The safety of early pharmacological venous thromboembolism prophylaxis in patients with traumatic intracranial haemorrhage: a systematic review and meta-analysis.

INTRODUCTION: In patients with traumatic intracranial haemorrhage (tICH) there is significant risk of both venous thromboembolism (VTE) and haemorrhage progression. There is a paucity of literature to inform the timing of pharmacological thromboprophylaxis (PTP) initiation. AIM: This meta-analysis aims to summarise the current literature on the timing of PTP initiation in tICH. METHODS: This meta-analysis followed the Methodological Expectations of Cochrane Intervention Reviews checklist and the Preferred Reporting Items for Systematic reviews and Meta-Analyses guidelines. Following the literature search, studies were matched against the criteria for inclusion. Data from included studies was pooled, analysed using random-effect analysis and presented as forest plots of risk ratios, except one result reported as difference of means. The ROBINS-I tool was used to assess the risk of bias in the studies. The GRADE approach was taken to assess the quality of included studies. Heterogeneity of studies was assessed using Tau∧2. Funnel plots were generated and used in conjunction with Harbord's test and Rucker's arcsine to assess for small-study effect including publication bias. RESULTS: A total of 9927 ICH patients who received PTP were included from 15 retrospective observational cohort studies, 4807 patients received early PTP, the remaining 5120 received late PTP. The definition of early was dependent on the study but no more than 72-hours after admission. The mean age of the included cohort was 45.3 (std dev ±9.5) years, and the proportion of males was 71%. Meta-analysis indicated that there was a significant difference between early and late groups for the rate of VTE (RR, 0.544; p = 0.000), pulmonary embolus (RR, 0.538; p = 0.004), deep vein thrombosis (RR, 0.484; p = 0.000) and the intensive care unit length of stay (difference of means, -2.021; 95% CI, -2.250, -1.792; p = 0.000; Tau∧2 = 0.000), favouring the early group. However, the meta-analysis showed no significant difference between the groups for the rate of mortality (RR, 1.008; p = 0.936), tICH progression (RR, 0.853; p = 0.157), and neurosurgical intervention (RR, 0.870; p = 0.480). CONCLUSION: These findings indicated that early PTP appears to be safe and effective in patients with tICH.

Lung vascular changes as biomarkers of severity in systemic sclerosis-associated interstitial lung disease.

OBJECTIVES: It has recently become possible to assess lung vascular and parenchymal changes quantitatively in thoracic CT images using automated software tools. We investigated the vessel parameters of patients with SSc, quantified by CT imaging, and correlated them with interstitial lung disease (ILD) features. METHODS: SSc patients undergoing standard of care pulmonary function testing and CT evaluation were retrospectively evaluated. CT images were analysed for ILD patterns and total pulmonary vascular volume (PVV) extents with Imbio lung texture analysis. Vascular analysis (volumes, numbers and densities of vessels, separating arteries and veins) was performed with an in-house developed software. A threshold of 5% ILD extent was chosen to define the presence of ILD, and commonly used cut-offs of lung function were adopted. RESULTS: A total of 79 patients [52 women, 40 ILD, mean age 56.2 (s.d. 14.2) years, total ILD extent 9.5 (10.7)%, PVV/lung volume % 2.8%] were enrolled. Vascular parameters for total and separated PVV significantly correlated with functional parameters and ILD pattern extents. SSc-associated ILD (SSc-ILD) patients presented with an increased number and volume of arterial vessels, in particular those between 2 and 4 mm of diameter, and with a higher density of arteries and veins of <6 mm in diameter. Considering radiological and functional criteria concomitantly, as well as the descriptive trends from the longitudinal evaluations, the normalized PVVs, vessel numbers and densities increased progressively with the increase/worsening of ILD extent and functional impairment. CONCLUSION: In SSc patients CT vessel parameters increase in parallel with ILD extent and functional impairment, and may represent a biomarker of SSc-ILD severity.

Substrate specificity of human chymotrypsin-like protease (CTRL) characterized by phage display-selected small-protein inhibitors.

Chymotrypsin-like protease (CTRL) is one of the four chymotrypsin isoforms expressed in the human exocrine pancreas. Human genetic and experimental evidence indicate that chymotrypsins B1, B2, and C (CTRB1, CTRB2 and CTRC) are important not only for protein digestion but also for protecting the pancreas against pancreatitis by degrading potentially harmful trypsinogen. CTRL has not been reported to play a similar role, possibly due to its low abundance and/or different substrate specificity. To address this problem, we investigated the specificity of the substrate-binding groove of CTRL by evolving the substrate-like canonical loop of the Schistocerca gregaria proteinase inhibitor 2 (SGPI-2), a small-protein reversible chymotrypsin inhibitor to bind CTRL. We found that phage-associated SGPI-2 variants with strong affinity to CTRL were similar to those evolved previously against CTRB1, CTRB2 or bovine chymotrypsin A (bCTRA), indicating comparable substrate specificity. When tested as recombinant proteins, SGPI-2 variants inhibited CTRL with similar or slightly weaker affinity than bCTRA, confirming that CTRL is a typical chymotrypsin. Interestingly, an SGPI-2 variant selected with a Thr29His mutation in its reactive loop was found to inhibit CTRL strongly, but it was digested rapidly by bCTRA. Finally, CTRL was shown to degrade human anionic trypsinogen, however, at a much slower rate than CTRB2, suggesting that CTRL may not have a significant role in the pancreatic defense mechanisms against inappropriate trypsinogen activation and pancreatitis.

Molecular Dynamics Simulation as a Tool to Identify Mutual Synergistic Folding Proteins.

Mutual synergistic folding (MSF) proteins belong to a recently emerged subclass of disordered proteins, which are disordered in their monomeric forms but become ordered in their oligomeric forms. They can be identified by experimental methods following their unfolding, which happens in a single-step cooperative process, without the presence of stable monomeric intermediates. Only a limited number of experimentally validated MSF proteins are accessible. The amino acid composition of MSF proteins shows high similarity to globular ordered proteins, rather than to disordered ones. However, they have some special structural features, which makes it possible to distinguish them from globular proteins. Even in the possession of their oligomeric three-dimensional structure, classification can only be performed based on unfolding experiments, which are frequently absent. In this work, we demonstrate a simple protocol using molecular dynamics simulations, which is able to indicate that a protein structure belongs to the MSF subclass. The presumption of the known atomic resolution quaternary structure is an obvious limitation of the method, and because of its high computational time requirements, it is not suitable for screening large databases; still, it is a valuable in silico tool for identification of MSF proteins.

Combined miRNA and SERS urine liquid biopsy for the point-of-care diagnosis and molecular stratification of bladder cancer.

BACKGROUND: Bladder cancer (BC) has the highest per-patient cost of all cancer types. Hence, we aim to develop a non-invasive, point-of-care tool for the diagnostic and molecular stratification of patients with BC based on combined microRNAs (miRNAs) and surface-enhanced Raman spectroscopy (SERS) profiling of urine. METHODS: Next-generation sequencing of the whole miRNome and SERS profiling were performed on urine samples collected from 15 patients with BC and 16 control subjects (CTRLs). A retrospective cohort (BC = 66 and CTRL = 50) and RT-qPCR were used to confirm the selected differently expressed miRNAs. Diagnostic accuracy was assessed using machine learning algorithms (logistic regression, naïve Bayes, and random forest), which were trained to discriminate between BC and CTRL, using as input either miRNAs, SERS, or both. The molecular stratification of BC based on miRNA and SERS profiling was performed to discriminate between high-grade and low-grade tumors and between luminal and basal types. RESULTS: Combining SERS data with three differentially expressed miRNAs (miR-34a-5p, miR-205-3p, miR-210-3p) yielded an Area Under the Curve (AUC) of 0.92 ± 0.06 in discriminating between BC and CTRL, an accuracy which was superior either to miRNAs (AUC = 0.84 ± 0.03) or SERS data (AUC = 0.84 ± 0.05) individually. When evaluating the classification accuracy for luminal and basal BC, the combination of miRNAs and SERS profiling averaged an AUC of 0.95 ± 0.03 across the three machine learning algorithms, again better than miRNA (AUC = 0.89 ± 0.04) or SERS (AUC = 0.92 ± 0.05) individually, although SERS alone performed better in terms of classification accuracy. CONCLUSION: miRNA profiling synergizes with SERS profiling for point-of-care diagnostic and molecular stratification of BC. By combining the two liquid biopsy methods, a clinically relevant tool that can aid BC patients is envisaged.

A Transfer Learning Approach on the Optimization of Edge Detectors for Medical Images Using Particle Swarm Optimization.

Edge detection is a fundamental image analysis task, as it provides insight on the content of an image. There are weaknesses in some of the edge detectors developed until now, such as disconnected edges, the impossibility to detect branching edges, or the need for a ground truth that is not always accessible. Therefore, a specialized detector that is optimized for the image particularities can help improve edge detection performance. In this paper, we apply transfer learning to optimize cellular automata (CA) rules for edge detection using particle swarm optimization (PSO). Cellular automata provide fast computation, while rule optimization provides adaptability to the properties of the target images. We use transfer learning from synthetic to medical images because expert-annotated medical data is typically difficult to obtain. We show that our method is tunable for medical images with different properties, and we show that, for more difficult edge detection tasks, batch optimization can be used to boost the quality of the edges. Our method is suitable for the identification of structures, such as cardiac cavities on medical images, and could be used as a component of an automatic radiology decision support tool.

Butterfly Effect in Chaotic Image Segmentation.

The exploitation of the important features exhibited by the complex systems found in the surrounding natural and artificial space will improve computational model performance. Therefore, the purpose of the current paper is to use cellular automata as a tool simulating complexity, able to bring forth an interesting global behaviour based only on simple, local interactions. We show that, in the context of image segmentation, a butterfly effect arises when we perturb the neighbourhood system of a cellular automaton. Specifically, we enhance a classical GrowCut cellular automaton with chaotic features, which are also able to improve its performance (e.g., a Dice coefficient of 71% in case of 2D images). This enhanced GrowCut flavor (referred to as Band-Based GrowCut) uses an extended, stochastic neighbourhood, in which randomly-selected remote neighbours reinforce the standard local ones. We demonstrate the presence of the butterfly effect and an increase in segmentation performance by numerical experiments performed on synthetic and natural images. Thus, our results suggest that, by having small changes in the initial conditions of the performed task, we can induce major changes in the final outcome of the segmentation.

SERS-based quantification of albuminuria in the normal-to-mildly increased range.

The lack of an accurate point-of-care detection system for microalbuminuria represents an important unmet medical need that contributes to the morbidity and mortality of patients with kidney diseases. In this proof-of-concept study, we used SERS spectroscopy to detect urinary albumin concentrations in the normal-to-mildly increased albuminuria range, a strategy that could be useful for the early diagnosis of renal impairment due to uncontrolled hypertension, cardiovascular disease or diabetes. We analyzed 27 urine samples by SERS, using iodide-modified silver nanoparticles and we could discriminate between groups with high and low albumin concentrations with an overall accuracy of 89%, 93% and 89%, using principal component analysis-linear discriminant analysis and cut-off values of 3, 6 and 10 µg mL-1 for urinary albumin concentrations, respectively. We achieved a detection limit of 3 µg mL-1 for human serum albumin based on the 1002 cm-1 SERS band, attributed to the ring breathing vibration of phenylalanine. Our detection limit is similar to that of the immunoturbidimetric assays and around one order of magnitude below the detection limit of urinary dipsticks used to detect microalbuminuria. We used principal least squares regression for building a spectral model for quantifying albumin. Using an independent prediction set, the R2 and root mean squared error of prediction between predicted and reference values of human serum albumin concentrations were 0.982 and 2.82, respectively. Here, we show that direct SERS spectroscopy has the sensitivity required for detecting clinically relevant concentrations of urinary albumin, a strategy that could be used in the future for the point-of-care screening of microalbuminuria.

Activated prostaglandin D2 receptors on macrophages enhance neutrophil recruitment into the lung.

BACKGROUND: Prostaglandin (PG) D2 is an early-phase mediator in inflammation, but its action and the roles of the 2 D-type prostanoid receptors (DPs) DP1 and DP2 (also called chemoattractant receptor-homologous molecule expressed on T(H)2 cells) in regulating macrophages have not been elucidated to date. OBJECTIVE: We investigated the role of PGD2 receptors on primary human macrophages, as well as primary murine lung macrophages, and their ability to influence neutrophil action in vitro and in vivo. METHODS: In vitro studies, including migration, Ca(2+) flux, and cytokine secretion, were conducted with primary human monocyte-derived macrophages and neutrophils and freshly isolated murine alveolar and pulmonary interstitial macrophages. In vivo pulmonary inflammation was assessed in male BALB/c mice. RESULTS: Activation of DP1, DP2, or both receptors on human macrophages induced strong intracellular Ca(2+) flux, cytokine release, and migration of macrophages. In a murine model of LPS-induced pulmonary inflammation, activation of each PGD2 receptor resulted in aggravated airway neutrophilia, tissue myeloperoxidase activity, cytokine contents, and decreased lung compliance. Selective depletion of alveolar macrophages abolished the PGD2-enhanced inflammatory response. Activation of PGD2 receptors on human macrophages enhanced the migratory capacity and prolonged the survival of neutrophils in vitro. In human lung tissue specimens both DP1 and DP2 receptors were located on alveolar macrophages along with hematopoietic PGD synthase, the rate-limiting enzyme of PGD2 synthesis. CONCLUSION: For the first time, our results show that PGD2 markedly augments disease activity through its ability to enhance the proinflammatory actions of macrophages and subsequent neutrophil activation.

STIM1/ORAI1-mediated Ca2+ Influx Regulates Enolase-1 Exteriorization.

Tumor cells use broad spectrum proteolytic activity of plasmin to invade tissue and form metastatic foci. Cell surface-associated enolase-1 (ENO-1) enhances plasmin formation and thus participates in the regulation of pericellular proteolysis. Although increased levels of cell surface bound ENO-1 have been described in different types of cancer, the molecular mechanism responsible for ENO-1 exteriorization remains elusive. In the present study, increased ENO-1 protein levels were found in ductal breast carcinoma and on the cell surface of highly metastatic breast cancer cell line MDA-MB-231. Elevated cell surface-associated ENO-1 expression correlated with augmented MDA-MB-231 cell migratory and invasive properties. Exposure of MDA-MB-231 cells to LPS potentiated translocation of ENO-1 to the cell surface and its release into the extracellular space in the form of exosomes. These effects were independent of de novo protein synthesis and did not require the classical endoplasmic reticulum/Golgi pathway. LPS-triggered ENO-1 exteriorization was suppressed by pretreatment of MDA-MB-231 cells with the Ca(2+) chelator BAPTA or an inhibitor of endoplasmic reticulum Ca(2+)-ATPase pump, cyclopiazonic acid. In line with these observations, the stromal interaction molecule (STIM) 1 and the calcium release-activated calcium modulator (ORAI) 1-mediated store-operated Ca(2+) entry were found to regulate LPS-induced ENO-1 exteriorization. Pharmacological blockage or knockdown of STIM1 or ORAI1 reduced ENO-1-dependent migration of MDA-MB-231 cells. Collectively, our results demonstrate the pivotal role of store-operated Ca(2+) channel-mediated Ca(2+) influx in the regulation of ENO-1 exteriorization and thus in the modulation of cancer cell migratory and invasive properties.

CD133+ cells in pulmonary arterial hypertension.

Circulating mononuclear cells may play an important role for the vascular remodelling in pulmonary arterial hypertension (PAH), but studies addressing multiple progenitor populations are rare and inconsistent.We used a comprehensive fluorescence-activated cell sorting analysis of circulating mononuclear cells in 20 PAH patients and 20 age- and sex-matched controls, and additionally analysed CD133(+) cells in the lung tissue of five PAH transplant recipients and five healthy controls (donor lungs).PAH patients were characterised by increased numbers of circulating CD133(+) cells and lymphopenia as compared with control. In PAH, CD133(+) subpopulations positive for CD117 or CD45 were significantly increased, whereas CD133(+)CD309(+), CD133(+)CXCR2(+) and CD133(+)CD31(+) cells were decreased. In CD133(+) cells, SOX2, Nanog, Ki67 and CXCR4 were not detected, but Oct3/4 mRNA was present in both PAH and controls. In the lung tissue, CD133(+) cells included three main populations: type 2 pneumocytes, monocytes and undifferentiated cells without significant differences between PAH and controls.In conclusion, circulating CD133(+) progenitor cells are elevated in PAH and consist of phenotypically different subpopulations that may be up- or downregulated. This may explain the inconsistent results in the literature. CD133(+) type 2 pneumocytes in the lung tissue are not associated with circulating CD133(+) mononuclear cells.

Comprehensive analysis of inflammatory markers in chronic thromboembolic pulmonary hypertension patients.

Chronic thromboembolic pulmonary hypertension (CTEPH) is associated with chronic inflammation but the pathological mechanisms are largely unknown. Our study aimed to simultaneously profile a broad range of cytokines in the supernatant of pulmonary endarterectomy (PEA) surgical material, as well as prospectively in patients with CTEPH to investigate whether circulating cytokines are associated with haemodynamic and physical characteristics of CTEPH patients. Herein, we show that PEA specimens revealed a significant upregulation of interleukin (IL)-6, monocyte chemoattractant protein-1, interferon-γ-induced protein-10 (IP)-10, macrophage inflammatory protein (MIP)1α and RANTES compared to lung tissue from healthy controls. In prospectively collected serum, levels of IL-6, IL-8, IP-10, monokine induced by interferon-γ (MIG) and MIP1α were significantly elevated in CTEPH patients compared to age- and sex-matched healthy controls. In serum of idiopathic pulmonary arterial hypertension (IPAH) patients, only IP-10 and MIG were significantly increased. In CTEPH but not in IPAH, IP-10 was negatively correlated with cardiac index, 6-min walking distance and carbon monoxide diffusion capacity. In vitro, IP-10 significantly increased migration of freshly isolated adventitial fibroblasts. Our study is the first to show that IP-10 secretion is associated with poor pulmonary haemodynamics and physical capacity in CTEPH and might be involved in the pathological mechanism of PEA tissue formation.

Non-invasive determination of pulmonary hypertension with dynamic contrast-enhanced computed tomography: a pilot study.

OBJECTIVES: In this pilot study we explored whether contrast-material bolus propagation time and speed in the pulmonary arteries (PAs) determined by dynamic contrast-enhanced computed tomography (DCE-CT) can distinguish between patients with and without pulmonary hypertension (PH). METHODS: Twenty-three patients (18 with and 5 without PH) were examined with a DCE-CT sequence following their diagnostic or follow-up right-sided heart catheterisation (RHC). X-ray attenuation over time curves were recorded for regions of interest in the main, right and left PA and fitted with a spline fit. Contrast material bolus propagation speeds and time differences between the peak concentrations were compared with haemodynamic parameters from RHC. RESULTS: Bolus speed correlated (ρ = -0.55) with mean pulmonary arterial pressure (mPAP) and showed a good discriminative power between patients with and without PH (cut-off speed 317 mm/s; sensitivity 100%/specificity 100%). Additionally, time differences between peaks correlated with mPAP (ρ = 0.64 and 0.49 for right and left PA, respectively) and discrimination was achieved with sensitivity 100%/specificity 100% (cut-off time 0.15 s) and sensitivity 93 %/specificity 80% (cut-off time 0.45 s), respectively. CONCLUSIONS: Bolus propagation speed and time differences between contrast material peaks in the PA can identify PH. This method could be used to confirm the indication for RHC in patients screened for pulmonary hypertension. KEY POINTS: • Dynamic contrast-enhanced computed tomography (CT) can identify patients with pulmonary hypertension. • Bolus propagation speed in the pulmonary artery is reduced in pulmonary hypertension. • Peak-contrast propagation times provide a practical surrogate for speed. • This non-invasive technique could serve as a screening method for pulmonary hypertension. • Invasive right-sided heart catheterisations might be restricted to a smaller group of patients.

Src tyrosine kinase is crucial for potassium channel function in human pulmonary arteries.

The potassium channel TWIK-related acid sensitive potassium (TASK)-1 channel, together with other potassium channels, controls the low resting tone of pulmonary arteries. The Src family tyrosine kinase (SrcTK) may control potassium channel function in human pulmonary artery smooth muscle cells (hPASMCs) in response to changes in oxygen tension and the clinical use of a SrcTK inhibitor has resulted in partly reversible pulmonary hypertension. This study aimed to determine the role of SrcTK in hypoxia-induced inhibition of potassium channels in hPASMCs. We show that SrcTK is co-localised with the TASK-1 channel. Inhibition of SrcTK decreases potassium current density and results in considerable depolarisation, while activation of SrcTK increases potassium current in patch-clamp recordings. Moderate hypoxia and the SrcTK inhibitor decrease the tyrosine phosphorylation state of the TASK-1 channel. Hypoxia also decreases the level of phospho-SrcTK (tyr419) and reduces the co-localisation of the TASK-1 channel and phospho-SrcTK. Corresponding to this, hypoxia reduces TASK-1 currents before but not after SrcTK inhibition and, in the isolated perfused mouse lung, SrcTK inhibitors increase pulmonary arterial pressure. We propose that the SrcTK is a crucial factor controlling potassium channels, acting as a cofactor for setting a negative resting membrane potential in hPASMCs and a low resting pulmonary vascular tone.

A Light, 3D UNet-based Architecture for Fully Automatic Segmentation of Prostate Lesions from T2-MRI Images.

INTRODUCTION: Prostate magnetic resonance imaging (MRI) has been recently integrated into the pathway of diagnosis of prostate cancer (PCa). However, the lack of an optimal contrast-to-noise ratio hinders automatic recognition of suspicious lesions, thus developing a solution for proper delimitation of the tumour and its separation from the healthy parenchyma, which is of primordial importance. METHOD: As a solution to this unmet medical need, we aimed to develop a decision support system based on artificial intelligence, which automatically segments the prostate and any suspect area from the 3D MRI images. We assessed retrospective data from all patients diagnosed with PCa by MRI-US fusion prostate biopsy, who underwent prostate MRI in our department due to a clinical or biochemical suspicion of PCa (n=33). All examinations were performed using a 1.5 Tesla MRI scanner. All images were reviewed by two radiologists, who performed manual segmentation of the prostate and all lesions. A total of 145 augmented datasets were generated. The performance of our fully automated end-to-end segmentation model based on a 3D UNet architecture and trained in two learning scenarios (on 14 or 28 patient datasets) was evaluated by two loss functions. RESULTS: Our model had an accuracy of over 90% for automatic segmentation of prostate and PCa nodules, as compared to manual segmentation. We have shown low complexity networks, UNet architecture with less than five layers, as feasible and to show good performance for automatic 3D MRI image segmentation. A larger training dataset could further improve the results. CONCLUSION: Therefore, herein, we propose a less complex network, a slim 3D UNet with superior performance, being faster than the original five-layer UNet architecture.

Fully automated bladder tumor segmentation from T2 MRI images using 3D U-Net algorithm.

Introduction: Bladder magnetic resonance imaging (MRI) has been recently integrated in the diagnosis pathway of bladder cancer. However, automatic recognition of suspicious lesions is still challenging. Thus, development of a solution for proper delimitation of the tumor and its separation from the healthy tissue is of primordial importance. As a solution to this unmet medical need, we aimed to develop an artificial intelligence-based decision support system, which automatically segments the bladder wall and the tumor as well as any suspect area from the 3D MRI images. Materials: We retrospectively assessed all patients diagnosed with bladder cancer, who underwent MRI at our department (n=33). All examinations were performed using a 1.5 Tesla MRI scanner. All images were reviewed by two radiologists, who performed manual segmentation of the bladder wall and all lesions. First, the performance of our fully automated end-to-end segmentation model based on a 3D U-Net architecture (by considering various depths of 4, 5 or 6 blocks) trained in two data augmentation scenarios (on 5 and 10 augmentation datasets per original data, respectively) was tested. Second, two learning setups were analyzed by training the segmentation algorithm with 7 and 14 MRI original volumes, respectively. Results: We obtained a Dice-based performance over 0.878 for automatic segmentation of bladder wall and tumors, as compared to manual segmentation. A larger training dataset using 10 augmentations for 7 patients could further improve the results of the U-Net-5 model (0.902 Dice coefficient at image level). This model performed best in terms of automated segmentation of bladder, as compared to U-Net-4 and U-Net-6. However, in this case increased time for learning was needed as compared to U-Net-4. We observed that an extended dataset for training led to significantly improved segmentation of the bladder wall, but not of the tumor. Conclusion: We developed an intelligent system for bladder tumors automated diagnostic, that uses a deep learning model to segment both the bladder wall and the tumor. As a conclusion, low complexity networks, with less than five-layers U-Net architecture are feasible and show good performance for automatic 3D MRI image segmentation in patients with bladder tumors.

MRI-Based Radiomics in Bladder Cancer: A Systematic Review and Radiomics Quality Score Assessment.

(1): Background: With the recent introduction of vesical imaging reporting and data system (VI-RADS), magnetic resonance imaging (MRI) has become the main imaging method used for the preoperative local staging of bladder cancer (BCa). However, the VI-RADS score is subject to interobserver variability and cannot provide information about tumor cellularity. These limitations may be overcome by using a quantitative approach, such as the new emerging domain of radiomics. (2) Aim: To systematically review published studies on the use of MRI-based radiomics in bladder cancer. (3) Materials and Methods: We performed literature research using the PubMed MEDLINE, Scopus, and Web of Science databases using PRISMA principles. A total of 1092 papers that addressed the use of radiomics for BC staging, grading, and treatment response were retrieved using the keywords "bladder cancer", "magnetic resonance imaging", "radiomics", and "textural analysis". (4) Results: 26 papers met the eligibility criteria and were included in the final review. The principal applications of radiomics were preoperative tumor staging (n = 13), preoperative prediction of tumor grade or molecular correlates (n = 9), and prediction of prognosis/response to neoadjuvant therapy (n = 4). Most of the developed radiomics models included second-order features mainly derived from filtered images. These models were validated in 16 studies. The average radiomics quality score was 11.7, ranging between 8.33% and 52.77%. (5) Conclusions: MRI-based radiomics holds promise as a quantitative imaging biomarker of BCa characterization and prognosis. However, there is still need for improving the standardization of image preprocessing, feature extraction, and external validation before applying radiomics models in the clinical setting.

Peroxisome proliferator-activated receptor-ß/δ, the acute signaling factor in prostacyclin-induced pulmonary vasodilation.

As powerful vasodilators, prostacyclin analogues are presently the mainstay in the treatment of severe pulmonary arterial hypertension. Although the hemodynamic effects of prostacyclin analogues are well known, the molecular mechanism of their acute effects on pulmonary vascular tone and systemic vascular tone remains poorly understood. Peroxisome proliferator-activated receptor-ß/δ (PPARß/δ) was previously identified as a putative receptor responsible for the modulation of target gene expression in response to prostacyclin analogues. The present study investigated the signaling pathway of prostacyclin in human pulmonary arterial smooth muscle cells (PASMCs), and sought to define the role of PPARß/δ in the acute vasodilating effect. In human PASMCs, prostacyclin rapidly activated TWIK-related acid-sensitive K channel 1 (TASK-1) and calcium-dependent potassium channels (K(Ca)). This pathway was mediated via the prostanoid I receptor-protein kinase A pathway. The silencing of PPARß/δ demonstrated that the downstream K(Ca) activation was exclusively dependent on PPARß/δ signaling, whereas the activation of TASK-1 was not. In addition, the PPARß/δ-induced activation of K(Ca) was independent of NO. The acute prostacyclin-induced K(Ca) activation is critically dependent on PPARß/δ as a rapid signaling factor. This accounts in part for the vasodilating effect of prostacyclin in pulmonary arteries, and provides insights into a new molecular explanation for the effects of prostanoids.

TRPV4 mutations in children with congenital distal spinal muscular atrophy.

Inherited disorders characterized by motor neuron loss and muscle weakness are genetically heterogeneous. The recent identification of mutations in the gene encoding transient receptor potential vanilloid 4 (TRPV4) in distal spinal muscular atrophy (dSMA) prompted us to screen for TRPV4 mutations in a small group of children with compatible phenotype. In a girl with dSMA and vocal cord paralysis, we detected a new variant (p.P97R) localized in the cytosolic N-terminus of the TRPV4 protein, upstream of the ankyrin-repeat domain, where the great majority of disease-associated mutations reside. In another child with congenital dSMA, in this case associated with bone abnormalities, we detected a previously reported mutation (p.R232C). Functional analysis of the novel p.P97R mutation in a heterologous system demonstrated a loss-of-function mechanism. Protein localization studies in muscle, skin, and cultured skin fibroblasts from both patients showed normal protein expression. No TRPV4 mutations were detected in four children with dSMA without bone or vocal cord involvement. Adding to the clinical and molecular heterogeneity of TRPV4-associated diseases, our results suggest that molecular testing of the TRPV4 gene is warranted in cases of congenital dSMA with bone abnormalities and vocal cord paralysis.

Interaction of eosinophils with endothelial cells is modulated by prostaglandin EP4 receptors.

Eosinophil extravasation across the endothelium is a key feature of allergic inflammation. Here, we investigated the role of PGE(2) and its receptor, E-type prostanoid receptor (EP)-4, in the regulation of eosinophil interaction with human pulmonary microvascular endothelial cells. PGE(2) and the EP4 receptor agonist ONO AE1-329 significantly reduced eotaxin-induced eosinophil adhesion to fibronectin, and formation of filamentous actin and gelsolin-rich adhesive structures. These inhibitory effects were reversed by a selective EP4 receptor antagonist, ONO AE3-208. PGE(2) and the EP4 agonist prevented the activation and cell-surface clustering of ß2 integrins, and L-selectin shedding of eosinophils. Under physiological flow conditions, eosinophils that were treated with the EP4 agonist showed reduced adhesion to endothelial monolayers upon stimulation with eotaxin, as well as after TNF-α-induced activation of the endothelial cells. Selective activation of EP1, EP2, and EP3 receptors did not alter eosinophil adhesion to endothelial cells, whereas the EP4 antagonist prevented PGE(2) from decreasing eosinophil adhesion. Finally, eosinophil transmigration across thrombin- and TNF-α-activated endothelial cells was effectively reduced by the EP4 agonist. These data suggest that PGE(2) -EP4 signaling might be protective against allergic responses by inhibiting the interaction of eosinophils with the endothelium and might hence be a useful therapeutic option for controlling inappropriate eosinophil infiltration.