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Concise appraisal

This peer-reviewed Veterinary Sciences study measured 30-day integrated cortisol in bristles from 18 nonpregnant female wild boars sampled monthly (January–June 2022; 108 samples) kept in a controlled rearing area and found a strong age effect (F=14.83, p<0.0001): juveniles (G1 <10 months) had higher mean bristle cortisol 3.90 ± 0.21 pg/mg than sub-adults (G2 2.57 ± 0.25) and adults (G3 2.83 ± 0.25), with group differences and month contrasts concentrated early in the monitoring period, interpreted as adaptation to captivity and providing preliminary reference values for welfare monitoringPrimary paper: bristle cortisol in wild boars

Paper Review: Appraisal of Allostatic Load in Wild Boars Under a Controlled Environment

Quick facts

• Publication: Veterinary Sciences, published 16 July 2025 (DOI 10.3390/vetsci12070667)Publication metadata and data access
• Subjects and samples: 18 nonpregnant female wild boars, 108 bristle samples over January–June 2022 (monthly sampling).
• Primary measurement: bristle cortisol (pg/mg) quantified by in-house ELISA after isopropanol washing and steroid extraction.

What the authors did and found

The authors captured wild female Sus scrofa, housed them in a fenced forest rearing and observation area with stable feed and water, and collected bristle samples using a shave-reshave protocol (first cut at arrival; monthly subsequent sampling). Bristle cortisol concentrations integrate retrospective 30-day glucocorticoid production and were measured by an in-house ELISA following established hair/hairlike protocols. Statistical approach used repeated-measures ANOVA with age as fixed effect and sampling month as repeated measure, using R 4.4.3, emmeans post-hoc testing, and visualization with ggplot2Methods excerpt: sampling, lab, stats

Main numerical results

ANOVA: overall age effect F = 14.83, p < 0.0001. Range reported across all samples 1.49–7.68 pg/mg. January and February showed elevated G1 values (January 4.88 ± 0.71; February re-growth 5.14 ± 0.54) with declines by May, interpreted as adaptation to the controlled environmentResults excerpt: age and time effects

Strengths of the study

• Noninvasive, longitudinal sampling that measures cumulative cortisol (bristle matrix) limits circadian/sampling artifacts common to blood or saliva and provides retrospective integrated exposure dataWhy bristle cortisol was used
• Repeated measures within individuals (monthly over six months) improves within-subject inference about adaptation trajectories.
• Clear, standard statistical procedures reported (tests of normality, Levene, repeated-measures aov, emmeans post-hoc).

Limitations, biases, and possible confounders

1. Small sample size and limited demographic: 18 animals, all nonpregnant females, from a single region (Campania) limits external generalizability to males, pregnant females, other geographies, or wild free-ranging contextsPaper limitations statement
2. Capture and relocation effects: first cut occurred 20 days before the study start but capture, transport, and initial handling remain potential acute stressors that could affect early bristle segments. The authors acknowledge hunting-season capture prior to relocation and a possible elevated allostatic load at study start — which can bias initial-month comparisons.
3. Matrix validation: the study used an in-house ELISA adapted from human hair methods; while common, full analytical validation (parallelism, recovery, cross-reactivity, limits of detection/quantification) are not described in detail in the supplied excerpts, reducing transparency for assay reproducibility.
4. Single biomarker focus: cortisol is a reasonable allostatic marker but allostatic load is multifactorial (immune, metabolic, behavioural axes); absence of corroborating physiological or behavioural endpoints (e.g., body condition, immune markers, behavior scoring) limits mechanistic interpretation.
5. Data access: dataset available on request rather than openly archived reduces immediate reproducibility and external reanalysis potential.

Key methodological critique

1) Assay validation transparency: the methods report an in-house ELISA adapted from human hair protocols and reference Bergamin and Falco methods for washing/extraction, but the publicly provided text does not include analytic validation metrics (intra/inter-assay CV, recovery, linearity) which are necessary for confidence in low pg/mg measurements; authors should supply validation data in supplements or on request to support quantitative claims.
2) Handling of capture stress: the first cut at arrival (20 days before) is reasonable but the authors also note hunting-season timing and possible prior allostatic load; a pre-capture baseline or comparison with non-captured controls would strengthen causal claims about adaptation under controlled housing.
3) Statistical model details: the repeated-measures ANOVA is appropriate, but mixed-effects modeling (lme4 or nlme) could better partition within-subject correlation structures and missing data handling; the paper does not report whether any missing monthly samples occurred or how sphericity was tested/handled.

How convincing are the conclusions?

The core empirical claim — juveniles have higher integrated bristle cortisol than older cohorts in this sampled cohort and that values decline across months consistent with adaptation — is supported by reported statistics (F=14.83, p<0.0001; pairwise contrasts) and so is credible for this datasetAuthors conclusions and interpretation

Confidence limit: moderate. The result is internally consistent but external validity is limited by sample size, single sex, single location, and single biomarker approach.

Practical and scientific value

• Usefulness: the paper provides preliminary reference bristle cortisol values for wild boars and demonstrates feasibility of longitudinal bristle sampling in a semi-controlled wildlife management setting — useful to wildlife vets and managers monitoring stress and welfare during containment or translocation.
• Scientific novelty: extending bristle/hair cortisol monitoring to wild boars in a longitudinal controlled-environment design adds valuable species-specific data, but conceptually follows established hair cortisol literature (domestic pigs, other wild species).

What would disprove the main interpretation?

If a larger, multi-site study including males and pregnant females failed to replicate the age effect, or showed no within-individual decline over time when controlling for capture timing and assay validation, that would challenge the adaptation interpretation; alternatively, if validated multi-matrix measures (fecal glucocorticoid metabolites, salivary/blood cortisol) did not correlate with bristle cortisol, then bristle-based inference about allostatic load would be weakened.

Concrete recommendations to authors and future studies

1. Provide full analytical validation for the in-house ELISA (parallelism, recovery, intra/inter-assay CVs, LOD/LOQ) as a supplement or data repository entry.
2. Publish anonymized sample-level data (deidentified) and analysis scripts (R) for reproducibility and permit reanalysis (authors state data available on request; open deposition would accelerate use).
3. Adopt linear mixed models to explicitly model subject random intercepts and time random slopes; report effect sizes and confidence intervals for pairwise contrasts.
4. In future cohorts, include additional physiological markers (acute phase proteins, immune cell counts), body condition scoring, and standardized behaviour/welfare assessments to triangulate allostatic load beyond cortisol alone.
5. Expand cohorts across seasons and incorporate males and reproductive states to test generality.

Suggested follow up experiments (testable and specific)

1. Paired-matrix validation: concurrently collect bristles, feces (for glucocorticoid metabolites), and saliva/blood (where feasible) from a replicate cohort during the first 6 months of captivity to test correlations and temporal concordance between matrices using validated assays (n>30 animals and both sexes).
2. Assay comparability experiment: distribute bristle extracts to two independent labs for blind ELISA and LC MS/MS cortisol quantification to test inter-laboratory reproducibility and measurement bias.

Visual summary (plotly)

Short checklist for readers who want to reuse these results

• Request raw data and R scripts from authors (Data Availability Statement indicates data available on request) to reproduce models.
• Check assay validation before combining these values with other datasets.
• When using bristle cortisol as welfare indicator, pair with behavioral and health endpoints to avoid single-marker over-interpretation.

Bottom line

This paper provides a credible, carefully executed preliminary dataset showing higher integrated cortisol exposure in juvenile wild boars temporarily held in a controlled environment, with statistical support for age differences and temporal decline consistent with adaptation. The main value is practical: demonstrating longitudinal bristle sampling in wild boars and supplying preliminary reference intervals, but inference about wider populations, sexes, or causality of adaptation requires larger, multi-matrix, multi-site, and multi-demographic follow-ups and transparent assay validationAuthors concluding remarks

Author reviews

Open bespoke author review pages for each listed author:

• Nadia Piscopo
• Anna Balestrieri
• Nicola D Alessio
• Pasqualino Silvestre
• Giovanna Bifulco
• Alessio Cotticelli
• Tanja Peric
• Alberto Prandi
• Danila D Angelo
• Francesco Napolitano
• Luigi Esposito

Note: data available on request; readers seeking to reuse or meta-analyze should request raw sample-level bristle cortisol values and the lab validation metrics.