Improving SNR and reducing training time of classifiers in large datasets via kernel averaging

Kernel methods are of growing importance in neuroscience research. As an elegant extension of linear methods, they are able to model complex non-linear relationships. However, since the kernel matrix grows with data size, the training of classifiers is computationally demanding in large datasets. Here, a technique developed for linear classifiers is extended to kernel methods: In linearly separable data, replacing sets of instances by their averages improves signal-to-noise ratio (SNR) and reduces data size. In kernel methods, data is linearly non-separable in input space, but linearly separable in the high-dimensional feature space that kernel methods implicitly operate in. It is shown that a classifier can be efficiently trained on instances averaged in feature space by averaging entries in the kernel matrix. Using artificial and publicly available data, it is shown that kernel averaging improves classification performance substantially and reduces training time, even in non-linearly separable data

Human aging and somatic point mutations in mtDNA: A comparative study of generational differences (grandparents and grandchildren)

The accumulation of somatic mutations in mtDNA is correlated with aging. In this work, we sought to identify somatic mutations in the HVS-1 region (D-loop) of mtDNA that might be associated with aging. For this, we compared 31 grandmothers (mean age: 63 ± 2.3 years) and their 62 grandchildren (mean age: 15 ± 4.1 years), the offspring of their daughters. Direct DNA sequencing showed that mutations absent in the grandchildren were detected in a presumably homoplasmic state in three grandmothers and in a heteroplasmic state in an additional 13 grandmothers; no mutations were detected in the remaining 15 grandmothers. However, cloning followed by DNA sequencing in 12 grandmothers confirmed homoplasia in only one of the three mutations previously considered to be homoplasmic and did not confirm heteroplasmy in three out of nine grandmothers found to be heteroplasmic by direct sequencing. Thus, of 12 grandmothers in whom mtDNA was analyzed by cloning, eight were heteroplasmic for mutations not detected in their grandchildren. In this study, the use of genetically related subjects allowed us to demonstrate the occurrence of age-related (> 60 years old) mutations (homoplasia and heteroplasmy). It is possible that both of these situations (homoplasia and heteroplasmy) were a long-term consequence of mitochondrial oxidative phosphorylation that can lead to the accumulation of mtDNA mutations throughout life

One-year follow-up of patients of the ongoing Dutch Q fever outbreak: clinical, serological and echocardiographic findings

Contains fulltext : 89915.pdf (publisher's version ) (Open Access)PURPOSE: In 2007, a large goat-farming-associated Q fever outbreak occurred in the Netherlands. Data on the clinical outcome of Dutch Q fever patients are lacking. The current advocated follow-up strategy includes serological follow-up to detect evolution to chronic disease and cardiac screening at baseline to identify and prophylactically treat Q fever patients in case of valvulopathy. However, serological follow-up using commercially available tests is complicated by the lack of validated cut-off values. Furthermore, cardiac screening in the setting of a large outbreak has not been implemented previously. Therefore, we report here the clinical outcome, serological follow-up and cardiac screening data of the Q fever patients of the current ongoing outbreak. METHODS: The implementation of a protocol including clinical and serological follow-up at baseline and 3, 6 and 12 months after acute Q fever and screening echocardiography at baseline. RESULTS: Eighty-five patients with acute Q fever were identified (male 62%, female 38%). An aspecific, flu-like illness was the most common clinical presentation. Persistent symptoms after acute Q fever were reported by 59% of patients at 6 months and 30% at 12 months follow-up. We observed a typical serological response to Coxiella burnetii infection in both anti-phase I and anti-phase II IgG antibodies, with an increase in antibody titres up to 3 months and a subsequent decrease in the following 9 months. Screening echocardiography was available for 66 (78%) out of 85 Q fever patients. Cardiac valvulopathy was present in 39 (59%) patients. None of the 85 patients developed chronic Q fever. CONCLUSIONS: Clinical, serological and echocardiographic data of the current ongoing Dutch Q fever outbreak cohort are presented. Screening echocardiography is no longer part of the standard work-up of Q fever patients in the Netherlands.1 december 201

Increased risk of venous thrombosis by AB alleles of the ABO blood group and Factor V Leiden in a Brazilian population

Most cases of a predisposition to venous thrombosis are caused by resistance to activated protein C, associated in 95% of cases with the Factor V Leiden allele (FVL or R506Q). Several recent studies report a further increased risk of thrombosis by an association between the AB alleles of the ABO blood group and Factor V Leiden. The present study investigated this association with deep vein thrombosis (DVT) in individuals treated at the Hemocentro de Pernambuco in northeastern Brazil. A case-control comparison showed a significant risk of thrombosis in the presence of Factor V Leiden (OR = 10.1), which was approximately doubled when the AB alleles of the ABO blood group were present as well (OR = 22.3). These results confirm that the increased risk of deep vein thrombosis in the combined presence of AB alleles and Factor V Leiden is also applicable to the Brazilian population suggesting that ABO blood group typing should be routinely added to FVL in studies involving thrombosis

Physical Stress, Not Biotic Interactions, Preclude an Invasive Grass from Establishing in Forb-Dominated Salt Marshes

Biological invasions have become the focus of considerable concern and ecological research, yet the relative importance of abiotic and biotic factors in controlling the invasibility of habitats to exotic species is not well understood. Spartina species are highly invasive plants in coastal wetlands; however, studies on the factors that control the success or failure of Spartina invasions across multiple habitat types are rare and inconclusive.We examined the roles of physical stress and plant interactions in mediating the establishment of the smooth cordgrass, Spartina alterniflora, in a variety of coastal habitats in northern China. Field transplant experiments showed that cordgrass can invade mudflats and low estuarine marshes with low salinity and frequent flooding, but cannot survive in salt marshes and high estuarine marshes with hypersaline soils and infrequent flooding. The dominant native plant Suaeda salsa had neither competitive nor facilitative effects on cordgrass. A common garden experiment revealed that cordgrass performed significantly better when flooded every other day than when flooded weekly. These results suggest that physical stress rather than plant interactions limits cordgrass invasions in northern China.We conclude that Spartina invasions are likely to be constrained to tidal flats and low estuarine marshes in the Yellow River Delta. Due to harsh physical conditions, salt marshes and high estuarine marshes are unlikely to be invaded. These findings have implications for understanding Spartina invasions in northern China and on other coasts with similar biotic and abiotic environments

Impacts of climate change on plant diseases – opinions and trends

There has been a remarkable scientific output on the topic of how climate change is likely to affect plant diseases in the coming decades. This review addresses the need for review of this burgeoning literature by summarizing opinions of previous reviews and trends in recent studies on the impacts of climate change on plant health. Sudden Oak Death is used as an introductory case study: Californian forests could become even more susceptible to this emerging plant disease, if spring precipitations will be accompanied by warmer temperatures, although climate shifts may also affect the current synchronicity between host cambium activity and pathogen colonization rate. A summary of observed and predicted climate changes, as well as of direct effects of climate change on pathosystems, is provided. Prediction and management of climate change effects on plant health are complicated by indirect effects and the interactions with global change drivers. Uncertainty in models of plant disease development under climate change calls for a diversity of management strategies, from more participatory approaches to interdisciplinary science. Involvement of stakeholders and scientists from outside plant pathology shows the importance of trade-offs, for example in the land-sharing vs. sparing debate. Further research is needed on climate change and plant health in mountain, boreal, Mediterranean and tropical regions, with multiple climate change factors and scenarios (including our responses to it, e.g. the assisted migration of plants), in relation to endophytes, viruses and mycorrhiza, using long-term and large-scale datasets and considering various plant disease control methods

Shared decision‐making and maternity care in the deep learning age: Acknowledging and overcoming inherited defeaters

In recent years there has been an explosion of interest in Artificial Intelligence (AI) both in health care and academic philosophy. This has been due mainly to the rise of effective machine learning and deep learning algorithms, together with increases in data collection and processing power, which have made rapid progress in many areas. However, use of this technology has brought with it philosophical issues and practical problems, in particular, epistemic and ethical. In this paper the authors, with backgrounds in philosophy, maternity care practice and clinical research, draw upon and extend a recent framework for shared decision‐making (SDM) that identified a duty of care to the client's knowledge as a necessary condition for SDM. This duty entails the responsibility to acknowledge and overcome epistemic defeaters. This framework is applied to the use of AI in maternity care, in particular, the use of machine learning and deep learning technology to attempt to enhance electronic fetal monitoring (EFM). In doing so, various sub‐kinds of epistemic defeater, namely, transparent, opaque, underdetermined, and inherited defeaters are taxonomized and discussed. The authors argue that, although effective current or future AI‐enhanced EFM may impose an epistemic obligation on the part of clinicians to rely on such systems' predictions or diagnoses as input to SDM, such obligations may be overridden by inherited defeaters, caused by a form of algorithmic bias. The existence of inherited defeaters implies that the duty of care to the client's knowledge extends to any situation in which a clinician (or anyone else) is involved in producing training data for a system that will be used in SDM. Any future AI must be capable of assessing women individually, taking into account a wide range of factors including women's preferences, to provide a holistic range of evidence for clinical decision‐making