THE IMPACT OF POWER COEFFICIENT OF REACTIVITY ON CANDU 6 REACTORS

The combined effects of reactivity coefficients, along with other core nuclear characteristics, determine reactor core behavior in normal operation and accident conditions. The Power Coefficient of Reactivity (PCR) is an aggregate indicator representing the change in reactor core reactivity per unit change in reactor power. It is an integral quantity which captures the contributions of the fuel temperature, coolant void, and coolant temperature reactivity feedbacks. All nuclear reactor designs provide a balance between their inherent nuclear characteristics and the engineered reactivity control features, to ensure that changes in reactivity under all operating conditions are maintained within a safe range. The CANDU® reactor design takes advantage of its inherent nuclear characteristics, namely a small magnitude of reactivity coefficients, minimal excess reactivity, and very long prompt neutron lifetime, to mitigate the demand on the engineered systems for controlling reactivity and responding to accidents. In particular, CANDU reactors have always taken advantage of the small value of the PCR associated with their design characteristics, such that the overall design and safety characteristics of the reactor are not sensitive to the value of the PCR. For other reactor design concepts a PCR which is both large and negative is an important aspect in the design of their engineered systems for controlling reactivity. It will be demonstrated that during Loss of Regulation Control (LORC) and Large Break Loss of Coolant Accident (LBLOCA) events, the impact of variations in power coefficient, including a hypothesized larger than estimated PCR, has no safety-significance for CANDU reactor design. Since the CANDU 6 PCR is small, variations in the range of values for PCR on the performance or safety of the reactor are not significant

Do Clawback Adoptions Influence Capital Investments?

We present evidence that clawback provision adoptions influence capital investment mix via managerial compensation incentives. Specifically, we find for a propensity-matched sample of 931 voluntary clawback adoptions that capital investments shift away from R&D and toward capital expenditures, and for firms with enabling liquidity toward acquisitions, consistent with clawback effects on earnings-linked compensation. Corroborating evidence confirms that these effects are positively related to performance-based pay, growth opportunities, and invariant to risk-toleration incentives, with firms adopting clawbacks also exhibiting capital over-investment. This evidence is timely given a pending SEC rule that would mandate clawbacks for all firms listing on US exchanges.postprin

Machine learning algorithm to predict mortality in patients undergoing continuous renal replacement therapy

Abstract Background Previous scoring models such as the Acute Physiologic Assessment and Chronic Health Evaluation II (APACHE II) and the Sequential Organ Failure Assessment (SOFA) scoring systems do not adequately predict mortality of patients undergoing continuous renal replacement therapy (CRRT) for severe acute kidney injury. Accordingly, the present study applies machine learning algorithms to improve prediction accuracy for this patient subset. Methods We randomly divided a total of 1571 adult patients who started CRRT for acute kidney injury into training (70%, n = 1094) and test (30%, n = 477) sets. The primary output consisted of the probability of mortality during admission to the intensive care unit (ICU) or hospital. We compared the area under the receiver operating characteristic curves (AUCs) of several machine learning algorithms with that of the APACHE II, SOFA, and the new abbreviated mortality scoring system for acute kidney injury with CRRT (MOSAIC model) results. Results For the ICU mortality, the random forest model showed the highest AUC (0.784 [0.744–0.825]), and the artificial neural network and extreme gradient boost models demonstrated the next best results (0.776 [0.735–0.818]). The AUC of the random forest model was higher than 0.611 (0.583–0.640), 0.677 (0.651–0.703), and 0.722 (0.677–0.767), as achieved by APACHE II, SOFA, and MOSAIC, respectively. The machine learning models also predicted in-hospital mortality better than APACHE II, SOFA, and MOSAIC. Conclusion Machine learning algorithms increase the accuracy of mortality prediction for patients undergoing CRRT for acute kidney injury compared with previous scoring models

Longitudinal trajectory of acidosis and mortality in acute kidney injury requiring continuous renal replacement therapy

Abstract Background Acidosis frequently occurs in severe acute kidney injury (AKI), and continuous renal replacement therapy (CRRT) can control this pathologic condition. Nevertheless, acidosis may be aggravated; thus, monitoring is essential after starting CRRT. Herein, we addressed the longitudinal trajectory of acidosis on CRRT and its relationship with worse outcomes. Methods The latent growth mixture model was applied to classify the trajectories of pH during the first 24 hours and those of C-reactive protein (CRP) after 24 hours on CRRT due to AKI (n = 1815). Cox proportional hazard models were used to calculate hazard ratios of all-cause mortality after adjusting multiple variables or matching their propensity scores. Results The patients could be classified into 5 clusters, including the normally maintained groups (1st cluster, pH = 7.4; and 2nd cluster, pH = 7.3), recovering group (3rd cluster with pH values from 7.2 to 7.3), aggravating group (4th cluster with pH values from 7.3 to 7.2), and ill-being group (5th cluster, pH < 7.2). The pH clusters had different trends of C-reactive protein (CRP) after 24 hours; the 1st and 2nd pH clusters had lower levels, but the 3rd to 5th pH clusters had an increasing trend of CRP. The 1st pH cluster had the best survival rates, and the 3rd to 5th pH clusters had the worst survival rates. This survival difference was significant despite adjusting for other variables or matching propensity scores. Conclusions Initial trajectories of acidosis determine subsequent worse outcomes, such as mortality and inflammation, in patients undergoing CRRT due to AKI

Liposarcoma: exploration of clinical prognostic factors for risk based stratification of therapy

<p>Abstract</p> <p>Background</p> <p>Prognosis and optimal treatment strategies of liposarcoma have not been fully defined. The purpose of this study is to define the distinctive clinical features of liposarcomas by assessing prognostic factors.</p> <p>Methods</p> <p>Between January 1995 and May 2008, 94 liposarcoma patients who underwent surgical resection with curative intent were reviewed.</p> <p>Results</p> <p>Fifty patients (53.2%) presented with well differentiated, 22 (23.4%) myxoid, 15 (16.0%) dedifferentiated, 5 (5.3%) round cell, and 2 (2.1%) pleomorphic histology. With the median 14 cm sized of tumor burden, about half of the cases were located in the retroperitoneum (46.8%). Seventy two (76.6%) patients remained alive with 78.1%, and 67.5% of the 5- and 10-year overall survival (OS) rates, respectively. Low grade liposarcoma (well differentiated and myxoid) had a significantly prolonged OS and disease free survival (DFS) with adjuvant radiotherapy when compared with those without adjuvant radiotherapy (5-year OS, 100% vs 66.3%, P = 0.03; 1-year DFS, 92.9% <it>vs </it>50.0%, respectively, P = 0.04). Independent prognostic factors for OS were histologic variant (P = 0.001; HR, 5.1; 95% CI, 2.0 – 12.9), and margin status (P = 0.005; HR, 4.1; 95% CI, 1.6–10.5). We identified three different risk groups: group 1 (n = 66), no adverse factors; group 2, one or two adverse factors (n = 28). The 5-year OS rate for group 1, and 2 were 91.9%, 45.5%, respectively.</p> <p>Conclusion</p> <p>The histologic subtype, and margin status were independently associated with OS, and adjuvant radiotherapy seems to confer survival benefit in low grade tumors. Our prognostic model for primary liposarcoma demonstrated distinct three groups of patients with good prognostic discrimination.</p

OsLIC, a Novel CCCH-Type Zinc Finger Protein with Transcription Activation, Mediates Rice Architecture via Brassinosteroids Signaling

Rice architecture is an important agronomic trait and a major limiting factor for its high productivity. Here we describe a novel CCCH-type zinc finger gene, OsLIC (Oraza sativa leaf and tiller angle increased controller), which is involved in the regulation of rice plant architecture. OsLIC encoded an ancestral and unique CCCH type zinc finge protein. It has many orthologous in other organisms, ranging from yeast to humane. Suppression of endogenous OsLIC expression resulted in drastically increased leaf and tiller angles, shortened shoot height, and consequently reduced grain production in rice. OsLIC is predominantly expressed in rice collar and tiller bud. Genetic analysis suggested that OsLIC is epistatic to d2-1, whereas d61-1 is epistatic to OsLIC. Interestingly, sterols were significantly higher in level in transgenic shoots than in the wild type. Genome-wide expression analysis indicated that brassinosteroids (BRs) signal transduction was activated in transgenic lines. Moreover, transcription of OsLIC was induced by 24-epibrassinolide. OsLIC, with a single CCCH motif, displayed binding activity to double-stranded DNA and single-stranded polyrA, polyrU and polyrG but not polyrC. It contains a novel conserved EELR domain among eukaryotes and displays transcriptional activation activity in yeast. OsLIC may be a transcription activator to control rice plant architecture

Efficient CO2-Reducing Activity of NAD-Dependent Formate Dehydrogenase from Thiobacillus sp KNK65MA for Formate Production from CO2 Gas

NAD-dependent formate dehydrogenase (FDH) from Candida boidinii (CbFDH) has been widely used in various CO2 reduction systems but its practical applications are often impeded due to low CO2-reducing activity. In this study, we demonstrated superior CO2-reducing properties of FDH from Thiobacillus sp. KNK65MA (TsFDH) for production of formate from CO2 gas. To discover more efficient CO2-reducing FDHs than a reference enzyme e. CbFDH, five FDHs were selected with biochemical properties and then, their CO2-reducing activities were evaluated. All FDHs including CbFDH showed better CO2-reducing activities at acidic pHs than at neutral pHs and four FDHs were more active than CbFDH in the CO2 reduction reaction. In particular, the FDH from Thiobacillus sp. KNK65IVIA (TsFDH) exhibited the highest CO2-reducing activity and had a dramatic preference for the reduction reaction, i.e., a 84.2-fold higher ratio of CO2 reduction to formate oxidation in catalytic efficiency (k(cat)/K-B) compared to CbFDH. Formate was produced from CO2 gas using TsFDH and CbFDH, and TsFDH showed a 5.8-fold higher formate production rate than CbFDH. A sequence and structural comparison showed that FDHs with relatively high CO2-reducing activities had elongated N- and C-terminal loops. The experimental results demonstrate that TsFDH can be an alternative to CbFDH as a biocatalyst in CO2 reduction systemsope

Sublingual Immunization with M2-Based Vaccine Induces Broad Protective Immunity against Influenza

The ectodomain of matrix protein 2 (M2e) of influenza A virus is a rationale target antigen candidate for the development of a universal vaccine against influenza as M2e undergoes little sequence variation amongst human influenza A strains. Vaccine-induced M2e-specific antibodies (Abs) have been shown to display significant cross-protective activity in animal models. M2e-based vaccine constructs have been shown to be more protective when administered by the intranasal (i.n.) route than after parenteral injection. However, i.n. administration of vaccines poses rare but serious safety issues associated with retrograde passage of inhaled antigens and adjuvants through the olfactory epithelium. In this study, we examined whether the sublingual (s.l.) route could serve as a safe and effective alternative mucosal delivery route for administering a prototype M2e-based vaccine. The mechanism whereby s.l. immunization with M2e vaccine candidate induces broad protection against infection with different influenza virus subtypes was explored.A recombinant M2 protein with three tandem copies of the M2e (3M2eC) was expressed in Escherichia coli. Parenteral immunizations of mice with 3M2eC induced high levels of M2e-specific serum Abs but failed to provide complete protection against lethal challenge with influenza virus. In contrast, s.l. immunization with 3M2eC was superior for inducing protection in mice. In the latter animals, protection was associated with specific Ab responses in the lungs.The results demonstrate that s.l. immunization with 3M2eC vaccine induced airway mucosal immune responses along with broad cross-protective immunity to influenza. These findings may contribute to the understanding of the M2-based vaccine approach to control epidemic and pandemic influenza infections

Comparison of carnivore, omnivore, and herbivore mammalian genomes with a new leopard assembly.

BACKGROUND: There are three main dietary groups in mammals: carnivores, omnivores, and herbivores. Currently, there is limited comparative genomics insight into the evolution of dietary specializations in mammals. Due to recent advances in sequencing technologies, we were able to perform in-depth whole genome analyses of representatives of these three dietary groups. RESULTS: We investigated the evolution of carnivory by comparing 18 representative genomes from across Mammalia with carnivorous, omnivorous, and herbivorous dietary specializations, focusing on Felidae (domestic cat, tiger, lion, cheetah, and leopard), Hominidae, and Bovidae genomes. We generated a new high-quality leopard genome assembly, as well as two wild Amur leopard whole genomes. In addition to a clear contraction in gene families for starch and sucrose metabolism, the carnivore genomes showed evidence of shared evolutionary adaptations in genes associated with diet, muscle strength, agility, and other traits responsible for successful hunting and meat consumption. Additionally, an analysis of highly conserved regions at the family level revealed molecular signatures of dietary adaptation in each of Felidae, Hominidae, and Bovidae. However, unlike carnivores, omnivores and herbivores showed fewer shared adaptive signatures, indicating that carnivores are under strong selective pressure related to diet. Finally, felids showed recent reductions in genetic diversity associated with decreased population sizes, which may be due to the inflexible nature of their strict diet, highlighting their vulnerability and critical conservation status. CONCLUSIONS: Our study provides a large-scale family level comparative genomic analysis to address genomic changes associated with dietary specialization. Our genomic analyses also provide useful resources for diet-related genetic and health research