Mechanical transmission of dengue virus by Aedes aegypti may influence disease transmission dynamics during outbreaks.

BACKGROUND: Dengue virus outbreaks are increasing in number and severity worldwide. Viral transmission is assumed to require a minimum time period of viral replication within the mosquito midgut. It is unknown if alternative transmission periods not requiring replication are possible. METHODS: We used a mouse model of dengue virus transmission to investigate the potential of mechanical transmission of dengue virus. We investigated minimal viral titres necessary for development of symptoms in bitten mice and used resulting parameters to inform a new model of dengue virus transmission within a susceptible population. FINDINGS: Naïve mice bitten by mosquitoes immediately after they took partial blood meals from dengue infected mice showed symptoms of dengue virus, followed by mortality. Incorporation of mechanical transmission into mathematical models of dengue virus transmission suggest that this supplemental transmission route could result in larger outbreaks which peak sooner. INTERPRETATION: The potential of dengue transmission routes independent of midgut viral replication has implications for vector control strategies that target mosquito lifespan and suggest the possibility of similar mechanical transmission routes in other disease-carrying mosquitoes. FUNDING: This study was funded by grants from the National Health Research Institutes, Taiwan (04D2-MMMOST02), the Human Frontier Science Program (RGP0033/2021), the National Institutes of Health (1R01AI143698-01A1, R01AI151004 and DP2AI152071) and the Ministry of Science and Technology, Taiwan (MOST104-2321-B-400-016).

CLEC5A mediates Zika virus-induced testicular damage.

BACKGROUND: Zika virus (ZIKV) infection is clinically known to induce testicular swelling, termed orchitis, and potentially impact male sterility, but the underlying mechanisms remain unclear. Previous reports suggested that C-type lectins play important roles in mediating virus-induced inflammatory reactions and pathogenesis. We thus investigated whether C-type lectins modulate ZIKV-induced testicular damage. METHODS: C-type lectin domain family 5 member A (CLEC5A) knockout mice were generated in a STAT1-deficient immunocompromised background (denoted clec5a-/-stat1-/-) to enable testing of the role played by CLEC5A after ZIKV infection in a mosquito-to-mouse disease model. Following ZIKV infection, mice were subjected to an array of analyses to evaluate testicular damage, including ZIKV infectivity and neutrophil infiltration estimation via quantitative RT-PCR or histology and immunohistochemistry, inflammatory cytokine and testosterone detection, and spermatozoon counting. Furthermore, DNAX-activating proteins for 12 kDa (DAP12) knockout mice (dap12-/-stat1-/-) were generated and used to evaluate ZIKV infectivity, inflammation, and spermatozoa function in order to investigate the potential mechanisms engaged by CLEC5A. RESULTS: Compared to experiments conducted in ZIKV-infected stat1-/- mice, infected clec5a-/-stat1-/- mice showed reductions in testicular ZIKV titer, local inflammation and apoptosis in testis and epididymis, neutrophil invasion, and sperm count and motility. CLEC5A, a myeloid pattern recognition receptor, therefore appears involved in the pathogenesis of ZIKV-induced orchitis and oligospermia. Furthermore, DAP12 expression was found to be decreased in the testis and epididymis tissues of clec5a-/-stat1-/- mice. As for CLEC5A deficient mice, ZIKV-infected DAP12-deficient mice also showed reductions in testicular ZIKV titer and local inflammation, as well as improved spermatozoa function, as compared to controls. CLEC5A-associated DAP12 signaling appears to in part regulate ZIKV-induced testicular damage. CONCLUSIONS: Our analyses reveal a critical role for CLEC5A in ZIKV-induced proinflammatory responses, as CLEC5A enables leukocytes to infiltrate past the blood-testis barrier and induce testicular and epididymal tissue damage. CLEC5A is thus a potential therapeutic target for the prevention of injuries to male reproductive organs in ZIKV patients.

Excitotoxic stimulation activates distinct pathogenic and protective expression signatures in the hippocampus.

Excitotoxic events underlying ischaemic and traumatic brain injuries activate degenerative and protective pathways, particularly in the hippocampus. To understand opposing pathways that determine the brain's response to excitotoxicity, we used hippocampal explants, thereby eliminating systemic variables during a precise protocol of excitatory stimulation. N-methyl-d-aspartate (NMDA) was applied for 20 min and total RNA isolated one and 24 h later for neurobiology-specific microarrays. Distinct groups of genes exhibited early vs. delayed induction, with 63 genes exclusively reduced 24-h post-insult. Egr-1 and NOR-1 displayed biphasic transcriptional modulation: early induction followed by delayed suppression. Opposing events of NMDA-induced genes linked to pathogenesis and cell survival constituted the early expression signature. Delayed degenerative indicators (up-regulated pathogenic genes, down-regulated pro-survival genes) and opposing compensatory responses (down-regulated pathogenic genes, up-regulated pro-survival genes) generated networks with temporal gene profiles mirroring coexpression network clustering. We then used the expression profiles to test whether NF-κB, a potent transcription factor implicated in both degenerative and protective pathways, is involved in the opposing responses. The NF-κB inhibitor MG-132 indeed altered NMDA-mediated transcriptional changes, revealing components of opposing expression signatures that converge on the single response element. Overall, this study identified counteracting avenues among the distinct responses to excitotoxicity, thereby suggesting multi-target treatment strategies and implications for predictive medicine.

Correction: Broad dengue neutralization in mosquitoes expressing an engineered antibody.

[This corrects the article DOI: 10.1371/journal.ppat.1008103.].

Broad dengue neutralization in mosquitoes expressing an engineered antibody.

With dengue virus (DENV) becoming endemic in tropical and subtropical regions worldwide, there is a pressing global demand for effective strategies to control the mosquitoes that spread this disease. Recent advances in genetic engineering technologies have made it possible to create mosquitoes with reduced vector competence, limiting their ability to acquire and transmit pathogens. Here we describe the development of Aedes aegypti mosquitoes synthetically engineered to impede vector competence to DENV. These mosquitoes express a gene encoding an engineered single-chain variable fragment derived from a broadly neutralizing DENV human monoclonal antibody and have significantly reduced viral infection, dissemination, and transmission rates for all four major antigenically distinct DENV serotypes. Importantly, this is the first engineered approach that targets all DENV serotypes, which is crucial for effective disease suppression. These results provide a compelling route for developing effective genetic-based DENV control strategies, which could be extended to curtail other arboviruses.

Engineered resistance to Zika virus in transgenic Aedes aegypti expressing a polycistronic cluster of synthetic small RNAs.

Recent Zika virus (ZIKV) outbreaks have highlighted the necessity for development of novel vector control strategies to combat arboviral transmission, including genetic versions of the sterile insect technique, artificial infection with Wolbachia to reduce population size and/or vectoring competency, and gene drive-based methods. Here, we describe the development of mosquitoes synthetically engineered to impede vector competence to ZIKV. We demonstrate that a polycistronic cluster of engineered synthetic small RNAs targeting ZIKV is expressed and fully processed in Aedes aegypti, ensuring the formation of mature synthetic small RNAs in the midgut where ZIKV resides in the early stages of infection. Critically, we demonstrate that engineered Ae. aegypti mosquitoes harboring the anti-ZIKV transgene have significantly reduced viral infection, dissemination, and transmission rates of ZIKV. Taken together, these compelling results provide a promising path forward for development of effective genetic-based ZIKV control strategies, which could potentially be extended to curtail other arboviruses.

Sequential deposition: optimization of solvent swelling for high-performance polymer solar cells.

Organic solar cells based on a typical DPP polymer were systematically optimized by a solvent swelling assisted sequential deposition process. We investigated the influence of solvent swelling on the morphology and structure order of the swollen film and the resultant device performance. Morphological and structural characterization confirmed the realization of ideal bulk heterojunctions using a suitable swelling solvent. A trilayered morphology was also found with the conjugated polymer concentrated bottom layer, PC71BM concentrated top layer, and interpenetrated networks of donor and acceptor in the middle by solvent swelling instead of thermal annealing in the sequential solution processing method. We proposed a simple strategy to optimize the sequential deposition fabricated devices by tuning the concentration of the PC71BM solution instead of thermal annealing. The best device showed a PCE of 7.59% with a Voc of 0.61 V, Jsc of 17.95 mA/cm(2), and FF of 69.6%, which is the highest reported efficiency for devices fabricated by a sequential processing method and among the best results for DPP polymers.

Azulene methacrylate polymers: synthesis, electronic properties, and solar cell fabrication.

We report the synthesis of novel azulene-substituted methacrylate polymers by free radical polymerization, in which the azulene moieties represent hydrophobic dipoles strung pendant to the polymer backbone and impart unique electronic properties to the polymers. Tunable optoelectronic properties were realized by adjusting the azulene density, ranging from homopolymers (having one azulene group per repeat unit) to copolymers in which the azulene density was diluted with other pendant groups. Treating these polymers with organic acids revealed optical and excitonic behavior that depended critically on the azulene density along the polymer chain. Copolymers of azulene with zwitterionic methacrylates proved useful as cathode modification layers in bulk-heterojunction solar cells, where the relative azulene content affected the device metrics and the power conversion efficiency reached 7.9%.

Machine learning-based methods for prediction of linear B-cell epitopes.

B-cell epitope prediction facilitates immunologists in designing peptide-based vaccine, diagnostic test, disease prevention, treatment, and antibody production. In comparison with T-cell epitope prediction, the performance of variable length B-cell epitope prediction is still yet to be satisfied. Fortunately, due to increasingly available verified epitope databases, bioinformaticians could adopt machine learning-based algorithms on all curated data to design an improved prediction tool for biomedical researchers. Here, we have reviewed related epitope prediction papers, especially those for linear B-cell epitope prediction. It should be noticed that a combination of selected propensity scales and statistics of epitope residues with machine learning-based tools formulated a general way for constructing linear B-cell epitope prediction systems. It is also observed from most of the comparison results that the kernel method of support vector machine (SVM) classifier outperformed other machine learning-based approaches. Hence, in this chapter, except reviewing recently published papers, we have introduced the fundamentals of B-cell epitope and SVM techniques. In addition, an example of linear B-cell prediction system based on physicochemical features and amino acid combinations is illustrated in details.

A local average distance descriptor for flexible protein structure comparison.

BACKGROUND: Protein structures are flexible and often show conformational changes upon binding to other molecules to exert biological functions. As protein structures correlate with characteristic functions, structure comparison allows classification and prediction of proteins of undefined functions. However, most comparison methods treat proteins as rigid bodies and cannot retrieve similarities of proteins with large conformational changes effectively. RESULTS: In this paper, we propose a novel descriptor, local average distance (LAD), based on either the geodesic distances (GDs) or Euclidean distances (EDs) for pairwise flexible protein structure comparison. The proposed method was compared with 7 structural alignment methods and 7 shape descriptors on two datasets comprising hinge bending motions from the MolMovDB, and the results have shown that our method outperformed all other methods regarding retrieving similar structures in terms of precision-recall curve, retrieval success rate, R-precision, mean average precision and F1-measure. CONCLUSIONS: Both ED- and GD-based LAD descriptors are effective to search deformed structures and overcome the problems of self-connection caused by a large bending motion. We have also demonstrated that the ED-based LAD is more robust than the GD-based descriptor. The proposed algorithm provides an alternative approach for blasting structure database, discovering previously unknown conformational relationships, and reorganizing protein structure classification.

Preparation of Low Band Gap Fibrillar Structures by Solvent-Induced Crystallization.

Solvent-induced crystallization of the low band gap polymer poly[N-9″-heptadecanyl-2,7-carbazole-alt-5,5-(4',7'-di-2-thienyl-2',1',3'-benzothiadiazole)] (PCDTBT) was shown to give fibril-like structures of 40-60 nm width and ∼0.5 µm length. These structures, formed by heating and cooling PCDTBT in a marginal solvent for the polymer, were characterized by AFM, TEM, GI-WAXS, and steady state absorption and emission spectroscopy. The width of the PCDTBT structures suggests that the polymer chains are oriented perpendicular to the fiber axis, while the observed undulated structure, as revealed by AFM, suggests that the nanostructures may be composed of smaller crystalline units that associate preferentially on specific faces of the crystals. The spectroscopic signatures of the suspended PCDTBT fibrils resembled that of the polymer in solution, in contrast to features associated with the fibril formation of the well-known conjugated polymer poly(3-hexyl thiophene) (P3HT). The solution-based crystallization of PCDTBT reported herein offers insight into the self-assembly of conjugated polymers toward better understanding of their role in photovoltaic devices.

Protein-ligand binding region prediction (PLB-SAVE) based on geometric features and CUDA acceleration.

BACKGROUND: Protein-ligand interactions are key processes in triggering and controlling biological functions within cells. Prediction of protein binding regions on the protein surface assists in understanding the mechanisms and principles of molecular recognition. In silico geometrical shape analysis plays a primary step in analyzing the spatial characteristics of protein binding regions and facilitates applications of bioinformatics in drug discovery and design. Here, we describe the novel software, PLB-SAVE, which uses parallel processing technology and is ideally suited to extract the geometrical construct of solid angles from surface atoms. Representative clusters and corresponding anchors were identified from all surface elements and were assigned according to the ranking of their solid angles. In addition, cavity depth indicators were obtained by proportional transformation of solid angles and cavity volumes were calculated by scanning multiple directional vectors within each selected cavity. Both depth and volume characteristics were combined with various weighting coefficients to rank predicted potential binding regions. RESULTS: Two test datasets from LigASite, each containing 388 bound and unbound structures, were used to predict binding regions using PLB-SAVE and two well-known prediction systems, SiteHound and MetaPocket2.0 (MPK2). PLB-SAVE outperformed the other programs with accuracy rates of 94.3% for unbound proteins and 95.5% for bound proteins via a tenfold cross-validation process. Additionally, because the parallel processing architecture was designed to enhance the computational efficiency, we obtained an average of 160-fold increase in computational time. CONCLUSIONS: In silico binding region prediction is considered the initial stage in structure-based drug design. To improve the efficacy of biological experiments for drug development, we developed PLB-SAVE, which uses only geometrical features of proteins and achieves a good overall performance for protein-ligand binding region prediction. Based on the same approach and rationale, this method can also be applied to predict carbohydrate-antibody interactions for further design and development of carbohydrate-based vaccines. PLB-SAVE is available at http://save.cs.ntou.edu.tw.

Helical phase from blending of chiral block copolymer and homopolymer.

The phase behavior of the binary blends of polystyrene-b-poly(L-lactide) chiral block copolymer (BCP*) and polystyrene homopolymer (HS) is found to be strongly dependent on the molecular weight (M(n)) of the HS. A helical phase is formed in the blends with low-M(n) HS due to an enhancement of helical steric hindrance.

The influence of operating parameters on the drug release and antibacterial performances of alginate fibrous dressings prepared by wet spinning.

Wet spinning was used to manufacture fibrous alginate hydrogel wound dressings. Samples manufactured using varied operating parameters (decreased air pressure and calcium concentration or increased nozzle diameter and alginate concentration) were compared with the control samples. The changes in the fiber size, Young's modulus, swelling ratio, fetal bovine serum (BSA) release efficacy, water vapor transmission rate (WVTR) and bacterial inhibition potential due to alterations of the operating parameters were measured. The samples manufactured using altered operating parameters had larger fiber sizes (p < 0.05) and lower Young's moduli (p < 0.05). The changes in swelling ratios, BSA release efficacies, WVTR and bacterial inhibition potential showed a significant dependence on the degree of calcium crosslinking of the hydrogel and on how tightly the fibers were bound with one another. By manipulating the operating parameters in the wet-spinning system, wound dressings with different properties were successfully made.

Prediction of B-cell linear epitopes with a combination of support vector machine classification and amino acid propensity identification.

Epitopes are antigenic determinants that are useful because they induce B-cell antibody production and stimulate T-cell activation. Bioinformatics can enable rapid, efficient prediction of potential epitopes. Here, we designed a novel B-cell linear epitope prediction system called LEPS, Linear Epitope Prediction by Propensities and Support Vector Machine, that combined physico-chemical propensity identification and support vector machine (SVM) classification. We tested the LEPS on four datasets: AntiJen, HIV, a newly generated PC, and AHP, a combination of these three datasets. Peptides with globally or locally high physicochemical propensities were first identified as primitive linear epitope (LE) candidates. Then, candidates were classified with the SVM based on the unique features of amino acid segments. This reduced the number of predicted epitopes and enhanced the positive prediction value (PPV). Compared to four other well-known LE prediction systems, the LEPS achieved the highest accuracy (72.52%), specificity (84.22%), PPV (32.07%), and Matthews' correlation coefficient (10.36%).

BiMFG: bioinformatics tools for marine and freshwater species.

Biomolecule sequences and structures of land, air and water species are determined rapidly and the data entries are unevenly distributed for different organisms. It frequently leads to the BLAST results of homologous search containing undesirable entries from organisms living in different environments. To reduce irrelevant searching results, a separate database for comparative genomics is urgently required. A comprehensive bioinformatics tool set and an integrated database, named Bioinformatics tools for Marine and Freshwater Genomics (BiMFG), are constructed for comparative analyses among model species and underwater species. Novel matching techniques based on conserved motifs and/or secondary structure elements are designed for efficiently and effectively retrieving and aligning remote sequences through cross-species comparisons. It is especially helpful when sequences under analysis possess low similarities and unresolved structural information. In addition, the system provides core techniques of multiple sequence alignment, multiple second structure profile alignment and iteratively refined multiple structural alignments for biodiversity analysis and verification in marine and freshwater biology. The BiMFG web server is freely available for use at http://bimfg.cs.ntou.edu.tw/.

An experimental investigation of masking in the US FDA adverse event reporting system database.

BACKGROUND: A phenomenon of 'masking' or 'cloaking' in pharmacovigilance data mining has been described, which can potentially cause signals of disproportionate reporting (SDRs) to be missed, particularly in pharmaceutical company databases. Masking has been predicted theoretically, observed anecdotally or studied to a limited extent in both pharmaceutical company and health authority databases, but no previous publication systematically assesses its occurrence in a large health authority database. OBJECTIVE: To explore the nature, extent and possible consequences of masking in the US FDA Adverse Event Reporting System (AERS) database by applying various experimental unmasking protocols to a set of drugs and events representing realistic pharmacovigilance analysis conditions. METHODS: This study employed AERS data from 2001 through 2005. For a set of 63 Medical Dictionary for Regulatory Activities (MedDRA®) Preferred Terms (PTs), disproportionality analysis was carried out with respect to all drugs included in the AERS database, using a previously described urn-model-based algorithm. We specifically sought masking in which drug removal induced an increase in the statistical representation of a drug-event combination (DEC) that resulted in the emergence of a new SDR. We performed a series of unmasking experiments selecting drugs for removal using rational statistical decision rules based on the requirement of a reporting ratio (RR) >1, top-ranked statistical unexpectedness (SU) and relatedness as reflected in the WHO Anatomical Therapeutic Chemical level 4 (ATC4) grouping. In order to assess the possible extent of residual masking we performed two supplemental purely empirical analyses on a limited subset of data. This entailed testing every drug and drug group to determine which was most influential in uncovering masked SDRs. We assessed the strength of external evidence for a causal association for a small number of masked SDRs involving a subset of 29 drugs for which level of evidence adjudication was available from a previous study. RESULTS: The original disproportionality analysis identified 8719 SDRs for the 63 PTs. The SU-based unmasking protocols generated variable numbers of masked SDRs ranging from 38 to 156, representing a 0.43-1.8% increase over the number of baseline SDRs. A significant number of baseline SDRs were also lost in the course of our experiments. The trend in the number of gained SDRs per report removed was inversely related to the number of lost SDRs per protocol. Both the number and nature of the reports removed influenced the number of gained SDRs observed. The purely empirical protocols unmasked up to ten times as many SDRs. None of the masked SDRs had strong external evidence supporting a causal association. Most involved associations for which there was no external supporting evidence or were in the original product label. For two masked SDRs, there was external evidence of a possible causal association. CONCLUSIONS: We documented masking in the FDA AERS database. Attempts at unmasking SDRs using practically implementable protocols produced only small changes in the output of SDRs in our analysis. This is undoubtedly related to the large size and diversity of the database, but the complex interdependencies between drugs and events in authentic spontaneous reporting system (SRS) databases, and the impact of measures of statistical variability that are typically used in real-world disproportionality analysis, may be additional factors that constrain the discovery of masked SDRs and which may also operate in pharmaceutical company databases. Empirical determination of the most influential drugs may uncover significantly more SDRs than protocols based on predetermined statistical selection rules but are impractical except possibly for evaluating specific events. Routine global exercises to elicit masking, especially in large health authority databases are not justified based on results available to date. Exercises to elicit unmasking should be driven by prior knowledge or obvious data imbalances.

Detection and alignment of 3D domain swapping proteins using angle-distance image-based secondary structural matching techniques.

This work presents a novel detection method for three-dimensional domain swapping (DS), a mechanism for forming protein quaternary structures that can be visualized as if monomers had "opened" their "closed" structures and exchanged the opened portion to form intertwined oligomers. Since the first report of DS in the mid 1990s, an increasing number of identified cases has led to the postulation that DS might occur in a protein with an unconstrained terminus under appropriate conditions. DS may play important roles in the molecular evolution and functional regulation of proteins and the formation of depositions in Alzheimer's and prion diseases. Moreover, it is promising for designing auto-assembling biomaterials. Despite the increasing interest in DS, related bioinformatics methods are rarely available. Owing to a dramatic conformational difference between the monomeric/closed and oligomeric/open forms, conventional structural comparison methods are inadequate for detecting DS. Hence, there is also a lack of comprehensive datasets for studying DS. Based on angle-distance (A-D) image transformations of secondary structural elements (SSEs), specific patterns within A-D images can be recognized and classified for structural similarities. In this work, a matching algorithm to extract corresponding SSE pairs from A-D images and a novel DS score have been designed and demonstrated to be applicable to the detection of DS relationships. The Matthews correlation coefficient (MCC) and sensitivity of the proposed DS-detecting method were higher than 0.81 even when the sequence identities of the proteins examined were lower than 10%. On average, the alignment percentage and root-mean-square distance (RMSD) computed by the proposed method were 90% and 1.8Å for a set of 1,211 DS-related pairs of proteins. The performances of structural alignments remain high and stable for DS-related homologs with less than 10% sequence identities. In addition, the quality of its hinge loop determination is comparable to that of manual inspection. This method has been implemented as a web-based tool, which requires two protein structures as the input and then the type and/or existence of DS relationships between the input structures are determined according to the A-D image-based structural alignments and the DS score. The proposed method is expected to trigger large-scale studies of this interesting structural phenomenon and facilitate related applications.

Block copolymers with a twist.

Chiral block copolymers (BCPs*) comprising chiral entities were designed to fabricate helical architectures (i.e., twisted morphologies) from self-assembly. A new helical phase (H*) with P622 symmetry was discovered in the self-assembly of poly(styrene)-b-poly(l-lactide) (PS-PLLA) BCPs*. Hexagonally packed, interdigitated PLLA helical microdomains in a PS matrix were directly visualized by electron tomography. The phase diagram of the PS-PLLA BCPs* was also established. Phase transitions from the H* phase to the stable cylinder and gyroid phases were found after long-time annealing, suggesting that the H* is a long-lived metastable phase. In contrast to racemic poly(styrene)-b-poly(d,l-lactide) BCPs, chiral interaction significantly enhances the incompatibility between achiral PS and chiral PLLA blocks in the PS-PLLA BCPs* and can be estimated through the determination of the interaction parameter.

HDAC3 impacts multiple oncogenic pathways in colon cancer cells with effects on Wnt and vitamin D signaling.

Histone deacetylase 3 (HDAC3) is overexpressed in approximately half of all colon adenocarcinomas. We took an RNAi approach to determine how HDAC3 influenced chromatin modifications and the expression of growth regulatory genes in colon cancer cells. A survey of histone modifications revealed that HDAC3 knockdown in SW480 cells significantly increased histone H4-K12 acetylation, a modification present during chromatin assembly that has been implicated in imprinting. This modification was found to be most prominent in proliferating cells in the intestinal crypt and in APC(Min) tumors, but was less pronounced in the tumors that overexpress HDAC3. Gene expression profiling of SW480 revealed that HDAC3 shRNA impacted the expression of genes in the Wnt and vitamin D signaling pathways. The impact of HDAC3 on Wnt signaling was complex, with both positive and negative effects observed. However, long-term knockdown of HDAC3 suppressed beta-catenin translocation from the plasma membrane to the nucleus, and increased expression of Wnt inhibitors TLE1, TLE4 and SMO. HDAC3 knockdown also enhanced expression of the TLE1 and TLE4 repressors in HT-29 and HCT116 cells. HDAC3 shRNA enhanced expression of the vitamin D receptor in SW480 and HCT116 cells, and rendered SW480 cells sensitive to 1,25-dihydroxyvitamin D3. We propose that HDAC3 overexpression alters the epigenetic programming of colon cancer cells to impact intracellular Wnt signaling and their sensitivity to external growth regulation by vitamin D.