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Background Trans-differentiation of human-induced pluripotent stem cells into neurons via Ngn2-induction (hiPSC-N) has become an efficient system to quickly generate neurons a likely significant advance for disease modeling and in vitro assay development. Recent single-cell interrogation of Ngn2-induced neurons, however, has revealed some similarities to unexpected neuronal lineages. Similarly, a straightforward method to generate hiPSC-derived astrocytes (hiPSC-A) for the study of neuropsychiatric disorders has also been described. Results Here, we examine the homogeneity and similarity of hiPSC-N and hiPSC-A to their in vivo counterparts, the impact of different lengths of time post Ngn2 induction on hiPSC-N (15 or 21 days), and the impact of hiPSC-N/hiPSC-A co-culture. Leveraging the wealth of existing public single-cell RNA-seq (scRNA-seq) data in Ngn2-induced neurons and in vivo data from the developing brain, we provide perspectives on the lineage origins and maturation of hiPSC-N and hiPSC-A. While induction protocols in different labs produce consistent cell type profiles, both hiPSC-N and hiPSC-A show significant heterogeneity and similarity to multiple in vivo cell fates, and both more precisely approximate their in vivo counterparts when co-cultured. Gene expression data from the hiPSC-N show enrichment of genes linked to schizophrenia (SZ) and autism spectrum disorders (ASD) as has been previously shown for neural stem cells and neurons. These overrepresentations of disease genes are strongest in our system at early times (day 15) in Ngn2-induction/maturation of neurons, when we also observe the greatest similarity to early in vivo excitatory neurons. We have assembled this new scRNA-seq data along with the public data explored here as an integrated biologist-friendly web-resource for researchers seeking to understand this system more deeply: https://nemoanalytics.org/p?l=DasEtAlNGN2&g=NES . Conclusions While overall we support the use of the investigated cellular models for the study of neuropsychiatric disease, we also identify important limitations. We hope that this work will contribute to understanding and optimizing cellular modeling for complex brain disorders.

Phenazine natural products/compounds possess a range of biological activities, including anti-microbial and cytotoxic, making them valuable starting materials for drug development in several therapeutic areas. These compounds are biosynthesized almost exclusively by eubacteria of both terrestrial and marine origins from erythrose 4-phosphate and phosphoenol pyruvate via the shikimate pathway. In this paper, we report isolation of actinomycete bacteria from marine sediment collected in the Trondheimfjord, Norway. Screening of the isolates for biological activity produced several “hits”, one of which was followed up by identification and purification of the active compound from the actinomycete bacterium Streptosporangium sp. The purified compound, identified as 1,6-dihydroxyphenazine-5,10-dioxide (iodinin), was subjected to extended tests for biological activity against bacteria, fungi and mammalian cells. In these tests, the iodinin demonstrated high anti-microbial and cytotoxic activity, and was particularly potent against leukaemia cell lines. This is the first report on the isolation of iodinin from a marine-derived Streptosporangium.

Regulated exocytosis establishes a narrow fusion pore as initial aqueous connection to the extracellular space, through which small transmitter molecules such as ATP can exit. Co-release of polypeptides and hormones like insulin requires further expansion of the pore. There is evidence that pore expansion is regulated and can fail in diabetes and neurodegenerative disease. Here, we report that the cAMP-sensor Epac2 (Rap-GEF4) controls fusion pore behavior by acutely recruiting two pore-restricting proteins, amisyn and dynamin-1, to the exocytosis site in insulin-secreting beta-cells. cAMP elevation restricts and slows fusion pore expansion and peptide release, but not when Epac2 is inactivated pharmacologically or in Epac2 -/- ( Rapgef4 -/- ) mice. Consistently, overexpression of Epac2 impedes pore expansion. Widely used antidiabetic drugs (GLP-1 receptor agonists and sulfonylureas) activate this pathway and thereby paradoxically restrict hormone release. We conclude that Epac2/cAMP controls fusion pore expansion and thus the balance of hormone and transmitter release during insulin granule exocytosis. Insulin is the hormone that signals to the body to take up sugar from the blood. Specialized cells in the pancreas – known as β-cells – release insulin after a meal. Before that, insulin molecules are stored in tiny granules inside the β-cells; these granules must fuse with the cells’ surface membranes to release their contents. The first step in this process creates a narrow pore that allows small molecules, but not the larger insulin molecules, to seep out. The pore then widens to release the insulin. Since the small molecules are known to act locally in the pancreas, it is possible that this “molecular sieve” is biologically important. Yet it is not clear how the pore widens. One of the problems for people with type 2 diabetes is that they release less insulin into the bloodstream. Two kinds of drugs used to treat these patients work by stimulating β-cells to release their insulin. One way to achieve this is by raising the levels of a small molecule called cAMP, which is well known to help prepare insulin granules for release. The cAMP molecule also seems to slow the widening of the pore, and Gucek et al. have now investigated how this happens at a molecular level. By observing individual granules of human β-cells using a special microscope, Gucek et al. could watch how different drugs affect pore widening and content release. They also saw that cAMP activated a protein called Epac2, which then recruited two other proteins – amisyn and dynamin – to the small pores. These two proteins together then closed the pore, rather than expanding it to let insulin out. Type 2 diabetes patients sometimes have high levels of amisyn in their β-cells, which could explain why they do not release enough insulin. The microscopy experiments also revealed that two common anti-diabetic drugs activate Epac2 and prevent the pores from widening, thereby counteracting their positive effect on insulin release. The combined effect is likely a shift in the balance between insulin and the locally acting small molecules. These findings suggest that two common anti-diabetic drugs activate a common mechanism that may lead to unexpected outcomes, possibly even reducing how much insulin the β-cells can release. Future studies in mice and humans will have to investigate these effects in whole organisms.

An eight-year long reanalysis of atmospheric composition data covering the period 2003–2010 was constructed as part of the FP7-funded Monitoring Atmospheric Composition and Climate project by assimilating satellite data into a global model and data assimilation system. This reanalysis provides fields of chemically reactive gases, namely carbon monoxide, ozone, nitrogen oxides, and formaldehyde, as well as aerosols and greenhouse gases globally at a horizontal resolution of about 80 km for both the troposphere and the stratosphere. This paper describes the assimilation system for the reactive gases and presents validation results for the reactive gas analysis fields to document the data set and to give a first indication of its quality. Tropospheric CO values from the MACC reanalysis are on average 10–20% lower than routine observations from commercial aircrafts over airports through most of the troposphere, and have larger negative biases in the boundary layer at urban sites affected by air pollution, possibly due to an underestimation of CO or precursor emissions. Stratospheric ozone fields from the MACC reanalysis agree with ozonesondes and ACE-FTS data to within ±10% in most seasons and regions. In the troposphere the reanalysis shows biases of −5% to +10% with respect to ozonesondes and aircraft data in the extratropics, but has larger negative biases in the tropics. Area-averaged total column ozone agrees with ozone fields from a multi-sensor reanalysis data set to within a few percent. NO2 fields from the reanalysis show the right seasonality over polluted urban areas of the NH and over tropical biomass burning areas, but underestimate wintertime NO2 maxima over anthropogenic pollution regions and overestimate NO2 in northern and southern Africa during the tropical biomass burning seasons. Tropospheric HCHO is well simulated in the MACC reanalysis even though no satellite data are assimilated. It shows good agreement with independent SCIAMACHY retrievals over regions dominated by biogenic emissions with some anthropogenic input, such as the eastern US and China, and also over African regions influenced by biogenic sources and biomass burning.

cAMP is involved in a wide variety of cellular processes that were thought to be mediated by protein kinase A (PKA) 1 . However, cAMP also directly regulates Epac1 and Epac2, guanine nucleotide-exchange factors (GEFs) for the small GTPases Rap1 and Rap2 (refs 2 , 3 ). Unfortunately, there is an absence of tools to discriminate between PKA- and Epac-mediated effects. Therefore, through rational drug design we have developed a novel cAMP analogue, 8-(4-chloro-phenylthio)-2′- O -methyladenosine-3′,5′-cyclic monophosphate (8CPT-2Me-cAMP), which activates Epac, but not PKA, both in vitro and in vivo . Using this analogue, we tested the widespread model that Rap1 mediates cAMP-induced regulation of the extracellular signal-regulated kinase (ERK) 4 , 5 . However, both in cell lines in which cAMP inhibits growth-factor-induced ERK activation and in which cAMP activates ERK, 8CPT-2Me-cAMP did not affect ERK activity. Moreover, in cell lines in which cAMP activates ERK, inhibition of PKA and Ras, but not Rap1, abolished cAMP-mediated ERK activation. We conclude that cAMP-induced regulation of ERK and activation of Rap1 are independent processes.

Despite the developments in the global modelling of chemistry and of the parameterization of the physical processes, carbon monoxide (CO) concentrations remain underestimated during Northern Hemisphere (NH) winter by most state-of-the-art chemistry transport models. The consequential model bias can in principle originate from either an underestimation of CO sources or an overestimation of its sinks. We address both the role of surface sources and sinks with a series of MOZART (Model for Ozone And Related Tracers) model sensitivity studies for the year 2008 and compare our results to observational data from ground-based stations, satellite observations, and vertical profiles from measurements on passenger aircraft. In our base case simulation using MACCity (Monitoring Atmospheric Composition and Climate project) anthropogenic emissions, the near-surface CO mixing ratios are underestimated in the Northern Hemisphere by more than 20 ppb from December to April, with the largest bias of up to 75 ppb over Europe in January. An increase in global biomass burning or biogenic emissions of CO or volatile organic compounds (VOCs) is not able to reduce the annual course of the model bias and yields concentrations over the Southern Hemisphere which are too high. Raising global annual anthropogenic emissions with a simple scaling factor results in overestimations of surface mixing ratios in most regions all year round. Instead, our results indicate that anthropogenic CO and, possibly, VOC emissions in the MACCity inventory are too low for the industrialized countries only during winter and spring. Reasonable agreement with observations can only be achieved if the CO emissions are adjusted seasonally with regionally varying scaling factors. A part of the model bias could also be eliminated by exchanging the original resistance-type dry deposition scheme with a parameterization for CO uptake by oxidation from soil bacteria and microbes, which reduces the boreal winter dry deposition fluxes. The best match to surface observations, satellite retrievals, and aircraft observations was achieved when the modified dry deposition scheme was combined with increased wintertime road traffic emissions over Europe and North America (factors up to 4.5 and 2, respectively). One reason for the apparent underestimation of emissions may be an exaggerated downward trend in the Representative Concentration Pathway (RCP) 8.5 scenario in these regions between 2000 and 2010, as this scenario was used to extrapolate the MACCity emissions from their base year 2000. This factor is potentially amplified by a lack of knowledge about the seasonality of emissions. A methane lifetime of 9.7 yr for our basic model and 9.8 yr for the optimized simulation agrees well with current estimates of global OH, but we cannot fully exclude a potential effect from errors in the geographical and seasonal distribution of OH concentrations on the modelled CO.

A representation of atmospheric chemistry has been included in the Integrated Forecasting System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF). The new chemistry modules complement the aerosol modules of the IFS for atmospheric composition, which is named C-IFS. C-IFS for chemistry supersedes a coupled system in which chemical transport model (CTM) Model for OZone and Related chemical Tracers 3 was two-way coupled to the IFS (IFS-MOZART). This paper contains a description of the new on-line implementation, an evaluation with observations and a comparison of the performance of C-IFS with MOZART and with a re-analysis of atmospheric composition produced by IFS-MOZART within the Monitoring Atmospheric Composition and Climate (MACC) project. The chemical mechanism of C-IFS is an extended version of the Carbon Bond 2005 (CB05) chemical mechanism as implemented in CTM Transport Model 5 (TM5). CB05 describes tropospheric chemistry with 54 species and 126 reactions. Wet deposition and lightning nitrogen monoxide (NO) emissions are modelled in C-IFS using the detailed input of the IFS physics package. A 1 year simulation by C-IFS, MOZART and the MACC re-analysis is evaluated against ozonesondes, carbon monoxide (CO) aircraft profiles, European surface observations of ozone (O3), CO, sulfur dioxide (SO2) and nitrogen dioxide (NO2) as well as satellite retrievals of CO, tropospheric NO2 and formaldehyde. Anthropogenic emissions from the MACC/CityZen (MACCity) inventory and biomass burning emissions from the Global Fire Assimilation System (GFAS) data set were used in the simulations by both C-IFS and MOZART. C-IFS (CB05) showed an improved performance with respect to MOZART for CO, upper tropospheric O3, and wintertime SO2, and was of a similar accuracy for other evaluated species. C-IFS (CB05) is about 10 times more computationally efficient than IFS-MOZART.

Background Patient engagement and learning from patients’ experiences may increase patient safety and reduce the occurrence of adverse events. Most adverse events are related to surgery, and patient outcomes are positively associated with patient safety culture. This study aimed to explore former surgical patients’ perspectives and experiences of adverse events and patient safety culture during their surgical pathway and identify themes relevant to adverse event causes and quality improvement projects. Methods The design of this qualitative study was explorative, utilizing an abductive approach. We purposefully recruited former surgical patients from Norwegian user organizations based on group characteristics sampling. The participants were 57% men and 43% women, aged 35 to 64 years. We conducted 14 individual semi-structured interviews between 18/01/24 and 07/03/24 using Zoom’s video audio software, with an average duration of 65 min. We analyzed the data using Braun and Clarke’s method for reflexive thematic analysis, and generated themes by examining patterns of meaning throughout the dataset. Results Data analysis generated three themes concerning the former surgical patients’ perspectives of patient safety culture and adverse events: (1) “Personalized care and predictable pathways increase patients’ sense of safety”; (2) “Surgical patients’ involvement: Aspire to be a resource – Not a threat”; and (3) “Time to cultivate a culture that fosters improvements and reconciliation.” Conclusions This study provided insight into patients’ perspectives on adverse events and patient safety culture in the surgical context. The patients underscored the value of predictable plans in caregiving, tailored information, personalized care, and dialogue on equal terms. They considered the demand for efficiency, professional hierarchy, status, prestige, and authority to be barriers to patient engagement and safety. Interventions to improve a culture of openness, psychological safety, and organizational learning in the surgical context could increase the safety of patients and healthcare professionals. Finally, acknowledgment of adverse events, information, and follow-up were essential for patients and next of kin to move on after an adverse event.

A dynamic, first-principles process model for a steelmaking electric arc furnace has been developed. The model is an integrated part of an application designed for optimization during operation of the furnace. Special care has been taken to ensure that the non-linear model is robust and accurate enough for real-time optimization. The model is formulated in terms of state variables and ordinary differential equations and is adapted to process data using recursive parameter estimation. Compared to other models available in the literature, a focus of this model is to integrate auxiliary process data in order to best predict energy efficiency and heat transfer limitations in the furnace. Model predictions are in reasonable agreement with steel temperature and weight measurements. Simulations indicate that industrial deployment of Model Predictive Control applications derived from this process model can result in electrical energy consumption savings of 1–2%.

A model-based system for real-time monitoring and operational support has been developed for the Composition Adjustment by Sealed argon-bubbling with Oxygen Blowing (CAS-OB) process. The model of the system is based on a previously developed dynamic model using first principles, i.e., mass and energy balances, reaction kinetics, and thermodynamics. Adaptive estimation of state variables has been implemented using a Kalman filter to ensure that the model is able to correct for deviations between measured and calculated temperatures in real-time operation. The estimation technique reduces the standard deviation of the predicted end temperature from 19.5 °C to 5.5 °C in a data series with more than 1000 heats. The system also includes an endpoint optimisation, which calculates the amount of scrap or oxygen to be added to achieve the target temperature at the end of the heat. The model has been implemented in the Cybernetica® CENIT™ framework. The overall model can be regarded as a hybrid digital twin, where a first principles model is adapted in real time using process measurements. The system also includes user interfaces for operators where process predictions can be followed, and suggested optimised inputs are presented. The system has been deployed at two refining stations at SSAB Europe OY in Raahe, Finland. The optimized suggestions for oxygen and scrap are presented to the operators in the graphical user interface. A projected temperature profile is calculated into the near future using the planned operational procedure as well as the projected temperature profile using optimised inputs. Both profiles are displayed in the user interface. Based on these trajectories, the operator can decide on whether to follow the nominal trajectory, or the recommendation from the optimisation This will help the operators make better decisions, which in turn reduces the number of rejected heats in the CAS-OB process.