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The human gut is a complex ecosystem consisting of hundreds of microbial species interacting with each other and with the human host. Mathematical models of the gut microbiome integrate our knowledge of this system and help to formulate hypotheses to explain observations. The generalized Lotka-Volterra model has been widely used for this purpose, but it does not describe interaction mechanisms and thus does not account for metabolic flexibility. Recently, models that explicitly describe gut microbial metabolite production and consumption have become popular. These models have been used to investigate the factors that shape gut microbial composition and to link specific gut microorganisms to changes in metabolite concentrations found in diseases. Here, we review how such models are built and what we have learned so far from their application to human gut microbiome data. In addition, we discuss current challenges of these models and how these can be addressed in the future., info:eu-repo/semantics/published

Sleep stage classification is an important tool for the diagnosis of sleep disorders. Because sleep staging has such a high impact on clinical outcome, it is important that it is done reliably. However, it is known that uncertainty exists in both expert scorers and automated models. On average, the agreement between human scorers is only 82.6%. In this study, we provide a theoretical framework to facilitate discussion and further analyses of uncertainty in sleep staging. To this end, we introduce two variants of uncertainty, known from statistics and the machine learning community: aleatoric and epistemic uncertainty. We discuss what these types of uncertainties are, why the distinction is useful, where they arise from in sleep staging, and provide recommendations on how this framework can improve sleep staging in the future.

135 p., ill., 1. APPENDIX: TERRITORIAL UNIT FOR ANALYSIS PURPOSES 6 -- 2. APPENDIX: MATURITY OF INTEGRATED CARE IN BELGIUM 7 -- 2.1. PROFESSIONAL’S ASSESSMENT OF INTEGRATED CARE 7 -- 2.1.1. Dutch survey 7 -- 2.1.2. French version of professional questionnaire available upon request 20 -- 2.1.3. Professional’s profiles 34 -- 2.1.4. Results of descriptive analysis by respondent’s professional category and level 38 -- 2.1.5. Scirocco spider diagrams per region 62 -- 2.2. ASSESSMENT OF MATURITY OF INTEGRATED CARE BY THE PATIENTS 63 -- 2.2.1. EuroQol Licence agreement for the EQ-5D-5L 63 -- 2.2.2. French patient questionnaire 67 -- 2.2.3. Dutch version of the patient questionnaire 71 -- 2.2.4. German version of the patient questionnaire 76 -- 2.2.5. Recruitment targets and response per geographical region 81 -- 2.2.6. Detailed list of participating recruiting organisations 82 -- 2.2.7. EQ – 5D -5L profiles 84 -- 2.2.8. EQ-5D-5L dimensions 86 -- 2.2.9. PACIC models 87 -- 3. APPENDIX: PROVIDER PAYMENT REFORMS – NARRATIVE LITERATURE REVIEW 89 -- 3.1. TYPES OF PAYMENT MECHANISMS 89 -- 3.2. PAY-FOR-PERFORMANCE (P4P) 91 -- 3.3. POPULATION-BASED PAYMENTS (INCLUDING ACCOUNTABLE CARE ORGANISATIONS (ACO)) 92 -- 3.4. BUNDLED PAYMENTS 99 -- 3.5. REFERENCE LIST OF THE LITERATURE REVIEW 102 -- 4. APPENDIX – TRAJECTORY OF CHANGE 107 -- 4.1. DUTCH VERSION OF THE TRAJECTORY OF CHANGE 107 -- 4.2. FRENCH VERSION OF THE TRAJECTORY OF CHANGE 116 -- 4.3. RÉFÉRENCES 125 -- 4.4. REFERENCES FOR THE TRAJECTORY OF CHANGE 126 -- 5. APPENDIX: SCRIPT OF DISCUSSION GROUPS AND TEMPLATE OF DATA REPORTING 127

224 p., ill., SCIENTIFIC REPORT 13 -- 1 INTRODUCTION .13 -- 1.1 WHAT IS INTEGRATED CARE? 13 -- 1.2 INTEGRATED CARE IN BELGIUM 17 -- 1.3 SCOPE OF THE PROJECT 21 -- 1.4 METHODS 21 -- 2 INTEGRATED CARE AS EXPRESSED IN THE BELGIAN POLICIES .24 -- 2.1 INTRODUCTION .25 -- 2.2 METHODS 25 -- 2.3 RESULTS 26 -- 2.3.1 Overview of the selected policy documents by level of authority 27 -- 2.3.2 Aims according to the dimensions of the SCIROCCO self-assessment tool .42 -- 2.4 DISCUSSION AND CONCLUSIONS 61 -- 2.4.1 Consistency in policy documents of both federal and federated entities despite different emphasis 61 -- 2.4.2 The complexity of Belgium's governance structure and its impact on integrated care policy 63 -- 2.4.3 Limitations of the policy documents review 64 -- 3 MATURITY OF INTEGRATED CARE IN BELGIUM 65 -- 3.1 PROFESSIONALS' ASSESSMENT OF INTEGRATED CARE 67 -- 3.1.1 Introduction .67 -- 3.1.2 Methods 67 -- 3.1.3 Results 69 -- 3.2 PATIENTS' EXPERIENCE OF INTEGRATED CARE .87 -- 3.2.1 Introduction .87 -- 3.2.2 Method 87 -- 3.2.3 Results 90 -- 3.3 DISCUSSION .102 -- 4 STAKEHOLDERS’ PROPOSITIONS OF ACTIONS TO DEVELOP AND IMPLEMENT INTEGRATED CARE .106 -- 4.1 INTRODUCTION 107 -- 4.2 METHODS 107 -- 4.3 RESULTS .111 -- 4.3.1 Discussion group participants .111 -- 4.3.2 Facilitators & barriers 112 -- 4.3.3 Action points .116 -- 4.4 DISCUSSION .135 -- 5 PROVIDER PAYMENT REFORMS FOR IMPLEMENTING INTEGRATED CARE AND VALUEBASED HEALTH CARE: A NARRATIVE LITERATURE REVIEW 137 -- 5.1 INTRODUCTION 138 -- 5.2 METHODS 139 -- 5.2.1 Provider payment mechanisms and integrated care 139 -- 5.2.2 Transition from a fee-for-service financing system to a mixed payment system 141 -- 5.3 RESULTS .142 -- 5.3.1 Provider payment mechanisms 142 -- 5.3.2 Mixed Provider Payment Systems (including alternative payment methods) .145 -- 5.3.3 Payment reforms: conditions and conducive factors 153 -- 5.4 DISCUSSION .161 -- 5.4.1 An incremental reform process 162 -- 5.4.2 New mode of governance at meso level is indispensable to

43 p., ill., Notre système actuel de soins de santé est essentiellement basé sur une approche par maladie et financé par prestation, ce qui n’est pas optimal pour faire face aux défis du vieillissement et de la multiplication des maladies chroniques. C’est pourquoi il est souhaitable d’évoluer vers un système de « soins intégrés », c’est-à-dire des soins plus adaptés aux besoins multidimensionnels des patients atteints de maladies chroniques, tout au long de leur vie et à travers les différentes lignes de soins. Différentes initiatives en ce sens sont déjà en cours en Belgique, tant au niveau fédéral que des entités fédérées, mais les acteurs de terrain ont l’impression que celles-ci ne sont pas encore assez coordonnées. Le nouveau Plan interfédéral sur les Soins intégrés, prévu pour début 2024, devrait pouvoir y remédier., PRÉFACE 1 -- SYNTHÈSE 2 -- 1. INTRODUCTION 4 -- 1.1. QU’EST-CE QUE LES “SOINS INTÉGRÉS” ? 4 -- 1.2. LES SOINS INTÉGRÉS EN BELGIQUE 4 -- 1.3. OBJECTIFS DE CETTE ÉTUDE 7 -- 2. OBJECTIFS DE SOINS INTÉGRÉS MENTIONNÉS DANS LES DOCUMENTS POLITIQUES BELGES 9 -- 3. MATURITÉ DES SOINS INTÉGRÉS EN BELGIQUE 10 -- 3.1. ÉVALUATION DE LA MATURITÉ DES SOINS INTÉGRÉS PAR LES PROFESSIONNELS 11 -- 3.2. ÉVALUATION DU VÉCU DES PATIENTS 12 -- 4. PISTES D’ACTION PROPOSÉES PAR LES PROFESSIONNELS BELGES 13 -- 4.1. OBSTACLES ET FACILITATEURS 14 -- 4.2. TROIS AXES FONDAMENTAUX 17 -- 5. EN AVANT VERS DES SOINS PLUS INTÉGRÉS ! 18 -- 5.1. STRUCTURER LE CADRE POLITIQUE 19 -- 5.2. DÉFINIR UNE APPROCHE TERRITORIALE 20 -- 5.2.1. Choisir la taille du ou des territoire(s) 20 -- 5.2.2. Intégrer les prestataires de soins et renforcer la 1e ligne 21 -- 5.2.3. Organiser la gestion des données vers une approche populationnelle 22 -- 5.3. REVOIR LE MODÈLE DE FINANCEMENT 23 -- 5.3.1. Vers des modèles mixtes 23 -- 5.3.2. Un déploiement progressif 24 -- 5.3.3. Renforcement des soins de 1e ligne 25 -- 5.3.4. Un investissement initial pour démarrer 25 -- 6. CONCLUSION 25 -- RECOMMANDATIONS 28

43 p., ill., Ons huidig gezondheidszorgsysteem is hoofdzakelijk gericht op de aanpak van acute ziekte-episodes met een betaling per prestatie als voornaamste financieringsmechanisme. Dit is niet optimaal om de uitdagingen ten gevolge van de vergrijzing en de toename van chronische ziekten het hoofd te bieden. Het is nodig om te evolueren naar geïntegreerde zorg. We verstaan hieronder een zorgsysteem dat beter afgestemd is op de multi-dimensionele noden van mensen met chronische aandoeningen, dat rekening houdt met de behoeften van mensen gedurende hun hele leven, en dat over de verschillende zorglijnen heen. In België lopen er hierover al verschillende initiatieven, zowel op federaal niveau als op het niveau van de deelstaten. Maar de actoren op het terrein hebben de indruk dat deze nog niet voldoende gecoördineerd worden. Het nieuw Interfederaal Plan voor Geïntegreerde zorg, gepland voor begin 2024, zou hierin een belangrijke stap kunnen zijn., VOORWOORD 1 -- SYNTHESE 2 -- 1. INLEIDING 4 -- 1.1. WAT IS ‘GEÏNTEGREERDE ZORG’? 4 -- 1.2. GEÏNTEGREERDE ZORG IN BELGIË 4 -- 1.3. DOELSTELLINGEN VAN DEZE STUDIE 7 -- 2. DOELSTELLINGEN GEÏNTEGREERDE ZORG VERMELD IN BELGISCHE BELEIDSDOCUMENTEN 10 -- 3. MATURITEIT VAN GEÏNTEGREERDE ZORG IN BELGIË 11 -- 3.1. BEOORDELING VAN DE MATURITEIT VAN GEÏNTEGREERDE ZORG DOOR PROFESSIONALS 11 -- 3.2. BEOORDELING VAN DE ERVARINGEN VAN PATIËNTEN 12 -- 4. ACTIEPUNTEN VOORGESTELD DOOR BELGISCHE PROFESSIONALS 14 -- 4.1. BARRIÈRES EN FACILITATOREN 14 -- 4.2. DRIE FUNDAMENTELE ASSEN 17 -- 5. OP WEG NAAR MEER GEÏNTEGREERDE ZORG! 19 -- 5.1. STRUCTURERING VAN HET BELEIDSKADER 19 -- 5.2. DEFINIËREN TERRITORIALE AANPAK 20 -- 5.2.1. De omvang van het gebied/territorium (of de gebieden/territoria) bepalen 20 -- 5.2.2. Integratie van professionals en versterking van de eerstelijnszorg 21 -- 5.2.3. Organisatie van het gegevensbeheer naar een populatiegerichte benadering 22 -- 5.3. HERZIENING VAN HET FINANCIERINGSMODEL 23 -- 5.3.1. Naar gemengde financieringsmodellen 23 -- 5.3.2. Een geleidelijke uitrol 24 -- 5.3.3. Versterking van de eerstelijnszorg 25 -- 5.3.4. Een initiële investering om te beginnen 25 -- 6. CONCLUSIE 26 -- AANBEVELINGEN 28

Traumatic spinal cord injury (SCI) is a neurologic condition characterized by long-term motor and sensory neurologic deficits as a consequence of an external physical impact damaging the spinal cord. Anatomic MRI is considered the gold-standard diagnostic tool to obtain structural information for the prognosis of acute SCI; however, it lacks functional objective information to assess SCI progression and recovery. In this study, we explored the use of synaptic vesicle glycoprotein 2A (SV2A) PET imaging to detect spinal cord lesions noninvasively after SCI. Mice ( = 7) and rats ( = 8) subjected to unilateral moderate cervical (C5) contusion were euthanized 1 wk after SCI for histologic and autoradiographic (H-labeled (4)-1-[(3-methylpyridin-4-yl)methyl]-4-(3,4,5-trifluorophenyl)pyrrolidin-2-one [UCB-J]) investigation of SV2A levels. Longitudinal C-UCB-J PET/CT imaging was performed in sham ( = 7) and SCI rats ( = 8) 1 wk and 6 wk after SCI. Animals also underwent an F-FDG PET scan during the latter time point. Postmortem tissue SV2A analysis to corroborate in vivo PET findings was performed 6 wk after SCI. A significant SV2A loss (ranging from -70.3% to -87.3%; < 0.0001) was measured at the epicenter of the impact in vitro in both mouse and rat contusion SCI models. Longitudinal C-UCB-J PET imaging detected SV2A loss in SCI rats (-49.0% ± 8.1% at 1 wk and -52.0% ± 12.9% at 6 wk after SCI), with no change observed in sham rats. In contrast, F-FDG PET imaging measured only subtle hypometabolism (-17.6% ± 14.7%). Finally, postmortem H-UCB-J autoradiography correlated with the in vivo SV2A PET findings ( = 0.92, < 0.0001). C-UCB-J PET/CT imaging is a noninvasive marker for SV2A loss after SCI. Collectively, these findings indicate that SV2A PET may provide an objective measure of SCI and thus represent a valuable tool to evaluate novel therapeutics. Clinical assessment of SCI with SV2A PET imaging is highly recommended.

We present a mathematical model of key glucose metabolic pathways in two cells of the human retina: the rods and the retinal pigmented epithelium (RPE). Computational simulations of glucose transporter 1 (GLUT1) inhibition in the model accurately reproduce experimental data from conditional knockout mice and reveal that modification of GLUT1 expression levels of both cells differentially impacts their metabolism. We hypothesize that, under glucose scarcity, the RPE’s energy producing pathways are altered in order to preserve its functionality, impacting the photoreceptors’ outer segment renewal. On the other hand, when glucose is limited in the rods, aerobic glycolysis is preserved, which maintains the lactate contribution to the RPE.

Adaptive modulation of the global cellular growth state of unicellular organisms is crucial for their survival in fluctuating nutrient environments. Because these organisms must be able to respond reliably to ever varying and unpredictable nutritional conditions, their nutrient signaling networks must have a certain inbuilt robustness. In eukaryotes, such as the budding yeast Saccharomyces cerevisiae, distinct nutrient signals are relayed by specific plasma membrane receptors to signal transduction pathways that are interconnected in complex information-processing networks, which have been well characterized. However, the complexity of the signaling network confounds the interpretation of the overall regulatory "logic"of the control system. Here, we propose a literature-curated molecular mechanism of the integrated nutrient signaling network in budding yeast, focusing on early temporal responses to carbon and nitrogen signaling. We build a computational model of this network to reconcile literature-curated quantitative experimental data with our proposed molecular mechanism. We evaluate the robustness of our estimates of the model's kinetic parameter values. We test the model by comparing predictions made in mutant strains with qualitative experimental observations made in the same strains. Finally, we use the model to predict nutrient-responsive transcription factor activities in a number of mutant strains undergoing complex nutrient shifts.

Adaptive modulation of the global cellular growth state of unicellular organisms is crucial for their survival in fluctuating nutrient environments. Because these organisms must be able to respond reliably to ever varying and unpredictable nutritional conditions, their nutrient signaling networks must have a certain inbuilt robustness. In eukaryotes, such as the budding yeast Saccharomyces cerevisiae, distinct nutrient signals are relayed by specific plasma membrane receptors to signal transduction pathways that are interconnected in complex information-processing networks, which have been well characterized. However, the complexity of the signaling network confounds the interpretation of the overall regulatory "logic"of the control system. Here, we propose a literature-curated molecular mechanism of the integrated nutrient signaling network in budding yeast, focusing on early temporal responses to carbon and nitrogen signaling. We build a computational model of this network to reconcile literature-curated quantitative experimental data with our proposed molecular mechanism. We evaluate the robustness of our estimates of the model's kinetic parameter values. We test the model by comparing predictions made in mutant strains with qualitative experimental observations made in the same strains. Finally, we use the model to predict nutrient-responsive transcription factor activities in a number of mutant strains undergoing complex nutrient shifts.

In this neurophysiological study in healthy humans, we assessed how central sensitization induced by either high-frequency stimulation (HFS) or topical capsaicin application modulates features of the RIII reflex response. The ability of these stimuli to engage the endogenous pain modulatory system was also tested. In 26 healthy participants we elicited an RIII reflex using suprathreshold stimulation of the sural nerve. Subsequently HFS or capsaicin were applied to the foot and the RIII reflex repeated after 15 minutes. Contact heating of the volar forearm served as the heterotopic test stimulus to probe activation of the endogenous pain modulatory system. HFS significantly reduced the pain threshold by 29% and the RIII reflex threshold by 20%. Capsaicin significantly reduced the pain threshold by 17% and the RIII reflex threshold by 18%. Both HFS and capsaicin left RIII reflex size unaffected. Numerical Rating Scale (NRS) pain scores elicited by the heterotopic noxious heat stimulus were unaffected by capsaicin and slightly increased by HFS. HFS and capsaicin similarly modulated the pain threshold and RIII reflex threshold, without a concomitant inhibitory effect of the endogenous pain modulatory system. Our neurophysiological study supports the use of the RIII reflex in investigating central sensitization in humans.

Before and immediately after passive upper limb neurodynamic mobilizations targeting the median nerve, grip ([Formula: see text]) and load ([Formula: see text]) forces applied by the thumb, index and major fingers (three-jaw chuck pinch) were collected using a manipulandum during three different grip precision tasks: grip-lift-hold-replace (GLHR), vertical oscillations (OSC), and vertical oscillations with up and down collisions (OSC/COLL/u, OSC/COLL/d). Several parameters were collected or computed from [Formula: see text] and [Formula: see text]. Maximum pinch strength and fingertips pressure sensation threshold were also examined. After the mobilizations, [Formula: see text] max changes from 3.2 ± 0.4 to 3.4 ± 0.4 N (p = 0.014), d[Formula: see text] from 89.0 ± 66.6 to 102.2 ± 59.6 [Formula: see text] (p = 0.009), and d[Formula: see text] from 43.6 ± 17.0 to 56.0 ± 17.9 [Formula: see text] ([Formula: see text]0.001) during GLHR. [Formula: see text] SD changes from 0.9 ± 0.3 to 1.0 ± 0.2 N (p = 0.004) during OSC. [Formula: see text] peak changes from 17.4 ± 8.3 to 15.1 ± 7.5 N ([Formula: see text]0.001), [Formula: see text] from 12.4 ± 6.7 to 11.3 ± 6.8 N (p = 0.033), and [Formula: see text] from 2.9 ± 0.4 to 3.00 ± 0.4 N (p = 0.018) during OSC/COLL/u. [Formula: see text] peak changes from 13.5 ± 7.4 to 12.3 ± 7.7 N (p = 0.030) and [Formula: see text] from 14.5 ± 6.0 to 13.6 ± 5.5 N (p = 0.018) during OSC/COLL/d. Sensation thresholds at index and thumb were reduced (p = 0.001, p = 0.008). Precision grip adaptations observed after the mobilizations could be partly explained by changes in cutaneous median-nerve pressure afferents from the thumb and index fingertips.

Certain applications require a contactless measurement to eliminate the risk of sensorinduced sample contamination. Examples can be found in chemical process control, biotechnology or medical technology. For instance, in critically ill patients requiring renal replacement therapy, continuous in‐line monitoring of blood conductivity as a measure for sodium should be considered. A differential inductive sensing system based on a differential transformer using a specific flow chamber has already proven suitable for this application. However, since the blood in renal replacement therapy is carried in plastic tubing, a direct measurement through the tubing offers a contactless method. Therefore, in this work we present a differential transformer for measuring directly through electrically non‐conductive tubing by winding the tube around the ferrite core of the transformer. Here, the dependence of the winding type and the number of turns of the tubing on the sensitivity has been analyzed by using a mathematical model, simulations and experimental validation. A maximum sensitivity of 364.9 mV/mol/L is measured for radial winding around the core. A longitudinal winding turns out to be less effective with 92.8 mV/mol/L. However, the findings prove the ability to use the differential transformer as a truly contactless sensing system. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

Adaptive modulation of the global cellular growth state of unicellular organisms is crucial for their survival in fluctuating nutrient environments. Because these organisms must be able to respond reliably to ever varying and unpredictable nutritional conditions, their nutrient signaling networks must have a certain inbuilt robustness. In eukaryotes, such as the budding yeast Saccharomyces cerevisiae, distinct nutrient signals are relayed by specific plasma membrane receptors to signal transduction pathways that are interconnected in complex information-processing networks, which have been well characterized. However, the complexity of the signaling network confounds the interpretation of the overall regulatory "logic"of the control system. Here, we propose a literature-curated molecular mechanism of the integrated nutrient signaling network in budding yeast, focusing on early temporal responses to carbon and nitrogen signaling. We build a computational model of this network to reconcile literature-curated quantitative experimental data with our proposed molecular mechanism. We evaluate the robustness of our estimates of the model's kinetic parameter values. We test the model by comparing predictions made in mutant strains with qualitative experimental observations made in the same strains. Finally, we use the model to predict nutrient-responsive transcription factor activities in a number of mutant strains undergoing complex nutrient shifts.

Certain applications require a contactless measurement to eliminate the risk of sensorinduced sample contamination. Examples can be found in chemical process control, biotechnology or medical technology. For instance, in critically ill patients requiring renal replacement therapy, continuous in‐line monitoring of blood conductivity as a measure for sodium should be considered. A differential inductive sensing system based on a differential transformer using a specific flow chamber has already proven suitable for this application. However, since the blood in renal replacement therapy is carried in plastic tubing, a direct measurement through the tubing offers a contactless method. Therefore, in this work we present a differential transformer for measuring directly through electrically non‐conductive tubing by winding the tube around the ferrite core of the transformer. Here, the dependence of the winding type and the number of turns of the tubing on the sensitivity has been analyzed by using a mathematical model, simulations and experimental validation. A maximum sensitivity of 364.9 mV/mol/L is measured for radial winding around the core. A longitudinal winding turns out to be less effective with 92.8 mV/mol/L. However, the findings prove the ability to use the differential transformer as a truly contactless sensing system. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

Ca2+ signaling plays an essential role in T cell activation, which is a key step to start an adaptive immune response. During the transition from a quiescent to a fully activated state, Ca2+ microdomains characterized by reduced spatial and temporal extents are observed in the junctions between the plasma membrane (PM) and the endoplasmic reticulum (ER). Such Ca2+ responses can also occur in response to T cell adhesion to other cells or extracellular matrix proteins in otherwise unstimulated T cells. These non-TCR/CD3-dependent Ca2+ microdomains rely on d-myo-inositol 1,4,5-trisphosphate (IP3) signaling and subsequent store operated Ca2+ entry (SOCE) via the ORAI/STIM system. The detailed molecular mechanism of adhesion-dependent Ca2+ microdomain formation remains to be fully elucidated. We used mathematical modeling to investigate the spatiotemporal characteristics of T cell Ca2+ microdomains and their molecular regulators. We developed a reaction-diffusion model using COMSOL Multiphysics to describe the evolution of cytosolic and ER Ca2+ concentrations in a three-dimensional ER-PM junction. Equations are based on a previously proposed realistic description of the junction, which is extended to take into account IP3 receptors (IP3R) that are located next to the junction. The first model only considered the ORAI channels and the SERCA pumps. Taking into account the existence of preformed clusters of ORAI1 and STIM2, ORAI1 slightly opens in conditions of a full ER. These simulated Ca2+ microdomains are too small as compared to those observed in unstimulated T cells. When considering the opening of the IP3Rs located near the junction, the local depletion of ER Ca2+ allows for larger Ca2+ fluxes through the ORAI1 channels and hence larger local Ca2+ concentrations. Computational results moreover show that Ca2+ diffusion in the ER has a major impact on the Ca2+ changes in the junction, by affecting the local Ca2+ gradients in the sub-PM ER. Besides pointing out the like, info:eu-repo/semantics/published

Purpose: Aim of this study was to develop a generalised radiomics model for predicting pathological complete response after neoadjuvant chemo-radiotherapy in locally advanced rectal cancer patients using pre-CRT T2-weighted images acquired at a 1.5 T and a 3 T scanner. Methods: In two institutions, 195 patients were scanned: 136 patients were scanned on a 1.5 T MR scanner, 59 patients on a 3 T MR scanner. Gross tumour volumes were delineated on the MR images and 496 radiomic features were extracted, applying the intensity-based (IB) filter. Features were standardised with Z-score normalisation and an initial feature selection was carried out using Wilcoxon–Mann–Whitney test: The most significant features at 1.5 T and 3 T were selected as main features. Several logistic regression models combining the main features with a third one selected by those resulting significant were elaborated and evaluated in terms of area under curve (AUC). A tenfold cross-validation was repeated 300 times to evaluate the model robustness. Results: Three features were selected: maximum fractal dimension with IB = 0–50, energy and grey-level non-uniformity calculated on the run-length matrix with IB = 0–50. The AUC of the model applied to the whole dataset after cross-validation was 0.72, while values of 0.70 and 0.83 were obtained when 1.5 T and 3 T patients were considered, respectively. Conclusions: The model elaborated showed good performance, even when data from patients scanned on 1.5 T and 3 T were merged. This shows that magnetic field intensity variability can be overcome by means of selecting appropriate image features.

Objective The study was aimed at comparing measles and rubella disease elimination levels in a homogeneous and heterogeneous population according to socioeconomic status with interactions amongst low- and high-income individuals and diversity in the average number of contacts amongst them. Methods Effective reproductive rate simulations were deduced from a susceptibleinfected-recovered (SIR) mathematical model according to different immunization rates using measles (1980 and 2005) and rubella (1998 and 2005) incidence data from Latin-America and the Caribbean. Low- and high-income individuals' social interaction and their average number of contacts were analysed by bipartite random network analysis. MAPLE 12 (Maplesoft Inc, Ontario Canada) software was used for making the simulations. Results The progress made in eliminating both diseases between both periods of time was reproduced in the socially-homogeneous population. Measles (2005) would be eliminated in high- and low-income groups; however, it would only be achieved in rubella (2005) if there were a high immunity rate amongst the low-income group. If the average number of contacts were varied, then rubella would not be eliminated, even with a 95 % immunity rate. Conclusion Monitoring the elimination level in diseases like measles and rubella requires that socio-economic status be considered as well as the population's interaction pattern. Special attention should be paid to communities having diversity in their average number of contacts occurring in confined spaces such as displaced communities, prisons, educational establishments, or hospitals.

Deterministic SIR models were applied to simulate Susceptible-Infected-Removed and to estimate the threshold condition for varicella outbreaks in children, reported in Medellin, Colombia. The expected numbers of susceptible, infected and removed individuals were compared with observed cases from notification of varicella outbreaks to the local Board of Health and from survey data. The threshold condition was estimated by the basic reproductive ratio and by the relative removal rate, through which measures for preventing and curtailing the outbreaks were identified. The model demonstrated a reasonable fit to the observations, except in two of the six outbreaks which probably reflected under-registration of cases. In order to have prevented these outbreaks, between 4.4% and 52.9% of the susceptible population should have been vaccinated assuming an 85% vaccine effectiveness. Similarly, isolation of affected children should have been increased to between 4.3% and 44.8% per week.

Background: Web-based patient education is increasingly offered to improve patients’ ability to learn, remember, and apply health information. Efficient organization, display, and structural design, that is, information architecture (IA), can support patients’ ability to independently use web-based patient education. However, the role of IA in the context of web-based patient education has not been examined systematically. Objective: To support intervention designers in making informed choices that enhance patients’ learning, this paper describes a randomized experiment on the effects of IA on the effectiveness, use, and user experience of a patient education website and examines the theoretical mechanisms that explain these effects. Methods: Middle-aged and older adults with self-reported hip or knee joint complaints were recruited to use and evaluate 1 of 3 patient education websites containing information on total joint replacement surgery. Each website contained the same textual content based on an existing leaflet but differed in the employed IA design (tunnel, hierarchical, or matrix design). Participants rated the websites on satisfaction, engagement, control, relevance, trust, and novelty and completed an objective knowledge test. Analyses of variance and structural equation modeling were used to examine the effects of IA and construct a theoretical model. Results: We included 215 participants in our analysis. IA did not affect knowledge gain (P=.36) or overall satisfaction (P=.07) directly. However, tunnel (mean 3.22, SD 0.67) and matrix (mean 3.17, SD 0.69) architectures were found to provide more emotional support compared with hierarchical architectures (mean 2.86, SD 0.60; P=.002). Furthermore, increased perceptions of personal relevance in the tunnel IA (β=.18) were found to improve satisfaction (β=.17) indirectly. Increased perceptions of active control in the matrix IA (β=.11) also improved satisfaction (β=.27) indirectly., Applied Ergonomics and Design, Human Information Communication Design

There is large interest in networked social science experiments for understanding human behavior at-scale. Significant effort is required to perform data analytics on experimental outputs and for computational modeling of custom experiments. Moreover, experiments and modeling are often performed in a cycle, enabling iterative experimental refinement and data modeling to uncover interesting insights and to generate/refute hypotheses about social behaviors. The current practice for social analysts is to develop tailor-made computer programs and analytical scripts for experiments and modeling. This often leads to inefficiencies and duplication of effort. In this work, we propose a pipeline framework to take a significant step towards overcoming these challenges. Our contribution is to describe the design and implementation of a software system to automate many of the steps involved in analyzing social science experimental data, building models to capture the behavior of human subjects, and providing data to test hypotheses. The proposed pipeline framework consists of formal models, formal algorithms, and theoretical models as the basis for the design and implementation. We propose a formal data model, such that if an experiment can be described in terms of this model, then our pipeline software can be used to analyze data efficiently. The merits of the proposed pipeline framework is elaborated by several case studies of networked social science experiments.

There is large interest in networked social science experiments for understanding human behavior at-scale. Significant effort is required to perform data analytics on experimental outputs and for computational modeling of custom experiments. Moreover, experiments and modeling are often performed in a cycle, enabling iterative experimental refinement and data modeling to uncover interesting insights and to generate/refute hypotheses about social behaviors. The current practice for social analysts is to develop tailor-made computer programs and analytical scripts for experiments and modeling. This often leads to inefficiencies and duplication of effort. In this work, we propose a pipeline framework to take a significant step towards overcoming these challenges. Our contribution is to describe the design and implementation of a software system to automate many of the steps involved in analyzing social science experimental data, building models to capture the behavior of human subjects, and providing data to test hypotheses. The proposed pipeline framework consists of formal models, formal algorithms, and theoretical models as the basis for the design and implementation. We propose a formal data model, such that if an experiment can be described in terms of this model, then our pipeline software can be used to analyze data efficiently. The merits of the proposed pipeline framework is elaborated by several case studies of networked social science experiments.

There is large interest in networked social science experiments for understanding human behavior at-scale. Significant effort is required to perform data analytics on experimental outputs and for computational modeling of custom experiments. Moreover, experiments and modeling are often performed in a cycle, enabling iterative experimental refinement and data modeling to uncover interesting insights and to generate/refute hypotheses about social behaviors. The current practice for social analysts is to develop tailor-made computer programs and analytical scripts for experiments and modeling. This often leads to inefficiencies and duplication of effort. In this work, we propose a pipeline framework to take a significant step towards overcoming these challenges. Our contribution is to describe the design and implementation of a software system to automate many of the steps involved in analyzing social science experimental data, building models to capture the behavior of human subjects, and providing data to test hypotheses. The proposed pipeline framework consists of formal models, formal algorithms, and theoretical models as the basis for the design and implementation. We propose a formal data model, such that if an experiment can be described in terms of this model, then our pipeline software can be used to analyze data efficiently. The merits of the proposed pipeline framework is elaborated by several case studies of networked social science experiments.

Quantifying evolutionary dynamics of cancer initiation and progression can provide insights into more effective strategies of early detection and treatment. Here we develop a mathematical model of colorectal cancer initiation through inactivation of two tumor suppressor genes and activation of one oncogene, accounting for the well-known path to colorectal cancer through loss of tumor suppressors APC and TP53 and gain of the KRAS oncogene. In the model, we allow mutations to occur in any order, leading to a complex network of premalignant mutational genotypes on the way to colorectal cancer. We parameterize the model using experimentally measured parameter values, many of them only recently available, and compare its predictions to epidemiological data on colorectal cancer incidence. We find that the reported lifetime risk of colorectal cancer can be recovered using a mathematical model of colorectal cancer initiation together with experimentally measured mutation rates in colorectal tissues and proliferation rates of premalignant lesions. We demonstrate that the order of driver events in colorectal cancer is determined primarily by the fitness effects that they provide, rather than their mutation rates. Our results imply that there may not be significant immune suppression of untreated benign and malignant colorectal lesions.

There is large interest in networked social science experiments for understanding human behavior at-scale. Significant effort is required to perform data analytics on experimental outputs and for computational modeling of custom experiments. Moreover, experiments and modeling are often performed in a cycle, enabling iterative experimental refinement and data modeling to uncover interesting insights and to generate/refute hypotheses about social behaviors. The current practice for social analysts is to develop tailor-made computer programs and analytical scripts for experiments and modeling. This often leads to inefficiencies and duplication of effort. In this work, we propose a pipeline framework to take a significant step towards overcoming these challenges. Our contribution is to describe the design and implementation of a software system to automate many of the steps involved in analyzing social science experimental data, building models to capture the behavior of human subjects, and providing data to test hypotheses. The proposed pipeline framework consists of formal models, formal algorithms, and theoretical models as the basis for the design and implementation. We propose a formal data model, such that if an experiment can be described in terms of this model, then our pipeline software can be used to analyze data efficiently. The merits of the proposed pipeline framework is elaborated by several case studies of networked social science experiments.

Quantifying evolutionary dynamics of cancer initiation and progression can provide insights into more effective strategies of early detection and treatment. Here we develop a mathematical model of colorectal cancer initiation through inactivation of two tumor suppressor genes and activation of one oncogene, accounting for the well-known path to colorectal cancer through loss of tumor suppressors APC and TP53 and gain of the KRAS oncogene. In the model, we allow mutations to occur in any order, leading to a complex network of premalignant mutational genotypes on the way to colorectal cancer. We parameterize the model using experimentally measured parameter values, many of them only recently available, and compare its predictions to epidemiological data on colorectal cancer incidence. We find that the reported lifetime risk of colorectal cancer can be recovered using a mathematical model of colorectal cancer initiation together with experimentally measured mutation rates in colorectal tissues and proliferation rates of premalignant lesions. We demonstrate that the order of driver events in colorectal cancer is determined primarily by the fitness effects that they provide, rather than their mutation rates. Our results imply that there may not be significant immune suppression of untreated benign and malignant colorectal lesions.

What does it mean to be happy? The vast majority of cross-cultural studies on happiness have employed a Western-origin, or "WEIRD" measure of happiness that conceptualizes it as a self-centered (or "independent"), high-arousal emotion. However, research from Eastern cultures, particularly Japan, conceptualizes happiness as including an interpersonal aspect emphasizing harmony and connectedness to others. Following a combined emicetic approach (Cheung, van de Vijver & Leong, 2011), we assessed the cross-cultural applicability of a measure of independent happiness developed in the US (Subjective Happiness Scale; Lyubomirsky & Lepper, 1999) and a measure of interdependent happiness developed in Japan (Interdependent Happiness Scale; Hitokoto & Uchida, 2015), with data from 63 countries representing 7 sociocultural regions. Results indicate that the schema of independent happiness was more coherent in more WEIRD countries. In contrast, the coherence of interdependent happiness was unrelated to a country's "WEIRD-ness." Reliabilities of both happiness measures were lowest in African and Middle Eastern countries, suggesting these two conceptualizations of happiness may not be globally comprehensive. Overall, while the two measures had many similar correlates and properties, the self-focused concept of independent happiness is "WEIRD-er" than interdependent happiness, suggesting cross-cultural researchers should attend to both conceptualizations.

This study explores speed choice behavior of travelers under realistic and fabricated Dynamic Message Signs (DMS) content. Using web-based survey information of 4,302 participants collected by Amazon Mechanical Turk in the United States, we develop a set of multivariate latent-based ordered probit models participants. Results show female, African-Americans, drivers with a disability, elderly, and drivers who trust DMS are likely to comply with the fabricated messages. Drivers who comply with traffic regulations, have a good driving record, and live in rural areas, as well as female drivers are likely to slow down under fabricated messages. We highlight that calling or texting, taking picture, and tuning the radio are distracting activities leading drivers to slow down or stop under fictitious scenarios.

The outbreak of coronavirus disease 2019 (COVID-19) requires urgent need for effective treatment. Severe COVID-19 is characterized by a cytokine storm syndrome with subsequent multiple organ failure (MOF) and acute respiratory distress syndrome (ARDS), which may lead to intensive care unit and increased risk of death. While awaiting a vaccine, targeting COVID-19-induced cytokine storm syndrome appears currently as the efficient strategy to reduce the mortality of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The stress-responsive enzyme, heme oxygenase-1 (HO-1) is largely known to protect against inflammatory response in animal models. HO-1 is induced by hemin, a well-tolerated molecule, used for decades in the treatment of acute intermittent porphyria. Experimental studies showed that hemin-induced HO-1 mitigates cytokine storm and lung injury in mouse models of sepsis and renal ischemia-reperfusion injury. Furthermore, HO-1 may also control numerous viral infections by inhibiting virus replication. In this context, we suggest the hypothesis that HO-1 cytoprotective pathway might be a promising target to control SARS-CoV-2 infection and mitigate COVID-19-induced cytokine storm and subsequent ARDS., info:eu-repo/semantics/published

Quantifying evolutionary dynamics of cancer initiation and progression can provide insights into more effective strategies of early detection and treatment. Here we develop a mathematical model of colorectal cancer initiation through inactivation of two tumor suppressor genes and activation of one oncogene, accounting for the well-known path to colorectal cancer through loss of tumor suppressors APC and TP53 and gain of the KRAS oncogene. In the model, we allow mutations to occur in any order, leading to a complex network of premalignant mutational genotypes on the way to colorectal cancer. We parameterize the model using experimentally measured parameter values, many of them only recently available, and compare its predictions to epidemiological data on colorectal cancer incidence. We find that the reported lifetime risk of colorectal cancer can be recovered using a mathematical model of colorectal cancer initiation together with experimentally measured mutation rates in colorectal tissues and proliferation rates of premalignant lesions. We demonstrate that the order of driver events in colorectal cancer is determined primarily by the fitness effects that they provide, rather than their mutation rates. Our results imply that there may not be significant immune suppression of untreated benign and malignant colorectal lesions.

In the 1960's Brian Goodwin published a couple of mathematical models showing how feedback inhibition can lead to oscillations and discussed possible implications of this behaviour for the physiology of the cell. He also presented key ideas about the rich dynamics that may result from the coupling between such biochemical oscillators. Goodwin's work motivated a series of theoretical investigations aiming at identifying minimal mechanisms to generate limit cycle oscillations and deciphering design principles of biological oscillators. The three-variable Goodwin model (adapted by Griffith) can be seen as a core model for a large class of biological systems, ranging from ultradian to circadian clocks. We summarize here main ideas and results brought by Goodwin and review a couple of modeling works directly or indirectly inspired by Goodwin's findings., info:eu-repo/semantics/published

There is large interest in networked social science experiments for understanding human behavior at-scale. Significant effort is required to perform data analytics on experimental outputs and for computational modeling of custom experiments. Moreover, experiments and modeling are often performed in a cycle, enabling iterative experimental refinement and data modeling to uncover interesting insights and to generate/refute hypotheses about social behaviors. The current practice for social analysts is to develop tailor-made computer programs and analytical scripts for experiments and modeling. This often leads to inefficiencies and duplication of effort. In this work, we propose a pipeline framework to take a significant step towards overcoming these challenges. Our contribution is to describe the design and implementation of a software system to automate many of the steps involved in analyzing social science experimental data, building models to capture the behavior of human subjects, and providing data to test hypotheses. The proposed pipeline framework consists of formal models, formal algorithms, and theoretical models as the basis for the design and implementation. We propose a formal data model, such that if an experiment can be described in terms of this model, then our pipeline software can be used to analyze data efficiently. The merits of the proposed pipeline framework is elaborated by several case studies of networked social science experiments.

Intraglottal pressure is the driving force of vocal fold vibration. Its time course during the open phase of the vibratory cycle is essential in the mechanics of phonation, but measuring it directly is difficult and may hinder spontaneous voicing. However, it can be computed from the in vivo measured transglottal flow and glottal area (hence the air particle velocity) on the basis of the Bernoulli energy law and the interaction with the inertance of the vocal tract. As to sustained modal phonation, calculations are presented for the two possible shapes of glottal duct: convergent and divergent, including absolute calibration in order to obtain quantitative physical values. Whatever the glottal duct configuration, the calculations based on measured values of glottal area and air flow show that the integrated intraglottal pressure during the opening phase systematically exceeds that during the closing phase, which is the basic condition for sustaining vocal fold oscillation. The key point is that the airflow curve is skewed to the right relative to the glottal area curve. The skewing results from air compressibility and vocal tract inertance. The intraglottal pressure becomes negative during the closing phase. As to the soft (or physiological) voice onset, a similar approach shows that the integrated pressure differences (opening phase - closing phase) actually increase as the onset progresses, and this applies to the results based on Bernoulli's energy law as well as to those based on the interaction with the inertance of the vocal tract. Furthermore and similarly, the phase lead of the pressure wave with respect to the glottal opening progressively increases. The underlying explanation lies in the progressively increasing skewing of the airflow curve to the right with respect to the glottal area curve.

There is large interest in networked social science experiments for understanding human behavior at-scale. Significant effort is required to perform data analytics on experimental outputs and for computational modeling of custom experiments. Moreover, experiments and modeling are often performed in a cycle, enabling iterative experimental refinement and data modeling to uncover interesting insights and to generate/refute hypotheses about social behaviors. The current practice for social analysts is to develop tailor-made computer programs and analytical scripts for experiments and modeling. This often leads to inefficiencies and duplication of effort. In this work, we propose a pipeline framework to take a significant step towards overcoming these challenges. Our contribution is to describe the design and implementation of a software system to automate many of the steps involved in analyzing social science experimental data, building models to capture the behavior of human subjects, and providing data to test hypotheses. The proposed pipeline framework consists of formal models, formal algorithms, and theoretical models as the basis for the design and implementation. We propose a formal data model, such that if an experiment can be described in terms of this model, then our pipeline software can be used to analyze data efficiently. The merits of the proposed pipeline framework is elaborated by several case studies of networked social science experiments.

An orb web’s prey capture thread relies on its glue droplets to retain insects until a spider can subdue them. Each droplet’s viscoelastic glycoprotein adhesive core extends to dissipate the forces of prey struggle as it transfers force to stiffer, support line flagelliform fibers. In large orb webs, switchback capture thread turns are placed at the bottom of the web before a continuous capture spiral progresses from the web’s periphery to its interior. To determine if the properties of capture thread droplets change during web spinning, we characterized droplet and glycoprotein volumes and material properties from the bottom, top, middle, and inner regions of webs. Both droplet and glycoprotein volume decreased during web construction, but there was a progressive increase in the glycoprotein’s Young’s modulus and toughness. Increases in the percentage of droplet aqueous material indicated that these increases in material properties are not due to reduced glycoprotein viscosity resulting from lower droplet hygroscopicity. Instead, they may result from changes in aqueous layer compounds that condition the glycoprotein. A 6-fold difference in glycoprotein toughness and a 70-fold difference in Young’s modulus across a web documents the phenotypic plasticity of this natural adhesive and its potential to inspire new materials.

Physical differences between youth and adults, which include incomplete myelination, limited neck muscle development, and a higher head-body ratio in the youth population, likely contribute towards the increased susceptibility of youth to concussion. Previous research efforts have considered the biomechanics of concussion for adult populations, but these known age-related differences highlight the necessity of quantifying the risk of concussion for a youth population. This study adapted the previously developed Generalized Acceleration Model for Brian Injury Threshold (GAMBIT) that combines linear and rotational head acceleration to model the risk of concussion for a youth population with the Generalized Acceleration Model for Concussion in Youth (GAM-CY). Survival analysis was used in conjunction with head impact data collected during participation in youth football to model risk between individuals who sustained medically-diagnosed concussions (n = 15). Receiver operator characteristic curves were generated for peak linear acceleration, peak rotational acceleration, and GAM-CY, all of which were observed to be better injury predictors than random guessing. GAM-CY was associated with an area under the curve of 0.89 (95% confidence interval: 0.82–0.95) when all head impacts experienced by the concussed players were considered. Concussion tolerance was observed to be lower for youth athletes, with average peak linear head acceleration of 62.4 ± 29.7 g compared to 102.5 ± 32.7 g for adults and average peak rotational head acceleration of 2609 ± 1591 rad/s2 compared to 4412 ± 2326 rad/s2. These data provide further evidence of age-related differences in concussion tolerance and may be used for the development of youth-specific protective designs.

Over the past 50 years, the use of mathematical models, derived from physical reasoning, to describe molecular and cellular systems has evolved from an art of the few to a cornerstone of biological inquiry. George Oster stood out as a pioneer of this paradigm shift from descriptive to quantitative biology not only through his numerous research accomplishments, but also through the many students and postdocs he mentored over his long career. Those of us fortunate enough to have worked with George agree that his sharp intellect, physical intuition, and passion for scientific inquiry not only inspired us as scientists but also greatly influenced the way we conduct research. We would like to share a few important lessons we learned from George in honor of his memory and with the hope that they may inspire future generations of scientists.

Background: Several studies have raised concerns that future demand for blood products may not be met. The ageing of the general population and the fact that a large proportion of blood products is transfused to elderly patients has been identified as an important driver of blood shortages. The aim of this study was to collect, for the first time, nationally representative data regarding blood donors and transfusion recipients in order to predict the future evolution of blood donations and red blood cell (RBC) use in Switzerland between 2014 and 2035. Materials and methods: Blood donor and transfusion recipient data, subdivided by the subjects' age and gender were obtained from Regional Blood Services and nine large, acute-care hospitals in various regions of Switzerland. Generalised additive regression models and time-series models with exponential smoothing were employed to estimate trends of whole blood donations and RBC transfusions. Results: The trend models employed suggested that RBC demand could equal supply by 2018 and could eventually cause an increasing shortfall of up to 77,000 RBC units by 2035. Discussion. Our study highlights the need for continuous monitoring of trends of blood donations and blood transfusions in order to take proactive measures aimed at preventing blood shortages in Switzerland. Measures should be taken to improve donor retention in order to prevent a further erosion of the blood donor base.

With the advent of high-throughput phenotyping platforms, plant breeders have a means to assess many traits for large breeding populations. However, understanding the genetic interdependencies among high-dimensional traits in a statistically robust manner remains a major challenge. Since multiple phenotypes likely share mutual relationships, elucidating the interdependencies among economically important traits can better inform breeding decisions and accelerate the genetic improvement of plants. The objective of this study was to leverage confirmatory factor analysis and graphical modeling to elucidate the genetic interdependencies among a diverse agronomic traits in rice. We used a Bayesian network to depict conditional dependencies among phenotypes, which can not be obtained by standard multi-trait analysis. We utilized Bayesian confirmatory factor analysis which hypothesized that 48 observed phenotypes resulted from six latent variables including grain morphology, morphology, flowering time, physiology, yield, and morphological salt response. This was followed by studying the genetics of each latent variable, which is also known as factor, using single nucleotide polymorphisms. Bayesian network structures involving the genomic component of six latent variables were established by fitting four algorithms (i.e., Hill Climbing, Tabu, Max-Min Hill Climbing, and General 2-Phase Restricted Maximization algorithms). Physiological components influenced the flowering time and grain morphology, and morphology and grain morphology influenced yield. In summary, we show the Bayesian network coupled with factor analysis can provide an effective approach to understand the interdependence patterns among phenotypes and to predict the potential influence of external interventions or selection related to target traits in the interrelated complex traits systems.

Magnetic particles are widely used in lab-on-chip and biosensing applications, because they have a high surface-to-volume ratio, they can be actuated with magnetic fields and many biofunctionalization options are available. The most well-known actuation method is to apply a magnetic field gradient which generates a translational force on the particles and allows separation of the particles from a suspension. A more recently developed magnetic actuation method is to exert torque on magnetic particles by a rotating magnetic field. Rotational actuation can be achieved with a field that is uniform in space and it allows for a precise control of torque, orientation, and angular velocity of magnetic particles in lab-on-chip devices. A wide range of studies have been performed with rotating MPs, demonstrating fluid mixing, concentration determination of biological molecules in solution, and characterization of structure and function of biomolecules at the single-molecule level. In this paper we give a comprehensive review of the historical development of MP rotation studies, including configurations for field generation, physical model descriptions, and biological applications. We conclude by sketching the scientific and technological developments that can be expected in the future in the field of rotating magnetic particles for lab-on-chip applications.

The oxidation of an organosolv lignin with tert-butylhydroperoxide, initiated by titanium grafted into the lignin structure, was investigated. Titanation of reactive groups on lignin is responsible for the cross-linking of the lignin structure. IR and MAS 13C NMR spectroscopy spectra confirmed the oxidation of the lignin structure and other pronounced structural changes. A study with guaiacol as a model compound helped to recognise that aromatic ring opening occurs under the given conditions and is catalysed by the grafted titanium. The structure of the oxidised lignin becomes less robust and therefore potentially more susceptible to be depolymerised and converted into monomeric units.

Background: Urothelial bladder cancer (BLCA) is one of the most common internal malignancies worldwide with poor prognosis. This study aims to explore effective prognostic biomarkers and construct a prognostic risk score model for patients with BLCA. Methods: Weighted gene co-expression network analysis (WGCNA) was used for identifying the co-expression module related to the pathological stage of BLCA based on the RNA-Seq data retrieved from The Cancer Genome Atlas database. Prognostic biomarkers screened by Cox proportional hazard regression model and random forest were used to construct a risk score model that can predict the prognosis of patients with BLCA. The GSE13507 dataset was used as the independent testing dataset to test the performance of the risk score model in predicting the prognosis of patients with BLCA. Results: WGCNA identified seven co-expression modules, in which the brown module consisted of 77 genes was most significantly correlated with the pathological stage of BLCA. Cox proportional hazard regression model and random forest identified TPST1 and P3H4 as prognostic biomarkers. Elevated TPST1 and P3H4 expressions were associated with the high pathological stage and worse survival. The risk score model based on the expression level of TPST1 and P3H4 outperformed pathological stage indicators and previously proposed prognostic models. Conclusion: The gene co-expression network-based study could provide additional insight into the tumorigenesis and progression of BLCA, and our proposed risk score model may aid physicians in the assessment of the prognosis of patients with BLCA.

Funding: This study was co-financed by the European Development Regional Fund "A way to achieve Europe" ERDF and partially by Pfizer, Inc., Objective: The aims of this study were as follows. First, we sought to compare the in vitro susceptibility of liposomal amphotericin B (LAmB) and anidulafungin on Candida albicans and Candida glabrata biofilms growing on silicone discs. Second, we sought to compare the activity of LAmB versus anidulafungin for the treatment of experimental catheter-related C. albicans and C. glabrata infections with the antifungal lock technique in a rabbit model. Methods: Two C. albicans and two C. glabrata clinical strains were used. The minimum biofilm eradication concentration for 90% eradication (MBEC ) values were determined after 48h of treatment with LAmB and anidulafungin. Confocal microscopy was used to visualize the morphology and viability of yeasts growing in biofilms. Central venous catheters were inserted into New Zealand rabbits, which were inoculated of each strain of C. albicans and C. glabrata. Then, catheters were treated for 48h with saline or with antifungal lock technique using either LAmB (5mg/mL) or anidulafungin (3.33mg/mL). Results: In vitro: anidulafungin showed greater activity than LAmB against C. albicans and C. glabrata strains. For C. albicans: MBEC of anidulafungin versus LAmB: CA176, 0.03 vs. 128 mg/L; CA180, 0.5 vs. 64 mg/L. For C. glabrata: MBEC of anidulafungin versus LAmB: CG171, 0.5 vs. 64 mg/L; CG334, 2 vs. 32 mg/L. In vivo: for C. albicans species, LAmB and anidulafungin achieved significant reductions relative to growth control of log cfu recovered from the catheter tips (CA176: 3.6±0.3 log CFU, p0.0001; CA180: 3.8±0.1 log CFU, p0.01). For C. glabrata, anidulafungin lock therapy achieved significant reductions relative to the other treatments (CG171: 4.8 log CFU, p0.0001; CG334: 5.1 log CFU, p0.0001) Conclusions: For the C. albicans strains, both LAmB and anidulafungin may be promising antifungal lock technique for long-term catheter-related infections; however, anidulafungin showed significantly higher activity than LAmB against the C. gla

With the advent of high-throughput phenotyping platforms, plant breeders have a means to assess many traits for large breeding populations. However, understanding the genetic interdependencies among high-dimensional traits in a statistically robust manner remains a major challenge. Since multiple phenotypes likely share mutual relationships, elucidating the interdependencies among economically important traits can better inform breeding decisions and accelerate the genetic improvement of plants. The objective of this study was to leverage confirmatory factor analysis and graphical modeling to elucidate the genetic interdependencies among a diverse agronomic traits in rice. We used a Bayesian network to depict conditional dependencies among phenotypes, which can not be obtained by standard multi-trait analysis. We utilized Bayesian confirmatory factor analysis which hypothesized that 48 observed phenotypes resulted from six latent variables including grain morphology, morphology, flowering time, physiology, yield, and morphological salt response. This was followed by studying the genetics of each latent variable, which is also known as factor, using single nucleotide polymorphisms. Bayesian network structures involving the genomic component of six latent variables were established by fitting four algorithms (i.e., Hill Climbing, Tabu, Max-Min Hill Climbing, and General 2-Phase Restricted Maximization algorithms). Physiological components influenced the flowering time and grain morphology, and morphology and grain morphology influenced yield. In summary, we show the Bayesian network coupled with factor analysis can provide an effective approach to understand the interdependence patterns among phenotypes and to predict the potential influence of external interventions or selection related to target traits in the interrelated complex traits systems.

Physical differences between youth and adults, which include incomplete myelination, limited neck muscle development, and a higher head-body ratio in the youth population, likely contribute towards the increased susceptibility of youth to concussion. Previous research efforts have considered the biomechanics of concussion for adult populations, but these known age-related differences highlight the necessity of quantifying the risk of concussion for a youth population. This study adapted the previously developed Generalized Acceleration Model for Brian Injury Threshold (GAMBIT) that combines linear and rotational head acceleration to model the risk of concussion for a youth population with the Generalized Acceleration Model for Concussion in Youth (GAM-CY). Survival analysis was used in conjunction with head impact data collected during participation in youth football to model risk between individuals who sustained medically-diagnosed concussions (n = 15). Receiver operator characteristic curves were generated for peak linear acceleration, peak rotational acceleration, and GAM-CY, all of which were observed to be better injury predictors than random guessing. GAM-CY was associated with an area under the curve of 0.89 (95% confidence interval: 0.82–0.95) when all head impacts experienced by the concussed players were considered. Concussion tolerance was observed to be lower for youth athletes, with average peak linear head acceleration of 62.4 ± 29.7 g compared to 102.5 ± 32.7 g for adults and average peak rotational head acceleration of 2609 ± 1591 rad/s2 compared to 4412 ± 2326 rad/s2. These data provide further evidence of age-related differences in concussion tolerance and may be used for the development of youth-specific protective designs.

© 2019 The Author(s). Background: Literature highlighted the importance of timely access and ongoing care provided at primary care settings in reducing hospitalisation and health care resource uses. However, the effect of timely access to primary care has not been fully captured in most of the current continuity of care indices. This study aimed to develop a time-duration measure of continuity of primary care ("cover index") capturing the proportion of time an individual is under the potentially protective effect of primary health care contacts. Methods: An observational study was conducted on 36,667 individuals aged 45 years or older with diabetes mellitus extracted from Western Australian linked administrative data. Threshold effect models were used to determine the maximum time interval between general practitioner (GP) visits that afforded a protective effect against avoidable hospitalisation across complication cohorts. The optimal maximum time interval was used to compute a cover index for each individual. The cover was evaluated using descriptive statistics stratified by population socio-demographic characteristics. Results: The optimal maximum time between GP visits was 9-13 months for people with diabetes with no complication, 5-11 months for people with diabetes with 1-2 complications, and 4-9 months for people with diabetes with 3+ complications. The cover index was lowest among those aged 75+ years, males, Indigenous people, socio-economically disadvantaged and those in very remote areas. Conclusions: This study developed a new measure of continuity of primary care that adds a time parameter to capturing longitudinal continuity. Cover has the potential to better capture underuse of primary care and will significantly contribute to the sparsely available methods for analysis of linked administrative data in evaluating continuity of care for people with chronic conditions.

Background: Several studies have raised concerns that future demand for blood products may not be met. The ageing of the general population and the fact that a large proportion of blood products is transfused to elderly patients has been identified as an important driver of blood shortages. The aim of this study was to collect, for the first time, nationally representative data regarding blood donors and transfusion recipients in order to predict the future evolution of blood donations and red blood cell (RBC) use in Switzerland between 2014 and 2035. Materials and methods: Blood donor and transfusion recipient data, subdivided by the subjects' age and gender were obtained from Regional Blood Services and nine large, acute-care hospitals in various regions of Switzerland. Generalised additive regression models and time-series models with exponential smoothing were employed to estimate trends of whole blood donations and RBC transfusions. Results: The trend models employed suggested that RBC demand could equal supply by 2018 and could eventually cause an increasing shortfall of up to 77,000 RBC units by 2035. Discussion. Our study highlights the need for continuous monitoring of trends of blood donations and blood transfusions in order to take proactive measures aimed at preventing blood shortages in Switzerland. Measures should be taken to improve donor retention in order to prevent a further erosion of the blood donor base.

Magnetic particles are widely used in lab-on-chip and biosensing applications, because they have a high surface-to-volume ratio, they can be actuated with magnetic fields and many biofunctionalization options are available. The most well-known actuation method is to apply a magnetic field gradient which generates a translational force on the particles and allows separation of the particles from a suspension. A more recently developed magnetic actuation method is to exert torque on magnetic particles by a rotating magnetic field. Rotational actuation can be achieved with a field that is uniform in space and it allows for a precise control of torque, orientation, and angular velocity of magnetic particles in lab-on-chip devices. A wide range of studies have been performed with rotating MPs, demonstrating fluid mixing, concentration determination of biological molecules in solution, and characterization of structure and function of biomolecules at the single-molecule level. In this paper we give a comprehensive review of the historical development of MP rotation studies, including configurations for field generation, physical model descriptions, and biological applications. We conclude by sketching the scientific and technological developments that can be expected in the future in the field of rotating magnetic particles for lab-on-chip applications.

The oxidation of an organosolv lignin with tert-butylhydroperoxide, initiated by titanium grafted into the lignin structure, was investigated. Titanation of reactive groups on lignin is responsible for the cross-linking of the lignin structure. IR and MAS 13C NMR spectroscopy spectra confirmed the oxidation of the lignin structure and other pronounced structural changes. A study with guaiacol as a model compound helped to recognise that aromatic ring opening occurs under the given conditions and is catalysed by the grafted titanium. The structure of the oxidised lignin becomes less robust and therefore potentially more susceptible to be depolymerised and converted into monomeric units.

Over the past 50 years, the use of mathematical models, derived from physical reasoning, to describe molecular and cellular systems has evolved from an art of the few to a cornerstone of biological inquiry. George Oster stood out as a pioneer of this paradigm shift from descriptive to quantitative biology not only through his numerous research accomplishments, but also through the many students and postdocs he mentored over his long career. Those of us fortunate enough to have worked with George agree that his sharp intellect, physical intuition, and passion for scientific inquiry not only inspired us as scientists but also greatly influenced the way we conduct research. We would like to share a few important lessons we learned from George in honor of his memory and with the hope that they may inspire future generations of scientists.