Translating daily COVID-19 screening into a simple glucose test: a proof of concept study.
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ABSTRACT:
SUBMITTER: Liu R
PROVIDER: S-EPMC8261732 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundReliable detection of slowed vertical saccades may help discriminate progressive supranuclear palsy (PSP) from the subset of Parkinson’s disease patients who lack tremor (akinetic-rigid or PD-postural instability and gait disorder PIGD subtype), and from age-related oculomotor changes. We investigated the feasibility of a camera-less computerized behavioral saccade latency paradigm previously validated in PD to discriminate probable PSP-Richardson syndrome (PSP-RS) from PD-PIGD and age-matched controls.MethodsIn this proof-of-concept case-control study, reflexive saccade latencies were measured in 5 subjects with probable PSP-RS, 5 subjects with PD-PIGD subtype, and 5 age-matched controls using the behavioral paradigm. The battery was repeated approximately one month later. All subjects were examined off levodopa by a movement disorders neurologist and by an ophthalmologist, who also performed a dilated eye exam.ResultsVertical prosaccade latencies were longer in the PSP group (median?=?903?ms) relative to PD (median?=?268?ms) and control groups (median?=?235?ms), with no overlap between groups (100% accuracy). PSP subjects also had larger vertical-horizontal discrepancies than comparison groups. Test-retest reliability for the behavioral saccade measures was good (interclass correlation coefficient?=?0.948; 95% confidence interval [0.856, 0.982]), and the measures strongly correlated with clinical ratings.ConclusionsComputerized behavioral measurement of reflexive saccade latency is feasible in PSP, and potentially discriminates probable PSP-RS from the PD-PIGD subtype. Findings from this proof-of-concept study support utility of the approach for obtaining objective saccade metrics in clinical evaluations and for tracking change in future, larger trials of moderately advanced PSP. Future studies should also examine the behavioral paradigm in earlier presentations of PSP and other subtypes of PSP.
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Project description:Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted in an unprecedented need for diagnostic testing that is critical in controlling the spread of COVID-19. We propose a portable infrared spectrometer with purpose-built transflection accessory for rapid point-of-care detection of COVID-19 markers in saliva. Initially, purified virion particles were characterized with Raman spectroscopy, synchrotron infrared (IR) and AFM-IR. A data set comprising 171 transflection infrared spectra from 29 subjects testing positive for SARS-CoV-2 by RT-qPCR and 28 testing negative, was modeled using Monte Carlo Double Cross Validation with 50 randomized test and model sets. The testing sensitivity was 93 % (27/29) with a specificity of 82 % (23/28) that included positive samples on the limit of detection for RT-qPCR. Herein, we demonstrate a proof-of-concept high throughput infrared COVID-19 test that is rapid, inexpensive, portable and utilizes sample self-collection thus minimizing the risk to healthcare workers and ideally suited to mass screening.
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Project description:The reverse transcription-polymerase chain reaction (RT-PCR) assay is the accepted standard for coronavirus disease 2019 (COVID-19) diagnosis. As any test, RT-PCR provides false negative results that can be rectified by clinicians by confronting clinical, biological and imaging data. The combination of RT-PCR and chest-CT could improve diagnosis performance, but this would requires considerable resources for its rapid use in all patients with suspected COVID-19. The potential contribution of machine learning in this situation has not been fully evaluated. The objective of this study was to develop and evaluate machine learning models using routine clinical and laboratory data to improve the performance of RT-PCR and chest-CT for COVID-19 diagnosis among post-emergency hospitalized patients. All adults admitted to the ED for suspected COVID-19, and then hospitalized at Rennes academic hospital, France, between March 20, 2020 and May 5, 2020 were included in the study. Three model types were created: logistic regression, random forest, and neural network. Each model was trained to diagnose COVID-19 using different sets of variables. Area under the receiving operator characteristics curve (AUC) was the primary outcome to evaluate model's performances. 536 patients were included in the study: 106 in the COVID group, 430 in the NOT-COVID group. The AUC values of chest-CT and RT-PCR increased from 0.778 to 0.892 and from 0.852 to 0.930, respectively, with the contribution of machine learning. After generalization, machine learning models will allow increasing chest-CT and RT-PCR performances for COVID-19 diagnosis.
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Project description:BackgroundThere is an urgent need to identify effective therapy to treat coronavirus diseases 2019 (COVID-19). Supplement consumption is becoming popular in this pandemic era. An example of this is probiotic consumption to improve the host's immune system.ObjectiveThis study aimed to prove whether antibodies from people taking probiotics could influence lactate dehydrogenase (LDH), adenosine triphosphate (ATP) values, and cell viability in vitro in peripheral blood mononuclear cells (PBMCs) inoculated with the SARS-CoV-2 spike protein as COVID-19 cells models.MethodsThis was an experimental study with control and intervention groups, totally in 12 groups divided based on antibody levels, probiotic intervention, probiotic non-intervention group, SARS-CoV-2 infection group, and non-SARS-CoV-2 infection group. In vitro assays were carried out on PBMC cell cultures inoculated with S1 SARS-CoV-2 recombinant as a COVID-19 cell model. The COVID-19 cell model was given antibodies divided into three antibody level groups: sRBD levels of <3, 325.76 and 646.18. The cytotoxicity assessment examined increased levels of LDH, cytopathic activity by measuring ATP levels, and cell viability by XTT (2,3-Bis-(2-Methoxy-4-Nitro-5-Sulfophenyl)-2H-Tetrazolium-5-Carboxanilide) assay. Data were analyzed with SPSS 21 for Windows.ResultsThis study showed a significant difference in the LDH value (p < 0.001) between each group. The difference in ATP values between groups was significant (p < 0.001). Meanwhile, the cell viability examination found that there was a tendency of decreased XTT (cell viability in %) when there was an increase of LDH and ATP.ConclusionThe change of LDH values occurred most in the antibody group that did not consume probiotics. The highest cytopathic activity based on the ATP values occurred in the infected cell culture group with antibody levels of 325.76 and consuming probiotics. In addition, LDH and ATP activities provided evidence of a significant influence on cell viability.
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