Data Analysis of Heart Rate Variability and Arrhythmia in Patients with Paroxysmal Atrial Fibrillation.

BACKGROUND: Atrial fibrillation (AF) is the most common type of arrhythmia. Heart rate variability (HRV) may be associated with AF risk. The aim of this study was to test HRV indices and arrhythmias as predictors of paroxysmal AF based on 24-hour dynamic electrocardiogram recordings of patients. METHODS: A total of 199 patients with paroxysmal AF (AF group) and 204 elderly volunteers over 60 years old (Control group) who underwent a 24-hour dynamic electrocardiogram from August 2022 to March 2023 were included. Time-domain indices, frequency-domain indices, and arrhythmia data of the two groups were classified and measured. Binary logistic regression analysis was performed on variables with significant differences to identify independent risk factors. A nomogram prediction model was established, and the sum of individual scores of each variable was calculated. RESULTS: Gender, age, body mass index and low-density lipoprotein (LDL) did not differ significantly between AF and Control groups (p > 0.05), whereas significant group differences were found for smoking, hypertension, diabetes, and high-density lipoprotein (HDL) (p < 0.05). The standard deviation of all normal to normal (NN) R-R intervals (SDNN), standard deviation of 5-minute average NN intervals (SDANN), root mean square of successive NN interval differences (rMSSD), 50 ms from the preceding interval (pNN50), low-frequency/high-frequency (LF/HF), LF, premature atrial contractions (PACs), atrial tachycardia (AT), T-wave index, and ST-segment index differed significantly between the two groups. Logistic regression analysis identified rMSSD, PACs, and AT as independent predictors of AF. For each unit increase in rMSSD and PACs, the odds of developing AF increased by 1.0357 and 1.0005 times, respectively. For each unit increase in AT, the odds of developing AF decreased by 0.9976 times. The total score of the nomogram prediction model ranged from 0 to 110. CONCLUSION: The autonomic nervous system (ANS) plays a pivotal role in the occurrence and development of AF. The individualized nomogram prediction model of AF occurrence contributes to the early identification of high-risk patients with AF.

Novel citrinin derivatives from fungus Penicillium sp. TW131-64 and their antimicrobial activities.

Six new citrinin derivatives (1, 2, 4, 10, 11, and 16), along with fourteen known analogues, were acquired from Penicillium sp. TW131-64, a marine-derived fungus strain. The chemical structures of new compounds were identified through adopting various spectroscopic methods in combination with X-ray diffraction technology and comparison of the experimental electronic circular dichroism (ECD) with calculated ones. Among them, compounds 1-4 were nitrogen-containing citrinin derivatives existing in enantiomers which were resolved by chiral chromatography. A putative biosynthetic pathway for compounds 1-4 was proposed. Additionally, the antimicrobial activities of these compounds were detected by the broth microdilution assays. Citrinin derivatives 1, 2, 4 and their corresponding enantiomers (1a, 2a, 4a, 1b, 2b, and 4b) exhibited potent antimicrobial activities towards Helicobacter pylori standard strains and multidrug-resistant strains (MIC values ranging from 0.25 to 8 µg/mL), which were comparable or even better than metronidazole. Moreover, compounds 1a and 1b also showed remarkable broad antimicrobial effects towards Staphylococcus aureus, Enterococcus faecalis, methicillin-resistant Staphylococcus aureus (MRSA), Bacillus subtilis, vancomycin-resistant Enterococcus faecium (VRE), and Candida albicans. In summary, our studies demonstrated that citrinin enantiomers 1a-4a and 1b-4b, especially 1a and 1b, can be lead compounds in the research and development (R & D) of novel antimicrobial drugs. KEY POINTS: • 3 novel nitrogen-containing citrinin derivatives (1, 2, 4) were isolated. • citrinin derivatives 1-4 in enantiomers were resolved by chiral chromatography. • citrinin derivatives 1a and 1b showed broad and significant antimicrobial effects.

Killing of Staphylococcus aureus persisters by a multitarget natural product chrysomycin A.

Staphylococcus aureus poses a severe public health problem as one of the vital causative agents of healthcare- and community-acquired infections. There is a globally urgent need for new drugs with a novel mode of action (MoA) to combat S. aureus biofilms and persisters that tolerate antibiotic treatment. We demonstrate that a benzonaphthopyranone glycoside, chrysomycin A (ChryA), is a rapid bactericide that is highly active against S. aureus persisters, robustly eradicates biofilms in vitro, and shows a sustainable killing efficacy in vivo. ChryA was suggested to target multiple critical cellular processes. A wide range of genetic and biochemical approaches showed that ChryA directly binds to GlmU and DapD, involved in the biosynthetic pathways for the cell wall peptidoglycan and lysine precursors, respectively, and inhibits the acetyltransferase activities by competition with their mutual substrate acetyl-CoA. Our study provides an effective antimicrobial strategy combining multiple MoAs onto a single small molecule for treatments of S. aureus persistent infections.

An immune-based risk-stratification system for predicting prognosis in pulmonary sarcomatoid carcinoma (PSC).

Pulmonary sarcomatoid carcinoma (PSC) is an uncommon subtype of lung cancer, and immune checkpoint blockade promises in clinical benefit. However, virtually nothing is known about the expression of common immune checkpoints in PSC. Here, we performed immunohistochemistry (IHC) to detect nine immune-related proteins in 97 PSC patients. Based on the univariable Cox regression, random forests were used to establish risk models for OS and DFS. Moreover, we used the GSEA, CIBERSORT, and ImmuCellAI to analyze the enriched pathways and microenvironment. Univariable analysis revealed that CD4 (P = 0.008), programmed cell death protein 1 (PD-1; P = 0.003), galectin-9 (Gal-9) on tumor cells (TCs; P = 0.021) were independent for DFS, while CD4 (P = 0.020), PD-1 (P = 0.004), Gal-9 (P = 0.033), and HLA on TILs (P = 0.031) were significant for OS. Meanwhile, the expression level of CD8 played a marginable role in DFS (P = 0.061), limited by the number of patients. The combination of Gal-9 on TC with CD4 and PD-1 on TILs demonstrated the most accurate prediction for DFS (AUC: 0.636-0.791, F1-score: 0.635-0.799), and a dramatic improvement to TNM-stage (P < 0.001 for F1-score of 1-y, 3-y, and 5-yDFS). A similar finding was also observed in the predictive ability of CD4 for OS (AUC: 0.602-0.678, F1-score: 0.635-0.679). CD4 was negatively associated with the infiltration of neutrophils (P = 0.015). PDCD1 (coding gene of PD-1) was positively correlated to the number of exhausted T cells (Texs; P = 0.020) and induced regulatory T cells (iTregs; P = 0.021), and LGALS9 (coding gene of Gal-9) was positively related to the level of dendritic cells (DCs; P = 0.021). Further, a higher combinational level of CD4, PDCD1 on TILs, and LAGLS9 on TCs were proved to be infiltrated with more M1-type macrophages (P < 0.05). We confirmed the expression status of nine immune-related proteins and established a TNM-Immune system for OS and DFS in PSC to assist clinical risk-stratification.