this research. RESULTS: Our study uncovers that LAMP3 possesses higher expression levels in UCEC compared to normal tissues, and this differential expression profile is tightly aligned with clinical and pathological features, and patients demonstrating high LAMP3 expression tend to have a shorter survival expectancy. The high expression of LAMP3 is modulated by the designated ceRNA network. LAMP3 is engaged in UCEC progression by functioning in a variety of biological roles of relevance to immunity. Furthermore, we predicted several prospering drugs based on drug sensitivity. Finally, we also constructed possible docking patterns of LAMP3 with ABCA3, RAB9A, and SGTB. CONCLUSIONS: LAMP3 is a formidable biomarker for UCEC and could be a prospective candidate for the diagnosis, treatment and prognostic assessment of UCEC.

Identification of a robust biomarker LAPTM4A for glioma based on comprehensive computational biology and experimental verification.

BACKGROUND: Glioma, a highly invasive and deadly form of human neoplasm, presents a pressing need for the exploration of potential therapeutic targets. While the lysosomal protein transmembrane 4A (LATPM4A) has been identified as a risk factor in pancreatic cancer patients, its role in glioma remains unexplored. METHODS: The analysis of differentially expressed genes (DEG) was conducted from The Cancer Genome Atlas (TCGA) glioma dataset and the Genotype Tissue Expression (GTEx) dataset. Through weighted gene co-expression network analysis (WGCNA), the key glioma-related genes were identified. Among these, by using Kaplan-Meier (KM) analysis and univariate/multivariate COX methods, LAPTM4A emerged as the most influential gene. Moreover, the bioinformatics methods and experimental verification were employed to analyze its relationships with diagnosis, clinical parameters, epithelial-mesenchymal transition (EMT), metastasis, immune cell infiltration, immunotherapy, drug sensitivity, and ceRNA network. RESULTS: Our findings revealed that LAPTM4A was up-regulated in gliomas and was associated with clinicopathological features, leading to poor prognosis. Furthermore, functional enrichment analysis demonstrated that LATPM4A played a role in the immune system and cancer progression. In vitro experiments indicated that LAPTM4A may influence metastasis through the EMT pathway in glioma. Additionally, we found that LAPTM4A was associated with the tumor microenvironment (TME) and immunotherapy. Notably, drug sensitivity analysis revealed that patients with high LAPTM4A expression were sensitive to doxorubicin, which contributed to a reduction in LAPTM4A expression. Finally, we uncovered the FGD5-AS1-hsa-miR-103a-3p-LAPTM4A axis as a facilitator of glioma progression. CONCLUSIONS: In conclusion, our study identifies LATPM4A as a promising biomarker for prognosis and immune characteristics in glioma.

Boosting exciton mobility approaching Mott-Ioffe-Regel limit in Ruddlesden-Popper perovskites by anchoring the organic cation.

Exciton transport in two-dimensional Ruddlesden-Popper perovskite plays a pivotal role for their optoelectronic performance. However, a clear photophysical picture of exciton transport is still lacking due to strong confinement effects and intricate exciton-phonon interactions in an organic-inorganic hybrid lattice. Herein, we present a systematical study on exciton transport in (BA)2(MA)n-1PbnI3n+1 Ruddlesden-Popper perovskites using time-resolved photoluminescence microscopy. We reveal that the free exciton mobilities in exfoliated thin flakes can be improved from around 8 cm2 V-1 s-1 to 280 cm2V-1s-1 by anchoring the soft butyl ammonium cation with a polymethyl methacrylate network at the surface. The mobility of the latter is close to the theoretical limit of Mott-Ioffe-Regel criterion. Combining optical measurements and theoretical studies, it is unveiled that the polymethyl methacrylate network significantly improve the lattice rigidity resulting in the decrease of deformation potential scattering and lattice fluctuation at the surface few layers. Our work elucidates the origin of high exciton mobility in Ruddlesden-Popper perovskites and opens up avenues to regulate exciton transport in two-dimensional materials.

Correlated Self-Trapped Excitons and Free Excitons with Intermediate Exciton-Phonon Coupling in 2D Mixed-Halide Perovskites.

Low-dimensional lead halides have attracted increasing attention due to their potential application as single-component white-light emitters. These materials exhibit a complex emission spectral structure, ranging from free exciton narrowband emissions to self-trapped exciton broadband emissions. However, there is still no consensus for the underlying physical mechanism, especially in the spectrum with both narrowband and broadband emissions. Here we aim to elucidate the correlation between the emission spectrum and the exciton-phonon coupling in the mixed halide perovskite BA2Pb(BrxCl1-x)4. Our findings reveal that the interplay between exciton localization and delocalization results in an intermediate exciton-phonon coupling, leading to line shapes beyond the Huang-Rhys model for the self-trapped exciton. By incorporating the exciton motional effect, we establish a unified photophysical model describing the emission spectrum from the self-trapped exciton type to the free exciton type. These results provide essential insights into the mechanisms governing exciton-phonon interactions and offer ways to control white-light emission in two-dimensional perovskites.

Identified RP2 as a prognostic biomarker for glioma, facilitating glioma pathogenesis mainly via regulating tumor immunity.

Glioma is the most common primary intracranial tumor in the central nervous system, with a high degree of malignancy and poor prognosis, easy to recur, difficult to cure. The mutation of Retinitis Pigmentosa 2 (RP2) can cause retinitis pigmentosa, it is a prognostic factor of osteosarcoma, however, its role in glioma remains unclear. Based on the data from TCGA and GTEx, we identified RP2 as the most related gene for glioma by WGCNA, and used a series of bioinformatics analyses including LinkedOmics, GSCA, CTD, and so on, to explore the expression of RP2 in glioma and the biological functions it is involved in. The results showed that RP2 was highly expressed in glioma, and its overexpression could lead to poor prognosis. In addition, the results of enrichment analysis showed that RP2 was highly correlated with cell proliferation and immune response. And then, we found significant enrichment of Macrophages among immune cells. Furthermore, our experiments have confirmed that Macrophages can promote the development of glioma by secreting or influencing the secretion of some cytokines. Moreover, we investigated the influence of RP2 on the immunotherapy of glioma and the role of m6A modification in the influence of RP2 on glioma. Ultimately, we determined that RP2 is an independent prognostic factor that is mainly closely related to immune for glioma.