Proteomic and Metabolomic Characterization of COVID-19 Patient Sera.

Early detection and effective treatment of severe COVID-19 patients remain major challenges. Here, we performed proteomic and metabolomic profiling of sera from 46 COVID-19 and 53 control individuals. We then trained a machine learning model using proteomic and metabolomic measurements from a training cohort of 18 non-severe and 13 severe patients. The model was validated using 10 independent patients, 7 of which were correctly classified. Targeted proteomics and metabolomics assays were employed to further validate this molecular classifier in a second test cohort of 19 COVID-19 patients, leading to 16 correct assignments. We identified molecular changes in the sera of COVID-19 patients compared to other groups implicating dysregulation of macrophage, platelet degranulation, complement system pathways, and massive metabolic suppression. This study revealed characteristic protein and metabolite changes in the sera of severe COVID-19 patients, which might be used in selection of potential blood biomarkers for severity evaluation.

Proteomics Investigation of Diverse Serological Patterns in COVID-19.

Serum antibodies IgM and IgG are elevated during Coronavirus Disease 2019 (COVID-19) to defend against viral attacks. Atypical results such as negative and abnormally high antibody expression were frequently observed whereas the underlying molecular mechanisms are elusive. In our cohort of 144 COVID-19 patients, 3.5% were both IgM and IgG negative, whereas 29.2% remained only IgM negative. The remaining patients exhibited positive IgM and IgG expression, with 9.3% of them exhibiting over 20-fold higher titers of IgM than the others at their plateau. IgG titers in all of them were significantly boosted after vaccination in the second year. To investigate the underlying molecular mechanisms, we classed the patients into four groups with diverse serological patterns and analyzed their 2-year clinical indicators. Additionally, we collected 111 serum samples for TMTpro-based longitudinal proteomic profiling and characterized 1494 proteins in total. We found that the continuously negative IgM and IgG expression during COVID-19 were associated with mild inflammatory reactions and high T cell responses. Low levels of serum IgD, inferior complement 1 activation of complement cascades, and insufficient cellular immune responses might collectively lead to compensatory serological responses, causing overexpression of IgM. Serum CD163 was positively correlated with antibody titers during seroconversion. This study suggests that patients with negative serology still developed cellular immunity for viral defense and that high titers of IgM might not be favorable to COVID-19 recovery.

Epidemiology, molecular characterization, and drug resistance of IncHI5 plasmids from Enterobacteriaceae.

The increasingly frequent occurence of IncHI5 plasmids has attracted worldwide attention. The aim of this study was to perform an in-depth bioinformatics analysis to determine the genetic characteristics and global distribution of all IncHI5 plasmids. The geographic distribution and epidemiology of all IncHI5 plasmids from GenBank were analyzed based on relevant literature reports and background information from the National Center for Biotechnology Information (NCBI). Detailed annotation of antibiotic resistance genes was performed. A total of 65 IncHI5 plasmid genomes were collected in GenBank. All IncHI5 plasmids were carried by Enterobacteriaceae, of which Klebsiella pneumoniae accounted for the largest proportion (50%, 33/65). The host bacterium of IncHI5 plasmids was mainly isolated from Homo Sapiens (81%, 53/65). All strains carrying IncHI5 plasmids were mainly distributed in China (83%, 54/65). Evolutionary analysis can divide IncHI5 plasmids into two groups, namely Groups I/II, of which Group II was more widely distributed worldwide. This study showed that Enterobacteriaceae, especially Klebsiella, was the main host for IncHI5 plasmid. Almost all IncHI5 plasmids carried multiple types of antibiotic resistance genes, related to Tn1696 or Tn6535. The IncHI5 plasmids should be of continuing interest as good repositories for antibiotic resistance genes.

Potential Use of Serum Proteomics for Monitoring COVID-19 Progression to Complement RT-PCR Detection.

RT-PCR is the primary method to diagnose COVID-19 and is also used to monitor the disease course. This approach, however, suffers from false negatives due to RNA instability and poses a high risk to medical practitioners. Here, we investigated the potential of using serum proteomics to predict viral nucleic acid positivity during COVID-19. We analyzed the proteome of 275 inactivated serum samples from 54 out of 144 COVID-19 patients and shortlisted 42 regulated proteins in the severe group and 12 in the non-severe group. Using these regulated proteins and several key clinical indexes, including days after symptoms onset, platelet counts, and magnesium, we developed two machine learning models to predict nucleic acid positivity, with an AUC of 0.94 in severe cases and 0.89 in non-severe cases, respectively. Our data suggest the potential of using a serum protein-based machine learning model to monitor COVID-19 progression, thus complementing swab RT-PCR tests. More efforts are required to promote this approach into clinical practice since mass spectrometry-based protein measurement is not currently widely accessible in clinic.

Integration of protein context improves protein-based COVID-19 patient stratification.

BACKGROUND: Classification of disease severity is crucial for the management of COVID-19. Several studies have shown that individual proteins can be used to classify the severity of COVID-19. Here, we aimed to investigate whether integrating four types of protein context data, namely, protein complexes, stoichiometric ratios, pathways and network degrees will improve the severity classification of COVID-19. METHODS: We performed machine learning based on three previously published datasets. The first was a SWATH (sequential window acquisition of all theoretical fragment ion spectra) MS (mass spectrometry) based proteomic dataset. The second was a TMTpro 16plex labeled shotgun proteomics dataset. The third was a SWATH dataset of an independent patient cohort. RESULTS: Besides twelve proteins, machine learning also prioritized two complexes, one stoichiometric ratio, five pathways, and five network degrees, resulting a 25-feature panel. As a result, a model based on the 25 features led to effective classification of severe cases with an AUC of 0.965, outperforming the models with proteins only. Complement component C9, transthyretin (TTR) and TTR-RBP (transthyretin-retinol binding protein) complex, the stoichiometric ratio of SAA2 (serum amyloid A proteins 2)/YLPM1 (YLP Motif Containing 1), and the network degree of SIRT7 (Sirtuin 7) and A2M (alpha-2-macroglobulin) were highlighted as potential markers by this classifier. This classifier was further validated with a TMT-based proteomic data set from the same cohort (test dataset 1) and an independent SWATH-based proteomic data set from Germany (test dataset 2), reaching an AUC of 0.900 and 0.908, respectively. Machine learning models integrating protein context information achieved higher AUCs than models with only one feature type. CONCLUSION: Our results show that the integration of protein context including protein complexes, stoichiometric ratios, pathways, network degrees, and proteins improves phenotype prediction.

Knockdown of TRIM27 alleviated sepsis-induced inflammation, apoptosis, and oxidative stress via suppressing ubiquitination of PPARγ and reducing NOX4 expression.

BACKGROUND: Sepsis is a global fatal disease and leads to severe lung injury due to dysfunction of inflammation response. TRIM27 is closely related to the diseased with dysfunction of inflammation response. The aim of this study was to clarify the role and mechanism of TRIM27 in sepsis-induced lung injury. METHODS: The lipopolysaccharide (LPS)-induced septic mouse model was successfully established. The lung injury was evaluated by lung wet/dry (W/D) ratio and hematoxylin-eosin (H&E) staining. The cell apoptosis was evaluated by TUNEL assay. The inflammatory cytokines were measured by quantitative real time-PCR (qRT-PCR) assay and commercial enzyme-linked immunosorbent assay (ELISA). The oxidative stress was assessed by the contents of superoxide dismutase (SOD) and malondialdehyde (MDA), and the expression of dihydroethidium (DHE). RESULTS: In this study, we demonstrated that TRIM27 was up-regulated in LPS-induced septic mice. In loss-of-function experiments, knockdown of TRIM27 alleviated sepsis-induced lung injury, inflammation, apoptosis, and oxidative stress. More importantly, knockdown of TRIM27 was observed to reduce p-p65/NOX4 expression via suppressing ubiquitination of PPARγ. In rescue experiments, overexpression of NOX4 abolished the effect of sh-TRIM27 on alleviating sepsis-induced inflammation, apoptosis, and oxidative stress. CONCLUSION: These findings highlighted that knockdown of TRIM27 alleviated sepsis-induced inflammation, oxidative stress and apoptosis via suppressing ubiquitination of PPARγ and reducing NOX4 expression, which supports the potential utility of TRIM27 as a therapeutic target in septic lung injury.

Germline and somatic mtDNA mutation spectrum of rheumatoid arthritis patients in the Taizhou area, China.

OBJECTIVE: Reactive oxygen species are believed to be involved in the onset of RA, and the association between nuclear-encoded mitochondrial respiratory chain-related variants and RA has recently been revealed. However, little is known about the landscape of mitochondrial DNA (mtDNA) variants in RA. METHODS: Next-generation sequencing was conducted to profile mtDNA germline and somatic variants in 124 RA patients and 123 age- and sex-matched healthy controls in the Taizhou area, China. Fisher's exact test, SKAT and SKAT-O were used for gene-burden tests to investigate RA-related variants of mitochondrial genes. Predictive tools were applied to evaluate the pathogenicity of mtDNA variants, and mtDNA haplogroups were assigned according to mtDNA mutations recorded in PhyloTree database. The frequency distribution of mtDNA haplogroups between the groups was compared using χ2 analysis. RESULTS: We identified 467 RA-unique and 341 healthy control-unique mtDNA variants, with 443 common variants. Only MT-ATP6 with a significant burden of variants was identified by Fisher's exact test, SKAT and SKAT-O, even after Bonferroni adjustment, and the enrichment variants in MT-ATP6 was mainly driven by m.8830C>A, m.8833G>C and m.8843T>A variants. Besides, four frequently low-heteroplasmic variants including the three variants above and m.14135T>G of MT-ND5 were detected in RA only; except for m.8830C>A, they are considered potential pathogenicity based on functional predictions. χ2 analysis before Bonferroni adjustment revealed haplogroup F1/F1a to be negatively associated with RA (P < 0.05). CONCLUSION: These results profiled the landscape of germline and somatic mtDNA variants in RA and supported the effects of mitochondrial genes on RA.

EZH2 promotes the expression of LPA1 by mediating microRNA-139 promoter methylation to accelerate the development of ovarian cancer.

BACKGROUND: It has been known that ovarian cancer (OC) is a leading cause for women mortality globally. We aimed to analyze the underlying mechanism supporting that enhancer of zeste homolog 2 (EZH2) affected the development of OC via the involvement of microRNA-139 (miR-139)/transforming growth factor beta (TGF-ß)/lysophosphatidic acid-1 (LPA1) axis. METHODS: High expression patterns of EZH2 and miR-139 and low LPA1 expression pattern in OC were evaluated using RT-qPCR and immunoblotting, while their correlation was assessed by the Spearman's rank and Pearson's correlation coefficient. Subsequently, dual-luciferase reporter gene assay was applied to validate the binding relationship between miR-139 and LPA1, while H3K27me enrichment was assessed by ChIP assay. After that, the effects of altered expression of EZH2, miR-194, or LPA1 on the cell biological functions and the expression pattern of TGF-related factors were evaluated. RESULTS: We found that EZH2 repressed the miR-139 expression pattern by recruiting H3K27me3 to promote miR-139 promoter methylation, while silencing of EZH2 suppressed in vitro cancer progression by increasing miR-139. LPA1 was a target of miR-139, and could activate the TGF-ß signaling pathway, which hastened the OC progression. miR-139-targeted inhibition of LPA1 and LPA1-activated TGF-ß signaling pathway were evidenced to be critical mechanisms underlying the effects of EZH2 on OC cells. Lastly, silencing of EZH2 inhibited the xenograft growth in vivo. CONCLUSIONS: EZH2 could down-regulate miR-139 expression pattern by recruiting H3K27me3 to promote the miR-139 promoter methylation and activate the TGF-ß pathway by up-regulating LPA1, which contributed to the progression of OC. The current study may possess potentials for OC treatment.

The hemocyte counts as a potential biomarker for predicting disease progression in COVID-19: a retrospective study.

Objectives In December 2019, there was an outbreak of coronavirus disease 2019 (COVID-19) in Wuhan, China, and since then, the disease has been increasingly spread throughout the world. Unfortunately, the information about early prediction factors for disease progression is relatively limited. Therefore, there is an urgent need to investigate the risk factors of developing severe disease. The objective of the study was to reveal the risk factors of developing severe disease by comparing the differences in the hemocyte count and dynamic profiles in patients with severe and non-severe COVID-19. Methods In this retrospectively analyzed cohort, 141 confirmed COVID-19 patients were enrolled in Taizhou Public Health Medical Center, Taizhou Hospital, Zhejiang Province, China, from January 17, 2020 to February 26, 2020. Clinical characteristics and hemocyte counts of severe and non-severe COVID patients were collected. The differences in the hemocyte counts and dynamic profiles in patients with severe and non-severe COVID-19 were compared. Multivariate Cox regression analysis was performed to identify potential biomarkers for predicting disease progression. A concordance index (C-index), calibration curve, decision curve and the clinical impact curve were calculated to assess the predictive accuracy. Results The data showed that the white blood cell count, neutrophil count and platelet count were normal on the day of hospital admission in most COVID-19 patients (87.9%, 85.1% and 88.7%, respectively). A total of 82.8% of severe patients had lymphopenia after the onset of symptoms, and as the disease progressed, there was marked lymphopenia. Multivariate Cox analysis showed that the neutrophil count (hazard ratio [HR] = 4.441, 95% CI = 1.954-10.090, p = 0.000), lymphocyte count (HR = 0.255, 95% CI = 0.097-0.669, p = 0.006) and platelet count (HR = 0.244, 95% CI = 0.111-0.537, p = 0.000) were independent risk factors for disease progression. The C-index (0.821 [95% CI, 0.746-0.896]), calibration curve, decision curve and the clinical impact curve showed that the nomogram can be used to predict the disease progression in COVID-19 patients accurately. In addition, the data involving the neutrophil count, lymphocyte count and platelet count (NLP score) have something to do with improving risk stratification and management of COVID-19 patients. Conclusions We designed a clinically predictive tool which is easy to use for assessing the progression risk of COVID-19, and the NLP score could be used to facilitate patient stratification management.

LncRNA MIAT Promotes Inflammation and Oxidative Stress in Sepsis-Induced Cardiac Injury by Targeting miR-330-5p/TRAF6/NF-κB Axis.

Sepsis is a whole-body inflammation and main cause of death in intensive care units worldwide. We aimed to investigate the roles of lncRNA MIAT and miR-330-5p in modulating inflammatory responses and oxidative stress in lipopolysachariden (LPS)-induced septic cardiomyopathy. Serum and heart tissue were collected from in vivo septic mice model, ELISA and qRT-PCR were used to measure the expression of pro-inflammation cytokines, MIAT and miR-330-5p, respectively. The knockdown of MIAT and overexpression of miR-330-5p were conducted to assess their effects on regulating inflammation response and intracellular oxidative stress in LPS-stimulated HL-1 cells. The reactive oxygen (ROS) level, mitochondrial membrane potential (MMP), GSH/GSSH ratio, and lipid peroxidation assessment (MDA) were used to evaluate the intracellular oxidative stress. Dual-luciferase reporter assay was performed to identify the association between MIAT and miR-330-5p, TRAF6 and miR-330-5p, respectively. In septic mice, the expression of MIAT and pro-inflammation cytokines was elevated while the expression of miR-330-5p decreased. Knockdown of MIAT or overexpression of miR-330-5p restrained inflammation and oxidative stress induced by LPS in vitro; MIAT directly targeted miR-330-5p to regulate NF-κB signaling, and miR-330-5p targeted against TRAF6 to suppress the activation of NF-κB signaling. We determined that lncRNA MIAT directly binds to miR-330-5p to activate TRAF6/NF-κB signaling axis and further promotes inflammation response as well as oxidative stress in LPS-induced septic cardiomyopathy. This finding suggests the potential therapeutic role of lncRNA MIAT and miR-330-5p in LPS-induced myocardial injury.

Sociodemographic and clinical factors influencing serum potassium concentration: A retrospective cohort study.

Background: Self-care is crucial for maintaining the health and quality of life of individuals undergoing physical examinations, especially those with abnormal test results because they are at a higher risk of experiencing worse outcomes. However, there is currently a lack of comprehensive literature on the impact of sociodemographic and clinical factors on self-care practices related to serum potassium concentration among individuals undergoing physical examinations. Therefore, this study aimed to explore the sociodemographic and clinical factors influencing serum potassium concentration. Methods: Data from 43,151 individuals who underwent physical examinations were retrospectively collected in January, April, July, and October of 2019-2021. The serum potassium concentrations of these individuals were compared based on sex, age, and residential area. Additionally, the whole cohort and a subset of 6698 individuals with available occupational information were included to analyze the sociodemographic factors associated with serum potassium concentration using logistic regression analysis. Furthermore, a propensity score matching approach was employed to match 642 individuals with abnormal serum potassium concentrations to 642 with normal serum potassium concentrations. Pearson's correlation analysis was subsequently used to investigate the clinical factors contributing to abnormalities in serum potassium concentration. Results: High temperatures; older age; male sex; living in the southern part of the city; and chemical, communication system, and transportation occupations were associated with a higher likelihood of experiencing abnormal serum potassium concentrations. Individuals with abnormal serum potassium concentrations had a higher prevalence of underlying diseases. Compared with the hypokalemia group, the hyperkalemia group exhibited a higher incidence of diabetes and cardiovascular disease. In the hyperkalemia group, serum potassium concentration positively correlated with serum creatinine concentration and negatively correlated with the estimated glomerular filtration rate (eGFR). In contrast, in the hypokalemia group, serum potassium concentration negatively correlated with creatinine concentrations, blood glucose concentration, and systolic and diastolic blood pressure, and positively correlated with eGFR. Conclusions: Sociodemographic and clinical factors can affect blood potassium concentration. During daily self-care, it is essential for individuals with abnormal potassium concentrations to avoid exposure to relevant sociodemographic risk factors and seek medical attention as soon as possible to screen for diseases, such as hypertension, cardiovascular disease, and diabetes.

Higher Virulence Renders K2 Klebsiella pneumoniae a Stable Share Among Those from Pyogenic Liver Abscess.

Objective: To explore why serotype K2 accounts for a stable share in Klebsiella pneumoniae from pyogenic liver abscess (PLA). Methods: Totally 15 K2 K. pneumoniae strains from PLA, 21 K2 from non-PLA, and 31 K1 from PLA were collected from China. Sequence typing, molecular serotyping, regular PCR, and Galleria mellonella lethality were performed. A total of 12 virulence genes were detected: peg-344, allS, p-rmpA, p-rmpA2, c-rmpA, fimH, mrkD, iucA, iroN, irp2, entB, and wzi. The differences between K2 K. pneumoniae strains from PLA and non-PLA were investigated along with K1 ones. Results: Significant differences were found between K2 strains from PLA and non-PLA for the rates of virulence genes peg-344 and iucA. The latter group also showed more diverse sequence types than the former. Significant differences were only found for virulence genes allS and irp2 between K1 and K2 strains from PLA. Based on the equal virulence factors backgrounds other than serotypes, K2 strain is more virulent than K1 as G. mellonella lethality confirmed. Gene p-rmpA only brings equal virulence to p-rmpA plus p-rmpA2 in K2 strain. Conclusion: Based on the same virulence factors backgrounds except serotypes, K2 K. pneumoniae is more virulent than K1 from PLA, which provides a survival advantage to maintain a stable share.

Efficacy of the neutralizing antibodies after the booster dose on SARS-CoV-2 Omicron variant and a two-year longitudinal antibody study on Wild Type convalescents.

OBJECTIVES: Waning vaccine-induced immunity and emergence of new severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) variants which may lead to immune escape, pose a major threat to the COVID-19 pandemic. Currently, enhanced efficacy of the neutralization antibodies (NAb) produced after the booster dose of vaccinations against the Omicron variant is the main focus of vaccine strategy research. In this study we have analyzed the potency of the NAbs and IgGs produced after the third vaccine dose in patients infected with Omicron variant and wild-type (WT) SARS-CoV-2. METHODS: We enrolled 75 patients with Omicron variant breakthrough infections, and 87 patients with WT infections. We recorded the clinical characteristics and vaccination information of all patients and measured the NAb and anti-S1 (spike protein) + N (nucleocapsid protein) IgG-binding antibodies against SARS-CoV-2 in serum samples of Omicron variant-infected patients at admission, and patients with WT COVID-19 infection from the time of admission and discharge, and one-year to two-years follow-ups. RESULTS: Our results demonstrated higher NAb levels, fewer clinical symptoms, and faster viral shedding in Omicron variant infected patients vaccinated with the booster dose. Hybrid immunity (natural infection plus vaccination) induces higher NAb levels than vaccine-only immunity. NAb and IgG levels decreased significantly at one-year follow-up in WT convalescents with natural infection. The NAb and IgG levels in booster-vaccinated COVID-19 patients were higher than those in two-dose-vaccinated patients. CONCLUSION: Our results suggest that booster vaccinations are required to improve the level of protective NAbs. Moreover, our data provide important evidence for vaccination strategies based on existing vaccines.

The Expression and Clinical Significance of Sphingosine Kinase 1 and Vascular Endothelial Growth Factor in Endometrial Carcinoma.

The aim of the study is to investigate the expression of sphingosine kinase 1 (SPHK1) and vascular endothelial growth factor (VEGF) in patients with endometrial carcinoma and its clinical significance. The tissues of 86 cases of patients with endometrial carcinoma and 54 cases of patients with endometrial atypical hyperplasia were collected. The expression of SPHK1 and VEGF in the tissue was detected by immunohistochemistry. The expression of SPHK1 in patients with endometrial carcinoma was compared with the clinicopathological data. Results. 69 cases (82.1%) of endometrial carcinoma were positive for SPHK1, which was higher than 2 cases (3.7%) of endometrial atypical hyperplasia (P < 0.05). The VEGF expression in 54 patients (62.8%) with endometrial carcinoma was higher than that in 12 patients with endometrial atypical hyperplasia (22.2%) (P < 0.05). There was a positive correlation between SPHK1 and VEGF expressions in endometrial carcinoma (c = 0.595). The expression of SPHK1 in endometrial cancer patients was different in different pathological types, FIGO stages, lymph node metastasis, ER, and PR positive or not, and the difference between the two groups was significant (P < 0.05). There was no difference in age, degree of differentiation, and depth of myometrial infiltration (P < 0.05). The expression of SPHK1 in patients with endometrial carcinoma is increased, which is helpful for early detection of patients with endometrial carcinoma, and may play a synergistic role with VEGF in the pathogenesis and development of endometrial carcinoma.

Differences Between Omicron Infections and Fever Outpatients: Comparison of Clinical Manifestations and Initial Routine Hematology Indicators.

Purpose: We evaluated the differences between patients with SARS-CoV-2 Omicron variant infections and Fever outpatients, so that prevention and control measures can be taken in time. Patients and Methods: This study retrospectively analyzed 65 patients with SARS-CoV-2 Omicron variant. Sixty-nine age- and sex-matched Fever outpatients were enrolled during the same period of time. We also reanalyzed data from 81 SARS-CoV-2 Wild-Type-infected patients. We compared the clinical characteristics and initial indexes of routine tests among the 3 groups. Results: A total of 93.8% of the patients with Omicron infections had clinical symptoms, and the major symptoms were cough, fever and pharyngalgia. Pharyngalgia was a specific manifestation in Omicron group compared to Wild-Type group. The white blood cell of the Omicron group was lower than that of the Fever group [5.0 (3.6-6.1) vs 10.1 (7.6-12.9) ×109/L, P < 0.001]. The neutrophil count in Omicron group was lower than that in Fever and Wild-Type group [2.6 (1.8-3.9) vs 8.1 (5.9-10.9), P < 0.001; 2.6 (1.8-3.9) vs 3.4 (2.5-4.7) ×109/L, P < 0.001]. The white blood cell and neutrophil counts were lower in Omicron group than in the Fever group. The top 5 major symptoms were fever, cough, pharyngalgia, headache and expectoration. Conclusion: There are differences between the patients with Omicron infections and Fever outpatients, both in clinical manifestations and initial routine hematology indicators. We hope to provide some clues for early identification combined with a history of living in the epidemic area.

NFIL3 and its immunoregulatory role in rheumatoid arthritis patients.

Nuclear-factor, interleukin 3 regulated (NFIL3) is an immune regulator that plays an essential role in autoimmune diseases. However, the relationship between rheumatoid arthritis (RA) and NFIL3 remains largely unknown. In this study, we examined NFIL3 expression in RA patients and its potential molecular mechanisms in RA. Increased NFIL3 expression levels were identified in peripheral blood mononuclear cells (PBMCs) from 62 initially diagnosed RA patients and 75 healthy controls (HCs) by quantitative real-time PCR (qRT-PCR). No correlation between NFIL3 and disease activity was observed. In addition, NFIL3 expression was significantly upregulated in RA synovial tissues analyzed in the Gene Expression Omnibus (GEO) dataset (GSE89408). Then, we classified synovial tissues into NFIL3-high (≥75%) and NFIL3-low (≤25%) groups according to NFIL3 expression levels. Four hundred five differentially expressed genes (DEGs) between the NFIL3-high and NFIL3-low groups were screened out using the "limma" R package. Enrichment analysis showed that most of the enriched genes were primarily involved in the TNF signaling pathway via NFκB, IL-17 signaling pathway, and rheumatoid arthritis pathways. Then, 10 genes (IL6, IL1ß, CXCL8, CCL2, PTGS2, MMP3, MMP1, FOS, SPP1, and ADIPOQ) were identified as hub genes, and most of them play a key role in RA. Positive correlations between the hub genes and NFIL3 were revealed by qRT-PCR in RA PBMCs. An NFIL3-related protein-protein interaction (PPI) network was constructed using the STRING database, and four clusters (mainly participating in the inflammatory response, lipid metabolism process, extracellular matrix organization, and circadian rhythm) were constructed with MCODE in Cytoscape. Furthermore, 29 DEGs overlapped with RA-related genes from the RADB database and were mainly enriched in IL-17 signaling pathways. Thus, our study revealed the elevated expression of NFIL3 in both RA peripheral blood and synovial tissues, and the high expression of NFIL3 correlated with the abnormal inflammatory cytokines and inflammatory responses, which potentially contributed to RA progression.

Proteomic and metabolomic profiling of urine uncovers immune responses in patients with COVID-19.

The utility of the urinary proteome in infectious diseases remains unclear. Here, we analyzed the proteome and metabolome of urine and serum samples from patients with COVID-19 and healthy controls. Our data show that urinary proteins effectively classify COVID-19 by severity. We detect 197 cytokines and their receptors in urine, but only 124 in serum using TMT-based proteomics. The decrease in urinary ESCRT complex proteins correlates with active SARS-CoV-2 replication. The downregulation of urinary CXCL14 in severe COVID-19 cases positively correlates with blood lymphocyte counts. Integrative multiomics analysis suggests that innate immune activation and inflammation triggered renal injuries in patients with COVID-19. COVID-19-associated modulation of the urinary proteome offers unique insights into the pathogenesis of this disease. This study demonstrates the added value of including the urinary proteome in a suite of multiomics analytes in evaluating the immune pathobiology and clinical course of COVID-19 and, potentially, other infectious diseases.

Oncogenic microRNA-181d binding to OGT contributes to resistance of ovarian cancer cells to cisplatin.

Ovarian cancer (OC), a common gynecological cancer, is characterized by a high malignant potential. MicroRNAs (miRNAs or miRs) have been associated with the chemo- or radiotherapeutic resistance of human malignancies. Herein, the current study set out to explore the regulatory mechanism of miR-181d involved in the cisplatin (DDP) resistance of OC cells. Firstly, in-situ hybridization method was performed to identify miR-181d expression in ovarian tissues of DDP-resistant or DDP-sensitive patients. In addition, miR-181d expression in A2780 cells and A2780/DDP cell lines was determined by RT-qPCR. Gain- and loss-of-function experiments were then performed to characterize the effect of miR-181d on OC cell behaviors. We probed the miR-181d affinity to OGT, as well as the downstream glycosylation of KEAP1 and ubiquitination of NRF2. Further, in vivo experiments were performed to define the role of miR-181d in tumor resistance to DDP. miR-181d was highly expressed in the ovarian tissues of DDP-resistant patients and the A2780/DDP cell line. Ectopic expression of miR-181d augmented DDP resistance in OC cells. In addition, miR-181d was found to target the 3'UTR of OGT mRNA, and negatively regulate the OGT expression. Mechanistic results indicated that OGT repressed NRF2 expression through glycosylation of KEAP1, thereby inhibiting the DDP resistance of OC cells. Furthermore, miR-181d negatively orchestrated the OGT/KEAP1/NRF2 axis to enhance the OC resistance to DDP in vivo. Overall, these findings suggest that miR-181d-mediated OGT inhibition restricts the glycosylation of KEAP1, and then reduces the ubiquitination and degradation of NRF2, leading to DDP resistance of OC. This study provides new insights for prevention and control of OC.

Paclitaxel alleviates the sepsis-induced acute kidney injury via lnc-MALAT1/miR-370-3p/HMGB1 axis.

AIMS: To investigate the effects of paclitaxel on lipopolysaccharide (LPS)-induced acute kidney injury (AKI) and its related mechanisms. MAIN METHODS: The sepsis-associated AKI was induced by LPS using HK-2 cells. Then the mRNA and protein expression levels of relevant genes in the serum of sepsis patients and HK-2 cells with LPS-induced AKI were detected by qRT-PCR and western blot analyses before and after paclitaxel treatment, respectively. Subsequently, the cell counting kit-8 (CCK-8) and flow cytometry assays were performed to estimate the effects of paclitaxel, lnc-MALAT1, miR-370-3p and HMGB1 on the proliferation and apoptosis of HK-2 cells injured by LPS. KEY FINDINGS: Lnc-MALAT1 was increased both in the serum of sepsis patients and cells injured by LPS, which could inhibit the cell proliferation, promote the cell apoptosis and increase the expression of TNF-α, IL-6 and IL-1ß caused by paclitaxel. Moreover, lnc-MALAT1 was sponged with miR-370-3p which had the inverse effects with lnc-MALAT1 in LPS induced HK-2 cells. What's more, miR-370-3p targeted HMGB1 which was induced in serum and cells of sepsis. Knockdown of miR-370-3p inhibited the expression of HMGB1 and suppressed the proliferation but promoted the apoptosis of HK-2 cells injured by LPS as well as the expression of TNF-α, IL-6 and IL-1ß. Besides, paclitaxel restrained the expression of HMGB1 via regulating lnc-MALAT1/miR-370-3p axis. SIGNIFICANCE: Paclitaxel could protect against LPS-induced AKI via the regulation of lnc-MALAT1/miR-370-3p/HMGB1 axis and the expression of TNF-α, IL-6 and IL-1ß, revealing that paclitaxel might act as a therapy drug in reducing sepsis-associated AKI.