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A digitally enabled environment is a setting which incorporates sensors coupled with reporting and analytics tools for understanding, observing or managing that environment. Large scale data collection and analysis are a part of the emerging digitally enabled approach for the characterisation and understanding of our environment. It is recognised as offering an effective methodology for addressing a range of complex and interrelated social, economic and environmental concerns. The development and construction of the approach requires advances in analytics control linked with a clear definition of the issues pertaining to the interaction between elements of these systems. This paper presents an analysis of selected issues in the field of analytics control. It also discusses areas of progress, and areas in need of further investigation as sensing networks evolve. Three case studies are described to illustrate these points. The first is a physical analytics test kit developed as a part of the “Reinvent the Toilet Challenge” (RTTC) for process control in a range of environments. The second case study is the Cranfield Urban Observatory that builds on elements of the RTTC and is designed to allow users to develop user interfaces to monitor, characterise and compare a variety of environmental and infrastructure systems plus behaviours (e.g., water distribution, power grids). The third is the Data and Analytics Facility for National Infrastructure, a cloud-based high-performance computing cluster, developed to receive, store and present such data to advanced analytical and visualisation tools.

Control of the reproduction of domesticated stocks is considered a prerequisite for aquaculture development of pikeperch. However, knowledge about the physiology of the captive pikeperch male reproductive system and the biology of semen is very limited, especially regarding protein characteristics. The aims of our study were to characterize pikeperch sperm quantity and quality parameters and to analyze changes in the proteome of the same males spawned for the first and second times. Moreover, attempts were made to generate the first proteomic library of seminal plasma proteins. Semen collected during the first spawning season was characterized by lower sperm concentration and volume than for the second season. Using mass spectrometry-based label-free quantitative proteomics, we identified 850 proteins in the seminal plasma of pikeperch from both spawning seasons, and 65 seminal proteins were found to be differentially abundant between the first and second spawning seasons. The majority of differentially abundant proteins were involved in stress and immune responses, developmental processes, cofactor metabolic processes, proteolysis, cellular oxidant detoxification and organization of the extracellular matrix (ECM). In addition, several proteins unique to pikeperch seminal plasma were identified, including antifreeze proteins, hibernation-specific plasma proteins, lectins and vitellogenin. In summary, our results indicate that males that spawned for the first time were characterized by incompletely mature gonads and the expression of proteins associated with the early phase of spermatogenesis and ECM organization. On the other hand, males that spawned for the second time exhibited advanced gonadal maturation and expression of proteins related to the late stage of spermatogenesis and sperm maturation, including regulation of reactive oxygen species generation, bicarbonate production, sperm elongation and separation. The identification of a large number of seminal plasma proteins provides a valuable resource for understanding the functions of seminal plasma and the molecular mechanisms involved in testicular development and maturation in domesticated fish, which is a prerequisite for better control of reproduction in captivity.

Alkaptonuria is a rare genetic disorder characterized by a high level of circulating (and urine) homogentisic acid (HGA), which contributes to ochronosis when it is deposited in connective tissue as a pigmented polymer. In an observational study carried out by National AKU Centre (NAC) in Liverpool, a total of thirty-nine AKU patients attended yearly visits in varying numbers. At each visit a mixture of clinical, joint and spinal assessments were carried out and the results calculated to yield an AKUSSI (Alkaptonuria Severity Score Index), see “Nitisinone arrests ochronosis and decreases rate of progression of Alkaptonuria: evaluation of the effect of nitisinone in the United Kingdom National Alkaptonuria Centre” (Ranganath at el., 2018). The aim of this data article is to produce visual representation of the change in the components of AKUSSI over 3 years, through radar charts. The metabolic effect of nitisinone is shown through box plots.

Introduction: The proliferation biomarker Ki-67 is a prognostic factor for breast cancer that has been investigated in several retrospective studies and a few prospective ones. The aims of the present study were to examine interactions between Ki-67 and other biomarkers in breast cancer patients and to assess the relationship of Ki-67 to histological grading., Patients and Methods: Patients with uniform immunohistochemical staining of Ki-67 by MIB-1 were identified from the database of the University Breast Center for Franconia. Data were available for 1232 of 2523 patients with invasive breast cancer who had been treated between 1998 and 2005. Ki-67 index was determined during routine work-up of the breast cancers by several surgical pathologists according to a standardized procedure. The Ki-67 proliferation index was correlated with hormone receptor status, HER2/neu status, age, tumor staging, and prognosis. In routine clinical practice, the grading was assessed according to Elston and Ellis, along with all other parameters., Results: Ki-67 proliferation index>or=20% was found to be associated with all of the prognostic factors that were tested. However, it also maintained statistical significance relative to poor overall survival in a multivariate Cox proportional hazards model (hazards ratio 1.81; 95% CI, 1.17-2.78). The hazards ratio for disease-free survival did not reach statistical significance (HR 1.41; 95% CI, 0.95-2.09; P=0.086). However, in both models the grade was not an independent prognostic factor., Conclusions: For routine clinical purposes, grading appears to add only limited information about the prognosis in comparison with Ki-67 expression. Further investigation of quality assurance for grading and of Ki-67 as a prognostic and predictive factor is warranted.