COVID-19 immune features revealed by a large-scale single-cell transcriptome atlas.

A dysfunctional immune response in coronavirus disease 2019 (COVID-19) patients is a recurrent theme impacting symptoms and mortality, yet a detailed understanding of pertinent immune cells is not complete. We applied single-cell RNA sequencing to 284 samples from 196 COVID-19 patients and controls and created a comprehensive immune landscape with 1.46 million cells. The large dataset enabled us to identify that different peripheral immune subtype changes are associated with distinct clinical features, including age, sex, severity, and disease stages of COVID-19. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA was found in diverse epithelial and immune cell types, accompanied by dramatic transcriptomic changes within virus-positive cells. Systemic upregulation of S100A8/A9, mainly by megakaryocytes and monocytes in the peripheral blood, may contribute to the cytokine storms frequently observed in severe patients. Our data provide a rich resource for understanding the pathogenesis of and developing effective therapeutic strategies for COVID-19.

Generation of a Broadly Useful Model for COVID-19 Pathogenesis, Vaccination, and Treatment.

COVID-19, caused by SARS-CoV-2, is a virulent pneumonia, with >4,000,000 confirmed cases worldwide and >290,000 deaths as of May 15, 2020. It is critical that vaccines and therapeutics be developed very rapidly. Mice, the ideal animal for assessing such interventions, are resistant to SARS-CoV-2. Here, we overcome this difficulty by exogenous delivery of human ACE2 with a replication-deficient adenovirus (Ad5-hACE2). Ad5-hACE2-sensitized mice developed pneumonia characterized by weight loss, severe pulmonary pathology, and high-titer virus replication in lungs. Type I interferon, T cells, and, most importantly, signal transducer and activator of transcription 1 (STAT1) are critical for virus clearance and disease resolution in these mice. Ad5-hACE2-transduced mice enabled rapid assessments of a vaccine candidate, of human convalescent plasma, and of two antiviral therapies (poly I:C and remdesivir). In summary, we describe a murine model of broad and immediate utility to investigate COVID-19 pathogenesis and to evaluate new therapies and vaccines.

Publisher Correction: Exuberant fibroblast activity compromises lung function via ADAMTS4.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Exuberant fibroblast activity compromises lung function via ADAMTS4.

Severe respiratory infections can result in acute respiratory distress syndrome (ARDS)1. There are no effective pharmacological therapies that have been shown to improve outcomes for patients with ARDS. Although the host inflammatory response limits spread of and eventually clears the pathogen, immunopathology is a major contributor to tissue damage and ARDS1,2. Here we demonstrate that respiratory viral infection induces distinct fibroblast activation states, which we term extracellular matrix (ECM)-synthesizing, damage-responsive and interferon-responsive states. We provide evidence that excess activity of damage-responsive lung fibroblasts drives lethal immunopathology during severe influenza virus infection. By producing ECM-remodelling enzymes-in particular the ECM protease ADAMTS4-and inflammatory cytokines, damage-responsive fibroblasts modify the lung microenvironment to promote robust immune cell infiltration at the expense of lung function. In three cohorts of human participants, the levels of ADAMTS4 in the lower respiratory tract were associated with the severity of infection with seasonal or avian influenza virus. A therapeutic agent that targets the ECM protease activity of damage-responsive lung fibroblasts could provide a promising approach to preserving lung function and improving clinical outcomes following severe respiratory infections.

Advance of microfluidic flow cytometry enabling high-throughput characterization of single-cell electrical and structural properties.

This paper reported a micro flow cytometer capable of high-throughput characterization of single-cell electrical and structural features based on constrictional microchannels and deep neural networks. When single cells traveled through microchannels with constricted cross-sectional areas, they effectively blocked concentrated electric field lines, producing large impedance variations. Meanwhile, the traveling cells were confined within the cross-sectional areas of the constrictional microchannels, enabling the capture of high-quality images without losing focuses. Then single-cell features from impedance profiles and optical images were extracted from customized recurrent and convolution networks (RNN and CNN), which were further fused for cell-type classification based on support vector machines (SVM). As a demonstration, two leukemia cell lines (e.g., HL60 vs. Jurkat) were analyzed, producing high-classification accuracies of 99.3% based on electrical features extracted from Long Short-Term Memory (LSTM) of RNN, 96.7% based on structural features extracted from Resnet18 of CNN and 100.0% based on combined features enabled by SVM. The microfluidic flow cytometry developed in this study may provide a new perspective for the field of single-cell analysis.

B-Glycine as a marker for ß cell imaging and ß cell mass evaluation.

PURPOSE: ß cell mass (BCM) and function are essential to the diagnosis and therapy of diabetes. Diabetic patients serve ß cell loss is, and damage of ß cells leads to severe insulin deficiency. Our understanding of the role of BCM in diabetes progression is extremely limited by lacking efficient methods to evaluate BCM in vivo. In vitro methods of labeling islets, including loading of contrast reagent or integration of exogenous biomarker, require artificial manipulation on islets, of which the clinical application is limited. Imaging methods targeting endogenous biomarkers may solve the above problems. However, traditional reagents targeting GLP-1R and VAMT2 result in a high background of adjacent tissues, complicating the identification of pancreatic signals. Here, we report a non-invasive and quantitative imaging technique by using radiolabeled glycine mimics ([18F]FBG, a boron-trifluoride derivative of glycine) to assay islet function and monitor BCM changes in living animals. METHODS: Glycine derivatives, FBG, FBSa, 2Me-FBG, 3Me-FBG, were successfully synthesized and labeled with 18F. Specificity of glycine derivatives were characterized by in vitro experiment. PET imaging and biodistribution studies were performed in animal models carring GLYT over-expressed cells. In vivo evaluation of BCM with [18F]FBG were performed in STZ (streptozocin) induced T1D (type 1 diabetes) models. RESULTS: GLYT responds to excess blood glycine levels and transports glycine into islet cells to maintain the activity of the glycine receptor (GLYR). Best PET imaging condition was 80 min after given a total of 240 ~ 250 nmol imaging reagent (a mixture of [18F]FBG and natural glycine) intravenously. [18F]FBG can detect both endogenous and exogenous islets clearly in vivo. When applied to STZ induced T1D mouse models, total uptake of [18F]FBG in the pancreas exhibited a linear correlation with survival BCM. CONCLUSION: [18F]FBG targeting the endogenous glycine transporter (GLYT), which is highly expressed on islet cells, avoiding extra modification on islet cells. Meanwhile the highly restricted expression pattern of GLYT excluded the background in adjacent tissues. This [18F]FBG-based imaging technique provides a non-invasive method to quantify BCM in vivo, implying a new evaluation index for diabetic assessment.

Identification of multiple plasma lipids as diagnostic biomarkers of hypercholesterolemia and the underlying mechanisms based on pseudo-targeted lipidomics.

RATIONALE: Hypercholesterolemia is an important risk factor for cardiovascular diseases and death. This study performed pseudo-targeted lipidomics to identify differentially expressed plasma lipids in hypercholesterolemia, to provide a scientific basis for the diagnosis and pathogenesis of hypercholesterolemia. METHODS: Pseudo-targeted lipidomic analyses of plasma lipids from 20 patients with hypercholesterolemia and 20 normal control subjects were performed using liquid chromatography-mass spectrometry. Differentially expressed lipids were identified by principal component analysis and orthogonal partial least squares discriminant analysis. Receiver operating characteristic curves were used to identify differentially expressed lipids with high diagnostic value. The Kyoto Encyclopedia of Genes and Genomes pathway database was used to identify enriched metabolic pathways. RESULTS: We identified 13 differentially expressed lipids in hypercholesterolemia using variable importance of projection > 1 and p < 0.05 as threshold parameters. The levels of eight sphingomyelins and cholesterol sulfate were higher and those of three triacylglycerols and lysophosphatidylcholine were reduced in hypercholesterolemia. Seven differentially expressed plasma lipids showed high diagnostic value for hypercholesterolemia. Functional enrichment analyses showed that pathways related to necroptosis, sphingolipid signaling, sphingolipid metabolism, and steroid hormone biosynthesis were enriched. CONCLUSIONS: This pseudo-targeted lipidomics study demonstrated that multiple sphingomyelins and cholesterol sulfate were differentially expressed in the plasma of patients with hypercholesterolemia. We also identified seven plasma lipids, including six sphingomyelins and cholesterol sulfate, with high diagnostic value.

Serum sCD25 is an indicator for rheumatoid arthritis-associated interstitial lung disease.

OBJECTIVES: CD25 (IL-2Rα) is one of IL-2 receptor's polypeptide subunits, and its soluble form is increased in patients with various inflammatory or autoimmune diseases. This study aimed to evaluate the clinical correlation of serum soluble CD25 (sCD25) with interstitial lung disease (ILD) in rheumatoid arthritis (RA) patients. METHODS: 294 RA patients, including 72 in the discovery cohort (15 patients with ILD, 57 patients without ILD), 222 in the validation cohort (41 patients with ILD and 181 patients without ILD), and 58 healthy controls (HCs) were recruited. High-resolution computed tomography (HRCT) scan provided evidence and patterns of RA-ILD. Serum sCD25 concentrations were measured by enzyme-linked immunosorbent assay (ELISA). Clinical and laboratory data were recorded and the association with sCD25 was also analysed. RESULTS: In the discovery cohort, 16 RA-related molecules including cytokines, chemokines and functional soluble cell surface proteins were investigated. The results showed that sCD25 was significantly higher in RA-ILD than in RA-no-ILD group (p=0.004). ROC analysis also showed RA-ILD was discriminated with RA-no-ILD by sCD25 (AUC=0.695, 95% CI=0.541-0.849). Logistics regression demonstrated that sCD25 was one of the risk factors of RA-ILD. This result was further confirmed in validation cohort (p<0.001). According to the cut-off value in the discovery cohort, the sensitivity and specificity of sCD25 in RA-ILD were 51.2%, 77.3%, respectively. Compared with RA-no-ILD, serum level of sCD25 was also higher in different HRCT patterns including UIP, NSIP and RA-ILA. The ROC curves revealed sCD25 as diagnostic marker in UIP, NSIP and RA-ILA (with AUCs of 0.730, 0.761, and 0. 694, respectively, p<0.05). The result indicated that sCD25 was a biomarker for RA-ILD subtypes. Although sCD25 was not correlated with HRCT scores, it was significantly higher in consolidation pattern by HRCT. CONCLUSIONS: sCD25 was significantly elevated in RA-ILD (including UIP, NSIP and RA-ILA) compared to RA-no-ILD and HCs, which supports their value as a potential biomarker in RA-ILD screening and assessment.

Sitagliptin Extends Lifespan of Caenorhabditis elegans by Inhibiting Insulin/Insulin-Like Signaling and Activating Dietary Restriction-Like Signaling Pathways.

INTRODUCTION: The discovery of longevity molecules that delay aging and prolong lifespan has always been a dream of humanity. Sitagliptin phosphate (SIT), an oral dipeptidyl peptidase-4 (DPP-4) inhibitor, is an oral drug commonly used in the treatment of type 2 diabetes (T2D). In addition to being antidiabetic, previous studies have reported that SIT has shown potential to improve health. However, whether SIT plays a role in the amelioration of aging and the underlying molecular mechanism remain undetermined. METHODS: Caenorhabditis elegans (C. elegans) was used as a model of aging. Lifespan assays were performed with adult-stage worms on nematode growth medium plates containing FUdR with or without the specific concentration of SIT. The period of fast body movement, body bending rates, and pharyngeal pumping rates were recorded to assess the healthspan of C. elegans. Gene expression was confirmed by GFP fluorescence signal of transgenic worms and qPCR. In addition, the intracellular reactive oxygen species levels were measured using a free radical sensor H2DCF-DA. RESULTS: We found that SIT significantly extended lifespan and healthspan of C. elegans. Mechanistically, we found that several age-related pathways and genes were involved in SIT-induced lifespan extension. The transcription factors DAF-16/FOXO, SKN-1/NRF2, and HSF-1 played important roles in SIT-induced longevity. Moreover, our findings illustrated that SIT-induced survival benefits by inhibiting the insulin/insulin-like signaling pathway and activating the dietary restriction-related and mitochondrial function-related signaling pathways. CONCLUSION: Our work may provide a theoretical basis for the development of anti-T2D drugs as antiaging drugs, especially for the treatment of age-related disease in diabetic patients.

Analysis of the phytochemical components of Prunella vulgaris using high-performance liquid chromatography quadrupole time-of-flight mass spectrometry combined with molecular networking and assessment of their antioxidant and anti-α-glucosidase activities.

Prunella vulgaris has long been used in traditional medicine and is consumed as a tea in China. Here, the total phenolic and flavonoid concentrations of plants from different geographical regions were measured. It was found that the total phenolic acid concentration ranged from 4.15 to 8.82 g of gallic acid equivalent per 100 g of dry weight (DW), and the total flavonoid concentration was 4.67-7.33 g of rutin equivalent per 100 g DW. Antioxidant activities were measured using 2,2-diphenyl-1-picrylhydrazyl and 2,2'-azino-bis-(3-ethylbenzothiazoline-6-sulfonic acid) diammonium salt, and the results ranged from 73.47% to 94.43% and 74.54% to 93.39%, respectively, whereas α-glucosidase inhibition was between 75.31% and 95.49%. Correlation analysis showed that the total flavonoids in P. vulgaris had superior antioxidant and anti-α-glucosidase activities compared to the total phenolic compounds. The active components of P. vulgaris were analyzed using high-performance liquid chromatography quadrupole time-of-flight mass spectrometry combined with both classical molecular networking and feature-based molecular networking on the Global Natural Products Social platform, identifying 32 compounds, namely 14 flavonoids, 12 phenolic compounds, and 6 other chemical components. These results could provide useful information on the use of P. vulgaris as a functional tea.

[A unicenter real-world study of the correlation factors for complete clinical response in idiopathic inflammatory myopathies].

OBJECTIVE: To investigate the correlation factors of complete clinical response in idiopathic inflammatory myopathies (IIMs) patients receiving conventional treatment. METHODS: Patients diagnosed with IIMs hospitalized in Peking University People's Hospital from January 2000 to June 2023 were included. The correlation factors of complete clinical response to conventional treatment were identified by analyzing the clinical characteristics, laboratory features, peripheral blood lymphocytes, immunological indicators, and therapeutic drugs. RESULTS: Among the 635 patients included, 518 patients finished the follow-up, with an average time of 36.8 months. The total complete clinical response rate of IIMs was 50.0% (259/518). The complete clinical response rate of dermatomyositis (DM), anti-synthetase syndrome (ASS) and immune-mediated necrotizing myopathy (IMNM) were 53.5%, 48.9% and 39.0%, respectively. Fever (P=0.002) and rapid progressive interstitial lung disease (RP-ILD) (P=0.014) were observed much more frequently in non-complete clinical response group than in complete clinical response group. The aspartate transaminase (AST), lactate dehydrogenase (LDH), D-dimer, erythrocyte sedimentation rate (ESR), C-reaction protein (CRP) and serum ferritin were significantly higher in non-complete clinical response group as compared with complete clinical response group. As for the treatment, the percentage of glucocorticoid received and intravenous immunoglobin (IVIG) were significantly higher in non-complete clinical response group than in complete clinical response group. Risk factor analysis showed that IMNM subtype (P=0.007), interstitial lung disease (ILD) (P=0.001), eleva-ted AST (P=0.012), elevated serum ferritin (P=0.016) and decreased count of CD4+T cells in peripheral blood (P=0.004) might be the risk factors for IIMs non-complete clinical response. CONCLUSION: The total complete clinical response rate of IIMs is low, especially for IMNM subtype. More effective intervention should be administered to patients with ILD, elevated AST, elevated serum ferritin or decreased count of CD4+T cells at disease onset.

Metagenome-wide association study of gut microbiome features for myositis.

PURPOSE: The clinical relevance and pathogenic role of gut microbiome in both myositis and its associated interstitial lung disease (ILD) are still unclear. The purpose of this study was to investigate the role of gut microbiome in myositis through comprehensive metagenomic-wide association studies (MWAS). METHODS: We conducted MWAS of the myositis gut microbiome in a Chinese cohort by using whole-genome shotgun sequencing of high depth, including 30 myositis patients and 31 healthy controls (HC). Among the myositis patients, 11 developed rapidly progressive interstitial lung disease (RP-ILD) and 10 had chronic ILD (C-ILD). RESULTS: Analysis for overall distribution level of the bacteria showed Alistipes onderdonkii, Parabacteroides distasonis and Escherichia coli were upregulated, Lachnospiraceae bacterium GAM79, Roseburia intestinalis, and Akkermansia muciniphila were downregulated in patients with myositis compared to HC. Bacteroides thetaiotaomicron, Parabacteroides distasonis and Escherichia coli were upregulated, Bacteroides A1C1 and Bacteroides xylanisolvens were downregulated in RP-ILD cases compared with C-ILD cases. A variety of biological pathways related to metabolism were enriched in the myositis and HC, RP-ILD and C-ILD comparison. And in the analyses for microbial contribution in metagenomic biological pathways, we have found that E. coli played an important role in the pathway expression in both myositis group and myositis-associated RP-ILD group. Anti-PL-12 antibody, anti-Ro-52 antibody, and anti-EJ antibody were found to have positive correlation with bacterial diversity (Shannon-wiener diversity index and Chao1, richness estimator) between myositis group and control groups. The combination of E. coli and R. intestinalis could distinguish myositis group from HC effectively. R. intestinalis can also be applied in the distinguishment of RP-ILD group vs. C-ILD group in myositis patients. CONCLUSION: Our MWAS study first revealed the link between gut microbiome and pathgenesis of myositis, which may help us understand the role of gut microbiome in the etiology of myositis and myositis-associated RP-ILD.

Plasma cell-free DNA promise monitoring and tissue injury assessment of COVID-19.

Coronavirus 2019 (COVID-19) is a complex disease that affects billions of people worldwide. Currently, effective etiological treatment of COVID-19 is still lacking; COVID-19 also causes damages to various organs that affects therapeutics and mortality of the patients. Surveillance of the treatment responses and organ injury assessment of COVID-19 patients are of high clinical value. In this study, we investigated the characteristic fragmentation patterns and explored the potential in tissue injury assessment of plasma cell-free DNA in COVID-19 patients. Through recruitment of 37 COVID-19 patients, 32 controls and analysis of 208 blood samples upon diagnosis and during treatment, we report gross abnormalities in cfDNA of COVID-19 patients, including elevated GC content, altered molecule size and end motif patterns. More importantly, such cfDNA fragmentation characteristics reflect patient-specific physiological changes during treatment. Further analysis on cfDNA tissue-of-origin tracing reveals frequent tissue injuries in COVID-19 patients, which is supported by clinical diagnoses. Hence, our work demonstrates and extends the translational merit of cfDNA fragmentation pattern as valuable analyte for effective treatment monitoring, as well as tissue injury assessment in COVID-19.

A diagnostic model for sepsis-induced acute lung injury using a consensus machine learning approach and its therapeutic implications.

BACKGROUND: A significant proportion of septic patients with acute lung injury (ALI) are recognized late due to the absence of an efficient diagnostic test, leading to the postponed treatments and consequently higher mortality. Identifying diagnostic biomarkers may improve screening to identify septic patients at high risk of ALI earlier and provide the potential effective therapeutic drugs. Machine learning represents a powerful approach for making sense of complex gene expression data to find robust ALI diagnostic biomarkers. METHODS: The datasets were obtained from GEO and ArrayExpress databases. Following quality control and normalization, the datasets (GSE66890, GSE10474 and GSE32707) were merged as the training set, and four machine learning feature selection methods (Elastic net, SVM, random forest and XGBoost) were applied to construct the diagnostic model. The other datasets were considered as the validation sets. To further evaluate the performance and predictive value of diagnostic model, nomogram, Decision Curve Analysis (DCA) and Clinical Impact Curve (CIC) were constructed. Finally, the potential small molecular compounds interacting with selected features were explored from the CTD database. RESULTS: The results of GSEA showed that immune response and metabolism might play an important role in the pathogenesis of sepsis-induced ALI. Then, 52 genes were identified as putative biomarkers by consensus feature selection from all four methods. Among them, 5 genes (ARHGDIB, ALDH1A1, TACR3, TREM1 and PI3) were selected by all methods and used to predict ALI diagnosis with high accuracy. The external datasets (E-MTAB-5273 and E-MTAB-5274) demonstrated that the diagnostic model had great accuracy with AUC value of 0.725 and 0.833, respectively. In addition, the nomogram, DCA and CIC showed that the diagnostic model had great performance and predictive value. Finally, the small molecular compounds (Curcumin, Tretinoin, Acetaminophen, Estradiol and Dexamethasone) were screened as the potential therapeutic agents for sepsis-induced ALI. CONCLUSION: This consensus of multiple machine learning algorithms identified 5 genes that were able to distinguish ALI from septic patients. The diagnostic model could identify septic patients at high risk of ALI, and provide potential therapeutic targets for sepsis-induced ALI.

Antibacterial and antibiofilm efficacy of repurposing drug hexestrol against methicillin-resistant Staphylococcus aureus.

There has been an explosion in the prevalence of methicillin-resistant Staphylococcus aureus (MRSA) because of the indiscriminate use of antibiotics. In this study, we repurposed hexestrol (HXS) as an antibacterial agent to fight planktonic and biofilm-related MRSA infections. HXS is a nonsteroidal synthetic estrogen that targets estrogen receptors (ERα and ERß) and has been used as a hormonal antineoplastic agent. In our work, the minimum inhibitory concentrations (MICs) were determined using the antimicrobial susceptibility of MSSA and MRSA strains. Anti-biofilm activity was evaluated using biofilm inhibition and eradication assays. Biofilm-related genes were analyzed with or without HXS treatment using RTqPCR analysis of S. aureus. HXS was tested using the checkerboard dilution assay to identify antibiotics that may have synergistic effects. Measurement of ATP and detection of ATPase allowed the determination of bacterial energy metabolism. As shown in the results, HXS showed effective antimicrobial activity against S. aureus, including both type strains and clinical isolations, with MICs of 16 µg/mL. Sub-HXS strongly inhibited the adhesion of S. aureus. The content of extracellular polymeric substances (EPS) and the relative transcription levels of eno, sacC, clfA, pls and fnbpB were reduced after HXS treatment. HXS showed antibacterial effects against S. aureus and synergistic activity with aminoglycosides by directly interfering with cellular energy metabolism. HXS inhibits adhesion and biofilm formation and eradicates biofilms formed by MRSA by reducing the expression of related genes. Furthermore, HXS increases the susceptibility of aminoglycosides against MRSA. In conclusion, HXS is a repurposed drug that may be a promising therapeutic option for MRSA infection.

Toward five-part differential of leukocytes based on electrical impedances of single cells and neural network.

The five-part differential of leukocytes plays key roles in the diagnosis of a variety of diseases and is realized by optical examinations of single cells, which is prone to various artifacts due to chemical treatments. The classification of leukocytes based on electrical impedances without cell treatments has not been demonstrated because of limitations in approaches of impedance acquisition and data processing. In this study, based on treatment-free single-cell impedance profiles collected from impedance flow cytometry leveraging constriction microchannels, two types of neural pattern recognition were conducted for comparisons with the purpose of realizing the five-part differential of leukocytes. In the first approach, 30 features from impedance profiles were defined manually and extracted automatically, and then a feedforward neural network was conducted, producing a classification accuracy of 84.9% in the five-part leukocyte differential. In the second approach, a customized recurrent neural network was developed to process impedance profiles directly and based on deep learning, a classification accuracy of 97.5% in the five-part leukocyte differential was reported. These results validated the feasibility of the five-part leukocyte differential based on label-free impedance profiles of single cells and thus provide a new perspective of differentiating white blood cells based on impedance flow cytometry.

Integrative evaluation and experimental validation of the immune-modulating potential of dysregulated extracellular matrix genes in high-grade serous ovarian cancer prognosis.

BACKGROUND: High-grade serous ovarian cancer (HGSOC) is a challenging malignancy characterized by complex interactions between tumor cells and the surrounding microenvironment. Understanding the immune landscape of HGSOC, particularly the role of the extracellular matrix (ECM), is crucial for improving prognosis and guiding therapeutic interventions. METHODS AND RESULTS: Using univariate Cox regression analysis, we identified 71 ECM genes associated with prognosis in seven HGSOC populations. The ECMscore signature, consisting of 14 genes, was validated using Cox proportional hazards regression with a lasso penalty. Cox regression analyses demonstrated that ECMscore is an excellent indicator for prognostic classification in prevalent malignancies, including HGSOC. Moreover, patients with higher ECMscores exhibited more active stromal and carcinogenic activation pathways, including apical surface signaling, Notch signaling, apical junctions, Wnt signaling, epithelial-mesenchymal transition, TGF-beta signaling, and angiogenesis. In contrast, patients with relatively low ECMscores showed more active immune-related pathways, such as interferon alpha response, interferon-gamma response, and inflammatory response. The relationship between the ECMscore and genomic anomalies was further examined. Additionally, the correlation between ECMscore and immune microenvironment components and signals in HGSOC was examined in greater detail. Moreover, the expression of MGP, COL8A2, and PAPPA and its correlation with FAP were validated using qRT-PCR on samples from HGSOC. The utility of ECMscore in predicting the prospective clinical success of immunotherapy and its potential in guiding the selection of chemotherapeutic agents were also explored. Similar results were obtained from pan-cancer research. CONCLUSION: The comprehensive evaluation of the ECM may help identify immune activation and assist patients in HGSOC and even pan-cancer in receiving proper therapy.

Prognostic value of fibroblast activation protein expressing tumor volume calculated from [68 Ga]Ga-FAPI PET/CT in patients with esophageal squamous cell carcinoma.

BACKGROUND: This study aimed to investigate the prognostic value of semiquantitative parameters derived from [68 Ga]Ga-fibroblast activation protein inhibitor (FAPI) PET/CT for patients with esophageal squamous cell carcinoma (ESCC) treated with definitive chemoradiotherapy. METHODS: We conducted a retrospective analysis on patients from a prospective parent study (NCT04416165). A total of 45 patients with locally advanced ESCC who underwent [68 Ga]Ga-FAPI from December 2019 to March 2021 were included. The maximum standard uptake value (SUVmax), gross tumor volume (GTV), and total lesion-FAPI (TL-FAPI) of the primary tumor were calculated from the corresponding PET/CT image. Unpaired parameters were compared using Student's t test or the Mann-Whitney U test. Paired parameters were compared using the paired t test or the Wilcoxon matched-pairs signed-rank test. Kaplan-Meier curves were generated to calculate progression-free survival (PFS) and overall survival (OS) rates, and Cox regression analysis was performed to determine which PET/CT parameters were prognostic factors for PFS and/or OS. RESULTS: Thirty-four of the 45 patients met the criteria, and the median follow-up time was 24 months (16-29 months). SUVmax-FAPI, GTVFAPI, and TL-FAPI in patients with stage T4 tumors were significantly higher than those in patients with stage T2/T3 tumors (all P < 0.01). In the univariate Cox regression analysis, T stage, N stage, GTVFAPI, and TL-FAPI were associated with PFS, and T stage, GTVFAPI, and TL-FAPI were associated with OS. Upon multivariable analysis, GTVFAPI was an independent prognostic factor for both PFS (hazard ratio (HR), 5.76; 95% confidence interval (CI), 2.13-15.57, P = 0.001) and OS (HR, 4.96; 95% CI, 2.55-18.79, P = 0.001). CONCLUSION: This pilot study revealed that [68 Ga]Ga-FAPI PET/CT may have prognostic value for patients with ESCC treated with definitive chemoradiotherapy. It may aid in personalized patient management by steering treatment modifications before therapy. Prospective studies with larger samples and longer observation periods are needed.

Ambient Pressure X-ray Photoelectron Spectroscopy Study of Oxidation Phase Transitions on Cu(111) and Cu(110).

The surface structure effect on the oxidation of Cu has been investigated by performing ambient-pressure X-ray photoelectron spectroscopy (APXPS) on Cu(111) and Cu(110) surfaces under oxygen pressures ranging from 10-8 to 1 mbar and temperatures from 300 to 750 K. The APXPS results show a subsequential phase transition from chemisorbed O/Cu overlayer to Cu2 O and then to CuO on both surfaces. For a given temperature, the oxygen pressure needed to induce initial formation of Cu2 O on Cu(110) is about two orders of magnitude greater than that on Cu(111), which is in contrast with the facile formation of O/Cu overlayer on clean Cu(110). The depth profile measurements during the initial stage of Cu2 O formation indicate the distinct growth modes of Cu2 O on the two surface orientations. We attribute these prominent effects of surface structure to the disparities in the kinetic processes, such as the dissociation and surface/bulk diffusion over O/Cu overlayers. Our findings provide new insights into the kinetics-controlled process of Cu oxidation by oxygen.