Variety Of Tests Research Articles

Impact of Device Type and Specimen Preparation on the Variability of the Indirect Tensile Cracking Test (IDT-CT) at Intermediate Temperatures

The Indirect Tensile Cracking Test (IDT-CT) is performed in accordance with ASTM D8225-19. This test method does not currently contain precision estimates. This creates potential issues when different test results are measured by individual laboratories conducting testing on the same asphalt mixture. In 2020, Phase I of an IDT-CT interlaboratory study (ILS) was conducted to establish precision estimates and statements for several indices associated with the IDT-CT (cracking tolerance index [CT index], fracture strain tolerance [FST], strength [St], and cracking resistance index [CRI]). This phase involved the evaluation of specimens fabricated and compacted by a third party laboratory and sent to participant laboratories for testing only. The objective of this paper was to assess the impact of device type and specimen preparation on the variability of IDT-CT results. This was accomplished through a second phase (Phase II) of the ILS program. This analysis involved the evaluation of specimens fabricated by the participant laboratories from loose mixtures, which were produced and sent from a third party laboratory along with detailed instructions for specimen fabrication and testing. The Phase II results suggest that device type might be a significant factor for mixtures with relatively low IDT-CT index values. Moreover, the precision estimates for the CT index, FST index, St, and CRI were determined. The precision estimates for single-operator conditions were similar, whether specimens of a given mixture were fabricated by the same laboratory or not. Finally, specimen preparation was found to induce additional variability in the precision estimates for multi-laboratory conditions.

Evaluation of autonomic nervous system functions by using tilt table test and heart rate variability in epileptic children

Objective: The value of head-up tilt test (HUTT) for differential diagnosis of epilepsy and the autonomic nervous system functions in
 epileptic children using heart rate variability (HRV) are studied.
 Patients and Methods: The study group consisted of 16 children with idiopatic/criptogenic epilepsy and 12 controls. Heart rate, PR
 interval, corrected QT (QTc) interval, QT and QTc dispersion were calculated using 12-lead electrocardiogram (ECG), HRV analysis
 was performed using the Holter recordings obtained both during HUTT and throughout the day. Time domain parameters, standard
 deviation of all RR intervals (SDNN), the standard deviation of mean NN intervals in five-minutes recording (SDANN), mean standard
 deviation of NN intervals in five-minutes recordings (SDNNi), root mean square of successive differences (RMSSD), count divided
 by the total number of all NN intervals (pNN50) and frequency domain parameters low frequency (LF), high frequency (HF), lowfrequency/
 high-frequency ratio (LF/HF) were calculated in both and compared between the two groups.
 Results: Head-up tilt test was positive in 4 epileptic children (25%), none of controls were positive. The heart rate of the patients were
 higher than the controls (p=0.015). LF/HF ratio in 24-hour Holter recordings, were significantly lower (1.13±0.6, 1.83±0.7 respectively,
 p=0.002); the SDANN during HUTT (28.7±20.2, 18.2 ± 19.9 respectively, p=0.024) were significantly higher in the patients than the
 controls.
 Conclusion: Head-up tilt test positivity is frequent in epileptic children, and cannot be used in differential diagnosis. HRV calculated
 both from 24 hour Holter recordings and Holter recordings under orthostatic stress were impaired in favour of parasympathetic
 system in epileptic children.

Asphalt concrete dynamic modulus prediction: Bayesian neural network approach

ABSTRACT This paper presents a probabilistic model for predicting the dynamic modulus |E*| of asphalt concrete (AC). A Bayesian Neural Network (BNN) trained on a substantial dataset collected from various states was employed. This approach accounts for the inherent stochasticity in the data generation process (i.e. aleatoric uncertainty) and addresses epistemic or model uncertainty as well. The model successfully predicted dynamic moduli for unseen testing datasets. In practice, predicted moduli could be as accurate and effective as measured values, considering the model uncertainty and |E*| test variability. However, an elevated epistemic uncertainty at extremely low and high |E*| ranges would be expected due to relatively low data points. To enhance interpretability, Shapley Additive Explanations (SHAP) analysis was utilised, demonstrating adherence to physical laws. The primary factors influencing predicted moduli, as identified by the analysis, are temperature, frequency, voids in mineral aggregates, reclaimed asphalt pavement content, and binder low-performance grade. The BNN model was deployed in a web application, making it accessible for application.

Testing of highly configurable cyber–physical systems — Results from a two-phase multiple case study

Cyber–physical systems are commonly highly configurable. Testing such systems is particularly challenging because they comprise numerous heterogeneous components that can be configured and combined in different ways. Despite a plethora of work investigating software testing in general and software product line testing in particular, variability in tests and how it is applied in industry with cyber–physical systems is not well understood. In this paper, we report on a multiple case study with four companies maintaining highly configurable cyber–physical systems focusing on their testing practices, with a particular focus on variability. Based on the results of the multiple case study, we conducted an interactive survey with experienced engineers from eight companies, including the initial four. We reflect on the lessons learned from the multiple case study. We conclude that experience-based selection of configurations for testing is currently predominant. We learned that variability modeling techniques and tools are not utilized and the dependencies between configuration options are only partially modeled at best using custom artifacts such as spreadsheets or configuration files. Another finding is that companies have the need and desire to cover more configuration combinations by automated tests. Our findings raise many questions interesting to the scientific community and motivating future research.

Understanding Atherosclerosis Pathophysiology: Can Additive Manufacturing Be Helpful?

Atherosclerosis is one of the leading causes of death worldwide. Although this subject arouses much interest, there are limitations associated with the biomechanical investigation done in atherosclerotic tissues, namely the unstandardized tests for the mechanical characterization of these tissues and the inherent non-consensual results obtained. The variability of tests and typologies of samples hampers direct comparisons between results and hinders the complete understanding of the pathologic process involved in atherosclerosis development and progression. Therefore, a consensual and definitive evaluation of the mechanical properties of healthy and atherosclerotic blood vessels would allow the production of physical biomodels that could be used for surgeons' training and personalized surgical planning. Additive manufacturing (AM), commonly known as 3D printing, has attracted significant attention due to the potential to fabricate biomodels rapidly. However, the existing literature regarding 3D-printed atherosclerotic vascular models is still very limited. Consequently, this review intends to present the atherosclerosis disease and the consequences of this pathology, discuss the mechanical characterization of atherosclerotic vessels/plaques, and introduce AM as a potential strategy to increase the understanding of atherosclerosis treatment and pathophysiology.

Taking More Society for Academic Emergency Medicine Practice Tests Does Not Lead to Improved National EM-M4 Exam Scores

Emergency medicine (EM) is a required clerkship for third-year medical students, and an elective EM acting internship (AI) is available to fourth-year students at our institution. The Society for Academic Emergency Medicine's (SAEM) National Emergency Medicine M4 Examination (EM-M4) is administered to students at the end of the EM AI experience. To prepare for the exam, students gain access to 23 practice tests available from SAEM. In this study we investigate the correlation between the number of practice tests taken and EM-M4 performance. We collected data for EM-M4 and the US Medical Licensing Exam (USMLE) Step 2 Clinical Knowledge (CK) from students completing a MS4 EM clerkship in consecutive medical school classes from 2014-2017 at a private medical school. In addition, we collected data during the clerkship on the number of practice exams taken and whether a comprehensive practice exam was taken. We analyzed the study population three ways to determine whether the number of practice tests impacted final exam results: a binary distribution (1-11 or 12-23 tests taken); quaternary distribution (1-6, 7-12, 13-18, or 19-23 tests taken); and individual test variability (1,2,3,…22,23 tests taken). Complete data for 147 students was used for data analysis. The EM-M4 showed moderate (r = 0.49) correlations with USMLE Step 2 CK. There was no significant difference in EM-M4 performance in the binary analysis (P ≤ 0.09), the quaternary analysis (P ≤ 0.09), or the continuous variable analysis (P ≤ 0.52). Inclusion of a comprehensive practice test also did not correlate with EM-M4 performance (P ≤ 0.78). Degree of utilization of SAEM practice tests did not seem to correlate with performance on the EM-M4 examination at our institution. This could be due to many factors including that the question bank is composed of items that had poor item discrimination, possible inadequate coverage of EM curriculum, and/or use of alternative study methods. While further investigation is needed, if our conclusions prove generalizable, then using the SAEM practice tests is an extraneous cognitive load from a modality without proven benefit.

Heart Rate Variability and Cold Pressor Test before Onset of Pre-eclampsia in Pregnant Women-A Longitudinal Study

Introduction: A major obstetric complication, that leads to severe maternal and foetal morbidity is Pre-eclampsia (PE). Studies evaluating the autonomic nervous activity in pregnant women with PE shows conflicting results. Previous studies are inadequate for the identification of the most useful tools to detect and monitor autonomic dysfunction prior to PE. The cold pressor test is a simple and validated test, in which the afferent sensory pathways are stimulated by the cold stimulus, resulting in an increase in Blood Pressure (BP). Aim: To evaluate the response to cold pressor test and Heart Rate Variability (HRV) to detect increased vascular reactivity and sympathetic activity prior to the clinical manifestation of PE in pregnant women. Materials and Methods: A longitudinal study was conducted in in the Department of Physiology at Hamdard Institute of Medical Sciences, HAHC Hospital, Jamia Hamdard, New Delhi, India. The duration of the study was 11 months, from December 2018 to November 2019. Subjects were 50 pregnant women, between age 18-40 years and of 12-14 weeks of gestation. Cold pressor test and HRV were parameters measured for the assessment of the autonomic functions during 12 and 21 weeks of gestational period. The Statistical Package for Social Sciences (SPSS) version 26.0 was used for analysis of the quantitative data. Paired t-test was done for comparison of all values. Results: The mean age of the study participants was 29±2.7 years. There was no hyper-reaction to cold pressor test at 12 weeks of gestation, nor the subjects showed any signs of PE. At 14 weeks of gestation, 2 (4%) showed hyper-reaction to cold pressor test. At 21 weeks of gestation, 3 (6%) subjects showed hyper-reactions to cold pressor test and out of them, 2 developed PE. Root Mean Square Standard Deviation (RMSSD) and difference between adjacent Standard Deviation of N-N intervals (SDNN) of HRV analysis were significantly higher in the first trimester as compared to 21 weeks of pregnancy. Conclusion: Response to cold pressor test showed increased vascular reactivity, as a sign before the development of PE. HRV analysis could not detect any significant features of increased sympathetic activity prior to the clinical manifestation of PE in pregnant women.

Prostate Specific Antigen Testing Behaviors for Prostate Cancer Screening Among U.S. Immigrants: A Cross-sectional Analysis Using the National Health Interview Survey.

Immigrants constitute 14% of the U.S. population, and this group is especially vulnerable to poor health care access. Prior research demonstrates U.S. immigrants have low rates of guideline-concordant breast and colorectal screening, but prostate cancer screening has not previously been evaluated. We sought to characterize screening behaviors among U.S. immigrants and to consider possible mechanisms to enhance PSA-based screening for this population. Data were obtained from the 2010, 2013, 2015, and 2018 National Health Interview Survey reports, which were the recent survey years that included questions about PSA testing. Complex samples logistic regression was performed to assess the relationship between immigrant-specific characteristics including region of birth, citizenship status, length of residence within the U.S., English language proficiency, and history of PSA testing. There were 22,997 survey respondents; 3,257 were foreign-born and 19,740 were U.S.-born. Rates of PSA testing were much lower among the foreign-born population compared to the U.S.-born population (43% vs 60%). Citizenship status, length of residence in the U.S. for more than 15 years, and English proficiency were directly linked to increased rates of PSA testing. There was significant variability in PSA testing among immigrant subgroups and Asian immigrants had the lowest rate of PSA testing. Annual physician visits and English language proficiency were associated with increased PSA testing among the U.S. immigrant population. Immigrants have relatively low rates of PSA testing. Improving health care utilization and language services may help to narrow the gap in guideline-concordant prostate cancer screening between immigrants and nonimmigrants.

Advanced glycation end-products are associated with diabetic neuropathy in young adults with type 1 diabetes.

Aims/hypothesisAdvanced glycation end-products (AGEs) may contribute to the development of diabetic neuropathy. In young adults with type 1 diabetes, we aimed to investigate the association between AGEs and cardiovascular autonomic neuropathy (CAN) and distal symmetric polyneuropathy (DSPN).MethodsThis cross-sectional study comprised 151 young adults. CAN was assessed by cardiovascular autonomic reflex tests; lying-to-standing test, deep breathing test (E/I), Valsalva manoeuvre, and heart rate variability indices; and the mean square of the sum of the squares of differences between consecutive R-R intervals and standard deviation of normal-to-normal intervals (SDNN), high- (HF) and low-frequency (LF) power, total frequency power, and the LF/HF ratio. DSPN was assessed by light touch, pain and vibration perception threshold (VPT), neuropathy questionnaires, and objective measures. AGEs were analysed in four groups using z-scores adjusted for relevant confounders and multiple testing: i) “glycolytic dysfunction”, ii) “lipid peroxidation”, iii) “oxidative stress”, and iv) “glucotoxicity”.ResultsA higher z-score of “glycolytic dysfunction” was associated with higher VPT (4.14% (95% CI 1.31; 7.04), p = 0.004) and E/I (0.03% (95% CI 0.01; 0.05), p = 0.005), “lipid peroxidation” was associated with higher LF/HF ratio (37.72% (95% CI 1.12; 87.57), p = 0.044), and “glucotoxicity” was associated with lower SDNN (−4.20% (95% CI −8.1416; −0.0896), p = 0.047). No significance remained after adjustment for multiple testing.Conclusions/interpretationsIn young adults with type 1 diabetes, increased levels of AGEs involving different metabolic pathways were associated with several measures of CAN and DSPN, suggesting that AGEs may play a diverse role in the pathogeneses of diabetic neuropathy.

Comparison of current methods for anti-dsDNA antibody detection and reshaping diagnostic strategies.

Anti-double-stranded DNA antibodies (anti-dsDNA) are considered a specific marker for systemic lupus erythematosus (SLE). Though the Farr technique was once the reference method for their detection, it has been almost entirely replaced by more recently developed assays. However, there is still no solid evidence of the commutability of these methods in terms of diagnostic accuracy and their correlation with the Crithidia luciliae immunofluorescence test (CLIFT). Anti-dsDNA antibody levels were measured in 80 subjects: 24 patients with SLE, 36 disease controls drawn from different autoimmune rheumatic diseases (14 systemic sclerosis, 10 Sjögren's syndrome, nine autoimmune myositis, three mixed connective tissue disease), 10 inflammatory arthritis and 10 apparently healthy blood donors by eight different methods: fluorescence enzyme immunoassay, microdot array, chemiluminescent immunoassay (two assays), multiplex flow immunoassay, particle multi-analyte technology immunoassay and two CLIFT. At the recommended manufacturer cut-off, the sensitivity varied from 67% to 92%, while the specificity ranged from 84% to 98%. Positive agreement among CLIFT and the other assays was higher than negative agreement. Mean agreement among methods assessed by the Cohen's kappa was 0.715, ranging from moderate (0.588) to almost perfect (0.888). Evaluation of the concordance among quantitative values by regression analysis showed a poor correlation index (mean r2, 0.66). The present study shows that current technologies for anti-dsDNA antibody detection are not fully comparable. In particular, their different correlation with CLIFT influences their positioning in the diagnostic algorithm for SLE (either in association or sequentially). Considering the high intermethod variability, harmonization and commutability of anti-dsDNA antibody testing remains an unachieved goal.

Plasma transfusion practices: A multicentre electronic audit.

Plasma is often transfused to patients with bleeding or requiring invasive procedures and with abnormal tests of coagulation. Chart audits find half of plasma transfusions unnecessary, resulting in avoidable complications and costs. This multicentre electronic audit was conducted to determine the proportion of plasma transfused without an indication and/or at a sub-therapeutic dose. Data were extracted on adult inpatients in 2017 at five academic sites from the hospital electronic chart, laboratory information systems and the Canadian Institute for Health Information Discharge Abstract Database. Electronic criteria for plasma transfusion outside recommended indications were: (1) international normalized ratio (INR) < 1.5 with no to moderate bleeding; (2) INR ≥ 1.5, with no to mild bleeding and no planned procedures; and (3) no INR before or after plasma infusion. Sub-therapeutic dose was defined as ≤2units transfused. In 1 year, 2590 patients received 6088 plasma transfusions encompassing 11,490 units of plasma occurred at the five sites. 77.7% of events were either outside indications or under-dosed. Of these, 34.8% of plasma orders had no indication identified, and 62% of these occurred in non-bleeding patients and no planned procedure with an isolated elevated INR. 70.7% of transfusions were under-dosed. Most plasma transfusions occurred in the intensive care unit or the operating room. Inter-hospital variability in peri-transfusion testing and dosing was observed. The majority of plasma transfusions are sub-optimal. Local hospital culture may be an important driver. Electronic audits, with definitions employed in this study, may be a practical alternative to costly chart audits.

Assessing the Generalizability of Deep Learning Models Trained on Standardized and Nonstandardized Images and Their Performance Against Teledermatologists: Retrospective Comparative Study.

Convolutional neural networks (CNNs) are a type of artificial intelligence that shows promise as a diagnostic aid for skin cancer. However, the majority are trained using retrospective image data sets with varying image capture standardization. The aim of our study was to use CNN models with the same architecture-trained on image sets acquired with either the same image capture device and technique (standardized) or with varied devices and capture techniques (nonstandardized)-and test variability in performance when classifying skin cancer images in different populations. In all, 3 CNNs with the same architecture were trained. CNN nonstandardized (CNN-NS) was trained on 25,331 images taken from the International Skin Imaging Collaboration (ISIC) using different image capture devices. CNN standardized (CNN-S) was trained on 177,475 MoleMap images taken with the same capture device, and CNN standardized number 2 (CNN-S2) was trained on a subset of 25,331 standardized MoleMap images (matched for number and classes of training images to CNN-NS). These 3 models were then tested on 3 external test sets: 569 Danish images, the publicly available ISIC 2020 data set consisting of 33,126 images, and The University of Queensland (UQ) data set of 422 images. Primary outcome measures were sensitivity, specificity, and area under the receiver operating characteristic curve (AUROC). Teledermatology assessments available for the Danish data set were used to determine model performance compared to teledermatologists. When tested on the 569 Danish images, CNN-S achieved an AUROC of 0.861 (95% CI 0.830-0.889) and CNN-S2 achieved an AUROC of 0.831 (95% CI 0.798-0.861; standardized models), with both outperforming CNN-NS (nonstandardized model; P=.001 and P=.009, respectively), which achieved an AUROC of 0.759 (95% CI 0.722-0.794). When tested on 2 additional data sets (ISIC 2020 and UQ), CNN-S (P<.001 and P<.001, respectively) and CNN-S2 (P=.08 and P=.35, respectively) still outperformed CNN-NS. When the CNNs were matched to the mean sensitivity and specificity of the teledermatologists on the Danish data set, the models' resultant sensitivities and specificities were surpassed by the teledermatologists. However, when compared to CNN-S, the differences were not statistically significant (sensitivity: P=.10; specificity: P=.053). Performance across all CNN models as well as teledermatologists was influenced by image quality. CNNs trained on standardized images had improved performance and, therefore, greater generalizability in skin cancer classification when applied to unseen data sets. This finding is an important consideration for future algorithm development, regulation, and approval.

Evaluation of factors contributing to variability of qualitative and quantitative proficiency testing for SARS-CoV-2 nucleic acid detection

The pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to unprecedented social and economic disruption. Many nucleic acid testing (NAT) laboratories in China have been established to control the epidemic better. This proficiency testing (PT) aims to evaluate the participants’ performance in qualitative and quantitative SARS-CoV-2 NAT and to explore the factors that contribute to differences in detection capabilities. Two different concentrations of RNA samples (A, B) were used for quantitative PT. Pseudovirus samples D, E (different concentrations) and negative sample (F) were used for qualitative PT. 50 data sets were reported for qualitative PT, of which 74.00% were entirely correct for all samples. Forty-two laboratories participated in the quantitative PT. 37 submitted all gene results, of which only 56.76% were satisfactory. For qualitative detection, it is suggested that laboratories should strengthen personnel training, select qualified detection kits, and reduce cross-contamination to improve detection accuracy. For quantitative detection, the results of the reverse transcription digital PCR (RT-dPCR) method were more comparable and reliable than those of reverse transcription quantitative PCR (RT-qPCR). The copy number concentration of ORF1ab and N in samples A and B scattered in 85, 223, 50, and 106 folds, respectively. The differences in the quantitative result of RT-qPCR was mainly caused by the non-standard use of reference materials and the lack of personnel operating skills. Comparing the satisfaction of participants participating in both quantitative and qualitative proficiency testing, 95.65% of the laboratories with satisfactory quantitative results also judged the qualitative results correctly, while 85.71% of the laboratories with unsatisfactory quantitative results were also unsatisfied with their qualitative judgments. Therefore, the quantitative ability is the basis of qualitative judgment. Overall, participants from hospitals reported more satisfactory results than those from enterprises and universities. Therefore, surveillance, daily qualitiy control and standardized operating procedures should be strengthened to improve the capability of SARS-CoV-2 NAT.

The impact of preventive measures on controlling Covid-19 pandemic: a statistical analysis study.

BackgroundThe purpose of this paper is to investigate the primary variables associated with the COVID-19 disease and to demonstrate how to evaluate the effect of the earlier consideration of the containment measure and the massive testing policy on controlling the spread of this pandemic. We introduced and analyzed, for the first time to our knowledge, a new variable referred to as the Gap, which was defined as the time between the appearance of the first case and the implementation of the containment measure.MethodsA correlation, linear, and nonlinear regression-based statistical analysis was conducted to determine the impact of numerous variables and factors on the spread of this pandemic.Results81.3% of the variability of total cases was explained by the variability of total tests, and 72.3% of the variability of total deaths was explained by the variability of total cases. In addition, we have constructed significant nonlinear models that explain 97.8% of the total cases’ information and 89.4% of the total deaths’ information as a function of the Gap variable. Furthermore, we have found no correlation between the total number of tests and the fatality rate.ConclusionConsideration of earlier containment is an effective measure that enables the prevention of a catastrophic disease spread scenario. In addition, the massive testing policy has no effect on the fatality rate. However, the performance of tests is highly effective at detecting new cases earlier, before they infect a large number of individuals, and is also an effective method for controlling the spread of this disease. Keywords: COVID-19 disease, preventive measures, containment measure, massive policy of tests, linear and nonlinear models. Copyright: © 2022 The Authors. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/.).

A direct contact bioassay using immobilized microalgal balls to evaluate the toxicity of contaminated field soils

The present study used a bioassay of immobilized microalgae (Chlorella vulgaris) via direct contact to assess the toxicity of eleven uncontaminated (reference) and five field contaminated soils with various physicochemical properties and contamination. Photosynthetic oxygen concentration in the headspace of the test kit by Chlorella vulgaris in the reference soils ranged between 12.93% and 14.80% and only 2.54%–7.14% in the contaminated soils, respectively. Inherent test variability (CVi) values ranged between 2.90% and 9.04%; variation due to soil natural properties (CVrs) ranged between 0.33% and 13.0%; and minimal detectable difference (MDD) values ranged from 4.69% to 11.6%. A computed toxicity threshold of 15% was established for microalgae soil toxicity tests based on calculations of the maximal tolerable inhibition (MTI). All contaminated soils were considered toxic to microalgae because their levels of inhibition ranged between 39.5% and 82.9%, exceeding the 15% toxicity threshold. It can be concluded that the elevated concentrations of heavy metals and organic contaminants in the contaminated soils induced the higher inhibitory levels. Overall, direct contact soil toxicity tests using immobilized microalgae provided coherent and repeatable data and can be utilized as a simple and suitable tool for the toxicity testing of contaminated field soils.

Effect of sample geometry and air voids on the 3-Point Bend Cylinder (3PBC) fatigue test for asphalt concrete

As part of NCHRP IDEA IDEA Project 218, a new testing protocol called Three-Point Bend Cylinder (3PBC) test was developed to speed up the fatigue characterization of asphalt mixtures. In this paper, the effects of sample geometry and air voids on the 3PBC fatigue test were investigated. The results showed that the VECD theory was successfully applied to all the selected geometries. This allowed the determination of fatigue life at any desired strain levels, temperatures, and frequencies. Based on the selected levels for each factor, specimen diameter significantly affected the 3PBC test results and fatigue lives. Specimen span length and air void content, however, did not appear to have considerable effects on the fatigue lives of the asphalt material. It should be noted that the sample variability of the 3PBC test may have softened the effects of air voids on the fatigue lives of the asphalt material.

International Delphi Recommendations for Pediatric Lower Limb Neurological Test Protocols for Muscle Strength, Reflexes, and Tactile Sensitivity.

To gain consensus from physical therapists on pediatric lower limb neurological tests of muscle strength, tactile sensitivity, and reflexes. A Delphi technique was used for 2 sequential questionnaire rounds to gain consensus from a panel of pediatric physical therapists (n = 28). Physical therapists rated their agreement to items from statements on pediatric lower limb neurological tests, their protocols, and interpretation using a 6-point Likert scale. Ninety percent of items gained consensus: 80% on pediatric lower limb neurological tests, 88% on test protocols, and 92% on test interpretation. Fifty-one percent of items had high agreement and high importance. There is variability in pediatric neurological tests used, their protocols, and interpretation. Identification of items with high agreement and importance is the first step to develop a standardized lower limb neurological assessment for pediatric clients of varying ages and diagnoses.

Correction: Fractional Excretion of Sodium (FENa): An Imperfect Tool for a Flawed Question.

<b>Introduction:</b> Monitoring of respiratory function is important in the diagnosis and management of respiratory disease. The forced oscillation technique requires minimal patient cooperation and is ideal for the determination of respiratory function in young children. This study aimed to develop reference ranges and to document the repeatability in healthy young children using commercially available forced oscillation equipment <b>Methods:</b> The forced oscillation technique, utilizing a pseudo-random noise forcing signal between 4 and 48 Hz (I2M, ChessMedical, Ghent, Belgium), was used to measure respiratory function in healthy young children. Repeatability over a 15 minute period was also assessed. Regression equations and standardized Z scores were determined for respiratory resistance (Rrs) and reactance (Xrs) at 6, 8 and 10 Hz. <b>Results:</b> Respiratory function was obtained in 158 healthy children, aged 2 to 7 years and between 92 and 127 cm in height. Oscillatory respiratory mechanics exhibited linear relationships with height. Within test variability for resistance ranged between 6-9% and between 17-20% for reactance. Resistance and reactance did not change significantly over a 15 minute period. <b>Conclusions:</b> Reference ranges for respiratory impedance variables in healthy children between 2 and 7 years of age are presented. The short-term repeatability of forced oscillatory variables in this age group are reported allowing appropriate cut-off values for therapeutic interventions to be defined.

A modified mouse model for observational fear learning and the influence of social hierarchy.

BackgroundIndirectly experiencing traumatic events either by witnessing or learning of a loved one’s suffering is associated with the highest prevalence rates of epidemiological features of PTSD. Social species can develop fear by observing conspecifics in distress. Observational fear learning (OFL) is one of the most widely used paradigms for studying fear contagion in mice. However, the impact of empathic fear behavior and social hierarchy on fear transfer in mice is not well understood.MethodsFear emotions are best characterized in mice by using complementary tests, rather than only freezing behavior, and simultaneously avoiding behavioral variability in different tests across time. In this study, we modified the OFL model by implementing freezing (FZ), open field (OF), and social interaction (SI) tests in a newly designed experimental facility and applied Z-normalization to assess emotionality changes across different behaviors.ResultsThe integrated emotionality scores revealed a robustly increased emotionality of observer mice and, more importantly, contributed to distinguishing susceptible individuals. Interestingly, fos-positive neurons were mainly found in the interoceptive network, and mice of a lower social rank showed more empathy-like behaviors.ConclusionOur findings highlight that combining this experimental model with the Z-scoring method yields robust emotionality measures of individual mice, thus making it easier to screen and differentiate between empathic fear-susceptible mice and resilient mice, and refining the translational applicability of these models.

Undiagnosed Diabetes in U.S. Adults: Prevalence and Trends.

Confirmatory testing is recommended for diabetes diagnosis in clinical practice. However, national estimates of undiagnosed diabetes are based on single elevated test measures, potentially resulting in overestimation. Our objective was to update trends in undiagnosed diabetes using definitions consistent with clinical practice. We included 30,492 adults (aged ≥20 years) from the National Health and Nutrition Examination Survey (1988-2020). Among adults without diagnosed diabetes, confirmed undiagnosed diabetes was defined as having both elevated levels of fasting plasma glucose (FPG) (≥126 mg/dL) and elevated glycated hemoglobin (HbA1c; ≥6.5%), and persistent undiagnosed diabetes was defined as having elevated HbA1c or FPG levels, adjusted for the within-person variability in HbA1c and FPG tests. From the periods 1988-1994 to 2017 to March 2020, there was an increase in the prevalence of diagnosed diabetes (from 4.6% to 11.7%), but no change in prevalence of persistent undiagnosed diabetes (from 2.23% to 2.53%) or confirmed undiagnosed diabetes (from 1.10% to 1.23%). Consequently, the proportion of all undiagnosed diabetes cases declined from 32.8% to 17.8% (persistent undiagnosed diabetes) and from 19.3% to 9.5% (confirmed undiagnosed diabetes). Undiagnosed diabetes was more prevalent in older and obese adults, racial/ethnic minorities, and those without health care access. Among persons with diabetes, Asian Americans and those without health care access had the highest proportion of undiagnosed cases, with rates ranging from 23% to 61%. From 1988 to March 2020, the proportion of undiagnosed diabetes cases declined substantially, suggesting major improvements in diabetes screening and detection. Undiagnosed diabetes currently affects 1-2% of US adults; up to 90% of all cases are diagnosed.