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Purpose To investigate relationships between blood pressure and the thickness of single retinal layers in the macula. Methods Participants of the population-based Beijing Eye Study, free of retinal or optic nerve disease, underwent medical and ophthalmological examinations including optical coherence tomographic examination of the macula. Applying a multiple-surface segmentation solution, we automatically segmented the retina into its various layers. Results The study included 2237 participants (mean age 61.8±8.4 years, range 50–93 years). Mean thicknesses of the retinal nerve fibre layer (RNFL), ganglion cell layer (GCL), inner plexiform layer, inner nuclear layer (INL), outer plexiform layer, outer nuclear layer/external limiting membrane, ellipsoid zone, photoreceptor outer segments (POS) and retinal pigment epithelium–Bruch membrane were 31.1±2.3 µm, 39.7±3.5 µm, 38.4±3.3 µm, 34.8±2.0 µm, 28.1±3.0 µm, 79.2±7.3 µm, 22.9±0.6 µm, 19.2±3.3 µm and 20.7±1.4 µm, respectively. In multivariable analysis, higher systolic blood pressure (SBP) and diastolic blood pressure (DBP) were associated with thinner GCL and thicker INL, after adjusting for age, sex and axial length (all p<0.0056). Higher SBP was additionally associated with thinner POS and higher DBP with thinner RNFL. For an elevation of SBP/DBP by 10 mm Hg, the RNFL, GCL, INL and POS changed by 2.0, 3.0, 1.5 and 2.0 µm, respectively. Conclusions Thickness of RNFL, GCL and POS was inversely and INL thickness was positively associated with higher blood pressure, while the thickness of the other retinal layers was not significantly correlated with blood pressure. The findings may be helpful for refinement of the morphometric detection of retinal diseases. 

Segmentation of multiple surfaces in optical coherence tomography (OCT) images is a challenging problem, further complicated by the frequent presence of weak boundaries, varying layer thicknesses, and mutual influence between adjacent surfaces. The traditional graph-based optimal surface segmentation method has proven its effectiveness with its ability to capture various surface priors in a uniform graph model. However, its efficacy heavily relies on handcrafted features that are used to define the surface cost for the “goodness” of a surface. Recently, deep learning (DL) is emerging as a powerful tool for medical image segmentation thanks to its superior feature learning capability. Unfortunately, due to the scarcity of training data in medical imaging, it is nontrivial for DL networks to implicitly learn the global structure of the target surfaces, including surface interactions. This study proposes to parameterize the surface cost functions in the graph model and leverage DL to learn those parameters. The multiple optimal surfaces are then simultaneously detected by minimizing the total surface cost while explicitly enforcing the mutual surface interaction constraints. The optimization problem is solved by the primal-dual interior-point method (IPM), which can be implemented by a layer of neural networks, enabling efficient end-to-end training of the whole network. Experiments on spectral-domain optical coherence tomography (SD-OCT) retinal layer segmentation demonstrated promising segmentation results with sub-pixel accuracy. 

A bstract We report on a measurement of the $$ {\Lambda}_c^{+} $$ Λ c + to D 0 production ratio in peripheral PbPb collisions at $$ \sqrt{s_{\textrm{NN}}} $$ s NN = 5 . 02 TeV with the LHCb detector in the forward rapidity region 2 < y < 4 . 5. The $$ {\Lambda}_c^{+} $$ Λ c + ( D 0 ) hadrons are reconstructed via the decay channel $$ {\Lambda}_c^{+} $$ Λ c + → pK − π + ( D 0 → K − π + ) for 2 < p T < 8 GeV/ c and in the centrality range of about 65–90%. The results show no significant dependence on p T , y or the mean number of participating nucleons. They are also consistent with similar measurements obtained by the LHCb collaboration in pPb and Pbp collisions at $$ \sqrt{s_{\textrm{NN}}} $$ s NN = 5 . 02 TeV. The data agree well with predictions from PYTHIA in pp collisions at $$ \sqrt{s} $$ s = 5 TeV but are in tension with predictions of the Statistical Hadronization model. 

A bstract A search for the lepton-flavour violating decays B 0 → K *0 μ ± e ∓ and $$ {B}_s^0 $$ B s 0 → ϕμ ± e ∓ is presented, using proton-proton collision data collected by the LHCb detector at the LHC, corresponding to an integrated luminosity of 9 fb − 1 . No significant signals are observed and upper limits of $$ {\displaystyle \begin{array}{c}\mathcal{B}\left({B}^0\to {K}^{\ast 0}{\mu}^{+}{e}^{-}\right)<5.7\times {10}^{-9}\left(6.9\times {10}^{-9}\right),\\ {}\mathcal{B}\left({B}^0\to {K}^{\ast 0}{\mu}^{-}{e}^{+}\right)<6.8\times {10}^{-9}\left(7.9\times {10}^{-9}\right),\\ {}\mathcal{B}\left({B}^0\to {K}^{\ast 0}{\mu}^{\pm }{e}^{\mp}\right)<10.1\times {10}^{-9}\left(11.7\times {10}^{-9}\right),\\ {}\mathcal{B}\left({B}_s^0\to \phi {\mu}^{\pm }{e}^{\mp}\right)<16.0\times {10}^{-9}\left(19.8\times {10}^{-9}\right)\end{array}} $$ B B 0 → K ∗ 0 μ + e − < 5.7 × 10 − 9 6.9 × 10 − 9 , B B 0 → K ∗ 0 μ − e + < 6.8 × 10 − 9 7.9 × 10 − 9 , B B 0 → K ∗ 0 μ ± e ∓ < 10.1 × 10 − 9 11.7 × 10 − 9 , B B s 0 → ϕ μ ± e ∓ < 16.0 × 10 − 9 19.8 × 10 − 9 are set at 90% (95%) confidence level. These results constitute the world’s most stringent limits to date, with the limit on the decay $$ {B}_s^0 $$ B s 0 → ϕμ ± e ∓ the first being set. In addition, limits are reported for scalar and left-handed lepton-flavour violating New Physics scenarios. 

A bstract A first search for the lepton-flavour violating decays B 0 → K *0 τ ± μ ∓ is presented. The analysis is performed using a sample of proton-proton collision data, collected with the LHCb detector at centre-of-mass energies of 7, 8 and 13 TeV between 2011 and 2018, corresponding to an integrated luminosity of 9 fb − 1 . No significant signal is observed, and upper limits on the branching fractions are determined to be $$ \mathcal{B}\left({B}^0\to {K}^{\ast 0}{\tau}^{+}{\mu}^{-}\right)<1.0(1.2)\times {10}^{-5} $$ B B 0 → K ∗ 0 τ + μ − < 1.0 1.2 × 10 − 5 and $$ \mathcal{B}\left({B}^0\to {K}^{\ast 0}{\tau}^{-}{\mu}^{+}\right)<8.2(9.8)\times {10}^{-6} $$ B B 0 → K ∗ 0 τ − μ + < 8.2 9.8 × 10 − 6 at the 90% (95%) confidence level. 

A bstract An amplitude analysis of the D + → π − π + π + decay is performed with a sample corresponding to 1.5 fb − 1 of integrated luminosity of pp collisions at a centre-of-mass energy $$ \sqrt{s} $$ s = 8 TeV collected by the LHCb detector in 2012. The sample contains approximately six hundred thousand candidates with a signal purity of 95%. The resonant structure is studied through a fit to the Dalitz plot where the π − π + S-wave amplitude is extracted as a function of π − π + mass, and spin-1 and spin-2 resonances are included coherently through an isobar model. The S-wave component is found to be dominant, followed by the ρ (770) 0 π + and f 2 (1270) π + components. A small contribution from the ω (782) → π − π + decay is seen for the first time in the D + → π − π + π + decay.