Aims/hypothesis
Increasing evidence suggests that environmental factors changing the normal colonisation pattern in the gut strongly influence the risk of developing autoimmune diabetes. The aim of ...this study was to investigate, both during infancy and adulthood, whether treatment with vancomycin, a glycopeptide antibiotic specifically directed against Gram-positive bacteria, could influence immune homeostasis and the development of diabetic symptoms in the NOD mouse model for diabetes.
Methods
Accordingly, one group of mice received vancomycin from birth until weaning (day 28), while another group received vancomycin from 8 weeks of age until onset of diabetes. Pyrosequencing of the gut microbiota and flow cytometry of intestinal immune cells was used to investigate the effect of vancomycin treatment.
Results
At the end of the study, the cumulative diabetes incidence was found to be significantly lower for the neonatally treated group compared with the untreated group, whereas the insulitis score and blood glucose levels were significantly lower for the mice treated as adults compared with the other groups. Mucosal inflammation was investigated by intracellular cytokine staining of the small intestinal lymphocytes, which displayed an increase in cluster of differentiation (CD)4
+
T cells producing pro-inflammatory cytokines in the neonatally treated mice. Furthermore, bacteriological examination of the gut microbiota composition by pyrosequencing revealed that vancomycin depleted many major genera of Gram-positive and Gram-negative microbes while, interestingly, one single species,
Akkermansia muciniphila
, became dominant.
Conclusions/interpretation
The early postnatal period is a critical time for microbial protection from type 1 diabetes and it is suggested that the mucolytic bacterium
A. muciniphila
plays a protective role in autoimmune diabetes development, particularly during infancy.
Full text
Available for:
EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Abstract Freeze-drying is the preferred method for stabilizing live, attenuated virus vaccines. After decades of research on several aspects of the process like the stabilization and destabilization ...mechanisms of the live, attenuated viruses during freeze-drying, the optimal formulation components and process settings are still matter of research. The molecular complexity of live, attenuated viruses, the multiple destabilization pathways and the lack of analytical techniques allowing the measurement of physicochemical changes in the antigen's structure during and after freeze-drying mean that they form a particular lyophilization challenge. The purpose of this review is to overview the available information on the development of the freeze-drying process of live, attenuated virus vaccines, herewith focusing on the freezing and drying stresses the viruses can undergo during processing as well as on the mechanisms and strategies (formulation and process) that are used to stabilize them during freeze-drying.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
MicroRNAs (miRNAs), a group of small non-coding RNAs that fine tune translation of multiple target mRNAs, are emerging as key regulators in cardiovascular development and disease. MiRNAs are involved ...in cardiac hypertrophy, heart failure and remodeling following cardiac infarction; however, miRNAs involved in hypertension have not been thoroughly investigated. We have recently reported that specific miRNAs play an integral role in Angiotensin II receptor (AT1R) signaling, especially after activation of the Gαq signaling pathway. Since AT1R blockers are widely used to treat hypertension, we undertook a detailed analysis of potential miRNAs involved in Angiotensin II (AngII) mediated hypertension in rats and hypertensive patients, using miRNA microarray and qPCR analysis. The miR-132 and miR-212 are highly increased in the heart, aortic wall and kidney of rats with hypertension (159 ± 12 mm Hg) and cardiac hypertrophy following chronic AngII infusion. In addition, activation of the endothelin receptor, another Gαq coupled receptor, also increased miR-132 and miR-212. We sought to extend these observations using human samples by reasoning that AT1R blockers may decrease miR-132 and miR-212. We analyzed tissue samples of mammary artery obtained from surplus arterial tissue after coronary bypass operations. Indeed, we found a decrease in expression levels of miR-132 and miR-212 in human arteries from bypass-operated patients treated with AT1R blockers, whereas treatment with β-blockers had no effect. Taken together, these data suggest that miR-132 and miR-212 are involved in AngII induced hypertension, providing a new perspective in hypertensive disease mechanisms.
Full text
Available for:
IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Most animal species on Earth are insects, and recent reports suggest that their abundance is in drastic decline. Although these reports come from a wide range of insect taxa and regions, the evidence ...to assess the extent of the phenomenon is sparse. Insect populations are challenging to study, and most monitoring methods are labor intensive and inefficient. Advances in computer vision and deep learning provide potential new solutions to this global challenge. Cameras and other sensors can effectively, continuously, and noninvasively perform entomological observations throughout diurnal and seasonal cycles. The physical appearance of specimens can also be captured by automated imaging in the laboratory. When trained on these data, deep learning models can provide estimates of insect abundance, biomass, and diversity. Further, deep learning models can quantify variation in phenotypic traits, behavior, and interactions. Here, we connect recent developments in deep learning and computer vision to the urgent demand for more cost-efficient monitoring of insects and other invertebrates. We present examples of sensor-based monitoring of insects. We show how deep learning tools can be applied to exceptionally large datasets to derive ecological information and discuss the challenges that lie ahead for the implementation of such solutions in entomology. We identify four focal areas, which will facilitate this transformation: 1) validation of image-based taxonomic identification; 2) generation of sufficient training data; 3) development of public, curated reference databases; and 4) solutions to integrate deep learning and molecular tools.
Full text
Available for:
BFBNIB, NMLJ, NUK, PNG, SAZU, UL, UM, UPUK
We performed triaxial compressive creep experiments on aggregates of San Carlos olivine to develop a flow law and to examine microstructural development in the dislocation‐accommodated grain boundary ...sliding regime (GBS). Each experiment included load and temperature steps to determine both the stress exponent and the activation energy. Grain boundary maps, created with electron backscatter diffraction data, were used to quantify grain size distributions for each sample. Inversion of the resulting data produced the following flow law for GBS: GBS = 104.8 ± 0.8 (σ2.9 ± 0.3/d0.7 ± 0.1) exp(−445 ± 20 kJ mol−1)/RT, with σ, d, and GBS in units of MPa, μm, and s−1, respectively. Although relatively weak, crystallographic‐preferred orientations (CPOs) have 010 maxima parallel to the compression direction along with 100 and 001 girdles perpendicular to the compression direction. CPOs and subgrain boundary misorientation axes suggest that the (010)100 slip system contributes significantly to deformation. We propose that these experimental results are best modeled by a deformation mechanism in which strain is accomplished primarily through grain boundary sliding accommodated by the motion of dislocations. Extrapolation of our flow laws to mantle conditions suggests that GBS is likely to be the dominant deformation mechanism in both lithospheric shear zones and asthenospheric flow, and therefore strong upper mantle seismic anisotropy can not be attributed solely to the dominance of dislocation creep.
Key Points
We determined a flow law for the grain boundary sliding (GBS) regime
Extrapolations of our flow law imply that GBS is dominant in the upper mantle
Observed crystallographic fabrics agree with patterns of seismic anisotropy
We examined whether metabolic conditions (MCs) during pregnancy (diabetes, hypertension, and obesity) are associated with autism spectrum disorder (ASD), developmental delays (DD), or impairments in ...specific domains of development in the offspring.
Children aged 2 to 5 years (517 ASD, 172 DD, and 315 controls) were enrolled in the CHARGE (Childhood Autism Risks from Genetics and the Environment) study, a population-based, case-control investigation between January 2003 and June 2010. Eligible children were born in California, had parents who spoke English or Spanish, and were living with a biological parent in selected regions of California. Children's diagnoses were confirmed by using standardized assessments. Information regarding maternal conditions was ascertained from medical records or structured interview with the mother.
All MCs were more prevalent among case mothers compared with controls. Collectively, these conditions were associated with a higher likelihood of ASD and DD relative to controls (odds ratio: 1.61 95% confidence interval: 1.10-2.37; odds ratio: 2.35 95% confidence interval: 1.43-3.88, respectively). Among ASD cases, children of women with diabetes had Mullen Scales of Early Learning (MSEL) expressive language scores 0.4 SD lower than children of mothers without MCs (P < .01). Among children without ASD, those exposed to any MC scored lower on all MSEL and Vineland Adaptive Behavior Scales (VABS) subscales and composites by at least 0.4 SD (P < .01 for each subscale/composite).
Maternal MCs may be broadly associated with neurodevelopmental problems in children. With obesity rising steadily, these results appear to raise serious public health concerns.
The analysis of nuclear magnetic resonance (NMR) spectra for the comprehensive and unambiguous identification and characterization of peaks is a difficult, but critically important step in all NMR ...analyses of complex biological molecular systems. Here, we introduce DEEP Picker, a deep neural network (DNN)-based approach for peak picking and spectral deconvolution which semi-automates the analysis of two-dimensional NMR spectra. DEEP Picker includes 8 hidden convolutional layers and was trained on a large number of synthetic spectra of known composition with variable degrees of crowdedness. We show that our method is able to correctly identify overlapping peaks, including ones that are challenging for expert spectroscopists and existing computational methods alike. We demonstrate the utility of DEEP Picker on NMR spectra of folded and intrinsically disordered proteins as well as a complex metabolomics mixture, and show how it provides access to valuable NMR information. DEEP Picker should facilitate the semi-automation and standardization of protocols for better consistency and sharing of results within the scientific community.
Although microstructural evolution is critical to strain‐dependent processes in Earth's mantle, flow laws for dunite have only been calibrated with low‐strain experiments. Therefore, we conducted a ...series of high‐strain torsion experiments on thin‐walled cylinders of iron‐rich olivine aggregates. Experiments were performed in a gas‐medium apparatus at 1200°C and constant strain rate. In our experiments, each at a different strain rate, a peak stress was observed followed by significant strain weakening. We first deformed samples to high enough strain that a steady state microstructure was achieved and then conducted strain rate stepping tests to characterize the creep behavior of each sample with constant microstructure. A global fit to the data yields a stress exponent of 4.1 and a grain‐size exponent of 0.73, values which agree well with those from previous small‐strain experiments conducted on olivine in the dislocation‐accommodated grain‐boundary sliding (GBS) regime. Strong crystallographic preferred orientations provide support for GBS accommodated by movement of (010)100 dislocations. The observed strain weakening is not entirely explained by grain‐size reduction; thus, we propose that the remaining 30% reduction in stress is related to CPO development. To incorporate microstructural evolution in a constitutive description of GBS in olivine, we (1) derive a flow law for high‐strain deformation with steady state microstructure, which results in an apparent stress exponent of 5.0, and (2) present a system of evolution equations that recreate the observed strain weakening. Our results corroborate flow‐law parameters and microstructural observations from low‐strain experiments and provide a means for incorporating strain weakening into geodynamic simulations.
Key Points
We explore the high‐strain behavior of olivine with a novel experiment design
We quantify the effect of grain size and crystallographic fabric on deformation
We develop a model that describes the strain dependence of olivine deformation
PDF
