Search

Abstract Foraminifera are single-celled protists which are important mediators of the marine carbon cycle. In our study, we explored the potential impact of polystyrene (PS) microplastic particles on two symbiont-bearing large benthic foraminifera species—Heterostegina depressa and Amphistegina lobifera—over a period of three weeks, employing three different approaches: investigating (1) stable isotope (SI) incorporation—via 13C- and 15N-labelled substrates—of the foraminifera to assess their metabolic activity, (2) photosynthetic efficiency of the symbiotic diatoms using imaging PAM fluorometry, and (3) microscopic enumeration of accumulation of PS microplastic particles inside the foraminiferal test. The active feeder A. lobifera incorporated significantly more PS particles inside the cytoplasm than the non-feeding H. depressa, the latter accumulating the beads on the test surface. Photosynthetic area of the symbionts tended to decrease in the presence of microplastic particles in both species, suggesting that the foraminiferal host cells started to digest their diatom symbionts. Compared to the control, the presence of microplastic particles lead to reduced SI uptake in A. lobifera, which indicates inhibition of inorganic carbon and nitrogen assimilation. Competition for particulate food uptake was demonstrated between algae and microplastic particles of similar size. Based on our results, both species seem to be sensitive to microplastic pollution, with non-feeding H. depressa being more strongly affected.

Abstract Modeling the functionality of the human brain is a major goal in neuroscience for which many powerful methodologies have been developed over the last decade. The impact of working memory and the associated brain regions on the brain dynamics is of particular interest due to their connection with many functions and malfunctions in the brain. In this context, the concept of brain flexibility has been developed for the characterization of brain functionality. We discuss emergence of brain flexibility that is commonly measured by the identification of changes in the cluster structure of co-active brain regions. We provide evidence that brain flexibility can be modeled by a system of coupled FitzHugh-Nagumo oscillators where the network structure is obtained from human brain Diffusion Tensor Imaging (DTI). Additionally, we propose a straightforward and computationally efficient alternative macroscopic measure, which is derived from the Pearson distance of functional brain matrices. This metric exhibits similarities to the established patterns of brain template flexibility that have been observed in prior investigations. Furthermore, we explore the significance of the brain’s network structure and the strength of connections between network nodes or brain regions associated with working memory in the observation of patterns in networks flexibility. This work enriches our understanding of the interplay between the structure and function of dynamic brain networks and proposes a modeling strategy to study brain flexibility.

Abstract Floodlight Open was a global, open-access, digital-only study designed to understand the drivers and barriers in deployment and use of a smartphone app in a naturalistic setting and broad study population of people with and without multiple sclerosis (MS). The study utilised the Floodlight Open app: a ‘bring-your-own-device’ solution that remotely measures a user’s mood, cognition, hand motor function, and gait and postural stability via smartphone sensor-based tests requiring active user input (‘active tests’). Levels of mobility of study participants (‘life-space measurement’) were passively measured. Study data from these tests were made available via an open-access platform. Data from 1350 participants with self-declared MS and 1133 participants with self-declared non-MS from 17 countries across four continents were included in this report. Overall, MS participants provided active test data for a mean duration of 5.6 weeks or a mean duration of 19 non-consecutive days. This duration increased among MS participants who persisted beyond the first week to a mean of 10.3 weeks or 36.5 non-consecutive days. Passively collected life-space measurement data were generated by MS participants for a mean duration of 9.8 weeks or 50.6 non-consecutive days. This duration increased to 16.3 weeks/85.1 non-consecutive days among MS participants who persisted beyond the first week. Older age, self-declared MS disease status, and clinical supervision as part of concomitant clinical research were all significantly associated with higher persistence of the use of the Floodlight Open app. MS participants performed significantly worse than non-MS participants on four out of seven active tests. The findings from this multinational study inform future research to improve the dynamics of persistence of use of digital monitoring tools and further highlight challenges and opportunities in applying them to support MS clinical care.

Abstract Challenges in social communication is one of the core symptom domains in autism spectrum disorder (ASD). Novel therapies are under development to help individuals with these challenges, however the ability to show a benefit is dependent on a sensitive and reliable measure of treatment effect. Currently, measuring these deficits requires the use of time-consuming and subjective techniques. Objective measures extracted from natural conversations could be more ecologically relevant, and administered more frequently—perhaps giving them added sensitivity to change. While several studies have used automated analysis methods to study autistic speech, they require manual transcriptions. In order to bypass this time-consuming process, an automated speaker diarization algorithm must first be applied. In this paper, we are testing whether a speaker diarization algorithm can be applied to natural conversations between autistic individuals and their conversational partner in a natural setting at home over the course of a clinical trial. We calculated the average duration that a participant would speak for within their turn. We found a significant correlation between this feature and the Vineland Adaptive Behaviour Scales (VABS) expressive communication score (r = 0.51, p = 7 × 10–5). Our results show that natural conversations can be used to obtain measures of talkativeness, and that this measure can be derived automatically, thus showing the promise of objectively evaluating communication challenges in ASD.

Abstract We studied metabolic activity of the symbiont-bearing large benthic foraminifer Heterostegina depressa under different light conditions. Besides the overall photosynthetic performance of the photosymbionts estimated by means of variable fluorescence, the isotope uptake (13C and 15N) of the specimens (= holobionts) was measured. Heterostegina depressa was either incubated in darkness over a period of 15 days or exposed to an 16:8 h light:dark cycle mimicking natural light conditions. We found photosynthetic performance to be highly related to light supply. The photosymbionts, however, survived prolonged darkness and could be reactivated after 15 days of darkness. The same pattern was found in the isotope uptake of the holobionts. Based on these results, we propose that 13C-carbonate and 15N-nitrate assimilation is mainly controlled by the photosymbionts, whereas 15N-ammonium and 13C-glucose utilization is regulated by both, the symbiont and the host cells.

Abstract In efforts to reduce greenhouse gas emissions, renewable energies have been increasingly leveraged to generate power; in particular, the number of wind turbines has risen sharply in recent years and continues to grow. However, being mechanically coupled to the earth, wind turbines also generate ground vibrations, which can have adverse effects on the capability of seismic observatories to detect and analyse earthquakes; nevertheless, the distances at which these signals modulate seismic records are disputed between the operators of wind farms and seismic observatories. Here, to quantify the noise signal amplitudes at distant seismometers, we develop the first numerical model to predict the seismic wavefield emitted by wind farms and simulate the complex effects of wavefield interferences, surface topography and attenuation. This modelling approach can reliably quantify the influences of multiple wind turbines on ground motion recordings and thus provide necessary information to aid decision-making in advance of wind farm installation.

Abstract Digital health technologies enable remote and therefore frequent measurement of motor signs, potentially providing reliable and valid estimates of motor sign severity and progression in Parkinson’s disease (PD). The Roche PD Mobile Application v2 was developed to measure bradykinesia, bradyphrenia and speech, tremor, gait and balance. It comprises 10 smartphone active tests (with ½ tests administered daily), as well as daily passive monitoring via a smartphone and smartwatch. It was studied in 316 early-stage PD participants who performed daily active tests at home then carried a smartphone and wore a smartwatch throughout the day for passive monitoring (study NCT03100149). Here, we report baseline data. Adherence was excellent (96.29%). All pre-specified sensor features exhibited good-to-excellent test–retest reliability (median intraclass correlation coefficient = 0.9), and correlated with corresponding Movement Disorder Society–Unified Parkinson's Disease Rating Scale items (rho: 0.12–0.71). These findings demonstrate the preliminary reliability and validity of remote at-home quantification of motor sign severity with the Roche PD Mobile Application v2 in individuals with early PD.

Abstract Foraminifera are abundant unicellular organisms that play an important role in marine element cycles. A large benthic foraminifer obligatory bearing photosymbionts is Heterostegina depressa. We studied potential impacts of sunscreens available on the market on the activity of photosymbionts on H. depressa by means of pulse-amplitude modulated (PAM) fluorescence microscopy. We included four different sunscreens, with two of them sold as “conventional” and two more stated as “eco-friendly”. Further, the impact of pure Ensulizole (phenylbenzimidazole sulfonic acid) was tested, which is a common agent of sunscreens. Foraminifera were incubated at varying concentrations (10, 50 and 200 mgL−1) of different sunscreens and the pure Ensulizole for 14 days. The photosynthetic performance was measured after 1,3, 7 and 14 days. Pure Ensulizole had a strong negative impact on the photobionts, which was reflected by a significant reduction of the areal fluorescence signal. “Eco-friendly” sunscreens affected the health of foraminifera more severely compared to “conventional” ones. We assume that metal nanoparticles like titanium dioxide or zinc oxide of “eco-friendly” sunscreens are causing this impact, because these substances were already classified as toxic for several microorganisms.

Abstract Multimorbidity is more than just the addition of individual illnesses, and its diagnosis and treatment poses special problems. General practitioners play an important role in looking after multimorbid patients. The aim of this study is to assess the prevalence and pattern of acute and chronic multimorbidity in primary care patients, regardless of body system and age group. A convenience sample of 2099 patients treated by 40 general practitioners was assessed using the Burvill scale. This measure of multimorbidity differentiates according to organ system and covers both acute and chronic illnesses. It also allows severity ratings to be assessed for both acute and chronic conditions, and thus patients’ actual need for general practice care. Patients reported an average of 3.5 (SD = 2.0) acute and/or chronically affected body systems. Overall, 12.7% of patients reported only one health problem, 83.0% at least two, 65.8% at least three, 46.1% at least four, and 29.7% five or more. The most frequent problems were musculoskeletal (62.5%) and psychological (56.6%). Some morbidities were interrelated, while others co-occurred despite being medically independent. In primary care, multimorbidity is the rule rather than the exception. Acute and chronic morbidity both contribute to the burden of illness. Body systems reflect treatment needs. Instead of specialist treatment for individual illnesses, an integrative treatment approach is needed. This is the specialty of general practitioners.

Abstract The emergence of digital technologies such as smartphones in healthcare applications have demonstrated the possibility of developing rich, continuous, and objective measures of multiple sclerosis (MS) disability that can be administered remotely and out-of-clinic. Deep Convolutional Neural Networks (DCNN) may capture a richer representation of healthy and MS-related ambulatory characteristics from the raw smartphone-based inertial sensor data than standard feature-based methodologies. To overcome the typical limitations associated with remotely generated health data, such as low subject numbers, sparsity, and heterogeneous data, a transfer learning (TL) model from similar large open-source datasets was proposed. Our TL framework leveraged the ambulatory information learned on human activity recognition (HAR) tasks collected from wearable smartphone sensor data. It was demonstrated that fine-tuning TL DCNN HAR models towards MS disease recognition tasks outperformed previous Support Vector Machine (SVM) feature-based methods, as well as DCNN models trained end-to-end, by upwards of 8–15%. A lack of transparency of “black-box” deep networks remains one of the largest stumbling blocks to the wider acceptance of deep learning for clinical applications. Ensuing work therefore aimed to visualise DCNN decisions attributed by relevance heatmaps using Layer-Wise Relevance Propagation (LRP). Through the LRP framework, the patterns captured from smartphone-based inertial sensor data that were reflective of those who are healthy versus people with MS (PwMS) could begin to be established and understood. Interpretations suggested that cadence-based measures, gait speed, and ambulation-related signal perturbations were distinct characteristics that distinguished MS disability from healthy participants. Robust and interpretable outcomes, generated from high-frequency out-of-clinic assessments, could greatly augment the current in-clinic assessment picture for PwMS, to inform better disease management techniques, and enable the development of better therapeutic interventions.

Abstract Minimum toe clearance (MTC) occurs during a highly dynamic phase of the gait cycle and is associated with the highest risk of unintentional contact with obstacles or the ground. Age, cognitive function, attention and visual feedback affect foot clearance but how these factors interact to influence MTC control is not fully understood. We measured MTC in 121 healthy individuals aged 20–80 under four treadmill walking conditions; normal walking, lower visual field restriction and two Stroop colour/word naming tasks of two difficulty levels. Competition for cognitive and attentional resources from the Stroop task resulted in significantly lower mean MTC in older adults, with the difficult Stroop task associated with a higher frequency of extremely low MTC values and subsequently an increased modelled probability of tripping in this group. While older adults responded to visual restriction by markedly skewing MTC distributions towards higher values, this condition was also associated with frequent, extremely low MTC values. We reveal task-specific, age-dependent patterns of MTC control in healthy adults. Age-related differences are most pronounced during heavy, distracting cognitive load. Analysis of critically-low MTC values during dual-task walking may have utility in the evaluation of locomotor control and fall risk in older adults and patients with motor control deficits.

Abstract Bdellovibrio bacteriovorus is an obligate predator of bacteria that grows and divides within the periplasm of its prey. Functions involved in the early steps of predation have been identified and characterized, but mediators of prey invasion are still poorly detailed. By combining omics data available for Bdellovibrio and like organisms (BALO’s), we identified 43 genes expressed in B. bacteriovorus during the early interaction with prey. These included genes in a tight adherence (TAD) operon encoding for two type IVb fimbriae-like pilin proteins (flp1 and flp2), and their processing and export machinery. Two additional flp genes (flp3 and flp4) were computationally identified at other locations along the chromosome, defining the largest and most diverse type IVb complement known in bacteria to date. Only flp1, flp2 and flp4 were expressed; their respective gene knock-outs resulted in a complete loss of the predatory ability without losing the ability to adhere to prey cells. Additionally, we further demonstrate differential regulation of the flp genes as the TAD operon of BALOs with different predatory strategies is controlled by a flagellar sigma factor FliA, while flp4 is not. Finally, we show that FliA, a known flagellar transcriptional regulator in other bacteria, is an essential Bdellovibrio gene.