Candida albicans commensalism in the oral mucosa is favoured by limited virulence and metabolic adaptation.

As part of the human microbiota, the fungus Candida albicans colonizes the oral cavity and other mucosal surfaces of the human body. Commensalism is tightly controlled by complex interactions of the fungus and the host to preclude fungal elimination but also fungal overgrowth and invasion, which can result in disease. As such, defects in antifungal T cell immunity render individuals susceptible to oral thrush due to interrupted immunosurveillance of the oral mucosa. The factors that promote commensalism and ensure persistence of C. albicans in a fully immunocompetent host remain less clear. Using an experimental model of C. albicans oral colonization in mice we explored fungal determinants of commensalism in the oral cavity. Transcript profiling of the oral isolate 101 in the murine tongue tissue revealed a characteristic metabolic profile tailored to the nutrient poor conditions in the stratum corneum of the epithelium where the fungus resides. Metabolic adaptation of isolate 101 was also reflected in enhanced nutrient acquisition when grown on oral mucosa substrates. Persistent colonization of the oral mucosa by C. albicans also correlated inversely with the capacity of the fungus to induce epithelial cell damage and to elicit an inflammatory response. Here we show that these immune evasive properties of isolate 101 are explained by a strong attenuation of a number of virulence genes, including those linked to filamentation. De-repression of the hyphal program by deletion or conditional repression of NRG1 abolished the commensal behaviour of isolate 101, thereby establishing a central role of this factor in the commensal lifestyle of C. albicans in the oral niche of the host.

Aerosol exposure of staff during dental treatments: a model study.

BACKGROUND: Due to exposure to potentially infectious aerosols during treatments, the dental personnel is considered being at high risk for aerosol transmitted diseases like COVID-19. The aim of this study was to evaluate aerosol exposure during different dental treatments as well as the efficacy of dental suction to reduce aerosol spreading. METHODS: Dental powder-jet (PJ; Air-Flow®), a water-cooled dental handpiece with a diamond bur (HP) and water-cooled ultrasonic scaling (US) were used in a simulation head, mounted on a dental unit in various treatment settings. The influence of the use of a small saliva ejector (SE) and high-volume suction (HVS) was evaluated. As a proxy of aerosols, air-born particles (PM10) were detected using a Laser Spectrometer in 30 cm distance from the mouth. As control, background particle counts (BC) were measured before and after experiments. RESULTS: With only SE, integrated aerosol levels [median (Q25/Q75) µg/m3 s] for PJ [91,246 (58,213/118,386) µg/m3 s, p < 0.001, ANOVA] were significantly increased compared to BC [7243 (6501/8407) µg/m3 s], whilst HP [11,119 (7190/17,234) µg/m3 s, p > 0.05] and US [6558 (6002/7066) µg/m3 s; p > 0.05] did not increase aerosol levels significantly. The use of HVS significantly decreased aerosol exposure for PJ [37,170 (29,634/51,719) µg/m3 s; p < 0.01] and HP [5476 (5066/5638) µg/m3 s; p < 0.001] compared to SE only, even reaching lower particle counts than BC levels for HP usage (p < 0.001). CONCLUSIONS: To reduce the exposure to potentially infectious aerosols, HVS should be used during aerosol-forming dental treatments.

Langerin+ DCs regulate innate IL-17 production in the oral mucosa during Candida albicans-mediated infection.

The opportunistic fungal pathogen Candida albicans frequently causes diseases such as oropharyngeal candidiasis (OPC) in immunocompromised individuals. Although it is well appreciated that the cytokine IL-17 is crucial for protective immunity against OPC, the cellular source and the regulation of this cytokine during infection are still a matter of debate. Here, we directly visualized IL-17 production in the tongue of experimentally infected mice, thereby demonstrating that this key cytokine is expressed by three complementary subsets of CD90+ leukocytes: RAG-dependent αß and γδ T cells, as well as RAG-independent ILCs. To determine the regulation of IL-17 production at the onset of OPC, we investigated in detail the myeloid compartment of the tongue and found a heterogeneous and dynamic mononuclear phagocyte (MNP) network in the infected tongue that consists of Zbtb46-Langerin- macrophages, Zbtb46+Langerin+ dendritic cells (DCs) and Ly6C+ inflammatory monocytes. Of those, the Langerin+ DC population stands out by its unique capacity to co-produce the cytokines IL-1ß, IL-6 and IL-23, all of which promote IL-17 induction in response to C. albicans in the oral mucosa. The critical role of Langerin+ DCs for the innate IL-17 response was confirmed by depletion of this cellular subset in vivo, which compromised IL-17 induction during OPC. In conclusion, our work revealed key regulatory factors and their cellular sources of innate IL-17-dependent antifungal immunity in the oral mucosa.

Study protocol for a multicenter randomized controlled trial to compare the efficacy of end-ischemic dual hypothermic oxygenated machine perfusion with static cold storage in preventing non-anastomotic biliary strictures after transplantation of liver grafts donated after circulatory death: DHOPE-DCD trial.

BACKGROUND: The major concern in liver transplantation of grafts from donation after circulatory death (DCD) donors remains the high incidence of non-anastomotic biliary strictures (NAS). Machine perfusion has been proposed as an alternative strategy for organ preservation which reduces ischemia-reperfusion injury (IRI). Experimental studies have shown that dual hypothermic oxygenated machine perfusion (DHOPE) is associated with less IRI, improved hepatocellular function, and better preserved mitochondrial and endothelial function compared to conventional static cold storage (SCS). Moreover, DHOPE was safely applied with promising results in a recently performed phase-1 study. The aim of the current study is to determine the efficacy of DHOPE in reducing the incidence of NAS after DCD liver transplantation. METHODS: This is an international multicenter randomized controlled trial. Adult patients (≥18 yrs. old) undergoing transplantation of a DCD donor liver (Maastricht category III) will be randomized between the intervention and control group. In the intervention group, livers will be subjected to two hours of end-ischemic DHOPE after SCS and before implantation. In the control group, livers will be subjected to care as usual with conventional SCS only. Primary outcome is the incidence of symptomatic NAS diagnosed by a blinded adjudication committee. In all patients, magnetic resonance cholangiography will be obtained at six months after transplantation. DISCUSSION: DHOPE is associated with reduced IRI of the bile ducts. Whether reduced IRI of the bile ducts leads to lower incidence of NAS after DCD liver transplantation can only be examined in a randomized controlled trial. TRIAL REGISTRATION: The trial was registered in Clinicaltrials.gov in September 2015 with the identifier NCT02584283 .

The development of an end-to-end service solution to support lupus patients and improve their experience in clinical trials.

OBJECTIVE: To develop an end-to-end clinical trial service to improve patient experience during trials, reduce the burden of participating in a trial, and increase trial retention. METHODS: A literature search and stakeholder interviews were used to identify current challenges and unmet needs of systemic lupus erythematosus patients and other systemic lupus erythematosus clinical trial stakeholders. The results from the literature search and interviews were used to create a five-phase map describing the current clinical trial experience of all stakeholders. A set of proposed solutions were developed to address the identified unmet needs and challenges. These solutions were presented to trial-experienced patients and study site personnel; any feedback obtained was used to further refine the solutions. RESULTS: Four site personnel and seven patients from three different systemic lupus erythematosus clinical trial sites were interviewed between September 2015 and December 2015. Key unmet needs and challenges were identified at each stage of the clinical trials. At the screening stage, some patients incorrectly thought they were successfully enrolled into the clinical trial. During enrollment, some patients found it difficult to keep fully informed about the trial and were unable to explain the trial process to loved ones. During the trial, patients struggled to prepare for study visits, felt overwhelmed by the trial process, and wanted someone to talk to for support. Clinical trial site personnel reported current key challenges as: delivering trial information clearly and consistently to patients, setting patient expectations, retaining enrolled patients, and providing non-clinical patient support. To address the needs of patients and site personnel, an end-to-end support service was designed, consisting of nine solutions: My Best Choice, My Eligibility, My Lupus Trial Kit, My Lupus Trial Coach, My Appointment Guide, My Clinic Compass, Our Gratitude, Building a Different Network, and My Next Chapter. CONCLUSION: The solutions proposed in this qualitative study may help improve the systemic lupus erythematosus clinical trial experience for patients, potentially helping to increase trial recruitment and retention. The solutions proposed here would also promote positive patient-trial personnel relationships, which may help site personnel identify patients at risk of early withdrawal, while ensuring that the time and resources of site personnel are used efficiently.

Impact of artificial intelligence on dentists' gaze during caries detection: A randomized controlled trial.

OBJECTIVES: We aimed to understand how artificial intelligence (AI) influences dentists by comparing their gaze behavior when using versus not using an AI software to detect primary proximal carious lesions on bitewing radiographs. METHODS: 22 dentists assessed a median of 18 bitewing images resulting in 170 datasets from dentists without AI and 179 datasets from dentists with AI, after excluding data with poor gaze recording quality. We compared time to first fixation, fixation count, average fixation duration, and fixation frequency between both trial groups. Analyses were performed for the entire image and stratified by (1) presence of carious lesions and/or restorations and (2) lesion depth (E1/2: outer/inner enamel; D1-3 outer-inner third of dentin). We also compared the transitional pattern of the dentists' gaze between the trial groups. RESULTS: Median time to first fixation was shorter in all groups of teeth for dentists with AI versus without AI, although p>0.05. Dentists with AI had more fixations (median=68, IQR=31, 116) on teeth with restorations compared to dentists without AI (median=47, IQR=19, 100), p = 0.01. In turn, average fixation duration was longer on teeth with caries for the dentists with AI than those without AI; although p>0.05. The visual search strategy employed by dentists with AI was less systematic with a lower proportion of lateral tooth-wise transitions compared to dentists without AI. CONCLUSIONS: Dentists with AI exhibited more efficient viewing behavior compared to dentists without AI, e.g., lesser time taken to notice caries and/or restorations, more fixations on teeth with restorations, and fixating for shorter durations on teeth without carious lesions and/or restorations. CLINICAL SIGNIFICANCE: Analysis of dentists' gaze patterns while using AI-generated annotations of carious lesions demonstrates how AI influences their data extraction methods for dental images. Such insights can be exploited to improve, and even customize, AI-based diagnostic tools, thus reducing the dentists' extraneous attentional processing and allowing for more thorough examination of other image areas.

Gaze patterns of dentists while evaluating bitewing radiographs.

OBJECTIVES: Understanding dentists' gaze patterns on radiographs may allow to unravel sources of their limited accuracy and develop strategies to mitigate them. We conducted an eye tracking experiment to characterize dentists' scanpaths and thus their gaze patterns when assessing bitewing radiographs to detect primary proximal carious lesions. METHODS: 22 dentists assessed a median of nine bitewing images each, resulting in 170 datasets after excluding data with poor quality of gaze recording. Fixation was defined as an area of attentional focus related to visual stimuli. We calculated time to first fixation, fixation count, average fixation duration, and fixation frequency. Analyses were performed for the entire image and stratified by (1) presence of carious lesions and/or restorations and (2) lesion depth (E1/2: outer/inner enamel; D1-3: outer-inner third of dentin). We also examined the transitional nature of the dentists' gaze. RESULTS: Dentists had more fixations on teeth with lesions and/or restorations (median=138 [interquartile range=87, 204]) than teeth without them (32 [15, 66]), p<0.001. Notably, teeth with lesions had longer fixation durations (407 milliseconds [242, 591]) than those with restorations (289 milliseconds [216, 337]), p<0.001. Time to first fixation was longer for teeth with E1 lesions (17,128 milliseconds [8813, 21,540]) than lesions of other depths (p = 0.049). The highest number of fixations were on teeth with D2 lesions (43 [20, 51]) and lowest on teeth with E1 lesions (5 [1, 37]), p<0.001. Generally, a systematic tooth-by-tooth gaze pattern was observed. CONCLUSIONS: As hypothesized, while visually inspecting bitewing radiographic images, dentists employed a heightened focus on certain image features/areas, relevant to the assigned task. Also, they generally examined the entire image in a systematic tooth-by-tooth pattern.

Cost-effectiveness of AI for caries detection: randomized trial.

OBJECTIVES: We assessed the cost-effectiveness of AI-supported detection of proximal caries in a randomized controlled clustered cross-over superiority trial. METHODS: Twenty-three dentists were sampled to assess 20 bitewings; 10 were randomly evaluated supported by an AI-based software (dentalXrai Pro 1.0.4, dentalXrai Ltd, Berlin, Germany) and the other 10 without AI support. The reference test had been established by four independent experts and an additional review. We evaluated the proportion of true and false positive and negative detections and the treatment decisions assigned to each detection (non-invasive, micro-invasive, invasive). Cost-effectiveness was assessed using a mixed public-private-payer perspective in German healthcare. Using the accuracy and treatment decision data from the trial, a Markov simulation model was populated and posterior permanent teeth in initially 31-years old individuals followed over their lifetime. The model allowed extrapolation from the initial detection and therapy to treatment success, re-treatments and, eventually, tooth loss and replacement, capturing long-term effectiveness (tooth retention) and costs (cumulative in Euro). Costs were estimated using the German public and private fee catalogues. Monte-Carlo microsimulations were used and incremental cost-effectiveness at different willingness-to-pay ceiling thresholds assessed. RESULTS: In the trial, AI-supported detection was significantly more sensitive than detection without AI. However, in the AI group, lesions were more often treated invasively. As a result, AI and no AI showed identical effectiveness (tooth retention for a mean (2.5-97.5%) 49 (48-51) years) and nearly identical costs (AI: 330 (250-409) Euro, no AI: 330 (248-410) Euro). 41% simulations found AI and 43% no AI to be more cost-effective. The resulting cost-effectiveness remained uncertain regardless of a payer's willingness-to-pay. CONCLUSIONS: Higher accuracy of AI did not lead to higher cost-effectiveness, as more invasive treatment approaches generated costs and diminished possible effectiveness advantages. CLINICAL SIGNIFICANCE: The cost-effectiveness of AI could be improved by supporting not only caries detection, but also subsequent management.

Barriers and Enablers for Artificial Intelligence in Dental Diagnostics: A Qualitative Study.

The present study aimed to identify barriers and enablers for the implementation of artificial intelligence (AI) in dental, specifically radiographic, diagnostics. Semi-structured phone interviews with dentists and patients were conducted between the end of May and the end of June 2020 (convenience/snowball sampling). A questionnaire developed along the Theoretical Domains Framework (TDF) and the Capabilities, Opportunities and Motivations influencing Behaviors model (COM-B) was used to guide interviews. Mayring's content analysis was employed to point out barriers and enablers. We identified 36 barriers, conflicting themes or enablers, covering nine of the fourteen domains of the TDF and all three determinants of behavior (COM). Both stakeholders emphasized chances and hopes for AI. A range of enablers for implementing AI in dental diagnostics were identified (e.g., the chance for higher diagnostic accuracy, a reduced workload, more comprehensive reporting and better patient-provider communication). Barriers related to reliance on AI and responsibility for medical decisions, as well as the explainability of AI and the related option to de-bug AI applications, emerged. Decision-makers and industry may want to consider these aspects to foster implementation of AI in dentistry.

Artificial intelligence for caries detection: Randomized trial.

OBJECTIVES: We aimed to assess the impact of an artificial intelligence (AI)-based diagnostic-support software for proximal caries detection on bitewing radiographs. METHODS: A cluster-randomized cross-over controlled trial was conducted. A commercially available software employing a fully convolutional neural network for caries detection (dentalXrai Pro, dentalXrai Ltd.) was randomly employed by 22 dentists, supporting their caries detection on 20 bitewings randomly chosen from a pool of 140 bitewings, with 10 bitewings randomly being supported by AI and 10 not. The reference test had been established by 4 + 1 independent experts in a pixelwise fashion. Caries was subgrouped as enamel, early dentin and advanced dentin caries, and accuracy and treatment decisions for each caries lesion assessed. RESULTS: Dentists with AI showed a significantly higher mean (95% CI) area under the Receiver-Operating-Characteristics curve (0.89; 0.87-0.90) than those without AI (0.85; 0.83-0.86; p<0.05), mainly as their sensitivity was significantly higher (0.81; 0.74-0.87 compared with 0.72; 0.64-0.79; p<0.05) while the specificity was not significantly affected (p>0.05). This increase in sensitivity was found for enamel, but not early or advanced dentin lesions. Higher sensitivity came with an increase in non-invasive, but also invasive treatment decisions (p<0.05). CONCLUSION: AI can increase dentists' diagnostic accuracy but may also increase invasive treatment decisions. CLINICAL SIGNIFICANCE: AI can increase dentists' diagnostic accuracy, mainly via increasing their sensitivity for detecting enamel lesions, but may also increase invasive therapy decisions. Differences in the effects of AI for different dentists should be explored, and dentists should be guided as to which therapy to choose when detecting caries lesions using AI support.

Detecting white spot lesions on dental photography using deep learning: A pilot study.

OBJECTIVES: We aimed to apply deep learning to detect white spot lesions in dental photographs. METHODS: Using 434 photographic images of 51 patients, a dataset of 2781 cropped tooth segments was generated. Pixelwise annotations of sound enamel as well as fluorotic, carious or other types of hypomineralized lesions were generated by experts and assessed by an independent second reviewer. The union of the reviewed annotations were used to segment the hard tissues (region-of-interest, ROI) of each image. SqueezeNet was employed for modelling. We trained models to detect (1) any white spot lesions, (2) fluorotic lesions and (3) other-than-fluorotic lesions. Modeling was performed on both the cropped and the ROI images and using ten-times repeated five-fold cross-validation. Feature visualization was applied to visualize salient areas. RESULTS: Lesion prevalence was 37 %; the majority of lesions (24 %) were fluorotic. None of the metrics differed significantly between the models trained on cropped and ROI imagery (p > 0.05/t-test). Mean accuracies ranged between 0.81-0.84, without significant differences between models trained to detect any, fluorotic or other-than-fluorotic lesions (p > 0.05). Specificities were 0.85-0.86; sensitivities were lower (0.58-0.66). Models to detect any lesions showed positive/negative predictive values (PPV/NPV) between 0.77-0.80, those to detect fluorotic lesions 0.67 (PPV) to 0.86 (NPV), and those to detect other-than-fluorotic lesions 0.46 (PPV) to 0.93 (NPV). Light reflections were the main reason for false positive detections. CONCLUSIONS: Deep learning showed satisfying accuracy to detect white spot lesions, particularly fluorosis. Some models showed limited stability given the small sample available. CLINICAL SIGNIFICANCE: Deep learning is suitable for automated classification of retro- or prospectively collected imagery and may assist practitioners in discriminating white spot lesions. Future studies should expand the scope into more granular multi-class detections on a larger and more generalizable dataset.

The Skin Commensal Yeast Malassezia Triggers a Type 17 Response that Coordinates Anti-fungal Immunity and Exacerbates Skin Inflammation.

Commensal fungi of the mammalian skin, such as those of the genus Malassezia, are associated with atopic dermatitis and other common inflammatory skin disorders. Understanding of the causative relationship between fungal commensalism and disease manifestation remains incomplete. By developing a murine epicutaneous infection model, we found Malassezia spp. selectively induce IL-17 and related cytokines. This response is key in preventing fungal overgrowth on the skin, as disruption of the IL-23-IL-17 axis compromises Malassezia-specific cutaneous immunity. Under conditions of impaired skin integrity, mimicking a hallmark of atopic dermatitis, the presence of Malassezia dramatically aggravates cutaneous inflammation, which again was IL-23 and IL-17 dependent. Consistently, we found a CCR6+ Th17 subset of memory T cells to be Malassezia specific in both healthy individuals and atopic dermatitis patients, whereby the latter showed enhanced frequency of these cells. Thus, the Malassezia-induced type 17 response is pivotal in orchestrating antifungal immunity and in actively promoting skin inflammation.

Neonatal security: it takes a community.

A heightened awareness of infant security issues surfaced in the 1990s, driven by attempted and successful infant abductions. During that time, many hospitals began implementing policies, procedures, and staff training to protect the babies in their care. In addition, high-profile hospitals began investing in infant security systems as a technological aid to bolster security.

Family planning and pregnancy issues for women with systemic inflammatory diseases: patient and physician perspectives.

OBJECTIVES: To identify family planning and pregnancy (FPP) issues for female patients of childbearing age living with a chronic inflammatory disease and to assess whether current clinical practice routinely provides adequate support to alleviate these concerns. SETTING: Multinational survey and an analysis of online patient activity. PARTICIPANTS: Premenopausal women (aged 20-45 years; N=969) were surveyed in the USA, the UK, Germany, France, Italy and Spain. Rheumatologists were surveyed in Germany (N=50), France (N=50), Italy (N=50) and the USA (N=100), and gastroenterologists were also surveyed in the USA (N=100). PRIMARY AND SECONDARY OUTCOME MEASURES: Two online surveys were undertaken to identify FPP issues for physicians and patients. The surveys examined the frequency of dialogue on these topics between physicians and patients, alongside assessment of patient satisfaction regarding these conversations. Online analysis identified key themes for patient discussion outside their doctors' office/clinic/surgery. RESULTS: 32-56% of physicians spontaneously reported having talked about FPP with their female patients of childbearing age. When prompted, the majority of rheumatologists (74-92%) and gastroenterologists (74%) reported having discussed conception/pregnancy with female patients; however, less than half reported consulting their patient's treating general practitioner/gynaecologist about these topics. The majority of patients reported their FPP-related concerns are not adequately addressed/settled during their medical appointments. Furthermore, only 30-40% of patients considered advice/information to be consistent across multiple healthcare professionals. Key online FPP-related patient discussions included disease state, adverse effects, treatment, switch behaviour and wash-out requirements. CONCLUSIONS: Female patients who live with chronic inflammatory disease have important FPP concerns. The majority of patients, however, do not feel that their FPP concerns are adequately addressed in current clinical practice and report that they receive inconsistent advice from the various healthcare professionals who manage different aspects of their care. There is a clear need for provision of up-to-date and consistent information/support to female patients.