Machine learning-based prediction of in-hospital mortality for critically ill patients with sepsis-associated acute kidney injury.

OBJECTIVES: This study aims to develop and validate a prediction model in-hospital mortality in critically ill patients with sepsis-associated acute kidney injury (SA-AKI) based on machine learning algorithms. METHODS: Patients who met the criteria for inclusion were identified in the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database and divided according to the validation (n = 2440) and development (n = 9756, 80%) queues. Ensemble stepwise feature selection method was used to screen for effective features. The prediction models of short-term mortality were developed by seven machine learning algorithms. Ten-fold cross-validation was used to verify the performance of the algorithm in the development queue. The area under the receiver operating characteristic curve (ROC-AUC) was used to evaluate the differentiation accuracy and performance of the prediction model in the validation queue. The best-performing model was interpreted by Shapley additive explanations (SHAP). RESULTS: A total of 12,196 patients were enrolled in this study. Eleven variables were finally chosen to develop the prediction model. The AUC of the random forest (RF) model was the highest value both in the Ten-fold cross-validation and evaluation (AUC: 0.798, 95% CI: 0.774-0.821). According to the SHAP plots, old age, low Glasgow Coma Scale (GCS) score, high AKI stage, reduced urine output, high Simplified Acute Physiology Score (SAPS II), high respiratory rate, low temperature, low absolute lymphocyte count, high creatinine level, dysnatremia, and low body mass index (BMI) increased the risk of poor prognosis. CONCLUSIONS: The RF model developed in this study is a good predictor of in-hospital mortality for patients with SA-AKI in the intensive care unit (ICU), which may have potential applications in mortality prediction.

Iron overload induces islet ß cell ferroptosis by activating ASK1/P-P38/CHOP signaling pathway.

Background: Recent studies have shown that the accumulation of free iron and lipid peroxides will trigger a new form of cell death-ferroptosis. This form of cell death is associated with a variety of diseases, including type 2 diabetes. We hypothesize that iron overload may play a role in driving glucose metabolism abnormalities by inducing endoplasmic reticulum stress that mediates ferroptosis in islet ß cells. In this study, we tested this conjecture from in vivo and in vitro experiments. Methods: We established a mouse iron overload model by intraperitoneal injection of iron dextrose (50 mg/kg) and an iron overload cell model by treating MIN6 cells with ferric ammonium citrate (640 µmol/L, 48 h) in vitro. The iron deposition in pancreatic tissue was observed by Prussian blue staining, and the pathological changes in pancreatic tissues by HE staining and the protein expression level by pancreatic immunohistochemistry. In the cellular experiments, we detected the cell viability by CCK8 and observed the cellular ultrastructure by transmission electron microscopy. We also used MDA and ROS kits to detect the level of oxidative stress and lipid peroxidation in cells. Western blotting was performed to detect the expression levels of target proteins. Results: Iron overload induces MIN6 cell dysfunction, leading to increased fasting blood glucose, impaired glucose tolerance, and significantly decreased insulin sensitivity in mice. This process may be related to the ferroptosis of islet ß cells and the activation of ASK1/P-P38/CHOP signaling pathway.

Development and validation of short-term renal prognosis prediction model in diabetic patients with acute kidney injury.

OBJECTIVE: Diabetes is a major cause of the progression of acute kidney injury (AKI). Few prediction models have been developed to predict the renal prognosis in diabetic patients with AKI so far. The aim of this study was to develop and validate a predictive model to identify high-risk individuals with non-recovery of renal function at 90 days in diabetic patients with AKI. METHODS: Demographic data and related laboratory indicators of diabetic patients with AKI in the First Affiliated Hospital of Guangxi Medical University from January 31, 2012 to January 31, 2022 were retrospectively analysed, and patients were followed up to 90 days after AKI diagnosis. Based on the results of Logistic regression, a model predicting the risk of non-recovery of renal function at 90 days in diabetic patients with AKI was developed and internal validated. Consistency index (C-index), calibration curve, and decision curve analysis were used to evaluate the differentiation, accuracy, and clinical utility of the prediction model, respectively. RESULTS: A total of 916 diabetic patients with AKI were enrolled, with a male to female ratio of 2.14:1. The rate of non-recovery of renal function at 90 days was 66.8% (612/916). There were 641 in development cohort and 275 in validation cohort (ration of 7:3). In the development cohort, a prediction model was developed based on the results of Logistic regression analysis. The variables included in the model were: diabetes duration (OR = 1.022, 95% CI 1.012-1.032), hypertension (OR = 1.574, 95% CI 1.043-2.377), chronic kidney disease (OR = 2.241, 95% CI 1.399-3.591), platelet (OR = 0.997, 95% CI 0.995-1.000), 25-hydroxyvitamin D3 (OR = 0.966, 95% CI 0.956-0.976), postprandial blood glucose (OR = 1.104, 95% CI 1.032-1.181), discharged serum creatinine (OR = 1.003, 95% CI 1.001-1.005). The C-indices of the prediction model were 0.807 (95% CI 0.738-0.875) and 0.803 (95% CI 0.713-0.893) in the development and validation cohorts, respectively. The calibration curves were all close to the straight line with slope 1. The decision curve analysis showed that in a wide range of threshold probabilities. CONCLUSION: A prediction model was developed to help predict short-term renal prognosis of diabetic patients with AKI, which has been verified to have good differentiation, calibration degree and clinical practicability.

Influence of Red Blood Cell Distribution Width on All-Cause Death in Critical Diabetic Patients with Acute Kidney Injury.

Objective: To explore the relationship between red blood cell distribution width (RDW) and all-cause death in critical diabetic patients with acute kidney injury (AKI). Methods: The clinical data of critical diabetic patients with AKI in MIMIC-III database were analyzed retrospectively. According to the survival status of 28-day after AKI and levels of RDW, patients were divided into survival and death groups, high RDW (RDW > 15.3%) and low RDW groups (RDW ≤ 15.3%). Kaplan-Meier curves were used to compare the survival rates of diabetic patients with AKI in different RDW and AKI stages, and Cox regression analysis was used to evaluate the risk factors of 28-day all-cause death in critical diabetic patients with AKI. Results: A total of 5200 patients with critical diabetic patients with AKI were included in this study with the male to female ratio of 1.53:1. The mean follow-up time was 24.97 ± 7.14 days, and the 28-day all-cause mortality was 17.9% (931/5200). Age, RDW, blood urea nitrogen, serum creatinine, lactic acid, proportion of AKI stage, sepsis and respiratory failure in the death group were higher than those in the survival group, while mean arterial pressure (MAP) and red blood cell count were lower than those in the survival group. Kaplan-Meier analysis showed that the 28-day survival rate of the high RDW group was significantly lower than that of the low RDW group (log-rank χ 2 = 9.970, P = 0.002). Multivariate Cox regression analysis showed that advanced age (HR = 1.042, 95% CI = 1.021-1.063), decreased MAP (HR = 0.984, 95% CI = 0.969-0.998), stage 3 AKI (HR = 3.318, 95% CI = 1.598-6.890) and increased RDW (HR = 1.255, 95% CI = 1.123-1.403) were independent risk factors of 28-day all-cause death in critical diabetic patients with AKI (P < 0.05). Conclusion: High level of RDW is an important risk factor of all-cause death in critical diabetic patients with AKI, and it may be used as a valuable index to classify the mortality.

Relationship between total testosterone, sex hormone-binding globulin levels and the severity of non-alcoholic fatty liver disease in males: a meta-analysis.

Background: In recent years, many studies have reported the relationship between non-alcoholic fatty liver disease (NAFLD) and sex hormones, especially total testosterone (TT) and sex hormone-binding globulin (SHBG). However, the relationship between sex hormones and the severity of NAFLD is still unclear. Methods: PubMed, Embase, Cochrane Library, Web of Science, WanFang, China National Knowledge Infrastructure and VIP databases were searched for relevant studies from inception to 31 August 2021. Values of weighted mean differences (WMDs) and odds ratios (ORs) with their 95% confidence intervals (CIs) were combined by Stata 12.0 software to evaluate the relationship between TT, SHBG and the severity of NAFLD in males. Results: A total of 2995 patients with NAFLD from 10 published cross-sectional studies were included for further analysis. The meta-analysis indicated that the moderate-severe group had a lower TT than the mild group in males with NAFLD (WMD: -0.35 ng/ml, 95% CI = -0.50 to -0.20). TT and SHBG were important risk factors of moderate-severe NAFLD in males (ORTT = 0.79, 95% CI = 0.73 to 0.86; ORSHBG = 0.22, 95% CI = 0.12 to 0.39; p < 0.001). Moreover, when the analysis was limited to men older than age 50, SHBG levels were lower in those with moderate-severe disease (WMD: -11.32 nmol/l, 95% CI = -14.23 to -8.40); while for men with body mass index (BMI) >27 kg/m2, moderate-severe NAFLD had higher SHBG levels than those with mild disease (WMD: 1.20 nmol/l, 95% CI = -2.01 to 4.42). Conclusion: The present meta-analysis shows that lower TT is associated with the severity of NAFLD in males, while the relationship between SHBG and severity of NAFLD is still to be further verified.

Association Between Iron Metabolism and Acute Kidney Injury in Critically Ill Patients With Diabetes.

Objective: Iron overload plays an important role in the pathogenesis of diabetes and acute kidney injury (AKI). The aim of this present study was to explore the relationship between iron metabolism and AKI in patients with diabetes. Methods: The clinical data of diabetes patients from MIMIC-III database in intensive care unit (ICU) were retrospectively analyzed. Regression analyses were used to explore the risk factors of AKI and all-cause death in critical patients with diabetes. Area under the receiver operating characteristic curves (AUROCs) were used to analyze serum ferritin (SF), and regression model to predict AKI in critical patients with diabetes. All diabetes patients were followed up for survival at 6 months, and Kaplan-Meier curves were used to compare the survival rate in patients with different SF levels. Results: A total of 4,997 diabetic patients in ICU were enrolled, with a male-to-female ratio of 1.37:1 and a mean age of 66.87 ± 12.74 years. There were 1,637 patients in the AKI group (32.8%) and 3,360 patients in the non-AKI group. Multivariate logistic regression showed that congestive heart failure (OR = 2.111, 95% CI = 1.320-3.376), serum creatinine (OR = 1.342, 95% CI = 1.192-1.512), Oxford Acute Severity of Illness Score (OR = 1.075, 95% CI = 1.045-1.106), increased SF (OR = 1.002, 95% CI = 1.001-1.003), and decreased transferrin (OR = 0.993, 95% CI = 0.989-0.998) were independent risk factors for AKI in critical patients with diabetes. Multivariate Cox regression showed that advanced age (OR = 1.031, 95% CI = 1.025-1.037), AKI (OR = 1.197, 95% CI = 1.011-1.417), increased Sequential Organ Failure Assessment score (OR = 1.055, 95% CI = 1.032-1.078), and increased SF (OR = 1.380, 95% CI = 1.038-1.835) were independent risk factors for 6-month all-cause death in critical diabetic patients. The AUROCs of SF and the regression model to predict AKI in critical patients with diabetes were 0.782 and 0.851, respectively. The Kaplan-Meier curve showed that the 6-month survival rate in SF-increased group was lower than that in SF-normal group (log-rank χ2 = 16.989, P < 0.001). Conclusion: Critically ill diabetic patients with AKI were easily complicated with abnormal iron metabolism. Increase of SF is an important risk factor for AKI and all-cause death in critically ill patients with diabetes.

The safety and efficacy evaluation of sodium-glucose co-transporter 2 inhibitors for patients with non-alcoholic fatty liver disease: An updated meta-analysis.

BACKGROUND: In recent years, sodium-glucose co-transporter 2 inhibitors (SGLT2is) have been increasingly used in the treatment of patients with non-alcoholic fatty liver disease (NAFLD). This updated meta-analysis aimed to evaluate the efficacy and safety of SGLT2is for patients with NAFLD. METHODS: PubMed, Embase, Cochrane Library, Web of Science, Wan Fang, China National Knowledge Infrastructure and VIP databases were searched for relevant studies from inception to April 30, 2021. Values of weighted mean differences (WMDs) and risk ratios (RRs) were determined for continuous and dichotomous outcomes, respectively. RESULTS: A total of 1,498 patients with NAFLD from 20 studies were included for further analysis. Pooled analyses indicated significant improvements in body mass index [WMD: -0.84 kg/m2, 95% CI (-1.09, -0.60)], alanine aminotransferase [WMD: -4.36 U/L, 95% CI (-7.17, -1.54)], aspartate aminotransferase [WMD: -2.94 U/L, 95% CI (-5.33, -0.55)], fasting plasma glucose [WMD: -4.08 mmol/L, 95% CI (-6.21, -1.95)] and fibrosis-4 index [WMD: -0.08, 95% CI (-0.11, -0.05)] following SGLT2i treatment (p < 0.01 for all above parameters). There was no significant difference in the incidence of total adverse events between the SGLT2i group and the control group (RR = 0.78, 95% CI (0.58, 1.06), p = 0.11]. CONCLUSION: SGLT2is seem to be a promising treatment for patients with NAFLD to improve metabolic and fibrosis indexes without increasing the incidence of adverse events. Most included studies were conducted in NAFLD patients with diabetes. Therefore, the results of this meta-analysis are more applicable to the diabetic population.

Coagulation parameters may predict clinical outcomes in patients with septic acute kidney injury.

BACKGROUND: Acute kidney injury (AKI) and coagulation disorders are common complications of sepsis that affect its prognosis. However, the relationship between coagulation function and the prognosis of septic AKI has not been fully elucidated. MATERIALS AND METHODS: In this retrospective study, clinical data from patients with septic AKI admitted to the First Affiliated Hospital of Guangxi Medical University from June 2016 to March 2019 were analyzed. Based on clinical outcomes within 60 days, septic AKI patients were divided into a survival and non-survival group, and the survivors were divided into a recovered and non-recovered group depending on renal function. RESULTS: A total of 338 septic AKI patients were enrolled and followed up; 86 patients died, and 124 patients' renal function did not recover. The all-cause mortality rate in the septic AKI group was higher than in the non-AKI group by 1 : 1 propensity score matching (25.4 vs. 18.9%). The recovery rate for renal function was 50.8% (128/252), and 228 patients (67.5%) had at least one abnormal coagulation index. Logistic analysis indicated that male sex, advanced age, multiple organ dysfunction syndrome, thrombocytopenia, and an increased international standardized ratio (INR) were independent risk factors for all-cause mortality in septic AKI. Concomitant heart disease and prolonged activated partial thrombin time (APTT) were independent risk factors for renal function non-recovery among survivors. Kaplan-Meier curves showed that the cumulative survival rate was lower, and the mean survival time was shorter, in the abnormal coagulation parameter group compared to the normal coagulation parameter group (all p < 0.05). CONCLUSION: Many patients with septic AKI have a poor prognosis. Coagulation disorders, including thrombocytopenia, increased INR, and prolonged APTT might predict poor clinical outcomes in patients with septic AKI.

Development and Validation of a Prediction Model for Survival in Diabetic Patients With Acute Kidney Injury.

Objective: We aimed to analyze the risk factors affecting all-cause mortality in diabetic patients with acute kidney injury (AKI) and to develop and validate a nomogram for predicting the 90-day survival rate of patients. Methods: Clinical data of diabetic patients with AKI who were diagnosed at The First Affiliated Hospital of Guangxi Medical University from April 30, 2011, to April 30, 2021, were collected. A total of 1,042 patients were randomly divided into a development cohort and a validation cohort at a ratio of 7:3. The primary study endpoint was all-cause death within 90 days of AKI diagnosis. Clinical parameters and demographic characteristics were analyzed using Cox regression to develop a prediction model for survival in diabetic patients with AKI, and a nomogram was then constructed. The concordance index (C-index), receiver operating characteristic curve, and calibration plot were used to evaluate the prediction model. Results: The development cohort enrolled 730 patients with a median follow-up time of 87 (40-98) days, and 86 patients (11.8%) died during follow-up. The 90-day survival rate was 88.2% (644/730), and the recovery rate for renal function in survivors was 32.9% (212/644). Multivariate analysis showed that advanced age (HR = 1.064, 95% CI = 1.043-1.085), lower pulse pressure (HR = 0.964, 95% CI = 0.951-0.977), stage 3 AKI (HR = 4.803, 95% CI = 1.678-13.750), lower 25-hydroxyvitamin D3 (HR = 0.944, 95% CI = 0.930-0.960), and multiple organ dysfunction syndrome (HR = 2.056, 95% CI = 1.287-3.286) were independent risk factors affecting the all-cause death of diabetic patients with AKI (all p < 0.01). The C-indices of the prediction cohort and the validation cohort were 0.880 (95% CI = 0.839-0.921) and 0.798 (95% CI = 0.720-0.876), respectively. The calibration plot of the model showed excellent consistency between the prediction probability and the actual probability. Conclusion: We developed a new prediction model that has been internally verified to have good discrimination, calibration, and clinical value for predicting the 90-day survival rate of diabetic patients with AKI.

CMIP SNPs and their haplotypes are associated with dyslipidaemia and clinicopathologic features of IgA nephropathy.

The relationship between serum lipid profiles and related clinicopathologic features of IgA nephropathy (IgAN) and c-Maf-inducing protein (CMIP) gene polymorphisms is unclear. The present study was designed to examine the effect of CMIP single-nucleotide polymorphisms (SNPs) on dyslipidaemia and clinicopathologic features of IgAN. Clinical and pathological data from patients with IgAN diagnosed at the First Affiliated Hospital of Guangxi Medical University were collected. DNA was extracted from blood samples. CMIP rs2925979 and CMIP rs16955379 genotypes were determined by PCR and direct sequencing. Among 543 patients, 281 had dyslipidaemia (51.7%). Compared with the non-dyslipidaemia group, the dyslipidaemia group exhibited higher blood pressure, blood urea nitrogen, uric acid, and body mass index; higher prevalence of oedema, haematuria, tubular atrophy, and interstitial fibrosis; and lower albumin and estimated glomerular filtration rate. In the dyslipidaemia group, the frequency of C allele carriers was higher than that of non-C allele carriers for rs16955379. Multivariate linear regression analysis showed that total cholesterol, low-density lipoprotein and high-density lipoprotein were associated with rs16955379C allele carriers. Apolipoprotein B was associated with A allele carriers of rs2925979. Linkage disequilibrium was observed between rs16955379 and rs2925979, and rs2925979G-rs16955379T was the most common haplotype. The frequencies of the four CMIP SNP haplotypes differed between dyslipidaemia and non-dyslipidaemia groups in IgAN (P<0.05, for all above). Dyslipidaemia is a common complication in IgAN patients, and those with dyslipidaemia present poor clinicopathologic features. CMIP SNPs and their haplotypes are closely correlated with the occurrence of dyslipidaemia and clinicopathologic damage in IgAN patients.

Association between VDR gene FokI polymorphism and renal function in patients with IgA nephropathy.

BACKGROUND: Studies have shown that the occurrence and development of IgA nephropathy (IgAN) are genetically susceptible, but the relationship between vitamin D receptor (VDR) gene polymorphisms and renal function in IgAN patients is unclear. METHODS: We investigated the relationship between VDR FokI (rs2228570) single nucleotide polymorphism (SNP) and renal function and related clinicopathologic parameters in IgAN patients. Clinical and pathological data of 282 IgAN patients treated at the First Affiliated Hospital of Guangxi Medical University were collected, and FokI genotypes were determined by PCR and direct sequencing. Patients were divided into the renal dysfunction group and normal renal function (control) group by estimated glomerular filtration rate (eGFR) and serum creatinine level. RESULTS: Frequencies of TT genotype and T allele in the renal dysfunction group were higher than those of the control group. Blood urea nitrogen, serum phosphorus (P), proportions of mesangial cell proliferation, interstitial fibrosis/tubular atrophy and crescents in T allele carriers were higher than those in non-T allele carriers, while eGFR and 25-Hydroxyvitamin D3 were lower in T allele carriers than non-T allele carriers. Multiple linear regression analysis showed that eGFR was affected by FokI genotypes in IgAN patients. Logistics regression analysis showed that middle and elderly age, elevated P, intact parathyroid hormone and TT genotype were independent risk factors for renal dysfunction in IgAN patients; the odds ratio of carrying the TT genotype was as high as 84.77 (P < 0.05 for all). CONCLUSIONS: IgA nephropathy patients carrying the VDR FokI TT genotype have an increased risk of renal dysfunction. VDR FokI SNP is closely related to renal function, calcium-phosphate metabolism, and related pathological damage in IgAN patients.

Association of BDNF rs11030104 SNP and serum lipid levels in two Chinese ethnic groups.

The correlation between the BDNF rs11030104 single nucleotide polymorphism (SNP) and serum lipid levels has been understudied. The present study was conducted to detect the association of the BDNF rs11030104 SNP and several environmental factors with serum lipid levels in the Jing and Han nationalities. Genotypes of the BDNF rs11030104 SNP in 709 unrelated subjects of Han and 706 unrelated participants of Jing populations were determined by polymerase chain reaction and restriction fragment length polymorphism combined with gel electrophoresis, and further verified by direct sequencing. There was no significant difference in either genotypic or allelic frequencies between the Han and Jing populations. The genotypic and allelic frequencies of the SNP in Jing but not in Han populations were different between male and female subgroups (P<0.05 for each). The levels of serum total cholesterol (TC) and low-density lipoprotein cholesterol (LDL-C) in the Jing population were different among the genotypes, the G allele carriers had lower TC and LDL-C levels than the G allele non-carriers. Subgroup analyses showed that the differences in serum TC and LDL-C levels among the genotypes were observed in the Jing males but not in females. Serum lipid profiles were also significantly associated with some environmental factors in the Han and Jing populations, or in male and female subgroups of the two ethnic groups (P<0.05 for all). Our study exhibited a correlation between the BDNF rs11030104 SNP and serum TC and LDL-C levels in the Jing males. These results indicate that there may be a racial/ethnic- and/or sex-specific association of the BDNF rs11030104 SNP and serum lipid parameters.

The association of the CMIP rs16955379 polymorphism with dyslipidemia and the clinicopathological features of IgA nephropathy.

Immunoglobulin A nephropathy (IgAN) is among the most common primary glomerular diseases. The prognosis in IgAN is affected by dyslipidemia, a risk factor for cardiovascular disease. The c-Maf inducing protein (CMIP) gene has been found to be associated with lipid metabolism. But the association between the CMIP rs16955379 single nucleotide polymorphism (SNP) and dyslipidemia or the related clinicopathological features in IgAN have not been reported thus far. The present study investigated the correlation between them. The CMIP rs16955379 SNP genotypes of 300 subjects with IgAN recruited from the First Affiliated Hospital of Guangxi Medical University were identified by polymerase chain reaction and direct sequencing. Compared with the control (normal lipid) group, the dyslipidemia group with IgAN had higher blood uric acid, serum creatinine, blood urea nitrogen and urinary protein quantity, higher proportions of mesangial cell proliferation and renal tubular atrophy/interstitial fibrosis (IFTA), and a lower estimated glomerular filtration rate and serum albumin. The frequencies of the CMIP rs16955379 SNP TT genotype and T allele in the dyslipidemia group were higher than in the control group. Triglyceride, apolipoprotein A1 (ApoA1), ApoA1/B, incidences of mesangial cell proliferation, and IFTA were higher in TT genotype carriers than in CC/CT genotype carriers. Serum lipid profiles and dyslipidemia were significantly associated with renal dysfunction and IFTA. IgAN patients with the TT genotype were more likely to have dyslipidemia, renal dysfunction and IFTA (P < 0.05 for all above). These results indicate that CMIP rs16955379 SNP may be a genetic susceptibility gene for dyslipidemia and poor renal outcome in IgAN.

Polysaccharide Extracted from Laminaria japonica Delays Intrinsic Skin Aging in Mice.

This study aimed to determine the effect of topically applied Laminaria polysaccharide (LP) on skin aging. We applied ointment containing LP (10, 25, and 50 µg/g) or vitamin E (10 µg/g) to the dorsal skin of aging mice for 12 months and young control mice for 4 weeks. Electron microscopy analysis of skin samples revealed that LP increased dermal thickness and skin collagen content. Tissue inhibitor of metalloprotease- (TIMP-) 1 expression was upregulated while that of matrix metalloproteinase- (MMP-) 1 was downregulated in skin tissue of LP-treated as compared to untreated aging mice. Additionally, phosphorylation of c-Jun N-terminal kinase (JNK) and p38 was higher in aging skin than in young skin, while LP treatment suppressed phospho-JNK expression. LP application also enhanced the expression of antioxidative enzymes in skin tissue, causing a decrease in malondialdehyde levels and increases in superoxide dismutase, catalase, and glutathione peroxidase levels relative to those in untreated aging mice. These results indicate that LP inhibits MMP-1 expression by preventing oxidative stress and JNK phosphorylation, thereby delaying skin collagen breakdown during aging.