African Swine Fever Virus Modulates the Endoplasmic Reticulum Stress-ATF6-Calcium Axis to Facilitate Viral Replication.

ABSTRACTAfrican swine fever (ASF), caused by African swine fever virus (ASFV), is a devastating infectious disease of domestic pigs and wild boar, which threatens the global pig industry. The endoplasmic reticulum (ER) is a multifunctional signaling organelle in eukaryotic cells that is involved in protein synthesis, processing, posttranslational modification and quality control. As intracellular parasitic organisms, viruses have evolved several strategies to modulate ER functions to favor their life cycles. We have previously demonstrated that the differentially expressed genes associated with the unfolded protein response (UPR) (downstream the ER stress) are significantly enriched upon ASFV infection. However, the correlation between the ER stress or UPR and ASFV replication has not been illuminated yet. Here, we demonstrated that ASFV infection induces ER stress both in target cells and in vivo, and subsequently activates the activating transcription factor 6 (ATF6) branch of the UPR to facilitate viral replication. Mechanistically, ASFV infection disrupts intracellular calcium (Ca2+) homeostasis, while the ATF6 pathway facilitates ASFV replication by increasing the cytoplasmic Ca2+ level. More specifically, we demonstrated that ASFV infection triggers ER-dependent Ca2+ release via the inositol triphosphate receptor (IP3R) channel. Notably, we showed that the ASFV B117L protein plays crucial roles in ER stress and the downstream activation of the ATF6 branch, as well as the disruption of Ca2+ homeostasis. Taken together, our findings reveal for the first time that ASFV modulates the ER stress-ATF6-Ca2+ axis to facilitate viral replication, which provides novel insights into the development of antiviral strategies for ASFV.

High Photocytotoxicity Iridium(III) Complex Photosensitizer for Photodynamic Therapy Induces Antitumor Effect Through GPX4-Dependent Ferroptosis.

The development of small molecule photosensitizers based on iridium complex is limited by the mismatch between therapeutic effect and systemic toxicity, as well as the incomplete understanding of the molecular mechanism underlying cell death induction. Herein, a small molecule iridium complex IrC with high photocytotoxicity is synthesized, with half maximal inhibitory concentration as low as 91 nm, demonstrating excellent anti-tumor, relief of splenomegaly, and negligible side effects. Starting from the factors of effective photosensitizers, the in-depth theoretical analysis on photon absorption efficiency, energy transfer level matching, and properties of the triplet excited state of IrC is conducted. This also elucidates the feasibility of generating the high singlet oxygen quantum yield. In addition, the death mechanism induced by IrC is focused, innovatively utilizing GPX4-overexpression and GPX4-knockout cells via CRISPR/Cas9 technique to comprehensively verify ferroptosis and its further molecular mechanism. The generation of ROS mediated by IrC, along with the direct inhibition of GPX4 and glutathione, synergistically increased cellular oxidative stress and the level of lipid peroxidation. This study provides an effective approach for small molecule complexes to induce GPX4-dependent ferroptosis at low-dose photodynamic therapy.

Nogo-B inhibition facilitates cholesterol metabolism to reduce hypercholesterolemia.

The strategy of lowering cholesterol levels by promoting cholesterol excretion is still lacking, and few molecular targets act on multiple cholesterol metabolic processes. In this study, we find that Nogo-B deficiency/inhibition simultaneously promotes hepatic uptake of cholesterol and cholesterol excretion. Nogo-B deficiency decreases cholesterol levels by activating ATP-binding cassette transporters (ABCs), apolipoprotein E (ApoE), and low-density lipoprotein receptor (LDLR) expression. We discover that Nogo-B interacts with liver X receptor α (LXRα), and Nogo-B deficiency inhibits ubiquitination degradation of LXRα, thereby enhancing its function on cholesterol excretion. Decreased cellular cholesterol levels further activate SREBP2 and LDLR expression, thereby promoting hepatic uptake of cholesterol. Nogo-B inhibition decreases atherosclerotic plaques and cholesterol levels in mice, and Nogo-B levels are correlated to cholesterol levels in human plasma. In this study, Nogo-B deficiency/inhibition not only promotes hepatic uptake of blood cholesterol but also facilitates cholesterol excretion. This study reports a strategy to lower cholesterol levels by inhibiting Nogo-B expression to promote hepatic cholesterol uptake and cholesterol excretion.

Machine learning-assisted diagnosis of parotid tumor by using contrast-enhanced CT imaging features.

PURPOSE: This study aims to develop a machine learning diagnostic model for parotid gland tumors based on preoperative contrast-enhanced CT imaging features to assist in clinical decision-making. MATERIALS AND METHODS: Clinical data and contrast-enhanced CT images of 144 patients with parotid gland tumors from the Peking University School of Stomatology Hospital, collected from January 2019 to December 2022, were gathered. The 3D slicer software was utilized to accurately annotate the tumor regions, followed by exploring the correlation between multiple preoperative contrast-enhanced CT imaging features and the benign or malignant nature of the tumor, as well as the type of benign tumor. A prediction model was constructed using the k-nearest neighbors (KNN) algorithm. RESULTS: Through feature selection, four key features-morphology, adjacent structure invasion, boundary, and suspicious cervical lymph node metastasis-were identified as crucial in preoperative discrimination between benign and malignant tumors. The KNN prediction model achieved an accuracy rate of 94.44 %. Additionally, six features including arterial phase CT value, age, delayed phase CT value, pre-contrast CT value, venous phase CT value, and gender, were also significant in the classification of benign tumors, with a KNN prediction model accuracy of 95.24 %. CONCLUSION: The machine learning model based on preoperative contrast-enhanced CT imaging features can effectively discriminate between benign and malignant parotid gland tumors and classify benign tumors, providing valuable reference information for clinicians.

Continuous Covalent Organic Framework Membranes with Ordered Nanochannels as Tunable Transport Layers for Fast Butanol/Water Separation.

Polymeric membranes with high permselective performance are desirable for energy-saving bioalcohol separations. However, it remains challenging to design membrane microstructures with low-resistance channels and a thin thickness for fast alcohol transport. Herein, we demonstrate highly crystalline covalent organic framework (COF) membranes with ordered nanochannels as tunable transport layers for efficient butanol/water separation. The thickness was well-regulated by altering the concentration and molar ratio of two aldehyde monomers with different reactivity. The surface-integrated poly(dimethylsiloxane) produced defect-free and hydrophobic COF membranes. The membrane with continuous transport channels exhibited an exceptional flux of up to 18.8 kg m-2 h-1 and a pervaporation separation index of 217.7 kg m-2 h-1 for separating 5 wt % n-butanol/water. The separation efficiency exceeded that of analogous membranes. The calculated mass-transfer coefficient of butanol followed an inverse relationship with the COF membrane thickness. Consequently, this work reveals the great potential of crystalline polymeric membranes with high-density nanopores for biofuel recovery.

Argonaute-2 autoantibodies: a promising biomarker for predicting mortality in HBV-related acute-on-chronic liver failure patients with cirrhosis.

Background & aims: HBV infection initiates autoimmune responses, leading to autoantibody generation. This research explores the role of autoantibodies in HBV-related Acute-on-Chronic Liver Failure (ACLF), offering novel perspectives for clinical management. Method: We applied immunoprecipitation and iTRAQ techniques to screen for autoantibodies in serum from HBV-related cirrhosis patients and conducted detection with conformation- stabilizing ELISA in a cohort of 238 HBV-infected individuals and 49 health controls. Our results were validated in a retrospective cohort comprising 106 ACLF patients and further assessed through immunohistochemical analysis in liver tissues from an additional 10 ACLF cases. Results: Utilizing iTRAQ, we identified Argonaute1-3 autoantibodies (AGO-Abs) in this research. AGO2-Abs notably increased in cirrhosis, decompensation, and further in ACLF, unlike AGO1-Abs and AGO3-Abs. This reflects disease severity correlation. Logistic regression and COX models confirmed AGO2-Abs as independent prognostic indicators for decompensated liver cirrhosis (DLC) and ACLF. In the ROC analysis, AGO2-Abs showed significant diagnostic value for predicting 28- and 90-day mortality (AUROC = 0.853 and 0.854, respectively). Furthermore, combining AGO2-Abs with the Child-Pugh, MELD, and AARC scores significantly improved their predictive accuracy (P < 0.05). Kaplan-Meier analysis showed poorer survival for AGO2-Abs levels above 99.14µg/ml. These findings were supported by a retrospective validation cohort. Additionally, immunohistochemistry revealed band-like AGO2 expression in periportal liver areas, with AGO2-Abs levels correlating with total bilirubin, indicating a potential role in exacerbating liver damage through periportal functions. Conclusions: AGO2-Abs is a robust biomarker for predicting the mortality of patients with HBV-related ACLF.

Research progress on nonsteroidal anti-inflammatory drugs in the treatment of pituitary neuroendocrine tumors.

Pituitary neuroendocrine tumor is the third most common primary intracranial tumor. Its main clinical manifestations include abnormal hormone secretion symptoms, symptoms caused by tumor compression of the surrounding pituitary tissue, pituitary stroke, and other anterior pituitary dysfunction. Its pathogenesis is yet to be fully understood. Surgical treatment is still the main treatment. Despite complete resection, 10%-20% of tumors may recur. While dopamine agonists are effective in over 90% of prolactinomas, prolonged use and individual variations can lead to increased drug resistance and a gradual decline in efficacy, which ultimately requires surgical intervention. Nonsteroidal anti-inflammatory drugs reduce the production of inflammatory mediator prostaglandins by inhibiting the activity of cyclooxygenase and exert antipyretic, analgesic, antiplatelet, and anti-inflammatory effects. In recent years, many in-depth studies have confirmed the potential of nonsteroidal anti-inflammatory drugs as a preventive and antitumor agent. It has been extensively utilized in the prevention and treatment of various types of cancer. However, their specific mechanisms of action still need to be fully elucidated. This article summarizes recent research progress on the expression of cyclooxygenase in pituitary neuroendocrine tumors and the treatment of nonsteroidal anti-inflammatory drugs. It provides a feasible theoretical basis for further research on pituitary neuroendocrine tumors and explores potential therapeutic targets.

An integrated approach for discrimination of Magnoliae officinalis cortex before and after being processed by ginger juice combining LC/MS, GC/MS, intelligent sensors, and chemometrics.

INTRODUCTION: Magnoliae officinalis cortex (MOC) is an important traditional Chinese medicine (TCM), and both raw and stir-fried MOC were commonly used in clinic. OBJECTIVES: This study aimed to discriminate MOC and MOC stir-fried with ginger juice (MOCG) using an integrated approach combining liquid chromatography/mass spectrometry (LC/MS), gas chromatography/mass spectrometry (GC/MS), intelligent sensors, and chemometrics. METHODS: The sensory characters of the samples were digitalized using intelligent sensors, i.e., colorimeter, electronic nose, and electronic tongue. Meanwhile, the chemical profiles of the samples were analyzed using LC/MS and GC/MS methods. Chemometric models were constructed to discriminate samples of MOC and MOCG based on not only the sensory data but also the chemical data. RESULTS: The differential sensory characters (L* and b* from colorimeter, ANS from electronic tongue, W1S and W2S from electronic nose) and the differential chemical compounds (26 and 11 compounds from LC/MS and GC/MS, respectively) were discovered between MOC and MOCG. Furthermore, twelve differential compounds showed good relations with differential sensory characters. Finally, artificial neural network models were established to discriminate samples of MOC and MOCG, in which W1S, W2S, ANS, b*, and 10 differential compounds were among the top 10 important variables, respectively. CONCLUSION: Samples of MOC and MOCG can be discriminated not only by the digitalized data of color, taste, and scent detected by intelligent sensors but also by chemical information obtained from LC/MS and GC/MS using chemometrics. The variations in sensory characters and chemical compounds between MOC and MOCG partially resulted from the Maillard reaction products and the oxidation of some compounds in the stir-frying process.

DEPDC1B: A novel tumor suppressor gene associated with immune infiltration in colon adenocarcinoma.

BACKGROUND: Recent research indicates a positive correlation between DEP structural domain-containing 1B (DEPDC1B) and the cell cycle in various tumors. However, the role of DEPDC1B in the infiltration of the tumor immune microenvironment (TIME) remains unexplored. METHODS: We analyzed the differential expression and prognostic significance of DEPDC1B in colon adenocarcinoma (COAD) using the R package "limma" and the Gene Expression Profiling Interactive Analysis (GEPIA) website. Gene set enrichment analysis (GSEA) was employed to investigate the functions and interactions of DEPDC1B expression in COAD. Cell Counting Kit-8 (CCK-8) assays and colony formation assays were utilized to assess the proliferative function of DEPDC1B. Correlations between DEPDC1B expression and tumor-infiltrating immune cells, immune checkpoints, tumor mutational burden (TMB), and microsatellite instability (MSI) status were examined using Spearman correlation analysis and CIBERSORT. RESULTS: DEPDC1B was highly expressed in COAD. Elevated DEPDC1B expression was associated with lower epithelial-to-mesenchymal transition (EMT) and TNM stages, leading to a favorable prognosis. DEPDC1B mRNA was prominently expressed in COAD cell lines. CCK-8 and colony formation assays demonstrated that DEPDC1B inhibited the proliferation of COAD cells. Analysis using the CIBERSORT database and Spearman correlation revealed that DEPDC1B correlated with four types of tumor-infiltrating immune cells. Furthermore, high DEPDC1B expression was linked to the expression of PD-L1, CTLA4, SIGLEC15, PD-L2, TMB, and MSI-H. High DEPDC1B expression also indicated responsiveness to anti-PD-L1 immunotherapy. CONCLUSIONS: DEPDC1B inhibits the proliferation of COAD cells and positively regulates the cell cycle, showing a positive correlation with CCNB1 and PBK expression. DEPDC1B expression in COAD is associated with tumor-infiltrating immune cells, immune checkpoints, TMB, and MSI-H in the tumor immune microenvironment. This suggests that DEPDC1B may serve as a novel prognostic marker and a potential target for immunotherapy in COAD.

Designing antibacterial materials through simulation and theory.

Antibacterial materials have a wide range of potential applications in bio-antimicrobial, environmental antimicrobial, and food antimicrobial fields due to their intrinsic antimicrobial properties, which can circumvent the development of drug resistance in bacteria. Understanding the intricate mechanisms and intrinsic nature of diverse antibacterial materials is significant for the formulation of guidelines for the design of materials with rapid and efficacious antimicrobial action and a high degree of biomedical material safety. Herein, this review highlights the recent advances in investigating antimicrobial mechanisms of different antibacterial materials with a particular focus on tailored computer simulations and theoretical analysis. From the view of structure and function, we summarize the characteristics and mechanisms of different antibacterial materials, introduce the latest advances of new antibacterial materials, and discuss the design concept and development direction of new materials. In addition, we underscore the significance of employing simulation and theoretical methodologies to elucidate the intrinsic antimicrobial mechanisms, which is crucial for a comprehensive comprehension of the control strategies, safer biomedical applications, and the management of health and environmental concerns associated with antibacterial materials. This review could potentially stimulate further endeavors in fundamental research and facilitate the extensive utilization of computational and theoretical approaches in the design of novel functional nanomaterials.

The transcriptional landscape and clinico-biological characterization of human endogenous retroviruses in esophageal squamous cell carcinoma.

Human endogenous retroviruses (HERVs) are emerging as critical elements in host genomic regulation. Aberrant HERV transcription has been implicated in developmental and tissue-specific aging and pathological processes. In this study, we presented a comprehensive locus-specific characterization of the HERV expression landscape in esophageal squamous cell carcinoma (ESCC). We demonstrated the transcriptional diversity among patients and identified 12 clinically relevant HERVs in the SCH cohort, which were experimentally validated by Real-Time Quantitative Polymerase Chain Reaction (RT-qPCR) in the CAMS cohort. ESCC patients were stratified into three HERV-based subtypes (HERVhigh, HERVmedian and HERVlow) with distinct clinical and biological characteristics. The HERVhigh subtype was associated with worse survival, increased CD4+ T cells infiltration and decreased metabolic activity, whereas the HERVlow subtype was characterized by abundant CD8+ T cells, increased metabolic activity, and better survival. The HERV-based tumor subtyping was further robustly validated by RNA sequencing and RT-qPCR in two additional external cohorts. Our findings demonstrate the clinical significance of HERVs for tumor subtyping and prognosis, provide insights into the functional role of HERVs and a valuable resource for developing novel biomarkers and therapeutic targets in ESCC.

Mapping Knowledge Landscapes and Emerging Trends in AI for Dementia Biomarkers: Bibliometric and Visualization Analysis.

BACKGROUND: With the rise of artificial intelligence (AI) in the field of dementia biomarker research, exploring its current developmental trends and research focuses has become increasingly important. This study, using literature data mining, analyzes and assesses the key contributions and development scale of AI in dementia biomarker research. OBJECTIVE: The aim of this study was to comprehensively evaluate the current state, hot topics, and future trends of AI in dementia biomarker research globally. METHODS: This study thoroughly analyzed the literature in the application of AI to dementia biomarkers across various dimensions, such as publication volume, authors, institutions, journals, and countries, based on the Web of Science Core Collection. In addition, scales, trends, and potential connections between AI and biomarkers were extracted and deeply analyzed through multiple expert panels. RESULTS: To date, the field includes 1070 publications across 362 journals, involving 74 countries and 1793 major research institutions, with a total of 6455 researchers. Notably, 69.41% (994/1432) of the researchers ceased their studies before 2019. The most prevalent algorithms used are support vector machines, random forests, and neural networks. Current research frequently focuses on biomarkers such as imaging biomarkers, cerebrospinal fluid biomarkers, genetic biomarkers, and blood biomarkers. Recent advances have highlighted significant discoveries in biomarkers related to imaging, genetics, and blood, with growth in studies on digital and ophthalmic biomarkers. CONCLUSIONS: The field is currently in a phase of stable development, receiving widespread attention from numerous countries, institutions, and researchers worldwide. Despite this, stable clusters of collaborative research have yet to be established, and there is a pressing need to enhance interdisciplinary collaboration. Algorithm development has shown prominence, especially the application of support vector machines and neural networks in imaging studies. Looking forward, newly discovered biomarkers are expected to undergo further validation, and new types, such as digital biomarkers, will garner increased research interest and attention.

Distinct characteristics of social anxiety among youths with childhood sexual abuse: A latent profile analysis.

BACKGROUND: Childhood sexual abuse (CSA) is one type of childhood trauma that has long-term effects on physical and mental health, predisposing to social anxiety. OBJECTIVE: This study attempted to investigate the characteristics of different subgroups of social anxiety among youths with CSA experiences. PARTICIPANTS AND SETTING: 83,219 participants were recruited in a cross-sectional study from 63 colleges and universities in Jilin Province, China. METHODS: The main variables were measured by a series of self-report questionnaires. Latent profile analysis was used to classify different subgroups of social anxiety, and multiple logistic regression was employed to investigate factors influencing transitions between different subgroups. RESULTS: 3022 (3.63 %) youths who suffered from CSA (46.8 % were male, Mage = 19.57, SD = 1.76) could be divided into four subgroups of social anxiety: low-risk social anxiety (16.4 %), medium-risk social anxiety with high public speaking anxiety (30.3 %), medium-risk social anxiety with no prominent characteristics (22.9 %), and high-risk social anxiety (30.4 %). Shy bladder and bowel and virtual life orientation increased the level of social anxiety from low to medium and high risk. Smoking and drinking were more prevalent in the low- and medium-risk subgroups than in the high-risk subgroup. CONCLUSIONS: There was heterogeneity in different subgroups of social anxiety among youths with CSA experiences. Potential targeted prevention and intervention suggestions could be beneficial in mitigating the risk of social anxiety and further preventing the aggravation of risk between subgroups.

Evidence of a causal relationship between blood pressure and pathological scars: a bidirectional Mendelian randomization study.

Background: Recent advancements in basic medicine and epidemiology suggest a potential influence of blood pressure on scar formation, yet the specifics of this relationship are not fully understood. This study aims to clarify the causal link between blood pressure and the development of pathological scars using Mendelian randomization (MR). Methods: This study employed genetic variants closely linked to blood pressure as instrumental variables to explore the relationship between blood pressure and pathological scars. The inverse variance weighted (IVW) method was used for analysis. Results: Our analysis identified a notable association where higher blood pressure was correlated with a lower risk of pathological scars. Specifically, an increase in diastolic blood pressure (odds ratio [OR] per standard deviation increase: 0.67 [95% Confidence Interval [CI], 0.49-0.99]), systolic blood pressure (OR per standard deviation increase: 0.66 [95% CI, 0.46-0.93]), and hypertension (pooled OR: 0.39 [95% CI, 0.18-0.85]) were significantly associated with a reduced risk of keloids. Similarly, a genetic predisposition to hypertension (pooled OR: 0.31 [95% CI, 0.11-0.89]) was significantly associated with a reduced risk of hypertrophic scars. Neither reverse MR analysis nor Steiger's test indicated a significant reverse causal relationship between hypertension and either keloids or hypertrophic scars. Conclusion: The findings suggest a protective role of higher blood pressure against the development of pathological scars, including keloids and hypertrophic scars. However, the inconsistency observed across different MR methods warrants cautious interpretation and underscores the need for further investigation to confirm these findings.

Revealing Dynamics of Protein Phosphorylation: A Study on the Cashmere Fineness Disparities in Liaoning Cashmere Goats.

Exploring the landscape of protein phosphorylation, this investigation focuses on skin samples from LCG (Liaoning Cashmere Goats), characterized by different levels of cashmere fineness. Employing LC-MS/MS technology, we meticulously scrutinized FT-LCG (fine-type Liaoning Cashmere Goats) and CT-LCG (coarse-type Liaoning Cashmere Goats). Identifying 512 modified proteins, encompassing 1368 phosphorylated peptide segments and 1376 quantifiable phosphorylation sites, our exploration further revealed consistent phosphorylation sites in both groups. Analysis of phosphorylated peptides unveiled kinase substrates, prominently featuring Protein Kinase C, Protein Kinase B and MAPK3-MAPK1-MAPK7-NLK-group. Differential analysis spotlighted 28 disparate proteins, comprising six upregulated and twenty-two downregulated. Cluster analysis showcased the robust clustering efficacy of the two sample groups. GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) enrichment analyses underscored the significance of the purine metabolism pathway, suggesting its pivotal role in modulating cashmere fineness in LCG. Notably, through differential protein analysis, two crucial proteins were identified: HSL-X (hormone-sensitive lipase isoform X1) and KPRP (keratinocyte proline-rich protein). Further evidence supports LIPE and KPRP as key genes regulating cashmere fineness, paving the way for promising avenues in further research. These findings not only contribute to a nuanced understanding of protein-level dynamics in cashmere but also provide a theoretical foundation for the selective breeding of superior Liaoning Cashmere Goat strands.

More is not always better: revealing the impact of cumulative risk on health-promoting behaviors among miners and the mediating role of health beliefs.

OBJECTIVE: Health-promoting behaviors carry substantial significance for miners' overall health and well-being. This study aimed to examine the association between cumulative risk (CR) and miners' health-promoting behaviors and test the mediating role of health beliefs in this relationship. METHODS: Data were collected from a sequential survey conducted among 712 frontline miners (Mage=41.7 ± 10.1 years) in China. The survey entailed online questionnaire measurements at three distinct time points, each spaced two weeks apart. This study utilized the conceptual model of health-promoting behaviors, the CR model, and structural equation modeling in the analysis of relationships. RESULTS: CR was negatively related to health-promoting behaviors, with a negative acceleration effect. CR was positively associated with perceived threat in a gradient effect, while negatively associated with perceived benefits in a gradient effect. Furthermore, CR was negatively related to self-efficacy, following a negative acceleration effect. Perceived threat, perceived benefits, and self-efficacy emerged as significant mediators in the relationship between CR and health-promoting behaviors. CONCLUSION: This study highlights the critical role of considering both CR and health beliefs in shaping miners' health-promoting behaviors. Understanding these dynamics is pivotal for developing interventions to enhance miners' health and well-being.

Postoperative facial prediction for mandibular defect based on surface mesh deformation.

OBJECTIVES: This study aims to introduce a novel predictive model for the post-operative facial contours of patients with mandibular defect, addressing limitations in current methodologies that fail to preserve geometric features and lack interpretability. METHODS: Utilizing surface mesh theory and deep learning, our model diverges from traditional point cloud approaches by employing surface triangular mesh grids. We extract latent variables using a Mesh Convolutional Restricted Boltzmann Machines (MCRBM) model to generate a three-dimensional deformation field, aiming to enhance geometric information preservation and interpretability. RESULTS: Experimental evaluations of our model demonstrate a prediction accuracy of 91.2 %, which represents a significant improvement over traditional machine learning-based methods. CONCLUSIONS: The proposed model offers a promising new tool for pre-operative planning in oral and maxillofacial surgery. It significantly enhances the accuracy of post-operative facial contour predictions for mandibular defect reconstructions, providing substantial advancements over previous approaches.

Increased Pan-Type, A1-Type, and A2-Type Astrocyte Activation and Upstream Inflammatory Markers Are Induced by the P2X7 Receptor.

This study asked whether the P2X7 receptor was necessary and sufficient to trigger astrocyte polarization into neuroinflammatory activation states. Intravitreal injection of agonist BzATP increased gene expression of pan-astrocyte activation markers Gfap, Steap4, and Vim and A1-type astrocyte activation markers C3, Serping1, and H2T23, but also the Cd14 and Ptx3 genes usually associated with the A2-type astrocyte activation state and Tnfa, IL1a, and C1qa, assumed to be upstream of astrocyte activation in microglia. Correlation analysis of gene expression suggested the P2X7 receptor induced a mixed A1/A2-astrocyte activation state, although A1-state genes like C3 increased the most. A similar pattern of mixed glial activation genes occurred one day after intraocular pressure (IOP) was elevated in wild-type mice, but not in P2X7-/- mice, suggesting the P2X7 receptor is necessary for the glial activation that accompanies IOP elevation. In summary, this study suggests stimulation of the P2X7R is necessary and sufficient to trigger the astrocyte activation in the retina following IOP elevation, with a rise in markers for pan-, A1-, and A2-type astrocyte activation. The P2X7 receptor is expressed on microglia, optic nerve head astrocytes, and retinal ganglion cells (RGCs) in the retina, and can be stimulated by the mechanosensitive release of ATP that accompanies IOP elevation. Whether the P2X7 receptor connects this mechanosensitive ATP release to microglial and astrocyte polarization in glaucoma remains to be determined.

Latent relation shared learning for endometrial cancer diagnosis with incomplete multi-modality medical images.

Magnetic resonance imaging (MRI), ultrasound (US), and contrast-enhanced ultrasound (CEUS) can provide different image data about uterus, which have been used in the preoperative assessment of endometrial cancer. In practice, not all the patients have complete multi-modality medical images due to the high cost or long examination period. Most of the existing methods need to perform data cleansing or discard samples with missing modalities, which will influence the performance of the model. In this work, we propose an incomplete multi-modality images data fusion method based on latent relation shared to overcome this limitation. The shared space contains the common latent feature representation and modality-specific latent feature representation from the complete and incomplete multi-modality data, which jointly exploits both consistent and complementary information among multiple images. The experimental results show that our method outperforms the current representative approaches in terms of classification accuracy, sensitivity, specificity, and area under curve (AUC). Furthermore, our method performs well under varying imaging missing rates.