Search

Excess reactive oxygen species (ROS) produced by abnormal mitochondria is one of the critical triggers of rheumatoid arthritis (RA). Existing nanocatalytic therapies can only catalyze the breakdown of ROS but cannot address the root cause of ROS production, i.e., abnormal mitochondria. Here, we designed an ultrasound (US) piezoelectric catalytic therapy, which can induce mitophagy in a spatiotemporally controlled manner to treat RA. The prepared two-dimensional piezoelectric nanosheets (NSs) Fe/BiOCl with US catalytic activity can efficiently generate electrons under US stimulation to meet the purpose of consuming H

The microorganism has become a promising therapeutic tool for many diseases because it is a kind of cell factory that can efficiently synthesize a variety of bioactive substances. However, the metabolic destiny of microorganisms is difficult to predictiin vivo/i. Here, a timing bionic dormant body with programmable destiny is reported, which can predict the metabolic time and location of microorganismsiin vivo/iand can prevent it from being damaged by the complex biological environmentiin vivo/i. Taking the complex digestive system as an example, the bionic dormant body exists in the upper digestive tract as a nonmetabolic dormant body after oral administration and will be awakened to synthesize bioactive substances about 2 h after reaching the intestine. Compared with oral microorganisms alone, the bioavailability of the biomimetic dormant body in the intestine is almost 3.5 times higher. The utilization rate of the oral bionic dormant body to synthesize drugs is 2.28 times higher than oral drugs. We demonstrated the significant efficacies of treatment using Parkinson's disease (PD) mice by dormant body capable of timed neurotransmitter production after oral delivery. The timed bionic dormant body with programmable destiny may provide an effective technology to generate advanced microbial therapies for the treatment of various diseases.

Objective: Large volume radiological text data have been accumulated since the incorporation of electronic health record (EHR) systems in clinical practice. We aimed to determine whether deep natural language processing algorithms could aid radiologists in improving thyroid cancer diagnosis. Methods: Sonographic EHR data were obtained from the EHR database. Pathological reports were used as the gold standard for diagnosing thyroid cancer. We developed thyroid cancer diagnosis based on natural language processing (THCaDxNLP) to interpret unstructured sonographic text reports for thyroid cancer diagnosis. We used the area under the receiver operating characteristic curve (AUROC) as the primary metric to measure the performance of the THCaDxNLP. We compared the performance of thyroid ultrasound radiologists aided with THCaDxNLP vs. those without THCaDxNLP using 5 independent test sets. Results: We obtained a total number of 788,129 sonographic radiological reports. The number of thyroid sonographic data points was 132,277, 18,400 of which were thyroid cancer patients. Among the 5 test sets, the numbers of patients per set were 439, 186, 82, 343, and 171. THCaDxNLP achieved high performance in identifying thyroid cancer patients (the AUROC ranged from 0.857–0.932). Thyroid ultrasound radiologists aided with THCaDxNLP achieved significantly higher performances than those without THCaDxNLP in terms of accuracy (93.8% vs. 87.2%; one-sided t-test, adjusted P = 0.003), precision (92.5% vs. 86.0%; P = 0.018), and F1 metric (94.2% vs. 86.4%; P = 0.007). Conclusions: THCaDxNLP achieved a high AUROC for the identification of thyroid cancer, and improved the accuracy, sensitivity, and precision of thyroid ultrasound radiologists. This warrants further investigation of THCaDxNLP in prospective clinical trials.

In China's long history tea culture, Zisha ceramic, from Yixing city, Jiangsu province of China, has been widely accepted as the optimum vessel for tea brewing. Zisha ceramic has existed for a millennium, but there are seldom studies that explore the composition and structure of this traditional ceramic. In this work, Dicaoqing-Zisha, a typical Zisha, is investigated as a representative. The results reveal that the Dicaoqing clay is natural composited clay and is very rich in Fe2O3. After fired at 1180 °C, Dicaoqing-Zisha is achieved with 33.2 wt% quartz, 32.8 wt% mullite, 3.2 wt% cristobalite, 5.9 wt% hematite, and 24.9 wt% amorphous phase. The percentages of mullite and cristobalite in Dicaoqing-Zisha are close to that in porcelain and much higher than that in pottery (an ordinary earthen pot). At the same time, the amorphous phase percentage of Dicaoqing-Zisha is in between that of porcelain and pottery. Compared with porcelain and pottery, the Dicaoqing-Zisha has specific pore structure including the highest specific surface area, middle porosity (larger than porcelain, but smaller than pottery), even distribution, and two main classes of pores: one is about 0.2 μm in diameter and the other is

Hashimoto’s thyroiditis (HT) is the main cause of hypothyroidism. We develop a deep learning model called HTNet for diagnosis of HT by training on 106,513 thyroid ultrasound images from 17,934 patients and test its performance on 5051 patients from 2 datasets of static images and 1 dataset of video data. HTNet achieves an area under the receiver operating curve (AUC) of 0.905 (95% CI: 0.894 to 0.915), 0.888 (0.836–0.939) and 0.895 (0.862–0.927). HTNet exceeds radiologists’ performance on accuracy (83.2% versus 79.8%; binomial test, p p p = 0.004) and static-image (AUC, 0.914 versus 0.901; p = 0.08) testing sets, respectively. HTNet may be helpful as a tool for the management of HT.

Investigating river bars and their vegetation dynamics in response to upstream damming is important for riverine flood management and ecological assessment. However, our mechanical understanding of the damming-induced changes in river bar and vegetation, such as bar area, morphology, and leaf area index (LAI), remains limited for large river systems. Leveraging satellite images and in situ observed hydrogeomorphic data from, we improve a machine learning-based LAI inversion model to quantify variations in river bar morphology, vegetation distribution, and LAI in the Middle Yangtze River (MYR) following the operation of the Three Gorges Dam (TGD). Then we analyze the mechanisms controlling the bar and vegetation dynamics based on high-resolution river cross-sectional profiles as well as daily discharge, water levels, and sediment in both the pre- and post-TGD periods. Our results indicate that the river bar area decreased by approximately 10% from 2003 to 2020, while the vegetation area and average LAI of these bars increased by >50% and >20%, respectively. Moreover, the plant community on most river bars tended to expand from the bar tail to the bar head and from the edge to the center. The main factor driving vegetation expansion in the MYR after the TGD’s operation was the reduction in bar submergence frequency (by 55%), along with a slight bar erosion. Further analysis revealed that the standard deviation of annual discharge decreased by approximately 37%, and the frequency of vegetation-erosive flow decreased by approximately 74%. Our data highlight the potential impact of large dams downstream flow regimes and vegetation encroachement. Such findings further the understanding of the biogeomorphological impacts of large dams on the river bar vegetation and have important implications for riverine plant flux estimatin, flood management and ecological restoration in dammed river systems.

Yixing Zisha ceramics are popular traditional tea sets with a long history in China but there are seldom studies to explore their compositions and microstructures. In this work, Benshanzhu-Zisha, a typical representation of Zisha from Yixing City of China, is investigated. The XRD results demonstrate that the Benshan Zhu clay is the natural mineral compound, which contains the high hematite content. After sintering, in comparison with pottery and porcelain, Benshanzhu-Zisha has the highest hematite (11.5 wt%) and amorphous phase (71.2 wt%) and the lowest mullite (10.7 wt%). Moreover, there are many dispersed and thin pores in Benshanzhu-Zisha ranging from nanometer to micron, and there are large numbers of hematite particles in the pores. It is the unique pore structures that make Benshanzhu-Zisha be perfect brewing tea vessel, impermeable to water but breathable to gas.

N6-methyladenosine (m6A) is a common transcriptomic modification in cancer. Recently, it has been found to be involved in the regulation of non-small cell lung cancer (NSCLC) formation and metastasis. Interleukin 37 (IL-37) plays a crucial protective role in lung cancer. In our previous studies, we found that IL-37 is a potential novel tumor suppressor by inhibiting IL-6 expression to suppress STAT3 activation and decreasing epithelial-to-mesenchymal transition. Moreover, we found that treatment of IL-37 in lung cancer cells induced widespread and dynamic RNA m6A methylation. The effects of RNA m6A methylation of IL-37 treatment require further study. However, the functions of RNA m6A methylation of IL-37 treatment still await elucidation. Using MeRIP-seq and RNA-seq, we uncovered a unique m6A methylation profile in the treatment of IL-37 on the A549 cell line. We also showed the expression of m6A writers METTL3, METTL14, and WTAP and erasers ALKBH5 and FTO in A549 cells and lung cancer tissues after the treatment of IL-37. This study showed that IL-37 could lead to changes in m6A methylation level and related molecule expression level in A546 cells and may downregulate the proliferation by inhibiting Wnt5a/5b pathway in A549 cells. We conclude that IL-37 suppresses tumor growth through regulation of RNA m6A methylation in lung cancer cells.