CenTime: Event-conditional modelling of censoring in survival analysis

Survival analysis is a valuable tool for estimating the time until specific events, such as death or cancer recurrence, based on baseline observations. This is particularly useful in healthcare to prognostically predict clinically important events based on patient data. However, existing approaches often have limitations; some focus only on ranking patients by survivability, neglecting to estimate the actual event time, while others treat the problem as a classification task, ignoring the inherent time-ordered structure of the events. Additionally, the effective utilisation of censored samples−data points where the event time is unknown− is essential for enhancing the model's predictive accuracy. In this paper, we introduce CenTime, a novel approach to survival analysis that directly estimates the time to event. Our method features an innovative event-conditional censoring mechanism that performs robustly even when uncensored data is scarce. We demonstrate that our approach forms a consistent estimator for the event model parameters, even in the absence of uncensored data. Furthermore, CenTime is easily integrated with deep learning models with no restrictions on batch size or the number of uncensored samples. We compare our approach to standard survival analysis methods, including the Cox proportional-hazard model and DeepHit. Our results indicate that CenTime offers state-of-the-art performance in predicting time-to-death while maintaining comparable ranking performance. Our implementation is publicly available at https://github.com/ahmedhshahin/CenTime

Cap-independent Nrf2 translation is part of a lipoic acid-stimulated detoxification stress response

AbstractLittle is known about either the basal or stimulated homeostatic mechanisms regulating nuclear tenure of Nf-e2-related factor 2 (Nrf2), a transcription factor that mediates expression of over 200 detoxification genes. Our data show that stress-induced nuclear Nrf2 accumulation is largely from de novo protein synthesis, rather than translocation from a pre-existing cytoplasmic pool. HepG2 cells were used to monitor nuclear Nrf2 24h following treatment with the dithiol micronutrient (R)-α-lipoic acid (LA; 50μM), or vehicle. LA caused a ≥2.5-fold increase in nuclear Nrf2 within 1h. However, pretreating cells with cycloheximide (50μg/ml) inhibited LA-induced Nrf2 nuclear accumulation by 94%. Providing cells with the mTOR inhibitor, rapamycin, decreased basal Nrf2 levels by 84% after 4h, but LA overcame this inhibition. LA-mediated de novo protein translation was confirmed using HepG2 cells transfected with a bicistronic construct containing an internal ribosome entry sequence (IRES) for Nrf2, with significant (P<0.05) increase in IRES use under LA treatment. These results suggest that a dithiol stimulus mediates Nrf2 nuclear tenure via cap-independent protein translation. Thus, translational control of Nrf2 synthesis, rather than reliance solely on pre-existing protein, may mediate the rapid burst of Nrf2 nuclear accumulation following stress stimuli

Optimization of glutathione production in batch and fed-batch cultures by the wild-type and recombinant strains of the methylotrophic yeast Hansenula polymorpha DL-1

<p>Abstract</p> <p>Background</p> <p>Tripeptide glutathione (gamma-glutamyl-L-cysteinyl-glycine) is the most abundant non-protein thiol that protects cells from metabolic and oxidative stresses and is widely used as medicine, food additives and in cosmetic industry. The methylotrophic yeast <it>Hansenula polymorpha </it>is regarded as a rich source of glutathione due to the role of this thiol in detoxifications of key intermediates of methanol metabolism. Cellular and extracellular glutathione production of <it>H. polymorpha </it>DL-1 in the wild type and recombinant strains which overexpress genes of glutathione biosynthesis (<it>GSH2</it>) and its precursor cysteine (<it>MET4</it>) was studied.</p> <p>Results</p> <p>Glutathione producing capacity of <it>H. polymorpha </it>DL-1 depending on parameters of cultivation (dissolved oxygen tension, pH, stirrer speed), carbon substrate (glucose, methanol) and type of overexpressed genes of glutathione and its precursor biosynthesis during batch and fed-batch fermentations were studied. Under optimized conditions of glucose fed-batch cultivation, the glutathione productivity of the engineered strains was increased from ~900 up to ~ 2300 mg of Total Intracellular Glutathione (TIG) or GSH+GSSG_in, per liter of culture medium. Meantime, methanol fed-batch cultivation of one of the recombinant strains allowed achieving the extracellular glutathione productivity up to 250 mg of Total Extracellular Glutathione (TEG) or GSH+GSSG_ex, per liter of the culture medium.</p> <p>Conclusions</p> <p><it>H. polymorpha </it>is an competitive glutathione producer as compared to other known yeast and bacteria strains (<it>Saccharomyces cerevisiae, Candida utilis, Escherichia coli, Lactococcus lactis </it>etc.) with good perspectives for further improvement especially for production of extracellular form of glutathione.</p

Innovating with confidence: embedding AI governance and fairness in a financial services risk management framework

An increasing number of financial services (FS) companies are adopting solutions driven by artificial intelligence (AI) to gain operational efficiencies, derive strategic insights, and improve customer engagement. However, the rate of adoption has been low, in part due to the apprehension around its complexity and self-learning capability, which makes auditability a challenge in a highly regulated industry. There is limited literature on how FS companies can implement the governance and controls specific to AI-driven solutions. AI auditing cannot be performed in a vacuum; the risks are not confined to the algorithm itself, but rather permeates the entire organization. Using the risk of unfairness as an example, this paper will introduce the overarching governance strategy and control framework to address the practical challenges in mitigating risks AI introduces. With regulatory implications and industry use cases, this framework will enable leaders to innovate with confidence

A Graph-Based Semantics Workbench for Concurrent Asynchronous Programs

A number of novel programming languages and libraries have been proposed that offer simpler-to-use models of concurrency than threads. It is challenging, however, to devise execution models that successfully realise their abstractions without forfeiting performance or introducing unintended behaviours. This is exemplified by SCOOP---a concurrent object-oriented message-passing language---which has seen multiple semantics proposed and implemented over its evolution. We propose a "semantics workbench" with fully and semi-automatic tools for SCOOP, that can be used to analyse and compare programs with respect to different execution models. We demonstrate its use in checking the consistency of semantics by applying it to a set of representative programs, and highlighting a deadlock-related discrepancy between the principal execution models of the language. Our workbench is based on a modular and parameterisable graph transformation semantics implemented in the GROOVE tool. We discuss how graph transformations are leveraged to atomically model intricate language abstractions, and how the visual yet algebraic nature of the model can be used to ascertain soundness.Comment: Accepted for publication in the proceedings of FASE 2016 (to appear

Denitrification bioreactor trial in the Russell River catchment of the Wet Tropics: final report

Dissolved inorganic nitrogen (DIN) in runoff from agricultural land is considered to have a significant detrimental impact on the Great Barrier Reef (GBR). Losses of DIN to runoff can be reduced by good agricultural practices, but they cannot be eliminated entirely in the Wet Tropics due to the need for adequate nitrogen supply to crops, the high solubility of DIN, particularly nitrate, and high rainfall. Thus, it is inevitable that DIN concentrations are higher in runoff from agricultural land than from forested areas. Some of this DIN is removed from the water as it moves through aquifers, creeks, rivers, and wetlands on its way to the sea, through the process of microbial denitrification. Denitrification involves the conversion of nitrate and nitrite (NOx-N) to dinitrogen (N2) gas, which is lost to the atmosphere. Denitrification requires NOx-N, organic matter, and low oxygen concentration. Wetlands provide these conditions, so DIN concentrations decline in water moving through them. Similarly, denitrifying bioreactors are designed to treat water by passing it through a porous organic material, typically woodchips. The woodchips provide organic matter for the microorganisms, which in turn lower the oxygen concentration, providing ideal conditions for denitrification. Denitrifying bioreactors are now widely used to remove the NOx-N component of DIN from agricultural runoff water elsewhere, but they have not yet been evaluated in the Wet Tropics. The Wet Tropics pose a challenge for efficacy due to the large volumes of water moving through the landscape. The objective of this project was “to establish the effectiveness of denitrifying bioreactors as a remediation technology for excess DIN in agricultural runoff within the Babinda Swamp Drainage Area (BSDA) of the Russell catchment”. The Russell River exports a disproportionate amount of DIN to the GBR lagoon because of the high rainfall and high proportion of agriculture, mostly sugarcane, in its catchment

Theoretical Aspects of Particle Production

These lectures describe some of the latest data on particle production in high-energy collisions and compare them with theoretical calculations and models based on QCD. The main topics covered are: fragmentation functions and factorization, small-x fragmentation, hadronization models, differences between quark and gluon fragmentation, current and target fragmentation in deep inelastic scattering, and heavy quark fragmentation.Comment: 26 pages, 27 figures. Lectures at International Summer School on Particle Production Spanning MeV and TeV Energies, Nijmegen, The Netherlands, August 199

Coarse-grained simulations suggest potential competing roles of phosphoinositides and amphipathic helix structures in membrane curvature sensing of the AP180 N-terminal homology domain

The generation and sensing of membrane curvature by proteins has become of increasing interest to researchers with multiple mechanisms, from hydrophobic insertion to protein crowding, being identified. However, the role of charged lipids in the membrane curvature-sensing process is still far from understood. Many proteins involved in endocytosis bind phosphatidylinositol 4,5-bisphosphate (PIP2) lipids, allowing these proteins to accumulate at regions of local curvature. Here, using coarse-grained molecular dynamics simulations, we study the curvature-sensing behavior of the ANTH domain, a protein crucial for endocytosis. We selected three ANTH crystal structures containing either an intact, split, or truncated terminal amphipathic helix. On neutral membranes, the ANTH domain has innate curvature-sensing ability. In the presence of PIP2, however, only the domain with an intact helix senses curvature. Our work sheds light on the role of PIP2 and its modulation of membrane curvature sensing by proteins

The unwarped, resolved, deformed conifold: fivebranes and the baryonic branch of the Klebanov-Strassler theory

We study a gravity solution corresponding to fivebranes wrapped on the $S^2$ of the resolved conifold. By changing a parameter the solution continuously interpolates between the deformed conifold with flux and the resolved conifold with branes. Therefore, it displays a geometric transition, purely in the supergravity context. The solution is a simple example of torsional geometry and may be thought of as a non-K\"ahler analog of the conifold. By U-duality transformations we can add D3 brane charge and recover the solution in the form originally derived by Butti et al. This describes the baryonic branch of the Klebanov-Strassler theory. Far along the baryonic branch the field theory gives rise to a fuzzy two-sphere. This corresponds to the D5 branes wrapping the two-sphere of the resolved conifold in the gravity solution.Comment: 41 pages, 7 figure