Improved model identification for non-linear systems using a random subsampling and multifold modelling (RSMM) approach

In non-linear system identification, the available observed data are conventionally partitioned into two parts: the training data that are used for model identification and the test data that are used for model performance testing. This sort of 'hold-out' or 'split-sample' data partitioning method is convenient and the associated model identification procedure is in general easy to implement. The resultant model obtained from such a once-partitioned single training dataset, however, may occasionally lack robustness and generalisation to represent future unseen data, because the performance of the identified model may be highly dependent on how the data partition is made. To overcome the drawback of the hold-out data partitioning method, this study presents a new random subsampling and multifold modelling (RSMM) approach to produce less biased or preferably unbiased models. The basic idea and the associated procedure are as follows. First, generate K training datasets (and also K validation datasets), using a K-fold random subsampling method. Secondly, detect significant model terms and identify a common model structure that fits all the K datasets using a new proposed common model selection approach, called the multiple orthogonal search algorithm. Finally, estimate and refine the model parameters for the identified common-structured model using a multifold parameter estimation method. The proposed method can produce robust models with better generalisation performance

Availability, formulation, labelling, and price of low-sodium salts worldwide

BACKGROUND: Regular salt is about 100% sodium chloride (NaCl). Low-sodium salts have reduced sodium chloride content, most commonly through substitution with potassium chloride (KCl). Low-sodium salts have a potential role in reducing population sodium intake level and blood pressure, but its availability in global market was unknown. OBJECTIVE: The aim of this study was to assess the availability, formulation, labelling, and price of low-sodium salts currently available to consumers around the world. METHODS: Low-sodium salts were identified through a systematic literature review, Google search, online shopping sites search, and inquiry of key informants. The keywords of "salt substitute", "low-sodium salt", "potassium salt", "mineral salt", and "sodium reduced salt" in six official languages of the United Nations were used for search. Information about the brand, formula, labelling, and price was extracted and analysed. RESULTS: Eighty-seven low-sodium salts were available in 47 out of 195 countries around the world (24%), including 28 high-income countries, 13 upper-middle-income countries, and six lower-middle-income countries. The proportion of sodium chloride varied from 0% (sodium-free) to 88% (as percent of weight, regular salt is 100% NaCl). Potassium chloride was the most frequent another component with levels ranging from 0% to 100% (potassium chloride salt). Forty-three (49%) had labels advising potential health risk, 33 (38%) labelling the advice of potential health benefits. The median price of low-sodium salts in high-income, upper-middle-income, lower-middle-income countries was USD 15.0/kg (IQR: 6.4 to 22.5), USD 2.7/kg (IQR: 1.7 to 5.5) and USD 2.9/kg (IQR: 0.50 to 22.2) respectively. The price of low-sodium salts was between 1.1 and 14.6 times that of regular salts. CONCLUSIONS: Low-sodium salts are not widely available and are commonly more expensive than regular salts. Policies that promote the availability, affordability and labelling of low-sodium salts should enhance appropriate uptake for blood pressure lowering and cardiovascular prevention. CLINICALTRIAL: INTERNATIONAL REGISTERED REPORT: RR2-10.1111/jch.14054

Visualizing dimensionality reduction of systems biology data

One of the challenges in analyzing high-dimensional expression data is the detection of important biological signals. A common approach is to apply a dimension reduction method, such as principal component analysis. Typically, after application of such a method the data is projected and visualized in the new coordinate system, using scatter plots or profile plots. These methods provide good results if the data have certain properties which become visible in the new coordinate system and which were hard to detect in the original coordinate system. Often however, the application of only one method does not suffice to capture all important signals. Therefore several methods addressing different aspects of the data need to be applied. We have developed a framework for linear and non-linear dimension reduction methods within our visual analytics pipeline SpRay. This includes measures that assist the interpretation of the factorization result. Different visualizations of these measures can be combined with functional annotations that support the interpretation of the results. We show an application to high-resolution time series microarray data in the antibiotic-producing organism Streptomyces coelicolor as well as to microarray data measuring expression of cells with normal karyotype and cells with trisomies of human chromosomes 13 and 21

Generating real-world evidence on the quality use, benefits and safety of medicines in australia: History, challenges and a roadmap for the future

Australia spends more than $20 billion annually on medicines, delivering significant health benefits for the population. However, inappropriate prescribing and medicine use also result in harm to individuals and populations, and waste of precious health resources. Medication data linked with other routine collections enable evidence generation in pharmacoepidemiology; the science of quantifying the use, effectiveness and safety of medicines in real-world clinical practice. This review details the history of medicines policy and data access in Australia, the strengths of existing data sources, and the infrastructure and governance enabling and impeding evidence generation in the field. Currently, substantial gaps persist with respect to cohesive, contemporary linked data sources supporting quality use of medicines, effectiveness and safety research; exemplified by Aus-tralia’s limited capacity to contribute to the global effort in real-world studies of vaccine and dis-ease-modifying treatments for COVID-19. We propose a roadmap to bolster the discipline, and population health more broadly, underpinned by a distinct capability governing and streamlining access to linked data assets for accredited researchers. Robust real-world evidence generation requires current data roadblocks to be remedied as a matter of urgency to deliver efficient and equitable health care and improve the health and well-being of all Australians

Fostering implementation of health services research findings into practice: a consolidated framework for advancing implementation science

Abstract Background Many interventions found to be effective in health services research studies fail to translate into meaningful patient care outcomes across multiple contexts. Health services researchers recognize the need to evaluate not only summative outcomes but also formative outcomes to assess the extent to which implementation is effective in a specific setting, prolongs sustainability, and promotes dissemination into other settings. Many implementation theories have been published to help promote effective implementation. However, they overlap considerably in the constructs included in individual theories, and a comparison of theories reveals that each is missing important constructs included in other theories. In addition, terminology and definitions are not consistent across theories. We describe the Consolidated Framework For Implementation Research (CFIR) that offers an overarching typology to promote implementation theory development and verification about what works where and why across multiple contexts. Methods We used a snowball sampling approach to identify published theories that were evaluated to identify constructs based on strength of conceptual or empirical support for influence on implementation, consistency in definitions, alignment with our own findings, and potential for measurement. We combined constructs across published theories that had different labels but were redundant or overlapping in definition, and we parsed apart constructs that conflated underlying concepts. Results The CFIR is composed of five major domains: intervention characteristics, outer setting, inner setting, characteristics of the individuals involved, and the process of implementation. Eight constructs were identified related to the intervention (e.g., evidence strength and quality), four constructs were identified related to outer setting (e.g., patient needs and resources), 12 constructs were identified related to inner setting (e.g., culture, leadership engagement), five constructs were identified related to individual characteristics, and eight constructs were identified related to process (e.g., plan, evaluate, and reflect). We present explicit definitions for each construct. Conclusion The CFIR provides a pragmatic structure for approaching complex, interacting, multi-level, and transient states of constructs in the real world by embracing, consolidating, and unifying key constructs from published implementation theories. It can be used to guide formative evaluations and build the implementation knowledge base across multiple studies and settings.http://deepblue.lib.umich.edu/bitstream/2027.42/78272/1/1748-5908-4-50.xmlhttp://deepblue.lib.umich.edu/bitstream/2027.42/78272/2/1748-5908-4-50-S1.PDFhttp://deepblue.lib.umich.edu/bitstream/2027.42/78272/3/1748-5908-4-50-S3.PDFhttp://deepblue.lib.umich.edu/bitstream/2027.42/78272/4/1748-5908-4-50-S4.PDFhttp://deepblue.lib.umich.edu/bitstream/2027.42/78272/5/1748-5908-4-50.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/78272/6/1748-5908-4-50-S2.PDFPeer Reviewe

C-reactive protein, interleukin-6, and prostate cancer risk in men aged 65 years and older.

Inflammation is believed to play a role in prostate cancer (PCa) etiology, but it is unclear whether inflammatory markers C-reactive protein (CRP) and interleukin-6 (IL-6) associate with PCa risk in older men. Using Cox regression, we assessed the relationship between baseline concentrations of CRP and IL-6 and the subsequent PCa risk in the Cardiovascular Health Study, a population-based cohort study of mostly European American men of ages >64 years (n = 2,234; mean follow-up = 8.7 years; 215 incident PCa cases). We also tested associations between CRP and IL-6 tagSNPs and PCa risk, focusing on SNPs that are known to associate with circulating CRP and/or IL-6. Neither CRP nor IL-6 blood concentrations was associated with PCa risk. The C allele of IL-6 SNP rs1800795 (-174), a known functional variant, was associated with increased risk in a dominant model (HR = 1.44; 95% CI = 1.03-2.01; p = 0.03), but was not statistically significant after accounting for multiple tests (permutation p = 0.21). Our results suggest that circulating CRP and IL-6 do not influence PCa risk. SNPs at the CRP locus are not associated with PCa risk in this cohort, while the association between rs1800795 and PCa risk warrants further investigation

Rational Design of Pathogen-Mimicking Amphiphilic Materials as Nanoadjuvants

An opportunity exists today for cross-cutting research utilizing advances in materials science, immunology, microbial pathogenesis, and computational analysis to effectively design the next generation of adjuvants and vaccines. This study integrates these advances into a bottom-up approach for the molecular design of nanoadjuvants capable of mimicking the immune response induced by a natural infection but without the toxic side effects. Biodegradable amphiphilic polyanhydrides possess the unique ability to mimic pathogens and pathogen associated molecular patterns with respect to persisting within and activating immune cells, respectively. The molecular properties responsible for the pathogen-mimicking abilities of these materials have been identified. The value of using polyanhydride nanovaccines was demonstrated by the induction of long-lived protection against a lethal challenge of Yersinia pestis following a single administration ten months earlier. This approach has the tantalizing potential to catalyze the development of next generation vaccines against diseases caused by emerging and re-emerging pathogens