Optimal control based seizure abatement using patient derived connectivity

Epilepsy is a neurological disorder in which patients have recurrent seizures. Seizures occur in conjunction with abnormal electrical brain activity which can be recorded by the electroencephalogram (EEG). Often, this abnormal brain activity consists of high amplitude regular spike-wave oscillations as opposed to low amplitude irregular oscillations in the non-seizure state. Active brain stimulation has been proposed as a method to terminate seizures prematurely, however, a general and widely-applicable approach to optimal stimulation protocols is still lacking. In this study we use a computational model of epileptic spike-wave dynamics to evaluate the effectiveness of a pseudospectral method to simulated seizure abatement. We incorporate brain connectivity derived from magnetic resonance imaging of a subject with idiopathic generalized epilepsy. We find that the pseudospectral method can successfully generate time-varying stimuli that abate simulated seizures, even when including heterogeneous patient specific brain connectivity. The strength of the stimulus required varies in different brain areas. Our results suggest that seizure abatement, modeled as an optimal control problem and solved with the pseudospectral method, offers an attractive approach to treatment for in vivo stimulation techniques. Further, if optimal brain stimulation protocols are to be experimentally successful, then the heterogeneity of cortical connectivity should be accounted for in the development of those protocols and thus more spatially localized solutions may be preferable.

Divergent brain functional network alterations in dementia with Lewy bodies and Alzheimer's disease

The clinical phenotype of dementia with Lewy bodies (DLB) is different from Alzheimer's disease (AD), suggesting a divergence between these diseases in terms of brain network organization. To fully understand this, we studied functional networks from resting-state functional magnetic resonance imaging in cognitively matched DLB and AD patients. The DLB group demonstrated a generalized lower synchronization compared with the AD and healthy controls, and this was more severe for edges connecting distant brain regions. Global network measures were significantly different between DLB and AD. For instance, AD showed lower small-worldness than healthy controls, while DLB showed higher small-worldness (AD < controls < DLB), and this was also the case for global efficiency (DLB > controls > AD) and clustering coefficient (DLB < controls < AD). Differences were also found for nodal measures at brain regions associated with each disease. Finally, we found significant associations between network performance measures and global cognitive impairment and severity of cognitive fluctuations in DLB. These results show network divergences between DLB and AD which appear to reflect their neuropathological differences.

Near-field electromagnetic holography for high-resolution analysis of network interactions in neuronal tissue

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We developed a method to estimate electromagnetic field vectors from microelectrode array data.

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The vectors allow high-resolution holographic reconstruction of spatiotemporal activity.

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Separation of electromagnetic source density and dissipation informs on activity structure.

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Electromagnetic flow maps quantify dynamic causal interactions in brain tissue.

Background

Brain function is dependent upon the concerted, dynamical interactions between a great many neurons distributed over many cortical subregions. Current methods of quantifying such interactions are limited by consideration only of single direct or indirect measures of a subsample of all neuronal population activity.

New method

Here we present a new derivation of the electromagnetic analogy to near-field acoustic holography allowing high-resolution, vectored estimates of interactions between sources of electromagnetic activity that significantly improves this situation. In vitro voltage potential recordings were used to estimate pseudo-electromagnetic energy flow vector fields, current and energy source densities and energy dissipation in reconstruction planes at depth into the neural tissue parallel to the recording plane of the microelectrode array.

Results

The properties of the reconstructed near-field estimate allowed both the utilization of super-resolution techniques to increase the imaging resolution beyond that of the microelectrode array, and facilitated a novel approach to estimating causal relationships between activity in neocortical subregions.

Comparison with existing methods

The holographic nature of the reconstruction method allowed significantly better estimation of the fine spatiotemporal detail of neuronal population activity, compared with interpolation alone, beyond the spatial resolution of the electrode arrays used. Pseudo-energy flow vector mapping was possible with high temporal precision, allowing a near-realtime estimate of causal interaction dynamics.

Conclusions

Basic near-field electromagnetic holography provides a powerful means to increase spatial resolution from electrode array data with careful choice of spatial filters and distance to reconstruction plane. More detailed approaches may provide the ability to volumetrically reconstruct activity patterns on neuronal tissue, but the ability to extract vectored data with the method presented already permits the study of dynamic causal interactions without bias from any prior assumptions on anatomical connectivity.

From Caenorhabditis elegans to the human connectome: a specific modular organization increases metabolic, functional and developmental efficiency

The connectome, or the entire connectivity of a neural system represented by a network, ranges across various scales from synaptic connections between individual neurons to fibre tract connections between brain regions. Although the modularity they commonly show has been extensively studied, it is unclear whether the connection specificity of such networks can already be fully explained by the modularity alone. To answer this question, we study two networks, the neuronal network of Caenorhabditis elegans and the fibre tract network of human brains obtained through diffusion spectrum imaging. We compare them to their respective benchmark networks with varying modularities, which are generated by link swapping to have desired modularity values. We find several network properties that are specific to the neural networks and cannot be fully explained by the modularity alone. First, the clustering coefficient and the characteristic path length of both C. elegans and human connectomes are higher than those of the benchmark networks with similar modularity. High clustering coefficient indicates efficient local information distribution, and high characteristic path length suggests reduced global integration. Second, the total wiring length is smaller than for the alternative configurations with similar modularity. This is due to lower dispersion of connections, which means each neuron in the C. elegans connectome or each region of interest in the human connectome reaches fewer ganglia or cortical areas, respectively. Third, both neural networks show lower algorithmic entropy compared with the alternative arrangements. This implies that fewer genes are needed to encode for the organization of neural systems. While the first two findings show that the neural topologies are efficient in information processing, this suggests that they are also efficient from a developmental point of view. Together, these results show that neural systems are organized in such a way as to yield efficient features beyond those given by their modularity alone.

Developmental time windows for axon growth influence neuronal network topology

Early brain connectivity development consists of multiple stages: birth of neurons, their migration and the subsequent growth of axons and dendrites. Each stage occurs within a certain period of time depending on types of neurons and cortical layers. Forming synapses between neurons either by growing axons starting at similar times for all neurons (much-overlapped time windows) or at different time points (less-overlapped) may affect the topological and spatial properties of neuronal networks. Here, we explore the extreme cases of axon formation during early development, either starting at the same time for all neurons (parallel, i.e., maximally overlapped time windows) or occurring for each neuron separately one neuron after another (serial, i.e., no overlaps in time windows). For both cases, the number of potential and established synapses remained comparable. Topological and spatial properties, however, differed: Neurons that started axon growth early on in serial growth achieved higher out-degrees, higher local efficiency and longer axon lengths while neurons demonstrated more homogeneous connectivity patterns for parallel growth. Second, connection probability decreased more rapidly with distance between neurons for parallel growth than for serial growth. Third, bidirectional connections were more numerous for parallel growth. Finally, we tested our predictions with C. elegans data. Together, this indicates that time windows for axon growth influence the topological and spatial properties of neuronal networks opening up the possibility to a posteriori estimate developmental mechanisms based on network properties of a developed network.

Structural connectivity changes in temporal lobe epilepsy: Spatial features contribute more than topological measures

Background

Previous studies reported reduced volumes of many brain regions for temporal lobe epilepsy (TLE). It has also been suggested that there may be widespread changes in network features of TLE patients. It is not fully understood, however, how these two observations are related.

Methods

Using magnetic resonance imaging data, we perform parcellation of the brains of 22 patients with left TLE and 39 non-epileptic controls. In each parcellated region of interest (ROI) we computed the surface area and, using diffusion tensor imaging and deterministic tractography, infer the number of streamlines and their average length between each pair of connected ROIs. For comparison to previous studies, we use a connectivity ‘weight’ and investigate how ROI surface area, number of streamlines & mean streamline length contribute to such weight.

Results

We find that although there are widespread significant changes in surface area and position of ROIs in patients compared to controls, the changes in connectivity are much more subtle. Significant changes in connectivity weight can be accounted for by decreased surface area and increased streamline count.

Conclusion

Changes in the surface area of ROIs can be a reliable biomarker for TLE with a large influence on connectivity. However, changes in structural connectivity via white matter streamlines are more subtle with a relatively lower influence on connection weights.

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Using MRI data, we analyse 22 patients with left TLE and 39 non-epileptic controls.

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With a connectomics approach we investigate how nodal properties such as surface area influence connectivity weight.

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We find significant atrophy (reduced node size) in many brain areas in patients with TLE.

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We show only subtle changes in connectivity.

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When both node size and node connectivity are combined we find significant changes in connection weight.

A computational model incorporating neural stem cell dynamics reproduces glioma incidence across the lifespan in the human population

Glioma is the most common form of primary brain tumor. Demographically, the risk of occurrence increases until old age. Here we present a novel computational model to reproduce the probability of glioma incidence across the lifespan. Previous mathematical models explaining glioma incidence are framed in a rather abstract way, and do not directly relate to empirical findings. To decrease this gap between theory and experimental observations, we incorporate recent data on cellular and molecular factors underlying gliomagenesis. Since evidence implicates the adult neural stem cell as the likely cell-of-origin of glioma, we have incorporated empirically-determined estimates of neural stem cell number, cell division rate, mutation rate and oncogenic potential into our model. We demonstrate that our model yields results which match actual demographic data in the human population. In particular, this model accounts for the observed peak incidence of glioma at approximately 80 years of age, without the need to assert differential susceptibility throughout the population. Overall, our model supports the hypothesis that glioma is caused by randomly-occurring oncogenic mutations within the neural stem cell population. Based on this model, we assess the influence of the (experimentally indicated) decrease in the number of neural stem cells and increase of cell division rate during aging. Our model provides multiple testable predictions, and suggests that different temporal sequences of oncogenic mutations can lead to tumorigenesis. Finally, we conclude that four or five oncogenic mutations are sufficient for the formation of glioma.

Optimization of in vitro inhibition of HT-29 colon cancer cell cultures by Solanum tuberosum L. extracts

Secondary metabolites in potato have been reported to possess bioactive properties, including growth inhibition of cancer cells. Because potatoes are widely consumed globally, potential health benefits may have broad application. Thus we investigated growth inhibition of HT-29 colon cancer cell cultures by extracts from 13 diverse genetic breeding clones. Extracts from three pigmented selections (CO97226-2R/R, CO97216-1P/P, CO04058-3RW/RW) inhibited growth of in vitro HT-29 cell cultures more effectively than other clones tested. While inhibition was highest from pigmented selections and pigmented tuber tissue sectors, not all pigmented breeding lines tested had appreciable inhibitory properties. Thus, inhibition was not uniquely linked to pigmentation. Immature tubers had the highest inhibitory properties, and in most cases mature tubers retained very low inhibition properties. Flowers and skins inhibited strongly at lower extract concentrations. An extract consisting of 7.2 mg mL⁻¹ cell culture medium was the lowest effective concentration. While raw tuber extracts inhibited most effectively, a few clones at higher concentrations retained inhibition after cooking. Heated whole tubers retained higher inhibition than heated aqueous extracts. While all aqueous extracts from the two tuber selections (CO97216-1P/P and CO97226-2R/R) inhibited HT-29 cell cultures, inhibition was significantly enhanced in purple pigmented tubers of CO97216-1P/P prepared cryogenically as liquid nitrogen powders compared to extracts from freeze dried samples. Upregulation of caspase-3 protease activity, indicative of apoptosis, was highest among the most inhibitory clone samples. The unique sectorial red pigment expressing selection (CO04058-3RW/RW) provided a model system that isolated expression in pigmented sectors, and thus eliminated developmental, environmental and genetic confounding.

Perspective: network-guided pattern formation of neural dynamics

The understanding of neural activity patterns is fundamentally linked to an understanding of how the brain's network architecture shapes dynamical processes. Established approaches rely mostly on deviations of a given network from certain classes of random graphs. Hypotheses about the supposed role of prominent topological features (for instance, the roles of modularity, network motifs or hierarchical network organization) are derived from these deviations. An alternative strategy could be to study deviations of network architectures from regular graphs (rings and lattices) and consider the implications of such deviations for self-organized dynamic patterns on the network. Following this strategy, we draw on the theory of spatio-temporal pattern formation and propose a novel perspective for analysing dynamics on networks, by evaluating how the self-organized dynamics are confined by network architecture to a small set of permissible collective states. In particular, we discuss the role of prominent topological features of brain connectivity, such as hubs, modules and hierarchy, in shaping activity patterns. We illustrate the notion of network-guided pattern formation with numerical simulations and outline how it can facilitate the understanding of neural dynamics.

Structural connectivity based whole brain modelling in epilepsy

Epilepsy is a neurological condition characterised by the recurrence of seizures. During seizures multiple brain areas can behave abnormally. Rather than considering each abnormal area in isolation, one can consider them as an interconnected functional 'network'. Recently, there has been a shift in emphasis to consider epilepsy as a disorder involving more widespread functional brain networks than perhaps was previously thought. The basis for these functional networks is proposed to be the static structural brain network established through the connectivity of the white matter. Additionally, it has also been argued that time varying aspects of epilepsy are of crucial importance and as such computational models of these dynamical properties have recently advanced. We describe how dynamic computer models can be combined with static human in vivo connectivity obtained through diffusion weighted magnetic resonance imaging. We predict that in future the use of these two methods in concert will lead to predictions for optimal surgery and brain stimulation sites for epilepsy and other neurological disorders.

Methylated Ammonium and Hydrazinium Salts of 5,5′-Azotetrazolate

Salts of the 5,5′-azotetrazolate dianion with methylated ammonium and hydrazinium cations were prepared. The compounds were characterized by elemental analysis, vibrational (IR, Raman) and multinuclear NMR spectroscopy (1H, 13C, 14N). The crystal structures of the di[ammonium], the bis[dimethylammonium] and the bis[trimethylhydrazinium] 5,5′-azo­ tetrazolate salts were determined. The thermal, shock and friction sensitivities of these com­ pounds were investigated and their explosion products were analysed.

New Hydrazinium Salts of 5,5'-Azotetrazolate

Salts of the 5,5′-azotetrazolate dianion with several different hydrazinium cations were pre­ pared. The compounds were characterized by elemental analysis, vibrational spectroscopy (IR, Raman) and multinuclear NMR spectroscopy (1H, 13C, 14 N). The crystal structures of the di-tert-butylhydrazinium, the ethylenedihydrazinium, the diguanidinium and the bis-triamino-guanidinium azotetrazolate were determined. The thermal, shock and friction sensitivities of all compounds were investigated and their explosion products were analysed. For the 5,5′-azotetr-azolate dianion the structure was calculated with density functional theory (B3-LYP). An NBO analysis was performed for the 5,5′-azotetrazolate dianion in order to understand the charge distribution of the dianion.

Virtual Electrode Recording Tool for EXtracellular potentials (VERTEX): comparing multi-electrode recordings from simulated and biological mammalian cortical tissue

Local field potentials (LFPs) sampled with extracellular electrodes are frequently used as a measure of population neuronal activity. However, relating such measurements to underlying neuronal behaviour and connectivity is non-trivial. To help study this link, we developed the Virtual Electrode Recording Tool for EXtracellular potentials (VERTEX). We first identified a reduced neuron model that retained the spatial and frequency filtering characteristics of extracellular potentials from neocortical neurons. We then developed VERTEX as an easy-to-use Matlab tool for simulating LFPs from large populations (>100,000 neurons). A VERTEX-based simulation successfully reproduced features of the LFPs from an in vitro multi-electrode array recording of macaque neocortical tissue. Our model, with virtual electrodes placed anywhere in 3D, allows direct comparisons with the in vitro recording setup. We envisage that VERTEX will stimulate experimentalists, clinicians, and computational neuroscientists to use models to understand the mechanisms underlying measured brain dynamics in health and disease.

Adolescent brain maturation and cortical folding: evidence for reductions in gyrification

Evidence from anatomical and functional imaging studies have highlighted major modifications of cortical circuits during adolescence. These include reductions of gray matter (GM), increases in the myelination of cortico-cortical connections and changes in the architecture of large-scale cortical networks. It is currently unclear, however, how the ongoing developmental processes impact upon the folding of the cerebral cortex and how changes in gyrification relate to maturation of GM/WM-volume, thickness and surface area. In the current study, we acquired high-resolution (3 Tesla) magnetic resonance imaging (MRI) data from 79 healthy subjects (34 males and 45 females) between the ages of 12 and 23 years and performed whole brain analysis of cortical folding patterns with the gyrification index (GI). In addition to GI-values, we obtained estimates of cortical thickness, surface area, GM and white matter (WM) volume which permitted correlations with changes in gyrification. Our data show pronounced and widespread reductions in GI-values during adolescence in several cortical regions which include precentral, temporal and frontal areas. Decreases in gyrification overlap only partially with changes in the thickness, volume and surface of GM and were characterized overall by a linear developmental trajectory. Our data suggest that the observed reductions in GI-values represent an additional, important modification of the cerebral cortex during late brain maturation which may be related to cognitive development.

Design and properties of a cryogenic dip-stick scanning tunneling microscope with capacitive coarse approach control

We present the design, setup, and operation of a new dip-stick scanning tunneling microscope. Its special design allows measurements in the temperature range from 4.7 K up to room temperature, where cryogenic vacuum conditions are maintained during the measurement. The system fits into every (4)He vessel with a bore of 50 mm, e.g., a transport dewar or a magnet bath cryostat. The microscope is equipped with a cleaving mechanism for cleaving single crystals in the whole temperature range and under cryogenic vacuum conditions. For the tip approach, a capacitive automated coarse approach is implemented. We present test measurements on the charge density wave system 2H-NbSe2 and the superconductor LiFeAs which demonstrate scanning tunneling microscopy and spectroscopy data acquisition with high stability, high spatial resolution at variable temperatures and in high magnetic fields.

Preferential detachment during human brain development: age- and sex-specific structural connectivity in diffusion tensor imaging (DTI) data

Human brain maturation is characterized by the prolonged development of structural and functional properties of large-scale networks that extends into adulthood. However, it is not clearly understood which features change and which remain stable over time. Here, we examined structural connectivity based on diffusion tensor imaging (DTI) in 121 participants between 4 and 40 years of age. DTI data were analyzed for small-world parameters, modularity, and the number of fiber tracts at the level of streamlines. First, our findings showed that the number of fiber tracts, small-world topology, and modular organization remained largely stable despite a substantial overall decrease in the number of streamlines with age. Second, this decrease mainly affected fiber tracts that had a large number of streamlines, were short, within modules and within hemispheres; such connections were affected significantly more often than would be expected given their number of occurrences in the network. Third, streamline loss occurred earlier in females than in males. In summary, our findings suggest that core properties of structural brain connectivity, such as the small-world and modular organization, remain stable during brain maturation by focusing streamline loss to specific types of fiber tracts.

The potential of the human connectome as a biomarker of brain disease

The human connectome at the level of fiber tracts between brain regions has been shown to differ in patients with brain disorders compared to healthy control groups. Nonetheless, there is a potentially large number of different network organizations for individual patients that could lead to cognitive deficits prohibiting correct diagnosis. Therefore changes that can distinguish groups might not be sufficient to diagnose the disease that an individual patient suffers from and to indicate the best treatment option for that patient. We describe the challenges introduced by the large variability of connectomes within healthy subjects and patients and outline three common strategies to use connectomes as biomarkers of brain diseases. Finally, we propose a fourth option in using models of simulated brain activity (the dynamic connectome) based on structural connectivity rather than the structure (connectome) itself as a biomarker of disease. Dynamic connectomes, in addition to currently used structural, functional, or effective connectivity, could be an important future biomarker for clinical applications.

Spreading dynamics on spatially constrained complex brain networks

The study of dynamical systems defined on complex networks provides a natural framework with which to investigate myriad features of neural dynamics and has been widely undertaken. Typically, however, networks employed in theoretical studies bear little relation to the spatial embedding or connectivity of the neural networks that they attempt to replicate. Here, we employ detailed neuroimaging data to define a network whose spatial embedding represents accurately the folded structure of the cortical surface of a rat brain and investigate the propagation of activity over this network under simple spreading and connectivity rules. By comparison with standard network models with the same coarse statistics, we show that the cortical geometry influences profoundly the speed of propagation of activation through the network. Our conclusions are of high relevance to the theoretical modelling of epileptic seizure events and indicate that such studies which omit physiological network structure risk simplifying the dynamics in a potentially significant way.

Toxicological, toxicokinetic and gastroprotective evaluation of the benzaldehyde semicarbazone

Benzaldehyde semicarbazone (BS) has presented positive results in several pharmacological models, including anticonvulsivant and anti-inflammatory models. The present study evaluated the preclinical toxicity (acute and subchronic), as well as the toxicokinetic and gastroprotective effects of BS against ethanol lesions. Oral doses of 300 and 2000mg/kg were used in the preclinical acute toxicity study; 100, 200, and 300mg/kg were used in both the subchronic toxicity evaluation and the gastric study; and 300mg/kg was used in the toxicokinetic study. No impact from the dose of 300mg/kg could be identified; while, one animal died at 2000mg/kg in the acute toxicity test. In the subchronic toxicity test, changes in the biochemical parameters of the liver, as well as in the histopatological evaluation, demonstrated that BS is a hepatotoxic drug. BS proved to be effective for moderate and severe gastric lesions. In the toxicokinetics study, BS presented a low concentration and rapid plasma disappearance. Several results also indicate that BS is likely to be mostly eliminated from the liver and may well undergo a first-pass effect after oral absorption. It was impossible to estimate the noobserved-adverse-effect-levels (NOAEL) and lowest-observed-adverse-effect-levels (LOAEL) due to the presence of hepatotoxicity in all tested doses.

Novel renal replacement strategies for the elimination of serum free light chains in patients with kappa light chain nephropathy

Multiple myeloma (MM) is a malignancy with excessive production of monoclonal proteins. At disease presentation 30% of MM patients have significant renal impairment which may progress to renal failure requiring dialysis. Besides chemotherapy extracorporeal elimination procedures such as plasma exchange have been applied as adjuvant strategies to eliminate free light chains from circulating blood, however the efficacy was poor with older techniques. We report about a highly efficient method to eliminate serum free light chain (sFLC) using a newly designed protein leaking membrane in patients suffering from sFLC induced acute renal failure. The protein leaking membrane (HCO 1100) is characterized by increased pore size facilitating elimination of middle molecules such as sFLC kappa (22.5 kD). The HCO 1100 membrane was applied in a hemodialysis and hemodiafiltration mode and compared to standard procedures (high flux hemodialysis, hemodiafiltration and plasma exchange). Hemodiafiltration with the protein leaking membrane HCO 1100 was superior to all other extracorporeal replacement strategies in eliminating sFLC-kappa from circulating blood. A median blood reduction rate of 40.8% (range 13.9% - 66.4%) was achieved during hemodiafiltration. The corresponding peak clearance rate was 25 ml/min. Importantly, the poorest elimination rate was achieved by plasma exchange followed by standard high flux hemodialysis. Extracorporeal elimination strategies with the protein leaking membrane HCO 1100 may be a promising adjuvant treatment strategy for patients with sFLC nephropathy requiring dialysis. Hemodiafiltration and to lesser extend also hemodialysis with the HCO 1100 hemofilter are able to eliminate substantial amounts of sFLC kappa in MM patients.

Insulin aspart has a shorter duration of action than human insulin over a wide dose-range

AIMS

Regular human insulin (RHI) at high doses shows prolongation of its duration of action potentially leading to late postprandial hypoglycaemia. This study compared late metabolic activity (4-12 and 6-12 h post-dosing) and duration of action (time to reach late half-maximal activity) over a range of doses between insulin aspart (IAsp) and RHI.

METHODS

Pharmacokinetic and pharmacodynamic properties of subcutaneous IAsp and RHI (6, 12 and 24 (I)U) were compared in 16 healthy subjects in this double-blind, randomized, six-way crossover glucose clamp study.

RESULTS

With increasing doses of both insulins, metabolic activity, insulin exposure, maximum metabolic effect and maximum serum insulin concentration increased linearly. Late metabolic activity was lower for IAsp than RHI at all doses, reaching statistical significance (p < 0.05) for 12 and 24 (I)U. Likewise, IAsp had a shorter duration of action at all doses (p < 0.01) and reached time to 80% of total metabolic activity earlier at doses of 12 and 24 (I)U (p < 0.05). IAsp, compared with RHI, showed a higher maximum metabolic effect at 12 and 24 (I)U (p < 0.0001) and a stronger early metabolic activity for all three doses (p < 0.05).

CONCLUSIONS

IAsp showed a shorter duration of action and, particularly with doses of 12 and 24 (I)U, less late metabolic activity than RHI. These properties might contribute to the lower incidence of hypoglycaemia observed with IAsp versus RHI in clinical trials as lower late metabolic activity should decrease the risk of late postprandial hypoglycaemia.

[Once daily insulin detemir in patients with type 2 diabetes: results of German centers in a 6-month international observational study (SOLVE)]

BACKGROUND

Hypoglycemic risk and improved glycemic control have to be weightened when a decision on intensification of treatment of type 2 diabetes mellitus with basal insulin is made. Findings from randomized studies are available in this respect, and should be complemented by data from routine treatment.

METHODS

The international, prospective, open-label, observational study SOLVE (Study of Once-Daily Levemir) investigated add-on treatment with basal insulin in type 2 diabetes mellitus using once daily insulin detemir in patients currently receiving oral antidiabetic drugs (OAD). Data were collected between initiation of insulin treatment and the final visit after approximately 24 weeks. The primary objective of the study was to evaluate the incidence of serious adverse drug reactions (SADR), including major hypoglycemic events.

RESULTS

In Germany, 2,090 patients were eligible for the full analysis set and 1,671 patients for the effectiveness analysis set. The mean age was 64.9 years, mean duration of diabetes 9.36 years, and mean duration of OAD treatment 7.29 years. Three patients (0.14%) experienced a SADR (1 fall resulting in death, 2 major hypoglycemic events). At the final visit, there was a significant reduction in major hypoglycemic events if compared with the period before starting insulin treatment (0.002 versus 0.120 events per patient year, p < 0.001), as were minor hypoglycemic events (0.880 versus 1.588 events per patient year, p = 0.006). The mean body weight and BMI decreased by -0.9 kg (p < 0.001) and-0.35 kg/m2 (p < 0.001) respectively and the mean HbA(1c) level improved from 8.45 +/- 1.19% to 7.30 +/- 0.92% (-1.15 +/- 1.08%; p < 0.001). The mean fasting plasma glucose level and plasma glucose variability were significantly reduced.

CONCLUSION

Baseline data of the study underline the need for earlier intensification of antidiabetic therapy in type 2 diabetes in Germany. Study results show that within the German diabetes care system, initiation of basal insulin therapy with insulin detemir is able to result in significant HbA(1c) improvements without increased risk of hypoglycemia and/or weight gain.

The safety and efficacy of adding once-daily insulin detemir to oral hypoglycaemic agents in patients with type 2 diabetes in a clinical practice setting in 10 countries

AIMS

Evaluate the safety and efficacy of once-daily insulin detemir initiated in routine clinical practice in patients with type 2 diabetes mellitus inadequately controlled with oral hypoglycaemic agents (OHAs).

METHODS

This large observational study was conducted in 10 countries. Adverse event data (including hypoglycaemia) and glycaemic control were recorded before and 24 weeks following insulin initiation while patients continued routine clinical management.

RESULTS

In this study, 17 374 patients (53% male) were included. Mean pre-insulin values (±s.d.) were: age 62 ± 12 years; body mass index (BMI) 29.3 ± 5.4 kg/m(2); diabetes duration 10 ± 7 years; haemoglobin A1c (HbA1c) 8.9 ± 1.6%. During the study, 27 patients experienced serious adverse drug reaction, severe hypoglycaemic events or both; and there were 31 episodes of severe hypoglycaemia in 21 patients. After 24 weeks, HbA1c was 7.5 ± 1.2% (change of -1.3%; p < 0.001) and mean weight change was -0.6 kg (confidence interval -0.7, -0.5 kg, p < 0.001). Daily insulin dose increased from 13 ± 6 U (0.16 ± 0.09 U/kg) to 22 ± 16 U (0.27 ± 0.17U/kg) by 24 weeks. Multivariate regression analysis identified several independent demographic and treatment predictors of end of study HbA1c.

CONCLUSIONS

Addition of once-daily insulin detemir to patients with type 2 diabetes mellitus on OHA therapy resulted in few adverse events, significant improvements in glycaemic control, small reductions in weight and low rates of hypoglycaemia. On the basis of this study, concerns about hypoglycaemia or weight gain should not preclude initiation of basal insulin analogues in patients with poor glycaemic control on OHAs.

Macrocyclic proteasome inhibitors

Proteasome inhibitors have proven to be effective anticancer agents. Despite the success of the first on the market proteasome inhibitor bortezomib in chemotherapy, alternative clinically useful proteasome inhibitors are still urgently needed as bortezomib therapy causes severe side effects and is limited by arising drug resistance. Experience from previous proteasome inhibitor studies has thereby demonstrated that the identification of proteasome inhibitor structures with suitable pharmacological properties is a key factor for a successful development of clinically useful proteasome inhibitors. Macrocycles often show distinct and in comparison to linear small molecules superior pharmacological properties. Consequently, macrocyclic proteasome inhibitors might represent promising small molecules for drug development. Here, we want to highlight the current state of the art of macrocyclic proteasome inhibitor research. To this end, we give an overview and critically discuss currently known classes of macrocyclic proteasome inhibitors.

Resting-state functional connectivity in late-life depression: higher global connectivity and more long distance connections

Functional magnetic resonance imaging recordings in the resting-state (RS) from the human brain are characterized by spontaneous low-frequency fluctuations in the blood oxygenation level dependent signal that reveal functional connectivity (FC) via their spatial synchronicity. This RS study applied network analysis to compare FC between late-life depression (LLD) patients and control subjects. Raw cross-correlation matrices (CM) for LLD were characterized by higher FC. We analyzed the small-world (SW) and modular organization of these networks consisting of 110 nodes each as well as the connectivity patterns of individual nodes of the basal ganglia. Topological network measures showed no significant differences between groups. The composition of top hubs was similar between LLD and control subjects, however in the LLD group posterior medial-parietal regions were more highly connected compared to controls. In LLD, a number of brain regions showed connections with more distant neighbors leading to an increase of the average Euclidean distance between connected regions compared to controls. In addition, right caudate nucleus connectivity was more diffuse in LLD. In summary, LLD was associated with overall increased FC strength and changes in the average distance between connected nodes, but did not lead to global changes in SW or modular organization.