Relevant Matrix Research Articles

Evaluation of Metallo-β-Lactamase Susceptibility Testing in a Physiologic Medium.

ABSTRACTResearch in identifying alternative growth media that better mimic host conditions is gaining ground. Relative to nutrient-rich Mueller-Hinton broth (MHB), data on the influence of physiologic or host-mimicking media on metallo-β-lactamase (MBL) resistance are lacking. The objective was to evaluate meropenem susceptibility against clinical and engineered MBL-harboring Enterobacterales strains in a physiologic medium (urine). Antimicrobial susceptibility testing (AST) by broth microdilution was conducted with a wild-type Klebsiella pneumoniae strain and two engineered isogenic variants harboring K. pneumoniae carbapenemase 2 (KPC-2) or New Delhi MBL 1 (NDM-1), as well as two clinical K. pneumoniae isolates (harboring NDM-1 and VIM-1). MICs were determined in conventional cation-adjusted MHB (caMHB) and sterile-filtered urine samples (18 patients). All KPC- and MBL-harboring isolates were meropenem resistant (MICs of ≥16 mg/liter) in caMHB. AST of the KPC isolate in urine resulted in 50% (9/18 urine samples) essential agreement (i.e., within ±1 dilution, relative to the caMHB MIC), highlighting challenges with the use of urine as a medium capable of supporting AST. In the 9 AST-viable urine samples, meropenem MICs were 2- to 9-fold lower than that in caMHB (MIC of 32 mg/liter) among MBL-harboring isolates. Zinc concentrations determined by inductively coupled plasma mass spectrometry averaged 1.25 mg/liter and ranged from 0.12 to 1.14 mg/liter in caMHB and 18 urine samples, respectively. The full extent of MBL-mediated resistance among K. pneumoniae isolates appears to be attenuated in urine. Factors influencing free bioactive zinc levels warrant further investigation.IMPORTANCE Studies assessing antibiotic susceptibility profiles in nonconventional media are lacking. MBL-mediated resistance has come under scrutiny due to the dependence on extracellular zinc concentrations, which makes the choice of testing medium influential for β-lactam MICs. This study explores human urine as a physiologically relevant matrix with which susceptibility profiles of MBL-harboring isolates can be assessed, relative to conventional broth.

Fibril Assembly and Gelation of Macromolecules with Amphiphilic Repeating Units.

This paper reports the self-assembly of the fibrillar network in a concentrated solution of macromolecules with an amphiphilic structure of repeating units. The investigation of amphiphilic homopolymers and alternating copolymers with the linear and cyclic topologies, the solution with different polymer concentrations and solvent qualities, allows us to conclude that the ability to form a fibrillar gel with branched fibrils and regular subchain thickness is inherent for macromolecules with the solvophobic backbone and solvophilic pendants. The elements of the gel structure, such as the mesh size and fibrillar thickness, the number of cross-links, and their functionality, can be tuned and customized according to the requirements of their application. The results could be helpful for the directed design of the synthetic analogue of the relevant extracellular matrix, in tissue engineering, for fibrotic disease treatment and cell encapsulation.

MODELLING CHANGES, STAKEHOLDERS AND THEIR RELATIONS IN SEMANTIC 3D CITY MODELS

Abstract. Urban digital twins have been increasingly adopted by cities worldwide. Digital twins, especially semantic 3D city models as key components, have quickly become a crucial platform for urban monitoring, planning, analyses and visualization. However, as the massive influx of data collected from cities accumulates quickly over time, one major problem arises as how to handle different temporal versions of a virtual city model. Many current city modelling deployments lack the capability for automatic and efficient change detection and often replace older city models completely with newer ones. Another crucial task is then to make sense of the detected changes to provide a deep understanding of the progresses made in the cities. Therefore, this research aims to provide a conceptual framework to better assist change detection and interpretation in virtual city models. Firstly, a detailed hierarchical model of all potential changes in semantic 3D city models is proposed. This includes appearance, semantic, geometric, topological, structural, Level of Detail (LoD), auxiliary and scoped changes. In addition, a conceptual approach to modelling most relevant stakeholders in smart cities is presented. Then, a model - reality graph is used to represent both the different groups of stakeholders and types of changes based on their relative interest and relevance. Finally, the study introduces two mathematical methods to represent the relevance relations between stakeholders and changes, namely the relevance graph and the relevance matrix.

Effect of misalignment on coupling efficiency in laser diode to single-mode circular core graded-index fiber coupling via cylindrical microlens on the fiber tip

Abstract We report here the first theoretical prediction of coupling efficiency of the laser diode to single-mode graded-index fiber coupling via cylindrical microlens on the tip of the fiber in presence of possible transverse and angular mismatches. Moderately efficient cylindrical microlens on the fiber is easily fabricable and graded-index fiber has less sensitivity to macro as well as micro bending. Thus this coupling device emerges as a potential candidate in the field of coupling optics. The analysis takes into consideration the allowable aperture provided by cylindrical microlens. Further, we shall consider here the coupling in the vertical plane only since the coupling in the horizontal plane has poor performance. Using the relevant ABCD matrix of refraction for a cylindrical lens in the vertical plane, we prescribe analytical expressions of the coupling efficiencies in presence of said kinds of misalignments. In our analysis, we use Gaussian field distribution for both the laser and fiber fields. We carry on our investigation for two commonly used wavelengths namely 1.3 and 1.5 µm. As an example of graded-index fiber, we use some typical step, parabolic, and triangular index fibers in our study. The execution of the prescribed formulations involves little computation. Thus the evaluation of the concerned coupling efficiencies is very much user friendly. The present analysis surfaces the tolerance factors of the coupling devices. Accordingly, the results will prove beneficial to designers and packagers in respect of the design of such coupler involving cylindrical microlens in the field of optimum launch optics.

Recognition and Diagnosis Method of Accelerated Aging of Lithium-Ion Battery Based on Logistic Regression

Aiming at the accelerated aging problem that may occur during the use of high specific energy lithium-ion batteries, this article proposes a method to judge the accelerated aging of lithium-ion batteries. Taking the IC curve and DV curve as the starting point, the complete characteristic curve of the new battery is used as a comparison benchmark, and the battery characteristic curves of different aging stages are compared and analyzed, and the parameters that have obvious changes before and after the accelerated aging of the battery are extracted as the characteristics that the battery has accelerated aging. It is important to establish the relevant characteristic parameter matrix, and use the logistic regression method to train the accelerating aging model of the battery to realize the diagnosis of accelerating aging fault. In view of the fact that lithium batteries rarely undergo a complete charging process, the characteristic parameter sets established in this paper are based on the IC curve and the DV curve in the 15–75% SOC range, which have certain practicability.

WITHDRAWN: A three-dimensional bioprinting technique, based on a gelatin/alginate hydrogel, for the tissue engineering of hair follicle reconstruction

Hair loss remains a challenging clinical problem that influences the quality of life. Three-dimensional (3D) bioprinting has become a valuable tool for fabricating tissue constructs for transplantation and other biomedical applications. Although some simple organs, such as skin and cartilage, have been successfully simulated, it remains challenging to make hair follicles (HFs), which are highly complex organs. The tissue engineering of human HFs has been a long-standing challenge, and progress with this has lagged behind that with other lab-grown tissues. This is principally due to a lack of availability of a platform that can successfully recapitulate the microenvironmental cues required to maintain the requisite cellular interactions for hair neogenesis. In this study, we used a 3D bioprinting technique based on a gelatin/alginate hydrogel to construct a multilayer composite scaffold with cuticular and corium layers to simulate the microenvironment of dermal papilla cells (DPCs) in the human body. This new approach permits the controllable formation of self-aggregating spheroids of DPCs in a physiologically relevant extracellular matrix and the initiation of epidermal-mesenchymal interactions, which results in HF formation in vivo. In conclusion, our 3D-bioprinted multilayer composite scaffold prepared using a gelatin/alginate hydrogel provides a suitable 3D microenvironment for DPCs to induce HF formation. The ability to regenerate entire HFs should have a significant impact on the medical management of hair loss. This method may also have critical applications for skin tissue engineering, with its appendages, for other purposes.

Convergence of Distributed Accelerated Algorithm Over Unbalanced Directed Networks

In this article, the problem of the distributed convex optimization is investigated, where the target is to collectively minimize a sum of local convex functions over an unbalanced directed multiagent network. Each agent in the network possesses only its private local objective function, and the sum of all local objective functions constitutes the global objective function. We particularly consider the scenario, where the underlying interaction network is strongly connected and the relevant weight matrix is row stochastic. To collectively figure out the optimization problem, a distributed accelerated convergence algorithm where agents utilize uncoordinated step-sizes is presented by incorporating consensus of multiagent networks into distributed inexact gradient tracking technique. Most of the existing methods require all agents to possess the out-degree information of their in-neighbors, which is impractical and hardly inevitable as interpreted in this article. By utilizing the small-gain theorem, we prove that if the maximum step-size is positive and sufficiently small (constrained by a specific upper bound), the proposed algorithm, termed as SGT-FROST, converges geometrically to the optimal solution given that the objective functions are smooth and strongly convex. A certain convergence rate is also shown. Simulations confirm the findings in this article.

Particle and metal exposure in Parisian subway: Relationship between exposure biomarkers in air, exhaled breath condensate, and urine.

Subway particulate toxicity results from in vitro and in vivo studies diverge and call for applied human research on outcomes from chronic exposures and potential exposure biomarkers. We aimed to (1) quantify airborne particulate matter (PM) concentrations (mass and number) and metal concentrations in exhaled breath condensate (EBC), urine, and PM; (2) investigate their associations (EBC vs. PM vs. urine); and (3) assess the relevance of EBC in biomonitoring. Nine subway workers in three jobs: station agents, locomotive operators and security guards were monitored during their 6-h shifts over two consecutive weeks. Six-hour weighed average mass concentrations expressed as PM10, PM2.5 and their metal concentrations were determined. Urine and EBC samples were collected pre- and post-shift. Ultrafine particle (UFP) number concentrations were quantified in PM and EBC samples. Metal concentrations in urine and EBC were standardized by creatinine and EBC volume, respectively, and log-transformed. Associations were investigated using Pearson correlation and linear mixed regression models, with participant's ID as random effect. PM concentrations were below occupational exposure limits (OEL) and varied significantly between jobs. Locomotive operators had the highest exposure (189 and 137μg/m3 for PM10 and PM2.5, respectively), while station agents had the highest UFP exposure (1.97×104 particles/cm3). Five metals (Al, Fe, Zn, Cu, and Mn) in PM2.5 and three (Al, Fe, and Zn) in PM10 were above the limit of quantification (LOQ). Fe, Cu, Al and Zn were the most abundant by mass fraction in PM. In EBC, the metal concentrations in decreasing order were: Zn>Cu>Ni>Ba>Mn. Security guards had the highest EBC metal concentrations, and in particular Zn and Cu. Urinary metal concentrations in decreasing order were: Si>Zn>Mo>Ti>Cu>Ba≈Ni>Co. All urinary metal concentrations from the subway workers were similar to concentrations found in the general population. A statistically significant relationship was found for ultrafine particle number concentrations in PM and in EBC. Zn and Cu concentrations in post-shift EBC were associated with Zn and Cu concentrations in PM10 and with post-shift urinary Zn and Cu concentrations. Therefore, EBC appears a relevant matrix for assessing exposure to UFP in human biomonitoring when inhalation is a primary route of exposure. We found different temporal variation patterns between particle and metal exposures in three matrices (PM, urine, EBC) quantified daily over two full weeks in subway workers. These patterns might be related to metal oxidation, particulates' solubility and size as well as their lung absorption capabilities, which need to be further explored in toxicological research. Further research should also focus on understanding possible influences of low chronic exposures to subway particulates on health in larger cohorts.

Fast Direct Solution of 2D Scalar Volume Integral Equation via Tensor Train Decomposition for Scatterers of Arbitrary Shape

The method of moments (MoM) discretization of the volume integral equation (VIE) is an effective tool for calculating field responses in the presence of arbitrary scatterers. This method scales poorly with problem size, however, due to the inherent difficulty of inverting the relevant matrix equations. The application of tensor train (TT) decomposition techniques has recently shown promise in alleviating the complexity of such calculations, with dramatic efficiency boosts in both computational time and memory having been proven possible for very simple scatterers. For arbitrary scatterers, previous work has shown that a conjugate gradient- TT (CG- TT) procedure was still capable of producing favorable runtime and memory complexities, particularly in quasi-constant rank regimes. In this work, we consider a direct solution of TT decomposed MoM matrix equation approach that is largely insensitive to MoM matrix condition number, while maintaining the generality of CG- TT. Preliminary results indicate that this approach is capable of matching the efficiency of CG- TT in the quasi-constant rank regime for scatterers of arbitrary geometry.

Exceptional points of degeneracy in traveling wave tubes

The traveling wave tube (TWT) is a powerful vacuum electronic device used to amplify radio-frequency signals with numerous applications, including radar, television, and telephone satellite communications. TWT design in a nutshell comprises a pencil-like electron beam (e-beam) in vacuum interacting with a guiding slow-wave structure (SWS). In our studies here, the e-beam is represented by one-dimensional electron flow and SWS is represented by a transmission line (TL). The interaction between the e-beam and the TL is modeled by an analytic theory that generalizes the well-known Pierce model by taking into account the so-called space-charge effects, particularly electron-to-electron repulsion (debunching). Many important aspects of the analytic theory of TWTs have been already analyzed in our monograph on the subject. The focus of the studies here is on degeneracies of the TWT dispersion relations, particularly on exceptional points of degeneracy and their applications. The term exceptional point of degeneracy (EPD) refers to the property of the relevant matrix to have a nontrivial Jordan block structure. Using special parameterization, particularly suited to chosen EPD, we derive exact formulas for the relevant Jordan basis, including the eigenvectors and the so-called root vector associated with the Jordan block. Based on these studies, we develop a constructive approach to sensing of small signals.

Frame-Based Filter-Function Formalism for Quantum Characterization and Control

We introduce a theoretical framework for resource-efficient characterization and control of non-Markovian open quantum systems, which naturally allows for the integration of given, experimentally motivated, control capabilities and constraints. This is achieved by developing a transfer filter-function formalism based on the general notion of a frame and by appropriately tying the choice of frame to the available control. While recovering the standard frequency-based filter-function formalism as a special instance, this control-adapted generalization affords intrinsic flexibility and, crucially, it permits an efficient representation of the relevant control matrix elements and dynamical integrals if an appropriate finite-size frame condition is obeyed. Our frame-based formulation overcomes important limitations of existing approaches. In particular, we show how to implement quantum noise spectroscopy in the presence of nonstationary noise sources, and how to effectively achieve control-driven model reduction for noise-optimized prediction and quantum gate design.

Using 3D perfusion bioreactor system to studying cell biology of ovarian cancer.

e17558 Background: Epithelial Ovarian Cancer (EOC) is the most common cause of death among gynecological malignancies. This is a result of the high rate of recurrence and chemo-resistance in EOC patients. Therefore, the development of new therapeutics is crucial. A major factor contributing to this is the lack of therapeutic candidates is lack of translational accuracy in preclinical models. Recently, 3-dimensional (3-D) models have aided in accurately recreating tumor biology. We have developed an EOC 3-D perfused bioreactor system that recapitulates EOC tumor biology and incorporates tumor biomechanical regulation. This model allows for us to more accurately predict the clinical response of new drug candidates, which aids in elimination of ineffective candidates prior to clinical trials. Methods: EOC cell lines (luciferase-taggedSKOV-3 and OVCAR-8) were embedded in a relevant extracellular matrix (ECM) and injected into a perfused, polydimethylsiloxane (PDMS) bioreactor. Microchannels were embedded in matrigel so that the cell culture media with or without chemotherapy could flow through the perfused PDMS to provide nutrient delivery and gas exchange enhancing viability and function of surrounding cells. The bioreactors were connected to a peristaltic pump that allowed for the cell culture media to perfuse over a 7-day period. We monitored cell viability using bioluminescence imaging (BLI), immunohistochemistry (IHC), and lactate dehydrogenase (LDH) release in media. Results: BLI showed a linear increase in SKOV-3 and OVCAR-8 cell growth over 7 days. These results were confirmed by IHC measuring the number of nucleated cells per micron2. Graphical representation of the region of interest (ROI) showed a high correlation between IHC staining of nucleated cells and BLI score. IHC analysis of PAX8 staining was positive and proved that the perfusion bioreactor system maintains EOC biology over time. In addition, our results suggest that the bioreactor is a suitable model for drug preclinical testing in both cell lines as well as in patients’ samples. Conclusions: Our preliminary results using the 3D EOC perfused, PDMS bioreactor model showed increased EOC cell growth overtime, while maintaining original EOC histology. Moreover, our results suggest that this model could provide a novel platform to study therapeutic interventions in EOC. Our ultimate goal is to implement ovarian cancer microenvironment components (e.g. immune cells) into bioreactor system to study different drug treatments to better determine drug candidate’s translational efficacy.

Role of Bc+→Bs,d(*)ℓ¯νℓ in the Standard Model and in the search for BSM signals

The decays $B_c^+ \to B_{a} \bar \ell \nu_\ell$ and $B_c^+ \to B_{a}^{*}(\to B_a \gamma) \bar \ell \nu_\ell$, with $a=s,d$ and $\ell=e,\mu$, are studied in the Standard Model (SM) and in the extension based on the low-energy Hamiltonian comprising the full set of dimension-$6$ semileptonic $c \to s,d$ operators with left-handed neutrinos. Tests of $\mu/e$ universality are investigated using such modes. The heavy quark spin symmetry is applied to relate the relevant hadronic matrix elements and to exploit lattice QCD results on $B_c$ form factors. Optimized observables are selected, and the pattern of their correlations is studied to identify the effects of the various operators in the extended low-energy Hamiltonian.

FunkR-pDAE: Personalized Project Recommendation Using Deep Learning

In open source communities, developers always need to spend plenty of time and energy on discovering specific projects from massive open source projects. Consequently, the study of personalized project recommendation for developers has important theoretical and practical significance. However, existing recommendation approaches have clear limitations, such as ignoring developers' operating behavior, social relationships and practical skills, and are very inefficient for large amounts of data. To address these limitations, this paper proposes FunkR-pDAE (Funk singular value decomposition Recommendation using pearson correlation coefficient and Deep Auto-Encoders), a novel personalized project recommendation approach using a deep learning model. FunkR-pDAE first extracts data related to developers and open source projects from open source communities, which build a developer-open source project relevance matrix and a developer-developer relevance matrix. Meanwhile, Pearson Correlation Coefficient is utilized to calculate developer similarity using the developer-developer relevance matrix. Second, deep auto-encoders are used to learn the factor vectors that represent developers and open source projects. Finally, a sorting method is defined to provide personalized project recommendations. Experimental results on real-world GitHub data sets show that FunkR-pDAE has a precision rate of 75.46 percent and a recall rate of 40.32 percent, which provides more effective recommendation compared with state-of-the-art approaches.

Tucumã (Astrocaryum aculeatum) Prevents Oxidative and DNA Damage to Retinal Pigment Epithelium Cells.

Eye diseases have a negative impact on the eyesight quality of the world population. The age-related macular degeneration (AMD) draws special attention since it is a chronic disorder characterized by oxidative and inflammatory damage to the retinal epithelial pigment, which triggers progressive vision loss. In the Brazilian Amazon, Astrocaryum aculeatum is an Amazonian fruit (Tucumã) used by riverside communities in traditional medicine to treat a number of ailments. These communities have recently shown to have increased longevity and reduced prevalence of age-related morbidity. Thus, the aim of this research was to chemically characterize and analyze the in vitro antioxidant effect and molecular damage prevention of the Tucumã ethanolic extract in retinal pigment epithelium (RPE) cells in a model for AMD. The extract was chemically characterized by ultra-high-performance liquid chromatography (HPLC) coupled with diode-array detection and mass spectrophotometry (HPLC-DAD-MS). In vitro protocols were performed, and the cytopreventive effect of Tucumã on RPE cells exposed to high concentrations of superoxide anion, an oxidant and genotoxic molecule, as well as the effect of Tucumã extract on oxidative and molecular makers were assessed. Biochemical and flow cytometry analyses were conducted in these protocols. The extract presents high concentrations of caffeic acid, gallic acid, catechin, luteolin, quercetin, and rutin. Treatment did not show cytotoxic effects in cells treated only with extract at 50 μg/mL. In fact, it improved cell viability and was able to prevent necrosis and apoptosis, and oxidative and molecular damage was significantly reduced. In summary, Tucumã is an important Amazon fruit, which seems to contribute significantly to improve human health conditions, as our findings suggest that its extract has a relevant chemical matrix rich in antioxidant molecules, and its consumption could improve eye health and contribute to prevention against oxidative stress through cytoprevention, reactive oxygen species reduction, and maintenance of DNA integrity in retinal pigment epithelium (RPE) cells.

SARS-CoV-2 is rapidly inactivated at high temperature

In the absence of a vaccine, preventing the spread of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the primary means to reduce the impact of the 2019 coronavirus disease (COVID-19). Multiple studies have reported the presence of SARS-CoV-2 genetic material on surfaces suggesting that fomite transmission of SARS-CoV-2 is feasible. High temperature inactivation of virus has been previously suggested, but not shown. In the present study, we investigated the environmental stability of SARS-CoV-2 in a clinically relevant matrix dried onto stainless steel at a high temperature. The results show that at 54.5 °C, the virus half-life was 10.8 ± 3.0 min and the time for a 90% decrease in infectivity was 35.4 ± 9.0 min. These findings suggest that in instances where the environment can reach temperatures of at least 54.5 °C, such as in vehicle interior cabins when parked in warmer ambient air, that the potential for exposure to infectious virus on surfaces could be decreased substantially in under an hour.

Pionless effective field theory evaluation of nuclear polarizability in muonic deuterium

We calculate the longitudinal structure function of the deuteron up through next-to-next-to-leading order in the framework of pionless effective field theory. We use these results to compute the two-photon polarizability contribution to Lamb shift in muonic deuterium, which can be utilized to extract the nuclear charge radius of the deuteron. We present analytical expressions order-by-order for the relevant transition matrix elements and the longitudinal structure function, and we give numerical results for the corresponding contributions to the Lamb shift. We also discuss the impact of relativistic and other higher-order effects. We find agreement with previous calculations and explain the accuracy of our calculation.

Optimal novel approach for estimating the pavement transition probabilities used in Markovian prediction models

ABSTRACT An optimal novel approach is proposed to estimate the transition probabilities associated with both homogeneous and non-homogeneous Markov chains. The approach applies an exhaustive optimisation technique to search for the optimal transition probabilities associated with minimal sum of squared errors (SSE), wherein the error defined as the difference between predicted and observed pavement condition ratings. Three state transitions are allowed in constructing the relevant transition probability matrix (TPM). In the homogenous chain, the approach yields one optimal TPM applicable to an analysis period of (n) years. Whereas, one distinct optimal TPM can be derived for each year if non-homogenous chain is deployed. A sequential iterative optimisation approach is proposed wherein the optimal TPM for a given year becomes the input for the subsequent year. Sample results are presented for two projects (A & B) with superior and inferior performances, respectively. The sample results indicate that the non-homogenous chain provided significant reduction in the SSE compared to the homogeneous one. However, the use of 10 condition states instead of 5 resulted in moderate reduction in the SSE considering both homogeneous and non-homogeneous Markov chains. Also, the results indicate that the use of three state transitions made significant impact when deploying 10 condition states instead of 5 especially in the case of inferior performance.

Mucoadhesive Poloxamer-Based Hydrogels for the Release of HP-β-CD-Complexed Dexamethasone in the Treatment of Buccal Diseases.

Oral lichen planus (OLP) is an ongoing and chronic inflammatory disease affecting the mucous membrane of the oral cavity. Currently, the treatment of choice consists in the direct application into the buccal cavity of semisolid formulations containing a corticosteroid molecule to decrease inflammatory signs and symptoms. However, this administration route has shown various disadvantages limiting its clinical use and efficacy. Indeed, the frequency of application and the incorrect use of the preparation may lead to a poor efficacy and limit the treatment compliance. Furthermore, the saliva clearance and the mechanical stress present in the buccal cavity also involve a decrease in the mucosal exposure to the drug. In this context, the design of a new pharmaceutical formulation, containing a steroidal anti-inflammatory, mucoadhesive, sprayable and exhibiting a sustained and controlled release seems to be suitable to overcome the main limitations of the existing pharmaceutical dosage forms. The present work reports the formulation, optimization and evaluation of the mucoadhesive and release properties of a poloxamer 407 thermosensitive hydrogel containing a poorly water-soluble corticosteroid, dexamethasone acetate (DMA), threaded into hydroxypropyl-beta-cyclodextrin (HP-β-CD) molecules. Firstly, physicochemical properties were assessed to ensure suitable complexation of DMA into HP-β-CD cavities. Then, rheological properties, in the presence and absence of various mucoadhesive agents, were determined and optimized. The hydration ratio (0.218–0.191), the poloxamer 407 (15–17 wt%) percentage and liquid-cyclodextrin state were optimized as a function of the gelation transition temperature, viscoelastic behavior and dynamic flow viscosity. Deformation and resistance properties were evaluated in the presence of various mucoadhesive compounds, being the sodium alginate and xanthan gum the most suitable to improve adhesion and mucoadhesion properties. Xanthan gum was shown as the best agent prolonging the hydrogel retention time up to 45 min. Furthermore, xanthan gum has been found as a relevant polymer matrix controlling drug release by diffusion and swelling processes in order to achieve therapeutic concentration for prolonged periods of time.

Selective Campylobacter detection and quantification in poultry: A sensor tool for detecting the cause of a common zoonosis at its source

Thermotolerant Campylobacter bacteria, most notably Campylobacter jejuni and Campylobacter coli, are a major cause of human foodborne gastroenteritis, which is usually related to consumption of contaminated poultry. In this work, we present a sensor and the associated assay for the on-site detection of the prevalent species C. jejuni and C. coli. The sensor uses surface-imprinted polymer (SIP) layers as selective, biomimetic recognition elements in combination with a modified heat-transfer method (M-HTM) as a label-free, quantitative readout principle. The selectivity for C. coli and C. jejuni was evaluated against six other morphologically similar Campylobacterales species, confirming that the sensor is selective at species level while responding uniformly to different strains within the same species. For the relevant matrix, that is chicken cecal droppings suspended in PBS buffer, the detection limits are 1.1 × 103 CFU/mL for C. coli and 2.7 × 104 CFU/mL for C. jejuni, which is both low enough for a meaningful diagnostic test. The sensor concept requires only a minimum of sample preparation and a given concentration can be measured within less than one hour: Both are important assets for on-site detection such as on a poultry farm or in a slaughterhouse, keeping in mind that Campylobacter detection with established methods in analytical laboratories takes 2–4 days for obtaining the result.