A5008399829- Immune responses and vaccinations
- COVID-19 Clinical Research Studies
- Immunodeficiency and Autoimmune Disorders
- COVID-19 epidemiological studies
- SARS-CoV-2 and COVID-19 Research
- Long-Term Effects of COVID-19
- COVID-19 Impact on Reproduction
- Bladder and Urothelial Cancer Treatments
- COVID-19 and healthcare impacts
- Single-cell and spatial transcriptomics
- COVID-19 Pandemic Impacts
- Cancer Immunotherapy and Biomarkers
- COVID-19 diagnosis using AI
- Circular RNAs in diseases
- Genital Health and Disease
- Neonatal Respiratory Health Research
- Vaccine Coverage and Hesitancy
- MicroRNA in disease regulation
- Extracellular vesicles in disease
- Infection Control and Ventilation
- Immune cells in cancer
- Nanoplatforms for cancer theranostics
Universidade Estadual de Campinas (UNICAMP)
2021-2024
Pontifícia Universidade Católica de São Paulo
2021-2022
Pontifícia Universidade Católica de Campinas
2021-2022
Abstract Background The Bacillus Calmette–Guérin (BCG) vaccine may confer cross‐protection against viral diseases in adults. This study evaluated BCG adults with convalescent coronavirus disease 2019 (COVID‐19). Method was a multicenter, prospective, randomized, placebo‐controlled, double‐blind phase III (ClinicalTrials.gov: NCT04369794). Setting: University Community Health Center and Municipal Outpatient South America. Patients: total of 378 adult patients COVID‐19 were included....
Bladder cancer (BC) is the 10th most common worldwide, with about 0.5 million reported new cases and 0.2 deaths per year.In this scoping review, we summarize current evidence regarding clinical implications of single-cell sequencing for bladder based on PRISMA guidelines.We searched PubMed, CENTRAL, Embase, supplemented manual searches through Scopus, Web Science published studies until February 2023.We included original that used at least one technology to study cancer.Forty-one...
Bacillus Calmette-Guérin (BCG) injected during the COVID-19 convalescence period was safe and enhanced recovery from anosmia dysgeusia in acute phase.
Abstract Coronavirus disease 2019 (COVID-19) is caused by Severe Acute Respiratory Syndrome 2 (SARS-CoV-2). Recent research has demonstrated how epigenetic mechanisms regulate the host–virus interactions in COVID-19. It also shown that microRNAs (miRNAs) are one of three fundamental regulation gene expression and play an important role viral infections. A pilot study published our group identified, through next-generation sequencing (NGS), miR-4433b-5p, miR-320b, miR-16–2-3p differentially...
To analyze the interfering effect of plasma from COVID-19 convalescent adults vaccinated or not with intradermal Bacillus Calmette-Guérin (BCG) on human macrophages.
To find whether an emergent airborne infection is more likely to spread among healthcare workers (HCW) based on data of SARS-CoV-2 and the number new cases such viral disease can be predicted using a method traditionally used in weather forecasting called Autoregressive Fractionally Integrated Moving Average (ARFIMA).We analyzed HCWs outpatient nasopharyngeal swabs for real-time polymerase chain reaction (RT-PCR) tests compared it non-HCW first second wave pandemic. We also generated ARFIMA...
ABSTRACT Introduction Heath care workers with direct (HCW-D) or indirect (HCW-A) patient contact represent 4.2% to 17.8% of COVID-19 cases. We evaluate the temporal infection behavior among HCW-D, HCW-A, and non-HCW. Methods From February 2020 April 2021, trained nurses recorded age, gender, occupation, symptoms in a testing outpatient health center. allocated data into weekly time fractals calculated proportion positive HCW vs. non-HCW incorporated an ARFIMA model (traditionally used...
ABSTRACT Purpose To develop a reliable tool that predicts which patients are most likely to be COVID-19 positive and ones have an increased risk of hospitalization. Methods From February 2020 April 2021, trained nurses recorded age, gender, symptoms in outpatient testing center. All were followed up by phone for 14 days or until symptom-free. We calculated the odds ratio results hospitalization proposed “random forest” machine-learning model predict testing. Results A total 8,998 over 16...