Vancomycin-Induced Changes in Host Immunity and Behavior: Comparative Genomic and Metagenomic Analysis in C57BL/6 and BALB/c Mice

Digestive Diseases and Sciences - The consequence of treatment with antibiotics on the gut microbiota can be destructive. The antibiotics, however, can be utilized to understand the role of gut...     

Nonlinear permanent migration response to climatic variations but minimal response to disasters

We present a microlevel study to simultaneously investigate the effects of variations in temperature and precipitation along with sudden natural disasters to infer their relative influence on migration that is likely permanent. The study is made possible by the availability of household panel data from Indonesia with an exceptional tracking rate combined with frequent occurrence of natural disasters and significant climatic variations, thus providing a quasi-experiment to examine the influence of environment on migration. Using data on 7,185 households followed over 15 y, we analyze whole-household, province-to-province migration, which allows us to understand the effects of environmental factors on permanent moves that may differ from temporary migration. The results suggest that permanent migration is influenced by climatic variations, whereas episodic disasters tend to have much smaller or no impact on such migration. In particular, temperature has a nonlinear effect on migration such that above 25 °C, a rise in temperature is related to an increase in outmigration, potentially through its impact on economic conditions. We use these results to estimate the impact of projected temperature increases on future permanent migration. Though precipitation also has a similar nonlinear effect on migration, the effect is smaller than that of temperature, underscoring the importance of using an expanded set of climatic factors as predictors of migration. These findings on the minimal influence of natural disasters and precipitation on permanent moves supplement previous findings on the significant role of these variables in promoting temporary migration.Human migration has been identified as a potentially important response to climate change. Where climate change makes habitation in certain places less desirable or even impossible, people may respond by moving elsewhere. However, the idea that environmental change induces people to migrate remains a widely contested topic, especially given recent findings suggesting that environmental changes may also constrain movement (1–3). Historically, there has been a paucity of empirical demonstrations of environmental effects on population mobility, partly due to sparse data and partly because migration studies have tended to focus on further exploration of social and economic predictors of migration that have already been established as primary drivers. More recently however, new empirical approaches to exploring the relationship between migration and climate change have emerged.Based on a review of the existing literature (SI Text, Literature Review), there is conflicting evidence on the effects of climatic variations and natural disasters on migration, partly arising from the inability to distinguish permanent moves from temporary ones, especially in the case of macrolevel studies that analyze aggregate flows of people. Furthermore, the effects may vary significantly by distance of migration destination, which may also confound the overall effect of environmental factors on migration. Above all, most studies at the microlevel do not simultaneously examine the effects of both disasters and climatic changes on migration, and often use only one aspect of climate, generally variation in rainfall. However, precipitation and temperature are historically correlated and to infer an unbiased effect of either one on migration probability, both need to be included in the model (4).The current study therefore attempts to improve on the existing studies. This study is, to our knowledge, the first at a microlevel to simultaneously explore the effects of sudden natural disasters and climatic variations on permanent migration of the whole household. (Household migration can take several forms: migration of a single member or individual migration; migration of one or more members of the household or split household migration; and migration of whole household, which includes migration of the entire household along with the head of household.) In doing so, we test the effect of temperature along with precipitation on migration decision. We include a summary that allows a quick comparison of the methodology used in our study compared with previous studies in terms of the choice of environmental variables to predict migration (Table S1). Prior studies have primarily examined individual migration behavior, which may capture both temporary and permanent migration. In contrast, province-level migration of entire households, as we show (with the use of data that follows households over a period of 15 y), tends to be more permanent. (We hereafter use the term “permanent.”) To our knowledge, the only other studies that focus on household migration explore the mechanisms by which natural disasters can deter migration of the household or its relatives (5, 6). By studying migration behavior of the whole household, we are able to focus on permanent migration, and therefore directly test how sudden disasters along with variations in rainfall and temperature affect permanent and relatively longer distance (province-to-province) migration as opposed to temporary movement; this allows us to complement the findings in some existing studies that generally conclude that natural disasters and rainfall result in temporary and short-distance moves while providing new evidence on the temperature–migration link in the context of microlevel studies.To achieve these goals, we chose Indonesia as our study site because as the world’s largest archipelago situated in a tectonically active location, the country is highly exposed to both geologic and climatic hazards (SI Text, Background on Indonesia). In addition, as the world’s fourth most populous country with ∼40% of the labor force engaged in agriculture and more than 60% of the total population living in the coastal areas, the country is extremely vulnerable to the impacts of climate variations and extreme events (SI Text, Background on Indonesia). At the same time, the availability of household panel data with an exceptional tracking rate allows us to use a difference-in-differences approach to study the migration of households before and after disasters as well as establish a plausibly causal link between climatic variations and migration. We use the Indonesian Family Life Survey (IFLS), a household panel survey representative of ∼83% of the Indonesian population from 13 of the 27 provinces in 1993 (Fig. S1). The IFLS provides data on 7,185 original households, followed over a period of 15 y (Materials and Methods). The migration outcome we predict captures migration of households, which is likely permanent. We track whole-household migration for a 15-y period during which the original households are followed with a very high retention rate even after they migrate. Some 95% of the migrant households end up migrating only once and do not return to their original province during the entire 15-y period. Therefore, at least in the Indonesian case, the provincial level migration of households seems to be permanent (see SI Text, Internal Migration in Indonesia, for more on internal migration in Indonesia).The household panel data are supplemented with data on natural disasters taken from DesInventar database, which provides disaster-related data using information on disasters of different intensities based on preexisting official data, academic records, newspaper sources, and institutional reports. Different types of disasters may not all affect migration in the same way, thus cancelling out each other’s effects on migration. For our analysis, we therefore separately estimate the effects of each type of disaster. Furthermore, we use multiple measures to capture the different ways in which a disaster may affect the population, for three primary reasons. First, we believe that the intensity of disaster rather than simply the occurrence of disaster should more accurately predict its effect. Measures such as number of deaths, number injured, number of houses destroyed, and amount of financial loss (captured by monetary loss measured in Indonesian Rupiah) from each type of disaster aggregated at the province level are used to capture both the frequency as well as the intensity of disasters. Second, relying on a single measure of a disaster may not capture its overall effect because a certain event may result in large financial losses but inflict little physical harm. Third, using alternate measures of disaster allows one to compare and confirm results, and can be used as a robustness check (Materials and Methods).Finally, for measures of climatic variations, we construct estimates of average temperature and precipitation for each province during each observation interval (Materials and Methods), because temperature and rainfall variations together provide a more complete measure of the extent of climate variations that may affect migration (7).     

The European Histamine Research Society 47th Annual Meeting

Protein Kinase C (PKC) regulates the release of pro-inflammatory compounds from IgE/antigen-activated mast cells by unknown mechanisms. In this study, we show for the first time that PKC inhibitor Ro-03-0432, which inhibits RBL-2H3 exocytosis/degranulation in a concentration-dependent fashion, prevents the phosphorylation of membrane fusion factor Munc18a at Ser 313. Our study provides fresh evidence that PKC-dependent protein phosphorylation may contribute to the intricate regulation of mast cell degranulation by directly targeting the fusion factors.     

Will Proton Pump Inhibitors Increase the Risk of Diabetes Mellitus? A Systemic Review and Meta-Analysis

Background: Proton pump inhibitor use was reported to potentially provide benefits to prevent diabetes mellitus. This study aims to investigate the association between proton pump inhibitor use and the risk of developing diabetes mellitus.Methods: This study was registered on the International Prospective Register of Systematic Reviews (PROSPERO) (ID: CRD42021238481). A systematic literature search was conducted to identify eligible studies up to February 2021. Quality assessment was conducted according to Jadad Scoring Scale and Newcastle–Ottawa Scale. The heterogeneity among studies was tested and estimated by Q test and I². Pooled hazard ratio with 95% CI was calculated using the random-effects or fixed-effects model depending on the heterogeneity. Subgroup analyses, sensitivity analysis, and publication bias assessment were also performed.Results: Eight studies including 850 019 participants were included. We found that proton pump inhibitor use was associated with a statistically non-significant increased risk of diabetes mellitus (pooled hazard ratio was 1.06, 95% CI = 0.89-1.28, P = .50). In subgroup analysis, 5 studies conducted in North America confirmed the overall result; however, one study conducted in Europe demonstrated a statistically significant increased risk, while one study in Asia revealed a statistically significant decreased risk.Conclusion: Proton pump inhibitor use is not associated with either increased or decreased risk of diabetes mellitus. However, more well-designed studies focusing on proton pump inhibitor use and the risk of diabetes mellitus, especially among populations with different backgrounds, are still needed.     

Subgingival Bacterial Burden in Relation to Clinical and Radiographic Periodontal Parameters

Background: This cross‐sectional study characterizes the association between subgingival bacterial profile and periodontal parameters in patients assigned to coronary angiography because of cardiologic problems, which may affect the oral microbiota. Methods: Pooled subgingival bacterial samples were collected from 477 dentate individuals during the oral examinations, along with periodontal probing depth (PD) and assessments of bleeding on probing (BOP) and radiographic alveolar bone loss (ABL). The checkerboard DNA–DNA hybridization assay was used to determine the levels of 29 oral bacteria, which were divided into three bacterial complexes. Results: All bacterial combinations from the etiologic bacterial group and each species from the red complex were significantly associated (P <0.001) with grade of ABL. The prevalence of the etiologic bacterial group and the level of each species were also associated strongly with the proportion of sites with PD 4 to 5 mm and ≥6 mm, BOP, and ABL, except Aggregatibacter actinomycetemcomitans. Levels of Gram‐negative oral bacteria correlated significantly with those of Gram‐positive species (r = 0.840, P <0.001). In multiple logistic regression analysis, the prevalence of the etiologic bacterial group, levels of Gram‐negative bacteria and Treponema denticola, and the prevalence of Porphyromonas gingivalis and T. denticola associated significantly with ABL, whereas other bacterial complexes and levels of Gram‐positive species did not. Conclusions: Although levels of Gram‐negative and ‐positive species paralleled periodontal parameters, only the species considered etiologic were associated with ABL.