The role of breastfeeding in improving allergy outcomes in early childhood is still unclear. Evidence suggests that immune mediators in human milk (HM) play a critical role in infant immune maturation as well as protection against atopy/allergy development. We investigated relationships between levels of immune mediators in colostrum and mature milk and infant outcomes in the first year of life. In a large prospective study of 398 pregnant/lactating women in the United Kingdom, Russia and Italy, colostrum and mature human milk (HM) samples were analysed for immune active molecules. Statistical analyses used models adjusting for the site of collection, colostrum collection time, parity and maternal atopic status. Preliminary univariate analysis showed detectable interleukin (IL) 2 and IL13 in HM to be associated with less eczema. This finding was further confirmed in multivariate analysis, with detectable HM IL13 showing protective effect OR 0.18 (95% CI 0.04–0.92). In contrast, a higher risk of eczema was associated with higher HM concentrations of transforming growth factor β (TGFβ) 2 OR 1.04 (95% CI 1.01–1.06) per ng/mL. Parental-reported food allergy was reported less often when IL13 was detectable in colostrum OR 0.10 (95% CI 0.01–0.83). HM hepatocyte growth factor (HGF) was protective for common cold incidence at 12 months OR 0.19 (95% CI 0.04–0.92) per ng/mL. Data from this study suggests that differences in the individual immune composition of HM may have an influence on early life infant health outcomes. Increased TGFβ2 levels in HM are associated with a higher incidence of reported eczema, with detectable IL13 in colostrum showing protective effects for food allergy and sensitization. HGF shows some protective effect on common cold incidence at one year of age. Future studies should be focused on maternal genotype, human milk microbiome and diet influence on human milk immune composition and both short- and long-term health outcomes in the infant. Increasing rates of allergy/atopy are of great concern with children bearing the greatest burden of this increase . Long-teHuman milk (HM) contains a large variety of active immune components , which aIt can be expected that HM composition may naturally change as a response to a number of environmental and genetic factors. HM immune components may influence immunological health outcomes but linear relationships between HM composition and subsequent health outcomes should be evaluated with care, due to potential confounding. Previously reported differences in HM immune composition between the countries and within the same populations provide evidence of volatility and reasons behind it remain unclear.Amongst immunologically active molecules studied in HM, transforming growth factor β (TGFβ) is the most well described. HM contains all the isoforms of TGFβ, with TGFβ2 being the most dominant; accounting for 95% of the total TGFβ . ProtectCytokines are one of the major classes of immune components in HM  but theyHepatocyte growth factor (HGF) is a less-studied component that is also present in HM in high amounts, comparable with those of TGFβ ,16,17, bWe aimed to assess the impact of maternal and environmental factors in relation to colostrum and mature human milk immune active components composition and health outcomes at the age of six and twelve months. The investigations and sample collection have been conducted following ethical approval by Ethics committees in three countries participating in the study: West London Rec 3 (UK) (Ref. number 10/H0706/32) and all paperwork has been completed according to the hospital R & D Joint Research Office (UK) (JROSM0072) policy; the Ethical Committee of the Azienda Ospedaliera di Verona  , and the Moscow Institute of Paediatrics and Child Health of the Ministry of Health of the Russian Federation (Russia) . All women provided written informed consent.Women were enrolled at antenatal and postnatal units of 3 participating centers: Maternity Hospital No. 1, Moscow, Russia; St. Mary’s Hospital, London, UK; G.B. Rossi Hospital, Verona, Italy. Details of recruitment are described in full elsewhere .Dermatophagoides pteronyssinus), Cat (Felix domesticus), Grass Pollen, Birch pollen, Peanut, Hazelnut, Egg , and Cow’s milk . SPT was performed by standard technique using 1 mm lancets , and were read at 15 min. Allergic sensitization was defined as a wheal ≥3 mm to at least one allergen, in the context of a wheal ≥3 mm to histamine and no wheal to the negative control.Following enrolment, participants underwent allergy skin prick testing (SPT) and answered a 10-minute interview-based questionnaire regarding their medical history. Exposure variables recorded were selected based on a detailed review of known determinants of HM composition . Informag for 15 min at 4 °C. The lipid layer was removed with a pipette and aqueous fraction was analysed for immune modulators [Participants were given sterile tubes to collect their own colostrum (once in the first 6 days of life) and mature HM (once at 4–6 weeks postpartum). Instructions were given for collection of samples by manual expression or by collecting the drip from the contra-lateral breast during feeding . Colostrdulators . All milWe used electro-chemiluminescence to measure immune mediators in colostrum and breast milk samples for Th1 and Th2 cytokines, HGF, and TGFβ1-3 . Laboratory experiments were run according to manufacturer’s protocol, using an eight-point standard curve. Assays were run in duplicate with no dilution used for Th1 and Th2 cytokines  and HGF, and 1:2 dilution for TGFβ assays, following pilot experiments which showed that TGFβ2 levels in undiluted milk samples were often greater than the upper limit of detection. For TGFβ analysis, samples were acidified by the addition of 1N HCl to colostrum or mature milk. Acidified samples were then neutralised by addition of 20 μL of 1.2 NaOH, 0.5 HEPES. Assays were run in duplicate, and mediator levels were excluded where the CV was >25%.The infants’ health outcomes were assessed at the age of 6 months by means of a phone questionnaire and at one year of age by a questionnaire during the follow-up visit. All questions were carefully explained to the mothers. All health outcomes were self-reported by the mother except atopic sensitization which was assessed by skin prick test. Information on fever, wheeze, common cold, eczematous rash, reflux and vomiting cumulative incidence, food allergy/sensitivity or intolerance incidence were solicited.Common cold was defined as at least one episode of runny nose or cold lasting for a minimum of 3 days. Cough/wheeze outcome was defined as at least one episode of recurrent cough or wheezing prior to assessment at one year of age. Eczema symptoms were considered present if the child had ever had a characteristic itchy eczematous rash intermittently at any time during the last 6 months. Parental-reported food allergy was defined as food allergy/sensitivity or intolerance incidence reported by the parents within the first 12 months of life. An infant was considered to be atopic if s/he had positive control wheal of ≥3 mm and any of the allergen-induced wheals being ≥3 mm greater than negative control.For exclusive breastfeeding, the World Health Organisation (WHO) recommended definition “that the infant receives only breast milk” was used. No other liquids or solids are given—not even water—with the exception of oral rehydration solution, or drops/syrups of vitamins, minerals or medicines” .We assessed the probability of infants to develop particular health outcomes (presented as a binary variables) depending on potential determinant, using a binomial GLmulti (GLM) and LASSO (Least Absolute Shrinkage and Selection Operator) analyses. The resulting term importance was plotted in order to graphically visualize the effects of determinants. Such plots provide a graphical representation of importance estimate or relative evidence weight of candidate determinants. These weights are computed as the sum of the relative evidence weights of all possible models in which the term appears. Sensitivity analysis was performed for both methods and all models; a different number of variables were included to make sure that those selected had a real and credible effect on the outcome. Health outcomes assessed using models were: fever, eczema, food allergy/sensitivity/intolerance assessed at 6 months. Common cold incidence, reflux and/or vomiting, and cough/wheeze were assessed both at 6 and 12 months. Influence of immune active molecules level in colostrum and mature HM in conjunction with potential confounding factors was analysed in relation to health outcomes at the age of 6 and 12 months. The most reliable information was available for eczema, cough/wheeze and food allergy at 6 months and common cold at 12 months, these data were used as health outcomes for the statistical modelling. The following determinants of health outcomes were included into the models: levels of growth factors in colostrum and mature human milk, detectability of cytokines in colostrum and breast milk, site of collection, colostrum collection time, maternal atopic status, delivery type, infant gender. Prior to inclusion, descriptive statistics, cross-tables, correlation and descriptive statistical tests were performed on each determinant to describe the importance of each variable and identify which may be the most useful in explaining and predicting a particular health outcome. Human milk immune active molecules assessed were presented as levels of HGF, TGFβ1, TGFβ2, TGFβ3, and cytokines  detectability. As cytokines are detected in human milk in low concentrations, data were transformed into binary variable (detectable vs. undetectable) to increase statistical analysis power. Data on cytokine detectability can be found elsewhere . Statistical analysis was performed using R statistical package version 3.1.0 . As a first step, univariate analysis and correlation matrix were used, followed by multivariate analysis which included modelling, using LASSO and GLM.n = 101, Russia n = 221, Italy n = 76) provided samples and were included in this study. The 83 mothers unwilling or unable to provide colostrum samples were not evaluated further.A total of 481 mothers were recruited into the study from June 2011 to March 2012 from the birth centres and antenatal and postnatal units of secondary and tertiary hospitals from three countries, located in Northern Europe, Eastern Europe, and the Mediterranean area. Of 481 women, 398  by mothers living in Moscow. Country of sample collection was not associated with parental-reported food allergy OR 0.13 (95% CI 0.01–1.46) and OR 2.07 (95% CI 0.47–9.02) for Verona and Moscow respectively. Among the studied variables, three were associated with eczema development at 6 months postpartum. Infants having breast milk with higher levels of TGFβ2 were at significantly higher risk OR 1.04 (95% CI 1.01–1.06) of eczema development. In contrast, if detectable levels of IL13 were present in HM, it was associated with a reduced risk OR 0.18 (95% CI 0.04–0.92) of eczema development. These results confirm the outcomes of the univariate analysis. In our cohort, boys tended to have eczema less often OR 0.2 (95% CI 0.05–0.84) compared with girls. Children fed colostrum with detectable levels of IL13 in colostrum were found to be less likely OR 0.1 (95% CI 0.01–0.83) associated with parental-reported food allergy at the age of 6 months. HGF concentration in breast milk was associated with less common cold development OR 0.19 (95% CI 0.04–0.92). No determinants were found to be associated with cough/wheeze development at the age of 12 months. There is some tendency for HGF to be associated with a higher risk of cough or wheeze development, but results did not reach significance OR 1.89 (95% CI 0.94–3.78). There was no association between any factor and infant allergic sensitisation at one year of age. It may be explained by a very small sample size as only 14 babies from the three cohorts developed allergic sensitisation.Mothers from the three geographical regions studied live in very different environments, have differences in diet, lifestyle and it is necessary to take into account many factors which may potentially influence human milk composition as well as health outcomes. In contrast to other studies, we included a large number of potential determinants, adjusting the results to the site of collection as a potential confounder making the results more robust. The aim of the study was to investigate whether peptide regulatory factors in human milk impacted infant health outcomes. Despite limitations, the results suggest that variability of human milk composition has an effect on parental-reported eczema, food allergy, and common cold development. The results support the concept that IL13 and HGF have protective effects and TGFβ2 may act as a risk factor, which may explain the diversity of results from epidemiological studies on the health-promoting effects of breastfeeding with regards to allergic diseases. Further, many studies attempted to evaluate colostrum and human milk composition influence on atopy and/or allergy development in the first years of life and produced conflicting results ,27,28,29As TGFβ is an important regulatory cytokine suppressing both Th-1 and 2 activity, it appears counter-intuitive that high levels are associated with increased risk of eczema development. However, eczema is primarily a condition of impaired skin barrier function with allergic sensitization being a secondary phenomenon. Our findings suggest that higher concentrations of TGFβ2 in mature human milk are associated with significantly increased risk of eczema reported by the age of 12 months. Some studies support this observation, having found increased TGFβ1 and TGFβ2 in colostrum associated with the eczema onset in infants ,28,29. HDetectable IL13 in mature milk reduced the risk of parent-reported eczematous rash development, whilst detectability of this cytokine in colostrum seems to have a similar association with food allergy/sensitivity/intolerance reported by the mothers at six months of age. This is the first study to report this association between IL13 in colostrum/human milk and eczema and/or food adverse events in children at 12 months of age. Eczema is not primarily an allergic condition but a heterogeneous disease. It may be speculated that a combination of TGFβ and IL13 may lead to TH1 responses impairment. The high IL-13 in colostrum fits well with the presumed impact on Immunoglobulin (Ig) E production but the counter effect of detectable levels in mature milk may be irrelevant as they are so low as to have little if any biological significance. Although maternal-reported events are a subjective measure and risk of bias is increased, these data should be validated on larger cohorts of high-risk infants. Most studies agree that levels of other human milk immune active molecules, cytokines in particular, are not associated with atopy and/or allergy development in early life ,27,29,30Human milk has been shown to be beneficial for infants in part by providing high concentrations of immune active molecules which are associated with a decreased incidence of neonatal respiratory infections as well as long-term outcomes, such as wheeze and/or asthma . GdaleviOur data did not show any significant association of colostrum and/or HM immune active molecules with parent-reported cough or wheeze episodes at 12 months of age. It is known that a large proportion of infants suffer asymptomatic infections during the first year of life . There wThe main strength of this study is that it is one of the largest to date, assessing immune active molecules in colostrum and mature milk. The main limitation of this study is recruitment of women from the general population. As a consequence, very few babies developed eczema. According to UK working party criteria, recurrent rash development reported by the mother is not the most accurate and precise criteria to use. An apparent weakness of this study is that all immunological outcomes were reported by the parents and not based on healthcare professional diagnosis. Mothers tend to over-report health outcomes, such as food allergy in their children, but childhood eczema can be accurately reported by caregivers . The samOur data suggests that another factor substantially increasing the risk of eczematous rash development is the gender of the baby, with girls at higher risk. This result is in agreement with the International Study of Asthma and Allergies in Childhood (ISAAC) phase three data , althougIn this large international cohort study of HM immune composition, we found an important association between HM constituents and infant health outcome. Our hypothesis is at least in part confirmed but will require more detailed evaluation of environments. We have also confirmed that variations in levels peptide regulatory factors in human milk do associate with different infant health outcomes. As we focused on an un-selected general population cohort, the power to detect effects on allergy outcomes was limited. Despite this, higher TGFβ and IL13 did associate with eczema. This will require confirmation in a high-risk cohort and could indicate targets for trial of interventions to prevent atopic diseases. Future research assessing human milk composition association with immunological health outcomes should include international collaborative studies with strict harmonisation of sampling, storage and analysis protocols between the sites. There is a need in studies, for evaluating human milk immune composition with samples collected at multiple time points prospectively. The only way forward is to bring different research groups together in an attempt to map human milk composition, highlighting differences between the countries and finding associations between human milk immunology and health outcomes.


Supplemental Digital Content is available in the text Recent studies have implied a prognostic value of the prognostic nutritional index (PNI) in postoperative septic complications of elective colorectal surgeries. However, the evaluation of PNI in contaminated surgeries for gastrointestinal (GI) fistula patients is lack of investigation. The purpose of this study was to explore the predictive value of PNI in surgical site infections (SSIs) for GI fistula patients undergoing bowel resections.A retrospective review of 290 GI patients who underwent intestinal resections between November 2012 and October 2015 was performed. Univariate and multivariate analyses were conducted to identify risk factors for SSIs, and receiver operating characteristic cure was used to quantify the effectiveness of PNI.P = 0.029] and leukocytosis  were independently associated with postoperative SSIs.SSIs were diagnosed in 99 (34.1%) patients, with incisional infection identified in 54 patients (18.6%), deep incisional infection in 13 (4.5%), and organ/space infection in 32 (11.0%). receiver operating characteristic curve analysis defined a PNI cut-off level of 45 corresponding to postoperative SSIs . Furthermore, a multivariate analysis indicated that the PNI < 45 [odd ratio (OR): 2.24, 95% confidence interval (CI): 1.09–4.61, Preoperative PNI is a simple and useful marker to predict SSIs in GI fistula patients after enterectomies. Measurement of PNI is therefore recommended in the routine assessment of patients with GI fistula receiving surgical treatment. Gastrointestinal (GI) fistula operations, which are commonly contaminated surgery, have higher risk of SSIs compared with other colorectal interventions. Additionally, intricate medical and surgical conditions for GI fistula patients collectively contribute to the development of an SSI. Therefore, early diagnosis and management of SSIs after GI fistula surgeries deserves our sufficient attention.Surgical site infections (SSIs) are deemed the third most common hospital-acquired infection, and elective colorectal surgery has the highest incidence of SSIs. The prognostic nutritional index (PNI) advocated by Onodera et al, calculated based on the serum albumin concentration and peripheral blood total lymphocyte count (TLC), was the simplest parameter among previously reported prognostic nutrition indices for determining the nutritional and inflammatory status of surgical patients. This formula was an established prognostic parameter for various types of cancer, which has been validated previously to evaluate the risk of postoperative complications and mortality in GI tract surgery.–6 A recent study also revealed that a preoperative low PNI correlated with the occurrence of incisional SSIs after bowel resections in patients with Crohn disease.Clinically, indices containing various nutritional and inflammatory parameters were used to predict surgical risks and postoperative complications.So far no reports have been published regarding association between PNI and SSIs in GI fistula patients undergoing intestinal resections. Thus, the primary objective of this study was to clarify the prognostic value of PNI in patients with GI fistula.22.1This was a retrospective, observational study carried out in GI Fistula Center of Department of Surgery, Jinling Hospital, China. GI fistula patients who underwent abdominal surgeries from November 2012 to October 2015 were enrolled in this study. The study was approved by the institutional review board of Jinling Hospital. Consent from participants was not required in this retrospective study.The inclusion criteria of patients were be at least 18 years of age; having an abdominal CT scan or fistulography that confirmed diagnosis of GI fistula, and being scheduled for GI fistula resections. All anastomoses were created using a linear stapler. A total of 290 GI fistula patients were enrolled in the analysis ; intraoperative blood loss; duration of operation; types of colectomies; and American Association of Anesthesiology score, methods of anastomosis, and number of anastomoses.am on the day of surgery. Routine laboratory measurements included Hemoglobin (Hb), white blood cell count, platelet count, C-reactive protein (CRP), procalcitonin (PCT), and serum albumin. According to the WHO, anemia is defined as Hb level less than 12 g/dL for nonpregnant females and less than 13 g/dL for males; leukocytosis was defined as a white blood cell greater than 11  × 109/L and serum albumin less than 3.5 g/dL was considered as hypoalbuminemia. The PNI was estimated according to the following formula: 10 × serum albumin (g/dL) + 0.05 × TLC (/mm3).Blood of GI fistula patients was drawn preoperatively at 5:00 2.3 The purpose of the preoperative management was to improve patients’ mental, nutritional, and inflammatory conditions. In the end, a definitive operation was subsequently considered to solve the existing fistula.When the GI patients were admitted in our institution, we initially corrected or maintained their hydroelectrolytic equilibration, controlled the infections using proper surgical drainage or antibiotics and reinforced patients’ nutritional status using parental nutrition or enteral nutrition. Moreover, a special modified double cannula drainage was used to improve drainage in our intestinal fistula center. SSIs were defined as occurrence of an infection within 30 days after operation, further classified as superficial incisional, deep incisional, and organ space infections. At our institution, SSIs were identified according to at least one of the following criteria: purulent drainage from the surgical site; an organism isolated from a culture of fluid from the surgical site; incisional pain, tenderness, localized swelling, redness, or heat and opening of the wound; or diagnosis of SSI by the surgeon or attending physician.,10 In the present study, anastomotic leakage or intra-abdominal abscesses after surgery was considered as an organ/space SSI.The major outcome of interest in the present study was incidence of SSIs. All SSIs events were defined on the basis of guidelines issued by National Nosocomial Infection Surveillance system of the Centers for Disease Control and Prevention.2.4P < 0.25 in the univariate analyses were enrolled into a multivariate logistic regression analysis. Comparisons of PNI and CRP were done by receiver operating characteristic (ROC) and binary logistic regression were also performed in SPSS. The thresholds were developed with an equal emphasis on sensitivity and specificity with the Youden index. The area under curve (AUC) was used to quantify the effectiveness of PNI and CRP levels in predicting postoperative SSIs. P < 0.05 was considered to be statistically significant.Statistical analyses were performed using SPSS 19.0 statistical software . Potential risk factors of SSIs were assessed by univariate and multivariate analyses. Univariate analyses were performed using the Chi-square test or Fisher's exact test. To better clarify the independent factors of SSIs in GI patients, all variables with a value 33.1P < 0.001) and statistical difference regarding the total cost of hospitalization was found between 2 groups . Table P = 0.012), PCT (P = 0.012) and TLC (P = 0.019), preoperative leukocytosis (P = 0.013), hypoalbuminemia (P = 0.001), and levels of PNI (P < 0.001). Moreover, the incidence of leukocytosis in SSI group (9.1%) increased more than 4-fold compared with patients in non-SSI group (2.1%). Table The clinical and demographic information from 290 patients with GI fistula who underwent intestinal resections in our institution were summarized in Table 3.2 In the present study, ROC analysis was performed to evaluate the performance of PNI and CRP levels in discriminating SSIs. The optimal cutoff value of PNI was determined at 45 and the AUC was 0.72 corresponding to the sensitivity and specificity of 76% and 55%, respectively. The AUC of CRP levels was 0.63 with 65% sensitivity and 52% specificity. In order to investigate whether the combination of PNI and CRP in clinical practice improved the prediction of SSIs, we performed binary logistic regression analysis including both parameters. The combination of PNI and CRP was not better than PNI alone to discriminate SSIs . Incisional SSIs were observed in 54 patients (18.6%), deep incisional SSIs in 13 patients (4.5%), and organ/space SSIs in 32 (11.0%) patients  and leukocytosis  were independently associated with postoperative SSIs in GI patients undergoing bowel resections. The preoperative CRP, PCT, TLC, and hypoalbuminemia were not found to be significant factors for the occurrence of SSIs  GI patients presented preoperative leukocytosis in our cohort  performed better than CRP (AUC = 0.63) in discriminating SSIs. Beyond that, PNI in combination with CRP did not enhance the discriminative power. Preoperative CRP levels, contrary to a previous research, were not an independent risk factor in predicting SSIs. These data suggested that PNI could be considered as a new significant marker to assess the risks in occurrence of SSIs.There is increasing evidence that the presence of a systematic inflammatory response, as indicated by an elevated circulating CRP concentration, is associated with postoperative complications (including SSIs) in patients with abdominal surgery.This study is subject to limitations: first, this was a retrospective and single-center study, which may also have potential flaws in the accuracy of documentation in the medical records. Second, details concerning operative procedure, such as time of using antibiotics, core body temperature, and degree of contamination were not evaluated in our study. Despite these limitations, to our knowledge, this is the first study to evaluate the prognostic significance of preoperative PNI in GI fistula patients undergoing intestinal resections.In conclusion, higher PNI in GI patients suggests a favorable prognosis. Considering that GI fistula patients at higher baseline risk for SSIs, preoperative PNI should be included in essential assessment of GI patients receiving enterectomies and patients with a lower PNI should monitored and receive targeted medical care to avoid postoperative SSIs.Chunyu Jian and Huan Su from affiliated hospital of southeast university greatly helped to make this study a reality when we started our study. I also owe my sincere appreciation to Chunyu Jian and Huan Su, who gave support and energy to me during the difficulty of the study.


The health-risk assessment paradigm is shifting from single stressor evaluation towards cumulative assessments of multiple stressors. Recent efforts to develop broad-scale public health hazard datasets provide an opportunity to develop and evaluate multiple exposure hazards in combination.We performed a multivariate study of the spatial relationship between 12 indicators of environmental hazard, 5 indicators of socioeconomic hardship, and 3 health outcomes. Indicators were obtained from CalEnviroScreen (version 3.0), a publicly available environmental justice screening tool developed by the State of California Environmental Protection Agency. The indicators were compared to the total rate of hospitalization for 14 ICD-9 disease categories (a measure of disease burden) at the zip code tabulation area population level. We performed principal component analysis to visualize and reduce the CalEnviroScreen data and spatial autoregression to evaluate associations with disease burden.2.5. Mass of pesticides used in agriculture was poorly or negatively correlated with all other environmental indicators, and with the CalEnviroScreen calculation method, suggesting a limited ability of the method to capture agricultural exposures. In a PCA of the 5 socioeconomic variables, the first PC explained 66% of variance, representing overall socioeconomic hardship. In simultaneous autoregressive models, the first environmental and socioeconomic PCs were both significantly associated with the disease burden measure, but more model variation was explained by the socioeconomic PCs.CalEnviroScreen was strongly associated with the first principal component (PC) from a principal component analysis (PCA) of all 20 variables (Spearman ρ = 0.95). In a PCA of the 12 environmental variables, two PC axes explained 43% of variance, with the first axis indicating industrial activity and air pollution, and the second associated with ground-level ozone, drinking water contamination and PMThis study supports the use of CalEnviroScreen for its intended purpose of screening California regions for areas with high environmental exposure and population vulnerability. Study results further suggest a hypothesis that, compared to environmental pollutant exposure, socioeconomic status has greater impact on overall burden of disease.The online version of this article (10.1186/s12940-017-0344-z) contains supplementary material, which is available to authorized users. A wide range of factors including demography, socioeconomic status, psychosocial stressors, and environmental exposures influence health outcomes –6. One oTo complement the development of new methods, there is an ongoing need to quantitatively examine existing methods and tools. Critical and impartial evaluations will ensure that integrated assessment methods are well characterized, technically defensible, and appropriate for intended uses. Further, methods and their underlying data can be analyzed for geographic and statistical patterns of public health hazards , 23, 24.An important case study for spatial health hazard evaluation is the California Communities Environmental Health Screening Tool version 3.0 . CalEnviroScreen was developed by the State of California Environmental Protection Agency’s  Office of Environmental Health Hazard Assessment (OEHHA) as a “screening methodology that can be used to help identify California communities that are disproportionately burdened by multiple sources of pollution .” CalEnvThe methodology for developing CalEnviroScreen has been detailed elsewhere, and CalEnviroScreen has previously been shown by the scientific development team to indicate strong racial disparities in environmental and socioeconomic vulnerability , 24. TheWe examined the multivariate associations in the data underlying CalEnviroScreen (Version 3.0) and the statistical association between the 17 environmental and socioeconomic variables that describe environmental hazard and population vulnerability with an indicator of disease burden. We developed the disease burden indicator using publicly available hospital discharge data at the zip code scale.The literature on model performance evaluation makes clear the need for systematic efforts to show how a decision-support model performs relative to its intended objectives . The worThe CalEnviroScreen data reduction and score calculation methodology is moderately complex, and is based on considerable professional judgment , 23. PubIn short, our aim was to systematically to describe associations among variables that go into the CalEnviroScreen score, whether the score strongly correlates with systematic change in the combined variables, and whether these indicators of hazard and vulnerability predict burden of disease. To achieve these objectives, we addressed four questions about the CalEnviroScreen source data and its use to produce an outcome score: 1. What are the correlation patterns and statistical associations in the variables? 2. How does the CalEnviroScreen numeric score compare to a score based on principal component analysis, employed as an alternate scoring method based on the statistical associations in the underlying data? 3. Using the alternate scoring method, what spatial patterns are evident in environmental hazard and population vulnerability in California? 4. Do the environmental hazard and population vulnerability indicators statistically predict overall disease burden? For this last question, we work to generate hypotheses regarding the ability of CalEnviroScreen to address health outcomes and the relative importance of environmental versus socioeconomic factors in determining disease burden.2.5), diesel particulate matter concentrations (diesel PM), traffic density, drinking water contamination, active pesticide mass used in agriculture (pesticide use), airborne toxic chemical releases, water body impairments, sites hazardous to groundwater (groundwater threats), sites targeted for cleanup, hazardous waste sites, and solid waste sites. CalEnviroScreen 3.0 also includes 5 socioeconomic vulnerability variables: low educational attainment, linguistic isolation, poverty, unemployment, and households severely burdened by housing costs . CalEnviroScreen 3.0 additionally includes three specific health outcome variables: asthma, low birth-weight, and cardiovascular disease, which are intended to indicate a combination of vulnerability to, and effects of, environmental exposures [We downloaded the CalEnviroScreen data along with the CalEnviroScreen 3.0 scores as a Microsoft Excel spreadsheet file from the CalEnviroScreen website . These dxposures . All varxposures , Faust exposures , and OEHxposures  provide The CalEnviroScreen 3.0 score is constructed from these data by a weighted averaging and multiplication algorithm, described elsewhere . BrieflyAlthough CalEnviroScreen does incorporate three specific health outcomes, we developed a separate disease burden measure independently of CalEnviroScreen to examine how well the environmental and socioeconomic variables in CalEnviroScreen predict overall burden of disease. To maintain transparency and potential for community access , 13, ourWe characterized burden of diseases using discharge diagnostic codes (which used the ICD-9-CM schema). We obtained these data for all hospitalizations for a given calendar year using publicly available, de-identified, statewide hospital discharge data from the California Office of Statewide Health Planning and Development, spanning the years 2008–2011. Using these data, we classified hospitalizations by pre-determined ICD-9 diagnostic categories, focusing on diseases having environmental etiology. We determined the sum total number of hospitalizations for 14 disease diagnostic categories representing serious or chronic ailments known to have potential environmental etiology. The 14 categories were pneumonia, chronic obstructive pulmonary disease (COPD), asthma, myocardial infarction (MI), cerebrovascular accident (CVA), diarrhea, pancreatic cancer, lung cancer, breast cancer, lymphoma, leukemia, depression, schizophrenia, and low birth weight.The overall approach of combining multiple diseases without weighting factors and assuming that hospital admissions can be a metric of regional disease patterns offers utility for impact assessment but has limitations. Combining multiple disease outcomes into a single metric of disease burden has the advantage of being comprehensive in capturing a large range of environmentally related diseases. The approach has been used in assessing global burden of disease for policy studies , but howIn a preliminary analysis, we found that the occurrence of these disease categories in hospitalized persons was positively correlated among the categories and also correlated with the total number of diagnoses  level, and divided by total population. For the denominator, we used ZCTA population estimates from the 2010 United States Census. We observed high variability in rates for populations below 100 individuals within a ZCTA , since apart from mortality, hospitalization is generally the most extreme result of any disease process.Expecting chronic disease burden to be higher among the elderly, we obtained the percent of the population over 65 years old for each ZCTA from the 2010 US Census. This parameter (Over65) was used in addition to the environmental and socioeconomic variables derived from CalEnviroScreen as a predictor in statistical models used to explain the disease burden measure.Hospitalization-related diagnoses were tabulated at the zip code scale, census population is at the ZCTA scale, and CalEnviroScreen data are available at the census-tract scale. Thus, spatial alignment was required prior to comparing CalEnviroScreen variables to the disease burden measure. The following data preprocessing steps were performed using ArcMap v10 : 1. average the CalEnviroScreen data at the zip code scale to achieve a consistent analysis scale; 2. link the CalEnviroScreen and ICD-9 data together; 3. combine with a shapefile of zip code polygons; and 4. standardize the health outcome data to total population per zip code tabulation area (ZCTA). Additional file n = 7929), PCA was performed on the correlation matrix using the R package factoMineR. Prior to PCA, missing values were imputed using the imputePCA command in the missMDA package [Statistical analysis was performed in R (version 3.4.0) . Princip package .Separate PCAs were performed to achieve different study objectives. A PCA was performed on all 20 CalEnviroScreen variables in combination in order to examine multivariate patterns of the entire data set. Two separate PCAs were also performed on the 12 environmental and the 5 socioeconomic variables to generate and evaluate a smaller number of variables representing the categories of environmental hazard, and socioeconomic status, respectively. Finally, another PCA was performed on the 17 environmental and socioeconomic variables. This PCA, which did not include the three health outcome variables , was compared to the hospitalization rate disease burden measure (described above). The goal of this analysis was to examine how these exposure and population variables underlying CalEnviroScreen are generally associated with disease burden.p values (α = 0.05) and on ∆BIC, employing the rule of thumb that ∆BIC ≥ 2 provides positive evidence of model improvement [2 was calculated as a measure of model goodness of fit for SAR models. Analogous to traditional R2 in meaning (though not directly comparable), the Nagelkerke pseudo-R2 estimates from 0 to 1 the improvement in proportion of variation explained by the fitted model, versus a null (intercept-only) model [2 was compared between the full model and the model with that parameter removed.Environmental hazard and socioeconomic status variables  were compared to the disease burden measure  using simultaneously autoregressive models (SAR), employing the R package spdep. SAR was chosen as a spatial autoregressive model appropriate to describe and test for linear relationships in the presence of spatial autocorrelation , 43. Approvement . Nagelkey) model . In orde10 (7 variables), cube root (6 variables), square root (5 variables), and arcsine square root transformation (drinking water). PM2.5 and low birth weight did not require transformation . The combined disease burden measure (DB) exhibited skewness and long tails (leptokurtic) and standard transformations failed to achieve normally distributed model residuals. Normal residuals were therefore achieved employing a modulus transformation: Prior to statistical analysis, all variables were transformed to approximate a normal distribution and multivariate linearity required for linear model analysis , 48. Trad Draper . The pred Draper .In the interest of independent assessment, we did not communicate with OEHHA, CalEPA, or any members of the CalEnviroScreen development team regarding any aspect of this study.For Question 1, describing the multivariate structure of the CalEnviroScreen source data, we employ PCA to visualize which exposures are associated with each other and the prevailing patterns of overall exposure encountered in California. For Question 2, how CalEnviroScreen compares to an alternate metric based on PCA, we present the correlation between the main principal components and the CalEnviroScreen score. For Question 3, spatial patterns in environmental hazard and population vulnerability, we map the first principal component (PC) of separate PCAs performed on the environmental hazard and socioeconomic vulnerability variables. Finally, Question 4 examines and compares whether the exposure and vulnerability indicators in CalEnviroScreen predict disease burden. We employ the PCs rather than the individual parameters to focus on overall patterns of exposure and vulnerability and to reduce the number of required analyses. The relative importance of environmental versus socioeconomic parameters in the model illustrates which factors most influence disease burden.2.5(r = 0.41) and traffic density (r = 0.56), and toxic release correlated with these three variables  . The strongest negative association among all variables is groundwater threats versus ozone (r = −0.33). Of the CalEnviroScreen health outcome variables, low birth weight is not well correlated with any environmental variables, but is highly correlated with housing burden (r = 0.72). Similarly, asthma is more positively correlated with the socioeconomic variables education (r = 0.51), poverty (0.53), and housing burden (0.50), than with any environmental variables. Cardiovascular disease exhibits moderate correlations with low educational attainment, poverty, and unemployment (r = 0.43–0.46) but also with the environmental variable, ozone (0.39).Pearson’s pairwise correlation coefficients (r) indicate multiple associations for the underlying CalEnviroScreen data Table . Positiv.5r = 0.4 and traf.5r = 0.4 and traf.5r = 0.4 and traf2.5 and diesel PM.PCA was performed on the entire CalEnviroScreen data set (20 variables), on the data set without the health outcome variables (17 variables), and on the environmental (12 variables) and socioeconomic (5 variables) data. For the entire data set, the first three PCs explain 50% of data variability in combination. The first principal component (PC)  represents general exposure to urban and industrial pollution. Interestingly, PC1env is strongly positively correlated at the zip code scale with population density , indicating densely populated areas are more exposed to the main environmental hazards measured by CalEnviroScreen.For the environmental PCA Fig. , the firThe second environmental PC  explains 20% of variance, and is negatively associated with ozone and drinking water contamination Fig. . ExaminaFor the socioeconomic PCA Fig. , the firn = 7929). Spearman’s ρ was employed as a measure of association that is robust to nonlinear relationships, which were evident in this analysis  multiplied by a weighted sum of the socioeconomic and health outcome variables (referred to as population characteristics) , 24. We In the all-variables PCA, CalEnviroScreen is strongly associated with PC1all  and a weak correlation between PC1env and PC2soc (r = −0.31). Percent population > 65 years old  was also included as a potential predictor. Over65 was moderately correlated with PC1all (r = −0.45), PC1soc (r = −0.36), and PC1env (r = −0.42), and uncorrelated with the other parameters.The principal components from the all environmental and socioeconomic variables PCA  and from the separated environmental and socioeconomic PCAs  were evaluated as possible predictors for the disease burden measure that we developed. The predictor variables were not correlated with each other (| r | ≤ 0.13), with the exception of a weak negative correlation between PC1env and PC1soc (n = 1606 Zip Code Tabulation Areas), the following model form was obtained :Initial modeling using linear regression to predict disease burden indicated clear evidence of spatial autocorrelation of residuals for all models . Thus, SAR was used to predict disease burden, and addressed these issues. For the SAR model on the all environmental and socioeconomic data PCA results , PC3all (p = 0.96), and the intercept (p = 0.97) were not significant as added model terms. For the final model, the Nagelkerke pseudo-R2 was 0.49, which was effectively unchanged when attempting to include PC2all or PC3all. Change in R2 after removing individual parameters illustrates the contribution of each parameter to explaining the variability in disease burden. Decrease was greater when removing Over65 (new R2 = 0.25) than when removing PC1all (new R2 = 0.42). The association with PC1all generally describes the association of disease burden with the correlated variability in all of the CalEnviroScreen environmental and socioeconomic indicators except for pesticide use and impaired water bodies , four model terms contributed to describing disease burden (coefficient estimate ± SE):For the separate environmental and socioeconomic PCA results  nor the intercept (p = 0.93) were significant. The model coefficient was largest for Over65, simply indicating that age must be accounted for in the analysis. The positive coefficient for PC1env and PC1soc indicate an overall association with environmental exposures and socioeconomic vulnerability. The coefficient for PC2soc further suggests an association with unemployment, rather than linguistic isolation, in particular. The association with two socioeconomic principal components but just one environmental principal component, with qualitatively similar coefficient magnitudes on standardized variables, suggest a greater importance of socioeconomic than environmental factors in predicting overall disease burden. Similarly, the Nagelkerke pseudo-R2 indicates more variability explained by socioeconomic variables. Compared to the full model (R2 = 0.51), the R2 slightly declined when removing PC1env (R2 = 0.48), PC1soc (R2 = 0.46), or PC2soc (R2 = 0.49) from the model, but declined more when removing Over65 (R2 = 0.27), or PC1soc and PC2soc in combination (R2 = 0.44). These results suggest that whereas environmental hazard and socioeconomic vulnerability both contribute, socioeconomic vulnerability is more important than environmental hazard for explaining disease burden at the zip code scale.∆BIC > 2 and individual parameter Our study results support the use of CalEnviroScreen as a census tract scale indicator of environmental health hazard and vulnerability. The CalEnviroScreen numeric score was strongly associated with the first principal components in all analyses, indicating that it represents the primary underlying gradients within the data set. Additionally, the spatial patterns in the first principal components matched those of the CalEnviroScreen combined indicators and numeric score. Further, the principal components from the CalEnviroScreen exposure and vulnerability variables were significantly associated with our estimate of disease burden, which is a general indicator of health care burden. Models that contained these variables, and also accounted for spatial autocorrelation and proportion of population that was over 65, explained approximately 50% of the variation in the underlying data. Given all of the uncertainty and assumptions with the study data and scale, this suggests that the CalEnviroScreen data includes multiple exposure hazards and socioeconomic vulnerability indicators, which in combination influence burden of disease. Our analysis, therefore, suggests that CalEnviroScreen is an appropriate tool for its intended purpose: to identify vulnerable communities for resource allocation in environmental health restoration .The first few principal components explained limited variance in the underlying data set, and many of the parameters, especially environmental exposure measures, were weakly correlated. Similar to our results, Lalloué et al.  observedThe limited variability explained by the first few principal components further suggests that for the 20 hazard parameters captured in CalEnviroScreen 3.0, there will be many exposure, vulnerability, and health outcome combinations that are not fully described by combined multivariate gradients. For example, the negative association of ozone air pollution with groundwater threats and water body impairments is not readily explained but suggests that residents of different regions encounter different exposure hazards. Further examination of the statistical properties and demographic vulnerability of sites exhibiting unique exposure combinations is ongoing. These efforts, performed by local agencies, interest groups, and community-based organizations in evaluating updates to the CalEnviroScreen method , complemThe evaluation and modification of CalEnviroScreen is reflected in the recent release of CalEnviroScreen 3.0, updating much of the data, and attempting to address prior community review comments. In comparison to CalEnviroScreen 2.0, CalEnviroScreen 3.0 added two new indicators , removed a vulnerable age indicator, and retained the other 18 indicators included in this paper . DespiteSome policy interventions may best be geographically targeted using additional information beyond the CalEnviroScreen score itself. Most of the environmental hazards measured were associated with urbanization and industrial activities, and the first environmental PC was strongly associated with population density. Although environmental exposure hazards are often elevated in urban areas , this isWe employed multivariable analytical methods to separate out chemical pollutant exposure hazard versus socioeconomic variation within California. Although environmental hazards and socioeconomic vulnerabilities are often correlated through complex causal pathways, and low income communities often face disproportionate environmental exposures , our mul2) suggest a stronger association of disease burden with socioeconomic status than with environmental pollution exposure. This was also evident in the greater correlation of individual socioeconomic variables with cardiovascular disease, asthma, and low birth weight. This supports the paradigm that underlying population vulnerability, resulting from socioeconomic conditions, must be considered in health risk assessment [The association of the disease burden variable with both socioeconomic principal components but only one environmental principal component, as well as the greater combined contribution to variability explained  between PM2.5  and emergency visits for asthma  employing CalEnviroScreen census tract data in six Sacramento, CA region counties. Especially, studies are needed combining longitudinal data sets of disease occurrence with CalEnviroScreen and other hazard measures [Like all census-tract-scale studies of publicly available spatial exposure and health data, this study has limitations. For their similar study of the San Joaquin Valley region, Huang and London  eloquentmeasures .Previous studies at similar spatial scales and resolutions have established relationships of environmental hazards and disease risk with race and socioeconomic status, with implications for resource allocation and policy , 24, 60.We observed that socioeconomic indicators were associated with each other and contributed to explaining disease burden, and that an environmental gradient of urban and industrial pollution also contributed to explaining disease burden. Ground-level ozone and drinking water threats were negatively associated with impaired water bodies and groundwater threats. Some of these findings corroborate findings from the preliminary analysis for CalEnviroScreen development using 30 zip codes by Meehan August et al. . The exiAdditional file 1:Supporting information . Includes the following: methods for spatial joining of CalEnviroScreen versus hospital data; correlation of variables in ICD-9 hospital data (text and Table S2); study variables description (Table S1); scatterplot matrix of hospital visit rate parameters ; total hospital ICD-9 codes vs. total population ; and scatterplot matrix of socioeconomic variables . (PDF 1699 kb)


This survey was designed as the first step in the development of a welfare assessment framework with the aim of identifying potential causes of welfare compromise and useful indicators for sheep in extensive Australian production systems. We asked the general public, sheep producers, service providers and sheep industry related scientists to provide their thoughts on the importance of a range of sheep welfare issues and possible key indicators. All respondents thought sheep welfare was adequate but that improvement was desired. Issues perceived to cause the most risk to sheep related to factors influenced by the environment , heat stress and lameness while key indicators useful to assess welfare were nutrition and food availability, mortality/management issues, pain and fear related indicators, and numbers of illness/injuries. Women and the general public perceived all issues and indicators to be more important than other groups of respondents. These results highlight the need to consult a wide range of stakeholders in order to develop a broadly acceptable assessment system.p < 0.05). Environmental issues were considered to pose the greatest risk to welfare (3.87/5), followed by heat stress (3.79), lameness (3.57) and husbandry practices (3.37). Key indicators recognised by all respondents were those associated with pain and fear (3.98/5), nutrition (4.23), mortality/management (4.27), food on offer (4.41) and number of illness/injures in a flock (4.33). There were gender and stakeholder differences in the perceived importance of both welfare issues and indicators with women and the public consistently rating issues  and indicators  to be of greater significance than other respondents. These results highlight the importance of including all stakeholders and an even balance of genders when developing a welfare framework that can address both practical and societal concerns.An online survey was designed to form the basis of a framework for the welfare assessment of extensively managed sheep in Australia. The survey focused on welfare compromise and useful welfare indicators. A total of 952 people completed the survey in its entirety, representing four stakeholder groups: Public (53.6%), Producer (27.4%), Scientist (9.9%), and Service provider (9.1%). Animal welfare was considered to be important by all participating groups in this survey (average score of 3.78/4). Respondents felt the welfare of grazing sheep was generally adequate but improvement was desired (2.98/5), with female members of the public rating sheep welfare significantly worse than other respondents ( Extensive sheep production systems differ considerably from more intensive systems and sheep tend to be maintained on pasture outdoors year round and provided supplementary feed as required. The welfare of sheep in these systems is generally considered to be high . This isHowever, the extensive management that creates a positive perception of sheep welfare may also create welfare risks. Extensively managed sheep are at risk of climatic extremes, predation and variable nutrition. Their contact with humans can be limited, and so any contact that does occur is likely to be associated with fear and distress, and this also reduces the ability to identify and treat health problems ,2. One cThe scientific assessment of animal welfare provides objective evidence about what an animal is experiencing, has experienced or is likely to experience. While such assessment is complex, decisions about what are acceptable levels of animal welfare require ethical judgements that underlie determining what is the “right” or “wrong” way to treat an animal . A varieSurveys about extensively managed sheep have been conducted on individual stakeholders ,15,16, aWith this in mind, the current study was designed to form the basis of a comprehensive framework for the welfare assessment of extensively managed sheep in Australia, thus adding to the work outlined above. We did so by surveying interested stakeholders to identify what they considered to be the important risks to sheep welfare and key indicators of welfare state. Based on previously published evidence, it was hypothesised differences would exist between stakeholder groups ,17,18. HThis study received ethics approval from the University of Melbourne’s School of Land and Environment Human Ethics Advisory Group on 14-11-2014 (Ethics ID: 1443082).n = 3), industry advisors (2), sheep extension officers (2) and sheep producers (3). The survey was conducted online and was developed using the online survey platform Survey Monkey [A large survey was conducted to obtain information about people’s perceptions of extensively farmed sheep in Australia. The final format of the survey was determined through extensive consultation with an advisory group of 10 that comprised experienced animal welfare scientists  news bulletin  to the Facebook pages of RSPCA Australia  and to 15 research institutions/universities/state government agricultural organisations.All data were managed and analysed using the statistical program R  . Before Principal Components Analyses (PCA) with Oblimin rotations were used to summarise the 20 welfare issues and the 17 welfare indicators into meaningful components. PCA is widely used to assist in classifying terms that have been measured using Likert scales . The criParametric analyses were used for the Likert Scale data, which is a common way to manage survey data, particularly in the case of composite scores that arise from PCA . AnalyseA total of 1535 people responded to the survey during the month it was open, and 956 of these completed the survey in its entirety. Of these, 15 were under 18 years of age. While the survey was voluntary, the ethics application only covered participants 18 years or over, and so these 15 were removed from the results. The breakdown of the 941 valid participants according to stakeholders was: General public = 499 (53.0%), Producer = 260 27.6%), Scientist = 95 (10.1%), and Service provider = 87 (9.2%). The genders of the respondents were skewed towards women , and a difference within each stakeholder category existed; the percentages of women represented in each group were: 27% for producers, 45% scientists, 25% service providers and 88% general public. The majority (70%) of survey respondents were tertiary educated,  and then Victoria (27.6%), South Australia (15.3%), Western Australia (10.8%), Queensland (9.9%), Tasmania (3.3%), the Australian Capital Territory (1.5%) and the Northern Territory (0.8%); with these proportions being roughly equitable with the overall distribution of the population. The general public, sheep industry service providers and sheep-specific scientists were asked to select their current residential location, with producers all being classified as rural and not included below. The majority of respondents were suburban (27.2%) and 14.2% were rural, followed by urban (11.4%), country town (9.5%), regional city (7.0%), peri-urban (3.5%) and remote (0.3%); which was again roughly equitable with the overall distribution of the population, except for rural respondents, which was higher and reflective of the agricultural focus of this survey.1 = 21.66, p < 0.001; The majority of respondents considered animal welfare to be of major importance and women scored significantly higher than men on this response . Gender differences were noted for all welfare issues , with women consistently considering the risk of welfare compromise to be higher than men  = −0.29, p < 0.001), indicating that as belief about the importance of animal welfare increases, perception of the welfare of grazing sheep decreases. There were no statistically significant relationships between education and animal welfare beliefs (r (955) = −0.056, p = 0.08), or the perception of grazing sheep welfare (r (929) = 0.048, p = 0.88), nor were there for age and animal welfare beliefs (r (952) = 0.015, p = 0.65), or age and the perception of grazing sheep welfare (r (926) = 0.026, p = 0.44).A minor, negative correlation was present between the two welfare belief-related questions , followed by “Mulesing/wrinkle score of the sheep/alternatives to mulesing”  and then “Flystrike” . For position 2 (the second most important welfare issue) the frequent responses were “Mulesing/wrinkle score of the sheep/alternatives to mulesing” , “Environmental comfort”  and “Pain, painful/stressful husbandry practices, stress and pain management” . In position 3 (the third most important welfare issue) the most frequent replies were “Nutrition” , “Predation and predator attacks” , “Pain, painful/stressful husbandry practices, stress and pain management”  and “Environmental comfort” . These open-ended responses were then summarised into 7 categories: disease and illness, environmental, injury and painful husbandry practices, management, nutrition, off-farm and other to enable visual comparisons  the frequent responses were “Live export” . There were significant gender differences between the perceived importance of management issues, food on offer and numbers of illness/injuries , with females consistently rating these welfare indicators as more important than males  with the general public ranking indicators as being more important than other respondent groups  while the pain and fear related indicators had the lowest (3.98 ± 0.03) and the scores were significantly different  respondents provided additional indicators. As these were open-ended responses the terms used and level of detail differed, with some respondents providing more than one indicator. The following comments were commonly perceived as being important welfare indicators: the provision of water (10.9%), improved transport conditions (10.1%), the cessation of/or better control over live export (9.5%), and the provision of shelter and/or shade (9.2%).r (929) = 0.82, p < 0.001). Weak negative correlations were seen between a person’s belief about the importance of animal welfare and their understanding of the sheep meat industry (r (952) = −0.13, p < 0.001) and the wool industry (r (931) = −0.13, p < 0.001). Weak positive correlations were also seen between a person’s belief about the welfare of grazing sheep and their understanding of the sheep meat industry (r (926) = 0.24, p < 0.001) and the wool industry (r (905) = 0.28, p < 0.001). Mean knowledge scores and associated correlations for each stakeholder category are presented separately in Participants were asked to rate their knowledge of the sheep industry. Overall average score for the self-rated understanding of the sheep meat industry was 3.63/5  and the wool industry was 3.58, with a very strong and highly significant correlation between self-rated understanding of both production systems .Respondents from the general public were also asked to rate their level of understanding on some specific sheep management issues . The genThe current study identified stakeholder perceptions of a variety of welfare issues facing extensively managed sheep. Stakeholder differences were present in three key responses: the perception of grazing sheep welfare, the importance of welfare issues (both specified and open-ended) and suitable key welfare indicators. The hypothesis was supported with the general public having a poorer perception of sheep welfare than producers, and the other two stakeholder groups having an intermediate perception. Additionally, there were gender differences throughout the results.Across all groups, all welfare issues and indicators were considered to be important, with average scores across all categories being above the median. These results support the growing body of evidence that animal welfare is of broad societal concern ; howeverA person’s attitude and beliefs are dependent on a variety of demographic, experiential and knowledge factors ,33, and Other attitude modifiers consist of animal attributes, individual human attributes and cultural factors . In thisUnderstanding the role of our survey’s voluntary respondents in shaping societal views around animal welfare is an important step when considering the validity of these results for a broadly accepted welfare framework. Work by Coleman and colleagues  suggesteIn the current study the importance of sheep welfare was endorsed by all stakeholders with all believing it to be of importance, and that there was the capacity for it to be compromised. There was a stakeholder × gender interaction in regard to the respondents’ perception of the welfare of grazing sheep with females from the general public stakeholder category believing welfare to be in more need of improvement than other groups. These findings are likely to be associated with the levels of understanding and knowledge of the general public, differences in perceptions between specific stakeholder groups such as the public and producers  as well When assessing risks to sheep welfare, some commonalities were evident with respondents’ answers to the specified and open-ended questions. Of the specified issues, flystrike, nutrition and predation were considered most likely to compromise a sheep’s welfare, and all of these contribute to the PCA component named “environmental issues”. Participants also identified flystrike, other environmental factors, nutrition and predation to be major risks in the open-ended questions, although these may have been influenced by the specified issues posed in the earlier questions. The perceived significance of these environmental issues supports previous expert and producer studies which have also identified nutrition, predation and other environmental factors as issues that significantly influence the welfare of sheep. ,6,16,38.There was also one very prominent response to the open-ended question, with issues around live export being identified as the single most significant issue facing sheep welfare. Examples of welfare compromise in live-exported sheep have been prominent in the last few years in Australia and have received a significant amount of media coverage. This likely influenced the views of the general public, who offered all responses on live export. While this was not identified as a key issue by the other stakeholder groups in the current survey, the live export of sheep has been previously identified as a significant welfare issue facing the sheep industry in a variety of reviews , industr® (WQ) framework consists of four principles of: good feeding, good housing, good health and appropriate behaviour [The results of the current survey show that the general public considered their understanding of both sheep meat and wool industries, tail docking and crutching/shearing highest, and nutritional requirements, parasite control and lambing the lowest. A survey by Phillips et al.  identifiehaviour . These cThe ranking of welfare indicators showed that, in general, respondents found all listed indicators to be of some use when assessing the welfare of grazing sheep. All 17 of the indicators are found, in various forms, on the list of indicators suggested by a UK based expert group , used inThe general public rated welfare indicators as more important than other stakeholders and an interaction was present between stakeholder and gender for the pain/fear and nutrition related composite scores. The pain/fear stakeholder × gender interaction showed that women from the general public believe this indicator to be more important when compared to other groups. As previously mentioned this corresponds with literature indicating that women place a greater significance on painful procedures in animals and rate occurrences of such procedures as being a significant compromise to welfare ,37. The Welfare indicators are generally identified through a process involving a literature review, discussion with an expert group  and scientific testing ,19. ThisSheep welfare was an important consideration to all stakeholders in this survey, and all issues were perceived to cause some degree of welfare compromise. Welfare issues of key importance to the stakeholders were those relating to environmental issues, heat stress, lameness and husbandry practices. The welfare indicators perceived to be of key importance were those related to nutrition, pain and fear, mortality and management, feed on offer and the number of illness/injuries occurring within a flock. Both gender and stakeholder differences were clear, the most notable were women’s greater concern for welfare and the general public’s concern for off-farm issues. These results highlight the importance of including all stakeholders and an even balance of genders when developing a welfare framework that can address both practical and societal concerns.


Fourier transform infrared spectroscopy confirmed the existence of hydrogen bonding between the poly(ethylene oxide) segment of F127 and the OH groups of the DGEBA resin. Small-angle X-ray scattering, atomic force microscopy, and transmission electron microscopy all revealed evidence for the microphase separation of F127 within the epoxy resin. Glass transition temperature (Tg) phenomena and mechanical properties (modulus) were determined through differential scanning calorimetry and dynamic mechanical analysis, respectively, of samples at various blend compositions. The modulus data provided evidence for the formation of wormlike micelle structures, through a RIMPS mechanism, in the flexible epoxy resin upon blending with the F127 triblock copolymer.In this study, we used diglycidyl ether bisphenol A (DGEBA) as a matrix, the ABA block copolymer poly(ethylene oxide– Epoxy resins have good mechanical integrity, high thermal stability, ready processability, good chemical resistance to solvents and moisture, and exceptional adhesion to many materials. In industry, the versatility in their formulations makes epoxy resins convenient to use and widely applicable—for example, in surface coatings, painting materials, adhesives, composites, insulating materials for electrical devices, and encapsulates for semiconductors ,2. One dIn recent years, many attempts have been made to enhance the toughness of crisp epoxy resins through the self-assembly of amphiphilic block copolymers that form ordered or disordered nanostructures within thermoset polymers ,16,17,18b–propylene oxide–b–ethylene oxide) . We expected that the OH groups of diglycidyl ether bisphenol A (DGEBA) would hydrogen bond primarily with the ether groups of the PEO segment of F127 at relatively low DGEBA concentrations, but would hydrogen bond with the ether groups of both the PEO and poly(propylene oxide) (PPO) blocks at relatively higher DGEBA resin concentrations, most likely forming a series of composition-dependent nanostructures  hydrogen bonds with the PEO segment appeared at 3275 cm−1 [···ether] > [OH···OH].Gradually upon increasing the concentration of the triblock copolymer F127. Sharp peaks centered at 3373 and 3245 cm275 cm−1 , suggest−1, respectively; furthermore, the signals of the ether groups of the PEO and PPO block segments hydrogen bonded to the OH groups of DGEBA were noted at 1090 and 1082 cm−1, respectively [−1, representing the free ether groups of the PEO and PPO block segments. This peak shifted to relatively higher wavenumber upon decreasing the DGEBA concentration. When the ether groups interacted through hydrogen bonding with the OH groups of DGEBA, the electron density of the ether oxygen atoms decreased, resulting in a signal shift to lower wavenumber. The main peak of the ether shifted from 1110 to 1105 cm−1 and became sharp when the DGEBA concentration was increased. Moreover, a shoulder signal arose at 1074 cm−1 upon increasing the DGEBA concentration; this signal represented the ether groups of the PPO segment hydrogen bonded with the OH groups of the DGEBA resin.ectively . In addiTg) of the pure polymers of the PEO and PPO block segments were both approximately −62 °C; that of the epoxy resin used in this study was approximately 165 °C. Tg of PEO and PPO are very close, we could not determine the miscibility between PEO and PPO using one or two values of Tg. The one value of Tg of PEO shifted to higher values upon increasing the content of epoxy resin from 30 to 70 wt %. This value of Tg presumably arose from the epoxy/PEO phase, because the strength of inter-association between the epoxy OH groups and the PEO ether groups was greater than the strength of inter-association between the epoxy OH groups and the PPO ether groups. Tg for the epoxy resin/F127 blend; these values were higher than those predicted using the Fox rule. Next, we used TEM, SAXS, AFM, and DMA analyses to investigate the morphological transformations, self-organized structures, and mechanical properties of these immiscible epoxy/F127 blends.The samples were heated to form bulk thermoset materials of epoxy/F127 blends. DSC has been used extensively to investigate miscibility behavior in polymer blends. The glass transition temperatures (d-spacings, based on the Bragg equation. The profile of the pure triblock copolymer F127 revealed lamellar character, as determined by the specific ratio of q* and 2q* [q*, 31/2q*, and 2q* at epoxy resin contents of 30 and 40 wt %, corresponding to the long period of hexagonally packed cylinders. Further increasing the epoxy resin content led to a phase transfer with different peaks in a ratio of q* and 2q* and an increased d-spacing. Furthermore, the profile of epoxy/F127 = 70/30 featured peaks in the ratio q*, 31/2q*, and 2q*, with a decreased d-spacing, due to incomplete disordering of the hexagonal cylinders in this blend system. We recorded SAXS profiles  of the e and 2q* . We obseTg of the epoxy resin was approximately 180 °C (Tg of the PPO segment, which we could not determine in the DSC analyses, was in the approximate range from −55 to −60 °C and independent of the epoxy resin content. In addition, the samples soften increased temperature larger than Tg (epoxy resin/F127 blend from DSC, et al. investigated the impact of different nanostructures on the mechanical properties of thermoset blends with block copolymers [9 Pa when the epoxy resin content was less than 50 wt % at 25 °C. y 180 °C f; the vapolymers . The toupolymers . Figure We have prepared flexible epoxy resins through a RIMPS mechanism upon blending with the triblock copolymer F127. We have used FTIR spectroscopy, DSC, SAXS, TEM, AFM, and DMA to investigate the miscibility, self-assembly behavior, hydrogen bonding interactions, and mechanical properties of the resulting epoxy resin/F127 triblock copolymer blends. FTIR spectroscopy provided evidence that the ether groups of the PEO and PPO segments functioned as hydrogen bond acceptors for the OH groups of the DGEBA epoxy resin. The SAXS data and TEM and AFM images revealed the presence of different microphase-separated structures within the epoxy resin/F127 blends at various compositions, each mediated through hydrogen bonding interactions. DSC and DMA provided thermal and mechanical data for these blends. We observed evidence for the formation of flexible epoxy resins as a result of wormlike micelles, with a high aspect ratio and an optimal length scale, of F127 acting as the second phase, resulting in greater toughness. The modulus data provided evidence for the wormlike micelles forming, through RIMPS, flexible thermosetting materials from the epoxy resin/triblock copolymer F127 blends.


Terminologies of ovary development, by somewhat subjective describing and naming main changes of oocytes, have been criticized for confusing and inconsistency of terms and classifications, and the incurred consequences impede communication among researchers. In the present work, we developed regression between ovary development and three ribosome RNA (rRNA) indexes, namely 5S rRNA percent, 18S rRNA percent, and 5S–18S rRNA ratio, using close relationship between volume percent of primary growth stage oocytes or gonadosomatic index and rRNA content, demonstrating species-specific quantification of ovary development can be established in species with either synchronous and asynchronous oogenesis. This approach may be extended to any species with primary growth oocytes, e.g. anurans and reptiles, to predict maturity stages in females. We further confirmed that 5S rRNA percent and 5S/18S rRNA ratio can serve as markers to distinguish sexes unambiguously. A micro-invasive sampling method may be invented for non-lethal prediction of ovary development and sex because only a small amount of ovary sample (<50 mg) is needed for the approach established in the current work. Researchers who work with ovary RNA-seq in these taxa should realize that insufficient depletion of rRNA will probably lead to incorrect quantification of gene expression and inaccurate conclusions. Once primordial germ cells differentiated into either female or male germ cells, they will undergo gametogenesis, reach full maturation, and be ready for fertilizing, along with a series of complex molecular and endocrine changes. In the process of gametogenesis, oocytes and spermatocyte undergo significantly diverse molecular, cellular, and structural changes. Particularly, the oocytes increase size by hundreds of times and accumulate reserve substances, e.g. RNAs, proteins, lipids, carbohydrates, vitamins, and hormones, which are indispensable for proper development of the embryo5. One of these molecules involved considerably in oogenesis is 5S ribosome RNA (5S rRNA). In the oocytes of some amphibian and teleost species, rDNA is amplified ≈1,000-fold and 5S rRNA and transfer RNA (tRNA) constituted more than 90% of the RNA content approximately at the end of primary growth or early cortical alveolus stage9.Sex differentiation, which is triggered by sex-determining factors, is to indicate the physical realization of the events in terms of ovarian or testicular development, including morphological, cellular, and molecular aspects11. However, its precise function remains unknown. Intriguingly, two different types of 5S rRNA genes with several sequence variations have been discovered in Xenopus laevis: one is only expressed in oocytes and the other in both somatic cells and gonads12. A similar pattern with two paralogue genes has been found in several fish species13. Specifically, only oocyte 5S rRNA accumulated in ovaries. The oocyte 5S rRNA undergoes considerable mobilization and decreases to baseline level when oocytes enter vitellogenesis and this massive amount of 5S rRNA is incorporated into the ribosomes in the amplified nucleoli15.The 5S rRNA was discovered as early as in 1963 and has been studied for RNA-protein interactions and used as a phylogenetic tool for several decadesTinca vulgaris and T. tinca7. This interesting feature then has been overlooked. 5S rRNA in fish ovaries has not received attention, until recently, probably due to the booming development of Real-time PCR (RT-PCR) and RNA-seq and their application in biological research in the past decade. The RNA integrity number (RIN), an index for assigning integrity values to RNA measurement combining different features of rRNAs obtained from microcapillary electrophoresis, has served as a “standard” for RNA quality control16 since it has been established. The “abnormal” feature of 5S rRNA in developing ovaries, however, confused many researchers at the beginning because it has been difficult to obtain expected high RIN from developing ovaries, as we obtained from developed ovaries, different stages of testes and somatic tissue samples. The overwhelming accumulation of 5S rRNA in either gonochoristic developing ovaries or hermaphroditic sex-changing gonads in electrophoresis, has been reported or mentioned in several studies regarding RT-PCR and RNA-Seq20, indicating it is a general feature in gonads with primary growth oocytes in fish, reptiles and anurans. In addition, there are indications that ovary 5S rRNA profiling could be applied in the identification of sex, ovarian development, reproductive endocrine disruption19. Changes of 18S rRNA were also observed in fishes and amphibians21.The dynamic feature of oocyte 5S rRNA during oogenesis had been studied in some fish species in the 1970s, e.g. However, how accurate are the rRNA features in sex identification and evaluation of ovary development? Does it work for species displaying asynchronous or synchronous ovaries? With these questions, plus our experience, the objectives of the present study are to: (1) develop an approach for sex identification and oogenesis stage determination in fish with asynchronous or synchronous ovaries using rRNA profiling and evaluate the accuracy; (2) alert researchers who are working on ovary transcriptomics in fish, anurans, and reptiles that incorrect depletion of rRNA, especially the mass accumulated 5S rRNA in developing ovary, may lead to misassembly and incorrect quantification of gene expression.19. Pearson correlation analysis indicates the consistency between the two indexes 5S rRNA/total RNA and 5S/18S rRNA, with correlation coefficient r = 0.947 (P < 0.001), 0.975 (P < 0.001), 0.986 (P < 0.001) in yellow perch, bluegill, and largemouth bass, respectively.RNA integrity index (RIN) ranged between 8.4 to 10 for testis samples, and under detectable level (1) to 10 for ovary samples. No signs of RNA degradation were observed in any of the samples from either regular electrophoresis or chip run in Agilent 2100 Bioanalyzer. A distinctive band with peak size between 130–145 bp were observed without exception, in all samples including gonad, brain, and liver in five studied species, yellow perch, bluegill, largemouth bass, channel catfish, and Nile tilapia. The band, constituted up to 98.77% of the total RNA content in the transcriptome of ovaries as measured in the electropherograms  before spawning season (March for yellow perch), but not at the later month Fig. . The 18SIn species with asynchronous oocyte development, 5S rRNA/total RNA and 5S/18S rRNA indexes can distinguish females from males unambiguously from early gonadal development up to gonadal maturation Fig. . The 18S2 = 0.958), and quadratic regression between Ln(5S/18S rRNA) or 18S rRNA/total RNA % and GSI  in yellow perch females , followed by between 18S rRNA/total RNA % and GSI (R2 = 0.736), and between Ln(5S/18S rRNA) and GSI (R2 = 0.693)  when female and male samples were analyzed separately. We then further examined whether a given rRNA content can be used to estimate the GSI. Results showed a good linear regression between Ln and GSI R = 0.958,The percentage was highest for 5S rRNA (98.77% for yellow perch and 68.58% for bluegill) and lowest for 18S rRNA (0.09% for yellow perch and 5.87% for bluegill) when ovaries are mainly composed of primary growth stage oocytes ; the opposite results were observed when ovaries were close to maturation Fig. . FurtherTotal RNA electropherograms of ovary samples in Channel catfish (6) and Nile tilapia (4), corresponding rRNA profiling and histological images can be found in Supplementary Figure No signs of RNA degradation were observed in any of the samples from either regular electrophoresis or chip run in Agilent 2100 Bioanalyzer. RNA integrity number (RIN) indicates the high quality of RNA from both brain and liver samples , while the 5S–18S rRNA ratio and 18S rRNA percent in brain tissue were significantly higher than liver in both species . Thanks to the technology combination of microfluidic chips, voltage-induced size separation in gel-filled channels, and laser-induced fluorescence detection on a miniaturized scale, Agilent 2100 bioanalyzer is capable of sizing and quantitation of RNA fragments in a high resolution27.The RIN has been considered the standard to evaluate total RNA quality, especially for studies that involve sequencing19. We found that in species with asynchronous oogenesis , either 5S rRNA percent or 5S/18S rRNA can be used to distinguish females from males unambiguously from very early stages of gonad development up to near maturation in bluegill and largemouth bass  and established significant regression with rRNA content , Ln(5S/18S rRNA), or 18SrRNA/total RNA% and ovary development (represented by GSI). The trends of regression were similar between species with synchronous and asynchronous oogenesis for all these three indexes, while the regression estimate was higher for synchronous ovaries than asynchronous ovaries Fig. . While Gent Fig. . It is ring Fig. . The tim34. Researchers criticized that “ovarian terminology is confusing” three decades ago35; nevertheless, the criticism is still relevant34. A major emphasis of a series of workshops on gonadal histology of fishes, including more than 30 papers, has been the development of terminology to describe the reproductive classification of fishes, due to the inconsistency and confusion34. Attempts to build up standardization and consistency into the reproductive classification in the past had not met researchers’ expectations, and the new classification system is still limited to describing and naming major phases during the fish reproductive cycle36. In addition, a diverse group of scientists, including fishery biologists, fishery managers, ecologists, physiologists, toxicologists, environmental biologists, endocrinologists, development biologists, and aquaculturists all work with reproductive biology in both marine and freshwater fishes. Some of them need a unified terminology that addresses morphological and cellular changes, while others may be interested in physiological processes. Therefore, a consistent, simple, and quantitative terminology is urgently needed.Traditionally, identification of the oogenesis stage in fish is dependent on a somewhat subjective description obtained from laborious histology and macroscopic observation23. While in these studies, electrophoresis analysis of RNA quality should be the indispensable procedure. Further, evaluation of fish fecundity, population sex ratio, and/or ovarian development are essential for various studies, such as fisheries, ecology, reproductive biology, sex determination and sex differentiation; traditionally it requires a considerable amount of samples for histological analysis39. Therefore, the approaches established for identification of sexes and quantification of ovary development in the current work, provide a low-cost, simple, and robust solution for these studies.In addition, as the increasing of accessibility of RNA sequencing, a lot of studies are addressing molecular mechanisms involved in gonadal development, markers of egg quality and embryo viability, maternal genes, molecular pathways of sexual size dimorphism, etc. In such studies, obtaining enough RNA samples, identifying sex and/or gonadal development stage from a gonad sample of the same individual are frequently required. However, there is not enough gonad tissue for both RNA isolation and histological analysis, especially during early gonadal developmentXenopus laevis long time ago40, while the other two have never been documented and the basics of dynamic variation of either 5S or 18S rRNA in gonad and somatic tissues are absolutely unknown.In the present work, we found that 18S rRNA percent in ovaries underwent dramatic increase from 0.04% to about 33% (close to the level in somatic tissue) during ovary development. We also discovered that in species with synchronous oogenesis, both 5S and 18S rRNA in testes displayed similar trends of variation as the trends observed in the ovaries Fig. . Interes26, while the precise function of 5S rRNA in protein synthesis is not fully understood41. Two types of 5S rRNA genes, designated as oocyte (or ovary) 5S rRNA and somatic 5S rRNA, have been discovered in many fish and anurans13. Oocyte 5S rRNA is expressed in oocytes while somatic 5S rRNA is found in both somatic cells and gonads. Intriguingly, only oocyte 5S rRNA accumulated and then disappeared in ovaries12. Previous reports suggested that synthesis of 5S rRNA reached a peak at late primary growth or the early cortical alveolus stage (previtellogenesis stage), and was incorporated progressively into ribosomes when the oocytes enter vitellogenesis25. Our data showed that 5S rRNA percent was the highest when ovaries only consist of primary growth stage oocytes in both fish species with synchronous and asynchronous oogenesis  accumulated in excess during the primary growth stage are stored as nucleoprotein particles, and are still present in the fertilized egg and in the developing embryoThe dynamic changes of 5S and 18S rRNA during the development of testis probably associated with protein synthesis in spermatogenesis as in oogenesis. As displayed in Fig. 18S rRNA gene, which has been used as an internal control for gene expression normalization more than a thousand times , should not be used as an internal control for any gene expression studies because of its variation in gonadal and somatic tissues.Changes of rRNA in brain and liver tissue as the gonads develop suggest their participation in oogenesis and spermatogenesis. The 46, if they are not correctly depleted, as we experienced for data generated from developing/resting ovaries. In one of our recent work47, the coverage (expressed as a number of raw reads) for samples from resting ovary (right after spawning) was only about a half for samples from testis or muscle , Ln(5S/18S rRNA), or 18SrRNA/total RNA%] and ovary development stages can be established and utilized as a reference for future prediction of ovary maturity in females. Especially, significant regression between rRNA content and volume percent of PGOO or GSI suggest that ovary development/maturity could be quantified. The confusing and inconsistency of terminology for ovary development may be resolved when this approach is utilized in a considerate amount of species. Meanwhile, laborious histology work can be largely reduced. The regression between testicular development and rRNA content deserves further investigation because the similar regression pattern in testes and ovaries indicate the importance of rRNA accumulation in reproductive success in both females and males. Researchers who work with ovary RNA-seq should realize that insufficient depletion of rRNA will probably lead to incorrect quantification of gene expression and inaccurate conclusions.This study and all experimental procedures involving animals were performed according to the protocol approved by the Ohio State University Institutional Animal Care and Use Committee.Perca flavescens) with synchronous oocyte development, and bluegill (Lepomis macrochirus) with asynchronous oocyte development. Yellow perch, bluegill, and Nile tilapia (Oreochromis niloticus) were obtained from the breeding center of The Ohio State University South Centers. Largemouth bass  and Channel catfish  were purchased from a local commercial fish hatchery. Following anesthetization using MS-222 and measurement of body weight, total length, and gonad weight, gonads of all individuals were dissected and divided into two parts. One part of the gonad was embedded in RNAlater® Stabilization Solution  and kept at 4 °C overnight and then stored at −80 °C until further analysis. The other part was fixed in Prefer  for histological analysis. Goandosomatic index (GSI) is expressed as percent of gonad weight relative to total body weight. Livers and brains were also collected and stored in RNAlater for further analysis.Five major aquaculture species were used for this study, with emphasis on two species: yellow perch  following the manufacturer instructions. Isolated RNA samples were evaluated by Nanodrop 1000  for concentration and by Agilent RNA 6000 Nano Kit Bioanalyzer  for capillary electrophoresis. Generated data were analyzed using Agilent 2100 Expert (free version B.02.08.SI648). The electropherograms generated in Agilent 2100 Bioanalyzer permit fast identification and quantification of 5S, 18S and 28S rRNA, and further comparative analysis. In the current case, as shown in Supplementary Figure 56 with extended time for ovary samples. Tissue slices were examined and photographed under a light microscope with an imaging system . At least four cuttings from two slices were analyzed from each individual. Oocytes were considered as oblate ellipsoid and volumes were calculated using the following formula: Oocyte volume = πab2/8, where a and b are long and short axises of oocytes respectively. Each oocyte which displayed a nucleolus was measured and counted from each cutting. Critical size points (long axis) for primary growth oocytes are 184 and 174 µm for yellow perch and bluegill respectively, according to species-specific measurement in histological images and criteria by McMillan4.Gonad tissues were transferred into 70% ethanol, gradually dehydrated, cleared, embedded in paraffin, cut at 5–7 µm, stained with hematoxylin, counterstained with eosin, and mounted, following routine histological proceduresP < 0.05).Data were analyzed using the SPSS program version 19. The correlation was estimated using two-tailed Pearson correlation. Best regression was obtained through comparing models generated using Curve Estimation. Data sets were checked for variance homogeneity and normality before further analysis. A t-test was applied to analyze the difference of rRNA percent in brain and liver. Significance was indicated at a 5% level (Dataset 1