Research progress in arthritis treatment with the active components of Herba siegesbeckiae.

Arthritis is a group of diseases characterized by joint pain, swelling, stiffness, and limited movement. Osteoarthritis, rheumatoid arthritis, and gouty arthritis are the most common types of arthritis. Arthritis severely affects the quality of life of patients and imposes a heavy financial and medical burden on their families and society at large. As a widely used traditional Chinese medicine, Herba siegesbeckiae has many pharmacological effects such as anti-inflammatory and analgesic, anti-ischemic injury, cardiovascular protection, and hypoglycemic. In addition, it has significant therapeutic effects on arthritis. The rich chemical compositions of H. siegesbeckiae primarily include diterpenoids, sesquiterpenoids, and flavonoids. As one of the main active components of H. siegesbeckiae, kirenol and quercetin play a vital role in reducing arthritis symptoms. In the present study, the research progress in arthritis treatment with the active components of H. siegesbeckiae is reviewed.

Research on Lung Ultrasound Image Classification Based on Compressed Sensing.

Pneumothorax is a common injury in disaster rescue, traffic accidents, and war trauma environments and requires early diagnosis and treatment. The commonly used X-ray, CT, and other diagnostic instruments are not suitable for rescue sites due to their large size, heavy weight, and difficulty in transportation. Ultrasound equipment is easy to carry and suitable for rescue environments. However, ultrasound images are noisy, have low resolution, and are difficult to get started, which affects the efficiency of diagnosis. This paper studies the effect of lung ultrasound image recognition and classification based on compressed sensing and BP neural network. We use ultrasound equipment to build a lung simulation model, collect five typical features of lung ultrasound images in M-mode, and build a dataset. Using compressed sensing theory, we design sparse matrix and observation matrix and perform data compression on the image data in the dataset to obtain observation values. We design a BP neural network, input the observations into the network for training, and compare it with the commonly used VGG16 network. The method proposed in this paper has higher recognition accuracy and significantly fewer parameters than VGG16, so it is suitable for use in embedded devices.

RNA Sequencing Reveals the Suitability of Cardiac Death Livers for Transplantation.

BACKGROUND: Organ transplantation is considered the best treatment for end-stage organ failure. However, the lack of available organs for transplantation and the increasing number of patients waiting for transplants are primary issues facing the transplant community. Thus, developing strategies to increase the number of donors, especially for liver transplantation, has become a priority. The use of organs acquired from donors who suffered cardiac related deaths has increased the pool of potential liver donors. However, donation after cardiac death (DCD) livers increases the risk of primary graft dysfunction. METHODS: In the current study, we conducted transcriptome sequencing using livers from a DCD rat to assess the short-term feasibility and functional efficacy of DCD livers. RNA sequencing (RNAseq) data showed that the liver transcriptome varied greatly in rat livers subjected to 15 minutes of cardiac arrest. RESULTS: The livers used in the current study had a significant loss of normal function before transplantation. Functional and network analyses consistently indicated that transcription and translation processes were inhibited after approximately 15 minutes of cardiac arrest. Moreover, the transcriptomic sequencing data provides significant insight for identifying functional genes and testing additional biological questions in DCD liver transplantation in future studies.

Magnetic resonance imaging and DWI features of orbital rhabdomyosarcoma.

PURPOSE: To describe the magnetic resonance imaging (MRI) features of orbital rhabdomyosarcoma (RMS). METHODS: Thirty-nine patients with histopathologically confirmed orbital RMS were retrospectively reviewed. All patients underwent orbital conventional MRI, including axial, sagittal, and coronal T1-weighted, T2-weighted, and postcontrast T1-weighted sequences. The location, shape, margin, and MRI signal of the 39 lesions were reviewed. DWI in 15 patients and susceptibility weighted imaging (SWI) in 2 patients were also analyzed. RESULTS: Orbital MRI was available in 39 patients and revealed a soft tissue mass in the orbital region in all cases. Of the 39 patients, the primary tumor sites were limited to the orbital proper in 31 cases, while 28 cases had extraocular muscle invasion and 8 cases had extraorbital invasion. All lesions were unilateral. Thirty-three cases were well-defined soft tissue masses and 6 cases appeared as less well-defined soft-issue masses. Thirty-four cases showed homogeneous isointense or slightly hypointense signals on T1-weighted imaging (T1WI) and hyperintense signal on T2-weighted imaging (T2WI) compared with extraocular muscles. Five cases had heterogeneous signals with focal areas of increased signal on T1WI or decreased signal on T2WI, including 1 case with hypointense signal on SWI. The mean apparent diffusion coefficient (ADC) value of the viable part of tumors was (0.925 ± 0.09) x 10(-3) mm2/s. All cases showed moderate to marked enhancement after contrast administration. CONCLUSION: Several MRI features-including homogeneous isointense or slightly hypointense signal on T1WI and slightly hyperintense signal on T2WI, relative low ADC values, and moderate to marked enhancement, extraocular muscles invasion, and extraorbital extensionare helpful in the diagnosis of orbital RMS.