Machine learning-based decision support system for orthognathic diagnosis and treatment planning.

BACKGROUND: Dento-maxillofacial deformities are common problems. Orthodontic-orthognathic surgery is the primary treatment but accurate diagnosis and careful surgical planning are essential for optimum outcomes. This study aimed to establish and verify a machine learning-based decision support system for treatment of dento-maxillofacial malformations. METHODS: Patients (n = 574) with dento-maxillofacial deformities undergoing spiral CT during January 2015 to August 2020 were enrolled to train diagnostic models based on five different machine learning algorithms; the diagnostic performances were compared with expert diagnoses. Accuracy, sensitivity, specificity, and area under the curve (AUC) were calculated. The adaptive artificial bee colony algorithm was employed to formulate the orthognathic surgical plan, and subsequently evaluated by maxillofacial surgeons in a cohort of 50 patients. The objective evaluation included the difference in bone position between the artificial intelligence (AI) generated and actual surgical plans for the patient, along with discrepancies in postoperative cephalometric analysis outcomes. RESULTS: The binary relevance extreme gradient boosting model performed best, with diagnostic success rates > 90% for six different kinds of dento-maxillofacial deformities; the exception was maxillary overdevelopment (89.27%). AUC was > 0.88 for all diagnostic types. Median score for the surgical plans was 9, and was improved after human-computer interaction. There was no statistically significant difference between the actual and AI- groups. CONCLUSIONS: Machine learning algorithms are effective for diagnosis and surgical planning of dento-maxillofacial deformities and help improve diagnostic efficiency, especially in lower medical centers.

Comparison of Effects between Total Maxillary Setback Osteotomy and Anterior Maxillary Segmental Osteotomy on Nasolabial Morphology.

BACKGROUND: The authors aimed to compare the effects of total maxillary setback osteotomy (TMSO) and anterior maxillary segmental osteotomy (AMSO) on nasolabial morphology. METHODS: This retrospective clinical trial enrolled 130 patients undergoing maxillary surgery using TMSO or AMSO. Ten nasolabial-related parameters and nasal airway volume were measured preoperatively and postoperatively. The soft-tissue digital model was reconstructed using Geomagic Studio and Dolphin image 11.0. Statistical analysis was performed using IBM SPSS Version 27.0. RESULTS: A total of 75 patients underwent TMSO, and 55 underwent AMSO. Both techniques achieved optimal repositioning of the maxilla. Except for the dorsal nasal length, the dorsal nasal height, the length of the nasal columella, and the upper lip thickness, the remaining parameters were significantly different in the TMSO group. In the AMSO group, only the nasolabial angle, the alar base width, and the greatest alar width showed significant differences. There was a significant difference in the nasal airway volume for the TMSO group. The results of matching maps are consistent with the statistical results. CONCLUSIONS: TMSO has a more significant impact on both nose and upper lip soft tissues, whereas AMSO has a more significant impact on the upper lip and less on the nasal soft tissue. There is a significant decrease in nasal airway volume after TMSO, whereas AMSO showed less decrease. This retrospective study is helpful for clinicians and patients to understand the different changes in nasolabial morphology caused by the two interventions, which is essential for effective intervention and physician-patient communication. CLINICAL QUESTION/LEVEL OF EVIDENCE: Therapeutic, III.

Artificial Intelligence Splint in Orthognathic Surgery for Skeletal Class III Malocclusion: Design and Application.

BACKGROUND: Digital splints are indispensable in orthognathic surgery. However, the present design process of splints is time-consuming and has low reproducibility. To solve these problems, an algorithm for artificial intelligent splints has been developed in this study, making the automatic design of splints accessible. METHODS: Firstly, the algorithm and program of the artificial intelligence splint were created. Then a total of 54 patients with skeletal class III malocclusion were included in this study from 2018 to 2020. Pre and postoperative radiographic examinations were performed. The cephalometric measurements were recorded and the difference between virtual simulation and postoperative images was measured. The time cost and differences between artificial intelligent splints and digital splints were analyzed through both model surgery and radiographic images. RESULTS: The results showed that the efficiency of designing splints is significantly improved. And the mean difference between artificial intelligent splints and digital splints was <0.15 mm in model surgery. Meanwhile, there was no significant difference between the artificial intelligent splints and digital splints in radiological image analysis. CONCLUSIONS: In conclusion, compared with digital splints, artificial intelligent splints could save time for preoperative design while ensuring accuracy. The authors believed that it is conducive to the presurgical design of orthognathic surgery.

Precise Sn-Doping Modulation for Optimizing CdWO4 Nanorod Photoluminescence.

The cadmium tungstate rods have been given much attention due to their potential for usage in numerous luminescent applications. We have prepared single crystalline Sn-doped Cd1-xSnxWO4 (where x = 0, 1, 3, and 5%) nanorods (NRDs) and characterized them using refined X-ray diffraction and TEM analysis, revealing a monoclinic phase and a crystallite size that decreased from 62 to 38 nm as Sn concentration increased. Precise Sn doping modulation in CdWO4 NRDs causes surface recombination of electrons and holes, which causes the PL intensity to decrease as the Sn content rises. The chromaticity diagram shows that an increase in the Sn content caused a change in the emission color from sky blue to light green, which was attributed to the increased defect density. The photoluminescence time decay curve of all samples fit well with double-order exponential decay, and the average decay lifetime was found to be 1.11, 0.93, and 1.16 ns for Cd1-xSnxWO4, x = 0, 1, and 5%, respectively. This work provides an understanding of the behavior of Sn-doped CdWO4 NRDs during electron transitions and the physical nature of emission that could be used in bio-imaging, light sources, displays, and other applications.

Surgical Guides and Prebent Titanium Improve the Planning for the Treatment of Dentofacial Deformities Secondary to Condylar Osteochondroma.

PURPOSE: To investigate current Computer-Aided Design and Computer-Aided Manufacturing (CAD/CAM) technologies applied in the treatment of dentofacial deformities secondary to condylar osteochondroma and introduce a modified method with additional pre-bent titanium miniplates to improve the accuracy of operation. METHODS: Literature review about the application of CAD/CAM in the treatment of condylar osteochondroma and secondary dentofacial deformities was conducted. And 8 patients with condylar osteochondroma and secondary dentofacial deformities were treated by the CAD/CAM cutting and drilling surgical guides as well as pre-bent titanium miniplates. Pre- and post-operative 3D-cephalometric measurement were recorded and the difference between virtual simulation and postoperative modeling images was measured. Follow-up and radiographic examinations were performed. RESULTS: A total of 17 studies (including 216 patients) about the application of CAD/CAM in the treatment of dentofacial deformities secondary to condylar osteochondroma have been reported since 2010, including the 8 present patients. In our study, all patients were satisfied with the surgical outcome, without obvious relapse or evidence of temporomandibular joint disorder or other complications during follow-up; all patients avoided condylar reconstruction and sagittal split of ramus osteotomy on the ipsilateral mandible side. Comparison between simulated plans and actual postoperative outcomes showed surgical simulation plan was accurately transferred to the actual surgery. CONCLUSIONS: The application of CAD/CAM cutting and drilling guides as well as pre-bent titanium plates could achieve more accurate and favorable outcomes, improving the clinical planning and surgical execution for patients with condylar osteochondroma and secondary dentofacial deformities.

Hybrid support vector machine optimization model for inversion of tunnel transient electromagnetic method.

The transient electromagnetic method (TEM) can effectively predict adverse geological conditions, and is widely used in underground engineering fields such as coal mining and tunneling. Accurate evaluation of adverse geological features is a crucial problem that requires urgent solutions. TEM inversion is an essential tool in solving such problems. However, the three-dimensional full-space detection of tunnels and its inversion are not sufficiently developed. Therefore, combining a least-squares support vector machine (LSSVM) with particle swarm optimization (PSO), this paper proposes a tunnel TEM inversion approach. Firstly, the PSO algorithm is adopted to optimize the LSSVM model, thus overcoming the randomness and uncertainty of model parameter selection. An orthogonal test method is adopted to optimize the initial parameter combination of the PSO algorithm, which further improves the accuracy of our PSO-LSSVM model. Numerical simulations are conducted to generate 125 sets of original data. The optimized PSO-LSSVM model is then used to predict certain values of the original data. Finally, the optimization model is compared with conventional machine learning methods, and the results show that the randomness of the initial parameters of the PSO algorithm has been reduced and the optimization effect has been improved. The optimized PSO algorithm further improves the stability and accuracy of the generalization ability of the model. Through a comparison of different machine learning methods and laboratory model tests, it is verified that the optimized PSO-LSSVM model proposed in this paper is an effective technique for tunnel TEM detection inversion.

Room Temperature Magnetic Memory Effect in Cluster-Glassy Fe-doped NiO Nanoparticles.

The Fe-doped NiO nanoparticles that were synthesized using a co-precipitation method are characterized by enhanced room-temperature ferromagnetic property evident from magnetic measurements. Neutron powder diffraction experiments suggested an increment of the magnetic moment of 3d ions in the nanoparticles as a function of Fe-concentration. The temperature, time, and field-dependent magnetization measurements show that the effect of Fe-doping in NiO has enhanced the intraparticle interactions due to formed defect clusters. The intraparticle interactions are proposed to bring additional magnetic anisotropy energy barriers that affect the overall magnetic moment relaxation process and emerging as room temperature magnetic memory. The outcome of this study is attractive for the future development of the room temperature ferromagnetic oxide system to facilitate the integration of spintronic devices and understanding of their fundamental physics.

Inadequate dietary energy intake associates with higher prevalence of metabolic syndrome in different groups of hemodialysis patients: a clinical observational study in multiple dialysis centers.

BACKGROUND: Metabolic syndrome (MetS) has been established as a risk for cardiovascular diseases and mortality in hemodialysis patients. Energy intake (EI) is an important nutritional therapy for preventing MetS. We examined the association of self-reported dietary EI with metabolic abnormalities and MetS among hemodialysis patients. METHODS: A cross-sectional study design was carried out from September 2013 to April 2017 in seven hemodialysis centers. Data were collected from 228 hemodialysis patients with acceptable EI report, 20 years old and above, underwent three hemodialysis sessions a week for at least past 3 months. Dietary EI was evaluated by a three-day dietary record, and confirmed by 24-h dietary recall. Body compositions were measured by bioelectrical impedance analysis. Biochemical data were analyzed using standard laboratory tests. The cut-off values of daily EI were 30 kcal/kg, and 35 kcal/kg for age ≥ 60 years and < 60 years, respectively. MetS was defined by the American Association of Clinical Endocrinologists (AACE-MetS), and Harmonizing Metabolic Syndrome (HMetS). Logistic regression models were utilized for examining the association between EI and MetS. Age, gender, physical activity, hemodialysis vintage, Charlson comorbidity index, high sensitive C-reactive protein, and interdialytic weight gains were adjusted in the multivariate analysis. RESULTS: The prevalence of inadequate EI, AACE-MetS, and HMetS were 60.5%, 63.2%, and 53.9%, respectively. Inadequate EI was related to higher proportion of metabolic abnormalities and MetS (p <  0.05). Results of the multivariate analysis shows that inadequate EI was significantly linked with higher prevalence of impaired fasting glucose (OR = 2.42, p <  0.01), overweight/obese (OR = 6.70, p <  0.001), elevated waist circumference (OR = 8.17, p <  0.001), AACE-MetS (OR = 2.26, p <  0.01), and HMetS (OR = 3.52, p <  0.01). In subgroup anslysis, inadequate EI strongly associated with AACE-MetS in groups of non-hypertension (OR = 4.09, p = 0.004), and non-cardiovascular diseases (OR = 2.59, p = 0.012), and with HMetS in all sub-groups of hypertension (OR = 2.59~ 5.33, p <  0.05), diabetic group (OR = 8.33, p = 0.003), and non-cardiovascular diseases (OR = 3.79, p <  0.001). CONCLUSIONS: Inadequate EI and MetS prevalence was high. Energy intake strongly determined MetS in different groups of hemodialysis patients.

Short-Range Correlated Magnetic Core-Shell CrO2/Cr2O3 Nanorods: Experimental Observations and Theoretical Considerations.

With the evolution of synthesis and the critical characterization of core-shell nanostructures, short-range magnetic correlation is of prime interest in employing their properties to develop novel devices and widespread applications. In this regard, a novel approach of the magnetic core-shell saturated magnetization (CSSM) cylinder model solely based on the contribution of saturated magnetization in one-dimensional CrO2/Cr2O3 core-shell nanorods (NRs) has been developed and applied for the determination of core-diameter and shell-thickness. The nanosized effect leads to a short-range magnetic correlation of ferromagnetic core-CrO2 extracted from CSSM, which can be explained using finite size scaling method. The outcome of this study is important in terms of utilizing magnetic properties for the critical characterization of core-shell nanomagnetic materials.

The cut-off values of dietary energy intake for determining metabolic syndrome in hemodialysis patients: A clinical cross-sectional study.

Dietary energy intake strongly linked to dialysis outcomes. We aimed to explore the optimal cut-off point of energy intake (EI) for identification of metabolic syndrome (MetS) in hemodialysis patients. The cross-sectional data of 243 hemodialysis patients from multi-dialysis centers in Taiwan was used. The dietary intake was assessed by using the three-day dietary questionnaire, and a 24-hour dietary recall, clinical and biochemical data were also evaluated. The MetS was diagnosed by the Harmonized Metabolic Syndrome criteria. The receiver operating characteristic (ROC) curve was to depict the optimal cut-off value of EI for the diagnosis of MetS. The logistic regression was also used to explore the association between inadequate EI and MetS. The optimal cut-off points of EI for identifying the MetS were 26.7 kcal/kg/day for patients aged less than 60 years, or with non-diabetes, and 26.2 kcal/kg/day for patients aged 60 years and above, or with diabetes, respectively. The likelihood of the MetS increased with lower percentiles of energy intake in hemodialysis patients. In the multivariate analysis, the inadequate dietary energy intake strongly determined 3.24 folds of the MetS. The assessment of dietary EI can help healthcare providers detecting patients who are at risk of metabolic syndrome.

Phonon Confinement Induced Non-Concomitant Near-Infrared Emission along a Single ZnO Nanowire: Spatial Evolution Study of Phononic and Photonic Properties.

The impact of mixed defects on ZnO phononic and photonic properties at the nanoscale is only now being investigated. Here we report an effective strategy to study the distribution of defects along the growth direction of a single ZnO nanowire (NW), performed qualitatively as well as quantitatively using energy dispersive spectroscopy (EDS), confocal Raman-, and photoluminescence (PL)-mapping technique. A non-concomitant near-infrared (NIR) emission of 1.53 ± 0.01 eV was observed near the bottom region of 2.05 ± 0.05 µm along a single ZnO NW and could be successfully explained by the radiative recombination of shallowly trapped electrons V_O^(**) with deeply trapped holes at V_Zn^''. A linear chain model modified from a phonon confinement model was used to describe the growth of short-range correlations between the mean distance of defects and its evolution with spatial position along the axial growth direction by fitting the E2H mode. Our results are expected to provide new insights into improving the study of the photonic and photonic properties of a single nanowire.

A two-stage matched case-control study on multiple hypertensive candidate genes in Han Chinese.

BACKGROUND: Hypertension affects about 1/3 of adults worldwide, ~3.8 million in Taiwan, 160 million in China, and 1 billion worldwide. It is a major risk factor leading to stroke, cardiovascular disease, and end-stage renal disease. In each year, more than 13.5 million deaths are due to hypertension-related diseases worldwide. METHODS: We performed a two-stage association study of hypertension using genotype data of single-nucleotide polymorphisms (SNPs) from 992 young-onset hypertensive cases and 992 matched controls of Han Chinese in Taiwan. A total of 238 SNPs of 36 highly replicated hypertension candidate genes with functional importance were investigated. Association analysis was carried out using conditional logistic regression. RESULTS: We identified two SNPs that were strongly associated with hypertension in both the first and the second stages. The first SNP (rs2301339) is located at guanine nucleotide-binding protein ß3 subunit (GNB3) and the other one (rs17254521) is located at insulin receptor (INSR). CONCLUSIONS: SNP rs2301339 is perfectly linked in linkage disequilibrium (LD) with C825T (rs5443) which has been associated with hypertension in Caucasian, but inconsistent in Asian populations. However, we found that in our sample this SNP has an opposite effect with the previous findings. In summary, this study identified one novel SNP in GNB3 and one novel SNP in INSR that are strongly associated with young-onset hypertension. Due to relatively small sample size, the results should still be interpreted with caution and need to be replicated in other studies.

Computational analysis of mRNA expression profiles identifies microRNA-29a/c as predictor of colorectal cancer early recurrence.

Colorectal cancer (CRC) is one of the leading malignant cancers with a rapid increase in incidence and mortality. The recurrences of CRC after curative resection are sometimes unavoidable and often take place within the first year after surgery. MicroRNAs may serve as biomarkers to predict early recurrence of CRC, but identifying them from over 1,400 known human microRNAs is challenging and costly. An alternative approach is to analyze existing expression data of messenger RNAs (mRNAs) because generally speaking the expression levels of microRNAs and their target mRNAs are inversely correlated. In this study, we extracted six mRNA expression data of CRC in four studies (GSE12032, GSE17538, GSE4526 and GSE17181) from the gene expression omnibus (GEO). We inferred microRNA expression profiles and performed computational analysis to identify microRNAs associated with CRC recurrence using the IMRE method based on the MicroCosm database that includes 568,071 microRNA-target connections between 711 microRNAs and 20,884 gene targets. Two microRNAs, miR-29a and miR-29c, were disclosed and further meta-analysis of the six mRNA expression datasets showed that these two microRNAs were highly significant based on the Fisher p-value combination (p = 9.14 × 10(-9) for miR-29a and p = 1.14 × 10(-6) for miR-29c). Furthermore, these two microRNAs were experimentally tested in 78 human CRC samples to validate their effect on early recurrence. Our empirical results showed that the two microRNAs were significantly down-regulated (p = 0.007 for miR-29a and p = 0.007 for miR-29c) in the early-recurrence patients. This study shows the feasibility of using mRNA profiles to indicate microRNAs. We also shows miR-29a/c could be potential biomarkers for CRC early recurrence.

Genetic association with rheumatoid arthritis-Genetic Analysis Workshop 15: summary of contributions from Group 2.

The papers in presentation group 2 of Genetic Analysis Workshop 15 (GAW15) conducted association analyses of rheumatoid arthritis data. The analyses were carried out primarily in the data provided by the North American Rheumatoid Arthritis Consortium (NARAC). One group conducted analyses in the data provided by the Canadian Rheumatoid Arthritis Genetics Study (CRAGS). Analysis strategies included genome-wide scans, the examination of candidate genes, and investigations of a region of interest on chromosome 18q21. Most authors employed relatively new methods, proposed extensions of existing methods, or introduced completely novel methods for aspects of association analysis. There were several common observations; a group of papers using a variety of methods found stronger association, on chromosomes 6 and 18 and in candidate gene PTPN22 among women with early onset. Generally, models that considered haplotypes or multiple markers showed stronger evidence for association than did single marker analyses.

LDMAP: the construction of high-resolution linkage disequilibrium maps of the human genome.

The precise characterization of the linkage disequilibrium (LD) landscape from high-density single-nucleotide polymorphism (SNP) data underpins the association mapping of diseases and other studies. We describe the algorithm and implementation of a powerful approach for constructing LD genetic maps with meaningful map distances. The computational problems posed by the enormous number of SNPs typed in the HapMap data are addressed by developing segmental map construction with the potential for parallelization, which we are developing. There is remarkably little loss of information (1-2%) through this approach, but the computation times are dramatically reduced (more than fourfold for sequential map assembly). These developments enable the construction of very high-density genome-wide LD maps using data from more than 3 million SNPs in HapMap. We anticipate that a whole-genome LD map will be useful for disease gene mapping, genomic research, and population genetics.

Association mapping of susceptibility loci for rheumatoid arthritis.

We analyzed a case-control data set for chromosome 18q from the Genetic Analysis Workshop 15 to detect susceptibility loci for rheumatoid arthritis (RA). A total number of 460 cases and 460 unaffected controls were genotyped on 2300 single-nucleotide polymorphisms (SNPs) by the North American Rheumatoid Arthritis Consortium. Using a multimarker approach for association mapping under the framework of the Malecot model and composite likelihood, we identified a region showing significant association with RA (p < 0.002) and the predicted disease locus was at a genomic location of 53,306 kb with a 95% confidence interval (CI) of 53,295-53,331 kb. A common haplotype in this region was protective against RA (p = 0.002). In another region showing nominal significant association (51,585 kb, 95% CI: 51,541-51,628 kb, p = 0.037), a haplotype was also protective (p = 0.002). We further demonstrated that reducing SNP density decreased power and accuracy of association mapping. SNP selection based on equal linkage disequilibrium (LD) distance generally produced higher accuracy than that based on equal kilobase distance or tagging.

Impact of marker density on the accuracy of association mapping.

We studied the impact of marker density on the accuracy of association mapping using Genetic Analysis Workshop 15 simulated dense single-nucleotide polymorphism (SNP) data on chromosome 6. A total of 1500 cases and 2000 unaffected controls genotyped for 17,820 SNPs were analyzed. We applied the approach that combines information from multiple SNPs under the framework of the Malecot model and composite likelihood to non-overlapping regions of the chromosome. We successfully detected the associations with disease Loci C and D and predicted their locations as small as zero distance to Locus C when it was "typed" and 112 kb from the untyped rare Locus D. Reducing marker density decreased the accuracy of location estimates. However, the predicted locations were robust to variations in the number of SNPs. Generally, the linkage disequilibrium (LD) map reflecting distances between markers in relation to LD produced higher accuracy than the physical map. We also demonstrated that SNP selection based on equal LD distance outperforms that based on equal physical distance or SNP tagging. Furthermore, ignoring rare SNPs diminished the ability to detect rare causal variants.

Exploiting large scale computing to construct high resolution linkage disequilibrium maps of the human genome.

UNLABELLED: Linkage disequilibrium (LD) maps increase power and precision in association mapping, define optimal marker spacing and identify recombination hot-spots and regions influenced by natural selection. Phase II of HapMap provides approximately 2.8-fold more single nucleotide polymorphisms (SNPs) than phase I for constructing higher resolution maps. LDMAP-cluster, is a parallel program for rapid map construction in a Linux environment used here to construct genome-wide LD maps with >8.2 million SNPs from the phase II data. AVAILABILITY: The LD maps, LDMAP-cluster and documentation are available from: http://www.som.soton.ac.uk/research/geneticsdiv/epidemiology/LDMAP. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.