Energy Efficient Memristor Based on Green-Synthesized 2D Carbonyl-Decorated Organic Polymer and Application in Image Denoising and Edge Detection: Toward Sustainable AI.

According to the United Nations, around 53 million metric tons of electronic waste is produced every year, worldwide, the big majority of which goes unprocessed. With the rapid advances in AI technologies and adoption of smart gadgets, the demand for powerful logic and memory chips is expected to boom. Therefore, the development of green electronics is crucial to minimizing the impact of the alarmingly increasing e-waste. Here, it is shown the application of a green synthesized, chemically stable, carbonyl-decorated 2D organic, and biocompatible polymer as an active layer in a memristor device, sandwiched between potentially fully recyclable electrodes. The 2D polymer's ultramicro channels, decorated with C═O and O─H groups, efficiently promote the formation of copper nanofilaments. As a result, the device shows excellent bipolar resistive switching behavior with the potential to mimic synaptic plasticity. A large resistive switching window (103), low SET/RESET voltage of ≈0.5/-1.5 V), excellent device-to-device stability and synaptic features are demonstrated. Leveraging the device's synaptic characteristics, its applications in image denoising and edge detection is examined. The results show a reduction in power consumption by a factor of 103 compared to a traditional Tesla P40 graphics processing unit, indicating great promise for future sustainable AI-based applications.

Highly Efficient Back-End-of-Line Compatible Flexible Si-Based Optical Memristive Crossbar Array for Edge Neuromorphic Physiological Signal Processing and Bionic Machine Vision.

The emergence of the Internet-of-Things is anticipated to create a vast market for what are known as smart edge devices, opening numerous opportunities across countless domains, including personalized healthcare and advanced robotics. Leveraging 3D integration, edge devices can achieve unprecedented miniaturization while simultaneously boosting processing power and minimizing energy consumption. Here, we demonstrate a back-end-of-line compatible optoelectronic synapse with a transfer learning method on health care applications, including electroencephalogram (EEG)-based seizure prediction, electromyography (EMG)-based gesture recognition, and electrocardiogram (ECG)-based arrhythmia detection. With experiments on three biomedical datasets, we observe the classification accuracy improvement for the pretrained model with 2.93% on EEG, 4.90% on ECG, and 7.92% on EMG, respectively. The optical programming property of the device enables an ultra-low power (2.8 × 10-13 J) fine-tuning process and offers solutions for patient-specific issues in edge computing scenarios. Moreover, the device exhibits impressive light-sensitive characteristics that enable a range of light-triggered synaptic functions, making it promising for neuromorphic vision application. To display the benefits of these intricate synaptic properties, a 5 × 5 optoelectronic synapse array is developed, effectively simulating human visual perception and memory functions. The proposed flexible optoelectronic synapse holds immense potential for advancing the fields of neuromorphic physiological signal processing and artificial visual systems in wearable applications.

Minimally Invasive Hypoglossal Nerve Stimulator Enabled by ECG Sensor and WPT to Manage Obstructive Sleep Apnea.

A hypoglossal nerve stimulator (HGNS) is an invasive device that is used to treat obstructive sleep apnea (OSA) through electrical stimulation. The conventional implantable HGNS device consists of a stimuli generator, a breathing sensor, and electrodes connected to the hypoglossal nerve via leads. However, this implant is bulky and causes significant trauma. In this paper, we propose a minimally invasive HGNS based on an electrocardiogram (ECG) sensor and wireless power transfer (WPT), consisting of a wearable breathing monitor and an implantable stimulator. The breathing external monitor utilizes an ECG sensor to identify abnormal breathing patterns associated with OSA with 88.68% accuracy, achieved through the utilization of a convolutional neural network (CNN) algorithm. With a skin thickness of 5 mm and a receiving coil diameter of 9 mm, the power conversion efficiency was measured as 31.8%. The implantable device, on the other hand, is composed of a front-end CMOS power management module (PMM), a binary-phase-shift-keying (BPSK)-based data demodulator, and a bipolar biphasic current stimuli generator. The PMM, with a silicon area of 0.06 mm2 (excluding PADs), demonstrated a power conversion efficiency of 77.5% when operating at a receiving frequency of 2 MHz. Furthermore, it offers three-voltage options (1.2 V, 1.8 V, and 3.1 V). Within the data receiver component, a low-power BPSK demodulator was ingeniously incorporated, consuming only 42 µW when supplied with a voltage of 0.7 V. The performance was achieved through the implementation of the self-biased phase-locked-loop (PLL) technique. The stimuli generator delivers biphasic constant currents, providing a 5 bit programmable range spanning from 0 to 2.4 mA. The functionality of the proposed ECG- and WPT-based HGNS was validated, representing a highly promising solution for the effective management of OSA, all while minimizing the trauma and space requirements.

Discovery and biological evaluation of a potent small molecule CRM1 inhibitor for its selective ablation of extranodal NK/T cell lymphoma.

Background: The overactivation of NF-κB signaling is a key hallmark for the pathogenesis of extranodal natural killer/T cell lymphoma (ENKTL), a very aggressive subtype of non-Hodgkin's lymphoma yet with rather limited control strategies. Previously, we found that the dysregulated exportin-1 (also known as CRM1) is mainly responsible for tumor cells to evade apoptosis and promote tumor-associated pathways such as NF-κB signaling. Methods: Herein we reported the discovery and biological evaluation of a potent small molecule CRM1 inhibitor, LFS-1107. We validated that CRM1 is a major cellular target of LFS-1107 by biolayer interferometry assay (BLI) and the knockdown of CRM1 conferred tumor cells with resistance to LFS-1107. Results: We found that LFS-1107 can strongly suppresses the growth of ENKTL cells at low-range nanomolar concentration yet with minimal effects on human platelets and healthy peripheral blood mononuclear cells. Treatment of ENKTL cells with LFS-1107 resulted in the nuclear retention of IkBα and consequent strong suppression of NF-κB transcriptional activities, NF-κB target genes downregulation and attenuated tumor cell growth and proliferation. Furthermore, LFS-1107 exhibited potent activities when administered to immunodeficient mice engrafted with human ENKTL cells. Conclusions: Therefore, LFS-1107 holds great promise for the treatment of ENKTL and may warrant translation for use in clinical trials. Funding: Yang's laboratory was supported by the National Natural Science Foundation of China (Grant: 81874301), the Fundamental Research Funds for Central University (Grant: DUT22YG122) and the Key Research project of 'be Recruited and be in Command' in Liaoning Province (Personal Target Discovery for Metabolic Diseases).

Associations between underlying diseases with COVID-19 and its symptoms among adults: a cross-sectional study.

Background: Specific underlying diseases were reported to be associated with severe COVID-19 outcomes, but little is known about their combined associations. The study was aimed to assess the relations of number of and specific underlying diseases to COVID-19, severe symptoms, loss of smell, and loss of taste. Methods: A total of 28,204 adult participants in the National Health Interview Survey 2021 were included. Underlying diseases (including cardiovascular diseases, cancer, endocrine diseases, respiratory diseases, neuropsychiatric diseases, liver and kidney diseases, fatigue syndrome, and sensory impairments), the history of COVID-19, and its symptoms were self-reported by structured questionnaires. Multivariable logistic regression models were used to assess the combined relation of total number of underlying diseases to COVID-19 and its symptoms, while mutually adjusted logistic models were used to examine their independent associations. Results: Among the 28,204 participants (mean ± standard deviation: 48.2 ± 18.5 years), each additional underlying disease was related to 33, 20, 37, and 39% higher odds of COVID-19 (odds ratio [OR]: 1.33, 95% confidence interval [CI]: 1.29-1.37), severe symptoms (OR: 1.20, 95% CI: 1.12-1.29), loss of smell (OR: 1.37, 95% CI: 1.29-1.46), and loss of taste (OR: 1.39, 95% CI: 1.31-1.49). In addition, independent associations of sensory impairments with COVID-19 (OR: 3.73, 95% CI: 3.44-4.05), severe symptoms (OR: 1.37, 95% CI: 1.13-1.67), loss of smell (OR: 8.17, 95% CI: 6.86-9.76), and loss of taste (OR: 6.13, 95% CI: 5.19-7.25), cardiovascular diseases with COVID-19 (OR: 1.13, 95% CI: 1.03-1.24), neuropsychiatric diseases with severe symptoms (OR: 1.41, 95% CI: 1.15-1.74), and endocrine diseases with loss of taste (OR: 1.28, 95% CI: 1.05-1.56) were observed. Conclusion: A larger number of underlying diseases were related to higher odds of COVID-19, severe symptoms, loss of smell, and loss of taste in a dose-response manner. Specific underlying diseases might be individually associated with COVID-19 and its symptoms.

Flexible Solution-Processable Black-Phosphorus-Based Optoelectronic Memristive Synapses for Neuromorphic Computing and Artificial Visual Perception Applications.

Being renowned for operating with visible-light pulses and electrical signals, optoelectronic memristive synaptic devices have excellent potential for neuromorphic computing systems and artificial visual information processing. Here, a flexible back-end-of-line-compatible optoelectronic memristor based on a solution-processable black phosphorus/HfOx bilayer with excellent synaptic features, toward biomimetic retinas is presented. The device shows highly stable synaptic features such as long-term potentiation (LTP) and long-term depression (LTD) for repetitive 1000 epochs, having 400 conductance pulses, each. The device presents advanced synaptic features in terms of long-term memory (LTM)/short term memory (STM), as well as learning-forgetting-relearning when visible light is induced on it. These advanced synaptic features can improve the information processing abilities for neuromorphic applications. Interestingly, the STM can be converted into LTM by adjusting the intensity of light and illumination time. Using the light-induced characteristics of the device, a 6 × 6 synaptic array is developed to exhibit possible use in artificial visual perception. Moreover, the devices are flexed using a silicon back-etching process. The resulting flexible devices demonstrate stable synaptic features when bent down to 1 cm radius. These multifunctional features in a single memristive cell make it highly suitable for optoelectronic memory storage, neuromorphic computing, and artificial visual perception applications.

Artificial visual perception neural system using a solution-processable MoS2-based in-memory light sensor.

Optoelectronic devices are advantageous in in-memory light sensing for visual information processing, recognition, and storage in an energy-efficient manner. Recently, in-memory light sensors have been proposed to improve the energy, area, and time efficiencies of neuromorphic computing systems. This study is primarily focused on the development of a single sensing-storage-processing node based on a two-terminal solution-processable MoS2 metal-oxide-semiconductor (MOS) charge-trapping memory structure-the basic structure for charge-coupled devices (CCD)-and showing its suitability for in-memory light sensing and artificial visual perception. The memory window of the device increased from 2.8 V to more than 6 V when the device was irradiated with optical lights of different wavelengths during the program operation. Furthermore, the charge retention capability of the device at a high temperature (100 °C) was enhanced from 36 to 64% when exposed to a light wavelength of 400 nm. The larger shift in the threshold voltage with an increasing operating voltage confirmed that more charges were trapped at the Al2O3/MoS2 interface and in the MoS2 layer. A small convolutional neural network was proposed to measure the optical sensing and electrical programming abilities of the device. The array simulation received optical images transmitted using a blue light wavelength and performed inference computation to process and recognize the images with 91% accuracy. This study is a significant step toward the development of optoelectronic MOS memory devices for neuromorphic visual perception, adaptive parallel processing networks for in-memory light sensing, and smart CCD cameras with artificial visual perception capabilities.

Tumor microenvironment responsive Mn3O4 nanoplatform for in vivo real-time monitoring of drug resistance and photothermal/chemodynamic synergistic therapy of gastric cancer.

BACKGROUND: Postoperative chemotherapy for gastric cancer often causes multidrug resistance (MDR), which has serious consequences for therapeutic effects. Individualized treatment based on accurate monitoring of MDR will greatly improve patient survival. RESULTS: In this article, a self-enhanced Mn3O4 nanoplatform (MPG NPs) was established, which can react with glutathione to produce Mn2+ to enhance T1-weighted magnetic resonance imaging (MRI) and mediate in vivo real-time MDR monitoring. In vitro MRI results showed that MRI signals could be enhanced in the presence of hydrogen peroxide and glutathione and at acidic pH. In vivo MRI results indicated that MPG NPs could specifically target MDR cells, thereby realizing real-time monitoring of MDR in gastric cancer. Furthermore, MPG NPs have good chemodynamic activity, which can convert the endogenous hydrogen peroxide of tumor cells into highly toxic hydroxyl radical through Fenton-like reaction at acidic pH to play the role of chemodynamic therapy. In addition, Mn3O4 can significantly enhance the chemodynamic therapy effect because of its good photothermal conversion effect. Furthermore, in situ photothermal/chemodynamic synergistic therapy obtained remarkable results, the tumors of the mice in the synergistic therapy group gradually became smaller or even disappeared. CONCLUSIONS: MPG NPs have good biocompatibility, providing a good nanoplatform for real-time monitoring and precise diagnosis and treatment of MDR in gastric cancer.

DNA Origami-Anthraquinone Hybrid Nanostructures for In Vivo Quantitative Monitoring of the Progression of Tumor Hypoxia Affected by Chemotherapy.

Hypoxia is a well-known feature of malignant solid tumors. To explain the misinterpretation of tumor hypoxia variation during chemotherapy, we developed a DNA origami-based theranostic nanoplatform with an intercalated anticancer anthraquinone as both the chemotherapeutic drug and the photoacoustic contrast agent. The size distribution of the DNA origami nanostructure is 44.5 ± 2.3 nm, whereas the encapsulation efficiency of the drug is 90.7 ± 1.0%, and the drug loading content is 92.2 ± 0.1%. The controlled cumulative release rates were measured in vitro, showing an acidic environment induced rapid drug release. The values of free energy of binding between the drugs and the DNA double helix were calculated through molecular simulations. The cell viability assay was used to characterize cytotoxicity, and fluorescence confocal cell imaging illustrates the biodistribution of the probe in vitro. Photoacoustic and fluorescence imaging were used to indicate drug delivery, release, and biodistribution to predict the drug's chemotherapeutic effect in vivo, whereas the photoacoustic signals were compared with those of deoxygenated/oxygenated hemoglobin to represent the tissue hypoxia/normoxia maps during the chemotherapeutic process and indicate alleviated tumor hypoxia. Staining of tissue sections taken from organs and tumors was used to verify the results of photoacoustic imaging. Our results suggest that photoacoustic imaging can visualize this DNA origami-based theranostic nanoplatform and reveal the mechanisms of chemotherapy on tumor hypoxia.