Assay validation and interspecific comparison of salivary glucocorticoids in three amphibian species

Amphibians are one of the most threatened groups of species, facing stressors ranging from habitat degradation and pollution to disease and overexploitation. Stress hormones (glucocorticoids, GCs) provide one quantitative metric of stress,and developing non-invasive methods for measuring GCs in amphibians would clarify how diverse environmental stressors impact individual health in this taxonomic group. Saliva is an advantageous matrix for quantifying GCs, as it is sampled less invasively than plasma while still detecting both baseline and acute elevation of GCs within a short timeframe. Little work has employed this method in amphibian species, and it has never been pharmacologically and biologically validated. Here, we conduct analytical, pharmacological and biological validation experiments for measuring salivary corticosterone in three amphibian species: the American bullfrog (Rana catesbeiana), the green frog (Rana clamitans) and the northern leopard frog (Rana pipiens). These species are faced with a broad range of environmental challenges, and in part of its range R. pipiens populations are currently in decline. In addition to demonstrating that this method can be reliably used in multiple amphibian species, we present an examination of intrinsic biological factors (sex, body condition) that may contribute to GC secretion, and a demonstration that saliva can be collected from free-living animals in the field to quantify corticosterone. Our findings suggest that saliva may be useful for less invasively quantifying GCs in many amphibian species

A prospective analysis describing the innovative use of liposomal bupivacaine in burn patients

Burn patients frequently require autograft harvesting to facilitate wound healing, often resulting in significant pain. Liposomal bupivacaine is indicated for administration into a surgical site to produce postsurgical analgesia. The objective of this study was to evaluate efficacy, safety, and duration of postoperative analgesia with liposomal bupivacaine for donor site pain in burn patients. This was an observational, case–control study including adult patients with <20% total body surface area (TBSA) burned who received liposomal bupivacaine for postoperative pain management after autograft harvesting from lower extremity donor site(s). Patients from the case group were matched to historical control patients treated with traditional pain management. The primary outcome was the cumulative pain scores on postoperative day one measured by the area under the curve (AUC0–24). Secondary outcomes included AUC0–72, total milligram morphine equivalents (MME), length of stay, and adverse events. Data were collected in 36 patients who received liposomal bupivacaine, with 21 patients eligible for matching to historical controls. Patients included in the intervention and control groups were well-matched at baseline. Patients in the intervention group had a significantly lower median (IQR) AUC0–24 [578 (408,740) vs. 680 (544,803); p = 0.05] and shorter length of stay [4 days (1,9.5) vs. 6 days (318); p = 0.01]. No differences in adverse events related to the administration of liposomal bupivacaine or opioid-related adverse events were observed. Results indicate liposomal bupivacaine is safe and effective in burn patients. The results of this study add to the limited body of literature examining efficacy in this population

Lab-on-chip for in situ analysis of nutrients in the deep sea

Microfluidic reagent-based nutrient sensors offer a promising technology to address the global undersampling of ocean chemistry but have so far not been shown to operate in the deep sea (>200 m). We report a new family of miniaturized lab-on-chip (LOC) colorimetric analyzers making in situ nitrate and phosphate measurements from the surface ocean to the deep sea (>4800 m). This new technology gives users a new low-cost, high-performance tool for measuring chemistry in hyperbaric environments. Using a combination of laboratory verification and field-based tests, we demonstrate that the analyzers are capable of in situ measurements during profiling that are comparable to laboratory-based analyses. The sensors feature a novel and efficient inertial-flow mixer that increases the mixing efficiency and reduces the back pressure and flushing time compared to a previously used serpentine mixing channel. Four separate replicate units of the nitrate and phosphate sensor were calibrated in the laboratory and showed an average limit of detection of 0.03 μM for nitrate and 0.016 μM for phosphate. Three on-chip optical absorption cell lengths provide a large linear range (to >750 μM (10.5 mg/L-N) for nitrate and >15 μM (0.47 mg/L-P) for phosphate), making the instruments suitable for typical concentrations in both ocean and freshwater aquatic environments. The LOC systems automatically collected a series of deep-sea nitrate and phosphate profiles in the northeast Atlantic while attached to a conductivity temperature depth (CTD) rosette, and the LOC nitrate sensor was attached to a PROVOR profiling float to conduct automated nitrate profiles in the Mediterranean Sea

Measuring the Initial Mass Function of Low Mass Stars and Brown Dwarfs

I review efforts to determine the form and any lower limit to the initial mass function in the Galactic disk, using observations of low-mass stars and brown dwarfs in the field, young clusters and star forming regions. I focus on the methodologies that have been used and the uncertainties that exist due to observational limitations and to systematic uncertainties in calibrations and theoretical models. I conclude that whilst it is possible that the low-mass IMFs deduced from the field and most young clusters are similar, there are too many problems to be sure; there are examples of low-mass cluster IMFs that appear to be very discrepant and the IMFs for brown dwarfs in the field and young clusters have yet to be reconciled convincingly.Comment: From a series of lectures presented at the Evry-Schatzman school on Low-mass stars and the transition from stars to brown dwarfs, edited by C. Charbonnel, C. Reyle, M. Schultheis. To appear in the EAS Conference Series. 47p

Cohesin Proteins Promote Ribosomal RNA Production and Protein Translation in Yeast and Human Cells

Cohesin is a protein complex known for its essential role in chromosome segregation. However, cohesin and associated factors have additional functions in transcription, DNA damage repair, and chromosome condensation. The human cohesinopathy diseases are thought to stem not from defects in chromosome segregation but from gene expression. The role of cohesin in gene expression is not well understood. We used budding yeast strains bearing mutations analogous to the human cohesinopathy disease alleles under control of their native promoter to study gene expression. These mutations do not significantly affect chromosome segregation. Transcriptional profiling reveals that many targets of the transcriptional activator Gcn4 are induced in the eco1-W216G mutant background. The upregulation of Gcn4 was observed in many cohesin mutants, and this observation suggested protein translation was reduced. We demonstrate that the cohesinopathy mutations eco1-W216G and smc1-Q843Δ are associated with defects in ribosome biogenesis and a reduction in the actively translating fraction of ribosomes, eiF2α-phosphorylation, and 35S-methionine incorporation, all of which indicate a deficit in protein translation. Metabolic labeling shows that the eco1-W216G and smc1-Q843Δ mutants produce less ribosomal RNA, which is expected to constrain ribosome biogenesis. Further analysis shows that the production of rRNA from an individual repeat is reduced while copy number remains unchanged. Similar defects in rRNA production and protein translation are observed in a human Roberts syndrome cell line. In addition, cohesion is defective specifically at the rDNA locus in the eco1-W216G mutant, as has been previously reported for Roberts syndrome. Collectively, our data suggest that cohesin proteins normally facilitate production of ribosomal RNA and protein translation, and this is one way they can influence gene expression. Reduced translational capacity could contribute to the human cohesinopathies

Autoimmune Disease Classification by Inverse Association with SNP Alleles

With multiple genome-wide association studies (GWAS) performed across autoimmune diseases, there is a great opportunity to study the homogeneity of genetic architectures across autoimmune disease. Previous approaches have been limited in the scope of their analysis and have failed to properly incorporate the direction of allele-specific disease associations for SNPs. In this work, we refine the notion of a genetic variation profile for a given disease to capture strength of association with multiple SNPs in an allele-specific fashion. We apply this method to compare genetic variation profiles of six autoimmune diseases: multiple sclerosis (MS), ankylosing spondylitis (AS), autoimmune thyroid disease (ATD), rheumatoid arthritis (RA), Crohn's disease (CD), and type 1 diabetes (T1D), as well as five non-autoimmune diseases. We quantify pair-wise relationships between these diseases and find two broad clusters of autoimmune disease where SNPs that make an individual susceptible to one class of autoimmune disease also protect from diseases in the other autoimmune class. We find that RA and AS form one such class, and MS and ATD another. We identify specific SNPs and genes with opposite risk profiles for these two classes. We furthermore explore individual SNPs that play an important role in defining similarities and differences between disease pairs. We present a novel, systematic, cross-platform approach to identify allele-specific relationships between disease pairs based on genetic variation as well as the individual SNPs which drive the relationships. While recognizing similarities between diseases might lead to identifying novel treatment options, detecting differences between diseases previously thought to be similar may point to key novel disease-specific genes and pathways

Polygenic risk scores for prediction of breast cancer risk in Asian populations.

PURPOSE: Non-European populations are under-represented in genetics studies, hindering clinical implementation of breast cancer polygenic risk scores (PRSs). We aimed to develop PRSs using the largest available studies of Asian ancestry and to assess the transferability of PRS across ethnic subgroups. METHODS: The development data set comprised 138,309 women from 17 case-control studies. PRSs were generated using a clumping and thresholding method, lasso penalized regression, an Empirical Bayes approach, a Bayesian polygenic prediction approach, or linear combinations of multiple PRSs. These PRSs were evaluated in 89,898 women from 3 prospective studies (1592 incident cases). RESULTS: The best performing PRS (genome-wide set of single-nucleotide variations [formerly single-nucleotide polymorphism]) had a hazard ratio per unit SD of 1.62 (95% CI = 1.46-1.80) and an area under the receiver operating curve of 0.635 (95% CI = 0.622-0.649). Combined Asian and European PRSs (333 single-nucleotide variations) had a hazard ratio per SD of 1.53 (95% CI = 1.37-1.71) and an area under the receiver operating curve of 0.621 (95% CI = 0.608-0.635). The distribution of the latter PRS was different across ethnic subgroups, confirming the importance of population-specific calibration for valid estimation of breast cancer risk. CONCLUSION: PRSs developed in this study, from association data from multiple ancestries, can enhance risk stratification for women of Asian ancestry

Application of a risk-management framework for integration of stromal tumor-infiltrating lymphocytes in clinical trials

Stromal tumor-infiltrating lymphocytes (sTILs) are a potential predictive biomarker for immunotherapy response in metastatic triple-negative breast cancer (TNBC). To incorporate sTILs into clinical trials and diagnostics, reliable assessment is essential. In this review, we propose a new concept, namely the implementation of a risk-management framework that enables the use of sTILs as a stratification factor in clinical trials. We present the design of a biomarker risk-mitigation workflow that can be applied to any biomarker incorporation in clinical trials. We demonstrate the implementation of this concept using sTILs as an integral biomarker in a single-center phase II immunotherapy trial for metastatic TNBC (TONIC trial, NCT02499367), using this workflow to mitigate risks of suboptimal inclusion of sTILs in this specific trial. In this review, we demonstrate that a web-based scoring platform can mitigate potential risk factors when including sTILs in clinical trials, and we argue that this framework can be applied for any future biomarker-driven clinical trial setting