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DECONSTRUCTING DATA PROTECTION: THE ‘ADDED-VALUE’ OF A RIGHT TO DATA PROTECTION IN THE EU LEGAL ORDER
Article 8 of the EU Charter of Fundamental Rights sets out a right to data protection which sits alongside, and in addition to, the established right to privacy in the Charter. The Charter's inclusion of an independent right to data protection differentiates it from other international human rights documents which treat data protection as a subset of the right to privacy. Its introduction and its relationship with the established right to privacy merit an explanation. This paper explores the relationship between the rights to data protection and privacy. It demonstrates that, to date, the Court of Justice of the European Union (CJEU) has consistently conflated the two rights. However, based on a comparison between the scope of the two rights as well as the protection they offer to individuals whose personal data are processed, it claims that the two rights are distinct. It argues that the right to data protection provides individuals with more rights over more types of data than the right to privacy. It suggests that the enhanced control over personal data provided by the right to data protection serves two purposes: first, it proactively promotes individual personality rights which are threatened by personal data processing and, second, it reduces the power and information asymmetries between individuals and those who process their data. For these reasons, this paper suggests that there ought to be explicit judicial recognition of the distinction between the two rights.
Journal Article
The Silver Bullet? Assessing the Role of Education for Sustainability
Abstract
The United Nations 2030 agenda for sustainable development calls on nation states to invest in national development trajectories that promote both human and environmental well-being. Given the complexity of this plan, and the increasing severity of the climate crisis, understanding the relationship between nations’ social and environmental outcomes is a critical task for social scientists. Raising national rates of educational attainment is a cornerstone national and international governance goal. This paper integrates Amartya Sen’s conceptualization of education as the expansion of human capabilities, with the ecological modernization position that more educated societies may be less ecologically intensive, and tests the resultant hypothesis that gains in education may support global sustainability. Specifically, this study uses two-way fixed effects longitudinal modeling techniques to assess the relationship between national educational attainment and the carbon intensity of well-being (CIWB) for 76 nations between 1960 and 2010. The CIWB ratio is a well-established metric for sustainability within sociology. The findings indicate that gains in educational attainment played an important historical role in reducing the carbon intensity with which nation states produce well-being for its citizens. Less encouraging, from a global sustainability perspective, is the uneven distribution of these desirable effects across regions, and the diminishment of the education effect over time in all regions outside of advanced economies.
Journal Article
Major advances in amyotrophic lateral sclerosis in 2020
[...]major advances in cell and molecular biology, neuroimaging, neuroelectric signal analyses, and neuropathology have categorically shown that ALS should be considered to be a neurodegenerative disorder, albeit with a substantial neuromuscular component.1 Although the biological processes underlying the pathogenesis and progression of the disease are multifactorial, there is increasing evidence that ALS is characterised by early cortical hyperexcitability with altered synaptic integrity, possibly mediated by the deposition of TAR DNA-binding protein 43 (TDP-43),2 followed by more widespread disruption of neuronal networks.3 These insights provide multiple potential targets for drug development, although it is likely that different pathogenic mechanisms will ultimately require a precision medicine approach to therapeutics. TRICALS's position paper describes the major barriers that impede the translation of therapeutics from promising pre-clinical studies to successful pivotal phase 3 studies.4 They suggest that overcoming these barriers will require better biomarkers for biological activity and target engagement; improvement of eligibility criteria for trials using statistical models that incorporate multiple prognostic factors; innovative trial designs (eg, using a platform design with a master protocol, multiple therapeutic groups, and a shared placebo group); and better quantitative outcome measures that address the current limitations of the Revised ALS Functional Rating Scale (ALSFRS-R). [...]the impact of the COVID-19 pandemic on clinical research in ALS has been considerable.
Journal Article
Selective stimulation of colonic L cells improves metabolic outcomes in mice
Aims/hypothesisInsulin-like peptide-5 (INSL5) is found only in distal colonic L cells, which co-express glucagon-like peptide-1 (GLP-1) and peptide YY (PYY). GLP-1 is a well-known insulin secretagogue, and GLP-1 and PYY are anorexigenic, whereas INSL5 is considered orexigenic. We aimed to clarify the metabolic impact of selective stimulation of distal colonic L cells in mice.MethodsInsl5 promoter-driven expression of Gq-coupled Designer Receptor Exclusively Activated by Designer Drugs (DREADD) was employed to activate distal colonic L cells (LdistalDq). IPGTT and food intake were assessed with and without DREADD activation.ResultsLdistalDq cell stimulation with clozapine N-oxide (CNO; 0.3 mg/kg i.p.) increased plasma GLP-1 and PYY (2.67- and 3.31-fold, respectively); INSL5 was not measurable in plasma but was co-secreted with GLP-1 and PYY in vitro. IPGTT (2 g/kg body weight) revealed significantly improved glucose tolerance following CNO injection. CNO-treated mice also exhibited reduced food intake and body weight after 24 h, and increased defecation, the latter being sensitive to 5-hydroxytryptamine (5-HT) receptor 3 inhibition. Pre-treatment with a GLP1 receptor-blocking antibody neutralised the CNO-dependent improvement in glucose tolerance but did not affect the reduction in food intake, and an independent group of animals pair-fed to the CNO-treatment group demonstrated attenuated weight loss. Pre-treatment with JNJ-31020028, a neuropeptide Y receptor type 2 antagonist, abolished the CNO-dependent effect on food intake. Assessment of whole body physiology in metabolic cages revealed LdistalDq cell stimulation increased energy expenditure and increased activity. Acute CNO-induced food intake and glucose homeostasis outcomes were maintained after 2 weeks on a high-fat diet.Conclusions/interpretationThis proof-of-concept study demonstrates that selective distal colonic L cell stimulation has beneficial metabolic outcomes.
Journal Article
Musculoskeletal anomalies in children with Down syndrome: an observational study
BackgroundMusculoskeletal complications of Down syndrome (DS) are common but infrequently reported. The combination of ligamentous laxity and low muscle tone contributes to increased risk of a number of musculoskeletal disorders and a delay in acquisition of motor milestones. The primary aim of this study was to describe musculoskeletal anomalies reported in a national cohort of children with DS.MethodsThis was an observational study. Children with DS, aged 0–21 years, were invited to attend a musculoskeletal assessment clinic conducted by a paediatric physician. Relevant musculoskeletal history and clinical findings were documented.ResultsOver an 18-month period, 503 children with DS were examined (56% male). The median age was 8.1 years (0.6–19.2). Pes planus was almost universal, occurring in 91% of the cohort. A range of other musculoskeletal anomalies were observed, with inflammatory arthritis (7%) and scoliosis (4.8%) occurring most frequently after pes planus. Delay in ambulation was common; the median age to walk was 28 months (12–84).ConclusionChildren with DS are at increased risk of a number of potentially debilitating musculoskeletal problems. These conditions can present in variable manners or be completely asymptomatic. Pes planus is common; therefore, early consideration of orthotics and lifelong appropriate supportive footwear should be considered. Delayed ambulation is frequently noted. A significant proportion of children with DS have arthritis; however, despite a high prevalence, it is often missed, leading to delayed diagnosis. An annual musculoskeletal assessment for all children with DS could potentially enable early detection of problems, allowing for timely multidisciplinary team intervention and better clinical outcomes.
Journal Article
Pathological neural networks and artificial neural networks in ALS: diagnostic classification based on pathognomonic neuroimaging features
The description of group-level, genotype- and phenotype-associated imaging traits is academically important, but the practical demands of clinical neurology centre on the accurate classification of individual patients into clinically relevant diagnostic, prognostic and phenotypic categories. Similarly, pharmaceutical trials require the precision stratification of participants based on quantitative measures. A single-centre study was conducted with a uniform imaging protocol to test the accuracy of an artificial neural network classification scheme on a cohort of 378 participants composed of patients with ALS, healthy subjects and disease controls. A comprehensive panel of cerebral volumetric measures, cortical indices and white matter integrity values were systematically retrieved from each participant and fed into a multilayer perceptron model. Data were partitioned into training and testing and receiver-operating characteristic curves were generated for the three study-groups. Area under the curve values were 0.930 for patients with ALS, 0.958 for disease controls, and 0.931 for healthy controls relying on all input imaging variables. The ranking of variables by classification importance revealed that white matter metrics were far more relevant than grey matter indices to classify single subjects. The model was further tested in a subset of patients scanned within 6 weeks of their diagnosis and an AUC of 0.915 was achieved. Our study indicates that individual subjects may be accurately categorised into diagnostic groups in an observer-independent classification framework based on multiparametric, spatially registered radiology data. The development and validation of viable computational models to interpret single imaging datasets are urgently required for a variety of clinical and clinical trial applications.
Journal Article