Defining the healthy "core microbiome" of oral microbial communities

<p>Abstract</p> <p>Background</p> <p>Most studies examining the commensal human oral microbiome are focused on disease or are limited in methodology. In order to diagnose and treat diseases at an early and reversible stage an in-depth definition of health is indispensible. The aim of this study therefore was to define the healthy oral microbiome using recent advances in sequencing technology (454 pyrosequencing).</p> <p>Results</p> <p>We sampled and sequenced microbiomes from several intraoral niches (dental surfaces, cheek, hard palate, tongue and saliva) in three healthy individuals. Within an individual oral cavity, we found over 3600 unique sequences, over 500 different OTUs or "species-level" phylotypes (sequences that clustered at 3% genetic difference) and 88 - 104 higher taxa (genus or more inclusive taxon). The predominant taxa belonged to Firmicutes (genus <it>Streptococcus</it>, family <it>Veillonellaceae</it>, genus <it>Granulicatella</it>), Proteobacteria (genus <it>Neisseria</it>, <it>Haemophilus</it>), Actinobacteria (genus <it>Corynebacterium</it>, <it>Rothia</it>, <it>Actinomyces</it>), Bacteroidetes (genus <it>Prevotella</it>, <it>Capnocytophaga, Porphyromonas</it>) and Fusobacteria (genus <it>Fusobacterium</it>).</p> <p>Each individual sample harboured on average 266 "species-level" phylotypes (SD 67; range 123 - 326) with cheek samples being the least diverse and the dental samples from approximal surfaces showing the highest diversity. Principal component analysis discriminated the profiles of the samples originating from shedding surfaces (mucosa of tongue, cheek and palate) from the samples that were obtained from solid surfaces (teeth).</p> <p>There was a large overlap in the higher taxa, "species-level" phylotypes and unique sequences among the three microbiomes: 84% of the higher taxa, 75% of the OTUs and 65% of the unique sequences were present in at least two of the three microbiomes. The three individuals shared 1660 of 6315 unique sequences. These 1660 sequences (the "core microbiome") contributed 66% of the reads. The overlapping OTUs contributed to 94% of the reads, while nearly all reads (99.8%) belonged to the shared higher taxa.</p> <p>Conclusions</p> <p>We obtained the first insight into the diversity and uniqueness of individual oral microbiomes at a resolution of next-generation sequencing. We showed that a major proportion of bacterial sequences of unrelated healthy individuals is identical, supporting the concept of a core microbiome at health.</p

Classification of Quantitative Light-Induced Fluorescence Images Using Convolutional Neural Network

Images are an important data source for diagnosis and treatment of oral diseases. The manual classification of images may lead to misdiagnosis or mistreatment due to subjective errors. In this paper an image classification model based on Convolutional Neural Network is applied to Quantitative Light-induced Fluorescence images. The deep neural network outperforms other state of the art shallow classification models in predicting labels derived from three different dental plaque assessment scores. The model directly benefits from multi-channel representation of the images resulting in improved performance when, besides the Red colour channel, additional Green and Blue colour channels are used.Comment: Full version of ICANN 2017 submissio

Online treatment of persistent complex bereavement disorder, posttraumatic stress disorder, and depression symptoms in people who lost loved ones during the COVID-19 pandemic:study protocol for a randomized controlled trial and a controlled trial

Background: Losing a loved one during the COVID-19 pandemic is a potentially traumatic loss that may result in symptoms of persistent complex bereavement disorder (PCBD), posttraumatic stress disorder (PTSD), and depression. To date, grief-specific cognitive-behavioural therapy (CBT) has mostly been delivered through individual face-to-face formats, while studies have shown that online treatment also yields promising results. Offering treatment online is now more than ever relevant during the pan demic and may offer important benefits compared with face-to-face CBT, such as lower costs and higher accessibility. Our expectation is that grief-specific online CBT is effective in reducing PCBD, PTSD, and depression symptoms. Objective: Our aim is to evaluate the short-term and long-term effectiveness of grief-specific online CBT in reducing PCBD, PTSD, and depression symptom-levels for adults who lost a loved one during the COVID-19 pandemic. Method: This study consists of two parts. In part 1, a two-armed (unguided online CBT versus waitlist controls) randomized controlled trial will be conducted. In part 2, a two-armed (guided online CBT versus unguided online CBT) controlled trial will be conducted. Symptoms of PCBD, PTSD, and depression will be assessed via telephone interviews at pre-treatment/pre-waiting period, post-treatment/post-waiting period, and six months post-treatment. Potential participants are people who lost a loved one at least three months earlier during the COVID-19 pandemic with clinically relevant levels of PCBD, PTSD, and/or depression. Analysis of covariance and multilevel modelling will be performed. Discussion: This is one of the first studies examining the effectiveness of online grief-specific CBT. More research is needed before implementing online grief-specific CBT into clinical practice

Care transformation defined by conditions, mechanisms, and outcomes: a systematic literature review

AbstractBackgroundQuality of care is under pressure due to demographic changes (shifting age of the population), epidemiological trends (more chronic diseases) and changes in the external environment (rapid development of technological innovations). Transformation in care is essential to deal with these changes. However, there is no consensus in the literature regarding the definition and factors contributing to care transformation.MethodsThis systematic review systematically searched the scientific databases Scopus, Web of Science and Pubmed until 22 January 2022. We included articles that focused on care transformation from a complex setting and multi-level perspective, with an empirical or theoretical rationale and methodology. Relevant data regarding the interconnection between contextual conditions, mechanism of change and outcomes were analysed using deductive coding. The generic contextual conditions-mechanisms outcome structure (CMO) [54]Pawson &amp; Tilly, 1997) was used as a framework to synthesise the results.ResultsNineteen articles were included. All related articles explain transformation from a complex systems perspective. Four of the 19 articles gave a definition of care transformation. These definitions of care transformation have the following in common: It involves radical and far-reaching change at an organisational and system-wide level, with the aim of improving performance, behaviour, efficiency, and quality of care, both at individual and population level. Relevant contextual conditions were the changing environment, organisational conditions, collaboration, direction of change and sources of funding. Relevant mechanisms for change were collaboration, leadership, interpersonal relationships, engagement, information technology and coordination. The key outcomes of care transformation are Integration of care, patient-centred care, and improvement of quality of care.ConclusionsAn important goal of care transformation is to deliver better quality of care and enable care integration. This study showed that effective collaboration among healthcare providers, supported by transformational leadership, strong interpersonal relationships, and coordination from multiple perspectives, play an important role in facilitating care transformation. Collaboration is an important mechanism for achieving the key outcomes of care transformation. Keywords: transformation, complex systems, collaboration, multi-level perspective, Quality of Healthcare<br/

Traumatic stress, depression, and non-bereavement grief following non-fatal traffic accidents:Symptom patterns and correlates

Non-fatal traffic accidents may give rise to mental health problems, including posttraumatic stress (PTS) and depression. Clinical evidence suggests that victims may also experience grief reactions associated with the sudden changes and losses caused by such accidents. The aim of this study was to examine whether there are unique patterns of symptoms of PTS, depression, and grief among victims of non-fatal traffic accidents. We also investigated associations of emerging symptom patterns with sociodemographic variables and characteristics of the accident, and with transdiagnostic variables, including self-efficacy, difficulties in emotion regulation, and trauma rumination. Participants (N = 328, M(age) = 32.6, SD(age) = 17.5 years, 66% female) completed self-report measures tapping the study variables. Using latent class analysis (including symptoms of PTS, depression, and grief), three classes were identified: a no symptoms class (Class 1; 59.1%), a moderate PTS and grief class (Class 2; 23.1%), and a severe symptoms class (Class 3; 17.7%). Summed symptom scores and functional impairment were lowest in Class 1, higher in Class 2, and highest in Class 3. Psychological variables were similarly ordered with the healthiest scores in Class 1, poorer scores in Class 2, and the worst scores in Class 3. Different sociodemographic and accident related variables differentiated between classes, including age, education, and time since the accident. In a regression including all significant univariate predictors, trauma rumination differentiated Class 2 from Class 1, all three psychological variables differentiated Class 3 from Class 1, and difficulties with emotion regulation and trauma rumination differentiated Class 3 from Class 2. This study demonstrates that most people respond resiliently to non-fatal traffic accident. Yet, approximately one in three victims experiences moderate to severe mental health symptoms. Increasing PTS coincided with similarly increasing grief, indicating that grief may be considered in interventions for victims of traffic accidents. Trauma rumination strongly predicted class membership and appears a critical treatment target to alleviate distress