Combination Of Markers Research Articles

Quantitative CT features on admission combined with laboratory biomarkers for predicting severe acute pancreatitis

To assess the association of quantitative computed tomography (CT) features on admission with acute pancreatitis (AP) severity, and to explore the performance of combined CT and laboratory markers for predicting severe AP (SAP). Data from 208 AP patients were reviewed retrospectively. Pancreas volume, the area of extrapancreatic inflammation, extrapancreatic fluid collection volume, and number were calculated based on CT images on admission. Laboratory biomarkers within 24 h of admission were collected. Interobserver agreement for CT measurements was measured by calculating interclass correlation coefficient (ICC). The associations of quantitative CT features with AP severity were evaluated. Predictive models for SAP were constructed based on CT and laboratory markers. Performances of single marker and the models were evaluated using receiver operating characteristic (ROC) curve and area under the ROC curve (AUC). Pancreas volume, area of extrapancreatic inflammation, extrapancreatic fluid collection volume, and number were significantly different between severe and non-severe AP groups. In predicting SAP, the AUCs of quantitative CT indicators ranged from 0.72 to 0.79; the AUCs of laboratory biomarkers were between 0.53 and 0.66. The combined model of area of extrapancreatic inflammation, serum calcium, and haematocrit yielded an AUC of 0.84, significantly higher than that of the laboratory model, single CT, or laboratory marker. Interobserver agreements for quantitative CT indicators were excellent, with ICC ranging from 0.91 to 0.98. Quantitative CT features on admission were significantly associated with AP severity; the combination of extrapancreatic inflammation area, serum calcium, and haematocrit could be taken as a new method for predicting SAP.

Combined score of Y chromosome loss and T-cell infiltration improves UICC based stratification of esophageal adenocarcinoma.

Staging, especially clinical lymph node staging in esophageal adenocarcinoma has only moderate sensitivity and specificity. Therefore, we evaluated combined molecular markers to predict prognosis. 890 tumor tissue samples were obtained from patients who underwent surgery for esophageal adenocarcinoma with curative intent. These were stained by tissue micro array for 48 markers which are associated with tumorigenesis and correlated with clinical data (TNM-staging, overall survival) by multivariate Cox regression. Two markers (preserved Y chromosome and high grade of (CD3+) T-cell infiltration) were found to be significantly and independently associated with better overall survival. We formed a score (called CY score) from the two markers. The more markers are positive and thus the higher the score (ranging from 0 to 2), the better the overall survival, independently of UICC. Moreover, we developed a combination score of the UICC and CY score based on cluster analysis. Patients with a UICC stage of III with the presence of both traits (CY=2) can be assigned to a better prognosis group (group II), whereas patients with a UICC stage of I without both traits (CY=0) must be assigned to a worse prognosis group (group II). Therefore, patients in stage I with adverse molecular signature might benefit of multimodal therapy. In summary, the CY score adds prognostic information to the UICC stage based on tumor biology in esophageal adenocarcinoma and warrants further evaluations in independent clinical cohorts.

Integrating fecal pollution markers and fluorescence analysis for water quality assessment of urban river

Human fecal contamination in urban rivers poses significant health risks, but their potential connections with other substances like dissolved organic matter (DOM) remain underexplored. In this study, five fecal pollution markers related to fecal Bacteroides or human fecal contamination (AllBac, HF183, BacH, Hum2, and Hum163) and DOM along an urban river were analyzed using quantitative polymerase chain reaction (qPCR) and three-dimensional excitation-emission (3D EEM) fluorescence spectrometry. All five markers were detected with average absolute abundance ranging from 2.51 to 6.28 lg gene copies/100 mL, showing a progressive increase along the river (R2 = 0.29–0.92, p < 0.05). Parallel factor analysis identified three dominant DOM components (humic acid-like, fulvic acid-like, and protein-like), with strong positive correlations between protein-like components and all fecal markers (R2 = 0.59–0.66, p < 0.001). Both fecal and DOM distributions consistently showed significant differences between upstream and downstream areas (p < 0.001), suggesting their complementary assessment. While DOM was more sensitive to environmental variables such as rainfall, rubber dam, and tidal dynamic, the combination of fecal pollution markers and 3D EEM analysis allowed a more comprehensive assessment of contamination levels, mitigating potential biases caused by the influence of multiple factors on a single method. Furthermore, due to the strong correlation between protein-like and fecal markers in the DOM, 3D EEM can be used as a pre-detection means for qPCR detection, reducing testing time and costs.

Combining hypothesis-driven ECG indices with machine learning improves ventricular arrhythmic risk prediction in a low-risk population

Abstract Background Life-threatening ventricular arrhythmias (LTVA) are a leading cause of mortality, but early identification of high-risk individuals remains a major challenge. An ECG index, TMV (T-wave morphology variations), predicts LTVA in 51,794 individuals without known cardiovascular disease from the UK Biobank (UKB) within a 10-year follow up (cohort 1), with an area under the ROC curve (AUC) of 0.558 and a hazard ratio (HR) of 1.57. Machine learning on the ECG has shown a high accuracy in detecting patients with cardiovascular disease, but its LTVA predictive value in a low-risk population and comparisons with hypothesis-driven risk markers, like TMV, is unknown. Purpose We tested the LTVA predictive value of a score combining a multi-layer convolutional neural network (CNN) model and TMV in individuals without known cardiovascular disease. Methods Using UKB we split the individuals from cohort 1 into training (90%) and internal test (10%) sets (Figure 1). In the training set, we applied 10-fold cross validation to train a multi-layer CNN with an attention layer, where the input was a 15-second ECG at rest (lead I), and the output was occurrence (or not) of LTVA within a 10-year follow-up. We used 10-second ECG data (lead I) from an independent cohort of 32,209 individuals without cardiovascular disease from UKB (cohort 2) as an external test set (median follow-up was 3.4 years), where we also calculated TMV. We next combined them into a score (weighted by their relative contribution to LTVA in a logistic regression). The AUC, and Cox regression HRs were calculated to estimate the performance of the CNN, TMV and the combined score. Results In cohort 1, 217 subjects had a LTVA during the follow-up period. In the internal test set, the AUC of the CNN was 0.707. In the external test set (60 LTVA events during the follow-up period), the CNN’s prediction and TMV led to AUCs of 0.610 and 0.604, respectively. Interestingly, the CNN’s prediction and TMV were not correlated (ρ = 0.005), and the combined score led to an AUC of 0.627. We set a threshold at the score value that maximised sensitivity and specificity, and survival analyses showed a HR of 3.007 (P &amp;lt; 0.0001) for individuals in the score+ (score &amp;gt; threshold) versus those in the score- (score &amp;lt; threshold) group, after adjusting for age and gender (Figure 2). The continuous score also predicted LTVA independently from age and gender. Conclusions A CNN-based model predicts LTVA in a low-risk population independently from TMV, a strong ECG risk predictor derived from knowledge on the underlying electrophysiology. When TMV and the CNN are combined into a score, the LTVA risk stratification improves, independently from age and gender. Our findings support the combination of hypothesis-based risk markers and CNN approaches to optimise LTVA prediction in a low-risk population.Study designSurvival curves

Combination of leucine-rich alpha-2 glycoprotein and fecal markers detect Crohn's disease activity confirmed by balloon-assisted enteroscopy.

Endoscopic activity confirmed by enteroscopy is associated with poor clinical outcome in Crohn's disease (CD). We investigated which of the existing biomarkers best reflects endoscopic activity in CD patients including the small bowel, and whether their combined use can improve accuracy. One hundred and four consecutive patients with ileal and ileocolonic type CD who underwent balloon-assisted enteroscopy (BAE) from October 2021 to August 2022 were enrolled, with clinical and laboratory data prospectively collected and analyzed. Hemoglobin, platelet count, C-reactive protein, leucine-rich alpha-2 glycoprotein (LRG), fecal calprotectin, and fecal hemoglobin all showed significant difference in those with ulcers found on BAE. LRG and fecal calprotectin showed the highest areas under the curve (0.841 and 0.853) for detecting ulcers. LRG showed a sensitivity of 78% and specificity of 80% at a cutoff value of 13 μg/mL, whereas fecal calprotectin showed a sensitivity of 91% and specificity of 67% at a cutoff value of 151 μg/g. Dual positivity for LRG and fecal calprotectin, as well as LRG and fecal hemoglobin, both predicted ulcers with an improved specificity of 92% and 100%. A positive LRG or fecal calprotectin/hemoglobin showed an improved sensitivity of 96% and 91%. Positivity for LRG and either of the fecal biomarkers was associated with increased risk of hospitalization, surgery, and relapse. The biomarkers LRG, fecal calprotectin, and fecal hemoglobin can serve as noninvasive and accurate tools for assessing activity in CD patients confirmed by BAE, especially when used in combination.

Clinicopathological features of olfactory carcinoma

Objective: To investigate the clinicopathological features and differential diagnosis of olfactory carcinoma (OC). Methods: Twenty-one cases of sinonasal tumors, including those initially diagnosed as olfactory neuroblastoma (ONB) and those with uncertain diagnosis, were collected from the Department of Pathology, the First Affiliated Hospital of University of Science and Technology of China (Anhui Provincial Hospital) from January 2016 to August 2022, among which 3 cases were reclassified as OC. The clinicopathological features were investigated, and the remaining 18 cases were used as control. Results: Of the three OC patients, 2 were male and 1 was female, with an average age of 57 years ranging from 35 to 74 years. Microscopically, the tumor cells were arranged in solid, nested or lobulated patterns with occasional palisading around the solid nests. The stroma was highly vascular with focal neurofibrillary areas. There were prominent rosettes or pseudorosettes formation. The tumor cells were mainly ovoid to spindly with scant to moderate amount of cytoplasm, one or several small nucleoli, and fine chromatin content. Brisk mitotic figures were seen. In all 3 cases of OC, there were scanty atypical glands and some were ciliated. Immunohistochemically, at least one epithelial marker and neuroendocrine marker were diffusely expressed in the tumor. Some of the tumor cells were positive for p40 and p63, and the sustentacular cells showed the expression of S-100 protein. All cases tested were negative for NUT, CD99 and desmin, with intact expression of SMARCA4 (BRG1) and SMARCB1 (INI-1). Ki-67 proliferation index varied from 20% to 80%. Follow-up after 16-18 months showed no mortality with tumor recurrence from 1 patient after 16 months. Conclusion: OC is a rare sinonasal tumor with neuroepithelial differentiation, its histomorphology is diverse, and the combination of immunohistochemical markers is essential for appropriate diagnosis.

Abstract 15497: Association of Blood Cell-Based Inflammatory Markers and C-Reactive Protein With Mortality in Acute Coronary Syndrome Patients: Analysis From the ATLAS ACS-TIMI 46 Trial

Background: Inflammation has been implicated in the pathogenesis of acute coronary syndrome (ACS). The comparative performance of blood cell-based inflammatory markers in mortality prediction among ACS patients remains unclear. Methods: In this multinational, double-blind, phase 2 trial, patients with recent ACS were randomized to receive rivaroxaban or a placebo. The relationship of inflammatory markers (including neutrophil-to-lymphocyte ratio [NLR], platelet-to-lymphocyte ratio [PLR], lymphocyte-to-monocyte ratio [LMR], systemic immune-inflammation index [SII], and C-reactive protein [CRP]) with 6-month all-cause mortality was assessed using logistic regression, and the optimal cut points were determined by the Youden index. The discriminative performance of the combinations of inflammatory markers was compared by the c statistic. Results: A total of 2918 patients were analyzed. A higher risk of mortality was observed in patients with elevated NLR (≥3.691; OR=3.732; 95% CI=1.930 to 7.217; p&lt;0.0001), elevated PLR (≥14.18; OR=2.915; 95% CI=1.447 to 5.873; p=0.0028), decreased LMR (&lt;3.125; OR=3.179; 95% CI=1.643 to 6.152; p=0.0006), elevated SII (≥875.7; OR=2.494; 95% CI=1.285 to 4.840; p=0.0069), or elevated CRP (≥26 mg/L; OR=3.435; 95% CI=1.771 to 6.662; p=0.0003). The discriminative capacity of CRP plus NLR (c statistic=0.7326) was greater than CRP or NLR alone (c statistic=0.6444 and 0.6443) but not significantly affected by further inclusion of PLR, PLR plus SII, or PLR plus SII plus LMR into the model (c statistic=0.7430, 0.7412, and 0.7406) (Figure 1). Conclusion: NLR calculated from differential white blood cell count provides incremental prognostic value to CRP in predicting mortality among ACS patients. Future studies may consider NLR and CRP conjunctively in constructing mortality risk assessment models.

Practical application of the CA-62 tumor marker in the initial diagnosis of oncological disease of epithelial origin: assistance to the doctor in interpreting the results

Aim. Demonstration the possibility of practical application of the highly sensitive tumor marker CA-62 in the initial diagnosis in asymptomatic patients with suspected cancer and/or the presence of pathological changes in instrumental studies, as well as describe the criteria for interpreting the results to help the doctor make a decision.&#x0D; Materials and methods. The article used the results and conclusions of blind clinical trials conducted to detect early stages of breast cancer (BC), prostate cancer (PC), colorectal cancer (CRC) and non-small cell lung cancer using the CA-62 tumor marker and other tumor markers. Statistical analysis was performed using the MedCalc program (MedCalc Software Ltd, Belgium). Diagnostic efficiency was assessed in terms of sensitivity, specificity, test accuracy, PPV and NPV, ROC analysis. The significance level was taken as p0.001.&#x0D; Results. The use of the standard cut-off value of 5000 U/ml of the CA-62 tumor marker makes it possible to achieve 97% sensitivity with 95% specificity in stage I BC. The combination of tumor markers CA-62 and CA 15-3 allows achieving 100% specificity in differentiation of BC and benign breast hyperplasia. The use of the CA-62 marker (6500 U/ml) in the gray zone of PSA 2.510 ng/ml improves the accuracy of detecting PC in biopsy from 35 to 93.1% with 90% sensitivity and 97% specificity. The use of a combination of tumor markers (CA-625000 U/ml, CYFRA 21-12.5 ng/ml and CEA5 ng/ml) will allow the doctor to improve the efficiency of differentiating lung cancer from chronic obstructive pulmonary disease. The combined use of markers (CEA3.5 ng/ml) and (CA-625000 U/ml) achieves 100% specificity with 97% sensitivity in detecting early stages of CRC.&#x0D; Conclusion. The article shows the possibilities of using the CA-62 marker, as well as new algorithms for the detection and differentiation of early stages of BC, PC, non-small cell lung cancer and CRC and benign neoplasms using the CA-62 marker in primary diagnosis. The use of the CA-62 tumor marker or its combination with other diagnostic methods can be a useful strategy for a comprehensive assessment of the risk of malignant neoplasms and increasing the diagnostic sensitivity of detecting early stages of cancer.

Human Adult Long-Term Repopulating Hematopoietic Stem Cells Can be Purified By Surface cMPL Expression

Simple combinations of markers that reliably demarcate human long-term repopulating hematopoietic stem cells (LT-HSCs) would facilitate our understanding of their unique molecular state and the development of stem cell-based therapeutics. The complex CD34+CD38-CD45RA-CD90+CD49f+ phenotype is now routinely accepted to define a subset of cord blood CD34+ cells enriched in LT-HSCs (Notta, Science 2011). The same phenotype with the addition of rhodamine can enrich human LT-HSCs within mobilized peripheral blood (MPB) CD34+ cells, but lower stem cell enrichment is observed (Huntsman, Blood 2015). The hematopoietic cytokine thrombopoietin (TPO) and its receptor cMPL act as primary regulators of HSC function. In recent clinical studies, the synthetic TPO agonist eltrombopag was shown to improve long-term trilineage hematopoiesis in patients with immune aplastic anemia, providing evidence that activation of cMPL receptor stimulates residual multipotent LT-HSCs within the bone marrow (BM). Building on these observations, we hypothesized that cMPL might also be a relevant marker to delineate LT-HSC activity within human adult CD34+ cell populations and provide the basis for a novel LT-HSC purification scheme. To assess the utility of surface cMPL expression for purification of human adult LT-HSCs, we first performed cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) of human MPB CD34+ cells from a healthy volunteer. CITE-seq was conducted with antibodies designed to react with human cMPL receptor and previously described HSC epitopes (CD34, CD38, CD90, CD45RA, and CD49f). We identified 7 distinct clusters in dimension-reduction (UMAP) analysis. By confirming expression levels of HSPC gene signatures and HSC surface markers, such as CD38, we assigned each CD34+ cell cluster to a distinct HSPC subpopulation, including a single LT-HSC population (cluster 2) (Fig A). Notably, CD34+ cell subsets expressing higher levels of surface cMPL expression were highly enriched in transcriptionally defined HSC population (cluster 2) and consistently co-expressing the known human LT-HSC phenotypic markers, including lower levels of surface CD38 and CD45RA expression and higher levels of surface CD90 and CD49f expression (Fig B). To determine whether surface cMPL expression can enrich functional LT-HSCs, we next performed serial xenotransplantation assays. We used fluorescence-activated cell sorting to partition human MPB CD34+ cells into cMPL high (top 10%) and cMPL low (bottom 10%) populations, and transplanted these cells into immunodeficient NBSGW mice. Serial peripheral blood (PB) sampling of primary xenografted mice revealed a striking difference in patterns of hematopoietic reconstitution over time between the two groups. In mice transplanted with cMPL high cells, human cell chimerism increased gradually throughout the 16-week engraftment period, while a progressive decline in engraftment was observed in the cMPL low group. Notably, mean human cell engraftment within the PB, BM and spleen of mice transplanted with cMPL high cells was 209-fold (p &amp;lt; 0.01), 37-fold (p &amp;lt; 0.0001) and 283-fold (p &amp;lt; 0.001) higher than mean human cell chimerism in the cMPL low group at 16 weeks post-transplantation, respectively. These data suggest that cMPL high and cMPL low populations are distinctly enriched in LT-HSCs and hematopoietic progenitors, respectively. Next, to quantitatively compare the frequency of self-renewing LT-HSCs within the cMPL high and cMPL low HSPC subsets, human CD45+ cells obtained from the BM of primary mice were injected into secondary NBSGW mice at limiting dilution and BM engraftment was measured at 16 weeks post-transplantation (total period of engraftment: 32 weeks). After accounting for engraftment parameters (i.e., cell dose and engraftment levels) in both primary and secondary mice, extreme limiting dilution analysis computed self-renewing LT-HSC frequencies of 1 in 1,267 within the cMPL high CD34+ cell population, and 1 in 149,010 in the cMPL low CD34+ cell fraction, representing a 116-fold enrichment of LT-HSCs using cMPL as a single marker purification strategy. Collectively, these data suggest that cMPL expression can effectively delineate LT-HSCs in human adult CD34+ HSPCs and thus serve as an additional relevant marker for the development of human adult HSC targeting therapeutics.

One Tube 23 Color Full Spectral Flow Cytometry Panel in Detecting Minimal Residual Disease in Pediatric B-Cell Acute Lymphoblastic Leukemia

Introduction Minimal residual disease (MRD) is a normalized tool for risk stratification in the treatment of pediatric acute lymphoblastic leukemia (ALL) and has been introduced into many standardized chemotherapy regimens. Flow cytometry (FC) plays an important role in the monitoring of MRD. However, FC-MRD can't reliably detect residual leukemic cells below level of 0.01% in real clinical scenarios and some patients with negative MRD relapsed, suggesting the current used set of markers are not sensitive enough or specific enough. Published studies has shown that more markers with more reliable combination of antibodies may help improve the sensitivity and specificity of FC-MRD. Spectral multicolor flow cytometry (SMFC) has shown an advantage over traditional FC that more fluorescent markers could be applied simultaneously and more complex marker combinations could be exploited to distinguish leukemic blasts from normal B cell precursors with high specificity. Here we designed a SMFC-based panel of 26 markers with 23 fluorescent colors in one tube to monitor B-ALL MRD. Method The one-tube 23-color panels was designed according to previously published studies and our clinical experience based on standardized EuroFlow 8-color MRD panel. All the leukemia-associated immunophenotypes (LAIPs) were defined based on its deviation from hematogones. For CD10, CD19, CD22, CD34, CD58, CD73, CD86, CD123, CD200and CD304, the overexpression was considered as LAIP, while the under-expression was considered as LAIP for CD24, CD38, CD45 and CD81. Asynchronous co-expression of CD34 and CD20, CD34 and CD21 were also included. The aberrant cross-lineage expression was taken as LAIP for CD2, CD56, CD65, CD15, CD13, CD33, CD66c, NG2 and CD133. For CD44, under-expression or overexpression can both be considered as LAIP. To verify the effectiveness of the panel, 317 bone marrow samples from 317 patients with B-ALL diagnosed between 2009 to 2014 at the Shanghai Children's Medical Center (SCMC) were included. These samples were collected at day 19 to 283 (median: day 35), with 213 (67.19%) collected at around day 35, which was a regular time point to monitor MRD and to readjust the risk stratification. The results were compared with those of conventional 8-color FC-MRD. Results The limit of blank (LOB), limit of detection (LOD), and lower limit of quantitation (LLOQ) were firstly determined, the results showed reproducible sensitivity up to 0.001% (1-in-10 5) after acquisition of 4.8 million cells for 23-color panel. The 8-color and 23-color MRD panels showed high correlation of the quantitation of MRD (r 2=0.80, p&amp;lt;0.0001). Among cases of discordant between 8-color MRD negative (with cutoff &amp;lt;0.01%) and 23-color MRD negative (with cutoff &amp;lt;0.001%), relapse only occurred in patients with 23-color MRD positive and 8-color MRD negative, rather than patients with 23-color MRD negative and 8-color MRD positive, suggesting a higher sensitivity and specificity for 23-color MRD assay (See Figure). Patients with detectable MRD by either 8-color or 23-color had a significantly higher incidence of relapse (CIR, p&amp;lt;0.05) and shorter event free survival (EFS, p&amp;lt;0.05). Positive 23-color MRD seemed to be an even stronger factor impacting CIR and EFS. Compared to patients with 8-color MRD negative and 23-color MRD positive, patients with 8-color MRD positive and 23-color MRD negative had a significantly lower CIR (p&amp;lt;0.05) and a better EFS (p=0.068). Patients with positive 23-color MRD lower than 0.01% showed a trend towards poorer EFS and OS (p=0.083% and p=0.061%, respectively) compared to patients with 23-color MRD negative. Conclusion Based on these evidences, SMFC-based one-tube 23-color MRD panel for B-ALL was convenient and maneuverable with higher sensitivity and specificity compared to conventional 8-color FC-MRD panel. It would be a promising method to improve the risk stratification.

ЦИФРОВЫЕ РЕСУРСЫ В ПРЕДИКЦИИ ПРЕЭКЛАМПСИИ И ЗАДЕРЖКИ РОСТА ПЛОДА

Abstact. Introduction. Preeclampsia and fetal growth restriction are pregnancy complications related to Great Obstetrical Syndromes and having a similar pathogenesis. No antipathogenetic therapy methods have been found for both pathologies, but there is a means of prevention: Acetylsalicylic acid. The drug is effective only in high-risk pregnant women; therefore, various models are being developed to predict preeclampsia and fetal growth restriction, including digital models. They aim to help select patients who need that prophylaxis. Aim. This study is aiming to create a digital model for the early prediction of preeclampsia, based on the patient’s electronic medical card. Materials and Methods. The investigation involved 231 pregnant women. An algorithm was developed for the early prediction of preeclampsia and fetal growth restriction, based on detecting a combination of systemic and local hemodynamic markers: High variability of blood pressure between visits (long-term variability) and high resistance of blood flow in uterine arteries. Long-term (intervisit) variability of blood pressure is calculated for each trimester: First, the arithmetic mean is calculated among the values of systolic blood pressure at successive visits; second, the standard deviation is computed based on the result. Uterine arteries are checked using Doppler ultrasound technology at 11-13 weeks of gestation: Resistivity of blood flow (peripheral resistivity) in the right and left uterine arteries is assessed. Results and Discussion. For this new prediction algorithm, a digital model was developed, the ECAPP program (registration certificate No. 2018660666 – Electronic Prenatal Record with assessing the risk of developing preeclampsia based on blood pressure variability and uterine blood flow resistance). Conclusions. The IT resource presented has a potential for the effective early prediction of preeclampsia, as well as for predicting fetal growth restriction. Keywords: preeclampsia, fetal growth restriction, prognosis, digital model.

Identifying tumor markers-stratified subtypes (CA-125/CA19-9/carcinoembryonic antigen) in cervical adenocarcinoma.

There is a lack of research evaluating the effect of tumor markers for prognosis in cervical adenocarcinoma. We aimed to develop and validate a preoperative tumor-marker-based model including clinicopathological factors to clarify the prognostic value of endocervical adenocarcinoma. A total of 572 patients with cervical adenocarcinoma who were staged at the International Federation of Gynecology and Obstetrics (FIGO) IA-IIA were reviewed retrospectively. Preoperative serum carcinoembryonic antigen (CEA), carbohydrate antigen (CA)-125 and CA19-9 levels were measured. The survival and recurrence patterns were analyzed according to the tumor-marker-related stratification. The predictive values of biomarkers and clinical variables were assessed with Cox regression and competing risk models. Patients with elevated preoperative tumor markers had evidently poor overall survival and recurrence-free survival. The triple-elevated tumor marker (TETM) subgroup had the worst overall survival and progression-free survival than the triple-negative tumor marker (TNTM) subgroup and the single-elevated tumor marker (SETM) subgroup. The most important predictors for overall survival were elevated tumor markers, FIGO-stage, tumor differentiation, lymphovascular space invasion (LVSI) and lymph nodes metastasis. The most important predictors for recurrence-free survival were elevated tumor markers, FIGO-stage, tumor differentiation, LVSI and deep stromal invasion. Stratified analysis showed that elevated CA-125 and CA19-9 were significantly associated with postoperative distant metastasis. A decision curve analysis confirmed that a combination of tumor markers as predictors significantly outperformed the other common predictors used (FIGO-stage, intermediate and high-risk factors, tumor differentiation, lymph nodes). Elevated preoperative serum CEA, CA-125, and CA19-9 levels exhibited poor overall survival and recurrence-free survival in cervical adenocarcinoma patients. Combined preoperative serum CA-125 and CA19-9 independently predicted distant metastasis in patients with endocervical adenocarcinoma.

Integrating genome-wide association study into genomic selection for the prediction of agronomic traits in rice (Oryza sativa L.)

Accurately identifying varieties with targeted agronomic traits was thought to contribute to genetic selection and accelerate rice breeding progress. Genomic selection (GS) is a promising technique that uses markers covering the whole genome to predict the genomic-estimated breeding values (GEBV), with the ability to select before phenotypes are measured. To choose the appropriate GS models for breeding work, we analyzed the predictability of nine agronomic traits measured from a population of 459 diverse rice varieties. By the comparison of eight representative GS models, we found that the prediction accuracies ranged from 0.407 to 0.896, with reproducing kernel Hilbert space (RKHS) having the highest predictive ability in most traits. Further results demonstrated the predictivity of GS is altered by several factors. Moreover, we assessed the method of integrating genome-wide association study (GWAS) into various GS models. The predictabilities of GS combined peak-associated markers generated from six different GWAS models were significantly different; a recommendation of Mixed Linear Model (MLM)-RKHS was given for the GWAS-GS-integrated prediction. Finally, based on the above result, we experimented with applying the P-values obtained from optimal GWAS models into ridge regression best linear unbiased prediction (rrBLUP), which benefited the low predictive traits in rice.

Cognitive and motor profiles as prodromal markers in predicting phenoconversion and phenotype in isolated REM sleep behavior disorder

ObjectiveTo determine the clinical markers based on cognitive and motor profiles in predicting phenoconverion and phenotype in isolated rapid eye movement sleep behavior disorder (iRBD). Methods45 iRBD patients and 25 healthy controls were included in the follow-up study. All participates received comprehensive evaluations of cognitive, motor and autonomic function at baseline. Positive phenoconversion were identified according to standard diagnostic criteria during follow-up. Results21 iRBD patients displayed phenoconversion in a mean follow-up of 2.9 ± 1.6 years, with 14 presenting motor phenotype and 7 cognitive phenotype. In iRBD, visuospatial, memory, attention-executive function, information processing speed, and motor function predicted phenoconversion, with the combination of Trail Making Test (TMT) and Alternate-tap Test (ATT) performing best (sensitivity = 95.0 %, specificity = 75.0 %); attention-executive function, information processing speed, and motor function predicted motor phenotype conversion, with the combination of TMT and ATT performing best (sensitivity = 100 %, specificity = 66.7 %); visuospatial, memory, and attention-executive function predicted cognitive phenotype conversion, with TMT performing best (sensitivity = 83.3 %, specificity = 91.7 %). Furthermore, individuals with lower z-scores of TMT, Symbol Digit Modalities Test, and ATT than the established cutoff values in iRBD exhibited a significantly higher risk for phenoconversion at follow-up (HR = 2.98, 9.53, 11.68; respectively). ConclusionsIn iRBD, the attention-executive and motor function served as optimum combined markers in predicting phenoconversion and motor phenotype, whereas the attention-executive function performed best in predicting cognitive phenotype. Poor attention-executive function, information processing speed and motor function in iRBD independently increased the risk of phenoconversion.

Anoectochilus zhongshanensis (Orchidaceae), a new species from Guangxi, China

A new species of Anoectochilus (Orchidaceae) from Guangxi, China, A. zhongshanensis, is described here, which was identified based on phylogenetic studies adopting combined plastid markers (rbcL-matK-trnL-F), morphological observation and chemical analysis. Molecular phylogenetic results support the systematic status of A. zhongshanensis as a new species in Anoectochilus genus. Morphologically, this new species is similar to A. zhejiangensis and A. malipoensis, but differs by its characteristic labellum and column, including the hastate or scalpel-shaped lobes of epichile, forward curved and pinnately divided cristate lobes at both sides of the mesochile and inverted triangle column wings. Furthermore, HPLC-ELSD analysis of these three species revealed the interesting chemotaxonomic difference that the principle and characteristic lactone glycoside in this new species was kinsenoside, rather than its diastereoisomer, goodyeroside A, a major glycoside in A. zhejiangensis and A. malipoensis.

Expanding the scope of methylation-sensitive restriction enzyme (MSRE) PCR for forensic identification of body fluids through the novel use of methylation-dependent restriction enzymes (MDRE) and the combination of autosomal and Y-chromosomal markers

Methylation-sensitive/-dependent restriction enzyme (MSRE/MDRE) PCR can be performed to detect hypomethylated or hypermethylated CpG sites. With the combined use of different tissue-specific CpG markers, MSRE/MDRE-PCR leads to tissue-specific methylation patterns (TSMPs), enabling the correlation of DNA samples to their source tissue. MSRE/MDRE assays can use the same platform as forensic STR typing and offer many advantages in the field of forensic body fluid detection. In the present study, we aimed to establish MSRE assays for the detection of blood, saliva, vaginal secretion, and semen, using markers from literature and from our own database search. We designed two different MSRE test-sets, which include two novel Y-chromosomal non-semen markers, and enable differentiation between female and male non-semen samples. Furthermore, we established an MSRE/MDRE semen approach, which includes only Y-chromosomal non-semen and semen markers. This Y-semen multiplex PCR utilizes the novel combination of the methylation-sensitive enzyme SmaI and the methylation-dependent enzyme GlaI, which enables more sensitive detection of male body fluids within male/female DNA mixtures. Our validation tests confirmed that MSRE/MDRE assays exhibit high sensitivity, similar to that of STR typing.

Combining Mass Cytometry Data by CyTOFmerge Reveals Additional Cell Phenotypes in the Heterogeneous Ovarian Cancer Tumor Microenvironment: A Pilot Study.

The prognosis of high-grade serous ovarian carcinoma (HGSOC) is poor, and treatment selection is challenging. A heterogeneous tumor microenvironment (TME) characterizes HGSOC and influences tumor growth, progression, and therapy response. Better characterization with multidimensional approaches for simultaneous identification and categorization of the various cell populations is needed to map the TME complexity. While mass cytometry allows the simultaneous detection of around 40 proteins, the CyTOFmerge MATLAB algorithm integrates data sets and extends the phenotyping. This pilot study explored the potential of combining two datasets for improved TME phenotyping by profiling single-cell suspensions from ten chemo-naïve HGSOC tumors by mass cytometry. A 35-marker pan-tumor dataset and a 34-marker pan-immune dataset were analyzed separately and combined with the CyTOFmerge, merging 18 shared markers. While the merged analysis confirmed heterogeneity across patients, it also identified a main tumor cell subset, additionally to the nine identified by the pan-tumor panel. Furthermore, the expression of traditional immune cell markers on tumor and stromal cells was revealed, as were marker combinations that have rarely been examined on individual cells. This study demonstrates the potential of merging mass cytometry data to generate new hypotheses on tumor biology and predictive biomarker research in HGSOC that could improve treatment effectiveness.

FCM marker importance for MRD assessment in T-cell acute lymphoblastic leukemia: An AIEOP-BFM-ALL-FLOW study group report.

T-lineage acute lymphoblastic leukemia (T-ALL) accounts for about 15% of pediatric and about 25% of adult ALL cases. Minimal/measurable residual disease (MRD) assessed by flow cytometry (FCM) is an important prognostic indicator for risk stratification. In order to assess the MRD a limited number of antibodies directed against the most discriminative antigens must be selected. We propose a pipeline for evaluating the influence of different markers for cell population classification in FCM data. We use linear support vector machine, fitted to each sample individually to avoid issues with patient and laboratory variations. The best separating hyperplane direction as well as the influence of omitting specific markers is considered. Ninety-one bone marrow samples of 43 pediatric T-ALL patients from five reference laboratories were analyzed by FCM regarding marker importance for blast cell identification using combinations of eight different markers. For all laboratories, CD48 and CD99 were among the top three markers with strongest contribution to the optimal hyperplane, measured by median separating hyperplane coefficient size for all samples per center and time point (diagnosis, Day 15, Day 33). Based on the available limited set tested (CD3, CD4, CD5, CD7, CD8, CD45, CD48, CD99), our findings prove that CD48 and CD99 are useful markers for MRD monitoring in T-ALL. The proposed pipeline can be applied for evaluation of other marker combinations in the future.

Assessment of MYC and TERT copy number variations in lung cancer using digital PCR

ObjectiveLung cancer is the second most frequent cancer type and the most common cause of cancer-related deaths worldwide. Alteration of gene copy numbers are associated with lung cancer and the determination of copy number variations (CNV) is appropriate for the discrimination between tumor and non-tumor tissue in lung cancer. As telomerase reverse transcriptase (TERT) and v-myc avian myelocytomatosis viral oncogene homolog (MYC) play a role in lung cancer the aims of this study were the verification of our recent results analyzing MYC CNV in tumor and non-tumor tissue of lung cancer patients using an independent study group and the assessment of TERT CNV as an additional marker.ResultsTERT and MYC status was analyzed using digital PCR (dPCR) in tumor and adjacent non-tumor tissue samples of 114 lung cancer patients. The difference between tumor and non-tumor samples were statistically significant (p < 0.0001) for TERT and MYC. Using a predefined specificity of 99% a sensitivity of 41% and 51% was observed for TERT and MYC, respectively. For the combination of TERT and MYC the overall sensitivity increased to 60% at 99% specificity. We demonstrated that a combination of markers increases the performance in comparison to individual markers. Additionally, the determination of CNV using dPCR might be an appropriate tool in precision medicine.

Action potential morphology affects T-wave symmetry (simulation study)

BackgroundAssessing T-wave symmetry in addition to QT subintervals measurements can provide novel independent data about ventricular repolarization abnormalities linked with arrhythmogenesis. However, the causes of the changes of T-wave symmetry are not completely understood. In silico studies showed that the more symmetrical T-waves were associated with shorter action potential duration (APD) and larger dispersion of ventricular repolarization (DOR). The aim of present simulation was to study the association between T-wave symmetry and action potential (AP) shape. MethodsECGs were simulated using a cellular automata model shaped as a ventricular wall segment, and two biophysically-detailed models of ventricular AP – the rabbit and the human. The symmetry ratio (SR) was calculated as a T-wave onset-peak to peak-end area ratio. The individual and combined effects of APD, DOR and AP shape on SR were simulated. To study the effect of AP shape, different APs from triangulated to rectangular were simulated. ResultsThe simulations showed that AP shape along with APD and DOR contributes much to T-wave symmetry. APs with a flat phase 3 (triangulated) produced asymmetrical T-waves (SR ≥ 1.5) in all simulations, except the shortest APD range. APs with a rapid phase 3 (rectangular) were associated with more symmetrical T-waves (SR ≤ =1) both at the short and the long APDs. ConclusionSR marker in combination with the standard ECG parameters (QT interval, Tpeak-Tend interval) may be useful to identify the proarrhythmic triangulated AP shape.