A Network Model for Detecting Marine Floating Weak Targets Based on Multimodal Data Fusion of Radar Echoes.

Due to the interaction between floating weak targets and sea clutter in complex marine environments, it is necessary to distinguish targets and sea clutter from different dimensions by designing universal deep learning models. Therefore, in this paper, we introduce the concept of multimodal data fusion from the field of artificial intelligence (AI) to the marine target detection task. Using deep learning methods, a target detection network model based on the multimodal data fusion of radar echoes is proposed. In the paper, according to the characteristics of different modalities data, the temporal LeNet (T-LeNet) network module and time-frequency feature extraction network module are constructed to extract the time domain features, frequency domain features, and time-frequency features from radar sea surface echo signals. To avoid the impact of redundant features between different modalities data on detection performance, a Self-Attention mechanism is introduced to fuse and optimize the features of different dimensions. The experimental results based on the publicly available IPIX radar and CSIR datasets show that the multimodal data fusion of radar echoes can effectively improve the detection performance of marine floating weak targets. The proposed model has a target detection probability of 0.97 when the false alarm probability is 10-3 under the lower signal-to-clutter ratio (SCR) sea state. Compared with the feature-based detector and the detection model based on single-modality data, the new model proposed by us has stronger detection performance and universality under various marine detection environments. Moreover, the transfer learning method is used to train the new model in this paper, which effectively reduces the model training time. This provides the possibility of applying deep learning methods to real-time target detection at sea.

Enhanced photodynamic therapy through multienzyme-like MOF for cancer treatment.

Overcoming resistance to apoptosis is a major challenge in cancer therapy. Recent research has shown that manipulating mitochondria, the organelles critical for energy metabolism in tumor cells, can increase the effectiveness of photodynamic therapy and trigger apoptosis in tumor cells. However, there is currently insufficient research and effective methods to exploit mitochondrial damage to induce apoptosis in tumor cells and improve the effectiveness of photodynamic therapy. In this study, we present a novel nanomedicine delivery and therapeutic system called PyroFPSH, which utilizes a nanozymes-modified metal-organic framework as a carrier. PyroFPSH exhibits remarkable multienzyme-like activities, including glutathione peroxidase (GPx) and catalase (CAT) mimicry, allowing it to overcome apoptosis resistance, reduce endogenous glutathione levels, and continuously generate reactive oxygen species (ROS). In addition, PyroFPSH can serve as a carrier for the targeted delivery of sulfasalazine, a drug that can induce mitochondrial depolarization in tumor cells, thereby reducing oxygen consumption and energy supply in the mitochondria of tumor cells and weakening resistance to other synergistic treatment approaches. Our experimental results highlight the potential of PyroFPSH as a versatile nanoplatform in cancer treatment. This study expands the biomedical applications of nanomaterials as platforms and enables the integration of various novel therapeutic strategies to synergistically improve tumor therapy. It deepens our understanding of multienzyme-mimicking active nanocarriers and mitochondrial damage through photodynamic therapy. Future research can further explore the potential of PyroFPSH in clinical cancer treatment and improve its drug loading capacity, biocompatibility and targeting specificity. In summary, PyroFPSH represents a promising therapeutic approach that can provide new insights and possibilities for cancer treatment.

Persistent Regulation of Tumor Hypoxia Microenvironment via a Bioinspired Pt-Based Oxygen Nanogenerator for Multimodal Imaging-Guided Synergistic Phototherapy.

Multifunctional nanoplatforms for imaging-guided synergistic antitumor treatment are highly desirable in biomedical applications. However, anticancer treatment is largely affected by the pre-existing hypoxic tumor microenvironment (TME), which not only causes the resistance of the tumors to photodynamic therapy (PDT), but also promotes tumorigenesis and tumor progression. Here, a continuous O2 self-enriched nanoplatform is constructed for multimodal imaging-guided synergistic phototherapy based on octahedral gold nanoshells (GNSs), which are constructed by a more facile and straightforward one-step method using platinum (Pt) nanozyme-decorated metal-organic frameworks (MOF) as the inner template. The Pt-decorated MOF@GNSs (PtMGs) are further functionalized with human serum albumin-chelated gadolinium (HSA-Gd, HGd) and loaded with indocyanine green (ICG) (ICG-PtMGs@HGd) to achieve a synergistic PDT/PTT effect and fluorescence (FL)/multispectral optoacoustic tomography (MSOT)/X-ray computed tomography (CT)/magnetic resonance (MR) imaging. The Pt-decorated nanoplatform endows remarkable catalase-like behavior and facilitates the continuous decomposition of the endogenous H2O2 into O2 to enhance the PDT effect under hypoxic TME. HSA modification enhances the biocompatibility and tumor-targeting ability of the nanocomposites. This TME-responsive and O2 self-supplement nanoparticle holds great potential as a multifunctional theranostic nanoplatform for the multimodal imaging-guided synergistic phototherapy of solid tumors.