Development of a Fit-For-Purpose Multi-Marker Panel for Early Diagnosis of Pancreatic Ductal Adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) suffers from a lack of an effective diagnostic method, which hampers improvement in patient survival. Carbohydrate antigen 19-9 (CA19-9) is the only FDA-approved blood biomarker for PDAC, yet its clinical utility is limited due to suboptimal performance. Liquid chromatography-mass spectrometry (LC-MS) has emerged as a burgeoning technology in clinical proteomics for the discovery, verification, and validation of novel biomarkers. A plethora of protein biomarker candidates for PDAC have been identified using LC-MS, yet few has successfully transitioned into clinical practice. This translational standstill is owed partly to insufficient considerations of practical needs and perspectives of clinical implementation during biomarker development pipelines, such as demonstrating the analytical robustness of proposed biomarkers which is critical for transitioning from research-grade to clinical-grade assays. Moreover, the throughput and cost-effectiveness of proposed assays ought to be considered concomitantly from the early phases of the biomarker pipelines for enhancing widespread adoption in clinical settings. Here, we developed a fit-for-purpose multi-marker panel for PDAC diagnosis by consolidating analytically robust biomarkers as well as employing a relatively simple LC-MS protocol. In the discovery phase, we comprehensively surveyed putative PDAC biomarkers from both in-house data and prior studies. In the verification phase, we developed a multiple-reaction monitoring (MRM)-MS-based proteomic assay using surrogate peptides that passed stringent analytical validation tests. We adopted a high-throughput protocol including a short gradient (<10 min) and simple sample preparation (no depletion or enrichment steps). Additionally, we developed our assay using serum samples, which are usually the preferred biospecimen in clinical settings. We developed predictive models based on our final panel of 12 protein biomarkers combined with CA19-9, which showed improved diagnostic performance compared to using CA19-9 alone in discriminating PDAC from non-PDAC controls including healthy individuals and patients with benign pancreatic diseases. A large-scale clinical validation is underway to demonstrate the clinical validity of our novel panel.

Network of Inorganic Nanocrystals Can Swell: Study of Swelling-Induced Surface Instability.

A unique organic-inorganic hybrid network composed of inorganic nanocores (ranging from semiconductors to metallic ones) interconnected through organic molecules can be produced by crosslinking the organic ligands of colloidal inorganic nanocrystals in assemblies. This work reports that this network, which is conventionally considered an inorganic film, can swell when exposed to a solvent because of the interaction between the solvent and the organic linkage within the network. Intriguingly, this work discovers that drying the solvent of the swollen organic-inorganic hybrid network can significantly affect the morphology owing to the swelling-induced compress stress, which is widely observed in various organic network systems. This work studies the surface instability of crosslinked organic-inorganic hybrid networks swollen by various organic solvents, which led to buckling delamination. Specifically, this work investigates the effects of the i) solvent-network interaction, ii) crosslinking density of the network, and iii) thickness of the film on the delamination behavior of the crosslinked network.

Co-assembly-Directed Enhancement of the Thermochromic Reversibility and Solvatochromic Selectivity of Supramolecular Polydiacetylene.

The construction of functional materials via the co-assembly of multimolecular systems has recently emerged as a fascinating topic. The co-assembled multicomponent could promote the evolution of supramolecular assemblies into a high-order nanoarchitecture with improved functional properties. We report the successful preparation of a dual-functional polydiacetylene (MCPDA-Tz-CA) having thermochromic and solvatochromic properties via facile co-assembly of MCDA-Tz and cyanuric acid (MCDA-Tz-CA) followed by ultraviolet-induced polymerization. Molecular packing patterns from powder X-ray diffraction and density functional theory calculations of molecular self-assembly processes confirm highly ordered co-assembled lamellar structures. MCPDA-Tz-CA showed excellent reversible thermochromism properties when the temperature was increased from 30 to 150 °C with a reversible blue-to-red color transition that could be detected by the naked eye. Also, MCPDA-Tz-CA displayed selective blue-to-red solvatochromism against dimethylformamide and dimethyl sulfoxide. Detailed investigations revealed that the enhanced thermochromic reversibility and solvatochromic selectivity could be attributed to the hydrogen-bonding interactions and the formation of a network structure in the MCDA-Tz/cyanuric acid co-assembly. Our research opens a promising route for improving the performance of functional materials via noncovalent multicomponent arrangements at the molecular level.

Activity-Based Protein Profiling Reveals Potential Dasatinib Targets in Gastric Cancer.

Dasatinib is a multi-target kinase inhibitor, whose targets include BCR-ABL, SRC family kinases, and various cancer kinases. The elevated SRC activity in gastric cancer (GC) has prompted the need for the therapeutic application of dasatinib in GC. We observed that the efficacy of dasatinib varied with the GC cell lines. The differential effect of dasatinib was not correlated with the basal SRC activity of each cell line. Moreover, the GC cell lines showing the strong antitumor effects of dasatinib were refractory to other SRC inhibitors, i.e., bosutinib and saracatinib, suggesting that unexpected dasatinib's targets could exist. To profile the targets of dasatinib in GC, we performed activity-based protein profiling (ABPP) via mass spectrometry using a desthiobiotin-ATP probe. We identified 29 and 18 kinases as potential targets in dasatinib-sensitive (SNU-216, MKN-1) and -resistant (SNU-484, SNU-601) cell lines, respectively. The protein-protein interaction mapping of the differential drug targets in dasatinib-sensitive and -resistant GC using the STRING database suggested that dasatinib could target cellular energy homeostasis in the drug-sensitive GC. RNAi screening for identified targets indicated p90RSK could be a novel dasatinib target, which is important for maintaining the viability and motility of GC cells. Further functional validation of dasatinib off-target actions will provide more effective therapeutic options for GC.

Highly Ordered Microscale-Pyramidal-Structure-Arrayed Silicon Membranes for Filter Applications.

Microscale-pyramidal-structure-arrayed patterned silicon membranes are manufactured using semiconductor processes and potassium hydroxide (KOH) etching techniques for filter applications. The silicon nitride on silicon on the insulator wafer functions as a masking layer, and the roughness of the silicon (100) plane strongly depends on the etching temperature and KOH concentration. To fabricate the membrane filter, a series of dry and wet etching using 45 wt% KOH solutions at the constant temperature of 70 °C was performed. With the dry and wet etching, micro-pyramidal arrays with 300 µm top and 16-20 µm bottom opening sizes were created. The morphological structures were analyzed using scanning electron microscopy. The manufactured membranes were tested as optical directional filters and particle filters.

Multi-domain vibration dataset with various bearing types under compound machine fault scenarios.

In modern complex mechanical systems, machine faults typically occur in multiple components simultaneously, and the domain of collected sensor data changes continuously due to variations in operating conditions. Deep learning-based fault diagnosis approaches have recently been enhanced to address these real-world industrial challenges. Comprehensive labeled data covering compound fault scenarios and multi-domain conditions are crucial for exploring these issues. However, existing multi-domain datasets focus on a limited range of operating conditions, such as motor rotating speeds and loads. This limits their applicability to real-world industrial scenarios. To bridge this gap, we present a novel multi-domain dataset that incorporates these basic conditions and extends to various bearing types and compound machine faults. The deep groove ball bearing, the cylindrical roller bearing, and the tapered roller bearing were utilized to provide data that reflect diverse mechanical interactions between the shaft and the bearing. Vibration data were collected using a USB digital accelerometer at two sampling rates and six rotating speeds, encompassing three single bearing faults, seven single rotating component faults, and 21 compound faults of the bearing and rotating component. Additionally, the dataset provides spectrograms of vibration data using short-time Fourier transform (STFT) for data-driven analysis with a 2-D input. This dataset encompasses more complex compound fault and domain shift problems than those presented in conventional public vibration datasets, thereby aiding researchers in studying intelligent fault diagnosis methods based on deep learning.

Shuffled ECA-Net for stress detection from multimodal wearable sensor data.

BACKGROUND: Recently, stress has been recognized as a key factor in the emergence of individual and social issues. Numerous attempts have been made to develop sensor-augmented psychological stress detection techniques, although existing methods are often impractical or overly subjective. To overcome these limitations, we acquired a dataset utilizing both wireless wearable multimodal sensors and salivary cortisol tests for supervised learning. We also developed a novel deep neural network (DNN) model that maximizes the benefits of sensor fusion. METHOD: We devised a DNN involving a shuffled efficient channel attention (ECA) module called a shuffled ECA-Net, which achieves advanced feature-level sensor fusion by considering inter-modality relationships. Through an experiment involving salivary cortisol tests on 26 participants, we acquired multiple bio-signals including electrocardiograms, respiratory waveforms, and electrogastrograms in both relaxed and stressed mental states. A training dataset was generated from the obtained data. Using the dataset, our proposed model was optimized and evaluated ten times through five-fold cross-validation, while varying a random seed. RESULTS: Our proposed model achieved acceptable performance in stress detection, showing 0.916 accuracy, 0.917 sensitivity, 0.916 specificity, 0.914 F1-score, and 0.964 area under the receiver operating characteristic curve (AUROC). Furthermore, we demonstrated that combining multiple bio-signals with a shuffled ECA module can more accurately detect psychological stress. CONCLUSIONS: We believe that our proposed model, coupled with the evidence for the viability of multimodal sensor fusion and a shuffled ECA-Net, would significantly contribute to the resolution of stress-related issues.

Patterning Quantum Dots via Photolithography: A Review.

Pixelating patterns of red, green, and blue quantum dots (QDs) is a critical challenge for realizing high-end displays with bright and vivid images for virtual, augmented, and mixed reality. Since QDs must be processed from a solution, their patterning process is completely different from the conventional techniques used in the organic light-emitting diode and liquid crystal display industries. Although innovative QD patterning technologies are being developed, photopatterning based on the light-induced chemical conversion of QD films is considered one of the most promising methods for forming micrometer-scale QD patterns that satisfy the precision and fidelity required for commercialization. Moreover, the practical impact will be significant as it directly exploits mature photolithography technologies and facilities that are widely available in the semiconductor industry. This article reviews recent progress in the effort to form QD patterns via photolithography. The review begins with a general description of the photolithography process. Subsequently, different types of photolithographical methods applicable to QD patterning are introduced, followed by recent achievements using these methods in forming high-resolution QD patterns. The paper also discusses prospects for future research directions.

Electronic transport of lateral PtSi/n/n+-Si Schottky diodes.

We investigated the transport properties of a lateral PtSi/n/n(+)-Si Schottky diode prepared on an n-type silicon-on-insulator (SOI) wafer with a special attention on the bipolar transport and the surface effect. With applying a back-gate bias changing from +18 V to -18 V, the unipolar transport behavior switched over to the bipolar one, where an enhanced surface recombination rate due to a high surface-to-volume ratio produced a current density approximately 3 x 10(3) A/cm2 for 2 V bias through a 40 nm-thick and 18 microm-long nanoribbon. The recombination time was estimated to be approximately 1 micros from independent CV measurements, which is much smaller value than that of a bulk. The local Fermi energy level for electrons at the channel center was monitored by an additional voltage probe during each I(D)-V(D) measurement and it revealed the intricate nature of the bipolar transport manifested by the huge asymmetrical hysteretic behavior on a drain bias cycle which is attributed to the charge storage effect and asymmetrical junction profiles.

Size and surface modification effects on the pH response of Si nanowire field-effect transistors.

We investigated the effects of Si nanowire (SiNW) dimensions and their surface modifications on the pH-dependent electronic transport characteristics of SiNW Electrolyte-insulator-Semiconductor Field-Effect Transistors (EISFETs). The threshold voltages, Vth's, of all devices were extracted from the Id-Vg characteristics with Vg applied to the reference electrode immersed in different pH solutions, and their pH-dependences were analyzed for various devices. We found that our devices produce the systematic pH-dependence of Vth with respect to the SiNW's length and show significant changes in a linear pH region and a pH sensitivity upon the Si surface modifications. Particularly in the case of the APTES-treated surface, the linear variation was observed in the wide region of pH = 2 to approximately 11 with the sensitivity of 54.7 +/- 0.6 mV/pH. Also we compared our data to a theoretical result based on the Gouy-Chapmam-Stern-Graham model and found a reasonable agreement between them.

Highly-dispersive transparency at optical frequencies in planar metamaterials based on two-bright-mode coupling.

Using a planar metamaterial, which consists of two silver strips, we theoretically demonstrate the plasmonic electromagnetically-induced transparency (EIT)-like spectral response at optical frequencies. The two silver strips serve as the bright modes, and are excited strongly by the incident wave. Based on the weak hybridization between the two bright modes, a highly-dispersive plasmonic EIT-like spectral response appears in our scheme. Moreover, the group index is higher than that of another scheme which utilizes the strong coupling between the bright and dark modes.

Identification of Nucleolin as a Novel AEG-1-Interacting Protein in Breast Cancer via Interactome Profiling.

Breast cancer is one of the most common malignant diseases worldwide. Astrocyte elevated gene-1 (AEG-1) is upregulated in breast cancer and regulates breast cancer cell proliferation and invasion. However, the molecular mechanisms by which AEG-1 promotes breast cancer have yet to be fully elucidated. In order to delineate the function of AEG-1 in breast cancer development, we mapped the AEG-1 interactome via affinity purification followed by LC-MS/MS. We identified nucleolin (NCL) as a novel AEG-1 interacting protein, and co-immunoprecipitation experiments validated the interaction between AEG-1 and NCL in breast cancer cells. The silencing of NCL markedly reduced not only migration/invasion, but also the proliferation induced by the ectopic expression of AEG-1. Further, we found that the ectopic expression of AEG-1 induced the tyrosine phosphorylation of c-Met, and NCL knockdown markedly reduced this AEG-1 mediated phosphorylation. Taken together, our report identifies NCL as a novel mediator of the oncogenic function of AEG-1, and suggests that c-Met could be associated with the oncogenic function of the AEG-1-NCL complex in the context of breast cancer.

Phosphatidylserine synthase plays an essential role in glia and affects development, as well as the maintenance of neuronal function.

Phosphatidylserine (PS) is an integral component of eukaryotic cell membranes and organelles. The Drosophila genome contains a single PS synthase (PSS)-encoding gene (Pss) homologous to mammalian PSSs. Flies with Pss loss-of-function alleles show a reduced life span, increased bang sensitivity, locomotor defects, and vacuolated brain, which are the signs associated with neurodegeneration. We observed defective mitochondria in mutant adult brain, as well as elevated production of reactive oxygen species, and an increase in autophagy and apoptotic cell death. Intriguingly, glial-specific knockdown or overexpression of Pss alters synaptogenesis and axonal growth in the larval stage, causes developmental arrest in pupal stages, and neurodegeneration in adults. This is not observed with pan-neuronal up- or down-regulation. These findings suggest that precisely regulated expression of Pss in glia is essential for the development and maintenance of brain function. We propose a mechanism that underlies these neurodegenerative phenotypes triggered by defective PS metabolism.

Attogram mass sensing based on silicon microbeam resonators.

Using doubly-clamped silicon (Si) microbeam resonators, we demonstrate sub-attogram per Hertz (ag/Hz) mass sensitivity, which is extremely high sensitivity achieved by micro-scale MEMS mass sensors. We also characterize unusual buckling phenomena of the resonators. The thin-film based resonator is composed of a Si microbeam surrounded by silicon nitride (SiN) anchors, which significantly improve performance by providing fixation on the microbeam and stabilizing oscillating motion. Here, we introduce two fabrication techniques to further improve the mass sensitivity. First, we minimize surface stress by depositing a sacrificial SiN layer, which prevents damage on the Si microbeam. Second, we modify anchor structure to find optimal design that allows the microbeam to oscillate in quasi-one dimensional mode while achieving high quality factor. Mass loading is conducted by depositing Au/Ti thin films on the local area of the microbeam surface. Using sequential mass loading, we test effects of changing beam dimensions, position of mass loading, and distribution of a metal film on the mass sensitivity. In addition, we demonstrate that microbeams suffer local micro-buckling and global buckling by excessive mass loading, which are induced by two different mechanisms. We also find that the critical buckling length is increased by additional support from the anchors.

Dialogue enabling speech-to-text user assistive agent system for hearing-impaired person.

A novel approach for assisting bidirectional communication between people of normal hearing and hearing-impaired is presented. While the existing hearing-impaired assistive devices such as hearing aids and cochlear implants are vulnerable in extreme noise conditions or post-surgery side effects, the proposed concept is an alternative approach wherein spoken dialogue is achieved by means of employing a robust speech recognition technique which takes into consideration of noisy environmental factors without any attachment into human body. The proposed system is a portable device with an acoustic beamformer for directional noise reduction and capable of performing speech-to-text transcription function, which adopts a keyword spotting method. It is also equipped with an optimized user interface for hearing-impaired people, rendering intuitive and natural device usage with diverse domain contexts. The relevant experimental results confirm that the proposed interface design is feasible for realizing an effective and efficient intelligent agent for hearing-impaired.