K+-Specification with Flavone P0 Probe in a G-Quadruplex DNA.

G-quadruplex (G4) DNA is considered as a prospective therapeutic target due to its potential biological significance. To understand G4 biological roles and function, a G4-specific fluorescent probe is necessary. However, it is difficult for versatile G4 to precisely recognize without perturbing their folding dynamics. Herein, we reported that flavone P0 can be a fluorescent probe for G4 DNA-specific recognition and have developed a highly selective detection of K+ ion by dimeric G4/P0 system. When comparing various nucleic acid structures, including G4, i-motif, ss/ds-DNA, and triplex, an apparent fluorescence enhancement is observed in the presence of G4 DNA for 85-fold, but only 8-fold for non-G4 DNA. Furthermore, based on fluorescent probe of flavone P0 for G4 DNA screening, the noncovalent dimeric G4/P0 system is exploited as a K+ sensor, that selectively responds to K+ with a 513-fold fluorescence enhancement and a detection range for K+ ion concentration from 0 to 500 mM. This K+ sensor also has a remarkably anti-interference ability for other metal cations, especially for a high concentration of Na+. These results have demonstrated that flavone P0 is an efficient tool for monitoring G-quadruplex DNA and endows flavone P0 with bioanalytical and medicinal applications.

Unraveling Intracellular Protein Corona Components of Nanoplastics via Photocatalytic Protein Proximity Labeling.

Bioaccumulation of nanoplastic particles has drawn increasing attention regarding environmental sustainability and biosafety. How nanoplastic particles interact with the cellular milieu still remains elusive. Herein, we exemplify a general approach to profile the composition of a "protein corona" interacting with nanoparticles via the photocatalytic protein proximity labeling method. To enable photocatalytic proximity labeling of the proteome interacting with particles, iodine-substituted BODIPY (I-BODIPY) is selected as the photosensitizer and covalently conjugated onto amino-polystyrene nanoparticles as a model system. Next, selective proximity labeling of interacting proteins is demonstrated using I-BODIPY-labeled nanoplastic particles in both Escherichia coli lysate and live alpha mouse liver 12 cells. Mechanistic studies reveal that the covalent modifications of proteins by an aminoalkyne substrate are conducted via a reactive oxygen species photosensitization pathway. Further proteomic analysis uncovers that mitochondria-related proteins are intensively involved in the protein corona, indicating substantial interactions between nanoplastic particles and mitochondria. In addition, proteostasis network components are also identified, accompanied by consequent cellular proteome aggregation confirmed by fluorescence imaging. Together, this work exemplifies a general strategy to interrogate the composition of the protein corona of nanomaterials by endowing them with photooxidation properties to enable photocatalytic protein proximity labeling function.

Chemical sensors detect and resolve proteome aggregation in peripheral neuropathy cell model induced by chemotherapeutic agents.

As a consequence of somatosensory nervous system injury or disease, neuropathic pain is commonly associated with chemotherapies, known as chemotherapy-induced peripheral neuropathy (CIPN). However, the mechanisms underlying CIPN-induced proteome aggregation in neuronal cells remain elusive due to limited detection tools. Herein, we present series sensors for fluorescence imaging (AggStain) and proteomics analysis (AggLink) to visualize and capture aggregated proteome in CIPN neuronal cell model. The environment-sensitive AggStain imaging sensor selectively binds and detects protein aggregation with 12.3 fold fluorescence enhancement. Further, the covalent AggLink proteomic sensor captures cellular aggregated proteins and profiles their composition via LC-MS/MS analysis. This integrative sensor platform reveals the presence of proteome aggregation in CIPN cell model and highlights its potential for broader applications in assessing proteome stability under various cellular stress conditions.

Tailoring the Amphiphilicity of Fluorescent Protein Chromophores to Detect Intracellular Proteome Aggregation in Diverse Biological Samples.

The formation of amorphous misfolded and aggregated proteins is a hallmark of proteome stress in diseased cells. Given its lack of defined targeting sites, the rational design of intracellular proteome aggregation sensors has been challenging. Herein, we modulate the amphiphilicity of fluorescent protein chromophores to enable selective detection of aggregated proteins in different biological samples, including recombinant proteins, stressed live cells, intoxicated mouse liver tissue, and human hepatocellular carcinoma tissue. By tuning the number of hydroxyl groups, we optimize the selectivity of fluorescent protein chromophores toward aggregated proteins in these biological samples. In recombinant protein applications, the most hydrophobic P0 (cLogP = 5.28) offers the highest fold change (FC = 31.6), sensitivity (LLOD = 0.1 µM), and brightness (Φ = 0.20) upon binding to aggregated proteins. In contrast, P4 of balanced amphiphilicity (cLogP = 2.32) is required for selective detection of proteome stresses in live cells. In mouse and human liver histology tissues, hydrophobic P1 exhibits the best performance in staining the aggregated proteome. Overall, the amphiphilicity of fluorescent chromophores governs the sensor's performance by matching the diverse nature of different biological samples. Together with common extracellular amyloid sensors (e.g., Thioflavin T), these sensors developed herein for intracellular amorphous aggregation complement the toolbox to study protein aggregation.

Developing an Affinity-Based Chemical Proteomics Method to In Situ Capture Amorphous Aggregated Proteome and Profile Its Heterogeneity in Stressed Cells.

Stress induced amorphous proteome aggregation is a hallmark for diseased cells, with the proteomic composition intimately associated with disease pathogenicity. Due to its particularly dynamic, reversible, and dissociable nature, as well as lack of specific recognition anchor, it is difficult to capture aggregated proteins in situ. In this work, we develop a chemical proteomics method (AggLink) to capture amorphous aggregated proteins in live stressed cells and identify the proteomic contents using LC-MS/MS. Our method relies on an affinity-based chemical probe (AggLink 1.0) that is optimized to selectively bind to and covalently label amorphous aggregated proteins in live stressed cells. Especially, chaotrope-compatible ligation enables effective enrichment of labeled aggregated proteins under urea denaturation and dissociation conditions. Compared to conventional fractionation-based method to profile aggregated proteome, our method showed improved enrichment selectivity, detection sensitivity, and identification accuracy. In HeLa cells, the AggLink method reveals the constituent heterogeneity of aggregated proteome induced by inhibition of pro-folding (HSP90) or pro-degradation (proteasome) pathway, which uncovers a synergistic strategy to reduce cancer cell viability. In addition, the unique fluorogenicity of our probe upon labeling aggregated proteome detects its cellular location and morphology. Together, the AggLink method may help to expand our knowledge of the previously nontargetable amorphous aggregated proteome.

Plastic nanoparticles cause proteome stress and aggregation by compromising cellular protein homeostasis ex vivo and in vivo.

Decomposition of plastic materials into minuscule particles and their long-term uptake pose increasing concerns on environmental sustainability and biosafety. Besides common cell viability and cytotoxicity evaluations, how plastic nanoparticles interfere with different stress response pathways and affect cellular fitness has been less explored. Here, we provided the first piece of evidence to demonstrate plastic nanoparticles potentially can deteriorate proteome stability, compromise cellular protein homeostasis, and consequently cause global proteome misfolding and aggregation. Polystyrene (PS) nanoparticles of different sizes and surface charges were exploited as model plastic materials. In cell lysate and human blood plasma, naked PS nanoparticles with hydrophobic surface deteriorated proteome thermodynamic stability and exaggerated its aggregation propensity. While no cell viability ablation was observed in cells treated with PS nanoparticles up to 200 µg·mL-1, global proteome aggregation and stress was detected by a selective proteome aggregation sensor. Further proteomics analysis revealed how protein homeostasis network was remodeled by positively charged PS nanoparticles via differential expression of key proteins to counteract proteome stress. In mice model, size-dependent liver accumulation of positively charged PS nanoparticles induced hepatocellular proteome aggregation and compromised protein homeostasis network capacity that were invisible to standard alanine transaminase and aspartate transaminase (ALT/AST) liver function as-say and histology. Meanwhile, long-term liver accumulation of plastic nanoparticles deteriorated liver metabolism and saturated liver detoxification capacity of overdosed acetaminophen. This work highlighted the impact of nanoplastics on cellular proteome integrity and cellular fitness that are invisible to current biochemical assays and clinical tests.

[Applications and challenges of wearable electroencephalogram signals in depression recognition and personalized music intervention].

Rapid and accurate identification and effective non-drug intervention are the worldwide challenges in the field of depression. Electroencephalogram (EEG) signals contain rich quantitative markers of depression, but whole-brain EEG signals acquisition process is too complicated to be applied on a large-scale population. Based on the wearable frontal lobe EEG monitoring device developed by the authors' laboratory, this study discussed the application of wearable EEG signal in depression recognition and intervention. The technical principle of wearable EEG signals monitoring device and the commonly used wearable EEG devices were introduced. Key technologies for wearable EEG signals-based depression recognition and the existing technical limitations were reviewed and discussed. Finally, a closed-loop brain-computer music interface system for personalized depression intervention was proposed, and the technical challenges were further discussed. This review paper may contribute to the transformation of relevant theories and technologies from basic research to application, and further advance the process of depression screening and personalized intervention.

A Novel Virus Detection Strategy Enabled by TR512-Peptide-Based Bioorthogonal Capture and Enrichment of Preamplified Nucleic Acid.

High-cost viral nucleic acid detection devices (e.g., qPCR system) are limited resources for developing counties and rural areas, leading to underdiagnosis or even pandemics of viral infectious diseases. Herein, a novel virus detection strategy is reported. Such detection method is enabled by TR512-peptide-based biorthogonal capture and enrichment of commercially available Texas red fluorophore labeled nucleic acid on the functionalized paper. The GST-TR512 fusion protein electrostatically immobilized on the paper is constructed to retain the binding affinity of TR512-peptide toward Texas red fluorophore labeled nucleic acid released in the preamplification process, then the enrichment of analytes enhances fluorescence signal for rapid detection as volume of sample filters through the paper. The method is generally applicable to different nucleic acid preamplification strategies (PCR, RAA, CRISPR) and different virus types (Hepatitis B virus (HBV), African swine fever virus (ASFV), human papillomavirus (HPV), and severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2 or 2019 nCoV)). Finally, a full-set virus detection device is developed in house to detect the presence of Hepatitis B virus (HBV) viral gene in patients' blood samples. Taken together, we first apply TR512-peptide in the signal enrichment and the novel detection strategy may offer an inexpensive, rapid, and portable solution for areas with limited access to a standard diagnosis laboratory.

Covalent Solvatochromic Proteome Stress Sensor Based on the Schiff Base Reaction.

Covalent-type probes or sensors have been seldom reported for aggregated proteins. Herein, we reported a series of covalent solvatochromic probes to selectively modify and detect aggregated proteomes through the Schiff base reaction. Such covalent modification was discovered by serendipity using the P1 probe with an aldehyde functional group, exhibiting enhanced fluorescence intensity and unusually large blue shift upon protein aggregation. Supported by the biochemical and mass spectrometry results, we identified that this probe can modify the lysine residue of aggregated proteins selectively over folded ones via the Schiff base reaction. The generality of designing such a covalent-type probe was demonstrated in multiple probe scaffolds using different model proteins. Finally, we exploited the distinct solvatochromism of P1 after Schiff base linkage with aggregated proteins to visualize the distinct morphology of aggregated proteomes, as well as to quantify the polarity heterogeneity inside it. This work may intrigue the exploration of other chemical reaction types to covalently functionalize aggregated proteins that were difficult to analyze.

Signal Quality Investigation of a New Wearable Frontal Lobe EEG Device.

The demand for non-laboratory and long-term EEG acquisition in scientific and clinical applications has put forward new requirements for wearable EEG devices. In this paper, a new wearable frontal EEG device called Mindeep was proposed. A signal quality study was then conducted, which included simulated signal tests and signal quality comparison experiments. Simulated signals with different frequencies and amplitudes were used to test the stability of Mindeep's circuit, and the high correlation coefficients (>0.9) proved that Mindeep has a stable and reliable hardware circuit. The signal quality comparison experiment, between Mindeep and the gold standard device, Neuroscan, included three tasks: (1) resting; (2) auditory oddball; and (3) attention. In the resting state, the average normalized cross-correlation coefficients between EEG signals recorded by the two devices was around 0.72 ± 0.02, Berger effect was observed (p < 0.01), and the comparison results in the time and frequency domain illustrated the ability of Mindeep to record high-quality EEG signals. The significant differences between high tone and low tone in auditory event-related potential collected by Mindeep was observed in N2 and P2. The attention recognition accuracy of Mindeep achieved 71.12% and 74.76% based on EEG features and the XGBoost model in the two attention tasks, respectively, which were higher than that of Neuroscan (70.19% and 72.80%). The results validated the performance of Mindeep as a prefrontal EEG recording device, which has a wide range of potential applications in audiology, cognitive neuroscience, and daily requirements.

Monitoring the Dynamics of Proteome Aggregation in Live Cells Using a Solubilized and Noncovalent Analogue of Fluorescent Protein Chromophores.

Stress-induced intracellular proteome aggregation is a hallmark and a biomarker of various human diseases. Current sensors requiring either cellular fixation or covalent modification of the entire proteome are not suitable for live-cell applications and dynamics study. Herein, we report a noncovalent, cell-permeable, and fluorogenic sensor that can reversibly bind to proteome amorphous aggregates and monitor their formation, transition, and clearance in live cells. This sensor was structurally optimized from previously reported fluorescent protein chromophores to enable noncovalent and reversible binding to aggregated proteins. Unlike all previous sensors, the noncovalent and reversible nature of this probe allows for dynamic detection of both the formation and clearance of aggregated proteome in one live-cell sample. Under different cellular stresses, this sensor reveals drastic differences in the morphology and location of aggregated proteome. Furthermore, we have shown that this sensor can detect the transition from proteome liquid-to-liquid phase separation to liquid-to-solid phase separation in a two-color imaging experiment. Overall, the sensor reported here can serve as a facile tool to screen therapeutic drugs and identify cellular pathways that ameliorate pathogenic proteome aggregation in live-cell models.

Regulation of Fluorescence Solvatochromism To Resolve Cellular Polarity upon Protein Aggregation.

Common solvatochromic fluorophores exhibit a bathochromic fluorescence emission wavelength shift accompanied by intensity attenuation due to the presence of nonradiative decay pathways at the excited state. Such intrinsic but inevitable fluorescence quenching of solvatochromism impedes its applications to faithfully quantify local polarity, especially in a polar environment. Herein, we report a new donor-π-acceptor (D-π-A) type solvatochromic fluorophore scaffold containing a perfluorophenyl group that exhibits both a solvatochromic emission wavelength shift and a controllable emission intensity upon polarity fluctuation. The regulation of fluorescence solvatochromism and colors was achieved by tuning the aryl donors. We exploited such desired solvatochromism of these probes to monitor protein misfolding and aggregation via wavelength shift. Finally, the polarity of pathogenic aggregated proteins was quantified by HaloTag bioorthogonal labeling technology in live cells. While much effort has been devoted to resolving the morphology of pathogenic aggregated proteins, this work provides quantitative hints regarding the chemical information at this disease-related protein interphase.

Static-Dynamic Fluorescence Patterns Based on Photodynamic Disulfide Reactions for Versatile Information Storage.

Dynamic fluorescence patterns with variable output in response to external stimulus can make the current information storage technologies more flexible and intelligent. Yet it remains a great challenge to create such dynamic patterns because of the complicated synthesis process, high cost, limited stability, and biocompatibility of the functional fluorophores. Herein, a facile approach is presented for creating dynamic fluorescence patterns using the photodynamic surface chemistry based on disulfide bonds. By this method, high-resolution (≈20 µm) multicolor dynamic fluorescence patterns that are low-cost and dynamically rewritable can be easily fabricated using classical fluorophores such as fluorescein, rhodamine, and dansyl acid. Owing to the spatio-temporal controllability of light, the fluorescence patterns can be partly or entirely erased/rewritten on demand, and complex gray-level fluorescence images with increased information capacity can be easily generated. The obtained fluorescence patterns exhibit little changes after storing in air and solvent environments for 100 days, demonstrating their high stability. In addition, static patterns can also be created on the same disulfide surface using irreversible disulfide-ene chemistry, to selectively control the dynamicity of the generated fluorescence patterns. The authors show the successful application of this strategy on information protection and transformation.

A Solvatochromic Fluorescent Probe Reveals Polarity Heterogeneity upon Protein Aggregation in Cells.

We report a crystallization-induced emission fluorophore to quantitatively interrogate the polarity of aggregated proteins. This solvatochromic probe, namely "AggRetina" probe, inherently binds to aggregated proteins and exhibits both a polarity-dependent fluorescence emission wavelength shift and a viscosity-dependent fluorescence intensity increase. Regulation of its polarity sensitivity was achieved by extending the conjugation length. Different proteins bear diverse polarity upon aggregation, leading to different resistance to proteolysis. Polarity primarily decreases during protein misfolding but viscosity mainly increases upon the formation of insoluble aggregates. We quantified the polarity of aggregated protein-of-interest in live cells via HaloTag bioorthogonal labeling, revealing polarity heterogeneity within cellular aggregates. The enriched micro-environment details inside misfolded and aggregated proteins may correlate to their bio-chemical properties and pathogenicity.

Rational Design of Crystallization-Induced-Emission Probes To Detect Amorphous Protein Aggregation in Live Cells.

Unlike amyloid aggregates, amorphous protein aggregates with no defined structures have been challenging to target and detect in a complex cellular milieu. In this study, we rationally designed sensors of amorphous protein aggregation from aggregation-induced-emission probes (AIEgens). Utilizing dicyanoisophorone as a model AIEgen scaffold, we first sensitized the fluorescence of AIEgens to a nonpolar and viscous environment mimicking the interior of amorphous aggregated proteins. We identified a generally applicable moiety (dimethylaminophenylene) for selective binding and fluorescence enhancement. Regulation of the electron-withdrawing groups tuned the emission wavelength while retaining selective detection. Finally, we utilized the optimized probe to systematically image aggregated proteome upon proteostasis network regulation. Overall, we present a rational approach to develop amorphous protein aggregation sensors from AIEgens with controllable sensitivity, spectral coverage, and cellular performance.

Covalent Probes for Aggregated Protein Imaging via Michael Addition.

Covalent chemical reactions to modify aggregated proteins are rare. Here, we reported covalent Michael addition can generally occur upon protein aggregation. Such reactivity was initially discovered by a bioinspired fluorescent color-switch probe mimicking the photo-conversion mechanism of Kaede fluorescent protein. This probe was dark with folded proteins but turned on red fluorescence (620 nm) when it non-covalently bound to misfolded proteins. Supported by the biochemical and mass spectrometry results, the probe chemoselectively reacted with the reactive cysteines of aggregated proteins via covalent Michael addition and gradually switched to green fluorescence (515 nm) upon protein aggregation. Exploiting this Michael addition chemistry in the malachite green dye derivatives demonstrated its general applicability and chemical tunability, resulting in different fluorescence color-switch responses. Our work may offer a new avenue to explore other chemical reactions upon protein aggregation and design covalent probes for imaging, chemical proteomics, and therapeutic purposes.

Highly Luminescent Heavier Main Group Analogues of Boron-Dipyrromethene.

The preparation and photophysical properties of two heavier main group element analogues of boron-dipyrromethene (BODIPY) chromophores are described. Specifically, we have prepared dipyrrin complexes of dichlorogallate (GADIPY) or phenylphosphenium (PHODIPY) units. Whereas cationic PHODIPY is labile, decomposing to a phosphine over time, GADIPY is readily prepared in good yield as a crystalline solid having moderate air- and water-stability. Crystallographically characterized GADIPY displays intense green photoluminescence (λem = 505 nm, Φem = 0.91 in toluene). These inaugural heavier main group element analogues of BODIPY offer a glimpse into the potential for elaboration to a panoply of chromophores with diverse photophysical properties.

Recognition of Emotional States Using Multiscale Information Analysis of High Frequency EEG Oscillations.

Exploring the manifestation of emotion in electroencephalogram (EEG) signals is helpful for improving the accuracy of emotion recognition. This paper introduced the novel features based on the multiscale information analysis (MIA) of EEG signals for distinguishing emotional states in four dimensions based on Russell's circumplex model. The algorithms were applied to extract features on the DEAP database, which included multiscale EEG complexity index in the time domain, and ensemble empirical mode decomposition enhanced energy and fuzzy entropy in the frequency domain. The support vector machine and cross validation method were applied to assess classification accuracy. The classification performance of MIA methods (accuracy = 62.01%, precision = 62.03%, recall/sensitivity = 60.51%, and specificity = 82.80%) was much higher than classical methods (accuracy = 43.98%, precision = 43.81%, recall/sensitivity = 41.86%, and specificity = 70.50%), which extracted features contain similar energy based on a discrete wavelet transform, fractal dimension, and sample entropy. In this study, we found that emotion recognition is more associated with high frequency oscillations (51-100Hz) of EEG signals rather than low frequency oscillations (0.3-49Hz), and the significance of the frontal and temporal regions are higher than other regions. Such information has predictive power and may provide more insights into analyzing the multiscale information of high frequency oscillations in EEG signals.

A size-dependent sodium storage mechanism in Li4Ti5O12 investigated by a novel characterization technique combining in situ X-ray diffraction and chemical sodiation.

A novel characterization technique using the combination of chemical sodiation and synchrotron based in situ X-ray diffraction (XRD) has been detailed illustrated. The power of this novel technique was demonstrated in elucidating the structure evolution of Li4Ti5O12 upon sodium insertion. The sodium insertion behavior into Li4Ti5O12 is strongly size dependent. A solid solution reaction behavior in a wide range has been revealed during sodium insertion into the nanosized Li4Ti5O12 (~44 nm), which is quite different from the well-known two-phase reaction of Li4Ti5O12/Li7Ti5O12 system during lithium insertion, and also has not been fully addressed in the literature so far. On the basis of this in situ experiment, the apparent Na(+) ion diffusion coefficient (DNa+) of Li4Ti5O12 was estimated in the magnitude of 10(-16) cm(2) s(-1), close to the values estimated by electrochemical method, but 5 order of magnitudes smaller than the Li(+) ion diffusion coefficient (D(Li+) ~10(-11) cm(2) s(-1)), indicating a sluggish Na(+) ion diffusion kinetics in Li4Ti5O12 comparing with that of Li(+) ion. Nanosizing the Li4Ti5O12 will be critical to make it a suitable anode material for sodium-ion batteries. The application of this novel in situ chemical sodiation method reported in this work provides a facile way and a new opportunity for in situ structure investigations of various sodium-ion battery materials and other systems.

Beyond Frequency Bands: Complementary-Ensemble-Empirical-Mode-Decomposition-Enhanced Microstate Sequence Non-Randomness Analysis for Aiding Diagnosis and Cognitive Prediction of Dementia.

Exploring the spatiotemporal dynamic patterns of multi-channel electroencephalography (EEG) is crucial for interpreting dementia and related cognitive decline. Spatiotemporal patterns of EEG can be described through microstate analysis, which provides a discrete approximation of the continuous electric field patterns generated by the brain cortex. Here, we propose a novel microstate spatiotemporal dynamic indicator, termed the microstate sequence non-randomness index (MSNRI). The essence of the method lies in initially generating a sequence of microstate transition patterns through state space compression of EEG data using microstate analysis. Following this, we assess the non-randomness of these microstate patterns using information-based similarity analysis. The results suggest that this MSNRI metric is a potential marker for distinguishing between health control (HC) and frontotemporal dementia (FTD) (HC vs. FTD: 6.958 vs. 5.756, p < 0.01), as well as between HC and populations with Alzheimer's disease (AD) (HC vs. AD: 6.958 vs. 5.462, p < 0.001). Healthy individuals exhibit more complex macroscopic structures and non-random spatiotemporal patterns of microstates, whereas dementia disorders lead to more random spatiotemporal patterns. Additionally, we extend the proposed method by integrating the Complementary Ensemble Empirical Mode Decomposition (CEEMD) method to explore spatiotemporal dynamic patterns of microstates at specific frequency scales. Moreover, we assessed the effectiveness of this innovative method in predicting cognitive scores. The results demonstrate that the incorporation of CEEMD-enhanced microstate dynamic indicators significantly improved the prediction accuracy of Mini-Mental State Examination (MMSE) scores (R2 = 0.940). The CEEMD-enhanced MSNRI method not only aids in the exploration of large-scale neural changes in populations with dementia but also offers a robust tool for characterizing the dynamics of EEG microstate transitions and their impact on cognitive function.