XIAP promotes the expansion and limits the contraction of CD8 T cell response through cell extrinsic and intrinsic mechanisms respectively.

XIAP is an endogenous inhibitor of cell death and inactivating mutations of XIAP are responsible for X-linked lymphoproliferative disease (XLP-2) and primary immunodeficiency, but the mechanism(s) behind these contradictory outcomes have been unclear. We report that during infection of macrophages and dendritic cells with various intracellular bacteria, XIAP restricts cell death and secretion of IL-1ß but promotes increased activation of NFκB and JNK which results in elevated secretion of IL-6 and IL-10. Poor secretion of IL-6 by Xiap-deficient antigen presenting cells leads to poor expansion of recently activated CD8 T cells during the priming phase of the response. On the other hand, Xiap-deficient CD8 T cells displayed increased proliferation and effector function during the priming phase but underwent enhanced contraction subsequently. Xiap-deficient CD8 T cells underwent skewed differentiation towards short lived effectors which resulted in poor generation of memory. Consequently Xiap-deficient CD8 T cells failed to provide effective control of bacterial infection during re-challenge. These results reveal the temporal impact of XIAP in promoting the fitness of activated CD8 T cells through cell extrinsic and intrinsic mechanisms and provide a mechanistic explanation of the phenotype observed in XLP-2 patients.

Isolates of Salmonella typhimurium circumvent NLRP3 inflammasome recognition in macrophages during the chronic phase of infection.

Inflammasome signaling results in cell death and release of cytokines from the IL-1 family, which facilitates control over an infection. However, some pathogens such as Salmonella typhimurium (ST) activate various innate immune signaling pathways, including inflammasomes, yet evade these cell death mechanisms, resulting in a chronic infection. Here we investigated inflammasome signaling induced by acute and chronic isolates of ST obtained from different organs. We show that ST isolated from infected mice during the acute phase displays an increased potential to activate inflammasome signaling, which then undergoes a protracted decline during the chronic phase of infection. This decline in inflammasome signaling was associated with reduced expression of virulence factors, including flagella and the Salmonella pathogenicity island I genes. This reduction in cell death of macrophages induced by chronic isolates had the greatest impact on the NLRP3 inflammasome, which correlated with a reduction in caspase-1 activation. Furthermore, rapid cell death induced by Casp-1/11 by ST in macrophages limited the subsequent activation of cell death cascade proteins Casp-8, RipK1, RipK3, and MLKL to prevent the activation of alternative forms of cell death. We observed that the lack of the ability to induce cell death conferred a competitive fitness advantage to ST only during the acute phase of infection. Finally, we show that the chronic isolates displayed a significant attenuation in their ability to infect mice through the oral route. These results reveal that ST adapts during chronic infection by circumventing inflammasome recognition to promote the survival of both the host and the pathogen.

The extended Granger causality analysis for Hodgkin-Huxley neuronal models.

How to extract directions of information flow in dynamical systems based on empirical data remains a key challenge. The Granger causality (GC) analysis has been identified as a powerful method to achieve this capability. However, the framework of the GC theory requires that the dynamics of the investigated system can be statistically linearized; i.e., the dynamics can be effectively modeled by linear regressive processes. Under such conditions, the causal connectivity can be directly mapped to the structural connectivity that mediates physical interactions within the system. However, for nonlinear dynamical systems such as the Hodgkin-Huxley (HH) neuronal circuit, the validity of the GC analysis has yet been addressed; namely, whether the constructed causal connectivity is still identical to the synaptic connectivity between neurons remains unknown. In this work, we apply the nonlinear extension of the GC analysis, i.e., the extended GC analysis, to the voltage time series obtained by evolving the HH neuronal network. In addition, we add a certain amount of measurement or observational noise to the time series to take into account the realistic situation in data acquisition in the experiment. Our numerical results indicate that the causal connectivity obtained through the extended GC analysis is consistent with the underlying synaptic connectivity of the system. This consistency is also insensitive to dynamical regimes, e.g., a chaotic or non-chaotic regime. Since the extended GC analysis could in principle be applied to any nonlinear dynamical system as long as its attractor is low dimensional, our results may potentially be extended to the GC analysis in other settings.

A computational investigation of electrotonic coupling between pyramidal cells in the cortex.

The existence of electrical communication among pyramidal cells (PCs) in the adult cortex has been debated by neuroscientists for several decades. Gap junctions (GJs) among cortical interneurons have been well documented experimentally and their functional roles have been proposed by both computational neuroscientists and experimentalists alike. Experimental evidence for similar junctions among pyramidal cells in the cortex, however, has remained elusive due to the apparent rarity of these couplings among neurons. In this work, we develop a neuronal network model that includes observed probabilities and strengths of electrotonic coupling between PCs and gap-junction coupling among interneurons, in addition to realistic synaptic connectivity among both populations. We use this network model to investigate the effect of electrotonic coupling between PCs on network behavior with the goal of theoretically addressing this controversy of existence and purpose of electrotonically coupled PCs in the cortex.

Coating M-CSF on plastic surface results in the generation of increased numbers of macrophages in vitro.

Macrophages are one of the important cell types in the innate immune system that are present in various anatomical regions of the body and promote early control of pathogens. The relative proportion of macrophages in various lymphoid and non-lymphoid regions is small, and as such it is tedious to purify these cells to homogeneity. Culture of bone marrow precursors with macrophage colony-stimulating factor (M-CSF) results in their differentiation to macrophages, however this procedure results in low numbers of differentiated macrophages. Herein we reveal a new approach of generating increased numbers of differentiated macrophages from bone marrow precursors. We show that M-CSF delivered in a plate-bound form results in the differentiation of significantly more macrophages in comparison to soluble M-CSF. Furthermore, the macrophages differentiated with plate-bound M-CSF display increased metabolic activity and cell death following infection with pathogens.

Maximum entropy principle analysis in network systems with short-time recordings.

In many realistic systems, maximum entropy principle (MEP) analysis provides an effective characterization of the probability distribution of network states. However, to implement the MEP analysis, a sufficiently long-time data recording in general is often required, e.g., hours of spiking recordings of neurons in neuronal networks. The issue of whether the MEP analysis can be successfully applied to network systems with data from short-time recordings has yet to be fully addressed. In this work, we investigate relationships underlying the probability distributions, moments, and effective interactions in the MEP analysis and then show that, with short-time recordings of network dynamics, the MEP analysis can be applied to reconstructing probability distributions of network states that is much more accurate than the one directly measured from the short-time recording. Using spike trains obtained from both Hodgkin-Huxley neuronal networks and electrophysiological experiments, we verify our results and demonstrate that MEP analysis provides a tool to investigate the neuronal population coding properties for short-time recordings.

Eagle Syndrome Secondary to Osteoradionecrosis of the Styloid Process.

BACKGROUND: Eagle syndrome is a rare condition caused by elongation of the styloid process or ossification of the stylohyoid ligament. The symptomatology can be vague but may include dysphagia, odynophagia, otalgia, foreign body sensation, facial pain, trismus, headache, tinnitus, increased salivation, and/or voice changes. CASE REPORT: We present the case of a 58-year-old male believed to have acquired Eagle syndrome secondary to osteoradionecrosis of the styloid process following radiation therapy used as adjuvant treatment for a surgically resected pT2N1M0 squamous cell carcinoma of the right tonsil. CONCLUSION: Radiation is a common component of treatment for head and neck cancers. The diagnosis of Eagle syndrome secondary to osteoradionecrosis of the styloid process is an elusive, but important, diagnosis to consider because the condition can be treated successfully.

NSQIP as a Predictor of Length of Stay in Patients Undergoing Free Flap Reconstruction.

OBJECTIVE: The National Surgical Quality Improvement Program (NSQIP) calculator was created to improve outcomes and guide cost-effective care in surgery. Patients with head and neck cancer (HNC) undergo ablative and free flap reconstructive surgery with prolonged postoperative courses. METHODS: A case series with chart review was performed on 50 consecutive patients with HNC undergoing ablative and reconstructive free flap surgery from October 2014 to March 2016 at a tertiary care center. Comorbidities and intraoperative and postoperative variables were collected. Predicted length of stay was tabulated with the NSQIP calculator. RESULTS: Thirty-five patients (70%) were male. The mean (SD) age was 67.2 (13.4) years. The mean (SD) length of stay (LOS) was 13.5 (10.3) days. The mean (SD) NSQIP-predicted LOS was 10.3 (2.2) days (P = .027). DISCUSSION: The NSQIP calculator may be an inadequate predictor for LOS in patients with HNC undergoing free flap surgery. Additional study is necessary to determine the accuracy of this tool in this patient population. IMPLICATIONS FOR PRACTICE: Head and neck surgeons performing free flap reconstructive surgery following tumor ablation may find that the NSQIP risk calculator underestimates the LOS in this population.

High CD49f expression is associated with osteosarcoma tumor progression: a study using patient-derived primary cell cultures.

Overall prognosis for osteosarcoma (OS) is poor despite aggressive treatment options. Limited access to primary tumors, technical challenges in processing OS tissues, and the lack of well-characterized primary cell cultures has hindered our ability to fully understand the properties of OS tumor initiation and progression. In this study, we have isolated and characterized cell cultures derived from four central high-grade human OS samples. Furthermore, we used the cell cultures to study the role of CD49f in OS progression. Recent studies have implicated CD49f in stemness and multipotency of both cancer stem cells and mesenchymal stem cells. Therefore, we investigated the role of CD49f in osteosarcomagenesis. First, single cell suspensions of tumor biopsies were subcultured and characterized for cell surface marker expression. Next, we characterized the growth and differentiation properties, sensitivity to chemotherapy drugs, and anchorage-independent growth. Xenograft assays showed that cell populations expressing CD49f(hi) /CD90(lo) cell phenotype produced an aggressive tumor. Multiple lines of evidence demonstrated that inhibiting CD49f decreased the tumor-forming ability. Furthermore, the CD49f(hi) /CD90(lo) cell population is generating more aggressive OS tumor growth and indicating this cell surface marker could be a potential candidate for the isolation of an aggressive cell type in OSs.

Dynamics of the exponential integrate-and-fire model with slow currents and adaptation.

In order to properly capture spike-frequency adaptation with a simplified point-neuron model, we study approximations of Hodgkin-Huxley (HH) models including slow currents by exponential integrate-and-fire (EIF) models that incorporate the same types of currents. We optimize the parameters of the EIF models under the external drive consisting of AMPA-type conductance pulses using the current-voltage curves and the van Rossum metric to best capture the subthreshold membrane potential, firing rate, and jump size of the slow current at the neuron's spike times. Our numerical simulations demonstrate that, in addition to these quantities, the approximate EIF-type models faithfully reproduce bifurcation properties of the HH neurons with slow currents, which include spike-frequency adaptation, phase-response curves, critical exponents at the transition between a finite and infinite number of spikes with increasing constant external drive, and bifurcation diagrams of interspike intervals in time-periodically forced models. Dynamics of networks of HH neurons with slow currents can also be approximated by corresponding EIF-type networks, with the approximation being at least statistically accurate over a broad range of Poisson rates of the external drive. For the form of external drive resembling realistic, AMPA-like synaptic conductance response to incoming action potentials, the EIF model affords great savings of computation time as compared with the corresponding HH-type model. Our work shows that the EIF model with additional slow currents is well suited for use in large-scale, point-neuron models in which spike-frequency adaptation is important.

Coding of odors by temporal binding within a model network of the locust antennal lobe.

The locust olfactory system interfaces with the external world through antennal receptor neurons (ORNs), which represent odors in a distributed, combinatorial manner. ORN axons bundle together to form the antennal nerve, which relays sensory information centrally to the antennal lobe (AL). Within the AL, an odor generates a dynamically evolving ensemble of active cells, leading to a stimulus-specific temporal progression of neuronal spiking. This experimental observation has led to the hypothesis that an odor is encoded within the AL by a dynamically evolving trajectory of projection neuron (PN) activity that can be decoded piecewise to ascertain odor identity. In order to study information coding within the locust AL, we developed a scaled-down model of the locust AL using Hodgkin-Huxley-type neurons and biologically realistic connectivity parameters and current components. Using our model, we examined correlations in the precise timing of spikes across multiple neurons, and our results suggest an alternative to the dynamic trajectory hypothesis. We propose that the dynamical interplay of fast and slow inhibition within the locust AL induces temporally stable correlations in the spiking activity of an odor-dependent neural subset, giving rise to a temporal binding code that allows rapid stimulus detection by downstream elements.

A faith- and community-based approach to identifying the individual at risk for head and neck cancer in an inner city.

OBJECTIVES/HYPOTHESIS: To perform a subset analysis of faith- and community-based screening events to further identify at-risk populations for head and neck cancer in hopes of further focusing screening efforts. STUDY DESIGN: Prospective cohort study. METHODS: Three hundred fifty-three individuals (n=353) presented to community events and self-selected for head and neck cancer screenings. A subgroup analysis focusing on risk factors for the development of head and neck cancer and for poor overall prognosis was performed. Subgroups analyzed were individuals screened at church-affiliated events, social events, or community outreach events at homeless shelters. Statistical analysis was performed using one-tailed analysis of variance test. RESULTS: The outreach group had more risk factors for development of cancer, and a significantly higher proportion who used tobacco (P<.05) and consumed >1 drink/day (P<.05). Those in the outreach and church groups had a greater number of risk factors for a poor prognosis with and neck cancer in comparison with the social group: number of uninsured subjects (P<.05), fewer subjects with private insurance (P<.05), fewer subjects with a primary care provider (P<.05), and more subjects with a reported barrier to care (P<.05). CONCLUSIONS: Inhabitants of homeless shelters represent a particularly vulnerable population for both the development and poor prognosis of head and neck cancer. Members of urban church groups are also an at-risk subpopulation due to the prevalence of poor prognostic risk factors. These groups may benefit from future targeted screenings for head and neck cancer.

Haemodynamics-driven developmental pruning of brain vasculature in zebrafish.

The brain blood vasculature consists of a highly ramified vessel network that is tailored to meet its physiological functions. How the brain vasculature is formed has long been fascinating biologists. Here we report that the developing vasculature in the zebrafish midbrain undergoes not only angiogenesis but also extensive vessel pruning, which is driven by changes in blood flow. This pruning process shapes the initial exuberant interconnected meshwork into a simplified architecture. Using in vivo long-term serial confocal imaging of the same zebrafish larvae during 1.5-7.5 d post-fertilization, we found that the early formed midbrain vasculature consisted of many vessel loops and higher order segments. Vessel pruning occurred preferentially at loop-forming segments via a process mainly involving lateral migration of endothelial cells (ECs) from pruned to unpruned segments rather than EC apoptosis, leading to gradual reduction in the vasculature complexity with development. Compared to unpruned ones, pruned segments exhibited a low and variable blood flow, which further decreased irreversibly prior to the onset of pruning. Local blockade of blood flow with micro-bead obstruction led to vessel pruning, whereas increasing blood flow by noradrenergic elevation of heartbeat impeded the pruning process. Furthermore, the occurrence of vessel pruning could be largely predicted by haemodynamics-based numerical simulation of vasculature refinement. Thus, changes of blood flow drive vessel pruning via lateral migration of ECs, leading to the simplification of the vasculature and possibly efficient routing of blood flow in the developing brain.

Coarse-grained event tree analysis for quantifying Hodgkin-Huxley neuronal network dynamics.

We present an event tree analysis of studying the dynamics of the Hodgkin-Huxley (HH) neuronal networks. Our study relies on a coarse-grained projection to event trees and to the event chains that comprise these trees by using a statistical collection of spatial-temporal sequences of relevant physiological observables (such as sequences of spiking multiple neurons). This projection can retain information about network dynamics that covers multiple features, swiftly and robustly. We demonstrate that for even small differences in inputs, some dynamical regimes of HH networks contain sufficiently higher order statistics as reflected in event chains within the event tree analysis. Therefore, this analysis is effective in discriminating small differences in inputs. Moreover, we use event trees to analyze the results computed from an efficient library-based numerical method proposed in our previous work, where a pre-computed high resolution data library of typical neuronal trajectories during the interval of an action potential (spike) allows us to avoid resolving the spikes in detail. In this way, we can evolve the HH networks using time steps one order of magnitude larger than the typical time steps used for resolving the trajectories without the library, while achieving comparable statistical accuracy in terms of average firing rate and power spectra of voltage traces. Our numerical simulation results show that the library method is efficient in the sense that the results generated by using this numerical method with much larger time steps contain sufficiently high order statistical structure of firing events that are similar to the ones obtained using a regular HH solver. We use our event tree analysis to demonstrate these statistical similarities.

Activation of autophagy in mesenchymal stem cells provides tumor stromal support.

Recent studies have implicated multipotential mesenchymal stem cells (MSCs) as an aid to breast cancer cell proliferation and metastasis, partly as a result of the MSCs secretome. As the tumor gets beyond 2 mm in diameter, the stromal cells could undergo starvation due to the lack of sufficient nutrients in solid tumor microenvironment. In this study, we investigated the survival mechanisms used by stressed stromal cells in breast cancers. We used serum-deprived mesenchymal stem cells (SD-MSCs) and MCF-7 breast cancer cells as model system with a hypothesis that stromal cells in the nutrient-deprived core utilize survival mechanisms for supporting surrounding cells. We tested this hypothesis using in vivo tumor xenografts in immunodeficient mice, which indicated that SD-MSCs supported MCF-7 tumor growth by protection from apoptosis. Histochemical assays showed that SD-MSCs-injected tumors exhibited higher cellularity, decreased apoptosis and decreased differentiation. Beclin-1 staining indicated autophagic areas surrounded by actively proliferating cells. Furthermore, in vitro studies demonstrate that SD-MSCs survive using autophagy and secrete paracrine factors that support tumor cells following nutrient/serum deprivation. Western blot and immunocytochemistry analysis of SD-MSCs demonstrated upregulation and perinuclear relocation of autophagy key regulators such as beclin-1, ATG10, ATG12, MAP-LC3 and lysosomes. Electron microscopic analysis detected a time-dependent increase in autophagosome formation and HDAC6 activity assays indicated the upregulation of autophagy. Taken together, these data suggest that under nutrient-deprived conditions that can occur in solid tumors, stromal cells utilize autophagy for survival and also secrete anti-apoptotic factors that can facilitate solid tumor survival and growth.

Pseudo-Lyapunov exponents and predictability of Hodgkin-Huxley neuronal network dynamics.

We present a numerical analysis of the dynamics of all-to-all coupled Hodgkin-Huxley (HH) neuronal networks with Poisson spike inputs. It is important to point out that, since the dynamical vector of the system contains discontinuous variables, we propose a so-called pseudo-Lyapunov exponent adapted from the classical definition using only continuous dynamical variables, and apply it in our numerical investigation. The numerical results of the largest Lyapunov exponent using this new definition are consistent with the dynamical regimes of the network. Three typical dynamical regimes-asynchronous, chaotic and synchronous, are found as the synaptic coupling strength increases from weak to strong. We use the pseudo-Lyapunov exponent and the power spectrum analysis of voltage traces to characterize the types of the network behavior. In the nonchaotic (asynchronous or synchronous) dynamical regimes, i.e., the weak or strong coupling limits, the pseudo-Lyapunov exponent is negative and there is a good numerical convergence of the solution in the trajectory-wise sense by using our numerical methods. Consequently, in these regimes the evolution of neuronal networks is reliable. For the chaotic dynamical regime with an intermediate strong coupling, the pseudo-Lyapunov exponent is positive, and there is no numerical convergence of the solution and only statistical quantifications of the numerical results are reliable. Finally, we present numerical evidence that the value of pseudo-Lyapunov exponent coincides with that of the standard Lyapunov exponent for systems we have been able to examine.

A successful combined endovascular and surgical treatment of a cranial base mucormycosis with an associated internal carotid artery pseudoaneurysm.

OBJECTIVE: We report a rare case of internal carotid artery pseudoaneurysm owing to rhinocerebral mucormycosis and review 40 reported cases from 1980 to present. CLINICAL PRESENTATION: A 38-year-old Caucasian man presented with a 3-day history of headache, diplopia, and numbness in the distribution of the left ophthalmic and maxillary branches of the trigeminal nerve. A complete left cavernous syndrome was discovered upon neurological examination. Magnetic resonance imaging scans revealed an inflammatory process involving the paranasal sinuses with extension into the left cavernous sinus, temporal fossa, and petrous bone. INTERVENTION: The patient was immediately treated with amphotericin B, atorvastatin, and daily hyperbaric oxygen sessions before surgical intervention. The patient underwent endovascular treatment of the associated mycotic pseudoaneurysm after carotid test occlusion in addition to a radical bilateral debridement of the paranasal sinuses and infratemporal and temporal fossa. CONCLUSION: Aggressive multimodal therapy is imperative for late-stage rhinocerebral mucormycosis. Extensive resection of infected tissue combined with amphotericin B, atorvastatin, and hyperbaric oxygen seems to be the best course of management. If the internal carotid artery is involved, endovascular intervention is clearly an option to attain this goal. Further research and longer follow-up periods are required to better understand the long-term implications of endovascular coiling and hyperbaric oxygen therapy for rhinocerebral mucormycosis.

Library-based numerical reduction of the Hodgkin-Huxley neuron for network simulation.

We present an efficient library-based numerical method for simulating the Hodgkin-Huxley (HH) neuronal networks. The key components in our numerical method involve (i) a pre-computed high resolution data library which contains typical neuronal trajectories (i.e., the time-courses of membrane potential and gating variables) during the interval of an action potential (spike), thus allowing us to avoid resolving the spikes in detail and to use large numerical time steps for evolving the HH neuron equations; (ii) an algorithm of spike-spike corrections within the groups of strongly coupled neurons to account for spike-spike interactions in a single large time step. By using the library method, we can evolve the HH networks using time steps one order of magnitude larger than the typical time steps used for resolving the trajectories without the library, while achieving comparable resolution in statistical quantifications of the network activity, such as average firing rate, interspike interval distribution, power spectra of voltage traces. Moreover, our large time steps using the library method can break the stability requirement of standard methods (such as Runge-Kutta (RK) methods) for the original dynamics. We compare our library-based method with RK methods, and find that our method can capture very well phase-locked, synchronous, and chaotic dynamics of HH neuronal networks. It is important to point out that, in essence, our library-based HH neuron solver can be viewed as a numerical reduction of the HH neuron to an integrate-and-fire (I&F) neuronal representation that does not sacrifice the gating dynamics (as normally done in the analytical reduction to an I&F neuron).

Comparative effect of soy protein, soy isoflavones, and 17beta-estradiol on bone metabolism in adult ovariectomized rats.

UNLABELLED: This study provided a comprehensive investigation on the effect of soy protein and soy isoflavones on both calcium and bone metabolism in virgin adult rats. The measurements included bone histology, calcium kinetic modeling, calcium balance, bone densitometry, and whole body densitometry. Results confirmed the bone-preserving effect of estrogen but did not support a bone-sparing role of soy isoflavones. INTRODUCTION: Several animal and short-term human studies have indicated that soy protein isolate enriched with isoflavones may be used as an alternative therapy to estrogen replacement therapy. However, none of the previous studies have investigated this estrogenic effect on both calcium and bone metabolism in animals or humans, which is essential in ascertaining the mode of action of isoflavones. MATERIALS AND METHODS: This study was designed to determine the effects of soy protein versus isoflavones on calcium and bone metabolism in an ovariectomized rat model. Unmated 6-month-old ovariectomized and sham-operated female Sprague-Dawley rats were randomly assigned to nine groups (16 rats/group) and pair-fed soy- or casein-based diets with or without isoflavones for 8 weeks. A reference group was administered estrogen through subcutaneous implants (20-35 pg/liter plasma). Bone densitometry, histomorphometry, and mechanical testing were used to study bone metabolism and quality. Calcium metabolism was studied using calcium tracer balance and kinetics. RESULTS: After ovariectomy, estrogen prevented bone loss in trabecular bone and suppressed formation on both trabecular and cortical bone surfaces. Isoflavones given as enriched soy protein isolate or supplements did not prevent trabecular bone loss. Combining isoflavones with estrogen had no additional benefits over estrogen alone. There were no differences in response to isoflavones caused by protein source. None of the treatments significantly affected either total Ca balance or (45)Ca absorption. However, soy protein showed significant effects on reducing urinary loss of Ca in animals, irrespective of isoflavone level, perhaps because of the lower amount of sulfur-containing amino acids in soy protein. CONCLUSION: Estrogen, but not isoflavones at the levels tested, suppressed bone remodeling in both trabecular and cortical bone after ovariectomy.