Chitosan oligosaccharides (COSs), depolymerized products of chitosan composed of β-(1→4) d-glucosamine units, have broad range of biological activities such as antitumour, antifungal, and antioxidant activities. In this study, peracetylated chitosan oligosaccharides (PACOs) and N-acetylated chitosan oligosaccharides (NACOs) were prepared from the COSs by chemcal modification. The structures of these monomers were identified using NMR and ESI-MS spectra. Their antagonist effects against glutamate-induced PC12 cell death were investigated. The results showed that pretreatment of PC12 cells with the PACOs markedly inhibited glutamate-induced cell death in a concentration-dependent manner. The PACOs were better glutamate antagonists compared to the COSs and the NACOs, suggesting the peracetylation is essential for the neuroprotective effects of chitosan oligosaccharides. In addition, the PACOs pretreatment significantly reduced lactate dehydrogenase release and reactive oxygen species production. It also attenuated the loss of mitochondrial membrane potential. Further studies indicated that the PACOs inhibited glutamate-induced cell death by preventing apoptosis through depressing the elevation of Bax/Bcl-2 ratio and caspase-3 activation. These results suggest that PACOs might be promising antagonists against glutamate-induced neural cell death.

Background and Aim. Redox equilibria are critical for life, but the biomarkers of redox status are currently unavailable. Gamma‐glutamyltransferase (GGT) is an essential factor for modulating redox equilibrium through glutathione. In clinical practice, increased circulating GGT activity is used as a hepatobiliary disease biomarker. However, increased circulating GGT activities have also been observed in cancers, heart disease, diabetes, hyperuricemia, inflammation, renal insufficiency, and other diseases, explained by its role in maintaining redox equilibrium inside and outside cells. Previous studies on GGT were mainly limited to one type of disease at one time. In the current study, we systematically compared the GGT levels in 44 different human diseases to test if it could serve as a redox status biomarker in blood circulation. Methods. The clinical GGT data from 168,858 patients with 44 diseases and 132,357 healthy control in the clinical laboratory of our hospital over the past five years were retrieved. All data were analyzed with SPSS, RStudio V.1.3.1073, and python libraries 3.8. Results. Thirty‐eight out of 44 diseases had significantly increased (p < 0.001) circulating GGT activities, whereas gastric cancer, anemia, renal cyst, cervical cancer, preeclampsia, and knee‐joint degenerative diseases had significantly decreased (p < 0.001) GGT activities compared to the healthy control. ROC analyses showed that GGT was an excellent biomarker for liver cancer (AUC = 0.86), pancreatitis (AUC = 0.84), or hepatic encephalopathy (AUC = 0.80). All pancreas‐related diseases had more than 8‐fold increases in GGT activity span than the healthy control, while pancreatic cancer had a 12‐fold increase (1021 U/L vs. 82 U/L). The knee‐joint degenerative disease had the lowest median and narrowest GGT activity range (63 U/L). Furthermore, most diseases’ lowest to highest GGT activities were beyond the healthy control in both directions. Conclusions. Thirty‐eight out of 44 diseases were in overall oxidative states defined by the increased GGT median values. In contrast, knee‐joint degenerative disease, gastric cancer, anemia, renal cyst, cervical cancer, and preeclampsia were in overall antioxidative states. Moreover, most diseases swing between oxidative and antioxidative states, evidenced by the increased lowest to highest GGT activity ranges than the healthy control. Liver‐ and pancreas‐related abnormalities were responsible for significantly increased GGT activities. Our overall results suggested that circulating GGT was a redox status biomarker.

Background: Lipoprotein(a) [Lp(a)] is a genetically determined cardiovascular risk factor, yet observational reports describe altered Lp(a) across many diseases, creating uncertainty about whether a single measurement remains interpretable in patients with hepatic or renal dysfunction. We tested whether disease-associated differences in Lp(a) are constitutional or dynamic.Methods: We conducted a prospective two-center study at discovery center SN (the Affiliated Hospital of Qingdao University and associated systems, Qingdao) and independent validation center HD (Honghui Hospital, Xi’an Jiaotong University, Xi’an). Fasting serum Lp(a) was linked at the blood-draw level to creatinine, total protein, and globulin across 48 disease categories and health-examination controls. eGFR was estimated by the 2021 CKD-EPI creatinine equation, and albumin was derived as total protein minus globulin. Between- and within-patient effects of renal function were separated by a Mundlak random-effects decomposition in patients with ≥2 longitudinal measurements (SN, 26,639 patients/106,295 measurements; HD, 11,573/47,695), using patient-clustered robust inference.Findings: The disease ranking of median Lp(a) replicated across centers (Spearman ρ = 0.90; 49 cohorts). The extremes were mechanistically distinct: hepatic disease suppressed Lp(a) (low albumin, normal eGFR), whereas the highest concentrations occurred in nephrotic syndrome (normal eGFR, lowest albumin; over-synthesis) and in uremia (very low eGFR; retention). Across patients, Lp(a) rose roughly 1.7- to 2-fold as eGFR fell; within the same patient over time, Lp(a) did not track changing eGFR (per 30 mL/min/1.73 m² lower eGFR: ×1.12–1.22 between-patient vs ×0.95–1.03 within-patient). Renal and hepatic biomarkers explained ≤5% of individual Lp(a) variance.Interpretation: Lp(a) disease associations are constitutional, not dynamic. A single Lp(a) measurement remains a valid genetic risk biomarker even in hepatic or renal disease, which is clinically relevant as Lp(a)-lowering therapies enter practice.