A Novel Implantable Glaucoma Valve Using Ferrofluid

Purpose To present a novel design of an implantable glaucoma valve based on ferrofluidic nanoparticles and to compare it with a well-established FDA approved valve. Setting: Massachusetts Eye & Ear Infirmary, Boston, USA. Methods: A glaucoma valve was designed using soft lithography techniques utilizing a water-immiscible magnetic fluid (ferrofluid) as a pressure-sensitive barrier to aqueous flow. Two rare earth micro magnets were used to calibrate the opening and closing pressure. In-vitro flow measurements were performed to characterize the valve and to compare it to Ahmed™ glaucoma valve. The reliability and predictability of the new valve was verified by pressure/flow measurements over a period of three months and X-ray diffraction (XRD) analysis over a period of eight weeks. In vivo assessment was performed in three rabbits. Results: In the in vitro experiments, the opening and closing pressures of the valve were 10 and 7 mmHg, respectively. The measured flow/pressure response was linearly proportional and reproducible over a period of three months (1.8 µl/min at 12 mmHg; 4.3 µl/min at 16 mmHg; 7.6 µl/min at 21 mmHg). X-ray diffraction analysis did not show oxidization of the ferrofluid when exposed to water or air. Preliminary in vivo results suggest that the valve is biocompatible and can control the intraocular pressure in rabbits. Conclusions: The proposed valve utilizes ferrofluid as passive, tunable constriction element to provide highly predictable opening and closing pressures while maintaining ocular tone. The ferrofluid maintained its magnetic properties in the aqueous environment and provided linear flow to pressure response. Our in-vitro tests showed reliable and reproducible results over a study period of three months. Preliminary in-vivo results were very promising and currently more thorough investigation of this device is underway

Microwave dielectric heating of non-aqueous droplets in a microfluidic device for nanoparticle synthesis

We describe a microfluidic device with an integrated microwave heater specifically designed to dielectrically heat non-aqueous droplets using time-varying electrical fields with the frequency range between 700 and 900 MHz. The precise control of frequency, power, temperature and duration of the applied field opens up new vistas for experiments not attainable by conventional microwave heating. We use a non-contact temperature measurement system based on fluorescence to directly determine the temperature inside a single droplet. The maximum temperature achieved of the droplets is 50 °C in 15 ms which represents an increase of about 25 °C above the base temperature of the continuous phase. In addition we use an infrared camera to monitor the thermal characteristics of the device allowing us to ensure that heating is exclusively due to the dielectric heating and not due to other effects like non-dielectric losses due to electrode or contact imperfection. This is crucial for illustrating the potential of dielectric heating of benzyl alcohol droplets for the synthesis of metal oxides. We demonstrate the utility of this technology for metal oxide nanoparticle synthesis, achieving crystallization of tungsten oxide nanoparticles and remarkable microstructure, with a reaction time of 64 ms, a substantial improvement over conventional heating methods.Engineering and Applied SciencesPhysic

Clinical and biomarker changes in dominantly inherited Alzheimer\u27s disease

BACKGROUND: The order and magnitude of pathologic processes in Alzheimer\u27s disease are not well understood, partly because the disease develops over many years. Autosomal dominant Alzheimer\u27s disease has a predictable age at onset and provides an opportunity to determine the sequence and magnitude of pathologic changes that culminate in symptomatic disease. METHODS: In this prospective, longitudinal study, we analyzed data from 128 participants who underwent baseline clinical and cognitive assessments, brain imaging, and cerebrospinal fluid (CSF) and blood tests. We used the participant\u27s age at baseline assessment and the parent\u27s age at the onset of symptoms of Alzheimer\u27s disease to calculate the estimated years from expected symptom onset (age of the participant minus parent\u27s age at symptom onset). We conducted cross-sectional analyses of baseline data in relation to estimated years from expected symptom onset in order to determine the relative order and magnitude of pathophysiological changes. RESULTS: Concentrations of amyloid-beta (Aβ) 42 in the CSF appeared to decline 25 years before expected symptom onset. Aβ deposition, as measured by positron-emission tomography with the use of Pittsburgh compound B, was detected 15 years before expected symptom onset. Increased concentrations of tau protein in the CSF and an increase in brain atrophy were detected 15 years before expected symptom onset. Cerebral hypometabolism and impaired episodic memory were observed 10 years before expected symptom onset. Global cognitive impairment, as measured by the Mini-Mental State Examination and the Clinical Dementia Rating scale, was detected 5 years before expected symptom onset, and patients met diagnostic criteria for dementia at an average of 3 years after expected symptom onset. CONCLUSIONS: We found that autosomal dominant Alzheimer\u27s disease was associated with a series of pathophysiological changes over decades in CSF biochemical markers of Alzheimer\u27s disease, brain amyloid deposition, and brain metabolism as well as progressive cognitive impairment. Our results require confirmation with the use of longitudinal data and may not apply to patients with sporadic Alzheimer\u27s disease. (Funded by the National Institute on Aging and others; DIAN ClinicalTrials.gov number, NCT00869817.

Decreased body mass index in the preclinical stage of autosomal dominant Alzheimer\u27s disease

The relationship between body-mass index (BMI) and Alzheimeŕs disease (AD) has been extensively investigated. However, BMI alterations in preclinical individuals with autosomal dominant AD (ADAD) have not yet been investigated. We analyzed cross-sectional data from 230 asymptomatic members of families with ADAD participating in the Dominantly Inherited Alzheimer Network (DIAN) study including 120 preclinical mutation carriers (MCs) and 110 asymptomatic non-carriers (NCs). Differences in BMI and their relation with cerebral amyloid load and episodic memory as a function of estimated years to symptom onset (EYO) were analyzed. Preclinical MCs showed significantly lower BMIs compared to NCs, starting 11.2 years before expected symptom onset. However, the BMI curves begun to diverge already at 17.8 years before expected symptom onset. Lower BMI in preclinical MCs was significantly associated with less years before estimated symptom onset, higher global Aβ brain burden, and with lower delayed total recall scores in the logical memory test. The study provides cross-sectional evidence that weight loss starts one to two decades before expected symptom onset of ADAD. Our findings point toward a link between the pathophysiology of ADAD and disturbance of weight control mechanisms. Longitudinal follow-up studies are warranted to investigate BMI changes over time

Clinical and Biomarker Changes in Dominantly Inherited Alzheimer's Disease

BACKGROUND: The order and magnitude of pathologic processes in Alzheimer's disease are not well understood, partly because the disease develops over many years. Autosomal dominant Alzheimer's disease has a predictable age at onset and provides an opportunity to determine the sequence and magnitude of pathologic changes that culminate in symptomatic disease. METHODS: In this prospective, longitudinal study, we analyzed data from 128 participants who underwent baseline clinical and cognitive assessments, brain imaging, and cerebrospinal fluid (CSF) and blood tests. We used the participant's age at baseline assessment and the parent's age at the onset of symptoms of Alzheimer's disease to calculate the estimated years from expected symptom onset (age of the participant minus parent's age at symptom onset). We conducted cross-sectional analyses of baseline data in relation to estimated years from expected symptom onset in order to determine the relative order and magnitude of pathophysiological changes. RESULTS: Concentrations of amyloid-beta (Aβ)(42) in the CSF appeared to decline 25 years before expected symptom onset. Aβ deposition, as measured by positron-emission tomography with the use of Pittsburgh compound B, was detected 15 years before expected symptom onset. Increased concentrations of tau protein in the CSF and an increase in brain atrophy were detected 15 years before expected symptom onset. Cerebral hypometabolism and impaired episodic memory were observed 10 years before expected symptom onset. Global cognitive impairment, as measured by the Mini-Mental State Examination and the Clinical Dementia Rating scale, was detected 5 years before expected symptom onset, and patients met diagnostic criteria for dementia at an average of 3 years after expected symptom onset. CONCLUSIONS: We found that autosomal dominant Alzheimer's disease was associated with a series of pathophysiological changes over decades in CSF biochemical markers of Alzheimer's disease, brain amyloid deposition, and brain metabolism as well as progressive cognitive impairment. Our results require confirmation with the use of longitudinal data and may not apply to patients with sporadic Alzheimer's disease. (Funded by the National Institute on Aging and others; DIAN ClinicalTrials.gov number, NCT00869817.)

Presymptomatic atrophy in autosomal dominant Alzheimer's disease: A serial magnetic resonance imaging study.

INTRODUCTION: Identifying at what point atrophy rates first change in Alzheimer's disease is important for informing design of presymptomatic trials. METHODS: Serial T1-weighted magnetic resonance imaging scans of 94 participants (28 noncarriers, 66 carriers) from the Dominantly Inherited Alzheimer Network were used to measure brain, ventricular, and hippocampal atrophy rates. For each structure, nonlinear mixed-effects models estimated the change-points when atrophy rates deviate from normal and the rates of change before and after this point. RESULTS: Atrophy increased after the change-point, which occurred 1-1.5 years (assuming a single step change in atrophy rate) or 3-8 years (assuming gradual acceleration of atrophy) before expected symptom onset. At expected symptom onset, estimated atrophy rates were at least 3.6 times than those before the change-point. DISCUSSION: Atrophy rates are pathologically increased up to seven years before "expected onset". During this period, atrophy rates may be useful for inclusion and tracking of disease progression

Automated Quantum Dots Purification via Solid Phase Extraction

The separation of colloidal nanocrystals from their original synthesis medium is an essential process step towards their application, however, the costs on a preparative scale are still a constraint. A new combination of approaches for the purification of hydrophobic Quantum Dots is presented, resulting in an efficient scalable process in regard to time and solvent consumption, using common laboratory equipment and low-cost materials. The procedure is based on a combination of solvent-induced adhesion and solid phase extraction. The platform allows the transition from manual handling towards automation, yielding an overall purification performance similar to one conventional batch precipitation/centrifugation step, which was investigated by thermogravimetry and gas chromatography. The distinct miscibility gaps between surfactants used as nanoparticle capping agents, original and extraction medium are clarified by their phase diagrams, which confirmed the outcome of the flow chemistry process. Furthermore, the solubility behavior of the Quantum Dots is put into context with the Hansen solubility parameters framework to reasonably decide upon appropriate solvent types

Single-cell ChIP-seq reveals cell subpopulations defined by chromatin state

Chromatin profiling provides a versatile means to investigate functional genomic elements and their regulation. However, current methods yield ensemble profiles that are insensitive to cell-to-cell variation. Here we combine microfluidics, DNA barcoding and sequencing to collect chromatin data at single-cell resolution. We demonstrate the utility of the technology by assaying thousands of individual cells, and using the data to deconvolute a mixture of ES cells, fibroblasts and hematopoietic progenitors into high-quality chromatin state maps for each cell type. The data from each single cell is sparse, comprising on the order of 1000 unique reads. However, by assaying thousands of ES cells, we identify a spectrum of sub-populations defined by differences in chromatin signatures of pluripotency and differentiation priming. We corroborate these findings by comparison to orthogonal single-cell gene expression data. Our method for single-cell analysis reveals aspects of epigenetic heterogeneity not captured by transcriptional analysis alone

DNA sequence analysis with droplet-based microfluidics

Droplet-based microfluidic techniques can form and process micrometer scale droplets at thousands per second. Each droplet can house an individual biochemical reaction, allowing millions of reactions to be performed in minutes with small amounts of total reagent. This versatile approach has been used for engineering enzymes, quantifying concentrations of DNA in solution, and screening protein crystallization conditions. Here, we use it to read the sequences of DNA molecules with a FRET-based assay. Using probes of different sequences, we interrogate a target DNA molecule for polymorphisms. With a larger probe set, additional polymorphisms can be interrogated as well as targets of arbitrary sequence