In motor functional neurological disorders (mFND), relationships between interoception (a construct of high theoretical relevance to its pathophysiology) and neuroanatomy have not been previously investigated. This study characterized white matter in mFND patients compared to healthy controls (HCs), and investigated associations between fiber bundle integrity and cardiac interoception. Voxel-based analysis and tractography quantified fractional anisotropy (FA) in 38 mFND patients compared to 38 HCs. Secondary analyses compared functional seizures (FND-seiz; n = 21) or functional movement disorders (n = 17) to HCs. Network lesion mapping identified gray matter origins of implicated fiber bundles. Within-group mFND analyses investigated relationships between FA, heartbeat tracking accuracy and interoceptive trait prediction error (discrepancies between interoceptive accuracy and self-reported bodily awareness). Results were corrected for multiple comparisons, and all findings were adjusted for depression and trait anxiety. mFND and HCs did not show any between-group interoceptive accuracy or FA differences. However, the FND-seiz subgroup compared to HCs showed decreased integrity in right-lateralized tracts: extreme capsule/inferior fronto-occipital fasciculus, arcuate fasciculus, inferior longitudinal fasciculus, and thalamic/striatum to occipital cortex projections. These alterations originated predominantly from the right temporoparietal junction and inferior temporal gyrus. In mFND patients, individual differences in interoceptive accuracy and interoceptive trait prediction error correlated with fiber bundle integrity originating from the insula, temporoparietal junction, putamen and thalamus among other regions. In this first study investigating brain-interoception relationships in mFND, individual differences in interoceptive accuracy and trait prediction error mapped onto multimodal integration-related fiber bundles. Right-lateralized limbic and associative tract disruptions distinguished FND-seiz from HCs.
- MeSH
- White Matter * diagnostic imaging pathology physiopathology MeSH
- Biological Variation, Population physiology MeSH
- Adult MeSH
- Interoception physiology MeSH
- Middle Aged MeSH
- Humans MeSH
- Young Adult MeSH
- Cerebral Cortex MeSH
- Movement Disorders * diagnostic imaging pathology physiopathology MeSH
- Anticipation, Psychological physiology MeSH
- Gray Matter * diagnostic imaging pathology physiopathology MeSH
- Heart Rate physiology MeSH
- Diffusion Tensor Imaging * MeSH
- Check Tag
- Adult MeSH
- Middle Aged MeSH
- Humans MeSH
- Young Adult MeSH
- Male MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Research Support, N.I.H., Extramural MeSH
Ciele: Analyzovať naše výsledky refrakcie po operácii sivého zákalu v závislosti od rôznych premených akými sú rôzne typy monofokálnych umelých vnútroočných šošoviek, vzorce pre ich výpočet, pohlavie, vek a lateralita Miesto výskumu: Klinika oftalmológie LFUK a UNB Ružinov, Bratislava, Slovensko Dizajn: Retrospektívna štúdia. Metodika: Analyzovali sme 173 očí (118 pacientov) po nekomplikovanej operácii sivého zákalu. Zisťovali sme rozdiel a absolútny rozdiel medzi skutočnou a odhadovanou pooperačnou refrakciou, tzv. priemernú chybu predikcie pooperačnej refrakcie (prediction error, PE) a jej priemernú absolútnu hodnotu (mean absolute error, MAE). Výsledky a záver: Neboli preukázané štatisticky významné rozdiely v PE a MAE v závislosti od jednotlivých vzorcov, typov umelých vnútroočných šošoviek, pohlavia, veku a laterality.
Purpose: To analyze refractive results after cataract surgery in relation to used type of monofocal intraocular lens, calculation formula, to age, gender and laterality. Settings: Department of Ophthalmology, Comenius University and University hospital in Bratislava, Slovakia Methods: We analyzed 173 eyes (118 patients) after uneventful cataract surgery. We calculated prediction error (PE) and mean absolute error (MAE) of postoperative refraction. Results and conclusion: We found no statistically significant differences in PE and MAE in relation to types of used IOL, calculation formulas, gender, age or laterality.
- Keywords
- optická biometrie, monofokální IOL, kalkulace IOL, pooperační refrakce,
- MeSH
- Biometry MeSH
- Adult MeSH
- Lens Implantation, Intraocular MeSH
- Data Interpretation, Statistical MeSH
- Cataract * therapy MeSH
- Middle Aged MeSH
- Humans MeSH
- Postoperative Period * MeSH
- Refraction, Ocular * MeSH
- Retrospective Studies MeSH
- Aged, 80 and over MeSH
- Aged MeSH
- Treatment Outcome MeSH
- Check Tag
- Adult MeSH
- Middle Aged MeSH
- Humans MeSH
- Male MeSH
- Aged, 80 and over MeSH
- Aged MeSH
- Female MeSH
Cílem práce bylo zkoumat vztah mezi zobecněnou entropií diskrétní náhodné veličiny (tzv. f-entropií, třídou funkcí, zahrnující řadu indexů používaných pří měření biodiverzity) a minimální Bayesovskou pravděpodobností chyby při odhadu hodnoty této náhodné veličiny. Zejména studovat těsnost jejich vztahu. Morales a Vajda [1] nedávno zavedli míru zvanou průměrná nepřesnost (average inaccuracy), která kvantifikuje těsnost vztahu mezi aposteriorní Bayesovskou pravděpodobností chyby a mocninnými entropiemi. Tato míra je definována jako normalizovaný průměrný rozdíl horní a dolní meze aposteriorní Bayesovské pravděpodobnosti chyby za dané entropie. Tuto míru je možno zobecnit na jakoukoli striktně konkávní f-entropii a použít ji k vyjádření těsnosti vztahu této f-entropie k aposteriorní Bayesovské pravděpodobnosti chyby. Získaný vztah je však většinou poměrně složitý a není možné snadno analyticky porovnat průměrné nepřesnosti různých f-entropií. Navrhujeme hladkou aproximaci dolní meze aposteriorní Bayesovské pravděpodobnosti chyby za dané f-entropie, jejíž použití zjednoduší formuli průměrné nepřesnosti. Ukázali jsme, že při použití této aproximace má kvadratická entropie nejtěsnější vztah k aposteriorní Bayesovské pravděpodobnosti chyby mezi f-entropiemi. Kvadratická entropie má těsnější vztah k Bayesovské pravděpodobnosti chyby (ve smyslu popsaném v článku) než Shannonova entropie a další funkce příslušící do třídy f-entropií, jako např. Emlenův index, Ferreriho index, Goodův index a další.
We deal with the relation between the generalized entropy (f-entropy, a family of functions that include several biodiversity measures) of a discrete random variable and the minimal probability of error (Bayes error) when the value of this random variable is estimated. Namely the tightness of their relation is studied. Morales and Vajda [1] recently introduced a measure called average inaccuracy that aims to quantify the tightness of the relation between the posterior Bayes error and the power entropies. It is defined as a standardized average difference between the upper and the lower bound for the posterior Bayes error under given entropy. Their concept can be generalized to any strictly concave f-entropy and used to evaluate its relation to the Bayes probability of error. However, due to a complex form of the formula of the average inaccuracy, it is difficult to compare the average inaccuracies of most f-entropies analytically. We propose a smooth approximation of the lower bound for the posterior Bayes error under given f-entropy that simplifies the formula of the average inaccuracy. We show that under this approximation, the quadratic entropy has the tightest relation to the posterior Bayes error among f-entropies. The quadratic entropy has the tightest relation to the posterior Bayes error (in the sense described in this paper) than the Shannon’s entropy and other functions that belong to the family of f-entropies, like Emlen’s index, Ferreri’s index and Good’s index.
Objective: A lack of acceptance has hindered the widespread adoption and implementation of clinical prediction rules (CPRs). The use of clinical decision support systems (CDSSs) has been advocated as one way of facilitating a broader dissemination and validation of CPRs. This requires computable models of clinical evidence based on open standards rather than closed proprietary content. Methods: The on-going TRANSFoRm project has developed ontological models of CPRs suitable for providing CPR based decision support.
- MeSH
- Acute Disease MeSH
- Algorithms * MeSH
- Appendicitis diagnosis MeSH
- Diagnosis, Computer-Assisted methods MeSH
- Diagnosis, Differential MeSH
- Humans MeSH
- Evidence-Based Medicine MeSH
- Decision Support Techniques * MeSH
- Software Design MeSH
- Primary Health Care MeSH
- Reproducibility of Results MeSH
- Decision Making MeSH
- Decision Support Systems, Clinical * MeSH
- Research Design MeSH
- Check Tag
- Humans MeSH
- Publication type
- Research Support, Non-U.S. Gov't MeSH
In the field of machine learning, building models and measuring their performance are two equally important tasks. Currently, measures of precision of regression models' predictions are usually based on the notion of mean error, where by error we mean a deviation of a prediction from an observation. However, these mean based measures of models' performance have two drawbacks. Firstly, they ignore the length of the prediction, which is crucial when dealing with chaotic systems, where a small deviation at the beginning grows exponentially with time. Secondly, these measures are not suitable in situations where a prediction is made for a specific point in time (e.g. a date), since they average all errors from the start of the prediction to its end. Therefore, the aim of this paper is to propose a new measure of models' prediction precision, a divergence exponent, based on the notion of the Lyapunov exponent which overcomes the aforementioned drawbacks. The proposed approach enables the measuring and comparison of models' prediction precision for time series with unequal length and a given target date in the framework of chaotic phenomena. Application of the divergence exponent to the evaluation of models' accuracy is demonstrated by two examples and then a set of selected predictions of COVID-19 spread from other studies is evaluated to show its potential.
OBJECTIVES: Compare overall Landing Error Scoring System (LESS) scores, risk categorisation, specific LESS errors, and double-leg jump-landing jump heights between overhead goal and no goal conditions. DESIGN: Randomised cross-over. SETTING: Laboratory. PARTICIPANTS: 76 (51% male). MAIN OUTCOME MEASURES: Participants landed from a 30-cm box to 50% of their body height and immediately jumped vertically for maximum height. Participants completed three trials under two random-ordered conditions: with and without overhead goal. Group-level mean LESS scores, risk categorisation (5-error threshold), specific landing errors, and jump heights were compared between conditions. RESULTS: Mean LESS scores were greater (0.3 errors, p < 0.001) with the overhead goal, but this small difference was not clinically meaningful. Similarly, although the number of high-risk participants was greater with the overhead goal (p = 0.039), the 9.2% difference was trivial. Participants jumped 2.7 cm higher with the overhead goal (p < 0.001) without affecting the occurrence of any specific LESS errors. DISCUSSION: Performing the LESS with an overhead goal enhances sport specificity and elicits greater vertical jump performances with minimal change in landing errors and injury-risk categorisation. Adding an overhead goal to LESS might enhance its suitability for injury risk screening, although the predictive value of LESS with an overhead goal needs confirmation.
- MeSH
- Cross-Over Studies MeSH
- Knee Joint MeSH
- Humans MeSH
- Movement MeSH
- Anterior Cruciate Ligament Injuries * MeSH
- Sports * MeSH
- Check Tag
- Humans MeSH
- Male MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- Randomized Controlled Trial MeSH
Our study aimed to establish the best prediction equation for different age ranges in estimating Glomerular Filtration Rate (GFR) in clinical practice in Slovakia. The GFR by 24-hour creatinine clearance (Ccr) and the estimated GFR (eGFR) using the Cockcroft-Gault (CG), the four-variable Modification of Diet in Renal Disease (MDRD4) and the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equations were obtained in adults aged 30-80 (n = 433, 10-years intervals). The correlation between these prediction equations and Ccr was evaluated. Errors in prediction equations were detected by moving average and by comparisons of the formulas for GFR < 1.5 ml/s and > 1.5 ml/s. The best correlations were established between Ccr and MDRD4 for women (r = 0.7790) and men (r = 0.8009), and between Ccr and CKD-EPI for women (r = 0.7780) and men (r = 0.8002) in the 60-69 age range. High correlation was also established between Ccr and CG (r = 0.8655) and MDRD4 (r = 0.8713) for men in the 40-49 age range. With the exception of the 30-40 age range, a low prediction error was observed for each age range in both genders when GFR was < 1.5 ml/s. We recommend utilization of the MDRD4 and CG equations for men (40-49 years) and MDRD4 and CKD-EPI for women and men (60-69 years), as preferred substitutes for Ccr.
- MeSH
- Renal Insufficiency, Chronic diagnosis physiopathology MeSH
- Adult MeSH
- Glomerular Filtration Rate physiology MeSH
- Creatinine blood urine MeSH
- Middle Aged MeSH
- Humans MeSH
- Predictive Value of Tests MeSH
- Aged MeSH
- Age Distribution MeSH
- Kidney Function Tests methods MeSH
- Check Tag
- Adult MeSH
- Middle Aged MeSH
- Humans MeSH
- Male MeSH
- Aged MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- Geographicals
- Slovakia MeSH
DNA conformation may deviate from the classical B-form in ∼13% of the human genome. Non-B DNA regulates many cellular processes; however, its effects on DNA polymerization speed and accuracy have not been investigated genome-wide. Such an inquiry is critical for understanding neurological diseases and cancer genome instability. Here, we present the first simultaneous examination of DNA polymerization kinetics and errors in the human genome sequenced with Single-Molecule Real-Time (SMRT) technology. We show that polymerization speed differs between non-B and B-DNA: It decelerates at G-quadruplexes and fluctuates periodically at disease-causing tandem repeats. Analyzing polymerization kinetics profiles, we predict and validate experimentally non-B DNA formation for a novel motif. We demonstrate that several non-B motifs affect sequencing errors (e.g., G-quadruplexes increase error rates), and that sequencing errors are positively associated with polymerase slowdown. Finally, we show that highly divergent G4 motifs have pronounced polymerization slowdown and high sequencing error rates, suggesting similar mechanisms for sequencing errors and germline mutations.
- MeSH
- DNA chemistry MeSH
- G-Quadruplexes MeSH
- Genomics * methods standards MeSH
- Kinetics MeSH
- Nucleic Acid Conformation * MeSH
- Humans MeSH
- Mutation MeSH
- Nucleotide Motifs MeSH
- DNA Replication MeSH
- Reproducibility of Results MeSH
- Sequence Analysis, DNA * methods MeSH
- High-Throughput Nucleotide Sequencing * methods standards MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
