8-Bromo­naphthalen-1-amine

The title compound, C10H8BrN, was obtained by slow addition of sodium azide to 8-bromo-1-naphthoic acid, followed by addition of aqueous ammonia. The crude product was crystallized from petroleum ether to give pink crystals. Compared to other 1,8-disubstituted naphthalene compounds, this compound exhibits less strain between the 1 and 8 substituents. Additionally, the NH protons form both intra- and inter­molecular hydrogen bonds. The naphthalene units are arranged in a herring-bone stacking motif

Platinum bis(phosphine) complexes of 1,8-naphthosultam

The work in this project was supported by the Engineering and Physical Sciences Research Council (EPSRC).A series of bis(phosphine) platinum complexes 1-4 and 6-8 that bear the 1,8-naphthosultam ligand (L) have been synthesised. The nitrogen atom in L was deprotonated with sodium tert-butoxide to form the sodium salt. Metathetical reaction of the sodium salt (1 eq.) with the appropriate cis-dichlorobis(phosphine) platinum (1 eq.) in THF resulted in the formation of platinum complexes [Pt(PR3)2(L)Cl] (R3 = Ph3; 1, Ph2Me; 2, PhMe2; 3, Me3; 4), whilst reaction with [Pt(COD)Cl2] afforded [Pt(COD)(L)Cl] (5). The corresponding reaction employing two equivalents of L, two equivalents of NaOtBu and one equivalent of [Pt(PR3)2Cl2]/[Pt(COD)Cl2] yielded complexes [Pt(PR3)2(L)2] (R3 = Ph2Me; 6, PhMe2; 7, Me3; 8) and [Pt(COD)(L)2] (9). L, 1, 5 and 9 have been fully characterised, principally by multinuclear magnetic resonance and IR spectroscopy and mass spectrometry, the remaining members of the series were analysed by 31P NMR only. Unsymmetrical complexes 1-4 provide examples of AX spin systems, with appropriate satellites attributed to 31P NMR-195Pt coupling. X-ray structures determined for 1,8-naphthosultam L, and complexes 1, 5 and 9 and where appropriate the platinum metal geometry, N-S distance and ligand distortions were compared.PostprintPeer reviewe

Metabolome-Informed Microbiome Analysis Refines Metadata Classifications and Reveals Unexpected Medication Transfer in Captive Cheetahs.

Even high-quality collection and reporting of study metadata in microbiome studies can lead to various forms of inadvertently missing or mischaracterized information that can alter the interpretation or outcome of the studies, especially with nonmodel organisms. Metabolomic profiling of fecal microbiome samples can provide empirical insight into unanticipated confounding factors that are not possible to obtain even from detailed care records. We illustrate this point using data from cheetahs from the San Diego Zoo Safari Park. The metabolomic characterization indicated that one cheetah had to be moved from the non-antibiotic-exposed group to the antibiotic-exposed group. The detection of the antibiotic in this second cheetah was likely due to grooming interactions with the cheetah that was administered antibiotics. Similarly, because transit time for stool is variable, fecal samples within the first few days of antibiotic prescription do not all contain detected antibiotics, and the microbiome is not yet affected. These insights significantly altered the way the samples were grouped for analysis (antibiotic versus no antibiotic) and the subsequent understanding of the effect of the antibiotics on the cheetah microbiome. Metabolomics also revealed information about numerous other medications and provided unexpected dietary insights that in turn improved our understanding of the molecular patterns on the impact on the community microbial structure. These results suggest that untargeted metabolomic data provide empirical evidence to correct records and aid in the monitoring of the health of nonmodel organisms in captivity, although we also expect that these methods may be appropriate for other social animals, such as cats.IMPORTANCE Metabolome-informed analyses can enhance omics studies by enabling the correct partitioning of samples by identifying hidden confounders inadvertently misrepresented or omitted from carefully curated metadata. We demonstrate here the utility of metabolomics in a study characterizing the microbiome associated with liver disease in cheetahs. Metabolome-informed reinterpretation of metagenome and metabolome profiles factored in an unexpected transfer of antibiotics, preventing misinterpretation of the data. Our work suggests that untargeted metabolomics can be used to verify, augment, and correct sample metadata to support improved grouping of sample data for microbiome analyses, here for nonmodel organisms in captivity. However, the techniques also suggest a path forward for correcting clinical information in microbiome studies more broadly to enable higher-precision analyses

Clickers Can Promote Fact Retention But Impede Conceptual Understanding: The Effect of the Interaction Between Clicker Use and Pedagogy on Learning

Highlights Two experiments explored the role of clickers on factual and conceptual learning. One course emphasized fact retention and the other emphasized conceptual understanding. Factual and conceptual clicker questions enhanced only fact learning in the didactic course. Factual questions impaired conceptual learning in the problem-oriented course. Clicker effects are mediated by pedagogy, learning strategy, and prior knowledge

The neonicotinoid insecticide Imidacloprid repels pollinating flies and beetles at field-realistic concentrations

Neonicotinoids are widely used systemic insecticides which, when applied to flowering crops, are translocated to the nectar and pollen where they may impact upon pollinators. Given global concerns over pollinator declines, this potential impact has recently received much attention. Field exposure of pollinators to neonicotinoids depends on the concentrations present in flowering crops and the degree to which pollinators choose to feed upon them. Here we describe a simple experiment using paired yellow pan traps with or without insecticide to assess whether the commonly used neonicotinoid imidacloprid repels or attracts flying insects. Both Diptera and Coleoptera exhibited marked avoidance of traps containing imidacloprid at a field-realistic dose of 1 μg L-1, with Diptera avoiding concentrations as low as 0.01 μg L-1. This is to our knowledge the first evidence for any biological activity at such low concentrations, which are below the limits of laboratory detection using most commonly available techniques. Catch of spiders in pan traps was also slightly reduced by the highest concentrations of imidacloprid used (1 μg L-1), but catch was increased by lower concentrations. It remains to be seen if the repellent effect on insects occurs when neonicotinoids are present in real flowers, but if so then this could have implications for exposure of pollinators to neonicotinoids and for crop pollination. © 2013 Easton, Goulson

Clinical Laboratories Collaborate to Resolve Differences in Variant Interpretations Submitted to ClinVar

Purpose Data sharing through ClinVar offers a unique opportunity to identify interpretation differences between laboratories. As part of a ClinGen initiative, four clinical laboratories (Ambry, GeneDx, Partners Healthcare Laboratory for Molecular Medicine, and University of Chicago Genetic Services Laboratory) collaborated to identify the basis of interpretation differences and to investigate if data sharing and reassessment resolves interpretation differences by analyzing a subset of variants. Methods: ClinVar variants with submissions from at least two of the four participating laboratories were compared. For a subset of identified differences, laboratories documented the basis for discordance, shared internal data, independently reassessed with the ACMG-AMP guidelines, and then compared interpretations. Results: 6,169 variants in ClinVar were interpreted by at least two of the participating laboratories, of which 88.3% were initially concordant. Laboratories reassessed 242/724 initially discordant variants, of which 87.2% (211) were resolved by reassessment with current criteria and/or internal data sharing. 12.8% (31) of reassessed variants remain discordant due to differences in application of the ACMG-AMP guidelines. Conclusion: Participating laboratories increased their overall concordance from 88.3% to 91.7%, indicating that sharing variant interpretations in ClinVar, allowing identification of differences and motivation to resolve those differences, is critical to move toward more consistent variant interpretations

New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk.

Levels of circulating glucose are tightly regulated. To identify new loci influencing glycemic traits, we performed meta-analyses of 21 genome-wide association studies informative for fasting glucose, fasting insulin and indices of beta-cell function (HOMA-B) and insulin resistance (HOMA-IR) in up to 46,186 nondiabetic participants. Follow-up of 25 loci in up to 76,558 additional subjects identified 16 loci associated with fasting glucose and HOMA-B and two loci associated with fasting insulin and HOMA-IR. These include nine loci newly associated with fasting glucose (in or near ADCY5, MADD, ADRA2A, CRY2, FADS1, GLIS3, SLC2A2, PROX1 and C2CD4B) and one influencing fasting insulin and HOMA-IR (near IGF1). We also demonstrated association of ADCY5, PROX1, GCK, GCKR and DGKB-TMEM195 with type 2 diabetes. Within these loci, likely biological candidate genes influence signal transduction, cell proliferation, development, glucose-sensing and circadian regulation. Our results demonstrate that genetic studies of glycemic traits can identify type 2 diabetes risk loci, as well as loci containing gene variants that are associated with a modest elevation in glucose levels but are not associated with overt diabetes

Single cell spatial analysis reveals inflammatory foci of immature neutrophil and CD8 T cells in COVID-19 lungs

Single cell spatial interrogation of the immune-structural interactions in COVID −19 lungs is challenging, mainly because of the marked cellular infiltrate and architecturally distorted microstructure. To address this, we develop a suite of mathematical tools to search for statistically significant co-locations amongst immune and structural cells identified using 37-plex imaging mass cytometry. This unbiased method reveals a cellular map interleaved with an inflammatory network of immature neutrophils, cytotoxic CD8 T cells, megakaryocytes and monocytes co-located with regenerating alveolar progenitors and endothelium. Of note, a highly active cluster of immature neutrophils and CD8 T cells, is found spatially linked with alveolar progenitor cells, and temporally with the diffuse alveolar damage stage. These findings offer further insights into how immune cells interact in the lungs of severe COVID-19 disease. We provide our pipeline [Spatial Omics Oxford Pipeline (SpOOx)] and visual-analytical tool, Multi-Dimensional Viewer (MDV) software, as a resource for spatial analysis

Associations of Circulating Estrogens and Estrogen Metabolites with Fecal and Oral Microbiome in Postmenopausal Women in the Ghana Breast Health Study

ABSTRACT The human fecal and oral microbiome may play a role in the etiology of breast cancer through modulation of endogenous estrogen metabolism. This study aimed to investigate associations of circulating estrogens and estrogen metabolites with the fecal and oral microbiome in postmenopausal African women. A total of 117 women with fecal (N = 110) and oral (N = 114) microbiome data measured by 16S rRNA gene sequencing, and estrogens and estrogen metabolites data measured by liquid chromatography tandem mass spectrometry were included. The outcomes were measures of the microbiome and the independent variables were the estrogens and estrogen metabolites. Estrogens and estrogen metabolites were associated with the fecal microbial Shannon index (global P < 0.01). In particular, higher levels of estrone (β = 0.36, P = 0.03), 2-hydroxyestradiol (β = 0.30, P = 0.02), 4-methoxyestrone (β = 0.51, P = 0.01), and estriol (β = 0.36, P = 0.04) were associated with higher levels of the Shannon index, while 16alpha-hydroxyestrone (β = −0.57, P < 0.01) was inversely associated with the Shannon index as indicated by linear regression. Conjugated 2-methoxyestrone was associated with oral microbial unweighted UniFrac as indicated by MiRKAT (P < 0.01) and PERMANOVA, where conjugated 2-methoxyestrone explained 2.67% of the oral microbial variability, but no other estrogens or estrogen metabolites were associated with any other beta diversity measures. The presence and abundance of multiple fecal and oral genera, such as fecal genera from families Lachnospiraceae and Ruminococcaceae, were associated with several estrogens and estrogen metabolites as indicated by zero-inflated negative binomial regression. Overall, we found several associations of specific estrogens and estrogen metabolites and the fecal and oral microbiome. IMPORTANCE Several epidemiologic studies have found associations of urinary estrogens and estrogen metabolites with the fecal microbiome. However, urinary estrogen concentrations are not strongly correlated with serum estrogens, a known risk factor for breast cancer. To better understand whether the human fecal and oral microbiome were associated with breast cancer risk via the regulation of estrogen metabolism, we conducted this study to investigate the associations of circulating estrogens and estrogen metabolites with the fecal and oral microbiome in postmenopausal African women. We found several associations of parent estrogens and several estrogen metabolites with the microbial communities, and multiple individual associations of estrogens and estrogen metabolites with the presence and abundance of multiple fecal and oral genera, such as fecal genera from families Lachnospiraceae and Ruminococcaceae, which have estrogen metabolizing properties. Future large, longitudinal studies to investigate the dynamic changes of the fecal and oral microbiome and estrogen relationship are needed