Comparison of Different Mass Spectrometry Workflows for the Proteomic Analysis of Tear Fluid

The tear film is a multi-layer fluid that covers the corneal and conjunctival epithelia of the eye and provides lubrication, nutrients, and protection from the outside environment. Tear fluid contains a high concentration of proteins and has thus been recognized as a potential source of biomarkers for ocular disorders due to its proximity to disease sites on the ocular surface and the non-invasive nature of its collection. This is particularly true in the case of dry eye disease, which directly impacts the tear film and its components. Proteomic analysis of tear fluid is challenging mainly due to the wide dynamic range of proteins and the small sample volumes. However, recent advancements in mass spectrometry have revolutionized the field of proteomics enabling unprecedented depth, speed, and accuracy, even with small sample volumes. In this study using the Orbitrap Fusion Tribrid mass spectrometer, we compared four different mass spectrometry workflows for the proteomic analysis of tear fluid collected via Schirmer strips. We were able to establish a method of in-strip protein digestion that identified >3000 proteins in human tear samples from 11 healthy subjects. Our method offers a significant improvement in the number of proteins identified compared to previously reported methods without pooling samples.     

Poly(ε‐caprolactone) composites containing gentamicin‐loaded β‐tricalcium phosphate/gelatin microspheres as bone tissue supports

In this work, novel antibacterial composites were prepared by using poly(ε‐caprolactone) (PCL) as the main matrix material, and gentamicin‐loaded microspheres composed of β‐tricalcium phosphate (β‐TCP) and gelatin. The purpose is to use this biodegradable material as a support for bone tissue. This composite system is expected to enhance bone regeneration by the presence of β‐TCP and prevent a possible infection that might occur around the defected bone region by the release of gentamicin. The effects of the ratio of the β‐TCP/gelatin microspheres on the morphological, mechanical, and degradation properties of composite films as well as in vitro antibiotic release and antibacterial activities against Escherichia coli and Staphylococcus aureus were investigated. The results showed that the composites of PCL and β‐TCP/gelatin microspheres had antibacterial activities for both bacteria. © 2012 Wiley Periodicals, Inc. J. Appl. Polym. Sci., 2013     

An Analytical Model for Compressive Creep Behavior of HDPE Used in Plastic Pipe Manufacturing

The creep behavior of high-density polyethylene has been studied by low compressive creep tests, and empirical results were analyzed and compared with analytically predicted results. The tests are performed upon ASTM standard specimens at various stress levels in the linear region. After these analyses, a mathematical model is derived and used to predict creep strain for long periods of time from the strain-time data obtained at different stresses over a time interval of 24 h.     

Spectroelectrochemical study of N‐ethyl‐carbazole in the presence of acrylamide

Polymerization of N‐ethylcarbazole (NECz) in the presence of acrylamide (AAm) has been investigated by in situ and ex situ UV–visible spectrophotometric measurements to obtain information about the reaction pathway, because NECz gives soluble oligomeric species allowing such measurements. A tentative mechanism is proposed in the light of these results. The redox properties of the new polymers have been studied for possible sensor application. © 2001 Society of Chemical Industry     

Changes in Volatile Compounds of Black Cumin Oil and Hazelnut Oil by Microwave Heating Process

Black cumin and hazelnut oils were subjected to a heating process in a microwave oven for a duration of 2, 4, 6 and 8 min at a constant frequency of 2450 MHz and a power of 0.45 kW. The ultraviolet absorption and volatile products of the oils were investigated in detail during the processes. The experimental evidences obtained show that K₂₃₂ and K₂₇₀ parameters reach values of 4.69 and 1.30 for black cumin oil, 3.22 and 1.75 for hazelnut oil, respectively with the increment of heating time. The headspace SPME method was used to analyze volatile compounds extracted from black cumin and hazelnut oils being exposed to the microwave heating process. The SPME–GC/MS method allowed the detection of 17 identified volatile compounds (hexanal, α‐thujene, α‐pinene, sabinene, β‐pinene, 2‐heptenal, α‐terpinene, limonene, p‐cymene, γ‐terpinene, E‐2‐octenal, nonanal, 4‐terpineol, thymoquinone, E,E‐2,4‐decadienal, α‐longipinene and isolongifolene) in black cumin oils. Of the products, hexanal, 2‐heptenal, E‐2‐octenal, nonanal and E,E‐2,4‐decadienal were determined to be the predominant volatile oxidation products. In fact, the hexanal was found as a major volatile oxidation compound and reached a local maximum point of 7.41 × 10⁶ AU at the end of heating. On the other hand, only 8 volatile oxidation products (hexanal, heptanal, 2‐heptenal, nonanal, E‐2‐decenal, E,Z‐2,4‐decadienal, E,E‐2,4‐decadienal and E‐2‐tridecenal) were identified in hazelnut oils as a consequence of the heating process. Based on the experimental evidence observed, it is reasonable to conclude that the nonanal content dramatically increased at the end of heating and reached a value of 9.22 × 10⁶ AU.     

Modeling uranium biosorption by Cystoseira sp. and application studies

The aim of the present work was to determine the applicability of raw and modified brown macroalga Cystoseira sp. as a biosorbent material for the sorption of uranium ions from aqueous solutions. Equilibrium of uranium biosorption was analyzed under isotherm models and thermodynamic parameters of the process. Recovery of uranium from acidic mine wastewater was also applied. The mechanism of biosorption was discussed considering experimental data and theoretical models. The bioremoval efficiency of modified biomass was higher than raw Cystoseira sp. and the theoretical biosorption capacity of modified biosorbent was calculated to be 468.01 mg U/g.     

Application of two non-linear prediction tools to the estimation of tunnel boring machine performance

Predicting tunnel boring machine (TBM) performance is a crucial issue for the accomplishment of a mechanical tunnel project, excavating via full face tunneling machine. Many models and equations have previously been introduced to estimate TBM performance based on properties of both rock and machine employing various statistical analysis techniques. However, considering the nature of the problem, it is relatively difficult to estimate tunnel boring machine performance by linear prediction models. Artificial neural networks (ANNs) and non-linear multiple regression models have great potential for establishing such prediction models. The purpose of the present study is the construction of non-linear multivariable prediction models to estimate TBM performance as a function of rock properties. For this purpose, rock properties and machine data were collected from recently completed TBM tunnel project in the City of New York, USA and consequently the database was established to develop performance prediction models utilizing the ANN and the non-linear multiple regression methods. This paper presents the results of study into the application of the non-linear prediction approaches providing the acceptable precise performance estimations.     

On decentralized stabilization and structure of linear large scale systems

Connective stabilizability of large-scale systems, which are composed of interconnected subsystems, is considered using decentralized feedback. Both analytical and graph-theoretic conditions are derived directly in terms of the interconnection structure, which ensure that stability of the overall closed-loop system is invariant under the structural perturbations caused by disconnections and reconnections of links among the subsystems. The conditions characterize a large class of decentrally stabilizable systems, which includes all classes of connectively stabilizable interconnected systems considered so far.     

A new technique for precedence-ordering chemical process equation sets

An algorithm that combines structural equation analysis with algebraic rearrangement and substitution has been developed to precedence-order algebraic chemical process equations. The SWS (Structural Analysis with Substitutions) algorithm selects an output variable for each equation, rearranges the equation to solve for that variable, and reduces the number of equations by substitution. The algorithm has been used for computer generation of Fortran programs to perform meterial and energy balances in the design of chemical processes.