Selectively enhanced expression of prophenoloxidase activating enzyme 1 (PPAE1) at a bacteria clearance site in the white shrimp, Litopenaeus vannamei

<p>Abstract</p> <p>Background</p> <p>The prophenoloxidase-activating (PO activating) system plays an important role in the crustacean innate immunity, particularly in wound healing and pathogen defense. A key member of this system is prophenoloxidase-activating enzyme (PPAE), which is the direct activator of prophenoloxidase (proPO). Despite their importance in crustacean PO activating system, the studies on them remain limited.</p> <p>Results</p> <p>Here we report on a PPAE of white shrimp, <it>Litopenaeus vannamei </it>(lvPPAE1), which showed 94% similarity to PPAE1 of <it>Penaeus monodon</it>. We found that lvPPAE1 in fluid hemocytes was down regulated after challenge by <it>Vibrio harveyi </it>but was enhanced when shrimps were exposed to a bacteria-rich environment for long-term. In <it>vivo </it>gene silence of lvPPAE1 by RNAi can significantly reduce the phenoloxidase activity (PO) and increase the susceptibility of shrimps to <it>V. harveyi</it>. Although lvPPAE1 was down-regulated in fluid hemocytes by <it>Vibrio </it>challenge, its expression increased significantly in gill after bacteria injection, which is the primary bacteria-clearance tissue.</p> <p>Conclusion</p> <p>Suppressed expression in fluid hemocytes and enhanced expression in gill indicates selectively enhanced expression at the bacterial clearance site. This is a novel feature for PPAE expression. The results will contribute to our understanding of the PO activating system in crustaceans.</p

Risk factors for hypoxaemia following hip fracture surgery in elderly patients who recovered from COVID-19: a multicentre retrospective study

ObjectivesTo explore the risk factors associated with postoperative hypoxaemia in elderly patients who have recovered from coronavirus disease (COVID-19) and underwent hip fracture surgery in the short term.DesignMulticentre retrospective study.SettingThe study was performed in three first 3A-grade hospitals in China.ParticipantsA sequential sampling method was applied to select study participants. Medical records of 392 patients aged ≥65 years who had recovered from COVID-19 and underwent hip fracture surgery at three hospitals in China between 1 November, 2022, and 15 February, 2023, were reviewed.InterventionsPatients were assigned to hypoxaemia or non-hypoxaemia groups, according to whether hypoxaemia occurred after surgery. Univariate and multivariate logistic regression analyses were used to identify independent risk factors for postoperative hypoxaemia.ResultsThe incidence of postoperative hypoxaemia was 38.01%. Statistically significant differences were found between the two groups in terms of age, body mass index (BMI), American Society of Anesthesiologists (ASA) classification, presence of expectoration symptoms, preoperative hypoxaemia, chronic obstructive pulmonary disease, pulmonary inflammation, time between recovery from COVID-19 and surgery, anaesthetic mode, surgical procedure, intraoperative blood loss, intraoperative infusion, duration of surgery, and length of hospital stay (p &lt; 0.05). Furthermore, patients with BMI ≥28.0 kg/m2, expectoration symptoms, presence of preoperative hypoxaemia, ASA classification III, time between recovery from COVID-19 and surgery ≤2 weeks, and general anaesthesia were potential risk factors for postoperative hypoxaemia.ConclusionObesity, expectoration symptoms, preoperative hypoxaemia, ASA classification III, time between recovery from COVID-19 and surgery ≤2 weeks, and general anaesthesia were potential risk factors for postoperative hypoxaemia in elderly patients who recovered from COVID-19 and underwent hip fracture surgery in the short term

MetaAdvDet: Towards Robust Detection of Evolving Adversarial Attacks

Deep neural networks (DNNs) are vulnerable to adversarial attack which is maliciously implemented by adding human-imperceptible perturbation to images and thus leads to incorrect prediction. Existing studies have proposed various methods to detect the new adversarial attacks. However, new attack methods keep evolving constantly and yield new adversarial examples to bypass the existing detectors. It needs to collect tens of thousands samples to train detectors, while the new attacks evolve much more frequently than the high-cost data collection. Thus, this situation leads the newly evolved attack samples to remain in small scales. To solve such few-shot problem with the evolving attack, we propose a meta-learning based robust detection method to detect new adversarial attacks with limited examples. Specifically, the learning consists of a double-network framework: a task-dedicated network and a master network which alternatively learn the detection capability for either seen attack or a new attack. To validate the effectiveness of our approach, we construct the benchmarks with few-shot-fashion protocols based on three conventional datasets, i.e. CIFAR-10, MNIST and Fashion-MNIST. Comprehensive experiments are conducted on them to verify the superiority of our approach with respect to the traditional adversarial attack detection methods.Comment: 10 pages, 2 figures, accepted as the conference paper of Proceedings of the 27th ACM International Conference on Multimedia (MM'19

Variance Change Point Detection Under a Smoothly-Changing Mean Trend with Application to Liver Procurement

Literature on change point analysis mostly requires a sudden change in the data distribution, either in a few parameters or the distribution as a whole. We are interested in the scenario, where the variance of data may make a significant jump while the mean changes in a smooth fashion. The motivation is a liver procurement experiment monitoring organ surface temperature. Blindly applying the existing methods to the example can yield erroneous change point estimates since the smoothly changing mean violates the sudden-change assumption. We propose a penalized weighted least-squares approach with an iterative estimation procedure that integrates variance change point detection and smooth mean function estimation. The procedure starts with a consistent initial mean estimate ignoring the variance heterogeneity. Given the variance components the mean function is estimated by smoothing splines as the minimizer of the penalized weighted least squares. Given the mean function, we propose a likelihood ratio test statistic for identifying the variance change point. The null distribution of the test statistic is derived together with the rates of convergence of all the parameter estimates. Simulations show excellent performance of the proposed method. Application analysis offers numerical support to non invasive organ viability assessment by surface temperature monitoring. Supplementary materials for this article are available online

Perfusion parameters of triphasic computed tomography hold preoperative prediction value for microvascular invasion in hepatocellular carcinoma

Abstract The purpose of this study was to evaluate perfusion parameters of triphasic computed tomography (CT) scans in predicting microvascular invasion (MVI) in hepatocellular carcinoma (HCC). All patients were pathologically diagnosed as HCC and underwent triple-phase enhanced CT imaging, which was used to calculate the blood perfusion parameters of hepatic arterial supply perfusion (HAP), portal vein blood supply perfusion (PVP), hepatic artery perfusion Index (HPI), and arterial enhancement fraction (AEF). Receiver operating characteristic (ROC) curve was used to evaluate the performance. The mean values of PVP(Min), AEF(Min), the difference in PVP, HPI and AEF related parameters, the relative PVP(Min) and AEF(Min) in MVI negative group were significantly higher than those in MVI positive group, while for the difference in HPI(Max), the relative HPI(Max) and AEF(Max), the value of MVI positive group significantly higher than that of negative group. The combination of PVP, HPI and AEF had the highest diagnostic efficacy. The two parameters related to HPI had the highest sensitivity, while the combination of PVP related parameters had higher specificity. A combination of perfusion parameters in patients with HCC derived from traditional triphasic CT scans can be used as a preoperative biomarker for predicting MVI

Review on the Application of Supplementary Cementitious Materials in Self-Compacting Concrete

For the sustainable development of construction materials, supplementary cementitious materials (SCMs) are commonly added to self-compacting concrete (SCC). This paper reviewed the application techniques and hydration mechanisms of SCMs in SCC. The impacts of SCMs on the microstructure and performance of SCC were also discussed. SCMs are used as a powder material to produce SCC by replacing 10% to 50% of cement. Hydration mechanisms include the pozzolanic reaction, alkaline activation, and adsorption effect. Moreover, the filling effect and dilution effect of some SCMs can refine the pore structure and decrease the temperature rise of concrete, respectively. Specifically, the spherical particles of fly ash can improve the fluidity of SCC, and the aluminum-containing mineral phase can enhance the resistance to chloride ion penetration. Silica fume will increase the water demand of the paste and promote its strength development (a replacement of 10% results in a 20% increase at 28 days). Ground-granulated blast furnace slag may reduce the early strength of SCC. The adsorption of Ca2+ by CaCO3 in limestone powder can accelerate the hydration of cement and promote its strength development

Review on the Application of Supplementary Cementitious Materials in Self-Compacting Concrete

For the sustainable development of construction materials, supplementary cementitious materials (SCMs) are commonly added to self-compacting concrete (SCC). This paper reviewed the application techniques and hydration mechanisms of SCMs in SCC. The impacts of SCMs on the microstructure and performance of SCC were also discussed. SCMs are used as a powder material to produce SCC by replacing 10% to 50% of cement. Hydration mechanisms include the pozzolanic reaction, alkaline activation, and adsorption effect. Moreover, the filling effect and dilution effect of some SCMs can refine the pore structure and decrease the temperature rise of concrete, respectively. Specifically, the spherical particles of fly ash can improve the fluidity of SCC, and the aluminum-containing mineral phase can enhance the resistance to chloride ion penetration. Silica fume will increase the water demand of the paste and promote its strength development (a replacement of 10% results in a 20% increase at 28 days). Ground-granulated blast furnace slag may reduce the early strength of SCC. The adsorption of Ca2+ by CaCO3 in limestone powder can accelerate the hydration of cement and promote its strength development

Variance Change Point Detection Under a Smoothly-Changing Mean Trend with Application to Liver Procurement

<p>Literature on change point analysis mostly requires a sudden change in the data distribution, either in a few parameters or the distribution as a whole. We are interested in the scenario, where the variance of data may make a significant jump while the mean changes in a smooth fashion. The motivation is a liver procurement experiment monitoring organ surface temperature. Blindly applying the existing methods to the example can yield erroneous change point estimates since the smoothly changing mean violates the sudden-change assumption. We propose a penalized weighted least-squares approach with an iterative estimation procedure that integrates variance change point detection and smooth mean function estimation. The procedure starts with a consistent initial mean estimate ignoring the variance heterogeneity. Given the variance components the mean function is estimated by smoothing splines as the minimizer of the penalized weighted least squares. Given the mean function, we propose a likelihood ratio test statistic for identifying the variance change point. The null distribution of the test statistic is derived together with the rates of convergence of all the parameter estimates. Simulations show excellent performance of the proposed method. Application analysis offers numerical support to non invasive organ viability assessment by surface temperature monitoring. Supplementary materials for this article are available online.</p

Methoprene-tolerant (Met) knockdown in the adult female cockroach, Diploptera punctata completely inhibits ovarian development.

Independent of the design of the life cycle of any insect, their growth and reproduction are highly choreographed through the action of two versatile hormones: ecdysteroids and juvenile hormones (JH). However, the means by which JH can target tissues and exert its pleiotropic physiological effects is currently still not completely elucidated. Although the identity of the one JH receptor is currently still elusive, recent evidence seems to point to the product of the Methoprene-tolerant gene (Met) as the most likely contender in transducing the action of JH. Studies on the role of this transcription factor have mostly been focused on immature insect stages. In this study we used the viviparous cockroach Diploptera punctata, a favorite model in studying JH endocrinology, to examine the role of Met during reproduction. A tissue distribution and developmental profile of transcript levels was determined for Met and its downstream partners during the first gonadotropic cycle of this cockroach. Using RNA interference, our study shows that silencing Met results in an arrest of basal oocyte development; vitellogenin is no longer transcribed in the fat body and no longer taken up by the ovary. Patency is not induced in these animals which fail to produce the characteristic profile of JH biosynthesis typical of the first gonadotropic cycle. Moreover, the ultrastructure of the follicle cells showed conspicuous whorls of rough endoplasmic reticulum and a failure to form chorion. Our study describes the role of Met on a cellular and physiological level during insect reproduction, and confirms the role of Met as a key factor in the JH signaling pathway

Noble Metallic Pyramidal Substrate for Surface-Enhanced Raman Scattering Detection of Plasmid DNA Based on Template Stripping Method

In this paper, a new method for manufacturing flexible and repeatable sensors made of silicon solar cells is reported. The method involves depositing the noble metal film directly onto the Si template and stripping out the substrate with a pyramid morphology by using an adhesive polymer. In order to evaluate the enhancement ability of the substrate, Rhodamine 6G (R6G) were used as surface-enhanced Raman scattering (SERS) probe molecules, and the results showed a high sensitivity and stability. The limit of detection was down to 10−12 M for R6G. The finite-difference time domain (FDTD) was used to reflect the distribution of the electromagnetic field, and the electric field was greatly enhanced on the surface of the inverted pyramidal substrate, especially in pits. The mechanism of Raman enhancement of two types of pyramidal SERS substrate, before and after stripping of the noble metal film, is discussed. By detecting low concentrations of plasmid DNA, the identification of seven characteristic peaks was successfully realized using a noble metallic pyramidal substrate