Chylothorax After Heart Surgery in Children.

Chylothorax is a consequence of a thoracic duct injury that can occur during surgical procedures in patients with congenital heart disease. It is associated with high rates of morbimortality and increased use of clinical and hospital resources. The aim of this study was to evaluate the risk factors, distribution, manifestations, complications, and treatments for chylothorax in patients undergoing cardiac surgery in a tertiary pediatric hospital in southern Brazil. This is a retrospective, quantitative study, in which all medical records (n = 166) of patients with chylothorax after pediatric cardiac surgery between January 2014 and December of 2020 and a matched control group (n = 166) were analyzed. Over the study period, there was an increase in incidence of chylothorax from 4.5% in 2014 to 7.6% in 2020, a trend that has been reported in the literature. After multivariate analysis, the following were identified as risk factors for the diagnosis of chylothorax: genetic syndrome (OR 2.298); prolonged cardiopulmonary bypass time (greater than 120 min) (OR 2.410); fluid overload in the immediate postoperative period (OR 1.110); and SIRS (OR 2.527). Mortality was two times greater (p = 0.021) and there was a higher rate (34.4%) of infection (p < 0.001) in patients who developed chylothorax. In addition, a sensitivity analysis was performed comparing patients with low- and high-output chylothorax (> 20 mL/kg), which confirmed unfavorable outcomes for the latter group. Herein, we show that hemodynamic alterations were important factors for diagnosis. Understanding the risk factors, outcomes, and complications helps early identification and enables the reduction of morbidity and mortality.

Efficacy and safety in the treatment of hyperprolactinemia: A systematic review and network meta-analysis.

WHAT IS KNOWN AND OBJECTIVE: Hyperprolactinemia is a neuroendocrine disease that is responsible for a quarter of cases of secondary amenorrhea, which can lead to infertility in women. Dopaminergic agonists (bromocriptine, cabergoline, quinagolide) can be used in the treatment. However, there is a lack of secondary studies that compare their efficacy and safety, especially through a network meta-analysis. Thus, to contribute to the decision-making, a systematic review and network meta-analyses (NMA) were performed to evaluate the efficacy and safety of dopaminergic agonists in the treatment of hyperprolactinemia. METHODS: Randomized clinical trials (RCT) were retrieved through PubMed, Web of Science and Scopus databases. The efficacy and safety of the drugs were compared, considering the following outcomes: prolactin (PRL) levels, number of patients with galactorrhoea, menstrual irregularities and adverse drug reactions. NMA was built for each outcome. Results were reported as odds ratios (OR) with 95% credibility intervals. Ranking probabilities were calculated by surface under the cumulative ranking analysis (SUCRA) and Stochastic multicriteria acceptability analysis (SMAA). RESULTS AND DISCUSSION: Seventeen RCTs were included in the systematic review and fifteen in the meta-analyses. The drugs had similar efficacy, considering the PRL levels. The SUCRA analysis showed that quinagolide (0.075 and 0.05 mg/day) was superior for reducing irregular menstruation, whereas bromocriptine was the best (97%) for galactorrhoea. Cabergoline proved to be the safest drug, except for abdominal pain at a dose of 1 mg/week. The SMAA demonstrated similar results to SUCRA. WHAT IS NEW AND CONCLUSION: This is the first network meta-analysis that evaluated the efficacy and safety of dopaminergic agonists in the treatment of hyperprolactinemia. The results of this review revealed that these drugs have similar efficacy, but cabergoline has a better safety profile.

LC-QToF-MS method for quantification of ethambutol, isoniazid, pyrazinamide and rifampicin in human plasma and its application.

In this research, we developed and validated a liquid chromatography coupled to mass spectrometry (LC-QToF-MS) method for simultaneous quantification of the anti-tuberculosis drugs ethambutol, isoniazid, pyrazinamide and rifampicin in human plasma. Plasma samples spiked with cimetidine (internal standard) were extracted using protein precipitation with acetonitrile containing 1% formic acid. Separation was performed using a C18 column under flow gradient conditions with water and acetonitrile, both containing 5 mm ammonium formate and 0.1% formic acid. The method was validated according to the ANVISA and US Food and Drug Administration guidelines for bioanalytical method validation. The calibration curve was linear over a concentration range of 0.2-5 µg ml-1 for ethambutol, 0.2-7.5 µg ml-1 for isoniazid, 1-40 µg ml-1 for pyrazinamide and 0.25-2 µg ml-1 for rifampicin, all with adequate precision and accuracy. The method was reproducible, selective and free of carryover and matrix effects. The validated LC-QToF-MS method was successfully applied to real samples and shown to be applicable to future therapeutic and pharmacokinetic monitoring studies.

A new HPLC-MS/MS method for the simultaneous quantification of SGLT2 inhibitors and metformin in plasma and its application to a pharmacokinetic study in healthy volunteers.

Monitoring the plasma concentrations of metformin and sodium-glucose cotransporter-2 inhibitors (canagliflozin, dapagliflozin and empagliflozin) is essential for pharmacokinetic and bioequivalence studies and therapeutic monitoring. The present work therefore aimed to develop and validate a high-performance liquid chromatography coupled to tandem mass spectrometry (HPLC-MS/MS) method for the simultaneous quantification of these drugs in human plasma. The analyses were performed using an Agilent 1200 HPLC system coupled to an Applied Biosystems API 3200 triple quadrupole MS/MS with electrospray ionization in positive ion mode. After one-step protein precipitation of plasma with acetonitrile containing 0.1% formic acid, chromatographic separation was achieved on an Xbridge C18 column, with a mobile phase consisting of a gradient of water and acetonitrile, both containing 1 mm ammonium formate and 0.1% formic acid. Quantification was performed in multiple reaction monitoring mode using m/z 130.1 → 71.1 for metformin, m/z 462.0 → 191.2 for canagliflozin, m/z 426.1 → 167.1 for dapagliflozin and m/z 468.0 → 354.9 for empagliflozin. The proposed method was validated and demonstrated to be adequate for the quantification of metformin, canagliflozin, dapagliflozin and empagliflozin for clinical monitoring, pharmacokinetics and bioequivalence studies.

Doxycycline for Multidrug-Resistant Gram-Negative Bacterial Infection Treatment: A Scoping Review.

Introduction: Multidrug-resistant bacterial infections limit available therapeutic options. Doxycycline is an old antibiotic from the tetracycline class that exhibits a wide antibacterial action, including Gram-negative bacteria (GNB), and could be an alternative for the treatment of multidrug-resistant (MDR) Enterobacteriaceae. The study aimed to systematically identify, evaluate, and summarize the results of studies related to outcomes of treatments for MDR-GNB infections in patients treated with doxycycline. Methods: This review was conducted in four databases during weeks 41-52 of 2022: PubMed, Medline, Scopus, and Web of Science, from the earliest year available on each database to December 2022. Preferred Reporting Items for Systematic Review and Meta-Analysis guidelines were followed in conducting this study, and PICO was used for the research question of this review. Results: This scoping review found 8 retrospective studies that included 59 patients. Of these, 69% were treated for ventilator-associated pneumonia (VAP), 27% for urinary tract infections, 2% for bloodstream infections, and 2% for wound infections, both of which were associated with VAP. The usual dosage of doxycycline was 100 mg intravenously or orally. Clinical and microbiologic improvements were achieved in 81.3% and 87% of all patients, respectively. The mortality rate was 17.3% and was exclusively due to VAP. Conclusions: Doxycycline showed promising results in this review; however, randomized clinical trials or prospective cohorts are recommended to demonstrate the efficacy of doxycycline in the treatment of MDR infections with GNB.

Naringenin-4'-glucuronide as a new drug candidate against the COVID-19 Omicron variant: a study based on molecular docking, molecular dynamics, MM/PBSA and MM/GBSA.

This study aimed to identify natural bioactive compounds (NBCs) as potential inhibitors of the spike (S1) receptor binding domain (RBD) of the COVID-19 Omicron variant using computer simulations (in silico). NBCs with previously proven biological in vitro activity were obtained from the ZINC database and analyzed through virtual screening, molecular docking, molecular dynamics (MD), molecular mechanics/Poisson-Boltzmann surface area (MM/PBSA), and molecular mechanics/generalized Born surface area (MM/GBSA). Remdesivir was used as a reference drug in docking and MD calculations. A total of 170,906 compounds were analyzed. Molecular docking screening revealed the top four NBCs with a high affinity with the spike (affinity energy <-7 kcal/mol) to be ZINC000045789238, ZINC000004098448, ZINC000008662732, and ZINC000003995616. In the MD analysis, the four ligands formed a complex with the highest dynamic equilibrium S1 (mean RMSD <0.3 nm), lowest fluctuation of the complex amino acid residues (RMSF <1.3), and solvent accessibility stability. However, the ZINC000045789238-spike complex (naringenin-4'-O glucuronide) was the only one that simultaneously had minus signal (-) MM/PBSA and MM/GBSA binding free energy values (-3.74 kcal/mol and -15.65 kcal/mol, respectively), indicating favorable binding. This ligand (naringenin-4'-O glucuronide) was also the one that produced the highest number of hydrogen bonds in the entire dynamic period (average = 4601 bonds per nanosecond). Six mutant amino acid residues formed these hydrogen bonds from the RBD region of S1 in the Omicron variant: Asn417, Ser494, Ser496, Arg403, Arg408, and His505. Naringenin-4'-O-glucuronide showed promising results as a potential drug candidate against COVID-19. In vitro and preclinical studies are needed to confirm these findings.Communicated by Ramaswamy H. Sarma.

Assessment of Pediatric Telemedicine Using Remote Physical Examinations With a Mobile Medical Device: A Nonrandomized Controlled Trial.

Importance: The number of innovations in health care based on the use of platforms, digital devices, apps, and artificial intelligence has grown exponentially in recent years. When used correctly, these technologies allow inequities in access to health care to be addressed by optimizing care and reducing social and geographic barriers. However, most of the technological health care solutions proposed have not undergone rigorous clinical studies. Objective: To assess the concordance between measurements from a remote physical examination using a mobile medical device and measurements from a conventional in-person physical examination. Design, Setting, and Participants: This nonrandomized controlled trial was conducted from January 1 to December 31, 2020. The clinical parameters compared were heart rate; body temperature; heart, lung, and abdominal auscultation; otoscopy; throat and oral examination; and skin examination. A total of 690 patients with clinical stability and various symptoms who were seen in the emergency department of 2 Brazilian pediatric hospitals were eligible to enter this study. Main Outcomes and Measures: The primary outcome was concordance between measurements from a telemedicine physical examination using a mobile medical device and measurements from a conventional in-person physical examination. The secondary outcome was the specificity and sensitivity of the digital device, considering the conventional in-person consultation as the gold standard. Results: Among 690 patients, the median (IQR) age at study entry was 5 (1-9) years; 348 (50.4%) were female, and 331 (48.0%) presented with a chronic disease. Regarding the primary outcome, the concordance values were 90% or greater for skin examination (94% for rash, 100% for hemorrhagic suffusion, and 95% for signs of secondary infection), characteristics of the mucosa (98% for hydration and 97% for coloring), and heart (95% for murmur, 97% for rhythms, and 98% for sounds), lung (91% for adventitious sounds, 97% for vesicular sounds, and 90% for fever), and abdominal (92% for abdominal sounds) auscultations. Concordance values were lower for otoscopy (72% for the ear canal and 86% for the tympanic membrane), throat and oral examination (72%), and rhinoscopy (79% for mucosa and 81% for secretion). The specificity was greater than 70% (ranging from 74.5% for the ear canal to 99.7% for hemorrhagic suffusion) for all variables. The sensitivity was greater than 52% for skin examination (58.0% for rash and 54.8% for signs of secondary infection), throat and oral examination (52.7%), and otoscopy (66.1% for the ear canal and 64.4% for the tympanic membrane). Conclusions and Relevance: In this study, measurements from remote physical examination with a mobile medical device had satisfactory concordance with measurements from in-person physical examination for otoscopy, throat and oral examination, skin examination, and heart and lung auscultation, with limitations regarding heart and lung auscultation in infants and abdominal auscultation in children of all ages. Measurements from remote physical examination via a mobile medical device were comparable with those from in-person physical examination in children older than 2 years. These findings suggest that telemedicine may be an alternative to in-person examination in certain contexts and may help to optimize access to health care services and reduce social and geographic barriers. Trial Registration: Brazilian Registry of Clinical Trials Identifier: RBR-346ymn.

Is the Pharmacokinetics of First-Line Anti-TB Drugs a Cause of High Mortality Rates in TB Patients Admitted to the ICU? A Non-Compartmental Pharmacokinetic Analysis.

BACKGROUND: Patients with tuberculosis (TB) may develop multi-organ failure and require admission to intensive care. In these cases, the mortality rates are as high as 78% and may be caused by suboptimal serum concentrations of first-line TB drugs. This study aims to compare the pharmacokinetics of oral rifampin, isoniazid, pyrazinamide and ethambutol patients in intensive care units (ICU) to outpatients and to evaluate drug serum concentrations as a potential cause of mortality. METHODS: A prospective pharmacokinetic (PK) study was performed in Amazonas State, Brazil. The primary PK parameters of outpatients who achieved clinical and microbiological cure were used as a comparative target in a non-compartmental analysis. RESULTS: Thirteen ICU and twenty outpatients were recruited. The clearance and volume of distribution were lower for rifampin, isoniazid, pyrazinamide and ethambutol. ICU thirty-day mortality was 77% versus a cure rate of 89% in outpatients. CONCLUSIONS: ICU patients had a lower clearance and volume of distribution for rifampin, isoniazid, pyrazinamide and ethambutol compared to the outpatient group. These may reflect changes to organ function, impeded absorption and distribution to the site of infection in ICU patients and have the potential to impact clinical outcomes.

Diagnosis and prognosis of COVID-19 employing analysis of patients' plasma and serum via LC-MS and machine learning.

OBJECTIVE: To implement and evaluate machine learning (ML) algorithms for the prediction of COVID-19 diagnosis, severity, and fatality and to assess biomarkers potentially associated with these outcomes. MATERIAL AND METHODS: Serum (n = 96) and plasma (n = 96) samples from patients with COVID-19 (acute, severe and fatal illness) from two independent hospitals in China were analyzed by LC-MS. Samples from healthy volunteers and from patients with pneumonia caused by other viruses (i.e. negative RT-PCR for COVID-19) were used as controls. Seven different ML-based models were built: PLS-DA, ANNDA, XGBoostDA, SIMCA, SVM, LREG and KNN. RESULTS: The PLS-DA model presented the best performance for both datasets, with accuracy rates to predict the diagnosis, severity and fatality of COVID-19 of 93%, 94% and 97%, respectively. Low levels of the metabolites ribothymidine, 4-hydroxyphenylacetoylcarnitine and uridine were associated with COVID-19 positivity, whereas high levels of N-acetyl-glucosamine-1-phosphate, cysteinylglycine, methyl isobutyrate, l-ornithine and 5,6-dihydro-5-methyluracil were significantly related to greater severity and fatality from COVID-19. CONCLUSION: The PLS-DA model can help to predict SARS-CoV-2 diagnosis, severity and fatality in daily practice. Some biomarkers typically increased in COVID-19 patients' serum or plasma (i.e. ribothymidine, N-acetyl-glucosamine-1-phosphate, l-ornithine, 5,6-dihydro-5-methyluracil) should be further evaluated as prognostic indicators of the disease.

A multivariate analysis of risk factors associated with death by Covid-19 in the USA, Italy, Spain, and Germany.

Aim: Our aim was to investigate the risk factors associated with death from COVID-19 in four countries: The USA, Italy, Spain, and Germany. Subject and methods: We used data from the Institute for Health Metrics and Evaluation with projection information from January-August 2020. A multivariate analysis of logistic regression was performed. The following factors were analyzed (per day): number of beds needed for the hospital services, number of intensive care units (ICU) beds required, number of ventilation devices, number of both hospital and ICU admissions due to COVID-19. Nagelkerke's R2 coefficient of determination was used to evaluate the model's predictive ability. The quality of the model's fit was assessed by the Hosmer-Lemeshow and the chi-square tests. Results: Among the evaluated countries, Italy presented greater need for ICU beds/day (≤ 98; OR = 2315.122; CI 95% [334.767-16,503.502]; p < 0.001) and daily ventilation devices (≤ 118; OR = 1784.168; CI 95% [250.217-12,721.995]; p < 0.001). It is expected that both Italy and Spain have a higher ICU admission rate due to COVID-19 (n = 14/day). Spain will need more beds/day (≤ 357; OR = 146.838; CI 95% [113.242-190.402]; p  < 0.001) and probably will have a higher number of daily hospital admissions (n = 48/day). All the above-mentioned factors have an important impact on patients' mortality due to COVID-19 in all four countries. Conclusions: Further investments in hospitals' infrastructure, as well as the development of innovative devices for patient's ventilation, are paramount to fight the pandemic in the USA, Italy, Spain, and Germany.

Bioactive profile of edible nasturtium and rose flowers during simulated gastrointestinal digestion.

Rose and nasturtium are common ornamental edible flowers rich in phytochemicals whose application as food is not widely explored. The gastrointestinal environment can modify these compounds, resulting in new combinations with different bioactivity. This study aimed to evaluate the effects of simulated gastrointestinal digestion (SGD) on rose and nasturtium flower extracts. Using UPLC-HRMS, 38 phenolic compounds were identified, and the SGD caused significant changes, mainly in the glycosylated phenolic. Furthermore, antioxidant activity was correlated with the increase in the concentrations of some polyphenols. Tested Gram-negative bacteria showed sensitivity to the flower extracts; their growth was inhibited by up to 82.7%. SGD interrupted the bacterial growth inhibition power of the rose extracts. On the other hand, an increase in inhibition ranging from 52.25 to 54.72%was found for nasturtium extracts, correlated to the behavior of some bioactive. Hence, SGD resulted in significant changes in phenolic profiles of the edible flowers, increasing antioxidant activity and changing antimicrobial effects.

Diagnosis and prediction of COVID-19 severity: can biochemical tests and machine learning be used as prognostic indicators?

OBJECTIVE: This study aimed to implement and evaluate machine learning based-models to predict COVID-19' diagnosis and disease severity. METHODS: COVID-19 test samples (positive or negative results) from patients who attended a single hospital were evaluated. Patients diagnosed with COVID-19 were categorised according to the severity of the disease. Data were submitted to exploratory analysis (principal component analysis, PCA) to detect outlier samples, recognise patterns, and identify important variables. Based on patients' laboratory tests results, machine learning models were implemented to predict disease positivity and severity. Artificial neural networks (ANN), decision trees (DT), partial least squares discriminant analysis (PLS-DA), and K nearest neighbour algorithm (KNN) models were used. The four models were validated based on the accuracy (area under the ROC curve). RESULTS: The first subset of data had 5,643 patient samples (5,086 negatives and 557 positives for COVID-19). The second subset included 557 COVID-19 positive patients. The ANN, DT, PLS-DA, and KNN models allowed the classification of negative and positive samples with >84% accuracy. It was also possible to classify patients with severe and non-severe disease with an accuracy >86%. The following were associated with the prediction of COVID-19 diagnosis and severity: hyperferritinaemia, hypocalcaemia, pulmonary hypoxia, hypoxemia, metabolic and respiratory acidosis, low urinary pH, and high levels of lactate dehydrogenase. CONCLUSION: Our analysis shows that all the models could assist in the diagnosis and prediction of COVID-19 severity.

Sensitivity and specificity of multibacillary and paucibacillary leprosy laboratory tests: A systematic review and meta-analysis.

This systematic review (number register: CRD42018112736) was performed to compare the sensitivity and specificity of leprosy diagnostic methods. The search was conducted in 3 electronic databases in January 2021. Studies evaluating leprosy diagnostic tests were included according the eligibility criteria. Meta-analysis was performed to calculate the sensibility and specificity of the groups. We included 36 studies. The test sensitivity for paucibacillary patients was 0.31 (95%CI: 0.29-0.33) and the specificity was 0.92 (95%CI: 0.92-0.93). In multibacillary patients, the sensitivity was 0.78 (95%CI: 0.77-0.80) and specificity was 0.92 (95%CI: 0.92-0.93). Comparing the sensitivity and specificity of the different techniques included, it should be noted that polymerase chain reaction (PCR) test presented the highest sensitivity for paucibacillary patients, while the western blot technique showed the highest sensitivity for multibacillary patients. However, further studies are needed to optimise the diagnosis of leprosy, requiring research with a larger number of samples and more uniform protocols.

Is Dosing of Ethambutol as Part of a Fixed-Dose Combination Product Optimal for Mechanically Ventilated ICU Patients with Tuberculosis? A Population Pharmacokinetic Study.

BACKGROUND: Tuberculosis (TB) patients admitted to intensive care units (ICU) have high mortality rates. It is uncertain whether the pharmacokinetics of first-line TB drugs in ICU patients are different from outpatients. This study aims to compare the pharmacokinetics of oral ethambutol in TB patients in ICU versus TB outpatients and to determine whether contemporary dosing regimens achieve therapeutic exposures. METHODS: A prospective population pharmacokinetic study of ethambutol was performed in Amazonas State, Brazil. Probability of target attainment was determined using AUC/MIC > 11.9 and Cmax/MIC > 0.48 values. Optimized dosing regimens were simulated at steady state. RESULTS: Ten ICU patients and 20 outpatients were recruited. Ethambutol pharmacokinetics were best described using a two-compartment model with first-order oral absorption. Neither ICU patients nor outpatients consistently achieved optimal ethambutol exposures. The absorption rate for ethambutol was 2-times higher in ICU patients (p < 0.05). Mean bioavailability for ICU patients was >5-times higher than outpatients (p < 0.0001). Clearance and volume of distribution were 93% (p < 0.0001) and 53% (p = 0.002) lower in ICU patients, respectively. CONCLUSIONS: ICU patients displayed significantly different pharmacokinetics for an oral fixed-dose combination administration of ethambutol compared to outpatients, and neither patient group consistently achieved pre-defined therapeutic exposures.

Risk factors associated with delay in diagnosis and mortality in patients with COVID-19 in the city of Rio de Janeiro, Brazil.

We investigated the predictors of delay in the diagnosis and mortality of patients with COVID-19 in Rio de Janeiro, Brazil. A cohort of 3,656 patients were evaluated (Feb-Apr 2020) and patients' sociodemographic characteristics, and social development index (SDI) were used as determinant factors of diagnosis delays and mortality. Kaplan-Meier survival analyses, time-dependent Cox regression models, and multivariate logistic regression analyses were conducted. The median time from symptoms onset to diagnosis was eight days (interquartile range [IQR] 7.23-8.99 days). Half of the patients recovered during the evaluated period, and 8.3% died. Mortality rates were higher in men. Delays in diagnosis were associated with male gender (p = 0.015) and patients living in low SDI areas (p < 0.001). The age groups statistically associated with death were: 70-79 years, 80-89 years, and 90-99 years. Delays to diagnosis greater than eight days were also risk factors for death. Delays in diagnosis and risk factors for death from COVID-19 were associated with male gender, age under 60 years, and patients living in regions with lower SDI. Delays superior to eight days to diagnosis increased mortality rates.

New Validated Method for Quantification of Glycated Hemoglobin by LC-QToF-MS: Is HRMS Able to Quantify Clinical Samples?

High-resolution mass spectrometry is a powerful tool in clinical analysis but remains less explored due to its lower dynamic range and sensitivity compared to triple quadrupoles. Glycated hemoglobin (HbA1c) is the current gold standard biomarker to monitor the control of diabetes, representing long-term plasma glycemic levels. Due to its clinical importance, several methods have been developed for HbA1c quantification, using different principles; however, the results obtained with these techniques may differ according to the method adopted. Hence, there is a great need to standardize the current methods to quantify glycated hemoglobin. A new UPLC-QToF-MS method was fully validated and tested to quantify HbA1c in human samples. The peptides VHLTPE m/z 695.373 and gly-VHLTPE m/z 857.426, obtained via Glu-C digestion, were the selected peptides for quantification of HbA1c (mmol/mol). Chromatographic separation was obtained in a C18 column, maintained at 40 °C. The mobile phase was composed of water and acetonitrile, both containing 0.02% TFA and 0.1% acetic acid, and eluted in gradient mode. The method was fully validated, being considered linear in the range of 25-107 mmol/mol of HbA1c, and was sensitive, selective, precise, accurate, and free of matrix and carryover effects. The method was successfully applied to real samples, reaching about 90% agreement with reference method results, providing accurate and precise information on peptide mass, without laborious sample preparation. These results support the use of HRMS to improve the quality of quantitative results of HbA1c in health services and demonstrate a possible application of peptide investigation for clinical analysis in the near future.

Improvement of phenolic compound bioaccessibility from yerba mate (Ilex paraguariensis) extracts after biosorption on Saccharomyces cerevisiae.

Great efforts have been made to increase the bioaccessibility of bioactive compounds from plant sources. This can be achieved by the innovative and effective method of biosorption of these compounds in Saccharomyces cerevisiae obtained from the industrial fermentative process (waste yeast). In this context, this research evaluated if chemical modifications of depleted yeast can improve the capacity to biosorb the phenolic compounds and if through in vitro digestion tests, this approach can increase bioaccessibility of the secondary metabolites from yerba mate. The results showed that the chemical modification of the yeast promoted an increase in the biosorption efficiency of the bioactive compounds. Mass spectrometry peaks for the phenolic compounds reduced after biosorption as observed for the caffeic and dicaffeoylquinic acids and for kaempferol and rutin. In addition, a 10% reduction of caffeine was verified after biosorption, quantified by mass spectrometry chromatography. This showing that the compounds were retained in the cells, which was also observed by an increase of cell turgidity with scanning electron microscopy (SEM). Mid-infrared spectroscopy showed that the major bands related to the components of the compounds increased proportionally after biosorption. Furthermore, an increase of bioaccessibility of the yerba mate bioactive compounds adsorbed in S. cerevisiae was verified when compared with the crude extract.

Development of a validated stability-indicating HPLC- DAD method for dasabuvir and the characterization of its degradation products using LC-QToF-MS/MS

Abstract A stability-indicating HPLC-DAD method was developed and validated for the simultaneous determination of dasabuvir and its degradation products in the pharmaceutical formulation. The proposed method utilized a Symmetry® C18 (4.6 x 75 mm, 3.5 µm) column, and the mobile phase consisted of an isocratic elution of formic acid (0.1%) and acetonitrile (55:45, v/v), at a flow of 1 mL min-1; analytes were detected at 244 nm. Dasabuvir was submitted to different stress degradation conditions, such as acidic, alkaline, neutral, thermal, oxidative and photolytic, and the structural elucidation of degradation products was performed using LC-QToF-MS/MS. The HPLC-DAD stability-indicating method was validated for selectivity, linearity, limit of detection and quantification, accuracy, precision and robustness, according to ICH guidelines. Dasabuvir produced two degradation products (DP1 and DP2) from the alkaline stress conditions, which were characterized in negative ion mode. Dasabuvir was linear in the range 9.78 to 136.92 µg mL-1, and DP and DP were linear in the range 2.9 to 20.2 µg mL-1 and 1.3 to 14.9 µg mL-1, respectively. The 1 2 recovery ranged between 99.16 and 100.86%, while precision ranged from 1.02 to 2.89%. As the method can effectively separate the dasabuvir from its degradation products and quantitate them, it may be employed as a stability-indicating method for the pharmaceutical formulation.

Bioanalytical methods for the detection of antidiabetic drugs: a review.

Type 2 diabetes mellitus, a disease which prevalence has been progressively increasing worldwide, is characterized by chronic hyperglycemia resulting from the combination of inappropriate insulin secretion and/or resistance to insulin action. If left uncontrolled, diabetes is associated with complications such as dysfunction and failure of various organs, and even premature death. Along with lifestyle-modification strategies, several classes of oral antidiabetic agents can be employed for glycemic control. Thus, therapeutic drug monitoring of these drugs is essential to maintain appropriate treatment. This review discusses the most frequently employed analytical techniques and sample preparation systems to obtain a reliable and trustworthy method to quantify antidiabetic drugs in biological matrices. An adequate choice of internal standard, ideal chromatography conditions and most suitable analytical detector are reported.

A systematic and critical review on bioanalytical method validation using the example of simultaneous quantitation of antidiabetic agents in blood.

A systematic and critical review was conducted on bioanalytical methods validated to quantify combinations of antidiabetic agents in human blood. The aim of this article was to verify how the validation process of bioanalytical methods is performed and the quality of the published records. The validation assays were evaluated according to international guidelines. The main problems in the validation process are pointed out and discussed to help researchers to choose methods that are truly reliable and can be successfully applied for their intended use. The combination of oral antidiabetic agents was chosen as these are some of the most studied drugs and several methods are present in the literature. Moreover, this article may be applied to the validation process of all bioanalytical.