3d single-ion magnets Craig, Gavin A; Murrie, Mark
Chemical Society reviews,
04/2015, Letnik:
44, Številka:
8
Journal Article
Recenzirano
Odprti dostop
One of the determining factors in whether single-molecule magnets (SMMs) may be used as the smallest component of data storage, is the size of the barrier to reversal of the magnetisation,
U
eff
. ...This physical quantity depends on the magnitude of the magnetic anisotropy of a complex and the size of its spin ground state. In recent years, there has been a growing focus on maximising the anisotropy generated for a single 3d transition metal (TM) ion, by an appropriate ligand field, as a means of achieving higher barriers. Because the magnetic properties of these compounds arise from a single ion in a ligand field, they are often referred to as single-ion magnets (SIMs). Here, the synthetic chemist has a significant role to play, both in the design of ligands to enforce propitious splitting of the 3d orbitals and in the judicious choice of TM ion. Since the publication of the first 3d-based SIM, which was based on Fe(
ii
), many other contributions have been made to this field, using different first row TM ions, and exploring varied coordination environments for the paramagnetic ions.
This review describes the recent approach to obtain single-molecule magnets where the magnetic properties arise from just one first row transition metal ion in a suitable ligand field.
The gut microbiome Kuziel, Gavin A.; Rakoff-Nahoum, Seth
CB/Current biology,
03/2022, Letnik:
32, Številka:
6
Journal Article
Recenzirano
Odprti dostop
All animals, from cnidarians to humans, are colonized with microbes, and the greatest diversity and magnitude of these host-associated microorganisms resides within the intestine. Referred to as the ...gut microbiome, membership can be as simple as one species of bacteria or can be composed of hundreds to thousands of different microbes across the domains of life. The relationship between the gut microbiome and host span from beneficial to detrimental; interactions may be context-dependent and occur across host physiology and organ systems. In this Primer, we focus on the mammalian host to discuss basic mechanisms by which the gut microbiome impacts the host and review mechanisms by which hosts and the environment shape the microbiome. We end by highlighting key concepts and discussing future directions for the field that will be critical for generating the next generation of knowledge of the gut microbiome.
All animals are colonized with microbes, particularly in the intestinal tract. In this Primer, Gavin Kuziel and Seth Rakoff-Nahoum focus on the mammalian host to discuss basic mechanisms by which the gut microbiome impacts the host, and vice-versa, highlighting key concepts and future directions critical for gut microbiome research.
Europe contains 9% of the world population but has a 25% share of the global cancer burden. Up-to-date cancer statistics in Europe are key to cancer planning. Cancer incidence and mortality estimates ...for 25 major cancers are presented for the 40 countries in the four United Nations-defined areas of Europe and for Europe and the European Union (EU-28) for 2018.
Estimates of national incidence and mortality rates for 2018 were based on statistical models applied to the most recently published data, with predictions obtained from recent trends, where possible. The estimated rates in 2018 were applied to the 2018 population estimates to obtain the estimated numbers of new cancer cases and deaths in Europe in 2018.
There were an estimated 3.91 million new cases of cancer (excluding non-melanoma skin cancer) and 1.93 million deaths from cancer in Europe in 2018. The most common cancer sites were cancers of the female breast (523,000 cases), followed by colorectal (500,000), lung (470,000) and prostate cancer (450,000). These four cancers represent half of the overall burden of cancer in Europe. The most common causes of death from cancer were cancers of the lung (388,000 deaths), colorectal (243,000), breast (138,000) and pancreatic cancer (128,000). In the EU-28, the estimated number of new cases of cancer was approximately 1.6 million in males and 1.4 million in females, with 790,000 men and 620,000 women dying from the disease in the same year.
The present estimates of the cancer burden in Europe alongside a description of the profiles of common cancers at the national and regional level provide a basis for establishing priorities for cancer control actions across Europe. The estimates presented here are based on the recorded data from 145 population-based cancer registries in Europe. Their long established role in planning and evaluating national cancer plans on the continent should not be undervalued.
•There were an estimated 3.9 million new cases of cancer and 1.9 million deaths from cancer in Europe in 2018.•The most common cancer sites were cancers of the female breast, followed by colorectal, lung and prostate cancer.•The most common causes of death from cancer were cancers of the lung, colorectal, breast and pancreatic cancer.•These estimates of the cancer burden in Europe provide a basis for establishing priorities for cancer control actions across Europe.
We present N-body simulations of planetary system formation in thermally evolving, viscous disc models. The simulations incorporate type I migration (including corotation torques and their ...saturation), gap formation, type II migration, gas accretion on to planetary cores and gas disc dispersal through photoevaporation. The aim is to examine whether or not the oligarchic growth scenario, when combined with self-consistent disc models and up-to-date prescriptions for disc-driven migration, can produce planetary systems similar to those that have been observed. The results correlate with the initial disc mass. Low-mass discs form close-packed systems of terrestrial-mass planets and super-Earths. Higher mass discs form multiple generations of planets, with masses in the range 10 ≲ m
p ≲ 45 M⊕. These planets generally type I migrate into the inner disc, because of corotation torque saturation, where they open gaps and type II migrate into the central star. Occasionally, a final generation of low- to intermediate-mass planets forms and survives due to gas disc dispersal. No surviving gas giants were formed in our simulations. Analysis shows that these planets can only survive migration if a core forms and experiences runaway gas accretion at orbital radii r ≳ 10 au prior to the onset of type II migration. We conclude that planet growth above masses m
p ≳ 10 M⊕ during the gas disc lifetime leads to corotation torque saturation and rapid inward migration, preventing the formation and survival of gas giants. This result is in contrast to the success in forming gas giant planets displayed by some population synthesis models. This discrepancy arises, in part, because the type II migration prescription adopted in the population synthesis models causes too large a reduction in the migration speed when in the planet-dominated regime.
The Intergovernmental Panel on Climate Change (IPCC), to its credit, has recognized this 'hot model' problem. Scientists contributing to the main sections of its Sixth Assessment Report (AR6; ...published over the past few months) reconciled the newest climate models with key observational constraints on global mean warming, sea-level rise and ocean heat content, and other analyses. ...some studies have reported projections that might be inconsistent with AR6 assessments. Hot tail The largest source of uncertainty in global temperatures 50 or 100 years from now is the volume of future greenhouse-gas emissions, which are largely under human control.
Our recent N-body simulations of planetary system formation, incorporating models for the main physical processes thought to be important during the building of planets (i.e. gas disc evolution, ...migration, planetesimal/boulder accretion, gas accretion on to cores, etc.), have been successful in reproducing some of the broad features of the observed exoplanet population (e.g. compact systems of low-mass planets, hot Jupiters), but fail completely to form any surviving cold Jupiters. The primary reason for this failure is rapid inward migration of growing protoplanets during the gas accretion phase, resulting in the delivery of these bodies on to orbits close to the star. Here, we present the results of simulations that examine the formation of gas giant planets in protoplanetary discs that are radially structured due to spatial and temporal variations in the effective viscous stresses, and show that such a model results in the formation of a population of cold gas giants. Furthermore, when combined with models for disc photoevaporation and a central magnetospheric cavity, the simulations reproduce the well-known hot-Jupiter/cold-Jupiter dichotomy in the observed period distribution of giant exoplanets, with a period valley between 10 and 100 d.
Retrospectively comparing future model projections to observations provides a robust and independent test of model skill. Here we analyze the performance of climate models published between 1970 and ...2007 in projecting future global mean surface temperature (GMST) changes. Models are compared to observations based on both the change in GMST over time and the change in GMST over the change in external forcing. The latter approach accounts for mismatches in model forcings, a potential source of error in model projections independent of the accuracy of model physics. We find that climate models published over the past five decades were skillful in predicting subsequent GMST changes, with most models examined showing warming consistent with observations, particularly when mismatches between model‐projected and observationally estimated forcings were taken into account.
Plain Language Summary
Climate models provide an important way to understand future changes in the Earth's climate. In this paper we undertake a thorough evaluation of the performance of various climate models published between the early 1970s and the late 2000s. Specifically, we look at how well models project global warming in the years after they were published by comparing them to observed temperature changes. Model projections rely on two things to accurately match observations: accurate modeling of climate physics and accurate assumptions around future emissions of CO2 and other factors affecting the climate. The best physics‐based model will still be inaccurate if it is driven by future changes in emissions that differ from reality. To account for this, we look at how the relationship between temperature and atmospheric CO2 (and other climate drivers) differs between models and observations. We find that climate models published over the past five decades were generally quite accurate in predicting global warming in the years after publication, particularly when accounting for differences between modeled and actual changes in atmospheric CO2 and other climate drivers. This research should help resolve public confusion around the performance of past climate modeling efforts and increases our confidence that models are accurately projecting global warming.
Key Points
Evaluation of uninitialized multidecadal climate model future projection performance provides a concrete test of model skill
The quasi‐linear relationship between model/observed forcings and temperature change is used to control for errors in projected forcing
Model simulations published between 1970 and 2007 were skillful in projecting future global mean surface warming
Abstract This review explores the topic of microRNAs (miRNAs) for improved early detection of imperceptible cancers, with potential to advance precision medicine and improve patient outcomes. ...Historical research exploring miRNA’s role in cancer detection collectively revealed initial hurdles in identifying specific miRNA signatures for early-stage and difficult-to-detect cancers. Early studies faced challenges in establishing robust biomarker panels and overcoming the heterogeneity of cancer types. Despite this, recent developments have supported the potential of miRNAs as sensitive and specific biomarkers for early cancer detection as well as having demonstrated remarkable potential as diagnostic tools for imperceptible cancers, such as those with elusive symptoms or challenging diagnostic criteria. This review discusses the advent of high-throughput technologies that have enabled comprehensive detection and profiling of unique miRNA signatures associated with early-stage cancers. Furthermore, advancements in bioinformatics and machine-learning techniques are considered, exploring the integration of multi-omics data which have potential to enhance both the accuracy and reliability of miRNA-based cancer detection assays. Finally, perspectives on the continuing development on technologies as well as discussion around challenges that remain, such as the need for standardised protocols and addressing the complex interplay of miRNAs in cancer biology are conferred.
Taxonomic classification of marker-gene sequences is an important step in microbiome analysis.
We present q2-feature-classifier ( https://github.com/qiime2/q2-feature-classifier ), a QIIME 2 plugin ...containing several novel machine-learning and alignment-based methods for taxonomy classification. We evaluated and optimized several commonly used classification methods implemented in QIIME 1 (RDP, BLAST, UCLUST, and SortMeRNA) and several new methods implemented in QIIME 2 (a scikit-learn naive Bayes machine-learning classifier, and alignment-based taxonomy consensus methods based on VSEARCH, and BLAST+) for classification of bacterial 16S rRNA and fungal ITS marker-gene amplicon sequence data. The naive-Bayes, BLAST+-based, and VSEARCH-based classifiers implemented in QIIME 2 meet or exceed the species-level accuracy of other commonly used methods designed for classification of marker gene sequences that were evaluated in this work. These evaluations, based on 19 mock communities and error-free sequence simulations, including classification of simulated "novel" marker-gene sequences, are available in our extensible benchmarking framework, tax-credit ( https://github.com/caporaso-lab/tax-credit-data ).
Our results illustrate the importance of parameter tuning for optimizing classifier performance, and we make recommendations regarding parameter choices for these classifiers under a range of standard operating conditions. q2-feature-classifier and tax-credit are both free, open-source, BSD-licensed packages available on GitHub.
At a distance of 1.295 parsecs, the red dwarf Proxima Centauri (α Centauri C, GL 551, HIP 70890 or simply Proxima) is the Sun's closest stellar neighbour and one of the best-studied low-mass stars. ...It has an effective temperature of only around 3,050 kelvin, a luminosity of 0.15 per cent of that of the Sun, a measured radius of 14 per cent of the radius of the Sun and a mass of about 12 per cent of the mass of the Sun. Although Proxima is considered a moderately active star, its rotation period is about 83 days (ref. 3) and its quiescent activity levels and X-ray luminosity are comparable to those of the Sun. Here we report observations that reveal the presence of a small planet with a minimum mass of about 1.3 Earth masses orbiting Proxima with a period of approximately 11.2 days at a semi-major-axis distance of around 0.05 astronomical units. Its equilibrium temperature is within the range where water could be liquid on its surface.
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