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The formation of an aneurysm in the false lumen (FL) is a long-term complication in a significant percentage of type B aortic dissection (AD) patients. The ability to predict which patients are likely to progress to aneurysm formation is key to justifying the risks of interventional therapy. The investigation of patient-specific hemodynamics has the potential to enable a patient-tailored approach to improve prognosis by guiding disease management for type B dissection. CFD-derived hemodynamic descriptors and geometric features were used to retrospectively assess individual aortas for a population of residual type B AD patients and analyze correlations with known outcomes (i.e., rapid aortic growth, death). The results highlight great variability in flow patterns and hemodynamic descriptors. A rapid aortic expansion was found to be associated with a larger FL. Time-averaged wall shear stress at the tear region emerged as a possible indicator of the dynamics of flow exchange between lumens and its effect on the evolution of individual aortas. High FL flow rate and tortuosity were associated with adverse outcomes suggesting a role as indicators of risk. AD induces complex changes in vessel geometry and hemodynamics. The reported findings emphasize the need for a patient-tailored approach when evaluating uncomplicated type B AD patients and show the potential of CFD-derived hemodynamics to complement anatomical assessment and help disease management.

Objective: This study correlates low strain tangential modulus (LTM) and transition zone onset (TZo) stress, biomechanical parameters that occur within the physiological range of stress seen in vivo, with tissue strength and histopathologic changes in aneurysmal ascending aortic tissue. Method: Ascending aortic aneurysm tissue samples were collected from 41 patients undergoing elective resection. Samples were subjected to planar biaxial testing to quantify LTM and TZo. These were then correlated with strength assessed from uniaxial testing and with histopathologic quantification of pathologic derangements in elastin, collagen, and proteoglycan (PG). Results: Decreased LTM and TZo were correlated with reduced strength (P

Abdominal aortic aneurysm (AAA) is one of the leading causes of death worldwide. AAAs often remain asymptomatic until they are either close to rupturing or they cause pressure to the spine and/or other organs. Fast progression has been linked to future clinical outcomes. Therefore, a reliable and efficient system to quantify geometric properties and growth will enable better clinical prognoses for aneurysms. Different imaging systems can be used to locate and characterize an aneurysm; computed tomography (CT) is the modality of choice in many clinical centers to monitor later stages of the disease and plan surgical treatment. The lack of accurate and automated techniques to segment the outer wall and lumen of the aneurysm results in either simplified measurements that focus on few salient features or time-consuming segmentation affected by high inter- and intra-operator variability. To overcome these limitations, we propose a model for segmenting AAA tissues automatically by using a trained deep learning-based approach. The model is composed of three different steps starting with the extraction of the aorta and iliac arteries followed by the detection of the lumen and other AAA tissues. The results of the automated segmentation demonstrate very good agreement when compared to manual segmentation performed by an expert.

Objective: The purpose of this study was to employ biomechanics-based biomarkers to locally characterize abdominal aortic aneurysm (AAA) tissue and investigate their relation to local aortic growth by means of an artificial intelligence model. Methods: The study focused on a population of 36 patients with AAAs undergoing serial monitoring with electrocardiogram-gated multiphase computed tomography angiography acquisitions. The geometries of the aortic lumen and wall were reconstructed from the baseline scans and used for the baseline assessment of regional aortic weakness with three functional biomarkers, time-averaged wall-shear stress, in vivo principal strain, and intra-luminal thrombus thickness. The biomarkers were encoded as regional averages on axial and circumferential sections perpendicularly to the aortic centerline. Local diametric growth was obtained as difference in diameter between baseline and follow-up at the level of each axial section. An artificial intelligence model was developed to predict accelerated aneurysmal growth with the Extra Trees algorithm used as a binary classifier where the positive class represented regions that grew more than 2.5 mm/year. Additional clinical biomarkers, such as maximum aortic diameter at baseline, were also investigated as predictors of growth. Results: The area under the curve for the constructed receiver operating characteristic curve for the Extra Trees classifier showed a very good performance in predicting relevant aortic growth (area under the curve = 0.92), with the three biomechanics-based functional biomarkers being objectively selected as the main predictors of growth. Conclusions: The use of features based on the functional and local characterization of the aortic tissue resulted in a superior performance in terms of growth prediction when compared with models based on geometrical assessments. With rapid growth linked to increasing risk for patients with AAAs, the ability to access functional information related to tissue weakening and disease progression at baseline has the potential to support early clinical decisions and improve disease management. : Clinical Relevance: Disease progression and tissue weakening in AAAs are complex and multifactorial processes linked to rapid growth and increased risk of adverse clinical outcomes. Serial monitoring is key in the management of AAAs and can be improved by accessing functional information at baseline to predict rapid growth in individual patients.

Background. Vehicular crowdsensing (VCS) can be a cost-effective solution to gather data in urban environments, leveraging the onboard sensors of modern vehicles moving around the city. Many experimental studies have proven that high-mileage vehicles, such as taxis, can be effectively used for VCS. However, these studies have been mostly carried out in cities with regular, grid-based, road networks. Conversely, little work has been conducted to assess the suitability of VCS in cities with more complex urban road networks, such as historical ones. Goal. As a step towards filling this gap, the present study investigates the feasibility of using different-sized fleets of taxis to crowdsense information in the urban areas of the historical cities of Porto (Portugal) and Rome (Italy), whose road networks evolved over the centuries and feature a complex topology. Data and Methodology. This work leverages massive real-world datasets of taxi trajectories collected over three contiguous weeks in the cities of Porto and Rome to estimate the spatiotemporal coverage achievable by different-sized fleets of taxis if they were used for VCS. Indeed, using these trajectories, several simulations were conducted, considering four sizes of taxi fleets, ranging from 50 to 400 vehicles, for both cities. The achievable spatiotemporal road network coverage metrics were computed at a fine-grained scale of single road segments. Results. Results show that the achievable coverage in both historical cities exhibits very similar trends, with as few as 50 vehicles being capable of visiting a relevant part of the road network at least once in the considered time frame. As expected, increasing the number of involved vehicles improves spatial and temporal coverage. Still, time gaps between subsequent visits can be possibly inadequate for some VCS use cases. As a consequence, recruiting more vehicles and/or devising specialized routing/incentivization mechanisms might be necessary to achieve more comprehensive coverage of the urban road network.

Continuous monitoring procedures are becoming even more crucial for assessing the potential deterioration of architectural structures, due to the many inducted advantages. A cultural heritage site, in fact, is constantly subject to degradation, due in particular to atmospheric agents. Preserving it with preventive analyses is an important goal for the scientific community. In this context, data collection methodologies, together with Artificial Intelligence, play a central role for the analysis of surface degradation. This study aims to present a proposal for the automated analysis of the state of degradation of an artefact, exploiting a novel solution including a combination of a graph database and a dynamic Digital Model. In this regard, a preliminary case study is presented, based on the Quadriportico of the Cathedral of San Matteo in Salerno, Italy.

Collagen has an essential role in aortic biomechanics, and collagen remodeling has been associated with the development and progression of aortic aneurysm. However, the exact mechanisms behind collagen remodeling and the biomechanical implications are not well understood. This study presents an investigation of the relationship between collagen remodeling in the aortic wall and biomechanics, by means of collagen assays, smooth muscle cell gene expression, and mechanical testing on human aortic specimens collected from patients with bicuspid aortic valve. Collagen assay analysis was employed to determine collagen-I and total collagen content; quantitative real-time PCR was used to determine amounts COL1A1 and COL3A1 expression in the tissue. These parameters were compared with the local biomechanical properties determined from biaxial and uniaxial tensile testing. Collagen-I content was found to relate to improved mechanical properties, while total collagen content did not exhibit a relationship with biomechanics. COL1A1 and COL3A1 expression were found to relate to the collagen-I content of the tissue, but not the total collagen content or biomechanical performance. Relationships between variables appeared to be dependent on the collagen content in specific layers of the aortic wall. The effect of age is also noted, as total collagen content and biomechanics were found to have significant associations with increasing age, while collagen-I content and collagen gene expression did not exhibit any correlation. Varying relationships were observed when looking at younger versus older patients. Findings highlight the importance of type and location in determining the influence of collagen on aortic biomechanics, as well as the role of gene expression in the onset and progression of collagen remodeling in aortic aneurysm.

Clinical decision-making for surgical repair of abdominal aortic aneurysms based on maximum aortic diameter presents limitations as rupture can occur below threshold for some aneurysms, whereas others are stable at large sizes. The proposed approach combines hemodynamics and geometric indices with in vivo deformation analysis to assess local weakening of the aortic wall for a case of impending rupture that was confirmed during open surgical repair. A new combined index, the Regional Rupture Potential, is introduced to help the assessment of individual aneurysms and their rupture risk, providing a rationale for clinical decisions.

Summary: Following full-thickness skin injuries, epithelialization of the wound is essential. The standard of care to achieve this wound “closure” in patients is autologous split-thickness skin grafting (STSG). However, patients living with STSGs report significant chronic impairments leading to functional deficiencies such as itch, altered sensation, fragility, hypertrophic scarring, and contractures. These features are attributable to the absence of functional dermis combined with the formation of disorganized fibrotic extracellular matrix. Recent work has demonstrated the existence of dermal progenitor cells (DPCs) residing within hair follicles that function to continuously regenerate mesenchymal tissue. The present work examines whether cultured DPCs could regenerate dermis within an STSG and improve overall graft function. Adult human DPCs were transplanted into a full-thickness skin wound in immune-compromised mice and closed with a human STSG. At 3 months, human DPCs (hDPCs) had successfully integrated into the xenograft and differentiated into various regionally specified phenotypes, improving both viscoelastic properties of the graft and mitigating pruritus. Keywords: skin, stem cell, dermal progenitor, skin graft, wound healing, regeneration, SKP, cell transplant, itch, fibroblast

Background: Current clinical practice for the assessment of abdominal aortic aneurysms (AAA) is based on vessel diameter and does not account for the multifactorial, heterogeneous remodeling that results in the regional weakening of the aortic wall leading to aortic growth and rupture. The present study was conducted to determine correlations between a novel non-invasive surrogate measure of regional aortic weakening and the results from invasive analyses performed on corresponding ex vivo aortic samples. Tissue samples were evaluated to classify local wall weakening and the likelihood of further degeneration based on non-invasive indices.Methods: A combined, image-based fluid dynamic and in-vivo strain analysis approach was used to estimate the Regional Aortic Weakness (RAW) index and assess individual aortas of AAA patients prior to elective surgery. Nine patients were treated with complete aortic resection allowing the systematic collection of tissue samples that were used to determine regional aortic mechanics, microstructure and gene expression by means of mechanical testing, microscopy and transcriptomic analyses.Results: The RAW index was significantly higher for samples exhibiting lower mechanical strength (p = 0.035) and samples classified as low elastin content (p = 0.020). Samples with higher RAW index had the greatest number of genes differentially expressed compared to any constitutive metric. High RAW samples showed a decrease in gene expression for elastin and a down-regulation of pathways responsible for cell movement, reorganization of cytoskeleton, and angiogenesis.Conclusions: This work describes the first AAA index free of assumptions for material properties and accounting for patient-specific mechanical behavior in relation to aneurysm strength. Use of the RAW index captured biomechanical changes linked to the weakening of the aorta and revealed changes in microstructure and gene expression. This approach has the potential to provide an improved tool to aid clinical decision-making in the management of aortic pathology.

OBJECTIVE: Many researches focus their attention on the behavior of cells to specific substances with alkalizing power. Each substance that we introduce with food, as well as water, contributes to conditioning the electrophilic balance (acid-base) of the extracellular matrix (MEC) of the whole organism. This systemic regulation of the MEC participates in modulating the expression of genes (transcriptome) and consequently participates in modulating the inflammatory response through the regulation of cellular signal molecules such as ROS (Reactive Oxygen Species) and RNS (Reactive Nitrogen Species). In this study, we investigated the influence of alkaline solutions (Alkawater and Alkacoffee) on one aspect of inflammation relating to the expression of immune modulation by tumor necrosis factor (TNF-α), interleukin 1β (IL-1β), interleukin 6 (IL-6), cyclooxygenase-2 (COX-2) on Caco-2 cell cultures. MATERIALS AND METHODS: In this paper, the transcriptome of human enterocyte-like Caco-2 cells, in a pH controlled environment with a mixture of alkalizing salts, AlkaWater® and AlkaCoffee®, has been studied. The cellular models used were Caco2 and LS174T cell lines. Isolation and purification of RNA from both Caco2 and LS174T cell lines were performed by TRIzol method. Transcriptome analysis was performed by RNA expression analysis of transcripts of the samples. The analysis was completed with the aid of information technology. RESULTS: When administered individually, Solution 1 (AlkaWater, alkaline water) and Solution 2 (AlkaCoffee, acidity corrector) decrease the expression levels of the four immune modulatory markers (TNF-α, IL-1β, IL-6, COX-2) in CaCo-2 cells (Figure 1), and even more pronounced effects were observed when alkaline solutions and coffee extract were administered in combination. About the influence of alkaline solutions on miR-146a expression, Solution 2 increases the expression of miR-146a gene, while the other solution combinations decrease its level. CONCLUSIONS: Cells prevent pathogens through inflammatory responses. Alkaline solutions have been thought as adjuvants of a balanced diet rich of alkaline foods.

Abstract Background Functional impairment of the aorta is a recognized complication of aortic and aortic valve disease. Aortic strain measurement provides effective quantification of mechanical aortic function, and 3-dimenional (3D) approaches may be desirable for serial evaluation. Computerized tomographic angiography (CTA) is routinely performed for various clinical indications, and offers the unique potential to study 3D aortic deformation. We sought to investigate the feasibility of performing 3D aortic strain analysis in a candidate population of patients undergoing transcatheter aortic valve replacement (TAVR). Methods Twenty-one patients with severe aortic valve stenosis (AS) referred for TAVR underwent ECG-gated CTA and echocardiography. CTA images were analyzed using a 3D feature-tracking based technique to construct a dynamic aortic mesh model to perform peak principal strain amplitude (PPSA) analysis. Segmental strain values were correlated against clinical, hemodynamic and echocardiographic variables. Reproducibility analysis was performed. Results The mean patient age was 81±6 years. Mean left ventricular ejection fraction was 52±14%, aortic valve area (AVA) 0.6±0.3 cm2 and mean AS pressure gradient (MG) 44±11 mmHg. CTA-based 3D PPSA analysis was feasible in all subjects. Mean PPSA values for the global thoracic aorta, ascending aorta, aortic arch and descending aorta segments were 6.5±3.0, 10.2±6.0, 6.1±2.9 and 3.3±1.7%, respectively. 3D PSSA values demonstrated significantly more impairment with measures of worsening AS severity, including AVA and MG for the global thoracic aorta and ascending segment (p

Objective: Glucans are already known as biological modifiers of the immune system and cytokine modulation (IFN-y; TNF; T-CD4/CD8), but the role of low molecular weight glucans on transcriptome regulation is not well documented. Materials and Methods: In this paper, the mechanism of action of a mix in capsules of 0.6 g of β-Glucan (Active hexose correlated compound "AHCC" and β-Glucan 1,3-1,6) on the neoplastic cell line transcriptome has been explored. The cellular models used were Caco2 and LS174T cell lines. Transcriptome analysis was performed by RNA expression analysis of transcripts of both single and multiple samples. The analysis was completed with the aid of information technology. Results: ROS (Reactive Oxygen Species) decrease following glucans treatment (Figure 1) combined with a marked improvement in the Redox control of SOD1 (Superoxide Dismutase 1) (Figure 2), which is present in the cytosol of all eukaryotic cells with copper and zinc (Cu-Zn-SOD). Following glucan mix treatment, COX-2 (cyclooxygenase-2) expression levels showed a marked reduction (Figure 3A). The combined glucan treatment on the two cell lines showed an over expression of SOD1 with a significant reduction in COX-2 expression (Figure 3A). Pro-inflammatory cytokines such as IL-1, IL-6, TNF-α, were consequently down-expressed (Figure 3B, C, D). Conclusions: The glucan mix reduces ROS significantly, decreasing COX-2 expression, reducing the inflammatory state and consequently decreasing TNF-α and IL-1.

OBJECTIVE: In our report, we prospectively estimated a cohort of patients with nodules considered suspicious sonographically, for PTC. We evaluated 24 samples from PTC patients. The sensitivity, specificity, and negative predictive values (NPV) of FNAB BRAF testing in this study were 0.1% (analytical sensitivity), 100%, and 78%, respectively. In terms of assay costs, our PNA PCR-based method could be like either Allele Specific-PCR (AS-PCR) and/or Restriction Fragment Length Polymorphism (RFLP). PATIENTS AND METHODS: PNA chemistry has been performed to amplify selectively minor mutant allele background variants in a large amount of wild type (wt) allele derived from DNA extracted by 24 thyroid biopsies; 14 of them were obtained from cytological slides and 10 from fresh Fine Needle Aspirate (FNA) of patients with papillary thyroid carcinoma (PTC). Finally, we compared the results with those gained by direct sequencing. RESULTS: The assay sensitivity of the method was 0.1% of mutant alleles, evaluated by serial dilution of DNA from ARO cell line (carrying heterozygous V600E), mixed to wild type DNA gained from healthy donors. Optimized concentration of the primer PNA clamping-wt DNA is 12 µM per reaction. Direct sequencing was able to detect mutation in only 33.3% (8/24), while PNA-based PCR assay 45.8% (11/24) of patients, carrying mutation at codon V600. The estimated reagents costs are about € 20.00 per sample, including controls and pre-analytical steps. This assay could be performed in a simple thermal cycler and results visualized by agarose ethidium bromide stained gels. CONCLUSIONS: PNA clamping wt-DNA could be performed in any laboratory with very cheap PCR equipment. It is very cost-effective and could easily be adapted to detect hot spot mutations in any other genes.

The current clinical guidelines for the management of aortic abdominal aneurysms (AAAs) overlook the structural and mechanical heterogeneity of the aortic tissue and its role in the regional weakening that drives disease progression. This study is a comprehensive investigation of the structural and biomechanical heterogeneity of AAA tissue along the length and circumference of the aorta, by means of regional ex vivo and in vivo properties. Biaxial testing and histological analysis were performed on ex vivo human aortic specimens systematically collected during open repair surgery. Wall-shear stress and three-dimensional principal strain analysis were performed to allow for in vivo regional characterization of individual aortas. A marked effect of position along the aortic length was observed in both ex vivo and in vivo properties, with the central regions corresponding to the aneurysmal sac being significantly different from the adjacent regions. The heterogeneity along the circumference of the aorta was reflected in the ex vivo biaxial response at low strains and histological properties. Present findings uniquely show the importance of regional characterization for aortic assessment and the need to correlate heterogeneity at the tissue level with non-invasive measurements aimed at improving clinical outcomes.

Introduction: Current recommendations for surgical treatment of abdominal aortic aneurysms (AAAs) rely on the assessment of aortic diameter as a marker for risk of rupture. The use of aortic size alone may overlook the role that vessel heterogeneity plays in aneurysmal progression and rupture risk. The aim of the current study was to investigate intra-patient heterogeneity of mechanical and fluid mechanical stresses on the aortic wall and wall tissue histopathology from tissue collected at the time of surgical repair.Methods: Finite element analysis (FEA) and computational fluid dynamics (CFD) simulations were used to predict the mechanical wall stress and the wall shear stress fields for a non-ruptured aneurysm 2 weeks prior to scheduled surgery. During open repair surgery one specimen partitioned into different regions was collected from the patient's diseased aorta according to a pre-operative map. Histological analysis and mechanical testing were performed on the aortic samples and the results were compared with the predicted stresses.Results: The preoperative simulations highlighted the presence of altered local hemodynamics particularly at the proximal segment of the left anterior area of the aneurysm. Results from the post-operative assessment on the surgical samples revealed a considerable heterogeneity throughout the aortic wall. There was a positive correlation between elastin fragmentation and collagen content in the media. The tensile tests demonstrated a good prediction of the locally varying constitutive model properties predicted using geometrical variables, i.e., wall thickness and thrombus thickness.Conclusions: The observed large regional differences highlight the local response of the tissue to both mechanical and biological factors. Aortic size alone appears to be insufficient to characterize the large degree of heterogeneity in the aneurysmal wall. Local assessment of wall vulnerability may provide better risk of rupture predictions.

Forty-two patients affected by osteoarthritis have been treated with two parallel schemes, in double blind, according to parallel groups, to have a correct evaluation of the efficacy and safety of Amtolmetin Guacyl administration on at full stomach or empty stomach. As parameters of efficacy the spontaneus pain and the pain caused by movements, the function and joint pain have been considered, while gastric tolerance has been evaluated by means of daily records made by patients and the general tolerance through an annotation of adverse events, vital signs as well as parameters of laboratory. The drug worked for both groups, but it has been particulary efficent in those who have assumed the drug on a empty stomach. The general tolerance has been good and some adverse side effects, concerning the gastric tolerance, have disappeared by reducing the dosage of the drug. As a result of this study we can assume that amtolmetin guacyl is much more efficent when it is assumed on a empty stomach, with its conseguent advantages in terms of compliance and its possible utilization in case of need.