The Internet comprises a decentralized global system that serves humanity’s collective effort to generate, process, and store data, most of which is handled by the rapidly expanding cloud. A stable, secure, real-time system may allow for interfacing the cloud with the human brain. One promising strategy for enabling such a system, denoted here as a “human brain/cloud interface” (“B/CI”), would be based on technologies referred to here as “neuralnanorobotics.” Future neuralnanorobotics technologies are anticipated to facilitate accurate diagnoses and eventual cures for the ∼400 conditions that affect the human brain. Neuralnanorobotics may also enable a B/CI with controlled connectivity between neural activity and external data storage and processing, via the direct monitoring of the brain’s ∼86 × 10 9 neurons and ∼2 × 10 14 synapses. Subsequent to navigating the human vasculature, three species of neuralnanorobots (endoneurobots, gliabots, and synaptobots) could traverse the blood–brain barrier (BBB), enter the brain parenchyma, ingress into individual human brain cells, and autoposition themselves at the axon initial segments of neurons (endoneurobots), within glial cells (gliabots), and in intimate proximity to synapses (synaptobots). They would then wirelessly transmit up to ∼6 × 10 16 bits per second of synaptically processed and encoded human–brain electrical information via auxiliary nanorobotic fiber optics (30 cm 3 ) with the capacity to handle up to 10 18 bits/sec and provide rapid data transfer to a cloud based supercomputer for real-time brain-state monitoring and data extraction. A neuralnanorobotically enabled human B/CI might serve as a personalized conduit, allowing persons to obtain direct, instantaneous access to virtually any facet of cumulative human knowledge. Other anticipated applications include myriad opportunities to improve education, intelligence, entertainment, traveling, and other interactive experiences. A specialized application might be the capacity to engage in fully immersive experiential/sensory experiences, including what is referred to here as “transparent shadowing” (TS). Through TS, individuals might experience episodic segments of the lives of other willing participants (locally or remote) to, hopefully, encourage and inspire improved understanding and tolerance among all members of the human family.

Cell-based mathematical models have previously been developed to simulate the immune system in response to pathogens. Mathematical modeling papers which study the human immune response to pathogens have predicted concentrations of a variety of cells, including activated and resting macrophages, plasma cells, and antibodies. This study aims to create a comprehensive mathematical model that can predict cytokine levels in response to a gram-positive bacterium, S. aureus by coupling previous models. To accomplish this, the cytokines Tumor Necrosis Factor Alpha (TNF-α), Interleukin 6 (IL-6), Interleukin 8 (IL-8), and Interleukin 10 (IL-10) are included to quantify the relationship between cytokine release from macrophages and the concentration of the pathogen, S. aureus, ex vivo. Partial differential equations (PDEs) are used to model cellular response and ordinary differential equations (ODEs) are used to model cytokine response, and interactions between both components produce a more robust and more complete systems-level understanding of immune activation. In the coupled cellular and cytokine model outlined in this paper, a low concentration of S. aureus is used to stimulate the measured cellular response and cytokine expression. Results show that our cellular activation and cytokine expression model characterizing septic conditions can predict ex vivo mechanisms in response to gram-negative and gram-positive bacteria. Our simulations provide new insights into how the human immune system responds to infections from different pathogens. Novel applications of these insights help in the development of more powerful tools and protocols in infection biology.

In several species caloric restriction (CR) extends life span. In this paper we integrate data from studies on CR and other sources to articulate the hypothalamic deregulation hypothesis by which estrogen receptor-alpha (ER-α) signaling in the hypothalamus and limbic system affects life span under the stress of CR in mammals. ER-α is one of two principal estrogen-binding receptors differentially expressed in the amygdala, hippocampus, and several key hypothalamic nuclei: the arcuate nucleus (ARN), preoptic area (POA), ventromedial nucleus (VMN), antero ventral periventricular nucleus (AVPV), paraventricular nucleus (PVN), supraoptic nucleus (SON), and suprachiasmatic nucleus (SCN). Estradiol signaling via ER-α is essential in basal level functioning of reproductive cycle, sexually receptive behaviors, physiological stress responses, as well as sleep cycle, and other nonsexual behaviors. When an organism is placed under long-term CR, which introduces an external stress to this ER-α signaling, the reduction of ER-α expression is attenuated over time in the hypothalamus. This review paper seeks to characterize the downstream effects of ER-α in the hypothalamus and limbic system that affect normal endocrine functioning.

Both life-long caloric restriction (CR) and the suppression of insulin-like growth factor-1 (IGF-1) signaling reliably extend the mammalian lifespan. The neuroendocrine system, regulated by the hypothalamus, remains the most convincing site of action for both these modes of life extension. Yet, determining whether CR actions are mediated by the modulation of neuroendocrine IGF-1 signaling remains unclear. Of the hypothalamic nuclei that express the IGF-1 receptor (IGF-1R), the cells of the supraoptic nucleus (SON) display some of the most robust IGF-1R expression. Taking IGF-1R immunoreactivity as an index of sensitivity to IGF-1, we counted IGF-1R immunoreactive and non-immunoreactive cells in the SON of young-ad-libitum fed (young-Al, 6 weeks), old-ad-libitum fed (Old-Al, 22 months), and old-calorie-restricted (Old-CR, 22 months) female B6D2F1 mice. An automated imaging microscopy system (AIMS) was used to generate cell counts for each section of supraoptic hypothalamus. Results show that while the total number of cells in the SON of ad-libitum fed mice does not change significantly with aging, a significant reduction in IGF-1R immunoreactive cells does occur in ad-libitum fed mice with aging. In contrast to this, calorie restricted mice show both a decline in the total number of cells and IGF-1R immunoreactive cells in the SON with age, but with the decrease in the latter being notably attenuated when compared to the degree of loss seen in ad-libitum fed mice. Thus, while CR induces greater loss in the total number of cells in the SON with age, it reduces the degree of age-dependent loss seen in IGF-1R expressing cells. As a result, when compared to Old-AL mice, the SON of Old-CR mice displays a greater proportion of IGF-1R cells and thus possibly enhanced IGF-1 sensitivity with aging.

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