Higher Mortality Is Not a Universal Cost of Dispersal: A Case Study in African Wild Dogs.

AbstractMortality is considered one of the main costs of dispersal. A reliable evaluation of mortality, however, is often hindered by a lack of information about the fate of individuals that disappear under unexplained circumstances (i.e., missing individuals). Here, we addressed this uncertainty by applying a Bayesian mortality analysis that inferred the fate of missing individuals according to information from individuals with known fate. Specifically, we tested the hypothesis that mortality during dispersal is higher than mortality among nondispersers using 32 years of mark-resighting data from a free-ranging population of the endangered African wild dog (Lycaon pictus) in northern Botswana. Contrary to expectations, we found that mortality during dispersal was lower than mortality among nondispersers, indicating that higher mortality is not a universal cost of dispersal. Our findings suggest that group living can incur costs for certain age classes, such as limited access to resources as group density increases, that exceed the mortality costs associated with dispersal. By challenging the accepted expectation of higher mortality during dispersal, we urge for further investigations of this key life history trait and propose a robust statistical approach to reduce bias in mortality estimates.

Combining accelerometry with allometry for estimating daily energy expenditure in joules when in-lab calibration is unavailable.

BACKGROUND: All behaviour requires energy, and measuring energy expenditure in standard units (joules) is key to linking behaviour to ecological processes. Animal-borne accelerometers are commonly used to infer proxies of energy expenditure, termed 'dynamic body acceleration' (DBA). However, converting acceleration proxies (m/s2) to standard units (watts) involves costly in-lab respirometry measurements, and there is a lack of viable substitutes for empirical calibration relationships when these are unavailable. METHODS: We used past allometric work quantifying energy expenditure during resting and locomotion as a function of body mass to calibrate DBA. We used the resulting 'power calibration equation' to estimate daily energy expenditure (DEE) using two models: (1) locomotion data-based linear calibration applied to the waking period, and Kleiber's law applied to the sleeping period (ACTIWAKE), and (2) locomotion and resting data-based linear calibration applied to the 24-h period (ACTIREST24). Since both models require locomotion speed information, we developed an algorithm to estimate speed from accelerometer, gyroscope, and behavioural annotation data. We applied these methods to estimate DEE in free-ranging meerkats (Suricata suricatta), and compared model estimates with published DEE measurements made using doubly labelled water (DLW) on the same meerkat population. RESULTS: ACTIWAKE's DEE estimates did not differ significantly from DLW (t(19) = - 1.25; P = 0.22), while ACTIREST24's estimates did (t(19) = - 2.38; P = 0.028). Both models underestimated DEE compared to DLW: ACTIWAKE by 14% and ACTIREST by 26%. The inter-individual spread in model estimates of DEE (s.d. 1-2% of mean) was lower than that in DLW (s.d. 33% of mean). CONCLUSIONS: We found that linear locomotion-based calibration applied to the waking period, and a 'flat' resting metabolic rate applied to the sleeping period can provide realistic joule estimates of DEE in terrestrial mammals. The underestimation and lower spread in model estimates compared to DLW likely arise because the accelerometer only captures movement-related energy expenditure, whereas DLW is an integrated measure. Our study offers new tools to incorporate body mass (through allometry), and changes in behavioural time budgets and intra-behaviour changes in intensity (through DBA) in acceleration-based field assessments of daily energy expenditure.

Assessment of PSIM (Prostatic Systemic Inflammatory Markers) Score in Predicting Pathologic Features at Robotic Radical Prostatectomy in Patients with Low-Risk Prostate Cancer Who Met the Inclusion Criteria for Active Surveillance.

BACKGROUND: circulating levels of lymphocytes, platelets and neutrophils have been identified as factors related to unfavorable clinical outcome for many solid tumors. The aim of this cohort study is to evaluate and validate the use of the Prostatic Systemic Inflammatory Markers (PSIM) score in predicting and improving the detection of clinically significant prostate cancer (csPCa) in men undergoing robotic radical prostatectomy for low-risk prostate cancer who met the inclusion criteria for active surveillance. METHODS: we reviewed the medical records of 260 patients who fulfilled the inclusion criteria for active surveillance. We performed a head-to-head comparison between the histological findings of specimens after radical prostatectomy (RP) and prostate biopsies. The PSIM score was calculated on the basis of positivity according to cutoffs (neutrophil-to-lymphocyte ratio (NLR) 2.0, platelets-to-lymphocyte ratio (PLR) 118 and monocyte-to-lymphocyte-ratio (MLR) 5.0), with 1 point assigned for each value exceeding the specified threshold and then summed, yielding a final score ranging from 0 to 3. RESULTS: median NLR was 2.07, median PLR was 114.83, median MLR was 3.69. CONCLUSION: we found a significantly increase in the rate of pathological International Society of Urological Pathology (ISUP) ≥ 2 with the increase of PSIM. At the multivariate logistic regression analysis adjusted for age, prostate specific antigen (PSA), PSA density, prostate volume and PSIM, the latter was found the sole independent prognostic variable influencing probability of adverse pathology.

Cost of dispersal in a social mammal: body mass loss and increased stress.

Dispersal is a key process influencing the dynamics of socially and spatially structured populations. Dispersal success is determined by the state of individuals at emigration and the costs incurred after emigration. However, quantification of such costs is often difficult, due to logistical constraints of following wide-ranging individuals. We investigated the effects of dispersal on individual body mass and stress hormone levels in a cooperative breeder, the meerkat ( Suricata suricatta). We measured body mass and faecal glucocorticoid metabolite (fGCM) concentrations from 95 dispersing females in 65 coalitions through the entire dispersal process. Females that successfully settled lost body mass, while females that did not settle but returned to their natal group after a short period of time did not. Furthermore, dispersing females had higher fGCM levels than resident females, and this was especially pronounced during the later stages of dispersal. By adding information on the transient stage of dispersal and by comparing dispersers that successfully settled to dispersers that returned to their natal group, we expand on previous studies focusing on the earlier stages of dispersal. We propose that body mass and stress hormone levels are good indicators to investigate dispersal costs, as these traits often play an important role in mediating the effects of the environment on other life-history events and individual fitness.

Cell-cycle Progression-score Might Improve the Current Risk Assessment in Newly Diagnosed Prostate Cancer Patients.

OBJECTIVE: To assess whether cell-cycle progression (CCP)-score (Prolaris) can improve the current risk assessment in newly diagnosed prostate cancer (PCa) patients. CCP-score is a well-validated prognostic assay predictive of PCa death, biochemical recurrence, and progression. METHODS: We evaluated CCP-score at biopsy in 52 patients newly diagnosed with PCa who underwent radical prostatectomy. CCP-score was calculated as average RNA expression of 31 CCP genes, normalized to 15 housekeeping genes. The predictive ability of CCP-score was assessed in univariate and multivariate analyses, and compared to that of Ki-67 levels and traditional clinical variables including prostate-specific antigen, Gleason score, stage, and percentage of positive cores at biopsy. RESULTS: In spite of an overall good accuracy in attributing the correct risk class, 7 high-risk and 13 intermediate-risk patients were misclassified by the Prolaris test. On analysis of variance, mean CCP-score significantly differed across different risk classes based on pathologic results (-1.2 in low risk, -0.444 in intermediate risk, 0.208 in high risk). CCP-score was a significant predictor of high-risk PCa both on univariate and multivariate analyses, after adjusting for clinical variables. Combining CCP-score and the European Association of Urology clinical risk assessment improved the accuracy of risk attribution by around 10%, up to 87.8%. CCP-score was a significant predictor of biochemical recurrence, but only on univariate analysis. CONCLUSION: The CCP-score might provide important new information to risk assessment of newly diagnosed PCa in addition to traditional clinical variables. A correct risk attribution is essential to tailor the best treatment for each patient.

Confirmatory biopsy for the assessment of prostate cancer in men considering active surveillance: reference centre experience.

OBJECTIVES: To evaluate how accurate a 12-core transrectal biopsy derived low-risk prostate cancer diagnosis is for an active surveillance programme by comparing the histological outcome with that from confirmatory transperineal sector biopsy. SUBJECTS AND METHODS: The cohort included 166 men diagnosed with low volume Gleason score 3+3 prostate cancer on initial transrectal biopsy who also underwent a confirmatory biopsy. Both biopsy techniques were performed according to standard protocols and samples were taken for histopathology analysis. Subgroup analysis was performed according to disease severity at baseline to determine possible disease parameters of upgrading at confirmatory biopsy. RESULTS: After confirmatory biopsy, 34% demonstrated Gleason score upgrade, out of which 25% were Gleason score 3+4 and 8.5% primary Gleason pattern 4. Results remained consistent for the subgroup analysis and a weak positive association, but not statistically significant, between prostate specific antigen (PSA), age, and percentage of positive cores, and PCa upgrading at confirmatory biopsy was found. CONCLUSION: In our single centre study, we found that one-third of patients had higher Gleason score at confirmatory biopsy. Furthermore 8.5% of these upgraders had a primary Gleason pattern 4. Our results together with previously published evidence highlight the need for the revision of current guidelines in prostate cancer diagnosis for the selection of men for active surveillance.