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Electrocardiograph signals reflect the current state of the heart and have great significance to the clinical diagnosis of the heart. Convolutional neural networks perform excellently in electrocardiograph pattern recognition. However, CNNs processing ECG signals need to convert them from 1D to 2D, leading to additional circuit and time costs in hardware. Here, a convolution organic transistor (COT) is proposed for monitoring the ECG with CNNs. Based on the surface electric field effect and trap effect, COT can directly process 1D ECG data without complex preprocessing. It can complete the convolution calculation of ECG signals ≈20 000 times per second in theory and reduce the number of devices by 83% compared to conventional arrays. Further, actual ECG signals are measured and input into the COT, which can initially recognize the type of ECG abnormality. Finally, a point calculation detection system is established with 96.2% recognition accuracy in the five‐heartbeat classification task by combining the 1D CNN. [ABSTRACT FROM AUTHOR]

Backgroud: Type II congenital pulmonary airway malformation (CPAM) is a rare pulmonary microcystic developmental malformation. Surgical excision is the primary treatment for CPAM, although maternal steroids and betamethasone have proven effective in reducing microcystic CPAM. Disturbed intercellular communication may contribute to the development of CPAM. This study aims to investigate the expression profile and analyze intercellular communication networks to identify genes potentially associated with type II CPAM pathogenesis and therapeutic targets. Methods: RNA sequencing (RNA-seq) was performed on samples extracted from both the cystic area and the adjacent normal tissue post-surgery in CPAM patients. Iterative weighted gene correlation network analysis (iWGCNA) was used to identify genes specifically expressed in type II CPAM. Single-cell RNA-seq (scRNA-seq) was integrated to unveil the heterogeneity in cell populations and analyze the communication and interaction within epithelial cell sub-populations. Results: A total of 2,618 differentially expressed genes were identified, primarily enriched in cilium-related biological process and inflammatory response process. Key genes such as EDN1, GPR17, FPR2, and CHRM1, involved in the G protein-coupled receptor (GPCR) signaling pathway and playing roles in cell differentiation, apoptosis, calcium homeostasis, and the immune response, were highlighted based on the protein-protein interaction network. Type II CPAM-associated modules, including ciliary function-related genes, were identified using iWGCNA. By integrating scRNA-seq data, AGR3 (related to calcium homeostasis) and SLC11A1 (immune related) were identified as the only two differently expressed genes in epithelial cells of CPAM. Cell communication analysis revealed that alveolar type 1 (AT1) and alveolar type 2 (AT2) cells were the predominant communication cells for outgoing and incoming signals in epithelial cells. The ligands and receptors between epithelial cell subtypes included COLLAGEN genes enriched in PI3K-AKT singaling and involved in epithelial to mesenchymal transition. Conclusions: In summary, by integrating bulk RNA-seq data of type II CPAM with scRNA-seq data, the gene expression profile and critical signaling pathways such as GPCR signaling and PI3K-AKT signaling pathways were revealed. Abnormally expressed genes in these pathways may disrupt epithelial-mesenchymal transition and contribute to the development of CPAM. Given the effectiveness of prenatal treatments of microcystic CPAM using maternal steroids and maternal betamethasone administration, targeting the genes and signaling pathways involved in the development of CPAM presents a promising therapeutic strategy. [ABSTRACT FROM AUTHOR]

Bone is one of the most frequent sites for metastasis in breast cancer patients. Bone metastasis significantly reduces the survival time and the life quality of breast cancer patients. Germacrone (GM) can serve humans as an anti‐cancer and anti‐inflammation agent, but its effect on breast cancer‐induced osteolysis remains unclear. This study aims to investigate the functions and mechanisms of GM in alleviating breast cancer‐induced osteolysis. The effects of GM on osteoclast differentiation, bone resorption, F‐actin ring formation, and gene expression were examined in vitro. RNA‐sequencing and Western Blot were conducted to explore the regulatory mechanisms of GM on osteoclastogenesis. The effects of GM on breast cancer‐induced osteoclastogenesis, and breast cancer cell malignant behaviors were also evaluated. The in vivo efficacy of GM in the ovariectomy model and breast cancer bone metastasis model with micro‐CT and histomorphometry. GM inhibited osteoclastogenesis, bone resorption and F‐actin ring formation in vitro. Meanwhile, GM inhibited the expression of osteoclast‐related genes. RNA‐seq analysis and Western Blot confirmed that GM inhibited osteoclastogenesis via inhibition of MAPK/NF‐κB signaling pathways. The in vivo mouse osteoporosis model further confirmed that GM inhibited osteolysis. In addition, GM suppressed the capability of proliferation, migration, and invasion and promoted the apoptosis of MDA‐MB‐231 cells. Furthermore, GM could inhibit MDA‐MB‐231 cell‐induced osteoclastogenesis in vitro and alleviate breast cancer‐associated osteolysis in vivo human MDA‐MB‐231 breast cancer bone metastasis‐bearing mouse models. Our findings identify that GM can be a promising therapeutic agent for patients with breast cancer osteolytic bone metastasis. [ABSTRACT FROM AUTHOR]

Organic photoelectric neuromorphic devices that mimic the brain are widely explored for advanced perceptual computing. However, current individual neuromorphic synaptic devices mainly focus on utilizing linear models to process optoelectronic signals, which means that there is a lack of effective response to nonlinear structural information from the real world, severely limiting the computational efficiency and adaptability of networks to static and dynamic information. Here, a feedforward photoadaptive organic neuromorphic transistor with mixed‐weight plasticity is reported. By introducing the potential of the space charge to couple gate potential, photoexcitation, and photoinhibition occur successively in the channel under the interference of constant light intensity, which enables the device to transform from a linear model to a nonlinear model. As a result, the device exhibits a dynamic range of over 100 dB, exceeding the currently reported similar neuromorphic synaptic devices. Further, the device achieves adaptive tone mapping within 5 s for static information and achieves over 90% robustness recognition accuracy for dynamic information. Therefore, this work provides a new strategy for developing advanced neuromorphic devices and has great potential in the fields of intelligent driving and brain‐like computing. [ABSTRACT FROM AUTHOR]