Biology subjects

Machado, R.

Publications and source records attributed to Machado, R..

5 recordsLinked to original sources

bioRxiv2025

Partial Wwox Loss of Function Increases Severity of Murine Sepsis and Neuroinflammation

RationaleWW domain-containing oxidoreductase (WWOX) is a gene associated implicated in both neurologic and inflammatory diseases and is susceptible to environmental stressors. We hypothesize partial loss of Wwox function will result in increased sepsis severity and neuroinflammation. MethodsWwox WT/P47T mice, generated by CRISPR/Cas9, and Wwox WT/WT mice were treated with intraperitoneal PBS vs LPS (10mg/kg) and euthanized 12 hours post-injection. Open Field Testing (OFT) and Murine Sepsis Severity Scores (MSS) were utilized to measure sickness behavior and sepsis severity, respectively. Brain tissue was analyzed using immunohistochemistry and PCR to measure neuroinflammation and apoptosis. ResultsWwox WT/P47T LPS mice demonstrated a more significant response to sepsis with an increase in sickness behavior, sepsis severity, gliosis, and apoptosis compared to Wwow WT/WT LPS littermates. ConclusionsPartial loss of Wwox function increases risk for severe sepsis and neuroinflammation. Given the susceptibility of WWOX to environmental stressors, this may be a target for future therapeutic interventions.

neuroscience↗

bioRxiv2020

Flexible multiplane structured illumination microscope with a four-camera detector

Fluorescence microscopy provides an unparalleled tool for imaging biological samples. However, producing high-quality volumetric images quickly and without excessive complexity remains a challenge. Here, we demonstrate a simple multi-camera structured illumination microscope (SIM) capable of simultaneously imaging multiple focal planes, allowing for the capture of 3D fluorescent images without any axial movement of the sample. This simple setup allows for the rapid acquisition of many different 3D imaging modes, including 3D time lapses, high-axial-resolution 3D images, and large 3D mosaics.

biophysics↗

bioRxiv2020

Fluorescence Microscopy Datasets for Training Deep Neural Networks

BackgroundFluorescence microscopy is an important technique in many areas of biological research. Two factors which limit the usefulness and performance of fluorescence microscopy are photobleaching of fluorescent probes during imaging, and, when imaging live cells, phototoxicity caused by light exposure. Recently developed methods in machine learning are able to greatly improve the signal to noise ratio of acquired images. This allows researchers to record images with much shorter exposure times, which in turn minimizes photobleaching and phototoxicity by reducing the dose of light reaching the sample. FindingsTo employ deep learning methods, a large amount of data is needed to train the underlying convolutional neural network. One way to do this involves use of pairs of fluorescence microscopy images acquired with long and short exposure times. We provide high quality data sets which can be used to train and evaluate deep learning methods under development. ConclusionThe availability of high quality data is vital for training convolutional neural networks which are used in current machine learning approaches.

bioinformatics↗

bioRxiv2019

Imaging Membrane Curvature inside a Model Immunological Synapse in RBL-2H3 Cells using TIRF Microscopy with Polarized Excitation

Total internal reflection fluorescence microscopy with polarized excitation (P-TIRF) can be used to image nanoscale curvature phenomena in live cells. We used P-TIRF to visualize rat basophilic leukemia cells (RBL-2H3 cells) coming into contact with a supported lipid bilayer, modeling an immunological synapse. These studies help correlate the dynamics of cell surface molecules with the mechanical properties of the plasma membrane during synapse formation.

biophysics↗

bioRxiv2018

Detection of HPV16, HPV18, p16, and E6/E7 MRNA in Nasopharyngeal Cancer: A Systematic Review and Meta-Analysis

IntroductionHuman Papilloma Virus (HPV) associated head and neck cancers, particularly oropharyngeal cancers (OPC), have a superior prognosis to HPV negative cancers. A literature review did not find any studies that analyzed HPV 16, HPV 18 DNA and p16 in the nasopharynx subsite, although it has been reported in the oropharynx. The detection of HPV DNA and p16 in the nasopharynx could have implications for the treatment of NPC. To date no one has reported the detection or concordance rates of HPV associated markers in nasopharyngeal carcinoma (NPC).\n\nMethodsA literature search was undertaken on Medline, EMBASE, Scopus, and the Cochrane Library to identify studies that used PCR and ISH for detection of HPV DNA and p16 in the nasopharynx. We included studies published between 1992 and 2017 that reported the prognostic impact of HPV DNA and/or p16, treated HPV and p16 as categorical variables with at least 10 patients who tested for p16 and/or HPV16/HPV18 DNA in NPC, irrespective of HPV status. We then collected information from many parameters, and performed a meta-analysis to produce pooled prevalence estimates and explored sources of heterogeneity\n\nResults21 studies published between 1992 and 2017 were selected for meta-analysis, with sample sizes ranging from 10 to 1328. The total (random effects) pooled detection of any HPV marker in NPC patients was 19.7% (95% CI: 12.56 to 28.00). The total (random effects) pooled detection of p16 positivity in NPC patients was 23.98% (95% CI: 14.82 to 34.54). The total (random effects) pooled detection of HPV DNA in NPC patients, detected by ISH, was 14.43% (95% CI: 10.13 to 19.33) and for HPV DNA in NPC patients including E6/E7 was 18.13% (95% CI: 11.45 to 25.94). The total (random effects) pooled detection of HPV DNA in NPC patients was 18.13% (95% CI: 11.45 to 25.94). The total (random effects) pooled detection of EBV positivity in NPC patients was 76.21% (95% CI: 66.40 to 84.80). Heterogeneity was high for all of the results. The attributable fraction of p16+ and HPV DNA+ in NPC is 0.029. The attributable fraction of EBV positive and HPV - in NPC is 0.827. The attributable fraction of EBV negative and HPV - in NPC is 0.0639. The attributable fraction of EBV negative and HPV + in NPC is 0.085. The attributable fraction of EBV positive and HPV + in NPC is 0.023. The attributable fraction of HPV positive and mRNA+ in NPC was 0.115. The attributable fraction of p16 in NPC was 0.123.\n\nDiscussionThis is the first study that contributes to the concordance and detection rates of HPV related markers in NPC.\n\nLimitationsMost of the studies included were of Asian extraction. Most of the papers also did not test for E6/E7 RNA and therefore we are unsure of the amount of active E6/E7 RNA in NPC.

cancer biology↗