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Dementia rates are projected to increase significantly by 2050, posing considerable challenges for healthcare systems worldwide. Developing efficient diagnostic tools is critical, and machine learning (ML) algorithms have shown potential for improving the accuracy of cognitive impairment classification. This study aims to address challenges in current systems by leveraging readily available electronic medical record (EMR) data to simplify and enhance the classification of cognitive impairment. The analysis includes 283 older adults, categorized into three groups: 144 individuals with mild cognitive impairment (MCI), 38 with dementia, and 101 healthy controls. Various ML techniques are evaluated to classify cognitive performance levels based on input features such as sociodemographic variables, lab results, comorbidities, Body Mass Index (BMI), and functional scales. Key predictors for distinguishing healthy controls from individuals with MCI are identified. These are history of myocardial infarction, vitamin D3 levels, the Instrumental Activities of Daily Living (IADL) scale, age, and sodium levels. The nonlinear Support Vector Machine (SVM) with a Radial Basis Function (RBF) kernel achieve the best performance for MCI classification, with an accuracy of 69%, an AUC of 0.75, and a Matthews Correlation Coefficient (MCC) of 0.43. For distinguishing healthy controls from those with dementia, the most influential factors include the IADL scale, the Activities of Daily Living (ADL) scale, education, vitamin D3 levels, and age. Here, the Random Forest algorithm demonstrates superior performance, achieving 84% accuracy, an AUC of 0.96, and an MCC of 0.71. These two models consistently outperform other ML techniques, such as K-Nearest Neighbors, Multi-Layer Perceptron, linear SVM, Naive Bayes, Quadratic Discriminant Analysis, Linear Discriminant Analysis, AdaBoost, and Gaussian Process Classifiers. The findings suggest that EMR data can be an effective resource for the initial classification of cognitive impairments. Integrating these ML-driven approaches into primary care settings may facilitate the early identification of older patients who could benefit from further cognitive assessments.

The large conductance voltage- and Ca 2+ -activated K + channels from the inner mitochondrial membrane (mitoBK) are modulated by a number of factors. Among them flavanones, including naringenin (Nar), arise as a promising group of mitoBK channel regulators from a pharmacological point of view. It is well known that in the presence of Nar the open state probability ( p op ) of mitoBK channels significantly increases. Nevertheless, the molecular mechanism of the mitoBK-Nar interactions remains still unrevealed. It is also not known whether the effects of naringenin administration on conformational dynamics can resemble those which are exerted by the other channel-activating stimuli. In aim to answer this question, we examine whether the dwell-time series of mitoBK channels which were obtained at different voltages and Nar concentrations (yet allowing to reach comparable p op s) are discernible by means of artificial intelligence methods, including k-NN and shapelet learning. The obtained results suggest that the structural complexity of the gating dynamics is shaped both by the interaction of channel gate with the voltage sensor (VSD) and the Nar-binding site. For a majority of data one can observe stimulus-specific patterns of channel gating. Shapelet algorithm allows to obtain better prediction accuracy in most cases. Probably, because it takes into account the complexity of local features of a given signal. About 30% of the analyzed time series do not sufficiently differ to unambiguously distinguish them from each other, which can be interpreted in terms of the existence of the common features of mitoBK channel gating regardless of the type of activating stimulus. There exist long-range mutual interactions between VSD and the Nar-coordination site that are responsible for higher levels of Nar-activation (Δ p op ) at deeply depolarized membranes. These intra-sensor interactions are anticipated to have an allosteric nature.

BackgroundIn infants and young children, a wide heterogeneity of foot shape is typical. Therefore, children, who are additionally influenced by rapid growth and maturation, are a very special cohort for foot measurements and the footwear industry. The importance of foot measurements for footwear fit, design, as well as clinical applications has been sufficiently described. New measurement techniques (3D foot scanning) allow the assessment of the individual foot shape. However, the validity in comparison to conventional methods remains unclear. Therefore, the purpose of this study was to compare 3D foot scanning with two established measurement methods (2D digital scanning/manual foot measurements).MethodsTwo hundred seventy seven children (125 m / 152 f; mean ± SD: 8.0 ± 1.5yrs; 130.2 ± 10.7cm; 28.0 ± 7.3kg) were included into the study. After collection of basic data (sex, age (yrs), body height (cm), body weight (kg)) geometry of the right foot was measured in static condition (stance) with three different measurement systems (fixed order): manual foot measurement, 2D foot scanning (2D desk scanner) and 3D foot scanning (hand-held 3D scanner). Main outcomes were foot length, foot width (projected; anatomical; instep), heel width and anatomical foot ball breadth. Analysis of variances for dependent samples was applied to test for differences between foot measurement methods (Post-hoc analysis: Tukey-Kramer-Test; α=0.05).ResultsSignificant differences were found for all outcome measures comparing the three methods (p<0.0001). The span of foot length differences ranged from 3 to 6mm with 2D scans showing the smallest and 3D scans the largest deviations. Foot width measurements in comparison of 3D and 2D scans showed consistently higher values for 3D measurements with the differences ranging from 1mm to 3mm.ConclusionsThe findings suggests that when comparing foot data, it is important to consider the differences caused by new measurement methods. Differences of about 0.6cm are relevant when measuring foot length, as this is the difference of a complete shoe size (Parisian point). Hence, correction factors may be required to compare the results of different measurements appropriately. The presented results may have relevance in the field of ergonomics (shoe industry) as well as clinical practice.

Accurate and reliable determination of the characteristic points of the impedance cardiogram (ICG) is an important research problem with a growing range of applications in the cardiological diagnostics of patients with heart failure (HF). The shapes of the characteristic waves of the ICG signal and the temporal location of the characteristic points B, C, and X provide significant diagnostic information. On this basis, essential diagnostic cardiological parameters can be determined, such as, e.g., cardiac output (CO) or stroke volume (SV). Although the importance of this problem is obvious, we face many challenges, including noisy signals and the big variability in the morphology, which altogether make the accurate identification of the characteristic points quite difficult. The paper presents an effective method of ICG points identification intended for conducting experimental research in the field of impedance cardiography. Its effectiveness is confirmed in clinical pilot studies.

The accurate detection of fiducial points in the impedance cardiography signal (ICG) has a decisive impact on the proper estimation of diagnostic parameters such as stroke volume or cardiac output. It is, therefore, necessary to find an algorithm that is able to assess their positions with great precision. The solution to this problem is, however, quite challenging with regard to the high sensitivity of the ICG technique to the noise and varying morphology of the acquired signals. The aim of this study is to propose a novel method that allows us to overcome these limitations. The developed algorithm is based on Empirical Mode Decomposition (EMD)—an effective technique for processing and analyzing various types of non-stationary signals. We find high correlations between the results obtained from the algorithm and annotated by an expert. This, in turn, implies that the difference in estimation of the diagnostic-relevant parameters is small, which suggests that the method can automatically provide precise clinical information.

We study contextuality of the three neutrinos oscillations using the Klyachko-Can-Binicioglu-Shumovsky 5-observable test. We show how the interaction between neutrinos and normal matter affects contextuality-its loss and its possible revivals. We show that for open neutrino's system, interacting with an environment, revivals of contextuality survive in a presence of decoherence included in the neutrino's Lindblad-Kossakowski master equation in a simplest Markovian approximation.

Even the subtle and apparently strange quantum effects can sometimes survive otherwise lethal influence of an omnipresent decoherence. We show that an archetypal quantum Cheshire Cat, a paradox of a separation between a position of a quantum particle, a photon, and its internal property, the polarization, in a two-path Mach–Zehnder setting, is robust to decoherence caused by a bosonic infinite bath locally coupled to the polarization of a photon. Decoherence affects either the cat or its grin depending on which of the two paths is noisy. For a pure decoherence, in an absence of photon–environment energy exchange, we provide exact results for weak values of the photon position and polarization indicating that the information loss affects the quantum Cheshire Cat only qualitatively and the paradox survives. We show that it is also the case beyond the pure decoherence for a small rate of dissipation.

The simple model of an ionic current flowing through a single channel in a biological membrane is used to depict the complexity of the corresponding empirical data underlying different internal constraints and thermal fluctuations. The residence times of the channel in the open and closed states are drawn from the exponential distributions to mimic the characteristics of the real channel system. In the selected state, the dynamics are modeled by the overdamped Brownian particle moving in the quadratic potential. The simulated data allow us to directly track the effects of temperature (signal-to-noise ratio) and the channel’s energetic landscape for conformational changes on the ionic currents’ complexity, which are hardly controllable in the experimental case. To accurately describe the randomness, we employed four quantifiers, i.e., Shannon, spectral, sample, and slope entropies. We have found that the Shannon entropy predicts the anticipated reaction to the imposed modification of randomness by raising the temperature (an increase of entropy) or strengthening the localization (reduction of entropy). Other complexity quantifiers behave unpredictably, sometimes resulting in non-monotonic behaviour. Thus, their applicability in the analysis of the experimental time series of single-channel currents can be limited.

Stroke is the leading cause of acquired disability in western societies. (Motor) cognitive deficits like apraxia significantly contribute to disability after stroke, harming activities of daily living and rehabilitation outcome. To date, efficient therapeutic options for apraxia remain sparse. Thus, randomized controlled trials (RCTs) are warranted. Based on promising results of a pilot study, the on-going RAdiCS ( ehabilitating stroke-induced praxia with rect urrent timulation) study is a randomized controlled trial, which follows a double-blinded (investigator and patient), two-arm parallel interventional model. It is designed to include 110 apraxic patients (as diagnosed by the Cologne Apraxia Screening, KAS) in the subacute phase after a left hemisphere (LH) stroke. The University of Cologne initiated the trial, which is conducted in two German Neurorehabilitation Centers.The study aims to evaluate the effect of anodal (versus sham) transcranial direct current stimulation (tDCS) applied over the left posterior parietal cortex (PPC) with an intensity of 2 mA for 10 min on five consecutive days on apraxic deficits. In addition to anodal or sham tDCS, all LH stroke patients undergo a motor (cognitive) training that is performed before and after the stimulation (off-line stimulation).The primary outcome measure is the (differential) change in the overall KAS score after five daily sessions of anodal versus sham tDCS when compared to the baseline assessment before tDCS. Secondary study outcomes include further apraxia scores, aphasia severity, and measures of motor performance and disability after stroke. All outcome measures are obtained in the post-stimulation assessment as well as during follow-up (3-4 months after tDCS). The RCT RAdiCS shall evaluate in a large number of LH stroke patients whether anodal tDCS (compared to sham tDCS) expedites the rehabilitation of apraxia - over and above additional motor (cognitive) training and standard care. A positive study outcome would provide a new strategy for the treatment of apraxia, which hopefully ameliorates the negative impact of apraxia on daily living and long-term outcome. Clinical Trials Gov: NCT03185234, registered 14 June 2017 ; Deutsches Register für Klinische Studien: DRKS00012292, registered 01 June 2017. Participant enrollment began on 22 June 2017. The trial is expected to be completed on 30 June 2022.

ZusammenfassungDas Therapie-Zentrum für Suizidgefährdete (TZS) am Universitätsklinikum Hamburg-Eppendorf wurde 1990 gegründet. Das Ziel des Projektes war, eine ambulante psychotherapeutische Behandlung für akut und chronisch suizidale Patienten ausschließlich auf psychoanalytischer/psychodynamischer Grundlage zu ermöglichen, wissenschaftlich zu begleiten und zu evaluieren. Der Beitrag beschreibt die Entwicklung des TZS, seine theoretischen und praktischen Arbeiten zum Verständnis der Suizidalität und deren Behandlung sowie seine weiteren nachhaltigen Aktivitäten in Forschung, Aus‑, Fort- und Weiterbildung, Medien- und Öffentlichkeitsarbeit und allgemein der Suizidprävention.