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Department of Psychiatry, UMDNJ—Robert Wood Johnson Medical School, Piscataway, NJ, USA
Departments of Psychiatry and Neurology, UMDNJ—Robert Wood Johnson Medical School, Piscataway, NJ, USA
Department of Psychiatry. UMDNJ—Robert Wood Johnson Medical School, Piscataway, NJ, USA
BACKGROUND: Hot flashes are one of the most troubling manifestations of menopause, affecting about 80% of women. Due to recent controversies about hormone replacement therapy, many women seek alternative treatments. The use of antidepressants to treat hot flashes and other menopausal symptoms has been an active area of investigation. However, the majority of past research in this area has included women with significant medical or psychiatric histories that may influence treatment response. This was the first study to examine the impact of escitalopram on hot flashes, mood, sleep, and quality of life in a sample of healthy nondepressed menopausal women.
METHODS: This study enrolled 25 menopausal women who had no significant psychiatric or medical history. All women were treated with escitalopram (10 to 20 mg flexibly dosed) for 8 weeks. The active treatment phase was preceded by a single-blind placebo lead-in period.
RESULTS: Over the course of the study, women reported significant decreases in both hot flash frequency and severity as well as improvements in dysphoria, anxiety, quality of life, and sleep.
CONCLUSION: These preliminary findings suggest that escitalopram may be a feasible and effective option for treating hot flashes and other menopausal symptoms in healthy women who might not ordinarily consider antidepressant treatment.
KEYWORDS: escitalopram, hot flashes, nonclinical sample, nondepressed menopausal women
Menopause is a physically and emotionally challenging transition phase in a woman's life. The cessation of menstrual periods is frequently accompanied by hot flashes, night sweats, fatigue, insomnia, depression, anxiety, memory loss, and urogenital symptoms, often resulting in a significant disturbance of quality of life.1,2 Of these, hot flashes have been reported to be one of the most troubling menopausal symptoms, affecting up to 80% of women.3,4
Because many of the physiological changes that occur during menopause result from decreased levels of estrogen, hormone replacement therapy (HRT) historically has been considered a first-line treatment for hot flashes.5,6 However, a number of recent studies have raised concerns about the adverse effects of HRT. For example, the Women's Health Initiative (WHI) randomized controlled trial was stopped early based on evidence that the increased risk of breast cancer, coronary heart disease, stroke, and pulmonary embolism associated with HRT use far outweighed the possible benefit of decreasing the risk for hip fractures and colorectal cancer.6 Later, the Women's International Study of Long Duration Oestrogen after Menopause (WISDOM) confirmed that HRT increased cardiovascular and thromboembolic risk when started many years after menopause.7 Additional studies also have linked the long-term use of HRT with increased risk of ovarian cancer8 and dementia in postmenopausal women age ≥65 years.9 The numerous risks and side effects (eg, vaginal bleeding, edema) associated with HRT often result in failure to initiate, poor adherence to, or abrupt discontinuation of HRT regimens.10-18
Therefore, many women seek novel interventions to help them cope with menopausal hot flashes. Complementary and alternative medicine (CAM) approaches (eg, acupuncture, reflexology, Chinese herbs, dong quai, evening primrose oil, ginseng, kava or red clover extracts, black cohosh) for the treatment of menopausal symptoms have received some empirical attention.19-22 However, results on the effectiveness of these treatments have been mixed, and data on the long-term safety of their use are lacking.20-23 Other prescription medications such as clonidine and gabapentin also have been investigated as a treatment for menopausal hot flashes but studies have yielded inconsistent results.24
Due to the potential interaction between estrogen and neurotransmitters such as serotonin, the use of antidepressants (eg, paroxetine, fluvoxamine, sertraline, venlafaxine, mirtazapine, citalopram, fluoxetine, desvenlafaxine) to treat hot flashes and other menopausal symptoms has become an important area of investigation.5,25-36 Whereas some pilot studies, case reports, and randomized controlled trials have linked the use of antidepressants to significant reductions in hot ashes, dysphoria, anxiety, and insomnia, as well as improvements in quality of life,25-33,36 other studies have reported null findings.34,35 However, most of this research has been conducted with oncology patients (eg, breast cancer survivors) for whom HRT is contraindicated.25-27,29,31 Of the nononcology studies conducted, very few have examined the use of antidepressants to treat hot flashes in a sample of psychologically healthy women.32,34-36 Therefore, it is important to continue to examine the impact of antidepressants on menopausal symptoms in populations of women without medical and psychiatric histories that may influence treatment response.
Escitalopram, the newest of the selective serotonin reuptake inhibitors (SSRIs), has not been previously evaluated as an alternative therapy for hot flashes in a sample of healthy, nondepressed women. The purpose of this pilot study was to explore the use of escitalopram (10 to 20 mg, flexibly dosed) for the treatment of hot flashes, as well as emotional distress, sleep, and quality of life, in nondepressed menopausal women who have no history of cancer.
Women were recruited from the local community via newspaper ads, as well as through physician referral at UMDNJ-Robert Wood Johnson Medical School (RWJMS). All participants received the study medication and all study-related evaluations free of charge. Women were paid $30 for each completed study visit to compensate for travel expenses and time.
A total of 25 nondepressed menopausal women who reported at least 14 hot flashes per week were enrolled in the trial. One additional woman withdrew consent after the screening appointment. All women had experienced a natural cessation of menstrual periods for at least 12 months, had no current psychiatric diagnosis per DSM-IV37 criteria as confirmed by the Structured Clinical Interview for DSM-IV (SCID),38 and had absent or minimal levels of depressive symptoms as defined by a Hamilton Depression Rating Scale (HAMD)39 score <11. None of the women included in the study had taken HRT within the past 6 months or had a history of poor response to HRT.
Women with a history of breast or other types of cancer and/or any current, medically unstable condition were excluded from the study. Other exclusion criteria included: a history of substance abuse or dependence within the past year; lifetime history of major depressive disorder, suicide attempts, or self-injurious behavior; initiation of psychotherapy within the past 3 months; or any major sleep disturbances.
Screening appointment. After completing a preliminary phone screen, potential participants were scheduled for an in-person evaluation. All women provided written informed consent prior to completing any study procedures. The study had full approval from the UMDNJRWJMS Institutional Review Board.
At the initial appointment, psychiatric and medical eligibility were determined via clinical interview, review of the patient's medical and psychiatric histories, and the administration of the SCID,38 the HAM-D,39 and the Pittsburgh Sleep Quality Index (PSQI).40 Hot flash diaries were distributed to the eligible women to complete on a daily basis at home during the following week.
Single-blind placebo lead-in appointment. Given the high rate of placebo response in hot flash studies,41 the active treatment phase was preceded by a single-blind placebo lead-in. At this appointment (1 week after screening), hot flash diaries were reviewed, and eligible women (ie, those with ≥14 hot flashes per week) were given a placebo to take for 1 week, while continuing to complete their hot flash diaries. All women were aware that they would be given placebo for 1 week during the trial. However, they did not know which week placebo would be administered. The placebo tablets appeared identical to the escitalopram tablets.
Baseline appointment. At the baseline appointment (2 weeks after screening), hot flash diaries were reviewed. Participants who were found to be placebo responders (ie, >25% reduction in hot flash frequency) were excluded from the active treatment trial and referred for appropriate follow-up.
Intervention. Women who were not placebo responders received escitalopram for 8 weeks (10 mg/d on weeks 1 to 4 and 10 to 20 mg/d on weeks 5 to 8, depending on participant and investigator assessment of efficacy and side effects).
Assessments/visits. All participants completed hot flash diaries on a daily basis throughout the duration of the study. In the diaries, women recorded the number of hot flashes experienced each day, the severity of each hot flash (1=mild, 2=moderate, 3=severe, 4=very severe), and the total hours of sleep obtained each night. Hot flash diaries were reviewed with women on a weekly basis. A composite score reflecting both the frequency and severity of hot flashes also was calculated for each weekly hot flash assessment. Hot flash frequency and hot flash composite scores were designated the co-primary study outcomes. In addition, treatment response was defined a priori as a ≥50% decrease in hot flash frequency from baseline (after the placebo lead-in) to end of treatment.
The following self-report questionnaires and clinician-administered measures were completed at the baseline appointment and at the end of weeks 3, 6, and 8 of the active trial for the assessment of secondary outcomes: the HAM-D,39 the Hamilton Anxiety Rating Scale (HAM-A),42 the Menopause Quality of Life Scale (MENQOL),43 the PSQI,40 and the Greene Climacteric Scale (GCS).44 Adverse events were collected at each visit by directly questioning the patient.
Data were analyzed using repeated measures analysis of variance (ANOVA), with SPSS 15.0 for Windows. Data analysis included all patients who started the trial and took at least 1 dose of escitalopram. For those who did not complete the study, the last observation was carried forward. A significance level of alpha=.01 was employed in all statistical analyses. Baseline data were obtained after the placebo lead-in period. Data were collected from October 2004 to July 2006.
A total of 25 nondepressed women (18 Caucasian, 5 African-American, 1 Hispanic, 1 Pacific Islander) were enrolled in the active treatment phase. There were no placebo responders, as defined above, during the lead-in period. On average, women experienced a 2% reduction in the frequency of hot flashes after taking placebo for 1 week, and repeated measures ANOVA indicated that this change was not significant.
Of the sample, 64% (n=16) remained on 10 mg of escitalopram throughout the trial. The remaining 36% of the sample (n=9) increased the dosage of escitalopram after week 4: in this group, 8 women titrated up to 20 mg and one up to 15 mg. Of the 8 women who increased to 20 mg, one chose to taper back down to 10 mg. However, she did not report any side effects while taking either dose.
In total, 22 women (88%) completed the trial. Three women dropped out of treatment due to medication side effects (anxiety and insomnia); all of these women were taking 10 mg of escitalopram.
TABLE 1 illustrates the results of the repeated measures ANOVAs as well as means and standard deviations for the hot flash variables assessed in the trial. Over the course of the study, women experienced significant decreases in both the hot flash frequency and hot flash composite scores. Sixteen women (64%) were treatment responders (>50% decrease in hot flash frequency), with an average decrease of 55% in hot flash frequency observed across all participants. Planned contrasts indicated that initial improvements in hot flashes were observed after 1 week of active treatment and were maintained throughout the 8-week treatment period.
TABLE 1 also depicts the results of the repeated measures ANOVAs as well as means and standard deviations for the assessment of depression, anxiety, and quality of life throughout the study. Significant improvements in depression, anxiety, and quality of life were also observed over the course of the trial. Planned contrasts indicated that these gains occurred by the third week of active treatment and were maintained throughout the 8-week treatment phase.
Several sleep parameters were also evaluated. Means, standard deviations, and the results of the repeated measures ANOVAs for all sleep assessments across time appear in TABLE 2. On the PSQI, subjective sleep quality and sleep disturbances significantly improved over the course of the study. There was a trend towards improvement in global ratings of sleep, sleep duration, sleep latency, and sleep efficiency. No change was noted in daytime dysfunction due to insomnia, although baseline rates of this complaint were quite low at the beginning of the study. The rate of change in the use of sleep medications was not explored, as the use of concomitant psychotropic medication was prohibited. No improvements in total sleep time were noted in the hot flash diaries.
Means and standard deviations for outcome measures across time
Women were directly asked about their experience of side effects throughout the study. Fifty-six percent of women (n=14) reported side effects while participating in the study. The majority of side effects were mild and transient, with the most frequently reported events being fatigue (16%, n=4) and decreased libido (16%, n=4). Additional side effects were noted infrequently, with 2 reports of anorgasmia, and 1 each of the following: constipation, dry mouth, muscle tension, shoulder pain, fogginess, diarrhea, irritability, anxiety, insomnia, mild nausea, leg cramps, mild spotting, and weight gain. Two participants also reported side effects (fatigue and anxiety) while receiving placebo.
This is the first study to evaluate escitalopram as an alternative treatment for menopausal symptoms in a sample of medically stable, nondepressed women. The results of this study suggest that escitalopram is an effective nonhormonal approach for the treatment of hot flashes and other symptoms associated with menopause. Over the course of the study, women reported significant decreases in both the frequency and severity of hot flashes, in addition to significant improvements in dysphoria, anxiety, quality of life, and sleep. Speed of relief from hot flashes was rapid (within a week of beginning active drug), and improvements were durable for the remainder of the trial. Escitalopram was well tolerated, with 88% of participants completing the study. This completion rate favorably compares with the rates observed in other published trials of SSRIs.45
Fatigue and decreased libido were the most commonly reported side effects in this trial, affecting approximately 16% of the patients. Other side effects, such as anxiety, insomnia, and irritability, were experienced less often. Overall, in studies of its efficacy for depression and anxiety, escitalopram has been shown to have a favorable side effect profile.46 The rate of adverse events reported in this trial (56% of the subjects) is comparable to the rates observed in 2 double-blind, randomized, placebo-controlled trials of escitalopram for depression (79% and 56.8%),47,48 and no unknown adverse events emerged in this population of women. Escitalopram may be even more well tolerated in menopausal women than in other populations, as the rates of adverse events in studies of SSRIs used to treat vasomotor symptoms tend to be lower than those observed for depression.49
A recent randomized trial of escitalopram vs hormone therapy for the treatment of menopausal depression has suggested that escitalopram can be as efficacious as, and perhaps better than, hormone therapy in treating menopause-related symptoms.50 In this study, both escitalopram and hormone therapy significantly alleviated the impact of hot flashes on daily functioning, with no significant difference observed between the 2 treatments (the study did not examine the treatments' impact on hot flash frequency).50 However, women treated with escitalopram also showed a significantly greater decrease in menopause-related symptoms in general when compared with those women treated with hormone therapy. Although the population under investigation was different (ie, women in this study were clinically depressed), these findings are similar to the results of our open-label trial, which suggest that escitalopram has a salubrious impact on hot flashes and other menopausal symptoms.
Yet, there are a few important limitations to the current trial that warrant consideration. The small sample size may limit the generalizability of study findings. In addition, as this pilot study was uncontrolled, the role of chance as well as nonspecific treatment factors could not be explored. Thus, it is possible that factors other than the study medication, such as time, patient expectations, clinician's attention, and demand characteristics, were responsible for the observed improvement in menopausal symptoms. In particular, high placebo response rates have often been found in hot flash studies.51,52 Although the current trial employed an open-label design, an attempt was made to at least partially control for placebo response with the use of a single-blind placebo lead-in period. A low rate of placebo response was noted during the lead-in period, and baseline data were not obtained until women had been on placebo for 1 week. However, larger, randomized, placebo-controlled trials in nondepressed menopausal women are needed to further evaluate the efficacy of this intervention.
In summary, escitalopram may be a safe and effective alternative treatment for symptomatic menopausal women who are reluctant to initiate HRT, as well as for those who need to discontinue HRT due to side effects or medical complications. For example, a recent Web-based survey assessing women's attitudes about HRT and CAM treatments found that 95% of women would prefer to try an alternative therapy before trying HRT.53 Additional research has indicated that many women are reluctant to initiate hormone replacement because of potential risks,54 and concerns about unwanted side effects, such as weight gain and monthly bleeding, may lead some women to prematurely discontinue HRT.55 Its favorable side effect profile, combined with the rapid and durable improvements in hot flashes observed in this pilot study, indicate that escitalopram may be a good treatment option for menopausal women experiencing vasomotor symptoms, who might not otherwise consider antidepressant treatment.
DISCLOSURES: Dr. Dobkin receives grants/research support from Forest Laboratories and the National Institutes of Health and National Institute of Neurological Disorders and Stroke (NIH/NINDS). Dr. Menza receives research support from the NIH/NINDS, AstraZeneca, Boehringer Ingelheim, Bristol-Myers Squibb, Forest Laboratories, GlaxoSmithKline, Eli Lilly and Company, Pfizer Inc, sanofi-aventis, Sepracor, Takeda, and Wyeth; and is a consultant to the NIH National Institute of Mental Health and NINDS, Bristol-Myers Squibb, GlaxoSmithKline, Kyowa, Labopharm, Lilly Research Laboratories, Pfizer Inc, Ono, and Sepracor; and is a speaker for sanofi-aventis and Takeda. Dr. Allen receives grant/research support from Eli Lilly and Company and Sepracor. Dr. Marin receives grant/research support from NIH/NINDS, GlaxoSmithKline, Eli Lilly and Company, sanofi-aventis, Sepracor, and Takeda and is a consultant to Lilly Research Laboratories. Dr. Bienfait, Ms. Tiu, and Ms. Howarth report no financial relationship with any company whose products are mentioned in this article or with manufacturers of competing products.
ACKNOWLEDGEMENT: This study was supported by Forest Laboratories.
CORRESPONDENCE: Roseanne DeFronzo Dobkin, PhD, Department of Psychiatry, UMDNJ—Robert Wood Johnson Medical School, 675 Hoes Lane, Room D-317, Piscataway NJ 08854 USA. E-MAIL: email@example.com
Annals of Clinical Psychiatry ©2009 American Academy of Clinical Psychiatrists
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Timing isn't the be-all and end-all of investing. Still, in-depth analysis of the property cycle to identify the best time to buy will boost your chances of buying a property that will outperform the average. In a depressed market, … Continue reading
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Renovating For Profit – Tips From The Experts
It's the Holy Grail for many property investors – buying a property, renovating it, and then selling it for a profit. Chris Gray, host of 'Sky News Business' and 'Your Property Empire' recently shared his thoughts on what property investors … Continue reading
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RNA secondary structure plays a scaffolding role for RNA tertiary conformation. Accurate secondary structure prediction can not only identify double-stranded helices and single stranded-loops but also help provide information for potential tertiary interaction motifs critical to the 3D conformation. The average accuracy in ab initio prediction remains 70%; performance improvement has only been limited to short RNA sequences. The prediction of tertiary interaction motifs is difficult without multiple, related sequences that are usually not available. This paper presents research that aims to improve the secondary structure prediction performance and to develop a capability to predict coaxial stacking between helices. Coaxial stacking positions two helices on the same axis, a tertiary motif present in almost all junctions that account for a high percentage of RNA tertiary structures.
This research identified energetic rules for coaxial stacks and geometric constraints on stack combinations, which were applied to developing an efficient dynamic programming application for simultaneous prediction of secondary structure and coaxial stacking. Results on a number of non-coding RNA data sets, of short and moderately long lengths, show a performance improvement (specially on tRNAs) for secondary structure prediction when compared with existing methods. The program also demonstrates a capability for prediction of coaxial stacking.
The significant leap of performance on tRNAs demonstrated in this work suggests that a breakthrough to a higher performance in RNA secondary structure prediction may lie in understanding contributions from tertiary motifs critical to the structure, as such information can be used to constrain geometrically as well as energetically the space of RNA secondary structure.
RNA secondary structure plays the critical role of scaffolding the tertiary structure (i.e., 3D conformation) [1-5]. In the secondary structure, Watson-Crick (AU and GC) and wobble GU pairs form double-stranded helices that enclose unpaired, single-strand loops [6]. The distinguishable pattern of canonical base pairs has enabled ab initio prediction of the secondary structure, typically by minimization of the global free energy associated with involved structure elements [7-10]. In the past three decades, considerable success has been made in secondary structure prediction, e.g., with average accuracy of about 70% [11-13], and offered a viable venue toward RNA tertiary structure prediction [4,5,13,14]. However, prediction performance breakthroughs have been limited to short RNA sequences; improvements on the accuracy for longer RNA sequences have relied on multiple related sequences [15,16], which are often not available, or profile based alignments [17,18], which can only be effective for known structures.
Elements of the secondary structure are interrelated with tertiary interaction motifs [2,4,19], which consist of less understood non-canonical base pairs, with some just being revealed recently [19,20]. Such motifs bundle and connect helices to form and stabilize the tertiary structure. As a common local motif, two helices sharing a contiguous backbone strand may coaxially stack resulting in an energetically more stable pseudo-contiguous helix [21,22]. Coaxial helices are prevalent in known RNA tertiary structures, for instance accounting for 32% of 613 tertiary interactions in 54 high-resolution RNA structures investigated by Schlick group [23]. In particular, they are present at about 84% of multiple loop junctions involved in these structures. Since junctions are single-strand loops joined and enclosed by helices, computational methods effective on prediction of coaxial stacking would substantially improve the performance of the secondary structure prediction as well.
There were only a few previous results in computational investigation of RNA helix coaxial stacking. Walter et al [24] demonstrated in a case study that base-pair to base-pair stacks between terminal base pairs of two neighboring helices provide free energy improvement for the predicted secondary structure. Tyagi and Mathews [22] tested the idea of predicting coaxial stacking by free energy minimization using nearest-neighborhood parameters on known RNA secondary structures. They showed the potential to predict coaxial stack with free energy minimization when the number of intervening mismatches between stacked helices is small. In the comparative analysis of 3-way junctions joined by three helices, Lescoute and Westhof measured distance distributions between the two coaxially stacked helices within the junctions [25]. For junctions of four-ways and of higher orders, it was observed by Schlick group [26,27] that coaxial stacking occurs preferentially in helices adjacent to loops of small size and rich in adenine. In this paper, we present a new method for the prediction of RNA secondary structure and coaxial stacking. Different from previous secondary structure prediction methods, ours can produce information of coaxially stacked helices included in the predicted structure. Unlike prediction of coaxial stacking upon an already predicted secondary structure, the new method offers the simultaneous prediction of the two. We discovered and applied rules of coaxial stacking, including both sequential and structural patterns, to the prediction of secondary structure. Such rules constrain possible energetic and geometric relationships between helices to be predicted, resulting in a reduced space of alternative structures and a potential improvement in secondary structure prediction.
The new method has been developed into a dynamic programming application (called RNAcoast). We conducted tests on five families of ncRNAs, of total 386 sequences, to evaluate the capability of the new method in simultaneous prediction of secondary structure and coaxial stacking. These ncRNAs were retrieved from Rfam database [28], of short to moderately long lengths, with and without coaxial stacking in the tertiary structure. RNAcoast produced comparable predictions as the state-of-the-art program RNAfold on all cases, it outperformed the latter on tRNAs, where coaxial stacks are present, by an additional 17% accuracy, a significant leap from the average performance (i.e., 60-70% of the number of correct base pairs) achievable by previous energy based models on tRNAs. The test results demonstrate that coaxial stacking rules can successfully narrow down a possibly large number of alternative structures within 5-10% of the predicted minimum energy, which would otherwise be difficult to distinguish.
We implemented the algorithm into a program named RNAcoast. We tested five ncRNA sets of sequences on our program and compared the predicted secondary structure with the original Rfam annotation to evaluate its accuracy. We also tested these ncRNA sequences on the state-of-the-art secondary structure prediction program RNAfold [9,29], and made performance comparisons between the mentioned programs. All test data and results are available at: http://www.cs.uga.edu/~shareghi/RNAcoast webcite.
Data preparation
We downloaded five ncRNA datasets from seed alignments of Rfam. Ninety-five (10% of) tRNA sequences were randomly picked up from the corresponding seed alignment of 967 tRNAs. All ninety-eight available Intron Group II sequences and all eighty-four available Hammerhead type III sequences were retrieved directly from seed datasets. We also downloaded all 30 Intron Group I sequences available from its seed alignment, and extracted the P4P6 domain of each sequence. Similarly, we retrieved all 79 HCV IRES sequences available from its seed alignment, and extracted domain III of each sequence. The average lengths of tRNAs, Intron group II, Hammerhead type III, P4P6, and domain III of HCV IRES are 73.62, 87.18, 55.36, 126, and 111.68, respectively. Many of these sequences contain long inserted regions compared to their annotated consensus structures, with lengths greatly exceeding the corresponding average lengths (see Table 1). Therefore, these collections of ncRNA sequences cover short to moderately long lengths. Coaxial stacks are present in tRNAs, Hammerhead type III, and HCV IRES domain III, while they are not present in the consensus of Intron Group II or the consensus of P4P6 domain. However, some P4P6 sequences have a long insertion region containing a three-way junction, where coaxial stacking may occur. The secondary structures of these ncRNAs vary as well, from simpler structures in Hammerhead type III and Intron Group II to more sophisticated tRNAs and some P4P6 sequences containing the inserted 3-way junction and a GAAA tetra-loop [1].
Table 1. Sensitivity based on the number of correctly predicted base pairs
Performance in secondary structure prediction
We conducted two types of evaluations on the predicted structures. One is to consider the percentage of base pairs correctly predicted by the programs. The other is to consider the number of sequences whose overall structure topology is correctly predicted. Shown in the next section, we also evaluated the capability of RNAcoast in predicting coaxial stacks.
Table 1 summarizes the performance of RNAcoast vs RNAfold with reference to the original annotated consensus structures for the tested ncRNAs. The sensitivity is computed as
where TP is the number of true positives (i.e. correctly predicted base pairs) and FN the number of false negatives (i.e. missed base pairs). The results show that for short sequences of simpler secondary structures, i.e., Hammerhead type III and Intron Group II, both RNAcoast and RNAfold performed well, with RNAcoast slightly less accurate than RNAfold. Also, for longer sequences in HCV IRES domain III dataset, both programs performed well, with RNAcoast slightly more accurate than RNAfold.
Test results on the tRNA data set demonstrates the true advantage of incorporating coaxial stacking into prediction of ncRNAs that may contain coaxial stacking motifs. RNAcoast outperformed RNAfold by more than 17% accuracy, a significant leap from the average performance (i.e., 60-70%) achievable by previous energy based models on tRNAs. The coaxial stacking rules successfully narrowed down a possibly large number of alternative structures within 5-10% of the predicted minimum energy, which would otherwise be difficult to distinguish [12].
Table 2 shows that the performance of RNAcoast was actually even better when the real structure of these tRNA sequences were examined against the consensus. RNAcoast captured the secondary structure topology correctly for more than 72% of sequences. We carefully examined those sequences whose topologies were not predicted correctly and were able to identify that half of them actually have a long variable loop (see Figure 1) which contains an extra helix, some correctly predicted by RNAcoast and RNAfold. Therefore, the percentage of correctly predicted topologies for RNAcoast was actually 86%, consistent with the sensitivity calculated based on correctly predicted base pairs. Since these tRNAs were randomly sampled from 967 sequences of the seed alignment in Rfam, the test results demonstrate the effectiveness of our method.
Table 2. Sensitivity based on the number of correctly predicted topologies
Figure 1. The general tRNA tertiary structure (and the secondary structure in the box). Four helices (in acceptor, D-arm, TΦC arm, and anticodon arm) enclose loops, including the variable loop (orange), possibly long in some tRNAs. The helix of acceptor (purple) and the helix of TΦC arm (green) coaxially stack (in the nested fashion); the helix of D-arm (red) and the helix of anticodon arm (blue) coaxially stack (in the parallel fashion). Figure modified from Rfam [28].
We point out that the relatively low sensitivity for RNAcoast on Hammerhead ribozyme type III shown in Table 2 was due to the extra stem-loop it predicted within the three-way junction, much as the situation of the variable loop of tRNAs.
For longer sequences of P4P6, counting correctly predicted base pairs appeared to distance RNAcoast a little more from RNAfold; but neither programs achieved a satisfactory sensitivity. The underperformance may be explained by the nature of the P4P6 sequences and the reference consensus structure from Rfam. Out of the thirty sequences tested, 12 of them have lengths exceeding 150 (but under 191), 6 sequences have lengths below 90, and another 12 have lengths in between. The consensus structure from Rfam was based on the smallest group of short sequences, leaving a long inserted region for others. Though both programs were able to predict the substructure formed in the inserted region, but the small number of base pairs annotated in the consensus made them easy to be missed by both programs. However, in spite of the low number of base pairs correctly predicted by RNAcoast, the program was able to achieve an adjusted 67% sensitivity in topology prediction.
Performance in coaxial stacking prediction
To evaluate the performance of our method in coaxial stacking prediction, we computed both the sensitivity and positive predictive value (PPV) on the number of correctly predicted coaxial stacks. The PPV is defined as
where FP stands for false positive, the number of incorrectly predicted coaxial stacks.
Table 3 shows both PPV and sensitivity for RNAcoast to predict coaxial stacks on tRNA, Hammerhead Type III, and HCV IRES domain III sequences, where coaxial stacks are present. There were 190 coaxial stacks in the 95 tRNAs, with two for each, 84 coaxial stacks in Hammerhead type III, with one in each, and 158 coaxial stacks in HCV, with two for each. The program was more specific on tRNAs, achieving a PPV of 75%, compared to 61% on Hammerhead type III, and 66% on HCV IRES domain III. It had the lowest sensitivity, 47%, on HCV IRES domain III compared with the other two families where sensitivity was around 70%.
Table 3. PPV and sensitivity based on the number of correctly predicted coaxial stackings
We compare these results with a previous work by Tyagi and Mathews who tested the idea of coaxial stack prediction using the energy minimization with nearest-neighbor parameters [22] on 31 ncRNAs (with known secondary structures and crystal tertiary structures). We notice that there were 17 tRNA sequences among these 31 sequences, for which the average PPV and sensitivity reported in the literature [22] were 58% and 66%, respectively on k = 0 and k = 1, where k is the number of unpaired nucleotides at the point of backbone joining of the two coaxially stacked helices.
While our program, RNAcoast, produced comparable predictions as the state-of-the-art program RNAfold on all cases, it outperformed the latter on tRNAs, where coaxial stacks are present, by more than 17% accuracy, a significant leap from the average performance (i.e., 60-70% of the number of correct base pairs) achievable by previous energy based models on tRNAs. Furthermore, RNAcoast predicted 86% of secondary structure topologies correctly, while RNAfold only predicted 27% of topologies correctly. Our coaxial stacking rules can successfully pick out the most plausible one from a possibly large number of alternative structures within 5-10% of the predicted minimum energy, which would otherwise be difficult to distinguish [12]. Such a performance is encouraging to solving the problem of RNA tertiary structure prediction.
We point out the small differences in performance between RNAcoast and RNAfold on Hammerhead type III and Intron Group II were most likely due to the simple strategy to exclude loop energies which was built into the current version RNAcoast. This was a little more of an issue for long sequences in the P4P6 dataset, which became serious when the consensus structure did not include a long inserted region. While improving the performance of RNAcoast can be achieved by incorporating the dismissed loop energies, a strategy different from evaluating predictions against the consensus structure may help as well.
We did not use the positive predictive value (PPV) to measure the performance in the correctly predicted base pairs. This was because some base pairs not belonging to the consensus structure but predicted by the programs may be valid if they fall in inserted regions of the consensus structure. Counting such base pairs as false positives would be bias against sequences substantially longer than the consensus. The situation was evident by our tests on these sequences, typically tRNAs where the variable loop may contain an extra stem-loop.
We have also examined the coaxial stacking prediction on the P4P6 sequences by RNAcoast. In contrast to RNAfold that predicted 8 three-way junctions in the long inserted region, our program predicted 5 three-way junctions in that region, with the same left nested coaxial stack predicted for 3 out of the 5 three-way junctions. Such a predicted coaxial stack has yet to be verified as it was counted as a real motif in one work [25] while was not by another [22].
The outcome of the tests on tRNAs is most interesting. The secondary structures of tRNAs were difficult to predict from individual sequences with energy-based methods, in spite of the conserved native structure across types and species. This is because a tRNA may have many alternative structures with free energies within 5-10% of the minimum free energy.
This work introduced a new method for simultaneous prediction of RNA secondary structure and coaxial stacking between helices. The aim of the incorporation of coaxial stacking detection included improving the performance of energy-based ab initio secondary structure prediction. Our research identified sequential, energetic, and geometric rules for helix coaxial stacking to apply to a dynamic programming algorithm for secondary structure prediction. Results from testing the implemented program RNAcoast on five ncRNA datasets obtained from Rfam demonstrated the effectiveness of our method.
The significant leap of performance on tRNAs in this work suggests that a breakthrough to a higher performance in RNA secondary structure prediction may lie in understanding contributions from tertiary motifs critical to the structure, as such information can be used to constrain geometrically as well as energetically the space of RNA secondary structure. Since coaxial stacking is still a local tertiary motif, incorporating information of tertiary motifs of higher orders, such junctions, may further improve the prediction performance.
In the secondary structure, canonical base pairs form double-stranded stems (called helices in tertiary structure) that join and enclose unpaired, single-strand loops. Figure 1 shows the secondary and tertiary structure of tRNAs in general, which consist of four helices enclosing loops. Two neighboring helices joined by a contiguous single-strand loop coaxially stack if they share the same axis in the tertiary structure with the two terminal base pairs of respective helices stacking on each other at the joining point. Figure 2 gives a schematic illustration of two coaxially stacked helices. Depending on where the 5' and 3' ends of the sequence are connected to, the coaxial stack can be nested or parallel (see definition in the section below). Figure 1 shows two pairs of coaxial stacks in the four-way junction of the tRNA tertiary structure. We introduce a new method for simultaneous prediction of RNA secondary structure and coaxial stacks. Our strategy is to reward each potential coaxial stacking with the amount of negative energy incurred by the stacking and to incorporate both the energetic and geometric rules into the secondary structure prediction process. The energy of coaxial stacking is calculated as that contributed by the two stacked terminal base pairs of the coaxial helices (see Figure 2). This is an approximate quantity as the full mechanism for coaxial stacking to stabilize the involved structure is still to be fully understood due to additional tertiary interactions often detected at multi-way junctions where coaxial stacking usually occurs.
Figure 2. Coaxial stacking of helices. A secondary structure illustration of a coaxial stacking between two helices that share the same contiguous single-strand loop, in which unpaired nucleotides may be present. The terminal base pairs from both helices stack each other, resulting in an extra energy reduction calculated as if they were contiguous base pairs (shown in the callout). A, B, C represent the three substructures connected to the two helices, where exactly two substructures can be formed each by one contiguous backbone, and exactly one substructure by two separate backbones. If substructure A or B is formed by two separated backbones, the coaxial stacking is nested; if C is formed by two separated backbones, the stacking is parallel.
Coaxial stacking rules
Previous investigations on three-way junctions [25] and junctions of higher orders [22,26,27] have revealed the small number k of unpaired nucleotides present at the joining loop between the two helices involved in a coaxial stacking. To verify this phenomenon for a wider spectrum of ncRNAs, we conducted a survey on the 51 sets of ncRNA seed alignments from Rfam [28], which had been used by software Infernal [18] as benchmarks. We computed the thermodynamic free energy of every helix instance using the RNAeval component of the Vienna RNA Package [9,29].
Based on this survey, we were able to identify two energy thresholds: less than -2.5 Kcal/mol for semi-stable helices, and less than -3.7 Kcal/mol for stable helices [30]. Both require at least three base pairs in which at least one is a G-C pair. We discovered that semi-stable helices are overwhelmingly very close to other helices in backbone positions. This confirms our conjecture that semi-stable helices interact with other helices on a contiguous strand, i.e., through coaxial stacking [30]. This also suggests a small distance k between coaxial stacked helices, consistent with the findings by others [22,25-27]. In this preliminary work, we used k ≤ 1 as a necessary condition for two neighboring helices to coaxially stack. In our method, coaxial stacking may occur in a two-way junction consisting of two helices sharing both connecting loops or in a multi-way junction joined by multiple helices.
Definition. We denote (X, Y) to be a coaxial stack between helices X and Y. Let L(X) be the set of indexes of nucleotides in the 5'-end base pair region of helix X; also let H(X) be the set of indexes of nucleotides in the 3'-end base pairing region of helix X.
1. Coaxial stack (X, Y) is nested if max L(X) <min L(Y) and max H(Y) < min H(X).
2. Coaxial stack (X, Y) is parallel if max H(X) <min L(Y).
In particular, coaxial stacks in two-way junctions are always nested. In multiple-way junctions, coaxial stacks may be either nested or parallel (see Figures 1 and 2). For example, Figure 1 shows two coaxial stacks: a parallel stack between the D helix and the anticodon helix, and a nested stack between the TΨC helix and the acceptor helix.
The amount of reduced energy, attributed to a coaxial stack, is defined as the free energy contributed from the two stacked base pairs on the interface (see Figure 2). The amount of energy, thus computed via software RNAeval, ranges from -0.9 Kcal/mol to -3.4 Kcal/mol. This is close to the parameter used by Tyagi and Mathews [22].
Geometric constraints
We applied additional constraints on coaxially stacked helices based on geometric feasibility. This is to consider when two or more coaxial stacks may occur simultaneously, and they all involve some helix. In particular, we identified the following rules to ensure consistency in geometry. Assume helix X coaxially stacks with two other helices Y and Z, then exactly one of the following situations must occur:
1. Stacks (X, Y) and (Z, X) are nested stacks,
2. Stack (X, Y) is nested and stack (X, Z) or (Z, X) is parallel,
3. Stack (Y, X) or (X, Y) is parallel and stack (X, Z) is nested.
Figure 3 illustrates the above compound coaxial stacks 1, 2, and 3, respectively from left to right.
Figure 3. Compound coaxial stacks. An illustration for the three general situations of compound coaxial stacks, where 5' and 3' indicate the backbones from the 5' end and to the 3' end of the sequence, respectively. In the left structure, the stacks (X, Y) and (Z, X) are nested stacks. In the middle structure, the stack (X, Y) is nested while (Z, X) is parallel. In the right structure, the stack (X, Y) is parallel while (X, Z) is nested.
We developed our method into an algorithm for ab initio and simultaneous prediction of secondary structure and coaxial stacks. There are two major phases: preprocessing and prediction. Given a query RNA sequence, the preprocessing step finds all semi-stable, stable, and ultra-stable helices (see the Algorithm overview section below), and also all potential coaxially stacked helix pairs. The computed information is then passed onto the prediction phase, which uses a dynamic programming algorithm in the spirit of Nussinov's algorithm. However, our algorithm is established at helix-level instead of nucleotide-level for the purpose of incorporating coaxial stacking. Since helices cannot be sorted in a linear order, the dynamic programming algorithm design became a non-trivial task.
Preprocessing of helices
The preprocessing step picks up helix candidates and identifies potential coaxial stacks. A semi-global alignment algorithm is used for searching helix candidates [30]. In a helix candidate, either backbone is allowed to contain at most one unpaired nucleotide. The free energy of helix candidates is measured using RNAeval, a component of the Vienna RNA Package [9,29].
Two helices are recognized as a potential coaxial stack if they share a contiguous single-strand backbone with at most one unpaired nucleotide. Potential coaxial stacks are classified into parallel and nested stacks based on the conditions given in the section above about Coaxial stacking rules. The extra energy reduction of a coaxial stacking is computed from the two terminal base pairs of the helices as if they were two contiguous base pairs (see the same section).
Prediction via dynamic programming
We adopted the idea in Nussinov's algorithm [7] to develop a dynamic programming algorithm for simultaneous prediction of secondary structure and coaxial stacks. Nussinov's algorithm and alike [9,11] use a simple dynamic programming approach, at the nucleotide level, to predict the secondary structure of an RNA. For each subsequence from position i to j, Nussinov's algorithm computes the substructure with the maximum number of base pairs. In contrast, however, our algorithm works at the helix level in order to incorporate coaxial stacking information. Since helix candidates cannot be sorted in a linear order, the dynamic programming is not straightforward. We addressed this issue by employing partial orderings.
Candidates and orderings
A helix consists of two base pairing regions; each region is a contiguous backbone consisting of a number consecutive nucleotides. A helix found by the preprocessing step can be viewed as two base pairing regions. Throughout this section we will refer to candidate regions simply as candidates.
On an RNA sequence x1 ... xn, for each subsequence from position xa to xb our algorithm goes through every pair of candidates i and j, where i starts at position xa and j ends at position xb. The preprocessing may generate several candidates that start at the same position or end at the same position. Therefore, the order in which we visit such overlapping candidates is important to ensure that we always move from smaller subproblems to larger ones. In other words, for the mentioned subsequence, we want to consider the longest candidate i and the longest candidate j before considering shorter ones. Hence, we assign two different indices to each candidate according to Starting Position Order (SPO) and Ending Position Order (EPO), i.e., for two candidate regions r and s, assuming b(r) gives the starting position of region r, and e(r) gives its ending position, we have:
• r ≤ SPO s, if b(r) < b(s), or if b(r) = b(s) &e(r) < e(s).
• r ≤ EPO s, if e(r) < e(s), or if e(r) = e(s) &b(r) < b(s).
If two candidates occupy the exact same region on the sequence, then one of them gets the lower index in a consistent manner throughout the algorithm.
The recurrence relations in our dynamic programming algorithm have the general form F(i, j), where F is a recursive function defined with specific semantic constraints; it gives the maximum score for the optimal substructure (following the mentioned constraints) of the subsequence that starts from the beginning of the candidate with SPO index i and ends at the end of the candidate with EPO index j. Henceforth, for convenience, i always refers to an SPO index, and j always refers to an EPO index.
Algorithm overview
Similar to Nussinov's algorithm, four different cases can happen when finding the optimal structure of the subsequence spanned from candidate i to j:
• Region i forms a helix (or pairs) with region j.
• Region i does not participate in the optimal structure.
• Region j does not participate in the optimal structure.
• The optimal structure is formed by putting together the optimal substructures of the subsequence from region i to region k, and of the subsequence from region k + 1 to region j, for some k.
Our algorithm can recursively generate the following types of topological constructs:
1. An m-way junction or a single helix not enclosed by any other helix. Such an m-way junction is without a coaxial stacking.
2. An m-way junction enclosed by a helix:
(a) an m-way junction, without coaxial stacking,
(b) a 2-way junction where the helices coaxially stack,
(c) an m-way junction, m > 2, with left or right nested coaxial stacking,
(d) an m-way junction, m > 2, where two of the helices form a parallel stacking.
Each of the three types of helices, defined earlier (see the Preprocessing section), contributes differently to building the above topological constructs. A semi-stable helix can appear in the predicted structure only if (a) it coaxially stacks with a stable helix and does not enclose any other helices, or (b) it participates in a 2-way junction and the two helices together are strong enough to act as a stable helix. The only restriction for a stable helix is that it cannot immediately enclose an m-way junction. In addition to semi-stable and stable helices, we also have ultra-stable helices. An ultra-stable helix has a free energy level lower than -4.6 Kcal/mol and has more than 5 base pairs. For an m-way, m > 2, junction to exist, it needs to be enclosed by an ultra-stable helix. An exception to this rule is when two helices involved in a 2-way junction, put together, are strong enough to act as an ultra-stable helix, then they also can enclose an m-way junction. We define different types of recurrences for generating an optimal secondary structure made of the above topological constructs such that the geometric constraints are met and the coaxial stacking rules are followed as well.
• M (i, j) in which the substructure for the subsequence from region i to j is not enclosed by any helix; it generates construct 1,
• Functions of the form Mxy (i, j) where it is assumed that the structure is enclosed by a helix outside the mentioned subsequence; henceforth, referred to as the enclosing helix. Such recurrences do not immediately cause a bifurcation, therefore, they do not immediately enclose an m-way, m > 2, junction. Instead they may form a helix between i and j, or ignore i and/or j in order to move to a smaller subproblem. The subscript xy is used to determine the type of the recurrence, and it can be any of
- 2W: i and j form a helix, and together with the outside enclosing helix they form a 2-way junction that may or may not involve a coaxial stacking.
- @ϵ: the left-most helix of the substructure coaxially stacks with the enclosing helix.
- ϵ@: the right-most helix of the substructure coaxially stacks with the enclosing helix.
- ϵ ||: the right-most helix of the substructure forms a parallel coaxial stack with a helix to the right of the subsequence from region i to region j.
- || ϵ: the left-most helix of the substructure forms a parallel coaxial stack with a helix to the left of the subsequence from region i to region j.
- ϵϵ: none of the helices in the substructure coaxially stack with any outside helices.
• Functions of the form , where B stands for bifurcation, and different cases of the subscript xy are defined similar to the ones above. Here the important assumption is that the structure is surrounded by an ultra-stable helix outside the mentioned subsequence. If the outside enclosing helix is not strong enough, but when put together with the possible i, j helix they can act as an ultra-stable helix, that is also acceptable. In these recurrences, the substructure predicted for the subsequence from region i to region j will be an m-way junction, m > 2, that may or may not be enclosed by a possible helix formed by i and j. The main difference between a function Mxy (i, j) and a function is that the latter may immediately cause a bifurcation, whereas the former may not.
We use the following notation throughout this section:
• i and i' are used for referring to indices of candidates in the Starting Position Order (SPO).
• j and j' are used for referring to indices of candidates in the Ending Position Order (EPO).
• d (a, b) is the distance between candidate regions a and b. It is the shortest nucleotide distance between the end of candidate a and the beginning of candidate b, assuming a ends before where b starts.
• i + 1 is the candidate region after (and possibly overlapping with) i in the SPO.
• j - 1 is the candidate region before (and possibly overlapping with) j in the EPO.
• s ≥ x (i) is the first non-overlapping successor of i in SPO at a distance greater than or equal to x.
• p ≥ y (j) is the first non-overlapping predecessor of j in EPO at a distance greater than or equal to y.
• represents any non-overlapping successor of i in SPO at distance at most 2 from i.
• represents any non-overlapping predecessor of j in EPO at distance at most 2 from j.
• Aij is the weight of any helix (semi-stable, stable, or ultra-stable) formed by i and j, or - ∞ if no such helix exists.
• Sij is the weight of a helix i, j that is stable or ultra-stable, or - ∞ if no such helix exists.
• Uij is the weight of a helix i, j that is ultra-stable, or - ∞ if no such helix exists.
• CS is the reward for a coaxial stacking. Its value depends on the terminal base pairs of the helices involved.
• In rules of the form F(i, j) = Aij + maxi',j'{M2W (i', j')} the requirement is that the helices formed by candidates i < i' < j' < j do not coaxially stack, |d(i, i') - d(j', j) | ≤ 4, d(i, i') ≤ 11, d(j', j) ≤ 11, and that d(i, i') and d(j', j) cannot both be 0.
Assuming that the preprocessing step results in N candidate regions, the score of the optimal structure for the whole sequence is equal to M(1, N), where
The function ST(i, j) gives the score of the optimal structure for the subsequence from region i to region j, where i and j form a helix.
In the above function, the first case, with M2W, is only allowed when Aij and Ai'j' put together are strong enough to act as a stable helix. The second case, with , is only allowed when Aij and Ai'j' put together are strong enough to act as an ultra-stable helix. The situation is similar for cases 3 and 4 where we have 2-way junctions with coaxial stacking. In case 5, with , helix Uij forms a left nested coaxial stack with a helix that it encloses, but since the enclosed structure is an m-way junction, m > 2, helix Uij has to be ultra stable. Cases 6 is defined and constrained similarly for a right nested coaxial stack. In cases 7 and 8, the helix Uij encloses an m-way junction, m > 2, that may either immediately or later on include a coaxial stacking, therefore it has to be ultra-stable. Case 7 results in an m-way junction that may later on include a coaxial stacking, whereas case 8 results in an m-way junction with a parallel coaxial stacking. Similar constraints are applied to the recurrences below.
The following recurrence is used for generating a helix that does not coaxially stack with any helix outside of the current subsequence.
The following recurrence is used for performing bifurcations such that no helix in the substructure coaxially stacks with any helix outside the current subsequence.
The following recurrence is used for the case that helix Aik forms a left nested coaxial stack with a helix that encloses the subsequence from region i to region j.
Similarly, the following recurrence is used for the case that helix Akj forms a right nested coaxial stack with a helix that encloses the subsequence from region i to region j.
The following recurrence is used for the case that helix Aij forms a 2-way junction with an outside enclosing helix, and it may also form a 2-way junction with a helix in the substructure it encloses.
The following recurrence is used for the case that helix Aij forms a 2-way junction with an outside enclosing helix, but unlike the case for M2W, it immediately encloses an m-way junction, where m > 2.
The following recurrence is used for generating a helix with the assumption that it forms a parallel coaxial stacking with a helix to the right of the subsequence from region i to region j.
The following recurrence is used for performing bifurcations such that the right-most helix of the resulting substructure forms a parallel coaxial stacking with a helix to the right of the subsequence from region i to region j.
Similarly we define the recurrences M||ϵ and for the cases that the left-most helix of the resulting substructure forms a parallel coaxial stack with a helix to left of the subsequence from region i to region j.
SPO: Starting Position Order; EPO: Ending Position Order.
Competing interests
The authors declare that they have no competing interests.
Authors' contributions
PS designed and implemented the prediction algorithm. In addition to contributing to drafting this manuscript, he was also in charge of acquiring data, testing, and analysing the results. YW designed and implemented the pre-processing algorithm. He also helped with data acquisition and result analysis. RM provided the biological insight, and also contributed to data acquisition and results analysis. LC conceived the overall model and algorithm and drafted the manuscript. All authors read and approved the manuscript.
This article has been published as part of BMC Genomics Volume 13 Supplement 3, 2012: Selected articles from the IEEE International Conference on Bioinformatics and Biomedicine 2011: Genomics. The full contents of the supplement are available online at http://www.biomedcentral.com/bmcgenomics/supplements/13/S3.
This research project was supported in part by the NSF MRI 0821263 grant, the NIH BISTI R01GM072080-01A1 grant, the NIH ARRA Administrative Supplement to NIH BISTI R01GM072080-01A1, and the NSF IIS grant of award No: 0916250. We used the software Graphviz (available at http://www.graphviz.org) to draw the predicted secondary structures.
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J Mol Biol 2009, 390:547-559. PubMed Abstract | Publisher Full Text | PubMed Central Full Text
Laing C, Jung S, Iabal A, Schlick T: Tertiary Motifs Revealed in Analyses of Higher-order RNA Junctions.
J Mol Biol 2009, 393:67-82. PubMed Abstract | Publisher Full Text | PubMed Central Full Text
Griffiths-Jones S, Moxon S, Marshall M, Khanna A, Eddy SR, Bateman A: Rfam: Annotating Non-Coding RNAs in Complete Genomes.
Nucleic Acids Res 2005, 33:D121-D141. PubMed Abstract | Publisher Full Text | PubMed Central Full Text
Hofacker IL: Vienna RNA Secondary Structure Server.
Nucleic Acids Res 2003, 31:3429-3431. PubMed Abstract | Publisher Full Text | PubMed Central Full Text
Wang Y, Manzour A, Shareghi P, Shaw T, Li Y, Malmberg R, Cai L: Stable Stem Enabled Shannon Entropies Distinguish Non-coding RNAs from Random Backgrounds.
BMC Bioinformatics 2012, 13(Suppl 5):S1. PubMed Abstract | BioMed Central Full Text | PubMed Central Full Text


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.Asics Hammer shirt and shorts have moisture wicking compression fabric and flatlock stitching.ON SALE NOW!
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.Asics Hammer shorts have moisture wicking, compression fabric, and flatlock stitching. multiple panel construction for a great fit
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. BRUTE OHIO STATE SINGLET AT CLOSEOUT PRICES! Toughtex Lycra singlet, high cut with hemmed legs and gripper elastic. Various color combinations.
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Front End Alignment in Inverness
Time to book a thorough front end alignment in Inverness? Turn to the Smart Service Technicians at Tires Plus Total Car Care — we deliver the professional skills and know-how you need to keep your steering and suspension components in top shape.
If you want to extend the life of your vehicle, regular maintenance is vital — so schedule an appointment in in Inverness today and discover how our convenient and affordable service can help save you from costly repairs in the future.
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When your tires show signs of uneven wear — or, worse, your steering pulls to one side — it may be the case that you're in need of our trademark Straight Forward Alignment Service. When you turn to us, you can be confident in knowing that our knowledgeable team will take the time to properly inspect your vehicle, so that you can drive away satisfied. They will:
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For top-notch service and premium products at affordable prices, turn to the professionals at Tires Plus Total Car Care. The PLUS in our name goes into everything we do — so contact us today to schedule your appointment.


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1,2-Bis(diisopropylamino)-1,2-dihydro-1,2-benzodiborete - a first thermally stable 1,2-dihydro-1,2-diborete.
In: Chemische Berichte (Chem.Ber.), Jg. 127 (1994) ; Nr. 11, S. 2349-2351
Zeitschriftenaufsatz / Fach: Chemie
Aminolysis of 1,2-(Cl2B)2C6H4 with R2NH (R = Me2CH throughout this abstr.) gave 1,2-[(R2N)(Cl)B]2C6H4 which on NaK8 mediated coupling gave title compd. I. Cryst. I is thermally stable; an x-ray crystallog. structure detn. for which has been carried out. In concd. soln., reaction of 1,2-[(R2N)(Cl)B]2C6H4 with sodium/potassium alloy predominantly leads to the formation of the tetraborocine II by dimerization. In the presence of (phthalocyaninato)palladium as catalyst I reacts with 2 equiv of di-Me acetylenedicarboxylate to give the benzo-annulated diborocine III.


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Happy Birthday to Cakespy!
Lately I've been obsessed with dessert writing, mostly because I started reading Cupcakes Take the Cake. That led me directly to reading Seattle's very own Cakespy.
Cakespy is a blog run by artist/writer Jessie Moore Oleson and if there is any place in Seattle that can satisfy your sugar cravings, she and her sweet tooth know about it. Last week, Cakespy celebrated its first year online and to celebrate both the blog's and Cakespy's personal birthdays, they're throwing a party.
It's at the Cupcake Royale in Ballard on Saturday, August 23, from 6-9 pm. Cupcake Royale will also be unveiling a brand new flavor of cupcakes that very day. More details are here.
1 imaginary liz said on August 6, 2008
I got a sugar rush just clicking through to the cakey websites. Mmm.... (!)
2 Imaginary Shrie said on August 6, 2008
OMG I just perused the Cupcakes Take the Cake site and went to a link for Alibeth Cakes. GOD. I now need a cupcake like my life depended on it.
3 Dylan said on August 8, 2008
i will be eager to claim this as my territory. totally all over the cupcake craze.


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Price Info | View Cart | Monthly Special | What's New
Sound Effects, Royalty Free Music & Production Elements
The Sound Effects and Ambience of the AMERICAN WEST... When the West was young and life was simple, when the sounds of a crackling campfire or a lone cowboy whistle could cut through the cool morning air, a young boy and future sound recordist named Burtis Bills listened. And learned. Bills noticed the sounds of a steam locomotive passing through the depot west of town on a cold, rainy night. He loved it all -- from rails clinking and clacking, to the hollow whistle blaring. But when the new trains moved in and changed the sounds of his small town, he grew nostalgic. He wanted to capture those sounds: the ones that reminded him most of the Old West as he remembered it.
Now, for the first time ever, the sounds of Burtis Bill's Wild West are available to you. Originally digitally recorded on 4 CDs, this library is currently available as a Download. Travel with Bill through the wild western frontier of Colorado, Utah, New Mexico, Arizona, Nevada and Wyoming as he captures the sounds of the untamable frontier.
Download the Burtis Bills' Sounds of the American West File Listing to see the complete contents of this package.
© The Hollywood Edge
241 Sound Effects
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$125 US Regular Price


text: Jim Phillips / TSM / Grant recipients at Bristol County Savings Bank Local Bank Delivers $40,000 To Non-Profits By Jim Phillips April 24, 2014 Bristol County Savings Bank is again coming to the assistance of non-profit organizations on the Southcoast. A ceremony was held Thursday at the bank's Ashley Boulevard branch, where bank President Patrick Murray handed out a total of $40,000 to seven area non-profits... Read More|Comment Category: Articles, Southcoast News Tags: Armand Marchand, Ashley Boulevard, Bristol County Savings Bank, Nativity Prep School, New Bedford Festivaql Theatre, non-profit organizations Send to a friend! Share on Facebook Share on Twitter Pin it! Reddit This! Share on Tumblr!


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HOPKINS COUNTY, Ky. - Carlos R. LeDee, Sr., 64 of Dawson Springs, Ky. passed away on Tuesday, June 25, 2013 at his home. He was born September 23, 1948 to Carlos LeDee and Virginia Morales LeDee.
He attended Christ the King Catholic Church in Madisonville, Ky.
He was preceded in death by his father and a granddaughter Stephanie LeDee..
He is survived by his mother Virginia Morales of Puerto Rico, his wife Tammy Thompson LeDee of Dawson Springs. Two sons Carlos LeDee, Jr. (Cindy) of Detroit, Mich. And Steve LeDee of Detroit, Mich. One daughter Donna Blakemore of Detroit, Mich. Three grandchildren Ashley LeDee (Antonio Lucia), Mariah LeDee and Cody Deason. Two great grandchildren Adilynn Mare Lucia and Zalee Justine Flores.
Funeral Services will be held at Reid-Walters Funeral Home in Earlington, Ky. on Saturday June 29, 2013 at 2:00 PM, with visitation from 11:00 A.M. until service time. With Father Suneesh Matthew officiating.
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The Art of Memoir with Rebecca WalkerMaui June 25-July 2, 2016
Feedback: You Said
"I can't even begin to express how much I loved this workshop. The revelations I gained along the way were priceless. Experiences like these come along once in a lifetime. Rebecca Walker is phenomenal." –Petrina Khashoggi
"I process experiences slowly and am now realizing the deep impact of Maui, the workshop and Rebecca's insights and teachings. Her talent is beyond recognition and I'm forever grateful." –Lia Longworthy
"This will change your life. I have never been happier. Rebecca is masterful in the way she leads this workshop. I left loving the writer that dwells inside me." –Candida Alvarez
"Rebecca Walker is a fearless and compassionate teacher. The AOM workshop provides an astonishing amount of information and coaching in one intense week. Rebecca feels for a pulse and, finding it faintly beating, draws your attention to it, helps you recognize its rhythm, and then teaches you how to write the story of your heart. I left inspired and emboldened!" –Porter Merriman
"The workshop was wonderful! Rebecca is a very special person. She immediately put all of us at ease and created a nurturing and non-judgmental space. I slipped into it like a warm bath. I feel rejuvenated and invigorated." –Mikkel Aaland
"Rebecca's workshop was one of the best creative experiences of my life: a real deep dive into what makes great writing. The commitment and love she has for writers and the process is beautifully evident. Her insights and advice were masterful." –Quddus Philippe
"Rebecca really, really listened, and really, really taught. Both were instrumental to my growth. I have never learned so much about writing and myself in such a short time."–Janice Hill
"If I had to use one word to describe Rebecca's workshop it would be "seismic."It was like an earthquake. You think you know the full magnitude while it's happening, but it's the aftershocks that get your attention. The highest compliment I can pay to Rebecca is that when my schedule permits I will take her workshop again to be in the company of her brilliance, honesty, nurturing spirit." –Juan Gaddis
"Rebecca's workshop is deep, transformative, inspirational, and pragmatic." –Marnie Matsuda
"Rebecca Walker's class exceeded all my expectations. Walker is so wicked smart and personable that I never wanted to leave! She truly holds space for you and your voice. Her suggestions and gentle nudges towards the truth were invaluable. Take this class. You will forever be grateful." –Tia Monteaux Walls
"I can easily say that studying with Rebecca Walker was a life-changing experience. She is one of the best listeners I have ever encountered. She sits, totally open and without judgment and assists you in taking your work to a new level by being direct and real. Alongside my creative catharsis I received very useful guidance about the business of getting published." –Katie Kraft
"I found Rebecca Walker's workshop invaluable. Her presence, respect and generosity are unparalleled." –Maribeth Thiesen
"I love Rebecca Walker! She is an extraordinary woman and writing coach. With her gentle cadence and dulcet tones, she enveloped our group in a safe and loving caress, tempered with tender, yet firm, nudging toward getting our words on the page. With Rebecca as my guide, I went from thinking I was no writer at all to seeing and KNOWING that I actually, indeed, am. She helped me find my voice and lay claim to it. Super cool." –Mia Klein
"I came to Maui feeling unsure about my commitment to my project and insecure about sharing my work with a group of strangers. Rebecca created an extraordinarily supportive and safe atmosphere to share and discuss work, which opened the group to engaging and intensely challenging critique. Her patient and generous guidance gave me a new sense of confidence in my voice, helped me to find a structure for my work, and inspired a strong commitment to bring my project to completion." –Heather Sparks
"Rebecca Walker's workshop is a powerful experience. If you are ready to learn the skills necessary to navigate the literary landscape, Rebecca will skillfully and gracefully take you on an intimate, insightful journey– a week long escape from reality with a book you can't put down." –Judith Carroll
"Rebecca's Maui workshop was AMAZING! The thoughtfulness and expertise shared was of a level I've never experienced before at a writer's workshop. The five day workshop in Maui was the most informative and rewarding experience I've had working on my craft."-Denny Bryce
"As an American expatriate living in the Netherlands, Rebecca Walker's workshop gave me the tools to grow and to thrive as a creative spirit. Rebecca's techniques gave me the foundation to structure my memoir in an effective manner. The workshop continues to influence me, guiding me as I work towards the next level of writing my memoir."–Pamela Armstrong de Vreeze
"Rebecca Walker has an uncanny ability to see what each piece of writing wants to be and the rare capacity to communicate this vision to its author.She's dedicated to bringing to new works of art into the world–a writer's dream."–Matt Fitzgerald
"The Art of Memoir workshop allowed my creativity to flow in a way I had never experienced before. I came with a sense of self-doubt and left feeling supported. Rebecca is a phenomenal and wise facilitator. I deeply appreciate the raw yet loving approach she brings to the table, and her ability to hone in on the deepest passions of each participant. I walked away from the workshop with a sense of understanding and clarity that I don't feel I would have found otherwise. I am so very grateful to have had the opportunity to participate, and I look forward to seeing my fellow participants get published!"–Haley Rabago
"Like a fierce dakini,Rebecca Walker dives into your work, cutting away what isn't necessary. Her editing style is not for the meek, but in the end, she is able to uncover your jewel. After making revisions based on Rebecca's feedback, my manuscript is being considered by a prominent NY agency and two other agents have asked for sample chapters." –Michelle O'neill
"I arrived in Thailand for 10 days with Rebecca. Our group discussions were guided by calmness, thought, precision, rationality, and technique-and silence, occasionally, where we could consider and reflect. We cruised deliberately and smoothly through our own lives as writers, on Rebecca's invincible spaceship– the craft of memoir and the vehicle of language." –Tanya Gupta
"Before I attended the Writers Conference, I'd read and come to admire both of Rebecca's memoirs. During the workshop, I was impressed with her insights and the nurturing way her criticism was offered. I was delighted when she agreed to read my novel, which has now been through a thorough revision and is almost ready to submit to agents. Rebecca's help has been crucial. It is very likely that she has saved me years of frustration and pain."–Carol Dussere
"I feel very, very blessed to have had an opportunity to work with Rebecca Walker. After the first day of the workshop I turned to my one of my peers and said, "I think my life as a writer will change after this week's workshop." She responded, "I think mine already has." I'm not trying to be melodramatic, but Rebecca set a tone during the week that allowed us to reveal our depths as memoirists. I feel like I take myself and the material I am working on much more seriously after a week in her workshop." –Beth Newberry
"What an amazing experience it was taking Rebecca's memoir class. I was so impressed with the way Rebecca reviewed the work, she was so caring and sensitive, yet at the same time provided motivation and thoughtful guidance. It was one of the best experiences I've had with a writing teacher. It wasn't just the advice Rebecca gave about writing–what made the course and our one-on-one session so unique was how Rebecca looks at the craft itself; the spiritual approach to writing that helped us to self-discovery." –-Loretta Worters
"Rebecca's workshop is intense. We spent our days discussing individual works and the craft of writing. In the evenings, we had reading and writing assignments to prepare us for the next day. The prompts Rebecca gave us each afternoon were soul and thought provoking. I learned a lot about myself, the nuances of writing, and most important, left with the confidence that I can indeed complete my book." –Jo Ann Kochner
"This was by far the best workshop I've attended. I am convinced Rebecca set the tone for the workshop: an open, academic, place of trust. I so appreciate how she encouraged us to go deeper, to uncover those suppressed parts of ourselves. This was a risk-taking workshop, one which was wholly successful." –Judy Shearer
"The leadership was the best I've had in an MFA workshop. When I think about what Rebecca did (or didn't) do to effect the workshop, I believe it was her ability to "zero in" on the heart of each piece -its strengths and weaknesses- that made all the difference."–Glenny Brock
"I'm forever indebted to Rebecca for her guidance and support of my memoir. She was prompt, focused and direct in her recommendations, allowing me to wrap my brain around the 80,000 word manuscript. In the end, I had a more focused, accessible book that was, as my publisher noted in his contract offer six months later, "…crystal clear and powerful." Thanks, Rebecca!" –Warren Read


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Minor League Notebook: Simi Valley graduate Brent Keys plays through hamstring issues
Brent Keys (Simi Valley) felt the first twinge as a junior in high school. He could have never imagined it would become such a chronic problem.
Keys, 22, has been battling hamstring troubles throughout his minor league baseball career.
He missed the first month of this season for the Single-A Advanced Jupiter (Fla.) Hammerheads with a left hamstring injury.
Despite visiting various doctors and physical therapists, Keys can't seem to find a solution to the constant tightness in the back of his legs.
"Some people say it's a muscle imbalance like my quads are too strong for my hamstrings or vice versa. Others say my running form is poor," Keys said. "It's not something you can pinpoint, and that is part of what makes it so frustrating. It's just one of those things I will have to battle and deal with my entire career."
There is no question Keys can be highly effective when he's on the field and not the disabled list.
Since entering the lineup, the center fielder is batting .329 with 48 hits and 18 runs scored in 36 games for the Hammerheads.
Last year, the 6-foot-1, 210-pound Keys won the South Atlantic League batting title while playing for Single-A Greensboro (N.C.) despite two stints on the DL.
"My focus as a leadoff hitter is doing whatever I can to get on base and create scoring opportunities," said Keys, the Miami Marlins' 20th-ranked prospect. "I want to put together good at-bats and try to get some runs to help us win games. I am just sticking to my game and knowing what kind of ballplayer I am and not varying from it."
Keys does as much as possible to ward off his hamstring problems. He takes care of his body, tries to play smart and listens to the trainers.
But the potential for another injury is never far from his mind.
"When you have pulled your hamstring six different times, it's kind of implanted in your head," Keys said. "I am always thinking about it, and I always have tightness in my hamstrings during games to remind me. I'm always stretching in the outfield to stay loose."
Because of his history, Keys hasn't set any major statistical goals this season. His biggest priority is just staying healthy and on the field.
He doesn't want his professional baseball aspirations hamstrung by his hamstrings.
"Obviously I probably would be at a little higher level than I am without all the injuries and time I've missed," Keys said. "But I can't complain. I am just happy to be playing baseball and doing what I love to do each and every day."
Around the diamond
Andrew Lambo (Newbury Park) was promoted to Triple-A last week, and wasted no time making his presence felt. Lambo hit a walk-off solo home run in the 13th inning to give the Indianapolis Indians a 9-8 victory over the Norfolk Tides. Before his promotion, Lambo was leading the Eastern League in home runs with 14 at Double-A Altoona. Pitcher C.J. Fick (Newbury Park) was released by the Houston Astros last Wednesday and signed a minor league contract with the Colorado Rockies on Thursday. Fick has been assigned to the Triple-A Colorado Sky Sox. Fick had a 5.23 ERA with 13 strikeouts and 13 walks in 20.2 innings for the Triple-A Oklahoma City RedHawks before being released by the Astros. Third baseman Jonathan Meyer (Simi Valley) is batting .264 with six home runs and 35 RBIs for the Double-A Corpus Christi Hooks. After batting .165 in April, Meyer batted .321 in May and is batting .318 so far in June. Left-hander Sean Gilmartin, a Moorpark resident, has hit a rough patch for the Triple-A Gwinnet Braves. Gilmartin is 0-2 in June with a 12.10 ERA. In his last outing, Gilmartin gave up nine earned runs on nine hits in 3.2 innings. On the season, Gilmartin is 3-6 with a 5.40 ERA, 45 strikeouts and 27 walks.
Promo of the week
The Myrtle Beach Pelicans held "Reverse the Curse" night last Thursday to help break out of a losing slump and improve the bad weather. The team asked fans to come to the ballpark dressed as their favorite superhero and held a pregame ceremony featuring religious leaders giving their blessings to the team. More important, the team raised money for Oklahoma tornado victims throughout the game.
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