The significance level was p < 0.05. The results showed that before calibration, the 95% CI of the OLP regression intercept and slope between the GXT-derived MAS and S2000 and S3000 did not include 0 and 1.00, respectively. These values, after calibration, included 0 and 1.00, respectively. Post hoc analysis revealed that S3000 closely approximated the GXT-derived MAS and underestimated 0.46% (0.06 km h−1 and p > 0.05), and S2000 overestimated 5.49% (0.81 km h−1 and p < 0.05) by the MAS. It concluded that the 3,000 m TT performance approximated the GXT-derived MAS compared to the 2,000 m TT performance. There exist fixed bias and proportional bias between the GXT-derived MAS and TT performance. More attention should be applied to calibration when using the TT performance to estimate the MAS.Considered to be a lesser resource burden, 2,000 and 3,000 m time trials (TTs) have been recognized as alternatives to accurately estimate the maximal aerobic speed (MAS) derived from laboratory-graded exercise testing (GXT). Previous studies have commonly used ordinary least squares linear regression and the Bland–Altman method to compare the agreement between MAS and TT performance. The agreement analysis aimed to identify the systematic bias between the results of the two methods, rather than to identify similarities. The model II regression technique (ordinary least product regression) is increasingly favored by researchers in the field of physiology. Thus, we aimed to 1) use the ordinary least product (OLP) and bootstrap methods to determine the agreement between the average speed of 2,000 m TT (S2000) and the average speed of 3,000 m TT (S3000) and 2) determine whether S2000 or S3000 can accurately approximate the GXT-derived MAS. It is used as an alternative to estimate the MAS and prescribe training intensity. Thirty-five Beijing Sport University recreational male runners completed an MAS test in laboratory settings, followed by 2,000 and 3,000 m TTs randomly, with a 7-day interval. OLP regression was used to analyze the agreement between the GXT-derived MAS and S2000 and S3000. The bootstrap method was used to calibrate the equations. Differences between the GXT-derived MAS and S2000 and S3000 were compared using a one-way repeated measure analysis of variance (ANOVA) and a  Severalproaches , elucidaproaches , better proaches , and preproaches . CoachesWith 100% MAS as the baseline, there exist MAS zones applied for aerobic training in running. Different training adaptations produced by MAS zones should be considered by recreational runners and coaches to achieve their goals. Continuous training sessions at a lower percentage of the MAS  can improve the running economy, and interval training sessions at a higher percentage of the MAS improve the running gait and MAS  . In addiThe laboratory GXT using a gas analyzer system is considered the most accurate method to identify the MAS directly, where an exhaustive exercise protocol of 10–14 min should be completed by the runners under a monitored treadmill . Howevert-test, correlation analysis, ordinary least squares linear regression, and Bland–Altman method, could not completely reflect the agreement between the two groups of data  to compare the average speed of 2,000 and 3,000 m TTs in agreement with the GXT-derived MAS and establish the calibration equations. We assume that the 3,000 m TT may be completed at a speed closer to the GXT-derived MAS and validate it with one-way repeated ANOVA. We believe that the findings of the study will help coaches implement valid field tests for estimating the MAS.Thirty-five recreational collegiate male runners free from injuries and experienced in middle running voluntarily agreed to participate in this study   conducted in a random order, with a 7-day interval between the testing sessions. All testing sessions were performed under similar weather conditions (temperature 20–23°C and humidity 50%–60%). The participants performed the GXT in the laboratory, whereas 2,000 and 3,000 m TTs were conducted on an official 400 m track under similar environmental conditions . A standardized 15 min warm-up was performed before the tests, including multiple dynamic stretch movements, including a knee-to-chest walk, walking quad stretch, hamstring hand walk-inchworm, and 6 min jog with an initial speed of 6 km/h2 max were determined using this protocol. The automatic gas analyzer system software was used to measure the VO2 max and provide analysis results for every second time frame . The highest average of VO2 for the last 30 s in any of the last steps was accepted as VO2 max. The major criterion for VO2 max determination was the existence of a “plateau,” an increment equal to or lower than 2.0 ml kg−1 min−1 in the last step or steps  respiratory exchange ratio (RER) > 1.1  > 1.1 .2 exhalation volume, and respiratory exchange rate. The VO2 was recorded automatically using the software of the metabolic cart, and the highest value was determined to be VO2 max if the previous inclusion criteria were achieved. The MAS was measured using the formula adapted by Kuipers: MAS (km.h−1) = Sf+ (t/120*i)  .f indicates the speed of the completed stage (km.h−1) after eliciting VO2 max, t represents the time spent running(s) of the uncompleted stage, and i denotes the increment of every stage (1 km h−1 increment to 14 and 0.5 km h−1 increment until exhaustion in the current study).Here, SThe heart rate data were monitored using Polar H10 and Polar M430  and synchronized using the gas analyzer system software. The rating of perceived exertion (RPE) was recorded immediately when participants were unable to maintain the required pace.2,000 and 3,000 m TTs: all participants did their best to complete a 2,000 and 3,000 m TT alone on a 400 m outdoor running track and recorded the RPE value immediately after testing. Time was recorded with a manual stopwatch. Heart rate data were monitored using Polar H10 and Polar M430 . The average speed of TTs was recorded as S2000 and S3000, which were compared by the GXT-derived MAS. There was no pace strategy requirement for participants.Data were analyzed using the R software (version 4.2.1). Ordinary least product regression (OLP) was used to compare the agreement between the MAS and S2000 and S3000, respectively. If the 95% CI for the OLP slope does not include 1.0, there was a fixed bias. If the 95% CI for the OLP intercept does not include 0, there was proportional bias . OLP regp < 0.05. If p < 0.05, a post hoc analysis (Bonferroni) was used to measure the difference between the GXT-derived MAS and S2000 and S3000, respectively.The normal distribution for gathered data was examined through the Shapiro–Wilk test. Differences between the MAS and S2000 and S3000 were compared using a one-way repeated-measure ANOVA, and the significance level was The slope of the OLP regression for MAS on S2000 was 0.65 (95% CI: 0.51–0.77), on S3000 was 0.65 (95% CI: 0.54–0.75), and the corresponding intercept was 4.59 (95% CI: 2.62–6.68) and 5.18 (95% CI: 3.57–6.84), respectively . AlthougUsing the MAS as the dependent variable and S2000 and S3000 as independent variables, the calibration equation for the OLP regression is MAS = 0.65 * S2000 + 4.59, MAS = 0.65 * S3000 + 5.18. The means and 95% CI of slopes and intercepts of the bootstrap sample calibration equations  are shown in The slope of the OLP regression of the calibrated MAS (95% CI) is 1.00 (0.91–1.10) and 1.00 (0.92–1.09), respectively and the intercept (95% CI) is 0 (−2.52 to 2.29) and 0 (−2.98 to 2.73), respectively.p < 0.05).The one-way repeated-measures ANOVA is determined to be statistically significant  show there was a significant difference between the MAS and S2000 (p < 0.05), and no significant difference was observed between the MAS and S3000 (p > 0.05), as shown in The results of 2 plateau). The VO2 plateau appears in the GXT protocol, meaning that all participants reached VO2 max. This is due to two fundamental reasons: first, the participants have a good training experience, allowing them to tolerate a high-load stimulation. Second, the GXT protocol is relatively reasonable, with each participant being able to reach exhaustion. The GXT lasting 620 s caters to the completion time, which falls within the duration ranging between 600 and 840 s recommended by the previous study. Shorter GXT protocols lasting 600–840 s permit the participants to reach their maximal potential not limited by accumulative fatigue of muscles and the cardiovascular system  must be used . Bland eThe OLP regression results revealed a proportional bias between the GXT-derived MAS and TT performance before calibration. The TT performance tended to underestimate the GXT-derived MAS for lower MAS and overestimates it for large MAS. The presence of proportional bias indicated that lower GXT-derived MAS is underestimated by TT performance and higher GXT-derived MAS is overestimated. In addition, there was a fixed bias between the GXT-derived MAS and TT performance before calibration, and the size of the fixed bias was affected by the proportional bias . The aboThe bootstrap sampling method  was used to validate the calibration equations. Both the calibrated GXT-derived MAS and TT performance were free of fixed and proportional bias, indicating that the calibrated equations improved the agreement between the GXT and TT, suggesting the need to calibrate the equations for using TT performance to estimate the GXT-derived MAS.Post hoc tests for one-way repeated-measures ANOVAs showed the 3,000 m TT performance closely approximated the GXT-derived MAS and underestimated 0.46% , and the 2,000 m TT performance overestimated 5.49%  by the GXT-derived MAS. Consequently, the 2,000 m TT enables the runners to elicit an average pace that exceeds the MAS , requiring more anaerobic contribution than that of the 3,000 m TT distance . A review suggested that these parameters led to a 10% variance in the MAS (The study had a few limitations: 1) Due to a limited sample, no further screening was performed for participants. Further studies could be conducted by expanding the sample to validate the calibration equations. 2) No specialized equipment was used to measure the wind speed, although TTs were conducted on an official 400 m outdoor track with no rain and light winds. 3) The variations in the MAS and physiological parameters depend on the subtle parameter of laboratory GXT protocols (incremental speeds and duration, 0.5–2 km h the MAS . Thus, t the MAS .This study indicated that the 3,000 m TT performance approximates the GXT-derived MAS compared to the 2,000 m TT performance. There are fixed bias and proportional bias between the GXT-derived MAS and TT performance, meaning poor agreement between the GXT-derived MAS and TT performance. More attention should be paid to calibration when using TT performance to estimate the GXT-derived MAS.


The purpose of this study is to analyze the histopathological features of resected testicular remnant specimens, ascertain the incidence of the presence of either germ cells (GCs) or seminiferous tubules (SNTs), and assess whether surgical excision of the remnant is necessary. A total of 332 boys with vanishing testis underwent surgical removal of unilateral testicular remnants, with age 7–164 months (median age 25 months). Among the total 332 cases, 212 (63.8%) were younger than 36 months and 143 (66.5%) were found to have hypertrophied contralateral testes larger than 1.6 cm in longitudinal diameter under sonography. SNTs were only present in 21 (6.3%) cases and GCs were present in 7 (2.1%) cases. Compared to the review studies, the very low incidence of SNTs and GCs in which implies extremely low chances of potential malignancy. We propose that surgical removal of vanishing testis remnants in an inguinal or scrotal position may not be necessary. Cryptorchidism or undescended testis (UDT) is reported in 1–4.6% of full-term and 1.1–45.3% of premature male infants . In someA retrospective review was performed for pediatric patients identified as unilateral testicular remnant consistent with vanishing testis after surgical excision between July 2008 and November 2018. Data were collected from surgical management details from both clinical notes and operative records. Pre-operative inguinal or scrotal ultrasound data in detecting non-ppalpable and contralateral testis were collected, including the location of the identified remnant in the affected side and the size of the contralateral testis. Histological findings including fibrosis, calcification, hemosiderin deposition , remnantIn our institution, all patients with clinical NPT undergo physical examination under anesthetic, and patients whose testes are still non-palpable proceed to a laparoscopy. During the laparoscopy, if no intra-abdominal testis is found and the spermatic cord enters into a closed internal ring, the inguinal or scrotal region is explored. A small fibrotic nodule or nubbin with no macroscopically normal testicular tissue identified is found at the end of the spermatic cord, and any testicular remnant is excised then. If a macroscopically abnormal intra-abdominal testicular remnant is revealed at laparoscopy, it is excised subsequently. Other patients with palpable nubbin in the inguinal or scrotal region undergo a direct inguinal or scrotal exploration instead of laparoscopy.Histologic confirmation of testicular or paratesticular tissue required the presence of at least one of the following: SNTs, GCs, Sertoli cells, Leydig cells (testicular tissue) and vas deferens, or epididymal structures (paratesticular tissue). Identification of specimens with SNTs and viable GCs was confirmed by an expert pathologist. Hematoxylin and eosins (H&E), monoclonal mouse antibody Oct3/4 , monoclonal mouse antibody Sal-like protein 4   stains were used to document the presence of GCs, while H&E, monoclonal mouse anti-androgen receptor (AR)  and polyclonal goat anti-anti-müllerian hormone (AMH)  stains were used to identify the presence of SNTs, which consist of Sertoli cells and Leydig cells.P < 0.05 was regarded as statistically significant.Results were presented as median (range) or absolute numbers (percentages), as appropriate. SPSS for Windows v20  was used for analysis. Data analysis included Fisher's exact test, and a P < 0.05). 41 (12.5%) nubbins were palpated in the inguinal or scrotal region. Within the 212 (63.8%) cases of patients younger than 36 months, 143 (66.5%) had hypertrophied contralateral testes and the sizes were larger than 1.6 cm in longitudinal diameter measured by sonography. 291 (87.5%) of the 332 patients underwent laparoscopic exploration; whereas the remaining 41 (12.5%) patients underwent direct inguinal or scrotal exploration initially.A total of 332 cases of testicular remnants are summarized. Median (range) age at surgery was 25 (7–164) months. Among these cases, the remnants of 258 (77.7%) cases were left sided ((P > 0.05). A summary of the four subgroups and a overall analysis is presented (Routine histologic studies showed fibrosis in 275 (82.8%), dystrophic calcification in 99 (29.8%), hemosiderin deposition in 39 (11.7%), vas deferens in 187 (56.3%) and epididymis in 111 (33.4%) cases. SNTs were present in 21 (6.3%) cases. GCs were available only in 7 (2.1%) cases with ages ranging from 10 to 126 months, including one intra-abdominal case . Compariresented . AccordiAll 7 GCs patients were positive for Sall4, while only 2 cases were positive for Oct3/4 . No recoVanishing testis, which was coined by Abeyaratne et al. , refers Enlargement of the contralateral descended testis is considered to be the most helpful clinical sign of vanishing testis , 18. ThiThere is controversy regarding the optimal management of vanishing testis patients. Some authors recommend surgical exploration, via either laparoscopic or inguinal or scrotal approach, whereas other authors believe that these procedures are unnecessary , 9. Lapap = 0.03, SNTs 6.3 vs. 10.7%, p = 0.04). However, there was a large range of GCs (0–15.4%) and SNTs (0–34%) incidence in the previous cohorts studies, in which significant heterogeneity was observed. It is obvious that our data are also in the range, but it seems as if the credibility of our analysis results was higher.Currently, the optimal management of the testicular remnant of vanishing testis is still under debate. Some advocate routine surgical exploration to remove the remnant, whereas others question its necessity –11, 24. To the best of our knowledge, it is well-known that there is increased future malignancy risk with congenital UDT with a standardized incidence ratio of 2.23 for younger children (<13 years old at operation) and 5.4 for adolescents (>13 years old at operation) . ClinicaOur study included several limitations, such as a reliable comparison group of children who did not have remnants excised and their long-term follow-up, and further analysis of costs and risks of performing potentially unnecessary resection . Further study to address these inadequacies would be valuable. Other limitations of our study were the small number of patients, especially older patients, and the inclusion of only pediatric patients ≤18 years old. The vanishing testis hypothetical future malignancy risk is lifelong, although there are no published findings which prove that vanishing testis is linked to malignancy during adulthood. A multi-center study with lifelong follow-up should be carried out to justify the surgical management.In this study, we propose that surgical removal of vanishing testis remnants in an inguinal or scrotal position may not be necessary owing to the very low incidence of SNTs and GCs in resected testicular remnant specimens. However, excision of intra-abdominal vanishing testis remnants is still necessary because intra-abdominal remnants may contain more elements and are difficult to monitor.The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.The studies involving human participants were reviewed and approved by the Ethics Board of the above Hospital. Written informed consent to participate in this study was provided by the participants' legal guardian/next of kin.LG: guarantor of integrity of the entire study, study concepts, study design, definition of intellectual content, literature research, clinical studies, experimental studies, data acquisition, data analysis, statistical analysis, manuscript preparation, and manuscript editing. DT: guarantor of integrity of the entire study, study concepts, study design, definition of intellectual content, literature research, clinical studies, data analysis, manuscript preparation, manuscript editing, and manuscript review. WG: clinical studies, experimental studies, and data acquisition. All authors contributed to the article and approved the submitted version.This work was supported by funding from Major State Basic Research Development Program of China (Grant Number 2018YFC1002700).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


In response to those results, we formulate an optimization problem and solve it through the particle swam method plus fmincon function in MATLAB to identify a new optimal weighting parameter set for each grade that produces more accurate predicted MEE and we compare our new findings with seven other MEE models in the literature. The current study matched the measured MEE the best with the lowest RMSE values for level (0.45 J·kg ⁻1·m ⁻1) and downhill (0.82 J·kg ⁻1·m ⁻1) walking and the third lowest RMSE value for uphill (1.56 J·kg ⁻1·m ⁻1) walking, where another MEE model, Looney et al., had the lowest RMSE for uphill (1.27 J·kg ⁻1·m ⁻1) walking. Bland-Altman plots and three independent-samples t-tests show that there was no statistical significant difference between experimentally measured MEE and estimated MEE during the three walking conditions, meaning that the three new optimal weighting parameter sets can be used with 6 degree of freedom (DOF) lower extremity motion data to better estimate whole body MEE in those scenarios. We believe that this work is a step towards identifying a single robust parameter set that allows for accurate estimation of MEE during any task, with the potential to mitigate a limitation of indirect calorimetry requiring lengthy steady state motion.A previously developed joint-space metabolic energy expenditure (MEE) model includes subject-specific parameters and was validated using level walking gait data. In this work, we determine how well this joint-space model performs during various walking grades  at 0.8 m·s ⁻ The ability to estimate metabolic energy expenditure (MEE) is desirable for many reasons. This measurement could inform physical laborers on when to stop a particular task, especially for those in the military. Gaining insight on how much energy a task requires could also pinpoint how much sustenance would be needed for the individual to achieve those goals. The ability to compare MEE between tasks would also be helpful. For example, a variety of lifting techniques could be evaluated to see which lifting task requires the least amount of energy, therefore, potentially identifying the most ergonomic and cost-effective approach to the lifting task.Experimental measurement of MEE can be done via indirect calorimetry which estimates MEE based on oxygen uptake. However, a shortcoming of indirect calorimetry measurement is that it is limited to steady state tasks such as walking or cycling . As an aEmpirical predictive equation formulations are typically simplistic, where whole body metabolic energy consumption is estimated by using few input variables. Some depend only on grade , while oMuscle MEE models define MEE by utilizing the first law of thermodynamics, where MEE is a summation of mechanical work and heat liberation. Many muscle-based MEE models exist , 12 and Joint-space-based MEE models are derived from muscle MEE models but are framed in the joint-space instead of the muscle-space , 18. UsiA previous study compared seven MEE models (6 muscle-space-based and 1 joint-space-based) and found that muscle-based MEE models performed better than the joint-based model . The joifmincon function in MATLAB. Finally, we compare our new results to the results found by using empirical predictive equation, muscle-spaced-based, and joint-space-based MEE models.The foundation of this work is built on the previously validated MEE model developed by Roberts et al. . In thisPublished gait data of 12 healthy subjects are used in this study and subject information is listed in 1 and 1.3 m·s⁻ 1) and grade  conditions. The order of trials was randomized. Pulmonary gas exchange rates were measured during all walking trials and was used to calculate measured metabolic rate (W·kg⁻ 1). Koelewijn et al. [1·m⁻ 1) for each trial is calculated through dividing the metabolic rate (W·kg⁻ 1) by the walking speed (m·s⁻ 1).As described in previous work , the parn et al. , 22 usedτi(t) is the joint torque and ith DOF. n is the total number of DOF in the human model. Next, M, A, H, and This study uses a metabolic energy consumption model which calculates MEE based on joint moments and joint angular velocities . The inton in Eq :W˙int(ns in Eq :U˙t(t)s et al.  as shownEEx represents the measured experimental energy expenditure and EM represents the energy expenditure estimated from the model, and N represents the number of data points.As described by Roberts et al. , the weied in Eq :f=. Although maximum VO2 can be estimated using age and resting heart rate [Emax, which we chose to be 110–115% of the measured MEE. The final constraint is defined in Eq  to identify three new parameter sets for level, uphill, and downhill walking, respectively. A swarm size of 100 was used and no upper or lower bounds were enforced. The particle swarm optimization would terminate when the relative change in the best objective function value was less than the default function tolerance (10−6). The results from the particle swarm optimization were used as the initial parameter values for the fmincon optimization. Default settings were used for fmincon optimization where function tolerance was 10−6 and the results from the fmincon optimization were used as the new parameter sets for the validation group to assess fit for the three walking conditions.Three optimizations were carried out via the MATLAB functions p > 0.05. Homogeneity of variance, as assessed by Levene’s test, is present in mass (p = 0.744) and age (p = 0.791) but could not be assumed for height (p = 0.031), therefore a Welch t-test is used for height [An independent-samples t-test is performed using SPSS to determine if there are any statistical differences in mass, height, and age between the training and validation groups. No outliers are identified via boxplots and both groups are normally distributed as assessed by Shapiro-Wilk’s test, r height .p > 0.05. Homogeneity of variance, as assessed by Levene’s test, is present in the three walking conditions, p > 0.05.A RMSE calculation, Bland-Altman plots, and independent-samples t-tests are used to assess how well the MEE results from the validation group matched the experimental measurements for level, uphill, and downhill walking. When comparing the measured MEE to the estimated MEE for the three walking conditions using the t-test, there were no outliers identified via boxplots and all groups were normally distributed as assessed by Shapiro-Wilk’s test, In addition to calculating the RMSE for the current model, seven other MEE models are included for comparison. These included two muscle-based models , 14, thrThe muscle-based models and Kim and Roberts  were pret(10) = -0.245; p = 0.811), height (t(7.449) = 1.142; p = 0.289), or age (t(10) = -0.417; p = 0.685) between the verification and validation groups.The results from the independent-samples t-test show that there is no significant statistical differences in mass . The weighting parameters, the design variables within the optimization, were not restricted to any upper or lower bounds. The After the parameter sets are identified for each walking case, they are used to evaluate the validation group’s energy expenditure using the joint-based MEE model. These joint-space model results are compared to the MEE estimations from other MEE models and measured MEE as shown in 1·m ⁻1. Our study had the highest average calculation (4.68 ± 0.60 J·kg ⁻1·m ⁻1) and Roberts has the lowest average calculation (2.58 ± 0.18 J·kg ⁻1·m ⁻1). Kim (2.80 ± 0.19 J·kg ⁻1·m ⁻1), like Roberts, largely underestimated the MEE measurement. The muscle-based models, Bhargava (3.00 ± 0.31 J·kg ⁻1·m ⁻1) and Umberger (3.36 ± 0.48 J·kg ⁻1·m ⁻1), also underestimate MEE and do not fall within the range of the measured MEE. The three empirical models, Pandolf (3.09 ± 0.02 J·kg ⁻1·m ⁻1), Ludlow (3.16 ± 0.35 J·kg ⁻1·m ⁻1), and Looney (3.72 ± 0.44 J·kg ⁻1·m ⁻1), underestimate measured MEE. This study has the closest agreement and falls within the range of the measured MEE with a RMSE of 0.45 J·kg ⁻1·m ⁻1.For level walking, the average measured walking MEE is 4.60 ± 0.49 J·kg ⁻1·m ⁻1. Our study has the highest estimation (7.91 ± 0.86 J·kg ⁻1·m ⁻1) and Roberts has the lowest estimation (2.89 ± 0.44 J·kg ⁻1·m ⁻1). Kim (3.59 ± 0.25 J·kg ⁻1·m ⁻1), Bhargava (4.08 ± 0.47 J·kg ⁻1·m ⁻1), Umberger (4.08 ± 0.53 J·kg ⁻1·m ⁻1), Ludlow (5.43 ± 0.22 J·kg ⁻1·m ⁻1), and Pandolf (5.89 ± 0.02 J·kg ⁻1·m ⁻1) each underestimate the measured MEE. Looney (6.12 ± 0.44 J·kg ⁻1·m ⁻1) also underestimates the measured MEE, although part of its range overlaps with the measured with a RMSE of 1.27 J·kg ⁻1·m ⁻1. Our study overestimates MEE but our range overlaps with the measured MEE with a RMSE of 1.56 J·kg ⁻1·m ⁻1.During uphill walking, the average measured walking MEE is 7.02 ± 0.99 J·kg ⁻1·m ⁻1. Our study (3.46 ± 0.89 J·kg ⁻1·m ⁻1) has the highest estimation of MEE and Bhargava (2.05 ± 0.25 J·kg ⁻1·m ⁻1) has the lowest estimation of MEE. Kim (2.57 ± 0.27 J·kg ⁻1·m ⁻1), Pandolf (2.29 ± 0.11 J·kg ⁻1·m ⁻1), Ludlow (2.61 ± 0.34 J·kg ⁻1·m ⁻1), and Bhargava all greatly underestimate MEE. Umberger (2.83 ± 0.48 J·kg ⁻1·m ⁻1), Roberts (2.96 ± 0.43 J·kg ⁻1·m ⁻1), and Looney (2.76 ± 0.34 J·kg ⁻1·m ⁻1) also underestimate MEE, but their ranges overlap with the range of the measured MEE. Our study underestimated MEE, but our range encompasses the measured MEE with a RMSE of 1.05 J·kg ⁻1·m ⁻1.The average measured metabolic cost during downhill walking is 3.68 ± 0.62 J·kg ⁻1·m ⁻1 and all data points fall within the 95% limits of agreement. The plot for uphill walking shows a bias of -0.89 J·kg ⁻1·m ⁻1 and all but one data point fall within the 95% limits of agreement. Finally, the downhill walking plot shows a bias of 0.21 J·kg ⁻1·m ⁻1 and all data points fall within the 95% limits of agreement.The Bland-Altmann plots in t(14) = -0.292, p = 0.774), uphill (t(14) = -1.919, p = 0.076), or downhill walking (t(14) = 0.556, p = 0.587).Our independent-samples t-test results showed that there were no statistical differences between the measured and estimated MEE values for level (It is important to ensure that respiratory exchange ratio (RER) values remain in bounds of 0.7 to 1.0 when calculating metabolic rate. Koelewijn et al.  stated tThe results from the optimal weighting parameter set provided interesting results. It was anticipated that the level walking parameter set would closely align with the original parameter set because Roberts et al.  validate1·m ⁻1. All empirical predictive equations underestimated the measured MEE values and followed a consistent trend of increasing MEE estimation when adjusting from downhill to level to uphill, which is consistent with the measured MEE trend. Out of the three empirical models, Looney had the best overall performance for all three walking conditions with a RMSE values of 1.10 J·kg ⁻1·m ⁻1 for all conditions. Further, Looney had the most accurate estimation for uphill walking out of all models tested in this study. This trend aligns with what was seen in Looney’s original paper where their predictive equation had the least bias in accuracy and precision of MEE estimation when compared to Pandolf’s equation [The empirical predictive equations, Looney, Ludlow and Pandolf had RMSE values which ranged from 0.95 to 1.86 J·kg ⁻The muscle-based models, Bhargava and Umberger, consistently underestimated MEE, but Umberger had better overall performance during level and downhill walking. The current study utilized a 6 DOF model that contained information for eight major muscles bilaterally within the lower extremity but did not include musculature for the trunk or arms which may explain the underestimated MEE calculation when using the muscle-based models. An advantage of using the muscle-based MEE models is that it allows the user to break down MEE by muscle and by joint, but it appears that it may not be capable of estimating whole body MEE without muscle information throughout the body.Surprisingly, the joint-based models, Kim and Roberts, had good agreement during downhill walking despite both being validated for level walking. They had the largest RMSE for the uphill and level walking conditions across all models tested in this work. Some reasons for this misalignment could be that only 6 DOFs were observed which was reflected in the underestimations of MEE, although Kim was originally validated with only lower extremity walking data. In addition, when we calculated MEE using Roberts’ original weighting parameter set, we used the same estimated maximum knee torque according to sex as we did for the current work. This lack of subject-specificity might explain why Roberts’ model did not perform as well as it could have. In addition, the inclusion of subject-specific parameters was meant to give Roberts’ an edge on its predecessor, but Kim’s model was more accurate during level and uphill walking.1·m ⁻1 for all conditions. The model overestimated MEE during level walking, but its range aligned well with the measured MEE values as shown by its RMSE of 0.45 J·kg ⁻1·m ⁻1. The Bland-Altman plot for level walking , capturing full body motion. While the results from our optimization is promising, it is reasonable to assume that a different parameter set could be identified when using 42 DOF data that would result in more accurate estimations of MEE. Regardless, our results align closely with the values from whole-body measurements via calorimetry. Therefore, it is reasonable to say that the parameter sets we have identified are sufficient to predict whole-body MEE while walking under the conditions described in this study if only 6 DOFs (in the lower extremities) are available. In addition, in this work we chose to estimate maximum MEE for each participant trial in response to not having access to resting heart rate from the published data, meaning that we could not estimate maximum n et al.  in theirn et al. . The datIn this work, we were able to identify three new optimal weighting parameter sets which can be used with 6 DOF lower extremity motion data to better estimate whole body MEE in different walking conditions. In our comparison, a variety of models perform differently under different walking conditions. The new optimal parameter sets that we found produced the lowest RMSE for level and downhill walking and the third to lowest RMSE for uphill walking. Further, there was no statistical difference between the measured MEE and the estimated MEE using the new parameter sets for the three walking conditions. The process of identifying these parameter sets via optimization leads us to believe that other parameter sets can be found for other tasks with varying availability of DOFs motion data. We believe that this work is a step towards identifying a single robust parameter set that allows for accurate estimation of MEE during any task, with the potential to mitigate a limitation of indirect calorimetry requiring lengthy steady state motion. Future work should include continued testing of Roberts’ model with a larger full-body (42 DOF) dataset as well as an expansion of tasks such as running, lifting, climbing, and jumping. In addition, the incorporation of extreme temperature and its influence on MEE could be explored and implemented in the joint-space MEE model.S1 FileDescribes each of the metabolic energy consumption models used within this study.(DOCX)Click here for additional data file.


In this paper, we used a computational model to estimate the clearance of a tracer driven by the circulation of cerebrospinal fluid (CSF) produced in the choroid plexus (CP) located within the lateral ventricles. CSF was assumed to exit the subarachnoid space (SAS) via different outflow routes such as the parasagittal dura, cribriform plate, and/or meningeal lymphatics. We also modelled a reverse case where fluid was produced within the spinal canal and absorbed in the choroid plexus in line with observations on certain iNPH patients. No directional interstitial fluid flow was assumed within the brain parenchyma. Tracers were injected into the foramen magnum. The models demonstrate that convection in the subarachnoid space yields rapid clearance from both the SAS and the brain interstitial fluid and can speed up intracranial clearance from years, as would be the case for purely diffusive transport, to days. Cerebrospinal fluid (CSF) flow plays a fundamental role in the clearance of solutes from intracranial compartments . CurrentImportantly, CSF circulation characteristics change under physiological transitions, in neurological disorders, and with neurodegenerative disease. In patients diagnosed with idiopathic normal pressure hydrocephalus (iNPH), magnetic resonance imaging (MRI) reveals altered solute influx and clearance rates . In bothA key question is to what extent the CSF circulation induced by CSF production, vascular pulsatility, and CSF efflux contributes to the transport of solutes (both influx and outflux) in the SAS and brain parenchyma. While intraparenchymal transport and glymphatics have received substantial attention over the last decade , the cleμm/s can be inferred from experimental measurements of microsphere movement in rodents   .in vivo observations of brain-wide distribution of tracers combined with fast clearance from the SAS, and we thus propose that a combination of different outflow routes seems more likely.In this study, using biophysics-based finite element computational models created from T1-and T2-weighted MR images , we studIn this computational study, we quantify and characterize CSF flow patterns and molecular transport in the SAS and parenchyma induced by different clearance pathways. We also consider a choroid plexus-based production of 0.5 L/day of CSF and efflux across the 1) parasagittal dura , 2) the We consider baseline T1-and T2-weighted MR images (resolution 1 mm) from an iNPH patient collected in a previous clinical study. This patient then underwent a  intrathecal injection of the gadolininium-based tracer gadobutrol, and follow-up MR images were taken at several time points post injection. LookLocker images were also obtained with the T1-weighted MR images. The clinical study was approved by the Regional Committee for Medical and Health Research Ethics (REK) of Health Region South-East, Norway (2015/96), the Institutional Review Board of Oslo University Hospital (2015/1868), and the National Medicines Agency (15/04932-7), and conducted in accordance with the ethical standards of the Declaration of Helsinki of 1975 (and as revised in 1983). All study participants were included after written and oral informed consent.The baseline MR images were post-processed using FreeSurfer v6.0  to obtaiP and surrounding CSF-spaces ΩF combined  by ∂ΩCP. The outer boundary of the SAS is split into three parts: ∂ΩS, ∂ΩFM, and ∂Ωout, representing the arachnoid membrane, foramen magnum, and a chosen efflux route, respectively. We consider and define three different regions Ωout for efflux of CSF: locally across the parasagittal dura (cribriform plate (lymphatics distributed over the outer (arachnoid) boundary  reported for flow in PVS .We model the flow of CSF in Ω10–3 Pas  is the Cw in PVS , we findng sleep , while hng sleep . We set ∂Ωout to be further specified. At these, we set a traction condition:R0 ≥ 0 represents an efflux resistance acting to moderate CSF outflow in these regions, and n denotes the outward-pointing boundary normal. The fluid source, in combination with the zero or low resistance efflux routes, induces a flow of CSF from the CP through the ventricular system, through the SAS, and out across either the parasagittal dura, cribriform plate, or meningeal lymphatics.We set the CSF velocity at the outer boundary (representing the arachnoid membrane) to be zero, except at specific efflux/absorption sites g is set negative with a value corresponding to a sink of 0.5 L/day, a zero traction condition is imposed at the foramen magnum ∂ΩFM, and zero velocity (no slip) is imposed on the remainder of the boundary.We also consider a reversed flow scenario, in which c in the entire domain Ω via the diffusion-convection equation.u is a convective velocity field, D denotes an apparent diffusion coefficient, and α is a dispersion factor. We set the apparent diffusion coefficients DF = 3.8 ⋅ 10–4 mm2/s in ΩF and 2/s in ΩP  or let u be given by solutions of the CSF flow Eq. 1 in combination with all α.We also model molecular transport within the CSF-spaces and parenchyma resulting from an influx of gadobutrol at the foramen magnum . We model transport of a concentration  in ΩP . Here, λspersion , we haverenchyma , and we To represent an influx of gadobutrol at the foramen magnum, we setF(t) is modeled as a linearly decreasing function until T0 ≈ 2.24 h  and zero thereafter, i.e.,Based on tracer enhancement as reported by F(t) (given in mmol/(s mm2) is chosen such that the total amount of gadobutrol injected is approximately 0.5 mmol. At the efflux sites ∂Ωout, we let the solute be absorbed via the relation.β is a given membrane permeability. The case β = 0 corresponds to no absorption, β = ∞ corresponds to free movement of solutes across the boundary, while 0 < β < ∞ represents a diffusive resistance to molecular outflow. On the remainder of the boundary, we do not allow for solute efflux, by setting D∇c ⋅ n − cu ⋅ n = 0. Moreover, we let the initial concentration be c  = 0. Note that to model transport associated with the reversed flow scenario, we let ∂ΩCP take the role of ∂Ωout.The solute influx F and ΩP we conserve mass (enforce conservation of molecules) by setting ϕDP∇cP ⋅ n = DF∇cF ⋅ n. Here, DP and DF denote D restricted to ΩP and ΩF; respectively, n is the normal vector on the interface, pointing from ΩP to ΩF and ϕ denotes the extracellular space (ECS) porosity.At the interface between Ωin-vivo observations of Gadobutrol transport. Model I and II describe flow induced by CSF production in the CP and CSF efflux across the parasagittal dura and cribriform plate, respectively. For these models, we assume free molecular efflux at the absorption sites. Model III is a variant of Model I with a finite molecular efflux permeability at the parasagittal dura absorption site. Model IV reflects a different efflux pathway with CSF production in the CP, CSF efflux in the meningeal lymphatics, and a finite molecular efflux permeability. Model V represents a reversed flow scenario with absorption of CSF in the CP region (and CSF influx at the foramen magnum). Model VI represents a variant of Model II with increased CSF production. CSF production has been reported to vary between subjects and different central nervous system disorders  elements for the velocity and pressure. The diffusion-convection equation with boundary conditions is solved numerically using the finite element method with continuous linear finite elements for the concentration in space and the backward Euler method in time; all using the FEniCS finite element software . The braA time resolution study was performed to ensure that our simulation results were independent of the choice of time step . As meshr1 is known as the T1 relaxivity of the agent, and T1(c) and T1 (0) denote the T1 time with and without concentration, respectively. The T1 times can be computed using a T1 mapping  at time t was computed as M(t) is then the sum M(t) = MP(t) + MF(t). The average concentrations per region over time were computed asVi refers to the volume of the respective region. To compare parenchymal influx between models, we compute the peak average concentration in the parenchyma and the time to reach this peak. We also compute the relative clearance of tracers after T1 = 3 days as 1—The total amount of solute in a given region ΩAll models induce non-trivial CSF flow through the ventricular system and subarachnoid space.μm/s. Models I (and III) reach peak CSF velocities of 40 μm/s. In model IV, CSF flow occurs mainly in the lower regions of the SAS, as CSF can exit the SAS along the entire boundary. Peak velocities in the SAS for model IV reach 20 μm/s. In models where CSF was allowed to exit through outflow routes other than the parasagittal dura (models II and IV), CSF velocity magnitudes were relatively small (<4 μm/s) in the SAS near the upper convexities of the brain.Models I–IV all reach maximal SAS velocities of 8.9 mm/s in the thinnest part of the aqueduct . Despiteμm/s, while the velocity in the aqueduct remains at 8.9 mm/s. In the upper regions of the SAS, not directly associated with the 3rd ventricle, CSF velocities were typically lower than 0.1 μm/s.Model V predicts that, under its assumptions, CSF will predominantly flow from the foramen magnum directly to the CP, limiting CSF flow in other parts of the SAS . Therefoμm/s in the CSF space (Doubling the CSF production (model VI versus model II) results in a doubling of the CSF velocity field by linearity. Therefore, we observe velocities of approx. 100 SF space  and a veWhen driven purely by diffusion (without convection or dispersion enhancements), the tracer spreads radially from the foramen magnum and distributes evenly throughout the brain. The distribution is slightly faster in the CSF than in the parenchyma, as the free diffusion coefficient in the CSF is larger. However, this effect is not very noticeable. For Models I–III the relative 1 year clearance is only 32.8%, 17.6 %, and 29.9%. Model IV displays faster clearance, clearing 92.5% over 1 week but with a late peak parenchyma concentration occurring after 79 h.Including the CSF circulation-induced flow as a convective velocity substantially speeds up the clearance rates, both from the SAS and parenchyma.α = 10 in Tracer distribution is shown for all models after 6 and 24 h and Model V is the only model where tracer reaches the ventricular system, while Model IV has a localized accumulation of tracers around the brain stem. Model VI, with increased CSF production, shows a generally lower concentration of tracers and some accumulation near the outflux route at the cribriform plate.α = 10, is compared in in vivo concentration estimates in both spaces. We observe that a combination of the different outflow routes, i.e., Models I and V, gives a comparable result to that of the MR images. Models I and III both display higher concentrations than the data in both the CSF and parenchyma/ISF . The lowest 3 day clearance is obtained with α = 1,000 for model III (36.3% clearance) and α = 10 for model IV  results in low parenchymal enrichment compared to Models I–IV . The 3 drenchyma . The timα = 1,000.Model VI, with double the sCSF production of the other models, displayed rapid clearance from the CSF . The rapIn this paper we have simulated molecular transport by diffusion and convection for six different models investigating the distribution of gadobutrol molecules entering the intracranial compartment via the foramen magnum. The different models represent different outflow routes, and CSF flow patterns vary considerably between models. The effects of outflow route and dispersion factor modify the distribution and clearance patterns in a non-linear and unpredictable manner. Outflow through either the parasagittal dura, the cribriform plate, or through meningeal lymphatics, typically clears 80%–99% of injected tracers over a time period of 3 days. These three models, however, display very different spatial distributions of tracers. In Models I and III tracer are distributed more or less throughout the frontal cortex, while when outflow occurs through meningeal lymphatics, tracers are mainly located at the brain stem at the base of the brain.With a daily production of 0.5 and 1.0 L/day in our models, the velocity reaches 10 and 17.8 mm/s in the aqueduct. Pulsatile aqueductal flow velocities of several cm/s have been measured experimentally  in the rμm/s in models I-IV, and up to 100 μm/s in model VI. These velocities align relatively well with experimentally observed bulk flow velocities of around 20 μm/s observed in mice  replicates experimentally observed ISF concentration without additional dispersion in the SAS, but clearance from the SAS is delayed in this model compared to experimental data. With a molecular resistance to outflow on the parasagittal dura (Model III), simulations reproduce accumulation of tracers in this region, but clearance kinetics are slower than expected. With a doubling of CSF production (Model VI), the kinetics of ISF and CSF clearance is faster than expected for all dispersion factors tested. In the model with reversed flow in the aqueduct (Model V), we qualitatively reproduce the tracer enhancement in the aqueduct as seen in iNPH patients  to days. As none of the models tested were able to reproduce the observed data perfectly , a combination of the different outflow routes seems most plausible, and their relative weight may differ between groups .


Within the study population, we found high levels of altruistic behaviors and positive attitudes toward organ donation. However, the level of behavioral intentions toward organ donation was low. No associations were found between altruism levels and attitudes toward organ donation, or between altruism levels and the degree of behavioral intentions toward organ donation. However, a positive relationship was found between attitudes toward organ donation and willingness to sign an organ donor card. In addition, positive associations were found between religiosity and altruism, while negative associations were found between religiosity and attitudes towards organ donation, and between religiosity and willingness to sign an organ donor card. Positive attitudes toward organ donation may result in increased organ donation in the future. Thus, raising awareness and positive attitudes toward organ donation among the wider public and, in particular, the ultra-Orthodox population in Israel in particular is necessary. Consequently, it is essential that information about the organ donation process is accessible and culturally adaptive to different sectors.The number of people on the waiting list for an organ transplant increases year after year. However, the number of donated organs available for transplantation does not rise in line with this increased demand. This study examines the associations between altruism, attitudes towards organ donation, and behavioral intentions regarding organ donation within the Jewish population in Israel. In a cross-sectional study, 452 participants completed an online questionnaire. Data collection occurred between November and December 2020. Convenience sampling was used, and participation was voluntary. Data were analyzed using Pearson correlations and independent samples  Organ transplantation is one of the clearest examples of how technological advancement has enabled the realization of ancient medical ideas. The possibility of transplanting an organ from a healthy person into the body of a sick person has captured the medical imagination for many centuries. However, it was only in the second half of the twentieth century that this vision became a reality, with the first kidney transplants in the 1950s followed by pancreas, liver, and heart transplants in the 1960s. Since then, technological development has enabled more organs and tissues to be transplanted, and organ transplants have become a viable solution for a growing number of medical conditions [The Gift Relationship [Since the outset of the development of transplant medicine, ethical rules have been established for the supply of human organs for transplantation. Above all, such organs must be obtained through altruistic donation, i.e., given freely without any material consideration. The source of the altruistic rule in organ donation can be found in the revolution that inspired Richard Titmuss’s book tionship . TitmussThis view is the dominant paradigm when it comes to collecting human cells, tissues, and organs for therapeutic purposes. Although Titmuss’s book is outdated in many ways, the paradigm he proposed still prevails as the ethical boundary when it comes to organ transplantation. For Titmuss, an individual’s altruistic behavior is the driving force behind the mechanism of organ donation. Altruistic individuals create a norm of volunteering and donating that, in turn, increases social solidarity. The state should create “opportunities for altruism” for individuals, such as, for example, the opportunity to donate blood or organs for transplantation. The aggregated altruistic behavior of individuals crystalizes into a social norm, contributes to social solidarity, and, in a virtuous circle, leads to an increase in altruistic behaviors. This position forms the basis for policies for collecting organs for transplantation and underpins advocacy systems for encouraging organ donation around the world. The assumption is that altruism constitutes an extant force in society and can be mobilized as a solid base for organ collection policies.Generally, deceased organ procurement schemes follow “opt-in” or “opt-out” models. In opt-in or informed consent models, organs are procured from deceased people who carried organ donor cards or any other form of personal statement of their will to donate their organs after death. These models are the current policy in Israel and in the US, as well as in other countries. In an opt-out system, organs are procured under the presumption that an individual consents to become an organ donor after death, unless that person has explicitly opted out of the system. Such a model is more widespread in Europe, with the UK, France, and Switzerland joining Spain, Germany, Austria, and other nations in their opt-out donation policies. There is an indication in most research that opt-out models yield more donations . In IsraThe impact of religion on organ donation is positive ,6. HowevThis paper examines the assumption that altruism is associated with organ donation in Israel and helps to shed light on the complexity of this concept. The paper also highlights the need for a broad cultural and social context if the complex interplay between social structures and organ donation is to be understood.Altruism is defined as behavior aimed at helping others ; it may Various scales for measuring altruism are described in the literature. For example, the “dictator game” examined altruistic charitable donation through a survey or experiment ,15,16. SThe most common scale for measuring altruistic behavior is Rushton’s Self-Report Altruism (SRA) scale. Rushton et al.  developeMany studies use altruism as a predictor of organ donation. Khalaila  used RusIn a meta-analysis that included 27 studies (most of them based on semi-structured interviews and focus groups), altruistic motivation to help others emerged as the most-identified motivator for becoming an organ donor. Altruistic motivation to help another person, while knowing that the organs help another person improve their quality of life and longevity, was a driving force behind the consent to donate organs. Other factors included a sense of solidarity with society and a belief that organ donation is used for beneficial purposes with patients [Given the deficiency in the number of organs and, therefore, long waiting times for transplantation (eight years on average in Israel and five years the US), policymakers face the challenge of raising organ donations . BecauseDrawing upon the literature on the association between altruism and organ donation, this study examined this relationship in Israeli society, and specifically considered whether altruism levels are linked to organ donation in Israel. We hypothesized that positive associations would be found between altruism, attitudes toward organ donation, and willingness to sign an organ donation card.Ethical approval for the current study was obtained from the Ethics Comity, Ashkelon Academic College (#26-2020).The cross-sectional study involved 452 participants from the adult population in Israel who were sampled by way of a convenience sample. The questionnaire was programmed using Qualtrics survey software, and on 14 November 2020 a link to fill out the questionnaire was distributed on social networks (WhatsApp and Facebook groups). A week later, a reminder was sent to the groups, and on 1 December 2020, the survey was closed. According to the survey data, the response time for the questionnaire was, on average, around 4.5 min. The survey contained 564 entries; 463 participants filled out the questionnaire and 11 participants were removed because they failed to fill out the answers for the dependent variable. Therefore, the response rate to the survey was 80% of the total entries. At the beginning of the questionnaire, the purpose of the study was explained. Filling out the questionnaire constituted informed consent to participate in the study and no questions were defined as mandatory. The survey was administered without prior information about donation.An online, closed, anonymous, self-report questionnaire was used. For validation purposes, the questionnaire was provided to ten employees at the Ashkelon Academic College between the ages of 25–50 from various departments, different sexes, and different ethnic origins. Four questions were corrected based on written comments made by participants. The questionnaire included 31 closed questions.Demographics: Sex, age, marital status, parental status, level of religiosity, country of birth.p = 0.79, p < 0.001). The short questionnaire was further examined by experts from the Chief Scientific Bureau of the Ministry of Education; based on their comments, the wording of the questionnaire was finalized. The reliability of the translated questionnaire was α = 0.83. Participants were asked to indicate their level of agreement with each statement on a Likert scale ranging from 1 (never) to 5 (often). The statements described everyday acts of altruism, such as “I donated money to charity.” The variables were constructed using a mean calculation for each participant, with a higher score indicating a higher level of altruistic behavior. The internal consistency of the study was α = 0.75. Altruistic behavior: The questionnaire included ten questions from Watad  that wermitzvah (commandment).” The variables were constructed using a mean calculation for each participant after reversing the scales in questions 1, 4, 5, 7, 8, and 10. A higher score indicated more positive attitudes toward organ donation. The internal consistency of the study was α = 0.94. Attitudes towards organ donation: The questionnaire included 13 questions taken from Utitz . The attBehavioral intentions regarding organ donation: Two questions were taken from Utitz . The quep values were based on two-sided tests and were considered significant when the values were below 0.05.The data were imported from the survey software and analyzed in SPSS v. 26 . A probing analysis found a normal distribution of the variable, and, therefore, parametric tests were used. The relationships between the variables were examined using Pearson correlations. The relationships between the level of religiosity and the study variables were analyzed using Spearman correlations. Differences between categories  were tested using independent samples t-tests. A linear regression model was used to test the prediction of willingness to donate. The independent variables were altruism and religiosity. All reported In total, 452 individuals participated in the study, of whom 72.1% were women, 60% were married, and 48.2% had children. Most of the participants were Israeli born (90%). About a quarter of the participants defined themselves as secular, 23.7% as traditional, 42.9% as religious, and 8.6% as ultra-Orthodox. Sample characteristics are shown in n = 111, 26%) had already signed an organ donor card. The remaining respondents (n = 341) responded to the statement, “I am considering signing an organ donor card,” as follows: 50% chose a low level of agreement (responses 1 and 2), 21% chose a medium level (response 3), and 29% chose a high level (responses 4 and 5). The mean for the variable “willingness to donate/sign an organ donor card” was 3.21 (SD = 1.52).In response to the statement, “I would like to donate organs after my death”, 30% of participants selected a low level of agreement (responses 1 and 2), 21% selected a medium level of agreement (response 3), and 49% chose a very high level of agreement (responses 4 and 5). A quarter of the sample (p > 0.05). Thus, the hypotheses in that regard were not confirmed. A positive, significant association was found between attitudes toward organ donation and the degree of willingness to donate/sign an organ donor card . That is, the more positive the attitudes toward organ donation, the higher the willingness to donate/sign an organ donor card. Thus, the hypothesis in that regard was confirmed.No relationship was found between altruism and attitudes toward organ donation, or between altruism and the level of willingness to donate/sign an organ donor card, as the results were not significant , between age and the attitude toward organ donation , and between age and the level of willingness to donate/sign an organ donor card . The older the respondents, the more altruistic they were, the more positive their attitudes were toward organ donation, and the higher their willingness to donate/sign an organ donor card.Positive, significant, weak-to-moderate associations were found between age and altruism . Further, negative and significant moderate-to-high associations were found between level of religiosity and (a) attitude toward organ donation  and (b) level of willingness to donate/sign an organ donor card . That is, as the religiosity level increased, the respondents were more altruistic, their attitudes toward organ donation were more negative, and their willingness to donate/sign an organ donor card was lower.A positive, significant, weak-to-moderate association was found between level of religiosity and altruism . No associations were found in the other categories of religiosity.A positive, significant, moderate association was found among the secular group participants between altruism and willingness to donate/sign an organ donor card (rp < 0.001), whereas the level of altruism did not make a significant contribution to the model . The model was significant (F(451) = 27.08, p < 0.001, Adj R2 = 0.10).In a linear regression that tested the prediction of willingness to donate, a significant predictive ability of the level of religiosity was found  = 17.57, p < 0.001). Those who had signed an organ donor card had more positive attitudes toward organ donation than those who had not signed an organ donor card (mean of 4.51 compared to 3.29). In terms of levels of altruism, no differences were found between respondents who had signed an organ donor card and respondents who had not signed an organ donor card. Statistically significant differences were found between respondents who had signed an organ donor card and respondents who had not signed an organ donor card (t(450) = 4.76, p = 0.001). Respondents who had children expressed higher levels of altruism compared with those who did not have children (mean of 3.43 vs. 3.12). Further, there were significant differences between respondents with children and respondents without children in terms of attitudes toward organ donation (t(450) = 2.06, p = 0.05). Respondents with children had more positive attitudes toward organ donation than those without children (mean of 3.70 vs. 3.49). In terms of willingness to donate organs/sign an organ donor card, no differences were found between respondents with children and respondents without children. In terms of altruism levels, statistically significant differences were found between respondents with children and respondents without children (t(446) = 4.71, p < 0.001). Respondents who were married or living with a spouse expressed higher levels of altruism, compared with others  (mean of 3.40 vs. 3.09). In terms of attitudes toward organ donation, no significant differences were found between married respondents, respondents living with a spouse, and other types of relationship status  (t(446) = 0.18, p = 0.856, mean of 3.60 vs. 3.58, respectively). In terms of willingness to donate organs/sign an organ donor card, no significant differences were found between married respondents, respondents living with a spouse, and other types of relationship status  (t(446) = 0.75, p = 0.453, mean of 3.17 vs. 3.28, respectively).In terms of altruism levels, significant differences were found between different types of relationship status (t(450) = 1.25, p = 0.211, mean of 3.34 vs. 3.25, respectively), attitudes toward organ donation (t(450) = 0.46, p = 0.645, mean of 3.63 vs. 3.58, respectively), and willingness to donate organs/sign an organ donor card (t(450) = 0.27, p = 0.784, mean of 3.24 vs. 3.20, respectively).No significant differences were found between males and females in terms of altruism levels (tmitzvah (“commandment”), only 55% were in favor of signing an organ donor card. Among respondents who believed that organ donation is a moral obligation, the study found an even lower percentage, 41%, with only 26% showing a real commitment to organ donation through signing an organ donor card. This large gap between explicit attitudes and actual commitment to donate organs may be due to religious beliefs. These findings reinforce the findings of previous studies, where similar gaps were found between intent and real actions [This study sought to investigate the levels of willingness in the general population in Israel to sign an organ donor card, the relationship between attitudes toward organ donation and altruism, and the relationship between attitudes toward organ donation and willingness to sign an organ donor card. The level of altruism among participants in the study was high ; the attitudes toward organ donation were positive ; and willingness to donate organs was high . A quarter of respondents had already signed an organ donor card. However, the distribution of responses to the statements revealed a complex picture: while the majority of respondents (68%) perceived organ donation as important, as having exemplary moral value, and as a human  actions . Even wi actions . There are numerous fears that prevent people from signing an organ donor card, including fear of bodily “mutilation” after death and anxiety issues concerning death. Indeed, only 58% of respondents agreed with the statement on the questionnaire, “The thought that I will be cut open after my death does not deter me”. Death and post-mortem organ donation are closely linked, as registering as an organ donor card holder requires an individual to recognize that he or she is “mortal.” Thus, our findings are consistent with studies that found that anxieties around death can intensify and be triggered when people are considering decisions regarding organ donation ,34.In the entire sample, no association was found between altruism and attitudes regarding organ donation, or between altruism and willingness to donate organs in practice. These findings are not consistent with previous studies ,37,38,39Examining the relationship between the variables according to religiosity levels, we found that there is no association between altruism and willingness to donate organs in the groups of traditional, religious, and ultra-Orthodox participants; however, we found a positive association between the variables among the secular participants. This finding underscores the importance of perceptions of Jewish law at their extreme level. Secular Jews generally do not delve into ways of determining death under Jewish law and, therefore, have no ideological-religious problem with organ donation.A positive, strong association was found between attitudes toward organ donation and willingness to donate organs in practice, a finding that was similar to findings in previous studies ,43,44,45Another point that emerged from this study was that the older the respondents, the more altruistic they were, the more positive their attitudes were toward organ donation, and the greater their willingness was to donate/sign organ donor cards. It may be that as a person grows older, and his or her convictions become stronger, he or she understands how precious life is and becomes more exposed to cases of illness. Among younger age groups, the issue of organ transplants may seem like a topic that is not relevant to them, and they may not have given sufficient thought to its importance, as Krupic et al.  and FebrIt also emerged from this study that respondents with children were characterized by a higher level of altruism and more positive attitudes toward the topic of organ transplantation. Again, this group may comprise older individuals whose views on life in general, and specifically on the issue of organ transplants, differ from those of younger people who are not at a stage of life where they have children.When it comes to the level of religiosity and its association with the study variables, a contradiction emerged: as the level of religiosity rose, so did the level of altruism, However, at the same time, willingness to donate organs decreased. Previous findings regarding the relationship between the level of religiosity and willingness to donate organs were not unequivocal. Past findings in other countries indicated that religiosity negatively impacts donation decisions, e.g., such findings were made in Spain , Sweden halakhic (Jewish law) aspects of organ donation after death. In ultra-Orthodox Judaism, there is a debate regarding the validity of the definition of brain death. The conservative point of view holds that the pulse is the ultimate measurement, even though the brain has stopped functioning. A second approach argues that brain death can be recognized as a condition for determining death, because the person cannot breathe independently. A third attitude accepts brain death as a determinant of death. Many groups within the ultra-Orthodox Israeli Jewish population do not sign organ donor cards or donate organs because of their rabbis’ opposition to the definition of brain death. However, in 1982 the Rabbinate of Israel adopted the third approach, that brain death is a determinant of death. Therefore, according to Jewish law, organ donation is permitted [The reasons for this are varied and lie mainly in the ermitted .In this context, it is worth noting that despite their reluctance to donate organs after death, the ultra-Orthodox are the largest group in terms of living organ donations. This group leads in the donations of organs from living people to total strangers. This behavior, which is certainly altruistic, is carried out by a group that in this study was found to be distant from engaging in organ donations.The willingness to donate organs can be equated with attitudes toward euthanasia, because both issues are moral and related to end-of-life decisions, and both issues are controversial in the context of Judaism. Dopelt et al.  examinedThe trend among the ultra-Orthodox communities in Israel in donating organs to strangers indicates the need for future studies to differentiate between motivations for post-mortem donations and living organ donations. While signing an organ donor card indicates a contribution to the community, living organ donation usually occurs within families to help a sick relative. These are two types of altruistic acts that require different definitions and different operationalizations.This paper has several important limitations. The study sample was limited and did not represent the entirety of the Israeli population . We focused on the Jewish population based on the assumption that religious beliefs and cultural differences might affect attitudes and viewpoints. In addition, the sample comprised mostly women (72%), and the ultra-Orthodox Jewish religious populations were over-represented relative to the general population. Further, there may have been biases in the study, such as a selection bias in response to the questionnaire, with the result that those who chose to respond may have had a special interest in the issue of organ donation. An additional bias was social desirability—some participants may have provided answers to questions on the attitudes and barriers questionnaire that they thought were expected of them and selected more positive or altruistic behaviors. An additional problem was the tools that were used for measuring altruism. The questionnaire examined altruistic behaviors that almost all people carry out by virtue of being social beings, but altruism should be examined as a personality trait and not as a behavior.halakhic (Jewish law)-religious issue and a lack of public awareness and positive incentives for organ donation. The positive association between attitudes and willingness to donate organs shows that positive attitudes toward organ donation may ultimately be translated into donations in the future. For this reason, increasing positive attitudes within the population is an important aspect of organ donation, because the formation of a positive approach is a critical step in making decisions regarding this complex topic, particularly if the aim is to reduce the number of people who oppose organ donation in Israel.In Israel, the current supply of human organs for transplantation is far less than the demand. Broadly, the reason for this is twofold: the Jewish-It is important to note the difference between willingness to donate organs to a stranger after death and willingness to donate organs to a stranger while alive. This difference is especially significant in relation to the study’s findings among the ultra-Orthodox populations in Israel. The data indicated a high level of altruism and a low level of willingness to donate organs within this population; however, these data should be interpreted with caution, because the low levels of willingness to donate organs relate to post-mortem organ donation, whereas there is a high level of willingness within this population for living organ donation to strangers, which is the most altruistic act of organ donation.


There are variabilities in the distance between the tibial tuberosity and the trochlear groove. The knee angle needs to be considered when talking about patellofemoral instability.  This retrospective study analyses the MRI images of knee angles from 0 and 30 degrees in the patella dislocation group (20 cases) and in the control group (20 cases) from Dec 2017 to Dec 2019. Two experienced orthopedic physicians separately measure the study with a blind experiment method. P < 0.01). The TT-TG data of the patella dislocation group and control group are 11.51 ± 3.60 mm and 7.40 ± 1.93 mm when the knee angle is at 30 degrees, indicating a statistically significant difference (P < 0.01). Also, the TT-TG data of both the patella dislocation group and control group have statistically significant differences within different knee angles of the same group (P < 0.01). The differences of TT-TG are 6.36 ± 2.43 mm and 5.92 ± 1.65 mm when the knee angle changes from 0 to 30, which shows no statistically significant difference (P > 0.01).  The TT-TG data of the patella dislocation group and control group are 17.88 ± 3.40 mm and 13.31 ± 3.01 mm when the knee angle is 0, which indicates a difference with statistical significance ( This research initially obtained the relevant MRI data of the TT-TG distance from different knee angles between the Chinese patella dislocation patient group and control group. The study received a new criterion to evaluate the TT-TG of patients with patella dislocations when the knee angle is below 30 degrees. The knee flexion angles need to be considered to measure the TT-TG distance when comprehensively evaluating patellofemoral instability. The TT-TG distance gradually increases when the knee changes from flexion to extension. The difference of the TT-TG distances shows no statistically significant difference. Goutallier et al. was the first one to propose that the tibial tuberosity to the trochlear groove (TT-TG) distance is an important indication of the patella instability . PatellaQ-angle; however, recent studies have shown that the measurement of the Q-angle is influenced by the patient's position and the observer's recognition of anatomical landmarks, which can lead to measurement errors. Therefore, the measurement of the tibial trochanteric groove (TT-TG) distance has largely replaced the traditional method of measurement. The TT-TG distance can be measured by the computerised axial tomography (CT) or magnetic resonance imaging (MRI) to test the degree of laterality of the tibial tuberosity relative to the centre of the talar groove. It has been shown that when the knee is gradually extended from flexion, the tibia rotates outward, resulting in a gradual increase in the TT-TG distance, and therefore, it is believed that the TT-TG distance is variable when the knee is flexed at different angles [The previous clinical assessment was the measurement of the t angles . In clinThere are few cases in homeland and abroad to study the TT-TG data of the patients with patellar dislocation at different knee flexion angles. The aim of this study was to find out the variation of the TT-TG distance in the knee joint at 0° and 30° in the patellar dislocation group and the control group, in order to provide theoretical guidance for clinical practice and medical research.This retrospective study collected the MRI images of 20 patients with patella dislocations in Aerospace General Hospital from Dec 2017 to Dec 2019. These patients include 8 males and 12 females aged 13 to 33 years . The average ages of these patients are 21.1 ± 4.8 years. 7 of these patients have patella dislocations on their left knees, and 13 of these patients have patella dislocations on their right knees. The research randomly selected the MRI images of 20 patients without patella dislocation (meniscus injury). 15 male patients and 5 female patients were included. The age range of these patients varies from 21 to 38, and their average ages are 28.5 ± 5.1 years. 6 of these patients have patella dislocation on their left knees, and 14 of these patients have patella dislocation on their right knees. The studies involving the human participants were reviewed and approved by the ethics committee of Xi'an Aerospace General Hospital, no. 319797/191.Patients have medical history of patella protruding outwards after knee trauma  TT-TG distance ≥20 mm is commonly considered as pathological, which can assist in the evaluation of patella instability –7.s).The t-test is used to test the data of different positions of the same knee joint and also the data of the same position of different knee joints. The difference is P < 0.05, indicating a significant meaning. This study repeats the measurement of reliability coefficients and analyses the data with interobserver reliability.Statistic software GraphPad Prism 6 was used to analyze the data. The measured data of the TT-TG distance is expressed as , the data for the subjects 1 and 2 are 13.47 ± 3.42 mm and 13.17 ± 2.82 mm, respectively, when their knee joint is completely straight, which shows a correlation coefficient of 0.8865. The data changed into 7.60 ± 2.39 mm and 7.20 ± 1.75 mm when the knee joint bends to 30 degrees, where the correlation coefficient is 0.7290 see . The scaP < 0.01. The TT-TG values of the patella dislocation group and the control group are 11.51 ± 3.60 mm and 7.40 ± 1.93 mm, respectively, when the knee joint bends to 30 degrees, which has a statistically significant difference of P < 0.01. Also, the TT-TG values of both the groups have statistically significant differences of P < 0.01 from different angles of the same group . The article mentions that a knee angle of 15 degrees puts the knee in a more comfortable position (lower limb muscles are relaxed) and helps to avoid the occurrence of artefacts due to activity. There is no evidence indicating that the TT-TG value obtained from positions where the knee joints fully straighten or the knee joints bend at different angles can evaluate the patella instability. The TT-TG value measured in current clinical practice is the data obtained when the knee joints fully straighten. The research has provided a reasonable explanation for the high variability of the TT-TG value from the literature.Dietrich et al. has researched the change of the TT-TG values in volunteers without patella dislocation when their knee joint angles are at 0, 15, and 30 degrees . The datP < 0.01. The TT-TG data for the patellar dislocation group and the control group when the knee was fully extended were 11.51 ± 3.60 mm and 7.40 ± 1.93 mm, respectively. When the lower limb is fully extended, the lower limb muscles become tight, and patients with patellar dislocation may not be able to keep their lower limb extended for long and, in turn, the pain can lead to artefacts which were present in this study and resulted in unmeasured data. Therefore, the different knee angles need to be considered to measure the TT-TG values, especially if MRI is required at a knee angle of 15 or 30 degrees, which would reduce the occurrence of MRI and improve the clarity and accuracy of the test, and then new TT-TG distances can be obtained to measure patellar instability. It also allows for new knee indications to be obtained through mild flexion. However, due to the small sample size in this study, more data and further studies are needed. Furthermore, the TT-TG values in both the patellar dislocation group and the control group were statistically significant (P < 0.01) at different angles in the same group. The TT-TG decreased with increasing knee angle and was in line with the results in the foreign literature. This article also investigated the difference in the TT-TG values at 0 and 30 degrees of the knee and concluded that the difference was not statistically significant (P > 0.01), suggesting that there was no difference in the coronal motion during knee flexion and extension between the patellar dislocation group and the control group.This study showed that the TT-TG data for the patellar dislocation group and the control group when the knee was fully extended were 17.88 ± 3.40 mm and 13.31 ± 3.01 mm, respectively, with a statistically significant difference of In Chinese medicine, patellar instability may be caused by the liver and kidney deficiency and blood stagnation and is usually treated with medicines to nourish the liver and kidneys along with medicines to invigorate blood circulation and remove blood stasis . If therBut there are still limitations to our study. The first is that the experimental sample is too small, and the chances are low. Then, there are many new metrics being considered to replace the TT-TG. Shu et al. used a new method to measure the TT-TG distance based on the TDR modelling. Their TDR-TT-TG method requires only one layer of measurement to be completed, and the results show that it has higher interobserver agreement than traditional TT-TG measurements and TT-PCL measurements. Therefore, we should look for more valid diagnostic criteria in terms of clinical significance in our subsequent experiments.In this study, the preliminary data related to the TT-TG values in our patellar dislocation group and the normal healthy group were obtained. This study obtained a new index for evaluating the TT-TG values (11.51 ± 3.60 mm) in patients with patellar dislocation at a knee angle of 30 degrees. The comprehensive evaluation of the patellofemoral instability requires consideration of the knee flexion angle. Because of the small sample size and the differences between the age groups in this study, further research and further discussion with a large sample is needed. As the knee joint changes from flexion to extension, the TT-TG values gradually increases, whereas the difference in the TT-TG values between the patellar dislocation group and the control group was not statistically significant.