Deep Learning for Noninvasive Assessment of H3 K27M Mutation Status in Diffuse Midline Gliomas Using MR Imaging.

BACKGROUND: Determination of H3 K27M mutation in diffuse midline glioma (DMG) is key for prognostic assessment and stratifying patient subgroups for clinical trials. MRI can noninvasively depict morphological and metabolic characteristics of H3 K27M mutant DMG. PURPOSE: This study aimed to develop a deep learning (DL) approach to noninvasively predict H3 K27M mutation in DMG using T2-weighted images. STUDY TYPE: Retrospective and prospective. POPULATION: For diffuse midline brain gliomas, 341 patients from Center-1 (27 ± 19 years, 184 males), 42 patients from Center-2 (33 ± 19 years, 27 males) and 35 patients (37 ± 18 years, 24 males). For diffuse spinal cord gliomas, 133 patients from Center-1 (30 ± 15 years, 80 males). FIELD STRENGTH/SEQUENCE: 5T and 3T, T2-weighted turbo spin echo imaging. ASSESSMENT: Conventional radiological features were independently reviewed by two neuroradiologists. H3 K27M status was determined by histopathological examination. The Dice coefficient was used to evaluate segmentation performance. Classification performance was evaluated using accuracy, sensitivity, specificity, and area under the curve. STATISTICAL TESTS: Pearson's Chi-squared test, Fisher's exact test, two-sample Student's t-test and Mann-Whitney U test. A two-sided P value <0.05 was considered statistically significant. RESULTS: In the testing cohort, Dice coefficients of tumor segmentation using DL were 0.87 for diffuse midline brain and 0.81 for spinal cord gliomas. In the internal prospective testing dataset, the predictive accuracies, sensitivities, and specificities of H3 K27M mutation status were 92.1%, 98.2%, 82.9% in diffuse midline brain gliomas and 85.4%, 88.9%, 82.6% in spinal cord gliomas. Furthermore, this study showed that the performance generalizes to external institutions, with predictive accuracies of 85.7%-90.5%, sensitivities of 90.9%-96.0%, and specificities of 82.4%-83.3%. DATA CONCLUSION: In this study, an automatic DL framework was developed and validated for accurately predicting H3 K27M mutation using T2-weighted images, which could contribute to the noninvasive determination of H3 K27M status for clinical decision-making. EVIDENCE LEVEL: 2 Technical Efficacy: Stage 2.

Review on Monitoring, Operation and Maintenance of Smart Offshore Wind Farms.

In recent years, with the development of wind energy, the number and scale of wind farms have been developing rapidly. Since offshore wind farms have the advantages of stable wind speed, being clean, renewable, non-polluting, and the non-occupation of cultivated land, they have gradually become a new trend in the wind power industry all over the world. The operation and maintenance of offshore wind power has been developing in the direction of digitization and intelligence. It is of great significance to carry out research on the monitoring, operation, and maintenance of offshore wind farms, which will be of benefit for the reduction of the operation and maintenance costs, the improvement of the power generation efficiency, improvement of the stability of offshore wind farm systems, and the building of smart offshore wind farms. This paper will mainly summarize the monitoring, operation, and maintenance of offshore wind farms, with particular focus on the following points: monitoring of "offshore wind power engineering and biological and environment", the monitoring of power equipment, and the operation and maintenance of smart offshore wind farms. Finally, the future research challenges in relation to the monitoring, operation, and maintenance of smart offshore wind farms are proposed, and the future research directions in this field are explored, especially in marine environment monitoring, weather and climate prediction, intelligent monitoring of power equipment, and digital platforms.

Simple and efficient registration of 3D point cloud and image data for an indoor mobile mapping system.

Registration of 3D lidar point clouds with optical images is critical in the combination of multisource data. Geometric misalignment originally exists in the pose data between lidar point clouds and optical images. To improve the accuracy of the initial pose and the applicability of the integration of 3D points and image data, we develop a simple but efficient registration method. We first extract point features from lidar point clouds and images: point features are extracted from single-frame lidar and point features are extracted from images using a classical Canny operator. The cost map is subsequently built based on Canny image edge detection. The optimization direction is guided by the cost map, where low cost represents the desired direction, and loss function is also considered to improve the robustness of the proposed method. Experiments show positive results.

Heterochromatin protects retinal pigment epithelium cells from oxidative damage by silencing p53 target genes.

Oxidative stress (OS)-induced retinal pigment epithelium (RPE) cell apoptosis is critically implicated in the pathogenesis of age-related macular degeneration (AMD), a leading cause of blindness in the elderly. Heterochromatin, a compact and transcriptional inert chromatin structure, has been recently shown to be dynamically regulated in response to stress stimuli. The functional mechanism of heterochromatin on OS exposure is unclear, however. Here we show that OS increases heterochromatin formation both in vivo and in vitro, which is essential for protecting RPE cells from oxidative damage. Mechanistically, OS-induced heterochromatin selectively accumulates at p53-regulated proapoptotic target promoters and inhibits their transcription. Furthermore, OS-induced desumoylation of p53 promotes p53-heterochromatin interaction and regulates p53 promoter selection, resulting in the locus-specific recruitment of heterochromatin and transcription repression. Together, our findings demonstrate a protective function of OS-induced heterochromatin formation in which p53 desumoylation-guided promoter selection and subsequent heterochromatin recruitment play a critical role. We propose that targeting heterochromatin provides a plausible therapeutic strategy for the treatment of AMD.

Errors-in-variables jump regression using local clustering.

Errors-in-variables (EIV) regression is widely used in econometric models. The statistical analysis becomes challenging when the regression function is discontinuous and the distribution of measurement error is unknown. In the literature, most existing jump regression methods either assume that there is no measurement error involved or require that jumps are explicitly detected before the regression function can be estimated. In some applications, however, the ultimate goal is to estimate the regression function and to preserve the jumps in the process of estimation. In this paper, we are concerned with reconstructing jump regression curve from data that involve measurement error. We propose a direct jump-preserving method that does not explicitly detect jumps. The challenge of restoring jump structure masked by measurement error is handled by local clustering. Theoretical analysis shows that the proposed curve estimator is statistically consistent. A numerical comparison with an existing jump regression method highlights its jump-preserving property. Finally, we demonstrate our method by an application to a health tax policy study in Australia.

3D indoor area recognition for personnel security using integrated UWB and barometer approach.

Real-time location tracking is essential for personal security in industrial scenes, e.g. monitoring worker safety in power substations. Ultra wideband (UWB) technology is suitable for indoor positioning thanks to its high penetration capability, high ranging accuracy and low power consumption. However, UWB based trilateration positioning requires high workload for field deployment of base stations. Indoor complex topology results in multipath and non-line of sight (NLOS) conditions of UWB signals, and degrades the positioning performance in terms of accuracy and reliability. This paper proposes a three-dimensional (3D) area recognition solution by integrating UWB time of flight (TOF) ranging and barometer measurements. The proposed solution utilizes a multi-tier distributed joint probabilistic inference model, which accomplishes the indoor 3D area recognition exploiting multiple clustering and prediction algorithms of machine learning. The field experiments showed that the proposed method can achieve an accuracy of 3D area recognition of more than 99.2%. The proposed method improves the computing efficiency by 93%. The errors of improved differential barometric height estimation method are less than 1 m, which means a success rate of 100% for floor identification, given a floor separation of 3-4 m. The proposed solution is suitable for personnel security applications of industrial scenes, which requires reliable real-time area information rather than just coordinates.

A study on community older people's willingness to use smart home-an extended technology acceptance model with intergenerational relationships.

Introduction: Despite the potential of smart home technology to promote sustainable lifestyles, the adoption rate among older adults remains relatively low. This study aims to investigate the influence of intergenerational relationships on the acceptance of smart home services among seniors. Methods: A survey was conducted among 298 older adults in China, and data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). Ten predictor variables were examined to assess their impact on the willingness to use smart home services. Results: Intergenerational relationships significantly influenced the utilization of smart home services among older adults. Specifically, intergenerational instrumental support had a direct positive effect on the behavioral intention to use smart homes. Additionally, intergenerational emotional and financial support affected life satisfaction, which subsequently influenced the behavioral intention to use smart homes. Discussion: The assistance and guidance provided by younger generations play a crucial role in shaping the willingness of older adults to adopt smart home technology. Intergenerational support can contribute positively to enabling aging individuals to age in place through the utilization of technology.

Identification and analysis of the secretome of plant pathogenic fungi reveals lifestyle adaptation.

The secretory proteome plays an important role in the pathogenesis of phytopathogenic fungi. However, the relationship between the large-scale secretome of phytopathogenic fungi and their lifestyle is not fully understood. In the present study, the secretomes of 150 plant pathogenic fungi were predicted and the characteristics associated with different lifestyles were investigated. In total, 94,974 secreted proteins (SPs) were predicted from these fungi. The number of the SPs ranged from 64 to 1,662. Among these fungi, hemibiotrophic fungi had the highest number (average of 970) and proportion (7.1%) of SPs. Functional annotation showed that hemibiotrophic and necrotroph fungi, differ from biotrophic and symbiotic fungi, contained much more carbohydrate enzymes, especially polysaccharide lyases and carbohydrate esterases. Furthermore, the core and lifestyle-specific SPs orthogroups were identified. Twenty-seven core orthogroups contained 16% of the total SPs and their motif function annotation was represented by serine carboxypeptidase, carboxylesterase and asparaginase. In contrast, 97 lifestyle-specific orthogroups contained only 1% of the total SPs, with diverse functions such as PAN_AP in hemibiotroph-specific and flavin monooxygenases in necrotroph-specific. Moreover, obligate biotrophic fungi had the largest number of effectors (average of 150), followed by hemibiotrophic fungi (average of 120). Among these effectors, 4,155 had known functional annotation and pectin lyase had the highest proportion in the functionally annotated effectors. In addition, 32 sets of RNA-Seq data on pathogen-host interactions were collected and the expression levels of SPs were higher than that of non-SPs, and the expression level of effector genes was higher in biotrophic and hemibiotrophic fungi than in necrotrophic fungi, while secretase genes were highly expressed in necrotrophic fungi. Finally, the secretory activity of five predicted SPs from Setosphearia turcica was experimentally verified. In conclusion, our results provide a foundation for the study of pathogen-host interaction and help us to understand the fungal lifestyle adaptation.

Automated Determination of the H3 K27-Altered Status in Spinal Cord Diffuse Midline Glioma by Radiomics Based on T2-Weighted MR Images.

BACKGROUND AND PURPOSE: Conventional MR imaging is not sufficient to discern the H3 K27-altered status of spinal cord diffuse midline glioma. This study aimed to develop a radiomics-based model based on preoperative T2WI to determine the H3 K27-altered status of spinal cord diffuse midline glioma. MATERIALS AND METHODS: Ninety-seven patients with confirmed spinal cord diffuse midline gliomas were retrospectively recruited and randomly assigned to the training (n = 67) and test (n = 30) sets. One hundred seven radiomics features were initially extracted from automatically-segmented tumors on T2WI, then 11 features selected by the Pearson correlation coefficient and the Kruskal-Wallis test were used to train and test a logistic regression model for predicting the H3 K27-altered status. Sensitivity analysis was performed using additional random splits of the training and test sets, as well as applying other classifiers for comparison. The performance of the model was evaluated through its accuracy, sensitivity, specificity, and area under the curve. Finally, a prospective set including 28 patients with spinal cord diffuse midline gliomas was used to validate the logistic regression model independently. RESULTS: The logistic regression model accurately predicted the H3 K27-altered status with accuracies of 0.833 and 0.786, sensitivities of 0.813 and 0.750, specificities of 0.857 and 0.833, and areas under the curve of 0.839 and 0.818 in the test and prospective sets, respectively. Sensitivity analysis confirmed the robustness of the model, with predictive accuracies of 0.767-0.833. CONCLUSIONS: Radiomics signatures based on preoperative T2WI could accurately predict the H3 K27-altered status of spinal cord diffuse midline glioma, providing potential benefits for clinical management.

Heterochromatin inhibits cGAS and STING during oxidative stress-induced retinal pigment epithelium and retina degeneration.

Age-related macular degeneration (AMD) is a leading cause of blindness characterized by degeneration of retina pigment epithelium (RPE) and photoreceptors in the macular region. Activation of the innate immune cGAS-STING signaling has been detected in RPE of dry AMD patients, but the regulatory basis is largely unexplored. Heterochromatin is a highly compact, transcription inert chromatin status. We have recently shown that heterochromatin is required for RPE survival through epigenetically silencing p53-mediated apoptosis signaling. Here, we found that cGAS and STING were dose-dependently upregulated in mouse RPE and retina during oxidative injury, correlated with decreased chromatin compaction in their gene loci. Genetic or pharmaceutical disruption of heterochromatin leads to elevated cGAS and STING expression and enhanced inflammatory response in oxidative stress-induced RPE and retina degeneration. In contrast, application of methotrexate (MTX), a recently identified heterochromatin-promoting drug, inhibits cGAS and STING in both RPE and retina, attenuates RPE/retina degeneration and inflammation. Further, we show that intact heterochromatin is required for MTX to repress cGAS and STING. Together, we demonstrated an unrevealed regulatory function of heterochromatin on cGAS and STING expression and provide potential new therapeutic strategy for AMD treatment.

Automated Classification of Intramedullary Spinal Cord Tumors and Inflammatory Demyelinating Lesions Using Deep Learning.

Accurate differentiation of intramedullary spinal cord tumors and inflammatory demyelinating lesions and their subtypes are warranted because of their overlapping characteristics at MRI but with different treatments and prognosis. The authors aimed to develop a pipeline for spinal cord lesion segmentation and classification using two-dimensional MultiResUNet and DenseNet121 networks based on T2-weighted images. A retrospective cohort of 490 patients (118 patients with astrocytoma, 130 with ependymoma, 101 with multiple sclerosis [MS], and 141 with neuromyelitis optica spectrum disorders [NMOSD]) was used for model development, and a prospective cohort of 157 patients (34 patients with astrocytoma, 45 with ependymoma, 33 with MS, and 45 with NMOSD) was used for model testing. In the test cohort, the model achieved Dice scores of 0.77, 0.80, 0.50, and 0.58 for segmentation of astrocytoma, ependymoma, MS, and NMOSD, respectively, against manual labeling. Accuracies of 96% (area under the receiver operating characteristic curve [AUC], 0.99), 82% (AUC, 0.90), and 79% (AUC, 0.85) were achieved for the classifications of tumor versus demyelinating lesion, astrocytoma versus ependymoma, and MS versus NMOSD, respectively. In a subset of radiologically difficult cases, the classifier showed an accuracy of 79%-95% (AUC, 0.78-0.97). The established deep learning pipeline for segmentation and classification of spinal cord lesions can support an accurate radiologic diagnosis. Supplemental material is available for this article. © RSNA, 2022 Keywords: Spinal Cord MRI, Astrocytoma, Ependymoma, Multiple Sclerosis, Neuromyelitis Optica Spectrum Disorder, Deep Learning.

Identification and validation of rice reference proteins for western blotting.

Studies of rice protein expression have increased considerably with the development of rice functional genomics. In order to obtain reliable expression results in western blotting, information on appropriate reference proteins is necessary for data normalization. To date, no published study has identified and systematically validated reference proteins suitable for the investigation of rice protein expression. In this study, nine candidate proteins were selected and their specific antibodies were obtained through immunization of rabbits with either recombinant proteins expressed in Escherichia coli or synthesized peptides. Western blotting was carried out to detect the expression of target proteins in a set of 10 rice samples representing different rice tissues/organs at different developmental stages. The expression stability of the proteins was analysed using geNorm and Microcal Origin 6.0 software. The results indicated that heat shock protein (HSP) and elongation factor 1-α (eEF-1α) were the most constantly expressed among all rice proteins tested throughout all developmental stages, while the proteins encoded by conventional internal reference genes fluctuated in amount. Comparison among the profiling of translation and transcription [expressed sequence tags (EST) and massively parallel signature sequencing (MPSS)] revealed that a correlation existed. Based on the standard curves derived from the antigen-antibody reaction, the concentrations of HSP and eEF-1α proteins in rice leaves were ∼0.12%. Under the present experimental conditions, the lower limits of detection for HSP and eEF-1α proteins in rice were 0.24 ng and 0.06 ng, respectively. In conclusion, the reference proteins selected in this study, and the corresponding antibodies, can be used in qualitative and quantitative analysis of rice proteins.

Effect of Osmotic Stress on the Growth, Development and Pathogenicity of Setosphaeria turcica.

Osmotic stress is a severe condition frequently encountered by microorganisms; however, there is limited knowledge on the influence of hyperosmotic stress on the growth, development and pathogenicity of phytopathogenic fungi. Here, three osmotic conditions (0.4 M NaCl, 0.4 M KCl, and 0.6 M sorbitol supplemented in potato dextrose agar medium) were used to identify the effect of osmotic stress on the growth, development and pathogenicity of Setosphaeria turcica which is a plant pathogenic fungus and causes northern corn leaf blight disease in maize, sorghum, and related grasses. In osmotic stress, the growth rate of mycelium was decreased, and the number of vesicular structures and flocculent secretion outside the hypha cell wall were significantly increased. The qRT-PCR results showed that the osmotic stress quickly activated the HOG-MAPK pathway, up-regulated the expression of the downstream genes, and these genes were most highly expressed within 30 min of exposure to osmotic stress. Furthermore, the germination rate and the yield of conidia were significantly higher under osmotic stress than in the control. A pathogenicity analysis confirmed that pathogenicity of the conidia which were cultured under osmotic stress was significantly enhanced. By analyzing the knock-out mutants of an osmotic stress responsed gene StFPS1, an aquaglyceroporin downstream of the HOG-MAPK pathway, we found that StFPS1 was involved in the formation of appressorium and penetration peg, which affected the penetration ability of S. turcica. In summary, our work explained the correlation between osmotic stress and growth, development, and pathogenicity in S. turcica.

Comparative proteomic analysis reveals insights into the dynamic responses of maize (Zea mays L.) to Setosphaeria turcica infection.

Maize (Zea mays L.) production is severely affected by northern corn leaf blight (NCLB), which is a destructive foliar disease caused by Setosphaeria turcica. In recent years, studies on the interaction between maize and S. turcica have been focused at the transcription level, with no research yet at the protein level. Here, we applied tandem mass tag labelling and liquid chromatography-tandem mass spectrometry to investigate the proteomes of maize leaves at 24 h and 72 h post-inoculation (hpi) with S. turcica. In total, 4740 proteins encoded by 4711 genes were quantified in this study. Clustering analyses provided an understanding of the dynamic reprogramming of leaves proteomes by revealing the functions of different proteins during S. turcica infection. Screening and classification of differentially expressed proteins (DEPs) revealed that numerous defense-related proteins, including defense marker proteins and proteins related to the phenylpropanoid lignin biosynthesis, benzoxazine biosynthesis and the jasmonic acid signalling pathway, participated in the defense responses of maize to S. turcica infection. Furthermore, the earlier induction of GST family proteins contributed to the resistance to S. turcica. In addition, the protein-protein interaction network of DEPs suggests that some defense-related proteins, for example, ZmGEB1, a hub node, play key roles in defense responses against S. turcica infection. Our study findings provide insight into the complex responses triggered by S. turcica at the protein level and lay the foundation for studying the interaction process between maize and S. turcica infection.

Aging-dependent loss of GAP junction proteins Cx46 and Cx50 in the fiber cells of human and mouse lenses accounts for the diminished coupling conductance.

The homeostasis of the ocular lens is maintained by a microcirculation system propagated through gap junction channels. It is well established that the intercellular communications of the lens become deteriorative during aging. However, the molecular basis for this change in human lenses has not been well defined. Here, we present evidence to show that over 90% of Cx46 and Cx50 are lost in the fiber cells of normal human lenses aged 50 and above. From transparent to cataractous lenses, while Cx43 was upregulated, both Cx46 and Cx50 were significantly down-regulated in the lens epithelia. During aging of mouse lenses, Cx43 remained unchanged, but both Cx46 and Cx50 were significantly downregulated. Under oxidative stress treatment, mouse lenses develop in vitro cataractogenesis. Associated with this process, Cx43 was significantly upregulated, in contrast, Cx46 and Cx50 were sharply downregulated. Together, our results for the first time reveal that downregulation in Cx46 and Cx50 levels appears to be the major reason for the diminished coupling conductance, and the aging-dependent loss of Cx46 and Cx50 promotes senile cataractogenesis.

PP-1ß and PP-2Aα modulate cAMP response element-binding protein (CREB) functions in aging control and stress response through de-regulation of αB-crystallin gene and p300-p53 signaling axis.

The function of the transcription factor, cAMP response element-binding protein (CREB), is activated through S133 phosphorylation by PKA and others. Regarding its inactivation, it is not well defined. cAMP response element-binding protein plays an essential role in promoting cell proliferation, neuronal survival and the synaptic plasticity associated with long-term memory. Our recent studies have shown that CREB is an important player in mediating stress response. Here, we have demonstrated that CREB regulates aging process through suppression of αB-crystallin and activation of the p300-p53-Bak/Bax signaling axis. First, we determined that two specific protein phosphatases, PP-1ß and PP-2Aα, can inactivate CREB through S133 dephosphorylation. Subsequently, we demonstrated that cells expressing the S133A-CREB, a mutant mimicking constant dephosphorylation at S133, suppress CREB functions in aging control and stress response. Mechanistically, S133A-CREB not only significantly suppresses CREB control of αB-crystallin gene, but also represses CREB-mediated activation of p53 acetylation and downstream Bak/Bax genes. cAMP response element-binding protein suppression of αB-crystallin and its activation of p53 acetylation are major molecular events observed in human cataractous lenses of different age groups. Together, our results demonstrate that PP-1ß and PP-2Aα modulate CREB functions in aging control and stress response through de-regulation of αB-crystallin gene and p300-p53-Bax/Bak signaling axis, which regulates human cataractogenesis in the aging lens.

The E3 Ligase PIAS1 Regulates p53 Sumoylation to Control Stress-Induced Apoptosis of Lens Epithelial Cells Through the Proapoptotic Regulator Bax.

Protein sumoylation is one of the most important post-translational modifications regulating many biological processes (Flotho A & Melchior F. 2013. Ann Rev. Biochem. 82:357-85). Our previous studies have shown that sumoylation plays a fundamental role in regulating lens differentiation (Yan et al., 2010. PNAS, 107(49):21034-9.; Gong et al., 2014. PNAS. 111(15):5574-9). Whether sumoylation is implicated in lens pathogenesis remains elusive. Here, we present evidence to show that the protein inhibitor of activated STAT-1 (PIAS1), a E3 ligase for sumoylation, is implicated in regulating stress-induced lens pathogenesis. During oxidative stress-induced cataractogenesis, expression of PIAS1 is significantly altered at both mRNA and protein levels. Upregulation and overexpression of exogenous PIAS1 significantly enhances stress-induced apoptosis. In contrast, silence of PIAS1 with CRISPR/Cas9 technology attenuates stress-induced apoptosis. Mechanistically, different from other cells, PIAS1 has little effect to activate JNK but upregulates Bax, a major proapoptotic regulator. Moreover, Bax upregulation is derived from the enhanced transcription activity of the upstream transcription factor, p53. As revealed previously in other cells by different laboratories, our data also demonstrate that PIAS1 promotes SUMO1 conjugation of p53 at K386 residue in lens epithelial cells and thus enhances p53 transcription activity to promote Bax upregulation. Silence of Bax expression largely abrogates PIAS1-mediated enhancement of stress-induced apoptosis. Thus, our results demonstrated that PIAS1 promotes oxidative stress-induced apoptosis through positive control of p53, which specifically upregulates expression of the downstream proapoptotic regulator Bax. As a result, PIAS1-promoted apoptosis induced by oxidative stress is implicated in lens pathogenesis.

Dynamic changes of T cell receptor repertoires in patients with hepatitis B virus-related acute-on-chronic liver failure.

BACKGROUND AND AIMS: T cell-mediated immune injury plays a critical role in the pathogenesis of hepatitis B virus-related acute-on-chronic liver failure (HBV-ACLF). Given the high short-term mortality and crucial role of T cells in the disease progression, it is necessary to investigate the dynamics of T cell clones during HBV-ACLF. The aim of this study was to longitudinally investigate dynamic changes in the composition and perturbation of T cell receptor ß (TCRß) chain repertoires and to determine whether TCR repertoire characteristics were associated with HBV-ACLF patient outcomes. METHODS: Peripheral blood mononuclear cells (PBMCs) were collected at two time points from 5 HBV-ACLF patients. Global CD4+ and CD8+ T cells were sorted using magnetic beads. TCRß complementarity-determining region 3 was analyzed by unbiased high-throughput sequencing. RESULTS: During HBV-ACLF, there was a significant decrease in the diversity of T cell repertoires and an increase in proportion of the most 100 abundant clonotypes of CD8 T cells but not CD4. Decreased CD8 repertoire diversity was positively correlated with the reduction of the Model for End-Stage Liver Disease (MELD) score. CONCLUSIONS: There was significant clonal expansion in CD8 but not in CD4 T cell repertoires in HBV-ACLF patients during disease progression. Patients with greater clonal expansions in CD8 T cell repertoires may have better outcomes. CD8 TCRß repertoire diversity may serve as a potential predictive marker for disease outcome.

Influence of Oxidation Damages on Mechanical Properties of SiC/SiC Composite Using Domestic Hi-Nicalon Type SiC Fibers.

Here, we show that when the oxidation treatment temperature exceeded 600°C, the tensile strength of SiC/SiC begins to decrease. Oxidation leads to the damages on the PyC fiber/matrix interface, which is replaced by SiO2 at higher temperature. The fracture mode converts from fiber pull-out to fiber-break as the fiber/matrix interface is filled with SiO2. Oxidation time also plays an important role in affecting the tensile strength of SiC/SiC. The tensile modulus decreases with temperature from RT to 800°C, then increases above 800°C due to the decomposition of remaining CSi x O y and crystallization of the SiC matrix. A special surface densification treatment performed in this study is confirmed to be an effective approach to reduce the oxidation damages and improve the tensile strength of SiC/SiC after oxidation.

Mechanical Properties and Failure Behavior of 3D-SiCf/SiC Composites with Different Interphases.

Continuous silicon carbide fiber-reinforced silicon carbide ceramic matrix composites (SiCf/SiC) are promising as thermal structural materials. In this work, the microstructure and static mechanical properties of 3D-SiCf/SiC with PyC, SiC, and PyC/SiC and without an interface prepared via polymer infiltration and pyrolysis (PIP) were investigated systematically in this paper. The results show that the microstructure and static mechanical properties of SiCf/SiC with an interphase layer were superior to the composites without an interlayer, and the interface debondings are existing in the composite without an interphase, resulting in a weak interface bonding. When the interphase is introduced, the interfacial shear strength is improved, the crack can be deflected, and the fracture energy can be absorbed. Meanwhile, the shear strength of the composites with PyC and PyC/SiC interfaces was 118 MPa and 124 MPa, respectively, and showing little difference in bending properties. This indicates that the sublayer SiC of the PyC/SiC multilayer interface limits the binding state and the plastic deformation of PyC interphase, and it is helpful to improve the mechanical properties of SiCf/SiC.