Shape parametrization of bio-mechanical finite element models based on medical images

The main objective of this study is to combine the statistical shape analysis with a morphing procedure in order to generate shape-parametric finite element models of tissues and organs and to explore the reliability and the limitations of this approach when applied to databases of real medical images. As classical statistical shape models are not always adapted to the morphing procedure, a new registration method was developed in order to maximize the morphing efficiency. The method was compared to the traditional iterative thin plate spline (iTPS). Two data sets of 33 proximal femora shapes and 385 liver shapes were used for the comparison. The principal component analysis was used to get the principal morphing modes. In terms of anatomical shape reconstruction (evaluated through the criteria of generalization, compactness and specificity), our approach compared fairly well to the iTPS method, while performing remarkably better in terms of mesh quality, since it was less prone to generate invalid meshes in the interior. This was particularly true in the liver case. Such methodology offers a potential application for the generation of automated finite element (FE) models from medical images. Parametrized anatomical models can also be used to assess the influence of inter-patient variability on the biomechanical response of the tissues. Indeed, thanks to the shape parametrization the user would easily have access to a valid FE model for any shape belonging to the parameters subspace

A model order reduction approach to create patient-specific mechanical models of human liver in computational medicine applications.

Background and objective: This paper focuses on computer simulation aspects of Digital Twin models in the medical framework. In particular, it addresses the need of fast and accurate simulators for the mechanical response at tissue and organ scale and the capability of integrating patient-specific anatomy from medical images to pinpoint the individual variations from standard anatomical models. Methods: We propose an automated procedure to create mechanical models of the human liver with patient-specific geometry and real time capabilities. The method hinges on the use of Statistical Shape Analysis to extract the relevant anatomical features from a database of medical images and Model Order Reduction to compute an explicit parametric solution for the mechanical response as a function of such features. The Sparse Subspace Learning, coupled with a Finite Element solver, was chosen to create low-rank solutions using a non-intrusive sparse sampling of the feature space. Results: In the application presented in the paper, the statistical shape model was trained on a database of 385 three dimensional liver shapes, extracted from medical images, in order to create a parametrized representation of the liver anatomy. This parametrization and an additional parameter describing the breathing motion in linear elasticity were then used as input in the reduced order model. Results show a consistent agreement with the high fidelity Finite Element models built from liver images that were excluded from the training dataset. However, we evidence in the discussion the difficulty of having compact shape parametrizations arising from the extreme variability of the shapes found in the dataset and we propose potential strategies to tackle this issue. Conclusions: A method to represent patient-specific real-time liver deformations during breathing is proposed in linear elasticity. Since the proposed method does not require any adaptation to the direct Finite Element solver used in the training phase, the procedure can be easily extended to more complex non-linear constitutive behaviors - such as hyperelasticity - and more general load cases. Therefore it can be integrated with little intrusiveness to generic simulation software including more sophisticated and realistic models

Brief communication: Chronic undernutrition is associated with higher mucosal antibody levels among ariaal infants of northern kenya

The immune activation that occurs with infection diverts energy from growth and can contribute to poor nutritional outcomes in developing infants and children. This study investigates the association between salivary immunoglobulin A (IgA) levels and growth outcomes among Ariaal infants of northern Kenya. The Ariaal are a group of settled northern Kenyan pastoralists who are under considerable nutritional stress. Two hundred and thirty‐nine breastfeeding Ariaal infants were recruited into the study and underwent anthropometric measurement and saliva collection, with mothers providing individual and household characteristics for them via questionnaire. Infant saliva samples were analyzed with an ELISA for IgA in the United States. Infant anthropometric measurements were converted to height‐for‐age z ‐scores (HAZ) using the WHO Child Growth Standards. Based on multivariate models performed in SAS 9.2 two main results emerge: 1) low HAZ, an indicator of chronic undernutrition, was significantly associated with higher IgA concentration (β = −0.12, P = 0.050) and 2) boys had significantly higher IgA levels than girls (β = 0.25, P = 0.039). Although there was not a significant interactive effect between HAZ and sex, the two variables confound each other, with boys having significantly lower HAZ values than girls do. In addition, maternal breastmilk IgA was significantly associated with infant salivary IgA, indicating that maternal effects play a role in infant IgA development. Future research will unravel the three‐way association between sex, stunting, and immune function in the Ariaal community. Am J PhyAnthropol 2012. © Wiley Periodicals, Inc.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/93535/1/22108_ftp.pd

Inventor Migration and Knowledge Flows: A Two-Way Communication Channel ?

This paper documents the influence of networks of highly skilled migrants on the international diffusion of knowledge – particularly those with degrees and occupations in science, technology, engineering and mathematics. It investigates knowledge inflows to host countries brought in by skilled immigrants. It then explores knowledge feedback to home countries generated by these migrants. We test our hypotheses in a country-pair gravity model setting, for the period 1990–2010, using patent citations across countries to measure international knowledge diffusion. Our results confirm our hypotheses on the positive impact of skilled migrants on knowledge flows to host and home countries. However, the former are not robust to instrumental variables and country-pair fixed-effects, and only matter in certain contexts: when the sending countries are developing nations and for knowledge diffusion within the boundaries of multinationals

Genetic Dissection of Acute Ethanol Responsive Gene Networks in Prefrontal Cortex: Functional and Mechanistic Implications

Background Individual differences in initial sensitivity to ethanol are strongly related to the heritable risk of alcoholism in humans. To elucidate key molecular networks that modulate ethanol sensitivity we performed the first systems genetics analysis of ethanol-responsive gene expression in brain regions of the mesocorticolimbic reward circuit (prefrontal cortex, nucleus accumbens, and ventral midbrain) across a highly diverse family of 27 isogenic mouse strains (BXD panel) before and after treatment with ethanol. Results Acute ethanol altered the expression of ~2,750 genes in one or more regions and 400 transcripts were jointly modulated in all three. Ethanol-responsive gene networks were extracted with a powerful graph theoretical method that efficiently summarized ethanol\u27s effects. These networks correlated with acute behavioral responses to ethanol and other drugs of abuse. As predicted, networks were heavily populated by genes controlling synaptic transmission and neuroplasticity. Several of the most densely interconnected network hubs, including Kcnma1 and Gsk3β, are known to influence behavioral or physiological responses to ethanol, validating our overall approach. Other major hub genes like Grm3, Pten and Nrg3 represent novel targets of ethanol effects. Networks were under strong genetic control by variants that we mapped to a small number of chromosomal loci. Using a novel combination of genetic, bioinformatic and network-based approaches, we identified high priority cis-regulatory candidate genes, including Scn1b,Gria1, Sncb and Nell2. Conclusions The ethanol-responsive gene networks identified here represent a previously uncharacterized intermediate phenotype between DNA variation and ethanol sensitivity in mice. Networks involved in synaptic transmission were strongly regulated by ethanol and could contribute to behavioral plasticity seen with chronic ethanol. Our novel finding that hub genes and a small number of loci exert major influence over the ethanol response of gene networks could have important implications for future studies regarding the mechanisms and treatment of alcohol use disorders

Mortality and pulmonary complications in patients undergoing surgery with perioperative SARS-CoV-2 infection: an international cohort study

Background: The impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on postoperative recovery needs to be understood to inform clinical decision making during and after the COVID-19 pandemic. This study reports 30-day mortality and pulmonary complication rates in patients with perioperative SARS-CoV-2 infection. Methods: This international, multicentre, cohort study at 235 hospitals in 24 countries included all patients undergoing surgery who had SARS-CoV-2 infection confirmed within 7 days before or 30 days after surgery. The primary outcome measure was 30-day postoperative mortality and was assessed in all enrolled patients. The main secondary outcome measure was pulmonary complications, defined as pneumonia, acute respiratory distress syndrome, or unexpected postoperative ventilation. Findings: This analysis includes 1128 patients who had surgery between Jan 1 and March 31, 2020, of whom 835 (74·0%) had emergency surgery and 280 (24·8%) had elective surgery. SARS-CoV-2 infection was confirmed preoperatively in 294 (26·1%) patients. 30-day mortality was 23·8% (268 of 1128). Pulmonary complications occurred in 577 (51·2%) of 1128 patients; 30-day mortality in these patients was 38·0% (219 of 577), accounting for 81·7% (219 of 268) of all deaths. In adjusted analyses, 30-day mortality was associated with male sex (odds ratio 1·75 [95% CI 1·28–2·40], p\textless0·0001), age 70 years or older versus younger than 70 years (2·30 [1·65–3·22], p\textless0·0001), American Society of Anesthesiologists grades 3–5 versus grades 1–2 (2·35 [1·57–3·53], p\textless0·0001), malignant versus benign or obstetric diagnosis (1·55 [1·01–2·39], p=0·046), emergency versus elective surgery (1·67 [1·06–2·63], p=0·026), and major versus minor surgery (1·52 [1·01–2·31], p=0·047). Interpretation: Postoperative pulmonary complications occur in half of patients with perioperative SARS-CoV-2 infection and are associated with high mortality. Thresholds for surgery during the COVID-19 pandemic should be higher than during normal practice, particularly in men aged 70 years and older. Consideration should be given for postponing non-urgent procedures and promoting non-operative treatment to delay or avoid the need for surgery. Funding: National Institute for Health Research (NIHR), Association of Coloproctology of Great Britain and Ireland, Bowel and Cancer Research, Bowel Disease Research Foundation, Association of Upper Gastrointestinal Surgeons, British Association of Surgical Oncology, British Gynaecological Cancer Society, European Society of Coloproctology, NIHR Academy, Sarcoma UK, Vascular Society for Great Britain and Ireland, and Yorkshire Cancer Research

Beuk (Fagus sylvatica L.) in het Nederlandse deel van het NW-Europees diluvium.

10.2139/ssrn.3707087SSRN Electronic Journal112United State

Cryptosporidium rhoptry effector protein ROP1 injected during invasion targets the host cytoskeletal modulator LMO7

The parasite Cryptosporidium invades and replicates in intestinal epithelial cells and is a leading cause of diarrheal disease and early childhood mortality. The molecular mechanisms that underlie infection and pathogenesis are largely unknown. Here we delineate the events of host cell invasion and uncover a mechanism unique to Cryptosporidium. We developed a screen to identify parasite effectors, finding injection of multiple parasite proteins into the host from the rhoptry organelle. These factors are targeted to diverse locations within the host cell and its interface with the parasite. One identified effector, ROP1 accumulates in the terminal web of enterocytes through direct interaction with the host protein LMO7, an organizer of epithelial cell polarity and cell-cell adhesion. Genetic ablation of LMO7 or ROP1 in mice or parasites respectively, impacts parasite burden in vivo in opposite ways. Taken together, these data provide molecular insight into how Cryptosporidium manipulates its intestinal host niche