Hardware-algorithm collaborative computing with photonic spiking neuron chip based on integrated Fabry-P\'erot laser with saturable absorber

Photonic neuromorphic computing has emerged as a promising avenue toward building a low-latency and energy-efficient non-von-Neuman computing system. Photonic spiking neural network (PSNN) exploits brain-like spatiotemporal processing to realize high-performance neuromorphic computing. However, the nonlinear computation of PSNN remains a significant challenging. Here, we proposed and fabricated a photonic spiking neuron chip based on an integrated Fabry-P\'erot laser with a saturable absorber (FP-SA) for the first time. The nonlinear neuron-like dynamics including temporal integration, threshold and spike generation, refractory period, and cascadability were experimentally demonstrated, which offers an indispensable fundamental building block to construct the PSNN hardware. Furthermore, we proposed time-multiplexed spike encoding to realize functional PSNN far beyond the hardware integration scale limit. PSNNs with single/cascaded photonic spiking neurons were experimentally demonstrated to realize hardware-algorithm collaborative computing, showing capability in performing classification tasks with supervised learning algorithm, which paves the way for multi-layer PSNN for solving complex tasks.Comment: 10 pages, 8 figure

Integrated single-cell and bulk RNA-sequencing data reveal prognosis and therapeutic response in low-grade glioma based on hypoxia-lactylation related genes

Abstract Background The prognosis of low-grade glioma (LGG) exhibits significant heterogeneity, and the optimal management strategy remains controversial. Therefore, identifying biomarkers associated with glioma prognosis is necessary. Methods Hub genes were identified and a prognostic risk signature was constructed in the TCGA cohort using LASSO Cox regression. The predictive significance of this model was assessed and confirmed in the independent CGGA cohort. Single-cell transcriptional profiling characterized the hub gene expression patterns across cell types. Results We screened four hub genes (SERPINE1, KIF2C, SLC16A1, FABP5). Patients were stratified into high- and low-risk groups using this model. The high-risk group had significantly lower survival rates in both TCGA and CGGA cohorts. The model demonstrated strong predictive power (1/2/3-year AUCs: 0.85/0.85/0.83 in TCGA; 0.73/0.71 for 2/3 years in CGGA). Functionally, the high-risk group exhibited activation of pro-tumorigenic pathways, showed higher levels of immune infiltration across multiple lymphocyte and myeloid subsets, and demonstrated higher sensitivity to drugs such as AZD5582 and AZD8055, evidenced by significantly lower IC50 values. At the single-cell level, FABP5 was highly expressed in myeloid cells, and FABP5 + tumor-associated macrophages (TAMs) were enriched in lipid metabolism and antigen presentation pathways. Pseudotime analysis suggested increasing FABP5 expression during TAMs differentiation. Conclusions The constructed 4-gene hypoxia-lactylation prognostic model can effectively predict survival risk in LGG patients. The high-risk group is characterized by activation of pro-tumorigenic pathways, high immune infiltration, and sensitivity to specific targeted drugs. FABP5 + TAMs participate in LGG progression by regulating lipid metabolism and inflammatory responses, representing a potential therapeutic target

Tunable superluminal propagation at spectral hole-burning regions in magneto-optical atomic medium

In the context of spectral hole-burning, normal dispersion with subluminal propagation is usually observed in the spectral hole-burning depth region. However, anomalous dispersion can occur in the continuous absorption peak region, which leads to superluminal light propagation. In this paper, we report an unusual behavior of dispersion at discontinued absorption kink regions. We demonstrate both normal dispersion at the kink absorption region and anomalous dispersion at the spectral hole-burning depth region. The unusual dispersion leads to a positive group index in the absorption kink region and a negative group index in the spectral hole-burning depth region. The spectral hole-burning is due to variation of magnetization rather than the molecular distribution. The outcomes of our work offer promising applications in communication technologies and storage devices

Adaptive polarization photoacoustic computed tomography for biological anisotropic tissue imaging

Most photoacoustic computed tomography (PACT) systems usually ignore the anisotropy of the tissue absorption coefficient, which will lead to the lack of information in reconstructed images. In this work, the effect is addressed of the possible optical absorption anisotropy of tissue on PACT images. The functional relationship is derived between the photoacoustic response and the polarization angle of the excitation light. An adaptive polarized light photoacoustic imaging (AP-PACT) approach is proposed and shown to make up for the lack of imaging information and achieve optimal image contrast when imaging samples with anisotropic optical absorption, by utilizing the standard deviation of photoacoustic response as the feedback signal in an adaptive data acquisition process. The method is implemented both on phantom and in vitro experiments, which show that AP-PACT can recover anisotropic absorption-related information from reconstructed images and thus significantly improve their quality