Significance of the plasma membrane H+-ATPase and V-ATPase for growth and pathogenicity in pathogenic fungi.

Pathogenic fungi are widespread and cause a variety of diseases in human beings and other organisms. At present, limited classes of antifungal agents are available to treat invasive fungal diseases. With the wide use of the commercial antifungal agents, drug resistance of pathogenic fungi are continuously increasing. Therefore, exploring effective antifungal agents with novel drug targets is urgently needed to cope with the challenges that the antifungal area faces. pH homeostasis is vital for multiple cellular processes, revealing the potential for defining novel drug targets. Fungi have evolved a number of strategies to maintain a stable pH internal environment in response to rapid metabolism and a dramatically changing extracellular environment. Among them, plasma membrane H+-ATPase (PMA) and vacuolar H+-ATPase (V-ATPase) play a central role in the regulation of pH homeostasis system. In this chapter, we will summarize the current knowledge about pH homeostasis and its regulation mechanisms in pathogenic fungi, especially for the recent advances in PMA and V-ATPase, which would help in revealing the regulating mechanism of pH on cell growth and pathogenicity, and further designing effective drugs and identify new targets for combating fungal diseases.

[Predictive value of neck circumference for cardiometabolic risk in children].

Objective: To investigate the predictive value of neck circumference on cardiometabolic risk in children. Methods: This was a cross-sectional study of natural sources. As the prediction cohort, clinical data were collected from 3 443 children aged 5-14 years who underwent physical examination in the Department of Child Healthcare, Children's Hospital of Nanjing Medical University from July 2021 to September 2022. As the validation cohort for external validation, clinical data were collected from 604 children aged 5-14 years who underwent physical examination in the Department of Child Healthcare, Children's Hospital of Nanjing Medical University from October 2022 to March 2023. Height, weight, neck circumference, waist circumference and body composition were measured in both groups, and body mass index, neck circumference to height ratio (NHtR), waist circumference to height ratio, body fat percentage and skeletal muscle percentage were calculated. Systolic blood pressure, diastolic blood pressure, fasting blood glucose, blood lipid and uric acid and other cardiovascular and metabolic risk indicators were collected in both groups. The prediction cohort was further stratified into clustered and non-clustered groups based on the clustering of cardiometabolic risk factors (CCRF). Various variables between these 2 groups were compared using the Mann-Whitney U test. Pearson correlation and binary Logistic regression were conducted to investigate the correlations between neck circumference and cardiovascular metabolic risk factors. The accuracy of NHtR in predicting the CCRF was evaluated using the area under the curve (AUC) of receiver operating characteristic (ROC). The cutoff value was determined using the Youden index. The validation cohort was then divided into groups above and below the cutoff value, and the detection rate of CCRF between the 2 groups was compared using the χ2 test for validation. Results: In the prediction cohort of 3 443 children (2 316 boys and 1 127 girls), 1 395 (40.5%) children were overweight or obese, and 1 157 (33.6%) children had CCRF. Pearson correlation analysis revealed all significant positive correlations (all P<0.01) between neck circumference and systolic blood pressure (r=0.47, 0.39), diastolic blood pressure (r=0.27, 0.21), uric acid (r=0.36, 0.30), and triglycerides (r=0.20, 0.20) after adjusting for age in both males and females. Among both males and females, neck circumference both showed significant negative correlation (both P<0.01) with high-density lipoprotein cholesterol (r=-0.27, -0.28), and no correlation with fasting glucose levels (r=0.03, -0.03, both P>0.05). After adjusting for gender, age, and body fat percentage, increased body mass index, neck circumference, or waist circumference increased the risks of hypertension (OR=1.23, 1.39, 1.07, all P<0.001), hyperuricemia (OR=1.16, 1.23, 1.05, all P<0.001), hypertriglyceridemia (OR=1.08, 1.16, 1.02, all P<0.01), low high-density lipoprotein cholesterol (OR=1.10, 1.27, 1.03, all P<0.01), and the CCRF (OR=1.51, 1.73, 1.15, all P<0.01). The areas under the ROC curves of NHtR in predicting CCRF was 0.73, with sensitivity and specificity at 0.66 and 0.71, respectively. The corresponding optimal cut-off value was 0.21. Validation with 604 children confirmed that the detection of CCRF in the NHtR≥0.21 group was 3.29 times (60.5% (112/185) vs. 18.7% (79/422),χ2=107.82, P<0.01) higher compared to the NHtR <0.21 group. Conclusions: Neck circumference is associated with cardiovascular metabolic risks such as hypertension, hyperlipidemia, hyperglycemia, and hyperuricemia in children. When the NHtR is ≥0.21, there is an increased likelihood of CCRF.

[Reference values of skeletal muscle mass for children in Nanjing area].

Objective: To establish the reference values and growth curves of skeletal muscle mass among children in the Nanjing area. Methods: A cross-sectional study was conducted with children who underwent physical examination at the Department of Child Health Care, Children's Hospital of Nanjing Medical University from 2020 January to 2022 September. Their height, weight, body fat mass and skeletal muscle mass were measured. Body mass index, percentage of body fat mass, percentage of skeletal muscle mass, relative skeletal muscle mass index and the ratio of skeletal muscle to body fat were calculated. The associations between skeletal muscle mass indices and physical measurements index were analyzed through the Spearman correlation test. The Mann-Kendall test was used to assess the trend for skeletal muscle mass. Generalized additive models for location, scale and shape were used to construct percentile reference values and growth curves of male and female skeletal muscle mass indices at different ages. Results: A total of 32 690 children aged 4-14 years were enrolled in this study, including 19 912 boys (60.91%). Skeletal muscle mass, percentage of skeletal muscle mass, relative skeletal muscle mass index and the ratio of skeletal muscle to body fat of boys and girls was 11.10 (8.40, 14.90) and 10.30 (7.90, 13.20) kg, 40.36% (37.01%, 43.13%) and 39.38% (36.43%, 41.88%), 6.70 (6.07, 7.52) and 6.33 (5.79, 7.00), 2.39 (1.46, 3.47) and 2.14 (1.45, 3.00) kg/m2, respectively. Skeletal muscle mass of both boys and girls was all positively associated with weight (r=0.97, 0.96), body mass index (r=0.68, 0.63) and percentage of body fat mass (r=0.40, 0.43) (all P<0.01). The reference values and growth curves showed that the percentage of skeletal muscle mass P50 ranged from 37.75%-44.61% in boys and from 36.22%-40.55% in girls. The relative skeletal muscle mass index P50 ranged from 5.80-9.68 kg/m2 in boys and from 5.57-7.98 kg/m2 in girls. The ratio of skeletal muscle to body fat P50 ranged from 1.86-2.67 in boys and from 1.29-2.41 in girls. There was an increasing trend with age for both boys and girls in the growth of skeletal muscle mass (Z=4.20, 3.75, both Ptrend<0.01), and increased slightly before 9 years of age and then increased rapidly until 14 years of age in both boys and girls. Conclusions: The skeletal muscle mass indices change with age and gender during childhood. Percentile reference values for pediatric skeletal muscle mass indices can be used to evaluate the muscular growth and development in children in the Nanjing area.

[The correlations of abdominal adipose tissue with anthropometric and metabolic parameters in obese children by magnetic resonance imaging].

Objective: To explore abdominal fat mass distribution and contents among obese children via magnetic resonance imaging (MRI), and analyze the correlations of abdominal adipose tissue with anthropometric and metabolic parameters. Methods: Cross-sectional study. There were 60 obese children admitted to the Children's Health Care Department and Endocrinology Department at Children's Hospital of Nanjing Medical University from July 2016 to December 2018. Children's gender, age, height, weight, body composition, waist circumference and blood pressure were recorded. The levels of fasting blood glucose, lipids, insulin were measured, and liver ultrasound was performed, and the body mass index Z score (BMI-Z), waist-to-height ratio (WHtR) and homeostasis model assessment of insulin resistance (HOMA-IR) were calculated. In addition, contents of subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT) and total abdominal adipose tissue (TAAT) were calculated according to feedback of abdominal MRI scan images. The associations between the contents of abdominal adipose tissue, physical examination status and metabolic disorders among obese children were analyzed through correlation analysis and regression analysis. Receiver operating characteristic (ROC) curve was used to compare the accuracy of fat mass in different parts of the abdomen in predicting their metabolic disorders. Results: A total of 60 children were enrolled in the study, included 44 boys and 16 girls, with age of (9.2±1.4) years. The contents of SAT, VAT and TAAT among the 60 children were positively associated with BMI-Z (r=0.60, 0.46, 0.59), body fat percentage (r=0.64, 0.67, 0.68) and waist-to-height ratio (r=0.60, 0.57, 0.61) (all P<0.01). Meanwhile, contents of SAT and TAAT were also positively correlated with systolic blood pressure (r=0.47, 0.49), triglyceride (r=0.33, 0.35) and HOMA-IR (r=0.33, 0.28)(all P<0.05). In order to adjust the confounding effects among various variables, regression analysis was applied and the result showed that the body fat percentage (ß=0.59, 0.66, 0.65) and waist-to-height ratio (ß=0.53, 0.63, 0.59) were most related to abdominal fat contents (all P<0.01), including SAT, VAT and TAAT among obese children. According to ROC, SAT had outstanding evaluation performances for the diagnosis of insulin resistance and metabolic syndrome, while VAT had excellent evaluation performances for non-alcoholic fatty liver disease (area under curve=0.68, 0.69, 0.69, 95%CI 0.54-0.82, 0.55-0.84, 0.53-0.85, P=0.017, 0.014, 0.019). Conclusions: As one of the best indexes, body fat percentage and WHtR can be used to predict the contents of SAT, VAT and TAAT among obese children. With the increase of abdominal SAT or VAT, the risks for insulin resistance, metabolic syndrome and non-alcoholic fatty liver disease would increase. Assessment of abdominal fat and metabolic risks in obese children should combine BMI-Z with waist circumference and body composition analysis.