An Anatomy-aware Framework for Automatic Segmentation of Parotid Tumor from Multimodal MRI

Magnetic Resonance Imaging (MRI) plays an important role in diagnosing the parotid tumor, where accurate segmentation of tumors is highly desired for determining appropriate treatment plans and avoiding unnecessary surgery. However, the task remains nontrivial and challenging due to ambiguous boundaries and various sizes of the tumor, as well as the presence of a large number of anatomical structures around the parotid gland that are similar to the tumor. To overcome these problems, we propose a novel anatomy-aware framework for automatic segmentation of parotid tumors from multimodal MRI. First, a Transformer-based multimodal fusion network PT-Net is proposed in this paper. The encoder of PT-Net extracts and fuses contextual information from three modalities of MRI from coarse to fine, to obtain cross-modality and multi-scale tumor information. The decoder stacks the feature maps of different modalities and calibrates the multimodal information using the channel attention mechanism. Second, considering that the segmentation model is prone to be disturbed by similar anatomical structures and make wrong predictions, we design anatomy-aware loss. By calculating the distance between the activation regions of the prediction segmentation and the ground truth, our loss function forces the model to distinguish similar anatomical structures with the tumor and make correct predictions. Extensive experiments with MRI scans of the parotid tumor showed that our PT-Net achieved higher segmentation accuracy than existing networks. The anatomy-aware loss outperformed state-of-the-art loss functions for parotid tumor segmentation. Our framework can potentially improve the quality of preoperative diagnosis and surgery planning of parotid tumors.Comment: under revie

Segmentation of Parotid Gland Tumors Using Multimodal MRI and Contrastive Learning

Parotid gland tumor is a common type of head and neck tumor. Segmentation of the parotid glands and tumors by MR images is important for the treatment of parotid gland tumors. However, segmentation of the parotid glands is particularly challenging due to their variable shape and low contrast with surrounding structures. Recently deep learning has developed rapidly, which can handle complex problems. However, most of the current deep learning methods for processing medical images are still based on supervised learning. Compared with natural images, medical images are difficult to acquire and costly to label. Contrastive learning, as an unsupervised learning method, can more effectively utilize unlabeled medical images. In this paper, we used a Transformer-based contrastive learning method and innovatively trained the contrastive learning network with transfer learning. Then, the output model was transferred to the downstream parotid segmentation task, which improved the performance of the parotid segmentation model on the test set. The improved DSC was 89.60%, MPA was 99.36%, MIoU was 85.11%, and HD was 2.98. All four metrics showed significant improvement compared to the results of using a supervised learning model as a pre-trained model for the parotid segmentation network. In addition, we found that the improvement of the segmentation network by the contrastive learning model was mainly in the encoder part, so this paper also tried to build a contrastive learning network for the decoder part and discussed the problems encountered in the process of building

Emulating Complex Synapses Using Interlinked Proton Conductors

In terms of energy efficiency and computational speed, neuromorphic electronics based on non-volatile memory devices is expected to be one of most promising hardware candidates for future artificial intelligence (AI). However, catastrophic forgetting, networks rapidly overwriting previously learned weights when learning new tasks, remains as a pivotal hurdle in either digital or analog AI chips for unleashing the true power of brain-like computing. To address catastrophic forgetting in the context of online memory storage, a complex synapse model (the Benna-Fusi model) has been proposed recently[1], whose synaptic weight and internal variables evolve following a diffusion dynamics. In this work, by designing a proton transistor with a series of charge-diffusion-controlled storage components, we have experimentally realized the Benna-Fusi artificial complex synapse. The memory consolidation from coupled storage components is revealed by both numerical simulations and experimental observations. Different memory timescales for the complex synapse are engineered by the diffusion length of charge carriers, the capacity and number of coupled storage components. The advantage of the demonstrated complex synapse in both memory capacity and memory consolidation is revealed by neural network simulations of face familiarity detection. Our experimental realization of the complex synapse suggests a promising approach to enhance memory capacity and to enable continual learning.Comment: 6 figure

Improving the accuracy of cotton seedling emergence rate estimation by fusing UAV-based multispectral vegetation indices

Timely and accurate estimation of cotton seedling emergence rate is of great significance to cotton production. This study explored the feasibility of drone-based remote sensing in monitoring cotton seedling emergence. The visible and multispectral images of cotton seedlings with 2 - 4 leaves in 30 plots were synchronously obtained by drones. The acquired images included cotton seedlings, bare soil, mulching films, and PE drip tapes. After constructing 17 visible VIs and 14 multispectral VIs, three strategies were used to separate cotton seedlings from the images: (1) Otsu’s thresholding was performed on each vegetation index (VI); (2) Key VIs were extracted based on results of (1), and the Otsu-intersection method and three machine learning methods were used to classify cotton seedlings, bare soil, mulching films, and PE drip tapes in the images; (3) Machine learning models were constructed using all VIs and validated. Finally, the models constructed based on two modeling strategies [Otsu-intersection (OI) and machine learning (Support Vector Machine (SVM), Random Forest (RF), and K-nearest neighbor (KNN)] showed a higher accuracy. Therefore, these models were selected to estimate cotton seedling emergence rate, and the estimates were compared with the manually measured emergence rate. The results showed that multispectral VIs, especially NDVI, RVI, SAVI, EVI2, OSAVI, and MCARI, had higher crop seedling extraction accuracy than visible VIs. After fusing all VIs or key VIs extracted based on Otsu’s thresholding, the binary image purity was greatly improved. Among the fusion methods, the Key VIs-OI and All VIs-KNN methods yielded less noises and small errors, with a RMSE (root mean squared error) as low as 2.69% and a MAE (mean absolute error) as low as 2.15%. Therefore, fusing multiple VIs can increase crop image segmentation accuracy. This study provides a new method for rapidly monitoring crop seedling emergence rate in the field, which is of great significance for the development of modern agriculture

Effects of AR7 Joint Complex on arthralgia for patients with osteoarthritis: Results of a three-month study in Shanghai, China

<p>Abstract</p> <p>Background</p> <p>Osteoarthritis-induced arthralgia is a common cause of morbidity in both men and women worldwide. AR7 Joint Complex is a nutritional supplement containing various ingredients including sternum collagen II and methylsulfonylmethane. The product has been marketed in United States for over a decade, but clinical data measuring the effectiveness of this supplement in relieving arthralgia is lacking. The goal of this study was to determine the effect of AR7 Joint Complex on osteoarthritis.</p> <p>Methods</p> <p>A total of 100 patients over the age of 50 who had osteoarthritis were recruited to the double-blind study and randomly assigned into either treatment or placebo control groups. The patients in the treatment group were given AR7 Joint Complex orally, 1 capsule daily for 12 weeks, while the patients in the control group were given a placebo for the same period of time. Prior to and at the end of the study, data including Quality of Life questionnaires (SF-36), visual analog scales (1 to 100 mm), and X-rays of affected joints were collected.</p> <p>Results</p> <p>A total of 89 patients completed the study: 44 from the treatment group and 45 from the control group. No significant change in X-ray results was found in either group after the study. However, there was a significant decrease in patients complaining of arthralgia and tenderness (P < 0.01) in the treatment group and there was also a significant difference between the treatment and control groups at the end of the study. In addition, for Quality of Life data, the body pain index (BP) in the treatment group was significantly improved (P < 0.05) compared to the control group. No significant toxicity was noted in either group.</p> <p>Conclusion</p> <p>AR7 Joint Complex appears to have short-term effects in relieving pain in patients with osteoarthritis. Whether such an effect is long-lasting remains to be seen.</p

Spatial-Temporal Evolution Relationship between Water Systems and Historical Settlement Sites Based on Quantitative Analysis: A Case Study of Hankou in Wuhan, China (1635–1949)

When deciding on and creating their own settlement environment, humans’ relationships with water resources have evolved. From the earliest times when they observed water and learned about its characteristics and laws to create artificial rivers, to the gradual development and use of water resources to create water plants and pumping stations, to the management of water resources to set up customs and dams to prevent and manage water hazards.To lay the groundwork for more sustainable development of the relationship between humans and water in the city, it is important to understand and summarize this state of change. Wuhan, known as the “City of a Thousand Lakes”, is a typical case of studying the traditional relationship between Chinese people and water, and can better provide modern cities with the value of historical experience in sustainable development. Therefore, this study takes the Hankou town of Wuhan from 1635 to 1949 as the research object, uses historical maps and written materials as data sources, and creates a database of historical information based on the water system of Hankou and the sites of artificial settlements such as buildings and streets. It takes quantitative analysis and map visualization techniques of the GIS platform from the perspective of quantitative historical research. Firstly, it creates a database of historical information based on the water system of Hankou and the sites of artificial settlements such as buildings and streets. Secondly, it gives the quantitation about the human–water relationship in Hankou by applying the spatial analysis methods of buffer analysis. The study’s findings demonstrate that from 1635 to 1864 there were an increasing number of artificial settlement sites that were distributed along the water system, keeping a reasonable distance from the water; from 1684 to 1905, people constructed dikes to prevent flooding, which resulted in an increase in urban space; and from 1905 to 1949, the development of Hankou shifted toward the Hanjiang River and the Yangtze River. The procedure shows a change in the relationship between avoiding water and subsequently managing water and using water. The results of the study indicate the following: (1) Water is essential for the environment of human settlements. (2) Human activities have an impact on the structure of water systems. (3) There is a high degree of coupling between the Hankou urban water system and the sites of artificial settlements. It proves that the relationship between humans and water is very close in the process of modern urbanization in Hankou. In building a traditional habitat environment to regulate water, it is consistent with the ancient Chinese concepts of “harmony between man and nature” and “the best place to live is close to water conservancy but also avoid flood.” This paper is helpful for re-examining and establishing the harmonious relationship between humans and water to encourage sustainable urban growth and reshape the urban spatial environment with Chinese characteristics. It also provides a method based on quantitative analysis for studying the evolution history of urban settlement environments

Numerical Simulation and Field Monitoring of Blasting Vibration for Tunnel In-Situ Expansion by a Non-Cut Blast Scheme

There have been ever more in-situ tunnel extension projects due to the growing demand for transportation. The traditional blast scheme requires a large quantity of explosive and the vibration effect is hard to control. In order to reduce explosive consumption and the vibration effect, an optimized non-cut blast scheme was proposed and applied to the in-situ expansion of the Gushan Tunnel. Refined numerical simulation was adopted to compare the traditional and optimized blast schemes. The vibration attenuation within the interlaid rock mass and the vibration effect on the adjacent tunnel were studied and compared. The simulation results were validated by the field monitoring of the vibration effect on the adjacent tunnel. Both the simulation and the monitoring results showed that the vibration velocity on the adjacent tunnel’s back side was much smaller than its counterpart on the blast side, i.e., the presence of cavity reduced the blasting vibration effect significantly. The optimized non-cut blast scheme, which effectively utilized the existing free surface, could reduce the explosive consumption and vibration effect significantly, and might be preferred for in-situ tunnel expansion projects

Drought-Modulated Boreal Forest Fire Occurrence and Linkage with La Nina Events in Altai Mountains, Northwest China

Warming-induced drought stress and El Nino-associated summer precipitation failure are responsible for increased forest fire intensities of tropical and temperate forests in Asia and Australia. However, both effects are unclear for boreal forests, the largest biome and carbon stock over land. Here, we combined fire frequency, burned area, and climate data in the Altai boreal forests, the southmost extension of Siberia&rsquo;s boreal forest into China, and explored their link with El Nino&ndash;Southern Oscillation (ENSO). Surprisingly, both summer drought severity and fire occurrence showed significant (p &lt; 0.05) correlation with La Nina events of the previous year and therefore provide an important reference for forest fire prediction and prevention in Altai. Despite a significant warming trend, the increased moisture over Altai has largely offset the effect of warming-induced drought stress and led to an insignificant fire frequency trend in the last decades, resulting in largely reduced burned area since the 1980s. The reduced burned area can also be attributed to fire suppression efforts and greatly increased investment in fire prevention since 1987

Effects of AR7 Joint Complex on arthralgia for patients with osteoarthritis: results of a three-month study in Shanghai, China.

BackgroundOsteoarthritis-induced arthralgia is a common cause of morbidity in both men and women worldwide. AR7 Joint Complex is a nutritional supplement containing various ingredients including sternum collagen II and methylsulfonylmethane. The product has been marketed in United States for over a decade, but clinical data measuring the effectiveness of this supplement in relieving arthralgia is lacking. The goal of this study was to determine the effect of AR7 Joint Complex on osteoarthritis.MethodsA total of 100 patients over the age of 50 who had osteoarthritis were recruited to the double-blind study and randomly assigned into either treatment or placebo control groups. The patients in the treatment group were given AR7 Joint Complex orally, 1 capsule daily for 12 weeks, while the patients in the control group were given a placebo for the same period of time. Prior to and at the end of the study, data including Quality of Life questionnaires (SF-36), visual analog scales (1 to 100 mm), and X-rays of affected joints were collected.ResultsA total of 89 patients completed the study: 44 from the treatment group and 45 from the control group. No significant change in X-ray results was found in either group after the study. However, there was a significant decrease in patients complaining of arthralgia and tenderness (P &lt; 0.01) in the treatment group and there was also a significant difference between the treatment and control groups at the end of the study. In addition, for Quality of Life data, the body pain index (BP) in the treatment group was significantly improved (P &lt; 0.05) compared to the control group. No significant toxicity was noted in either group.ConclusionAR7 Joint Complex appears to have short-term effects in relieving pain in patients with osteoarthritis. Whether such an effect is long-lasting remains to be seen

5-fluorouracil suppresses stem cell-like properties by inhibiting p38 in pancreatic cancer cell line PANC-1

Introduction. Suppressing the phenotype of cancer stem cells (CSCs) is a promising treatment strategy for cancer. P38 mitogen-activated protein kinases (MAPK, p38) play an important role in the occurrence, development, and stemness maintenance of tumors. The aim of the current study was to investigate the effect of p38 on the stemness maintenance of CSCs in pancreatic cancer cell line PANC-1. Material and methods. PANC-1 human pancreatic cancer cells were treated with 5-fluorouracil (5-FU) at 0.5 IC50, IC50, and 2 IC50 for 24 h. PANC-1 cells were treated for 24 h with 5-FU at 0.5IC50, IC50, and 2IC50 with or without VX-702, p38 phosphorylation inhibitor. Cells were resuspended in DMEM supplemented with 20 ng/ml epidermal growth factor, 2% B27, 5 mg/ml insulin, 20 g/ml basic fibroblast growth factor, and 10 μg/ml transferrin. Cells were seeded in ultra-low adhesion 6-well dishes to observe tumor spheroidization. The expression of CDK2, cyclin B1, cyclin D1, OCT4, SOX2, Nanog, and p38 was measured by Western blot. The mRNA expression of p38, OCT4, Nanog, and SOX2 was measured by RT-PCR. Flow cytometry was performed to evaluate the cell cycle, apoptosis, and proportion of CD44+CD133+ PANC-1 cells. Results. 5-FU decreased cell viability and increased apoptosis. 5-FU suppressed the stemness maintenance of CSCs in PANC-1 cells, as demonstrated by the inhibition of tumorsphere formation, the decrease in CD44+CD133+ cells’ fraction, and downregulation of OCT4, Nanog, and SOX2 expression. In addition, 5-FU inhibited the phosphorylation of p38 in PANC-1 cells. The phosphorylation of p38 was subsequently suppressed by VX-702, p38 mitogen-activated protein kinase inhibitor, which exhibited similar effects as those of 5-FU treatment. The effect of VX-702 on PANC-1 cells was further enhanced by 5-FU treatment. Thus, p38 inhibitor decreased the viability and increased the apoptosis of PANC-1 cells. P38 inhibitor suppressed the stemness maintenance of CSCs in PANC-1 cells, as demonstrated by the inhibition of tumorsphere formation, the decrease in CD44+CD133+ cells, and the downregulation of OCT4, Nanog, and SOX2 expression. Conclusions. These findings indicate that the inhibition of p38 phosphorylation suppresses the stemness maintenance and 5-FU resistance of PANC-1 cells, providing a potential therapeutic target for the prevention and treatment of pancreatic cancer