SwiftLib: rapid degenerate-codon-library optimization through dynamic programming

Degenerate codon (DC) libraries efficiently address the experimental library-size limitations of directed evolution by focusing diversity toward the positions and toward the amino acids (AAs) that are most likely to generate hits; however, manually constructing DC libraries is challenging, error prone and time consuming. This paper provides a dynamic programming solution to the task of finding the best DCs while keeping the size of the library beneath some given limit, improving on the existing integer-linear programming formulation. It then extends the algorithm to consider multiple DCs at each position, a heretofore unsolved problem, while adhering to a constraint on the number of primers needed to synthesize the library. In the two library-design problems examined here, the use of multiple DCs produces libraries that very nearly cover the set of desired AAs while still staying within the experimental size limits. Surprisingly, the algorithm is able to find near-perfect libraries where the ratio of amino-acid sequences to nucleic-acid sequences approaches 1; it effectively side-steps the degeneracy of the genetic code. Our algorithm is freely available through our web server and solves most design problems in about a second

Involving patients, families and medical staff in the evaluation of 3D printing models of congenital heart disease

Objective: To evaluate the usefulness of 3D printing patient-specific models of congenital heart disease (CHD) from the perspective of different stakeholders potentially benefiting from the technology (patients, parents, clinicians and nurses). &#x0D; Methods: Workshops, focus groups and teaching sessions were organized, each targeting a different group of stakeholders. Sessions involved displaying and discussing different 3D models of CHD. Model evaluation involved questionnaires, audio-recorded discussions and written feedback. &#x0D; Results: All stakeholders expressed a liking for the 3D models and for the patient-specific quality of such models. Patients indicated that 3D models can help them imagine “what’s going on inside” and parents agreed that these tools can spark curiosity in the young people. Clinicians indicated that teaching might be the most relevant application of such novel technology and nurses agreed that 3D models improved their learning experience during a course focused on CHD. &#x0D; Conclusion: The successful engagement of different stakeholders to evaluate 3D printing technology for CHD identified different priorities, highlighting the importance of eliciting the views of different groups. &#x0D; Practice Implications: A PPI-based approach in the evaluation and translation of 3D printing technology may increase patient empowerment, improve patient-doctor communication and provide better access to a new teaching and training tool.</jats:p

Piloting the Use of Patient-Specific Cardiac Models as a Novel Tool to Facilitate Communication During Cinical Consultations

This pilot study aimed to assess the impact of using patient-specific three-dimensional (3D) models of congenital heart disease (CHD) during consultations with adolescent patients. Adolescent CHD patients (n = 20, age 15-18 years, 15 male) were asked to complete two questionnaires during a cardiology transition clinic at a specialist centre. The first questionnaire was completed just before routine consultation with the cardiologist, the second just after the consultation. During the consultation, each patient was presented with a 3D full heart model realised from their medical imaging data. The model was used by the cardiologist to point to main features of the CHD. Outcome measures included rating of health status, confidence in explaining their condition to others, name and features of their CHD (as a surrogate for CHD knowledge), impact of CHD on their lifestyle, satisfaction with previous/current visits, positive/negative features of the 3D model, and open-ended feedback. Significant improvements were registered in confidence in explaining their condition to others (p = 0.008), knowledge of CHD (p < 0.001) and patients' satisfaction (p = 0.005). Descriptions of CHD and impact on lifestyle were more eloquent after seeing a 3D model. The majority of participants reported that models helped their understanding and improved their visit, with a non-negligible 30% of participants indicating that the model made them feel more anxious about their condition. Content analysis of open-ended feedback revealed an overall positive attitude of the participants toward 3D models. Clinical translation of 3D models of CHD for communication purposes warrants further exploration in larger studies

A Generic Program for Multistate Protein Design

Some protein design tasks cannot be modeled by the traditional single state design strategy of finding a sequence that is optimal for a single fixed backbone. Such cases require multistate design, where a single sequence is threaded onto multiple backbones (states) and evaluated for its strengths and weaknesses on each backbone. For example, to design a protein that can switch between two specific conformations, it is necessary to to find a sequence that is compatible with both backbone conformations. We present in this paper a generic implementation of multistate design that is suited for a wide range of protein design tasks and demonstrate in silico its capabilities at two design tasks: one of redesigning an obligate homodimer into an obligate heterodimer such that the new monomers would not homodimerize, and one of redesigning a promiscuous interface to bind to only a single partner and to no longer bind the rest of its partners. Both tasks contained negative design in that multistate design was asked to find sequences that would produce high energies for several of the states being modeled. Success at negative design was assessed by computationally redocking the undesired protein-pair interactions; we found that multistate design's accuracy improved as the diversity of conformations for the undesired protein-pair interactions increased. The paper concludes with a discussion of the pitfalls of negative design, which has proven considerably more challenging than positive design

The clinical utility of pain classification in non-specific arm pain

Mechanisms-based pain classification has received considerable attention recently for its potential use in clinical decision making. A number of algorithms for pain classification have been proposed. Non-specific arm pain (NSAP) is a poorly defined condition, which could benefit from classification according to pain mechanisms to improve treatment selection. This study used three published classification algorithms (hereafter called NeuPSIG, Smart, Schafer) to investigate the frequency of different pain classifications in NSAP and the clinical utility of these systems in assessing NSAP. Forty people with NSAP underwent a clinical examination and quantitative sensory testing. Findings were used to classify participants according to three classification algorithms. Frequency of pain classification including number unclassified was analysed using descriptive statistics. Inter-rater agreement was analysed using kappa coefficients. NSAP was primarily classified as ‘unlikely neuropathic pain’ using NeuPSIG criteria, ‘peripheral neuropathic pain’ using the Smart classification and ‘peripheral nerve sensitisation’ using the Schafer algorithm. Two of the three algorithms allowed classification of all but one participant; up to 45% of participants (n = 18) were categorised as mixed by the Smart classification. Inter-rater agreement was good for the Schafer algorithm (к = 0.78) and moderate for the Smart classification (к = 0.40). A kappa value was unattainable for the NeuPSIG algorithm but agreement was high. Pain classification was achievable with high inter-rater agreement for two of the three algorithms assessed. The Smart classification may be useful but requires further direction regarding the use of clinical criteria included. The impact of adding a pain classification to clinical assessment on patient outcomes needs to be evaluated

Efficacy of manipulation for non-specific neck pain of recent onset: design of a randomised controlled trial

BACKGROUND: Manipulation is a common treatment for non-specific neck pain. Neck manipulation, unlike gentler forms of manual therapy such as mobilisation, is associated with a small risk of serious neurovascular injury and can result in stroke or death. It is thought however, that neck manipulation provides better results than mobilisation where clinically indicated. There is long standing and vigorous debate both within and between the professions that use neck manipulation as well as the wider scientific community as to whether neck manipulation potentially does more harm than good. The primary aim of this study is to determine whether neck manipulation provides more rapid resolution of an episode of neck pain than mobilisation. METHODS/DESIGN: 182 participants with acute and sub-acute neck pain will be recruited from physiotherapy, chiropractic and osteopathy practices in Sydney, Australia. Participants will be randomly allocated to treatment with either manipulation or mobilisation. Randomisation will occur after the treating practitioner decides that manipulation is an appropriate treatment for the individual participant. Both groups will receive at least 4 treatments over 2 weeks. The primary outcome is number of days taken to recover from the episode of neck pain. Cox regression will be used to compare survival curves for time to recovery for the manipulation and mobilisation treatment groups. DISCUSSION: This paper presents the rationale and design of a randomised controlled trial to compare the effectiveness of neck manipulation and neck mobilisation for acute and subacute neck pain

Mapping genetic variations to three- dimensional protein structures to enhance variant interpretation: a proposed framework

The translation of personal genomics to precision medicine depends on the accurate interpretation of the multitude of genetic variants observed for each individual. However, even when genetic variants are predicted to modify a protein, their functional implications may be unclear. Many diseases are caused by genetic variants affecting important protein features, such as enzyme active sites or interaction interfaces. The scientific community has catalogued millions of genetic variants in genomic databases and thousands of protein structures in the Protein Data Bank. Mapping mutations onto three-dimensional (3D) structures enables atomic-level analyses of protein positions that may be important for the stability or formation of interactions; these may explain the effect of mutations and in some cases even open a path for targeted drug development. To accelerate progress in the integration of these data types, we held a two-day Gene Variation to 3D (GVto3D) workshop to report on the latest advances and to discuss unmet needs. The overarching goal of the workshop was to address the question: what can be done together as a community to advance the integration of genetic variants and 3D protein structures that could not be done by a single investigator or laboratory? Here we describe the workshop outcomes, review the state of the field, and propose the development of a framework with which to promote progress in this arena. The framework will include a set of standard formats, common ontologies, a common application programming interface to enable interoperation of the resources, and a Tool Registry to make it easy to find and apply the tools to specific analysis problems. Interoperability will enable integration of diverse data sources and tools and collaborative development of variant effect prediction methods

Corporate Governance for Sustainability

The current model of corporate governance needs reform. There is mounting evidence that the practices of shareholder primacy drive company directors and executives to adopt the same short time horizon as financial markets. Pressure to meet the demands of the financial markets drives stock buybacks, excessive dividends and a failure to invest in productive capabilities. The result is a ‘tragedy of the horizon’, with corporations and their shareholders failing to consider environmental, social or even their own, long-term, economic sustainability. With less than a decade left to address the threat of climate change, and with consensus emerging that businesses need to be held accountable for their contribution, it is time to act and reform corporate governance in the EU. The statement puts forward specific recommendations to clarify the obligations of company boards and directors and make corporate governance practice significantly more sustainable and focused on the long term

Relationship between the Clinical Frailty Scale and short-term mortality in patients ≥ 80 years old acutely admitted to the ICU: a prospective cohort study.

BACKGROUND: The Clinical Frailty Scale (CFS) is frequently used to measure frailty in critically ill adults. There is wide variation in the approach to analysing the relationship between the CFS score and mortality after admission to the ICU. This study aimed to evaluate the influence of modelling approach on the association between the CFS score and short-term mortality and quantify the prognostic value of frailty in this context. METHODS: We analysed data from two multicentre prospective cohort studies which enrolled intensive care unit patients ≥ 80 years old in 26 countries. The primary outcome was mortality within 30-days from admission to the ICU. Logistic regression models for both ICU and 30-day mortality included the CFS score as either a categorical, continuous or dichotomous variable and were adjusted for patient's age, sex, reason for admission to the ICU, and admission Sequential Organ Failure Assessment score. RESULTS: The median age in the sample of 7487 consecutive patients was 84 years (IQR 81-87). The highest fraction of new prognostic information from frailty in the context of 30-day mortality was observed when the CFS score was treated as either a categorical variable using all original levels of frailty or a nonlinear continuous variable and was equal to 9% using these modelling approaches (p < 0.001). The relationship between the CFS score and mortality was nonlinear (p < 0.01). CONCLUSION: Knowledge about a patient's frailty status adds a substantial amount of new prognostic information at the moment of admission to the ICU. Arbitrary simplification of the CFS score into fewer groups than originally intended leads to a loss of information and should be avoided. Trial registration NCT03134807 (VIP1), NCT03370692 (VIP2)

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease