MXene-Mediated Catalytic Redox Reactions for Biomedical Applications

Reactive oxygen species (ROS) play a crucial role in orchestrating a myriad of physiological processes within living systems. With the advent of materdicine, an array of nanomaterials has been intricately engineered to influence the redox equilibrium in biological milieus, thereby pioneering a distinctive therapeutic paradigm predicated on ROS-centric biochemistry. Among these, two-dimensional carbides, nitrides, and carbonitrides, collectively known as MXenes, stand out due to their multi-valent and multi-elemental compositions, large surface area, high conductivity, and pronounced local surface plasmon resonance effects, positioning them as prominent contributors in ROS modulation. This review aims to provide an overview of the advancements in harnessing MXenes for catalytic redox reactions in various biological applications, including tumor, anti-infective, and anti-inflammatory therapies. The emphasis lies on elucidating the therapeutic mechanism of MXenes, involving both pro-oxidation and anti-oxidation processes, underscoring the redox-related therapeutic applications facilitated by self-catalysis, photo-excitation, and sono-excitation properties of MXenes. Furthermore, this review highlights the existing challenges and outlines future development trends in leveraging MXenes for ROS-involving disease treatments, marking a significant step towards the integration of these nanomaterials into clinical practice.

Exploring the role of mutual prediction in inter-brain synchronization during competitive interactions: an fNIRS hyperscanning investigation

Mutual prediction is crucial for understanding the mediation of bodily actions in social interactions. Despite this importance, limited studies have investigated neurobehavioral patterns under the mutual prediction hypothesis in natural competitive scenarios. To address this gap, our study employed functional near-infrared spectroscopy hyperscanning to examine the dynamics of real-time rock-paper-scissors games using a computerized paradigm with 54 participants. Firstly, our results revealed activations in the right inferior frontal gyrus, bilateral dorsolateral prefrontal cortex, and bilateral frontopolar cortex, each displaying distinct temporal profiles indicative of diverse cognitive processes during the task. Subsequently, a task-related increase in inter-brain synchrony was explicitly identified in the right dorsolateral prefrontal cortex, which supported the mutual prediction hypothesis across the two brains. Moreover, our investigation uncovered a close association between the coherence value in the right dorsolateral prefrontal cortex and the dynamic predictive performances of dyads using inter-subject representational similarity analysis. Finally, heightened inter-brain synchrony values were observed in the right dorsolateral prefrontal cortex before a draw compared to a no-draw scenario in the second block, suggesting that cross-brain signal patterns could be reflected in behavioral responses during competition. In summary, these findings provided initial support for expanding the understanding of cognitive processes underpinning natural competitive engagements.

Language Nativeness Modulates Physiological Responses to Moral vs. Immoral Concepts in Chinese-English Bilinguals: Evidence from Event-Related Potential and Psychophysiological Measures

Morality has been an integral part of social cognition and our daily life, and different languages may exert distinct impacts on human moral judgment. However, it remains unclear how moral concept is encoded in the bilingual brain. This study, therefore, aimed to explore the emotional and cognitive involvement of bilingual morality judgement by using combined event-related potential (ERP) and psychophysiological (including skin, heart, and pulse) measures. In the experiment, thirty-one Chinese-English bilingual participants were asked to make moral judgments in Chinese and English, respectively. Our results revealed increased early frontal N400 and decreased LPC in L1 moral concept encoding as compared to L2, suggesting that L1 was more reliant on automatic processes and emotions yet less on elaboration. In contrast, L2 moral and immoral concepts elicited enhanced LPC, decreased N400, and greater automatic psychophysiological electrocardiograph responses, which might reflect more elaborate processing despite blunted emotional responses and increased anxiety. Additionally, both behavioral and P200 data revealed a reliable immorality bias across languages. Our results were discussed in light of the dual-process framework of moral judgments and the (dis)embodiment of bilingual processing, which may advance our understanding of the interplay between language and morality as well as between emotion and cognition.

Liquid Nanoparticles for Nanocatalytic Cancer Therapy

Nanotechnology is revolutionizing cancer therapy, and catalyzes the emerging of ion-involved cancer-therapeutic modality, which unfortunately suffers from undesirable nanocarriers for efficient intracellular ion delivery. To radically extricate from this critical issue, the glutathione (GSH)-responsive organosilica network is employed to lock the liquid drops at the nanoscale via a general bottom-up strategy to achieve the systemic delivery of "ion drugs". In this work, a sulfate radical generation donor (Na2 S2 O8 ), as a paradigm "ion drug", is entrapped into this liquid nanoparticle for efficiently delivering to the tumor region. After further surface engineering with pH-responsive tannic acid-Fe2+ framework, these liquid nanoparticles achieve tumor-microenvironmental pH/GSH-dual responsive ion release (Fe2+ /Na+ /S2 O8 2- ) after reaching the tumor sites, where the Fe2+ further triggers S2 O8 2- to generate toxic •SO4 - and •OH, effectively executing cancer cell ferroptosis (Fe2+ , reactive oxygen species-ROS) and pyroptosis (Na+ , ROS). Such a tumor-responsive/specific liquid nanoplatform is highly instructive for further ion-mediated nanomedicine and disease treatment.

Dynamic Growth of Macroscopically Structured Supramolecular Hydrogels through Orchestrated Reaction-Diffusion

Living organisms are capable of dynamically changing their structures for adaptive functions through sophisticated reaction-diffusion processes. Here we show how active supramolecular hydrogels with programmable lifetimes and macroscopic structures can be created by relying on a simple reaction-diffusion strategy. Two hydrogel precursors (poly(acrylic acid) PAA/CaCl2 and Na2 CO3 ) diffuse from different locations and generate amorphous calcium carbonate (ACC) nanoparticles at the diffusional fronts, leading to the formation of hydrogel structures driven by electrostatic interactions between PAA and ACC nanoparticles. Interestingly, the formed hydrogels are capable of autonomously disintegrating over time because of a delayed influx of electrostatic-interaction inhibitors (NaCl). The hydrogel growth process is well explained by a reaction-diffusion model which offers a theoretical means to program the dynamic growth of structured hydrogels. Furthermore, we demonstrate a conceptual access to dynamic information storage in soft materials using the developed reaction-diffusion strategy. This work may serve as a starting point for the development of life-like materials with adaptive structures and functionalities.

Atomically Dispersed Co2 MnN8 Triatomic Sites Anchored in N-Doped Carbon Enabling Efficient Oxygen Reduction Reaction

Atomically dispersed transition metal-nitrogen/carbon (M-N/C) catalysts have emerged as the most promising substitutes to the precious platinum counterparts toward the oxygen reduction reaction (ORR). However, the reported M-N/C catalysts are usually in the form of common M-N4 moieties with only a single metal active site, and they suffer from insufficient activity. Herein, an unusual trinuclear active structure is elaborately developed with a nitrogen-coordinated single Mn atom adjacent to two Co atoms (Co2 MnN8 ) anchored in N-doped carbon as a highly efficient ORR catalyst via adsorption-pyrolysis of a bimetallic zeolitic imidazolate framework precursor. Atomic structural investigations and density functional theory (DFT) calculations reveal that Co2 MnN8 would experience a spontaneous OH binding to form Co2 MnN8 -2OH as the real active site, leading to a single electron-filled state in thed z 2 ${\mathrm{d}}_{{z}^{2}}$ orbital and an optimized binding energy of intermediates. Accordingly, the as-developed Co2 MnN8 /C exhibits an unprecedented ORR activity with a high half-wave potential of 0.912 V and outstanding stability, not only surpassing the Pt/C catalyst but also representing a new record for the Co-based catalyst.

Non-Invasive Detection, Precise Localization, and Perioperative Navigation of In Vivo Deep Lesions Using Transmission Raman Spectroscopy

Non-invasive detection and precise localization of deep lesions have attracted significant attention for both fundamental and clinical studies. Optical modality techniques are promising with high sensitivity and molecular specificity, but are limited by shallow tissue penetration and the failure to accurately determine lesion depth. Here the authors report in vivo ratiometric surface-enhanced transmission Raman spectroscopy (SETRS) for non-invasive localization and perioperative surgery navigation of deep sentinel lymph nodes in live rats. The SETRS system uses ultrabright surface-enhanced Raman spectroscopy (SERS) nanoparticles with a low detection limit of 10 pM and a home-built photosafe transmission Raman spectroscopy setup. The ratiometric SETRS strategy is proposed based on the ratio of multiple Raman spectral peaks for obtaining lesion depth. Via this strategy, the depth of the phantom lesions in ex vivo rat tissues is precisely determined with a mean-absolute-percentage-error of 11.8%, and the accurate localization of a 6-mm-deep rat popliteal lymph node is achieved. The feasibility of ratiometric SETRS allows the successful perioperative navigation of in vivo lymph node biopsy surgery in live rats under clinically safe laser irradiance. This study represents a significant step toward the clinical translation of TRS techniques, providing new insights for the design and implementation of in vivo SERS applications.

An Active Vibration Isolation and Compensation System for Improving Optical Image Quality: Modeling and Experiment

Optical detection equipment (ODE) is subjected to vibrations that hamper the quality of imaging. In this paper, an active vibration isolation and compensation system (VICS) for the ODE is developed and systematically studied to improve the optical imaging quality. An active vibration isolator for cameras is designed, employing a dual-loop control strategy with position compensation and integral force feedback (IFF) control, and establishing the mapping relationship between vibration and image quality. A performance metric for evaluating images is also proposed. Finally, an experimental platform is constructed to verify its effectiveness. Based on the experimental results, it can be concluded that the proposed VICS effectively isolates vibrations, resulting in a reduction of 13.95 dB in the peak at the natural frequency and an 11.76 Hz widening of the isolation bandwidth compared with the system without it. At the same time, the experiments demonstrate that the image performance metric value increases by 46.03% near the natural frequency.

Novel CH25H+ and OASL+ microglia subclusters play distinct roles in cerebral ischemic stroke

BACKGROUND

Microglial polarization is one of the most promising therapeutic targets for multiple central nervous system (CNS) disorders, including ischemic stroke. However, detailed transcriptional alteration of microglia following cerebral ischemic stroke remains largely unclear.

METHODS

Focal cerebral ischemia was induced by transient middle cerebral artery occlusion (tMCAO) for 60 min in mice. Single-cell RNA sequencing (scRNA-seq) was performed using ischemic brain tissues from tMCAO and sham mice 3 days after surgery. Ch25h^-/- mice were used to investigate the role of specific microglia subcluster on post-stroke infarct volume and neuroinflammation.

RESULTS

We identified a relatively homeostatic subcluster with enhanced antigen processing and three "ischemic stroke associated microglia" (ISAM): MKI67⁺, CH25H⁺ and OASL⁺ subclusters. We found the MKI67⁺ subcluster undergo proliferation and differentiation into CH25H⁺ and OASL⁺ subclusters. CH25H⁺ microglia was a critical subcluster of ISAM that exhibited increased phagocytosis and neuroprotective property after stroke. Ch25h^-/- mice developed significantly increased infarct volume following ischemic stroke compared to Ch25h^+/-. Meanwhile, the OASL⁺ subcluster accumulated in the ischemic brain and was associated with the evolving of neuroinflammation after stroke, which was further aggravated in the aged mice brain.

CONCLUSIONS

Our data reveal previously unrecognized roles of the newly defined CH25H⁺ and OASL⁺ microglia subclusters following ischemic stroke, with novel insights for precise microglia modulation towards stroke therapy.

M2e-specific antibodies protect against influenza PR8 virus in an isotype and route dependent manner

The ectodomain of influenza matrix protein 2 (M2e) is a promising target for the development of universal prophylactic and therapeutic agents against influenza viruses of different subtypes. We constructed three M2e-specific monoclonal antibody variants, M2A1-1 (IgG1), M2A1-2a (IgG2a), M2A1-2b (IgG2b), which have the same Fab region targeting the M2e epitope but different isotypes, and compared their protective efficacy in influenza PR8-infected mice. We found that anti-M2e antibodies provided protection against influenza virus in a subtype-dependent manner, with the IgG2a variant providing significantly better protection with lower virus titers and milder lung injury than IgG1 and IgG2b isotypes. Additionally, we observed that the protective efficacy was dependent on the administration routes, with intranasal administration of antibody providing better protection than intraperitoneal administration. The timing of administration was also critical in determining the protective efficacy; while all the antibody isotypes provided protection when administered before influenza challenge, only IgG2a provided minimal protection when the antibodies were administered after virus challenge. These results provide valuable information for optimizing the therapeutics usage of M2e-based antibodies and furthering the development of M2e-based universal influenza vaccines.

The Online Strength-Informed Acceptance and Commitment Therapy Among COVID-19-Affected Adolescents

Purpose: This study develops and investigates the changes in anxiety symptoms and quality of life (QoL) among participants of the online Strength-informed Acceptance and Commitment Therapy (SACT) across three tests.

METHODS

A small-scale, quasi-experiment with no control group was conducted. Repeated-measures analysis was employed to assess the changes of the three tests, which were the pre-experimental, post-test, and 3-month follow-up test. A total of 47 adolescents (ages 10-12) completed the 45-min intervention that lasted 10 weeks.

RESULTS

Compared with the pre-experimental, the post-test indicated significant anxiety symptoms reduction but not a statistically significant increase in QoL. The 3-month follow-up test indicated reduced anxiety symptoms and improved QoL compared with the pre-experimental. The with-in subject changes were substantial.

CONCLUSIONS

The online SACT is a promising model to reduce anxiety symptoms and promote QoL among adolescents during the current COVID-19 pandemic, which show both short- and long-term benefit to the participants.

Cancer classification based on chromatin accessibility profiles with deep adversarial learning model

Given the complexity and diversity of the cancer genomics profiles, it is challenging to identify distinct clusters from different cancer types. Numerous analyses have been conducted for this propose. Still, the methods they used always do not directly support the high-dimensional omics data across the whole genome (Such as ATAC-seq profiles). In this study, based on the deep adversarial learning, we present an end-to-end approach ClusterATAC to leverage high-dimensional features and explore the classification results. On the ATAC-seq dataset and RNA-seq dataset, ClusterATAC has achieved excellent performance. Since ATAC-seq data plays a crucial role in the study of the effects of non-coding regions on the molecular classification of cancers, we explore the clustering solution obtained by ClusterATAC on the pan-cancer ATAC dataset. In this solution, more than 70% of the clustering are single-tumor-type-dominant, and the vast majority of the remaining clusters are associated with similar tumor types. We explore the representative non-coding loci and their linked genes of each cluster and verify some results by the literature search. These results suggest that a large number of non-coding loci affect the development and progression of cancer through its linked genes, which can potentially advance cancer diagnosis and therapy.