Research最新文献

Photonic synapses combining photosensitivity and synaptic function can efficiently perceive and memorize visual information, making them crucial for the development of artificial vision systems. However, the development of high-performance photonic synapses with low power consumption and rapid optical erasing ability remains challenging. Here, we propose a photon-modulated charging/discharging mechanism for self-powered photonic synapses. The current hysteresis enables the devices based on CsPbBr₃/solvent/carbon nitride multilayer architecture to emulate synaptic behaviors, such as excitatory postsynaptic currents, paired-pulse facilitation, and long/short-term memory. Intriguingly, the unique radiation direction-dependent photocurrent endows the photonic synapses with the capability of optical writing and rapid optical erasing. Moreover, the photonic synapses exhibit exceptional performance in contrast enhancement and noise reduction owing to the notable synaptic plasticity. In simulations based on artificial neural network (ANN) algorithms, the pre-processing by our photonic synapses improves the recognition rate of handwritten digit from 11.4% (200 training epochs) to 85% (~60 training epochs). Furthermore, due to the excellent feature extraction and memory capability, an array based on the photonic synapses can imitate facial recognition of human retina without the assistance of ANN.

Dietary factors play a crucial role in irritable bowel syndrome (IBS) pathogenesis. Therefore, the dietary contraindications for patients with IBS require further supplementation. Recent investigations have revealed that ginger consumption may pose a risk of aggravating the symptoms and incidence of IBS; however, the specific mechanism remains unknown. In this study, we developed experimental IBS and intestinal organoid differentiation screening models to elucidate the mechanisms underlying the ginger-mediated exacerbation of IBS symptoms. Subsequently, we used a knockout approach combined with click chemistry as well as virus infection to identify the toxic components of ginger and the target mechanism. Our results showed that a daily intake of 90 to 300 mg/kg ginger (equivalent to a human daily dose of 0.6 to 2 g per person) may pose a risk of exacerbating IBS symptoms. Furthermore, a component derived from 6-gingerol (ginger's main ingredient) through in vivo gastric acid and heat processing inhibited the formation of the eIF3 transcription initiation complex by covalently binding to the Cys⁵⁸ site of eIF3A, a key factor regulating intestinal crypt stem cell differentiation, further reducing the goblet cell number and related mucus layer thickness and increasing lipopolysaccharide infiltration and low-grade inflammation in the ileum crypts, thereby exacerbating the symptoms of IBS in mice. Our study suggests that dietary ginger aggravates IBS and provides safety evaluation methods for the proper use of foods in specific populations.

Polymer fibers are attracting increasing attention as a type of fundamental material for a wide range of products. However, to incorporate novel functionality, a crucial challenge is to simultaneously manipulate their structuring across multiple length scales. In this research, a facile and universal approach is proposed by directly drawing a pre-gel feedstock embedding a cellulose cholesteric liquid crystal (CLC). An in situ photo-polymerization process is applied, which not only allows for the continuous drawing of the filaments without breakup but also makes the final CLC fibers a colored appearance. More importantly, the multiscale properties of the fibers, such as their diameter, morphology, and the internal liquid crystalline ordering of the molecules (and thus structural color), can be manipulated by several controlling parameters. Combining this cross-scale tunability with a smart functional hydrogel system results in the formation of fibers with structural coloration, self-healing, electrical conduction, and thermal-sensing abilities. We believe that this platform can be extended to other hydrogel systems and will help unlock a wide variety of real-life applications.

Ultrasound (US) has emerged as a noninvasive neurostimulation method for motor control in Parkinson's disease (PD). Previous in vivo US neuromodulation studies for PD were single-target stimulation. However, the motor symptoms of PD are linked with neural circuit dysfunction, and multi-target stimulation is conducted in clinical treatment for PD. Thus, in the present study, we achieved multi-target US stimulation using holographic lens transducer based on the Rayleigh-Sommerfeld diffraction integral and time-reversal methods. We demonstrated that holographic US stimulation of the bilateral dorsal striatum (DS) could improve the motor function in 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced mouse model of PD. The holographic US wave (fundamental frequency: 3 MHz, pulse repetition frequency: 500 Hz, duty cycle: 20%, tone-burst duration: 0.4 ms, sonication duration: 1 s, interstimulus interval: 4 s, spatial-peak temporal-average intensity: 180 mw/cm²) was delivered to the bilateral DS 20 min per day for consecutive 10 d after the last injection of MPTP. Immunohistochemical c-Fos staining demonstrated that holographic US significantly increased the c-Fos-positive neurons in the bilateral DS compared with the sham group (P = 0.003). Moreover, our results suggested that holographic US stimulation of the bilateral DS ameliorated motor dysfunction (P < 0.05) and protected the dopaminergic (DA) neurons (P < 0.001). The neuroprotective effect of holographic US was associated with the prevention of axon degeneration and the reinforcement of postsynaptic densities [growth associated protein-43 (P < 0.001), phosphorylated Akt (P = 0.001), β3-tubulin (P < 0.001), phosphorylated CRMP2 (P = 0.037), postsynaptic density (P = 0.023)]. These data suggested that holographic US-induced acoustic radiation force has the potential to achieve multi-target neuromodulation and could serve as a reliable tool for the treatment of PD.

Current integration methods for single-cell RNA sequencing (scRNA-seq) data and spatial transcriptomics (ST) data are typically designed for specific tasks, such as deconvolution of cell types or spatial distribution prediction of RNA transcripts. These methods usually only offer a partial analysis of ST data, neglecting the complex relationship between spatial expression patterns underlying cell-type specificity and intercellular cross-talk. Here, we present eMCI, an explainable multimodal correlation integration model based on deep neural network framework. eMCI leverages the fusion of scRNA-seq and ST data using different spot-cell correlations to integrate multiple synthetic analysis tasks of ST data at cellular level. First, eMCI can achieve better or comparable accuracy in cell-type classification and deconvolution according to wide evaluations and comparisons with state-of-the-art methods on both simulated and real ST datasets. Second, eMCI can identify key components across spatial domains responsible for different cell types and elucidate the spatial expression patterns underlying cell-type specificity and intercellular communication, by employing an attribution algorithm to dissect the visual input. Especially, eMCI has been applied to 3 cross-species datasets, including zebrafish melanomas, soybean nodule maturation, and human embryonic lung, which accurately and efficiently estimate per-spot cell composition and infer proximal and distal cellular interactions within the spatial and temporal context. In summary, eMCI serves as an integrative analytical framework to better resolve the spatial transcriptome based on existing single-cell datasets and elucidate proximal and distal intercellular signal transduction mechanisms over spatial domains without requirement of biological prior reference. This approach is expected to facilitate the discovery of spatial expression patterns of potential biomolecules with cell type and cell-cell communication specificity.

While the expression of programmed death ligand-1 (PD-L1) is associated with response to immune therapy, PD-L1-negative patients may still benefit from immune treatment. Programmed death ligand-2 (PD-L2), another crucial immune checkpoint molecule interacting with PD-1, correlates with the efficacy of various tumor immune therapies. This study investigates the expression of PD-L2 in non-small cell lung cancer (NSCLC) patients following anti-PD-1 therapy and its predictive value for clinical survival outcomes. Additionally, we explore the noninvasive, real-time, and dynamic quantitative analysis potential of PD-L2 positron emission tomography (PET) imaging in transplanted tumors. We utilized [⁶⁸Ga]Ga-labeled peptide HN11-1 for PD-L2 PET imaging. The results indicate a higher response rate to anti-PD-1 therapy in patients positive for both PD-L1 and PD-L2, with PD-L2 status independently predicting progression-free survival (PFS) with pembrolizumab treatment. Furthermore, [⁶⁸Ga]Ga-HN11-1 PET imaging demonstrates specificity in assessing PD-L2 status. Overall, we confirm the correlation between high PD-L2 expression and favorable PFS in NSCLC patients post anti-PD-1 therapy and highlight the promising potential of [⁶⁸Ga]Ga-HN11-1 as a specific tracer for PD-L2 in preclinical and initial human trials.

While a hippocampal-cortical dialogue is generally thought to mediate memory consolidation, which is crucial for engram function, how it works remains largely unknown. Here, we examined the interplay of neural signals from the retrosplenial cortex (RSC), a neocortical region, and from the hippocampus in memory consolidation by simultaneously recording sharp-wave ripples (SWRs) of dorsal hippocampal CA1 and neural signals of RSC in free-moving mice during the delayed spatial alternation task (DSAT) and subsequent sleep. Hippocampal-RSC coordination during SWRs was identified in nonrapid eye movement (NREM) sleep, reflecting neural reactivation of decision-making in the task, as shown by a peak reactivation strength within SWRs. Using modified generalized linear models (GLMs), we traced information flow through the RSC-CA1-RSC circuit around SWRs during sleep following DSAT. Our findings show that after spatial training, RSC excitatory neurons typically increase CA1 activity prior to hippocampal SWRs, potentially initiating hippocampal memory replay, while inhibitory neurons are activated by hippocampal outputs in post-SWRs. We further identified certain excitatory neurons in the RSC that encoded spatial information related to the DSAT. These neurons, classified as splitters and location-related cells, showed varied responses to hippocampal SWRs. Overall, our study highlights the complex dynamics between the RSC and hippocampal CA1 region during SWRs in NREM sleep, underscoring their critical interplay in spatial memory consolidation.

Accurate visualization and 3-dimensional (3D) morphological profiling of small model organisms can provide quantitative phenotypes benefiting genetic analysis and modeling of human diseases in tractable organisms. However, in the highly studied nematode Caenorhabditis elegans, accurate morphological phenotyping remains challenging because of notable decrease in image resolution of distant signal under high magnification and complexity in the 3D reconstruction of microscale samples with irregular shapes. Here, we develop a robust robotic system that enables the contactless, stable, and uniform rotation of C. elegans for multi-view fluorescent imaging and 3D morphological phenotyping via the precise reconstruction of 3D models. Contactless animal rotation accommodates a variety of body shapes and sizes found at different developmental stages and in mutant strains. Through controlled rotation, high-resolution fluorescent imaging of C. elegans structures is obtained by overcoming the limitations inherent in both widefield and confocal microscopy. Combining our robotic system with machine learning, we create, for the first time, precise 3D reconstructions of C. elegans at the embryonic and adult stages, enabling 3D morphological phenotyping of mutant strains in an accurate and comprehensive fashion. Intriguingly, our morphological phenotyping discovered a genetic interaction between 2 RNA binding proteins (UNC-75/CELF and MBL-1/MBNL), which are highly conserved between C. elegans and humans and implicated in neurological and muscular disorders. Our system can thus generate quantitative morphological readouts facilitating the investigation of genetic variations and disease mechanisms. More broadly, our method will also be amenable for 3D phenotypic analysis of other biological samples, like zebrafish and Drosophila larvae.

Improving the adsorption efficiency of porous adsorbent materials for organic liquids with high viscosity is crucial for addressing oil spill incidents. In this study, a high-performance aerogel adsorbent composed of polyimide (PI), hydroxyapatite nanowires (HAPnws), and reduced graphene oxide (rGO) has been fabricated, which leverages reduced flow tortuosity through anisotropic structures and solar-assisted viscosity reduction via photothermal materials. The prepared anisotropic PI/HAP/rGO aerogel, with directional channels, shows unique mechanical properties with high stiffness along the axial direction and compressibility along the radial direction. PI/HAP/rGO, featuring vertically aligned channels, demonstrated superior adsorption efficiency (the adsorption coefficient K _s reached 0.37 kg m^-1 s^-1/2 for an engine oil with a viscosity of ~144 mPa·s) for oil of varying viscosities compared to similar aerogels with uniform pores, because of the substantially reduced flow tortuosity. The photothermal properties of rGO further enhance the adsorption speed of PI/HAP/rGO for viscous oil under sunlight, including crude oil with ultrahigh viscosity. In addition, PI/HAP/rGO exhibits excellent fire resistance, allowing for reusability via both adsorption-compression and adsorption-combustion cycles. The robust and compressible PI/HAP/rGO aerogels with high adsorption efficiency for viscous oil and fire resistance represent an ideal solution for practical oil spill treatment, and this approach also offers inspiration for the development of advanced adsorbent materials.