The interactions of age, genetics, and disease severity on tacrolimus dosing requirements after pediatric kidney and liver transplantation

Purpose: In children, data on the combined impact of age, genotype, and disease severity on tacrolimus (TAC) disposition are scarce. The aim of this study was to evaluate the effect of these covariates on tacrolimus dose requirements in the immediate post-transplant period in pediatric kidney and liver recipients. Methods: Data were retrospectively collected describing tacrolimus disposition, age, CYP3A5 and ABCB1 genotype, and pediatric risk of mortality (PRISM) scores for up to 14 days post-transplant in children receiving liver and renal transplants. Initial TAC dosing was equal in all patients and adjusted using therapeutic drug monitoring. We determined the relationship between covariates and tacrolimus disposition. Results: Forty-eight kidney and 42 liver transplant recipients (median ages 11.5 and 1.5 years, ranges 1.5-17.7 and 0.05-14.8 years, respectively) received TAC post-transplant. In both transplant groups, younger children (<5 years) needed higher TAC doses than older children [kidney: 0.15 (0.07-0.35) vs. 0.09 (0.02-0.20) mg/kg/12h, p = 0.046, liver: 0.12 (0.04-0.32) vs. 0.09 (0.01-0.18) mg/kg/12h, p

Galactic Core-Collapse Supernovae at IceCube: “Fire Drill” Data Challenges and follow-up

The next Galactic core-collapse supernova (CCSN) presents a once-in-a-lifetime opportunity to make astrophysical measurements using neutrinos, gravitational waves, and electromagnetic radiation. CCSNe local to the Milky Way are extremely rare, so it is paramount that detectors are prepared to observe the signal when it arrives. The IceCube Neutrino Observatory, a gigaton water Cherenkov detector below the South Pole, is sensitive to the burst of neutrinos released by a Galactic CCSN at a level >10σ. This burst of neutrinos precedes optical emission by hours to days, enabling neutrinos to serve as an early warning for follow-up observation. IceCube\u27s detection capabilities make it a cornerstone of the global network of neutrino detectors monitoring for Galactic CCSNe, the SuperNova Early Warning System (SNEWS 2.0). In this contribution, we describe IceCube\u27s sensitivity to Galactic CCSNe and strategies for operational readiness, including "fire drill" data challenges. We also discuss coordination with SNEWS 2.0

All-Energy Search for Solar Atmospheric Neutrinos with IceCube

The interaction of cosmic rays with the solar atmosphere generates a secondary flux of mesons that decay into photons and neutrinos – the so-called solar atmospheric flux. Although the gamma-ray component of this flux has been observed in Fermi-LAT and HAWC Observatory data, the neutrino component remains undetected. The energy distribution of those neutrinos follows a soft spectrum that extends from the GeV to the multi-TeV range, making large Cherenkov neutrino telescopes a suitable for probing this flux. In this contribution, we will discuss current progress of a search for the solar neutrino flux by the IceCube Neutrino Observatory using all available data since 2011. Compared to the previous analysis which considered only high-energy muon neutrino tracks, we will additionally consider events produced by all flavors of neutrinos down to GeV-scale energies. These new events should improve our analysis sensitivity since the flux falls quickly with energy. Determining the magnitude of the neutrino flux is essential, since it is an irreducible background to indirect solar dark matter searches

Searching for IceCube sub-TeV neutrino counterparts to sub-threshold Gravitational Wave events

Since the release of the Gravitational Wave Transient Catalogue GWTC-2.1 by the LIGO-Virgo collaboration, sub-threshold gravitational wave (GW) candidates are publicly available. They are expected to be released in real-time as well, in the upcoming O4 run. Using these GW candidates for multi-messenger studies complement the ongoing efforts to identify neutrino counterparts to GW events. This in turn, allows us to schedule electromagnetic follow-up searches more efficiently. However, the definition and criteria for sub-threshold candidates are pretty flexible. Finding a multi-messenger counterpart via archival studies for these candidates will help to set up strong bounds on the GW parameters which are useful for defining a GW signal as sub-threshold, thereby increasing their significance for scheduling follow-up searches. Here, we present the current status of this ongoing work with the IceCube Neutrino Observatory. We perform a selection of the sub-threshold GW candidates from GWTC-2.1 and conduct an archival search for sub-TeV neutrino counterparts detected by the dense infill array of the IceCube Neutrino Observatory, known as "DeepCore". For this, an Unbinned Maximum Likelihood (UML) method is used. We report the 90% C.L. sensitivities of this sub-TeV neutrino dataset for each selected sub-threshold GW candidate, considering the spatial and temporal correlation between the GW and neutrino events within a 1000 s time window

Search for Cosmic-Ray Events Using Radio Signals and CNNs in Data from the IceTop Enhancement Prototype Station

Cosmic-ray air showers emit radio waves that can be used to measure the properties of cosmic-ray primary particles. The radio detection technique presents several advantages, such as low cost and year-round duty cycle as well as the ability to provide high sensitivity to Xmax and energy estimation with minimal theoretical uncertainties, making it a promising tool for studying cosmic rays at the highest energies. However, the primary limitation of radio detection is the irreducible background from various sources that obscure the impulsive signals generated by air showers. To address this issue, we investigated the use of Convolutional Neural Networks (CNNs), trained on CoREAS simulations and radio backgrounds measured by a prototype station at the South Pole. We developed two different CNNs: a Classifier that distinguishes between cosmic ray event radio signals and pure background waveforms, and a Denoiser that mitigates background noise to recover the underlying cosmic-ray signal. After training the networks we apply them to the air-shower data to search for radio events. With two months data, we were able to identify 51 candidate events. The event’s arrival direction reconstructed using CNN denoised radio waveforms is found to bein good agreement with the IceTop reconstruction. Finally, our approach demonstrated improved directional reconstruction compared to traditional methods