634 research outputs found
Reduction of antimicrobials by use of vaccination - the ileitis experience
Porcine Enteropathy also known as ileitis in pigs, caused by Lawsonia intracellularis, is regarded as one of the major gut related health issues in pork production. Recent reports from national institutes for pharmaceutical products show that the annual amount of antibiotics against enteric diseases has increased over the last few years. Despite the ban of antimicrobial growth promoters in Europe since January 2006, the total amount of antibiotics used in pigs does not seem to be significantly reduced. This is contradictory to the demands of the consumers for a reduction in antibiotic use and the efforts to reduce the risk of antibiotic resistance. Recently several field studies have demonstrated that the use of Enterisol ileitis (Boehringer lngelheim), a vaccine against ileitis can reduce the amount of antibiotics needed to prevent this disease. Additionally, vaccination can contribute to the overall reduction in use of antimicrobials on farms due to the higher health status of the farms. This oral vaccine is therefore a better alternative compared to antibiotics to prevent ileitis
Humanistische antwoorden op de financiel-economische crisis?
De auteurs gaan in het artikel te rade bij verschillende humanistische organisaties en humanistieke publicisten in hun zoektocht naar humanistische antwoorden op de maatschappelijke en individuele gevolgen van de huidige financieel-economische crisis. Ze betogen dat de huidige humanistische antwoorden ontoereikend zijn om het sociaal-politieke gezicht van de humanistische beweging recht te doen, zoals dat in jaren zestig en zeventig door Max Rood, Arie den Broeder en Aad van Oosten werd voorgestaan. Bij deze auteurs was de relatie humanisme en politiek veel pregnanter en stond de vraag naar om de kwaliteit van het bestaan veel centraler
An investigation of motor memory deficits in Parkinson’s disease
People with Parkinson’s disease (PD) display motor memory deficits when tested on motor adaptation tasks involving visuomotor rotations, while the process of adaptation itself seems largely unaffected. Other forms of adaptation are unexplored and the mechanisms underlying their motor memory deficits unknown. Previous research has suggested reinforcement mechanisms to be affected in PD, but whether defective reinforcement is underlying motor memory impairments has never been directly investigated. Firstly, we investigated if the motor memory deficits shown by earlier studies also hold for force-field adaptation, where the participant learns to compensate for a perturbation caused by an external force acting on the limb. We then explored if adaptation to such force-fields was possible when adaptation was dependent on contextual cues, i.e. if people with PD were able to make context-motor associations, and in addition we investigated whether augmentation of reward and punishment improved reinforcement in PD. To increase our understanding of the effect of reward and punishment feedback on context-dependent motor learning their separate effects were investigated in a group of young adults. Results showed intact recall of the learned adapted state in people with PD, suggesting intact consolidation, but motor memory as tested with interference, where memory of the initial adaptation impairs learning of an opposite adaptation, to be strongly reduced in PD. We found evidence that people with PD were less able to learn context-motor associations in comparison to older Controls and these deficits became more pronounced when success-based feedback was strengthened suggesting reduced sensitivity to augmentation of reward and/or punishment. In young adults, reward and punishment feedback did not influence context-dependent motor adaptation itself, but it had some effect on movement velocity. We conclude that PD pathology leads to weaker context-motor associations and defective reinforcement processes, which may be underlying impaired recall of certain motor states
Munc18-1 promotes larger dense-core vesicle docking.
AbstractSecretory vesicles dock at the plasma membrane before Ca2+ triggers their exocytosis. Exocytosis requires the assembly of SNARE complexes formed by the vesicle protein Synaptobrevin and the membrane proteins Syntaxin-1 and SNAP-25. We analyzed the role of Munc18-1, a cytosolic binding partner of Syntaxin-1, in large dense-core vesicle (LDCV) secretion. Calcium-dependent LDCV exocytosis was reduced 10-fold in mouse chromaffin cells lacking Munc18-1, but the kinetic properties of the remaining release, including single fusion events, were not different from controls. Concomitantly, mutant cells displayed a 10-fold reduction in morphologically docked LDCVs. Moreover, acute overexpression of Munc18-1 in bovine chromaffin cells increased the amount of releasable vesicles and accelerated vesicle supply. We conclude that Munc18-1 functions upstream of SNARE complex formation and promotes LDCV docking
Efficacy of simultaneous vaccination with Enterisol® Ileitis and Ingelvac® CircoFLEXTM in a Swiss breeding farm
This study explores administration of two piglet vaccines as compared to the mono- and adjuvant-application. A vaccine against the Porcine Circovirus Type 2 (PCV2) cap protein subunit and a vaccine with attenuated live culture against Lawsonia (L.) intracellularis were applied to piglets aged 23.5 days on average. 1'405 animals were divided randomly into four groups. One piglet group was immunized with both vaccines while two other groups were immunized with a combination of one vaccine and adjuvants of alternate vaccination protocol and vice versa. These piglet groups were also compared to a control group supplemented with both adjuvants only. During fattening, pigs, which were simultaneously immunized with Enterisol(®) Ileitis and Ingelvac(®) CircoFLEX(TM) vaccine, gained significantly more weight (792 g/day) when compared to piglet groups mono-vaccinated with Ingelvac® CircoFLEXTM (772 g/day) or either with Enterisol® Ileitis (774 g/day). Moreover, immunized piglet groups showed significantly higher daily weight gain when compared to adjuvants only inoculated control group (751 g/day). Additionally, during fattening the control group displayed higher mortality (6,3 %) than the three vaccinated groups (Ingelvac(®) CircoFLEX(TM) 2,5 %, Enterisol(®) Ileitis 2,3 % and the combination of both vaccines 1,1 %). These data imply that simultaneous immunization with PCV2- and L. intracellularis specific vaccines positively benefit piglet growth observed by an additive effect on growth parameters in farms harboring both pathogens. Return of investment was calculated of 2.10 on the additional Enterisol(®) Ileitis vaccination
Revealing natural relationships among arbuscular mycorrhizal fungi: culture line BEG47 represents Diversispora epigaea, not Glomus versiforme
Background: Understanding the mechanisms underlying biological phenomena, such as evolutionarily conservative trait inheritance, is predicated on knowledge of the natural relationships among organisms. However, despite their enormous ecological significance, many of the ubiquitous soil inhabiting and plant symbiotic arbuscular mycorrhizal fungi (AMF, phylum Glomeromycota) are incorrectly classified.
Methodology/Principal Findings:
Here, we focused on a frequently used model AMF registered as culture BEG47. This fungus is a descendent of the ex-type culture-lineage of Glomus epigaeum, which in 1983 was synonymised with Glomus versiforme. It has since then been used as ‘G. versiforme BEG47’. We show by morphological comparisons, based on type material, collected 1860–61, of G. versiforme and on type material and living ex-type cultures of G. epigaeum, that these two AMF species cannot be conspecific, and by molecular phylogenetics that BEG47 is a member of the genus Diversispora.
Conclusions: This study highlights that experimental works published during the last >25 years on an AMF named ‘G. versiforme’ or ‘BEG47’ refer to D. epigaea, a species that is actually evolutionarily separated by hundreds of millions of years from all members of the genera in the Glomerales and thus from most other commonly used AMF ‘laboratory strains’. Detailed redescriptions substantiate the renaming of G. epigaeum (BEG47) as D. epigaea, positioning it systematically in the order Diversisporales, thus enabling an evolutionary understanding of genetical, physiological, and ecological traits, relative to those of other AMF. Diversispora epigaea is widely cultured as a laboratory strain of AMF, whereas G. versiforme appears not to have been cultured nor found in the field since its original description
Application of deep learning on mammographies to discriminate between low and high-risk DCIS for patient participation in active surveillance trials
Background: Ductal Carcinoma In Situ (DCIS) can progress to invasive breast cancer, but most DCIS lesions never will. Therefore, four clinical trials (COMET, LORIS, LORETTA, AND LORD) test whether active surveillance for women with low-risk Ductal carcinoma In Situ is safe (E. S. Hwang et al., BMJ Open, 9: e026797, 2019, A. Francis et al., Eur J Cancer. 51: 2296–2303, 2015, Chizuko Kanbayashi et al. The international collaboration of active surveillance trials for low-risk DCIS (LORIS, LORD, COMET, LORETTA), L. E. Elshof et al., Eur J Cancer, 51, 1497–510, 2015). Low-risk is defined as grade I or II DCIS. Because DCIS grade is a major eligibility criteria in these trials, it would be very helpful to assess DCIS grade on mammography, informed by grade assessed on DCIS histopathology in pre-surgery biopsies, since surgery will not be performed on a significant number of patients participating in these trials. Objective: To assess the performance and clinical utility of a convolutional neural network (CNN) in discriminating high-risk (grade III) DCIS and/or Invasive Breast Cancer (IBC) from low-risk (grade I/II) DCIS based on mammographic features. We explored whether the CNN could be used as a decision support tool, from excluding high-risk patients for active surveillance. Methods: In this single centre retrospective study, 464 patients diagnosed with DCIS based on pre-surgery biopsy between 2000 and 2014 were included. The collection of mammography images was partitioned on a patient-level into two subsets, one for training containing 80% of cases (371 cases, 681 images) and 20% (93 cases, 173 images) for testing. A deep learning model based on the U-Net CNN was trained and validated on 681 two-dimensional mammograms. Classification performance was assessed with the Area Under the Curve (AUC) receiver operating characteristic and predictive values on the test set for predicting high risk DCIS-and high-risk DCIS and/ or IBC from low-risk DCIS. Results: When classifying DCIS as high-risk, the deep learning network achieved a Positive Predictive Value (PPV) of 0.40, Negative Predictive Value (NPV) of 0.91 and an AUC of 0.72 on the test dataset. For distinguishing high-risk and/or upstaged DCIS (occult invasive breast cancer) from low-risk DCIS a PPV of 0.80, a NPV of 0.84 and an AUC of 0.76 were achieved. Conclusion: For both scenarios (DCIS grade I/II vs. III, DCIS grade I/II vs. III and/or IBC) AUCs were high, 0.72 and 0.76, respectively, concluding that our convolutional neural network can discriminate low-grade from high-grade DCIS.</p
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