In implant dentistry, three-dimensional (3D) imaging can be realised by dental cone beam computed tomography (CBCT), offering volumetric data on jaw bones and teeth with relatively low radiation ...doses and costs. The latter may explain why the market has been steadily growing since the first dental CBCT system appeared two decades ago. More than 85 different CBCT devices are currently available and this exponential growth has created a gap between scientific evidence and existing CBCT machines. Indeed, research for one CBCT machine cannot be automatically applied to other systems.
Supported by a narrative review, recommendations for justified and optimized CBCT imaging in oral implant dentistry are provided.
The huge range in dose and diagnostic image quality requires further optimization and justification prior to clinical use. Yet, indications in implant dentistry may go beyond diagnostics. In fact, the inherent 3D datasets may further allow surgical planning and transfer to surgery via 3D printing or navigation. Nonetheless, effective radiation doses of distinct dental CBCT machines and protocols may largely vary with equivalent doses ranging between 2 to 200 panoramic radiographs, even for similar indications. Likewise, such variation is also noticed for diagnostic image quality, which reveals a massive variability amongst CBCT technologies and exposure protocols. For anatomical model making, the so-called segmentation accuracy may reach up to 200 μm, but considering wide variations in machine performance, larger inaccuracies may apply. This also holds true for linear measures, with accuracies of 200 μm being feasible, while sometimes fivefold inaccuracy levels may be reached. Diagnostic image quality may also be dramatically hampered by patient factors, such as motion and metal artefacts. Apart from radiodiagnostic possibilities, CBCT may offer a huge therapeutic potential, related to surgical guides and further prosthetic rehabilitation. Those additional opportunities may surely clarify part of the success of using CBCT for presurgical implant planning and its transfer to surgery and prosthetic solutions.
Hence, dental CBCT could be justified for presurgical diagnosis, preoperative planning and peroperative transfer for oral implant rehabilitation, whilst striving for optimisation of CBCT based machine-dependent, patient-specific and indication-oriented variables.
Diagnostic radiology is an essential component of treatment planning in the field of implant dentistry. This narrative review will present current concepts for the use of cone beam computed ...tomography imaging, before and after implant placement, in daily clinical practice and research. Guidelines for the selection of three‐dimensional imaging will be discussed, and limitations will be highlighted. Current concepts of radiation dose optimization, including novel imaging modalities using low‐dose protocols, will be presented. For preoperative cross‐sectional imaging, data are still not available which demonstrate that cone beam computed tomography results in fewer intraoperative complications such as nerve damage or bleeding incidents, or that implants inserted using preoperative cone beam computed tomography data sets for planning purposes will exhibit higher survival or success rates. The use of cone beam computed tomography following the insertion of dental implants should be restricted to specific postoperative complications, such as damage of neurovascular structures or postoperative infections in relation to the maxillary sinus. Regarding peri‐implantitis, the diagnosis and severity of the disease should be evaluated primarily based on clinical parameters and on radiological findings based on periapical radiographs (two dimensional). The use of cone beam computed tomography scans in clinical research might not yield any evident beneficial effect for the patient included. As many of the cone beam computed tomography scans performed for research have no direct therapeutic consequence, dose optimization measures should be implemented by using appropriate exposure parameters and by reducing the field of view to the actual region of interest.
To investigate the current clinical applications and diagnostic performance of artificial intelligence (AI) in dental and maxillofacial radiology (DMFR).
Studies using applications related to DMFR to ...develop or implement AI models were sought by searching five electronic databases and four selected core journals in the field of DMFR. The customized assessment criteria based on QUADAS-2 were adapted for quality analysis of the studies included.
The initial electronic search yielded 1862 titles, and 50 studies were eventually included. Most studies focused on AI applications for an automated localization of cephalometric landmarks, diagnosis of osteoporosis, classification/segmentation of maxillofacial cysts and/or tumors, and identification of periodontitis/periapical disease. The performance of AI models varies among different algorithms.
The AI models proposed in the studies included exhibited wide clinical applications in DMFR. Nevertheless, it is still necessary to further verify the reliability and applicability of the AI models prior to transferring these models into clinical practice.
Roux-en-Y gastric bypass (RYGB) has become a prominent therapeutic option for long-term treatment of morbid obesity and type 2 diabetes mellitus (T2D). Cross talk and pathogenetic consequences of ...RYGB-induced profound effects on metabolism and gut microbiome are poorly understood. The aim of the present study therefore was to characterize intra-individual changes of gut microbial composition before and 3 months after RYGB by metagenomic sequencing in morbidly obese patients (body mass index (BMI)>40 kg m(-)(2)) with T2D. Subsequently, metagenomic data were correlated with clinical indices. Based on gene relative abundance profile, 1061 species, 729 genera, 44 phyla and 5127 KO (KEGG Orthology) were identified. Despite high diversity, bacteria could mostly be assigned to seven bacterial divisions. The overall metagenomic RYGB-induced shift was characterized by a reduction of Firmicutes and Bacteroidetes and an increase of Proteobacteria. Twenty-two microbial species and 11 genera were significantly altered by RYGB. Using principal component analysis, highly correlated species were assembled into two common components. Component 1 consisted of species that were mainly associated with BMI and C-reactive protein. This component was characterized by increased numbers of Proteobacterium Enterobacter cancerogenus and decreased Firmicutes Faecalibacterium prausnitzii and Coprococcus comes. Functional analysis of carbohydrate metabolism by KO revealed significant effects in 13 KOs assigned to phosphotransferase system. Spearmen's Rank correlation indicated an association of 10 species with plasma total- or low-density lipoprotein cholesterol, and 5 species with triglycerides. F. prausnitzii was directly correlated to fasting blood glucose. This is the first clinical demonstration of a profound and specific intra-individual modification of gut microbial composition by full metagenomic sequencing. A clear correlation exists of microbiome composition and gene function with an improvement in metabolic and inflammatory parameters. This will allow to develop new diagnostic and therapeutic strategies based on metagenomic sequencing of the human gut microbiome.
Key pointsProvides a definition of the terms artificial intelligence (AI) and personalised dental medicine.Highlights currents fields of use of AI in dental medicine.Highlights potential risks of big ...data use in the context of AI and P4 dentistry.Tries to take a look into the crystal ball regarding the future developments of AI and P4 dental medicine.
We tested a newly described molecular memory system, CCR5 signaling, for its role in recovery after stroke and traumatic brain injury (TBI). CCR5 is uniquely expressed in cortical neurons after ...stroke. Post-stroke neuronal knockdown of CCR5 in pre-motor cortex leads to early recovery of motor control. Recovery is associated with preservation of dendritic spines, new patterns of cortical projections to contralateral pre-motor cortex, and upregulation of CREB and DLK signaling. Administration of a clinically utilized FDA-approved CCR5 antagonist, devised for HIV treatment, produces similar effects on motor recovery post stroke and cognitive decline post TBI. Finally, in a large clinical cohort of stroke patients, carriers for a naturally occurring loss-of-function mutation in CCR5 (CCR5-Δ32) exhibited greater recovery of neurological impairments and cognitive function. In summary, CCR5 is a translational target for neural repair in stroke and TBI and the first reported gene associated with enhanced recovery in human stroke.
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•CCR5 is differentially upregulated in neurons after stroke•Knockdown of CCR5 induces motor recovery after stroke and improves cognition after TBI•Treatment with an FDA-approved drug, maraviroc induces recovery after stroke and TBI•Human carriers for CCR5delta32 have better outcomes after stroke
Genetic and small molecule-based perturbation of CCR5 promotes functional recovery from stroke and traumatic brain injury.
In a follow-up to a 1-year study involving patients who had a TIA or minor stroke, the rate of cardiovascular events including stroke was 6.4% in the first year and 6.4% in the second through fifth ...years.
Parkinson's disease or parkinsonism have been described after infections by viruses, such as influenza A, Epstein-Barr virus, varicella zoster, hepatitis C virus, HIV, Japanese encephalitis virus, or ...West Nile virus.1 We report a patient with probable Parkinson's disease, who was diagnosed after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Because of the worsening of tremor in his right extremities, in a follow-up visit on June 29, biperiden was added at a dose of 2 mg daily, and increased to 4 mg daily after 1 week, which resulted in improvement of the tremor. Other researchers have proposed the so-called multiple hit hypothesis, by which the combination of toxic stress and an inhibition of neuroprotective responses can lead to neuronal death.4 Parkinson's disease is often preceded by anosmia, which is a common feature of SARS-CoV-2 infection.5 Immune activation in the olfactory system might eventually lead to the misfolding of α-synuclein and the development of Parkinson's disease.6 This mechanism is supported by post-mortem studies, showing increased levels of TNF,7 IL1, and IL6.8 Moreover, patients with Parkinson's disease had an elevated CSF antibody response to seasonal coronaviruses, compared with age-matched healthy controls.9 In Ashkenazi-Jewish people with Parkinson's disease, about a third are carriers of either a GBA or a LRRK2 mutation.10 A genetic analysis for these mutations and 62 other mutations associated with the disease was negative and our patient had no previous family history of Parkinson's disease.
We remember when things change. Particularly salient are experiences where there is a change in rewards, eliciting reward prediction errors (RPEs). How do RPEs influence our memory of those ...experiences? One idea is that this signal directly enhances the encoding of memory. Another, not mutually exclusive, idea is that the RPE signals a deeper change in the environment, leading to the mnemonic separation of subsequent experiences from what came before, thereby creating a new latent context and a more separate memory trace. We tested this in four experiments where participants learned to predict rewards associated with a series of trial-unique images. High-magnitude RPEs indicated a change in the underlying distribution of rewards. To test whether these large RPEs created a new latent context, we first assessed recognition priming for sequential pairs that included a high-RPE event or not (Exp. 1: n = 27 & Exp. 2: n = 83). We found evidence of recognition priming for the high-RPE event, indicating that the high-RPE event is bound to its predecessor in memory. Given that high-RPE events are themselves preferentially remembered (Rouhani, Norman, & Niv, 2018), we next tested whether there was an event boundary across a high-RPE event (i.e., excluding the high-RPE event itself; Exp. 3: n = 85). Here, sequential pairs across a high RPE no longer showed recognition priming whereas pairs within the same latent reward state did, providing initial evidence for an RPE-modulated event boundary. We then investigated whether RPE event boundaries disrupt temporal memory by asking participants to order and estimate the distance between two events that had either included a high-RPE event between them or not (Exp. 4). We found (n = 49) and replicated (n = 77) worse sequence memory for events across a high RPE. In line with our recognition priming results, we did not find sequence memory to be impaired between the high-RPE event and its predecessor, but instead found worse sequence memory for pairs across a high-RPE event. Moreover, greater distance between events at encoding led to better sequence memory for events across a low-RPE event, but not a high-RPE event, suggesting separate mechanisms for the temporal ordering of events within versus across a latent reward context. Altogether, these findings demonstrate that high-RPE events are both more strongly encoded, show intact links with their predecessor, and act as event boundaries that interrupt the sequential integration of events. We captured these effects in a variant of the Context Maintenance and Retrieval model (CMR; Polyn, Norman, & Kahana, 2009), modified to incorporate RPEs into the encoding process.
•Reward prediction errors (RPEs) create event boundaries in memory by interfering with the integration of events across them•High-RPE events are better remembered, show intact links with their predecessors, yet interrupt the structure of memories•We developed a variant of the Context Maintenance and Retrieval model (Polyn et al., 2009) to simulate our memory results
We provide evidence that decisions are made by consulting memories for individual past experiences, and that this process can be biased in favour of past choices using incidental reminders. First, in ...a standard rewarded choice task, we show that a model that estimates value at decision-time using individual samples of past outcomes fits choices and decision-related neural activity better than a canonical incremental learning model. In a second experiment, we bias this sampling process by incidentally reminding participants of individual past decisions. The next decision after a reminder shows a strong influence of the action taken and value received on the reminded trial. These results provide new empirical support for a decision architecture that relies on samples of individual past choice episodes rather than incrementally averaged rewards in evaluating options and has suggestive implications for the underlying cognitive and neural mechanisms.
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