The Ship of Theseus: The Lanham Act, Chanel and the Secondhand Luxury Goods Market

The ship wherein Theseus and the youth of Athens returned had thirty oars, and was preserved by the Athenians down even to the time of Demetrius Phale- reus, for they took away the old planks as they de- cayed, putting in new and stronger timber in their place, insomuch that this ship became a standing ex- ample among the philosophers, for the logical ques- tion of things that grow; one side holding that the ship remained the same, and the other contending that it was not the same. – Plutarch

Self-organized soft-hard interfaces: From surfaces to biologically integrated hybrid materials

The biological material systems promise the possibility of developing innovative materials that simultaneously self-assembled, self-organized and self-regulated; characteristics that are difficult to achieve in purely synthetic systems. Proteins play an essential role in fabrication of biological materials due to their diverse functions ranging from structural to biochemical. The ability to mimic any of these functions can be a game changer in designing new biomaterials. There are several challenges in these strategies including replicating the hierarchical organization of biological materials, organization that provides multi-scale structure/property interdependence. The interfacial interactions become critical in tuning the individual components towards the functional needs. There is a need for strategies that can control self-organization at a molecular level and thus provide predictability over the biological and inorganic interfaces. In the recent years, there has been a proliferating interest in creating advanced bio-interfaces resolving protein modulated material surfaces that allow as well as enhance favorable interactions with the surrounding biological systems. Smaller protein domains, i.e. peptides, have been utilized as the key fundamental building blocks to mimic the molecular recognition as the basis of molecular scale interactions. Our approach includes decoding the peptide-material interactions, and using these foundations to develop self-organized and multifunctional hybrid systems. Following Nature’s molecular footsteps, we explore tuning molecular interactions at bio-interfaces to create integrated bio-hybrid systems. In this presentation, we summarize our approach, which includes decoding the peptide-material interactions, and using these foundations to have better control specifically at the soft-hard interfaces. We will first describe our chimeric peptide-based approach for titanium and titanium alloys used for skeletal implants. These self-assembling binding motifs in combination with other small bioactive peptide molecules enable us to introduce additional functions encoded within the combined molecule. The resulting chimeric molecule maintains both functions, controlling their surface organization at the implantable material interface while also retaining the desired orientation to present a bioactive signal to the cells to direct their behavior. Our examples will include: i) to utilize antimicrobial peptides in controlling bacteria-surface interactions at the interfaces to prevent biofilm formation and consequent implications such as implant failure due to bacterial infections [1], ii) to direct cell-to-implant interactions by chimeric peptides that are displayed at the material interfaces to achieve guided stem cell differentiation [2]. We will finally describe our fusion protein based approach where engineered peptide tags and nanoparticle based systems are used to generate self-organized biologically integrated hybrid materials. Here we demonstrate modularity of our approach in designing polymer nanofibers integrated with nanoparticles assembled with engineered peptides that are genetically conjugated to photoactive biomarker proteins [3].The selected bio-hybrid composites will be presented in three different categories, their ability for bio-sensing, antimicrobial property and producing integrated mineralized interfaces. The integration of biological building blocks may allow harnessing the extraordinary diversity and protein functions to generate smart bio-hybrid materials for wide range of applications including sensing and tissue engineering applications

Self-Assembled Recombinant Proteins on Metallic Nanoparticles as Bimodal Imaging Probes

Combining multiple modalities is central to developing the new methods for sensing and imaging that are required for comprehensive understanding of events at the molecular level. Various imaging modalities have been developed using metallic nanoparticles owing to their exceptional physical and chemical properties. Due to their localized surface plasmon resonance characteristics, gold and silver nanoparticles exhibit unique optoelectronic properties commonly used in biomedical sciences and engineering. Self-assembled monolayers or physical adsorption have previously been adapted to functionalize the surfaces of nanoparticles with biomolecules for targeted imaging. However, depending on differences among the functional groups used on the nanoparticle surface, wide variation in the displayed biomolecular property to recognize its target may result. In the last decade, the properties of inorganic binding peptides have been proven advantageous for assembling selective functional nano-entities or proteins onto nanoparticle surfaces. Herein we explored the formation of self-assembled hybrid metallic nano-architectures composed of gold and silver nanoparticles with fluorescent proteins for use as bimodal imaging probes. We employed metal-binding peptide-based assembly to self-assemble green fluorescence protein onto metallic substrates of various geometries. Assembly of the green fluorescent proteins, genetically engineered to incorporate gold- or silver-binding peptides onto metallic nanoparticles, resulted in the generation of hybrid-, biomodal-imaging probes in a single step. Green fluorescent activity on gold and silver surfaces can be monitored using both plasmonic and fluorescent signatures. Our results demonstrate a novel bimodal imaging system that can be finely tuned with respect to nanoparticle size and protein concentration. Resulting hybrid probes may mitigate the limitation of depth penetration into biologic tissues and provide a high signal-to-noise ratio and sensitivity

Heterologous expression and characterization of a high redox potential laccase from Coriolopsis polyzona MUCL 38443

In this study, a novel laccase gene, named as Cplcc1, and its corresponding cDNA were isolated and characterized from the Coriolopsis polyzona MUCL 38443 strain. The Cplcc1 gene consists of a 1563-bp open reading frame encoding a protein of 520 amino acids with a 20-residue putative signal peptide. The size of the Cplcc1 gene is 2106 bp and it contains ten introns and five potential N-glycosylation sites. Additionally, the isolated full-length Cplcc1 cDNA was successfully expressed in Pichia pastoris. The heterologous expression conditions were also optimized and the highest activity value increased to 800 U L–1 with 1.5% methanol, 0.8 mM CuSO4, and 0.6% L-alanine supplementation. The recombinant laccase was partially purified and the molecular weight was found as approximately 54 kDa. The maximum oxidation activity was observed for 2,2-azinobis-(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) at pH 3.0. The optimal temperature was found as 70 °C. On the other hand, at 30 °C, the enzyme was stable for more than a week and its half-life was longer than 8 h. The Km, Vmax, kcat, and kcat Km –1 values of the recombinant laccase were identified as 0.137 mM, 288.6 µmol min–1 L–1, 5.73 × 105 min–1, and 4.18 × 106 min–1 mM–1,respectively. Sodium azide, L-cysteine, and SDS were found as usual inhibitors

Autonomous-Strengthening Adhesive Provides Hydrolysis-Resistance and Enhanced Mechanical Properties in Wet Conditions

The low-viscosity adhesive that is used to bond composite restorative materials to the tooth is readily damaged by acids, enzymes, and oral fluids. Bacteria infiltrate the resulting gaps at the composite/tooth interface, demineralize the tooth, and further erode the adhesive. This paper presents the preparation and characterization of a low-crosslink-density hydrophilic adhesive that capitalizes on sol-gel reactions and free-radical polymerization to resist hydrolysis and provide enhanced mechanical properties in wet environments. Polymerization behavior, water sorption, and leachates were investigated. Dynamic mechanical analyses (DMA) were conducted using water-saturated adhesives to mimic load transfer in wet conditions. Data from all tests were analyzed using appropriate statistical tests (α = 0.05). The degree of conversion was comparable for experimental and control adhesives at 88.3 and 84.3%, respectively. HEMA leachate was significantly lower for the experimental (2.9 wt%) compared to control (7.2 wt%). After 3 days of aqueous aging, the storage and rubbery moduli and the glass transition temperature of the experimental adhesive (57.5MPa, 12.8MPa, and 38.7 °C, respectively) were significantly higher than control (7.4MPa, 4.3 MPa, and 25.9 °C, respectively). The results indicated that the autonomic sol-gel reaction continues in the wet environment, leading to intrinsic reinforcement of the polymer network, improved hydrolytic stability, and enhanced mechanical properties

Combining genetic algorithm with machine learning strategies for designing potent antimicrobial peptides

Background Current methods in machine learning provide approaches for solving challenging, multiple constraint design problems. While deep learning and related neural networking methods have state-of-the-art performance, their vulnerability in decision making processes leading to irrational outcomes is a major concern for their implementation. With the rising antibiotic resistance, antimicrobial peptides (AMPs) have increasingly gained attention as novel therapeutic agents. This challenging design problem requires peptides which meet the multiple constraints of limiting drug-resistance in bacteria, preventing secondary infections from imbalanced microbial flora, and avoiding immune system suppression. AMPs offer a promising, bioinspired design space to targeting antimicrobial activity, but their versatility also requires the curated selection from a combinatorial sequence space. This space is too large for brute-force methods or currently known rational design approaches outside of machine learning. While there has been progress in using the design space to more effectively target AMP activity, a widely applicable approach has been elusive. The lack of transparency in machine learning has limited the advancement of scientific knowledge of how AMPs are related among each other, and the lack of general applicability for fully rational approaches has limited a broader understanding of the design space. Methods Here we combined an evolutionary method with rough set theory, a transparent machine learning approach, for designing antimicrobial peptides (AMPs). Our method achieves the customization of AMPs using supervised learning boundaries. Our system employs in vitro bacterial assays to measure fitness, codon-representation of peptides to gain flexibility of sequence selection in DNA-space with a genetic algorithm and machine learning to further accelerate the process. Results We use supervised machine learning and a genetic algorithm to find a peptide active against S. epidermidis, a common bacterial strain for implant infections, with an improved aggregation propensity average for an improved ease of synthesis. Conclusions Our results demonstrate that AMP design can be customized to maintain activity and simplify production. To our knowledge, this is the first time when codon-based genetic algorithms combined with rough set theory methods is used for computational search on peptide sequences

Fabrication of hybrid crosslinked network with buffering capabilities and autonomous strengthening characteristics for dental adhesives

Ingress of bacteria and fluids at the interfacial gaps between the restorative composite biomaterial and the tooth structure contribute to recurrent decay and failure of the composite restoration. The inability of the material to increase the pH at the composite/tooth interface facilitates the outgrowth of bacteria. Neutralizing the microenvironment at the tooth/composite interface offers promise for reducing the damage provoked by cariogenic and aciduric bacteria. We address this problem by designing a dental adhesive composed of hybrid network to provide buffering and autonomous strengthening simultaneously. Two amino functional silanes, 2-hydroxy-3-morpholinopropyl (3-(triethoxysilyl)propyl) carbamate and 2-hydroxy-3-morpholinopropyl (3-(trimethoxysilyl)propyl) carbamate were synthesized and used as co-monomers. Combining free radical initiated polymerization (polymethacrylate-based network) and photoacid-induced sol-gel reaction (polysiloxane) results in the hybrid network formation. Resulting formulations were characterized with regard to real-time photo-polymerization, water sorption, leached species, neutralization, and mechanical properties. Results from real-time FTIR spectroscopic studies indicated that ethoxy was less reactive than methoxy substituent. The neutralization results demonstrated that the methoxy-containing adhesives have acute and delayed buffering capabilities. The mechanical properties of synthetic copolymers tested in dry conditions were improved via condensation reaction of the hydrolyzed organosilanes. The leaching from methoxy containing copolymers was significantly reduced. The sol-gel reaction provided a chronic and persistent reaction in wet condition-performance that offers potential for reducing secondary decay and increasing the functional lifetime of dental adhesives

New Generation of Tunable Bioactive Shape Memory Mats Integrated with Genetically Engineered Proteins

Aligned poly(l-lactide)/poly(methyl methacrylate) binary blend fibers and mats loaded with a chimeric green fluorescence protein having a bioactive peptide with hydroxyapatite binding and mineralization property are prepared by pressurized gyration. The effect of processing parameters on the product morphologies, and the shape memory properties of these samples are investigated. Integration of hydroxyapatite nanoparticles into the fiber assembly is self-directed using the hydroxyapatite-binding property of the peptide genetically engineered to green fluorescence protein. Fluorescence microscopy analysis corroborated with Fourier transform infrared spectroscopy (FTIR) data confirms the integration of the chimeric protein with the fibers. An enzyme based remineralization assay is conducted to study the effects of peptide-mediated mineralization within the fiber mats. Raman and FTIR spectral changes observed following the peptide-mediated mineralization provides an initial step toward a soft-hard material transition. These results show that programmable shape memory properties can be obtained by incorporating genetically engineered bioactive peptide domains into polymer fibers