ntsm: an alignment-free, ultra-low-coverage, sequencing technology agnostic, intraspecies sample comparison tool for sample swap detection.

BACKGROUND: Due to human error, sample swapping in large cohort studies with heterogeneous data types (e.g., mix of Oxford Nanopore Technologies, Pacific Bioscience, Illumina data, etc.) remains a common issue plaguing large-scale studies. At present, all sample swapping detection methods require costly and unnecessary (e.g., if data are only used for genome assembly) alignment, positional sorting, and indexing of the data in order to compare similarly. As studies include more samples and new sequencing data types, robust quality control tools will become increasingly important. FINDINGS: The similarity between samples can be determined using indexed k-mer sequence variants. To increase statistical power, we use coverage information on variant sites, calculating similarity using a likelihood ratio-based test. Per sample error rate, and coverage bias (i.e., missing sites) can also be estimated with this information, which can be used to determine if a spatially indexed principal component analysis (PCA)-based prescreening method can be used, which can greatly speed up analysis by preventing exhaustive all-to-all comparisons. CONCLUSIONS: Because this tool processes raw data, is faster than alignment, and can be used on very low-coverage data, it can save an immense degree of computational resources in standard quality control (QC) pipelines. It is robust enough to be used on different sequencing data types, important in studies that leverage the strengths of different sequencing technologies. In addition to its primary use case of sample swap detection, this method also provides information useful in QC, such as error rate and coverage bias, as well as population-level PCA ancestry analysis visualization.

Diversity study of Beauveria bassiana species for finding the most virulent strain to manage Bemisia tabaci in cotton.

Beauveria bassiana (Bal.-Criv.) is an important entomopathogenic fungus being used for the management of various agricultural pests worldwide. However, all strains of B. bassiana may not be effective against whitefly, Bemisia tabaci, or other pests, and strains show diversity in their growth, sporulation, virulence features, and overall bioefficacy. Thus, to select the most effective strain, a comprehensive way needs to be devised. We studied the diversity among the 102 strains of B. bassiana isolated from 19 insect species based on their physiological features, virulence, and molecular phylogeny, to identify promising ones for the management of B. tabaci. Strains showed diversity in mycelial growth, conidial production, and their virulence against B. tabaci nymphs. The highest nymphal mortality (2nd and 3rd instar) was recorded with MTCC-4511 (95.1%), MTCC-6289 (93.8%), and MTCC-4565 (89.9%) at a concentration of 1 × 106 conidia ml-1 under polyhouse conditions. The highest bioefficacy index (BI) was in MTCC-4511 (78.3%), MTCC-4565 (68.2%), and MTCC-4543 (62.1%). MTCC-4511, MTCC-4565, and MTCC-4543 clustered with positive loading of eigenvalues for the first two principal components and the cluster analysis also corresponded well with PCA (principal component analysis) (nymphal mortality and BI). The molecular phylogeny could not draw any distinct relationship between physiological features, the virulence of B. bassiana strains with the host and location. The BI, PCA, and square Euclidean distance cluster were found the most useful tools for selecting potential entomopathogenic strains. The selected strains could be utilized for the management of the B. tabaci nymphal population in the field through the development of effective formulations. KEY POINTS: • 102 B. bassiana strains showed diversity in growth and virulence against B. tabaci. • Bioefficacy index, PCA, and SED group are efficient tools for selecting potential strains. • MTCC-4511, 4565, and 4543 chosen as the most virulent strains to kill whitefly nymphs.

Androgen Signaling in Prostate Cancer: When a Friend Turns Foe.

Androgen (AR) signaling is the main signaling for the development of the prostate and its normal functioning. AR is highly specific for testosterone and dihydrotestosterone, significantly contributing to prostate development, physiology, and cancer. All these receptors have emerged as crucial therapeutic targets for PCa. In the year 1966, the Noble prize was awarded to Huggins and Hodge for their groundbreaking discovery of AR. As it is a pioneer transcription factor, it belongs to the steroid hormone receptor family and consists of domains, including DNA binding domain (DBD), hormone response elements (HRE), C-terminal ligand binding domain (LBD), and N-terminal regulatory domains. Structural variations in AR, such as AR gene amplification, LBD mutations, alternative splicing of exons, hypermethylation of AR, and co- regulators, are major contributors to PCa. It's signaling is crucial for the development and functioning of the prostate gland, with the AR being the key player. The specificity of AR for testosterone and dihydrotestosterone is important in prostate physiology. However, when it is dysregulated, AR contributes significantly to PCa. However, the structural variations in AR, such as gene amplification, mutations, alternative splicing, and epigenetic modifications, drive the PCa progression. Therefore, understanding AR function and dysregulation is essential for developing effective therapeutic strategies. Thus, the aim of this review was to examine how AR was initially pivotal for prostate development and how it turned out to show both positive and detrimental implications for the prostate.

Analysis of characteristic aromas of buckwheat with different germplasm using gas chromatography-mass spectrometry combined with chemometrics and multivariate statistical analysis.

In this study, the volatile components in 40 samples of Tartary buckwheat and common buckwheat from 6 major producing areas in China were analyzed. A total of 77 volatile substances were identified, among which aldehydes and hydrocarbons were the main volatile components. Odor activity value analysis revealed 26 aromatic compounds, with aldehydes making a significant contribution to the aroma of buckwheat. Seven key compounds that could be used to distinguish Tartary buckwheat from common buckwheat were identified. The orthogonal partial least squares-discriminant analysis was effectively used to classify Tartary buckwheat and common buckwheat from different producing areas. This study provides valuable information for evaluating buckwheat quality, breeding high-quality varieties, and enhancing rational resource development.

Assessing the effectiveness of spatial PCA on SVM-based decoding of EEG data.

Principal component analysis (PCA) has been widely employed for dimensionality reduction prior to multivariate pattern classification (decoding) in EEG research. The goal of the present study was to provide an evaluation of the effectiveness of PCA on decoding accuracy (using support vector machines) across a broad range of experimental paradigms. We evaluated several different PCA variations, including group-based and subject-based component decomposition and the application of Varimax rotation or no rotation. We also varied the numbers of PCs that were retained for the decoding analysis. We evaluated the resulting decoding accuracy for seven common event-related potential components (N170, mismatch negativity, N2pc, P3b, N400, lateralized readiness potential, and error-related negativity). We also examined more challenging decoding tasks, including decoding of face identity, facial expression, stimulus location, and stimulus orientation. The datasets also varied in the number and density of electrode sites. Our findings indicated that none of the PCA approaches consistently improved decoding performance related to no PCA, and the application of PCA frequently reduced decoding performance. Researchers should therefore be cautious about using PCA prior to decoding EEG data from similar experimental paradigms, populations, and recording setups.

Urban air PCDD/Fs: Atmospheric concentrations, temporal changes, gas/particle partitioning, possible sources and cancer risks.

Polychlorinated dibenzo-p-dioxins/furans (PCDD/Fs) are pollutants of concern due to their toxic effects. No active sampling study on PCDD/Fs has been conducted in Bursa. This study aimed to fill this gap by measuring PCDD/F levels in the region. Accordingly, the samples were collected from an urban area in Bursa, covering four seasons between June 2022 and April 2023. The total (gas+particulate) ambient air concentrations were between 312.23 and 829.80 fg/m3 (mean: 555.05 ± 173.62 fg/m3). In terms of toxic equivalents (TEQ), the average concentration was 43.29 ± 9.18 fg WHOTEQ/m3. Based on the concentration values obtained, cancer and non-carcinogenic risk values of PCDD/Fs were calculated for three different age groups. The results indicated negligible health risks for all age groups. In addition, a seasonal assessment was also made and it was observed that PCDD/F concentration values varied with the ambient air temperatures. In general, higher values were measured in colder months compared to warmer months. This was probably due to the additional sources and adverse meteorological conditions. Moreover, the gas/particle partitioning of PCDD/Fs was investigated in detail. The average gas and particulate phase concentrations for PCDD/Fs were 101.81 ± 20.77 and 453.24 ± 172.50, respectively. It was found that an equilibrium state was not reached in the gas/particle partitioning. Two different gas/particle partition models based on adsorption and absorption mechanisms were compared, and the absorption model gave more consistent predictions. The Principal Component Analysis (PCA) was employed to identify the possible PCDD/F sources. The results indicated that the region was influenced by vehicle emissions, residential heating, organized industrial zones and metal recycling facilities. In addition, 72-hour backward air mass trajectory analyses were performed to understand the long-range transported air masses. However, it was found that the transported air masses did not significantly affect the concentration values measured in the sampling site.

lncRNA Biomarkers of Glioblastoma Multiforme.

Long noncoding RNAs (lncRNAs) are RNA molecules of 200 nucleotides or more in length that are not translated into proteins. Their expression is tissue-specific, with the vast majority involved in the regulation of cellular processes and functions. Many human diseases, including cancer, have been shown to be associated with deregulated lncRNAs, rendering them potential therapeutic targets and biomarkers for differential diagnosis. The expression of lncRNAs in the nervous system varies in different cell types, implicated in mechanisms of neurons and glia, with effects on the development and functioning of the brain. Reports have also shown a link between changes in lncRNA molecules and the etiopathogenesis of brain neoplasia, including glioblastoma multiforme (GBM). GBM is an aggressive variant of brain cancer with an unfavourable prognosis and a median survival of 14-16 months. It is considered a brain-specific disease with the highly invasive malignant cells spreading throughout the neural tissue, impeding the complete resection, and leading to post-surgery recurrences, which are the prime cause of mortality. The early diagnosis of GBM could improve the treatment and extend survival, with the lncRNA profiling of biological fluids promising the detection of neoplastic changes at their initial stages and more effective therapeutic interventions. This review presents a systematic overview of GBM-associated deregulation of lncRNAs with a focus on lncRNA fingerprints in patients' blood.

Designing a Simple Electrochemical Genosensor for the Detection of Urinary PCA3, a Prostate Cancer Biomarker.

This study investigates the feasibility of a simple electrochemical detection of Prostate Cancer Antigen 3 (PCA3) fragments extracted from patients' urine, using a thiolated single-strand DNA probe immobilized on a gold surface without using a redox probe. To enhance the PCA3 recognition process, we conducted a comparative analysis of the hybridization location using two thiolated DNA probes: Probe 1 targets the first 40 bases, while Probe 2 targets the fragment from bases 47 to 86. Hybridization with PCA3 followed, using square wave voltammetry. The limit of detection of the designed genosenors were of the order of (2.2 ng/mL), and (1.6 ng/mL) for Probes 1 and 2, respectively, and the subsequent sensitivities were of the order of (0.09 ± 0.01) µA-1 · µg-1 · mL and (0.10 ± 0.01) µA-1 · µg-1 · mL. Specificity tests were then conducted with the sensor functionalized with Probe 2, as it presents better analytical performances. The electrochemical results indicate that the designed sensor can clearly discriminate a complementary target from a non-complementary one. A further modeling of the calibration curves with the Power Law/Hill model indicates that the dissociation constant increases by one order of magnitude, confirming the ability of the designed sensor to perfectly discriminate complementary targets from non-complementary ones.

A Novel High-Precision Railway Obstacle Detection Algorithm Based on 3D LiDAR.

This article presents a high-precision obstacle detection algorithm using 3D mechanical LiDAR to meet railway safety requirements. To address the potential errors in the point cloud, we propose a calibration method based on projection and a novel rail extraction algorithm that effectively handles terrain variations and preserves the point cloud characteristics of the track area. We address the limitations of the traditional process involving fixed Euclidean thresholds by proposing a modulation function based on directional density variations to adjust the threshold dynamically. Finally, using PCA and local-ICP, we conduct feature analysis and classification of the clustered data to obtain the obstacle clusters. We conducted continuous experiments on the testing site, and the results showed that our system and algorithm achieved an STDR (stable detection rate) of over 95% for obstacles with a size of 15 cm × 15 cm × 15 cm in the range of ±25 m; at the same time, for obstacles of 10 cm × 10 cm × 10 cm, an STDR of over 80% was achieved within a range of ±20 m. This research provides a possible solution and approach for railway security via obstacle detection.

Elderberry Leaves with Antioxidant and Anti-Inflammatory Properties as a Valuable Plant Material for Wound Healing.

Sambuci folium (elderberry leaves) have been used in traditional medicine, mainly externally, to treat skin diseases and wounds. Therefore, the aim of this study was to screen the biological activity of elderberry leaves (antioxidant potential and possibility of inhibition of tyrosinase and hyaluronidase enzymes) combined with phytochemical analysis. For this purpose, a phytochemical analysis was carried out. Elderberry leaves of 12 varieties ("Sampo", "Obelisk", "Dwubarwny", "Haschberg", "Haschberg 1", "Koralowy", "Sambo", "Black Beauty", "Black Tower", "Golden hybrid", "Samyl", "Samyl 1") in two growth stages. The compounds from the selected groups, phenolic acids (chlorogenic acid) and flavonols (quercetin), were chromatographically determined in hydroalcoholic leaf extracts. All tested elderberry leaf extracts showed antioxidant effects, but the most promising potential: very high compounds content (TPC = 61.85 mg GAE/g), antioxidant (e.g., DPPH IC50 = 1.88 mg/mL; CUPRAC IC0.5 = 0.63 mg/mL) and optimal anti-inflammatory (inhibition of hyaluronidase activity 41.28%) activities were indicated for older leaves of the "Sampo" variety. Additionally, the extract obtained from "Sampo" and "Golden hybrid" variety facilitated the treatment of wounds in the scratch test. In summary, the best multidirectional pro-health effect in treating skin inflammation was specified for "Sampo" leaves II extract (leaves during the flowering period); however, wound treatment was noted as rich in chlorogenic acid younger leaf extracts of the "Golden hybrid" variety.

In Silico Discovery and Predictive Modeling of Novel Acetylcholinesterase (AChE) Inhibitors for Alzheimer's Treatment.

INTRODUCTION: Alzheimer's disease, akin to coronary artery disease of the heart, is a progressive brain disorder driven by nerve cell damage. METHOD: This study utilized computational methods to explore 14 anti-acetylcholinesterase (AChE) derivatives (1 ̶ 14) as potential treatments. By scrutinizing their interactions with 11 essential target proteins (AChE, Aß, BChE, GSK-3ß, MAO B, PDE-9, Prion, PSEN-1, sEH, Tau, and TDP-43) and comparing them with established drugs such as donepezil, galantamine, memantine, and rivastigmine, ligand 14 emerged as notable. During molecular dynamics simulations, the protein boasting the strongest bond with the critical 1QTI protein and exceeding drug-likeness criteria also exhibited remarkable stability within the enzyme's pocket across diverse temperatures (300 ̶ 320 K). In addition, we utilized density functional theory (DFT) to compute dipole moments and molecular orbital properties, including assessing the thermodynamic stability of AChE derivatives. RESULT: This finding suggests a welldefined, potentially therapeutic interaction further supported by theoretical and future in vitro and in vivo investigations. CONCLUSION: Ligand 14 thus emerges as a promising candidate in the fight against Alzheimer's disease.

Survey of Physicochemical Variables in Molepo Dam, South Africa, Using Multivariate Analysis.

<b>Background and Objective:</b> Molepo Dam is a small dam with several aquatic animal species. An assessment of the water quality index of Molepo Dam is necessary because it is situated close to a largely rural community. In this study, the physicochemical variables of Molepo Dam were observed to better understand the water quality situation of this dam. <b>Materials and Methods:</b> The study was carried out from October 2022 to March 2023; 126 samples of water were taken from the Molepo Dam. The physicochemical parameters of the water were determined through standard methods. <b>Results:</b> The site within the dam exhibited a clear separation. Site 1, 2 and 4 were found to be more similar to each other, while Site 3 was separated from them. Site 5, 6 and 7 were more similar together as well. The results showed that the pollution level in Site 3 was the lowest. The pollution level in Site 1, 2 and 4 was more similar and the level of pollution in Site 5, 6 and 7 was the highest. <b>Conclusion:</b> According to the study, pollution levels were found to be different in various parts of the Molepo Dam. This was because the wastewater generated by rural communities was predominantly discharged towards the northern part of the dam.

Heavy Metal(oid)s Contamination and Potential Ecological Risk Assessment in Agricultural Soils.

Soil pollution caused by heavy metal(oid)s has generated great concern worldwide due to their toxicity, persistence, and bio-accumulation properties. To assess the baseline data, the heavy metal(oid)s, including manganese (Mn), iron (Fe), Cobalt (Co), nickel (Ni), copper (Cu), zinc (Zn), arsenic (As), lead (Pb), mercury (Hg), chromium (Cr), and cadmium (Cd), were evaluated in surface soil samples collected from the farmlands of Grand Forks County, North Dakota. Samples were digested via acid mixture and analyzed via inductively coupled plasma mass spectrometry (ICP MS) analysis to assess the levels, ecological risks, and possible sources. The heavy metal(oid) median levels exhibited the following decreasing trend: Fe > Mn > Zn > Ni > Cr > Cu > Pb > Co > As > Cd > Hg. Principal component analysis (PCA) and hierarchical cluster analysis (HCA) suggested the main lithogenic source for the studied metal(oid)s. Metal(oid) levels in the current investigation, except Mn, are lower than most of the guideline values set by international agencies. The contamination factor (Cf), geo accumulation index (Igeo) and enrichment factor (EF) showed considerable contamination, moderate contamination, and significant enrichment, respectively, for As and Cd on median value basis. Ecological risk factor (Er) results exhibited low ecological risk for all studied metal(oid)s except Cd, which showed considerable ecological risk. The potential ecological risk index (PERI) levels indicated low ecological risk to considerable risk. Overall, the results indicate the accumulation of As and Cd in the study area. The high nutrients of the soils potentially affect their accumulation in crops and impact on consumers' health. This drives the impetus for continued environmental monitoring programs.

A framework for performance enhancement of classifiers in detection of prostate cancer from microarray gene.

Prostate cancer is a major world health problem for men. This shows how important early detection and accurate diagnosis are for better treatment and patient outcomes. This study compares different ways to find Prostate Cancer (PCa) and label tumors as normal or abnormal, with the goal of speeding up current work in microarray gene data analysis. The study looks at how well several feature extraction methods work with three feature selection strategies: Harmonic Search (HS), Firefly Algorithm (FA), and Elephant Herding Optimization (EHO). The techniques tested are Expectation Maximization (EM), Nonlinear Regression (NLR), K-means, Principal Component Analysis (PCA), and Discrete Cosine Transform (DCT). Eight classifiers are used for the task of classification. These are Random Forest, Decision Tree, Adaboost, XGBoost, and Support Vector Machine (SVM) with linear, polynomial, and radial basis function kernels. This study looks at how well these classifiers work with and without feature selection methods. It finds that the SVM with radial basis function kernel, using DCT for feature extraction and EHO for feature selection, does the best of all of them, with an accuracy of 94.8 % and an error rate of 5.15 %.

Multivariate analysis applied to X-ray fluorescence to assess soil contamination pathways: case studies of mass magnetic susceptibility in soils near abandoned coal and W/Sn mines.

Determining the origin and pathways of contaminants in the natural environment is key to informing any mitigation process. The mass magnetic susceptibility of soils allows a rapid method to measure the concentration of magnetic minerals, derived from anthropogenic activities such as mining or industrial processes, i.e., smelting metals (technogenic origin), or from the local bedrock (of geogenic origin). This is especially effective when combined with rapid geochemical analyses of soils. The use of multivariate analysis (MVA) elucidates complex multiple-component relationships between soil geochemistry and magnetic susceptibility. In the case of soil mining sites, X-ray fluorescence (XRF) spectroscopic data of soils contaminated by mine waste shows statistically significant relationships between magnetic susceptibility and some base metal species (e.g., Fe, Pb, Zn, etc.). Here, we show how qualitative and quantitative MVA methodologies can be used to assess soil contamination pathways using mass magnetic susceptibility and XRF spectra of soils near abandoned coal and W/Sn mines (NW Portugal). Principal component analysis (PCA) showed how the first two primary components (PC-1 + PC-2) explained 94% of the sample variability, grouped them according to their geochemistry and magnetic susceptibility in to geogenic and technogenic groups. Regression analyses showed a strong positive correlation (R2 > 0.95) between soil geochemistry and magnetic properties at the local scale. These parameters provided an insight into the multi-element variables that control magnetic susceptibility and indicated the possibility of efficient assessment of potentially contaminated sites through mass-specific soil magnetism.

A Semiquantitative Protein-Fragment Complementation Assay to Study Protein-Protein Interactions of the Polymerase Complex in Cellula.

Protein-fragment complementation assays (PCAs) are powerful tools to investigate protein-protein interactions in a cellular context. These are especially useful to study unstable proteins and weak interactions that may not resist protein isolation or purification. The PCA based on the reconstitution of the Gaussia princeps luciferase (split-luc) is a sensitive approach allowing the mapping of protein-protein interactions and the semiquantitative measurement of binding affinity. Here, we describe the split-luc protocol we used to map the viral interactome of measles virus polymerase complex.

Brevilin A Inhibits Prostate Cancer Progression by Decreasing PAX5-Activated SOX4.

Brevilin A possesses inhibitory effects on the development of prostate cancer (PCa); however, the underlying mechanism remains unclear. The present work aims to analyze how Brevilin A regulates PCa cell malignancy. RNA expression of paired box 5 (PAX5) and SRY-box transcription factor 4 (SOX4) was analyzed by quantitative real-time polymerase chain reaction. Protein expression of PAX5, SOX4, and nuclear proliferation marker (Ki67) was detected by western blotting or immunohistochemistry assay. The viability, proliferation, apoptosis, and migratory and invasive abilities of PCa cells were investigated by cell counting kit-8 (CCK-8), 5-Ethynyl-2'-deoxyuridine (EdU), flow cytometry, and transwell assays, respectively. The association between PAX5 and SOX4 was identified by dual-luciferase reporter assay and chromatin immunoprecipitation assay. Xenograft mouse model assay was used to reveal the effect of Brevilin A on tumor tumorigenesis in vivo. PAX5 and SOX4 expression were upregulated in PCa tissues and cells relative to normal prostate tissues and human prostate epithelial cells. Brevilin A treatment inhibited PAX5 protein expression in PCa cells. Additionally, Brevilin A inhibited proliferation, migration and invasion and induced apoptosis of PCa cells, whereas these effects were attenuated after PAX5 overexpression. SOX4 was transcriptionally activated by PAX5, and its introduction partially relieved the inhibitory effects of PAX5 knockdown on PCa cell malignancy. Moreover, Brevilin A delayed tumor formation in vivo. Brevilin A inhibited PCa progression by regulating SOX4 expression in a PAX5-dependent manner, providing a promising anti-tumor drug for PCa.

Abiraterone-Induced Secondary Hypertension: Two Wrongs Don't Make a Right.

Abiraterone, an inhibitor of both 17α-hydroxylase and 17,20-lyase, is considered a novel, state-of-the-art, life-prolonging therapy in the urologists' arsenal when treating prostate cancer. Despite its efficacy, it is linked with an increased risk of cardiovascular adverse effects. Herein, we report a case in which the administration of abiraterone resulted in a full-blown syndrome of apparent mineralocorticoid excess despite the concomitant administration of prednisolone; that is, secondary hypertension, hypokalemia, metabolic alkalosis, as well as elevated levels of adrenocorticotropic hormone (ACTH).

High performance liquid chromatography (HPLC) based genetic diversity profiling of chilli germplasm for fruit pungency and phytochemical contents.

Chilli peppers are widely consumed for their pungency, as used in flavoring the food and has many pharmaceutical and medicinal properties. Based on these properties an experiment was held using 83 varieties of chilli (Hot pepper and sweet pepper) were grown in suitable environment using Augment Block design and evaluated for fruit pungency and phytochemical contents using high proficiency liquid chromatography. Analysis of variance (ANOVA) of traits showed highly significant for all traits except for fruit length and capsaicin contents. The value of Least significant increase (LSI)was ranged 0.27-1289.9 for all traits showed high variation among varieties. Highly significant correlation was found among fruit diameter to fruit weight 0.98, while moderate to high correlation was present among all traits. The most pungent genotype 24,634 was 4.8 g in weight, while the least pungent genotypes i.e. PPE-311 (32.8 g), green wonder (40.67) had higher in weight. The genotypes 24,627, 32,344, 32,368 and 1108 marked as higher number of seeds in their placental region. It was observed that chilli genotype 24,621 had maximum length with considerable high amount of pungency act as novel cultivar. Principal component analysis (PCA) showed the high variability of 46.97 for two PCs with the eigen value 2.6 and 1.63 was recorded. Biplot analysis showed a considerable variability for fruit pungency, while huge variability was found for all traits among given varieties. PPE-311, T5 and T3 are found as highly divergent for all traits. The findings of this study are instrumental for selecting parents to improve desirable traits in future chilli pepper breeding programs. It will help plant/vegetable breeders for development of highly nutrient and pungent varieties and attractive for the consumer of food sector.

Effects of small extracellular vesicles derived from normoxia- and hypoxia-treated prostate cancer cells on the submandibular salivary gland epithelium in vitro.

Small extracellular vesicles (sEVs) are an important part of intercellular communication. They are phospholipid bilayer particles that carry active biomolecules such as proteins, various nucleic acids, and lipids. In recipient cells, sEVs can alter cellular functions, including cancer development and premetastatic niche formation in distant organs. Moreover, sEVs can carry cancer-specific features, which makes them promising biomarker candidates. However, the interactions of sEVs with biological barriers and consequences thereof, are not clarified yet. The blood-saliva barrier is crucial for preventing the entry of pathogens and (in)organic substances into the bloodstream, as well as molecule filtration from blood to saliva. The effects of brain derived DU145 prostate cancer (PCa) sEVs on a human submandibular salivary gland barrier (SSGB) in vitro were investigated. Small EVs were harvested from normoxic (N, atmospheric O2) or hypoxic (H, 1% O2) conditions, fluorescently labeled with CellTrackerTM Orange and thoroughly characterized. HTB-41 B2 cells were used as SSGB model cultured on 24-well ThinCert® inserts. After model optimization indicating effects of serum and serum-sEVs on barrier properties, PCa sEVs were applied to the basolateral (blood) side in either 10% serum, or serum-free conditions, and barrier integrity was continuously monitored for 40 hours. This study found that H and N PCa sEVs were uptaken by the SSGB in vitro model in similar quantities regardless of the media composition in the basolateral compartment. Permeation of fluorescent PCa sEVs into the apical compartment was not detectable with the applied methods. However, treatment with H and N sEVs under different serum conditions revealed distinct molecular clusters after hierarchical analysis of mRNA data measured by high-throughput qPCR, which were partly reflected at the protein level. For example, serum-reduction dependent decrease of barrier properties was accompanied with the decrease of CDH1 or Claudin-7 expression. Interestingly, the presence of H sEVs significantly increased the number of sEV-sized particles in the apical compartment of the SSGB model compared to basolaterally added N sEVs. This functional effect on the number of particles in the saliva (apical) compartment induced by different sEVs applied in the blood (basolateral) compartment might be a new approach to understand one possible mechanism how differences of salivary EVs might occur which then could be used as biomarker.