Thrombomodulin reduces α-synuclein generation and ameliorates neuropathology in a mouse model of Parkinson's disease.

The neurotoxic α-synuclein (α-syn) oligomers play an important role in the occurrence and development of Parkinson's disease (PD), but the factors affecting α-syn generation and neurotoxicity remain unclear. We here first found that thrombomodulin (TM) significantly decreased in the plasma of PD patients and brains of A53T α-syn mice, and the increased TM in primary neurons reduced α-syn generation by inhibiting transcription factor p-c-jun production through Erk1/2 signaling pathway. Moreover, TM decreased α-syn neurotoxicity by reducing the levels of oxidative stress and inhibiting PAR1-p53-Bax signaling pathway. In contrast, TM downregulation increased the expression and neurotoxicity of α-syn in primary neurons. When TM plasmids were specifically delivered to neurons in the brains of A53T α-syn mice by adeno-associated virus (AAV), TM significantly reduced α-syn expression and deposition, and ameliorated the neuronal apoptosis, oxidative stress, gliosis and motor deficits in the mouse models, whereas TM knockdown exacerbated these neuropathology and motor dysfunction. Our present findings demonstrate that TM plays a neuroprotective role in PD pathology and symptoms, and it could be a novel therapeutic target in efforts to combat PD. Schematic representation of signaling pathways of TM involved in the expression and neurotoxicity of α-syn. A TM decreased RAGE, and resulting in the lowered production of p-Erk1/2 and p-c-Jun, and finally reduce α-syn generation. α-syn oligomers which formed from monomers increase the expression of p-p38, p53, C-caspase9, C-caspase3 and Bax, decrease the level of Bcl-2, cause mitochondrial damage and lead to oxidative stress, thus inducing neuronal apoptosis. TM can reduce intracellular oxidative stress and inhibit p53-Bax signaling by activating APC and PAR-1. B The binding of α-syn oligomers to TLR4 may induce the expression of IL-1ß, which is subsequently secreted into the extracellular space. This secreted IL-1ß then binds to its receptor, prompting p65 to translocate from the cytoplasm into the nucleus. This translocation downregulates the expression of KLF2, ultimately leading to the suppression of TM expression. By Figdraw.

MSCs alleviate LPS-induced acute lung injury by inhibiting the proinflammatory function of macrophages in mouse lung organoid-macrophage model.

Acute lung injury (ALI) is an inflammatory disease associated with alveolar injury, subsequent macrophage activation, inflammatory cell infiltration, and cytokine production. Mesenchymal stem cells (MSCs) are beneficial for application in the treatment of inflammatory diseases due to their immunomodulatory effects. However, the mechanisms of regulatory effects by MSCs on macrophages in ALI need more in-depth study. Lung tissues were collected from mice for mouse lung organoid construction. Alveolar macrophages (AMs) derived from bronchoalveolar lavage and interstitial macrophages (IMs) derived from lung tissue were co-cultured, with novel matrigel-spreading lung organoids to construct an in vitro model of lung organoids-immune cells. Mouse compact bone-derived MSCs were co-cultured with organoids-macrophages to confirm their therapeutic effect on acute lung injury. Changes in transcriptome expression profile were analyzed by RNA sequencing. Well-established lung organoids expressed various lung cell type-specific markers. Lung organoids grown on spreading matrigel had the property of functional cells growing outside the lumen. Lipopolysaccharide (LPS)-induced injury promoted macrophage chemotaxis toward lung organoids and enhanced the expression of inflammation-associated genes in inflammation-injured lung organoids-macrophages compared with controls. Treatment with MSCs inhibited the injury progress and reduced the levels of inflammatory components. Furthermore, through the nuclear factor-κB pathway, MSC treatment inhibited inflammatory and phenotypic transformation of AMs and modulated the antigen-presenting function of IMs, thereby affecting the inflammatory phenotype of lung organoids. Lung organoids grown by spreading matrigel facilitate the reception of external stimuli and the construction of in vitro models containing immune cells, which is a potential novel model for disease research. MSCs exert protective effects against lung injury by regulating different functions of AMs and IMs in the lung, indicating a potential mechanism for therapeutic intervention.

Mesenchymal stem cells alleviate mouse liver fibrosis by inhibiting pathogenic function of intrahepatic B cells.

BACKGROUND AIMS: The immunomodulatory characteristics of mesenchymal stem cells (MSCs) make them a promising therapeutic approach for liver fibrosis (LF). Here, we postulated that MSCs could potentially suppress the pro-fibrotic activity of intrahepatic B cells, thereby inhibiting LF progression. APPROACH RESULTS: Administration of MSCs significantly ameliorated LF as indicated by reduced myofibroblast activation, collagen deposition, and inflammation. The treatment efficacy of MSCs can be attributed to decreased infiltration, activation, and pro-inflammatory cytokine production of intrahepatic B cells. Single-cell RNA sequencing revealed a distinct intrahepatic B cell atlas and a subtype of naive B cells (B-II) was identified, which were markedly abundant in fibrotic liver, displaying mature features with elevated expression of several proliferative and inflammatory genes. Transcriptional profiling of total B cells revealed that intrahepatic B cells displayed activation, proliferation, and pro-inflammatory gene profile during LF. Fibrosis was attenuated in mice ablated with B cells (µMT) or in vivo treatment with anti-CD20. Moreover, fibrosis was recapitulated in µMT after adoptive transfer of B cells, which in turn could be rescued by MSC injection, validating the pathogenic function of B cells and the efficacy of MSCs on B cell-promoted LF progression. Mechanistically, MSCs could inhibit the proliferation and cytokine production of intrahepatic B cells through exosomes, regulating the MAPK and NF-kappa B signaling pathways. CONCLUSIONS: Intrahepatic B-cell serve as a target of MSCs, play an important role in the process of MSC-induced amelioration of LF, and may provide new clues for revealing the novel mechanisms of MSC action.

Bearing fault detection by using graph autoencoder and ensemble learning.

The research and application of bearing fault diagnosis techniques are crucial for enhancing equipment reliability, extending bearing lifespan, and reducing maintenance expenses. Nevertheless, most existing methods encounter challenges in discriminating between signals from machines operating under normal and faulty conditions, leading to unstable detection results. To tackle this issue, the present study proposes a novel approach for bearing fault detection based on graph neural networks and ensemble learning. Our key contribution is a novel stochasticity-based compositional method that transforms Euclidean-structured data into a graph format for processing by graph neural networks, with feature fusion and a newly proposed ensemble learning strategy for outlier detection specifically designed for bearing fault diagnosis. This approach marks a significant advancement in accurately identifying bearing faults, highlighting our study's pivotal role in enhancing diagnostic methodologies.

MSC-derived exosomes attenuate hepatic fibrosis in primary sclerosing cholangitis through inhibition of Th17 differentiation.

Primary sclerosing cholangitis (PSC) is an autoimmune cholangiopathy characterized by chronic inflammation of the biliary epithelium and periductal fibrosis, with no curative treatment available, and liver transplantation is inevitable for end-stage patients. Human placental mesenchymal stem cell (hpMSC)-derived exosomes have demonstrated the ability to prevent fibrosis, inhibit collagen production and possess immunomodulatory properties in autoimmune liver disease. Here, we prepared hpMSC-derived exosomes (ExoMSC) and further investigated the anti-fibrotic effects and detailed mechanism on PSC based on Mdr2-/- mice and multicellular organoids established from PSC patients. The results showed that ExoMSC ameliorated liver fibrosis in Mdr2-/- mice with significant collagen reduction in the preductal area where Th17 differentiation was inhibited as demonstrated by RNAseq analysis, and the percentage of CD4+IL-17A+T cells was reduced both in ExoMSC-treated Mdr2-/- mice (Mdr2-/--Exo) in vivo and ExoMSC-treated Th17 differentiation progressed in vitro. Furthermore, ExoMSC improved the hypersecretory phenotype and intercellular interactions in the hepatic Th17 microenvironment by regulating PERK/CHOP signaling as supported by multicellular organoids. Thus, our data demonstrate the anti-fibrosis effect of ExoMSC in PSC disease by inhibiting Th17 differentiation, and ameliorating the Th17-induced microenvironment, indicating the promising potential therapeutic role of ExoMSC in liver fibrosis of PSC or Th17-related diseases.

Single-cell RNA sequencing reveals the immunoregulatory roles of PegIFN-α in patients with chronic hepatitis B.

BACKGROUND AND AIMS: Chronic hepatitis B (CHB) is caused by HBV infection and affects the lives of millions of people worldwide by causing liver inflammation, cirrhosis, and liver cancer. Interferon-alpha (IFN-α) therapy is a conventional immunotherapy that has been widely used in CHB treatment and achieved promising therapeutic outcomes by activating viral sensors and interferon-stimulated genes (ISGs) suppressed by HBV. However, the longitudinal landscape of immune cells of CHB patients and the effect of IFN-α on the immune system are not fully understood. APPROACH AND RESULTS: Here, we applied single-cell RNA sequencing (scRNA-seq) to delineate the transcriptomic landscape of peripheral immune cells in CHB patients before and after PegIFN-α therapy. Notably, we identified three CHB-specific cell subsets, pro-inflammatory (Pro-infla) CD14+ monocytes, Pro-infla CD16+ monocytes and IFNG+ CX3CR1- NK cells, which highly expressed proinflammatory genes and positively correlated with HBsAg. Furthermore, PegIFN-α treatment attenuated percentages of hyperactivated monocytes, increased ratios of long-lived naive/memory T cells and enhanced effector T cell cytotoxicity. Finally, PegIFN-α treatment switched the transcriptional profiles of entire immune cells from TNF-driven to IFN-α-driven pattern and enhanced innate antiviral response, including virus sensing and antigen presentation. CONCLUSIONS: Collectively, our study expands the understanding of the pathological characteristics of CHB and the immunoregulatory roles of PegIFN-α, which provides a new powerful reference for the clinical diagnosis and treatment of CHB.

Successful treatment of early ischemic contracture in the upper arm caused by traumatic haematoma through surgical muscle release and continuous passive motion: Case report.

BACKGROUND: Compartment syndrome is a condition that occurs when there is an increase in pressure within a muscle compartment, leading to a decrease in blood flow to the muscles and nerves within that compartment. If left untreated, this can lead to ischemic contracture, which is a late sequelae of compartment syndrome that occurs when there is sustained ischemic damage to the muscles. Timely diagnosis and treatment are critical in reducing the extent of permanent changes within muscle and nerve tissue. No previously published studies have reported on the treatment of early ischemic contracture resulting from traumatic haematoma in the upper arm. We present an exceptional case involving a 17-year-old male who developed this condition following a collision during a basketball game, resulting in a haematoma with severe pain, tightness and restricted range of motion in the affected arm. He was treated through surgical intervention involving surgical muscle release, haematoma evacuation and continuous passive motion (CPM) postoperatively to restore the range of motion and improve overall function with complete recovery at the 27-month follow-up.

Applying self-powered sensor and support vector machine in load energy consumption modeling and prediction of relational database.

This study explores the analysis and modeling of energy consumption in the context of database workloads, aiming to develop an eco-friendly database management system (DBMS). It leverages vibration energy harvesting systems with self-sustaining wireless vibration sensors (WVSs) in combination with the least square support vector machine algorithm to establish an energy consumption model (ECM) for relational database workloads. Through experiments, the performance of self-sustaining WVS in providing power is validated, and the accuracy of the proposed ECM during the execution of Structured Query Language (SQL) statements is evaluated. The findings demonstrate that this approach can reliably predict the energy consumption of database workloads, with a maximum prediction error rate of 10% during SQL statement execution. Furthermore, the ECM developed for relational databases closely approximates actual energy consumption for query operations, with errors ranging from 1 to 4%. In most cases, the predictions are conservative, falling below the actual values. This finding underscores the high predictive accuracy of the ECM in anticipating relational database workloads and their associated energy consumption. Additionally, this paper delves into prediction accuracy under different types of operations and reveals that ECM excels in single-block read operations, outperforming multi-block read operations. ECM exhibits substantial accuracy in predicting energy consumption for SQL statements in sequential and random read modes, especially in specialized database management system environments, where the error rate for the sequential read model is lower. In comparison to alternative models, the proposed ECM offers superior precision. Furthermore, a noticeable correlation between model error and the volume of data processed by SQL statements is observed. In summary, the relational database ECM introduced in this paper provides accurate predictions of workload and database energy consumption, offering a theoretical foundation and practical guidance for the development of eco-friendly DBMS.

A Cardinality Estimator in Complex Database Systems Based on TreeLSTM.

Cardinality estimation is critical for database management systems (DBMSs) to execute query optimization tasks, which can guide the query optimizer in choosing the best execution plan. However, traditional cardinality estimation methods cannot provide accurate estimates because they cannot accurately capture the correlation between multiple tables. Several recent studies have revealed that learning-based cardinality estimation methods can address the shortcomings of traditional methods and provide more accurate estimates. However, the learning-based cardinality estimation methods still have large errors when an SQL query involves multiple tables or is very complex. To address this problem, we propose a sampling-based tree long short-term memory (TreeLSTM) neural network to model queries. The proposed model addresses the weakness of traditional methods when no sampled tuples match the predicates and considers the join relationship between multiple tables and the conjunction and disjunction operations between predicates. We construct subexpressions as trees using operator types between predicates and improve the performance and accuracy of cardinality estimation by capturing the join-crossing correlations between tables and the order dependencies between predicates. In addition, we construct a new loss function to overcome the drawback that Q-error cannot distinguish between large and small cardinalities. Extensive experimental results from real-world datasets show that our proposed model improves the estimation quality and outperforms traditional cardinality estimation methods and the other compared deep learning methods in three evaluation metrics: Q-error, MAE, and SMAPE.

Immunomodulatory and Antiviral Therapy Improved Functional Cure Rate in CHB Patients with High HBsAg Level Experienced NA.

Background and Aims: A functional cure, or hepatitis B virus (HBV) surface antigen (HBsAg) loss, is difficult to achieve in patients with hepatitis B virus e antigen (HBeAg)-positive chronic hepatitis B. The HBV vaccine and granulocyte-macrophage colony-stimulating factor (GM-CSF) have been reported to help reduce HBsAg levels and promote HBsAg loss. In this prospective randomized trial, we evaluated HBsAg loss in patients receiving pegylated interferon-α2b (PEGIFN-α2b) and tenofovir disoproxil fumarate (TDF), with and without GM-CSF and HBV vaccination. Methods: A total of 287 patients with HBeAg positive chronic hepatitis B and seroconversion after nucleot(s)ide analog treatment were assigned randomly to three treatment groups for 48 weeks, TDF alone (control), PEGIFN-α2b + TDF, and PEGIFN-α2b + TDF + GM-CSF + HBV vaccine. The primary endpoints were the proportions of patients with HBsAg loss and seroconversion at 48 and 72 weeks. Results: The cumulative HBsAg loss rates in the control, PEGIFN-α2b + TDF, and PEGIFN-α2b + TDF + GM-CSF + HBV vaccine groups at week 48 were 0.0%, 28.3%, and 41.1%, respectively. The cumulative HBsAg seroconversion rates in these groups at week 48 were 0.0%, 21.7%, and 33.9%, respectively. Multivariate regression analysis showed that GM-CSF use plus HBV vaccination was significantly associated with HBsAg loss (p=0.017) and seroconversion (p=0.030). Conclusions: In patients with HBeAg-positive chronic hepatitis B and seroconversion after nucleot(s)ide analog treatment, immunomodulatory/antiviral treatment regimens effectively improved HBsAg loss, and the regimen including GM-CSF and HBV vaccination was most effective.

Human Placental Mesenchymal Stem Cells Relieve Primary Sclerosing Cholangitis via Upregulation of TGR5 in Mdr2-/- Mice and Human Intrahepatic Cholangiocyte Organoid Models.

Primary sclerosing cholangitis (PSC) is a biliary disease accompanied by chronic inflammation of the liver and biliary stricture. Mesenchymal stem cells (MSCs) are used to treat liver diseases because of their immune regulation and regeneration-promoting functions. This study was performed to explore the therapeutic potential of human placental MSCs (hP-MSCs) in PSC through the Takeda G protein-coupled receptor 5 (TGR5) receptor pathway. Liver tissues were collected from patients with PSC and healthy donors (n = 4) for RNA sequencing and intrahepatic cholangiocyte organoid construction. hP-MSCs were injected via the tail vein into Mdr2-/-, bile duct ligation (BDL), and 3,5-diethoxycarbonyl-1,4-dihydrocollidine (DDC) mouse models or co-cultured with organoids to confirm their therapeutic effect on biliary cholangitis. Changes in bile acid metabolic profile were analyzed by liquid chromatography/tandem mass spectrometry (LC-MS/MS). Compared with healthy controls, liver tissues and intrahepatic cholangiocyte organoids from PSC patients were characterized by inflammation and cholestasis, and marked downregulation of bile acid receptor TGR5 expression. hP-MSC treatment apparently reduced the inflammation, cholestasis, and fibrosis in Mdr2-/-, BDL, and DDC model mice. By activating the phosphatidylinositol 3 kinase/extracellular signal-regulated protein kinase pathway, hP-MSC treatment promoted the proliferation of cholangiocytes, and affected the transcription of downstream nuclear factor κB through regulation of the binding of TGR5 and Pellino3, thereby affecting the cholangiocyte inflammatory phenotype.

MSA-YOLO: A Remote Sensing Object Detection Model Based on Multi-Scale Strip Attention.

Remote sensing image object detection holds significant research value in resources and the environment. Nevertheless, complex background information and considerable size differences between objects in remote sensing images make it challenging. This paper proposes an efficient remote sensing image object detection model (MSA-YOLO) to improve detection performance. First, we propose a Multi-Scale Strip Convolution Attention Mechanism (MSCAM), which can reduce the introduction of background noise and fuse multi-scale features to enhance the focus of the model on foreground objects of various sizes. Second, we introduce the lightweight convolution module GSConv and propose an improved feature fusion layer, which makes the model more lightweight while improving detection accuracy. Finally, we propose the Wise-Focal CIoU loss function, which can reweight different samples to balance the contribution of different samples to the loss function, thereby improving the regression effect. Experimental results show that on the remote sensing image public datasets DIOR and HRRSD, the performance of our proposed MSA-YOLO model is significantly better than other existing methods.

Mesenchymal stem cells shift the pro-inflammatory phenotype of neutrophils to ameliorate acute lung injury.

BACKGROUND: Mesenchymal stem cell (MSC) treatment plays a major role in the management of acute lung injury (ALI), and neutrophils are the initial line of defense against ALI. However, the effect of MSCs on neutrophils in ALI remains mostly unknown. METHODS: We investigated the characteristics of neutrophils in lung tissue of ALI mice induced by lipopolysaccharide after treatment with MSCs using single-cell RNA sequencing. Neutrophils separated from lung tissue in ALI were co-cultured with MSCs, and then samples were collected for reverse transcription-polymerase chain reaction and flow cytometry. RESULTS: During inflammation, six clusters of neutrophils were identified, annotated as activated, aged, and circulatory neutrophils. Activated neutrophils had higher chemotaxis, reactive oxygen species (ROS) production, and nicotinamide adenine dinucleotide phosphate (NADPH) oxidase scores than aged neutrophils. Circulatory neutrophils occurred mainly in healthy tissue and were characterized by higher expression of Cxcr2 and Sell. Activated neutrophils tended to exhibit higher expression of Cxcl10 and Cd47, and lower expression of Cd24a, while aged neutrophils expressed a lower level of Cd47 and higher level of Cd24a. MSC treatment shifted activated neutrophils toward an aged neutrophil phenotype by upregulating the expression of CD24, thereby inhibiting inflammation by reducing chemotaxis, ROS production, and NADPH oxidase. CONCLUSION: We identified the immunosuppressive effects of MSCs on the subtype distribution of neutrophils and provided new insight into the therapeutic mechanism of MSC treatment in ALI.

Graph Neural Network-Guided Contrastive Learning for Sequential Recommendation.

Sequential recommendation uses contrastive learning to randomly augment user sequences and alleviate the data sparsity problem. However, there is no guarantee that the augmented positive or negative views remain semantically similar. To address this issue, we propose graph neural network-guided contrastive learning for sequential recommendation (GC4SRec). The guided process employs graph neural networks to obtain user embeddings, an encoder to determine the importance score of each item, and various data augmentation methods to construct a contrast view based on the importance score. Experimental validation is conducted on three publicly available datasets, and the experimental results demonstrate that GC4SRec improves the hit rate and normalized discounted cumulative gain metrics by 1.4% and 1.7%, respectively. The model can enhance recommendation performance and mitigate the data sparsity problem.

Efficient-Lightweight YOLO: Improving Small Object Detection in YOLO for Aerial Images.

The most significant technical challenges of current aerial image object-detection tasks are the extremely low accuracy for detecting small objects that are densely distributed within a scene and the lack of semantic information. Moreover, existing detectors with large parameter scales are unsuitable for aerial image object-detection scenarios oriented toward low-end GPUs. To address this technical challenge, we propose efficient-lightweight You Only Look Once (EL-YOLO), an innovative model that overcomes the limitations of existing detectors and low-end GPU orientation. EL-YOLO surpasses the baseline models in three key areas. Firstly, we design and scrutinize three model architectures to intensify the model's focus on small objects and identify the most effective network structure. Secondly, we design efficient spatial pyramid pooling (ESPP) to augment the representation of small-object features in aerial images. Lastly, we introduce the alpha-complete intersection over union (α-CIoU) loss function to tackle the imbalance between positive and negative samples in aerial images. Our proposed EL-YOLO method demonstrates a strong generalization and robustness for the small-object detection problem in aerial images. The experimental results show that, with the model parameters maintained below 10 M while the input image size was unified at 640 × 640 pixels, the APS of the EL-YOLOv5 reached 10.8% and 10.7% and enhanced the APs by 1.9% and 2.2% compared to YOLOv5 on two challenging aerial image datasets, DIOR and VisDrone, respectively.

A novel HIF2A mutation causes dyslipidemia and promotes hepatic lipid accumulation.

Hypoxia-inducible factor-2α (HIF-2α) is a transcription factor responsible for regulating genes related to angiogenesis and metabolism. This study aims to explore the effect of a previously unreported mutation c.C2473T (p.R825S) in the C-terminal transactivation domain (CTAD) of HIF-2α that we detected in tissue of patients with liver disease. We sequenced available liver and matched blood samples obtained during partial liver resection or liver transplantation performed for clinical indications including hepatocellular carcinoma and liver failure. In tandem, we constructed cell lines and a transgenic mouse model bearing the corresponding identified mutation in HIF-2α from which we extracted primary hepatocytes. Lipid accumulation was evaluated in these cells and liver tissue from the mouse model using Oil Red O staining and biochemical measurements. We identified a mutation in the CTAD of HIF-2α (c.C2473T; p.R825S) in 5 of 356 liver samples obtained from patients with hepatopathy and dyslipidemia. We found that introduction of this mutation into the mouse model led to an elevated triglyceride level, lipid droplet accumulation in liver of the mutant mice and in their extracted primary hepatocytes, and increased transcription of genes related to hepatic fatty acid transport and synthesis in the mutant compared to the control groups. In mutant mice and cells, the protein levels of nuclear HIF-2α and its target perilipin-2 (PLIN2), a lipid droplet-related gene, were also elevated. Decreased lipophagy was observed in mutant groups. Our study defines a subpopulation of dyslipidemia that is caused by this HIF-2α mutation. This may have implications for personalized treatment.

Investigating 3D-printed disk compressing against skin for pain relief in intradermal infiltration anesthesia: a randomized controlled trial.

BACKGROUND: Pain intensity may be varied during the needle advancing through different skin layers, injection into the intradermal layer may exclude mixed pain from deeper planes. This study aimed to investigate whether compressing a three-dimensional (3D)-printed disk against the skin may relieve pain associated with intradermal injection of local anesthetic which mimics the skin test procedure. METHODS: After institutional review board approval, 3D-printed disks with projections were designed for this study. Enrolled patients were randomized to receive either a disk compressing against the axillary skin during the intradermal injection of local anesthesia (compressing disk group) or an intradermal injection of local anesthesia without any compression (no compressing disk group). The primary outcomes were pain intensity (100-mm visual analog scale) and satisfaction (5-point Likert scale) as assessed by patients. RESULTS: Ninety patients with American Society of Anesthesiologists I-II physical status receiving intradermal local anesthesia prior to an ultrasound-guided axillary approach were included. Eighty-seven patients completed the study, with 44 and 43 patients in disk and no disk groups, respectively. Pain scores were significantly different (P < 0.001) in compressing disk (median, 10; IQR, 5-20) and no compressing disk (median, 30; IQR, 20-40) groups. The median satisfaction score was 5 in both groups. No complications occurred during follow-up. CONCLUSION: Compressing a 3D-printed disk against the skin may reduce intradermal needle pain and offers an effective alternative for nerve block induction.

Speech Recognition of Accented Mandarin Based on Improved Conformer.

The convolution module in Conformer is capable of providing translationally invariant convolution in time and space. This is often used in Mandarin recognition tasks to address the diversity of speech signals by treating the time-frequency maps of speech signals as images. However, convolutional networks are more effective in local feature modeling, while dialect recognition tasks require the extraction of a long sequence of contextual information features; therefore, the SE-Conformer-TCN is proposed in this paper. By embedding the squeeze-excitation block into the Conformer, the interdependence between the features of channels can be explicitly modeled to enhance the model's ability to select interrelated channels, thus increasing the weight of effective speech spectrogram features and decreasing the weight of ineffective or less effective feature maps. The multi-head self-attention and temporal convolutional network is built in parallel, in which the dilated causal convolutions module can cover the input time series by increasing the expansion factor and convolutional kernel to capture the location information implied between the sequences and enhance the model's access to location information. Experiments on four public datasets demonstrate that the proposed model has a higher performance for the recognition of Mandarin with an accent, and the sentence error rate is reduced by 2.1% compared to the Conformer, with only 4.9% character error rate.

Pooled Analysis of Mesenchymal Stromal Cell-Derived Extracellular Vesicle Therapy for Liver Disease in Preclinical Models.

BACKGROUND: Although increasing preclinical studies have emphasized the benefits of exosome-related therapies, the efficacy of mesenchymal stromal cell (MSC)-derived extracellular vesicles (EV) for liver injury is unclear. In this work, a pooled analysis was conducted to explore the overall effect of MSC-EV in animal models. METHODS: A systematic search of the PubMed, EMBASE, Web of Science, and Cochrane Library databases was performed, from initiation to February 2022, for preclinical studies with liver disease models. The treatment outcomes were evaluated based on liver function, histological analysis, and inflammatory cytokines. RESULTS: After screening, 39 studies were included. Pooled analyses demonstrated that MSC-EV therapy significantly improved liver functions (ALB, ALT, AST, ALP, and γ-GT), promoted the repair of injured liver tissue (damaged area, Ishak's score), reduced inflammatory factors (TNF-α, IL-1ß, IL-6, and IFN-γ), and increased an anti-inflammatory cytokine (IL-10) compared to the placebo control group. Subgroup analyses indicated that MSC-EV had therapeutic effects on liver fibrosis (n = 16), acute liver injury (n = 11), non-alcoholic fatty liver disease (n = 3), autoimmune hepatitis (n = 4), and hepatic ischemia-reperfusion injury (n = 6). Additionally, the therapeutic effect of EV was comparable to that of MSCs. CONCLUSION: MSC-EV have therapeutic potential for acute and chronic liver diseases.