Prolonged exposure for the treatment of Spanish-speaking Puerto Ricans with posttraumatic stress disorder: a feasibility study

<p>Abstract</p> <p>Background</p> <p>Most of the empirical studies that support the efficacy of prolonged exposure (PE) for treating posttraumatic stress disorder (PTSD) have been conducted on white mainstream English-speaking populations. Although high PTSD rates have been reported for Puerto Ricans, the appropriateness of PE for this population remains unclear. The purpose of this study was to examine the feasibility of providing PE to Spanish speaking Puerto Ricans with PTSD. Particular attention was also focused on identifying challenges faced by clinicians with limited experience in PE. This information is relevant to help inform practice implications for training Spanish-speaking clinicians in PE.</p> <p>Results</p> <p>Fourteen patients with PTSD were randomly assigned to receive PE (n = 7) or usual care (UC) (n = 7). PE therapy consisted of 15 weekly sessions focused on gradually confronting and emotionally processing distressing trauma-related memories and reminders. Five patients completed PE treatment; all patients attended the 15 sessions available to them. In UC, patients received mental health services available within the health care setting where they were recruited. They also had the option of self-referring to a mental health provider outside the study setting. The Clinician-Administered PTSD Scale (CAPS) was administered at baseline, mid-treatment, and post-treatment to assess PTSD symptom severity. Treatment completers in the PE group demonstrated significantly greater reductions in PTSD symptoms than the UC group. Forty percent of the PE patients showed clinically meaningful reductions in PTSD symptoms from pre- to post-treatment.</p> <p>Conclusions</p> <p>PE appears to be viable for treating Puerto Rican Spanish-speaking patients with PTSD. This therapy had good patient acceptability and led to improvements in PTSD symptoms. Attention to the clinicians' training process contributed strongly to helping them overcome the challenges posed by the intervention and increased their acceptance of PE.</p

Predicting mostly disordered proteins by using structure-unknown protein data

BACKGROUND: Predicting intrinsically disordered proteins is important in structural biology because they are thought to carry out various cellular functions even though they have no stable three-dimensional structure. We know the structures of far more ordered proteins than disordered proteins. The structural distribution of proteins in nature can therefore be inferred to differ from that of proteins whose structures have been determined experimentally. We know many more protein sequences than we do protein structures, and many of the known sequences can be expected to be those of disordered proteins. Thus it would be efficient to use the information of structure-unknown proteins in order to avoid training data sparseness. We propose a novel method for predicting which proteins are mostly disordered by using spectral graph transducer and training with a huge amount of structure-unknown sequences as well as structure-known sequences. RESULTS: When the proposed method was evaluated on data that included 82 disordered proteins and 526 ordered proteins, its sensitivity was 0.723 and its specificity was 0.977. It resulted in a Matthews correlation coefficient 0.202 points higher than that obtained using FoldIndex, 0.221 points higher than that obtained using the method based on plotting hydrophobicity against the number of contacts and 0.07 points higher than that obtained using support vector machines (SVMs). To examine robustness against training data sparseness, we investigated the correlation between two results obtained when the method was trained on different datasets and tested on the same dataset. The correlation coefficient for the proposed method is 0.14 higher than that for the method using SVMs. When the proposed SGT-based method was compared with four per-residue predictors (VL3, GlobPlot, DISOPRED2 and IUPred (long)), its sensitivity was 0.834 for disordered proteins, which is 0.052–0.523 higher than that of the per-residue predictors, and its specificity was 0.991 for ordered proteins, which is 0.036–0.153 higher than that of the per-residue predictors. The proposed method was also evaluated on data that included 417 partially disordered proteins. It predicted the frequency of disordered proteins to be 1.95% for the proteins with 5%–10% disordered sequences, 1.46% for the proteins with 10%–20% disordered sequences and 16.57% for proteins with 20%–40% disordered sequences. CONCLUSION: The proposed method, which utilizes the information of structure-unknown data, predicts disordered proteins more accurately than other methods and is less affected by training data sparseness

Accurate Prediction of Secreted Substrates and Identification of a Conserved Putative Secretion Signal for Type III Secretion Systems

The type III secretion system is an essential component for virulence in many Gram-negative bacteria. Though components of the secretion system apparatus are conserved, its substrates—effector proteins—are not. We have used a novel computational approach to confidently identify new secreted effectors by integrating protein sequence-based features, including evolutionary measures such as the pattern of homologs in a range of other organisms, G+C content, amino acid composition, and the N-terminal 30 residues of the protein sequence. The method was trained on known effectors from the plant pathogen Pseudomonas syringae and validated on a set of effectors from the animal pathogen Salmonella enterica serovar Typhimurium (S. Typhimurium) after eliminating effectors with detectable sequence similarity. We show that this approach can predict known secreted effectors with high specificity and sensitivity. Furthermore, by considering a large set of effectors from multiple organisms, we computationally identify a common putative secretion signal in the N-terminal 20 residues of secreted effectors. This signal can be used to discriminate 46 out of 68 total known effectors from both organisms, suggesting that it is a real, shared signal applicable to many type III secreted effectors. We use the method to make novel predictions of secreted effectors in S. Typhimurium, some of which have been experimentally validated. We also apply the method to predict secreted effectors in the genetically intractable human pathogen Chlamydia trachomatis, identifying the majority of known secreted proteins in addition to providing a number of novel predictions. This approach provides a new way to identify secreted effectors in a broad range of pathogenic bacteria for further experimental characterization and provides insight into the nature of the type III secretion signal

BDNF Methylation and Maternal Brain Activity in a Violence-Related Sample

It is known that increased circulating glucocorticoids in the wake of excessive, chronic, repetitive stress increases anxiety and impairs Brain-Derived Neurotrophic Factor (BDNF) signaling. Recent studies of BDNF gene methylation in relation to maternal care have linked high BDNF methylation levels in the blood of adults to lower quality of received maternal care measured via self-report. Yet the specific mechanisms by which these phenomena occur remain to be established. The present study examines the link between methylation of the BDNF gene promoter region and patterns of neural activity that are associated with maternal response to stressful versus non-stressful child stimuli within a sample that includes mothers with interpersonal violence-related PTSD (IPV-PTSD). 46 mothers underwent fMRI. The contrast of neural activity when watching children-including their own-was then correlated to BDNF methylation. Consistent with the existing literature, the present study found that maternal BDNF methylation was associated with higher levels of maternal anxiety and greater childhood exposure to domestic violence. fMRI results showed a positive correlation of BDNF methylation with maternal brain activity in the anterior cingulate (ACC), and ventromedial prefrontal cortex (vmPFC), regions generally credited with a regulatory function toward brain areas that are generating emotions. Furthermore we found a negative correlation of BDNF methylation with the activity of the right hippocampus. Since our stimuli focus on stressful parenting conditions, these data suggest that the correlation between vmPFC/ACC activity and BDNF methylation may be linked to mothers who are at a disadvantage with respect to emotion regulation when facing stressful parenting situations. Overall, this study provides evidence that epigenetic signatures of stress-related genes can be linked to functional brain regions regulating parenting stress, thus advancing our understanding of mothers at risk for stress-related psychopathology

The origin, composition and rates of organic nitrogen deposition: A missing piece of the nitrogen cycle?

Organic forms of nitrogen are widespread in the atmosphere and their deposition may constitute a substantive input of atmospheric N to terrestrial and aquatic ecosystems. Recent studies have expanded the pool of available measurements and our awareness of their potential significance. Here, we use these measurements to provide a coherent picture of the processes that produce both oxidized and reduced forms of organic nitrogen in the atmosphere, examine how those processes are linked to human activity and how they may contribute to the N load from the atmosphere to ecosystems. We summarize and synthesize data from 41 measurements of the concentrations and fluxes of atmospheric organic nitrogen (AON). In addition, we examine the contribution of reduced organic nitrogen compounds such as amino acids, bacterial/particulate N, and oxidized compounds such as organic nitrates to deposition fluxes of AON. The percentage contribution of organic N to total N loading varies from site to site and with measurement methodology but is consistently around a third of the total N load with a median value of 30% (Standard Deviation of 16%). There are no indications that AON is a proportionally greater contributor to N deposition in unpolluted environments and there are not strong correlations between fluxes of nitrate and AON or ammonium and AON. Possible sources for AON include byproducts of reactions between NO_x and hydrocarbons, marine and terrestrial sources of reduced (amino acid) N and the long- range transport of organic matter (dust, pollen etc.) and bacteria. Both dust and organic nitrates such as PAN appear to play an important role in the overall flux of AON to the surface of the earth. For estimates of organic nitrate deposition, we also use an atmospheric chemical transport model to evaluate the spatial distribution of fluxes and the globally integrated deposition values. Our preliminary estimate of the magnitude of global AON fluxes places the flux between 10 and 50 Tg of N per year with substantial unresolved uncertainties but clear indications that AON deposition is an important aspect of local and global atmospheric N budgets and deserves further consideration