Ptenb Mediates Gastrulation Cell Movements via Cdc42/AKT1 in Zebrafish

Phosphatidylinositol 3-kinase (PI3 kinase) mediates gastrulation cell migration in zebrafish via its regulation of PIP2/PIP3 balance. Although PI3 kinase counter enzyme PTEN has also been reported to be essential for gastrulation, its role in zebrafish gastrulation has been controversial due to the lack of gastrulation defects in pten-null mutants. To clarify this issue, we knocked down a pten isoform, ptenb by using anti-sense morpholino oligos (MOs) in zebrafish embryos and found that ptenb MOs inhibit convergent extension by affecting cell motility and protrusion during gastrulation. The ptenb MO-induced convergence defect could be rescued by a PI3-kinase inhibitor, LY294002 and by overexpressing dominant negative Cdc42. Overexpression of human constitutively active akt1 showed similar convergent extension defects in zebrafish embryos. We also observed a clear enhancement of actin polymerization in ptenb morphants under cofocal microscopy and in actin polymerization assay. These results suggest that Ptenb by antagonizing PI3 kinase and its downstream Akt1 and Cdc42 to regulate actin polymerization that is critical for proper cell motility and migration control during gastrulation in zebrafish

A retrospective analysis of normal saline and lactated ringers as resuscitation fluid in sepsis

BackgroundThe Surviving Sepsis Campaign suggested preferential resuscitation with balanced crystalloids, such as Lactated Ringer’s (LR), although the level of recommendation was weak, and the quality of evidence was low. Past studies reported an association of unbalanced solutions, such as normal saline (NS), with increased AKI risks, metabolic acidosis, and prolonged ICU stay, although some of the findings are conflicting. We have compared the outcomes with the preferential use of normal saline vs. ringer’s lactate in a cohort of sepsis patients.MethodWe performed a retrospective cohort analysis of patients visiting the ED of 19 different Mayo Clinic sites between August 2018 to November 2020 with sepsis and receiving at least 30 mL/kg fluid in the first 6 h. Patients were divided into two cohorts based on the type of resuscitation fluid (LR vs. NS) and propensity-matching was done based on clinical characteristics as well as fluid amount (with 5 ml/kg). Single variable logistic regression (categorical outcomes) and Cox proportional hazards regression models were used to compare the primary and secondary outcomes between the 2 groups.ResultsOut of 2022 patients meeting our inclusion criteria; 1,428 (70.6%) received NS, and 594 (29.4%) received LR as the predominant fluid (>30 mL/kg). Patients receiving predominantly NS were more likely to be male and older in age. The LR cohort had a higher BMI, lactate level and incidence of septic shock. Propensity-matched analysis did not show a difference in 30-day and in-hospital mortality rate, mechanical ventilation, oxygen therapy, or CRRT requirement. We did observe longer hospital LOS in the LR group (median 5 vs. 4 days, p = 0.047 and higher requirement for ICU post-admission (OR: 0.70; 95% CI: 0.51–0.96; p = 0.026) in the NS group. However, these did not remain statistically significant after adjustment for multiple testing.ConclusionIn our matched cohort, we did not show any statistically significant difference in mortality rates, hospital LOS, ICU admission after diagnosis, mechanical ventilation, oxygen therapy and RRT between sepsis patients receiving lactated ringers and normal saline as predominant resuscitation fluid. Further large-scale prospective studies are needed to solidify the current guidelines on the use of balanced crystalloids

EMPress Enables Tree-Guided, Interactive, and Exploratory Analyses of Multi-omic Data Sets.

Standard workflows for analyzing microbiomes often include the creation and curation of phylogenetic trees. Here we present EMPress, an interactive web tool for visualizing trees in the context of microbiome, metabolome, and other community data scalable to trees with well over 500,000 nodes. EMPress provides novel functionality-including ordination integration and animations-alongside many standard tree visualization features and thus simplifies exploratory analyses of many forms of 'omic data.IMPORTANCE Phylogenetic trees are integral data structures for the analysis of microbial communities. Recent work has also shown the utility of trees constructed from certain metabolomic data sets, further highlighting their importance in microbiome research. The ever-growing scale of modern microbiome surveys has led to numerous challenges in visualizing these data. In this paper we used five diverse data sets to showcase the versatility and scalability of EMPress, an interactive web visualization tool. EMPress addresses the growing need for exploratory analysis tools that can accommodate large, complex multi-omic data sets

EMPress Enables Tree-Guided, Interactive, and Exploratory Analyses of Multi-omic Data Sets.

Standard workflows for analyzing microbiomes often include the creation and curation of phylogenetic trees. Here we present EMPress, an interactive web tool for visualizing trees in the context of microbiome, metabolome, and other community data scalable to trees with well over 500,000 nodes. EMPress provides novel functionality-including ordination integration and animations-alongside many standard tree visualization features and thus simplifies exploratory analyses of many forms of 'omic data.IMPORTANCE Phylogenetic trees are integral data structures for the analysis of microbial communities. Recent work has also shown the utility of trees constructed from certain metabolomic data sets, further highlighting their importance in microbiome research. The ever-growing scale of modern microbiome surveys has led to numerous challenges in visualizing these data. In this paper we used five diverse data sets to showcase the versatility and scalability of EMPress, an interactive web visualization tool. EMPress addresses the growing need for exploratory analysis tools that can accommodate large, complex multi-omic data sets