Randomized phase III KEYNOTE-045 trial of pembrolizumab versus paclitaxel, docetaxel, or vinflunine in recurrent advanced urothelial cancer: results of >2 years of follow-up.

BackgroundNovel second-line treatments are needed for patients with advanced urothelial cancer (UC). Interim analysis of the phase III KEYNOTE-045 study showed a superior overall survival (OS) benefit of pembrolizumab, a programmed death 1 inhibitor, versus chemotherapy in patients with advanced UC that progressed on platinum-based chemotherapy. Here we report the long-term safety and efficacy outcomes of KEYNOTE-045.Patients and methodsAdult patients with histologically/cytologically confirmed UC whose disease progressed after first-line, platinum-containing chemotherapy were enrolled. Patients were randomly assigned 1 : 1 to receive pembrolizumab [200 mg every 3 weeks (Q3W)] or investigator's choice of paclitaxel (175 mg/m2 Q3W), docetaxel (75 mg/m2 Q3W), or vinflunine (320 mg/m2 Q3W). Primary end points were OS and progression-free survival (PFS) per Response Evaluation Criteria in Solid Tumors, version 1.1 (RECIST v1.1) by blinded independent central radiology review (BICR). A key secondary end point was objective response rate per RECIST v1.1 by BICR.ResultsA total of 542 patients were enrolled (pembrolizumab, n = 270; chemotherapy, n = 272). Median follow-up as of 26 October 2017 was 27.7 months. Median 1- and 2-year OS rates were higher with pembrolizumab (44.2% and 26.9%, respectively) than chemotherapy (29.8% and 14.3%, respectively). PFS rates did not differ between treatment arms; however, 1- and 2-year PFS rates were higher with pembrolizumab. The objective response rate was also higher with pembrolizumab (21.1% versus 11.0%). Median duration of response to pembrolizumab was not reached (range 1.6+ to 30.0+ months) versus chemotherapy (4.4 months; range 1.4+ to 29.9+ months). Pembrolizumab had lower rates of any grade (62.0% versus 90.6%) and grade ≥3 (16.5% versus 50.2%) treatment-related adverse events than chemotherapy.ConclusionsLong-term results (>2 years' follow-up) were consistent with those of previously reported analyses, demonstrating continued clinical benefit of pembrolizumab over chemotherapy for efficacy and safety for treatment of locally advanced/metastatic, platinum-refractory UC.Trial registrationClinicalTrials.gov: NCT02256436

Assessing cortical bone mechanical properties using collagen proton fraction from ultrashort echo time magnetization transfer (UTE-MT) MRI modeling.

Cortical bone shows as a signal void when using conventional clinical magnetic resonance imaging (MRI). Ultrashort echo time MRI (UTE-MRI) can acquire high signal from cortical bone, thus enabling quantitative assessments. Magnetization transfer (MT) imaging combined with UTE-MRI can indirectly assess protons in the organic matrix of bone. This study aimed to examine UTE-MT MRI techniques to estimate the mechanical properties of cortical bone. A total of 156 rectangular human cortical bone strips were harvested from the tibial and femoral midshafts of 43 donors (62 ± 22 years old, 62 specimens from females, 94 specimens from males). Bone specimens were scanned using UTE-MT sequences on a clinical 3 T MRI scanner and on a micro-computed tomography (μCT) scanner. A series of MT pulse saturation powers (400°, 600°, 800°) and frequency offsets (2, 5, 10, 20, 50 kHz) was used to measure the macromolecular fraction (MMF) utilizing a two-pool MT model. Failure mechanical properties of the bone specimens were measured using 4-point bending tests. MMF from MRI results showed significant strong correlations with cortical bone porosity (R = -0.72, P < 0.01) and bone mineral density (BMD) (R = +0.71, P < 0.01). MMF demonstrated significant moderate correlations with Young modulus, yield stress, and ultimate stress (R = 0.60-0.61, P < 0.01). These results suggest that the two-pool UTE-MT model focusing on the organic matrix of bone can potentially serve as a novel tool to detect the variations of bone mechanical properties and intracortical porosity

Network 'small-world-ness': a quantitative method for determining canonical network equivalence

Background: Many technological, biological, social, and information networks fall into the broad class of 'small-world' networks: they have tightly interconnected clusters of nodes, and a shortest mean path length that is similar to a matched random graph (same number of nodes and edges). This semi-quantitative definition leads to a categorical distinction ('small/not-small') rather than a quantitative, continuous grading of networks, and can lead to uncertainty about a network's small-world status. Moreover, systems described by small-world networks are often studied using an equivalent canonical network model-the Watts-Strogatz (WS) model. However, the process of establishing an equivalent WS model is imprecise and there is a pressing need to discover ways in which this equivalence may be quantified. Methodology/Principal Findings: We defined a precise measure of 'small-world-ness' S based on the trade off between high local clustering and short path length. A network is now deemed a 'small-world' if S. 1-an assertion which may be tested statistically. We then examined the behavior of S on a large data-set of real-world systems. We found that all these systems were linked by a linear relationship between their S values and the network size n. Moreover, we show a method for assigning a unique Watts-Strogatz (WS) model to any real-world network, and show analytically that the WS models associated with our sample of networks also show linearity between S and n. Linearity between S and n is not, however, inevitable, and neither is S maximal for an arbitrary network of given size. Linearity may, however, be explained by a common limiting growth process. Conclusions/Significance: We have shown how the notion of a small-world network may be quantified. Several key properties of the metric are described and the use of WS canonical models is placed on a more secure footing

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Daphnia revisited: Local stability and bifurcation theory for physiologically structured population models explained by way of an example

We consider the interaction between a general size-structured consumer population and an unstructured resource. We show that stability properties and bifurcation phenomena can be understood in terms of solutions of a system of two delay equations (a renewal equation for the consumer population birth rate coupled to a delay differetial equation for the resource concentration). As many results for such systems are available, we can draw rigorous conclusions concerning dynamical behaviour from an analysis of a characteristic equation. We derive the characteristic equation for a fairly general class of population models, including those based on the Kooijman-Metz Daphnia model and a model introduced by Gurney-Nisbet and Jones et al., and next obtain various ecological insights by analytical or numerical studies of special cases

Magnetic resonance microimaging of the spinal cord in the SOD1 mouse model of amyotrophic lateral sclerosis detects motor nerve root degeneration

Amyotrophic lateral sclerosis (ALS) is characterized by selective degeneration of motor neurons. Current imaging studies have concentrated on areas of the brain and spinal cord that contain mixed populations of sensory and motor neurons. In this study, ex vivo magnetic resonance microimaging (MRM) was used to separate motor and sensory components by visualizing individual dorsal and ventral roots in fixed spinal cords. MRM at 15 pm in plane resolution enabled the axons of pure populations of sensory and motor neurons to be measured in the lumbar region of the SOD1 mouse model of ALS. MRM signal intensity increased by 38.3% (p < 0.05) exclusively in the ventral motor nerve roots of the lumbar spinal cord of ALS-affected SOD1 mice compared to wildtype littermates. The hyperintensity was therefore limited to white matter tracts arising from the motor neurons, whereas sensory white matter fibers were unchanged. Significant decreases in ventral nerve root volume were also detected in the SOD1 mice, which correlated with the axonal degeneration observed by microscopy. These results demonstrate the usefulness of MRM in visualizing the ultrastructure of the mouse spinal cord. The detailed 3D anatomy allowed the processes of pure populations of sensory and motor neurons to be compared. (C) 2011 Elsevier Inc. All rights reserved

Reconstructing the three-dimensional GABAergic microcircuit of the striatum

A system's wiring constrains its dynamics, yet modelling of neural structures often overlooks the specific networks formed by their neurons. We developed an approach for constructing anatomically realistic networks and reconstructed the GABAergic microcircuit formed by the medium spiny neurons (MSNs) and fast-spiking interneurons (FSIs) of the adult rat striatum. We grew dendrite and axon models for these neurons and extracted probabilities for the presence of these neurites as a function of distance from the soma. From these, we found the probabilities of intersection between the neurites of two neurons given their inter-somatic distance, and used these to construct three-dimensional striatal networks. The MSN dendrite models predicted that half of all dendritic spines are within 100 mu m of the soma. The constructed networks predict distributions of gap junctions between FSI dendrites, synaptic contacts between MSNs, and synaptic inputs from FSIs to MSNs that are consistent with current estimates. The models predict that to achieve this, FSIs should be at most 1% of the striatal population. They also show that the striatum is sparsely connected: FSI-MSN and MSN-MSN contacts respectively form 7% and 1.7% of all possible connections. The models predict two striking network properties: the dominant GABAergic input to a MSN arises from neurons with somas at the edge of its dendritic field; and FSIs are interconnected on two different spatial scales: locally by gap junctions and distally by synapses. We show that both properties influence striatal dynamics: the most potent inhibition of a MSN arises from a region of striatum at the edge of its dendritic field; and the combination of local gap junction and distal synaptic networks between FSIs sets a robust input-output regime for the MSN population. Our models thus intimately link striatal micro-anatomy to its dynamics, providing a biologically grounded platform for further study