Receiver Operating Characteristic Analysis Research Articles

Revealing the potential therapeutic mechanism of Lonicerae Japonicae Flos in Alzheimer’s disease: a computational biology approach

BackgroundAlzheimer’s disease (AD) is a degenerative brain disease without a cure. Lonicerae Japonicae Flos (LJF), a traditional Chinese herbal medicine, possesses a neuroprotective effect, but its mechanisms for AD are not well understood. This study aimed to investigate potential targets and constituents of LJF against AD.MethodsNetwork pharmacology and bioinformatics analyses were performed to screen potential compounds and targets. Gene Expression Omnibus (GEO) datasets related to AD patients were used to screen core targets of differential expression. Gene expression profiling interactive analysis (GEPIA) was used to validate the correlation between core target genes and major causative genes of AD. The receiver operating characteristic (ROC) analysis was used to evaluate the predictive efficacy of core targets based on GEO datasets. Molecular docking and dynamics simulation were conducted to analyze the binding affinities of effective compounds with core targets.ResultsNetwork pharmacology analysis showed that 112 intersection targets were identified. Bioinformatics analysis displayed that 32 putative core targets were identified from 112 intersection targets. Only eight core targets were differentially expressed based on GEO datasets. Finally, six core targets of MAPK8, CTNNB1, NFKB1, EGFR, BCL2, and NFE2L2 were related to AD progression and had good predictive ability based on correlation and ROC analyses. Molecular docking and dynamics simulation analyses elucidated that the component of lignan interacted with EGFR, the component of β-carotene interacted with CTNNB1 and BCL2, the component of β-sitosterol interacted with BCL2, the component of hederagenin interacted with NFKB1, the component of berberine interacted with EGFR and BCL2, and the component of baicalein interacted with NFKB1, EGFR and BCL2.ConclusionThrough a comprehensive analysis, this study revealed that six core targets (MAPK8, CTNNB1, NFKB1, EGFR, BCL2, and NFE2L2) and six practical components (lignan, β-carotene, β-sitosterol, hederagenin, berberine, and baicalein) were involved in the mechanism of action of LJF against AD. Our work demonstrated that LJF effectively treats AD through its multi-component and multi-target properties. The findings of this study will establish a theoretical basis for the expanded application of LJF in AD treatment and, hopefully, can guide more advanced experimental research in the future.

The Impact of Systemic Inflammation on Recurrence in Patients with Congenital Nasolacrimal Duct Obstruction

Background/Objective: Congenital nasolacrimal duct obstruction (CNLDO) is commonly treated by probing, but recurrence remains a clinical issue. This study investigates the potential role of inflammatory biomarkers, such as the neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), and platelet-to-lymphocyte ratio (PLR), in predicting recurrence after probing in children with CNLDO. Methods: This retrospective cohort study included 172 patients who underwent initial probing for unilateral CNLDO. The patients were then categorized into two groups: those who experienced the complete resolution of symptoms after primary probing, and those who required Ritleng tube intubation due to recurrence following primary probing. Blood samples for calculating inflammatory biomarkers in all subjects were collected during general anesthesia preparation prior to initial probing. NLR, MLR, and PLR values were compared between the groups using the independent samples t-test. The predictive performance of the inflammatory biomarkers for recurrence was assessed using Receiver Operating Characteristic (ROC) curve analysis. Results: A total of 110 patients were included in the probing group, while 62 patients were in the recurrence group. The mean age at the time of the initial probing procedure was 15 ± 4.06 months in the probing group and 15.83 ± 4.02 months in the recurrence group. There was no difference in the duration of the probing procedure between the groups. The mean age at the time of Ritleng tube intubation in the recurrence group was 37.80 ± 13.34 months. The recurrence group exhibited significantly higher values in all analyzed inflammatory markers compared to the probing group, including the NLR (1.12 ± 0.56 vs. 0.86 ± 0.39, p = 0.002), MLR (0.16 ± 0.06 vs. 0.14 ± 0.06, p = 0.005), and PLR (95.13 ± 24.34 vs. 82.23 ± 22.77, p < 0.001). ROC curve analysis indicated that these inflammatory biomarkers demonstrated moderate performance in predicting recurrence. Conclusions: Recurrence following probing in children with CNLDO was associated with complete blood cell count-derived inflammatory biomarkers. The preoperative assessment of these biomarkers may aid in the individualization of disease management and inform the development of new therapeutic strategies.

Association between nutritional status, injury severity, and physiological responses in trauma patients

PurposeTo evaluate the predictive value of the Controlling Nutritional Status (CONUT) score and Injury Severity Score (ISS) in assessing physiological abnormalities and outcomes in trauma patients.MethodsA retrospective analysis was conducted on 354 trauma patients. Physiological parameters were assessed, including cardiovascular function, inflammatory response, liver and kidney function, and nutritional status. The CONUT score and ISS were calculated for each patient. Binary logistic regression was used to identify independent predictors of trauma severity. Receiver operating characteristic (ROC) curve analysis evaluated the predictive accuracy of the CONUT and ISS scores for adverse outcomes.ResultsSeverely injured patients exhibited more significant abnormalities in cardiovascular function, inflammatory response, liver and kidney function, and nutritional status compared to those with minor injuries. These patients had significantly higher CONUT scores. Logistic regression analysis identified white blood cell count, hemoglobin, and CONUT score as independent predictors of trauma severity. ROC analysis showed that both CONUT and ISS scores effectively predicted adverse outcomes, with ISS demonstrating better specificity.ConclusionThe CONUT and ISS scores are effective tools for predicting physiological abnormalities and adverse outcomes in trauma patients. Incorporating these scores into clinical practice may enhance prognostic assessments and improve management strategies for trauma patients.

Abstract 4136597: Atherosclerotic plaque healing as a marker of plaque vulnerability: Insight from intracoronary polarization-sensitive optical frequency domain imaging

Background: Collagen is the major extracellular matrix that imparts mechanical strength to fibrous caps covering fibroatheromas. Intracoronary polarimetry with polarization-sensitive (PS) optical frequency domain imaging (OFDI) measures polarization properties, such as birefringence and depolarization (Figure 1). Birefringence is elevated in collagen and collagen-synthesizing smooth muscle cells, while depolarization is increased by the presence of macrophages and lipid/necrotic cores. Purpose: This study aimed to investigate polarimetric signatures of coronary lesions with healed coronary plaques (HCP) in patients with ACS and chronic coronary syndrome (CCS). Furthermore, we aimed to investigate diagnostic value for birefringence and depolarization of ACS culprit lesions discriminating from CCS target lesions. Methods: We conducted a single center prospective registry of intracoronary PS-OFDI imaging in patients with coronary artery disease (n = 50). A total of 862 OFDI frames selected from culprit or target lesions were analyzed. Coronary plaque phenotypes were assessed using conventional OFDI imaging. HCP was defined as plaques with one or more layers of different optical density and a clear demarcation from underlying components on intensity images. Birefringence and depolarization of the newer intima was measured in cross-sectional images. Birefringence and depolarization of ACS- and CCS-lesions were compared using a generalized estimating equation model. Receiver operating characteristic (ROC) analysis was used to investigate the diagnostic performance of polarimetric signatures for identifying ACS-lesions. Results: Compared to CCS-lesions, ACS-lesions featured significantly higher lipid-burden index and maximum lipid arc (both p < 0.05). Compared to the CCS-lesions, ACS-lesions exhibited significantly lower birefringence (p < 0.05) and higher depolarization (p < 0.05). In the ROC analysis for differentiating ACS-lesions from CCS-lesions, area under the curves (AUC) for birefringence and depolarization were 0.712 and 0.672, respectively. In the multivariable ROC analysis in diagnosing ACS lesions, combination of birefringence with depolarization improved the AUC to 0.755 (p ＝ 0.025). Conclusions: Intracoronary polarimetry provides quantitative assessment of plaque composition in patients. Further research is warranted to investigate whether birefringence can serve as a marker of healing failure following plaque rupture and erosion.

Feature genes identification and immune infiltration assessment in abdominal aortic aneurysm using WGCNA and machine learning algorithms

ObjectiveAbdominal aortic aneurysm (AAA) is a life-threatening vascular condition. This study aimed to discover new indicators for the early detection of AAA and explore the possible involvement of immune cell activity in its development.MethodsSourced from the Gene Expression Omnibus, the AAA microarray datasets GSE47472 and GSE57691 were combined to generate the training set. Additionally, a separate dataset (GSE7084) was designated as the validation set. Enrichment analyses were carried out to explore the underlying biological mechanisms using Disease Ontology, Kyoto Encyclopedia of Genes and Genomes, and Gene Ontology. We then utilized weighted gene co-expression network analysis (WGCNA) along with 3 machine learning techniques: least absolute shrinkage and selection operator, support vector machine-recursive feature elimination, and random forest, to identify feature genes for AAA. Moreover, data were validated using the receiver operating characteristic (ROC) curve, with feature genes defined as those having an area under the curve above 85% and a p-value below 0.05. Finally, the single sample gene set enrichment analysis algorithm was applied to probe the immune landscape in AAA and its connection to the selected feature genes.ResultsWe discovered 72 differentially expressed genes (DEGs) when comparing healthy and AAA samples, including 36 upregulated and 36 downregulated genes. Functional enrichment analysis revealed that the DEGs associated with AAA are primarily involved in inflammatory regulation and immune response. By intersecting the result of 3 machine learning algorithms and WGCNA, 3 feature genes were identified, including MRAP2, PPP1R14A, and PLN genes. The diagnostic performance of all these genes was strong, as revealed by the ROC analysis. A significant increase in 15 immune cell types in AAA samples was observed, based on the analysis of immune cell infiltration. In addition, the 3 feature genes show a strong linkage with different types of immune cells.ConclusionThree feature genes (MRAP2, PPP1R14A, and PLN) related to the development of AAA were identified. These genes are linked to immune cell activity and the inflammatory microenvironment, providing potential biomarkers for early detection and a basis for further research into AAA progression.

Abstract 4138237: Clinical Utility of T2 Mapping for the Assessment of Myocardial Inflammation in Patients With Cardiac Sarcoidosis

Introduction: 18 F-FDG PET has been used for the evaluation of active inflammatory lesions in cardiac sarcoidosis (CS), but it is burdensome for patients to perform as a routine follow-up. Late gadolinium enhancement (LGE) on cardiac magnetic resonance (CMR) that can detect myocardial fibrosis is limited in its ability to assess active inflammation. T2 mapping has been shown to detect myocardial inflammation in myocardial diseases without radiation exposure and contrast agents (Figure). However, the ability of T2 mapping for discriminating inflammatory myocardium has not been fully clarified in patients with CS. Hypothesis: We assessed the hypothesis that T2 mapping has potential for the discrimination of inflammatory myocardium in patients with CS. Methods: Twenty-seven subjects who underwent CMR at 3T and 18 F-FDG PET to diagnose CS were enrolled. Fourteen subjects were diagnosed as CS due to LGE and myocardial FDG uptake on 18 F-FDG PET (PET-positive group). Thirteen subjects showed no myocardial FDG uptake (PET-negative group). NativeT1, T2, and extracellular volume fraction (ECV) were measured using a 16-segment model. Receiver-operating characteristic (ROC) curve analysis was performed to evaluate T1 and T2 mapping in discriminating between active and inactive inflammatory segments in the PET-positive group. Results: Mean native T1, native T2 and ECV showed no significant differences between the PET-positive and the PET-negative groups. However, maximum T2 values, which were highest ones in the 16 segments, were significantly higher in the PET-positive group than the PET-negative group (51.3 ± 7.7 ms vs 45.7 ± 3.6 ms, p = 0.014). In the PET-positive group, ROC analysis showed AUC of 0.72 in native T2, 0.61 in native T1, and 0.68 in ECV for discriminating inflammatory myocardium. The optimal cutoff value of native T2 was 45.7 ms, and the diagnostic performance had a sensitivity of 44.4 %, specificity of 93.3 % , positive predictive value of 88.1 %, and negative predictive value of 60.1 %. Conclusion: T2 mapping is a promising approach for the discrimination of inflammatory myocardium without radiation exposure and contrast agents in patients with cardiac sarcoidosis.

Early dFLC response by C1D7 predicts complete hematologic response in systemic AL amyloidosis

AbstractDaratumumab and bortezomib, the first-line drugs for AL amyloidosis, typically yield a complete hematologic response (CHR) rate of nearly 60% when used in combinations. An early achievement of CHR is crucial in amyloidosis. We retrospectively evaluated the relationship between dFLC (the difference between free light chain) reduction by Day 7 in Cycle 1 (C1D7) and CHR, organ response, and survival in 48 newly diagnosed AL amyloidosis patients receiving daratumumab, bortezomib, and dexamethasone. The CHR rate within six months was 66.7%. Using Receiver Operating Characteristic Curve curve analysis, we predicted CHR based on a dFLC reduction in C1D7 (67.0% change, optimal sensitivity 87.5%, specificity 81.3%). We introduce the novel concept of “rapid hematologic dFLC response”, defined as a reduction in dFLC levels ≥ 67% in C1D7. The CHR rate in rapid responders’ groups was higher than that in slow responders’ group (90.3% vs. 23.5%, P<0.01). After a median follow-up of 19 months (range: 0.3–57), the renal response rate in rapid responders was higher than that in slow responders (72.0% vs. 27.5%, P = 0.025). The median major organ deterioration event-free survival in the rapid responders’ group (not reached) was significantly superior to that in the slow responders’ group (19 m, 95% CI: 1.79–23.14 m, P = 0.048). In conclusion, early dFLC reduction in C1D7 indicates a high possibility of CHR and organ response and may allow for early modification of therapy in selected patients.

The established of a machine learning model for predicting the efficacy of adjuvant interferon alpha1b in patients with advanced melanoma

BackgroundInterferon-alpha1b (IFN-α1b) has shown remarkable therapeutic potential as adjuvant therapy for melanoma. This study aimed to develop five machine learning models to evaluate the efficacy of postoperative IFN-α1b in patients with advanced melanoma.MethodsWe retrospectively analyzed 113 patients with the American Joint Committee on Cancer (AJCC) stage III-IV melanoma who received postoperative IFN-α1b therapy between July 2009 and February 2024. Recurrence-free survival (RFS) and overall survival (OS) were assessed using Kaplan-Meier analysis. Five machine learning models (Decision Tree, Cox Proportional Hazards, Random Forest, Support Vector Machine, and LASSO regression) were developed and compared for their capacity to predict the outcomes of patients. Model performance was evaluated using concordance index (C-index), time-dependent receiver operating characteristic (ROC) curves, and decision curve analysis.ResultsThe 1-year, 2-year, and 3-year RFS rates were 71.10%, 43.10%, and 31.10%, respectively. For OS, the 1-year, 2-year, and 3-year OS rates were 99.10%, 82.30%, and 75.00%, respectively. The Decision Tree (DT) model demonstrated superior predictive performance with the highest C-index of 0.792. Time-dependent ROC analysis for predicting 1-, 2-, and 3-year RFS based on the DT model is 0.77, 0.79 and 0.76, respectively. Serum albumin emerged as the important predictor of RFS.ConclusionsOur study demonstrates the considerable efficacy DT model for predicting the efficacy of adjuvant IFN-α1b in patients with advanced melanoma. Serum albumin was identified as a key predictive factor of the treatment efficacy.

NIMG-66. DEFINING PROGRESSIVE DISEASE: LOCALIZING VOXEL-AT-RISK ON MAGNETIC RESONANCE IMAGING USING DEEP LEARNING

Abstract Follow-up magnetic resonance imaging (MRI) of post-treatment glioblastoma (GBM) can be diagnostically challenging in differentiating progressive disease (PD) from coexisting treatment-related changes. The study aim was to train a machine learning model using multiple MRI timepoints from treated GBM patients with subsequent PD or at least six months of tumor-like, persistently stable disease (SD) to estimate PD risk. A retrospective, post-treatment GBM cohort (n=189) with 453 timepoints was identified with available MRI sequences (T1-weighted with and without contrast, T2-weighted, and fluid-attenuated inversion recovery). PD cases (n=154) showed new, enhancing PD followed by death within 3-6 months; timepoints included the MRI on the PD diagnosis date and the one directly prior. SD cases (n=35) exhibited stable, tumor-like enhancement over timepoints. Cases underwent voxel-wise annotation of PD versus SD. A multiclass, three-dimensional nnU-Net was trained to label voxels as PD, SD, or neither using timepoint sequences with five-fold cross-validation. Model performance was assessed using the ratio of predicted PD/SD voxels compared to each case’s actual PD or SD status. Classification accuracy of PD versus SD status, PD case-wise sensitivity and specificity, and a Receiver Operating Characteristic (ROC) analysis using the PD/SD ratio were presented. The five-fold model ensemble was evaluated on a holdout test set. Validation set performance showed 74.3% accuracy, 0.73 PD case-wise sensitivity, and 0.80 specificity. The holdout set exhibited 79.8% accuracy, 0.81 sensitivity, and 0.78 specificity for PD cases. The ROC analysis showed an area under the curve of 0.80 and 0.83 on the validation and holdout sets, respectively. The model showed high performance and classification accuracy in predicting which voxels were at risk of PD in post-treatment GBM cases. The model also differentiated between PD and SD regions. The model’s predicted PD/SD ratio may be clinically used to stratify patients’ PD risk.

NIMG-51. PROSPECTIVE CASE CONTROL STUDY OF HYPOXIA FMISO PET/MRI AS A DIAGNOSTIC FEATURE OF GLIOBLASTOMA IMMUNOTHERAPY FAILURE

Abstract BACKGROUND Hypoxia is a prognostic biological feature of glioblastoma. 18F-fluoromisonidazole (FMISO) PET quantifies tumor hypoxia. Efficacy of checkpoint immunotherapy is being investigated, but specific response assessment criteria remain unknown. We hypothesized that tumor hypoxia is a defining feature of immunotherapy failure in patients with glioblastoma. METHODS A prospective case control study was undertaken in patients with newly diagnosed IDH wildtype glioblastoma (NCT03649880). Cases were concurrently enrolled in a phase II study (NCT03347617) of pembrolizumab immunotherapy (200 mg IV every 3 weeks) combined with Stupp protocol temozolomide-based chemoradiotherapy following maximal safe resection. Controls did not receive pembrolizumab. FMISO PET/MRI (3.7 MBq/kg, 90 min uptake) was performed at time of mRANO presumed progression. Hypoxic volume (HV) was defined by pixels with FMISO uptake ≥1.2x that of mean cerebellar uptake. MRI-Gd enhancing volume was segmented using a semi-automated approach. Hypoxic fraction (HF) was defined as the HV-to-MRI enhancing volume ratio. Disease progression or pseudoprogression (Psp) was confirmed through surgery or follow-up MRI. T-test and receiver operator characteristic (ROC) analysis assessed differences and diagnostic performance. RESULTS 18 patients (14 cases [11 progression and 3 Psp] and 4 controls [3 progression and 1 Psp]) provided evaluable disease. For all patients, HF was significantly elevated with progression (1.44 ± 0.8; N=14) compared to Psp (0.31 ± 0.3; N= 4; P=0.01). HV was not different (P=0.10). No difference in HV or HF was observed between Cases and Controls (P> 0.42). Use of HF yielded an AUROC of 0.96 with an optimal cut off of 0.74, to differentiate progression from Psp. CONCLUSION At mRANO presumed progression HF with FMISO PET/MRI accurately distinguishes tumor progression from neuroinflammatory Psp, irrespective of prior pembrolizumab immunotherapy. The incorporation of FMISO PET/MRI in larger prospective therapeutic clinical trials in patients with glioblastoma is underway and likely to improve response assessment criteria.

NIMG-42. ANALYSIS OF TUMOR RELAPSE PROBABILITY AND OVERALL SURVIVAL PREDICTION FOLLOWING TEMOZOLOMIDE CHEMORADIATION USING FET PET INCLUDING RADIOMICS IN PATIENTS WITH GLIOBLASTOMA

Abstract BACKGROUND Early after surgery and completion of first-line concomitant chemoradiation with temozolomide, the evaluation of tumor relapse probability and overall survival prediction is of considerable interest for the management of patients with glioblastoma METHODS Sixty-three newly diagnosed patients with glioblastoma (age range, 19-82) who received static and dynamic PET imaging using the radiolabeled amino acid O-(2-[18F]fluoroethyl)-L-tyrosine (FET) after surgery or biopsy and completion of concomitant chemoradiation with temozolomide were evaluated. Static FET PET parameters such as maximum and mean tumor-to-brain ratios (TBRmax, TBRmean) and metabolic tumor volumes (MTV), and the dynamic FET PET parameter time-to-peak (TTP) were obtained. Additionally, FET PET radiomics features (n=1,303) were extracted for each patient and a test-retest analysis was performed to identify robust features prior to feature selection. The prognostic value of FET PET parameters and radiomics features was evaluated using receiver-operating-characteristic (ROC) analyses with regard to a significantly prolonged progression-free and overall survival (PFS, OS). Subsequently, univariate and multivariate survival estimates were performed to assess the prognostic value of these parameters to predict a significantly longer PFS and OS RESULTS ROC analyses revealed that the parameter TBRmax was a powerful parameter to predict both a significantly longer PFS (20.3 vs. 8.9 months; P=0.002; threshold, 2.75) and OS (34.9 vs. 18.7 months; P=0.005; threshold, 2.75). MTV had a similar prognostic value for both PFS (16.7 vs. 7.2 months; P=0.002; threshold, 34.0 mL) and OS (30.6 vs. 14.8 months; P=0.002; threshold, 32.6 mL). After feature selection, 3 of 15 selected radiomics features predicted a significantly longer PFS and OS in univariate analyses. TBRmax, MTV, and one of 15 radiomics features remained significant in multivariate survival analysis (all P≤0.03) CONCLUSION Our results suggest that FET PET and radiomics parameters were highly prognostic in this group of patients at an early stage of first-line therapy.

Establishment of potential lncRNA-related hub genes involved competitive endogenous RNA in lung adenocarcinoma

Long non-coding RNAs (lncRNAs) have a notable role in the diagnosis and prognosis of cancer. However, the associations between lncRNA-related hub genes (LRHGs) expression and the corresponding outcomes have not been fully understood in lung adenocarcinoma (LUAD). Here, a total of 71 patients diagnosed with LUAD and 60 healthy volunteers at The First Affiliated Hospital of Huzhou University from April, 2023 to December, 2023 were enrolled in the present study. A LRHGs model was established using least absolute shrinkage and selection operator analyses of The Cancer Genome Atlas-LUAD datasets. The underlying mechanisms of the LRHGs were investigated via Gene Set Enrichment Analysis and Gene Set Variation Analysis. Additionally, the diagnostic role of serum HOXD cluster antisense RNA 2 (HOXD-AS2) was assessed by receiver operating characteristic (ROC) curve analysis. Lastly, TCGA-LUAD samples were divided into high- and low-HOXD-AS2 expression groups based on the median expression. The associations between HOXD-AS2 expression and miR-4538 as well as Calmodulin-Dependent Protein Kinase Type II subunit Beta (CAMK2B) levels were conducted through Pearson correlation analysis. A comprehensive analysis identified 141 differentially expressed lncRNAs between 539 LUAD tissues and 59 normal samples. A prognostic marker for overall survival was established by constructing a predictive signature consisting of 9 LRHGs. Subsequently, 474 LUAD samples were categorized into a high or low-risk group based on the median of the risk score. An independent prognostic model was constructed to confirm the validity of this categorization. Further comparisons of the clinicopathological features and LRHG-related pathways were performed between the two groups. Examinations of LRHG expression in two LUAD clusters and of the association between LRHG expression and immune infiltration were also conducted. HOXD-AS2 expression was shown to be elevated in LUAD tissues compared with matched normal tissues, and the serum HOXD-AS2 level was also notably increased in LUAD samples compared with healthy controls. The results of the ROC analysis indicated that the sensitivity and specificity of HOXD-AS2 were higher than that of cytokeratin-19 fragment (CYFRA21-1), which is a serum marker for LUAD. Pearson analyses indicated that miR-4538 level was negatively associated with HOXD-AS2 expression, but CAMK2B level showed positive correlation in LUAD. The results of the present study therefore indicated that the constructed LRHG model, particularly HOXD-AS2, could independently diagnose and predict the prognosis of LUAD, which suggested the underlying mechanism of the HOXD-AS2/miR-4538/CAMK2B, and might offer efficient strategies for LUAD treatment.

Soluble adhesion molecules in serum and peritoneal fluid areassociated with pelvic pain in endometriosis.

To investigate the association between soluble adhesion molecules (sE-cadherin, sE-selectin, sICAM-1, sVCAM-1) in serum and peritoneal fluid and pelvic pain in infertile women with endometriosis. This observational study included 86 infertile women undergoing diagnostic laparoscopy, 43 of whom were diagnosed with endometriosis. Pain intensity was evaluated using the visual analog scale (VAS). Levels of soluble adhesion molecules in serum and peritoneal fluid were quantified using ELISA. Statistical analysis included the Mann-Whitney U test for group comparisons, Spearman's rank correlation for associations with VAS scores, and receiver operating characteristic (ROC) curve analysis for diagnostic performance. Serum sE-selectin levels were significantly higher in women with pelvic pain (P = 0.022) and correlated with VAS scores (r = 0.271, P = 0.012). Peritoneal sE-selectin and sICAM-1 levels were elevated in women with pelvic pain (P = 0.044 and P = 0.029, respectively) and showed positive correlations with VAS scores (r = 0.246, P = 0.022 and r = 0.310, P = 0.004, respectively). Comparing endometriosis and control groups, peritoneal sE-selectin and sICAM-1 levels were significantly higher in endometriosis cases with pelvic pain (P = 0.003 and P < 0.001, respectively). ROC analysis revealed the potential diagnostic value of serum sE-selectin (AUC = 0.698, P = 0.002), serum sICAM-1 (AUC = 0.721, P < 0.001), and serum sVCAM-1 (AUC = 0.750, P < 0.001) in distinguishing endometriosis from non-endometriosis cases. Elevated levels of sE-selectin and sICAM-1 in serum and peritoneal fluid are associated with pelvic pain in women with endometriosis, suggesting their role in pain pathogenesis and potential as biomarkers for pain severity and disease diagnosis. Further research is warranted to explore the underlying mechanisms and validate these findings in larger cohorts.

Association between relative fat mass and kidney stones in American adults

Our study aimed to investigate the association between RFM and kidney stones, focusing specifically on the mediating role of high-density lipoprotein cholesterol (HDL-C). We performed a cross-sectional analysis using data from the National Health and Nutrition Examination Survey (NHANES) covering the years 2007 to 2018. Our analytical approach included multivariate logistic regression modeling, subgroup analysis, generalized additive modeling (GAM), smoothed curve fitting, and receiver operating characteristic (ROC) curve, as well as mediation analysis to assess the association between RFM and kidney stones. Finally, we categorized RFM into normal and elevated groups to conduct a sensitivity analysis. This study involved 29,712 participants, with a kidney stone prevalence of 9.88%. We discovered a positive association between RFM and kidney stones (OR = 1.41 per SD increment, 95% CI: 1.24, 1.60). Subgroup analysis revealed a consistent positive association across all subgroups, with a notably higher likelihood of developing kidney stones in young adulthood (P for interaction < 0.05). The smooth curve fitting shows that RFM is nonlinearly and positively correlated with the prevalence of kidney stones. Additionally, HDL-C was found to be negatively associated with kidney stones. Importantly, HDL-C demonstrated a significant mediating effect, with a mediation ratio of 13.52%. ROC analysis indicated that RFM (AUC = 0.616) provided better diagnostic accuracy than traditional measures such as BMI (AUC = 0.565) and WC (AUC = 0.599). Furthermore, the sensitivity analysis further supports the robustness of our findings. RFM is nonlinearly and positively correlated with the prevalence of kidney stones, with HDL cholesterol playing a significant mediating role in this relationship. However, further studies are needed to confirm these associations and explore potential mechanisms.

Prognostic value of neutrophil to lymphocyte ratio and platelet indices in cats with feline panleukopenia

The aim of this study was to ascertain the prognostic significance of the neutrophil to lymphocyte ratio (NLR) and platelet indices during hospital admission in cats with feline panleukopenia (FPV). A prospective observational study was conducted on 24 cats diagnosed with FPV. The results of the study demonstrated a significant decrease in NLR, platelet count (PLT), and platelet concentration (PCT) in the FPV survivor group compared to the control group. Furthermore, these parameters exhibited a notable decline in the FPV non-survivor group when compared to both the control group and the FPV survivor group. In contrast, mean platelet volume (MPV) and platelet distribution width (PDW) were significantly elevated in the FPV non-surviving cats compared to the control group. Moreover, receiver operating characteristic (ROC) curve analysis was employed to identify a prognostic cut-off value for predicting the prognosis of cats with FPV. The positive predictive values (PPVs) for survival were determined to be 90 %, 95 %, 85 %, 85 %, 85 %, and 75 %, respectively, using cut-off values of NLR (≤ 0.29), PLT (≤ 202.5 ×10³/µL), PCT (≤ 0.19 %), MPV (≥ 10.3 fL), and PDW (≥ 34.9 %). Based on the sensitivity, specificity and positive predictive values obtained from the ROC analysis, it was concluded that the NLR, MPV, and PLT are excellent biomarkers for determining prognosis in cats with FPV. Nevertheless, the PLT level is of greater significance, exhibiting a higher AUC.

Assessing the validity of METS-IR for predicting the future onset of diabetes: an analysis using time-dependent receiver operating characteristics

BackgroundThe Metabolic Insulin Resistance Score (METS-IR) is a non-invasive proxy for insulin resistance (IR) that has been newly developed in recent years and has been shown to be associated with diabetes risk. Our aim was to assess the predictive value of METS-IR for the future development of diabetes and its temporal differences in people of different sex, age, and body mass index (BMI).MethodsThe current study included 15,453 baseline non-diabetic subjects in the NAGALA cohort and then grouped according to the World Health Organization’s (WHO) recommended criteria for age and BMI. Multivariate Cox regression and time-dependent receiver operator characteristics (ROC) curves were used to analyze the value of METS-IR in assessing and predicting the risk of diabetes in people of different sexes, ages, and BMIs.Results373 individuals developed diabetes during the observation period. By multivariate COX regression analysis, the development of future diabetes was significantly associated with increased METS-IR, and this positive association was stronger in women than in men and in individuals < 45 years than in individuals ≥ 45 years; while no significant differences were observed between non-obese and overweight/obesity individuals. Using time-dependent ROC analysis we also assessed the predictive value of METS-IR for future diabetes at a total of 11-time points between 2 and 12 years. The results showed that METS-IR had a higher predictive value for the future development of diabetes in women or individuals < 45 years of age compared to men or individuals ≥ 45 years of age for almost the entire follow-up period. Furthermore, across different BMI categories, we also found that in the short term (3–5 years), METS-IR had a higher predictive value for the development of diabetes in individuals with overweight/obesity, while in the medium to long term (6–12 years), METS-IR was more accurate in predicting the development of diabetes in non-obese individuals.ConclusionsOur study showed that METS-IR was independently associated with the development of future diabetes in a non-diabetic population. METS-IR was a good predictor of diabetes, especially for women and individuals < 45 years old for predicting the future risk of developing diabetes at all times.

Reliability and utility of blood glucose levels in the periodontal pockets of patients with type 2 diabetes mellitus: a cross-sectional study

Background Several studies have measured gingival blood glucose (GBG) levels, but few have confirmed systematic bias using Bland–Altman analysis. This study compared the effectiveness of GBG levels with that of fingertip blood glucose (FTBG) levels using Bland–Altman and receiver operating characteristic (ROC) analyses. Methods A total of 15 healthy volunteers and 15 patients with type 2 diabetes were selected according to inclusion and exclusion criteria. Each group comprised eight male and seven female participants. The GBG and FTBG levels were measured using a self-monitoring blood glucose device after periodontal examination. Pearson’s product‒moment correlation and simple linear regression analyses were performed. In addition, Bland‒Altman analysis was also performed to assess the degree of agreement between the two methods. ROC analysis was conducted to determine the sensitivity, specificity, and cutoff values for patients with diabetes. The area under the ROC curve (AUC) was used to identify significant differences. Results The mean GBG and FTBG levels were 120 ± 44.8 mg/dL and 137 ± 45.1, respectively, for the whole sample. The mean GBG and FTBG levels were 145 ± 47.2 mg/dL and 163 ± 49.1, respectively, in the diabetes group. The mean GBG and FTBG levels in the nondiabetes group were 95.3 ± 25.2 and 111 ± 18.8, respectively. Patients with diabetes were more likely to have a probing pocket depth (PPD) of ≥4 mm at the sampled site. Pearson’s product‒moment correlation and simple linear regression analyses revealed a significant correlation between the GBG and FTBG measurements. Bland–Altman analysis revealed that GBG and FTBG measurements differed significantly among all participants; however, no significant differences were observed among the patients with diabetes (mean difference (MD) ± standard deviation (SD) = −18.1 ± 34.2, 95% confidence interval (CI) [−37.0 to 0.88]) or among the participants with a PPD of ≥4 mm (MD ± SD = −15.2 ± 30.4, 95% CI [−30.8 to 0.43]). The sensitivity, specificity, and cutoff values of the GBG measurements for detecting diabetes were 80%, 93%, and 123.5 mg/dL, respectively. The sensitivity, specificity, and cutoff values of the FTBG measurements for detecting diabetes were 73%, 87%, and 134.0 mg/dL, respectively. No significant differences were observed between the AUCs (0.078, 95% CI [−0.006 to 0.161]). Conclusions The GBG measurements aligned with the FTBG measurements in the patients with diabetes and among the participants with a PPD of ≥4 mm. Patients with diabetes were more likely to have a PPD of ≥4 mm at the sampled site, GBG levels can be used to screen for type 2 diabetes in dental clinics.

Serum IgG Antibody against Helicobacter pylori and the CagA-VacA s1 Genotype as a Predictor of Gastric Cancer Development: A Case-control Study

Helicobacter pylori (H. pylori)-induced inflammation increases the risk of developing various upper gastrointestinal conditions which may progress to gastric cancer (CA). Early prediction and detection of infection are crucial for reducing cancer-induced mortality rates. The present case-control study aimed to investigate the combination of serum and molecular markers and H. pylori-associated gastro-duodenal conditions as risk factors for predicting CA development in dyspeptic patients. Consecutive gastric biopsies and blood samples were collected from 100 adult dyspeptic patients. Serum IgG antibody levels against H. pylori were determined, and receiver operating characteristic (ROC) analysis was performed. The expression of the virulence genes cagA and vacA was evaluated by polymerase chain reaction (PCR). A significant association was reported between the disease condition and the status of several risk factors, such as family history, serum IgG antibody concentration, and the virulence genes cagA and vacA. Among the 71 H. pylori-positive patients, 35.2% (25/71) had CA. Both cagA and vacA genes were found in 46 out of 71 (64.7%) patients, and 92% (23/25) of CA patients carried the cagA+vacA s1 gene. ROC analysis of the serum IgG concentrations revealed AUC values of 0.81 and 0.78 for differentiating patients with non-ulcer dyspepsia from those with ulceration/inflammation and CA, respectively. The concordance between the IgG-positive and PCR-positive patients was 84% (k value=0.41). Patients who had a family history of CA with an increased serum IgG concentration and the presence of H. pylori cagA-vacA s1 genotypes may be considered strong predictors of future development of gastric pathologies, including CA.

Preoperative red cell distribution width and its relation with in-hospital morbidities including atrial fibrillation after coronary artery bypass

Background and Aims: Atrial fibrillation (AF) and other adverse events are significant concerns following coronary artery bypass grafting (CABG). In recent years, Red Cell Distribution Width (RDW) has been identified as a potential biomarker for predicting these adverse outcomes. This study aims to assess early in-hospital adverse events in patients undergoing isolated off-pump CABG (OPCAB) and to analyze the relationship between these events and preoperative RDW levels. Methods: This study prospectively included 150 patients who underwent elective isolated OPCAB procedures. Patients were categorized into an “event group” (those experiencing adverse events) and a “no-event group” (those who did not). Additionally, they were stratified according to preoperative RDW levels into three groups: Group A (RDW ≤14%), Group B (RDW 14-16%), and Group C (RDW ≥16%). A receiver operating characteristic (ROC) curve, followed by both univariate and multivariate regression analyses were utilized to evaluate the predictive value of RDW for in-hospital morbidity. Results: The in-hospital mortality rate was 2.7%, and AF occurred in 20.7% of the patient population. The ROC analysis for early adverse events yielded an Area Under the Curve (AUC) of 0.681 with a p-value &lt;0.001, indicating moderate predictive capability; the sensitivity was 73% and specificity was 64% for RDW ≥14.05%. Multivariate regression analysis demonstrated that RDW independently predicts in-hospital morbidity after OPCAB, with an odds ratio of 0.713 (95% CI 0.566-0.899, p=0.004). Conclusion: Elevated preoperative RDW levels serve as a simple and cost-effective independent predictor of early adverse events following isolated OPCAB.

Utility of First-Morning-Voided Urinary Total Luteinizing Hormone in Detecting the Onset of Central Puberty

Introduction: Early morning basal serum luteinizing hormone (S-LH) ≥0.3 IU/L is a specific marker for the onset of central puberty. In this study, we aimed to investigate the sensitivity and specificity of the first-morning-voided (FMV) total urinary LH (U-LH) to replace this marker. Methods: We re-analyzed our previously published data set of 297 children (145 boys and 152 girls, aged 5–15 years, across Tanner stages 1 through 5) using receiver operating characteristic (ROC) analysis and determined cutoff values for FMV total U-LH in predicting early morning S-LH concentration at or above 0.3 IU/L. We also determined S-LH and serum follicle-stimulating hormone (S-FSH) concentrations in girls at different stages of sexual maturation. Results: ROC analysis showed that FMV total U-LH levels of 0.60 and 0.63 IU/L in girls and boys, respectively, predicted early morning S-LH levels of 0.3 IU/L or higher with 97.4% sensitivity and 90.6% specificity. Higher cutoff levels for U-LH (0.78 IU/L for boys and 0.79 IU/L for girls) yielded 94.7% specificity at the expense of a relatively lower level of sensitivity (94.1%). The areas under the curve were 0.98 in boys and 0.99 in girls, respectively. Additionally, the increase in FMV total U-LH (or S-LH) levels identified the activation of central pubertal development at the mean age of 10.3 (10.3) in boys and 10.5 (10.6) in girls. The S-FSH concentrations of the six biochemically prepubertal girls with thelarche, ranging between 2.3 and 2.7 IU/L, were significantly higher than those measured in biochemically and clinically prepubertal girls of the same 10–12-year-old age group and significantly lower than those measured in both biochemically and clinically pubertal girls (p = 0.039 and p = 0.018, respectively). Conclusions: A FMV total U-LH concentration of 0.6 IU/L or above reliably reflects pubertal morning S-LH levels and is effective in detecting the onset of central puberty, which occurs at similar ages in both sexes. Concurrent S-FSH or noninvasive FMV U-FSH determinations may be useful in the differential diagnosis of isolated thelarche.