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The tendency of relative motion via rolling between contacting objects exists in various aspects of industry and nature because, in many practical situations, forces and moments may be simultaneously induced at the contacting interfaces. Due to the presence of adhesion, which may be prominent on small scales, research on contacts with the tendency to roll, termed herein as rolling adhesion, is very limited. In the present work, a novel double-Hertz model is developed for adhesive contact between spherical objects subjected to the combined action of normal forces and moments. The results from the new model agree well with available numerical simulations and experimental results. It has been demonstrated that the contact behavior with the effect of rolling adhesion seemingly resembles that of conventional adhesive contact, but the applied moment may impact the pull-off force and may even induce novel contact instability if large enough. The resistance moment at the interface has also been obtained analytically, which is proportional to adhesion hysteresis and contact area. Given the applicability to the full range of the Tabor parameter and nonsingular stresses involved, these results might shed light on adhesive contacts with rolling adhesion and help to characterize them better than existent models. [ABSTRACT FROM AUTHOR]

Background: The NAC transcription factor family, which is recognized as one of the largest plant-specific transcription factor families, comprises numerous members that are widely distributed among various higher plant species and play crucial regulatory roles in plant immunity. Results: In this paper, we provided a detailed summary of the roles that NAC transcription factors play in plant immunity via plant hormone pathways and reactive oxygen species pathways. In addition, we conducted in-depth investigations into the interactions between NAC transcription factors and pathogen effectors to summarize the mechanism through which they regulate the expression of defense-related genes and ultimately affect plant disease resistance. Conclusions: This paper presented a comprehensive overview of the crucial roles that NAC transcription factors play in regulating plant disease resistance through their involvement in diverse signaling pathways, acting as either positive or negative regulators, and thus provided references for further research on NAC transcription factors. [ABSTRACT FROM AUTHOR]

Neurofeedback, when combined with cognitive reappraisal, offers promising potential for emotion regulation training. However, prior studies have predominantly relied on functional magnetic resonance imaging, which could impede its clinical feasibility. Furthermore, these studies have primarily focused on reducing negative emotions while overlooking the importance of enhancing positive emotions. In our current study, we developed a novel electroencephalogram (EEG) neurofeedback-guided cognitive reappraisal training protocol for emotion regulation. We recruited forty-two healthy subjects (20 females; 22.4 ± 2.2 years old) who were randomly assigned to either the neurofeedback group or the control group. We evaluated the efficacy of this newly proposed neurofeedback training approach in regulating emotions evoked by pictures with different valence levels (low positive and high negative). Initially, we trained an EEG-based emotion decoding model for each individual using offline data. During the training process, we calculated the subjects' real-time self-regulation performance based on the decoded emotional states and fed it back to the subjects as feedback signals. Our results indicate that the proposed decoded EEG neurofeedback-guided cognitive reappraisal training protocol significantly enhanced emotion regulation performance for stimuli with low positive valence. Additionally, wavelet energy and differential entropy features in the high-frequency band played a crucial role in emotion classification and were associated with neural plasticity changes induced by emotion regulation. These findings validate the beneficial effects of the proposed EEG neurofeedback protocol and offer insights into the neural mechanisms underlying its training effects. This novel decoded neurofeedback training protocol presents a promising cost-effective and non-invasive treatment technique for emotion-related mental disorders. [ABSTRACT FROM AUTHOR]

Aluminum alloy is widely used in modern manufacturing industry but whose deformation when under certain regime of loading rates or temperature involves prominent Portevin–Le Chatelier (PLC) effect. In the present work the PLC effect in AA5052 aluminum alloy under different loading rates has been characterized via combined usage of digital image correlation (DIC) and acoustic emission (AE) techniques. Under the loading rates considered, different types of PLC bands have been found to yield distinct distribution of stress drops. The spatiotemporal evolution of the PLC bands at low loading rate may be accessible by both the DIC and AE techniques while those at high loading rates are accessible only by the AE technique. All the results may support that the PLC bands are nucleated rather than continuously propagating at high loading rates, which is in contrast to the conventionally held views. [ABSTRACT FROM AUTHOR]

Purpose: To compare performance of whole-body [68Ga]Ga-FAPI-04 and [18F]FDG PET imaging in the detection of Krukenberg tumors (KTs), primary site and extra-ovarian metastases of gastric signet-ring-cell carcinoma (GSRCC), and evaluate the value of [68Ga]Ga-FAPI-04 PET/MR imaging strategy and its potential impact on the management of KTs from GSRCC. Methods: Twelve patients with twenty-three KTs from GSRCC, who underwent both [68Ga]Ga-FAPI-04 pelvic PET/MR and whole-body [68Ga]Ga-FAPI-04 and [18F]FDG PET imaging were retrospectively analyzed. [68Ga]Ga-FAPI-04 and [18F]FDG uptakes were compared by using Wilcoxon signed-rank test or paired t test. McNemar's test was used to compare lesion detectability between two modalities. Two-tailed P<0.05 was considered statistically significant. Immunohistochemistry staining was utilized to analyze the fibroblast activation protein (FAP) expression in KTs. Results: A total of 12 patients with 23 KTs from GSRCC (8 synchronous and 4 metachronous) were evaluated. [68Ga]Ga-FAPI-04 was superior to [18F]FDG PET in detecting primary sites of GSRCC (100% [11/11] vs. 18.2% [2/11], p = 0.002), involved lymph nodes (90.9% [10/11] vs. 54.5% [6/11], p = 0.046) and peritoneal metastases (100% [12/12] vs. 41.7% [5/12], p = 0.008), with higher SUVmax and TBR (all p < 0.005). Both tracers had limited value in identifying KTs, with 100% false negative rate on [68Ga]Ga-FAPI-04 PET and a low detection rate of 8.7% on [18F]FDG PET. Fap immunohistochemistry showed negative or slight FAP expression in neoplastic signet ring cells and ovarian stroma. [68Ga]Ga-FAPI-04 PET/MR imaging strategy greatly improved the detection rate of Krukenberg tumors (87%, 20/23). After adding diffusion-weighted imaging (DWI), the detection rate was further improved (87.5% vs. 100%, p = 0.083). [68Ga]Ga-FAPI-04 PET/MR imaging strategy either upgraded TNM staging or changed treatment management in twelve patients. Conclusions: [68Ga]Ga-FAPI-04 PET outperformed [18F]FDG PET in detecting primary site and most extra-ovarian metastases of GSRCC, but both tracers had limited value in identifying Krukenberg tumors. Pelvis MRI should be applied to compensate the limitation of [68Ga]Ga-FAPI-04 PET imaging to identify Krukenberg tumours. The [68Ga]Ga-FAPI-04 PET/MR imaging strategy has the potential to impact treatment decisions for GSRCC patients with KTs. [ABSTRACT FROM AUTHOR]

Adhesive contact with the effect of tangential force may have important implications in friction and wear performances of small-sized devices and joining technologies. In the present work, adhesive contact involving tangential loading but before gross slip between spherical objects has been simulated through molecular dynamics (MD) to reveal the interaction between adhesion and the applied forces. When only the normal force is present, the results on force–displacement relationship and interfacial traction have been presented to compare with the predictions of Johnson–Kendall–Roberts (JKR), Maugis–Dugdale (M–D) and the Double–Hertz (D–H) models with the purpose of evaluating their applicability. In the presence of additional tangential forces, their interaction with adhesion has been studied in depth through loading and unloading. Distribution of the shear traction at the interface which is different from that in the existent models has been obtained. Those altogether may help to develop reasonable continuum models for adhesive contact under inclined forces. [ABSTRACT FROM AUTHOR]

Variation in emitted particle sizes between sources offers potential for source identification. Seven thousand two hundred particle size distributions collected in a single-family home were categorized into four classes: (1) smoking, (2) cooking, (3) household cleaning, and (4) background (no source). We created a multi-class classifier (neural network) to predict the presence of these three source types and background air. Number, surface, and volume concentration profiles (each with 16 particle size bins from 0.3 to 10 µm) were used as input features. Surface or volume concentration profiles were better predictors than number concentration profiles; accuracy was highest when concatenating the number, surface, and volume profiles (48 features). The model achieved ~ 98% accuracy in predicting the four classes when using a 10-unit hidden layer for the 48 input features (compared to ~ 66% for multinomial logistic regression). Smoking has the highest F-score among the four classes (0.999). We applied the model to time series of size-resolved concentrations for three successive indoor particle emissions (pan frying food, sweeping the floor, and smoldering marijuana). Time-varying probabilities of the four classes were visualized. We examined the effects of source, space, ventilation, and temperature/relative humidity on source identification. Using training examples from the single-family home, the model reasonably predicted smoking in another residence under different indoor settings (accuracies > 96%). This study applied, for the first time, the neural network method to identify patterns across different particle size distribution types (number, surface, and volume). It demonstrates the potential of using machine learning for source recognition of transient indoor aerosol emissions (e.g., identifying smoking in a rental property). [ABSTRACT FROM AUTHOR]

We compare the performance of photovoltaic (PV), flat-plate and evacuated-tube solar-thermal (ST), and hybrid photovoltaic-thermal (PV-T) collectors to meet the energy demands of multi-effect distillation (MED) desalination plants across four locations. We consider three scales: 1700 m3day−1, 120 m3day−1 and 3 m3day−1. We find a strong dependence of the capacity and configuration of the solar collectors on both the cost of sourcing electricity from the grid and the specific collector employed. We find specific costs as low as 7.8, 3.4 and 3.7 USDm−3 for the three plant capacities. We find that solar-driven systems optimised for the lowest specific cost result in CO2eq emissions equal to, or higher than, those from grid-driven reverse osmosis (RO) and in line with PV-RO. This highlights the need to consider the environmental footprint of these systems to ensure that desalination is in line with the United Nations' Sustainable Development Goal 6. [ABSTRACT FROM AUTHOR]

Recognizing human emotions from complex, multivariate, and non-stationary electroencephalography (EEG) time series is essential in affective brain-computer interface. However, because continuous labeling of ever-changing emotional states is not feasible in practice, existing methods can only assign a fixed label to all EEG timepoints in a continuous emotion-evoking trial, which overlooks the highly dynamic emotional states and highly non-stationary EEG signals. To solve the problems of high reliance on fixed labels and ignorance of time-changing information, in this paper we propose a time-aware sampling network (TAS-Net) using deep reinforcement learning (DRL) for unsupervised emotion recognition, which is able to detect key emotion fragments and disregard irrelevant and misleading parts. Specifically, we formulate the process of mining key emotion fragments from EEG time series as a Markov decision process and train a time-aware agent through DRL without label information. First, the time-aware agent takes deep features from a feature extractor as input and generates sample-wise importance scores reflecting the emotion-related information each sample contains. Then, based on the obtained sample-wise importance scores, our method preserves top-X continuous EEG fragments with relevant emotion and discards the rest. Finally, we treat these continuous fragments as key emotion fragments and feed them into a hypergraph decoding model for unsupervised clustering. Extensive experiments are conducted on three public datasets (SEED, DEAP, and MAHNOB-HCI) for emotion recognition using leave-one-subject-out cross-validation, and the results demonstrate the superiority of the proposed method against previous unsupervised emotion recognition methods. The proposed TAS-Net has great potential in achieving a more practical and accurate affective brain-computer interface in a dynamic and label-free circumstance. [ABSTRACT FROM AUTHOR]

Depression is a major psychological disorder with a growing impact worldwide. Traditional methods for detecting the risk of depression, predominantly reliant on psychiatric evaluations and self-assessment questionnaires, are often criticized for their inefficiency and lack of objectivity. Advancements in deep learning have paved the way for innovations in depression risk detection methods that fuse multimodal data. This paper introduces a novel framework, the Audio, Video, and Text Fusion-Three Branch Network (AVTF-TBN), designed to amalgamate auditory, visual, and textual cues for a comprehensive analysis of depression risk. Our approach encompasses three dedicated branches—Audio Branch, Video Branch, and Text Branch—each responsible for extracting salient features from the corresponding modality. These features are subsequently fused through a multimodal fusion (MMF) module, yielding a robust feature vector that feeds into a predictive modeling layer. To further our research, we devised an emotion elicitation paradigm based on two distinct tasks—reading and interviewing—implemented to gather a rich, sensor-based depression risk detection dataset. The sensory equipment, such as cameras, captures subtle facial expressions and vocal characteristics essential for our analysis. The research thoroughly investigates the data generated by varying emotional stimuli and evaluates the contribution of different tasks to emotion evocation. During the experiment, the AVTF-TBN model has the best performance when the data from the two tasks are simultaneously used for detection, where the F1 Score is 0.78, Precision is 0.76, and Recall is 0.81. Our experimental results confirm the validity of the paradigm and demonstrate the efficacy of the AVTF-TBN model in detecting depression risk, showcasing the crucial role of sensor-based data in mental health detection. [ABSTRACT FROM AUTHOR]

EEG neurofeedback using frontal alpha asymmetry (FAA) has been widely used for emotion regulation, but its effectiveness is controversial. Studies indicated that individual differences in neurofeedback training can be traced to neuroanatomical and neurofunctional features. However, they only focused on regional brain structure or function and overlooked possible neural correlates of the brain network. Besides, no neuroimaging predictors for FAA neurofeedback protocol have been reported so far. We designed a single-blind pseudo-controlled FAA neurofeedback experiment and collected multimodal neuroimaging data from healthy participants before training. We assessed the learning performance for evoked EEG modulations during training (L1) and at rest (L2), and investigated performance-related predictors based on a combined analysis of multimodal brain networks and graph-theoretical features. The main findings of this study are described below. First, both real and sham groups could increase their FAA during training, but only the real group showed a significant increase in FAA at rest. Second, the predictors during training blocks and at rests were different: L1 was correlated with the graph-theoretical metrics (clustering coefficient and local efficiency) of the right hemispheric gray matter and functional networks, while L2 was correlated with the graph-theoretical metrics (local and global efficiency) of the whole-brain and left the hemispheric functional network. Therefore, the individual differences in FAA neurofeedback learning could be explained by individual variations in structural/functional architecture, and the correlated graph-theoretical metrics of learning performance indices showed different laterality of hemispheric networks. These results provided insight into the neural correlates of inter-individual differences in neurofeedback learning. [ABSTRACT FROM AUTHOR]

Digital twin network (DTN) as an emerging network paradigm, have garnered growing attention. For large-scale networks, a crucial problem is how to effectively map physical networks onto the infrastructure platform of DTN. To address this issue, we propose a heuristic method of the adaptive boundary whale optimization algorithm (ABWOA) to solve the digital twin network construction problem, improving the efficiency and reducing operational costs of DTN. Extensive comparison experiments are conducted between ABWOA and various algorithms such as genetic algorithm, particle swarm optimization, artificial bee colony, differential evolution algorithm, moth search algorithm and original whale optimization algorithm. The experimental results show that ABWOA is superior to other algorithms in terms of solution quality, convergence speed, and time cost. It can solve the digital twin network construction problem more effectively. [ABSTRACT FROM AUTHOR]

Background and purpose: The pre-surgical estimation of lymph node (LN) metastasis in colorectal cancer (CRC) poses a significant diagnostic predicament. The associations between LN morphology, density, and metabolic heterogeneity and LN metastasis status in CRCs have been seldomly examined through the lens of radiomics. This research aimed to assess 2-[18F]FDG PET-based quantification of intratumoral metabolic heterogeneity for predicting lymph node metastasis in patients with colorectal cancer. Materials and methods: The construction of the model utilized data from 264 CRC patients, all of whom underwent preoperative 2-[18F]FDG PET/CT. Radiomic features were extracted from PET and CT images of LNs. Least absolute shrinkage and selection operator (LASSO) regression was implemented for selecting pertinent imaging features with a tenfold cross-validation. The predictive accuracy for LN metastasis status was juxtaposed against traditional methodologies (comprising CT-reported LN status and PET/CT-reported LN status) by deploying the receiver operating characteristic (ROC) curve analysis. The radiomics signature was evaluated based on discrimination, calibration, and clinical utility parameters. The model was further subjected to validation using an independent cohort of 132 patients from the period of January 2012 to June 2020. Results: The radiomics model was composed of eight significant radiomic features (five from PET and three from CT), encapsulating metabolic and density heterogeneity. The radiomics signature (area under the curve (AUC), 0.908) showcased a significantly superior performance compared to CT-reported LN status (AUC, 0.563, P < 0.001) and PET/CT-reported LN status (AUC, 0.64, P < 0.001) for predicting LN-positive or LN-negative status. The radiomics signature (AUC, 0.885) also showcased a significantly superior performance compared to CT-reported LN status (AUC, 0.587, P < 0.001) and PET/CT-reported LN status (AUC, 0.621, P < 0.001) to identify N1 and N2. This signature maintained its independence from clinical risk factors and exhibited robustness in the validation test set. Decision curve analysis attested to the clinical utility of the radiomics signature. Conclusions: The radiomics signature based on 2-[18F]FDG PET/CT, which derived image features directly from LNs irrespective of clinical risk factors, displayed enhanced diagnostic performance compared to conventional CT or PET/CT-reported LN status. This allows for the identification of pre-surgical LN metastasis status and facilitates a patient-specific prediction of LN metastasis status in CRC patients. [ABSTRACT FROM AUTHOR]

Affective brain-computer interface based on electroencephalography (EEG) is an important branch in the field of affective computing. However, the individual differences in EEG emotional data and the noisy labeling problem in the subjective feedback seriously limit the effectiveness and generalizability of existing models. To tackle these two critical issues, we propose a novel transfer learning framework with Prototypical Representation based Pairwise Learning (PR-PL). The discriminative and generalized EEG features are learned for emotion revealing across individuals and the emotion recognition task is formulated as pairwise learning for improving the model tolerance to the noisy labels. More specifically, a prototypical learning is developed to encode the inherent emotion-related semantic structure of EEG data and align the individuals’ EEG features to a shared common feature space under consideration of the feature separability of both source and target domains. Based on the aligned feature representations, pairwise learning with an adaptive pseudo labeling method is introduced to encode the proximity relationships among samples and alleviate the label noises effect on modeling. Extensive results on two benchmark databases (SEED and SEED-IV) under four different cross-validation evaluation protocols validate the model reliability and stability across subjects and sessions. Compared to the literature, the average enhancement of emotion recognition across four different evaluation protocols is 2.04% (SEED) and 2.58% (SEED-IV). [ABSTRACT FROM AUTHOR]

Morphologically, cell death can be divided into apoptosis and necrosis. Apoptosis, which is a type of regulated cell death, is well tolerated by the immune system and is responsible for hemostasis and cellular turnover under physiological conditions. In contrast, necrosis is defined as a form of passive cell death that leads to a dramatic inflammatory response (also referred to as necroinflammation) and causes organ dysfunction under pathological conditions. Recently, a novel form of cell death named regulated necrosis (such as necroptosis, pyroptosis, and ferroptosis) was discovered. Distinct from apoptosis, regulated necrosis is modulated by multiple internal or external factors, but meanwhile, it results in inflammation and immune response. Accumulating evidence has indicated that regulated necrosis is associated with multiple diseases, including diabetes. Diabetes is characterized by hyperglycemia caused by insulin deficiency and/or insulin resistance, and long-term high glucose leads to various diabetes-related complications. Here, we summarize the mechanisms of necroptosis, pyroptosis, and ferroptosis, and introduce recent advances in characterizing the associations between these three types of regulated necrosis and diabetes and its complications. [ABSTRACT FROM AUTHOR]

Aims: Recently, exosomal miRNAs have been shown to play important roles in multiple diseases, including type 1 diabetes (T1D). To assess the biomarker potential of exosomal miRNAs for T1D, we measured the expression profiles of plasma‐derived exosomal miRNAs in T1D and explored their potential functions by bioinformatic analysis. Materials and methods: In the discovery phase, exosome samples were isolated from plasma by size exclusion chromatography from 10 T1D patients and 10 sex‐ (p = 0.36), age‐ (p = 0.97), and body mass index‐matched (p = 0.47) healthy control subjects. Exosomal miRNA expression profiles were measured using the Illumina NovaSeq 6000 platform. With verification by quantitative real‐time PCR (qRT‒PCR), we used multiple bioinformatics approaches to explore the potential biological functions of the identified differentially expressed miRNAs. The diagnostic signature of exosomal miRNAs was evaluated by least absolute shrinkage and selection operator (LASSO) regression and evaluated based on the area under the receiver operating characteristic curve (AUC). Results: In total, 43 differentially expressed miRNAs, among which 34 were upregulated and 9 were downregulated, were identified in T1D. After correcting for multiple testing using false discovery rate, 11 identified exosomal miRNAs still showed statistical significance. Among the 5 selected miRNAs, 3 miRNAs (miR‐103a‐3p, miR‐144‐5p and miR‐454‐3p) were successfully validated by qRT‒PCR. The biological analysis‐enriched terms included protein autophosphorylation and the Hedgehog signalling pathway. The highest AUC of exosomal miRNA was 0.889 under the LASSO model. The expression levels of 5 selected exosomal miRNAs were correlated with multiple clinical characteristics such as fasting C‐peptide and postprandial C‐peptide. Conclusions: Our results indicated that plasma‐derived exosomal miRNAs could serve as promising diagnostic biomarkers of T1D. [ABSTRACT FROM AUTHOR]

Software-Defined Networking (SDN) has emerged as an innovative networking method that offers effective management and remarkable flexibility. However, current SDN-based solutions primarily focus on static networks or concentrate on backbone networks, where network dynamics have minimal impact. The existing methods for placing flow entries in Software-Defined Networking (SDN)-based Internet of Things (IoT) systems exhibit shortcomings in accurately predicting outcomes and efficiently reducing table misses and associated performance metrics. This research introduces a new approach, specifically the mobility-aware adaptive flow entry placement scheme for SDN-based Internet of Things (IoT) environments, to address the mobility aspect of networks. The proposed scheme utilizes the Q-learning algorithm to predict the next possible location of end devices, while the cost-sensitive AdaBoost algorithm is employed to select heavy and active flows. As a result, efficient flow rules for incoming flows can be dynamically implemented without controller intervention. Extensive computer simulations demonstrate that this approach significantly enhances match probability and prediction accuracy while concurrently reducing the number of table misses and resource expenditure compared to existing schemes. [ABSTRACT FROM AUTHOR]

Background: Inflammatory response triggered by innate immunity plays a pivotal element in the progress of ischemic stroke. Receptor-interacting kinase 2 (RIP2) is implicated in maintaining immunity homeostasis and regulating inflammatory response. However, the underlying mechanism of RIP2 in ischemic stroke is still not well understood. Hence, the study investigated the role and the ubiquitination regulatory mechanism of RIP2 in ischemic stroke. Methods: Focal cerebral ischemia was introduced by middle cerebral artery occlusion (MCAO) in wild-type (WT) and OTUD1-deficient (OTUD1−/−) mice, oxygen glucose deprivation and reoxygenation (OGD/R) models in BV2 cells and primary cultured astrocytes were performed for monitoring of experimental stroke. GSK2983559 (GSK559), a RIP2 inhibitor was intraventricularly administered 30 min before MCAO. Mice brain tissues were collected for TTC staining and histopathology. Protein expression of RIP2, OTUD1, p-NF-κB–p65 and IκBα was determined by western blot. Localization of RIP2 and OTUD1 was examined by immunofluorescence. The change of IL-1β, IL-6 and TNF-α was detected by ELISA assay and quantitative real-time polymerase chain reaction. Immunoprecipitation and confocal microscopy were used to study the interaction of RIP2 and OTUD1. The activity of NF-κB was examined by dual-luciferase assay. Results: Our results showed upregulated protein levels of RIP2 and OTUD1 in microglia and astrocytes in mice subjected to focal cerebral ischemia. Inhibition of RIP2 by GSK559 ameliorated the cerebral ischemic outcome by repressing the NF-κB activity and the inflammatory response. Mechanistically, OTUD1 interacted with RIP2 and sequentially removed the K63-linked polyubiquitin chains of RIP2, thereby inhibiting NF-κB activation. Furthermore, OTUD1 deficiency exacerbated cerebral ischemic injury in response to inflammation induced by RIP2 ubiquitination. Conclusions: These findings suggested that RIP2 mediated cerebral ischemic lesion via stimulating inflammatory response, and OTUD1 ameliorated brain injury after ischemia through inhibiting RIP2-induced NF-κB activation by specifically cleaving K63-linked ubiquitination of RIP2. [ABSTRACT FROM AUTHOR]

Background: Atypical speech prosody has been commonly found among autistic children. Yet it remains unknown whether prosody impairment originates from poor pitch ability in general or whether it is the result of the difficulty in understanding and using prosody for communicative purposes. Aims: To investigate whether native Mandarin Chinese‐speaking autistic children with intellectual impairment were able to accurately produce native lexical tones, which are pitch patterns that distinguish word meaning lexically and serve little social purpose. Methods & Procedures: Using a picture‐naming task, thirteen 8–13‐year‐old Mandarin Chinese‐speaking autistic children with intellectual impairment were tested on their production of Chinese lexical tones. Chronical age‐matched typically developing (TD) children were included as the control group. Perceptual assessment and phonetic analyses were conducted with the produced lexical tones. Outcomes & Results: The majority of the lexical tones produced by the autistic children were perceived as accurate by adult judges. Phonetic analysis of the pitch contours found no significant difference between the two groups, and the autistic children and TD children used the phonetic features in comparable ways when differentiating the lexical tones. However, the lexical tone accuracy rate was lower among the autistic children than among the TDs, and the larger individual difference was observed among the autistic children than the TD children. Conclusions & Implications: These results indicate that autistic children are able to produce the global contours of the lexical tones, and pitch deficits do not seem to qualify as a core feature of autism. What this paper adds: What is already known on the subject: Atypical prosody has been considered a maker of the speech of autistic children, and meta‐analysis found a significant difference in mean pitch and pitch range between TD children and autistic children. Yet it remains unknown whether the pitch deficits are the result of impaired perceptual–motoric ability or if they reflect failure in learning sentential prosody, which requires an understanding of the interlocutors' mind. In addition, research on pitch ability of autistic children with intellectual disabilities has been scarce, and whether these children are able to produce pitch variation is largely unknown. What this paper adds to existing knowledge: We tested native Mandarin Chinese autistic children with intellectual impairment on their production of native lexical tones. The lexical tones in Chinese are pitch variations realized on individual syllables that distinguish lexical meaning, but they do not serve social pragmatic purposes. We found that although these autistic children had only developed limited spoken language, the majority of their lexical tones were perceived as accurate. They were able to use the phonetic features in comparable ways with the TD children when distinguishing the lexical tones. What are the potential or actual clinical implications of this work?: It seems unlikely that pitch processing at the lexical level is fundamentally impaired in autistic children, and pitch deficits do not seem to qualify for a core feature of their speech. Practitioners should be cautious when using pitch production as a clinical marker for autistic children. [ABSTRACT FROM AUTHOR]

Aims: Idiopathic type 1 diabetes (T1D) is a neglected subtype of T1D. Our aim was to investigate the frequency, clinical characteristics, and human leucocyte antigen (HLA) genotypes of idiopathic T1D. Methods: We enrolled 1205 newly diagnosed T1D patients in our analysis. To exclude monogenic diabetes in autoantibody‐negative patients, we utilised a custom monogenic diabetes gene panel. Individuals negative for autoantibodies and subsequently excluded for monogenic diabetes were diagnosed with idiopathic T1D. We collected clinical characteristics, measured islet autoantibodies by radioligand assay and obtained HLA data. Results: After excluding 11 patients with monogenic diabetes, 284 cases were diagnosed with idiopathic T1D, accounting for 23.8% (284/1194) of all newly diagnosed T1D cases. When compared with autoimmune T1D, idiopathic T1D patients showed an older onset age, higher body mass index among adults, lower haemoglobin A1c, higher levels of fasting C‐peptide and 2‐h postprandial C‐peptide, and were likely to have type 2 diabetes (T2D) family history and carry 0 susceptible HLA haplotype (all p < 0.01). A lower proportion of individuals carrying 2 susceptible HLA haplotypes in idiopathic T1D was observed in the adult‐onset subgroup (15.7% vs. 38.0% in child‐onset subgroup, p < 0.001) and in subgroup with preserved beta‐cell function (11.0% vs. 30.1% in subgroup with poor beta‐cell function, p < 0.001). Multivariable correlation analyses indicated that being overweight, having T2D family history and lacking susceptible HLA haplotypes were associated with negative autoantibodies. Conclusions: Idiopathic T1D represents about 1/4 of newly diagnosed T1D, with adult‐onset and preserved beta‐cell function patients showing lower HLA susceptibility and more insulin resistance. [ABSTRACT FROM AUTHOR]

Numerous studies of perceptual decision-making have shown that lower prestimulus alpha power leads to a higher hit rate in visual detection, which is believed to correlate with the top-down control. However, whether frontal-occipital phase synchronization underlying the top-down control could impact the occipital alpha power that directly affects the perceptual performance remains unclear. In this study, we used analyses of the general linear mixed model (GLMM) and event-related potentials (ERPs) to show that the prestimulus alpha power over the occipital area directly affected visual perception. Using both the univariate and multivariate methods, we found that low-frequency (4–30 Hz) frontal-occipital phase synchronization predicted the prestimulus alpha power over the occipital area. Overall, our results suggested that frontal-occipital phase synchronization could predict occipital alpha power that directly affects perceptual decision-making. [ABSTRACT FROM AUTHOR]

Background: Chrysanthemum Fusarium wilt is a common fungal disease caused by Fusarium oxysporum, which causes continuous cropping obstacles and huge losses to the chrysanthemum industry. The defense mechanism of chrysanthemum against F. oxysporum remains unclear, especially during the early stages of the disease. Therefore, in the present study, we analyzed chrysanthemum 'Jinba' samples inoculated with F. oxysporum at 0, 3, and 72 h using RNA-seq. Results: The results revealed that 7985 differentially expressed genes (DEGs) were co-expressed at 3 and 72 h after F. oxysporum infection. We analyzed the identified DEGs using Kyoto Encyclopedia of Genes and Genomes and Gene Ontology. The DEGs were primarily enriched in "Plant pathogen interaction", "MAPK signaling pathway", "Starch and sucrose metabolism", and "Biosynthesis of secondary metabolites". Genes related to the synthesis of secondary metabolites were upregulated in chrysanthemum early during the inoculation period. Furthermore, peroxidase, polyphenol oxidase, and phenylalanine ammonia-lyase enzymes were consistently produced to accumulate large amounts of phenolic compounds to resist F. oxysporum infection. Additionally, genes related to the proline metabolic pathway were upregulated, and proline levels accumulated within 72 h, regulating osmotic balance in chrysanthemum. Notably, the soluble sugar content in chrysanthemum decreased early during the inoculation period; we speculate that this is a self-protective mechanism of chrysanthemums for inhibiting fungal reproduction by reducing the sugar content in vivo. In the meantime, we screened for transcription factors that respond to F. oxysporum at an early stage and analyzed the relationship between WRKY and DEGs in the "Plant-pathogen interaction" pathway. We screened a key WRKY as a research target for subsequent experiments. Conclusion: This study revealed the relevant physiological responses and gene expression changes in chrysanthemum in response to F. oxysporum infection, and provided a relevant candidate gene pool for subsequent studies on chrysanthemum Fusarium wilt. [ABSTRACT FROM AUTHOR]

Most solar energy incident (>70%) upon commercial photovoltaic panels is dissipated as heat, increasing their operating temperature, and leading to significant deterioration in electrical performance. The solar utilisation efficiency of commercial photovoltaic panels is typically below 25%. Here, we demonstrate a hybrid multi-generation photovoltaic leaf concept that employs a biomimetic transpiration structure made of eco-friendly, low-cost and widely-available materials for effective passive thermal management and multi-generation. We demonstrate experimentally that bio-inspired transpiration can remove ~590 W/m2 of heat from a photovoltaic cell, reducing the cell temperature by ~26 °C under an irradiance of 1000 W/m2, and resulting in a relatively 13.6% increase in electrical efficiency. Furthermore, the photovoltaic leaf is capable of synergistically utilising the recovered heat to co-generate additional thermal energy and freshwater simultaneously within the same component, significantly elevating the overall solar utilisation efficiency from 13.2% to over 74.5%, along with over 1.1 L/h/m2 of clean water. Most sunlight received by photovoltaic panels is converted to and lost as heat, increasing their temperature and deteriorating their performance. Here, the authors propose a multi-energy generation photovoltaic leaf concept with biomimetic transpiration and demonstrate much improved performance. [ABSTRACT FROM AUTHOR]

Bone is a highly vascularized tissue, and the ability of magnesium (Mg) to promote osteogenesis and angiogenesis has been widely studied. The aim of bone tissue engineering is to repair bone tissue defects and restore its normal function. Various Mg-enriched materials that can promote angiogenesis and osteogenesis have been made. Here, we introduce several types of orthopedic clinical uses of Mg; recent advances in the study of metal materials releasing Mg ions (pure Mg, Mg alloy, coated Mg, Mg-rich composite, ceramic, and hydrogel) are reviewed. Most studies suggest that Mg can enhance vascularized osteogenesis in bone defect areas. Additionally, we summarized some research on the mechanisms related to vascularized osteogenesis. In addition, the experimental strategies for the research of Mg-enriched materials in the future are put forward, in which clarifying the specific mechanism of promoting angiogenesis is the crux. [ABSTRACT FROM AUTHOR]

Objectives: To investigate changes in brain‐glucose metabolism in anti‐N‐methyl‐D‐aspartate receptor (NMDAR) encephalitis, and compare results with MRI and electroencephalography (EEG) findings at different disease stages. Methods: The clinical data of 18 patients (median age, 35 years; 11 men) were retrospectively collected. Patients were divided into groups based on the time of symptom onset to examination, (≤1 month, >1 but ≤3 months, >3 months). Two‐sample t‐test results were compared with age and sex‐paired healthy controls using statistical parametric mapping and verified using a NeuroQ software normal database with a discriminating z‐score of 2. Results: Abnormal patterns on FDG‐PET differed over time (T = 3.21–8.74, Z = 2.68–4.23, p < 0.005). Regional analysis showed hypometabolic left middle or medial frontal cortex in 4/5, 5/7, and 5/6 patients, respectively. Time‐subgroup analysis revealed hypermetabolic supertemporal cortex in 4/5, 5/7, and 2/6, patients, respectively. MRI and EEG abnormalities in any region and stage occurred in 10/18 and 10/16 patients, respectively. MRI and EEG time‐subgroup analysis showed abnormalities in 5/9, 4/5, and 1/4, and 1/3, 6/7, and 3/6 patients, respectively. Abnormal temporal lobes were detected most frequently in MRI analyses and occurred in 3/10 patients. Conclusions: Decreased left middle/medial frontal metabolism could be common to all stages. Metabolism in other regions, MRI, and EEG results were associated with the progression of anti‐NMDAR encephalitis. The sensitivity rate of FDG‐PET was superior to that of MRI and EEG. [ABSTRACT FROM AUTHOR]

Objects: To evaluate the prognostic value of radiomics features extracted from 18F-FDG-PET/CT images and integrated with clinical characteristics and conventional PET/CT metrics in newly diagnosed multiple myeloma (NDMM) patients. Methods: We retrospectively reviewed baseline clinical information and 18F-FDG-PET/CT imaging data of MM patients with 18F-FDG-PET/CT. Multivariate Cox regression models involving different combinations were constructed, and stepwise regression was performed: (1) radiomics features of PET/CT alone (Rad Model); (2) Using clinical data (including clinical/laboratory parameters and conventional PET/CT metrics) only (Cli Model); (3) Combination radiomics features and clinical data (Cli-Rad Model). Model performance was evaluated by C-index and Net Reclassification Index (NRI). Results: Ninety-eight patients with NDMM who underwent 18F-FDG-PET/CT between 2014 and 2019 were included in this study. Combining radiomics features from PET/CT with clinical data showed higher prognostic performance than models with radiomics features or clinical data alone (C-index 0.790 vs. 0.675 vs. 0.736 in training cohort; 0.698 vs. 0.651 vs. 0.563 in validation cohort; AUC 0.761, sensitivity 56.7%, specificity 85.7%, p < 0.05 in training cohort and AUC 0.650, sensitivity 80.0%, specificity78.6%, p < 0.05 in validation cohort) When clinical data was combined with radiomics, an increase in the performance of the model was observed (NRI > 0). Conclusions: Radiomics features extracted from the PET and CT components of baseline 18F-FDG-PET/CT images may become an effective complement to provide prognostic information; therefore, radiomics features combined with clinical characteristic may provide clinical value for MM prognosis prediction. [ABSTRACT FROM AUTHOR]

Aims: This study investigated insulinoma‐associated‐2 autoantibody (IA‐2A) and zinc transporter 8 autoantibody (ZnT8A) distribution in patients with type 1 diabetes (T1D) and latent autoimmune diabetes (LAD) and the autoantibodies' association with clinical characteristics and HLA‐DR‐DQ genes. Materials and Methods: This cross‐sectional study recruited 17,536 patients with diabetes from 46 hospitals across China. A total of 189 patients with T1D and 58 patients with LAD with IA‐2A positivity, 126 patients with T1D and 86 patients with LAD with ZnT8A positivity, and 231 patients with type 2 diabetes (T2D) were selected to evaluate islet autoantibodies, clinical phenotypes, and HLA‐DR‐DQ gene frequency. Results: IA‐2A was bimodally distributed in patients with T1D and LAD. Patients with low IA‐2A titre LAD had lower fasting C‐peptide (FCP) (p < 0.01), lower postprandial C‐peptide (PCP) (p < 0.001), and higher haemoglobin A1c (HbA1c) levels (p < 0.05) than patients with T2D. Patients with high IA‐2A titre LAD were younger than patients with low IA‐2A titre LAD (p < 0.05). Patients with low IA‐2A titre T1D had lower FCP (p < 0.01), lower PCP (p < 0.01), and higher HbA1c levels (p < 0.05) than patients with high IA‐2A titre LAD. HLA‐DR‐DQ genetic analysis demonstrated that the frequency of susceptible HLA haplotypes was higher in IA‐2A‐positive patients (p < 0.001) than in patients with T2D. Patients with high ZnT8A titre LAD had lower FCP (p = 0.045), lower PCP (p = 0.023), and higher HbA1c levels (p = 0.009) and a higher frequency of total susceptible haplotypes (p < 0.001) than patients with low ZnT8A titre LAD. Conclusions: IA‐2A in patients with T1D and LAD was bimodally distributed, and the presence of IA‐2A could demonstrate partial LAD clinical characteristics. ZnT8A titre had a certain predictive value for islet functions in patients with LAD. [ABSTRACT FROM AUTHOR]

Aim: To investigate the impact of family history of type 2 diabetes (T2D) on the clinical phenotypes of patients with idiopathic type 1 diabetes (T1D). Methods: In clinically diagnosed T1D cases, a total of 335 idopathic T1D patients were included in the study, after excluding autoimmune T1D using islet autoantibody testing and monogenic diabetes using a custom monogenic diabetes gene panel obtained from clinically diagnosed T1D cases. A semi‐structured questionnaire was used to collect information on the presence of T2D in first‐degree relatives. The demographic and metabolic markers of idiopathic T1D patients were analysed. Subgroup analysis was performed to investigate potential interactions between T2D family history and human leukocyte antigen (HLA) genotypes. Results: A total of 18.2% of individuals with idiopathic T1D had a T2D family history, and these individuals were more likely to have features associated with T2D, such as older age of onset, higher body mass index at diagnosis, lower insulin dosage and better beta‐cell function, as indicated by higher levels of fasting C‐peptide and 2‐hour postprandial C‐peptide (all P < 0.05). Additionally, regardless of HLA susceptible genotypes, the impact of family history of T2D was consistently observed in idiopathic T1D patients. Multivariable analyses showed that T2D family history was negatively correlated with the risk of beta‐cell function failure in idiopathic T1D patients (P < 0.05). Conclusions: Family history of T2D may be implicated in the heterogeneity of idiopathic T1D patients. [ABSTRACT FROM AUTHOR]

The choice of an appropriate fuel can effectively prolong the refueling cycle of a reactor core. The Th-U cycle and U-Pu cycle are commonly used fuel breeding cycles. Oxide fuels, nitride fuels, and metal fuels are the primary candidate fuels for lead-based reactors. For fuel selection, a core model of a 60 MWt reactor was established. The results show that the breeding performance of the breeding fuel Th-232 is better than that of U-238, and the driving performance of the driving fuel Pu-239 is better than that of U-235. Therefore, PuO2-ThO2, PuN-ThN, and Pu-Th-Zr fuels may have good performance. By comparing the reactivity loss of three types of fuel, it was found that the reactivity loss of PuN-ThN fuel is the smallest. Hence, using PuN-ThN fuel as a core fuel can result in a longer refueling cycle. On this basis, PuN-ThN fuel was used in the preliminary design of the 120 MWt core physical model. It can be seen that when PuN-ThN fuel is used as the core fuel, a smaller reactivity swing (1408 pcm), smaller power peak factor, and super long refueling cycle (more than 30 years) can be obtained. [ABSTRACT FROM AUTHOR]

Background: Facial paralysis is a common clinical disease, it was named intractable facial paralysis when the clinical course more than 2 months. Intractable facial paralysis will produce anxiety and depression, which will seriously affect patients' life and work. Electric acupuncture has been widely used in the treatment of intractable facial paralysis. However, the results of clinical studies on the efficacy and safety have been inconsistent. This study aims to evaluate the efficacy and safety of electric acupuncture for intractable facial paralysis patients by systematic review and meta-analysis, so as to provide clinical decision-making based on evidence-based medicine. Methods: The following databases will be searched by electronic methods: PubMed, Embase, Cochrane Library, Chinese National Knowledge Infrastructure, VIP Database, Wan-fang Data and Chinese Biomedical Database. All of them will be retrieved from the establishment date of the electronic database to March 2022, all included studies will be evaluated risk of bias by the Cochrane Handbook. The total effective rate will be the primary outcome. The systematic review will be conducted with the use of the RevMan5.3 software in this study. Results: This study will obtain efficacy and safety of electric acupuncture for the treatment of intractable facial paralysis. Discussion: This study will provide clinical decision-making based on evidence-based medicine that whether electric acupuncture could be used to treat intractable facial paralysis, and when and how it might be more effective and safety. It will help standardize electric acupuncture treatment strategies for intractable facial paralysis. PROSPERO registration number: CRD42021278541. [ABSTRACT FROM AUTHOR]

Multi-objective particle swarm optimization (MOPSO) algorithms based on angle preference provide a set of preferred solutions by incorporating a user's preference. However, since the search mechanism is stochastic and asymmetric, traditional MOPSO based on angle preference are still easy to fall into local optima and lack enough selection pressure on excellent individuals. In this paper, an improved MOPSO algorithm based on angle preference called IAPMOPSO is proposed to alleviate those problems. First, to create a stricter partial order among the non-dominated solutions, reference vectors are established in the preference region, and the adaptive penalty-based boundary intersection (PBI) value is used to update the external archive. Second, to effectively alleviate the swarm to fall into local optima, an adaptive preference angle is designed to increase the diversity of the population. Third, neighborhood individuals are selected for each particle to update the individual optimum to increase the information exchange among the particles. With the proposed angle preference-based external archive update strategy, solutions with a smaller PBI are given higher priority to be selected, and thus the selection pressure on excellent individuals is enhanced. In terms of an increase in the diversity of the population, the adaptive preference angle adjustment strategy that gradually narrows the preferred area, and the individual optimum update strategy which updates the individual optimum according to the information of neighborhood individuals, are presented. The experimental results on the benchmark test functions and GEM data verify the effectiveness and efficiency of the proposed method. [ABSTRACT FROM AUTHOR]

The rising aging population, inequality of medical resources, and severe COVID-19 infection rate raise inevitable individual and social contradictions. One of the representative developing technologies, smart wearables, is dedicated to offering accurate personal healthcare. Nevertheless, energy constraints as well as unpredictable data transmission are critical in the development of wearable devices. In this regard, we investigate the key concerns of energy life and quality of service (QoS) for smart clothing. Unlike general wireless sensing networks (WSNs), the wireless body area network (WBAN) embedded in smart clothing is highly affected by human postural changes. In this article, we formulate the smart clothing with multiposture participated from two perspectives: 1) for energy life, we address the energy consumption, the energy harvested by the nodes, and the battery discharge and 2) the QoS involves the path loss and time delay. Moreover, five typical daily activity states have been discussed to model the impact of posture changes. Under the influence of the posture state, the tradeoff between the collected tribological electrical energy and the consumed energy is also presented in the article. We parameterize the path loss, transmission delay, energy consumption, and collection in each posture and integrally formulate the energy problem and QoS to a joint optimization problem. Particle swarm optimization (PSO), sine cosine algorithm (SCA), and Q-learning algorithm are adopted to optimize the overall cost, time delay, and energy consumption. In addition, a comparison of the battery power of the nodes is conducted. Simulation results show that each algorithm achieves certain optimization effects, for example, PSO, SCA, and Q-learning reduce total costs by 14%, 22%, and 30%, respectively. Q-learning is also effectively decreasing latency and energy consumption and improving battery life. [ABSTRACT FROM AUTHOR]

Aims: To investigate glycaemic variability (GV) patterns in patients with type 1 diabetes (T1D), type 2 diabetes (T2D), and latent autoimmune diabetes in adults (LADA). Materials and Methods: A total of 842 subjects (510 T1D, 105 LADA, 227 T2D) were enrolled and underwent 1 week of continuous glucose monitoring (CGM). Clinical characteristics and CGM parameters were compared among T1D, LADA, and T2D. LADA patients were divided into two subgroups based on glutamic acid decarboxylase autoantibody titres (≥180 U/mL [LADA‐1], <180 U/mL [LADA‐2]) and compared. The C‐peptide cut‐offs for predicting a coefficient of variation (CV) of glucose ≥36% and a time in range (TIR) > 70% were determined using receiver operating characteristic analysis. Results: Twenty‐seven patients (9 T1D, 18 T2D) were excluded due to insufficient CGM data. Sex, diabetes duration and HbA1c were comparable among the three groups. Fasting and 2‐h postprandial C‐peptide (FCP, 2hCP) increased sequentially across T1D, LADA, and T2D. T1D and LADA patients had comparable TIR and GV, whereas those with T2D had much higher TIR and lower GV (p < 0.001). The GV of LADA‐1 was close to that of T1D, while the GV of LADA‐2 was close to that of T2D. CP exhibited the strongest negative correlation with GV. The cut‐offs of FCP/2hCP for predicting a CV ≥ 36% and TIR >70% were 121.6/243.1 and 128.9/252.8 pmol/L, respectively. Conclusions: GV presented a continuous spectrum across T1D, LADA‐1, LADA‐2, and T2D. More frequent glucose monitoring is suggested for patients with impaired insulin secretion. Clinical Trail Registration: Chinese Clinical Trial Registration (ChiCTR) website approved by WHO; http://www.chictr.org.cn/ ‐ ChiCTR2200065036 [ABSTRACT FROM AUTHOR]

Backgrounds: Both exosome and circular RNA (circRNA) have been reported to participate in the pathogenesis of type 1 diabetes mellitus (T1DM). However, the exact role of exosomal circRNA in T1DM is largely unknown. Here, we identified the exosomal circRNA expression profiles in the plasma of T1DM patients and explored their potential function using bioinformatics analysis. Material and Methods. Exosomes were extracted by the size exclusion chromatography method from plasma of 10 T1DM patients and 10 age- and sex- matched control subjects. Illumina Novaseq6000 platform was used to detect the exosomal circRNA expression profiles. Multiple bioinformatics analysis was applied to investigate the potential biological functions of exosomal circRNAs.Results: A total of 784 differentially expressed exosomal circRNAs have been identified in T1DM patients, of which 528 were upregulated and 256 were downregulated. Gene Ontology analysis enriched terms such as protein ubiquitination involved in ubiquitin-dependent protein catabolic protein (GO:0042787), membrane (GO:0016020), and GTPase activator activity (GO:0005096). The most enriched pathway in Kyoto Encyclopedia of Genes and Genomes was ubiquitin-mediated proteolysis (ko04120). The miRNA-targeting prediction method was used to identify the miRNAs that bind to circRNAs, and circRNA-miRNA-mRNA pathways were constructed, indicating that interactions between circRNA, miRNA, and gene might be involved in the disease progression.Conclusions: The present study identified the exosomal circRNA expression profiles in T1DM for the first time. Our results threw novel insights into the molecular mechanisms of T1DM. [ABSTRACT FROM AUTHOR]

Type 1 diabetes (T1D) is a complex autoimmune disease characterized by an absolute deficiency of insulin. It affects more than 20 million people worldwide and imposes an enormous financial burden on patients. The underlying pathogenic mechanisms of T1D are still obscure, but it is widely accepted that both genetics and the environment play an important role in its onset and development. Previous studies have identified more than 60 susceptible loci associated with T1D, explaining approximately 80%‐85% of the heritability. However, most identified variants confer only small increases in risk, which restricts their potential clinical application. In addition, there is still a so‐called 'missing heritability' phenomenon. While the gap between known heritability and true heritability in T1D is small compared with that in other complex traits and disorders, further elucidation of T1D genetics has the potential to bring novel insights into its aetiology and provide new therapeutic targets. Many hypotheses have been proposed to explain the missing heritability, including variants remaining to be found (variants with small effect sizes, rare variants and structural variants) and interactions (gene–gene and gene–environment interactions; e.g. epigenetic effects). In the following review, we introduce the possible sources of missing heritability and discuss the existing related knowledge in the context of T1D. [ABSTRACT FROM AUTHOR]

Aim: To investigate the prevalence and clinical features of latent autoimmune diabetes in youth (LADY) diagnosed between 15 and 29 years old as a component of an age‐related autoimmune diabetes spectrum. Research Design and Methods: This nationwide, multicenter, cross‐sectional study continuously included 19,100 newly diagnosed diabetes patients over 15 years old across China. LADY patients were screened from 1803 subjects aged between 15 and 29 years old, with the type 2 diabetes (T2D) phenotype and positive autoantibodies against glutamic acid decarboxylase (GADA), insulinoma‐associated‐2 (IA‐2A) or zinc transporter‐8 (ZnT8A). The clinical features of LADY, including metabolic status, β‐cell function and insulin resistance, were investigated and compared with those of latent autoimmune diabetes in adults (LADA) identified from 17,297 other subjects over 30 years old. The age‐related characteristics of the latent autoimmune diabetes spectrum were explored. Results: A total of 135 subjects were diagnosed as LADY, accounting for 9.0% of the T2D phenotypic youth. Compared with autoantibody‐negative T2D patients, LADY patients had fewer metabolic syndrome, less insulin resistance and poorer β‐cell function, which were closely related to their autoantibody status (all p < 0.05). After stratifying LADA according to age, the GADA titer decreased across the LADY, "Y‐LADA" (young LADA, onset age < 60 years old) and "E‐LADA" (elderly LADA, onset age ≥ 60 years old) groups, while the prevalence of metabolic syndrome and level of β‐cell function increased (all p < 0.05). Conclusions: A high prevalence of LADY exists in youth with T2D phenotype. Latent autoimmune diabetes forms a continuous age‐related spectrum from LADY to LADA, in which LADY shows greater autoimmunity. [ABSTRACT FROM AUTHOR]

Polymorphisms rs231775 and rs3087243 of cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4) gene have been associated with risk of latent autoimmune diabetes in adults (LADA). However, the results were inconsistent. The purpose of this study was to quantitatively assess the relationship between polymorphisms rs231775 and rs3087243 of CTLA-4 and LADA in a larger pooled population by performing a meta-analysis. Systematic search for eligible studies was conducted in PubMed, Web of Science, and Embase. Case–control studies containing genotype frequencies of polymorphisms rs231775 or rs3087243 were selected, and pooled odds ratios (ORs) with 95% confidence intervals (CIs) were used to assess the associations between polymorphisms of CTLA-4 and LADA in allelic, dominant and recessive genetic model. A total of eleven studies, in which five studies reported rs231775, two studies reported rs3087342, and four studies reported both rs231775 and rs3087243, were identified. Among them, one study wasn't included in the following meta-analysis because the distribution of genotypes in the control group didn't comply with Hardy–Weinberg equilibrium. Significant associations with susceptibility to LADA were detected for rs231775 (785 cases and 3435 controls) and for rs3087243 (820 cases and 4824 controls) in overall population. Further subgroup analyses for ethnicity (Asian, Caucasian, and African) have also indicated the positive association between rs231775 and LADA. As for rs3087243, subgroup analyses detected the association between polymorphism and LADA in Caucasian population under recessive model. Polymorphisms rs231775 and rs3087243 of CTLA-4 gene are potential risk factors for LADA and may serve as novel genetic biomarkers of LADA. [ABSTRACT FROM AUTHOR]

Smart windows can selectively regulate excess solar radiation to reduce heating and cooling energy consumption in the built environment. However, the inevitable dissipation of ultraviolet and near‐infrared into waste heat results in inefficient solar utilization. Herein, a dual‐band selective solar harvesting (SSH) window is developed to realize full‐spectrum utilization. A transparent photovoltaic, converting ultraviolet into electricity, and a transparent solar absorber, converting near‐infrared into thermal energy, are integrated and coupled with a ventilation system to extract heat for indoor use. Compared with common transparent photovoltaics, the SSH window increases solar harvesting efficiency up to threefold while maintaining a considerable visible transmittance. Simulations suggest that the SSH window, besides generating electricity, delivers energy savings by over 30% higher than common smart windows. This is the first integration of transparent photovoltaic and transparent solar absorber into a window, which may open up a new avenue for the development of energy‐efficient buildings. [ABSTRACT FROM AUTHOR]

Backgrounds: Exosomes contain several types of transcripts, including long non-coding RNAs (lncRNAs), and have been shown to exert important effects in human diseases. However, the roles of exosomal lncRNAs in type 1 diabetes mellitus (T1DM) have not been well investigated. In the present study, we characterized the plasma-derived exosomal lncRNAs expression profiles of T1DM and predict their potential function in the pathogenesis of T1DM. Material and Methods: Exosomal lncRNA expression profiles were detected by Illumina Hiseq platform (T1DM subjects N=10; age-, sex- matched Control subjects N=10). Six exosomal lncRNAs were selected to validate their expression level by using quantitative real-time PCR (qRT-PCR) (T1DM subjects N=30; age-, sex- matched Control subjects N=30). Bioinformatics analysis approaches were carried out to explore the potential biological function of differentially expressed lncRNAs. Results: A total of 162 differentially expressed exosomal lncRNAs were identified in T1DM patients compared with control subjects, among which 77 up-regulated and 85 down-regulated. The expression level of the selected six lncRNAs didn't show significant difference in the following qRT-PCR analysis. Gene Ontology analysis enriched terms such as activation of phospholipase D activity, neuronal cell body membrane, and calcium sensitive guanylate cyclase activator activity for cis-acting genes of lncRNAs, and metal ion binding for trans-acting genes. The most enriched Kyoto Encyclopedia of Genes and Genomes pathways for the lncRNAs were associated with oxidative phosphorylation and Parkinson's disease for cis-acting genes, and pathways in cancer as well as focal adhesion for trans-acting genes. Conclusions: This study characterized the lncRNA profiles of plasma-derived exosomes from T1DM for the first time and these results highlighted the potential role of exosomal lncRNAs in T1DM pathogenesis. A better understanding of exosomal lncRNA profiling will provide novel insights into its molecular mechanisms. [ABSTRACT FROM AUTHOR]

With the widespread use and abuse of antibiotics, Helicobacter pylori (H. pylori) has become seriously drug resistant. The development of new antibiotics is an important way to solve H. pylori 's drug resistance. Screening antibacterial ingredients from natural products is a convenient way to develop new antibiotics. Phillygenin, an effective antibacterial component, was selected from the natural product, forsythia, in this study. Its minimal inhibitory concentration (MIC) for 18 H. pylori strains was 16–32 μg/ml. The minimum bactericidal concentration (MBC) of H. pylori G27 was 128 μg/ml; the higher the drug concentration and the longer the time, the better the sterilization effect. It was non-toxic to gastric epithelial cell (GES)-1 and BGC823 cells at the concentration of 100 μg/ml. It presented a better antibacterial effect on H. pylori in an acidic environment, and after 24 days of induction on H. pylori with 1/4 MIC of phillygenin, no change was found in the MIC of H. pylori. In the mechanism of action, phillygenin could cause ATP leakage and inhibit the biofilm formation; the latter was associated with the regulation of spoT and Hp1174 genes. In addition, phillygenin could regulate the genes of Nhac, caggamma, MATE, MdoB, flagellinA , and lptB , leading to the weakening of H. pylori 's acid resistance and virulence, the diminishing of H. pylori 's capacity for drug efflux, H. pylori 's DNA methylation, the initiation of human immune response, and the ATP leakage of H. pylori , thus accelerating the death of H. pylori. In conclusion, phillygenin was a main ingredient inhibiting H. pylori in Forsythia suspensa , with a good antibacterial activity, high safety, strong specificity, better antibacterial effect under acidic conditions, and low risk of resistance development by H. pylori. Its mechanism of action was mainly associated with inhibiting the biofilm formation and resulting in ATP leakage. In addition, phillygenin was shown to be able to reduce the acid resistance and virulence of H. pylori. [ABSTRACT FROM AUTHOR]

Background: Anti- N -methyl-D-aspartate receptor (NMDAR) encephalitis is the most common autoimmune encephalitis (AE), and the prognosis may significantly be improved if identified earlier and immune-related treated more effectively. This study evaluated the brain metabolic network using fluorodeoxyglucose positron emission tomography (FDG PET). Material and methods: FDG PET imaging of patients with NMDAR encephalitis was used to investigate the metabolic connectivity network, which was analyzed using the graph theory. The results in patients were compared to those in age- and sex-matched healthy controls. Results: The hub nodes were mainly in the right frontal lobe in patients with NMDAR encephalitis. The global and local efficiencies in most brain regions were significantly reduced, and the shortest characteristic path length was significantly longer, especially in the temporal and occipital lobes. Significant network functions of topology properties were enhanced in the right frontal, caudate nucleus, and cingulate gyrus. In addition, the internal connection integration in the left cerebral hemisphere was poor, and the transmission efficiency of Internet information was low. Conclusion: The present findings indicate that those characteristic and connections of metabolic network were changed in the brain by graph theory analysis quantitatively, which is helpful to better understand neuropathological and physiological mechanisms in patients with anti-NMDAR encephalitis. [ABSTRACT FROM AUTHOR]

Background and Aims: The NLRP3 gene is reportedly associated with several autoimmune diseases. However, in the Chinese Han population, whether NLRP3 polymorphisms are associated with type 1 diabetes (T1D) is unclear. Therefore, this study examined the associations of rs3806265 and rs4612666 of the NLRP3 gene with T1D susceptibility and the clinical characteristics of Chinese Han T1D patients. Methods: In total, 510 classic T1D patients and 531 healthy controls from the Chinese Han population were recruited for a case-control study. rs3806265 and rs4612666 of the NLRP3 gene were genotyped by MassARRAY. Logistic regression analysis and the chi-square test were used to compare the distributions of the alleles and genotypes of rs3806265 and rs4612666. The relationships between rs3806265 and rs4612666 and the clinical characteristics of T1D patients were analyzed by Kruskal-Wallis one-way ANOVA. Student's t test was used to analyze normally distributed data. Bonferroni correction was used for multiple comparisons. Results: 1) rs3806265 was associated with glutamic acid decarboxylase antibody (GADA) titers (P = 0.02), and patients with the CC genotype had higher GADA titers than patients with the TT genotype. 2) rs4612666 was also associated with GADA titers (P=0.041). Compared with patients with the CC genotype, patients with the TT genotype had higher GADA titers. 3) rs3806265 and rs4612666 of the NLRP3 gene were not significantly associated with T1D susceptibility under different genetic models. Conclusion: rs3806265 and rs4612666 of the NLRP3 gene were significantly associated with GADA titers in Chinese Han T1D patients. [ABSTRACT FROM AUTHOR]

Background: This study aimed to determine the effect of PKM2 knockout in STZ induced type 1 diabetes mellitus (T1D) mouse models and to explore the possible mechanism. Method: PKM2fl/fl C57BL/6 mouse was backcrossed with Ins‐1cre C57BL/6 mouse to generate β‐cell‐specific PKM2 knockout mouse after tamoxifen administration. The expression level of PKM2 in pancreas tissues was detected by quantitative reverse‐transcription polymerase chain reaction and western blot analysis. The blood glucose levels in STZ induced T1D mouse models were measured to validate the establishment of T1D models. The pathological changes of T1D mouse were examined by hematoxylin and eosin. The oxidative stress (OS) and inflammatory response in T1D mouse were determined by measuring the expression levels of malondialdehyde, superoxide dismutase, and 8‐OHdG in pancreatic tissues and the serum levels of interleukin‐6 and tumor necrosis factor‐α. The ability to catabolize glucose was assessed through intraperitoneal glucose tolerance test and insulin tolerance test. Results: β‐cell‐specific PKM2 knockout was successfully achieved in PKM2fl/flcre+ mouse. T1D mouse with PKM2 knockdown had decreased blood glucose level and suppressed cell apoptosis. PKM2 knockout in T1D mouse attenuated β cell injury. OS and inflammatory response in T1D mouse with PKM2 knockout were also suppressed compared with T1D mouse without PKM2 knockout. Conclusion: PKM2 knockout in T1D mouse can attenuate OS and inflammatory response as well as decrease blood glucose level, suggesting the potential of PKM2 as a drug target for T1D treatment. [ABSTRACT FROM AUTHOR]