Engineered Cytokine-Primed Extracellular Vesicles with High PD-L1 Expression Ameliorate Type 1 Diabetes.

Type 1 diabetes (T1D), which is a chronic autoimmune disease, results from the destruction of insulin-producing ß cells targeted by autoreactive T cells. The recent discovery that mesenchymal stem cell-derived extracellular vesicles (MSC-EVs) function as therapeutic tools for autoimmune conditions has attracted substantial attention. However, the in vivo distribution and therapeutic effects of MSC-EVs potentiated by pro-inflammatory cytokines in the context of T1D have yet to be established. Here, it is reported that hexyl 5-aminolevulinate hydrochloride (HAL)-loaded engineered cytokine-primed MSC-EVs (H@TI-EVs) with high expression of immune checkpoint molecule programmed death-legend 1 (PD-L1) exert excellent inflammatory targeting and immunosuppressive effects for T1D imaging and therapy. The accumulated H@TI-EVs in injured pancreas not only enabled the fluorescence imaging and tracking of TI-EVs through the intermediate product protoporphyrin (PpIX) generated by HAL, but also promoted the proliferative and anti-apoptotic effects of islet ß cells. Further analysis revealed that H@TI-EVs exhibited an impressive ability to reduce CD4+ T cell density and activation through the PD-L1/PD-1 axis, and induced M1-to-M2 macrophage transition to reshape the immune microenvironment, exhibiting high therapeutic efficiency in mice with T1D. This work identifies a novel strategy for the imaging and treatment of T1D with great potential for clinical application.

White matter hyperintensities segmentation using an ensemble of neural networks.

White matter hyperintensities (WMHs) represent the most common neuroimaging marker of cerebral small vessel disease (CSVD). The volume and location of WMHs are important clinical measures. We present a pipeline using deep fully convolutional network and ensemble models, combining U-Net, SE-Net, and multi-scale features, to automatically segment WMHs and estimate their volumes and locations. We evaluated our method in two datasets: a clinical routine dataset comprising 60 patients (selected from Chinese National Stroke Registry, CNSR) and a research dataset composed of 60 patients (selected from MICCAI WMH Challenge, MWC). The performance of our pipeline was compared with four freely available methods: LGA, LPA, UBO detector, and U-Net, in terms of a variety of metrics. Additionally, to access the model generalization ability, another research dataset comprising 40 patients (from Older Australian Twins Study and Sydney Memory and Aging Study, OSM), was selected and tested. The pipeline achieved the best performance in both research dataset and the clinical routine dataset with DSC being significantly higher than other methods (p < .001), reaching .833 and .783, respectively. The results of model generalization ability showed that the model trained on the research dataset (DSC = 0.736) performed higher than that trained on the clinical dataset (DSC = 0.622). Our method outperformed widely used pipelines in WMHs segmentation. This system could generate both image and text outputs for whole brain, lobar and anatomical automatic labeling WMHs. Additionally, software and models of our method are made publicly available at https://www.nitrc.org/projects/what_v1.

Predicting functional outcome in patients with acute brainstem infarction using deep neuroimaging features.

BACKGROUND AND PURPOSE: Acute brainstem infarctions can lead to serious functional impairments. We aimed to predict functional outcomes in patients with acute brainstem infarction using deep neuroimaging features extracted by convolutional neural networks (CNNs). METHODS: This nationwide multicenter stroke registry study included 1482 patients with acute brainstem infarction. We applied CNNs to automatically extract deep neuroimaging features from diffusion-weighted imaging. Deep learning models based on clinical features, laboratory features, conventional imaging features (infarct volume, number of infarctions), and deep neuroimaging features were trained to predict functional outcomes at 3 months poststroke. Unfavorable outcome was defined as modified Rankin Scale score of 3 or higher at 3 months. The models were evaluated by comparing the area under the receiver operating characteristic curve (AUC). RESULTS: A model based solely on 14 deep neuroimaging features from CNNs achieved an extremely high AUC of 0.975 (95% confidence interval [CI] = 0.934-0.997) and significantly outperformed the model combining clinical, laboratory, and conventional imaging features (0.772, 95% CI = 0.691-0.847, p < 0.001) in prediction of functional outcomes. The deep neuroimaging model also demonstrated significant improvement over traditional prognostic scores. In an interpretability analysis, the deep neuroimaging features displayed a significant correlation with age, National Institutes of Health Stroke Scale score, infarct volume, and inflammation factors. CONCLUSIONS: Deep learning models can successfully extract objective neuroimaging features from the routine radiological data in an automatic manner and aid in predicting the functional outcomes in patients with brainstem infarction at 3 months with very high accuracy.

De novo biosynthesis of p-coumaric acid and caffeic acid from carboxymethyl-cellulose by microbial co-culture strategy.

BACKGROUND: Aromatic compounds, such as p-coumaric acid (p-CA) and caffeic acid, are secondary metabolites of various plants, and are widely used in diet and industry for their biological activities. In addition to expensive and unsustainable methods of plant extraction and chemical synthesis, the strategy for heterologous synthesis of aromatic compounds in microorganisms has received much attention. As the most abundant renewable resource in the world, lignocellulose is an economical and environmentally friendly alternative to edible, high-cost carbon sources such as glucose. RESULTS: In the present study, carboxymethyl-cellulose (CMC) was utilized as the sole carbon source, and a metabolically engineered Saccharomyces cerevisiae strain SK10-3 was co-cultured with other recombinant S. cerevisiae strains to achieve the bioconversion of value-added products from CMC. By optimizing the inoculation ratio, interval time, and carbon source content, the final titer of p-CA in 30 g/L CMC medium was increased to 71.71 mg/L, which was 155.9-fold higher than that achieved in mono-culture. The de novo biosynthesis of caffeic acid in the CMC medium was also achieved through a three-strain co-cultivation. Caffeic acid production was up to 16.91 mg/L after optimizing the inoculation ratio of these strains. CONCLUSION: De novo biosynthesis of p-CA and caffeic acid from lignocellulose through a co-cultivation strategy was achieved for the first time. This study provides favorable support for the biosynthesis of more high value-added products from economical substrates. In addition, the multi-strain co-culture strategy can effectively improve the final titer of the target products, which has high application potential in the field of industrial production.

Ultrasound Shear Wave Elastography for Evaluation of Diaphragm Stiffness in Patients with Stable COPD: A Pilot Trial.

OBJECTIVES: Skeletal muscle dysfunction is one of the most common comorbidities in chronic obstructive pulmonary disease (COPD). The occurrence of respiratory failure in COPD is common and leads to the patient's death. The diaphragm is the most important muscle in the respiratory system and plays a key role in the onset of respiratory failure. This study explores the feasibility of ultrasound shear wave elastography (SWE) to measure diaphragmatic stiffness and evaluates its changes in COPD patients. METHODS: In total, 77 participants (43 patients with stable COPD and 34 healthy controls) were enrolled. All subjects underwent complete diaphragmatic ultrasound SWE measurements and pulmonary function tests. The diaphragmatic stiffness was indicated via diaphragmatic shear wave velocity (SWV) at functional residual capacity (FRC). A trained operator performed the ultrasound SWE examinations of the first 15 healthy controls thrice to assess the reliability of diaphragmatic SWE. RESULTS: A good to excellent reliability was found in diaphragmatic SWV at FRC (ICC = 0.93, 95%CI 0.82-0.98). As compared to the control group, the diaphragmatic SWV at FRC was considerably high in the COPD group (median 2.5 m/s versus 2.1 m/s, P = .008). Diaphragmatic SWV at FRC was linked to forced expiratory volume in one second (r = -0.30, P = .009), forced vital capacity (r = -0.33, P = .003), modified Medical Research Council score (r = 0.30, P = .001), and COPD assessment test score (r = 0.48, P < .001). CONCLUSIONS: Ultrasound SWE may be employed as an effective tool for quantitative evaluation of diaphragm stiffness and can help in personalized management of COPD, such as treatment guidance and follow-up monitoring.

High-efficiency protein delivery into transfection-recalcitrant cell types.

Intracellular delivery of functional proteins is of great interest for basic biological research as well as for clinical applications. Transfection is the most commonly used method, however, it is not applicable to large-scale manipulation and inefficient in important cell types implicated in biomedical applications, such as epithelial, immune and pluripotent stem cells. In this study, we explored a bacterial type III secretion system (Bac-T3SS)-mediated proteofection method to overcome these limitations. An attenuated Pseudomonas aeruginosa vector was constructed, which has features of low toxicity, high T3SS activity, and self-limiting growth. Compared to the method of transfection, the Bac-T3SS showed significantly higher efficiencies of Cre recombinase translocation and target site recombination for hard-to-transfect human cell lines. Furthermore, through the delivery of ß-lactamase in live animals, we demonstrated the feasibility and biosafety of in vivo application of the Bac-T3SS. This study provided an efficient and low-cost proteofection strategy for laboratory use as well as for application in large-scale cell manipulations.

Engineering Lactococcus lactis as a multi-stress tolerant biosynthetic chassis by deleting the prophage-related fragment.

BACKGROUND: In bioengineering, growth of microorganisms is limited because of environmental and industrial stresses during fermentation. This study aimed to construct a nisin-producing chassis Lactococcus lactis strain with genome-streamlined, low metabolic burden, and multi-stress tolerance characteristics. RESULTS: The Cre-loxP recombination system was applied to reduce the genome and obtain the target chassis strain. A prophage-related fragment (PRF; 19,739 bp) in the L. lactis N8 genome was deleted, and the mutant strain L. lactis N8-1 was chosen for multi-stress tolerance studies. Nisin immunity of L. lactis N8-1 was increased to 6500 IU/mL, which was 44.44% higher than that of the wild-type L. lactis N8 (4500 IU/mL). The survival rates of L. lactis N8-1 treated with lysozyme for 2 h and lactic acid for 1 h were 1000- and 10,000-fold higher than that of the wild-type strain, respectively. At 39 â„ƒ, the L. lactis N8-1 could still maintain its growth, whereas the growth of the wild-type strain dramatically dropped. Scanning electron microscopy showed that the cell wall integrity of L. lactis N8-1 was well maintained after lysozyme treatment. Tandem mass tags labeled quantitative proteomics revealed that 33 and 9 proteins were significantly upregulated and downregulated, respectively, in L. lactis N8-1. These differential proteins were involved in carbohydrate and energy transport/metabolism, biosynthesis of cell wall and cell surface proteins. CONCLUSIONS: PRF deletion was proven to be an efficient strategy to achieve multi-stress tolerance and nisin immunity in L. lactis, thereby providing a new perspective for industrially obtaining engineered strains with multi-stress tolerance and expanding the application of lactic acid bacteria in biotechnology and synthetic biology. Besides, the importance of PRF, which can confer vital phenotypes to bacteria, was established.

Effect of green tea consumption on human brain function in resting-state functional MRI.

BACKGROUND AND OBJECTIVES: Green tea is reported to have wide benefits on psychological states and cognitive functions. Studies that focus on the underlying neural mechanisms of green tea are limited to its single composition while people usually benefit from green tea water that contains various composition. In this study, we examined the human brain activity changes after drinking natural green tea by using regional homogeneity and functional connectivity based on the resting-state functional MRI technique. METHODS AND STUDY DESIGN: Fifteen healthy volunteers participated in two imaging sessions: a control (water) session and a green tea session, each session comprised a predrinking, drinking, and postdrinking section, during the drinking section, the subject consumed 200 mL of green tea infusion or water in 3 to 5 minutes. Then the post-tea and post-water imaging data were selected for regional homogeneity and functional connectivity analysis. RESULTS: Our results revealed that, compared with the control group, the green tea group exhibited an increased regional homogeneity in the frontal, parietal, and occipital areas of the brain, decreased regional homogeneity values in the left cuneus and left lingual gyrus, mainly a decreased functional connectivity in the default mode network, somatosensory, visual cortex, and parieto-frontal areas and enhanced functional connectivity in brain regions associated with memory. CONCLUSIONS: This result indicates that green tea consumption impacts the brain activity during resting state.

Autophagy maintains the integrity of endothelial barrier in LPS-induced lung injury.

Understanding the role and underlying regulation mechanism of autophagy in lipopolysaccharide-induced lung injury (LPS-LI) may provide potentially new pharmacological targets for treatment of acute lung injury. The aim of this study was to investigate the functional significance of autophagy in LPS-LI. The autophagy of human pulmonary microvascular endothelial cells (HPMVECs) and mice was inhibited before they were challenged with LPS. In vitro, permeability, vitality, and the LDH release rate of the cells were detected, the zonula occluden-1 (ZO-1) expression and the stress fiber formation were determined. In vivo, the lung injury was assessed. We found LPS caused high permeability and increased lactate dehydrogenase (LDH) release rate, lowered viability of the cells, inhibited the ZO-1 expression and induced stress fiber formation, these effects were further aggravated by prohibiting the level of autophagy. Consistently, in in vivo experiments, LPS-induced serious lung injury, which was reflected as edema, leukocyte infiltration and hemorrhage in lung tissue, and the high concentration of pro-inflammation cytokines tumor necrosis factor (TNF)-α and interleukin (IL)-1ß in bronchoalveolar lavage fluid (BALF). Inhibiting autophagy further exacerbated LPS-LI. It appears that autophagy played a protective role in LPS-LI in part through restricting the injury of lung microvascular barrier.

γδ T cells are indispensable for interleukin-23-mediated protection against Concanavalin A-induced hepatitis in hepatitis B virus transgenic mice.

Hepatitis B virus surface antigen (HBsAg) carriers are highly susceptible to liver injury triggered by environmental biochemical stimulation. Previously, we have reported an inverse correlation between γδ T cells and liver damage in patients with hepatitis B virus (HBV). However, whether γδ T cells play a role in regulating the hypersensitivity of HBsAg carriers to biochemical stimulation-induced hepatitis is unknown. In this study, using HBV transgenic (HBs-Tg) and HBs-Tg T-cell receptor-δ-deficient (TCR-δ-/- ) mice, we found that mice genetically deficient in γδ T cells exhibited more severe liver damage upon Concanavalin A (Con A) treatment, as indicated by substantially higher serum alanine aminotransferase levels, further elevated interferon-γ (IFN-γ) levels and more extensive necrosis. γδ T-cell deficiency resulted in elevated IFN-γ in CD4+ T cells but not in natural killer or natural killer T cells. The depletion of CD4+ T cells and neutralization of IFN-γ reduced liver damage in HBs-Tg and HBs-Tg-TCR-δ-/- mice to a similar extent. Further investigation revealed that HBs-Tg mice showed an enhanced interleukin-17 (IL-17) signature. The administration of exogenous IL-23 enhanced IL-17A production from Vγ4 γδ T cells and ameliorated liver damage in HBs-Tg mice, but not in HBs-Tg-TCR-δ-/- mice. In summary, our results demonstrated that γδ T cells played a protective role in restraining Con A-induced hepatitis by inhibiting IFN-γ production from CD4+ T cells and are indispensable for IL-23-mediated protection against Con A-induced hepatitis in HBs-Tg mice. These results provided a potential therapeutic approach for treating the hypersensitivity of HBV carriers to biochemical stimulation-induced liver damage.

An active contour model based on local fitted images for image segmentation.

Active contour models are popular and widely used for a variety of image segmentation applications with promising accuracy, but they may suffer from limited segmentation performances due to the presence of intensity inhomogeneity. To overcome this drawback, a novel region-based active contour model based on two different local fitted images is proposed by constructing a novel local hybrid image fitting energy, which is minimized in a variational level set framework to guide the evolving of contour curves toward the desired boundaries. The proposed model is evaluated and compared with several typical active contour models to segment synthetic and real images with different intensity characteristics. Experimental results demonstrate that the proposed model outperforms these models in terms of accuracy in image segmentation.

miR-20b suppresses Th17 differentiation and the pathogenesis of experimental autoimmune encephalomyelitis by targeting RORγt and STAT3.

The differentiation and function of IL-17-producing Th17 cells are tightly regulated by specific transcription factors and cytokines, which are the key participants in the pathogenesis of multiple sclerosis (MS) and experimental autoimmune encephalomyelitis (EAE). Although specific miRNAs have been shown to be involved in the development of MS and EAE, the potential role of miRNAs in the context of Th17-driven autoimmunity is just beginning to be clarified. miR-20b has been reported as a downregulated miRNA in blood cells of MS patients. In this report, it was further studied in greater detail because we found it was significantly downregulated during EAE, and, in the in vitro differentiation model, Th17 cells had lower expression of miR-20b than did Th1, Th2, or inducible T regulatory cells. Ectopic expression of miR-20b repressed Th17 differentiation in vitro. Using lentiviral vectors for miR-20b overexpression in vivo, we demonstrated that overexpression of miR-20b led to decreased Th17 cells and reduced severity of EAE. Furthermore, we also identified both RAR-related orphan receptor γt and STAT3 as potential targets of miR-20b. Finally, we confirmed that the mild disease severity and low number of Th17 cells in LV-miR-20b-infected mice were largely reversed by coinfection of these mice with lentivirus-expressing RAR-related orphan receptor γt or STAT3 3'-untranslated regions. Taken together, our results contribute to the importance of miRNAs in Th17 differentiation and pathogenesis of MS and EAE.

Interleukin-6 (IL-6) Receptor Antagonist Protects Against Rheumatoid Arthritis.

BACKGROUND The aim of this study was to investigate the protective effect of interleukin-6 (IL-6) receptor antagonist tocilizumab (TCZ) on rheumatoid arthritis (RA) and its related mechanism. MATERIAL AND METHODS Thirty RA patients receiving long-term methotrexate therapy at moderate and severe active stages were selected and treated with TCZ 8 mg/kg/time iv gtt intravenously guttae every 4 weeks. Peripheral blood was extracted before and 24 weeks after TCZ treatment. Peripheral blood mononuclear cells (PBMC) were collected by density gradient centrifugation. Flow cytometry was used to detect the ratio of CD4 naïve T cells and CD4 memory T cells, Th17 cells, and Treg cells in PBMC. DAS28 score, CRP, RF, and CCP levels in patients were evaluated. RESULTS Compared with before treatment, IL-6 receptor antagonist TCZ significantly improved patients' condition, including DAS28 score, CRP, RF, and CCP levels (P<0.01). Furthermore, TCZ obviously upregulated CD4 naïve T cells proportion and decreased CD4 memory T cells ratio (P<0.01). TCZ also markedly reduced the proportion of Th17 cells and increased the proportion of Treg cells (P<0.01). CONCLUSIONS TCZ can treat RA patients through regulating the ratio of CD4 naïve T cells, CD4 memory T cells, Th17 cells, and Treg cells in PBMC.

Significant association between upstream transcription factor 1 rs2516839 polymorphism and hepatocellular carcinoma risk: a case-control study.

Hepatocellular carcinoma (HCC) is one of the most common cancers worldwide with high mortality rate. Upstream transcription factor 1 (USF1) is a ubiquitously expressed transcription factor that regulates the expression of genes involving in different biological processes, including cancer. The aim of this study is to examine the correlation between USF1 polymorphisms and HCC susceptibility. Ninety-four HCC patients and 100 healthy volunteers are recruited in our study. Tag single nucleotide polymorphisms (Tag-SNPs) were retrieved in the International HapMap Project Databases. Extraction of genomic DNAs was conducted with TaqMan Blood DNA kits. Genotyping of USF1 polymorphisms were carried out with TaqMan SNPs genotyping assay. Odds ratios (ORs) and their 95% confidence intervals (CIs) were calculated to evaluate the association between USF1 polymorphisms and HCC risk. All statistical analyses were performed with SPSS 20.0 software. Five tag-SNPs were identified to represent the genetic variants of USF1. Our results suggested that rs2516839 in the 5'UTR of USF1 was significantly associated with increased HCC risk (AA vs GG: OR = 3.15; 95% CI 1.44-6.87; P = 0.003; GA + AA vs AA: OR = 1.85; 95% CI 1.04-3.30; P = 0.034; AA vs GG + GA: OR = 2.96; 95% CI 1.40-6.26; P = 0.004; A vs G: OR = 2.09; 9% CI 1.35-3.23; P < 0.001). Although rs2073655 in the intron region of USF1 was also shown to be correlated with decreased HCC susceptibility in recessive model (TT vs CC + CT: OR = 0.40; 95% CI 0.54-0.75; P = 0.004), this association was not conclusive. Our results indicated that the SNP of rs2516839 have close association with increased risk of HCC. Further studies may be needed to validate our results and gain insights into the pathological mechanism of USF1 gene in the HCC tumorigenesis.

Critical role of dendritic cell-derived IL-27 in antitumor immunity through regulating the recruitment and activation of NK and NKT cells.

Critical roles of IL-27 in autoimmune diseases and infections have been reported; however, the contribution of endogenous IL-27 to tumor progression remains elusive. In this study, by using IL-27p28 conditional knockout mice, we demonstrate that IL-27 is critical in protective immune response against methyl-cholanthrene-induced fibrosarcoma and transplanted B16 melanoma, and dendritic cells (DCs) are the primary source. DC-derived IL-27 is required for shaping tumor microenvironment by inducing CXCL-10 expression in myeloid-derived suppressor cells and regulating IL-12 production from DCs, which lead to the recruitment and activation of NK and NKT cells resulting in immunological control of tumors. Indeed, reconstitution of IL-27 or CXCL-10 in tumor site significantly inhibits tumor growth and restores the number and activation of NK and NKT cells. In summary, our study identifies a previous unknown critical role of DC-derived IL-27 in NK and NKT cell-dependent antitumor immunity through shaping tumor microenvironment, and sheds light on developing novel therapeutic approaches based on IL-27.

[Protective role of γδ T cells in concanavalin A-induced liver injury].

OBJECTIVE: To investigate the role played by γδ T cells in acute liver injury using the concanavalin A (ConA)-induced liver injury mouse model. METHODS: Acute liver injury was induced by intravenous injection of 10 mug/g of ConA into male C57BL/6J mice with wild-type or T cell receptor-γ knockout (TCR δ-/-) genetic backgrounds. Mice injected with PBS alone served as negative controls. The degree of liver damage was assessed by measuring serum levels of transaminase and cytokines at post-injection hours 3, 6, 12, 24, 48, and 72. The percentage of γδ T cells and proportions of different subsets in liver lymphocytes were measured by flow cytometry. RESULTS: The TCR δ-/- mice showed significantly higher levels of the inflammatory cytokines IFN-γ, TNFα and IL-4 than the wild-type mice at post-injection hour 3. The percentage of liver γδ T cells increased with increased injury degree, and the extent of increase was significantly higher in the TCR δ-/- mice than the wild-type mice (post-injection hour 6: 6302.61+/-592.06 vs. 1319.26+/-355.48, 12: 6569.44+/-1060.98 vs. 3415.53+/-343.90, 24: 6514.29+/-757.26 vs. 2062.73+/-365.67, 48: 1262.61+/-558.07 vs. 113.66+/-113.26, and 72: 226.54+/-98.20 vs. 42.35+/-21.51 U/L; all P less than 0.05). In addition, compared to the negative control mice, the ConA-induced mice showed a higher proportions of Vγ4 γδ T cells to total γδ T cells (17.78+/-2.95 vs. 25.26+/-2.43) and to total liver lymphocytes (0.47+/-0.07 vs. 0.66+/-0.05). Similarly, compared to the negative control mice, the ConA-induced mice showed a higher proportion of Vγ1 γδ T cells to total γδ T cells (38.37+/-6.10 vs. 50.19+/-5.52) but the proportion to total liver lymphocytes was not significantly different among the groups (0.76+/-0.18 vs. 0.78+/-0.25). Reinfusion of Vγ4 γδ T lymphocytes into TCR δ-/- mice led to lower serum ALT levels than reinfusion of Vγ1 γδ T lymphocytes (5054.10+/-1748.51 vs. 12333.56+/-663.535 U/L). CONCLUSION: γδ T cells play a protective role in ConA-induced liver injury and this effect maybe mediated by the Vγ4 γδ T cell subset.

Decreased Vδ2 γδ T cells associated with liver damage by regulation of Th17 response in patients with chronic hepatitis B.

BACKGROUND: γδ T cells comprise a small subset of T cells and play a protective role against cancer and viral infections; however, their precise role in patients with chronic hepatitis B remains unclear. METHODS: Flow cytometry and immunofunctional assays were performed to analyze the impact of Vδ2 γδ (Vδ2) T cells in 64 immune-activated patients, 22 immune-tolerant carriers, and 30 healthy controls. RESULTS: The frequencies of peripheral and hepatic Vδ2 T cells decreased with disease progression from immune tolerant to immune activated. In the latter group of patients, the decreases in peripheral and intrahepatic frequencies of Vδ2 T cells reversely correlated with alanine aminotransferase levels and histological activity index. These activated terminally differentiated memory phenotypic Vδ2 T cells exhibited impaired abilities in proliferation and chemotaxis, while maintained a relative intact interferon (IFN) γ production. Importantly, Vδ2 T cells, in vitro, significantly suppressed the production of cytokines associated with interleukin 17-producing CD4+ T (Th17) cells through both cell contact-dependent and IFN-γ-dependent mechanisms. CONCLUSIONS: Inflammatory microenvironment in IA patients result in decreased numbers of Vδ2 T cells, which play a novel role by regulating the pathogenic Th17 response to protect the liver in patients with chronic hepatitis B.

Production of bacterial cellulose-based peptidopolysaccharide BC-L with anti-listerial properties using a co-cultivation strategy.

Bacterial cellulose (BC) has been found extensive applications in diverse domains for its exceptional attributes. However, the lack of antibacterial properties hampers its utilization in food and biomedical sectors. Leucocin, a bacteriocin belonging to class IIa, is synthesized by Leuconostoc that demonstrates potent efficacy against the foodborne pathogen, Listeria monocytogenes. In the current study, co-culturing strategy involving Kosakonia oryzendophytica FY-07 and Leuconostoc carnosum 4010 was used to confer anti-listerial activity to BC, which resulted in the generation of leucocin-containing BC (BC-L). The physical characteristics of BC-L, as determined by X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), and thermogravimetric analysis (TGA), were similar to the physical characteristics of BC. Notably, the experimental results of disc diffusion and growth curve indicated that the BC-L film exhibited a potent inhibitory effect against L. monocytogenes. Scanning electron microscopy (SEM) showed that BC-L exerts its bactericidal activity by forming pores on the bacterial cell wall. Despite the BC-L antibacterial mechanism, which involves pore formation, the mammalian cell viability remained unaffected by the BC-L film. The measurement results of zeta potential indicated that the properties of BC changed after being loaded with leucocin. Based on these findings, the anti-listerial BC-L generated through this co-culture system holds promise as a novel effective antimicrobial agent for applications in meat product preservation and packaging.

Prediction of futile recanalisation after endovascular treatment in acute ischaemic stroke: development and validation of a hybrid machine learning model.

BACKGROUND: Identification of futile recanalisation following endovascular therapy (EVT) in patients with acute ischaemic stroke is both crucial and challenging. Here, we present a novel risk stratification system based on hybrid machine learning method for predicting futile recanalisation. METHODS: Hybrid machine learning models were developed to address six clinical scenarios within the EVT and perioperative management workflow. These models were trained on a prospective database using hybrid feature selection technique to predict futile recanalisation following EVT. The optimal model was validated and compared with existing models and scoring systems in a multicentre prospective cohort to develop a hybrid machine learning-based risk stratification system for futile recanalisation prediction. RESULTS: Using a hybrid feature selection approach, we trained and tested multiple classifiers on two independent patient cohorts (n=1122) to develop a hybrid machine learning-based prediction model. The model demonstrated superior discriminative ability compared with other models and scoring systems (area under the curve=0.80, 95% CI 0.73 to 0.87) and was transformed into a web application (RESCUE-FR Index) that provides a risk stratification system for individual prediction (accessible online at fr-index.biomind.cn/RESCUE-FR/). CONCLUSIONS: The proposed hybrid machine learning approach could be used as an individualised risk prediction model to facilitate adherence to clinical practice guidelines and shared decision-making for optimal candidate selection and prognosis assessment in patients undergoing EVT.

Diagnosis of intracranial aneurysms by computed tomography angiography using deep learning-based detection and segmentation.

BACKGROUND: Detecting and segmenting intracranial aneurysms (IAs) from angiographic images is a laborious task. OBJECTIVE: To evaluates a novel deep-learning algorithm, named vessel attention (VA)-Unet, for the efficient detection and segmentation of IAs. METHODS: This retrospective study was conducted using head CT angiography (CTA) examinations depicting IAs from two hospitals in China between 2010 and 2021. Training included cases with subarachnoid hemorrhage (SAH) and arterial stenosis, common accompanying vascular abnormalities. Testing was performed in cohorts with reference-standard digital subtraction angiography (cohort 1), with SAH (cohort 2), acquired outside the time interval of training data (cohort 3), and an external dataset (cohort 4). The algorithm's performance was evaluated using sensitivity, recall, false positives per case (FPs/case), and Dice coefficient, with manual segmentation as the reference standard. RESULTS: The study included 3190 CTA scans with 4124 IAs. Sensitivity, recall, and FPs/case for detection of IAs were, respectively, 98.58%, 96.17%, and 2.08 in cohort 1; 95.00%, 88.8%, and 3.62 in cohort 2; 96.00%, 93.77%, and 2.60 in cohort 3; and, 96.17%, 94.05%, and 3.60 in external cohort 4. The segmentation accuracy, as measured by the Dice coefficient, was 0.78, 0.71, 0.71, and 0.66 for cohorts 1-4, respectively. VA-Unet detection recall and FPs/case and segmentation accuracy were affected by several clinical factors, including aneurysm size, bifurcation aneurysms, and the presence of arterial stenosis and SAH. CONCLUSIONS: VA-Unet accurately detected and segmented IAs in head CTA comparably to expert interpretation. The proposed algorithm has significant potential to assist radiologists in efficiently detecting and segmenting IAs from CTA images.