Due to a lack of reliable reference intervals (RIs) for Kenya, we set out to determine RIs for 40 common chemistry and immunoassay tests as part of the IFCC global RI project.Apparently healthy adults aged 18–65 years were recruited according to a harmonized protocol and samples analyzed using Beckman-Coulter analyzers. Value assigned serum panels were measured to standardize chemistry results. The need for partitioning reference values by sex and age was based on between-subgroup differences expressed as standard deviation ratio (SDR) or bias in lower or upper limits (LLs and ULs) of the RI. RIs were derived using a parametric method with/without latent abnormal value exclusion (LAVE).Sex-specific RIs were required for uric acid, creatinine, total bilirubin (TBil), total cholesterol (TC), ALT, AST, CK, GGT, transferrin, transferrin saturation (TfSat) and immunoglobulin-M. Age-specific RIs were required for glucose and triglyceride for both sexes, and for urea, magnesium, TC, HDL-cholesterol ratio, ALP, and ferritin for females. LAVE was effective in optimizing RIs for AST, ALT, GGT iron-markers and CRP by reducing influence of latent anemia and metabolic diseases. Thyroid profile RIs were derived after excluding volunteers with anti-thyroid antibodies. Kenyan RIs were comparable to those of other countries participating in the global study with a few exceptions such as higher ULs for TBil and CRP.Kenyan RIs for major analytes were established using harmonized protocol from well-defined reference individuals. Standardized RIs for chemistry analytes can be shared across sub-Saharan African laboratories with similar ethnic and life-style profile. Overall, only 80.9% of reference values (RVs) for clinical chemistry tests from healthy individuals in Tanzania would have been classified as normal as per the US RIs published by Kratz et al  and expressed it as bias ratio (BR) at LL or UL (BRLL or BRUL). For example, the formula for determining BR for sex was:However, SDR represents between-subgroup difference at the center of the RV distribution, which may not reflect the difference (bias) at LL or UL (ΔLL or ΔUL). Therefore, we also evaluated ΔLL or ΔUL as its ratio to SD comprising RI  should be equal to or more than 3 times the “reporting unit (RU)” to allow partitioning of RVs. RU represents a unit of value for reporting test results. If the number of digits below the decimal point in reporting test results is 2, 1, or 0, RU is 0.01, 0.1, or 1, respectively. The flow of logic in deciding the need for partitioning by sex or age is shown in In setting the threshold for the bias ratios, we followed the convention of allowable limits of bias in measurements: t papers ,9. On thth and 97.5th percentiles after sorting the data in ascending order were used as the lower and upper limits  of the RI. For the parametric method, the RVs were transformed into a Gaussian form by the Box-Cox power transformation formula, and then mean±1.96 SD was computed as the central 95% limits (LL−UL) under the transformed scale, which were then reverse transformed to get the LL and UL in the original scale [RIs were determined using both parametric and non-parametric methods before and after applying the latent abnormal values exclusion (LAVE) method ,11. For As a measure for secondary exclusion of abnormal values, we tried to apply LAVE in deriving the RI both by parametric and nonparametric methods . For LAVOn the other hand, for determination of RIs for the thyroid panel, the LAVE procedure was not applied because reference tests associated with the thyroid panel were not available. Rather, we first estimated the cutoff values for anti-thyroglobulin antibody (TgAb), and anti-thyroid peroxidase antibody (TPOAb) from the probability paper plot drawn with x-axis in logarithmic scale, as an intersection of the central linear part with the horizontal line at 97.5 percentile as shown in LL and BRUL by setting LLs and ULs of RIs with/without LAVE: i.e., SDRI in the denominator was set to the RI by the LAVE procedure. The 90% confidence intervals (CIs) of LL and UL were derived by the bootstrap method with resampling of the final set of RVs and repeated computations of LL and UL for 50 iterations. Accordingly, final RIs were determined as the averages of LL and UL thus derived.For judging the need for adopting LAVE, we computed BROut of 596 volunteers, 533 met the inclusion criteria: 260 (48.8%) males and 273 (51.2%) females. The main reason for exclusion was hypertension as shown in The median age was 39 years with a range of 18–65 years. The participant characteristics are summarized in Sex, age and BMI as sources of variation were explored with SDR≥0.4 regarded as being significant as shown in Between-sex differences exceeded that level in Alb, UA, Cre, TBil, Cl, ALT, AST, CK, GGT, Ferr, Tf, TfSat, and IgM. Similarly, between-age subgroup differences were significant for Alb, Cl, Glu, and TG in males, and for Alb, urea, Na, Mg, Glu, TC, TG, HDLrat, LDL-C, ALT, ALP, and Ferr in females. BMI was an independent source of variation for UA, Glu, TC, HDLrat, nonHDL-C, LDL-C, ALT, AST, LDH, and GGT in males, and for CRP only in females. Graphical representations of reference value distribution sub-grouped by sex and age are shown for 12 representative analytes in Generally, the parametric method resulted in similar or lower RI ULs, and narrower 90% CIs for the LL and UL of the RIs compared to the non-parametric method as shown in UL or BRLL > 0.375) for some analytes as shown in The LAVE method resulted in significant differences in LL or UL . We chose to adopt partitioned RIs only when the difference at LL or UL was ≥3RU. We believe this three-way consideration ensured optimal judgement in partitioning RIs by sex and age as shown in In order to decide the need for partitioning RVs into subgroups by sex or age, we primarily used SDR, but it tended to provide an inflated value when the width of the RI was narrow. Another problem of SDR is that it reflects between-subgroup difference at the central part which may not reflect between-subgroup bias at the LL or UL, hence the use of BRRIs can vary appreciably across different populations as demonstrated in the interim report of the global study analyzing RVs of 12 countries . They idOur electrolytes didn’t differ much from other published IFCC studies except that Mg levels increased with age in females. It has been documented that reduced levels of oestrogen are associated with increased Mg levels in post-menopausal women as well as in the follicular phase of the menstrual cycle in women of reproductive age ,17.et al who carried out a similar study in a rural Kenyan population [Our TC and TG RIs were higher than those reported by Kibaya pulation . Our stupulation . Accordipulation . Our UL We obtained fasting plasma glucose (FPG) RIs of 3.9−5.8 and 4.4−7.3 mmol/L for those aged <45 and ≥45 years respectively. The former RI is comparable to what was obtained in Turkey (3.96−5.88 mmol/L) and Saudi Arabia (4.0−5.9 mmol/L) ,13. The et al also found high levels of IgG in several SSA countries [et al in a similar study carried out in Asia found that the closer the country or region was to the equator, the higher the serum concentrations of positive inflammatory markers  a phenomenon they ascribed to increased exposure to infectious agents [Our RIs for immunoglobulins are higher than those derived in the US but very similar to those derived in India ,15. Kariountries . We hypoountries . Ichihars agents . Similars agents .et al has demonstrated that BMI is a major source of variation in RVs for many analytes and that the magnitude of this association varies across different populations [Ichihara ulations . For exaulations . BMI wasFor iron markers, we also applied LAVE to reduce the influence of latent anemia. Although it was very effective in raising their LLs, the female LL for ferritin was still lower than the WHO cutoff value of <15 μg/L for iron deficiency .The strengths of our study include the deliberate recruitment of healthy individuals using a harmonized protocol to ensure pre-analytical confounders were minimized, centralized analysis of samples in an accredited laboratory with excellent internal quality control, standardization of the RIs by use of a value-assigned panel of sera and use of the LAVE procedure to reduce the influence of sub-clinical disease on the derived RIs.The weaknesses include failure to perform infectious serology to rule out chronic infections such as HIV, HBV or HCV, and over representation of an urban population hence limiting the generalizability of our findings to a rural population.According to the harmonized IFCC-C-RIDL protocol, we established RIs for 40 major chemistry and immunoassay tests from well-defined healthy Kenyan volunteers by use of the up-to-date statistical methods for the first time in Africa. The LAVE method was effective in reducing the influence on RIs of latent anemia and metabolic disorders. Based on SD ratio and bias ratios, we developed a flow chart to judge the need for partitioning RVs by sex and age subgroups, which we believe is helpful for the future RI study. RIs for chemistry analytes were standardized by use of a value assigned serum panel, and thus could be shared across sub-Saharan African laboratories with similar ethnic and life-style profile. As a whole, Kenyan RIs were comparable to those of other countries participating in the global study with a few exceptions such as higher ULs for TBil and CRP.S1 FigThe distributions of reference values are shown based on age and sex stratification for all analytes. The SDRsex and SDRage for each sex are shown at the top of each analyte chart. No secondary exclusion was performed in plotting the data. The box in each scattergram represents central 50% range and the vertical bar in the middle represents a median point.(PDF)Click here for additional data file.S2 FigThe RIs of all analytes were derived in four ways by parametric (P) or nonparametric (NP) method with/without the LAVE procedure, separately in males+Females (MF), males, and females. Each horizontal bar represents the range of the RI, and the vertical line in the center corresponds to the mid-point. The shades on both ends of the bar represent 90%CI for the limits of the RI predicted by the bootstrap method.(PDF)Click here for additional data file.S3 FigThe accuracy of Gaussian transformation by Box-Cox formula can be assessed from theoretical Gaussian curves in two histograms shown on left top (before and after the transformation) of each panel. Accuracy can be also seen from the linearity in probability paper plot on the right. The limits of the RI by nonparametric method corresponds to the points where red zigzag line intersect with horizontal 2.5 and 97.5% red lines of cumulative frequencies.(PDF)Click here for additional data file.S4 FigThe panel of sera from 50 healthy volunteers, each of which were value assigned for 40 chemistry analytes were measured. Our measured values were plotted on Y-axis and assigned values on X-axis. Major axis linear regression was used as a structural relationship for the method comparison. The Y = X line is shown as a diagonal broken line.(PDF)Click here for additional data file.S1 Table(PDF)Click here for additional data file.S2 Table(PDF)Click here for additional data file.


This study aimed to develop and validate two predictive models of postpartum post-traumatic stress disorder (PTSD) risk using a retrospective cohort study of women who gave birth between 2018 and 2019 in Spain. The predictive models were developed using a referral cohort of 1752 women (2/3) and were validated on a cohort of 875 women (1/3). The predictive factors in model A were delivery type, skin-to-skin contact, admission of newborn to care unit, presence of a severe tear, type of infant feeding at discharge, postpartum hospital readmission. The area under curve (AUC) of the receiver operating characteristic (ROC) in the referral cohort was 0.70 (95% CI: 0.67–0.74), while in the validation cohort, it was 0.69 (95% CI: 0.63–0.75). The predictive factors in model B were delivery type, admission of newborn to care unit, type of infant feeding at discharge, postpartum hospital readmission, partner support, and the perception of adequate respect from health professionals. The predictive capacity of model B in both the referral cohort and the validation cohort was superior to model A with an AUC-ROC of 0.82 (95% CI: 0.79–0.85) and 0.83 (95% CI: 0.78–0.87), respectively. A predictive model (model B) formed by clinical variables and the perception of partner support and appropriate treatment by health professionals had a good predictive capacity in both the referral and validation cohorts. This model is preferred over the model (model A) that was formed exclusively by clinical variables. Post-traumatic stress disorder (PTSD) has been described as “the complex somatic, cognitive, affective, and behavioral effects of psychological trauma” . PTSD afSeveral factors have been associated with the development of postpartum PTSD . HoweverOne of the biggest challenges in health is creating tools for predicting the risk of particular health problems. The purpose of these tools is the early identification of those most susceptible to developing the problem or anticipating the appearance of the first symptoms. Several published prediction models exist for PTSD after childbirth, using different variables and populations ,25,26,27Therefore, the objective of this study was to develop and validate two postpartum PTSD risk prediction models, one based exclusively on objective clinical predictive factors and another including subjective factors such as perceptions of partner support and treatment received by professionals.An observational study was conducted using a retrospective cohort of women who gave birth between 2018 and 2019. The Research Ethics Committee of the province of Jaen approved this study with reference number TD-VCDEPP-2019/1417-N-19. The main tool employed to collect the relevant data for this study was medical records. The women were required to read an information sheet about the study and its objectives and check a box in which they showed their consent to participate in it; that is, they signed an ad hoc digital informed consent. The STROBE statement has been followed in the reporting of this study. This analytical and observational study used a retrospective cohort of women who gave birth between 2018 and 2019. A total of 1752 women were included in the referral cohort for the predictive models, which were subsequently validated with a cohort of 875 women. The Clinical Research Ethics Committees of Universidad de Jaen gave ethical approval prior to the start of the study. All of the participants received written information on the study, including the fact that participation was completely voluntary and anonymous.We used the maximum modeling principle to estimate the sample size. We needed 10 events (women at risk of PTSD) per each incorporated variable . If we cThe main tool employed to collect the relevant data for this study was medical records. The primary outcome variable—risk of PTSD—and the following objective independent variables were collected from the medical records.Maternal: maternal age, education level, nationality, attendance at maternal education classes, and the use of a birth plan.Obstetric: previous cesarean section (CS), number of deliveries, induction of labor, type of labor, use of regional analgesia, use of general anesthesia, use of natural analgesic methods, episiotomy, and perineal tear.Fetal: prematurity, twin pregnancy, breastfeeding in the first hour, skin-to-skin contact, admission of the newborn to care unit, type of feeding at hospital discharge.Subjective variables evaluated with a Likert-type scale (scores 1–5): degree of support from the partner during pregnancy, delivery, and postpartum; respectful treatment by professionals during pregnancy, delivery, and postpartum. The different categories used for each variable are detailed in Independent variables were:The primary outcome variable, risk of PTSD, was determined using the modified Perinatal Post-Traumatic Stress Disorder Questionnaire (PPQ)   for quantitative variables was performed.t-test to estimate qualitative and quantitative variables, respectively. Of these variables, and following Lemeshow’s statistical criteria, associations with p-values < 0.25 were selected for inclusion in the multivariate binary logistic regression model [The analysis of potential predictive factors, which have been previously identified in the literature as risk factors of delayed onset breastfeeding, was carried out in a bivariate analysis using the chi-square and Student’s on model ,32  selected for the multivariate analysis were: maternal age, parity, live birth, place of delivery, induced delivery, use of natural methods for pain, regional analgesia, general anesthesia, type of delivery, perineal tear, skin-to-skin contact, breastfeeding the first hour of life, admission of the newborn to care unit, hospital stay, breastfeeding at discharge, postpartum surgical intervention, postpartum readmission, degree of partner support during pregnancy, delivery and postpartum, and degree of respect received from professionals during pregnancy, delivery and postpartum.  and 10.9% (95), respectively. First, we built predictive models using the derivation cohort. The variables associated with the risk of PTSD  in the referral cohort was 0.70 (95% CI: 0.67–0.74) , while ip = 0.018), which was 14.2% (248) in the referral cohort and 10.9% (95) in the validation cohort  in the derivation cohort was 0.82 (95% CI: 0.79–0.85) , while ihort see .This study presents the main results of the development of two postpartum PTSD risk prediction models. Model A, constructed using only clinical variables, presented a satisfactory predictive capacity (AUC-ROC = 0.70), while model B, constructed with clinical variables and subjective patient perceptions, presented a good predictive capacity (AUC-ROC = 0.82). The predictive variables common to both models were: type of delivery, admission of the newborn to care unit, type of infant feeding at discharge, and postpartum hospital readmission. However, model A also included skin-to-skin contact and the presence of a severe tear as exclusive variables. In contrast, model B included variables relating to the support received from the partner and the perception of respect from healthcare professionals during childbirth.Currently, there are several studies published with PTSD risk prediction models ,25,26,27Regarding neonatal variables as factors that influence the risk of PTSD, various variables related to the newborn were identified, including the newborn’s hospital admission . Along sAnother variable included in our model B was the perception of respectful treatment by healthcare professionals toward women. This aspect is closely related to the concept of obstetric violence and has not been evaluated in other predictive models, despite the existence of publications that identify a relationship between the treatment received by healthcare professionals during childbirth care and the presence of PTSD ,37. ThisFinally, the support provided by the partner plays a relevant role in the risk of PTSD, in such a way that women who perceived that their partners supported them during pregnancy, childbirth and the postpartum period had a lower risk of PTSD, coinciding with the model of Czarnocka and Slade based on a study carried out with 264 women .One of the potential limitations of this study was that the observed prevalence of PTSD risk was high compared to other studies. In a systematic review with a meta-analysis carried out by Yildiz et al., average rates of 4.0% were found overall (95% CI: 2.77–5.71), and 18.5% (95% CI: 10.6–30.38) in women at risk [Another limitation of the study was that it was carried out in a population residing in Spain, and even though the validation results were good, they need validation in other countries and cultural contexts. Regarding strengths, in addition to satisfactory predictive capacity, these models have other positive characteristics, such as including only five variables (parsimony principle), using variables that are usually recorded in medical records, and having a justified relationship with the risk of PTSD. We should also highlight that the model was validated in a population different than the one used to create the models, and they also had different prevalences for PTSD risk. These differences are interesting for the extrapolation of results; this validation cohort could almost be considered external validation. Additionally, creating two predictive models may be useful for clinicians because it will expand application possibilities. For example, in situations where verbal contact with patients is not possible, model A, based on clinical variables recorded in medical records, could be used. While when verbal contact with the patient is possible, model B would be the instrument of choice. In particular, this tool is especially useful for professionals who have initial contact with women after childbirth. These professionals can use this tool as screening to identify patients who require further evaluation by more specialized professionals in the field of postpartum PTSD, such as psychologists and psychiatrists.In short, two predictive models formed by clinical variables and perceptions of support from their partner and the care received from health professionals presented adequate predictive capacities to predict the risk of postpartum PTSD both in the referral cohort and in the validation cohort. The model of choice includes the woman’s perceptions of support received from her partner and the relationship with healthcare professionals. These models can help identify women at increased risk for postpartum PTSD, increasing the early detection of this increasingly prevalent problem. On the other hand, they can also be useful in primary prevention if health policies are applied that reduce risk factors such as cesarean delivery and inadequate treatment by health professionals and encourage other factors such as skin-to-skin contact and breastfeeding.


This study aims to evaluate the influence of dietary flavonoids on the growth performance, blood and intestinal profiles, and carcass characteristics of broilers by employing a meta-analysis method.A database was built from published studies which have reported on the addition of various levels of flavonoids from herbs into broiler diets and then monitored growth performance, blood constituents, carcass proportion and small intestinal morphology. A total of 42 articles were integrated into the database. Several forms of flavonoids in herbs were applied in the form of unextracted and crude extracts. The database compiled was statistically analyzed using mixed model methodology. Different studies were considered as random effects, and the doses of flavonoids were treated as fixed effects. The model statistics used were the p-values and the Akaike information criterion. The significance of an effect was stated when its p-value was <0.05.Dietary flavonoids increased  the average daily gain of broilers in the finisher phase. There was a reduction (p<0.01) in the feed conversion ratio of the broilers both in the starter (linear pattern) and finisher phases (quadratic pattern). The mortality rate tended to decrease linearly (p<0.1) with the addition of flavonoids, while the carcass parameter was generally not influenced. A reduction (p<0.001) in cholesterol and malondialdehyde concentrations (both linearly) was observed, while super oxide dismutase activity increased linearly (p<0.001). Increasing the dose of flavonoids increased (p<0.01) the villus height (VH) and villus height and crypt depth (VH:CD) ratio (p<0.05) in the duodenum. Similarly, the VH:CD ratio was elevated (p<0.001) in the jejunum following flavonoid supplementation.Increasing levels of flavonoids in broilers diet leads to an improvement in growth performance, blood constituents, carcass composition and small intestinal morphology. Two main goals of the broiler industry are to improve growth performance and optimize the quality of broiler meat. In addition, another objective at present is to produce healthy broiler meat without the addition of any antibiotic growth promoters. This is considered to be important, as regulations in many countries prohibit the use of antibiotics and hormones for growth . HoweverOne of the potential secondary metabolites for use in broiler production are flavonoids, a compound that can be found in various parts of plants, such as the fruits, leaves, stems, and bark. It had been reported that flavonoids can be used as human and animal medicine since the compound possesses antibacterial, antioxidant, antiinflammation and hepatoprotective properties ,10. FlavA database was built from published studies which have reported on the addition of various levels of flavonoids from herbs to broiler diets. Accordingly, different forms and levels of flavonoid supplementation, as well as various flavonoid sources, were specified in the database. Science Direct, Google Scholar and Scopus were used as the search tools to compile the related articles, using the keywords “flavonoid”, “herbs”, and “broiler”. Growth performance ; blood constituents ; carcass proportion ; and small intestinal morphology  were the parameters included in the database.in vivo on broilers. A total of 60 articles were initially found after searching using the above-mentioned keywords. All these papers were further evaluated on the basis of their abstracts and full texts, which resulted in 42 papers being integrated into the database (The criteria for articles to be included in the database were that: i) they were published in English; ii) treatments included the addition of a flavonoid source to certain basal feeds; and iii) experiments were conducted database . When anThe database was statistically analyzed using mixed model methodology in which the model has been widely used in meta-analysis research related to animal nutrition ,14. DiffYij = dependent variable, B0 = overall intercept across all studies (fixed effect), B1 = linear regression coefficient of Y on X (fixed effect), B2 = quadratic regression coefficient of Y on X (fixed effect), Xij = value of the continuous predictor variable (flavonoid addition level), si = random effect of study i, bi = random effect of study i on the regression coefficient of Y on X in study i, eij = the unexplained residual error. When the respective quadratic regression model was not significant at p<0.05, the corresponding linear regression mixed model was applied. Variable study was declared in the class statement since it does not contain any quantitative information. The model statistics used were p-values and the Akaike information criterion. The significance of an effect was stated when the p-value was <0.05. All statistical analyses were carried out using R software, version 3.60.where The addition of flavonoids quadratically increased (p<0.05) the ADG of broilers in the finisher phase, but the effect was insignificant in the starter phase . Feed inThe effects of flavonoids on blood constituents and the small intestinal morphology of broilers are presented in This meta-analysis study generally indicates the positive effects of dietary flavonoid addition on the growth performance, blood metabolites and small intestinal morphology of broilers. Flavonoids are a class of phytochemicals that possess antibacterial activity against a wide range of microbial species, including pathogenic and other undesirable bacteria present in the digestive tract. Pathogenic bacteria, as a main cause of disorders in the digestive tract, can apparently be inhibited by flavonoids. Such pathogens may injure the intestinal villi and therefore interfere with nutrient absorption . Their pThe meta-analysis shows limited effects of flavonoids on the carcass and organ composition of broilers, except for the liver. This was confirmed by previous studies ,20. The With regard to blood glucose levels, flavonoids contain β-flavonoid rings  which plThe meta-analysis has discovered that increasing flavonoid levels in broiler diets leads to an improvement in growth performance, blood constituents, carcass composition and small intestinal morphology, based on various literatures. Interestingly, the ADG increase due to dietary flavonoids is linked with improvement in small intestinal morphology, such as VH and the VH:CD ratio, without interfering with carcass composition. The concentration of blood constituents such as cholesterol, MDA, triglycerides, and low-density lipoprotein falls with higher doses of flavonoids, while increasing super oxide dismutase activity and high-density lipoprotein.


The mDurance® system is an innovative digital tool that combines wearable surface electromyography (sEMG), mobile computing and cloud analysis to streamline and automatize the assessment of muscle activity. The tool is particularly devised to support clinicians and sport professionals in their daily routines, as an assessment tool in the prevention, monitoring rehabilitation and training field. This study aimed at determining the validity of the mDurance system for measuring muscle activity by comparing sEMG output with a reference sEMG system, the Delsys® system. Fifteen participants were tested during isokinetic knee extensions at three different speeds , for two muscles  and two different electrodes locations . The maximum voluntary isometric contraction was carried out for the normalization of the signal, followed by dynamic isokinetic knee extensions for each speed. The sEMG output for both systems was obtained from the raw sEMG signal following mDurance's processing and filtering. Mean, median, first quartile, third quartile and 90th percentile was calculated from the sEMG amplitude signals for each system. The results show an almost perfect ICC relationship for the VL (ICC > 0.81) and substantial to almost perfect for the RF (ICC > 0.762) for all variables and speeds. The Bland-Altman plots revealed heteroscedasticity of error for mean, quartile 3 and 90th percentile (60 and 300 deg/s) for RF and at mean and 90th percentile for VL (300 deg/s). In conclusion, the results indicate that the mDurance® sEMG system is a valid tool to measure muscle activity during dynamic contractions over a range of speeds. This innovative system provides more time for clinicians  and sport trainers , thanks to automatic processing and filtering of the raw sEMG signal and generation of muscle activity reports in real-time. The application of surface electromyography (sEMG) has been widely used to measure muscle activity signals, facilitating access to electrophysiological processes that cause the muscle to generate force and produce movement De Luca, . In mediThe electromyographs present valued benefits providing depth knowledge as an assessment tool in the prevention, monitoring rehabilitation, and training field. The most advanced and complex electromyographs in the field of research have incorporated numerous sEMG channels and synchronization with other technologies such as accelerometry, force platforms and motion capture systems  and software (proprietary android app and cloud service), has not been validated yet, so a joint validation (software and hardware) is found fundamental. Hence, the aim of the current study is to evaluate the concurrent validity of the mDurance system, both hardware and software, for measuring muscle activity by comparing sEMG output with a reference sEMG system .Fifteen participants  were recruited for this study. All participants met the inclusion criteria: (1) older than 18 years old; (2) be able to extend and flex the knee with a range of motion >90° (between 90 and 180°); and (3) free of any neurological disorders or musculoskeletal injuries within the last 6 months. After receiving detailed information on the objectives and procedures of the study, each participant signed an informed consent form in order to participate, which complied with the ethical standards of the World Medical Association's Declaration of Helsinki (2013). It was made clear that the participants were free to leave the study at their convenience. The study was approved by the Universidad de La Frontera (Chile).Participants were refrained from severe physical activity for, at least, 48 h before the tests. All tests were conducted, at least, 3 h after eating. Prior to all testing, height and body mass were measured using a precision stadiometer and balance  for descriptive purposes. For the measurements, the vastus lateralis (VL) and rectus femoris (RF) were collected from both legs and with both sEMG systems simultaneously  is a portable and low-cost sEMG system that consists of three parts. First, a Shimmer3 EMG unit , that is a bipolar sEMG sensor for the acquisition of superficial muscle activity. Each Shimmer sensor is composed of two sEMG channels, with a sampling rate at 1,024 Hz. Shimmer applies a bandwidth 8.4 kHz, the EMG signal resolution is 24 bits and overall amplification of 100–10,000 V/V. The electrodes used were pre-gelled Ag/AgCl with a diameter of 10 mm and an interelectrode distance of 20 mm. Second, the mDurance (Android) mobile application is responsible for receiving data from the Shimmer unit and sending it to a cloud service. And, third, the mDurance cloud service where the sEMG signals are stored, filtered, and analyzed, generating the reports.TrignoTM Wireless System , henceforth Delsys, was the reference system used to compare with the novel electromyograph. It is a widespread commercial sEMG system with 16 channels and a sampling rate at 2,000 Hz. Besides, Delsys applies a built-in filter of 20–450 Hz bandwidth, the EMG signal resolution is 16 bits, and the inter-sensor latency <500 us. The acquisition was carried out via the EMGworks® Software .Both sEMG systems were compared through their natural hardware configurations despite their differences , and it was taken into account for the processing and filtering of the signal.A HUMAC Norm  isokinetic dynamometer was used to control and measure angular displacement during knee extension sets. The dynamometer was used to reduce variability in the performance of the movement by controlling motion speed and position.For the validation testing, participants were instructed to cycle for 10-min on a stationary bike at a self-selected pace followed by mobility exercises  for the warm up . Then, wFor the processing and filtering of the raw signals of the two independent systems into the sEMG output signal, we implemented in Python the mDurance methodology used in its cloud service. (1) First, both the isometric and dynamic tests were filtered using a fourth order Butterworth bandpass filter with a cut-off frequency at 20–450 Hz, only for mDurance raw signal since Delsys already includes this filter by the hardware. (2) Second, the signal was smoothed using a window size of 0.025 s root mean square (RMS) and a overlapping of 0.0125 s between windows for both systems separately. (3) And third, the MVIC value was calculated using the average of the three maximum peaks of the RMS signal during the 5 s isometric test, and being the MVIC used for normalized the RMS signal of each system. The use of the average (following mDurance mythology) instead of the peak for the MVIC calculation will not affect the magnitude of the sEMG outputs inter-systems Burden, . Python To determine the onset and offset of each muscle contraction, a threshold of 10% was applied to the normalized RMS signal from the MVIC  De Luca. Subsequt-test) was conducted between systems, and the Cohen's d effect size (ES) was used to interpret the magnitude of the differences . Descriptive statistics are represented as mean and standard deviation (SD). In order to examine the concurrent validity between systems , the level of agreement between sEMG data from both devices was examined. To that end, a comparison of means  between systems for measuring the sEMG activity of the RF at different speeds (r > 0.7) between data from both systems for all parameters at 60, 180, and 300 deg/s. The ICCs reported almost perfect relationships (ICC > 0.81) for every variable at any speed condition .Despite the pairwise comparisons showed some significant differences , and substantial to almost perfect ICCs (ICC > 0.762) for all parameters at every speed.Regarding the other muscle , the means comparison revealed the lack of differences at any speed . The corIn order to ensure the lack of effect of electrode position , a between systems comparison  was performed for every parameter at every speed for both right and left leg. Almost perfect ICCs were obtained, with ICCs > 0.88, where the confidence interval spans between moderate and almost perfect (0.411–0.980) in all cases.The Bland-Altman plots revealed heteroscedasticity of error for some sEMG-related parameters of the RF at 60 deg/s , at 180 deg/s , and 300 deg/s  .For the VL , the BlaThis study aimed at determining the validity of the mDurance system for measuring muscle activity during isokinetic knee extensions at three different speeds , for two muscles  and two different electrodes locations , by comparing sEMG output with a reference sEMG system, the Delsys. The results obtained suggest that the mDurance system provides valid sEMG output data for VL and RF during knee extensions at 60, 180, and 300 deg/s speed, showing a strong concurrent validity as compared to Delsys sEMG system, based on Pearson's coefficients and ICCs referring to a relative validity. However, Bland-Altman plots suggest an acceptable absolute validity, due to the random errors, going from ±8% for the mean to ±15% for the Perc90.r > 0.7, p < 0.001) reported by the Pearson correlation analysis for the RF, and significant for the VL , for all speeds and all variables. In comparison with our results, Burns et al.  and sports  applications. Thirdly, the lack of standardized methods and analysis for sEMG validations studies may make difficult to compare with similar validations. Finally, an important consideration is that validation data were obtained from an analysis based on within-participant variation (CV) rather than on different days  so, our current reliability statistics might not generalize to runs performed several days apart.The results indicate that the mDurance® sEMG system is a valid tool to measure muscle activity during isokinetic contractions over a range of speeds, tested in laboratory conditions. Our results revealed an excellent relative validity for all variables, and an acceptable to good-enough absolute validity, with a systematic bias of 1.62 ± 8% random error for the mean. From a practical standpoint, mDurance as a system made up of Shimmer sensor and proprietary software, is a valid sEMG system, as compared to Delsys. This novel system includes a user-friendly software, a light hardware and a reasonable price, which make it more affordable and accessible for clinicians and sport trainers. In addition, it provides more time for interpretation and for addressing patients' pathologies or making recommendations to athletes instantly, thanks to the generation of real-time reports. Further research is required to establish reliability (test-re-test) over several days and to check the validity of mDurance measurements in more muscles from other areas and sizes, in more exercises modalities  and at different submaximal intensities.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving human participants were reviewed and approved by Universidad de La Frontera, Temuco, Chile. The patients/participants provided their written informed consent to participate in this study.AM-M, FC-P, MD, and OB defined the experimental design. AM-M and ER-M collected the data. FC-P carried out in Python the mDurance's cloud computing simulation for signal processing and filtering. FG-P carried out the statistical analysis. AM-M conceptualized the approach and together with FG-P wrote the paper. LR-S, MD, OB, ER-M and FG-P reviewed the manuscript for scientific content. All authors have read and agreed to the published version of the manuscript.MD and OB were affiliated with the company mDurance Solutions S.L. The remaining 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.


Background: Estrogen replacement therapy (ERT) is a common treatment method for menopausal syndrome; however, its therapeutic value for the treatment of neurological diseases is still unclear. Epidemiological studies were performed, and the effect of postmenopausal ERT on treating neurodegenerative diseases, including Alzheimer's disease (AD) and Parkinson's disease (PD), was summarized through a meta-analysis.Methods: Twenty-one articles were selected using a systematic searching of the contents listed on PubMed and Web of Science before June 1, 2019. Epidemiological studies were extracted, and relevant research data were obtained from the original articles based on the predefined inclusion criteria and data screening principles. The Comprehensive Meta-Analysis Version 2 software was used to pool effective size, test heterogeneity, conduct meta-regression and subgroup analysis, and to calculate publication bias.Results: Our results showed that ERT significantly decreased the risk of onset and/or development of AD  and PD  compared with the control group. A subgroup and meta-regression analysis showed that study design and measure of effect were the source of heterogeneity. Age, sample size, hormone therapy ascertainment, duration of the treatment, or route of administration did not play a significant role in affecting the outcome of the meta-analysis.Conclusion: We presented evidence here to support the use of estrogen therapy for the treatment of AD and PD. Neurodegenerative diseases, such as Alzheimer's disease (AD) and Parkinson's disease (PD), are characterized by the sustained cell cycle arrest and production of a continuous senescence-associated secretory phenotype due to structural and functional changes in neurons  and its treatment effect on AD and PD. Several studies demonstrated that AD-related cognitive decline was improved and a lower risk of onset and/or developing AD was observed following the menopausal hormone therapy , no control group (n = 21), meta-analyses studies (n = 13), or repeated analysis with some documents (n = 6). Therefore, a total of 21 studies with 1,266 patient cases and 3,845 control cases were included in this meta-analysis. A flowchart of the selection process was presented in The initial search yielded 3,668 records from PubMed and 3,201 records from Web of Science. After the screening of titles and abstracts, 6,758 records were excluded because they were not related to our present subject. The remaining 111 articles were selected for full-text scrutiny. Ninety studies were excluded due to no usable data  and model, or other covariates.Age was provided in the form of the mean value, unless otherwise stated. Nearly all the studies included adjusted odds ratio (OR)/relative risk (RR)/hazard risk (HR) values because there were some differences in covariates among the studies.The Comprehensive Meta-Analysis Version 2 software  was used for all the statistical analyses. We grouped study findings on the basis of how hormone therapy was categorized  and included a summary for measure of effect and 95% CIs in the tables. These summaries were calculated based on random-effects models which involved a weighting scheme.P < 0.05. I2 index was used to determine the inconsistency across different studies to evaluate the impact of heterogeneity. We used 25, 50, and 75% of I2 to define low, medium, and high levels of heterogeneity. The Egger's test was used to determine the significance of a statistical test for publication bias to assess the degree of asymmetry in the funnel plot.Cochran Q test was applied to evaluate the statistical difference of heterogeneity across different studies. It was considered statistically significant when P < 0.05. Meanwhile, the change in I2 was compared before and after the introduction of covariates into the regression model.Meta regression was conducted among factors that might lead to heterogeneity in order to identify the main factors. A predefined subgroup analysis was used to assess the impact of various factors in the study. The following subgroups were defined in the AD group: case >500 vs. case ≤500, case-control study vs. prospective cohort, publishing year ≤1995 vs. 1996–2005 vs. 2006–2019, women age ≤70 vs. 71–79 vs. age ≥80, measure of effect: OR vs. HR vs. RR, hormone therapy ascertainment by interview vs. questionnaires vs. prescription database vs. medical records, duration of the treatment <5 years vs. 5–10 years vs. treatment >10 years. It was considered as statistically significant if We found 111 potentially relevant articles. Among these articles, a total of 21 eligible studies were pooled together for analyses . The NewStratification of the study: 13 were case-control studies, five were prospective cohort studies, and three were cross-sectional studies. Stratification of the location: 15 studies were conducted in America, three in Europe , and two other countries . In the AD group, there were 13 studies in America, two in Europe (one in the UK and one in Netherlands), and one in other countries. Stratification of neurological disorders: five cases evaluated the impact of ERT on PD and 16 cases on AD. All studies were collected on the use of hormone therapy either by self-report  at the start of the study, by electronic prescription database, or by medical records. Furthermore, all studies were included in this review except one reported using standard criteria to diagnose AD and dementia .P < 0.001) and PD  in patients compared with the control , but five studies of PD showed no heterogeneity . Since the data of PD were not enough, we only performed meta-regression analysis on the AD group. Study design (P = 0.01) and effect measure (P = 0.03) might be the sources of heterogeneity in the AD group, but number of cases (P = 0.172), age (P = 0.986), publication year (P = 0.712), hormone therapy ascertainment (P = 0.494), and duration of the treatment (P = 0.217) had no moderating effects on the significant association between hormone replacement therapy (HRT) and AD incidence (P > 0.05 in these studies)  .P = 0.01) and measure of effect (P = 0.03). Estimated pooled differences among each subgroup are presented in P < 0.001), adding more proof that ERT is indeed beneficial for treating AD.Furthermore, according to the results of subgroup analyses in the AD group, heterogeneity came from data measure. Two of the interaction terms of the predefined subgroups showed statistical significance: study design . Pathological cognitive changes had been a big challenge to recall the memory of hormone therapy use. We included several studies with hospital records or multidisciplinary evaluations on top of patient's self-report to reduce the chance of recall bias.P = 0.01). Therefore, we classified the articles into case-control study and prospective cohort study according to different study designs and then re-conducted meta-analysis. When only prospective cohort studies were included, we observed an increased effective size for AD studies , adding more proof that ERT is indeed beneficial for treating AD  showed no statistical significance. According to the subgroup analysis among age ≤70 , age 71–79 , and age ≥80 , there was no evidence indicating that age was associated with the risk of disease development.Some literature suggests that the role of ERT may depend on the age of menopause and the therapeutic intervention used. The time window of estrogen therapy is associated with the risk of onset and/or developing neurodegenerative disease, and early treatment performed 10 years after menopause can decrease the risk , as shown in Through different regulatory mechanisms, estrogen affects the conduction of nerve signals and tissue changes in the brain. At the same time, genes associated with neurodegenerative diseases are also shown to be regulated by estrogen  (Szmuilowicz et al., All datasets generated for this study are included in the article/supplementary material.QL and YC conceived and designed the study. SL and YS collected the data. YS, XC, and XL analyzed and interpreted the data. YS drafted the manuscript with critical revisions from all the authors.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.


M = 13.34; SD = 1.04) from the State of Nuevo León, Mexico. A MANOVA 3 × 2 was performed to analyze the data. The results revealed that adolescents involved in CPV showed higher levels of psychological distress and suicidal ideation and lower levels of family and social self-concept. It was also observed that girls with higher levels of CPV scored the lowest levels of psychological distress and suicidal ideation, as well as the lowest levels of family self-concept. The findings highlight that adolescents and especially girls involved in CPV also report internal maladjustment outcomes. Finally, the results and their implications for research and intervention with adolescents involved in CPV are discussed.Child-to-parent violence (CPV) is a growing public health problem with consequences for perpetrators and families. Most research has focused on individual and family risk factors. However, little is known about its links with individual outcomes. The aim of this study was to analyze the relationships between CPV and psychological distress, suicidal ideation, and self-concept in school-aged adolescents, taking into account the gender perspective. A study was conducted with a sample of 8,115 adolescents, aged between 11 and 16 years ( Child-to-parent violence (CPV) is defined as repeated behaviors of physical, psychological, or economic violence directed at parents . The incInvolvement in CPV is the result of the complex interplay between individuals and their broader social environment. Based on the ecological model by According to the General Strain Theory , CPV couCertain protector factors are related to lower involvement in CPV, despite psychological distress. Previous studies have highlighted that adolescents who reported lower levels of CPV have high levels of emotional regulation  and empaBoth psychological distress and self-concept are related to suicidal ideation among adolescents . FurtherPrior research has analyzed CPV taking into account socio-ecological theoretical frameworks. The present study also takes into account the General Strain Theory  and examBased on the foregoing research, the following hypotheses were proposed:H1: Adolescents reporting higher levels of CPV were expected to show higher levels of psychological distress and suicidal ideation.H2: Adolescents with low levels of involvement in CPV were expected to show higher levels of family and social self-concept.H3: Girls were expected to report higher levels of psychological distress, suicidal ideation, and family self-concept, and lower levels of social self-concept than boys.H4: Girls highly involved in CPV were expected to report the most adverse maladjustment outcomes, characterized by the highest levels of psychological distress and suicidal ideation and the lowest level of family and social self-concept.Proportional stratified sampling was carried out according to urban and rural educational centers  in the State of Nuevo León (Mexico) . A total of 8,115 adolescents participated (51.5% boys and 48.5% girls) from 118 centers , of which 62.1% studied in urban schools and 37.9% studied in rural schools. The ages ranged from 12–13 years (53.7%) to 14–16 years (46.3%). Data lost by scale or sub-scale, provided they did not exceed 15%, were processed using the multiple linear regression imputation model . UnivariConflict Tactics Scales, CTS2, children to parents version ] for the subscale of violence toward the mother; and  for the subscale of violence toward the father. version  adapted Psychological Distress Scale (K10) ].le (K10) . It consSuicidal Ideation Scale ].on Scale , adaptedForm-5 Scale—AF-5—].ale—AF-5—. For theResearchers from the Autonomous University of Nuevo León (Mexico) in collaboration with the Pablo de Olavide University (Spain) carried out the planning and the research. First, an informative seminar was held with the students to explain the objectives, the scope of the study, and the procedure to be followed. Then, the necessary authorizations were obtained from school administrators and participating families were requested to give active parental consent for their child to participate in the study. The battery of instruments was administered voluntarily, anonymously, and supervised in two different sessions of approximately 25 min during school hours with a 15 min rest period between sessions. The questionnaires were answered individually on paper, administered in groups, and supervised by a group of previously trained researchers. Participation was voluntary and anonymous, with a rejection rate of 0.21%. It is important to underline that the study fulfilled the ethical values required in research with human beings, respecting the fundamental principles included in the Helsinki Declaration : informeThe studies involving human participants were reviewed and approved by Institutional Review Board of the Faculty of Psychology of Autonomous University of Nuevo Leon.First, in order to obtain an optimal number of clusters, a two-stage cluster analysis was performed using the two dimensions of CPV  toward the mother and the father. Three clusters were obtained with a good fit: low, moderate, and high CPV. Next, the k-means cluster analysis was performed. Finally, a multivariate factorial design was carried out (MANOVA 3 × 2) with CPV  and gender (boy and girl) as fixed factors, and as dependent variables, psychological distress, suicidal ideation, and self-concept , in order to analyze possible interaction effects. SPSS software (version 25) was used.F = 159.598, p < 0.001, η2 = 0.073], and gender   = 7.735, p < 0.001, η2 = 0.004] was obtained.A MANOVA was carried out and significant differences were obtained in the main effects of CPV  see . The effF = 545.973, p < 0.001, η2 = 0.119], suicidal ideation , family self-concept , and social self-concept  (see 2p is low and moderate (between 0.008 and 0.119).Regarding CPV, the ANOVA results found significant differences in psychological distress [008] see . The resF = 572.304, p < 0.001, η2 = 0.066], suicidal ideation , and family self-concept . As shown in Regarding gender, the ANOVA results showed significant differences in psychological distress . The results of the post hoc contrasts performed with the Bonferroni test (α = 0.05)  see  indicateF = 14.311, p < 0.001, η2 = 0.004]. The results of the post hoc contrasts performed with the Bonferroni test (α = 0.05)  see  revealedF = 9.396, p < 0.001, η2 = 0.002] was also obtained. As illustrated in Further, a statistically significant interaction effect between CPV, gender, and family self-concept [This study aimed to broaden knowledge of CPV and its association with various maladjustment outcomes. Based on the General Strain Theory, this research examined the relationships between CPV, psychological distress, suicidal ideation, and family and social self-concept, according to the gender of adolescents. Firstly, results indicated that CPV levels increased as psychological distress increased, confirming our hypothesis. These findings are consistent with those found in previous studies highlighting the direct association between adolescent aggression toward parents and outcomes of psychological distress such as depressive symptoms and anxiety . Our resSecondly, regarding suicidal ideation, the findings are very similar to the ones above. As expected, our findings showed that greater involvement in CPV resulted in higher levels of suicidal ideation. Previous studies have reported the relationship between suicidal ideation and other forms of violence, such as bullying and cyberbullying ; howeverThirdly, with regard to the second hypothesis, the results showed that CPV levels increased as family and social self-concept decreased. These results are consistent with those reported in previous studies for other forms of violence, and also they add scientific evidence to support the fact that adolescents who engage in CPV have psychological adjustment problems . More spFinally, in terms of gender differences, the results showed that girls reported higher levels of psychological distress and suicide ideation and lower levels of family self-concept than boys. However, outcomes for the interaction between CPV and gender revealed the need for more in-depth analysis of these relationships. Findings obtained indicated that girls scored higher on psychological distress than boys and as their involvement in CPV was more frequent, the differences between boys and girls were greater. This trend was observed for suicidal ideation too. Girls showed more suicidal ideation than boys, especially those with high CPV. These results are in line with prior studies  and withFirst, variables did not exhibit causal relationships because a cross-sectional design was applied. Longitudinal studies should therefore be carried out in the future. Second, these findings were obtained from a Mexican sample and could influence the generalization of the study results. Further research in other countries is needed to address these findings in other cultural contexts. In addition, this research was conducted with a school sample, thus, in future studies it would be interesting to expand the sample in other areas of study, such as in clinical and judicial samples. Moreover, it is important to highlight that this study was carried out with self-report measures, therefore, obtaining information from fathers, mothers, and teachers is necessary in order to better understand the relationships between the variables analyzed. Likewise, these results should be interpreted with caution because the Conflict Tactics Scale (CTS2) does not have a time parameter and could lead to recall bias due to the difficulty in accurately and completely remembering previous memories. Future research that includes the temporal dimension would allow us to further develop the findings obtained. Finally, we mentioned the differences found between CPV toward mothers and CPV toward fathers in previous research at the introduction of this work. However, these differences have not been analyzed in our study, and we consider it worthwhile to separately examine these dimensions of CPV, in order to advance the understanding of this kind of violence.The findings obtained in this study provide, in our opinion, relevant information in the field of psychology and education regarding the relationships between CPV and psychological distress, suicidal ideation, and self-concept in school-aged adolescents. It has been demonstrated that these three variables are significantly related, requiring an expansion of knowledge in the field of psychology and education. Thus far, these variables as a whole have been little explored. Findings reveal that CPV perpetrators, especially girls, also show maladjustment problems such as psychological distress, suicidal ideation, and poor family self-concept. Although boys are more frequently involved in CPV, girls show greater maladjustment problems. Our results also suggest the importance of examining self-concept from a multidimensional perspective. These findings underline that different self-concept domains are more related to different forms of violence. While social self-concept is important when examining peer aggression, family self-concept has been found to be especially relevant for understanding CPV. Finally, based on these findings, intervention programs should take into account that girls engaging in CPV also have more maladjustment outcomes. For example, actions should be implemented to foster family self-concept and to help adolescents involved in CPV  and their families cope with stressful situations in the family. In addition, some relevant implications for prevention and intervention programs in CPV were identified. On the one hand, the appropriateness of continuing to develop educational and treatment programs that promote networking and jointly consider different areas of intervention: school, family, and individual, should be considered; on the other hand, the need to consider psychological distress, suicidal ideation, and self-concept in the design of CPV prevention and intervention programs is highlighted.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation, to any qualified researcher.The studies involving human participants were reviewed and approved by the Institutional Review Board of the Faculty of Psychology of Autonomous University of Nuevo Leon. Written informed consent to participate in this study was provided by the participants’ legal guardian/next of kin.All authors of the manuscript contributed equally to the research and writing of the present study.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.


To correlate body weight, body mass index (BMI), and water-equivalent diameter , and SSDE for 1178 consecutive patients undergoing chest and abdomen-pelvic CT examinations. Associations among body weight, BMI, and dw were determined, and linear equations were generated using linear regression analysis of the first 50% of the patient population. SSDEs (SSDEweight and SSDEBMI) were calculated based on body weight and BMI as dw surrogates on the second 50% of the patient population. Mean root-mean-square errors of SSDEweight and SSDEBMI were computed with SSDE from the axial images as reference values.  An in-house program was used to calculate dw for the chest  and abdomen-pelvis . Mean values of SSDEweight and SSDEBMI based on the linear equations for body weight, BMI, and dw were in close agreement with SSDE from the axial images, with overall mean root-mean-square errors of 0.62 mGy (6.10%) and 0.57 mGy (5.65%), for chest, and 0.76 mGy (5.61%) and 0.71 mGy (5.22%), for abdomen-pelvis, respectively.  Both body weight and BMI correlated strongly with dw surrogates, can be used to calculate SSDEs in the chest and abdomen-pelvis CT examinations, providing values comparable to SSDEs from the axial images, with an overall mean root-mean-square error of less than 0.76 mGy or 6.10%. Both body weight and BMI, serving as  Owing to the fact that the parameter does not account for factors related to patients, CTDIvol only reflects the average output level of the CT scanner for certain scan settings and is appropriately adapted to its purposes for the comparison of different CT scanners and scanning protocols.The increased risk of radiation-induced cancer from CT scans is a major concern for the medical community –4. Compa patient , 9. CTDIvol on the basis of patient body size [vol is normalized to SSDE using size-dependent conversion factor (f) based on patient size expressed through an effective diameter (deff) or water-equivalent diameter (dw). Measured in centimeters, deff can be computed in combination with the anterior-posterior (AP) and lateral (LAT) dimensions. Measurements of AP and LAT are performed using the axial images or CT scanogram, as recommended by AAPM [dw requires delineating the region of interest and measuring CT attenuation on the axial images slice by slice to accurately calculate SSDE [deff and weight or body mass index (BMI) [deff, which only represents the geometric size of the patient, the accuracy of SSDE is inferior to that calculated using dw. Consequently, a number of efforts [deff and dw with the aims of using deff as the dw surrogate and achieving an accurate SSDE, comparable to that derived from the dw of the axial images. However, the methodologies still required measuring deff on the axial images, and a prescan SSDE could not be obtained. In addition, until recently, CT scanner manufacturers have not included SSDE on the CT scanner console display. Therefore, optimization of CT protocols on the basis of SSDE is impractical, and radiologists cannot use SSDE to assess the risk versus benefits of a patient undergoing a CT examination prior to imaging.The concept of size-specific dose estimate (SSDE) was introduced by the American Association of Physicists in Medicine (AAPM) to refine CTDIody size , 11. In  by AAPM , whereasex (BMI) –16. Beca efforts –19 have dw is a function of patient weight, suggesting that the calculation of SSDEs could be simplified using weight [dw. Hence, this study is aimed at determining the correlations between two biometric indicators of weight, BMI with dw and verifying the accuracy of an SSDE predicted using weight and BMI as surrogate body size metrics for dw for the chest and abdomen-pelvic CT examinations of adult patients.Sarmento et al.'s study reported that g weight , 21. To This retrospective study was executed with approval from Zhejiang Provincial People's Hospital Ethics Committee. The requirement of written informed consent was waived in accordance with hospital policies for clinical retrospective studies.n = 616) and abdomen-pelvic CT (n = 562). Among the patients, there were 782 males and 396 females with a mean age of 58.50 ± 13.20 years , mean weight of 63.07 ± 11.73 kg , and mean BMI of 23.00 ± 3.41 kg/m2 . The first 50% of patients in chronological order, 308 and 281 individuals that received chest and abdomen-pelvic CT examinations, respectively, served as a model sample to generate regression equations of body weight, BMI, and dw. The second 50% of patients, referred to as the verified sample, were used to confirm the feasibility of calculating SSDE based on body weight and BMI.A Picture Archive and Communication System  terminal was used to extract axial images and radiation dose structured reports. For the period between January and August 2019, the records of consecutive inpatients undergoing chest and abdomen-pelvic CT examinations were electronically retrieved. Patients with nondiagnostic images, truncated images, severe motion artifacts, and in-body or in-skin metal objects were excluded from this study. Patients with renal insufficiency (serum creatinine > 1.5 mg/dL) or known allergic reactions to iodinated contrast medium for contrast-enhanced CT were excluded from the study. The final study cohort was composed of a total of 1178 patients, including those that underwent chest CT (2). The body habitus was divided into four types according to the redefined World Health Organization (WHO) criteria for the Asia-Pacific Region [n = 102); B2: normal weight, 18.5 < BMI < 22.9 (n = 492); B3: overweight, 23.0 < BMI < 29.9 (n = 559); and B4: obese, BMI > 30 (n = 25).In accordance with our hospital's clinical practice, the weight and height of inpatients had been documented in the electronic medical records and displayed in the electronic application form for CT examination. BMI was calculated as weight divided by height squared . The scan parameters of both chest and abdomen-pelvic CT examinations were 100 or 120 kVp tube voltage, 0.5-second rotation-time, and a pitch factor of 1.35. Automatic tube current modulation (ATCM) was activated to reduce the radiation dose for all scans. ATCM is a combination of applications that reduce dose exposure in four dimensions (CARE Dose 4D), created by the manufacturer Siemens. Axial images were reconstructed with a standard tissue algorithm (B30f), a 512 × 512 matrix, 400 × 400 mm FOV, and 5/5 mm slice thickness and increment. The scan range for the chest CT was from the lung apices to the costophrenic angle, and the scan range for abdomen-pelvis CT included diaphragmatic top and pubic symphysis. The aforementioned scan parameters were set according to standard department CT protocols for adults.dw, f, and SSDE slice by slice and provide mean values across all axial images in accordance with the methodologies detailed in the AAPM report 220 [dw, f, and SSDE, including a single value slice by slice and mean values across all slices. The automatic calculation of dw, f, and SSDE required the following formulas [vol(s) is the slice CTDIvol, mAs(s) is the actual mAs per slice, mAs(a) is the averaged mAs displayed in the radiation dose structured report, CTDIvol is the volume CT dose index displayed in the radiation dose structured report, dw is the water-equivalent diameter, CTROI is the CT number of the whole axial image, AROI is the area of the axial image, f is the size-dependent conversion factor, and SSDE is the size-specific dose estimate.An in-house program based on MATLAB  was developed to automatically calculate port 220 . The autformulas :(1)CTDIweight, and SSDEBMI. SSDEweight and SSDEBMI, defined as the new radiation dose indicators, required three steps. Firstly, linear regression analysis was used to generate linear equations (y = a + bx) for body weight and BMI with dw across all modeled patients. Secondly, new body size metrics of dw, defined as dw,weight and dw,BMI, were predicted from body weight or BMI, after which the corresponding f was obtained using formula (weight and SSDEBMI were computed via f multiplied by CTDIvol(s). All three steps were performed with a Microsoft Excel 2016 spreadsheet embedded with all linear equations of dw and two biometric indicators of body weight and BMI. Only plain axial CT images were analyzed in this study.To analyze the radiation dose, we listed three SSDE measurements as follows: SSDE, SSDE formula . Finallydw, body weight, and BMI with dw were assessed with Spearman's rank correlation analysis and Pearson's correlation analysis, respectively. Steiger's test was used to compare the correlation coefficients of body weight and BMI with dw as the common variable in chest and abdomen-pelvis. A paired t-test was used for SSDEweight and SSDEBMI in chest and abdomen-pelvic CT examinations. The Bland-Altman test was performed to determine the accuracy of the linear equations compared with the measured values . The normality of continuous variables was determined using the Shapiro-Wilk test. Continuous variables with normal distributions were described as the mean ± standard deviation, and dichotomous variables were reported as counts and percent. The Spearman Rho test was used to assess the correlation of variables that do not follow normal distribution and Pearson's test for those which follow normal distribution. Associations between age and d values . With SSvol and values of dw, f, and SSDE, calculated using the in-house program, are shown in dw for both chest and abdomen-pelvis were considerably less than the 32 cm diameter of the standard AAPM phantom used to determine CTDIvol.The number of CT examinations for chest and abdomen-pelvis was 264 and 239 on the 40-slice scanner and 352 and 323 on the 128-slice scanner, respectively. Patient demographics are listed in dw for chest and abdomen-pelvis CT . Pearson's correlation analysis indicated that both body weight and BMI were strongly correlated with dw for the chest  and abdomen-pelvis . Steiger's test showed a statistically significant difference associated with the correlation coefficients of body weight and BMI with dw as a common variable for the chest . However, no significant difference was observed for two correlation coefficients of body weight and BMI and dw as a common variable for abdomen-pelvis using Steiger's test . dw automatically derived from axial images of modeled patients. The Bland-Altman test indicated that there was good agreement between measured dw and predicted values based on the linear equations for chest and abdomen-pelvis CTs ; SSDEweight and SSDEBMI were 13.81 ± 1.98 mGy and 13.79 ± 1.95 mGy in abdomen-pelvic CT examination, respectively . Compared with reference values of SSDE, slightly greater dispersions were observed for SSDEweight and SSDEBMI with respect to standard deviation, range, and coefficient of variation, as shown in weight and SSDEBMI were less than 11%, as shown in SSDEvol were underestimated compared to actual values [Prior to estimating patients' absorbed radiation dose, accurate measurements of patient size are necessary, as the radiation dose is closely related to patient factors as well as the output of the CT scanner. Similarly to previous studies , 23, we l values , 23, 24.deff and dw are suitable for quantifying patient size [deff, dw can be considered the gold standard for patient size, as it can be adapted to different body shapes, including complex deformities and asymmetric contours, and accounts for X-ray attenuations of heterogeneous tissues within the body. However, owing to the unavailability of commercial or in-house software in many health institutions worldwide, the measurement of dw is often a complex and time-consuming process for routine CT radiation dose calculations in radiological practice. The need for a simplified and efficient method to obtain dw is clear, and, in the meantime, accurate SSDEs are required.Previous studies have shown that the measurement of some patient size metrics, including age, height, body weight, BMI, body circumference, and body diameter, could be integrated into routine clinical practice for dose optimization , 26, 27.ent size , 11. Comdw. Because age is an easily obtainable factor, the correlation between age and dw was also assessed to determine whether age can be used as a dw surrogate to estimate SSDEs. Unfortunately, unlike the observation that dw increases with age for the pediatric population [dw and age for chest and abdomen-pelvis CT, which is attributed to the lack of growth of dw with the increasing ages of adult patients. However, similar to previous results reported by Menke [dw in chest and abdomen-pelvis, despite different populations in Asian-Pacific and European-American regions. Thus, age cannot be used to generate f for calculating SSDEs in adult patients. In contrast, both body weight and BMI can be used as dw surrogates for accurate patient size, while accounting for geometric dimensions and X-ray attenuation characteristics. However, it is important to note that an automated software program is required to calculate dw, which must be verified first. Only then is the implementation of dw surrogates recommended in clinical practice.The primary aim of this study was to determine the correlations between body weight, BMI, and pulation , no signby Menke , 25, we dw in chest. However, dw,weight was in good agreement with the measured dw, comparable to dw,BMI for chest. Our results also reveal that accurate measurements of patient size, i.e., dw, can be predicted using both body weight and BMI in abdomen-pelvis. With regard to the accuracy of SSDEs based on body weight and BMI, overall mean root-square-mean errors were less than 6.10% in chest and abdomen-pelvis CTs across all verified patients, although SSDEweight and SSDEBMI had slightly greater dispersion than the reference SSDEs. Additionally, a higher correlation coefficient between BMI and dw generated a smaller overall mean root-square-mean error of SSDEBMI compared with SSDEweight in chest and abdomen-pelvis across all verified patients, even when the two values of SSDEweight and SSDEBMI were similar. This result may be attributed to the fact that BMI, which takes height into account, is a better indicator of body size. For males, SSDEweight had a smaller overall mean root-square-mean error than SSDEBMI in the chest CT, while the opposite was true for the abdomen-pelvis region. For females, SSDEBMI had a smaller overall mean root-square-mean error than SSDEweight in either chest or abdomen-pelvis regions. These different results of males and female may be related to the distribution of fat. In general, fat is more distributed in the abdomen-pelvic region, and females tend to have relatively more fat content compared with males [weight and SSDEBMI were relatively small. In this study, we further investigated the accuracy of SSDEweight and SSDEBMI for eight different patient BMI populations. Our results indicate that the maximal mean root-square-mean errors were achieved for obese patients, which may be related to the smaller sample size of obese patients in this study.In terms of correlation coefficients, a significant difference was found between body weight and BMI with a common variable of th males . Furtherth males . Hence, dw and SSDE obtained were approximated, compared with a prospective study. Second, although the patient population had a wide BMI spectrum, a relatively small sample size of underweight and obese patients was available and no pediatric patients were enrolled. Therefore, further study is needed to determine whether our findings are applicable for overly small and overly large patients, and our results apply only for adult patients. Third, patient data in this study were acquired only from one health institution. As different CT scanners and subtly different CT protocol details, including pitch factor, dose modulation mode, scan range, and respiratory phase, are available in individual health institutions, our results need to be confirmed using data from multiple health institutions. Finally, the BMI of our patients was lower than that of Westerners, although some overweight and obese patients were enrolled in the study. Our results presented correspond to Asian-Pacific body types and may not be generalized for other body types.This study had some limitations. First, it was a retrospective study, and patient choice was a possible bias. However, the patient population was retrieved consecutively. It is likely that the values of dw and can be used as dw surrogates of anatomic regions of the chest and abdomen-pelvis. On the basis of the linear equations of body weight, BMI, and dw, SSDEs can be calculated efficiently and accurately in chest and abdomen-pelvis CTs, and the predicted values of SSDEweight and SSDEBMI are comparable to the reference SSDEs derived from axial images with an overall mean root-mean-square error of less than 0.76 mGy or 6.10% for chest and abdomen-pelvis CT. Therefore, we conclude that body weight and BMI can be used to simply and accurately estimate SSDE in the absence of software that automatically calculates SSDEs.Body weight and BMI were found to closely correlate with


Depth needs to be considered to understand visual information processing in cluttered environments in the wild. Since differences in depth depend on current gaze position, eye movements were avoided by short presentations in a real depth setup. Thus, allowing only peripheral vision, crowding was tested. That is, the impairment of peripheral target recognition by the presence of nearby flankers was measured. Real depth was presented by a half-transparent mirror that aligned the displays of two orthogonally arranged, distance-adjustable screens. Fixation depth was at a distance of 190 cm, defocused depth planes were presented either near or far, in front of or behind the fixation depth, all within the depth of field. In Experiments 1 and 2, flankers were presented defocused, while the to-be-identified targets were on the fixation depth plane. In Experiments 3–5, targets were presented defocused, while the flankers were kept on the fixation depth plane. Results for defocused flankers indicate increased crowding effects with increased flanker distance from the target at focus (near to far). However, for defocused targets, crowding for targets in front of the focus as compared to behind was increased. Thus, defocused targets produce decreased crowding with increased target distance from the observer. To conclude, the effects of flankers in depth seem to be centered around fixation, while effects of target depth seem to be observer-centered. One central question in vision science is how we are able to perceive and select distinct objects in a usually cluttered environment full of visual information. The visual search paradigm led to a wealth of insights how scanning the visual scenery for relevant information proceeds. A typical visual search task involves finding a target stimulus among distractor stimuli. In such cluttered displays, extrafoveal vision is usually involved, either to find the target, or to plan a next saccade. Presuming that target and distractors are individuated on a level of early visual representation, it is assumed that the deployment of attention needed to select relevant information is mainly guided by basic visual features .However, early visual representation is in almost all natural scenes restricted by crowding . CrowdinUsually, visual search and crowding experiments are conducted on two-dimensional planes. However, to understand information processing in the real world, the third spatial dimension, i.e., depth, needs to be considered. Evidence on the impact of depth on information processing in cluttered visual environments is yet scarce, especially for crowding. Most studies worked with virtual depth, i.e., stereoscopic presentations manipulating binocular disparity in order to induce the impression of depth. Here, we present a set of five experiments examining crowding effects in a real three-dimensional set-up.Reviewing studies investigating how depth affects visual search shows that depth information seem to promote efficient visual search. For example, Nakayama and Silverman  showed tThe assumption of an observer-centered spatial gradient of attention receives support from findings of prioritized processing of close stimuli: investigations of processing single stimuli in depth for example, show faster and more forceful reactions towards closer targets . NeurophHowever, other studies did not find evidence for observer-centered spatial effects: although Plewan and Rinkenauer ,24 foundIn visual search, depth is regarded as one feature capable of guiding attention , suggesKooi et al.  found leThe generalizability of the above reviewed findings to information processing in the real world might be limited, because all of these studies used stereoscopy. That way, only one depth cue is varied, namely binocular disparity. However, in real depth, a variety of further cues contribute to the perception of depth. Especially depth information from focus cues, which is, accommodation and defocus blur, are usually invalid in stereoscopic depth presentations and were shown to contribute to distortions of depth perception e.g., ,31). Thu. Thu31])One previous study that was conducted in real depth on the effect of depth on crowding suggests that there is a fixation-centered effect in depth, analogous to the effect of eccentricity in two-dimensional space (2D): Eberhardt and Huckauf  presenteThis research was conducted according to guidelines of the German Psychological Society (DGPs), the German Research Foundation (DFG), and in line with the declaration of Helsinki; all of the studies were considered exempt from formal ethical review. In all Experiments, prior to testing participants were fully informed about the experiment and that no harm is caused from participation. All of the participants gave their written informed consent for inclusion before they took part in the experiment.The apparatus consisted of two orthogonally arranged screens that were adjustable along a rail ,33. The All of the stimuli were presented on a dark background : tar: tar2). p is the inter-pupillary distance, a is the depth difference, a is the fixation distance, and Defocused stimuli either appeared in a distance near to or far from the fixation depth, each in both directions, in front of and behind the fixation depth of 190 cm. Near distance in front of the fixation depth was at 170 cm from the participant, near distance behind the fixation depth was at 215 cm. This is ±0.06 diopters (dpt), given by the difference between the distances of the fixation and the near depth planes in diopters . Stereovision was tested with red-green random-dot stereograms of the TNO Stereo Vision Test, and with real depth, using the Frisby Stereotest (except Experiment 3). The crowding task was conducted in a dimly lit room (approx. 2.5 lx). Participant’s head position was fixed by a head-chin rest, which was initially calibrated in order to ensure perfect individual central viewing and avoid vertical displacement of stimuli in defocused depth conditions. Prior to the experimental blocks, participants were familiarized with the task and went through extensive practice. Different depth conditions were tested block-wise, with pauses in between. In all experiments, the order of experimental blocks was varied between and balanced across participants.Participants’ task was to indicate the gap position of the target Landolt ring by keypress. The aim of Experiment 1 was to investigate the effects of flanker depth on crowding. Because previous studies found fixation- as well as observer-centered effects of flanker depth , flankeIn addition, Experiment 1 aimed at investigating which extent potential effects of real depth are driven by binocular depth information by applying a monocular control condition: If monocularly available defocus blur accounts for differences in depth, the effects of flanker distance and direction in depth should occur similarly under monocular and binocular observation. If differences in depth are mainly driven by binocular depth information, crowding effects across depth for monocular observation should not vary with flanker depth (compare ).The sample consisted of 20 participants  and screen configuration (fixation depth on Screen 1 or Screen 2). Thus, each participant went through ten experimental blocks. The presentation of isolated targets was evenly distributed across the ten blocks. In each block, 48 trials were conducted: four (gap position of the target Landolt ring) Monocular and binocular data were obtained in two separate sessions, with a pause of at least 15 min. in between. For monocular observation, the non-dominant eye was occluded while the dominant eye was centered. Half of the sample started with binocular, the other half with monocular viewing.Data analysis was performed using IBM SPSS Statistics Version 25 . An alpha level of t-Tests were performed post-hoc in order to compare conditions with defocused flankers to the two-dimensional condition at the fixation depth.Crowding effects were analyzed, i.e., the difference between isolated and flanked accuracy in target recognition. To investigate the impact of flanker depth, we conducted a M = 98.16% (standard error (SE) = 0.49) substantially higher than for flanked targets in all depth conditions. This shows that the presence of the flankers resulted in substantial crowding in all of the tested depth conditions.In the upper part of F = 41.54, p < 0.01, F = 6.03, p = 0.02, F = 1.43, p = 0.25. These effects were replicated in another study with a sample of n = 24 participants. The results can be reviewed in the There was a significant main effect of flanker distance, p < 0.01. Flankers in far distance behind the fixation depth produced significantly more crowding when compared to the fixation depth, p = 0.01. The two other comparisons were not significant .In addition to the effects of flanker distance and direction in depth, we compared crowding effects for defocused flanker conditions to the control condition at the fixation depth by Bonferroni-corrected one sample T-Tests. Relative to fixation depth, crowding was significantly lower when flankers were in near distance in front of the fixation depth Taken together, binocular data revealed a fixation-centered effect, i.e., increased crowding with increased flanker distance, as well as an observer-centered effect, i.e., less crowding for flankers in front as compared behind the fixation plane, of flanker depth on crowding effects.M = 94.4 (SE = 1.71) substantially higher than for flanked targets in all of the depth conditions. This shows that the presence of the flankers resulted in crowding in all tested depth conditions.Crowding effects with monocular viewing are given in the top right panel of F = 1.57, p = 0.23, for flanker direction, F = 3.86, p = 0.06, or for the interaction of distance and direction, F = 2.43, p = 0.14. Thus, with defocus blur as the only possibly available depth cue, flanker depth did not affect target recognition differentially. This replicates earlier findings )The examined data were normalized to the number of all incorrect responses (compare ) to avoiThe data show that flanker confusions were substantially higher than expected by chance performance in all flanker depth conditions. Thus, flanker processing is in general impaired only little. This is particularly astonishing because the task irrelevant, i.e., the flanking, stimuli varied in depth. Converging evidence from Experiment 1 and Experiment 2 shows no clear indication for systematic effects of flanker distance or direction, though, a final conclusion would require inferential analysis on a more reliable database. Nevertheless, taking together Experiments 1 and 2, the data suggest that flanker features were processed well. It seems unlikely that impaired feature processing for flankers in depth explains differences among the depth conditions.In the previously described Experiments 1 and 2, we investigated how depth deviation of irrelevant, i.e., flanking, stimuli affects crowding. The aim of Experiment 3 was to examine how depth deviation of the relevant, to-be-identified target stimulus affects crowding. Feature processing of defocused stimuli was affected only few in the previous experiments. This suggests that a defocused target stimulus should also not suffer from decreased resolution. Transferring results from Experiments 1 and 2, processing of a target stimulus should be affected similarly by depth variation: applying the fixation-centered effect of depth distance suggests also for the variation of target distance increased crowding with increased target distance. Regarding the observer-centered effect of direction observed in Experiments 1 and 2 as an effect of relative target-to-flanker configuration in depth , more crowding for targets in front when compared to targets in the back should be expected.The sample consisted of 24 participants , two visual fields , and four target gap positions , repeated five times in both screen configurations.F = 12.21, p < 0.01, F < 0.01, p = 0.93, and F = 3.81, p = 0.06, respectively.In the upper part of p = 0.93, p > 0.99, p > 0.99, and p = 0.25.In addition to the effects of target distance and direction in depth, we compared the crowding effects for defocused target conditions to the control condition at the fixation depth by Bonferroni-corrected one sample T-Tests. The results indicated no significant difference between the condition at the fixation depth and defocused targets at far front, near front, near back, or far back, i.e., Taken together, we observed for defocused targets only an observer-centered effect of target direction, indicating more crowding for targets in the front when compared to in the back. This mimics the results of defocused flankers where there was more crowding when flankers were displayed behind the target. In sum, both of the results could be explained by relative target-to-flanker configuration. Nevertheless, the absence of an effect of target’s distance from fixation is surprising, since, for defocused flankers, distance in depth produced the strongest effects on performance. Therefore, reconsidering the results pattern of Experiment 3, the observer-centered effect of target direction could also be due to the absolute target depth distance from the observer, rather than the relative target-to-flanker configuration in depth. We address this question in Experiments 4 and 5.Rephrasing the pattern of results that were observed in Experiment 3 for target depth, decreased crowding with increased target distance from the observer was found. This raises the question the role of relative depth information like target-to-flanker depth configuration and the role of the relation of stimuli to fixation and the possible contribution of absolute depth to the effects. Therefore, in Experiment 4 the fixation depth was varied in addition to target depth.The sample consisted of 20 participants , In F = 12.23, p < 0.01, F = 2.31, p = 0.15, and F < 0.01, p > 0.99, respectively. Thus, the results suggest an observer-centered effect: absolute target distance from the observer affects crowding, irrespective of the spatial relation between target and flankers and/or fixation. While the flankers are presented at the fixated depth, the variation of target depth within the depth of field produces systematic changes in crowding, depending on the absolute target distance from the observer: targets closer to the observer result in more crowding.In order to investigate the impact of target depth, we conducted a M = 50.76% (SE = 0.48) of correct estimation —might be that presentation duration was too short to enable the appearance of depth. Thus, the aim of Experiment 5 was to replicate results from Experiment 4 using a prolonged presentation duration in order to examine whether the observed effects of target depth on crowding are due to restricted presentation duration.The sample consisted of 20 participants  = 20.47, p < 0.01, F = 1.77, p = 0.2, and F < 0.6, p = 0.45, respectively. Thus, the results from Experiment 4 were replicated with a prolonged presentation duration, showing that the presentation duration does not alter the crowding effects in depth.A M = 49.34% (SE = 0.54) of correct estimation  and fixation- and observer-centered references in real three-dimensional (3D)-space within the depth of field. Therefore, in Experiments 1 and 2 flanker depth was varied while targets were presented at the fixation depth; in Experiments 3–5 target depth was varied while the flankers were presented at the fixation depth.For defocused flankers, we found both an effect of flanker direction and an effect of flanker distance in depth. Comparing their effect sizes shows that the effect of flanker direction on crowding was clearly pronounced weaker than the effect of flanker distance in depth , but rather, processing of the spatial stimulus configuration and consequential problems to localize the relative positions of the stimuli in depth, might have caused the effect.Interestingly, a previous study also observed increased crowding when strings containing target and flankers were defocused . Thus, oAt this point, it should not be neglected that both the effect of flanker distance as well as the effect of flanker direction show up in the present study in opposite directions than found by Astle et al. . HoweverFor defocused targets, we found only an effect of target direction in depth, indicating more crowding for targets in front, i.e., closer to the observer, compared to behind the fixation depth. In Experiments 4 and 5 we further investigated whether this effect of target direction was due to absolute target depth, or target-to-flanker relation in depth. The data suggest a subordinate role of target-to-flanker relation in depth. Rather, the effect of more crowding for targets in front of as compared to behind fixation was driven by absolute target distance from the observer. It seems that flanked targets closer to the observer produce more crowding than flanked targets more distant from the observer, irrespective of flanker depth, and also irrespective of fixation depth (as shown by Experiments 4 and 5). It seems that the spatial reference for the effects of the variation of target depth is the observer’s position in space.Accordingly, what makes crowding of defocused targets different from crowding by defocused flankers? When varying target depth, a feature of the task relevant stimulus is manipulated while for variation of flanker depth task irrelevant stimuli are manipulated. Theeuwes et al.  suggest Another interesting finding in the present data is the direction of the effect of target depth: targets closer to the observer produced more crowding. Similar results were found in some other studies using the visual search paradigm ,23. AndeIn addition to this perceptual factor, Maringelli et al.  found thIn the present study, we investigated whether varying stimulus depth affects crowding. Although, systematic effects of depth on crowding were found, and Experiment 1 confirms that these effects of depth occur after binocular images are combined, Experiments 4 and 5 show that explicit depth estimation was not possible, neither for 20 ms nor for 100 ms of presentation duration. Thus, the present study covers the effects of early depth processing in real three-dimensional space.These early effects of depth in the present set of Experiments were not sufficient to alleviate crowding substantially in the tested range of depth within the depth of field. Only in Experiment 1 for near flankers in front was crowding reduced as compared to fixation. In most conditions, stimulus selection was impaired by stimulus depth. One possibility is that the spatial configuration of depth cannot be extracted in these early stages of depth estimation. Studies on depth perception have shown that depth of nearby stimuli is averaged when segmentation is not possible . HoweveThe early effects of depth on stimulus selection in real depth described in the present paper might be modulated by other subsequent processes. For example, in visual search, depth can be estimated based on several saccades across depth.Because saccade planning in visual search relies on peripheral visual information in cluttered environments, crowding is inherent to visual search. Hence, which consequences do the present findings have for visual search in real depth space? Given that crowding can impair estimation of spatial relationships across real depth, visual search in real depth space might take longer because visual selection is impaired. This should result in delayed or inaccurate fixations .The present results seem to be especially relevant for mixed reality settings. Here, situations of crowded information can occur very quickly and depth differences are innate to the presentation devices. The present data showed that when it is not possible to gain information about the spatial relationships in depth, perception is impaired in that crowding increases. One can think of various situations: for example, task that are irrelevant virtual information (operating like flankers) can interfere with identifying real objects, or irrelevant real information can interfere with identifying virtual objects. Thus, the design of augmented reality devices should ensure that the presented information is embedded into the spatial context of the visual scenery to avoid additional interference by spatial uncertainty.