Mycetoma trichophyton

A 2-year-old female child admitted to the hospital due to a palpable mass at her scalp referred by her parents. Her past medical history was clear. The clinical examination revealed edema, redness/erythema, blisters, tenderness and itching. No neurological changes were referred, no hair loss occurred and no other areas of the body were affected. The initial evaluation included X-rays, an ultrasonography and a magnetic resonance imaging (MRI) scan. The imaging findings were not pathognomonic but in combination with the clinical features, the differential diagnosis shrinked between mycetoma and pilomatrixoma (or calcifying epithelioma of Malherbe). For further evaluation, a small specimen of the scalp was obtained by scraping the skin with a scalpel. Cytological investigation revealed fungi infection caused by trichophyton species. So the final accurate diagnosis was mycetoma trichophyton. Patient was treated with miconazole nitrate (daktarin cream 2%), 1x3 for 15 days. First follow-up (day 15) showed improvement to complete cure. At the second follow up (day 30) there was no evidence of relapse. Mycetoma trichophyton must be differentiated from pilomatrixoma (which may appear with similar clinical and sonographic features), cutaneous tuberculosis, folliculitis, actinomycosis, chromomycosis, sporotrichosis, coccidioidomycosis, blastomycosis of the skin, botryomycosis etc. Dermatophyte infections usually occur in immuno compromised patients. In our case, the young patient was healthy and no medication administration had previously happened. A trichophyton infection mainly causes superficial lesions to the skin, nails and hair, deeper dermis and subcutaneous tissue anywhere on the body but most frequently at the lower extremities

White Dwarfs in our Galaxy using Gaia EDR3 data

Στην εργασία αυτή μελετήσαμε το πληθυσμό των λευκών νάνων (ΛΝ) του Γαλαξία μας, χρησιμοποιώντας δεδομένα Gaia EDR3. Αρχικά, μελετήθηκε το θεωρητικό υπόβαθρο που περιλαμβάνει την εσωτερική δομή των ΛΝ, τη χημική σύσταση, φασματικούς τύπους, μαγνητικά πεδία και ατμόσφαιρες. Το δείγμα των ΛΝ που αξιοποιήθηκε προέρχεται από το κατάλογο των Gentile Fusillo et al. 2019. Ο κατάλογος αυτός βασιζόταν σε δεδομένα Gaia DR2 και τον ενημερώσαμε με EDR3. Διαγράμματα χρώματος μεγέθους (colour magnitude diagrams, CMDs) και αντιπροσωπευτικά διαγράμματα χρώματος-χρώματος έγιναν και πριν και μετά τη διόρθωση για ερύθρωση (reddening) και απόσταση (η οποία βασίστηκε σε παραλλάξεις από Gaia EDR3). Εξελικτικά μοντέλα για ΛΝ από εξέλιξη μονού αστέρα με σύνθεση είτε υδρογόνου (H) είτε ηλίου (He) χρησιμοποιήθηκαν για να εξαχθούν οι μάζες και οι ηλικίες των ΛΝ. Μια σημαντική πλευρά της δουλειάς μας ήταν να καθορίσουμε ποιοι από αυτούς τους ΛΝ ανήκουν σε ανοιχτά σμήνη. Χρησιμοποιήσαμε το κατάλογο ανοικτών σμηνών των Cantat-Gaudin et al. 2018a. Αυτός ο κατάλογος επίσης ενημερώθηκε με δεδομένα Gaia EDR3. Χρησιμοποιήσαμε συντεταγμένες και ιδίες κινήσεις για να καθορίσουμε την ιδιότητα του μέλους. Μετά από διεξοδικό έλεγχο χρησιμοποιώντας τις παραλλάξεις, αποκτήσαμε το τελικό μας δείγμα 16 σμηνών που περιέχουν τουλάχιστον έναν ΛΝ ως πιθανό ή δυνατό μέλος. Το τελευταίο κομμάτι της δουλειάς μας ήταν να χρησιμοποιήσουμε το πληθυσμό των ΛΝ στα ανοικτά σμήνη ώστε να βάλουμε περιορισμούς στην εξάρτηση της απώλειας μάζας από την αρχική μάζα του αστέρα και τη μεταλλικότητα.In this work, we studied the white dwarfs (WD) of our Galaxy using Gaia EDR3 data. First, the theoretical background was explored such as their internal structure, their chemical composition, their spectral types, their magnetic fields, their atmospheres. The sample of WDs that was utilised comes from the catalogue of Gentile Fusillo et al. 2019. This catalogue was updated with Gaia EDR3, since it contains Gaia DR2 data. Then, the colour magnitude diagramme (CMDs) and representative colour colour diagrammes (CCDs) were constructed, both before and after the correction for reddening. Also, evolutionary models for WDs from single star evolution with hydrogen (H) or helium (He) composition were used to infer the WD masses and ages. An important aspect of our work was to determine which of these WDs belong to open clusters. We used the open cluster catalogue of Cantat-Gaudin et al. 2018a. This catalogue was also updated with Gaia EDR3 data, since it was based on Gaia DR2 data. We used coordinates and proper motions to define membership. After thorough check using the parallaxes, we were able to obtain our final sample of 16 clusters containing at least one possible or probable WD member. The final part of the work was to use the WD population in open clusters to constrain the dependence of mass loss on initial mass and metallicity

Living with satisfactory vision and no comorbidity 28 years after bilateral retinoblastoma: a case report and mini literature review

Background: Retinoblastoma is the most common primary intraocular malignancy in children, although it is a rare neural retinal tumor. Improving the quality of life is the next goal after the primary medical goal of life preservation. The genotype-phenotype correlation may vary with the progression of retinoblastoma. Expressivity is determined by different RB1 gene mutations among individuals. Herein, we share our experience on the evaluation of the long-term progression of retinoblastoma, its treatment consequences, its impact on the quality of life, and how the underlying genotypes are related to the phenotypes. We provide a review of the relevant literature and present a case of a sporadic heritable bilateral retinoblastoma. Case Presentation: We report the outcomes of a 28-year follow-up of a female diagnosed with an infantile disease. The patient’s best eye, according to the tumor classification and genetic results, was treated conservatively whereas the worst eye was enucleated. On re-examinations, she had complications of the treatment she received. Therefore, another intervention was administered for several years. The patient’s pathogenic variant and RB1 gene mutational inactivation were predispositions to the recurrence of the tumor and non-ocular primary malignancy. Nevertheless, the disease had no progression. The patient is stable despite her type of retinoblastoma, which is the sporadic heritable bilateral form. Conclusions: Each phenotype of bilateral retinoblastoma varies in progression. The nature of the genetic mutation may determine its expressivity. It is of great significance to individualize every decision. In each case, the sequelae of the disease and treatment-induced complications may have an impact on the quality of the patient’s life

Improving the Price of Anarchy for Selfish Routing via Coordination Mechanisms

We reconsider the well-studied Selfish Routing game with affine latency functions. The Price of Anarchy for this class of games takes maximum value 4/3; this maximum is attained already for a simple network of two parallel links, known as Pigou's network. We improve upon the value 4/3 by means of Coordination Mechanisms. We increase the latency functions of the edges in the network, i.e., if $\ell_e(x)$ is the latency function of an edge $e$, we replace it by $\hat{\ell}_e(x)$ with $\ell_e(x) \le \hat{\ell}_e(x)$ for all $x$. Then an adversary fixes a demand rate as input. The engineered Price of Anarchy of the mechanism is defined as the worst-case ratio of the Nash social cost in the modified network over the optimal social cost in the original network. Formally, if \CM(r) denotes the cost of the worst Nash flow in the modified network for rate $r$ and \Copt(r) denotes the cost of the optimal flow in the original network for the same rate then [\ePoA = \max_{r \ge 0} \frac{\CM(r)}{\Copt(r)}.] We first exhibit a simple coordination mechanism that achieves for any network of parallel links an engineered Price of Anarchy strictly less than 4/3. For the case of two parallel links our basic mechanism gives 5/4 = 1.25. Then, for the case of two parallel links, we describe an optimal mechanism; its engineered Price of Anarchy lies between 1.191 and 1.192.Comment: 17 pages, 2 figures, preliminary version appeared at ESA 201

Deployment of Image Analysis Algorithms under Prevalence Shifts

Domain gaps are among the most relevant roadblocks in the clinical translation of machine learning (ML)-based solutions for medical image analysis. While current research focuses on new training paradigms and network architectures, little attention is given to the specific effect of prevalence shifts on an algorithm deployed in practice. Such discrepancies between class frequencies in the data used for a method's development/validation and that in its deployment environment(s) are of great importance, for example in the context of artificial intelligence (AI) democratization, as disease prevalences may vary widely across time and location. Our contribution is twofold. First, we empirically demonstrate the potentially severe consequences of missing prevalence handling by analyzing (i) the extent of miscalibration, (ii) the deviation of the decision threshold from the optimum, and (iii) the ability of validation metrics to reflect neural network performance on the deployment population as a function of the discrepancy between development and deployment prevalence. Second, we propose a workflow for prevalence-aware image classification that uses estimated deployment prevalences to adjust a trained classifier to a new environment, without requiring additional annotated deployment data. Comprehensive experiments based on a diverse set of 30 medical classification tasks showcase the benefit of the proposed workflow in generating better classifier decisions and more reliable performance estimates compared to current practice

Prognostic stratification of patients with advanced renal cell carcinoma treated with sunitinib: comparison with the Memorial Sloan-Kettering prognostic factors model

<p>Abstract</p> <p>Background</p> <p>The treatment paradigm in advanced renal cell carcinoma (RCC) has changed in the recent years. Sunitinib has been established as a new standard for first-line therapy. We studied the prognostic significance of baseline characteristics and we compared the risk stratification with the established Memorial Sloan Kettering Cancer Center (MSKCC) model.</p> <p>Methods</p> <p>This is a retrospective analysis of patients treated in six Greek Oncology Units of HECOG. Inclusion criteria were: advanced renal cell carcinoma not amenable to surgery and treatment with Sunitinib. Previous cytokine therapy but no targeted agents were allowed. Overall survival (OS) was the major end point. Significance of prognostic factors was evaluated with multivariate cox regression analysis. A model was developed to stratify patients according to risk.</p> <p>Results</p> <p>One hundred and nine patients were included. Median follow up has been 15.8 months and median OS 17.1 months (95% CI: 13.7-20.6). Time from diagnosis to the start of Sunitinib (<= 12 months vs. >12 months, p = 0.001), number of metastatic sites (1 vs. >1, p = 0.003) and performance status (PS) (<= 1 vs >1, p = 0.001) were independently associated with OS. Stratification in two risk groups ("low" risk: 0 or 1 risk factors; "high" risk: 2 or 3 risk factors) resulted in distinctly different OS (median not reached [NR] vs. 10.8 [95% confidence interval (CI): 8.3-13.3], p < 0.001). The application of the MSKCC risk criteria resulted in stratification into 3 groups (low and intermediate and poor risk) with distinctly different prognosis underlying its validity. Nevertheless, MSKCC model did not show an improved prognostic performance over the model developed by this analysis.</p> <p>Conclusions</p> <p>Studies on risk stratification of patients with advanced RCC treated with targeted therapies are warranted. Our results suggest that a simpler than the MSKCC model can be developed. Such models should be further validated.</p

Systematic mapping of free energy landscapes of a growing filamin domain during biosynthesis

Cotranslational folding (CTF) is a fundamental molecular process that ensures efficient protein biosynthesis and minimizes the formation of misfolded states. However, the complexity of this process makes it extremely challenging to obtain structural characterizations of CTF pathways. Here, we correlate observations of translationally arrested nascent chains with those of a systematic C-terminal truncation strategy. We create a detailed description of chain length-dependent free energy landscapes associated with folding of the FLN5 filamin domain, in isolation and on the ribosome, and thus, quantify a substantial destabilization of the native structure on the ribosome. We identify and characterize two folding intermediates formed in isolation, including a partially folded intermediate associated with the isomerization of a conserved cis proline residue. The slow folding associated with this process raises the prospect that neighboring unfolded domains might accumulate and misfold during biosynthesis. We develop a simple model to quantify the risk of misfolding in this situation and show that catalysis of folding by peptidyl-prolyl isomerases is sufficient to eliminate this hazard. [Abstract copyright: Copyright © 2018 the Author(s). Published by PNAS.

Common Limitations of Image Processing Metrics:A Picture Story

While the importance of automatic image analysis is continuously increasing, recent meta-research revealed major flaws with respect to algorithm validation. Performance metrics are particularly key for meaningful, objective, and transparent performance assessment and validation of the used automatic algorithms, but relatively little attention has been given to the practical pitfalls when using specific metrics for a given image analysis task. These are typically related to (1) the disregard of inherent metric properties, such as the behaviour in the presence of class imbalance or small target structures, (2) the disregard of inherent data set properties, such as the non-independence of the test cases, and (3) the disregard of the actual biomedical domain interest that the metrics should reflect. This living dynamically document has the purpose to illustrate important limitations of performance metrics commonly applied in the field of image analysis. In this context, it focuses on biomedical image analysis problems that can be phrased as image-level classification, semantic segmentation, instance segmentation, or object detection task. The current version is based on a Delphi process on metrics conducted by an international consortium of image analysis experts from more than 60 institutions worldwide.Comment: This is a dynamic paper on limitations of commonly used metrics. The current version discusses metrics for image-level classification, semantic segmentation, object detection and instance segmentation. For missing use cases, comments or questions, please contact [email protected] or [email protected]. Substantial contributions to this document will be acknowledged with a co-authorshi

Understanding metric-related pitfalls in image analysis validation

Validation metrics are key for the reliable tracking of scientific progress and for bridging the current chasm between artificial intelligence (AI) research and its translation into practice. However, increasing evidence shows that particularly in image analysis, metrics are often chosen inadequately in relation to the underlying research problem. This could be attributed to a lack of accessibility of metric-related knowledge: While taking into account the individual strengths, weaknesses, and limitations of validation metrics is a critical prerequisite to making educated choices, the relevant knowledge is currently scattered and poorly accessible to individual researchers. Based on a multi-stage Delphi process conducted by a multidisciplinary expert consortium as well as extensive community feedback, the present work provides the first reliable and comprehensive common point of access to information on pitfalls related to validation metrics in image analysis. Focusing on biomedical image analysis but with the potential of transfer to other fields, the addressed pitfalls generalize across application domains and are categorized according to a newly created, domain-agnostic taxonomy. To facilitate comprehension, illustrations and specific examples accompany each pitfall. As a structured body of information accessible to researchers of all levels of expertise, this work enhances global comprehension of a key topic in image analysis validation.Comment: Shared first authors: Annika Reinke, Minu D. Tizabi; shared senior authors: Paul F. J\"ager, Lena Maier-Hei

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries