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Tumor-derived exosomes carrying unique surface proteins have shown great promise as novel biomarkers for liquid biopsies. However, point-of-care analysis for tumor-derived exosomes in the blood with low-cost and easy processing is still challenging. Herein, we develop an integrated approach, homogenous magneto-fluorescent exosome (hMFEX) nanosensor, for rapid and on-site tumor-derived exosomes analysis. Tumor-derived exosomes are captured immunomagnetically, which further initiates the aptamer-triggered assembly of DNA three-way junctions in homogenous solution containing aggregation-induced emission luminogens and graphene oxide, resulting in an amplified fluorescence signal. By integrating magnetic isolation and enhanced fluorescence measurement, the hMFEX nanosensor detects tumor-derived exosomes in the dynamic range spanning 5 orders of magnitude with high specificity, and the limit of detection is 6.56 × 104 particles/μL. Analyzing tumor-derived exosomes in limited volume plasma from breast cancer patients demonstrates the excellent clinical diagnostic efficacy of the hMFEX nanosensor. This study provides new insights into the point-of-care testing of tumor-derived exosomes for cancer diagnostics.

It is challenging to develop molecular fluorophores in the second near-infrared (NIR-II) window with long wavelength emission and high brightness, which can improve the performance of biological imaging. Herein, we report a molecular engineering approach to afford NIR-II fluorophores with these merits based on fused-ring acceptor (FRA) molecules. Dioctyl 3,4-propylenedioxy thiophene (PDOT-C8) is utilized as the bridging donor to replace 3-ethylhexyloxy thiophene (3-EHOT), leading to more than 20 times enhancement of brightness. The nanofluorophores (NFs) based on the optimized CPTIC-4F molecule exhibit an emission peak of 1,110 nm with a fluorescence quantum yield (QY) of 0.39% (QY of IR-26 is 0.050% in dichloroethane as reference) and peak absorption coefficient of 14.5 × 104 M−1cm−1 in aqueous solutions, which are significantly higher than those of 3-EHOT based COTIC-4F NFs. It is found that PDOT-C8 can weaken intermolecular aggregation, enhance protection of molecular backbone from water, and decrease backbone distortion, beneficial for the high brightness. Compared with indocyanine green with same injection dose, CPTIC-4F NFs show 10 times higher signal-to-background ratio for whole body vessels imaging at 1,300 nm long pass filters.

Developing molecular fluorophores with high brightness is of considerable importance to achieve superior biological imaging quality in the second near-infrared (NIR-II) window. It has been demonstr...

Depiction on an energetic chain in terms of assimilation, allocation and consumption as well as the linkage between energetic alteration and physiological process was performed in blue mussel Mytilus edulis coping with tetrabromodiphenyl ether (BDE-47) based on a 21-day bioassay to shed light on the possible mechanism from energetic perspective. The filtration was hindered along with BDE-47 concentration increment and the influence of digestion was suggested according to the combination of the digestive enzymatic activities’ alteration and digestive gland tissue impairment, both of which decided the energy availability reduction. Energy consumption indicated by the electron transport system activity was firstly inhibited while was greatly increased with BDE-47 increment, and the cellular energy allocation and adenylate pool were decreased simultaneously. An energetic chain was thus depicted: it tended to reduce energy absorption, elevate the energy consumption and decrease the energy metabolism with BDE-47 exposure, and M. edulis adopted the energetic strategy with variation regarding to the stressing level, suggesting as the preference switched from protein utilization to lipid utilization with the concentration increment. A consistence was observed in index of growth and survival with the change of energy allocation, inferring the energetic involvement in sustaining the viability of the mussel.

Exosomes shed by tumor cells have been recognized as promising biomarkers for cancer diagnostics due to their unique composition and functions. Quantification of low concentrations of specific exosomes present in very small volumes of clinical samples may be used for noninvasive cancer diagnosis and prognosis. We developed an immunosorbent assay for digital qualification of target exosomes using droplet microfluidics. The exosomes were immobilized on magnetic microbeads through sandwich ELISA complexes tagged with an enzymatic reporter that produces a fluorescent signal. The constructed beads were further isolated and encapsulated into a sufficient number of droplets to ensure only a single bead was encapsulated in a droplet. Our droplet-based single-exosome-counting enzyme-linked immunoassay (droplet digital ExoELISA) approach enables absolute counting of cancer-specific exosomes to achieve unprecedented accuracy. We were able to achieve a limit of detection (LOD) down to 10 enzyme-labeled exosome complexes per microliter (∼10

The enzymatic antioxidant system (EAS) protects aerobic cells from oxidative stress. However, it is brittle and susceptible of inactivation of reactive oxygen species (ROS) immoderate production. Here, we demonstrated that MoS2 nanosheets (few-layer MoS2), as a multifunctional nanozyme, possess intrinsic activity of mimicking enzymes of superoxide dismutases (SODs), catalases (CATs), and peroxidases (PODs) under physiological conditions (pH 7.4, 25 °C). Further, MoS2 nanosheets showed POD-like activity by transferring electrons instead of generating ROS. Similar to EAS, a defense termed nanozymatic antioxidant system (NAS) was developed by MoS2 nanosheets, for regulation of oxidative stress. Surprisingly, this NAS can effectively scavenge other free radicals including hydroxyl radicals (•OH), nitrogen-centered free radicals (•DPPH), and nitric oxide (•NO). To evaluate these unique properties of MoS2-based NAS in vivo, Escherichia coli (E. coli), Staphylococcus aureus (S. aureus), and A549 cell models were...

Touch sensing has been widely implemented as a main methodology to bridge human and machine interactions. The traditional touch sensing range is 2-D and therefore limits the user experience. To overcome these limitations, we propose a novel 3-D contactless touch sensing called Airtouch system, which improves user experience by remotely detecting single/multi-finger position. A single layer touch panel with triangle-shaped electrodes is proposed to achieve multitouch detection capability as well as manufacturing cost reduction. Moreover, an oscillator-based-capacitive touch sensing circuit is implemented as the sensing hardware with the bootstrapping technique to eliminate the interchannel coupling effects. To further improve the system accuracy, a grouping algorithm is proposed to group the useful channels’ data and filter out hardware noise impact. Finally, improved algorithms are proposed to eliminate the fringing capacitance effect and achieve accurate finger position estimation. EM simulation proved that the proposed algorithm reduced the maximum systematic error by 11 dB in the horizontal position detection. The proposed system consumes 2.3 mW and is fully compatible with existing mobile device environments. A prototype is built to demonstrate that the system can successfully detect finger movement in a vertical direction up to 6 cm and achieve a horizontal resolution up to 0.6 cm at 1 cm finger-height. As a new interface for human and machine interactions, this system offers great potential in finger movement detection and gesture recognition for small-sized electronics and advanced human interactive games for mobile device.

Convolutional neural network (CNN) offers significant accuracy in image detection. To implement image detection using CNN in the Internet of Things (IoT) devices, a streaming hardware accelerator is proposed. The proposed accelerator optimizes the energy efficiency by avoiding unnecessary data movement. With unique filter decomposition technique, the accelerator can support arbitrary convolution window size. In addition, max-pooling function can be computed in parallel with convolution by using separate pooling unit, thus achieving throughput improvement. A prototype accelerator was implemented in TSMC 65-nm technology with a core size of 5 mm2. The accelerator can support major CNNs and achieve 152GOPS peak throughput and 434GOPS/W energy efficiency at 350 mW, making it a promising hardware accelerator for intelligent IoT devices.

A cognitive tri-band transmitter (TX) with a forwarded clock using multiband signaling and high-order digital signal modulations is presented for serial link applications. The TX features learning an arbitrary channel response by sending a sweep of continuous wave, detecting power level at the receiver side, and then adapting modulation scheme, data bandwidth, and carrier frequencies accordingly based on detected channel information. The supported modulation scheme ranges from nonreturn to zero/Quadrature phase shift keying (QPSK) to Pulse-amplitude modulation (PAM) 16/256-Quadrature amplitude modulation(QAM). The proposed highly reconfigurable TX is capable of dealing with low-cost serial channels, such as low-cost connectors, cables, or multidrop buses with deep and narrow notches in the frequency domain (e.g., a 40-dB loss at notches). The adaptive multiband scheme mitigates equalization requirements and enhances the energy efficiency by avoiding frequency notches and utilizing the maximum available signal-to-noise ratio and channel bandwidth. The implemented TX prototype consumes a 14.7-mW power and occupies 0.016 mm2 in a 28-nm CMOS. It achieves a maximum data rate of 16 Gb/s with forwarded clock through one differential pair and the most energy efficient figure of merit of 20.4 $\mu \text{W}$ /Gb/s/dB, which is calculated based on power consumption of transmitting per gigabits per second data and simultaneously overcoming per decibel worst case channel loss within the Nyquist frequency.

This brief discusses an oscillator-based capacitive 3-D touch-sensing circuit for mobile devices. The proposed 3-D touch sensor uses correlated double sampling to achieve a high sensing resolution in the Z-direction and employs bootstrapping circuitry to reduce the mobile screen's interchannel-coupling effects. Additionally, to reduce chip area and assembly, the sensing oscillator is implemented with inverter-based active resonators instead of using either on- or off-chip inductors. The prototyped 3-D touch sensor is fabricated using 65-nm CMOS process technology and consumes an area of 2 mm2, with a 2.3-mW power consumption from a 1-V power supply. Measured together with a 3.4′′ HTC standard mobile screen, the sensor achieves an 11-cm Z-direction sensing range with a 1-cm resolution, demonstrating the potential implementation of 3-D finger position sensing in a mobile device.

In this manuscript, indigo and isoindigo-based π-conjugated molecules with thermal removable tert-butoxycarbonyl (t-Boc) side groups were designed and synthesized. It was noted that the t-Boc side groups can be eliminated in nearly quantitative yields after thermal treatment at 200 °C for 15 min, as confirmed by thermogravimetric analysis and Fourier transform infrared spectroscopy. From the thermal treated solution of isoindigo-based molecule DTIIC8C12 in the co-solvent of 1,2-dichlorobenzene/pyridine with volume ratio of 10/90, one-dimensional nanowires can be formed due to the hydrogen bonding assisted self-assembly. The afforded nanowires exhibited a moderate hole mobility of 1.3 × 10−3 cm2 V−1 s−1, as estimated from the organic field effect transistors. These observations illustrated that the utilization of thermal removable side chain functionalized conjugated polymers can be an effective strategy for developing conjugated polymers with impressive charge carrier transport.

Surface protein patterns of tumor-derived exosomes could be promising noninvasive diagnostic biomarkers for liquid biopsy. However, a convenient and cost-effective platform for exosomal protein profiling is still lacking. Herein, a facile fluorescent aptasensor is developed to assess exosomal tumor-associated proteins, combining aptamers, aggregation-induced emission luminogens (AIEgens), and graphene oxide (GO) as recognition elements, fluorescent dye, and the quencher, respectively. Specifically, numberous TPE-TAs could bind one aptamer and form aggregates rapidly, resulting in an amplified fluorescence signal. In the absence of tumor-derived exosomes, GO absorbs the TPE-TAs/aptamer complex, allowing fluorescence quenching. When the target exosomes are introduced, the aptamer preferentially binds with its target. Thus the TPE-TAs/aptamer complexes detach from GO surface, followed by the appearance of a “turn-on” fluorescent signal. Under the optimized conditions, the linear range of target exosomes is estimated to be 4.07 × 105 to 1.83 × 107 particles/μL (0.68–30.4 pM) with a detection limit of 3.43 × 105 particles/μL (0.57 pM). This strategy demonstrated great performance in differentiating prostate cancer from healthy individuals (AUC: 0.9790). Furthermore, by profiling three tumor-associated protein markers including epidermal growth factor receptor (EGFR), epithelial cell adhesion molecule (EpCAM), and human epidermal growth factor receptor 2 (HER2) on exosomes in a breast tumor cohort, this sensing platform diagnoses breast tumors with high efficiency (AUC: 0.9845) and exhibits a high sensitivity of 97.37% for distinguishing malignant breast cancers, where the stage I cases were detected with 92.31% sensitivity. Therefore, this aptasensor provides a promising strategy to profile tumor-derived exosomal proteins for early diagnosis in liquid biopsy.

A fluorescent "turn-on" sensor for fast measurement of aliphatic biogenic amines (BAs) was developed based on fluorescent carboxylated polyfluorene (PFTBTCOOH)/chitosan-graft-oleic acid (CS-graft-OA) micelles. In this system, biobased CS-graft-OA micelles, prepared by graft modification of CS with OA, serve as the vector of the hydrophobic fluorescent probe. Bright turn-on fluorescence was achieved by the intermolecular fluorescence resonance energy transfer of the encapsulated PFTBTCOOH, driven by the formation of an electrostatic complex with aliphatic BAs, which facilitate visual identification. The peak intensity ratio of the PFTBTCOOH/CS-graft-OA micelles toward an increasing amount of aliphatic BAs was calibrated, giving a linear relationship. The fluorescence response of PFTBTCOOH/CS-graft-OA micelles to aliphatic BAs in milk and yogurt matrixes reaches a detection concentration as low as 10 μM, showing that the PFTBTCOOH/CS-graft-OA micelle solution is a potential chemosensor for fast and selective detection of trace aliphatic BAs, which is of great significance to public health and food safety.

Recently, advanced driver assistance system (ADAS) has attracted a lot of attention due to the fast growing industry of smart cars, which is believed to be the next human-computer interaction after smart phones. As ADAS is a critical enabling component in a human-in-the-loop cyber-physical system (CPS) involving complicated physical environment, it has stringent requirements on reliability, accuracy as well as latency. Lane and vehicle detections are the basic functions in ADAS, which provide lane departure warning (LDW) and forward collision warning (FCW) to predict the dangers and warn the drivers. While extensive literature exists on this topic, none of them considers the important fact that many vehicles today do not have powerful embedded electronics or cameras. It will be costly to upgrade the vehicle just for ADAS enhancement. To address this issue, we demonstrate a new framework that utilizes microprocessors in mobile devices with embedded cameras for advanced driver assistance. The main challenge that comes with this low cost solution is the dilemma between limited computing power and tight latency requirement, and uncalibrated camera and high accuracy requirement. Accordingly, we propose an efficient, accurate, flexible yet light-weight real-time lane and vehicle detection method and implement it on Android devices. Real road test results suggest that an average latency of 15 fps can be achieved with a high accuracy of 12.58 average pixel offset for each lane in all scenarios and 97+ precision for vehicle detection. To the best of the authors' knowledge, this is the very first implementation of both lane and vehicle detections on mobile devices with un-calibrated embedded camera.

In this paper we propose an innovative 3D IC architecture that combines reconfigurable 2D structure with monolithic 3D. This new architecture not only resolves Power Distributive Network (PDN) design and thermal management issues of traditional 3D-IC, but also provides additional power control and programmable routing capability. It provides a cost effective way to integrate different modules together using stacked interposer structure. With power rails and signal paths that can be routed dynamically using reconfigurable peripheral switches, the new system is adjustable. Moreover, area saving is achieved by using monolithic 3D to realize the modules. With the corresponding new thermal aware hierarchical simulated annealing floorplan algorithm designed for our hybrid reconfigurable architecture, the thermal problem can be further alleviated. Our testing results on 15 benchmarks show that we obtain an average 1.69× lower temperature and average 2.82× smaller power compared with traditional 2D SoC structure, 1.3× lower temperature compared to traditional 3D structure.

Recent growing needs for real time data analytics have increased importance of streaming model selection. Real-world streaming observations are often obtained by dynamically-changing or heterogeneous data sources, and learning machines must identify the complexities of the data generation processes on the fly without prior knowledge. This paper proposes online FAB (OFAB) inference as a general framework for streaming model selection of latent variable models. The key idea in OFAB inference is degeneration, i.e. it intentionally considers a "redundant" latent space anddynamically derives a "non-redundant" latent sub-space using a FAB-unique shrinkage mechanism on demand. By integrating the idea of stochastic variational inference, OFAB automatically and dynamically selects the best dimensionality of latent variables in a streaming and Bayesian principled manner. Empirical results on two applications, density estimation and abnormal detection, show that online FAB (OFAB) outperformed the state-of-the-art online inference methods.

Touchscreen technology plays an important role in the booming mobile devices market. Traditional touchscreen only provides 2D interactions with limited user experience. To overcome these limitations, we propose a novel 3D touch sensing system called the Airtouch system, which can recognize the movement of the finger in a 3-dimensional space. Half of the manufacturing cost is reduced by applying only single layer electrodes in the touch panel design. Moreover, an oscillator based correlated double sampling circuit is implemented as the self-capacitive sensor with bootstrapping technique to reduce inter-channel-coupling effect. Additionally, new algorithm for finger positioning is created with grouping filter invented to reduce system background noise. The demonstrated setup can successfully detect finger movement within a vertical range of 6cm and achieve a horizontal resolution up to 1cm. This system offers great potential in both gesture recognition for small-sized electronics, and advanced human interactive games for TV and mobile device.