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Aims LDL cholesterol (LDL-C) is the current lipid standard for cardiovascular disease (CVD)-risk assessment in type 1 diabetes. Apolipoprotein B (apoB) may be helpful to further stratify CVD risk. We explored the association between apoB and pulse wave velocity (PWV) to determine if apoB would improve CVD-risk stratification, especially in type 1 diabetes adolescents with borderline LDL-C (100–129 mg/dL). We hypothesized that type 1 diabetes adolescents with borderline LDL-C and elevated apoB (≥90 mg/dL) would have increased PWV compared to those with borderline LDL-C and normal apoB (<90 mg/dL), and that apoB would explain more of the variability of PWV than alternative lipid indices. Methods Fasting lipids, including apoB, were collected in 267 adolescents, age 12–19 years, with diabetes duration >5 years and HbA1c 8.9 ± 1.6 %. Triglyceride to HDL-C ratio (TG/HDL-C) and nonHDL-cholesterol (nonHDL-C) were calculated. PWV was measured in the carotid–femoral segment. Results ApoB, nonHDL-C and TG/HDL-C correlated with PWV ( p  < 0.0001). ApoB, nonHDL-C and TG/HDL-C remained significantly associated with PWV in fully adjusted models. In adolescents with borderline LDL-C ( n  = 61), PWV was significantly higher in those with elevated apoB than in those with normal apoB (5.6 ± 0.6 vs. 5.2 ± 0.6 m/s, p  < 0.01) and also remained significant after adjustment for CVD-risk factors ( p  = 0.0002). Moreover, in those with borderline LDL-C, apoB explained more of the variability of PWV than nonHDL-C and TG/HDL-C. Conclusion Elevated apoB is associated with increased arterial stiffness in type 1 diabetes adolescents. Measurement of apoB in addition to LDL-C may be helpful in stratifying CVD risk in type 1 diabetes adolescents, especially in those with borderline LDL-C.

California has experienced enhanced extreme wildfire behaviour in recent years 1 – 3 , leading to substantial loss of life and property 4 , 5 . Some portion of the change in wildfire behaviour is attributable to anthropogenic climate warming, but formally quantifying this contribution is difficult because of numerous confounding factors 6 , 7 and because wildfires are below the grid scale of global climate models. Here we use machine learning to quantify empirical relationships between temperature (as well as the influence of temperature on aridity) and the risk of extreme daily wildfire growth (>10,000 acres) in California and find that the influence of temperature on the risk is primarily mediated through its influence on fuel moisture. We use the uncovered relationships to estimate the changes in extreme daily wildfire growth risk under anthropogenic warming by subjecting historical fires from 2003 to 2020 to differing background climatological temperatures and aridity conditions. We find that the influence of anthropogenic warming on the risk of extreme daily wildfire growth varies appreciably on a fire-by-fire and day-by-day basis, depending on whether or not climate warming pushes conditions over certain thresholds of aridity, such as 1.5 kPa of vapour-pressure deficit and 10% dead fuel moisture. So far, anthropogenic warming has enhanced the aggregate expected frequency of extreme daily wildfire growth by 25% (5–95 range of 14–36%), on average, relative to preindustrial conditions. But for some fires, there was approximately no change, and for other fires, the enhancement has been as much as 461%. When historical fires are subjected to a range of projected end-of-century conditions, the aggregate expected frequency of extreme daily wildfire growth events increases by 59% (5–95 range of 47–71%) under a low SSP1–2.6 emissions scenario compared with an increase of 172% (5–95 range of 156–188%) under a very high SSP5–8.5 emissions scenario, relative to preindustrial conditions. Quantification of climate warming in California using machine learning shows increased daily wildfire growth risk by 25%, with an expected increase of 59% and 172% in 2100, for low- and very-high-emissions scenarios, respectively.

An observation of a rare merger of two massive submillimetre bright galaxies that is forming stars at an unexpectedly high rate of 2,000 solar masses a year shows that such mergers can indeed form the most massive elliptical galaxies by about redshift 1.5. A massive starburst merger Multi-wavelength observations of the HXMM01 system, a pair of lensed star-forming galaxies first identified in the Herschel Multi-tiered Extragalactic Survey (HerMES), provide a view of a galactic merger taking place about 11 billion years ago, a period when most of the massive elliptical galaxies existing today were formed. Such events are short-lived on cosmological timescales so are rarely observed. The merging galaxies are forming stars at a rate of 2,000 solar masses per year. The gas reservoir is likely to be exhausted within about 200 million years, by which time a massive elliptical galaxy will have been produced. Stellar archaeology 1 shows that massive elliptical galaxies formed rapidly about ten billion years ago with star-formation rates of above several hundred solar masses per year. Their progenitors are probably the submillimetre bright galaxies 2 at redshifts z greater than 2. Although the mean molecular gas mass 3 (5 × 10 10 solar masses) of the submillimetre bright galaxies can explain the formation of typical elliptical galaxies, it is inadequate to form elliptical galaxies 4 that already have stellar masses above 2 × 10 11 solar masses at z  ≈ 2. Here we report multi-wavelength high-resolution observations of a rare merger of two massive submillimetre bright galaxies at z = 2.3. The system is seen to be forming stars at a rate of 2,000 solar masses per year. The star-formation efficiency is an order of magnitude greater than that of normal galaxies, so the gas reservoir will be exhausted and star formation will be quenched in only around 200 million years. At a projected separation of 19 kiloparsecs, the two massive starbursts are about to merge and form a passive elliptical galaxy with a stellar mass of about 4 × 10 11 solar masses. We conclude that gas-rich major galaxy mergers with intense star formation can form the most massive elliptical galaxies by z ≈  1.5.

Increasing fuel aridity due to climate warming has and will continue to increase wildfire danger in California. In addition to reducing global greenhouse gas emissions, one of the primary proposals for counteracting this increase in wildfire danger is a widespread expansion of hazardous fuel reductions. Here, we quantify the potential for fuel reduction to reduce wildfire intensity using empirical relationships derived from historical observations with a novel combination of spatiotemporal resolution (0.375 km, instantaneous) and extent (48 million acres, 9 years). We use machine learning to quantify relationships between sixteen environmental conditions (including ten fuel characteristics and four temperature-affected aridity characteristics) and satellite-observed fire radiative power. We use the derived relationships to create fire intensity potential (FIP) maps for sixty historical weather snapshots at a 2 km and hourly resolution. We then place these weather snapshots in differing background climatological temperature and fuel characteristic conditions to quantify their independent and combined influence on FIP. We find that in order to offset the effect of climate warming under the SSP2-4.5 emissions scenario, fuel reduction would need to be maintained perpetually on ∼3 million acres (or 600 000 acres per year, 1% of our domain, at a 5 year return frequency) by 2050 and ∼8 million acres (or 1.6 million acres per year, 3% of our domain, at a 5 year return frequency) by 2090. Overall, we find substantial potential for fuel reduction to negate the effects of climate warming on FIP.

We present confusion-limited SCUBA-2 450 μm observations in the COSMOS-CANDELS region as part of the James Clerk Maxwell Telescope Large Program SCUBA-2 Ultra Deep Imaging EAO Survey. Our maps at 450 and 850 μm cover an area of 450 arcmin2. We achieved instrumental noise levels of σ 450 = 0.59 mJy beam−1 and σ 850 = 0.09 mJy beam−1 in the deepest area of each map. The corresponding confusion noise levels are estimated to be 0.65 and 0.36 mJy beam−1. Above the 4σ (3.5σ) threshold, we detected 360 (479) sources at 450 μm and 237 (314) sources at 850 μm. We derive the deepest blank-field number counts at 450 μm, covering the flux-density range of 2–43 mJy. These are in agreement with other SCUBA-2 blank-field and lensing-cluster observations but are lower than various model counts. We compare the counts with those in other fields and find that the field-to-field variance observed at 450 μm at the R=6′ scale is consistent with Poisson noise, so there is no evidence of strong 2D clustering at this scale. Additionally, we derive the integrated surface brightness at 450 μm down to 2.1 mJy to be 57.3−6.2+1.0 Jy deg−2, contributing to 41% ± 4% of the 450 μm extragalactic background light (EBL) measured by Cosmic Background Explorer and Planck. Our results suggest that the 450 μm EBL may be fully resolved at 0.08−0.08+0.09 mJy, which extremely deep lensing-cluster observations and next-generation submillimeter instruments with large aperture sizes may be able to achieve.

Transitioning to clean cooking fuels is not only part of achieving SDG7 but also makes a significant contribution to mitigating climate change by reducing carbon emissions. Research projects and pilots across a number of countries in Africa and South Asia have been exploring the suitability and energy performance of different cooking appliances and fuels. The paper presents the first statistical analysis across these multiple datasets to determine the range of energy required to cook dishes using different technologies and fuels. The paper draws out distinctions between African and Asian dishes, notably the impact of energy-intensive dishes prepared mostly in Africa. The paper demonstrates that the standard efficiency-based approaches to comparing the performance of stoves are not appropriate to modern electric cooking devices, so a novel alternative approach based on specific energy consumption and termed energy ratios is developed. Charcoal stoves are shown to use 15 times as much energy as electric pressure cookers (EPCs) to cook African dishes, and a detailed review of how the EPC works explains why this should be. Energy ratios provide a basis for estimating carbon emission reductions associated with transitioning to modern cooking fuels and also for estimating household cooking costs. Fuel and electricity prices from studies show that the cost of cooking with an EPC can be only 20% of the cost of cooking with charcoal, which highlights the potential for modern, energy-efficient electric cooking devices to defy the conventional wisdom of the energy ladder.

A massive starburst galaxy with 100 billion solar masses of gas is identified at a redshift of 6.34; a ‘maximum starburst’ converts the gas into stars at a rate more than 2,000 times that of the Milky Way. A massive starburst galaxy unveiled The physical properties of the first massive starburst galaxies in the Universe provide important clues as to patterns of early cosmic structure formation. But as regions of intense star formation tend to be shrouded in dust, the search for such systems at very high redshift has been a major challenge. Now a massive starburst galaxy has been identified at a redshift z = 6.34, just 880 million years after the Big Bang when the Universe was one-sixteenth of its present age. Line-emission data reveal the presence of 100 billion solar masses of gas, equivalent to at least 40% of the galaxy's baryonic (visible matter) mass. The galaxy hosts an intense starburst, converting gas into stars at a rate more than 2,000 times that of the Milky Way. These findings are consistent with the theory that massive galaxies form via extreme starbursts in the early Universe. Massive present-day early-type (elliptical and lenticular) galaxies probably gained the bulk of their stellar mass and heavy elements through intense, dust-enshrouded starbursts—that is, increased rates of star formation—in the most massive dark-matter haloes at early epochs. However, it remains unknown how soon after the Big Bang massive starburst progenitors exist. The measured redshift ( z ) distribution of dusty, massive starbursts has long been suspected to be biased low in z owing to selection effects 1 , as confirmed by recent findings of systems with redshifts as high as ∼5 (refs 2–4 ). Here we report the identification of a massive starburst galaxy at z = 6.34 through a submillimetre colour-selection technique. We unambiguously determined the redshift from a suite of molecular and atomic fine-structure cooling lines. These measurements reveal a hundred billion solar masses of highly excited, chemically evolved interstellar medium in this galaxy, which constitutes at least 40 per cent of the baryonic mass. A ‘maximum starburst’ converts the gas into stars at a rate more than 2,000 times that of the Milky Way, a rate among the highest observed at any epoch. Despite the overall downturn in cosmic star formation towards the highest redshifts 5 , it seems that environments mature enough to form the most massive, intense starbursts existed at least as early as 880 million years after the Big Bang.

Myeloid-derived suppressor cells (MDSC) contribute to an immunosuppressive network that drives cancer escape by disabling T cell adaptive immunity. The prevailing view is that MDSC-mediated immunosuppression is restricted to tissues where MDSC co-mingle with T cells. Here we show that splenic or, unexpectedly, blood-borne MDSC execute far-reaching immune suppression by reducing expression of the L-selectin lymph node (LN) homing receptor on naïve T and B cells. MDSC-induced L-selectin loss occurs through a contact-dependent, post-transcriptional mechanism that is independent of the major L-selectin sheddase, ADAM17, but results in significant elevation of circulating L-selectin in tumor-bearing mice. Even moderate deficits in L-selectin expression disrupt T cell trafficking to distant LN. Furthermore, T cells preconditioned by MDSC have diminished responses to subsequent antigen exposure, which in conjunction with reduced trafficking, severely restricts antigen-driven expansion in widely-dispersed LN. These results establish novel mechanisms for MDSC-mediated immunosuppression that have unanticipated implications for systemic cancer immunity.

As we enter the next phase of international policy commitments to halt biodiversity loss (e.g., Kunming-Montreal Global Biodiversity Framework), biodiversity indicators will play an important role in forming the robust basis upon which targeted, and time sensitive conservation actions are developed. Population trend indicators are one of the most powerful tools in biodiversity monitoring due to their responsiveness to changes over short timescales and their ability to aggregate species trends from global down to sub-national or even local scale. We consider how the project behind one of the foremost population level indicators - the Living Planet Index - has evolved over the last 25 years, its value to the field of biodiversity monitoring, and how its components have portrayed a compelling account of the changing status of global biodiversity through its application at policy, research and practice levels. We explore ways the project can develop to enhance our understanding of the state of biodiversity and share lessons learned to inform indicator development and mobilise action.