Keratinized squamous cells in fine needle aspiration of the brain. Cytopathologic correlates and differential diagnosis

OBJECTIVE: To analyze the differential diagnosis when keratinized squamous cells are found in a brain aspirate. STUDY DESIGN: Twenty cases of brain aspirates with keratinized squamous cells were retrieved (1982-2001). Diagnoses included craniopharyngioma (CP) (n = 11), metastatic squamous cell carcinoma (SCC) (n = 5), epidermoid cyst (EC) (n = 3) and Rathke cleft cyst (RCC) (n = 1). Aspirates were obtained under stereotactic radiologic (CT) guidance. Smears were stained with Diff-Quik or Papanicolaou stain, and cell block sections were stained with hematoxylin and eosin. Radiologic and histopathologic correlation with subsequent resection specimens was performed in selected cases. RESULTS: CP showed cellular smears with numerous keratinized squamous cells in a background of degenerated cellular and keratinaceous debris. Also noted were clusters of anucleate squamous cells, multinucleated giant cells, histiocytes, calcified debris and characteristic fragments of basaloid epithelial cells. Metastatic SCC showed single cells and tissue fragments of markedly atypical and focally keratinized cells with enlarged, hyperchromatic nuclei; prominent pleomorphism in a background of necrotic cellular debris and acute inflammatory exudate. EC showed numerous isolated keratinized squamous cells often with prominent keratohyaline granules and occasional parakeratotic cells in a relatively clean background. RCC showed single cells and aggregates of benign-appearing squamous cells admixed with numerous anucleate squames and hemosiderin-laden macrophages. Glandular-type epithelium was present only rarely. CONCLUSION: Squamous cell-containing lesions in the brain present a spectrum of pathologic entities. Although they all display the common morphologic denominator of keratinizing squamous cells, subtle cytomorphologic differences exist in these lesions, permitting an accurate cytopathologic diagnosis. Clinicardiologic features and anatomic location of the tumor in the brain are additionally helpful.     

Multifrequency cw-EPR investigation of the catalytic molybdenum cofactor of polysulfide reductase from<Emphasis Type="Italic"> Wolinella succinogenes</Emphasis>

Electron paramagnetic resonance (EPR) spectra of the molybdenum centre in polysulfide reductase (Psr) from Wolinella succinogenes with unusually high G-tensor values have been observed for the first time. Three different Mo(V) states have been generated (by the addition of the substrate polysulfide and different redox agents) and analysed by their G- and hyperfine tensors using multifrequency (S-, X- and Q-band) cw-EPR spectroscopy. The unusually high G-tensor values are attributed to a large number of sulfur ligands. Four sulfur ligands are assumed to arise from two pterin cofactors; one additional sulfur ligand was identified from mutagenesis studies to be a cysteine residue of the protein backbone. One further sulfur ligand is proposed for two of the Mo(V) states, based on the experimentally observed shift of the g(av) value. This sixth sulfur ligand is postulated to belong to the polysulfide substrate consumed within the catalytic reaction cycle of the enzyme. The influence of the co-protein sulfur transferase on the Mo(V) G-tensor supports this assignment.     

The cell graphs of cancer

We report a novel, proof-of-concept, computational method that models a type of brain cancer (glioma) only by using the topological properties of its cells in the tissue image. From low-magnification (80x) tissue images of 384 x 384 pixels, we construct the graphs of the cells based on the locations of the cells within the images. We generate such cell graphs of 1000-3000 cells (nodes) with 2000-10,000 links, each of which is calculated as a decaying exponential function of the Euclidean distance between every pair of cells in accordance with the Waxman model. At the cellular level, we compute the graph metrics of the cell graphs, including the degree, clustering coefficient, eccentricity and closeness for each cell. Working with a total of 285 tissue samples surgically removed from 12 different patients, we demonstrate that the self-organizing clusters of cancerous cells exhibit distinctive graph metrics that distinguish them from the healthy cells and the unhealthy inflamed cells at the cellular level with an accuracy of at least 85%. At the tissue level, we accomplish correct tissue classifications of cancerous, healthy and non-neoplastic inflamed tissue samples with an accuracy of 100% by requiring correct classification for the majority of the cells within the tissue sample.     

A Detailed Chemical and Biological Investigation of Twelve Allium Species from Eastern Anatolia with Chemometric Studies

Allium species are widely consumed as food all over the world. The phenolic profile of ethanol extracts of aerial parts and roots of 12 Allium species, collected from five different Eastern Anatolia regions, were studied using LC-MS/MS. In vitro antioxidant, anticholinesterase, cytotoxic and antimicrobial activities were also tested. The multivariate analyses were performed using principal component and hierarchical cluster analyses. Seventeen of 27 standard compounds were detected in all Allium species. The major components were mainly identified as quinic acid, malic acid, vanillin, and p-coumaric acid. The aerial parts possessed better antioxidant activity than roots. Aerial parts of A. atroviolaceum, A. chrysantherum, A. kharputense, and A. shirnakiense exhibited high cytotoxic activity against DLD-1 colon cancer cell lines (IC₅₀ 12.5 μg/mL). A. shatakiense and A. vineale demonstrated good antimicrobial activity against S. aureus and E. coli (MIC 75 μg/mL). According to chemometric analysis, differences were detected between aerial parts and the roots. The aerial parts of A. atroviolaceum, A. chrysantherum, A. kharputense, and A. shirnakiense could be potent in the pharmaceutical industry while A. shatakiense and A. vineale in the food industry after further investigations.     

Phytochemical Fingerprints and Bioactivities of Ripe Disseminules (Fruit-Seeds) of Seventeen Gundelia (Kenger-Kereng Dikeni) Species from Anatolia with Chemometric Approach

Gundelia species are known as “Kenger-kereng dikeni” in Anatolia, and their aerial parts are consumed as food. Also, roots and seeds (disseminules) of the Gundelia species are used to prepare gum and coffee. The chemical contents of ethanol and hexane extracts of disseminules of 17 Gundelia species, 13 of them are endemic, were studied using LC/MS/MS and GC/MS. Additionally, their antioxidant potential and enzyme inhibitory capacity against acetyl- and butyryl-cholinesterase, urease, and tyrosinase were determined. The unsaturated fatty acid ratios of Gundelia species were higher than their saturated fatty acid ratio. The highest sum of oleic and linoleic acid was detected in G. tournefortii var. tenuisecta (70.42 %). β-Sitosterol, α-amyrin, 3-acetyllupeol were identified in 17 Gundelia species by GC/MS, while chlorogenic acid and luteolin by LC/MS/MS as major compounds. The ethanol and hexane extracts of G. siirtica, G. rosea, and G. mesopotamica indicated good cholinesterase inhibitory activity. Among all species, ethanol extract of G. colemerikensis exhibited the best activity in ABTS (IC₅₀: 32.30±0.98 μg/mL), DPPH (IC₅₀: 59.91±0.89 μg/mL), and CUPRAC (A_0.5: 57.41±1.03 μg/mL) assays. Ethanol extract of G. colemerikensis also displayed the highest inhibitory activity against butyrylcholinesterase (51.14±0.25 % at 200 μg/mL), urease (51.71±1.75 % at 200 μg/mL), and tyrosinase (39.50±0.85 % at 200 μg/mL) enzymes. According to the chemometric analysis of fatty acids, four groups were observed. Therefore, it is suggested that G. colemerikensis can be used in the pharmaceutical, food, and cosmetic industries due to its antioxidant and enzyme inhibition properties.     

Spectrum of risk of malignancy in subcategories of 'atypia of undetermined significance'

Objective: To determine if focal 'nuclear atypia' or 'microfollicular architecture' portends a higher risk of malignancy than other subcategories of atypia of undetermined significance (AUS) in thyroid fine-needle aspirations (FNAs). Study Design: The frequencies of The Bethesda System for Reporting Thyroid Cytopathology (TBSRTC) categories were calculated from 3,956 thyroid FNAs interpreted over a 26-month period at The Johns Hopkins Hospital after adoption of TBSRTC. TBSRTC criteria were applied strictly. The risk of malignancy, specifically for AUS subcategories, was analyzed by cyto-histo correlation. Results: Of the 133 cases diagnosed as AUS, 32% were found to have stageable carcinoma (not incidental microcarcinoma) on resection. When the subset of AUS with 'nuclear atypia' (AUS-N) was separated from other AUS cases, 48% (30/62) of them had stageable carcinoma on resection; of the AUS subset with 'microfollicular architecture' (AUS-F), 27% (8/30) were malignant on resection. The 'suspicious for papillary thyroid carcinoma' (SPTC) group maintained a higher risk of malignancy versus AUS-N (relative risk, RR 1.57; 95% CI 1.23-1.81). Conclusion: The subcategory of 'nuclear atypia' within AUS indicates a higher risk of malignancy than other subcategories of AUS but has a lower risk of malignancy than SPTC does. Thus, it is an important distinction with potential clinical implications.     

A probabilistic approach to microRNA-target binding

Elucidation of microRNA activity is a crucial step in understanding gene regulation. One key problem in this effort is how to model the pairwise interactions of microRNAs with their targets. As this interaction is strongly mediated by their sequences, it is desired to set-up a probabilistic model to explain the binding preferences between a microRNA sequence and the sequence of a putative target. To this end, we introduce a new model of microRNA-target binding, which transforms an aligned duplex to a new sequence and defines the likelihood of this sequence using a Variable Length Markov Chain. It offers a complementary representation of microRNA–mRNA pairs for microRNA target prediction tools or other probabilistic frameworks of integrative gene regulation analysis. The performance of present model is evaluated by its ability to predict microRNA–target mRNA interaction given a mature microRNA sequence and a putative mRNA binding site. In regard to classification accuracy, it outperforms two recent methods based on thermodynamic stability and sequence complementarity. The experiments can also unveil the effects of base pairing types and non-seed region in duplex formation.     

Multiway analysis of epilepsy tensors

MOTIVATION: The success or failure of an epilepsy surgery depends greatly on the localization of epileptic focus (origin of a seizure). We address the problem of identification of a seizure origin through an analysis of ictal electroencephalogram (EEG), which is proven to be an effective standard in epileptic focus localization. SUMMARY: With a goal of developing an automated and robust way of visual analysis of large amounts of EEG data, we propose a novel approach based on multiway models to study epilepsy seizure structure. Our contributions are 3-fold. First, we construct an Epilepsy Tensor with three modes, i.e. time samples, scales and electrodes, through wavelet analysis of multi-channel ictal EEG. Second, we demonstrate that multiway analysis techniques, in particular parallel factor analysis (PARAFAC), provide promising results in modeling the complex structure of an epilepsy seizure, localizing a seizure origin and extracting artifacts. Third, we introduce an approach for removing artifacts using multilinear subspace analysis and discuss its merits and drawbacks. RESULTS: Ictal EEG analysis of 10 seizures from 7 patients are included in this study. Our results for 8 seizures match with clinical observations in terms of seizure origin and extracted artifacts. On the other hand, for 2 of the seizures, seizure localization is not achieved using an initial trial of PARAFAC modeling. In these cases, first, we apply an artifact removal method and subsequently apply the PARAFAC model on the epilepsy tensor from which potential artifacts have been removed. This method successfully identifies the seizure origin in both cases.