An Inverse QSAR Method Based on a Two-Layered Model and Integer Programming.

A novel framework for inverse quantitative structure-activity relationships (inverse QSAR) has recently been proposed and developed using both artificial neural networks and mixed integer linear programming. However, classes of chemical graphs treated by the framework are limited. In order to deal with an arbitrary graph in the framework, we introduce a new model, called a two-layered model, and develop a corresponding method. In this model, each chemical graph is regarded as two parts: the exterior and the interior. The exterior consists of maximal acyclic induced subgraphs with bounded height, the interior is the connected subgraph obtained by ignoring the exterior, and the feature vector consists of the frequency of adjacent atom pairs in the interior and the frequency of chemical acyclic graphs in the exterior. Our method is more flexible than the existing method in the sense that any type of graphs can be inferred. We compared the proposed method with an existing method using several data sets obtained from PubChem database. The new method could infer more general chemical graphs with up to 50 non-hydrogen atoms. The proposed inverse QSAR method can be applied to the inference of more general chemical graphs than before.

Association between lymph node ratio and survival outcomes in patients with oral squamous cell carcinoma.

BACKGROUND: Recent reports have shown that the Lymph node ratio (LNR) is useful for predicting the prognosis in some cancers, however there are few reports on the usefulness of LNR in predicting the prognosis of oral squamous cell carcinoma (OSCC). The predictive value of LNR for prognosis of OSCC was investigated. MATERIALS AND METHODS: The study included 152 patients with OSCC and histologically confirmed cervical lymph node metastasis who underwent neck dissection. We analyzed the relationship between LNR and overall survival (OS) and recurrence-free survival (RFS) retrospectively in these cases, with the relationship between prognosis and clinicopathological findings also examined. RESULTS: Using a receiver operating characteristics curve, the LNR cutoff value was set at 0.095, categorizing 64 and 88 cases into high LNR (≥ 0.095) and low LNR (< 0.095) groups, respectively. Regarding OS and RFS, the prognosis was significantly worse in the high LNR group compared with the low LNR group. In multivariate analysis, sex, postoperative nodal stage, and LNR merged as independent prognostic factors. CONCLUSION: This study's findings suggest that LNR may represent a prognostic indicator in OSCC with cervical lymph node metastasis.

Molecular Design Based on Integer Programming and Splitting Data Sets by Hyperplanes.

A novel framework for designing the molecular structure of chemical compounds with a desired chemical property has recently been proposed. The framework infers a desired chemical graph by solving a mixed integer linear program (MILP) that simulates the computation process of two functions: a feature function defined by a two-layered model on chemical graphs and a prediction function constructed by a machine learning method. To improve the learning performance of prediction functions in the framework, we design a method that splits a given data set C into two subsets C(i),i=1,2 by a hyperplane in a chemical space so that most compounds in the first (resp., second) subset have observed values lower (resp., higher) than a threshold θ. We construct a prediction function ψ to the data set C by combining prediction functions ψi,i=1,2 each of which is constructed on C(i) independently. The results of our computational experiments suggest that the proposed method improved the learning performance for several chemical properties to which a good prediction function has been difficult to construct.

An Inverse QSAR Method Based on Linear Regression and Integer Programming.

BACKGROUND: Drug design is one of the important applications of biological science. Extensive studies have been done on computer-aided drug design based on inverse quantitative structure activity relationship (inverse QSAR), which is to infer chemical compounds from given chemical activities and constraints. However, exact or optimal solutions are not guaranteed in most of the existing methods. METHOD: Recently a novel framework based on artificial neural networks (ANNs) and mixed integer linear programming (MILP) has been proposed for designing chemical structures. This framework consists of two phases: an ANN is used to construct a prediction function, and then an MILP formulated on the trained ANN and a graph search algorithm are used to infer desired chemical structures. In this paper, we use linear regression instead of ANNs to construct a prediction function. For this, we derive a novel MILP formulation that simulates the computation process of a prediction function by linear regression. RESULTS: For the first phase, we performed computational experiments using 18 chemical properties, and the proposed method achieved good prediction accuracy for a relatively large number of properties, in comparison with ANNs in our previous work. For the second phase, we performed computational experiments on five chemical properties, and the method could infer chemical structures with around up to 50 non-hydrogen atoms. CONCLUSIONS: Combination of linear regression and integer programming is a potentially useful approach to computational molecular design.

Human telomerase reverse transcriptase protein expression is associated with survival in patients with oral squamous cell carcinoma.

Despite improvements in diagnosis and treatment, the 5-year survival of oral squamous cell carcinoma (OSCC), no matter the location, remains low, averaging 50%. Telomerase is expressed in 85% of malignancies and may play an important role in human carcinogenesis. Its catalytic component is human telomerase reverse transcriptase (hTERT), which has been thought, but not proven, to be involved in survival with OSCC. We investigated whether hTERT protein was a prognostic factor in OSCC by evaluating its association with clinicopathologic findings and OSCC survival. We found that in comparison to patients with high hTERT expression, patients with low hTERT expression survived significantly longer, including a longer 5-year overall survival. In addition, overall survival was significantly correlated to hTERT expression and the histologic grade and N status of the tumor. Disease-free survival was significantly related to hTERT expression, the histologic grade and N status of the tumor, and mode of invasion. These results suggest that hTERT protein is involved in cervical lymph node metastasis, that its levels may be increased during carcinogenesis, and that it may influence tumor invasion. We believe that this study is the first to demonstrate that OSCC with high hTERT expression carries a worse prognosis than cases with low hTERT expression.

A Novel Method for Inferring Chemical Compounds With Prescribed Topological Substructures Based on Integer Programming.

Drug discovery is one of the major goals of computational biology and bioinformatics. A novel framework has recently been proposed for the design of chemical graphs using both artificial neural networks (ANNs) and mixed integer linear programming (MILP). This method consists of a prediction phase and an inverse prediction phase. In the first phase, an ANN is trained using data on existing chemical compounds. In the second phase, given a target chemical property, a feature vector is inferred by solving an MILP formulated from the trained ANN and then a set of chemical structures is enumerated by a graph enumeration algorithm. Although exact solutions are guaranteed by this framework, the types of chemical graphs have been restricted to such classes as trees, monocyclic graphs, and graphs with a specified polymer topology with cycle index up to 2. To overcome the limitation on the topological structure, we propose a new flexible modeling method to the framework so that we can specify a topological substructure of graphs and a partial assignment of chemical elements and bond-multiplicity to a target graph. The results of computational experiments suggest that the proposed system can infer chemical graphs with around up to 50 non-hydrogen atoms.

A guiding role of the Arabidopsis circadian clock in cell differentiation revealed by time-series single-cell RNA sequencing.

Circadian rhythms and progression of cell differentiation are closely coupled in multicellular organisms. However, whether establishment of circadian rhythms regulates cell differentiation or vice versa has not been elucidated due to technical limitations. Here, we exploit high cell fate plasticity of plant cells to perform single-cell RNA sequencing during the entire process of cell differentiation. By analyzing reconstructed actual time series of the differentiation processes at single-cell resolution using a method we developed (PeakMatch), we find that the expression profile of clock genes is changed prior to cell differentiation, including induction of the clock gene LUX ARRYTHMO (LUX). ChIP sequencing analysis reveals that LUX induction in early differentiating cells directly targets genes involved in cell-cycle progression to regulate cell differentiation. Taken together, these results not only reveal a guiding role of the plant circadian clock in cell differentiation but also provide an approach for time-series analysis at single-cell resolution.

Depth of invasion determined by magnetic resonance imaging in tongue cancer can be a predictor of cervical lymph node metastasis.

OBJECTIVES: We evaluated the relationships between depth of invasion (DOI) of tongue cancer, as measured with preoperative T1- and T2-weighted magnetic resonance imaging (MRI) and postoperative histopathologic (Path) specimens, with cervical lymph node metastasis (CLNM) and tumor stage. We also calculated the correlation of MRI and Path DOI measurements. STUDY DESIGN: This retrospective study included 101 patients who had squamous cell carcinoma of the tongue and were treated surgically. Two observers measured DOI on all 3 modalities. RESULTS: DOI thresholds for predicting CLNM with high diagnostic efficacy were 6.99 mm and 8.32 mm for MRI and 5 mm for Path. DOI values from all modalities were significantly different for tumors with and without CLNM (P < .01) and for the 4 TNM stages (P ≤ .05), with increasing values corresponding to advancement in tumor stage. Addition of DOI changed the T level of many tumors based on the new TNM (tumor-node-metastasis) classification. The correlation coefficient between DOI calculated on each MRI sequence and Path was 0.90. CONCLUSIONS: MRI-derived DOI accurately reflected the subsequent metastatic status and degree of progression of tumor stages, with a strong positive correlation to Path values, and may be considered a predictor of tumor stage and CLNM.

The methylation status and expression of human telomerase reverse transcriptase is significantly high in oral carcinogenesis.

Telomerase activity is present in most cancers and is tightly regulated by the expression of human telomerase reverse transcriptase (hTERT). Hypermethylation in the promoter region of hTERT contributes to the regulation of hTERT expression. In this study, we investigated the methylation and expression of hTERT in oral squamous cell carcinoma (OSCC), oral leukoplakia, and normal oral mucosa. Furthermore, we investigated the significance of hTERT to the clinicopathological findings of OSCC. 35 OSCC, 50 oral leukoplakia (epithelial dysplasia n = 25, squamous cell hyperplasia n = 25), and 10 normal oral mucosa samples were investigated through methylation-specific PCR. Immunohistochemistry was analyzed in 35 OSCC, 50 oral leukoplakia, and 4 normal oral mucosa samples. The methylation and expression of hTERT increased from normal oral mucosa to oral leukoplakia to OSCC. In OSCC, all samples were methylated. However, partial methylation (20%) or unmethylation (80%), but never complete methylation, was observed in normal oral mucosa. Additionally, hTERT expression correlated with cervical lymph node metastasis. These results suggested that the methylation and expression of hTERT is high in oral carcinogenesis and may play an important role in oral cancer. hTERT expression may also be predictive of cervical lymph node metastasis.

Electrochemical telomerase assay for screening for oral cancer.

Telomerase has long been known to be a marker for cancer. We have developed a new method of detecting it: the electrochemical telomerase assay (ECTA). We have previously confirmed that the assay is easier to do and more precise than the conventional telomeric repeat amplification protocol, which is currently the most widely used. Here we describe a pilot study made to establish a screening system for oral cancer using ECTA. We evaluated three types of clinical samples obtained from 44 patients with oral cancer and 26 healthy volunteers: exfoliated cells from the whole oral cavity, exfoliated cells from local lesions, and tissue from the lesion itself. The current increase ratio (Δi) obtained by ECTA was significantly higher in the oral cancer group for each type of sampling used. The threshold value for Δi was 19% when calculated by analysis of receiver-operating characteristic curves. Sensitivity and specificity values were 86% and 85% for cells from the oral cavity, 82% and 85% in cells from local lesions, and 95% and 92% in cells from the tumour itself, respectively. There were also no significant differences in sensitivity and specificity associated with age, size of tumour, site of lesion, or degree of malignancy. ECTA therefore seems to be a promising assay for screening for oral cancer.

Fluorescence-guided bone resection by using Visually Enhanced Lesion Scope in diffuse chronic sclerosingosteomyelitis of the mandible: Clinical and pathological evaluation.

UNLABELLED: Diffuse chronic sclerosingosteomyelitis (DCSO) is a refractory disease, becausethe etiology and pathogenesis remain poorly understood and to determine the border betweenunhealthy boneandhealthybone is difficult. However, progressive inflammation, clinical symptoms and a high recurrence rate of DCSO were the reasons for surgical treatment. We report a case of a 66-year old woman with DCSO of the right side of mandible who was treated with hemimandibulectomy and simultaneous reconstruction by vascularized free fibula flap. After preoperative administration of minocycline for 1 month, the bone fluorescence was successfully monitored by using a Visually Enhanced Lesion Scope (VELscope®). Intraoperatively, we could determine the resection boundaries. We investigated the clinical and histopathological findings. The fluorescence findings were well correlated with histopathological findings. Using a VELscope®was handy and useful to determine the border between DCSO lesion andhealthybone.The free fibula flap under the minocycline-derived bone fluorescence by using a VELscope®offered a good quality of mandibular bone and the successful management of an advanced and refractory DCSO. KEY WORDS: Fluorescence-guided bone resection, fibular free flap, osteomyelitis of the mandible, diffuse chronicosteomyelitis, VELscope®.

Ferrocenylnaphthalene diimide-based electrochemical detection of aberrant methylation in hTERT gene.

Since aberrant methylation at CpG sites is linked to the silencing of tumor suppressor genes, DNA methylation analysis is important for cancer diagnosis. We developed ferrocenylnaphthalene diimide (FND), which has two ferrocenyl moieties at the substituent termini, as an electrochemical indicator for hybridized DNA duplexes. In this study, we attempted to detect aberrant methylation of human telomerase reverse transcriptase gene (hTERT), an efficient cancer marker, using FND-based hybridization coupled with electrochemical detection via a multi-electrode chip.