Modeling a gene's expression from its intergenic locus and trans-regulatory context is a fundamental goal in computational biology. Owing to the distributed nature of cis-regulatory information and the poorly understood mechanisms that integrate such information, gene locus modeling is a more challenging task than modeling individual enhancers. Here we report the first quantitative model of a gene's expression pattern as a function of its locus. We model the expression readout of a locus in two tiers: 1) combinatorial regulation by transcription factors bound to each enhancer is predicted by a thermodynamics-based model and 2) independent contributions from multiple enhancers are linearly combined to fit the gene expression pattern. The model does not require any prior knowledge about enhancers contributing toward a gene's expression. We demonstrate that the model captures the complex multi-domain expression patterns of anterior-posterior patterning genes in the early Drosophila embryo. Altogether, we model the expression patterns of 27 genes; these include several gap genes, pair-rule genes, and anterior, posterior, trunk, and terminal genes. We find that the model-selected enhancers for each gene overlap strongly with its experimentally characterized enhancers. Our findings also suggest the presence of sequence-segments in the locus that would contribute ectopic expression patterns and hence were “shut down” by the model. We applied our model to identify the transcription factors responsible for forming the stripe boundaries of the studied genes. The resulting network of regulatory interactions exhibits a high level of agreement with known regulatory influences on the target genes. Finally, we analyzed whether and why our assumption of enhancer independence was necessary for the genes we studied. We found a deterioration of expression when binding sites in one enhancer were allowed to influence the readout of another enhancer. Thus, interference between enhancer activities was a possible factor necessitating enhancer independence in our model.
Quantitative modeling of gene expression from DNA sequences and regulatory inputs underpin our studies of gene regulation. The existing literature focuses on modeling parts of a gene's expression pattern from its experimentally characterized “enhancers”, which are ∼1 Kbp long sequences, often located in the gene's intergenic region or “locus.” However, a far-reaching goal is to model all aspects of a gene's expression based on the genome sequence, without prior knowledge of enhancers. With this motivation, we have developed a model that maps a gene's locus and cellular context to its expression in that context. Using this model, we study the regulation of 27 genes having complex expression patterns in the Drosophila embryo. Our findings suggest the presence of sequence segments that can irreconcilably distort the gene's expression pattern and thus have to be “shut-down” by the model. We also apply the model to identify the transcription factors forming the stripe boundaries of the studied genes; and our results agree remarkably with experimental findings of decades of work. Finally, we develop a new method to analyze if and why multiple segments influencing a gene's expression need to avoid interaction between themselves.
Poloxamers (known by the trade name Pluronic®) are triblock copolymer surfactants that contain two polyethylene glycol blocks and one polypropylene glycol block of various sizes. Poloxamers are widely used as nanoparticle dispersants for nanotoxicity studies wherein nanoparticles are sonicated with a dispersant to prepare suspensions. It is known that poloxamers can be degraded during sonication and that reactive oxygen species contribute to the degradation process. However, the possibility that poloxamer degradation products are toxic to mammalian cells has not been well studied. We report here that aqueous solutions of poloxamer 188 (Pluronic® F-68) and poloxamer 407 (Pluronic® F-127) sonicated in the presence or absence of multi-walled carbon nanotubes (MWNTs) can became highly toxic to cultured cells. Moreover, toxicity correlated with the sonolytic degradation of the polymers. These findings suggest that caution should be used in interpreting the results of nanotoxicity studies where the potential sonolytic degradation of dispersants was not controlled.
nanotoxicology; nanoparticles; poloxamer; carbon nanotubes; ultrasound
In our series of 710 consecutive laparoscopic total-extra-peritoneal hernia repairs over a period of 10 years (2001–2010), the authors report a rare case of delayed mesh infection developing 7 years postoperatively. A 56-year-old patient presented with diarrhoea and fullness in right iliac fossa region. Radiological imaging confirmed a floating mesh in a fluid-containing cavity. Subsequent exploration revealed a large preperitoneal cavity containing 550 ml of pus with a floating mesh in it. The mesh was removed and the patient was discharged after making a good recovery.
There is growing interest in models of regulatory sequence evolution. However, existing models specifically designed for regulatory sequences consider the independent evolution of individual transcription factor (TF)–binding sites, ignoring that the function and evolution of a binding site depends on its context, typically the cis-regulatory module (CRM) in which the site is located. Moreover, existing models do not account for the gene-specific roles of TF-binding sites, primarily because their roles often are not well understood. We introduce two models of regulatory sequence evolution that address some of the shortcomings of existing models and implement simulation frameworks based on them. One model simulates the evolution of an individual binding site in the context of a CRM, while the other evolves an entire CRM. Both models use a state-of-the art sequence-to-expression model to predict the effects of mutations on the regulatory output of the CRM and determine the strength of selection. We use the new framework to simulate the evolution of TF-binding sites in 37 well-studied CRMs belonging to the anterior–posterior patterning system in Drosophila embryos. We show that these simulations provide accurate fits to evolutionary data from 12 Drosophila genomes, which includes statistics of binding site conservation on relatively short evolutionary scales and site loss across larger divergence times. The new framework allows us, for the first time, to test hypotheses regarding the underlying cis-regulatory code by directly comparing the evolutionary implications of the hypothesis with the observed evolutionary dynamics of binding sites. Using this capability, we find that explicitly modeling self-cooperative DNA binding by the TF Caudal (CAD) provides significantly better fits than an otherwise identical evolutionary simulation that lacks this mechanistic aspect. This hypothesis is further supported by a statistical analysis of the distribution of intersite spacing between adjacent CAD sites. Experimental tests confirm direct homodimeric interaction between CAD molecules as well as self-cooperative DNA binding by CAD. We note that computational modeling of the D. melanogaster CRMs alone did not yield significant evidence to support CAD self-cooperativity. We thus demonstrate how specific mechanistic details encoded in CRMs can be revealed by modeling their evolution and fitting such models to multispecies data.
enhancer; evolution; cis-regulatory module; cooperativity; simulation
The authors report a case of a 79-year-old female who presented with signs and symptoms of acute cholecystitis. She was taken to theatre within 24 h of acute admission to undergo laparoscopic cholecystectomy. The gallbladder was found to have undergone torsion upon its mesentery leading to its infarction and necrosis. Laparoscopic cholecystectomy was performed, and the patient made an uneventful recovery.
Management of vaginal prolapse in the elderly lacks a uniform consensus and continues to remain challenging. The authors report a case of an elderly lady who presented with a spontaneous vaginal evisceration. She had a long-standing vaginal prolapse being controlled by a shelf pessary, which, in her case became displaced 2 weeks prior to admission. The patient underwent a laparotomy with an intent to replace the bowel back within the peritoneal cavity and repair the vault. During the pelvic floor repair, she sustained an inadvertent button-hole injury to the rectum, which was oversewn. She went on to develop a rectovaginal fistula requiring a de-functioning colostomy. The patient made good recovery subsequently.
Discovering new biomarkers has a great role in improving early diagnosis of Hepatocellular carcinoma (HCC). The experimental determination of biomarkers needs a lot of time and money. This motivates this work to use in-silico prediction of biomarkers to reduce the number of experiments required for detecting new ones. This is achieved by extracting the most representative genes in microarrays of HCC.
In this work, we provide a method for extracting the differential expressed genes, up regulated ones, that can be considered candidate biomarkers in high throughput microarrays of HCC. We examine the power of several gene selection methods (such as Pearson’s correlation coefficient, Cosine coefficient, Euclidean distance, Mutual information and Entropy with different estimators) in selecting informative genes. A biological interpretation of the highly ranked genes is done using KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways, ENTREZ and DAVID (Database for Annotation, Visualization, and Integrated Discovery) databases. The top ten genes selected using Pearson’s correlation coefficient and Cosine coefficient contained six genes that have been implicated in cancer (often multiple cancers) genesis in previous studies. A fewer number of genes were obtained by the other methods (4 genes using Mutual information, 3genes using Euclidean distance and only one gene using Entropy). A better result was obtained by the utilization of a hybrid approach based on intersecting the highly ranked genes in the output of all investigated methods. This hybrid combination yielded seven genes (2 genes for HCC and 5 genes in different types of cancer) in the top ten genes of the list of intersected genes.
To strengthen the effectiveness of the univariate selection methods, we propose a hybrid approach by intersecting several of these methods in a cascaded manner. This approach surpasses all of univariate selection methods when used individually according to biological interpretation and the examination of gene expression signal profiles.
A 52-year-old woman was admitted with neutropenic sepsis, 3 days following the final cycle of adjuvant chemotherapy for breast cancer. Her condition deteriorated with progressive abdominal distension, bilious vomiting and diarrhoea. Abdominal examination revealed a mild degree of peritonism. Five days later she passed a small bowel cast per rectum, showing gross fungal contamination on histology. She was managed conservatively with antibiotics and antifungal medications and nutritional support.
Mucosa-associated lymphoid tissue (MALT) is a type of extra nodal malignant lymphoma seen in organs such as the stomach, thyroid and salivary glands. Furthermore, occurrence of colorectal MALT lymphoma is extremely rare. We report a case of a solitary rectal MALT lymphoma treated by surgical resection and radiotherapy. Lymphoma should be considered as a rare differential diagnosis when dealing with large bowel pathology. We would advocate the use of surgery as a primary treatment option for a medically fit patient.
We report a case of a sixty year old man with a mycotic infra-renal abdominal aortic aneurysm complicated by a left psoas abscess. After treatment with parenteral antibiotics he underwent early aortic reconstruction with an in-situ prosthetic graft wrapped in an omental pedicle. Mycotic abdominal aortic aneurysms can be treated in this way despite the potential for graft infection from persisting retroperitoneal sepsis.
Aneurysm; Omentum; Psoas abscess
Management of rectal cancer has evolved over the years. In this condition preoperative investigations assist in deciding the optimal treatment. The relation of the tumor edge to the circumferential margin (CRM) is an important factor in deciding the need for neoadjuvant treatment and determines the prognosis. Those with threatened or involved margins are offered long course chemoradiation to enable R0 surgical resection. Endoanal ultrasound (EUS) is useful for tumor (T) staging; hence EUS is a useful imaging modality for early rectal cancer. Magnetic resonance imaging (MRI) is useful for assessing the mesorectum and the mesorectal fascia which has useful prognostic significance and for early identification of local recurrence. Computerized tomography (CT) of the chest, abdomen and pelvis is used to rule out distant metastasis. Identification of the malignant nodes using EUS, CT and MRI is based on the size, morphology and internal characteristics but has drawbacks. Most of the common imaging techniques are suboptimal for imaging following chemoradiation as they struggle to differentiate fibrotic changes and tumor. In this situation, EUS and MRI may provide complementary information to decide further treatment. Functional imaging using positron emission tomography (PET) is useful, particularly PET/CT fusion scans to identify areas of the functionally hot spots. In the current state, imaging has enabled the multidisciplinary team of surgeons, oncologists, radiologists and pathologists to decide on the patient centered management of rectal cancer. In future, functional imaging may play an active role in identifying patients with lymph node metastasis and those with residual and recurrent disease following neoadjuvant chemoradiotherapy.
Rectal cancer; Staging; Investigations; Magnetic resonance imaging; Ultrasound; Endoanal ultrasound; Positron emission tomography; Computerized tomography
Quantitative models of cis-regulatory activity have the potential to improve our mechanistic understanding of transcriptional regulation. However, the few models available today have been based on simplistic assumptions about the sequences being modeled, or heuristic approximations of the underlying regulatory mechanisms. We have developed a thermodynamics-based model to predict gene expression driven by any DNA sequence, as a function of transcription factor concentrations and their DNA-binding specificities. It uses statistical thermodynamics theory to model not only protein-DNA interaction, but also the effect of DNA-bound activators and repressors on gene expression. In addition, the model incorporates mechanistic features such as synergistic effect of multiple activators, short range repression, and cooperativity in transcription factor-DNA binding, allowing us to systematically evaluate the significance of these features in the context of available expression data. Using this model on segmentation-related enhancers in Drosophila, we find that transcriptional synergy due to simultaneous action of multiple activators helps explain the data beyond what can be explained by cooperative DNA-binding alone. We find clear support for the phenomenon of short-range repression, where repressors do not directly interact with the basal transcriptional machinery. We also find that the binding sites contributing to an enhancer's function may not be conserved during evolution, and a noticeable fraction of these undergo lineage-specific changes. Our implementation of the model, called GEMSTAT, is the first publicly available program for simultaneously modeling the regulatory activities of a given set of sequences.
The development of complex multicellular organisms requires genes to be expressed at specific stages and in specific tissues. Regulatory DNA sequences, often called cis-regulatory modules, drive the desired gene expression patterns by integrating information about the environment in the form of the activities of transcription factors. The rules by which regulatory sequences read this type of information, however, are unclear. In this work, we developed quantitative models based on physicochemical principles that directly map regulatory sequences to the expression profiles they generate. We evaluated these models on the segmentation network of the model organism Drosophila melanogaster. Our models incorporate mechanistic features that attempt to capture how activating and repressing transcription factors work in the segmentation system. By evaluating the importance of these features, we were able to gain insights on the quantitative regulatory rules. We found that two different mechanisms may contribute to cooperative gene activation and that repressors often have a short range of influence in DNA sequences. Combining the quantitative modeling with comparative sequence analysis, we also found that even functional sequences may be lost during evolution.
Identifying a threshold number of drinks/day, beyond which there is a high risk of developing alcoholic behavior, would enable physicians to more confidently support the use of alcohol for CV risk prevention.
In a randomly selected, population-based sample of 2042 adults, age ≥ 45, we graded alcohol drinking behavior using the Self Administered Alcoholism Screening Test (SAAST), quantified alcohol amount by questionnaire, and assessed the prevalence of CV disease (coronary, peripheral or cerebrovascular disease) by medical record review.
Although optimal alcohol use (≤2 drinks/day) as associated with reduced odds of CV disease, 43% of alcoholics and 82% of problem drinkers reported alcohol use in the optimal range as well.
The association of use of alcohol in the optimal range with alcohol related behavioral problems supports the reluctance in physicians from recommending alcohol use for CV benefit, not withstanding the underreporting of alcohol use by alcoholics.
Alcoholism; risk factor; coronary heart disease; alcohol
Ethanol extracts of brown seaweeds from Pakistan and China were isolated and compared for their antiallergenic activities. They included Sargassum tennerimum (ST) and Sargassum cervicorne (SC) from Pakistan, and Sargassum graminifolium turn (SG), Sargassum thunbergii (STH), and Laminaria japonica (LJ) from China. The ethanol extracts of these brown seaweeds were optimized at 85% (v/v) ethanol for the maximum yield of phlorotannin, an inhibitor against hyaluronidase. Total phlorotannins contained in the crude extracts were measured as 1.71% (SG), 0.74% (STH), 0.97% (LJ), 3.30% (SC), and 5.06% (ST). The 50% inhibitory concentrations (IC50) of Pakistani SC and ST were 109.5 and 21 μg/ml, respectively, lower than those of Chinese SG, STH, and LJ (134, 269, and 148 μg/ml, respectively). An antiallergic drug, disodium cromoglycate (DSCG), had an IC50=39 μg/ml, and a natural inhibitor of hyaluronidase, catechin, had an IC50=20 μg/ml. The IC50 of ST extract was found similar to that of catechin (21 vs 20 μg/ml) and lower than that of DSCG (21 vs 39 μg/ml). This suggests that ST is a potent inhibitor of hyaluronidase, indicating a promising future development of natural antiallergic medicines or functional foods.
Anti-allergic activity; Brown seaweed; Ethanol extracts; Hyaluronidase; Phlorotannin
A series of 7-hydroxy, 8-hydroxy and 7,8-dihydroxy synthetic chromone derivatives was evaluated for their DPPH free radical scavenging activities. A training set of 30 synthetic chromone derivatives was subject to three-dimensional quantitative structure-activity relationship (3D-QSAR) studies using molecular field analysis (MFA). The substitutional requirements for favorable antioxidant activity were investigated and a predictive model that could be used for the design of novel antioxidants was derived. Regression analysis was carried out using genetic partial least squares (G/PLS) method. A highly predictive and statistically significant model was generated. The predictive ability of the developed model was assessed using a test set of 5 compounds (r2pred = 0.924). The analyzed MFA model demonstrated a good fit, having r2 value of 0.868 and cross-validated coefficient r2cv value of 0.771.
3D-QSAR; Chromone; Molecular field analysis (MFA); Antioxidants; Genetic partial least squares (G/PLS) method
Gamma interferon (IFN-γ) is produced by activated natural killer and T cells under pathologic circumstances. The objective of our study was to compare the level of IFN-γ in open and endoscopic methods of vein harvesting for coronary artery bypass surgery (CABG).
Ninety samples of human saphenous veins harvested from patients prepared for CABG. Pre- and post-procedure sera of the patients, in addition to super-natants of 3-day endothelial cell culture, were analyzed for IFN-γ.
The mean preoperative IFN-γ level (0.09 ± 0.03 pg/mL) and that for postoperative sera (0.08 ± 0.02 pg/mL) were not significantly different (P = 0.2). The mean IFN-γ level in endothelial cell culture from the endoscopic (0.18 ± 0.21 pg/mL) and the open method (0.19 ± 0.39 pg/mL) were not significant (P = 0.89).
We recommend the endoscopic method of vein harvesting because of its lower morbidity and earlier hospital discharge.
IFN-γ; CABG; Endoscopic and open saphenectomies