Loss of murine Paneth cell function alters the immature intestinal microbiome and mimics changes seen in neonatal necrotizing enterocolitis

Necrotizing enterocolitis (NEC) remains the leading cause of gastrointestinal morbidity and mortality in premature infants. Human and animal studies suggest a role for Paneth cells in NEC pathogenesis. Paneth cells play critical roles in host-microbial interactions and epithelial homeostasis. The ramifications of eliminating Paneth cell function on the immature host-microbial axis remains incomplete. Paneth cell function was depleted in the immature murine intestine using chemical and genetic models, which resulted in intestinal injury consistent with NEC. Paneth cell depletion was confirmed using histology, electron microscopy, flow cytometry, and real time RT-PCR. Cecal samples were analyzed at various time points to determine the effects of Paneth cell depletion with and without Klebsiella gavage on the microbiome. Deficient Paneth cell function induced significant compositional changes in the cecal microbiome with a significant increase in Enterobacteriacae species. Further, the bloom of Enterobacteriaceae species that occurs is phenotypically similar to what is seen in human NEC. This further strengthens our understanding of the importance of Paneth cells to intestinal homeostasis in the immature intestine

Simultaneous Disruption of Mouse ASIC1a, ASIC2 and ASIC3 Genes Enhances Cutaneous Mechanosensitivity

Three observations have suggested that acid-sensing ion channels (ASICs) might be mammalian cutaneous mechanoreceptors; they are structurally related to Caenorhabditis elegans mechanoreceptors, they are localized in specialized cutaneous mechanosensory structures, and mechanical displacement generates an ASIC-dependent depolarization in some neurons. However, previous studies of mice bearing a single disrupted ASIC gene showed only subtle or no alterations in cutaneous mechanosensitivity. Because functional redundancy of ASIC subunits might explain limited phenotypic alterations, we hypothesized that disrupting multiple ASIC genes would markedly impair cutaneous mechanosensation. We found the opposite. In behavioral studies, mice with simultaneous disruptions of ASIC1a, -2 and -3 genes (triple-knockouts, TKOs) showed increased paw withdrawal frequencies when mechanically stimulated with von Frey filaments. Moreover, in single-fiber nerve recordings of cutaneous afferents, mechanical stimulation generated enhanced activity in A-mechanonociceptors of ASIC TKOs compared to wild-type mice. Responses of all other fiber types did not differ between the two genotypes. These data indicate that ASIC subunits influence cutaneous mechanosensitivity. However, it is unlikely that ASICs directly transduce mechanical stimuli. We speculate that physical and/or functional association of ASICs with other components of the mechanosensory transduction apparatus contributes to normal cutaneous mechanosensation

Tumor Necrosis Factor Induces Developmental Stage-Dependent Structural Changes in the Immature Small Intestine

Background. Premature infants are commonly subject to intestinal inflammation. Since the human small intestine does not reach maturity until term gestation, premature infants have a unique challenge, as either acute or chronic inflammation may alter the normal development of the intestinal tract. Tumor necrosis factor (TNF) has been shown to acutely alter goblet cell numbers and villus length in adult mice. In this study we tested the effects of TNF on villus architecture and epithelial cells at different stages of development of the immature small intestine. Methods. To examine the effects of TNF-induced inflammation, we injected acute, brief, or chronic exposures of TNF in neonatal and juvenile mice. Results. TNF induced significant villus blunting through a TNF receptor-1 (TNFR1) mediated mechanism, leading to loss of villus area. This response to TNFR1 signaling was altered during intestinal development, despite constant TNFR1 protein expression. Acute TNF-mediated signaling also significantly decreased Paneth cells. Conclusions. Taken together, the morphologic changes caused by TNF provide insight as to the effects of inflammation on the developing intestinal tract. Additionally, they suggest a mechanism which, coupled with an immature immune system, may help to explain the unique susceptibility of the immature intestine to inflammatory diseases such as NEC

The difference in mean arterial pressure induced by remimazolam compared to etomidate in the presence of fentanyl at tracheal intubation: A randomized controlled trial

Background: Combined use of hypnotic and opioids during anesthesia inductions decreases blood pressure. Post-induction hypotension (PIHO) is the most common side effect of anesthesia induction. We aimed to compare the difference in mean arterial pressure (MAP) induced by remimazolam with that induced by etomidate in the presence of fentanyl at tracheal intubation.Methods: We assessed 138 adult patients with American Society of Anesthesiologists physical status I–II who underwent elective urological surgery. Patients were randomly allocated to receive either remimazolam or etomidate as alterative hypnotic in the presence of fentanyl during anesthesia induction. Comparable BIS values were achieved in both groups. The primary outcome was the difference in the MAP at tracheal intubation. The secondary outcomes included the characteristics of anesthesia, surgery, and adverse effects.Results: The MAP was higher in the etomidate group than in the remimazolam group at tracheal intubation (108 [22] mmHg vs. 83 [16] mmHg; mean difference, −26; 95% confidence interval [CI], −33 to −19; p < 0.0001). Heart rate was significantly higher in the etomidate group than in the remimazolam group at tracheal intubation. The patients’ condition warranted the administration of ephedrine more frequently in the remimazolam group (22%) than in the etomidate group (5%) (p = 0.0042) during anesthesia induction. The remimazolam group had a lower incidence of hypertension (0% vs. 9%, p = 0.0133), myoclonus (0% vs. 47%, p < 0.001), and tachycardia (16% vs. 35%, p = 0.0148), and a higher incidence of PIHO (42% vs. 5%, p = 0.001) than the etomidate group during anesthesia induction.Conclusion: Remimazolam was associated with lower MAP and lower heart rate compared to etomidate in the presence of fentanyl at tracheal intubation. Patients in the remimazolam group had a higher incidence of PIHO, and their condition warranted the administration of ephedrine more frequently than in the etomidate group during anesthesia induction

Effects of Climate and Land Use changes on Vegetation Dynamics in the Yangtze River Delta, China Based on Abrupt Change Analysis

Vegetation dynamics is thought to be affected by climate and land use changes. However, how the effects vary after abrupt vegetation changes remains unclear. Based on the Mann-Kendall trend and abrupt change analysis, we monitored vegetation dynamics and its abrupt change in the Yangtze River delta during 1982–2016. With the correlation analysis, we revealed the relationship of vegetation dynamics with climate changes (temperature and precipitation) pixel-by-pixel and then with land use changes analysis we studied the effects of land use changes (unchanged or changed land use) on their relationship. Results showed that: (1) the Normalized Vegetation Index (NDVI) during growing season that is represented as GSN (growing season NDVI) showed an overall increasing trend and had an abrupt change in 2000. After then, the area percentages with decreasing GSN trend increased in cropland and built-up land, mainly located in the eastern, while those with increasing GSN trend increased in woodland and grassland, mainly located in the southern. Changed land use, except the land conversions from/to built-up land, is more favor for vegetation greening than unchanged land use (2) after abrupt change, the significant positive correlation between precipitation and GSN increased in all unchanged land use types, especially for woodland and grassland (natural land use) and changed land use except built-up land conversion. Meanwhile, the insignificant positive correlation between temperature and GSN increased in woodland, while decreased in the cropland and built-up land in the northwest (3) after abrupt change, precipitation became more important and favor, especially for natural land use. However, temperature became less important and favor for all land use types, especially for built-up land. This research indicates that abrupt change analysis will help to effectively monitor vegetation trend and to accurately assess the relationship of vegetation dynamics with climate and land use changes

Nonlinear Characteristics of NPP Based on Ensemble Empirical Mode Decomposition from 1982 to 2015—A Case Study of Six Coastal Provinces in Southeast China

Monitoring vegetation net primary productivity (NPP) is very important for evaluating ecosystem health. However, the nonlinear characteristics of the vegetation NPP remain unclear in the six provinces along the Maritime Silk Road in China. In this study, using NDVI and meteorological data from 1982 to 2015, NPP was estimated with the Carnegie-Ames-Stanford Approach (CASA) model based on vegetation type dynamics, and its nonlinear characteristics were explored through the ensemble empirical mode decomposition (EEMD) method. The results showed that: (1) The total NPP in the changed vegetation types caused by ecological engineering and urbanization increased but decreased in those caused by agricultural reclamation and vegetation destruction, (2) the vegetation NPP was dominated by interannual variations, mainly in the middle of the study area, while by long-term trends, mainly in the southwest and northeast, (3) for most of the vegetation types, NPP was dominated by the monotonically increasing trend. Although vegetation NPP in the urban land mainly showed a decreasing trend (monotonic decrease and decrease from increase), there were large areas in which NPP increased from decreasing. Although vegetation NPP in the farmland mainly showed increasing trends, there were large areas that faced the risk of NPP decreasing; (4) dynamical changes of vegetation type by agricultural reclamation and vegetation destruction made the NPP trend monotonically decrease in large areas, leading to ecosystem degradation, while those caused by urbanization and ecological engineering mainly made the NPP increase from decreasing, leading to later recovery from early degradation. Our results highlighted the importance of vegetation type dynamics for accurately estimating vegetation NPP, as well as for assessing their impacts, and the importance of nonlinear analysis for deepening our understanding of vegetation NPP changes

Nonlinear Characteristics of NPP Based on Ensemble Empirical Mode Decomposition from 1982 to 2015—A Case Study of Six Coastal Provinces in Southeast China

Monitoring vegetation net primary productivity (NPP) is very important for evaluating ecosystem health. However, the nonlinear characteristics of the vegetation NPP remain unclear in the six provinces along the Maritime Silk Road in China. In this study, using NDVI and meteorological data from 1982 to 2015, NPP was estimated with the Carnegie-Ames-Stanford Approach (CASA) model based on vegetation type dynamics, and its nonlinear characteristics were explored through the ensemble empirical mode decomposition (EEMD) method. The results showed that: (1) The total NPP in the changed vegetation types caused by ecological engineering and urbanization increased but decreased in those caused by agricultural reclamation and vegetation destruction, (2) the vegetation NPP was dominated by interannual variations, mainly in the middle of the study area, while by long-term trends, mainly in the southwest and northeast, (3) for most of the vegetation types, NPP was dominated by the monotonically increasing trend. Although vegetation NPP in the urban land mainly showed a decreasing trend (monotonic decrease and decrease from increase), there were large areas in which NPP increased from decreasing. Although vegetation NPP in the farmland mainly showed increasing trends, there were large areas that faced the risk of NPP decreasing; (4) dynamical changes of vegetation type by agricultural reclamation and vegetation destruction made the NPP trend monotonically decrease in large areas, leading to ecosystem degradation, while those caused by urbanization and ecological engineering mainly made the NPP increase from decreasing, leading to later recovery from early degradation. Our results highlighted the importance of vegetation type dynamics for accurately estimating vegetation NPP, as well as for assessing their impacts, and the importance of nonlinear analysis for deepening our understanding of vegetation NPP changes

Appling the One-Class Classification Method of Maxent to Detect an Invasive Plant Spartina alterniflora with Time-Series Analysis

Spartina alterniflora has become the main invasive plant along the Chinese coast and now threatens the local ecological environment. Accurately monitoring the distribution of S. alterniflora is urgent and essential for developing cost-effective control strategies. In this study, we applied the One-Class Classification (OCC) methods of Maximum entropy (Maxent) and Biased Support Vector Machine (BSVM) based on Landsat time-series imagery to detect the species on the middle coast of Jiangsu in east China. We conducted four experimental setups (i.e., single-scene analysis, time-series analysis, Normalized Difference Vegetation Index (NDVI) time-series analysis and a compressed time-series analysis), using OCC methods to recognize the species. Then, we tested the performance of a compressed time-series model for S. alterniflora detection and evaluated the expansibility of this approach when it was applied to a larger region. Our principal findings are as follows: (1) Maxent and BSVM performed equally well, and Maxent appeared to have a more balanced performance over the summer months; (2) the Maxent model with the Default Parameter Set (Maxent-DPS) showed a slightly higher accuracy and more overfitting than Maxent with the Akaike Information Criterion corrected for small samples sizes (AICc)-selected parameter set model, but a t-test found no significant difference between these two settings; (3) April and December were deemed to be important periods for the detection of S. alterniflora; (4) a compressed time-series analysis model—including only three variables (December NDVI, March green and the third Principal Component in January, PC3)—yielded higher accuracy than single-scene analyses, which indicated that time-series analysis can better detect S. alterniflora than single-scene analyses; and (5) the Maxent model using the reconstructed optimal variables and 70 training samples over a larger region produced encouraging results with an overall accuracy of 90.88% and a Kappa of 0.78. The one-class classification method combined with a phenology-based detection strategy is therefore promising for the application of the long-term detection of S. alterniflora over extended areas