Piotr Słowiński

This study developed an ultrasound prediction equation for measuring fat fraction in lower limb muscles of healthy middle‐aged and young participants and applied it in a randomised controlled trial (RCT) to assess the relationship between fat fraction and strength in exercising and non‐exercising females. Twenty‐eight participants were recruited into 50 years (8m, 5f, age 60.4 ± 5.7 years, BMI 24.8 ± 3.6 kg m ⁻² ) groups. T1‐weighted magnetic resonance imaging (MRI)‐Dixon fat fraction in gastrocnemius medialis (GM) and vastus lateralis (VL) and ¹ H‐magnetic resonance spectroscopy for intramyocellular (IMCL) and extramyocellular (EMCL) lipid content in GM was used to validate ultrasound measures of muscle, subcutaneous fat thickness (SFT) and echointensity to generate a multivariable model of fat infiltration. For the RCT, 72 females aged 40–60 years were recruited to either a low impact resistance exercise (4–5 sessions/week for 12 weeks) or a control group, and muscle strength was tested using isokinetic dynamometry. Multiple linear regression models for ultrasound measurement of fat fraction were validated for GM ( r ² = 0.71) and VL ( r ² = 0.91). SFT was the dominant variable in the older group in GM (77%) and VL (92%), but of near equal proportion, with echointensity, in GM (52%) and VL (51%) in the younger group. Strength was negatively correlated with fat fraction ( r = −0.44). Strength increased in the exercising group, but fat fraction remained unchanged. A multivariable model using ultrasound measurements of SFT, muscle thickness, echointensity and age demonstrates that ultrasound is capable of predicting lower limb muscle fat infiltration.

Auditory stream segregation plays a crucial role in understanding the auditory scene. This study investigates the role of tactile stimulation in auditory stream segregation through psychophysics experiments and a computational model of audio-tactile interactions. We examine how tactile pulses, synchronized with specific tones in a sequence of interleaved high- and low-frequency tones (ABA-triplets), influence the likelihood of perceiving integrated or segregated auditory streams. Our findings reveal that tactile pulses synchronized with specific tones enhance perceptual segregation, while pulses synchronized with both tones promote integration. Based on these findings, we developed a dynamical model that captures interactions between auditory and tactile neural circuits, including recurrent excitation, mutual inhibition, adaptation, and noise. The proposed model shows excellent agreement with the experiment. Model predictions are validated through psychophysics experiments. In the model, we assume that selective tactile stimulation dynamically modulates the tonotopic organization within the auditory cortex. This modulation facilitates segregation by reinforcing specific tonotopic responses through single-tone synchronization while smoothing neural activity patterns with dual-tone alignment to promote integration. The model offers a robust computational framework for exploring cross-modal effects on stream segregation and predicts neural behaviour under varying tactile conditions. Our findings imply that cross-modal synchronization, with carefully timed tactile cues, could improve auditory perception with potential applications in auditory assistive technologies aimed at enhancing speech recognition in noisy settings.

Timely interventions have a proven benefit for people experiencing psychotic illness. One bottleneck to accessing timely interventions is the referral process to the specialist team for early psychosis (STEP). Many general practitioners lack awareness or confidence in recognising psychotic symptoms or state. Additionally, referrals for people without apparent psychotic symptoms, although beneficial at a population level, lead to excessive workload for STEPs. There is a clear unmet need for accurate stratification of STEPs users and healthy cohorts. Here we propose a new approach to addressing this need via the application of digital behavioural tests. To demonstrate that digital behavioural tests can be used to discriminate between the STEPs users (SU; n = 32) and controls (n = 32, age and sex matched), we compared performance of five different classifiers applied to objective, quantitative and interpretable features derived from the ‘mirror game’ (MG) and trail making task (TMT). The MG is a movement coordination task shown to be a potential socio-motor biomarker of schizophrenia, while TMT is a neuropsychiatric test of cognitive function. All classifiers had AUC in the range of 0.84–0.92. The best of the five classifiers (linear discriminant classifier) achieved an outstanding performance, AUC = 0.92 (95%CI 0.75–1), Sensitivity = 0.75 (95%CI 0.5–1), Specificity = 1 (95%CI 0.75–1), evaluated on 25% hold-out and 1000 folds. Performance of all analysed classifiers is underpinned by the large effect sizes of the differences between the cohorts in terms of the features used for classification what ensures generalisability of the results. We also found that MG and TMT are unsuitable in isolation to successfully differentiate between SU with and without at-risk-mental-state or first episode psychosis with sufficient level of performance. Our findings show that standardised batteries of digital behavioural tests could benefit both clinical and research practice. Including digital behavioural tests into healthcare practice could allow precise phenotyping and stratification of the highly heterogenous population of people referred to STEPs resulting in quicker and more personalised diagnosis. Moreover, the high specificity of digital behavioural tests could facilitate the identification of more homogeneous clinical high-risk populations, benefiting research on prognostic instruments for psychosis. In summary, our study demonstrates that cheap off-the-shelf equipment (laptop computer and a leap motion sensor) can be used to record clinically relevant behavioural data that could be utilised in digital mental health applications.

Nitric oxide (NO) produced by nitric-oxide synthase (NOS) is a key regulator of animal physiology. Here we uncover a function for NO in the integration of UV exposure and the gating of a UV-avoidance circuit. We studied UV/violet avoidance mediated by brain ciliary photoreceptors (cPRCs) in larvae of the annelid Platynereis dumerilii . In the larva, NOS is expressed in interneurons (INNOS) postsynaptic to cPRCs. UV stimulation of cPRCs triggers INNOS activation and NO production. NO signals retrogradely to cPRCs to induce their sustained post-stimulus activation through an unconventional guanylate cyclase. This late activation drives ciliary beating through serotonergic ciliomotor neurons during UV avoidance. In NOS mutants, retrograde signalling, ciliary activation and UV avoidance are defective. By mathematical modelling, we recapitulate phototransduction and circuit dynamics in wild-type and mutant larvae. Our results reveal how NO-mediated retrograde signalling gates a synaptic circuit and induces short-term memory of UV exposure to orchestrate light-avoidance behaviour.

Background Timely interventions have a proven benefit for people experiencing psychotic illness. One bottleneck to accessing timely interventions is the referral process to the specialist team for early psychosis (STEP). Many general practitioners lack awareness or confidence in recognising psychotic symptoms or state. Additionally, referrals for people without apparent psychotic symptoms, although beneficial at a population level, lead to excessive workload for STEPs. There is a clear unmet need for accurate stratification of STEPs users and healthy cohorts that this study aimed to investigate by applying digital behavioural tests. Methods To discriminate between the STEPs users (SU; n=32) and controls (n=32, age and sex matched), we employed naïve Bayes classifier, and applied it to objective, quantitative and interpretable features of a ‘mirror game’ (MG) and trail making task (TMT). The MG is a movement coordination task shown to be a potential socio-motor biomarker of schizophrenia, while TMT is a neuropsychiatric test of cognitive function. Findings The proposed classifier shows an excellent performance, AUC = 0.92 (95%CI 0.75-1), Sensitivity = 0.88 (95%CI 0.62-1), Specificity = 1 (95%CI 0.75-1), evaluated on 25% hold-out and 1000 folds. The study demonstrates that cheap off-the-shelf equipment (laptop computer and a leap motion sensor) records clinically relevant behavioural data sufficiently. We also find that MG and TMT are unsuitable in isolation to successfully differentiate between SU with and without at-risk-mental-state or first episode psychosis with sufficient level of performance. Interpretation Including digital behavioural tests into healthcare practice could allow improvements in care for people at risk of developing psychotic illness. Our findings show that introduction of standardised battery of digital behavioural tests would benefit both clinical and research practice. It would allow standardization of referrals, while the high specificity of digital behavioural tests would benefit research on prognostic instruments for psychosis by enriching and homogenising clinical high-risk populations. Here we demonstrate that digital behavioural tests can be successfully used and could help to address this need. Funding EPSRC Impact Acceleration Account, Impact & Knowledge Exchange Award, Jean Golding Institute seed corn, Avon & Wiltshire Mental Health Partnership NHS Trust Research Capability Funding. PS was generously supported by the Wellcome Trust Institutional Strategic Support Award 204909/Z/16/Z. KTA gratefully acknowledges the financial support of the EPSRC via grant EP/T017856/1. Evidence before this study We searched PubMed (without any date or language restrictions) for articles published up to 11 January 2023 that contained following combinations of terms: (psychosis OR schizophrenia) AND (motor coordination) 396 publications; (psychosis OR schizophrenia) AND (trail making task) 93; (psychosis OR schizophrenia) AND (mirror game) 3 publications; (psychosis OR schizophrenia) AND (digital tests battery) 13. The large number of publications related to the first search is due to well-known association of motor abnormalities (that include deficits in motor coordination) with psychosis and schizophrenia. Similarly, trail making task (TMT) is a well-established instrument for assessment of cognitive function, with performance worsened in psychosis and schizophrenia. Of interest are two recent publications, a meta-analysis showing that performance in TMT differs in clinical high-risk population between people who did and did not transition to psychosis and a longitudinal study showing that deficits in motor coordination could help predict the long-term severity of psychosis. The search including mirror game (MG) returned our own work demonstrating that MG could be used as a base for socio-motor biomarkers in schizophrenia; proposed socio-motor biomarkers include measures based on motor coordination. Search for digital test returned two studies of interest on using digital/ web-based test to assess cognitive function in schizophrenia. One study showed that some digital/ web-based test are affected by practice effects. The other showed that web-based battery of tests had low performance in terms of discriminating between schizophrenia patients and healthy controls (AUROC > 0.70). Added value of this study This study demonstrates that combining digital tests with data analytics has potential for simplifying neuropsychiatric assessment. It shows that using measurements from TMT and MG allows to differentiate between people accepted for assessment in specialist team for early psychosis (STEP) and controls with excellent performance (AUROC > 0.9), while achieving 100% specificity (no false positive detections). The study shows feasibility of using cheap, portable equipment, assembled from off-the-shelf components, for collection of clinically relevant data that could be used to inform clinical decision making. Implications of all the available evidence Our study, with its state-of-the-art performance and interpretable results, demonstrate high clinical potential of implementing digital batteries of behavioural tests in clinical practice. Future work should focus on identification of optimal set of tests for establishing standardised digital batteries of behavioural tests as well as on longitudinal studies to understand how socio-motor function changes in the course of psychosis. Such developments would not only help to stratify STEPs users but would facilitate rapid assessment for all people seeking care in mental health early intervention services improving their quality of life and wellbeing.

We study an individual’s propensity for rational thinking; the avoidance of cognitive biases (unconscious errors generated by our mental simplification methods) using a novel augmented reality (AR) platform. Specifically, we developed an odd-one-out (OOO) game-like task in AR designed to try to induce and assess confirmatory biases. Forty students completed the AR task in the laboratory, and the short form of the comprehensive assessment of rational thinking (CART) online via the Qualtrics platform. We demonstrate that behavioural markers (based on eye, hand and head movements) can be associated (linear regression) with the short CART score – more rational thinkers have slower head and hand movements and faster gaze movements in the second more ambiguous round of the OOO task. Furthermore, short CART scores can be associated with the change in behaviour between two rounds of the OOO task (one less and one more ambiguous) – hand-eye-head coordination patterns of the more rational thinkers are more consistent in the two rounds. Overall, we demonstrate the benefits of augmenting eye-tracking recordings with additional data modalities when trying to understand complicated behaviours.

We study an individual’s propensity for rational thinking; the avoidance of cognitive biases (unconscious errors generated by our mental simplification methods) using a novel augmented reality (AR) platform. Specifically, we developed an odd-one-out game-like task in AR designed to try to induce and assess confirmatory biases. Forty students completed the AR task in the laboratory, and the short form of the comprehensive assessment of rational thinking (CART) online via the Qualtrics platform. We used distance correlation approaches and stepwise regression to identify objective markers (based on eye, hand and head movements) associated with the psychometric measures of propensity for rational thinking. We show that the proposed markers are associated with the short CART score – more rational thinkers have slower head and hand movements, faster gaze movements and more consistent hand-eye-head coordination patterns across conditions.

Clinical classification is essential for estimating disease prevalence but is difficult, often requiring complex investigations. The widespread availability of population level genetic data makes novel genetic stratification techniques a highly attractive alternative. We propose a generalizable mathematical framework for determining disease prevalence within a cohort using genetic risk scores. We compare and evaluate methods based on the means of genetic risk scores’ distributions; the Earth Mover’s Distance between distributions; a linear combination of kernel density estimates of distributions; and an Excess method. We demonstrate the performance of genetic stratification to produce robust prevalence estimates. Specifically, we show that robust estimates of prevalence are still possible even with rarer diseases, smaller cohort sizes and less discriminative genetic risk scores, highlighting the general utility of these approaches. Genetic stratification techniques offer exciting new research tools, enabling unbiased insights into disease prevalence and clinical characteristics unhampered by clinical classification criteria.

Variant allele frequencies (VAF) are an important measure of genetic variation that can be estimated at single-nucleotide variant (SNV) sites. RNA and DNA VAFs are used as indicators of a wide-range of biological traits, including tumor purity and ploidy changes, allele-specific expression and gene-dosage transcriptional response. Here we present a novel methodology to assess gene and chromosomal allele asymmetries and to aid in identifying genomic alterations in RNA and DNA datasets. Our approach is based on analysis of the VAF distributions in chromosomal segments (continuous multi-SNV genomic regions). In each segment we estimate variant probability, a parameter of a random process that can generate synthetic VAF samples that closely resemble the observed data. We show that variant probability is a biologically interpretable quantitative descriptor of the VAF distribution in chromosomal segments which is consistent with other approaches. To this end, we apply the proposed methodology on data from 72 samples obtained from patients with breast invasive carcinoma (BRCA) from The Cancer Genome Atlas (TCGA). We compare DNA and RNA VAF distributions from matched RNA and whole exome sequencing (WES) datasets and find that both genomic signals give very similar segmentation and estimated variant probability profiles. We also find a correlation between variant probability with copy number alterations (CNA). Finally, to demonstrate a practical application of variant probabilities, we use them to estimate tumor purity. Tumor purity estimates based on variant probabilities demonstrate good concordance with other approaches (Pearson's correlation between 0.44 and 0.76). Our evaluation suggests that variant probabilities can serve as a dependable descriptor of VAF distribution, further enabling the statistical comparison of matched DNA and RNA datasets. Finally, they provide conceptual and mechanistic insights into relations between structure of VAF distributions and genetic events. The methodology is implemented in a Matlab toolbox that provides a suite of functions for analysis, statistical assessment and visualization of Genome and Transcriptome allele frequencies distributions. GeTallele is available at: https://github.com/SlowinskiPiotr/GeTallele.

Recently, pioneering eQTLs studies on single cell RNA-seq (scRNA-seq) data have revealed new and cell-specific regulatory SNVs. Because eQTLs correlate genotypes and gene expression across multiple individuals, they are confined to SNVs with sufficient population frequency. Here, we present an alternative sc-eQTL approach – scReQTL - wherein we substitute the genotypes with expressed Variant Allele Fraction (VAF _RNA ) at heterozygous SNV sites. Our approach employs the advantage that, when estimated from multiple cells, VAF _RNA can be used to assess effects of rare SNVs in a single individual. ScReQTLs are enriched in known genetic interactions, therefore can be used to identify novel regulatory SNVs.