Product–process matrix and complementarity approach

The relationship between different types of innovation is analysed from three different approaches. On the one hand, the distinctive view assumes that the determinants of each type of innovation are different and therefore there is no relationship between them. On the other hand, the integrative view considers that the different types of innovation are complementary. Finally, the product–process matrix framework suggests that the relationship between product innovation and process innovation is substitutive. Using data from Spain belonging to the Technological Innovation Panel (PITEC) for the years 2008, 2009, 2010, 2011 and 2012, we tested which of the three approaches is predominant. To perform the hypothesis test, we used the so-called complementarity approach. We find that there is no unique relation. The nature of the relationship depends on the types of innovation that interact. Our most significant finding is that the relationship between product innovation and process innovation is complementary. This finding contradicts the proposal of the product–process matrix framework. Consequently, the joint implementation of both types of innovation generates a greater impact on the performance of a company than the sum of their separate implementation

Caveolin-1 enhances resveratrol-mediated cytotoxicity and transport in a hepatocellular carcinoma model

<p>Abstract</p> <p>Background</p> <p>Resveratrol (RES), an estrogen analog, is considered as a potential cancer chemo-preventive agent. However, it remains unclear how RES is transported into cells. In this study, we observed that Caveolin-1(CAV1) expression can increase the cytotoxic and pro-apoptotic activity of RES in a dose- and time-dependent manner both <it>in vitro </it>and <it>in vivo </it>in a Hepatocellular Carcinoma animal model.</p> <p>Methods</p> <p>High performance liquid chromatography (HPLC) demonstrated that RES intra-cellular concentration is increased about 2-fold in cells stably expressing CAV1 or CAVM1 (a scaffolding domain (81-101AA)-defective CAV1 mutant) compared to the untransduced human Hepatoblastoma cell line (HepG2) or after transduction with the green fluorescent protein (GFP) control vector. The increased intra-cellular transport of RES was abolished in cells stably expressing CAVM2 (a cholesterol shuttle domain (143-156AA)-defective CAV1 mutant) or CAVRNAi. In order to further characterize CAV1-dependent RES transport, we synthesized RES-dansyl chloride derivatives as fluorescent probes to visualize the transport process, which demonstrated a distribution consistent with that of CAV1 in HepG2 cells.</p> <p>Results</p> <p>In addition, RES endocytosis was not mediated by estrogen receptor (ER) α and β, as suggested by lack of competitive inhibition by estrogen or Tamoxifen. Pathway analysis showed that RES can up-regulate the expression of endogenous CAV1; this activates further the MAPK pathway and caspase-3 expression.</p> <p>Discussion</p> <p>This study provides novel insights about the role played by CAV1 in modulating cellular sensitivity to RES through enhancement of its internalization and trafficking.</p

Additional psychometric data for the Spanish Modified Dental Anxiety Scale, and psychometric data for a Spanish version of the Revised Dental Beliefs Survey

<p>Abstract</p> <p>Background</p> <p>Hispanics comprise the largest ethnic minority group in the United States. Previous work with the Spanish Modified Dental Anxiety Scale (MDAS) yielded good validity, but lower test-retest reliability. We report the performance of the Spanish MDAS in a new sample, as well as the performance of the Spanish Revised Dental Beliefs Survey (R-DBS).</p> <p>Methods</p> <p>One hundred sixty two Spanish-speaking adults attending Spanish-language church services or an Hispanic cultural festival completed questionnaires containing the Spanish MDAS, Spanish R-DBS, and dental attendance questions, and underwent a brief oral examination. Church attendees completed the questionnaire a second time, for test-retest purposes.</p> <p>Results</p> <p>The Spanish MDAS and R-DBS were completed by 156 and 136 adults, respectively. The test-retest reliability of the Spanish MDAS was 0.83 (95% CI = 0.60-0.92). The internal reliability of the Spanish R-DBS was 0.96 (95% CI = 0.94-0.97), and the test-retest reliability was 0.86 (95% CI = 0.64-0.94). The two measures were significantly correlated (Spearman's rho = 0.38, p < 0.001). Participants who do not currently go to a dentist had significantly higher MDAS scores (t = 3.40, df = 106, p = 0.003) as well as significantly higher R-DBS scores (t = 2.21, df = 131, p = 0.029). Participants whose most recent dental visit was for pain or a problem, rather than for a check-up, scored significantly higher on both the MDAS (t = 3.00, df = 106, p = 0.003) and the R-DBS (t = 2.85, df = 92, p = 0.005). Those with high dental fear (MDAS score 19 or greater) were significantly more likely to have severe caries (Chi square = 6.644, df = 2, p = 0.036). Higher scores on the R-DBS were significantly related to having more missing teeth (Spearman's rho = 0.23, p = 0.009).</p> <p>Conclusion</p> <p>In this sample, the test-retest reliability of the Spanish MDAS was higher. The significant relationships between dental attendance and questionnaire scores, as well as the difference in caries severity seen in those with high fear, add to the evidence of this scale's construct validity in Hispanic samples. Our results also provide evidence for the internal and test-retest reliabilities, as well as the construct validity, of the Spanish R-DBS.</p

Phyto-oestrogens and breast cancer chemoprevention

Phytoestrogens are polyphenol compounds of plant origin that exhibit a structural similarity to the mammalian steroid hormone 17β-oestradiol. In Asian nations the staple consumption of phyto-oestrogen-rich foodstuffs correlates with a reduced incidence of breast cancer. Human dietary intervention trials have noted a direct relationship between phyto-oestrogen ingestion and a favourable hormonal profile associated with decreased breast cancer risk. However, these studies failed to ascertain the precise effect of dietary phyto-oestrogens on the proliferation of mammary tissue. Epidemiological and rodent studies crucially suggest that breast cancer chemoprevention by dietary phyto-oestrogen compounds is dependent on ingestion before puberty, when the mammary gland is relatively immature. Phyto-oestrogen supplements are commercially marketed for use by postmenopausal women as natural and safe alternatives to hormone replacement therapy. Of current concern is the effect of phyto-oestrogen compounds on the growth of pre-existing breast tumours. Data are contradictory, with cell culture studies reporting both the oestrogenic stimulation of oestrogen receptor-positive breast cancer cell lines and the antagonism of tamoxifen activity at physiological phyto-oestrogen concentrations. Conversely, phyto-oestrogen ingestion by rodents is associated with the development of less aggressive breast tumours with reduced metastatic potential. Despite the present ambiguity, current data do suggest a potential benefit from use of phyto-oestrogens in breast cancer chemoprevention and therapy. These aspects are discussed

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency–Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research

Graphics Processing Unit–Enhanced Genetic Algorithms for Solving the Temporal Dynamics of Gene Regulatory Networks

Understanding the regulation of gene expression is one of the key problems in current biology. A promising method for that purpose is the determination of the temporal dynamics between known initial and ending network states, by using simple acting rules. The huge amount of rule combinations and the nonlinear inherent nature of the problem make genetic algorithms an excellent candidate for finding optimal solutions. As this is a computationally intensive problem that needs long runtimes in conventional architectures for realistic network sizes, it is fundamental to accelerate this task. In this article, we study how to develop efficient parallel implementations of this method for the fine-grained parallel architecture of graphics processing units (GPUs) using the compute unified device architecture (CUDA) platform. An exhaustive and methodical study of various parallel genetic algorithm schemes—master-slave, island, cellular, and hybrid models, and various individual selection methods (roulette, elitist)—is carried out for this problem. Several procedures that optimize the use of the GPU’s resources are presented. We conclude that the implementation that produces better results (both from the performance and the genetic algorithm fitness perspectives) is simulating a few thousands of individuals grouped in a few islands using elitist selection. This model comprises 2 mighty factors for discovering the best solutions: finding good individuals in a short number of generations, and introducing genetic diversity via a relatively frequent and numerous migration. As a result, we have even found the optimal solution for the analyzed gene regulatory network (GRN). In addition, a comparative study of the performance obtained by the different parallel implementations on GPU versus a sequential application on CPU is carried out. In our tests, a multifold speedup was obtained for our optimized parallel implementation of the method on medium class GPU over an equivalent sequential single-core implementation running on a recent Intel i7 CPU. This work can provide useful guidance to researchers in biology, medicine, or bioinformatics in how to take advantage of the parallelization on massively parallel devices and GPUs to apply novel metaheuristic algorithms powered by nature for real-world applications (like the method to solve the temporal dynamics of GRNs)

Risk stratification for splenic marginal zone lymphoma based on hemoglobin, platelet count, high LDH level and extrahilar lymphadenopathy: development and validation on 593 cases

We report an international retrospective study of 593 Splenic Marginal Zone Lymphoma (SMZL) patients aiming to identify factors conditioning the starting of treatment and the factors influencing lymphoma-specific survival (LSS). Logistic regression was used to identify the factors associated with treatment. A Cox regression was used to analyze LSS in a training set of 366 patients. This produced a prognostic index (PI) and enabled to identify three risk groups. The resulting stratification was validated in another set of 227 patients. The present stratification was compared with the Interguppo Italiano Linfomi (IIL) score in the set of 450 patients for whom all the required data were available using an extension of the net reclassification improvement. Hemoglobin, extrahilar lymphadenopathy and HCV status were associated with the initiation of treatment. Hemoglobin, platelet count, high LDH and extrahilar lymphadenopathy were independently associated with LSS. Three risk groups with significantly different five-year LSS (94%, 78% and 69%, respectively) were identified. This stratification (named HPLL on the basis of determinant factors) had a better discriminative power than the IIL score. This system is useful to stratify SMZL patients into risk groups and may help selecting risk-tailored treatment approaches