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Objectives: This prospective, population-based cohort study aimed to investigate the development of facial asymmetry up to 6 years of age using a three-dimensional (3D) soft tissue imaging method in a normal population. In addition, the study sought to identify potential predisposing factors to facial asymmetry. Methods: A total of 102 newborns were enrolled in the study at birth. 3D stereophotogrammetric images of the head and face were analysed at the ages of 12 months (T1), 3 years (T2), and 6 years (T3). The surface-based analysis involved the calculation of the average distance (mm) and the symmetry percentage (%) between the original and mirrored surfaces. For landmark-based analysis, the distance of facial landmarks to the facial midline was examined. Results: The final analysis included 70 (68.6%) subjects. Surface-based analysis showed a significant improvement of facial symmetry from T1 to T3 in all facial areas. Landmark-based analysis showed that upper facial landmarks were located, on average, slightly on the left and lower facial landmarks slightly on the right in relation to the facial midline (P < 0.001). Limitations: The size of the study population was limited. Facial posture may affect the reliability of the results, especially in younger children. Conclusions: Facial asymmetry is detectable in early childhood and tends to reduce with age in young children. The lower face deviates slightly to the right, and the upper face to the left in relation to the facial midline. Possible predisposing factors for facial asymmetry at the age of 6 years include deformational plagiocephaly, sleeping position, and previous facial asymmetry.

BACKGROUND: Respiratory syncytial virus (RSV) is the most common cause of acute lower respiratory infection in young children. We previously estimated that in 2015, 33·1 million episodes of RSV-associated acute lower respiratory infection occurred in children aged 0-60 months, resulting in a total of 118 200 deaths worldwide. Since then, several community surveillance studies have been done to obtain a more precise estimation of RSV associated community deaths. We aimed to update RSV-associated acute lower respiratory infection morbidity and mortality at global, regional, and national levels in children aged 0-60 months for 2019, with focus on overall mortality and narrower infant age groups that are targeted by RSV prophylactics in development. METHODS: In this systematic analysis, we expanded our global RSV disease burden dataset by obtaining new data from an updated search for papers published between Jan 1, 2017, and Dec 31, 2020, from MEDLINE, Embase, Global Health, CINAHL, Web of Science, LILACS, OpenGrey, CNKI, Wanfang, and ChongqingVIP. We also included unpublished data from RSV GEN collaborators. Eligible studies reported data for children aged 0-60 months with RSV as primary infection with acute lower respiratory infection in community settings, or acute lower respiratory infection necessitating hospital admission; reported data for at least 12 consecutive months, except for in-hospital case fatality ratio (CFR) or for where RSV seasonality is well-defined; and reported incidence rate, hospital admission rate, RSV positive proportion in acute lower respiratory infection hospital admission, or in-hospital CFR. Studies were excluded if case definition was not clearly defined or not consistently applied, RSV infection was not laboratory confirmed or based on serology alone, or if the report included fewer than 50 cases of acute lower respiratory infection. We applied a generalised linear mixed-effects model (GLMM) to estimate RSV-associated acute lower respir

Tiivistelmä Lähtökohdat: Suuskannereita alettiin hyödyntää oikomishoidossa vuosituhannen vaihteessa, ja nykyään skannerien markkinat kasvavat jatkuvasti sitä mukaa, kun kalvo-oikominen yleistyy. Artikkelissa käsitellään suuskannerien toimintaperiaatteita ja käyttömahdollisuuksia ortodontiassa sekä vertaillaan niitä perinteisiin jäljentämismenetelmiin. Lisäksi luodaan katsaus skannauksen kehitykseen ja tämänhetkisiin markkinoihin. Menetelmät: Tutkimusmenetelmänä käytettiin kirjallisuuskatsausta. Aihetta käsitteleviä tuoreita artikkeleita etsittiin PubMed- ja Scopus-tietokannoista. Tulokset ja johtopäätökset: Markkinoilla olevat skannerit hyödyntävät hyvin monenlaisia teknologioita. Suuskannerien tarkkuudessa on eroavaisuuksia: eräät skannerit tuottavat tarkempia digitaalisia jäljennöksiä kuin muut. Eroista huolimatta skannerien on osoitettu olevan kliinisesti riittävän tarkkoja, mutta niiden hinnat ovat vielä korkeita. Monissa tutkimuksissa on todettu, että opetteluvaiheen jälkeen työn tehokkuus ja potilastyytyväisyys ovat skannerilla työskenneltäessä merkittävästi paremmat kuin perinteisiä jäljennösmenetelmiä käytettäessä. Hammaslääkärin työhön kuuluu jatkuva oman ammattitaidon kehittäminen. Uusi oikojasukupolvi on edellistä valmiimpi hyödyntämään digitaalisia laitteita, ja kynnys niiden käyttöönottoon madaltuu arkisen viestintäteknologian yleistyessä.

Objective: To resolve how the preferred chewing side (PCS) affects facial asymmetry in twins, whether there are differences between monozygotic (MZ) and dizygotic (DZ) twins, and whether the twins with PCS have more asymmetric faces compared to symmetrically chewing twins. Material and methods: The study included 106 Lithuanian twin pairs of the same sex, 59 MZ and 47 DZ pairs. The data were analysed from facial 3D images and manually added landmarks. 3D images were analysed by Rapidform2006 software and statistical analyses were done by using the R software environment version 4.1.0. Results: The contralateral effect of PCS and larger chin side was dominant among right and non-right side chewing twins. Being female increased the whole face symmetry. Conclusion: The volume of the chin becomes larger on the side opposite to the twins’ habitual chewing side. As the results are quite similar in both twin types, functional factors are more prominent than heredity.

Background and Objectives: Multilevel statistical models represent the existence of hierarchies or clustering within populations of subjects (or shapes in this work). This is a distinct advantage over single-level methods that do not. Multilevel partial-least squares regression (mPLSR) is used here to study facial shape changes with age during adolescence in Welsh and Finnish samples comprising males and females. Methods: 3D facial images were obtained for Welsh and Finnish male and female subjects at multiple ages from 12 to 17 years old. 1000 3D points were defined regularly for each shape by using “meshmonk” software. A three-level model was used here, including level 1 (sex/ethnicity); level 2, all “subject” variations excluding sex, ethnicity, and age; and level 3, age. The mathematical formalism of mPLSR is given in an Appendix. Results: Differences in facial shape between the ages of 12 and 17 predicted by mPLSR agree well with previous results of multilevel principal components analysis (mPCA); buccal fat is reduced with increasing age and features such as the nose, brow, and chin become larger and more distinct. Differences due to ethnicity and sex are also observed. Plausible simulated faces are predicted from the model for different ages, sexes and ethnicities. Our models provide good representations of the shape data by consideration of appropriate measures of model fit (RMSE and R²). Conclusions: Repeat measures in our dataset for the same subject at different ages can only be modelled indirectly at the lowest level of the model at discrete ages via mPCA. By contrast, mPLSR models age explicitly as a continuous covariate, which is a strong advantage of mPLSR over mPCA. These investigations demonstrate that multivariate multilevel methods such as mPLSR can be used to describe such age-related changes for dense 3D point data. mPLSR might be of much use in future for the prediction of facial shapes for missing persons at specific ages or for simul

PURPOSE To estimate age-specific relative and absolute cancer risks of breast cancer and to estimate risks of ovarian, pancreatic, male breast, prostate, and colorectal cancers associated with germline PALB2 pathogenic variants (PVs) because these risks have not been extensively characterized. METHODS We analyzed data from 524 families with PALB2 PVs from 21 countries. Complex segregation analysis was used to estimate relative risks (RRs; relative to country-specific population incidences) and absolute risks of cancers. The models allowed for residual familial aggregation of breast and ovarian cancer and were adjusted for the family-specific ascertainment schemes. RESULTS We found associations between PALB2 PVs and risk of female breast cancer (RR, 7.18; 95% CI, 5.82 to 8.85; P = 6.5 x 10-76), ovarian cancer (RR, 2.91; 95% CI, 1.40 to 6.04; P = 4.1 x 10-3), pancreatic cancer (RR, 2.37; 95% CI, 1.24 to 4.50; P = 8.7 x 10-3), and male breast cancer (RR, 7.34; 95% CI, 1.28 to 42.18; P = 2.6 3 1022). There was no evidence for increased risks of prostate or colorectal cancer. The breast cancer RRs declined with age (P for trend = 2.0 x 10-3). After adjusting for family ascertainment, breast cancer risk estimates on the basis of multiple case families were similar to the estimates from families ascertained through population-based studies (P for difference = .41). On the basis of the combined data, the estimated risks to age 80 years were 53% (95% CI, 44% to 63%) for female breast cancer, 5% (95% CI, 2% to 10%) for ovarian cancer, 2%-3% (95% CI females, 1% to 4%; 95% CI males, 2% to 5%) for pancreatic cancer, and 1% (95% CI, 0.2% to 5%) for male breast cancer. CONCLUSION These results confirm PALB2 as a major breast cancer susceptibility gene and establish substantial associations between germline PALB2 PVs and ovarian, pancreatic, and male breast cancers. These findings will facilitate incorporation of PALB2 into risk prediction models and optimize the clinical cancer ri

PURPOSE: To estimate age-specific relative and absolute cancer risks of breast cancer and to estimate risks of ovarian, pancreatic, male breast, prostate, and colorectal cancers associated with germline PALB2 pathogenic variants (PVs) because these risks have not been extensively characterized. METHODS: We analyzed data from 524 families with PALB2 PVs from 21 countries. Complex segregation analysis was used to estimate relative risks (RRs; relative to country-specific population incidences) and absolute risks of cancers. The models allowed for residual familial aggregation of breast and ovarian cancer and were adjusted for the family-specific ascertainment schemes. RESULTS: We found associations between PALB2 PVs and risk of female breast cancer (RR, 7.18; 95% CI, 5.82 to 8.85; P = 6.5 × 10-76), ovarian cancer (RR, 2.91; 95% CI, 1.40 to 6.04; P = 4.1 × 10-3), pancreatic cancer (RR, 2.37; 95% CI, 1.24 to 4.50; P = 8.7 × 10-3), and male breast cancer (RR, 7.34; 95% CI, 1.28 to 42.18; P = 2.6 × 10-2). There was no evidence for increased risks of prostate or colorectal cancer. The breast cancer RRs declined with age (P for trend = 2.0 × 10-3). After adjusting for family ascertainment, breast cancer risk estimates on the basis of multiple case families were similar to the estimates from families ascertained through population-based studies (P for difference = .41). On the basis of the combined data, the estimated risks to age 80 years were 53% (95% CI, 44% to 63%) for female breast cancer, 5% (95% CI, 2% to 10%) for ovarian cancer, 2%-3% (95% CI females, 1% to 4%; 95% CI males, 2% to 5%) for pancreatic cancer, and 1% (95% CI, 0.2% to 5%) for male breast cancer. CONCLUSION: These results confirm PALB2 as a major breast cancer susceptibility gene and establish substantial associations between germline PALB2 PVs and ovarian, pancreatic, and male breast cancers. These findings will facilitate incorporation of PALB2 into risk prediction models and optimize the clinical cance

Background and objectives: The study of age-related facial shape changes across different populations and sexes requires new multivariate tools to disentangle different sources of variations present in 3D facial images. Here we wish to use a multivariate technique called multilevel principal components analysis (mPCA) to study three-dimensional facial growth in adolescents. Methods: These facial shapes were captured for Welsh and Finnish subjects (both male and female) at multiple ages from 12 to 17 years old (i.e., repeated-measures data). 1000 “dense” 3D points were defined regularly for each shape by using a deformable template via “meshmonk” software. A three-level model was used here, namely: level 1 (sex/ethnicity); level 2, all “subject” variations excluding sex, ethnicity, and age; and level 3, age. The technicalities underpinning the mPCA method are presented in Appendices. Results: Eigenvalues via mPCA predicted that: level 1 (ethnicity/sex) contained 7.9% of variation; level 2 contained 71.5%; and level 3 (age) contained 20.6%. The results for the eigenvalues via mPCA followed a similar pattern to those results of single-level PCA. Results for modes of variation made sense, where effects due to ethnicity, sex, and age were reflected in modes at appropriate levels of the model. Standardised scores at level 1 via mPCA showed much stronger differentiation between sex and ethnicity groups than results of single-level PCA. Results for standardised scores from both single-level PCA and mPCA at level 3 indicated that females had different average “trajectories” with respect to these scores than males, which suggests that facial shape matures in different ways for males and females. No strong evidence of differences in growth patterns between Finnish and Welsh subjects was observed. Conclusions: mPCA results agree with existing research relating to the general process of facial changes in adolescents with respect to age quoted in the literature. They sup