Grounding, Analysis, and Russellian Monism

Few these days dispute that the knowledge argument demonstrates an epistemic gap between the physical facts and the facts about experience. It is much more contentious whether that epistemic gap can be used to demonstrate a metaphysical gap of a kind that is inconsistent with physicalism. In this paper I will explore two attempts to block the inference from an epistemic gap to a metaphysical gap – the first from the phenomenal concept strategy, the second from Russellian monism – and suggest how the proponent of the knowledge argument might respond to each of these challenges. In doing so, I will draw on recent discussions of grounding and essence in the metaphysics literature

Mary's Powers of Imagination

One common response to the knowledge argument is the ability hypothesis. Proponents of the ability hypothesis accept that Mary learns what seeing red is like when she exits her black-and-white room, but they deny that the kind of knowledge she gains is propositional in nature. Rather, she acquires a cluster of abilities that she previously lacked, in particular, the abilities to recognize, remember, and imagine the color red. For proponents of the ability hypothesis, knowing what an experience is like simply consists in the possession of these abilities. Criticisms of the ability hypothesis tend to focus on this last claim. Such critics tend to accept that Mary gains these abilities when she leaves the room, but they deny that such abilities constitute knowledge of what an experience is like. To my mind, however, this critical strategy grants too much. Focusing specifically on imaginative ability, I argue that Mary does not gain this ability when she leaves the room for she already had the ability to imagine red while she was inside it. Moreover, despite what some have thought, the ability hypothesis cannot be easily rescued by recasting it in terms of a more restrictive imaginative ability. My purpose here is not to take sides in the debate about physicalism, i.e., my criticism of the ability hypothesis is not offered in an attempt to defend the anti-physicalist conclusion of the knowledge argument. Rather, my purpose is to redeem the imagination from the misleading picture of it that discussion of the knowledge argument has fostered

Heart rate variability and target organ damage in hypertensive patients

Background: We evaluated the association between linear standard Heart Rate Variability (HRV) measures and vascular, renal and cardiac target organ damage (TOD). Methods: A retrospective analysis was performed including 200 patients registered in the Regione Campania network (aged 62.4 ± 12, male 64%). HRV analysis was performed by 24-h holter ECG. Renal damage was assessed by estimated glomerular filtration rate (eGFR), vascular damage by carotid intima-media thickness (IMT), and cardiac damage by left ventricular mass index. Results: Significantly lower values of the ratio of low to high frequency power (LF/HF) were found in the patients with moderate or severe eGFR (p-value < 0.001). Similarly, depressed values of indexes of the overall autonomic modulation on heart were found in patients with plaque compared to those with a normal IMT (p-value <0.05). These associations remained significant after adjustment for other factors known to contribute to the development of target organ damage, such as age. Moreover, depressed LF/HF was found also in patients with left ventricular hypertrophy but this association was not significant after adjustment for other factors. Conclusions: Depressed HRV appeared to be associated with vascular and renal TOD, suggesting the involvement of autonomic imbalance in the TOD. However, as the mechanisms by which abnormal autonomic balance may lead to TOD, and, particularly, to renal organ damage are not clearly known, further prospective studies with longitudinal design are needed to determine the association between HRV and the development of TOD

Response to androgen therapy in patients with dyskeratosis congenita

Dyskeratosis congenita (DC) is an inherited bone marrow failure syndrome and telomere biology disorder characterized by dysplastic nails, reticular skin pigmentation and oral leucoplakia. Androgens are a standard therapeutic option for bone marrow failure in those patients with DC who are unable to undergo haematopoietic stem cell transplantation, but there are no systematic data on its use in those patients. We evaluated haematological response and side effects of androgen therapy in 16 patients with DC in our observational cohort study. Untreated DC patients served as controls. Seventy percent of treated DC patients had a haematological response with red blood cell and/or platelet transfusion independence. The expected age-related decline in telomere length was noted in androgen-treated patients. All treated DC patients had at least one significant lipid abnormality. Additional treatment-related findings included a significant decrease in thyroid binding globulin, accelerated growth in pre-pubertal children and splenic peliosis in two patients. Liver enzymes were elevated in both androgen-treated and untreated patients, suggesting underlying liver involvement in DC. This study suggests that androgen therapy can be effectively used to treat bone marrow failure in DC, but that side effects need to be closely monitored

Robust Detection of Hierarchical Communities from Escherichia coli Gene Expression Data

Determining the functional structure of biological networks is a central goal of systems biology. One approach is to analyze gene expression data to infer a network of gene interactions on the basis of their correlated responses to environmental and genetic perturbations. The inferred network can then be analyzed to identify functional communities. However, commonly used algorithms can yield unreliable results due to experimental noise, algorithmic stochasticity, and the influence of arbitrarily chosen parameter values. Furthermore, the results obtained typically provide only a simplistic view of the network partitioned into disjoint communities and provide no information of the relationship between communities. Here, we present methods to robustly detect coregulated and functionally enriched gene communities and demonstrate their application and validity for Escherichia coli gene expression data. Applying a recently developed community detection algorithm to the network of interactions identified with the context likelihood of relatedness (CLR) method, we show that a hierarchy of network communities can be identified. These communities significantly enrich for gene ontology (GO) terms, consistent with them representing biologically meaningful groups. Further, analysis of the most significantly enriched communities identified several candidate new regulatory interactions. The robustness of our methods is demonstrated by showing that a core set of functional communities is reliably found when artificial noise, modeling experimental noise, is added to the data. We find that noise mainly acts conservatively, increasing the relatedness required for a network link to be reliably assigned and decreasing the size of the core communities, rather than causing association of genes into new communities.Comment: Due to appear in PLoS Computational Biology. Supplementary Figure S1 was not uploaded but is available by contacting the author. 27 pages, 5 figures, 15 supplementary file

Batch effect confounding leads to strong bias in performance estimates obtained by cross-validation.

BACKGROUND: With the large amount of biological data that is currently publicly available, many investigators combine multiple data sets to increase the sample size and potentially also the power of their analyses. However, technical differences ("batch effects") as well as differences in sample composition between the data sets may significantly affect the ability to draw generalizable conclusions from such studies. FOCUS: The current study focuses on the construction of classifiers, and the use of cross-validation to estimate their performance. In particular, we investigate the impact of batch effects and differences in sample composition between batches on the accuracy of the classification performance estimate obtained via cross-validation. The focus on estimation bias is a main difference compared to previous studies, which have mostly focused on the predictive performance and how it relates to the presence of batch effects. DATA: We work on simulated data sets. To have realistic intensity distributions, we use real gene expression data as the basis for our simulation. Random samples from this expression matrix are selected and assigned to group 1 (e.g., 'control') or group 2 (e.g., 'treated'). We introduce batch effects and select some features to be differentially expressed between the two groups. We consider several scenarios for our study, most importantly different levels of confounding between groups and batch effects. METHODS: We focus on well-known classifiers: logistic regression, Support Vector Machines (SVM), k-nearest neighbors (kNN) and Random Forests (RF). Feature selection is performed with the Wilcoxon test or the lasso. Parameter tuning and feature selection, as well as the estimation of the prediction performance of each classifier, is performed within a nested cross-validation scheme. The estimated classification performance is then compared to what is obtained when applying the classifier to independent data

Research on information systems failures and successes: Status update and future directions

The final publication is available at Springer via http://dx.doi.org/10.1007/s10796-014-9500-yInformation systems success and failure are among the most prominent streams in IS research. Explanations of why some IS fulfill their expectations, whereas others fail, are complex and multi-factorial. Despite the efforts to understand the underlying factors, the IS failure rate remains stubbornly high. A Panel session was held at the IFIP Working Group 8.6 conference in Bangalore in 2013 which forms the subject of this Special Issue. Its aim was to reflect on the need for new perspectives and research directions, to provide insights and further guidance for managers on factors enabling IS success and avoiding IS failure. Several key issues emerged, such as the need to study problems from multiple perspectives, to move beyond narrow considerations of the IT artifact, and to venture into underexplored organizational contexts, such as the public sector. © 2014 Springer Science+Business Media New York

Lack of Protection following Passive Transfer of Polyclonal Highly Functional Low-Dose Non-Neutralizing Antibodies

Recent immune correlates analysis from the RV144 vaccine trial has renewed interest in the role of non-neutralizing antibodies in mediating protection from infection. While neutralizing antibodies have proven difficult to induce through vaccination, extra-neutralizing antibodies, such as those that mediate antibody-dependent cellular cytotoxicity (ADCC), are associated with long-term control of infection. However, while several non-neutralizing monoclonal antibodies have been tested for their protective efficacy in vivo, no studies to date have tested the protective activity of naturally produced polyclonal antibodies from individuals harboring potent ADCC activity. Because ADCC-inducing antibodies are highly enriched in elite controllers (EC), we passively transferred highly functional non-neutralizing polyclonal antibodies, purified from an EC, to assess the potential impact of polyclonal non-neutralizing antibodies on a stringent SHIV-SF162P3 challenge in rhesus monkeys. Passive transfer of a low-dose of ADCC inducing antibodies did not protect from infection following SHIV-SF162P3 challenge. Passively administered antibody titers and gp120-specific, but not gp41-specific, ADCC and antibody induced phagocytosis (ADCP) were detected in the majority of the monkeys, but did not correlate with post infection viral control. Thus these data raise the possibility that gp120-specific ADCC activity alone may not be sufficient to control viremia post infection but that other specificities or Fc-effector profiles, alone or in combination, may have an impact on viral control and should be tested in future passive transfer experiments

The inference of gray whale (Eschrichtius robustus) historical population attributes from whole-genome sequences

Commercial whaling caused extensive demographic declines in many great whale species, including gray whales that were extirpated from the Atlantic Ocean and dramatically reduced in the Pacific Ocean. The Eastern Pacific gray whale has recovered since the 1982 ban on commercial whaling, but the Western Pacific gray whale-once considered possibly extinct-consists of only about 200 individuals and is considered critically endangered by some international authorities. Herein, we use whole-genome sequencing to investigate the demographic history of gray whales from the Pacific and use environmental niche modelling to make predictions about future gene flow.Our sequencing efforts and habitat niche modelling indicate that: i) western gray whale effective population sizes have declined since the last glacial maximum; ii) contemporary gray whale genomes, both eastern and western, harbor less autosomal nucleotide diversity than most other marine mammals and megafauna; iii) the extent of inbreeding, as measured by autozygosity, is greater in the Western Pacific than in the Eastern Pacific populations; and iv) future climate change is expected to open new migratory routes for gray whales.Our results indicate that gray whale genomes contain low nucleotide diversity and have been subject to both historical and recent inbreeding. Population sizes over the last million years likely peaked about 25,000 years before present and have declined since then. Our niche modelling suggests that novel migratory routes may develop within the next century and if so this could help retain overall genetic diversity, which is essential for adaption and successful recovery in light of global environmental change and past exploitation