BackgroundIn the weeks following the first imported case of Ebola in the U. S. on September 29, 2014, coverage of the very limited outbreak dominated the news media, in a manner quite disproportionate to the actual threat to national public health; by the end of October, 2014, there were only four laboratory confirmed cases of Ebola in the entire nation. Public interest in these events was high, as reflected in the millions of Ebola-related Internet searches and tweets performed in the month following the first confirmed case. Use of trending Internet searches and tweets has been proposed in the past for real-time prediction of outbreaks (a field referred to as “digital epidemiology”), but accounting for the biases of public panic has been problematic. In the case of the limited U. S. Ebola outbreak, we know that the Ebola-related searches and tweets originating the U. S. during the outbreak were due only to public interest or panic, providing an unprecedented means to determine how these dynamics affect such data, and how news media may be driving these trends.MethodologyWe examine daily Ebola-related Internet search and Twitter data in the U. S. during the six week period ending Oct 31, 2014. TV news coverage data were obtained from the daily number of Ebola-related news videos appearing on two major news networks. We fit the parameters of a mathematical contagion model to the data to determine if the news coverage was a significant factor in the temporal patterns in Ebola-related Internet and Twitter data.ConclusionsWe find significant evidence of contagion, with each Ebola-related news video inspiring tens of thousands of Ebola-related tweets and Internet searches. Between 65% to 76% of the variance in all samples is described by the news media contagion model.

Targeting key regulators of the cancer stem cell phenotype to overcome their critical influence on tumor growth is a promising new strategy for cancer treatment. Here we present a modeling framework that operates at both the cellular and molecular levels, for investigating IL-6 mediated, cancer stem cell driven tumor growth and targeted treatment with anti-IL6 antibodies. Our immediate goal is to quantify the influence of IL-6 on cancer stem cell self-renewal and survival, and to characterize the subsequent impact on tumor growth dynamics. By including the molecular details of IL-6 binding, we are able to quantify the temporal changes in fractional occupancies of bound receptors and their influence on tumor volume. There is a strong correlation between the model output and experimental data for primary tumor xenografts. We also used the model to predict tumor response to administration of the humanized IL-6R monoclonal antibody, tocilizumab (TCZ), and we found that as little as 1mg/kg of TCZ administered weekly for 7 weeks is sufficient to result in tumor reduction and a sustained deceleration of tumor growth.

In this paper, an aqueous-based approach is introduced for facile, fast, and green synthesis of gradient-alloyed Fe-doped ZnSe(S)@ZnSe(S) core:shell quantum dots (QDs) with intense and stable emission. Co-utilization of co-nucleation and growth doping strategies, along with systematic optimization of emission intensity, provide a well-controllable/general method to achieve internally doped QDs (d-dots) with intense emission. Results indicate that the alloyed ZnSe(S)@ZnSe(S) core:shell QDs have a gradient structure that consists of a Se-rich core and a S-rich shell. This gradient structure cannot only passivate the core d-dots by means of the wider band gap S-rich shell, but also minimizes the lattice mismatch between alloyed core-shell structures. Using this novel strategy and utilizing the wider band gap S-rich shell can obviously increase the cyan emission intensity and also drastically improve the emission stability against chemical and optical corrosion. Furthermore, the cytotoxicity experiments indicate that the obtained d-dots are nontoxic nanomaterials, and thus they can be considered as a promising alternative to conventional Cd-based QDs for fluorescent probes in biological fields. Finally, it is demonstrated that the present low-toxicity and gradient-alloyed core:shell d-dots can be used as sensitive chemical detectors for Pb ions with excellent selectivity, small detection limit, and rapid response time.

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BackgroundDuoBody-PD-L1×4-1BB (GEN1046) is a class-defining bispecific antibody, designed to elicit an anti-tumor immune response by simultaneous and complementary blockade of PD-L1 on tumor cells and conditional stimulation of 4-1BB on T-cells and NK cells. Optimizing target engagement for a bispecific antibody is challenging, as it involves binding with two targets, and predicting trimer levels in tumors based on affinity of individual arms and target expression. Here we describe a semimechanistic, physiologically based pharmacokinetic/pharmacodynamic (PK/PD) model that predicts a dosing regimen for DuoBody-PD-L1×4-1BB, which results in the formation of maximum levels of a therapeutically active 4-1BB-bispecific antibody-PD-L1 trimolecular complex (trimer), and optimal PD-L1 receptor occupancy (RO).MethodsAn integrated semimechanistic PK/PD model that describes the distribution of DuoBody-PD-L1×4-1BB into central and peripheral compartments and partitioning into tumor/lymph nodes was developed. The model used PK/PD data and physiological parameters from the literature for parameterizations of PD-L1 and 4-1BB expression levels and T-cell trafficking. The model incorporates dynamic binding of DuoBody-PD-L1×4-1BB to its targets to predict trimer formation and RO for PD-L1 in tumors. Model parameters were calibrated to match in vitro PD studies, such as analyses of T-cell proliferation and cytokine release, as well as clinical PK data. Sensitivity to model assumptions were assessed by varying PK/PD parameters, and assessing their impact on trimer formation and PD-L1 RO. The model was subsequently used to explore in vivo trimer levels and PD-L1 RO in tumors at various dosing regimens.ResultsThe model was able to adequately describe the PK of DuoBody-PD-L1×4-1BB in the central compartment. Simulations showed a bell-shaped response for average trimer levels in tumors that peaked at 100 mg every 3 weeks (Q3W), with doses >100 mg resulting in reduced trimer formation. Average PD-L1 receptor occupancy at the 100 mg dose was predicted to be approximately 70% over 21 days and increased at higher doses. Based on these model predictions, and available safety, anti-tumor activity, and PD data from the ongoing GCT1046-01 trial (NCT03917381), 100 mg Q3W was chosen as the expansion dose for further evaluation in Part 2 of the study.ConclusionsThis semimechanistic PK/PD model provides a novel approach for dose selection of bispecific antibodies such as DuoBody-PD-L1×4-1BB, by using preclinical and clinical PK/PD data to predict formation of optimal trimer levels and PD-L1 receptor occupancy.AcknowledgementsThe authors thank Friederike Gieseke and Zuzana Jirakova at BioNTech SE; Kalyanasundaram Subramanian at Applied Biomath LLC for their valuable contributions.Trial RegistrationWritten informed consent, in accordance with principles that originated in the Declaration of Helsinki 2013, current ICH guidelines including ICH-GCP E6(R2), applicable regulatory requirements, and sponsor policy, was provided by the patients.