ESKNet-An enhanced adaptive selection kernel convolution for breast tumors segmentation

Breast cancer is one of the common cancers that endanger the health of women globally. Accurate target lesion segmentation is essential for early clinical intervention and postoperative follow-up. Recently, many convolutional neural networks (CNNs) have been proposed to segment breast tumors from ultrasound images. However, the complex ultrasound pattern and the variable tumor shape and size bring challenges to the accurate segmentation of the breast lesion. Motivated by the selective kernel convolution, we introduce an enhanced selective kernel convolution for breast tumor segmentation, which integrates multiple feature map region representations and adaptively recalibrates the weights of these feature map regions from the channel and spatial dimensions. This region recalibration strategy enables the network to focus more on high-contributing region features and mitigate the perturbation of less useful regions. Finally, the enhanced selective kernel convolution is integrated into U-net with deep supervision constraints to adaptively capture the robust representation of breast tumors. Extensive experiments with twelve state-of-the-art deep learning segmentation methods on three public breast ultrasound datasets demonstrate that our method has a more competitive segmentation performance in breast ultrasound images.Comment: 12 pages, 8 figure

Developmental Stage-Specific Imprinting of IPL in Domestic Pigs (Sus scrofa)

Imprinted in placenta and liver (IPL) gene has been identified as an imprinted gene in the mouse and human. Its sequence and imprinting status, however, have not been determined in the domestic pigs. In the present study, a 259 base pair-specific sequence for IPL gene of the domestic pig was obtained and a novel SNP, a T/C transition, was identified in IPL exon 1. The C allele of this polymorphism was found to be the predominant allele in Landrace,Yorkshire, and Duroc. The frequency of CC genotype and C allele are different in Duroc as compared with Yorkshire (P = .038 and P = .005, resp.). Variable imprinting status of this gene was observed in different developmental stages. For example, it is imprinted in 1-dayold newborns (expressed from the maternal allele), but imprinting was lost in 180-day-old adult (expressed from both parental alleles). Real-time PCR analysis showed the porcine IPL gene is expressed in all tested eight organ/tissues. The expression level was significantly higher in spleen, duodenum, lung, and bladder of 180-day-old Lantang adult compared to that in 1-day-old newborns Lantang pigs (P < .05). In conclusion, the imprinting of the porcine IPL gene is developmental stage and tissue specific

Homocysteine and Carotid Plaque Stability: A Cross-Sectional Study in Chinese Adults

Background and Purpose This study aimed to explore the possible association of plasma total homocysteine with carotid plaque stability. Methods: A cross-sectional study was conducted from 2010 to 2011. A stratified random sample of 2,919 Chinese participants aged 40 years or older was enrolled. Plasma total homocysteine levels were measured and carotid plaques were evaluated by ultrasonography. Logistic regression model was used to analyze the association of homocysteine levels to the progression of carotid plaque development, while adjusting for demographics and vascular risk factors. Results: The mean level of plasma homocysteine in the subjects was 14.9 µmol/l. Along with increase in homocysteine level, the risk of advanced carotid plaque elevated (odds ratio = 1.28; 95% confidence interval = 1.09–1.51) after adjusting for age, sex, and other potential confounders. Stratified by sex, higher homocysteine level was strongly associated with advanced carotid plaque in men (OR = 1.41; 95% confidence interval = 1.17–1.70), but not in women. Conclusion: The findings suggest that plasma level of homocysteine may be associated with advanced carotid plaque, which constitutes high risks of stroke, in male Chinese adults

The non-gibberellic acid-responsive semi-dwarfing gene uzu affects Fusarium crown rot resistance in barley

BACKGROUND: Studies in Arabidopsis show that DELLA genes may differentially affect responses to biotrophic and necrophic pathogens. A recent report based on the study of DELLA-producing reduced height (Rht) genes in wheat and barley also hypothesized that DELLA genes likely increased susceptibility to necrotrophs but increased resistance to biotrophs. RESULTS: Effects of uzu, a non-GA (gibberellic acid)-responsive semi-dwarfing gene, on Fusarium crown rot (FCR) resistance in barley were investigated. Fifteen pairs of near isogenic lines for this gene were generated and assessed under two different temperature regimes. Similar to its impacts on plant height, the semi-dwarfing gene uzu also showed larger effects on FCR severity in the high temperature regime when compared with that in the low temperature regime. CONCLUSIONS: Results from this study add to the growing evidence showing that the effects of plant height on Fusarium resistances are unlikely related to DELLA genes but due to direct or indirect effects of height difference per se. The interaction between these two characteristics highlights the importance of understanding relationships between resistance and other traits of agronomic importance as the value of a resistance gene could be compromised if it dramatically affects plant development and morphology

Probabilistic power flow calculation using principal component analysis-based compressive sensing

The increasing scale of the injection of renewable energy has brought about great uncertainty to the operation of power grid. In this situation, probabilistic power flow (PPF) calculation has been introduced to mitigate the low accuracy of traditional deterministic power flow calculation in describing the operation status and power flow distribution of power systems. Polynomial chaotic expansion (PCE) method has become popular in PPF analysis due to its high efficiency and accuracy, and sparse PCE has increased its capability of tackling the issue of dimension disaster. In this paper, we propose a principal component analysis-based compressive sensing (PCA-CS) algorithm solve the PPF problem. The l1-optimization of CS is used to tackle the dimension disaster of sparse PCE, and PCA is included to further increase the sparsity of expansion coefficient matrix. Theoretical and numerical simulation results show that the proposed method can effectively improve the efficiency of PPF calculation in the case of random inputs with higher dimensions

Variance-constrained dissipative observer-based control for a class of nonlinear stochastic systems with degraded measurements

The official published version of the article can be obtained from the link below.This paper is concerned with the variance-constrained dissipative control problem for a class of stochastic nonlinear systems with multiple degraded measurements, where the degraded probability for each sensor is governed by an individual random variable satisfying a certain probabilistic distribution over a given interval. The purpose of the problem is to design an observer-based controller such that, for all possible degraded measurements, the closed-loop system is exponentially mean-square stable and strictly dissipative, while the individual steady-state variance is not more than the pre-specified upper bound constraints. A general framework is established so that the required exponential mean-square stability, dissipativity as well as the variance constraints can be easily enforced. A sufficient condition is given for the solvability of the addressed multiobjective control problem, and the desired observer and controller gains are characterized in terms of the solution to a convex optimization problem that can be easily solved by using the semi-definite programming method. Finally, a numerical example is presented to show the effectiveness and applicability of the proposed algorithm.This work was supported in part by the Distinguished Visiting Fellowship of the Royal Academy of Engineering of the UK, the Royal Society of the UK, the GRF HKU 7137/09E, the National Natural Science Foundation of China under Grant 61028008, the International Science and Technology Cooperation Project of China under Grant 2009DFA32050, and the Alexander von Humboldt Foundation of Germany

A Hybrid Deep Feature-Based Deformable Image Registration Method for Pathology Images

Pathologists need to combine information from differently stained pathology slices for accurate diagnosis. Deformable image registration is a necessary technique for fusing multi-modal pathology slices. This paper proposes a hybrid deep feature-based deformable image registration framework for stained pathology samples. We first extract dense feature points via the detector-based and detector-free deep learning feature networks and perform points matching. Then, to further reduce false matches, an outlier detection method combining the isolation forest statistical model and the local affine correction model is proposed. Finally, the interpolation method generates the deformable vector field for pathology image registration based on the above matching points. We evaluate our method on the dataset of the Non-rigid Histology Image Registration (ANHIR) challenge, which is co-organized with the IEEE ISBI 2019 conference. Our technique outperforms the traditional approaches by 17% with the Average-Average registration target error (rTRE) reaching 0.0034. The proposed method achieved state-of-the-art performance and ranked 1st in evaluating the test dataset. The proposed hybrid deep feature-based registration method can potentially become a reliable method for pathology image registration.Comment: 22 pages, 12 figures. This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibl

Prime-boost vaccination of mice and rhesus macaques with two novel adenovirus vectored COVID-19 vaccine candidates.

ABSTRACTCOVID-19 vaccines are being developed urgently worldwide. Here, we constructed two adenovirus vectored COVID-19 vaccine candidates of Sad23L-nCoV-S and Ad49L-nCoV-S carrying the full-length gene of SARS-CoV-2 spike protein. The immunogenicity of two vaccines was individually evaluated in mice. Specific immune responses were observed by priming in a dose-dependent manner, and stronger responses were obtained by boosting. Furthermore, five rhesus macaques were primed with 5 × 109 PFU Sad23L-nCoV-S, followed by boosting with 5 × 109 PFU Ad49L-nCoV-S at 4-week interval. Both mice and macaques well tolerated the vaccine inoculations without detectable clinical or pathologic changes. In macaques, prime-boost regimen induced high titers of 103.16 anti-S, 102.75 anti-RBD binding antibody and 102.38 pseudovirus neutralizing antibody (pNAb) at 2 months, while pNAb decreased gradually to 101.45 at 7 months post-priming. Robust T-cell response of IFN-γ (712.6 SFCs/106 cells), IL-2 (334 SFCs/106 cells) and intracellular IFN-γ in CD4+/CD8+ T cell (0.39%/0.55%) to S peptides were detected in vaccinated macaques. It was concluded that prime-boost immunization with Sad23L-nCoV-S and Ad49L-nCoV-S can safely elicit strong immunity in animals in preparation of clinical phase 1/2 trials

Clinical Study Recombinant Brain Natriuretic Peptide for the Prevention of Contrast-Induced Nephropathy in Patients with Chronic Kidney Disease Undergoing Nonemergent Percutaneous Coronary Intervention or Coronary Angiography: A Randomized Controlled Tria

The role of brain natriuretic peptide (BNP) in the prevention of contrast-induced nephropathy (CIN) is unknown. This study aimed to investigate BNP&apos;s effect on CIN in chronic kidney disease (CKD) patients undergoing elective percutaneous coronary intervention (PCI) or coronary angiography (CAG). The patients were randomized to BNP (0.005 g/kg/min before contrast media (CM) exposure and saline hydration, = 106) or saline hydration alone ( = 103). Cystatin C, serum creatinine (SCr) levels, and estimated glomerular filtration rates (eGFR) were assessed at several time points. The primary endpoint was CIN incidence; secondary endpoint included changes in cystatin C, SCr, and eGFR. CIN incidence was significantly lower in the BNP group compared to controls (6.6% versus 16.5%, = 0.025). In addition, a more significant deterioration of eGFR, cystatin C, and SCr from 48 h to 1 week ( &lt; 0.05) was observed in controls compared to the BNP group. Although eGFR gradually deteriorated in both groups, a faster recovery was achieved in the BNP group. Multivariate logistic regression revealed that using &gt;100 mL of CM (odds ratio: 4.36, = 0.004) and BNP administration (odds ratio: 0.21, = 0.006) were independently associated with CIN. Combined with hydration, exogenous BNP administration before CM effectively decreases CIN incidence in CKD patients