Early identification of false news is now essential to save lives from the dangers posed by its spread. People keep sharing false information even after it has been debunked. Those responsible for spreading misleading information in the first place should face the consequences, not the victims of their actions. Understanding how misinformation travels and how to stop it is an absolute need for society and government. Consequently, the necessity to identify false news from genuine stories has emerged with the rise of these social media platforms. One of the tough issues of conventional methodologies is identifying false news. In recent years, neural network models' performance has surpassed that of classic machine learning approaches because of their superior feature extraction. This research presents Deep learning-based Fake News Detection (DeepFND). This technique has Visual Geometry Group 19 (VGG-19) and Bidirectional Long Short Term Memory (Bi-LSTM) ensemble models for identifying misinformation spread through social media. This system uses an ensemble deep learning (DL) strategy to extract characteristics from the article's text and photos. The joint feature extractor and the attention modules are used with an ensemble approach, including pre-training and fine-tuning phases. In this article, we utilized a unique customized loss function. In this research, we look at methods for detecting bogus news on the internet without human intervention. We used the Weibo, liar, PHEME, fake and real news, and Buzzfeed datasets to analyze fake and real news. Multiple methods for identifying fake news are compared and contrasted. Precision procedures have been used to calculate the proposed model's output. The model's 99.88% accuracy is better than expected.

• Klíčová slova
• Deep learning, DeepFND, Ensemble model, Fake news, Joint feature extraction,
• Publikační typ
• zprávy MeSH

BACKGROUND: Genomics and proteomics are nowadays the dominant techniques for novel biomarker discovery. However, histopathology images contain a wealth of information related to the tumor histology, morphology and tumor-host interactions that is not accessible through these techniques. Thus, integrating the histopathology images in the biomarker discovery workflow could potentially lead to the identification of new image-based biomarkers and the refinement or even replacement of the existing genomic and proteomic signatures. However, extracting meaningful and robust image features to be mined jointly with genomic (and clinical, etc.) data represents a real challenge due to the complexity of the images. RESULTS: We developed a framework for integrating the histopathology images in the biomarker discovery workflow based on the bag-of-features approach - a method that has the advantage of being assumption-free and data-driven. The images were reduced to a set of salient patterns and additional measurements of their spatial distribution, with the resulting features being directly used in a standard biomarker discovery application. We demonstrated this framework in a search for prognostic biomarkers in breast cancer which resulted in the identification of several prognostic image features and a promising multimodal (imaging and genomic) prognostic signature. The source code for the image analysis procedures is freely available. CONCLUSIONS: The framework proposed allows for a joint analysis of images and gene expression data. Its application to a set of breast cancer cases resulted in image-based and combined (image and genomic) prognostic scores for relapse-free survival.

• Klíčová slova
• Biomarker discovery, Gene expression, Histopathology images, Image analysis, Multimodal data mining,
• MeSH
• genomika metody   MeSH
• Kaplanův-Meierův odhad MeSH
• lidé MeSH
• nádory prsu genetika   patologie   MeSH
• počítačové zpracování obrazu * MeSH
• regulace genové exprese u nádorů * MeSH
• shluková analýza MeSH
• stanovení celkové genové exprese MeSH
• Check Tag
• lidé MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH

BACKGROUND: Presentation of visual stimuli can induce changes in EEG signals that are typically detectable by averaging together data from multiple trials for individual participant analysis as well as for groups or conditions analysis of multiple participants. This study proposes a new method based on the discrete wavelet transform with Huffman coding and machine learning for single-trial analysis of evenal (ERPs) and classification of different visual events in the visual object detection task. METHODS: EEG single trials are decomposed with discrete wavelet transform (DWT) up to the [Formula: see text] level of decomposition using a biorthogonal B-spline wavelet. The coefficients of DWT in each trial are thresholded to discard sparse wavelet coefficients, while the quality of the signal is well maintained. The remaining optimum coefficients in each trial are encoded into bitstreams using Huffman coding, and the codewords are represented as a feature of the ERP signal. The performance of this method is tested with real visual ERPs of sixty-eight subjects. RESULTS: The proposed method significantly discards the spontaneous EEG activity, extracts the single-trial visual ERPs, represents the ERP waveform into a compact bitstream as a feature, and achieves promising results in classifying the visual objects with classification performance metrics: accuracies 93.60[Formula: see text], sensitivities 93.55[Formula: see text], specificities 94.85[Formula: see text], precisions 92.50[Formula: see text], and area under the curve (AUC) 0.93[Formula: see text] using SVM and k-NN machine learning classifiers. CONCLUSION: The proposed method suggests that the joint use of discrete wavelet transform (DWT) with Huffman coding has the potential to efficiently extract ERPs from background EEG for studying evoked responses in single-trial ERPs and classifying visual stimuli. The proposed approach has O(N) time complexity and could be implemented in real-time systems, such as the brain-computer interface (BCI), where fast detection of mental events is desired to smoothly operate a machine with minds.

• Klíčová slova
• Discrete wavelet transform, Huffman coding, Machine learning classifiers, Single trials analysis (ERPs), Visual object detection,
• MeSH
• algoritmy MeSH
• elektroencefalografie * metody   MeSH
• evokované potenciály fyziologie   MeSH
• lidé MeSH
• plocha pod křivkou MeSH
• počítačové zpracování signálu MeSH
• strojové učení MeSH
• vlnková analýza * MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

PURPOSE: Brittle cornea syndrome 1 (BCS1) is a rare recessive condition characterized by extreme thinning of the cornea and sclera, caused by mutations in ZNF469. Keratoconus is a relatively common disease characterized by progressive thinning and ectasia of the cornea. The etiology of keratoconus is complex and not yet understood, but rare ZNF469 variants have recently been associated with disease. We investigated the phenotype of BCS1 carriers with known pathogenic ZNF469 mutations, and recruited families in which aggregation of keratoconus was observed to establish if rare variants in ZNF469 segregated with disease. METHODS: Patients and family members were recruited and underwent comprehensive anterior segment examination, including corneal topography. Blood samples were donated and genomic DNA was extracted. The coding sequence and splice sites of ZNF469 were PCR amplified and Sanger sequenced. RESULTS: Four carriers of three BCS1-associated ZNF469 loss-of-function mutations (p.[Glu1392Ter], p.[Gln1930Argfs*6], p.[Gln1930fs*133]) were examined and none had keratoconus. One carrier had partially penetrant features of BCS1, including joint hypermobility. ZNF469 sequencing in 11 keratoconus families identified 9 rare (minor allele frequency [MAF] ≤ 0.025) variants predicted to be potentially damaging. However, in each instance the rare variant(s) identified, including two previously reported as potentially keratoconus-associated, did not segregate with the disease. CONCLUSIONS: The presence of heterozygous loss-of-function alleles in the ZNF469 gene did not cause keratoconus in the individuals examined. None of the rare nonsynonymous ZNF469 variants identified in the familial cohort conferred a high risk of keratoconus; therefore, genetic variants contributing to disease pathogenesis in these 11 families remain to be identified.

• Klíčová slova
• ZNF469, brittle cornea syndrome, familial keratoconus, keratoconus,
• MeSH
• abnormality očí MeSH
• dospělí MeSH
• Ehlersův-Danlosův syndrom genetika   patologie   MeSH
• fenotyp MeSH
• heterozygot MeSH
• jednonukleotidový polymorfismus MeSH
• keratokonus genetika   patologie   MeSH
• kožní abnormality MeSH
• lidé MeSH
• mladý dospělý MeSH
• mutace * MeSH
• mutační analýza DNA MeSH
• nestabilita kloubu vrozené   MeSH
• polymerázová řetězová reakce MeSH
• rodokmen MeSH
• rohovková topografie MeSH
• transkripční faktory genetika   MeSH
• Check Tag
• dospělí MeSH
• lidé MeSH
• mladý dospělý MeSH
• mužské pohlaví MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Názvy látek
• transkripční faktory MeSH
• ZNF469 protein, human MeSH Prohlížeč

PURPOSE: Differentiating the anatomical variations of the anterosuperior portion of the glenoid labrum from pathologies is important to avoid unnecessary iatrogenic complications resulting from inaccurate diagnosis. Additionally, the presence of several variations was reported to be conductive to lesions involving the glenoid labrum. Thus, the aim of this study was to state the prevalence rates of the sublabral recess, sublabral foramen, and the Buford complex, and to verify their association with labral lesions. METHODS: Systematic search of electronic databases was conducted to gain potentially eligible literature. Suitable studies were selected in a two-round screening, and relevant data were subsequently extracted. Calculation of the pooled prevalence estimates, including sub-analyses on cohort size, study type, and geographical variance, was conducted. Pooled analysis of risk ratios (RR) was used to assess the conductive nature of the discussed variants to superior labrum anterior to posterior (SLAP) lesions. RESULTS: The screening resulted in selection of 20 studies investigating the morphological features of the glenoid labrum, consisting of 7601 upper limbs. On the bases of random-effects meta-analysis the sublabral recess, sublabral foramen and Buford complex occur with a pooled prevalence of 57.2% (95% CI 30.0-84.4%), 13.5% (95% CI 8.2-18.9%), and 3.0% (95% CI 1.5-4.5), respectively. Moreover, individuals with Buford complex have RR 2.4 (95% CI 1.3-4.7) of developing SLAP lesions, especially type II (95.5%; 95% CI 86.1-100%), whereas such risk for sublabral recess and sublabral foramen was not statistically significant. CONCLUSION: Morphological variants of the glenoid labrum posing diagnostic confusion are frequently observed. Gradually, the Buford complex may be a predisposing factor for sustaining a SLAP lesion.

• Klíčová slova
• Buford complex, Glenoid labrum, SLAP lesion, Sublabral foramen, Sublabral recess,
• MeSH
• artroskopie MeSH
• horní končetina MeSH
• lidé MeSH
• poranění ramene * epidemiologie   MeSH
• prevalence MeSH
• ramenní kloub * patologie   MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• metaanalýza MeSH
• systematický přehled MeSH

PURPOSE: The accessory bones around the elbow are very rare variant structures, present in approximately 0.7% of cases. They can cause diagnostic problems and can be mistaken for pathological structures, especially when pain and limitation of elbow movements are present and a trauma can be traced in the patient's history. They are of different nature, either presenting within muscle tendons as sesamoids (brachialis and triceps brachii muscles) or presenting intra-articularly probably as separated or accessory ossification centres. The least common is the os supratrochleare anterius. METHODS: We present a case of a young male, featuring chronic blocking and 20° limited flexion of his right elbow, which bothered him during his occupation as a locksmith. In history, he suffered minor trauma to the elbow 20 years ago. X-ray and CT showed a large ossicle in the coronoid fossa of the humerus. RESULTS: The ossicle was surgically extracted in small pieces. The patient left satisfied with no mention of complaints. CONCLUSION: The os supratrochleare anterius is a very rare accessory bone of the elbow, located in the coronoid fossa of the humerus which can mimic many pathological states, and limit movements and causing pain around the elbow.

• Klíčová slova
• Accessory bone, Accessory ossicle, Elbow, Os supratrochleare anterius,
• MeSH
• anatomická variace * MeSH
• humerus diagnostické zobrazování   MeSH
• lidé MeSH
• loketní kloub * MeSH
• počítačová rentgenová tomografie MeSH
• Check Tag
• lidé MeSH
• mužské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• kazuistiky MeSH
• přehledy MeSH

BACKGROUND: Identification of parameters for early diagnosis and treatment response would be beneficial for patients with early rheumatoid arthritis (ERA) to prevent ongoing joint damage. miRNAs have features of potential biomarkers, and an altered expression of miRNAs was shown in established rheumatoid arthritis (RA). OBJECTIVE: To analyse RA associated miRNAs in the sera of patients with ERA to find markers of early disease, clinical activity or predictors of disease outcome. METHODS: Total RNA was isolated from whole sera in ERA patients (prior to and after 3 and 12 months of therapy with disease modifying antirheumatic drugs), in patients with established RA and in healthy controls (HC) using phenol-chloroform extraction. Expression of miR-146a, miR-155, miR-223, miR-16, miR-203, miR-132 and miR-124a was analysed by TaqMan Real Time PCR. RESULTS: From all analysed miRNAs, levels of miR-146a, miR-155 and miR-16 were decreased in the sera of ERA patients in comparison with established RA. A change in circulating miR-16 in the first 3 months of therapy was associated with a decrease in DAS28 in long term follow-up in ERA (p=0.002). Levels of circulating miR-223 in treatment naïve ERA correlated with C reactive protein (p=0.008), DAS28 (p=0.031) and change in DAS28 after 3 months (p=0.003) and 12 months (p=0.011) of follow-up. However, neither miR-16 nor miR-223 could distinguish ERA from HC. CONCLUSIONS: Differential expression of circulating miR-146a, miR-155 and miR-16 in the sera of ERA patients may characterise an early stage of the disease. We suggest miR-223 as a marker of disease activity and miR-16 and miR-223 as possible predictors for disease outcome in ERA.

• Klíčová slova
• DAS28, Early Rheumatoid Arthritis, Rheumatoid Arthritis,
• MeSH
• antirevmatika terapeutické užití   MeSH
• biologické markery krev   metabolismus   MeSH
• časná diagnóza MeSH
• dospělí MeSH
• exprese genu MeSH
• fibroblasty metabolismus   MeSH
• kultivované buňky MeSH
• lidé středního věku MeSH
• lidé MeSH
• mikro RNA biosyntéza   krev   genetika   MeSH
• následné studie MeSH
• počet leukocytů MeSH
• prognóza MeSH
• revmatoidní artritida diagnóza   farmakoterapie   genetika   MeSH
• senioři MeSH
• studie případů a kontrol MeSH
• stupeň závažnosti nemoci MeSH
• synoviální membrána metabolismus   patologie   MeSH
• Check Tag
• dospělí MeSH
• lidé středního věku MeSH
• lidé MeSH
• mužské pohlaví MeSH
• senioři MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Názvy látek
• antirevmatika MeSH
• biologické markery MeSH
• mikro RNA MeSH
• MIRN16 microRNA, human MeSH Prohlížeč
• MIRN223 microRNA, human MeSH Prohlížeč