Osteoblasts-derived exosomes as potential novel communicators in particle-induced periprosthetic osteolysis.

The inflammatory response to wear particles derived from hip prothesis is considered a hallmark of periprosthetic osteolysis, which can ultimately lead to the need for revision surgery. Exosomes (Exos) have been associated with various bone pathologies, and there is increasing recognition in the literature that they actively transport molecules throughout the body. The role of wear particles in osteoblast-derived Exos is unknown, and the potential contribution of Exos to osteoimmune communication and periprosthetic osteolysis niche is still in its infancy. Given this, we investigate how titanium dioxide nanoparticles (TiO2 NPs), similar in size and composition to prosthetic wear particles, affect Exos biogenesis. Two osteoblastic cell models commonly used to study the response of osteoblasts to wear particles were selected as a proof of concept. The contribution of Exos to periprosthetic osteolysis was assessed by functional assays in which primary human macrophages were stimulated with bone-derived Exos. We demonstrated that TiO2 NPs enter multivesicular bodies, the nascent of Exos, altering osteoblast-derived Exos secretion and molecular cargo. No significant differences were observed in Exos morphology and size. However, functional assays reveal that Exos cargo enriched in uPA stimulates macrophages to a mixed M1 and M2 phenotype, inducing the release of pro- and anti-inflammatory signals characteristic of periprosthetic osteolysis. In addition, we demonstrated the expression of uPA in exosomes derived from the urine of patients with osteolysis. These results suggest that uPA can be a potential biomarker of osteolysis. In the future, uPa may serve as a possible non-invasive biomarker to identify patients at risk for peri-implant osteolysis.

The ultrametric backbone is the union of all minimum spanning forests.

Minimum spanning trees and forests are powerful sparsification techniques that remove cycles from weighted graphs to minimize total edge weight while preserving node reachability, with applications in computer science, network science, and graph theory. Despite their utility and ubiquity, they have several limitations, including that they are only defined for undirected networks, they significantly alter dynamics on networks, and they do not generally preserve important network features such as shortest distances, shortest path distribution, and community structure. In contrast, distance backbones, which are subgraphs formed by all edges that obey a generalized triangle inequality, are well defined in directed and undirected graphs and preserve those and other important network features. The backbone of a graph is defined with respect to a specified path-length operator that aggregates weights along a path to define its length, thereby associating a cost to indirect connections. The backbone is the union of all shortest paths between each pair of nodes according to the specified operator. One such operator, the max function, computes the length of a path as the largest weight of the edges that compose it (a weakest link criterion). It is the only operator that yields an algebraic structure for computing shortest paths that is consistent with De Morgan's laws. Applying this operator yields the ultrametric backbone of a graph in that (semi-triangular) edges whose weights are larger than the length of an indirect path connecting the same nodes (i.e. those that break the generalized triangle inequality based on max as a path-length operator) are removed. We show that the ultrametric backbone is the union of minimum spanning forests in undirected graphs and provides a new generalization of minimum spanning trees to directed graphs that, unlike minimum equivalent graphs and minimum spanning arborescences, preserves all max - min shortest paths and De Morgan's law consistency.

Prevalence and differences in the co-administration of drugs known to interact: an analysis of three distinct and large populations.

BACKGROUND: The co-administration of drugs known to interact greatly impacts morbidity, mortality, and health economics. This study aims to examine the drug-drug interaction (DDI) phenomenon with a large-scale longitudinal analysis of age and gender differences found in drug administration data from three distinct healthcare systems. METHODS: This study analyzes drug administrations from population-wide electronic health records in Blumenau (Brazil; 133 K individuals), Catalonia (Spain; 5.5 M individuals), and Indianapolis (USA; 264 K individuals). The stratified prevalences of DDI for multiple severity levels per patient gender and age at the time of administration are computed, and null models are used to estimate the expected impact of polypharmacy on DDI prevalence. Finally, to study actionable strategies to reduce DDI prevalence, alternative polypharmacy regimens using drugs with fewer known interactions are simulated. RESULTS: A large prevalence of co-administration of drugs known to interact is found in all populations, affecting 12.51%, 12.12%, and 10.06% of individuals in Blumenau, Indianapolis, and Catalonia, respectively. Despite very different healthcare systems and drug availability, the increasing prevalence of DDI as patients age is very similar across all three populations and is not explained solely by higher co-administration rates in the elderly. In general, the prevalence of DDI is significantly higher in women - with the exception of men over 50 years old in Indianapolis. Finally, we show that using proton pump inhibitor alternatives to omeprazole (the drug involved in more co-administrations in Catalonia and Blumenau), the proportion of patients that are administered known DDI can be reduced by up to 21% in both Blumenau and Catalonia and 2% in Indianapolis. CONCLUSIONS: DDI administration has a high incidence in society, regardless of geographic, population, and healthcare management differences. Although DDI prevalence increases with age, our analysis points to a complex phenomenon that is much more prevalent than expected, suggesting comorbidities as key drivers of the increase. Furthermore, the gender differences observed in most age groups across populations are concerning in regard to gender equity in healthcare. Finally, our study exemplifies how electronic health records' analysis can lead to actionable interventions that significantly reduce the administration of known DDI and its associated human and economic costs.

The secretome of macrophages has a differential impact on spinal cord injury recovery according to the polarization protocol.

Introduction: The inflammatory response after spinal cord injury (SCI) is an important contributor to secondary damage. Infiltrating macrophages can acquire a spectrum of activation states, however, the microenvironment at the SCI site favors macrophage polarization into a pro-inflammatory phenotype, which is one of the reasons why macrophage transplantation has failed. Methods: In this study, we investigated the therapeutic potential of the macrophage secretome for SCI recovery. We investigated the effect of the secretome in vitro using peripheral and CNS-derived neurons and human neural stem cells. Moreover, we perform a pre-clinical trial using a SCI compression mice model and analyzed the recovery of motor, sensory and autonomic functions. Instead of transplanting the cells, we injected the paracrine factors and extracellular vesicles that they secrete, avoiding the loss of the phenotype of the transplanted cells due to local environmental cues. Results: We demonstrated that different macrophage phenotypes have a distinct effect on neuronal growth and survival, namely, the alternative activation with IL-10 and TGF-ß1 (M(IL-10+TGF-ß1)) promotes significant axonal regeneration. We also observed that systemic injection of soluble factors and extracellular vesicles derived from M(IL-10+TGF-ß1) macrophages promotes significant functional recovery after compressive SCI and leads to higher survival of spinal cord neurons. Additionally, the M(IL-10+TGF-ß1) secretome supported the recovery of bladder function and decreased microglial activation, astrogliosis and fibrotic scar in the spinal cord. Proteomic analysis of the M(IL-10+TGF-ß1)-derived secretome identified clusters of proteins involved in axon extension, dendritic spine maintenance, cell polarity establishment, and regulation of astrocytic activation. Discussion: Overall, our results demonstrated that macrophages-derived soluble factors and extracellular vesicles might be a promising therapy for SCI with possible clinical applications.

Validation of the natural sedimentation technique in the diagnosis of chronic fasciolosis.

There are various diagnostic techniques available for chronic fasciolosis in ruminants. However, many of them exhibit low specificity and sensitivity, making them impractical for field use and in low-resource laboratories. The present study evaluates the usefulness of the Natural Sedimentation technique in diagnosing chronic fasciolosis in three domestic species conducted at the Laboratorio de Parasitología y Enfermedades Parasitarias, Facultad de Ciencias Veterinas, Universidad Nacional de Cajamarca. Fecal samples were collected from n = 323 cattle, n = 362 sheep, and n = 231 swine for Fasciola hepatica fecal egg counts. The visualization of adult parasites in animal livers post-mortem was considered the gold standard. Additionally, the sensitivity of the technique was evaluated using five different amounts of feces. In cattle, a sensitivity of 0.93 ± 0.03, specificity of 0.91 ± 0.06, positive predictive value of 0.96 ± 0.03, and negative predictive value of 0.86 ± 0.07 were obtained. In sheep, a sensitivity of 0.79 ± 0.05, specificity of 0.83 ± 0.07, positive predictive value of 0.90 ± 0.04, and negative predictive value of 0.66 ± 0.08 were observed. In swine, a sensitivity of 0.92 ± 0.06, specificity of 1.00 ± 0.00, positive predictive value of 1.00 ± 0.00, and negative predictive value of 0.96 ± 0.03 were found. There was no statistical difference in egg counts when using 1, 2, 3, 4, and 5 g of feces (p = 0.907). Furthermore, 1 to 688 fecal eggs of F. hepatica were counted in 1 g of feces. The Natural Sedimentation technique has both qualitative and quantitative applications with satisfactory results when using 1 g of feces in the diagnosis of chronic fasciolosis in domestic animals. Due to its simplicity, it can be implemented in field conditions and low-resource laboratories.

Bursts of communication increase opinion diversity in the temporal Deffuant model.

Human interactions create social networks forming the backbone of societies. Individuals adjust their opinions by exchanging information through social interactions. Two recurrent questions are whether social structures promote opinion polarisation or consensus and whether polarisation can be avoided, particularly on social media. In this paper, we hypothesise that not only network structure but also the timings of social interactions regulate the emergence of opinion clusters. We devise a temporal version of the Deffuant opinion model where pairwise social interactions follow temporal patterns. Individuals may self-organise into a multi-partisan society due to network clustering promoting the reinforcement of local opinions. Burstiness has a similar effect and is alone sufficient to refrain the population from consensus and polarisation by also promoting the reinforcement of local opinions. The diversity of opinions in socially clustered networks thus increases with burstiness, particularly, and counter-intuitively, when individuals have low tolerance and prefer to adjust to similar peers. The emergent opinion landscape is well-balanced regarding groups' size, with relatively short differences between groups, and a small fraction of extremists. We argue that polarisation is more likely to emerge in social media than offline social networks because of the relatively low social clustering observed online, despite the observed online burstiness being sufficient to promote more diversity than would be expected offline. Increasing the variance of burst activation times, e.g. by being less active on social media, could be a venue to reduce polarisation. Furthermore, strengthening online social networks by increasing social redundancy, i.e. triangles, may also promote diversity.

A Case of Porto-Sinusoidal Vascular Disease.

Introduction: Porto-sinusoidal vascular syndrome is characterised by specific histological changes that do not include cirrhosis, with or without portal hypertension. Patients are usually asymptomatic until development of portal hypertension complications. Case description: A 69-year-old female with history of JAK2 positive essential thrombocythemia (ET) was referred to internal medicine consultation due to elevated liver enzymes. The patient had no previous history of liver disease. Seven months earlier, she had an ischaemic stroke and started treatment with atorvastatin. After discontinuing medication, liver enzymes returned to normal and atorvastatin-related drug-induced liver disease (DILI) was presumed.During a follow-up visit, iron deficiency anaemia was detected and an endoscopic study was performed. It revealed a gastric varix actively bleeding, which was successfully treated with cyanoacrylate.Two months later, the patient was admitted due to a new episode of variceal bleeding, and a portal hypertension complementary study was made. Discussion: Although the pathogenesis of porto-sinusoidal vascular disease (PSVD) remains poorly understood, vascular changes within the liver have been associated with several predisposing conditions, such as hypercoagulable states. Patients with ET, especially those with JAK2 mutation, are known to be at increased risk of non-cirrhotic vein thrombosis. Concerning PSVD, the association is not clear but it is believed that both PSVD and myeloproliferative neoplasms share a common denominator: a state characterised by hypercoagulability, inflammation, endothelial dysfunction and, in some cases, portal hypertension. Conclusion: Portal hypertension without cirrhosis is a rare condition, presenting diagnostic challenges and significant impact on the patient's prognosis. LEARNING POINTS: The suspicion of PSVD should be raised when signs of portal hypertension are present with normal or mildly elevated liver enzymes and normal liver stiffness measurement. A liver biopsy should be performed in this situation.Although the pathogenesis of PSVD is not clearly understood, it is based on the development of vascular changes within the liver and there might be several predisposing conditions such as coagulation disorders.

The distance backbone of directed networks.

In weighted graphs the shortest path between two nodes is often reached through an indirect path, out of all possible connections, leading to structural redundancies which play key roles in the dynamics and evolution of complex networks. We have previously developed a parameter-free, algebraically-principled methodology to uncover such redundancy and reveal the distance backbone of weighted graphs, which has been shown to be important in transmission dynamics, inference of important paths, and quantifying the robustness of networks. However, the method was developed for undirected graphs. Here we expand this methodology to weighted directed graphs and study the redundancy and robustness found in nine networks ranging from social, biomedical, and technical systems. We found that similarly to undirected graphs, directed graphs in general also contain a large amount of redundancy, as measured by the size of their (directed) distance backbone. Our methodology adds an additional tool to the principled sparsification of complex networks and the measure of their robustness.

Pharmacokinetic-Pharmacodynamic Modeling of Midazolam in Pediatric Surgery.

Midazolam (MDZ) is used for sedation in surgical procedures; its clinical effect is related to its receptor affinity and the dose administered. Therefore, a pharmacokinetic-pharmacodynamic (PK-PD) population model of MDZ in pediatric patients undergoing minor surgery is proposed. A descriptive, observational, prospective, and longitudinal, study that included patients of both sexes, aged 2-17 years, ASA I/II, who received MDZ in IV doses (0.05 mg/kg) before surgery. Three blood samples were randomly taken between 5-120 min; both sedation by the Bispectral Index Scale (BIS) and its adverse effects were recorded. The PK-PD relationship was determined using a nonlinear mixed-effects, bicompartmental first-order elimination model using Monolix Suite™. Concentrations and the BIS were fitted to the sigmoid Emax PK-PD population and sigmoid Emax PK/PD indirect binding models, obtaining drug concentrations at the effect site (biophase). The relationship of concentrations and BIS showed a clockwise hysteresis loop, probably indicating time-dependent protein binding. Of note, at half the dose used in pediatric patients, adequate sedation without adverse effects was demonstrated. Further PK-PD studies are needed to optimize dosing schedules and avoid overdosing or possible adverse effects.

Understanding Contexts and Challenges of Information Management for Epilepsy Care.

Epilepsy is a common chronic neurological disease. People with epilepsy (PWE) and their caregivers face several challenges related to their epilepsy management, including quality of care, care coordination, side effects, and stigma management. The sociotechnical issues of the information management contexts and challenges for epilepsy care may be mitigated through effective information management. We conducted 4 focus groups with 5 PWE and 7 caregivers to explore how they manage epilepsy-related information and the challenges they encountered. Primary issues include challenges of finding the right information, complexities of tracking and monitoring data, and limited information sharing. We provide a framework that encompasses three attributes - individual epilepsy symptoms and health conditions, information complexity, and circumstantial constraints. We suggest future design implications to mitigate these challenges and improve epilepsy information management and care coordination.

Comparison of 3D Sensors for Automating Bolt-Tightening Operations in the Automotive Industry.

Machine vision systems are widely used in assembly lines for providing sensing abilities to robots to allow them to handle dynamic environments. This paper presents a comparison of 3D sensors for evaluating which one is best suited for usage in a machine vision system for robotic fastening operations within an automotive assembly line. The perception system is necessary for taking into account the position uncertainty that arises from the vehicles being transported in an aerial conveyor. Three sensors with different working principles were compared, namely laser triangulation (SICK TriSpector1030), structured light with sequential stripe patterns (Photoneo PhoXi S) and structured light with infrared speckle pattern (Asus Xtion Pro Live). The accuracy of the sensors was measured by computing the root mean square error (RMSE) of the point cloud registrations between their scans and two types of reference point clouds, namely, CAD files and 3D sensor scans. Overall, the RMSE was lower when using sensor scans, with the SICK TriSpector1030 achieving the best results (0.25 mm ± 0.03 mm), the Photoneo PhoXi S having the intermediate performance (0.49 mm ± 0.14 mm) and the Asus Xtion Pro Live obtaining the higher RMSE (1.01 mm ± 0.11 mm). Considering the use case requirements, the final machine vision system relied on the SICK TriSpector1030 sensor and was integrated with a collaborative robot, which was successfully deployed in an vehicle assembly line, achieving 94% success in 53,400 screwing operations.

Validation of a Questionnaire on Sexual and Reproductive Health Among Immigrant Vocational Education Students in Portugal from São Tomé and Príncipe.

Sexual and reproductive health interventions' effectiveness should be evaluated using a valid instrument. This study aimed to validate a questionnaire on sexual and reproductive health in adolescents and young adults from São Tomé and Príncipe who voluntarily enrolled in a vocational school in Portugal to complete their 12th school year and obtain a professional card.A questionnaire consisting of perception and knowledge sections was adapted from previous questionnaires. We followed the steps of psychometric analysis. Firstly, we assessed face validity and content validity. We used factorial analysis to validate the perceptions section (which included Likert-type questions). For the knowledge section (which consisted of multiple-choice questions), we used the key check, discrimination index, and difficulty index. We evaluated internal consistency through Cronbach's alpha for the perceptions section and the Kuder-Richardson score for the knowledge section.Out of 105 invited students, a total of ninety students were enrolled in this study, of whom 88 completed most of the questions. The exploratory analysis showed that most students agreed with the right to refuse intercourse. However, while approximately 23% disagreed that consensual sex among adult women or men is always wrong, around the same proportion agreed. A considerable number of students recognized condoms and pills as effective methods of contraception. However, most students were unfamiliar with other methods. Most knowledge questions showed acceptable difficulty levels, and the discrimination index varied among questions. The knowledge questions demonstrated good consistency levels. This study enabled us to develop an appropriate instrument for evaluating the effectiveness of public health interventions and identifying specific knowledge gaps in migrant populations from low-income countries. This will help prioritise topics to be addressed in sexual health education sessions.

Dynamical Modularity in Automata Models of Biochemical Networks.

Given the large size and complexity of most biochemical regulation and signaling networks, there is a non-trivial relationship between the micro-level logic of component interactions and the observed macro-dynamics. Here we address this issue by formalizing the concept of pathway modules developed by Marques-Pita and Rocha [1], which are sequences of state updates that are guaranteed to occur (barring outside interference) in the causal dynamics of automata networks after the perturbation of a subset of driver nodes. We present a novel algorithm to automatically extract pathway modules from networks and characterize the interactions that may take place between the modules. This methodology uses only the causal logic of individual node variables (micro-dynamics) without the need to compute the dynamical landscape of the networks (macro-dynamics). Specifically, we identify complex modules, which maximize pathway length and require synergy between their components. This allows us to propose a new take on dynamical modularity that partitions complex networks into causal pathways of variables that are guaranteed to transition to specific dynamical states given a perturbation to a set of driver nodes. Thus, the same node variable can take part in distinct modules depending on the state it takes. Our measure of dynamical modularity of a network is then inversely proportional to the overlap among complex modules and maximal when complex modules are completely decouplable from one another in the network dynamics. We estimate dynamical modularity for several genetic regulatory networks, including the full Drosophila melanogaster segment-polarity network. We discuss how identifying complex modules and the dynamical modularity portrait of networks explains the macro-dynamics of biological networks, such as uncovering the (more or less) decouplable building blocks of emergent computation (or collective behavior) in biochemical regulation and signaling.

Contact networks have small metric backbones that maintain community structure and are primary transmission subgraphs.

The structure of social networks strongly affects how different phenomena spread in human society, from the transmission of information to the propagation of contagious diseases. It is well-known that heterogeneous connectivity strongly favors spread, but a precise characterization of the redundancy present in social networks and its effect on the robustness of transmission is still lacking. This gap is addressed by the metric backbone, a weight- and connectivity-preserving subgraph that is sufficient to compute all shortest paths of weighted graphs. This subgraph is obtained via algebraically-principled axioms and does not require statistical sampling based on null-models. We show that the metric backbones of nine contact networks obtained from proximity sensors in a variety of social contexts are generally very small, 49% of the original graph for one and ranging from about 6% to 20% for the others. This reflects a surprising amount of redundancy and reveals that shortest paths on these networks are very robust to random attacks and failures. We also show that the metric backbone preserves the full distribution of shortest paths of the original contact networks-which must include the shortest inter- and intra-community distances that define any community structure-and is a primary subgraph for epidemic transmission based on pure diffusion processes. This suggests that the organization of social contact networks is based on large amounts of shortest-path redundancy which shapes epidemic spread in human populations. Thus, the metric backbone is an important subgraph with regard to epidemic spread, the robustness of social networks, and any communication dynamics that depend on complex network shortest paths.

Effective Connectivity and Bias Entropy Improve Prediction of Dynamical Regime in Automata Networks.

Biomolecular network dynamics are thought to operate near the critical boundary between ordered and disordered regimes, where large perturbations to a small set of elements neither die out nor spread on average. A biomolecular automaton (e.g., gene, protein) typically has high regulatory redundancy, where small subsets of regulators determine activation via collective canalization. Previous work has shown that effective connectivity, a measure of collective canalization, leads to improved dynamical regime prediction for homogeneous automata networks. We expand this by (i) studying random Boolean networks (RBNs) with heterogeneous in-degree distributions, (ii) considering additional experimentally validated automata network models of biomolecular processes, and (iii) considering new measures of heterogeneity in automata network logic. We found that effective connectivity improves dynamical regime prediction in the models considered; in RBNs, combining effective connectivity with bias entropy further improves the prediction. Our work yields a new understanding of criticality in biomolecular networks that accounts for collective canalization, redundancy, and heterogeneity in the connectivity and logic of their automata models. The strong link we demonstrate between criticality and regulatory redundancy provides a means to modulate the dynamical regime of biochemical networks.

Titanium dioxide nanoparticles affect osteoblast-derived exosome cargos and impair osteogenic differentiation of human mesenchymal stem cells.

Titanium (Ti) and its alloys are the most widely used metallic biomaterials in total joint replacement; however, increasing evidence supports the degradation of its surface due to corrosion and wear processes releasing debris (ions, and micro and nanoparticles) and contribute to particle-induced osteolysis and implant loosening. Cell-to-cell communication involving several cell types is one of the major biological processes occurring during bone healing and regeneration at the implant-bone interface. In addition to the internal response of cells to the uptake and intracellular localization of wear debris, a red flag is the ability of titanium dioxide nanoparticles (mimicking wear debris) to alter cellular communication with the tissue background, disturbing the balance between osseous tissue integrity and bone regenerative processes. This study aims to understand whether titanium dioxide nanoparticles (TiO2 NPs) alter osteoblast-derived exosome (Exo) biogenesis and whether exosomal protein cargos affect the communication of osteoblasts with human mesenchymal stem/stromal cells (HMSCs). Osteoblasts are derived from mesenchymal stem cells coexisting in the bone microenvironment during development and remodelling. We observed that TiO2 NPs stimulate immature osteoblast- and mature osteoblast-derived Exo secretion that present a distinct proteomic cargo. Functional tests confirmed that Exos derived from both osteoblasts decrease the osteogenic differentiation of HMSCs. These findings are clinically relevant since wear debris alter extracellular communication in the bone periprosthetic niche, contributing to particle-induced osteolysis and consequent prosthetic joint failure.

Influence of Age and Sex on the Pharmacokinetics of Midazolam and the Depth of Sedation in Pediatric Patients Undergoing Minor Surgeries.

Whether age and sex influence the depth of sedation and the pharmacokinetics of midazolam is currently unknown. The influence of age and sex was investigated in 117 children (2 to 17 years) who required intravenous sedation for minor surgery (0.05 mg/kg). Plasma concentrations and sedation effects were simultaneously measured. The measured concentrations were analyzed using a two-compartment model with first-order elimination. Among the age ranges, significant differences were found (p < 0.05) between the volume of distribution (Vd) of the first compartment (V1) and that of the second (V2). With respect to sex, differences in V2 were found between age groups. At the administered dose, in patients younger than 6 years, a profound sedative effect (40-60 BIS) was observed for up to 120 min, while in older children, the effect lasted only half as long. The differences found in the Vd and bispectral index (BIS) in patients younger than 6 years compared to older patients may be due to immature CYP3A activity and body fat content; furthermore, the Vd varies with age due to changes in body composition and protein binding. Patients younger than 6 years require intravenous (IV) doses <0.05 mg/kg of midazolam for deep sedation. Dosage adjustments according to age group are suggested.

Analysis of electronic health records from three distinct and large populations reveals high prevalence and biases in the co-administration of drugs known to interact.

The co-administration of drugs known to interact has a high impact on morbidity, mortality, and health economics. We study the drug-drug interaction (DDI) phenomenon by analyzing drug administrations from population-wide Electronic Health Records (EHR) in Blumenau (Brazil), Catalonia (Spain), and Indianapolis (USA). Despite very different health care systems and drug availability, we find a common large risk of DDI administration that affected 13 to 20% of patients in these populations. In addition, the increasing risk of DDI as patients age is very similar across all three populations but is not explained solely by higher co-administration rates in the elderly. We also find that women are at higher risk of DDI overall- except for men over 50 years old in Indianapolis. Finally, we show that PPI alternatives to Omeprazole can reduce the number of patients affected by known DDIs by up to 21% in both Blumenau and Catalonia, and 2% in Indianapolis, exemplifying how analysis of EHR data can lead to a significant reduction of DDI and its associated human and economic costs. Although the risk of DDIs increases with age, administration patterns point to a complex phenomenon that cannot be solely explained by polypharmacy and multimorbidity. The lack of safer drug alternatives, particularly for chronic conditions, further overburdens health systems, thus highlighting the need for disruptive drug research.

LargeNetVis: Visual Exploration of Large Temporal Networks Based on Community Taxonomies.

Temporal (or time-evolving) networks are commonly used to model complex systems and the evolution of their components throughout time. Although these networks can be analyzed by different means, visual analytics stands out as an effective way for a pre-analysis before doing quantitative/statistical analyses to identify patterns, anomalies, and other behaviors in the data, thus leading to new insights and better decision-making. However, the large number of nodes, edges, and/or timestamps in many real-world networks may lead to polluted layouts that make the analysis inefficient or even infeasible. In this paper, we propose LargeNetVis, a web-based visual analytics system designed to assist in analyzing small and large temporal networks. It successfully achieves this goal by leveraging three taxonomies focused on network communities to guide the visual exploration process. The system is composed of four interactive visual components: the first (Taxonomy Matrix) presents a summary of the network characteristics, the second (Global View) gives an overview of the network evolution, the third (a node-link diagram) enables community- and node-level structural analysis, and the fourth (a Temporal Activity Map - TAM) shows the community- and node-level activity under a temporal perspective. We demonstrate the usefulness and effectiveness of LargeNetVis through two usage scenarios and a user study with 14 participants.

Meningococcal Septic Oligoarthritis: An Unusual Presentation Revealing Concurrent Multiple Myeloma.

Meningococcal invasive disease is rare in immunocompetent hosts but may occur in patients with risk factors. Septic arthritis is an uncommon form of presentation and is usually due to surgical colonization or hematogenous dissemination. We present a case of a 73-year-old woman, who recently underwent knee replacement surgery, presenting with right knee and left shoulder pain, swelling, and reduced range of motion. Antibiotic therapy was promptly initiated, and the identification of invasive meningococcal disease with septic arthritis was possible through blood cultures and synovial fluid analysis.