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BACKGROUND: The alkaloid camptothecin analog SN38 is a potent antineoplastic agent, but cannot be used directly for clinical application due to its poor water solubility. Currently, the prodrug approach on SN38 has resulted in 3 FDA-approved cancer therapeutics, irinotecan, ONIVYDE, and Trodelvy. However, only 2-8% of irinotecan can be transformed enzymatically in vivo into the active metabolite SN38, which severely limits the drugs efficacy. While numerous drug delivery systems have been attempted to achieve effective SN38 delivery, none have produced drug products with antitumor efficacy better than irinotecan in clinical trials. Therefore, novel approaches are urgently needed for effectively delivering SN38 to cancer cells with better efficacy and lower toxicity. METHODS: Based on the unique properties of human serum albumin (HSA), we have developed a novel single protein encapsulation (SPE) technology to formulate cancer therapeutics for improving their pharmacokinetics (PK) and antitumor efficacy and reducing their side effects. Previous application of SPE technology to doxorubicin (DOX) formulation has led to a promising drug candidate SPEDOX-6 (FDA IND #, 152154), which will undergo a human phase I clinical trial. Using the same SPE platform on SN38, we have now produced two SPESN38 complexes, SPESN38-5 and SPESN38-8. We conducted their pharmacological evaluations with respect to maximum tolerated dose, PK, and in vivo efficacy against colorectal cancer (CRC) and soft tissue sarcoma (STS) in mouse models. RESULTS: The lyophilized SPESN38 complexes can dissolve in aqueous media to form clear and stable solutions. Maximum tolerated dose (MTD) of SPESN38-5 is 250 mg/kg by oral route (PO) and 55 mg/kg by intravenous route (IV) in CD-1 mice. SPESN38-8 has the MTD of 45 mg/kg by IV in the same mouse model. PK of SPESN38-5 by PO at 250 mg/kg gave mouse plasma AUC0-∞ of 0.05 and 4.5 nmol × h/mL for SN38 and SN38 glucuronidate (SN38G), respectively, with a surprisingly high molar ratio of SN38G:SN38 = 90:1. However, PK of SPESN38-5 by IV at 55 mg/kg yielded much higher mouse plasma AUC0-∞ of 19 and 28 nmol × h/mL for SN38 and SN38G, producing a much lower molar ratio of SN38G:SN38 = 1.5:1. Antitumor efficacy of SPESN38-5 and irinotecan (control) was evaluated against HCT-116 CRC xenograft tumors. The data indicates that SPESN38-5 by IV at 55 mg/kg is more effective in suppressing HCT-116 tumor growth with lower systemic toxicity compared to irinotecan at 50 mg/kg. Additionally, SPESN38-8 and DOX (control) by IV were evaluated in the SK-LMS-1 STS mouse model. The results show that SPESN38-8 at 33 mg/kg is highly effective for inhibiting SK-LMS-1 tumor growth with low toxicity, in contrast to DOXs insensitivity to SK-LMS-1 with high toxicity. CONCLUSION: SPESN38 complexes provide a water soluble SN38 formulation. SPESN38-5 and SPESN38-8 demonstrate better PK values, lower toxicity, and superior antitumor efficacy in mouse models, compared with irinotecan and DOX.

This paper proposes a method for the intelligent detection of high-frequency surface wave radar (HFSWR) targets. This method cascades the adaptive constant false alarm (CFAR) detector variability index (VI) with the convolutional neural network (CNN) to form a cascade detector (VI)CFAR-CNN. First, the (VI)CFAR algorithm is used for the first-level detection of the range–Doppler (RD) spectrum; based on this result, the two-dimensional window slice data are extracted using the window with the position of the target on the RD spectrum as the center, and input into the CNN model to carry out further target and clutter identification. When the detection rate of the detector reaches a certain level and cannot be further improved due to the convergence of the CNN model, this paper uses a dual-detection maps fusion method to compensate for the loss of detection performance. First, the optimized parameters are used to perform the weighted fusion of the dual-detection maps, and then, the connected components in the fused detection map are further processed to achieve an independent (VI)CFAR to compensate for the (VI)CFAR-CNN detection results. Due to the difficulty in obtaining HFSWR data that include comprehensive and accurate target truth values, this paper adopts a method of embedding targets into the measured background to construct the RD spectrum dataset for HFSWR. At the same time, the proposed method is compared with various other methods to demonstrate its superiority. Additionally, a small amount of automatic identification system (AIS) and radar correlation data are used to verify the effectiveness and feasibility of this method on completely measured HFSWR data. [ABSTRACT FROM AUTHOR]

Investigating the dynamic evolution process of the ocean and ionosphere in sudden sea conditions poses a challenging problem. To address this objective, this study utilizes actual data from high-frequency surface wave radar (HFSWR) to analyze, validate, summarize, and characterize the echo properties of the ocean and ionosphere during the severe Typhoon Muifa. By employing the short-time Fourier transform (STFT) method, the HFSWR ocean and ionosphere echoes stimulated by typhoon-induced gravity waves are observed, and the joint gravity wave features of the ocean and ionosphere echoes at different time scales are extracted. Additionally, the phase-space reconstruction method is employed to characterize the dynamical evolution of the joint gravity wave features in higher-dimensional space. Furthermore, the chaotic dynamics behavior of the joint gravity wave features is analyzed using the largest Lyapunov exponents. By combining the gravity wave features with chaotic dynamics, this study introduces a method to characterize the joint gravity wave features. The extraction of joint gravity wave features in HFSWR echoes stimulated by typhoons, along with the construction of a chaotic characterization scheme for the gravity wave features, provides an innovative approach and a solid technical foundation for studying the ocean and ionosphere using HFSWR under sudden sea conditions. [ABSTRACT FROM AUTHOR]

The problem of accurate source localization has been an area of focus in high-frequency surface wave radar (HFSWR) applications. However, antenna pattern distortion (APD) decreases the direction-of-arrival (DOA) estimation performance of the multiple signal classification (MUSIC) algorithm. Up to now, limited studies have been conducted on the calibration of antenna pattern distortion for phased arrays in HFSWR. In this paper, we first analyze the effect of APD on the performance of the MUSIC algorithm through estimation of accuracy and angular resolution. We demonstrate that using the actual pattern (or say APD) can improve DOA estimation performance. Based on this proposition, we propose a novel iterative calibration method that employs the first-order sea clutter data and can jointly estimate DOA and APD in an iterative way. To obtain available calibration points, we introduce the extraction methods of the first-order sea clutter spectrum and single-DOA spectrum points. Meanwhile, in each iteration, the Beamspace MUSIC algorithm and artificial hummingbird algorithm (AHA) are utilized to estimate the DOA and APD, respectively. Numerical results reveal a good coincidence between the actual pattern and the estimated APD. We also apply this method to process the experimental data of HFSWR. We obtain the APD vector of the real phased array and improve the direction-finding performance of several real ship targets using this vector. Both numerical and experimental results prove the correctness of our proposed calibration method. [ABSTRACT FROM AUTHOR]

The gravity wave produced by typhoons has been an essential subject of study that concerns numerous researchers. The damage to human beings and infrastructure in coastal regions caused by typhoon disasters annually is very severe, and analyzing gravity wave variation is a reliable approach to research typhoons. High-frequency surface wave radar (HFSWR) as an over-the-horizon radar can achieve real-time monitoring of an extensive sea area and space. This paper derived the gravity wave perturbation spectrum by handling high-frequency surface wave radar data during typhoons. The gravity wave spectrum data were examined by applying the chaos examination approaches of the Lyapunov exponent and phase-space reconstruction to the gravity wave spectrum data after processing and extraction. The reconstructed phase space had a specific shape in a certain direction, with the maximum Lyapunov exponent greater than zero. The gravity wave spectrum data are suggested to have chaotic properties through two chaos examination approaches. This paper demonstrated that the gravity waves observed by a radar have chaotic properties through the measurement data of HFSWR. While the chaotic properties suggest that observed gravity wave data are predictable in the short term, they are unpredictable in the long term. Predicting gravity wave data is important for understanding the chaotic properties of the atmosphere and for future gravity wave prediction. [ABSTRACT FROM AUTHOR]

In radar array signal processing, weak nonstationary polarization signal direction of arrival (DOA) estimation is a challenging and significant issue when both strong and weak nonstationary signals coexist. Time-frequency (T-F) analysis is an effective method to deal with nonstationary signals. In the last decade, spatial time-frequency distributions (STFDs) have been proposed for multiple dual-polarization antenna arrays and efficaciously used for nonstationary signal DOA estimation. In this article, we introduced a novelty means for estimating weak nonstationary polarization signal DOA by utilizing spatial polarimetric time-frequency distributions (SPTFDs) of cross terms when there are strong nonstationary polarization interference signals and additive Gaussian white noise. The cross terms' SPTFDs are considered via a replaceability matrix for data covariance in multiple signal classification (MUSIC) and the estimation of signal parameters using the rotational invariance technique (ESPRIT). Combining the STFDs of cross terms with polarization information about weak nonstationary signals improves signal DOA estimation accuracy. The combined MUSIC and ESPRIT are used in the algorithm to further ensure the success probability and accuracy of DOA estimation. Through simulation analyses, the proposed algorithm is more suitable for the required application scenarios than other algorithms and is superior to other algorithms. [ABSTRACT FROM AUTHOR]