Hospitals as innovators in the health-care system: a literature review and research agenda

This paper aims to improve understanding of the role of hospitals in the generation of innovations. It presents a systematic and critical review of the interdisciplinary literature that addresses the links between the activities of hospitals and medical innovation. It identifies three major research streams: studies of the contribution of medical research and clinical staff to innovation, analyses of novel practices developed and diffused in hospitals, and evolutionary studies of technical change in the context of human health care. This is a highly heterogeneous body of literature, in which comprehensive theoretical frameworks are rare, and empirical studies have tended to focus on a narrow range of hospitals' innovation activities. The paper introduces and discusses a framework integrating different perspectives that can be used to analyze the functions performed by hospitals at the intersection with different partners in the health innovation system and at different stages of innovation trajectories. On the basis of current gaps in the literature, a research agenda is discussed for a relational and co-evolutionary approach to the study of hospitals as innovators.Research for this article was funded by the Research Council of Norway under the project “Synergies and tensions in innovation in the life sciences,” as well as by the South-Eastern Norway Regional Health Authority and the University of Oslo

Scaling of the conductance in gold nanotubes

A new form of gold nanobridges has been recently observed in ultrahigh-vacuum experiments, where the gold atoms rearrange to build helical nanotubes, akin in some respects to carbon nanotubes. The good reproducibility of these wires and their unexpected stability will allow for conductance measurements and make them promising candidates for future applications . We present here a study of the transport properties of these nanotubes in order to understand the role of chirality and of the different orbitals in quantum transport observables. The conductance per atomic row shows a light decreasing trend as the diameter grows, which is also shown through an analytical formula based on a one-orbital model.Comment: 5 pages, 6 figure

Surface induced selective delamination of amphiphilic ABA block copolymer thin films

This is the result of an ongoing collaboration with Dr. N. Sommerdijk’s Biomaterials group at the University of Eindhoven (the Netherlands) and illustrates the close collaboration that exists in pursuing the design and application of novel polymeric materials between the two groups. This details work on a physical phenomenon (selective delamination) and key materials (amphiphilic block copolymers) that have subsequently been applied in the design of novel biomaterials. These results have appeared in a larger body of work including Advanced Materials, Angewandtie Chemie International Edition and the Journal of Materials Chemistry

KNN-Based ML Model for the Symbol Prediction in TCM Trellis Coded Modulation TCM Decoder

Machine Learning is a booming technology today. In a machine learning set of training, data is to be provided to the model for training and that model predicts the output. Machine Learning models are trained using a computer program known as ML algorithms.The new machine learning-based Transition Metric Unit (TMU) of 4D- 8PSK Trellis coded Modulation TCM Decoder is presented in this work. The classic Viterbi decoder's branch metric unit, or TMU, takes on a complex structure. Trellis coded Modulation (TCM) is a combination of 8 PSK modulations and Error Correcting Code (ECC). TMU is one of the complex units of the TCM decoder, which is essentially a Viterbi decoder. Similar to how the first Branch metric is determined in the straightforward Viterbi decoder, the TCM decoder performs this BM computation via the TMU unit. The TMU becomes challenging and uses more dynamic power as a result of the enormous constraint length and the vast number of encoder states.In the proposed algorithm innovative KNN (K nearest neighbours) based ML model is developed. It is a supervised learning model in which input and output both are provided to the model, training data also called the labels, when a new set of data will come the model will give output based on its previous set experience and data.Here we are using this ML model for the symbol prediction at the receiver end of the TCM decoder based on the previous learning. Using the proposed innovation, the paper perceives the optimization of the TCM Decoder which will further reduce the H/W requirements and low latency which results in less power consumption

State of Art of meat inspection of pigs in the EU

The current meat inspection in the European Union (EU) is based on principles that are around 100 years old. However, the zoonotic hazards have shifted and the production systems for livestock are changing. This makes it necessary to look at whether the present way of conducting meat inspection is efficient or not

A factor analysis approach to examining relationships among ovarian steroid concentrations, gonadotrophin concentrations and menstrual cycle length characteristics in healthy, cycling women

STUDY QUESTION: How are ovarian steroid concentrations, gonadotrophins and menstrual cycle characteristics inter-related within normal menstrual cycles? SUMMARY ANSWER: Within cycles, measures of estradiol production are highly related to one another, as are measures of progesterone production; however, the two hormones also show some independence from one another, and measures of cycle length and gonadotrophin concentrations show even greater independence, indicating minimal integration within cycles. WHAT IS KNOWN ALREADY: The menstrual cycle is typically conceptualized as a cohesive unit, with hormone levels, follicular development and ovulation all closely inter-related within a single cycle. Empirical support for this idea is limited, however, and to our knowledge, no analysis has examined the relationships among all of these components simultaneously. STUDY DESIGN, SIZE, DURATION: A total of 206 healthy, cycling Norwegian women participated in a prospective cohort study (EBBA-I) over the duration of a single menstrual cycle. Of these, 192 contributed hormonal and cycle data to the current analysis. PARTICIPANTS/MATERIALS, SETTING, METHODS: Subjects provided daily saliva samples throughout the menstrual cycle from which estradiol and progesterone concentrations were measured. FSH and LH concentrations were measured in serum samples from three points in the same menstrual cycle and cycle length characteristics were calculated based on hormonal data and menstrual records. A factor analysis was conducted to examine the underlying relationships among 22 variables derived from the hormonal data and menstrual cycle characteristics. MAIN RESULTS AND THE ROLE OF CHANCE: Six rotated factors emerged, explaining 80% of the variance in the data. Of these, factors representing estradiol and progesterone concentrations accounted for 37 and 13% of the variance, respectively. There was some association between measures of estradiol and progesterone production within cycles; however, cycle length characteristics and gonadotrophin concentrations showed little association with any measure of ovarian hormone concentrations. LIMITATIONS, REASONS FOR CAUTION: Our summary measures of ovarian hormones may be imprecise in women with extremely long or short cycles, which could affect the patterns emerging in the factor analysis. Given that we only had data from one cycle on each woman, we cannot address how cycle characteristics may covary within individual women across multiple cycles. WIDER IMPLICATIONS OF THE FINDINGS: Our findings are generalizable to other healthy populations with typical cycles, however, may not be applicable to cycles that are anovulatory, extreme in length or otherwise atypical. The results support previous findings that measures of estradiol production are highly correlated across the cycle, as are measures of progesterone production. Estradiol and progesterone concentrations are associated with one another, furthermore. However factor analysis also revealed more complex underlying patterns in the menstrual cycle, highlighting the fact that gonadotrophin concentrations and cycle length characteristics are virtually independent of ovarian hormones. These results suggest that despite integration of follicular and luteal ovarian steroid production across the cycle, cycle quality is a multi-faceted construct, rather than a single dimension. STUDY FUNDING/COMPETING INTEREST(S): The EBBA-I study was supported by a grant from the Norwegian Cancer Society (49 258, 05087); Foundation for the Norwegian Health and Rehabilitation Organizations (59010-2000/2001/2002); Aakre Foundation (5695-2000, 5754-2002) and Health Region East. The current analyses were completed under funding from the National Institutes of Health (K12 ES019852). No competing interests declared.Anthropolog

Hofstadter butterflies of carbon nanotubes: Pseudofractality of the magnetoelectronic spectrum

The electronic spectrum of a two-dimensional square lattice in a perpendicular magnetic field has become known as the Hofstadter butterfly [Hofstadter, Phys. Rev. B 14, 2239 (1976).]. We have calculated quasi-one-dimensional analogs of the Hofstadter butterfly for carbon nanotubes (CNTs). For the case of single-wall CNTs, it is straightforward to implement magnetic fields parallel to the tube axis by means of zone folding in the graphene reciprocal lattice. We have also studied perpendicular magnetic fields which, in contrast to the parallel case, lead to a much richer, pseudofractal spectrum. Moreover, we have investigated magnetic fields piercing double-wall CNTs and found strong signatures of interwall interaction in the resulting Hofstadter butterfly spectrum, which can be understood with the help of a minimal model. Ubiquitous to all perpendicular magnetic field spectra is the presence of cusp catastrophes at specific values of energy and magnetic field. Resolving the density of states along the tube circumference allows recognition of the snake states already predicted for nonuniform magnetic fields in the two-dimensional electron gas. An analytic model of the magnetic spectrum of electrons on a cylindrical surface is used to explain some of the results.Comment: 14 pages, 12 figures update to published versio

17-beta-Estradiol in relation to age at menarche and adult obesity in premenopausal women

BACKGROUND: We hypothesize that premenopausal endogenous estradiol may be associated with age at menarche and adult overweight and obesity, potentially contributing to breast cancer risk. METHODS: We assessed age at menarche by questionnaire among 204 healthy Norwegian women, aged 25 – 35 years. Measures of body composition included body mass index (BMI, kg/m2), waist circumference (WC, cm), waist-to-hip ratio (WHR) and fat percentage dual energy X-ray absorptiometry, (DEXA). Daily salivary 17-b-estradiol (E2) concentrations were collected throughout one entire menstrual cycle and assessed by radioimmunoassay (RIA). Linear regression analyses and linear mixed models for repeated measures were used and potential confounding factors and effect modifiers were tested. RESULTS: Among women with an early age at menarche (12 years), the overall mean salivary E2 concentration increased by 3.7 pmol/l (95% confidence interval, 1.8 – 5.7 pmol/l) with each 9.8 cm (1 SD) increase in WC, which represents a 20.7% change in the mean for the total group. Among the same early maturers, a 1 SD (0.06) change in WHR was directly associated with a 24.0% change in mean E2 concentration for the total group. CONCLUSIONS: Our findings support the hypothesis that early age at menarche, together with adult overweight and obesity, result in high levels of 17-b-estradiol throughout the menstrual cycle.AnthropologyHuman Evolutionary Biolog

Adult Height, Insulin Levels and 17β-Estradiol in Young Women

Background: Adult height and insulin levels have independently been associated with breast cancer risk. However, little is known about whether these factors influence estradiol levels. Thus, we hypothesize that adult height in combination with insulin levels may influence premenopausal 17β-estradiol throughout the entire menstrual cycle of possible importance of breast cancer risk. Methods: Among 204 healthy women, aged 25-35 years who participated in the Norwegian EBBA I study, birth weight and age at menarche were assessed by questionnaire, personal health record and interview. 17β-estradiol concentrations were estimated by daily saliva samples throughout one entire menstrual cycle using radioimmunoassay (RIA). Measures of height (cm) were taken as well as waist circumference (cm), body mass index (BMI kg/m2) and total fat percentage (DEXA % fat). Fasting blood samples were drawn, and serum concentrations of insulin were determined. Results: The women reported a mean height of 166.5 cm, birth weight of 3389 g and age at menarche 13.1 years. Mean BMI was 24.4 kg/m2, mean waist circumference 79.5 cm and mean total fat percentage 34.1%. Women with an adult height of more than 170 cm and insulin levels higher than 90 pmol/L experienced on average an 37.2 % increase in 17β- estradiol during an entire menstrual cycle compared to those with the same height, and insulin levels below 90 pmol/L. Moreover, this was also observed throughout the entire menstrual cycle. Conclusion: Our findings support that premenopausal levels of 17β-estradiol vary in response to adult height and insulin levels, suggesting that women who become taller are put at risk for higher estradiol levels when their insulin levels rise of possible importance for breast cancer risk.Anthropolog

Exploring the effects of lifestyle on breast cancer risk, age at diagnosis, and survival: the EBBA-Life study

Purpose - Whether an unfavorable lifestyle not only affects breast cancer risk, but also influences age at onset of breast cancer and survival, is under debate. Methods - In a population-based cohort, the Energy Balance and Breast Cancer Aspects throughout life (EBBA-Life) study, a total of 17,145 women were included. During follow-up, 574 women developed invasive breast cancer. Breast cancer cases were followed for an additional 9.1 years. Detailed medical records were obtained. Cox’s proportional hazard regression models were used to study the association between pre-diagnostic lifestyle factors (weight, physical activity, alcohol use, smoking, and hypertension), breast cancer risk, age at diagnosis, and survival. Results - At study entry, 34.3% of the participating women were overweight and 30.7% were physically inactive. Mean age at breast cancer diagnosis was 58.0 years, and 78.9% of the tumors were estrogen receptor positive. Among menopausal women who did not use hormone therapy and had an unfavorable lifestyle (3–5 unfavorable factors), compared with women who had a favorable lifestyle, we observed a twofold higher risk for postmenopausal breast cancer (hazard ratio [HR] 2.13, 95% confidence interval [CI] 1.23–3.69), and they were 3.4 years younger at diagnosis (64.8 versus 68.2 years, P = 0.032). Breast cancer patients with an unfavorable lifestyle, compared with patients with a favorable lifestyle, had almost a two times higher overall mortality risk (HR 1.96, 95% CI 1.01–3.80). Conclusions - Our study supports a healthy lifestyle improving breast cancer prevention, postponing onset of disease, and extending life expectancy among breast cancer patients