Machine learning and statistics shape a novel path in archaeal promoter annotation.

BACKGROUND: Archaea are a vast and unexplored domain. Bioinformatic techniques might enlighten the path to a higher quality genome annotation in varied organisms. Promoter sequences of archaea have the action of a plethora of proteins upon it. The conservation found in a structural level of the binding site of proteins such as TBP, TFB, and TFE aids RNAP-DNA stabilization and makes the archaeal promoter prone to be explored by statistical and machine learning techniques. RESULTS AND DISCUSSIONS: In this study, experimentally verified promoter sequences of the organisms Haloferax volcanii, Sulfolobus solfataricus, and Thermococcus kodakarensis were converted into DNA duplex stability attributes (i.e. numerical variables) and were classified through Artificial Neural Networks and an in-house statistical method of classification, being tested with three forms of controls. The recognition of these promoters enabled its use to validate unannotated promoter sequences in other organisms. As a result, the binding site of basal transcription factors was located through a DNA duplex stability codification. Additionally, the classification presented satisfactory results (above 90%) among varied levels of control. CONCLUDING REMARKS: The classification models were employed to perform genomic annotation into the archaea Aciduliprofundum boonei and Thermofilum pendens, from which potential promoters have been identified and uploaded into public repositories.

Taxonomy, comparative genomics and evolutionary insights of Penicillium ucsense: a novel species in series Oxalica.

The genomes of two Penicillium strains were sequenced and studied in this study: strain 2HH was isolated from the digestive tract of Anobium punctatum beetle larva in 1979 and the cellulase hypersecretory strain S1M29, derived from strain 2HH by a long-term mutagenesis process. With these data, the strains were reclassified and insight is obtained on molecular features related to cellulase hyperproduction and the albino phenotype of the mutant. Both strains were previously identified as Penicillium echinulatum and this investigation indicated that these should be reclassified. Phylogenetic and phenotype data showed that these strains represent a new Penicillium species in series Oxalica, for which the name Penicillium ucsense is proposed here. Six additional strains (SFC101850, SFCP10873, SFCP10886, SFCP10931, SFCP10932 and SFCP10933) collected from the marine environment in the Republic of Korea were also classified as this species, indicating a worldwide distribution of this new taxon. Compared to the closely related strain Penicillium oxalicum 114-2, the composition of cell wall-associated proteins of P. ucsense 2HH shows five fewer chitinases, considerable differences in the number of proteins related to ß-D-glucan metabolism. The genomic comparison of 2HH and S1M29 highlighted single amino-acid substitutions in two major proteins (BGL2 and FlbA) that can be associated with the hyperproduction of cellulases. The study of melanin pathways shows that the S1M29 albino phenotype resulted from a single amino-acid substitution in the enzyme ALB1, a precursor of the 1,8-dihydroxynaphthalene (DHN)-melanin biosynthesis. Our study provides important knowledge towards understanding species distribution, molecular mechanisms, melanin production and cell wall biosynthesis of this new Penicillium species.

Omentin-1 and its relationship with inflammatory factors in maternal plasma and visceral adipose tissue of women with gestational diabetes mellitus.

PURPOSE: To investigate the association of omentin-1 and inflammatory factors in serum and visceral adipose tissue (VAT) of women with gestational diabetes mellitus (GDM) compared to normal pregnant (NP) subjects. Furthermore, to examine their correlation with maternal clinical characteristics. METHODS: We compared 116 GDM women to 115 NP women, at the time of cesarean section. Circulating omentin-1 and pro-inflammatory (IL-1ß, IL-6, TNF-α), and anti-inflammatory cytokines (IL-1RA, IL-10) were examined. Moreover, their mRNA expression in VAT, along with inflammatory factors involved in the NF-κB pathway (TLR2, TLR4, NF-κB, IKκB), were examined. RESULTS: Circulating omentin-1 (p = 0.022) was lower and circulating IL-1-ß, IL-1RA, as well as IL-10 (p = 0.005, p = 0.007, and p = 0.015, respectively), were higher in GDM compared to NP women. Omentin-1 correlated negatively with pre-pregnancy and gestational BMI, and HOMA-IR in all women, but was not associated with cytokines. TLR2, TLR4, IL-1ß, IL-1RA, IL-6, IL-10 mRNA expression in VAT was lower in GDM compared with controls (p < 0.05 all). In multivariate analysis, BMI at delivery was significantly correlated to omentin-1 concentrations in all and NP subjects. In addition, omentin-1 expression was correlated to inflammatory gene expression in all, GDM and NP, women (p < 0.05 all). CONCLUSION: Serum levels and VAT gene expression of omentin-1 are not independently linked to GDM; notwithstanding, GDM women have a VAT-altered inflammatory status. In addition, no systemic association between omentin-1 and inflammatory factors was found, whereas associations between their expression in all women were observed, indicating that expression of these adipokines is linked between them regardless of GDM.

Effect of land uses and land cover on soil attributes in the southern Brazilian Amazon.

The growth of the world population has led to the expansion of agricultural areas to produce food that meets world demand, making it necessary to increase productivity and maintain environmental sustainability in these areas. Seeking sustainable food production, the agricultural use of soil must be assessed in view of optimal use or land as natural resource, as well as minimize the effects of global warming related to land use and land cover (LULC). We hypothesize that different LULC affects Amazonian soil attributes. In this study, the effect of different LULC in the southern Brazilian Amazon, namely, native forest, pasture, and rice and soybean crops, on the spatial variability of soil fertility and texture was assessed, seeking to obtain information that will guide farmers in the near future to better exploit their areas and contribute to a more sustainable agriculture. Descriptive statistical analysis was performed for the pH, H + Al, Al, Ca, Mg, P, K, Cu, Fe, Mn, Zn, V, m, organic matter, clay, silt, and sand values from soil samples under different LULC. To verify the data normality, the Shapiro-Wilk test at 5% significance was performed. Outlier analysis using boxplot graphics, principal component analysis (PCA), and cluster analysis was performed. Data were submitted to geostatistical analysis to verify the spatial dependence degree of the variables through semivariograms for interpolated kriging maps. Except for silt, all variables were well represented in the factor map. PCA revealed that the data variability can be explained mainly by pH, V, Ca, K, and Zn values, which are inversely proportional to m, P, and sand. Through geostatistical analysis, spatial dependence ranging from moderate to strong was observed, generating reliability in the prediction of most attributes in pasture, rice, and soybean areas. Yet, a spatial dependence ranging from moderate to strong was found, generating reliability in the prediction of most attributes in pasture, rice, and soybean areas. Our findings reveal a lower fertility and higher acidity in forest areas, whereas crop areas presented the opposite result.

Mitochondrial genome of Rhabdosynochus viridisi (Monogenea: Diplectanidae), a parasite of Pacific white snook Centropomus viridis.

We report the nearly complete mitochondrial genome of Rhabdosynochus viridisi - the first for this genus - achieved by combining shotgun sequencing of genomic and cDNA libraries prepared using low-input protocols. This integration of genomic information leads us to correct the annotation of the gene features. The mitochondrial genome consists of 13,863 bp. Annotation resulted in the identification of 12 protein-encoding genes, 22 tRNA genes and two rRNA genes. Three non-coding regions, delimited by three tRNAs, were found between the genes nad5 and cox3. A phylogenetic analysis grouped R. viridisi with three other species of diplectanid monogeneans for which mitochondrial genomes are available.

Evaluation of a psychoeducational intervention including emotional intelligence to increase treatment adherence in rheumatoid arthritis (A pilot study).

Our objective was to perform two studies: a cross-sectional study in order to identify the main psychological variables associated to treatment adherence in rheumatoid arthritis and an intervention based on psychoeducation to assess its impact on the variables identified in the first study. We measured treatment adherence, self-efficacy, beliefs about medication, emotional intelligence and disability along with personal and disease variables in the cross-sectional study and the same variables were measured in the intervention before and after the program and 3 months later in 2 groups (an experimental group and an active control group). In the cross-sectional study (N=33) we found that the variables most associated with treatment adherence were emotional clarity (r=0.352, p<0.05) and emotional repair (r=0.363, p<0.05). In the intervention, we divided the patients into 2 groups: the control group (N=7) and the intervention group (N=10). At the end of the study and at follow-up, we found a significant increase in adherence and self-efficacy in the intervention group, when compared with the control group. Emotional clarity was increased only in the post-test, and at follow up a decrease in beliefs of concern about medication was found. Psychoeducational programs based on information about the disease and its treatment together with emotional management are effective in increasing treatment adherence in the long term.

Silver nanoparticles are lethal to the ciliate model Tetrahymena and safe to the pike silverside Chirostoma estor.

Ciliate ectoparasites are one of the most important groups of pathogens in fish culture, and the traditional treatments are sometimes harmful to the fish and the environment. Thus, the search for novel compounds that are effective at low concentrations and safe for fish are necessary to optimise treatments in aquaculture. The antiprotozoal capacity of silver nanoparticles (AgNPs) against the ciliate Tetrahymena has been documented; however, their toxicity may vary with the synthesis methodology and nanoparticle size. The objectives of this study were a) to evaluate the acute toxicity in vitro of two AgNPs (Argovit™ and UTSA) on Tetrahymena sp., a biological model for ciliated ectoparasites of fish and b) to test the safety of lethal and higher doses of UTSA AgNPs for ciliates on the fish C. estor. Light microscopy and scanning electron microscopy (SEM) were used to determine whether AgNPs affected the structure of the cell surface of Tetrahymena. The mortality, histopathological alterations and metagenomics of the fish were used to determine the major effects of UTSA AgNPs. In Tetrahymena, the median lethal concentration (LC50) for Argovit™ was 2501 ± 1717 ng/L at 15 min and 796 ± 510 ng/L at 60 min, while the LC50 for UTSA AgNPs was 4 ± 2 and 1 ± 0.6 ng/L at 15 min and 60 min, respectively. A concentration of 3300 ng/L Argovit™ and 10.6 ng/L UTSA AgNPs for 15 and 60 min, respectively, was 100% effective against Tetrahymena. After 60 min of exposure to 0.25 and 0.50 ng/L UTSA AgNPs, the number of cilia significantly reduced, there were small holes on the cell surface, and the cellular membrane was ruptured. In fish exposed to lethal (10.6 ng/L) and higher (31.8 and 95.4 ng/L) doses of UTSA, the AgNPs did not affect fish survival after 96 h, and there were no signs of histopathological damage or gut microbial changes. This study is the first report on microscopic and ultrastructural changes in Tetrahymena after exposure to significantly low concentrations of UTSA AgNPs with antiprotozoal efficacy without evidence of harmful effects on fish. These results provide the basis for further studies of both pet aquarium and commercial fish that may validate these findings at a larger experimental scale, taking into account AgNPs bioaccumulation, safety for human consumption and environmental impact.

Analysis of the nucleotide content of Escherichia coli promoter sequences related to the alternative sigma factors.

Promoters are DNA sequences located upstream of the transcription start site of genes. In bacteria, the RNA polymerase enzyme requires additional subunits, called sigma factors (σ) to begin specific gene transcription in distinct environmental conditions. Currently, promoter prediction still poses many challenges due to the characteristics of these sequences. In this paper, the nucleotide content of Escherichia coli promoter sequences, related to five alternative σ factors, was analyzed by a machine learning technique in order to provide profiles according to the σ factor which recognizes them. For this, the clustering technique was applied since it is a viable method for finding hidden patterns on a data set. As a result, 20 groups of sequences were formed, and, aided by the Weblogo tool, it was possible to determine sequence profiles. These found patterns should be considered for implementing computational prediction tools. In addition, evidence was found of an overlap between the functions of the genes regulated by different σ factors, suggesting that DNA structural properties are also essential parameters for further studies.

Quantitative real-time PCR (qPCR) for the detection and quantification of dactylogyrid parasites infecting Lutjanus guttatus.

Severe infections of the spotted rose snapper Lutjanus guttatus resulting from dactylogyrid monogeneans present a risk to aquaculture. Currently, the diagnosis of this infection requires the morphological identification and manual quantification of parasites. Based on the characterization of the 28S rRNA gene of dactylogyrid species present in L. guttatus, specific primers were designed for real-time polymerase chain reaction (qPCR) using EvaGreen® chemistry. The standard curve method estimated the number of dactylogyrids accurately. A total of 85 gill samples from cage-cultured fish infected with dactylogyrids were analysed. The estimated number of dactylogyrids using this molecular method was very similar to the manual count that was performed initially. The standardized qPCR approach will be helpful as a complementary method for the early routine monitoring of dactylogyrid infections and for epidemiological studies in which a high number of fish must be studied.

Trichomonas vaginalis exosome-like vesicles modify the cytokine profile and reduce inflammation in parasite-infected mice.

Trichomonas vaginalis (Tv) is a flagellated parasite commonly spread through sexual transmission. This protozoan initiates a severe inflammatory process, inducing nitric oxide, interleukin-6 (IL-6), IL-8, IL-10, IL-17 and IL-22 production by host immune cells. The parasites elicit these responses by releasing surface lipophosphoglycan, small extracellular vesicles (exosomes) and other factors. Tv exosomes are similar to mammalian exosomes and have been implicated in the modulation of IL-8 secretion by epithelial cells. Here, we report that exosome-like vesicles from T. vaginalis (Tv-ELVs) induced a more than 15-fold increase in IL-10 expression in RAW264.7 macrophages but only a two fold increase in IL-6 and TNF-α expression levels measured by RT-PCR. Because Tv-ELVs modulated the macrophage response, we also explored the effect of Tv-ELVs in a murine model of infection. Pretreatment with Tv-ELVs significantly increased IL-10 production as measured in vaginal washes by days 8 and 16 post-infection. Remarkably, Tv-ELVs-pretreated mice exhibited a decrease in IL-17 production and a significant decrease in vulvar inflammation. In addition, IL-6 and IL-13 were decreased during infection. Our results suggest that Tv-ELVs have an immunomodulatory role on the cytokine profile induced by the parasite and promote a decrease in the inflammatory process in mice infected with T. vaginalis.

BacPP: a web-based tool for Gram-negative bacterial promoter prediction.

Bacterial Promoter Prediction (BacPP) is a tool used to predict given sequences as promoters of Gram-negative bacteria according to the σ factor that recognizes it. The first version of BacPP was implemented in Python language in a desktop version without a friendly interface. For this reason, a web version of BacPP is now available with the purpose of improving its usability and availability. The present paper describes the implementation of the web version of this tool, focusing on its software architecture and user functionalities. The software is available at www.bacpp.bioinfoucs.com/home.

A cis-acting element in the promoter of human ether à go-go 1 potassium channel gene mediates repression by calcitriol in human cervical cancer cells.

The human ether à go-go 1 potassium channel (hEAG1) is required for cell cycle progression and proliferation of cancer cells. Inhibitors of hEAG1 activity and expression represent potential therapeutic drugs in cancer. Previously, we have shown that hEAG1 expression is downregulated by calcitriol in a variety of cancer cells. Herein, we provided evidence on the regulatory mechanism involved in such repressive effect in cells derived from human cervical cancer. Our results indicate that repression by calcitriol occurs at the transcriptional level and involves a functional negative vitamin D response element (nVDRE) E-box type in the hEAG1 promoter. The described mechanism in this work implies that a protein complex formed by the vitamin D receptor-interacting repressor, the vitamin D receptor, the retinoid X receptor, and the Williams syndrome transcription factor interact with the nVDRE in the hEAG1 promoter in the absence of ligand. Interestingly, all of these transcription factors except the vitamin D receptor-interacting repressor are displaced from hEAG1 promoter in the presence of calcitriol. Our results provide novel mechanistic insights into calcitriol mode of action in repressing hEAG1 gene expression.

A PCR procedure for the detection of Giardia intestinalis cysts and Escherichia coli in lettuce.

Giardia intestinalis is a pathogen associated with foodborne outbreaks and Escherichia coli is commonly used as a marker of faecal contamination. Implementation of routine identification methods of G. intestinalis is difficult for the analysis of vegetables and the microbiological detection of E. coli requires several days. This study proposes a PCR-based assay for the detection of E. coli and G. intestinalis cysts using crude DNA isolated from artificially contaminated lettuce. The G. intestinalis and E. coli PCR assays targeted the ß-giardin and uidA genes, respectively, and were 100% specific. Forty lettuces from local markets were analysed by both PCR and light microscopy and no cysts were detected, the calculated detection limit was 20 cysts per gram of lettuce; however, by PCR, E. coli was detected in eight of ten randomly selected samples of lettuce. These data highlight the need to validate procedures for routine quality assurance. These PCR-based assays can be employed as alternative methods for the detection of G. intestinalis and E. coli and have the potential to allow for the automation and simultaneous detection of protozoa and bacterial pathogens in multiple samples. Significance and impact of the study: There are few studies for Giardia intestinalis detection in food because methods for its identification are difficult for routine implementation. Here, we developed a PCR-based method as an alternative to the direct observation of cysts in lettuce by light microscopy. Additionally, Escherichia coli was detected by PCR and the sanitary quality of lettuce was evaluated using molecular and standard microbiological methods. Using PCR, the detection probability of Giardia cysts inoculated onto samples of lettuce was improved compared to light microscopy, with the advantage of easy automation. These methods may be employed to perform timely and affordable detection of foodborne pathogens.

DNA duplex stability as discriminative characteristic for Escherichia coli σ(54)- and σ(28)- dependent promoter sequences.

The advent of modern high-throughput sequencing has made it possible to generate vast quantities of genomic sequence data. However, the processing of this volume of information, including prediction of gene-coding and regulatory sequences remains an important bottleneck in bioinformatics research. In this work, we integrated DNA duplex stability into the repertoire of a Neural Network (NN) capable of predicting promoter regions with augmented accuracy, specificity and sensitivity. We took our method beyond a simplistic analysis based on a single sigma subunit of RNA polymerase, incorporating the six main sigma-subunits of Escherichia coli. This methodology employed successfully re-discovered known promoter sequences recognized by E. coli RNA polymerase subunits σ(24), σ(28), σ(32), σ(38), σ(54) and σ(70), with highlighted accuracies for σ(28)- and σ(54)- dependent promoter sequences (values obtained were 80% and 78.8%, respectively). Furthermore, the discrimination of promoters according to the σ factor made it possible to extract functional commonalities for the genes expressed by each type of promoter. The DNA duplex stability rises as a distinctive feature which improves the recognition and classification of σ(28)- and σ(54)- dependent promoter sequences. The findings presented in this report underscore the usefulness of including DNA biophysical parameters into NN learning algorithms to increase accuracy, specificity and sensitivity in promoter beyond what is accomplished based on sequence alone.

CDBProm: the Comprehensive Directory of Bacterial Promoters.

The decreasing cost of whole genome sequencing has produced high volumes of genomic information that require annotation. The experimental identification of promoter sequences, pivotal for regulating gene expression, is a laborious and cost-prohibitive task. To expedite this, we introduce the Comprehensive Directory of Bacterial Promoters (CDBProm), a directory of in-silico predicted bacterial promoter sequences. We first identified that an Extreme Gradient Boosting (XGBoost) algorithm would distinguish promoters from random downstream regions with an accuracy of 87%. To capture distinctive promoter signals, we generated a second XGBoost classifier trained on the instances misclassified in our first classifier. The predictor of CDBProm is then fed with over 55 million upstream regions from more than 6000 bacterial genomes. Upon finding potential promoter sequences in upstream regions, each promoter is mapped to the genomic data of the organism, linking the predicted promoter with its coding DNA sequence, and identifying the function of the gene regulated by the promoter. The collection of bacterial promoters available in CDBProm enables the quantitative analysis of a plethora of bacterial promoters. Our collection with over 24 million promoters is publicly available at https://aw.iimas.unam.mx/cdbprom/.

Spinal motoneurons respond aberrantly to serotonin in a rabbit model of cerebral palsy.

Cerebral palsy (CP) is caused by a variety of factors that damage the developing central nervous system. Impaired motor control, including muscle stiffness and spasticity, is the hallmark of spastic CP. Rabbits that experience hypoxic-ischemic (HI) injury in utero (at 70-80% gestation) are born with muscle stiffness, hyperreflexia, and, as recently discovered, increased serotonin (5-HT) in the spinal cord. To determine whether serotonergic modulation of spinal motoneurons (MNs) contributes to motor deficits, we performed ex vivo whole cell patch clamp in neonatal rabbit spinal cord slices at postnatal day (P) 0-5. HI MNs responded to application of α-methyl 5-HT (a 5-HT 1 /5-HT 2 receptor agonist) and citalopram (a selective 5-HT reuptake inhibitor) with hyperpolarization of persistent inward currents and threshold voltage for action potentials, reduced maximum firing rate, and an altered pattern of spike frequency adaptation while control MNs did not exhibit any of these responses. To further explore the differential sensitivity of MNs to 5-HT, we performed immunohistochemistry for inhibitory 5-HT 1A receptors in lumbar spinal MNs at P5. Fewer HI MNs expressed the 5-HT 1A receptor compared to age-matched controls. This suggests many HI MNs lack a normal mechanism of central fatigue mediated by 5-HT 1A receptors. Other 5-HT receptors (including 5-HT 2 ) are likely responsible for the robust increase in HI MN excitability. In summary, by directly exciting MNs, the increased concentration of spinal 5-HT in HI rabbits can cause MN hyperexcitability, muscle stiffness, and spasticity characteristic of CP. Therapeutic strategies that target serotonergic neuromodulation may be beneficial to individuals with CP. Key points: After prenatal hypoxia-ischemia (HI), neonatal rabbits that show hypertonia are known to have higher levels of spinal serotoninWe tested responsivity of spinal motoneurons (MNs) in neonatal control and HI rabbits to serotonin using whole cell patch clampMNs from HI rabbits showed a more robust excitatory response to serotonin than control MNs, including hyperpolarization of the persistent inward current and threshold for action potentials, larger post-inhibitory rebound, and less spike frequency adaptation Based on immunohistochemistry of lumbar MNs, fewer HI MNs express inhibitory 5HT 1A receptors than control MNs, which could account for the more robust excitatory response of HI MNs. These results suggest that after HI injury, the increased serotonin could trigger a cascade of events leading to muscle stiffness and altered motor unit development.

Explainable artificial intelligence as a reliable annotator of archaeal promoter regions.

Archaea are a vast and unexplored cellular domain that thrive in a high diversity of environments, having central roles in processes mediating global carbon and nutrient fluxes. For these organisms to balance their metabolism, the appropriate regulation of their gene expression is essential. A key momentum in regulating genes responsible for the life maintenance of archaea is when transcription factor proteins bind to the promoter element. This DNA segment is conserved, which enables its exploration by machine learning techniques. Here, we trained and tested a support vector machine with 3935 known archaeal promoter sequences. All promoter sequences were coded into DNA Duplex Stability. After, we performed a model interpretation task to map the decision pattern of the classification procedure. We also used a dataset of known-promoter sequences for validation. Our results showed that an AT rich region around position - 27 upstream (relative to the start TSS) is the most conserved in the analyzed organisms. In addition, we were able to identify the BRE element (- 33), the PPE (at - 10) and a position at + 3, that provides a more understandable picture of how promoters are organized in all the archaeal organisms. Finally, we used the interpreted model to identify potential promoter sequences of 135 unannotated organisms, delivering regulatory regions annotation of archaea in a scale never accomplished before ( https://pcyt.unam.mx/gene-regulation/ ). We consider that this approach will be useful to understand how gene regulation is achieved in other organisms apart from the already established transcription factor binding sites.

Differentially regulated targets in the fast-acting antidepressant effect of (R)-ketamine: A systems biology approach.

Approximately two-thirds of patients with major depressive disorder (MDD) fail to respond to conventional antidepressants, suggesting that additional mechanisms are involved in the MDD pathophysiology. In this scenario, the glutamatergic system represents a promising therapeutic target for treatment-resistant depression. To our knowledge, this is the first study using semantic approach with systems biology to identify potential targets involved in the fast-acting antidepressant effects of ketamine and its enantiomers as well as identifying specific targets of (R)-ketamine. We performed a systematic review, followed by a semantic analysis and functional gene enrichment to identify the main biological processes involved in the therapeutic effects of these agents. Protein-protein interaction networks were constructed, and the genes exclusively regulated by (R)-ketamine were explored. We found that the regulation of α-Amino-3-Hydroxy-5-Methyl-4-Isoxazolepropionic Acid (AMPA) receptor and N-methyl-d-aspartate (NMDA) receptor subunits-Postsynaptic Protein 95 (PSD-95), Brain Derived Neurotrophic Factor (BDNF), and Tyrosine Receptor Kinase B (TrkB) are shared by the three-antidepressant agents, reinforcing the central role of the glutamatergic system and neurogenesis on its therapeutic effects. Differential regulation of Transforming Growth Factor Beta 1 (TGF-ß1) receptors-Mitogen-Activated Protein Kinases (MAPK's), Receptor Activator of Nuclear Factor-Kappa Beta Ligand (RANKL), and Serotonin Transporter (SERT) seems to be particularly involved in (R)-ketamine antidepressant effects. Our data helps further studies investigating the relationship between these targets and the mechanisms of (R)-ketamine and searching for other therapeutic compounds that share the regulation of these specific biomolecules. Ultimately, this study could contribute to improve the fast management of depressive-like symptoms with less detrimental side effects than ketamine and (S)-ketamine.

ß-(1 → 3)(1 → 6)glucan from Schizophyllum commune 227E.32: High yield production via glucose/xylose co-metabolization.

A co-metabolization of xylose and glucose by Schizophyllum commune 227E.32 wild mushroom for exopolysaccharide (EPS) production is presented. Cultivations performed with S. commune 227E.32 at different xylose concentrations demonstrated that the concentration of 50 g·L-1 of xylose achieved the highest EPS production, around 4.46 g·L-1. Scale-up in a stirred tank reactor (STR) was performed. 10 % inoculum showed the highest cost/benefit ratio regarding sugar conversion and EPS production (Y P/S = 0.90 g·g-1), achieving 1.82 g·L-1 of EPS. Isolation, purification, and characterization were conducted with EPS produced in flasks and STR. GC-MS analysis showed glucose as main monosaccharide constituents for both isolates. 13C NMR and HSQC-edited showed that both EPS isolated consisted of a ß-D-Glcp (1 â†’ 3) main chain, partially substituted at O-6 with nonreducing ß-D-Glcp ends on every third residue, similar to ß-D-glucan isolated from S. commune basidiomes known as schizophyllan (SPG). The Mw was determined by GPC to 1.5 × 106 Da (flasks) and 1.1 × 106 Da (STR). AFM topographs revealed a semi-flexible appearance of the ß-D-glucan, consistent with the triple helical structures adopted by SPG and overall contour length consistent with a high molar mass.

Stratifying risk outcomes among adult COVID-19 inpatients with high flow oxygen: The R4 score.

BACKGROUND: High flow oxygen therapy (HFO) is a widely used intervention for pulmonary complications. Amid the coronavirus infectious disease 2019 (COVID-19) pandemic, HFO became a popular alternative to conventional oxygen supplementation therapies. Risk stratification tools have been repurposed -and new ones developed- to estimate outcome risks among COVID-19 patients. This study aims to provide a simple risk stratification system to predict invasive mechanical ventilation (IMV) or death among COVID-19 inpatients on HFO. METHODS: Among 529 adult inpatients with COVID-19 pneumonia, we selected unadjusted clinical risk factors for developing the composite endpoint of IMV or death. The risk for the primary outcome by each category was estimated using a Cox proportional hazards model. Bootstrapping was used to validate the results. RESULTS: Age above 62, eGFR under 60 ml/min, room air SpO2 ≤89 % upon admission, history of hypertension, history of diabetes, and any comorbidity (cancer, cardiovascular disease, COPD/ asthma, hypothyroidism, or autoimmune disease) were considered for the score. Each of the six criteria scored 1 point. The score was further simplified into 4 categories: 1) 0 criteria, 2) 1 criterion, 3) 2-3 criteria, and 4) ≥4 criteria. Taking the first category as the reference, risk estimates for the primary endpoint were HR; 2.94 [1.67 - 5.26], 4.08 [2.63 - 7.05], and 6.63 [3.74 - 11.77], respectively. In ROC analysis, the AUC for the model was 0.72. CONCLUSIONS: Our score uses simple criteria to estimate the risk for IMV or death among COVID-19 inpatients with HFO. Higher category reflects consistent increases in risk for the endpoint.