Genomic Characterization of Multidrug-Resistant Extended Spectrum ß-Lactamase-Producing Klebsiella pneumoniae from Clinical Samples of a Tertiary Hospital in South Kivu Province, Eastern Democratic Republic of Congo.

Multidrug-resistant (MDR) and extended spectrum ß-lactamase (ESBL)-producing extra-intestinal K. pneumoniae are associated with increased morbidity and mortality. This study aimed to characterize the resistance and virulence profiles of extra-intestinal MDR ESBL-producing K. pneumoniae associated with infections at a tertiary hospital in South-Kivu province, DRC. Whole-genome sequencing (WGS) was carried out on 37 K. pneumoniae isolates displaying MDR and ESBL-producing phenotype. The assembled genomes were analysed for phylogeny, virulence factors and antimicrobial resistance genes (ARG) determinants. These isolates were compared to sub-Saharan counterparts. K. pneumoniae isolates displayed a high genetic variability with up to 16 sequence types (ST). AMR was widespread against ß-lactamases (including third and fourth-generation cephalosporins, but not carbapenems), aminoglycosides, ciprofloxacin, tetracycline, erythromycin, nitrofurantoin, and cotrimoxazole. The blaCTX-M-15 gene was the most common ß-lactamase gene among K. pneumoniae isolates. No carbapenemase gene was found. ARG for aminoglycosides, quinolones, phenicols, tetracyclines, sulfonamides, nitrofurantoin were widely distributed among the isolates. Nine isolates had the colistin-resistant R256G substitution in the pmrB efflux pump gene without displaying reduced susceptibility to colistin. Despite carrying virulence genes, none had hypervirulence genes. Our results highlight the genetic diversity of MDR ESBL-producing K. pneumoniae isolates and underscore the importance of monitoring simultaneously the evolution of phenotypic and genotypic AMR in Bukavu and DRC, while calling for caution in administering colistin and carbapenem to patients.

Medical device SALs and surgical site infections: a mathematical model.

It is commonly accepted that terminally sterilized healthcare products are rarely the source of a hospital-acquired infection (HAI). The vast majority of HAIs arise from human-borne contamination from the workforce, the clinical environment, less-than-aseptic handling techniques, and the patients themselves. Nonetheless, the requirement for a maximal sterility assurance level (SAL) of a terminally sterilized product has remained at 10(-6), which is the probability of one in one million that a single viable microorganism will be on a product after sterilization. This paper presents a probabilistic model that predicts choosing an SAL greater than 10(-6) (e.g. 10(-5) or 10(-4), and in some examples even 10(-3) or 10(-2)) does not have a statistically significant impact on the incidence of surgical site infections (SSIs). The use of a greater SAL might allow new, potentially life-saving products that cannot withstand sterilization to achieve a 10(-6) SAL to be terminally sterilized instead of being aseptically manufactured.

Interactions between core and matrix thalamocortical projections in human sleep spindle synchronization.

Sleep spindles are bursts of 11-15 Hz that occur during non-rapid eye movement sleep. Spindles are highly synchronous across the scalp in the electroencephalogram (EEG) but have low spatial coherence and exhibit low correlation with the EEG when simultaneously measured in the magnetoencephalogram (MEG). We developed a computational model to explore the hypothesis that the spatial coherence spindles in the EEG is a consequence of diffuse matrix projections of the thalamus to layer 1 compared with the focal projections of the core pathway to layer 4 recorded in the MEG. Increasing the fanout of thalamocortical connectivity in the matrix pathway while keeping the core pathway fixed led to increased synchrony of the spindle activity in the superficial cortical layers in the model. In agreement with cortical recordings, the latency for spindles to spread from the core to the matrix was independent of the thalamocortical fanout but highly dependent on the probability of connections between cortical areas.

Thalamic burst firing propensity: a comparison of the dorsal lateral geniculate and pulvinar nuclei in the tree shrew.

Relay neurons in dorsal thalamic nuclei can fire high-frequency bursts of action potentials that ride the crest of voltage-dependent transient (T-type) calcium currents [low-threshold spike (LTS)]. To explore potential nucleus-specific burst features, we compared the membrane properties of dorsal lateral geniculate nucleus (dLGN) and pulvinar nucleus relay neurons using in vitro whole-cell recording in juvenile and adult tree shrew (Tupaia) tissue slices. We injected current ramps of variable slope into neurons that were sufficiently hyperpolarized to de-inactivate T-type calcium channels. In a small percentage of juvenile pulvinar and dLGN neurons, an LTS could not be evoked. In the remaining juvenile neurons and in all adult dLGN neurons, a single LTS could be evoked by current ramps. However, in the adult pulvinar, current ramps evoked multiple LTSs in >70% of recorded neurons. Using immunohistochemistry, Western blot techniques, unbiased stereology, and confocal and electron microscopy, we found that pulvinar neurons expressed more T-type calcium channels (Ca(v) 3.2) and more small conductance potassium channels (SK2) than dLGN neurons and that the pulvinar nucleus contained a higher glia-to-neuron ratio than the dLGN. Hodgkin-Huxley-type compartmental models revealed that the distinct firing modes could be replicated by manipulating T-type calcium and SK2 channel density, distribution, and kinetics. The intrinsic properties of pulvinar neurons that promote burst firing in the adult may be relevant to the treatment of conditions that involve the adult onset of aberrant thalamocortical interactions.

Interplay between spontaneous and induced brain activity during human non-rapid eye movement sleep.

Humans are less responsive to the surrounding environment during sleep. However, the extent to which the human brain responds to external stimuli during sleep is uncertain. We used simultaneous EEG and functional MRI to characterize brain responses to tones during wakefulness and non-rapid eye movement (NREM) sleep. Sounds during wakefulness elicited responses in the thalamus and primary auditory cortex. These responses persisted in NREM sleep, except throughout spindles, during which they became less consistent. When sounds induced a K complex, activity in the auditory cortex was enhanced and responses in distant frontal areas were elicited, similar to the stereotypical pattern associated with slow oscillations. These data show that sound processing during NREM sleep is constrained by fundamental brain oscillatory modes (slow oscillations and spindles), which result in a complex interplay between spontaneous and induced brain activity. The distortion of sensory information at the thalamic level, especially during spindles, functionally isolates the cortex from the environment and might provide unique conditions favorable for off-line memory processing.

Corticothalamic feedback controls sleep spindle duration in vivo.

Spindle oscillations are commonly observed during stage 2 of non-rapid eye movement sleep. During sleep spindles, the cerebral cortex and thalamus interact through feedback connections. Both initiation and termination of spindle oscillations are thought to originate in the thalamus based on thalamic recordings and computational models, although some in vivo results suggest otherwise. Here, we have used computer modeling and in vivo multisite recordings from the cortex and the thalamus in cats to examine the involvement of the cortex in spindle oscillations. We found that although the propagation of spindles depended on synaptic interaction within the thalamus, the initiation and termination of spindle sequences critically involved corticothalamic influences.

"Relevance vector machine" consciousness classifier applied to cerebral metabolism of vegetative and locked-in patients.

The vegetative state is a devastating condition where patients awaken from their coma (i.e., open their eyes) but fail to show any behavioural sign of conscious awareness. Locked-in syndrome patients also awaken from their coma and are unable to show any motor response to command (except for small eye movements or blinks) but recover full conscious awareness of self and environment. Bedside evaluation of residual cognitive function in coma survivors often is difficult because motor responses may be very limited or inconsistent. We here aimed to disentangle vegetative from "locked-in" patients by an automatic procedure based on machine learning using fluorodeoxyglucose PET data obtained in 37 healthy controls and in 13 patients in a vegetative state. Next, the trained machine was tested on brain scans obtained in 8 patients with locked-in syndrome. We used a sparse probabilistic Bayesian learning framework called "relevance vector machine" (RVM) to classify the scans. The trained RVM classifier, applied on an input scan, returns a probability value (p-value) of being in one class or the other, here being "conscious" or not. Training on the control and vegetative state groups was assessed with a leave-one-out cross-validation procedure, leading to 100% classification accuracy. When applied on the locked-in patients, all scans were classified as "conscious" with a mean p-value of .95 (min .85). In conclusion, even with this relatively limited data set, we could train a classifier distinguishing between normal consciousness (i.e., wakeful conscious awareness) and the vegetative state (i.e., wakeful unawareness). Cross-validation also indicated that the clinical classification and the one predicted by the automatic RVM classifier were in accordance. Moreover, when applied on a third group of "locked-in" consciously aware patients, they all had a strong probability of being similar to the normal controls, as expected. Therefore, RVM classification of cerebral metabolic images obtained in coma survivors could become a useful tool for the automated PET-based diagnosis of altered states of consciousness.

Functional neuroimaging insights into the physiology of human sleep.

Functional brain imaging has been used in humans to noninvasively investigate the neural mechanisms underlying the generation of sleep stages. On the one hand, REM sleep has been associated with the activation of the pons, thalamus, limbic areas, and temporo-occipital cortices, and the deactivation of prefrontal areas, in line with theories of REM sleep generation and dreaming properties. On the other hand, during non-REM (NREM) sleep, decreases in brain activity have been consistently found in the brainstem, thalamus, and in several cortical areas including the medial prefrontal cortex (MPFC), in agreement with a homeostatic need for brain energy recovery. Benefiting from a better temporal resolution, more recent studies have characterized the brain activations related to phasic events within specific sleep stages. In particular, they have demonstrated that NREM sleep oscillations (spindles and slow waves) are indeed associated with increases in brain activity in specific subcortical and cortical areas involved in the generation or modulation of these waves. These data highlight that, even during NREM sleep, brain activity is increased, yet regionally specific and transient. Besides refining the understanding of sleep mechanisms, functional brain imaging has also advanced the description of the functional properties of sleep. For instance, it has been shown that the sleeping brain is still able to process external information and even detect the pertinence of its content. The relationship between sleep and memory has also been refined using neuroimaging, demonstrating post-learning reactivation during sleep, as well as the reorganization of memory representation on the systems level, sometimes with long-lasting effects on subsequent memory performance. Further imaging studies should focus on clarifying the role of specific sleep patterns for the processing of external stimuli, as well as the consolidation of freshly encoded information during sleep.

M-type channels selectively control bursting in rat dopaminergic neurons.

Midbrain dopaminergic neurons in the substantia nigra, pars compacta and ventral tegmental area are critically important in many physiological functions. These neurons exhibit firing patterns that include tonic slow pacemaking, irregular firing and bursting, and the amount of dopamine that is present in the synaptic cleft is much increased during bursting. The mechanisms responsible for the switch between these spiking patterns remain unclear. Using both in-vivo recordings combined with microiontophoretic or intraperitoneal drug applications and in-vitro experiments, we have found that M-type channels, which are present in midbrain dopaminergic cells, modulate the firing during bursting without affecting the background low-frequency pacemaker firing. Thus, a selective blocker of these channels, 10,10-bis(4-pyridinylmethyl)-9(10H)-anthracenone dihydrochloride, specifically potentiated burst firing. Computer modeling of the dopamine neuron confirmed the possibility of a differential influence of M-type channels on excitability during various firing patterns. Therefore, these channels may provide a novel target for the treatment of dopamine-related diseases, including Parkinson's disease and drug addiction. Moreover, our results demonstrate that the influence of M-type channels on the excitability of these slow pacemaker neurons is conditional upon their firing pattern.

Some facts about sleep relevant for Landau-Kleffner syndrome.

Our understanding of the neural mechanisms of non-rapid eye movement sleep (NREM) is steadily increasing. Given the intriguing activation of paroxysmal activity during NREM sleep in patients with Landau-Kleffner syndrome (LKS), a thorough characterization of commonalities and differences between the neural correlates of LKS paroxysms and normal sleep oscillations might provide useful information on the neural underpinning of this disorder. Especially, given the suspected role of sleep in brain plasticity, this type of information is needed to assess the link between cognitive deterioration and electroencephalography (EEG) paroxysms during sleep.

An in computo investigation of the Landau-Kleffner syndrome.

We describe a computational model of the thalamus and the cortex able to reproduce some essential epileptiform features commonly observed in the Landau-Kleffner syndrome. Investigation with this realistic model leads us to the formulation of a cellular mechanism that could be responsible for the epileptic discharges occuring with this severe syndrome. Understanding this mechanism is of prime importance for developing new therapeutical strategies.