Confusing the extragalactic neutrino flux limit with a neutrino propagation limit

We study the possible suppression of the extragalactic neutrino flux due to a nonstandard interaction during its propagation. In particular, we study neutrino interaction with an ultra-light scalar field dark matter. It is shown that the extragalactic neutrino flux may be suppressed by such an interaction, leading to a new mechanism to reduce the ultra-high energy neutrino flux. We study both the cases of non-self-conjugate as well as self-conjugate dark matter. In the first case, the suppression is independent of the neutrino and dark matter masses. We conclude that care must be taken when explaining limits on the neutrino flux through source acceleration mechanisms only, since there could be other mechanisms for the reduction of the neutrino flux.Comment: 15 pages, 4 figures. Important changes implemented. Abstract modified. Conclusions remain. To be published in JCA

City-wide wastewater genomic surveillance through the successive emergence of SARS-CoV-2 Alpha and Delta variants

Genomic surveillance of SARS-CoV-2 has provided a critical evidence base for public health decisions throughout the pandemic. Sequencing data from clinical cases has helped to understand disease transmission and the spread of novel variants. Genomic wastewater surveillance can offer important, complementary information by providing frequency estimates of all variants circulating in a population without sampling biases. Here we show that genomic SARS-CoV-2 wastewater surveillance can detect fine-scale differences within urban centres, specifically within the city of Liverpool, UK, during the emergence of Alpha and Delta variants between November 2020 and June 2021. Furthermore, wastewater and clinical sequencing match well in the estimated timing of new variant rises and the first detection of a new variant in a given area may occur in either clinical or wastewater samples. The study's main limitation was sample quality when infection prevalence was low in spring 2021, resulting in a lower resolution of the rise of the Delta variant compared to the rise of the Alpha variant in the previous winter. The correspondence between wastewater and clinical variant frequencies demonstrates the reliability of wastewater surveillance. However, discrepancies in the first detection of the Alpha variant between the two approaches highlight that wastewater monitoring can also capture missing information, possibly resulting from asymptomatic cases or communities less engaged with testing programmes, as found by a simultaneous surge testing effort across the city

Enabling global clinical collaborations on identifiable patient data: The Minerva Initiative

The clinical utility of computational phenotyping for both genetic and rare diseases is increasingly appreciated; however, its true potential is yet to be fully realized. Alongside the growing clinical and research availability of sequencing technologies, precise deep and scalable phenotyping is required to serve unmet need in genetic and rare diseases. To improve the lives of individuals affected with rare diseases through deep phenotyping, global big data interrogation is necessary to aid our understanding of disease biology, assist diagnosis, and develop targeted treatment strategies. This includes the application of cutting-edge machine learning methods to image data. As with most digital tools employed in health care, there are ethical and data governance challenges associated with using identifiable personal image data. There are also risks with failing to deliver on the patient benefits of these new technologies, the biggest of which is posed by data siloing. The Minerva Initiative has been designed to enable the public good of deep phenotyping while mitigating these ethical risks. Its open structure, enabling collaboration and data sharing between individuals, clinicians, researchers and private enterprise, is key for delivering precision public health

City-wide wastewater genomic surveillance through the successive emergence of SARS-CoV-2 Alpha and Delta variants

Genomic surveillance of SARS-CoV-2 has provided a critical evidence base for public health decisions throughout the pandemic. Sequencing data from clinical cases has helped to understand disease transmission and the spread of novel variants. Genomic wastewater surveillance can offer important, complementary information by providing frequency estimates of all variants circulating in a population without sampling biases. Here we show that genomic SARS-CoV-2 wastewater surveillance can detect fine-scale differences within urban centres, specifically within the city of Liverpool, UK, during the emergence of Alpha and Delta variants between November 2020 and June 2021. Furthermore, wastewater and clinical sequencing match well in the estimated timing of new variant rises and the first detection of a new variant in a given area may occur in either clinical or wastewater samples. The study's main limitation was sample quality when infection prevalence was low in spring 2021, resulting in a lower resolution of the rise of the Delta variant compared to the rise of the Alpha variant in the previous winter. The correspondence between wastewater and clinical variant frequencies demonstrates the reliability of wastewater surveillance. However, discrepancies in the first detection of the Alpha variant between the two approaches highlight that wastewater monitoring can also capture missing information, possibly resulting from asymptomatic cases or communities less engaged with testing programmes, as found by a simultaneous surge testing effort across the city

Novel Loci for Adiponectin Levels and Their Influence on Type 2 Diabetes and Metabolic Traits : A Multi-Ethnic Meta-Analysis of 45,891 Individuals

J. Kaprio, S. Ripatti ja M.-L. Lokki työryhmien jäseniä.Peer reviewe

Best be(e) on low fat: linking nutrient perception, regulation and fitness

Preventing malnutrition through consuming nutritionally appropriate resources represents a challenge for foraging animals. This is due to often high variation in the nutritional quality of available resources. Foragers consequently need to evaluate different food sources. However, even the same food source can provide a plethora of nutritional and non‐nutritional cues, which could serve for quality assessment. We show that bumblebees, Bombus terrestris , overcome this challenge by relying on lipids as nutritional cue when selecting pollen. The bees ‘prioritised’ lipid perception in learning experiments and avoided lipid consumption in feeding experiments, which supported survival and reproduction. In contrast, survival and reproduction were severely reduced by increased lipid contents. Our study highlights the importance of fat regulation for pollen foraging bumblebees. It also reveals that nutrient perception, nutrient regulation and reproductive fitness can be linked, which represents an effective strategy enabling quick foraging decisions that prevent malnutrition and maximise fitness

Enabling Global Clinical Collaborations on Identifiable Patient Data: The Minerva Initiative

Contains fulltext : 206175.pdf (publisher's version ) (Open Access