The increasing use of ionizing radiation has raised concerns about adverse and long-term health risks for individuals. Therefore, to evaluate the range of risks and protection against ionizing radiation, it is necessary to assess the dosimetry calculation uncertainty of the absorbed dose of organs and tissues in the body. On the other hand, absorbed dose calculation with low computational load plays a noted role in dosimetry studies. Considering the Monte Carlo simulation's time-consuming and high computational cost, we present a novel model-based organ dosimetry for uncertainty evaluation. We attempt to model and estimate the organ-absorbed dose for lung organ size by combining computational phantoms and ANFIS. Two input variables were used, including variations in lung size and photon energy. The results showed that the proposed hybrid approach increased the speed of evaluation of the uncertainty of dosimetry calculations. The promising results of the hybrid approach demonstrate that it can be a suitable alternative to the time-consuming conventional methods of dosimetry calculations in dosimetry calculations, which will lead to the development of a rapid and reliable tool for organ dose estimation in dosimetry applications in the future.

Neuropathic pain is a significant therapeutic challenge due to the co-occurrence with other neurological symptoms such as paresthesia. Human-based models such as cuff algometry can enhance our understanding of pain-paresthesia relationships. This experiment aimed to characterize (psychophysically) pain and paresthesia evoked by stimuli of different temporal and intensity parameters and to demonstrate the reliability of experimental induction of these two symptoms using cuff algometry. Forty participants, aged 18-35, were exposed to mechanical pressure stimuli at three intensities (100, 150, 200 mmHg) and three durations (90, 120, 150 s). Skin Conductance (SC) was continuously monitored, and participants rated pain and paresthesia in real-time using a computerized visual analog scale. The General Linear Model analysis revealed significant differences in paresthesia across all durations (p<0.01), but not all intensities, as paresthesia did not increase from 150 to 200 mmHg (p>0.05). Conversely, pain responses showed significant differences across all pressure intensities (p<0.05) but not durations, as pain did not increase from 90 to 120 and from 120 to 150 s (p>0.05). No interaction effects were found for either symptom. SC analysis showed no significant main or interaction effects. Intraclass correlation coefficients (ICCs) indicated moderate to excellent reliability for pain and paresthesia induction across different durations and intensities (ICC: 0.51-0.91), while SC showed poor to good reliability (ICC: 0.17-0.79). In conclusion, computerized cuff algometry seems to be an effective and reliable method for simultaneously inducing and assessing pain and paresthesia, revealing that these symptoms follow different patterns based on pressure duration and intensity. PERSPECTIVE: This study demonstrates that pain and paresthesia respond differently to varying intensities and durations of mechanical pressure, revealing their distinct psychophysical characteristics. This model can advance the understanding of neuropathic conditions and aid the development of more targeted therapeutic approaches for both pain and paresthesia.

To investigate the test-retest reliability and construct validity of the Brief Pain Inventory-Short Form (BPI-SF) in individuals with rotator cuff-related shoulder pain (RCRSP).

Sixty-one participants with RCRSP completed the BPI-SF twice with an interval of two to seven days and Shoulder Pain and Disability Index (SPADI) at the initial visit. The BPI-SF pain severity subscale, pain interference subscale, and stand-alone pain severity items were analysed using intraclass correlation coefficients (ICCs) and minimal detectable change at the 95% confidence interval (MDC95). The construct validity of BPI-SF was assessed against SPADI using Pearson's correlation.

The BPI-SF pain severity and pain interference subscales presented moderate test-retest reliability (ICC = 0.73, 0.53) and MDC95 were 2.05 and 2.36. All stand-alone BPI-SF pain severity items presented a moderate reliability (ICC = 0.62, 0.70). BPI-SF interference items presented poor to moderate reliability (ICC = 0.39, 0.68). The correlation coefficients between the BPI-SF and SPADI subscales or total scores were large (r = 0.61, 0.75).

BPI-SF pain severity and pain interference subscales have a moderate reliability in individuals with RCRSP. BPI-SF pain severity and interference subscales showed high construct validity in individuals with RCRSP. MDC95 values are useful metrics for interpreting a true change in BPI-SF scores following interventions in individuals with RCRSP.

The purpose of this study was to evaluate the impact of probability map threshold on pleural mesothelioma (PM) tumor delineations generated using a convolutional neural network (CNN). One hundred eighty-six CT scans from 48 PM patients were segmented by a VGG16/U-Net CNN. A radiologist modified the contours generated at a 0.5 probability threshold. Percent difference of tumor volume and overlap using the Dice Similarity Coefficient (DSC) were compared between the reference standard provided by the radiologist and CNN outputs for thresholds ranging from 0.001 to 0.9. CNN-derived contours consistently yielded smaller tumor volumes than radiologist contours. Reducing the probability threshold from 0.5 to 0.01 decreased the absolute percent volume difference, on average, from 42.93% to 26.60%. Median and mean DSC ranged from 0.57 to 0.59, with a peak at a threshold of 0.2; no distinct threshold was found for percent volume difference. The CNN exhibited deficiencies with specific disease presentations, such as severe pleural effusion or disease in the pleural fissure. No single output threshold in the CNN probability maps was optimal for both tumor volume and DSC. This study emphasized the importance of considering both figures of merit when evaluating deep learning-based tumor segmentations across probability thresholds. This work underscores the need to simultaneously assess tumor volume and spatial overlap when evaluating CNN performance. While automated segmentations may yield comparable tumor volumes to that of the reference standard, the spatial region delineated by the CNN at a specific threshold is equally important.

Metabolic inflexibility to Western high-fat diets may contribute to the obesity epidemic. However, validated methods for assessing metabolic flexibility (MetFlex) to high-fat meals are currently lacking. The purpose of this study was to evaluate the reliability of a novel approach for determining MetFlex to a high-fat meal and to compare it with the gold standard for measuring MetFlex to high-carbohydrate loads.

Eight healthy adults were enrolled in our study, which consisted of the following two assessments of MetFlex: 1) MetFlex to fat, via two overnight stays in a metabolic chamber separated by 5 to 7 days; and 2) Metflex to carbohydrates, via a two-step hyperinsulinemic-euglycemic clamp measured >5 days later.

Participants were predominantly White and male, with mean (SD) age of 29.4 (6.3) years and BMI of 25.4 (4.1) kg/m2. MetFlex to fat displayed satisfactory test-retest reliability (intraclass correlation coefficient > 0.70) for several outcomes but showed no correlation to MetFlex measured during the clamp.

Overnight changes in substrate oxidation following a high-fat dinner meal represent a unique aspect of MetFlex that cannot be captured using more conventional methods. Our findings warrant prospective studies to determine whether these parameters are predictive of the development of obesity or metabolic dysfunction.

To compare the keratometry measurements between IOLMaster and Pentacam in dry eyes.

A total of 122 eyes of 95 age-related cataract patients with dry eye disease were enrolled in this study. Keratometry measurements including flat and steep keratometry (K), mean keratometry, axis of the flat K, astigmatism of anterior corneal surface (A-ACS) were obtained using IOLMaster and Pentacam. A second series of examinations were performed 1 min after instillation of artificial tears. Values of keratometry measured by two devices were compared both before and after using artificial tears. Changes of the above parameters in each device were also analyzed.

The mean flat K of IOLMaster was significantly lower than Pentacam. A-ACS was significantly larger in IOLMaster than in Pentacam, with a mean discrepancy of 0.46 D and an upper limit of 95 % LoA of 1.48 D. The 95 % LoA for flat K axis also exceeded the clinically relevant margin. Keratometry and A-ACS measurements were significantly modified after instillation of artificial tears. None of the above parameters showed significant difference between two devices except for A-ACS, with the mean difference decreased to 0.17 D with 95 % LoA of -0.20 to 0.54 D. Intra device comparison showed that changes of A-ACS and flat K axis measured with IOLMaster were greater than those measured with Pentacam.

Dry eye has significantly greater impact on keratometry measured with IOLMaster than with Pentacam. For cases with A-ACS between the two devices over 0.5 D, artificial tears are recommended before performing biometry.

Acute Febrile Illness (AFI) like Malaria, Dengue, Chikungunya, and Enteric fever still remain the most common cause of seeking healthcare in low-middle-income countries and need to be constantly monitored for any impending outbreak. Digital epidemiology promises to assist traditional health surveillance. The health data (including AFI) collated by Google using specialised platforms like Google Trends (GT) is known to correlate with actual disease trends. The present study thus aims to assess the potential of GT to support routine surveillance system and forecast AFI outbreaks reported through the Indian Integrated Disease Surveillance Programme (IDSP).

We utilised Haryana's IDSP portal to retrieve the weekly data of the most commonly reported infectious diseases causing AFI between 2011 and 2020. Internet search trends were downloaded using GT. Descriptive statistics estimated the burden of the AFI and Bland-Altman's plot depicted statistical agreement between the two. We adopted the Box-Jenkins approach to attain the final SARIMA model and explain the time-dependent weekly incidence of AFI.

The time series plot of the reported AFI displayed trends. Martin- Bland plots depicted acceptable agreement between two datasets for all Chikungunya and Dengue. Among the models evaluated, the Malaria model [SARIMA(1,1,1)(1,1,1)] demonstrated the best performance with a balanced fit and reasonable accuracy, while the Enteric Fever model [SARIMA(0,1,0)(1,1,1)] exhibited low prediction error but weak seasonal significance. In contrast, the Dengue [SARIMA(1,1,0)(1,1,0)] and Chikungunya [ARIMA(1,0,0)(0,0,0)] models had high forecast errors, limiting their predictive reliability. Overall, GT supplemented the prediction performance of the SARIMA models with adjusted R2 of 46%, 50%, 50%, and 52% compared to the original 43%, 49%, 20%, and 48%.

Our study observed modest improvements in GT-based SARIMA forecasting models compared to routine IDSP mechanisms for predicting AFI outbreaks in Haryana, highlighting the potential for further enhancement. As more granular GT data becomes available, its integration with traditional surveillance systems could significantly enhance forecasting accuracy for AFI and other infectious disease outbreaks. At no additional cost to the health system, GT can serve as a valuable, real-time digital epidemiology tool, strengthening public health preparedness and enabling timely interventions for the early containment of emerging diseases.

This study aims to determine the feasibility, image quality, intra-subject repeatability and inter-reader variability of Diffusion tensor (DTI) and Diffusion kurtosis imaging (DKI) for pancreatic imaging using different protocols and report normative values in healthy individuals.

Single-institution prospective study performed on healthy volunteers in a clinical 3T scanner, using two different protocols (6/16 diffusion directions). Acquisitions were repeated twice to assess intra-subject repeatability. To assess inter-reader variability, Mean diffusivity (MD), Axial diffusivity (AD), Radial diffusivity (RD), Apparent diffusion coefficient (ADC) and Mean kurtosis (MK) values were extracted from segmented pancreas by two radiologists. A Likert scale was used by both readers to assess subjective image quality.

Twelve healthy volunteers were recruited for each MRI protocol. The 6 diffusion directions protocol was shorter: 7 min vs. 14 min (corresponding to 4 min vs. 7.5 min for a DTI only reconstruction). No differences in image quality were found between protocols. Only MK maps showed implausible estimates, leading to the exclusion of median 16% and 17.7% pixels for the 6- and 16-direction protocols, respectively. Intra-subject repeatability was determined with negligible coefficients of repeatability for DTI; however, MK presented slightly higher values. Inter-reader agreement was excellent for all maps (ICC > 0.9).

DTI and DKI of the pancreas are feasible in clinical settings, with excellent inter-observer agreement and good image quality. Intra-subject repeatability is excellent for DTI, but some variability was observed with DKI. A 6-directions protocol may be preferred due to faster acquisition without quantitatively compromising estimates. MK inaccuracies prompt further research for improving artifact correction.

Models predicting in-hospital mortality for intensive care unit (ICU) patients, like Acute Physiologic and Chronic Health Evaluation (APACHE) IV, depend on correct data about admission diagnoses. Incorrectly recording diagnoses or changes in diagnoses during admission may impact estimating mortality.

All deceased patients admitted to the ICU between Jan 1, 2018 and Dec 31, 2020 were included. Up to two discharge diagnoses were assigned using APACHE IV diagnostic codes. These were compared to the up to two diagnoses documented at admission. When differences occurred, these were classified as registration errors or diagnostic change. The APACHE IV predicted mortality was calculated using either admission or discharge diagnoses. The agreement between both methods was expressed as the mean difference and the intra-class correlation coefficient (ICC).

886 (16 %) of 5633 patients died. In 363 (41 %) patients, there was no difference between admission and discharge diagnoses. Registration errors occurred in 138 (16 %) patients. 416 (47 %) patients had diagnostic change. The mean difference between predictions was 0.019 (95 % CI: 0.015-0.024). The ICC was 0.97 (95 % CI: 0.97-0.98).

Differences between ICU admission and discharge diagnoses occur frequently, this leads to only a small discrepancy in the overall predicted mortality of deceased ICU patients.

To investigate the accuracy and repeatability of the Q-NRG Max® metabolic system against a VacuMed metabolic simulator using a wide range of metabolic rates.

Sixteen metabolic rates (oxygen consumption 0.9-6 L/min), with different combinations of minute ventilation, oxygen consumption, and carbon dioxide production, were measured for 5 minutes, two times by a single Q-NRG Max® unit over the course of one week. Recordings were performed early in the morning, by the same trained technician, in a ventilated laboratory under the same atmospheric conditions. Accuracy was assessed by ordinary least products (OLP) regression analysis, Bland-Altman plots, intraclass correlation coefficients (ICC), mean percentage differences, technical errors (TE) and minimum detectable change (MDC) for all three variables. This analysis was performed using 10 metabolic rates (oxygen consumption 0.9-4 L/min) and 16 metabolic rates (oxygen consumption 0.9-6 L/min) to allow comparisons with previous research. Intra-device repeatability was performed by absolute percentage differences between measurements (MAPE), ICC, TE, and MDC for the same variables. Repeatability was investigated using 16 metabolic rates.

High agreement and excellent ICCs (>0.998) were observed for all variables when considering both 10 and 16 metabolic rates. The mean percentage difference, TE and MDC were 0.87%-1.01%, 0.67%-1.07%, 1.55%-2.49%, respectively for the first 10 metabolic rates, and -0.39%-0.65%, 0.58%-1.63%, 1.35%-3.81%, respectively for the 16 metabolic rates. The intra-device repeatability results showed an excellent ICCs (=1.000), MAPE < 0.5%, TE < 1%, and MDC ≤ 2%.

The Q-NRG Max® is a valid and reliable mobile metabolic system for the measurement of ventilation, oxygen consumption, and carbon dioxide production. Measurements were below the 5% TE and MDC, and 2% MAPE recommended thresholds across a wide range of metabolic rates up to 6 L/min oxygen consumption.

Ambient temperature conditions are a common concern during laboratory analysis. Due to unexpected shipping conditions, leptin ELISA kits (Leptin Ultrasensitive, ALPCO USA; Catalog #22-LEPHUU-E01) arrived from the manufacturer at our laboratory at a temperature (76.3°F/24.6°C) well above the 2-8°C conditions recommended by the manufacturer. Since no data are available on the effects of high ambient temperature exposure on the performance of this commercial assay, we opportunistically assessed assay performance using human milk samples. Leptin measurement of recently collected and frozen human milk samples was compared between the warm temperature exposed assay kits and Normal kits that arrived and were stored at recommended temperatures (2-8 °C). We found that assay kit exposure to warm temperature during shipping resulted in sample results that were significantly different from Normal kits despite similar standard curve performance. Measurement variability from human milk samples increased with warmed kits in association with greater freeze/thaw times. This suggests that even under high temperature transportation conditions, this leptin assay performance is robust with kit reagents but compromised with human milk samples. We conclude that kits exposed to high temperature during shipment and/or storage should not be used to run human milk samples and that our concerns may extend to other biological media (i.e., serum, urine, or saliva). This study fills a critical gap in the literature on assay performance validation under non-ideal conditions, such as high temperatures. As global temperatures continue to rise, this question will become more pertinent to research integrity if left unaddressed. In light of our findings, we propose that industry standards for ELISA kit shipping and handling should be evaluated to ensure that all kits are being received in an optimal condition.

Ring-trackers are a growing consumer wearable category that provide a number of sleep metrics, yet their measurement accuracy remains poorly understood. Previous validation studies have mainly focused on healthy individuals, while a significant part of the potential present and future value lies in applications on non-healthy subjects. To enable applications in research and medical applications, rigorous evaluation of performance in clinical settings against the gold-standard polysomnography is needed. To address this knowledge gap, we investigated how the measurements of three commercially available ring trackers (Oura, SleepOn, Circul) perform against polysomnography in a university sleep lab population with a diverse set sleep-related disorders as well as sleep-unrelated medical conditions. We evaluated individual-level and group-level discrepancies of standard sleep measures and conducted an epoch-by-epoch analysis of sleep staging classification performance using a standardized analysis framework. While average group-level sleep measures are similar (e.g., TST differences between rings and gold standard were below 12 min for the Oura ring), individual-level differences often remained large. Ring-derived sleep metrics were characterized by complex bias, indicating that their correction is non-trivial. Sleep/Wake distinction of the Oura and SleepOn rings reached similar performance as previously reported for healthy individuals (~ 85% accuracy), but was worse for the Circul ring (~ 65% accuracy). Sleep stage classification (Wake, Light, Deep, REM sleep) sensitivity ranged from 0.14 (REM sleep classification of the Circul ring) to 0.58 (Light sleep classification of the SleepOn ring). Across all sleep stages, the Oura and SleepOn ring performed similarly (53.18% and 50.48% accuracy), whereas the Circul ring performed worse (35.06% accuracy). Our findings confirm recent descriptions of device-related bias and additionally uncover practical limitations in the application in a real-world sleep laboratory patient cohort. Critically, while some devices may demonstrate reasonable agreement with PSG on average, this agreement masks substantial individual-level inaccuracies, prohibiting their use in clinical sleep medicine, as accurate assessment of individual nights, including both nights with exceptionally low or high sleep quality and quantity, is essential for patient care.

Formal governments alone struggle to effectively manage and navigate undesirable changes in social-ecological systems. Informal governance networks are often seen as essential to address shortcomings of government; however, the roles and influence of these networks are poorly understood. Given the increasing prominence of multiparty processes for environmental governance in the U.S. and beyond, it is critical to understand the shifting roles and influences of both formal and informal organizations in governing large-scale social-ecological systems-specifically regarding social-ecological regime shifts that result in undesirable outcomes. The current conversion of grasslands to woodlands in the U.S. Great Plains biome exemplifies such a social-ecological regime shift. We leverage this ongoing regime shift to better understand the roles of formal and informal organizations in environmental governance networks. Through a social science survey, we measured risk perceptions, organizational learning, organizational influence and social networks among Nebraska and Montana conservation professionals from organizations engaged in grassland governance. We found differences between formal and informal governance organization in risk perceptions and organizational priorities. Additionally, informal organizations demonstrated lower occupational similarity of conservation professionals' social networks. Our results suggest meaningful differences in how formal vs. informal governance organizations are responding to the regime shift and support the hypothesis that informal governance organizations bridge between sectors and enhance the nimbleness of environmental governance during times of social-ecological change. However, low representation of producers within conservation professionals' networks, among other challenges with effective bottom-up environmental governance, illustrate important gaps for effectively governing social-ecological regime shifts.

Glucose tolerance during an oral glucose tolerance test (OGTT) is affected by variations in glucose effectiveness (GE) and glucose absorption and thus affects minimal model calculations of insulin sensitivity (SI). The widely used OGTT SI by Dalla Man et al does not account for variances in GE and glucose absorption.

To develop a novel model that concurrently assesses SI, GE, and glucose absorption.

In this cross-sectional study conducted at an academic medical center, 17 subjects without abnormalities on OGTT (controls) and 88 subjects with diabetes underwent a 75-gram 120-minute 6-timepoint OGTT. The SI from the Dalla Man model was validated with the novel model SI using Bland-Altman limits of agreement methodology. Comparisons of SI, GE, and gastrointestinal glucose half-life (GIGt1/2), a surrogate measure for glucose absorption, were made between subjects with diabetes and controls.

In controls and diabetes, the novel model SI was higher than the current OGTT model. The SI from both controls (ƿ=0.90, P < .001) and diabetes (ƿ=0.77, P < .001) has high agreement between models. GE was higher in diabetes (median: 0.021 1/min, interquartile range [IQR]: 0.020-0.022) compared to controls (median: 0.016 1/min, IQR: 0.015-0.017), P = .02. GIGt1/2 was shorter in diabetes (median: 48.404 min, IQR: 54.424-39.426) than in controls (median: 55.086 min, IQR: 61.368-48.502) without statistical difference.

Our novel model SI has a good correlation with SI from the widely used Dalla Man's model while concurrently calculating GE and GIGt1/2. Thus, besides estimating SI, our novel model can quantify differences in insulin-independent glucose disposal mechanisms important for diabetes pathophysiology.

The physical integrity of insecticidal-treated nets (ITNs) is important for creating a barrier against host-seeking mosquitoes and, therefore, influences people's perception of the net's effectiveness and their willingness to use it. Monitoring the physical integrity of ITNs over time provides information for replenishment schedules and purchasing decisions. Currently, the assessment of physical integrity of ITNs is conducted by manually counting holes and estimating their size to class the net as functional or not. This approach is laborious to routinely conduct during field surveys of ITNs. Automated image analysis may provide a rapid assessment of the physical integrity of ITNs but it is not known if the images can capture sufficient information. As a first step, this study aimed to assess the agreement between estimated hole surface areas derived from (1) manually segmented images, (2) manual hole counting compared to (3) ground truth obtained by calibrated close-up shots of individual holes.

The physical integrity of 75 ITNs purposely selected from an ongoing study was assessed by manual hole counting, image analysis and ground truth. For the image analysis, a graphical user interface was developed and used for the segmentation of holes visible in photographs taken from each side of the net. The hole surface area was then computed from this data. The agreement between the estimates from image analysis and manual hole counting was compared to the ground truth using the Bland-Altman method.

There was substantial agreement between the manually segmented image analysis estimates and the ground truth hole surface areas. The overall bias was small, with a mean ratio of the hole surface area from image analysis to the ground truth of 0.70, and the 95% limits of agreement ranging from 0.35 to 1.38. Manual hole counting underestimated the hole surface area compared to the ground truth, particularly among nets with holes above 10 cm in diameter.

Images coupled with manual segmentation contain sufficient information to calculate hole surface area. This lays the groundwork for incorporating automatic hole detection, and then assessing whether this method will offer a fast and objective method for routine assessment of physical integrity of ITNs. While the WHO method underestimated the hole surface area, it remains useful in classifying nets as either serviceable or too torn because the cut-off is specific to this method.

Quantifying aortic valve calcification is critical for assessing the severity of aortic stenosis, predicting cardiovascular risk, and guiding treatment decisions. This study evaluated the feasibility of a deep learning-based automatic quantification of aortic valve calcification using contrast-enhanced coronary CT angiography and compared the results with manual calcium scoring. A retrospective analysis of 177 patients undergoing aortic stenosis evaluation was conducted, divided into a development set (n = 97) and an internal validation set (n = 80). The DeepLab v3 + model segmented the ascending aorta, and the XGBoost model refined the aortic valve region using representative attenuation values. Calcifications were identified with a tailored threshold based on these values and quantified using a weighted scoring method analogous to the Agatston score. The automated method showed excellent agreement with manual Agatston scores derived from non-contrast CT (Pearson correlation coefficient = 0.93, 95% confidence interval [CI]: 0.89-0.95, p < 0.001, concordance correlation coefficient = 0.92, 95% CI: 0.87-0.95). For classifying severe aortic stenosis, defined by calcium scores exceeding 2000 for men and 1300 for women, the approach achieved a sensitivity of 88.6%, specificity of 91.1%, and overall accuracy of 90.0%. This deep learning model provides automated aortic valve calcification quantification with high accuracy on enhanced CT. This approach offers an alternative for measuring aortic valve calcium when non-contrast CT is unavailable, with the potential to reduce reliance on non-contrast CT, minimize operator dependency, and lower patient radiation exposure.

Global health clinical research is commonly led by high-income countries (HICs) as low- and middle-income countries (LMICs) face barriers to participate, including lack of financial and human capacity and lack of research environment. Respiratory syncytial virus (RSV) vaccine development is also led by HICs, while LMICs carry the burden of life-threatening disease. Representative trials and research capacity strengthening in LMICs are needed to ensure global vaccine access and equity. This study aims to transfer an RSV neutralisation assay, which uses live cells and virus with inherent high variation, to a country eligible to receive support from the Gavi, the Vaccine Alliance.

Using a train-the-trainer approach, a Ghanaian researcher was trained in the Netherlands on the dried blood-based RSV neutralisation assay. Subsequently, a Dutch researcher visited Ghana to support the process of adapting the technique to the Ghanaian setting. In a previously validated RSV neutralisation assay on dried blood, Hep-2 cells were infected with a serial dilution of sample-virus mixture to determine the half-maximal inhibitory concentration. Fifty-one dried blood and serum samples were tested in parallel in both countries to assess concordance.

Training and technology transfer was deemed successful, which was defined as neutralisation measurements by the Ghana team and high concordance (Lin's concordance correlation coefficient (CCC)>0.8). Neutralising capacity measured in identical samples in Ghana and the Netherlands correlated highly (Lin's CCC=0.87; Spearman rho=0.89) but was systematically lower in Ghana than the Netherlands.

We show successful transfer of an RSV neutralisation assay, thereby strengthening the laboratory research capacity in a Gavi-eligible country. Reliable measurement of RSV neutralising antibodies in a Gavi-eligible country and the use of dried blood can contribute to inclusion of LMICs in RSV vaccine development and access.

The purpose of this study was to provide proof of concept for at-home measurements of the tinnitus spectrum.

Nineteen participants completed pitch similarity ratings in the laboratory and at home. All participants first completed laboratory tests (at 500-16000 Hz) and then later completed at-home tests (at 250-8000 Hz) using their own personal computers and headphones. Six participants repeated these measurements after at least 3 weeks.

Tinnitus spectra (plots of pitch similarity rating vs. frequency) were analyzed using linear regression and Bland-Altman plots for frequencies that were common to both environments (500-8000 Hz). Although the Bland-Altman plots indicated that absolute ratings used by participants differed in the two settings with online ratings tending to be higher than lab ratings, the regression analysis indicated that the tinnitus spectra had similar shapes (evidenced by significantly positive slopes) between the two environments for 14 of the 19 participants. Similar results were evident for test-retest reliability of the six returning participants in both settings.

We conclude that the pitch similarity rating method is potentially viable for measuring tinnitus pitch at home. At-home implementation could expedite clinical tinnitus assessments and could be used in conjunction with at-home implementations of tinnitus treatment strategies. However, future studies should include participants who are tested at home prior to being tested in the lab and include an evaluation of extended high frequencies at home.

The rabbit is a popular experimental model in orthopaedic biomechanics due to the presence of natural Haversian remodeling, allowing for better translational relevance to the mechanobiology of human bone over traditional rodent models. Although rabbits are often used with computational modeling approaches such as the finite element (FE) method, a validated and widely agreed upon density-elasticity relationship, which is required to make subject-specific predictions, does not exist. Therefore, the purpose of this study was to determine and validate an accurate density-elasticity relationship for rabbit hindlimb bones using mathematical optimization. Fourteen tibiae and thirteen femora were harvested from New Zealand White Rabbits, imaged with computed tomography (CT), and cyclically loaded in uniaxial compression while strain gauge rosette data were recorded. The CT images were processed into subject-specific FE models which were used in a Nelder-Mead optimization routine to determine a density-elasticity relationship that minimized the error between experimentally measured and FE-predicted principal strains. Optimizations were performed for the tibiae and femora independently, and for both bones combined. A subset of 4 tibiae and 4 femora that were excluded from the optimization were then used to validate the derived relationships. All equations that were determined by the initial optimization exhibited a Y=X type of relationship with strong correlations (Tibiae: R2=0.96; Femora: R2=0.85; Combined: R2=0.90) and good agreement. The validation groups yielded similar results with strong correlations (Tibiae: R2=0.94; Femora: R2=0.87; Combined: R2=0.91). These findings suggest that any of the derived density-elasticity relationships are suitable for computational modeling of the rabbit hindlimb and that a single relationship could be used for the whole rabbit hindlimb in studies where greater computational efficiency is necessary.

Objective  In nuclear medicine, quality control (QC) activities adhere to international standards, yet their complexity can pose challenges. Gamma camera manufacturers have introduced integrated QC software, offering instantaneous results. However, the agreement of these automated processes with established protocols remains uncertain. This study aims to clarify this uncertainty by comparatively analyzing uniformity from various software solutions for a dual-head gamma camera. Methods  The study utilized integrated QC analysis software and three free QC analysis tools (IAEA-NMQC Toolkit, NM Toolkit, and Fiji) for uniformity analyses. Following the National Electrical Manufacturers Association standards, NEMA Standards Publication NU 1-2018, the intrinsic uniformity test was performed on a GE Discovery NM/CT 670 Pro system. Ten uniformity QC images underwent analysis with both integrated QC software and alternative software. Data agreements were tested using the Blant-Altman regression-based analysis. Results  Significant differences were observed in integral and differential uniformities ( p  < 0.001). The central field of view (useful field of view) integral uniformity mean differences for NMQC Toolkit, NM Toolkit, and Fiji were 2.46% (2.34%), 2.44% (2.31%), and 2.56% (2.64%), respectively. Conversely, x-differential and y-differential uniformity mean differences were consistently under 2%. Regression-based analysis confirmed good agreement between computed values. Conclusion  The integrated QC software of Discovery NM/CT 670 Pro provides reliable uniformity analysis, aligned with the NEMA standards. Variations in computed values may stem from differences in pixel values and applied data corrections.

Systemic heparinization during cardiopulmonary bypass (CPB) can significantly affect thromboelastography (TEG). This study investigated the feasibility of adding protamine in vitro to allow assessment of coagulation status using the TEG 6s system during CPB.

In this prospective observational study, 21 patients undergoing elective cardiac valve surgery were evaluated. During CPB, protamine was added in vitro to the heparinized blood of these patients at a concentration of 0.05 mg/mL and analyzed with the TEG 6s (Pre). The TEG parameters were compared to those analyzed after CPB withdrawal and systemic protamine administration (Post).

The citrated kaolin maximal amplitude (CK-MA) and the citrated functional fibrinogen maximal amplitude (CFF-MA) exhibited strong correlations between Pre and Post measurements (r = 0.790 and 0.974, respectively, P < 0.001 for both), despite significant mean differences (-2.23 mm for CK-MA and -0.68 mm for CFF-MA). Bland-Altman analysis showed a clinically acceptable agreement between Pre and Post measurement of CK-MA and CFF-MA (the percentage error was 10.6% and 12.2%, respectively). In contrast, the citrated kaolin reaction time (CK-R) showed no significant correlation between Pre and Post measurements (r = 0.328, P = 0.146), with a mean difference of 1.42 min (95% CI: -0.45 to 3.29).

In vitro protamine addition allows assessment of coagulation status during CPB using the TEG 6s system. CK-MA and CFF-MA measured during CPB using this method revealed a strong correlation and agreement with post-CPB measurements, suggesting that our method potentially facilitates early prediction of post-CPB coagulation status and decision-making on transfusion strategies.

The study was registered in the University Hospital Medical Information Network Clinical Trials Registry (UMIN-CTR, registration number: UMIN000041097, date of registration: July 13, 2020, https://center6.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000046925 ) before the recruitment of participants.

Reliable assessment is critical for diagnosing and managing meibomian gland dysfunction. Multi-functional diagnostic devices, such as meibographers, streamline clinical workflows by integrating multiple ocular assessments. Ensuring reproducibility across examiners is vital for accurate diagnosis and monitoring of treatment. This prospective study determined the inter-examiner reproducibility (IER), inter-rater reproducibility (IRR) and within-subject variability (WSV) of the Huvitz HRK-9000A meibographer.

Meibomian glands (MGs) of both eyelids of healthy participants were captured during the same session by Examiner 1 (E1) and Examiner 2 (E2) in a counter-balanced design. The images were rated offline by E1, E2 and an Independent rater (R1). The inter-examiner reproducibility (IER between E1 vs. E2) and inter-rater reproducibility (IRR between E1 vs. R1 and E2 vs. R1) were determined based on non-parametric Bland-Altman plots, intraclass correlation coefficients (ICCs) and weighted Kappa (κ) values. Within-subject variability (WSV) was determined using ICCs.

Mean MG loss of the upper (E1: 1.0 ± 0.8 vs. R1: 0.9 ± 0.8, E2: 1.2 ± 0.8 vs. R1: 0.9 ± 0.7) and lower eyelids (E1: 1.9 ± 0.9 vs. R1: 2.1 ± 1.1, E2: 1.5 ± 1.0 vs. R1: 1.8 ± 1.0) of 35 participants (mean age 22 ± 3 years, range 19-30) was significantly correlated (p < 0.001) for all pairs of examiners (E1-E2, E1-R1 and E2-R1), but was significantly different for the upper eyelids of E2 vs. E1 (p < 0.002) and E2 vs. R1 (p < 0.003). Median differences between pairs of raters for both eyelids were close to zero, with >74% of comparisons falling within the interquartile range, except for the upper eyelids of E2 vs. E1 and E2 vs. R1 (63% and 66%, respectively). IRR demonstrated moderate agreement (0.43-0.57) with good reliability (ICC range 0.76-0.86) for the upper eyelids and good agreement (0.60-0.65) with good reliability (ICC range 0.85-0.88) for the lower eyelids. The WSV was excellent (ICCs for repeated measurements > 0.90).

The HRK-9000A meibographer demonstrated excellent reliability, with good inter-examiner and inter-rater reproducibility. It is suitable for meibographic assessment, follow-up or treatment.

The FDA-approved ClearLLab 10C Reagents Panel (Beckman Coulter) simplified the diagnosis of leukemias and lymphomas by flow cytometry. However, the requirement of using 3 × 106 cells/mL cannot be met for paucicellular samples. Therefore, we tested whether this 10-color panel can be reliably employed to analyze specimens with low cell concentrations. Serial dilutions of 16 samples (5 normal, 11 abnormal), yielding concentrations ranging from 3.0 × 106 to 0.0469 × 106 cells/mL (64-fold difference), were stained using the B-cell and T-cell panels of the ClearLLab 10C system, and mean fluorescence intensity (MFI) was measured for each antibody. For each cell dilution, the deviation from the value obtained with the FDA-approved concentration of 3.0 × 106 cells/mL was calculated. The agreement between the highest and lowest cell concentration data was evaluated by the Bland and Altman method, Pearson's and Spearman's correlation analyses, and linear regression. In all patients, the antigen expression pattern was similar at all cell concentrations tested, and the mean deviation of the MFI from the value obtained using 3.0 × 106 cells/mL never exceeded 10% for any of the antibodies. The Bland-Altman method demonstrated the similarity between results obtained with the FDA-approved cell concentration and a 64-fold diluted cell suspension, and a high positive correlation was found between MFI acquired under these two conditions. The tests utilizing the lowest density of cells yielded the same patterns of antigen expression in all patients as those performed with the FDA-approved concentration, documenting a 100% concordance between these two protocols. The ClearLLab 10C panel can reliably determine the expression of markers of leukemias and lymphomas in paucicellular samples containing as little as 0.0469 × 106 cells/mL (64-fold lower than the FDA-approved concentration). This finding markedly expands the applicability of the ClearLLab 10C platform in a clinical setting.

Phenobarbital is a common antiseizure medication that has a relatively narrow therapeutic window. Therapeutic drug monitoring (TDM) is a helpful tool to guide dose adjustments for phenobarbital and avoid its toxicity. We investigated the agreement among 3 methods of quantifying phenobarbital in canine plasma: high-performance liquid chromatography (HPLC), point-of-care (POC) testing, and the FDA-approved immunoassay analyzer. We randomly selected 45 plasma samples obtained by the TDM service (College of Veterinary Medicine, Auburn University, Auburn, AL, USA). Passing-Bablok regression and Lin concordance correlation coefficients (CCCs) were used to determine the agreement of the results obtained for the 3 methods; Bland-Altman plots were used for bias analysis using the results from the HPLC method as a reference. The FDA-approved immunoassay analyzer and POC immunoassay method results agreed with the HPLC. The results from the FDA-approved immunoassay analyzer were better correlated than those from the POC method, with Lin CCCs of 0.96 (95% CI: 0.93-0.98) and 0.94 (95% CI: 0.90-0.97), respectively. The average biases of the FDA-approved and the POC immunoassay analyzers were 0.80 and -0.64 µg/mL, respectively. Based on the CIs of Lin CCCs, the commercial POC phenobarbital test is a good screening tool and agrees with the HPLC method. However, the FDA-approved immunoassay analyzer method allows for more accurate quantification of phenobarbital concentrations, which is required for appropriate dose adjustment of phenobarbital.

To describe progression of best-corrected visual acuity (BCVA), full-field stimulus thresholds (FST), and electroretinography (ERG) over 4 years in the USH2A-related Retinal Degeneration study and to assess their suitability as clinical trial endpoints.

Prospective natural history study.

Participants (n = 105) with biallelic disease-causing sequence variants in USH2A and BCVA letter scores of ≥54 were included.

BCVA, FST, fundus-guided microperimetry, static perimetry, and spectral domain OCT were performed annually and ERG at baseline and 4 years only. Mixed effects models were used to estimate annual rates of change with 95% confidence intervals. Associations of change from baseline to 4 years between BCVA, FST, ERG, and other metrics were assessed with Spearman correlation coefficients (rs).

Best-corrected visual acuity, FST, and ERG.

The annual rate of decline in BCVA was 0.83 (95% confidence interval: 0.65-1.02) letters/year. For FST, the change was 0.09 (0.07-0.11) log cd.s/m2/year for white threshold, 0.10 (0.08-0.12) log cd.s/m2/year for blue threshold, and 0.05 (0.04-0.06) log cd.s/m2/year for red threshold. Changes were 22.6 (17.4-28.2)%/year for white threshold, 26.0 (20.3-32.1)%/year for blue threshold, and 12.3 (8.7-16.0)%/year for red threshold. The high percentage of eyes with undetectable ERGs at baseline limited assessment of change.

Best-corrected visual acuity was not a sensitive measure of progression over 4 years. Full-field stimulus threshold was a more sensitive measure; however, additional information on the clinical relevance of changes in FST is needed before this test can be adopted as an endpoint for clinical trials.

Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Primarily, to evaluate the repeatability and reproducibility of the new noncontact esthesiometer (NCE) in healthy subjects. Secondarily, the corneal sensitivity threshold measurements of the NCE were compared with those of the Cochet-Bonnet esthesiometer (CBE).

Assessment reliability study.

Two examiners measured bilateral corneal sensitivity thresholds by NCE and CBE. Triple NCE measurements were performed per eye at all 5 levels, whereas single CBE measurements were performed per eye. When appropriate, NCE (mBar) and CBE (mm) measurements were converted to millinewtons (mN) for direct comparison between devices. The NCE measurement variations were calculated with the intra-class correlation coefficients (ICC) for the primary objective. For the secondary objective, Bland-Altman plots with 95% limits of agreement (95%-LoA) and Spearman's rank correlation coefficients were used to evaluate the level of agreement and linear relationship between the corneal sensitivity thresholds obtained with both devices. Generalized estimating equation models were used to account for the inter-eye correlation of the same study participant.

Fifty subjects (100 eyes) aged 29 years (median) were included. There were no statistically significant differences in the pressure measured by both observers at each NCE level (all P > .05). There was a high intra-observer and inter-observer repeatability of the NCE measurements (ICC > 0.90) and a strong linear correlation (rho > 0.7) at each NCE level. The difference between the mean corneal sensitivity thresholds (mN) measured with the NCE (0.052 ± 0.021 mN) and CBE (0.046 ± 0.005 mN) was statistically significant (P = .001). Bland-Altman analysis revealed a differential bias of +0.00578 mN (95%-LoA -0.03677 - +0.04833 mN) between threshold measurements.

The NCE provides reliable user-independent corneal sensitivity measurements. The NCE and CBE do not yield similar values. Thus, both devices cannot be used interchangeably.

Whilst improving hygiene and sanitation behaviours is key to cost-effective and sustainable water, sanitation and hygiene interventions, measuring behaviour change remains a challenge. This study assessed the validity and reliability of pictorial 24-h recall (P24 hR), a novel method using unprompted recall of past activities through pictures, compared to structured observation for measuring handwashing with soap (HWWS) and safe child faeces disposal in rural Malawi. Data were collected from 88 individuals across 74 households in Chiradzulu district using both methods over a two-day period, with the recall period of the P24 hR corresponding to the period of structured observation completed the previous day. Results showed poor agreement between P24 hR and observations in detection of hygiene opportunities and behaviours. P24 hR under-reported handwashing opportunities when frequency was high and over-reported them when frequency was low. The 95% limits of agreement for handwashing opportunities estimated through Bland-Altman analysis (-7.62 to 4.89) were unacceptably wide given median 5 opportunities observed per participant. P24 hR also over-reported HWWS and safe child faeces disposal, and kappa statistics indicated agreement no better than by chance. Structured observation remains the better method for measuring hygiene behaviours as compared to the P24 hR method despite its known limitations, including potential reactivity bias.

Emerging clinical trials for inherited retinal disease (IRD) require an understanding of long-term progression. This longitudinal study investigated the genetic diagnosis and change in retinal structure and function over 10 years in rod-cone dystrophies (RCDs).

Longitudinal observational follow-up study.

Individuals initially diagnosed with retinitis pigmentosa who underwent baseline assessment between 2010 and 2013.

Baseline and follow-up assessments included best-corrected visual acuity (VA), Goldmann visual field (GVF) perimetry, spectral-domain OCT imaging, electroretinogram, and panel-based genetic testing. Linear mixed models were used to investigate disease progression and interaction between progression rate and baseline measurement. Interocular symmetry in disease progression was assessed using intraclass correlation coefficients (ICCs).

Change in VA, GVF area, and ellipsoid zone (EZ) width over 10 years in RCD.

A total of 23 participants attended follow-up (mean age 63 ± 15 years at follow-up; 48% female), with 20 classified as having RCD and 3 reclassified as having cone-rod dystrophy based on genetic diagnosis. At 10-year follow-up, only 60% of RCD participants showed progression of ≥15 letters in either or both eyes, and 40% did not meet the criteria in either eye. Between the eye with poorer versus better VA at baseline, high symmetry in disease progression was observed for GVF area (ICC = 0.87; 95% confidence interval [CI]: 0.68-0.95), and moderate interocular symmetry in disease progression was observed for VA (ICC = 0.50 [95% CI: 0.07-0.77]) and EZ width (ICC = 0.64 [95% CI: 0.25-0.85]). Baseline values influenced progression for VA and percentage change in GVF area, whereas total percentage change in EZ width did not differ across baseline values.

Many individuals with RCD did not have a significant 15-letter decline in VA over a 10-year follow-up, highlighting the challenges of relying on VA as a measure of disease progression. Symmetry between eyes varies, emphasizing a key consideration for selection of outcome measures in IRD clinical trials.

Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

The aim of the study was to evaluate conventional ultrasound (US) as a radiation-free alternative to X-ray for determining biological age (BA; indicated by skeletal age). BA, was determined in 24 healthy, male, elite youth soccer goalkeepers around peak height velocity (11-16 years of age) using both X-ray and conventional US scans of the left hand. X-ray scans were evaluated using the Tanner-Whitehouse 2 method. Conventional US scans served to determine BA via ossification ratios of 13 hand and wrist bones. The new conventional US method showed very strong correlation with X-ray r = 0.90 (p < 0.05). However, the agreement for the difference in BA and CA, which accounts for age-related variance, was classified poor (ICC = 0.48, p < 0.05). Additionally, linear regression analysis and the Bland-Altman plot suggested the presence of a systematic and proportional overestimation of BA in younger players and an underestimation of BA in older players. Furthermore, Cohen's kappa showed a moderate agreement between players' classification into maturity groups for the two assessment methods. In conclusion, our study has shown that using US-derived ossification ratios did not deliver valid results compared to X-ray when determining BA in youth soccer goalkeepers.

This paper presents a study undertaken to evaluate the sensor systems that were shortlisted to be used in the development of a portable respiratory-gated transcutaneous auricular vagus nerve stimulation (taVNS) system. To date, all published studies assessing respiratory-gated taVNS have been performed in controlled laboratory environments. This limitation arises from the reliance on non-portable sensing equipment, which poses significant logistical challenges. Therefore, we recognised a need to develop a portable sensor system for future research, enabling participants to perform respiratory-gated stimulation conveniently from their homes. This study aimed to measure the accuracy of an in-ear and a fingertip-based photoplethysmography (PPG) sensor in measuring cardiac vagal tone relevant heart rate variability (HRV) parameters of root mean square of successive R-R interval differences (RMSSDs) and the high-frequency (HF) component of HRV. Thirty healthy participants wore the prototype sensor equipment and the gold standard electrocardiogram (ECG) equipment to record beat-to-beat intervals simultaneously during 10 min of normal breathing and 10 min of deep slow breathing (DSB). Additionally, a stretch sensor was evaluated to measure its accuracy in detecting exhalation when compared to the gold standard sensor. We used Bland-Altman analysis to establish the agreement between the prototypes and the ECG system. Intraclass correlation coefficients (ICCs) were calculated to establish consistency between the prototypes and the ECG system. For the stretch sensor, the true positive rate (TPR), false positive rate (FPR), and false negative rate (FNR) were calculated. Results indicate that while ICC values were generally good to excellent, only the fingertip-based sensor had an acceptable level of agreement in measuring RMSSDs during both breathing phases. Only the fingertip-based sensor had an acceptable level of agreement during normal breathing in measuring HF-HRV. The study highlights that a high correlation between sensors does not necessarily translate into a high level of agreement. In the case of the stretch sensor, it had an acceptable level of accuracy with a mean TPR of 85% during normal breathing and 95% during DSB. The results show that the fingertip-based sensor and the stretch sensor had acceptable levels of accuracy for use in the development of the respiratory-gated taVNS system.

Low-luminance visual acuity and low-luminance deficit (standard visual acuity minus low-luminance visual acuity) are gaining popularity as outcome measures in clinical trials for retinal disease, demonstrating capability to detect central visual function changes earlier than standard visual acuity.

The aim of this study is to explore suspected sources of low-luminance visual acuity variability, standardise the method of measurement of low-luminance visual acuity, and define a 'normal' low-luminance deficit upper limit for young adults (<55 years).

Data from three separate studies were collated. Standard visual acuity was obtained using ETDRS charts (Precision Vision, Bloomington, IL, USA) and low-luminance visual acuity was obtained with the addition of a 2.0-log neutral density filter. The effects of dark adaptation and different background luminance levels on low-luminance visual acuity results were explored. The Electronic Visual Acuity chart (M&S Technologies, Niles, IL, USA) for low-luminance visual acuity testing was also assessed.

Three-minutes of dark adaptation and different background luminance levels (1.6 and 0.85 cd/m2) did not demonstrate clinically significant changes in low-luminance visual acuity and low-luminance deficit. Bland-Altman analyses revealed significant variability between the ETDRS physical charts and the electronic chart indicating the two cannot be used interchangeably in the presence of a luminance difference. An upper low-luminance deficit limit of 11 ETDRS letters for younger individuals was also identified.

Formal dark adaptation does not improve low-luminance visual acuity results since any increased sensitivity is nullified by extremely quick cone light adaptation times. Small reductions in background luminance levels are not a clinically significant source of variability. However, for consistency, the same luminance level should be maintained throughout testing. Results from electronic and physical charts are not transferrable without proper luminance calibration. A low-luminance deficit greater than 11 ETDRS letters, in younger individuals, should prompt further investigation.

In laboratory setting evaluating the agreement between two measurement methods is a very frequent practice. Unfortunately, the guidelines to refer to are not free from criticisms from a statistical methodological point of view. We reviewed the Clinical and Laboratory Standards Institute guideline EP09c, 3rd ed. pointing out some drawbacks and some aspects that have not been well defined, leaving situations of uncertainty and/or of excessive subjectivity in the judgement.

We have stressed the need of having replicates to estimate the systematic and the proportional biases of the measurement methods to be compared. Indeed, unequal variance of the two measurement methods gives a slope and intercept of the regression between the difference and the mean of the two values of the measurement methods to be compared that can be absolutely calculated from their means, their variances and their correlation coefficient. So, it is not possible to disentangle true from spurious biases. For laboratory professionals we have developed a worked exemplification of an agreement assessment.

We have stressed the need of other approaches than the classic Bland and Altman method to calculate the systematic and proportional biases of two measurement methods compared for their agreement in a study with replicates.

We aim to assess the real-world accuracy (primary outcome), feasibility and acceptability (secondary outcomes) of an automated retinal photography and artificial intelligence (AI)-based cardiovascular disease (CVD) risk assessment system (rpCVD) in Australian primary care settings. Participants aged 45-70 years who had recently undergone all or part of a CVD risk assessment were recruited from two general practice clinics in Victoria, Australia. After consenting, participants underwent retinal imaging using an automated fundus camera, and an rpCVD risk score was generated by a deep learning algorithm. This score was compared against the World Health Organisation (WHO) CVD risk score, which incorporates age, sex, and other clinical risk factors. The predictive accuracy of the rpCVD and WHO CVD risk scores for 10-year incident CVD events was evaluated using data from the UK Biobank, with the accuracy of each system assessed through the area under the receiver operating characteristic curve (AUC). Participant satisfaction was assessed through a survey, and the imaging success rate was determined by the percentage of individuals with images of sufficient quality to produce an rpCVD risk score. Of the 361 participants, 339 received an rpCVD risk score, resulting in a 93.9% imaging success rate. The rpCVD risk scores showed a moderate correlation with the WHO CVD risk scores (Pearson correlation coefficient [PCC] = 0.526, 95% CI: 0.444-0.599). Despite this, the rpCVD system, which relies solely on retinal images, demonstrated a similar level of accuracy in predicting 10-year incident CVD (AUC = 0.672, 95% CI: 0.658-0.686) compared to the WHO CVD risk score (AUC = 0.693, 95% CI: 0.680-0.707). High satisfaction rates were reported, with 92.5% of participants and 87.5% of general practitioners (GPs) expressing satisfaction with the system. The automated rpCVD system, using only retinal photographs, demonstrated predictive accuracy comparable to the WHO CVD risk score, which incorporates multiple clinical factors including age, the most heavily weighted factor for CVD prediction. This underscores the potential of the rpCVD approach as a faster, easier, and non-invasive alternative for CVD risk assessment in primary care settings, avoiding the need for more complex clinical procedures.

Low-dose sublingual estradiol gender-affirming hormone therapy (GAHT) in treatment-naive transgender women effectively suppresses testosterone and initiates breast development, comparable to oral estradiol with cyproterone acetate; however, its impact on body composition remains unstudied.

To assess early body composition changes with low-dose estradiol, compare sublingual versus oral administration efficacy, and evaluate bioelectrical impedance analysis (BIA) and dual-energy X-ray absorptiometry (DXA) agreement in transgender women undergoing GAHT.

In this 6-month prospective study, 22 treatment-naïve transgender women received either 2 mg/day sublingual estradiol (SLE) or combined oral (CO)-2 mg/day oral estradiol plus 10 mg/day cyproterone acetate. Body composition was assessed using DXA and BIA at baseline and after 6 months.

Changes in body composition, including lean body mass, fat mass, visceral fat area, waist-to-hip ratio, and android-to-gynoid fat ratio.

BIA and DXA measurements showed good agreement. Both groups experienced decreased lean body mass and increased fat mass. The SLE group showed less increase in total and segmental body fat, and visceral fat area compared to CO. Both treatments decreased waist-to-hip ratio and android-to-gynoid fat ratio, indicating early achievement of a more feminine body shape.

These findings may help optimize GAHT protocols, improve patient satisfaction with treatment, and enable monitoring outcome assessment in transgender women.

This study provides valuable insights into early body composition changes with low-dose estradiol administration via different administration routes and validates BIA as an alternative to DXA. However, the sample size was relatively small, the study arm allocation was not randomized, and the study duration was only 6 months.

Low-dose estradiol induces significant feminizing body composition changes within 6 months of GAHT, with sublingual administration potentially limiting fat accumulation while achieving a feminine body shape.

ISRCTN15726488 Entire data set found at:  https://doi.org/10.17605/OSF.IO/VNC54.

Movement smoothness is a critical metric for evaluating motor control and sensorimotor impairments, with increasing relevance in neurorehabilitation and everyday functional assessments. This study investigates the correlation between two smoothness metrics (Log Dimensionless Jerk): LDLJV, derived from body center of mass (BCoM) trajectories using a gold-standard stereophotogrammetric system, and LDLJA, calculated from acceleration data recorded via an inertial measurement unit (IMU) placed at the L1-L2 level. Ten healthy adults (six men and four women; height: 1.71 ± 0.08 m; body mass: 68.2 ± 10.2 kg; age: 34.5 ± 8.5 years) walked on a treadmill at seven different speeds, with stride-specific data analyzed to compute smoothness indices for three anatomical components (antero-posterior, medio-lateral, cranio-caudal). Concordance between the metrics was evaluated using Bland-Altman analysis, Spearman's correlation, and the mean absolute percentage error. The results revealed weak correlations and substantial biases across all components and speeds, reflecting inherent differences between IMU- and BCoM-derived data. Correcting biases improved alignment but did not eliminate discrepancies. The findings highlight that LDLJA captures only localized trunk accelerations, whereas BCoM-derived LDLJV approximates whole-body dynamics, making direct substitution infeasible. This study emphasizes the need for careful interpretation of IMU-based metrics and contributes to refining their application in real-world gait analyses.

The 10-m walk test (10MWT) is a stopwatch-based clinical mobility assessment. To better understand mobility limitations, 10MWT test completion times may be complemented with gait parameters like step length. State-of-the-art augmented reality (AR) glasses can potentially do this given their unique 3D-positional data from which gait parameters may be derived. We examined the test-retest reliability, concurrent validity, and face validity of gait parameters derived from AR glasses during a 10MWT in 20 people with Parkinson's disease, performed at self-selected comfortable and fast-but-safe walking speeds. AR-derived 10MWT completion times and gait parameters (mean step length, cadence, and maximal gait speed) were compared across repetitions and with lab-based (Interactive Walkway) and clinical (stopwatch) reference systems. Good-to-excellent test-retest reliability statistics were observed for test completion times and gait parameters for all systems and conditions alike. Concurrent validity was demonstrated between AR, lab-based, and clinical references for test completion times (good-to-excellent agreement: ICC > 0.879) and gait parameters (excellent agreement: ICC > 0.942). Face validity was confirmed by significant differences in test completion times and gait parameters between speed conditions in a-priori expected directions. These findings support the conclusion that gait parameters can be derived reliably and validly from AR glasses in people with Parkinson's disease.

Background/Objectives: The accurate measurement of corneal epithelial thickness (CET) and pachymetry is essential for diagnosing and managing corneal conditions such as keratoconus and for optimizing outcomes in refractive surgery. This study aimed to evaluate the agreement and repeatability of measurements between two anterior segment optical coherence tomography (AS-OCT) devices-OCT REVO FC 130 and Optovue RTV XR Avanti-in healthy individuals. Methods: This prospective, cross-sectional, observational study included 53 healthy participants. High-quality scans were performed using both devices by two trained operators. Agreement between devices was assessed using Bland-Altman analysis and Deming regression, while repeatability and reproducibility were evaluated through intraclass correlation coefficients (ICCs) and test-retest variability (TRT). Results: Both devices demonstrated high repeatability and reproducibility across central and peripheral zones, with ICCs exceeding 0.98 for central pachymetry and stroma measurements. Repeatability and reproducibility were slightly higher for the OCT REVO FC 130 compared to the Optovue RTV XR Avanti, particularly for central measurements. Bland-Altman analysis revealed a mean difference near zero with narrow limits of agreement for most parameters, indicating strong inter-device agreement. Variability in CET measurements was higher, potentially due to the inclusion of tear film in OCT segmentation. Conclusions: The OCT REVO FC 130 and Optovue RTV XR Avanti offer comparable reliability and precision for corneal thickness measurements in healthy eyes, with the REVO demonstrating slightly better repeatability and reproducibility. These findings support the use of either device in clinical practice and research for corneal assessment.

Migraine is known to be caused by calcitonin gene-related peptide (CGRP), prompting the need for quantitative analysis of CGRP for the clinical treatment of monoclonal antibodies targeting CGRP. Since CGRP is cleaved by proteolytic enzymes post-blood collection, rapid analysis methods are required. In this study, a one-step immunoassay for CGRP was developed using chemically mimicking peptides (mimotopes) with an analysis time of 32 min. Four clones from an Fv-antibody library were screened using two types of monoclonal antibodies against CGRP. Mimotopes for each monoclonal antibody were synthesized into peptides of 15 residues. The binding affinity (KD) was estimated, and the interaction with monoclonal antibodies was analyzed using docking simulations. Finally, a one-step immunoassay for CGRP was demonstrated using migraine patient samples (n = 57) and healthy volunteer controls (n = 18). The limit of detection (LOD) of one-step immunoassay based on Fremanezumab (mimotope F1) was estimated to be 8.8 pg/mL with the limit of quantification (LOQ) of 125.9 pg/mL. And, the one-step immunoassay based on Galcanezumab (mimotope G7) showed the LOD of 9.4 pg/mL and the LOQ of 84.7 pg/mL. The total analysis time was estimated to be approximately 32 min and the assay results were estimated to be statistically consistent with conventional CGRP assay.

Apart from objectivity and validity, reliability is considered a precondition for testing within scientific works, as unreliable testing protocols limit conclusions, especially for practical application. Classification guidelines commonly refer to relative reliability, focusing on Pearson correlation coefficients (rp) and intraclass correlation coefficients (ICC). On those, the standard error of measurement (SEM) and the minimal detectable change (MDC) are often calculated in addition to the variability coefficient (CV). These, however, do not account for systematic or random errors (e.g., standardization problems). To illustrate, we applied common reliability statistics in sports science on simulated data which extended the sample size of two original counter-movement-jump sessions from (youth) elite basketball players. These show that excellent rp and ICC (≥ 0.9) without a systematic bias were accompanied by a mean absolute percentage error of over 20%. Furthermore, we showed that the ICC does not account for systematic errors and has only limited value for accuracy, which can cause misleading conclusions of data. While a simple re-organization of data caused an improvement in relative reliability and reduced limits of agreement meaningfully, systematic errors occurred. This example underlines the lack of validity and objectivity of commonly used ICC-based reliability statistics (SEM, MDC) to quantify the primary and secondary variance sources. After revealing several caveats in the literature (e.g., neglecting of the systematic and random error or not distinguishing between protocol and device reliability), we suggest a methodological approach to provide reliable data collections as a precondition for valid conclusions by, e.g., recommending pre-set acceptable measurement errors.

Hospitalised, unwell patients have vital signs such as heart rate (HR), oxygen saturation (SpO2) and temperature measured multiple times a day to detect clinical deterioration and monitor health trajectories. Advancements in contact-free (ambient) sensors (AS) to measure vital signs can help mitigate risks due to skin injury and infection transmission seen in conventional hospital equipment. This prospective, observational clinical study aims to validate vital sign measurements from a multi-channel AS compared to conventional equipment in three cohorts: patients in a hospital ward, patients at home within a Hospital-at-Home service, and healthy volunteers. Data analysis of 571 paired measurements from 29 participants indicates that heart rate measurements via AS were accurate, though they lacked precision, with the clinical agreement range between 6.38 and 6.49 beats per minute. Temperature and oxygen saturation measurements showed less agreement when compared with the reference standard. In conclusion, ambient sensors show promising utility in measuring vital signs, with this study amongst the first of its kind to utilise this in measuring vital signs in hospitalised patient cohorts in both ward and home environments.

Monitoring nociception under general anesthesia remains challenging due to the complexity of pain pathways and the limitations of single-parameter methods. In this study, we introduce a multimodal approach that integrates electroencephalogram (EEG), photoplethysmography (PPG), and electrocardiogram (ECG) signals to predict nociception. We collected data from patients undergoing general anesthesia at two hospitals and developed and compared two deep learning models: a Multilayer Perceptron (MLP) and a Long Short-Term Memory (LSTM) network. Both models were trained on expert anesthesiologists' assessments of nociception. We evaluated normalization strategies for offline and online usage and found that Min-Max normalization was most effective for our dataset. Our results demonstrate that the MLP model accurately captured nociceptive changes in response to painful surgical stimuli, whereas the LSTM model provided smoother predictions but with lower sensitivity to rapid changes. These findings underscore the potential of multimodal, deep learning-based solutions to improve real-time nociception monitoring in diverse clinical settings.