Obesity and periodontal disease in diabetic pregnant women Obesidade e doença periodontal em gestantes diabéticas

This cross-sectional study investigated the impact of pregestational overweight and obesity on periodontal status of patients with gestational diabetes mellitus (GDM). Sixty pregnant women with gestational diabetes mellitus (GDM) were recruited for the study. According to the pregestational body mass index (BMI), patients were classified into 3 groups: normal, overweight or obese. The periodontal assessment parameters were the presence of gingival bleeding (GB) and bleeding on probing (BOP) per tooth. Clinical attachment loss (CAL) was assessed per tooth and classified according to following values: 1) absence of attachment loss; 2) between 1 and 2 mm, 3) between 3 and 5 mm; and 4) CAL > 6 mm. The means of individual percentage of teeth with GB and BOP and the means of the individual classified values of CAL were compared through ANOVA. Differences between the groups were established through post hoc Bonferroni test for multiple comparisons (p < 0.05). The analysis revealed significant differences between the normal group and the obese group considering GB (52.76% &plusmn; 27.99% and 78.85% &plusmn; 27.44%, respectively) and CAL (2.21 &plusmn; 0.41 and 2.61 &plusmn; 0.54, respectively). Although an increase was found in BOP as the BMI increased (ranging from 55.65% to 75.31%), no statistically significant differences were found among the groups. Patients with GDM and pregestational obesity had significantly more gingivitis and periodontal attachment loss that those with normal pregestational BMI. Periodontal treatment should be considered in the establishment of future recommendations for metabolic control for this special group of patients.<br>O objetivo do presente estudo foi examinar o efeito da massa corporal prévia à gestação (IMC - índice de massa corpórea) sobre o periodonto de pacientes com diabete mellitus gestacional (DMG). A amostra constituiu-se de 60 gestantes classificadas em 3 grupos segundo o IMC: normal, sobrepeso ou obeso. Os parâmetros de avaliação periodontal foram sangramento gengival (SG), sangramento à sondagem (SS) e perda de inserção clínica periodontal (PI) categorizada de acordo com os seguintes valores: 1) correspondente à ausência de perda de inserção; 2) PI entre 1 e 2 mm, 3) PI entre 3 e 5 mm; e 4) PI > 6 mm. Médias das porcentagens dos dentes com SG e SS e as médias dos valores categorizados, por dente, da perda de inserção foram comparadas por meio do teste ANOVA e as diferenças entre os grupos foram estabelecidas por meio do teste post hoc de Bonferroni para comparações múltiplas (p < 0,05). Diferenças estatisticamente significantes foram identificadas entre o grupo normal e obeso com relação às médias percentuais da presença de SG (52,76 &plusmn; 27,99% e 78,85 &plusmn; 27,44%, respectivamente) e às médias da categorização da PI (2,21 &plusmn; 0,41 mm e 2,61 &plusmn; 0,54 mm, respectivamente). Embora tenha se observado aumento no percentual médio de SS à medida do incremento do IMC, não foram observadas diferenças estatisticamente significantes entre os grupos, e a variação foi de 55,65% a 75,31%. Pacientes com DMG e obesidade pré-gestacional apresentaram significativamente mais gengivite e perda de inserção periodontal que aquelas com IMC pré-gestacional normal. O tratamento periodontal deve ser considerado na determinação de futuras recomendações de controle metabólico para esse grupo especial de pacientes

Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge

Gliomas are the most common primary brain malignancies, with different degrees of aggressiveness, variable prognosis and various heterogeneous histologic sub-regions, i.e., peritumoral edematous/invaded tissue, necrotic core, active and non-enhancing core. This intrinsic heterogeneity is also portrayed in their radio-phenotype, as their sub-regions are depicted by varying intensity profiles disseminated across multi-parametric magnetic resonance imaging (mpMRI) scans, reflecting varying biological properties. Their heterogeneous shape, extent, and location are some of the factors that make these tumors difficult to resect, and in some cases inoperable. The amount of resected tumor is a factor also considered in longitudinal scans, when evaluating the apparent tumor for potential diagnosis of progression. Furthermore, there is mounting evidence that accurate segmentation of the various tumor sub-regions can offer the basis for quantitative image analysis towards prediction of patient overall survival. This study assesses the state-of-the-art machine learning (ML) methods used for brain tumor image analysis in mpMRI scans, during the last seven instances of the International Brain Tumor Segmentation (BraTS) challenge, i.e., 2012-2018. Specifically, we focus on i) evaluating segmentations of the various glioma sub-regions in pre-operative mpMRI scans, ii) assessing potential tumor progression by virtue of longitudinal growth of tumor sub-regions, beyond use of the RECIST/RANO criteria, and iii) predicting the overall survival from pre-operative mpMRI scans of patients that underwent gross total resection. Finally, we investigate the challenge of identifying the best ML algorithms for each of these tasks, considering that apart from being diverse on each instance of the challenge, the multi-institutional mpMRI BraTS dataset has also been a continuously evolving/growing dataset

Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge

Gliomas are the most common primary brain malignancies, with different degrees of aggressiveness, variable prognosis and various heterogeneous histologic sub-regions, i.e., peritumoral edematous/invaded tissue, necrotic core, active and non-enhancing core. This intrinsic heterogeneity is also portrayed in their radio-phenotype, as their sub-regions are depicted by varying intensity profiles disseminated across multi-parametric magnetic resonance imaging (mpMRI) scans, reflecting varying biological properties. Their heterogeneous shape, extent, and location are some of the factors that make these tumors difficult to resect, and in some cases inoperable. The amount of resected tumor is a factor also considered in longitudinal scans, when evaluating the apparent tumor for potential diagnosis of progression. Furthermore, there is mounting evidence that accurate segmentation of the various tumor sub-regions can offer the basis for quantitative image analysis towards prediction of patient overall survival. This study assesses the state-of-the-art machine learning (ML) methods used for brain tumor image analysis in mpMRI scans, during the last seven instances of the International Brain Tumor Segmentation (BraTS) challenge, i.e., 2012-2018. Specifically, we focus on i) evaluating segmentations of the various glioma sub-regions in pre-operative mpMRI scans, ii) assessing potential tumor progression by virtue of longitudinal growth of tumor sub-regions, beyond use of the RECIST/RANO criteria, and iii) predicting the overall survival from pre-operative mpMRI scans of patients that underwent gross total resection. Finally, we investigate the challenge of identifying the best ML algorithms for each of these tasks, considering that apart from being diverse on each instance of the challenge, the multi-institutional mpMRI BraTS dataset has also been a continuously evolving/growing dataset

Search for pair production of vector-like quarks in leptonic final states in proton-proton collisions at s \sqrt{s} = 13 TeV

A search is presented for vector-like T and B quark-antiquark pairs produced in proton-proton collisions at a center-of-mass energy of 13 TeV. Data were collected by the CMS experiment at the CERN LHC in 2016–2018, with an integrated luminosity of 138 fb$^{−1}$. Events are separated into single-lepton, same-sign charge dilepton, and multi-lepton channels. In the analysis of the single-lepton channel a multilayer neural network and jet identification techniques are employed to select signal events, while the same-sign dilepton and multilepton channels rely on the high-energy signature of the signal to distinguish it from standard model backgrounds. The data are consistent with standard model background predictions, and the production of vector-like quark pairs is excluded at 95% confidence level for T quark masses up to 1.54 TeV and B quark masses up to 1.56 TeV, depending on the branching fractions assumed, with maximal sensitivity to decay modes that include multiple top quarks. The limits obtained in this search are the strongest limits to date for $\textrm{T}\overline{\textrm{T}}$ production, excluding masses below 1.48 TeV for all decays to third generation quarks, and are the strongest limits to date for $\textrm{B}\overline{\textrm{B}}$ production with B quark decays to tW.[graphic not available: see fulltext

Search for CPCP violation in ttH and tH production in multilepton channels in proton-proton collisions at s\sqrt{s} = 13 TeV

International audienceThe charge-parity (CP) structure of the Yukawa interaction between the Higgs (H) boson and the top quark is measured in a data sample enriched in the t$\overline{\textrm{t}}$H and tH associated production, using 138 fb$^{−1}$ of data collected in proton-proton collisions at $\sqrt{s}$ = 13 TeV by the CMS experiment at the CERN LHC. The study targets events where the H boson decays via H → WW or H → ττ and the top quarks decay via t → Wb: the W bosons decay either leptonically or hadronically, and final states characterized by the presence of at least two leptons are studied. Machine learning techniques are applied to these final states to enhance the separation of CP -even from CP -odd scenarios. Two-dimensional confidence regions are set on κ$_{t}$ and $\overset{\sim }{\kappa } _{t}$, which are respectively defined as the CP -even and CP -odd top-Higgs Yukawa coupling modifiers. No significant fractional CP -odd contributions, parameterized by the quantity |${f}_{CP}^{\textrm{Htt}}$| are observed; the parameter is determined to be |${f}_{CP}^{\textrm{Htt}}$| = 0.59 with an interval of (0.24, 0.81) at 68% confidence level. The results are combined with previous results covering the H → ZZ and H → γγ decay modes, yielding two- and one-dimensional confidence regions on κ$_{t}$ and $\overset{\sim }{\kappa } _{t}$, while |${f}_{CP}^{\textrm{Htt}}$| is determined to be |${f}_{CP}^{\textrm{Htt}}$| = 0.28 with an interval of |${f}_{CP}^{\textrm{Htt}}$| < 0.55 at 68% confidence level, in agreement with the standard model CP -even prediction of |${f}_{CP}^{\textrm{Htt}}$| = 0.[graphic not available: see fulltext

Search for a charged Higgs boson decaying into a heavy neutral Higgs boson and a W boson in proton-proton collisions at s=\sqrt{s} = 13 TeV

A search for a charged Higgs boson ${\mathrm{\tilde{H}^{\pm}}}$ decaying into a heavy neutral Higgs boson H and a W boson is presented. The analysis targets the H decay into a pair of tau leptons with at least one of them decaying hadronically and with an additional electron or muon present in the event. The search is based on proton-proton collision data recorded by the CMS experiment during 2016-2018 at $\sqrt{s} =$ 13 TeV, corresponding to an integrated luminosity of 138 fb$^{-1}$. The data are consistent with standard model background expectations. Upper limits at 95% confidence level are set on the product of the cross section and branching fraction for an ${\mathrm{\tilde{H}^{\pm}}}$ in the mass range of 300-700 GeV, assuming an H with a mass of 200 GeV. The observed limits range from 0.085 pb for an ${\mathrm{\tilde{H}^{\pm}}}$ mass of 300 GeV to 0.019 pb for a mass of 700 GeV. These are the first limits on ${\mathrm{\tilde{H}^{\pm}}}$ production in the ${\mathrm{\tilde{H}^{\pm}}} \to \mathrm{H} \mathrm{W^{\pm}}$ decay channel at the LHC.A search for a charged Higgs boson H$^{±}$ decaying into a heavy neutral Higgs boson H and a W boson is presented. The analysis targets the H decay into a pair of tau leptons with at least one of them decaying hadronically and with an additional electron or muon present in the event. The search is based on proton-proton collision data recorded by the CMS experiment during 2016–2018 at $\sqrt{s}$ = 13 TeV, corresponding to an integrated luminosity of 138 fb$^{−1}$. The data are consistent with standard model background expectations. Upper limits at 95% confidence level are set on the product of the cross section and branching fraction for an H$^{±}$ in the mass range of 300–700 GeV, assuming an H with a mass of 200 GeV. The observed limits range from 0.085 pb for an H$^{±}$ mass of 300 Ge V to 0.019 pb for a mass of 700 GeV. These are the first limits on H$^{±}$ production in the H$^{±}$→ HW$^{±}$ decay channel at the LHC.[graphic not available: see fulltext]A search for a charged Higgs boson H$^\pm$ decaying into a heavy neutral Higgs boson H and a W boson is presented. The analysis targets the H decay into a pair of tau leptons with at least one of them decaying hadronically and with an additional electron or muon present in the event. The search is based on proton-proton collision data recorded by the CMS experiment during 2016-2018 at $\sqrt{s}$ = 13 TeV, corresponding to an integrated luminosity of 138 fb$^{-1}$. The data are consistent with standard model background expectations. Upper limits at 95% confidence level are set on the product of the cross section and branching fraction for an H$^\pm$ in the mass range of 300-700 GeV, assuming an H with a mass of 200 GeV. The observed limits range from 0.085 pb for an H$^\pm$ mass of 300 GeV to 0.019 pb for a mass of 700 GeV. These are the first limits on H$^\pm$ production in the H$^\pm$ $\to$ HW$^\pm$ decay channel at the LHC

Measurement of the Higgs boson inclusive and differential fiducial production cross sections in the diphoton decay channel with pp collisions at s \sqrt{s} = 13 TeV

The measurements of the inclusive and differential fiducial cross sections of the Higgs boson decaying to a pair of photons are presented. The analysis is performed using proton-proton collisions data recorded with the CMS detector at the LHC at a centre-of-mass energy of 13 TeV and corresponding to an integrated luminosity of 137 fb$^{−1}$. The inclusive fiducial cross section is measured to be ${\sigma}_{\textrm{fid}}={73.4}_{-5.3}^{+5.4}{\left(\textrm{stat}\right)}_{-2.2}^{+2.4}\left(\textrm{syst}\right)$ fb, in agreement with the standard model expectation of 75.4 ± 4.1 fb. The measurements are also performed in fiducial regions targeting different production modes and as function of several observables describing the diphoton system, the number of additional jets present in the event, and other kinematic observables. Two double differential measurements are performed. No significant deviations from the standard model expectations are observed.[graphic not available: see fulltext

Search for resonant and nonresonant production of pairs of dijet resonances in proton-proton collisions at s \sqrt{s} = 13 TeV

A search for pairs of dijet resonances with the same mass is conducted in final states with at least four jets. Results are presented separately for the case where the four jet production proceeds via an intermediate resonant state and for nonresonant production. The search uses a data sample corresponding to an integrated luminosity of 138 fb$^{−1}$ collected by the CMS detector in proton-proton collisions at $\sqrt{s}$ = 13 TeV. Model-independent limits, at 95% confidence level, are reported on the production cross section of four-jet and dijet resonances. These first LHC limits on resonant pair production of dijet resonances via high mass intermediate states are applied to a signal model of diquarks that decay into pairs of vector-like quarks, excluding diquark masses below 7.6 TeV for a particular model scenario. There are two events in the tails of the distributions, each with a four-jet mass of 8 TeV and an average dijet mass of 2 TeV, resulting in local and global significances of 3.9 and 1.6 standard deviations, respectively, if interpreted as a signal. The nonresonant search excludes pair production of top squarks with masses between 0.50 TeV to 0.77 TeV, with the exception of a small interval between 0.52 and 0.58 TeV, for supersymmetric R-parity-violating decays to quark pairs, significantly extending previous limits. Here, the most significant excess above the predicted background occurs at an average dijet mass of 0.95 TeV, for which the local and global significances are 3.6 and 2.5 standard deviations, respectively.[graphic not available: see fulltext