Care after premenopausal risk-reducing salpingo-oophorectomy in high-risk women: Scoping review and international consensus recommendations

Women at high inherited risk of ovarian cancer are offered risk-reducing salpingo-oophorectomy (RRSO) from age 35 to 45 years. Although potentially life-saving, RRSO may induce symptoms that negatively affect quality of life and impair long-term health. Clinical care following RRSO is often suboptimal. This scoping review describes how RRSO affects short- and long-term health and provides evidence-based international consensus recommendations for care from preoperative counselling to long-term disease prevention. This includes the efficacy and safety of hormonal and non-hormonal treatments for vasomotor symptoms, sleep disturbance and sexual dysfunction and effective approaches to prevent bone and cardiovascular disease

Explanation and elaboration of the Standards for UNiversal reporting of patient Decision Aid Evaluations (SUNDAE) guidelines: examples of reporting SUNDAE items from patient decision aid evaluation literature

This Explanation and Elaboration (E&E) article expands on the 26 items in the Standards for UNiversal reporting of Decision Aid Evaluations (SUNDAE) guidelines. The E&E provides a rationale for each item and includes examples for how each item has been reported in published papers evaluating patient decision aids. The Explanation and Elaboration focuses on items key to reporting studies evaluating patient decision aids and is intended to be illustrative rather than restrictive. Authors and reviewers may wish to use the Explanation and Elaboration broadly to inform structuring of patient decision aid evaluation reports, or use it as a reference to obtain details about how to report individual Checklist items

Searching for early breast cancer biomarkers by serum protein profiling of pre-diagnostic serum; a nested case-control study

<p>Abstract</p> <p>Background</p> <p>Serum protein profiles have been investigated frequently to discover early biomarkers for breast cancer. So far, these studies used biological samples collected <it>at </it>or <it>after </it>diagnosis. This may limit these studies' value in the search for cancer biomarkers because of the often advanced tumor stage, and consequently risk of reverse causality. We present for the first time pre-diagnostic serum protein profiles in relation to breast cancer, using the Prospect-EPIC (European Prospective Investigation into Cancer and nutrition) cohort.</p> <p>Methods</p> <p>In a nested case-control design we compared 68 women diagnosed with breast cancer within three years after enrollment, with 68 matched controls for differences in serum protein profiles. All samples were analyzed with SELDI-TOF MS (surface enhanced laser desorption/ionization time-of-flight mass spectrometry). In a subset of 20 case-control pairs, the serum proteome was identified and relatively quantified using isobaric Tags for Relative and Absolute Quantification (iTRAQ) and online two-dimensional nano-liquid chromatography coupled with tandem MS (2D-nanoLC-MS/MS).</p> <p>Results</p> <p>Two SELDI-TOF MS peaks with m/z 3323 and 8939, which probably represent doubly charged apolipoprotein C-I and C3a des-arginine anaphylatoxin (C3a_desArg), were higher in pre-diagnostic breast cancer serum (p = 0.02 and p = 0.06, respectively). With 2D-nanoLC-MS/MS, afamin, apolipoprotein E and isoform 1 of inter-alpha trypsin inhibitor heavy chain H4 (ITIH4) were found to be higher in pre-diagnostic breast cancer (p < 0.05), while alpha-2-macroglobulin and ceruloplasmin were lower (p < 0.05). C3a_desArgand ITIH4 have previously been related to the presence of symptomatic and/or mammographically detectable breast cancer.</p> <p>Conclusions</p> <p>We show that serum protein profiles are already altered up to three years before breast cancer detection.</p

Acoustic-Prosodic Entrainment in Human-Human and Human-Computer Dialogue

Entrainment (sometimes called adaptation or alignment) is the tendency of human speakers to adapt to or imitate characteristics of their interlocutors' behavior. This work focuses on entrainment on acoustic-prosodic features. Acoustic-prosodic entrainment has been extensively studied but is not well understood. In particular, it is difficult to compare the results of different studies, since entrainment is usually measured in different ways, reflect- ing disparate conceptualizations of the phenomenon. In the first part of this thesis, we look for evidence of entrainment on a variety of acoustic-prosodic features according to various conceptualizations, and show that human speakers of both Standard American English and Mandarin Chinese entrain to each other globally and locally, in synchrony, and that this entrainment can be constant or convergent. We explore the relationship between entrainment and gender and show that entrainment on some acoustic-prosodic features is related to social behavior and dialogue coordination. In addition, we show that humans entrain in a novel domain, backchannel-inviting cues, and propose and test a novel hypothesis: that entrainment will be stronger in the case of an outlier feature value. In the second part of the thesis, we describe a method for flexibly and dynamically entraining a TTS voice to multiple acoustic-prosodic features of a user's input utterances, and show in an exploratory study that users prefer an entraining avatar to one that does not entrain, are more likely to ask its advice, and choose more positive adjectives to describe its voice. This work introduces a coherent view of entrainment in both familiar and novel domains. Our results add to the body of knowledge of entrainment in human-human conversations and propose new directions for making use of that knowledge to enhance human-computer interactions

Identifying Speaker State from Multimodal Cues

Automatic identification of speaker state is essential for spoken language understanding, with broad potential in various real-world applications. However, most existing work has focused on recognizing a limited set of emotional states using cues from a single modality. This thesis describes my research that addresses these limitations and challenges associated with speaker state identification by studying a wide range of speaker states, including emotion and sentiment, humor, and charisma, using features from speech, text, and visual modalities. The first part of this thesis focuses on emotion and sentiment recognition in speech. Emotion and sentiment recognition is one of the most studied topics in speaker state identification and has gained increasing attention in speech research recently, with extensive emotional speech models and datasets published every year. However, most work focuses only on recognizing a set of discrete emotions in high-resource languages such as English, while in real-life conversations, emotion is changing continuously and exists in all spoken languages. To address the mismatch, we propose a deep neural network model to recognize continuous emotion by combining inputs from raw waveform signals and spectrograms. Experimental results on two datasets show that the proposed model achieves state-of-the-art results by exploiting both waveforms and spectrograms as input. Due to the higher number of existing textual sentiment models than speech models in low-resource languages, we also propose a method to bootstrap sentiment labels from text transcripts and use these labels to train a sentiment classifier in speech. Utilizing the speaker state information shared across modalities, we extend speech sentiment recognition from high-resource languages to low-resource languages. Moreover, using the natural verse-level alignment in the audio Bibles across different languages, we also explore cross-lingual and cross-modality sentiment transfer. In the second part of the thesis, we focus on recognizing humor, whose expression is related to emotion and sentiment but has very different characteristics. Unlike emotion and sentiment that can be identified by crowdsourced annotators, humorous expressions are highly individualistic and cultural-specific, making it hard to obtain reliable labels. This results in the lack of data annotated for humor, and thus we propose two different methods to automatically and reliably label humor. First, we develop a framework for generating humor labels on videos, by learning from extensive user-generated comments. We collect and analyze 100 videos, building multimodal humor detection models using speech, text, and visual features, which achieves an F1-score of 0.76. In addition to humorous videos, we also develop another framework for generating humor labels on social media posts, by learning from user reactions to Facebook posts. We collect 785K posts with humor and non-humor scores and build models to detect humor with performance comparable to human labelers. The third part of the thesis focuses on charisma, a commonly found but less studied speaker state with unique challenges -- the definition of charisma varies a lot among perceivers, and the perception of charisma also varies with speakers' and perceivers' different demographic backgrounds. To better understand charisma, we conduct the first gender-balanced study of charismatic speech, including speakers and raters from diverse backgrounds. We collect personality and demographic information from the rater as well as their own speech, and examine individual differences in the perception and production of charismatic speech. We also extend the work to politicians' speech by collecting speaker trait ratings on representative speech segments of politicians and study how the genre, gender, and the rater's political stance influence the charisma ratings of the segments

EXAMINING THE BEHAVIORAL INTENTIONS OF OLDER ADULTS AS VIRTUAL TOURISTS IN THE CONTEXT OF A SECOND LIFE DESTINATION

ABSTRACT Tourism opportunities are being promoted heavily on the web, yet one of the largest and most lucrative markets, older adults are least likely to use the internet. In an effort to explore barriers to and potential acceptance of technology for tourism experiences, this study followed closely ten older adults through a learning process with technology. Qualitative methodology was used to explore in-depth the experience of these older adults being exposed to online virtual world technology for the first time and exploring the process by which technology acceptance takes place. The findings indicate that online virtual world such as Second Life (SL) experiences have a high ease of use, and high perception of usefulness. However, with more immersed experiences, problems do rise due to inauthentic nature of SL. Overall the technology is not hard to learn for older adults, according to the study participants, and they did have a positive experience with the interactive nature of the virtual travel experience. They also saw benefits related to increased access to places that are difficult to reach physically for them. The Tourism industry may benefit from use of SL type technology as a tool to engage potential tourists. This study points to future research to prepare the tourism industry to take full advantage of this new cutting edge interactive technology in order to both market and maximize the tourist experience and increase satisfaction levels

Distributional and Acoustic Characteristics of Filler Particles in German with Consideration of Forensic-Phonetic Aspects

In this study, we investigate the use of the filler particles (FPs) uh, um, hm, as well as glottal FPs and tongue clicks of 100 male native German speakers in a corpus of spontaneous speech. For this purpose, the frequency distribution, FP duration, duration of pauses surrounding FPs, voice quality of FPs, and their vowel quality are investigated in two conditions, namely, normal speech and Lombard speech. Speaker-specific patterns are investigated on the basis of twelve sample speakers. Our results show that tongue clicks and glottal FPs are as common as typically described FPs, and should be a part of disfluency research. Moreover, the frequency of uh, um, and hm decreases in the Lombard condition while the opposite is found for tongue clicks. Furthermore, along with the usual F1 increase, a considerable reduction in vowel space is found in the Lombard condition for the vowels in uh and um. A high degree of within- and between-speaker variation is found on the individual speaker level

Casco Bay Weekly : 30 July 1998

https://digitalcommons.portlandlibrary.com/cbw_1998/1032/thumbnail.jp