A Cross-Sectional Study of Atherosclerosis in Newly Diagnosed Patients with Ketosis-Prone Type 2 Diabetes.

Purpose: To investigate the prevalence, clinical and metabolic characteristics of atherosclerosis (AS) in newly diagnosed patients with ketosis-prone type 2 diabetes (KPT2D) or non-ketotic type 2 diabetes (NKPT2D). Patients and Methods: About 1072 subjects with non-autoimmune new-onset diabetes were included in the cross-sectional study. Patients were classified as non-ketotic type 2 diabetes (NKPT2D, n = 662) or ketosis-prone type 2 diabetes (KPT2D, n = 410). Blood samples were collected to determine the levels of glucose, HbA1c, insulin and C-peptide. Routine liver and kidney function tests were also performed. AS was determined by vascular ultrasonography. Results: The levels of fasting blood glucose and HbA1c were significant higher in the KPT2D group when compared to the NKPT2D group (P<0.001). The levels of fasting C-peptide, 2 h C-peptide and HOMA-ß were lower in the KPT2D group than those in NKPT2D group (P<0.001). However, no significant difference was observed for HOMA-IR between the two groups. The onset age of the patients with KPT2D was significantly lower compared to NKPT2D patients (38±13 vs 49±14, P<0.001). After adjusting age of the two groups, the KPT2D patients had a higher prevalence of AS compared to the NKPT2D patients (31.4% vs 21.1%, P=0.005). In both groups, age and gender were independent risk factors for AS, whereas estimated glomerular filtration rate (eGFR) was an independent risk factor in the NKPT2D patients and 2-h postprandial plasma glucose (2h-PPG) was an independent risk factor in the KPT2D patients. Conclusion: AS was more prevalent in KPT2D patients compared to the NKPT2D cohort, which was independent of age and gender. These data suggest that KPT2D patients may have a higher risk of macrovascular complications compared to NKPT2D of the same age.

Bioinformatics and Transcriptome Analysis of CFEM Proteins in Fusarium graminearum.

Fusarium blight of wheat is usually caused by Fusarium graminearum, and the pathogenic fungi will secrete effectors into the host plant tissue to affect its normal physiological process, so as to make it pathogenic. The CFEM (Common in Fungal Extracellular Membrane) protein domain is unique to fungi, but it is not found in all fungi. The CFEM protein contained in F. graminearum may be closely related to pathogenicity. In this study, 23 FgCFEM proteins were identified from the F. graminearum genome. Then, features of these proteins, such as signal peptide, subcellular localization, and transmembrane domains, etc., were analyzed and candidate effectors were screened out. Sequence alignment results revealed that each FgCFEM protein contains one CFEM domain. The amino acids of the CFEM domain are highly conserved and contain eight spaced cysteines, with the exception that FgCFEM8, 9, and 15 lack two cysteines and three cysteines were missed in FgCFEM18 and FgCFEM22. A recently identified CFEM_DR motif was detected in 11 FgCFEMs, and importantly we identified two new conserved motifs containing about 29 and 18 amino acids (CFEM_WR and CFEM_KF), respectively, in some of FgCFEM proteins. Transcriptome analysis of the genes encoding CFEM proteins indicated that all the CFEM-containing genes were expressed during wheat infection, with seven and six genes significantly up- and down-regulated, respectively, compared with in planta and in vitro. Based on the above analysis, FgCFEM11 and FgCFEM23 were predicted to be F. graminearum effectors. This study provides the basis for future functional analyses of CFEM proteins in F. graminearum.

Predictive value of the prognostic nutritional index for the severity of coronavirus disease 2019.

OBJECTIVES: Malnutrition plays a critical role in the onset and progress of the coronavirus disease 2019 (COVID-19). The aim of the present study was to explore the association of the prognostic nutritional index (PNI) score with the severity of COVID-19 and its predictive value of the severe form of COVID-19. METHODS: Clinical data were collected from 122 patients infected with COVID-19 and hospitalized at the Sixth People's Hospital of Wenzhou, China, a specialized infectious hospital affiliated with the Wenzhou Central Hospital. PNI score was calculated as serum albumin (g/L) + 5 × total lymphocyte count (/nL). RESULTS: The study population consisted of 105 patients (86.1%) with a common form and 17 patients (13.9%) with a severe form of COVID-19. PNI score significantly decreased from patients with common to severe forms of COVID-19 (P = .029) regardless of sex, age range, and body mass index (BMI). After adjustment for sex, age, indexes of liver and renal function, C-reactive protein, and current smoking status, PNI scores remained independently and inversely associated with the severity of COVID-19 (odd ratio: 0.797; P = .030). A receiver operating characteristic analysis showed that PNI scores had a similar accuracy to predict severe forms of COVID-19 compared with its combination with sex, age, and BMI (P = .402). PNI < 49 was defined as the cutoff value to predict the severe form of COVID-19. CONCLUSIONS: Poorer nutritional status predisposed patients infected with COVID-19 to its severe form. Independently associated with the severity of COVID-19, PNI score could serve as a simple, fast, and effective predictor among patients with different sex, age, and BMI.