An interpretable machine learning framework for dark matter halo formation

We present a generalization of our recently proposed machine-learning framework, aiming to provide new physical insights into dark matter halo formation. We investigate the impact of the initial density and tidal shear fields on the formation of haloes over the mass range 11.4 ≤ log (M/M⊙) ≤ 13.4. The algorithm is trained on an N-body simulation to infer the final mass of the halo to which each dark matter particle will later belong. We then quantify the difference in the predictive accuracy between machine-learning models using a metric based on the Kullback–Leibler divergence. We first train the algorithm with information about the density contrast in the particles’ local environment. The addition of tidal shear information does not yield an improved halo collapse model over one based on density information alone; the difference in their predictive performance is consistent with the statistical uncertainty of the density-only based model. This result is confirmed as we verify the ability of the initial conditions-to-halo mass mapping learnt from one simulation to generalize to independent simulations. Our work illustrates the broader potential of developing interpretable machine-learning frameworks to gain physical understanding of non-linear large-scale structure formation

Trypanosoma brucei PRMT1 Is a Nucleic Acid Binding Protein with a Role in Energy Metabolism and the Starvation Stress Response.

In Trypanosoma brucei and related kinetoplastid parasites, transcription of protein coding genes is largely unregulated. Rather, mRNA binding proteins, which impact processes such as transcript stability and translation efficiency, are the predominant regulators of gene expression. Arginine methylation is a posttranslational modification that preferentially targets RNA binding proteins and is, therefore, likely to have a substantial impact on T. brucei biology. The data presented here demonstrate that cells depleted of T. brucei PRMT1 (TbPRMT1), a major type I protein arginine methyltransferase, exhibit decreased virulence in an animal model. To understand the basis of this phenotype, quantitative global proteomics was employed to measure protein steady-state levels in cells lacking TbPRMT1. The approach revealed striking changes in proteins involved in energy metabolism. Most prominent were a decrease in glycolytic enzyme abundance and an increase in proline degradation pathway components, changes that resemble the metabolic remodeling that occurs during T. brucei life cycle progression. The work describes several RNA binding proteins whose association with mRNA was altered in TbPRMT1-depleted cells, and a large number of TbPRMT1-interacting proteins, thereby highlighting potential TbPRMT1 substrates. Many proteins involved in the T. brucei starvation stress response were found to interact with TbPRMT1, prompting analysis of the response of TbPRMT1-depleted cells to nutrient deprivation. Indeed, depletion of TbPRMT1 strongly hinders the ability of T. brucei to form cytoplasmic mRNA granules under starvation conditions. Finally, this work shows that TbPRMT1 itself binds nucleic acids in vitro and in vivo, a feature completely novel to protein arginine methyltransferases.IMPORTANCETrypanosoma brucei infection causes human African trypanosomiasis, also known as sleeping sickness, a disease with a nearly 100% fatality rate when untreated. Current drugs are expensive, toxic, and highly impractical to administer, prompting the community to explore various unique aspects of T. brucei biology in search of better treatments. In this study, we identified the protein arginine methyltransferase (PRMT), TbPRMT1, as a factor that modulates numerous aspects of T. brucei biology. These include glycolysis and life cycle progression signaling, both of which are being intensely researched toward identification of potential drug targets. Our data will aid research in those fields. Furthermore, we demonstrate for the first time a direct association of a PRMT with nucleic acids, a finding we believe could translate to other organisms, including humans, thereby impacting research in fields as distant as human cancer biology and immune response modulation. Copyright © 2018 Kafková et al

Machine learning cosmological structure formation

We train a machine learning algorithm to learn cosmological structure formation from N-body simulations. The algorithm infers the relationship between the initial conditions and the final dark matter haloes, without the need to introduce approximate halo collapse models. We gain insights into the physics driving halo formation by evaluating the predictive performance of the algorithm when provided with different types of information about the local environment around dark matter particles. The algorithm learns to predict whether or not dark matter particles will end up in haloes of a given mass range, based on spherical overdensities. We show that the resulting predictions match those of spherical collapse approximations such as extended Press–Schechter theory. Additional information on the shape of the local gravitational potential is not able to improve halo collapse predictions; the linear density field contains sufficient information for the algorithm to also reproduce ellipsoidal collapse predictions based on the Sheth–Tormen model. We investigate the algorithm’s performance in terms of halo mass and radial position and perform blind analyses on independent initial conditions realizations to demonstrate the generality of our results

Acromegaly, Mr Punch and caricature.

The origin of Mr Punch from the Italian Pulcinella of the Commedia dell'arte is well known but his feature, large hooked nose, protruding chin, kyphosis and sternal protrusion all in an exaggerated form also suggest the caricature of an acromegalic. This paper looks at the physical characteristics of acromegaly, the origin of Mr Punch and the development of caricature linking them together in the acromegalic caricature that now has a life of its own

Canopy nitrogen, carbon assimilation, and albedo in temperate and boreal forests: Functional relations and potential climate feedbacks

The availability of nitrogen represents a key constraint on carbon cycling in terrestrial ecosystems, and it is largely in this capacity that the role of N in the Earth\u27s climate system has been considered. Despite this, few studies have included continuous variation in plant N status as a driver of broad-scale carbon cycle analyses. This is partly because of uncertainties in how leaf-level physiological relationships scale to whole ecosystems and because methods for regional to continental detection of plant N concentrations have yet to be developed. Here, we show that ecosystem CO2 uptake capacity in temperate and boreal forests scales directly with whole-canopy N concentrations, mirroring a leaf-level trend that has been observed for woody plants worldwide. We further show that both CO2 uptake capacity and canopy N concentration are strongly and positively correlated with shortwave surface albedo. These results suggest that N plays an additional, and overlooked, role in the climate system via its influence on vegetation reflectivity and shortwave surface energy exchange. We also demonstrate that much of the spatial variation in canopy N can be detected by using broad-band satellite sensors, offering a means through which these findings can be applied toward improved application of coupled carbon cycle–climate models

Evaluating a pre-surgical health optimisation programme: a feasibility study

BACKGROUND: Health optimisation programmes are increasingly popular and aim to support patients to lose weight or stop smoking ahead of surgery, yet there is little published evidence about their impact. This study aimed to assess the feasibility of evaluating a programme introduced by a National Health Service (NHS) clinical commissioning group offering support to smokers/obese patients in an extra 3 months prior to the elective hip/knee surgery pathway. METHODS: Feasibility study mapping routinely collected data sources, availability and completeness for 502 patients referred to the hip/knee pathway in February–July 2018. RESULTS: Data collation across seven sources was complex. Data completeness for smoking and ethnicity was poor. While 37% (184) of patients were eligible for health optimisation, only 28% of this comparatively deprived patient group accepted referral to the support offered. Patients who accepted referral to support and completed the programme had a larger median reduction in BMI than those who did not accept referral (− 1.8 BMI points vs. − 0.5). Forty-nine per cent of patients who accepted support were subsequently referred to surgery, compared to 61% who did not accept referral to support. CONCLUSIONS: Use of routinely collected data to evaluate health optimisation programmes is feasible though demanding. Indications of the positive effects of health optimisation interventions from this study and existing literature suggest that the challenge of programme evaluation should be prioritised; longer-term evaluation of costs and outcomes is warranted to inform health optimisation policy development. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13741-022-00255-2

Novel benzothiazole-based ureas as 17β-HSD10 inhibitors, a potential Alzheimer’s disease treatment

Funding: This work was supported by Alzheimer’s Society (specifically The Barcopel Foundation), Scottish Universities Life Science Alliance (SULSA), The Rosetrees Trust, WT-ISSF and RS MacDonald Charitable Trust, Ministry of Education, Youth and Sports of Czech Republic (project ESF no. CZ.02.1.01/0.0/0.0/18_069/0010054), and University of Hradec Kralove (Faculty of Science, no. VT2019-2021, SV2115-2018, and Postdoctoral job positions at UHK).It has long been established, that mitochondrial dysfunction in Alzheimer’s disease (AD) patients can trigger pathological changes in cell metabolism by altering metabolic enzymes such as the mitochondrial 17β-hydroxysteroid dehydrogenase type 10 (17β-HSD10) also known as amyloid-binding alcohol dehydrogenase (ABAD). We and others have shown that frentizole and riluzole derivatives can inhibit 17β-HSD10 and that this inhibition is beneficial and holds therapeutic merit for the treatment of AD. Here we evaluate several novel series based on benzothiazolylurea scaffold evaluating key structural and activity relationships required for the inhibition of 17β-HSD10. Results show that the most promising of these compounds have markedly increased potency on our previously published inhibitors, with the most promising exhibiting advantageous features like low cytotoxicity and target engagement in living cells.Publisher PDFPeer reviewe

The state of the Martian climate

60°N was +2.0°C, relative to the 1981–2010 average value (Fig. 5.1). This marks a new high for the record. The average annual surface air temperature (SAT) anomaly for 2016 for land stations north of starting in 1900, and is a significant increase over the previous highest value of +1.2°C, which was observed in 2007, 2011, and 2015. Average global annual temperatures also showed record values in 2015 and 2016. Currently, the Arctic is warming at more than twice the rate of lower latitudes

Durable response with single-agent acalabrutinib in patients with relapsed or refractory mantle cell lymphoma

Bruton tyrosine kinase (BTK) inhibitors have greatly improved the spectrum of treatment options in mantle cell lymphoma (MCL) [1–4]. Acalabrutinib is a highly selective, orally administered, and potent BTK inhibitor with limited off-target activity [5]. Acalabrutinib was approved in 2017 by the US Food and Drug Administration for the treatment of relapsed/refractory MCL based on clinical data from the open-label, multicenter, phase 2 ACE-LY-004 study of acalabrutinib 100 mg twice daily [1]. Here, we present updated results from the ACE-LY-004 study after a median 26-month follow-up. Eligibility criteria and study design were published previously (Supplementary methods) [1]. Analysis of minimal residual disease (MRD) was conducted after complete response (CR) or partial response (PR) was achieved using the quantitative ClonoSEQ next-generation sequencing (5 × 10−6 ) assay (Adpative Biotechnologies, Seattle, WA, USA) in consenting patients with available paired archival tumor and whole blood samples. Data are updated as of February 12, 2018