Liquid Metal-Based Multifunctional Micropipette for 4D Single Cell Manipulation.

A novel manufacturing approach to fabricate liquid metal-based, multifunctional microcapillary pipettes able to provide electrodes with high electrical conductivity for high-frequency electrical stimulation and measurement is proposed. 4D single cell manipulation is realized by applying multifrequency, multiamplitude, and multiphase electrical signals to the microelectrodes near the pipette tip to create 3D dielectrophoretic trap and 1D electrorotation, simultaneously. Functions such as single cell trapping, patterning, transfer, and rotation are accomplished. Cell viability and multiday proliferation characterization has confirmed the biocompatibility of this approach. This is a simple, low-cost, and fast fabrication process that requires no cleanroom and photolithography step to manufacture 3D microelectrodes and microchannels for easy access to a wide user base for broad applications

Hotspots of dendritic spine turnover facilitate clustered spine addition and learning and memory.

Modeling studies suggest that clustered structural plasticity of dendritic spines is an efficient mechanism of information storage in cortical circuits. However, why new clustered spines occur in specific locations and how their formation relates to learning and memory (L&M) remain unclear. Using in vivo two-photon microscopy, we track spine dynamics in retrosplenial cortex before, during, and after two forms of episodic-like learning and find that spine turnover before learning predicts future L&M performance, as well as the localization and rates of spine clustering. Consistent with the idea that these measures are causally related, a genetic manipulation that enhances spine turnover also enhances both L&M and spine clustering. Biophysically inspired modeling suggests turnover increases clustering, network sparsity, and memory capacity. These results support a hotspot model where spine turnover is the driver for localization of clustered spine formation, which serves to modulate network function, thus influencing storage capacity and L&M

The Genomes of Oryza sativa: A History of Duplications

We report improved whole-genome shotgun sequences for the genomes of indica and japonica rice, both with multimegabase contiguity, or almost 1,000-fold improvement over the drafts of 2002. Tested against a nonredundant collection of 19,079 full-length cDNAs, 97.7% of the genes are aligned, without fragmentation, to the mapped super-scaffolds of one or the other genome. We introduce a gene identification procedure for plants that does not rely on similarity to known genes to remove erroneous predictions resulting from transposable elements. Using the available EST data to adjust for residual errors in the predictions, the estimated gene count is at least 38,000–40,000. Only 2%–3% of the genes are unique to any one subspecies, comparable to the amount of sequence that might still be missing. Despite this lack of variation in gene content, there is enormous variation in the intergenic regions. At least a quarter of the two sequences could not be aligned, and where they could be aligned, single nucleotide polymorphism (SNP) rates varied from as little as 3.0 SNP/kb in the coding regions to 27.6 SNP/kb in the transposable elements. A more inclusive new approach for analyzing duplication history is introduced here. It reveals an ancient whole-genome duplication, a recent segmental duplication on Chromosomes 11 and 12, and massive ongoing individual gene duplications. We find 18 distinct pairs of duplicated segments that cover 65.7% of the genome; 17 of these pairs date back to a common time before the divergence of the grasses. More important, ongoing individual gene duplications provide a never-ending source of raw material for gene genesis and are major contributors to the differences between members of the grass family

Multifunctional Neural Probes for Electrochemical Sensing, Chemical Delivery and Optical Stimulation

Implantable neural probes are one of the most important technologies for neuroscientists to detect and stimulate neural activities inside the brain to advance the understanding of brain function and behavior, especially in the deep brain regions where other non-invasive approaches cannot reach. With the development of microelectromechanical systems (MEMS) in the past few decades, a great amount of efforts has been made to improve the neural probes to provide reliable and versatile tools to enable neuroscience studies that otherwise impossible to conduct. In this dissertation, I focused on three important objectives to improve the current neural probe platform: 1) to incorporate optical stimulation capability on top of the current silicon-based microelectrode arrays (MEAs) with electrochemical sensing function for optogenetics applications; 2) to integrate microfluidic channels with the current silicon platform for chemical deliveries; and 3) to develop a soft neural probe to reduce the brain damage and foreign body response. All the probes developed in this work are capable of deep brain implantation (>5 mm) and equipped with various electrochemical biosensors to study neural activities in deep brain regions. For the first objective, an ultra-thin silicon nitride waveguide was integrated on top of the silicon probe using grating couplers to couple light in and out of the waveguide. PECVD silicon nitride film was optimized to reduce the waveguide propagation loss to ~ 3dB/cm at 450 nm wavelength. The probe is capable of delivering ~40 μW light power to the probe tip with ~2 mW input light power from a 3 μm polarization maintaining optical fiber coupled with a pigtailed laser diode. The average light intensity is ~200 mW/mm2 which is sufficient for Channelrhodopsin-2 excitation. Using this probe, we have detected optically-evoked glutamate release in the rat nucleus accumbens several weeks after injection of channelrhodopsin-expressing AAV into the above region. For the second objective, PDMS microfluidic channels were transferred to the front and backside of the current Si probes using a novel PDMS thin-film transfer process. With this process, microfluidic channels can be easily bonded to Si probes as an add-on module to provide a simple solution to integrate chemical delivery functions into existing silicon-based probes, providing another level of control of the brain activities. Local injection of drug solution with nanoliter precision can be controlled by the pumping pressure and duration. The system was validated in vivo by local glucose injection through the fluidic channel and detection by biosensors in rat striatum. For the third objective, a multifunctional neural probe with Ultra-Large Tunable Stiffness (ULTS) was developed for chemical sensing, delivery and deep brain implantation, whose stiffness can be tuned by 5 orders of magnitude before and after brain implantation. ULTS probe is stiff enough to penetrate 2 cm deep into a gel with similar mechanical properties as the brain tissue and becomes soft and flexible within few minutes to minimize brain damage due to the brain movements in all directions. With appropriate coatings, the electrodes on ULTS were converted into different biosensors which exhibits similar sensing performance as previous Si probes. The integration of microfluidic channels permits delivery of chemicals in the local vicinity of the sensing sites. Acute stimulation and sensing experiments were conducted in rats, in which potassium induced glutamate release was recorded demonstrating the capability of in vivo application. The chronic immune response was compared between ULTS and silicon probes with similar geometry, which shows a reduced immune response indicated by the lower astrocytes density around ULTS

Flexible, multifunctional neural probe with liquid metal enabled, ultra-large tunable stiffness for deep-brain chemical sensing and agent delivery.

Flexible neural probes have been pursued previously to minimize the mechanical mismatch between soft neural tissues and implants and thereby improve long-term performance. However, difficulties with insertion of such probes deep into the brain severely restricts their utility. We describe a solution to this problem using gallium (Ga) in probe construction, taking advantage of the solid-to-liquid phase change of the metal at body temperature and probe shape deformation to provide temperature-dependent control of stiffness over 5 orders of magnitude. Probes in the stiff state were successfully inserted 2 cm-deep into agarose gel "brain phantoms" and into rat brains under cooled conditions where, upon Ga melting, they became ultra soft, flexible, and stretchable in all directions. The current 30 μm-thick probes incorporated multilayer, deformable microfluidic channels for chemical agent delivery, electrical interconnects through Ga wires, and high-performance electrochemical glutamate sensing. These PDMS-based microprobes of ultra-large tunable stiffness (ULTS) should serve as an attractive platform for multifunctional chronic neural implants

An implantable multifunctional neural microprobe for simultaneous multi-analyte sensing and chemical delivery

A multifunctional chemical neural probe fabrication process exploiting PDMS thin-film transfer to incorporate a microfluidic channel onto a silicon-based microelectrode array (MEA) platform, and enzyme microstamping to provide multi-analyte detection is described. The Si/PDMS hybrid chemtrode, modified with a nano-based on-probe IrOx reference electrode, was validated in brain phantoms and in rat brain

Hotspots of dendritic spine turnover facilitate clustered spine addition and learning and memory.

Modeling studies suggest that clustered structural plasticity of dendritic spines is an efficient mechanism of information storage in cortical circuits. However, why new clustered spines occur in specific locations and how their formation relates to learning and memory (L&M) remain unclear. Using in vivo two-photon microscopy, we track spine dynamics in retrosplenial cortex before, during, and after two forms of episodic-like learning and find that spine turnover before learning predicts future L&M performance, as well as the localization and rates of spine clustering. Consistent with the idea that these measures are causally related, a genetic manipulation that enhances spine turnover also enhances both L&M and spine clustering. Biophysically inspired modeling suggests turnover increases clustering, network sparsity, and memory capacity. These results support a hotspot model where spine turnover is the driver for localization of clustered spine formation, which serves to modulate network function, thus influencing storage capacity and L&M