Jejunogastric intussusception presented with hematemesis: a case presentation and review of the literature

BACKGROUND: Jejunogastric intussusception (JGI) is a rare but potentially very serious complication of gastrectomy or gastrojejunostomy. To avoid mortality early diagnosis and prompt surgical intervention is mandatory. CASE PRESENTATION: A young man presented with epigastric pain and bilous vomiting followed by hematemesis,10 years after vagotomy and gastrojejunostomy for a bleeding duodenal ulcer. Emergency endoscopy showed JGI and the CT scan of the abdomen was compatible with this diagnosis. At laparotomy a retrograde type II, JGI was confirmed and managed by reduction of JGI without intestinal resection. Postoperative recovery was uneventful. CONCLUSIONS: JGI is a rare condition and less than 200 cases have been published since its first description in 1914. The clinical picture is almost diagnostic. Endoscopy performed by someone familiar with this rare entity is certainly diagnostic and CT-Scan of the abdomen could also help. There is no medical treatment for acute JGI and the correct treatment is surgical intervention as soon as possible

Cholesterol Metabolism Is Required for Intracellular Hedgehog Signal Transduction In Vivo

We describe the rudolph mouse, a mutant with striking defects in both central nervous system and skeletal development. Rudolph is an allele of the cholesterol biosynthetic enzyme, hydroxysteroid (17-beta) dehydrogenase 7, which is an intriguing finding given the recent implication of oxysterols in mediating intracellular Hedgehog (Hh) signaling. We see an abnormal sterol profile and decreased Hh target gene induction in the rudolph mutant, both in vivo and in vitro. Reduced Hh signaling has been proposed to contribute to the phenotypes of congenital diseases of cholesterol metabolism. Recent in vitro and pharmacological data also indicate a requirement for intracellular cholesterol synthesis for proper regulation of Hh activity via Smoothened. The data presented here are the first in vivo genetic evidence supporting both of these hypotheses, revealing a role for embryonic cholesterol metabolism in both CNS development and normal Hh signaling

The Reproductive Ecology of Industrial Societies, Part I : Why Measuring Fertility Matters.

Is fertility relevant to evolutionary analyses conducted in modern industrial societies? This question has been the subject of a highly contentious debate, beginning in the late 1980s and continuing to this day. Researchers in both evolutionary and social sciences have argued that the measurement of fitness-related traits (e.g., fertility) offers little insight into evolutionary processes, on the grounds that modern industrial environments differ so greatly from those of our ancestral past that our behavior can no longer be expected to be adaptive. In contrast, we argue that fertility measurements in industrial society are essential for a complete evolutionary analysis: in particular, such data can provide evidence for any putative adaptive mismatch between ancestral environments and those of the present day, and they can provide insight into the selection pressures currently operating on contemporary populations. Having made this positive case, we then go on to discuss some challenges of fertility-related analyses among industrialized populations, particularly those that involve large-scale databases. These include "researcher degrees of freedom" (i.e., the choices made about which variables to analyze and how) and the different biases that may exist in such data. Despite these concerns, large datasets from multiple populations represent an excellent opportunity to test evolutionary hypotheses in great detail, enriching the evolutionary understanding of human behavior

Advanced Modeling of Cellular Proliferation: Toward a Multi-scale Framework Coupling Cell Cycle to Metabolism by Integrating Logical and Constraint-Based Models

Biological functions require a coherent cross talk among multiple layers of regulation within the cell. Computational efforts that aim to understand how these layers are integrated across spatial, temporal, and functional scales represent a challenge in Systems Biology. We have developed a computational, multi-scale framework that couples cell cycle and metabolism networks in the budding yeast cell. Here we describe the methodology at the basis of this framework, which integrates on off-the-shelf logical (Boolean) models of a minimal yeast cell cycle with a constraint-based model of metabolism (i.e., the Yeast 7 metabolic network reconstruction). Models are implemented in Python code using the BooleanNet and COBRApy packages, respectively, and are connected through the Boolean logic. The methodology allows for incorporation of interaction data, and validation through -omics data. Furthermore, evolutionary strategies may be incorporated to explore regulatory structures underlying coherent cross talks among regulatory layers