Ruminants play a great role in sustainable livestock since they transform pastures, silage, and crop residues into high-quality human food (i.e. milk and beef). Animals with better ability to convert food into animal protein, measured as a trait called feed efficiency (FE), also produce less manure and greenhouse gas per kilogram of produced meat. Thus, the identification of high feed efficiency cattle is important for sustainable nutritional management. Our aim was to evaluate the potential of serum metabolites to identify FE of beef cattle before they enter the feedlot.r = 0.55, P < 0.05). Pathway enrichment analysis (Mummichog) yielded the Retinol metabolism pathway associated with feed efficiency in beef cattle in our conditions.A total of 3598 and 4210 m/z features was detected in negative and positive ionization modes via liquid chromatography-mass spectrometry. A single feature was different between high and low FE groups. Network analysis (WGCNA) yielded the detection of 19 and 20 network modules of highly correlated features in negative and positive mode respectively, and 1 module of each acquisition mode was associated with RFI  contains supplementary material, which is available to authorized users. The Food and Agriculture Organization of the United Nations estimates the world population will reach 9 billion people by 2050 and as a consequence, livestock production must double to meet the demand for food . SustainDue to its importance, more than two dozen feed efficiency measurements have been proposed to select efficient animals and from those, residual feed intake (RFI) is considered one of the most effective methods , 7. As aMetabolomics is the systems-scale study of low-molecular-weight biochemicals < 1500 Da) involved in metabolism, including carbohydrates, lipids, amino acids, biogenic amines, and organic acids , 11. Due00 Da invCurrently, there is an urgent need to develop new ways to predict FE in livestock, since the use of the commercially available genomic markers for genetic selection is not sensitive enough due to low to moderate heritability (ranging from 0.08 to 0.49) of the FE trait –22. TherBrachiaria spp. pastures. On adaptation period, animals received corn silage (ad libitum), gradually replaced by trial diet  offered at 8:00 h and 16:00 h. After the experiment, all animals were slaughtered following the guidelines of the Institutional Animal Care and Use Committee. More details regarding animals, diet and experimental design can be found in Alexandre et al. [All animal procedures were approved by the Institutional Animal Care and Use Committee of the Faculty of Food Engineering and Animal Science at the University of Sao Paulo (protocol 14.1.636.74.1). The serum of 98 Nellore young bulls (16 to 20 months old and 376 ± 29 kg BW) born and raised in the University of Sao Paulo were collected 21 days prior to a 70-d feedlot. Briefly, the feeding-trial period was preceded by 21 days of adaptation to diet and location and before that, the animals were maintained in a single group on e et al. .RFI was calculated as the difference between the expected and observed feed intake, considering the average metabolic weight (MBW) and ADG to predict DMI . The 98 Yij is the observation of jth individual, son of ith sire, with k age; μ is the general mean of the RFI; βi is the sire effect; βj is the age effect and eij is the random residual error, ~NID ; and σ2e is the residual variance. The phenotypic measures included: initial body weight (BWi), final body weight (BWF), dry matter intake (DMI), average daily gain (ADG), feed conversion ratio (FCR), residual feed intake (RFI), residual body weight gain (RWG), residual intake and body weight gain (RIG), initial ribeye area (REAi), final ribeye area (REAf) and gain of ribeye area (REAg). Normality of data was tested by the Shapiro-Wilk test. Student’s t-test was applied to compare the groups for normally distributed variables and Mann-Whitney-Wilcoxon test for nonparametric variables using R STATS package. Results were considered significant when p-value (P) ≤ 0.05. The RFI values were adjusted using regression model, in which the age was fitted as a covariate for network analysis  by jugular venipuncture using vacutainer tubes. After 30 min at room temperature for clot formation, all samples were centrifuged at 3500×g for 15 min at 4 °C and stored at − 80 °C until further analysis, following the recommendations of Tuck et al. .g for 4 min at room temperature, and the supernatants were dried in a vacuum centrifugal evaporator for 3 h at 30 °C and stored at − 20 °C prior to analysis. The samples were reconstituted in 200 μL H2O and centrifuged at 12000 rpm for 15 min. The supernatants were transferred to analytical vials for analysis using a Xevo G2 XS quadrupole-time-of-flight mass spectrometer (Q-TOF-MS) in positive and negative modes . Chromatographic separation was performed by an Acquity I-Class UPLC system  using a Waters Acquity BEH C18 column   at 50 °C. The injected sample volume was 5 μL. The mobile phase consisted of 0.1% formic acid-water (eluent A) and 0.1% formic acid-methanol (eluent B). The gradient elution in positive mode was performed at a flow rate of 0.4 ml/min, as follows: between 0 and 1 min 0% eluent B; 1–16 min increasing up to 100% eluent B;16–20 min at 100% eluent B and 20–22 min decreasing back to 0% eluent B. The elution flow rate was 0.36 ml/min in negative mode, with an elution gradient as follows: 0–2 min 0% eluent B; 2–17 min increasing up to 100% eluent B; 17–22 min at 100% eluent B and 22–24 min decreasing back to 0% eluent B.Protein precipitation of serum samples was performed at 4 °C by adding methanol (1:4 serum: methanol) and vortexing for 120 s at 5000 rpm . The samΔM at fwhm) from 100 m/z (mass/charge ratio) to 1200 m/z, collected over 250 ms per spectrum in centroid mode. To avoid problems due to instrument drift, the sequence of samples was randomized and pooled quality-control samples (QC) were injected periodically for use in downstream data processing and correction [The UPLC was connected to the electrospray ionization (ESI) interface, operating in negative and positive modes, with a capillary voltage of − 2.5/+ 3 KV, source temperature of 150 °C, cone gas flow of 50 L/h, cone voltage of 40 V, desolvation temperature of 550 °C and desolvation gas flow of 800 L/h. The spectra were collected at high resolution  Software v4.1 and Progenesis QI . Following the manufacturer’s instructions, a reference run was automatically selected, and the precursor ion traces were processed for alignment, peak picking and normalization with default parameters. Locally estimated scatterplot smoothing (LOESS) signal correction based on QC samples was performed using MATLAB 2016 software with a script built for this purpose .Afterward, a quality assurance (QA) step was used for analytical validation: variables with unacceptable reproducibility in QC samples (RSD > 20% in QCs or detected in less than 50% of QCs) and samples (detected in less than 90% of QC) were removed from the dataset . The con2) and goodness of prediction (Q2) in cross-validation and using a permutation test with 2000 permutations [p-values were corrected for multiple tests by Significance Analysis of Microarrays (SAM-FDR) method [q-value < 0.05 were considered different between groups.Univariate and multivariate analyses were carried out using Metaboanalyst 4.0 Web Server . Glog trutations . For UA,) method . Feature2 = 0.9). Modules containing at least 20 features were retained.Network and clustering analysis were performed using the Weighted Gene Co-expression Network Analysis (WGCNA) R package , 32. NorP ≤ 0.05) were considered significant. Individual features were considered for further analysis only if they had module membership (MM) > 0.6 (P < 0.01) and gene significance (GS) > 0.5 (P < 0.05). GS is defined as the association of features with RFI, and MM is defined as the correlation of the features with the module eigengene. High GS and MM scores indicate a feature is a central element of a module and is significantly associated with the trait [To select modules associated with FE, Pearson correlations between each module’s “eigengene” and the RFI were calculated. The “eigengene” is the first principal component of a given module and a representative measure of its metabolic profile.  Modules with a module-trait relationship magnitude (correlation) > 0.5 for RFI (he trait .Bos taurus species (KEGG database) as reference [P < 0.01 were used as input to mummichog to test for pathway enrichment compared to random data resampled from the reference list, yielding an empirical p-value per pathway. Pathways with corrected q-value < 0.05 were considered significant.Metabolic pathway analysis was performed using Mummichog software 1.0.9 with eference . Using dP ≤ 0.05) for all FE traits (feed conversion ratio (FCR), RFI, residual weight gain (RWG) and residual intake and weight gain (RIG), dry matter intake (DMI)) and also for average daily gain (ADG). There was also a significant difference for backfat thickness at the end of the experiment , which were greater in the LFE group  which is greater on HFE group. No significantly different m/z were identified in negative mode.After quality assurance processing, a total of 3598 and 4210 m/z in negative and positive ionization modes, respectively, were used for parallel analyses. For Principal component analysis (PCA), no separation was observed for high and low FE animals in the first five principal components , indicating higher levels in LFE animals. The blue module contains 196 features , also indicating higher levels in LFE animals. This module contains 112 features , to improve body weight gain before slaughter. We used serum samples collected before the feedlot period to search for a potential early metabolomic signature for FE, with the intent to support nutritional management decisions to improve productivity and sustainability of livestock. Thus, we performed an exploratory analysis using untargeted metabolomics coupled with bioinformatics and interpretation tools including Mummichog and WGCNA. We found one differentially expressed feature between HFE and LFE animals in these conditions, but most importantly, we also found one enriched pathway and two sets of highly correlated features significantly associated with FE, which could be considered a potential molecular signature of FE in Nellore cattle before they enter the feedlot period.p-values  in LFE, which implies the enzymes aldehyde oxidase and retinal dehydrogenase  as probably less active/expressed in LFE animals. This result is in accordance with Zhao and colleagues  who demoProgesterone (P4) was another feature predicted in the molecular signature of FE being more present in the blood of LFE animals. Steroid hormone biosynthesis was overrepresented in the set of genes in the liver that were upregulated in the high-RFI (low FE) group of Jersey cows , which iThe stearic acid is a saturated acid (C18:0) and one of the end products of the fatty acid biosynthesis pathway in animals. This fatty acid was found increased in plasma of steers with least ADG in comparison with greatest ADG , and thiFrom all predicted molecules, Vomifoliol, 2,3 Dihydroflavone, Limonoate and Phytanic acid are molecules produced exclusively by bacteria or plants and not mammals. The higher presence of these molecules in the blood of LFE animals could be due to higher DMI of these animals in comparison with HFE animals, allowing the higher presence of these metabolites in the blood. However, this possibility lacks further evidence since we did not evaluate the pasture DMI of these animals, i.e. feed intake before they arrive at the feedlot. From these 4 molecules, the Phytanic Acid could have a role on feed efficiency. Phytanic acid is a branched-chain fatty acid formed during the metabolism of phytol  by ruminOur integrated approach using data annotation, mummichog prediction and WGCNA co-expression analyses indicated a molecular signature enriched for biological processes previously associated with FE. The metabolites in WGCNA modules were also predicted by mummichog, which supports the validity of the in silico network analysis since the two different analyses yielded consistent results. Therefore, we believe metabolomics based modules associated with FE possibly represent a molecular metabolic signature of FE. Although we have not yet been able to identify the majority of the features in those modules, previous studies on feed efficiency support the network analysis results. Moreover, we noted it is possible to have a molecular signature associated with a phenotype without knowing the function of the components, just by (for metabolites) tracking m/z ratio and retention time in a standardized assay. As an example, this is the case for commercially available genomic selection in dairy cattle using DNA markers, where the majority of the markers are not functional SNPs.In our data, we found only one feature statistically different between the FE groups: the feature with m/z 183.1670 and RT of 4.00 min (positive mode) is upregulated in HFE animals. This result along with the co-expressed module provides evidence of early serum metabolome differences between high and low FE animals. Between both the positive and negative ionization modes and after quality control-based filtering, the serum metabolome of the animals in this experiment consisted of approximately 8000 features. One may expect a priori to identify more than just one different feature between high and low FE animals using such a powerful tool. Possible explanations for this result include, but are not limited to: (1) although the groups are very distinct phenotypically at the end of the experiment, their baseline metabolic profiles may have been more similar at the time when samples were collected  ; (2) theThe conclusion from this work is the detection of a molecular signature for feed efficiency of beef cattle based on untargeted metabolomics. This molecular signature indicated the vitamin A metabolism pathway as one of the important pathways for this phenotype.Additional file 1:P < 0.05). To perform the Network analysis, the phenotype was adjusted by age, fitted as a covariate. (CSV 905 bytes)Experiment information of animals including group, birth, days of life at before feedlot (− 21 days), father, residual feed intake and residual feed intake adjusted by age as a covariate. The FE groups had different ages ; Gene significance (GS); Module Membership (MM); Feature connectivity within the module (Kwithin); Adducts; Highest abundance group; Adducts; Matched Compound (KEGG by mummichog); Mass difference between m/z and matched compound. (CSV 6 kb)Additional file 3:Important features in blue module in positive acquisition mode. Mass/charge ratio (m/z); Gene significance (GS); Module Membership (MM); Feature connectivity within the module (Kwithin); Adducts; Highest abundance group; Adducts; Matched Compound (KEGG by mummichog); Mass difference between m/z and matched compound. (CSV 3 kb)


An increasing amount of evidence supports an association between sedentary behaviors and chronic knee pain. However, the association between the total daily duration of sedentary behavior and chronic knee pain in the general population remains unclear. We aimed to analyze the association between sedentary behavior and chronic knee pain in a study population representative of the general Korean population aged > 50 years while also considering the physical activity or body mass index (BMI).This cross-sectional study used data from the 6th Korean National Health and Nutrition Examination Survey (KNHANES VI) of 2013–2015, which was completed by 22,948 Korean adult participants aged > 50 years. The participants were divided into two groups based on the status of the chronic knee pain. Data were analyzed using multivariable logistic regression after adjustment for age, sex, and individual factors.p = 0.03). Participants with high levels of physical activity were less likely to suffer from chronic knee pain , and women with over 10 daily hours of sedentary behavior with high levels of physical activity were more likely to have chronic knee pain. A significant association was noted between chronic knee pain and obesity (≥30.0 kg/m2) individuals .Longer sedentary behavior was correlated with chronic knee pain (p for trend = 0.02). Sedentary behavior exceeding 10 h/day was significantly associated with chronic knee pain (adjusted odds ratio, 1.28; Longer duration of sedentary behaviors was correlated with chronic knee pain. Our study suggests the need to encourage reductions in overall sedentary behavior to < 10 h daily. A high physical activity level is recommended, particularly for women > 50 years and those with obesity. Osteoarthritis (OA) is the most common form of arthritis and the leading cause of disability globally, with pain being the main symptom. Most adults with OA experience associated pain. Particularly, the pain associated with knee OA develops from intermittent weight-bearing pain that evolves to chronic pain . AccordiOA imposes a substantial burden on individuals and society. The burden of OA and chronic knee pain includes direct costs , indirect costs , and intangible costs  . ChronicThe etiology of chronic knee pain is multifactorial and complex, and several factors, including demographic, clinical, and psychological factors collectively contribute to its severity . In the The decline in physical activity owing to the development of personal transportation , increased accessibility to the internet, and increase in the prevalence of a sedentary lifestyle is gradually becoming a global problem . The WorSedentary behaviors are defined as activities that do not increase energy consumption much higher than those during resting . These behaviors typically include activities, such as time spent sitting or lying down during waking hours , 19. SpePhysical activity is body movement resulting in energy expenditure by skeletal muscle contraction. Physical activity includes exercise and a wide range of sports as well as all body movements that occur during daily activities . Based oThe American College of Rheumatology Work Group Panel suggested that knee osteoarthritis patients engage in moderate-intensity (50–70% maximum heart rate) exercise 3 days per week . Korea rAccording to the World Health Organization’s global recommendations on physical activity for health and Korea’s physical activity guidelines, adults aged 18–64 years and those over 65 years should complete at least 150 min of moderate-intensity aerobic physical activity per week, at least 75 min of vigorous-intensity aerobic physical activity per week, or an equivalent combination thereof , 25, 26.Older people with chronic knee pain may have lower activity levels than the general population . In the Obesity can cause various complications and reportedly influences knee pain –32. PrevThis study aimed to analyze the association between the duration of sedentary behavior and chronic knee pain in a study population representative of the general Korean population aged over 50 years while also considering physical activity and obesity.Data from Korea’s 6th National Health and Nutrition Examination Survey (KNHANES VI), 2013–2015 were used in this study. A nationwide, multistage, stratified, clustered, and random sampling method was used, which was proportionally distributed by sex, living area, and age of the Korean population.A total of 22,948 participants completed the KNHANES VI-1 (2013), VI-2 (2014), and VI-3 (2015) examinations and health surveys. The following participants were excluded: 1) those under 50 years of age and 2) those that did not respond to the chronic knee pain, sedentary behaviors, physical activity, and body mass index (BMI) surveys. Therefore, this analysis was confined to 8008 participants aged 50–89 years who answered the chronic knee pain examination survey and for whom no data regarding sedentary behaviors, physical activity, and BMI survey were missing  or yes (current smoker) based on the present smoking status. Alcohol consumption was categorized as none, < 1 drink/month, 2 drinks/month to 3 drinks/week, or ≥ 4 drinks/month. Occupations were categorized as unemployed, office work, sales and services, agriculture, forestry and fishery, or machine fitting and simple labor. Household income was categorized into low, mid-low, mid-high, and high quartiles. Educational level was categorized as ≤6 years, 7–9 years, 10–12 years, and ≥ 13 years. Sleep duration was assessed using the following question: “How many hours per day do you usually sleep?”Patients with chronic knee pain were evaluated using the following questions based on the classification criteria for idiopathic OA of the knee recommended by the American College of Rheumatology : “Have ySedentary behaviors were self-reported using the following question: How much time do you spend sitting or lying down during waking hours? The overall duration of sedentary behaviors was categorized as < 5, 5–7, 8–10, or > 10 h/day , 36.The International Physical Activity Questionnaire measures moderate- and vigorous-intensity physical activity and has tested reliability and validity with objective measurement tools . High ph2), normal weight (18.5–24.9 kg/m2), overweight (25.0–29.9 kg/m2), and obesity (≥30.0 kg/m2) [BMI was categorized into underweight (< 18.5 kg/m0 kg/m2) .All statistical analyses were performed using SAS version 9.4  and consisted of complex sample analysis–stratified cluster sampling with weighted samples.p values of all analyses performed in this study were two-tailed with a significance level of < 0.05.General characteristics were compared between participants with and without chronic knee pain using Student’s t-test and Chi-square test. The latter was used to examine the likelihood associated with chronic knee pain. Furthermore, to identify factors associated with chronic knee pain, odds ratios (ORs) and 95% confidence intervals (CIs) were calculated through multivariable logistic regression analysis after setting chronic knee pain as the dependent variable and sedentary behaviors as the main independent variable with control for sociodemographic, lifestyle, and health factors. The association between sedentary behavior and chronic knee pain was analyzed using subgroups based on sex, physical activity and BMI. The p < 0.0001). The low PA group (22.6%) had a higher prevalence of chronic knee pain than the high PA group (17.2%) (p < 0.0001). Participants with chronic knee pain demonstrated longer hours of daily sedentary behavior (6.9 ± 3.8 h) than those without chronic knee pain (6.5 ± 3.6 h) (p < 0.0001).The characteristics of the study population from the survey with and without chronic knee pain are shown in Table 2) were older than those in the group without chronic knee pain (24.0 ± 3.1 kg/m2) (p < 0.0001). In the chronic knee pain group, the prevalence of obesity (30 kg/m2) was the highest at 32.4%, followed by overweight (25.0–29.9 kg/m2) (p < 0.0001).The mean age of the BMI in the group with chronic knee pain . Among women participants, a significant association between chronic knee pain and > 10 h/day of sedentary behavior was seen . The ORs of chronic knee pain for > 10 h/day of sedentary behaviors were 1.56  for unadjusted model and 1.33  for Model 2. Regarding the p-value for trend, the ORs for chronic knee pain increased with increase in the level of sedentary behavior in unadjusted model (p = 0.00) and in Model 2 (p = 0.02). Among men, there was no significant association between chronic knee pain and level of sedentary behavior.Overall, the ORs of chronic knee pain for participants with > 10 h/day of sedentary behaviors was 1.28  for unadjusted and 1.28  for Model 2, showing a significant association between chronic knee pain and sedentary behavior of > 10 h/day . A significant association was noted between chronic knee pain and high physical activity  among men participants. The ORs of chronic knee pain for high physical activity were 0.68  for unadjusted model and 0.70  for Model 1. Women participants showed a significant association between chronic knee pain and physical activity . The ORs of chronic knee pain for high physical activity were 0.69  for unadjusted model and 0.84  for Model 1. However, the associations for total, men, and women participants in the full adjusted model 2 were not significant.Overall, the ORs of chronic knee pain for high physical activity were 0.64  for unadjusted model and 0.78  for Model 1. In the total population, a significant association was noted between chronic knee pain and high physical activity (Table 2) were 1.79  and 1.86  for Model 1 and Model 2, respectively. A significant association between chronic knee pain and overweight (25.0–29.9 kg/m2)  was noted. The ORs of chronic knee pain and obesity (≥30.0 kg/m2) were 2.44  for unadjusted model, 2.64  for model 1, and 2.45 (1.43–4.21) for Model 2. A significant association was noted between chronic knee pain and obesity (≥30.0 kg/m2) . In p for trend, the chronic knee pain correlated with BMI in unadjusted model , Model 1  and in Model 2 .Overall, the ORs of chronic knee pain and overweight (25.0–29.9 kg/m2) (p = 0.04). The ORs of chronic knee pain for obesity (≥30.0 kg/m2) were 3.17  for Model 1 and 3.48  for Model 2. Among the women participants, a significant association was noted between chronic knee pain and obesity (≥30.0 kg/m2). The ORs of chronic knee pain for obesity were 1.97  for unadjusted model, 2.36  for Model 1, and 2.01  for Model 2. Further, the women participants showed a significant association between chronic knee pain and BMI . In p for trend, chronic knee pain was correlated to BMI in unadjusted model , Model 1  and Model 2 .Among men participants, a significant association was noted between chronic knee pain and obesity . The OR of chronic knee pain for high levels of physical activity was 1.33  in Model 3. In p for trend, chronic knee pain correlated with sedentary behaviors at high physical activity in unadjusted model  and Model 1 .In the subgroup analysis, the association between chronic knee pain and sedentary behaviors based on high physical activity and sex was analyzed in more detail using multivariable logistic regression . The ORs of chronic knee pain for high physical activity was 1.37  in Model 1. Meanwhile, women showed no statistically significant differences between sedentary behavior and chronic pain when overweight or obesity. Men participants also showed no statistically significant differences between sedentary behavior and chronic pain with normal weight or overweight. In obesity men participants, statistical analysis could not be performed owing to lack of numbers.In subgroup analysis, the association between chronic knee pain and sedentary behaviors by BMI and sex was analyzed in further detail using multivariable logistic regression  was associated with chronic knee pain among women.A previous study that analyzed data from the KNHANES in 2010–2012 reported that age, women sex, lower education level, obesity, and depression were risk factors for knee pain in adults > 50 years of age . This isKnee joints can become stiff while getting out of bed in the morning or after long periods of sitting . OA painAn earlier clinical study examined the correlation between longer sedentary behaviors and arthritis among obesity men participants and found that longer periods of sedentary behaviors gradually resulted in weakness of the quadriceps muscle, resulting in wear and tear in the area below the patella, causing pain . In one Promotion of health among the elderly by emphasizing on moderate-intensity aerobic and muscle strengthening activities and by reducing sedentary behaviors is encouraged based on the recommendations of the American College of Sports Medicine and American Heart Association . This isThis study had a number of advantages. First, it was based on the reliable data obtained from the Korean government agencies from questionnaires completed by a sample representative of the general Korean population. Second, this was the first study to investigate the relationship between sedentary behaviors and chronic knee pain based on levels of physical activity or BMI. Third, individuals in East Asia, including Korea, commonly sit on the floor in a crossed-leg or kneeling posture; therefore, research investigating the effect of sedentary behaviors on knee pain is important.There were some limitations to our research. First, this study used a cross-sectional design to analyze a sample of the general population. Therefore, a causal relationship could not be explored. However, this study aimed to observe the general population in Korea. Sampling error was minimized using a clustering multistage random sampling method. Second, the brief questionnaire used in this study to evaluate chronic knee pain did not describe its severity, source, or duration, probably by using a pain measurement tool with a scale . Third, the relationship between sedentary behaviors and chronic knee pain determined here was dependent on ethnicity. The KNHANES is a nationwide survey targeting the general public in Korea. Therefore, as our findings are representative of the general Korean population, extrapolating our results to other populations may not be valid. Fourth, the confounders  used in this study did not significantly influence chronic knee pain; thus, they were used only as control variables. We did not identify the multicollinearity statistically because the confounders used in this study were considered to have little influence on chronic knee pain , 10, 45.In conclusion, sedentary behaviors are significantly positively correlated with chronic knee pain. Obesity individuals with low physical activity and longer sedentary behaviors are more likely to suffer from chronic knee pain. However, among women participants who demonstrated high levels of physical activity, being sedentary for more than 10 h was more likely to cause chronic knee pain. Thus, the findings of our population-based study suggest that reductions in overall sedentary behaviors should be encouraged, particularly among individuals with chronic knee pain. High levels of physical activity are, particularly for women > 50 years old and those with obesity.Additional file 1: Table S1. Association between sedentary behaviors and chronic knee pain according to high physical activity using multivariable logistic regression by sex.Additional file 2: Table S2. Association between sedentary behaviors and chronic knee pain according to BMI using multiple logistic regression by sex.


Pleural infection managed with intrapleural therapy using a combination of 10 mg of tissue plasminogen activator (tPA) and 5 mg of deoxyribonuclease (DNase) has been shown in randomized and open‐label studies to successfully treat >90% of patients without resorting to surgery. Potential bleeding risks, although low, and costs associated with tPA remain important concerns. No phase I studies exist for intrapleural tPA therapy and the lowest effective dose has not been established. In patients with high bleeding risks, lower doses may present a safer alternative. We report a case of a complex parapneumonic effusion in a patient with coagulopathy that was successfully treated with a very low dose tPA (1 mg) and DNase (5 mg) regime. Pleural infection is common. Intrapleural therapy with tissue plasminogen activator tPA; 10 mg) and deoxyribonuclease  has been shown to successfully treat up to 96% of patients without needing surgery 0 mg and Finding a lowest effective dose of tPA/DNase is especially beneficial in patients with high bleeding risks (e.g. coagulopathy) who need pleural drainage. We report the successful use of 1 mg tPA with 5 mg DNase in a patient with coagulopathy.9/L and C‐reactive protein (CRP) 420 mg/L). Baseline blood tests revealed deranged liver function  and gamma‐glutamyl transferase = 78 U/L ). She was coagulopathic  of 44.4 s and international normalized ratio (INR) of 1.8). Chest X‐ray (CXR) and computed tomography (CT) of the chest demonstrated left‐sided consolidation complicated by a small loculated pleural effusion , tachypnoeic and hypoxic but haemodynamically stable. Her inflammatory markers were raised  in blood cultures. There was initial improvement in symptoms, fever, oxygen saturations, and inflammatory markers (CRP decreased to 36 mg/L by day 5). She was also a subject of a double‐blinded randomized trial and received either i.v. dexamethasone or placebo for 48 h on days 2 and 3. The pleural effusion was not drained because of good clinical response, its small size and the coagulopathy, which persisted despite administration of two doses of i.v. vitamin K 10 mg.She was initially managed with intravenous (i.v.) ceftriaxone 2 g plus azithromycin 500 mg daily. This regime was then changed to i.v. benzylpenicillin 1.8 g 4‐hourly plus clindamycin 600 mg 8‐hourly on day 2 upon identification of However, she deteriorated and became febrile again at day 6 and her CRP rose to 130 mg/L. Repeat imaging showed a worsening loculated pleural effusion, particularly at the lung apex  and CXR Fig. E confirmThe patient had significant clinical, radiological, and serological response to the 1 mg tPA/5 mg DNase regime. The volume of pleural fluid drained in the 72 h preceding fibrinolytic treatment was 175 mL and increased to 675 mL in the first 24 h of tPA/DNase treatment and 1450 mL after five doses of tPA/DNase. She was afebrile and her CRP decreased to 49 mg/L. TUS and CXR showed radiological resolution of the pleural effusion and her ICC was subsequently removed  administered twice daily for the treatment of pleural infection can be considered in high‐risk subjects.Appropriate written informed consent was obtained for publication of this case report and accompanying images. Professor Lee is a National Health & Medical Research Council Career Development Fellow and has received research project grant funding from iCare Dust Disease Authority, Sir Charles Gairdner Research Advisory Committee, Cancer Australia, and the Cancer Council of Western Australia.


Hypertensive disorders of pregnancy (HDP) are characterized by hemodynamic disturbances. Altered thyroid function is a risk factor for poor outcomes of pregnancy. However, the associations between thyroid function biomarkers and maternal hemodynamics during pregnancy in HDP remain unclear.From January 2016 to January 2018, pregnant women diagnosed with HDP admitted to the Nanjing Maternity and Child Health Care Hospital were prospectively enrolled in the third trimester. Normally distributed variables were expressed as mean ± standard deviation and skewed variables were expressed as median . Correlations between thyroid-stimulating hormone (TSH) or free thyroxine (FT4) and maternal hemodynamic parameters were assessed by Pearson’s correlation coefficient and 95% confidence interval (95%CI). Bonferroni’s correction for multiple correlations was performed. Logistic regression models with odd ratio (OR) and 95%CI were applied to confirm the associations.p = 0.002). Reduced cardiac output (CO) was defined as CO < 3.5 L/min. The infant birth weight of patients with reduced CO was lower than that of patients with normal CO . TSH levels were significantly and negatively correlated with CO . FT4 levels were not significantly correlated with any of the maternal hemodynamic parameters . TSH level  was confirmed associated with reduced CO in the logistic regression analysis.A total of 163 third-trimester pregnant women with HDP with a mean gestational age of 35.62 ± 2.83 weeks were recruited. The infant birth weight of patients with elevated TSH levels was lower than that of patients with normal TSH levels (2635 ± 867 g vs. 3037 ± 673 g, Elevated TSH levels are associated with reduced CO in HDP during the third trimester. Hypertensive disorders of pregnancy (HDP) are common complications during pregnancy, with incidence rates of approximately 2–8% , 2, and Maternal hemodynamic alterations occur in pregnant women with HDP , 11. As Thyroid dysfunction frequently occurs during pregnancy . Both hyFrom January 2016 to January 2018, pregnant women with HDP who were admitted to the Nanjing Maternity and Child Health Care Hospital were prospectively enrolled in the third trimester. Data were analyzed retrospectively from our prospectively collected dataset. The diagnostic criterion for HDP was an increase in blood pressure to ≥140/90 mmHg after 20 gestational weeks in previously normotensive women . The ele5.We applied a noninvasive hemodynamic monitoring technique with electronic impedance cardiography  to analyze the circulatory function of HDP patients at enrollment. Electronic impedance cardiography is widely used and enables clinicians to quickly and easily observe the cardiac function and peripheral resistance of patients. The performance of electronic impedance cardiography in pregnancy was validated previously , and theFasting maternal venous blood samples were obtained on the day of electronic impedance cardiography monitoring. Samples were centrifuged, and supernatants were stored at − 80 °C. TSH was measured using an Elecsys-TSH kit . FT4 was measured using an FT4 Flex reagent . Thyroid peroxidase antibody was measured with an E-Anti-TPO kit  and was graded as positive when greater than 60 IU/ml. The normal reference for TSH in the third trimester was 0.3 to 3.5 mIU/L, as recommended .The demographic information of the patients included age, body mass index  before pregnancy, gravidity, parity, gestational age at enrollment and complications of PE. The diagnostic criterion for PE was the presence of HDP with urinary protein above 300 mg/24 h . Laborat2 -test). Correlations between thyroid function biomarkers and maternal hemodynamic parameters were assessed with Pearson’s correlation coefficient and 95% confidence interval (95%CI). Bonferroni’s correction for multiple correlations was performed. The maternal hemodynamic parameters that had significant correlations with thyroid function biomarkers per Pearson’s correlation coefficient were stratified for logistic regression, and thyroid function biomarkers were plotted into univariate and multivariate regression models (per the stepwise method) with odd ratio (OR) and 95%CI to confirm the associations. A two-sided p < 0.05 was considered statistically significant.Data were analyzed by SPSS version 20.0  and MedCalc Statistical Software version 15.2.2 . Normally distributed continuous variables were expressed as the means± standard deviations, skewed data were expressed as medians , and the data were analyzed by independent Student’s t-test and the Mann-Whitney U test, respectively. Categorical variables were expressed as frequencies and proportions, and they were analyzed with the chi-square test (χp = 0.013). There were 71 patients with TSH levels above 3.5 mIU/L. The birth weights of the infants of the patients with normal TSH levels and elevated TSH levels were 3037 ± 673 g and 2635 ± 867 g, respectively (p = 0.002) and the proportions of low-birth-weight infants were 15.2 and 49.3%, respectively (p < 0.001).The present study consisted of 163 pregnant women with a clear diagnosis of HDP. All patients were enrolled in the third trimester with a mean gestational age of 35.62 ± 2.83 weeks. The mean levels of TSH and FT4 were 3.67 ± 2.21 mIU/L and 11.58 ± 2.15 pmol/L, respectively (Table p = 0.039), indicating that systemic vascular resistance increased with increasing TSH levels. After adjustments for multiple correlations by Bonferroni’s correction, only CO was significantly correlated with TSH. The TSH level was not correlated with other maternal hemodynamic parameters . The FT4 level was not significantly correlated with any of the maternal hemodynamic parameters . The 95%CI for the r values were shown in Table The TSH level was significantly and negatively correlated with CO , indicating that cardiac output decreased with increasing TSH levels. The TSH level was significantly and positively correlated with SVR , complications of PE (p = 0.044), GFR (p = 0.049), albumin level (p = 0.033) and TSH level (p < 0.001) were significantly different between the CO normal and CO reduction groups  was confirmed to be significantly associated with CO reduction. (Table According to the electronic impedance cardiography machine instructions for pregnancy, women with CO < 3.5 L/min were categorized as the CO reduction group. BMI before pregnancy ( p < 0.00 were sigThis observation demonstrated that elevated TSH levels were associated with reduced cardiac output in pregnant women with HDP in the third trimester.Previous findings suggested that both overt and subclinical hypothyroidism during pregnancy are associated with a negative gestational prognosis, including the occurrence of gestation induced hypertension and PE, spontaneous abortion, premature delivery, fetal distress, fetal growth restriction and fetal death , 22, 23.Thyroid dysfunction is closely correlated with cardiovascular disorders in the general population , 27. Li In the present study, TSH levels were significantly and negatively correlated with CO. These results indicated that cardiac output in HDP declined with the elevation in serum TSH during the third trimester. The physiological adaptation of the cardiovascular system in normal pregnancy was characterized by a significant increase in CO , 36, whiThere were several limitations in the present research. First, this study contained a small sample size and was based on a single-center design assessing a Chinese population. Multi-center investigations containing larger sample sizes should be conducted further. Second, the patients in the present study were enrolled during the third trimester, and the conclusions are limited to this trimester. Studies on longitudinal changes in TSH and hemodynamics are warranted in the future. Third, this study lacked a comparison with normotensive pregnancies. It was unclear whether this association existed regardless of whether a woman had a hypertensive pregnancy.The research revealed that pregnancies with elevated TSH levels and reduced CO have higher rates of low-birth-weight infants. Elevated TSH levels were associated with reduced CO in HDP women during the third trimester of pregnancy. The co-existing correlation between elevated TSH level and reduced CO may provide new insight into the underlying mechanism of the linkage between hypothyroidism in pregnancy and FGR or low birth weight in HDP patients. Mechanisms of the associations between TSH and reduced CO warrants future investigation.Additional file 1: Table S1. Comparison of baseline characteristics between normal CO and reduced CO groups.


Treatment with intravenous paracetamol may impair hemodynamics in critically ill adults. Few data are available in children. The aim of this study was to investigate the frequency, extent, and risk factors of hypotension following intravenous paracetamol administration in children with septic shock on inotropic support.We retrospectively reviewed the electronic medical charts of all children aged 1 month to 18 years with septic shock who were treated with intravenous paracetamol while on inotropic support at the critical care unit of a tertiary pediatric medical center in 2013–2018. Data were collected on patient demographics, underlying disease, Pediatric Logistic Organ Dysfunction (PELOD) score, hemodynamic parameters before and up to 120 min after paracetamol administration, and need for inotropic support or intravenous fluid bolus. The main outcome measures were a change in blood pressure, hypotension, and hypotension requiring intervention.p = 0.002). Systolic blood pressure decreased at 30, 60, 90, and 120 min after delivery of 50, 67, 61, and 59 drug doses, respectively. There were 5 events of systolic hypotension . Mean arterial pressure decreased by ≥ 15% in 8 drug doses at 30 min , 18 doses at 60 min , 16 doses at 90 min , and 17 doses at 120 min . Mean arterial hypotension occurred at the respective time points in 2, 13, 10, and 9 drug doses. After 12 drug doses (11.4%), patients required an inotropic dose increment or fluid bolus.The cohort included 45 children of mean age 8.9 ± 5.1 years. The mean inotropic support score was 12.1 ± 9.5. A total of 105 doses of paracetamol were administered. The lowest mean systolic pressure (108 ± 15 mmHg) was recorded at 60 min (Hypotensive events are not uncommon in critically ill children on inotropic support treated with intravenous paracetamol, and physicians should be alert to their occurrence and the need for intervention. Paracetamol was introduced in the late nineteenth century and is currently one of the most common antipyretic, analgesic drugs used worldwide. The mechanism of action of paracetamol is unclear and may involve inhibition of the cyclooxygenase, cannabinoid, or nitric oxide pathways in the central nervous system . PerfalgComplementary data in the pediatric medical literature are sparse. A case report by Yaman et al.  describeThe aim of the present study was to evaluate the frequency, extent, and risk factors of hypotension associated with intravenous administration of paracetamol in children with septic shock supported with inotropic drugs.A retrospective chart review study design was used. The study was approved by the institutional review board. The cohort included all children hospitalized in the pediatric intensive care unit (PICU) of a tertiary pediatric medical center in 2013–2018 with septic shock  who wereiMDsoft, Tel Aviv, Israel). For the present study, the following data were collected from the medical charts: patient age and sex; underlying disease; amount of sedative drugs; Pediatric Logistic Organ Dysfunction (PELOD) score; hemodynamic parameters  immediately before paracetamol administration and 30, 60, 90, and 120 min after; and need for inotropic support or intravenous fluid bolus during the 4 h before and 2 h after paracetamol administration. The main outcome measures of the study were change in blood pressure, hypotension, and hypotension requiring intervention.All patient parameters at our center are continuously and automatically recorded in the individual electronic charts  vital signs chart . As for In addition, we calculated the differences between the systolic and diastolic blood pressure values and the respective normal means for age expressed as delta (Δ). A negative change of ≥ 15% in MAP after intravenous paracetamol administration was also evaluated, similar to previous studies , 9. Tempp value of < 0.05 was considered statistically significant.Statistical analysis was performed with ©2018 QuickCalcs software . Changes in blood pressures, heart rates, and VIS were analyzed using analysis of variance (ANOVA) with repeated measures. Potential baseline factors predicting a risk of hypotension after paracetamol treatment were tested by ANOVA. For all tests, a The cohort included 45 children who received a total of 105 intravenous paracetamol prescriptions (3 prescriptions were included in our earlier study of paracetamol ). Their p < 0.001). In 83 cases, patients were being mechanically ventilated at the time paracetamol was prescribed. Three children did not survive to pediatric intensive care unit discharge.The mean dose of intravenous paracetamol was 12 ± 3 mg/kg. The indications for treatment were fever in 83 (79%) prescriptions and pain in 22. Paracetamol treatment led to a decrease in mean temperature from 38.6 ± 0.6 to 37.5 ± 0.8 °C . The lowest systolic blood pressure value was 8 ± 17 mmHg higher than the lower limit of normal systolic blood pressure, adjusted for age. There was no statistically significant change in diastolic blood pressure (Table p < 0.001) than the pre-paracetamol value.For the whole cohort, mean systolic blood pressure before paracetamol administration was 113 ± 15 mmHg, and the lowest value after paracetamol administration was 108 ± 15 mmHg at 60 min. The difference between these values was statistically significant p = 0.00. The lowThere was no statistically significant change in VIS before and after paracetamol administration Table .MAP decreased by ≥ 15% from the pre-paracetamol value in 8 doses (7.6%) at 30 min (mean drop − 19 ± 4 mmHg), 18 doses (17.1%) at 60 min (mean drop − 20 ± 7 mmHg), 16 doses (15.2%) at 90 min (mean drop − 20 ± 5 mmHg), and 17 doses (16.2%) at 120 min (mean drop − 19 ± 5 mmHg). Mean arterial hypotension occurred after 34 doses of paracetamol (32.4%); in 23 doses, hypotension was recorded at 60 and 90 min after paracetamol infusion , and another 6 required fluid boluses to maintain systolic blood pressure or MAP within the normal range. Figure p = 0.49, ANOVA). Similarly, no statistically significant association was found between a drop in MAP to below normal and patient diagnosis  (p = 0.52), amount of sedative drugs , or indication (fever/pain) for paracetamol administration (p = 0.89). On stepwise logistic regression analysis, there was no association between these three variables  and a drop in MAP to below normal.There was no statistically significant association between baseline VIS and a decrease in MAP below the normal range , and warranting intervention in 12 patients in the form of a fluid bolus or an increment in inotropic support. Among patients who experienced a decrease in systolic blood pressure after intravenous paracetamol, the highest number of negative events occurred at 60 min (67 events), with a decrease of − 15 ± 12 mmHg from the mean pre-paracetamol value.The hypotensive effect of intravenous paracetamol is multifactorial and well recognized in the adult literature. More than 20 years ago, Brown  describeKelly et al.  reportedIn children with septic shock, two possible mechanisms may exaggerate the hypotensive effect of paracetamol. One is skin vasodilatation. Owing to the higher ratio of surface area to weight than in adults, skin vasodilatation occurring when temperature drops may exaggerate relative hypovolemia and facilitate hypotension. The other is the additive lowering effect of paracetamol on the already low cardiac output and myocardial depression characteristic of pediatric septic shock.Ray et al.  reportedHowever, since MAP and heart rate would be expected to decrease to normal range on relief of fever and discomfort, the definition of hypotension as a decrease of > 15% mmHg in MAP can be misleading. Therefore, to identify true hypotension, we not only presented the negative changes in systolic and diastolic blood pressures and MAP after intravenous paracetamol, but also calculated the difference (Δ) in the post-paracetamol values from the lower normal range and hypotensive limit for age. We found that despite the drop in mean systolic blood pressure, the mean difference from the systolic hypotensive value was in the safe range, and only 5 events were by definition systolic hypotension. Furthermore, in only 34 of the 59 events in which MAP decreased by ≥ 15% relative to baseline, MAP was below the normal age-adjusted value. Thus, we suggest that rather than defining hypotensive events after paracetamol administration by the change from baseline, we should consider the change in blood pressure values  relative to the normal range. Furthermore, since sedated children may experience low blood pressures, we suggest that low blood pressure together with the need for intervention is more clinically relevant than the change in pressure per se.The present findings do not agree with our recently published study of 100 consecutive children treated with intravenous paracetamol , whereinNone of the potential risk factors evaluated in this study, i.e., baseline VIS, underlying diagnosis, sedative drugs, and indication for paracetamol administration, was associated with the development of hypotension after intravenous administration of paracetamol.Our study has several limitations. First, although the data had been recorded electronically and continuously, they were collected retrospectively. Second, patients who received known hypotensive medications were excluded, but it is still possible that some patients experienced an unexpected hypotension event in response to some other medication that was given at the time of paracetamol administration. There are also other potential causes of hypotension in this setting, such as are unmet ongoing fluid loss and septic shock deterioration. Third, the cohort was relatively small, with some patients had more than one dose of paracetamol, and was not powered to identify all risk factors for hypotensive events after treatment.Clinicians should be alert to the occurrence of hypotensive events and the need for intervention following intravenous paracetamol administration in critically ill children with septic shock on inotropic support. Future prospective controlled studies are warranted to investigate below-normal blood pressures and the need to intervene and to further characterize the mechanisms and risk factors of paracetamol-induced hypotension in this patient group.


Common facial expressions of emotion have distinctive patterns of facial muscle movements that are culturally similar among humans, and perceiving these expressions is associated with stereotypical gaze allocation at local facial regions that are characteristic for each expression, such as eyes in angry faces. It is, however, unclear to what extent this ‘universality’ view can be extended to process heterospecific facial expressions, and how ‘social learning’ process contributes to heterospecific expression perception. In this eye-tracking study, we examined face-viewing gaze allocation of human (including dog owners and non-dog owners) and monkey observers while exploring expressive human, chimpanzee, monkey and dog faces . Human observers showed species- and experience-dependent expression categorization accuracy. Furthermore, both human and monkey observers demonstrated different face-viewing gaze distributions which were also species dependent. Specifically, humans predominately attended at human eyes but animal mouth when judging facial expressions. Monkeys’ gaze distributions in exploring human and monkey faces were qualitatively different from exploring chimpanzee and dog faces. Interestingly, the gaze behaviour of both human and monkey observers were further affected by their prior experience of the viewed species. It seems that facial expression processing is species dependent, and social learning may play a significant role in discriminating even rudimentary types of heterospecific expressions. It is plausible that both the “universality” and “social leaning” processes could be reduced in perceiving heterospecific facial expressions as they are less biologically relevant to the viewers. To maximally promote and also distinguish between these two processes, we only presented the very basic high-intensity angry and happy conspecific and heterospecific facial expressions, as these expressions are likely to be homologous in morphological features and social functions across the presented species . In contrast, the “social learning” process would predict an experience-dependent expression categorization accuracy in human viewers , and a species-dependent face-viewing gaze distribution in both human and monkey viewers .Fifty-six Caucasian undergraduate participants , age ranging from 18 to 26 years with a mean of 19.88 ± 1.27 (mean ± SD), volunteered to participate in this study conducted at the University of Lincoln. This sample size was determined based on previous research in the same field and was comparable to the published reports  with the resolution of 1024 × 768 pixels. At a viewing distance of 57 cm, the monitor subtended a visual angle of 40 × 30°.Digitized greyscale face images were presented through a ViSaGe graphics system  and displayed on a high-frequency non-interlaced gamma-corrected colour monitor (30 cd/mPan troglodytes) faces, 12 monkey (9 Rhesus macaques and 3 Japanese macaques) faces and 18 dog (Canis familiaris) faces. Human faces were selected from the “Pictures of Facial Affect”  was displayed randomly at one of nine positions (3 × 3 matrix) across the monitor. The distance between adjacent FP positions was 10°. The participant was instructed to follow the FP and maintain fixation for 1 s. After the calibration procedure, the participant pressed the response box to initiate a trial. The trial was started with an FP displayed 10° left or right to the screen centre to minimize central fixation bias  were measured using a Video Eyetracker Toolbox  with 250 Hz sampling frequency and up to 0.25° accuracy . The software developed in Matlab computed horizontal and vertical eye displacement signals as a function of time to determine eye velocity and position. Fixations were then extracted from the raw eye-tracking data using velocity (less than 0.2° eye displacement at a velocity of less than 20°/s) and duration (greater than 50 ms) criteria , a consistent criterion was adopted to define boundaries between local facial features for different faces  analysis with expression categorization accuracy as the dependent variable. Only significant main and interaction effect was reported.F = 65.57, p < 0.001, ηp2 = 0.27; expression type: F = 88.29, p < 0.001, ηp2 = 0.25; face species × expression type: F = 41.36, p < 0.001, ηp2= 0.24; Fig. ps < 0.001) and indistinguishable categorization performance for chimpanzee and monkey faces . For negative expressions, they showed the highest categorization performance for dog and human faces , followed by chimpanzee faces (CN: 73% ± 2), and then by monkey faces .Regardless of dog ownership, human facial expression categorization performance varied according to the viewed face species and facial expressions , dog owners were more accurate in detecting dog negative or positive expressions than non-owners . There was no correlation between the length of dog ownership and owners’ categorization performance for dog expressions , probably due to their ceiling level of expression categorization accuracy.Although dog ownership did not show significant impact on overall expression recognition accuracy . Specifically, when viewing human faces, human viewers tended to direct the highest proportion of fixations at the eyes (46–50%), followed by the nose (25–30%) and then by the mouth (13–18%) irrespective of the viewed expressions  that was higher than those attracted by dog mouth .A GLM analysis with proportion of fixations directed at each face region as the dependent variable was then conducted to quantitatively compare fixation distribution across different face image categories. Although dog ownership had no direct impact on gaze distribution in judging human, chimpanzee, monkey and dog facial expressions . The monkey was required to follow the FP and maintain fixation for 1 s. After the calibration, a trial was started with an FP displayed 10° left or right to the screen centre. If the monkey maintained fixation for 1 s, the FP disappeared and an image was presented for 5 s. Unlike human viewers showing concentrated gaze allocation at the presented image, monkey viewers frequently gazed at regions outside of the screen during the image presentation. To ensure a sufficient image-viewing time for monkey viewers which was comparable to human viewers, we adopted longer image presentation duration for monkeys (5 s for monkeys vs 3 s for humans). During the free-viewing image presentation, monkeys passively viewed the images with an average image-viewing time of 3.5 s per trial. The inter-trial interval was 1 s within which monkeys received a juice reward without any specific task requirement related to the stimuli. Each monkey was tested for two identical sessions (60 images per session) separated by at least 48 h. The same eye movement analysis protocol was used for both monkey and human participants.The presented face images were identical to those described in Experiment 1. During the recording, monkeys were seated in a primate chair with their head restrained, and viewed the display binocularly. Their horizontal and vertical eye positions were measured by EyeLink 1000 (SR Research Ltd) with 500 Hz sampling frequency, 0.25–0.5° accuracy and 0.01° root-mean-square resolution. During the calibration of eye movement signals, a small FP  = 0.42, p = 0.74, ηp2 = 0.02; expression type: F = 0.88, p = 0.42, ηp2 = 0.03; face species × expression type: F = 0.53, p = .72, ηp2= 0.03]. In agreement with previous observation  , indicating that rhesus macaques showed the same gaze behaviour in viewing of rhesus macaque and Japanese macaque facial expressions.It should be noted that in this study the monkey viewers were rhesus macaques, but the presented monkey faces were from both rhesus and Japanese macaques. To check whether these mixed monkey face stimuli would affect our findings shown in Fig. F = 82.23, p < 0.001, ηp2 = 0.04]. To present these findings informatively, for each face species and facial expression we subtracted the averaged and normalized monkey gaze allocation at a given face region from the averaged and normalized human gaze allocation at the same face region  except for the eyes in aggressive monkey faces (p = 0.46), at the nose (6–16% more) in the majority of faces  except for the nose in relaxed human (p = 0.24) and chimpanzee faces (p = 0.65), and at the mouth (7–21% more) in all expressive faces regardless of face species . Monkeys, on the other hand, only looked more often (6–8% more) at the mouth in relaxed human, monkey and dog faces . Interestingly, these differences, especially in gaze allocation at the mouth region, were affected more by the viewed facial expressions than by the viewed face species. In comparison with monkeys, humans directed similar or less amount of fixations at the mouth in relaxed faces, but higher proportion of fixations at the mouth in expressive faces irrespective of the viewed face species.As shown in Fig. Clearly, the viewed face species and facial expressions significantly modulated face-viewing gaze distribution for both human and monkey viewers. For instance, in comparison with human faces, expressive  non-human faces tended to attract fewer fixations at the eyes, but more fixations at the mouth from human viewers. As the same facial feature in faces of different species and/or different expressions varies in size  and low-level image salience, such as feature structure, shape, luminance intensity and contrast in local image region , it is plausible that these changes of facial feature size and local image saliency could (at least partly) account for the observed differences in gaze allocation at a given facial feature. We examined this possibility by computing and comparing local facial feature size and local image saliency in the eyes, nose and mouth across face image categories.http://ilab.usc.edu). The model compares local image intensity, colour and orientation, combines them into a single salience map with a winner-take-all network and inhibition-of-return, and then produces a sequence of predicted fixations that scan the whole face in order of decreasing salience. We calculated the top nine salient regions within each face image because our human and monkey viewers on average made 8.5 fixations per image in face viewing. The number of predicted fixations at the eyes, nose and mouth was then normalized to the total number of predicted fixations in that face.For each of the face images used in this study, we first measured the proportion of the area of each facial feature  relative to the whole image. Its local image saliency was then computed in Matlab using the most widely used computational salience model of Itti and Koch , with thF = 48.54, p < 0.001, ηp2 = 0.50; expression type: F = 0.42, p = 0.66, ηp2 = 0.01; face region: F = 71.05, p < 0.001, ηp2 = 0.49; face species × expression type × face region: F = 3.26, p = 0.002, ηp2= 0.15]. Specifically, the average facial feature size in chimpanzee and monkey faces was slightly larger than in human and dog faces . Animals also tended to have larger mouth than humans , and displaying expression could further enlarge the mouth in animal faces which was proportionally significantly larger than the mouth in expressive human faces .As shown in Fig. F = 3.88, p = 0.01, ηp2 = 0.07; expression type: F = 14.59, p < 0.001, ηp2 = 0.16; face region: F = 40.34, p < 0.001, ηp2 = 0.35; face species × expression type × face region: F = 6.12, p = 0.002, ηp2= 0.15]. For instance, the local image saliency around the mouth in expressive non-human faces was significantly higher than those in human faces . Furthermore, facial feature size and its local image saliency tended to be correlated, in which larger facial features were normally associated with higher number of predicted fixations .The computed local image saliency of different face regions also varied significantly according to the face species and facial expressions  and monkey viewers , suggesting the face-viewing gaze allocation in human and monkey viewers was not entirely driven by facial feature size and local image saliency. For instance, irrespective of the viewed face species and facial expressions, the relatively small eye region attracted substantially more actual fixations, especially from human viewers, than predicted . However, the quantitative changes of the proportion of actual fixations at the mouth in expressive  faces across different non-human face species showed similar trend as the changes in the mouth size and those predicted by the computational visual saliency model . In comparison with the amount of fixations at the human mouth, it seems that the increased fixations at the expressive non-human animal mouth could be largely accounted for by the changes of mouth size and local image salience  between humans and non-human animals.The comparison between the predicted Fig.  and actuIn this comparative investigation about whether the same cognitive process is used to perceive basic heterospecific facial expressions in human and monkey viewers, we presented human, chimpanzee, monkey and dog faces displaying positive (happy/playful), relaxed  and negative (angry/threatening) expressions. Human viewers showed species- and experience-dependent expression categorization accuracy. Regarding face-viewing gaze behaviour, humans and monkeys often demonstrated different gaze distribution when exploring the same face images, and the viewed face species and facial expressions could further modify their gaze allocation at the eyes, nose and mouth regions. Interestingly, such modulation of gaze behaviour was further affected by their prior experience of the viewed species. It seems that facial expression processing is species dependent, and social learning may play a significant role in discriminating even rudimentary types of heterospecific expressions.When free labelling the perceived expressions, human viewers showed differential categorization performance for the most common types of facial expressions displayed by different species. They had the highest categorization accuracy for human faces, followed by dog and chimpanzee faces, and then by monkey faces Fig. . It seemInterestingly, humans’ expression categorization bias was also modulated by experience. When confused with relaxed faces of different species, they tended to mislabel familiar human and dog relaxed expressions as sad, but less familiar chimpanzee and monkey relaxed expressions as sad and happy.Regarding gaze pattern associated with facial expression categorization, the viewed face species (human vs non-human faces) and expressions (relaxed vs expressive faces) had evident modulatory effect on humans’ face-viewing gaze allocation. In agreement with previous report that human spontaneous gaze behaviour in exploring relaxed conspecific and heterospecific faces is constrained by general facial configurations , mouth viewing was monotonically increased from human to dog, monkey and then to chimpanzee faces (a change related more to experience or exposure). It seems that both phylogenetic distance and prior experience play a role in humans’ viewing of heterospecific facial expressions.Like human viewers, monkeys’ face-viewing gaze distribution was also significantly modulated by the viewed face species. They showed human-like gaze allocation when exploring human faces . Similar prolonged eye viewing was also observed on monkey and chimpanzee faces, but not on unfamiliar dog faces, suggesting that the preference of monkey’s visual system is tuned towards primate eyes. Such preference is unlikely due to low-level appearance or physical saliency in the eye region, but is more likely driven by high-level expectation of the spatial location of the eyes in facial configuration Guo  which isThe viewed facial expressions further modulated monkeys’ gaze distribution. The eyes in expressive faces  tended to attract fewer fixations in comparison with the eyes in relaxed faces, implying an avoidance gaze behaviour in monkeys’ viewing of aggressive conspecific and heterospecific faces , possibly via facial action coding system. We did not include positive chimpanzee and monkey expressions in our presentation; future research could also examine interspecies emotional understanding of those well-defined primate facial displays in positive social contact, such as play faces in chimpanzees. Furthermore, the face images used in this study were in full frontal view with direct gaze. It is well established that direct gaze represents a strong signal of threat for macaque monkeys Dunbar , and vieNevertheless, the current study represents an important step forward in our understanding of how primates read and understand heterospecific facial displays of emotion. Comparing face-viewing gaze allocation between human and monkey viewers revealed both species-general and species-specific forms of facial communication. The common characteristics is that both species showed the persistent and prolonged eye viewing for primate faces  irrespective of facial expressions, which enables the constant retrieval of subtle emotional and intentional (e.g. gaze direction) information conveyed by the eye region in primates.Furthermore, the significance of face signalling and face reading in primates’ social interaction, and very similar cortical mechanism in face processing would suggest a comparable visual sensitivity and recognition performance of conspecific and heterospecific facial expressions across primates (Leopold and Rhodes Indeed, it has been proposed that the lifelong social learning is crucial to shape our emotion perception and emotional responses, such as cognitive representations of emotional triggers, experiences and associated coping responses (Ekman and Cordaro


DEGs) related to the colorectal normal mucosa–adenoma–carcinoma sequence using bioinformatics analysis. Raw data files were downloaded from Gene Expression Omnibus (GEO) and underwent quality assessment and preprocessing. DEGs were analyzed by the limma package in R software (R version 3.3.2). Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed with the DAVID online tool. In a comparison of colorectal adenoma (n = 20) and colorectal cancer (CRC) stage I (n = 31), II (n = 38), III (n = 45), and IV (n = 62) with normal colorectal mucosa (n = 19), we identified 336 common DEGs. Among them, seven DEGs were associated with patient prognosis. Five  of the seven genes presented a sequentially descending trend in expression with tumor progression. In contrast, TIMP1 showed a sequentially ascending trend. GCG was constantly downregulated compared with the gene expression level in normal mucosa. The significantly enriched GO terms included extracellular region, extracellular space, protein binding, and carbohydrate binding. The KEGG categories included HIF‐1 signaling pathway, insulin secretion, and glucagon signaling pathway. We discovered seven DEGs in the normal colorectal mucosa–adenoma–carcinoma sequence that was associated with CRC patient prognosis. Monitoring changes in these gene expression levels may be a strategy to assess disease progression, evaluate treatment efficacy, and predict prognosis.This study aimed to identify differentially expressed genes ( Colorectal cancer (CRC) is the third leading cause of cancer and cancer‐related death in patients with cancer worldwide, accounting for more than 134,000 estimated new cases and 49,000 estimated deaths in 2016 APC inactivation was an early event in more than 70% of colorectal adenomas and carcinomas KRAS and TP53 mutations participated in the adenoma–carcinoma sequence Most CRC cases develop slowly through the normal mucosa–adenoma–carcinoma sequence over several years Bioinformatics is a newly emerging scientific field that combines biology, mathematics, and information technology, making it possible to analyze large and increasingly complex molecular datasets. Microarray assays can acquire expression information on thousands of genes simultaneously and explore the genomic alterations associated with the progress of colorectal initiation and development In our study, we aimed to identify DEGs related to the colorectal normal mucosa–adenoma–carcinoma sequence. Original data were downloaded from GEO and analyzed with R software (R version 3.3.2). Gene expression levels in colorectal adenoma and CRC stage I, II, III, and IV were compared with those in normal colorectal mucosa. We eventually identified seven potential DEGs related to CRC patient prognosis and explored their function by performing Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis.The GEO database was systematically searched without language, race, region, and time restrictions (up to 7 January 2017). The advanced search strategy insured the comprehensiveness of the search results  and an adjusted P‐value <0.05 were considered DEGs. Then, all DEGs underwent prognostic analysis with the survival information from TCGA. TCGA database had no separate colorectal adenoma data, and thus, this information was only used to validate the DEGs in colorectal cancer with four stages with RNA‐seq data.Data preprocessing was performed with a standard robust multiarray average (RMA) method, including background correction, normalization, and logarithmic conversion P‐values <0.05.GO annotates and classifies genes based on three categories, including biology process, molecular function, and cellular component A total of 592 search results were obtained by our search strategy  family that regulates matrix metalloproteinases (MMPs) and disintegrin metalloproteinases TIMP1 was associated with cancer progression TIMP1 was shown to predict worse prognosis of laryngeal carcinoma TIMP1 was upregulated in both early and advanced CRC TIMP1 presented a sequentially ascending trend through the normal colorectal mucosa–adenoma–carcinoma sequence, and the upregulation of TIMP1 indicated a poor survival prognosis, consistent with previous studies. GCG is involved in the regulation of incretin synthesis, secretion, inactivation, and RET signaling. Diseases related to GCG are diabetes GCG was a preproprotein, which could be cleaved into four mature peptides and regulated cell proliferation, differentiation, and apoptosis. However, few studies have focused on the role of GCG in CRC progression. We discovered that GCG expression was downregulated in both adenomas and carcinomas, which was also confirmed by Spisak et al. We obtained seven DEGs of interest, which were HEPACAM2, ITLN1, LGALS2, MUC12, and NXPE1, even rare in CRC. These five genes all presented a sequentially descending trend in expression through the normal colorectal mucosa–adenoma–carcinoma sequence. HEPACAM2 is a member of the immunoglobulin family of adhesion genes. The clinical importance of HEPACAM2 in CRC remains unclear. ITLN1 encodes intelectin‐1, which functions as a receptor for both bacterial arabinogalactans and lactoferrin. Li et al. ITLN1 in CRC. LGALS2 encodes galectin‐2, which participates in non‐small‐cell lung cancer MUC12 is a member of mucin family. Matsuyama et al. MUC12 mRNA expression was an independent marker of prognosis in stage II and stage III colorectal cancer. For NXPE1, we found two studies, which were bioinformatics studies, but they did not determine the function of this gene. Although there are few studies on the functions of these genes, we used GO analysis and KEGG pathway analysis to predict the possible function of the genes and the possible signaling pathways, providing a direction for subsequent functional research.There are few studies about MUC12. However, MUC12 was also downregulated in colorectal cancer tissues compared with normal colorectal mucosa, and its expression levels in our own patient validation cases were consistent with the predictions of the GEO database, indicating that MUC12 is a promising marker. However, one‐third of cases in TCGA were extracted again for further prognosis validation, and all seven DEGs showed a close relationship with patient prognosis .Click here for additional data file.Figure S3. Survival curve of A. HEPACAM2, B. ITLN1, C. LGALS2, D. MUC12, E. NXPE1, F. TIMP1 and G. GCG from patients in our hospital for medical treatment.Click here for additional data file.Table S1. Search strategies.Table S2. Summary of thirty‐eight datasets.Table S3. Eighty‐seven genes present sequentially expression level changes through normal colorectal mucosa‐adenoma‐carcinoma sequence.Table S4. Further prognosis validation with one‐third cases on TCGA.Click here for additional data file. Click here for additional data file.


Drosophila melanogaster GAL4 lines for expression in two neuropils, the noduli (NO) of the central complex and the asymmetrical body (AB), and used multicolor stochastic labeling to analyze the morphology, polarity, and organization of individual cells in a subset of the GAL4 lines that showed expression in these neuropils. We identified nine NO and three AB cell types and describe them here. The morphology of the NO neurons suggests that they receive input primarily in the lateral accessory lobe and send output to each of the six paired noduli. We demonstrate that the AB is a bilateral structure which exhibits asymmetry in size between the left and right bodies. We show that the AB neurons directly connect the AB to the central complex and accessory neuropils, that they target both the left and right ABs, and that one cell type preferentially innervates the right AB. We propose that the AB be considered a central complex neuropil in Drosophila. Finally, we present highly restricted GAL4 lines for most identified protocerebral bridge, NO, and AB cell types. These lines, generated using the split‐GAL4 method, will facilitate anatomical studies, behavioral assays, and physiological experiments.The central complex, a set of neuropils in the center of the insect brain, plays a crucial role in spatial aspects of sensory integration and motor control. Stereotyped neurons interconnect these neuropils with one another and with accessory structures. We screened over 5,000  A comprehensive review of the functional roles of the central complex in diverse insects can be found in Pfeiffer and Homberg .One of the most studied roles of the insect central complex is the integration of sensory information, predominantly from visual input. The output of this sensory processing encompasses diverse motor and behavioral responses. In this capacity, the central complex regulates locomotor behaviors such as handedness, turn direction, initiation and termination of walking  displays some hint of a transverse division  and ventral (NO3) noduli exhibit longitudinal segmentation. NO2 is divided into dorsal and ventral subdomains  is a relatively inconspicuous structure located at the midline, adjacent to the ventral FB. It was first described in the fly as a round, almost exclusively right‐hemisphere structure  and activation domain (AD) of the GAL4 transcription factor are separately linked to complementary leucine zippers and placed under the control of different gene enhancers to create “hemidriver lines” . This mask was used to search a database of aligned neurons for pixel overlap using a comparison algorithm described in https://www.biorxiv.org/content/early/2018/05/09/318006.In addition, searches for both NO and AB neurons were performed against a database of “MCFO brains” (adult brains prepared using the MCFO technique) representing 2,200 GAL4 lines.  In these “color depth mask searches,” a binarized image stack of the neuron to be searched was projected into two‐dimensional space and colored by its position in the The following fly stock was used for MCFO: attP1/TM3, Sb]. GAL4 and split‐GAL4 stocks are noted throughout the text. Details concerning constructs and methods for the MCFO technique are described in Nern et al. . Briefly2.3attP18 ; . Imaging conditions for each brain and corresponding VNC are identical, so the intensity seen in the brain and VNC for each line accurately reflects the relative levels of expression in these two regions. Microscope settings were adjusted as necessary in different lines.The expression patterns of split‐GAL4 lines are visualized in Figure 2.4bruchpilot were ectopically expressed in the wing imaginal disc, trachea and epidermal cells. Furthermore, they show a correspondence between GFP and endogenous BRP patterns when a panneural driver is used to drive GFP‐tagged bruchpilot. Brp expression is lost in brp mutants and rescued by expression of BRP in these mutants . DPX was allowed to dry for 2 days before imaging.2.6A Zeiss LSM 710 confocal microscope was used to collect images, using a Plan‐Apochromat 63×/NA1.4 oil immersion objective. Frame sizes were 1,024 × 1,024 pixels, voxel size 0.19 × 0.19 × 0.38 µm, zoom factor 0.8, and one frame average. While reference channel intensity was adjusted throughout the depth of the sample to maximize image quality, the gain and power were maintained at constant levels within each sample. The “Janelia Workstation” image‐viewing software  was used to analyze confocal stacks.2.7https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-017-1694-9 or Wan et al., Registration of data collected from individual brains into a standardized frame of reference can distort the morphology of neurons, so unaligned data was used to characterize the morphology of neurons described here. On the other hand, since aligning the data to a standard brain allows a comparison between brains, registered data was used for the color depth mask searches. Details for preparation of the standard brain used in this work (JFRC2013) can be found in Aso, Hattori, et al. . Neuropi2.8In cases in which the neuron intensity in MCFO images was below the threshold required for visibility in a publication, brightness, and contrast were increased in the Janelia Workstation. In several cases, anti‐nc82 label and neuron fragments from neurons that were not the focus of the figure, were “erased” using Adobe Photoshop . Brightness and contrast for each pair of brains and VNCs shown in Figure 33.1Most GAL4 lines drive expression in multiple cell types, sometimes making it difficult to isolate individual cells for anatomical analysis using the MCFO technique. Their activity in multiple cell types also makes these lines problematic for behavioral assays. To circumvent these limitations, the split‐GAL4 intersectional method . These polarity data rely on the correct targeting of an exogenous fusion protein and can overpredict presynaptic sites in cases where expression levels are too high  of the GAL4 lines listed in Table In the third method of analysis, brains were prepared using the Chrimson‐Venus marker to reveal the expression patterns . Structures that are targeted by central complex neurons and that have unique first letters are similarly abbreviated .The remaining neuropils follow the three‐letter designations presented in Ito et al. . To avoiG1–9.s‐EBt.b‐D/V GA.b and PBG1–8.b‐EBw.s‐D/V GA.b, respectively. These abbreviations will remain as such.The field has established P‐EG and E‐PG as the abbreviations for the neurons PBG1–9.s‐EBc.b‐D/V GA.b, is abbreviated P‐ECG, and the gall tip E‐PG cell, PBG9.b‐EB.P.s‐GA‐t.b, is abbreviated E‐PGT.  In these two cases, the subscripted “C” and “T” disambiguate these two cell types from the P‐EG and E‐PG noted in #3, above.Neuropil subdomain information is included only when necessary to distinguish between otherwise identical abbreviations. In these cases, the first letter of the subdomain's name is appended as a subscripted capital letter. For example, the canal P‐EG, PBApparent input (spiny morphology) neuropils are listed first followed by neuropils with mixed input and output followed last by apparent output neuropils (boutons).Input, mixed, and output neuropils are separated with hyphens.Variants that are not morphologically distinct are assigned arbitrary, nonsubscripted numerals that follow the designated abbreviation .Cells with formal names that convert to pronounceable acronyms will adopt those acronyms .The nomenclature used in this publication and in Wolff et al.  is compr3.4The classification of a neuron as a PB, FB, EB, or NO cell is somewhat arbitrary since central complex neurons arborize in one to three structures of the central complex and could therefore be classified by any one of the three targeted neuropils. We began our studies of the central complex with the PB  has been identified, the ipsilateral LAL.s‐GAi.s‐NO1i.b neuron  designations. Five NO2 cell types are described, although four are rare. Although the sample size for these four neurons is small, their morphologies differ significantly from the most common cell type, LAL.s‐NO2i.b (below), and they display features that distinguish them from one another. These morphological criteria suggest that these four neurons are strong candidates to be bona fide distinct neuronal types; they are therefore described here.The NO2i.b neuron has predominantly spiny branches in the LAL whereas the NO2 arbor is a densely packed bundle of boutons Four additional “putative” NOOf the putative cell types described below, the first is most dissimilar to the rest and the remaining three share several features in common (discussed below). Definitive classification of these putative cell types awaits dense EM‐level reconstruction of this neuropil.2i.b‐FBℓ3i.b‐CREi.b  and just the ventral portion of NO1 as well as about two‐thirds of the width of layer 3 of the FB. As with the previously described cell type, it is possible that this arbor should extend the span of FBℓ3 but is truncated due to driver toxicity. The most obvious morphological difference between this cell and the LAL.s‐GAi.s‐CREi.s‐NO2i.b‐FBℓ3i.b‐CREi.b cell described above is the extensive array of boutons that is absent in the CRE of this cell (LAL.s‐GAi.s‐CREi.s‐NO2i.b‐FBℓ3.b).With the exception of the FB arbor in this cell, this is an ipsilateral neuron  that terminates in a single bouton and the bifurcating trajectory to the ipsilateral superior clamp (SCL), where it terminates in a small number of boutons , although more samples are needed to confirm this observation. This cell most closely resembles LAL.s‐GAi.s‐CREi.s‐NO2i.b‐FBℓ3.b .The LAL.s‐NOL Figure c. An occ3P/Mi.b .The ipsilateral LAL.s‐CREi.s‐NO3Pc.b neuron , the morphology suggests the predominant input comes from the LAL  on one side of the brain and is delivered to the contralateral nodulus. Unlike the LAL.s‐CREi.s‐NO3P/Mi.b neuron described above, only the NO3P subcompartment is targeted by this cell  as well as the Berlin , DL , and Oregon R  wild‐type strains.The analysis presented here indicates that the AB, while asymmetric in morphology, is present in both hemispheres in all brains  and 522 μ3  versus 7 μ for the left, and 590 μ3.5.2Three AB neurons or neuron families have been identified and are described below. These classes of neurons are primarily, but not exclusively, a conduit for information flow between the superior lateral protocerebrum (SLP), FB, and AB. No intrinsic AB neurons have been identified. The AB cell types described in this report innervate both the left and right AB. One or both ABs can be targeted by a single neuron, depending on the cell type. One cell type only innervates the left AB if the right AB is also innervated by the same neuron (see below). The AB neurons appear, based on anatomy, to primarily provide input to the AB, with two of the three AB neurons or families of neurons exhibiting predominantly boutons in the AB. Since the small, left AB is innervated, it is reasonable to conclude it is a functional neuropil.The SLP.s‐AB.b cell type arborizes in just two neuropils, the SLP and AB. The arbors are predominantly spiny in the SLP and consist overwhelmingly of boutons in the AB. This neuron type exhibits three trajectories: an ipsilateral path , n =  40; left SLP, both ABs (SLP.s‐ABic.b), n =  18; and right SLP, both ABs (SLP.s‐ABic.b), n =  10.The SLP.s‐ABic.b trajectory is less common than either the SLP.s‐ABi.b or SLP.s‐ABc.b trajectories; the latter two occur in approximately equal numbers. Furthermore, there is no strong bias toward the left or right SLP for the SLP.s‐ABic.b trajectory. One hundred fourteen MCFO‐labeled SLP‐AB neurons in line SS04682 were characterized as follows: right SLP, right AB (SLP.s‐ABi.b), These data indicate that the SLP‐AB neuron exhibits a strong asymmetric bias toward the right AB, but a similar strong right/left preference does not extend to the SLP. Furthermore, a single AB  is targeted more frequently than both simultaneously . An additional 23 neurons labeled using MCFO, distributed among six stable split lines , fell into the following classes: 7 SLP.s‐ABc.b , 10 SLP.s‐ABi.b , and 6 SLP.s‐ABic.b. Imaging data for these lines in which the entire population is labeled support the right AB bias for this neuron (not shown).The AB.s.b‐FBℓ8.b neuron comprises three sometimes subtly morphologically distinct forms . (c) AB.s.b‐FBℓ8i.b‐FBℓ8c.b, which has mixed terminals in the AB and two apparent output arbors in FBℓ8, one in each “shoulder,” or lateral margin  AB.s.b‐FBℓ8i.b, which has mixed terminals in the AB and apparent output in the ipsilateral layer 8 of the FB , is supported by the observation that the various forms occur in each of the GAL4 and split‐GAL4 lines examined, as well as in both split half parents of a given split‐Gal4 line. For example, a range of morphologies has been seen in VT006486 and two split‐GAL4 lines for which VT006486 is a parent line, SS04457 and SS04423. It is possible that results from behavior and physiology assays, as well as type‐specific split‐GAL4 lines, will indicate these forms are distinct cell types.Arbors of these family members are predominantly spiny in the SLP and the remaining arbors are composed primarily of boutons and are therefore presumed to be output. The SLP.s‐ABic.b‐FBℓ8.b neuron, the “core” member of the family, is shown in Figures The arbor in FBℓ8 in this family always spans the midline but varies in the degree to which it permeates this layer; as few as five medially located boutons have been seen. The cells shown in Figure 3.6G1–8.s‐EBt.b‐D/V GA.b , which derives its name from the Latin “glomus,” meaning “ball of yarn.” In keeping with the standard established in Hanesch et al.  for DrosWe identified a cell that bears a strong morphological resemblance to the tile cell, a PB‐EB‐GA cell .AD and DBD split half parents from the tile cell line, R33A12, were crossed to complementary split half parents that drive expression in a “tile‐like” cell in line VT040589. The tile cells present in the progeny of this cross  was PB1 glomerulus‐ > EBC‐IDFBDSB from the Lin et al.  Since MCFO enables a detailed analysis of circuitry and morphology, here we build upon the description provided in Lin et al.  in the original classification; instead, this arbor targets a structure named the round body by Lin et al. . Golgi preparations and data from the likely locust equivalent of the PB‐FB‐NO neuron (the CPU4 neuron), however, indicate these NO arbors are mixed  also receives ipsilateral terminals from the LAL via LAL.s‐CREi.s‐NO3P/Mi.b, this subcompartment may act as a limited integration center between the fly's left and right sensory fields.The LAL.s‐CREc.s‐NO4.4Drosophila neurons.Physiological data from two neurons in the sweat bee offer insight into a likely role for the NO neurons described here. The TN1 and TN2 neurons  share a high degree of anatomical homology with the LAL‐NO neurons: TN1 and TN2 are ipsilateral neurons with input branches in the lateral central brain and blebbed branches in the noduli  prior to publication and to Jens Goldammer, Masayoshi Ito, Ryo Minegishi, and Aljoscha Nern for generously sharing MCFO data. We thank A. Nern for data that was used to generate panels in Figure The authors are grateful to Laszlo Tirian and Barry Dickson for providing