Zinc absorption in adult humans: the effect of iron fortification

The effect of Fe fortification on the absorption of Zn was studied by radioisotopic labelling of single meals, followed by measurements of whole-body retention of 65Zn at 14 d after intake. Healthy adult volunteers participated in the study. Weaning cereal, wheat bread and infant formula, foods that are all frequently Fe-fortified, were evaluated in the study. The amounts of Fe added as FeSO4 were similar to the levels in commercial products in Europe and the USA, and were 200 or 500 mg Fe/kg (weaning cereal), 65 mg Fe/kg (white wheat flour) and 12 mg Fe/1 (infant formula). For comparison, Zn absorption was measured in the same subjects, from identical test meals containing no added Fe. No statistically significant differences were found when Zn absorption from the Fe-fortified test meals was compared with that from non-Fe-fortified test meals. Fractional Zn-absorption values from Fe-fortified v. non-fortified meals were 31·1 (sd 1·19) v. 30·7 (SD 7·0)% (weaning cereal; 200 mg Fe/kg), 37·7 (SD 16·6) v. 30·2 (SD 9·9)% (weaning cereal; 500 mg Fe/kg), 36·5 (SD 14·4) v. 38·2 (SD 18·1)% (bread; 65 mg Fe/kg flour) and 41·6 (SD 8·1) v. 38·9 (SD 14·5)% (infant formula; 12 mg Fe/1). The addition of Fe to foods at the currently used fortification levels was thus not associated with impaired absorption of Zn and the consumption of these Fe-fortified foods would not be expected to have a negative effect on Zn nutritio

Generating large labeled data sets for laparoscopic image processing tasks using unpaired image-to-image translation

In the medical domain, the lack of large training data sets and benchmarks is often a limiting factor for training deep neural networks. In contrast to expensive manual labeling, computer simulations can generate large and fully labeled data sets with a minimum of manual effort. However, models that are trained on simulated data usually do not translate well to real scenarios. To bridge the domain gap between simulated and real laparoscopic images, we exploit recent advances in unpaired image-to-image translation. We extent an image-to-image translation method to generate a diverse multitude of realistically looking synthetic images based on images from a simple laparoscopy simulation. By incorporating means to ensure that the image content is preserved during the translation process, we ensure that the labels given for the simulated images remain valid for their realistically looking translations. This way, we are able to generate a large, fully labeled synthetic data set of laparoscopic images with realistic appearance. We show that this data set can be used to train models for the task of liver segmentation of laparoscopic images. We achieve average dice scores of up to 0.89 in some patients without manually labeling a single laparoscopic image and show that using our synthetic data to pre-train models can greatly improve their performance. The synthetic data set will be made publicly available, fully labeled with segmentation maps, depth maps, normal maps, and positions of tools and camera (http://opencas.dkfz.de/image2image).Comment: Accepted at MICCAI 201

Towards greater transparency and coherence in funding for sustainable marine fisheries and healthy oceans

This final manuscript in the special issue on “Funding for ocean conservation and sustainable fisheries” is the result of a dialogue aimed at connecting lead authors of the special issue manuscripts with relevant policymakers and practitioners. The dialogue took place over the course of a two-day workshop in December 2018, and this “coda” manuscript seeks to distil thinking around a series of key recurring topics raised throughout the workshop. These topics are collected into three broad categories, or “needs”: 1) a need for transparency, 2) a need for coherence, and 3) a need for improved monitoring of project impacts. While the special issue sought to collect new research into the latest trends and developments in the rapidly evolving world of funding for ocean conservation and sustainable fisheries, the insights collected during the workshop have helped to highlight remaining knowledge gaps. Therefore, each of the three “needs” identified within this manuscript is followed by a series of questions that the workshop participants identified as warranting further attention as part of a future research agenda. The crosscutting nature of many of the issues raised as well as the rapid pace of change that characterizes this funding landscape both pointed to a broader need for continued dialogue and study that reaches across the communities of research, policy and practice.S

Differential responses to woodland character and landscape context by cryptic bats in urban environments

© 2015 Lintott et al. Urbanisation is one of the most dramatic forms of land use change which relatively few species can adapt to. Determining how and why species respond differently to urban habitats is important in predicting future biodiversity loss as urban areas rapidly expand. Understanding how morphological or behavioural traits can influence species adaptability to the built environment may enable us to improve the effectiveness of conservation efforts. Although many bat species are able to exploit human resources, bat species richness generally declines with increasing urbanisation and there is considerable variation in the responses of different bat species to urbanisation. Here, we use acoustic recordings from two cryptic, and largely sympatric European bat species to assess differential responses in their use of fragmented urban woodland and the surrounding urban matrix. There was a high probability of P. pygmaeus activity relative to P. pipistrellus in woodlands with low clutter and understory cover which were surrounded by low levels of built environment. Additionally, the probability of recording P. pygmaeus relative to P. pipistrellus was considerably higher in urban woodland interior or edge habitat in contrast to urban grey or non-wooded green space. These results show differential habitat use occurring between two morphologically similar species; whilst the underlying mechanism for this partitioning is unknown it may be driven by competition avoidance over foraging resources. Their differing response to urbanisation indicates the difficulties involved when attempting to assess how adaptable a species is to urbanisation for conservation purposes

Age differences in gain- and loss-motivated attention

Adaptive gain theory (Aston-Jones & Cohen, 2005) suggests that the phasic release of norepinephrine (NE) to cortical areas reflects changes in the utility of ongoing tasks. In the context of aging, this theory raises interesting questions, given that the motivations of older adults differ from those of younger adults. According to socioemotional selectivity theory (Carstensen, Isaacowitz, & Charles, 1999), aging is associated with greater emphasis on emotion-regulation goals, leading older adults to prioritize positive over negative information. This suggests that the phasic release of NE in response to threatening stimuli may be diminished in older adults. In the present study, younger adults (aged 18–34 years) and older adults (60–82 years) completed the Attention Network Test (ANT), modified to include an incentive manipulation. A behavioral index of attentional alerting served as a marker of phasic arousal. For younger adults, this marker correlated with the effect of both gain and loss incentives on performance. For older adults, in contrast, the correlation between phasic arousal and incentive sensitivity held for gain incentives only. These findings suggest that the enlistment of phasic NE activity may be specific to approach-oriented motivation in older adults

Methyl Complexes of the Transition Metals

Organometallic chemistry can be considered as a wide area of knowledge that combines concepts of classic organic chemistry, that is, based essentially on carbon, with molecular inorganic chemistry, especially with coordination compounds. Transition-metal methyl complexes probably represent the simplest and most fundamental way to view how these two major areas of chemistry combine and merge into novel species with intriguing features in terms of reactivity, structure, and bonding. Citing more than 500 bibliographic references, this review aims to offer a concise view of recent advances in the field of transition-metal complexes containing M-CH fragments. Taking into account the impressive amount of data that are continuously provided by organometallic chemists in this area, this review is mainly focused on results of the last five years. After a panoramic overview on M-CH compounds of Groups 3 to 11, which includes the most recent landmark findings in this area, two further sections are dedicated to methyl-bridged complexes and reactivity.Ministerio de Ciencia e Innovación Projects CTQ2010–15833, CTQ2013-45011 - P and Consolider - Ingenio 2010 CSD2007 - 00006Junta de Andalucía FQM - 119, Projects P09 - FQM - 5117 and FQM - 2126EU 7th Framework Program, Marie Skłodowska - Curie actions C OFUND – Agreement nº 26722

Buildout and integration of an automated high-throughput CLIA laboratory for SARS-CoV-2 testing on a large urban campus

In 2019, the first cases of SARS-CoV-2 were detected in Wuhan, China, and by early 2020 the first cases were identified in the United States. SARS-CoV-2 infections increased in the US causing many states to implement stay-at-home orders and additional safety precautions to mitigate potential outbreaks. As policies changed throughout the pandemic and restrictions lifted, there was an increase in demand for COVID-19 testing which was costly, difficult to obtain, or had long turn-around times. Some academic institutions, including Boston University (BU), created an on-campus COVID-19 screening protocol as part of a plan for the safe return of students, faculty, and staff to campus with the option for in-person classes. At BU, we put together an automated high-throughput clinical testing laboratory with the capacity to run 45,000 individual tests weekly by Fall of 2020, with a purpose-built clinical testing laboratory, a multiplexed reverse transcription PCR (RT-qPCR) test, robotic instrumentation, and trained staff. There were many challenges including supply chain issues for personal protective equipment and testing materials in addition to equipment that were in high demand. The BU Clinical Testing Laboratory (CTL) was operational at the start of Fall 2020 and performed over 1 million SARS-CoV-2 PCR tests during the 2020-2021 academic year.Boston UniversityPublished versio

Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity

The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management. © 2021, The Author(s)