Mycobacterium tuberculosis Bacteremia in a Cohort of HIV-Infected Patients Hospitalized with Severe Sepsis in Uganda–High Frequency,Low Clinical Sand Derivation of a Clinical Prediction Score

Background

When manifested as Mycobacterium tuberculosis (MTB) bacteremia, disseminated MTB infection clinically mimics other serious blood stream infections often hindering early diagnosis and initiation of potentially life-saving anti-tuberculosis therapy. In a cohort of hospitalized HIV-infected Ugandan patients with severe sepsis, we report the frequency, management and outcomes of patients with MTB bacteremia and propose a risk score based on clinical predictors of MTB bacteremia.

Methods

We prospectively enrolled adult patients with severe sepsis at two Ugandan hospitals and obtained blood cultures for MTB identification. Multivariable logistic regression modeling was used to determine predictors of MTB bacteremia and to inform the stratification of patients into MTB bacteremia risk categories based on relevant patient characteristics.

Results

Among 368 HIV-infected patients with a syndrome of severe sepsis, eighty-six (23%) had MTB bacteremia. Patients with MTB bacteremia had a significantly lower median CD4 count (17 vs 64 lymphocytes/mm³, p<0.001) and a higher 30-day mortality (53% vs 32%, p = 0.001) than patients without MTB bacteremia. A minority of patients with MTB bacteremia underwent standard MTB diagnostic testing (24%) or received empiric anti-tuberculosis therapy (15%). Independent factors associated with MTB bacteremia included male sex, increased heart rate, low CD4 count, absence of highly active anti-retroviral therapy, chief complaint of fever, low serum sodium and low hemoglobin. A risk score derived from a model containing these independent predictors had good predictive accuracy [area under the curve = 0.85, 95% CI 0.80–0.89].

Conclusions

Nearly 1 in 4 adult HIV-infected patients hospitalized with severe sepsis in 2 Ugandan hospitals had MTB bacteremia. Among patients in whom MTB was suspected, standard tests for diagnosing pulmonary MTB were inaccurate for correctly classifying patients with or without bloodstream MTB infection. A MTB bacteremia risk score can improve early diagnosis of MTB bacteremia particularly in settings with increased HIV and MTB co-infection.     

The tumor suppressor CDKN3 controls mitosis

Mitosis is controlled by a network of kinases and phosphatases. We screened a library of small interfering RNAs against a genome-wide set of phosphatases to comprehensively evaluate the role of human phosphatases in mitosis. We found four candidate spindle checkpoint phosphatases, including the tumor suppressor CDKN3. We show that CDKN3 is essential for normal mitosis and G1/S transition. We demonstrate that subcellular localization of CDKN3 changes throughout the cell cycle. We show that CDKN3 dephosphorylates threonine-161 of CDC2 during mitotic exit and we visualize CDC2^pThr-161 at kinetochores and centrosomes in early mitosis. We performed a phosphokinome-wide mass spectrometry screen to find effectors of the CDKN3-CDC2 signaling axis. We found that one of the identified downstream phosphotargets, CKβ phosphorylated at serine 209, localizes to mitotic centrosomes and controls the spindle checkpoint. Finally, we show that CDKN3 protein is down-regulated in brain tumors. Our findings indicate that CDKN3 controls mitosis through the CDC2 signaling axis. These results have implications for targeted anticancer therapeutics.     

Germ lineage properties in the urochordate Botryllus schlosseri – From markers to temporal niches

The primordial germ cells (PGCs) in the colonial urochordate Botryllus schlosseri are sequestered in late embryonic stage. PGC-like populations, located at any blastogenic stage in specific niches, inside modules with curtailed lifespan, survive throughout the life of the colony by repeated weekly migration to newly formed buds. This cyclical migration and the lack of specific markers for PGC-like populations are obstacles to the study on PGCs. For that purpose, we isolated the Botryllus DDX1 (BS-DDX1) and characterized it by normal expression patterns and by specific siRNA knockdown experiments. Expression of BS-DDX1 concurrent with BS-Vasa, γ-H2AX, BS-cadherin and phospho-Smad1/5/8, demarcate PGC cells from soma cells and from more differentiated germ cells lineages, which enabled the detection of additional putative transient niches in zooids. Employing BS-cadherin siRNA knockdown, retinoic acid (RA) administration or β-estradiol administration affirmed the BS-Vasa⁺BS-DDX1⁺BS-cadherin⁺γ-H2AX⁺phospho-Smad1/5/8⁺ population as the B. schlosseri PGC-like cells. By striving to understand the PGC-like cells trafficking between transient niches along blastogenic cycles, CM-DiI-stained PGC-like enriched populations from late blastogenic stage D zooids were injected into genetically matched colonial ramets at blastogenic stages A or C and their fates were observed for 9 days. Based on the accumulated data, we conceived a novel network of several transient and short lived ‘germ line niches’ that preserve PGCs homeostasis, protecting these cells from the weekly astogenic senescence processes, thus enabling the survival of the PGCs throughout the organism's life.     

Reception and learning of electric fields in bees

Honeybees, like other insects, accumulate electric charge in flight, and when their body parts are moved or rubbed together. We report that bees emit constant and modulated electric fields when flying, landing, walking and during the waggle dance. The electric fields emitted by dancing bees consist of low- and high-frequency components. Both components induce passive antennal movements in stationary bees according to Coulomb''s law. Bees learn both the constant and the modulated electric field components in the context of appetitive proboscis extension response conditioning. Using this paradigm, we identify mechanoreceptors in both joints of the antennae as sensors. Other mechanoreceptors on the bee body are potentially involved but are less sensitive. Using laser vibrometry, we show that the electrically charged flagellum is moved by constant and modulated electric fields and more strongly so if sound and electric fields interact. Recordings from axons of the Johnston organ document its sensitivity to electric field stimuli. Our analyses identify electric fields emanating from the surface charge of bees as stimuli for mechanoreceptors, and as biologically relevant stimuli, which may play a role in social communication.     

Integrating Genetic,Neuropsychological and Neuroimaging Data to Model Early-Onset Obsessive Compulsive Disorder Severity

We propose an integrative approach that combines structural magnetic resonance imaging data (MRI), diffusion tensor imaging data (DTI), neuropsychological data, and genetic data to predict early-onset obsessive compulsive disorder (OCD) severity. From a cohort of 87 patients, 56 with complete information were used in the present analysis. First, we performed a multivariate genetic association analysis of OCD severity with 266 genetic polymorphisms. This association analysis was used to select and prioritize the SNPs that would be included in the model. Second, we split the sample into a training set (N = 38) and a validation set (N = 18). Third, entropy-based measures of information gain were used for feature selection with the training subset. Fourth, the selected features were fed into two supervised methods of class prediction based on machine learning, using the leave-one-out procedure with the training set. Finally, the resulting model was validated with the validation set. Nine variables were used for the creation of the OCD severity predictor, including six genetic polymorphisms and three variables from the neuropsychological data. The developed model classified child and adolescent patients with OCD by disease severity with an accuracy of 0.90 in the testing set and 0.70 in the validation sample. Above its clinical applicability, the combination of particular neuropsychological, neuroimaging, and genetic characteristics could enhance our understanding of the neurobiological basis of the disorder.