Breast Cancer Pathology, Receptor Status, and Patterns of Metastasis in a Rural Appalachian Population

Breast cancer patients in rural Appalachia have a high prevalence of obesity and poverty, together with more triple-negative phenotypes. We reviewed clinical records for tumor receptor status and time to distant metastasis. Body mass index, tumor size, grade, nodal status, and receptor status were related to metastatic patterns. For 687 patients, 13.8% developed metastases to bone (n=42) or visceral sites (n=53). Metastases to viscera occurred within five years, a latent period which was shorter than that for bone (P=0.042). More women with visceral metastasis presented with grade 3 tumors compared with the bone and nonmetastatic groups (P=0.0002). There were 135/574 women (23.5%) with triple-negative breast cancer, who presented with lymph node involvement and visceral metastases (68.2% versus 24.3%; P=0.033). Triple-negative tumors that metastasized to visceral sites were larger (P=0.007). Developing a visceral metastasis within 10 years was higher among women with triple-negative tumors. Across all breast cancer receptor subtypes, the probability of remaining distant metastasis-free was greater for brain and liver than for lung. The excess risk of metastatic spread to visceral organs in triple-negative breast cancers, even in the absence of positive nodes, was combined with the burden of larger and more advanced tumors

Construction of an Optimized Multi-Stage High-Throughput Virtual Screening Pipeline for Long Non-Coding RNA's

Long non-coding RNA’s(lncRNA’s) are a type of RNA transcripts with a length of more than 200 nucleotides which cannot be translated into proteins. The study of lncRNAs is extremely important since it has been discovered that a wide range of biological processes are affected by them, such as epigenetic regulation, metabolic processes, chromosome dynamics and cell differentiation. This work investigates the classification of lncRNA’s from protein coding transcripts (PCT’s) using a multi-stage high throughput virtual screening (HTVS) pipeline. Each stage of the pipeline is a support vector machine (SVM) model. Various features associated with RNAs in general have been calculated. These features are divided into three groups- sequence based, secondary structure based and physicochemical property based. These features were first calculated and analyzed in a method called LncFinder. Support vector machines have been trained on these features on the basis of complexity and time taken for calculation. Support-vector machines are supervised learning models with associated learning algorithms that analyze data for classification and regression analysis. These SVM’s have then been arranged on an HTVS pipeline as different stages of the pipeline. The pipeline has been optimized using an optimization framework, for determining the screening thresholds of each stage of the HTS pipeline. The final number of lncRNA’s obtained can then be further used for drug discovery purposes. This multi-stage classification process significantly reduces the effective selection cost per potential candidate and make the HTS pipelines less sensitive to their structural variations

From Quantum Chemistry to Networks in Biology: A Graph Spectral Approach to Protein Structure Analyses

In this perspective article, we present a multi-disciplinary approach for characterizing protein structure networks. We first place our approach in its historical context and describe the manner in which it synthesizes concepts from quantum chemistry, biology of polymer conformations, matrix mathematics, and percolation theory. We then explicitly provide the method for constructing the protein structure network in terms of non-covalently interacting amino acid side chains and show how a mine of information can be obtained from the graph spectra of these networks. Employing suitable mathematical approaches, such as the use of a weighted, Laplacian matrix to generate the spectra, enables us to develop rigorous methods for network comparison and to identify crucial nodes responsible for the network integrity through a perturbation approach. Our scoring methods have several applications in structural biology that are elusive to conventional methods of analyses. Here, we discuss the instances of (a) protein structure comparison that includes the details of side chain connectivity, (b) contribution to node clustering as a function of bound ligand, explaining the global effect of local changes in phenomena such as allostery, and (c) identification of crucial amino acids for structural integrity, derived purely from the spectra of the graph. We demonstrate how our method enables us to obtain valuable information on key proteins involved in cellular functions and diseases such as GPCR and HIV protease and discuss the biological implications. We then briefly describe how concepts from percolation theory further augment our analyses. In our concluding perspective for future developments, we suggest a further unifying approach to protein structure analyses and a judicious choice of questions to employ our methods for larger, more complex networks, such as metabolic and disease networks

Single incision laparoscopic distal pancreatectomy with splenectomy for neuroendocrine tumor of the tail of pancreas

Laparoscopic resection is becoming the standard of care for tumors located in the body and tail of pancreas. We herein report a patient with neuroendocrine tumor in the tail of pancreas who underwent single incision laparoscopic distal pancreatectomy with splenectomy without the use of a commercial port device

Use real-time near-infrared fluorescence during Heller's cardiomyotomy for achalasia cardia

Laparoscopic Heller's cardiomyotomy is the surgical procedure of choice in the management of oesophageal achalasia. It is critical to confirm the completeness of the myotomy and mucosal integrity at the conclusion of the procedure. This is conventionally achieved by intraoperative endoscopy and dynamic air leak test. Other modalities that can be used to confirm the myotomy and the integrity of the mucosa at the myotomy site are oesophageal manometry and a methylene blue dye study, respectively. Indocyanine green (ICG) has been in clinical use for more than six decades. The real-time integration of ICG fluorescence with laparoscopy is a relatively new breakthrough. Here, we present a novel method of using real-time near-infrared ICG fluorescence for confirming the completeness of the myotomy and mucosal integrity at the myotomy site post laparoscopic Heller's myotomy. This is the first report on the use of ICG in laparoscopic Heller's cardiomyotomy that we are aware of

Validation of protein structure models using network similarity score

Accurate structural validation of proteins is of extreme importance in studies like protein structure prediction, analysis of molecular dynamic simulation trajectories and finding subtle changes in very similar structures. The benchmarks for today's structure validation are scoring methods like global distance test-total structure (GDT-TS), TM-score and root mean square deviations (RMSD). However, there is a lack of methods that look at both the protein backbone and side-chain structures at the global connectivity level and provide information about the differences in connectivity. To address this gap, a graph spectral based method (NSS-network similarity score) which has been recently developed to rigorously compare networks in diverse fields, is adopted to compare protein structures both at the backbone and at the side-chain noncovalent connectivity levels. In this study, we validate the performance of NSS by investigating protein structures from X-ray structures, modeling (including CASP models), and molecular dynamics simulations. Further, we systematically identify the local and the global regions of the structures contributing to the difference in NSS, through the components of the score, a feature unique to this spectral based scoring scheme. It is demonstrated that the method can quantify subtle differences in connectivity compared to a reference protein structure and can form a robust basis for protein structure comparison. Additionally, we have also introduced a network-based method to analyze fluctuations in side chain interactions (edge-weights) in an ensemble of structures, which can be an useful tool for the analysis of MID trajectories

Laparoscopic resection of giant liver hemangioma using laparoscopic Habib probe for parenchymal transection

Experience with laparoscopic liver resections is limited. Laparoscopic resection of a variety of liver lesions has been reported and is considered appropriate for lesions in the left lateral segment and inferior segments of the right lobe. Herein, we report a 52-year-old male patient who underwent a laparoscopic resection of giant liver hemangioma with the use of a laparoscopic 4× Habib probe