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.

The expression of RBPJ and its potential role in rheumatoid arthritis.

BACKGROUND: Recombination signal-binding protein for immunoglobulin kappa J region (RBPJ) is a transcriptional regulator that plays an important role in maintaining immune homeostasis. This study aimed to estimate the expression of RBPJ in rheumatoid arthritis (RA) patients and investigate its relationship with RA. METHODS: A total of 83 newly diagnosed RA patients and 70 healthy controls were included. mRNA was extracted from peripheral blood mononuclear cells (PBMCs), and the expression of RBPJ was detected using quantitative real-time PCR (qRT‒PCR). An RA dataset (GSE89408) was obtained from the Gene Expression Omnibus (GEO) database, and RA synovial tissues were divided into two groups. The differentially expressed genes (DEGs) were selected with the "DESeq2" R package. RESULTS: RBPJ expression was lower in RA patients than in health controls and was negatively correlated with the DAS28 score, C-reactive protein (CRP) level and erythrocyte sedimentation rate (ESR). RA synovial tissues from GSE89408 were classified into RBPJ-low (≤ 25%) and RBPJ-high (≥ 75%) groups according to RBPJ expression, and 562 DEGs were identified. Gene Ontology (GO) enrichment analyses revealed that the DEGs significantly affected the regulation of T cell activation and lymphocyte/mononuclear cell differentiation. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed that the most enriched pathways of DEGs were the T cell receptor signaling pathway, Th1/2 and Th17 cell differentiation, the PI3K - Akt signaling pathway and cytokine‒cytokine receptor interaction. CytoHubba Plugin revealed that most of the top 10 genes were involved in osteoclast differentiation, the T cell receptor signaling pathway and cytokine‒cytokine receptor interaction. CONCLUSIONS: RBPJ expression was significantly lower in RA patients and negatively correlated with disease activity. GEO dataset analysis demonstrated that RBPJ may be involved in osteoclast differentiation, T cell activation and differentiation, and the T cell receptor signaling pathway. Our research may contribute to understanding the potential mechanisms by which RBPJ regulates T cell differentiation and cytokine‒cytokine receptor interaction in RA patients.

Periodate-Based Perovskite Energetic Materials: A Strategy for High-Energy Primary Explosives.

The requirements for high energy and green primary explosives are more and more stringent because of the rising demand in the application of micro initiation explosive devices. Four new energetic compounds with powerful initiation ability are reported and their performances are experimentally proven as designed, including non-perovskites ([H2 DABCO](H4 IO6 )2 ·2H2 O, named TDPI-0) and perovskitoid energetic materials (PEMs) ([H2 DABCO][M(IO4 )3 ]; DABCO=1,4-Diazabicyclo[2.2.2]octane, M=Na+ , K+ , and NH4 + for TDPI-1, -2, and -4, respectively). The tolerance factor is first introduced to guide the design of perovskitoid energetic materials (PEMs). In conjunction with [H2 DABCO](ClO4 )2 ·H2 O (DAP-0) and [H2 DABCO][M(ClO4 )3 ] (M=Na+ , K+ , and NH4 + for DAP-1, -2, and -4), the physiochemical properties of the two series are investigated between PEMs and non-perovskites (TDPI-0 and DAP-0). The experimental results show that PEMs have great advantages in improving the thermal stability, detonation performance, initiation capability, and regulating sensitivity. The influence of X-site replacement is illustrated by hard-soft-acid-base (HSAB) theory. Especially, TDPIs possess much stronger initiation capability than DAPs, which indicates that periodate salts are in favor of deflagration-to-detonation transition. Therefore, PEMs provide a simple and feasible method for designing advanced high energy materials with adjustable properties.

An electronic tongue based on conjugated polymers for the discrimination and quantitative detection of tetracyclines.

A fluorescent sensor array has been developed based on conjugated polymers (CPs) having six different skeletons for the detection of tetracyclines (TCs), which are known as environmental pollutants. CPs were synthesized from confined nanoreactors in a controlled manner. The fluorescent response occurs through the fluorescence resonance energy transfer (FRET) effect. By utilizing linear discriminant analysis (LDA), effective differentiation of TCs was accomplished with a very low detection concentration (66 nM). Moreover, the sensor array exhibited a highly sensitive ability to quantitatively distinguish different concentrations of TCs. Finally, the sensor array's potential for detecting TCs in aqueous solutions has been successfully demonstrated, widening its applications in practical environments. With simple preparation process, a low cost of detection and high sensitivity, the experimental results indicate that the CP-based sensor array is a promising platform for the sensitive and quantitative detection of TCs, and provides a good reference for future scientific research.

An Improved SAMP Algorithm for Sparse Channel Estimation in OFDM System.

Channel estimation of an orthogonal frequency division multiplexing (OFDM) system based on compressed sensing can effectively reduce the pilot overhead and improve the utilization rate of spectrum resources. The traditional SAMP algorithm with a fixed step size for sparse channel estimation has the disadvantages of a low estimation efficiency and limited estimation accuracy. An Improved SAMP (ImpSAMP) algorithm is proposed to estimate the channel state information of the OFDM system. In the proposed ImpSAMP algorithm, the received signal is firstly denoised based on the energy-detection method, which can reduce the interferences on channel estimation. Furthermore, the step size is adjusted dynamically according to the l2 norm of difference between two estimated sparse channel coefficients of adjacent phases to estimate the sparse channel coefficients quickly and accurately. In addition, the double threshold judgment is adopted to enhance the estimation efficiency. The simulation results show that the ImpSAMP algorithm outperforms the traditional SAMP algorithm in estimation efficiency and accuracy.

Lifting Wavelet-Assisted EM Joint Estimation and Detection in Cooperative Spectrum Sensing.

Spectrum sensing in Cognitive radio (CR) is a way to improve spectrum utilization by detecting spectral holes to achieve a dynamic allocation of spectrum resources. As it is often difficult to obtain accurate wireless environment information in real-world scenarios, the detection performance is limited. Signal-to-noise ratio (SNR), noise variance, and channel prior occupancy rate are critical parameters in wireless spectrum sensing. However, obtaining these parameter values in advance is challenging in practical scenarios. A lifting wavelet-assisted Expectation-Maximization (EM) joint estimation and detection method is proposed to estimate multiple parameters and achieve full-blind detection, which uses lifting wavelet in noise variance estimation to improve detection probability and convergence speed. Moreover, a stream learning strategy is used in estimating SNR and channel prior occupancy rate to fit the scenario where the SU has mobility. The simulation results demonstrate that the proposed method can achieve comparable detection performance to the semi-blind EM method.

Preference-Matched Multitask Assignment for Group Socialization under Mobile Crowdsensing.

Mobile crowdsensing (MCS) has been an emerging sensing paradigm in recent years, which uses a sensing platform for real-time processing to support various services for the Internet of Things (IoT) and promote the development of IoT. As an important component of MCS, how to design task assignment algorithms to cope with the coexistence of multiple concurrent heterogeneous tasks in group-oriented social relationships while satisfying the impact of users' preferences on heterogeneous multitask assignment and solving the preference matching problem under heterogeneous tasks, is one of the most pressing issues. In this paper, a new algorithm, group-oriented adjustable bidding task assignment (GO-ABTA), is considered to solve the group-oriented bilateral preference-matching problem. First, the initial leaders and their collaborative groups in the social network are selected by group-oriented collaboration, and then the preference assignment of task requesters and users is modeled as a stable preference-matching problem. Then, a tunable bidding task assignment process is completed based on preference matching under budget constraints. Finally, the individual reasonableness, stability, and convergence of the proposed algorithm are demonstrated. The effectiveness of the proposed algorithm and its superiority to other algorithms are verified by simulation results.

Resource Allocation and Data Offloading Strategy for Edge-Computing-Assisted Intelligent Telemedicine System.

Intelligent telemedicine technology has been widely applied due to the quick development of the Internet of Things (IoT). The edge-computing scheme can be regarded as a feasible solution to reduce energy consumption and enhance the computing capabilities for the Wireless Body Area Network (WBAN). For an edge-computing-assisted intelligent telemedicine system, a two-layer network architecture composed of WBAN and Edge-Computing Network (ECN) was considered in this paper. Moreover, the age of information (AoI) was adopted to describe the time cost for the TDMA transmission mechanism in WBAN. According to the theoretical analysis, the strategy for resource allocation and data offloading in edge-computing-assisted intelligent telemedicine systems can be expressed as a system utility function optimizing problem. To maximize the system utility, an incentive mechanism based on contract theory (CT) was considered to motivate edge servers (ESs) to participate in system cooperation. To minimize the system cost, a cooperative game was developed to address the slot allocation in WBAN, while a bilateral matching game was utilized to optimize the data offloading problem in ECN. Simulation results have verified the effectiveness of the strategy proposed in terms of the system utility.

Joint User Clustering and Graph Coloring Based Pilot Assignment for Cell-Free Massive MIMO Systems.

Pilot contamination due to pilot reuse seriously mitigates the performance of the cell-free massive multiple-input multiple-output (MIMO) systems. In this paper, we propose a joint pilot assignment scheme that employs user clustering and graph coloring (UC-GC) to reduce pilot contamination. The proposed method consists of two steps: firstly, we utilize AP selection to classify all users; secondly, we assign pilots to users with more severe pilot contamination using the graph coloring algorithm and then assign pilots to the remaining users. The numerical simulation results show that the proposed scheme outperforms existing pilot assignment schemes and significantly improves throughout with low complexity.

Effect of phenyllactic acid on silage fermentation and bacterial community of reed canary grass on the Qinghai Tibetan Plateau.

BACKGROUND: This study aimed to investigate the effect of phenyllactic acid as an additive on silage fermentation and bacterial community of reed canary grass (RCG, Phalaris arundinacea L.) on the Qinghai Tibetan Plateau. At the heading stage, RCG was harvested, chopped and ensiled in small bag silos. The silage was treated without (control, 1.0 g/mL sterile water, on a fresh matter basis (FM)) or with phenyllactic acid (PLA, 3 mg/mL, FM), antimicrobial additive (PSB, a mixture of potassium sorbate and sodium benzoate, 2%, FM), lactic acid bacteria inoculant (LABi, L. plantarum + L. curvatus, 1 × 106 cfu/g, FM) and PLA + LABi, and then stored in a dark room at the ambient temperature (5 ~ 15 °C) for 60 days. RESULTS: Compared with control, PLA decreased lactic acid, acetic acid and ammonia-N contents, and subsequently increased CP content of RCG silage. PLA enhanced the growth of lactic acid bacteria and reduced the count of yeasts (P < 0.05) in RCG silage, with reduced bacterial richness index (Chao1), observed operational taxonomic units and diversity index (Simpson). In relative to control, moreover, PLA and PLA + LABi increased the relative abundance of Lactococcus in RCG silage by 27.73 and 16.93%, respectively. CONCLUSIONS: Therefore, phenyllactic acid at ensiling improved nutritional quality of RCG silage by advancing the disappearance of yeasts and the dominance of Lactococcus.

Different antigen ratio in bivalent vaccine can affect immunological activation and protection against Aeromonas salmonicida and Vibrio anguillarum in Atlantic salmon.

To effectively prevent the outbreak of furunculosis and vibriosis in Atlantic salmon culture in northern China, the immunological properties and efficacies of bivalent inactivated vaccines composed of two local pathogenic strains, Aeromonas salmonicida C4 and Vibrio anguillarum M3, was analyzed in salmon. The effect of formalin-inactivated A. salmonicida C4, V. anguillarum M3, and their combined vaccines with different antigen ratio of 1:1, 1:2 and 2:1 on relative percentage of survival (RPS), specific antibody production and expression of immune-related genes of fish were investigated. It was found that both C4 and M3 antigen had adjuvant effects on each other's vaccines. Furthermore, the proportion of antigens in the combined vaccines had significantly different effects on immune response and protection against A. salmonicida or V. anguillarum infection. Compared with other vaccinated groups, the C4:M3 = 1:2 vaccine group had the highest immunological activation ability and best immune protection against A. salmonicida and V. anguillarum. Our studies suggest that the development of new multivalent vaccines should carefully design the ratio of different antigens in according to their immunological properties to achieve efficient protection and avoid inhibitory effects of antigens on specific pathogen.

Serum short-chain fatty acids and its correlation with motor and non-motor symptoms in Parkinson's disease patients.

BACKGROUND: Parkinson's disease (PD) is associated with enteric nervous system dysfunction and gut microbiota dysbiosis. Short-chain fatty acids (SCFAs), derived from gut microbiota, are supposed to anticipate PD pathogenesis via the pathway of spinal cord and vagal nerve or the circulatory system. However, the serum concentration of SCFAs in PD patients is poorly known. This study aims to investigate the exact level of SCFAs in PD patients and its correlation with Parkinson's symptoms. METHODS: 50 PD patients and 50 healthy controls were recruited, and their demographic and clinical characteristics were collected. The serum concentration of SCFAs was detected using a gas chromatography-mass spectrometer. SCFAs were compared between PD and control groups. The correlation between serum SCFAs and Parkinson's symptoms and the potential effects of medications on the serum SCFAs was analyzed. RESULTS: Serum propionic acid, butyric acid and caproic acid were lower, while heptanoic acid was higher in PD patients than in control subjects. However, only the serum level of propionic acid was correlated with Unified Parkinson's Disease Rating Scale (UPDRs) part III score (R = -0.365, P = 0.009), Mini-mental State Examination (MMSE) score (R = -0.416, P = 0.003), and Hamilton Depression Scale (HAMD) score (R = 0.306, P = 0.03). There was no correlation between other serum SCFAs and motor complications. The use of trihexyphenidyl or tizanidine increased the serum concentration of propionic acid. CONCLUSIONS: Serum SCFAs are altered in PD patients, and the decrease of serum propionic acid level is correlated with motor symptoms, cognitive ability and non-depressed state. Thus, the gut microbial-derived SCFAs potentially affect Parkinson's symptoms through the blood circulation. Propionic acid supplementation might ameliorate motor and non-motor symptoms of PD patients, although clinical trials are needed to test this hypothesis.

Long non-coding RNA small nucleolar RNA host genes: functions and mechanisms in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors of the digestive system, with a high degree of malignancy. Although treatment methods are constantly improving, the mortality of patients is still very high, and the small nucleolar RNA host gene (SNHG) plays an important role in the occurrence and development of cancer. It can activate downstream signaling molecules by acting on microRNA and microRNA target genes, promote the proliferation, invasion, and migration of HCC cells, and provide a new molecular target for the treatment of HCC. At present, the molecular mechanisms of HCC remain unclear. In this study, the mechanism and signaling pathway of SNHG in HCC are reviewed, which provides a theoretical basis for the clinical treatment of HCC.

Maximizing Average Throughput of Cooperative Cognitive Radio Networks Based on Energy Harvesting.

Energy harvesting (EH) and cooperative communication techniques have been widely used in cognitive radio networks. However, most studies on throughput in energy-harvesting cooperative cognitive radio networks (EH-CCRNs) are end-to-end, which ignores the overall working state of the network. For the above problems, under the premise of prioritizing the communication quality of short-range users, this paper focuses on the optimization of the EH-CCRN average throughput, with energy and transmission power as constraints. The formulated problem was an unsolved non-deterministic polynomial-time hardness (NP-hard) problem. To make it tractable to solve, a multi-user time-power resource allocation algorithm (M-TPRA) is proposed, which is based on sub-gradient descent and unary linear optimization methods. Simulation results show that the M-TPRA algorithm can improve the average throughput of the network. In addition, the energy consumed by executing the M-TPRA algorithm is analyzed.

Proteomic and metabolomic investigation of serum lactate dehydrogenase elevation in COVID-19 patients.

Serum lactate dehydrogenase (LDH) has been established as a prognostic indicator given its differential expression in COVID-19 patients. However, the molecular mechanisms underneath remain poorly understood. In this study, 144 COVID-19 patients were enrolled to monitor the clinical and laboratory parameters over 3 weeks. Serum LDH was shown elevated in the COVID-19 patients on admission and declined throughout disease course, and its ability to classify patient severity outperformed other biochemical indicators. A threshold of 247 U/L serum LDH on admission was determined for severity prognosis. Next, we classified a subset of 14 patients into high- and low-risk groups based on serum LDH expression and compared their quantitative serum proteomic and metabolomic differences. The results showed that COVID-19 patients with high serum LDH exhibited differentially expressed blood coagulation and immune responses including acute inflammatory responses, platelet degranulation, complement cascade, as well as multiple different metabolic responses including lipid metabolism, protein ubiquitination and pyruvate fermentation. Specifically, activation of hypoxia responses was highlighted in patients with high LDH expressions. Taken together, our data showed that serum LDH levels are associated with COVID-19 severity, and that elevated serum LDH might be consequences of hypoxia and tissue injuries induced by inflammation.

Pareuzebyella sediminis gen. nov., sp. nov., a novel marine bacterium in the family Flavobacteriaceae, isolated from a tidal flat sediment.

Two marine bacterial strains, designated S2-4-21T and MT2-5-19, were isolated from two tidal flat sediments of cordgrass Spartina alterniflora and adjacent oyster culture field in Quanzhou bay, China, respectively. Both strains were Gram-staining-negative, rod-shaped, non-flagellated, non-motile, aerobic, had NaCl requirements, and contained carotenoid and flexirubin pigments. The 16S rRNA gene sequence similarity (99.8%), average nucleotide identity value (99.4%) and average amino acid identity (99.3%) between strain S2-4-21T and strain MT2-5-19 strongly supported that they belonged to a single species. Phylogenetic analysis based on 16S rRNA gene sequences indicated that strain S2-4-21T and strain MT2-5-19 formed a monophyletic branch affiliated to the family Flavobacteriaceae, sharing similarities of 94.6% with Euzebyella marina CY01T and E. saccharophila 7SM30T, and of 94.1 and 92.8% with E. algicola MEBiC 12267T and Pseudozobellia thermophile DSM 19858T, respectively. Phylogenomic analysis based on the whole genome sequences supported that the two strains formed a distinct monophyletic clade within Flavobacteriaceae members, which was phylogenetically different from the clades of Euzebyella and Pseudozobellia. The major respiratory quinone was menaquinone MK-6. The major fatty acids (>10%) consisted of C15 : 0 iso, C16 : 0, summed feature 9 (C17 : 1 iso ω9c/C16 : 0 10-methyl) and C17 : 0 iso 3-OH. The polar lipid profiles of strain S2-4-21T and strain MT2-5-19 are identical, including phosphatidylethanolamine, four unidentified aminolipids, and four unidentified lipids. The genomic size was 4.9-5.0 Mb with genomic DNA G+C content of 41.5 mol%. Based on the above characteristics, strains S2-4-21T and MT2-5-19 represented a novel species of a novel genus in the family Flavobacteriaceae. Thus, Pareuzebyella sediminis gen. nov. sp. nov. is proposed with type strain S2-4-21T (=MCCC 1K03818T=KCTC 72152T), and another strain MT2-5-19 (=KCTC 72539=MCCC 1K03874).

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.

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.

Prediction of severe illness due to COVID-19 based on an analysis of initial Fibrinogen to Albumin Ratio and Platelet count.

Concomitant coagulation disorder can occur in severe patients withCOVID-19, but in-depth studies are limited. This study aimed to describe the parameters of coagulation function of patients with COVID-19 and reveal the risk factors of developing severe disease. This study retrospectively analyzed 113patients with SARS-CoV-2 infection in Taizhou Public Health Center. Clinical characteristics and indexes of coagulation function were collected. A multivariate Cox analysis was performed to identify potential biomarkers for predicting disease progression. Based on the results of multivariate Cox analysis, a Nomogram was built and the predictive accuracy was evaluated through the calibration curve, decision curve, clinical impact curve, and Kaplan-Meier analysis. Sensitivity, specificity, predictive values were calculated to assess the clinical value. The data showed that Fibrinogen, FAR, and D-dimer were higher in the severe patients, while PLTcount, Alb were much lower. Multivariate Cox analysis revealed that FAR and PLT count were independent risk factors for disease progression. The optimal cutoff values for FAR and PLT count were 0.0883 and 135*109/L, respectively. The C-index [0.712 (95% CI = 0.610-0.814)], decision curve, clinical impact curve showed that Nomogram could be used to predict the disease progression. In addition, the Kaplan-Meier analysis revealed that potential risk decreased in patients with FAR<0.0883 and PLT count>135*109/L.The model showed a good negative predictive value [(0.9474 (95%CI = 0.845-0.986)].This study revealed that FAR and PLT count were independent risk factors for severe illness and the severity of COVID-19 might be excluded when FAR<0.0883 and PLT count>135*109/L.

Pseudopuniceibacterium sediminis gen. nov., sp. nov., a member of the family Rhodobacteraceae isolated from sediment.

A novel Gram-stain-negative bacterium, strain CY03T, was isolated from sediment of the Yellow Sea, PR China. Cells of strain CY03T were rods, aerobic and non-flagellated. Growth occurred at 5-40 °C (optimum, 30 °C), pH 5.5-9.5 (pH 7.5) and with 0.5-9.0 % NaCl (1.5-2.0 %). The 16S rRNA gene sequence comparison showed affiliation to the family Rhodobacteraceae with Puniceibacterium confluentis (97.0 %) as the most closely related species, followed by members of the genus Pseudooceanicola, Pseudooceanicola antarcticus (96.8 %) and Pseudooceanicola nitratireducens (96.7 %). The major cellular fatty acids were cyclo-C19 : 0 ω8c, C16 : 0, summed feature 8 (C18 : 1 ω7c and/or C18 : 1 ω6c) and 11-methyl C18 : 1 ω7c. The polar lipids consisted of phosphatidylcholine, phosphatidylglycerol, one unidentified phospholipid, one unidentified aminolipid and five unidentified lipids. The predominant respiratory quinone was Q-10. The DNA G+C content of the type strain was 62.8 mol%. Based on the results of the polyphasic characterization for strain CY03T, it represents a novel species of a novel genus of the family Rhodobacteraceae, for which the name Pseudopuniceibacterium sediminis gen. nov., sp. nov. is proposed. The type strain is CY03T (=CCTCC AB 2017195T=KCTC 62198T).