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Background Failure to rescue (FTR) is increasingly recognised as a measure of the quality care provided by a health service in recognising and responding to patient deterioration. We report the association between a patient’s pre-operative status and FTR following major abdominal surgery. Methods A retrospective chart review was conducted on patients who underwent major abdominal surgery and who suffered Clavien–Dindo (CDC) III-V complications at the University Hospital Geelong between 2012 and 2019. For each patient suffering a major complication, pre-operative risk factors including demographics, comorbidities (Charlson Comorbidity Index (CCI)), American Society of Anaesthesiology (ASA) Score and biochemistry were compared for patients who survived and patients who died. Statistical analysis utilised logistic regression with results reported as odds ratios (ORs) and 95% confidence intervals (CIs). Results There were 2579 patients who underwent major abdominal surgery, of whom 374 (14.5%) suffered CDC III-V complications. Eighty-eight patients subsequently died from their complication representing a 23.5% FTR and an overall operative mortality of 3.4%. Pre-operative risk factors for FTR included ASA score ≥ 3, CCI ≥ 3 and pre-operative serum albumin of Conclusion Identification of patients at high risk of FTR should they develop a complication would inform shared decision-making, highlight the need for optimisation prior to surgery, or in some cases, result in surgery not being undertaken.

Significance Coordinated activity of sensory and motor cortices is essential for adjusting movements based on sensory feedback. Sensory and motor cortices communicate directly as well as via the thalamus and also receive indirect input from the cerebellum. We show here that cerebellar activity can affect the amplitude and coherence of fast sensorimotor responses in the primary somatosensory and motor cortices upon whisker stimulation. The cerebellum can differentially alter sensory-induced theta- and gamma-band cortical coherences via a fast ascending pathway. In line with the functional heterogeneity of its modular organization, cerebellar impact is region-specific and tuned to ongoing motor responses. Our data highlight site-specific and context-dependent cerebello-cerebral interactions that can come into play during a plethora of sensorimotor functions., Activity of sensory and motor cortices is essential for sensorimotor integration. In particular, coherence between these areas may indicate binding of critical functions like perception, motor planning, action, or sleep. Evidence is accumulating that cerebellar output modulates cortical activity and coherence, but how, when, and where it does so is unclear. We studied activity in and coherence between S1 and M1 cortices during whisker stimulation in the absence and presence of optogenetic Purkinje cell stimulation in crus 1 and 2 of awake mice, eliciting strong simple spike rate modulation. Without Purkinje cell stimulation, whisker stimulation triggers fast responses in S1 and M1 involving transient coherence in a broad spectrum. Simultaneous stimulation of Purkinje cells and whiskers affects amplitude and kinetics of sensory responses in S1 and M1 and alters the estimated S1–M1 coherence in theta and gamma bands, allowing bidirectional control dependent on behavioral context. These effects are absent when Purkinje cell activation is delayed by 20 ms. Focal stimulation of Purkinje cells revealed site specificity, with cells in medial crus 2 showing the most prominent and selective impact on estimated coherence, i.e., a strong suppression in the gamma but not the theta band. Granger causality analyses and computational modeling of the involved networks suggest that Purkinje cells control S1–M1 phase consistency predominantly via ventrolateral thalamus and M1. Our results indicate that activity of sensorimotor cortices can be dynamically and functionally modulated by specific cerebellar inputs, highlighting a widespread role of the cerebellum in coordinating sensorimotor behavior.

We present the concept of a novel thermal power plant process in conjunction with low-temperature selective catalytic reduction (SCR). This process can be employed to achieve modern standards for NOx emissions and solve problems related to post-gas cleaning processes, such as thermal fatigue, catalyst damage, and an increase in differential pressure in the boiler. Therefore, this study is aimed at evaluating the performance of a novel flue-gas cleaning process for use in a thermal power plant, where a low-temperature SCR is implemented, along with the existing SCR. We developed a process model for a large-scale power plant, in which the thermal power plant was divided into a series of heat exchanger block models. The mass and energy balances were solved by considering the heat transfer interaction between the hot and cold sides to obtain the properties of each material flow. Using the process model, we performed a simulation of the new process. New optimal operating conditions were derived, and the effects that the new facilities have on the existing process were evaluated. The results show that the new process is feasible in terms of operating stability and cost, as well as showing an increase in the boiler thermal efficiency of up to 1.3%.

Both spike rate and timing transmit information in the brain, yet how rate-modulated cellular properties affect spike timing is largely unexplored. Phase response curves (PRCs), quantifying how a neuron transforms input to output by spike timing, exhibit strong rate-adaptation, but its mechanism and relevance for network output are poorly understood. Using our Purkinje cell (PC) model and pyramidal neuron model, we demonstrate that the rate-adaptation is caused by rate-dependent subthreshold membrane potentials efficiently regulating the activation of Na + channels. Then we use a realistic PC network model to examine how rate-dependent responses synchronize spikes in the scenario of reciprocal inhibition-caused high-frequency oscillations. Large and broad PRCs at high rates increase oscillation power and spike correlations. The irregularity of spiking and the network connectivity also regulate oscillations. The combination of these factors enables transient oscillations between fast-spiking neurons. Our work demonstrates that rate-adaptation of PRCs can spatio-temporally organize neuronal output.

Mammalian circadian clocks have a hierarchical organization, governed by the suprachiasmatic nucleus (SCN) in the hypothalamus. The brain itself contains multiple loci that maintain autonomous circadian rhythmicity, but the contribution of the non-SCN clocks to this hierarchy remains unclear. We examine circadian oscillations of clock gene expression in various brain loci and discovered that in mouse, robust, higher amplitude, relatively faster oscillations occur in the choroid plexus (CP) compared to the SCN. Our computational analysis and modeling show that the CP achieves these properties by synchronization of "twist" circadian oscillators via gap-junctional connections. Using an in vitro tissue coculture model and in vivo targeted deletion of the Bmal1 gene to silence the CP circadian clock, we demonstrate that the CP clock adjusts the SCN clock likely via circulation of cerebrospinal fluid, thus finely tuning behavioral circadian rhythms.

[This corrects the article DOI: 10.1371/journal.pcbi.1005754.].

Mammalian circadian clocks have a hierarchical organization, governed by the suprachiasmatic nucleus (SCN) in the hypothalamus. The brain itself contains multiple loci that maintain autonomous circadian rhythmicity, but the contribution of the non-SCN clocks to this hierarchy remains unclear. We examine circadian oscillations of clock gene expression in various brain loci and discovered that in mouse, robust, higher amplitude, relatively faster oscillations occur in the choroid plexus (CP) compared to the SCN. Our computational analysis and modeling show that the CP achieves these properties by synchronization of “twist” circadian oscillators via gap-junctional connections. Using an in vitro tissue coculture model and in vivo targeted deletion of the Bmal1 gene to silence the CP circadian clock, we demonstrate that the CP clock adjusts the SCN clock likely via circulation of cerebrospinal fluid, thus finely tuning behavioral circadian rhythms., The suprachiasmatic nucleus (SCN) has been thought of as the master circadian clock, but peripheral circadian clocks do exist. Here, the authors show that the choroid plexus displays oscillations more robust than the SCN and that can be described as a Poincaré oscillator with negative twist.

The granular layer, which mainly consists of granule and Golgi cells, is the first stage of the cerebellar cortex and processes spatiotemporal information transmitted by mossy fiber inputs with a wide variety of firing patterns. To study its dynamics at multiple time scales in response to inputs approximating real spatiotemporal patterns, we constructed a large-scale 3D network model of the granular layer. Patterned mossy fiber activity induces rhythmic Golgi cell activity that is synchronized by shared parallel fiber input and by gap junctions. This leads to long distance synchrony of Golgi cells along the transverse axis, powerfully regulating granule cell firing by imposing inhibition during a specific time window. The essential network mechanisms, including tunable Golgi cell oscillations, on-beam inhibition and NMDA receptors causing first winner keeps winning of granule cells, illustrate how fundamental properties of the granule layer operate in tandem to produce (1) well timed and spatially bound output, (2) a wide dynamic range of granule cell firing and (3) transient and coherent gating oscillations. These results substantially enrich our understanding of granule cell layer processing, which seems to promote spatial group selection of granule cell activity as a function of timing of mossy fiber input., Author summary The cerebellum is an organ of peculiar geometrical properties, and has been attributed the function of applying spatiotemporal transforms to sensorimotor data since Eccles. In this work we have analyzed the spatiotemporal response properties of the first part of the cerebellar circuit, the granule layer. On the basis of a biophysically plausible and large-scale model of the cerebellum, constrained by a wealth of anatomical data, we study the network dynamics and firing properties of individual cell populations in response to 'realistic' input patterns. We make specific predictions about the spatiotemporal features of granule layer processing regarding the effects of the gap junction coupled network of Golgi cells on a spatially restricted input, in an effect we denominate first-takes-all. Furthermore, we calculate that the granule cell layer has a wide dynamic range, indicating that this is a system that can transmit large variations of input intensities.

This study aimed to evaluate the effect of biocompatible polymers on the physicochemical and dissolution properties of poorly water-soluble drugs in nanoparticle systems. Four types of nanoparticles containing poorly water-soluble fenofibrate were prepared using solvent evaporation technique with different biocompatible polymers such as polyvinylpyrrolidone (PVP), hydroxypropylmethyl cellulose (HPMC), carbopol and ethylcellulose. Their physicochemical properties were investigated using scanning electron microscopy, differential scanning calorimetry, and powder X-ray diffraction. The solubility and dissolution of nanoparticle-entrapped fenofibrate were compared with those of free drug powder. Biocompatible polymers affected the morphology and sizes of fenofibrate nanoparticles. PVP or carbopol-based nanoparticles showed spherical appearance, whereas HPMC or ethylcellulose-based nanoparticles formed aggregates with irregular shape. The particle sizes increased in the order of the nanoparticle prepared with carbopol ≤ PVP HPMC > carbopol > ethylcellulose. The enhanced solubility and dissolution of poorly water-soluble fenofibrate via nanoparticle system did not depend on particle size but on crystallinity. In conclusion, in nanoparticle development of poorly water-soluble drugs such as fenofibrate, the nature of biocompatible polymers plays an important role in the physicochemical and dissolution of poorly water-soluble drugs in the nanoparticles.

Circadian oscillators in the suprachiasmatic nucleus (SCN) collectively orchestrate 24 h rhythms in the body while also coding for seasonal rhythms. Although synchronization is required among SCN oscillators to provide robustness for regular timekeeping (Herzog et al., 2004), heterogeneity of period and phase distributions is needed to accommodate seasonal variations in light duration (Pittendrigh and Daan, 1976b). In the mouse SCN, the heterogeneous phase distribution has been recently found in the cycling of clock genes Period 1 and Period 2 (Per1, Per2) and has been shown to reorganize by relative day lengths (Inagaki et al., 2007). However, it is not yet clearly understood what underlies the spatial patterning of Per1 and Per2 expression (Yamaguchi et al., 2003; Foley et al., 2011) and its plasticity. We found that the period of the oscillation in Bmal1 expression, a positive-feedback component of the circadian clock, preserves the behavioral circadian period under culture and drives clustered oscillations in the mouse SCN. Pharmacological and physical isolations of SCN subregions indicate that the period of Bmal1 oscillation is subregion specific and is preserved during culture. Together with computer simulations, we show that either the intercellular coupling does not strongly influence the Bmal1 oscillation or the nature of the coupling is more complex than previously assumed. Furthermore, we have found that the region-specific periods are modulated by the light conditions that an animal is exposed to. Based on these, we suggest that the period forms the basis of seasonal coding in the SCN.

The mammalian suprachiasmatic nucleus (SCN) forms not only the master circadian clock but also a seasonal clock. This neural network of ∼10,000 circadian oscillators encodes season-dependent day-length changes through a largely unknown mechanism. We show that region-intrinsic changes in the SCN fine-tune the degree of network synchrony and reorganize the phase relationship among circadian oscillators to represent day length. We measure oscillations of the clock gene Bmal1, at single-cell and regional levels in cultured SCN explanted from animals raised under short or long days. Coupling estimation using the Kuramoto framework reveals that the network has couplings that can be both phase-attractive (synchronizing) and -repulsive (desynchronizing). The phase gap between the dorsal and ventral regions increases and the overall period of the SCN shortens with longer day length. We find that one of the underlying physiological mechanisms is the modulation of the intracellular chloride concentration, which can adjust the strength and polarity of the ionotropic GABAA-mediated synaptic input. We show that increasing day-length changes the pattern of chloride transporter expression, yielding more excitatory GABA synaptic input, and that blocking GABAA signaling or the chloride transporter disrupts the unique phase and period organization induced by the day length. We test the consequences of this tunable GABA coupling in the context of excitation–inhibition balance through detailed realistic modeling. These results indicate that the network encoding of seasonal time is controlled by modulation of intracellular chloride, which determines the phase relationship among and period difference between the dorsal and ventral SCN.

The growth characteristics of Pb(ZrxTi1-x)O3 (PZT) thin films were investigated for application to high-density ferroelectric random access memories (FeRAM) devices. Films were grown by the liquid source metal-organic chemical vapor deposition (LS-MOCVD) method with tmhd-family precursors, such as Pb(tmhd)2, Zr(tmhd)2(OiPr)2 and Ti(tmhd)2(OiPr)2, dissolved in octane. Film deposition was mainly performed at 560°C, because it is the highest temperature at which bottom electrode contact could be maintained against oxidation in our capacitor over bit-line (COB) structure. The control of Pb precursor supply plays the most critical role in realizing a reliable process for PZT thin film deposition. We have monitored the changes in the microstructure and electrical properties of films on increasing the Pb precursor supply into the reaction chamber. Under optimized conditions, Ir/IrO2/PZT(100 nm)/Ir capacitor shows well-saturated hysteresis loops with a remanent polarization (Pr) of ~ 28 µC/cm2 and coercive voltage of 0.8 V at 2.5 V.

Cerebellar Purkinje neurons generate characteristic complex spikes; but are these bursts of activity generated by somatic or dendritic excitability? A recent study may have settled this debate by giving the soma the dominant role, but it does not fully resolve the question of what information is transmitted downstream of the Purkinje cells.

In this study, we identified different strains of Bifidobacterium isolates from ten set of discordant monozygotic twin pairs who has more than 10% of differential BMI index and compared their strai...

Hong S, Robberechts Q, De Schutter E. Efficient estimation of phase-response curves via compressive sensing. J Neurophysiol 108: 2069-2081, 2012. First published June 20, 2012; doi: 10.1152/jn.00919.2011.-The phase-response curve (PRC), relating the phase shift of an oscillator to external perturbation, is an important tool to study neurons and their population behavior. It can be experimentally estimated by measuring the phase changes caused by probe stimuli. These stimuli, usually short pulses or continuous noise, have a much wider frequency spectrum than that of neuronal dynamics. This makes the experimental data high dimensional while the number of data samples tends to be small. Current PRC estimation methods have not been optimized for efficiently discovering the relevant degrees of freedom from such data. We propose a systematic and efficient approach based on a recently developed signal processing theory called compressive sensing (CS). CS is a framework for recovering sparsely constructed signals from undersampled data and is suitable for extracting information about the PRC from finite but high-dimensional experimental measurements. We illustrate how the CS algorithm can be translated into an estimation scheme and demonstrate that our CS method can produce good estimates of the PRCs with simulated and experimental data, especially when the data size is so small that simple approaches such as naive averaging fail. The tradeoffs between degrees of freedom vs. goodness-of-fit were systematically analyzed, which help us to understand better what part of the data has the most predictive power. Our results illustrate that finite sizes of neuroscientific data in general compounded by large dimensionality can hamper studies of the neural code and suggest that CS is a good tool for overcoming this challenge.

Correlated spiking has been widely observed, but its impact on neural coding remains controversial. Correlation arising from comodulation of rates across neurons has been shown to vary with the firing rates of individual neurons. This translates into rate and correlation being equivalently tuned to the stimulus; under those conditions, correlated spiking does not provide information beyond that already available from individual neuron firing rates. Such correlations are irrelevant and can reduce coding efficiency by introducing redundancy. Using simulations and experiments in rat hippocampal neurons, we show here that pairs of neurons receiving correlated input also exhibit correlations arising from precise spike-time synchronization. Contrary to rate comodulation, spike-time synchronization is unaffected by firing rate, thus enabling synchrony- and rate-based coding to operate independently. The type of output correlation depends on whether intrinsic neuron properties promote integration or coincidence detection: “ideal” integrators (with spike generation sensitive to stimulus mean) exhibit rate comodulation, whereas ideal coincidence detectors (with spike generation sensitive to stimulus variance) exhibit precise spike-time synchronization. Pyramidal neurons are sensitive to both stimulus mean and variance, and thus exhibit both types of output correlation proportioned according to which operating mode is dominant. Our results explain how different types of correlations arise based on how individual neurons generate spikes, and why spike-time synchronization and rate comodulation can encode different stimulus properties. Our results also highlight the importance of neuronal properties for population-level coding insofar as neural networks can employ different coding schemes depending on the dominant operating mode of their constituent neurons.

Previous studies have suggested that the activity pattern of a cerebellar Purkinje cells (PC) is significantly controlled by voltage activated Ca2+ channels and Ca2+ activated K+ channels, present mainly on its elaborate dendritic tree [1]. Although the main somatic excitatory drive propagates very weakly into the dendritic tree [2], somehow a significant interaction between somatic and dendritic spiking occurs. Ca2+ entering through P-type channel is thought to be the main source of this excitability modulation, and this Ca2+ influx also activates large conductance (BK) and small conductance (SK) Ca2+ dependent K+ channels [1,3]. This interaction often results in the counter-intuitive computational somatic and dendritic spiking behavior of PCs [4], but nevertheless this important aspect has not been thoroughly investigated in previous computational modeling studies.

Pairwise correlation in a population activity is a widelyobserved neural phenomenon. In particular, even withthe same mean stimulus, noisy fluctuations in the popu-lation firings are often correlated, and this so-called noisecorrelation has attracted a lot of attention in regard towhether it might transfer independent informationbeyond a mean population response [1]. However, in thecontext of the common input model where a commoninput noise drives the noise correlation, a recent influen-tial study suggested that the noise correlation must have asimple relationship with the average firing rate, or moreprecisely the average gain, and therefore claimed that thenoise correlation might not carry any independent infor-mation [2].In this work, we carried out a model study to probe thecorrelation-gain/rate relationship with biophysicallydefined single neuron models and found out that the rela-tionship with gain actually fails to capture large noise cor-relations in some models. We suggest that this is closelyrelated to the type 3 excitability of these neuron models.Type 3 excitability has been seen recently in model studies[3] and in some cortical neurons in the