Values, quality, and evaluation in ethics consultation

Background: The American Society for Bioethics and Humanities has recommended regular evaluation of the quality of health care ethics consultation. This article discusses the impact of ethics consultation on clinicians' perceptions of a patient's plan of care and on the personal values of clinicians who participated in an ethics consultation. Methods: Following institutional review board (IRB) approval, select data points were abstracted from case file report forms for ethics consultations over a 12-month period. Clinicians involved in the care of a patient who was the focus of an ethics consultation were invited to participate in an anonymous online survey. Clinicians who initiated an ethics consultation, were interviewed during the course of an ethics consultation, or were present at a patient care conference attended by an ethics consultant were invited to participate. A purposive sampling approach was used to invite clinicians to participate in an in-person interview. Results: The survey response rate was 44.4% (123 respondents from 277 invited). More than 60% of participants felt the consultation helped clarify the values of the patient and/or patient's family and helped them clarify their own values. Only 32% of participants indicated the patient's plan of care changed as a result of the ethics consultation, yet 75% indicated their confidence in the plan of care increased as a result of the ethics consultation. Preliminary findings from the qualitative interviews support the overall positive assessments reported by survey respondents. Conclusions: Ethics consultation can help clinicians clarify their own values and helps them clarify the values of patients and patients' families. Ethics consultation offers meaningful support when clinicians face ethically challenging cases, provides an opportunity to address moral distress, and is viewed favorably by those who experience the resource

nucleAIzer : A Parameter-free Deep Learning Framework for Nucleus Segmentation Using Image Style Transfer

Single-cell segmentation is typically a crucial task of image-based cellular analysis. We present nucleAIzer, a deep-learning approach aiming toward a truly general method for localizing 2D cell nuclei across a diverse range of assays and light microscopy modalities. We outperform the 739 methods submitted to the 2018 Data Science Bowl on images representing a variety of realistic conditions, some of which were not represented in the training data. The key to our approach is that during training nucleAIzer automatically adapts its nucleus-style model to unseen and unlabeled data using image style transfer to automatically generate augmented training samples. This allows the model to recognize nuclei in new and different experiments efficiently without requiring expert annotations, making deep learning for nucleus segmentation fairly simple and labor free for most biological light microscopy experiments. It can also be used online, integrated into CellProfiler and freely downloaded at www.nucleaizer.org. A record of this paper's transparent peer review process is included in the Supplemental Information.Peer reviewe

Towards standardized metrics for measuring takeover performance in conditionally automated driving: A systematic review

A particular concern with SAE Level 3 automated vehicles is the takeover transition from the automated vehicle to the driver. Prior research has employed a wide range of metrics for measuring takeover performance. However, the lack of a set of standard metrics for measuring takeover performance makes it difficult to consolidate findings and summarize the influence of different factors. This article presents a review of the metrics employed in empirical literature examining takeover transitions in Level 3 automated driving and proposes a framework for standardizing the objective takeover performance metrics.University of Michigan McityNational Science FoundationPeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/168148/1/Cao et al. 2021 (DeepBlue).pdfDescription of Cao et al. 2021 (DeepBlue).pdf : Main FileSEL

Pcdp1 is a central apparatus protein that binds Ca2+-calmodulin and regulates ciliary motility

A complex that localizes to the C1d central pair projection of cilia controls flagellar waveform and beat frequency in response to calcium

Detailed SZ study of 19 LoCuSS galaxy clusters: masses and temperatures out to the virial radius

We present 16-GHz AMI SZ observations of 19 clusters with L_X >7x10^37 W (h50=1) selected from the LoCuS survey (0.142<z<0.295) and of A1758b, in the FoV of A1758a. We detect 17 clusters with 5-23sigma peak surface brightnesses. Cluster parameters are obtained using a Bayesian cluster analysis. We fit isothermal beta-models to our data and assume the clusters are virialized (with all the kinetic energy in gas internal energy). Our gas temperature, T_AMI, is derived from AMI SZ data, not from X-ray spectroscopy. Cluster parameters internal to r500 are derived assuming HSE. We find: (i) Different gNFW parameterizations yield significantly different parameter degeneracies. (ii) For h70 = 1, we find the virial radius r200 to be typically 1.6+/-0.1 Mpc and the total mass M_T(r200) typically to be 2.0-2.5xM_T(r500).(iii) Where we have found M_T X-ray (X) and weak-lensing (WL) values in the literature, there is good agreement between WL and AMI estimates (with M_{T,AMI}/M_{T,WL} =1.2^{+0.2}_{-0.3} and =1.0+/-0.1 for r500 and r200, respectively). In comparison, most Suzaku/Chandra estimates are higher than for AMI (with M_{T,X}/M_{T,AMI}=1.7+/-0.2 within r500), particularly for the stronger mergers.(iv) Comparison of T_AMI to T_X sheds light on high X-ray masses: even at large r, T_X can substantially exceed T_AMI in mergers. The use of these higher T_X values will give higher X-ray masses. We stress that large-r T_SZ and T_X data are scarce and must be increased. (v) Despite the paucity of data, there is an indication of a relation between merger activity and SZ ellipticity. (vi) At small radius (but away from any cooling flow) the SZ signal (and T_AMI) is less sensitive to ICM disturbance than the X-ray signal (and T_X) and, even at high r, mergers affect n^2-weighted X-ray data more than n-weighted SZ, implying significant shocking or clumping or both occur even in the outer parts of mergers.Comment: 45 pages, 33 figures, 13 tables Accepted for publication in MNRA