Variation In Weddell Seal Pup Mass: Maternal Investment In Offspring

Life history theory predicts that individuals face physiological tradeoffs between current and future reproduction. These tradeoffs ultimately lead to reproductive costs which can affect survival, fecundity, condition of the female and offspring survival. Reproduction itself is costly and involves a number of sequential physiological processes that require different levels of energetic investment. In mammalian species gestation and lactation require the most energy and energy expenditure during these times is a characteristic of females and can vary among individuals. Mass measurements, used to quantify pre- and post-partum maternal investment, were collected from 887 Weddell seal (Leptonychotes weddellii) pups at parturition and throughout lactation in Erebus Bay, Antarctica during the 2002 through 2010 field seasons. Preliminary analysis demonstrated high individual variation in pup mass within a season and modest variation among seasons suggesting that pup mass may be affected more by individual animal attributes than annual variation in environmental conditions. This variation in maternal investment was investigated using maternal traits taken from the long term database. We found that maternal traits have different affects on pup mass at different stages of investment. Maternal age and birth date were found to be influential on pre- and post-partum investment along with age at first reproduction on pre-natal investment and breeding status the previous year on post-natal investment. The variation in the influence of maternal traits on maternal investment may be due to the increased energy requirement of lactation and reproductive costs that females accrue throughout their lifetime

Volatile Compounds in Honey: A Review on Their Involvement in Aroma, Botanical Origin Determination and Potential Biomedical Activities

Volatile organic compounds (VOCs) in honey are obtained from diverse biosynthetic pathways and extracted by using various methods associated with varying degrees of selectivity and effectiveness. These compounds are grouped into chemical categories such as aldehyde, ketone, acid, alcohol, hydrocarbon, norisoprenoids, terpenes and benzene compounds and their derivatives, furan and pyran derivatives. They represent a fingerprint of a specific honey and therefore could be used to differentiate between monofloral honeys from different floral sources, thus providing valuable information concerning the honey’s botanical and geographical origin. However, only plant derived compounds and their metabolites (terpenes, norisoprenoids and benzene compounds and their derivatives) must be employed to discriminate among floral origins of honey. Notwithstanding, many authors have reported different floral markers for honey of the same floral origin, consequently sensory analysis, in conjunction with analysis of VOCs could help to clear this ambiguity. Furthermore, VOCs influence honey’s aroma described as sweet, citrus, floral, almond, rancid, etc. Clearly, the contribution of a volatile compound to honey aroma is determined by its odor activity value. Elucidation of the aroma compounds along with floral origins of a particular honey can help to standardize its quality and avoid fraudulent labeling of the product. Although only present in low concentrations, VOCS could contribute to biomedical activities of honey, especially the antioxidant effect due to their natural radical scavenging potential

The IDENTIFY study: the investigation and detection of urological neoplasia in patients referred with suspected urinary tract cancer - a multicentre observational study.

Funder: Action Bladder Cancer UKFunder: Rosetrees Trust; Id: http://dx.doi.org/10.13039/501100000833Funder: Urology Care Foundation; Id: http://dx.doi.org/10.13039/100006280OBJECTIVE: To evaluate the contemporary prevalence of urinary tract cancer (bladder cancer, upper tract urothelial cancer [UTUC] and renal cancer) in patients referred to secondary care with haematuria, adjusted for established patient risk markers and geographical variation. PATIENTS AND METHODS: This was an international multicentre prospective observational study. We included patients aged ≥16 years, referred to secondary care with suspected urinary tract cancer. Patients with a known or previous urological malignancy were excluded. We estimated the prevalence of bladder cancer, UTUC, renal cancer and prostate cancer; stratified by age, type of haematuria, sex, and smoking. We used a multivariable mixed-effects logistic regression to adjust cancer prevalence for age, type of haematuria, sex, smoking, hospitals, and countries. RESULTS: Of the 11 059 patients assessed for eligibility, 10 896 were included from 110 hospitals across 26 countries. The overall adjusted cancer prevalence (n = 2257) was 28.2% (95% confidence interval [CI] 22.3-34.1), bladder cancer (n = 1951) 24.7% (95% CI 19.1-30.2), UTUC (n = 128) 1.14% (95% CI 0.77-1.52), renal cancer (n = 107) 1.05% (95% CI 0.80-1.29), and prostate cancer (n = 124) 1.75% (95% CI 1.32-2.18). The odds ratios for patient risk markers in the model for all cancers were: age 1.04 (95% CI 1.03-1.05; P < 0.001), visible haematuria 3.47 (95% CI 2.90-4.15; P < 0.001), male sex 1.30 (95% CI 1.14-1.50; P < 0.001), and smoking 2.70 (95% CI 2.30-3.18; P < 0.001). CONCLUSIONS: A better understanding of cancer prevalence across an international population is required to inform clinical guidelines. We are the first to report urinary tract cancer prevalence across an international population in patients referred to secondary care, adjusted for patient risk markers and geographical variation. Bladder cancer was the most prevalent disease. Visible haematuria was the strongest predictor for urinary tract cancer

The IDENTIFY study: the investigation and detection of urological neoplasia in patients referred with suspected urinary tract cancer - a multicentre observational study

Objective To evaluate the contemporary prevalence of urinary tract cancer (bladder cancer, upper tract urothelial cancer [UTUC] and renal cancer) in patients referred to secondary care with haematuria, adjusted for established patient risk markers and geographical variation. Patients and Methods This was an international multicentre prospective observational study. We included patients aged ≥16 years, referred to secondary care with suspected urinary tract cancer. Patients with a known or previous urological malignancy were excluded. We estimated the prevalence of bladder cancer, UTUC, renal cancer and prostate cancer; stratified by age, type of haematuria, sex, and smoking. We used a multivariable mixed-effects logistic regression to adjust cancer prevalence for age, type of haematuria, sex, smoking, hospitals, and countries. Results Of the 11 059 patients assessed for eligibility, 10 896 were included from 110 hospitals across 26 countries. The overall adjusted cancer prevalence (n = 2257) was 28.2% (95% confidence interval [CI] 22.3–34.1), bladder cancer (n = 1951) 24.7% (95% CI 19.1–30.2), UTUC (n = 128) 1.14% (95% CI 0.77–1.52), renal cancer (n = 107) 1.05% (95% CI 0.80–1.29), and prostate cancer (n = 124) 1.75% (95% CI 1.32–2.18). The odds ratios for patient risk markers in the model for all cancers were: age 1.04 (95% CI 1.03–1.05; P < 0.001), visible haematuria 3.47 (95% CI 2.90–4.15; P < 0.001), male sex 1.30 (95% CI 1.14–1.50; P < 0.001), and smoking 2.70 (95% CI 2.30–3.18; P < 0.001). Conclusions A better understanding of cancer prevalence across an international population is required to inform clinical guidelines. We are the first to report urinary tract cancer prevalence across an international population in patients referred to secondary care, adjusted for patient risk markers and geographical variation. Bladder cancer was the most prevalent disease. Visible haematuria was the strongest predictor for urinary tract cancer

Data from: Patterns of age-related change in reproductive effort differ in the pre-natal and post-natal periods in a long-lived mammal

Age-related changes in maternal reproductive allocation for long-lived species are a key prediction from life-history theory. Theoretical and empirical work suggests that allocation may increase with age due to constraint (increases with experience) or restraint (increases with age in the face of declining residual reproductive value), and may decrease among the oldest aged animals due to senescence in reproductive function. Here, we use a hierarchical modelling approach to investigate the age-related patterns of change in maternal reproductive effort in the Weddell seal, a long-lived marine mammal with a protracted period of maternal care during which mothers allocate a large proportion of body mass while feeding little. We find that maternal allocation increases with age for young mothers during both the pre-natal and post-natal periods. In contrast, older mothers demonstrate a senescent decline in pre-natal allocation but allocate more of their declining resources to their offspring during the post-natal period. We also find strong evidence for the importance of individual effects in reproductive allocation among mothers: some mothers consistently produce heavier (or lighter) pups than expected. Our results indicate that maternal allocation changes over a mother's reproductive life span and that age-specific differences differ in notable ways in pre-natal and post-natal periods

Data for pup masses near parturition, and daily gains during early and late lactation

This file contains the data used for models of pup mass near parturition and contains the following columns: PartMass (kg), momAGE.c (maternal ages in years at weighing, centered using the mean), MidGain (kg/day for the first 20 days), LateGain (kg/day for days 20 to 35), Season (year of measurement), DTA (deviation from target age), Female (indicator variable for female), Btime.c (birthdate centered using the mean), Btime.c.sq (square of the previous term), momSPENO (unique identifier for mother), momAGE.c.sq (the square of the previous term), momAGE.log (the log transform of maternal age in years, made by subtracting the minimum age from each animal and adding a small constant), NPrevPup.c (the number of previous pups for each mother, scaled by the average number of pups at each age), PrevState (breeding state the previous season), PartMass.c (parturition mass centered according to the mean)

Data for maternal masses near parturition.

This file contains the data used for models of maternal mass near parturition and contains the following columns: Mass (kg), momAGE.c (maternal ages in years at weighing, centered using the mean), momAGE.c.sq (the square of the previous term), momAGE.log (the log transform of maternal age in years, made by subtracting the minimum age from each animal and adding a small constant), PrevState (breeding state the previous season), NPrevPup.c (the number of previous pups for each mother, scaled by the average number of pups at each age), Season (year of measurement)