Volume 139 · Issue 19 · 2026

Mitochondria are central to cellular energy metabolism, and their functional integrity is essential for maintaining cellular homeostasis and life processes. Mitochondrial quality control (MQC) encompasses a complex network of mechanisms—including mitochondrial biogenesis, mitochondrial dynamics, mitophagy, mitochondrial proteostasis, and mitochondrial-derived vesicles—that collectively preserve the structural and functional balance of mitochondria. Recent studies have revealed that dysregulation of MQC is closely associated with a broad spectrum of diseases, such as neurodegenerative disorders, cardiovascular diseases, kidney diseases, metabolic syndrome, and cancers, highlighting its critical role in pathological processes. Despite significant progress in elucidating the molecular regulation of MQC, many aspects of its complexity and multilayered regulatory mechanisms remain unresolved. This review provides a comprehensive overview of the major molecular pathways involved in MQC and their functional alterations under physiological and pathological conditions. It emphasizes the abnormalities of MQC in various diseases and explores potential therapeutic targets. Moreover, integrating the latest research advances, this article discusses emerging treatment strategies aimed at restoring and optimizing MQC, with the goal of offering theoretical insights and clinical translation avenues for future disease prevention and management.

Regular physical activity exerts systemic metabolic benefits that are pivotal for preventing and managing metabolic diseases. These effects are mediated in part by exerkines, which are signaling molecules released from various organs in response to exercise. Exerkines encompass polypeptides, nucleic acids, and bioactive lipids that collectively orchestrate metabolic adaptations. Recent metagenomic analyses have identified the gut microbiota as an additional source of exercise-responsive factors that modulate host metabolism and may influence individual responsiveness to training. Together, these diverse exerkines coordinate interorgan communication, enhance insulin sensitivity, maintain glucose and lipid homeostasis, and modulate inflammatory pathways. This review summarizes representative exerkines from skeletal muscle, adipose tissue, and liver, including interleukin-6, myostatin, fibroblast growth factor 21, adiponectin, and growth differentiation factor 15, which have shown promising therapeutic efficacy in preclinical studies and clinical trials for complex metabolic diseases. We also discuss microbiota-derived metabolites such as short-chain fatty acids that improve glucose and lipid metabolism, as well as host-derived metabolites including N-lactoyl-phenylalanine, betaine, and β-aminoisobutyric acid that regulate appetite, substrate utilization, and insulin action. Furthermore, we highlight recent progress in understanding how dynamic regulation of these exerkines mediates the metabolic benefits of exercise and their potential as targets for precision management of metabolic diseases. Understanding these molecular mediators of exercise provides a framework for integrating physical activity with pharmacological and nutritional strategies to improve metabolic health.

In recent decades, the advent of revascularization treatments (RVTs), such as intravenous thrombolysis (IVT) and endovascular therapy, has significantly improved clinical outcomes in patients with acute ischemic stroke (AIS). However, stroke-associated pneumonia (SAP) remains a common complication that has a negative impact on the prognosis. This review addresses the mechanisms underlying the development of SAP in patients with AIS, evaluates risk factors, and discusses therapeutic and preventive measures in the era of RVTs. Despite advances in acute stroke care, the incidence of SAP remains high and comparable between IVT and endovascular treatment (EVT), although EVT may confer specific procedural risks related to prolonged mechanical ventilation, anesthesia, and intensive care unit stays. Current prevention strategies, including screening for dysphagia, oral hygiene, and immunomodulation, show promise but require further validation. Future research should focus on integrating biomarkers and imaging markers for early prediction of SAP and developing targeted interventions to improve patient outcomes.

Background: Colorectal cancer (CRC) is among the most prevalent malignancies, with an increasing incidence in China, posing increasing challenges to current screening strategies. This study aimed to evaluate the feasibility of a screening strategy based on the stool-based methylated Syndecan-2 gene (mSDC2) test for detecting advanced colorectal neoplasia in the Chinese population. Methods: In this multicenter randomized study, participants aged 45-80 years and identified through community screening were randomized to take either the mSDC2 test or a fecal immunochemical test (FIT), and those with positive results were referred for colonoscopy between 2020 and 2022. The primary outcome was the detection rate of advanced colorectal neoplasia, including advanced adenoma, advanced serrated polyps, and CRC. The secondary outcome was adherence to colonoscopy. Univariable and multivariable logistic regression analyses were conducted to evaluate colonoscopy adherence among participants with positive stool-based test results. Results: A total of 44,475 eligible participants were enrolled from 189 communities (93 in the mSDC2 test group and 96 in the FIT group). In the mSDC2 test group (n = 21,854), the detection rate of advanced neoplasia was 0.53% (n = 115), including 93 (0.43%) advanced adenomas, 8 (0.04%) advanced serrated polyps, and 17 (0.08%) CRC cases. In the FIT group (n = 22,621), the detection rate of advanced neoplasia was 0.47% (n = 106), including 71 (0.31%) advanced adenomas, 9 (0.04%) advanced serrated polyps, and 29 (0.13%) CRC cases. In addition, adherence to colonoscopy was greater in the mSDC2 test group (35.6% vs. 26.4%; odds ratio: 1.59, 95% confidence interval: 1.36-1.87; P <0.001). Conclusions: This study revealed the effectiveness of the mSDC2 test and FIT in detecting advanced colorectal neoplasia in a large Chinese population in a real-world setting, and indicated a possible improvement in adherence to colonoscopy for the mSDC2 test. Further studies with improved comparability and longer follow-up are warranted to clarify its clinical utility.

Background: Serum uric acid (SUA) has been implicated in various inflammatory conditions, yet its association with inflammatory proteins and treatment outcomes in psoriasis remains unclear. This study aimed to investigate the association of SUA levels with specific circulating inflammatory proteins and treatment response to ixekizumab, a monoclonal antibody against interleukin-17A, in patients with moderate-to-severe psoriasis. Methods: Patients attending 26 dermatology centers across China were recruited into this real-world prospective cohort study conducted between August 2020 and May 2022. The SUA levels of the participants were measured to assess hyperuricemia, and treatment response was evaluated using the Psoriasis Area and Severity Index (PASI). All participants received ixekizumab at a dose of 160 mg at week 0, followed by 80 mg every 2 weeks through week 12. Adjusted logistic regression analysis was used to explore differences in treatment response between patients with and without hyperuricemia. The restricted cubic spline (RCS) was employed to explore the continuous relationship between SUA and the response outcomes. Specifically, we measured 92 circulating plasma inflammatory markers using the Olink Proteomics. Results: A total of 390 patients with psoriasis were included in the study. The psoriasis patients with hyperuricemia demonstrated a higher prevalence of obesity, hyperlipidemia, and hyperglycemia compared with those without hyperuricemia. After 12 weeks of ixekizumab treatment, patients with hyperuricemia exhibited a lower likelihood of achieving PASI 75 (adjusted odds ratio [aOR] 0.84, 95% confidence interval [CI] 0.69-0.99), PASI 90 (aOR 0.37, 95% CI 0.15-0.62), and PASI 100 (aOR 0.57, 95% CI 0.37-0.91). Olink Proteomics identified significant correlations between SUA concentration and the levels of 26 circulating inflammatory proteins, and pathway analysis showed enrichment of pathways such as response to tumor necrosis factor (TNF), lymphocyte activation, and cytokine activity. Conclusion: Elevated SUA levels can hinder the effectiveness of ixekizumab and positively correlate with specific circulating inflammatory proteins in patients with psoriasis, emphasizing the need for further investigation and consideration of metabolic factors in psoriasis management strategies.

Background: The cognitive-enhancing effects of dietary lecithin are gaining increasing attention, but evidence supporting these claims remains limited. This study aims to explore the relationship between dietary lecithin intake and cognitive function, as well as the prevalence of mild cognitive impairment (MCI), in adults aged over 60 years. Methods: This cross-sectional study included participants aged over 60 years recruited from Beijing, Jincheng City (Shanxi Province), and Linyi City (Shandong Province) from 2020 to 2023. Cognitive function and dietary intake were assessed using neuropsychological tests and a food frequency questionnaire, respectively. Body composition was measured by bioelectrical impedance analysis, and blood lipids by an automated biochemistry analyzer. Spearman correlation analysis, multiple linear regression, logistic regression, and receiver operating characteristic (ROC) curve analysis were performed. Results: Among the 1917 participants enrolled, 1023 (1023/1917, 53.4%) had MCI, of whom 542 (542/1023, 53.0%) were women. Multiple linear regression showed that after dichotomizing lecithin and serum cholesterol indicators according to the median, high levels of dietary lecithin, total cholesterol (TC), and high-density lipoprotein cholesterol (HDL-C) were associated with higher Montreal Cognitive Assessment (MoCA, regression coefficients were 0.49, 0.44, and 0.38, respectively); logistic regression showed that, compared with low intake level, the odds ratio (95% confidence interval [CI]) of MCI in high dietary lecithin intake group was 0.80 (95% CI: 0.64, 0.99). ROC analysis of a model incorporating dietary lecithin, energy intake, demographic, and clinical characteristics yielded an area under the curve (AUC) of 0.735 (95% CI: 0.713-0.757). Targeted lipidomic analysis revealed that the MCI group exhibited a lower total phosphatidylcholine (PC) level, a reduced proportion of PC containing polyunsaturated fatty acid (PUFA), and a higher proportion of PC containing saturated fatty acid (SFA). Conclusion: Higher dietary lecithin intake was associated with better cognitive performance and a lower prevalence of MCI among the elderly population aged 60 and above.

Background: Programmed death-ligand 1 (PD-L1) expression and CD8-positive (CD8+) T-cell infiltration in tumor tissue are associated with prognosis in non-small cell lung cancer (NSCLC). However, the prognostic value of combined PD-L1/CD8 immune phenotyping in surgically treated NSCLC and the feasibility of predicting high-risk immune phenotypes using routine clinical indicators remain unclear. This study aimed to evaluate the prognostic significance of PD-L1/CD8 status and to develop machine learning models for predicting PD-L1-positive/CD8-negative (PD-L1+ CD8-) status. Methods: This study included 844 patients with NSCLC who underwent surgical resection at Wuhan Union Hospital and Renmin Hospital of Wuhan University between March 2012 and November 2022. PD-L1 expression and CD8+ T-cell infiltration were assessed by immunohistochemistry, and preoperative clinical data were collected. Kaplan-Meier analysis, stratified survival analysis, univariable and multivariable Cox proportional hazards regression models were used to evaluate the association between PD-L1/CD8 status and overall survival (OS). Patients from Wuhan Union Hospital were divided into training, test, and internal validation sets, whereas patients from Renmin Hospital of Wuhan University were used as an external validation set. Multiple machine learning models were developed to predict PD-L1+ CD8- status. Feature importance and SHapley Additive exPlanations (SHAP) analysis were used to interpret model predictions. Results: Based on PD-L1/CD8 status, tumors from the 844 patients were classified into four immune phenotypes. Kaplan-Meier analyses revealed significant differences in OS among the four PD-L1/CD8 subgroups, with the PD-L1+ CD8- subgroup displaying the poorest survival. This pattern was also observed in several stratified analyses. Multivariable Cox regression analysis further demonstrated that PD-L1+ CD8- status was independently associated with worse OS compared with PD-L1+ CD8+ status (hazard ratio = 3.261, 95% confidence interval: 1.310-8.116, P = 0.011). On this basis, machine learning models were developed to predict PD-L1+ CD8- status. Among the evaluated models, the stacking model showed the best overall performance, with area under the curve values of 0.998, 0.700, 0.853, and 0.783 in the training, test, internal validation, and external validation sets, respectively. Feature importance and SHAP analyses suggested that PD-L1+ CD8- status was associated with a composite pattern involving hematologic, biochemical, inflammatory, and coagulation-related indicators. Conclusions: PD-L1/CD8-based phenotyping identified prognostically distinct subgroups in surgically treated NSCLC, with PD-L1+ CD8- status defining a high-risk phenotype associated with poor survival. A machine learning model based on clinical indicators may enable efficient, noninvasive identification of PD-L1+ CD8- status and help guide treatment decisions.

Background: Prospective real-world data on poly(adenosine diphosphate-ribose [ADP]-ribose) polymerase inhibitors (PARPi) as first-line maintenance therapy (1LMT) for ovarian cancer are limited. This study was conducted to evaluate the treatment patterns, efficacy, and safety of niraparib as 1LMT in Chinese patients with ovarian cancer. Methods: This was a prospective, multicenter, noninterventional, real-world study evaluating niraparib as 1LMT in newly diagnosed ovarian cancer. The primary endpoint was treatment patterns. Secondary endpoints included progression-free survival (PFS), chemotherapy-free interval (CFI), time to first subsequent treatment (TFST), overall survival (OS), safety, and quality of life (QoL). Results: A total of 227 patients were enrolled. The median time to maintenance initiation was 7.4 weeks. Most patients (218/227, 96.0%) received niraparib monotherapy; 95.6% (n = 217) started at 200 mg daily, and 73.6% (n = 167) maintained a stable 200 mg dose. After a median follow-up of 41.5 months, the median PFS was 36.5 months in the intention-to-treat (ITT) population and 25.4 months in patients with The International Federation of Gynecology and Obstetrics (FIGO) stage III-IV disease. Median PFS was not reached (NR) in the BRCA1/2-mutated and homologous recombination deficiency (HRD) positive subgroups, and it was 25.4 and 22.2 months in the BRCA1/2 wild-type and HRD-proficient subgroups, respectively. PFS rates at 36 months were 67.5% in the BRCA1/2-mutated, 58.7% in the HRD-positive, and 50.1% in the ITT population. Median CFI, TFST, and OS were NR; OS rate at 36 months was 80.2%. Factors associated with longer PFS included R0 resection, primary debulking surgery, complete response after chemotherapy, BRCA1/2 mutation, and HRD positivity. No new safety concerns were identified, and QoL remained stable. Conclusion: As the prospective real-world study of niraparib 1LMT in China, it provides powerful complementary evidence to pivotal randomized controlled trials conducted in highly selective populations, further supporting niraparib as the first-line maintenance standard treatment.

Background: Diabetic nephropathy (DN) is the leading cause of end-stage renal disease. The retinal microvasculature, as the only directly observable microvasculature, may reflect DN progression. This study aims to construct a non-invasive diagnostic and prognostic prediction model using the mixed effects of retinal vascular geometric parameters and clinical data. Methods: We constructed a multimodal database including 397 patients with type 2 diabetes and chronic kidney disease from multiple centers in China. The primary cohort (374 patients) was recruited from the Department of Nephrology at the First Medical Center of the Chinese People’s Liberation Army General Hospital in Beijing between 2017 and 2022, while an external validation cohort (23 patients) was collected from five other hospitals across China from September 2022 to March 2023. Fundus images, clinical characteristics, renal biopsy diagnoses, and follow-up data were collected. Unsupervised learning and Resnet neural networks were used to segment and calculate retinal vascular geometric parameters. Weighted quantile regression (WQS), Lasso, and COX univariable regressions were employed to assess the mixed effects of retinal vascular geometric parameters and select relevant clinical characteristics. Logistic regression and Cox regression with random forest (COX-RF) were used for model construction. Results: A multimodal database of 397 patients was constructed. A diagnostic model combining retinal parameters (WQS-diagnosis) and seven clinical characteristics achieved superior performance: AUC 0.98, accuracy 0.92 on the test set, outperforming models using only clinical data (AUC 0.93) or two retinal parameters plus clinical data (AUC 0.94). On the multi-centre validation set, the model maintained accuracy 0.91 and AUC 0.95. For prognosis, a mixed-effects parameter (WQS-prognosis) was derived; the COX-RF model achieved an AUC of 0.88. Conclusions: Retinal microvasculature are effective biomarkers for DN. The proposed non-invasive model demonstrated high accuracy and generalizability, offering a valuable tool for optimising DN management.