Updating age-specific contact structures to match evolving demography in a dynamic mathematical model of tuberculosis vaccination

We investigated the effects of updating age-specific social contact matrices to match evolving demography on vaccine impact estimates. We used a dynamic transmission model of tuberculosis in India as a case study. We modelled four incremental methods to update contact matrices over time, where each method incorporated its predecessor: fixed contact matrix (M0), preserved contact reciprocity (M1), preserved contact assortativity (M2), and preserved average contacts per individual (M3). We updated the contact matrices of a deterministic compartmental model of tuberculosis transmission, calibrated to epidemiologic data between 2000 and 2019 derived from India. We additionally calibrated the M0, M2, and M3 models to the 2050 TB incidence rate projected by the calibrated M1 model. We stratified age into three groups, children (<15y), adults (≥15y, <65y), and the elderly (≥65y), using World Population Prospects demographic data, between which we applied POLYMOD-derived social contact matrices. We simulated an M72-AS01_E-like tuberculosis vaccine delivered from 2027 and estimated the per cent TB incidence rate reduction (IRR) in 2050 under each update method. We found that vaccine impact estimates in all age groups remained relatively stable between the M0–M3 models, irrespective of vaccine-targeting by age group. The maximum difference in impact, observed following adult-targeted vaccination, was 7% in the elderly, in whom we observed IRRs of 19% (uncertainty range 13–32), 20% (UR 13–31), 22% (UR 14–37), and 26% (UR 18–38) following M0, M1, M2 and M3 updates, respectively. We found that model-based TB vaccine impact estimates were relatively insensitive to demography-matched contact matrix updates in an India-like demographic and epidemiologic scenario. Current model-based TB vaccine impact estimates may be reasonably robust to the lack of contact matrix updates, but further research is needed to confirm and generalise this finding.     

AC impedance of the perineurium of the frog sciatic nerve

The AC impedance of the isolated perineurium of the frog sciatic nerve was examined at frequencies from 2 Hz to 100 kHz. A Nyquist plot of the imaginary and real components of the impedance demonstrated more than 1 capacitative element, and a DC resistance of 478 +/- 34 (SEM, n = 27) omega cm2. Transperineurial potential in the absence of externally applied current was 0.0 +/- 0.5 mV. The impedance data were fitted by nonlinear least squares to an equation representing the generalized impedance of four equivalent circuits each with two resistive and two capacitative elements. Only two of these circuits were consistent with perineurial morphology, however. In both, the perineurial cells were represented by a resistive and capacitative element in parallel, where capacitance was less than 0.1 microF/cm2. The extracellular matrix and intercellular junctions of the perineurium were represented as single resistive and capacitative elements in parallel or in series, where capacitance exceeded 2 microF/cm2. Immersion of the perineurium in low conductance Ringer's solution increased DC resistive elements as compared with their values in isotonic Ringer's solution, whereas treatment for 10 min with a hypertonic Ringer's solution (containing an additional 1.0 or 2.0 mol NaCl/liter of solution) reduced DC resistive elements, consistent with changes in perineurial permeability. The results indicate that (a) perineurial impedance contains two time constants and can be analyzed in terms of contributions from cellular and extracellular elements, and (b) transperineurial DC resistance, which is intermediate between DC resistance for leaky and nonleaky epithelia, represents intercellular resistance and can be experimentally modified by hypertonicity.     

Alpha 2-adrenoceptor agonists stimulate growth hormone secretion but have no acute effects on plasma cortisol under basal conditions

Ten normal male subjects were administered clonidine (0.1 and 0.2 mg) or a highly-selective alpha 2-adrenoceptor agonist S 3341 (1 and 2 mg) on separate occasions in a double-blind randomised placebo-controlled study; blood samples were obtained for measurement of serum GH and plasma cortisol via an indwelling venous cannula for 4 h after each drug administration. Both clonidine and S 3341 were equally effective at lowering supine, and particularly standing BP; both also caused mild sedation, although this was slightly less marked for S 3341. High doses of both clonidine and S 3341 significantly increased serum GH (peak increment after clonidine: 18.8 +/- 5.5 mU/l (mean +/- SEM); peak increment after S 3341: 21.1 +/- 4.8 mU/l). Neither drug affected plasma cortisol. It is concluded that GH release may be stimulated by alpha 2-adrenoceptor agonism. As S 3341 has slightly less central activity than clonidine at the doses employed, but is at least equally potent at stimulating GH release, it is probable that the alpha 2-adrenoceptor stimulation of GH release occurs outside the blood-brain barrier. The pituitary-adrenal axis appears resistant to manipulation of alpha 2-adrenoceptors under basal conditions.     

Schema-based learning of adaptable and flexible prey- catching in anurans II. Learning after lesioning

The previous companion paper describes the initial (seed) schema architecture that gives rise to the observed prey-catching behavior. In this second paper in the series we describe the fundamental adaptive processes required during learning after lesioning. Following bilateral transections of the hypoglossal nerve, anurans lunge toward mealworms with no accompanying tongue or jaw movement. Nevertheless anurans with permanent hypoglossal transections eventually learn to catch their prey by first learning to open their mouth again and then lunging their body further and increasing their head angle. In this paper we present a new learning framework, called schema-based learning (SBL). SBL emphasizes the importance of the current existent structure (schemas), that defines a functioning system, for the incremental and autonomous construction of ever more complex structure to achieve ever more complex levels of functioning. We may rephrase this statement into the language of Schema Theory (Arbib 1992, for a comprehensive review) as the learning of new schemas based on the stock of current schemas. SBL emphasizes a fundamental principle of organization called coherence maximization, that deals with the maximization of congruence between the results of an interaction (external or internal) and the expectations generated for that interaction. A central hypothesis consists of the existence of a hierarchy of predictive internal models (predictive schemas) all over the control center-brain-of the agent. Hence, we will include predictive models in the perceptual, sensorimotor, and motor components of the autonomous agent architecture. We will then show that predictive models are fundamental for structural learning. In particular we will show how a system can learn a new structural component (augment the overall network topology) after being lesioned in order to recover (or even improve) its original functionality. Learning after lesioning is a special case of structural learning but clearly shows that solutions cannot be known/hardwired a priori since it cannot be known, in advance, which substructure is going to break down.     

Responses of medullary neurons to moving visual stimuli in the common toad

The concept of coded 'command releasing systems' proposes that visually specialized descending tectal (and pretectal) neurons converge on motor pattern generating medullary circuits and release--in goal-specific combination--specific action patterns. Extracellular recordings from medullary neurons of the medial reticular formation of the awake immobilized toad in response to moving visual stimuli revealed the following main results. (i) Properties of medullary neurons were distinguished by location, shape, and size of visual receptive fields (ranging from relatively small to wide), by trigger features of various moving configural stimulus objects (including prey- and predator-selective properties), by tactile sensitivity, and by firing pattern characteristics (sluggish, tonic, warming-up, and cyclic). (ii) Visual receptive fields of medullary neurons and their responses to moving configural objects suggest converging inputs of tectal (and pretectal) descending neurons. (iii) In contrast to tectal monocular 'small-field' neurons, the excitatory visual receptive fields of comparable medullary neurons were larger, ellipsoidally shaped, mostly oriented horizontally, and not topographically mapped in an obvious fashion. Furthermore, configural feature discrimination was sharper. (iv) The observation of multiple properties in most medullary neurons (partly showing combined visual and cutaneous sensitivities) suggests integration of various inputs by these cells, and this is in principle consistent with the concept of command releasing systems. (v) There is evidence for reciprocal tectal/medullary excitatory pathways suitable for premotor warming-up. (vi) Cyclic bursting of many neurons, spontaneously or as a post-stimulus sustaining event, points to a medullary premotor/motor property.