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Scientific Reports Jun 2024Circulating leukocytes enter tissue either through endothelial junctions (paracellular) or via a pore through the body of endothelial cells (transcellular). We have...
Circulating leukocytes enter tissue either through endothelial junctions (paracellular) or via a pore through the body of endothelial cells (transcellular). We have previously shown that genetically replacing VE-cadherin with a VE-cadherin-α-catenin (VEC-αC) fusion construct-which binds constitutively to actin-obstructs junctions, and blocks leukocyte extravasation in lung, skin and postcapillary venules of cremaster muscle. However, neutrophil recruitment into the inflamed peritoneal cavity was unimpaired. Investigating reasons for this, here, we visualized neutrophil diapedesis by 3D intravital video microscopy in the cremaster muscle and omentum, the major site of neutrophil recruitment into the peritoneal cavity. We found that 80% of neutrophil-extravasation occurred through HEVs in the omentum, which was unimpaired by VEC-αC. In addition, in larger venules (60-85 µm) of both tissues, less than 15% of neutrophils extravasated transcellularly in WT mice. However, in VEC-α-C mice, transcellular diapedesis increased severalfold in the omentum, but not in the cremaster. In line with this, omental venules expressed higher levels of ICAM-1 and atypical chemokine receptor 1. Furthermore, only in the omentum, VEC-αC expression caused reduced elongation of venular endothelium in flow-direction, suggesting different biomechanical properties. Collectively, VEC-αC does not inhibit paracellular transmigration in all types of venules and can modulate the diapedesis route.
Topics: Animals; Neutrophils; Mice; Transendothelial and Transepithelial Migration; Omentum; Cadherins; Venules; Intercellular Adhesion Molecule-1; Endothelial Cells; Antigens, CD; Neutrophil Infiltration; Mice, Inbred C57BL; Transcellular Cell Migration
PubMed: 38914623
DOI: 10.1038/s41598-024-65173-3 -
Journal of Applied Biomedicine Jun 2024In 2020, there were numerous cases in Kazakhstan with clinical symptoms of COVID-19 but negative PCR results in nasopharyngeal and oropharyngeal swabs. The diagnosis was...
In 2020, there were numerous cases in Kazakhstan with clinical symptoms of COVID-19 but negative PCR results in nasopharyngeal and oropharyngeal swabs. The diagnosis was confirmed clinically and by CT scans (computed tomography). The problem with such negative PCR results for SARS-CoV-2 infection confirmation still exists and indicates the need to confirm the diagnosis in the bronchoalveolar lavage in such cases. There is also a lack of information about confirmation of SARS-CoV-2 infection in deceased patients. In this study, various tissue materials, including lungs, bronchi, and trachea, were examined from eight patients who died, presumably from SARS-CoV-2 infection, between 2020 and 2022. Naso/oropharyngeal swabs taken from these patients in hospitals tested PCR negative for SARS-CoV-2. This study presents a modified RNA isolation method based on a comparison of the most used methods for RNA isolation in laboratories: QIAamp Viral RNA Mini Kit and TRIzol-based method. This modified nucleic acid extraction protocol can be used to confirm SARS-CoV-2 infection by RT-qPCR in the tissues of deceased patients in disputed cases. RT-qPCR with RNA of SARS-CoV-2 re-extracted with such method from post-mortem tissues that were stored at -80 °C for more than 32 months still demonstrated high-yielding positive results.
Topics: Humans; COVID-19; SARS-CoV-2; RNA, Viral; Male; Autopsy; Real-Time Polymerase Chain Reaction; Female; Lung; Middle Aged; Aged; COVID-19 Nucleic Acid Testing; Trachea; Adult; Nasopharynx
PubMed: 38912867
DOI: 10.32725/jab.2024.013 -
Acta Oncologica (Stockholm, Sweden) Jun 2024The delineation of intraprostatic lesions is vital for correct delivery of focal radiotherapy boost in patients with prostate cancer (PC). Errors in the delineation... (Comparative Study)
Comparative Study
BACKGROUND
The delineation of intraprostatic lesions is vital for correct delivery of focal radiotherapy boost in patients with prostate cancer (PC). Errors in the delineation could translate into reduced tumour control and potentially increase the side effects. The purpose of this study is to compare PET-based delineation methods with histopathology.
MATERIALS AND METHODS
The study population consisted of 15 patients with confirmed high-risk PC intended for prostatectomy. [68Ga]-PSMA-PET/MR was performed prior to surgery. Prostate lesions identified in histopathology were transferred to the in vivo [68Ga]-PSMA-PET/MR coordinate system. Four radiation oncologists manually delineated intraprostatic lesions based on PET data. Various semi-automatic segmentation methods were employed, including absolute and relative thresholds, adaptive threshold, and multi-level Otsu threshold.
RESULTS
The gross tumour volumes (GTVs) delineated by the oncologists showed a moderate level of interobserver agreement with Dice similarity coefficient (DSC) of 0.68. In comparison with histopathology, manual delineations exhibited the highest median DSC and the lowest false discovery rate (FDR) among all approaches. Among semi-automatic approaches, GTVs generated using standardized uptake value (SUV) thresholds above 4 (SUV > 4) demonstrated the highest median DSC (0.41), with 0.51 median lesion coverage ratio, FDR of 0.66 and the 95th percentile of the Hausdorff distance (HD95%) of 8.22 mm.
INTERPRETATION
Manual delineations showed a moderate level of interobserver agreement. Compared to histopathology, manual delineations and SUV > 4 exhibited the highest DSC and the lowest HD95% values. The methods that resulted in a high lesion coverage were associated with a large overestimation of the size of the lesions.
Topics: Humans; Male; Prostatic Neoplasms; Gallium Radioisotopes; Tumor Burden; Gallium Isotopes; Positron-Emission Tomography; Aged; Prostatectomy; Middle Aged; Radiopharmaceuticals; Oligopeptides; Magnetic Resonance Imaging; Edetic Acid
PubMed: 38912830
DOI: 10.2340/1651-226X.2024.39041 -
JCI Insight May 2024Immune therapy is the new frontier of cancer treatment. Therapeutic radiation is a known inducer of immune response and can be limited by immunosuppressive mediators...
Immune therapy is the new frontier of cancer treatment. Therapeutic radiation is a known inducer of immune response and can be limited by immunosuppressive mediators including cyclooxygenase-2 (COX2) that is highly expressed in aggressive triple negative breast cancer (TNBC). A clinical cohort of TNBC tumors revealed poor radiation therapeutic efficacy in tumors expressing high COX2. Herein, we show that radiation combined with adjuvant NSAID (indomethacin) treatment provides a powerful combination to reduce both primary tumor growth and lung metastasis in aggressive 4T1 TNBC tumors, which occurs in part through increased antitumor immune response. Spatial immunological changes including augmented lymphoid infiltration into the tumor epithelium and locally increased cGAS/STING1 and type I IFN gene expression were observed in radiation-indomethacin-treated 4T1 tumors. Thus, radiation and adjuvant NSAID treatment shifts "immune desert phenotypes" toward antitumor M1/TH1 immune mediators in these immunologically challenging tumors. Importantly, radiation-indomethacin combination treatment improved local control of the primary lesion, reduced metastatic burden, and increased median survival when compared with radiation treatment alone. These results show that clinically available NSAIDs can improve radiation therapeutic efficacy through increased antitumor immune response and augmented local generation of cGAS/STING1 and type I IFNs.
Topics: Animals; Membrane Proteins; Mice; Female; Signal Transduction; T-Lymphocytes, Cytotoxic; Triple Negative Breast Neoplasms; Indomethacin; Cell Line, Tumor; Humans; Lung Neoplasms; Cyclooxygenase Inhibitors; Nucleotidyltransferases; Interferon Type I; Cyclooxygenase 2; Lymphocytes, Tumor-Infiltrating; Mice, Inbred BALB C
PubMed: 38912586
DOI: 10.1172/jci.insight.165356 -
Heliyon Jun 2024Renal calculi (RC) represent a prevalent disease of the urinary system characterized by a high incidence rate. The traditional clinical diagnosis of RC emphasizes...
Renal calculi (RC) represent a prevalent disease of the urinary system characterized by a high incidence rate. The traditional clinical diagnosis of RC emphasizes imaging and stone composition analysis. However, the significance of metabolic status in RC diagnosis and prevention remains unclear. This study aimed to investigate serum metabolites in RC patients to identify those associated with RC and to develop a metabolite-based diagnostic model. We employed nontargeted metabolomics utilizing ultra-performance liquid chromatography‒mass spectrometry (UPLC‒MS) to compare serum metabolites between RC patients and healthy controls. Our findings demonstrated significant disparities in serum metabolites, particularly in fatty acids and glycerophospholipids, between the two groups. Notably, the glycerophospholipid (GP) metabolic pathway in RC patients was significantly disrupted. Logistic regression models using differentially abundant metabolites revealed that elevated levels of 2-butyl-4-methyl phenol and reduced levels of phosphatidylethanolamine (P-16:0/22:6(4Z,7Z,10Z,13Z,16Z,19Z)) had the most substantial effect on RC risk. Overall, our study indicates that RC induces notable alterations in serum metabolites and that the diagnostic model based on these metabolites effectively distinguishes RC. This research offers promising insights and directions for further diagnostic and mechanistic studies on RC.
PubMed: 38912451
DOI: 10.1016/j.heliyon.2024.e32482 -
Precision Clinical Medicine Jun 2024The prognosis of breast cancer is often unfavorable, emphasizing the need for early metastasis risk detection and accurate treatment predictions. This study aimed to...
BACKGROUND
The prognosis of breast cancer is often unfavorable, emphasizing the need for early metastasis risk detection and accurate treatment predictions. This study aimed to develop a novel multi-modal deep learning model using preoperative data to predict disease-free survival (DFS).
METHODS
We retrospectively collected pathology imaging, molecular and clinical data from The Cancer Genome Atlas and one independent institution in China. We developed a novel Deep Learning Clinical Medicine Based Pathological Gene Multi-modal (DeepClinMed-PGM) model for DFS prediction, integrating clinicopathological data with molecular insights. The patients included the training cohort ( = 741), internal validation cohort ( = 184), and external testing cohort ( = 95).
RESULT
Integrating multi-modal data into the DeepClinMed-PGM model significantly improved area under the receiver operating characteristic curve (AUC) values. In the training cohort, AUC values for 1-, 3-, and 5-year DFS predictions increased to 0.979, 0.957, and 0.871, while in the external testing cohort, the values reached 0.851, 0.878, and 0.938 for 1-, 2-, and 3-year DFS predictions, respectively. The DeepClinMed-PGM's robust discriminative capabilities were consistently evident across various cohorts, including the training cohort [hazard ratio (HR) 0.027, 95% confidence interval (CI) 0.0016-0.046, < 0.0001], the internal validation cohort (HR 0.117, 95% CI 0.041-0.334, < 0.0001), and the external cohort (HR 0.061, 95% CI 0.017-0.218, < 0.0001). Additionally, the DeepClinMed-PGM model demonstrated C-index values of 0.925, 0.823, and 0.864 within the three cohorts, respectively.
CONCLUSION
This study introduces an approach to breast cancer prognosis, integrating imaging and molecular and clinical data for enhanced predictive accuracy, offering promise for personalized treatment strategies.
PubMed: 38912415
DOI: 10.1093/pcmedi/pbae012 -
ACS Nanoscience Au Jun 2024Gold nanoparticles (AuNPs) are a promising platform for biomedical applications including therapeutics, imaging, and drug delivery. While much of the literature...
Gold nanoparticles (AuNPs) are a promising platform for biomedical applications including therapeutics, imaging, and drug delivery. While much of the literature surrounding the introduction of AuNPs into cellular systems focuses on uptake and cytotoxicity, less is understood about how AuNPs can indirectly affect cells via interactions with the extracellular environment. Previous work has shown that the monocytic cell line THP-1's ability to undergo chemotaxis in response to a gradient of monocyte chemoattractant protein 1 (MCP-1) was compromised by extracellular polysulfonated AuNPs, presumably by binding to MCP-1 with some preference over other proteins in the media. The hypothesis to be explored in this work is that the degree of sulfonation of the surface would therefore be correlated with the ability of AuNPs to interrupt chemotaxis. Highly sulfonated poly(styrenesulfonate)-coated AuNPs caused strong inhibition of THP-1 chemotaxis; by reducing the degree of sulfonation on the AuNP surface with copolymers [poly(styrenesulfonate--maleate) of different compositions], it was found that medium and low sulfonation levels caused weak to no inhibition, respectively. Small, rigid molecular sulfonate surfaces were relatively ineffective at chemotaxis inhibition. Unusually, free poly(styrenesulfonate) caused a dose-dependent reversal of THP-1 cell migration: at low concentrations, free poly(styrenesulfonate) significantly inhibited MCP-1-induced chemotaxis. However, at high concentrations, free poly(styrenesulfonate) acted as a chemorepellent, causing a reversal in the cell migration direction.
PubMed: 38912285
DOI: 10.1021/acsnanoscienceau.3c00055 -
Frontiers in Oncology 2024Cyclin-dependent kinase 4/6 inhibitors (CDK4/6i) represent the gold standard of the hormone receptor positive human epidermal growth factor receptor 2 (HER-2) negative...
BACKGROUND
Cyclin-dependent kinase 4/6 inhibitors (CDK4/6i) represent the gold standard of the hormone receptor positive human epidermal growth factor receptor 2 (HER-2) negative advanced breast cancer. However, optimal treatment after disease progression is a matter of debate. We aimed to assess predictive and prognostic factors associated with the treatment outcome following CDK4/6i progression.
METHODS
We retrospectively analyzed patients who progressed on CDK4/6i treatment between 2018 and 2024. Treatment based on molecular findings (PIK3CA mutation), genetic findings (BRCA1/2 germline mutation), or adapted to the change in the tumor phenotype in rebiopsy (anti-HER2 therapy in the transformation to HER-2-positive disease) was grouped into tailored treatment and compared to the endocrine-based therapy and chemotherapy alone.
RESULTS
Five hundred twelve patients were treated with CDK4/6i. Two hundred patients with disease progression were enrolled in the study. Duration of response to CDK4/6i was not predictive of the response to subsequent treatment, whereas the progression in the central nervous system was the worst prognostic factor. Thirty patients were ineligible for subsequent treatment. Survival after CDK4/6i progression was significantly longer in patients eligible for tailored treatment. The median PFS in patients with tailored treatment (n=19) was 13.5 months vs. 4.9 months in patients with non-tailored therapy (n=151; p=0.045). 12-month PFS was 54.1% with tailored treatment [95% CI 24.1-76.7%] compared to 18.5% with non-tailored therapy [95% CI 11.6-26.6%]. The median OS for patients treated with a tailored approach was not reached compared to 11.5 months with non-tailored treatment (p=0.016). The 24-month OS for patients treated with a tailored approach was 80.2% [95% CI 40.3-94.8%] compared to 21.1% [95% CI 12.2-31.7%] for patients with non-tailored treatment.
CONCLUSIONS
Tailoring of subsequent treatment strategy seems to be essential for achieving long-term benefit. Further studies are required, as the prognosis after CDK4/6i progression remains dismal, especially in cases affecting the central nervous system.
PubMed: 38912058
DOI: 10.3389/fonc.2024.1408664 -
Open Forum Infectious Diseases Jun 2024Understanding changes in diagnostic performance after symptom onset and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) exposure within different...
Performance of and Severe Acute Respiratory Syndrome Coronavirus 2 Diagnostics Based on Symptom Onset and Close Contact Exposure: An Analysis From the Test Us at Home Prospective Cohort Study.
BACKGROUND
Understanding changes in diagnostic performance after symptom onset and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) exposure within different populations is crucial to guide the use of diagnostics for SARS-CoV-2.
METHODS
The Test Us at Home study was a longitudinal cohort study that enrolled individuals across the United States between October 2021 and February 2022. Participants performed paired antigen-detection rapid diagnostic tests (Ag-RDTs) and reverse-transcriptase polymerase chain reaction (RT-PCR) tests at home every 48 hours for 15 days and self-reported symptoms and known coronavirus disease 2019 exposures immediately before testing. The percent positivity for Ag-RDTs and RT-PCR tests was calculated each day after symptom onset and exposure and stratified by vaccination status, variant, age category, and sex.
RESULTS
The highest percent positivity occurred 2 days after symptom onset (RT-PCR, 91.2%; Ag-RDT, 71.1%) and 6 days after exposure (RT-PCR, 91.8%; Ag-RDT, 86.2%). RT-PCR and Ag-RDT performance did not differ by vaccination status, variant, age category, or sex. The percent positivity for Ag-RDTs was lower among exposed, asymptomatic than among symptomatic individuals (37.5% (95% confidence interval [CI], 13.7%-69.4%) vs 90.3% (75.1%-96.7%). Cumulatively, Ag-RDTs detected 84.9% (95% CI, 78.2%-89.8%) of infections within 4 days of symptom onset. For exposed participants, Ag-RDTs detected 94.0% (95% CI, 86.7%-97.4%) of RT-PCR-confirmed infections within 6 days of exposure.
CONCLUSIONS
The percent positivity for Ag-RDTs and RT-PCR tests was highest 2 days after symptom onset and 6 days after exposure, and performance increased with serial testing. The percent positivity of Ag-RDTs was lowest among asymptomatic individuals but did not differ by sex, variant, vaccination status, or age category.
PubMed: 38911947
DOI: 10.1093/ofid/ofae304 -
Journal of Cancer 2024Triple-negative breast cancer (TNBC) poses significant diagnostic challenges due to its aggressive nature. This research develops an innovative deep learning (DL) model...
Triple-negative breast cancer (TNBC) poses significant diagnostic challenges due to its aggressive nature. This research develops an innovative deep learning (DL) model based on the latest multi-omics data to enhance the accuracy of TNBC subtype and prognosis prediction. The study focuses on addressing the constraints of prior studies by showcasing a model with substantial advancements in data integration, statistical performance, and algorithmic optimization. Breast cancer-related molecular characteristic data, including mRNA, miRNA, gene mutations, DNA methylation, and magnetic resonance imaging (MRI) images, were retrieved from the TCGA and TCIA databases. This study not only compared single-omics with multi-omics machine learning models but also applied Bayesian optimization to innovatively optimize the neural network structure of a DL model for multi-omics data. The DL model for multi-omics data significantly outperformed single-omics models in subtype prediction, achieving a 98.0% accuracy in cross-validation, 97.0% in the validation set, and 91.0% in an external test set. Additionally, the MRI radiomics model showed promising performance, especially with the training set; however, a decrease in performance during transfer testing underscored the advantages of the DL model for multi-omics data in data consistency and digital processing. Our multi-omics DL model presents notable innovations in statistical performance and transfer learning capability, bearing significant clinical relevance for TNBC classification and prognosis prediction. While the MRI radiomics model proved effective, it requires further optimization for cross-dataset application to enhance accuracy and consistency. Our findings offer new insights into improving TNBC classification and prognosis through multi-omics data and DL algorithms.
PubMed: 38911381
DOI: 10.7150/jca.93215