Designing Robots for Care: Care Centered Value-Sensitive Design

The prospective robots in healthcare intended to be included within the conclave of the nurse-patient relationship—what I refer to as care robots—require rigorous ethical reflection to ensure their design and introduction do not impede the promotion of values and the dignity of patients at such a vulnerable and sensitive time in their lives. The ethical evaluation of care robots requires insight into the values at stake in the healthcare tradition. What’s more, given the stage of their development and lack of standards provided by the International Organization for Standardization to guide their development, ethics ought to be included into the design process of such robots. The manner in which this may be accomplished, as presented here, uses the blueprint of the Value-sensitive design approach as a means for creating a framework tailored to care contexts. Using care values as the foundational values to be integrated into a technology and using the elements in care, from the care ethics perspective, as the normative criteria, the resulting approach may be referred to as care centered value-sensitive design. The framework proposed here allows for the ethical evaluation of care robots both retrospectively and prospectively. By evaluating care robots in this way, we may ultimately ask what kind of care we, as a society, want to provide in the futur

Protein structural variation in computational models and crystallographic data

Normal mode analysis offers an efficient way of modeling the conformational flexibility of protein structures. Simple models defined by contact topology, known as elastic network models, have been used to model a variety of systems, but the validation is typically limited to individual modes for a single protein. We use anisotropic displacement parameters from crystallography to test the quality of prediction of both the magnitude and directionality of conformational variance. Normal modes from four simple elastic network model potentials and from the CHARMM forcefield are calculated for a data set of 83 diverse, ultrahigh resolution crystal structures. While all five potentials provide good predictions of the magnitude of flexibility, the methods that consider all atoms have a clear edge at prediction of directionality, and the CHARMM potential produces the best agreement. The low-frequency modes from different potentials are similar, but those computed from the CHARMM potential show the greatest difference from the elastic network models. This was illustrated by computing the dynamic correlation matrices from different potentials for a PDZ domain structure. Comparison of normal mode results with anisotropic temperature factors opens the possibility of using ultrahigh resolution crystallographic data as a quantitative measure of molecular flexibility. The comprehensive evaluation demonstrates the costs and benefits of using normal mode potentials of varying complexity. Comparison of the dynamic correlation matrices suggests that a combination of topological and chemical potentials may help identify residues in which chemical forces make large contributions to intramolecular coupling.Comment: 17 pages, 4 figure

Optimization and evaluation of a coarse-grained model of protein motion using X-ray crystal data

Simple coarse-grained models, such as the Gaussian Network Model, have been shown to capture some of the features of equilibrium protein dynamics. We extend this model by using atomic contacts to define residue interactions and introducing more than one interaction parameter between residues. We use B-factors from 98 ultra-high resolution X-ray crystal structures to optimize the interaction parameters. The average correlation between GNM fluctuation predictions and the B-factors is 0.64 for the data set, consistent with a previous large-scale study. By separating residue interactions into covalent and noncovalent, we achieve an average correlation of 0.74, and addition of ligands and cofactors further improves the correlation to 0.75. However, further separating the noncovalent interactions into nonpolar, polar, and mixed yields no significant improvement. The addition of simple chemical information results in better prediction quality without increasing the size of the coarse-grained model.Comment: 18 pages, 4 figures, 1 supplemental file (cnm_si.tex

The ethics of inherent trust in care robots for the elderly

The way elderly care is delivered is changing. Attempts are being made to accommodate the increasing number of elderly, and the decline in the number of people available to care for them, with care robots. This change introduces ethical issues into robotics and healthcare. The two-part study (heuristic evaluation and survey) reported here examines a phenomenon which is a result of that change. The phenomenon rises out of a contradiction. All but 2 (who were undecided) of the 12 elderly survey respondents, out of the total of 102 respondents, wanted to be able to change how the presented care robot made decisions and 7 of those 12 elderly wanted to be able to examine its decision making process so as to ensure the care provided is personalized. However, at the same time, 34% of the elderly participants said they were willing to trust the care robot inherently, compared to only 16% of the participants who were under fifty. Additionally, 66% of the elderly respondents said they were very likely or likely to accept and use such a care robot in their everyday lives. The contradiction of inherent trust and simultaneous wariness about control gives rise to the phenomenon: elderly in need want control over their care to ensure it is personalized, but many may desperately take any help they can get. The possible causes, and ethical implications, of this phenomenon are the focus of this paper

oGNM: online computation of structural dynamics using the Gaussian Network Model

An assessment of the equilibrium dynamics of biomolecular systems, and in particular their most cooperative fluctuations accessible under native state conditions, is a first step towards understanding molecular mechanisms relevant to biological function. We present a web-based system, oGNM that enables users to calculate online the shape and dispersion of normal modes of motion for proteins, oligonucleotides and their complexes, or associated biological units, using the Gaussian Network Model (GNM). Computations with the new engine are 5–6 orders of magnitude faster than those using conventional normal mode analyses. Two cases studies illustrate the utility of oGNM. The first shows that the thermal fluctuations predicted for 1250 non-homologous proteins correlate well with X-ray crystallographic data over a broad range [7.3–15 Å] of inter-residue interaction cutoff distances and the correlations improve with increasing observation temperatures. The second study, focused on 64 oligonucleotides and oligonucleotide–protein complexes, shows that good agreement with experiments is achieved by representing each nucleotide by three GNM nodes (as opposed to one-node-per-residue in proteins) along with uniform interaction ranges for all components of the complexes. These results open the way to a rapid assessment of the dynamics of DNA/RNA-containing complexes. The server can be accessed at

Determinants of mRNA recognition and translation regulation by Lin28

Lin28 is critical for stem cell maintenance and is also associated with advanced human malignancies. Our recent genome-wide studies mark Lin28 as a master post-transcriptional regulator of a subset of messenger RNAs important for cell growth and metabolism. However, the molecular basis underpinning the selective mRNA target regulation is unclear. Here, we provide evidence that Lin28 recognizes a unique motif in multiple target mRNAs, characterized by a small but critical ‘A’ bulge flanked by two G:C base pairs embedded in a complex secondary structure. This motif mediates Lin28-dependent stimulation of translation. As Lin28 is also known to inhibit the biogenesis of a cohort of miRNAs including let-7, we propose that Lin28 binding to different RNA types (precursor miRNAs versus mRNAs) may facilitate recruitment of different co-factors, leading to distinct regulatory outcomes. Our findings uncover a putative yet unexpected motif that may constitute a mechanistic base for the multitude of functions regulated by Lin28 in both stem cells and cancer cells