Benchmarking Deep Learning Architectures for Predicting Readmission to the ICU and Describing Patients-at-Risk

Objective: To compare different deep learning architectures for predicting the risk of readmission within 30 days of discharge from the intensive care unit (ICU). The interpretability of attention-based models is leveraged to describe patients-at-risk. Methods: Several deep learning architectures making use of attention mechanisms, recurrent layers, neural ordinary differential equations (ODEs), and medical concept embeddings with time-aware attention were trained using publicly available electronic medical record data (MIMIC-III) associated with 45,298 ICU stays for 33,150 patients. Bayesian inference was used to compute the posterior over weights of an attention-based model. Odds ratios associated with an increased risk of readmission were computed for static variables. Diagnoses, procedures, medications, and vital signs were ranked according to the associated risk of readmission. Results: A recurrent neural network, with time dynamics of code embeddings computed by neural ODEs, achieved the highest average precision of 0.331 (AUROC: 0.739, F1-Score: 0.372). Predictive accuracy was comparable across neural network architectures. Groups of patients at risk included those suffering from infectious complications, with chronic or progressive conditions, and for whom standard medical care was not suitable. Conclusions: Attention-based networks may be preferable to recurrent networks if an interpretable model is required, at only marginal cost in predictive accuracy

Optical absorption of ion-beam sputtered amorphous silicon coatings

Low mechanical loss at low temperatures and a high index of refraction should make silicon optimally suited for thermal noise reduction in highly reflective mirror coatings for gravitational wave detectors. However, due to high optical absorption, amorphous silicon (aSi) is unsuitable for being used as a direct high-index coating material to replace tantala. A possible solution is a multimaterial design, which enables exploitation of the excellent mechanical properties of aSi in the lower coating layers. The possible number of aSi layers increases with absorption reduction. In this work, the optimum heat treatment temperature of aSi deposited via ion-beam sputtering was investigated and found to be 450 °C. For this temperature, the absorption after deposition of a single layer of aSi at 1064 nm and 1550 nm was reduced by more than 80%

Quantitative profiling of the human substantia nigra proteome from laser-capture microdissected FFPE tissue

Laser-capture microdissection (LCM) allows the visualization and isolation of morphologically distinct subpopulations of cells from heterogeneous tissue specimens. In combination with formalin-fixed and paraffin-embedded (FFPE) tissue it provides a powerful tool for retrospective and clinically relevant studies of tissue proteins in a healthy and diseased context. We first optimized the protocol for efficient LCM analysis of FFPE tissue specimens. The use of SDS containing extraction buffer in combination with the single-pot solid-phase-enhanced sample preparation (SP3) digest method gave the best results regarding protein yield and protein/peptide identifications. Microdissected FFPE human substantia nigra tissue samples (~3,000 cells) were then analyzed, using tandem mass tag (TMT) labeling and LC-MS/MS, resulting in the quantification of &gt;5,600 protein groups. Nigral proteins were classified and analyzed by abundance, showing an enrichment of extracellular exosome and neuron-specific gene ontology (GO) terms among the higher abundance proteins. Comparison of microdissected samples with intact tissue sections, using a label-free shotgun approach, revealed an enrichment of neuronal cell type markers, such as tyrosine hydroxylase and alpha-synuclein, as well as proteins annotated with neuron-specific GO terms. Overall, this study provides a detailed protocol for laser-capture proteomics using FFPE tissue and demonstrates the efficiency of LCM analysis of distinct cell subpopulations for proteomic analysis using low sample amounts.</p

Anomalous optical surface absorption in nominally pure silicon samples at 1550 nm

The announcement of the direct detection of Gravitational Waves (GW) by the LIGO and Virgo collaboration in February 2016 has removed any uncertainty around the possibility of GW astronomy. It has demonstrated that future detectors with sensitivities ten times greater than the Advanced LIGO detectors would see thousands of events per year. Many proposals for such future interferometric GW detectors assume the use of silicon test masses. Silicon has low mechanical loss at low temperatures, which leads to low displacement noise for a suspended interferometer mirror. In addition to the low mechanical loss, it is a requirement that the test masses have a low optical loss. Measurements at 1550 nm have indicated that material with a low enough bulk absorption is available; however there have been suggestions that this low absorption material has a surface absorption of &gt; 100 ppm which could preclude its use in future cryogenic detectors. We show in this paper that this surface loss is not intrinsic but is likely to be a result of particular polishing techniques and can be removed or avoided by the correct polishing procedure. This is an important step towards high gravitational wave detection rates in silicon based instruments

Effect of stress and temperature on the optical properties of silicon nitride membranes at 1550 nm

Future gravitational-wave detectors operated at cryogenic temperatures are expected to be limited by thermal noise of the highly reflective mirror coatings. Silicon nitride is an interesting material for such coatings as it shows very low mechanical loss, a property related to low thermal noise, which is known to further decrease under stress. Low optical absorption is also required to maintain the low mirror temperature. Here, we investigate the effect of stress on the optical properties at 1,550 nm of silicon nitride membranes attached to a silicon frame. Our approach includes the measurement of the thermal expansion coefficient and the thermal conductivity of the membranes. The membrane and frame temperatures are varied, and translated into a change in stress using finite element modeling. The resulting product of the optical absorption and thermo-optic coefficient (dn/dT) is measured using photothermal common-path interferometry

Mapping the optical absorption of a substrate-transferred crystalline AlGaAs coating at 1.5 µm

The sensitivity of 2nd and 3rd generations of interferometric gravitational wave detectors will be limited by thermal noise of the test-mass mirrors and highly reflective coatings. Recently developed crystalline coatings show a promising thermal noise reduction compared to presently used amorphous coatings. However, stringent requirements apply to the optical properties of the coatings as well. We have mapped the optical absorption of a crystalline AlGaAs coating which is optimized for high reflectivity for a wavelength of 1064nm. The absorption was measured at 1550nm where the coating stack transmits approximately 70% of the laser light. The measured absorption was lower than (30.2 +/- 11.1)ppm which is equivalent to (3.6 +/- 1.3)ppm for a coating stack that is highly reflective at 1530nm. While this is a very promising low absorption result for alternative low--loss coating materials, further work will be necessary to reach the requirements of &lt;1ppm for future gravitational wave detectors. Jessica Steinlechner, Iain W Martin, Angus Bell, Garrett Cole, Jim Hough, Steven Penn, Sheila Rowan, Sebastian Steinlechne

Exploring the baseline knowledge and experience of healthcare professionals in the United Kingdom on Novel Psychoactive Substances

Submitted 28 january 2020. Reviwers' comments received 11 February 2020. Accepted 26 February 2020. Published 2 March 2020.Objective: This survey aimed to explore knowledge and experience on novel psychoactive substances (NPS) of healthcare professionals (HCPs). The study also aimed to assess how HCPs would like to improve their knowledge of NPS. Methods: Seventy paper questionnaires were disseminated in 2017 within continuing education events to pharmacists, nurses and general practitioners (GPs). Additionally, 127 online surveys were completed using the Qualtrics platform by other HCPs and mental health nurses in six United Kingdom (UK) independent mental health hospitals long-stay in-patient rehabilitation services. Two educational sessions involving pharmacists and GPs were also held in late 2017 and mid-2018. Knowledge of NPS by HCPs was evaluated prior to the start of the educational events. Evaluation forms were handed out post-sessions to garner feedback, especially on areas for improvement for future sessions. Statistical analysis of data was undertaken using SPSS (V.25). Results: Most HCPs reported only 'basic' to 'intermediate' NPS knowledge. Substance misuse service staff felt more informed, were more often consulted and had greater confidence regarding NPS compared to hospital and primary care professionals. A negative association was found between the age of the HCP and knowledge of NPS. Most participants expressed a need for regular training and updates as insufficient NPS-related information is currently received. Conclusions: An improvement within the self-reported knowledge of HCPs on NPS is evident in comparison to previous studies. Continued education of HCPs on NPS is fundamental for the provision of improved harm reduction services, which can enhance overall care for NPS service users.Peer reviewedFinal Published versio

Detection and location of a partial blockage in a pipeline using damping of fluid transients

The effects of a partial blockage on pipeline transients are investigated analytically. A partial blockage is simulated using an orifice equation, and the influence of the blockage on the unsteady pipe flow is considered in the governing equations using a Dirac delta function. A simplified, linear dimensionless governing equation has been derived, and an analytical solution expressed in terms of a Fourier series has been developed under nonvarying boundary conditions. The linear analysis indicates that pipe friction and a partial blockage both introduce damping on fluid transients. The friction damping and blockage damping are exponential for each of the individual harmonic components. For each individual harmonic component, the blockage-induced damping depends on the blockage magnitude and position and is also independent of measurement location and the transient event. A new blockage detection method using the blockage-induced transient damping is developed based on the analytical solution. The magnitude of the blockage-induced damping rate indicates the size of the blockage, and the ratios of different damping rates can be used to locate the blockage. The proposed blockage detection method has been successfully used in detecting, locating, and quantifying a pipe blockage based on laboratory experiments. [Abstract from author