Diverticulosis morphology is associated with risk of diverticulitis.

The size, number and distribution of diverticula vary greatly in patients with diverticulosis. We aimed to study the association between the morphology of diverticulosis assessed on colonoscopy and the risk of diverticulitis. We performed a retrospective, case-control study of cases with a history of diverticulitis and controls with diverticulosis without diverticulitis matched on sex, age (within 5 years) and year of colonoscopy. Diverticulosis characteristics were obtained from endoscopy reports and were categorized according to severity, extent, number and size. We used conditional logistic regression on matched pairs to calculate the odds of diverticulitis among patients with diverticulosis according to differing morphologic characteristics. We identified 85 cases with computed tomography-documented diverticulitis and 85 matched controls with diverticulosis without a diagnosis of diverticulitis. In cases, 60% had left-sided only diverticulosis, 2% had right-sided only and 38% had both right and left-sided diverticulosis; whereas in controls, the distribution was 53%, 18% and 29%, respectively. Cases were more likely to have large diverticula [odds ratio (OR), 3.33; 95% confidence interval (CI), 1.30-8.56 for left colon only and 1.89, 95% CI, 0.78-4.57 for both right and left]. Similarly, when the severity of diverticulosis was compared between the groups, cases were more likely to have moderate or severe diverticulosis (OR, 3.44; 95% CI, 1.51-7.84 for moderate and OR, 8.87; 95% CI, 2.98-26.37 for severe). Diverticulitis cases were more likely to have large diverticula and severe diverticulosis when compared to controls suggesting that size and severity are novel risk factors for diverticulitis.

A Bayesian approach to modeling phytoplankton population dynamics from size distribution time series.

The rates of cell growth, division, and carbon loss of microbial populations are key parameters for understanding how organisms interact with their environment and how they contribute to the carbon cycle. However, the invasive nature of current analytical methods has hindered efforts to reliably quantify these parameters. In recent years, size-structured matrix population models (MPMs) have gained popularity for estimating division rates of microbial populations by mechanistically describing changes in microbial cell size distributions over time. Motivated by the mechanistic structure of these models, we employ a Bayesian approach to extend size-structured MPMs to capture additional biological processes describing the dynamics of a marine phytoplankton population over the day-night cycle. Our Bayesian framework is able to take prior scientific knowledge into account and generate biologically interpretable results. Using data from an exponentially growing laboratory culture of the cyanobacterium Prochlorococcus, we isolate respiratory and exudative carbon losses as critical parameters for the modeling of their population dynamics. The results suggest that this modeling framework can provide deeper insights into microbial population dynamics provided by size distribution time-series data.

Probing Lipophilic Adamantyl Group as the P1-Ligand for HIV-1 Protease Inhibitors: Design, Synthesis, Protein X-ray Structural Studies, and Biological Evaluation.

A series of potent HIV-1 protease inhibitors with a lipophilic adamantyl P1 ligand have been designed, synthesized, and evaluated. We have developed an enantioselective synthesis of adamantane-derived hydroxyethylamine isosteres utilizing Sharpless asymmetric epoxidation as the key step. Various inhibitors incorporating P1-adamantylmethyl in combination with P2 ligands such as 3-(R)-THF, 3-(S)-THF, bis-THF, and THF-THP were examined. The S1' pocket was also probed with phenyl and phenylmethyl ligands. Inhibitor 15d, with an isobutyl P1' ligand and a bis-THF P2 ligand, proved to be the most potent of the series. The cLogP value of inhibitor 15d is improved compared to inhibitor 2 with a phenylmethyl P1-ligand. X-ray structural studies of 15d, 15h, and 15i with HIV-1 protease complexes revealed molecular insight into the inhibitor-protein interaction.