Impairments of cerebral blood flow microcirculation in rats brought on by cardiac cessation and respiratory arrest

The impairments of cerebral blood flow microcirculation brought on by cardiac and respiratory arrest were assessed with multi-modal diagnostic facilities, utilising laser speckle contrast imaging, fluorescence spectroscopy and diffuse reflectance spectroscopy. The results of laser speckle contrast imaging show a notable reduction of cerebral blood flow in small and medium size vessels during a few minutes of respiratory arrest, while the same effect was observed in large sinuses and their branches during the circulatory cessation. Concurrently, the redox ratio assessed with fluorescence spectroscopy indicates progressing hypoxia, NADH accumulation and increase of FAD consumption. The results of diffuse reflectance spectra measurements display a more rapid grow of the perfusion of deoxygenated blood in case of circulatory impairment. In addition, consequent histopathological analysis performed by using new tissue staining procedure developed in-house. It shows notably higher reduction of size of the neurons due to their wrinkling within brain tissues influenced by circulation impair. Whereas, the brain tissues altered with the respiratory arrest demonstrate focal perivascular oedema and mild hypoxic changes of neuronal morphology. Thus, the study suggests that consequences of a cessation of cerebral blood flow become more dramatic and dangerous compare to respiratory arrest

Identification of autoimmune markers in pulmonary tuberculosis

IntroductionPathogenesis of many autoimmune diseases is mainly promoted by poorly regulated and/or wrong targeted immune response to pathogens including M. tuberculosis. Autoimmunity is one of the processes with are characteristics of tuberculosis (Tbc). The aim was to determine the autoimmune clinical and immunological features in patients with pulmonary Tbc.Materials and methodsA prospective comparative study was performed in 2017 – 2019 with the inclusion of 46 patients with Tbc. The trigger factors and clinical manifestations, autoantibodies, peripheral blood B cell subsets were stained with fluorochrome-conjugated monoclonal antibodies. 40 healthy volunteers in the control group, were matched for age with no chronic diseases, contacts with TB patients and changes in their laboratory parameters. A statistical analysis was done with GraphPad Prism 6, Statistica 10 (Statsoft) and MedCalc – version 18.2.1 values.ResultsThere were no significant ASIA triggers in Tbc patients and control group. 21.1% of Tbc patients had a high level of a rheumatoid factor and in 47.4% complement system factor C3 was high; anti-MCV was detected in 60.7% of Tbc patients. Relative and absolute frequencies of “naïve” Bm1 cells and eBm5 were significantly decreased and activated pre-germinal-center Bm2’ cells were significantly increased in Tbc patients. The CD24++CD38++ B cells were increased in Tbc vs control group (10.25% vs 5.42%), p < 0.001, and 19 cell/1μL (10; 290 vs 11 cell/1μL (6; 20), p = 0.029, respectively). The frequency of CXCR3+CCR4– Tfh1 cells was significantly lower in Tbc vs control one (26.52% vs. 31.00%, p = 0.004), while CXCR3–CCR4+ Tfh2 cells were increased in Tbc (20.31% vs. controls (16.56%, p = 0.030). The absolute numbers of Tfh1 cells were decreased in the Tbc vs. control (24 cell/1μL vs. 37 cell/1μL p = 0.005).ConclusionThe results of our study showed that the detection of a rheumatoid factor, the components of complement system and anti-MCV in complex with alterations in B cells and follicular Th cell subsets may indicate a presence of autoimmunity in the pathogenesis of tuberculosis, but they are not specific. The indicators of autoimmune-related provide new opportunities in the Tbc treatment

Evaluation of global ocean–sea-ice model simulations based on the experimental protocols of the Ocean Model Intercomparison Project phase 2 (OMIP-2)

We present a new framework for global ocean–sea-ice model simulations based on phase 2 of the Ocean Model Intercomparison Project (OMIP-2), making use of the surface dataset based on the Japanese 55-year atmospheric reanalysis for driving ocean–sea-ice models (JRA55-do). We motivate the use of OMIP-2 over the framework for the first phase of OMIP (OMIP-1), previously referred to as the Coordinated Ocean–ice Reference Experiments (COREs), via the evaluation of OMIP-1 and OMIP-2 simulations from 11 state-of-the-science global ocean–sea-ice models. In the present evaluation, multi-model ensemble means and spreads are calculated separately for the OMIP-1 and OMIP-2 simulations and overall performance is assessed considering metrics commonly used by ocean modelers. Both OMIP-1 and OMIP-2 multi-model ensemble ranges capture observations in more than 80 % of the time and region for most metrics, with the multi-model ensemble spread greatly exceeding the difference between the means of the two datasets. Many features, including some climatologically relevant ocean circulation indices, are very similar between OMIP-1 and OMIP-2 simulations, and yet we could also identify key qualitative improvements in transitioning from OMIP-1 to OMIP-2. For example, the sea surface temperatures of the OMIP-2 simulations reproduce the observed global warming during the 1980s and 1990s, as well as the warming slowdown in the 2000s and the more recent accelerated warming, which were absent in OMIP-1, noting that the last feature is part of the design of OMIP-2 because OMIP-1 forcing stopped in 2009. A negative bias in the sea-ice concentration in summer of both hemispheres in OMIP-1 is significantly reduced in OMIP-2. The overall reproducibility of both seasonal and interannual variations in sea surface temperature and sea surface height (dynamic sea level) is improved in OMIP-2. These improvements represent a new capability of the OMIP-2 framework for evaluating process-level responses using simulation results. Regarding the sensitivity of individual models to the change in forcing, the models show well-ordered responses for the metrics that are directly forced, while they show less organized responses for those that require complex model adjustments. Many of the remaining common model biases may be attributed either to errors in representing important processes in ocean–sea-ice models, some of which are expected to be reduced by using finer horizontal and/or vertical resolutions, or to shared biases and limitations in the atmospheric forcing. In particular, further efforts are warranted to resolve remaining issues in OMIP-2 such as the warm bias in the upper layer, the mismatch between the observed and simulated variability of heat content and thermosteric sea level before 1990s, and the erroneous representation of deep and bottom water formations and circulations. We suggest that such problems can be resolved through collaboration between those developing models (including parameterizations) and forcing datasets. Overall, the present assessment justifies our recommendation that future model development and analysis studies use the OMIP-2 framework.This research has been supported by the Integrated Research Program for Advancing Climate Models (TOUGOU) of the Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan (grant nos. JPMXD0717935457 and JPMXD0717935561), the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) (grant no. 274762653), the Helmholtz Climate Initiative REKLIM (Regional Climate Change) and European Union's Horizon 2020 Research & Innovation program (grant nos. 727862 and 800154), the Research Council of Norway (EVA (grant no. 229771) and INES (grant no. 270061)), the US National Science Foundation (NSF) (grant no. 1852977), the National Natural Science Foundation of China (grant nos. 41931183 and 41976026), NOAA's Science Collaboration Program and administered by UCAR's Cooperative Programs for the Advancement of Earth System Science (CPAESS) (grant nos. NA16NWS4620043 and NA18NWS4620043B), and NOAA (grant no. NA18OAR4320123).Peer ReviewedPostprint (published version

Evaluation of global ocean–sea-ice model simulations based on the experimental protocols of the Ocean Model Intercomparison Project phase 2 (OMIP-2)

We present a new framework for global ocean- sea-ice model simulations based on phase 2 of the Ocean Model Intercomparison Project (OMIP-2), making use of the surface dataset based on the Japanese 55-year atmospheric reanalysis for driving ocean-sea-ice models (JRA55-do).We motivate the use of OMIP-2 over the framework for the first phase of OMIP (OMIP-1), previously referred to as the Coordinated Ocean-ice Reference Experiments (COREs), via the evaluation of OMIP-1 and OMIP-2 simulations from 11 state-of-the-science global ocean-sea-ice models. In the present evaluation, multi-model ensemble means and spreads are calculated separately for the OMIP-1 and OMIP-2 simulations and overall performance is assessed considering metrics commonly used by ocean modelers. Both OMIP-1 and OMIP-2 multi-model ensemble ranges capture observations in more than 80% of the time and region for most metrics, with the multi-model ensemble spread greatly exceeding the difference between the means of the two datasets. Many features, including some climatologically relevant ocean circulation indices, are very similar between OMIP-1 and OMIP- 2 simulations, and yet we could also identify key qualitative improvements in transitioning from OMIP-1 to OMIP- 2. For example, the sea surface temperatures of the OMIP- 2 simulations reproduce the observed global warming during the 1980s and 1990s, as well as the warming slowdown in the 2000s and the more recent accelerated warming, which were absent in OMIP-1, noting that the last feature is part of the design of OMIP-2 because OMIP-1 forcing stopped in 2009. A negative bias in the sea-ice concentration in summer of both hemispheres in OMIP-1 is significantly reduced in OMIP-2. The overall reproducibility of both seasonal and interannual variations in sea surface temperature and sea surface height (dynamic sea level) is improved in OMIP-2. These improvements represent a new capability of the OMIP-2 framework for evaluating processlevel responses using simulation results. Regarding the sensitivity of individual models to the change in forcing, the models show well-ordered responses for the metrics that are directly forced, while they show less organized responses for those that require complex model adjustments. Many of the remaining common model biases may be attributed either to errors in representing important processes in ocean-sea-ice models, some of which are expected to be reduced by using finer horizontal and/or vertical resolutions, or to shared biases and limitations in the atmospheric forcing. In particular, further efforts are warranted to resolve remaining issues in OMIP-2 such as the warm bias in the upper layer, the mismatch between the observed and simulated variability of heat content and thermosteric sea level before 1990s, and the erroneous representation of deep and bottom water formations and circulations. We suggest that such problems can be resolved through collaboration between those developing models (including parameterizations) and forcing datasets. Overall, the present assessment justifies our recommendation that future model development and analysis studies use the OMIP-2 framework

Access control model to the systems containing the interchangeable objects

This article describes the access control model which extends TBAC. The model is applied in the systems containing the interchangeable objects. Model elements and properties, are defined formall