Hybrid modeling of an ultracentrifugation process for separation of full and empty adeno-associated virus particles.

Ultracentrifugation is an attractive method for separating full and empty capsids, exploiting their density difference. Changes of the serotype/capsid, density of loading material, or the genetic information contained in the adeno-associated viruses (AAVs) require the adaptation of the harvesting parameters and the density gradient loaded onto the centrifuge. To streamline these adaptations, a mathematical model could support the design and testing of operating conditions.Here, hybrid models, which combine empirical functions with artificial neural networks, are proposed to describe the separation of full and empty capsids as a function of material and operational parameters, i.e., the harvest model. In addition, critical quality attributes are estimated by a quality model which is operating on top of the harvest model. The performance of these models was evaluated using test data and two additional blind runs. Also, a "what-if" analysis was conducted to investigate whether the models' predictions align with expectations.It is concluded that the models are sufficiently accurate to support the design of operating conditions, though the accuracy and applicability of the models can further be increased by training them on more specific data with higher variability.

Advances in life-history knowledge for 35 seahorse species from community science.

Marine community science presents an important route to gather valuable scientific information while also influencing local management and policy, thus contributing to marine conservation efforts. Because seahorses are cryptic but charismatic species, they are good candidates for engaging diverse people to help overcome the many gaps in biological knowledge. We have synthesized information contributed to the community science project iSeahorse from October 2013 to April 2022 for 35 of 46 known seahorse species. We then compared the obtained results with information in existing IUCN Red List assessments, executed from 2014 to 2017, to explore the potential of iSeahorse in expanding seahorse knowledge. Our results show updated geographic ranges for 7 seahorse species, new habitats described for 24 species, observations outside the previously recorded depth range for 14 species, and new information on sex ratio for 15 species and on pregnancy seasonality for 11 species. As one example of the power of iSeahorse, contributed observations on Coleman's pygmy seahorse (Hippocampus colemani) indicated that its geographic range is thousands of square kilometers larger, its habitat more diverse, and its depth range shallower than previously known. It is clear that iSeahorse is expanding knowledge on seahorses to a level that will help improve IUCN Red List assessments. The power of community science for marine conservation in general needs to be fully explored.

Minding your steps: a cross-sectional pilot study using foot-worn inertial sensors and dual-task gait analysis to assess the cognitive status of older adults with mobility limitations.

BACKGROUND: Cognitive impairment is a critical aspect of our aging society. Yet, it receives inadequate intervention due to delayed or missed detection. Dual-task gait analysis is currently considered a solution to improve the early detection of cognitive impairment in clinical settings. Recently, our group proposed a new approach for the gait analysis resorting to inertial sensors placed on the shoes. This pilot study aimed to investigate the potential of this system to capture and differentiate gait performance in the presence of cognitive impairment based on single- and dual-task gait assessments. METHODS: We analyzed demographic and medical data, cognitive tests scores, physical tests scores, and gait metrics acquired from 29 older adults with mobility limitations. Gait metrics were extracted using the newly developed gait analysis approach and recorded in single- and dual-task conditions. Participants were stratified into two groups based on their Montreal Cognitive Assessment (MoCA) global cognitive scores. Statistical analysis was performed to assess differences between groups, discrimination ability, and association of gait metrics with cognitive performance. RESULTS: The addition of the cognitive task influenced gait performance of both groups, but the effect was higher in the group with cognitive impairment. Multiple dual-task costs, dual-task variability, and dual-task asymmetry metrics presented significant differences between groups. Also, several of these metrics provided acceptable discrimination ability and had a significant association with MoCA scores. The dual-task effect on gait speed explained the highest percentage of the variance in MoCA scores. None of the single-task gait metrics presented significant differences between groups. CONCLUSIONS: Our preliminary results show that the newly developed gait analysis solution based on foot-worn inertial sensors is a pertinent tool to evaluate gait metrics affected by the cognitive status of older adults relying on single- and dual-task gait assessments. Further evaluation with a larger and more diverse group is required to establish system feasibility and reliability in clinical practice. TRIAL REGISTRATION: ClinicalTrials.gov (identifier: NCT04587895).

Detection of Intermittent Claudication from Smartphone Inertial Data in Community Walks Using Machine Learning Classifiers.

Peripheral arterial disease (PAD) causes blockage of the arteries, altering the blood flow to the lower limbs. This blockage can cause the individual with PAD to feel severe pain in the lower limbs. The main contribution of this research is the discovery of a solution that allows the automatic detection of the onset of claudication based on data analysis from patients' smartphones. For the data-collection procedure, 40 patients were asked to walk with a smartphone on a thirty-meter path, back and forth, for six minutes. Each patient conducted the test twice on two different days. Several machine learning models were compared to detect the onset of claudication on two different datasets. The results suggest that we can identify the onset of claudication using inertial sensors with a best case accuracy of 92.25% for the Extreme Gradient Boosting model.

Androglobin gene expression patterns and FOXJ1-dependent regulation indicate its functional association with ciliogenesis.

Androglobin (ADGB) represents the latest addition to the globin superfamily in metazoans. The chimeric protein comprises a calpain domain and a unique circularly permutated globin domain. ADGB expression levels are most abundant in mammalian testis, but its cell-type-specific expression, regulation, and function have remained unexplored. Analyzing bulk and single-cell mRNA-Seq data from mammalian tissues, we found that-in addition to the testes-ADGB is prominently expressed in the female reproductive tract, lungs, and brain, specifically being associated with cell types forming motile cilia. Correlation analysis suggested coregulation of ADGB with FOXJ1, a crucial transcription factor of ciliogenesis. Investigating the transcriptional regulation of the ADGB gene, we characterized its promoter using epigenomic datasets, exogenous promoter-dependent luciferase assays, and CRISPR/dCas9-VPR-mediated activation approaches. Reporter gene assays revealed that FOXJ1 indeed substantially enhanced luciferase activity driven by the ADGB promoter. ChIP assays confirmed binding of FOXJ1 to the endogenous ADGB promoter region. We dissected the minimal sequence required for FOXJ1-dependent regulation and fine mapped the FOXJ1 binding site to two evolutionarily conserved regions within the ADGB promoter. FOXJ1 overexpression significantly increased endogenous ADGB mRNA levels in HEK293 and MCF-7 cells. Similar results were observed upon RFX2 overexpression, another key transcription factor in ciliogenesis. The complex transcriptional regulation of the ADGB locus was illustrated by identifying a distal enhancer, responsible for synergistic regulation by RFX2 and FOXJ1. Finally, cell culture studies indicated an ADGB-dependent increase in the number of ciliated cells upon overexpression of the full-length protein, confirming a ciliogenesis-associated role of ADGB in mammals.

A systematic review with meta-analysis of the diagnostic test accuracy of pedicle screw electrical stimulation.

PURPOSE: To provide a systematic review with meta-analysis providing evidence of the current diagnostic test accuracy (DTA) of pedicle screw electrical stimulation. METHODS: A systematic database search on PubMed, Scopus and Web of Science was performed according to the PRISMA-DTA guidelines, and eligibility criteria applied to reduce the results to: (1) only journal articles reporting electrical stimulation of the pedicle screw head, (2) screw position confirmation by imaging techniques, and (3) enough information allowing the calculation of a 2 × 2 contingency table. Sample characteristics, image confirmation method, electrical current threshold and stimulation results were retrieved and analyzed using according to appropriate DTA analysis methods, and allowing the calculation of specificity, sensitivity for pedicle screws insertion at the lumbar and thoracic levels. RESULTS: Lumbar screw stimulation presents a higher sensitivity (0.586 [0.336, 0.798] and specificity (0.984 [0.958, 0.994]) than thoracic screws (sensitivity: 0.270 [0.096; 0.562]; specificity: 0.958 [0.931, 0.975]). The same is observed in terms of the diagnostic odds ratio for lumbar (88.32 [32.136, 242.962]) and thoracic (8.460 [2.139, 33.469]) levels. When performing a sub-group analysis, it is possible to divide the lumbar stimulation threshold as 8 and 10-12 mA, and the thoracic threshold as 6 and 9-12 mA. A threshold of 8 mA at the lumbar level provides higher sensitivity and specificity. Increasing the threshold results in higher specificity but not sensitivity. In fact, at the range of 10-12 mA, the diagnostic validity is too low to confer this technique any robust diagnostic validity. Similarly, at the thoracic level, lower threshold currents are associated with increased sensitivity, but their diagnostic validity is very low. CONCLUSION: Electrical stimulation of the pedicle screw can be used as an adequate diagnostic capability at the lumbar level with a threshold of 8 mA. However, thoracic stimulation is currently not reliable, with very low sensitivity and diagnostic validity at 6 mA or higher.

Identity Recognition in Sanitary Facilities Using Invisible Electrocardiography.

This article proposes a new method of identity recognition in sanitary facilities based on electrocardiography (ECG) signals. Our team previously proposed a novel approach of invisible ECG at the thighs using polymeric electrodes, leading to the creation of a proof-of-concept system integrated into a toilet seat. In this work, a biometrics pipeline was devised, which tested four different classifiers, varying the population from 2 to 17 subjects and simulating a residential environment. However, for this approach to be industrially viable, further optimization is required, particularly regarding electrode materials that are compatible with industrial processes. As such, we also explore the use of a conductive silicone material as electrodes, aiming at the industrial-scale production of a toilet seat capable of recording ECG data, without the need for body-worn devices. A desirable aspect when using such a system is matching the recorded data with the monitored user, ideally using a minimal sensor set, further reinforcing the relevance of user identification through ECG signals collected at the thighs. Our approach was evaluated against a reference device for a population of 17 healthy and pathological individuals, covering a wide age range (24-70 years). With the silicone composite, we were able to acquire signals in 100% of the sessions, with a mean heart rate deviation between a reference system and our experimental device of 2.82 ± 1.99 beats per minute (BPM). In terms of ECG waveform morphology, the best cases showed a Pearson correlation coefficient of 0.91 ± 0.06. For biometric detection, the best classifier was the Binary Convolutional Neural Network (BCNN), with an accuracy of 100% for a population of up to four individuals.

Plateau Waves of Intracranial Pressure: Methods for Automatic Detection and Prediction.

Plateau waves are recurrent phenomena observed in traumatic brain injury (TBI) patients, characterised by an increase in intracranial pressure (ICP) above 40 mmHg combined with an almost zero arterial blood pressure (ABP) variation and, hence, a decrease in cerebral perfusion pressure (CPP). A raised ICP for a long period of time, namely plateau waves, can lead to a secondary brain injury. Due to the impaired cerebral autoregulation mechanism these TBI patients present, they are admitted to neurocritical care units (NCCUs) to be under continuous multimodal monitoring, which allows a correct diagnosis for each patient. Plateau waves can end naturally by activating a vasoconstriction mechanism which decreases the amount of blood available in the brain. Alternatively, the phenomenon can end with therapeutic treatment.In this sense, the present study consists in the development of an algorithm capable of automatically detecting plateau waves using offline data, i.e. data already collected from patients. This creates an extra tool which allows for faster detection of events to assist their identification and final diagnosis. Despite the additional steps that can be included to improve the algorithm, the results show good performance, and thus it may be applied in NCCUs.

A Deep Learning Approach for Foot Trajectory Estimation in Gait Analysis Using Inertial Sensors.

Gait performance is an important marker of motor and cognitive decline in older adults. An instrumented gait analysis resorting to inertial sensors allows the complete evaluation of spatiotemporal gait parameters, offering an alternative to laboratory-based assessments. To estimate gait parameters, foot trajectories are typically obtained by integrating acceleration two times. However, to deal with cumulative integration errors, additional error handling strategies are required. In this study, we propose an alternative approach based on a deep recurrent neural network to estimate heel and toe trajectories. We propose a coordinate frame transformation for stride trajectories that eliminates the dependency from previous strides and external inputs. Predicted trajectories are used to estimate an extensive set of spatiotemporal gait parameters. We evaluate the results in a dataset comprising foot-worn inertial sensor data acquired from a group of young adults, using an optical motion capture system as a reference. Heel and toe trajectories are predicted with low errors, in line with reference trajectories. A good agreement is also achieved between the reference and estimated gait parameters, in particular when turning strides are excluded from the analysis. The performance of the method is shown to be robust to imperfect sensor-foot alignment conditions.

Orientation-Invariant Spatio-Temporal Gait Analysis Using Foot-Worn Inertial Sensors.

Inertial sensors can potentially assist clinical decision making in gait-related disorders. Methods for objective spatio-temporal gait analysis usually assume the careful alignment of the sensors on the body, so that sensor data can be evaluated using the body coordinate system. Some studies infer sensor orientation by exploring the cyclic characteristics of walking. In addition to being unrealistic to assume that the sensor can be aligned perfectly with the body, the robustness of gait analysis with respect to differences in sensor orientation has not yet been investigated-potentially hindering use in clinical settings. To address this gap in the literature, we introduce an orientation-invariant gait analysis approach and propose a method to quantitatively assess robustness to changes in sensor orientation. We validate our results in a group of young adults, using an optical motion capture system as reference. Overall, good agreement between systems is achieved considering an extensive set of gait metrics. Gait speed is evaluated with a relative error of -3.1±9.2 cm/s, but precision improves when turning strides are excluded from the analysis, resulting in a relative error of -3.4±6.9 cm/s. We demonstrate the invariance of our approach by simulating rotations of the sensor on the foot.

Invisible ECG for High Throughput Screening in eSports.

eSports is a rapidly growing industry with increasing investment and large-scale international tournaments offering significant prizes. This has led to an increased focus on individual and team performance with factors such as communication, concentration, and team intelligence identified as important to success. Over a similar period of time, personal physiological monitoring technologies have become commonplace with clinical grade assessment available across a range of parameters that have evidenced utility. The use of physiological data to assess concentration is an area of growing interest in eSports. However, body-worn devices, typically used for physiological data collection, may constitute a distraction and/or discomfort for the subjects. To this end, in this work we devise a novel "invisible" sensing approach, exploring new materials, and proposing a proof-of-concept data collection system in the form of a keyboard armrest and mouse. These enable measurements as an extension of the interaction with the computer. In order to evaluate the proposed approach, measurements were performed using our system and a gold standard device, involving 7 healthy subjects. A particularly advantageous characteristic of our setup is the use of conductive nappa leather, as it preserves the standard look and feel of the keyboard and mouse. According to the results obtained, this approach shows 3-15% signal loss, with a mean difference in heart rate between the reference and experimental device of -1.778 ± 4.654 beats per minute (BPM); in terms of ECG waveform morphology, the best cases show a Pearson correlation coefficient above 0.99.

Field studies of seahorse population density, structure and habitat use in a semi-closed north-eastern Mediterranean marine area (Stratoni, North Aegean Sea).

The present study was carried out in the marine area of Stratoni, Greece, where two seahorse species are present (Hippocampus hippocampus and Hippocampus guttulatus). Two surveys were conducted (September 2016 and May 2019) to gather information regarding seahorse species' abundance, distribution and habitat characteristics. Four different seahorse natural and artificial habitat types were identified. The results revealed that the presence of H. hippocampus was relatively high, especially at sites with artificial structures, whereas the presence of H. guttulatus was rare. Data collected can provide baseline information for future population assessments.

Low-cost wearable data acquisition for stroke rehabilitation: a proof-of-concept study on accelerometry for functional task assessment.

BACKGROUND: An increasingly aging society and consequently rising number of patients with poststroke-related neurological dysfunctions are forcing the rehabilitation field to adapt to ever-growing demands. Although clinical reasoning within rehabilitation is dependent on patient movement performance analysis, current strategies for monitoring rehabilitation progress are based on subjective time-consuming assessment scales, not often applied. Therefore, a need exists for efficient nonsubjective monitoring methods. Wearable monitoring devices are rapidly becoming a recognized option in rehabilitation for quantitative measures. Developments in sensors, embedded technology, and smart textile are driving rehabilitation to adopt an objective, seamless, efficient, and cost-effective delivery system. This study aims to assist physiotherapists' clinical reasoning process through the incorporation of accelerometers as part of an electronic data acquisition system. METHODS: A simple, low-cost, wearable device for poststroke rehabilitation progress monitoring was developed based on commercially available inertial sensors. Accelerometry data acquisition was performed for 4 first-time poststroke patients during a reach-press-return task. RESULTS: Preliminary studies revealed acceleration profiles of stroke patients through which it is possible to quantitatively assess the functional movement, identify compensatory strategies, and help define proper movement. CONCLUSION: An inertial data acquisition system was designed and developed as a low-cost option for monitoring rehabilitation. The device seeks to ease the data-gathering process by physiotherapists to complement current practices with accelerometry profiles and aid the development of quantifiable methodologies and protocols.

Sit4 Genetically Interacts with Vps27 to Regulate Mitochondrial Function and Lifespan in Saccharomyces cerevisiae.

The Sit4 protein phosphatase plays a key role in orchestrating various cellular processes essential for maintaining cell viability during aging. We have previously shown that SIT4 deletion promotes vacuolar acidification, mitochondrial derepression, and oxidative stress resistance, increasing yeast chronological lifespan. In this study, we performed a proteomic analysis of isolated vacuoles and yeast genetic interaction analysis to unravel how Sit4 influences vacuolar and mitochondrial function. By employing high-resolution mass spectrometry, we show that sit4Δ vacuolar membranes were enriched in Vps27 and Hse1, two proteins that are part of the endosomal sorting complex required for transport-0. In addition, SIT4 exhibited a negative genetic interaction with VPS27, as sit4∆vps27∆ double mutants had a shortened lifespan compared to sit4∆ and vps27∆ single mutants. Our results also show that Vps27 did not increase sit4∆ lifespan by improving protein trafficking or vacuolar sorting pathways. However, Vps27 was critical for iron homeostasis and mitochondrial function in sit4∆ cells, as sit4∆vps27∆ double mutants exhibited high iron levels and impaired mitochondrial respiration. These findings show, for the first time, cross-talk between Sit4 and Vps27, providing new insights into the mechanisms governing chronological lifespan.

Ultrasound-Guided Radiofrequency Ablation for Chronic Hip Pain Due to Osteoarthritis.

BACKGROUND AND AIMS: Hip osteoarthritis (OA) has a prevalence of 2.9% in Portugal and is a related cause of pain and disability. A sufficient number of patients report these symptoms even after total hip arthroplasty (THA), while others are contraindicated to such surgery and suffer from uncontrolled pain. Percutaneous denervation of hip nerve branches using radiofrequency ablation (RFA) has emerged as a powerful therapeutic avenue to consider for patients with chronic hip pain. METHODS: Between January 2020 and March 2021, 26 patients with chronic hip pain received ultrasound-guided RFA with a pericapsular nerve group (PENG) block technique adaptation. Patients suffering from chronic hip pain for more than three months with radiographic evidence of osteoarthritis were included. A numeric rating scale (NRS) and pain medication reduction were defined as outcome variables assessed before treatment and at three-, six-, nine-, and 12-month follow-ups. RESULTS: All selected patients underwent the procedure. All the patients had hip osteoarthritis. Twelve-month follow-up data revealed a statistically significant decrease in the numeric rating scale. The mean NRS for pain was 2 after the procedure. Over 75% of patients reported >50% pain relief during the follow-up and 85% reduced pain medication consumption. No side effects were reported. CONCLUSION: Hip sensory articular branch RFA is a treatment option with interesting outcomes for chronic hip pain, as demonstrated by our study.

Parsonage-Turner Syndrome Post-COVID-19 Oxford/AstraZeneca Vaccine Inoculation: A Case Report and Brief Literature Review.

Parsonage-Turner syndrome (PTS) is a rare brachial plexus neuropathy that typically presents as a severe, sudden-onset pain followed by atrophic weakness with slow recovery, which may occur after an identifiable triggering event. Vaccination is one of several known triggers of PTS, and this syndrome has already been reported in other patients who were vaccinated against coronavirus disease. We report the case of a 75-year-old Caucasian man who received the third dose of the coronavirus disease 2019 (COVID-19) Oxford/AstraZeneca vaccine and was diagnosed with PTS. A week after inoculation, the patient, with no history of trauma, developed a sudden-onset left shoulder mechanical pain and later reported an abduction deficit. Neurological examination showed an atrophy of the proximal muscles of the left upper limb. No bulbar weakness or pathological upper motor neuron signs were seen. The MRI excluded rotator cuff pathology, including ruptures and tendinopathy. Electroneuromyography findings carried out 10 months after the onset of symptoms indicated left brachial panplexopathy, suggestive of PTS. The raised consciousness of PTS and vaccine association is crucial for prompt identification and diagnosis and, therefore, better clinical outcomes.

Carbon Conductive Paste Smart Textile Strain Sensor for Sports and Rehabilitation.

Due to the growth observed in the wearable market, stretchable strain sensors have been the focus of several studies. However, combining high sensitivity and linearity with low hysteresis presents a difficult challenge.Here, we propose a stretchable strain sensor obtained with off-the-shelf materials by printing a carbon conductive paste into a piece of fabric to be integrated into a smart garment. This process is cheap and easily scalable, allowing its mass production. The sensor developed has a large sensitivity (GF=11.27), high linearity (R2>0.99), very low hysteresis (γH =4.23%) and brings an added value, for example, in sports or rehabilitation monitoring.

Using shoe-mounted inertial sensors and stepping exergames to assess the motor-cognitive status of older adults: A correlational study.

Objective: Stepping exergames designed to stimulate physical and cognitive skills can provide important information concerning individuals' performance. In this study, we investigated the potential of stepping and gameplay metrics to assess the motor-cognitive status of older adults. Methods: Stepping and gameplay metrics were recorded in a longitudinal study involving 13 older adults with mobility limitations. Game parameters included games' scores and reaction times. Stepping parameters included length, height, speed, and duration, measured by inertial sensors placed on the shoes while interacting with the exergames. Parameters measured on the first gameplay were correlated against standard cognitive and mobility assessments, including the Montreal Cognitive Assessment (MoCA), gait speed, and the Short Physical Performance Battery. Based on MoCA scores, patients were then stratified into two groups: cognitively impaired and healthy controls. The differences between the two groups were visually inspected, considering their within-game progression over the training period. Results: Stepping and gameplay metrics had moderate-to-strong correlations with cognitive and mobility performance indicators: faster, longer, and higher steps were associated with better mobility scores; better cognitive games' scores and reaction times, and longer and faster steps were associated with better cognitive performance. The preliminary visual analysis revealed that the group with cognitive impairment required more time to advance to the next difficulty level, also presenting slower reaction times and stepping speeds when compared to the healthy control group. Conclusion: Stepping exergames may be useful for assessing the cognitive and motor status of older adults, potentially allowing assessments to be more frequent, affordable, and enjoyable. Further research is required to confirm results in the long term using a larger and more diverse sample.