Artificial Intelligence in Orthodontics: Critical Review.

With increasing digitalization in orthodontics, certain orthodontic manufacturing processes such as the fabrication of indirect bonding trays, aligner production, or wire bending can be automated. However, orthodontic treatment planning and evaluation remains a specialist's task and responsibility. As the prediction of growth in orthodontic patients and response to orthodontic treatment is inherently complex and individual, orthodontists make use of features gathered from longitudinal, multimodal, and standardized orthodontic data sets. Currently, these data sets are used by the orthodontist to make informed, rule-based treatment decisions. In research, artificial intelligence (AI) has been successfully applied to assist orthodontists with the extraction of relevant data from such data sets. Here, AI has been applied for the analysis of clinical imagery, such as automated landmark detection in lateral cephalograms but also for evaluation of intraoral scans or photographic data. Furthermore, AI is applied to help orthodontists with decision support for treatment decisions such as the need for orthognathic surgery or for orthodontic tooth extractions. One major challenge in current AI research in orthodontics is the limited generalizability, as most studies use unicentric data with high risks of bias. Moreover, comparing AI across different studies and tasks is virtually impossible as both outcomes and outcome metrics vary widely, and underlying data sets are not standardized. Notably, only few AI applications in orthodontics have reached full clinical maturity and regulatory approval, and researchers in the field are tasked with tackling real-world evaluation and implementation of AI into the orthodontic workflow.

Multi-modal deep learning for automated assembly of periapical radiographs.

OBJECTIVES: Periapical radiographs are oftentimes taken in series to display all teeth present in the oral cavity. Our aim was to automatically assemble such a series of periapical radiographs into an anatomically correct status using a multi-modal deep learning model. METHODS: 4,707 periapical images from 387 patients (on average, 12 images per patient) were used. Radiographs were labeled according to their field of view and the dataset split into a training, validation, and test set, stratified by patient. In addition to the radiograph the timestamp of image generation was extracted and abstracted as follows: A matrix, containing the normalized timestamps of all images of a patient was constructed, representing the order in which images were taken, providing temporal context information to the deep learning model. Using the image data together with the time sequence data a multi-modal deep learning model consisting of two residual convolutional neural networks (ResNet-152 for image data, ResNet-50 for time data) was trained. Additionally, two uni-modal models were trained on image data and time data, respectively. A custom scoring technique was used to measure model performance. RESULTS: Multi-modal deep learning outperformed both uni-modal image-based learning (p<0.001) and time-based learning (p<0.05). The multi-modal deep learning model predicted tooth labels with an F1-score, sensitivity and precision of 0.79, respectively, and an accuracy of 0.99. 37 out of 77 patient datasets were fully correctly assembled by multi-modal learning; in the remaining ones, usually only one image was incorrectly labeled. CONCLUSIONS: Multi-modal modeling allowed automated assembly of periapical radiographs and outperformed both uni-modal models. Dental machine learning models can benefit from additional data modalities. CLINICAL SIGNIFICANCE: Like humans, deep learning models may profit from multiple data sources for decision-making. We demonstrate how multi-modal learning can assist assembling periapical radiographs into an anatomically correct status. Multi-modal learning should be considered for more complex tasks, as clinically a wealth of data is usually available and could be leveraged.

Microbial contamination on ambulance surfaces: a systematic literature review.

Healthcare-associated infections (HAIs) are infections that patients acquire while receiving medical treatment in a healthcare facility. During ambulatory transport, the patient may be exposed to pathogens transmitted from emergency medical service (EMS) personnel or EMS surfaces.The aim of this study was to determine whether organisms commonly associated with HAIs have been detected on surfaces in the patient-care compartment of ambulances. Five electronic databases - PubMed, Scopus, Web of Science, Embase and Google Scholar were used to search for articles using inclusion and exclusion criteria following the PRISMA checklist. Inclusion criteria consisted of articles published in English, between 2009 and 2020, had positive samples collected from the patient-care compartment of a ground ambulance, and reported sample collection methods of either swab sampling and/or Replicate Organism Detection and Counting (RODAC) contact plates. Studies not meeting these criteria were excluded from this review. From a total of 1376 articles identified, 16 were included in the review. Organisms associated with HAIs were commonly detected in the patient-care compartment of ambulances across a variety of different surfaces, including blood pressure cuffs, oxygen apparatuses, and areas of patient stretchers. A high prevalence of pathogenic bacteria in ambulances suggests that standard protocols related to cleaning compliance may not be effective. The primary recommendation is that designated subject matter experts in infection prevention should be incorporated as liaisons in the pre-hospital setting, acting as a link between the pre-hospital (e.g., ambulance transport) and hospital environments.

Benchmarking atlas-level data integration in single-cell genomics.

Single-cell atlases often include samples that span locations, laboratories and conditions, leading to complex, nested batch effects in data. Thus, joint analysis of atlas datasets requires reliable data integration. To guide integration method choice, we benchmarked 68 method and preprocessing combinations on 85 batches of gene expression, chromatin accessibility and simulation data from 23 publications, altogether representing >1.2 million cells distributed in 13 atlas-level integration tasks. We evaluated methods according to scalability, usability and their ability to remove batch effects while retaining biological variation using 14 evaluation metrics. We show that highly variable gene selection improves the performance of data integration methods, whereas scaling pushes methods to prioritize batch removal over conservation of biological variation. Overall, scANVI, Scanorama, scVI and scGen perform well, particularly on complex integration tasks, while single-cell ATAC-sequencing integration performance is strongly affected by choice of feature space. Our freely available Python module and benchmarking pipeline can identify optimal data integration methods for new data, benchmark new methods and improve method development.

scCODA is a Bayesian model for compositional single-cell data analysis.

Compositional changes of cell types are main drivers of biological processes. Their detection through single-cell experiments is difficult due to the compositionality of the data and low sample sizes. We introduce scCODA ( https://github.com/theislab/scCODA ), a Bayesian model addressing these issues enabling the study of complex cell type effects in disease, and other stimuli. scCODA demonstrated excellent detection performance, while reliably controlling for false discoveries, and identified experimentally verified cell type changes that were missed in original analyses.

Tiny golden angle stack-of-stars (tygaSoS) free-breathing functional lung imaging.

PURPOSE: MRI of the lung parenchyma is still challenging due to cardiac and respiratory motion, and the low proton density and short T2*. Clinical feasible MRI methods for functional lung assessment are of great interest. It was the objective of this study to evaluate the potential of combining the ultra-short echo-time stack-of-stars approach with tiny golden angle (tyGASoS) profile ordering for self-gated free-breathing lung imaging. METHODS: Free-breathing tyGASoS data were acquired in 10 healthy volunteers (3 smoker (S), 7 non-smoker (NS)). Images in different respiratory phases were reconstructed applying an image-based self-gating technique. Resulting image quality and sharpness, and parenchyma visibility were qualitatively scored by three blinded independent reader, and the signal-to-noise ratio (SNR), proton fraction (fP) and fractional ventilation (FV) quantified. RESULT: The imaging protocol was well tolerated by all volunteers. Image quality was sufficient for subsequent quantitative analysis in all cases with good to excellent inter-reader reliability. Between expiration (EX) and inspiration (IN) significant differences (p < 0.001) were observed in SNR (EX: 3.73 ± 0.89, IN: 3.14 ± 0.74) and fP (EX: 0.27 ± 0.09, IN: 0.25 ± 0.08). A significant (p < 0.05) higher fP (EX/IN: 0.22 ± 0.07/0.21 ± 0.07 (NS), 0.33 ± 0.07/0.30 ± 0.06 (S)) was observed in the smoker group. No significant FV differences resulted between S and NS. CONCLUSION: The study proves the feasibility of free-breathing tyGASoS for multiphase lung imaging. Changes in fP may indicate an initial response in the smoker group and as such proves the sensitivity of the proposed technique. A major limitation in FV quantification rises from the large inter-subject variability of breathing patterns and amplitudes, requiring further consideration.

The Region of Difference Four is a Robust Genetic Marker for Subtyping Mycobacterium caprae Isolates and is Linked to Spatial Distribution of Three Subtypes.

Alpine Mycobacterium caprae isolates found in cattle and red deer display at least three genetic variations in the region of difference four (RD4) that can be used for further differentiation of the isolates into the subtypes 'Allgäu', 'Karwendel' and 'Lechtal'. Each genomic subtype is thereby characterized by a specific nucleotide deletion pattern in the 12.7-kb RD4 region. Even though M. caprae infections are frequently documented in cattle and red deer, little is known about the transmission routes. Hence, robust markers for M. caprae subtyping are needed to gain insight into the molecular epidemiology. For this reason, a rapid and robust multiplex PCR was developed for the simultaneous detection of three M. caprae RD4 subtypes and was used to subtype a total number of 241 M. caprae isolates from animals (145 cattle, 95 red deer and one fox) from Bavaria and Austria. All three subtypes occur spatially distributed and are found in cattle and in red deer suggesting transmission between the two species. As subtypes are genetically stable in both species it is hypothesized that the described genetic variations developed within the host due to 'within-host replication'. The results of this study recommend the genomic RD4 region as a reliable diagnostic marker for M. caprae subtype differentiation.

Influenza A Viruses Detected in Swine in Southern Germany after the H1N1 Pandemic in 2009.

Infections with influenza A viruses (IAV) are highly prevalent in swine populations, and stable cocirculation of at least three lineages has been well documented in European swine - till 2009. However, since the emergence of the human pandemic pdmH1N1 virus in 2009, which has been (re)introduced into individual swine herds worldwide, the situation has been changing. These variations in the respective IAV pools within pig populations are of major interest, and the zoonotic potential of putative emerging viruses needs to be evaluated. As data on recent IAV in swine from southern Germany were relatively sparse, the purpose of this study was to determine the major IAV subtypes actually present in this region. To this aim, from 2010 to 2013, 1417 nasal swabs or lung tissue samples from pigs with respiratory disease were screened for IAV genomes. Overall, in 130 holdings IAV genomes were detected by real-time RT-PCR targeting the matrix protein gene. For further analyses, several PCR protocols were adapted to quickly subtype between H1, pdmH1, H3, N1 and N2 sequences. Taken together, cocirculation of the three stable European lineages of IAV was confirmed for Bavaria. H1N1 sequences were identified in 59, whereas H1N2 genomes were only diagnosed in 14, and H3N2 in 9 of the holdings analysed. However, pdmH1 in combination with N1 was detected in 2010, 2012 and 2013 confirming a presence, albeit in low prevalence, likewise pdmH1N2 reassortant viruses. Interestingly, individual cases of coinfections with more than one subtype were diagnosed. Partial genome sequences were determined and phylogenetic analyses performed. Clearly other than in the human population classically circulating IAV have not been displaced by pdmH1N1 in Bavarian swine. However, some interesting viruses were detected. Further surveillance of these viruses in the Bavarian pig population will be of major importance, to monitor future developments.

[Validation of the German version of the Singing Voice Handicap Index]. / Validierung des Singing Voice Handicap Index in der deutschen Fassung.

The Singing Voice Handicap Index (SVHI) was developed in the United States for the self-assessment of patients with singing problems. It has been translated into German and its reliability and validity have been assessed. In total, 54 (35 female, 19 male) dysphonic singers and 130 (74 female, 56 male) non-dysphonic professional singers were included in the study. Reliability rested on high test-retest reliability (r = 0.960, p ≤ 0.001, Pearson correlation) and a Cronbach's α of 0.975. A principal component analysis using the Varimax method and the results of the screeplot suggest the SVHI scored as a single scale. Validity rested on a highly significant correlation between the severity of the self-rated voice impairment by the patient and the total SVHI score. Dysphonic singers have significantly higher SVHI scores than healthy singers. The SVHI is thus suited to implementation as a diagnostic tool in German-speaking countries.

Radiochemotherapy induces a favourable tumour infiltrating inflammatory cell profile in head and neck cancer.

Head and neck squamous cell cancers (HNSSC) generate an immune-suppressive micro-environment by a specific pattern of tumour infiltrating inflammatory cells. The aim of our study was to evaluate the impact of radiochemotherapy on the numbers and composition of inflammatory cells and its influence on outcome. Fifty-eight patients suffering from oral cavity cancer were studied, whose therapy consisted of concurrent radiochemotherapy followed by surgery. Numbers and ratios of tumour infiltrating inflammatory cells were compared prior to and after radiochemotherapy. Intraepithelial and stromal location of tumour infiltrating inflammatory cells was analysed separately. Infiltration of CD3(+), CD4(+), CD25(+), FoxP3(+), CD8(+), Granzyme B(+), CD20(+) and CD68(+) cells predominated in the peritumoural stromal compartment, whereas CD1a(+) dendritic cells were found more frequently in the intraepithelial compartment. Neoadjuvant treatment was associated with a general decrease of tumour infiltrating inflammatory cells in both compartments. The CD8(+) and Granzyme B(+) cytotoxic cells decreased only slightly after RCT. In contrast, the decrease of FoxP3(+) regulatory T cells was more pronounced and the cytotoxic T-cell/FoxP3(+) ratio increased 2- to 3-fold in both compartments, respectively. Patients with high cytotoxic cell numbers, high dendritic cell numbers and a high ratio of cytotoxic cells to regulatory T cells had a better disease free survival. Concurrent radiochemotherapy of oral squamous cell carcinoma was shown to drive the composition of inflammatory cells in a direction which is supposed to be prognostically favourable.

Original findings associated with two cases of bovine papular stomatitis.

Bovine papular stomatitis virus was isolated from two calves in an animal house with biosafety level 3 confinement. The hypotheses on the origin of the infection, the interesting features of the partial amino acid sequences of the major envelope viral protein, and the importance of diagnostic tools available for animal diseases that are not listed by the World Organization for Animal Health (OIE) are discussed.

[Evaluation of a renal biopsy: what information is important for nephrologists?]. / Beurteilung der Nierenbiopsie: Was der Nephrologe vom (Nephro-)Pathologen wissen will.

A kidney biopsy is an important and frequently used diagnostic tool in routine nephrology. In order to obtain relevant clinical information from a renal biopsy close cooperation between clinicians and pathologists is mandatory. The better the information obtained from nephrologists and the better the understanding by nephrologists and the quality of the kidney biopsy, the more rewarding is the information from pathologists. The following paper will discuss some practical aspects regarding the interaction between nephrology and pathology which may not be known or poorly handled and may thus cause misunderstanding. In order to facilitate interaction between clinicians and pathologists some guidelines concerning the procedure and work-up of routine kidney biopsies have been established and will be discussed in detail.

Effects of Elevated Atmospheric CO(2) on Rhizosphere Soil Microbial Communities in a Mojave Desert Ecosystem.

The effects of elevated atmospheric carbon dioxide [CO(2)] on microbial communities in arid rhizosphere soils beneath Larrea tridentata were examined. Roots of Larrea were harvested from plots fumigated with elevated or ambient levels of [CO(2)] using Free-Air CO(2) Enrichment (FACE) technology. Twelve bacterial and fungal rRNA gene libraries were constructed, sequenced and categorized into operational taxonomical units (OTUs). There was a significant decrease in OTUs within the Firmicutes (bacteria) in elevated [CO(2)], and increase in Basiomycota (fungi) in rhizosphere soils of plots exposed to ambient [CO(2)]. Phylogenetic analyses indicated that OTUs belonged to a wide range of bacterial and fungal taxa. To further study changes in bacterial communities, Quantitative Polymerase Chain Reaction (QPCR) was used to quantify populations of bacteria in rhizosphere soil. The concentration of total bacteria 16S rDNA was similar in conditions of enriched and ambient [CO(2)]. However, QPCR of Gram-positive microorganisms showed a 43% decrease in the population in elevated [CO(2)]. The decrease in representation of Gram positives and the similar values for total bacterial DNA suggest that the representation of other bacterial taxa was promoted by elevated [CO(2)]. These results indicate that elevated [CO(2)] changes structure and representation of microorganisms associated with roots of desert plants.

[Kidney transplant pathology]. / Nierentransplantatpathologie.

Biopsy of the transplanted kidney plays an important role in the care and treatment of patients after kidney transplantation. Today the renal biopsy is a standard procedure which is performed early after renal transplantation in the case of a primary non-functioning graft or a significant rise in serum creatinine. On the other hand, a kidney biopsy is performed if an acute or creeping rise in serum creatinine or acute onset of proteinuria or erythrocyturia is observed during follow-up. Furthermore, zero biopsies or intraoperative biopsies of the graft are important in order to obtain information about the initial quality of the graft. This is particularly important in view of the shortage of donor organs and the resulting necessity to accept increasingly marginal organs, such as for example in the ESP program. In addition, an increasing number of transplant centres perform protocol biopsies, i.e. biopsies that are not based on clinical indication, but are performed at a certain time point after transplantation to detect subclinical rejections as well as histological alterations pointing to chronic allograft damage. Additionally, there is much scientific interest in protocol biopsies.

ARFI-based tissue elasticity quantification and kidney graft dysfunction: first clinical experiences.

BACKGROUND AND PURPOSE: Beyond the medical history, the clinical exam and lab findings, non-invasive ultrasound parameters such as kidney size and Doppler values (e.g. the resistive index) are important tools assisting clinical decision making in the monitoring of renal allografts. The gold standard for the diagnosis of renal allograft dysfunction remains the renal biopsy; while an invasive procedure, the justifiable necessity for this derives from its definitive nature a requirement beyond the synopses of all non-invasive tools. "Acoustic Radiation Force Impulse Imaging"(ARFI)-quantification is a novel ultrasound-based technology measuring tissue elasticity properties. So far experience related to this new method has not been reported in renal transplant follow-up. The purpose of this study was to evaluate changes in ARFI-measurements between clinically stable renal allografts and biopsy-proven transplant dysfunction. METHODS: We employed "Virtual Touch™ tissue quantification" (Siemens Acuson, S2000) for the quantitative measurement of tissue stiffness in the cortex of transplant kidneys. We performed initial baseline and later disease-evaluative ultrasound examinations in 8 renal transplant patients in a prospective study design. Patients were first examined during stable allograft function with a routine post-transplant renal ultrasound protocol. A second follow-up examination was carried out on subsequent presentation with transplant dysfunction prior to allograft biopsy and histological evaluation. All patiens were examined using ARFI-quantification (15 measurements/kidney). Resistive indices (RI) were calculated using pulsed-wave Doppler ultrasound, and transplant kidney size was measured on B-mode ultrasound images. All biopsies were evaluated histologically by a reference nephropathologist unaware of the results of the ultrasound studies. Histopathological diagnoses were based on biopsy results, taking clinical and laboratory findings into account. Finally we calculated the relative changes in ARFI-quantification, resistive indices and the absolute change of kidney size on a percentage basis at these defined assessment times and compared the results with the final pathologic diagnosis. RESULTS: Histological results enumerated five cases of acute T-cell-mediated rejection, one case of calcineurin inhibitor toxicity and two cases of acute tubular necrosis. Calcineurin inhibitor toxicity and acute tubular necrosis were subsumed as "other pathologies". Mean ARFI-values showed an average increase of more than 15% percent in transplants with histologically proven acute rejection whereas no increase was seen in transplants with other pathologies. Mean RI-values showed no increase either in the diagnostic group of acute rejection, nor in the group with other pathologies. Kidney size showed a mean absolute increase of 0.5 centimetres in allografts with acute rejection, whereas a mean decrease of 0.17 centimetres was seen in the group with other pathologies. CONCLUSION: As shown before in other studies, RI values and kidney size are of doubtful utility in the evaluation of kidney allograft dysfunction. ARFI-based elasticity measurement shows promise as a complementary non-invasive parameter in follow-on diagnosis of renal allograft rejection.

ARFI-based tissue elasticity quantification in comparison to histology for the diagnosis of renal transplant fibrosis.

BACKGROUND AND PURPOSE: Until recently clinical diagnosis of chronic renal allograft dysfunction could only be established invasively by renal biopsy. Given the risks of that procedure, a non-invasive, diagnostic test would be very advantageous. Novel ultrasound-based elasticity tools, using "Acoustic Radiation Force Impulse (ARFI)" technology are now available. Previously this technique has been utilised to quantify liver fibrosis. First results of these studies are promising. The purpose of our study was to investigate correlation between stiffness values obtained by ARFI-quantification and histological fibrosis score in renal transplants. METHODS: We employed "Virtual Touch™ tissue quantification" (Siemens Acuson, S2000) to quantitatively measure tissue stiffness in the cortex of transplant kidneys. Eighteen patients were included in this prospective study, recording close temporal ARFI-quantification and fibrosis measurements. All patients undergoing renal transplant biopsy were examined with ARFI-quantification (15 measurements per transplant kidney). Resistive indices were also calculated from pulsed-wave Doppler ultrasound. Transplant biopsies were histologically evaluated by a reference nephropathologist and graded according to the percentage of fibrosis and to the BANFF-score. Due to the non-normal distribution of the data the Spearman-correlation-coefficient (rho) was used to assess the bivariate relationship of ARFI and fibrosis in the transplant kidney. RESULTS: There was a significant positive moderate correlation between mean ARFI-values and the grade of fibrosis (rho = +0.465; p = 0.026). This correlation was also valid for the mean ARFI-values and the BANFF-category (rho = +0.468; p = 0.025). There was no significant correlation between the mean ARFI-values and the resistive indices in the transplant kidney (rho = +0.034; p = 0.904). Nevertheless, a positive correlation between the mean RI-values of the kidney and the grade of fibrosis was established (rho = +0.563; p = 0.015). CONCLUSION: The mean values of ARFI measurements and the resistive indices are potentially independent explanation variables for evaluating the grade of fibrosis in transplant kidneys.

The Arabidopsis sugar transporter (AtSTP) family: an update.

The Arabidopsis sugar transporter (AtSTP) family is one of the best characterised families within the monosaccharide transporter (MST)-like genes. However, several aspects are still poorly investigated or not yet addressed experimentally, such as post-translational modifications and other factors affecting transport activity. This mini-review summarises recent advances in the AtSTP family as well as objectives for future studies.