An efficient auxin-inducible degron system with low basal degradation in human cells

Auxin-inducible degron technology allows rapid and controlled protein depletion. However, basal degradation without auxin and inefficient auxin-inducible depletion have limited its utility. We have identified a potent auxin-inducible degron system composed of auxin receptor F-box protein AtAFB2 and short degron minilAA7. The system showed minimal basal degradation and enabled rapid auxin-inducible depletion of endogenous human transmembrane, cytoplasmic and nuclear proteins in 1 h with robust functional phenotypes.Peer reviewe

Ireland’s unseen majority – microbial diversity of the seabed

Despite their size, prokaryote (bacteria and archaea) biomass is estimated to represent between 15 and 30% of total living biomass1,2. Prokaryotes play major roles in marine ecosystems and in global biogeochemical cycling3,4. Molecular phylogenetic approaches have revolutionised microbiology and have revealed that the complexity of microbial life is orders of magnitude greater than previous estimates based on cultivation-based approaches5. This highlights how little we currently know about the microbial world and the clear potential of this vast untapped resource for human application. Here we present the first in-depth analysis of microbial community diversity and composition in the Irish Sea. The western Irish Sea is characterised by distinct hydrographic conditions, resulting in summer stratified offshore deeper waters and settling of fine mud, while well-mixed waters and coarser sediment type dominate in the south and coastal regions. We wished to assess whether these factors play a role in prokaryote abundance and diversity

An efficient auxin-inducible degron system with low basal degradation in human cells

Auxin-inducible degron technology allows rapid and controlled protein depletion. However, basal degradation without auxin and inefficient auxin-inducible depletion have limited its utility. We have identified a potent auxin-inducible degron system composed of auxin receptor F-box protein AtAFB2 and short degron minilAA7. The system showed minimal basal degradation and enabled rapid auxin-inducible depletion of endogenous human transmembrane, cytoplasmic and nuclear proteins in 1 h with robust functional phenotypes.Peer reviewe

Open Versus Robotic Cystectomy: A Propensity Score Matched Analysis Comparing Survival Outcomes

Background: To assess the differential effect of robotic assisted radical cystectomy (RARC) versus open radical cystectomy (ORC) on survival outcomes in matched analyses performed on a large multicentric cohort. Methods: The study included 9757 patients with urothelial bladder cancer (BCa) treated in a consecutive manner at each of 25 institutions. All patients underwent radical cystectomy with bilateral pelvic lymphadenectomy. To adjust for potential selection bias, propensity score matching 2:1 was performed with two ORC patients matched to one RARC patient. The propensity-matched cohort included 1374 patients. Multivariable competing risk analyses accounting for death of other causes, tested association of surgical technique with recurrence and cancer specific mortality (CSM), before and after propensity score matching. Results: Overall, 767 (7.8%) patients underwent RARC and 8990 (92.2%) ORC. The median follow-up before and after propensity matching was 81 and 102 months, respectively. In the overall population, the 3-year recurrence rates and CSM were 37% vs. 26% and 34% vs. 24% for ORC vs. RARC (all p values > 0.1), respectively. On multivariable Cox regression analyses, RARC and ORC had similar recurrence and CSM rates before and after matching (all p values > 0.1). Conclusions: Patients treated with RARC and ORC have similar survival outcomes. This data is helpful in consulting patients until long term survival outcomes of level one evidence is available

Genetic trends in the Zimbabwe’s national maize breeding program over two decades

Monitoring genetic gains within breeding programs is a critical component for continuous improvement. While several national breeding programs in Africa have assessed genetic gain using era studies, this study is the first to use two decades of historical data to estimate genetic trends within a national breeding program. The objective of this study was to assess genetic trends within the final two stages of Zimbabwe’s Department of Research & Specialist Services maize breeding pipeline between 2002 and 2021. Data from 107 intermediate and 162 advanced variety trials, comprising of 716 and 398 entries, respectively, was analyzed. Trials were conducted under optimal, managed drought stress, low nitrogen stress, low pH, random stress, and disease pressure (maize streak virus (MSV), grey leaf spot (GLS), and turcicum leaf blight under artificial inoculation. There were positive and significant genetic gains for grain yield across management conditions (28–35 kg ha-1 yr-1), under high-yield potential environments (17–61 kg ha-1 yr-1), and under low-yield potential environments (0–16 kg ha-1 yr-1). No significant changes were observed in plant and ear height over the study period. Stalk and root lodging, as well as susceptibility to MSV and GLS, significantly decreased over the study period. New breeding technologies need to be incorporated into the program to further increase the rate of genetic gain in the maize breeding programs and to effectively meet future needs

Federated learning enables big data for rare cancer boundary detection.

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing

Author Correction: Federated learning enables big data for rare cancer boundary detection.

10.1038/s41467-023-36188-7NATURE COMMUNICATIONS14

Network Linkages to Predict Bank Distress

Building on the literature on systemic risk and financial contagion, the paper introduces estimated network linkages into an early-warning model to predict bank distress among European banks. We use multivariate extreme value theory to estimate equity-based tail-dependence networks, whose links proxy for the markets' view of bank interconnectedness in case of elevated financial stress. The paper finds that early warning models including estimated tail dependencies consistently outperform bank-specific benchmark models with- out networks. The results are robust to variation in model specification and also hold in relation to simpler benchmarks of contagion. Generally, this paper gives direct support for measures of interconnectedness in early-warning models, and moves toward a unified representation of cyclical and cross-sectional dimensions of systemic risk

Measurement of t(t)over-bar normalised multi-differential cross sections in pp collisions at root s=13 TeV, and simultaneous determination of the strong coupling strength, top quark pole mass, and parton distribution functions

Peer reviewe

MUSiC : a model-unspecific search for new physics in proton-proton collisions at root s=13TeV

Results of the Model Unspecific Search in CMS (MUSiC), using proton-proton collision data recorded at the LHC at a centre-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 35.9 fb(-1), are presented. The MUSiC analysis searches for anomalies that could be signatures of physics beyond the standard model. The analysis is based on the comparison of observed data with the standard model prediction, as determined from simulation, in several hundred final states and multiple kinematic distributions. Events containing at least one electron or muon are classified based on their final state topology, and an automated search algorithm surveys the observed data for deviations from the prediction. The sensitivity of the search is validated using multiple methods. No significant deviations from the predictions have been observed. For a wide range of final state topologies, agreement is found between the data and the standard model simulation. This analysis complements dedicated search analyses by significantly expanding the range of final states covered using a model independent approach with the largest data set to date to probe phase space regions beyond the reach of previous general searches.Peer reviewe