Working with a tiny cantilever, physicists managed to violate the second law of thermodynamics, using less energy than expected to change the cantilever’s motion

As a 15-kilometre crack formed ahead of the recent eruptions, magma flowed into it at the highest rate observed anywhere in the world

The Kikai-Akahoya eruption of an underwater volcano off the coast of Japan ejected enough material to fill Lake Tahoe twice, three times as much as the eruption of Mount Tambora in 1815

The networks of fibre optic cables that criss-cross the planet could be used to better understand what’s happening inside it

Long feted by fossil hunters and geologists, if UNESCO recognises the extraordinary rock formation at Madygen in Kyrgyzstan, it will soon be a player on the world stage

Millions of tonnes of water vapour have been lingering in the atmosphere since the Hunga Tonga-Hunga Ha’apai volcano erupted in 2022– possibly contributing to global warming

The books, TV, games and more that New Scientist staff have enjoyed this week

A scientific drilling ship has burrowed further into Earth’s mantle than ever before, obtaining new clues about the processes that feed oceanic volcanoes and the possible origins of life

After over a year of record-high global sea temperatures, the equatorial Atlantic is cooling off more quickly than ever recorded, which could impact weather around the world

An annual accounting of CO2 emissions from burning fossil fuels and land use change finds no sign emissions will peak this year

As organic material in a bone gets replaced by minerals over time, it becomes a fossil. But that can happen at different rates even within the same individual

The technologies introduced by the Romans after they conquered Britain led to the kind of economic growth seen in the industrial age

An analysis of 20,000 metal objects from Bronze Age Europe suggests human economic behaviour may not have changed much over the past 3500 years

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The poly(A) signal, together with auxiliary elements, directs cleavage of a pre-mRNA and thus determines the 3' end of the mature transcript. In many species, including humans, the poly(A) signal is an AAUAAA hexamer, but we recently found that the deeply branching eukaryote Giardia lamblia uses a distinct hexamer (AGURAA) and lacks any known auxiliary elements. Our discovery prompted us to explore the evolutionary dynamics of poly(A) signals and auxiliary elements in the eukaryotic kingdom. We use direct RNA sequencing to determine poly(A) signals for four protists within the Metamonada clade (which also contains G. lamblia) and two outgroup protists. These experiments reveal that the AAUAAA hexamer serves as the poly(A) signal in at least four different eukaryotic clades, indicating that it is likely the ancestral signal, whereas the unusual Giardia version is derived. We find that the use and relative strengths of auxiliary elements are also plastic; in fact, within Metamonada, species like G. lamblia make use of a previously unrecognized auxiliary element where nucleotides flanking the poly(A) signal itself specify genuine cleavage sites. Thus, despite the fundamental nature of pre-mRNA cleavage for the expression of all protein-coding genes, the motifs controlling this process are dynamic on evolutionary timescales, providing motivation for future biochemical and structural studies as well as new therapeutic angles to target eukaryotic pathogens.

Two decades into the era of Electronic Health Records (EHRs), the promise of streamlining clinical care, reducing burden, and improving patient outcomes has yet to be realized. A cross-sectional family physician census conducted by the American Board of Family Medicine in 2022 and 2023 included self-reported physician EHR satisfaction. Of the nearly 10,000 responding family physicians, only one-in-four (26.2%) report being very satisfied and one-in-three (33.8%) were not satisfied. These low levels of satisfaction point to the need for greater transparency in the marketplace and pressure to increase user-centric EHR design.

Introduction:

High-quality primary care can reduce avoidable emergency department visits and emergency hospitalizations. The availability of electronic medical record (EMR) data and capacities for data storage and processing have created opportunities for predictive analytics. This systematic review examines studies which predict emergency department visits, hospitalizations, and mortality using EMR data from primary care.

Massively parallel reporter assays (MPRAs) are powerful tools for quantifying the impacts of sequence variation on gene expression. Reading out molecular phenotypes with sequencing enables interrogating the impact of sequence variation beyond genome scale. Machine learning models integrate and codify information learned from MPRAs and enable generalization by predicting sequences outside the training data set. Models can provide a quantitative understanding of cis-regulatory codes controlling gene expression, enable variant stratification, and guide the design of synthetic regulatory elements for applications from synthetic biology to mRNA and gene therapy. This review focuses on cis-regulatory MPRAs, particularly those that interrogate cotranscriptional and post-transcriptional processes: alternative splicing, cleavage and polyadenylation, translation, and mRNA decay.

Caenorhabditis elegans is an important model organism for human health and disease, with foundational contributions to the understanding of gene expression and tissue patterning in animals. An invaluable tool in modern gene expression research is the presence of a high-resolution ribosome structure, though no such structure exists for C. elegans. Here, we present a high-resolution single-particle cryogenic electron microscopy (cryo-EM) reconstruction and molecular model of a C. elegans ribosome, revealing a significantly streamlined animal ribosome. Many facets of ribosome structure are conserved in C. elegans, including overall ribosomal architecture and the mechanism of cycloheximide, whereas other facets, such as expansion segments and eL28, are rapidly evolving. We identify uL5 and uL23 as two instances of tissue-specific ribosomal protein paralog expression conserved in Caenorhabditis, suggesting that C. elegans ribosomes vary across tissues. The C. elegans ribosome structure will provide a basis for future structural, biochemical, and genetic studies of translation in this important animal system.

The spliceosome is a eukaryotic multimegadalton RNA–protein complex that removes introns from transcripts. The spliceosome ensures the selection of each exon-intron boundary through multiple recognition events. Initially, the 5' splice site (5' SS) and branch site (BS) are bound by the U1 small nuclear ribonucleoprotein (snRNP) and the U2 snRNP, respectively, while the 3' SS is mostly determined by proximity to the branch site. A large number of splicing factors recognize the splice sites and recruit the snRNPs before the stable binding of the snRNPs occurs by base-pairing the snRNA to the transcript. Fidelity of this process is crucial, as mutations in splicing factors and U2 snRNP components are associated with many diseases. In recent years, major advances have been made in understanding how splice sites are selected in Saccharomyces cerevisiae and humans. Here, I review and discuss the current understanding of the recognition of splice sites by the spliceosome with a focus on recognition and binding of the branch site by the U2 snRNP in humans.

Extract

With a disproportionate burden of tuberculosis (TB) amongst migrants in Europe [1], Burman et al. [2] have highlighted the pressing need for alternative approaches to make TB infection (TBI) screening comprehensive and accessible. Across high-income Organisation for Economic Co-operation and development countries, a median of 52% of TB cases occur in foreign-born individuals, who are at their highest risk of developing TB disease within the first 5 years of migration [3]. Molecular epidemiological studies indicate that the majority of these cases occur as a result of TBI reactivation, often acquired overseas [4]. Within the UK, overseas-born migrants have a 14-fold higher TB incidence than UK-born individuals [5]. The World Health Organization therefore recommends that migrants from countries with a high TB burden may be prioritised for TBI screening [6, 7].

Extract

In cystic fibrosis (CF), Pseudomonas aeruginosa acquisition represents a turning point in disease progression. The presence of chronic P. aeruginosa infection is associated with worsening lung function and increased risk of earlier death, whereas treatment substantially improves lung function and survival [1, 2]. Efforts to diagnose and eradicate early P. aeruginosa provide lasting benefits for children with CF [3, 4]. However, the timing of infection varies considerably between individuals with CF, treatment centres [5, 6], and different birth cohorts of people with the disease [7, 8].

Background

Control of latent tuberculosis infection (LTBI) is a priority in the World Health Organization strategy to eliminate TB. Many high-income, low TB incidence countries have prioritised LTBI screening and treatment in recent migrants. We tested whether a novel model of care, based entirely within primary care, was effective and safe compared to secondary care.

BACKGROUND AND PURPOSE:

Intracranial vessel wall imaging is technically challenging to implement, given the simultaneous requirements of high spatial resolution, excellent blood and CSF signal suppression, and clinically acceptable gradient times. Herein, we present our preliminary findings on the evaluation of a deep learning–optimized sequence using T1-weighted imaging.

BackgroundOrlistat is recommended as an adjunct to diet and exercise for weight loss in the treatment of type 2 diabetes mellitus (T2DM).AimTo explore associations between patient characteristics and orlistat prescribing, and to determine associations of orlistat with weight loss in T2DM and prediabetes.Design and settingCohort study using anonymised health records from a UK database of general practice.MethodThe UK Clinical Practice Research Datalink (CPRD) Aurum database was searched to compile a cohort of patients aged ≥18 years, first diagnosed with T2DM or prediabetes in 2016 or 2017. Once the data had been collated, multivariable logistic regression models were used to determine associations with starting orlistat and stopping it early (<12 weeks of prescriptions) and orlistat’s associations with weight loss in those who had not been prescribed second-line antidiabetic medications.ResultsOut of 100 552 patients with incident T2DM or prediabetes, 655 (0.8%) patients with T2DM and 128 (0.7%) patients with prediabetes were prescribed orlistat. Younger people, females, those in areas of deprivation, current smokers, those coprescribed metformin, and those recorded as having hypertension were statistically significantly more likely to be prescribed orlistat; higher baseline glycated haemoglobin levels were associated with early stopping. In comparison with patients not on orlistat, those who continued using it for ≥12 weeks were more likely to lose ≥5% weight (adjusted odds ratio [AOR] 1.69, 95% confidence interval [CI] = 1.07 to 2.67) but those who stopped orlistat early were less likely to lose ≥5% weight (AOR 0.56, 95% CI = 0.29 to 1.09).ConclusionOrlistat was significantly associated with weight loss in patients with T2DM and prediabetes when taken for at least 12 weeks; however, it was infrequently prescribed and often taken for <12 weeks. Orlistat may be a useful adjunct to lifestyle modifications for patients with T2DM and prediabetes, but barriers to continued use means it may not be effective for everyone in managing weight loss.

Comprehensive maps of neuronal connectivity provide a foundation for understanding the structure of neural circuits. In a circuit, neurons are diverse in morphology, electrophysiology, gene expression, activity, and other neuronal properties. Thus, constructing a comprehensive connectivity map requires associating various properties of neurons, including their connectivity, at cellular resolution. A commonly used approach is to use the gene expression profiles as an anchor to which all other neuronal properties are associated. Recent advances in genomics and anatomical techniques dramatically improved the ability to determine and associate the long-range projections of neurons with their gene expression profiles. These studies revealed unprecedented details of the gene–projection relationship, but also highlighted conceptual challenges in understanding this relationship. In this article, I delve into the findings and the challenges revealed by recent studies using state-of-the-art neuroanatomical and transcriptomic techniques. Building upon these insights, I propose an approach that focuses on understanding the gene–projection relationship through basic features in gene expression profiles and projections, respectively, that associate with underlying cellular processes. I then discuss how the developmental trajectories of projections and gene expression profiles create additional challenges and necessitate interrogating the gene–projection relationship across time. Finally, I explore complementary strategies that, together, can provide a comprehensive view of the gene–projection relationship.

The current growth and consumption based economy is not sustainable. The world must move towards a circular economy and sustainability.

The post Degrowth, green energy, social equity, and circular economy appeared first on rabble.ca.

PM Malcolm Turnbull says Australians should vote to keep a stable majority government in uncertain economic times, as the fallout from Brexit continues.