Post-traumatic stress disorder and smoking: a systematic review.

We conducted a systematic review of what is known about the relationship between post-traumatic stress disorder (PTSD) and smoking to guide research on underlying mechanisms and to facilitate the development of evidence-based tobacco treatments for this population of smokers. We searched Medline, PsychINFO, and the Cochrane Central Register of Controlled Trials and identified 45 studies for review that presented primary data on PTSD and smoking. Smoking rates were high among clinical samples with PTSD (40%-86%) as well as nonclinical populations with PTSD (34%-61%). Most studies showed a positive relationship between PTSD and smoking and nicotine dependence, with odds ratios ranging between 2.04 and 4.52. Findings also suggest that PTSD, rather than trauma exposure itself, is more influential for increasing risk of smoking. A small but growing literature has examined psychological factors related to smoking initiation and maintenance and the overlapping neurobiology of PTSD and nicotine dependence. Observational studies indicate that smokers with PTSD have lower quit rates than do smokers without PTSD. Yet a few tobacco cessation treatment trials in smokers with PTSD have achieved quit rates comparable with controlled trials of smokers without mental disorders. In conclusion, the evidence points to a causal relationship between PTSD and smoking that may be bidirectional. Specific PTSD symptoms may contribute to smoking and disrupt cessation attempts. Intervention studies that test behavioral and pharmacological interventions designed specifically for use in patients with PTSD are needed to reduce morbidity and mortality in this population.     

Reengineering the Internet for Better Security

The growing proliferation of malware is raising doubts about the Internet's future. Security measures primarily target inbound traffic, but service providers have no incentive to stop attacks and spam at the source. A proposed certification scheme motivates providers to control outgoing traffic, efficiently increasing overall security while preserving the Internet's open, decentralized structure     

Turnover rates for heptane reforming over Pt/L zeolites with different alkali cations

A series of 0.6 wt% Pt/BaL catalysts with different alkali cations have been tested for heptane reforming at 440 ° C, 0.16 atm heptane, 0.95 atm H₂, 6.7 atm He, 3 to 5 h of reaction, and conversions between 2 and 10%. As the cations in the zeolite are progressively changed from lithium to cesium, the turnover rates for hydrogenolysis and dehydrocyclization increase by about 5–10 times, while the turnover rate for isomerization remains unchanged. Since the turnover rates for hydrogenolysis and dehydrocyclization are similarly affected, exchanging lighter alkali cations for heavier ones increases the aromatics selectivity by a small amount, from 72 to 82%. These results indicate that metal-support interactions have a moderate effect on the heptane reforming activity, but only a weak effect on the selectivity.     

A New Approach to Abstract Syntax with Variable Binding

The permutation model of set theory with atoms (FM-sets), devised by Fraenkel and Mostowski in the 1930s, supports notions of ‘name-abstraction’ and ‘fresh name’ that provide a new way to represent, compute with, and reason about the syntax of formal systems involving variable-binding operations. Inductively defined FM-sets involving the name-abstraction set former (together with Cartesian product and disjoint union) can correctly encode syntax modulo renaming of bound variables. In this way, the standard theory of algebraic data types can be extended to encompass signatures involving binding operators. In particular, there is an associated notion of structural recursion for defining syntax-manipulating functions (such as capture avoiding substitution, set of free variables, etc.) and a notion of proof by structural induction, both of which remain pleasingly close to informal practice in computer science. Received October 2000 / Accepted in revised form April 2001     

Treating smokers before the quit date: can nicotine patches and denicotinized cigarettes reduce cravings?

The present study investigated whether treatment with the combination of denicotinized cigarettes and 21-mg nicotine patch for 2 weeks before a designated quit date could lessen cravings for smoking, thereby helping smokers abstain from smoking. The study was a randomized controlled clinical trial conducted at Roswell Park Cancer Institute, Buffalo, New York, in 2004 and 2005. Patients included 98 adult heavy smokers (using 20 or more cigarettes/day). Half of the subjects received 2 weeks of combination of denicotinized cigarettes (Quest 3) and 21-mg nicotine patch for 2 weeks before the quit date. The remaining smokers were switched to light cigarettes (Quest 1) during the 2 weeks before the quit date. After the quit date, all subjects received counseling for smoking cessation and were provided nicotine patches for up to 8 weeks after the quit date. Self-reported cravings for smoking, withdrawal symptoms, and smoking abstinence were measured at predetermined intervals using phone-based surveys and in clinical visits. The group that used denicotinized cigarettes and nicotine patch before quitting reported less frequent and less intense cravings for cigarettes in the 2 weeks before and after the designated quit date. Self-reported withdrawal symptoms and quit rates did not differ significantly between the groups. The use of a denicotinized cigarette combined with the nicotine patch appears to lessen cravings to smoke in the immediate postcessation period. A larger, better-powered study is needed to test if this treatment combination has merit for increasing quit rates.     

Hydrophilic peptides derived from the transframe region of Gag-Pol inhibit the HIV-1 protease

The HIV-1 transframe region (TFR) is between the structural and functional domains of the Gag-Pol polyprotein, flanked by the nucleocapsid and the protease domains at its N and C termini, respectively. Transframe octapeptide (TFP) Phe-Leu-Arg-Glu-Asp-Leu-Ala-Phe, the N terminus of TFR, and its analogues are competitive inhibitors of the action of the mature HIV-1 protease. The smallest, most potent analogues are tripeptides: Glu-Asp-Leu and Glu-Asp-Phe with Ki values of approximately 50 and approximately 20 microM, respectively. Substitution of the acidic amino acids in the TFP by neutral amino acids and d or retro-d configurations of Glu-Asp-Leu results in an >40-fold increase in Ki. Protease inhibition by Glu-Asp-Leu is dependent on a protonated form of a group with a pKa of 3.8; unlike other inhibitors of HIV-1 protease which are highly hydrophobic, Glu-Asp-Leu is extremely soluble in water, and its binding affinity decreases with increasing NaCl concentration. However, Glu-Asp-Leu is a poor inhibitor (Ki approximately 7.5 mM) of the mammalian aspartic acid protease pepsin. X-ray crystallographic studies at pH 4.2 show that the interactions of Glu at P2 and Leu at P1 of Glu-Asp-Leu with residues of the active site of HIV-1 protease are similar to those of other product-enzyme complexes. It was not feasible to understand the interaction of intact TFP with HIV-1 protease under conditions of crystal growth due to its hydrolysis giving rise to two products. The sequence-specific, selective inhibition of the HIV-1 protease by the viral TFP suggests a role for TFP in regulating protease function during HIV-1 replication.     

On-Line Shape recognition with incremental training using binary synaptic weights algorithm

Recognition of hand drawn shapes is beneficial in drawing packages and automated sketch entry in handheld computers. In this paper, we propose a new approach to on-line geometric shape recognition with incremental training function, which utilizes a heuristic function to reduce noise and a neural network for classification and on-line training. Instead of recognizing segments of a drawing and then performing syntactical analysis to match with a predefined shape, which is weak in terms of generalization and dealing with noise, we examine the shape as a whole. The main concept of the recognition method is derived from the fact that internal angles are very important in the perceived shape of outlines. Our application's aim is to recognize elliptic, rectangular, and triangular shapes in a way similar to human cognition of these shapes. Human beings recognize such basic shapes regardless of the variations in size, noise on the shape border, rotation and in the case of triangles, regardless of the type of the triangle. The key concept is that the neural network learns the relationships between the internal angles of a shape and its classification, therefore only a few training samples which represent the class of the shape are sufficient. Fast meremental training, which is performed on-line, is accomplished by the use of the Binary Synaptic Weights algorithm, a one pass, feedforward neural network training algorithm. Incremental training offers the advantage of adjusting the recognition capability of the system to the user's drawings. the results are very successful, such that the neural network correctly classified shapes that did not have any resemblance to the shapes in the initial training set.