Stable Coexistence of an Invasive Plant and Biocontrol Agent: A Parameterized Coupled Plant-Herbivore Model

1. Coupled plant-herbivore models, allowing feedback from plant to herbivore populations and vice versa, enable us to predict the impact of biocontrol agents on their target weed populations; however, they are rarely used in biocontrol studies. We describe the population biology of the invasive plant Echium plantagineum and the weevil Mogulones larvatus, a biocontrol agent, in Australia. In order to understand the dynamics of this plant-herbivore system, a series of coupled models of increasing complexity was developed. 2. A simple model was extended to include a seed bank, density-dependent plant fecundity, competition between weevil larvae and plant tolerance of herbivory, where below a threshold plants could compensate for larval feeding. Parameters and functional forms were estimated from experimental and field data. 3. The plant model, in the absence of the weevil, exhibited stable dynamics and provided a good quantitative description of field densities before the weevil was introduced. 4. In the coupled plant-herbivore model, density dependence in both plant fecundity and weevil larval competition stabilized the dynamics. Without larval competition the model was unstable, and plant tolerance of herbivory exacerbated this instability. This was a result of a time delay in plant response to herbivore densities. 5. Synthesis and applications. The coupled plant-herbivore model allowed us to predict whether stable coexistence of target plant and biocontrol agents was achievable at an acceptable level. We found this to be the case for the Echium-Mogulones system and believe that similar models would be of use when assessing new agents in this and other invasive plant biocontrol systems. Density dependence in new biocontrol agents should be assessed in order to determine whether it is likely to result in the aims of classical biocontrol: low, stable and sustainable populations of plant and herbivore. Further work should be done to characterize the strength of density dependence according to the niche occupied by the biocontrol agent, for example the strength and functional form of density dependence in stem borers may be quite different to that of defoliators

The path to a better biomarker: Application of a risk management framework for the implementation of PD-L1 and TILs as immuno-oncology biomarkers in breast cancer clinical trials and daily practice

Immune checkpoint inhibitor therapies targeting PD-1/PD-L1 are now the standard of care in oncology across several hematologic and solid tumor types, including triple negative breast cancer (TNBC). Patients with metastatic or locally advanced TNBC with PD-L1 expression on immune cells occupying 651% of tumor area demonstrated survival benefit with the addition of atezolizumab to nab-paclitaxel. However, concerns regarding variability between immunohistochemical PD-L1 assay performance and inter-reader reproducibility have been raised. High tumor-infiltrating lymphocytes (TILs) have also been associated with response to PD-1/PD-L1 inhibitors in patients with breast cancer (BC). TILs can be easily assessed on hematoxylin and eosin\u2013stained slides and have shown reliable inter-reader reproducibility. As an established prognostic factor in early stage TNBC, TILs are soon anticipated to be reported in daily practice in many pathology laboratories worldwide. Because TILs and PD-L1 are parts of an immunological spectrum in BC, we propose the systematic implementation of combined PD-L1 and TIL analyses as a more comprehensive immuno-oncological biomarker for patient selection for PD-1/PD-L1 inhibition-based therapy in patients with BC. Although practical and regulatory considerations differ by jurisdiction, the pathology community has the responsibility to patients to implement assays that lead to optimal patient selection. We propose herewith a risk-management framework that may help mitigate the risks of suboptimal patient selection for immuno-therapeutic approaches in clinical trials and daily practice based on combined TILs/PD-L1 assessment in BC. \ua9 2020 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd

Application of a risk-management framework for integration of stromal tumor-infiltrating lymphocytes in clinical trials

Stromal tumor-infiltrating lymphocytes (sTILs) are a potential predictive biomarker for immunotherapy response in metastatic triple-negative breast cancer (TNBC). To incorporate sTILs into clinical trials and diagnostics, reliable assessment is essential. In this review, we propose a new concept, namely the implementation of a risk-management framework that enables the use of sTILs as a stratification factor in clinical trials. We present the design of a biomarker risk-mitigation workflow that can be applied to any biomarker incorporation in clinical trials. We demonstrate the implementation of this concept using sTILs as an integral biomarker in a single-center phase II immunotherapy trial for metastatic TNBC (TONIC trial, NCT02499367), using this workflow to mitigate risks of suboptimal inclusion of sTILs in this specific trial. In this review, we demonstrate that a web-based scoring platform can mitigate potential risk factors when including sTILs in clinical trials, and we argue that this framework can be applied for any future biomarker-driven clinical trial setting

The detection of density-dependence from a series of annual censuses

We report a distribution—free approach to the detection of density—dependence in the variation of population abundance, measured by a series of annual censuses. The method uses the correlation coefficient between the observed population changes and population size and proposes a randomization procedure to define a rejection region for the hypothesis of density—independence. It is shown that the use of the proposed statistic under the randomization approach is equivalent to the likelihood ratio test for a particular family of time series models. The randomization test is compared with two other recently proposed tests. Using computer—generated density—independent and density—dependent data, it is shown that, unlike the other tests, the randomization test is effective whether or not there is a marked trend in the observed data. Arguments are presented showing how one of the other two tests can be further improved. Caution is urged in the use and interpretation of any test for detecting density—dependence in census data because (a) the tests depend on assumptions about population processes, (b) errors of measurement may lead to spurious detection of density—dependence

On the Optimal Coding

Novel coding schemes are introduced and relationships between optimal codes and Huffman codes are discussed. It is shown that, for finite source alphabets, the Huffman coding is the optimal coding, and conversely the optimal coding needs not to be the Huffman coding. It is also proven that there always exists the optimal coding for infinite source alphabets. We show that for every random variable with a countable infinite set of outcomes and finite entropy there exists an optimal code constructed from optimal codes for truncated versions of the random variable. And the average code word lengths of any sequence of optimal codes for the truncated versions converge to that of the optimal code. Furthermore, a case study of data compression is given