Publications by authors named "Daniel L D Freitas"

Osteosarcopenia is a complex geriatric syndrome characterized by the presence of both sarcopenia and osteopenia/osteoporosis. This condition increases rates of disability, falls, fractures, mortality, and mobility impairments in older adults. The purpose of this study was to analyze the Fourier-transform infrared (FTIR) spectroscopy diagnostic power for osteosarcopenia in community-dwelling older women (n = 64; 32 osteosarcopenic and 32 non-osteosarcopenia).

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  • The study developed an AI-based predictive length of stay (LOS) score specifically for patients with advanced high-grade serous ovarian cancer following surgery, aiming to improve hospital care efficiency.
  • Machine learning techniques, including artificial neural networks, were applied alongside logistic regression to predict LOS outcomes, yielding high accuracy rates between 70-98% for different prediction scenarios.
  • The research identified key factors influencing LOS, such as surgical complexity and postoperative complications, and showcased a user-friendly interface for clinicians to access these insights, ultimately aiding in the analysis of factors prolonging hospital stays.
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One of the most important steps in preventing arboviruses is entomological surveillance. The main entomological surveillance action is to detect vector foci in the shortest possible stages. In this work, near and medium infrared spectra collected from female Aedes aegypti mosquitoes recently infected and not infected with dengue were used in order to build chemometric models capable of differentiating the spectra of each class.

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  • Biospectroscopy allows for the identification of biochemical changes in tissues linked to diseases, aiding in biomarker extraction and lesion detection.
  • The study explored the use of machine learning with Raman spectroscopy as a cost-effective method for detecting disease activity in patients with ANCA-associated glomerulonephritis by analyzing renal biopsy and urine samples.
  • Results showed that the spectral data could accurately distinguish disease activity with high sensitivities and specificities, but further research is needed to explore non-invasive biomarkers and enhance prediction of clinical outcomes.
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Prevention of mother-to-child transmission programs have been one of the hallmarks of success in the fight against HIV/AIDS. In Brazil, access to antiretroviral therapy (ART) during pregnancy has increased, leading to a reduction in new infections among children. Currently, lifelong ART is available to all pregnant, however yet challenges remain in eliminating mother-to-child transmission.

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  • Blood plasma and serum Raman spectroscopy has shown promising results in pilot studies for diagnosing ovarian cancer, with this study comparing these fluids along with urine in a large sample size.
  • Principal component analysis revealed significant spectral differences between untreated ovarian cancer patients and those who had undergone neo-adjuvant chemotherapy (NACT).
  • Classification algorithms applied in the study achieved up to 73% sensitivity for plasma, indicating the potential of Raman spectroscopy not only for diagnosis but also for monitoring treatment response.
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The current lack of a reliable biomarker of disease activity in anti-neutrophil cytoplasmic autoantibody (ANCA) associated vasculitis poses a significant clinical unmet need when determining relapsing or persisting disease. In this study, we demonstrate for the first time that attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy offers a novel and functional candidate biomarker, distinguishing active from quiescent disease with a high degree of accuracy. Paired blood and urine samples were collected within a single UK centre from patients with active disease, disease remission, disease controls and healthy controls.

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The primary concern for HIV-infected pregnant women is the vertical transmission that can occur during pregnancy, in the intrauterine period, during labour or even breastfeeding. The risk of vertical transmission can be reduced by early diagnosis. Therefore, it is necessary to develop new methods to detect this virus in a quick and low-cost fashion, as colorimetric assays for HIV detection tend to be laborious and costly.

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Gestational diabetes mellitus (GDM) is a hyperglycaemic imbalance first recognized during pregnancy, and affects up to 22% of pregnancies worldwide, bringing negative maternal-fetal consequences in the short- and long-term. In order to better characterize GDM in pregnant women, 100 blood plasma samples (50 GDM and 50 healthy pregnant control group) were submitted Attenuated Total Reflection Fourier-transform infrared (ATR-FTIR) spectroscopy, using chemometric approaches, including feature selection algorithms associated with discriminant analysis, such as Linear Discriminant Analysis (LDA), Quadratic Discriminant Analysis (QDA) and Support Vector Machines (SVM), analyzed in the biofingerprint region between 1800 and 900 cm followed by Savitzky-Golay smoothing, baseline correction and normalization to Amide-I band (~ 1650 cm). An initial exploratory analysis of the data by Principal Component Analysis (PCA) showed a separation tendency between the two groups, which were then classified by supervised algorithms.

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  • Mortality from breast cancer can be decreased through screening programs that identify cancer biomarkers in asymptomatic populations, enabling earlier diagnosis and treatment.
  • Newer and less-invasive technologies for breast cancer detection, like liquid biopsies, are being promoted for their effectiveness.
  • A study using spectrochemical analyses of blood plasma samples showed high sensitivity (94%) and specificity (91%) compared to traditional mammography, offering better prognosis and lower costs, making it a promising option for clinical use.
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Fibromyalgia is a rheumatologic condition characterized by multiple and chronic body pain, and other typical symptoms such as intense fatigue, anxiety and depression. It is a very complex disease where treatment is often made by non-medicated alternatives in order to alleviate symptoms and improve the patient's quality of life. Herein, we propose a method to detect patients with fibromyalgia (n = 252, 126 controls and 126 patients with fibromyalgia) through the analysis of their blood plasma using attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy in conjunction with chemometric techniques, hence, providing a low-cost, fast and accurate diagnostic approach.

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Alzheimer's disease (AD) is currently under-diagnosed and is predicted to affect a great number of people in the future, due to the unrestrained aging of the population. An accurate diagnosis of AD at an early stage, prior to (severe) symptomatology, is of crucial importance as it would allow the subscription of effective palliative care and/or enrolment into specific clinical trials. Today, new analytical methods and research initiatives are being developed for the on-time diagnosis of this devastating disorder.

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