Quantitative reconstruction of climatic variations during the Bronze and early Iron ages based on pollen and lake-level data in the NW Alps, France

International audienceVegetation and lake-level data from the archaeological site of Tresserve, on the eastern shore of Lake Le Bourget (Savoie, France), are used to provide quantitative estimates of climatic variables over the period 4000-2300 cal BP in the northern French Pre-Alps, and to examine the possible impact of climatic changes on societies of the Bronze and early Iron Ages. The results obtained indicate that phases of higher lake level at 3500-3100 and 2750-2350 cal BP coincided with major climate reversals in the North Atlantic area. In west-central Europe, they were marked by cooler and wetter conditions. These two successive events may have affected ancient agricultural communities in west-central Europe by provoking harvest failures, more particularly due to increasing precipitation during the growing season. However, archaeological data in the region of Franche-Comté (Jura Mountains, eastern France) show a general expansion of population density from the middle Bronze Age to the early Iron Age. This suggests a relative emancipation of proto-historic societies from climatic conditions, probably in relation to the spread of new modes of social and economic organisation

Clinical Outcomes of Community-Acquired Pneumonia in Patients with Diabetes Mellitus

Background: Studies have found admission hyperglycemia as a predictor of poor outcomes in Community acquired Pneumonia (CAP), whereas others have not. The objective of this study was to evaluate the impact of diabetes mellitus (DM) on mortality as well as Length of stay (LOS) and Time to clinical stability (TCS) of hospitalized patients with CAP. Materials and Methods: Adult patients hospitalized with CAP enrolled at Community-Acquired Pneumonia Organization (CAPO) database with DM were categorized as admission blood glucose ≥ 250 mg/dL (diabetes mellitus blood sugar (BG) \u3e 250) and admission blood glucose ≤ 250 mg/dL (DM BG ≤ 250). CAP outcomes included: all-cause in-hospital mortality, all-cause 28-day mortality, length of stay (LOS) and time to clinical stability (TCS). Results: From a total of 7,303 patients with CAP, 294 (17.7%) had DM; out of whom 960 (13.1%) patients had BG ≤ 250 mg/dL, and 334 (4.6%) patients had BG \u3e 250 mg/dL. The in-hospital mortality was 9.3% for controls, 9.9% for the DM BG ≤ 250 mg/dL group and 13.4% for DM BG \u3e 250 mg/dL group (p = 0.04). Patients with DM BG \u3e 250 mg/dL compared to the control group had a higher risk of in-hospital mortality (Hazard ratio (RR) = 1.32, 95% CI: 1.02-1.72, p = 0.034) and 28-day mortality (RR = 1.31, 95% CI: 1.01-1.71, p = 0.048). Patients in the DM BG ≤ 250 mg/dL group compared to the control group did not have a greater risk for in-hospital mortality (RR = 1.23, 95% CI: 0.16-8.09, p = 0.237), 28-day mortality (RR = 1.09, 95% CI: 0.90-1.32, p = 0.398), LOS (HR = 0.93, 95% CI: 0.85-1.02, p = 0.130), or TCS (HR = 0.95, 95% CI: 0.87-1.05, p = 0.320). Conclusions: DM patients with BG \u3e 250 mg/dL were associated with increased in-hospital mortality and 28-day mortality. Further studies are needed to link the role of hyperglycemia to CAP outcome

The family as a determinant of stunting in children living in conditions of extreme poverty: a case-control study

BACKGROUND: Malnutrition in children can be a consequence of unfavourable socioeconomic conditions. However, some families maintain adequate nutritional status in their children despite living in poverty. The aim of this study was to ascertain whether family-related factors are determinants of stunting in young Mexican children living in extreme poverty, and whether these factors differ between rural or urban contexts. METHODS: A case-control study was conducted in one rural and one urban extreme poverty level areas in Mexico. Cases comprised stunted children aged between 6 and 23 months. Controls were well-nourished children. Independent variables were defined in five dimensions: family characteristics; family income; household allocation of resources and family organisation; social networks; and child health care. Information was collected from 108 cases and 139 controls in the rural area and from 198 cases and 211 controls in the urban area. Statistical analysis was carried out separately for each area; unconditional multiple logistic regression analyses were performed to obtain the best explanatory model for stunting. RESULTS: In the rural area, a greater risk of stunting was associated with father's occupation as farmer and the presence of family networks for child care. The greatest protective effect was found in children cared for exclusively by their mothers. In the urban area, risk factors for stunting were father with unstable job, presence of small social networks, low rate of attendance to the Well Child Program activities, breast-feeding longer than six months, and two variables within the family characteristics dimension (longer duration of parents' union and migration from rural to urban area). CONCLUSIONS: This study suggests the influence of the family on the nutritional status of children under two years of age living in extreme poverty areas. Factors associated with stunting were different in rural and urban communities. Therefore, developing and implementing health programs to tackle malnutrition should take into account such differences that are consequence of the social, economic, and cultural contexts in which the family lives

How to handle mortality when investigating length of hospital stay and time to clinical stability

<p>Abstract</p> <p>Background</p> <p>Hospital length of stay (LOS) and time for a patient to reach clinical stability (TCS) have increasingly become important outcomes when investigating ways in which to combat Community Acquired Pneumonia (CAP). Difficulties arise when deciding how to handle in-hospital mortality. Ad-hoc approaches that are commonly used to handle time to event outcomes with mortality can give disparate results and provide conflicting conclusions based on the same data. To ensure compatibility among studies investigating these outcomes, this type of data should be handled in a consistent and appropriate fashion.</p> <p>Methods</p> <p>Using both simulated data and data from the international Community Acquired Pneumonia Organization (CAPO) database, we evaluate two ad-hoc approaches for handling mortality when estimating the probability of hospital discharge and clinical stability: 1) restricting analysis to those patients who lived, and 2) assigning individuals who die the "worst" outcome (right-censoring them at the longest recorded LOS or TCS). Estimated probability distributions based on these approaches are compared with right-censoring the individuals who died at time of death (the complement of the Kaplan-Meier (KM) estimator), and treating death as a competing risk (the cumulative incidence estimator). Tests for differences in probability distributions based on the four methods are also contrasted.</p> <p>Results</p> <p>The two ad-hoc approaches give different estimates of the probability of discharge and clinical stability. Analysis restricted to patients who survived is conceptually problematic, as estimation is conditioned on events that happen <it>at a future time</it>. Estimation based on assigning those patients who died the worst outcome (longest LOS and TCS) coincides with the complement of the KM estimator based on the subdistribution hazard, which has been previously shown to be equivalent to the cumulative incidence estimator. However, in either case the time to in-hospital mortality is ignored, preventing simultaneous assessment of patient mortality in addition to LOS and/or TCS. The power to detect differences in underlying hazards of discharge between patient populations differs for test statistics based on the four approaches, and depends on the underlying hazard ratio of mortality between the patient groups.</p> <p>Conclusions</p> <p>Treating death as a competing risk gives estimators which address the clinical questions of interest, and allows for simultaneous modelling of both in-hospital mortality and TCS / LOS. This article advocates treating mortality as a competing risk when investigating other time related outcomes.</p

Enforced Expression of the Transcriptional Coactivator OBF1 Impairs B Cell Differentiation at the Earliest Stage of Development

OBF1, also known as Bob.1 or OCA-B, is a B lymphocyte-specific transcription factor which coactivates Oct1 and Oct2 on B cell specific promoters. So far, the function of OBF1 has been mainly identified in late stage B cell populations. The central defect of OBF1 deficient mice is a severely reduced immune response to T cell-dependent antigens and a lack of germinal center formation in the spleen. Relatively little is known about a potential function of OBF1 in developing B cells. Here we have generated transgenic mice overexpressing OBF1 in B cells under the control of the immunoglobulin heavy chain promoter and enhancer. Surprisingly, these mice have greatly reduced numbers of follicular B cells in the periphery and have a compromised immune response. Furthermore, B cell differentiation is impaired at an early stage in the bone marrow: a first block is observed during B cell commitment and a second differentiation block is seen at the large preB2 cell stage. The cells that succeed to escape the block and to differentiate into mature B cells have post-translationally downregulated the expression of transgene, indicating that expression of OBF1 beyond the normal level early in B cell development is deleterious. Transcriptome analysis identified genes deregulated in these mice and Id2 and Id3, two known negative regulators of B cell differentiation, were found to be upregulated in the EPLM and preB cells of the transgenic mice. Furthermore, the Id2 and Id3 promoters contain octamer-like sites, to which OBF1 can bind. These results provide evidence that tight regulation of OBF1 expression in early B cells is essential to allow efficient B lymphocyte differentiation

Single-cell analysis tools for drug discovery and development

The genetic, functional or compositional heterogeneity of healthy and diseased tissues presents major challenges in drug discovery and development. Such heterogeneity hinders the design of accurate disease models and can confound the interpretation of biomarker levels and of patient responses to specific therapies. The complex nature of virtually all tissues has motivated the development of tools for single-cell genomic, transcriptomic and multiplex proteomic analyses. Here, we review these tools and assess their advantages and limitations. Emerging applications of single cell analysis tools in drug discovery and development, particularly in the field of oncology, are discussed