Enhancing the selectivity of gas sensing materials towards specific volatile organic compounds (VOCs) is
challenging due to the chemical simplicity of VOCs as well as the difficulty in interfacing VOC selective
biological elements with electronic components used in the transduction process. We aimed to tune the
selectivity of gas sensing materials through the incorporation of VOC-selective peptides into gel-like gas
sensing materials. Specifically, a peptide (P1) known to discriminate single carbon deviations among benzene
and derivatives, along with two modified versions (P2 and P3), were integrated with gel compositions
containing gelatin, ionic liquid and without or with a liquid crystal component (ionogels and hybrid gels
respectively). These formulations change their electrical or optical properties upon VOC exposure, and were
tested as sensors in an in-house developed e-nose. Their ability to distinct and identify VOCs was evaluated
via a supervised machine learning classifier. Enhanced discrimination of benzene and hexane was detected
for the P1-based hybrid gel. Additionally, complementarity of the electrical and optical sensors was observed
considering that a combination of both their accuracy predictions yielded the best classification results for the
tested VOCs. This indicates that a combinatorial array in a dual-mode e-nose could provide optimal
performance and enhanced selectivity.

Ionogel are versatile materials, as they present the electrical properties of ionic liquids and also dimensional stability, since they are trapped in a solid matrix, allowing application in electronic devices such as gas sensors and electronic noses. In this work, ionogels were designed to act as a sensitive layer for the detection of volatiles in a custom-made electronic nose. Ionogels composed of gelatin and a single imidazolium ionic liquid were doped with bare and functionalized iron oxide nanoparticles, producing ionogels with adjustable target selectivity. After exposing an array of four ionogels to 12 distinct volatile organic compounds, the collected signals were analyzed by principal component analysis (PCA) and by several supervised classification methods, in order to assess the ability of the electronic nose to distinguish different volatiles, which showed accuracy above 98%.

Antimicrobial resistance is one of the most worrying threats to humankind with extremely high healthcare costs associated. The current technologies used in clinical microbiology to identify the bacterial agent and profile antimicrobial susceptibility are time‐consuming and frequently expensive. As a result, physicians prescribe empirical antimicrobial therapies. This scenario is often the cause of therapeutic failures, causing higher mortality rates and healthcare costs, as well as the emergence and spread of antibiotic resistant bacteria. As such, new technologies for rapid identification of the pathogen and antimicrobial susceptibility testing are needed. This review summarizes the current technologies, and the promising emerging and future alternatives for the identification and profiling of antimicrobial resistance bacterial agents, which are expected to revolutionize the field of clinical diagnostics.

The development of gas sensing materials is relevant in the field of non-invasive biodevices. In this work, we used an electronic nose (E-nose) developed by our research group, which possess versatile and unique sensing materials. These are gels that can be spread over the substrate by Film Coating or Spin Coating. This study aims to evaluate the influence of the sensing film spreading method selected on the classification capabilities of the E-nose. The methodology followed consisted of performing an experiment where the E-nose was exposed to 13 different pure volatile organic compounds. The sensor array had two sensing films produced by Film Coating, and other two produced by Spin Coating. After data collection, a set of features was extracted from the original signal curves, and the best were selected by Recursive Feature Elimination. Then, the classification performance of Multinomial Logistic regression, Decision Tree, and Naíve Bayes was evaluated. The results showed that both s preading methods for sensing film’s production are adequate since the estimated error of classification was inferior to 4 % for all the classification tools applied.

The human Pin1 WW domain (hPin1_WW) is a 38 residue protein which specifically recognizes ligands rich in proline and phosphorylated in Ser and Thr residues. This work presents a protocol for the improved chemical synthesis and modification of this protein through automated microwave assisted synthesis combined with the incorporation of pseudoproline units in the protein sequence. After purification{,} the protein was characterized by Mass Spectrometry and Circular Dichroism spectroscopy with results comparable to the same WW domain chemically synthesized by other strategies or biologically expressed. The protein was further immobilized on a matrix and tested for the selective binding and mild elution of phosphorylated sequences at Ser{,} Thr and Tyr residues. These results suggest that hPin1_WW is a useful protein scaffold for the purification of phosphorylated species in pTyr and pSer{,} which can be easily produced and modified by chemical methods.

Laboratory studies were conducted to evaluate the interaction between bare and polymer-coated magnetic nanoparticles (MNPs) with various environmentally relevant carrying solutions including natural oceanic seawater with and without addition of algal exopolymeric substances (EPS). The MNPs were coated with three different stabilising agents, namely gum Arabic (GA-MNP), dextran (D-MNP) and carboxymethyl-dextran (CMD-MNP). The colloidal stability of the suspensions was evaluated over 48 h and we demonstrated that: (i) hydrodynamic diameters increased over time regardless of carrying solution for all MNPs except the GA-coated ones; however, the relative changes were carrying solution- and coat-dependent; (ii) polydispersity indexes of the freshly suspended MNPs are below 0.5 for all coated MNPs, unlike the much higher values obtained for the uncoated MNPs; (iii) freshly prepared MNP suspensions (both coated and uncoated) in Milli-Q (MQ) water show high colloidal stability as indicated by zeta-potential values below -30 mV, which however decrease in absolute value within 48 h for all MNPs regardless of carrying solution; (iv) EPS seems to "stabilise" the GA-coated and the CMD-coated MNPs, but not the uncoated or the D-coated MNPs, which form larger aggregates within 48 h; (v) despite this aggregation, iron (Fe)-leaching from MNPs is sustained over 48h, but remained within the range of 3-9% of the total iron-content of the initially added MNPs regardless of suspension media and capping agent. The environmental implications of our findings and biotechnological applicability of MNPs are discussed.

Background
In situ magnetic separation (ISMS) has emerged as a powerful tool to overcome process constraints such as product degradation or inhibition of target production. In the present work, an integrated ISMS process was established for the production of his-tagged single chain fragment variable (scFv) D1.3 antibodies (?D1.3?) produced by E. coli in complex media. This study investigates the impact of ISMS on the overall product yield as well as its biocompatibility with the bioprocess when metal-chelate and triazine-functionalized magnetic beads were used.

Results
Both particle systems are well suited for separation of D1.3 during cultivation. While the triazine beads did not negatively impact the bioprocess, the application of metal-chelate particles caused leakage of divalent copper ions in the medium. After the ISMS step, elevated copper concentrations above 120?mg/L in the medium negatively influenced D1.3 production. Due to the stable nature of the model protein scFv D1.3 in the biosuspension, the application of ISMS could not increase the overall D1.3 yield as was shown by simulation and experiments.

Conclusions
We could demonstrate that triazine-functionalized beads are a suitable low-cost alternative to selectively adsorb D1.3 fragments, and measured maximum loads of 0.08?g D1.3 per g of beads. Although copper-loaded metal-chelate beads did adsorb his-tagged D1.3 well during cultivation, this particle system must be optimized by minimizing metal leakage from the beads in order to avoid negative inhibitory effects on growth of the microorganisms and target production. Hereby, other types of metal chelate complexes should be tested to demonstrate biocompatibility. Such optimized particle systems can be regarded as ISMS platform technology, especially for the production of antibodies and their fragments with low stability in the medium. The proposed model can be applied to design future ISMS experiments in order to maximize the overall product yield while the amount of particles being used is minimized as well as the number of required ISMS steps.

Iron oxide magnetic nanoparticles {(MNPs)} were synthesized by the chemical co-precipitation method and coated with gum arabic {(GA)} by physical adsorption and covalent attachment. Cultures of mammalian cell lines {(HEK293}, {CHO} and {TE671)} were grown in the presence of uncoated and {GA-coated} {MNPs.} Cellular growth was followed by optical microscopy in order to assess the proportion of cells with particles, alterations in cellular density and the presence of debris. The in vitro assays demonstrated that cells from different origins are affected differently by the presence of the nanoparticles. Also, the methods followed for {GA} coating of {MNPs} endow distinct surface characteristics that probably underlie the observed differences when in contact with the cells. In general, the nanoparticles to which the {GA} was adsorbed had a smaller ability to attach to the cells' surface and to compromise the viability of the cultures. Copyright © 2010 John Wiley & Sons, Ltd.