Prognostic and risk factor analysis of cancer patients after unplanned ICU admission: a real-world multicenter study.

To investigate the occurrence and 90-day mortality of cancer patients following unplanned admission to the intensive care unit (ICU), as well as to develop a risk prediction model for their 90-day prognosis. We prospectively analyzed data from cancer patients who were admitted to the ICU without prior planning within the past 7 days, specifically between May 12, 2021, and July 12, 2021. The patients were grouped based on their 90-day survival status, and the aim was to identify the risk factors influencing their survival status. A total of 1488 cases were included in the study, with an average age of 63.2 ± 12.4 years. The most common reason for ICU admission was sepsis (n = 940, 63.2%). During their ICU stay, 29.7% of patients required vasoactive drug support (n = 442), 39.8% needed invasive mechanical ventilation support (n = 592), and 82 patients (5.5%) received renal replacement therapy. We conducted a multivariate COX proportional hazards model analysis, which revealed that BMI and a history of hypertension were protective factors. On the other hand, antitumor treatment within the 3 months prior to admission, transfer from the emergency department, general ward, or external hospital, high APACHE score, diagnosis of shock and respiratory failure, receiving invasive ventilation, and experiencing acute kidney injury (AKI) were identified as risk factors for poor prognosis within 90 days after ICU admission. The average length of stay in the ICU was 4 days, while the hospital stay duration was 18 days. A total of 415 patients died within 90 days after ICU admission, resulting in a mortality rate of 27.9%. We selected 8 indicators to construct the predictive model, which demonstrated good discrimination and calibration. The prognosis of cancer patients who are unplanned transferred to the ICU is generally poor. Assessing the risk factors and developing a risk prediction model for these patients can play a significant role in evaluating their prognosis.

Large-Scale Qualitative and Quantitative Assessment of Dityrosine Crosslinking Omics in Response to Endogenous and Exogenous Hydrogen Peroxide in Escherichia coli.

Excessive hydrogen peroxide causes oxidative stress in cells. The oxidation of two tyrosine residues in proteins can generate o,o'-dityrosine, a putative biomarker for protein oxidation, which plays critical roles in a variety of organisms. Thus far, few studies have investigated dityrosine crosslinking under endogenous or exogenous oxidative conditions at the proteome level, and its physiological function remains largely unknown. In this study, to investigate qualitative and quantitative dityrosine crosslinking, two mutant Escherichia coli strains and one mutant strain supplemented with H2O2 were used as models for endogenous and exogenous oxidative stress, respectively. By integrating high-resolution liquid chromatography-mass spectrometry and bioinformatic analysis, we created the largest dityrosine crosslinking dataset in E. coli to date, identifying 71 dityrosine crosslinks and 410 dityrosine loop links on 352 proteins. The dityrosine-linked proteins are mainly involved in taurine and hypotaurine metabolism, citrate cycle, glyoxylate, dicarboxylate metabolism, carbon metabolism, etc., suggesting that dityrosine crosslinking may play a critical role in regulating the metabolic pathways in response to oxidative stress. In conclusion, we have reported the most comprehensive dityrosine crosslinking in E. coli for the first time, which is of great significance in revealing its function in oxidative stress.

Discovery and validation of glucose-sensitive peptide biomarkers from human serum albumin to diagnose type 2 diabetes mellitus.

Glycated albumin (GA), which represents the global glycation level of albumin, has emerged as a biomarker for diagnosing prediabetes and diabetes. In our previous study, we developed a peptide-based strategy and found three putative peptide biomarkers from the tryptic peptides of GA to diagnose type 2 diabetes mellitus (T2DM). However, the trypsin cleavage sites at the carboxyl side of lysine (K) and arginine (R) are consistent with the nonenzymatic glycation modification site residues, which considerably increases the number of missed cleavage sites and half-cleaved peptides. To solve this problem, the endoproteinase Glu-C was used to digest GA from human serum to screen putative peptides to diagnose T2DM. In the discovery phase, we found eighteen and fifteen glucose-sensitive peptides from purified albumin and human serum incubated with 13C glucose in vitro, respectively. In the validation phase, eight glucose-sensitive peptides were screened and validated in 72 clinical samples (28 healthy controls and 44 patients with diabetes) using label-free LC-ESI-MRM. Three putative sensitive peptides (VAHRFKDLGEE, FKPLVEEPQNLIKQNCE and NQDSISSKLKE) from albumin exhibited good specificity and sensitivity based on receiver operating characteristic analysis. In summary, three peptides were found as promising biomarkers for the diagnosis and assessment of T2DM based on mass spectrometry.

Multi-Omics Strategies to Investigate the Biodegradation of Hexahydro-1,3,5-trinitro-1,3,5-triazine in Rhodococcus sp. Strain DN22.

Hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) is an energetic and persistent explosive with long-lasting properties. Rhodococcus sp. strain DN22 has been discovered to be a microbe capable of degrading RDX. Herein, the complete genome of Rhodococcus sp. strain DN22 was sequenced and analyzed. The entire sequences of genes that encoded the two proteins participating in RDX degradation in Rhodococcus sp. strain DN22 were obtained, and were validated through proteomic data. In addition, few studies have investigated the physiological changes and metabolic pathways occurring within Rhodococcus sp. cells when treated with RDX, particularly through mass spectrometry-based omics. Hence, proteomic and metabolomic analyses were carried out on Rhodococcus sp. strain DN22 with the existence or lack of RDX in the medium. A total of 3186 proteins were identified between the two groups, with 115 proteins being significantly differentially expressed proteins. There were 1056 metabolites identified in total, among which 130 metabolites were significantly different. Through the combined analysis of differential proteomics and metabolomics, KEGG pathways including two-component system, ABC transporters, alanine, aspartate and glutamate metabolism, arginine biosynthesis, purine metabolism, nitrogen metabolism, and phosphotransferase system (PTS), were observed to be significantly enriched. These findings provided ponderable perspectives on the physiological alterations and metabolic pathways in Rhodococcus sp. strain DN22, responding to the existence or lack of RDX. This study is anticipated to expand the knowledge of Rhodococcus sp. strain DN22, as well as advancing understanding of microbial degradation.