Microbial carbon mineralization in tropical lowland and montane forest soils of Peru

Climate change is affecting the amount and complexity of plant inputs to tropical forest soils. This is likely to influence the carbon (C) balance of these ecosystems by altering decomposition processes e.g., "positive priming effects" that accelerate soil organic matter mineralization. However, the mechanisms determining the magnitude of priming effects are poorly understood. We investigated potential mechanisms by adding (13)C labeled substrates, as surrogates of plant inputs, to soils from an elevation gradient of tropical lowland and montane forests. We hypothesized that priming effects would increase with elevation due to increasing microbial nitrogen limitation, and that microbial community composition would strongly influence the magnitude of priming effects. Quantifying the sources of respired C (substrate or soil organic matter) in response to substrate addition revealed no consistent patterns in priming effects with elevation. Instead we found that substrate quality (complexity and nitrogen content) was the dominant factor controlling priming effects. For example a nitrogenous substrate induced a large increase in soil organic matter mineralization whilst a complex C substrate caused negligible change. Differences in the functional capacity of specific microbial groups, rather than microbial community composition per se, were responsible for these substrate-driven differences in priming effects. Our findings suggest that the microbial pathways by which plant inputs and soil organic matter are mineralized are determined primarily by the quality of plant inputs and the functional capacity of microbial taxa, rather than the abiotic properties of the soil. Changes in the complexity and stoichiometry of plant inputs to soil in response to climate change may therefore be important in regulating soil C dynamics in tropical forest soils.This study was financed by the UK Natural Environment Research Council (NERC) grant NE/G018278/1 and is a product of the Andes Biodiversity and Ecosystem Research Group consortium (www.andesconservation.org); Patrick Meir was also supported by ARC FT110100457

Comparative study of ChatGPT and human evaluators on the assessment of medical literature according to recognized reportingstandards

Introduction Amid clinicians’ challenges in staying updated with medical research, artificial intelligence (AI) tools like the large language model (LLM) ChatGPT could automate appraisal of research quality, saving time and reducing bias. This study compares the proficiency of ChatGPT3 against human evaluation in scoring abstracts to determine its potential as a tool for evidence synthesis.Methods We compared ChatGPT’s scoring of implant dentistry abstracts with human evaluators using the Consolidated Standards of Reporting Trials for Abstracts reporting standards checklist, yielding an overall compliance score (OCS). Bland-Altman analysis assessed agreement between human and AI-generated OCS percentages. Additional error analysis included mean difference of OCS subscores, Welch’s t-test and Pearson’s correlation coefficient.Results Bland-Altman analysis showed a mean difference of 4.92% (95% CI 0.62%, 0.37%) in OCS between human evaluation and ChatGPT. Error analysis displayed small mean differences in most domains, with the highest in ‘conclusion’ (0.764 (95% CI 0.186, 0.280)) and the lowest in ‘blinding’ (0.034 (95% CI 0.818, 0.895)). The strongest correlations between were in ‘harms’ (r=0.32, p<0.001) and ‘trial registration’ (r=0.34, p=0.002), whereas the weakest were in ‘intervention’ (r=0.02, p<0.001) and ‘objective’ (r=0.06, p<0.001).Conclusion LLMs like ChatGPT can help automate appraisal of medical literature, aiding in the identification of accurately reported research. Possible applications of ChatGPT include integration within medical databases for abstract evaluation. Current limitations include the token limit, restricting its usage to abstracts. As AI technology advances, future versions like GPT4 could offer more reliable, comprehensive evaluations, enhancing the identification of high-quality research and potentially improving patient outcomes

Impact of the COVID-19 global pandemic on symptomatic diagnosis of cancer - the view from primary care

The entire landscape of cancer management in primary care, from case identification to the management of those living with and beyond cancer, is evolving rapidly in the face of the coronavirus (COVID-19) pandemic.1 In a climate of fear and mandated avoidance of all but essential clinical services, delays in patient, population and healthcare system responses to suspected cancer symptoms seem inevitable

A Gravitationally Lensed Supernova with an Observable Two-Decade Time Delay

When the light from a distant object passes very near to a foreground galaxy or cluster, gravitational lensing can cause it to appear as multiple images on the sky. If the source is variable, it can be used to constrain the cosmic expansion rate and dark energy models. Achieving these cosmological goals requires many lensed transients with precise time delay measurements. Lensed supernovae (SN) are attractive for this purpose because they have relatively simple photometric behavior, with well-understood light curve shapes and colours $-$ in contrast to the stochastic variation of quasars. Here we report the discovery of a multiply-imaged supernova, AT2016jka ("SN Requiem"). It appeared in an evolved galaxy at $z=1.95$, gravitationally lensed by a foreground galaxy cluster. It is likely a Type Ia supernova $-$ the explosion of a low-mass stellar remnant, whose light curve can be used to measure cosmic distances. In archival Hubble Space Telescope imaging, three lensed images of the supernova are detected with relative time delays of $<$200 days. We predict a fourth image will appear close to the cluster core in the year 2037$\pm$2. Observation of the fourth image could provide a time delay precision of $\approx$7 days, $<1\%$ of the extraordinary 20 year baseline. The SN classification and the predicted reappearance time could be improved with further lens modelling and a comprehensive analysis of systematic uncertainties.Comment: Accepted for publication in a peer-reviewed journal. Main text = 6 pages, 3 figures, 1 table; Full document = 28 pages, 12 figures with Methods, Supplemental Info and references. v2: reformatted; minor corrections in S

Microbial responses to warming enhance soil carbon loss following translocation across a tropical forest elevation gradient

Tropical soils contain huge carbon stocks, which climate warming is projected to reduce by stimulating organic matter decomposition, creating a positive feedback that will promote further warming. Models predict that the loss of carbon from warming soils will be mediated by microbial physiology, but no empirical data are available on the response of soil carbon and microbial physiology to warming in tropical forests, which dominate the terrestrial carbon cycle. Here we show that warming caused a considerable loss of soil carbon that was enhanced by associated changes in microbial physiology. By translocating soils across a 3000 m elevation gradient in tropical forest, equivalent to a temperature change of ± 15 °C, we found that soil carbon declined over 5 years by 4% in response to each 1 °C increase in temperature. The total loss of carbon was related to its original quantity and lability, and was enhanced by changes in microbial physiology including increased microbial carbon‐use‐efficiency, shifts in community composition towards microbial taxa associated with warmer temperatures, and increased activity of hydrolytic enzymes. These findings suggest that microbial feedbacks will cause considerable loss of carbon from tropical forest soils in response to predicted climatic warming this century

The International Surface Pressure Databank version 2

The International Surface Pressure Databank (ISPD) is the world's largest collection of global surface and sea-level pressure observations. It was developed by extracting observations from established international archives, through international cooperation with data recovery facilitated by the Atmospheric Circulation Reconstructions over the Earth (ACRE) initiative, and directly by contributing universities, organizations, and countries. The dataset period is currently 1768–2012 and consists of three data components: observations from land stations, marine observing systems, and tropical cyclone best track pressure reports. Version 2 of the ISPD (ISPDv2) was created to be observational input for the Twentieth Century Reanalysis Project (20CR) and contains the quality control and assimilation feedback metadata from the 20CR. Since then, it has been used for various general climate and weather studies, and an updated version 3 (ISPDv3) has been used in the ERA-20C reanalysis in connection with the European Reanalysis of Global Climate Observations project (ERA-CLIM). The focus of this paper is on the ISPDv2 and the inclusion of the 20CR feedback metadata. The Research Data Archive at the National Center for Atmospheric Research provides data collection and access for the ISPDv2, and will provide access to future versions

CTGF drives autophagy, glycolysis and senescence in cancer-associated fibroblasts via HIF1 activation, metabolically promoting tumor growth

Previous studies have demonstrated that loss of caveolin-1 (Cav-1) in stromal cells drives the activation of the TGF-β signaling, with increased transcription of TGF-β target genes, such as connective tissue growth factor (CTGF). In addition, loss of stromal Cav-1 results in the metabolic reprogramming of cancer-associated fibroblasts, with the induction of autophagy and glycolysis. However, it remains unknown if activation of the TGF-β / CTGF pathway regulates the metabolism of cancer-associated fibroblasts. Therefore, we investigated whether CTGF modulates metabolism in the tumor microenvironment. For this purpose, CTGF was overexpressed in normal human fibroblasts or MDA-MB-231 breast cancer cells. Overexpression of CTGF induces HIF-1α-dependent metabolic alterations, with the induction of autophagy/mitophagy, senescence, and glycolysis. Here, we show that CTGF exerts compartment-specific effects on tumorigenesis, depending on the cell-type. In a xenograft model, CTGF overexpressing fibroblasts promote the growth of co-injected MDA-MB-231 cells, without any increases in angiogenesis. Conversely, CTGF overexpression in MDA-MB-231 cells dramatically inhibits tumor growth in mice. Intriguingly, increased extracellular matrix deposition was seen in tumors with either fibroblast or MDA-MB-231 overexpression of CTGF. Thus, the effects of CTGF expression on tumor formation are independent of its extracellular matrix function, but rather depend on its ability to activate catabolic metabolism. As such, CTGF-mediated induction of autophagy in fibroblasts supports tumor growth via the generation of recycled nutrients, whereas CTGF-mediated autophagy in breast cancer cells suppresses tumor growth, via tumor cell self-digestion. Our studies shed new light on the compartment-specific role of CTGF in mammary tumorigenesis, and provide novel insights into the mechanism(s) generating a lethal tumor microenvironment in patients lacking stromal Cav-1. As loss of Cav-1 is a stromal marker of poor clinical outcome in women with primary breast cancer, dissecting the downstream signaling effects of Cav-1 are important for understanding disease pathogenesis, and identifying novel therapeutic targets

JWST UNCOVER: Discovery of z>9z>9 Galaxy Candidates Behind the Lensing Cluster Abell 2744

We present the results of a search for high-redshift ($z>9$) galaxy candidates in the JWST UNCOVER survey, using deep NIRCam and NIRISS imaging in 7 bands over $\sim45$ arcmin$^2$ and ancillary HST observations. The NIRCam observations reach a $5-\sigma$ limiting magnitude of $\sim 29.2$ AB. The identification of high$-z$ candidates relies on a combination of a dropout selection and photometric redshifts. We find 16 candidates at $9<z<12$ and 3 candidates at $12<z<13$, eight candidates are deemed very robust. Their lensing amplification ranges from $\mu=1.2$ to 11.5. Candidates have a wide range of (lensing-corrected) luminosities and young ages, with low stellar masses ($6.8<$ log(M$_{\star}$/M$_{\odot}$) $<9.5$) and low star formation rates (SFR=0.2-7 M$_{\odot}$ yr$^{-1}$), confirming previous findings in early JWST observations of $z>9$. A few galaxies at $z\sim9-10$ appear to show a clear Balmer break between the F356W and F444W/F410M bands, which helps constrain their stellar mass. We estimate blue UV continuum slopes between $\beta=-1.8$ and $-2.3$, typical for early galaxies at $z>9$ but not as extreme as the bluest recently discovered sources. We also find evidence for a rapid redshift-evolution of the mass-luminosity relation and a redshift-evolution of the UV continuum slope for a given range of intrinsic magnitude, in line with theoretical predictions. These findings suggest that deeper JWST observations are needed to reach the fainter galaxy population at those early epochs, and follow-up spectroscopy will help better constrain the physical properties and star formation histories of a larger sample of galaxies.Comment: Submitted to MNRA

Body mass index and height over three generations: evidence from the Lifeways cross-generational cohort study

Background: Obesity and its measure of body mass index are strongly determined by parental body size. Debate continues as to whether both parents contribute equally to offspring body mass which is key to understanding the aetiology of the disease. The aim of this study was to use cohort data from three generations of one family to examine the relative maternal and paternal associations with offspring body mass index and how these associations compare with family height to demonstrate evidence of genetic or environmental cross-generational transmission. Methods: 669 of 1082 families were followed up in 2007/8 as part of the Lifeways study, a prospective observational cross-generation linkage cohort. Height and weight were measured in 529 Irish children aged 5 to 7 years and were self-reported by parents and grandparents. All adults provided information on self-rated health, education status, and indicators of income, diet and physical activity. Associations between the weight, height, and body mass index of family members were examined with mixed models and heritability estimates computed using linear regression analysis. Results: Self-rated health was associated with lower BMI for all family members, as was age for children. When these effects were accounted for evidence of familial associations of BMI from one generation to the next was more apparent in the maternal line. Heritability estimates were higher (h2 = 0.40) for mother-offspring pairs compared to father-offspring pairs (h2 = 0.22). In the previous generation, estimates were higher between mothersparents (h2 = 0.54-0.60) but not between fathers-parents (h2 = -0.04-0.17). Correlations between mother and offspring across two generations remained significant when modelled with fixed variables of socioeconomic status, health, and lifestyle. A similar analysis of height showed strong familial associations from maternal and paternal lines across each generation. Conclusions: This is the first family cohort study to report an enduring association between mother and offspring BMI over three generations. The evidence of BMI transmission over three generations through the maternal line in an observational study corroborates the findings of animal studies. A more detailed analysis of geno and phenotypic data over three generations is warranted to understand the nature of this maternal-offspring relationship.TS 24.4.1