On the size of binary decision diagrams representing Boolean functions

AbstractWe consider the size of the representation of Boolean functions by several classes of binary decision diagrams (BDDs) (also called branching programs), namely the classes of arbitrary BDDs of real time BDD (RBDD) (i.e. BDDs where each computation path is limited to the number of variables), of free BDDs (FBDDs) (also called read-once-only branching programs), of ordered BDDs (OBDDS) i.e. FBDDs where variables are tested in the same order along all paths), and binary decision trees (BDTs).Using well-known techniques, we first establish asymptotically sharp bounds as a function of n on the minimum size of arbitrary BDDs representing almost all Boolean functions of n variables and provide asymptotic lower and upper bounds, differing only by a factor of two, on the minimum size OBDDs representing almost all Boolean functions of n variables.We then, using a method to obtain exponential lower bounds on complexity of computation of Boolean functions by RBDD, FBDD and OBDD that originated in (Breitbart, 1968), present the highest such bounds to date and also present improved bounds on the relative economy of description of particular Boolean functions by the above classes of BDDs. For each nontrivial pair of BDD classes considered, we exhibit infinite families of Boolean functions representable much more concisely by BDDs in one class than by BDDs in the other

Plant Virus Biodiversity and Ecology

The Plant Virus Biodiversity and Ecology (PVBE) project has been initiated to survey the biodiversity of viruses affecting vascular plants

Death ideation in cancer patients: contributing factors

Advances in cancer research and therapy have improved prognosis and the quality of life of many patients. However, previous epidemiological studies in oncologic patients have shown an increased risk of suicide. Suicidal thoughts, relatively well known in those terminally ill, may be just as important for cancer patients who are survivors or are living with the disease. Nonetheless, there is a relative paucity of data about suicidality in this setting. The authors conducted a prospective observational study to identify death thoughts and to explore the factors associated with suicidal ideation in cancer patients. A sample of 130 patients referred for psychiatric consultation was obtained following informed consent and authorization from the local ethics committee. A semistructured interview assessed sociodemographic data, psychosocial support, and information regarding the cancer process and its treatment. Psychometric instruments were used to evaluate psychopathology, namely the Hospital Anxiety and Depression Scale, the Beck Hopelessness Scale, and the Beck Scale for Suicide Ideation. Psychiatric diagnoses were obtained through the application of the Mini International Neuropsychiatric Interview. Death ideation was identified in 34.6% of patients, yet only 10% had active suicidal thoughts. Risk of suicide was associated with female gender, a psychiatric diagnosis (major depressive disorder, panic disorder, or dysthymia), difficult interpersonal relationships, associated pain, high hopelessness, and depressive and anxiety symptoms. Although suicidal thoughts are frequent in cancer patients at different stages of disease, most are transitory. Risk factors for suicidal ideation have been identified, such as depression, hopelessness, uncontrolled pain, and difficult interpersonal relationships. Further assessment is necessary to identify those at higher risk of attempting suicide, and underlying psychiatric disorders should be vigorously treated

Occupancy Modeling, Maximum Contig Size Probabilities and Designing Metagenomics Experiments

Mathematical aspects of coverage and gaps in genome assembly have received substantial attention by bioinformaticians. Typical problems under consideration suppose that reads can be experimentally obtained from a single genome and that the number of reads will be set to cover a large percentage of that genome at a desired depth. In metagenomics experiments genomes from multiple species are simultaneously analyzed and obtaining large numbers of reads per genome is unlikely. We propose the probability of obtaining at least one contig of a desired minimum size from each novel genome in the pool without restriction based on depth of coverage as a metric for metagenomic experimental design. We derive an approximation to the distribution of maximum contig size for single genome assemblies using relatively few reads. This approximation is verified in simulation studies and applied to a number of different metagenomic experimental design problems, ranging in difficulty from detecting a single novel genome in a pool of known species to detecting each of a random number of novel genomes collectively sized and with abundances corresponding to given distributions in a single pool

Characterization of virus-like particles associated with the human faecal and caecal microbiota

This work represents an investigation into the presence, abundance and diversity of virus-like particles (VLPs) associated with human faecal and caecal samples. Various methodologies for the recovery of VLPs from faeces were tested and optimized, including successful down-stream processing of such samples for the purpose of an in-depth electron microscopic analysis, pulsed-field gel electrophoresis and efficient DNA recovery. The applicability of the developed VLP characterization method beyond the use of faecal samples was then verified using samples obtained from human caecal fluid

The attitudes of brain cancer patients and their caregivers towards death and dying: a qualitative study

<p>Abstract</p> <p>Background</p> <p>Much money and energy has been spent on the study of the molecular biology of malignant brain tumours. However, little attention has been paid to the wishes of patients afflicted with these incurable tumours, and how this might influence treatment considerations.</p> <p>Methods</p> <p>We interviewed 29 individuals – 7 patients dying of a malignant brain tumor and 22 loved ones. One-on-one interviews were conducted according to a pre-designed interview guide. A combination of open-ended questions, as well as clinical scenarios was presented to participants in order to understand what is meaningful and valuable to them when determining treatment options and management approaches. The results were analyzed, coded, and interpreted using qualitative analytic techniques in order to arrive at several common overarching themes.</p> <p>Results</p> <p>Seven major themes were identified. In general, respondents were united in viewing brain cancer as unique amongst malignancies, due in large part to the premium placed on mental competence and cognitive functioning. Importantly, participants found their experiences, however difficult, led to the discovery of inner strength and resilience. Responses were usually framed within an interpersonal context, and participants were generally grateful for the opportunity to speak about their experiences. Attitudes towards religion, spirituality, and euthanasia were also probed.</p> <p>Conclusion</p> <p>Several important themes underlie the experiences of brain cancer patients and their caregivers. It is important to consider these when managing these patients and to respect not only their autonomy but also the complex interpersonal toll that a malignant diagnosis can have.</p

Viral population estimation using pyrosequencing

The diversity of virus populations within single infected hosts presents a major difficulty for the natural immune response as well as for vaccine design and antiviral drug therapy. Recently developed pyrophosphate based sequencing technologies (pyrosequencing) can be used for quantifying this diversity by ultra-deep sequencing of virus samples. We present computational methods for the analysis of such sequence data and apply these techniques to pyrosequencing data obtained from HIV populations within patients harboring drug resistant virus strains. Our main result is the estimation of the population structure of the sample from the pyrosequencing reads. This inference is based on a statistical approach to error correction, followed by a combinatorial algorithm for constructing a minimal set of haplotypes that explain the data. Using this set of explaining haplotypes, we apply a statistical model to infer the frequencies of the haplotypes in the population via an EM algorithm. We demonstrate that pyrosequencing reads allow for effective population reconstruction by extensive simulations and by comparison to 165 sequences obtained directly from clonal sequencing of four independent, diverse HIV populations. Thus, pyrosequencing can be used for cost-effective estimation of the structure of virus populations, promising new insights into viral evolutionary dynamics and disease control strategies.Comment: 23 pages, 13 figure

Exploring the Diversity of Plant DNA Viruses and Their Satellites Using Vector-Enabled Metagenomics on Whiteflies

Current knowledge of plant virus diversity is biased towards agents of visible and economically important diseases. Less is known about viruses that have not caused major diseases in crops, or viruses from native vegetation, which are a reservoir of biodiversity that can contribute to viral emergence. Discovery of these plant viruses is hindered by the traditional approach of sampling individual symptomatic plants. Since many damaging plant viruses are transmitted by insect vectors, we have developed “vector-enabled metagenomics” (VEM) to investigate the diversity of plant viruses. VEM involves sampling of insect vectors (in this case, whiteflies) from plants, followed by purification of viral particles and metagenomic sequencing. The VEM approach exploits the natural ability of highly mobile adult whiteflies to integrate viruses from many plants over time and space, and leverages the capability of metagenomics for discovering novel viruses. This study utilized VEM to describe the DNA viral community from whiteflies (Bemisia tabaci) collected from two important agricultural regions in Florida, USA. VEM successfully characterized the active and abundant viruses that produce disease symptoms in crops, as well as the less abundant viruses infecting adjacent native vegetation. PCR assays designed from the metagenomic sequences enabled the complete sequencing of four novel begomovirus genome components, as well as the first discovery of plant virus satellites in North America. One of the novel begomoviruses was subsequently identified in symptomatic Chenopodium ambrosiodes from the same field site, validating VEM as an effective method for proactive monitoring of plant viruses without a priori knowledge of the pathogens. This study demonstrates the power of VEM for describing the circulating viral community in a given region, which will enhance our understanding of plant viral diversity, and facilitate emerging plant virus surveillance and management of viral diseases