Coumarin embryopathy in an extremely low birth weight infant associated with neonatal hepatitis and ocular malformations

Coumarin embryopathy (CE) is a well-documented sequelae of prenatal exposure to vitaminK antagonists. We report on a female premature infant (25weeks' gestation) born to a mother who had received phenprocoumon during pregnancy following mechanical heart valve replacement. The infant presented with impaired coagulation, intraventricular and minor parenchymal cerebral haemorrhages and midface hypoplasia typical of CE. In addition, there was hepatopathy with conjugated hyperbilirubinemia, elevated liver enzymes and repeated episodes of hypoglycemia upon attempts to discontinue glucose supplementation, all lasting for 4months. There was corneal opacity with anterior segment dygenesis in the left eye, and persistent pupillary membrane, cataract and persistent hyperplastic primary vitreous in the right eye. While liver disease is an uncommon but serious side effect of vitaminK antagonists, this is the first report describing neonatal hepatopathy as part of CE. In anticoagulation of pregnant women with mechanical heart valves, vitaminK antagonists should be used with utmost restrain

Circulatory response to blood gas pertubations

PURPOSE. To investigate the response of the optic nerve head and the choroidal circulation to blood gas perturbations in otherwise healthy subjects with a history of cold hands. METHODS. Thirty-five healthy subjects were selected and grouped according to the related history of cold hands. All 12 selected male subjects, aged 21 to 38 years (mean Ϯ SD ϭ 28 Ϯ 5.2 years) had a negative history of cold hands. Female subjects were almost equally divided between the groups with a negative (11 subjects, aged 18 -36 years; mean, 25.7 Ϯ 5.5) or positive (12 subjects, aged 19 -45 years; mean, 25 Ϯ 6.8) history of cold hands. Blood gas perturbations were created by having subjects breath a gas mixture consisting of 21% O 2 , 74% N 2 , and 5% CO 2 . The partial pressures pCO 2 and pO 2 were continuously monitored transcutaneously. Choroidal and optic nerve head blood flow response was evaluated by means of laser Doppler flowmetry. RESULTS. Systolic and diastolic blood pressure (SBP/DBP at baseline, three-group average: 111.2/71.9 mm Hg), heart rate (HR; 70.3 bpm), and intraocular pressure (IOP; 14.7 mm Hg) increased during the blood gas perturbation phase (123.1/77.7 mm Hg, 78.5 bpm, and 15.6 mm Hg, respectively) and returned to baseline in the recovery phase (109.9/73.4 mm Hg, 69.5 bpm, and 13.5 mm Hg, respectively). There was no difference between groups (one-way ANOVA of the percentage change from baseline for SBP, P ϭ 0.75; DBP, P ϭ 0.36; HR, P ϭ 0.95; and IOP, P ϭ 0.72). pCO 2 increased from 5.52 to 6.59 kPa and returned to 5.50 kPa. pO 2 increased from 10.64 to 13.12 kPa and returned to 10.73 kPa. Again, there was no difference between groups (one-way ANOVA for the percentage change: pCO 2 , P ϭ 0.17; pO 2 , P ϭ 0.78). In the women with vasospasm, optic nerve head blood flow increased 17.1% and the choroidal blood flow decreased Ϫ3.6%, whereas in the women and men without vasospasm the optic nerve head blood flow decreased Ϫ5.8% and -4.8%, and the choroidal blood flow increased 13.3% and 18.3%, respectively (two-way ANOVA interaction; P ϭ 0.001). CONCLUSIONS. The pCO 2 increase was accompanied by a pO 2 increase. Blood pressure and HR increased comparably in all groups, indicating sympathetic arousal. The women with vasospasm demonstrated an inverse response pattern of choroidal and optic nerve head circulation to blood gas perturbation compared with the women without vasospasm and compared with the men. (Invest Ophthalmol Vis Sci. 2005;46:3288 -3294

Convolutions in Overdrive: Maliciously Secure Convolutions for MPC

Machine learning (ML) has seen a strong rise in popularity in recent years and has become an essential tool for research and industrial applications. Given the large amount of high quality data needed and the often sensitive nature of ML data, privacy-preserving collaborative ML is of increasing importance. In this paper, we introduce new actively secure multiparty computation (MPC) protocols which are specially optimized for privacy-preserving machine learning applications. We concentrate on the optimization of (tensor) convolutions which belong to the most commonly used components in ML architectures, especially in convolutional neural networks but also in recurrent neural networks or transformers, and therefore have a major impact on the overall performance. Our approach is based on a generalized form of structured randomness that speeds up convolutions in a fast online phase. The structured randomness is generated with homomorphic encryption using adapted and newly constructed packing methods for convolutions, which might be of independent interest. Overall our protocols extend the state-of-the-art Overdrive family of protocols (Keller et al., EUROCRYPT 2018). We implemented our protocols on-top of MP-SPDZ (Keller, CCS 2020) resulting in a full-featured implementation with support for faster convolutions. Our evaluation shows that our protocols outperform state-of-the-art actively secure MPC protocols on ML tasks like evaluating ResNet50 by a factor of 3 or more. Benchmarks for depthwise convolutions show order-of-magnitude speed-ups compared to existing approaches

Multipars: Reduced-Communication MPC over Z2k

In recent years, actively secure SPDZ-like protocols for dishonest majority, like SPD$\mathbb Z_{2^k}$, Overdrive2k, and MHz2k, over base rings $\mathbb Z_{2^k}$ have become more and more efficient. In this paper, we present a new actively secure MPC protocol Multipars that outperforms these state-of-the-art protocols over $\mathbb Z_{2^k}$ by more than a factor of 2 in the two-party setup in terms of communication. Multipars is the first actively secure N-party protocol over $\mathbb Z_{2^k}$ that is based on linear homomorphic encryption (LHE) in the offline phase (instead of oblivious transfer or somewhat homomorphic encryption in previous works). The strong performance of Multipars relies on a new adaptive packing for BGV ciphertexts that allows us to reduce the parameter size of the encryption scheme and the overall communication cost. Additionally, we use modulus switching for further size reduction, a new type of enhanced CPA security over $\mathbb Z_{2^k}$, a truncation protocol for Beaver triples, and a new LHE-based offline protocol without sacrificing over $\mathbb Z_{2^k}$. We have implemented Multipars and therewith provide the fastest preprocessing phase over $\mathbb Z_{2^k}$. Our evaluation shows that Multipars offers at least a factor of 8 lower communication costs and up to a factor of 15 faster runtime in the WAN setting compared to the currently best available actively secure MPC implementation over $\mathbb Z_{2^k}$

Registration based assessment of femoral torsion for rotational osteotomies based on the contralateral anatomy

BACKGROUND Computer-assisted techniques for surgical treatment of femoral deformities have become increasingly important. In state-of-the-art 3D deformity assessments, the contralateral side is used as template for correction as it commonly represents normal anatomy. Contributing to this, an iterative closest point (ICP) algorithm is used for registration. However, the anatomical sections of the femur with idiosyncratic features, which allow for a consistent deformity assessment with ICP algorithms being unknown. Furthermore, if there is a side-to-side difference, this is not considered in error quantification. The aim of this study was to analyze the influence and value of the different sections of the femur in 3D assessment of femoral deformities based on the contralateral anatomy. MATERIAL AND METHODS 3D triangular surface models were created from CT of 100 paired femurs (50 cadavers) without pathological anatomy. The femurs were divided into sections of eponymous anatomy of a predefined percentage of the whole femoral length. A surface registration algorithm was applied to superimpose the ipsilateral on the contralateral side. We evaluated 3D femoral contralateral registration (FCR) errors, defined as difference in 3D rotation of the respective femoral section before and after registration to the contralateral side. To compare this method, we quantified the landmark-based femoral torsion (LB FT). This was defined as the intra-individual difference in overall femoral torsion using with a landmark-based method. RESULTS Contralateral rotational deviation ranged from 0° to 9.3° of the assessed femoral sections, depending on the section. Among the sections, the FCR error using the proximal diaphyseal area for registration was larger than any other sectional error. A combination of the lesser trochanter and the proximal diaphyseal area showed the smallest error. The LB FT error was significantly larger than any sectional error (p < 0.001). CONCLUSION We demonstrated that if the contralateral femur is used as reconstruction template, the built-in errors with the registration-based approach are smaller than the intraindividual difference of the femoral torsion between both sides. The errors are depending on the section and their idiosyncratic features used for registration. For rotational osteotomies a combination of the lesser trochanter and the proximal diaphyseal area sections seems to allow for a reconstruction with a minimal error

Intensity-based Choroidal Registration Using Regularized Block Matching

Detecting and monitoring changes in the human choroid play a crucial role in treating ocular diseases such as myopia. However, reliable segmentation of optical coherence tomography (OCT) images at the choroid-sclera interface (CSI) is notoriously difficult due to poor contrast, signal loss and OCT artefacts. In this paper we present blockwise registration of successive scans to improve stability also during complete loss of the CSI-signal. First, we formulated the problem as minimization of a regularized energy functional. Then, we tested our automated method for piecewise Intensity-based Choroidal rigid Registration using regularized block matching (ICR) on 20 OCT 3D-volume scan-rescan data set pairs. Finally, we used these data set pairs to determine the precision of our method, while the accuracy was determined by comparing our results with those using manually annotated scans

Overdrive LowGear 2.0: Reduced-Bandwidth MPC without Sacrifice

Some of the most efficient protocols for Multi-Party Computation (MPC) follow a two-phase approach where correlated randomness, in particular Beaver triples, is generated in the offline phase and then used to speed up the online phase. Recently, more complex correlations have been introduced to optimize certain operations even further, such as matrix triples for matrix multiplications. In this paper, our goal is to improve the efficiency of the triple generation in general and in particular for classical field values as well as matrix operations. To this end, we modify the Overdrive LowGear protocol to remove the costly sacrificing step and therewith reduce the round complexity and the bandwidth. We extend the state-of-the-art MP-SPDZ implementation with our new protocols and show that the new offline phase outperforms state-of-the-art protocols for the generation of Beaver triples and matrix triples. For example, we save 33 % in bandwidth compared to Overdrive LowGear

Long-Term Clinical and Multimodal Imaging Findings in Patients with Disseminated Mycobacterium Chimaera Infection

BACKGROUND To analyze long-term ophthalmic clinical and multimodal imaging findings of disseminated Mycobacterium (M.) chimaera infection after cardiothoracic surgery among the Swiss Cohort. METHODS Systemic and multimodal ophthalmic imaging and clinical findings including rate of recurrence were reviewed and correlated to a previously proposed classification system of choroidal lesions and classification of ocular disease. MAIN OUTCOMES MEASURES long-term clinical and multimodal ocular imaging findings of M. chimaera. RESULTS Twelve patients suffering from systemic infection from M. chimaera were included. Mean age at the first ophthalmic examination was 59 years (range from 48 to 66 years). Mean duration of the follow-up was 22.63 ± 17.8 months. All patients presented with bilateral chorioretinal lesions at baseline; 5 patients had additional signs, including optic disc swelling (2), choroidal neovascularization (1), retinal neovascularization (1) and cilioretinal vascular occlusion (1). Four recurrence events after discontinuation or adjustment of the antibiotic treatment were observed. Progressive choroiditis was seen in 5 patients under treatment, 4 of them deceased. CONCLUSIONS Expertise from ophthalmologists is not only relevant but also critical for the assessment of the adverse drug effect of antimycobacterial treatment along with monitoring therapeutic response and identifying recurrences

Uncovering of intraspecies macular heterogeneity in cynomolgus monkeys using hybrid machine learning optical coherence tomography image segmentation

The fovea is a depression in the center of the macula and is the site of the highest visual acuity. Optical coherence tomography (OCT) has contributed considerably in elucidating the pathologic changes in the fovea and is now being considered as an accompanying imaging method in drug development, such as antivascular endothelial growth factor and its safety profiling. Because animal numbers are limited in preclinical studies and automatized image evaluation tools have not yet been routinely employed, essential reference data describing the morphologic variations in macular thickness in laboratory cynomolgus monkeys are sparse to nonexistent. A hybrid machine learning algorithm was applied for automated OCT image processing and measurements of central retina thickness and surface area values. Morphological variations and the effects of sex and geographical origin were determined. Based on our findings, the fovea parameters are specific to the geographic origin. Despite morphological similarities among cynomolgus monkeys, considerable variations in the foveolar contour, even within the same species but from different geographic origins, were found. The results of the reference database show that not only the entire retinal thickness, but also the macular subfields, should be considered when designing preclinical studies and in the interpretation of foveal data

Validation of automated artificial intelligence segmentation of optical coherence tomography images

PURPOSE To benchmark the human and machine performance of spectral-domain (SD) and swept-source (SS) optical coherence tomography (OCT) image segmentation, i.e., pixel-wise classification, for the compartments vitreous, retina, choroid, sclera. METHODS A convolutional neural network (CNN) was trained on OCT B-scan images annotated by a senior ground truth expert retina specialist to segment the posterior eye compartments. Independent benchmark data sets (30 SDOCT and 30 SSOCT) were manually segmented by three classes of graders with varying levels of ophthalmic proficiencies. Nine graders contributed to benchmark an additional 60 images in three consecutive runs. Inter-human and intra-human class agreement was measured and compared to the CNN results. RESULTS The CNN training data consisted of a total of 6210 manually segmented images derived from 2070 B-scans (1046 SDOCT and 1024 SSOCT; 630 C-Scans). The CNN segmentation revealed a high agreement with all grader groups. For all compartments and groups, the mean Intersection over Union (IOU) score of CNN compartmentalization versus group graders' compartmentalization was higher than the mean score for intra-grader group comparison. CONCLUSION The proposed deep learning segmentation algorithm (CNN) for automated eye compartment segmentation in OCT B-scans (SDOCT and SSOCT) is on par with manual segmentations by human graders