Lentiviral vectors with amplified beta cell-specific gene expression.

An important goal of gene therapy is to be able to deliver genes, so that they express in a pattern that recapitulates the expression of an endogenous cellular gene. Although tissue-specific promoters confer selectivity, in a vector-based system, their activity may be too weak to mediate detectable levels in gene-expression studies. We have used a two-step transcriptional amplification system to amplify gene expression from lentiviral vectors using the human insulin promoter. In this system, the human insulin promoter drives expression of a potent synthetic transcription activator (the yeast GAL4 DNA-binding domain fused to the activation domain of the Herpes simplex virus-1 VP16 activator), which in turn activates a GAL4-responsive promoter, driving the enhanced green fluorescent protein reporter gene. Vectors carrying the human insulin promoter did not express in non-beta-cell lines, but expressed in murine insulinoma cell lines, indicating that the human insulin promoter was capable of conferring cell specificity of expression. The insulin-amplifiable vector was able to amplify gene expression five to nine times over a standard insulin-promoter vector. In primary human islets, gene expression from the insulin-promoted vectors was coincident with insulin staining. These vectors will be useful in gene-expression studies that require a detectable signal and tissue specificity

Optimal positive end-expiratory pressure in mechanically ventilated patients: a clinical study

The optimal level of positive end-expiratory pressure (PEEP) is still widely debated in treating acute respiratory distress syndrome (ARDS) patients. Current methods of selecting PEEP only provide a range of values and do not provide unique patient-specific solutions. Model-based methods offer a novel way of using non-invasive pressure-volume (PV) measurements to estimate patient recruitability. This paper examines the clinical viability of such models in pilot clinical trials to assist therapy, optimise patient-specific PEEP, assess the disease state and response over time

Respiratory system elastance monitoring during PEEP titration

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Glucometer accuracy and implications for clinical studies

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Spina bifida

Spina bifida is a birth defect in which the vertebral column is open, often with spinal cord involvement. The most clinically significant subtype is myelomeningocele (open spina bifida), which is a condition characterized by failure of the lumbosacral spinal neural tube to close during embryonic development. The exposed neural tissue degenerates in utero, resulting in neurological deficit that varies with the level of the lesion. Occurring in approximately 1 per 1,000 births worldwide, myelomeningocele is one of the most common congenital malformations, but its cause is largely unknown. The genetic component is estimated at 60-70%, but few causative genes have been identified to date, despite much information from mouse models. Non-genetic maternal risk factors include reduced folate intake, anticonvulsant therapy, diabetes mellitus and obesity. Primary prevention by periconceptional supplementation with folic acid has been demonstrated in clinical trials, leading to food fortification programmes in many countries. Prenatal diagnosis is achieved by ultrasonography, enabling women to seek termination of pregnancy. Individuals who survive to birth have their lesions closed surgically, with subsequent management of associated defects, including the Chiari II brain malformation, hydrocephalus, and urological and orthopaedic sequelae. Fetal surgical repair of myelomeningocele has been associated with improved early neurological outcome compared with postnatal operation. Myelomeningocele affects quality of life during childhood, adolescence and adulthood, posing a challenge for individuals, families and society as a whole. For an illustrated summary of this Primer, visit: http://go.nature.com/fK9XNa

Increased insulin resistance in intensive care: longitudinal retrospective analysis of glycaemic control patients in a New Zealand ICU

Background: Critical care populations experience demographic shifts in response to trends in population and healthcare, with increasing severity and/or complexity of illness a common observation worldwide. Inflammation in critical illness impacts glucose–insulin metabolism, and hyperglycaemia is associated with mortality and morbidity. This study examines longitudinal trends in insulin sensitivity across almost a decade of glycaemic control in a single unit. Methods: A clinically validated model of glucose–insulin dynamics is used to assess hour–hour insulin sensitivity over the first 72 h of insulin therapy. Insulin sensitivity and its hour–hour percent variability are examined over 8 calendar years alongside severity scores and diagnostics. Results: Insulin sensitivity was found to decrease by 50–55% from 2011 to 2015, and remain low from 2015 to 2018, with no concomitant trends in age, severity scores or risk of death, or diagnostic category. Insulin sensitivity variability was found to remain largely unchanged year to year and was clinically equivalent (95% confidence interval) at the median and interquartile range. Insulin resistance was associated with greater incidence of high insulin doses in the effect saturation range (6–8 U/h), with the 75th percentile of hourly insulin doses rising from 4–4.5 U/h in 2011–2014 to 6 U/h in 2015–2018. Conclusions: Increasing insulin resistance was observed alongside no change in insulin sensitivity variability, implying greater insulin needs but equivalent (variability) challenge to glycaemic control. Increasing insulin resistance may imply greater inflammation and severity of illness not captured by existing severity scores. Insulin resistance reduces glucose tolerance, and can cause greater incidence of insulin saturation and resultant hyperglycaemia. Overall, these results have significant clinical implications for glycaemic control and nutrition management

Expiratory model-based method to monitor ARDS disease state

INTRODUCTION: Model-based methods can be used to characterise patient-specific condition and response to mechanical ventilation (MV) during treatment for acute respiratory distress syndrome (ARDS). Conventional metrics of respiratory mechanics are based on inspiration only, neglecting data from the expiration cycle. However, it is hypothesised that expiratory data can be used to determine an alternative metric, offering another means to track patient condition and guide positive end expiratory pressure (PEEP) selection. METHODS: Three fully sedated, oleic acid induced ARDS piglets underwent three experimental phases. Phase 1 was a healthy state recruitment manoeuvre. Phase 2 was a progression from a healthy state to an oleic acid induced ARDS state. Phase 3 was an ARDS state recruitment manoeuvre. The expiratory time-constant model parameter was determined for every breathing cycle for each subject. Trends were compared to estimates of lung elastance determined by means of an end-inspiratory pause method and an integral-based method. All experimental procedures, protocols and the use of data in this study were reviewed and approved by the Ethics Committee of the University of Liege Medical Faculty. RESULTS: The overall median absolute percentage fitting error for the expiratory time-constant model across all three phases was less than 10 %; for each subject, indicating the capability of the model to capture the mechanics of breathing during expiration. Provided the respiratory resistance was constant, the model was able to adequately identify trends and fundamental changes in respiratory mechanics. CONCLUSION: Overall, this is a proof of concept study that shows the potential of continuous monitoring of respiratory mechanics in clinical practice. Respiratory system mechanics vary with disease state development and in response to MV settings. Therefore, titrating PEEP to minimal elastance theoretically results in optimal PEEP selection. Trends matched clinical expectation demonstrating robustness and potential for guiding MV therapy. However, further research is required to confirm the use of such real-time methods in actual ARDS patients, both sedated and spontaneously breathing.Peer reviewe

Oscillatory, Computational, and Behavioral Evidence for Impaired GABAergic Inhibition in Schizophrenia

The dysconnection hypothesis of schizophrenia (SZ) proposes that psychosis is best understood in terms of aberrant connectivity. Specifically, it suggests that dysconnectivity arises through aberrant synaptic modulation associated with deficits in GABAergic inhibition, excitation-inhibition balance and disturbances of high-frequency oscillations. Using a computational model combined with a graded-difficulty visual orientation discrimination paradigm, we demonstrate that, in SZ, perceptual performance is determined by the balance of excitation-inhibition in superficial cortical layers. Twenty-eight individuals with a DSM-IV diagnosis of SZ, and 30 age- and gender-matched healthy controls participated in a psychophysics orientation discrimination task, a visual grating magnetoencephalography (MEG) recording, and a magnetic resonance spectroscopy (MRS) scan for GABA. Using a neurophysiologically informed model, we quantified group differences in GABA, gamma measures, and the predictive validity of model parameters for orientation discrimination in the SZ group. MEG visual gamma frequency was reduced in SZ, with lower peak frequency associated with more severe negative symptoms. Orientation discrimination performance was impaired in SZ. Dynamic causal modeling of the MEG data showed that local synaptic connections were reduced in SZ and local inhibition correlated negatively with the severity of negative symptoms. The effective connectivity between inhibitory interneurons and superficial pyramidal cells predicted orientation discrimination performance within the SZ group; consistent with graded, behaviorally relevant, disease-related changes in local GABAergic connections. Occipital GABA levels were significantly reduced in SZ but did not predict behavioral performance or oscillatory measures. These findings endorse the importance, and behavioral relevance, of GABAergic synaptic disconnection in schizophrenia that underwrites excitation-inhibition balance