<ol>
	<li>Fang, B., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Simultaneous+sEMG+recognition+of+gestures+and+force+levels+for+interaction+with+prosthetic+hand.">Simultaneous sEMG recognition of gestures and force levels for interaction with prosthetic hand.</a> IEEE Trans Neural Sys Rehabilitation Eng. 30, 2426-2436 (2022).</li><li>Yadav, D., Veer, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Recent+trends+and+challenges+of+surface+electromyography+in+prosthetic+applications.">Recent trends and challenges of surface electromyography in prosthetic applications.</a> Biomed Eng Lett. 13 (3), 353-373 (2023).</li><li>Sapsanis, C., Georgoulas, G., Tzes, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=EMG+based+classification+of+basic+hand+movements+based+on+time-frequency+features.">EMG based classification of basic hand movements based on time-frequency features.</a> , 716-722 (2013).</li><li>Qaisar, S. M., Lopez, A., Dallet, D., Ferrero, F. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=sEMG+signal+based+hand+gesture+recognition+by+using+selective+subbands+coefficients+and+machine+learning.">sEMG signal based hand gesture recognition by using selective subbands coefficients and machine learning.</a> , 1-6 (2022).</li><li>Zhang, X., Zhou, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=High-density+myoelectric+pattern+recognition+toward+improved+stroke+rehabilitation.">High-density myoelectric pattern recognition toward improved stroke rehabilitation.</a> IEEE Trans Biomed Eng. 59 (6), 1649-1657 (2012).</li><li>Guo, K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Empowering+hand+rehabilitation+with+AI-powered+gesture+recognition:+a+study+of+an+sEMG-based+system.">Empowering hand rehabilitation with AI-powered gesture recognition: a study of an sEMG-based system.</a> Bioengineering. 10 (5), 557 (2023).</li><li>Sun, T., Hu, Q., Libby, J., Atashzar, S. F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Deep+heterogeneous+dilation+of+LSTM+for+transient-phase+gesture+prediction+through+high-density+electromyography:+towards+application+in+neurorobotics.">Deep heterogeneous dilation of LSTM for transient-phase gesture prediction through high-density electromyography: towards application in neurorobotics.</a> IEEE Robot Autom Lett. 7 (2), 2851-2858 (2022).</li><li>Atzori, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Characterization+of+a+benchmark+database+for+myoelectric+movement+classification.">Characterization of a benchmark database for myoelectric movement classification.</a> IEEE Trans Neural Sys Rehabilitat Eng. 23 (1), 73-83 (2015).</li><li>Amma, C., Krings, T., Schultz, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Advancing+muscle-computer+interfaces+with+high-density+electromyography.">Advancing muscle-computer interfaces with high-density electromyography.</a> , 929-938 (2015).</li><li>Geng, W., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Gesture+recognition+by+instantaneous+surface+EMG+images.">Gesture recognition by instantaneous surface EMG images.</a> Sci Rep. 6 (1), 36571 (2016).</li><li>Wei, W., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+multi-stream+convolutional+neural+network+for+sEMG-based+gesture+recognition+in+muscle-computer+interface.">A multi-stream convolutional neural network for sEMG-based gesture recognition in muscle-computer interface.</a> Pattern Recognit Lett. 119, 131-138 (2019).</li><li>Padhy, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+tensor-based+approach+using+multilinear+SVD+for+hand+gesture+recognition+from+sEMG+signals.">A tensor-based approach using multilinear SVD for hand gesture recognition from sEMG signals.</a> IEEE Sens J. 21 (5), 6634-6642 (2021).</li><li>Moin, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+wearable+biosensing+system+with+in-sensor+adaptive+machine+learning+for+hand+gesture+recognition.">A wearable biosensing system with in-sensor adaptive machine learning for hand gesture recognition.</a> Nat Electron. 4 (1), 54-63 (2021).</li><li>C&#244;t&#233;-Allard, U., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Deep+learning+for+electromyographic+hand+gesture+signal+classification+using+transfer+learning.">Deep learning for electromyographic hand gesture signal classification using transfer learning.</a> IEEE Trans Neural Sys Rehabilita Eng. 27 (4), 760-771 (2019).</li><li>Liu, Y., Zhang, S., Gowda, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=NeuroPose:+3D+hand+pose+tracking+using+EMG+wearables.">NeuroPose: 3D hand pose tracking using EMG wearables.</a> , 1471-1482 (2021).</li><li>Dere, M. D., Lee, B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+novel+approach+to+surface+EMG-based+gesture+classification+using+a+vision+transformer+integrated+with+convolutive+blind+source+separation.">A novel approach to surface EMG-based gesture classification using a vision transformer integrated with convolutive blind source separation.</a> IEEE J Biomed Health Inform. 28 (1), 181-192 (2024).</li><li>Chen, X., Li, Y., Hu, R., Zhang, X., Chen, X. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Hand+gesture+recognition+based+on+surface+electromyography+using+convolutional+neural+network+with+transfer+learning+method.">Hand gesture recognition based on surface electromyography using convolutional neural network with transfer learning method.</a> IEEE J Biomed Health Inform. 25 (4), 1292-1304 (2021).</li><li>Lee, K. H., Min, J. Y., Byun, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Electromyogram-based+classification+of+hand+and+finger+gestures+using+artificial+neural+networks.">Electromyogram-based classification of hand and finger gestures using artificial neural networks.</a> Sensors. 22 (1), 225 (2022).</li><li>Zhou, X., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+novel+muscle-computer+interface+for+hand+gesture+recognition+using+depth+vision.">A novel muscle-computer interface for hand gesture recognition using depth vision.</a> J Ambient Intell Humaniz Comput. 11 (11), 5569-5580 (2020).</li><li>Zhang, Z., Yang, K., Qian, J., Zhang, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Real-time+surface+EMG+pattern+recognition+for+hand+gestures+based+on+an+artificial+neural+network.">Real-time surface EMG pattern recognition for hand gestures based on an artificial neural network.</a> Sensors. 19 (14), 3170 (2019).</li><li>Nieuwoudt, L., Fisher, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Investigation+of+real-time+control+of+finger+movements+utilizing+surface+EMG+signals.">Investigation of real-time control of finger movements utilizing surface EMG signals.</a> IEEE Sens J. 23 (18), 21989-21997 (2023).</li><li>Ben-Ari, L., Ben-Ari, A., Hermon, C., Hanein, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Finger+gesture+recognition+with+smart+skin+technology+and+deep+learning.">Finger gesture recognition with smart skin technology and deep learning.</a> Flexible Printed Electron. 8 (2), 25012 (2023).</li><li>Yang, C., Xie, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Gesture+recognition+method+based+on+computer+vision+and+surface+electromyography:+implementing+intention+recognition+of+the+healthy+side+in+the+hand+assessment+process.">Gesture recognition method based on computer vision and surface electromyography: implementing intention recognition of the healthy side in the hand assessment process.</a> , 663-668 (2024).</li><li>Lin, J., Wu, Y., Huang, T. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Modeling+the+constraints+of+human+hand+motion.">Modeling the constraints of human hand motion.</a> Proc Workshop Human Motion. , 121-126 (2000).</li><li>Arch&#233;-N&#250;&#241;ez, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Bio-potential+noise+of+dry+printed+electrodes:+physiology+versus+the+skin-electrode+impedance.">Bio-potential noise of dry printed electrodes: physiology versus the skin-electrode impedance.</a> Physiol Meas. 44 (9), 95006 (2023).</li><li>Gracia-Ib&#225;&#241;ez, V., Vergara, M., Sancho-Bru, J. L., Mora, M. 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<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Adjustable Selfie Stick</td>
			<td></td>
			<td></td>
			<td>Used to position and angle the hand-tracking camera in the desired orientation for optimal data capture during the experiment.</td>
		</tr>
		<tr>
			<td>Alcohol pad</td>
			<td></td>
			<td></td>
			<td>To clean the area for electrode placement.</td>
		</tr>
		<tr>
			<td>Data acquisition unit (DAU)</td>
			<td>X-trodes Ltd.</td>
			<td>&#160;XTR-BT V1.3</td>
			<td>Realtime compatible DAU 2.0.17 or 4.0.1</td>
		</tr>
		<tr>
			<td>Finger Gestures Recognition library</td>
			<td></td>
			<td></td>
			<td>https://github.com/NeuroEngLabTAU/Fingers_Gestures_Recognition.git</td>
		</tr>
		<tr>
			<td>Leap Motion Controller 2</td>
			<td>Ultraleap</td>
			<td>129-SP4-00005-03</td>
			<td>Hand-tracking camera</td>
		</tr>
		<tr>
			<td>Long Type-C to Type-C cable</td>
			<td></td>
			<td></td>
			<td>Connection of the hand-tracking camera to the PC.</td>
		</tr>
		<tr>
			<td>PC Monitors</td>
			<td></td>
			<td></td>
			<td>One for guidelines, one for viewing the hand-tracking camera data&#160;</td>
		</tr>
		<tr>
			<td>Personal Computer (PC)</td>
			<td>Windows</td>
			<td></td>
			<td>Windows 10+; Processors: Inteli7 processor. BT receiver.</td>
		</tr>
		<tr>
			<td>Python code</td>
			<td></td>
			<td></td>
			<td>A script enabling seamless data streaming and recording up to 500 S/s when DAU is connected to PC via Bluetooth</td>
		</tr>
		<tr>
			<td>Ultraleap Camera Python API</td>
			<td>Ultraleap</td>
			<td></td>
			<td>Python API and instructions from Ultraleap&#8217;s GitHub repository (https://github.com/ultraleap/leapc-python-bindings) used to collect data from the Ultraleap unit during the experiment</td>
		</tr>
		<tr>
			<td>Ultraleap Hyperion</td>
			<td>Ultraleap</td>
			<td></td>
			<td>Tracking software</td>
		</tr>
		<tr>
			<td>XTR EXG16</td>
			<td>X-trodes Ltd.</td>
			<td>XTELC0003405RM</td>
			<td>16-channel wearable dry electrode array patch for EMG, ECG monitoring</td>
		</tr>
		<tr>
			<td>X-trodes PC App</td>
			<td>X-trodes Ltd.</td>
			<td>1.1.35.0</td>
			<td>An application for connecting X-trodes DAU to PC via BT</td>
		</tr>
	</tbody>
</table>

capturing dynamic finger gesturing with high-resolution surface electromyography and computer vision

Acquisizione di gesti dinamici delle dita con l'elettromiografia di superficie ad alta risoluzione e la visione artificiale

Finger gestures are a critical element in human communication, and as such, finger gesture recognition is widely studied as a human-computer interface for ...

capturing-dynamic-finger-gesturing-with-high-resolution-surface

Nanyang Technological University

Research

JoVE Journal

Bioengineering

Capturing Dynamic Finger Gesturing with High-resolution Surface Electromyography and Computer Vision

246 Views.  Tel Aviv University. L'articolo presenta un protocollo completo per la registrazione simultanea dell'elettromiografia manuale (EMG) e del tracciamento visivo delle dita durante la gestualità naturale delle dita. I dati visivi sono progettati per fungere da base per lo sviluppo di modelli computazionali accurati basati su EMG per il riconoscimento dei gesti delle dita. 

Video: Acquisizione di gesti dinamici delle dita con l'elettromiografia di superficie ad alta risoluzione e la visione artificiale

High-resolution Fiber-optic Microendoscopy for in situ Cellular Imaging

Many biological and clinical studies require the longitudinal study and analysis of morphology and function with cellular level resolution. Traditionally, multiple experiments are run in parallel, with individual samples removed from the study at sequential time points for evaluation by light microscopy. Several intravital techniques have been developed, with confocal, multiphoton, and second harmonic microscopy all demonstrating their ability to be used for imaging in situ 1. With these systems, however, the required infrastructure is complex and expensive, involving scanning laser systems and complex light sources. Here we present a protocol for the design and assembly of a high-resolution microendoscope which can be built in a day using off-the-shelf components for under US$5,000. The platform offers flexibility in terms of image resolution, field-of-view, and operating wavelength, and we describe how these parameters can be easily modified to meet the specific needs of the end user.
We and others have explored the use of the high-resolution microendoscope (HRME) in in vitro cell culture 2-5, in excised 6 and living animal tissues 2,5, and in human tissues in vivo 2,7. Users have reported the use of several different fluorescent contrast agents, including proflavine 2-4, benzoporphyrin-derivative monoacid ring A (BPD-MA) 5, and fluoroscein 6,7, all of which have received full, or investigational approval from the FDA for use in human subjects. High-resolution microendoscopy, in the form described here, may appeal to a wide range of researchers working in the basic and clinical sciences. The technique offers an effective and economical approach which complements traditional benchtop microscopy, by enabling the user to perform high-resolution, longitudinal imaging in situ.

High-resolution Fiber-optic Microendoscopy for in situ Cellular Imaging

In many biological and clinical situations it is advantageous to study cellular processes as they evolve in their native microenvironment. Here we describe the assembly and use of a low-cost fiber-optic microscope which can provide real time imaging in cell culture, animal studies, and clinical patient studies.

Ad alta risoluzione in fibra ottica per Microendoscopy In situ Cellular Imaging

Many biological and clinical studies require the longitudinal study and analysis of morphology and function with cellular level resolution.  ...

Ricerca

Bioingegneria

High Resolution 3D Imaging of Ex-Vivo Biological Samples by Micro CT

Non-destructive volume visualization can be achieved only by tomographic techniques, of which the most efficient is the x-ray micro computerized tomography (&mu;CT).
High resolution &mu;CT is a very versatile yet accurate (1-2 microns of resolution) technique for 3D examination of ex-vivo biological samples1, 2. As opposed to electron tomography, the &mu;CT allows the examination of up to 4 cm thick samples. This technique requires only few hours of measurement as compared to weeks in histology. In addition, &mu;CT does not rely on 2D stereologic models, thus it may complement and in some cases can even replace histological methods3, 4, which are both time consuming and destructive. Sample conditioning and positioning in &mu;CT is straightforward and does not require high vacuum or low temperatures, which may adversely affect the structure. The sample is positioned and rotated 180&deg; or 360&deg;between a microfocused x-ray source and a detector, which includes a scintillator and an accurate CCD camera, For each angle a 2D image is taken, and then the entire volume is reconstructed using one of the different available algorithms5-7. The 3D resolution increases with the decrease of the rotation step. The present video protocol shows the main steps in preparation, immobilization and positioning of the sample followed by imaging at high resolution.

High Resolution 3D Imaging of Ex-Vivo Biological Samples by Micro CT

Non-destructive volume visualization can be achieved only by tomographic techniques, of which the most efficient is the x-ray micro computerized tomography ( CT).

Ad alta risoluzione di immagini 3D Ex-Vivo I campioni biologici da Micro CT

Non-destructive volume visualization can be achieved only by tomographic techniques, of which the most efficient is the x-ray micro computerized ...

Continuous High-resolution Microscopic Observation of Replicative Aging in Budding Yeast

We demonstrate the use of a simple microfluidic setup, in which single budding yeast cells can be tracked throughout their entire lifespan. The microfluidic chip exploits the size difference between mother and daughter cells using an array of micropads. Upon loading, cells are trapped underneath these micropads, because the distance between the micropad and cover glass is similar to the diameter of a yeast cell (3-4 &mu;m). After the loading procedure, culture medium is continuously flushed through the chip, which not only creates a constant and defined environment throughout the entire experiment, but also flushes out the emerging daughter cells, which are not retained underneath the pads due to their smaller size. The setup retains mother cells so efficiently that in a single experiment up to 50 individual cells can be monitored in a fully automated manner for 5 days or, if necessary, longer. In addition, the excellent optical properties of the chip allow high-resolution imaging of cells during the entire aging process.

We describe here the operation of a microfluidic device that allows continuous and high-resolution microscopic imaging of single budding yeast cells during their complete replicative and/or chronological lifespan.

Continuo ad alta risoluzione osservazione microscopica di replicativo invecchiamento nel lievito germogliante

We demonstrate the use of a simple microfluidic setup, in which single budding yeast cells can be tracked throughout their entire lifespan. The ...

High-resolution Spatiotemporal Analysis of Receptor Dynamics by Single-molecule Fluorescence Microscopy

Single-molecule microscopy is emerging as a powerful approach to analyze the behavior of signaling molecules, in particular concerning those aspect (e.g., kinetics, coexistence of different states and populations, transient interactions), which are typically hidden in ensemble measurements, such as those obtained with standard biochemical or microscopy methods. Thus, dynamic events, such as receptor-receptor interactions, can be followed in real time in a living cell with high spatiotemporal resolution. This protocol describes a method based on labeling with small and bright organic fluorophores and total internal reflection fluorescence (TIRF) microscopy to directly visualize single receptors on the surface of living cells. This approach allows one to precisely localize receptors, measure the size of receptor complexes, and capture dynamic events such as transient receptor-receptor interactions. The protocol provides a detailed description of how to perform a single-molecule experiment, including sample preparation, image acquisition and image analysis. As an example, the application of this method to analyze two G-protein-coupled receptors, i.e., &#946;2-adrenergic and &#947;-aminobutyric acid type B (GABAB) receptor, is reported. The protocol can be adapted to other membrane proteins and different cell models, transfection methods and labeling strategies.

This protocol describes how to use total internal reflection fluorescence microscopy to visualize and track single receptors on the surface of living cells and thereby analyze receptor lateral mobility, size of receptor complexes as well as to visualize transient receptor-receptor interactions. This protocol can be extended to other membrane proteins.

Ad alta risoluzione Spatiotemporal Analisi del recettore Dynamics per singola molecola di microscopia a fluorescenza

Single-molecule microscopy is emerging as a powerful approach to analyze the behavior of signaling molecules, in particular concerning those aspect (e.g., ...

Preparation of Mica Supported Lipid Bilayers for High Resolution Optical Microscopy Imaging

Supported lipid bilayers (SLBs) are widely used as a model for studying membrane properties (phase separation, clustering, dynamics) and its interaction with other compounds, such as drugs or peptides. However SLB characteristics differ depending on the support used. 
Commonly used techniques for SLB imaging and measurements are single molecule fluorescence microscopy, FCS and atomic force microscopy (AFM). Because most optical imaging studies are carried out on a glass support, while AFM requires an extremely flat surface (generally mica), results from these techniques cannot be compared directly, since the charge and smoothness properties of these materials strongly influence diffusion. Unfortunately, the high level of manual dexterity required for the cutting and gluing thin slices of mica to the glass slide presents a hurdle to routine use of mica for SLB preparation. Although this would be the method of choice, such prepared mica surfaces often end up being uneven (wavy) and difficult to image, especially with small working distance, high numerical aperture lenses. Here we present a simple and reproducible method for preparing thin, flat mica surfaces for lipid vesicle deposition and SLB preparation. Additionally, our custom made chamber requires only very small volumes of vesicles for SLB formation. The overall procedure results in the efficient, simple and inexpensive production of high quality lipid bilayer surfaces that are directly comparable to those used in AFM studies.

We present a method of preparing mica supported lipid bilayers for high resolution microscopy. Mica is transparent and flat on an atomic scale, but rarely used in imaging because of handling difficulties; our preparation results in even deposition of the mica sheet, and reduces the material used in bilayer preparation.

Preparazione di Mica supportati doppi strati lipidici per alta risoluzione microscopia ottica Imaging

Supported lipid bilayers (SLBs) are widely used as a model for studying membrane properties (phase separation, clustering, dynamics) and its interaction ...

Flying Insect Detection and Classification with Inexpensive Sensors

An inexpensive, noninvasive system that could accurately classify flying insects would have important implications for entomological research, and allow for the development of many useful applications in vector and pest control for both medical and agricultural entomology. Given this, the last sixty years have seen many research efforts devoted to this task. To date, however, none of this research has had a lasting impact. In this work, we show that pseudo-acoustic optical sensors can produce superior data; that additional features, both intrinsic and extrinsic to the insect&#8217;s flight behavior, can be exploited to improve insect classification; that a Bayesian classification approach allows to efficiently learn classification models that are very robust to over-fitting, and a general classification framework allows to easily incorporate arbitrary number of features. We demonstrate the findings with large-scale experiments that dwarf all previous works combined, as measured by the number of insects and the number of species considered.

We proposed a system that uses inexpensive, noninvasive pseudo-acoustic optical sensors to automatically and accurately detect, count, and classify flying insects based on their flying sound.

Volare Insetto rilevamento e classificazione con sensori Economico

An inexpensive, noninvasive system that could accurately classify flying insects would have important implications for entomological research, and allow ...

Microfluidic Platform with Multiplexed Electronic Detection for Spatial Tracking of Particles

Microfluidic processing of biological samples typically involves differential manipulations of suspended particles under various force fields in order to spatially fractionate the sample based on a biological property of interest. For the resultant spatial distribution to be used as the assay readout, microfluidic devices are often subjected to microscopic analysis requiring complex instrumentation with higher cost and reduced portability. To address this limitation, we have developed an integrated electronic sensing technology for multiplexed detection of particles at different locations on a microfluidic chip. Our technology, called Microfluidic CODES, combines Resistive Pulse Sensing with Code Division Multiple Access to compress 2D spatial information into a 1D electrical signal. In this paper, we present a practical demonstration of the Microfluidic CODES technology to detect and size cultured cancer cells distributed over multiple microfluidic channels. As validated by the high-speed microscopy, our technology can accurately analyze dense cell populations all electronically without the need for an external instrument. As such, the Microfluidic CODES can potentially enable low-cost integrated lab-on-a-chip devices that are well suited for the point-of-care testing of biological samples.

We demonstrate a microfluidic platform with an integrated surface electrode network that combines resistive pulse sensing (RPS) with code division multiple access (CDMA), to multiplex detection and sizing of particles in multiple microfluidic channels.

Piattaforma microfluidica con multiplex di rilevamento elettronico per spaziale monitoraggio di particelle

Microfluidic processing of biological samples typically involves differential manipulations of suspended particles under various force fields in order to ...

High Resolution 3D Imaging of the Human Pancreas Neuro-insular Network

Using traditional histological methods, researchers are hampered in their ability to image whole tissues or organs in large-scale 3D. Histological sections are generally limited to &#60;20 &#181;m as formalin fixed paraffin section on glass slides or &#60;500 &#181;m for free-floating fixed sections. Therefore, extensive efforts are required for serial sectioning and large-scale image reconstruction methods to recreate 3D for samples &#62;500 &#181;m using traditional methods. In addition, light scatters from macromolecules within tissues, particularly lipids, prevents imaging to a depth &#62;150 &#181;m with most confocal microscopes. To reduce light scatter and to allow for deep tissue imaging using simple confocal microscopy, various optical clearing methods have been developed that are relevant for rodent and human tissue samples fixed by immersion. Several methods are related and use protein crosslinking with acrylamide and tissue clearing with sodium dodecyl sulfate (SDS). Other optical clearing techniques used various solvents though each modification had various advantages and disadvantages. Here, an optimized passive optical clearing method is described for studies of the human pancreas innervation and specifically for interrogation of the innervation of human islets.

Here, we present a protocol to image human pancreas sections in three dimensions (3D) using optimized passive clearing methods. This manuscript demonstrates these procedures for passive optical clearing followed by multiple immunofluorescence staining to identify key elements of the autonomic and sensory neural networks innervating human islets.

Immagini 3D ad alta risoluzione della rete Neuro-insulari Pancreas umano

Using traditional histological methods, researchers are hampered in their ability to image whole tissues or organs in large-scale 3D. Histological ...

Surface Engineering of Pancreatic Islets with a Heparinized StarPEG Nanocoating

Cell surface engineering can protect implanted cells from host immune attack. It can also reshape cellular landscape to improve graft function and survival post-transplantation. This protocol aims to achieve surface engineering of pancreatic islets using an ultrathin heparin-incorporated starPEG (Hep-PEG) nanocoating. To generate the Hep-PEG nanocoating for pancreatic islet surface engineering, heparin succinimidyl succinate (Heparin-NHS) was first synthesized by modification of its carboxylate groups using N-(3-dimethylamino propyl)-N'-ethyl carbodiimide hydrochloride (EDC) and N-hydroxysuccinimide (NHS). The Hep-PEG mixture was then formed by crosslinking of the amino end-functionalized eight-armed starPEG (starPEG-(NH2)8) and Heparin-NHS. For islet surface coating, mouse islets were isolated via collagenase digestion and gradient purification using Histopaque. Isolated islets were then treated with ice cold Hep-PEG solution for 10 min to allow covalent binding between NHS and the amine groups of islet cell membrane. Nanocoating with the Hep-PEG incurs minimal alteration to islet size and volume and heparinization of the islets with Hep-PEG may also reduce instant blood-mediated inflammatory reaction during islet transplantation. This "easy-to-adopt" approach is mild enough for surface engineering of living cells without compromising cell viability. Considering that heparin has shown binding affinity to multiple cytokines, the Hep-PEG nanocoating also provides an open platform that enables incorporation of unlimited functional biological mediators and multi-layered surfaces for living cell surface bioengineering.

This protocol aims to achieve surface engineering of pancreatic islets using a heparin-incorporated starPEG nanocoating via pseudo-bioorthogonal chemistry between the N-hydroxysuccinimide groups of the nanocoating and the amine groups of islet cell membrane.

Ingegneria delle superfici degli isolotti pancreatici con un nanorivestimento StarPEG eparinizzata

Cell surface engineering can protect implanted cells from host immune attack. It can also reshape cellular landscape to improve graft function and ...

High-resolution Patterning Using Two Modes of Electrohydrodynamic Jet: Drop on Demand and Near-field Electrospinning

Electrohydrodynamic (EHD) jet printing has drawn attention in various fields because it can be used as a high-resolution and low-cost direct patterning tool. EHD printing uses a fluidic supplier to maintain the extruded meniscus by pushing the ink out of the nozzle tip. The electric field is then used to pull the meniscus down to the substrate to produce high-resolution patterns. Two modes of EHD printing have been used for fine patterning: continuous near-field electrospinning (NFES) and dot-based drop-on-demand (DOD) EHD printing. According to the printing modes, the requirements for the printing equipment and ink viscosity will differ. Even though two different modes can be implemented with a single EHD printer, the realization methods significantly differ in terms of ink, fluidic system, and driving voltage. Consequently, without a proper understanding of the jetting requirements and limitations, it is difficult to obtain the desired results. The purpose of this paper is to present a guideline so that inexperienced researchers can reduce the trial and error efforts to use the EHD jet for their specific research and development purposes. To demonstrate the fine-patterning implementation, we use Ag nanoparticle ink for the conductive patterning in the protocol. In addition, we also present the generalized printing guidelines that can be used for other types of ink for various fine-patterning applications.

Here, we present a protocol to produce high-resolution conductive patterns using electrohydrodynamic (EHD) jet printing. The protocol includes two modes of EHD jet printing: the continuous near-field electrospinning (NFES) and the dot-based drop-on-demand (DOD) EHD printing.

Alta risoluzione Patterning utilizzando due modalità di idrodinamiche Jet: Drop on Demand e Near-field elettrofilatura

Electrohydrodynamic (EHD) jet printing has drawn attention in various fields because it can be used as a high-resolution and low-cost direct patterning ...