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This paper proposes a smartphone-based method for measuring Blood Pressure (BP) using the oscillometric method. For oscillometry, it is necessary to measure (1) the pressure applied to the artery and (2) the local blood volume change. This is accomplished by performing an oscillometric measurement at the fingers digital artery, whereby a user presses down on the phones camera with steadily increasing force. The camera is used to capture the blood volume change using photoplethysmography. We devised a novel method for measuring the force applied of the finger without the use of specialized smartphone hardware with a technique called Vibrometric Force Estimation (VFE). The fundamental concept of VFE relies on a phenomenon where a vibrating object is dampened when an external force is applied on to it. This phenomenon can be recreated using the phones own vibration motor and measured using the phones Inertial Measurement Unit (IMU). A cross device reliability study with three smartphones of different manufacturers, shape, and prices results in similar force estimation performance across all smartphone models. In an N = 24 proof of concept study of the BP measurement, the smartphone technique achieves a mean absolute error of 9.21 mmHg and 7.77 mmHg of systolic and diastolic BP, respectively, compared to an FDA approved BP cuff. The vision for this technology is not necessarily to replace existing BP monitoring solutions, but rather to introduce a downloadable smartphone software application that could serve as a low-barrier hypertension screening measurement fit for widespread adoption.

BACKGROUND: Intraocular pressure (IOP) monitoring in glaucoma management is evolving with novel devices. We investigated the reproducibility of 24 hour profiles on two consecutive days and after 30 days of self-measurements via telemetric IOP monitoring. METHODS: Seven primary patients with open-angle glaucoma previously implanted with a telemetric IOP sensor in one eye underwent automatic measurements throughout 24 hours on two consecutive days (day 1 and day 2). Patients wore an antenna adjacent to the study eye connected to a reader device to record IOP every 5 min. Also, self-measurements in six of seven patients were collected for a period of 30 days. Analysis included calculation of hourly averages to correlate time-pairs of day 1 versus day 2 and the self-measurements vers day 2. RESULTS: The number of IOP measurements per patient ranged between 151 and 268 on day 1, 175 and 268 on day 2 and 19 and 1236 during 30 days of self-measurements. IOP time-pairs of automatic measurements on day 1 and day 2 were significantly correlated at the group level (R=0.83, p

The tutelage of our mentors as scientists included the analogy that writing a good scientific paper was an exercise in storytelling that omitted unessential details that did not move the story forward or that detracted from the overall message. However, the advice to not get lost in the details had an important flaw. In science, it is the many details of the data themselves and the methods used to generate and analyze them that give conclusions their probative meaning. Facts may sometimes slow or distract from the clarity, tidiness, intrigue, or flow of the narrative, but nevertheless they are important for the assessment of what was done, the trustworthiness of the science, and the meaning of the findings. Nevertheless, many critical elements and facts about research studies may be omitted from the narrative and become hidden from scholarly scrutiny. We describe a bakers dozen shortfalls in which such elements that are pertinent to evaluating the validity of scientific studies are sometimes hidden in reports of the work. Such shortfalls may be intentional or unintentional or lie somewhere in between. Additionally, shortfalls may occur at the level of the individual or an institution or of the entire system itself. We conclude by proposing countermeasures to these shortfalls.

Inquiries into properties of brain structure and function have progressed due to developments in magnetic resonance imaging (MRI). To sustain progress in investigating and quantifying neuroanatomical details in vivo, the reliability and validity of brain measurements are paramount. Quality control (QC) is a set of procedures for mitigating errors and ensuring the validity and reliability of brain measurements. Despite its importance, there is little guidance on best QC practices and reporting procedures. The study of hippocampal subfields in vivo is a critical case for QC because of their small size, inter-dependent boundary definitions, and common artifacts in the MRI data used for subfield measurements. We addressed this gap by surveying the broader scientific community studying hippocampal subfields on their views and approaches to QC. We received responses from 37 investigators spanning 10 countries, covering different career stages, and studying both healthy and pathological development and aging. In this sample, 81% of researchers considered QC to be very important or important, and 19% viewed it as fairly important. Despite this, only 46% of researchers reported on their QC processes in prior publications. In many instances, lack of reporting appeared due to ambiguous guidance on relevant details and guidance for reporting, rather than absence of QC. Here, we provide recommendations for correcting errors to maximize reliability and minimize bias. We also summarize threats to segmentation accuracy, review common QC methods, and make recommendations for best practices and reporting in publications. Implementing the recommended QC practices will collectively improve inferences to the larger population, as well as have implications for clinical practice and public health.

INTRODUCTION: The Fear of Pain Questionnaire (FOPQ) is a self-report tool designed to measure an individuals fear of pain (FOP). While the Persian version of the FOPQ (FOPQ-P) has been developed, its validity and reliability have not yet been assessed in the Iranian context. This study aims to evaluate the psychometric properties of the FOPQ-P among Iranian patients after surgery. METHODS: A methodological study was conducted in 2023 involving 400 post-surgery patients selected with a convenience sampling. The FOPQ was translated into Persian, and its psychometric properties were analyzed using network analysis, exploratory factor analysis (EFA), confirmatory factor analysis (CFA), as well as assessments of convergent and discriminant validity. Internal consistency was measured using Cronbachs alpha, McDonalds Omega, average inter-item correlation coefficient, Composite Reliability, and Maximal Reliability. RESULTS: The EFA results with Promax and Kaiser Normalization rotation identified two factors that explained 54.32% of the variance, comprising seven items. The CFA confirmed the models validity. Both convergent and discriminant validity were established. The reliability analyses showed that Cronbachs alpha, McDonalds omega, composite reliability, and MaxR for all constructs were above 0.7. Additionally, the average inter-item correlation coefficient was greater than 0.5, indicating strong internal consistency and construct reliability. CONCLUSION: The findings suggest that the FOPQ-P possesses a valid structure and was acceptable reliability in patients cultural context of Iran post-surgery, making it a suitable instrument for measuring fear of pain in this population.

Adoption of high-content omic technologies in clinical studies, coupled with computational methods, has yielded an abundance of candidate biomarkers. However, translating such findings into bona fide clinical biomarkers remains challenging. To facilitate this process, we introduce Stabl, a general machine learning method that identifies a sparse, reliable set of biomarkers by integrating noise injection and a data-driven signal-to-noise threshold into multivariable predictive modeling. Evaluation of Stabl on synthetic datasets and five independent clinical studies demonstrates improved biomarker sparsity and reliability compared to commonly used sparsity-promoting regularization methods while maintaining predictive performance; it distills datasets containing 1,400-35,000 features down to 4-34 candidate biomarkers. Stabl extends to multi-omic integration tasks, enabling biological interpretation of complex predictive models, as it hones in on a shortlist of proteomic, metabolomic and cytometric events predicting labor onset, microbial biomarkers of pre-term birth and a pre-operative immune signature of post-surgical infections. Stabl is available at https://github.com/gregbellan/Stabl .

Clinical trials in metabolic dysfunction-associated steatohepatitis (MASH, formerly known as nonalcoholic steatohepatitis) require histologic scoring for assessment of inclusion criteria and endpoints. However, variability in interpretation has impacted clinical trial outcomes. We developed an artificial intelligence-based measurement (AIM) tool for scoring MASH histology (AIM-MASH). AIM-MASH predictions for MASH Clinical Research Network necroinflammation grades and fibrosis stages were reproducible (κ = 1) and aligned with expert pathologist consensus scores (κ = 0.62-0.74). The AIM-MASH versus consensus agreements were comparable to average pathologists for MASH Clinical Research Network scores (82% versus 81%) and fibrosis (97% versus 96%). Continuous scores produced by AIM-MASH for key histological features of MASH correlated with mean pathologist scores and noninvasive biomarkers and strongly predicted progression-free survival in patients with stage 3 (P

The functional Scale for the Assessment and Rating of Ataxia (f-SARA) assesses Gait, Stance, Sitting, and Speech. It was developed as a potentially clinically meaningful measure of spinocerebellar ataxia (SCA) progression for clinical trial use. Here, we evaluated content validity of the f-SARA. Qualitative interviews were conducted among individuals with SCA1 (n = 1) and SCA3 (n = 6) and healthcare professionals (HCPs) with SCA expertise (USA, n = 5; Europe, n = 3). Interviews evaluated symptoms and signs of SCA and relevance of f-SARA concepts for SCA. HCP cognitive debriefing was conducted. Interviews were recorded, transcribed, coded, and analyzed by ATLAS.TI software. Individuals with SCA1 and 3 reported 85 symptoms, signs, and impacts of SCA. All indicated difficulties with walking, stance, balance, speech, fatigue, emotions, and work. All individuals with SCA1 and 3 considered Gait, Stance, and Speech relevant f-SARA concepts; 3 considered Sitting relevant (42.9%). All HCPs considered Gait and Speech relevant; 5 (62.5%) indicated Stance was relevant. Sitting was considered a late-stage disease indicator. Most HCPs suggested inclusion of appendicular items would enhance clinical relevance. Cognitive debriefing supported clarity and comprehension of f-SARA. Maintaining current abilities on f-SARA items for 1 year was considered meaningful for most individuals with SCA1 and 3. All HCPs considered meaningful changes as stability in f-SARA score over 1-2 years, 1-2-point change in total f-SARA score, and deviation from natural history. These results support content validity of f-SARA for assessing SCA disease progression in clinical trials.

OBJECTIVE: To evaluate the reliability, responsiveness, and validity of the Scale for the Assessment and Rating of Ataxia (SARA) in patients with lysosomal storage disorders (LSDs) who present with neurological symptoms, and quantify the threshold for a clinically meaningful change. METHODS: We analyzed data from three clinical trial cohorts (IB1001-201, IB1001-202, and IB1001-301) of patients with Niemann-Pick disease type C (NPC) and GM2 Gangliosidoses (Tay-Sachs and Sandhoff disease) comprising 122 patients and 703 visits. Reproducibility was described as re-test reliability between repeat baseline visits or baseline and post-treatment washout visits. Responsiveness was determined in relation to the Investigators, Caregivers, and Patients Clinical Global Impression of Improvement (CGI-I). The CGI-I data was also used to quantify a threshold for a clinically meaningful improvement on the SARA scale. Using a qualitative methods approach, patient/caregiver interviews from the IB1001-301 trial were further used to assess a threshold of meaningful change as well as the breadth of neurological signs and symptoms captured and evaluated by the SARA scale. RESULTS: The Inter-Class Correlation (ICC) was 0.95 or greater for all three trials, indicating a high internal consistency/reliability. The mean change in SARA between repeat baseline and post-treatment washout visit assessments in all trials was -0.05, SD 1.98, i.e., minimal, indicating no significant differences, learning effects or other systematic biases. For the CGI-I responses and change in SARA scores, Area Under the Curve (AUC) values were 0.82, 0.71, and 0.77 for the Investigators, Caregivers, and Patients CGI-I respectively, indicating strong agreement. Further qualitative analyses of the patient/caregiver interviews demonstrated a 1-point or greater change on SARA to be a clinically meaningful improvement which is directly relevant to the patients everyday functioning and quality of life. Changes captured by the SARA were also paralleled by improvement in a broad range of neurological signs and symptoms and beyond cerebellar ataxia. CONCLUSION: Qualitative and quantitative data demonstrate the reliability and responsiveness of the SARA score as a valid measure of neurological signs and symptoms in LSDs with CNS involvement, such as NPC and GM2 Gangliosidoses. A 1-point change represents a clinically meaningful transition reflecting the gain or loss of complex function.

Spinocerebellar ataxias (SCA) are rare inherited neurodegenerative disorders characterized by a progressive impairment of gait, balance, limb coordination, and speech. There is currently no composite scale that includes multiple aspects of the SCA experience to assess disease progression and treatment effects. Applying the method of partial least squares (PLS) regression, we developed the Spinocerebellar Ataxia Composite Scale (SCACOMS) from two SCA natural history datasets (NCT01060371, NCT02440763). PLS regression selected items based on their ability to detect clinical decline, with optimized weights based on the items degree of progression. Following model validation, SCACOMS was leveraged to examine disease progression and treatment effects in a 48-week SCA clinical trial cohort (NCT03701399). Items from the Clinical Global Impression-Global Improvement Scale (CGI-I), the Friedreich Ataxia Rating Scale (FARS) - functional stage, and the Modified Functional Scale for the Assessment and Rating of Ataxia (f-SARA) were objectively selected with weightings based on their sensitivity to clinical decline. The resulting SCACOMS exhibited improved sensitivity to disease progression and greater treatment effects (compared to the original scales from which they were derived) in a 48-week clinical trial of a novel therapeutic agent. The trial analyses also provided a SCACOMS-derived estimate of the temporal delay in SCA disease progression. SCACOMS is a useful composite measure, effectively capturing disease progression and highlighting treatment effects in patients with SCA. SCACOMS will be a powerful tool in future studies given its sensitivity to clinical decline and ability to detect a meaningful clinical impact of disease-modifying treatments.

The fruit fly Drosophila melanogaster has emerged as a key model organism in neuroscience, in large part due to the concentration of collaboratively generated molecular, genetic and digital resources available for it. Here we complement the approximately 140,000 neuron FlyWire whole-brain connectome1 with a systematic and hierarchical annotation of neuronal classes, cell types and developmental units (hemilineages). Of 8,453 annotated cell types, 3,643 were previously proposed in the partial hemibrain connectome2, and 4,581 are new types, mostly from brain regions outside the hemibrain subvolume. Although nearly all hemibrain neurons could be matched morphologically in FlyWire, about one-third of cell types proposed for the hemibrain could not be reliably reidentified. We therefore propose a new definition of cell type as groups of cells that are each quantitatively more similar to cells in a different brain than to any other cell in the same brain, and we validate this definition through joint analysis of FlyWire and hemibrain connectomes. Further analysis defined simple heuristics for the reliability of connections between brains, revealed broad stereotypy and occasional variability in neuron count and connectivity, and provided evidence for functional homeostasis in the mushroom body through adjustments of the absolute amount of excitatory input while maintaining the excitation/inhibition ratio. Our work defines a consensus cell type atlas for the fly brain and provides both an intellectual framework and open-source toolchain for brain-scale comparative connectomics.

A catalogue of neuronal cell types has often been called a 'parts list' of the brain1, and regarded as a prerequisite for understanding brain function2,3. In the optic lobe of Drosophila, rules of connectivity between cell types have already proven to be essential for understanding fly vision4,5. Here we analyse the fly connectome to complete the list of cell types intrinsic to the optic lobe, as well as the rules governing their connectivity. Most new cell types contain 10 to 100 cells, and integrate information over medium distances in the visual field. Some existing type families (Tm, Li, and LPi)6-10 at least double in number of types. A new serpentine medulla (Sm) interneuron family contains more types than any other. Three families of cross-neuropil types are revealed. The consistency of types is demonstrated by analysing the distances in high-dimensional feature space, and is further validated by algorithms that select small subsets of discriminative features. We use connectivity to hypothesize about the functional roles of cell types in motion, object and colour vision. Connectivity with 'boundary types' that straddle the optic lobe and central brain is also quantified. We showcase the advantages of connectomic cell typing: complete and unbiased sampling, a rich array of features based on connectivity and reduction of the connectome to a substantially simpler wiring diagram of cell types, with immediate relevance for brain function and development.

Western blot is a popular biomolecular analysis method for measuring the relative quantities of independent proteins in complex biological samples. However, variability in quantitative western blot data analysis poses a challenge in designing reproducible experiments. The lack of rigorous quantitative approaches in current western blot statistical methodology may result in irreproducible inferences. Here we describe best practices for the design and analysis of western blot experiments, with examples and demonstrations of how different analytical approaches can lead to widely varying outcomes. To facilitate best practices, we have developed the blotRig tool for designing and analyzing western blot experiments to improve their rigor and reproducibility. The blotRig application includes functions for counterbalancing experimental design by lane position, batch management across gels, and analytics with covariates and random effects.

Food cue reactivity (FCR) is an appetitive trait associated with overeating and weight gain. We developed a laboratory craving assessment to objectively evaluate cognitive aspects of FCR. This study examined the preliminary construct and criterion validity of this craving assessment and evaluated 4 different interventions, 2 of which incorporated cue-exposure treatment for food, on craving over treatment and follow-up. 271 treatment-seeking adults with overweight/obesity (body mass index = 34.6[5.2]; age = 46.5[11.8]; 81.2% female; 61.6% non-Latinx White) completed the Food Cue Responsivity Scale and the laboratory craving assessment, during which they alternated holding and smelling a highly craved food and provided craving ratings over 5 min. Participants were subsequently randomized to 26 treatment sessions over 12-months of ROC, Behavioral Weight Loss (BWL), a combined arm (ROC+) and an active comparator (AC), and repeated the craving assessment at post-treatment and 12-month follow-up. Linear mixed-effects models assessed associations between trial type (holding vs. smelling), trial number, pre-treatment FCR, treatment arm, assessment time point, and craving. Cravings were greater when smelling vs. holding food (b = 0.31, p

Preliminary evidence from the Childhood Joint Attention Rating Scale (C-JARS; Mundy et al., 2017) suggests symptoms related to diminished joint attention and the spontaneous sharing of experience with others can be assessed with a parent-report measure in children and adolescents with autism. This study was designed to expand on the previous study by examining the validity of both a Social Symptom (SS) and a Prosocial (PS) scale of the C-JARS in a study of school-aged autistic children (n  = 89) with and without co-occurring intellectual disability (ID), as well as an age matched neurotypical sample (n  = 62). Results indicated that both C-JARS scales were sensitive and specific with respect to identifying the diagnostic status of the children. In addition, the PS scale was sensitive to differences in cognitive abilities (IQ) and sex differences in the autism group. These results are consistent with the hypothesis that joint attention and spontaneous sharing of experience symptoms are not only characteristic of preschool children with autism but may also constitute a developmentally continuous dimension of the social phenotype of autism that can be measured in school-aged children.

Blood pressure variability (BPV) is emerging as an important risk factor across numerous disease states, including cerebrovascular and neurodegenerative disease in older adults. However, there is no current consensus regarding specific use cases for the numerous available BPV metrics. There is also little published data supporting the ability to reliably measure BPV across metrics in older adults. The present study derived BPV metrics from continuous beat-to-beat blood pressure monitoring data. Two sequential 7 min waveforms were analyzed. Absolute and relative reliability testing was performed. Differences between antihypertensive medication users and non-users on BPV metric reliability was also assessed. All sequence and dispersion based BPV metrics displayed good test-retest reliability. A measure of BP instability displayed only moderate reliability. Systolic and diastolic average real variability displayed the highest levels of reliability at ICC = 0.87 and 0.82 respectively. Additionally, systolic average real variability was the most reliable metric in both the antihypertensive use group, and the no antihypertensive use group. In conclusion, beat-to-beat dispersion and sequence-based metrics of BPV can be reliably obtained in older adults using noninvasive continuous blood pressure monitoring. Average real variability may be the most reliable and specific beat-to-beat blood pressure variability metric due to its decreased susceptibility to outliers and low frequency blood pressure oscillations.

IntroductionThe Weight Loss Readiness Test (WLRT) was developed to encourage consideration of factors influencing readiness to engage in weight loss. The WLRT is used clinically, most notably to assess motivation before initiating Navy weight management programs, yet little is known about its psychometric properties.Materials and methodsThis study examined the reliability, convergent and predictive validity, and factor structure of the WLRT in a sample of active duty service members enrolling in a Navy-based weight management program (N = 178, identified as female = 61%, mean age = 29.7 years, mean baseline body mass index = 33.1 kg/m2). All procedures were approved by the respective Institutional Review Boards and research committees.ResultsExploratory factor analysis revealed a 5-factor structure explaining 52% of the variance that best fit the data with low to moderate correlations between factors: (1) Motivation, (2) Exercise-Related Confidence, (3) Non-Exercise Confidence, (4) Cues, and (5) Anticipated Satisfaction. Internal reliability of subscales was acceptable to good (α = 0.755-0.903). Generally, convergent validity was found between the identified subscales and other measures of motivation, confidence, and disinhibited eating in expected directions. No relationships were found between the subscales and predictive validity outcomes (weight change, program attendance).ConclusionsResults indicate adequate structural and convergent validity in the WLRT, but that weight loss readiness, as measured by the WLRT, does not provide predictive validity regarding weight loss or attendance outcomes in this sample. Nonetheless, this measure offers clinical utility in fostering thoughtful conversations about weight loss. The WLRT uniquely focuses on long-term maintenance of behavior change and differentiates between exercise-related and non-exercise confidence. Future studies should further probe the utility of this measure in other populations and the contexts in which it is being used.

Actinic keratosis (AK) is a common precancerous skin condition predominantly affecting older males with fair skin and significant UV exposure. The clinical significance of AK is related to its potential for malignant transformation and progression to squamous cell carcinoma (SCC). Accurate diagnosis of AK is essential for adequate treatment, evaluation of therapeutic efficacy, and mitigating the risk of developing SCC. However, clinician variability due to the subjective nature of current diagnostic tools presents significant challenges to achieving consistent and reliable AK diagnoses. Thus, there is no universally accepted standard for measuring AK.This review evaluates current methods for evaluating and diagnosing AK, focusing on clinician variability through inter- and intraobserver agreement. Eight peer-reviewed studies investigating the reliability of various approaches for AK evaluation show substantial variability in interobserver or intraobserver agreement, with most methods demonstrating only slight to moderate reliability. Some suggest that consensus discussions and simplified rating scales can modestly improve diagnostic reliability. However, remaining variability and the lack of a universally accepted standard for measuring AK underscore the need for more robust and standardized diagnostic and evaluation methods.The review emphasizes the need for improved diagnostic tools and standardized methods to enhance the accuracy and reliability of AK assessments. It also proposes applying a novel examination approach using 1,3-dihydroxyacetone (DHA) staining which may improve the visualization and identification of AK lesions. Advancements in these areas have significant potential, promising better clinical practices and patient outcomes in AK management.

AIMS: The purpose of this study is to evaluate the accuracy and validity of the determination of cause of death (COD) and manner of death (MOD) at the completion of the forensic autopsy prosection. METHODS: We analysed 952 autopsy cases conducted from 2019 to 2020 and compared every patients COD, other significant contributing factors to death (OSC), and MOD after prosection to their COD, OSC and MOD after completion of the final autopsy report. RESULTS: We found that 83% of cases (790 patients) did not have an unexpected change and 17% of cases (162 patients) exhibited a true change in their final diagnosis; the relationship between age and changes in COD and MOD was significant. CONCLUSIONS: Our findings indicate that in the majority of forensic autopsy cases, medical professionals can reasonably complete death certification after the autopsy prosection. In addition to improving the accuracy of COD and MOD, advances in this field will enhance timely decedent affairs management, timely investigations of crimes and timely closure to families who have lost loved ones. We recommend implementing combined interventional education and consultation with expert pathologists, and a well-followed structured method of death classification as the best course of practice.

Antibodies are used in many areas of biomedical and clinical research, but many of these antibodies have not been adequately characterized, which casts doubt on the results reported in many scientific papers. This problem is compounded by a lack of suitable control experiments in many studies. In this article we review the history of the antibody characterization crisis, and we document efforts and initiatives to address the problem, notably for antibodies that target human proteins. We also present recommendations for a range of stakeholders - researchers, universities, journals, antibody vendors and repositories, scientific societies and funders - to increase the reproducibility of studies that rely on antibodies.

BACKGROUND: We prospectively assessed the reproducibility of a novel low-dose single-volume dynamic computed tomography (CT) myocardial blood flow measurement technique. METHODS: Thirty-four pairs of measurements were made under rest and stress conditions in 13 swine (54.3 ± 12.3 kg). One or two acquisition pairs were acquired in each animal with a 10-min delay between each pair. Contrast (370 mgI/mL; 0.5 mL/kg) and a diluted contrast/saline chaser (0.5 mL/kg; 30:70 contrast/saline) were injected peripherally at 5 mL/s, followed by bolus tracking and acquisition of a single volume scan (100 kVp; 200 mA) with a 320-slice CT scanner. Bolus tracking and single volume scan data were used to derive perfusion in mL/min/g using a first-pass analysis model; the coronary perfusion territories of the left anterior descending (LAD), left circumflex (LCx), and right coronary artery (RCA) were automatically assigned using a previously validated minimum-cost path technique. The reproducibility of CT myocardial perfusion measurement within the LAD, LCx, RCA, and the whole myocardium was assessed via regression analysis. The average CT dose index (CTDI) of perfusion measurement was recorded. RESULTS: The repeated first (Pmyo1) and second (Pmyo2) single-volume CT perfusion measurements were related by Pmyo2 = 1.01Pmyo1 - 0.03(ρ = 0.96; RMSE = 0.08 mL/min/g; RMSE = 0.07 mL/min/g) for the whole myocardium, and by Preg2 = 0.86Preg1 + 0.13(ρ = 0.87; RMSE = 0.31 mL/min/g; RMSE = 0.29 mL/min/g) for the LAD, LCx, and RCA perfusion territories. The average CTDI of the single-volume CT perfusion measurement was 10.5 mGy. CONCLUSION: The single-volume CT blood flow measurement technique provides reproducible low-dose myocardial perfusion measurement using only bolus tracking data and a single whole-heart volume scan. RELEVANCE STATEMENT: The single-volume CT blood flow measurement technique is a noninvasive tool that reproducibly measures myocardial perfusion and provides coronary CT angiograms, allowing for simultaneous anatomic-physiologic assessment of myocardial ischemia. KEY POINTS: A low-dose single-volume dynamic CT myocardial blood flow measurement technique is reproducible. Motion misregistration artifacts are eliminated using a single-volume CT perfusion technique. This technique enables combined anatomic-physiologic assessment of coronary artery disease.

Proximity labeling (PL) via biotinylation coupled with mass spectrometry (MS) captures spatial proteomes in cells. Large-scale processing requires a workflow minimizing hands-on time and enhancing quantitative reproducibility. We introduced a scalable PL pipeline integrating automated enrichment of biotinylated proteins in a 96-well plate format. Combining this with optimized quantitative MS based on data-independent acquisition (DIA), we increased sample throughput and improved protein identification and quantification reproducibility. We applied this pipeline to delineate subcellular proteomes across various compartments. Using the 5HT2A serotonin receptor as a model, we studied temporal changes of proximal interaction networks induced by receptor activation. In addition, we modified the pipeline for reduced sample input to accommodate CRISPR-based gene knockout, assessing dynamics of the 5HT2A network in response to perturbation of selected interactors. This PL approach is universally applicable to PL proteomics using biotinylation-based PL enzymes, enhancing throughput and reproducibility of standard protocols.

PURPOSE: To evaluate Humphrey Visual Field (HVF) test reliability and its associated risk factors in children with glaucoma or glaucoma suspect. DESIGN: Retrospective cohort study. METHODS: None. SETTING: Single-center childhood glaucoma clinic. PATIENT POPULATION: One hundred thirty-six patients aged ≤18 years with glaucoma/glaucoma suspect, and least 1 completed 24 to 2 HVF test between 2018 and 2023. OBSERVATION PROCEDURE: Demographic and clinical characteristics including age, primary language, visual acuity (VA), and glaucoma diagnosis were extracted from electronic health records. MAIN OUTCOME MEASURES: HVF 24 to 2 testing metrics, including FP, FN, and FL. Tests were defined as reliable using manufacturer guidelines of ≤33% FP, ≤33% FN, and ≤20% FL. For each patient, a reliability score was calculated as the percentage of reliable tests among all tests completed. A multivariable logistic regression model was used to determine factors associated with test-level reliability (yes/no). A multivariable linear regression model was used to determine factors associated with patient-level reliability score. RESULTS: Among 634 HVFs from 136 patients (Mean ± SD age at first test 12.0 ± 3.2 years, 47.8% female), 51.3% were reliable. Older age, better baseline VA, and English as primary language were associated with greater odds of test-level reliability (P < .04). Mean ± SD patient-level reliability score was 51.7 ± 38.1%. Older age at first clinic visit, better baseline VA, and English as primary language were associated with higher reliability scores (all P < .02), and number of prior VF tests was not (P = .56). CONCLUSIONS: Younger age, worse visual acuity, and non-English as primary language were associated with decreased reliability and should be considered when interpreting VF testing in children. A significant learning effect was not observed with repeated testing.

PURPOSE: To determine the reliability of a nine-point summary scale for grading intermediate age-related macular degeneration (AMD) image morphologic features based on the Early Treatment Diabetic Retinopathy Study (ETDRS) grid. METHODS: Two trained graders independently divided spectral domain-optical coherence tomography (SD-OCT) scans into nine subfields and then graded each subfield for the presence of intraretinal hyperreflective foci (HRF), reticular pseudodrusen (RPD), and incomplete or complete retinal pigment epithelium and outer retinal atrophy (iRORA or cRORA). Grading results were assessed by summing the subfield grades into a nine-point summary score and also by using an eye-level binary grade for presence of the finding in any subfield. Gwets first-order agreement coefficient (AC1) was calculated to assess intergrader agreement. RESULTS: Images of 79 eyes from 52 patients were evaluated. Intergrader agreement was higher when the OCT grades were summarized with a nine-point summary score (Gwets AC1 0.92, 0.89, 0.99, and 0.99 for HRF, RPD, iRORA, and cRORA, respectively) compared with the eye-level binary grade (Gwets AC1 0.75, 0.76, 0.97, and 0.96 for HRF, RPD, iRORA, and cRORA, respectively), with significant differences detected for HRF and RPD. CONCLUSIONS: The use of a nine-point summary score showed higher reliability in grading when compared to the binary subfield- and eye-level data, and thus may offer more precise estimation of AMD disease staging. TRANSLATIONAL RELEVANCE: These findings suggest that a nine-point summary score could be a useful means of disease staging by using findings on OCT in clinical studies of AMD.

SIGNIFICANCE: Spatial frequency domain imaging (SFDI) applies patterned near-infrared illumination to quantify the optical properties of subsurface tissue. The periocular region is unique due to its complex ocular adnexal anatomy. Although SFDI has been successfully applied to relatively flat in vivo tissues, regions that have significant height variations and curvature may result in optical property inaccuracies. AIM: We characterize the geometric impact of the periocular region on SFDI imaging reliability. APPROACH: SFDI was employed to measure the reduced scattering coefficient ( μ s ) and absorption coefficient ( μ a ) of the periocular region in a cast facial tissue-simulating phantom by capturing images along regions of interest (ROIs): inferior temporal quadrant (ITQ), inferior nasal quadrant (INQ), superior temporal quadrant (STQ), central eyelid margin (CEM), rostral lateral nasal bridge (RLNB), and forehead (FH). The phantom was placed on a chin rest and imaged nine times from an en face or side profile position, and the flat back of the phantom was measured 15 times. RESULTS: The measured μ a and μ s of a cast facial phantom are accurate when comparing the ITQ, INQ, STQ, and FH to its flat posterior surface. Paired t tests of ITQ, INQ, STQ, and FH μ a and μ s concluded that there is not enough evidence to suggest that imaging orientation impacted the measurement accuracy. Regions of extreme topographical variation, i.e., CEM and RLNB, did exhibit differences in measured optical properties. CONCLUSIONS: We are the first to evaluate the geometric implications of wide-field imaging along the periocular region using a solid tissue-simulating facial phantom. Results suggest that the ITQ, INQ, STQ, and FH of a generalized face have minimal impact on the SFDI measurement accuracy. Areas with heightened topographic variation exhibit measurement variability. Device and facial positioning do not appear to bias measurements. These findings confirm the need to carefully select ROIs when measuring optical properties along the periocular region.

Machine learning can be used to define subtypes of psychiatric conditions based on shared biological foundations of mental disorders. Here we analyzed cross-sectional brain images from 4,222 individuals with schizophrenia and 7038 healthy subjects pooled across 41 international cohorts from the ENIGMA, non-ENIGMA cohorts and public datasets. Using the Subtype and Stage Inference (SuStaIn) algorithm, we identify two distinct neurostructural subgroups by mapping the spatial and temporal trajectory of gray matter change in schizophrenia. Subgroup 1 was characterized by an early cortical-predominant loss with enlarged striatum, whereas subgroup 2 displayed an early subcortical-predominant loss in the hippocampus, striatum and other subcortical regions. We confirmed the reproducibility of the two neurostructural subtypes across various sample sites, including Europe, North America and East Asia. This imaging-based taxonomy holds the potential to identify individuals with shared neurobiological attributes, thereby suggesting the viability of redefining existing disorder constructs based on biological factors.

INTRODUCTION: Fear-avoidance beliefs (FAB) play a crucial role in the treatment outcomes of post-surgery patients. These beliefs can lead to activity avoidance, increased pain, and decreased quality of life. Therefore, accurately measuring these beliefs in Iranian patients is of significant importance. The Fear-Avoidance Belief Questionnaire (FABQ) is a patient-reported questionnaire that evaluates individuals FAB. Since the validity and reliability of the Persian version of FABQ (FABQ-P) have not been assessed based on the Iranian population and sociocultural contexts, the current study has been implemented to determine the reliability and validity of the FABQ-P among Iranian post-operative patients by translation and psychometric properties. METHODS: This methodological study conducted in 2023, a sample of 400 patients who had undergone surgery were selected using a convenience sampling method. The scale used in the study was translated and its psychometric properties were evaluated through network analysis and assessments of construct validity (including exploratory and confirmatory factor analysis), convergent validity, and discriminant validity. Additionally, the study assessed the internal consistency of the scale. RESULTS: The MLEFA results with Promax and Kaiser Normalization rotation yielded two factors explaining 57.91% of the variance, encompassing 13 items. Also, the model was approved by CFA. Convergent and discriminant validity have been confirmed through the following criteria: Average Variance Extracted (AVE) exceeding 0.5, Composite Reliability (CR) surpassing 0.7, and Heterotrait-Monotrait Ratio of Correlations (HTMT) equating to 0.597. As for reliability, Cronbachs alpha, composite reliability (CR), and MaxR for all constructs were greater than 0.7, demonstrating good internal consistency. CONCLUSION: As demonstrated by the results, the FABQ-P has a satisfactory level of reliability along with authentic validity according to the sociocultural contexts of Iranian post-operative patients.

The biomedical research community addresses reproducibility challenges in animal studies through standardized nomenclature, improved experimental design, transparent reporting, data sharing, and centralized repositories. The ARRIVE guidelines outline documentation standards for laboratory animals in experiments, but genetic information is often incomplete. To remedy this, we propose the Laboratory Animal Genetic Reporting (LAG-R) framework. LAG-R aims to document animals genetic makeup in scientific publications, providing essential details for replication and appropriate model use. While verifying complete genetic compositions may be impractical, better reporting and validation efforts enhance reliability of research. LAG-R standardization will bolster reproducibility, peer review, and overall scientific rigor.

OBJECTIVE: Increased subcutaneous and visceral adipose tissue (SAT/VAT) volume is associated with risk for cardiometabolic diseases. This work aimed to develop and evaluate automated abdominal SAT/VAT segmentation on longitudinal MRI in adults with overweight/obesity using attention-based competitive dense (ACD) 3D U-Net and 3D nnU-Net with full field-of-view volumetric multi-contrast inputs. MATERIALS AND METHODS: 920 adults with overweight/obesity were scanned twice at multiple 3 T MRI scanners and institutions. The first scan was divided into training/validation/testing sets (n = 646/92/182). The second scan from the subjects in the testing set was used to evaluate the generalizability for longitudinal analysis. Segmentation performance was assessed by measuring Dice scores (DICE-SAT, DICE-VAT), false negatives (FN), and false positives (FP). Volume agreement was assessed using the intraclass correlation coefficient (ICC). RESULTS: ACD 3D U-Net achieved rapid ( 0.997) in longitudinal analysis. DISCUSSION: ACD 3D U-Net and 3D nnU-Net can be automated tools to quantify abdominal SAT/VAT volume rapidly, accurately, and longitudinally in adults with overweight/obesity.

As the microbiome field moves from descriptive and associative research to mechanistic and interventional studies, being able to account for all confounding variables in the experimental design, which includes the maternal effect1, cage effect2, facility differences3, as well as laboratory and sample handling protocols4, is critical for interpretability of results. Despite significant procedural and bioinformatic improvements, unexplained variability and lack of replicability still occur. One underexplored factor is that the microbiome is dynamic and exhibits diurnal oscillations that can change microbiome composition5-7. In this retrospective analysis of 16S amplicon sequencing studies in male mice, we show that sample collection time affects the conclusions drawn from microbiome studies and its effect size is larger than those of a daily experimental intervention or dietary changes. The timing of divergence of the microbiome composition between experimental and control groups is unique to each experiment. Sample collection times as short as only 4 hours apart can lead to vastly different conclusions. Lack of consistency in the time of sample collection may explain poor cross-study replicability in microbiome research. The impact of diurnal rhythms on the outcomes and study design of other fields is unknown but likely significant.

Coronary artery calcification is a significant predictor of cardiovascular disease, with current detection methods like Agatston scoring having limitations in sensitivity. This study aimed to evaluate the effectiveness of a novel CAC quantification method using dual-energy material decomposition, particularly its ability to detect low-density calcium and microcalcifications. A simulation study was conducted comparing the dual-energy material decomposition technique against the established Agatston scoring method and the newer volume fraction calcium mass technique. Detection accuracy and calcium mass measurement were the primary evaluation metrics. The dual-energy material decomposition technique demonstrated fewer false negatives than both Agatston scoring and volume fraction calcium mass, indicating higher sensitivity. In low-density phantom measurements, material decomposition resulted in only 7.41% false-negative (CAC = 0) measurements compared to 83.95% for Agatston scoring. For high-density phantoms, false negatives were removed (0.0%) compared to 20.99% in Agatston scoring. The dual-energy material decomposition technique presents a more sensitive and reliable method for CAC quantification.

IntroductionCoronary artery calcium (CAC) scans contain useful information beyond the Agatston CAC score that is not currently reported. We recently reported that artificial intelligence (AI)-enabled cardiac chambers volumetry in CAC scans (AI-CAC™) predicted incident atrial fibrillation in the Multi-Ethnic Study of Atherosclerosis (MESA). In this study, we investigated the performance of AI-CAC cardiac chambers for prediction of incident heart failure (HF).MethodsWe applied AI-CAC to 5750 CAC scans of asymptomatic individuals (52% female, White 40%, Black 26%, Hispanic 22% Chinese 12%) free of known cardiovascular disease at the MESA baseline examination (2000-2002). We used the 15-year outcomes data and compared the time-dependent area under the curve (AUC) of AI-CAC volumetry versus NT-proBNP, Agatston score, and 9 known clinical risk factors (age, gender, diabetes, current smoking, hypertension medication, systolic and diastolic blood pressure, LDL, HDL for predicting incident HF over 15 years.ResultsOver 15 years of follow-up, 256 HF events accrued. The time-dependent AUC [95% CI] at 15 years for predicting HF with AI-CAC all chambers volumetry (0.86 [0.82,0.91]) was significantly higher than NT-proBNP (0.74 [0.69, 0.77]) and Agatston score (0.71 [0.68, 0.78]) (p ​

BACKGROUND: Social desirability can negatively affect the validity of self-reported measures, including underreporting of stigmatized behaviors like alcohol consumption. The Marlowe-Crowne Social Desirability Scale (SDS) is widely implemented and comprised of Denial and Attribution Domains (i.e., tendencies to deny undesirable traits or attribute socially desirable traits to oneself, respectively). Yet, limited psychometric research has been conducted in sub-Saharan Africa, where the prevalence of unhealthy alcohol consumption is high as well as religiosity and hierarchical social norms. To address this gap, we (a) conducted an exploratory study assessing certain psychometric properties of the 28-item SDS (Runyankole-translated) among persons with HIV (PWH) in Uganda, and (b) examined the relationship between social desirability and self-reported alcohol use. METHODS: We pooled baseline data (N = 1153) from three studies of PWH engaged in alcohol use from 2017 to 2021. We assessed the translated scales construct validity (via confirmatory factor analysis), internal consistency, item performance, differential item functioning by gender, concurrent validity with the DUREL religiosity index domains, and the association between social desirability and self-reported alcohol use. RESULTS: Participants had a mean age of 40.42 years, 63% were men, and 91% had an undetectable HIV viral load. The 28-item SDS had satisfactory construct validity (Model fit indices: RMSEA = 0.07, CFI = 0.84, TLI = 0.82) and internal consistency (Denial Domain ΩTotal = 0.82, Attribution Domain ΩTotal = 0.69). We excluded Item 14 (I never hesitate to help someone in trouble) from the Attribution Domain, which mitigated differential measurement error by gender and slightly improved the construct validity (Model fit indices: RMSEA = 0.06, CFI = 0.86, TLI = 0.85) and reliability (Attribution Domain ΩTotal = 0.72) of the 27-item modified SDS. Using the 27-item SDS, we found that social desirability was weakly correlated with religiosity and inversely associated with self-reported alcohol use after adjusting for biomarker-measured alcohol use and other confounders (β = -0.05, 95% confidence interval: -0.09 to -0.01, p-value = 0.03). CONCLUSIONS: We detected and mitigated measurement error in the 28-item Runyankole-translated SDS, and found that the modified 27-item scale had satisfactory construct validity and internal consistency in our sample. Future studies should continue to evaluate the psychometric properties of the Runyankole-translated SDS, including retranslating Item 14 and reevaluating its performance.

Digital PCR (dPCR) holds immense potential for precisely detecting nucleic acid markers essential for personalized medicine. However, its broader application is hindered by high consumable costs, complex procedures, and restricted multiplexing capabilities. To address these challenges, an all-in-one dPCR system is introduced that eliminates the need for microfabricated chips, offering fully automated operations and enhanced multiplexing capabilities. Using this innovative oscillation-induced droplet generation technique, OsciDrop, this system supports a comprehensive dPCR workflow, including precise liquid handling, pipette-based droplet printing, in situ thermocycling, multicolor fluorescence imaging, and machine learning-driven analysis. The system's reliability is demonstrated by quantifying reference materials and evaluating HER2 copy number variation in breast cancer. Its multiplexing capability is showcased with a quadruplex dPCR assay that detects key EGFR mutations, including 19Del, L858R, and T790M in lung cancer. Moreover, the digital stepwise melting analysis (dSMA) technique is introduced, enabling high-multiplex profiling of seven major EGFR variants spanning 35 subtypes. This innovative dPCR system presents a cost-effective and versatile alternative, overcoming existing limitations and paving the way for transformative advances in precision diagnostics.

PurposeTo assess the feasibility and performance of Vivid Vision Perimetry (VVP), a new virtual reality (VR)-based visual field platform.MethodsChildren 7-18 years of age with visual acuity of 20/80 or better undergoing Humphrey visual field (HVF) testing were recruited to perform VVP, a VR-based test that uses suprathreshold stimuli to test 54 field locations and calculates a fraction seen score. Pearson correlation coefficients were calculated to evaluate correlation between HVF mean sensitivity and VVP mean fraction seen scores. Participants were surveyed regarding their experience.ResultsA total of 37 eyes of 23 participants (average age, 12.9 ± 3.1 years; 48% female) were included. All participants successfully completed VVP testing. Diagnoses included glaucoma (12), glaucoma suspect (7), steroid-induced ocular hypertension (3), and craniopharyngioma (1). Sixteen participants had prior HVF experience, and none had prior VVP experience, although 7 had previously used VR. Of the 23 HVF tests performed, 9 (39%) were unreliable due to fixation losses, false positives, or false negatives. Similarly, 35% of VVP tests were unreliable (as defined by accuracy of blind spot detection). Excluding unreliable HVF tests, the correlation between HVF average mean sensitivity and VVP mean fraction seen score was 0.48 (P = 0.02; 95% CI, 0.09-0.74). When asked about preference for the VVP or HVF examination, all participants favored the VVP, and 70% were "very satisfied" with VVP.ConclusionsIn our cohort of 23 pediatric subjects, VVP proved to be a clinically feasible VR-based visual field testing, which was uniformly preferred over HVF.

BACKGROUND: Single-cell transcriptome sequencing (scRNA-Seq) has allowed new types of investigations at unprecedented levels of resolution. Among the primary goals of scRNA-Seq is the classification of cells into distinct types. Many approaches build on existing clustering literature to develop tools specific to single-cell. However, almost all of these methods rely on heuristics or user-supplied parameters to control the number of clusters. This affects both the resolution of the clusters within the original dataset as well as their replicability across datasets. While many recommendations exist, in general, there is little assurance that any given set of parameters will represent an optimal choice in the trade-off between cluster resolution and replicability. For instance, another set of parameters may result in more clusters that are also more replicable. RESULTS: Here, we propose Dune, a new method for optimizing the trade-off between the resolution of the clusters and their replicability. Our method takes as input a set of clustering results-or partitions-on a single dataset and iteratively merges clusters within each partitions in order to maximize their concordance between partitions. As demonstrated on multiple datasets from different platforms, Dune outperforms existing techniques, that rely on hierarchical merging for reducing the number of clusters, in terms of replicability of the resultant merged clusters as well as concordance with ground truth. Dune is available as an R package on Bioconductor: https://www.bioconductor.org/packages/release/bioc/html/Dune.html . CONCLUSIONS: Cluster refinement by Dune helps improve the robustness of any clustering analysis and reduces the reliance on tuning parameters. This method provides an objective approach for borrowing information across multiple clusterings to generate replicable clusters most likely to represent common biological features across multiple datasets.

Monofluoroacetate is a highly lethal toxin that causes death by inhibiting cellular adenosine triphosphate (ATP) production. The heart and brain are the primary target organs. Acute death is attributed to cardiac fibrillation and/or convulsions. Although it occurs naturally in some plants, a major source of animal intoxication is access to sodium monofluoroacetate (NaMFA) pesticide, which continues to be a concern in the USA and around the world despite restricted use in some countries including the USA. There are also concerns about misuse of this pesticide for malicious poisoning. Currently, a tissue-based diagnostic method for NaMFA intoxication in animals is lacking. There is a critical need by the veterinary diagnostic community for a simple, sensitive and reliable tissue-based diagnostic test to confirm NaMFA poisoning in animals. We have developed and extensively evaluated a sensitive novel liquid chromatography combined with tandem mass spectrometry method suitable for this purpose. The limits of detection and limits of quantitation are 1.7 and 5.0 ng/g, respectively. The accuracy and precision met or exceeded expectations. The method performance was verified using the incurred kidney obtained from animal diagnostic cases. This novel kidney-based method is now available for clinical use and can help with diagnostic purposes, including detecting potential issues related to animal foods.

BACKGROUND: To evaluate the reproducibility of a vessel-specific minimum cost path (MCP) technique used for lobar segmentation on noncontrast computed tomography (CT). METHODS: Sixteen Yorkshire swine (49.9 ± 4.7 kg, mean ± standard deviation) underwent a total of 46 noncontrast helical CT scans from November 2020 to May 2022 using a 320-slice scanner. A semiautomatic algorithm was employed by three readers to segment the lung tissue and pulmonary arterial tree. The centerline of the arterial tree was extracted and partitioned into six subtrees for lobar assignment. The MCP technique was implemented to assign lobar territories by assigning lung tissue voxels to the nearest arterial tree segment. MCP-derived lobar mass and volume were then compared between two acquisitions, using linear regression, root mean square error (RMSE), and paired sample t-tests. An interobserver and intraobserver analysis of the lobar measurements was also performed. RESULTS: The average whole lung mass and volume was 663.7 ± 103.7 g and 1,444.22 ± 309.1 mL, respectively. The lobar mass measurements from the initial (MLobe1) and subsequent (MLobe2) acquisitions were correlated by MLobe1 = 0.99 MLobe2 + 1.76 (r = 0.99, p = 0.120, RMSE = 7.99 g). The lobar volume measurements from the initial (VLobe1) and subsequent (VLobe2) acquisitions were correlated by VLobe1 = 0.98VLobe2 + 2.66 (r = 0.99, p = 0.160, RSME = 15.26 mL). CONCLUSIONS: The lobar mass and volume measurements showed excellent reproducibility through a vessel-specific assignment technique. This technique may serve for automated lung lobar segmentation, facilitating clinical regional pulmonary analysis. RELEVANCE STATEMENT: Assessment of lobar mass or volume in the lung lobes using noncontrast CT may allow for efficient region-specific treatment strategies for diseases such as pulmonary embolism and chronic thromboembolic pulmonary hypertension. KEY POINTS: • Lobar segmentation is essential for precise disease assessment and treatment planning. • Current methods for segmentation using fissure lines are problematic. • The minimum-cost-path technique here is proposed and a swine model showed excellent reproducibility for lobar mass measurements. • Interobserver agreement was excellent, with intraclass correlation coefficients greater than 0.90.

Machine learning (ML) methods are proliferating in scientific research. However, the adoption of these methods has been accompanied by failures of validity, reproducibility, and generalizability. These failures can hinder scientific progress, lead to false consensus around invalid claims, and undermine the credibility of ML-based science. ML methods are often applied and fail in similar ways across disciplines. Motivated by this observation, our goal is to provide clear recommendations for conducting and reporting ML-based science. Drawing from an extensive review of past literature, we present the REFORMS checklist (recommendations for machine-learning-based science). It consists of 32 questions and a paired set of guidelines. REFORMS was developed on the basis of a consensus of 19 researchers across computer science, data science, mathematics, social sciences, and biomedical sciences. REFORMS can serve as a resource for researchers when designing and implementing a study, for referees when reviewing papers, and for journals when enforcing standards for transparency and reproducibility.

PURPOSE: The Quality of Recovery-15 (QoR-15) tool, validated for measuring postoperative recovery following scheduled surgeries, has not been psychometrically assessed in emergency contexts. Moreover, the QoR-15s associations with long-term outcomes remain underexplored. This study aimed to confirm the validity and reliability of the QoR-15 following emergency surgery and assess its association with three-month postoperative quality of life. METHODS: We conducted a prospective cohort study (August 2021-April 2022) on adult patients who underwent emergency surgery. The QoR-15 questionnaire was administered before surgery (H0) and at 24 hr (H24) and 48 hr (H48) after surgery. We examined the H24 scores associations with both the three-month quality of life, as assessed by the EQ-5D scale, and the number of days spent at home at 30 (DAH30) and 90 (DAH90) days. RESULTS: Of the 375 included patients, 352 (94%) completed the QoR-15 at H24 and 338 (90%) were followed up at three months. The population represented the following diverse surgical specialties: orthopedic (51%), gastrointestinal (27%), urologic (13%), and others (9%). The QoR-15 questionnaire confirmed all psychometric qualities (internal consistency, reproducibility, responsiveness, acceptability, construct, and convergent validities) in the emergency context. The average minimum clinical difference was 8.0 at H24. There was an association between QoR-15 at H24 and the three-month quality of life (r = 0.24; 95% confidence interval [CI], 0.14 to 0.34; P

Sphingolipids are an essential subset of bioactive lipids found in most eukaryotic cells that contribute to membrane biophysical properties and are involved in cellular differentiation, recognition, and mediating interactions. The described nanoHPLC-ESI-Q/ToF methodology utilizes known biosynthetic pathways, accurate mass detection, optimized collision-induced disassociation, and a robust nanoflow chromatographic separation for the analysis of intact sphingolipids found in human tissue, cells, and serum. The methodology was developed and validated with an emphasis on addressing the common issues experienced in profiling these amphipathic lipids, which are part of the glycocalyx and lipidome. The high sensitivity obtained using nanorange flow rates with robust chromatographic reproducibility over a wide range of concentrations and injection volumes results in confident identifications for profiling these low-abundant biomolecules.

To accelerate medical breakthroughs, the All of Us Research Program aims to collect data from over one million participants. This report outlines processes used to construct the All of Us Social Determinants of Health (SDOH) survey and presents the psychometric characteristics of SDOH survey measures in All of Us. A consensus process was used to select SDOH measures, prioritizing concepts validated in diverse populations and other national cohort surveys. Survey item non-response was calculated, and Cronbachs alpha was used to analyze psychometric properties of scales. Multivariable logistic regression models were used to examine associations between demographic categories and item non-response. Twenty-nine percent (N = 117,783) of eligible All of Us participants submitted SDOH survey data for these analyses. Most scales had less than 5% incalculable scores due to item non-response. Patterns of item non-response were seen by racial identity, educational attainment, income level, survey language, and age. Internal consistency reliability was greater than 0.80 for almost all scales and most demographic groups. The SDOH survey demonstrated good to excellent reliability across several measures and within multiple populations underrepresented in biomedical research. Bias due to survey non-response and item non-response will be monitored and addressed as the survey is fielded more completely.

This paper describes the SocialVidStim-a database of video stimuli available to the scientific community depicting positive and negative social evaluative and neutral statements. The SocialVidStim comprises 53 diverse individuals reflecting the demographic makeup of the USA, ranging from 9 to 41 years old, saying 20-60 positive and 20-60 negative social evaluative statements (e.g. 'You are a very trustworthy/annoying person'), and 20-60 neutral statements (e.g. 'The sky is blue'), totaling 5793 videos post-production. The SocialVidStim are designed for use in behavioral and functional magetic resonance imaging paradigms, across developmental stages, in diverse populations. This study describes stimuli development and reports initial validity and reliability data on a subset videos (N = 1890) depicting individuals aged 18-41 years. Raters perceive videos as expected: positive videos elicit positively valenced ratings, negative videos elicit negatively valenced ratings and neutral videos are rated as neutral. Test-retest reliability data demonstrate intraclass correlations in the good-to-excellent range for negative and positive videos and the moderate range for neutral videos. We also report small effects on valence and arousal that should be considered during stimuli selection, including match between rater and actor sex and actor believability. The SocialVidStim is a resource for researchers and we offer suggestions for using the SocialVidStim in future research.

PURPOSE: This study sought to identify the sources of differential performance and misclassification error among local (Indian) and external (non-Indian) corneal specialists in identifying bacterial and fungal keratitis based on corneal photography. METHODS: This study is a secondary analysis of survey data assessing the ability of corneal specialists to identify acute bacterial versus fungal keratitis by using corneal photography. One-hundred images of 100 eyes from 100 patients with acute bacterial or fungal keratitis in South India were previously presented to an international cohort of cornea specialists for interpretation over the span of April to July 2021. Each expert provided a predicted probability that the ulcer was either bacterial or fungal. Using these data, we performed multivariable linear regression to identify factors predictive of expert performance, accounting for primary practice location and surrogate measures to infer local fungal ulcer prevalence, including locality, latitude, and dew point. In addition, Brier score decomposition was used to determine experts reliability (calibration) and resolution (boldness) and were compared between local (Indian) and external (non-Indian) experts. RESULTS: Sixty-six experts from 16 countries participated. Indian practice location was the only independently significant predictor of performance in multivariable linear regression. Resolution among Indian experts was significantly better (0.08) than among non-Indian experts (0.01; P < 0.001), indicating greater confidence in their predictions. There was no significant difference in reliability between the two groups ( P = 0.40). CONCLUSION: Local cornea experts outperformed their international counterparts independent of regional variability in tropical risk factors for fungal keratitis. This may be explained by regional characteristics of infectious ulcers with which local corneal specialists are familiar.

ObjectiveAssessing functional limitations for adults at high risk of frailty yields valuable information for identifying those in need of therapy. We evaluate a self-report measure used to assess physical function among Medicare recipients in the United States.DesignSecondary analysis of the 2020 Medicare Health Outcomes Survey.SettingA random sample of adult enrollees of 510 managed care plans.Participants287,476 adults (37% completion rate): 58% women; 16% were

Interventional researchers face many design challenges when assessing intervention implementation in real-world settings. Intervention implementation requires holding fast on internal validity needs while incorporating external validity considerations (such as uptake by diverse subpopulations, acceptability, cost, and sustainability). Quasi-experimental designs (QEDs) are increasingly employed to achieve a balance between internal and external validity. Although these designs are often referred to and summarized in terms of logistical benefits, there is still uncertainty about (a) selecting from among various QEDs and (b) developing strategies to strengthen the internal and external validity of QEDs. We focus here on commonly used QEDs (prepost designs with nonequivalent control groups, interrupted time series, and stepped-wedge designs) and discuss several variants that maximize internal and external validity at the design, execution and implementation, and analysis stages.

Single-cell and single-nucleus RNA-sequencing technologies capture the expression of plant genes at an unprecedented resolution. Therefore, these technologies are gaining traction in plant molecular and developmental biology for elucidating the transcriptional changes across cell types in a specific tissue or organ, upon treatments, in response to biotic and abiotic stresses, or between genotypes. Despite the rapidly accelerating use of these technologies, collective and standardized experimental and analytical procedures to support the acquisition of high-quality data sets are still missing. In this commentary, we discuss common challenges associated with the use of single-cell transcriptomics in plants and propose general guidelines to improve reproducibility, quality, comparability, and interpretation and to make the data readily available to the community in this fast-developing field of research.

A wooden house frame consists of many different lumber pieces, but because of the regularity of these building blocks, the structure can be designed using straightforward geometrical principles. The design of multicomponent protein assemblies, in comparison, has been much more complex, largely owing to the irregular shapes of protein structures1. Here we describe extendable linear, curved and angled protein building blocks, as well as inter-block interactions, that conform to specified geometric standards; assemblies designed using these blocks inherit their extendability and regular interaction surfaces, enabling them to be expanded or contracted by varying the number of modules, and reinforced with secondary struts. Using X-ray crystallography and electron microscopy, we validate nanomaterial designs ranging from simple polygonal and circular oligomers that can be concentrically nested, up to large polyhedral nanocages and unbounded straight 'train track' assemblies with reconfigurable sizes and geometries that can be readily blueprinted. Because of the complexity of protein structures and sequence-structure relationships, it has not previously been possible to build up large protein assemblies by deliberate placement of protein backbones onto a blank three-dimensional canvas; the simplicity and geometric regularity of our design platform now enables construction of protein nanomaterials according to 'back of an envelope' architectural blueprints.

BACKGROUND: Active commuting to school can be a meaningful contributor to overall physical activity in children. To inform better micro-level urban design near schools that can support active commuting to school, there is a need for measures that capture these elements. This paper describes the adaptation of an observational instrument for use in assessing micro-scale environments around urban elementary schools in the United States. METHODS: The Micro-scale Audit of Pedestrian Streetscapes for Safe Routes to School (MAPS-SRTS) was developed from existing audit instruments not designed for school travel environments and modifications for the MAPS-SRTS instrument include the structure of the audit tool sections, the content, the observation route, and addition of new subscales. Subscales were analyzed for inter-rater reliability in a sample of 36 schools in Austin, TX. To assess reliability for each subscale, one-way random effects single-measure intraclass correlation coefficients (ICC) were used. RESULTS: Compared to the 30 original subscales, the adapted MAPS-SRTS included 26 (86.6%) subscales with revised scoring algorithms. Most MAPS-SRTS subscales had acceptable inter-rater reliability, with an ICC of 0.97 for the revised audit tool. CONCLUSIONS: The MAPS-SRTS audit tool is a reliable instrument for measuring the school travel environment for research and evaluation purposes, such as assessing human-scale determinants of active commuting to school behavior and documenting built environment changes from infrastructure interventions.

Managing patients with kidney allografts largely depends on biopsy diagnosis which is based on semiquantitative assessments of rejection features and extent of acute and chronic changes within the renal parenchyma. Current methods lack reproducibility while digital image data-driven computational models enable comprehensive and quantitative assays. In this study we aimed to develop a computational method for automated assessment of histopathology transformations within the tubulointerstitial compartment of the renal cortex. Whole slide images of modified Picrosirius red-stained biopsy slides were used for the training (n = 852) and both internal (n = 172) and external (n = 94) tests datasets. The pipeline utilizes deep learning segmentations of renal tubules, interstitium, and peritubular capillaries from which morphometry features were extracted. Seven indicators were selected for exploring the intrinsic spatial interactions within the tubulointerstitial compartment. A principal component analysis revealed two independent factors which can be interpreted as representing chronic and acute tubulointerstitial injury. A K-means clustering classified biopsies according to potential phenotypes of combined acute and chronic transformations of various degrees. We conclude that multivariate analyses of tubulointerstitial morphometry transformations enable extraction of and quantification of acute and chronic components of injury. The method is developed for renal allograft biopsies; however, the principle can be applied more broadly for kidney pathology assessment.