First Affiliated Hospital of Dalian Medical University

To compare two region-of-interest (ROI) measurement methods based on mDIXON-Quant for distinguishing healthy volunteers (HV), chronic kidney disease (CKD) patients with low (≤ 15%) and high (> 15%) glomerulosclerosis (GS), and establish a non-invasive auxiliary protocol. A total of 42 CKD patients and 25 HV underwent mDIXON-Quant MRI. CKD patients were stratified into low (n = 24) and high (n = 18) GS groups via renal biopsy. Two ROI methods were applied: Method 1 (cortex/medulla separation, 15–20 mm² circular ROIs at renal hilum, upper/lower poles) and Method 2 (whole-kidney contour tracing). R2* and fat fraction (FF) parameters were analyzed using ANOVA, LSD tests, and DeLong tests for diagnostic efficacy (AUC). R2* parameters (RcR2*, RR2*) showed significant differences across groups (P < 0.05), increasing with GS severity. LcR2* and RmR2* distinguished HV from high GS (P < 0.05), while LFF differentiated low vs. high GS (P < 0.05). Combining FF with R2* improved AUC from 0.685 to 0.877 (P < 0.05) for low/high GS discrimination. Method 1’s RcR2* (AUC = 0.957) and Method 2’s RR2* (AUC = 0.9) were most accurate for distinguishing high GS from HV, with no significant difference between them (P > 0.05). RcR2* outperformed medullary parameters (P < 0.05). The present study demonstrates that employing the Method 2(whole-kidney contour tracing) based on mDIXON-Quant technology enables auxiliary quantitative assessment of the severity of GS via the R2 parameter of the right kidney, thereby confirming its role as an adjunctive tool in GS evaluation.

By systematically reviewing existing studies on the sense of coherence (SOC) in patients with Parkinson's disease (PD), this paper summarizes the current research status and analyzes major influencing factors associated with SOC in this population. Parkinson's disease is characterized by progressive motor dysfunction accompanied by complex psychological and social challenges, which significantly impair patients’ adaptive capacity and quality of life. As a core psychological construct derived from the salutogenic model, sense of coherence represents an individual's ability to comprehend, manage, and assign meaning to stressful life events. Increasing evidence suggests that SOC plays a crucial protective role in psychological adjustment, disease coping, and health behavior maintenance among patients with chronic illnesses. This review integrates domestic and international findings to clarify the multidimensional determinants of SOC in PD patients, including social support, educational level, disease severity, psychological status, exercise participation, and adaptive capacity. Furthermore, the clinical implications of strengthening SOC through nursing interventions are discussed. The study aims to provide theoretical support for developing targeted psychosocial and nursing strategies to enhance psychological resilience, promote self-management ability, and ultimately improve quality of life in patients with Parkinson's disease.

Neurodegenerative diseases (NDDs), including Alzheimer's disease (AD), Parkinson's disease (PD), multiple system atrophy (MSA), amyotrophic lateral sclerosis (ALS), and others, represent an escalating public health burden in aging populations. NDDs are characterized by progressive neuronal loss and misfolded protein aggregation. Despite distinct clinical heterogeneity, these diseases universally present with debilitating non-motor symptoms, among which sleep-wake disorders are highly prevalent. Once considered secondary to neuronal damage, growing evidence now highlights a bidirectional interplay: sleep disruption is not only a consequence of neurodegeneration but also exacerbates its progression. This review synthesizes this complex interplay, outlining sleep phenotypes across major NDDs, dissecting key underlying mechanisms (impaired protein homeostasis, glymphatic dysfunction, chronic neuroinflammation, sleep-regulatory nucleus vulnerability, and circadian dysregulation), and summarizing current pharmacotherapeutic and non-pharmacological interventions. Attenuating sleep disorders may therefore provide symptomatic relief and disease‑modifying effects for NDDs.

Based on multiscale computed tomography (CT) radiomics, a better model was established to differentially diagnose benign lesions and lung adenocarcinoma of Lung-RADS 2022 category 4B solid lung nodules. The retrospective study included 178 patients with solid pulmonary nodules were assigned to the training dataset (n = 124) and the testing dataset (n = 54). Gradient boosting decision tree (GBDT) was used to reduce the dimensionality of data and select the best radiomics features. Four models were developed by logistic regression method, namely the clinical and imaging model (CIM), the plain CT radiomics model (PRM), the enhanced CT radiomics model (ERM), and the combined model (CM). Area under the curve (AUC) evaluates the model performance. Net reclassification improvement (NRI) and the integrated discrimination index (IDI) were calculated to compare the performance of different models to determine the best model. In the training dataset, the AUC of CIM, PRM, ERM, and CM were 0.795, 0.791, 0.828, and 0.888. The continuous NRI and IDI of CM was better than that of CIM, PRM, ERM (P < 0.001), CM is optimal. In the testing dataset, the AUC of CIM, PRM, ERM and CM were 0.810, 0.689, 0.864 and 0.881. The continuous NRI of CM was better than that of CIM, PRM, ERM (P < 0.050). The IDI of CM was better than that of CIM and PRM (P < 0.050). The AUC values of the Mayo Clinic (Mayo) model, Veterans Administration (VA) model, Peking University People’s Hospital (PKUPH) model and United Imaging Artificial Intelligence (UI AI) model were 0.419, 0.410, 0.676 and 0.675, CM is still optimal. Radiomics can be used as a non-invasive tool to distinguish between benign lesions and lung adenocarcinoma of Lung-RADS 2022 category 4B solid lung nodules, and CM is the best predictive model.

Study DesignRetrospective cohort study.ObjectiveTo establish a novel lumbar subcutaneous adipose classification (LSAC) based on sagittal MRI and determine its predictive value for surgical site infection (SSI) and postoperative adverse events (PAE) following posterior lumbar fusion.MethodsA retrospective analysis of 1122 patients undergoing posterior lumbar interbody fusion was performed. Lumbar subcutaneous adipose distribution at the L3 endplate level was categorized into five types (Low, Cranial, Caudal, Cranial-Caudal, and Diffuse). Surgical segment subcutaneous fat thickness (SFT), facet joint to lumbar dorsal fascia distance (FJ-LDF), paraspinal muscle cross-sectional area, paraspinal muscle fat infiltration, and Modic changes were assessed. Associations between LSAC and SSI/PAE were examined using multivariate logistic regression.ResultsLSAC demonstrated excellent inter- and intra-observer reliability. Significant differences in patient characteristics were observed among the five types, with type 5 and type 2 showing higher BMI, diabetes and spondylolisthesis rate. SSI and PAE incidence were highest in type 5, followed by type 2. Multivariate analyses identified LSAC (OR 1.534, P = 0.007), BMI (OR 1.156, P = 0.010), transfusion (OR 1.002, P < 0.001), and smoking (OR 2.646, P = 0.035) as independent predictors of SSI; and LSAC (OR 1.477, P = 0.002), age (OR 1.037, P = 0.016), smoking (OR 2.607, P = 0.007), and higher drainage volume (OR 1.001, P < 0.001) as predictors of PAE. ROC curve demonstrated that LSAC was more sensitive than BMI and SFT to predict the SSI and PAE.ConclusionThe LSAC system provides a simple, reproducible method for quantifying lumbar subcutaneous fat distribution and outperforms traditional single adiposity indices such as BMI or SFT in predicting postoperative complications. Type 5 and type 2 represent high-risk phenotypes requiring enhanced perioperative optimization and surveillance.

To the Editor, I read with great interest the study by Wang et al titled “Deciphering pathogenic mechanisms of BDCPP exposure in endometrial cancer progression via an integrated approach combining network toxicology, machine learning, and molecular docking” recently published in the International Journal of Surgery, which elucidates the pathogenic mechanisms by which bis(1,3-dichloro-2-propyl) phosphate (BDCPP) exposure promotes endometrial cancer (EC) progression[1]. The authors have utilized a robust multi-omics approach to identify ESR1 and VEGFA as central nodes in BDCPP-induced malignancy. This research is timely, as it bridges environmental toxicology with surgical oncology, yet several points regarding its clinical translation for surgeons warrant further discussion. The identification of BDCPP as an environmental driver of EC has significant implications for postoperative risk stratification. In current surgical practice, prognosis is largely determined by FIGO staging and histological grading. However, findings by Wang et al suggest that environmental exposure history could be a hidden variable. For patients undergoing hysterectomy, it would be insightful to investigate whether high systemic levels of BDCPP correlate with lymphovascular space invasion or occult lymph node metastasis, as environmental endocrine disruptors have been linked to increased invasiveness in other hormone-dependent tumors[2]. If such a correlation exists, BDCPP levels could potentially help surgeons decide between radical versus fertility-sparing surgery. The study highlights ESR1 as a primary target. Since endocrine therapy is a cornerstone for many EC patients, particularly those desiring fertility preservation, the interference of environmental disruptors with estrogen receptor signaling is concerning. Recent evidence suggests that exposure to organophosphate flame retardants can alter the therapeutic efficacy of hormonal agents[3]. Clarifying whether patients with high BDCPP exposure require escalated hormonal treatment or adjuvant anti-VEGF therapy (targeting the identified VEGFA node) would be a valuable step toward personalized management. While molecular docking provided insights into the BDCPP-ESR1 interaction, the spatial toxicological effect within the uterine microenvironment remains unexplored. We suggest that future studies employ spatial transcriptomics to visualize the recruitment of angiogenic factors at the tumor-stroma interface[4]. This would provide surgeons with a “molecular map” of how environmental toxins reshape the surgical landscape. Conclusion In summary, Wang et al provide a compelling roadmap for understanding how ubiquitous pollutants fuel EC progression. Integrating toxicological data into clinical surgical frameworks will undoubtedly enhance our ability to predict recurrence and tailor treatment for EC patients.

Germline pathogenic alleles predispose carriers to malignancies; failure to recognize the underlying cancer susceptibility and subsequent delayed diagnosis may lead to severe health impairment. It remains largely undetermined what the somatic mutation characteristics are in colorectal cancer (CRC) patients with pathogenic/likely pathogenic (P/LP) germline mutations and whether, and how, these germline mutations typically located in non-mismatch repair genes, are associated with CRC tumorigenesis. From 8,676 Chinese patients with CRC, we initially screened those who had undergone both germline and somatic mutation testing. We analyzed the relationship between germline mutations and the somatic mutational landscape in this cohort. Germline alterations were examined with a 556- or 105- gene next-generation sequencing panel, and somatic alterations were examined with a 556-gene panel. Overall, 80 CRC patients were identified as carriers of P/LP germline mutations. After excluding 6 patients lacking somatic mutation testing data, 74 patients with P/LP germline mutations and 100 patients without germline mutations were finally enrolled in this study. Twenty-one germline genes were detected in the 74 patients. Compared with patients without P/LP mutations (non-P group), those in the P/LP mutations (P group) had significantly lower age and a higher ratio of microsatellite instability. Patients harboring P/LP germline mutations in MMR genes (P-MMR) were significantly younger and more frequently exhibited high tumor mutational burden. The most frequent somatic variations were KRAS and TP53. The somatic mutational landscape revealed a significantly higher mutational frequency in the P group than in the non-P group, and in the P-MMR group than in the P-non-MMR group. The MAPK pathway was significantly enriched in the P and P-MMR groups. Our data showed lower mutation rate of MSH2 among all MMR genes than in the Western population. Population-based risk analysis indicated that the odds ratio of BRCA2 and ATM mutations exceeded 10. Our findings offer a comprehensive overview of genetic susceptibility in Chinese CRC, which may help to shape a more comprehensive understanding of genetic structure of CRC and generate accurate individualized risk management strategies for mutation carriers.