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Intervertebral disc degeneration (IVDD) is a prevalent chronic condition causing spinal pain and functional impairment. This study investigates the role of extracellular vesicles (EVs) derived from human umbilical cord mesenchymal stem cells (hUCMSCs) in regulating IVDD. Using RNA-seq, we analyzed differential expressions of lncRNA and miRNA in nucleus pulposus tissues from various mouse groups. We identified key regulatory molecules, MALAT1 and miRNA-138-5p, which contribute to IVDD. Further experiments demonstrated that MALAT1 can up-regulate SLC7A11 expression by competitively binding to miR-138-5p, forming a MALAT1/miR-138-5p/SLC7A11 coexpression regulatory network. This study elucidates the molecular mechanism by which hUCMSC-derived EVs regulate IVDD and could help develop novel therapeutic strategies for treating this condition. Our findings demonstrate that hUCMSCs-EVs inhibit ferroptosis in nucleus pulposus cells, thereby improving IVDD. These results highlight the therapeutic potential of hUCMSCs-EVs in ameliorating the development of IVDD, offering significant scientific and clinical implications for new treatments.

Targeted sentiment analysis has shown great promise in the field of e-commerce review processing. In recent years, research is ongoing to optimize the current targeted sentiment analysis approaches. This paper, from the innovation perspective, proposes a method referred to as granular computing-based multi-level interactive attention networks (GC-MIA). The method is constructed on the basis of granular computing. Each word is treated as an indivisible granule which constitutes the contexts and the target, respectively. Aiming at exploring the information within each word in the sentence, the multi-level interactive attention networks are established to make full use of every single granule. The representations of the target and the contexts are revised via multi-level interactive learning. Experimental results on the SemEval 2014 dataset are presented to verify the effectiveness of the GC-MIA model. The high accuracy indicates the significance of the proposed method in the targeted sentiment analysis.

Heart rate variability (HRV) is an important metric with a variety of applications in clinical situations such as cardiovascular diseases, diabetes mellitus, and mental health. HRV data can be potentially obtained from electrocardiography and photoplethysmography signals, then computational techniques such as signal filtering and data segmentation are used to process the sampled data for calculating HRV measures. However, uncertainties arising from data acquisition, computational models, and physiological factors can lead to degraded signal quality and affect HRV analysis. Therefore, it is crucial to address these uncertainties and develop advanced models for HRV analysis. Although several reviews of HRV analysis exist, they primarily focus on clinical applications, trends in HRV methods, or specific aspects of uncertainties such as measurement noise. This paper provides a comprehensive review of uncertainties in HRV analysis, quantifies their impacts, and outlines potential solutions. To the best of our knowledge, this is the first study that presents a holistic review of uncertainties in HRV methods and quantifies their impacts on HRV measures from an engineer's perspective. This review is essential for developing robust and reliable models, and could serve as a valuable future reference in the field, particularly for dealing with uncertainties in HRV analysis.

The significant features of carbon dots (CDs), such as bright and tunable photoluminescence, high thermal stability, and low toxicity, endow them with tremendous potential for application in next generation optoelectronics. Despite great progress achieved in the design of high-performance CDs so far, the practical applications in solid-state lighting and displays have been retarded by the aggregation-caused quenching (ACQ) effect ascribed to direct π–π interactions. This review provides a comprehensive overview of the recent progress made in solid-state CD emitters, including their synthesis, optical properties and applications in light-emitting diodes (LEDs). Their triplet-excited-state-involved properties, as well as their recent advances in phosphor-converted LEDs and electroluminescent LEDs, are mainly reviewed here. Finally, the prospects and challenges of solid-state CD-based LEDs are discussed with an eye on future development. We hope that this review will provide critical insights to inspire new exciting discoveries on solid-state CDs from both fundamental and practical standpoints so that the realization of their potential in optoelectronic areas can be facilitated.

The precise gait phase detection with lightweight equipment under variable conditions is crucial for low limb exoskeleton robots. Therefore, the kinematics and dynamics information are investigated. In this paper, a novel radius-margin-based support vector machine (SVM) model with particle swarm optimization (PSO) in feature space called PSO-FSVM is proposed for gait phase detection. The proposed method addresses the dual objectives of maximizing margin while minimizing radius, employing PSO to fine-tune the parameters of the FSVM. This enhancement significantly bolsters the classification accuracy of the SVM. For the measurement of gait features with a lightweight sensor system, the plantar pressure insoles equipped with flexible and elastic sensors are designed. To evaluate the effectiveness of our method, we conducted comparative experiments, pitting the proposed PSO-FSVM against other support vector machine variants, across four treadmill speeds. The experimental results indicate that the proposed method achieves an accuracy of over 98% at four different speeds indoors. Furthermore, the proposed method is compared with other algorithms (SVM, k-nearest neighbor (KNN), adaptive boosting (AdaBoost), and quadratic discriminant analysis (QDA)) under outdoor experiments. The experimental results demonstrate that the average recognition accuracy of this method reaches 96.13% under variable speed conditions, with an average accuracy of 98.06% under slow walking conditions, surpassing the performance of the above four algorithms.

Recent advances in machine learning, particularly deep neural network architectures, have shown substantial promise in classifying and predicting cardiac abnormalities from electrocardiogram (ECG) data. Such data are rich in information content, typically in morphology and timing, due to the close correlation between cardiac function and the ECG. However, the ECG is usually not measured ubiquitously in a passive manner from consumer devices, and generally requires ‘active’ sampling whereby the user prompts a device to take an ECG measurement. Conversely, photoplethysmography (PPG) data are typically measured passively by consumer devices, and therefore available for long-period monitoring and suitable in duration for identifying transient cardiac events. However, classifying or predicting cardiac abnormalities from the PPG is very difficult, because it is a peripherally-measured signal. Hence, the use of the PPG for predictive inference is often limited to deriving physiological parameters (heart rate, breathing rate, etc.) or for obvious abnormalities in cardiac timing, such as atrial fibrillation/flutter (“palpitations”). This work aims to combine the best of both worlds: using continuously-monitored, near-ubiquitous PPG to identify periods of sufficient abnormality in the PPG such that prompting the user to take an ECG would be informative of cardiac risk. We propose a dual-convolutional-attention network (DCA-Net) to achieve this ECG-based PPG classification. With DCA-Net, we prove the plausibility of this concept on MIMIC Waveform Database with high performance level (AUROC $>$ 0.9 and AUPRC $>$ 0.7) and receive satisfactory result when testing the model on an independent dataset (AUROC $>$ 0.7 and AUPRC $>$ 0.6) which it is not perfectly-matched to the MIMIC dataset.

Electrocardiography (ECG) is a non-invasive tool for predicting cardiovascular diseases (CVDs). Current ECG-based diagnosis systems show promising performance owing to the rapid development of deep learning techniques. However, the label scarcity problem, the co-occurrence of multiple CVDs and the poor performance on unseen datasets greatly hinder the widespread application of deep learning-based models. Addressing them in a unified framework remains a significant challenge. To this end, we propose a multi-label semi-supervised model (ECGMatch) to recognize multiple CVDs simultaneously with limited supervision. In the ECGMatch, an ECGAugment module is developed for weak and strong ECG data augmentation, which generates diverse samples for model training. Subsequently, a hyperparameter-efficient framework with neighbor agreement modeling and knowledge distillation is designed for pseudo-label generation and refinement, which mitigates the label scarcity problem. Finally, a label correlation alignment module is proposed to capture the co-occurrence information of different CVDs within labeled samples and propagate this information to unlabeled samples. Extensive experiments on four datasets and three protocols demonstrate the effectiveness and stability of the proposed model, especially on unseen datasets. As such, this model can pave the way for diagnostic systems that achieve robust performance on multi-label CVDs prediction with limited supervision.

Eucommia ulmoidesrubber particles (EuRPs) are organelles that synthesise and store E. ulmoidesrubber (EuR). In this study, the lipids dynamic change of EuRPs from leaf tissue at different growth period were investigated. The results showed that there were 1149 lipid species belonging to 39 lipid classes that were identified; TGs, DGs and Cers were the most abundant among all lipids of EuRPs. Lipid expression analysis demonstrated that the expression intensity of TGs was almost 1 × 104-fold and 10-fold higher than those of MGs and DGs, respectively. Among sphingolipids, the expression intensity of SoP, CerG2, GM3, SM and GerG3 increased throughout the duration of investigation (August–November 2021). Further analysis found that the Cers species accounted for 9.40% of total lipid species and the number of Cers species in EuRPs isolated from leaves in August was the most, with gradual decline in the following 3 months. Meanwhile, hierarchical clustering indicated that there were seven types of highly abundant lipid species in leaf EuRPs from September to November, i.e.SQDG (18:3/18:3), SQDG (34:3), SQDG (17:5/23:2), DGDG (38:12), Co (Q9), TG (16:0/16:0/18:3) and TG (39:1). Compared with leaf EuRPs in August, there were 79, 101 and 107 lipid species which showed significant differential expression in September, October and November. Based on the high expression intensity of SQDG in EuRPs, the correlation between the genes mediated in EuR or SQDG biosynthesis was further analysed, whereby the results indicated co-expression of some genes, which implies the synergistic regulatory role in SQDG EuR biosynthesis.

The effect of pre-stretching on solid-liquid interaction, microstructure and brazing performance of AA4343/AA3xxx/AA4343 layered aluminum sheet during brazing at the atomic level (solid solution), nanoscale (dislocation) and micron level (grain boundary) are studied by glow discharge optical emission spectrometry (GDOES), scanning electron microscope (SEM), electron backscatter diffraction (EBSD) and transmission electron microscopy (TEM). The microstructure after brazing largely depends on the forming condition. The driving force of liquid film migration (LFM) is the reduction of stored deformation energy. The interaction between the liquid clad and solid core layers changes the elemental distribution and microstructure, which in turn affects the brazing performance of the sheet. The results reveal the mechanism of solid-liquid interaction of layered aluminum sheet during brazing and clarify the driving force of LFM of layered aluminum sheet during brazing. Consequently, these results provide important insights for the design and theoretical research of functional layered aluminum sheet.

Biosignals collected by wearable devices, such as electrocardiogram and photoplethysmogram, exhibit redundancy and global temporal dependencies, posing a challenge in extracting discriminative features for blood pressure (BP) estimation. To address this challenge, we propose HGCTNet, a handcrafted feature-guided CNN and transformer network for cuffless BP measurement based on wearable devices. By leveraging convolutional operations and self-attention mechanisms, we design a CNN-Transformer hybrid architecture to learn features from biosignals that capture both local information and global temporal dependencies. Then, we introduce a handcrafted feature-guided attention module that utilizes handcrafted features extracted from biosignals as query vectors to eliminate redundant information within the learned features. Finally, we design a feature fusion module that integrates the learned features, handcrafted features, and demographics to enhance model performance. We validate our approach using two large wearable BP datasets: the CAS-BP dataset and the Aurora-BP dataset. Experimental results demonstrate that HGCTNet achieves an estimation error of 0.9 $\pm$ 6.5 mmHg for diastolic BP (DBP) and 0.7 $\pm$ 8.3 mmHg for systolic BP (SBP) on the CAS-BP dataset. On the Aurora-BP dataset, the corresponding errors are $-$0.4 $\pm$ 7.0 mmHg for DBP and $-$0.4 $\pm$ 8.6 mmHg for SBP. Compared to the current state-of-the-art approaches, HGCTNet reduces the mean absolute error of SBP estimation by 10.68% on the CAS-BP dataset and 9.84% on the Aurora-BP dataset. These results highlight the potential of HGCTNet in improving the performance of wearable cuffless BP measurements.

The effects of particles on precipitation reactions in aluminum alloy have been widely unknown. Al–Fe–Mn–Si–Mg–Cu alloy strengthened with uniformly distributed Al(Fe,Mn)Si nanoparticles was successfully produced in this study. The alloy was then characterised using high-resolution scanning transmission electron microscopy (HRTEM), to provide a fundamental insight into the interface precipitation. Interfacial precipitations of several tens of nanometers in size was formed after aging, which were found to be Al5Cu6Mg2and Si phases. The results demonstrated that the facetted α-Al(Fe,Mn)Si particles had a significant influence on precipitation adjacent to the α-Al(Fe,Mn)Si/Al interfaces. Semi-coherent α-Al(Fe,Mn)Si/Al interfaces were revealed to have periodically spaced misfit dislocations that are generally considered to be beneficial to heterogeneous precipitation. They not only reduce nucleation energy barriers but also act as short-circuit diffusion paths to accelerate growth rates by transporting solute atoms and vacancies.

• Dilute Mg-0.6Al-0.5Mn-0.2Ca-0.3Ce alloy sheet was designed to show an admirable balance between anti-corrosion and mechanical properties. • Ce micro-alloying results in lower cathodic activity, better Fe scavenger effect, and denser Ce oxide containing surface film. • Uniform fine-grained structure and ordered Al-Ca-rich G.P. zones are obtained via controlled rolling, solid solution, and aging. • The precipitation of Al-Ca-rich G.P. zones is responsible for pronounced age-hardening response while not causing severe weakening micro-galvanic corrosion. • Inherent strength-corrosion trade-off can be overcome by clever alloying and reasonable thermomechanical processes. Low strength and poor corrosion resistance are two long-standing bottlenecks with dilute Mg alloys. Here, we report that the corrosion resistance of Mg-0.6Al-0.5Mn-0.2Ca (wt.%) alloy sheet can be significantly improved by micro-alloying with 0.3 wt.% Ce, and the strength can be considerably augmented after aging treatment. Simultaneous optimization of strength, ductility, and corrosion resistance is difficult due to the inherent trade-off in Mg alloys. Surprisingly, our aged Mg-0.6Al-0.5Mn-0.2Ca-0.3Ce alloy features with yield strength (YS) of ∼194 MPa, ultimate tensile strength (UTS) of ∼265 MPa, elongation to failure (EF) of ∼17.2%, and corrosion rate (CR) of 2.2 mm y−1, the combination of which exhibits competitive advantage over other comparative dilute Mg alloys. It is found that Ce addition decreases the activity of cathodic phases, inhibits detrimental effects of Fe impurities, and forms a protective Ce-containing surface film. The high strength stems from the precipitation of ordered Guinier-Preston (G.P.) zones dispersed in uniform fine grains with an average grain size of ∼8.2 μm. The atomic-scale G.P. zones result in a noticeable age hardening response but do not act as crack initiation and propagation site, so our alloy also performs satisfactory ductility. This work sheds light on the design and fabrication of strong, ductile, and corrosion-resistant dilute magnesium alloys to be used in electronic products and automotive bodies. [Display omitted] [ABSTRACT FROM AUTHOR]

This study aimed to evaluate the performance of cuffless blood pressure (BP) measurement techniques in a large and diverse cohort of participants. We enrolled 3077 participants (aged 18–75, 65.16% women, 35.91% hypertensive participants) and conducted followed-up for approximately 1 month. Electrocardiogram, pulse pressure wave, and multiwavelength photoplethysmogram signals were simultaneously recorded using smartwatches; dual-observer auscultation systolic BP (SBP) and diastolic BP (DBP) reference measurements were also obtained. Pulse transit time, traditional machine learning (TML), and deep learning (DL) models were evaluated with calibration and calibration-free strategy. TML models were developed using ridge regression, support vector machine, adaptive boosting, and random forest; while DL models using convolutional and recurrent neural networks. The best-performing calibration-based model yielded estimation errors of 1.33 $\pm$ 6.43 mmHg for DBP and 2.31 $\pm$ 9.57 mmHg for SBP in the overall population, with reduced SBP estimation errors in normotensive (1.97 $\pm$ 7.85 mmHg) and young (0.24 $\pm$ 6.61 mmHg) subpopulations. The best-performing calibration-free model had estimation errors of $-$0.29 $\pm$ 8.78 mmHg for DBP and $-$0.71 $\pm$ 13.04 mmHg for SBP. We conclude that smartwatches are effective for measuring DBP for all participants and SBP for normotensive and younger participants with calibration; performance degrades significantly for heterogeneous populations including older and hypertensive participants. The availability of cuffless BP measurement without calibration is limited in routine settings. Our study provides a large-scale benchmark for emerging investigations on cuffless BP measurement, highlighting the need to explore additional signals or principles to enhance the accuracy in large-scale heterogeneous populations.

• The EMI shielding performances and mechanical properties of MXene functionalized CF/PEKK composites are simultaneously improved. • The obtained CF/PEKK composites show an excellent EMI SE of 65.2 dB. • The CF/PEKK composites present superior mechanical properties with a flexible strength of 1127 MPa, flexible modulus of 81 GPa and ILSS of 89 MPa. In this study, two-dimensional MXene (Ti 3 C 2 T x) was employed to modify the interface of carbon fiber-reinforced polyetherketoneketone (CF/PEKK) composites, in order to simultaneously improve the electromagnetic interference (EMI) shielding performances and mechanical properties. The obtained CF/PEKK composites possessed outstanding EMI and mechanical performances, as anticipated. Specifically, the CF/PEKK composites modified with MXene at 1 mg mL–1 exhibited an excellent EMI shielding effectiveness of 65.2 dB in the X-band, a 103.1% enhancement compared with the unmodified CF/PEKK composites. The attractive EMI shielding performances of CF/PEKK composites originated from enhanced ohmic losses and multiple reflections of electromagnetic waves with the help of the MXene and CF layers. In addition, CF/PEKK composites achieved the best mechanical properties by optimizing the dispersion concentration of MXene to 0.1 mg mL–1. The flexural strength, flexural modulus, and interlaminar shear strength of CF/PEKK composites reached 1127 MPa, 81 GPa, and 89 MPa, which were 28.5%, 9.5%, and 29.7% higher than that of the unmodified CF/PEKK composites, respectively. Such improvement in mechanical properties could be ascribed to the comprehensive effect of mechanical interlocking, hydrogen bonds, and Van der Waals forces between the introduced MXene and CF, PEKK, respectively. [Display omitted] [ABSTRACT FROM AUTHOR]

The effects of an interlayer on the corrosion resistance and mechanical properties of multi-layered aluminum sheets were studied. The interlayer prevents Si diffusion to the core layer and optimizes the potential gradient from the Zn-containing interlayer to the core layer. The presence of the interlayer changes the corrosion mode from pitting and intergranular corrosion (IGC) to exfoliation corrosion. Additionally, the natural aging process forms Guinier-Preston (GP) zones in the core layer, which improves the material's yield strength. First principle calculations show that there is minimal corrosion between the GP zones and Al matrix. Thus, the mechanical properties and corrosion resistance of multi-layered aluminum sheets are improved simultaneously.

The pivotal role of lithium (Li) in improving the comprehensive mechanical properties of third-generation Al–Li alloys remains significant even at a low content. However, the strengthening contribution of a low dosage lithium and its combination with different processing methods remain largely unknown. This study aimed to investigate the strengthening effects of room-temperature (RT) equal channel angular pressing (ECAP) and rolling on Al–0.6Li alloy. Microstructural evolution during processing was monitored by optical microscope (OM), scanning electron microscope (SEM), electron backscattered diffraction (EBSD), transmission electron microscope (TEM) and X-ray diffraction (XRD). The results revealed that simultaneous high ultimate tensile strength (UTS, 243 MPa) and yield strength (YS, 210 MPa) of the developed Al–0.6Li alloy were specifically achieved with a combination of RT ECAP and rolling, alongside an elongation (EL) of 9.5%. The gained strength improvement was primarily credited to the excellent fine-grain strengthening, as evidenced by a significant reduction in grain size from 101 μm to 1.47 μm, and dislocation strengthening, which, respectively, contributed to an increase of 91 MPa and 100 MPa in YS. Findings from this study demonstrate that with proper processing technology, the mechanical properties of Al–Li alloys with low Li content can be effectively improved, opening new avenues to develop high-performance Al–Li alloys.

• The twin-roll cast 6061 strip with alleviative center segregation was achieved. • The mitigation of center segregation was related to the thermal-mechanical process. • The change of cooling rate could affect the phase selection of Fe-containing phase. • The α-AlFeSi shows favorable crystallographic matching with Mg 2 Si and Q phases. • Three matching planes between α-AlFeSi and Q/Mg 2 Si were examined by EBSD analysis. Serious center segregation greatly limits the application of twin-roll casting (TRC) technology for producing 6xxx alloy strips. Herein, Al-0.9Mg-0.6Si-0.2Cu-0.1Fe (wt.%, 6061) strips with different thicknesses were fabricated by TRC, and we found that the center segregation was well relieved with the thickness increased from 3 mm to 4 mm. To reveal the mechanisms of mitigation of center segregation in the 4 mm strip, various techniques including solidification simulation, crystallographic calculation, electron backscatter diffraction (EBSD), and electron probe micro-analyzer (EPMA) were utilized. The results disclosed that the Fe-containing phase in the 3 mm strip was π-AlFeMgSi, while the counterpart in the 4 mm strip was α-AlFeSi. The α-AlFeSi could serve as nucleation substrates for Mg 2 Si and Q-AlCuMgSi phases, thus promoting the uniform distribution of elements and preventing the accumulation of phases in the center region. Three matching planes between the α-AlFeSi and Q/Mg 2 Si were examined as: (11 2 ¯ 0) α-AlFeSi // (0001) Q, (0001) α-AlFeSi // (110) Mg2Si, and (11 2 ¯ 0) α-AlFeSi // (1 1 ¯ 0) Mg2Si. Meanwhile, the smaller roll separating force during the TRC process in the 4 mm strip could weaken the force-induced liquid flow behavior in the semi-solid region, which is the other reason for the alleviation of center segregation. Owing to the elimination of the center segregation, a more excellent fracture elongation was achieved in the as-homogenized 4 mm strip (∼29%) compared with the counterpart of the 3 mm strip (∼20%). This work may provide a strategy to eliminate the center segregation, thus further promoting the application of TRC process and producing high-performance Al alloy strips efficiently. [Display omitted] [ABSTRACT FROM AUTHOR]

With the development of modern cameras, more physiological signals can be obtained from portable devices like smartphone. Some hemodynamically based non-invasive video processing applications have been applied for blood pressure classification and blood glucose prediction objectives for unobtrusive physiological monitoring at home. However, this approach is still under development with very few publications. In this paper, we propose an end-to-end framework, entitled cocktail causal container, to fuse multiple physiological representations and to reconstruct the correlation between frequency and temporal information during multi-task learning. Cocktail causal container processes hematologic reflex information to classify blood pressure and blood glucose. Since the learning of discriminative features from video physiological representations is quite challenging, we propose a token feature fusion block to fuse the multi-view fine-grained representations to a union discrete frequency space. A causal net is used to analyze the fused higher-order information, so that the framework can be enforced to disentangle the latent factors into the related endogenous association that corresponds to down-stream fusion information to improve the semantic interpretation. Moreover, a pair-wise temporal frequency map is developed to provide valuable insights into extraction of salient photoplethysmograph (PPG) information from fingertip videos obtained by a standard smartphone camera. Extensive comparisons have been implemented for the validation of cocktail causal container using a Clinical dataset and PPG-BP benchmark. The root mean square error of $1.329\pm 0.167$ for blood glucose prediction and precision of $0.89\pm 0.03$ for blood pressure classification are achieved in Clinical dataset.

BackgroundAdult asthma is phenotypically heterogeneous with unclear aetiology. We aimed to evaluate the potential contribution of environmental exposure and its ensuing response to asthma and its heterogeneity.MethodsEnvironmental risk was evaluated by assessing the records of National Health Insurance Research Database (NHIRD) and residence-based air pollution (particulate matter with diameter less than 2.5 micrometers (PM2.5) and PM2.5-bound polycyclic aromatic hydrocarbons (PAHs)), integrating biomonitoring analysis of environmental pollutants, inflammatory markers and sphingolipid metabolites in case–control populations with mass spectrometry and ELISA. Phenotypic clustering was evaluated by t-distributed stochastic neighbor embedding (t-SNE) integrating 18 clinical and demographic variables.FindingsIn the NHIRD dataset, modest increase in the relative risk with time-lag effect for emergency (N=209 837) and outpatient visits (N=638 538) was observed with increasing levels of PM2.5and PAHs. Biomonitoring analysis revealed a panel of metals and organic pollutants, particularly metal Ni and PAH, posing a significant risk for current asthma (ORs=1.28–3.48) and its severity, correlating with the level of oxidative stress markers, notably Nε-(hexanoyl)-lysine (r=0.108–0.311, p<0.05), but not with the accumulated levels of PM2.5exposure. Further, levels of circulating sphingosine-1-phosphate and ceramide-1-phosphate were found to discriminate asthma (p<0.001 and p<0.05, respectively), correlating with the levels of PAH (r=0.196, p<0.01) and metal exposure (r=0.202–0.323, p<0.05), respectively, and both correlating with circulating inflammatory markers (r=0.186–0.427, p<0.01). Analysis of six phenotypic clusters and those cases with comorbid type 2 diabetes mellitus (T2DM) revealed cluster-selective environmental risks and biosignatures.InterpretationThese results suggest the potential contribution of environmental factors from multiple sources, their ensuing oxidative stress and sphingolipid remodeling to adult asthma and its phenotypic heterogeneity.

Adding cuffless blood pressure (BP) measurement function to wearable devices is of great value in the fight against hypertension. The widely used arterial pulse transit time (PTT)-based method for BP monitoring relies primarily on vascular status-determined BP models and typically exhibits degraded performance over time and is sensitive to measurement procedures. Developing alternative methods with improved accuracy and adaptability to various application scenarios is highly desired for cuffless BP measurement. In this work, we proposed a pattern-fusion (PF) method that incorporates cardiovascular coupling effects in the vascular model by combining three calculation modules – cardiac parameter extraction module, cardiac parameter-to-BP mapping module, and BP regulation module. Specifically, the first module combines feedforward, feedback, and propagation modes to model different modulation functions of a cardiovascular system and is responsible for extracting BP-related features from electrocardiography (ECG) and photoplethysmography (PPG) signals; the cardiac parameter-to-BP mapping module is used to map cardiac parameters into mean blood pressure (MBP) by fusing different features; finally, the BP regulation module recovers accurate systolic BP (SBP) and diastolic BP (DBP) from given MBP. With the concerted use of these three modules, the pattern fusion method consistently demonstrates excellent BP prediction accuracy in a variety of measurement scenarios and durations, exhibiting SBP/DBP mean absolute error (MAE) of 3.65/4.56 mmHg for the short-term (&lt;10 mins) continuous measurement dataset, SBP/DBP MAE of 6.84/3.81 mmHg for the medium-term (avg. > 20 hours) continuous measurement dataset, and SBP/DBP MAE of 6.24/3.65 mmHg for the long-term (>1 month) intermittent measurement dataset.

The tea tussock moth (Euproctis pseudoconspersa) is one of the most destructive chewing pests in tea plantations and causes a serious allergic reaction on the skin of tea plantation workers. The sex pheromone components of its Japanese population were first identified as 10,14-dimethylpentadecyl isobutyrate (10Me14Me-15:iBu) and 14-methylpentadecyl isobutyrate (14Me-15:iBu), with a stereogenic center. Only 10Me14Me-15:iBu has been identified in the Chinese E. pseudoconspersapopulation. However, field tests have shown that 10Me14Me-15:iBu cannot meet the demand of effective pest control in China. To develop a high-efficiency E. pseudoconspersasex pheromone formula, electroantennogram (EAG) recordings of (S)- and (R)-enantiomers of 10Me14Me-15:iBu and 14Me-15:iBu were obtained in the present study. The results demonstrated that the EAG responses of male antennae to (R)-enantiomers were significantly higher than responses to the (S)-enantiomers, and 14Me-15:iBu also elicited EAG activity. Field tests showed that the catch numbers of male moths by (R)-enantiomers were significantly higher (P<0.05) than those of (S)-enantiomers. Addition of 14Me-15:iBu significantly increased the catch numbers of both the (S)- and (R)-enantiomers. The efficient pheromone formula containing 0.75 mg (R)-10Me14Me-15:iBu and 0.1 mg 14Me-15:iBu showed significantly higher attractiveness than commercial pheromone products. Our study demonstrated that (R)-10Me14Me-15:iBu was the major sex pheromone component of E. pseudoconspersa, and 14Me-15:iBu might be the minor sex pheromone component. Furthermore, a high-efficiency sex pheromone formula for E. pseudoconspersacontrol was defined in this study.

Pigmentation is a variable trait of insects that help in adapting to the external natural environment. It plays an important role in concealment, mimicry, sex selection signals, and immune responses. Ectropis grisescens is the main lepidopteran pest in the tea gardens of China. The use of body color to simulate tea branches is a key characteristic of E. grisescens larvae that aids in predator evasion. However, no study has reported melanization in E. grisescens. In the present study, the E. grisescens tyrosine hydroxylase (EgTH) gene was cloned and characterized. The phylogenetic tree and stage expression profiles revealed that EgTH may be involved in the melanin pathway. CRISPR/Cas9-mediated targeted mutagenesis of EgTH was conducted to understand its functional role in pigmentation; it was revealed that the intensity of the black pigment systemically and proportionally decreased in the cuticle of the mutant larvae but did not disappear. Importantly, the mutation had no effect on the pigmentation of sclerotized tissues including the crochets, spiracles, claws, ocelli and mouth parts. This study provides the first evidence that CRISPR/Cas9-mediated EgTH knockout induces marked body pigmentation defects that can be visualized in the larvae. It was also demonstrated that another gene or pathway with a function similar to that of EgTH could be present. Additionally, EgTH might be not involved in the pigmentation of sclerotized tissues in E. grisescens. Further, EgTH mutations do not lead to embryonic death in insect species. Thus, the present study provides new insights into the function of insect TH genes.

Glove-based wearable sensors can offer the potential ability to a fast and on-site environmental threat assessment, which is crucial for timely and informed incident management. In this study, an on-demand surface-enhanced Raman scattering (SERS) array sensor has been patterned on fire-retardant fibre gloves viathe screen-printing technique in large batches. The screen-printed ink contains one-pot synthesized silver nanoparticle and molybdenum disulfide nanocomposite (Ag/MoS2), and polyanionic cellulose (PAC) as a new adhesive agent. Rhodamine 6G (R6G) was employed as an initial probe molecule to systematically evaluate the performance of the resulting sensor. The results suggest that the fabricated fire-retardant screen-printed SERS array sensor displays high reproducibility and stability at 250 °C, with the lower detection limit of 10−13M for R6G. The spot-to-spot SERS signals show that the intensity variation was less than 10%. Besides, the SERS signals can be maintained over 7 weeks. Further investigation was then successfully carried out to detect polycyclic aromatic hydrocarbons (PAHs), which are commonly used as flammable chemicals. In our perception, this wearable fire-retardant screen-printed SERS array sensor would be an ideal candidate for practical on-site environmental emergency monitoring due to its fire-retardant capability and timely measurement on a portable carrier.

Regulating the morphology and composition of Fe-containing phases can significantly improve the mechanical properties of Al–Mg–Si alloys. Here, we successfully prepared the high-performance AA6061 alloys by the route of sub-rapid solidification (SRS) based on twin-roll casting (TRC). Excellent tensile strength (∼372 MPa) and elongation (∼19%) were achieved in the peak-aged TRC sample, which increased simultaneously compared with the counterpart (∼351 MPa and ∼14%) fabricated via ingot casting (IC). It was found that the strength-ductility synergy of the TRC sample was caused by the high cooling rate, wherein the SRS can refine the microstructure significantly and promote the reaction from the AlFeSi to the AlFeMgSi (Mg:Fe:Si = 1:1.5:2.5) phase. The centerline segregation in the TRC strip could be well mitigated during solution treatment because the reduced size and Mg-incorporation accelerated the redissolution of AlFeMgSi phases. The alleviative segregation greatly promoted supersaturated solution, and thus contributing to the synergy of strength and ductility. Meanwhile, the Si-rich AlFeMgSi phase could decompose into the Fe-rich α-AlFeSi (Fe:Si > 1) during solution treatment, which expanded the solid solubility of Si and Mg. Therefore, an enhanced aging hardening response was obtained in the peak-aged TRC sample, showing the high number density and volume fraction of β” phase. The results would provide guidelines for developing high-performance Al–Mg–Si alloys based on the SRS during TRC.

Anandamide (AEA) analogs show fair effects in counteracting the deterioration of Alzheimer's disease (AD). Our previous studies demonstrated that AEA analog-N-linoleyltyrosine (NITyr) exerted significant activities. In our current research, the role and mechanisms of NITyr were assessed in APP/PS1 mice mimicking the AD model. NITyr improved motor coordination in the rotarod test (RRT) and ameliorated spatial memory in the Morris water maze (MWM) but did not increase spontaneous locomotor activity in the open field test (OFT). In addition, NITyr protected neurons against β-amyloid (Aβ) injury via hematoxylin-eosin (HE) and Nissl staining. Moreover, the related biochemical indexes showed that NITyr reduced the levels of Aβ40and Aβ42in the hippocampus but did not affect the expression of p-APP and β-secretase 1 (BACE1). Furthermore, the autophagy inhibitor 3-methyladenine (3 MA) attenuated the effect of NITyr on animal behaviors and neurons. Meanwhile, NITyr upregulated the expression levels of LC3-II and Beclin-1, which were weakened by AM630 (an antagonist of CB2receptor and a weak partial agonist of CB1receptors). AM630 also weakened the role of NITyr in animal behaviors. Thus, NITyr improved behavioral impairment and neural loss by inducing autophagy mainly mediated by the CB2receptor, and weakly mediated by the CB1receptor.

To compare the mortality associated with percutaneous coronary intervention (PCI) and coronary artery bypass grafting (CABG) in patients with non–ST elevation acute coronary syndrome (NSTE-ACS).

Carbon quantum dots (CQDs) have developed into prospective nanomaterials for next-generation lighting and displays due to their intrinsic advantages of high stability, low cost, and environmental friendliness. However, confined by the spin-forbidden nature of triplet state transitions, the highest theoretical value of external quantum efficiency (EQE) of fluorescent CQDs is merely 5%, which fundamentally limits their further application in electroluminescent light-emitting diodes (LEDs). Soluble phosphorescent CQDs offer a means of breaking the shackle to achieve efficient monochromatic electroluminescence, especially red emission, which is a pivotal constituent in full-color displays. Here, the synthesis of red (625 nm) phosphorescent carbon quantum dot organic frameworks (CDOFs) with a quantum yield of up to 42.3% and realization of high-efficiency red phosphorescent electroluminescent LEDs are reported. The LEDs based on the CDOFs exhibited a red emission with a maximum luminance of 1818 cd m–2and an EQE of 5.6%. This work explores the possibility of a new perspective for developing high-performance CQD-based electroluminescent LEDs.

Idiopathic pulmonary fibrosis (IPF) is the most common type of idiopathic interstitial pneumonia and has one of the poorest prognosis. However, the molecular mechanisms underlying IPF progression remain largely unknown. In this study, we determined that IL-24, an IL-20 subfamily cytokine member, was increased both in the serum of IPF patients and the bronchoalveolar lavage fluid (BALF) of mice following bleomycin (BLM)-induced pulmonary fibrosis. As a result, IL-24deficiency protected mice from BLM-induced lung injury and fibrosis. Specifically, loss of IL-24significantly attenuated transforming growth factor β1 (TGF-β1) production and reduced M2 macrophage infiltration in the lung of BLM-induced mice. Mechanistically, IL-24 alone did not show a perceptible impact on the induction of M2 macrophages, but it synergized with IL-4 to promote M2 program in macrophages. IL-24 suppressed IL-4-induced expression of suppressor of cytokine signaling 1 (SOCS1) and SOCS3, through which it enhanced signal transducer and activator of transcription 6/peroxisome proliferator-activated receptor gamma (STAT6/PPARγ) signaling, thereby promoting IL-4-induced production of M2 macrophages. Collectively, our data support that IL-24 synergizes with IL-4 to promote macrophage M2 program contributing to the development of pulmonary fibrosis.

Altered Branched Chain Amino Acids (BCAA), including leucine, isoleucine and valine, are frequently observed in patients with advanced cancer. We evaluated the efficacy of Chimeric Antigen Receptor (CAR) T cell-mediated cancer cell lysis potential in the immune microenvironment of BCAA supplementation and deletion. BCAA supplementation increased cancer cell killing percentage, while accelerating BCAA catabolism and deceasing BCAA transporter decreased cancer cell lysis efficacy. We thus designed BCKDK engineering CAR T cells for the reprogramming of BCAA metabolism in the tumor microenvironment based on the genotype and phenotype modification. BCKDK overexpression (OE) in CAR-T cells significantly improved cancer cell lysis, while BCKDK knockout (KO) resulted in inferior lysis potential. In an in vivoexperiment, BCKDK-OE CAR-T cells treatment significantly prolonged the survival of mice bearing NALM6-GL cancer cells, with the differentiation of central memory cells and the increasing proportion of CAR-T cells in peripheral circulation. BCKDK-KO CAR-T cells treatment resulted in shorter survival and decreasing percentage of CAR-T cells in peripheral circulation. In conclusion, BCKDK engineered CAR-T cells exert distinct phenotype for the superior anticancer efficiency.

Background Middle meningeal artery embolization (MMAE) for chronic subdural hematoma (CSDH) has gained much attention in recent years. However, unintended embolization may occur when employing liquid embolic agents or particles. We present our clinical experience in simple coiling of MMAE to manage CSDH.Methods Patients underwent either surgical evacuation or MMAE with simple coiling for CSDH were reviewed. Clinical and radiographic outcomes were assessed at admission, 1-month, and 6-month intervals. Two treatment groups were matched with inverse probability of treatment weighting.Results One hundred twelve patients were included, with 27 patients in MMAE group and 87 patients in surgery group. In MMAE group, significant reductions were observed in hematoma width (admission vs. 1-month, 2.04 [1.44–2.60] cm vs. 0.62 [0.37–0.95] cm, p< 0.001). The adjusted odds ratio (aOR) of surgical rescue rate (0.77 95%CI 0.13–4.47, p= 0.77), hematoma reduction (>50%) (0.21 95%CI 0.04–1.07, p= 0.06), and midline shift improvement rate (3.22, 95%CI 0.84–12.4, p= 0.09) had no substantial disparities between two groups at 1-month follow-up. In addition, no significant difference was noted between two groups in terms of hematoma reduction (>50%) at 6-month follow-up (aOR 1.09 95%CI 0.32–3.70, p= 0.89). No procedure-related complications were found in MMA embolization group.Conclusion Simple coiling for MMA had comparable outcomes with surgical evacuation for CSDH. Our findings suggest that simple coiling can be an alternative choice for liquid agents or particles in MMA embolization for CSDH with acceptable safety.

Background: Cardiovascular diseases (CVDs) are the leading cause of death worldwide. Genome-wide association studies (GWAS) have identified many single nucleotide polymorphisms (SNPs) appearing in non-coding genomic regions in CVDs. The SNPs may alter gene expression by modifying transcription factor (TF) binding sites and lead to functional consequences in cardiovascular traits or diseases. To understand the underlying molecular mechanisms, it is crucial to identify which variations are involved and how they affect TF binding. Methods: The SNEEP (SNP exploration and analysis using epigenomics data) pipeline was used to identify regulatory SNPs, which alter the binding behavior of TFs and link GWAS SNPs to their potential target genes for six CVDs. The human-induced pluripotent stem cells derived cardiomyocytes (hiPSC-CMs), monoculture cardiac organoids (MCOs) and self-organized cardiac organoids (SCOs) were used in the study. Gene expression, cardiomyocyte size and cardiac contractility were assessed. Results: By using our integrative computational pipeline, we identified 1905 regulatory SNPs in CVD GWAS data. These were associated with hundreds of genes, half of them non-coding RNAs (ncRNAs), suggesting novel CVD genes. We experimentally tested 40 CVD-associated non-coding RNAs, among them RP11-98F14.11, RPL23AP92, IGBP1P1, and CTD-2383I20.1, which were upregulated in hiPSC-CMs, MCOs and SCOs under hypoxic conditions. Further experiments showed that IGBP1P1 depletion rescued expression of hypertrophic marker genes, reduced hypoxia-induced cardiomyocyte size and improved hypoxia-reduced cardiac contractility in hiPSC-CMs and MCOs. Conclusions: IGBP1P1 is a novel ncRNA with key regulatory functions in modulating cardiomyocyte size and cardiac function in our disease models. Our data suggest ncRNA IGBP1P1 as a potential therapeutic target to improve cardiac function in CVDs.