Comparison of standard dose and reduced dose treatment of metastatic prostate cancer with enzalutamide, apalutamide or darolutamide: a rapid review

Objective: To review the efficacy and safety of low dose versus standard dose enzalutamide, apalutamide or darolutamide treatment for metastatic prostate cancer.Methods and Analysis: Keyword searches in MEDLINE and EMBASE up to 1 June 2023, with forward and backward citation searches of potentially relevant studies. Studies were included if primary outcome data were reported for patients with metastatic prostate cancer who had received reduced doses of enzalutamide, apalutamide or darolutamide. Searches were limited to original full-text and English language studies. Key outcomes included overall survival (OS), progression-free survival (PFS), prostate-specific antigen (PSA) response, and treatment-related adverse events. The review was performed in accordance with Cochrane Rapid Reviews Methods Group guidelines.Results: Ten studies were identified that met the eligibility criteria (PROSPERO number: CRD42023440371); five phase I studies, two post-hoc analyses of phase III trials, and three retrospective analyses. No consistent association between OS, PFS, and drug dose was identified. Fewer severe treatment-related adverse events were observed at lower drug doses.Conclusion: This review provides evidence that enzalutamide, apalutamide or darolutamide could be given at a lower than the standard recommended dose without loss of anti-tumour activity. A prospective near-equivalence randomised trial should be undertaken to compare registered and lower doses of these agents. <br/

Understanding and assessing climate risk to green infrastructure: experiences from Greater Manchester (UK)

The existing body of research into the environmental and socio-economic benefits of green infra-structure supports the case for it to be positioned as a form of critical infrastructure, particularly in urban settings. It is broadly recognized that extreme weather and climate change pose signifi-cant risks to critical infrastructure systems linked to the provision of services including electrici-ty, water, communications, and transport, and consequently risk assessments and associated adaptation strategies are common practice. However, although green infrastructure is also at risk from extreme weather and climate change, threatening the realization of benefits that it can de-liver in urban settings, associated risks to green infrastructure are not widely understood or as-sessed in practice. This paper discusses the status of existing research on this topic and uses this as a foundation for a Greater Manchester (UK) case study that assesses the risk of low water avail-ability to grassed areas, which represent a key element of the city-region’s green infrastructure. In doing so, the paper demonstrates how risks linked to extreme weather and climate change can be assessed spatially to inform green infrastructure planning. In summary, this paper aims to raise awareness of extreme weather and climate change risk to urban green infrastructure, present an empirical case study and associated methodological approach on this topic, and ultimately to support efforts to enhance the resilience of urban green infrastructure to extreme weather and cli-mate change

Chimeric Antigen Receptor T-Cell Therapy: A New Emerging Landscape in Autoimmune Rheumatic Diseases

Chimeric antigen receptor T-cell (CAR-T) therapy, an innovative immune cell therapy, has revolutionised the treatment landscape of haematological malignancies. The past two years have witnessed the successful application of CD19-targeting CAR constructs in refractory cases of autoimmune rheumatic diseases, including systemic lupus erythematosus, systemic sclerosis, and anti-synthetase syndrome. In comparison to existing B-cell depletion therapies, targeting CD19 has demonstrated a more rapid and profound therapeutic effect, enabling drug-free remission with manageable adverse events. These promising results necessitate validation through long-term, large-sample, randomized controlled studies. Corroborating the role of CAR-T therapy in refractory rheumatological disorders and affirming safety, efficacy and durability of responses are the aims of future clinical studies. Optimising the engineering strategies and better patient selection are also critical to further refining the successful clinical implementation of CAR-T therapy

Farpls:A Feature-Augmented Robot Trajectory Preference Labeling System to Assist Human Labelers' Preference Elicitation

Preference-based learning aims to align robot task objectives with human values. One of the most common methods to infer human preferences is by pairwise comparisons of robot task trajectories. Traditional comparison-based preference labeling systems seldom support labelers to digest and identify critical differences between complex trajectories recorded in videos. Our formative study (N = 12) suggests that individuals may overlook non-salient task features and establish biased preference criteria during their preference elicitation process because of partial observations. In addition, they may experience mental fatigue when given many pairs to compare, causing their label quality to deteriorate. To mitigate these issues, we propose FARPLS, a Feature-Augmented Robot trajectory Preference Labeling System. FARPLS highlights potential outliers in a wide variety of task features that matter to humans and extracts the corresponding video keyframes for easy review and comparison. It also dynamically adjusts the labeling order according to users' familiarities, difficulties of the trajectory pair, and level of disagreements. At the same time, the system monitors labelers' consistency and provides feedback on labeling progress to keep labelers engaged. A between-subjects study (N = 42, 105 pairs of robot pick-and-place trajectories per person) shows that FARPLS can help users establish preference criteria more easily and notice more relevant details in the presented trajectories than the conventional interface. FARPLS also improves labeling consistency and engagement, mitigating challenges in preference elicitation without raising cognitive loads significantl

Anomalies of solute transport in flow of shear-thinning fluids in heterogeneous porous media

Solute transport and mixing in heterogeneous porous media are important to many processes of practical applications. Most of the previous studies focused on solute transport in flow of Newtonian fluids, whereas there are many processes in which the phenomenon takes place in flow of a non-Newtonian fluid. In this paper, we develop a computational approach to evaluate and upscale dispersion of a solute in flow of a shear-thinning (ST) fluid in a heterogeneous porous medium. Our results indicate that the dispersivity is a non-monotonic function of the Péclet number and the shear rate, and this behavior is accentuated by the heterogeneity of the pore space and spatial correlations between the local permeabilities. As a result, solute transport in ST fluids deviates significantly from the same phenomenon in Newtonian fluids. Moreover, the shear-dependence of the dispersivity strongly influences the fate of solute transport in porous media at large length scales, including larger effluent concentration at the breakthrough point, which also occurs much faster than Newtonian fluids. To provide further evidence for the numerical findings, we compare dispersion in flow of a power-law fluid in a single tube with the same in a bundle of such tubes. Our results emphasize the shortcomings of the current theories of dispersion to account for the role of fluid rheology in solute mixing and spreading

PARTICLE BEAM-DRIVEN WAKEFIELD IN CARBON NANOTUBES:HYDRODYNAMIC MODEL VS PIC SIMULATIONS

The interactions of charged particles with carbon nanotubes (CNTs) may excite electromagnetic modes in the electron gas that makes up the nanotube surface. This novel effect has recently been proposed as an alternative method to achieve ultra-high gradients for particle acceleration. In this contribution, the excitations produced by a localized point-like charge propagating in a single wall nanotube are described by means of the linearized hydrodynamic model. In this model, the electron gas is treated as a plasma with specific solid-state properties. The governing set of differential equations consists of the continuity and momentum equations for the electron fluid, in conjunction with Poisson’s equation. The excited wakefields obtained from the hydrodynamic model are compared with Particle-in-Cell (PIC) simulations. A comprehensive discussion is presented to analyze similarities, differences and limitations of both methods. This research provides a valuable perspective on the potential use of CNTs to enhance particle acceleration techniques, paving the way for further advancements in high-energy physics and related fields.<br/