In a separate experiment, cookies were baked under four dynamic heating conditions 135℃/high humidity, 135℃/low humidity, 150℃/high humidity, and 150℃/low humidity. Process humidity measurements, time-temperature profiles for the product core, surface, and bulk air, and microbial survivor ratios were collected for the four conditions at six residence times (n=144). The traditional isothermal model had a poor root mean square error (RMSE) of 856.51 log (CFU/g), significantly overpredicting bacterial inactivation during the process. The modified model accounting for the dynamic time-temperature profile and process humidity data yielded a better predictive performance with a RMSE of 0.55 log CFU/g. The results demonstrate the importance of accounting for additional process parameters in baking inactivation models, and that model performance can be improved by utilizing model parameters obtained directly from industrial-scale experimental data.The collection of 3D cell tracking data from live images of micro-tissues is a recent innovation made possible due to advances in imaging techniques. As such there is increased interest in studying cell motility in 3D in vitro model systems but a lack of rigorous methodology for analysing the resulting data sets. One such instance of the use of these in vitro models is in the study of cancerous tumours. Growing multicellular tumour spheroids in vitro allows for modelling of the tumour microenvironment and the study of tumour cell behaviours, such as migration, which improves understanding of these cells and in turn could potentially improve cancer treatments. In this paper, we present a workflow for the rigorous analysis of 3D cell tracking data, based on the persistent random walk model, but adaptable to other biologically informed mathematical models. We use statistical measures to assess the fit of the model to the motility data and to estimate model parameters and provide confidence intervals for those parameters, to allow for parametrization of the model taking correlation in the data into account. We use in silico simulations to validate the workflow in 3D before testing our method on cell tracking data taken from in vitro experiments on glioblastoma tumour cells, a brain cancer with a very poor prognosis. The presented approach is intended to be accessible to both modellers and experimentalists alike in that it provides tools for uncovering features of the data set that may suggest amendments to future experiments or modelling attempts.Processes based on generating vapor phase hydroxyl-radicals or chlorine-radicals were developed for inactivating Listeria monocytogenes on mushrooms without negatively affecting quality.  https://www.selleckchem.com/products/bx-795.html  Antimicrobial radicals were generated from the UV-C degradation of hydrogen peroxide or hypochlorite and ozone gas. Response Surface Modelling (RMS) was used to identify the interaction between the operating parameters for the hydroxyl-radical process; UV-C 254nm intensity, hydrogen peroxide concentration and ozone delivered. There was an inverse relationship between hydrogen peroxide concentration and UV-C intensity in terms of the log reduction of L. monocytogenes . The independent parameters for the chlorine-radical process were hypochlorite concentration, pH, and UV-C intensity. From predictive models, the optimal hydroxyl-radical treatment was found to be 5% v/v H 2 O 2 , 2.86 mW/cm 2 UV-C intensity (total UV-C dose 144 mJ/cm 2 ) and 16.5 mg ozone. The chlorine-radical optimal process parameters were 10 ppm hypochlorite (pH 3.0), ozone 11.0 mg and 4.60 mW/cm 2 UV-C intensity. When inoculated mushrooms were treated with the optimal hydroxyl-radical and chlorine-radical process the log CFU reduction of L. monocytogenes was found to be 2.42±0.42 and 2.61±0.30 log CFU respectively without any negative effects on mushroom quality (weight loss and Browning Index during 14 days storage at 4°C). The levels of L. monocytogenes inactivation were significantly greater compared to when the individual elements of the radical processes were applied and control using a 90 s dip in 1% v/v hydrogen peroxide. The study has demonstrated that both hydroxyl-radical and chlorine-radical vapor-phase treatments are both equally effective at inactivating L. monocytogenes on mushrooms and can be considered as a preventative control step.Mantle cell lymphoma (MCL) is a mature B-cell neoplasm with a heterogeneous clinical and biological behavior. SOX11 oncogenic expression contributes to the aggressiveness of these tumors by different mechanisms including tumor and stromal cell interactions. However, the precise composition of the immune cell microenvironment of MCL, its possible relationship to SOX11 expression, and how it may contribute to tumor behavior is not well known. Here, we performed an integrative transcriptome analysis of 730 immune-related genes combined with the immune cell phenotype analysis by immunohistochemistry in SOX11+ and SOX11- primary nodal MCL cases and non-neoplastic reactive lymph nodes (RLN). SOX11+ MCL had a significant lower T-cell intratumoral infiltration compared to negative cases. A reduced expression of MHCI/II-like and T-cell costimulation and signaling activation related transcripts was significantly associated with poor clinical outcome. Moreover, we identified CD70 as a SOX11 direct target gene, whose overexpression was induced in SOX11+ but not SOX11- tumor cells by CD40L in vitro. CD70 was overexpressed in primary SOX11+ MCL and it was associated with an immune unbalance of the tumor microenvironment characterized by increased number of effector Treg cell infiltration, higher proliferation, and aggressive clinical course. CD27 was expressed with moderate to strong intensity in 76% of cases. Overall, our results suggest that SOX11 expression in MCL is associated with an immunosuppressive microenvironment characterized by CD70 overexpression in tumor cells, increased Treg cell infiltration and downmodulation of antigen-processing and -presentation and T-cell activation that could promote MCL progression and represent a potential target for tailored therapies.