The m6A writer RBM15 drives the growth of triple-negative breast cancer cells through the stimulation of serine and glycine metabolism.

N6-adenosine methylation (m6A) is critical for controlling cancer cell growth and tumorigenesis. However, the function and detailed mechanism of how m6A methyltransferases modulate m6A levels on specific targets remain unknown. In the current study, we identified significantly elevated levels of RBM15, an m6A writer, in basal-like breast cancer (BC) patients compared to nonbasal-like BC patients and linked this increase to worse clinical outcomes. Gene expression profiling revealed correlations between RBM15 and serine and glycine metabolic genes, including PHGDH, PSAT1, PSPH, and SHMT2. RBM15 influences m6A levels and, specifically, the m6A levels of serine and glycine metabolic genes via direct binding to target RNA. The effects of RBM15 on cell growth were largely dependent on serine and glycine metabolism. Thus, RBM15 coordinates cancer cell growth through altered serine and glycine metabolism, suggesting that RBM15 is a new therapeutic target in BC.

Toward Ideal Low-Frequency Noise in Monolayer CVD MoS2 FETs: Influence of van der Waals Junctions and Sulfur Vacancy Management.

The pursuit of sub-1-nm field-effect transistor (FET) channels within 3D semiconducting crystals faces challenges due to diminished gate electrostatics and increased charge carrier scattering. 2D semiconductors, exemplified by transition metal dichalcogenides, provide a promising alternative. However, the non-idealities, such as excess low-frequency noise (LFN) in 2D FETs, present substantial hurdles to their realization and commercialization. In this study, ideal LFN characteristics in monolayer MoS2 FETs are attained by engineering the metal-2D semiconductor contact and the subgap density of states (DOS). By probing non-ideal contact resistance effects using CuS and Au electrodes, it is uncovered that excess contact noise in the high drain current (ID) region can be substantially reduced by forming a van der Waals junction with CuS electrodes. Furthermore, thermal annealing effectively mitigates sulfur vacancy-induced subgap density of states (DOS), diminishing excess noise in the low ID region. Through meticulous optimization of metal-2D semiconductor contacts and subgap DOS, alignment of 1/f noise with the pure carrier number fluctuation model is achieved, ultimately achieving the sought-after ideal LFN behavior in monolayer MoS2 FETs. This study underscores the necessity of refining excess noise, heralding improved performance and reliability of 2D electronic devices.

Rapid Surface Reconstruction of In2S3 Photoanode via Flame Treatment for Enhanced Photoelectrochemical Performance.

Surface reconstruction, reorganizing the surface atoms or structure, is a promising strategy to manipulate materials' electrical, electrochemical, and surface catalytic properties. Herein, a rapid surface reconstruction of indium sulfide (In2S3) is demonstrated via a high-temperature flame treatment to improve its charge collection properties. The flame process selectively transforms the In2S3 surface into a diffusionless In2O3 layer with high crystallinity. Additionally, it controllably generates bulk sulfur vacancies within a few seconds, leading to surface-reconstructed In2S3 (sr-In2S3). When using those sr-In2S3 as photoanode for photoelectrochemical water splitting devices, these dual functions of surface In2O3/bulk In2S3 reduce the charge recombination in the surface and bulk region, thus improving photocurrent density and stability. With optimized surface reconstruction, the sr-In2S3 photoanode demonstrates a significant photocurrent density of 8.5 mA cm-2 at 1.23 V versus a reversible hydrogen electrode (RHE), marking a 2.5-fold increase compared to pristine In2S3 (3.5 mA cm-2). More importantly, the sr-In2S3 photoanode exhibits an impressive photocurrent density of 7.3 mA cm-2 at 0.6 V versus RHE for iodide oxidation reaction. A practical and scalable surface reconstruction is also showcased via flame treatment. This work provides new insights for surface reconstruction engineering in sulfide-based semiconductors, making a breakthrough in developing efficient solar-fuel energy devices.

MicroRNA-135b-5p Is a Pathologic Biomarker in the Endothelial Cells of Arteriovenous Malformations.

Arteriovenous malformations (AVMs) are congenital vascular anomalies with a poor prognosis. AVMs are considered intractable diseases, as there is no established approach for early diagnosis and treatment. Therefore, this study aimed to provide new evidence by analyzing microRNAs (miRNAs) associated with AVM. We present fundamental evidence for the early diagnosis and treatment of AVM by analyzing miRNAs in the endothelial cells of AVMs. This study performed sequencing and validation of miRNAs in endothelial cells from normal and AVM tissues. Five upregulated and two downregulated miRNAs were subsequently analyzed under hypoxia and vascular endothelial growth factor (VEGF) treatment by one-way analysis of variance (ANOVA). Under hypoxic conditions, miR-135b-5p was significantly upregulated in the AVM compared to that under normal conditions, corresponding to increased endothelial activity (p-value = 0.0238). VEGF treatment showed no significant increase in miR-135b-5p under normal conditions, however, a surge in AVM was observed. Under both hypoxia and VEGF treatment, comparison indicated a downregulation of miR-135b-5p in AVM. Therefore, miR-135b-5p was assumed to affect the pathophysiological process of AVM and might play a vital role as a potential biomarker of AVMs for application related to diagnosis and treatment.

Demonstration of In-Memory Biosignal Analysis: Novel High-Density and Low-Power 3D Flash Memory Array for Arrhythmia Detection.

Smart healthcare systems integrated with advanced deep neural networks enable real-time health monitoring, early disease detection, and personalized treatment. In this work, a novel 3D AND-type flash memory array with a rounded double channel for computing-in-memory (CIM) architecture to overcome the limitations of conventional smart healthcare systems: the necessity of high area and energy efficiency while maintaining high classification accuracy is proposed. The fabricated array, characterized by low-power operations and high scalability with double independent channels per floor, exhibits enhanced cell density and energy efficiency while effectively emulating the features of biological synapses. The CIM architecture leveraging the fabricated array achieves high classification accuracy (93.5%) for electrocardiogram signals, ensuring timely detection of potentially life-threatening arrhythmias. Incorporated with a simplified spike-timing-dependent plasticity learning rule, the CIM architecture is suitable for robust, area- and energy-efficient in-memory arrhythmia detection systems. This work effectively addresses the challenges of conventional smart healthcare systems, paving the way for a more refined healthcare paradigm.

On-Chip Annealing Using Embedded Micro-Heater for Highly Sensitive and Selective Gas Detection.

The demand for gas sensing systems that enable fast and precise gas recognition is growing rapidly. However, substantial challenges arise from the complex fabrication process of sensor arrays, time-consuming data transmission to an external processor, and high energy consumption in multi-stage data processing. In this study, a gas sensing system using on-chip annealing for fast and power-efficient gas detection is proposed. By utilizing a micro-heater embedded in the gas sensor, the sensing material of adjacent sensors in the same substrate can be easily varied without further fabrication steps. The response to oxidizing gas is constrained in metal oxide (MOX) sensing material with small grain sizes, as the depletion width of grain cannot extend beyond the grain size during the gas reaction. On the other hand, the response to reducing gases and humidity, which decrease the depletion width, is less affected by grain sizes. A readout circuit integrating a differential amplifier and dual FET-type gas sensors effectively emphasizes the response to oxidizing gases by canceling the response to reducing gases and humidity. The selective on-chip annealing method is applicable to various MOX sensing materials, demonstrating its potential for application in commercial fields due to its simplicity and expandability.

Randomized controlled trial of digital therapeutics for temporomandibular disorder: A pilot study.

OBJECTIVES: Temporomandibular disorder (TMD) is a common condition that affects the temporomandibular joint (TMJ) and the muscles of the jaw, resulting in pain and dysfunction. TMD is affected by both behavioral and psychological factors. Digital therapeutics (DTx) can exert therapeutic effects by controlling behavioral factors through the delivery of appropriate interventions. Here, we report an open-label randomized control trial to evaluate the efficacy of DTx for TMD. METHODS: We recruited 40 participants diagnosed with TMD. Participants were randomly divided into an intervention group (DTx use, n = 20) and a control group (n = 20). The intervention group received the usual treatment process for TMD in addition to the use of the DTx. The control group received the usual treatments only. Patients in both groups were followed up for 3-4 weeks, and outcome data were collected and analyzed. RESULT: The intervention group showed a significant reduction in pain scores as measured by the numerical rating scale (NRS) (p = 0.016). Additionally, the intervention group showed a statistically significant increase in maximal mouth opening compared to the control group (p = 0.0079). However, there were no significant differences in improvement in the Jaw Functional Limitation Scale, Oral Behavior Checklist, and Patient Health Questionnaire-4 between the two groups (p = 0503, = 0.820, and = 0.943, respectively). CONCLUSION: This RCT reveals DTx potential in TMD, showing pain and mouth opening improvements with conventional treatment. But no significant changes were noted in other outcomes. The findings advocate for more extensive, long-term research to solidify DTx's role in TMD management. CLINICAL SIGNIFICANCE: This research underlines DTx potential to improve pain outcomes in TMD therapy, reinforcing its value as a complementary treatment modality.

Identification and pathogen detection of a Neocypholaelaps species (Acari: Mesostigmata: Ameroseiidae) from beehives in the Republic of Korea.

In this study, we identified a new strain of the genus Neocypholaelaps from the beehives of Apis mellifera colonies in the Republic of Korea (ROK). The Neocypholaelap sp. KOR23 mites were collected from the hives of honeybee apiaries in Wonju, Gangwon-do, in May 2023. Morphological and molecular analyses based on 18S and 28S rRNA gene regions conclusively identified that these mites belong to the genus Neocypholaelaps, closely resembling Neocypholaelaps sp. APGD-2010 that was first isolated from the United States. The presence of 9 of 25 honeybee pathogens in these mite samples suggests that Neocypholaelaps sp. KOR23 mite may act as an intermediate vector and carrier of honeybee diseases. The identification of various honeybee pathogens within this mite highlights their significance in disease transmission among honeybee colonies. This comprehensive study provides valuable insights into the taxonomy and implications of these mites for bee health management and pathogen dissemination.

Metformin Suppresses Both PD-L1 Expression in Cancer Cells and Cancer-Induced PD-1 Expression in Immune Cells to Promote Antitumor Immunity.

Background: Metformin, a drug prescribed for patients with type 2 diabetes, has potential efficacy in enhancing antitumor immunity; however, the detailed underlying mechanisms remain to be elucidated. Therefore, we aimed to identify the inhibitory molecular mechanisms of metformin on programmed death ligand 1 (PD-L1) expression in cancer cells and programmed death 1 (PD-1) expression in immune cells. Methods: We employed a luciferase reporter assay, quantitative real-time PCR, immunoblotting analysis, immunoprecipitation and ubiquitylation assays, and a natural killer (NK) cell-mediated tumor cell cytotoxicity assay. A mouse xenograft tumor model was used to evaluate the effect of metformin on tumor growth, followed by flow-cytometric analysis using tumor-derived single-cell suspensions. Results: Metformin decreased AKT-mediated ß-catenin S552 phosphorylation and subsequent ß-catenin transactivation in an adenosine monophosphate-activated protein kinase (AMPK) activation-dependent manner, resulting in reduced CD274 (encoding PD-L1) transcription in cancer cells. Tumor-derived soluble factors enhanced PD-1 protein stability in NK and T cells via dissociation of PD-1 from ubiquitin E3 ligases and reducing PD-1 polyubiquitylation. Metformin inhibited the tumor-derived soluble factor-reduced binding of PD-1 to E3 ligases and PD-1 polyubiquitylation, resulting in PD-1 protein downregulation in an AMPK activation-dependent manner. These inhibitory effects of metformin on both PD-L1 and PD-1 expression ameliorated cancer-reduced cytotoxic activity of immune cells in vitro and decreased tumor immune evasion and growth in vivo. Conclusions: Metformin blocks both PD-L1 and PD-1 within the tumor microenvironment. This study provided a mechanistic insight into the efficacy of metformin in improving immunotherapy in human cancer.

Novel Four-Way Variant Translocation, t(1;9;22;16)(q21;q34;q11.2;q24), in a Patient with Chronic Myeloid Leukemia.

Chronic myeloid leukemia (CML) is characterized by the Philadelphia (Ph) chromosome resulting from the translocation of t(9;22)(q34;q11), producing the BCR::ABL1 fusion gene. Variant Ph chromosome translocations, involving rearrangements in chromosomes other than 9 and 22, occur in 5-10% of CML cases. Herein, we report a unique case of a 36-year-old male with a four-way variant Ph chromosome. Conventional chromosomal analysis performed on bone marrow aspirate samples showed 46, XY, t(1;9;22;16)(q21;q34;q11.2;q24). Nested RT-PCR of the BCR::ABL1 gene revealed a major BCR::ABL rearrangement. The treatment with nilotinib achieved a complete hematologic, cytogenetic, and molecular response after 12 months.

Multifunctional HfAlO thin film: Ferroelectric tunnel junction and resistive random access memory.

This study presents findings indicating that the ferroelectric tunnel junction (FTJ) or resistive random-access memory (RRAM) in one cell can be intentionally selected depending on the application. The HfAlO film annealed at 700 °C shows stable FTJ characteristics and can be converted into RRAM by forming a conductive filament inside the same cell, that is, the process of intentionally forming a conductive filament is the result of defect generation and redistribution, and applying compliance current prior to a hard breakdown event of the dielectric film enables subsequent RRAM operation. The converted RRAM demonstrated good memory performance. Through current-voltage fitting, it was confirmed that the two resistance states of the FTJ and RRAM had different transport mechanisms. In the RRAM, the 1/f noise power of the high-resistance state (HRS) was about ten times higher than that of the low-resistance state (LRS). This is because the noise components increase due to the additional current paths in the HRS. The 1/f noise power according to resistance states in the FTJ was exactly the opposite result from the case of the RRAM. This is because the noise component due to the Poole-Frenkel emission is added to the noise component due to the tunneling current in the LRS. In addition, we confirmed the potentiation and depression characteristics of the two devices and further evaluated the accuracy of pattern recognition through a simulation by considering a dataset from the Modified National Institute of Standards and Technology.

Customized three-dimensional printed ceramic bone grafts for osseous defects: a prospective randomized study.

Ridge resorption can result in insufficient bone volume for implant surgery, necessitating bone substitutes to restore the resorption area. Recent advances in computer-aided design and manufacturing enable the use of alloplastic bone graft materials with customizable compositions or shapes. This randomized study evaluated the clinical effectiveness of a customized three-dimensional (3D) printed alloplastic bone material. Sixty patients requiring guided bone regeneration for implant installation following tooth extraction due to alveolar bone resorption were recruited at two institutions. The participants were randomly allocated to either a group that received 3D-printed patient-customized bone graft material or a group that received conventional block bone graft material. Implant installation with bone harvesting was performed approximately 5 months after bone grafting. Histological and radiological assessments of the harvested bone area were performed. The experimental group had a significantly higher percent bone volume and a smaller tissue surface than the control group. Bone volume, bone surface, bone surface/volume ratio, bone surface density (bone surface/total volume), and bone mineral density did not differ significantly between groups. Patient-customized bone graft materials offer convenience and reduce patient discomfort. The findings suggest 3D-printed patient-customized bone graft materials could be used as an alternative for simpler bone grafting procedures.

Enhancing deep learning classification performance of tongue lesions in imbalanced data: mosaic-based soft labeling with curriculum learning.

BACKGROUND: Oral potentially malignant disorders (OPMDs) are associated with an increased risk of cancer of the oral cavity including the tongue. The early detection of oral cavity cancers and OPMDs is critical for reducing cancer-specific morbidity and mortality. Recently, there have been studies to apply the rapidly advancing technology of deep learning for diagnosing oral cavity cancer and OPMDs. However, several challenging issues such as class imbalance must be resolved to effectively train a deep learning model for medical imaging classification tasks. The aim of this study is to evaluate a new technique of artificial intelligence to improve the classification performance in an imbalanced tongue lesion dataset. METHODS: A total of 1,810 tongue images were used for the classification. The class-imbalanced dataset consisted of 372 instances of cancer, 141 instances of OPMDs, and 1,297 instances of noncancerous lesions. The EfficientNet model was used as the feature extraction model for classification. Mosaic data augmentation, soft labeling, and curriculum learning (CL) were employed to improve the classification performance of the convolutional neural network. RESULTS: Utilizing a mosaic-augmented dataset in conjunction with CL, the final model achieved an accuracy rate of 0.9444, surpassing conventional oversampling and weight balancing methods. The relative precision improvement rate for the minority class OPMD was 21.2%, while the relative [Formula: see text] score improvement rate of OPMD was 4.9%. CONCLUSIONS: The present study demonstrates that the integration of mosaic-based soft labeling and curriculum learning improves the classification performance of tongue lesions compared to previous methods, establishing a foundation for future research on effectively learning from imbalanced data.

Clinical retrospective analysis of peri-implant oral malignancies.

PURPOSE: Complications of implant prostheses have direct correlation with the increased use of implants for dental rehabilitation. In this study, we present cases of peri-implant oral malignancies (PIOM) around dental implants and a retrospective analysis of patients treated for PIOM. METHODS: The retrospective analysis was performed with patients treated for PIOM at the Department of Oral and Maxillofacial Surgery of the Seoul National University Dental Hospital between 2006 and 2014. The patient records were thoroughly screened for previous medical issues, human papilloma virus infections, and other clinical data with a focus on relevant information such as localization, time from implant insertion to the development of the carcinoma, implant type and prosthetic rehabilitation. RESULTS: Twenty-one patients were diagnosed with PIOM. The male-to-female ratio was 1.625. The mean age of the patients was 60.42 ± 9.35 years old. Three patients reported ongoing alcohol/tobacco consumption. Five patients had a history of previous oral cancer surgery or exhibited mucosal lesions. The time from implant placement until carcinoma diagnosis was 49.13 ± 33.63 months on average. Most PIOM patients (95.2%) were diagnosed with SCC. All patients had previously been treated for peri-implantitis. In 85.7% of the patients, prostheses were observed on the opposing teeth where PIOM occurred. CONCLUSION: Based on the review of these cases, it can be deduced that there is a possibility that implant treatment and galvanic currents between prosthesis may constitute an irritant and/or inflammatory cofactor which contributes to the formation and/or development of malignant tumors. Patients at potential risk may benefit from individualized recall intervals and careful evaluations.

Proposition of Adaptive Read Bias: A Solution to Overcome Power and Scaling Limitations in Ferroelectric-Based Neuromorphic System.

Hardware neuromorphic systems are crucial for the energy-efficient processing of massive amounts of data. Among various candidates, hafnium oxide ferroelectric tunnel junctions (FTJs) are highly promising for artificial synaptic devices. However, FTJs exhibit non-ideal characteristics that introduce variations in synaptic weights, presenting a considerable challenge in achieving high-performance neuromorphic systems. The primary objective of this study is to analyze the origin and impact of these variations in neuromorphic systems. The analysis reveals that the major bottleneck in achieving a high-performance neuromorphic system is the dynamic variation, primarily caused by the intrinsic 1/f noise of the device. As the device area is reduced and the read bias (VRead ) is lowered, the intrinsic noise of the FTJs increases, presenting an inherent limitation for implementing area- and power-efficient neuromorphic systems. To overcome this limitation, an adaptive read-biasing (ARB) scheme is proposed that applies a different VRead to each layer of the neuromorphic system. By exploiting the different noise sensitivities of each layer, the ARB method demonstrates significant power savings of 61.3% and a scaling effect of 91.9% compared with conventional biasing methods. These findings contribute significantly to the development of more accurate, efficient, and scalable neuromorphic systems.

Disruption of phosphofructokinase activity and aerobic glycolysis in human bronchial epithelial cells by atmospheric ultrafine particulate matter.

Exposure to ambient ultrafine particulate matter (UPM) causes respiratory disorders; however, the underlying molecular mechanisms remain unclear. In this study, we synthesized simulated UPM (sUPM) with controlled physicochemical properties using the spark-discharge method. Subsequently, we investigated the biological effects of sUPM using BEAS-2B human bronchial epithelial cells (HBECs) and a mouse intratracheal instillation model. High throughput RNA-sequencing and bioinformatics analyses revealed that dysregulation of the glycolytic metabolism is involved in the inhibited proliferation and survival of HBECs by sUPM treatment. Furthermore, signaling pathway and enzymatic analyses showed that the treatment of BEAS-2B cells with sUPM induces the inactivation of extracellular signal-regulated kinase (ERK) and protein kinase B (PKB, also known as AKT), resulting in the downregulation of phosphofructokinase 2 (PFK2) S483 phosphorylation, PFK enzyme activity, and aerobic glycolysis in HBECs in an oxidative stress-independent manner. Additionally, intratracheal instillation of sUPM reduced the phosphorylation of ERK, AKT, and PFK2, decreased proliferation, and increased the apoptosis of bronchial epithelial cells in mice. The findings of this study imply that UPM induces pulmonary toxicity by disrupting aerobic glycolytic metabolism in lung epithelial cells, which can provide novel insights into the toxicity mechanisms of UPM and strategies to prevent their toxic effects.

AMPK-HIF-1α signaling enhances glucose-derived de novo serine biosynthesis to promote glioblastoma growth.

BACKGROUND: Cancer cells undergo cellular adaptation through metabolic reprogramming to sustain survival and rapid growth under various stress conditions. However, how brain tumors modulate their metabolic flexibility in the naturally serine/glycine (S/G)-deficient brain microenvironment remain unknown. METHODS: We used a range of primary/stem-like and established glioblastoma (GBM) cell models in vitro and in vivo. To identify the regulatory mechanisms of S/G deprivation-induced metabolic flexibility, we employed high-throughput RNA-sequencing, transcriptomic analysis, metabolic flux analysis, metabolites analysis, chromatin immunoprecipitation (ChIP), luciferase reporter, nuclear fractionation, cycloheximide-chase, and glucose consumption. The clinical significances were analyzed in the genomic database (GSE4290) and in human GBM specimens. RESULTS: The high-throughput RNA-sequencing and transcriptomic analysis demonstrate that the de novo serine synthesis pathway (SSP) and glycolysis are highly activated in GBM cells under S/G deprivation conditions. Mechanistically, S/G deprivation rapidly induces reactive oxygen species (ROS)-mediated AMP-activated protein kinase (AMPK) activation and AMPK-dependent hypoxia-inducible factor (HIF)-1α stabilization and transactivation. Activated HIF-1α in turn promotes the expression of SSP enzymes phosphoglycerate dehydrogenase (PHGDH), phosphoserine aminotransferase 1 (PSAT1), and phosphoserine phosphatase (PSPH). In addition, the HIF-1α-induced expression of glycolytic genes (GLUT1, GLUT3, HK2, and PFKFB2) promotes glucose uptake, glycolysis, and glycolytic flux to fuel SSP, leading to elevated de novo serine and glycine biosynthesis, NADPH/NADP+ ratio, and the proliferation and survival of GBM cells. Analyses of human GBM specimens reveal that the levels of overexpressed PHGDH, PSAT1, and PSPH are positively correlated with levels of AMPK T172 phosphorylation and HIF-1α expression and the poor prognosis of GBM patients. CONCLUSION: Our findings reveal that metabolic stress-enhanced glucose-derived de novo serine biosynthesis is a critical metabolic feature of GBM cells, and highlight the potential to target SSP for treating human GBM.

Efficient Hybrid Training Method for Neuromorphic Hardware Using Analog Nonvolatile Memory.

Neuromorphic hardware using nonvolatile analog synaptic devices provides promising advantages of reducing energy and time consumption for performing large-scale vector-matrix multiplication (VMM) operations. However, the reported training methods for neuromorphic hardware have appreciably shown reduced accuracy due to the nonideal nature of analog devices, and use conductance tuning protocols that require substantial cost for training. Here, we propose a novel hybrid training method that efficiently trains the neuromorphic hardware using nonvolatile analog memory cells, and experimentally demonstrate the high performance of the method using the fabricated hardware. Our training method does not rely on the conductance tuning protocol to reflect weight updates to analog synaptic devices, which significantly reduces online training costs. When the proposed method is applied, the accuracy of the hardware-based neural network approaches to that of the software-based neural network after only one-epoch training, even if the fabricated synaptic array is trained for only the first synaptic layer. Also, the proposed hybrid training method can be efficiently applied to low-power neuromorphic hardware, including various types of synaptic devices whose weight update characteristics are extremely nonlinear. This successful demonstration of the proposed method in the fabricated hardware shows that neuromorphic hardware using nonvolatile analog memory cells becomes a more promising platform for future artificial intelligence.

Enhancement of Mechanical Properties of Multilayer Ceramic Capacitors through a BaTiO3/polydopamine Cover Layer.

To fabricate multilayer ceramic capacitors (MLCCs) that can withstand external impacts, technologies to achieve excellent adhesion and mechanical strength of the cover layer should be essentially developed. Low adhesion and strength of the cover layer can lead to delamination and cracks in the MLCC, respectively. In this study, we present a method for applying polydopamine (PDA), a mussel-inspired adhesive protein, for as robust cover layer on an MLCC. Barium titanate (BT) particles treated with PDA increase the dispersion stability of the BT/PDA slurry, preventing re-agglomeration of the particles and enhancing the adhesiveness and strength owing to the cohesive properties of PDA. Compared to the BT layer, the adhesion of the BT/PDA layer was significantly enhanced by 217%; consequently, the compression modulus of the BT/PDA cover layer increased by 29.4%. After firing, the N-doped graphitic PDA played an important role in producing an MLCC cover layer with increased hardness and toughness. Furthermore, the N-doped graphitic PDA with a hydrophobic surface forms tortuous moisture paths in the cover layer, preventing the degradation of insulation resistance of the MLCC.

Energy Efficient Artificial Olfactory System with Integrated Sensing and Computing Capabilities for Food Spoilage Detection.

Artificial olfactory systems (AOSs) that mimic biological olfactory systems are of great interest. However, most existing AOSs suffer from high energy consumption levels and latency issues due to data conversion and transmission. In this work, an energy- and area-efficient AOS based on near-sensor computing is proposed. The AOS efficiently integrates an array of sensing units (merged field effect transistor (FET)-type gas sensors and amplifier circuits) and an AND-type nonvolatile memory (NVM) array. The signals of the sensing units are directly connected to the NVM array and are computed in memory, and the meaningful linear combinations of signals are output as bit line currents. The AOS is designed to detect food spoilage by employing thin zinc oxide films as gas-sensing materials, and it exhibits low detection limits for H2 S and NH3 gases (0.01 ppm), which are high-protein food spoilage markers. As a proof of concept, monitoring the entire spoilage process of chicken tenderloin is demonstrated. The system can continuously track freshness scores and food conditions throughout the spoilage process. The proposed AOS platform is applicable to various applications due to its ability to change the sensing temperature and programmable NVM cells.