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The global outbreak of coronavirus disease 2019 (COVID-19) has raised concerns about the risk of airborne infection during dental treatment. Fasudil Aerosol-generating dental procedures (AGDP) produce droplets and aerosols, but the details of the risks of COVID-19 transmission in AGDP are not well-understood. By discriminating between droplets and aerosols, we devised a method to measure particle size using laser diffraction analysis and evaluated aerosols generated from dental devices for providing a basis for proper infection control procedures. The droplets and aerosols generated from dental devices were characterized by multimodal properties and a wide range of droplet sizes, with the majority of droplets larger than 50 μm. AGDP emitted few aerosols smaller than 5 μm, which are of concern for pulmonary infections due to airborne transmission. In addition, the use of extraoral suction was found to prevent the spread of aerosols from high-speed dental engines. This study suggests that the risk of aerosol infections is considerably limited in regular dental practice and that current standard precautions, such as mainly focusing on protection against droplet and contact infections, are sufficient. While several cases of airborne transmission of COVID-19 in general clinics and emergency hospitals have been reported, cluster outbreaks in dental clinics have not yet been reported, which may indicate that AGDP does not pose a significant threat in contributing to the spread of SARS-CoV-2.Medication-related osteonecrosis of the jaw (MRONJ) is a growing problem without an effective treatment, presenting as necrotic bone sections exposed via lesions in the overlying soft tissue. There is currently a lack of clarity on how the factors involved in MRONJ development and progression contribute to disease prognosis and outcomes. Bisphosphonates (BPs), the most common cause of MRONJ, affect bone remodeling, angiogenesis, infection, inflammation and soft tissue toxicity, all of which contribute to MRONJ development. This article reviews the cellular mechanisms through which BPs contribute to MRONJ pathology, with a focus on the effects on cells of the oral mucosa. BPs have been shown to reduce cell viability, reduce proliferation, and increase apoptosis in oral keratinocytes and fibroblasts. BPs have also been demonstrated to reduce epithelial thickness and prevent epithelial formation in three-dimensional tissue engineered models of the oral mucosa. This combination of factors demonstrates how BPs lead to the reduced wound healing seen in MRONJ and begins to uncover the mechanisms through which these effects occur. The evidence presented here supports identification of targets which can be used to develop novel treatment strategies to promote soft tissue wound healing and restore mucosal coverage of exposed bone in MRONJ.The oral mucosa contains distinct tissue sites with immune niches capable of either immunogenic or tolerogenic responses. However, immune cell compositions within oral mucosal tissues at homeostasis have not been well-characterized in human relevant tissues. Non-human primates (NHP) are a major model for the human immune system and oral anatomy, and therefore improved understanding of NHP oral immune cell populations can provide important insights for studying disease pathologies and developing therapies. Herein, we characterize immune cell types of three sites within the oral cavity (buccal, sublingual, lingual tonsil) sampled by biopsy and cytobrush in pigtail macaques. Tonsil biopsies had more T-cells, dendritic cells (DCs), DC subtypes, and CD4+ T-cells than buccal or sublingual biopsies when normalized by tissue mass. Biopsy proved to collect more immune cells than cytobrushes, however frequencies of CD45+ subpopulations were comparable between methods. Live cells isolated from biopsied tonsils had greater CD45+ leukocyte frequencies (mean 31.6 ± SD 20.4%) than buccal (13.8 ± 4.6%) or sublingual (10.0 ± 5.1%) tissues. T-cells composed more than half of the CD45+ population in sublingual tissue (60.1 ± 9.6%) and the tonsil (54.6 ± 7.5%), but only 31.9 ± 7.2% in buccal samples. CD20+ B-cells composed a greater percentage of CD45+ leukocytes in the tonsil (12.8 ± 9.1%) than buccal (1.2 ± 1.0%) or sublingual tissues (0.8 ± 1.2%). Immune population comparisons are also made between sex and age. These results present an important step for understanding the oral immune environment, oral disease, and site-specific therapy development.Genome editing technologies, including CRISPR/Cas9 and TALEN, are excellent genetic modification techniques and are being proven to be powerful tools not only in the field of basic science but also in the field of crop breeding. Recently, two genome-edited crops targeted for nutritional improvement, high GABA tomatoes and high oleic acid soybeans, have been released to the market. Nutritional improvement in cultivated crops has been a major target of conventional genetic modification technologies as well as classical breeding methods. Mutations created by genome editing are considered to be almost identical to spontaneous genetic mutations because the mutation inducer, the transformed foreign gene, can be completely eliminated from the final genome-edited hosts after causing the mutation. Therefore, genome-edited crops are expected to be relatively easy to supply to the market, unlike GMO crops. On the other hand, due to their technical feature, the main goal of current genome-edited crop creation is often the total or partial disruption of genes rather than gene delivery. Therefore, to obtain the desired trait using genome editing technology, in some cases, a different approach from that of genetic recombination technology may be required. In this mini-review, we will review several nutritional traits in crops that have been considered suitable targets for genome editing, including the two examples mentioned above, and discuss how genome editing technology can be an effective breeding technology for improving nutritional traits in crops.
Personal technology (e.g., smartphones, wearable health devices) has been leveraged extensively for mental health purposes, with upwards of 20,000 mobile applications on the market today and has been considered an important implementation strategy to overcome barriers many people face in accessing mental health care. The main question yet to be addressed is the role consumers feel technology should play in their care. One underserved demographic often ignored in this discussion are people over the age of 60. The population of adults 60 and older is predicted to double by 2,050 signaling a need to address how older adults view technology for their mental health care.

The objective of this study is to better understand why digital mental health tools are not as broadly adopted as predicted, what role people with lived mental health experience feel technology should play in their care and how those results compare across age groups.

In a mixed-methods approach, we analyzed results from a one-time cross-secoups, but preferences for its role in care remain largely administrative and supportive. Future development of digital mental health should reflect these preferences.
Digital mental health is seen as a valuable care management tool across all age groups, but preferences for its role in care remain largely administrative and supportive. Future development of digital mental health should reflect these preferences.Ear related concerns and symptoms represent the leading indication for seeking pediatric healthcare attention. Despite the high incidence of such encounters, the diagnostic process of commonly encountered diseases of the middle and external presents a significant challenge. Much of this challenge stems from the lack of cost effective diagnostic testing, which necessitates the presence or absence of ear pathology to be determined clinically. Research has, however, demonstrated considerable variation among clinicians in their ability to accurately diagnose and consequently manage ear pathology. With recent advances in computer vision and machine learning, there is an increasing interest in helping clinicians to accurately diagnose middle and external ear pathology with computer-aided systems. It has been shown that AI has the capacity to analyze a single clinical image captured during the examination of the ear canal and eardrum from which it can determine the likelihood of a pathognomonic pattern for a specific diagnosis being present. The capture of such an image can, however, be challenging especially to inexperienced clinicians. To help mitigate this technical challenge, we have developed and tested a method using video sequences. The videos were collected using a commercially available otoscope smartphone attachment in an urban, tertiary-care pediatric emergency department. We present a two stage method that first, identifies valid frames by detecting and extracting ear drum patches from the video sequence, and second, performs the proposed shift contrastive anomaly detection (SCAD) to flag the otoscopy video sequences as normal or abnormal. Our method achieves an AUROC of 88.0% on the patient level and also outperforms the average of a group of 25 clinicians in a comparative study, which is the largest of such published to date. We conclude that the presented method achieves a promising first step toward the automated analysis of otoscopy video.In recent years, behavioral markers such as spoken language and lexical preferences have been studied in the early detection of mild cognitive impairment (MCI) using conversations. While the combination of linguistic and acoustic signals have been shown to be effective in detecting MCI, they have generally been restricted to structured conversations in which the interviewee responds to fixed prompts. In this study, we show that linguistic and acoustic features can be combined synergistically to identify MCI in semi-structured conversations. Using conversational data from an on-going clinical trial (Clinicaltrials.gov NCT02871921), we find that the combination of linguistic and acoustic features on semi-structured conversations achieves a mean AUC of 82.7, significantly (p less then 0.01) out-performing linguistic-only (74.9 mean AUC) or acoustic-only (65.0 mean AUC) detections on hold-out data. Additionally, features (linguistic, acoustic and combination) obtained from semi-structured conversations outperform their counterparts obtained from structured weekly conversations in identifying MCI. Some linguistic categories are significantly better at predicting MCI status (e.g., death, home) than others.The COVID-19 pandemic is adversely impacting suicidality at a population level, with consequences resulting from a variety of pandemic-driven disruptions, including social activities and connectedness. This paper uses a single case study design to explore how members of the Reddit r/COVID19_support community create a sense of connectedness among those who have suicidal thoughts due to the pandemic. Data were gathered from posts to the r/COVID19_support subreddit forum from February 2020 through December 2020. The second step of Klonsky and May's (2015) Three-Step Theory (3ST) of suicide, connectedness as a key protective factor, was used as the theoretical framework. This study explored r/COVID19_support's constructed environment, users' dialogical interactions, and the four primary tenets of connectedness as proposed by Klonsky and May - Purpose and Meaning, Relationships, Religiosity, and Employment. Findings demonstrate a deep sense of connectedness for online community members. Relationships and Purpose and Meaning featured as the most salient sources of connectedness within this subreddit, whereas Religiosity was rarely discussed, and Employment was often spoken of in negative terms (i.
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