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"Geng, Yang"
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Multifunctional Flexible Humidity Sensor Systems Towards Noncontact Wearable Electronics
HighlightsThis report summarizes recent advances of flexible humidity sensors and their integrated systems.Typical examples of noncontact detections based on flexible and wearable humidity sensors are highlighted.Research opportunities and challenges of pushing flexible humidity sensors towards practical contactless measurements are discussed.In the past decade, the global industry and research attentions on intelligent skin-like electronics have boosted their applications in diverse fields including human healthcare, Internet of Things, human–machine interfaces, artificial intelligence and soft robotics. Among them, flexible humidity sensors play a vital role in noncontact measurements relying on the unique property of rapid response to humidity change. This work presents an overview of recent advances in flexible humidity sensors using various active functional materials for contactless monitoring. Four categories of humidity sensors are highlighted based on resistive, capacitive, impedance-type and voltage-type working mechanisms. Furthermore, typical strategies including chemical doping, structural design and Joule heating are introduced to enhance the performance of humidity sensors. Drawing on the noncontact perception capability, human/plant healthcare management, human–machine interactions as well as integrated humidity sensor-based feedback systems are presented. The burgeoning innovations in this research field will benefit human society, especially during the COVID-19 epidemic, where cross-infection should be averted and contactless sensation is highly desired.
Journal Article
SRGN amplifies microglia-mediated neuroinflammation and exacerbates ischemic brain injury
Background
Microglia is the major contributor of post-stroke neuroinflammation cascade and the crucial cellular target for the treatment of ischemic stroke. Currently, the endogenous mechanism underlying microglial activation following ischemic stroke remains elusive. Serglycin (SRGN) is a proteoglycan expressed in immune cells. Up to now, the role of SRGN on microglial activation and ischemic stroke is largely unexplored.
Methods
Srgn
knockout (KO),
Cd44
-KO and wild-type (WT) mice were subjected to middle cerebral artery occlusion (MCAO) to mimic ischemic stroke. Exogenous SRGN supplementation was achieved by stereotactic injection of recombinant mouse SRGN (rSRGN). Cerebral infarction was measured by 2,3,5-triphenyltetrazolium chloride (TTC) staining. Neurological functions were evaluated by the modified neurological severity score (mNSS) and grip strength. Microglial activation was detected by Iba1 immunostaining, morphological analysis and cytokines’ production. Neuronal death was examined by MAP2 immunostaining and FJB staining.
Results
The expression of SRGN and its receptor CD44 was significantly elevated in the ischemic mouse brains, especially in microglia. In addition, lipopolysaccharide (LPS) induced SRGN upregulation in microglia in vitro. rSRGN worsened ischemic brain injury in mice and amplified post-stroke neuroinflammation, while gene knockout of
Srgn
exerted reverse impacts. rSRGN promoted microglial proinflammatory activation both in vivo and in vitro
,
whereas
Srgn
-deficiency alleviated microglia-mediated inflammatory response. Moreover, the genetic deletion of
Cd44
partially rescued rSRGN-induced excessed neuroinflammation and ischemic brain injury in mice. Mechanistically, SRGN boosted the activation of NF-κB signal, and increased glycolysis in microglia.
Conclusion
SRGN acts as a novel therapeutic target in microglia-boosted proinflammatory response following ischemic stroke.
Journal Article
Multi-view clustering via global-view graph learning
Multiview clustering aims to improve clustering performance by exploring multiple representations of data and has become an important research direction. Meanwhile, graph-based methods have been extensively studied and have shown promising performance in multiview clustering tasks. However, most existing graph-based multiview clustering methods rely on assigning appropriate weights to each view based on its importance, with the clustering results depending on these weight assignments. In this paper, we propose an a novel multiview spectral clustering framework with reduced computational complexity that captures complementary information across views by optimizing a global-view graph using adaptive weight learning. Additionally, in our method, once the Global-view Graph is obtained, cluster labels can be directly assigned to each data point without the need for any post-processing, such as the K-means required in standard spectral clustering. Our method not only improves clustering performance but also reduces computational resource consumption. Experimental results on real-world datasets demonstrate the effectiveness of our approach.
Journal Article
Chaperone-mediated autophagy is involved in the execution of ferroptosis
Necroptosis and ferroptosis are two distinct necrotic cell death modalities with no known common molecular mechanisms. Necroptosis is activated by ligands of death receptors such as tumor necrosis factor-α (TNF-α) under caspase-deficient conditions, whereas ferroptosis is mediated by the accumulation of lipid peroxides upon the depletion/or inhibition of glutathione peroxidase 4 (GPX4). The molecular mechanism that mediates the execution of ferroptosis remains unclear. In this study, we identified 2-amino-5-chloro-N,3-dimethylbenzamide (CDDO), a compound known to inhibit heat shock protein 90 (HSP90), as an inhibitor of necroptosis that could also inhibit ferroptosis. We found that HSP90 defined a common regulatory nodal between necroptosis and ferroptosis. We showed that inhibition of HSP90 by CDDO blocked necroptosis by inhibiting the activation of RIPK1 kinase. Furthermore, we showed that the activation of ferroptosis by erastin increased the levels of lysosome-associated membrane protein 2a to promote chaperone-mediated autophagy (CMA), which, in turn, promoted the degradation of GPX4. Importantly, inhibition of CMA stabilized GPX4 and reduced ferroptosis. Our results suggest that activation of CMA is involved in the execution of ferroptosis.
Journal Article
Metabolomic Identification of Exosome-Derived Biomarkers for Schizophrenia: A Large Multicenter Study
Abstract
Exosomes have been suggested as promising targets for the diagnosis and treatment of neurological diseases, including schizophrenia (SCZ), but the potential role of exosome-derived metabolites in these diseases was rarely studied. Using ultra-performance liquid chromatography-tandem mass spectrometry, we performed the first metabolomic study of serum-derived exosomes from patients with SCZ. Our sample comprised 385 patients and 332 healthy controls recruited from 3 clinical centers and 4 independent cohorts. We identified 25 perturbed metabolites in patients that can be used to classify samples from patients and control participants with 95.7% accuracy (95% CI: 92.6%–98.9%) in the training samples (78 patients and 66 controls). These metabolites also showed good to excellent performance in differentiating between patients and controls in the 3 test sets of participants, with accuracies 91.0% (95% CI: 85.7%–96.3%; 107 patients and 62 controls), 82.7% (95% CI: 77.6%–87.9%; 104 patients and 142 controls), and 99.0% (95% CI: 97.7%–100%; 96 patients and 62 controls), respectively. Bioinformatic analysis suggested that these metabolites were enriched in pathways implicated in SCZ, such as glycerophospholipid metabolism. Taken together, our findings support a role for exosomal metabolite dysregulation in the pathophysiology of SCZ and indicate a strong potential for exosome-derived metabolites to inform the diagnosis of SCZ.
Journal Article
Machine Learning‐Enabled Tactile Sensor Design for Dynamic Touch Decoding
Skin‐like flexible sensors play vital roles in healthcare and human–machine interactions. However, general goals focus on pursuing intrinsic static and dynamic performance of skin‐like sensors themselves accompanied with diverse trial‐and‐error attempts. Such a forward strategy almost isolates the design of sensors from resulting applications. Here, a machine learning (ML)‐guided design of flexible tactile sensor system is reported, enabling a high classification accuracy (≈99.58%) of tactile perception in six dynamic touch modalities. Different from the intuition‐driven sensor design, such ML‐guided performance optimization is realized by introducing a support vector machine‐based ML algorithm along with specific statistical criteria for fabrication parameters selection to excavate features deeply concealed in raw sensing data. This inverse design merges the statistical learning criteria into the design phase of sensing hardware, bridging the gap between the device structures and algorithms. Using the optimized tactile sensor, the high‐quality recognizable signals in handwriting applications are obtained. Besides, with the additional data processing, a robot hand assembled with the sensor is able to complete real‐time touch‐decoding of an 11‐digit braille phone number with high accuracy.
Journal Article
Phenolic composition and nutritional attributes of diaphragma juglandis fructus and shell of walnut (Juglans regia L.)
Phenolic composition and nutritional attributes of diaphragma juglandis fructus (Djf) and walnut shells (Ws) were investigated. Phenolic acids, hydroxybenzoic acid, isoflavone, and flavone were identified in the free phenolic fractions (FPFs) of both Djf and Ws. Bound phenolic fractions were less than FPFs both in content and diversity. The soluble dietary fiber contents of Djf and Ws were 25.56 g/100 g and 9.5 g/100 g, respectively. The contents of unsaturated fatty acids (1912.28 mg/kg and 9137.56 mg/kg, respectively) were significantly higher than that of saturated fatty acid both in Djf and Ws. The content of essential amino acids in Djf (9.67 mg/g) was significantly higher than that in Ws. More than eight types of monosaccharides were detected in Djf and Ws. The monosaccharide content of Djf (314.16 mg/g) was significantly higher than that of Ws (60.97 mg/g). Trehalose was the predominant component both in Djf (71.2%) and Ws (78.6%).
Journal Article
Clinical characteristics, diagnostic modalities, and therapeutic strategies of spontaneous renal artery dissection: A systematic review and diagnostic analysis
To investigate the clinical features, diagnostic approaches, and treatment strategies of spontaneous renal artery dissection (SRAD) through systematic review and data analysis, thereby providing evidence-based insights for optimizing clinical management.
A systematic search was conducted across PubMed, Embase, Cochrane Library, Web of Science, China National Knowledge Infrastructure (CNKI), and Wanfang Database. Case-control studies, cohort studies, and case series were included. Demographic data, symptomatology, diagnostic modalities, treatment regimens, and clinical outcomes were extracted. Statistical analyses were performed using RStudio.
A total of 73 case reports involving 97 patients were included. The mean patient age was 46 years, with a male predominance (82.5%, 80/97). The most common presenting symptom was acute-onset flank pain (74.2%), and comorbid hypertension was observed in 61.9% of cases. Computed tomography angiography (CTA) was the primary diagnostic modality (85.6%), with multimodal imaging utilized in 87.6% of cases. Revascularization rates differed significantly between conservative management (37.1%), endovascular intervention (71.0%), and surgical intervention (6.2%) (P < 0.01). Regarding blood pressure outcomes: the proportion of patients achieving normotension without medication was significantly higher in the non-conservative group (54.1%, 20/37) than in the conservative group (30.0%, 6/20) (P < 0.05); however, there was no statistically significant disparity in the overall blood pressure control rate (normotension without medication + controlled with medication) between groups (P > 0.05). Overall mortality was 3.1%, and renal function deterioration occurred in 30.9% of patients.
Management of SRAD necessitates individualized decision-making. Conservative therapy remains appropriate for most patients, while endovascular intervention demonstrates superior revascularization efficacy in cases with severe symptomatology or dissection progression. Prospective studies are warranted to validate therapeutic disparities and establish standardized diagnostic and treatment protocols.
Journal Article
High-Accuracy Indoor Multiple-Extended-Target Tracking Algorithm Based on 60 GHz Millimeter-Wave Radar
The rapid development of Internet of Things technologies has accelerated the deployment of smart home systems. However, perception solutions based on visual sensors remain constrained by illumination sensitivity, occlusion, and privacy concerns. Frequency-modulated continuous-wave (FMCW) millimeter-wave radar provides a promising alternative because it operates independently of lighting conditions, is robust to environmental changes, and preserves user privacy. To address multiple-extended-target tracking in cluttered indoor environments, this paper proposes a high-accuracy tracking algorithm that combines an improved Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm, an optimized Nearest-Neighbor Data Association (NNDA) scheme, and an Extended Kalman Filter (EKF). The improved DBSCAN algorithm introduces spatial-extent constraints, velocity-consistency checks, and candidate-cluster validation to cluster raw radar point clouds and convert extended targets into representative point targets with little additional computational cost. The optimized NNDA scheme then integrates clustering information into the association process, improving the matching accuracy between existing tracks and current measurements. Finally, the EKF estimates the state of each target from the associated measurements. Real-world experiments show that the proposed algorithm achieves tracking errors below 0.4 m in typical motion scenarios, maintains continuous tracking in two-person crossing scenarios, and reaches 93.3% counting accuracy in five-person scenarios. These results outperform the tracking system based on the commercial Texas Instruments (TI) IWR6843ISK millimeter-wave radar evaluation board. The proposed method offers a reliable and privacy-preserving sensing solution for smart homes, elderly care, and intelligent building applications.
Journal Article