Machine Learning Reveals Serum Glycopatterns as Potential Biomarkers for the Diagnosis of Nonalcoholic Fatty Liver Disease (NAFLD).

Nonalcoholic fatty liver disease (NAFLD) has emerged as the predominant chronic liver condition globally, and underdiagnosis is common, particularly in mild cases, attributed to the asymptomatic nature and traditional ultrasonography's limited sensitivity to detect early-stage steatosis. Consequently, patients may experience progressive liver pathology. The objective of this research is to ascertain the efficacy of serum glycan glycopatterns as a potential diagnostic biomarker, with a particular focus on the disease's early stages. We collected a total of 170 serum samples from volunteers with mild-NAFLD (Mild), severe-NAFLD (Severe), and non-NAFLD (None). Examination via lectin microarrays has uncovered pronounced disparities in serum glycopatterns identified by 19 distinct lectins. Following this, we employed four distinct machine learning algorithms to categorize the None, Mild, and Severe groups, drawing on the alterations observed in serum glycopatterns. The gradient boosting decision tree (GBDT) algorithm outperformed other models in diagnostic accuracy within the validation set, achieving an accuracy rate of 95% in differentiating the None group from the Mild group. Our research indicates that employing lectin microarrays to identify alterations in serum glycopatterns, when integrated with advanced machine learning algorithms, could constitute a promising approach for the diagnosis of NAFLD, with a special emphasis on its early detection.

Ultra-low-field magnetization transfer imaging at 0.055T with low specific absorption rate.

PURPOSE: To demonstrate magnetization transfer (MT) effects with low specific absorption rate (SAR) on ultra-low-field (ULF) MRI. METHODS: MT imaging was implemented by using sinc-modulated RF pulse train (SPT) modules to provide bilateral off-resonance irradiation. They were incorporated into 3D gradient echo (GRE) and fast spin echo (FSE) protocols on a shielding-free 0.055T head scanner. MT effects were first verified using phantoms. Brain MT imaging was conducted in both healthy subjects and patients. RESULTS: MT effects were clearly observed in phantoms using six SPT modules with total flip angle 3600° at central primary saturation bands of approximate offset ±786 Hz, even in the presence of large relative B0 inhomogeneity. For brain, strong MT effects were observed in gray matter, white matter, and muscle in 3D GRE and FSE imaging using six and sixteen SPT modules with total flip angle 3600° and 9600°, respectively. Fat, cerebrospinal fluid, and blood exhibited relatively weak MT effects. MT preparation enhanced tissue contrasts in T2-weighted and FLAIR-like images, and improved brain lesion delineation. The estimated MT SAR was 0.0024 and 0.0008 W/kg for two protocols, respectively, which is far below the US Food and Drug Administration (FDA) limit of 3.0 W/kg. CONCLUSION: Robust MT effects can be readily obtained at ULF with extremely low SAR, despite poor relative B0 homogeneity in ppm. This unique advantage enables flexible MT pulse design and implementation on low-cost ULF MRI platforms to achieve strong MT effects in brain and beyond, potentially augmenting their clinical utility in the future.

Nitrogen-mediated volatilisation of defensive metabolites in tomato confers resistance to herbivores.

Plants synthesise a vast array of volatile organic compounds (VOCs), which serve as chemical defence and communication agents in their interactions with insect herbivores. Although nitrogen (N) is a critical resource in the production of plant metabolites, its regulatory effects on defensive VOCs remain largely unknown. Here, we investigated the effect of N content in tomato (Solanum lycopersicum) on the tobacco cutworm (Spodoptera litura), a notorious agricultural pest, using biochemical and molecular experiments in combination with insect behavioural and performance analyses. We observed that on tomato leaves with different N contents, S. litura showed distinct feeding preference and growth and developmental performance. Particularly, metabolomics profiling revealed that limited N availability conferred resistance upon tomato plants to S. litura is likely associated with the biosynthesis and emission of the volatile metabolite α-humulene as a repellent. Moreover, exogenous application of α-humulene on tomato leaves elicited a significant repellent response against herbivores. Thus, our findings unravel the key factors involved in N-mediated plant defence against insect herbivores and pave the way for innovation of N management to improve the plant defence responses to facilitate pest control strategies within agroecosystems.

Ultra-low-field magnetic resonance angiography at 0.05 T: A preliminary study.

We aim to explore the feasibility of head and neck time-of-flight (TOF) magnetic resonance angiography (MRA) at ultra-low-field (ULF). TOF MRA was conducted on a highly simplified 0.05 T MRI scanner with no radiofrequency (RF) and magnetic shielding. A flow-compensated three-dimensional (3D) gradient echo (GRE) sequence with a tilt-optimized nonsaturated excitation RF pulse, and a flow-compensated multislice two-dimensional (2D) GRE sequence, were implemented for cerebral artery and vein imaging, respectively. For carotid artery and jugular vein imaging, flow-compensated 2D GRE sequences were utilized with venous and arterial blood presaturation, respectively. MRA was performed on young healthy subjects. Vessel-to-background contrast was experimentally observed with strong blood inflow effect and background tissue suppression. The large primary cerebral arteries and veins, carotid arteries, jugular veins, and artery bifurcations could be identified in both raw GRE images and maximum intensity projections. The primary brain and neck arteries were found to be reproducible among multiple examination sessions. These preliminary experimental results demonstrated the possibility of artery TOF MRA on low-cost 0.05 T scanners for the first time, despite the extremely low MR signal. We expect to improve the quality of ULF TOF MRA in the near future through sequence development and optimization, ongoing advances in ULF hardware and image formation, and the use of vascular T1 contrast agents.

Modulation of Intermolecular Interactions in Organic Emitters for Highly Efficient Organic Light-Emitting Diodes.

The adverse aggregated-caused quenching (ACQ) problem of most electroluminescent materials existing in highly doped thin films is one of the key factors impeding the commercialization of high-efficiency organic light-emitting diodes (OLEDs) panel. Whereas, by delicately constructing and modulating moderate intermolecular interactions, some aggregates have been demonstrated to present distinct luminescent properties such as tunable emission spectra, improved photoluminescence quantum yields, different emission mechanism and enhanced horizontal transition dipole ratio (Θ) of emitting layer, providing feasible solution for ACQ problem. The luminescence from newly generated emissive state in aggregates is different from the traditional "isolated" molecules in organic electronics and will possess novel properties and applications. Herein, we summarize the different types of intermolecular interactions within emitter aggregates exhibiting distinct luminescent mechanisms, as well as their effects on photoluminescent and electroluminescent properties, offering reliable reference for the advancement of highly efficient OLEDs utilizing aggregated emitters.

Operational Deflection Shape Measurements on Bladed Disks with Continuous Scanning Laser Doppler Vibrometry.

The continuous scanning laser Doppler vibrometry (CSLDV) technique is usually used to evaluate the vibration operational deflection shapes (ODSs) of structures with continuous surfaces. In this paper, an extended CSLDV is demonstrated to measure the non-continuous surface of the bladed disk and to obtain the ODS efficiently. For a bladed disk, the blades are uniformly distributed on a given disk. Although the ODS of each blade can be derived from its response data along the scanning path with CSLDV, the relative vibration direction between different blades cannot be determined from those data. Therefore, it is difficult to reconstruct the complete vibration mode of the whole blade disk. In order to measure the complete ODS of the bladed disk, a method based on ODS frequency response functions (ODS FRFs) has been proposed. While the ODS of each blade is measured by designing the suitable scanning paths in CSLDV, an additional response signal is obtained at a fixed point as the reference signal to identify the relative vibration phase between the blade and the blade of the bladed disk. Finally, a measurement is performed with a simple bladed disk and the results demonstrate the feasibility and effectiveness of the proposed extended CSLDV method.

In Situ Transmission Electron Microscopy Investigation on Oriented Attachment of Nanodiamonds.

Oriented attachment (OA) plays an important role in the assembly of nanoparticles and the regulation of their size and morphology, which is expected to be an effective means to modulate the properties of nanodiamonds (NDs). However, there remains a dearth of comprehensive investigation into the OA mechanism of NDs. Using in situ transmission electron microscopy, we conducted atomic-resolution investigation on the OA events of ND pairs under electron beam irradiation. The occurrence of an OA event is contingent upon the alignment between two ND surfaces, and the coalesced particles undergo recrystallization to form spherical shapes. Both experimental observations and molecular dynamics (MD) simulations reveal that ND pairs exhibit a preference for coalescing along the {111} surfaces. Additionally, MD simulations indicate that kinetic factors, such as contact surface area and contact angle, also influence the coalescence process.

Regional Functionalization Molecular Design Strategy: A Key to Enhancing the Efficiency of Multi-Resonance OLEDs.

Herein, we propose a regional functionalization molecular design strategy that enables independent control of distinct pivotal parameters through distinct segments of the molecule. Three novel blue emitters A-BN, DA-BN, and A-DBN, have been successfully synthesized by integrating highly rigid and three-dimensional adamantane-containing spirofluorene units into the MR framework. These molecules form two distinctive functional parts: part 1 comprises a boron-nitrogen (BN)-MR framework with adjacent benzene and fluorene units forming a central luminescent core characterized by an exceptionally rigid planar geometry, allowing for narrow FWHM values; part 2 includes peripheral mesitylene, benzene, and adamantyl groups, creating a unique three-dimensional "umbrella-like" conformation to mitigate intermolecular interactions and suppress exciton annihilation. The resulting A-BN, DA-BN, and A-DBN exhibit remarkably narrow FWHM values ranging from 18 to 14 nm and near-unity photoluminescence quantum yields. Particularly, OLEDs based on DA-BN and A-DBN demonstrate outstanding efficiencies of 35.0% and 34.3%, with FWHM values as low as 22 nm and 25 nm, respectively, effectively accomplishing the integration of high color purity and high device performance.

Synergetic Modulation of Steric Hindrance and Excited State for Anti-Quenching and Fast Spin-Flip Multi-Resonance Thermally Activated Delayed Fluorophore.

Multi-resonance thermally activated delayed fluorescence (MR-TADF) materials hold great promise for advanced high-resolution organic light-emitting diode (OLED) displays. However, persistent challenges, such as severe aggregation-caused quenching (ACQ) and slow spin-flip, hinder their optimal performance. We propose a synergetic steric-hindrance and excited-state modulation strategy for MR-TADF emitters, which is demonstrated by two blue MR-TADF emitters, IDAD-BNCz and TIDAD-BNCz, bearing sterically demanding 8,8-diphenyl-8H-indolo[3,2,1-de]acridine (IDAD) and 3,6-di-tert-butyl-8,8-diphenyl-8H-indolo[3,2,1-de]acridine (TIDAD), respectively. These rigid and bulky IDAD/TIDAD moieties, with appropriate electron-donating capabilities, not only effectively mitigate ACQ, ensuring efficient luminescence across a broad range of dopant concentrations, but also induce high-lying charge-transfer excited states that facilitate triplet-to-singlet spin-flip without causing undesired emission redshift or spectral broadening. Consequently, implementation of a high doping level of IDAD-BNCz resulted in highly efficient narrowband electroluminescence, featuring a remarkable full-width at half-maximum of 34 nm and record-setting external quantum efficiencies of 34.3 % and 31.8 % at maximum and 100 cd m-2, respectively. The combined steric and electronic effects arising from the steric-hindered donor introduction offer a compelling molecular design strategy to overcome critical challenges in MR-TADF emitters.

Pushing the limits of low-cost ultra-low-field MRI by dual-acquisition deep learning 3D superresolution.

PURPOSE: Recent development of ultra-low-field (ULF) MRI presents opportunities for low-power, shielding-free, and portable clinical applications at a fraction of the cost. However, its performance remains limited by poor image quality. Here, a computational approach is formulated to advance ULF MR brain imaging through deep learning of large-scale publicly available 3T brain data. METHODS: A dual-acquisition 3D superresolution model is developed for ULF brain MRI at 0.055 T. It consists of deep cross-scale feature extraction, attentional fusion of two acquisitions, and reconstruction. Models for T1 -weighted and T2 -weighted imaging were trained with 3D ULF image data sets synthesized from the high-resolution 3T brain data from the Human Connectome Project. They were applied to 0.055T brain MRI with two repetitions and isotropic 3-mm acquisition resolution in healthy volunteers, young and old, as well as patients. RESULTS: The proposed approach significantly enhanced image spatial resolution and suppressed noise/artifacts. It yielded high 3D image quality at 0.055 T for the two most common neuroimaging protocols with isotropic 1.5-mm synthetic resolution and total scan time under 20 min. Fine anatomical details were restored with intrasubject reproducibility, intercontrast consistency, and confirmed by 3T MRI. CONCLUSION: The proposed dual-acquisition 3D superresolution approach advances ULF MRI for quality brain imaging through deep learning of high-field brain data. Such strategy can empower ULF MRI for low-cost brain imaging, especially in point-of-care scenarios or/and in low-income and mid-income countries.

Calibrationless reconstruction of uniformly-undersampled multi-channel MR data with deep learning estimated ESPIRiT maps.

PURPOSE: To develop a truly calibrationless reconstruction method that derives An Eigenvalue Approach to Autocalibrating Parallel MRI (ESPIRiT) maps from uniformly-undersampled multi-channel MR data by deep learning. METHODS: ESPIRiT, one commonly used parallel imaging reconstruction technique, forms the images from undersampled MR k-space data using ESPIRiT maps that effectively represents coil sensitivity information. Accurate ESPIRiT map estimation requires quality coil sensitivity calibration or autocalibration data. We present a U-Net based deep learning model to estimate the multi-channel ESPIRiT maps directly from uniformly-undersampled multi-channel multi-slice MR data. The model is trained using fully-sampled multi-slice axial brain datasets from the same MR receiving coil system. To utilize subject-coil geometric parameters available for each dataset, the training imposes a hybrid loss on ESPIRiT maps at the original locations as well as their corresponding locations within the standard reference multi-slice axial stack. The performance of the approach was evaluated using publicly available T1-weighed brain and cardiac data. RESULTS: The proposed model robustly predicted multi-channel ESPIRiT maps from uniformly-undersampled k-space data. They were highly comparable to the reference ESPIRiT maps directly computed from 24 consecutive central k-space lines. Further, they led to excellent ESPIRiT reconstruction performance even at high acceleration, exhibiting a similar level of errors and artifacts to that by using reference ESPIRiT maps. CONCLUSION: A new deep learning approach is developed to estimate ESPIRiT maps directly from uniformly-undersampled MR data. It presents a general strategy for calibrationless parallel imaging reconstruction through learning from the coil and protocol-specific data.

Conventional photon blockade in the dispersive limit for Tavis-Cummings model.

In the dispersive limit, the conventional photon blockade effect cannot be realized due to the absence of photon nonlinearity. We propose a scheme to recover the photon blockade effect of the dispersive Tavis-Cummings model, which makes it possible to realize the conventional photon blockade effect in the dispersive limit. It is shown that both single-photon and two-photon blockade effects can be recovered at appropriate qubit driving strength. The optimal qubit drive strength and cavity field drive detuning are given analytically. All analyses can be verified by numerical simulation, and the strongest photon blockade effect with the largest average photon number can be produced when the single excitation resonance condition is satisfied. Moreover, we find that the achieved two-photon blockade effect is relatively robust to thermal noise. Our proposal is able to obtain single-photon sources with high purity and high brightness and has great potential for applications in quantum communication processing.

Squeezing-induced nonreciprocal photon blockade in an optomechanical microresonator.

We propose a scheme to generate nonreciprocal photon blockade in a stationary whispering gallery microresonator system based on two physical mechanisms. One of the two mechanisms is inspired by recent work [Phys. Rev. Lett.128, 083604 (2022)10.1103/PhysRevLett.128.083604], where the quantum squeezing caused by parametric interaction not only shifts the optical frequency of propagating mode but also enhances its optomechanical coupling, resulting in a nonreciprocal conventional photon blockade phenomenon. On the other hand, we also give another mechanism to generate stronger nonreciprocity of photon correlation according to the destructive quantum interference. Comparing these two strategies, the required nonlinear strength of parametric interaction in the second one is smaller, and the broadband squeezed vacuum field used to eliminate thermalization noise is no longer needed. All analyses and optimal parameter relations are further verified by numerically simulating the quantum master equation. Our proposed scheme opens a new avenue for achieving the nonreciprocal single photon source without stringent requirements, which may have critical applications in quantum communication, quantum information processing, and topological photonics.

Sulfur-Decorated Nonaromatic Amine Emitters Towards Efficient Triplet Exciton Utilization in Organic Light-Emitting Diodes.

Purely organic compounds served as promising materials for organic electronics have intrigued extensive research focuses owing to their unique photophysical and electronic properties. In the field of organic light-emitting diodes (OLEDs), the utilization of triplet excitons is of great significance for realizing high-performance devices. In contrast to the traditional aromatic amine-based counterparts, sulfur atom with a high-level outer orbit simultaneously provides powerful electron-donating ability and striking spin-orbit coupling effect to facilitate the utilization of theoretically spin-forbidden triplet excitons, demonstrating great prospect in constructing highly emissive purely organic emitters for OLED applications. Herein, we summarize the currently developed sulfur-decorated nonaromatic amine-based emitters exhibiting attractive photoelectronic characteristics, and gain insight into the understanding of molecular design and photophysical processes of these emitters, providing new perspectives for enriching the existing luminescent material systems and designing high-performance emitters.

A Feasible Strategy for a Highly Efficient Thermally Activated Delayed Fluorescence Emitter Over 900 nm Based on Phenalenone Derivatives.

Near-infrared (NIR) organic light-emitting diodes (OLEDs) suffer from the low external electroluminescence (EL) quantum efficiency (EQE), which is a critical obstacle for potential applications. Herein, 1-oxo-1-phenalene-2,3-dicarbonitrile (OPDC) is employed as an electron-withdrawing aromatic ring, and by incorporating with triphenylamine (TPA) and biphenylphenylamine (BBPA) donors, two novel NIR emitters with thermally activated delayed fluorescence (TADF) characteristics, namely OPDC-DTPA and OPDC-DBBPA, are first developed and compared in parallel. Intense NIR emission peaks at 962 and 1003 nm are observed in their pure films, respectively. Contributed by the local excited (LE) characteristics in the triplet (T1 ) state in synergy with the charge transfer (CT) characteristics for the singlet (S1 ) state to activate TADF emission, the solution processable doped NIR OLEDs based on OPDC-DTPA and OPDC-DBBPA yield EL peaks at 834 and 906 nm, accompanied with maximum EQEs of 0.457 and 0.103 %, respectively, representing the state-of-the-art EL performances in the TADF emitter-based NIR-OLEDs in the similar EL emission regions so far. This work manifests a simple and effective strategy for the development of NIR TADF emitters with long wavelength and efficiency synchronously.

Identification and expression characteristics of NLP (NIN-like protein) gene family in pepper (Capsicum annuum L.).

BACKGROUND: Pepper (Capsicum annum L.) is the main crop in the vegetable industry. The growth and development of peppers are regulated by nitrate, but there is limited research on the molecular mechanisms of nitrate absorption and assimilation in peppers. A plant specific transcription factor NLP plays an important role in nitrate signal transduction. METHODS AND RESULTS: In this study, a total of 7 NLP members were identified based on pepper genome data. Two nitrogen transport elements (GCN4) were found in the CaNLP5 promoter. In the phylogenetic tree, CaNLP members are divided into three branches, with pepper NLP and tomato NLP having the closest genetic relationship. The expression levels of CaNLP1, CaNLP3, and CaNLP4 are relatively high in the roots, stems, and leaves. The expression level of CaNLP7 gene is relatively high during the 5-7 days of pepper fruit color transformation. After various non-Biotic stress and hormone treatments, the expression of CaNLP1 was at a high level. The expression of CaNLP3 and CaNLP4 was down regulated in leaves, but up regulated in roots. Under conditions of nitrogen deficiency and sufficient nitrate, the expression patterns of NLP genes in pepper leaves and roots were determined. CONCLUSION: These results provide important insights into the multiple functions of CaNLPs in regulating nitrate absorption and transport.

Investigation of critical factors influencing the underestimation of hearing loss predicted by the ISO 1999 predicting model.

OBJECTIVE: To analyze factors influencing the underestimation of noise-induced permanent threshold shift (NIPTS) among manufacturing workers, providing baseline data for revising noise exposure standard. DESIGN: A cross-sectional study was designed with 2702 noise-exposed workers from 35 enterprises from 10 industries. Personal noise exposure level(LAeq,8h) and noise kurtosis level were determined by a noise dosimeter. Questionnaires and hearing loss tests were performed for each subject. The predicted NIPTS was calculated using the ISO 1999:2013 model for each participant, and the actual measured NIPTS was corrected for age and sex. The factors influencing the underestimation of NIPTS were investigated. RESULTS: The predicted NIPTS at each test frequency (0.5, 1, 2, 3, 4, or 6kHz) and mean NIPTS at 2, 3, 4, and 6kHz (NIPTS2346) using the ISO 1999:2013 model were significantly lower than their corresponding measured NIPTS, respectively (P < 0.001). The ISO model significantly underestimated the NIPTS2346 by 12.36 dB HL. The multiple linear regression analysis showed that noise exposure level, exposure duration, age, and kurtosis could affect the degree of underestimation of NIPTS2346. The generalized additive model (GAM) with (penalized) spline components showed nonlinear relationships between critical factors (age, exposure duration, noise level, and kurtosis) and the underestimated NIPTS2346.The underestimated NIPTS2346 decreased with an increase in exposure duration (especially over ten years). There was no apparent trend in the underestimated NIPTS2346 with age. The underestimated NIPTS2346 decreased with the increased noise level [especially > 90 dB(A)]. The underestimated NIPTS2346 increased with an increase in noise kurtosis after adjusting for the noise exposure level and exposure duration and ultimately exhibiting a linear regression relationship. CONCLUSIONS: The ISO 1999 predicting model significantly underestimated the noise-induced hearing loss among manufacturing workers. The degree of underestimation became more significant at the noise exposure condition of fewer than ten years, less than 90 dB(A), and higher kurtosis levels. It is necessary to apply kurtosis to adjust the underestimation of hearing loss and consider the applying condition of noise energy metrics when using the ISO predicting model.

An ECG Signal Acquisition and Analysis System Based on Machine Learning with Model Fusion.

Recently, cardiovascular disease has become the leading cause of death worldwide. Abnormal heart rate signals are an important indicator of cardiovascular disease. At present, the ECG signal acquisition instruments on the market are not portable and manual analysis is applied in data processing, which cannot address the above problems. To solve these problems, this study proposes an ECG acquisition and analysis system based on machine learning. The ECG analysis system responsible for ECG signal classification includes two parts: data preprocessing and machine learning models. Multiple types of models were built for overall classification, and model fusion was conducted. Firstly, traditional models such as logistic regression, support vector machines, and XGBoost were employed, along with feature engineering that primarily included morphological features and wavelet coefficient features. Subsequently, deep learning models, including convolutional neural networks and long short-term memory networks, were introduced and utilized for model fusion classification. The system's classification accuracy for ECG signals reached 99.13%. Future work will focus on optimizing the model and developing a more portable instrument that can be utilized in the field.

Mild Synthesis of Polychlorinated Arenes for Efficient Organic Light-emitting Diodes with Dual Thermally Activated Delayed Fluorescence.

Polychlorinated (hetero)arenes have shown great promise for organic optoelectronics applications. However, the harsh synthetic routes for polychlorinated compounds and the possible luminescence quenching from the compact intermolecular π-π stacking induced by chlorine atoms limit their investigations and applications in luminescent materials. Herein, two isomeric polychlorinated polycyclic aromatic hydrocarbon (PAH) compounds JY-1-Cl and JY-2-Cl consisting of rigidified aryl ketones and amine are designed and synthesized under mild conditions through nucleophilic chlorination intermediated by an electron donor-acceptor complex. Among them, as a result of the strong π-π interactions induced by chlorine atoms, JY-2-Cl exhibits bright monomer and dimer emissions with dual thermally activated delayed fluorescence (TADF) characters. Notably, compared with the non-chlorinated compounds, a high photoluminescence quantum yield is maintained after introducing multiple chlorine atoms into JY-2-Cl. The first dual-TADF organic light-emitting diodes are also successfully fabricated with maximum external quantum efficiency as high as 29.1 % by employing JY-2-Cl as emitter. This work presents a new paradigm and synthesis of polychlorinated amine-carbonyl PAHs and demonstrates the great potential of the chlorinated materials for luminescent applications.

Sulfone-Embedded Heterocyclic Narrowband Emitters with Strengthened Molecular Rigidity and Suppressed High-Frequency Vibronic Coupling.

Sulfone-embedded heterocyclics are of great interest in organic light-emitting diodes (OLEDs), however, exploring highly efficient narrowband emitters based on sulfone-embedded heterocyclics remains challenging. Herein, five emitters with different sulfur valence state and molecular rigidity, namely tP, tCPD, 2tCPD, tPD and tPT, are thoroughly analysed. With restricted twisting of flexible peripheral phenyl by strengthening molecular rigidity, molecular emission spectra can be enormously narrowed. Further, introducing the sulfone group with bending vibration in low-frequency region that suppresses high-frequency vibration, sharp narrow full-widths at half-maximum of 28 and 25 nm are achieved for 2tCPD and tPD, respectively. Maximum external quantum efficiencies of 22.0 % and 27.1 % are successfully realized for 2tCPD- and tPD-based OLED devices. These results offer a novel design strategy for constructing narrowband emitters by introducing sulfone group into a rigid molecular framework.