Effect of thermal decarbonation on the stable isotope composition of carbonates

The unusual texture and stable isotope variability of carbonates in AH84001 have been used as evidence for early life on Mars (Romanek et al., 1994; McKay et al., 1996). Oxygen and carbon isotope variability is most commonly attributed to low-temperature processes, including Rayleigh-like fractionation associated with biological activity. Another possible explanation for the isotopic variability in meteoritic samples is thermal decarbonation. In this report, different carbonates were heated in a He-stream until decomposition temperatures were reached. The oxygen and carbon isotope ratios ({delta}{sup 18}O and {delta}{sup 13}C values) of the resulting gas were measured on a continuous flow isotope ratio mass spectrometer. The aim of this work is to evaluate the possibility that large isotopic variations can be generated on a small scale abiogenically, by the process of thermal decarbonation. Oxygen isotope fractionations of >4{per_thousand} have been measured during decarbonation of calcite at high temperatures (McCrea, 1950), and in excess of 6{per_thousand} for dolomite decarbonated between 500 and 600 C (Sharma and Clayton, 1965). Isotopic fractionations of this magnitude, coupled with Rayleigh-like distillation behavior could result in very large isotopic variations on a small scale. To test the idea, calcite, dolomite and siderite were heated in a quartz tube in a He-stream in excess of 1 atmosphere. Simultaneous determinations of {delta}{sup 13}C and {Delta}{sup 18}O values were obtained on 250 {micro}l aliquots of the CO{sub 2}-bearing He gas using an automated 6-way switching valve system (Finnigan MAT GasBench II) and a Finnigan MAT Delta Plus mass spectrometer. It was found that decarbonation of calcite in a He atmosphere begins at 720 C, but the rate significantly increases at temperatures of 820 C. After an initial light {delta}{sup 18}O value of -14.1{per_thousand} at 720 C associated with very early decarbonation, {delta}{sup 18}0 values increase to a constant -11.8{per_thousand}, close to the accepted value of -12.09{per_thousand} (PDB). After 10 minutes at 820 C, the {delta}{sup 18}O values and signal strength both begin to decrease linearly to a {delta}{sup 18}O value of -14.75 and very low amounts of CO{sub 2} (Fig. 1). In contrast, the {delta}{sup 13}C values are extremely constant (0.12 {+-} 0.25{per_thousand}) for all measurements, in very good agreement with accepted values of 0.33{per_thousand} (PDB). There is much less isotopic variability during dolomite decarbonation. CO{sub 2} is first detected at 600 C. The signal strength increases by an order of magnitude between 670 and 700 C and again at 760 C. Both {delta}{sup 13}C and {delta}{sup 18}O values are nearly constant over the entire temperature range and sample size. For oxygen, the measured {delta}{sup 18}O values averaged -20.9 {+-} 0.7{per_thousand} (n = 30). Including only samples over 700 C, the average is -21.2 {+-} 0.2{per_thousand} compared to the accepted value of -21{per_thousand}. Carbon is similarly constant. The average {delta}{sup 13}C value is -2.50{per_thousand} compared to the accepted value of -2.62{per_thousand}. Far more variability is seen during the decomposition of siderite. Two samples were analyzed. In both samples, the initial {delta}{sup 18}O values were far lower than expected

Triple Oxygen Isotope Measurements (Δ\u27\u3csup\u3e17\u3c/sup\u3eO) of Body Water Reflect Water Intake, Metabolism, and δ\u3csup\u3e18\u3c/sup\u3eO of Ingested Water in Passerines

Understanding physiological traits and ecological conditions that influence a species reliance on metabolic water is critical to creating accurate physiological models that can assess their ability to adapt to environmental perturbations (e.g., drought) that impact water availability. However, relatively few studies have examined variation in the sources of water animals use to maintain water balance, and even fewer have focused on the role of metabolic water. A key reason is methodological limitations. Here, we applied a new method that measures the triple oxygen isotopic composition of a single blood sample to estimate the contribution of metabolic water to the body water pool of three passerine species. This approach relies on Δ\u2717O, defined as the residual from the tight linear correlation that naturally exists between δ17O and δ18O values. Importantly, Δ\u2717O is relatively insensitive to key fractionation processes, such as Rayleigh distillation in the water cycle that have hindered previous isotope-based assessments of animal water balance. We evaluated the effects of changes in metabolic rate and water intake on Δ\u2717O values of captive rufous-collared sparrows (Zonotrichia capensis) and two invertivorous passerine species in the genus Cinclodes from the field. As predicted, colder acclimation temperatures induced increases in metabolic rate, decreases in water intake, and increases in the contribution of metabolic water to the body water pool of Z. capensis, causing a consistent change in Δ\u2717O. Measurement of Δ\u2717O also provides an estimate of the δ18O composition of ingested pre-formed (drinking/food) water. Estimated δ18O values of drinking/food water for captive Z. capensis were ~ −11‰, which is consistent with that of tap water in Santiago, Chile. In contrast, δ18O values of drinking/food water ingested by wild-caught Cinclodeswere similar to that of seawater, which is consistent with their reliance on marine resources. Our results confirm the utility of this method for quantifying the relative contribution of metabolic versus pre-formed drinking/food water to the body water pool in birds

A Multi-Isotope Approach Reveals Seasonal Variation in the Reliance on Marine Resources, Production of Metabolic Water, and Ingestion of Seawater by Two Species of Coastal Passerine to Maintain Water Balance

Tracing how free-ranging organisms interact with their environment to maintain water balance is a difficult topic to study for logistical and methodological reasons. We use a novel combination of triple-oxygen stable isotope analyses of water extracted from plasma (δ16O, δ17O, δ18O) and bulk tissue carbon (δ13C) and nitrogen (δ15N) isotopes of feathers and blood to estimate the proportional contribution of marine resources, seawater, and metabolic water used by two species of unique songbirds (genus Cinclodes) to maintain their water balance in a seasonal coastal environment. We also assessed the physiological adjustments that these birds use to maintain their water balance. In agreement with previous work on these species, δ13C and δ15N data show that the coastal resident and invertivore C. nigrofumosus consumes a diet rich in marine resources, while the diet of migratory C. oustaleti shifts seasonally between marine (winter) to freshwater aquatic resources (summer). Triple-oxygen isotope analysis (Δ17O) of blood plasma, basal metabolic rate (BMR), and total evaporative water loss (TEWL) revealed that ~25% of the body water pool of both species originated from metabolic water, while the rest originated from a mix of seawater and fresh water. Δ17O measurements suggest that the contribution of metabolic water tends to increase in summer in C. nigrofumosus, which is coupled with a significant increase in BMR and TEWL. The two species had similar BMR and TEWL during the austral winter when they occur sympatrically in coastal environments. We also found a positive and significant association between the use of marine resources as measured by δ13C and δ15N values and the estimated δ18O values of ingested (pre-formed) water in both species, which indicates that Cinclodes do not directly drink seawater but rather passively ingest when consuming marine invertebrates. Finally, results obtained from physiological parameters and the isotope-based estimates of marine (food and water) resource use are consistent, supporting the use of the triple-oxygen isotopes to quantify the contribution of water sources to the total water balance of free-ranging birds

13[C]-Urea Breath Test as a Novel Point-of-Care Biomarker for Tuberculosis Treatment and Diagnosis

BACKGROUND: Pathogen-specific metabolic pathways may be detected by breath tests based on introduction of stable isotopically-labeled substrates and detection of labeled products in exhaled breath using portable infrared spectrometers. METHODOLOGY/PRINCIPAL FINDINGS: We tested whether mycobacterial urease activity could be utilized in such a breath test format as the basis of a novel biomarker and diagnostic for pulmonary TB. Sensitized New-Zealand White Rabbits underwent bronchoscopic infection with either Mycobacterium bovis or Mycobacterium tuberculosis. Rabbits were treated with 25 mg/kg of isoniazid (INH) approximately 2 months after infection when significant cavitary lung pathology was present. [(13)C] urea was instilled directly into the lungs of intubated rabbits at selected time points, exhaled air samples analyzed, and the kinetics of delta(13)CO(2) formation were determined. Samples obtained prior to inoculation served as control samples for background (13)CO(2) conversion in the rabbit model. (13)CO(2), from metabolic conversion of [(13)C]-urea by mycobacterial urease activity, was readily detectable in the exhaled breath of infected rabbits within 15 minutes of administration. Analyses showed a rapid increase in the rate of (13)CO(2) formation both early in disease and prior to treatment with INH. Following INH treatment, all evaluable rabbits showed a decrease in the rate of (13)CO(2) formation. CONCLUSIONS/SIGNIFICANCE: Urea breath testing may provide a useful diagnostic and biomarker assay for tuberculosis and for treatment response. Future work will test specificity for M. tuberculosis using lung-targeted dry powder inhalation formulations, combined with co-administering oral urease inhibitors together with a saturating oral dose of unlabeled urea, which would prevent the delta(13)CO(2) signal from urease-positive gastrointestinal organisms

The contribution of depressive ‘disorder characteristics’ to determinations of prognosis for adults with depression : an individual patient data meta-analysis

This is the final version. Available on open access from Cambridge University Press via the DOI in this record.The supplementary material for this article can be found at https://doi.org/10.1017/S0033291721001367Background This study aimed to investigate general factors associated with prognosis regardless of the type of treatment received, for adults with depression in primary care. Methods We searched Medline, Embase, PsycINFO and Cochrane Central (inception to 12/01/2020) for RCTs that included the most commonly used comprehensive measure of depressive and anxiety disorder symptoms and diagnoses, in primary care depression RCTs (the Revised Clinical Interview Schedule: CIS-R). Two-stage random-effects meta-analyses were conducted. Results. Twelve (n = 6024) of thirteen eligible studies (n = 6175) provided individual patient data. There was a 31% (95%CI: 25 to 37) difference in depressive symptoms at 3–4 months per standard deviation increase in baseline depressive symptoms. Four additional factors: the duration of anxiety; duration of depression; comorbid panic disorder; and a history of antidepressant treatment were also independently associated with poorer prognosis. There was evidence that the difference in prognosis when these factors were combined could be of clinical importance. Adding these variables improved the amount of variance explained in 3–4 month depressive symptoms from 16% using depressive symptom severity alone to 27%. Risk of bias (assessed with QUIPS) was low in all studies and quality (assessed with GRADE) was high. Sensitivity analyses did not alter our conclusions. Conclusions. When adults seek treatment for depression clinicians should routinely assess for the duration of anxiety, duration of depression, comorbid panic disorder, and a history of antidepressant treatment alongside depressive symptom severity. This could provide clinicians and patients with useful and desired information to elucidate prognosis and aid the clinical management of depression. IntroductionMedical Research Council (MRC)Wellcome TrustMQ FoundationNational Institute of Health Research (NIHR)University College LondonUniversity of PennsylvaniaUniversity of SouthamptonUniversity of YorkUniversity of Exete

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment