Anonymous and EST-based microsatellite DNA markers that transfer broadly across the fig genus (Ficus, Moraceae)

• Premise of the study: We developed a set of microsatellite markers for broad utility across the species-rich pantropical tree genus Ficus (fig trees). The markers were developed to study population structure, hybridization, and gene flow in neotropical species. • Methods and Results: We developed seven novel primer sets from expressed sequence tag (EST) libraries of F. citrifolia and F. popenoei (subgen. Urostigma sect. Americana) and optimized five previously developed anonymous loci for cross-species amplification. The markers were successfully tested on four species from the basal subgenus Pharmacosycea sect. Pharmaco- sycea (F. insipida, F. maxima, F. tonduzii, and F. yoponensis) and seven species of the derived subgenus Urostigma (F. citrifolia, F. colubrinae, F. costaricana, F. nymphaeifolia, F. obtusifolia, F. pertusa, and F. popenoei). The 12 markers amplified consis- tently and displayed polymorphism in all the species. • Conclusions: This set of microsatellite markers is transferable across the phylogenetic breadth of Ficus, and should therefore be useful for studies of population structure and gene flow in approximately 750 fig species worldwide.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/92471/1/Heer2012.pdf8

Headache severity in patients with post COVID-19 condition: a case-control study.

Post COVID-19 conditions (PCC) present with a wide range of symptoms. Headache is one of the most frequently reported neurological symptoms by patients with PCC. We aimed to assess the prevalence of headache in patients with PCC who attended the Post-COVIDLMU outpatient department at LMU University Hospital in Munich. We hypothesized that headaches occur more frequently in patients with PCC than in the control group. Patients answered a questionnaire containing sociodemographic characteristics, their current symptoms, and prior psychiatric and somatic diagnoses, the WHO Quality of Life assessment (WHOQOL-BREF), 9-item Patient Health Questionnaire (PHQ-9), and the Fatigue Severity Scale (FSS). 188 PCC patients were included in this study and compared to a control group of patients with a history of COVID-19 or a different infectious disease - but no consecutive post-infectious condition (nc=27). 115 (61%) of our PCC patients were female. The median age was 41 years. 60 (32%, p = 0.001) had a pre-existing psychiatric diagnosis. PCC was associated with worse outcomes in all four domains of the WHOQOL-BREF (p < 0.001), high levels of fatigue (FSS; p < 0.001), and a higher likeliness for symptoms of depression (PHQ-9; p < 0.001). We were able to confirm that psychiatric disorders are more frequently associated with headaches in PCC patients. Headache should be assessed and treated in the context of PCC not only by neurologists but by multi-professional teams and regarding all PCC symptoms

Comparison of clinical geneticist and computer visual attention in assessing genetic conditions

Artificial intelligence (AI) for facial diagnostics is increasingly used in the genetics clinic to evaluate patients with potential genetic conditions. Current approaches focus on one type of AI called Deep Learning (DL). While DL- based facial diagnostic platforms have a high accuracy rate for many conditions, less is understood about how this technology assesses and classifies (categorizes) images, and how this compares to humans. To compare human and computer attention, we performed eye-tracking analyses of geneticist clinicians (n = 22) and non-clinicians (n = 22) who viewed images of people with 10 different genetic conditions, as well as images of unaffected individuals. We calculated the Intersection-over-Union (IoU) and Kullback–Leibler divergence (KL) to compare the visual attentions of the two participant groups, and then the clinician group against the saliency maps of our deep learning classifier. We found that human visual attention differs greatly from DL model’s saliency results. Averaging over all the test images, IoU and KL metric for the successful (accurate) clinician visual attentions versus the saliency maps were 0.15 and 11.15, respectively. Individuals also tend to have a specific pattern of image inspection, and clinicians demonstrate different visual attention patterns than non-clinicians (IoU and KL of clinicians versus non-clinicians were 0.47 and 2.73, respectively). This study shows that humans (at different levels of expertise) and a computer vision model examine images differently. Understanding these differences can improve the design and use of AI tools, and lead to more meaningful interactions between clinicians and AI technologies

Absence of the Autophagy Adaptor SQSTM1/p62 Causes Childhood-Onset Neurodegeneration with Ataxia, Dystonia, and Gaze Palsy

Peer reviewe

The Profumo affair in popular culture: The Keeler Affair (1963) and ‘the commercial exploitation of a public scandal’

This article demonstrates that the Profumo affair, which obsessed Britain for large parts of 1963, was not simply a political scandal, but was also an important cultural event. Focussing on the production of The Keeler Affair, a feature film that figured prominently in contemporary coverage of the scandal but which has been largely overlooked since, the article shows that this film emerged from a situation in which cultural entrepreneurs, many of them associated with the satire boom, sought to exploit the scandal for financial gain. Many Profumo-related cultural products found an audience, and thus formed an integral part of, and helped to shape public attitudes towards, the Profumo affair. However, these products did not go uncontested, and resistance to them, and especially to the idea that Keeler might benefit materially from her role in the scandal, speak to concerns about cultural mediations of sex, politics and humour in early-1960s Britain

BioTIME: A database of biodiversity time series for the Anthropocene.

MotivationThe BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community-led open-source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene.Main types of variables includedThe database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of 2 years, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology and contextual information about each record.Spatial location and grainBioTIME is a global database of 547,161 unique sampling locations spanning the marine, freshwater and terrestrial realms. Grain size varies across datasets from 0.0000000158 km2 (158 cm2) to 100 km2 (1,000,000,000,000 cm2).Time period and grainBioTIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year.Major taxa and level of measurementBioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton and terrestrial invertebrates to small and large vertebrates.Software format.csv and .SQL