Can inhaled foreign body mimic asthma in an adolescent?

A 14 year old male was diagnosed with asthma but didn't improve with appropriate inhalation therapy. Rigid bronchoscopy revealed a food fragment, almost completely occluding the lower-left bronchus lumen. Based on the reported history, it had been likely there for several years

Implicit Neural Representation as a Differentiable Surrogate for Photon Propagation in a Monolithic Neutrino Detector

Optical photons are used as signal in a wide variety of particle detectors. Modern neutrino experiments employ hundreds to tens of thousands of photon detectors to observe signal from millions to billions of scintillation photons produced from energy deposition of charged particles. These neutrino detectors are typically large, containing kilotons of target volume, with different optical properties. Modeling individual photon propagation in form of look-up table requires huge computational resources. As the size of a table increases with detector volume for a fixed resolution, this method scales poorly for future larger detectors. Alternative approaches such as fitting a polynomial to the model could address the memory issue, but results in poorer performance. Both look-up table and fitting approaches are prone to discrepancies between the detector simulation and the data collected. We propose a new approach using SIREN, an implicit neural representation with periodic activation functions, to model the look-up table as a 3D scene and reproduces the acceptance map with high accuracy. The number of parameters in our SIREN model is orders of magnitude smaller than the number of voxels in the look-up table. As it models an underlying functional shape, SIREN is scalable to a larger detector. Furthermore, SIREN can successfully learn the spatial gradients of the photon library, providing additional information for downstream applications. Finally, as SIREN is a neural network representation, it is differentiable with respect to its parameters, and therefore tunable via gradient descent. We demonstrate the potential of optimizing SIREN directly on real data, which mitigates the concern of data vs. simulation discrepancies. We further present an application for data reconstruction where SIREN is used to form a likelihood function for photon statistics

An enrichment protocol and analysis pipeline for long read sequencing of the hepatitis B virus transcriptome

Hepatitis B virus (HBV) is one of the smallest human DNA viruses and its 3.2 Kb genome encodes multiple overlapping open reading frames, making its viral transcriptome challenging to dissect. Previous studies have combined quantitative PCR and Next Generation Sequencing to identify viral transcripts and splice junctions, however the fragmentation and selective amplification used in short read sequencing precludes the resolution of full length RNAs. Our study coupled an oligonucleotide enrichment protocol with state-of-the-art long read sequencing (PacBio) to identify the repertoire of HBV RNAs. This methodology provides sequencing libraries where up to 25 % of reads are of viral origin and enable the identification of canonical (unspliced), non-canonical (spliced) and chimeric viral-human transcripts. Sequencing RNA isolated from de novo HBV infected cells or those transfected with 1.3 × overlength HBV genomes allowed us to assess the viral transcriptome and to annotate 5' truncations and polyadenylation profiles. The two HBV model systems showed an excellent agreement in the pattern of major viral RNAs, however differences were noted in the abundance of spliced transcripts. Viral-host chimeric transcripts were identified and more commonly found in the transfected cells. Enrichment capture and PacBio sequencing allows the assignment of canonical and non-canonical HBV RNAs using an open-source analysis pipeline that enables the accurate mapping of the HBV transcriptome

Investigating the Paleoecological Consequences of Supercontinent Breakup: Sponges Clean Up in the Early Jurassic

The continued release of fossil fuel carbon into the atmosphere today means it is imperative to understand Earth system response to CO2 rise, and the geologic record offers unique opportunities to investigate such behavior. Stomatal and paleosol proxies demonstrate a large change in atmospheric pCO2 across the Triassic-Jurassic (T-J) transition, concomitant with the eruption and emplacement of the Central Atlantic Magmatic Province (CAMP) and the splitting of Pangea. As one of the “big 5” mass extinctions—when the so-called modern fauna was particularly hard hit—we know the biosphere was severely affected during this time, but the details are relatively poorly understood, particularly with respect to an Earth system perspective. As part of the NSF Earth Life Transitions initiative, our team has targeted the T-J for integrative investigation to explore, among other things, alternative ecological states that may exist in the aftermath of mass extinctions. The initial findings reveal a global “sponge takeover” in the Early Jurassic following the extinction that lasted nearly 2 million years. The sponge takeover may be linked to an unusual confluence of factors, including potential ocean acidification and intense silicate weathering following the emplacement of CAMP