Loss of FUT8 in renal tubules ameliorates ischemia-reperfusion injury-induced renal interstitial inflammation transition to fibrosis via the TLR3-NF-κB pathway.

Renal ischemia-reperfusion injury (IRI) is a common reason of acute kidney injury (AKI). AKI can progress to chronic kidney disease (CKD) in some survivors. Inflammation is considered the first-line response to early-stage IRI. We previously reported that core fucosylation (CF), specifically catalyzed by α-1,6 fucosyltransferase (FUT8), exacerbates renal fibrosis. However, the FUT8 characteristics, role, and mechanism in inflammation and fibrosis transition remain unclear. Considering renal tubular cells are the trigger cells that initiate the fibrosis in the AKI-to-CKD transition in IRI, we targeted CF by generating a renal tubular epithelial cell (TEC)-specific FUT8 knockout mouse and measured FUT8-driven and downstream signaling pathway expression and AKI-to-CKD transition. During the IRI extension phase, specific FUT8 deletion in the TECs ameliorated the IRI-induced renal interstitial inflammation and fibrosis mainly via the TLR3 CF-NF-κB signaling pathway. The results firstly indicated the role of FUT8 in the transition of inflammation and fibrosis. Therefore, the loss of FUT8 in TECs may be a novel potential strategy for treating AKI-CKD transition.

A New Risk Score to Predict Intensive Care Unit Admission for Patients with Acute Pancreatitis 48 Hours After Admission: Multicenter Study.

AIMS: The objective of this study was to develop and validate an easy-to-use risk score (APRS) to predict which patients with acute pancreatitis (AP) will need intensive care unit (ICU) treatment within 48 h post-hospitalization on the basis of the ubiquitously available clinical records. METHODS: Patients with acute pancreatitis were retrospectively included from three independent institutions (RM cohort, 5280; TJ cohort, 262; SN cohort, 196), with 56 candidate variables collected within 48 h post-hospitalization. The RM cohort was randomly divided into a training set (N = 4220) and a test set (N = 1060). The most predictive features were extracted by LASSO from the RM cohort and entered into multivariate analysis. APRS was constructed using the coefficients of the statistically significant variables weighted by the multivariable logistic regression model. The APRS was validated by RM, TJ, and SN cohorts. The C-statistic was employed to evaluate the APRS's discrimination. DeLong test was used to compare area under the receiver operating characteristic curve (AUC) differences. RESULTS: A total of 5738 patients with AP were enrolled. Eleven variables were selected by LASSO and entered into multivariate analysis. APRS was inferred using the above five factors (pleural effusion, ALT/AST, ALB/GLB, urea, and glucose) weighted by their regression coefficients in the multivariable logistic regression model. The C-statistics of APRS were 0.905 (95% CI 0.82-0.98) and 0.889 (95% CI 0.81-0.96) in RM and TJ validation. An online APRS web-based calculator was constructed to assist the clinician to earlier assess the clinical outcomes of patients with AP. CONCLUSION: APRS could effectively stratify patients with AP into high and low risk of ICU admission within 48 h post-hospitalization, offering clinical value in directing management and personalize therapeutic selection for patients with AP.

Molecular Cytological Analysis and Specific Marker Development in Wheat-Psathyrostachys huashanica Keng 3Ns Additional Line with Elongated Glume.

Psathyrostachys huashanica Keng (2n = 2x = 14, NsNs) is an excellent gene resource for wheat breeding, which is characterized by early maturity, low plant height, and disease resistance. The wheat-P. huashanica derivatives were created by the elite genes of P. huashanica and permeate into common wheat through hybridization. Among them, a long-glume material 20JH1155 was identified, with larger grains and longer spike than its parents. In the present study, the methods of cytological observation, GISH, and sequential FISH analysis showed that 20JH1155 contained 21 pairs of wheat chromosomes and a pair of P. huashanica. There were some differences in 5A and 7B chromosomes between 20JH1155 and parental wheat 7182. Molecular marker, FISH, and sequence cloning indicated 20JH1155 alien chromosomes were 3Ns of P. huashanica. In addition, differentially expressed genes during immature spikelet development of 20JH1155 and 7182 and predicted transcription factors were obtained by transcriptome sequencing. Moreover, a total of 7 makers derived from Ph#3Ns were developed from transcriptome data. Taken together, the wheat-P. huashanica derived line 20JH1155 provides a new horizon on distant hybridization of wheat and accelerates the utilization of genes of P. huashanica.

Machine learning model identifies aggressive acute pancreatitis within 48 h of admission: a large retrospective study.

BACKGROUND: Acute pancreatitis (AP) with critical illness is linked to increased morbidity and mortality. Current risk scores to identify high-risk AP patients have certain limitations. OBJECTIVE: To develop and validate a machine learning tool within 48 h after admission for predicting which patients with AP will develop critical illness based on ubiquitously available clinical, laboratory, and radiologic variables. METHODS: 5460 AP patients were enrolled. Clinical, laboratory, and imaging variables were collected within 48 h after hospital admission. Least Absolute Shrinkage Selection Operator with bootstrap method was employed to select the most informative variables. Five different machine learning models were constructed to predictive likelihood of critical illness, and the optimal model (APCU) was selected. External cohort was used to validate APCU. APCU and other risk scores were compared using multivariate analysis. Models were evaluated by area under the curve (AUC). The decision curve analysis was employed to evaluate the standardized net benefit. RESULTS: Xgboost was constructed and selected as APCU, involving age, comorbid disease, mental status, pulmonary infiltrates, procalcitonin (PCT), neutrophil percentage (Neu%), ALT/AST, ratio of albumin and globulin, cholinesterase, Urea, Glu, AST and serum total cholesterol. The APCU performed excellently in discriminating AP risk in internal cohort (AUC = 0.95) and external cohort (AUC = 0.873). The APCU was significant for biliogenic AP (OR = 4.25 [2.08-8.72], P < 0.001), alcoholic AP (OR = 3.60 [1.67-7.72], P = 0.001), hyperlipidemic AP (OR = 2.63 [1.28-5.37], P = 0.008) and tumor AP (OR = 4.57 [2.14-9.72], P < 0.001). APCU yielded the highest clinical net benefit, comparatively. CONCLUSION: Machine learning tool based on ubiquitously available clinical variables accurately predicts the development of AP, optimizing the management of AP.

The in Situ NHC-Palladium Catalyzed Selective Activation of B(3)-H or B(6)-H Bonds of o-Carboranes for Hydroboration of Alkynes: An Efficient Approach to Alkenyl-o-carboranes.

An in situ Pd-NHC catalyzed selective B(3,6)-H activation for hydroboration of internal alkynes has been accomplished under mild conditions. This work offers a facile approach for the synthesis of alkenyl-o-carboranes and has important reference for selective functionalization of B(3,6)-H bonds.

Palladium Catalyzed Selective B(3)-H Activation/Oxidative Dehydrogenative Coupling for the Synthesis of Bis(o-carborane)s.

A palladium catalyzed selective B(3)-H activation/oxidative dehydrogenative coupling for the synthesis of bis(o-carborane)s connected with B(3)-B(3') and B(3)-B(6') bonds has been developed for the first time. A plausible mechanism involving stepwise activation of B(3)-H and B(3'/6')-H bonds by PdII and PdIV was proposed. This work is the first example and the most efficient protocol for synthesis of bis(o-carborane)s connected with B(3)-B(3') and B(3)-B(6') bonds, which has important reference for design, synthesis, and application of bis(o-carborane)s in related fields.

Development and evaluation of an element-tagged immunoassay coupled with inductively coupled plasma mass spectrometry detection: can we apply the new assay in the clinical laboratory?

Introduction Element-tagged immunoassay coupled with inductively coupled plasma-mass spectrometry (ICP-MS) detection has the potential to revolutionize immunoassay analysis in clinical detection; however, a systematic evaluation with the standard guidelines of the assay is needed to ensure its performance meets the requirements of the clinical laboratory. Methods Carcinoembryonic antigen (CEA) was chosen for analysis using the proposed method. A systematic evaluation of the proposed assay was carried out according to the Clinical and Laboratory Standards Institute (CLSI). The 469 clinical samples were analyzed using the new method and compared with the electrochemiluminescent immunoassay (ECLIA) method. Results The measurement range of the assay was 1-900 ng/mL, with a detection limit of 0.83 ng/mL. The inter-assay and intra-assay imprecision were 4.67% and 5.38% with high concentration samples, and 9.27% and 17.64% with low concentration samples, respectively. The cross-reactivity (%) for different antigens was less than 0.05%, and the recovery was between 94% and 108%. Percentage deviation of all the dilutions was less than 12.5% during linearity estimation. The interference bias caused by different substances was less than 10%. The reference interval of the assay was 0-4.442 ng/mL. Comparison with the commercial ECLIA method for clinical sample detection, the proposed method showed a correlation of 0.9878 and no significant differences between the methods were observed (p = 0.6666). Conclusions The ICP-MS based immunoassay was successfully developed, and the analytical performance of the assay met the requirements of the CLSI, which fully proved the clinical transferability and application of the new method.

Evolution and forcing mechanisms of El Niño over the past 21,000 years.

The El Niño Southern Oscillation (ENSO) is Earth's dominant source of interannual climate variability, but its response to global warming remains highly uncertain. To improve our understanding of ENSO's sensitivity to external climate forcing, it is paramount to determine its past behaviour by using palaeoclimate data and model simulations. Palaeoclimate records show that ENSO has varied considerably since the Last Glacial Maximum (21,000 years ago), and some data sets suggest a gradual intensification of ENSO over the past ∼6,000 years. Previous attempts to simulate the transient evolution of ENSO have relied on simplified models or snapshot experiments. Here we analyse a series of transient Coupled General Circulation Model simulations forced by changes in greenhouse gasses, orbital forcing, the meltwater discharge and the ice-sheet history throughout the past 21,000 years. Consistent with most palaeo-ENSO reconstructions, our model simulates an orbitally induced strengthening of ENSO during the Holocene epoch, which is caused by increasing positive ocean-atmosphere feedbacks. During the early deglaciation, ENSO characteristics change drastically in response to meltwater discharges and the resulting changes in the Atlantic Meridional Overturning Circulation and equatorial annual cycle. Increasing deglacial atmospheric CO2 concentrations tend to weaken ENSO, whereas retreating glacial ice sheets intensify ENSO. The complex evolution of forcings and ENSO feedbacks and the uncertainties in the reconstruction further highlight the challenge and opportunity for constraining future ENSO responses.

Development and Evaluation of a Combined Immunoassay Method Based on a Stable Isotope Tagging Strategy and Inductively Coupled Plasma Mass Spectrometry for Detecting Human Chorionic Gonadotropin.

BACKGROUND: The development of a combined immunoassay method, based on a stable isotope tagging strategy and inductively coupled plasma mass spectrometry (ICP-MS), has created options for quantitative bioanalysis. The aim of the study was to develop a combined immunoassay, featuring ICP-MS and a stable element labeling strategy, for the detection of human chorionic gonadotropin (HCG), and developed methodology applicable for clinical practice. METHODS: In accordance with guidelines published by the Clinical and Laboratory Standards Institute (CLSI), we developed our assay and then evaluated its analytical performance, including the limit of detection (LOD), the upper limit of quantification (ULoQ), linearity, precision, recovery, cross reactivity, and interference. Next, we collected 130 clinical samples for analysis with the new assay. The data derived from our assay were then compared with those derived by an existing electrochemiluminescence immunoassay (ECLIA). RESULTS: The LOD of the assay was 0.33 mIU/mL and the ULoQ was 11,300 mIU/mL. The coefficient of determina-tion of linearity was higher than 0.99 in the range of 1 to 8,917 mIU/mL (R2 = 0.9964). The obtained recoveries ranged from 97.08% to 103.50%, while the intra-assay imprecision of high value samples and low value samples were 2.97% and 6.08%, respectively. The inter-assay imprecision of high value samples and low value samples were 3.98% and 7.08%, respectively. Interference test results deviated by less than ± 10% in the presence of hemoglobin ≤ 2 g/L, bilirubin ≤ 274 mol/L, or triglycerides ≤ 37 mmol/L. Compared with the commercial ECLIA method for clinical sample detection, the proposed method showed a significant correlation (R2 = 0.9770) and satisfactory agreement. CONCLUSIONS: The combination of ICP-MS and a stable element labeling based immunoassay for HCG detection was established successfully and the general performance of this system was acceptable, thus indicating that the assay has potential for the clinical application.

A preliminary study for the establishment of a reference interval for vitamin B12 in China after performance verification of a second-generation ECLIA kit.

BACKGROUND: The second-generation electrochemiluminescence immunoassay (ECLIA) kit of vitamin B12 is widely used in clinical laboratories, and the establishment of a reference interval (RI) is essential to provide the basis for clinical monitoring. The purpose of this study was to establish a laboratory RI for vitamin B12 in China and at the same time verify the method performance of the second-generation kit. METHODS: The verification of the method performance was conducted according to the Clinical and Laboratory Standards Institute (CLSI) guidelines. Based on these guidelines, a total of 580 serum samples were collected, and 391 serum samples were used for the establishment of the RI according to CLSI guidelines. The subjects were grouped by sex and age. The age groups were as follows: 21-40, 41-60, and 61-80 years. The RI was defined by nonparametric 2.5th and 97.5th percentile intervals. RESULTS: The performance of the second-generation kit of vitamin B12 from the Roche Cobas E602 system was in compliance with laboratory requirements. Serum vitamin B12 levels conformed to a non-Gaussian distribution. Harris-Boyd's test did not indicate partitioning for different age and gender group. Besides, there was no significant difference between different age groups (P = .07) and gender groups (P = .2002). The RI for healthy Chinese adults (aged 21-80 years) calculated by the nonparametric method was 250.8-957.1 pg/mL. CONCLUSIONS: The reference range of vitamin B12 was established, which provided a theoretical basis for the clinical application and monitoring of vitamin B12 detection.

Simultaneous determination of gastric cancer biomarkers pepsinogen PGI/PGII using element tagged immunoassay coupled with inductively coupled plasma mass spectrometry detection.

OBJECTIVES: In this study, a new immunoassay for the simultaneous determination of pepsinogen I (PGI) and pepsinogen II (PGII) in serum based on element labeling strategy coupled with inductively coupled plasma mass spectrometry (ICP-MS) detection was proposed. METHODS: The sandwich-type immunoassay was used to simultaneously detect PGI and PGII in serum. PGI and PGII were captured by anti-PGI and anti-PGII antibody immobilized on the magnetic beads and then banded with Eu3+ labeled anti-PGI detection antibody and Sm3+ labeled anti-PGII detection antibody, followed by ICP-MS detection. RESULTS: The linear correlation coefficient (R2 ) of PGI and PGII standard curves was .9938 and .9911, with the dynamic range of 0-200 ng/mL and 0-60 ng/mL, respectively. The limit of detection for PGI and PGII was 1.8 ng/mL and 0.3 ng/mL, respectively. The average recovery was 101.41% ± 6.74% for PGI and 101.47% ± 4.20% for PGII. Good correlations were obtained between the proposed method and CLIA (r = .9588 for PGI, r = .9853 for PGII). CONCLUSIONS: We established a mass spectrometry-based immunoassay for the simultaneous detection of PGI and PGII in a single analysis. The element tagged immunoassay coupled with ICP-MS detection has high sensitivity, accuracy, and specificity in clinical serum sample analysis.

Screening and identification of serum biomarkers of osteoarticular tuberculosis based on mass spectrometry.

BACKGROUND: In view of the current difficulty of clinically diagnosing osteoarticular tuberculosis, our aim was to use mass spectrometry to establish diagnostic models and to screen and identify serum proteins which could serve as potential diagnostic biomarkers for early detection of osteoarticular tuberculosis. METHODS: Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) was used to select an osteoarticular tuberculosis-specific serum peptide profile and establish diagnostic models. Further, liquid chromatography-tandem mass spectrometry (LC-MS/MS) was used to identify potential serum biomarkers that could be used for auxiliary diagnosis of osteoarticular tuberculosis, and then clinical serum samples were used to verify these biomarkers by enzyme-linked immunosorbent assay (ELISA). RESULTS: We established four diagnostic models that can distinguish osteoarticular tuberculosis from rheumatoid arthritis, ankylosing spondylitis, osteoarticular infections, and healthy adults. The models were osteoarticular tuberculosis-rheumatoid arthritis, osteoarticular tuberculosis-ankylosing spondylitis, osteoarticular tuberculosis-osteoarticular infections, and osteoarticular tuberculosis-healthy adult, and their accuracy was 76.78%, 79.02%, 83.77%, and 88.16%, respectively. Next, we selected and identified 18 proteins, including complement factor H-related protein 1 (CFHR1) and complement factor H-related protein 2 (CFHR2), which were upregulated in the tuberculosis group only. CONCLUSIONS: We successfully established four diagnostic models involving osteoarticular tuberculosis, rheumatoid arthritis, ankylosing spondylitis, osteoarticular infections, and healthy adults. Furthermore, we found that CFHR1 and CFHR2 may be two valuable auxiliary diagnostic indicators for osteoarticular tuberculosis. These results provide reference values for rapid and accurate diagnosis of osteoarticular tuberculosis.

Proteome profiling of gestational diabetes mellitus at 16-18 weeks revealed by LC-MS/MS.

BACKGROUND: The practices used to diagnose gestational diabetes mellitus (GDM) could only be carried out around the time of detectable symptoms, and predictive capacity is little. METHODS: LC-MS/MS was conducted to explore overview proteomics for GDM complicated pregnant woman at 16-18 gestation weeks, while normal pregnant for control. Enzyme-linked immunosorbent assay was further applied in an independent cohort of 15 GDM cases and 15 controls for verification. RESULTS: The results indicated that 24 protein expression levels were significantly changed in GDM group samples, and inflammation, oxidative stress, insulin resistance, blood coagulation, and lipid homeostasis were associated with GDM. The abnormal expression of CRP and IGFBP2 was verified in the first-trimester maternal plasma in women who subsequently developed GDM. CONCLUSIONS: This study not only identified 24 potential predictive biomarkers for GDM also provided a global overview of protein rearrangements induced by GDM.

Synthesis of Polyhedral Borane Cluster Fused Heterocycles via Transition Metal Catalyzed B-H Activation.

Aromatic heterocycles are ubiquitous building blocks in bioactive natural products, pharmaceutical and agrochemical industries. Accordingly, the carborane-fused heterocycles would be potential candidates in drug discovery, nanomaterials, metallacarboranes, as well as photoluminescent materials. In recent years, the transition metal catalyzed B-H activation has been proved to be an effective protocol for selective functionalization of B-H bond of o-carboranes, which has been further extended for the synthesis of polyhedral borane cluster-fused heterocycles via cascade B-H functionalization/annulation process. This article summarizes the recent progress in construction of polyhedral borane cluster-fused heterocycles via B-H activation.

Frequent inactivating germline mutations in DNA repair genes in patients with Ewing sarcoma.

PURPOSE: Ewing sarcoma is a small round blue cell tumor that is highly malignant and predominantly affects the adolescent and young adult population. It has long been suspected that a genetic predisposition exists for this cancer, but the germ-line genetic underpinnings of this disease have not been well established. METHODS: We performed germline variant analysis of whole-genome or whole-exome sequencing of samples from 175 patients affected by Ewing sarcoma. RESULTS: We discovered pathogenic or likely pathogenic germline mutations in 13.1% of our cohort. Pathogenic mutations were highly enriched for genes involved with DNA damage repair and for genes associated with cancer predisposition syndromes. CONCLUSION: Our findings reported here have important clinical implications for patients and families affected by Ewing sarcoma. Genetic counseling should be considered for patients and families affected by this disease to take advantage of existing risk management strategies. Our study also highlights the importance of germline sequencing for patients enrolled in precision-medicine protocols.Genet Med advance online publication 26 January 2017.

The genomic landscape of the Ewing Sarcoma family of tumors reveals recurrent STAG2 mutation.

The Ewing sarcoma family of tumors (EFT) is a group of highly malignant small round blue cell tumors occurring in children and young adults. We report here the largest genomic survey to date of 101 EFT (65 tumors and 36 cell lines). Using a combination of whole genome sequencing and targeted sequencing approaches, we discover that EFT has a very low mutational burden (0.15 mutations/Mb) but frequent deleterious mutations in the cohesin complex subunit STAG2 (21.5% tumors, 44.4% cell lines), homozygous deletion of CDKN2A (13.8% and 50%) and mutations of TP53 (6.2% and 71.9%). We additionally note an increased prevalence of the BRCA2 K3326X polymorphism in EFT patient samples (7.3%) compared to population data (OR 7.1, p = 0.006). Using whole transcriptome sequencing, we find that 11% of tumors pathologically diagnosed as EFT lack a typical EWSR1 fusion oncogene and that these tumors do not have a characteristic Ewing sarcoma gene expression signature. We identify samples harboring novel fusion genes including FUS-NCATc2 and CIC-FOXO4 that may represent distinct small round blue cell tumor variants. In an independent EFT tissue microarray cohort, we show that STAG2 loss as detected by immunohistochemistry may be associated with more advanced disease (p = 0.15) and a modest decrease in overall survival (p = 0.10). These results significantly advance our understanding of the genomic and molecular underpinnings of Ewing sarcoma and provide a foundation towards further efforts to improve diagnosis, prognosis, and precision therapeutics testing.

Identification of microRNAs specific for epithelial cell adhesion molecule-positive tumor cells in hepatocellular carcinoma.

UNLABELLED: Therapies that target cancer stem cells (CSCs) hold promise in eliminating cancer burden. However, normal stem cells are likely to be targeted owing to their similarities to CSCs. It is established that epithelial cell adhesion molecule (EpCAM) is a biomarker for normal hepatic stem cells (HpSCs), and EpCAM(+) AFP(+) hepatocellular carcinoma (HCC) cells have enriched hepatic CSCs. We sought to determine whether specific microRNAs (miRNAs) exist in hepatic CSCs that are not expressed in normal HpSCs. We performed a pair-wise comparison of the miRNA transcriptome of EpCAM(+) and corresponding EpCAM(-) cells isolated from two primary HCC specimens, as well as from two fetal livers and three healthy adult liver donors by small RNA deep sequencing. We found that miR-150, miR-155, and miR-223 were preferentially highly expressed in EpCAM(+) HCC cells, which was further validated. Their gene surrogates, identified using miRNA and messenger RNA profiling in a cohort of 292 HCC patients, were associated with patient prognosis. We further demonstrated that miR-155 was highly expressed in EpCAM(+) HCC cells, compared to corresponding EpCAM(-) HCC cells, fetal livers with enriched normal hepatic progenitors, and normal adult livers with enriched mature hepatocytes. Suppressing miR-155 resulted in a decreased EpCAM(+) fraction in HCC cells and reduced HCC cell colony formation, migration, and invasion in vitro. The reduced levels of identified miR-155 targets predicted the shortened overall survival and time to recurrence of HCC patients. CONCLUSION: miR-155 is highly elevated in EpCAM(+) HCC cells and might serve as a molecular target to eradicate the EpCAM(+) CSC population in human HCCs.

Development of a multi-marker model combining HE4, CA125, progesterone, and estradiol for distinguishing benign from malignant pelvic masses in postmenopausal women.

The purpose of this study was to evaluate HE4, CA125, progesterone (Prog), and estradiol (E2) for differentiating pelvic masses in postmenopausal women and aimed to build a multi-marker model which may improve the diagnostic value. HE4, CA125, Prog, and E2 were detected in 57 benign pelvic masses (BPM) and 92 epithelial ovarian cancer (EOC) patients. A total of 66.66 % of the BPM and EOC serum samples were used for building the differentiation model, and the remaining 33.33 % of the BPM and EOC serum samples were used for validation of the differentiation model. After comparing by Z score statistics, HE4 + CA125 + E2 model was chosen as the best multi-marker model. In the training group, the area under curve of the HE4 + CA125 + E2 model was 0.97 (0.93, 1.00), sensitivities of the model for distinguishing BPM from EOC, from early EOC, and from advanced EOC were 90.16, 86.21, and 95.65 %; specificities were 92.11, 92.11, and 92.11 %. In the validation group, sensitivities of HE4 + CA125 + E2 model for distinguishing BPM from EOC, from early EOC, and from advanced EOC were 96.77, 100.00, and 87.50 %, specificities were 84.21, 100.00, and 84.21 %. The multi-marker model showed significant improvement when compared to CA125 or HE4, and it might be an effective pelvic mass differentiation method.

A novel mixed integer programming for multi-biomarker panel identification by distinguishing malignant from benign colorectal tumors.

Multi-biomarker panels can capture the nonlinear synergy among biomarkers and they are important to aid in the early diagnosis and ultimately battle complex diseases. However, identification of these multi-biomarker panels from case and control data is challenging. For example, the exhaustive search method is computationally infeasible when the data dimension is high. Here, we propose a novel method, MILP_k, to identify serum-based multi-biomarker panel to distinguish colorectal cancers (CRC) from benign colorectal tumors. Specifically, the multi-biomarker panel detection problem is modeled by a mixed integer programming to maximize the classification accuracy. Then we measured the serum profiling data for 101 CRC patients and 95 benign patients. The 61 biomarkers were analyzed individually and further their combinations by our method. We discovered 4 biomarkers as the optimal small multi-biomarker panel, including known CRC biomarkers CEA and IL-10 as well as novel biomarkers IMA and NSE. This multi-biomarker panel obtains leave-one-out cross-validation (LOOCV) accuracy to 0.7857 by nearest centroid classifier. An independent test of this panel by support vector machine (SVM) with threefold cross validation gets an AUC 0.8438. This greatly improves the predictive accuracy by 20% over the single best biomarker. Further extension of this 4-biomarker panel to a larger 13-biomarker panel improves the LOOCV to 0.8673 with independent AUC 0.8437. Comparison with the exhaustive search method shows that our method dramatically reduces the searching time by 1000-fold. Experiments on the early cancer stage samples reveal two panel of biomarkers and show promising accuracy. The proposed method allows us to select the subset of biomarkers with best accuracy to distinguish case and control samples given the number of selected biomarkers. Both receiver operating characteristic curve and precision-recall curve show our method's consistent performance gain in accuracy. Our method also shows its advantage in capturing synergy among selected biomarkers. The multi-biomarker panel far outperforms the simple combination of best single features. Close investigation of the multi-biomarker panel illustrates that our method possesses the ability to remove redundancy and reveals complementary biomarker combinations. In addition, our method is efficient and can select multi-biomarker panel with more than 5 biomarkers, for which the exhaustive methods fail. In conclusion, we propose a promising model to improve the clinical data interpretability and to serve as a useful tool for other complex disease studies. Our small multi-biomarker panel, CEA, IL-10, IMA, and NSE, may provide insights on the disease status of colorectal diseases. The implementation of our method in MATLAB is available via the website: http://doc.aporc.org/wiki/MILP_k.

Identification and characterization of novel serum microRNAs in unstable angina pectoris and subclinical atherosclerotic patients.

BACKGROUND: MicroRNAs (miRNAs) are involved in cardiac developmental and pathological processes, and serum profile is useful for identifying novel miRNAs. METHODS AND RESULTS: Serum samples were collected from unstable angina pectoris (UAP) and subclinical atherosclerotic (AS) patients. Solexa sequencing was used to predict novel miRNAs in 15 control individuals, 15 AS patients and 15 UAP patients. After bioinformatics analysis and filtering out in the newest version of miRbase (version 20.0), three novel miRNAs were validated in 80 control individuals, 80 AS patients and 80 UAP patients by quantitative reverse transcriptase polymerase chain reaction. Two of the three novel microRNAs (N1 and N3) were expressed at the highest levels in the AS group. N1 had an area under curve (AUC) of 0.811 (95% confidence interval 0.743-0.880) for AS. N3 showed a moderate separation with an area under curve (AUC) of 0.748 (95% confidence interval 0.664-0.833) for AS. Combined the two novel microRNAs can significantly distinguish AS from control. CONCLUSIONS: Three novel miRNAs were identified by Solexa sequencing and two of them may be new potential predictors for arthrosclerosis.