Predicting clinical progression trajectories of early Alzheimer's disease patients

BACKGROUND

Models for forecasting individual clinical progression trajectories in early Alzheimer's disease (AD) are needed for optimizing clinical studies and patient monitoring.

METHODS

Prediction models were constructed using a clinical trial training cohort (TC; n = 934) via a gradient boosting algorithm and then evaluated in two validation cohorts (VC 1, n = 235; VC 2, n = 421). Model inputs included baseline clinical features (cognitive function assessments, APOE ε4 status, and demographics) and brain magnetic resonance imaging (MRI) measures.

RESULTS

The model using clinical features achieved R2 of 0.21 and 0.31 for predicting 2-year cognitive decline in VC 1 and VC 2, respectively. Adding MRI features improved the R2 to 0.29 in VC 1, which employed the same preprocessing pipeline as the TC. Utilizing these model-based predictions for clinical trial enrichment reduced the required sample size by 20% to 49%.

DISCUSSION

Our validated prediction models enable baseline prediction of clinical progression trajectories in early AD, benefiting clinical trial enrichment and various applications.

Development of a Prototype E-Textile Sock

The aim of this work is to design and develop a sensorized sock in Electronic Textile (ET), SWEET-Sock. The device has been realized by three textile sensor placed in a specific points of plantar arch and an accelerometer unit, both embedded and connected by conductive thread. The sensors allows the acquisition of plantar pressure and acceleration signals deriving from the motion of the lower limbs. The detected biosignals have been condictionated by a voltage divider and then were acquired through a LilyPad Arduino microcontroller and transmitted using the Simblee BLE technology to a custom made mobile app. Data were afterwards uploaded through a smartphone on a dropbox cloud where a custom made MATLAB GUI platform has been developed for further digital signal processing of main biomechanical parameters of clinical interest in postural and gait analysis.

Real-time algorithm for Poissonian noise reduction in low-dose fluoroscopy: performance evaluation

BACKGROUND

Quantum noise intrinsically limits the quality of fluoroscopic images. The lower is the X-ray dose the higher is the noise. Fluoroscopy video processing can enhance image quality and allows further patient's dose lowering. This study aims to assess the performances achieved by a Noise Variance Conditioned Average (NVCA) spatio-temporal filter for real-time denoising of fluoroscopic sequences. The filter is specifically designed for quantum noise suppression and edge preservation. It is an average filter that excludes neighborhood pixel values exceeding noise statistic limits, by means of a threshold which depends on the local noise standard deviation, to preserve the image spatial resolution. The performances were evaluated in terms of contrast-to-noise-ratio (CNR) increment, image blurring (full width of the half maximum of the line spread function) and computational time. The NVCA filter performances were compared to those achieved by simple moving average filters and the state-of-the-art video denoising block matching-4D (VBM4D) algorithm. The influence of the NVCA filter size and threshold on the final image quality was evaluated too.

RESULTS

For NVCA filter mask size of 5 × 5 × 5 pixels (the third dimension represents the temporal extent of the filter) and a threshold level equal to 2 times the local noise standard deviation, the NVCA filter achieved a 10% increase of the CNR with respect to the unfiltered sequence, while the VBM4D achieved a 14% increase. In the case of NVCA, the edge blurring did not depend on the speed of the moving objects; on the other hand, the spatial resolution worsened of about 2.2 times by doubling the objects speed with VBM4D. The NVCA mask size and the local noise-threshold level are critical for final image quality. The computational time of the NVCA filter was found to be just few percentages of that required for the VBM4D filter.

CONCLUSIONS

The NVCA filter obtained a better image quality compared to simple moving average filters, and a lower but comparable quality when compared with the VBM4D filter. The NVCA filter showed to preserve edge sharpness, in particular in the case of moving objects (performing even better than VBM4D). The simplicity of the NVCA filter and its low computational burden make this filter suitable for real-time video processing and its hardware implementation is ready to be included in future fluoroscopy devices, offering further lowering of patient's X-ray dose.

Correction: Visualising mouse neuroanatomy and function by metal distribution using laser ablation-inductively coupled plasma-mass spectrometry imaging

Correction for ‘Visualising mouse neuroanatomy and function by metal distribution using laser ablation-inductively coupled plasma-mass spectrometry imaging’ by Bence Paul et al., Chem. Sci., 2015, 6, 5383–5393.

Tolerance to silver of an Aspergillus fumigatus strain able to grow on cyanide containing wastes

We studied the strategy of an Aspergillus fumigatus strain able to grow on metal cyanide wastes to cope with silver. The tolerance test revealed that the Minimum Inhibitory Concentration of Ag(I) was 6mM. In 1mM AgNO3 aqueous solution the fungus was able to reduce and sequestrate silver into the cell in the form of nanoparticles as evidenced by the change in color of the biomass and Electron Microscopy observations. Extracellular silver nanoparticle production also occurred in the filtrate solution after previous incubation of the fungus in sterile, double-distilled water for 72h, therefore evidencing that culture conditions may influence nanoparticle formation. The nanoparticles were characterized by UV-vis spectrometry, X-ray diffraction and Energy Dispersion X-ray analysis. Atomic absorption spectrometry revealed that the optimum culture conditions for silver absorption were at pH 8.5.The research is part of a polyphasic study concerning the behavior of the fungal strain in presence of metal cyanides; the results provide better understanding for further research targeted at a rationale use of the microorganism in bioremediation plans, also in view of possible metal recovery. Studies will be performed to verify if the fungus maintains its ability to produce nanoparticles using KAg(CN)2.

Opportunities and challenges for metal chemistry in molecular imaging: from gamma camera imaging to PET and multimodality imaging

The development of medical imaging is a highly multidisciplinary endeavor requiring the close cooperation of clinicians, physicists, engineers, biologists and chemists to identify capabilities, conceive challenges and solutions and apply them in the clinic. The chemistry described in this article illustrates how synergistic advances in these areas drive the technology and its applications forward, with each discipline producing innovations that in turn drive innovations in the others. The main thread running through the article is the shift from single photon radionuclide imaging towards PET, and in turn the emerging shift from PET/CT towards PET/MRI and further, combination of these with optical imaging. Chemistry to support these transitions is exemplified by building on a summary of the status quo, and recent developments, in technetium-99m chemistry for SPECT imaging, followed by a report of recent developments to support clinical application of short lived (Ga-68) and long-lived (Zr-89) positron emitting isotopes, copper isotopes for PET imaging, and combined modality imaging agents based on radiolabelled iron oxide based nanoparticles.

Correction: Visualising mouse neuroanatomy and function by metal distribution using laser ablation-inductively coupled plasma-mass spectrometry imaging

Correction for 'Visualising mouse neuroanatomy and function by metal distribution using laser ablation-inductively coupled plasma-mass spectrometry imaging' by Bence Paul et al., Chem. Sci., 2015, DOI: 10.1039/c5sc02231b.

Visualising mouse neuroanatomy and function by metal distribution using laser ablation-inductively coupled plasma-mass spectrometry imaging

Studying the neuroanatomy of the mouse brain using imaging mass spectrometry and chemometric analysis.

Metals have a number of important roles within the brain. We used laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) to map the three-dimensional concentrations and distributions of transition metals, in particular iron (Fe), copper (Cu) and zinc (Zn) within the murine brain. LA-ICP-MS is one of the leading analytical tools for measuring metals in tissue samples. Here, we present a complete data reduction protocol for measuring metals in biological samples, including the application of a pyramidal voxel registration technique to reproducibly align tissue sections. We used gold (Au) nanoparticle and ytterbium (Yb)-tagged tyrosine hydroxylase antibodies to assess the co-localisation of Fe and dopamine throughout the entire mouse brain. We also examined the natural clustering of metal concentrations within the murine brain to elucidate areas of similar composition. This clustering technique uses a mathematical approach to identify multiple ‘elemental clusters’, avoiding user bias and showing that metal composition follows a hierarchical organisation of neuroanatomical structures. This work provides new insight into the distinct compartmentalisation of metals in the brain, and presents new avenues of exploration with regard to region-specific, metal-associated neurodegeneration observed in several chronic neurodegenerative diseases.

Novel method to label solid lipid nanoparticles with 64cu for positron emission tomography imaging

Solid lipid nanoparticles (SLNs) are submicrometer (1-1000 nm) colloidal carriers developed in the past decade as an alternative system to traditional carriers (emulsions, liposomes, and polymeric nanoparticles) for intravenous applications. Because of their potential as drug carriers, there is much interest in understanding the in vivo biodistribution of SLNs following intravenous (i.v.) injection. Positron emission tomography (PET) is an attractive method for investigating biodistribution but requires a radiolabeled compound. In this work, we describe a method to radiolabel SLN for in vivo PET studies. A copper specific chelator, 6-[p-(bromoacetamido)benzyl]-1,4,8,11-tetraazacyclotetradecane-N,N',N'',N'''-tetraacetic acid (BAT), conjugated with a synthetic lipid, was incorporated into the SLN. Following incubation with (64)CuCl(2) for 1 h at 25 °C in 0.1 M NH(4)OAc buffer (pH 5.5), the SLNs (∼150 nm) were successfully radiolabeled with (64)Cu (66.5% radiolabeling yield), exhibiting >95% radiolabeled particles following purification. The (64)Cu-SLNs were delivered intravenously to mice and imaged with PET at 0.5, 3, 20, and 48 h post injection. Gamma counting was utilized post imaging to confirm organ distributions. Tissue radioactivity (% injected dose/gram, %ID/g), obtained by quantitative analysis of the images, suggests that the (64)Cu-SLNs are circulating in the bloodstream after 3 h (blood half-life ∼1.4 h), but are almost entirely cleared by 48 h. PET and gamma counting demonstrate that approximately 5-7%ID/g (64)Cu-SLNs remain in the liver at 48 h post injection. Stability assays confirm that copper remains associated with the SLN over the 48 h time period and that the biodistribution patterns observed are not from free, dissociated copper. Our results indicate that SLNs can be radiolabeled with (64)Cu, and their biodistribution can be quantitatively evaluated by in vivo PET imaging and ex vivo gamma counting.