Local binary pattern
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Silva invasion pattern can help predict lymph node metastasis risk in endocervical adenocarcinoma. We analysed Silva pattern of invasion and lymphovascular invasion to determine associations with clinical outcomes in stage IA and IB1 endocervical adenocarcinomas. International Federation of Gynecology and Obstetrics (FIGO; 2019 classification) stage IA-IB1 endocervical adenocarcinomas from 15 international institutions were examined for Silva pattern, presence of lymphovascular invasion, and other prognostic parameters. Lymph node metastasis status, local/distant recurrences, and survival data were compared using appropriate statistical tests. Of 399 tumours, 152 (38.1%) were stage IA [IA1, 77 (19.3%); IA2, 75 (18.8%)] and 247 (61.9%) were stage IB1. On multivariate analysis, lymphovascular invasion (p=0.008) and Silva pattern (p<0.001) were significant factors when comparing stage IA versus IB1 endocervical adenocarcinomas. Overall survival was significantly associated with lymph node metastasis (p=0.028); recurrence-free survival was significantly associated with lymphovascular invasion (p=0.002) and stage (1B1 versus 1A) (p=0.002). Five and 10 year overall survival and recurrence-free survival rates were similar among Silva pattern A cases and Silva pattern B cases without lymphovascular invasion (p=0.165 and p=0.171, respectively). Silva pattern and lymphovascular invasion are important prognostic factors in stage IA1-IB1 endocervical adenocarcinomas and can supplement 2019 International Federation of Gynecology and Obstetrics staging. Our binary Silva classification system groups patients into low risk (patterns A and B without lymphovascular invasion) and high risk (pattern B with lymphovascular invasion and pattern C) categories.
BACKGROUND: One of the major challenges in the analysis of gene expression data is to identify local patterns composed of genes showing coherent expression across subsets of experimental conditions. Such patterns may provide an understanding of underlying biological processes related to these conditions. This understanding can further be improved by providing concise characterizations of the genes and situations delimiting the pattern. RESULTS: We propose a method called semantic biclustering with the aim to detect interpretable rectangular patterns in binary data matrices. As usual in biclustering, we seek homogeneous submatrices, however, we also require that the included elements can be jointly described in terms of semantic annotations pertaining to both rows (genes) and columns (samples). To find such interpretable biclusters, we explore two strategies. The first endows an existing biclustering algorithm with the semantic ingredients. The other is based on rule and tree learning known from machine learning. CONCLUSIONS: The two alternatives are tested in experiments with two Drosophila melanogaster gene expression datasets. Both strategies are shown to detect sets of compact biclusters with semantic descriptions that also remain largely valid for unseen (testing) data. This desirable generalization aspect is more emphasized in the strategy stemming from conventional biclustering although this is traded off by the complexity of the descriptions (number of ontology terms employed), which, on the other hand, is lower for the alternative strategy.
An automatic method of segmenting the retinal vessel tree and estimating status of retinal neural fibre layer (NFL) from high resolution fundus camera images is presented. First, reliable blood vessel segmentation, using 2D directional matched filtering, enables to remove areas occluded by blood vessels thus leaving remaining retinal area available to the following NFL detection. The local existence of rather faint and hardly visible NFL is detected by combining several newly designed local textural features, sensitive to subtle NFL characteristics, into feature vectors submitted to a trained neural-network classifier. Obtained binary retinal maps of NFL distribution show a good agreement with both medical expert evaluations and quantitative results obtained by optical coherence tomography.
- MeSH
- fluoresceinová angiografie metody MeSH
- interpretace obrazu počítačem metody MeSH
- lidé MeSH
- nemoci zrakového nervu patologie MeSH
- nervová síť patologie MeSH
- reprodukovatelnost výsledků MeSH
- retinální cévy patologie MeSH
- retinoskopie metody MeSH
- rozpoznávání automatizované metody MeSH
- senzitivita a specificita MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
Z důvodu omezené dostupnosti přípravků průmyslově vyráběných s obsahem lokálního anestetika určených k aplikaci na kůži a zvýšené poptávky po lidokainovém gelu použitelném před aplikací přípravku s obsahem kapsaicinu určeného k léčbě neuropatické bolesti se nabízí možnost magistraliter přípravy topického polotuhého přípravku s obsahem lokálního anestetika. Cílem bylo připravit směsný systém hydrogelu s vemulgovaným léčivem, využít látky snižující teplotu tání lidokainu a vytvořit eutektickou směs s vysokou koncentrací lidokainu, která tvoří olejovou fázi systému. Dle údajů ze zahraniční literatury byl pro vytvoření binární eutektické směsi s lidokainem zvolen thymol a za přídavku dalších pomocných látek formulován emulzní systém s vemulgovaným léčivem v lipofilní fázi stabilizovaný komplexním neiontovým emulgátorem a karbomerem. Pro vyhovující anestezující účinnost je dále třeba upravit hodnotu pH přípravku. Vhodnou zásaditě reagující látkou byl zvolen trometamol. Na základě přídavku různých množství trometamolu bylo následně měřeno pH jednotlivých vzorků emulgelů a v porovnání s hodnotou pH přípravku EMLA pak vytvořeno výsledné složení lidokainového emulgelu. Při formulaci receptury byl brán zřetel na praktičnost a dostupnost obsažených látek. Všechny složky jsou k dispozici pro přípravu léčivých přípravků v České republice s příslušným certifikátem jakosti. Receptura 5% lidokainového emulgelu s hodnotou pH cca 9,1 je formulována na bázi gelotvorné látky karbomeru s vemulgovanou olejovou fází představovanou eutektickou směsí lidokainu s thymolem, za přídavku ethanolu a propylenglykolu, stabilizovaného komplexním emulgátorem. Výhodou je absence přísady jiného lokálního anestetika.
Due to a limited availability of industrially manufactured products containing local anesthetics for skin application and an increased demand for lidocaine-containing gel applicable prior to a product containing capsaicin for neuropathic pain treatment, it is necessary to prepare a topical semi-solid preparation containing the local anesthetic in pharmacies. Our aim was to create a mixed system of a hydrophilic gel with the emulsified drug, using excipients to decrease the lidocaine melting point, thereby creating a eutectic mixture with a high concentration of lidocaine in the oil phase. Based on bibliographic data, thymol creating a binary eutectic system containing lidocaine has been chosen. After addition of other excipients, an emulsion system was prepared and the drug was stabilized in the oil phase by a mixed nonionic emulsifier and carbomera. For the optimal anesthetic effects, the pH value should be adjusted; trometamol has been chosen as a suitable basic reacting excipient. Based on the addition of different amounts of trometamol, pH values of individual emulgels have been measured and the final composition of lidocaine emulgel has been created. A recipe for a 5 % lidocaine emulgel with the pH value of 9.1 has been created, based on the gel-forming substance carbomera with an emulsion of the oil phase containing a eutectic mixture of lidocaine and thymol, with an addition of ethanol and propylenglycol, stabilized by a mixed nonionic emulsifier. The advantage is the absence of other local anesthetics.
- Klíčová slova
- binary eutectic mixture,
- MeSH
- anestetika lokální * MeSH
- aplikace kožní * MeSH
- aplikace lokální MeSH
- dermatologické látky MeSH
- elektronová mikroskopie * MeSH
- emulze MeSH
- hydrogely MeSH
- kapsaicin MeSH
- lidé MeSH
- lidokain * MeSH
- okluzivní ošetření rány * MeSH
- povrchově aktivní látky MeSH
- příprava léků * MeSH
- schvalování léčiv MeSH
- thymol MeSH
- Check Tag
- lidé MeSH
- Geografické názvy
- Česká republika MeSH
Images of ocular fundus are routinely utilized in ophthalmology. Since an examination using fundus camera is relatively fast and cheap procedure, it can be used as a proper diagnostic tool for screening of retinal diseases such as the glaucoma. One of the glaucoma symptoms is progressive atrophy of the retinal nerve fiber layer (RNFL) resulting in variations of the RNFL thickness. Here, we introduce a novel approach to capture these variations using computer-aided analysis of the RNFL textural appearance in standard and easily available color fundus images. The proposed method uses the features based on Gaussian Markov random fields and local binary patterns, together with various regression models for prediction of the RNFL thickness. The approach allows description of the changes in RNFL texture, directly reflecting variations in the RNFL thickness. Evaluation of the method is carried out on 16 normal ("healthy") and 8 glaucomatous eyes. We achieved significant correlation (normals: ρ=0.72±0.14; p≪0.05, glaucomatous: ρ=0.58±0.10; p≪0.05) between values of the model predicted output and the RNFL thickness measured by optical coherence tomography, which is currently regarded as a standard glaucoma assessment device. The evaluation thus revealed good applicability of the proposed approach to measure possible RNFL thinning.
- MeSH
- barva * MeSH
- discus nervi optici patologie MeSH
- fundus oculi MeSH
- glaukom patologie MeSH
- lidé MeSH
- Markovovy řetězce * MeSH
- nervová vlákna patologie MeSH
- normální rozdělení MeSH
- optická koherentní tomografie MeSH
- retinální gangliové buňky patologie MeSH
- vylepšení obrazu metody MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
