PCDAL: A Perturbation Consistency-Driven Active Learning Approach for Medical Image Segmentation and Classification

In recent years, deep learning has become a breakthrough technique in assisting medical image diagnosis. Supervised learning using convolutional neural networks (CNN) provides state-of-the-art performance and has served as a benchmark for various medical image segmentation and classification. However, supervised learning deeply relies on large-scale annotated data, which is expensive, time-consuming, and even impractical to acquire in medical imaging applications. Active Learning (AL) methods have been widely applied in natural image classification tasks to reduce annotation costs by selecting more valuable examples from the unlabeled data pool. However, their application in medical image segmentation tasks is limited, and there is currently no effective and universal AL-based method specifically designed for 3D medical image segmentation. To address this limitation, we propose an AL-based method that can be simultaneously applied to 2D medical image classification, segmentation, and 3D medical image segmentation tasks. We extensively validated our proposed active learning method on three publicly available and challenging medical image datasets, Kvasir Dataset, COVID-19 Infection Segmentation Dataset, and BraTS2019 Dataset. The experimental results demonstrate that our PCDAL can achieve significantly improved performance with fewer annotations in 2D classification and segmentation and 3D segmentation tasks. The codes of this study are available at https://github.com/ortonwang/PCDAL

The diversity and structure of diazotrophic communities in the rhizosphere of coastal saline plants is mainly affected by soil physicochemical factors but not host plant species

The diversity and community structure of rhizospheric microbes are largely affected by soil physicochemical properties and plant species. In this work, high throughput sequencing and quantitative real-time PCR targeting nifH gene were used to assess the abundance and diversity of diazotrophic community in the coastal saline soils of Yellow River Delta (YRD). We demonstrated that the copy number of nifH gene encoding the Fe protein subunit of the nitrogenase in the nitrogen fixation process was significantly affected by soil physiochemical factors, and the abundance of diazotrophs in the rhizospheric soil samples collected from different locations was positively related with soil physicochemical properties. Soil salinity (P=0.003) and moisture (P=0.003) were significantly co-varied with the OTU-based community composition of diazotrophs. Taxonomic analysis showed that most diazotrophs belonged to the Alphaproteobacteria, Gammaproteobacteria and Deltaproteobacteria. Linear discriminant analysis (LDA) effect size (LEfSe) and canonical correspondence analysis (CCA) showed that diazotrophic community structure significantly varied with soil salinity, moisture, pH and total nitrogen, carbon, sulphur and nitrite (NO2–N) content. Our findings provide direct evidence toward the understanding of different effects of soil physicochemical properties and host plant traits such as halophytes types, life span and cotyledon type, on the community composition of diazotrophic populations in the rhizosphere of plants grown in coastal saline soils

The gap in injury mortality rates between urban and rural residents of Hubei province, China

<p>Abstract</p> <p>Background</p> <p>Injury is a growing public health concern in China. Injury death rates are often higher in rural areas than in urban areas in general. The objective of this study is to compare the injury mortality rates in urban and rural residents in Hubei Province in central China by age, sex and mechanism of injury.</p> <p>Methods</p> <p>Using data from the Disease Surveillance Points (DSP) system maintained by the Hubei Province Centers for Disease Control and Prevention (CDC) from 2006 to 2008, injury deaths were classified according to the International Classification of Disease-10^thRevision (ICD-10). Crude and age-adjusted annual mortality rates were calculated for rural and urban residents of Hubei Province.</p> <p>Results</p> <p>The crude and age-adjusted injury death rates were significantly higher for rural residents than for urban residents (crude rate ratio 1.9, 95% confidence interval 1.8-2.0; adjusted rate ratio 2.4, 95% confidence interval 2.3-2.4). The age-adjusted injury death rate for males was 81.6/100,000 in rural areas compared with 37.0/100 000 in urban areas; for females, the respective rates were 57.9/100,000 and 22.4/100 000. Death rates for suicide (32.4 per 100 000 vs 3.9 per 100 000), traffic-related injuries (15.8 per 100 000 vs 9.5 per 100 000), drowning (6.9 per 100 000 vs 2.3 per 100 000) and crushing injuries (2.0 per 100 000 vs 0.7 per 100 000) were significantly higher in rural areas. Overall injury death rates were much higher in persons over 65 years, with significantly higher rates in rural residents compared with urban residents for suicide (279.8 per 100 000 vs 10.7 per 100 000), traffic-related injuries, and drownings in this age group. Death rates for falls, poisoning, and suffocation were similar in the two geographic groups.</p> <p>Conclusions</p> <p>Rates of suicide, traffic-related injury deaths and drownings are demonstrably higher in rural compared with urban locations and should be targeted for injury prevention activity. There is a need for injury prevention policies targeted at elderly residents, especially with regard to suicide prevention in rural areas in Central China.</p

A High-Dynamic-Range Optical Remote Sensing Imaging Method for Digital TDI CMOS

The digital time delay integration (digital TDI) technology of the complementary metal-oxide-semiconductor (CMOS) image sensor has been widely adopted and developed in the optical remote sensing field. However, the details of targets that have low illumination or low contrast in scenarios of high contrast are often drowned out because of the superposition of multi-stage images in digital domain multiplies the read noise and the dark noise, thus limiting the imaging dynamic range. Through an in-depth analysis of the information transfer model of digital TDI, this paper attempts to explore effective ways to overcome this issue. Based on the evaluation and analysis of multi-stage images, the entropy-maximized adaptive histogram equalization (EMAHE) algorithm is proposed to improve the ability of images to express the details of dark or low-contrast targets. Furthermore, in this paper, an image fusion method is utilized based on gradient pyramid decomposition and entropy weighting of different TDI stage images, which can improve the detection ability of the digital TDI CMOS for complex scenes with high contrast, and obtain images that are suitable for recognition by the human eye. The experimental results show that the proposed methods can effectively improve the high-dynamic-range imaging (HDRI) capability of the digital TDI CMOS. The obtained images have greater entropy and average gradients

Visual Modeling of Rice Root Growth Based on B-Spline Curve

As a major food production crop in China, the growth and development of rice is an extremely complex systemic process, and the root system is the main organ for rice to obtain nutrients. Therefore, 3D modeling and visualization of the rice root system can help to further understand its morphology, structure and function, and provide an aid for scientific cultivation of rice and improving rice yield for decision making. In this paper, a mathematical model of the rice root system is established based on the B spline curve combined with the L-system approach, using mathematical knowledge based on the 3D morphological characteristics of the real rice root system. The B-Spline Curve is chosen to simulate this, and the recursive definition of B-Spline Curve and its formula are used to realize the modeling of the rice root system curve. Based on the mathematical method of rice root system integration, the bending effect of rice root system at different periods and different growth positions is realized. Finally, the L-system combined with B-Spline Curve is used to construct a rice root system model and realize the rice root system visualization simulation. The simulated image is closer to the real rice root system image in terms of morphological structure and has a strong sense of realism

Protective effects of HBSP on ischemia reperfusion and cyclosporine a induced renal injury.

Ischemia reperfusion (IR) and cyclosporine A (CsA) injuries are unavoidable in kidney transplantation and are associated with allograft dysfunction. Herein, the effect and mechanism of a novel tissue protective peptide, helix B surface peptide (HBSP) derived from erythropoietin, were investigated in a rat model. The right kidney was subjected to 45 min ischemia, followed by left nephrectomy and 2-week reperfusion, with or without daily treatment of CsA 25 mg/kg and/or HBSP 8 nmol/kg. Blood urea nitrogen was increased by CsA but decreased by HBSP at 1 week and 2 weeks, while the same changes were revealed in urinary protein/creatinine only at 2 weeks. HBSP also significantly ameliorated tubulointerstitial damage and interstitial fibrosis, which were gradually increased by IR and CsA. In addition, apoptotic cells, infiltrated inflammatory cells, and active caspase-3+ cells were greatly reduced by HBSP in the both IR and IR + CsA groups. The 17 kD active caspase-3 protein was decreased by HBSP in the IR and IR + CsA kidneys, with decreased mRNA only in the IR + CsA kidneys. Taken together, it has been demonstrated, for the first time, that HBSP effectively improved renal function and tissue damage caused by IR and/or CsA, which might be through reducing caspase-3 activation and synthesis, apoptosis, and inflammation

Porous Minerals Improve Wheat Shoot Growth and Grain Yield through Affecting Soil Properties and Microbial Community in Coastal Saline Land

Soil salinization has become a major environmental factor severely threatening global food security. The application of porous minerals could significantly ameliorate soil fertility and promote plant productivity under salt stress conditions. However, the effects of porous minerals on improving the salt resistance of grain crops in coastal saline soils is not fully studied. In this work, the shoot growth and grain yield of wheat plants grown in coastal saline fields, respectively amended with the four naturally available porous minerals, diatomite, montmorillonite, bentonite and zeolite, were assessed. The application of porous minerals, especially zeolite, significantly improved the biomass and grain yield of wheat plants under saline conditions, as demonstrated by the augmented plant fresh mass (14.8~61.2%) and increased seed size (3.8~58.8%) and number (1.4~57.5%). Soil property analyses exhibited that porous-mineral amendment decreased soil sodium content and sodium absorption ratio, and increased soil nutrients in both the rhizosphere and nonrhizosphere of wheat plants. Further quantitative-PCR and 16S high-throughput sequencing analysis revealed that porous-mineral application also remarkably increased the abundance of bacterial 16S rRNA (0.8~102.4%) and fungal 18S rRNA (89.2~209.6%), and altered the composition of the soil microbial community in the rhizosphere of wheat. Our findings suggest that zeolite could be used as an ideal salt soil amendment, and the changes in soil properties and microorganisms caused by the application of porous minerals like zeolite improved the salt resistance of wheat plants in coastal saline land, leading to increased shoot growth and seed production