Nontargeted Analysis of Coumarins in Source Water and Their Formation of Chlorinated Coumarins as DBPs in Drinking Water.

Coumarin was detected as one of the most abundant compounds by nontargeted analysis of natural product components in actual water samples prior to disinfection. More importantly, prechlorination of humic acid generated 3-hydroxycoumarin and monohydroxy-monomethyl-substituted coumarin with a total yield of ≤10.1%, which suggested the humic substance in raw water is an important source of coumarins. 7-Hydroxycoumarin, 6-hydroxy-4-methylcoumarin, 6,7-dihydroxycoumarin, and 7-methoxy-4-methylcoumarin were identified in raw water by high-performance liquid chromatography-tandem high-resolution mass spectrometry because only some coumarin standards were commercially available. Their chlorination generated monochlorinated and polychlorinated coumarins, and their structures were confirmed by the synthesized standards. These products could form at various dosages of chlorine and pH levels, and some with a concentration of 600 ng/L can be stable in tap water for days. 3,6,8-Trichloro-7-hydroxycoumarin, 3-chloro-7-methoxy-4-methylcoumarin, and 3,6-dichloro-7-methoxy-4-methylcoumarin were first identified in finished water with concentrations of 0.0670, 78.1, and 14.7 ng/L, respectively, but not in source water, suggesting that they are new DBPs formed during disinfection. The cytotoxicity of 3-chloro-7-methoxy-4-methylcoumarin in CHO-K1 cells was comparable to those of 2,6-dibromo-1,4-benzoquinone and 2,6-dichloro-1,4-benzoquinone in TIC-Tox analyses, suggesting that further investigation of their occurrence and control in drinking water systems is warranted.

Identification of RACK1 as a novel regulator of non-structural protein 4 of chikungunya virus.

Chikungunya virus (CHIKV) is a neglected arthropod-borne and anthropogenic alphavirus. Over the past two decades, the CHIKV distribution has undergone significant changes worldwide, from the original tropics and subtropics regions to temperate regions, which has attracted global attention. However, the interactions between CHIKV and its host remain insufficiently understood, which dampens the need for the development of an anti-CHIKV strategy. In this study, on the basis of the optimal overexpression of non-structural protein 4 (nsP4), we explore host interactions of CHIKV nsP4 using mass spectrometry-based protein-protein interaction approaches. The results reveal that some cellular proteins that interact with nsP4 are enriched in the ubiquitin-proteasome pathway. Specifically, the scaffold protein receptor for activated C kinase 1 (RACK1) is identified as a novel host interactor and regulator of CHIKV nsP4. The inhibition of the interaction between RACK1 and nsP4 by harringtonolide results in the reduction of nsP4, which is caused by the promotion of degradation but not the inhibition of nsP4 translation. Furthermore, the decrease in nsP4 triggered by the RACK1 inhibitor can be reversed by the proteasome inhibitor MG132, suggesting that RACK1 can protect nsP4 from degradation through the ubiquitin-proteasome pathway. This study reveals a novel mechanism by which the host factor RACK1 regulates CHIKV nsP4, which could be a potential target for developing drugs against CHIKV.

Degradation characteristics and effect mechanisms of estrogens during aerobic composting of chicken manure based on the orthogonal test.

Environmental estrogens are currently a significant research topic, and poultry manure serves as a crucial source. This study investigated the degradation characteristics and effect mechanisms of six estrogens (E1, 17α-E2, 17ß-E2, E3, 17α-EE2, and DES) during the aerobic composting of chicken manure. An orthogonal test comprising four factors (aeration rate, calcium-magnesium-phosphorus fertilizer (Ca-Mg-P fertilizer), coconut shell biochar, initial moisture content) and three levels of aerobic composting was conducted over a 45-day period to monitor the changes in estrogens and basic parameters. The results indicated that the factors influencing the estrogen degradation rate ranked as: initial moisture content (MC) > Ca-Mg-P fertilizer > aeration rate > coconut shell biochar. These factors significantly influenced the abundance of estrogen-degrading genera. Optimal composting conditions for estrogen degradation were identified as the addition of 10% coconut shell biochar, maintaining an initial moisture content of 60%, and using an aeration rate of 0.08 L min-1∙kg-1DM (dry matter), with an average degradation rate of 86.88% for the six estrogens under these conditions. During the composting process under various treatments, five known estrogen-degrading genera were observed with high relative abundance (max 31.08%), and the predominant genera were Staphylococcus and Brachybacterium for 17α-E2, 17ß-E2, E3, 17α-EE2, and DES, and Pusillimonas for E1. The composition of microbial community structure changed significantly, and the dominated environment factors effecting the composition and succession of these genera were carbon to nitrogen ratio (C/N) and MC. The research results can provide both a theoretical basis and practical reference for the effective degradation of estrogens during the composting of chicken manure.

MIMIC: an optimization method to identify cell type-specific marker panel for cell sorting.

Multi-omics data allow us to select a small set of informative markers for the discrimination of specific cell types and study of cellular heterogeneity. However, it is often challenging to choose an optimal marker panel from the high-dimensional molecular profiles for a large amount of cell types. Here, we propose a method called Mixed Integer programming Model to Identify Cell type-specific marker panel (MIMIC). MIMIC maintains the hierarchical topology among different cell types and simultaneously maximizes the specificity of a fixed number of selected markers. MIMIC was benchmarked on the mouse ENCODE RNA-seq dataset, with 29 diverse tissues, for 43 surface markers (SMs) and 1345 transcription factors (TFs). MIMIC could select biologically meaningful markers and is robust for different accuracy criteria. It shows advantages over the standard single gene-based approaches and widely used dimensional reduction methods, such as multidimensional scaling and t-SNE, both in accuracy and in biological interpretation. Furthermore, the combination of SMs and TFs achieves better specificity than SMs or TFs alone. Applying MIMIC to a large collection of 641 RNA-seq samples covering 231 cell types identifies a panel of TFs and SMs that reveal the modularity of cell type association networks. Finally, the scalability of MIMIC is demonstrated by selecting enhancer markers from mouse ENCODE data. MIMIC is freely available at https://github.com/MengZou1/MIMIC.

Laparoscopic revision of duct-to-mucosa pancreaticojejunostomy anastomotic stricture after laparoscopic pancreaticoduodenectomy.

PURPOSE: Pancreaticojejunostomy stricture (PJS) is an uncommon late complication of laparoscopic pancreaticoduodenectomy (LPD). The incidence, clinical characteristics, and managements of PJS after LPD are still unreported. METHODS: All patients undergoing LPD between January 2015 and December 2019 were identified from an institutional database. All pancreaticojejunostomies were performed using Bing's duct-to-mucosa anastomosis. PJS was diagnosed by computed tomography or magnetic resonance cholangio-pancreatography with secretin administration. Re-operation was performed in those patients with persistent abdominal pain and/or recurrent pancreatitis. Patients' demographic characteristics, perioperative outcomes, and follow-up outcomes were retrospectively collected. RESULTS: During the 5-year study period, 506 cases of LPD were performed. Among these patients, 13 patients (2.6%) were diagnosed with PJS. Only seven patients presented with abdominal pain and/or recurrent pancreatitis and underwent re-operation. The interval between the diagnosis of PJS and the original operation was 23 months. The median operative time was 140 min (range 90 to 210 min). The estimated blood loss was 40 ml (range 10 to 100 ml). The post-operative outcomes were favorable. Only one patient suffered from biochemical fistula. Six of these 7 patients (85.7%) reported complete pain resolution after the re-operation. The other patient reported partial resolution after surgery. All patients did not need to take analgesic drugs after the operation. CONCLUSION: PJS following LPD is a late complication that was underestimated. It is technically safe and clinically effective to perform laparoscopic revision of the PJS after LPD.

Identification of autophagy-related genes in diabetic foot ulcer based on bioinformatic analysis.

Diabetic foot ulcer (DFU) complications involve autophagy dysregulation. This study aimed to identify autophagy-related bioindicators in DFU. Differentially expressed genes (DEGs) between DFU and healthy samples were analysed from the Gene Expression Omnibus (GEO) datasets, GSE7014 and GSE29221. The roles of autophagy-related DEGs were investigated using protein-protein interaction (PPI) networks, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, Gene Ontology (GO) enrichment, and Gene Set Enrichment Analysis (GSEA). Immune cell infiltration's correlation with these DEGs was also assessed. From the Human Autophagy Database (HADB), 232 autophagy-related genes (ARGs) were identified, with an intersection of 17 key DEGs between GSE7014 and GSE29221. These genes are involved in pathways like autophagy-animal, NOD-like receptor signalling, and apoptosis. In the protein network, epidermal growth factor receptor (EGFR) and phosphatase and tensin homologue (PTEN) showed significant interactions with ARGs. Survival analysis indicated the prognostic importance of calpain 2 (CAPN2), integrin subunit beta 1 (ITGB1), and vesicle-associated membrane protein 3 (VAMP3). Lower immune scores were observed in the type 2 diabetes mellitus (DM2) group than in controls. Autophagy and ARGs significantly influence DFU pathophysiology.

The aerobic electron flux is deficient in fumarate respiration of a strict anaerobe Bacteroides thetaiotaomicron.

Why oxygen ceases the growth of strictly anaerobic bacteria is a longstanding question, yet the answer remains unclear. Studies have confirmed that the dehydratase-fumarase containing an iron-sulfur cluster ([4Fe-4S]) is inactivated upon exposure to oxygen in the intestinal obligate anaerobe, Bacteroides thetaiotaomicron (B. thetaiotaomicron); this blocks fumarate respiration, which is the essential energy-producing pathway in anaerobes. Here, we substituted the [4Fe-4S]-dependent fumarase in B. thetaiotaomicron with an iron-free isozyme from E. coli (Ec-FumC). Results show that Ec-FumC successfully performed the catalytic function of fumarase in B. thetaiotaomicron, as the fum-mutant strain that expressed Ec-FumC exhibited succinate-producing ability under anaerobic growth conditions. Ec-FumC is oxygen-resistant and remains active to produce fumarate upon aeration; however, B. thetaiotaomicron mutant that expressed Ec-FumC did not convert fumarate to succinate during air exposure. Biochemical assays of inverted membrane vesicles from wild-type B. thetaiotaomicron confirmed that the electron flux from NADH to fumarate was less efficient in the presence of air as compared to that without oxygen. Our findings suggest that the anaerobic fumarate respiration might be paralyzed due to electron dissipations upon aeration of the obligate anaerobe.

Single-molecule long-read sequencing reveals the chromatin basis of gene expression.

Genome-wide chromatin accessibility and nucleosome occupancy profiles have been widely investigated, while the long-range dynamics remain poorly studied at the single-cell level. Here, we present a new experimental approach, methyltransferase treatment followed by single-molecule long-read sequencing (MeSMLR-seq), for long-range mapping of nucleosomes and chromatin accessibility at single DNA molecules and thus achieve comprehensive-coverage characterization of the corresponding heterogeneity. MeSMLR-seq offers direct measurements of both nucleosome-occupied and nucleosome-evicted regions on a single DNA molecule, which is challenging for many existing methods. We applied MeSMLR-seq to haploid yeast, where single DNA molecules represent single cells, and thus we could investigate the combinatorics of many (up to 356) nucleosomes at long range in single cells. We illustrated the differential organization principles of nucleosomes surrounding the transcription start site for silent and actively transcribed genes, at the single-cell level and in the long-range scale. The heterogeneous patterns of chromatin status spanning multiple genes were phased. Together with single-cell RNA-seq data, we quantitatively revealed how chromatin accessibility correlated with gene transcription positively in a highly heterogeneous scenario. Moreover, we quantified the openness of promoters and investigated the coupled chromatin changes of adjacent genes at single DNA molecules during transcription reprogramming. In addition, we revealed the coupled changes of chromatin accessibility for two neighboring glucose transporter genes in response to changes in glucose concentration.

The influence of cooperative action intention on object affordance: evidence from the perspective-taking ability of individuals.

In complex interactive scenarios, action understanding lies at the heart of social interactions. Nevertheless, the ability to understand action intention may differ among people. The current study distinguished two groups of participants with different social intention-understanding abilities (high and low) based on a perspective-taking task to investigate the influence of social intention on object affordance under conditions of individual and cooperative action intention. In the affordance perception experiment, participants were shown a video with the presenter reaching to grasp an object in different grips and asked to classify objects into kitchen or non-kitchen items by pressing the left- or right-hand button under the two intention conditions. The results showed that the object affordance effects were modulated by the participants' understanding of social intention in the interactive scenarios. Specifically, the object affordance effects were observed only in the high perspective-taking ability group under the condition of cooperative action intention. However, under the condition of individual action intention, object affordance effects were shown in both the high and low perspective-taking ability groups, and the difference between the two groups was not significant. This study suggests that processing of object affordance depends greatly on the contextual correspondence of perception and action and that the understanding of cooperative action intention can affect the activation of object affordance.

[Relationship Between Social Isolation and Health Behaviors and Ulcer Severity in Diabetic Foot Patients].

Objective: To explore the relationship between social isolation and health behaviors and ulcer severity in patients with diabetic foot. Methods: A cross-sectional study was conducted with 160 patients suffering from type 2 diabetes mellitus combined with diabetic foot. The patients received treatment at the Department of Endocrinology and Metabolism, Nanfang Hospital, Southern Medical University between September 2020 and December 2021. Patient information was collected, including the scores for Lubben Social Network Scale and the Wagner classification of foot ulcers. Analysis was conducted to study the characteristics of the patients' health behaviors, including whether they received information and education on diabetic foot, whether there were delays in their attempt to access medical service, the frequency of foot examinations, etc. In addition, patient demographic data were collected, including sex, age, education, and employment status. According to their scores for Lubben Social Network Scale, the patients were divided into a social isolation group ( n=60) and a non-social-isolation group ( n=100). The severity of the foot ulcers and the health behaviors of the two groups were compared to identify differences. Results: The findings suggest that, compared with the non-social-isolation group, the social isolation group had a higher proportion of diabetic foot patients with Wagner grade 3-5 diabetic foot ulcers ( P<0.05). Analysis of the health behaviors showed that the social isolation group had a higher proportion of diabetes foot patients who had never undergone examination of their feet and those who had delayed attempts to access medical service for their condition ( P<0.05). There were no significant differences between the two groups in terms of whether the patients had received information and education concerning diabetic foot, causes of foot injury, self-treatment of wounds, smoking, and drinking. Correlational analysis suggested that the scores of Lubben Social Network Scale were negatively correlated with the delayed attempts to access medical service ( r=-0.353, P=0.001), that is, the higher the degree of social isolation, the longer the delay in patients' attempt to access medical service for their diabetic foot. Conclusions: Social isolation is correlated to health behaviors and ulcer severity in patients with diabetic foot. Giving more attention to the problem of social isolation of diabetic foot patients and increasing their ties with the social environment and the members of their social network may have a positive effect on improving the delays in diabetic foot patients' attempt to access medical service, which is particularly important for follow-up treatment.

Revealing tumor heterogeneity of breast cancer by utilizing the linkage between somatic and germline mutations.

The intra-tumor heterogeneity is associated with cancer progression and therapeutic resistance, such as in breast cancer. While the existing methods for studying tumor heterogeneity only analyze variant allele frequency (VAF), the genotype of variant is also informative for inferring subclones, which can be detected by long reads or paired-end reads. We developed GenoClone to integrate VAF with the genotype of variant innovatively, so it showed superior performance of inferring the number of subclones, estimating the fractions of subclones and identifying somatic single-nucleotide variants composition of subclones. When GenoClone was applied to 389 TCGA breast cancer samples, it revealed extensive intra-tumor heterogeneity. We further found that a few somatic mutations were relevant to the late stage of tumor evolution, including the ones at the oncogene PIK3CA and the tumor suppress gene TP53. Moreover, 52 subclones that were identified from 167 samples shared high similarity of somatic mutations, which were clustered into three groups with the sizes of 24, 14 and 14. It is helpful for understanding the development of breast cancer in certain subgroups of people and the drug development for population level. Furthermore, GenoClone also identified the tumor heterogeneity in different aliquots of the same samples. The implementation of GenoClone is available at http://www.healthcare.uiowa.edu/labs/au/GenoClone/.

Diabetes duration and glycaemic control as predictors of cardiovascular disease and mortality.

AIMS: To assess the associations of diabetes duration and glycaemic control (defined by plasma glycated haemoglobin [HbA1c] level) with the risks of cardiovascular disease (CVD) and all-cause mortality and to determine whether the addition of either or both to the established CVD risk factors can improve predictions. MATERIALS AND METHODS: A total of 435 679 participants from the UK Biobank without CVD at baseline were included. Cox models adjusting for classic risk factors (sociodemographic and anthropometric characteristics, lipid profiles and medication use) were used, and predictive utility was determined by the C-index and net reclassification improvement (NRI). RESULTS: Compared with participants without diabetes, participants with longer diabetes durations and poorer glycaemic control had a higher risk of fatal/nonfatal CVD. Among participants with diabetes, the fully-adjusted hazard ratios (HRs) for diabetes durations of 5 to <10 years, 10 to <15 years and ≥15 years were 1.15 (95% confidence interval [CI] 0.99, 1.34), 1.50 (95% CI 1.26, 1.79) and 2.22 (95% CI 1.90, 2.58; P-trend <0.01), respectively, compared with participants with diabetes durations <5 years. In addition, those with the longest disease duration (≥15 years) and poorer glycaemic control (HbA1c ≥64 mmol/mol [8%]) had the highest risk of fatal/nonfatal CVD (HR 3.12, 95% CI 2.52, 3.86). Among participants with diabetes, the addition of both diabetes duration and glycaemic control levels significantly improved both the C-index (change in C-index +0.0254; 95% CI 0.0111, 0.0398) and the overall NRI for fatal/nonfatal CVD (0.0992; 95% CI 0.0085, 0.1755) beyond the use of the classic risk factors. CONCLUSIONS: Both longer diabetes duration and poorer glycaemic control were associated with elevated risks of CVD and mortality. Clinicians should consider not only glycaemic control but also diabetes duration in CVD risk assessments for participants with diabetes.

Identification and functional analysis of glycemic trait loci in the China Health and Nutrition Survey.

To identify genetic contributions to type 2 diabetes (T2D) and related glycemic traits (fasting glucose, fasting insulin, and HbA1c), we conducted genome-wide association analyses (GWAS) in up to 7,178 Chinese subjects from nine provinces in the China Health and Nutrition Survey (CHNS). We examined patterns of population structure within CHNS and found that allele frequencies differed across provinces, consistent with genetic drift and population substructure. We further validated 32 previously described T2D- and glycemic trait-loci, including G6PC2 and SIX3-SIX2 associated with fasting glucose. At G6PC2, we replicated a known fasting glucose-associated variant (rs34177044) and identified a second signal (rs2232326), a low-frequency (4%), probably damaging missense variant (S324P). A variant within the lead fasting glucose-associated signal at SIX3-SIX2 co-localized with pancreatic islet expression quantitative trait loci (eQTL) for SIX3, SIX2, and three noncoding transcripts. To identify variants functionally responsible for the fasting glucose association at SIX3-SIX2, we tested five candidate variants for allelic differences in regulatory function. The rs12712928-C allele, associated with higher fasting glucose and lower transcript expression level, showed lower transcriptional activity in reporter assays and increased binding to GABP compared to the rs12712928-G, suggesting that rs12712928-C contributes to elevated fasting glucose levels by disrupting an islet enhancer, resulting in reduced gene expression. Taken together, these analyses identified multiple loci associated with glycemic traits across China, and suggest a regulatory mechanism at the SIX3-SIX2 fasting glucose GWAS locus.

Removal efficiency, kinetic, and behavior of antibiotics from sewage treatment plant effluent in a hybrid constructed wetland and a layered biological filter.

Sewage treatment plant (STP) is the major point source of antibiotic contamination, yet the advanced treatment of antibiotic polluted STP effluent has not been given necessary attention. This study is conducted to evaluate the removal efficiency, kinetic, and behavior of sulfonamides, quinolones, tetracyclines, and macrolides antibiotics from STP effluent in a hybrid constructed wetland (HCW) and a layered biological filter (LBF) at different hydraulic loading rates (HLRs). The results showed that the removal efficiency of antibiotics in all the HLRs was ranked as follow: quinolones of HCW (70-95%) > macrolides of HCW (58-77%) > tetracyclines of both systems (59-67%) > quinolones of LBF (28-64%) > macrolides of LBF (13-25%) > sulfonamides of both systems (<0%). The optimal HLR is 1.0 m/day for quinolones and 2.0 m/day for tetracyclines-macrolides in the HCW, and 6.4 m/day for quinolones-tetracyclines in the LBF, respectively. Although HCW performed better on the removal of most antibiotics, LBF exhibited stronger total loading toleration and higher removal loading ability to antibiotics. Among them, quinolones were markedly removed by multiple effect of substrate adsorption, microbial anaerobic degradation, and photolysis in the HCW (planted), and by filter sorption and interception in the LBF (unplanted); adsorption is the dominant elimination approach for tetracyclines in both systems; plant uptake plays a significant role on the removal of macrolides in the HCW.

The role of response readiness in subliminal visuomotor processes.

The present study aims to examine the impact of response readiness on visuomotor processes triggered by subliminal stimuli using a mixed paradigm involving the masked prime paradigm and a foreperiod paradigm. Experiment 1 ensured that response readiness was successfully manipulated in the mixed paradigm. Importantly, Experiment 2 found that the negative compatibility effect (NCE; a behavioral indicator of subliminal visuomotor processes) disappeared and that response time lost its power to modulate the compatibility effect (CE) with reduced response readiness (due to temporal uncertainty). These results of CEs both independent of response latency and across different levels of response latency indicate that response readiness is a prerequisite for obtaining the NCE. The findings suggest that automatic processing of subliminal stimuli is susceptible to top-down control for reducing the interference of irrelevant information, which ensures a high degree of adaptability and flexibility of our cognitive system in interactions with the changing environment.

Complete Sequence of the FII Plasmid p42-2, Carrying blaCTX-M-55, oqxAB, fosA3, and floR from Escherichia coli.

We sequenced a novel conjugative multidrug resistance IncF plasmid, p42-2, isolated from Escherichia coli strain 42-2, previously identified in China. p42-2 is 106,886 bp long, composed of a typical IncFII-type backbone (∼54 kb) and one distinct acquired DNA region spanning ∼53 kb, harboring 12 antibiotic resistance genes [blaCTX-M-55, oqxA, oqxB, fosA3, floR, tetA(A), tetA(R), strA, strB, sul2, aph(3')-II, and ΔblaTEM-1]. The spread of these multidrug resistance determinants on the same plasmid is of great concern and, because of coresistance to antibiotics from different classes, is therapeutically challenging.

NCC-AUC: an AUC optimization method to identify multi-biomarker panel for cancer prognosis from genomic and clinical data.

MOTIVATION: In prognosis and survival studies, an important goal is to identify multi-biomarker panels with predictive power using molecular characteristics or clinical observations. Such analysis is often challenged by censored, small-sample-size, but high-dimensional genomic profiles or clinical data. Therefore, sophisticated models and algorithms are in pressing need. RESULTS: In this study, we propose a novel Area Under Curve (AUC) optimization method for multi-biomarker panel identification named Nearest Centroid Classifier for AUC optimization (NCC-AUC). Our method is motived by the connection between AUC score for classification accuracy evaluation and Harrell's concordance index in survival analysis. This connection allows us to convert the survival time regression problem to a binary classification problem. Then an optimization model is formulated to directly maximize AUC and meanwhile minimize the number of selected features to construct a predictor in the nearest centroid classifier framework. NCC-AUC shows its great performance by validating both in genomic data of breast cancer and clinical data of stage IB Non-Small-Cell Lung Cancer (NSCLC). For the genomic data, NCC-AUC outperforms Support Vector Machine (SVM) and Support Vector Machine-based Recursive Feature Elimination (SVM-RFE) in classification accuracy. It tends to select a multi-biomarker panel with low average redundancy and enriched biological meanings. Also NCC-AUC is more significant in separation of low and high risk cohorts than widely used Cox model (Cox proportional-hazards regression model) and L1-Cox model (L1 penalized in Cox model). These performance gains of NCC-AUC are quite robust across 5 subtypes of breast cancer. Further in an independent clinical data, NCC-AUC outperforms SVM and SVM-RFE in predictive accuracy and is consistently better than Cox model and L1-Cox model in grouping patients into high and low risk categories. CONCLUSION: In summary, NCC-AUC provides a rigorous optimization framework to systematically reveal multi-biomarker panel from genomic and clinical data. It can serve as a useful tool to identify prognostic biomarkers for survival analysis. AVAILABILITY AND IMPLEMENTATION: NCC-AUC is available at http://doc.aporc.org/wiki/NCC-AUC. CONTACT: ywang@amss.ac.cn SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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.

Femtosecond Laser Ablated FBG with Composite Microstructure for Hydrogen Sensor Application.

A composite microstructure in fiber Bragg grating (FBG) with film deposition for hydrogen detection is presented. Through ablated to FBG cladding by a femtosecond laser, straight-trenches and spiral micro-pits are formed. A Pd-Ag film is sputtered on the surface of the laser processed FBG single mode fiber, and acts as hydrogen sensing transducer. The demonstrated experimental outcomes show that a composite structure produced the highest sensitivity of 26.3 pm/%H, nearly sevenfold more sensitive compared with original standard FBG. It offers great potential in engineering applications for its good structure stability and sensitivity.

Development of serum parameters panels for the early detection of pancreatic cancer.

Early detection of pancreatic cancer is promising for improving clinical outcome; however, no effective biomarker has yet been identified. Here, we detected 61 clinical serum parameters in 200 healthy controls (Ctrls), 163 pancreatic ductal adenocarcinoma (PDAC) patients and 109 benign pancreatitis patients (Benign) in the training group. A metropolis algorithm with Monte Carlo simulation was used for identifying parameter panels. Sera from 183 Ctrl, 129 PDAC and 95 Benign individuals were used for cross-validation. Samples from 77 breast, 72 cervical, 101 colorectal, 138 gastric, 108 prostate and 132 lung cancer patients were collected for evaluating cancer selectivity. A panel consisting of carbohydrate antigen (CA)19-9, albumin (ALB), C-reactive protein (CRP) and interleukin (IL)-8 had the highest diagnostic value for discriminating between PDAC and Ctrl. The sensitivity (SN) was 99.39% for all-stage, 96.10% for early-stage and 98.80% for advanced-stage PDAC at 90% specificity (SP). In the validation group, the sensitivities were 93.80, 93.10 and 94.40%, respectively, at 90% SP. This panel also identified 80.52% of the breast cancer, 66.67% cervical cancer, 86.14% colorectal cancer, 89.86% gastric cancer, 71.30% prostate cancer and 93.85% lung cancer samples as non-PDAC. The panel consisting of CA19-9, carbon dioxide, CRP and IL-6 panel had the highest diagnostic value for discriminating between PDAC and Benign. The SN was 74.23% for all-stage, 75.30% for early-stage and 74.40% for advanced-stage PDAC at 90% SP. In the validation group, the sensitivities were 72.10, 76.10 and 67.20%, respectively, at 90% SP. Our parameter panels may aid in the early detection of PDAC to improve clinical outcome.