Flexible constrained sampling with guarantees for pattern mining

Pattern sampling has been proposed as a potential solution to the infamous pattern explosion. Instead of enumerating all patterns that satisfy the constraints, individual patterns are sampled proportional to a given quality measure. Several sampling algorithms have been proposed, but each of them has its limitations when it comes to 1) flexibility in terms of quality measures and constraints that can be used, and/or 2) guarantees with respect to sampling accuracy. We therefore present Flexics, the first flexible pattern sampler that supports a broad class of quality measures and constraints, while providing strong guarantees regarding sampling accuracy. To achieve this, we leverage the perspective on pattern mining as a constraint satisfaction problem and build upon the latest advances in sampling solutions in SAT as well as existing pattern mining algorithms. Furthermore, the proposed algorithm is applicable to a variety of pattern languages, which allows us to introduce and tackle the novel task of sampling sets of patterns. We introduce and empirically evaluate two variants of Flexics: 1) a generic variant that addresses the well-known itemset sampling task and the novel pattern set sampling task as well as a wide range of expressive constraints within these tasks, and 2) a specialized variant that exploits existing frequent itemset techniques to achieve substantial speed-ups. Experiments show that Flexics is both accurate and efficient, making it a useful tool for pattern-based data exploration.Comment: Accepted for publication in Data Mining & Knowledge Discovery journal (ECML/PKDD 2017 journal track

Core components for effective infection prevention and control programmes: new WHO evidence-based recommendations

Abstract Health care-associated infections (HAI) are a major public health problem with a significant impact on morbidity, mortality and quality of life. They represent also an important economic burden to health systems worldwide. However, a large proportion of HAI are preventable through effective infection prevention and control (IPC) measures. Improvements in IPC at the national and facility level are critical for the successful containment of antimicrobial resistance and the prevention of HAI, including outbreaks of highly transmissible diseases through high quality care within the context of universal health coverage. Given the limited availability of IPC evidence-based guidance and standards, the World Health Organization (WHO) decided to prioritize the development of global recommendations on the core components of effective IPC programmes both at the national and acute health care facility level, based on systematic literature reviews and expert consensus. The aim of the guideline development process was to identify the evidence and evaluate its quality, consider patient values and preferences, resource implications, and the feasibility and acceptability of the recommendations. As a result, 11 recommendations and three good practice statements are presented here, including a summary of the supporting evidence, and form the substance of a new WHO IPC guideline

Evidence for an ependymoma tumour suppressor gene in chromosome region 22pter–22q11.2

Ependymomas are glial tumours of the brain and spinal cord. The most frequent genetic change in sporadic ependymoma is monosomy 22, suggesting the presence of an ependymoma tumour suppressor gene on that chromosome. Clustering of ependymomas has been reported to occur in some families. From an earlier study in a family in which four cousins developed an ependymoma, we concluded that an ependymoma-susceptibility gene, which is not the NF2 gene in 22q12, might be located on chromosome 22. To localize that gene, we performed a segregation analysis with chromosome 22 markers in this family. This analysis revealed that the susceptibility gene may be located proximal to marker D22S941 in 22pter–22q11.2. Comparative genomic hybridization showed that monosomy 22 was the sole detectable genetic aberration in the tumour of one of the patients. Loss of heterozygosity studies in that tumour revealed that, in accordance to Knudson’s two-hit theory of tumorigenesis, the lost chromosome 22 originated from the parent presumed to have contributed the wild-type allele of the susceptibility gene. Thus, our segregation and tumour studies collectively indicate that an ependymoma tumour suppressor gene may be present in region 22pter–22q11.2. © 1999 Cancer Research Campaig

Distinct Early Molecular Responses to Mutations Causing vLINCL and JNCL Presage ATP Synthase Subunit C Accumulation in Cerebellar Cells

Variant late-infantile neuronal ceroid lipofuscinosis (vLINCL), caused by CLN6 mutation, and juvenile neuronal ceroid lipofuscinosis (JNCL), caused by CLN3 mutation, share clinical and pathological features, including lysosomal accumulation of mitochondrial ATP synthase subunit c, but the unrelated CLN6 and CLN3 genes may initiate disease via similar or distinct cellular processes. To gain insight into the NCL pathways, we established murine wild-type and CbCln6nclf/nclf cerebellar cells and compared them to wild-type and CbCln3Δex7/8/Δex7/8 cerebellar cells. CbCln6nclf/nclf cells and CbCln3Δex7/8/Δex7/8 cells both displayed abnormally elongated mitochondria and reduced cellular ATP levels and, as cells aged to confluence, exhibited accumulation of subunit c protein in Lamp 1-positive organelles. However, at sub-confluence, endoplasmic reticulum PDI immunostain was decreased only in CbCln6nclf/nclf cells, while fluid-phase endocytosis and LysoTracker® labeled vesicles were decreased in both CbCln6nclf/nclf and CbCln3Δex7/8/Δex7/8 cells, though only the latter cells exhibited abnormal vesicle subcellular distribution. Furthermore, unbiased gene expression analyses revealed only partial overlap in the cerebellar cell genes and pathways that were altered by the Cln3Δex7/8 and Cln6nclf mutations. Thus, these data support the hypothesis that CLN6 and CLN3 mutations trigger distinct processes that converge on a shared pathway, which is responsible for proper subunit c protein turnover and neuronal cell survival

Raman spectroscopy: techniques and applications in the life sciences

Raman spectroscopy is an increasingly popular technique in many areas including biology and medicine. It is based on Raman scattering, a phenomenon in which incident photons lose or gain energy via interactions with vibrating molecules in a sample. These energy shifts can be used to obtain information regarding molecular composition of the sample with very high accuracy. Applications of Raman spectroscopy in the life sciences have included quantification of biomolecules, hyperspectral molecular imaging of cells and tissue, medical diagnosis, and others. This review briefly presents the physical origin of Raman scattering explaining the key classical and quantum mechanical concepts. Variations of the Raman effect will also be considered, including resonance, coherent, and enhanced Raman scattering. We discuss the molecular origins of prominent bands often found in the Raman spectra of biological samples. Finally, we examine several variations of Raman spectroscopy techniques in practice, looking at their applications, strengths, and challenges. This review is intended to be a starting resource for scientists new to Raman spectroscopy, providing theoretical background and practical examples as the foundation for further study and exploration

Genetic, cellular, and connectomic characterization of the brain regions commonly plagued by glioma.

For decades, it has been known that gliomas follow a non-random spatial distribution, appearing more often in some brain regions (e.g. the insula) compared to others (e.g. the occipital lobe). A better understanding of the localization patterns of gliomas could provide clues to the origins of these types of tumours, and consequently inform treatment targets. Following hypotheses derived from prior research into neuropsychiatric disease and cancer, gliomas may be expected to localize to brain regions characterized by functional hubness, stem-like cells, and transcription of genetic drivers of gliomagenesis. We combined neuroimaging data from 335 adult patients with high- and low-grade glioma to form a replicable tumour frequency map. Using this map, we demonstrated that glioma frequency is elevated in association cortex and correlated with multiple graph-theoretical metrics of high functional connectedness. Brain regions populated with putative cells of origin for glioma, neural stem cells and oligodendrocyte precursor cells, exhibited a high glioma frequency. Leveraging a human brain atlas of post-mortem gene expression, we found that gliomas were localized to brain regions enriched with expression of genes associated with chromatin organization and synaptic signalling. A set of glioma proto-oncogenes was enriched among the transcriptomic correlates of glioma distribution. Finally, a regression model incorporating connectomic, cellular, and genetic factors explained 58% of the variance in glioma frequency. These results add to previous literature reporting the vulnerability of hub regions to neurological disease, as well as provide support for cancer stem cell theories of glioma. Our findings illustrate how factors of diverse scale, from genetic to connectomic, can independently influence the anatomic localization of brain dysfunction

Balancing modularity and solution space freedom:effects on organisational learning and sustainable innovation

\u3cp\u3eMany technology-intensive (TI) firms find it challenging to leverage customisation and achieve sustainable innovation. Although some firms use modularity to tackle this challenge, mixed effects on sustainable innovation have been reported. This study uses organisational learning and ambidexterity theory to provide insights into how TI firms can achieve ‘win-win’ situations where sustainable innovation is increased through customisation. First, we argue that customisation should be viewed two-dimensionally and identify both modularity and solution space freedom as important dimensions. We argue that modularity reflects knowledge specialisation and solution space freedom reflects knowledge variety. Both of these dimensions affect organisational learning and, in turn, sustainable innovation. Second, we argue that the relationship between customisation and organisational learning is affected by supplier characteristics, specifically supplier sophistication. Survey data from 166 managers were used to empirically test the conceptual model and hypotheses. Polynomial response surface analysis confirms that customising by balancing high degrees of both modularity and solution space freedom results in superior organisational learning. High levels of supplier sophistication do not strengthen these effects. Rather, our results show that combining high degrees of modularity with constrained solution spaces increases learning for TI firms working with less sophisticated suppliers. In addition, organisational learning fully mediates the effect of customisation on sustainable product and process innovation.\u3c/p\u3