Vitalograph (Ireland)

Hundreds of domes are scattered over a plain composed of different geological units in the western margin of Utopia Planitia, near the northern martian dichotomy. These structures have traditionally been considered of igneous origin. In this work, we utilized recent data to study the geomorphological and compositional properties of this dome field. We found that the domes originated from an intrusive-to-extrusive system, since they range from cryptodomes to volcanic domes. Each dome appears to represent a single magmatic event, indicating they formed in a monogenetic regime. Two main groups of domes were identified according to their shapes and stratigraphic relationships with the floor units, which represent two different stages of igneous activity. It was established from a linear analysis that the domes are preferentially aligned following a NW-SE trend, which is consistent with the regional faults and fractures. The domes field in Utopia Planitia was likely created by two monogenetic magmatic events at different ages, which took advantage of the tectonic configuration of the area to be emplaced. Some magmas were able to reach the surface creating extrusive structures, while the majority crystalized near the surface creating intrusive ones. Of the last group, the majority were uncovered by tectonic or erosive processes, while a small number of them remained trapped underground as cryptodomes. This sequence of events would explain the large distribution of the domes, as well as the wide variety of morphologies that we observe today. • The domes in Utopia Planitia are likely igneous due to their morphological properties. • The domes in Utopia Planitia were formed by two magmatic pulses at different times. • A distribution analysis showed that the intrusions used fractures to raise. • This might be one of the youngest large volcanics event in this location of Mars.

<h3>Background</h3> Previous analyses from the AX8–003 clinical study indicated that in patients with refractory or unexplained chronic cough (RCC/UCC) and throat discomfort (baseline visual analogue scale [VAS] score ≥55 mm), the TRPM8 agonist AX-8 reduced bout frequency (cough bouts are defined as clusters of ≥2 coughs separated by ≤2 seconds),¹ more effectively than cough frequency. This study further explores how AX-8 preferentially targets bouts, examining detailed count- and duration-based metrics. <h3>Methods</h3> This was a randomized, double-blind, placebo-controlled crossover study of RCC/UCC patients (≥1 year cough duration, cough severity VAS score ≥40 mm, and 24h cough frequency ≥10 coughs/h at screening). In the throat discomfort subgroup (n=24), we compared the effect of AX-8 (40 mg orally disintegrating tablet BID) versus placebo on cough and bout frequencies, as previously, as well as on single and bout cough frequencies, mean number of coughs per bout, and total and mean bout durations. Analyses below focus on the 4-hour period following the first dose on day 1. <h3>Results</h3> AX-8 showed a non-significant decrease in single cough frequency (15.5%, p&gt;0.2) but significantly reduced bout cough frequency (50.4%, p=0.001) without affecting the number of coughs per bout (p&gt;0.2). Placebo, conversely, moderately reduced the number of coughs per bout. In terms of cough duration, AX-8 significantly lowered the total bout duration (51.4%, p&lt;0.01), primarily by reducing bout frequency (p&lt;0.001) but not the mean bout duration (p&gt;0.1). In contrast, placebo’s small benefit arose from shortening the mean bout duration. <h3>Conclusion</h3> These data demonstrate that AX-8 selectively targets the initiation of bouts rather than single coughs, which are less important for RCC/UCC patients. The different effects of AX-8 and placebo on bout characteristics may reflect distinct underlying neurophysiological mechanisms. <h3>Clinical Trial Registry</h3> NCT04866563 <h3>Reference</h3> Holt KJ, <i>et al. ERJ Open Res.</i> 2024;<b>10</b>(6):00316–2024. https://doi.org/10.1183/23120541.00316-2024

Abstract Body-worn sensors have contributed to a rich and growing body of literature in public health and clinical research in the last decades. The translation of these research findings to clinical application, however, is lagging. A major challenge is the lack of consistency and standardization of the collection and reporting of the sensor data. In the case of accelerometer, the most used body-worn sensor, device manufacturers provided “activity counts” as a summary of total acceleration for each 5s to 60s epoch of data collected. The algorithms used to derive these activity counts can be vastly different between manufactures and not always transparent to the researchers. This discrepancy in “activity counts” can lead to confusion and misuse of actigraphy data in research and make it challenging to compare data collected from different devices. With Philips, one of the major research-grade wearable device manufacturers, discontinuing this product line, many researchers are left in need of alternative solutions and at the risk of not being able to relate their historical data using Philips devices to future findings with other devices. Recognizing this gap and urgent needs, we here provide a comparison analysis and conversion method that can be used to convert activity counts from Philips to those from ActiGraph, another major manufacturer who provide both raw acceleration data and open-source count algorithm to the research community. This work provides an approach to maximize the scientific value of actigraphy data collected by Philips devices to support research continuity in this community. The conversion, however, is not perfect and only offers a proximation, due to the intrinsic difference in the count algorithms between ActiGraph and Philips, and the permanent information loss during data reduction. We encourage future research using body-worn sensors retain raw sensor data as the source data to ensure data consistency, comparability, and the ability to leverage future algorithm improvement.

Alzheimer's disease (AD) is a neurodegenerative disease that impairs multiple memory domains without an effective prevention or treatment approach. Amyloid plaque-induced neuroinflammation exacerbates neurodegeneration and cognitive impairment in AD. To reduce neuroinflammation, we applied prebiotics or synbiotics to modulate the gut-brain axis in the AD mouse model. AD-like deficits were reduced in mice treated with synbiotics, suggesting that dietary modulation of the gut-brain axis is a potential approach to delay AD progression.

<b>Background:</b> The VitaloJAK cough monitor is an approved ambulatory medical device that records sound simultaneously from a chest wall contact microphone and free-field lapel microphone to quantify coughing in clinical trials. A digital signal processing algorithm (WH03_V3.0) utilises both microphones data (dual processing) to identify coughs and remove non-cough sounds, thereby reducing the time taken to count the number of coughs. The wearing of face masks/coverings during the Covid-19 pandemic distorts sounds from the lapel microphone but not the contact sensor. <b>Aim:</b> We investigated the utility of an algorithm using only the contact microphone data for cough detection and removal of non-cough sounds (WH03_V3.03). <b>Methods:</b> 24h sound recordings from 60 patients with refractory chronic cough underwent both single and dual channel processing. The performance of each algorithm was assessed by the ability to retain coughs pre-identified by manual counting of the 24h recordings (sensitivity) and filter out non-cough sounds (reduction in recording length). <b>Results:</b> Dual channel processing had a median sensitivity of 99.7%(IQR 99.0-100) and shortened the 24h file to a median 114.5mins(154.8-70.8), 7.9% of the 24h. Single channel processing (contact sensor only) maintained sensitivity, median 100%(99.7-100.0), but reduced filtering efficiency, file length 197.3mins(151.5-262.7), 13.7%. Single channel processing has been implemented in up to 50% of monthly cough analysis during the pandemic, maintaining data integrity ≥98%. <b>Conclusion:</b> Processing of contact microphone data is an acceptable alternative for the VitaloJAK cough monitoring system, however the accuracy of systems reliant on free-field microphones may be compromised during the pandemic.

The anti-programmed cell death protein-1 (PD-1) immune checkpoint inhibitor nivolumab is currently approved for the treatment of patients with metastatic renal cell carcinoma (mRCC); approximately 25% of patients respond. We hypothesized that we could identify a biomarker of response using radiomics to train a machine learning classifier to predict nivolumab response outcomes. Patients with mRCC of different histologies treated with nivolumab in a single institution between 2013 and 2017 were retrospectively identified. Patients were labelled as responders (complete response [CR]/partial response [PR]/durable stable disease [SD]) or non-responders based on investigator tumor assessment using RECIST 1.1 criteria. For each patient, lesions were contoured from pre-treatment and first post-treatment computed tomography (CT) scans. This information was used to train a radial basis function support vector machine classifier to learn a prediction rule to distinguish responders from non-responders. The classifier was internally validated by a 10-fold nested cross-validation. Thirty-seven patients were identified; 27 (73%) met the inclusion criteria. One hundred and four lesions were contoured from these 27 patients. The median patient age was 56 years, 78% were male, 89% had clear-cell histology, 89% had prior nephrectomy, and 89% had prior systemic therapy. There were 19 responders vs. eight non-responders. The lesions selected were lymph nodes (60%), lung metastases (23%), and renal/adrenal metastases (17%). For the classifier trained on the baseline CT scans, 69% accuracy was achieved. For the classifier trained on the first post-treatment CT scans, 66% accuracy was achieved. The set of radiomic signatures was found to have limited ability to discriminate nivolumab responders from non-responders. The use of novel texture features (two-point correlation measure, two-point cluster measure, and minimum spanning tree measure) did not improve performance.

Narrow linewidth tunable diode lasers are an important tool for spectroscopic instrumentation. Conventional external cavity diode lasers are designed as laboratory instrument and do not allow hand-held operation for portable instruments. A new miniaturized type of tunable external cavity tunable diode laser will be presented. The presentation will focus on requirements on the assembly technology of micro-optic components as well as on the physical properties of such devices. Examples for the realization of this new technology will be given in the NIR for Alkaline Spectroscopy as well as in the MIR at 1908nm.

The UK Refractory Asthma Stratification Programme (RASP-UK) will explore novel biomarker stratification strategies in severe asthma to improve clinical management and accelerate development of new therapies. Prior asthma mechanistic studies have not stratified on inflammatory phenotype and the understanding of pathophysiological mechanisms in asthma without Type 2 cytokine inflammation is limited. RASP-UK will objectively assess adherence to corticosteroids (CS) and examine a novel composite biomarker strategy to optimise CS dose; this will also address what proportion of patients with severe asthma have persistent symptoms without eosinophilic airways inflammation after progressive CS withdrawal. There will be interactive partnership with the pharmaceutical industry to facilitate access to stratified populations for novel therapeutic studies.