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Dynamic contrast optical coherence tomography (DyC-OCT), an emerging imaging method, utilizes fluctuation patterns in OCT signals to enhance contrast, thereby enabling non-invasive label-free volumetric live cell imaging. In this mini review, we explain the core concepts behind DyC-OCT image formation and its system configurations, serving as practical guidance for future DyC-OCT users. Subsequently, we explore its applications in delivering high-quality, contrast-enhanced images of cellular morphology, as well as in monitoring changes in cellular activity/viability assay experiments., (© 2024. The Author(s).)

Antifungal stewardship is a critical component of healthcare management that focuses on optimizing the use of antifungal medications to improve patient outcomes, minimize resistance, and reduce healthcare costs.  In resource-limited settings, the prevalence of fungal infections remains a significant health concern, often exacerbated by factors such as compromised immune systems, inadequate diagnostic capabilities, and limited access to antifungal agents. This paper reviews the current state of antifungal stewardship practices in developing countries, addressing the unique socioeconomic and healthcare landscape., Competing Interests: The authors have no conflicts of interest., (© The Author(s) 2023.)

Motion artifacts, from such sources as heartbeats, respiration, or peristalsis, often degrade microscopic images or videos of live subjects. We have developed a method using circular optical coherence tomography (OCT) scans to track the transverse and axial motion of biological samples at speeds ranging from several micrometers per second to several centimeters per second. We achieve fast and high-precision measurements of the magnitude and direction of the sample's motion by adaptively controlling the circular scan pattern settings and applying interframe and intraframe analyses. These measurements are the basis of active motion compensation via feedback control for future in vivo microscopic and macroscopic imaging applications., Competing Interests: SH and CZ are inventors of a patent application submitted by Washington University in St. Louis regarding methods described in this work., (© 2023 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.)

Ovarian tissue cryopreservation has been successfully applied worldwide for fertility preservation. Correctly selecting the ovarian tissue with high follicle loading for freezing and reimplantation increases the likelihood of restoring ovarian function, but it is a challenging process. In this work, we explore the use of three-dimensional spectral-domain optical coherence tomography (SD-OCT) to identify different follicular stages, compare the identifications with H&E images, and measure the size and age-related follicular density distribution differences in mice ovaries. We use the thickness of the layers of granulosa cells to differentiate primordial and primary follicles from secondary follicles. The measured dimensions and age-related follicular distribution agree well with histological images and physiological aging. Finally, we apply attenuation coefficient map analyses to significantly improve the image contrast and the contrast-to-noise ratio (p < 0.001), facilitating follicle identification and quantification. We conclude that SD-OCT is a promising method to noninvasively evaluate ovarian follicles for ovarian tissue cryopreservation., Competing Interests: The authors declare no conflicts of interest., (© 2023 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.)

Candidemia remains a major public health challenge due to its high mortality rates, especially in developing countries. Monitoring epidemiological trends may provide insights for better clinical outcomes. This study aimed to describe trends in the epidemiology, therapeutic practices, and mortality in candidemia through a retrospective comparative analysis between two surveillance cohorts of all candidemic adults at eleven tertiary hospitals in Brazil, from 2010-2011 (Period I) versus 2017-2018 (Period II). A total of 616 cases were diagnosed, with 247 being from Period II. These patients were more likely to have three or more coexisting comorbidities [72 (29.1%) vs. 60 (16.3%), p < 0.001], had a prior history of in-hospital admissions more often [102 (40.3%) vs. 79 (21.4%), p = 0.001], and presented with candidemia earlier after admission, within 15 days (0-328) vs. 19 (0-188), p = 0.01. Echinocandins were more frequently prescribed [102 (41.3%) vs. 50 (13.6%), p = 0.001], but time to antifungal initiation [2 days (0-14) vs. 2 (0-13), p = 0.369] and CVC removal within 48 h [90/185 (48.6%) vs. 148/319 (46.4%), p = 0.644] remained unchanged. Additionally, many patients went untreated in both periods I and II [87 (23.6%) vs. 43 (17.4%), p = 0.07], respectively. Unfortunately, no improvements in mortality rates at 14 days [123 (33.6%) vs. 93 (37.7%), p = 0.343] or at 30 days [188 (51.4%) vs. 120 (48.6%), p = 0.511] were observed. In conclusion, mortality rates remain exceedingly high despite therapeutic advances, probably associated with an increase in patients' complexity and suboptimal therapeutic interventions. Management strategies should be tailored to suit epidemiological changes, expedite diagnosis to reduce the number of untreated eligible patients and guarantee early antifungal initiation and source control.

Introduction: Optimized allocation of medical resources to patients with COVID-19 has been a critical concern since the onset of the pandemic., Methods: In this retrospective cohort study, the authors used data from a Brazilian tertiary university hospital to explore predictors of Intensive Care Unit (ICU) admission and hospital mortality in patients admitted for COVID-19. Our primary aim was to create and validate prediction scores for use in hospitals and emergency departments to aid clinical decisions and resource allocation., Results: The study cohort included 3,022 participants, of whom 2,485 were admitted to the ICU; 1968 survived, and 1054 died in the hospital. From the complete cohort, 1,496 patients were randomly assigned to the derivation sample and 1,526 to the validation sample. The final scores included age, comorbidities, and baseline laboratory data. The areas under the receiver operating characteristic curves were very similar for the derivation and validation samples. Scores for ICU admission had a 75% accuracy in the validation sample, whereas scores for death had a 77% accuracy in the validation sample. The authors found that including baseline flu-like symptoms in the scores added no significant benefit to their accuracy. Furthermore, our scores were more accurate than the previously published NEWS-2 and 4C Mortality Scores., Discussion and Conclusions: The authors developed and validated prognostic scores that use readily available clinical and laboratory information to predict ICU admission and mortality in COVID-19. These scores can become valuable tools to support clinical decisions and improve the allocation of limited health resources., Competing Interests: Conflicts of interest The authors declare no conflicts of interest., (Copyright © 2023 HCFMUSP. Published by Elsevier España, S.L.U. All rights reserved.)

Chronic pulmonary aspergillosis (CPA) is divided into five subtypes. The diagnosis of CPA is complicated due to poor sensitivity of the laboratory tests. Diagnostic performance of different antigen, serological, and microbiological methods in subtypes of CPA is unknown. The purpose of this study was to evaluate the diagnostic performance in different subtypes of CPA. A total of 91 participants with CPA were included, and the study was performed at Hospital das Clínicas of University of São Paulo. Bronchoalveolar lavage galactomannan (73%, 11/15), serology by immunodiffusion test (81%, 61/75), and histology (78%, 39/50) had the best sensitivity. The counterimmunoelectrophoresis (CIE) titers had a significant statistical difference between the CPA subtypes (P < 0.001), in which the forms chronic fibrosing pulmonary aspergillosis (CFPA) and subacute invasive aspergillosis (SAIA) had higher titers: 1/64 (interquartile range [IQR]: 1/32-1/256) and 1/64 (1/32-1/128). C-reactive protein generally presented lower values (median 15 mg/L, IQR: 6-33), with higher values in SAIA and lower values for Aspergillus nodule. Overall, we found a low diagnostic sensitivity of current tests. Regarding the CPA subtypes, we did not find great differences in the performance of the tests, but it is observed that the inflammatory markers and CIE titers tend to be higher in forms of the more extensive lung parenchyma involvement, such as SAIA and CFPA.

The rhizosphere yeast Torulaspora globosa is known to produce indole acetic acid (IAA) and to solubilize minerals. Due to the prospective use of this yeast as a biostimulant for agricultural applications, this work aimed to optimize the cultural conditions for both IAA production and phosphate solubilization. For phosphate solubilization, the temperature (20, 25 and 30 °C), initial medium pH (3.0, 5.0, and 7.0), and shaker speed (without mixing, 100 rpm, 150 rpm, and 200 rpm) were considered using the one-factor-at-a-time (OFAT) design. Temperature of 25 °C, initial medium pH 7.0, and static cultures were the conditions of greatest phosphate solubilization, with 40% of the total phosphorus content solubilized from calcium phosphate (419.86 mg L -1 ) after 48 h. By using the response surface methodology, the maximum IAA production (217.73 µg mL -1 ) was obtained with the highest initial pH 7.0, the lowest nitrogen, and glucose concentrations (5 g L -1 and 10 g L -1 , respectively) and the lowest agitator speed (100 rpm). Further tests indicated that nitrogen affected significantly IAA production and the absence of nitrogen in the medium promoted higher IAA production (457 µg mL -1 ). The results obtained here may contribute to the scaling up for industrial and agricultural applications of a yeast-based product with T. globosa ., Competing Interests: Conflict of interestThe authors declare that they have no competing interests., (© King Abdulaziz City for Science and Technology 2022, Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.)

Background: Optimal COVID-19 management is still undefined. In this complicated scenario, the construction of a computational model capable of extracting information from electronic medical records, correlating signs, symptoms and medical prescriptions, could improve patient management/prognosis., Methods: The aim of this study is to investigate the correlation between drug prescriptions and outcome in patients with COVID-19. We extracted data from 3674 medical records of hospitalized patients: drug prescriptions, outcome, and demographics. The outcome evaluated was hospital outcome. We applied correlation analysis using a Logistic Regression algorithm for machine learning with Lasso and Matthews correlation coefficient., Results: We found correlations between drugs and patient outcomes (death/discharged alive). Anticoagulants, used very frequently during all phases of the disease, were associated with good prognosis only after the first week of symptoms. Antibiotics very frequently prescribed, especially early, were not correlated with outcome, suggesting that bacterial infections may not be important in determining prognosis. There were no differences between age groups., Conclusions: In conclusion, we achieved an important result in the area of Artificial Intelligence, as we were able to establish a correlation between concrete variables in a real and extremely complex environment of clinical data from COVID-19. Our results are an initial and promising contribution in decision-making and real-time environments to support resource management and forecasting prognosis of patients with COVID-19., (© 2022. The Author(s).)

Background: COVID-19 caused more than 622 thousand deaths in Brazil. The infection can be asymptomatic and cause mild symptoms, but it also can evolve into a severe disease and lead to death. It is difficult to predict which patients will develop severe disease. There are, in the literature, machine learning models capable of assisting diagnose and predicting outcomes for several diseases, but usually these models require laboratory tests and/or imaging., Methods: We conducted a observational cohort study that evaluated vital signs and measurements from patients who were admitted to Hospital das Clínicas (São Paulo, Brazil) between March 2020 and October 2021 due to COVID-19. The data was then represented as univariate and multivariate time series, that were used to train and test machine learning models capable of predicting a patient's outcome., Results: Time series-based machine learning models are capable of predicting a COVID-19 patient's outcome with up to 96% general accuracy and 81% accuracy considering only the first hospitalization day. The models can reach up to 99% sensitivity (discharge prediction) and up to 91% specificity (death prediction)., Conclusions: Results indicate that time series-based machine learning models combined with easily obtainable data can predict COVID-19 outcomes and support clinical decisions. With further research, these models can potentially help doctors diagnose other diseases., (© 2022. The Author(s).)

There is already a societal awareness of the growing impact of nanoscience and nanotechnology, with nanomaterials (with at least one dimension less than 100 nm) now incorporated in items as diverse as mobile phones, clothes or dentifrices. In the healthcare area, nanoparticles of biocompatible materials have already been used for cancer treatment or bioimaging enhancement. Nanotechnology in dentistry, or nanodentistry, has already found some developments in dental nanomaterials for caries management, restorative dentistry and orthodontic adhesives. In this review, we present state-of-the-art scientific development in nanodentistry with an emphasis on two imaging techniques exploiting nanomaterials: optical coherence tomography (OCT) and photoacoustic imaging (PAI). Examples will be given using OCT with nanomaterials to enhance the acquired imaging, acting as optical clearing agents for OCT. A novel application of gold nanoparticles and nanorods for imaging enhancement of incipient occlusal caries using OCT will be described. Additionally, we will highlight how the OCT technique can be properly managed to provide imaging with spatial resolution down to 10's-100's nm resolution. For PAI, we will describe how new nanoparticles, namely TiN, prepared by femtosecond laser ablation, can be used in nanodentistry and will show photoacoustic microscopy and tomography images for such exogenous agents.

Purpose: The aim of this work was to analyze the effect of fibrin biopolymer sealant (FS) associated or not to aquatic exercise (AE) on the calcaneal tendon repair., Methods: Forty-four female Wistar rats were randomly divided into four experimental groups: Lesion control (L), Lesion and FS (LS), Lesion and AE (LE) and Lesion and FS associated to AE (LSE). The edema volume (EV), collagen ratio, and histopathological analysis were evaluated after 7, 14, and 21 days of partial tendon transection., Results: The EV was statistically reduced for all treatment groups after 7 and 21 days when compared to L group. The LS and LSE had the highest EV reduction after 21 days of treatment. The FS group didn't induce tissue necrosis or infections on the histopathological analysis. It was observed tenocytes proliferation, granulation tissue and collagen formation in the tendon partial transection area in the FS group. The LSE demonstrated higher amount of granulation tissue and increased the collagen deposition at the injury site., Conclusions: Our data suggests that the therapeutic potential of the association of heterologous fibrin biopolymer sealant with aquatic exercise program should be further explored as it may stimulate the regeneration phase and optimize calcaneal tendon recovery.

The profiles of 61 Candida tropicalis isolates from 43 patients (28 adults and 15 children) diagnosed with candidemia at two teaching hospitals in São Paulo, Brazil, were characterized by multilocus sequence typing (MLST). For the 14 patients who had bloodstream infections, 32 isolates were serially collected from their blood and/or catheters. Thirty-nine diploid sequence types (DSTs) were differentiated. According to the C. tropicalis MLST database (http://pubmlst.org/ctropicalis/), 36 DSTs and 23 genotypes identified from the 61 isolates had not previously been described. This report represents the first study to characterize sequential isolates of C. tropicalis from candidemia cases in South America. Microvariation in a single gene was found in the sequential isolates from 7 patients. The main polymorphisms occurred in the alleles of the XYR1 gene, specifically at nucleotide positions 215, 242, and 344. Macrovariation in six gene fragments was detected in the isolates from 3 patients. eBURST analysis added two new groups to this study (groups 6 and 18). Additionally, susceptibility tests indicate that 3 isolates were resistant to fluconazole. No correlation was found between the DSTs and susceptibility to fluconazole and/or selective antifungal pressure. Two patients were sequentially infected with resistant and susceptible strains. MLST is an important tool for studying the genetic diversity of multiple/sequential isolates of patients with candidemia, allowing the comparison of our data with those from other regions of the world, as well as allowing an analysis of the genetic relationship among several clones in sequential isolates from the same or different candidemia patient sites (blood or catheter).

Introduction: Paracoccidioidomycosis is a type of mycosis that is endemic to Brazil and is triggered by the fungus Paracoccidioides brasiliensis. Isolated bone involvement in this disease is very rare, especially in children. To the best of our knowledge this report documents the first case of an immunocompetent pediatric patient in which paracoccidioidomycosis of the hip articulation was the sole manifestation of the disease (that is, there were no pulmonary or skin lesions)., Case Presentation: An 11-year-old Brazilian Caucasian boy from a rural area was examined in the orthopedic ward of our emergency department. Our patient reported a three-month history of pain in the right hip with intermittent claudication and also complained of recurring episodes of intense pain and an inability to walk, which he had been experiencing for the previous five days. He additionally presented with a fever that had persisted for two days. Our patient's medical history did not include any clinical respiratory manifestations, skin lesions, history of trauma or immunosuppression risk factors., Conclusions: This is one of the very few reported cases of isolated articular involvement in osteomyelitis in a pediatric immunocompetent patient. Paracoccidioidomycosis should be considered among the differential diagnoses in such cases, especially in cases of patients who reside in rural areas where the condition is considered to be endemic, in order to administer the proper course of treatment in a timely fashion and improve the chances of a favorable prognosis.