Determinants of Polar versus Nematic Organization in Networks of Dynamic Microtubules and Mitotic Motors.

During cell division, mitotic motors organize microtubules in the bipolar spindle into either polar arrays at the spindle poles or a "nematic" network of aligned microtubules at the spindle center. The reasons for the distinct self-organizing capacities of dynamic microtubules and different motors are not understood. Using in vitro reconstitution experiments and computer simulations, we show that the human mitotic motors kinesin-5 KIF11 and kinesin-14 HSET, despite opposite directionalities, can both organize dynamic microtubules into either polar or nematic networks. We show that in addition to the motor properties the natural asymmetry between microtubule plus- and minus-end growth critically contributes to the organizational potential of the motors. We identify two control parameters that capture system composition and kinetic properties and predict the outcome of microtubule network organization. These results elucidate a fundamental design principle of spindle bipolarity and establish general rules for active filament network organization.

Biophysics of Frequency-Dependent Variation in Paresthesia and Pain Relief during Spinal Cord Stimulation.

The neurophysiological effects of spinal cord stimulation (SCS) for chronic pain are poorly understood, resulting in inefficient failure-prone programming protocols and inadequate pain relief. Nonetheless, novel stimulation patterns are regularly introduced and adopted clinically. Traditionally, paresthetic sensation is considered necessary for pain relief, although novel paradigms provide analgesia without paresthesia. However, like pain relief, the neurophysiological underpinnings of SCS-induced paresthesia are unknown. Here, we paired biophysical modeling with clinical paresthesia thresholds (of both sexes) to investigate how stimulation frequency affects the neural response to SCS relevant to paresthesia and analgesia. Specifically, we modeled the dorsal column (DC) axonal response, dorsal column nucleus (DCN) synaptic transmission, conduction failure within DC fiber collaterals, and dorsal horn network output. Importantly, we found that high-frequency stimulation reduces DC fiber activation thresholds, which in turn accurately predicts clinical paresthesia perception thresholds. Furthermore, we show that high-frequency SCS produces asynchronous DC fiber spiking and ultimately asynchronous DCN output, offering a plausible biophysical basis for why high-frequency SCS is less comfortable and produces qualitatively different sensation than low-frequency stimulation. Finally, we demonstrate that the model dorsal horn network output is sensitive to SCS-inherent variations in spike timing, which could contribute to heterogeneous pain relief across patients. Importantly, we show that model DC fiber collaterals cannot reliably follow high-frequency stimulation, strongly affecting the network output and typically producing antinociceptive effects at high frequencies. Altogether, these findings clarify how SCS affects the nervous system and provide insight into the biophysics of paresthesia generation and pain relief.

Computational modelling of mouse atrio ventricular node action potential and automaticity.

The atrioventricular node (AVN) is a crucial component of the cardiac conduction system. Despite its pivotal role in regulating the transmission of electrical signals between atria and ventricles, a comprehensive understanding of the cellular electrophysiological mechanisms governing AVN function has remained elusive. This paper presents a detailed computational model of mouse AVN cell action potential (AP). Our model builds upon previous work and introduces several key refinements, including accurate representation of membrane currents and exchangers, calcium handling, cellular compartmentalization, dynamic update of intracellular ion concentrations, and calcium buffering. We recalibrated and validated the model against existing and unpublished experimental data. In control conditions, our model reproduces the AVN AP experimental features, (e.g. rate = 175 bpm, experimental range [121, 191] bpm). Notably, our study sheds light on the contribution of L-type calcium currents, through both Cav1.2 and Cav1.3 channels, in AVN cells. The model replicates several experimental observations, including the cessation of firing upon block of Cav1.3 or INa,r current. If block induces a reduction in beating rate of 11%. In summary, this work presents a comprehensive computational model of mouse AVN cell AP, offering a valuable tool for investigating pacemaking mechanisms and simulating the impact of ionic current blockades. By integrating calcium handling and refining formulation of ionic currents, our model advances understanding of this critical component of the cardiac conduction system, providing a platform for future developments in cardiac electrophysiology. KEY POINTS: This paper introduces a comprehensive computational model of mouse atrioventricular node (AVN) cell action potentials (APs). Our model is based on the electrophysiological data from isolated mouse AVN cells and exhibits an action potential and calcium transient that closely match the experimental records. By simulating the effects of blocking specific ionic currents, the model effectively predicts the roles of L-type Cav1.2 and Cav1.3 channels, T-type calcium channels, sodium currents (TTX-sensitive and TTX-resistant), and the funny current (If) in AVN pacemaking. The study also emphasizes the significance of other ionic currents, including IKr, Ito, IKur, in regulating AP characteristics and cycle length in AVN cells. The model faithfully reproduces the rate dependence of action potentials under pacing, opening the possibility of use in impulse propagation models. The population-of-models approach showed the robustness of this new AP model in simulating a wide spectrum of cellular pacemaking in AVN.

The Impact of Preventive Treatment for Multidrug- and Rifampin-Resistant Tuberculosis Exceeds Trial-Based Estimates.

BACKGROUND: Several clinical trials of tuberculosis preventive treatment (TPT) for household contacts of patients with multidrug- or rifampin-resistant tuberculosis (MDR/RR-TB) are nearing completion. The potential benefits of delivering TPT to MDR/RR-TB contacts extend beyond the outcomes that clinical trials can measure. METHODS: We developed an agent-based, household-structured TB and MDR/RR-TB transmission model, calibrated to an illustrative setting in India. We simulated contact investigation in households of patients with MDR/RR-TB, comparing an MDR/RR-TPT regimen (assuming 6-month duration, 70% efficacy) and associated active case finding against alternatives of contact investigation without TPT or no household intervention. We simulated the TB and MDR/RR-TB incidence averted relative to placebo over 2 years, as measurable by a typical trial, as well as the incidence averted over a longer time horizon, in the broader population, and relative to no contact investigation. RESULTS: Observing TPT and placebo recipients for 2 years as in a typical trial, MDR/RR-TPT was measured to prevent 72% (interquartile range, 45%-100%) of incident MDR/RR-TB among recipients; the median number needed to treat (NNT) to prevent 1 MDR/RR-TB case was 73, compared to placebo. This NNT decreased to 54 with 13-18 years of observation, to 27 when downstream transmission effects were also considered, and to 12 when the effects of active TB screening were included by comparing to a no-household-contact-intervention scenario. CONCLUSIONS: If forthcoming trial results demonstrate efficacy, the long-term population impact of TPT for MDR/RR-TB-including the large effect of increased active TB detection among MDR/RR-TB contacts-could be much greater than suggested by trial outcomes alone.

Principles of Cold Adaptation of Fish Lactate Dehydrogenases Revealed by Computer Simulations of the Catalytic Reaction.

Cold-adapted enzymes from psychrophilic and psychrotolerant species are characterized by a higher catalytic activity at low temperature than their mesophilic orthologs and are also usually found to be more thermolabile. Computer simulations of the catalytic reactions have been shown to be a very powerful tool for analyzing the structural and energetic origins of these effects. Here, we examine the cold adaptation of lactate dehydrogenases from two Antarctic and sub-Antarctic fish species using this approach and compare our results with those obtained for the orthologous dogfish enzyme. Direct calculations of thermodynamic activation parameters show that the cold-adapted fish enzymes are characterized by a lower activation enthalpy and a more negative entropy term. This appears to be a universal feature of psychrophilic enzymes, and it is found to originate from a higher flexibility of certain parts of the protein surface. We also carry out free energy simulations that address the differences in thermal stability and substrate binding affinity between the two cold-adapted enzymes, which only differ by a single mutation. These calculations capture the effects previously seen in in vitro studies and provide straightforward explanations of these experimental results.

Single-cell ionic current phenotyping explains stem cell-derived cardiomyocyte action potential morphology.

Human induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) are a promising tool to study arrhythmia-related factors, but the variability of action potential (AP) recordings from these cells limits their use as an in vitro model. In this study, we use recently published brief (10 s), dynamic voltage-clamp (VC) data to provide mechanistic insights into the ionic currents contributing to AP heterogeneity; we call this approach rapid ionic current phenotyping (RICP). Features of this VC data were correlated to AP recordings from the same cells, and we used computational models to generate mechanistic insights into cellular heterogeneity. This analysis uncovered several interesting links between AP morphology and ionic current density: both L-type calcium and sodium currents contribute to upstroke velocity, rapid delayed rectifier K+ current is the main determinant of the maximal diastolic potential, and an outward current in the activation range of slow delayed rectifier K+ is the main determinant of AP duration. Our analysis also identified an outward current in several cells at 6 mV that is not reproduced by iPSC-CM mathematical models but contributes to determining AP duration. RICP can be used to explain how cell-to-cell variability in ionic currents gives rise to AP heterogeneity. Because of its brief duration (10 s) and ease of data interpretation, we recommend the use of RICP for single-cell patch-clamp experiments that include the acquisition of APs.NEW & NOTEWORTHY We present rapid ionic current phenotyping (RICP), a current quantification approach based on an optimized voltage-clamp protocol. The method captures a rich snapshot of the ionic current dynamics, providing quantitative information about multiple currents (e.g., ICa,L, IKr) in the same cell. The protocol helped to identify key ionic determinants of cellular action potential heterogeneity in iPSC-CMs. This included unexpected results, such as the critical role of IKr in establishing the maximum diastolic potential.

Mobilization in two-step capillary isoelectric focusing: Concepts assessed by computer simulation.

The mobilization step in a two-step capillary isoelectric focusing protocol is discussed by means of dynamic computer simulation data for systems without and with spacer compounds that establish their zones at the beginning and end of the focusing column. After focusing in an electroosmosis-free environment (first step), mobilization (second step) can be induced electrophoretically, by the application of a hydrodynamic flow, or by a combination of both means. Dynamic simulations provide insight into the complexity of the various modes of electrophoretic mobilization and dispersion associated with hydrodynamic mobilization. The data are discussed together with the relevant literature.

Optimized signal of calcifications in wide-angle digital breast tomosynthesis: a virtual imaging trial.

OBJECTIVES: Evaluate microcalcification detectability in digital breast tomosynthesis (DBT) and synthetic 2D mammography (SM) for different acquisition setups using a virtual imaging trial (VIT) approach. MATERIALS AND METHODS: Medio-lateral oblique (MLO) DBT acquisitions on eight patients were performed at twice the automatic exposure controlled (AEC) dose. The noise was added to the projections to simulate a given dose trajectory. Virtual microcalcification models were added to a given projection set using an in-house VIT framework. Three setups were evaluated: (1) standard acquisition with 25 projections at AEC dose, (2) 25 projections with a convex dose distribution, and (3) sparse setup with 13 projections, every second one over the angular range. The total scan dose and angular range remained constant. DBT volume reconstruction and synthetic mammography image generation were performed using a Siemens prototype algorithm. Lesion detectability was assessed through a Jackknife-alternative free-response receiver operating characteristic (JAFROC) study with six observers. RESULTS: For DBT, the area under the curve (AUC) was 0.97 ± 0.01 for the standard, 0.95 ± 0.02 for the convex, and 0.89 ± 0.03 for the sparse setup. There was no significant difference between standard and convex dose distributions (p = 0.309). Sparse projections significantly reduced detectability (p = 0.001). Synthetic images had a higher AUC with the convex setup, though not significantly (p = 0.435). DBT required four times more reading time than synthetic mammography. DISCUSSION: A convex setup did not significantly improve detectability in DBT compared to the standard setup. Synthetic images exhibited a non-significant increase in detectability with the convex setup. Sparse setup significantly reduced detectability in both DBT and synthetic mammography. CLINICAL RELEVANCE STATEMENT: This virtual imaging trial study allowed the design and efficient testing of different dose distribution trajectories with real mammography images, using a dose-neutral protocol. KEY POINTS: • In DBT, a convex dose distribution did not increase the detectability of microcalcifications compared to the current standard setup but increased detectability for the SM images. • A sparse setup decreased microcalcification detectability in both DBT and SM images compared to the convex and current clinical setups. • Optimal microcalcification cluster detection in the system studied was achieved using either the standard or convex dose setting, with the default number of projections.

Circular at the very beginning: on the initial genomes in the RNA world.

It is likely that an RNA world existed in early life, when RNA played both the roles of the genome and functional molecules, thereby undergoing Darwinian evolution. However, even with only one type of polymer, it seems quite necessary to introduce a labour division concerning these two roles because folding is required for functional molecules (ribozymes) but unfavourable for the genome (as a template in replication). Notably, while ribozymes tend to have adopted a linear form for folding without constraints, a circular form, which might have been topologically hindered in folding, seems more suitable for an RNA template. Another advantage of involving a circular genome could have been to resist RNA's end-degradation. Here, we explore the scenario of a circular RNA genome plus linear ribozyme(s) at the precellular stage of the RNA world through computer modelling. The results suggest that a one-gene scene could have been 'maintained', albeit with rather a low efficiency for the circular genome to produce the ribozyme, which required precise chain-break or chain-synthesis. This strict requirement may have been relieved by introducing a 'noncoding' sequence into the genome, which had the potential to derive a second gene through mutation. A two-gene scene may have 'run well' with the two corresponding ribozymes promoting the replication of the circular genome from different respects. Circular genomes with more genes might have arisen later in RNA-based protocells. Therefore, circular genomes, which are common in the modern living world, may have had their 'root' at the very beginning of life.

A therapeutic approach for the hepatitis C virus: in silico design of an antisense oligonucleotide-based candidate capsid inhibitor.

Direct-acting antiviral (DAA) drugs have been shown to effectively reduce viral load and cure a high proportion of hepatitis C virus (HCV) infections. However, costs associated with the course of therapy and any possible adverse effects should also be considered. It is important to acknowledge, moreover, that certain groups may not be eligible for treatment. Given that there is currently no approved vaccine for HCV infection, the need for an effective, safe, and accessible treatment remains a crucial priority. The aim of this study is to develop an antisense oligonucleotide (ASO)-based therapeutic drug that can inhibit HCV capsid. After analyzing 817 HCV capsid protein mRNA sequences using the NCBI Virus Data Portal, a conserved region of 7 nucleotides (nt) was identified in all genotypes (1-7). However, because of its high GC% content, this region is not a suitable target for ASO. Conversely, the other highly conserved region, which is only 8 nt long, was preserved in 801 datasets after removing missing and differing sequence data. The candidate ASO was then investigated using computer simulations to assess its potential. Thus, it is possible that the ASO sequence consisting of 8 nt could be a viable therapeutic target for the inhibition of HCV capsid. Furthermore, the 7 nt sequence, which is conserved in all datasets, may be targeted using alternative strategies in lieu of ASO-based targeting.

Predictive pharmacodynamic performance of the Eleveld pharmacokinetic-pharmacodynamic model for propofol: comparison of predicted and measured bispectral index.

BACKGROUND: The Eleveld pharmacokinetic-pharmacodynamic model for propofol predicts bispectral index (BIS) processed electroencephalogram values from estimated effect-site concentrations. We investigated agreement between measured and predicted BIS values during total intravenous anaesthesia (TIVA). METHODS: Forty participants undergoing lower limb surgery received TIVA using remifentanil target-controlled infusions and propofol by manually controlled, target-guided infusions based upon the Eleveld model and directed by two pharmacokinetic computer simulation applications: PKPD Tools and StelSim. We evaluated the predictive performance of the Eleveld model by calculating median prediction errors (BIS units) and by Bland-Altman analyses. We also performed |Bland-Altman analysis of supplementary data provided by the authors of the Eleveld model. RESULTS: Whereas median prediction errors were small (MDPE -1.9, MDAPE 10), the ranges were wide (-18.5 to 24.3 and 1.7 to 24.3). The proportion of MDAPE >10 BIS units was 47.8%. Bland-Altman analysis showed a small mean bias (-0.52 BIS units) with wide limits of agreement (-27.7 to 26.2). Each participant's limits of agreement did not meet the requirements for declaring interchangeability between the two measurements. The measurement differences depended on the BIS values, as indicated by the positive slopes of the differences vs BIS values. Bland-Altman analysis of the Eleveld model supplementary data revealed similar results. CONCLUSION: BIS predictions by the Eleveld model should be interpreted with caution. In spite of the acceptable MDPE and MDAPE, there are unacceptable degrees of both within-subject and between-subject variation during propofol target-controlled infusions. This limits the use of adjusting targeted concentrations to achieve desired simulated BIS values with confidence.

Exploring the therapeutic potential of rutin through investigating its inhibitory mechanism on lactate dehydrogenase: Multi-spectral methods and computer simulation.

Lactate dehydrogenase (LDH), a crucial enzyme in anaerobic glycolysis, plays a pivotal role in the energy metabolism of tumor cells, positioning it as a promising target for tumor treatment. Rutin, a plant-based flavonoid, offers benefits like antioxidant, antiapoptotic, and antineoplastic effects. This study employed diverse experiments to investigate the inhibitory mechanism of rutin on LDH through a binding perspective. The outcomes revealed that rutin underwent spontaneous binding within the coenzyme binding site of LDH, leading to the formation of a stable binary complex driven by hydrophobic forces, with hydrogen bonds also contributing significantly to sustaining the stability of the LDH-rutin complex. The binding constant (Ka) for the LDH-rutin system was 2.692 ± 0.015 × 104 M-1 at 298 K. Furthermore, rutin induced the alterations in the secondary structure conformation of LDH, characterized by a decrease in α-helix and an increase in antiparallel and parallel ß-sheet, and ß-turn. Rutin augmented the stability of coenzyme binding to LDH, which could potentially hinder the conversion process among coenzymes. Specifically, Arg98 in the active site loop of LDH provided essential binding energy contribution in the binding process. These outcomes might explain the dose-dependent inhibition of the catalytic activity of LDH by rutin. Interestingly, both the food additives ascorbic acid and tetrahydrocurcumin could reduce the binding stability of LDH and rutin. Meanwhile, these food additives did not produce positive synergism or antagonism on the rutin binding to LDH. Overall, this research could offer a unique insight into the therapeutic potential and medicinal worth of rutin.

A comprehensive review on computational analysis, research advances, and major findings on Abdominal Aortic Aneurysms for the years 2021 to 2023.

BACKGROUND: Abdominal Aortic Aneurysm (AAA) is a pathological condition characterized by the dilation of the lower part of the aorta, where significant hemodynamic forces are present. The prevalence and high mortality risk associated with AAA remain major concerns within the scientific community. There is a critical need for extensive research to understand the underlying mechanisms, pathophysiological characteristics, and effective detection methods for abdominal aortic abnormalities. Additionally, it is imperative to develop and refine both medical and surgical management strategies. This review aims to indicate the role of computational analysis in the comprehension and management of AAAs and covers recent research studies regarding the computational analysis approach conducted between 2021 and 2023. Computational analysis methods have emerged as sophisticated and non-invasive approaches, providing detailed insights into the complex dynamics of AAA and enhancing our ability to study and manage this condition effectively. METHODS: Computational analysis relies on fluid mechanics principles applied to arterial flow, using the Navier-Stokes equations to model blood flow dynamics. Key hemodynamic indicators relevant to AAAs include Time-Average Wall Shear Stress (TAWSS), Oscillatory Shear Index (OSI), Endothelial Cell Activation Potential (ECAP), and Relative Residence Time (RRT). The primary methods employed for simulating the abdominal aorta and studying its biomechanical environment are Computational Fluid Dynamics (CFD) and Finite Element Methods (FEM). This review paper encompasses a thorough examination of recent literature, focusing on studies conducted between 2021 and 2023. RESULTS: The latest studies have elucidated crucial insights into the blood flow characteristics and geometric attributes of AAAs. Notably, blood flow patterns within AAAs are associated with increased rupture risk, along with elevated intraluminal thrombus volume and specific calcification thresholds. Asymmetric AAAs exhibit heightened risks of rupture and thrombus formation due to low and oscillating wall shear stresses. Moreover, larger aneurysms demonstrate increased wall stress, pressure, and energy loss. Advanced modeling techniques have augmented predictive capabilities concerning growth rates and surgical thresholds. Additionally, the influence of material properties and thrombus volume on wall stress levels is noteworthy, while inlet velocity profiles significantly modulate blood flow dynamics within AAAs. CONCLUSIONS: This review highlights the potential utility of computational modeling. However, the clinical applicability of computational modeling has been limited by methodological variability, despite the ongoing accumulation of evidence supporting the prognostic significance of biomechanical and hemodynamic indices in this field. The establishment of standardized reporting is critical for clinical implementation.

A quality improvement study on how a simulation model can help decision making on organization of ICU wards.

BACKGROUND: Intensive Care Unit (ICU) capacity management is essential to provide high-quality healthcare for critically ill patients. Yet, consensus on the most favorable ICU design is lacking, especially whether ICUs should deliver dedicated or non-dedicated care. The decision for dedicated or non-dedicated ICU design considers a trade-off in the degree of specialization for individual patient care and efficient use of resources for society. We aim to share insights of a model simulating capacity effects for different ICU designs. Upon request, this simulation model is available for other ICUs. METHODS: A discrete event simulation model was developed and used, to study the hypothetical performance of a large University Hospital ICU on occupancy, rejection, and rescheduling rates for a dedicated and non-dedicated ICU design in four different scenarios. These scenarios either simulate the base-case situation of the local ICU, varying bed capacity levels, potential effects of reduced length of stay for a dedicated design and unexpected increased inflow of unplanned patients. RESULTS: The simulation model provided insights to foresee effects of capacity choices that should be made. The non-dedicated ICU design outperformed the dedicated ICU design in terms of efficient use of scarce resources. CONCLUSIONS: The choice to use dedicated ICUs does not only affect the clinical outcome, but also rejection- rescheduling and occupancy rates. Our analysis of a large university hospital demonstrates how such a model can support decision making on ICU design, in conjunction with other operation characteristics such as staffing and quality management.

Trapping or slowing the diffusion of T cell receptors at close contacts initiates T cell signaling.

T cell activation is initiated by T cell receptor (TCR) phosphorylation. This requires the local depletion of large receptor-type phosphatases from "close contacts" formed when T cells interact with surfaces presenting agonistic TCR ligands, but exactly how the ligands potentiate signaling is unclear. It has been proposed that TCR ligands could enhance receptor phosphorylation and signaling just by holding TCRs in phosphatase-depleted close contacts, but this has not been directly tested. We devised simple methods to move the TCR in and out of close contacts formed by T cells interacting with supported lipid bilayers (SLBs) and to slow the receptor's diffusion in the contacts, using a series of anti-CD3ε Fab- and ligand-based adducts of the receptor. TCRs engaging a Fab extended with the large extracellular region of CD45 were excluded from contacts and produced no signaling. Conversely, allowing the extended Fab to become tethered to the SLB trapped the TCR in the close contacts, leading to very strong signaling. Importantly, attaching untethered anti-CD3ε Fab or peptide/MHC ligands, each of which were largely inactive in solution but both of which reduced TCR diffusion in close contacts approximately fivefold, also initiated signaling during cell/SLB contact. Our findings indicate that holding TCRs in close contacts or simply slowing their diffusion in phosphatase-depleted regions of the cell surface suffices to initiate signaling, effects we could reproduce in single-particle stochastic simulations. Our study shows that the TCR is preconfigured for signaling in a way that allows it to be triggered by ligands acting simply as receptor "traps."

The Second Life Metaverse and Its Usefulness in Medical Education After a Quarter of a Century.

The immersive virtual world platform Second Life (SL) was conceived 25 years ago, when Philip Rosedale founded Linden Lab in 1999 with the intention of developing computing hardware that would allow people to immerse themselves in a virtual world. This initial effort was transformed 4 years later into SL, a universally accessible virtual world centered on the user, with commercial transactions and even its own virtual currency, which fully connects with the concept of the metaverse, recently repopularized after the statements of the chief executive officer of Meta (formerly Facebook) in October 2021. SL is considered the best known virtual environment among higher education professionals. This paper aimed to review medical education in the SL metaverse; its evolution; and its possibilities, limitations, and future perspectives, focusing especially on medical education experiences during undergraduate, residency, and continuing medical education. The concept of the metaverse and virtual worlds was described, making special reference to SL and its conceptual philosophy, historical evolution, and technical aspects and capabilities for higher education. A narrative review of the existing literature was performed, including at the same time a point of view from our teaching team after an uninterrupted practical experience of undergraduate and postgraduate medical education in the last 13 years with >4000 users and >10 publications on the subject. From an educational point of view, SL has the advantages of being available 24/7 and creating in the student the important feeling of "being there" and of copresence. This, together with the reproduction of the 3D world, real-time interaction, and the quality of voice communication, makes the immersive experiences unique, generating engagement and a fluid interrelation of students with each other and with their teachers. Various groups of researchers in medical education have developed experiences during these years, which have shown that courses, seminars, workshops and conferences, problem-based learning experiences, evaluations, teamwork, gamification, medical simulation, and virtual objective structured clinical examinations can be successfully carried out. Acceptance from students and faculty is generally positive, recognizing its usefulness for undergraduate medical education and continuing medical education. In the 25 years since its conception, SL has proven to be a virtual platform that connects with the concept of the metaverse, an interconnected, open, and globally accessible system that all humans can access to socialize or share products for free or using a virtual currency. SL remains active and technologically improved since its creation. It is necessary to continue carrying out educational experiences, outlining the organization, objectives, and content and measuring the actual educational impact to make SL a tool of more universal use.

A methodology to estimate postdisaster unmet housing needs using limited data: Application to the 2017 California wildfires.

In the United States, assistance from the Department of Housing and Urban Development (HUD) plays an essential role in supporting the postdisaster recovery of states with unmet housing needs. HUD requires data on unmet needs to appropriate recovery funds. Ground truth data are not available for months after a disaster, however, so HUD uses a simplified approach to estimate unmet housing needs. State authorities argue that HUD's simplified approach underestimates the state's needs. This article presents a methodology to estimate postdisaster unmet housing needs that is accurate and relies only on data obtained shortly after a disaster. Data on the number of damaged buildings are combined with models for expected repair costs. Statistical models for aid distributed by the Federal Emergency Management Agency (FEMA) and the Small Business Administration (SBA) are then developed and used to forecast funding provided by those agencies. With these forecasts, the unmet need to be funded by HUD is estimated. The approach can be used for multiple states and hazard types. As validation, the proposed methodology is used to estimate the unmet housing needs following disasters that struck California in 2017. California authorities suggest that HUD's methodology underestimated the state's needs by a factor of 20. Conversely, the proposed methodology can replicate the estimates by the state authorities and provide accounts of losses, the amount of funding from FEMA and SBA, and the total unmet housing needs without requiring data unavailable shortly after a disaster. Thus, the proposed methodology can help improve HUD's funding appropriation without delays.

In silico toxicity and immunological interactions of components of calcium silicate-based and epoxy resin-based endodontic sealers.

OBJECTIVES: The present study aimed to determine in silico toxicity predictions of test compounds from hydraulic calcium silicate-based sealers (HCSBS) and AH Plus and computationally simulate the interaction between these substances and mediators of periapical inflammation via molecular docking. MATERIALS AND METHODS: All chemical information of the test compounds was obtained from the PubChem site. Predictions for bioavailability and toxicity analyses were determined by the Molinspiration Cheminformatics, pkCSM, ProTox-II and OSIRIS Property Explorer platforms. Molecular docking was performed using the Autodock4 AMDock v.1.5.2 program to analyse interactions between proteins (IL-1ß, IL-6, IL-8, IL-10 and TNF-α) and ligands (calcium silicate hydrate, zirconium oxide, bisphenol-A epoxy resin, dibenzylamine, iron oxide and calcium tungstate) to establish the affinity and bonding mode between systems. RESULTS: Bisphenol-A epoxy resin had the lowest maximum dose tolerated in humans and was the test compound with the largest number of toxicological properties (hepatotoxicity, carcinogenicity and irritant). All systems had favourable molecular docking. However, the ligands bisphenol-A epoxy resin and dibenzylamine had the greatest affinity with the cytokines tested. CONCLUSION: In silico predictions and molecular docking pointed the higher toxicity and greater interaction with mediators of periapical inflammation of the main test compounds from AH Plus compared to those from HCSBS. CLINICAL RELEVANCE: This is the first in silico study involving endodontic materials and may serve as the basis for further research that can generate more data, producing knowledge on the interference of each chemical compound in the composition of different root canal sealers.

Buck Converter with Cubic Static Conversion Ratio.

The paper introduces a step-down converter that exhibits a static conversion ratio of cubic nature, providing an output voltage which is much closer to the input voltage, and at the same duty cycle, compared to a wide class of one-transistor buck-type topologies. Although the proposed topology contains many components, its control is still simple, as it employs only one transistor. A dc analysis is performed, the semiconductor stresses are derived in terms of input and output voltages and output power, revealing that the semiconductor voltage stresses remain acceptable and anyway lower than in other cubic buck topology. All detailed design equations are provided. The state-space approach is used to analyze the converter in the presence of conduction losses and a procedure for calculating the individual power dissipation is provided. The feasibility of the proposed cubic buck topology is first validated by computer simulation and finally confirmed by an experimental 12 V-10 W prototype.

Building Your Future Holographic Mentor: Can We Use Mixed Reality Holograms for Visual Spatial Motor Skills Acquisition in Surgical Education?

Learning surgical skills require critical visual-spatial motor skills. Current learning methods employ costly and limited in-person teaching in addition to supplementation by videos, textbooks, and cadaveric labs. Increasingly limited healthcare resources and in-person training has led to growing concerns for skills acquisition of trainees. Recent Mixed Reality (MR) devices offer an attractive solution to these resource barriers by providing three-dimensional holographic representations of reality that mimic in-person experiences in a portable, individualized, and cost-effective form. We developed and evaluated two holographic MR models to explore the feasibility of visual-spatial motor skill acquisition from a technical development, learning, and usability perspective. In our first, a pair of holographic hands were created and projected in front of the trainee, and participants were evaluated on their ability to learn complex hand motions in comparison to traditional methods of video and apprenticeship-based learning. The second model displayed a 3D holographic model of the middle and inner ear with labeled anatomical structures which users could explore and user experience feedback was obtained. Our studies demonstrated that scores between MR and apprenticeship learning were comparable. All felt MR was an effective learning tool and most noted that the MR models were better than existing didactic methods of learning. Identified advantages of MR included the ability to provide true 3D spatial representation, improved visualization of smaller structures in detail by upscaling the models, and improved interactivity. Our results demonstrate that holographic learning is able to mimic in-person learning for visual-spatial motor skills and could be a new effective form of self-directed apprenticeship learning.