Fluoxetine alters rat's milk properties causing impact on offspring's development.

Fluoxetine is an antidepressant used to treat several conditions including postpartum depression. This disease causes cognitive, emotional, behavioral and physical changes, negatively affecting the mother, child and family life. However, fluoxetine is excreted in breast milk, causing short and long-term effects on children who were exposed to the drug during lactation, so studies that seek to uncover the consequences of these effects are needed. Thus, the aim of this study was to evaluate the effects of fluoxetine on the nutritional characteristics of milk and on growth and neurobehavioral development of the offspring on a rat model. Lactating rats were divided into 4 groups: control group and three experimental groups, which were treated with different doses of fluoxetine (1, 10 and 20 mg/kg) during the lactation. Dams body weight and milk properties were measured, as well as offspring's growth and physical and neurobehavioral development. Results showed that the use of fluoxetine during lactation decreased dam's body weight and alters milk's properties, leading to a decrease in offspring's growth until adulthood. Therefore, the use of fluoxetine during lactation needs to be cautiously evaluated, with the benefits to the mothers and the associated risk to the offspring carefully balance.

Successful treatment with alectinib after crizotinib-induced hepatitis in ALK-rearranged advanced lung cancer patient: a case report.

BACKGROUND: Besides the clinical benefit of crizotinib in ALK-rearranged metastatic non-small cell lung cancer (NSCLC), concerns about its hepatotoxicity have arisen. It is not clear whether this is a drug class side effect or if the use of other selective ALKs inhibitors is safe after this serious adverse event. While evidence from clinical trials is scarce, reports of treatment after crizotinib-induces hepatitis may add to clinical decision. CASE PRESENTATION: Herein, we report a case of acute hepatitis induced by crizotinib in a 32-years-old female diagnosed with metastatic NSCLC, harboring the ALK-rearrangement. After 60 days of crizotinib therapy, the patient presented with acute hepatitis, diagnosed after investigation of non-specific symptoms, such as nausea and fatigue. Serum aspartate aminotransferase and alanine aminotransferase levels had increased from baseline to 3010 IU/L and 9145 IU/L, respectively. Total bilirubin increased up to 7.91 mg/dL, but she did not develop liver failure. After crizotinib discontinuation, a gradual hepatic function recovery occurred. Unfortunately, during the period without specific oncology treatment, her disease showed an unequivocal progression. Therefore, she started on alectinib with great response, and no liver function alteration recurred. CONCLUSIONS: This case suggests that alectinib, even belonging to the same drug class, could be used as an alternative agent when crizotinib is the etiology of liver damage, but more robust evidence has awaited.

Multi-omic serum biomarkers for prognosis of disease progression in prostate cancer.

BACKGROUND: Predicting the clinical course of prostate cancer is challenging due to the wide biological spectrum of the disease. The objective of our study was to identify prostate cancer prognostic markers in patients 'sera using a multi-omics discovery platform. METHODS: Pre-surgical serum samples collected from a longitudinal, racially diverse, prostate cancer patient cohort (N = 382) were examined. Linear Regression and Bayesian computational approaches integrated with multi-omics, were used to select markers to predict biochemical recurrence (BCR). BCR-free survival was modeled using unadjusted Kaplan-Meier estimation curves and multivariable Cox proportional hazards analysis, adjusted for key pathologic variables. Receiver operating characteristic (ROC) curve statistics were used to examine the predictive value of markers in discriminating BCR events from non-events. The findings were further validated by creating a training set (N = 267) and testing set (N = 115) from the cohort. RESULTS: Among 382 patients, 72 (19%) experienced a BCR event in a median follow-up time of 6.9 years. Two proteins-Tenascin C (TNC) and Apolipoprotein A1V (Apo-AIV), one metabolite-1-Methyladenosine (1-MA) and one phospholipid molecular species phosphatidic acid (PA) 18:0-22:0 showed a cumulative predictive performance of AUC = 0.78 [OR (95% CI) = 6.56 (2.98-14.40), P < 0.05], in differentiating patients with and without BCR event. In the validation set all four metabolites consistently reproduced an equivalent performance with high negative predictive value (NPV; > 80%) for BCR. The combination of pTstage and Gleason score with the analytes, further increased the sensitivity [AUC = 0.89, 95% (CI) = 4.45-32.05, P < 0.05], with an increased NPV (0.96) and OR (12.4) for BCR. The panel of markers combined with the pathological parameters demonstrated a more accurate prediction of BCR than the pathological parameters alone in prostate cancer. CONCLUSIONS: In this study, a panel of serum analytes were identified that complemented pathologic patient features in predicting prostate cancer progression. This panel offers a new opportunity to complement current prognostic markers and to monitor the potential impact of primary treatment versus surveillance on patient oncological outcome.

Effect of the essential oils from Melaleuca alternifolia, Melaleuca quinquenervia and Backhousia citriodora on the synthesis of ochratoxin A by Aspergillus niger and Aspergillus carbonarius isolated from tropical wine grapes.

The influence of essential oils (EOs) extracted from the leaves of Melaleuca alternifolia, Melaleuca quinquenervia and Backhousia citriodora on ochratoxin A (OTA) synthesis by fungi was studied. The extraction of EOs was performed by hydrodistillation (Clevenger apparatus) over a 2-h period and subsequently analyzed by GC-MS and GC-FID. The toxigenic activity of the essential oils (31.25; 15.62 and 7.81 µg mL-1) was evaluated by inhibiting the production of OTA by Aspergillus niger and Aspergillus carbonarius in Czapek agar medium culture. The quantification of the toxin was performed by HPLC. The production of OTA was dependent on the fungal species, incubation temperature (15 and 25 °C) and the presence of the essential oils. In tests carried out at 15 °C, the oils caused a reduction in OTA synthesis that ranged from 57.60 to 76.93% and from 54.78 to 98.68% for the fungal species A. carbonarius and A. niger, respectively. At 25 °C, reductions ranged from the 38.66 to 75.93% and from 17.94 to 71.79% for the respective fungi. The study concluded that natural products could be potential biocontrol agents against OTA contamination in food.

A Temperature-Dependent Battery Model for Wireless Sensor Networks.

Energy consumption is a major issue in Wireless Sensor Networks (WSNs), as nodes are powered by chemical batteries with an upper bounded lifetime. Estimating the lifetime of batteries is a difficult task, as it depends on several factors, such as operating temperatures and discharge rates. Analytical battery models can be used for estimating both the battery lifetime and the voltage behavior over time. Still, available models usually do not consider the impact of operating temperatures on the battery behavior. The target of this work is to extend the widely-used Kinetic Battery Model (KiBaM) to include the effect of temperature on the battery behavior. The proposed Temperature-Dependent KiBaM (T-KiBaM) is able to handle operating temperatures, providing better estimates for the battery lifetime and voltage behavior. The performed experimental validation shows that T-KiBaM achieves an average accuracy error smaller than 0.33%, when estimating the lifetime of Ni-MH batteries for different temperature conditions. In addition, T-KiBaM significantly improves the original KiBaM voltage model. The proposed model can be easily adapted to handle other battery technologies, enabling the consideration of different WSN deployments.

BRAF V600E and loss of heterozygosity assessment in benign oralneural tumours.

BACKGROUND: The purpose of this study was to evaluate loss of heterozygosity (LOH) and to assess BRAF V600E mutation in oral neurofibromas, palisaded encapsulated neuromas (PEN) and schwannomas. METHODS: Six oral neurofibroma, 5 PEN and 3 schwannoma samples were included in the study. LOH was assessed using polymorphic microsatellite markers at chromosome regions 3p (marker D3S1029), 9p (markers D9S171, D9S162, D9S157), 11q (marker D11S1369), and 17p (markers AFM238WF2 and P53), and results were evaluated after capillary electrophoresis. BRAF mutation encoding V600E was assessed by real-time PCR with a specific TaqMan probe to detect the T>A transversion at position c.1799. RESULTS: LOH occurred at chromosomes 3p (marker D3S1029), 11q (D11S1369) and 17p (AFM238WF2 and P53). LOH occurred in 2/6 neurofibromas, 2/5 PEN and in none of the 3 schwannoma samples. The 6 neurofibromas, 2/2 PEN evaluated and the 3 schwannomas were BRAF wild type. CONCLUSION: According to our results, oral benign peripheral nerve sheath tumours have a low LOH rate, but P53 locus alteration is occasionally found. Additionally, BRAF V600E mutation is either not relevant to the molecular pathogenesis of this group of lesions of the oral cavity, or may occur at very low rates.

Normal and neoplastic nonstem cells can spontaneously convert to a stem-like state.

Current models of stem cell biology assume that normal and neoplastic stem cells reside at the apices of hierarchies and differentiate into nonstem progeny in a unidirectional manner. Here we identify a subpopulation of basal-like human mammary epithelial cells that departs from that assumption, spontaneously dedifferentiating into stem-like cells. Moreover, oncogenic transformation enhances the spontaneous conversion, so that nonstem cancer cells give rise to cancer stem cell (CSC)-like cells in vitro and in vivo. We further show that the differentiation state of normal cells-of-origin is a strong determinant of posttransformation behavior. These findings demonstrate that normal and CSC-like cells can arise de novo from more differentiated cell types and that hierarchical models of mammary stem cell biology should encompass bidirectional interconversions between stem and nonstem compartments. The observed plasticity may allow derivation of patient-specific adult stem cells without genetic manipulation and holds important implications for therapeutic strategies to eradicate cancer.

Green Analytical Toxicology procedure for determination of ketamine, its metabolites and analogues in oral fluid samples using dispersive liquid-liquid microextraction (DLLME).

New psychoactive substances (NPS) are often synthesized via small changes in the molecular structure, producing drugs whose effect and potency are not yet fully known. Ketamine is one of the oldest NPS, with therapeutic use in human and veterinary medicine authorized in several countries, being metabolized mainly into norketamine and 6-hydroxy-norketamine. Furthermore, two structural analogues of ketamine have recently been identified, deschloroketamine and 2-fluorodeschloroketamine, marketed as drugs of abuse. To comply with Green Analytical Toxicology (GAT) fundamentals, miniaturized techniques such as dispersive liquid-liquid microextraction (DLLME) were employed to determine toxicants in biological fluids. An analytical method for determining ketamine, its metabolites and its analogues in oral fluid was fully developed and validated by using DLLME and liquid chromatography-tandem mass spectrometry (LC-MS-MS). The extraction parameters were optimized by multivariate analysis, obtaining the best conditions with 200 µL of sample, 100 µL of methanol as dispersive solvent and 50 µL of chloroform as extractor solvent. Linearity was obtained from 10 to 1,000 ng/mL, with limit of detection (LOD) and lower limit of quantification (LLOQ) at 10 ng/mL. Imprecision (% relative standard deviation) and bias (%) were less than 8.2% and 9.5%, respectively. The matrix effect did not exceed 10.6%, and the recovery values varied from 24% to 42%. No matrix interference and good selectivity in the evaluation of 10 different sources of oral fluid and 42 drugs at 500 ng/mL, respectively, were observed. The method was applied in the analysis of 29 authentic oral fluid samples and had its green characteristic evaluated by three different tools: the Green Analytical Procedure Index (GAPI), the Analytical Eco-Scale and the Analytical GREEnness (AGREE) metrics.

Identification and validation of N-acetylputrescine in combination with non-canonical clinical features as a Parkinson's disease biomarker panel.

Parkinson's disease is a progressive neurodegenerative disorder in which loss of dopaminergic neurons in the substantia nigra results in a clinically heterogeneous group with variable motor and non-motor symptoms with a degree of misdiagnosis. Only 3-25% of sporadic Parkinson's patients present with genetic abnormalities that could represent a risk factor, thus environmental, metabolic, and other unknown causes contribute to the pathogenesis of Parkinson's disease, which highlights the critical need for biomarkers. In the present study, we prospectively collected and analyzed plasma samples from 194 Parkinson's disease patients and 197 age-matched non-diseased controls. N-acetyl putrescine (NAP) in combination with sense of smell (B-SIT), depression/anxiety (HADS), and acting out dreams (RBD1Q) clinical measurements demonstrated combined diagnostic utility. NAP was increased by 28% in Parkinsons disease patients and exhibited an AUC of 0.72 as well as an OR of 4.79. The clinical and NAP panel demonstrated an area under the curve, AUC = 0.9 and an OR of 20.4. The assessed diagnostic panel demonstrates combinatorial utility in diagnosing Parkinson's disease, allowing for an integrated interpretation of disease pathophysiology and highlighting the use of multi-tiered panels in neurological disease diagnosis.

Germination of Pisum sativum L. Seeds Is Associated with the Alternative Respiratory Pathway.

The alternative oxidase (AOX) is a ubiquinol oxidase with a crucial role in the mitochondrial alternative respiratory pathway, which is associated with various processes in plants. In this study, the activity of AOX in pea seed germination was determined in two pea cultivars, 'Maravilha d'América' (MA) and 'Torta de Quebrar' (TQ), during a germination trial using cytochrome oxidase (COX) and AOX inhibitors [rotenone (RT) and salicylic hydroxamic acid (SHAM), respectively]. Calorespirometry was used to assess respiratory changes during germination. In both cultivars, SHAM had a greater inhibitory effect on germination than RT, demonstrating the involvement of AOX in germination. Although calorespirometry did not provide direct information on the involvement of the alternative pathway in seed germination, this methodology was valuable for distinguishing cultivars. To gain deeper insights into the role of AOX in seed germination, the AOX gene family was characterized, and the gene expression pattern was evaluated. Three PsAOX members were identified-PsAOX1, PsAOX2a and PsAOX2b-and their expression revealed a marked genotype effect. This study emphasizes the importance of AOX in seed germination, contributing to the understanding of the role of the alternative respiratory pathway in plants.

Colony Age of Trichoderma azevedoi Alters the Profile of Volatile Organic Compounds and Ability to Suppress Sclerotinia sclerotiorum in Bean Plants.

Common bean (Phaseolus vulgaris L.) is one of the most important crops in human food production. The occurrence of diseases, such as white mold, caused by Sclerotinia sclerotiorum can limit the production of this legume. The use of Trichoderma has become an important strategy in the suppression of this disease. The aim of the present study was to evaluate the effect of volatile organic compounds (VOCs) emitted by Trichoderma azevedoi CEN1241 in five different growth periods on the severity of white mold in common bean. The in vitro assays were carried out in double-plate and split-plate, and the in vivo assays, through the exposure of the mycelia of S. sclerotiorum to the VOCs of T. azevedoi CEN1241 and subsequent inoculation in bean plants. Chemical analysis by gas chromatography coupled to mass spectrometry detected 37 VOCs produced by T. azevedoi CEN1241, covering six major chemical classes. The profile of VOCs produced by T. azevedoi CEN1241 varied according to colony age and was shown to be related to the ability of the biocontrol agent to suppress S. sclerotiorum. T. azevedoi CEN1241 VOCs reduced the size of S. sclerotiorum lesions on bean fragments in vitro and reduced disease severity in a greenhouse. This study demonstrated in a more applied way that the mechanism of antibiosis through the production of volatile compounds exerted by Trichoderma can complement other mechanisms, such as parasitism and competition, thus contributing to a better efficiency in the control of white mold in bean plants.

Evaluation of konjac noodle as a microsurgery training model: learning curve analysis.

BACKGROUND: classical models of microsurgical anastomosis training are expensive and have ethical implications. Some alternatives join low cost and easiness to store. However, the translation of knowledge acquired by training in these methods into the traditional ones is not clear. This project aims to assess the feasibility of konjac noodles as a reliable microsurgery-training model. METHODS: 10 neurosurgery residents performed an end-to-end anastomosis in a 2-3mm placenta artery. The anastomoses were evaluated quantitatively, recording time; and qualitatively, applying a validated score (Anastomosis Lapse Index - ALI) by three experienced neurosurgeons and verifying the presence of gross leakage through the infusion of fluorescein. Subsequently, they performed 10 non-consecutive sessions of anastomosis training in the konjac noodle. Eventually, a final anastomosis in the placenta model was performed and the same parameters were scored. RESULTS: we observed a 17min reduction in the mean time to perform the anastomosis in the placenta model after the training in the konjac (p<0.05). There was a non-significant 20% reduction in gross leakage, but the training sessions were not able to consistently improve the ALI score. CONCLUSIONS: we demonstrate a reduction in anastomosis performing time in placental arteries after training sessions in the konjac noodle model, which can be regarded as a feasible low-cost method, particularly useful in centers with surgical microscopes only in the operation room.

Dispersive liquid-liquid microextraction of 11-nor-Δ9-tetrahydrocannabinol-carboxylic acid applied to urine testing.

Aim: THC-COOH is the major metabolite of Δ9-tetrahydrocannabinol commonly tested in urine to determine cannabis intake. In this study, a method based on dispersive liquid-liquid microextraction was developed for testing THC-COOH in urine. Materials & methods: Hydrolyzed urine specimens were extracted via dispersive liquid-liquid microextraction with acetonitrile (disperser solvent) and chloroform (extraction solvent). Derivatization was performed with N,O-Bis(trimethylsilyl)trifluoroacetamide with 1% trichloro(chloromethyl)silane. Analysis was performed by GC-MS/MS. Results: The method showed acceptable linearity (5-500 ng/ml), imprecision (<10.5%) and bias (<4.9%). Limits of detection and quantitation were 1 and 5 ng/ml, respectively. Twenty-four authentic samples were analyzed, with 22 samples being positive for THC-COOH. Conclusion: The proposed method is more environmentally friendly and provided good sensitivity, selectivity and reproducibility.

Tweetable abstract Green analytical toxicology: Dispersive liquid­liquid microextraction applied to the analysis of THC-COOH in urine by GC­MS/MS.

Plasma Metabolite Signature Classifies Male LRRK2 Parkinson's Disease Patients.

Parkinson's disease (PD) is a progressive neurodegenerative disease, causing loss of motor and nonmotor function. Diagnosis is based on clinical symptoms that do not develop until late in the disease progression, at which point the majority of the patients' dopaminergic neurons are already destroyed. While many PD cases are idiopathic, hereditable genetic risks have been identified, including mutations in the gene for LRRK2, a multidomain kinase with roles in autophagy, mitochondrial function, transcription, molecular structural integrity, the endo-lysosomal system, and the immune response. A definitive PD diagnosis can only be made post-mortem, and no noninvasive or blood-based disease biomarkers are currently available. Alterations in metabolites have been identified in PD patients, suggesting that metabolomics may hold promise for PD diagnostic tools. In this study, we sought to identify metabolic markers of PD in plasma. Using a 1H-13C heteronuclear single quantum coherence spectroscopy (HSQC) NMR spectroscopy metabolomics platform coupled with machine learning (ML), we measured plasma metabolites from approximately age/sex-matched PD patients with G2019S LRRK2 mutations and non-PD controls. Based on the differential level of known and unknown metabolites, we were able to build a ML model and develop a Biomarker of Response (BoR) score, which classified male LRRK2 PD patients with 79.7% accuracy, 81.3% sensitivity, and 78.6% specificity. The high accuracy of the BoR score suggests that the metabolomics/ML workflow described here could be further utilized in the development of a confirmatory diagnostic for PD in larger patient cohorts. A diagnostic assay for PD will aid clinicians and their patients to quickly move toward a definitive diagnosis, and ultimately empower future clinical trials and treatment options.

Multiplex CRISPR/Cas9-mediated knockout of the phytoene desaturase gene in Coffea canephora.

Coffea canephora (2n = 2x = 22 chromosomes) is a species with extensive genetic diversity and desirable agronomic traits for coffee breeding programs. However, obtaining a new coffee cultivar through conventional breeding techniques may require more than 30 years of crossing cycles and selection, which hampers the effort of keeping up with market demands and rapidly proposing more resilient to climate change varieties. Although, the application of modern biotechnology tools such as precision genetic engineering technologies may enable a faster cultivar development process. Therefore, we aimed to validate the CRISPR/Cas9 system to generate mutations on a selected genotype of C. canephora, the clone 14. Embryogenic calli and a multiplex binary vector containing two sgRNAs targeting different exons of the CcPDS gene were used. The sgRNAs were under the C. canephora U6 promoter regulation. The target gene encodes phytoene desaturase, an enzyme essential for photosynthesis involved in ß-carotene biosynthesis. Somatic seedlings and embryos with albino, variegated and green phenotypes regenerated after Agrobacterium tumefaciens-mediated genetic transformation were analyzed by verifying the insertion of the Cas9 gene and later by sequencing the sgRNAs target regions in the genome of Robusta modified seedlings. Among them, 77% had the expected mutations, and of which, 50% of them had at least one target with a homozygous mutation. The genotype, temperature of co-cultivation with the bacteria, and light intensity used for subsequent embryo regeneration appeared to strongly influence the successful regeneration of plants with a mutated CcPDS gene in the Coffea genus.

Development of analytical method for the determination of methylphenidate, the analog ethylphenidate and their metabolite ritalinic acid in oral fluid samples by micro-QuEChERS and liquid chromatography-tandem mass spectrometry.

The aim of this study was to develop a quantitative method for the analysis of methylphenidate, the analog ethylphenidate and their metabolite ritalinic acid in oral fluid, using micro-QuEChERS extraction and liquid chromatography-tandem mass spectrometry (LC-MS/MS). Oral fluid samples were collected with Quantisal™ device, extracted by micro-QuEChERS technique and analyzed by LC-MS/MS. The developed method met the validation criteria of Academy Standards Board (ASB) Standard Practices for Method Validation in Forensic Toxicology (Standard 036, 2019) with limits of detection and quantification of 0.5 ng/mL and calibration curve from 0.5 to 50 ng/mL. Within-run imprecision was greater than 18.7% while between-run imprecision was greater than 17.0 % for all analytes. Bias did not vary more than 7.7 %. No evidence of carryover was found. Stability studies presented satisfactory results for 24 h on autosampler (10 °C), after 3 cycles of freeze/thaw, 7 days on freezer (-20 °C) and until 7 days on refrigerator (4 °C) for methylphenidate. The validated method was further successfully applied to the analysis of 5 authentic oral fluid samples collected from volunteers at parties and music festivals from different cities in Brazil. Four samples had positive results for methylphenidate and ritalinic acid, and only one sample was positive for methylphenidate. Ethylphenidate was not detected in the samples. The method showed acceptable analytical performance and is environmentally friendly, requiring reduced use of solvents and reagents, with potential to be applied to clinical and forensic analyses.

Impact of using cocoa bean shell powder as a substitute for wheat flour on some of chocolate cake properties.

The cocoa bean shell is a residue rich in bioactive compounds and its use as an ingredient in the food industry has been studied. This work had the objective of proposing the elaboration of chocolate cake with substitution of wheat flour by cocoa bean shell powder (CSp). Five formulations with different percentages of CSp were used: 25%, 50%, 75%, 100% and 0% (control). The cakes were evaluated by technological characteristics (volume, texture profile, firmness and colour), antioxidant profile (DPPH, ß-carotene/linoleic acid system, phenolic compounds, anthocyanins and tannins) and sensory tests (TDS and acceptance). The technological characteristics and antioxidant activity of the cakes were influenced by the different concentrations of CSp compared to the control sample. The cakes containing up to 75% CSp presented satisfactory sensory acceptance. Therefore, CSp has been revealed to be a prominent alternative substitute ingredient to be used promisingly in the food industry.

Impact of hemolysis on multi-OMIC pancreatic biomarker discovery to derisk biomarker development in precision medicine studies.

Cancer biomarker discovery is critically dependent on the integrity of biofluid and tissue samples acquired from study participants. Multi-omic profiling of candidate protein, lipid, and metabolite biomarkers is confounded by timing and fasting status of sample collection, participant demographics and treatment exposures of the study population. Contamination by hemoglobin, whether caused by hemolysis during sample preparation or underlying red cell fragility, contributes 0-10 g/L of extraneous protein to plasma, serum, and Buffy coat samples and may interfere with biomarker detection and validation. We analyzed 617 plasma, 701 serum, and 657 buffy coat samples from a 7-year longitudinal multi-omic biomarker discovery program evaluating 400+ participants with or at risk for pancreatic cancer, known as Project Survival. Hemolysis was undetectable in 93.1% of plasma and 95.0% of serum samples, whereas only 37.1% of buffy coat samples were free of contamination by hemoglobin. Regression analysis of multi-omic data demonstrated a statistically significant correlation between hemoglobin concentration and the resulting pattern of analyte detection and concentration. Although hemolysis had the greatest impact on identification and quantitation of the proteome, distinct differentials in metabolomics and lipidomics were also observed and correlated with severity. We conclude that quality control is vital to accurate detection of informative molecular differentials using OMIC technologies and that caution must be exercised to minimize the impact of hemolysis as a factor driving false discovery in large cancer biomarker studies.

Hypothesis-Agnostic Network-Based Analysis of Real-World Data Suggests Ondansetron is Associated with Lower COVID-19 Any Cause Mortality.

BACKGROUND: The COVID-19 pandemic generated a massive amount of clinical data, which potentially hold yet undiscovered answers related to COVID-19 morbidity, mortality, long-term effects, and therapeutic solutions. OBJECTIVES: The objectives of this study were (1) to identify novel predictors of COVID-19 any cause mortality by employing artificial intelligence analytics on real-world data through a hypothesis-agnostic approach and (2) to determine if these effects are maintained after adjusting for potential confounders and to what degree they are moderated by other variables. METHODS: A Bayesian statistics-based artificial intelligence data analytics tool (bAIcis®) within the Interrogative Biology® platform was used for Bayesian network learning and hypothesis generation to analyze 16,277 PCR+ patients from a database of 279,281 inpatients and outpatients tested for SARS-CoV-2 infection by antigen, antibody, or PCR methods during the first pandemic year in Central Florida. This approach generated Bayesian networks that enabled unbiased identification of significant predictors of any cause mortality for specific COVID-19 patient populations. These findings were further analyzed by logistic regression, regression by least absolute shrinkage and selection operator, and bootstrapping. RESULTS: We found that in the COVID-19 PCR+ patient cohort, early use of the antiemetic agent ondansetron was associated with decreased any cause mortality 30 days post-PCR+ testing in mechanically ventilated patients. CONCLUSIONS: The results demonstrate how a real-world COVID-19-focused data analysis using artificial intelligence can generate unexpected yet valid insights that could possibly support clinical decision making and minimize the future loss of lives and resources.

Closed doors: Predictors of stress, anxiety, depression, and PTSD during the onset of COVID-19 pandemic in Brazil.

BACKGROUND: The rise in mental health problems in the population directly or indirectly because of the coronavirus disease 2019 (COVID-19) pandemic is a major concern. The aim of this study was to investigate and compare independent predictors of symptoms of stress, anxiety, depression, and posttraumatic stress disorder (PTSD) in Brazilians one month after the implementation of measures of social distancing. METHODS: This cross-sectional study was performed using a web-based survey. The Depression, Anxiety, and Stress Scale (DASS-21) and PTSD Checklist for DSM-5 (PCL-5) were the outcomes. Data were gathered regarding demographics, social distancing, economic problems, exposure to the news of the pandemic, psychiatric history, sleep disturbances, traumatic situations, and substance use. The Alcohol Use Disorders Identification Test - Consumption (AUDIT-C) was also administered. The predictors of the symptoms were investigated using hierarchical multiple linear regression. RESULTS: Of a sample of 3587 participants, approximately two-thirds considered that their mental health worsened after the beginning of the social restriction measures. The most important predictors of the symptoms investigated were the intensity of the distress related to the news of the pandemic, younger age, current psychiatric diagnosis, trouble sleeping, emotional abuse or violence, and economic problems. CONCLUSIONS: These results confirmed the hypothesis that the pandemic impacted the mental health of the population and indicated that the level of distress related to the news was the most important predictor of psychological suffering.