Protein nanobarcodes enable single-step multiplexed fluorescence imaging.

Multiplexed cellular imaging typically relies on the sequential application of detection probes, as antibodies or DNA barcodes, which is complex and time-consuming. To address this, we developed here protein nanobarcodes, composed of combinations of epitopes recognized by specific sets of nanobodies. The nanobarcodes are read in a single imaging step, relying on nanobodies conjugated to distinct fluorophores, which enables a precise analysis of large numbers of protein combinations. Fluorescence images from nanobarcodes were used as input images for a deep neural network, which was able to identify proteins with high precision. We thus present an efficient and straightforward protein identification method, which is applicable to relatively complex biological assays. We demonstrate this by a multicell competition assay, in which we successfully used our nanobarcoded proteins together with neurexin and neuroligin isoforms, thereby testing the preferred binding combinations of multiple isoforms, in parallel.

3D surface reconstruction of cellular cryo-soft X-ray microscopy tomograms using semisupervised deep learning.

Cryo-soft X-ray tomography (cryo-SXT) is a powerful method to investigate the ultrastructure of cells, offering resolution in the tens of nanometer range and strong contrast for membranous structures without requiring labeling or chemical fixation. The short acquisition time and the relatively large field of view leads to fast acquisition of large amounts of tomographic image data. Segmentation of these data into accessible features is a necessary step in gaining biologically relevant information from cryo-soft X-ray tomograms. However, manual image segmentation still requires several orders of magnitude more time than data acquisition. To address this challenge, we have here developed an end-to-end automated 3D segmentation pipeline based on semisupervised deep learning. Our approach is suitable for high-throughput analysis of large amounts of tomographic data, while being robust when faced with limited manual annotations and variations in the tomographic conditions. We validate our approach by extracting three-dimensional information on cellular ultrastructure and by quantifying nanoscopic morphological parameters of filopodia in mammalian cells.

Body Mechanics, Optimality, and Sensory Feedback in the Human Control of Complex Objects.

Humans are adept at a wide variety of motor skills, including the handling of complex objects and using tools. Advances to understand the control of voluntary goal-directed movements have focused on simple behaviors such as reaching, uncoupled to any additional object dynamics. Under these simplified conditions, basic elements of motor control, such as the roles of body mechanics, objective functions, and sensory feedback, have been characterized. However, these elements have mostly been examined in isolation, and the interactions between these elements have received less attention. This study examined a task with internal dynamics, inspired by the daily skill of transporting a cup of coffee, with additional expected or unexpected perturbations to probe the structure of the controller. Using optimal feedback control (OFC) as the basis, it proved necessary to endow the model of the body with mechanical impedance to generate the kinematic features observed in the human experimental data. The addition of mechanical impedance revealed that simulated movements were no longer sensitively dependent on the objective function, a highly debated cornerstone of optimal control. Further, feedforward replay of the control inputs was similarly successful in coping with perturbations as when feedback, or sensory information, was included. These findings suggest that when the control model incorporates a representation of the mechanical properties of the limb, that is, embodies its dynamics, the specific objective function and sensory feedback become less critical, and complex interactions with dynamic objects can be successfully managed.

Could various angulated implant depths affect the positional accuracy of digital impressions? An in vitro study.

PURPOSE: The purpose of this in vitro investigation was to assess how implant depth could affect the three-dimensional positional accuracy of digital impressions made from angulated implants. MATERIALS AND METHODS: Four modified maxillary models were printed and divided into four study groups. In each model, two angulated implant analogs were placed at the sites of the first premolar and first molar at four different depths of 1 (G1), 2 (G2), 3 (G3), and 4 (G4) mm from the models' edentate area. Scan bodies were connected to the analogs, and one operator made 10 full-arch scans for each master model using an intraoral scanner. Afterward, the marginal gingival part of all models was removed, and digital scans were performed for each model using a laboratory scanner to achieve a reference STL file as the control group. One-way ANOVA and Leven's tests were used to measure and compare the 3D distance deviations across research groups after the superimposing test and control scans. RESULTS: A significant difference between research groups was revealed by trueness and precision analysis (p < 0.001). The trueness and precision results obtained for G1 and G4 were significantly better than those for G2 and G3 (p < 0.05). CONCLUSION: This study demonstrated that implant depth could affect the digital implant impressions' 3D positional accuracy.

Preparing to move: Setting initial conditions to simplify interactions with complex objects.

Humans dexterously interact with a variety of objects, including those with complex internal dynamics. Even in the simple action of carrying a cup of coffee, the hand not only applies a force to the cup, but also indirectly to the liquid, which elicits complex reaction forces back on the hand. Due to underactuation and nonlinearity, the object's dynamic response to an action sensitively depends on its initial state and can display unpredictable, even chaotic behavior. With the overarching hypothesis that subjects strive for predictable object-hand interactions, this study examined how subjects explored and prepared the dynamics of an object for subsequent execution of the target task. We specifically hypothesized that subjects find initial conditions that shorten the transients prior to reaching a stable and predictable steady state. Reaching a predictable steady state is desirable as it may reduce the need for online error corrections and facilitate feed forward control. Alternative hypotheses were that subjects seek to reduce effort, increase smoothness, and reduce risk of failure. Motivated by the task of 'carrying a cup of coffee', a simplified cup-and-ball model was implemented in a virtual environment. Human subjects interacted with this virtual object via a robotic manipulandum that provided force feedback. Subjects were encouraged to first explore and prepare the cup-and-ball before initiating a rhythmic movement at a specified frequency between two targets without losing the ball. Consistent with the hypotheses, subjects increased the predictability of interaction forces between hand and object and converged to a set of initial conditions followed by significantly decreased transients. The three alternative hypotheses were not supported. Surprisingly, the subjects' strategy was more effortful and less smooth, unlike the observed behavior in simple reaching movements. Inverse dynamics of the cup-and-ball system and forward simulations with an impedance controller successfully described subjects' behavior. The initial conditions chosen by the subjects in the experiment matched those that produced the most predictable interactions in simulation. These results present first support for the hypothesis that humans prepare the object to minimize transients and increase stability and, overall, the predictability of hand-object interactions.

Investigating the entropic nature of membrane-mediated interactions driving the aggregation of peripheral proteins.

Peripheral membrane-associated proteins are known to accumulate on the surface of biomembranes as a result of membrane-mediated interactions. For a pair of rotationally-symmetric curvature-inducing proteins, membrane mechanics at the low-temperature limit predicts pure repulsion. On the other hand, temperature-dependent entropic forces arise between pairs of stiff-binding proteins suppressing membrane fluctuations. These Casimir-like interactions have thus been suggested as candidates for attractive forces leading to aggregation. With dense assemblies of peripheral proteins on the membrane, both these abstractions encounter short-range and multi-body complications. Here, we make use of a particle-based membrane model augmented with flexible peripheral proteins to quantify purely membrane-mediated interactions and investigate their underlying nature. We introduce a continuous reaction coordinate corresponding to the progression of protein aggregation. We obtain free energy and entropy landscapes for different surface concentrations along this reaction coordinate. In parallel, we investigate time-dependent estimates of membrane entropy corresponding to membrane undulations and coarse-grained director field and how they change dynamically with protein aggregation. Congruent outcomes of the two approaches point to the conclusion that for low surface concentrations, interactions with an entropic nature may drive the aggregation. But at high concentrations, enthalpic contributions due to concerted membrane deformation by protein clusters are dominant.

Hydrodynamic coupling for particle-based solvent-free membrane models.

The great challenge with biological membrane systems is the wide range of scales involved, from nanometers and picoseconds for individual lipids to the micrometers and beyond millisecond for cellular signaling processes. While solvent-free coarse-grained membrane models are convenient for large-scale simulations and promising to provide insight into slow processes involving membranes, these models usually have unrealistic kinetics. One major obstacle is the lack of an equally convenient way of introducing hydrodynamic coupling without significantly increasing the computational cost of the model. To address this, we introduce a framework based on anisotropic Langevin dynamics, for which major in-plane and out-of-plane hydrodynamic effects are modeled via friction and diffusion tensors from analytical or semi-analytical solutions to Stokes hydrodynamic equations. Using this framework, in conjunction with our recently developed membrane model, we obtain accurate dispersion relations for planar membrane patches, both free-standing and in the vicinity of a wall. We briefly discuss how non-equilibrium dynamics is affected by hydrodynamic interactions. We also measure the surface viscosity of the model membrane and discuss the affecting dissipative mechanisms.

ß-Thalassemia minor & renal tubular dysfunction: is there any association?

OBJECTIVE: Beta(ß)-thalassemia is one of the most common hereditary hematologic disorders. Patients with thalassemia minor (TM) are often asymptomatic and the rate of renal dysfunction is unknown in these patients. Due to the high prevalence of renal dysfunction in Iran, the current study aimed to determine renal tubular dysfunction in patients with beta-TM. METHODS: In this case-control study, 40 patients with TM and 20 healthy subjects were enrolled and urinary and blood biochemical analysis was done on their samples. Renal tubular function indices were determined and compared in both groups. Data was analyzed by SPSS software, version 20.0. RESULTS: The fraction excretion (FE) of uric acid was 8.31 ± 3.98% in the case and 6.2 ± 34.71% in the control group (p = 0.048). Also, FE of potassium was significantly higher in patients with TM (3.22 ± 3.13 vs. 1.91 ± 0.81; p = 0.036). The mean Plasma NGAL level was 133.78 ± 120.28 ng/mL in patients with thalassemia and 84.55 ± 45.50 ng/mL in the control group (p = 0.083). At least one parameter of tubular dysfunction was found in 45% of patients with thalassemia. CONCLUSION: Based on the results of this study, the prevalence of tubular dysfunction in beta-thalassemia minor patients is high. Due to the lack of knowledge of patients about this disorder, periodic evaluation of renal function in TM patients can prevent renal failure by early diagnosis.

Evaluation of CCR5-Δ32 mutation among individuals with high risk behaviors, neonates born to HIV-1 infected mothers, HIV-1 infected individuals, and healthy people in an Iranian population.

One of the important genetic factors related to resistance to HIV-1 infection is the presence of the C-C chemokine receptor type 5 delta 32 (CCR5-Δ32) homozygous genotype (Δ32/Δ32). The aim of this study was to evaluate the CCR5-Δ32 mutation among individuals with high-risk behaviors, neonates born to HIV-1-infected mothers in the prevention of mother-to-child transmission (PMTCT) project, HIV-1-infected individuals, and healthy people. The frequency of the CCR5-Δ32 genotype was assessed in a cross-sectional survey carried out from March 2014 to March 2019 among four different groups of the Iranian population. Genomic DNA was extracted from peripheral blood mononuclear cells of 140 Iranian healthy people, 84 neonates born to HIV-1-infected mothers in the PMTCT project, 71 people with high-risk behaviors, and 76 HIV-1-infected individuals. The polymerase chain reaction method was used for the amplification of the CCR5 gene. The CCR5-Δ32 heterozygous deletion was detected in five (6.6%) HIV-1-infected individuals, four (4.7%) neonates born to HIV-1 positive mothers, two (1.4%) healthy people, and also three (4.2%) people with high-risk behaviors whereas the CCR5-Δ32 homozygous deletion was absent in all the groups (Fisher's exact test, P = .0242). The allele of CCR5-Δ32 homozygous was not detected in the four study groups, and no significant difference was seen in the frequency of the CCR5Δ32 heterozygous allele between HIV seropositive and seronegative individuals. Therefore, it seems that this allele alone cannot explain the natural resistance to HIV-1 infection and probably several mechanisms are responsible for these processes and it should be further investigated.

An error-tuned model for sensorimotor learning.

Current models of sensorimotor control posit that motor commands are generated by combining multiple modules which may consist of internal models, motor primitives or motor synergies. The mechanisms which select modules based on task requirements and modify their output during learning are therefore critical to our understanding of sensorimotor control. Here we develop a novel modular architecture for multi-dimensional tasks in which a set of fixed primitives are each able to compensate for errors in a single direction in the task space. The contribution of the primitives to the motor output is determined by both top-down contextual information and bottom-up error information. We implement this model for a task in which subjects learn to manipulate a dynamic object whose orientation can vary. In the model, visual information regarding the context (the orientation of the object) allows the appropriate primitives to be engaged. This top-down module selection is implemented by a Gaussian function tuned for the visual orientation of the object. Second, each module's contribution adapts across trials in proportion to its ability to decrease the current kinematic error. Specifically, adaptation is implemented by cosine tuning of primitives to the current direction of the error, which we show to be theoretically optimal for reducing error. This error-tuned model makes two novel predictions. First, interference should occur between alternating dynamics only when the kinematic errors associated with each oppose one another. In contrast, dynamics which lead to orthogonal errors should not interfere. Second, kinematic errors alone should be sufficient to engage the appropriate modules, even in the absence of contextual information normally provided by vision. We confirm both these predictions experimentally and show that the model can also account for data from previous experiments. Our results suggest that two interacting processes account for module selection during sensorimotor control and learning.

Particle-based membrane model for mesoscopic simulation of cellular dynamics.

We present a simple and computationally efficient coarse-grained and solvent-free model for simulating lipid bilayer membranes. In order to be used in concert with particle-based reaction-diffusion simulations, the model is purely based on interacting and reacting particles, each representing a coarse patch of a lipid monolayer. Particle interactions include nearest-neighbor bond-stretching and angle-bending and are parameterized so as to reproduce the local membrane mechanics given by the Helfrich energy density over a range of relevant curvatures. In-plane fluidity is implemented with Monte Carlo bond-flipping moves. The physical accuracy of the model is verified by five tests: (i) Power spectrum analysis of equilibrium thermal undulations is used to verify that the particle-based representation correctly captures the dynamics predicted by the continuum model of fluid membranes. (ii) It is verified that the input bending stiffness, against which the potential parameters are optimized, is accurately recovered. (iii) Isothermal area compressibility modulus of the membrane is calculated and is shown to be tunable to reproduce available values for different lipid bilayers, independent of the bending rigidity. (iv) Simulation of two-dimensional shear flow under a gravity force is employed to measure the effective in-plane viscosity of the membrane model and show the possibility of modeling membranes with specified viscosities. (v) Interaction of the bilayer membrane with a spherical nanoparticle is modeled as a test case for large membrane deformations and budding involved in cellular processes such as endocytosis. The results are shown to coincide well with the predicted behavior of continuum models, and the membrane model successfully mimics the expected budding behavior. We expect our model to be of high practical usability for ultra coarse-grained molecular dynamics or particle-based reaction-diffusion simulations of biological systems.

Integron types, gene cassettes and antimicrobial resistance profile of Acinetobacter baumannii isolated from BAL samples in Babol, north of Iran.

Multi-drug resistant isolates of Acinetobacter baumannii have created therapeutic problems worldwide. This current study was intended to determine the Integron types, gene cassettes and antimicrobial resistance profile of A. baumannii isolated from BAL samples in Babol, north of Iran. During a 15-month period, 35 A. baumannii isolates were studied. Different classes of antimicrobial agents were used to determine the resistance ratios. Multiplex-PCR was used to detect different types of integrons and associated gene cassettes. The resistance rates to GM, FEP, AK, TOB, CP, PIP, SAM, IPM, SXT, CTX, CAZ, CL, TIM, MEM, and TZP were 85.7%, 100%, 91.4%, 68.5%, 94.3%, 88.5%, 97.1%, 94.3%, 100%, 100%, 100%, 0.0%, 91.4%, 94.3% and 91.4%, respectively. The distribution analysis of int genes showed that 25.7%, 88.6% and 28.6% of isolates carried the intI, intII and intIII genes, respectively. The prevalence of aadB, dfrA1, bla-OXA30 and aadA1 genes were 94.3%, 77.1%, 40% and 5.7%, respectively. The current study showed that a high level of A. baumannii isolates harbor integrons in our therapeutic center, which may lead to distribution of multiple antimicrobial resistance. The different types of gene cassette arrays in the present study highlight the important role of geographical features in MDR isolates dissemination which could be credited to different profiles of drug consumption in different areas. The findings emphasized that the need for continuous surveillance to prevent distribution of multidrug resistance among A. baumannii strains in Iran.

Comparison consequences of Jackson-Pratt drain versus chest tube after coronary artery bypass grafting: A randomized controlled clinical trial.

BACKGROUND: Chest tubes are used in every case of coronary artery bypass grafting (CABG) to evacuate shed blood from around the heart and lungs. This study was designed to assess the effective of Jackson-Pratt drain in compare with conventional chest drains after CABG. MATERIALS AND METHODS: This was a randomized controlled trial that conducted on 218 patients in Chamran hospital from February to December 2016. Eligible patients were randomized in a 1:1 ratio. Jackson-Pratt drain group had 109 patients who received a chest tube insertion in the pleural space of the left lung and a Jackson-Pratt drain in mediastinum, and Chest tube drainage group had 109 patients who received double chest tube insertion in the pleural space of the left lung and the mediastinum. RESULTS: The incidence of pleural effusions in Jackson-Pratt drain group and chest tube group were not statistically different. The pain score at 2-h in Drain group was significantly higher than chest tube group (P = 0.001), but the trend of pain score between groups was not significantly different (P = 0.097). The frequency of tamponade and atrial fibrillation (AF) were significantly lower in Jackson-Pratt drain group (P < 0.05). CONCLUSION: The Jackson-Pratt drain is equally effective for preventing cardiac tamponade, pleural effusions, and pain intensity in patients after CABG when compared with conventional chest tubes, but was significantly superior regarding efficacy to hospital and Intensive Care Unit length of stay and the incidence of AF.

Efficacy of olanzapine in symptom relief and quality of life in gastric cancer patients receiving chemotherapy.

BACKGROUND: Considering the incidence and prevalence rates of gastric cancer in Mazandaran Province of Iran, this research was performed to evaluate the efficacy and safety of olanzapine in symptom relief and quality of life (QOL) improvement of gastric patients receiving chemotherapy. MATERIALS AND METHODS: This clinical trial was conducted on thirty new cases of gastric cancer patients whose treatment protocol was planned on chemotherapy and were allocated into two groups by simple random sampling. Intervention group (15 patients) received olanzapine tablets (2.5-10 mg/day) a day before the beginning of chemotherapy; in the 1st day of chemotherapy to 8 weeks after chemotherapy, besides the routine treatment regimens. The control group received only the routine treatment regimens. The patients were followed for 8 weeks after intervention. All of the patients were assessed with Hospital Anxiety and Depression Scale (HADS) and WHO-QOL-BREF questionnaires; further, Rhodes index was used to evaluate nausea and vomiting (N/V) status. RESULTS: All the recruited patients continued the allocated interventions (no lost to follow-up). N/V decreased in the case group, but the difference was not statistically significant (P = 0.438). The patients' appetite and body mass index increased (P = 0.006). Anxiety and depression subscales of HADS had significant differences between the two groups (P < 0.001) in the 4th and 8th week after treatment. Among the different subdomains of QOL, only physical health improved significantly after intervention (P < 0.05), but no significant difference was observed in other subdomains and also total QOL score (P > 0.05). No significant increase was observed in fasting and 2-h postprandial blood glucose and lipid profile (P > 0.05). CONCLUSION: Olanzapine can be considered as an effective drug to increase appetite and decrease anxiety and depression in patients with gastric cancer.

Dynamic framework for large-scale modeling of membranes and peripheral proteins.

In this chapter, we present a novel computational framework to study the dynamic behavior of extensive membrane systems, potentially in interaction with peripheral proteins, as an alternative to conventional simulation methods. The framework effectively describes the complex dynamics in protein-membrane systems in a mesoscopic particle-based setup. Furthermore, leveraging the hydrodynamic coupling between the membrane and its surrounding solvent, the coarse-grained model grounds its dynamics in macroscopic kinetic properties such as viscosity and diffusion coefficients, marrying the advantages of continuum- and particle-based approaches. We introduce the theoretical background and the parameter-space optimization method in a step-by-step fashion, present the hydrodynamic coupling method in detail, and demonstrate the application of the model at each stage through illuminating examples. We believe this modeling framework to hold great potential for simulating membrane and protein systems at biological spatiotemporal scales, and offer substantial flexibility for further development and parametrization.

Acute effects of Nordic hamstring exercise on hip and knee joints proprioception.

BACKGROUND AND OBJECTIVES: Nordic Hamstring Exercise (NHE) is one of the best exercises proposed for injury prevention of hamstring muscles. However, its effects on lower extremity proprioception are unclear. The aim of this study was to investigate the immediate effects of a single bout of NHE on hip and knee joints' proprioception. METHODS: Forty collegiate male soccer players participated in this study with a mean age of 22.85 ± 1.82 years and were randomized into either control (n = 20) or experimental (n = 20) groups. Each subject participated in pre-test measurements in which hip and knee active joints position sense (JPS) were assessed in standing and lying tasks using the image-capturing method. The experimental group then performed three sets of NHE with 10 repetitions in each set, while the control group rested for 10 min. Paired and independent t-tests were used for calculating the differences within and between groups on SPSS software, respectively. The level of significance was P ≤ 0.05. RESULTS: Hip JPS in the lying task and knee JPS in both of the standing and lying tasks were impaired significantly after performing a single bout of NHE (P ≤ 0.05). However, the effects of this exercise on hip JPS in the standing task were not significant (P ≥ 0.05). CONCLUSIONS: NHE performing with three sets of 10 repetitions can significantly impair hip and knee JPS immediately after exercise and reduce the proprioception acuity of the lower limbs. It is recommended to perform this exercise at a time rather than before training or match sessions.

Inferring control objectives in a virtual balancing task in humans and monkeys.

Natural behaviors have redundancy, which implies that humans and animals can achieve their goals with different strategies. Given only observations of behavior, is it possible to infer the control objective that the subject is employing? This challenge is particularly acute in animal behavior because we cannot ask or instruct the subject to use a particular strategy. This study presents a three-pronged approach to infer an animal's control objective from behavior. First, both humans and monkeys performed a virtual balancing task for which different control strategies could be utilized. Under matched experimental conditions, corresponding behaviors were observed in humans and monkeys. Second, a generative model was developed that represented two main control objectives to achieve the task goal. Model simulations were used to identify aspects of behavior that could distinguish which control objective was being used. Third, these behavioral signatures allowed us to infer the control objective used by human subjects who had been instructed to use one control objective or the other. Based on this validation, we could then infer objectives from animal subjects. Being able to positively identify a subject's control objective from observed behavior can provide a powerful tool to neurophysiologists as they seek the neural mechanisms of sensorimotor coordination.

Sub-membrane actin rings compartmentalize the plasma membrane.

The compartmentalization of the plasma membrane (PM) is a fundamental feature of cells. The diffusivity of membrane proteins is significantly lower in biological than in artificial membranes. This is likely due to actin filaments, but assays to prove a direct dependence remain elusive. We recently showed that periodic actin rings in the neuronal axon initial segment (AIS) confine membrane protein motion between them. Still, the local enrichment of ion channels offers an alternative explanation. Here we show, using computational modeling, that in contrast to actin rings, ion channels in the AIS cannot mediate confinement. Furthermore, we show, employing a combinatorial approach of single particle tracking and super-resolution microscopy, that actin rings are close to the PM and that they confine membrane proteins in several neuronal cell types. Finally, we show that actin disruption leads to loss of compartmentalization. Taken together, we here develop a system for the investigation of membrane compartmentalization and show that actin rings compartmentalize the PM.

Trajectory of human movement during sit to stand: a new modeling approach based on movement decomposition and multi-phase cost function.

The purpose of this work is to develop a computational model to describe the task of sit to stand (STS). STS is an important movement skill which is frequently performed in human daily activities, but has rarely been studied from the perspective of optimization principles. In this study, we compared the recorded trajectories of STS with the trajectories generated by several conventional optimization-based models (i.e., minimum torque, minimum torque change and kinetic energy cost models) and also with the trajectories produced by a novel multi-phase cost model (MPCM). In the MPCM, we suggested that any complex task, such as STS, is decomposable into successive motion phases, so that each phase requires a distinct strategy to be performed. In this way, we proposed a multi-phase cost function to describe the STS task. The results revealed that the conventional optimization-based models failed to correctly predict the invariable features of STS, such as hip flexion and ankle dorsiflexion movements. However, the MPCM not only predicted the general features of STS with a sufficient accuracy, but also showed a potential flexibility to distinguish between the movement strategies from one subject to the other. According to the results, it seems plausible to hypothesize that the central nervous system might apply different strategies when planning different phases of a complex task. The application areas of the proposed model could be generating optimized trajectories of STS for clinical applications (such as functional electrical stimulation) or providing clinical and engineering insights to develop more efficient rehabilitation devices and protocols.

Infectious endocardial intracardiac defibrillator lead, infectious pericarditis, and delayed constrictive pericarditis.

The usage of Implantable Cardiac Defibrillator (ICD) since 1980s is becoming more popular these days. The rate of both, endocarditis and constrictive pericarditis are low but it still needs attention. We are reporting a rare case of ICD endocarditis as a result of toe infection in a diabetic patient. This was followed by infectious pericarditis after device removal by open heart surgery and then delayed constrictive pericarditis.