Degradation of intestinal mRNA:A matter of treatment

AIM: To characterize the influence of location, species and treatment upon RNA degradation in tissue samples from the gastrointestinal tract. METHODS: The intestinal samples were stored in different medium for different times under varyingconditions: different species(human and rat), varying temperature(storage on crushed ice or room temperature), time point of dissection of the submucous-mucous layer from the smooth muscle(before or after storage), different rinsing methods(rinsing with Medium, PBS, RNALater or without rinsing at all) and different regions of the gut(proximal and distal small intestine, caecum, colon and rectum). The total RNA from different parts of the gut(rat: proximal and distal small intestine, caecum, colon and rectum, human: colon and rectum) and individual gut layers(muscle and submucosal/mucosal) was extracted. The quality of the RNA was assessed by micro capillary electrophoresis. The RNA quality was expressed by the RNA integrity number which is calculated from the relative height and area of the 18 S and 28 S RNA peaks. From rat distal small intestine q PCR was performed for neuronal and glial markers.RESULTS: RNA obtained from smooth muscle tissue is much longer stable than those from submucosal/mucosal tissue. At RT muscle RNA degrades after one day, on ice it is stable at least three days. Cleaning and separation of gut layers before storage and use of RNALater, maintains the stability of muscle RNA at RT for much longer periods. Different parts of the gut show varying degradation periods. RNA obtained from the submucosal/mucosal layer always showed a much worse amplification rate than RNA from muscle tissue. In general RNA harvested from rat tissue, either smooth muscle layer or submucosal/mucosal layer is much longer stable than RNA from human gut tissue, and RNA obtained from smooth muscle tissue shows an increased stability compared to RNA from submucosal/mucosal tissue. At RT muscle RNA degrades after one day, while the stability on ice lasts at least three days. Cleaning and separation of gut layers before storage and use of RNALater, maintains the stability of muscle RNA at RT for much longer periods. Different parts of the gut show varying degradation periods. The RNA from muscle and submucosal/mucosal tissue of the proximal small intestine degrades much faster than the RNA of distal small intestine, caecum or colonwith rectum. RNA obtained from the submucosal/mucosal layer always showed a much more reduced amplification rate than RNA from muscle tissue [β-Tubulin Ⅲ for muscle quantification cycle(Cp): 22.07 ± 0.25, for β-Tubulin Ⅲ submucosal/mucosal Cp: 27.42 ± 0.19].CONCLUSION: Degradation of intestinal m RNA depends on preparation and storage conditions of the tissue. Cooling, rinsing and separating of intestinal tissue reduce the degradation of m RNA.     

Interleukin‐10 is a critical regulator of white matter lesion containment following viral induced demyelination

Neurotropic coronavirus induces an acute encephalomyelitis accompanied by focal areas of demyelination distributed randomly along the spinal column. The initial areas of demyelination increase only slightly after the control of infection. These circumscribed focal lesions are characterized by axonal sparing, myelin ingestion by macrophage/microglia, and glial scars associated with hypertrophic astrocytes, which proliferate at the lesion border. Accelerated virus control in mice lacking the anti‐inflammatory cytokine IL‐10 was associated with limited initial demyelination, but low viral mRNA persistence similar to WT mice and declining antiviral cellular immunity. Nevertheless, lesions exhibited sustained expansion providing a model of dysregulated white matter injury temporally remote from the acute CNS insult. Expanding lesions in the absence of IL‐10 are characterized by sustained microglial activation and partial loss of macrophage/microglia exhibiting an acquired deactivation phenotype. Furthermore, IL‐10 deficiency impaired astrocyte organization into mesh like structures at the lesion borders, but did not prevent astrocyte hypertrophy. The formation of discrete foci of demyelination in IL‐10 sufficient mice correlated with IL‐10 receptor expression exclusively on astrocytes in areas of demyelination suggesting a critical role for IL‐10 signaling to astrocytes in limiting expansion of initial areas of white matter damage. GLIA 2015;63:2106–2120     

Fast sensory–motor reactions in echolocating bats to sudden changes during the final buzz and prey intercept

Echolocation is an active sense enabling bats and toothed whales to orient in darkness through echo returns from their ultrasonic signals. Immediately before prey capture, both bats and whales emit a buzz with such high emission rates (≥180 Hz) and overall duration so short that its functional significance remains an enigma. To investigate sensory–motor control during the buzz of the insectivorous bat Myotis daubentonii, we removed prey, suspended in air or on water, before expected capture. The bats responded by shortening their echolocation buzz gradually; the earlier prey was removed down to approximately 100 ms (30 cm) before expected capture, after which the full buzz sequence was emitted both in air and over water. Bats trawling over water also performed the full capture behavior, but in-air capture motions were aborted, even at very late prey removals (<20 ms = 6 cm before expected contact). Thus, neither the buzz nor capture movements are stereotypical, but dynamically adapted based on sensory feedback. The results indicate that echolocation is controlled mainly by acoustic feedback, whereas capture movements are adjusted according to both acoustic and somatosensory feedback, suggesting separate (but coordinated) central motor control of the two behaviors based on multimodal input. Bat echolocation, especially the terminal buzz, provides a unique window to extremely fast decision processes in response to sensory feedback and modulation through attention in a naturally behaving animal.Most sensory systems passively sample the environment by relying on extrinsic energy sources like light or sound to stimulate sensory receptors. Truly active senses, e.g., the electric sense of weakly electric fishes (1) and echolocation (2), where the animal itself produces the energy used to probe the surroundings, are rare (3). The advanced echolocation systems of bats and toothed whales involve dynamic adaptation of the outgoing sound and behavior based on perception of the surroundings through information processing of returning echoes.The temporal pattern of echolocation signals during prey pursuit changes through three phases: search, approach, and terminal buzz. The buzz, immediately preceding prey capture, is characterized by a dramatic increase in signal repetition rate and is universally present in both bats and whales capturing moving prey (4–8). Repetition rates up to 640 Hz have been reported for porpoises and, contrary to bats, odontocete buzzes usually continue beyond prey contact (6). The buzz of many vespertilionid and molossid bats has two distinct subphases: buzz I with decreasing call durations and intervals, followed by buzz II, with a constant maximum call repetition rate and a characteristic frequency drop of up to an octave (4, 9–14).The function of the terminal buzz is still not understood (15). It has been hypothesized that odontocete buzzes not only track prey before capture (7), but may also serve to follow escaping prey (6). Bat buzzes have also been hypothesized to help track evasive targets (16). Other suggestions are distance gauging by pitch perception (17), or guidance to a safe landing (18). In contrast, Melcón et al. argue that echo returns from buzz II would reach the bat too late to serve immediate adaptive reactions when buzz II starts around 50 ms before contact, corresponding to the estimated reaction time. Instead, they propose that buzz II provides post hoc information, helping bats assess the cause of unsuccessful capture attempts and eventually react adequately (19).Here we examined the buzz by provoking very fast acoustic and flight behavior responses in the bat Myotis daubentonii (Vespertilionidae). M. daubentonii catches insects from water surfaces (trawling) or occasionally in air. Its echolocation calls are frequency modulated from 90 down to 40 kHz. In buzz II, call rates increase to 180–200 Hz (12, 20, 21). In two parallel series of experiments, in the field and in a flight room, we suddenly removed the prey in the final phase of pursuit down to a few milliseconds before expected capture. Based on our findings, we discuss the function of the final buzz and rapid dynamic adjustments of motor output and decision making in response to fast sensory feedback in general.     

Musical expertise is related to altered functional connectivity during audiovisual integration

The present study investigated the cortical large-scale functional network underpinning audiovisual integration via magnetoencephalographic recordings. The reorganization of this network related to long-term musical training was investigated by comparing musicians to nonmusicians. Connectivity was calculated on the basis of the estimated mutual information of the sources’ activity, and the corresponding networks were statistically compared. Nonmusicians’ results indicated that the cortical network associated with audiovisual integration supports visuospatial processing and attentional shifting, whereas a sparser network, related to spatial awareness supports the identification of audiovisual incongruences. In contrast, musicians’ results showed enhanced connectivity in regions related to the identification of auditory pattern violations. Hence, nonmusicians rely on the processing of visual clues for the integration of audiovisual information, whereas musicians rely mostly on the corresponding auditory information. The large-scale cortical network underpinning multisensory integration is reorganized due to expertise in a cognitive domain that largely involves audiovisual integration, indicating long-term training-related neuroplasticity.Multisensory integration is of such importance for our understanding of the surrounding world that its cortical correlates interact with most of the neocortical regions, including the ones traditionally considered as unisensory (1). The cortical areas that are usually referred to as multisensory include the superior temporal sulcus, the intraparietal sulcus, and the frontal cortex (2). Nevertheless, recent evidence suggests that multisensory perception engages more widespread areas than what the classic modular approaches have so far assumed (1). Moreover, audiovisual integration emerges from a dynamic interplay of distributed regions operating in large-scale networks (3).The amount of shared information within these large-scale networks of distributed neuronal groups conceptualizes the notion of functional connectivity (4). Recent methodological advances allow the identification of networks that emerge from whole-brain analyses of neuroimaging data such as functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG) (5) and provide fertile ground for studying the functional connectivity patterns of higher cognitive processes. These kinds of networks are modeled as graphs composed of nodes, which represent the cortical areas contributing to the network, and by edges, which represent the connections between the nodes. Each network has specific attributes that quantify connectivity organization (6). These graphs depict the functional connectome of the respective cognitive processes. Recent evidence suggests that functional connectivity networks may be reorganized by factors mediating neuroplasticity such as learning and development (7), altering information processing pathways.Music notation reading encapsulates auditory, visual, and motor information in a highly organized manner and therefore provides a useful model for studying multisensory phenomena (8). A recent study by Paraskevopoulos et al. (9) used MEG to reveal the cortical response related to identification of audiovisual incongruences. These incongruences occurred on the basis of an explicitly learned rule, binding otherwise unrelated unisensory stimuli. The rule was comparable to musical reading: “the higher the position of the circle, the higher the pitch of the tone.” We recorded cortical responses to violations of this rule, to incongruences between expected auditory and visual input. This response was located in frontotemporal cortical areas. Plasticity effects related to long-term musical training were investigated in this cross-sectional study by comparison of musicians and nonmusicians, whereas effects of short-term music reading training were investigated in a follow-up longitudinal study that allowed causal inference of the neuroplastic effects (10).A recent fMRI study by Lee and Noppeney (11) investigated how sensorimotor experience molds temporal binding of auditory and visual signals. The results of this study indicated that musicians exhibited increased audiovisual asynchrony responses and increased connectivity selectively for music, and not for speech, in a superior temporal sulcus–premotor–cerebellar circuitry that was defined and constrained by the corresponding fMRI activation results. Nevertheless, larger scale connectivity networks underpinning multisensory perception still remain undiscovered.The goal of the present study was to investigate the functional connectivity of the cortical network underpinning audiovisual integration, and particularly the identification of abstract audiovisual incongruences. Additionally, we aimed to address how this network is reorganized due to learning and whether expertise in a cognitive domain that largely involves audiovisual integration, such as music reading, may relate to changes in whole-brain functional connectivity. To this aim we used MEG to measure the cortical connectivity of a group of musicians and a group of musically naïve controls to congruent and incongruent audiovisual stimuli (Fig. 1). Source analysis was performed using a realistic head model to solve the forward problem and standardized low resolution electromagnetic tomography (sLORETA) (12) to solve the inverse one. The source time series were analyzed in terms of their underlying connectivity, by measuring their mutual information (MI) and applying a statistical model to extract the significant connections of the network. This approach allowed us to identify the corresponding whole-head, node-to-node network following a graph theoretical approach. Our hypothesis for this analysis was that a widespread network connecting cortical areas previously identified to be important for audiovisual integration would emerge. Regarding training effects, we anticipated that musicians would show greater connectivity between distributed cortical areas and that the network characteristics would indicate enhanced processing efficacy compared with the nonmusicians'' network.Open in a separate windowFig. 1.Paradigm of an audiovisual congruent and incongruent trial. (A) A congruent trial. (B) An incongruent trial. The line “time” represents the duration of the presentation of the auditory and visual part of the stimulus. The last picture of each trial represents the intertrial stimulus in which subjects had to answer if the trial was congruent or incongruent.     

Day-to-day variations in health behaviors and daily functioning: two intensive longitudinal studies

In two intensive longitudinal studies we examined the daily dynamics in health behaviors and their associations with two important indicators of young adults’ daily functioning, namely, affect and academic performance. Over a period of 8 months, university students (Study 1: N = 292; Study 2: N = 304) reported sleep, physical activity, snacking, positive and negative affect, and learning goal achievement. A subsample wore an actigraph to provide an additional measurement of sleep and physical activity and participated in a controlled laboratory snacking situation. Multilevel structural equation models showed that better day-to-day sleep quality or more physical activity than usual, but not snacking, were associated with improved daily functioning, namely, affect and learning goal achievement. Importantly, self-report measurements of health behaviors correlated with behavioral measurements. These findings have the potential to inform health promotion programs aimed at supporting young adults in their daily functioning in good physical and mental health.     

Sulfadiazine—Chitosan Conjugates and Their Polyelectrolyte Complexes with Hyaluronate Destined to the Management of Burn Wounds

In the present study polyelectrolyte complexes (PECs) based on new sulfadiazine-chitosan conjugates with sodium hyaluronate have been developed with potential use in treatment of burn wounds. The PECs were chemically characterized using Fourier Transform—Infrared Spectroscopy, Scanning Electon Microscopy and Near Infrared Chemical Imaging Technique. The swelling behavior and in vitro sulfadiazine release were also investigated. The antimicrobial activity was evaluated towards three bacterial strains: Escherichia coli, Listeria monocytogenes and Salmonella thyphymurium. The developed PECs demonstrated their antimicrobial efficiency against tested bacterial strains, the PECs containing sulfadiazine-modified chitosan being more active than PECs containing unmodified chitosan.     

System Accuracy Evaluation of Four Systems for Self-Monitoring of Blood Glucose Following ISO 15197 Using a Glucose Oxidase and a Hexokinase-Based Comparison Method

Background:

The standard ISO (International Organization for Standardization) 15197 is widely accepted for the accuracy evaluation of systems for self-monitoring of blood glucose (SMBG). Accuracy evaluation was performed for 4 SMBG systems (Accu-Chek® Aviva, Contour®XT, GlucoCheck XL, GlucoMen® LX PLUS) with 3 test strip lots each. To investigate a possible impact of the comparison method on system accuracy data, 2 different established methods were used.

Methods:

The evaluation was performed in a standardized manner following test procedures described in ISO 15197:2003 (section 7.3). System accuracy was assessed by applying ISO 15197:2003 and in addition ISO 15197:2013 criteria (section 6.3.3). For each system, comparison measurements were performed with a glucose oxidase (YSI 2300 STAT Plus™ glucose analyzer) and a hexokinase (cobas® c111) method.

Results:

All 4 systems fulfilled the accuracy requirements of ISO 15197:2003 with the tested lots. More stringent accuracy criteria of ISO 15197:2013 were fulfilled by 3 systems (Accu-Chek Aviva, ContourXT, GlucoMen LX PLUS) when compared to the manufacturer’s comparison method and by 2 systems (Accu-Chek Aviva, ContourXT) when compared to the alternative comparison method. All systems showed lot-to-lot variability to a certain degree; 2 systems (Accu-Chek Aviva, ContourXT), however, showed only minimal differences in relative bias between the 3 evaluated lots.

Conclusions:

In this study, all 4 systems complied with the evaluated test strip lots with accuracy criteria of ISO 15197:2003. Applying ISO 15197:2013 accuracy limits, differences in the accuracy of the tested systems were observed, also demonstrating that the applied comparison method/system and the lot-to-lot variability can have a decisive influence on accuracy data obtained for a SMBG system.     

Rate-of-Change Dependence of the Performance of Two CGM Systems During Induced Glucose Swings

Introduction:

The accuracy of continuous glucose monitoring (CGM) systems is often assessed with respect to blood glucose (BG) readings. CGM readings are affected by a physiological and a technical time delay when compared to BG readings. In this analysis, the dependence of CGM performance parameters on the BG rate of change was investigated for 2 CGM systems.

Methods:

Data from a previously published study were retrospectively analyzed. An established CGM system (Dexcom G4, Dexcom, San Diego, CA; system A) and a prototype system (Roche Diagnostics GmbH, Mannheim, Germany; system B) with 2 sensors each were worn by 10 subjects in parallel. Glucose swings were induced to achieve rapidly changing BG concentrations. Mean absolute relative differences (MARD) were calculated in different BG rate-of-change categories. In addition, sensor-to-sensor precision was assessed.

Results:

At BG rates of change of –1 mg/dl/min to 0 mg/dl/min and 0 mg/dl/min to +1 mg/dl/min, MARD results were 12.6% and 11.3% for system A and 8.2% and 10.0% for system B. At rapidly changing BG concentrations (<–3 mg/dl/min and ≥+3 mg/dl/min), higher MARD results were found for both systems, but system B was less affected (system A: 24.9% and 29.6%, system B: 10.6% and 16.3%). The impact of rate of change on sensor-to-sensor precision was less pronounced.

Conclusions:

Both systems were affected by rapidly changing BG concentrations to some degree, although system B was mostly unaffected by decreasing BG concentrations. It would seem that technological advancements in CGM systems might allow for a more precise tracking of BG concentrations even at rapidly changing BG concentrations.