38 research outputs found
On the Role of the Head Ganglia in Posture and Walking in Insects
In insects, locomotion is the result of rhythm generating thoracic circuits and their modulation by sensory reflexes and by inputs from the two head ganglia, the cerebral and the gnathal ganglia (GNG), which act as higher order neuronal centers playing different functions in the initiation, goal-direction, and maintenance of movement. Current knowledge on the various roles of major neuropiles of the cerebral ganglia (CRG), such as mushroom bodies (MB) and the central complex (CX), in particular, are discussed as well as the role of the GNG. Thoracic and head ganglia circuitries are connected by ascending and descending neurons. While less is known about the ascending neurons, recent studies in large insects and Drosophila have begun to unravel the identity of descending neurons and their appropriate roles in posture and locomotion. Descending inputs from the head ganglia are most important in initiating and modulating thoracic central pattern generating circuitries to achieve goal directed locomotion. In addition, the review will also deal with some known monoaminergic descending neurons which affect the motor circuits involved in posture and locomotion. In conclusion, we will present a few issues that have, until today, been little explored. For example, how and which descending neurons are selected to engage a specific motor behavior and how feedback from thoracic circuitry modulate the head ganglia circuitries. The review will discuss results from large insects, mainly locusts, crickets, and stick insects but will mostly focus on cockroaches and the fruit fly, Drosophila
AMP-Activated Protein Kinase (AMPK) Mediates Nutrient Regulation of Thioredoxin-Interacting Protein (TXNIP) in Pancreatic Beta-Cells
Thioredoxin-interacting protein (TXNIP) regulates critical biological processes including inflammation, stress and apoptosis. TXNIP is upregulated by glucose and is a critical mediator of hyperglycemia-induced beta-cell apoptosis in diabetes. In contrast, the saturated long-chain fatty acid palmitate, although toxic to the beta-cell, inhibits TXNIP expression. The mechanisms involved in the opposing effects of glucose and fatty acids on TXNIP expression are unknown. We found that both palmitate and oleate inhibited TXNIP in a rat beta-cell line and islets. Palmitate inhibition of TXNIP was independent of fatty acid beta-oxidation or esterification. AMP-activated protein kinase (AMPK) has an important role in cellular energy sensing and control of metabolic homeostasis; therefore we investigated its involvement in nutrient regulation of TXNIP. As expected, glucose inhibited whereas palmitate stimulated AMPK. Pharmacologic activators of AMPK mimicked fatty acids by inhibiting TXNIP. AMPK knockdown increased TXNIP expression in presence of high glucose with and without palmitate, indicating that nutrient (glucose and fatty acids) effects on TXNIP are mediated in part via modulation of AMPK activity. TXNIP is transcriptionally regulated by carbohydrate response element-binding protein (ChREBP). Palmitate inhibited glucose-stimulated ChREBP nuclear entry and recruitment to the Txnip promoter, thereby inhibiting Txnip transcription. We conclude that AMPK is an important regulator of Txnip transcription via modulation of ChREBP activity. The divergent effects of glucose and fatty acids on TXNIP expression result in part from their opposing effects on AMPK activity. In light of the important role of TXNIP in beta-cell apoptosis, its inhibition by fatty acids can be regarded as an adaptive/protective response to glucolipotoxicity. The finding that AMPK mediates nutrient regulation of TXNIP may have important implications for the pathophysiology and treatment of diabetes
Non-AIDS defining cancers in the D:A:D Study-time trends and predictors of survival : a cohort study
BACKGROUND:Non-AIDS defining cancers (NADC) are an important cause of morbidity and mortality in HIV-positive individuals. Using data from a large international cohort of HIV-positive individuals, we described the incidence of NADC from 2004-2010, and described subsequent mortality and predictors of these.METHODS:Individuals were followed from 1st January 2004/enrolment in study, until the earliest of a new NADC, 1st February 2010, death or six months after the patient's last visit. Incidence rates were estimated for each year of follow-up, overall and stratified by gender, age and mode of HIV acquisition. Cumulative risk of mortality following NADC diagnosis was summarised using Kaplan-Meier methods, with follow-up for these analyses from the date of NADC diagnosis until the patient's death, 1st February 2010 or 6 months after the patient's last visit. Factors associated with mortality following NADC diagnosis were identified using multivariable Cox proportional hazards regression.RESULTS:Over 176,775 person-years (PY), 880 (2.1%) patients developed a new NADC (incidence: 4.98/1000PY [95% confidence interval 4.65, 5.31]). Over a third of these patients (327, 37.2%) had died by 1st February 2010. Time trends for lung cancer, anal cancer and Hodgkin's lymphoma were broadly consistent. Kaplan-Meier cumulative mortality estimates at 1, 3 and 5 years after NADC diagnosis were 28.2% [95% CI 25.1-31.2], 42.0% [38.2-45.8] and 47.3% [42.4-52.2], respectively. Significant predictors of poorer survival after diagnosis of NADC were lung cancer (compared to other cancer types), male gender, non-white ethnicity, and smoking status. Later year of diagnosis and higher CD4 count at NADC diagnosis were associated with improved survival. The incidence of NADC remained stable over the period 2004-2010 in this large observational cohort.CONCLUSIONS:The prognosis after diagnosis of NADC, in particular lung cancer and disseminated cancer, is poor but has improved somewhat over time. Modifiable risk factors, such as smoking and low CD4 counts, were associated with mortality following a diagnosis of NADC
Development and Validation of a Risk Score for Chronic Kidney Disease in HIV Infection Using Prospective Cohort Data from the D:A:D Study
Ristola M. on työryhmien DAD Study Grp ; Royal Free Hosp Clin Cohort ; INSIGHT Study Grp ; SMART Study Grp ; ESPRIT Study Grp jäsen.Background Chronic kidney disease (CKD) is a major health issue for HIV-positive individuals, associated with increased morbidity and mortality. Development and implementation of a risk score model for CKD would allow comparison of the risks and benefits of adding potentially nephrotoxic antiretrovirals to a treatment regimen and would identify those at greatest risk of CKD. The aims of this study were to develop a simple, externally validated, and widely applicable long-term risk score model for CKD in HIV-positive individuals that can guide decision making in clinical practice. Methods and Findings A total of 17,954 HIV-positive individuals from the Data Collection on Adverse Events of Anti-HIV Drugs (D:A:D) study with >= 3 estimated glomerular filtration rate (eGFR) values after 1 January 2004 were included. Baseline was defined as the first eGFR > 60 ml/min/1.73 m2 after 1 January 2004; individuals with exposure to tenofovir, atazanavir, atazanavir/ritonavir, lopinavir/ritonavir, other boosted protease inhibitors before baseline were excluded. CKD was defined as confirmed (>3 mo apart) eGFR In the D:A:D study, 641 individuals developed CKD during 103,185 person-years of follow-up (PYFU; incidence 6.2/1,000 PYFU, 95% CI 5.7-6.7; median follow-up 6.1 y, range 0.3-9.1 y). Older age, intravenous drug use, hepatitis C coinfection, lower baseline eGFR, female gender, lower CD4 count nadir, hypertension, diabetes, and cardiovascular disease (CVD) predicted CKD. The adjusted incidence rate ratios of these nine categorical variables were scaled and summed to create the risk score. The median risk score at baseline was -2 (interquartile range -4 to 2). There was a 1: 393 chance of developing CKD in the next 5 y in the low risk group (risk score = 5, 505 events), respectively. Number needed to harm (NNTH) at 5 y when starting unboosted atazanavir or lopinavir/ritonavir among those with a low risk score was 1,702 (95% CI 1,166-3,367); NNTH was 202 (95% CI 159-278) and 21 (95% CI 19-23), respectively, for those with a medium and high risk score. NNTH was 739 (95% CI 506-1462), 88 (95% CI 69-121), and 9 (95% CI 8-10) for those with a low, medium, and high risk score, respectively, starting tenofovir, atazanavir/ritonavir, or another boosted protease inhibitor. The Royal Free Hospital Clinic Cohort included 2,548 individuals, of whom 94 individuals developed CKD (3.7%) during 18,376 PYFU (median follow-up 7.4 y, range 0.3-12.7 y). Of 2,013 individuals included from the SMART/ESPRIT control arms, 32 individuals developed CKD (1.6%) during 8,452 PYFU (median follow-up 4.1 y, range 0.6-8.1 y). External validation showed that the risk score predicted well in these cohorts. Limitations of this study included limited data on race and no information on proteinuria. Conclusions Both traditional and HIV-related risk factors were predictive of CKD. These factors were used to develop a risk score for CKD in HIV infection, externally validated, that has direct clinical relevance for patients and clinicians to weigh the benefits of certain antiretrovirals against the risk of CKD and to identify those at greatest risk of CKD.Peer reviewe
Mind Control: How Parasites Manipulate Cognitive Functions in Their Insect Hosts
Neuro-parasitology is an emerging branch of science that deals with parasites that can control the nervous system of the host. It offers the possibility of discovering how one species (the parasite) modifies a particular neural network, and thus particular behaviors, of another species (the host). Such parasite–host interactions, developed over millions of years of evolution, provide unique tools by which one can determine how neuromodulation up-or-down regulates specific behaviors. In some of the most fascinating manipulations, the parasite taps into the host brain neuronal circuities to manipulate hosts cognitive functions. To name just a few examples, some worms induce crickets and other terrestrial insects to commit suicide in water, enabling the exit of the parasite into an aquatic environment favorable to its reproduction. In another example of behavioral manipulation, ants that consumed the secretions of a caterpillar containing dopamine are less likely to move away from the caterpillar and more likely to be aggressive. This benefits the caterpillar for without its ant bodyguards, it is more likely to be predated upon or attacked by parasitic insects that would lay eggs inside its body. Another example is the parasitic wasp, which induces a guarding behavior in its ladybug host in collaboration with a viral mutualist. To exert long-term behavioral manipulation of the host, parasite must secrete compounds that act through secondary messengers and/or directly on genes often modifying gene expression to produce long-lasting effects
Sensory arsenal on the stinger of the parasitoid jewel wasp and its possible role in identifying cockroach brains.
The parasitoid jewel wasp uses cockroaches as live food supply for its developing larva. To this end, the adult wasp stings a cockroach and injects venom directly inside its brain, turning the prey into a submissive 'zombie'. Here, we characterize the sensory arsenal on the wasp's stinger that enables the wasp to identify the brain target inside the cockroach's head. An electron microscopy study of the stinger reveals (a) cuticular depressions innervated by a single mechanosensory neuron, which are presumably campaniform sensilla; and (b) dome-shaped structures innervated by a single mechanosensory neuron and 4-5 chemosensory neurons, which are presumably contact-chemoreceptive sensilla. Extracellular electrophysiological recordings from stinger afferents show increased firing rate in response to mechanical stimulation with agarose. This response is direction-selective and depends upon the concentration (density) of the agarose, such that the most robust response is evoked when the stinger is stimulated in the distal-to-proximal direction (concomitant with the penetration during the natural stinging behavior) and penetrating into relatively hard (0.75%-2.5%) agarose pellets. Accordingly, wasps demonstrate a normal stinging behavior when presented with cockroaches in which the brain was replaced with a hard (2.5%) agarose pellet. Conversely, wasps demonstrate a prolonged stinging behavior when the cockroach brain was either removed or replaced by a soft (0.5%) agarose pellet, or when stinger sensory organs were ablated prior to stinging. We conclude that the parasitoid jewel wasp uses at least mechanosensory inputs from its stinger to identify the brain within the head capsule of the cockroach prey
Correction: AMP-Activated Protein Kinase (AMPK) Mediates Nutrient Regulation of Thioredoxin-Interacting Protein (TXNIP) in Pancreatic Beta-Cells
The stinger possesses mechanosensory and dual mechano-chemosensory organs.
<p>(<b>A</b>) Frontal view of the tip of the stinger (Scanning Electron Micrograph; SEM). <i>DV</i>: dorsal valve, <i>VV1/2</i>: first/second ventral valve. Dome-shaped sensilla (<i>arrowheads</i>) can be seen at the apex of the DV (two opposing triplets) and between serrations of the two VVs. (<b>B</b>) Cross-section of the stinger (light micrograph) showing the DV and two VVs enclosing the egg canal (<i>EC</i>). The tongue-and-groove structure of the rachis (<i>Ra</i>) and aulax (<i>Au</i>) enables intricate movements of the valves relative to each other. (<b>C</b>) Dorsal view of the stinger (SEM). The VVs in this image are extended distally to reveal their serrations (<i>arrows</i>) and a part of the EC. (<b>D</b>) Outlines of the stinger (distal part enlarged on the right) showing the distribution of different sensilla along the DV. <i>Red arrows</i> indicate the position of campaniform sensilla; <i>black arrowheads</i> indicate the position of dome-shaped sensilla. (<b>E</b>) External morphology of one campaniform sensillum (SEM). (<b>F</b>) A mechanosensory dendrite innervating a campaniform sensillum (Transmission Electron Micrograph; TEM). <i>OvW</i>: ovipositor wall, <i>MT</i>: microtubules, <i>Sh</i>: dendritic sheath. (<b>G</b>) External morphology of one dome-shaped sensillum (SEM). (<b>H</b>) A bundle of 4 chemosensory dendrites (<i>CD</i>) and 1 mechanosensory dendrite (<i>MD</i>) innervating a dome-shaped sensillum (TEM). <i>OvW</i>: ovipositor wall; <i>Ap</i>: apodeme. <i>Sh</i>: sheath. (<b>I</b>) Longitudinal section (TEM) through one dome-shaped sensillum demonstrating the apical pore (<i>arrow</i>) and sensillar sinus (<i>SS</i>). (<b>J</b>) Silver nitrate staining (light micrograph) of the stinger showing penetration of the tracer (<i>black staining</i>) through the pores of dome-shaped sensilla.</p
Stinger afferents show spiking activity in response to mechanical stimulation.
<p>(<b>A</b>) Recording set-up (top view). The wasp’s stinger and terminal abdominal ganglion (TAG) are bathed in saline but with the distal half of the stinger protruding in an approximately 45<sup>0</sup> angle above the saline. The tip of the stinger is stimulated with either hard agarose or soft agarose in a glass capillary (grey rectangle) which can be moved in the distal-to-proximal (D-P) or in the proximal-to-distal (P-D) direction along the longitudinal axis of the stinger, by means of a peristaltic pump. <i>En passant</i> sensory responses are recorded from stinger afferents with a suction electrode placed on the nerves between the stinger and the TAG. A confocal micrograph (bottom) shows Neurobiotin backfills from the tip of the stinger, highlighting sensory afferents ascending from stinger sensilla to the TAG. Scale bar = 50 µm. (<b>B</b>) Representative neuronal responses for a stinger isolated from one wasp and stimulated sequentially with hard (2.5%, top) and then with soft (0.5%, bottom) agarose. Left and right shaded areas in each trace represent the duration in which the agarose was actively pushed against (D-P) or pulled away from (P-D) the stinger, respectively. (<b>C</b>) Peristimulus time histogram of neuronal activity evoked by hard (blue) or soft (red) agarose stimulation. Data points represent the mean (±SEM) number of sensory spikes within 200 ms time bins. Data is pooled from 5 different wasps, each stimulated at least 10 times in each condition. Left and right grey vertical bars indicate the 500 ms of the stimulus during which the agarose is actively pushed against (D-P) or pulled away from (P-D) the stinger, respectively. **p<0.01 for hard compared with soft agarose during the first 500 ms of the stimulation (t-test; n = 5 wasps).</p