ROC Curve Analysis Research Articles

SUSD2+ cancer-associated fibroblasts in gastric cancer mediate the effect of immunosuppression and predict overall survival and the effectiveness of neoadjuvant immunotherapy.

The expression patterns and functions of Sushi Domain Containing 2 (SUSD2) differ among various malignancies. This research aims to investigate the expression of SUSD2 and the role of the SUSD2+ cancer-associated fibroblasts (CAFs) for immunotherapy in gastric cancer. The expression of SUSD2 and specific markers (CD4, CD8, PD-1, TIGIT, TIM-3 and CD163) was determined using immunohistochemistry and multiplex immunofluorescence (mIHC) on paraffin sections. Flow cytometry and western blot were used to assess the expression of SUSD2 in fibroblasts from fresh samples. Also, analysis of single-cell and bulk RNA sequencing was employed to confirm the presence and characterize the function of SUSD2+ CAFs. The predictive power of indicators for neoadjuvant immunotherapy was evaluated via ROC curve analysis. Animal experiment was employed to validate the immunosuppressive effect of SUSD2+ CAFs. SUSD2 is mainly expressed on fibroblasts within the tumors and the high infiltration of SUSD2+ CAFs went together with a poor survival and a more advanced tumor stage. Significantly, the joint use of SUSD2+ CAFs and CD8+ T cells demonstrated a remarkable ability to predict the efficacy of neoadjuvant immunotherapy superior to PD-L1 combined positive score. High SUSD2+ CAFs was correlated with resistance to immunotherapy as well as low CD8+ T infiltration and high exhausted T cell infiltration. We have identified a novel subset of CAFs that could predict the survival and response to neoadjuvant immunotherapy of patients. The SUSD2+ CAFs have the potential to serve as a predictive biomarker and a promising target for immunotherapy.

Inadequate identification of high cardiovascular risk and carotid plaques in rheumatoid arthritis patients by the 2024 Predicting Risk of Cardiovascular EVENTs and the 2013 Atherosclerotic Cardiovascular Disease algorithms: findings from a Mexican cohort.

The American College of Cardiology/American Heart Association introduced the Predicting Risk of Cardiovascular EVENTs (PREVENT™) algorithm to estimate the 10-year risk of developing cardiovascular disease. We aimed to assess the cardiovascular risk (CVR) reclassification among rheumatoid arthritis (RA) patients using traditional CVR algorithms-the 2024 PREVENT™ and the 2013 Atherosclerotic Cardiovascular Disease (ASCVD)-and the presence of carotid plaque (CP). This was a cross-sectional study nested of a RA patients' cohort. A certified radiologist performed a high-resolution B-mode carotid ultrasound to identify the presence of CP. The CVR evaluation was performed by a cardiologist, blinded to carotid ultrasound results, using the PREVENT™ and the ASCVD algorithms. Cohen's kappa (k) coefficient assessed concordance between high-risk classification by CVR algorithms and CP presence. ROC curve analysis evaluated the algorithms' capacity to identify RA patients with CP. The cutoff point was determined by the Youden-Index, with p < 0.05 as statistically significant. A total of 210 RA patients were included. The reclassification of CVR due to CP was 34.3% for the PREVENT™ algorithm and 30.0% for the ASCVD algorithm. Of these, 44.4% and 71.4%, respectively, were initially classified as low risk. Concordance between CVR algorithms and carotid ultrasound showed slight agreement (k = 0.032 and k = 0.130, respectively). The PREVENT™ algorithm did not identify more than one-third of high-CVR RA patients with indication of starting statin therapy based on carotid ultrasound findings. The PREVENT™ and ASCVD algorithms showed poor performance in identifying RA patients with CP. Key Points • The presence of CP was identified in more than a third of the evaluated RA patients (35.7%), classifying them as high CVR. • CVR reclassification by the presence of CP was observed in 34.3% RA patients with the PREVENTTM algorithm and in 30.0% RA patients with the ASCVD algorithm. • Most of the reclassified patients belonged to the low-risk category, 44.4% with the PREVENTTM algorithm and 71.4% with the ASCVD algorithm. • When evaluating the concordance between the ASCVD algorithm and the carotid ultrasound for high-risk classification, a slight agreement was found (k = 0.130).

Cardiometabolic Index is associated with heart failure: a cross-sectional study based on NHANES

IntroductionHeart failure is a complex syndrome characterized by impaired cardiac function. Despite improvements in treatment, the prevalence of heart failure continues to rise. The Cardiometabolic Index (CMI), a novel measure combining abdominal obesity and lipid levels, has emerged as a potential predictor of cardiac metabolic risk.MethodsWe analyzed data from the National Health and Nutrition Examination Survey (NHANES) involving 22,586 participants to investigate the association between CMI and heart failure. Multivariable logistic regression models and RCS analysis were used to explore the association between heart failure and CMI after adjusting for potential confounders. Subgroup analyses were performed among populations with different demographic and clinical characteristics.ResultsOur results revealed a significant positive correlation between CMI and heart failure, with odds ratios of 2.77 and 1.87 for the highest quartile after adjusting for confounders. Subgroup analyses indicated heightened risks among older adults and those with hypertension or diabetes. ROC curve analysis demonstrated that CMI offers good diagnostic value for heart failure, surpassing traditional measures like BMI.DiscussionOur findings suggest that CMI is a valuable tool for assessing the risk of heart failure, particularly in individuals with increased abdominal obesity or abnormal lipid profiles. This highlights the importance of addressing cardiac metabolic health in both prevention and treatment strategies for heart failure. Future research should focus on exploring causal relationships and refining predictive models that incorporate CMI to enhance early detection and intervention.

. Diagnostic value of HMGB-1 and Acetylcholinesterase in Assessing the Prognosis of Patients with Acute Pancreatitis

Aim: Acute pancreatitis (AP) is a disorder of tissue digestion caused by abnormal activation of pancreatic enzymes, which may lead to multi-organ failure and ultimately death as the disease progresses. How to quickly and accurately evaluate the progression of AP has always been a hotspot and difficulty in clinical research. Methods: Sixty-four AP patients admitted to our hospital from August 2022 to June 2023 and 60 concurrent healthy people were selected as the research subjects, with AP patients as the observation group and healthy people as the control group. Using kits from Wuhan Fine Biotechnology Co., Ltd., an enzyme-linked immunosorbent assay (ELISA) was carried out to measure HMGB-1 and AChE levels. In addition, an automatic biochemical analyzer was utilized to quantify the levels of nutritional proteins albumin (ALB), transferrin (TRF), and total protein (TP) in the observation group. Results: Compared with the control group, the HMGB-1 in the observation group was higher while the AChE was lower (P&lt;0.05). ROC curve analysis showed that when HMGB-1 was less than 7.25 mg/L, the sensitivity and specificity for diagnosing AP were 89.06% and 51.67%, respectively (P&lt;0.05); when AChE was less than 6.18 U/L, the sensitivity for diagnosing AP was 43.75% and the specificity was 90.00% (P&lt;0.05). Using the joint detection Log(P)=-1.736+(0.645×HMGB-1)+(-0.454×AChE), it was found that HMGB-1+AChE had a sensitivity of 48.44% and a specificity of 88.33% for the diagnosis of AP (P&lt;0.05, cut-off&gt;0.639,) Conclusion: In this study, we found elevated HMGB-1 expression in AP and reduced acetylcholinesterase (AChE), suggesting that both of them may be involved in the occurrence and development of AP. Meanwhile, the two demonstrated excellent diagnostic efficacy in the onset and poor prognosis of AP, and were closely related to AP progression, confirming their potential as new clinical indicators for AP. Due to the self-digestion by pancreatic enzymes, the nutritional metabolism of AP patients is disrupted, so protein loss is also a focus of attention. In this study, we also found a negative correlation of nutritional protein levels with HMGB-1 in AP patients and a positive correlation between them with AChE, further supporting the relationship between the two and AP progression. The findings can lay a reliable foundation for future research on the diagnosis and treatment of AP based on HMGB-1 and AChE.

The role of inflammasome dysregulation in obstructive and non-obstructive azoospermia: a comparative molecular analysis of blood, tissue, and seminal plasma

BackgroundTo address knowledge gaps, this study aimed to investigate the involvement of inflammasomes in the etiology of azoospermia. This study focused on the gene expression of key inflammasome components, including NLR family pyrin domain containing 3 (NLRP-3), CASPASE-1, Interleukin-1β (IL-1β), Interleukin-18 (IL-18), NLR family CARD domain-containing protein 4/ice protease-activating factor (NLRC-4/IPAF), and Absent in melanoma 2 (AIM-2).MethodsWe analyzed gene expression in blood and testicular tissue from patients with obstructive azoospermia (OA) and non-obstructive azoospermia (NOA). Additionally, we compared IL-1β and IL-18 expression levels in seminal plasma samples using the Enzyme-Linked Immunosorbent Assay (ELISA) method. For comparison, blood samples from normospermic (NS) individuals were also genetically evaluated.ResultsOur results indicated significantly higher gene expression of inflammasome components in NOA patients than those in OA patients either in blood or in testicular tissue. Both azoospermic groups exhibited higher mRNA levels of inflammasome genes comparing with those from blood samples of NS men. Seminal plasma samples showed significantly increased levels of IL-1β and IL-18 in NOA patients compared to men with OA. The ROC curve analysis indicated strong and significant predictive power of IL-18, AIM-2 and NLRC-4/IPAF gene expression profiles between NOA vs. NS patients and NOA vs. OA.ConclusionsOur findings highlight the role of hidden chronic inflammation in azoospermia, particularly within the NOA group. This study provides a foundation for further detailed research, which could aid in the development of diagnostic panels to differentiate between various azoospermic groups.

BIRC5 as a prognostic and diagnostic biomarker in pan-cancer: an integrated analysis of expression, immune subtypes, and functional networks

IntroductionBIRC5 (Survivin) is a crucial anti-apoptotic protein overexpressed in various cancers, promoting tumor growth and treatment resistance. This study investigates its expression across 33 cancer types and explores its diagnostic, prognostic, and immune-related significance.MethodsWe analyzed RNA-seq data from TCGA and protein expression data from the Human Protein Atlas. Expression levels were compared between tumor and normal tissues. Correlations with molecular and immune subtypes were explored using TISIDB. Prognostic significance was evaluated through survival analysis, Cox regression, and ROC curve analysis. The PPI network was constructed using STRING.ResultsBIRC5 was significantly overexpressed in tumor tissues across 33 cancer types, with higher expression levels observed in tumors compared to normal tissues. The protein expression analysis revealed a similar trend. BIRC5 expression was significantly correlated with various molecular and immune subtypes in multiple cancer types. Survival analysis indicated that high BIRC5 expression was associated with poor prognosis across multiple cancers, including lung adenocarcinoma (LUAD) and kidney renal clear cell carcinoma (KIRC). ROC analysis showed that BIRC5 exhibited strong diagnostic potential, with high AUC values (&amp;gt;0.9) in several cancers. The PPI network analysis identified key interacting proteins involved in the cell cycle and tumor progression, further supporting BIRC5's role in cancer biology. Functional experiments in lung adenocarcinoma (LUAD) revealed that BIRC5 upregulation enhances cell proliferation, migration, and invasion, while its knockdown suppresses these activities.DiscussionBIRC5 is a promising diagnostic and prognostic biomarker in multiple cancers. Its association with immune subtypes suggests a potential role in the tumor immune microenvironment. These findings support BIRC5 as a therapeutic target for cancer treatment.

Application of optical coherence tomography angiography to study retinal and choroidal vascular changes in patients with first-time coronary artery stenosis

ObjectiveTo study the changes in retinal and choroidal vessels in patients with coronary artery stenosis via optical coherence tomography angiography (OCTA). MethodsA total of 100 subjects were enrolled in this study and divided into two groups:the observation group consisted of 50 patients with angina who were first diagnosed with coronary artery stenosis, and the control group consisted of 50 healthy adults without angina symptoms. All of the subjects underwent OCTA to investigate changes in retinochoroidal vessel density in patients with a first diagnosis of coronary artery stenosis. The parameters included superficial capillary plexus density (SCD), deep capillary plexus density (DCD), retinal peripapillary capillary plexus density(RPD), the choroidal vascular index (CVI), and the macular foveal avascular zone(FAZ area, perimeter, acircularity index, FD-300 vessel density). ResultsSCD and DCD in the coronary artery stenosis group were lower than those in the control group (P=0.045 and P=0.034, respectively), the CVI was lower than that in the control group (P=0.029), the FAZ perimeter and acircularity index were greater than those in the control group (P=0.003,P=0.024). Logistic regression and ROC curve analysis revealed that FAZ perimeter was the most significant risk factor for predicting coronary artery stenosis (P=0.005, AUC=0.664), and the cut-off value for FAZ perimeter was 2.065 mm. ConclusionsIn patients with a first diagnosis of coronary artery stenosis, both retinal and choroidal blood flow are reduced. FAZ perimeter is a risk factor for predicting the occurrence of coronary artery stenosis.

Prognostic value of preoperative D-dimer to albumin ratio in patients with locally advanced rectal cancer after neoadjuvant chemoradiotherapy

BackgroundThe prognostic value of Albumin and D-dimer has been established for multiple tumor types, indicating their potential for predicting tumor development. Nevertheless, the predictive capability of the DDI-to-albumin ratio (DAR) in locally advanced rectal cancer (LARC) remains uncertain.PurposeThe objective of this study was to investigate the prognostic significance of the DAR in LARC.MethodsA total of 513 patients who underwent neoadjuvant chemoradiotherapy (nCRT) prior to total mesorectal excision (TME) between March 2013 to October 2019 were included in this study. Patients were divided into high-level DAR (> 0.016) or low-level DAR (≤ 0.016) groups based on ROC curve analysis optimum cut-off value. The prognostic value of the DAR in LARC was analyzed.ResultsThe study enrolled 513 patients. Patients were stratified into high-level DAR (> 0.016) and low-level DAR (≤ 0.016) cohorts according to the optimal cut-off value determined by ROC curve analysis. The 5-year overall survival (OS) rates for patients in the low DAR group (≤ 0.016) and the high DAR group (> 0.016) were 89.4% and 80.9%, respectively (p = 0.013). The 5-year disease-free survival (DFS) rates were 85.7% and 77.4% (p = 0.027). Multivariate analyses demonstrated that DAR were independent prognostic factors for OS (p = 0.02) and DFS (0.025). Predictive nomograms that included the DAR score group (C-index: OS-0.743, DFS-0.705) were superior to those without DAR scores (C-index: OS-0.721, DFS-0.697).ConclusionThe DAR demonstrates high usability and prognostic value in predicting OS and DFS outcomes among patients diagnosed with LARC who undergo nCRT.

High expression of RHOF is an effective diagnostic marker and a potential prognostic indicator for primary mediastinal large B-cell lymphoma.

Due to the overlap of histological and molecular features of primary mediastinal large B-cell lymphoma (PMBL) with other lymphomas and its low incidence, the diagnosis and prognostic assessment of PMBL pose certain challenges. This study included 51 PMBL and 375 diffuse large B-cell lymphoma, not otherwise specified (DLBCL-NOS) from the GEO database and 65 PMBL and 117 DLBCL-NOS from a single center. At the transcriptional and protein levels, RHOF expression in PMBL was significantly higher than in DLBCL-NOS (P < 0.001). ROC curve analysis suggested that high RHOF expression had a high discriminative diagnostic ability for PMBL and DLBCL-NOS (transcriptional level, AUC = 0.913-0.940; protein level, AUC = 0.878). Comparing RHOF with commonly used PMBL diagnostic markers CD23, CD30, and PD-L1, it was found that high RHOF expression is a more useful diagnostic marker for PMBL (AUC (RHOF) = 0.878 > AUC (CD23) = 0.818 > AUC (CD30) = 0.756 > AUC (PD-L1) = 0.590). The diagnostic model based on CD23, CD30, and RHOF exhibits higher sensitivity for the diagnosis of PMBL than any of the individual markers mentioned above. Concerning prognosis, high RHOF transcriptional expression was significantly associated with poorer overall survival (OS) in PMBL (P = 0.00037), while high RHOF protein expression was significantly associated with poorer OS and progression-free survival (PFS) in PMBL (P = 0.034; P = 0.034). This study indicates that high RHOF expression in PMBL is closely associated with the diagnosis, prognosis, and clinical pathological features of the disease. High RHOF expression demonstrates a superior diagnostic ability in distinguishing PMBL from DLBCL-NOS compared to existing markers. Furthermore, research on RHOF expression in PMBL holds promise for providing new targets and insights for prognosis assessment and treatment of PMBL.

CineECG Repolarization Gradients Predict Acute Hemodynamic Response in CRT Patients.

A variable proportion of non-responders to cardiac resynchronization therapy (CRT) warrants the search for new approaches to optimize the position of the left ventricular (LV) lead and the CRT device programming. CineECG is a novel ECG modality proposed for the spatial visualization and quantification of myocardial depolarization and repolarization sequences. The present study aimed to evaluate CineECG-derived parameters in different pacing modes and to test their associations with acute hemodynamic responses in CRT patients. CineECG was used to construct the average electrical path within the cardiac anatomy from the 12-lead ECG. CineECG and LV dP/dt max were tested in 15 patients with nonischemic dilated cardiomyopathy and left bundle branch block (QRS: 170 ± 17 ms; LVEF: 26 ± 5.5%) under pacing protocols with different LV lead localizations. The CineECG-derived path directions were computed for the QRS and ST-T intervals for the anteroposterior (Xh), interventricular (Yh), and apicobasal (Zh) axes. In a multivariate linear regression analysis with adjustment for the pacing protocol type, the ST-T path direction Yh was independently associated with the increase in dP/dt max during CRT, [regression coefficient 639.4 (95% confidence interval: 187.9-1090.9), p = 0.006]. In ROC curve analysis, the ST-T path direction Yh was associated with the achievement of a 10% increase in dP/dt max (AUC: 0.779, p = 0.002) with the optimal cut-off > 0.084 (left-to-right direction) with sensitivity 0.67 and specificity 0.92. The acute hemodynamic response in CRT patients was associated with specific CineECG repolarization sequence parameters, warranting their further testing as potential predictors of clinical outcomes.

Thermographic images for screening oral health problems in older adults: A pilot study

ObjectiveThis pilot study assessed the feasibility of using facial thermography to detect intra-oral problems in older adults with cognitive decline and care-resistant behaviors, who are often unable to communicate pain or early symptoms. MethodsTwenty-three older adults (mean age 73.7 ± 13.2 years) with cognitive decline were enrolled. Thermal images of four facial views were taken using a smartphone-connected FLIR thermal camera. Intra-oral examinations were conducted, and the thermographic data were analyzed to extract temperature values in the regions of interest (ROI). Point-biserial correlations and ROC curve analyses were performed to evaluate associations between temperature data and clinical findings, with a significance level of p<0.05. ResultsIntra-oral issues requiring treatment were found in 12 participants, with six reporting clinical pain. The overall mean temperature in the ROI was 33.5 ± 3.9°C, and significant temperature differences were found between the body and ROI temperatures. Correlations were observed between clinical problems and various temperature metrics, including the minimum and maximum ROI temperatures (rpb=-0.327, p=0.002 and rpb=-0.309, p=0.003). ROC analysis indicated that ROI temperature could predict the presence or absence of clinical problems, with AUC values ranging from 0.651 to 0.796 for different metrics. ConclusionThermographic facial imaging shows significant potential as a non-invasive tool for detecting oral health problems in vulnerable older adults. While promising, further research is essential to enhance image quality, streamline the technique, and incorporate AI for improved diagnostic accuracy and ease of use. Clinical SignificanceThis non-invasive, inexpensive technique is easy to perform, independent of patient compliance and, is promising to detect early oral problems in noncommunicative patients.

Diagnostic performance of FibroTouch® in assessing hepatic steatosis and fibrosis in patients with metabolic dysfunction-associated steatotic liver disease: An Asian experience.

FibroTouch® has shown efficacy in staging hepatic fibrosis in patients with chronic viral hepatitis B, but its performance in assessing liver steatosis and fibrosis in metabolic dysfunction-associated steatotic liver disease (MASLD) patients remains understudied. We aimed to evaluate the diagnostic performance of FibroTouch® in assessing steatosis and fibrosis in the MASLD population. Liver stiffness measurements and steatosis were assessed using FibroTouch® and FibroScan®, with FibroScan® as the reference standard. Pearson's correlation test evaluated correlations, and kappa statistics determined agreement between the two methods. Optimal cut-off values of FibroTouch® for predicting hepatic steatosis and fibrosis stages were determined through ROC curve analysis with the Youden index method. Strong correlations were observed between FibroTouch® UAP and FibroScan® CAP (rho=0.74) and LSM values (rho=0.87) (p<0.001 for both) in a total of 380 patients. The mean CAP value for the entire cohort was 285±51 dB/m, and the median LSM for the cohort was 5.3kPa. The optimal FibroTouch® UAP cutoffs were 229 dB/m for S0 vs. S1, 267 dB/m for S1 vs. S2, and 294 dB/m for S2 vs. S3. For FibroTouch® LSM, the optimal cutoffs were 6.0kPa for F0-F1 vs. F2, 7.9kPa for F2 vs. F3, and 10.6kPa for F3 vs. F4. Moreover, FibroTouch® effectively assessed hepatic steatosis and fibrosis in patients with different BMIs. FibroTouch® proved valuable in assessing hepatic steatosis and liver fibrosis staging in MASLD patients, enhancing its applicability in various clinical settings as a suitable and convenient option for MASLD patients.

Correlation between the Atherogenic Index of Plasma and Progression of Non-target Lesion Vascular Disease Following Percutaneous Coronary Intervention using Drug-eluting Stents.

To examine the correlation between Atherogenic Index of Plasma (AIP) levels and the progression of non-target lesion vascular disease following the deployment of Drug-eluting Stents (DES). We retrospectively enrolled patients who had undergone successful treatment for CAD with DES and subsequently underwent a coronary angiography follow-up at the Cardiology Department of Tianjin Third Central Hospital from January 2017 to July 2022. The annual change in Gensini Score (GS) was calculated according to two angiographic evaluations in order to assess the progression of non-target lesion vascular disease; a change greater than 1 indicated progression, while a change of 1 or less indicated stability. AIP was calculated according to serum lipid parameters. Multivariate Logistic regression model was used to evaluate the relationship between AIP level and progression of non-target coronary artery lesions. The ROC curve analysis was performed to evaluate the diagnostic value of AIP for coronary artery non-target lesion vascular disease progression. Out of the 344 patients who were monitored over a median duration of 1.2 years, 113 exhibited progression of non-target lesion vascular disease. Initially, baseline AIP levels were notably higher in the progression group compared to the non-progression group (0.30 [0.14, 0.43] vs. 0.11 [-0.06, 0.31]), and this difference remained significant during the follow-up period (0.19 [0.06, 0.34] vs. 0.11 [-0.06, 0.22]). Multivariate logistic regression revealed that AIP is an independent predictor for the progression of non-target lesion vascular disease following DES treatment. Individuals in the highest tertile of AIP faced a considerably elevated risk compared to those in the lowest tertile (OR = 4.88, 95% CI: 2.12-11.21, P < 0.001). Moreover, utilizing receiver operating characteristic curve analysis, a 0.15 AIP level cut-off was determined for diagnosing disease progression, with a sensitivity of 73.5% and specificity of 56.7%, and an area under the curve of 0.672 (95% CI: 0.613-0.731, P < 0.01). AIP significantly correlates with the progression of non-target lesion vascular disease among patients with coronary artery disease who have undergone DES treatment, establishing itself as an independent risk factor in addition to conventional predictors.

Evaluation of the analytic performance and macroprolactin sensitivity of a new prolactin immunoassay.

Prolactin measurement is essential in endocrine diagnostics. Challenges such as the hook effect and reactivity to macroprolactin, which varies according to the reagent, complicate accurate measurement. The present study evaluated a newly marketed reagent to detect prolactin, IDS Prolactin, comparing it to an established reagent, Roche Elecsys Prolactin, assessing its behavior toward macroprolactin and polyethylene glycol (PEG) treatment, and establishing reference intervals. The IDS Prolactin and Roche Elecsys Prolactin assays were compared using 44 samples containing macroprolactin confirmed on gel filtration chromatography (macroprolactin: BBPRL) and 104 samples for which the diagnosis of macroprolactin was excluded (monomeric prolactin: MNPRL). Analytic performance of the IDS Prolactin assay was also assessed. The new reagent showed satisfactory analytic performance, meeting EFLM standards for repeatability and intermediate imprecision. Comparison between the two methods found robust correlation for monomeric samples (y=1.060x-18.28; r2=0.993). Compared to the Roche assay, which is particularly low in its reaction to macroprolactin, the IDS assay displayed a higher level of detection. PEG precipitation effectively separated monomeric and macroprolactin samples when a cut-off of 65% recovery was used or at the threshold of 444 mIU/L (20.9 µg/L) for post-PEG monomeric prolactin upper limit of normal. Reference intervals were established for women, with ROC curve analysis demonstrating high sensitivity and specificity. The IDS Prolactin assay showed excellent analytic performance and satisfactory characteristics on macroprolactinemic samples.

The diagnostic validity of the cervical side bend-rotation test for C 1/2 dysfunction

ABSTRACT Introduction Neck pain and headaches are common, with a reported lifetime prevalence of up to 66%. Upper cervical segmental dysfunction has been implicated as meaningful in neck pain and multiple headache types. Several tests have been described to assess upper cervical joint dysfunction, including the flexion-rotation test (FRT), the side bend-rotation test (SBRT), and joint play assessment (PA). The purpose of this study was to determine the diagnostic validity of the SBRT to detect C1–2 dysfunction in a sample of people with medically diagnosed sinus headaches and controls. Methods Design: prospective diagnostic accuracy study, occurring during an observational case-control study in a sample of individuals with medically diagnosed sinus headaches. All participants were assessed using the SBRT, FRT, and C1–2 joint play assessments. The diagnostic accuracy of the SBRT was assessed using a reference standard of concurrent positive FRT (a loss of at least 10° from expected ROM (≤34°)) and restriction of C1–2 joint play. Cut-off scores for the SBRT were determined using ROC curve analysis, and tests of diagnostic accuracy were calculated using 2 × 2contingency tables. Results A total of 80 individuals (40 headache, 64 female, mean age 32.9 ± 13.8 yrs.) were included in the study. Mean ROM for the tests was: SBRT 31.4 ± 9.4°, FRT 44.9 ± 9.5°, and C1–2 mobility 22 hypomobile/58 normal. An SBRT cutoff score of <25° was confirmed using ROC curves. Using this cutoff score, the SBRT demonstrated 100% sensitivity and 62% specificity to detect C1–2 hypomobility. Discussion/conclusion The SBRT, using a cutoff score of ≤25°, appears to be a sensitive test to detect C1–2 dysfunction. Based on the strong sensitivity and negative predictive values, scores greater than 25° may effectively rule-out C1–2 dysfunction. The SBRT should be considered as part of a sequential clinical decision-making process when screening for C1–2 dysfunction, although further research is required to improve generalizability of these findings.

Delays in the final stages of fertilization are strongly associated with trichotomous cytokinesis and cleavage arrest.

Recent evidence showed that the phase between pronuclear fading and the first cleavage is a perilous bridge connecting the zygote and the embryo. Indeed, delay in the short interval between pronuclear breakdown (PNBD) and the first cytokinesis may result in chromosome segregation errors. We tested the hypothesis that delays in this final phase of fertilization are associated with a detrimental impact on embryo development. This is a retrospective study of 1315 zygotes cultured using time lapse technologies generated in 205 first ICSI-cycles. We observed an association between increasing times of the pronuclear fading-first cleavage interval (t2-tPNf) and the rates of trichotomous/direct unequal cleavage at the first (DUC-1) and second (DUC-2) mitotic cycle. Moreover, we observed a reduced blastulation rate. No significant associations were observed between rates of direct unequal cleavage at the third mitotic cycle (DUC-3) and top-quality blastocysts, euploidy, and live births. To evaluate whether the interval t2-tPNf could have a predictive value for the onset of DUC-1 and DUC-2, ROC curve analyses were performed. The area under the curve values obtained for DUC-1 showed a significant prediction accuracy. The best cut-offs to identify zygotes with a high risk of DUC-1 and DUC-2 occurrence were t2-tPNf > 2.78 (hours) and t2-tPNf > 2.50 (hours), respectively. Delay in the short interval between PNBD and the first cytokinesis result in trichotomous cleavage and early developmental arrest. However, if the embryos reach the blastocyst stage, rates of euploidy and live birth do not appear to be compromised.

Analysis of four long non-coding RNAs for hepatocellular carcinoma screening and prognosis by the aid of machine learning techniques

Hepatocellular carcinoma (HCC) represents a significant health burden in Egypt, largely attributable to the endemic prevalence of hepatitis B and C viruses. Early identification of HCC remains a challenge due to the lack of widespread screening among at-risk populations. The objective of this study was to assess the utility of machine learning in predicting HCC by analyzing the combined expression of lncRNAs and conventional laboratory biomarkers. Plasma levels of four lncRNAs (LINC00152, LINC00853, UCA1, and GAS5) were quantified in a cohort of 52 HCC patients and 30 age-matched controls. The individual diagnostic performance of each lncRNA was assessed using ROC curve analysis. Subsequently, a machine learning model was constructed using Python’s Scikit-learn platform to integrate these lncRNAs with additional clinical laboratory parameters for HCC diagnosis. Individual lncRNAs exhibited moderate diagnostic accuracy, with sensitivity and specificity ranging from 60 to 83% and 53–67%, respectively. In contrast, the machine learning model demonstrated superior performance, achieving 100% sensitivity and 97% specificity. Notably, a higher LINC00152 to GAS5 expression ratio significantly correlated with increased mortality risk. The integration of lncRNA biomarkers with conventional laboratory data within a machine learning framework demonstrates significant potential for developing a precise and cost-effective diagnostic tool for HCC. To enhance the model’s robustness and prognostic capabilities, future studies should incorporate larger cohorts and explore a wider array of lncRNAs.

Sanguinarine identified as a natural dual inhibitor of AURKA and CDK2 through network pharmacology and bioinformatics approaches

Cervical cancer (CA) continues to be a female malignant tumor with limited therapeutic options, resulting in a high mortality rate. Sanguinarine (SANG), a naturally occurring alkaloid, has demonstrated notable efficacy in preclinical treatment of CA. However, the mechanism through which SANG acts against CA is not fully understood. To address this, utilizing nine drug target prediction databases, we have successfully identified 379 potential targets for SANG. Venn diagram analysis compared 2367 CA-related targets from the GeneCards disease database, 2618 CA-closely related targets derived from multiple datasets in GEO through WGCNA analysis, and the 379 potential targets of SANG, resulting in 35 shared targets. Subsequently, by employing PPI network analysis, the Cytohubba plugin, the Human Protein Atlas, TCGA database data, and ROC curve analysis, we have identified AURKA and CDK2 as key targets of SANG in combating CA. Single-gene GSEA results suggest that the overexpression of AURKA and CDK2 is closely correlated with DNA replication, cell cycle progression, and various DNA repair pathways in CA. Molecular docking and molecular simulation dynamics analyses have confirmed the stable binding of both AURKA and CDK2 to SANG. In summary, by integrating diverse methodological approaches, this study discovered that SANG potentially inhibits the malignant features of CA by targeting AURKA and CDK2, thereby regulating DNA replication, cell cycle progression, and multiple DNA repair pathways. This lays a solid foundation for further exploring the pharmacological role of SANG in CA therapy. However, further in-depth in vitro and in vivo experiments are required to corroborate our findings.

Immunoinformatic predictions and characterization of Schistosoma mansoni peptides as candidates for immunodiagnostic

Schistosoma mansoni represents a significant etiological agent of schistosomiasis, a neglected tropical disease with a global distribution. Although the Kato-Katz technique is an effective diagnostic tool in areas with a high prevalence of the disease, it lacks sensitivity in regions with lower prevalence. The objective of this study was to identify and validate novel immunogenic peptide targets derived from the S. mansoni proteome. The initial set of 14,499 predicted sequences were obtained from the WormBase database, and it was filtered to 8,308 by removing proteins lacking start or stop codons, shorter than 100 amino acids, or with undetermined amino acids. The sequences were then cross-referenced for cross-reactivity and ranked based on B-cell immunogenicity, resulting in the selection of 442 peptides for synthesis and screening. Immunoblotting revealed 22 reactive peptides, with 15 exhibiting specificities for sera from individuals at the initial infection (T0) stage and five reactive to both T0 and post-treatment (30D) sera. Subsequently, 19 peptides were subjected to further validation through molecular weight assessment and synthesized for ELISA testing. The multi-peptide pool demonstrated a reactivity frequency of 54.5 % in infected individuals, which surpassed the reactivity frequencies observed for individual peptides. The six peptides exhibiting the highest reactivity were subsequently analyzed according to infection intensity. The multi-peptide pool exhibited the highest reactivity (65.2 %) in low-intensity cases. ROC curve analysis indicated that Peptide 15 demonstrated the highest sensitivity (78.79 %) and specificity (87.5 %), while the multi-peptide pool exhibited 67.65 % sensitivity and 81.82 % specificity. These findings highlight the potential of peptide-based diagnostics to enhance the detection and control of schistosomiasis.

Constructing and identifying an eighteen-gene tumor microenvironment prognostic model for non-small cell lung cancer

BackgroundThe tumor microenvironment (TME) plays a crucial role in tumorigenesis and tumor progression. This study aimed to identify novel TME-related biomarkers and develop a prognostic model for patients with non-small-cell lung cancer (NSCLC).MethodsAfter downloading and preprocessing data from The Cancer Genome Atlas (TCGA) data portal and Gene Expression Omnibus (GEO) datasets, we classified the molecular subtypes using the “NMF” R package. We performed survival analysis and quantified immune scores between clusters. A Cox proportional hazards model was then constructed, and its formula was produced. We assessed model performance and clinical utility. A prediction nomogram was also constructed and validated. Additionally, we explored the potential regulatory mechanisms of our TME gene signature using Gene Set Enrichment Analysis (GSEA).ResultsFrom data processing and univariate Cox regression analysis, 57 TME-related prognostic genes were identified, and two significantly distinct clusters were established. Using Cox regression and Lasso regression, an 18-gene TME-related prognostic model was developed. Patients were stratified into high- and low-risk groups based on the risk score, with survival analysis showing that the low-risk group had significantly better outcomes than the high-risk group (P < 0.01). ROC curve analysis demonstrated strong predictive performance, with 1-year, 3-year, and 5-year AUC values ranging from 0.654 to 0.702 across different cohorts. The model accurately predicted survival outcomes across subgroups with varying clinical features, and its predictive accuracy was validated through a nomogram.ConclusionsWe developed a prognostic model based on TME-related genes in NSCLC. Our 18-gene TME signature can effectively predict the prognosis of NSCLC with high accuracy.