Scalable optical neural networks based on temporal computing

The optical neural network (ONN) has been considered as a promising candidate for next-generation neurocomputing due to its high parallelism, low latency, and low energy consumption, with significant potential to release unprecedented computational capability. Large-scale ONNs could process more neural information and improve the prediction performance. However, previous ONN architectures based on matrix multiplication are difficult to scale up due to manufacturing limitations, resulting in limited scalability and small input data volumes. To address this challenge, we propose a compact and scalable photonic computing architecture based on temporal photoelectric multiplication and accumulate (MAC) operations, allowing direct processing of large-scale matrix computations in the time domain. By employing a temporal computing unit composed of cascaded modulators and time-integrator, we conduct a series of proof-of-principle experiments including image edge detection, optical neural networks-based recognition tasks, and sliding-window method-based multi-target detection. Thanks to its intrinsic scalability, the demonstrated photonic computing architecture could be easily integrated on a single chip toward large-scale photonic neural networks with ultrahigh computation throughputs

Additional file 1 of Identification of sulfur metabolism-related gene signature in osteoarthritis and TM9SF2’s sustenance effect on M2 macrophages' phagocytic activity

Additional file 1. Table 1. Gene lists for analysis

Table4_A novel m7G methylation–related signature associated with chromosome homeostasis in patients with lung adenocarcinoma.XLSX

Lung adenocarcinoma (LUAD) is a malignant tumor of the respiratory system with poor prognosis. Recent studies have revealed that N7-methylguanosine (m7G) methylation is a widespread modification occurring in RNA. But the expression of m7G methylation–related genes in LUAD and their correlations with prognosis are still unclear. In this study, we found 12 m7G methylation–related regulators with differential expression between LUAD and normal lung tissues. According to differentially expressed genes (DEGs), all LUAD cases were separated into two subtypes. The prognostic value of each m7G methylation–related gene for survival was evaluated to construct a multigene signature using The Cancer Genome Atlas (TCGA) cohort. Finally, an m7G methylation–related prognostic signature based on three genes was built to classify LUAD patients into two risk groups. Patients in the high-risk group showed significantly reduced overall survival (OS) when compared with patients in the low-risk group (p < 0.05). The receiver operating characteristic (ROC) curve analysis confirmed the predictive capacity of the signature. The Gene Ontology (GO) functional annotation analysis disclosed that chromosome homeostasis plays an important role in this process. The gene set enrichment analysis (ssGSEA) implied that the immune status was decreased in the high-risk group. To sum up, m7G methylation–related genes play a vital role in tumor immunity and the related signature is a reliable predictor for LUAD prognosis.</p

Table2_A novel m7G methylation–related signature associated with chromosome homeostasis in patients with lung adenocarcinoma.XLSX

Lung adenocarcinoma (LUAD) is a malignant tumor of the respiratory system with poor prognosis. Recent studies have revealed that N7-methylguanosine (m7G) methylation is a widespread modification occurring in RNA. But the expression of m7G methylation–related genes in LUAD and their correlations with prognosis are still unclear. In this study, we found 12 m7G methylation–related regulators with differential expression between LUAD and normal lung tissues. According to differentially expressed genes (DEGs), all LUAD cases were separated into two subtypes. The prognostic value of each m7G methylation–related gene for survival was evaluated to construct a multigene signature using The Cancer Genome Atlas (TCGA) cohort. Finally, an m7G methylation–related prognostic signature based on three genes was built to classify LUAD patients into two risk groups. Patients in the high-risk group showed significantly reduced overall survival (OS) when compared with patients in the low-risk group (p < 0.05). The receiver operating characteristic (ROC) curve analysis confirmed the predictive capacity of the signature. The Gene Ontology (GO) functional annotation analysis disclosed that chromosome homeostasis plays an important role in this process. The gene set enrichment analysis (ssGSEA) implied that the immune status was decreased in the high-risk group. To sum up, m7G methylation–related genes play a vital role in tumor immunity and the related signature is a reliable predictor for LUAD prognosis.</p

Table1_A novel m7G methylation–related signature associated with chromosome homeostasis in patients with lung adenocarcinoma.XLSX

Lung adenocarcinoma (LUAD) is a malignant tumor of the respiratory system with poor prognosis. Recent studies have revealed that N7-methylguanosine (m7G) methylation is a widespread modification occurring in RNA. But the expression of m7G methylation–related genes in LUAD and their correlations with prognosis are still unclear. In this study, we found 12 m7G methylation–related regulators with differential expression between LUAD and normal lung tissues. According to differentially expressed genes (DEGs), all LUAD cases were separated into two subtypes. The prognostic value of each m7G methylation–related gene for survival was evaluated to construct a multigene signature using The Cancer Genome Atlas (TCGA) cohort. Finally, an m7G methylation–related prognostic signature based on three genes was built to classify LUAD patients into two risk groups. Patients in the high-risk group showed significantly reduced overall survival (OS) when compared with patients in the low-risk group (p < 0.05). The receiver operating characteristic (ROC) curve analysis confirmed the predictive capacity of the signature. The Gene Ontology (GO) functional annotation analysis disclosed that chromosome homeostasis plays an important role in this process. The gene set enrichment analysis (ssGSEA) implied that the immune status was decreased in the high-risk group. To sum up, m7G methylation–related genes play a vital role in tumor immunity and the related signature is a reliable predictor for LUAD prognosis.</p

Table1_RETRACTED: LINC00174 Facilitates Cell Proliferation, Cell Migration and Tumor Growth of Osteosarcoma via Regulating the TGF-β/SMAD Signaling Pathway and Upregulating SSH2 Expression.XLSX

Osteosarcoma (OS), a frequent malignant tumor which mainly occurs in the bone. The roles of long noncoding RNAs (lncRNAs) have been revealed in cancers, including OS. LncRNA long intergenic non-protein coding RNA (LINC00174) has been validated as an oncogene in several cancers. However, the role of LINC00174 in OS has not been explored. In our research, loss-of-function assays were conducted to explore the function of LINC00174 in OS cells. Then, we explored the downstream pathway of LINC00174 in OS cells. Bioinformatics, RNA pull-down and RIP experiments investigated the downstream mechanism of LINC00174 in OS cells. Finally, in vivo assays clarified the effect of LINC00174 on tumorigenesis. We found that LINC00174 was upregulated in OS tissues and cells. LINC00174 knockdown repressed OS cell growth. Mechanistically, LINC00174 knockdown suppressed the TGF-β/SMAD pathway. LINC00174 interacted with miR-378a-3p, and slingshot protein phosphatase 2 (SSH2) 3′UTR was targeted by miR-378a-3p in OS cells. Rescue assays showed that SSH2 upregulation or miR-378a-3p inhibition counteracted the inhibitory effect of LINC00174 depletion in OS cell growth. Additionally, LINC00174 depletion suppressed tumor growth in mice. In conclusion, LINC00174 promotes OS cellular malignancy and tumorigenesis via the miR-378a-3p/SSH2 axis and the TGF-β/SMAD pathway, which might provide a novel insight for OS treatment.</p

Table3_A novel m7G methylation–related signature associated with chromosome homeostasis in patients with lung adenocarcinoma.XLSX

Lung adenocarcinoma (LUAD) is a malignant tumor of the respiratory system with poor prognosis. Recent studies have revealed that N7-methylguanosine (m7G) methylation is a widespread modification occurring in RNA. But the expression of m7G methylation–related genes in LUAD and their correlations with prognosis are still unclear. In this study, we found 12 m7G methylation–related regulators with differential expression between LUAD and normal lung tissues. According to differentially expressed genes (DEGs), all LUAD cases were separated into two subtypes. The prognostic value of each m7G methylation–related gene for survival was evaluated to construct a multigene signature using The Cancer Genome Atlas (TCGA) cohort. Finally, an m7G methylation–related prognostic signature based on three genes was built to classify LUAD patients into two risk groups. Patients in the high-risk group showed significantly reduced overall survival (OS) when compared with patients in the low-risk group (p < 0.05). The receiver operating characteristic (ROC) curve analysis confirmed the predictive capacity of the signature. The Gene Ontology (GO) functional annotation analysis disclosed that chromosome homeostasis plays an important role in this process. The gene set enrichment analysis (ssGSEA) implied that the immune status was decreased in the high-risk group. To sum up, m7G methylation–related genes play a vital role in tumor immunity and the related signature is a reliable predictor for LUAD prognosis.</p

Ultra-directional high-efficient chiral silicon photonic circuits

Chiral light matter interaction enables new fundamental researches and applications of light. The interaction has traditionally faced challenges in low directionality and efficiency based on spin orbit interaction of light in microscopic waveguides. It is pivotal to exploit photonic integrated circuits to efficiently engineer photonic chiral behavior. Here, we present ultra directional high efficient chiral coupling in silicon photonic circuits based on low order to high order mode conversion and interference. We show that the directionality of chiral coupling, in principle, can approach minus/plus 1 with circular polarization inputs, benefited from the underlying mechanism of complete destructive and constructive interference. The chiral coupling efficiency can exceed 70%, with negligible scattering to nonguided modes, much higher than conventional coupling mechanisms. Moreover, the chiral silicon photonic circuits can function as a perfect 3 dB power splitter for arbitrarily linear polarization inputs, and also open up the possibility of on chip chirality determination to further flourish the development of chiral optics

Inverse-designed Photonic Computing Core for Parallel Matrix-vector Multiplication

On-chip optical neural networks (ONNs) have recently emerged as an attractive hardware accelerator for deep learning applications, characterized by high computing density, low latency, and compact size. As these networks rely heavily on massive matrix multiplication, photonic computing cores for matrix computation become crucial components for on-chip ONNs, which harness the degree of freedoms (DOFs) in photonics including space, wavelength and mode dimensions. However, previous photonic computing devices have not fully utilized the orthogonality and the conversion characteristic of the waveguide modes, which as we show here, allows for the simultaneous parallel computing of several independent matrix-vector multiplications within the same device. In this work, we propose an inverse-designed photonic computing core for parallel matrix-vector multiplication. The matrices are implemented through a mode conversion process, where the input fundamental modes are simultaneously converted into several orthogonal output modes. Specifically, we target the complex-valued conversion matrices between input and output modes and inversely design the dielectric distribution within the device to achieve parallel matrix-vector multiplication. As a demonstration, the proposed photonic computing core supports simultaneous parallel computing of two independent matrix-vector multiplications, with an ultra-compact footprint and high computing precision (relative error < 8%) at 1550 nm wavelength. The inverse-designed photonic computing devices hold great potential for high-performance on-chip ONNs with low energy consumption and high computing density

WTAP regulates autophagy in colon cancer cells by inhibiting FLNA through N6-methyladenosine

Our study investigated the role of WTAP in colon cancer. We employed experiments including m6A dot blot hybridization, methylated RNA immunoprecipitation, dual-luciferase, and RNA immunoprecipitation to investigate the regulatory mechanism of WTAP. Western blot was performed to analyze the expression of WTAP, FLNA and autophagy-related proteins in cells. Our results confirmed the up-regulation of WTAP in colon cancer and its promoting effect on proliferation and inhibiting effect on apoptosis. FLNA was the downstream gene of WTAP and WTAP-regulated m6A modification led to post-transcriptional repression of FLNA. The rescue experiments showed that WTAP/FLNA could inhibit autophagy. WTAP-mediated m6A modification was confirmed to be crucial in colon cancer development, providing new insights into colon cancer therapy.</p