Combination Of Markers Research Articles

Combined with prognostic nutritional index and IgM for predicting the clinical outcomes of gastric cancer patients who received surgery.

Although the survival rate of patients who undergo surgery for gastric cancer has greatly improved, still many patients have a poor prognosis. This retrospective study aimed to investigate the predictive ability of the PNI-IgM score, a combined prognostic nutritional index (PNI), and immunoglobulin M (IgM), on the prognosis of patients undergoing surgery for gastric cancer. 340 patients with gastric cancer who underwent surgery from January 2016 to December 2017 were selected. The PNI-IgM score ranged from 1 to 3: score of 1, low PNI (< 48.45) and low IgM (< 0.87); score of 2, low PNI and high IgM, or high PNI and low IgM; score of 3, high PNI and high IgM. We compared the differences in disease-free survival (DFS) and overall survival (OS) among the three groups, while univariate and multivariate analyses calculated prognostic factors for DFS and OS. In addition, the nomograms were constructed based on the results of multivariate analysis to estimate the 1-, 3- and 5-year survival probability. There were 67 cases in the PNI-IgM score 1 group, 160 cases in the PNI-IgM score 2 group, and 113 cases in the PNI-IgM score 3 group. The median survival times of DFS in the PNI-IgM score group 1, the PNI-IgM score group 2, and the PNI-IgM score group 3 were 62.20 months, not reached, and not reached, and 67.57 months vs. not reached vs. not reached in three groups for OS. Patients in the PNI-IgM score group 1 had a lower DFS than the PNI-IgM score group 2 (HR = 0.648, 95% CI: 0.418-1.006, P = 0.053) and the PNI-IgM score group 3 (HR = 0.337, 95% CI: 0.194-0.585, P < 0.001). In stratified analysis, PNI-IgM score 1 had a worse prognosis in the age < 60 years group and CA724 < 2.11 U/m group. PNI-IgM score is a novel combination of nutritional and immunological markers that can be used as a sensitive biological marker for patients with gastric cancer who undergo surgery. The lower the PNI-IgM score, the worse the prognosis.

Blood Glucose, Lactate and Platelet Count in Infants with Spontaneous Intestinal Perforation versus Necrotizing Enterocolitis-A Pilot Study.

The incidence of spontaneous intestinal perforation (SIP) increases up to 10% with decreasing gestational age (GA). We aimed to explore early biomarkers for predicting SIP in preterm infants. In this case-control study, neonates born at ≤34 weeks GA diagnosed with SIP were compared with GA and/or birth-weight-matched neonates diagnosed with necrotizing enterocolitis (NEC). Laboratory markers assessed prior and adjacent to the day of SIP or NEC diagnosis were evaluated. The cohort included 16 SIP and 16 matched NEC infants. Hyperlactatemia was less frequent in SIP than in NEC infants (12% vs. 50%, p = 0.02). The platelets count was lower in SIP than in NEC infants (p < 0.001). Glucose levels strongly correlated with lactate levels (p = 0.01) only in the NEC group. The odds of being diagnosed with SIP decreased as lactate levels increased (OR = 0.607, 95% CI: 0.377-0.978, p = 0.04). Our results suggest that a combination of laboratory markers, namely glucose and lactate, could help differentiate SIP from NEC at early stages so that, in the presence of an elevated blood glucose, an increase in blood lactate was associated with a decrease in the odds of being diagnosed with SIP.

TP53 Gain-of-Function Mutation is a Poor Prognostic Factor in High-Methylated Metastatic Colorectal Cancer

BackgroundNeither TP53 mutation nor DNA methylation status has been established as a biomarker alone of metastatic colorectal cancer. We analyzed the association between TP53 mutation functional subtypes and genome-wide DNA methylation status (GWMS) as combined prognostic markers. MethodsPatient clinical data were obtained from the TRICOLORE study, a randomized phase III trial. The TP53 mutations were classified into wild-type, gain-of-function (GOF) mutations, and non-gain-of-function (non-GOF) mutations. GWMS of the tumor tissues classified them into high-methylated colorectal cancer (HMCC) and low-methylated colorectal cancer (LMCC). Overall survival (OS) was compared based on these subgroups. ResultsOf the 209 patients, 60 (28.7%) were HMCC and 149 (71.3%) were LMCC, 35 (16.7%) were TP53 wild-type and 174 (83.3%) were TP53 mutants including 79 (45.4%) GOF mutations and 95 (54.6%) non-GOF mutations. The OS of the HMCC group was shorter than that of the LMCC group (median 25.3 vs. 40.3 months, P < .001, hazard ratio 1.87) in the total cohort. The combined subgroup analyses of GWMS and TP53 mutation subtypes showed that the HMCC/GOF group had significantly shorter OS than the HMCC/non-GOF group, the LMCC/GOF group, and the LMCC/non-GOF group (median 17.7; 35.3, 40.3, and 41.2 months, P = .007, P < .001, and P < .001, respectively), regardless of the primary tumor location. By the multivariate analysis, only HMCC (P = .009) was a poor prognostic factor in the GOF mutation group. ConclusionsTP53 GOF with HMCC is a newly identified poorest prognostic molecular subset in metastatic colorectal cancer.

Morpho-biochemical characterization and molecular marker based genetic diversity of pearl millet (Pennisetum glaucum (L.) R. Br.).

Pearl millet is a key food for millions living in semi-arid and arid regions and is a main diet for poorer populations. The genetic diversity existing in the pearl millet germplasm can be used to improve the micronutrient content and grain yield. Effective and organized exploitation of diversity at morphological and DNA levels is the strategy for any crop improvement program. In this study, the genetic diversity of 48 pearl millet genotypes was evaluated for eight morphological traits and eleven biochemical characters. All genotypes were also characterized using twelve SSR and six SRAP markers to evaluate genetic diversity. The significant mean difference between morphological and biochemical traits were detected. The productive tillers per plant varied from 2.65 to 7.60 with a mean of 4.80. The grain yield of genotypes varied more than 3× from 15.85 g (ICMR 07222) to 56.75 g (Nandi 75) with an average of 29.54 g per plant. Higher levels of protein, iron, and zinc contents were found to be present in ICMR 12555 (20.6%), ICMR 08666 (77.38 ppm), and IC 139900 (55.48 ppm), respectively, during the experiment. Substantial variability was observed for grain calcium as it ranged from 100.00 ppm (ICMR 10222) to 256.00 ppm (ICMR 12888). The top eight nutrient-dense genotypes flowered in 34-74 days and had 5.71-9.39 g 1,000 grain weight. Genotype ICMR 08666 was superior for Fe, Zn, K and P. The inter-genotype similarity coefficient at the genetic level, generated using DNA markers, ranged from 0.616 to 0.877 with a mean of 0.743. A combination of morpho-biochemical traits and DNA markers based diversity may help to differentiate the genotypes and diverse genotypes can be used in breeding programs to improve the mineral content in pearl millet.

The LASSIE MPS panel: Predicting externally visible traits in dogs for forensic purposes

Predicting the outward appearance of dogs via their DNA, also known as Canine DNA Phenotyping, is a young, emerging field of research in forensic genetics. The few previous studies published in this respect were restricted to the consecutive analysis of single DNA markers, a process that is time- and sample-consuming and therefore not a viable option for limited forensic specimens. Here, we report on the development and evaluation of a Massively Parallel Sequencing (MPS) based molecular genetic assay, the LASSIE MPS Panel. This panel aims to predict externally visible as well as skeletal traits, which include coat color, coat pattern, coat structure, tail morphology, skull shape, ear shape, eye color and body size from DNA using 44 genetic markers in a single molecular genetic assay. A biostatistical naïve Bayes classification approach was applied to identify the most informative marker combinations for predicting phenotypes. Overall, the predictive performance was characterized by a very high classification success for some of the trait categories, and high to moderate success for others. The performance of the developed predictive framework was further evaluated using blind samples from three randomly selected dog individuals, whose appearance was well predicted.

IDENTIFICATION OF IMMUNE RESPONSE COMBINATIONS ASSOCIATED WITH HETEROGENEOUS INFECTION RISK IN THE IMMUNE CORRELATES ANALYSIS OF HIV VACCINE STUDIES.

In HIV vaccine/prevention research, probing into the vaccine-induced immune responses that can help predict the risk of HIV infection provides valuable information for the development of vaccine regimens. Previous correlate analysis of the Thai vaccine trial aided the discovery of interesting immune correlates related to the risk of developing an HIV infection. The present study aimed to identify the combinations of immune responses associated with the heterogeneous infection risk. We explored a "change-plane" via combination of a subset of immune responses that could help separate vaccine recipients into two heterogeneous subgroups in terms of the association between immune responses and the risk of developing infection. Additionally, we developed a new variable selection algorithm through a penalized likelihood approach to investigate a parsimonious marker combination for the change-plane. The resulting marker combinations can serve as candidate correlates of protection and can be used for predicting the protective effect of the vaccine against HIV infection. The application of the proposed statistical approach to the Thai trial has been presented, wherein the marker combinations were explored among several immune responses and antigens.

Fully automated prostate cancer identification using multiplex fluorescence immunohistochemistry to assess prognosis markers on a single tissue section.

e17118 Background: Most prostate cancers diagnosed are low to intermediate risk and face the decision on whether active surveillance or active treatment represents the optimal treatment option. To incorporate a reproduceable parameter in treatment planning, prognostic marker assessment using multi-gene panels has been frequently proposed. However, the fluctuating tumor purity can reduce the predictive value of such tests. A more accurate prognostication would be the quantification of prognosis markers exclusively on cancer cells. Methods: To enable automated prognosis marker quantification, a framework for automated prostate cancer detection that comprises three different artificial intelligence analysis steps and an algorithm for cell-distance analysis have been developed and validated using 8 marker BLEACH&amp;STAIN mfIHC (i.e., panCK, p63, PSA, PSMA, INSM1, AR, Ki-67, CD56) in a tissue microarray and prostate biopsy cohort of 10’234 prostate cancers. Results: The approach for automated prostate cancer detection mimics the way pathologists use for identification of cancer cells and identified epithelial cells (CKpan positive) that were non-adjacent to basal cells (p63 positive). Validation experiments revealed that the optimal distance between p63+ basal cells and benign panCK+ cells was 23 µm to exclude benign glands from the prognosis marker analysis. A distance of 23µm as threshold for automated cancer detection showed a 39% higher accuracy compared to the cutoff value 5 µm. To compare this automated mfIHC-based prognosis marker assessment with the frequently used bright field IHC-based QuPath software package, and the manual prostate identification by pathologists, a cohort of 30 biopsies from routine clinical practice was assessed. An excellent agreement between the mfIHC-based automated cancer detection and manual cancer identification by pathologists was found (intraclass correlation [ICC]: 0.94 [95% CI 0.87 – 0.97]), while the QuPath-based model showed a 20 % deviation from the gold standard (manual assessment by pathologists). Accordingly, the automated mfIHC-based approach was used to search for a prognosis marker panel for routine clinical practice. 5 out of 6 analyzed prognosis markers (PSA, PSMA, INSM1, AR, Ki-67) were significantly liked to biochemical recurrence in univariate analysis (p ≤ 0.021) and 2 of 6 parameters (AR, Ki-67) were independent in multivariate analysis (each p≤ 0.0078). Several prognosis scores of different marker combinations were found that showed strong prognostic relevance in univariate analysis (p &lt; 0.001) and were independent from Gleason groups, pT, pN, serum PSA and R-Status (p = 0.001). Conclusions: Automated prostate cancer identification enables fully automated prognosis marker assessment in routine clinical practice using deep learning and mfIHC.

Application of Monocyte-to-Albumin Ratio and Neutrophil Percentage-to-Hemoglobin Ratio on Distinguishing Non-Small Cell Lung Cancer Patients from Healthy Subjects.

This study aims at assessing the potential benefits of observation of monocyte-to-albumin ratio (MAR) and neutrophil percentage-to-hemoglobin ratio (NPHR) in the detection of non-small cell lung cancer (NSCLC). This study retrospectively involved 195 NSCLC patients and 204 healthy volunteers. The correlations between the clinicopathological characteristics of NSCLC and the two ratios including MAR and NPHR were assessed. The diagnostic efficiency of NSCLC patients by MAR and NPHR, alone or in combination with carcinoembryonic antigen (CEA), was assessed by receiver operating characteristic (ROC) curve. The risk factors for NSCLC were analyzed with binary logistic regression. Compared to healthy controls, the levels of MAR and NPHR in NSCLC patients were elevated. MAR and NPHR were related to clinicopathologic characteristics and increased significantly along with the progression of NSCLC. The area under the curve (AUC) for 95% confidence interval (95% CI) of MAR and NPHR in the diagnosis of NSCLC was 0.812 (0.769-0.854) and 0.724 (0.675-0.774), respectively. The combination of MAR, NPHR, and CEA achieved the highest diagnostic utility compared to each individually or combined markers (AUC, 0.86; 95% CI, 0.824-0.896; sensitivity, 72.8%; specificity, 87.3%). Further analysis showed that MAR combined with NPHR presented the potential to detect early-stage (IA-IIB) NSCLC (AUC, 0.794; 95% CI, 0.743-0.845; sensitivity, 55.1%; specificity, 87.7%). The result indicated that MAR and NPHR might be risk factors for NSCLC. MAR and NPHR could be novel and effective auxiliary indexes in the detection of NSCLC, especially when combined with CEA.

Combining stable isotopes, trace elements, and distribution models to assess the geographic origins of migratory bats

AbstractThe expansion of industrial‐scale wind‐energy facilities has not only increased the production of low‐carbon emission energy but has also resulted in mortality of wildlife, including migratory bats. Management decisions can be limited by a lack of understanding of the geographic impact of bats killed at wind‐energy facilities. Several studies have leveraged stable hydrogen isotope ratios (δ2H) of bat fur to illuminate this issue but are limited in the precision of conclusion because δ2H values vary primarily across latitudinal and elevational bands. One approach to increase the precision of geographic assignment is to combine independent inferences about spatial location from additional biomarkers and other related information. To test this possibility, we assigned known‐origin individuals of three bat species (Lasiurus borealis, L. cinereus, and Lasionycteris noctivagans) commonly killed at on‐shore wind‐energy facilities in North America to a probable origin using δ2H values, trace element concentrations, and species distribution models. We used cross‐validated calibrated combined model tuning to determine the degree to which assignment probabilities improved when combining datasets. We found that combining markers typically performed better than single approaches. For Lasiurus borealis and L. cinereus, combining all three data sources outperformed any single or other combined approach. With an accuracy set at 80%, an average of 39.7% and 36.0% of each species' total geographic range was considered a potential origin, respectively; stable hydrogen alone included 51.8% and 50.6% of the total geographic area. In contrast, for Lasionycteris noctivagans, including trace elements did not increase precision and adding distribution data to δ2H values only improved precision by 0.6%. Thus, we found that a combination of multiple biomarkers typically, but not always, outperforms single‐marker approaches and optimized combinations of different markers outperform equal weighting of each marker. From a practical perspective, δ2H values performed better than trace elements alone; in cases where cost is a limiting factor, the stable hydrogen should be the single biomarker used in conjunction with species distribution models. Overall, these results highlight the importance of validating methods for each species they are applied to and show that combining information from intrinsic biomarker approaches is a useful tool to document bat movements.

Detecting introgressive hybridization to maintain genetic integrity in endangered large waterbird: a case study in milky stork

Hybridization between milky stork (Mycteria cinerea) and painted stork (M. leucocephala) occurs frequently in captivity. Dusit Zoo is a captive breeding facility where storks with phenotypically ambiguous patterns have recently been observed, and their status remaining inconclusive. Here, we used a combination of phenotypic characters and genetic markers (cytochrome b and 14 microsatellite markers) to distinguish and identify hybrids from the two parental species (n = 114). Haplotype analysis revealed asymmetric mtDNA introgression from M. cinerea to M. leucocephala, with twelve morphologically classified M. leucocephala individuals carrying heterospecific mtDNA. Comprehensive biparental genetic assessments identified 33% of all three genetic clusters as admixed individuals, of which most were either F2 hybrids, backcrosses with M. leucocephala, or hybrids of unknown generation, implying weak premating isolation with the absence of intrinsic postzygotic isolation between parentals. Morphological analysis demonstrated that the absence or indistinctness of a black bar across the breast is the most noticeable trait to identify these hybrids. The endangered M. cinerea was found to have genomic contamination from M. leucocephala and vice versa, with at least 41 hybrid individuals being identified. These findings provide critical information for detecting hybrids and identifying suitable breeding stocks with genetic purity for future reintroduction and conservation management.

Identification of a real-world clinical model associated with atrial fibrillation in a large french primary care database

Abstract Funding Acknowledgements Type of funding sources: Private company. Main funding source(s): Bristol Myers Squibb and Pfizer. Background Undiagnosed atrial fibrillation (AF) is associated with a higher risk of stroke and mortality. To date, the 2020 European Society of Cardiology (ESC) guidelines recommend opportunistic screening for AF in patients ≥65 years (Class I), or with hypertension (HTN) (Class I), or obstructive sleep apnea (OSA) (IIa), and systematic ECG screening in patients ≥75 years or at high risk of stroke defined by the CHA2DS2-VASc score (Class IIa).1 However, in a primary care practice, these criteria cover a large number of patients. Purpose Evaluate the performance of several clinical markers or combination of clinical markers to identify patients at high-risk of AF in a primary care database. Methods This retrospective national study used patients’ data from the French electronic health records THIN® database of 2 000 General Practitioners (GP). Patients included had visited their GP in 2019 and were followed for ≥ 3 years, were aged ≥ 50 with ≥ 1 risk markers potentially associated with AF (HTN, diabetes, obesity, dyslipidaemia, smoking, alcohol dependence, cardiopathy, heart failure (HF), vascular disease, OSA, chronic obstructive pulmonary disease, inflammatory disease, thyroid or renal dysfunction). Non-AF patients with anticoagulant treatment were excluded. The tested variables and models included the 2020 ESC guidelines criteria for AF screening (age ≥65, age ≥ 75, high stroke risk defined as CHA2DS2-VASc ≥ 2 (male) or ≥ 3 (female), HTN, OSA), the CHA2DS2-VASc taken as a score as well as the multivariate analysis of its components (congestive HF, HTN, age ≥ 75, diabetes, stroke, vascular disease, age 65-74, female sex), and an ad hoc model based on the combination of risk markers associated with AF (15 variables based on cardiovascular and non-cardiovascular comorbidities; Figure 1). Multivariate models were performed with logistical regression. Results Among 573 539 screened patients (mean follow-up 13.5 years), 30 476 had AF (5.3%). The ad hoc model using the 15 variables showed the highest performance with AUC 0.80 (Se 69%, Sp 77%) (Figure 1). In this model, all variables were significantly associated with AF except diabetes, dyslipidaemia, and HIV. Age ≥ 75, HF, age 65-74 and male sex were the most significant risk markers associated with AF (Figure 1). In the CHA2DS2-VASc model, AUC was 0.78 for multivariate analysis (Se 69%; Sp 72%), and 0.71 for the score result (Se 77%, Sp 56%). Regarding the ESC guidelines criteria, age ≥ 75 years had the best performance with AUC 0.69 (Se 62%, Sp 75%), then age ≥65 (AUC 0.67), high stroke risk (AUC 0.66), versus AUC &amp;lt; 0.60 for HTN and OSA. Conclusion In this study on a large primary care database, the ad hoc model had the highest performance, sensitivity and specificity. In the future, it might help GPs to identify patients at high-risk of AF in clinical practice and to propose targeted preventive interventions and screening.

Which Combination is the Best? A Comparison of the Predictive Potential of Serum Biomarker Combinations to Diagnose Periprosthetic Joint Infection

BackgroundWithout a gold-standard test, recent periprosthetic joint infections (PJI) literature has explored the utility of combining serological results, with promising findings. However, previous studies evaluated fewer than 200 patients and often studied only 1 to 2 test combinations. The purpose of this study was to accumulate a large single-institution cohort of revision total joint arthroplasty (rTJA) patients to determine the diagnostic utility of combination serum biomarkers to identify PJI. MethodsA single institution longitudinal database was assessed to identify all patients who underwent rTJA from 2017 to 2020. There were 1,363 rTJA patients (715 rTKA patients and 648 rTHA patients) including 273 PJI cases (20%) analyzed. The PJI was diagnosed post-rTJA utilizing 2011 Musculoskeletal Infection Society (MSIS) criteria. Erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), D-dimer, and interleukin 6 (IL-6) were systematically collected for all patients. ResultsThe rTKA combination markers of CRP + ESR (sensitivity: 78.3%, specificity: 88.8%, positive predictive value (PPV): 70.0%, negative predictive value (NPV): 92.5%), CRP + D-dimer (sensitivity: 60.5%, specificity: 92.6%, PPV: 63.4%, NPV: 91.7%), and CRP + IL-6 (sensitivity: 38.5%, specificity: 100.0%, PPV: 100.0%, NPV: 92.9%) all yielded higher specificity than CRP alone (sensitivity: 94.4%, specificity: 75.0%, PPV: 55.5%, NPV: 97.6%). Similarly, the rTHA combination markers of CRP + ESR (sensitivity: 70.1%, specificity: 88.8%, PPV: 58.1%, NPV: 93.1%), CRP + D-dimer (sensitivity: 57.1%, specificity: 90.1%, PPV: 43.2%, NPV: 94.1%), and CRP + IL-6 (sensitivity: 21.4%, specificity: 98.4%, PPV: 60.0%, NPV: 91.7%) all yielded higher specificity than CRP alone (sensitivity: 84.7%, specificity: 77.5%, PPV: 45.4%, NPV: 95.8%). ConclusionOverall, in diagnosing PJI for both rTKA and rTHA, 2-marker combinations yielded higher specificity, while 3-marker combinations yielded higher sensitivity compared to CRP alone. However, compared to all 2-marker and 3-marker combinations, CRP demonstrated superior overall diagnostic utility. These findings suggest that routine combination testing of markers for PJI diagnosis may be excessive and an unnecessary use of resources, especially in resource-limited situations.

Optimizing maternal and neonatal outcomes through tight control management of inflammatory bowel disease during pregnancy: a pilot feasibility study

A home point-of care FCP test (IBDoc) and a self-reported clinical disease activity program (IBD Dashboard) may improve routine monitoring of IBD activity during pregnancy. We aimed to evaluate the feasibility of tight control management using remote monitoring in pregnant patients with IBD. Pregnant patients (< 20 weeks) with IBD were prospectively enrolled from Mount Sinai Hospital between 2019 and 2020. Patients completed the IBDoc and IBD Dashboard at three core time points. Disease activity was measured clinically using the Harvey–Bradshaw Index (mHBI) for CD and partial Mayo (pMayo) for UC, or objectively using FCP. A feasibility questionnaire was completed in the third trimester. Seventy-seven percent of patients (24 of 31) completed the IBDoc and IBD Dashboard at all core time points. Twenty-four patients completed the feasibility questionnaires. All survey respondents strongly preferred using the IBDoc over standard lab-based testing and would use the home kit in the future. Exploratory analysis identified discordance rates of more than 50% between clinical and objective disease activity. Tight control management using remote monitoring may be feasible among pregnant patients with IBD. A combination of both clinical scores and objective disease markers may better predict disease activity.

Peripheral Markers of Suicidal Behavior: Current Findings and Clinical Implications.

Biomarkers of suicidal behavior (SB), particularly peripheral biomarkers, may aid in the development of preventive and intervention strategies. The peripheral biomarkers of SB should be easily accessible, cost-effective, and minimally invasive. To identify peripheral biomarkers of SB, we summarized the current knowledge related to SB biomarkers with a focus on suicidal outcomes (suicidal ideation [SI], suicide risk [SR], suicide attempt [SA], and suicide death [SD]), measured site (center or periphery), and study design (cross-sectional or longitudinal). We also evaluated the central findings to validate the findings of peripheral biomarkers of SB. We found reduced peripheral interleukin (IL)-2 levels in individuals with a recent SA, higher cerebrospinal fluid (CSF) IL-6 levels in patients with a current SR and future SD, higher CSF tumor necrosis factor-α levels for current and future SRs, higher high-sensitivity C-reactive protein levels and lower peripheral total cholesterol levels for recent SAs, lower peripheral 5-HT levels for present SR, and a lower folate level for future SR and SA within 1 year. Previous studies have shown inconsistent associations of low peripheral leptin levels with SR and recent SA; therefore, further study is required. Given the multiple determinants of SB and weak associations with single biological markers, combinations of potential biological markers rather than single markers may improve the screening, diagnosis, and prediction of SB.

Diagnostic performance of the normal range of gastrin calculated using strict criteria based on a combination of serum markers and pathological evaluation for detecting gastritis: a retrospective study

BackgroundThe ABC method, which combines the pepsinogen method and anti-Helicobacter pylori antibody titers, has been used for risk screening for gastric cancer in Japan. However, it has been reported that there are cases of gastritis and carcinogenesis risk even in group A, which is considered to be a low-risk group based on the ABC method. Currently, in group A, endoscopic examination is needed to strictly discriminate “patients without gastritis” (defined as true A patients) from those “with gastritis.” A simple and minimally invasive diagnostic criterion for gastritis using serological markers is desirable. In this study, we aimed to identify the normal serum gastrin concentrations in normal stomach cases based on pathological diagnosis and investigate the usefulness of serum gastrin concentrations in diagnosing gastritis.MethodsPatients who underwent endoscopy and blood tests at Hiroshima University Hospital were enrolled in the study and categorized into the “pathologically-evaluated group” and “endoscopically-evaluated group,” according to the evaluation method of atrophic gastritis. Initially, we measured serum gastrin concentrations in the normal stomach cases in the pathologically-evaluated group and calculated the normal range of serum gastrin concentrations. We used the upper limit of this normal range of serum gastrin concentrations and performed a validation study to determine its usefulness as a diagnostic marker for distinguishing between cases of gastritis and true A in the endoscopically-evaluated group.ResultsThe 95th percentile of serum gastrin concentrations in pathologically-evaluated normal stomach cases was 34.12–126.03 pg/mL. Using the upper limit of this normal range of serum gastrin concentrations, the sensitivity, specificity, positive predictive value, and negative predictive value for gastritis were 52.8%, 92.6%, 97.0%, and 31.0%, respectively. Additionally, the receiver operating characteristic (ROC) curve for the endoscopically-evaluated group showed an area under the ROC curve of 0.80.ConclusionThe gastrin cut-off value of 126 pg/mL has a good positive predictive value (97.0%) for detecting gastritis positing its use as a marker for cases requiring endoscopy. However, the identification of patients with gastritis having normal serum gastrin concentrations due to insufficient sensitivity remains a challenge for the future.

Landscapes of gut microbiome and bile acid signatures and their interaction in HBV-associated acute-on-chronic liver failure.

Submassive hepatic necrosis (SMHN, defined as necrosis of 15-90% of the entire liver on explant) is a likely characteristic pathological feature of ACLF in patients with hepatitis B cirrhosis. We aimed to comprehensively explore microbiome and bile acids patterns across enterhepatic circulation and build well-performing machine learning models to predict SMHN status. Based on the presence or absence of SMHN, 17 patients with HBV-related end-stage liver disease who received liver transplantation were eligible for inclusion. Serum, portal venous blood, and stool samples were collected for comparing differences of BA spectra and gut microbiome and their interactions. We adopted the random forest algorithm with recursive feature elimination (RF-RFE) to predict SMHN status. By comparing total BA spectrum between SMHN (-) and SMHN (+) patients, significant changes were detected only in fecal (P = 0.015). Compared with the SMHN (+) group, the SMHN (-) group showed that UDCA, 7-KLCA, 3-DHCA, 7-KDCA, ISOLCA and α-MCA in feces, r-MCA, 7-KLCA and 7-KDCA in serum, γ-MCA and 7-KLCA in portal vein were enriched, and TUDCA in feces was depleted. PCoA analysis showed significantly distinct overall microbial composition in two groups (P = 0.026). Co-abundance analysis showed that bacterial species formed strong and broad relationships with BAs. Among them, Parabacteroides distasonis had the highest node degree. We further identified a combinatorial marker panel with a high AUC of 0.92. Our study demonstrated the changes and interactions of intestinal microbiome and BAs during enterohepatic circulation in ACLF patients with SMHN. In addition, we identified a combinatorial marker panel as non-invasive biomarkers to distinguish the SMHN status with high AUC.

Hepatocellular carcinoma: A clinicopathological and immunohistochemical study of 116 cases from a tertiary care hospital in Southern India.

Diagnosis of hepatocellular carcinoma (HCC) is difficult on morphology alone in poorly differentiated tumors and metastatic carcinomas. Appropriate immunohistochemical markers are required for definite diagnosis. In this article, we have analyzed the histopathological and immunohistochemical features of HCC and elucidate the best possible immunohistochemistry (IHC) marker combination by comparing the sensitivity of various markers in different grades of tumor. A total of 116 consecutive cases were analyzed retrospectively. The hematoxylin and eosin stained sections were reviewed in all the cases. IHC was done using hepatocellular specific antigen (HSA), arginase-1, glypican-3, and polyclonal carcinoembryonic antigen (pCEA). The sensitivity of various immunohistochemical markers individually as well as in combination for different tumor grades was determined. Histologically, the predominant subtype comprised of classic variant (109,93.9%) followed by combined hepatocellular and cholangiocarcinoma (4,3.4%) and fibrolamellar variant (3,2.6%). Trabecular pattern was the most common histological pattern. On grading, 65,56.03% were moderately differentiated, 34,29.31% well differentiated, and17, 14.65% poorly differentiated. HSA and polyclonal-CEA showed higher sensitivity than arginase-1 and glypican-3 in well and moderately differentiated tumors. In contrast arginase-1 and glypican-3 showed better sensitivity in poorly differentiated HCC. The overall sensitivity increased to greater than 90% if HSA/polyclonal-CEA is combined with either arginase-1/glypican-3 irrespective of tumor grade. Majority of the tumors were classic variants and moderately differentiated. HSA along with either arginase-1 or glypican-3 is the best combination of immunomarker for identification of hepatocellular differentiation irrespective of tumor grade.

Exploitation of a Type 1 Toxin-Antitoxin System as an Inducible Counter-Selective Marker for Genome Editing in the Acetogen Eubacterium limosum.

Targeted mutations in the anaerobic methylotroph Eubacterium limosum have previously been obtained using CRISPR-based mutagenesis methods. In this study, a RelB-family toxin from Eubacterium callanderi was placed under the control of an anhydrotetracycline-sensitive promoter, forming an inducible counter-selective system. This inducible system was coupled with a non-replicative integrating mutagenesis vector to create precise gene deletions in Eubacterium limosum B2. The genes targeted in this study were those encoding the histidine biosynthesis gene hisI, the methanol methyltransferase and corrinoid protein mtaA and mtaC, and mtcB, encoding an Mttb-family methyltransferase which has previously been shown to demethylate L-carnitine. A targeted deletion within hisI brought about the expected histidine auxotrophy, and deletions of mtaA and mtaC both abolished autotrophic growth on methanol. Deletion of mtcB was shown to abolish the growth of E. limosum on L-carnitine. After an initial selection step to isolate transformant colonies, only a single induction step was required to obtain mutant colonies for the desired targets. The combination of an inducible counter-selective marker and a non-replicating integrative plasmid allows for quick gene editing of E. limosum.

Triglyceride glucose index, pediatric NAFLD fibrosis index, and triglyceride-to-high-density lipoprotein cholesterol ratio are the most predictive markers of the metabolically unhealthy phenotype in overweight/obese adolescent boys.

The prevalence of obesity constantly increases worldwide and definitely increases the risk of premature death in early adulthood. While there is no treatment yet with proven efficacy for the metabolic clamp such as arterial hypertension, dyslipidemia, insulin resistance, diabetes type 2, and fatty liver disease, it is imperative to find a way to decrease cardiometabolic complications. Early prevention strategies beginning in childhood are the most logical step to reduce future cardiovascular morbidity and mortality. Therefore, the aim of the current study is to determine the most sensitive and specific predictive markers of the metabolically unhealthy phenotype with high cardiometabolic risk in overweight/obese adolescent boys. This study was carried out at the Ternopil Regional Children's hospital (Western Ukraine) and involved 254 randomly chosen adolescent overweight or obese boys [median age was 16.0 (15.0,16.1) years]. A control group of 30 healthy children with proportional body weight comparable in gender and age to the main group was presented. A list of anthropometrical markers with biochemical values of carbohydrate and lipid metabolism with hepatic enzymes was determined. All overweight/obese boys were divided into three groups: 51.2% of the boys with metabolic syndrome (MetS) based on the IDF criteria; 19.7% of the boys were metabolically healthy obese (MHO) without hypertension, dyslipidemia, and hyperglycemia; and the rest of the boys (29.1%) were classified as metabolically unhealthy obese (MUO) with only one criterion (hypertension, dyslipidemia, or hyperglycemia). Based on multiple logistic regression analysis that included all anthropometric and biochemical values and calculated indexes in boys from the MHO group and MetS, it was revealed that the maximum likelihood in the prediction of MetS makes the combination of triglyceride glucose index, pediatric nonalcoholic fatty liver disease fibrosis index (PNFI), and triglyceride-to-high-density lipoprotein cholesterol ratio (R2 =0.713, p<0.000). By tracing the receiver operating characteristic curve, the model is confirmed as a good predictor of MetS (AUC=0.898, odds ratio=27.111 percentage correct=86.03%) in overweight and obese boys. Triglyceride glucose index, pediatric NAFLD fibrosis index, and triglyceride-to-high-density lipoprotein cholesterol ratio are a valuable combination of predictive markers of the metabolically unhealthy phenotype in Ukrainian overweight/obese boys.

Endoscopic ultrasound fine-needle biopsy to assess DAXX/ATRX expression and alternative lengthening of telomeres status in non-functional pancreatic neuroendocrine tumors

Background/objectivesDeath domain-associated protein (DAXX) and/or α-thalassemia/mental retardation X-linked (ATRX) chromatin remodeling genes mutations and alternative lengthening of telomeres (ALT) activation are associated with more aggressive behavior of non-functional pancreatic neuroendocrine tumors (NF-PanNETs). We aimed to evaluate the reliability of such markers on endoscopic-ultrasound fine-needle biopsy (EUS-FNB) specimens. MethodsPatients who underwent EUS-FNB and subsequent surgical resection for PanNETs between January 2017 and December 2019 were retrospectively identified. Immunohistochemistry (IHC) to evaluate DAXX/ATRX expression and fluorescence in situ hybridization (FISH) for ALT status were performed. Primary outcome was the concordance rate of markers expression between EUS-FNB and surgical specimens. Secondary aims were association between markers and lesion aggressiveness, their diagnostic performance in predicting aggressiveness, and agreement of preoperative and post-surgical Ki67-based grading. ResultsForty-one NF-PanNETs (mean diameter 36.1 ± 26.5 mm) were included. Twenty-four showed features of lesion aggressiveness. Concordance of expressions of DAXX, ATRX, and ALT status between EUS-FNB and surgical specimens were 95.1% (κ = 0.828; p < 0.001), 92.7% (κ = 0.626; p < 0.001), and 100% (κ = 1; p < 0.001), respectively. DAXX/ATRX loss and ALT-positivity were significantly (p < 0.05) associated with metastatic lymphnodes and lymphovascular invasion. The combination of all tumor markers (DAXX/ATRX loss + ALT-positivity + grade 2) reached an accuracy of 73.2% (95%CI 57.1–85.8) in identifying aggressive lesions. Pre- and post-operative ki-67-based grading was concordant in 80.5% of cases (k = 0.573; p < 0.001). ConclusionDAXX/ATRX expression and ALT status can be accurately evaluated in a preoperative setting on EUS-FNB samples, potentially improving the identification of patients with increased risk and poorer prognosis.