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Cellular senescence, a hallmark of aging, is pathogenically linked to the development of aging-related diseases. This study demonstrates that FRMD6, an upstream component of the Hippo/YAP signaling cascade, is a key regulator of senescence. Proteomic analysis revealed that FRMD6 is upregulated in senescent IMR90 fibroblasts under various senescence-inducing conditions. Silencing FRMD6 mitigated the senescence of IMR90 cells, suggesting its requirement in senescence. Conversely, the overexpression of FRMD6 alone induced senescence in cells and in lung tissue, establishing a causal link. The elevated FRMD6 levels correlated well with increased levels of the inhibitory phosphorylated YAP/TAZ. We identified cellular communication network factor 3 (CCN3), a key component of the senescence-associated secretory phenotype regulated by YAP, whose administration attenuated FRMD6-induced senescence in a dose-dependent manner. Mechanistically, FRMD6 interacted with and activated MST kinase, which led to YAP/TAZ inactivation. The expression of FRMD6 was regulated by the p53 and SMAD transcription factors in senescent cells. Accordingly, the expression of FRMD6 was upregulated by TGF-β treatment that activates those transcription factors. In TGF-β-treated IMR90 cells, FRMD6 mainly segregated with p21, a senescence marker, but rarely segregated with α-SMA, a myofibroblast marker, which suggests that FRMD6 has a role in directing cells towards senescence. Similarly, in TGF-β-enriched environments, such as fibroblastic foci (FF) from patients with idiopathic pulmonary fibrosis, FRMD6 co-localized with p16 in FF lining cells, while it was rarely detected in α-SMA-positive myofibroblasts that are abundant in FF. In sum, this study identifies FRMD6 as a novel regulator of senescence and elucidates the contribution of the FRMD6-Hippo/YAP-CCN3 axis to senescence.

Alternative cleavage and polyadenylation within introns (intronic APA) generate shorter mRNA isoforms; however, their physiological significance remains elusive. In this study, we developed a comprehensive workflow to analyze intronic APA profiles using the mammalian target of rapamycin (mTOR)-regulated transcriptome as a model system. Our investigation revealed two contrasting effects within the transcriptome in response to fluctuations in cellular mTOR activity: an increase in intronic APA for a subset of genes and a decrease for another subset of genes. The application of this workflow to RNA-seq data from The Cancer Genome Atlas demonstrated that this dichotomous intronic APA pattern is a consistent feature in transcriptomes across both normal tissues and various cancer types. Notably, our analyses of protein length changes resulting from intronic APA events revealed two distinct phenomena in proteome programming: a loss of functional domains due to significant changes in protein length or minimal alterations in C-terminal protein sequences within unstructured regions. Focusing on conserved intronic APA events across 10 different cancer types highlighted the prevalence of the latter cases in cancer transcriptomes, whereas the former cases were relatively enriched in normal tissue transcriptomes. These observations suggest potential, yet distinct, roles for intronic APA events during pathogenic processes and emphasize the abundance of protein isoforms with similar lengths in the cancer proteome. Furthermore, our investigation into the isoform-specific functions of JMJD6 intronic APA events supported the hypothesis that alterations in unstructured C-terminal protein regions lead to functional differences. Collectively, our findings underscore intronic APA events as a discrete molecular signature present in both normal tissues and cancer transcriptomes, highlighting the contribution of APA to the multifaceted functionality of the cancer proteome.

The monitoring of arterial blood pressure (ABP) in anesthetized patients is crucial for preventing hypotension, which can lead to adverse clinical outcomes. Several efforts have been devoted to develop artificial intelligence-based hypotension prediction indices. However, the use of such indices is limited because they may not provide a compelling interpretation of the association between the predictors and hypotension. Herein, an interpretable deep learning model is developed that forecasts hypotension occurrence 10 min before a given 90-s ABP record. Internal and external validations of the model performance show the area under the receiver operating characteristic curves of 0.9145 and 0.9035, respectively. Furthermore, the hypotension prediction mechanism can be physiologically interpreted using the predictors automatically generated from the proposed model for representing ABP trends. Finally, the applicability of a deep learning model with high accuracy is demonstrated, thus providing an interpretation of the association between ABP trends and hypotension in clinical practice.

Tin–lead (Sn–Pb) perovskite solar cells (PSCs) hold considerable potential for achieving efficiencies near the Shockley–Queisser (S–Q) limit. Notably, the inverted structure stands as the preferred fabrication method for the most efficient Sn–Pb PSCs. In this regard, it is imperative to implement a strategic customization of the hole selective layer to facilitate carrier extraction and refine the quality of perovskite films, which requires effective hole selectivity and favorable interactions with Sn–Pb perovskites. Herein, we propose the development of Co-Self-Assembled Monolayers (Co-SAM) by integrating both [2-(9H-carbazol-9-yl)ethyl]phosphonic acid (2PACz) and glycine at the buried contacts. The one-step deposition process employed in the fabrication of the Co-SAM ensures uniform coverage, resulting in a homogeneous surface potential. This is attributed to the molecular interactions occurring between 2PACz and glycine in the processing solution. Furthermore, the amine (−NH2) and ammonium (−NH3+) groups in glycine effectively passivate Sn4+defects at the buried interface of Sn–Pb perovskite films, even under thermal stress. Consequently, the synergistic buried interface regulation of Co-SAM leads to a power conversion efficiency (PCE) of 23.46%, which outperforms devices modified with 2PACz or glycine alone. The Co-SAM-modified Sn–Pb PSC demonstrates enhanced thermal stability, maintaining 88% of its initial PCE under 65 °C thermal stress for 590 h.

In this work, we reveal the role of non-covalent interactions, which are known to play important roles in supramolecular phenomena, in achieving efficient perovskite surface and grain boundary passivation. By using a series of pseudohalides, we find that trifluoroacetate (TFA−) provides the strongest binding to iodide vacancies by means of non-covalent hydrogen bonding and dispersion interactions. By exploiting additional non-covalent dispersion and hydrophobic interactions in aromatic 3,3-diphenylpropylammonium (DPA+), we present a dual-ion passivation strategy that not only minimizes the non-radiative recombination center and local chemical inhomogeneities but also induces preferentially oriented growth of α-FAPbI3lattice. This leads to an outstanding power conversion efficiency (PCE) of 25.63% with an exceptional open-circuit voltage of 1.191 V in a perovskite solar cell with a small area, while perovskite solar mini modules with aperture areas of 25 and 64 cm2achieved PCE of 22.47% (quasi-steady-state [QSS]-certified 20.50%) and 20.88%, respectively, with outstanding stability under high-humidity conditions.

Inducing strain in the lattice effectively enhances the intrinsic activity of electrocatalysts by shifting the metal’s d-band center and tuning the binding energy of reaction intermediates. NiFe-layered double hydroxides (NiFe LDHs) are promising electrocatalysts for the oxygen evolution reaction (OER) due to their cost-effectiveness and high catalytic activity. The distorted β-NiOOH phase produced by the Jahn–Teller effect under the oxidation polarization is known to exhibit superior catalytic activity, but it eventually transforms to the undistorted γ-NiOOH phase during the OER process. Such a reversible lattice distortion limits the OER activity. In this study, we propose a facile boron tungstate (BWO) anion intercalation method to induce irreversible lattice distortion in NiFe LDHs, leading to significantly enhanced OER activity. Strong interactions with BWO anions induce significant stress on the LDH’s metal-hydroxide slab, leading to an expansion of metal–oxygen bonds and subsequent lattice distortion. In situRaman spectroscopy revealed that lattice-distorted NiFe LDHs (D-NiFe LDHs) stabilize the β-NiOOH phase under the OER conditions. Consequently, D-NiFe LDHs exhibited low OER overpotentials (209 and 276 mV for 10 and 500 mA cm–2, respectively), along with a modest Tafel slope (33.4 mV dec–1). Moreover, D-NiFe LDHs demonstrated excellent stability at 500 mA cm–2for 50 h, indicating that the lattice distortion of the LDHs is irreversible. The intercalation-induced lattice strain reported in this study can provide a general strategy to enhance the activity of electrocatalysts.

Proteases function as pivotal molecular switches, initiating numerous biological events. Notably, potyviral protease, derived from plant viruses, has emerged as a trusted proteolytic switch in synthetic biological circuits. To harness their capabilities, we have developed a single-component photocleavable switch, termed LAUNCHER (Light-Assisted UNcaging switCH for Endoproteolytic Release), by employing a circularly permutated tobacco etch virus protease and a blue-light-gated substrate, which are connected by fine-tuned intermodular linkers. As a single-component system, LAUNCHER exhibits a superior signal-to-noise ratio compared with multi-component systems, enabling precise and user-controllable release of payloads. This characteristic renders LAUNCHER highly suitable for diverse cellular applications, including transgene expression, tailored subcellular translocation and optochemogenetics. Additionally, the plug-and-play integration of LAUNCHER into existing synthetic circuits facilitates the enhancement of circuit performance. The demonstrated efficacy of LAUNCHER in improving existing circuitry underscores its significant potential for expanding its utilization in various applications.

This study proposes a slip prevention algorithm with a load angle controller to prevent the slip phenomenon in dual-rotor PM synchronous motor (DR-PMSM) drives. A DR-PMSM employs inherent magnetic coupling between the inner and outer rotors for power transmission. This structure may lead to slip and desynchronization between the inner and outer rotors at sudden load variations; therefore, a slip prevention algorithm is necessary to enhance its reliability. Conventional passive slip prevention algorithms may induce load angle oscillation around the critical load angle, which will result in desynchronization between the inner and outer rotors. The PI load angle controller proposed in this study can prevent slip and load angle oscillation near the critical angle. The effectiveness of the proposed slip prevention algorithm is verified through mathematical modeling and simulation with MATLAB/Simulink, as well as through an experiment on a horse-power DR-PMSM.

Recently, inverted perovskite solar cells (PeSCs) have witnessed significant advancements; however, their long-term stability remains a challenge because of the oxidation of silver cathodes to form AgI by mobile iodides. To overcome this problem, we propose the integration of an electron-deficient naphthalene diimide-based zwitterion (NDI-ZI) as the cathode interlayer. Compared to the physical ion-blocking layer, it effectively captures ions by forming ionic bonds viaelectrostatic Coulombic interaction to suppress the migration of iodide and Ag ions. The NDI-ZI interlayer also suppresses the shunt paths and modulates the work function of the Ag electrode by forming interface dipoles, thereby enhancing charge extraction. FA0.85Cs0.15PbI3based PeSCs incorporating NDI-ZI exhibited a noticeably high power conversion efficiency of up to 23.3% and outstanding stability, maintaining ∼80% of their initial performance over 1500 h at 85 °C and over 500 h under continuous 1-sun illumination. This study highlights the potential of a zwitterionic cathode interlayer in diverse perovskite optoelectronic devices, leading to their improved efficiency and stability.

In microgrids, energy management systems (EMS) have been considered essential systems to optimize energy scheduling, control and operation for reliable power systems. Conventional EMS researches have been predominantly performed by employing demand-side management and demand response (DR). Nonetheless, multi-action control in EMS is confronted with operational challenges in terms of the profitability and stability. In this paper, energy information systems (EIS), energy storage systems (ESS), energy trading risk management systems (ETRMS), and automatic DR (ADR) are integrated to efficiently manage the profitability and stability of the whole EMS by optimal energy scheduling. The proposed microgrid EMS architecture is optimized by using proximal policy optimization (PPO) algorithm, which has been known to have good performance in terms of learning stability and complexity. A novel performance metric, represented as a burden of load and generation (BoLG), is proposed to evaluate the energy management performance. The BoLG is incorporated into the reward settings for optimizing the management of multi-action controls such as load shifting, energy charging-discharging, and transactions. From the simulation results, it is confirmed that the proposed architecture can improve energy management performance with the proper trade-off between stability and profitability, compared to dynamic programming (DP)-based and double deep Q-network (DDQN)-based operation.

A monitoring technique for detecting changes in the root gap of butt joints during the flux-cored arc welding (FCAW) was proposed. FCAW experiments were conducted for both increasing and decreasing root gap conditions, and current and voltage were measured during the root-pass welding. The measured time series signals were used as input data for training Random Convolution Kernel Transform (ROCKET) algorithm, which consists of a feature extractor with multiple random kernels, and a linear classifier. A univariate model using current and voltage, respectively, and a multivariate model using both were compared, and the multivariate model showed the highest classification accuracy of 96.2%. Moreover, the classification errors were investigated by correlating the geometry of the root bead with the measured signals.

Air quality in China has continuously improved during the Three-Year Action Plan (2018–2020); however, the changes in aerosol composition, properties, and sources in Beijing summer remain poorly understood. Here, we conducted real-time measurements of aerosol composition in five summers from 2018 to 2022 along with WRF-Community Multiscale Air Quality simulations to characterize the changes in aerosol chemistry and the roles of meteorology and emission reductions. Largely different from winter, secondary inorganic aerosol and photochemical-related secondary organic aerosol (SOA) showed significant decreases by 55–67% in summer, and the most decreases occurred in 2021. Comparatively, the decreases in the primary aerosol species and gaseous precursors were comparably small. While decreased atmospheric oxidation capacity as indicated by ozone changes played an important role in changing SOA composition, the large decrease in aerosol liquid water and small increase in particle acidity were critical for nitrate changes by decreasing gas-particle partitioning substantially (∼28%). Analysis of meteorological influences demonstrated clear and similar transitions in aerosol composition and formation mechanisms at a relative humidity of 50–60% in five summers. Model simulations revealed that emission controls played the decisive role in reducing sulfate, primary OA, and anthropogenic SOA during the Three-Year Action Plan, while meteorology affected more nitrate and biogenic SOA.

Highly active, stable, and low-cost oxygen evolution reaction (OER) electrocatalysts are urgently needed for the realization of large-scale industrial hydrogen production via water electrolysis. Layered double hydroxides (LDHs) stand out as one of the most promising nonprecious electrocatalysts worth pursuing. Here, a hierarchical heterogeneous Ni2+Fe3+@Ni2+Fe2+LDH was successfully synthesized via a sequential electrodeposition technique using separate electrolytes containing iron precursors with different valence states (Fe2+, Fe3+). The underlying highly crystalline Ni2+Fe2+LDH nanosheet array provides a large surface for the catalytically more active Ni2+Fe3+LDH overlayer with low crystallinity. The resulting Ni2+Fe3+@Ni2+Fe2+LDH demonstrates excellent OER activity with overpotentials of 218 and 265 mV to reach current densities of 10 and 100 mA cm–2, respectively, as well as good long-term stability for 30 h even at a high current density of 500 mA cm–2. In an overall water splitting, an electrolyzer using an electrocatalyst of Sn4P3/CoP2as a cathode requires only a cell voltage of 1.55 V at 10 mA cm–2. Furthermore, the solar-powered overall water splitting system consisting of our electrolyzer and a perovskite/Si tandem solar cell exhibits a high solar-to-hydrogen conversion efficiency of 15.3%.

Supplemental Digital Content is Available in the Text.This study analyzed the risk factors for pupillary optic capture following flanged intraocular lens fixation in patients with intraocular lens dislocation. The identified risk factors were larger differences in the nasal and temporal scleral tunnel angles and larger horizontal tilt, which surgeons should avoid to prevent this complication.

ABSTRACTParking structures taller than 8 m in height are difficult to design because both fire and seismic resistance must be considered, whereas structures shorter than this threshold are simpler to design and are subject to fewer construction restrictions. Therefore, to optimize the design of these low parking structures, we propose a novel wide, long-span, steel-concrete composite beam that can be applied to reduce their story height. We investigated flexural and shear-bonding performance of the developed composite beams based on experiments, as well as theoretical and analytical research. Seven flexural beams were loaded at two points prior to monotonic bending tests, and four shear bonding beams were tested using compressive loading schemes. The results of the flexural tests indicated that the flexural strength of the wide composite-steel beams increased by approximately 20% as steel thickness increased by 3 mm (from 6 to 9 mm). Shear-bonding tests showed that all specimens without shear connectors exhibited insufficient shear-bonding strength to resist the mechanical bond mechanism; therefore, they should be reinforced with two or more flat bars. As a result, the novel composite beam system can be applied to reduce construction costs and resources by decreasing floor height in systems with long-span beams.

Dopamine (DA) homeostasis influences emotions, neural circuit development, cognition, and the reward system. Dysfunctions in DA regulation can lead to neurological disorders, including depression, developmental disorders, and addiction. DA homeostasis disruption is a primary cause of Parkinson’s Disease (PD). Therefore, understanding the relationship between DA homeostasis and PD progression may clarify the mechanisms for pharmacologically treating PD. This study developed a novel in vitroDA homeostasis platform which consists of three main parts: (1) a microfluidic device for culturing DAergic neurons, (2) an optical detection system for reading DA levels, and (3) an automatic closed-loop control system that establishes when and how much medication to infuse; this uses a microfluidic device that can cultivate DAergic neurons, perfuse solutions, perform in vitroPD modeling, and continuously monitor DA concentrations. The automatically controlled closed-loop control system simultaneously monitors pharmacological PD treatment to support long-term monitoring of DA homeostasis. SH-SY5Y neuroblastoma cells were chosen as DAergic neurons. They were cultivated in the microfluidic device, and real-time cellular DA level measurements successfully achieved long-term monitoring and modulation of DA homeostasis. When applied in combination with multiday cell culture, this advanced system can be used for drug screening and fundamental biological studies.

Enhanced device performance of flexible organic solar cells (FOSCs) was achieved according to the development of organic solar cells (OSCs). OSCs are promising candidates as energy sources for low-power supply systems such as the Internet of Things (IoT) under indoor lighting environments. To apply FOSCs to flexible or wearable applications, they must be mechanically stable. In this study, we fabricated FOSCs with silver nanomesh (AgNM) as the bottom transparent conductive electrode (TCE). Instead of indium tin oxide (ITO), AgNMs were prepared using three pitches of 25, 50, and 100 μm with a square pattern, using a poly(ethylene terephthalate) (PET) substrate. Notably, the device using AgNMs with a pitch of 25 μm exhibited a power conversion efficiency (PCE) of 14.93% under 1 sun illumination and 17.91% under 1000 lux of light-emitting diode (LED) light conditions. Flexible devices using AgNMs maintained over 92% of their initial PCE under 1 sun illumination (PCE decreased to 12.98 from 14.04%) and over 92% when tested under 1000 lux of LED light illumination (PCE decreased to 16.57 from 17.91%) after 1000 instances of bending. These results demonstrate the advantages of using AgNMs as an alternative TCE under both 1 sun and indoor lightning environments and are promising candidates for flexible applications.

Autism spectrum disorder (ASD) is a major neurodevelopmental disorder in which patients present with core symptoms of social communication impairment, restricted interest, and repetitive behaviors. Although various studies have been performed to identify ASD-related mechanisms, ASD pathology is still poorly understood. CNTNAP2genetic variants have been found that represent ASD genetic risk factors, and disruption of Cntnap2expression has been associated with ASD phenotypes in mice. In this study, we performed an integrative multi-omics analysis by combining quantitative proteometabolomic data obtained with Cntnap2knockout (KO) mice with multi-omics data obtained from ASD patients and forebrain organoids to elucidate Cntnap2-dependent molecular networks in ASD. To this end, a mass spectrometry-based proteometabolomic analysis of the medial prefrontal cortex in Cntnap2KO mice led to the identification of Cntnap2-associated molecular features, and these features were assessed in combination with multi-omics data obtained on the prefrontal cortex in ASD patients to identify bona fide ASD cellular processes. Furthermore, a reanalysis of single-cell RNA sequencing data obtained from forebrain organoids derived from patients with CNTNAP2-associated ASD revealed that the aforementioned identified ASD processes were mainly linked to excitatory neurons. On the basis of these data, we constructed Cntnap2-associated ASD network models showing mitochondrial dysfunction, axonal impairment, and synaptic activity. Our results may shed light on the Cntnap2-dependent molecular networks in ASD.

This article proposes a method of automatically classifying videos into human emotional categories by imitating human neural processes, in which emotion-specific electroencephalography (EEG) characteristics are generated by audiovisual stimulation. In the proposed method, sophisticated emotional features are first extracted from EEG signals that are generated while a subject watches a video, using a sample-attention-based deep neural network encoder. Next, the direct mapping relationship between the extracted emotional EEG features and audiovisual features extracted from the contents of the corresponding videos are learned by a deep belief network. For practical application, the EEG features corresponding to the input video are automatically generated based on the machine’s learned ability without measuring human EEG signals and subsequently applied to a segment-attention-based deep neural network decoder for emotion classification of the video. The experimental results demonstrated that the proposed method significantly outperforms the existing methods with an average accuracy of about 95% for classifying four emotional classes of the video. As for automated emotional video classification, our artificial emotional EEG features-based approach obtains competitive performance, comparable to models that directly measure EEG, and can be generalized to various audiovisual data sets.

Magnetic field mapping is tedious; a magnetometer probe collects magnetic field data in a point-by-point manner within a two-dimensional (2-D) or three-dimensional (3-D) space. Magnetometer arrays accelerate this process by replacing point-by-point mapping with plane-by-plane mapping. When mapping a large space, a motorized stage is additionally required; the limitations include power inefficiencies, large footprints, cost, and the absence of real-time data acquisition. Here, we introduce MagMaps, a modular Lego-like approach to Magnetic field mapping that overcomes the limitations described above. MagMaps includes a set of physically identical modules termed “MagBricks” that can be stacked in all three axes (similar to Lego bricks); this covers the region of interest and eliminates the need for a motorized stage. Each MagBrick is an independent enslaved module with a unique address, having a microcontroller that continuously acquires magnetic field data from a magnetometer array. An additional brick termed the “MasterBrick” serves as a bridge between the computer and the MagBricks. The MasterBrick collects magnetic field data from uniquely addressed MagBricks and communicates them to a computer, where they are sorted and displayed in real time. This modular Lego-like approach and the use of only off-the-shelf electronic components allow MagMaps to offer real-time MagMaps that is portable, power-efficient, and economical for various 2-D or 3-D spaces.

ADNP syndrome, involving the ADNP transcription factor of the SWI/SNF chromatin-remodeling complex, is characterized by developmental delay, intellectual disability, and autism spectrum disorders (ASD). Although Adnp-haploinsufficient (Adnp-HT) mice display various phenotypic deficits, whether these mice display abnormal synaptic functions remain poorly understood. Here, we report synaptic plasticity deficits associated with cognitive inflexibility and CaMKIIα hyperactivity in Adnp-HT mice. These mice show impaired and inflexible contextual learning and memory, additional to social deficits, long after the juvenile-stage decrease of ADNP protein levels to ~10% of the newborn level. The adult Adnp-HT hippocampus shows hyperphosphorylated CaMKIIα and its substrates, including SynGAP1, and excessive long-term potentiation that is normalized by CaMKIIα inhibition. Therefore, Adnphaploinsufficiency in mice leads to cognitive inflexibility involving CaMKIIα hyperphosphorylation and excessive LTP in adults long after its marked expressional decrease in juveniles.

It has been shown that the detection of flat body surfaces (thorax, pelvis) using the three-dimensional optical surface imaging system (3D–OSIS) is less accurate than curved surfaces (head, neck). Here, we evaluated the applicability and technical performance of the 3D–OSIS for prone breast radiotherapy using silicon cup markers. Three silicon cups were attached on the dorsal surface of a female atom phantom. We evaluated the data reproducibility with these marker cups and compared the accuracy with or without their use. For the reproducibility test, we scanned an object 11 times every 15 s with the 3D–OSIS and registered the differences. For the accuracy test, we positioned the phantom on the table and manually moved it in the X, Y, and Z directions to predetermined values. These values were compared to those measured with the 3D–OSIS. This process was repeated 21 times and the differences of the measured values were compared according to the presence or absence of markers. In reproducibility test, the mean variations for the shifts in the lateral, longitudinal, and vertical directions were 0.15 ± 0.22 mm, 0.47 ± 0.13 mm, and 0.34 ± 0.19 mm, respectively. And the mean deviations elicited based on the accuracy test for the manually applied and the measured shifts in the lateral, longitudinal, and vertical directions were (a) 0.23 ± 0.1 mm, 0.044 ± 0.39 mm, and 0.18 ± 0.1 mm with the use of markers, and (b) 0.44 ± 0.33 mm, 0.97 ± 0.55 mm, and 0.63 ± 0.55 mm without the markers, respectively. The use of silicon cup markers yielded highly accurate results in the 3D–OSIS. The use of 3D–OSIS and silicon cups has potential in achieving precise patient setup and in reducing the CBCT frequency in prone breast radiotherapy.

Gastric cancer (GC) is a highly heterogeneous disease regarding histologic features, genotypes, and molecular phenotypes. Here, we investigate extracellular matrix (ECM)-centric analysis, examining its association with histologic subtypes and patient prognosis in human GC. We performed quantitative proteomic analysis of decellularized GC tissues that characterizes tumorous ECM, highlighting proteomic heterogeneity in ECM components. We identified 20 tumor-enriched proteins including four glycoproteins, serpin family H member 1 (SERPINH1), annexin family (ANXA3/4/5/13), S100A family (S100A6/8/9), MMP14, and other matrisome-associated proteins. In addition, histopathological characteristics of GC reveals differential expression in ECM composition, with the poorly cohesive carcinoma-not otherwise specified (PCC-NOS) subtype being distinctly demarcated from other histologic subtypes. Integrating ECM proteomics with single-cell RNA sequencing, we identified crucial molecular markers in the PCC-NOS-specific stroma. PCC-NOS-enriched matrisome proteins and gene expression signatures of adipogenic cancer-associated fibroblasts (CAFadi) are closely linked, both associated with adverse outcomes in GC. Using tumor microarray analysis, we confirmed the CAFadisurface marker, ATP binding cassette subfamily A member 8 (ABCA8), predominantly present in PCC-NOS tumors. Our ECM-focused analysis paves the way for studies to determine their utility as biomarkers for patient stratification, offering valuable insights for linking molecular and histologic features in GC.

In vivomodels of brain pathology are crucial for studying neurological diseases. Here, we present a protocol to induce a pathological condition in a mouse brain area by local injection of neurotoxic stimulus. We describe steps for preparing reagents, stereotaxic injection procedures to induce neurodegeneration in the hippocampus, and preparation of brain sections to examine the induced model. This protocol is useful for studying how local pathology affects other brain areas and neighbor cells and its functional consequences in behavior.

Halide perovskites, promising top-cell materials for efficient Si tandem solar cells, suffer from halide segregation, which results from the halide mixing necessary for achieving band-gap widening. We report pure-iodide wide-band-gap perovskite top cells that are fundamentally free of halide segregation. Cs and dimethylammonium cations were incorporated simultaneously into the A-site of perovskite structure to increase the band gap while maintaining the tolerance factor. However, the incorporation of dual cations resulted in the simultaneous formation of orthorhombic and hexagonal secondary phases rather than forming the pure perovskite phase, owing to the different precipitation kinetics between cations. We demonstrated that this strategy can only be implemented by the phase-controlled nucleation of the Cs-rich composition that governs the desired phase evolution. The pure-iodide perovskite top cell exhibited excellent photo-stability (1% degradation after 1,000 h of continuous operation; ISOS-L-1I, white LED), and its Si tandem exhibited a high conversion efficiency of 29.4% (28.37% certified).

Time-shift is a crucial function of interactive Televisions as like DVR and internet TV broadcasting services. Automatic important event detection allows users utilize time-shift function conveniently. In this paper, we propose a method to extract important events in baseball videos. In the proposed method, we first detect play scenes and audio events separately from video and audio tracks. For robust play scene extraction, we proposed off-line learning model having local adaptation based on ongoing analyzed video. And we implemented the audio event detection with a SVM-based classifier. Final important events are determined by a combination of each audio-visual detection results in real time. We evaluated our method with a baseball database of Korean and Major League games. Experimental results show that the implemented system runs in real time and achieves a remarkable performance of 0.85 recall and 0.97 precision rates (1). Index Terms--Event Detection, Video Summarization, Real Time Video Analysis, Video Indexing.

In this paper we present a low complexity decoding algorithm for Raptor codes which is used for incremental redundancy hybrid ARQ schemes. Encoding and decoding Raptor codes are the processes of making encoding symbols from the source symbols and the recovery of the source symbols from the received encoding symbols transmitted through an erasure channel, respectively. If the received encoding symbols are insufficient to recover the source symbols, additional encoding symbols are delivered and decoded with the previously received encoding symbols. We propose a low complexity decoding algorithm which efficiently combines the previously received encoding symbols and incremental encoding symbols. The proposed algorithm has excellent potential for realizing low power operation and higher throughput transmission due to its highly reduced computational complexity. Index Terms--Raptor codes, Fountain codes, Hybrid-ARQ

Alcohol and cocaine (COC) are commonly co-used drugs that cause addiction and have harmful effects. Their abuse may threaten the health of the abuser and public safety by causing serious accidents or crimes. The recidivism rate of drug-related crimes closely correlates with alcoholism. Several incidences of alcohol consumption in combination with drug abuse have been reported. Here, liquid chromatography tandem mass spectrometric method was developed to simultaneously analyze ethyl glucuronide (EtG), a metabolite of ethanol; COC; cocaethylene (CE), an alcohol-derived metabolite of COC; and benzoylecgonine (BZE), a major metabolite of COC, to determine the concurrent use of alcohol with COC. For pre-treatment, ultracentrifugation (5 min, 50,000 g) and mixed-mode anion exchange solid-phase extraction were used to increase the recovery of target compounds and minimize the matrix effect of hair. The lower limits of quantification were: 7 pg/mg (EtG), 2 pg/mg (COC), 10 pg/mg (CE), and 1 pg/mg (BZE). The correlation coefficient (r) of the calibration curve within the quantified range of target compounds was ≥ 0.9978. The intra- and inter-day accuracies were − 6.1–9.7% and − 9.3–8.3%, and intra- and inter-day precisions were 0.5–10.3% and 0.6–14.4%, respectively. The recovery, matrix effect, process efficiency, and autosampler stability were 89.2–104.8%, 81.6–105.4%, 81.5–107.1%, and 96.6–109.7%, respectively. The novel analytical method was validated with hair samples from individuals suspected of alcohol and COC use, and the method could distinguish between independent and concurrent use. Based on the findings, the analytical approach developed in this study is anticipated to be valuable in drug and alcohol dependence tests that require the simultaneous detection of alcohol and COC abuse.

Background: Recent advances in high-resolution mass spectrometry have now enabled the study of proteomes at the single-cell level, offering the potential to unveil novel aspects of cellular processes. Remarkably, there has been no prior attempt to investigate single-plant cell proteomes. In this study, we aimed to explore the feasibility of conducting a proteomic analysis on individual protoplasts. Findings: As a result, our analysis identified 978 proteins from the 180 protoplasts, aligning with well-known biological processes in plant leaves, such as photosynthetic electron transport in photosystem II. Employing the SCP package in the SCoPE2 workflow revealed a notable batch effect and extensive missing values in the data. Following correction, we observed the heterogeneity in single-protoplast proteome expression. Comparing the results of single-protoplast proteomics with those of bulk leaf proteomics, we noted that only a small fraction of bulk data was detected in the single-protoplast proteomics data, highlighting a technical limitation of the current single-cell proteomics method. Conclusions: In summary, we demonstrated the feasibility of conducting a single-protoplast proteomic experiment, revealing heterogeneity in plant cellular proteome expression. This underscores the importance of analyzing a substantial number of plant cells to discern statistically significant changes in plant cell proteomes upon perturbation such as abscisic acid treatment in future studies. We anticipate that our study will contribute to advancing single-protoplast proteomics in the near future.

This paper presents a video retrieval system (VRS) for Interactive-Television as like internet protocol television (IPTV). A video bookmark initiated by users is performed based on snippets of the background soundtrack corresponding to the ongoing program. Our VRS has two special aspects compared with previous bookmark systems. First, we adopt the robust audio fingerprint feature of long-term logarithmic modified DCT modulation coefficients (LMDCT-MC) for audio indexing and retrieval. Second, we propose and apply a two-stage search (TSS) algorithm for fast searching. In the first stage of TSS, candidate video segments are roughly determined with audio index bit vectors (IBV) and then the optimal video clip is obtained by fingerprint bit vectors (FBV). We evaluate the proposed system with a database of 100 TV programs including news, panel discussions, music shows, advertisements, and dramas. The experimental results show that our VRS achieve fast search, robustness to noise and high precision of retrieval. A search accuracy of 99.67% was accomplished. Index Terms--IPTV, soundtrack identification, bookmarking, long-term dynamic audio fingerprint feature, video shot changes.

Photoacoustic microscopy (PAM) embedded with a 532 nm pulse laser is widely used to visualize the microvascular structures in both small animals and humans in vivo. An opto-ultrasound combiner (OUC) is often utilized in high-speed PAM to confocally align the optical and acoustic beams to improve the system's sensitivity. However, acoustic impedance mismatch in the OUC results in little improvement in the sensitivity. Alternatively, a ring-shaped ultrasound transducer (RUT) can also accomplish the confocal configuration. Here, we compare the performance of OUC and RUT modules through ultrasound pulse-echo tests and PA imaging experiments. The signal-to-noise ratios (SNRs) of the RUT-based system were 15 dB, 12 dB, and 7 dB higher when compared to the OUC-based system for ultrasound pulse-echo test, PA phantom imaging test, and PA in-vivo imaging test, respectively. In addition, the RUT-based system could image the microvascular structures of small parts of a mouse body in a few seconds with minimal loss in SNR. Thus, with increased sensitivity, improved image details, and fast image acquisition, we believe the RUT-based systems could play a significant role in the design of future fast-PAM systems.

An iridium(III)-catalyzed regioselective acylmethylation of the cage B(4)–H bond in o-carborane acids with sulfoxonium ylides is demonstrated through B(4)–H activation in ethanol under very mild conditions, affording a number of B(4)-acylmethylated o-carboranes. Additionally, the selective sequential B(4)- and B(6)-acylmethylation reactions finally gave B(3,5)-diacylmethylated o-carboranes in one pot.

In this paper, performance of LMDS (local multi-point distribution service) system with parallel concatenated convolutional coding (Pace) is analyzed and simulated. The channel of a LMDS system is modeled as a Rician fading channel with strong Rician factor because it is generally accepted that there always exists a line-of-sight (LOS) path between base station and subscriber units. The performance is evaluated in terms of codeword error probability. From the simulation results, it is confirmed that the performance is significantly improved by employing the PCCC. The results in the paper can be applied to radio modern design of a LMDS system.

In this paper, the performance of OFDM/CDMA system with turbo coding is analyzed and simulated in a multipath fading channel. Bit error probability is derived for a frequency-selective Rayleigh fading channel. In OFDM/CDMA system, an OFDM and a CDMA techniques are combined to exploit the advantages of both techniques. For decoding of turbo code, MAP decoding algorithm is employed. And, implementation issues are discussed for an OFDM, a CDMA system, and a turbo decoding procedure. From the simulation results, it is demonstrated that turbo coding offers considerable coding gain with reasonable encoding/decoding complexity. Also, it is shown that the BER performance is substantially improved by increasing the interleaver length for a fixed code rate and the increasing number of iterations used in the decoding process. The results in the paper can be applied to the design of OFDM-based CDMA system.

Sentinel lymph node biopsy with an indocyanine green-based near-infrared fluorescence imaging system avoids the shortcomings of using a radioisotope or a combination of a blue dye and a radioactive tracer. To improve surgical precision, recent research has provided a depth profile of the sentinel lymph node by fusing fluorescence and ultrasound imaging. Here, we present a combined near-infrared fluorescence and ultrasound imaging system based on a transparent ultrasound transducer. The transparent ultrasound transducer enables seamless coaxial alignment of the fluorescence and ultrasound beam paths, allowing bi-modal observation of a single region of interest. Further, we demonstrate that the sentinel lymph node of mice injected with indocyanine green can be successfully localized and dissected based on information from the bi-modal imaging system.

Cell therapy refers to a treatment that involves the delivery of cells or cellular material by means of injection, grafting, or implantation in order to replace damaged tissue and restore its function, or to aid the body in fighting disease. However, limitations include poor targeting delivery and low therapeutic efficacy due to low cell survival. Hence, novel approaches are required to increase cell delivery efficiency and enhance therapeutic efficacy viaselective cell differentiation at target areas. Here, we present a stamping magnetoelectric microscale biorobot (SMMB) consisting of neuron-like cell spheroids loaded with magnetoelectric nanoparticles. The SMMB enables not only effective targeted delivery of cells to multiple target areas (viaminimally invasive stamping employing magnetic actuation) but also facilitates selective neuronal differentiation viamagnetoelectric (ME) stimulation. This ensures rapid colonization and enhances efficacy. SMMBs were fabricated using SH-SY5Y cells. Magnetoelectric nanoparticles for ME stimulation responded to an alternating magnetic field that ensured targeted cell differentiation. Multi-target cell therapy facilitated the targeted delivery and selective differentiation of SH-SY5Y cells to multiple regions using a single SMMB with rotating and alternating magnetic fields for delivery and ME stimulation. This promising tool may overcome the limitations of existing cell therapy for neurodegenerative diseases.

This study is to assess the clinical use of commercial PerFRACTION™ for patient-specific quality assurance of volumetric-modulated arc therapy. Forty-six pretreatment verification plans for patients treated using a TrueBeam STx linear accelerator for lesions in various treatment sites such as brain, head and neck (H&N), prostate, and lung were included in this study. All pretreatment verification plans were generated using the Eclipse treatment planning system (TPS). Dose distributions obtained from electronic portal imaging device (EPID), ArcCHECK™, and two-dimensional (2D)/three-dimensional (3D) PerFRACTION™ were then compared with the dose distribution calculated from the Eclipse TPS. In addition, the correlation between the plan complexity (the modulation complexity score and the leaf travel modulation complexity score) and the gamma passing rates (GPRs) of each quality assurance (QA) system was evaluated by calculating Spearman’s rank correlation coefficient (rs) with the corresponding p-values. The gamma passing rates of 46 patients analyzed with the 2D/3D PerFRACTION™ using the 2%/2 mm and 3%/3 mm criteria showed almost similar trends to those analyzed with the Portal dose imaging prediction (PDIP) and ArcCHECK™ except for those analyzed with ArcCHECK™ using the 2%/2 mm criterion. Most of weak or moderate correlations between GPRs and plan complexity were observed for all QA systems. The trend of mean rsbetween GPRs using PDIP and 2D/3D PerFRACTION™ for both criteria and plan complexity indices as in the GPRs analysis was significantly similar for brain, prostate, and lung cases with lower complexity compared to H&N case. Furthermore, the trend of mean rsfor 2D/3D PerFRACTION™ for H&N case with high complexity was similar to that of ArcCHECK™ and slightly lower correlation was observed than that of PDIP. This work showed that the performance of 2D/3D PerFRACTION™ for pretreatment patient-specific QA was almost comparable to that of PDIP, although there was small difference from ArcCHECK™ for some cases. Thus, we found that the PerFRACTION™ is a suitable QA system for pretreatment patient-specific QA in a variety of treatment sites.

Purpose: This retrospective study aimed to evaluate the baseline characteristics of asymptomatic patients with coronavirus disease 2019 at admission and to follow-up their clinical manifestations and radiological findings during hospitalization. Methods: Patients with coronavirus disease 2019 who were asymptomatic at admission were divided into two groups—those with no symptoms until discharge (group A) and those who developed symptoms after admission (group B). Patients who could not express their own symptoms were excluded. Results: Overall, 127 patients were enrolled in the study, of whom 19 and 108 were assigned to groups A and B, respectively. The mean age and median C-reactive protein level were higher in group B than in group A. All patients in group A and one-third of patients in group B had normal initial chest radiographs; 15.8% and 48.1% of patients in groups A and B, respectively, had pneumonia during hospitalization. One patient in group B, whose condition was not severe at the time of admission, deteriorated due to aggravated pneumonia and was transferred to a tertiary hospital. Conclusion: We summarize the clinical characteristics during hospitalization of patients with coronavirus disease 2019 who were purely asymptomatic at the time of admission. The majority of asymptomatic patients with coronavirus disease 2019 were discharged without significant events during hospitalization. However, it may be difficult to predict subsequent events from initial chest radiographs or oxygen saturation at admission.

As the efficiency of perovskite/Si tandem solar cells (PVSK/Si TSCs) surpasses the practical limit of single-junction cells, consideration of device stability is critical for real-world application. Demonstrated recently, potential-induced degradation (PID) and partial recovery can occur in PVSK/Si TSCs depending on the external potential, indicating that the hitherto underresearched PID issues must be addressed for successful commercialization.

Glycoproteomics is a powerful yet analytically challenging research tool. Software packages aiding the interpretation of complex glycopeptide tandem mass spectra have appeared, but their relative performance remains untested. Conducted through the HUPO Human Glycoproteomics Initiative, this community study, comprising both developers and users of glycoproteomics software, evaluates solutions for system-wide glycopeptide analysis. The same mass spectrometry based glycoproteomics datasets from human serum were shared with participants and the relative team performance for N -and O-glycopeptide data analysis was comprehensively established by orthogonal performance tests. Although the results were variable, several high-performance glycoproteomics informatics strategies were identified. Deep analysis of the data revealed key performance-associated search parameters and led to recommendations for improved ‘high-coverage’ and ‘high-accuracy’ glycoproteomics search solutions. This study concludes that diverse software packages for comprehensive glycopeptide data analysis exist, points to several high-performance search strategies and specifies key variables that will guide future software developments and assist informatics decision-making in glycoproteomics.

In this study, we propose a novel method of pKaprediction in a diverse set of acids, which combines density functional theory (DFT) method with machine learning (ML) methods. First, the DFT method with B3LYP/6-31++G**/SM8 is used to predict pKa, yielding a mean absolute error of 1.85 pKaunits. Subsequently, such pKavalues predicted from the DFT method are employed as one of 10 molecular descriptors for developing ML models trained on experimental data. Kernel Ridge Regression (KRR), Gaussian Process Regression, and Artificial Neural Network are optimized using three Pipelines: Pipeline 1involving only hyperparameter optimization (HPO), Pipeline 2involving HPO followed by a relative contribution analysis (RCA) and recursive feature elimination (RFE), and Pipeline 3involving HPO followed by RCA and RFE on an expanded set of composite features. Finally, it is demonstrated that KRR with Pipeline 3yields optimal pKaprediction at an MAE of 0.60 log units. This algorithm was then utilized to predict the pKaof 37 novel acids. The two most important features were determined to be the number of hydrogen atoms in the molecule and the degree of oxidation of the acid. The predicted pKavalues were documented for future reference.

The Coronary Artery Disease Reporting and Data System score has incremental prognostic value compared with coronary artery calcium score in predicting future major adverse cardiovascular events in patients presenting to the emergency department with chest pain.

Two kinds of dumbbell-shaped acceptor–donor–acceptor (A–D–A)-type triad single-component (SC) photovoltaic molecules based on a benzodithiophene-rhodanine (BDTRh) core and [6,6]-phenyl-C61butyric acid (PC61BA) termini, BDTRh–C2–PC61BA and BDTRh–C10–PC61BA, were synthesized by modulating the alkyl (C2 and C10) spacer lengths. Both SC photovoltaic structures had similar UV–vis spectra in solution, but BDTRh–C10–PC61BA showed a significantly higher absorption coefficient as a thin film. In films, a more facile intermolecular photo-induced charge transfer was observed for BDTRh–C10–PC61BA in the broad-band transient absorption measurements. BDTRh–C10–PC61BA also exhibited a higher hole mobility (by 25 times) and less bimolecular recombination than BDTRh–C2–PC61BA. By plotting the normalized external quantum efficiency data, a higher charge-transfer state was measured for BDTRh–C10–PC61BA, reducing its voltage loss. A higher power conversion efficiency of ∼2% was obtained for BDTRh–C10–PC61BA, showing higher open-circuit voltage, short-circuit current density, and fill factor than those of BDTRh–C2–PC61BA devices. The different carrier dynamics, voltage loss, and optical and photoelectrical characteristics depending on the spacer length were interpreted in terms of the film morphology. The longer decyl spacer in BDTRh–C10–PC61BA afforded a significantly enhanced intermolecular ordering of the p-type core compared to BDTRh–C2–PC61BA, suggesting that the alkyl spacer length plays a critical role in controlling the intermolecular packing interaction.

Organic–inorganic hybrid perovskites hold great potential for various optoelectronic devices with exceptional properties. Although the direct generation of circularly polarized emission from perovskites would enable various compact devices, achieving a large degree of circular polarization (DCP) at room temperature still remains challenging. Herein, we demonstrate that DCP can be strongly enhanced at the narrow mode position of chiral Fano resonances. In our design, a perovskite film is spin-coated on a symmetry-broken structure with a relatively large feature size. A large DCP of more than 0.5 is achieved at room temperature without the direct patterning of the perovskite layer. Reciprocity calculation reveals that chiral field enhancement enables the emission of opposite helicity to couple into counter-propagating slab modes and leads to a large DCP. Our design is very general and scalable. Our work may lead to circularly polarized light sources based on various perovskite materials.