Licarin-B Exhibits Activity Against the Toxoplasma gondii RH Strain by Damaging Mitochondria and Activating Autophagy

Toxoplasma gondii is an obligate intracellular pathogen that infects warm-blooded animals and humans. However, side effects limit toxoplasmosis treatment, and new drugs with high efficiency and low toxicity need to be developed. Natural products found in plants have become a useful source of drugs for toxoplasmosis. In this study, twenty natural compounds were screened for anti-T. gondii activity by Giemsa staining or real-time fluorescence quantitative polymerase chain reaction (qPCR) in vitro. Among these, licarin-B from nutmeg exhibited excellent anti-T. gondii activity, inhibiting T. gondii invasion and proliferation in a dose-dependent manner, with an EC50 of 14.05 ± 3.96 μg/mL. In the in vivo, licarin-B treatment significantly reduced the parasite burden in tissues compared to no treatment, protected the 90% infected mice from to death at 50 mg/kg.bw. Flow cytometry analysis suggested a significant reduction in T. gondii survival after licarin-B treatment. Ultrastructural changes in T. gondii were observed by transmission electron microscopy (TEM), as licarin-B induced mitochondrial swelling and formation of cytoplasmic vacuoles, an autophagosome-like double-membrane structure and extensive clefts around the T. gondii nucleus. Furthermore, MitoTracker Red CMXRos, MDC, and DAPI staining showed that licarin-B promoted mitochondrial damage, autophagosome formation, and nuclear disintegration, which were consistent with the TEM observations. Together, these findings indicate that licarin-B is a promising anti-T. gondii agent that potentially functions by damaging mitochondria and activating autophagy, leading to T. gondii death

GastroBot: a Chinese gastrointestinal disease chatbot based on the retrieval-augmented generation

IntroductionLarge Language Models (LLMs) play a crucial role in clinical information processing, showcasing robust generalization across diverse language tasks. However, existing LLMs, despite their significance, lack optimization for clinical applications, presenting challenges in terms of illusions and interpretability. The Retrieval-Augmented Generation (RAG) model addresses these issues by providing sources for answer generation, thereby reducing errors. This study explores the application of RAG technology in clinical gastroenterology to enhance knowledge generation on gastrointestinal diseases.MethodsWe fine-tuned the embedding model using a corpus consisting of 25 guidelines on gastrointestinal diseases. The fine-tuned model exhibited an 18% improvement in hit rate compared to its base model, gte-base-zh. Moreover, it outperformed OpenAI’s Embedding model by 20%. Employing the RAG framework with the llama-index, we developed a Chinese gastroenterology chatbot named “GastroBot,” which significantly improves answer accuracy and contextual relevance, minimizing errors and the risk of disseminating misleading information.ResultsWhen evaluating GastroBot using the RAGAS framework, we observed a context recall rate of 95%. The faithfulness to the source, stands at 93.73%. The relevance of answers exhibits a strong correlation, reaching 92.28%. These findings highlight the effectiveness of GastroBot in providing accurate and contextually relevant information about gastrointestinal diseases. During manual assessment of GastroBot, in comparison with other models, our GastroBot model delivers a substantial amount of valuable knowledge while ensuring the completeness and consistency of the results.DiscussionResearch findings suggest that incorporating the RAG method into clinical gastroenterology can enhance the accuracy and reliability of large language models. Serving as a practical implementation of this method, GastroBot has demonstrated significant enhancements in contextual comprehension and response quality. Continued exploration and refinement of the model are poised to drive forward clinical information processing and decision support in the gastroenterology field

The SAR Payload Design and Performance for the GF-3 Mission

This paper describes the C-band multi-polarization Synthetic Aperture Radar (SAR) sensor for the Gaofen-3 (GF-3) mission. Based on the requirement analysis, the design of working modes and SAR payload are given. An accurate antenna model is introduced for the pattern optimization and SAR performance calculation. The paper concludes with an overview of predicted performance which was verified by in-orbit tests

A Novel Phase Compensation Method for Urban 3D Reconstruction Using SAR Tomography

Synthetic aperture radar (SAR) tomography (TomoSAR) has been widely used in the three-dimensional (3D) reconstruction of urban areas using the multi-baseline (MB) SAR data. For urban scenarios, the MB SAR data are often acquired by repeat-pass using the spaceborne SAR system. Such a data stack generally has long time baselines, which result in different atmospheric disturbances of the data acquired by different tracks. These factors can lead to the presence of phase errors (PEs). PEs are multiplicative noise for observation data, which can cause diffusion and defocus in TomoSAR imaging and seriously affect the extraction of target 3D information. In this paper, we combine the methods of the block-building network (BBN) and phase gradient autofocus (PGA) to propose a novel phase compensation method called BBN-PGA. The BBN-PGA method can effectively and efficiently compensate for PEs of the MB SAR data over a wide area and improve the accuracy of 3D reconstruction of urban areas. The applicability of this proposed BBN-PGA method is proved by using simulated data and the spaceborne MB SAR data acquired by the TerraSAR-X satellite over an area in Barcelona, Spain

A Novel Phase Compensation Method for Urban 3D Reconstruction Using SAR Tomography

Synthetic aperture radar (SAR) tomography (TomoSAR) has been widely used in the three-dimensional (3D) reconstruction of urban areas using the multi-baseline (MB) SAR data. For urban scenarios, the MB SAR data are often acquired by repeat-pass using the spaceborne SAR system. Such a data stack generally has long time baselines, which result in different atmospheric disturbances of the data acquired by different tracks. These factors can lead to the presence of phase errors (PEs). PEs are multiplicative noise for observation data, which can cause diffusion and defocus in TomoSAR imaging and seriously affect the extraction of target 3D information. In this paper, we combine the methods of the block-building network (BBN) and phase gradient autofocus (PGA) to propose a novel phase compensation method called BBN-PGA. The BBN-PGA method can effectively and efficiently compensate for PEs of the MB SAR data over a wide area and improve the accuracy of 3D reconstruction of urban areas. The applicability of this proposed BBN-PGA method is proved by using simulated data and the spaceborne MB SAR data acquired by the TerraSAR-X satellite over an area in Barcelona, Spain

The SAR Payload Design and Performance for the GF-3 Mission

This paper describes the C-band multi-polarization Synthetic Aperture Radar (SAR) sensor for the Gaofen-3 (GF-3) mission. Based on the requirement analysis, the design of working modes and SAR payload are given. An accurate antenna model is introduced for the pattern optimization and SAR performance calculation. The paper concludes with an overview of predicted performance which was verified by in-orbit tests

Error Source Analysis and Correction of GF-3 Polarimetric Data

The GaoFen-3 (GF-3) satellite is the first polarimetric synthetic aperture radar (PolSAR) satellite in China. With a designed in-orbit life of 8 years, it will provide large amounts of PolSAR data for ocean monitoring, disaster reduction, and many other applications. The polarimetric data quality is essential for all these applications, so the analysis and calibration of the polarimetric error sources are very important for GF-3. In this study, we established a full-link error model for GF-3 PolSAR system. Based on this model, we comprehensively analyzed the quantitative effects of the main error sources including the composition, figured out characteristics of the phase imbalance introduced by the antenna, and pointed out the error sources which have to be corrected. Furthermore, the polarimetric correction method for GF-3 PolSAR system is proposed. Finally, assisted by several external calibration experiments, polarimetric errors of GF-3 data are efficiently corrected during in-orbit-test phase

The influence of power-take-off control on the dynamic response and power output of combined semi-submersible floating wind turbine and point-absorber wave energy converters

Floating offshore wind turbines (FOWTs) have received extensive attention in recent years, particularly after the successful demonstration of several pilot projects, such as Hywind and WindFloat. Integrating wave energy converters (WECs) into FOWTs could potentially help reduce cost of energy by absorbing additional power from waves and introduce restoring moments and extra damping to the floating platform thus reducing motion responses and fatigue loads. In this work, we propose a hybrid floating wind and wave power generation platform, consisting of a semi-submersible FOWT and three point-absorber WECs. Preliminary feasibility study of this concept is performed with verified integrated aero-hydro-servo-mooring numerical simulations. Dynamic response and power output of this hybrid concept are evaluated under several typical environmental conditions. Particularly, different WEC power-take-off control strategies have been comparatively studied, which have shown considerable influences on the platform dynamics and power generation. More specifically, reactive control generally worsen the platform motion responses, while spring–damping control is able to mitigate the pitch motion to certain extent. Regarding power output, reactive control leads to the highest wave power generation, almost twice as much as that of spring–damping, which has been used in most existing works on hybrid power generation system. Moreover, it is found the optimal control design for point-absorber WEC attached to fixed structures is no longer optimal for the combined floating wind and wave energy production platform, which needs further investigations in the future

A High-Resolution SAR Focusing Experiment Based on GF-3 Staring Data

Spotlight synthetic aperture radar (SAR) is a proven technique, which can provide high-resolution images as compared to those produced by traditional stripmap SAR. This paper addresses a high-resolution SAR focusing experiment based on Gaofen-3 satellite (GF-3) staring data with about 55 cm azimuth resolution and 240 MHz range bandwidth. In staring spotlight (ST) mode, the antenna always illuminates the same scene on the ground, which can extend the synthetic aperture. Based on a two-step processing algorithm, some special aspects such as curved-orbit model error correction, stop-and-go correction, and antenna pattern demodulation must be considered in image focusing. We provide detailed descriptions of all these aspects and put forward corresponding solutions. Using these suggested methods directly in an imaging module without any modification for other data processing software can make the most of the existing ground data processor. Finally, actual data acquired in GF-3 ST mode is used to validate these methodologies, and a well-focused, high-resolution image is obtained as a result of this focusing experiment