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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.

Michaela Auer-Grumbach and colleagues report that missense alterations in the N-terminal ankyrin domain of TRPV4 underlie three distinct autosomal dominant disorders of the peripheral nervous system. Alterations in other regions of TRPV4 have been shown to underlie a family of autosomal dominant skeletal dysplasias, underscoring the marked clinical heterogeneity associated with mutations in this channel. Spinal muscular atrophies (SMA, also known as hereditary motor neuropathies) and hereditary motor and sensory neuropathies (HMSN) are clinically and genetically heterogeneous disorders of the peripheral nervous system. Here we report that mutations in the TRPV4 gene cause congenital distal SMA, scapuloperoneal SMA, HMSN 2C. We identified three missense substitutions (R269H, R315W and R316C) affecting the intracellular N-terminal ankyrin domain of the TRPV4 ion channel in five families. Expression of mutant TRPV4 constructs in cells from the HeLa line revealed diminished surface localization of mutant proteins. In addition, TRPV4-regulated Ca 2+ influx was substantially reduced even after stimulation with 4αPDD, a TRPV4 channel-specific agonist, and with hypo-osmotic solution. In summary, we describe a new hereditary channelopathy caused by mutations in TRPV4 and present evidence that the resulting substitutions in the N-terminal ankyrin domain affect channel maturation, leading to reduced surface expression of functional TRPV4 channels.

Renal cancer (RC) represents 3% of all cancers, with a 2% annual increase in incidence worldwide, opening the discussion about the need for screening. However, no established screening tool currently exists for RC. To tackle this issue, we assessed surface-enhanced Raman scattering (SERS) profiling of serum as a liquid biopsy strategy to detect renal cell carcinoma (RCC), the most prevalent histologic subtype of RC. Thus, serum samples were collected from 23 patients with RCC and 27 controls (CTRL) presenting with a benign urological pathology such as lithiasis or benign prostatic hypertrophy. SERS profiling of deproteinized serum yielded SERS band spectra attributed mainly to purine metabolites, which exhibited higher intensities in the RCC group, and Raman bands of carotenoids, which exhibited lower intensities in the RCC group. Principal component analysis (PCA) of the SERS spectra showed a tendency for the unsupervised clustering of the two groups. Next, three machine learning algorithms (random forest, kNN, naïve Bayes) were implemented as supervised classification algorithms for achieving discrimination between the RCC and CTRL groups, yielding an AUC of 0.78 for random forest, 0.78 for kNN, and 0.76 for naïve Bayes (average AUC 0.77 ± 0.01). The present study highlights the potential of SERS liquid biopsy as a diagnostic and screening strategy for RCC. Further studies involving large cohorts and other urologic malignancies as controls are needed to validate the proposed SERS approach.

The ideal photothermal therapy agent should exhibit a high energy conversion capacity, but it should not induce any cytotoxic effects unless it is exposed to electromagnetic radiation. We present data on biocompatibility and photothermal conversion capacity of colloidal gold nanoparticle assemblies (NPAs), obtained by hydroxylamine hydrochloride reduction at room temperature. The cytotoxic profile of NPAs with a mean diameter of 20 and 120 nm, respectively, was assessed using 3-[4,5-dimethylthiazole-2-yl]-2,5-diphenyltetrazolium bromide (MTT) assay, demonstrating tolerable cytotoxic effect on A549 human lung adenocarcinoma cell line at gold concentrations up to 150 μg gold/mL. Insights regarding the oxidative stress were gained using peroxide-sensitive fluorescent probes, which showed no additional oxidative stress due to NPA exposure. Using infrared thermal imaging, the photothermal conversion was evidenced, the effect being more prominent for the 120-nm diameter NPAs irradiated with the 785-nm laser. The photothermal capabilities of NPAs were highlighted also by Raman imaging studies, showing intracellular carbon by-products due to the thermal damage. Intracellular carbon deposits overlapping with the nanoparticle-rich sites were identified. These results highlight that NPAs are a versatile platform with possible applications in nanoparticle-based photothermal therapy.

Aims: We aimed to compare cardiac volumes measured with echocardiography (echo) and cardiac magnetic resonance imaging (MRI) in a mixed cohort of healthy controls (controls) and patients with atrial fibrillation (AF). Materials and methods: In total, 123 subjects were included in our study; 99 full datasets were analyzed. All the participants underwent clinical evaluation, EKG, echo, and cardiac MRI acquisition. Participants with full clinical data were grouped into 63 AF patients and 36 controls for calculation of left atrial volume (LA Vol) and 51 AF patients and 30 controls for calculation of left ventricular end-diastolic volume (LV EDV), end-systolic volume (ESV), and LV ejection fraction (LV EF). Results: No significant differences in LA Vol were observed (p > 0.05) when measured by either echo or MRI. However, echo provided significantly lower values for left ventricular volume (p < 0.0001). The echo LA Vol of all the subjects correlated well with that measured by MRI (Spearmen correlation coefficient r = 0.83, p < 0.0001). When comparing the two methods, significant positive correlations of EDV (all subjects: r = 0.55; Controls: r = 0.71; and AF patients: r = 0.51) and ESV (all subjects: r = 0.62; Controls: r = 0.47; and AF patients: r = 0.66) were found, with a negative bias for values determined using echo. For a subgroup of participants with ventricular volumes smaller than 49.50 mL, this bias was missing, thus in this case echocardiography could be used as an alternative for MRI. Conclusion: Good correlation and reduced bias were observed for LA Vol and EF determined by echo as compared to cardiac MRI in a mixed cohort of patients with AF and healthy volunteers. For the determination of volume values below 49.50 mL, an excellent correlation was observed between values obtained using echo and MRI, with comparatively reduced bias for the volumes determined by echo. Therefore, in certain cases, echocardiography could be used as a less expensive, less time-consuming, and contraindication free alternative to MRI for cardiac volume determination.

Circulating RNA may result from excessive cell damage or acute viral infection and can interact with vascular endothelial cells. Despite the obvious clinical implications associated with the presence of circulating RNA, its pathological effects on endothelial cells and the governing molecular mechanisms are still not fully elucidated. We analyzed the effects of double stranded RNA on primary human pulmonary artery endothelial cells (hPAECs). The effect of natural and synthetic double-stranded RNA (dsRNA) on hPAECs was investigated using trans-endothelial electric resistance, molecule trafficking, calcium (Ca(2+)) homeostasis, gene expression and proliferation studies. Furthermore, the morphology and mechanical changes of the cells caused by synthetic dsRNA was followed by in-situ atomic force microscopy, by vascular-endothelial cadherin and F-actin staining. Our results indicated that exposure of hPAECs to synthetic dsRNA led to functional deficits. This was reflected by morphological and mechanical changes and an increase in the permeability of the endothelial monolayer. hPAECs treated with synthetic dsRNA accumulated in the G1 phase of the cell cycle. Additionally, the proliferation rate of the cells in the presence of synthetic dsRNA was significantly decreased. Furthermore, we found that natural and synthetic dsRNA modulated Ca(2+) signaling in hPAECs by inhibiting the sarco-endoplasmic Ca(2+)-ATPase (SERCA) which is involved in the regulation of the intracellular Ca(2+) homeostasis and thus cell growth. Even upon synthetic dsRNA stimulation silencing of SERCA3 preserved the endothelial monolayer integrity. Our data identify novel mechanisms by which dsRNA can disrupt endothelial barrier function and these may be relevant in inflammatory processes.

The main objective of this paper is to determine the thermal stresses and displacements in multilayered curved beams subjected to thermal loading and concentrated moment. An analytical solution is presented to tackle this thermoelastic problem of multilayered circular arc with constant radius. The model can be modified to determine the stresses within radially graded curved beams. The developed plane stress method is compared to result coming from finite element simulations. Our main focus is to determine the analytical solution for the stresses and displacement within the beam which is subjected to constant temperature field and concentrated moment at the end of the beam.

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.

Magnetic resonance imaging (MRI) is conventionally used for the detection and diagnosis of multiple sclerosis (MS), often complemented by lumbar puncture-a highly invasive method-to validate the diagnosis. Additionally, MRI is periodically repeated to monitor disease progression and treatment efficacy. Recent research has focused on the application of artificial intelligence (AI) and radiomics in medical image processing, diagnosis, and treatment planning. A review of the current literature was conducted, analyzing the use of AI models and texture analysis for MS lesion segmentation and classification. The study emphasizes common models, including U-Net, Support Vector Machine, Random Forest, and -Nearest Neighbors, alongside their evaluation metrics. The analysis revealed a fragmented research landscape, with significant variation in model architectures and performance. Evaluation metrics such as Accuracy, Dice score, and Sensitivity are commonly employed, with some models demonstrating robustness across multi-center datasets. However, most studies lack validation in clinical scenarios. The absence of consensus on the optimal model for MS lesion segmentation highlights the need for standardized methodologies and clinical validation. Future research should prioritize clinical trials to establish the real-world applicability of AI-driven decision support tools. This review provides a comprehensive overview of contemporary advancements in AI and radiomics for analyzing and monitoring emerging MS lesions in MRI.

In parallel with the growing concerns of climate change, sustainability, and a perceived lack of urban vibrancy and vitality, an increased number of planning and design movements, policies, and incentives have emerged in the US during the last decades, criticizing urban sprawl and praising the idea of 15-minute, compact cities. However, the tools meant to achieve these, including transport-oriented and mixed-use developments were typically hampered by residential perceptions and demand, especially in the spread, auto-dependent urban regions of the western USA. The aim of the research was to explore current trends in the development of mixed-use projects and the extent to which these processes are stimulated by sustainability concerns in Phoenix and Tempe, Arizona, located in one of the most spread urban regions in the world. Interviews were conducted with planners and city representatives in the Phoenix Metropolitan Area, which are complemented by the review of municipal strategies and zoning ordinances, visualization and analysis of GIS data, and implementation of site visits. The findings show that the strategic aspirations towards mixed-use developments lack environmental considerations due to public perceptions being tied to other issues related to mixed-use developments, which can be traced primarily to Phoenix Downtown. As general difficulties, concerns aggravated by political, administrative, and funding problems. However, decoupled from sustainability, mixed-use developments are likely to proliferate in the Phoenix and Tempe areas due to political will and continuous gentrification processes.