Search Results (14)

The cerebral small vessel disease (cSVD) is one of the main causes of vascular and mixed cognitive impairment (CI), and it is associated, in particular, with brain ageing. An understanding of structural tissue changes in an intact cerebral white matter in cSVD might allow one to develop the sensitive biomarkers for early diagnosis and monitoring of disease progression. Purpose of the study: to evaluate microstructural changes in the corpus callosum (CC) using diffusion MRI (D-MRI) approaches in cSVD patients with different severity of CI and reveal the most sensitive correlations of diffusion metrics with CI. Methods: the study included 166 cSVD patients (51.8% women; 60.4 ± 7.6 years) and 44 healthy volunteers (65.9% women; 59.6 ± 6.8 years). All subjects underwent D-MRI (3T) with signal (diffusion tensor and kurtosis) and biophysical (neurite orientation dispersion and density imaging, NODDI, white matter tract integrity, WMTI, multicompartment spherical mean technique, MC-SMT) modeling in three CC segments as well as a neuropsychological assessment. Results: in cSVD patients, microstructural changes were found in all CC segments already at the subjective CI stage, which was found to worsen into mild CI and dementia. More pronounced changes were observed in the forceps minor. Among the signal models FA, MD, MK, RD, and RK, as well as among the biophysical models, MC-SMT (EMD, ETR) and WMTI (AWF) metrics exhibited the largest area under the curve (>0.85), characterizing the loss of microstructural integrity, the severity of potential demyelination, and the proportion of intra-axonal water, respectively. Conclusion: the study reveals the relevance of advanced D-MRI approaches for the assessment of brain tissue changes in cSVD. The identified diffusion biomarkers could be used for the clarification and observation of CI progression. Full article

The aim of this work was to extend the VERDICT-MRI framework for modelling brain tumours, enabling comprehensive characterisation of both intra- and peritumoural areas with a particular focus on cellular and vascular features. Diffusion MRI data were acquired with multiple b-values (ranging from 50 to 3500 s/mm²), diffusion times, and echo times in 21 patients with brain tumours of different types and with a wide range of cellular and vascular features. We fitted a selection of diffusion models that resulted from the combination of different types of intracellular, extracellular, and vascular compartments to the signal. We compared the models using criteria for parsimony while aiming at good characterisation of all of the key histological brain tumour components. Finally, we evaluated the parameters of the best-performing model in the differentiation of tumour histotypes, using ADC (Apparent Diffusion Coefficient) as a clinical standard reference, and compared them to histopathology and relevant perfusion MRI metrics. The best-performing model for VERDICT in brain tumours was a three-compartment model accounting for anisotropically hindered and isotropically restricted diffusion and isotropic pseudo-diffusion. VERDICT metrics were compatible with the histological appearance of low-grade gliomas and metastases and reflected differences found by histopathology between multiple biopsy samples within tumours. The comparison between histotypes showed that both the intracellular and vascular fractions tended to be higher in tumours with high cellularity (glioblastoma and metastasis), and quantitative analysis showed a trend toward higher values of the intracellular fraction (fic) within the tumour core with increasing glioma grade. We also observed a trend towards a higher free water fraction in vasogenic oedemas around metastases compared to infiltrative oedemas around glioblastomas and WHO 3 gliomas as well as the periphery of low-grade gliomas. In conclusion, we developed and evaluated a multi-compartment diffusion MRI model for brain tumours based on the VERDICT framework, which showed agreement between non-invasive microstructural estimates and histology and encouraging trends for the differentiation of tumour types and sub-regions. Full article

Candida species are opportunistic fungi, which are primary causative agents of vulvovaginal candidiasis. The cure of candidiasis is difficult, lengthy, and associated with the fungi resistivity. Therefore, the research for novel active substances and unconventional drug delivery systems providing effective and safe treatment is still an active subject. Microparticles, as multicompartment dosage forms due to larger areas, provide short passage of drug diffusion, which might improve drug therapeutic efficiency. Sodium alginate is a natural polymer from a polysaccharide group, possessing swelling, mucoadhesive, and gelling properties. Gelatin A is a natural high-molecular-weight polypeptide obtained from porcine collagen. The purpose of this study was to prepare microparticles by the spray-drying of alginate/gelatin polyelectrolyte complex mixture, with a novel antifungal drug—luliconazole. In the next stage of research, the effect of gelatin presence on pharmaceutical properties of designed formulations was assessed. Interrelations among polymers were evaluated with thermal analysis and Fourier transform infrared spectroscopy. A valid aspect of this research was the in vitro antifungal activity estimation of designed microparticles using Candida species: C. albicans, C. krusei, and C. parapsilosis. It was shown that the gelatin addition affected the particles size, improved encapsulation efficiency and mucoadhesiveness, and prolonged the drug release. Moreover, gelatin addition to the formulations improved the antifungal effect against Candida species. Full article

Although the free water content within the perilesional T2 hyperintense region should differ between glioblastomas (GBM) and brain metastases based on histological differences, the application of classical MR diffusion models has led to inconsistent results regarding the differentiation between these two entities. Whereas diffusion tensor imaging (DTI) considers the voxel as a single compartment, multicompartment approaches such as neurite orientation dispersion and density imaging (NODDI) or the recently introduced diffusion microstructure imaging (DMI) allow for the calculation of the relative proportions of intra- and extra-axonal and also free water compartments in brain tissue. We investigate the potential of water-sensitive DTI, NODDI and DMI metrics to detect differences in free water content of the perilesional T2 hyperintense area between histopathologically confirmed GBM and brain metastases. Respective diffusion metrics most susceptible to alterations in the free water content (MD, V-ISO, V-CSF) were extracted from T2 hyperintense perilesional areas, normalized and compared in 24 patients with GBM and 25 with brain metastases. DTI MD was significantly increased in metastases (p = 0.006) compared to GBM, which was corroborated by an increased DMI V-CSF (p = 0.001), while the NODDI-derived ISO-VF showed only trend level increase in metastases not reaching significance (p = 0.060). In conclusion, diffusion MRI metrics are able to detect subtle differences in the free water content of perilesional T2 hyperintense areas in GBM and metastases, whereas DMI seems to be superior to DTI and NODDI. Full article

Humans are exposed to persistent organic pollutants, such as dioxin-like compounds (DLCs), as mixtures. Understanding and predicting the toxicokinetics and thus internal burden of major constituents of a DLC mixture is important for assessing their contributions to health risks. PBPK models, including dioxin models, traditionally focus on one or a small number of compounds; developing new or extending existing models for mixtures often requires tedious, error-prone coding work. This lack of efficiency to scale up for multi-compound exposures is a major technical barrier toward large-scale mixture PBPK simulations. Congeners in the DLC family, including 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), share similar albeit quantitatively different toxicokinetic and toxicodynamic properties. Taking advantage of these similarities, here we reported the development of a human PBPK modeling framework for DLC mixtures that can flexibly accommodate an arbitrary number of congeners. Adapted from existing TCDD models, our mixture model contains the blood and three diffusion-limited compartments—liver, fat, and rest of the body. Depending on the number of congeners in a mixture, varying-length vectors of ordinary differential equations (ODEs) are automatically generated to track the tissue concentrations of the congeners. Shared ODEs are used to account for common variables, including the aryl hydrocarbon receptor (AHR) and CYP1A2, to which the congeners compete for binding. Binary and multi-congener mixture simulations showed that the AHR-mediated cross-induction of CYP1A2 accelerates the sequestration and metabolism of DLC congeners, resulting in consistently lower tissue burdens than in single exposure, except for the liver. Using dietary intake data to simulate lifetime exposures to DLC mixtures, the model demonstrated that the relative contributions of individual congeners to blood or tissue toxic equivalency (TEQ) values are markedly different than those to intake TEQ. In summary, we developed a mixture PBPK modeling framework for DLCs that may be utilized upon further improvement as a quantitative tool to estimate tissue dosimetry and health risks of DLC mixtures. Full article

Studying microbes at the single-cell level in space can accelerate human space exploration both via the development of novel biotechnologies and via the understanding of cellular responses to space stressors and countermeasures. High-throughput technologies for screening natural and engineered cell populations can reveal cellular heterogeneity and identify high-performance cells. Here, we present a method to desiccate and preserve microbes in nanoliter-scale compartments, termed PicoShells, which are microparticles with a hollow inner cavity. In PicoShells, single cells are confined in an inner aqueous core by a porous hydrogel shell, allowing the diffusion of nutrients, wastes, and assay reagents for uninhibited cell growth and flexible assay protocols. Desiccated PicoShells offer analysis capabilities for single-cell derived colonies with a simple, low resource workflow, requiring only the addition of water to rehydrate hundreds of thousands of PicoShells and the single microbes encapsulated inside. Our desiccation method results in the recovery of desiccated microparticle morphology and porosity after a multi-week storage period and rehydration, with particle diameter and porosity metrics changing by less than 18% and 7%, respectively, compared to fresh microparticles. We also recorded the high viability of Saccharomyces cerevisiae yeast desiccated and rehydrated inside PicoShells, with only a 14% decrease in viability compared to non-desiccated yeast over 8.5 weeks, although we observed an 85% decrease in initial growth potential over the same duration. We show a proof-of-concept for a growth rate-based analysis of single-cell derived colonies in rehydrated PicoShells, where we identified 11% of the population that grows at an accelerated rate. Desiccated PicoShells thus provide a robust method for cell preservation before and during launch, promising a simple single-cell analysis method for studying heterogeneity in microbial populations in space. Full article

Diffusion-weighted MRI (DW-MRI) offers a potential adjunct to dynamic contrast-enhanced MRI to discriminate benign from malignant breast lesions by yielding quantitative information about tissue microstructure. Multi-component modeling of the DW-MRI signal over an extended b-value range (up to 3000 s/mm²) theoretically isolates the slowly diffusing (restricted) water component in tissues. Previously, a three-component restriction spectrum imaging (RSI) model demonstrated the ability to distinguish malignant lesions from healthy breast tissue. We further evaluated the utility of this three-component model to differentiate malignant from benign lesions and healthy tissue in 12 patients with known malignancy and synchronous pathology-proven benign lesions. The signal contributions from three distinct diffusion compartments were measured to generate parametric maps corresponding to diffusivity on a voxel-wise basis. The three-component model discriminated malignant from benign and healthy tissue, particularly using the restricted diffusion C₁ compartment and product of the restricted and intermediate diffusion compartments (C₁ and C₂). However, benign lesions and healthy tissue did not significantly differ in diffusion characteristics. Quantitative discrimination of these three tissue types (malignant, benign, and healthy) in non-pre-defined lesions may enhance the clinical utility of DW-MRI in reducing excessive biopsies and aiding in surveillance and surgical evaluation without repeated exposure to gadolinium contrast. Full article

Compartmentalisation by bioenergetic membranes is a universal feature of life. The eventual compartmentalisation of prebiotic systems is therefore often argued to comprise a key step during the origin of life. Compartments may have been active participants in prebiotic chemistry, concentrating and spatially organising key reactants. However, most prebiotically plausible compartments are leaky or unstable, limiting their utility. Here, we develop a new hypothesis for an origin of life environment that capitalises upon, and mitigates the limitations of, prebiotic compartments: multi-compartmentalised layers in the near surface environment—a ’scum’. Scum-type environments benefit from many of the same ensemble-based advantages as microbial biofilms. In particular, scum layers mediate diffusion with the wider environments, favouring preservation and sharing of early informational molecules, along with the selective concentration of compatible prebiotic compounds. Biofilms are among the earliest traces imprinted by life in the rock record: we contend that prebiotic equivalents of these environments deserve future experimental investigation. Full article

Multiple sclerosis (MS) is characterised by widespread damage of the central nervous system that includes alterations in normal-appearing white matter (NAWM) and demyelinating white matter (WM) lesions. Neurite orientation dispersion and density imaging (NODDI) has been proposed to provide a precise characterisation of WM microstructures. NODDI maps can be calculated for the Neurite Density Index (NDI) and Orientation Dispersion Index (ODI), which estimate orientation dispersion and neurite density. Although NODDI has not been widely applied in MS, this technique is promising in investigating the complexity of MS pathology, as it is more specific than diffusion tensor imaging (DTI) in capturing microstructural alterations. We conducted a meta-analysis of studies using NODDI metrics to assess brain microstructural changes and neuroaxonal pathology in WM lesions and NAWM in patients with MS. Three reviewers conducted a literature search of four electronic databases. We performed a random-effect meta-analysis and the extent of between-study heterogeneity was assessed with the I2 statistic. Funnel plots and Egger’s tests were used to assess publication bias. We identified seven studies analysing 374 participants (202 MS and 172 controls). The NDI in WM lesions and NAWM were significantly reduced compared to healthy WM and the standardised mean difference of each was −3.08 (95%CI −4.22 to (−1.95), p ≤ 0.00001, I2 = 88%) and −0.70 (95%CI −0.99 to (−0.40), p ≤ 0.00001, I2 = 35%), respectively. There was no statistically significant difference of the ODI in MS WM lesions and NAWM compared to healthy controls. This systematic review and meta-analysis confirmed that the NDI is significantly reduced in MS lesions and NAWM than in WM from healthy participants, corresponding to reduced intracellular signal fraction, which may reflect underlying damage or loss of neurites. Full article

Fungal infections and invasive mycoses, despite the continuous medicine progress, are an important globally therapeutic problem. Multicompartment dosage formulations (e.g., microparticles) ensure a short drug diffusion way and high surface area of drug release, which as a consequence can provide improvement of therapeutic efficiency compared to the traditional drug dosage forms. As fucoidan is promising component with wide biological activity per se, the aim of this study was to prepare fucospheres (fucoidan microparticles) and fucoidan/gelatin microparticles with posaconazole using the one-step spray-drying technique. Pharmaceutical properties of designed fucospheres and the impact of the gelatin addition on their characteristics were evaluated. An important stage of this research was in vitro evaluation of antifungal activity of developed microparticles using different Candida species. It was observed that gelatin presence in microparticles significantly improved swelling capacity and mucoadhesiveness, and provided a sustained POS release. Furthermore, it was shown that gelatin addition enhanced antifungal activity of microparticles against tested Candida spp. strains. Microparticles formulation GF6, prepared by the spray drying of 20% fucoidan, 5% gelatin and 10% Posaconazole, were characterized by optimal mucoadhesive properties, high drug loading and the most sustained drug release (after 8 h 65.34 ± 4.10% and 33.81 ± 5.58% of posaconazole was dissolved in simulated vaginal fluid pH 4.2 or 0.1 M HCl pH 1.2, respectively). Full article

A60 class bulkhead penetration piece is a fire-resistance apparatus installed on bulkhead compartments to protect lives and to prevent flame diffusion in case of fire accident in ships and offshore plants. In this study, approximate optimization with discrete variables was carried out for the fire-resistance design of an A60 class bulkhead penetration piece (A60 BPP) using various meta-models and multi-island genetic algorithms. Transient heat transfer analysis was carried out to evaluate the fire-resistance design of the A60 class bulkhead penetration piece, and we verified the results of the analysis via a fire test. The design of the experiment’s method was applied to generate the meta-models to be used for the approximate optimization, and the verified results of the transient heat transfer analysis were integrated with the design of the experiment’s method. The meta-models used in the approximate optimization were response surface model, Kriging, and radial basis function-based neural network. In the approximate optimization, the bulkhead penetration piece length, diameter, material type, and insulation density were applied to discrete design variables, and constraints that were considered include temperature, productivity, and cost. The approximate optimum design problem based on the meta-model was formulated such that the discrete design variables were determined by minimizing the weight of the A60 class bulkhead penetration piece subject to the limit values of constraints. In the context of approximate accuracy, the solution results from the approximate optimization were compared to actual analysis results. It was concluded that the radial basis function-based neural network, among the meta-models used in the approximate optimization, showed the most accurate optimum design results for the fire-resistance design of the A60 class bulkhead penetration piece. Full article

Viruses have a dual nature: particles are “passive substances” lacking chemical energy transformation, whereas infected cells are “active substances” turning-over energy. How passive viral substances convert to active substances, comprising viral replication and assembly compartments has been of intense interest to virologists, cell and molecular biologists and immunologists. Infection starts with virus entry into a susceptible cell and delivers the viral genome to the replication site. This is a multi-step process, and involves the cytoskeleton and associated motor proteins. Likewise, the egress of progeny virus particles from the replication site to the extracellular space is enhanced by the cytoskeleton and associated motor proteins. This overcomes the limitation of thermal diffusion, and transports virions and virion components, often in association with cellular organelles. This review explores how the analysis of viral trajectories informs about mechanisms of infection. We discuss the methodology enabling researchers to visualize single virions in cells by fluorescence imaging and tracking. Virus visualization and tracking are increasingly enhanced by computational analyses of virus trajectories as well as in silico modeling. Combined approaches reveal previously unrecognized features of virus-infected cells. Using select examples of complementary methodology, we highlight the role of actin filaments and microtubules, and their associated motors in virus infections. In-depth studies of single virion dynamics at high temporal and spatial resolutions thereby provide deep insight into virus infection processes, and are a basis for uncovering underlying mechanisms of how cells function. Full article

Water quality models are of great importance for developing policies to control water pollution, with the model parameters playing a decisive role in the simulation results. It is necessary to introduce estimation through multi-objective parameters, which is often affected by noise in the data, into water quality models. This paper presents a multi-objective particle swarm optimization algorithm, which is based on the Mahalanobis distance operation, mechanism of cardinality preference and advection-diffusion operator. The Mahalanobis distance operation can effectively reduce the influence of noise in the data on model calibration. The mechanism of cardinality preference and the use of the advection-diffusion operator can prevent non-dominated solutions from falling into the local optimum. Four cases were used to test the proposed approach. The first two cases with true Pareto fronts show that this approach can accurately estimate the true Pareto front with a good distribution, even in the presence of noise. Furthermore, the application of the approach was tested by the O’Connor model and Crops of Engineers Integrated Compartment Water Quality Model. We show that our approach can produce satisfactory results for the multi-objective calibration of complex water quality models. In general, the proposed approach can provide accurate and efficient parameter estimation in water quality models. Full article

We report on the spatial and temporal signaling properties of a yeast pheromone-based cell communication and amplifier system. It utilizes the Saccharomyces cerevisiae mating response pathway and relies on diffusion of the pheromone α–factor as key signaling molecule between two cell types. One cell type represents the α–factor secreting sensor part and the other the reporter part emitting fluorescence upon activation. Although multi-cellular signaling systems promise higher specificity and modularity, the complex interaction of the cells makes prediction of sensor performance difficult. To test the maximum distance and response time between sensor and reporter cells, the two cell types were spatially separated in defined compartments of agarose hydrogel (5 ´ 5 mm) and reconnected by diffusion of the yeast pheromone. Different ratios of sensor to reporter cells were tested to evaluate the minimum amount of sensor cells required for signal transduction. Even the smallest ratio, one α–factor-secreting cell to twenty reporter cells, generated a distinct fluorescence signal. When using a 1:1 ratio, the secreted pheromone induced fluorescence in a distance of up to four millimeters after six hours. We conclude from both our experimental results and a mathematical diffusion model that in our approach: (1) the maximum dimension of separated compartments should not exceed five millimeters in gradient direction; and (2) the time-limiting step is not diffusion of the signaling molecule but production of the reporter protein. Full article