This paper presents an adaBoost approach for schizophrenia relapse prediction. The data for the adaBoost are extracted from patients answers to Early Warning Signs questionnaires sent regularly via mobile phone messages. The performance of the adaBoost algorithm is confronted with current ITAREPS system with sensitivity 0.65 and specificity 0.73. AdaBoost has the same sensitivity 0.65 but higher specificity 0.84 and is then ready to became the part of the ITAREPS care program.

• MeSH
• adherence pacienta MeSH
• algoritmy MeSH
• časové faktory MeSH
• chování MeSH
• diagnóza počítačová metody   MeSH
• hospitalizace MeSH
• konzultace na dálku metody   MeSH
• lidé MeSH
• posílání textových zpráv MeSH
• recidiva MeSH
• rozvoj plánování metody   MeSH
• schizofrenie (psychologie) MeSH
• schizofrenie diagnóza   prevence a kontrola   MeSH
• software MeSH
• systémy pro podporu klinického rozhodování MeSH
• telemedicína metody   MeSH
• znovupřijetí pacienta MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

MOTIVATION: G-quadruplex is a DNA or RNA form in which four guanine-rich regions are held together by base pairing between guanine nucleotides in coordination with potassium ions. G-quadruplexes are increasingly seen as a biologically important component of genomes. Their detection in vivo is problematic; however, sequencing and spectrometric techniques exist for their in vitro detection. We previously devised the pqsfinder algorithm for PQS identification, implemented it in C++ and published as an R/Bioconductor package. We looked for ways to optimize pqsfinder for faster and user-friendly sequence analysis. RESULTS: We identified two weak points where pqsfinder could be optimized. We modified the internals of the recursive algorithm to avoid matching and scoring many sub-optimal PQS conformations that are later discarded. To accommodate the needs of a broader range of users, we created a website for submission of sequence analysis jobs that does not require knowledge of R to use pqsfinder. AVAILABILITY AND IMPLEMENTATION: https://pqsfinder.fi.muni.cz, https://bioconductor.org/packages/pqsfinder. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

• MeSH
• algoritmy MeSH
• G-kvadruplexy * MeSH
• genom MeSH
• RNA MeSH
• software MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

OBJECTIVES: The objective of this study was to assess the robustness of a novel test bolus (TB)-based computed tomographic angiography (CTA) contrast-enhancement-prediction (CEP) algorithm by retrospectively quantifying the systematic and random errors between the predicted and true enhancements. MATERIALS AND METHODS: All local institutional review boards approved this retrospective study, in which a total of 72 (3 × 24) anonymized cardiac CTA examinations were collected from 3 hospitals. All patients (46 men; median age, 62 years [range, 31-81 years]) underwent a TB scan and a cardiac CTA according to local scan and injection protocols. For each patient, a shorter TB signal and TB signals with lower temporal resolution were derived from the original TB signal. The CEP algorithm predicted the enhancement in the descending aorta (DAo) on the basis of the TB signals in the DAo, the injection protocols and kilovolt settings, as well as population-averaged blood circulation characteristics. The true enhancement was extracted with a region of interest along the DAo centerline. For each patient, the errors in timing and amplitude were calculated; differences between the hospitals were assessed using the 1-way analysis of variance (P < 0.05) and variations between the TB signals were assessed using the within-subject standard deviation. RESULTS: No significant differences were found between the 3 hospitals for any of the TB signals. With errors in the amplitude and timing of 0.3% ± 15.6% and -0.2 ± 2.0 seconds, respectively, no clinically relevant systematic errors existed. Shorter- and coarser-time-sampled TB signals introduced a within-subject standard deviation of 4.0% and 0.5 seconds, respectively. CONCLUSIONS: This TB-based CEP algorithm has no systematic errors in the timing and amplitude of predicted enhancements and is robust against coarser-time-sampled and incomplete TB scans.

• MeSH
• algoritmy * MeSH
• dospělí MeSH
• jopamidol analogy a deriváty   diagnostické užití   MeSH
• kontrastní látky diagnostické užití   MeSH
• koronární angiografie metody   MeSH
• lidé středního věku MeSH
• lidé MeSH
• nemoci koronárních tepen radiografie   MeSH
• počítačová rentgenová tomografie metody   MeSH
• počítačové zpracování obrazu metody   MeSH
• prediktivní hodnota testů MeSH
• reprodukovatelnost výsledků MeSH
• retrospektivní studie MeSH
• senioři nad 80 let MeSH
• senioři MeSH
• vylepšení rentgenového snímku metody   MeSH
• Check Tag
• dospělí MeSH
• lidé středního věku MeSH
• lidé MeSH
• mužské pohlaví MeSH
• senioři nad 80 let MeSH
• senioři MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• hodnotící studie MeSH

Neoadjuvant concomitant chemoradiotherapy has become a standard treatment of locally advanced rectal adenocarcinomas (LARA). It leads to shrinkage of the tumor mass and subsequently to an increase in complete resections (R0 resections), increasing a feasibility of sphincter-sparing intervention avoiding colostomy. It is based on concurrent application of fluoropyrimidines (5-fluorouracil, capecitabine) and radiotherapy (45 - 50,4 Gy). It shows less acute toxicity and improves local control rate in comparison to adjuvant treatment. Unfortunately, neoadjuvant chemoradiotherapy is not beneficial for all patients. The treatment response ranges from a complete pathological remission (pCR, ypT0ypN0) to a resistance. It is reported that cca 15 percent of patients with advanced rectal cancer show pCR which is indicative of improved long-term prognosis. DESIGN: The following is a review of the significance of neoadjuvant concomitant chemoradiotherapy in the treatment algorithm of patients with LARA and summary of potentional clinical-pathological and molecular markers of response prediction to neoadjuvant therapy. The most important clinical studies concern serum tumor markers levels, clinical lymph node classification. The components of the carcinogenic pathways are explored, including oncogenes, tumor supressor genes, microsatellite instability (MSI) and potentional markers involved in apoptosis, angiogionesis, proliferation as well as metastasis and invasion, are reviewed. Finally, the role of specific enzymes associated with the metabolism of fluoropyrimidines are examined. CONCLUSIONS: No one marker has been consistently identified as clinically applicable. Studies designed to determine the potentional markers are hampered by various techniques as well as tumor heterogenity and recent scientific approach--studying individual molecular markers. Gene expression profiling analysis of multiple genes from the same tumor is becoming reality. We suppose that this assessment will lead in future in finding combination of markers for predicting prognosis and response to therapy in rectal cancer.

• MeSH
• adenokarcinom farmakoterapie   chirurgie   radioterapie   MeSH
• adjuvantní chemoterapie MeSH
• adjuvantní radioterapie MeSH
• deoxycytidin analogy a deriváty   terapeutické užití   MeSH
• fluoruracil analogy a deriváty   terapeutické užití   MeSH
• lidé MeSH
• nádorové biomarkery analýza   MeSH
• nádory rekta farmakoterapie   chirurgie   radioterapie   MeSH
• neoadjuvantní terapie MeSH
• prognóza MeSH
• protinádorové antimetabolity terapeutické užití   MeSH
• výsledek terapie MeSH
• Check Tag
• lidé MeSH

Protože exprese hormonálních receptorů v karcinomech mléčné žlázy u části případů neodráží jejich aktuální funkční stav a neposkytuje pevný základ pro predikci odezvy nádorových buněk na hormonální terapii, byla provedena analýza vztahu mezi expresí estrogenovych i progesteronových receptorů, proliferační aktivitou nádoru a expresí „estrogen receptor related" proteinu p29. Cílem bylo nalézt způsob interpretace výsledků imunohistochemických vyšetření z hlediska funkčního stavu estrogeny zprostředkované regulační kaskády. Na základě této analýzy byl navržen algoritmus pro vyhodnocení funkčnosti estrogenovych receptorů v karcinomech mléčné žlázy.

Hormone receptor expression in breast cancer is not always a reliable reflection of their functional ability. This limitation affords a less valid prediction of tumor cell response to hormone treatment. For explanation of this phenomenon, the relationship between estrogen and progesterone receptor expression versus proliferative activity and the estrogen receptor related protein p29 expression was examined. Additional aim was to provide clues for interpretation of immunohistochemical findings from the point of view of the functional status of the estrogen receptor regulatory cascade. The results made possible establishment of a new diagnostic algorithm for evaluation of the estrogen receptor functional ability in breast cancer.

• MeSH
• imunohistochemie MeSH
• karcinom MeSH
• lidé MeSH
• nádory prsu MeSH
• proliferační antigen buněčného jádra izolace a purifikace   MeSH
• proteiny přístrojové vybavení   MeSH
• receptory pro estrogeny izolace a purifikace   MeSH
• receptory progesteronu izolace a purifikace   MeSH
• Check Tag
• lidé MeSH

Diet, stress, genetics, and a sedentary lifestyle may all contribute to heart disease rates. Although recent studies propose comprehensive automated diagnostic systems, these systems tend to focus on one aspect, such as feature selection, prioritization, or predictive accuracy. A more complete approach that considers all of these factors can improve the efficiency of a cardiac prediction system. This study uses an appropriate strategy to overcome potential network design problems, design challenges, overfitting, and lack of robustness that can interfere with system performance. The research introduces an ideally designed deep trust network called ID-DTN to improve system performance. The Ruzzo-Tompa method is used to eliminate noncontributory features. The Seagull Optimization Algorithm (SOA) is introduced to optimize the trust depth network to achieve optimal network design. The study scrutinizes the deep trust network (ID-DTN) and the restricted Boltzmann machine (RBM) and sheds light on the system's operation. This proposal can optimize both network architecture and feature selection, which is the main novelty. The proposed method is analyzed using the below-mentioned metrics: Matthew's correlation coefficient, F1 score, accuracy, sensitivity, specificity, and accuracy. ID-DTN performs well compared to other state-of-the-art methods. The validation results confirm that the proposed method improves the prediction accuracy to 97.11% and provides reliable recommendations for patients with cardiovascular disease.

• MeSH
• algoritmy * MeSH
• lidé MeSH
• nemoci srdce * diagnóza   MeSH
• neuronové sítě MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH

BACKGROUND: Young people with psychosis are at high risk of developing cardiometabolic disorders; however, there is no suitable cardiometabolic risk prediction algorithm for this group. We aimed to develop and externally validate a cardiometabolic risk prediction algorithm for young people with psychosis. METHODS: We developed the Psychosis Metabolic Risk Calculator (PsyMetRiC) to predict up to 6-year risk of incident metabolic syndrome in young people (aged 16-35 years) with psychosis from commonly recorded information at baseline. We developed two PsyMetRiC versions using the forced entry method: a full model (including age, sex, ethnicity, body-mass index, smoking status, prescription of a metabolically active antipsychotic medication, HDL concentration, and triglyceride concentration) and a partial model excluding biochemical results. PsyMetRiC was developed using data from two UK psychosis early intervention services (Jan 1, 2013, to Nov 4, 2020) and externally validated in another UK early intervention service (Jan 1, 2012, to June 3, 2020). A sensitivity analysis was done in UK birth cohort participants (aged 18 years) who were at risk of developing psychosis. Algorithm performance was assessed primarily via discrimination (C statistic) and calibration (calibration plots). We did a decision curve analysis and produced an online data-visualisation app. FINDINGS: 651 patients were included in the development samples, 510 in the validation sample, and 505 in the sensitivity analysis sample. PsyMetRiC performed well at internal (full model: C 0·80, 95% CI 0·74-0·86; partial model: 0·79, 0·73-0·84) and external validation (full model: 0·75, 0·69-0·80; and partial model: 0·74, 0·67-0·79). Calibration of the full model was good, but there was evidence of slight miscalibration of the partial model. At a cutoff score of 0·18, in the full model PsyMetRiC improved net benefit by 7·95% (sensitivity 75%, 95% CI 66-82; specificity 74%, 71-78), equivalent to detecting an additional 47% of metabolic syndrome cases. INTERPRETATION: We have developed an age-appropriate algorithm to predict the risk of incident metabolic syndrome, a precursor of cardiometabolic morbidity and mortality, in young people with psychosis. PsyMetRiC has the potential to become a valuable resource for early intervention service clinicians and could enable personalised, informed health-care decisions regarding choice of antipsychotic medication and lifestyle interventions. FUNDING: National Institute for Health Research and Wellcome Trust.

• MeSH
• algoritmy * MeSH
• dospělí MeSH
• kardiometabolické riziko * MeSH
• lidé MeSH
• metabolický syndrom diagnóza   MeSH
• mladiství MeSH
• mladý dospělý MeSH
• psychotické poruchy * diagnóza   MeSH
• reprodukovatelnost výsledků MeSH
• Check Tag
• dospělí MeSH
• lidé MeSH
• mladiství MeSH
• mladý dospělý MeSH
• mužské pohlaví MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• validační studie MeSH

Diagnostický algoritmus svalových dystrofií se v uplynulé dekádě výrazně změnil, a to zejména díky rozvoji a zvýšení dostupnosti molekulárně genetických a zobrazovacích metod. Aktuálně, kromě podrobně odebrané anamnézy, detailního klinického vyšetření, biochemického a elektrofyziologického testování, přibylo vyšetření svalů magnetickou rezonancí a nové metody molekulárně genetického vyšetření, naopak svalová biopsie přestala být nezbytnou metodou v diagnostice hereditárních myopatií. Rutinní provádění MRI u pacientů se svalovými dystrofiemi umožnilo odhalení a popsání vzorců svalového postižení (pattern of recognition) charakteristických pro určité klinické jednotky. Molekulárně genetická vyšetření pak, jako jediná, umožňují stanovení definitivní diagnózy na základě detekce kauzální mutace. Pro lepší orientaci v běžné ambulantní praxi popisuje článek hlavní kroky vedoucí k odhalení jednotlivých typů svalových dystrofií s ohledem na úroveň dnešních znalostí a zkušeností.

The diagnostics algorithm of muscular dystrophies has changed significantly over the past decade, mainly due to the development and increase of availability of molecular genetics and imaging methods. The golden standard of detailed medical history, attentive clinical examination, biochemical and electrophysiological testing now includes also magnetic resonance imaging and targeted or more extensive molecular genetic examinations, while muscle biopsy ceased to be the first choice method in the diagnostic process of hereditary myopathies. Routine MRI performance in patients with muscle. dystrophies allowed the detection and description of patterns of recognition characteristic for certain clinical units. Molecular genetic examinations as the only one allow definitive diagnosis to be determined by causal mutation detection. For better orientation in common outpatient practice, the article describes the crucial steps leading to the discovery of individual types of muscular dystrophy with respect to the level of today's knowledge and experience.

• MeSH
• biopsie MeSH
• diferenciální diagnóza MeSH
• elektromyografie metody   MeSH
• fenotyp MeSH
• genetické testování metody   MeSH
• kosterní svaly diagnostické zobrazování   MeSH
• kreatinkinasa krev   MeSH
• lidé MeSH
• magnetická rezonanční tomografie MeSH
• nemoci svalů diagnostické zobrazování   diagnóza   metabolismus   MeSH
• svalové dystrofie * diagnostické zobrazování   diagnóza   MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• přehledy MeSH

BACKGROUND AND OBJECTIVE: In silico prediction of drug-target interactions (DTI) could provide valuable information and speed-up the process of drug repositioning - finding novel usage for existing drugs. In our work, we focus on machine learning algorithms supporting drug-centric repositioning approach, which aims to find novel usage for existing or abandoned drugs. We aim at proposing a per-drug ranking-based method, which reflects the needs of drug-centric repositioning research better than conventional drug-target prediction approaches. METHODS: We propose Bayesian Ranking Prediction of Drug-Target Interactions (BRDTI). The method is based on Bayesian Personalized Ranking matrix factorization (BPR) which has been shown to be an excellent approach for various preference learning tasks, however, it has not been used for DTI prediction previously. In order to successfully deal with DTI challenges, we extended BPR by proposing: (i) the incorporation of target bias, (ii) a technique to handle new drugs and (iii) content alignment to take structural similarities of drugs and targets into account. RESULTS: Evaluation on five benchmark datasets shows that BRDTI outperforms several state-of-the-art approaches in terms of per-drug nDCG and AUC. BRDTI results w.r.t. nDCG are 0.929, 0.953, 0.948, 0.897 and 0.690 for G-Protein Coupled Receptors (GPCR), Ion Channels (IC), Nuclear Receptors (NR), Enzymes (E) and Kinase (K) datasets respectively. Additionally, BRDTI significantly outperformed other methods (BLM-NII, WNN-GIP, NetLapRLS and CMF) w.r.t. nDCG in 17 out of 20 cases. Furthermore, BRDTI was also shown to be able to predict novel drug-target interactions not contained in the original datasets. The average recall at top-10 predicted targets for each drug was 0.762, 0.560, 1.000 and 0.404 for GPCR, IC, NR, and E datasets respectively. CONCLUSIONS: Based on the evaluation, we can conclude that BRDTI is an appropriate choice for researchers looking for an in silico DTI prediction technique to be used in drug-centric repositioning scenarios. BRDTI Software and supplementary materials are available online at www.ksi.mff.cuni.cz/∼peska/BRDTI.

• MeSH
• algoritmy MeSH
• Bayesova věta * MeSH
• datové soubory jako téma MeSH
• farmakologie * MeSH
• lidé MeSH
• přehodnocení terapeutických indikací léčivého přípravku MeSH
• strojové učení MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH

Seizure prediction is feasible, but greater accuracy is needed to make seizure prediction clinically viable across a large group of patients. Recent work crowdsourced state-of-the-art prediction algorithms in a worldwide competition, yielding improvements in seizure prediction performance for patients whose seizures were previously found hard to anticipate. The aim of the current analysis was to explore potential performance improvements using an ensemble of the top competition algorithms. The results suggest that minor increments in performance may be possible; however, the outcomes of statistical testing limit the confidence in these increments. Our results suggest that for the specific algorithms, evaluation framework, and data considered here, incremental improvements are achievable but there may be upper bounds on machine learning-based seizure prediction performance for some patients whose seizures are challenging to predict. Other more tailored approaches that, for example, take into account a deeper understanding of preictal mechanisms, patient-specific sleep-wake rhythms, or novel measurement approaches, may still offer further gains for these types of patients.

• MeSH
• algoritmy * MeSH
• crowdsourcing MeSH
• elektroencefalografie MeSH
• elektrokortikografie metody   MeSH
• epilepsie parciální diagnóza   MeSH
• lidé středního věku MeSH
• lidé MeSH
• mladý dospělý MeSH
• prediktivní hodnota testů MeSH
• refrakterní epilepsie diagnóza   MeSH
• reprodukovatelnost výsledků MeSH
• senzitivita a specificita MeSH
• spánek MeSH
• strojové učení MeSH
• studie proveditelnosti MeSH
• záchvaty diagnóza   MeSH
• Check Tag
• lidé středního věku MeSH
• lidé MeSH
• mladý dospělý MeSH
• mužské pohlaví MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH