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Study Objectives: While various wearable EEG devices have been developed, performance evaluation of the devices and their associated automated sleep stage classification models is mostly limited to healthy subjects. A major barrier for applying automated wearable EEG sleep staging in clinical populations is the need for large-scale data for model training. We therefore investigated transfer learning as strategy to overcome limited data availability and optimize automated single-channel EEG sleep staging in people with sleep disorders., Methods: We acquired 52 single-channel frontopolar headband EEG recordings from a heterogeneous sleep-disordered population with concurrent PSG. We compared three model training strategies: 'pre-training' (i.e., training on a larger dataset of 901 conventional PSGs), 'training-from-scratch' (i.e., training on wearable headband recordings), and 'fine-tuning' (i.e., training on conventional PSGs, followed by training on headband recordings). Performance was evaluated on all headband recordings using 10-fold cross-validation., Results: Highest performance for 5-stage classification was achieved with fine-tuning (κ = .778), significantly higher than with pre-training (κ = .769) and with training-from-scratch (κ = .733). No significant differences or systematic biases were observed with clinically relevant sleep parameters derived from PSG. All sleep disorder categories showed comparable performance., Conclusions: This study emphasizes the importance of leveraging larger available datasets through deep transfer learning to optimize performance with limited data availability. Findings indicate strong similarity in data characteristics between conventional PSG and headband recordings. Altogether, results suggest the combination of the headband, classification model, and training methodology can be viable for sleep monitoring in the heterogeneous clinical population., (© 2024 American Academy of Sleep Medicine.)

Organoids are three-dimensional (3D) cultures, normally derived from stem cells, that replicate the complex structure and function of human tissues. They offer a physiologically relevant model to address important questions in cancer research. The generation of patient-derived organoids (PDOs) from various human cancers allows for deeper insights into tumor heterogeneity and spatial organization. Additionally, interrogating non-tumor stromal cells increases the relevance in studying the tumor microenvironment, thereby enhancing the relevance of PDOs in personalized medicine. PDOs mark a significant advancement in cancer research and patient care, signifying a shift toward more innovative and patient-centric approaches. This review covers aspects of PDO cultures to address the modeling of the tumor microenvironment, including extracellular matrices, air-liquid interface and microfluidic cultures, and organ-on-chip. Specifically, the role of PDOs as preclinical models in gene editing, molecular profiling, drug testing, and biomarker discovery and their potential for guiding personalized treatment in clinical practice are discussed., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Overnight sleep staging is an important part of the diagnosis of various sleep disorders. Polysomnography is the gold standard for sleep staging, but less-obtrusive sensing modalities are of emerging interest. Here, we developed and validated an algorithm to perform "proxy" sleep staging using cardiac and respiratory signals derived from a chest-worn accelerometer. We collected data in two sleep centers, using a chest-worn accelerometer in combination with full PSG. A total of 323 participants were analyzed, aged 13-83 years, with BMI 18-47 kg/m 2 . We derived cardiac and respiratory features from the accelerometer and then applied a previously developed method for automatic cardio-respiratory sleep staging. We compared the estimated sleep stages against those derived from PSG and determined performance. Epoch-by-epoch agreement with four-class scoring (Wake, REM, N1+N2, N3) reached a Cohen's kappa coefficient of agreement of 0.68 and an accuracy of 80.8%. For Wake vs. Sleep classification, an accuracy of 93.3% was obtained, with a sensitivity of 78.7% and a specificity of 96.6%. We showed that cardiorespiratory signals obtained from a chest-worn accelerometer can be used to estimate sleep stages among a population that is diverse in age, BMI, and prevalence of sleep disorders. This opens up the path towards various clinical applications in sleep medicine.

We aimed to conduct a biophysical comparison of angular (Biorower) and linear (Concept2) rowing ergometers across a wide spectrum of exercise intensities. Sixteen (eleven male) skilled rowers, aged 29.8 ± 8.6 and 23.6 ± 1.5 years, with international competitive experience, performed 7 × 3 min bouts with 30 W increments and 60 s intervals, plus 1 min of all-out rowing on both machines with 48 h in between. The ventilatory and kinematical variables were measured breath-by-breath using a telemetric portable gas analyzer and determined using a full-body markerless system, respectively. Similar values of oxygen uptake were observed between ergometers across all intensity domains (e.g., 60.36 ± 8.40 vs. 58.14 ± 7.55 mL/min/kg for the Biorower and Concept2 at severe intensity). The rowing rate was higher on the Biorower vs. Concept2 at heavy and severe intensities (27.88 ± 3.22 vs. 25.69 ± 1.99 and 30.63 ± 3.18 vs. 28.94 ± 2.29). Other differences in kinematics were observed across all intensity domains, particularly in the thorax angle at the finish (e.g., 19.44 ± 4.49 vs. 27.51 ± 7.59° for the Biorower compared to Concep2 at heavy intensity), likely due to closer alignment of the Biorower with an on-water rowing technique. The overall perceived effort was lower on the Biorower when compared to the Concept2 (14.38 ± 1.76 vs. 15.88 ± 1.88). Rowers presented similar cardiorespiratory function on both rowing ergometers, while important biomechanical differences were observed, possibly due to the Biorower's closer alignment with an on-water rowing technique.

We investigated the acute biophysical responses of changing the mandibular position during a rowing incremental protocol. A World-class 37-year-old male rower performed two 7 × 3 min ergometer rowing trials, once with no intraoral splint (control) and the other with a mandibular forward repositioning splint (splint condition). Ventilatory, kinematics and body electromyography were evaluated and compared between trials (paired samples t -test, p ≤ 0.05). Under the splint condition, oxygen uptake was lower, particularly at higher exercise intensities (67.3 ± 2.3 vs. 70.9 ± 1.5 mL·kg -1 ·min -1 ), and ventilation increased during specific rowing protocol steps (1st-4th and 6th). Wearing the splint condition led to changes in rowing technique, including a slower rowing frequency ([18-30] vs. [19-32] cycles·min -1 ) and a longer propulsive movement ([1.58-1.52] vs. [1.56-1.50] m) than the control condition. The splint condition also had a faster propulsive phase and a prolonged recovery period than the control condition. The splint reduced peak and mean upper body muscle activation, contrasting with an increase in lower body muscle activity, and generated an energetic benefit by reducing exercise cost and increasing rowing economy compared to the control condition. Changing the mandibular position benefited a World-class rower, supporting the potential of wearing an intraoral splint in high-level sports, particularly in rowing.

Beach volleyball (BV) is an intermittent sport characterised by short-duration and highly demanding activities with low intensity periods. Establishing if players' jump ability is influenced by sand granulometry is a useful information for sport scientists, coaches and players. This study aimed to assess the possible differences in the kinetics parameters of the vertical jump on different types of sand performed by BV players. Twelve elite female players performed six countermovement jumps (CMJs) in three different surface conditions (fine sand, reference, coarse sand) in a random counterbalanced order (216 jumps). A generalised mixed model approach detected differences for CMJ model in total duration (p: 0.016), eccentric phase duration (p: 0.007), concentric phase duration (p: 0.011), time to peak power (p: < 0.001), time to peak force (p: 0.014), maximum rate force development concentric phase (p: 0.004), maximum velocity (p: 0.028) and peak power eccentric (p: 0.018). Coarse sand decreases the time spent jumping compared to fine sand, without a penalty to jump height. Coaches and athletes should take this information into account to enhance their understanding of practice strategies and game conditions. One might anticipate a faster pace in games played on coarse sand and a slower pace on fine sand.

Investigating the evolutionary trajectory of synapsid sensory and cephalic systems is pivotal for understanding the emergence and diversification of mammals. Recent studies using CT-scanning to analyze the rostral foramina and maxillary canals morphology in fossilized specimens of probainognathian cynodonts have contributed to clarifying the homology and paleobiological interpretations of these structures. In the present work, μCT-scannings of three specimens of Riograndia guaibensis, an early Norian cynodont from southern Brazil, were analyzed and revealed an incomplete separation between the lacrimal and maxillary canals, with points of contact via non-ossified areas. While the maxillary canal exhibits a consistent morphological pattern with other Prozostrodontia, featuring three main branches along the lateral region of the snout, the rostral alveolar canal in Riograndia displays variability in the number of extra branches terminating in foramina on the lateral surface of the maxilla, showing differences among individuals and within the same skull. Additionally, pneumatization is observed in the anterior region of the skull, resembling similar structures found in reptiles and mammals. Through this pneumatization, certain branches originating from the maxillary canal extend to the canine alveolus. Further investigation is warranted to elucidate the functionality of this structure and its occurrence in other cynodont groups., (© 2024 The Author(s). The Anatomical Record published by Wiley Periodicals LLC on behalf of American Association for Anatomy.)

Extracellular vesicles (EVs) hold promise as a source of disease biomarkers. The diverse molecular cargo of EVs can potentially indicate the status of their tissue of origin, even against the complex background of whole plasma. The main tools currently available for assessing biomarkers of brain health include brain imaging and analysis of the cerebrospinal fluid of patients. Given the costs and difficulties associated with these methods, isolation of EVs of neuronal origin (NEVs) from the blood is an attractive approach to identify brain-specific biomarkers. This perspective describes current key challenges in EV- and NEV-based biomarker research. These include the relative low abundance of EVs, the lack of validated isolation methods, and the difficult search for an adequate target for immunocapturing NEVs. We discuss that these challenges must be addressed before NEVs can fulfill their potential for biomarker research. HIGHLIGHTS: NEVs are promising sources of biomarkers for brain disorders. Immunocapturing NEVs from complex biofluids presents several challenges. The choice of surface target for capture will determine NEV yield. Contamination by non-EV sources is relevant for biomarkers at low concentrations., (© 2024 The Author(s). Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Objective: wearable sensor technology has progressed significantly in the last decade, but its clinical usability for the assessment of obstructive sleep apnea (OSA) is limited by the lack of large and representative datasets simultaneously acquired with polysomnography (PSG). The objective of this study was to explore the use of cardiorespiratory signals common in standard PSGs which can be easily measured with wearable sensors, to estimate the severity of OSA., Methods: an artificial neural network was developed for detecting sleep disordered breathing events using electrocardiogram (ECG) and respiratory effort. The network was combined with a previously developed cardiorespiratory sleep staging algorithm and evaluated in terms of sleep staging classification performance, apnea-hypopnea index (AHI) estimation, and OSA severity estimation against PSG on a cohort of 653 participants with a wide range of OSA severity., Results: four-class sleep staging achieved a κ of 0.69 versus PSG, distinguishing wake, combined N1-N2, N3 and REM. AHI estimation achieved an intraclass correlation coefficient of 0.91, and high diagnostic performance for different OSA severity thresholds., Conclusions: this study highlights the potential of using cardiorespiratory signals to estimate OSA severity, even without the need for airflow or oxygen saturation (SpO2), traditionally used for assessing OSA., Significance: while further research is required to translate these findings to practical and unobtrusive sensors, this study demonstrates how existing, large datasets can serve as a foundation for wearable systems for OSA monitoring. Ultimately, this approach could enable long-term assessment of sleep disordered breathing, facilitating new avenues for clinical research in this field.

The electrical stimulation of pedicle screws is a technique used to ensure its correct placement within the vertebrae pedicle. Several authors have studied these screws' electrical properties with the objective of understanding if they are a potential source of false negatives. As titanium screws are anodized with different thicknesses of a high electrical resistance oxide (TiO 2 ), this study investigated, using analytical, numerical, and experimental methods, how its thickness may affect pedicle screw's resistance and conductivity. Analytical results have demonstrated that the thickness of the TiO 2 layer does result in a significant radial resistance increase (44.21 mΩ/nm, for Ø 4.5 mm), and a decrease of conductivity with layers thicker than 150 nm. The numerical approach denotes that the geometry of the screw further results in a decrease in the pedicle screw conductivity, especially after 125 nm. Additionally, the experimental results demonstrate that there is indeed an effective decrease in conductivity with an increase in the TiO 2 layer thickness, which is also reflected in the screw's total resistance. While the magnitude of the resistance associated with each TiO 2 layer thickness may not be enough to compromise the ability to use anodized pedicle screws with a high-voltage electrical stimulator, pedicle screws should be the subject of more frequent electrical characterisation studies.

The nasal cavity of living mammals is a unique structural complex among tetrapods, acquired along a series of major morphological transformations that occurred mainly during the Mesozoic Era, within the Synapsida clade. Particularly, non-mammaliaform cynodonts document several morphological changes in the skull, during the Triassic Period, that represent the first steps of the mammalian bauplan. We here explore the nasal cavity of five cynodont taxa, namely Thrinaxodon, Chiniquodon, Prozostrodon, Riograndia, and Brasilodon, in order to discuss the main changes within this skull region. We did not identify ossified turbinals in the nasal cavity of these taxa and if present, as non-ossified structures, they would not necessarily be associated with temperature control or the development of endothermy. We do, however, notice a complexification of the cartilage anchoring structures that divide the nasal cavity and separate it from the brain region in these forerunners of mammals., (© 2024. The Author(s).)

To explore the diversity of scenarios in nature, animals have evolved tools to interact with different environmental conditions. Chemoreceptors are an important interface component and among them, olfactory receptors (ORs) and gustatory receptors (GRs) can be used to find food and detect healthy resources. Drosophila is a model organism in many scientific fields, in part due to the diversity of species and niches they occupy. The contrast between generalists and specialists Drosophila species provides an important model for studying the evolution of chemoreception. Here, we compare the repertoire of chemoreceptors of different species of Drosophila with that of D. incompta, a highly specialized species whose ecology is restricted to Cestrum flowers, after reporting the preferences of D. incompta to the odor of Cestrum flowers in olfactory tests. We found evidence that the chemoreceptor repertoire in D. incompta is smaller than that presented by species in the Sophophora subgenus. Similar patterns were found in other non-Sophophora species, suggesting the presence of underlying phylogenetic trends. Nevertheless, we also found autapomorphic gene losses and detected some genes that appear to be under positive selection in D. incompta, suggesting that the specific lifestyle of these flies may have shaped the evolution of individual genes in each of these gene families.

Musicians' body behaviour has a preponderant role in audience perception. We investigated how performers' motion is perceived depending on the musical style and musical expertise. To further explore the effect of visual input, stimuli were presented in audio-only, audio-visual and visual-only conditions. We used motion and audio recordings of expert saxophone players playing two contrasting excerpts (positively and negatively valenced). For each excerpt, stimuli represented five motion degrees with increasing quantity of motion (QoM) and distinct predominant gestures. In the experiment (online and in-person), 384 participants rated performance recordings for expressiveness, professionalism and overall quality. Results revealed that, for the positively valenced excerpt, ratings increased as a function of QoM, whilst for the negatively valenced, the recording with predominant flap motion was favoured. Musicianship did not have a significant effect in motion perception. Concerning multisensory integration, both musicians and non-musicians presented visual dominance in the positively valenced excerpt, whereas in the negatively valenced, musicians shifted to auditory dominance. Our findings demonstrate that musical style not only determines the way observers perceive musicians' movement as adequate, but also that it can promote changes in multisensory integration., (© 2024. The Author(s).)

Purpose: To evaluate the balance in patients with total knee arthroplasty (TKA) and knee osteoarthrosis (KOA), measured by postural stability computerized evaluation (PSCE), and to evaluate the effect of post-TKA patients' characteristics in their performance on PSCE., Materials and Methods: An observational cross-sectional study was conducted in two sets of patients: (A) patients with KOA and primary TKA surgery scheduled and (B) patients who underwent primary TKA >9 months. Sociodemographic, radiographic, clinical and PSCE parameters (using the Biodex Balance System) were assessed., Results: Post-TKA patients placed more load on the replaced knee than the contralateral osteoarthritic knee ( p  = 0.027). They had less imbalance on the balance tests performed with the eyes open, on stable ( p  = 0.032), and unstable platforms ( p  = 0.022). These patients also showed better postural stability in monopodalic stance, both standing on the TKA ( p  = 0.010) and contralateral knee ( p  = 0.017). Age, weight, pain on the operated knee, extension deficit on the operated knee, and Berg Balance Scale scores on post-TKA patients were significantly associated with their performance on PSCE tests., Conclusions: PSCE can be useful to quantify the balance of post-TKA and KOA patients.

This study aimed to systematically review and summarise the evidence about the effect of muscle fatigue on the knee proprioception of trained and non-trained individuals. A search in PubMed, Scopus, Web of Science and EBSCO databases and Google Scholar was conducted using the expression: "fatigue" AND ("proprioception" OR "position sense" OR "repositioning" OR "kinesthesia" OR "detection of passive motion" OR "force sense" OR "sense of resistance") AND "knee". Forty-two studies were included. Regarding joint-position sense, higher repositioning errors were reported after local and general protocols. Kinesthesia seems to be more affected when fatigue is induced locally, and force sense when assessed at higher target forces and after eccentric protocols. Muscle fatigue, both induced locally or generally, has a negative impact on the knee proprioception.

Objective. Intra-esophageal pressure (Pes) measurement is the recommended gold standard to quantify respiratory effort during sleep, but used to limited extent in clinical practice due to multiple practical drawbacks. Respiratory inductance plethysmography belts (RIP) in conjunction with oronasal airflow are the accepted substitute in polysomnographic systems (PSG) thanks to a better usability, although they are partial views on tidal volume and flow rather than true respiratory effort and are often used without calibration. In their place, the pressure variations measured non-invasively at the suprasternal notch (SSP) may provide a better measure of effort. However, this type of sensor has been validated only for respiratory events in the context of obstructive sleep apnea syndrome (OSA). We aim to provide an extensive verification of the suprasternal pressure signal against RIP belts and Pes, covering both normal breathing and respiratory events. Approach. We simultaneously acquired suprasternal (207) and esophageal pressure (20) signals along with RIP belts during a clinical PSG of 207 participants. In each signal, we detected breaths with a custom algorithm, and evaluated the SSP in terms of detection quality, breathing rate estimation, and similarity of breathing patterns against RIP and Pes. Additionally, we examined how the SSP signal may diverge from RIP and Pes in presence of respiratory events scored by a sleep technician. Main results. The SSP signal proved to be a reliable substitute for both esophageal pressure (Pes) and respiratory inductance plethysmography (RIP) in terms of breath detection, with sensitivity and positive predictive value exceeding 75%, and low error in breathing rate estimation. The SSP was also consistent with Pes (correlation of 0.72, similarity 80.8%) in patterns of increasing pressure amplitude that are common in OSA. Significance. This work provides a quantitative analysis of suprasternal pressure sensors for respiratory effort measurements., (Creative Commons Attribution license.)

Lower limb exoskeletons have the potential to mitigate work-related musculoskeletal disorders; however, they often lack user-oriented control strategies. Human-in-the-loop (HITL) controls adapt an exoskeleton's assistance in real time, to optimize the user-exoskeleton interaction. This study presents a HITL control for a knee exoskeleton using a CMA-ES algorithm to minimize the users' physical effort, a parameter innovatively evaluated using the interaction torque with the exoskeleton (a muscular effort indicator) and metabolic cost. This work innovates by estimating the user's metabolic cost within the HITL control through a machine-learning model. The regression model estimated the metabolic cost, in real time, with a root mean squared error of 0.66 W/kg and mean absolute percentage error of 26% ( n = 5), making faster (10 s) and less noisy estimations than a respirometer (K5, Cosmed). The HITL reduced the user's metabolic cost by 7.3% and 5.9% compared to the zero-torque and no-device conditions, respectively, and reduced the interaction torque by 32.3% compared to a zero-torque control ( n = 1). The developed HITL control surpassed a non-exoskeleton and zero-torque condition regarding the user's physical effort, even for a task such as slow walking. Furthermore, the user-specific control had a lower metabolic cost than the non-user-specific assistance. This proof-of-concept demonstrated the potential of HITL controls in assisted walking.

Objective. Sleep staging based on full polysomnography is the gold standard in the diagnosis of many sleep disorders. It is however costly, complex, and obtrusive due to the use of multiple electrodes. Automatic sleep staging based on single-channel electro-oculography (EOG) is a promising alternative, requiring fewer electrodes which could be self-applied below the hairline. EOG sleep staging algorithms are however yet to be validated in clinical populations with sleep disorders. Approach. We utilized the SOMNIA dataset, comprising 774 recordings from subjects with various sleep disorders, including insomnia, sleep-disordered breathing, hypersomnolence, circadian rhythm disorders, parasomnias, and movement disorders. The recordings were divided into train (574), validation (100), and test (100) groups. We trained a neural network that integrated transformers within a U-Net backbone. This design facilitated learning of arbitrary-distance temporal relationships within and between the EOG and hypnogram. Main results. For 5-class sleep staging, we achieved median accuracies of 85.0% and 85.2% and Cohen's kappas of 0.781 and 0.796 for left and right EOG, respectively. The performance using the right EOG was significantly better than using the left EOG, possibly because in the recommended AASM setup, this electrode is located closer to the scalp. The proposed model is robust to the presence of a variety of sleep disorders, displaying no significant difference in performance for subjects with a certain sleep disorder compared to those without. Significance. The results show that accurate sleep staging using single-channel EOG can be done reliably for subjects with a variety of sleep disorders., (Creative Commons Attribution license.)

Background: Sleep-disordered breathing (SDB) affects a significant portion of the population. As such, there is a need for accessible and affordable assessment methods for diagnosis but also case-finding and long-term follow-up. Research has focused on exploiting cardiac and respiratory signals to extract proxy measures for sleep combined with SDB event detection. We introduce a novel multi-task model combining cardiac activity and respiratory effort to perform sleep-wake classification and SDB event detection in order to automatically estimate the apnea-hypopnea index (AHI) as severity indicator., Methods: The proposed multi-task model utilized both convolutional and recurrent neural networks and was formed by a shared part for common feature extraction, a task-specific part for sleep-wake classification, and a task-specific part for SDB event detection. The model was trained with RR intervals derived from electrocardiogram and respiratory effort signals. To assess performance, overnight polysomnography (PSG) recordings from 198 patients with varying degree of SDB were included, with manually annotated sleep stages and SDB events., Results: We achieved a Cohen's kappa of 0.70 in the sleep-wake classification task, corresponding to a Spearman's correlation coefficient (R) of 0.830 between the estimated total sleep time (TST) and the TST obtained from PSG-based sleep scoring. Combining the sleep-wake classification and SDB detection results of the multi-task model, we obtained an R of 0.891 between the estimated and the reference AHI. For severity classification of SBD groups based on AHI, a Cohen's kappa of 0.58 was achieved. The multi-task model performed better than a single-task model proposed in a previous study for AHI estimation, in particular for patients with a lower sleep efficiency (R of 0.861 with the multi-task model and R of 0.746 with single-task model with subjects having sleep efficiency < 60%)., Conclusion: Assisted with automatic sleep-wake classification, our multi-task model demonstrated proficiency in estimating AHI and assessing SDB severity based on AHI in a fully automatic manner using RR intervals and respiratory effort. This shows the potential for improving SDB screening with unobtrusive sensors also for subjects with low sleep efficiency without adding additional sensors for sleep-wake detection., (© 2024. The Author(s).)

Objective: To explore sleep structure in participants with obstructive sleep apnea (OSA) and comorbid insomnia (COMISA) and participants with OSA without insomnia (OSA-only) using both single-night polysomnography and multi-night wrist-worn photoplethysmography/accelerometry., Methods: Multi-night 4-class sleep-staging was performed with a validated algorithm based on actigraphy and heart rate variability, in 67 COMISA (23 women, median age: 51 years) and 50 OSA-only (15 women, median age: 51) participants. Sleep statistics were compared using linear regression models and mixed-effects models. Multi-night variability was explored using a clustering approach and between- and within-participant analysis., Results: Polysomnographic parameters showed no significant group differences. Multi-night measurements, during 13.4 ± 5.2 nights per subject, demonstrated a longer sleep onset latency and lower sleep efficiency for the COMISA group. Detailed analysis of wake parameters revealed longer mean durations of awakenings in COMISA, as well as higher numbers of awakenings lasting 5 min and longer (WKN ≥5min ) and longer wake after sleep onset containing only awakenings of 5 min or longer. Within-participant variance was significantly larger in COMISA for sleep onset latency, sleep efficiency, mean duration of awakenings and WKN ≥5min . Unsupervised clustering uncovered three clusters; participants with consistently high values for at least one of the wake parameters, participants with consistently low values, and participants displaying higher variability., Conclusion: Patients with COMISA more often showed extended, and more variable periods of wakefulness. These observations were not discernible using single night polysomnography, highlighting the relevance of multi-night measurements to assess characteristics indicative for insomnia., Competing Interests: Declaration of competing interest At the time of writing, BW, NT and PF were employed and/or affiliated with Royal Philips, a commercial company and manufacturer of consumer and medical electronic devices, commercializing products in the area of sleep diagnostics and sleep therapy. Philips had no role in the study design, decision to publish or preparation of the manuscript. JA received financial support from Philips and SomnoMed for research and participated in advisory boards for Jazz Pharmaceuticals and Bioprojet, all unrelated to the present work. SO received an unrestricted research grant from UCB Pharma and participated in advisory boards for UCB Pharma, Jazz Pharmaceuticals, Takeda and Bioprojet and speaking engagements for Takeda and AbbVie. The other authors have no conflicts of interest., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Purpose: Comorbid insomnia often occurs in patients with obstructive sleep apnea (OSA), referred to as COMISA. Cortical arousals manifest as a common feature in both OSA and insomnia, often accompanied by elevated heart rate (HR). Our objective was to evaluate the heart rate response to nocturnal cortical arousals in patients with COMISA and patients with OSA alone., Methods: We analyzed data from patients with COMISA and from patients with OSA matched for apnea-hypopnea index. Sleep staging and analysis of respiratory events and cortical arousals were performed using the Philips Somnolyzer automatic scoring system. Beat-by-beat HR was analyzed from the onset of the cortical arousal to 30 heartbeats afterwards. HR responses were divided into peak and recovery phases. Cortical arousals were separately evaluated according to subtype (related to respiratory events and spontaneous) and duration (3-6 s, 6-10 s, 10-15 s)., Results: A total of 72 patients with COMISA and 72 patients with OSA were included in this study. There were no overall group differences in the number of cortical arousals with and without autonomic activation. No significant differences were found for spontaneous cortical arousals. The OSA group had more cortical arousals related to respiratory events (21.0 [14.8-30.0] vs 16.0 [9.0-27.0], p = 0.016). However, the COMISA group had longer cortical arousals (7.2 [6.4-7.8] vs 6.7 [6.2-7.7] s, p = 0.024) and the HR recovery phase was prolonged (52.5 [30.8-82.5] vs 40.0 [21.8-55.5] beats/min, p = 0.017). Both the peak and the recovery phase for longer cortical arousals with a duration of 10-15 s were significantly higher in patients with COMISA compared to patients with OSA (47.0 [27.0-97.5] vs 34.0 [21.0-71.0] beats/min, p = 0.032 and 87.0 [47.0-132.0] vs 71.0 [43.0-103.5] beats/min, p = 0.049, respectively)., Conclusions: The HR recovery phase after cortical arousals related to respiratory events is prolonged in patients with COMISA compared to patients with OSA alone. This response could be indicative of the insomnia component in COMISA., (© 2023. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Background: Tumor cells have the ability to invade and form small clusters that protrude into adjacent tissues, a phenomenon that is frequently observed at the periphery of a tumor as it expands into healthy tissues. The presence of these clusters is linked to poor prognosis and has proven challenging to treat using conventional therapies. We previously reported that p60AmotL2 expression is localized to invasive colon and breast cancer cells. In vitro, p60AmotL2 promotes epithelial cell invasion by negatively impacting E-cadherin/AmotL2-related mechanotransduction., Methods: Using epithelial cells transfected with inducible p60AmotL2, we employed a phenotypic drug screening approach to find compounds that specifically target invasive cells. The phenotypic screen was performed by treating cells for 72 h with a library of compounds with known antitumor activities in a dose-dependent manner. After assessing cell viability using CellTiter-Glo, drug sensitivity scores for each compound were calculated. Candidate hit compounds with a higher drug sensitivity score for p60AmotL2-expressing cells were then validated on lung and colon cell models, both in 2D and in 3D, and on colon cancer patient-derived organoids. Nascent RNA sequencing was performed after BET inhibition to analyse BET-dependent pathways in p60AmotL2-expressing cells., Results: We identified 60 compounds that selectively targeted p60AmotL2-expressing cells. Intriguingly, these compounds were classified into two major categories: Epidermal Growth Factor Receptor (EGFR) inhibitors and Bromodomain and Extra-Terminal motif (BET) inhibitors. The latter consistently demonstrated antitumor activity in human cancer cell models, as well as in organoids derived from colon cancer patients. BET inhibition led to a shift towards the upregulation of pro-apoptotic pathways specifically in p60AmotL2-expressing cells., Conclusions: BET inhibitors specifically target p60AmotL2-expressing invasive cancer cells, likely by exploiting differences in chromatin accessibility, leading to cell death. Additionally, our findings support the use of this phenotypic strategy to discover novel compounds that can exploit vulnerabilities and specifically target invasive cancer cells., (© 2024. The Author(s).)

Body size influences most aspects of an animal's biology, consequently, evolutionary diversification is often accompanied by differentiation of body sizes within a lineage. It is accepted that miniaturization, or the evolution of extremely small body sizes, played a key role in the origin and early evolution of different mammalian characters in non-mammaliaform cynodonts. However, while there are multiple studies on the biomechanical, behavioral, and physiological consequences of smaller sizes, few explore the evolutionary processes that lead to them. Here, we use body mass as a universal size measurement in phylogenetic comparative analyses to explore aspects of body size evolution in Cynodontia, focusing on the cynodont-mammal transition, and test the miniaturization hypothesis for the origin of Mammaliaformes. We estimated the body masses of 29 species, ranging from Theriocephalia to Mammaliaformes, providing the largest collection of Triassic cynodont body mass estimates that we know of, and used these estimates in analyses of disparity through time and RR phylo . Unexpectedly, our results did not support the miniaturization hypothesis. Even though cynodont body size disparity fell during the Late Triassic, and remained lower than expected under a purely Brownian motion model of evolution up until the Early Jurassic, we found that rates of body size evolution were significantly lower in prozostrodontians leading to the first Mammaliaformes than in other lineages. Evolution rates were higher in medium and large-sized taxa, indicating that size was changing more rapidly in those lineages and that small sizes were probably a persistent plesiomorphic character-state in Cynodontia., (© 2024 American Association for Anatomy.)

Automatic estimation of sleep structure is an important aspect in moving sleep monitoring from clinical laboratories to people's homes. However, the transition to more portable systems should not happen at the expense of important physiological signals, such as respiration. Here, we propose the use of cardiorespiratory signals obtained by a suprasternal pressure (SSP) sensor to estimate sleep stages. The sensor is already used for diagnosis of sleep-disordered breathing (SDB) conditions, but besides respiratory effort it can detect cardiac vibrations transmitted through the trachea. We collected the SSP sensor signal in 100 adults (57 male) undergoing clinical polysomnography for suspected sleep disorders, including sleep apnea syndrome, insomnia, and movement disorders. Here, we separate respiratory effort and cardiac activity related signals, then input these into a neural network trained to estimate sleep stages. Using the original mixed signal the results show a moderate agreement with manual scoring, with a Cohen's kappa of 0.53 in Wake/N1-N2/N3/rapid eye movement sleep discrimination and 0.62 in Wake/Sleep. We demonstrate that decoupling the two signals and using the cardiac signal to estimate the instantaneous heart rate improves the process considerably, reaching an agreement of 0.63 and 0.71. Our proposed method achieves high accuracy, specificity, and sensitivity across different sleep staging tasks. We also compare the total sleep time calculated with our method against manual scoring, with an average error of -1.83 min but a relatively large confidence interval of ±55 min. Compact systems that employ the SSP sensor information-rich signal may enable new ways of clinical assessments, such as night-to-night variability in obstructive sleep apnea and other sleep disorders., (© 2023 The Authors. Journal of Sleep Research published by John Wiley & Sons Ltd on behalf of European Sleep Research Society.)

Study Objectives: Automatic sleep staging based on cardiorespiratory signals from home sleep monitoring devices holds great clinical potential. Using state-of-the-art machine learning, promising performance has been reached in patients with sleep disorders. However, it is unknown whether performance would hold in individuals with potentially altered autonomic physiology, for example under the influence of medication. Here, we assess an existing sleep staging algorithm in patients with sleep disorders with and without the use of beta blockers., Methods: We analyzed a retrospective dataset of sleep recordings of 57 patients with sleep disorders using beta blockers and 57 age-matched patients with sleep disorders not using beta blockers. Sleep stages were automatically scored based on electrocardiography and respiratory effort from a thoracic belt, using a previously developed machine-learning algorithm (CReSS algorithm). For both patient groups, sleep stages classified by the model were compared to gold standard manual polysomnography scoring using epoch-by-epoch agreement. Additionally, for both groups, overall sleep parameters were calculated and compared between the two scoring methods., Results: Substantial agreement was achieved for four-class sleep staging in both patient groups (beta blockers: kappa = 0.635, accuracy = 78.1%; controls: kappa = 0.660, accuracy = 78.8%). No statistical difference in epoch-by-epoch agreement was found between the two groups. Additionally, the groups did not differ on agreement of derived sleep parameters., Conclusions: We showed that the performance of the CReSS algorithm is not deteriorated in patients using beta blockers. Results do not indicate a fundamental limitation in leveraging autonomic characteristics to obtain a surrogate measure of sleep in this clinically relevant population., Citation: Hermans L, van Meulen F, Anderer P, et al. Performance of cardiorespiratory-based sleep staging in patients using beta blockers. J Clin Sleep Med . 2024;20(4):575-581., (© 2024 American Academy of Sleep Medicine.)

Objective . Unobtrusive long-term monitoring of cardiac parameters is important in a wide variety of clinical applications, such as the assesment of acute illness severity and unobtrusive sleep monitoring. Here we determined the accuracy and robustness of heartbeat detection by an accelerometer worn on the chest. Approach . We performed overnight recordings in 147 individuals (69 female, 78 male) referred to two sleep centers. Two methods for heartbeat detection in the acceleration signal were compared: one previously described approach, based on local periodicity, and a novel extended method incorporating maximum a posteriori estimation and a Markov decision process to approach an optimal solution. Main results . The maximum a posteriori estimation significantly improved performance, with a mean absolute error for the estimation of inter-beat intervals of only 3.5 ms, and 95% limits of agreement of -1.7 to +1.0 beats per minute for heartrate measurement. Performance held during posture changes and was only weakly affected by the presence of sleep disorders and demographic factors. Significance . The new method may enable the use of a chest-worn accelerometer in a variety of applications such as ambulatory sleep staging and in-patient monitoring., (Creative Commons Attribution license.)

Study Objectives: Hypnograms contain a wealth of information and play an important role in sleep medicine. However, interpretation of the hypnogram is a difficult task and requires domain knowledge and "clinical intuition." This study aimed to uncover which features of the hypnogram drive interpretation by physicians. In other words, make explicit which features physicians implicitly look for in hypnograms., Methods: Three sleep experts evaluated up to 612 hypnograms, indicating normal or abnormal sleep structure and suspicion of disorders. ElasticNet and convolutional neural network classification models were trained to predict the collected expert evaluations using hypnogram features and stages as input. The models were evaluated using several measures, including accuracy, Cohen's kappa, Matthew's correlation coefficient, and confusion matrices. Finally, model coefficients and visual analytics techniques were used to interpret the models to associate hypnogram features with expert evaluation., Results: Agreement between models and experts (Kappa between 0.47 and 0.52) is similar to agreement between experts (Kappa between 0.38 and 0.50). Sleep fragmentation, measured by transitions between sleep stages per hour, and sleep stage distribution were identified as important predictors for expert interpretation., Conclusions: By comparing hypnograms not solely on an epoch-by-epoch basis, but also on these more specific features that are relevant for the evaluation of experts, performance assessment of (automatic) sleep-staging and surrogate sleep trackers may be improved. In particular, sleep fragmentation is a feature that deserves more attention as it is often not included in the PSG report, and existing (wearable) sleep trackers have shown relatively poor performance in this aspect., (© The Author(s) 2023. Published by Oxford University Press on behalf of Sleep Research Society. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Competing Interests: The authors report no conflicts of interest.

Rowing performance depends on the design and building materials used for competition. Recently, attempting to improve rowing performance, the Randall foil has been attached to the top edge of a rowing Big blade, making it spoon shaped. The current study aimed to analyse the differences between Big blades with and without Randall foils in force-related variables. Nineteen rowers performed two bouts of 90 s at maximal effort tethered rowing and differences were found in cycle average peak force (4.33 ± 1.46 vs. 5.26 ± 1.57 N/kg), propulsive cycle average time (1.79 ± 0.38 vs. 1.52 ± 0.24 N/kg.s) and rate of force development (8.79 ± 4.75 vs. 12.07 ± 4.60 N/kg/s) for Big blades with and without foils (respectively). Differences were also observed between the middle (4.79 ± 1.21 vs. 4.08 ± 1.48 N/kg) and final phases (4.86 ± 1.45 vs. 4.04 ± 1.47 N/kg) of the rowing effort for the cycle average peak force of Big blades with and without Randall foils. Data suggest a positive effect of these foils on the force-time curve profile. Future studies should focus on testing its influence on free on-water rowing.

Purpose: Fran is one of the most popular CrossFit benchmark workouts used to control CrossFitters' improvements. Detailed physiological characterization of Fran is needed for a more specific evaluation of CrossFitters' training performance improvements. The aim of the study was to analyze the oxygen uptake (V˙O2) kinetics and characterize the energy system contributions and the degree of postexercise fatigue of the unbroken Fran., Methods: Twenty trained CrossFitters performed Fran at maximal exertion. V˙O2 and heart-rate kinetics were assessed at baseline and during and post-Fran. Blood lactate and glucose concentrations and muscular fatigue were measured at baseline and in the recovery period., Results: A marked increase in V˙O2 kinetics was observed at the beginning of Fran, remaining elevated until the end (V˙O2peak: 49.2 [3.7] mL·kg-1·min-1, V˙O2 amplitude: 35.8 [5.2] mL·kg-1·min-1, time delay: 4.7 [2.5] s and time constant: 23.7 [11.1] s; mean [SD]). Aerobic, anaerobic lactic, and alactic pathways accounted for 62% (4%), 26% (4%), and 12% (2%) of energy contribution. Reduction in muscle function in jumping ability (jump height: 8% [6%], peak force: 6% [4%], and maximum velocity: 4% [2%]) and plank prone test (46% [20%]) was observed in the recovery period., Conclusions: The Fran unbroken workout is a high-intensity effort associated with an elevated metabolic response. This pattern of energy response highlights the primary contribution of aerobic energy metabolism, even during short and very intense CrossFit workouts, and that recovery can take >24 hours due to cumulative fatigue.

Introduction: Automated sleep staging using deep learning models typically requires training on hundreds of sleep recordings, and pre-training on public databases is therefore common practice. However, suboptimal sleep stage performance may occur from mismatches between source and target datasets, such as differences in population characteristics (e.g., an unrepresented sleep disorder) or sensors (e.g., alternative channel locations for wearable EEG). Methods: We investigated three strategies for training an automated single-channel EEG sleep stager: pre-training (i.e., training on the original source dataset), training-from-scratch (i.e., training on the new target dataset), and fine-tuning (i.e., training on the original source dataset, fine-tuning on the new target dataset). As source dataset, we used the F3-M2 channel of healthy subjects (N = 94). Performance of the different training strategies was evaluated using Cohen's Kappa ( κ ) in eight smaller target datasets consisting of healthy subjects (N = 60), patients with obstructive sleep apnea (OSA, N = 60), insomnia (N = 60), and REM sleep behavioral disorder (RBD, N = 22), combined with two EEG channels, F3-M2 and F3-F4. Results: No differences in performance between the training strategies was observed in the age-matched F3-M2 datasets, with an average performance across strategies of κ = .83 in healthy, κ = .77 in insomnia, and κ = .74 in OSA subjects. However, in the RBD set, where data availability was limited, fine-tuning was the preferred method ( κ = .67), with an average increase in κ of .15 to pre-training and training-from-scratch. In the presence of channel mismatches, targeted training is required, either through training-from-scratch or fine-tuning, increasing performance with κ = .17 on average. Discussion: We found that, when channel and/or population mismatches cause suboptimal sleep staging performance, a fine-tuning approach can yield similar to superior performance compared to building a model from scratch, while requiring a smaller sample size. In contrast to insomnia and OSA, RBD data contains characteristics, either inherent to the pathology or age-related, which apparently demand targeted training., Competing Interests: At the time of writing, JA, DE, and PF were employed and/or affiliated with Royal Philips, a commercial company and manufacturer of consumer and medical electronic devices, commercializing products in the area of sleep diagnostics and sleep therapy. Philips had no role in the study design, decision to publish or preparation of the manuscript. SO received an unrestricted research grant from UCB Pharma and participated in advisory boards for UCB Pharma, Takeda, Jazz Pharmaceuticals and Bioprojet, all paid to institution and all unrelated to the present work. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Van Der Aar, Van Den Ende, Fonseca, Van Meulen, Overeem, Van Gilst and Peri.)

Lower limb exoskeletons and orthoses have been increasingly used to assist the user during gait rehabilitation through torque transmission and motor stability. However, the physical human-robot interface (HRi) has not been properly addressed. Current orthoses lead to spurious forces at the HRi that cause adverse effects and high abandonment rates. This study aims to assess and compare, in a holistic approach, human-robot joint misalignment and gait kinematics in three fixation designs of ankle-foot orthoses (AFOs). These are AFOs with a frontal shin guard (F-AFO), lateral shin guard (L-AFO), and the ankle modulus of the H2 exoskeleton (H2-AFO). An experimental protocol was implemented to assess misalignment, fixation displacement, pressure interactions, user-perceived comfort, and gait kinematics during walking with the three AFOs. The F-AFO showed reduced vertical misalignment (peak of 1.37 ± 0.90 cm, p -value < 0.05), interactions (median pressures of 0.39-3.12 kPa), and higher user-perceived comfort ( p -value < 0.05) when compared to H2-AFO (peak misalignment of 2.95 ± 0.64 and pressures ranging from 3.19 to 19.78 kPa). F-AFO also improves the L-AFO in pressure (median pressures ranging from 8.64 to 10.83 kPa) and comfort ( p -value < 0.05). All AFOs significantly modified hip joint angle regarding control gait ( p -value < 0.01), while the H2-AFO also affected knee joint angle ( p -value < 0.01) and gait spatiotemporal parameters ( p -value < 0.05). Overall, findings indicate that an AFO with a frontal shin guard and a sports shoe is effective at reducing misalignment and pressure at the HRI, increasing comfort with slight changes in gait kinematics.

Sleep staging is the process by which an overnight polysomnographic measurement is segmented into epochs of 30 seconds, each of which is annotated as belonging to one of five discrete sleep stages. The resulting scoring is graphically depicted as a hypnogram, and several overnight sleep statistics are derived, such as total sleep time and sleep onset latency. Gold standard sleep staging as performed by human technicians is time-consuming, costly, and comes with imperfect inter-scorer agreement, which also results in inter-scorer disagreement about the overnight statistics. Deep learning algorithms have shown promise in automating sleep scoring, but struggle to model inter-scorer disagreement in sleep statistics. To that end, we introduce a novel technique using conditional generative models based on Normalizing Flows that permits the modeling of the inter-rater disagreement of overnight sleep statistics, termed U-Flow. We compare U-Flow to other automatic scoring methods on a hold-out test set of 70 subjects, each scored by six independent scorers. The proposed method achieves similar sleep staging performance in terms of accuracy and Cohen's kappa on the majority-voted hypnograms. At the same time, U-Flow outperforms the other methods in terms of modeling the inter-rater disagreement of overnight sleep statistics. The consequences of inter-rater disagreement about overnight sleep statistics may be great, and the disagreement potentially carries diagnostic and scientifically relevant information about sleep structure. U-Flow is able to model this disagreement efficiently and can support further investigations into the impact inter-rater disagreement has on sleep medicine and basic sleep research.

Pregnancy complications are associated with abnormal maternal autonomic regulation. Subsequently, thoroughly understanding maternal autonomic regulation during healthy pregnancy may enable the earlier detection of complications, in turn allowing for the improved management thereof. Under healthy autonomic regulation, reciprocal interactions occur between the cardiac and respiratory systems, i.e., cardiorespiratory coupling (CRC). Here, we investigate, for the first time, the differences in CRC between healthy pregnant and nonpregnant women. We apply two algorithms, namely, synchrograms and bivariate phase-rectified signal averaging, to nighttime recordings of ECG and respiratory signals. We find that CRC is present in both groups. Significantly less ( P < 0.01) cardiorespiratory synchronization occurs in pregnant women (11% vs. 15% in nonpregnant women). Moreover, there is a smaller response in the heart rate of pregnant women corresponding to respiratory inhalations and exhalations. In addition, we stratified these analyses by sleep stages. As each sleep stage is governed by different autonomic states, this stratification not only amplified some of the differences between groups but also brought out differences that remained hidden when analyzing the full-night recordings. Most notably, the known positive relationship between CRC and deep sleep is less prominent in pregnant women than in their nonpregnant counterparts. The decrease in CRC during healthy pregnancy may be attributable to decreased maternal parasympathetic activity, anatomical changes to the maternal respiratory system, and the increased physiological stress accompanying pregnancy. This work offers novel insight into the physiology of healthy pregnancy and forms part of the base knowledge needed to detect abnormalities in pregnancy. NEW & NOTEWORTHY We compare CRC, i.e., the reciprocal interaction between the cardiac and respiratory systems, between healthy pregnant and nonpregnant women for the first time. Although CRC is present in both groups, CRC is reduced during healthy pregnancy; there is less synchronization between maternal cardiac and respiratory activity and a smaller response in maternal heart rate to respiratory inhalations and exhalations. Stratifying this analysis by sleep stages reveals that differences are most prominent during deep sleep.

Competing Interests: The authors report no conflicts of interest.

Preserving an accurate cell count is crucial for maintaining homeostasis. Apical extrusion, a process in which redundant cells are eliminated by neighboring cells, plays a key role in this regard. Recent studies have revealed that apical extrusion can also be triggered in cells transformed by oncogenes, suggesting it may be a mechanism through which tumor cells escape their microenvironment. In previous work, we demonstrated that p60AmotL2 modulates the E-cadherin function by inhibiting its connection to radial actin filaments. This isoform of AmotL2 is expressed in invasive breast and colon tumors and promotes invasion in vitro and in vivo. Transcriptionally regulated by c-Fos, p60AmotL2 is induced by local stress signals such as severe hypoxia. In this study, we investigated the normal role of p60AmotL2 in epithelial tissues. We found that this isoform is predominantly expressed in the gut, where cells experience rapid turnover. Through time-lapse imaging, we present evidence that cells expressing p60AmotL2 are extruded by their normal neighboring cells. Based on these findings, we hypothesize that tumor cells exploit this pathway to detach from normal epithelia and invade surrounding tissues.

Introduction: The apnea-hypopnea index (AHI), defined as the number of apneas and hypopneas per hour of sleep, is still used as an important index to assess sleep disordered breathing (SDB) severity, where hypopneas are confirmed by the presence of an oxygen desaturation or an arousal. Ambulatory polygraphy without neurological signals, often referred to as home sleep apnea testing (HSAT), can potentially underestimate the severity of sleep disordered breathing (SDB) as sleep and arousals are not assessed. We aim to improve the diagnostic accuracy of HSATs by extracting surrogate sleep and arousal information derived from autonomic nervous system activity with artificial intelligence. Methods: We used polysomnographic (PSG) recordings from 245 subjects (148 with simultaneously recorded HSATs) to develop and validate a new algorithm to detect autonomic arousals using artificial intelligence. A clinically validated auto-scoring algorithm (Somnolyzer) scored respiratory events, cortical arousals, and sleep stages in PSGs, and provided respiratory events and sleep stages from cardio-respiratory signals in HSATs. In a four-fold cross validation of the newly developed algorithm, we evaluated the accuracy of the estimated arousal index and HSAT-derived surrogates for the AHI. Results: The agreement between the autonomic and cortical arousal index was moderate to good with an intraclass correlation coefficient of 0.73. When using thresholds of 5, 15, and 30 to categorize SDB into none, mild, moderate, and severe, the addition of sleep and arousal information significantly improved the classification accuracy from 70.2% (Cohen's κ = 0.58) to 80.4% ( κ = 0.72), with a significant reduction of patients where the severity category was underestimated from 18.8% to 7.3%. Discussion: Extracting sleep and arousal information from autonomic nervous system activity can improve the diagnostic accuracy of HSATs by significantly reducing the probability of underestimating SDB severity without compromising specificity., Competing Interests: Work was performed at Philips Sleep and Respiratory Care in Pittsburgh, Pennsylvania and Vienna, Austria. During the time that the analyses reported in this manuscript were undertaken, co-authors MR, AC, PA, PF, ES, RV were employees of Royal Philips, a commercial company and manufacturer of consumer and medical electronic devices, commercializing products in the area of sleep diagnostics and sleep therapy. Their employer had no influence on the study and on the decision to publish. PA is a freelancer at and shareholder of The Siesta Group Schlafanalyse GmbH, Vienna, Austria. The remaining author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Ross, Fonseca, Overeem, Vasko, Cerny, Shaw and Anderer.)

Trained individuals may require variations in training stimuli and advanced resistance training paradigms (ADV) to increase skeletal muscle hypertrophy. However, no meta-analysis has examined how ADV versus traditional (TRAD) approaches may differentially affect hypertrophic outcomes in trained populations. The aim of this review was to determine whether the skeletal muscle hypertrophy responses induced by TRAD differed from ADV in resistance-trained individuals. Furthermore, we sought to examine potential effects of dietary factors, participants' training status, and training loads. We searched for peer-reviewed, randomized controlled trials (published in English) conducted in healthy resistance-trained adults performing a period of TRAD and ADV with pre-to-post measurement(s) of muscle hypertrophy in PubMed, Web of Science, SPORTDiscus, and MEDLINE databases up to October 2022. A formal meta-analysis was conducted in Revman5, and risk of bias was assessed by ROB2. Ten studies met the inclusion criteria. Results indicated no difference between ADV and TRAD for muscle thickness (SMD = 0.05, 95% CI: -0.20 0.29, p  = 0.70), lean mass (SMD = -0.01, 95% CI: -0.26 0.23, p  = 0.92), muscle cross-sectional area (SMD = -0.07, 95% CI: -0.36 0.22, p  = 0.64), or all measurements analyzed together (SMD = -0.00, 95% CI: -0.15 0.14, p  = 0.95). No heterogeneity or inconsistencies were observed; however, unclear risk of bias was present in most of the studies. Short-term ADV does not induce superior skeletal muscle hypertrophy responses when compared with TRAD in trained individuals. This review was not previously registered., Competing Interests: The authors declare that they have no conflicts of interest., (Copyright © 2023 Pedro A. B. Fonseca et al.)

Background: Prostate cancer is the second most common cancer type and the second most common cancer-related cause of death in men. Cabazitaxel, a next-generation taxane, shows favorable toxicity profile and is effective in docetaxel-resistant tumors. Despite initial responses, in most cases, prostate cancer patients acquire resistance to cabazitaxel. There is a need to identify molecular markers that can monitor and predict treatment response., Methods: We performed transcriptional exosome profiling (Human Transcriptome Array-HTA 2.0) from the plasma of 19 patients with castration-resistant prostate cancer at baseline and in patients after one cycle of cabazitaxel (C1). The patients were stratified in two groups (responders and nonresponders) according to their clinical response to cabazitaxel. Gene set enrichment analysis and ingenuity pathway analysis platforms were used for gene and pathway analysis., Results: We detected molecular differences in the exosomes from two groups of patients (nonresponders vs. responders) at baseline in pathways related to prostate cancer, oncogenic signaling, cytoskeleton, and immune system. In nonresponders, we found enrichment of cytoskeleton related gene (Stathmin-1 and ITSN1) that have been associated with resistance to cabazitaxel. Monitoring of exosomal transcripts after the first cycle of treatment revealed changes in pathways associated with response to treatment., Conclusions: Sequential transcriptional profiling of plasma-derived exosomes reveals differential expression of genes that may reflect resistance to cabazitaxel treatment and therapy response., (© 2023 Wiley Periodicals LLC.)

Background: Sleep apnea is a prevalent sleep-disordered breathing (SDB) condition that affects a large population worldwide. Research has demonstrated the potential of using electrocardiographic (ECG) signals (heart rate and ECG-derived respiration, EDR) to detect SDB. However, EDR may be a suboptimal replacement for respiration signals., Methods: We evaluated a previously described ECG-based deep learning algorithm in an independent dataset including 198 patients and compared performance for SDB event detection using thoracic respiratory effort versus EDR. We also evaluated the algorithm in terms of apnea-hypopnea index (AHI) estimation performance, and SDB severity classification based on the estimated AHI., Results: Using respiratory effort instead of EDR, we achieved an improved performance in SDB event detection (F1 score = 0.708), AHI estimation (Spearman's correlation = 0.922), and SDB severity classification (Cohen's kappa of 0.62 was obtained based on AHI)., Conclusion: Respiratory effort is superior to EDR to assess SDB. Using respiratory effort and ECG, the previously described algorithm achieves good performance in a new dataset from an independent laboratory confirming its adequacy for this task.

The spread of tumor cells and the formation of distant metastasis remain the main causes of mortality in cancer patients. However, the mechanisms governing the release of cells from micro-environmental constraints remain unclear. E-cadherin negatively controls the invasion of epithelial cells by maintaining cell-cell contacts. Furthermore, the inactivation of E-cadherin triggers invasion in vitro. However, the role of E-cadherin is complex, as metastasizing cells maintain E-cadherin expression, which appears to have a positive role in the survival of tumor cells. In this report, we present a novel mechanism delineating how E-cadherin function is modulated to promote invasion. We have previously shown that E-cadherin is associated with p100AmotL2, which is required for radial actin formation and the transmission of mechanical force. Here, we present evidence that p60AmotL2, which is expressed in invading tumor cells, binds to the p100AmotL2 isoform and uncouples the mechanical constraint of radial actin filaments. We show for the first time that the coupling of E-cadherin to the actin cytoskeleton via p100AmotL2 is directly connected to the nuclear membrane. The expression of p60AmotL2 inactivates this connection and alters the properties of the nuclear lamina, potentiating the invasion of cells into micropores of the extracellular matrix. In summary, we propose that the balance of the two AmotL2 isoforms is important in the modulation of E-cadherin function and that an imbalance of this axis promotes ameboid cell invasion.

This study describes a computationally efficient algorithm for 4-class sleep staging based on cardiac activity and body movements. Using an accelerometer to calculate gross body movements and a reflective photoplethysmographic (PPG) sensor to determine interbeat intervals and a corresponding instantaneous heart rate signal, a neural network was trained to classify between wake, combined N1 and N2, N3 and REM sleep in epochs of 30 s. The classifier was validated on a hold-out set by comparing the output against manually scored sleep stages based on polysomnography (PSG). In addition, the execution time was compared with that of a previously developed heart rate variability (HRV) feature-based sleep staging algorithm. With a median epoch-per-epoch κ of 0.638 and accuracy of 77.8% the algorithm achieved an equivalent performance when compared to the previously developed HRV-based approach, but with a 50-times faster execution time. This shows how a neural network, without leveraging any a priori knowledge of the domain, can automatically "discover" a suitable mapping between cardiac activity and body movements, and sleep stages, even in patients with different sleep pathologies. In addition to the high performance, the reduced complexity of the algorithm makes practical implementation feasible, opening up new avenues in sleep diagnostics., (© 2023. The Author(s).)

Swimming performance is likely influenced by strength, but differences between butterfly, backstroke, breaststroke and front crawl, as well as between novice and expert swimmers, are unclear. We have examined the associations between sprint performances, upper and lower limb strength, and anthropometric characteristics in 14 (six males and eight females) non-elite and 16 (nine males and seven females) elite-level swimmers. After an anthropometric characterisation, participants performed four 25 m maximal swims (one per technique) with 10 min intervals, right and left shoulder flexion/extension isokinetic testing at 90 and 300º/s angular velocities and three countermovement jumps. Pearson correlation analysis showed that sprint times were moderate-largely negatively correlated with upper and lower limb strength and power (r ± 95%CI = 0.39 ± 0.26-0.77 ± 0.13, p  < 0.05). Elite swimmers higher strength levels were associated with longer stroke length in butterfly and front crawl, and with higher stroke rate in backstroke and breaststroke (r ± 95%CI = 0.37 ± 0.32-0.68 ± 0.21; p  < 0.05). Butterfly, backstroke and front crawl sprint times were moderate-largely negatively related with arm span (r ± 95%CI = 0.37 ± 0.26, 0.39 ± 0.25 and 0.69 ± 0.17, p  < 0.05). The predictive model indicated that higher dry-land strength values distinguished elite from non-elite swimmers (r 2  = 0.67-0.81; p  < 0.001). This association was not observed per performance level and per sex, confirming that sprint swimming performance levels can be differentiated by dry-land strength testing.

Study Objectives: Obstructive sleep apnea (OSA) and insomnia frequently co-occur, making diagnosis and treatment challenging. We investigated differences in sleep structure between patients with OSA, insomnia, and comorbid insomnia and sleep apnea (COMISA) to identify characteristics that can be used to improve the diagnosis of COMISA., Methods: We obtained polysomnography data of 326 patients from the Sleep and OSA Monitoring with Non-Invasive Applications database. The group included patients with OSA (n = 199), insomnia (n = 47), and COMISA (n = 80). We compared statistics related to sleep structure between the 3 patient groups., Results: Wake after sleep onset was significantly shorter for the OSA group (median: 60.0 minutes) compared to the COMISA (median: 83.3 minutes, P < .01) and the insomnia (median: 83.5 minutes, P = .01) groups. No significant differences were found in the total number of awakenings and the number of short (up to and including 2 minutes) and medium-length awakenings (2.5 up to and including 4.5 minutes). However, the number of long awakenings (5 minutes or longer) and wake after sleep onset containing only long awakenings was significantly lower for patients with OSA (median: 2 awakenings and 25.5 minutes) compared to patients with COMISA (median: 3 awakenings, P < .01 and 43.3 minutes, P < .001) or with insomnia (median: 3 awakenings, P < .01 and 56.0 minutes, P < .001). Total sleep time was significantly longer and sleep efficiency was significantly higher for the OSA group (median: 418.5 minutes and 84.4%) compared to both the COMISA (median: 391.5 minutes, P < .001 and 77.3%, P < .001) and the insomnia (median: 381.5 minutes, P < .001 and 78.2%, P < .001) groups. The number of sleep-stage transitions during the night for patients with COMISA (median: 194.0) was lower compared to that for patients with OSA (median: 218.0, P < .01) and higher compared to that for patients with insomnia (median: 156.0, P < .001). Other sleep architectural parameters were not discriminative between the groups., Conclusions: Patients with COMISA show specific characteristics of insomnia, including prolonged awakenings. This variable is distinctive in comparison to patients with OSA. The combination of prolonged awakenings and the presence of sleep-disordered breathing leads to increased sleep disturbance compared to patients having only 1 of the sleep disorders., Citation: Wulterkens BM, Hermans LWA, Fonseca P, et al. Sleep structure in patients with COMISA compared to OSA and insomnia. J Clin Sleep Med . 2023;19(6):1051-1059., (© 2023 American Academy of Sleep Medicine.)

Aim: To quantify the physiological demands and impact of muscle function t of the Fran workout, one of the most popular CrossFit benchmarks., Methods: Twenty experienced CrossFitters-16 male: 29 (6) years old and 4 female: 26 (5) years old- performed 3 rounds (with 30-s rests in between) of 21-21, 15-15, and 9-9 front squats to overhead press plus pull-up repetitions. Oxygen uptake and heart rate were measured at baseline, during the workout, and in the recovery period. Rating of perceived exertion, blood lactate, and glucose concentrations were assessed at rest, during the intervals, and in the recovery period. Muscular fatigue was also monitored at rest and at 5 minutes, 30 minutes, and 24 hours postexercise. Repeated-measures analysis of variance was performed to compare time points., Results: Aerobic (52%-29%) and anaerobic alactic (30%-23%) energy contributions decreased and the anaerobic lactic contribution increased (18%-48%) across the 3 rounds of the Fran workout. Countermovement jump height decreased by 8% (-12 to -3) mean change (95% CI), flight duration by 14% (-19 to -7), maximum velocity by 3% (-5 to -0.1), peak force 4% (-7 to -0.1), and physical performance (plank prone 47% [-54 to -38]) were observed., Conclusions: It appears that the Fran workout is a physically demanding activity that recruits energy from both aerobic and anaerobic systems. This severe-intensity workout evokes substantial postexercise fatigue and corresponding reduction in muscle function.

We characterized the physical and physiological profiles of high-level female Portuguese handball players and examined the relationships between their anthropometric characteristics, general motor performance and cardiopulmonary fitness. Twenty-four high-level female handball players with an average age of 23.6 ± 5.5 years, height of 173.6 ± 5.1 cm and body mass of 72.6 ± 9.1 kg volunteered to participate. A Pearson correlation test was used to assess the relationship between variables. Direct relationships were observed between the players' height and arm span (r = 0.741), as well as between their squat jump and countermovement jump performances with regard to body mass (r = 0.448 and 0.496, respectively). The 9 m jump shot has a large relationship with the 7 m standing throw (r = 0.786) and between left hand dynamometry and body mass index (r = 0.595). The 30 m sprint has a relationship with the 7 m standing throw (r = -0.526) and the 9 m jump throw (r = -0.551). Oxygen uptake has a relationship with the players' height (r = -0.482) and time limit (r = 0.513), while the fitness index has a relation to the players' height (r = -0.488) and arm span (r = -0.422). Our results should be considered when using physical testing to plan optimal physical training regimens in elite team handball., Competing Interests: The authors declare no conflicts of interest.

Understanding the mechanisms that shape the architecture, diversity, and adaptations of genomes and their ecological and genetic interfaces is of utmost importance to understand biological evolution. Transposable elements (TEs) play an important role in genome evolution, due to their ability to transpose within and between genomes, providing sites of nonallelic recombination. Here we investigate patterns and processes of TE-driven genome evolution associated with niche diversification. Specifically, we compared TE content, TE landscapes, and frequency of horizontal transposon transfers (HTTs) across genomes of flower-breeding Drosophila (FBD) with different levels of specialization on flowers. Further, we investigated whether niche breadth and ecological and geographical overlaps are associated with a potential for HTT rates. Landscape analysis evidenced a general phylogenetic pattern, in which species of the D. bromeliae group presented L-shaped curves, indicating recent transposition bursts, whereas D. lutzii showed a bimodal pattern. The great frequency of highly similar sequences recovered for all FBD suggests that these species probably experienced similar ecological pressures and evolutionary histories that contributed to the diversification of their mobilomes. Likewise, the richness of TEs superfamilies also appears to be associated with ecological traits. Furthermore, the two more widespread species, the specialist D. incompta and the generalist D. lutzii, presented the highest frequency of HTT events. Our analyses also revealed that HTT opportunities are positively influenced by abiotic niche overlap but are not associated with phylogenetic relationships or niche breadth. This suggests the existence of intermediate vectors promoting HTTs between species that do not necessarily present overlapping biotic niches., (© The Author(s) 2023. Published by Oxford University Press on behalf of Society for Molecular Biology and Evolution.)

In investigating the influence of body movement in multimodal perception, human motion displays are frequently used as a means of visual standardization and control of external confounders. However, no principle is established regarding the selection of an adequate display for specific study purposes. The aim of this study was to evaluate the effects of adopting 4 visual displays (point-light, stick figure, body mass, skeleton) on the observers' perception of music performances in 2 expressive conditions (immobile, projected expressiveness). Two hundred eleven participants rated 8 audio-visual samples in expressiveness, match between movement and music, and overall evaluation. The results revealed significant isolated main effects of visual display and expressive condition on the observers' ratings (in both, p < 0.001), and interaction effects between the two factors (p < 0.001). Displays closer to a human form (mostly skeleton, sometimes body mass) exponentiated the evaluations of expressiveness and music-movement match in the projected expressiveness condition, and of overall evaluation in the immobile condition; the opposite trend occurred with the simplified motion display (stick figure). Projected expressiveness performances were higher rated than immobile performances. Although the expressive conditions remained distinguishable across displays, the more complex ones potentiated the attribution of subjective qualities. We underline the importance of considering the variable display as an influencing factor in perceptual studies., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Moura et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Leber's Hereditary Optic Neuropathy (LHON) has been mainly (90-95 %) associated to one of three variants: m.3460G>A, m.11778G>A, m.14484T>C. Herein, a screening method was developed for its detection, supporting clinical/therapeutics decision. It relies on real-time PCR with High-Resolution Melting (HRM) analysis. Variant classification is made using HRM Software and quality controls. A total of 101 samples were analyzed. All samples were correctly assigned: 58 wild-type, 35 positive for m.11778G>A, 6 positive for m.14484T>C, 2 positive for m.3460G>A. Results presented sensitivity = 1, specificity = 1, Positive Predictive Value = 1 and Negative Predictive Value = 1. A new Real-Time PCR/HRM screening method cost-efficient, simple, robust and quick, detecting LHON's top-3 is described., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Author(s). Published by Elsevier B.V. All rights reserved.)