Analytical rheology as a tool for the structural investigation of citrus pectin.

Rheological analysis of citrus pectin at pH 3 and 7 elucidates its structural dynamics, revealing distinct behaviors influenced by pH. At pH 3, pectin exhibits shear-thinning, with solvent-independent unified rheological profiles identifying three concentration regimes: 0.5%-1.5%, 2%-3%, and 3.5%-4%. These regimes, alongside Cox-Merz superpositions, outline the semi-dilute (c*) and concentrated (c**) transitions at 1.5%-2% and 3%-3.5%, respectively. Moreover, a Morris equation exponent of 0.65 indicates flexible, mobility-restricted macromolecules. Conversely, at pH 7, increased viscosities and Morris plot linearity for p = .1 suggest rigid chain behavior due to electrostatic repulsion among ionized acidic groups. This rigidity leads to concentration-dependent self-assembly structures that diverge from expected unified rheological profiles, a deviation amplified by heating-cooling cycles. This study clarifies the impact of pH on citrus pectin's rheology and emphasizes the intricate relationship between polymeric chain rigidity, self-assembly, and viscosity. By providing a refined understanding of these mechanisms, our findings contribute to the broader field of polysaccharide research, offering insights critical for developing and optimizing pectin-based applications in various industries.

Development and characterization of solid lipid-based formulations (sLBFs) of ritonavir utilizing a lipolysis and permeation assay.

As a high number of active pharmaceutical ingredients (APIs) under development belong to BCS classes II and IV, the need for improving bioavailability is critical. A powerful approach is the use of lipid-based formulations (LBFs) that usually consist of a combination of liquid lipids, cosolvents, and surfactants. In this study, ritonavir loaded solid LBFs (sLBFs) were prepared using solid lipid excipients to investigate whether sLBFs are also capable of improving solubility and permeability. Additionally, the influence of polymeric precipitation inhibitors (PVP-VA and HPMC-AS) on lipolysis triggered supersaturation and precipitation was investigated. One step intestinal digestion and bicompartmental permeation studies using an artificial lecithin-in-dodecane (LiDo) membrane were performed for each formulation. All formulations presented significantly higher solubility (5 to >20-fold higher) during lipolysis and permeation studies compared to pure ritonavir. In the combined lipolysis-permeation studies, the formulated ritonavir concentration increased 15-fold in the donor compartment and the flux increased up to 71 % as compared to non-formulated ritonavir. The formulation with the highest surfactant concentration showed significantly higher ritonavir solubility compared to the formulation with the highest amount of lipids. However, the precipitation rates were comparable. The addition of precipitation inhibitors did not influence the lipolytic process and showed no significant benefit over the initial formulations with regards to precipitation. While all tested sLBFs increased the permeation rate, no statistically significant difference was noted between the formulations regardless of composition. To conclude, the different release profiles of the formulations were not correlated to the resulting flux through a permeation membrane, further supporting the importance of making use of combined lipolysis-permeation assays when exploring LBFs.

Exploring the use of modified in vitro digestion assays for the evaluation of ritonavir loaded solid lipid-based formulations.

Solid lipid-based formulations (sLBFs) have the potential to increase the oral bioavailability of drugs with poor solubility in water, while counteracting some of the disadvantages of liquid LBFs. The most common experimental set-up to study the performance of LBFs in vitro is the lipolysis assay, during which the LBFs are digested by lipases in an environment mimicking the human small intestine. However, this assay has failed in many cases to correctly predict the performance of LBFs in vivo, highlighting the need for new and improved in vitro assays to evaluate LBFs at the preclinical stage. In this study, the suitability of three different in vitro digestion assays for the evaluation of sLBFs was assessed; the classic one-step intestinal digestion assay, a two-step gastrointestinal digestion assay and a bicompartmental assay permitting the simultaneous monitoring of digestion and permeation of the active pharmaceutical ingredient (API) across an artificial membrane (Lecithin in Dodecane - LiDo). Three sLBFs (M1-M3) with varied composition and ritonavir as model drug were prepared and examined. When comparing the ability of these formulations to keep the drug solubilized in the aqueous phase, all three assays show that M1 performs better, while M3 presents poor performance. However, the classic in vitro intestinal digestion assay fails to provide a clear ranking of the three formulations, something that is more evident when using the two modified and more physiologically relevant assays. Also, the two modified assays provide additional information about the performance of the formulations including the performance in the gastric environment and intestinal flux of the drug. These modified in vitro digestion assays are valuable tools for the development and evaluation of sLBFs to make better informed decisions of which formulations to pursue for in vivo studies.

A Convolutional Neural Network-Based Conditional Random Field Model for Structured Multi-Focus Image Fusion Robust to Noise.

The limited depth of field of optical lenses, makes multi-focus image fusion (MFIF) algorithms of vital importance. Lately, Convolutional Neural Networks (CNN) have been widely adopted in MFIF methods, however their predictions mostly lack structure and are limited by the size of the receptive field. Moreover, since images have noise due to various sources, the development of MFIF methods robust to image noise is required. A novel robust to noise Convolutional Neural Network-based Conditional Random Field (mf-CNNCRF) model is introduced. The model takes advantage of the powerful mapping between input and output of CNN networks and the long range interactions of the CRF models in order to reach structured inference. Rich priors for both unary and smoothness terms are learned by training CNN networks. The α -expansion graph-cut algorithm is used to reach structured inference for MFIF. A new dataset, which includes clean and noisy image pairs, is introduced and is used to train the networks of both CRF terms. A low-light MFIF dataset is also developed to demonstrate real-life noise introduced by the camera sensor. Qualitative and quantitative evaluation prove that mf-CNNCRF outperforms state-of-the-art MFIF methods for clean and noisy input images, while being more robust to different noise types without requiring prior knowledge of noise.

Nonlinear dynamics in Divisia monetary aggregates: an application of recurrence quantification analysis.

We construct recurrence plots (RPs) and conduct recurrence quantification analysis (RQA) to investigate the dynamic properties of the new Center for Financial Stability (CFS) Divisia monetary aggregates for the United States. In this study, we use the latest vintage of Divisia aggregates, maintained within CFS. We use monthly data, from January 1967 to December 2020, which is a sample period that includes the extreme economic events of the 2007-2009 global financial crisis. We then make comparisons between narrow and broad Divisia money measures and find evidence of a nonlinear but reserved possible chaotic explanation of their origin. The application of RPs to broad Divisia monetary aggregates encompasses an additional drift structure around the global financial crisis in 2008. Applying the moving window RQA to the growth rates of narrow and broad Divisia monetary aggregates, we identify periods of changes in data-generating processes and associate such changes to monetary policy regimes and financial innovations that occurred during those times.

Correction: Andreadis et al. The Advent of a New Era in Digital Healthcare: A Role for 3D Printing Technologies in Drug Manufacturing? Pharmaceutics2022, 14, 609.

In the original publication [...].

Conditional Random Field-Guided Multi-Focus Image Fusion.

Multi-Focus image fusion is of great importance in order to cope with the limited Depth-of-Field of optical lenses. Since input images contain noise, multi-focus image fusion methods that support denoising are important. Transform-domain methods have been applied to image fusion, however, they are likely to produce artifacts. In order to cope with these issues, we introduce the Conditional Random Field (CRF) CRF-Guided fusion method. A novel Edge Aware Centering method is proposed and employed to extract the low and high frequencies of the input images. The Independent Component Analysis-ICA transform is applied to high-frequency components and a Conditional Random Field (CRF) model is created from the low frequency and the transform coefficients. The CRF model is solved efficiently with the α-expansion method. The estimated labels are used to guide the fusion of the low-frequency components and the transform coefficients. Inverse ICA is then applied to the fused transform coefficients. Finally, the fused image is the addition of the fused low frequency and the fused high frequency. CRF-Guided fusion does not introduce artifacts during fusion and supports image denoising during fusion by applying transform domain coefficient shrinkage. Quantitative and qualitative evaluation demonstrate the superior performance of CRF-Guided fusion compared to state-of-the-art multi-focus image fusion methods.

Stability and rheology of plant-derived hydrocolloid-mucin mixtures.

Mixtures of mucin with pectin were investigated in a range of pectin to mucin ratios and pH values. The phase stability was first studied as absorbance measured at 500 nm (turbidity). Co-existence of the two materials did not result in co-sedimentation or relevant phase separations, while lower pH enhanced aggregation and partial sedimentation of individual components, especially for mucin. The above are in line with the recorded zeta potential values, which are negative for both components at neutral pH and drop down to almost zero at acidic values. The sizes of the particles, as recorded by dynamic light scattering, show a similar trend to the absorbance values, indicating that phase separations are in line with events at the scale of a few hundred nm. Such interactions reflect in shear rheology: The viscosity corresponding to 50 s-1 decreases upon substitution of pectin with mucin at pH 7 and 3, suggesting a flow dominated by changes in the space occupancy by the two components and by changes in the size of the self-assembled structures. The results were compared with those of more complex and typical hydrocolloids extracted from olive compost: The overall shape of the stability diagram of the two ingredients match, suggesting similar modes of action in the presence of mucin for other natural materials. These data throw some light in the norms during the co-existence of food polysaccharides and mucin in oral and gastrointestinal environments.

The Advent of a New Era in Digital Healthcare: A Role for 3D Printing Technologies in Drug Manufacturing?

The technological revolution has physically affected all manufacturing domains, at the gateway of the fourth industrial revolution. Three-dimensional (3D) printing has already shown its potential in this new reality, exhibiting remarkable applications in the production of drug delivery systems. As part of this concept, personalization of the dosage form by means of individualized drug dose or improved formulation functionalities has concentrated global research efforts. Beyond the manufacturing level, significant parameters must be considered to promote the real-time manufacturing of pharmaceutical products in distributed areas. The majority of current research activities is focused on formulating 3D-printed drug delivery systems while showcasing different scenarios of installing 3D printers in patients' houses, hospitals, and community pharmacies, as well as in pharmaceutical industries. Such research presents an array of parameters that must be considered to integrate 3D printing in a future healthcare system, with special focus on regulatory issues, drug shortages, quality assurance of the product, and acceptability of these scenarios by healthcare professionals and public parties. The objective of this review is to critically present the spectrum of possible scenarios of 3D printing implementation in future healthcare and to discuss the inevitable issues that must be addressed.

In Situ Gelling Electrospun Ocular Films Sustain the Intraocular Pressure-Lowering Effect of Timolol Maleate: In Vitro, Ex Vivo, and Pharmacodynamic Assessment.

Most common intraocular pressure (IOP) reduction regimens for the management of glaucoma include the topical use of eye drops, a dosage form that is associated with short residence time at the site of action, increased dosing frequency, and reduced patient compliance. In situ gelling nanofiber films comprising poly(vinyl alcohol) and Poloxamer 407 were fabricated via electrospinning for the ocular delivery of timolol maleate (TM), aiming to sustain the IOP-lowering effect of the ß-blocker, compared to conventional eye drops. The electrospinning process was optimized, and the physicochemical properties of the developed formulations were thoroughly investigated. The fiber diameters of the drug-loaded films ranged between 123 and 145 nm and the drug content between 5.85 and 7.83% w/w. Total in vitro drug release from the ocular films was attained within 15 min following first-order kinetics, showing higher apparent permeability (Papp) values across porcine corneas compared to the drug's solution. The fabricated films did not induce any ocular irritation as evidenced by both the hen's egg test on chorioallantoic membrane and the in vivo Draize test. In vivo administration of the ocular films in rabbits induced a faster onset of action and a sustained IOP-lowering effect up to 24 h compared to TM solution, suggesting that the proposed ocular films are promising systems for the sustained topical delivery of TM.

Development of 3D printed drug-eluting contact lenses.

OBJECTIVES: The aim of the work was to introduce 3D printing technology for the design and fabrication of drug-eluting contact lenses (DECL) for the treatment of glaucoma. The development of 3D printed lenses can effectively overcome drawbacks of existing approaches by using biocompatible medical grade polymers that provide sustained drug release of timolol maleate for extended periods. METHODS: Hot melt extrusion was coupled with fusion deposition modelling (FDM) to produce printable filaments of ethylene-vinyl acetate copolymer-polylactic acid blends at various ratios loaded with timolol maleate. Physicochemical and mechanical characterisation of the printed filaments was used to optimise the printing of the contact lenses. KEY FINDINGS: 3D printed lenses with an aperture (opening) and specified dimensions could be printed using FDM technology. The lenses presented a smooth surface with good printing resolution while providing sustained release of timolol maleate over 3 days. The findings of this study can be used for the development of personalised DECL in the future.

Physico-mechanical and finite element analysis evaluation of 3D printable alginate-methylcellulose inks for wound healing applications.

The present study reports on the comprehensive physico-mechanical evaluation of 3D printable alginate-methylcellulose hydrogels with bioactive components (Manuka honey, aloe vera gel, eucalyptus essential oil) using a combined experimental-numerical approach. The 3D printable carbohydrate inks demonstrated good swelling properties under moist conditions and adequate antimicrobial and antibiofilm efficacy against both Gram positive and negative bacteria. The effect of the bioactive compounds on the viscosity and mechanical properties of the 3D printable hydrogels was assessed with rheological, nanoindentation and shear test measurements. All hydrogel compositions showed good biocompatibility on human dermal fibroblasts, stimulating cell growth as confirmed by an in vitro wound healing assay. Finite element analysis simulation was employed to further advance the calculation accuracy of the nanoindentation tests, concluding that combination of an experimental and a numerical technique may constitute a useful method to characterize the mechanical behavior of composite hydrogel films for use in wound healing applications.

Motion synchronisation patterns of the carotid atheromatous plaque from B-mode ultrasound.

Asynchronous movement of the carotid atheromatous plaque from B-mode ultrasound has been previously reported, and associated with higher risk of stroke, but not quantitatively estimated. Based on the hypothesis that asynchronous plaque motion is associated with vulnerable plaque, in this study, synchronisation patterns of different tissue areas were estimated using cross-correlations of displacement waveforms. In 135 plaques (77 subjects), plaque radial deformation was synchronised by approximately 50% with the arterial diameter, and the mean phase shift was 0.4 s. Within the plaque, the mean phase shifts between the displacements of the top and bottom surfaces were 0.2 s and 0.3 s, in the radial and longitudinal directions, respectively, and the synchronisation about 80% in both directions. Classification of phase-shift-based features using Random Forests yielded Area-Under-the-Curve scores of 0.81, 0.79, 0.89 and 0.90 for echogenicity, symptomaticity, stenosis degree and plaque risk, respectively. Statistical analysis showed that echolucent, high-stenosis and high-risk plaques exhibited higher phase shifts between the radial displacements of their top and bottom surfaces. These findings are useful in the study of plaque kinematics.

Self-Nanoemulsifying Drug Delivery Systems (SNEDDS) Containing Rice Bran Oil for Enhanced Fenofibrate Oral Delivery: In Vitro Digestion, Ex Vivo Permeability, and In Vivo Bioavailability Studies.

Lipid-based drug delivery systems (LbDDS), such as self-nanoemulsifying drug delivery systems (SNEDDS), constitute a prominent formulation approach for enhancing the aqueous solubility and oral bioavailability of poorly water-soluble compounds. Utilization of biorefinery wastes, such as oil from rice bran, may prove advantageous to both improving drug solubilization and absorption and to achieving sustainable agri-food waste valorization. Here, we assessed the effect of four SNEDDS compositions differing in the oil (rice bran oil and corn oil) and surfactant type (Kolliphor RH40 and EL) on the oral bioavailability of fenofibrate, a BCS class II compound. Prior to the in vivo oral administration of the SNEDDS in rats, drug solubilization was tested in vitro using the static digestion model, followed by the ex vivo permeability study of the predigested SNEDDS using the non-everted gut sac model. No significant variation was observed in the solubilization capacity within the different SNEDDS formulations. On the other hand, the ex vivo permeability data of the predigested SNEDDS correlated well with the in vivo bioavailability data designating the superiority of rice bran oil with Kolliphor EL as the surfactant, to enhance the oral absorption of fenofibrate. Results indicated that valorization of agro-industrial waste such as rice bran oil may prove useful in enhancing the oral performance of LbDDS in the case of fenofibrate, while at the same time maximizing the use of agricultural by-products via the creation of new sustainable value chains in the pharmaceutical field.

On a topological criterion to select a recurrence threshold.

In this work, a topological criterion is proposed for selecting a recurrence threshold for constructing a recurrence plot of a time series. It is based on a metric structure of the set of the recurrence plots that is defined by the recurrence plot deviation distance among recurrence plots, introduced in a previous paper by the authors. In this process for a range of threshold values, the corresponding recurrence plots are constructed. Then, a value of the threshold is considered to be optimal when the image of its recurrence plot remains close to images of the other recurrence plots constructed for close values of thresholds based on the topological criterion introduced in the present work. The results are applied both to time series emanating from the Lorenz dynamical system and to Molecular Dynamic simulations.

Conditional Random Field Model for Robust Multi-Focus Image Fusion.

In this paper, a novel multi-focus image fusion algorithm based on conditional random field optimization (mf-CRF) is proposed. It is based on an unary term that includes the combined activity estimation of both high and low frequencies of the input images, while a spatially varying smoothness term is introduced, in order to align the graph-cut solution with boundaries of focused and defocused pixels. The proposed model retains the advantages of both spatial-domain methods and multi-spectral methods and by solving an energy minimization problem and finds an optimal solution for the multi-focus image fusion problem. Experimental results demonstrate the effectiveness of the proposed method that outperforms current state-of-the-art multi-focus image fusion algorithms in both qualitative and quantitative comparisons. In this paper, the successful application of the mf-CRF model in multi-modal image fusion (visible-infrared and medical) is also presented.

On a topological classification of recurrence plots: Application to noise perturbed molecular dynamics time series.

In the present paper, a topological classification of recurrence plots of time series that are constructed with equal embedding dimension and delay time is proposed by defining a metric structure in the set of those recurrence plots. To achieve this, the Recurrence Plot deviation distance and the Recurrence deviation plot are introduced along with qualitative and quantitative indices, which allows for a detailed comparison of the recurrence plots of two time series and their corresponding dynamical systems. In the range of values studied, the application of additive noise on the thermostat results in a less deterministic system behavior, quite close to that of the system with the unperturbed thermostat. On the other hand, multiplicative noise of small strength results in a less deterministic system quite close to the unperturbed system behavior. For a larger strength, the system presents a behavior which is significantly different from that of the unperturbed system. The new methodology introduced here provides detailed quantitative and graphical insights for the way that noise, additive and multiplicative, influences on the morphology of recurrence plots of the unperturbed and noise perturbed time series. The results are encouraging for potential future applications on the analysis of complex dynamical systems.

The Promise of Mobile Technologies for the Health Care System in the Developing World: A Systematic Review.

Evolution of mobile technologies and their rapid penetration into people's daily lives, especially in the developing countries, have highlighted mobile health, or m-health, as a promising solution to improve health outcomes. Several studies have been conducted that characterize the impact of m-health solutions in resource-limited settings and assess their potential to improve health care. The aim of this review is twofold: 1) to present an overview of the background and significance of m-health and 2) to summarize and discuss the existing evidence for the effectiveness of m-health in the developing world. A systematic search in the literature was performed in Pubmed, Scopus, as well as reference lists, and a broad sample of 98 relevant articles was identified, which were then categorized into five wider m-health categories. Although statistically significant conclusions cannot be drawn since the majority of studies relied on small-scale trials and limited assessment of long-term effects, this review provides a systematic and extensive analysis of the advantages, disadvantages, and challenges of m-health in developing countries in an attempt to determine future research directions of m-health interventions.

Start Spreading the News: A Comparative Experiment on the Effects of Populist Communication on Political Engagement in Sixteen European Countries.

Although populist communication has become pervasive throughout Europe, many important questions on its political consequences remain unanswered. First, previous research has neglected the differential effects of populist communication on the Left and Right. Second, internationally comparative studies are missing. Finally, previous research mostly studied attitudinal outcomes, neglecting behavioral effects. To address these key issues, this paper draws on a unique, extensive, and comparative experiment in sixteen European countries (N = 15,412) to test the effects of populist communication on political engagement. The findings show that anti-elitist populism has the strongest mobilizing effects, and anti-immigrant messages have the strongest demobilizing effects. Moreover, national conditions such as the level of unemployment and the electoral success of the populist Left and Right condition the impact of populist communication. These findings provide important insights into the persuasiveness of populist messages spread throughout the European continent.