Correlation between in vitro cytotoxicity and in vivo lethal activity in mice of epsilon toxin mutants from Clostridium perfringens

Epsilon toxin (Etx) from Clostridium perfringens is a pore-forming protein with a lethal effect on livestock, producing severe enterotoxemia characterized by general edema and neurological alterations. Site-specific mutations of the toxin are valuable tools to study the cellular and molecular mechanism of the toxin activity. In particular, mutants with paired cysteine substitutions that affect the membrane insertion domain behaved as dominant-negative inhibitors of toxin activity in MDCK cells. We produced similar mutants, together with a well-known non-toxic mutant (Etx-H106P), as green fluorescent protein (GFP) fusion proteins to perform in vivo studies in an acutely intoxicated mouse model. The mutant (GFP-Etx-I51C/A114C) had a lethal effect with generalized edema, and accumulated in the brain parenchyma due to its ability to cross the blood-brain barrier (BBB). In the renal system, this mutant had a cytotoxic effect on distal tubule epithelial cells. The other mutants studied (GFP-Etx-V56C/F118C and GFP-Etx-H106P) did not have a lethal effect or cross the BBB, and failed to induce a cytotoxic effect on renal epithelial cells. These data suggest a direct correlation between the lethal effect of the toxin, with its cytotoxic effect on the kidney distal tubule cells, and the ability to cross the BBB

Experimental study of the atmospheric neutrino backgrounds for proton decay to positron and neutral pion searches in water Cherenkov detectors

The atmospheric neutrino background for proton decay to positron and neutral pion in ring imaging water Cherenkov detectors is studied with an artificial accelerator neutrino beam for the first time. In total, about 314,000 neutrino events corresponding to about 10 megaton-years of atmospheric neutrino interactions were collected by a 1,000 ton water Cherenkov detector (KT). The KT charged-current single neutral pion production data are well reproduced by simulation programs of neutrino and secondary hadronic interactions used in the Super-Kamiokande (SK) proton decay search. The obtained proton to positron and neutral pion background rate by the KT data for SK from the atmospheric neutrinos whose energies are below 3 GeV is about two per megaton-year. This result is also relevant to possible future, megaton-scale water Cherenkov detectors.Comment: 13 pages, 16 figure

Proxy Measures of Fitness Suggest Coastal Fish Farms Can Act as Population Sources and Not Ecological Traps for Wild Gadoid Fish

Background: Ecological traps form when artificial structures are added to natural habitats and induce mismatches between habitat preferences and fitness consequences. Their existence in terrestrial systems has been documented, yet little evidence suggests they occur in marine environments. Coastal fish farms are widespread artificial structures in coastal ecosystems and are highly attractive to wild fish. Methodology/Principal Findings: To investigate if coastal salmon farms act as ecological traps for wild Atlantic cod (Gadus morhua) and saithe (Pollachius virens), we compared proxy measures of fitness between farm-associated fish and control fish caught distant from farms in nine locations throughout coastal Norway, the largest coastal fish farming industry in the world. Farms modified wild fish diets in both quality and quantity, thereby providing farm-associated wild fish with a strong trophic subsidy. This translated to greater somatic (saithe: 1.06–1.12 times; cod: 1.06–1.11 times) and liver condition indices (saithe: 1.4–1.8 times; cod: 2.0–2.8 times) than control fish caught distant from farms. Parasite loads of farm-associated wild fish were modified from control fish, with increased external and decreased internal parasites, however the strong effect of the trophic subsidy overrode any effects of altered loads upon condition. Conclusions and Significance: Proxy measures of fitness provided no evidence that salmon farms function as ecological traps for wild fish. We suggest fish farms may act as population sources for wild fish, provided they are protected from fishing while resident at farms to allow their increased condition to manifest as greater reproductive output.Funding was provided by the Norwegian Research Council Havet og kysten program to the CoastACE project (no: 173384)

Measurement of single charged pion production in the charged-current interactions of neutrinos in a 1.3 GeV wide band beam

Single charged pion production in charged-current muon neutrino interactions with carbon is studied using data collected in the K2K long-baseline neutrino experiment. The mean energy of the incident muon neutrinos is 1.3 GeV. The data used in this analysis are mainly from a fully active scintillator detector, SciBar. The cross section for single $\pi^{+}$ production in the resonance region ($W<2$ GeV/$c^2$) relative to the charged-current quasi-elastic cross section is found to be 0.734 $^{+0.140}_{-0.153}$. The energy-dependent cross section ratio is also measured. The results are consistent with a previous experiment and the prediction of our model.Comment: 15 pages, 12 figures, 7 tables. Uses revtex4. Minor revisions to match version accepted for publication in Physical Review

Surgical site infection after gastrointestinal surgery in high-income, middle-income, and low-income countries: a prospective, international, multicentre cohort study

Background: Surgical site infection (SSI) is one of the most common infections associated with health care, but its importance as a global health priority is not fully understood. We quantified the burden of SSI after gastrointestinal surgery in countries in all parts of the world. Methods: This international, prospective, multicentre cohort study included consecutive patients undergoing elective or emergency gastrointestinal resection within 2-week time periods at any health-care facility in any country. Countries with participating centres were stratified into high-income, middle-income, and low-income groups according to the UN's Human Development Index (HDI). Data variables from the GlobalSurg 1 study and other studies that have been found to affect the likelihood of SSI were entered into risk adjustment models. The primary outcome measure was the 30-day SSI incidence (defined by US Centers for Disease Control and Prevention criteria for superficial and deep incisional SSI). Relationships with explanatory variables were examined using Bayesian multilevel logistic regression models. This trial is registered with ClinicalTrials.gov, number NCT02662231. Findings: Between Jan 4, 2016, and July 31, 2016, 13 265 records were submitted for analysis. 12 539 patients from 343 hospitals in 66 countries were included. 7339 (58·5%) patient were from high-HDI countries (193 hospitals in 30 countries), 3918 (31·2%) patients were from middle-HDI countries (82 hospitals in 18 countries), and 1282 (10·2%) patients were from low-HDI countries (68 hospitals in 18 countries). In total, 1538 (12·3%) patients had SSI within 30 days of surgery. The incidence of SSI varied between countries with high (691 [9·4%] of 7339 patients), middle (549 [14·0%] of 3918 patients), and low (298 [23·2%] of 1282) HDI (p < 0·001). The highest SSI incidence in each HDI group was after dirty surgery (102 [17·8%] of 574 patients in high-HDI countries; 74 [31·4%] of 236 patients in middle-HDI countries; 72 [39·8%] of 181 patients in low-HDI countries). Following risk factor adjustment, patients in low-HDI countries were at greatest risk of SSI (adjusted odds ratio 1·60, 95% credible interval 1·05–2·37; p=0·030). 132 (21·6%) of 610 patients with an SSI and a microbiology culture result had an infection that was resistant to the prophylactic antibiotic used. Resistant infections were detected in 49 (16·6%) of 295 patients in high-HDI countries, in 37 (19·8%) of 187 patients in middle-HDI countries, and in 46 (35·9%) of 128 patients in low-HDI countries (p < 0·001). Interpretation: Countries with a low HDI carry a disproportionately greater burden of SSI than countries with a middle or high HDI and might have higher rates of antibiotic resistance. In view of WHO recommendations on SSI prevention that highlight the absence of high-quality interventional research, urgent, pragmatic, randomised trials based in LMICs are needed to assess measures aiming to reduce this preventable complication

Measurement of neutrino oscillation by the K2K experiment

We present measurements of nu(mu) disappearance in K2K, the KEK to Kamioka long-baseline neutrino oscillation experiment. One-hundred and twelve beam-originated neutrino events are observed in the fiducial volume of Super-Kamiokande with an expectation of 158.1(-8.6)(+9.2) events without oscillation. A distortion of the energy spectrum is also seen in 58 single-ring muonlike events with reconstructed energies. The probability that the observations are explained by the expectation for no neutrino oscillation is 0.0015% (4.3 sigma). In a two-flavor oscillation scenario, the allowed Delta m(2) region at sin(2)2 theta=1 is between 1.9 and 3.5x10(-3) eV(2) at the 90% C.L. with a best-fit value of 2.8x10(-3) eV(2)

Gene-Trap Mutagenesis Identifies Mammalian Genes Contributing to Intoxication by Clostridium perfringens ε-Toxin

The Clostridium perfringens ε-toxin is an extremely potent toxin associated with lethal toxemias in domesticated ruminants and may be toxic to humans. Intoxication results in fluid accumulation in various tissues, most notably in the brain and kidneys. Previous studies suggest that the toxin is a pore-forming toxin, leading to dysregulated ion homeostasis and ultimately cell death. However, mammalian host factors that likely contribute to ε-toxin-induced cytotoxicity are poorly understood. A library of insertional mutant Madin Darby canine kidney (MDCK) cells, which are highly susceptible to the lethal affects of ε-toxin, was used to select clones of cells resistant to ε-toxin-induced cytotoxicity. The genes mutated in 9 surviving resistant cell clones were identified. We focused additional experiments on one of the identified genes as a means of validating the experimental approach. Gene expression microarray analysis revealed that one of the identified genes, hepatitis A virus cellular receptor 1 (HAVCR1, KIM-1, TIM1), is more abundantly expressed in human kidney cell lines than it is expressed in human cells known to be resistant to ε-toxin. One human kidney cell line, ACHN, was found to be sensitive to the toxin and expresses a larger isoform of the HAVCR1 protein than the HAVCR1 protein expressed by other, toxin-resistant human kidney cell lines. RNA interference studies in MDCK and in ACHN cells confirmed that HAVCR1 contributes to ε-toxin-induced cytotoxicity. Additionally, ε-toxin was shown to bind to HAVCR1 in vitro. The results of this study indicate that HAVCR1 and the other genes identified through the use of gene-trap mutagenesis and RNA interference strategies represent important targets for investigation of the process by which ε-toxin induces cell death and new targets for potential therapeutic intervention

Computational approaches to explainable artificial intelligence: Advances in theory, applications and trends

Deep Learning (DL), a groundbreaking branch of Machine Learning (ML), has emerged as a driving force in both theoretical and applied Artificial Intelligence (AI). DL algorithms, rooted in complex and non-linear artificial neural systems, excel at extracting high-level features from data. DL has demonstrated human-level performance in real-world tasks, including clinical diagnostics, and has unlocked solutions to previously intractable problems in virtual agent design, robotics, genomics, neuroimaging, computer vision, and industrial automation. In this paper, the most relevant advances from the last few years in Artificial Intelligence (AI) and several applications to neuroscience, neuroimaging, computer vision, and robotics are presented, reviewed and discussed. In this way, we summarize the state-of-the-art in AI methods, models and applications within a collection of works presented at the 9th International Conference on the Interplay between Natural and Artificial Computation (IWINAC). The works presented in this paper are excellent examples of new scientific discoveries made in laboratories that have successfully transitioned to real-life applications.MCIU - Nvidia(UMA18-FEDERJA-084

Computational approaches to Explainable Artificial Intelligence:Advances in theory, applications and trends

Deep Learning (DL), a groundbreaking branch of Machine Learning (ML), has emerged as a driving force in both theoretical and applied Artificial Intelligence (AI). DL algorithms, rooted in complex and non-linear artificial neural systems, excel at extracting high-level features from data. DL has demonstrated human-level performance in real-world tasks, including clinical diagnostics, and has unlocked solutions to previously intractable problems in virtual agent design, robotics, genomics, neuroimaging, computer vision, and industrial automation. In this paper, the most relevant advances from the last few years in Artificial Intelligence (AI) and several applications to neuroscience, neuroimaging, computer vision, and robotics are presented, reviewed and discussed. In this way, we summarize the state-of-the-art in AI methods, models and applications within a collection of works presented at the 9th International Conference on the Interplay between Natural and Artificial Computation (IWINAC). The works presented in this paper are excellent examples of new scientific discoveries made in laboratories that have successfully transitioned to real-life applications.</p

Computational Approaches to Explainable Artificial Intelligence:Advances in Theory, Applications and Trends

Deep Learning (DL), a groundbreaking branch of Machine Learning (ML), has emerged as a driving force in both theoretical and applied Artificial Intelligence (AI). DL algorithms, rooted in complex and non-linear artificial neural systems, excel at extracting high-level features from data. DL has demonstrated human-level performance in real-world tasks, including clinical diagnostics, and has unlocked solutions to previously intractable problems in virtual agent design, robotics, genomics, neuroimaging, computer vision, and industrial automation. In this paper, the most relevant advances from the last few years in Artificial Intelligence (AI) and several applications to neuroscience, neuroimaging, computer vision, and robotics are presented, reviewed and discussed. In this way, we summarize the state-of-the-art in AI methods, models and applications within a collection of works presented at the 9 International Conference on the Interplay between Natural and Artificial Computation (IWINAC). The works presented in this paper are excellent examples of new scientific discoveries made in laboratories that have successfully transitioned to real-life applications