Dynamic Measurement of a Cancer Biomarker: Towards In Situ Application of a Fiber-Optic Ball Resonator Biosensor in CD44 Protein Detection.

The accuracy and efficacy of medical treatment would be greatly improved by the continuous and real-time monitoring of protein biomarkers. Identification of cancer biomarkers in patients with solid malignant tumors is receiving increasing attention. Existing techniques for detecting cancer proteins, such as the enzyme-linked immunosorbent assay, require a lot of work, are not multiplexed, and only allow for single-time point observations. In order to get one step closer to clinical usage, a dynamic platform for biosensing the cancer biomarker CD44 using a single-mode optical fiber-based ball resonator biosensor was designed, constructed and evaluated in this work. The main novelty of the work is an in-depth study of the capability of an in-house fabricated optical fiber biosensor for in situ detection of a cancer biomarker (CD44 protein) by conducting several types of experiments. The main results of the work are as follows: (1) Calibration of the fabricated fiber-optic ball resonator sensors in both static and dynamic conditions showed similar sensitivity to the refractive index change demonstrating its usefulness as a biosensing platform for dynamic measurements; (2) The fabricated sensors were shown to be insensitive to pressure changes further confirming their utility as an in situ sensor; (3) The sensor's packaging and placement were optimized to create a better environment for the fabricated ball resonator's performance in blood-mimicking environment; (4) Incubating increasing protein concentrations with antibody-functionalized sensor resulted in nearly instantaneous signal change indicating a femtomolar detection limit in a dynamic range from 7.1 aM to 16.7 nM; (5) The consistency of the obtained signal change was confirmed by repeatability studies; (6) Specificity experiments conducted under dynamic conditions demonstrated that the biosensors are highly selective to the targeted protein; (7) Surface morphology studies by AFM measurements further confirm the biosensor's exceptional sensitivity by revealing a considerable shift in height but no change in surface roughness after detection. The biosensor's ability to analyze clinically relevant proteins in real time with high sensitivity offers an advancement in the detection and monitoring of malignant tumors, hence improving patient diagnosis and health status surveillance.

Electrofermentation increases concentration of poly γ-glutamic acid in Bacillus subtilis biofilms.

Fluctuations in redox conditions in bioprocesses can alter the end-products, reduce their concentration, and lengthen the process time. Electrofermentation enables rapid metabolic modulation of biosynthesis and allows control of redox imbalances in biofilm-based fermentation processes. In this study, electrofermentation is used to boost the production of the bacterial biopolymer poly-γ-glutamic acid (γ-PGA) from Bacillus subtilis ATCC 6051. When compared to control experiments (3.3 ± 0.99 g L-1 ), the application of an electrode potential E = 0.4 V versus Ag/AgCl results in a more than two-fold increase in the production of γ-PGA (9.13 ± 1.4 g L-1 ). Using an engineered B. subtilis strain, in which γ-PGA production is driven by isopropyl ß-d-1-thiogalactopyranoside, electrofermentation improves polymer concentrations from 15.4 ± 1.5 to 23.1 ± 1.6 versus g L-1 . These results confirm that electrofermentation conditions can be adopted to increase the concentration of γ-PGA and perhaps other extracellular biopolymers in industrial strains.

Functionalized optical fiber ball-shaped biosensor for label-free, low-limit detection of IL-8 protein.

Detection of biomarkers for tracking disease progression is becoming increasingly important in biomedicine. Using saliva as a diagnostic sample appears to be a safe, cost-effective, and non-invasive approach. Salivary interleukin-8 levels demonstrate specific changes associated with diseases such as obstructive pulmonary disease, squamous cell carcinoma, oral cancer, and breast cancer. Traditional protein detection methods, such as enzyme-linked immunosorbent assay (ELISA), mass spectrometry, and Western blot are often expensive, complex, and time-consuming. In this study, an optical fiber-based biosensor was developed to detect salivary IL-8 protein in a label-free manner. The biosensor was able to achieve an ultra-low limit detection of 0.91 fM. Moreover, the tested concentration range was wide: from 273 aM to 59 fM. As a proof-of-concept for detecting the protein in real clinical samples, the detection was carried out in artificial saliva. It was possible to achieve high sensitivity for the target protein and minimal signal alterations for the control proteins.

A hybrid fluorescent nanofiber membrane integrated with microfluidic chips towards lung-on-a-chip applications.

Here, we report a fluorescent electrospun nanofiber membrane for integration into microfluidic devices towards lung-on-a-chip applications complemented with the results of computational fluid dynamics modelling. A proposed hybrid poly(ε-caprolactone) (PCL)-collagen membrane was developed, characterized, tested, and integrated into a prototype microfluidic chip for biocompatibility studies. The resulting membrane has a thickness of approximately 10 µm, can be adjusted for appropriate porosity, and offers excellent biocompatibility for mimicry of a basement membrane to be used in lung-on-a-chip device applications. Several membrane variations were synthesized and evaluated using SEM, FTIR, AFM, and high-resolution confocal fluorescence microscopy. A sample microfluidic chip made of cyclic olefin copolymer and polydimethylsiloxane was built and integrated with the developed PCL-collagen membrane for on-chip cell culture visualisation and biocompatibility studies. The sample chip design was modelled to determine the optimal fluidic conditions for using the membrane in the chip under fluidic conditions for future studies. The integration of the proposed membrane into microfluidic devices represents a novel strategy for improving lung-on-a-chip applications which can enhance laboratory recapitulation of the lung microenvironment.

4-Nitrophenol reduction and antibacterial activity of Ag-doped TiO2 photocatalysts.

Water contamination by organic pollutants is a serious environmental problem. 4-Nitrophenol (4-NP) is a potentially harmful chemical, which is commonly present in industrial effluents and can severely damage human health. Photocatalytic reduction of hazardous 4-NP by nano-sized materials to produce 4-aminophenol (4-AP), which is a commercially valuable product, is a promising alternative as the process is framed within the circular economy. In this context, Ag-doped TiO2 (AT) catalysts were synthesized by liquid impregnation and reduction techniques, and their structure, morphology, elemental composition, textural, and light absorption properties were evaluated by XRD, Raman spectroscopy, SEM, TEM, EDS, BET, and DRS spectroscopy. AT catalysts exhibited an enhanced photocatalytic reduction of 4-NP into 4-aminophenol (4-AP) in the presence of NaBH4. Among the tested catalysts, AT21 prepared by a simple aqueous reduction method showed the highest activity reaching about 98% 4-NP reduction within 10 min. Antibacterial tests of these catalysts against Bacillus subtilis, Escherichia coli, Staphylococcus aureus, and Pseudomonas aeruginosa revealed that AT21 also exhibited the lowest minimum inhibitory concentration, suggesting that it has the strongest antibacterial activity. These findings suggest that AT21 catalyst with improved catalytic and antibacterial properties can potentially be utilized for the remediation of 4-NP-contaminated water environment.

Novel carbon nanozymes with enhanced phosphatase-like catalytic activity for antimicrobial applications.

In this work, Sulfur and Nitrogen co-doped carbon nanoparticles (SN-CNPs) were synthesized by hydrothermal method using dried beet powder as the carbon source. TEM and AFM images indicated that these SN-CNPs form a round-shape ball with an approximate diameter of 50 nm. The presence of Sulfur and Nitrogen in these carbon-based nanoparticles was confirmed by FTIR and XPS analyses. These SN-CNPs were found to have strong phosphatase-like enzymatic activity. The enzymatic behavior of SN-CNPs follows the Michaelis-Menten mechanism with greater vmax and much lower Km values compared to alkaline phosphatase. Their antimicrobial properties were tested on E. coli and L. lactis, with MIC values of 63 µg mL-1 and 250 µg mL-1, respectively. SEM and AFM images of fixed and live E. coli cells revealed that SN-CNPs strongly interacted with the outer membranes of bacterial cells, significantly increasing the cell surface roughness. The chemical interaction between SN-CNPs and phospholipid modeled using quantum mechanical calculations further support our hypothesis that the phosphatase and antimicrobial properties of SN-CNPs are due to the thiol group on the SN-CNPs, which is a mimic of the cysteine-based protein phosphatase. The present work is the first to report carbon-based nanoparticles with strong phosphatase activity and propose a phosphatase natured antimicrobial mechanism. This novel class of carbon nanozymes has the potential to be used for effective catalytic and antibacterial applications.

Biochemical and electrochemical characterization of biofilms formed on everolimus-eluting coronary stents.

Drug-eluting stents (DES) are mostly used in percutaneous coronary intervention, which is the main treatment for coronary artery occlusion. This procedure aims to restore the natural lumen, while minimizing the risk of restenosis. However, stent insertion increases the risk for infections, due to contamination of the device or insertion hub with normal skin flora. While coronary stent infection is a rare complication, it can be fatal. Currently, there is little information on biofilm formation on everolimus-eluting stents. Although everolimus is not designed as an antimicrobial agent, its antimicrobial activity should be investigated. In this study, biofilm formation on everolimus-eluting and bare metal stents (BMS) is characterized through biochemical and electrochemical methods. DES and BMS are inoculated with Pseudomonas aeruginosa and Staphylococcus epidermidis, both independently and in co-culture. Biofilms formed on DES were 49.6 %, 12.9 % and 47.5 % higher than on BMS for P. aeruginosa, S. epidermidis and their co-culture, respectively. Further, the charge output for DES was 18.9 % and 59.7 % higher than BMS for P. aeruginosa and its co-culture with S. epidermidis, respectively. This observation is most likely due to higher surface roughness of DES, which favors biofilm formation. This work shows that bioelectrochemical methods can be used for rapid detection of biofilms on drug-eluting and bare metal stents, which may find application in quality assessment of stents and in characterization of stents removed after polymicrobial infections.

Linear Basis Function Approach to Efficient Alchemical Free Energy Calculations. 1. Removal of Uncharged Atomic Sites.

We present a general approach to transform between molecular potential functions during free energy calculations using a variance minimized linear basis functional form. This approach splits the potential energy function into a sum of pairs of basis functions, which depend on coordinates, and 'alchemical' switches, which depend only on the coupling variable. The power of this approach is that, first, the calculation of the coupling parameter dependent terms is removed from inner loop force calculation routines, second, the flexibility in specifying basis functions and alchemical switches allows users to choose transformation pathways that maximize statistical efficiency, and third, it is possible to predict entirely in postprocessing, without any additional energy evaluations, the thermodynamic properties along any alchemical path with moderate overlap from an initial simulation that uses the same basis functions. This allows construction of optimized, minimum variance alchemical switches from a single simulation with fixed basis functions and trial alchemical switching functions. We describe how to construct these linear basis potentials for real molecular systems of different sizes and shapes, considering particularly the problems of eliminating singularities and minimizing variance of particle removal in dense fluids. The statistical error in free energy calculations using the optimized basis functions is lower than standard soft core models, and approach the minimum variance possible over all pair potentials. We recommend an optimized set of basis functions and alchemical switches for standard molecular free energy calculations.

Optimal pairwise and non-pairwise alchemical pathways for free energy calculations of molecular transformation in solution phase.

We estimate the global minimum variance path for computing the free energy insertion into or deletion of small molecules from a dense fluid. We perform this optimization over all pair potentials, irrespective of functional form, using functional optimization with a two-body approximation for the radial distribution function. Surprisingly, the optimal pairwise path obtained via this method is almost identical to the path obtained using a optimized generalized "soft core" potential reported by Pham and Shirts [J. Chem. Phys. 135, 034114 (2011)]. We also derive the lowest variance non-pairwise potential path for molecular insertion or deletion and compare its efficiency to the pairwise path. Under certain conditions, non-pairwise pathways can reduce the total variance by up to 60% compared to optimal pairwise pathways. However, optimal non-pairwise pathways do not appear generally feasible for practical free energy calculations because an accurate estimate of the free energy, the parameter that is itself is desired, is required for constructing this non-pairwise path. Additionally, simulations at most intermediate states of these non-pairwise paths have significantly longer correlation times, often exceeding standard simulation lengths for solvation of bulky molecules. The findings suggest that the previously obtained soft core pathway is the lowest variance pathway for molecular insertion or deletion in practice. The findings also demonstrate the utility of functional optimization for determining the efficiency of thermodynamic processes performed with molecular simulation.

Identifying low variance pathways for free energy calculations of molecular transformations in solution phase.

Improving the efficiency of free energy calculations is important for many biological and materials design applications, such as protein-ligand binding affinities in drug design, partitioning between immiscible liquids, and determining molecular association in soft materials. We show that for any pair potential, moderately accurate estimation of the radial distribution function for a solute molecule is sufficient to accurately estimate the statistical variance of a sampling along a free energy pathway. This allows inexpensive analytical identification of low statistical error free energy pathways. We employ a variety of methods to estimate the radial distribution function (RDF) and find that the computationally cheap two-body "dilute gas" limit performs as well or better than 3D-RISM theory and other approximations for identifying low variance free energy pathways. With a RDF estimate in hand, we can search for pairwise interaction potentials that produce low variance. We give an example of a search minimizing statistical variance of solvation free energy over the entire parameter space of a generalized "soft core" potential. The free energy pathway arising from this optimization procedure has lower curvature in the variance and reduces the total variance by at least 50% compared to the traditional soft core solvation pathway. We also demonstrate that this optimized pathway allows free energies to be estimated with fewer intermediate states due to its low curvature. This free energy variance optimization technique is generalizable to solvation in any homogeneous fluid and for any type of pairwise potential and can be performed in minutes to hours, depending on the method used to estimate g(r).

Implicit and explicit solvent models for the simulation of a single polymer chain in solution: Lattice Boltzmann versus Brownian dynamics.

We present a comparative study of two computer simulation methods to obtain static and dynamic properties of dilute polymer solutions. The first approach is a recently established hybrid algorithm based on dissipative coupling between molecular dynamics and lattice Boltzmann (LB), while the second is standard Brownian dynamics (BD) with fluctuating hydrodynamic interactions. Applying these methods to the same physical system (a single polymer chain in a good solvent in thermal equilibrium) allows us to draw a detailed and quantitative comparison in terms of both accuracy and efficiency. It is found that the static conformations of the LB model are distorted when the box length L is too small compared to the chain size. Furthermore, some dynamic properties of the LB model are subject to an L(-1) finite-size effect, while the BD model directly reproduces the asymptotic L-->infinity behavior. Apart from these finite-size effects, it is also found that in order to obtain the correct dynamic properties for the LB simulations, it is crucial to properly thermalize all the kinetic modes. Only in this case, the results are in excellent agreement with each other, as expected. Moreover, Brownian dynamics is found to be much more efficient than lattice Boltzmann as long as the degree of polymerization is not excessively large.