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Background Smart-bar device (SBD) is a newly developed device to measure the body range of motion (ROM) by a kinetic sensor and to provide an exercise program with augmented reality (AR) guidance of body-frame image and audio feedback by mobile application. Objective This study aims to compare the performance of SBD with AR function with a goniometer and to verify the clinical utility of SBD with AR guide function` Methods Ten healthy individuals were enrolled and measured the ROM of body lateral flexion, extension, and rotation using a goniometer and SBD simultaneously. To evaluate the accuracy of an AR-guided exercise, we enrolled three patients with adolescent idiopathic scoliosis and measured the ROM of trunk lateral flexion and rotation during stretching exercises using SBD with or without AR guidance. Results Concurrent validity between the goniometer and SBD was statistically significant, with a very high correlation coefficient from r = 0.836–0.988 (p p Conclusions The SBD could be a valid device to measure the joint angle of neck, shoulder, and trunk. AR guidance increased the accuracy of the stretching exercise, and mobile application of AR-guided stretching exercises with SBD should be useful for scoliosis patients to correct their posture.

We report a miniaturized, minimally invasive high-density neural recording interface that occupies only a 1.53 mm2 footprint for hybrid integration of a flexible probe and a 256-channel integrated circuit chip. To achieve such a compact form factor, we developed a custom flip-chip bonding technique using anisotropic conductive film and analog circuit-under-pad in a tiny pitch of 75 m. To enhance signal-to-noise ratios, we applied a reference-replica topology that can provide the matched input impedance for signal and reference paths in low-noise aimpliers (LNAs). The analog front-end (AFE) consists of LNAs, buffers, programmable gain amplifiers, 10b ADCs, a reference generator, a digital controller, and serial-peripheral interfaces (SPIs). The AFE consumes 51.92 W from 1.2 V and 1.8 V supplies in an area of 0.0161 mm2 per channel, implemented in a 180 nm CMOS process. The AFE shows > 60 dB mid-band CMRR, 6.32 Vrms input-referred noise from 0.5 Hz to 10 kHz, and 48 M input impedance at 1 kHz. The fabricated AFE chip was directly flip-chip bonded with a 256-channel flexible polyimide neural probe and assembled in a tiny head-stage PCB. Full functionalities of the fabricated 256-channel interface were validated in both in vitro and in vivo experiments, demonstrating the presented hybrid neural recording interface is suitable for various neuroscience studies in the quest of large scale, miniaturized recording systems.

This study presents a CMOS image sensor (CIS) with a two-step single-slope (TS-SS) analog-to-digital convertor (ADC), wherein the differential topology characteristics of a ramp generator are used. The proposed TS-SS ADC effectively resolves 1 most significant bit (MSB) with a half-ramping of a full analog-to-digital (A/D) reference at coarse conversion and the remaining least significant bits (LSBs) with differential slope ramping signals from the ramp generator. The proposed readout scheme maintains the existing column readout structure and does not require to regenerate the coarse-step region in each column. Moreover, the proposed TS-SS readout scheme is verified for a frame rate enhancement, that is, the efficiency increases as the bit depth of the ADC increases. A prototype CIS with the proposed 10-bit TS-SS ADC was implemented in a 1P4M 0.11- $\mu \text{m}$ CIS process with a 2.9- $\mu \text{m}$ pitch. The measurement results of the prototype CIS demonstrated the figure of merits (FoMs) of $102~\mu \text{V}\cdot $ pJ/steps and $2.79~\mu \text{V}$ /MHz/steps.

We present a high-power conversion efficiency (PCE) on-chip switched-capacitor (SC) DC–DC step-up converter for a fully implantable neural interface operating with less than a few tens µW from energy harvesting. To improve the PCE in such light loads and wide variations of voltage-conversion ratio (VCR), which is a typical scenario for ultra-low-power fully implantable systems depending on energy harvesting, a phase-reduced soft-charging technique has been implemented in a step-up converter, thereby achieving very low VCR-sensitive PCE variation compared with other state-of-the-art works. The proposed DC–DC converter has been fabricated in a standard 180 nm CMOS 1P6M process. It exhibits high PCE (~80%) for wide input and output ranges from 0.5 V to 1.2 V and from 1.2 V to 1.8 V, respectively, with switching frequencies of 0.3–2 MHz, achieving a peak efficiency of 82.6% at 54 µW loads.

We report a low-power, bio-inspired mixed-signal 2-D optic flow sensor to realize artificial compound eyes, which can provide a wide field of view (FoV) sensing capability for autonomous navigation of micro-air-vehicles (MAVs). Inspired by insect vision, a 2-D time-stamp algorithm has been developed to scale the number of deployable sensors at low power. The fabricated sensor estimates 16-b 2-D optic flows of maximum 1.96 rad/s with FoV of 60° from the integrated mixed-signal algorithm core, which consumes only 243.3 pJ/pixel or $\sim 30~\mu \text{W}$ at 120 fps. In addition, the peripheral circuits for modular design have been integrated on chip to provide optic flow data compression, wide-field integration (WFI), and serial peripheral interface (SPI). More than 25 sensors can be connected in a single SPI bus and transmit the full resolution optic flows. The fabricated prototype sensor supports full resolution 2-D optic flows from an array of $64\times 64$ pixels at 120 fps through a 3 MB/s SPI bus (4 wires total).

The Golgi is the central sorting station in the secretory pathway and thus the destination of transport vesicles arriving from the endoplasmic reticulum and endosomes and from within the Golgi itself. Cell viability, therefore, requires that the Golgi accurately receives multiple classes of vesicle. One set of proteins proposed to direct vesicle arrival at the Golgi are the golgins, long coiled-coil proteins localized to specific parts of the Golgi stack. In mammalian cells, three of the golgins, TMF, golgin-84, and GMAP-210, can capture intra-Golgi transport vesicles when placed in an ectopic location. However, the individual golgins are not required for cell viability, and mouse knockout mutants only have defects in specific tissues. To further illuminate this system, we examine the Drosophila orthologs of these three intra-Golgi golgins. We show that ectopic forms can capture intra-Golgi transport vesicles, but strikingly, the cargo present in the vesicles captured by each golgin varies between tissues. Loss-of-function mutants show that the golgins are individually dispensable, although the loss of TMF recapitulates the male fertility defects observed in mice. However, the deletion of multiple golgins results in defects in glycosylation and loss of viability. Examining the vesicles captured by a particular golgin when another golgin is missing reveals that the vesicle content in one tissue changes to resemble that of a different tissue. This reveals a plasticity in Golgi organization between tissues, providing an explanation for why the Golgi is sufficiently robust to tolerate the loss of many of the individual components of its membrane traffic machinery.

Neural interfaces, which enable the recording and stimulation of living neurons, have emerged as valuable tools in understanding the brain in health and disease, as well as serving as neural prostheses. While neural interfaces are typically based on electrical transduction, alternative energy modalities have been explored to create safe and effective approaches. Among these approaches, optical methods of linking neurons to the outside world have gained attention because light offers high spatial selectivity and decreased invasiveness. Here, we review the current state-of-art of optical neural interfaces and their clinical applications. Optical neural interfaces can be categorized into optical control and optical readout, each of which can be divided into intrinsic and extrinsic approaches. We discuss the advantages and disadvantages of each of these methods and offer a comparison of relative performance. Future directions, including their clinical opportunities, are discussed with regard to the optical properties of biological tissue.

We present a CMOS imager for low-latency face detection empowered by parallel imaging and computing of machine-learning (ML) classifiers. The energy-efficient parallel operation and multi-scale detection eliminate image capture delay and significantly alleviate backend computational loads. The proposed pixel architecture, composed of dynamic samplers in a global shutter (GS) pixel array, allows for energy-efficient in-memory charge-domain computing of feature extraction and classification. The illumination-invariant detection was realized by using log-Haar features. A prototype 240×240 imager achieved an on-chip face detection latency of 5.1ms with a 97.9% true positive rate and 2% false positive rate at 120fps. Moreover, a dynamic nature of in-memory computing allows an energy efficiency of 419pJ/pixel for feature extraction and classification, leading to the smallest latency-energy product of 3.66ms∙nJ/pixel with digital backend processing.

Aims Berteroin (5-methylthiopentyl isothiocyanate) is a naturally occurring sulforaphane analog containing a non-oxidized sulfur atom in cruciferous vegetables. The objectives of the present study were to determine the effects of berteroin on lipid metabolism in hepatocytes and adipocytes and to elucidate the mechanisms involved. Main methods The effect of berteroin on lipid metabolism were evaluated in liver X receptor α agonist-stimulated HepG2 cells and adipocyte differentiation-induced 3T3-L1 cells using MTT assay, western blot, real time polymerase chain reaction, oil red O staining, and triglyceride assay. Key findings T0901317 treatment increased the expression of sterol regulatory element binding protein (SREBP)-1c, a major transcription factor that mediates lipogenesis, and berteroin pretreatment significantly inhibited the expressions of T0901317-induced SREBP-1c and lipogenic genes. Especially, berteroin had a greater inhibitory effect on T0901317-induced SREBP-1c activation than sulforaphane, AICAR, or metformin. Berteroin also markedly suppressed lipid droplet formations and triglyceride accumulations caused by both T0901317 stimulation in HepG2 hepatocytes and differentiation induction in 3T3-L1 preadipocytes. However, berteroin significantly increased the expression of mitochondrial fatty acid oxidation-related genes (carnitine palmitoyltransferase 1 (CPT-1) and peroxisome proliferator-activated receptor gamma coactivator-1α) and the phosphorylation of adenosine monophosphate-activated protein kinase (AMPK) in HepG2 cells. Interestingly, effects of berteroin on the expressions of SREBP-1c protein and CPT-1 mRNA were remarkably prevented by compound C (an AMPK inhibitor). Significance Our results suggest berteroin-inhibited hepatic lipid accumulation and adipocyte differentiation might be mediated by AMPK activation and that berteroin might be useful for the prevention, amelioration, and treatment of metabolic diseases, including hepatic steatosis.

For centuries, Fructus ligustri lucidi (FLL, the fruit of Ligustrum lucidum Aiton or Ligustrum japonicum Thunb.) has been commonly used in traditional Chinese medicine for treating hepatitis and aging-related symptoms and in traditional Korean medicine to detoxify kidneys and the liver. Pharmacological research has shown FLL has antioxidant, anti-inflammatory, anticancer, anti-osteoporosis, and hepatoprotective activities. This study was undertaken to investigate the effects of FLL extract (FLLE) on neuroinflammation. After setting a non-toxic concentration using MTT [3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl-tetrazolium bromide] assay data, we investigated the effects of FLLE using Western blotting, cell migration, enzyme-linked immunosorbent assay, a nitric oxide (NO) assay, and immunofluorescence staining in lipopolysaccharide (LPS)-stimulated murine BV2 microglial cells. FLLE was non-toxic to BV2 cells up to a concentration of 500 μg/mL and concentration-dependently inhibited the production of NO and prostaglandin E2 and the protein levels of inducible nitric oxide synthase and cyclooxygenase-2 under LPS-induced inflammatory conditions. It also inhibited the secretion of the inflammatory cytokines tumor necrosis factor-α (TNF-α) and interleukin-6 (IL-6). Furthermore, FLLE pretreatment attenuated LPS-induced increases of CD68 (a marker of microglia activation) and suppressed the activation of mitogen-activated protein kinases (MAPKs) and nuclear factor-kappa B (NF-κB) signaling pathways in LPS-stimulated BV2 cells, and significantly increased heme oxygenase (HO)-1 levels. FLLE also reduced the LPS-induced increase in the migratory ability of BV2 cells and the phosphorylation of vascular endothelial growth factor receptor 1. Collectively, FLLE effectively inhibited inflammatory response by suppressing the MAPK and NF-κB signaling pathways and inducing HO-1 in LPS-stimulated BV2 microglial cells. Our findings provide a scientific basis for further study of FLL as a candidate for preventing or alleviating neuroinflammation.

Objectives. Ginsenoside Rg3 (Rg3), a main active component of Panax ginseng, has various therapeutic properties in literatures, and it has been studied for its potential use in obesity control due to its antiadipogenic effects in white adipocytes. However, little is known about its effects on brown adipocytes. Methods. The mechanisms through which Rg3 inhibits differentiation, adipogenesis, and ER stress-mediated cell death in mouse primary brown adipocytes (MPBAs) are explored. Results. Rg3 significantly induced cytotoxicity in differentiated MPBAs but not in undifferentiated MPBAs. Rg3 treatment downregulated the expression of differentiation and adipogenesis markers and the level of perilipin in MPBAs while upregulating the expression of lipolytic Kruppel-like factor genes. Rg3 also induced lipolysis and efflux of triglycerides from MPBAs and subsequently increased proinflammatory cytokine levels. Notably, Rg3 treatment resulted in elevation of ER stress and proapoptotic markers in MPBAs. Conclusions. Our results demonstrate that Rg3 is able to selectively exert cytotoxicity in differentiated MPBAs while leaving undifferentiated MPBAs intact, resulting in the induction of ER stress and subsequent cell death in MPBAs via regulation of various genes related to adipocyte differentiation, adipogenesis, lipolysis, and inflammation. These results indicate that further studies on the potential therapeutic applications of Rg3 are warranted.

We present a prototype CMOS active pixel that is capable of simultaneous imaging and energy harvesting without introducing additional in-plane p-n junctions. The prototype pixel uses a vertical ${p}^{+}/{n}_{\text {well}}/{p}_{\text {sub}}$ junction that is available in standard CMOS processes. Unlike the conventional CMOS electron-based imaging pixels, where the ${n}_{\text {well}}$ region is used as a sensing node for image capture, we adopted a hole-based imaging technique, while exploiting the ${n}_{\text {well}}$ region for energy harvesting at a high fill-factor of >94%. To verify the feasibility, CMOS image sensors are fabricated and characterized. We successfully demonstrated that the energy harvesting can be achieved with a power density of 998 pW/klux/mm2, while capturing images at 74.67 pJ/pixel. The fabricated prototype device has achieved the highest power density among the recent state-of-the-art works and can self-sustain its image capturing operation at 15 fps without external power sources above ~60 klux of illumination.

We report a scalable neural recording interface with embedded lossless compression to reduce dynamic power consumption ( $\text{P}_{D}$ ) for data transmission in high-density neural recording systems. We investigated the characteristics of neural signals and implemented effective lossless compression for local field potential (LFP) and extracellular action potential (EAP or spike) in separate signal paths. For LFP, spatial–temporal (spatiotemporal) correlation of the LFP signals is exploited in a $\Delta $ -modulated $\Delta \Sigma $ analog-to-digital converter ( $\Delta -\Delta \Sigma $ ADC) and a dedicated digital difference circuit. Then, statistical redundancy is further eliminated through entropy encoding without information loss. For spikes, only essential parts of waveforms in the spikes are extracted from the raw data by using spike detectors and reconfigurable analog memories. The prototype chip was fabricated using 180-nm CMOS processes, incorporating 128 channels into a modular architecture that is easily scalable and expandable for high-density neural recordings. The fabricated chip achieved the data rate reduction for the LFPs and spikes by a factor of 5.35 and 10.54, respectively, from the proposed compression scheme. Consequently, $P_{D}$ was reduced by 89%, when compared to the uncompressed case. We also achieved the state-of-the-art recording performance of 3.37 $\mu \text{W}$ per channel, 5.18 $\mu V_{\mathrm {rms}}$ noise, and 3.41 ${\text {NEF}}^{2}V_{\mathrm {DD}}$ .

We report an area- and energy-efficient integrated circuit architecture of a 128-channel $\Delta$ -modulated $\Delta \Sigma$ analog front-end ( $\Delta$ - $\Delta \Sigma$ AFE) for 1024-channel 3-D massive-parallel neural recording microsystems. Our platform has adopted a modularity of 128 channels and consists of eight multi-shank neural probes connected to individual AFEs through interposers in a small form factor. In order to reduce both area and energy consumption in the recording circuits, we implemented a spectrum equalization scheme to take advantage of the inherent spectral characteristics of neural signals, where most of the energy is confined in low frequencies and follows a ~1/f curve in the spectrum. This allows us to implement the AFE with a relaxed dynamic range by ~30 dB, thereby contributing to the significant reduction of both energy and area without sacrificing signal integrity. The $\Delta$ - $\Delta \Sigma$ AFE was fabricated using 0.18- $\mu \text{m}$ CMOS processes. The single-channel AFE consumes 3.05 $\mu \text{W}$ from 0.5 and 1.0 V supplies in an area of 0.05 mm2 with 63.8-dB signal-to-noise-and-distortion ratio, 3.02 noise efficiency factor (NEF), and 4.56 NEF2VDD. We also have achieved an energy-area product, a figure-of-merit most critical for massive-parallel neural recording systems, of 6.34 fJ/ $\text{C}\cdot \text{s}\cdot$ mm2.

We present an AC-coupled modular 16-channel analog frontend with 1.774 fJ/c-s∙mm2 energy- and area-product for a multichannel recording of broadband neural signals including local field potentials (LFPs) and extracellular action potentials (EAPs). To achieve such a small area- and energy-product, we employed an operational transconductance amplifier (OTA) with local positive feedback, instead of a widely-used folded cascode OTA (FC-OTA) or current mirror OTA for conventional neural recordings, while optimizing the design parameters affecting performance, power, and area trade-offs. In addition, a second pole was strategically introduced in the LNA to reduce the noise bandwidth without an in-channel low-pass filter. Compared to conventional works, the presented method shows better performance in terms of noise, power, and area usages. The performance of the fabricated 16-channel analog frontend is fully characterized in a benchtop and an in vitro setup. The 16-channel frontend embraces LFPs and EAPs with 4.27 μVrms input referred noise (0.5–10 kHz) and 53.17 dB dynamic range, consuming 3.44 μW and 0.012 mm2 per channel. The channel figure of merit (FoM) of the prototype is 147.87 fJ/c-s and the energy-area FoM (E-A FoM) is 1.774 fJ/c-s∙mm2.

In this paper, we present a low-power, low-noise fully differential pseudo-open-loop preamplifier with programmable bandwidth for monitoring neural activities. The proposed pseudo-open-loop topology can achieve high-power-noise efficiency as well as high linearity and precise gain control over process. The proposed fully differential preamplifier can balance the common mode of the differential outputs without a common-mode feedback circuit, and bias the ac-coupled input transistors without an external reference. A current-ratio gain design can set a stable gain over process and bias current variations. A programmable embedded $g_{m}-C$ low-pass filter (LPF) can be tuned by adjusting bias current, so that the proposed preamplifier can be configured to be used in recording single neuron spikes or field potentials (EEG, ECoG). The proposed amplifier is configured to consume 400 nA at 2.5-V power supply; the total chip area is 0.189 mm2. The measured thermal noise floor is 85 nV/ $\surd $ Hz and input-referred noise is $1.69~\mu \text{V}_{\mathrm {rms}}$ from 0.3 Hz to 1 kHz when using a chopper stabilization technique to suppress 1/f noise. The fabricated preamplifier shows a noise efficiency factor of 2.43 in the fully differential topology.

We present an ultralow-power, ultra-wideband (UWB) transmitter (TX) in standard 65-nm CMOS processes. The TX consists of feedforward edge combiners and interpolators for ultralow-power operation and reliable pulse generation that is essential in UWB TXs. The implemented circuit avoids pulse overlapping without complicated calibrations and has achieved an energy efficiency of 4.32 pJ/b at 200-Mbps data rate. The TX is suitable for energy-constraint, high-data-rate applications such as wireless telemetry in implantable high-density neural recording interfaces.

The phosphoinositide 3‑kinase (PI3K) signaling pathway plays an important role in human cancer as it regulates critical cellular functions, such as survival, proliferation and metabolism. In the present study, a novel PI3Kα inhibitor (HS‑146) was synthesized and its anticancer effects on MCF‑7, MDA‑MB‑231, SKBR3 and BT‑474 human breast cancer cell lines were confirmed. HS‑146 was found to be most effective in inhibiting the proliferation of MCF‑7 cells and in inducing cell cycle arrest in the G0/G1 phase by downregulating cyclin D1, cyclin E, cyclin‑dependent kinase (Cdk)2 and Cdk4, and upregulating p21Waf1/Cip1 protein levels in this cell line. The induction of apoptosis by HS‑146 was confirmed by DAPI staining and western blot analysis. Cell shrinkage and nuclear condensation, which are typical morphological markers of apoptosis, were increased by HS‑146 in the MCF‑7 cells in a concentration‑dependent manner, and HS‑146 also increased the protein expression levels of cleaved poly(ADP‑ribose) polymerase (PARP) and decreased the protein expression levels of Mcl‑1 and caspase‑7. In addition, HS‑146 effectively decreased the phosphorylation levels of downstream PI3K effectors, such as Akt, mammalian target of rapamycin (mTOR), glycogen synthase kinase 3β (GSK3β), p70S6K1 and eukaryotic translation initiation factor 4E‑binding protein 1 (4E‑BP1). Hypoxia‑inducible factor (HIF)‑1α and vascular endothelial growth factor (VEGF) expression were also suppressed by HS‑146 under hypoxic conditions, and HS‑146 inhibited the migration and invasion of MCF‑7 cells in a concentration‑dependent manner. On the whole, the findings of the present study suggest that HS‑146, a novel PI3Kα inhibitor, may be an effective novel therapeutic candidate that suppresses breast cancer proliferation and metastasis by inhibiting the PI3K/Akt/mTOR pathway.

We present a neural interface IC for high-precision optical stimulation and electrical recording from implanted optoelectrodes with the highest system integration to date. The system combines 12 high-resolution constant-current LED driver channels, 32 recording channels, and an efficient PMU for operation from a low voltage Li battery on a wireless platform. A novel LED driver architecture features a high-efficiency wide-current-range fully-integrated voltage regulator and a high-resolution pulse shaper to minimize recording artifacts from sharp current pulse edges. A prototype, fabricated in 0.18µm CMOS, occupies 7.35mm2. The LED driver has a peak efficiency of 50% and consumes 31µW quiescent power. We demonstrate in-vivo that the pulse-shaping scheme prevents stimulation artifacts. Key Words: neural interface, LED driver, optogenetics.

Background. Obesity is a pathological condition associated with various diseases including diabetes, stroke, arthritis, infertility, and heart disease. Moxibustion is widely used to prevent and manage obesity in traditional Asian medicine. We tested our hypothesis that moxibustion-simulating bipolar radiofrequency (M-RF) can suppress total body and white adipose tissue (WAT) weight gain via induction of WAT browning in a mouse model of diet-induced obesity (DIO). Methods. We designed an M-RF device that could accurately adjust the depth and temperature at which heat stimulation was administered into the abdomen of DIO mice. High-fat-fed male C57BL/6 mice were treated with the M-RF device every two or three days for three weeks. We then harvested WAT and serum from the mice and measured total body and WAT weight, size of adipocytes, mitochondrial contents, features of the dead adipocyte environment, and levels of uncoupling protein 1 (UCP1) and fibroblast growth factor 21 (FGF21). Results. Heat stimulation by M-RF in DIO mice resulted in precise temperature adjustment in the mice abdomen, with variance less than 1°C. Additionally, M-RF stimulation inhibited body and WAT weight gain, resulting in increased formation of beige adipocytes, increased mitochondrial content, and decreased formation of dead adipocytes in WAT. Moreover, treatment of M-RF induced expression of UCP1 and FGF21 in serum and/or epididymal WATs in DIO mice. Conclusion. Heat stimulation by M-RF treatment induced upregulation of UCP1 and FGF21 expression in serum and/or WATs, which was correlated with reduced total body and WAT weight gain in DIO mice.

Here, the speckle noise in ultrasonic images is removed using an image fusion-based denoising method. To optimize the denoising performance, each discrete wavelet transform (DWT) and filtering technique was analyzed and compared. In addition, the performances were compared in order to derive the optimal input conditions. To evaluate the speckle noise removal performance, an image fusion algorithm was applied to the ultrasound images, and comparatively analyzed with the original image without the algorithm. As a result, applying DWT and filtering techniques caused information loss and noise characteristics, and did not represent the most significant noise reduction performance. Conversely, an image fusion method applying SRAD-original conditions preserved the key information in the original image, and the speckle noise was removed. Based on such characteristics, the input conditions of SRAD-original had the best denoising performance with the ultrasound images. From this study, the best denoising technique proposed based on the results was confirmed to have a high potential for clinical application.