Intraosseous verrucous carcinoma originating from an odontogenic cyst: a case report

Carcinoma originating in bone is uncommon; most of them apparently arise in odontogenic cysts. In this paper, we report an extremely rare case in which, verrucous carcinoma originated from an odontogenic cyst. This lesion was firm and non-tender on palpation and had a white-pink appearance. It was encased in the anterior aspect of the maxilla and exhibited microscopic features of verrucous carcinoma of the oral mucosa. After surgical enucleation, no recurrence or metastasis has been observed up to now. It is mandatory to correlate the clinical and histopathologic findings to establish a true diagnosis.     

Assessment and Investigation on the Fate of Organochlorine Pesticides in Water and Sediments of International Amir-kalaye Wetland in North of Iran

A total of 48 water samples and 24 sediment samples were collected at four sampling stations along the wetland during four seasons from 2009 to 2010 and analyzed by gas chromatograph–electron capture detector (GC–ECD). In water the total concentration of OCPs was 0.33, 0.01, 0.1 and 0.07 mg/L in summer, autumn, winter and spring, respectively. The most frequent OCP compounds detected were endrin and chlordane (0.08 and 0.07 mg/L), heaxachlorobenzene and chlordane (0.06, 0.02 mg/L), and chlordane (0.07 mg/L) in summer, winter and spring, respectively. The maximum concentration of ΣOCPs was found in samples collected from station 1 in summer (0.26 mg/L). In sediments the total concentrations of OCPs were 15.84 and 2.62 mg/g-dry weight (dw) in summer and winter, respectively. Chlordane was the most frequently found OCP compound, followed by lindane, 9.92 and 2.47 mg/g-dry weight (dw), respectively, in summer. While, lindane (2.52 mg/g-dw) and endosulfan I (0.1 mg/g-dw) were the highest OCP compounds detected in winter. The results obtained in this study show that there still exist a variety of organochlorine pesticide residues in the water and sediments from the Amir-kalaye wetland in Iran.     

The rat pineal gland comprises an endocannabinoid system

In the mammalian pineal gland, the rhythm in melatonin biosynthesis depends on the norepinephrine (NE)-driven regulation of arylalkylamine N-acetyltransferase (AANAT), the penultimate enzyme of melatonin biosynthesis. A recent study showed that phytocannabinoids like tetrahydrocannabinol reduce AANAT activity and attenuate NE-induced melatonin biosynthesis in rat pineal glands, raising the possibility that an endocannabinoid system is present in the pineal gland. To test this hypothesis, we analyzed cannabinoid (CB) receptors and specific enzymes for endocannabinoid biosynthesis or catabolism in rat pineal glands and cultured pinealocytes. Immunohistochemical and immunoblot analyses revealed the presence of CB1 and CB2 receptor proteins, of N-acyl phosphatidyl ethanolamine hydrolyzing phospholipase D (NAPE-PLD), an enzyme catalyzing endocannabinoid biosynthesis and of fatty acid amide hydrolase (FAAH), an endocannabinoid catabolizing enzyme, in pinealocytes, and in pineal sympathetic nerve fibers identified by double immunofluorescence with an antibody against tyrosine hydroxylase. The immunosignals for the CB2 receptor, NAPE-PLD, and FAAH found in pinealocytes did not vary under a 12 hr light:12 hr dark cycle. The CB1 receptor immunoreaction in pinealocytes was significantly reduced at the end of the light phase [zeitgeber time (ZT) 12]. The immunosignal for NAPE-PLD found in pineal sympathetic nerve fibers was reduced in the middle of the dark phase (ZT 18). Stimulation of cultured pinealocytes with NE affected neither the subcellular distribution nor the intensity of the immunosignals for the investigated CB receptors and enzymes. In summary, the pineal gland comprises indispensable compounds of the endocannabinoid system indicating that endocannabinoids may be involved in the control of pineal physiology.     

Individualizing glycemic targets in type 2 diabetes mellitus: implications of recent clinical trials

One of the first steps in the management of patients with type 2 diabetes mellitus is setting glycemic goals. Professional organizations advise setting specific hemoglobin A(1c) (HbA(1c)) targets for patients, and individualization of these goals has more recently been emphasized. However, the operational meaning of glycemic goals, and specific methods for individualizing them, have not been well-described. Choosing a specific HbA(1c) target range for a given patient requires taking several factors into consideration, including an assessment of the patient's risk for hyperglycemia-related complications versus the risks of therapy, all in the context of the overall clinical setting. Comorbid conditions, psychological status, capacity for self-care, economic considerations, and family and social support systems also play a key role in the intensity of therapy. The individualization of HbA(1c) targets has gained more traction after recent clinical trials in older patients with established type 2 diabetes mellitus failed to show a benefit from intensive glucose-lowering therapy on cardiovascular disease (CVD) outcomes. The limited available evidence suggests that near-normal glycemic targets should be the standard for younger patients with relatively recent onset of type 2 diabetes mellitus and little or no micro- or macrovascular complications, with the aim of preventing complications over the many years of life. However, somewhat higher targets should be considered for older patients with long-standing type 2 diabetes mellitus and evidence of CVD (or multiple CVD risk factors). This review explores these issues further and proposes a framework for considering an appropriate and safe HbA(1c) target range for each patient.     

Effect of Hypoglycemia on Brain Structure in People With Type 2 Diabetes: Epidemiological Analysis of the ACCORD-MIND MRI Trial

OBJECTIVEThe effect of hypoglycemia related to treatment of type 2 diabetes mellitus (T2DM) on brain structure remains unclear. We aimed to assess whether symptomatic severe hypoglycemia is associated with brain atrophy and/or white matter abnormalities.RESULTSOf the 503 T2DM participants (mean age, 62 years) with successful baseline and 40-month brain MRI, 28 had at least one HA episode during the 40-month follow-up. Compared with participants without HA, those with HA had marginally significant less atrophy (less decrease in TBV) from baseline to 40 months (−9.55 [95% CI −15.21, −3.90] vs. −15.38 [95% CI −16.64, −14.12], P = 0.051), and no significant increase of AWM volume (2.06 [95% CI 1.71, 2.49] vs. 1.84 [95% CI 1.76, 1.91], P = 0.247). In addition, no unexpected local signal changes or volume loss were seen on hypoglycemic participants’ brain MRI scans.CONCLUSIONSOur study suggests that hypoglycemia related to T2DM treatment may not accentuate brain pathology, specifically brain atrophy or white matter abnormalities.     

Protective hinge in insulin opens to enable its receptor engagement

Insulin provides a classical model of a globular protein, yet how the hormone changes conformation to engage its receptor has long been enigmatic. Interest has focused on the C-terminal B-chain segment, critical for protective self-assembly in β cells and receptor binding at target tissues. Insight may be obtained from truncated “microreceptors” that reconstitute the primary hormone-binding site (α-subunit domains L1 and αCT). We demonstrate that, on microreceptor binding, this segment undergoes concerted hinge-like rotation at its B20-B23 β-turn, coupling reorientation of Phe^B24 to a 60° rotation of the B25-B28 β-strand away from the hormone core to lie antiparallel to the receptor''s L1–β₂ sheet. Opening of this hinge enables conserved nonpolar side chains (Ile^A2, Val^A3, Val^B12, Phe^B24, and Phe^B25) to engage the receptor. Restraining the hinge by nonstandard mutagenesis preserves native folding but blocks receptor binding, whereas its engineered opening maintains activity at the price of protein instability and nonnative aggregation. Our findings rationalize properties of clinical mutations in the insulin family and provide a previously unidentified foundation for designing therapeutic analogs. We envisage that a switch between free and receptor-bound conformations of insulin evolved as a solution to conflicting structural determinants of biosynthesis and function.How insulin engages the insulin receptor has inspired speculation ever since the structure of the free hormone was determined by Hodgkin and colleagues in 1969 (1, 2). Over the ensuing decades, anomalies encountered in studies of analogs have suggested that the hormone undergoes a conformational change on receptor binding: in particular, that the C-terminal β-strand of the B chain (residues B24–B30) releases from the helical core to expose otherwise-buried nonpolar surfaces (the detachment model) (3–6). Interest in the B-chain β-strand was further motivated by the discovery of clinical mutations within it associated with diabetes mellitus (DM) (7). Analysis of residue-specific photo–cross-linking provided evidence that both the detached strand and underlying nonpolar surfaces engage the receptor (8).The relevant structural biology is as follows. The insulin receptor is a disulfide-linked (αβ)₂ receptor tyrosine kinase (Fig. 1A), the extracellular α-subunits together binding a single insulin molecule with high affinity (9). Involvement of the two α-subunits is asymmetric: the primary insulin-binding site (site 1^*) comprises the central β-sheet (L1–β₂) of the first leucine-rich repeat domain (L1) of one α-subunit and the partially helical C-terminal segment (αCT) of the other α-subunit (Fig. 1A) (10). Such binding initiates conformational changes leading to transphosphorylation of the β-subunits’ intracellular tyrosine kinase (TK) domains. Structures of wild-type (WT) insulin (or analogs) bound to extracellular receptor fragments were recently described at maximum resolution of 3.9 Å (11), revealing that hormone binding is primarily mediated by αCT (receptor residues 704–719); direct interactions between insulin and L1 were sparse and restricted to certain B-chain residues. On insulin binding, αCT was repositioned on the L1–β₂ surface, and its helix was C-terminally extended to include residues 711–714. None of these structures defined the positions of C-terminal B-chain residues beyond B21. Support for the detachment model was nonetheless provided by entry of αCT into a volume that would otherwise be occupied by B-chain residues B25–B30 (i.e., in classical insulin structures; Fig. 1B) (11).Open in a separate windowFig. 1.Insulin B-chain C-terminal β-strand in the μIR complex. (A) Structure of apo-receptor ectodomain. One monomer is in tube representation (labeled), the second is in surface representation. L1, first leucine-rich repeat domain; CR, cysteine-rich domain; L2, second leucine-rich repeat domain; FnIII-1, -2 and -3; first, second and third fibronectin type III domains, respectively; αCT, α-subunit C-terminal segment; coral disk, plasma membrane. (B) Insulin bound to μIR; the view direction with respect to L1 in the apo-ectodomain is indicated by the arrow in A. Only B-chain residues indicated in black were originally resolved (11). The brown tube indicates classical location of residues B20-B30 in free insulin, occluded in the complex by αCT. (C) Orthogonal views of unmodeled 2F_obs-F_calc difference electron density (SI Appendix), indicating association of map segments with the αCT C-terminal extension (transparent magenta), insulin B-chain C-terminal segment (transparent gray), and Asn^A21 (transparent yellow). Difference density is sharpened (B_sharp = −160 Ų). (D–F) Refined models of respective segments insulin B20–B27, αCT 714–719, and insulin A17-A21 within postrefinement 2F_obs-F_calc difference electron density (B_sharp = −160 Ų). D is in stereo.We describe here the structure and interactions of the detached B-chain C-terminal segment of insulin on its binding to a “microreceptor” (μIR), an L1–CR domain-minimized version of the α-subunit (designated IR310.T) plus exogenous αCT peptide 704–719 (11). Our analysis defines a hinge in the B chain whose opening is coupled to repositioning of αCT between nonpolar surfaces of L1 and the insulin A chain. To understand the role of this hinge in holoreceptor binding and signaling, we designed three insulin analogs containing structural constraints (d-Ala^B20, d-Ala^B23]-insulin, ∆Phe^B25-insulin, and ∆Phe^B24-insulin, where ∆Phe is (α,β)-dehydrophenylalanine (Fig. 2) (12). The latter represents, to our knowledge, the first use of ∆Phe—a rigid “β-breaker” with extended electronic conjugation between its side chain and main chain (SI Appendix, Fig. S1)—as a probe of induced fit in macromolecular recognition. In addition, a fourth analog, active but with anomalous flexibility in the B chain (5, 6) (

Significance of Platelet Count in Esophageal Carcinomas

Background/Aim:

Thrombocytosis is found to be associated with unfavorable prognosis in esophageal carcinoma. Platelets produce thymidine phosphorylase which is a platelet-derived endothelial cell growth factor with angiogenic activity. Increased platelet count may be translated into enhanced tumor growth. We examined the relation between platelet count and several prognostic variables in patients with esophageal cancer.

Patients and Methods:

Three hundred and eighty-one cases with esophageal cancer that underwent esophagectomy in a referral cancer institute during a 5-year period were studied retrospectively. The relation between preoperative platelet count and patient age, gender, site of tumor, presence of multiple cancers and clinicopathological characteristics including histological type, tumor size, depth of penetration (T), lymph node involvement (N), distant metastasis (M), degree of differentiation, presence of vascular, lymphatic and perineural invasion was examined.

Results:

Squamous cell carcinoma (SCC) constituted 93% and adenocarcinoma 7% of cases. Most of patients were in stage III, followed by stage II. The mean platelet count was 245±76 (× 10⁹ /L). There was no statistically significant correlation between platelet counts with prognostic factors except a weak linear correlation between platelet count and and tumor size (P= 0.03, Pearson correlation coefficient: 0.16). Patients with adenocarcinoma had a higher platelet count than those with SCC (P= 0.003).

Conclusion:

Platelet count does not correlate with prognostic factors in esophageal cancer. However, it is significantly different between SCC and adenocarcinoma of esophagus.