Vancomycin-modified nitrogen and chloride doped carbon dots and their application as a Staphylococcus aureus probe.

In this research, N, Cl-doped carbon dots (N, Cl-CDs) were prepared in choline chloride-glycerol deep eutectic solvent (DES) by microwave method. N, Cl-CDs surface was modified with vancomycin for detection of Staphylococcus aureus (S. aureus) bacteria in the range of 102-107 colony-forming unit per milliliter (CFU/mL). The detection limit was 101 CFU/mL. Morphology and structure of N, Cl-CDs were characterized by transmission electron microscopy (TEM), X-ray photon spectroscopy (XPS), photoluminescence spectroscopy, FT-IR spectroscopy, energy dispersive X-ray spectroscopy (EDXS) and zeta potential. The prepared N, Cl-CDs had excellent dispersion in water, particle size range of 2-3 nm, and quantum yield of 38.75%. Speed, wide linear range and more convenient were advantages of new probe with respect to other methods.

Fluorescence turn off-on detection of Co2+ and enrofloxacin by N, Cl-carbon dots prepared in deep eutectic solvent and study of their photocatalytic antibacterial activity.

Nitrogen, chloride doped carbon dots (N, Cl-CDs) were synthesized in deep eutectic solvent. TEM, XRD, FT-IR, XPS, EDAX, UV-Vis and fluorescence were used for characterization. Quantum yield and average size of N, Cl-CDs were 38.75 % and 2-3 nm, respectively. N, Cl-CDs fluorescence was turn off by cobalt ion and then turn on gradually after addition of enrofloxacin. Linear dynamic range and detection limit (DL) for Co2+ and enrofloxacin were (0.1-70 µM and 30 nM) and (0.05-50 µM and 25 nM), respectively. Enrofloxacin was detected in blood serum and water samples with the recovery of 96-103 %. Finally, Antibacterial activity of the carbon dots was also investigated.

A global method for fast simulations of molecular dynamics in multiscale agent-based models of biological tissues.

Agent-based models (ABMs) are a natural platform for capturing the multiple time and spatial scales in biological processes. However, these models are computationally expensive, especially when including molecular-level effects. The traditional approach to simulating this type of multiscale ABM is to solve a system of ordinary differential equations for the molecular events per cell. This significantly adds to the computational cost of simulations as the number of agents grows, which contributes to many ABMs being limited to around 10 5 cells. We propose an approach that requires the same computational time independent of the number of agents. This speeds up the entire simulation by orders of magnitude, allowing for more thorough explorations of ABMs with even larger numbers of agents. We use two systems to show that the new method strongly agrees with the traditionally used approach. This computational strategy can be applied to a wide range of biological investigations.

Comparison of Carbon Dots Prepared in Deep Eutectic Solvent and Water/Deep Eutectic Solvent: Study of Fluorescent Detection of Fe3+ and Cetirizine and their Photocatalytic Antibacterial Activity.

In this study, two solvents (deep eutectic and water/deep eutectic solvents) were used for N-doped carbon dots (N-CDs) preparation by microwave irradiation. The solvent can influence surface chemical composition, quantum yield, morphology, and fluorescence of CDs. N-CDs synthesized in water/deep eutectic solvent (DES) had better quantum yield (24.5%) with respect to N-CDs synthesized in deep eutectic solvent (17.4%). These carbon dots were used as a rapid and high sensitive "off-on" fluorescent probe for the determination of Fe3+ ion and cetirizine. Morphology and structure of the N-CDs were characterized by FT-IR, UV-Vis, XRD and TEM. Linear range and detection limit for N-CDs synthesis in deep eutectic solvent for cetirizine were 0.08-48 µM and 15 nM, respectively and for N-CDs synthesis in water/deep eutectic solvent were 0.03-50 µM and 10 nM, respectively. Applicability of this nanoprobe was tested in cetirizine determination in serum sample. Antibacterial activities of the two synthesized N-CDs were also investigated using agar disk diffusion method.

Sensitive fluorescence detection of atorvastatin by doped carbon dots synthesized in deep eutectic media.

Fluorescence properties of nanoparticles can be influenced by solvent. In this work, carbon dots (CDs) were synthesized in deep eutectic solvent by microwave assisted method. Quantum yield (QY) and size of the synthesized CDs were 41.3% and 2 nm, respectively. N/Cl -doped CDs had excellent sensitivity and selectivity for atorvastatin and detection limit was 0.8 nM. Simple and low-cost synthesis method and excellent sensitivity are advantages of this detection method for atorvastatin. The as-synthesized N/Cl-doped CDs were successfully used to determine atorvastatin in blood serum.

In Silico Models Accurately Predict In Vivo Response for IL6 Blockade in Head and Neck Cancer.

Malignant features of head and neck squamous cell carcinoma (HNSCC) may be derived from the presence of stem-like cells that are characterized by uniquely high tumorigenic potential. These cancer stem cells (CSC) function as putative drivers of tumor initiation, therapeutic evasion, metastasis, and recurrence. Although they are an appealing conceptual target, CSC-directed cancer therapies remain scarce. One promising CSC target is the IL6 pathway, which is strongly correlated with poor patient survival. In this study we created and validated a multiscale mathematical model to investigate the impact of cross-talk between tumor cell- and endothelial cell (EC)-secreted IL6 on HNSCC growth and the CSC fraction. We then predicted and analyzed the responses of HNSCC to tocilizumab (TCZ) and cisplatin combination therapy. The model was validated with in vivo experiments involving human ECs coimplanted with HNSCC cell line xenografts. Without artificial tuning to the laboratory data, the model showed excellent predictive agreement with the decrease in tumor volumes observed in TCZ-treated mice, as well as a decrease in the CSC fraction. This computational platform provides a framework for preclinical cisplatin and TCZ dose and frequency evaluation to be tested in future clinical studies. SIGNIFICANCE: A mathematical model is used to rapidly evaluate dosing strategies for IL6 pathway modulation. These results may lead to nonintuitive dosing or timing treatment schedules to optimize synergism between drugs.

Luminescent, low-toxic and stable gradient-alloyed Fe:ZnSe(S)@ZnSe(S) core:shell quantum dots as a sensitive fluorescent sensor for lead ions.

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 Pb2+ ions with excellent selectivity, small detection limit, and rapid response time.

A mathematical model for IL-6-mediated, stem cell driven tumor growth and targeted treatment.

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.

A two-strain TB model with multiple latent stages.

A two-strain tuberculosis (TB) transmission model incorporating antibiotic-generated TB resistant strains and long and variable waiting periods within the latently infected class is introduced. The mathematical analysis is carried out when the waiting periods are modeled via parametrically friendly gamma distributions, a reasonable alternative to the use of exponential distributed waiting periods or to integral equations involving ``arbitrary'' distributions. The model supports a globally-asymptotically stable disease-free equilibrium when the reproduction number is less than one and an endemic equilibriums, shown to be locally asymptotically stable, or l.a.s., whenever the basic reproduction number is greater than one. Conditions for the existence and maintenance of TB resistant strains are discussed. The possibility of exogenous re-infection is added and shown to be capable of supporting multiple equilibria; a situation that increases the challenges faced by public health experts. We show that exogenous re-infection may help established resilient communities of actively-TB infected individuals that cannot be eliminated using approaches based exclusively on the ability to bring the control reproductive number just below 1.

Mass Media and the Contagion of Fear: The Case of Ebola in America.

BACKGROUND: In 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. METHODOLOGY: We 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. CONCLUSIONS: We 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.