The relationship between tomographic sagittal root position of maxillary anterior teeth and the bone housing.

STATEMENT OF PROBLEM: In a prosthetically driven treatment plan, the tomographic sagittal root position in relation to the bone housing is an important factor in the decision-making process for immediate implant placement. However, other important parameters must be considered in the bone housing of each tooth, including the alveolar ridge dimensions, the buccal and the palatal bone thickness, and the root dimensions. PURPOSE: The purpose of this clinical study was to evaluate the relationship between the sagittal root position of maxillary anterior teeth and the bone housing. MATERIALS AND METHODS: A total of 420 maxillary anterior teeth were analyzed in 70 participants. The tomographic scans were classified as sagittal root position classes I, II, III, and IV. Measurements included buccal and palatal bone thickness, alveolar ridge height, alveolar ridge width, apical bone height, root length, and root width. The Pearson correlation, ANOVA, and Tukey post hoc tests were used to determine statistically significant differences (α=0.05). RESULTS: The sagittal root position distribution was 65.2%, 9.3%, 0.7%, and 24.8% for classes I, II, III, and IV, respectively. Bone housing measurements were significantly different in relation to the 4 sagittal root position classes (P<.05), except for alveolar ridge height. Post hoc analysis showed that, in class I, buccal bone thickness and alveolar bone height were significantly low, whereas root length and palatal bone thickness were high. The higher buccal bone thickness was found in class II, and lower alveolar ridge width and palatal bone thickness in class IV. These measurements in tooth groups were also significantly different over the sagittal root position classes (P<.05). The buccal bone thickness, palatal bone thickness, and alveolar ridge width presented different levels of correlation with alveolar ridge width over the sagittal root position classes. The buccal bone thickness and palatal bone thickness were weakly correlated in class I (r=0.163) and IV (r=0.222). CONCLUSIONS: Bone housing measurements were significantly different in relation to the sagittal root position of maxillary anterior teeth.

Relationship between anterior maxillary tooth sagittal root position and periodontal phenotype: a clinical and tomographic study.

OBJECTIVES: To evaluate the relationship between the tomographic sagittal root position (SRP) of maxillary anterior teeth and periodontal phenotype (PP). MATERIAL AND METHODS: Seventy volunteers (420 teeth) were evaluated. Clinical and photographic exams included the evaluation of gingival phenotype (GP) by transparency of the periodontal probe, keratinized tissue width (KTW), gingival architecture, tooth shape, and papilla height (PH). Soft tissue tomographic scan (ST-CBCT) measurements included the SRP classification, GP, gingival thickness in the tissue zone (GT-TZ) and in the bone zone (GT-BZ), buccal bone thickness (BBT), and the distances from the gingival margin and from cementoenamel junction to the buccal bone crest (GM-BBC and CEJ-BBC). Kruskal-Wallis test and a linear regression analysis model were used. RESULTS: The frequency of SRP over the 420 teeth was 65.2% (class I), 9.3% (class II), 0.7% (class III), and 24.8% (class IV). Linear regression analysis showed that SRP is related to PP (p < 0.05). Significantly different measurements of PP parameters were found in SRP classes. The higher and lower GT and BBT were found in classes II and I, respectively. Class IV presented the highest KTW, PH, CEJ-BBC, and GM-BBC. Central incisors (CI) classes I and II were most frequently square-shaped, while 89% of CI Class IV were triangular-shaped. CONCLUSION: The SRP of maxillary anterior teeth is related to periodontal phenotype. CLINICAL RELEVANCE: Clinical and ST-CBCT individual analysis of PP and SRP may be helpful for an esthetic and functional treatment plan based on soft and hard tissue thickness and tooth positioning.

Can nonlinear agrometeorological models estimate coffee foliation?

BACKGROUND: The loss of coffee leaves caused by the attack of pests and diseases significantly reduces its production and bean quality. Thus this study aimed to estimate foliation for regions with the highest production of arabica coffee in Brazil using nonlinear models as a function of climate. A 25-year historical series (1995-2019) of Coffea arabica foliation (%) data was obtained by the Procafé Foundation in cultivations with no phytosanitary treatment. The climate data were obtained on a daily scale by NASA/POWER platform with a temporal resolution of 33 years (1987-2019) and a spatial resolution of approximately 106 km, thus allowing the calculation of the reference evapotranspiration (PET). Foliation estimation models were adjusted through regression analysis using four-parameter sigmoidal logistic models. The analysis of the foliation trend of coffee plantations was carried out from degrees-day for 70 locations. RESULTS: The general model calibrated to estimate the arabica coffee foliation was accurate (mean absolute percentage error = 2.19%) and precise (R2 adj  = 0.99) and can be used to assist decision-making by coffee growers. The model had a sigmoidal trend of reduction, with parameters ymax  = 97.63%, ymin  = 9%, Xo  = 3517.41 DD, and p = 6.27%, showing that foliation could reach 0.009% if the necessary phytosanitary controls are not carried out. CONCLUSION: Locations with high air temperatures over the year had low arabica coffee foliation, as shown by the correlation of -0.94. Therefore, coffee foliation can be estimated using degree days with accuracy and precision through the air temperature. This represents great convenience because crop foliation can be obtained using only a thermometer. © 2021 Society of Chemical Industry.