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We present an unusual case of Mondor disease (MD) occurring secondary to elliptical excision of a naevus on the chest wall. MD is a rare superficial thrombophlebitis classically occurring on the anterolateral thoracoabdominal wall. It can be idiopathic, can be due to trauma, breast malignancy, hypercoagulable states or can be iatrogenic, most commonly arising from breast surgery. The condition is generally self-resolving within weeks.

Rationale: The ZZ genotype of alpha-1 antitrypsin deficiency (AATD) is associated with chronic obstructive pulmonary disease (COPD), even among never-smokers. The SZ genotype is also considered severe; yet, its effect on lung health remains unclear. Objectives: To determine the effect of SZ-AATD on spirometry compared with a normal-risk population and to determine the effect of smoking cessation in this genotype. Methods: We prospectively enrolled 166 related individuals, removing lung index cases to reduce bias, and compared spirometry between 70 SZ and 46 MM/MS individuals (control subjects). The effect of AAT concentrations on outcomes was assessed in 82 SZ individuals (including lung index cases). Subsequently, we analyzed retrospective SZ registry data to determine the effect of smoking cessation on spirometry decline (n = 60) and plasma anti–neutrophil elastase capacity (n = 20). Measurements and Main Results: No difference between SZ and control never-smokers was seen. Ever smoking was associated with a lower FEV(1)% predicted (−14.3%; P = 0.0092) and a lower FEV(1)/FVC ratio (−0.075; P = 0.0041) in SZ-AATD. No association was found between AAT concentration and outcomes for SZ-AATD. Longitudinal analysis of 60 SZ individuals demonstrated that COPD at baseline, but not former smoking or AAT concentrations, predicted greater spirometry decline. Finally, anti–neutrophil elastase capacity did not differ between former smokers and never-smokers (P = 0.67). Conclusions: SZ never-smokers demonstrated no increased risk of COPD, regardless of AAT concentration. Smoking interacts with SZ-AATD to significantly increase airflow obstruction. Former smoking alone is not associated with greater spirometry decline in SZ-AATD, suggesting that cessation attenuates the obstructive process. We found no evidence that the putative protective threshold or AAT concentrations predict risk within the SZ genotype, raising further doubts over the need for intravenous AAT augmentation in this cohort.

Altered microRNA expression patterns in bronchial brushings from people with versus without cystic fibrosis (CF) relate to functional changes and disease pathophysiology. The expression of microRNAs encoded on the X chromosome is also altered in peripheral blood monocytes of p. Phe508del homozygous versus non-CF individuals. Here we investigate whether levels of the top seven X-linked microRNAs (miR-224-5p, miR-452-5p, miR-450b-5p, miR-542-3p, miR-450a-5p, miR-424-5p, and miR-545-5p) that are significantly increased over 1.5 fold in CF versus non-CF monocytes correlate with lung function. CD14+ monocytes were isolated from males and females with (n = 12) and without cystic fibrosis (n = 12) and examined for the expression of X-linked microRNAs by qRT-PCR array. MicroRNA target mRNA levels were quantified using qRT-PCR. Clinical correlations with lung function data were analysed in the CF cohort. Increasing levels of miR-545-5p correlated moderately with FEV1% predicted (r = -0.4553, p > 0.05) and strongly with exacerbation rate (r = 0.5858, p = 0.0483). miR-224-5p levels were significantly higher in the severe (FEV1 p = 0.0377) or moderate (FEV1 40–79%, p = 0.0350) groups. MiR-224-5p expression inversely correlated with lung function (FEV1%: r = -0.5944, p = 0.0457) and positively correlated with exacerbation rates (r = 0.6139, p = 0.0370). These data show that peripheral blood monocyte miR-545-5p and miR-224-5p levels correlate with exacerbation rate, whilst miR-224-5p levels also correlate with lung function in cystic fibrosis.

In considering what constitutes the ideal born-digital literary archive and what interventions are possible, or even necessary, from a collecting institution in determining the make-up and ...

Introduction: A novel monoclonal antibody therapy termed mogamulizumab is currently seeking approval for treatment of mycosis fungoides and Sezary syndrome. Mogamulizumab is a humanized IgG1 κ monoclonal antibody which targets C-C chemokine receptor type 4 (CCR4), a transmembrane chemokine receptor which promotes T cell migration to the skin and is expressed at high levels on the surface of the malignant cells which drive cutaneous lymphomas. Methods: We performed a multi-centre clinical audit using data from 16 patients who have received mogamulizumab through a patient access programme at The Christie (8) and University Hospitals Birmingham (8) NHS Foundation Trusts. Our cohort had a median age of 68.1 (57.1–71.5) years at initiation of treatment, with a male to female sex ratio of 1.67 and varied diagnoses including Sezary syndrome (62.5%), classical mycosis fungoides (18.8%) and folliculotropic mycosis fungoides (12.5%). We assessed objective measures of disease response in the skin (mSWAT scores) and blood (flow cytometry), progression free survival (PFS) and the incidence of adverse events with the aim to further assess the efficacy and safety of mogamulizumab in this setting. Results: The patients in our cohort showed significant responses to mogamulizumab with median mSWAT score falling from 108 (53.8–139.1) to 23.1 (8.8–75.0) at peak response which was achieved at a median of 202 (115.5–328) days. 31.3% of our patients achieved a complete skin response whilst 37.5% achieved a partial skin response. The flow cytometry results of our cohort showed a marked improvement after initiation of mogamulizumab with median CD4/CD8 ratio, median number of circulating CD4+CD7– and CD4+CD26–being reduced by 89.0%, 96.8% and 95.8% respectively with median time to peak response being 193 (139.75–305.25) days. 62.5% of patients achieved a complete blood response with a further 25% achieving a partial blood response. Mogamulizumab was generally well tolerated with a median number of CTCAE events of 1.5 (0–4.25), which were predominantly grade 1 (62.9%) followed by grade 2 (22.9%) and grade 3 (14.3%) with no higher-grade adverse events being reported by any of the patients who had received mogamulizumab. One patient did discontinue treatment due to toxicity. Progression was only seen in 2 of the 16 with a medium follow up of 267 days (194.3–462.8) The median PFS has not been reached. 3 of the 16 patients have died, causes of death were CTCL (1), squamous cell carcinoma (1) and upper gastrointestinal haemorrhage (1). Conclusion: Mogamulizumab treatment resulted in marked improvements in skin and blood disease activity for patients across both centres whilst being generally well tolerated. The median PFS has not been reached after a median FU of 8.9 months. This compares favourably with the PFS of 7.7 months seen in the MAVORIC study. This observational study confirmed a high response rate in blood and skin in this group of diseases.

Introduction: Prioritisation of National Health Service (NHS) resources to cope with the COVID-19 pandemic has had a major impact on dermatology services. The consequences of the pandemic on the care of patients with primary cutaneous lymphoma (CL) in the U.K. is unknown. Objective: To examine the impact of the Covid-19 pandemic on patients enrolled in the prospective registration and data collection study for newly diagnosed patients with all stages of MF/SS ‘PROCLIPI (PROspective Cutaneous Lymphoma International Prognostic Index) Study’. Methods: The impact of the COVID-19 pandemic was assessed by comparing the pre-COVID clinical stage (TNMB stage, mSWAT score, global response assessment) and health-related quality of life (HRQoL (Skindex-29) prior to and 4.5 (4.0-5.6) months after the onset of the COVID-19 pandemic. A specific COVID-19 dataset was used to capture the impact of the pandemic on study participants. Results: PROCLIPI study visit data was analysed in 75 patients with a mean (±SD) age of 65.19 (±14.31) years with a male: female ratio of 1.4:1. 61 patients had early stage (IA, n=41; IB, n=17 and IIA, n=3) and 14 had late-stage disease (IIB, n=3; IIIA, n=4; IIIB, n=1; IVA1, n=3 and IVA2, n=3) of whom 70 had MF and five SS. Global response assessment was possible in 40 patients. 17.1% (n=7) had an overall response (CR=1; PR=6), 43.9% (n=18) stable disease and 39% (n=16) progressive disease. The mean (±SEM) time to disease progression was 13.82 (±1.22) months and the median (IQR) mSWAT score increased from 7.25 (0.85–30.25) to 26.4 (2.6–41.78), p=0.08. 12 patients had missed/delayed treatments (phototherapy, n=5; radiotherapy, n=1; topical skin direct therapy, n=3; extracorporeal photopheresis, n=1; investigational medicinal product, n=2). We found no quantitative differences in health-related quality of life (HRQoL) using Skindex-29 (n=75) however 40.6% of patients rated the pandemic as having a moderate to severe impact on their QoL. COVID-19 risk group stratification identified 16.7% of patients with high risk and 54.5% of patients with moderate risk features for severe illness from the virus. Five patients developed COVID-19 illness and one with advanced disease (SS, Stage IVA2) in a high-risk COVID-19 group died. Conclusion: The COVID-19 pandemic has significantly impacted the care of patients with CL. From March 2020 all CL clinics were cancelled, clinical trials were suspended and only emergency appointments permitted. Further work comparing progression status in a matched cohort from 2015 and 2016 will further assess the impact of the COVID-19 pandemic in CL.

International audience; This paper addresses the simultaneous design and path planning problem, in which features associated to the bodies of a mobile system have to be selected to find the best design that optimizes its motion between two given configurations. Solving individual path planning problems for all possible designs and selecting the best result would be a straightforward approach for very simple cases. We propose a more efficient approach that combines discrete (design) and continuous (path) optimization in a single stage. It builds on an extension of a sampling-based algorithm, which simultaneously explores the configuration-space costmap of all possible designs aiming to find the best path-design pair. The algorithm filters out unsuitable designs during the path search, which breaks down the combinatorial explosion. Illustrative results are presented for relatively simple (academic) examples. While our work is currently motivated by problems in computational biology, several applications in robotics can also be envisioned.

Motivation Loop portions in proteins are involved in many molecular interaction processes. They often exhibit a high degree of flexibility, which can be essential for their function. However, molecular modeling approaches usually represent loops using a single conformation. Although this conformation may correspond to a (meta-)stable state, it does not always provide a realistic representation. Results In this paper, we propose a method to exhaustively sample the conformational space of protein loops. It exploits structural information encoded in a large library of three-residue fragments, and enforces loop-closure using a closed-form inverse kinematics solver. A novel reinforcement-learning-based approach is applied to accelerate sampling while preserving diversity. The performance of our method is showcased on benchmark datasets involving 9-, 12- and 15-residue loops. In addition, more detailed results presented for streptavidin illustrate the ability of the method to exhaustively sample the conformational space of loops presenting several meta-stable conformations. Availability and implementation We are developing a software package called MoMA (for Molecular Motion Algorithms), which includes modeling tools and algorithms to sample conformations and transition paths of biomolecules, including the application described in this work. The binaries can be provided upon request and a web application will also be implemented in the short future. Supplementary information Supplementary data are available at Bioinformatics online.

Cystic fibrosis is a genetic disease caused by mutations in the CFTR gene, whereas chronic obstructive pulmonary disease (COPD) is mainly caused by environmental factors (mostly cigarette smoking) on a genetically susceptible background. Although the etiology and pathogenesis of these diseases are different, both are associated with progressive airflow obstruction, airway neutrophilic inflammation, and recurrent exacerbations, suggesting common mechanisms. The airway epithelium plays a crucial role in maintaining normal airway functions. Major molecular and morphologic changes occur in the airway epithelium in both CF and COPD, and growing evidence suggests that airway epithelial dysfunction is involved in disease initiation and progression in both diseases. Structural and functional abnormalities in both airway and alveolar epithelium have a relevant impact on alteration of host defences, immune/inflammatory response, and the repair process leading to progressive lung damage and impaired lung function. In this review, we address the evidence for a critical role of dysfunctional airway epithelial cells in chronic airway inflammation and remodelling in CF and COPD, highlighting the common mechanisms involved in the epithelial dysfunction as well as the similarities and differences of the two diseases.

Background: Health-related quality of life (HRQoL) in patients with cutaneous lymphoma (CL) is negatively impacted by a large burden of disease symptoms including intractable itch, pain, discomfort and socially stigmatising cosmetic disfigurement which may adversely affect patient self-esteem and interpersonal relationships. There is currently no cure for CL and as such, accurate determination of patient HRQoL is of paramount importance. To date, the impact of both skin disease and of a cancer diagnosis on patient HRQoL in CL is assessed using separate, non-CL-specific questionnaires. A composite HRQoL questionnaire addressing all aspects of the disease is lacking. Methods: The EORTC Quality of Life Group questionnaire development guidelines were followed. For phase I, semi-structured interviews were conducted in 15 patients with early-stage mycosis fungoides (IA–IIA), 30 patients with late-stage mycosis fungoides/Sezary syndrome (IIB–IVB) (15 patients 3 years from diagnosis) and 15 patients with cutaneous B cell lymphoma. Collaborators communicated during the patient recruitment to ensure balanced patient selection with respect to age, gender, stage, duration of the disease, and number of (previous) treatments. Results: Patients were recruited in 5 countries (6 centres) across Europe. So far, 62 patients participated (target 60) from each of the following representative patient groups: early MF (stage IA–IIA), late MF (stage IIB–IVB) and cutaneous B cell lymphoma. Data from patient interviews and questionnaires is being analyzed using basic quantitative analyses, including generation of descriptive statistics (e.g., %missing data, means and standard deviations, floor and ceiling effects, etc.), prevalence (number of patients who experienced each complaint i.e. who scored 2, 3 or 4, divided by the total number of patients who completed that item, multiplied by 100), priority ratings (number of patients and professionals who have given priority ratings to each item) and range of responses for each item. The data from the debriefing questions will be reported both quantitatively and qualitatively (in narrative form). Conclusion: Once completed, phase I issues will be operationalised into items and any new items created in a style and format compatible with the EORTC quality of life group translation guidelines (phase II). The preliminary module will be pre-tested in phase III followed by large-scale international field-testing in phase IV. A comprehensive HRQoL questionnaire (module) for patients with CL is being developed to more accurately measure assessment of the impact of HRQoL in patients with skin lymphomas.

Stenotrophomonas maltophilia is an emerging global opportunistic pathogen that has been appearing with increasing prevalence in cystic fibrosis (CF). A secreted protease from S. maltophilia has been reported as its chief potential virulence factor. Here, using the reference clinical strain S. maltophilia K279a, the major secreted proteases were identified. Protein biochemistry and mass spectrometry were carried out on K279a culture supernatant. The effect of K279a culture supernatant on cleavage and anti-neutrophil elastase activity of the three majors pulmonary antiproteases was quantified. A deletion mutant of S. maltophilia lacking expression of a protease was constructed. The serine proteases StmPR1, StmPR2 and StmPR3, in addition to chitinase A and an outer membrane esterase were identified in culture supernatants. Protease activity was incompletely abrogated in a K279a-&Delta, StmPR1: Erm mutant. Wild type K279a culture supernatant degraded alpha-1 antitrypsin (AAT), secretory leucoprotease inhibitor (SLPI) and elafin, important components of the lung&rsquo, s innate immune defences. Meanwhile SLPI and elafin, but not AAT, retained their ability to inhibit neutrophil elastase. StmPR3 together with StmPR1 and StmPR2, is likely to contribute to protease-mediated innate immune dysfunction in CF.

SUMMARYEvidence is emerging that the role of protein structure in disease needs to be rethought. Sequence mutations in proteins are often found to affect the rate at which a protein switches between structures. Modeling structural transitions in wildtype and variant proteins is central to understanding the molecular basis of disease. This paper investigates an efficient algorithmic realization of the stochastic roadmap simulation framework to model structural transitions in wildtype and variants of proteins implicated in human disorders. Our results indicate that the algorithm is able to extract useful information on the impact of mutations on protein structure and function.

International audience; The study of the conformational energy landscape of a molecule is essential for the understanding of its physicochemical properties. This requires the exploration of a continuous, high-dimensional space to identify the most probable conformations and the transition paths between them. The problem is computationally difficult, in particular for highly-flexible biomolecules such as Intrinsically Disordered Proteins (IDPs). In recent years, a robotics-inspired algorithm called Transition-based Rapidly-exploring Random Tree (TRRT) has been proposed to solve this problem, and has been shown to provide good results with small and middle-sized biomolecules. Aiming to treat larger systems, we propose a hybrid strategy for the efficient parallelization of a multi-tree variant of TRRT, called Multi-TRRT, enabling an efficient execution in (possibly large) computer clusters. The parallel algorithm uses OpenMP multi-threading for computation inside each multi-core processor and MPI to perform the communication between processors. Results show a near-linear speedup for a wide range of cluster configurations. Although the paper mainly deals with the application of the proposed parallel algorithm to the investigation of biomolecules, the explanations concerning the methods are general, aiming to inspire future work on the parallelization of related algorithms.

With biomolecular structure recognized as central to understanding mechanisms in the cell, dry laboratories have spent significant efforts on modeling and analyzing structure and dynamics. While significant advances have been made, particularly in the design of sophisticated energetic models and molecular representations, such efforts are experiencing diminishing returns. One of the culprits is the low exploration capability of Molecular Dynamics- and Monte Carlo-based exploration algorithms. The impasse has attracted AI researchers bringing complementary tools, such as randomized search and stochastic optimization. The tutorial introduces students and researchers to stochastic optimization treatments and methodologies for understanding and elucidating the role of biomolecular structure and dynamics in function. In addition, the tutorial allows attendees to connect between structures, motions, and function via analysis tools that take an energy landscape view of the relationship between biomolecular structure, dynamics, and function. The presentation is enhanced via open-source software that permit hands-on exercises, which benefits both students and senior researchers keen to make their own contributions.

The rapid accumulation of protein structures presents a unique set of challenges and opportunities in the analysis, comparison, modeling, and prediction of macromolecular structures and their interactions. This workshop brought together researchers with expertise in bioinformatics, structural computational biology, machine learning, optimization, and high performance computing, to disseminate new results, and discuss techniques and research problems.

International audience; This paper addresses the simultaneous design and path planning problem, in which features associated to the bodies of a mobile system have to be selected to find the best design that optimizes its motion between two given configurations. Solving individual path planning problems for all possible designs and selecting the best result would be a straightforward approach for very simple cases. We propose a more efficient approach that combines discrete (design) and continuous (path) optimization in a single stage. It builds on an extension of a sampling-based algorithm, which simultaneously explores the configuration-space costmap of all possible designs aiming to find the best path-design pair. The algorithm filters out unsuitable designs during the path search, which breaks down the combinatorial explosion. Illustrative results are presented for relatively simple (academic) robotic examples, showing that even in these simple cases, the computational cost can be reduced by two orders of magnitude with respect to the na¨ıvena¨ıve approach. A preliminary application to challenging problems in computational biology related to protein design is also discussed at the end of the paper.

Interleukin (IL)-8 levels are higher than normal in cystic fibrosis (CF) airways, causing neutrophil infiltration and non-resolving inflammation. Overexpression of microRNAs that target IL-8 expression in airway epithelial cells may represent a therapeutic strategy for cystic fibrosis.IL-8 protein and mRNA were measured in cystic fibrosis and non-cystic fibrosis bronchoalveolar lavage fluid and bronchial brushings (n=20 per group). miRNAs decreased in the cystic fibrosis lung and predicted to target IL-8 mRNA were quantified in βENaC-transgenic, cystic fibrosis transmembrane conductance regulator (Cftr)-/- and wild-type mice, primary cystic fibrosis and non-cystic fibrosis bronchial epithelial cells and a range of cystic fibrosis versus non-cystic fibrosis airway epithelial cell lines or cells stimulated with lipopolysaccharide, Pseudomonas-conditioned medium or cystic fibrosis bronchoalveolar lavage fluid. The effect of miRNA overexpression on IL-8 protein production was measured.miR-17 regulates IL-8 and its expression was decreased in adult cystic fibrosis bronchial brushings, βENaC-transgenic mice and bronchial epithelial cells chronically stimulated with Pseudomonas-conditioned medium. Overexpression of miR-17 inhibited basal and agonist-induced IL-8 protein production in F508del-CFTR homozygous CFTE29o− tracheal, CFBE41o− and/or IB3 bronchial epithelial cells.These results implicate defective CFTR, inflammation, neutrophilia and mucus overproduction in regulation of miR-17. Modulating miR-17 expression in cystic fibrosis bronchial epithelial cells may be a novel anti-inflammatory strategy for cystic fibrosis and other chronic inflammatory airway diseases.

The rapid accumulation of macromolecular structures presents a unique set of challenges and opportunities in the analysis, comparison, modeling, and prediction of macromolecular structures and interactions. This workshop aims to bring together researchers with expertise in bioinformatics, computational biology, structural biology, data mining, optimization and high performance computing to discuss new results, techniques, and research problems in computational structural bioinformatics.

With biomolecular structure recognized as central to understanding mechanisms in the cell, computational chemists and biophysicists have spent significant efforts on modeling structure and dynamics. While significant advances have been made, particularly in the design of sophisticated energetic models and molecular representations, such efforts are experiencing diminishing returns. One of the culprits is low exploration capability. The impasse has attracted AI researchers to offer adaptations of robot motion planning algorithms for modeling biomolecular structures and motions. This tutorial introduces students and researchers to robotics-inspired treatments and methodologies for understanding and elucidating the role of structure and dynamics in the function of biomolecules. The presentation is enhanced via an open-source software developed in the Shehu Computational Biology laboratory. The software allows researchers to integrate themselves in a new research domain and drive further research via plug-and-play capabilities. The hands-on approach in the the tutorial benefits both students and senior researchers keen to make contributions in computational structural biology.