The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of pathway/genome databases

The MetaCyc database (MetaCyc.org) is a comprehensive and freely accessible resource for metabolic pathways and enzymes from all domains of life. The pathways in MetaCyc are experimentally determined, small-molecule metabolic pathways and are curated from the primary scientific literature. With more than 1400 pathways, MetaCyc is the largest collection of metabolic pathways currently available. Pathways reactions are linked to one or more well-characterized enzymes, and both pathways and enzymes are annotated with reviews, evidence codes, and literature citations. BioCyc (BioCyc.org) is a collection of more than 500 organism-specific Pathway/Genome Databases (PGDBs). Each BioCyc PGDB contains the full genome and predicted metabolic network of one organism. The network, which is predicted by the Pathway Tools software using MetaCyc as a reference, consists of metabolites, enzymes, reactions and metabolic pathways. BioCyc PGDBs also contain additional features, such as predicted operons, transport systems, and pathway hole-fillers. The BioCyc Web site offers several tools for the analysis of the PGDBs, including Omics Viewers that enable visualization of omics datasets on two different genome-scale diagrams and tools for comparative analysis. The BioCyc PGDBs generated by SRI are offered for adoption by any party interested in curation of metabolic, regulatory, and genome-related information about an organism

Generation of Abundant Defects in Ferrite Carbon Magnetic Nanomaterials for Eliminating Electromagnetic Interference in Communication

A series of novel ferrite carbon nanomaterials are considered to obtain the potential advantages in elimination of the electromagnetic interference effects. Herein, the iron nanoparticles coated on amorphous carbon were prepared by facile agar-gel synthesis. Meanwhile, the synergy between carbon supporting and ferrite nanomaterials could be proved to promote the absorption properties. Among all samples, the iron nanoparticles coated on amorphous carbon show the highest microwave absorption properties, achieving the maximum reflection loss (RL) of −14.3 dB at 6 GHz (5.5-milimeter thickness), and the bandwidths over −10 dB (90% absorption) was 2.5 GHz. Combining analysis results, it is confirmed that the as-prepared iron nanoparticles have the highest surface area, homogeneous distribution, abundant defect, and well-defined pore structure, which could significantly affect the absorption properties at 6 GHz. Furthermore, the abundant defects derived from the interface were the essential reason for the improved absorption properties. Overall, it provided a new strategy to design an effective method to absorb nanomaterials for the elimination of electromagnetic interference, especially the coordination of metal species and carbon supporting

The incidence, risk factors and in-hospital mortality of acute kidney injury in patients after abdominal aortic aneurysm repair surgery

Abstract Background Acute kidney injury (AKI) is a severe complication associated with abdominal aortic aneurysm (AAA) repair. In this study, we evaluated the incidence, risk factors and in-hospital mortality of AKI in patients after the AAA repair surgery. Methods A total of 314 Chinese AAA patients who underwent endovascular aneurysm repair (EVAR) or open aneurysm repair (OPEN) were enrolled in this study. AKI was diagnosed according to the 2012 KDIGO criteria. Logistic regression modeling was used to explore risk factors of AKI, while risk factors associated with in-hospital mortality in AKI patients were investigated using Cox proportional hazards model and Kaplan-Meier analysis, respectively. Multicollinearity analysis was performed to identify the collinearity between the variables before logistic regression analysis and Cox proportional hazards analysis. Results Among 314 patients, 94 (29.9%) developed AKI after AAA repair surgery. Severity of AKI and ruptured AAA were independently associated with an increase in in-hospital mortality in AKI patients after AAA repair. Kaplan-Meier analysis identified severity of AKI as being negatively associated with hospital survival in AKI patients. Risk factors associated with AKI included cardiovascular disease (OR 3.169, 95% confidence interval (CI) 1.538 to 6.527, P = 0.002), decreased eGFR (OR 0.965, 95%CI 0.954 to 0.977, P < 0.001), ruptured AAA (OR 2.717, 95%CI 1.320 to 5.592, P = 0.007), renal artery involvement (OR 2.903, 95%CI 1.219 to 6.912, P = 0.016) and OPEN (OR 2.094, 95%CI 1.048 to 4.183, P = 0.036). Further subgroup analysis identified OPEN as an important risk factor of AKI in ruptured AAA patients but not in ruptured AAA patients. The incidence of AKI was significantly lower in EVAR than in OPEN (27.1% vs. 42.8%) and, similarly lower in nonruptured AAA than in ruptured AAA (26.2% vs. 48.1%). Conclusion One-third of AAA patients developed AKI after repair surgery. Severity of AKI was associated with reduced survival rate in AAA patients who developed postoperative AKI. Decreased preoperative creatinine clearance, cardiovascular disease, ruptured AAA and OPEN were independent risk factors for postoperative AKI in all 314 AAA patients. Although a lower rate of incident AKI was observed in EVAR compared with OPEN, subgroup analysis of ruptured AAA versus nonruptured AAA showed that EVAR was an independent protective factor for AKI only in ruptured AAA patients but not in nonruptured AAA patients

Image_1_Plasma exosomal IRAK1 can be a potential biomarker for predicting the treatment response to renin-angiotensin system inhibitors in patients with IgA nephropathy.jpeg

BackgroundRenin-angiotensin system inhibitors (RASi) are the first choice and basic therapy for the treatment of IgA nephropathy (IgAN) with proteinuria. However, approximately 40% of patients have no response to RASi treatment. The aim of this study was to screen potential biomarkers for predicting the treatment response of RASi in patients with IgAN.MethodsWe included IgAN patients who were treatment-naive. They received supportive treatment, including a maximum tolerant dose of RASi for 3 months. According to the degree of decrease in proteinuria after 3 months of follow-up, these patients were divided into a sensitive group and a resistant group. The plasma of the two groups of patients was collected, and the exosomes were extracted for high-throughput sequencing. The screening of hub genes was performed using a weighted gene co-expression network (WGCNA) and filtering differentially expressed genes (DEGs). We randomly selected 20 patients in the sensitive group and 20 patients in the resistant group for hub gene validation by real-time quantitative polymerase chain reaction (qRT−PCR). A receiver operating characteristic (ROC) curve was used to evaluate hub genes that predicted the efficacy of the RASi response among the 40 validation patients.ResultsAfter screening 370 IgAN patients according to the inclusion and exclusion criteria and the RASi treatment response evaluation, there were 38 patients in the sensitive group and 32 patients in the resistant group. IRAK1, ABCD1 and PLXNB3 were identified as hub genes by analyzing the high-throughput sequencing of the plasma exosomes of the two groups through WGCNA and DEGs screening. The sequencing data were consistent with the validation data showing that these three hub genes were upregulated in the resistant group compared with the sensitive group. The ROC curve indicated that IRAK1 was a good biomarker to predict the therapeutic response of RASi in patients with IgAN.ConclusionsPlasma exosomal IRAK1 can be a potential biomarker for predicting the treatment response of RASi in patients with IgAN.</p

Table_1_Plasma exosomal IRAK1 can be a potential biomarker for predicting the treatment response to renin-angiotensin system inhibitors in patients with IgA nephropathy.docx

BackgroundRenin-angiotensin system inhibitors (RASi) are the first choice and basic therapy for the treatment of IgA nephropathy (IgAN) with proteinuria. However, approximately 40% of patients have no response to RASi treatment. The aim of this study was to screen potential biomarkers for predicting the treatment response of RASi in patients with IgAN.MethodsWe included IgAN patients who were treatment-naive. They received supportive treatment, including a maximum tolerant dose of RASi for 3 months. According to the degree of decrease in proteinuria after 3 months of follow-up, these patients were divided into a sensitive group and a resistant group. The plasma of the two groups of patients was collected, and the exosomes were extracted for high-throughput sequencing. The screening of hub genes was performed using a weighted gene co-expression network (WGCNA) and filtering differentially expressed genes (DEGs). We randomly selected 20 patients in the sensitive group and 20 patients in the resistant group for hub gene validation by real-time quantitative polymerase chain reaction (qRT−PCR). A receiver operating characteristic (ROC) curve was used to evaluate hub genes that predicted the efficacy of the RASi response among the 40 validation patients.ResultsAfter screening 370 IgAN patients according to the inclusion and exclusion criteria and the RASi treatment response evaluation, there were 38 patients in the sensitive group and 32 patients in the resistant group. IRAK1, ABCD1 and PLXNB3 were identified as hub genes by analyzing the high-throughput sequencing of the plasma exosomes of the two groups through WGCNA and DEGs screening. The sequencing data were consistent with the validation data showing that these three hub genes were upregulated in the resistant group compared with the sensitive group. The ROC curve indicated that IRAK1 was a good biomarker to predict the therapeutic response of RASi in patients with IgAN.ConclusionsPlasma exosomal IRAK1 can be a potential biomarker for predicting the treatment response of RASi in patients with IgAN.</p

Analysis of 394 COVID-19 cases infected with Omicron variant in Shenzhen: impact of underlying diseases to patient’s symptoms

Abstract Objectives The emergence of new variants of SARS-CoV-2 is continuously posing pressure to the epidemic prevention and control in China. The Omicron variant of SARS-CoV-2 having stronger infectivity, immune escape ability, and capability causing repetitive infection spread to many countries and regions all over the world including South Africa, United States and United Kingdom etc., in a short time. The outbreaks of Omicron variant also occurred in China. The aim of this study is to understand the epidemiological characteristics of Omicron variant infection in Shenzhen and to provide scientific basis for effective disease control and prevention. Methods The clinical data of 394 imported COVID-19 cases infected with Omicron variant from 16 December 2021 to 24 March 2022 admitted to the Third People’s hospital of Shenzhen were collected and analyzed retrospectively. Nucleic acid of SARS-CoV-2 of nasopharyngeal swabs and blood samples was detected using 2019-nCoV nucleic acid detection kit. Differences in Ct values of N gene were compared between mild group and moderate group. The specific IgG antibody was detected using 2019-nCoV IgG antibody detection kit. Statistical analysis was done using SPSS software and graphpad prism. Results Patients were categorized into mild group and moderate group according to disease severity. The data on the general conditions, underlying diseases, COVID-19 vaccination and IgG antibody, viral load, laboratory examination results, and duration of hospitalization, etc., were compared among disease groups. Mild gorup had higher IgG level and shorter nucleic acid conversion time. Patients with underlying diseases have 4.6 times higher probability to progress to moderate infection. Conclusion In terms of epidemic prevention, immunization coverage should be strengthened in the population with underlying diseases. In medical institutions, more attention needs to be paid to such vulnerable population and prevent further deterioration of the disease