Oral intake of Lactobacillus pentosus strain b240 accelerates salivary immunoglobulin A secretion in the elderly: A randomized, placebo-controlled, double-blind trial

<p>Abstract</p> <p>Background</p> <p>Immunoglobulin A (IgA) secretion in saliva decreases with age and may be the cause of increased vulnerability of the elderly to respiratory infections. The effect of oral intake of lactic acid bacteria on salivary secretory IgA (SIgA) in the elderly has not been reported. The objective of this study was to demonstrate the acceleration of salivary SIgA secretion by oral intake of <it>Lactobacillus pentosus </it>strain b240 (b240) in the elderly.</p> <p>Results</p> <p>A total of 80 healthy elderly individuals were randomly allocated to either an intervention (i.e., b240) or a control (i.e., placebo) group. The elderly individuals in the b240 group were given a sterile water beverage (125 mL) containing heat-killed b240 (4 × 10⁹cells), while those in the placebo group were given only a sterile water beverage (125 mL); both groups received their respective beverages once daily for 12 weeks. Saliva was collected before initiation of the study and every 2 weeks thereafter. Saliva flow rate and SIgA concentration were determined, and the SIgA secretion rate was calculated. The mean salivary SIgA secretion rate in the b240 group steadily increased until week 4 (exhibiting a 20% elevation relative to that at week 0), and then remained stable until week 12. Changes in SIgA secretion rate over the intervention period were significantly greater in the b240 group than in the placebo group. The treatment groups exhibited no significant differences in adverse events.</p> <p>Conclusions</p> <p>Oral intake of <it>L. pentosus </it>strain b240 for 12 weeks significantly accelerated salivary SIgA secretion, thereby indicating its potential utility in the improvement of mucosal immunity and resistance against infection in the elderly.</p

Anterior Medial Prefrontal Cortex Exhibits Activation during Task Preparation but Deactivation during Task Execution

BACKGROUND: The anterior prefrontal cortex (PFC) exhibits activation during some cognitive tasks, including episodic memory, reasoning, attention, multitasking, task sets, decision making, mentalizing, and processing of self-referenced information. However, the medial part of anterior PFC is part of the default mode network (DMN), which shows deactivation during various goal-directed cognitive tasks compared to a resting baseline. One possible factor for this pattern is that activity in the anterior medial PFC (MPFC) is affected by dynamic allocation of attentional resources depending on task demands. We investigated this possibility using an event related fMRI with a face working memory task. METHODOLOGY/PRINCIPAL FINDINGS: Sixteen students participated in a single fMRI session. They were asked to form a task set to remember the faces (Face memory condition) or to ignore them (No face memory condition), then they were given 6 seconds of preparation period before the onset of the face stimuli. During this 6-second period, four single digits were presented one at a time at the center of the display, and participants were asked to add them and to remember the final answer. When participants formed a task set to remember faces, the anterior MPFC exhibited activation during a task preparation period but deactivation during a task execution period within a single trial. CONCLUSIONS/SIGNIFICANCE: The results suggest that the anterior MPFC plays a role in task set formation but is not involved in execution of the face working memory task. Therefore, when attentional resources are allocated to other brain regions during task execution, the anterior MPFC shows deactivation. The results suggest that activation and deactivation in the anterior MPFC are affected by dynamic allocation of processing resources across different phases of processing

BEYONDPLANCK

End-to-end simulations play a key role in the analysis of any high-sensitivity cosmic microwave background (CMB) experiment, providing high-fidelity systematic error propagation capabilities that are unmatched by any other means. In this paper, we address an important issue regarding such simulations, namely, how to define the inputs in terms of sky model and instrument parameters. These may either be taken as a constrained realization derived from the data or as a random realization independent from the data. We refer to these as posterior and prior simulations, respectively. We show that the two options lead to significantly different correlation structures, as prior simulations (contrary to posterior simulations) effectively include cosmic variance, but they exclude realization-specific correlations from non-linear degeneracies. Consequently, they quantify fundamentally different types of uncertainties. We argue that as a result, they also have different and complementary scientific uses, even if this dichotomy is not absolute. In particular, posterior simulations are in general more convenient for parameter estimation studies, while prior simulations are generally more convenient for model testing. Before BEYONDPLANCK, most pipelines used a mix of constrained and random inputs and applied the same hybrid simulations for all applications, even though the statistical justification for this is not always evident. BEYONDPLANCK represents the first end-to-end CMB simulation framework that is able to generate both types of simulations and these new capabilities have brought this topic to the forefront. The BEYONDPLANCK posterior simulations and their uses are described extensively in a suite of companion papers. In this work, we consider one important applications of the corresponding prior simulations, namely, code validation. Specifically, we generated a set of one-year LFI 30 GHz prior simulations with known inputs and we used these to validate the core low-level BEYONDPLANCK algorithms dealing with gain estimation, correlated noise estimation, and mapmaking