The Mathematical Modeling of the Host-Virus Interaction in Dengue Virus Infection: A Quantitative Study.

Infectious diseases, such as Dengue fever, pose a significant public health threat. Developing a reliable mathematical model plays a crucial role in quantitatively elucidating the kinetic characteristics of antibody-virus interactions. By integrating previous models and incorporating the antibody dynamic theory, we have constructed a novel and robust model that can accurately simulate the dynamics of antibodies and viruses based on a comprehensive understanding of immunology principles. It explicitly formulates the viral clearance effect of antibodies, along with the positive feedback stimulation of virus-antibody complexes on antibody regeneration. In addition to providing quantitative insights into the dynamics of antibodies and viruses, the model exhibits a high degree of accuracy in capturing the kinetics of viruses and antibodies in Dengue fever patients. This model offers a valuable solution to modeling the differences between primary and secondary Dengue infections concerning IgM/IgG antibodies. Furthermore, it demonstrates that a faster removal rate of antibody-virus complexes might lead to a higher peak viral loading and worse clinical symptom. Moreover, it provides a reasonable explanation for the antibody-dependent enhancement of heterogeneous Dengue infections. Ultimately, this model serves as a foundation for constructing an optimal mathematical model to combat various infectious diseases in the future.

Bioinformatic analysis of defective viral genomes in SARS-CoV-2 and its impact on population infection characteristics.

DVGs (Defective Viral Genomes) are prevalent in RNA virus infections. In this investigation, we conducted an analysis of high-throughput sequencing data and observed widespread presence of DVGs in SARS-CoV-2. Comparative analysis between SARS-CoV-2 and diverse DNA viruses revealed heightened susceptibility to damage and increased sequencing sample heterogeneity within the SARS-CoV-2 genome. Whole-genome sequencing depth variability analysis exhibited a higher coefficient of variation for SARS-CoV-2, while DVG analysis indicated a significant proportion of recombination sites, signifying notable genome heterogeneity and suggesting that a large proportion of assembled virus particles contain incomplete RNA sequences. Moreover, our investigation explored the sequencing depth and DVG content differences among various strains. Our findings revealed that as the virus evolves, there is a notable increase in the proportion of intact genomes within virus particles, as evidenced by third-generation sequencing data. Specifically, the proportion of intact genome in the Omicron strain surpassed that of the Delta and Alpha strains. This observation effectively elucidates the heightened infectiousness of the Omicron strain compared to the Delta and Alpha strains. We also postulate that this improvement in completeness stems from enhanced virus assembly capacity, as the Omicron strain can promptly facilitate the binding of RNA and capsid protein, thereby reducing the exposure time of vulnerable virus RNA in the host environment and significantly mitigating its degradation. Finally, employing mathematical modeling, we simulated the impact of DVG effects under varying environmental factors on infection characteristics and population evolution. Our findings provide an explanation for the close association between symptom severity and the extent of virus invasion, as well as the substantial disparity in population infection characteristics caused by the same strain under distinct environmental conditions. This study presents a novel approach for future virus research and vaccine development.

An agent-based model with antibody dynamics information in COVID-19 epidemic simulation.

Accurate prediction of the temporal and spatial characteristics of COVID-19 infection is of paramount importance for effective epidemic prevention and control. In order to accomplish this objective, we incorporated individual antibody dynamics into an agent-based model and devised a methodology that encompasses the dynamic behaviors of each individual, thereby explicitly capturing the count and spatial distribution of infected individuals with varying symptoms at distinct time points. Our model also permits the evaluation of diverse prevention and control measures. Based on our findings, the widespread employment of nucleic acid testing and the implementation of quarantine measures for positive cases and their close contacts in China have yielded remarkable outcomes in curtailing a less transmissible yet more virulent strain; however, they may prove inadequate against highly transmissible and less virulent variants. Additionally, our model excels in its ability to trace back to the initial infected case (patient zero) through early epidemic patterns. Ultimately, our model extends the frontiers of traditional epidemiological simulation methodologies and offers an alternative approach to epidemic modeling.

The Noninvasive Sonothermogenetics Used for Neuromodulation in M1 Region of Mice Brain by Overexpression of TRPV1.

Sonogenetics is preferred for neuroregulation and the treatment of brain diseases due to its noninvasive properties. Ultrasonic stimulation produces thermal and mechanical effects, among others. Since transient receptor potential vanilloid 1 (TRPV1) could be activated at 42 °C, it is overexpressed in the M1 region of the mouse motor cortex to sense the change of temperature upon being stimulated by focused ultrasound. Whether the heat generated by ultrasonic stimulation could activate TRPV1 in the M1 region and induce changes in electromyography (EMG) signals collected from the mice's triceps was carefully verified. The position of the focused ultrasound and the temperature of the tissue at the location of the focused position were simulated using COMSOL software and verified via experiments. For Neuro-2a cells with TRPV1 overexpression, 42 °C could activate the TRPV1 and induce calcium influx. For mice with TRPV1 overexpression in the M1 region, tissue temperature of >42 °C in the M1 region induces an increased number of cfos, suggesting that neurons with overexpressed TRPV1 in the M1 region can be activated using focused ultrasound. Furthermore, when the temperature is >42 °C, the peak-to-peak value of the EMG signal for mice with TRPV1 overexpression in the M1 region was higher than that for mice without TRPV1 overexpression. The immunohistochemical results showed that ultrasound was not harmful to the stimulation site. The noninvasive ultrasound stimulation combined with thermosensitive protein TRPV1 overexpressed in neurocytes as sonothermogenetics technology has great potential to be used for the treatment of neurological diseases.

Antibody Dynamics Simulation-A Mathematical Exploration of Clonal Deletion and Somatic Hypermutation.

We have employed mathematical modeling techniques to construct a comprehensive framework for elucidating the intricate response mechanisms of the immune system, facilitating a deeper understanding of B-cell clonal deletion and somatic hypermutation. Our improved model introduces innovative mechanisms that shed light on positive and negative selection processes during T-cell and B-cell development. Notably, clonal deletion is attributed to the attenuated immune stimulation exerted by self-antigens with high binding affinities, rendering them less effective in eliciting subsequent B-cell maturation and differentiation. Secondly, our refined model places particular emphasis on the crucial role played by somatic hypermutation in modulating the immune system's functionality. Through extensive investigation, we have determined that somatic hypermutation not only expedites the production of highly specific antibodies pivotal in combating microbial infections but also serves as a regulatory mechanism to dampen autoimmunity and enhance self-tolerance within the organism. Lastly, our model advances the understanding of the implications of antibody in vivo evolution in the overall process of organismal aging. With the progression of time, the age-associated amplification of autoimmune activity becomes apparent. While somatic hypermutation effectively delays this process, mitigating the levels of autoimmune response, it falls short of reversing this trajectory entirely. In conclusion, our advanced mathematical model offers a comprehensive and scholarly approach to comprehend the intricacies of the immune system. By encompassing novel mechanisms for selection, emphasizing the functional role of somatic hypermutation, and illuminating the consequences of in vivo antibody evolution, our model expands the current understanding of immune responses and their implications in aging.

Precision Joint RF Measurement of Inter-Satellite Range and Time Difference and Scalable Clock Synchronization for Multi-Microsatellite Formations.

The rapid development of multi-satellite formations requires inter-satellite radio frequency (RF) measurement to be both precise and scalable. The navigation estimation of multi-satellite formations using a unified time reference demands the simultaneous RF measurement of the inter-satellite range and time difference. However, high-precision inter-satellite RF ranging and time difference measurements are investigated separately in existing studies. Different from the conventional two-way ranging (TWR) method, which is limited by its reliance on a high-performance atomic clock and navigation ephemeris, asymmetric double-sided two-way ranging (ADS-TWR)-based inter-satellite measurement schemes can eliminate such reliance while ensuring measurement precision and scalability. However, ADS-TWR was originally proposed for ranging-only applications. In this study, by fully exploiting the time-division non-coherent measurement characteristic of ADS-TWR, a joint RF measurement method is proposed to obtain the inter-satellite range and time difference simultaneously. Moreover, a multi-satellite clock synchronization scheme is proposed based on the joint measurement method. The experimental results show that when inter-satellite ranges are hundreds of kilometers, the joint measurement system has a centimeter-level accuracy for ranging and a hundred-picosecond-level accuracy for time difference measurement, and the maximum clock synchronization error was only about 1 ns.

The lack of Troponin I Ser-23/24 phosphorylation is detrimental to in vivo cardiac function and exacerbates cardiac disease.

Troponin I (TnI) is a key regulator of cardiac contraction and relaxation with TnI Ser-23/24 phosphorylation serving as a myofilament mechanism to modulate cardiac function. Basal cardiac TnI Ser-23/24 phosphorylation is high such that both increased and decreased TnI phosphorylation may modulate cardiac function. While the effects of increasing TnI Ser-23/24 phosphorylation on heart function are well established, the effects of decreasing TnI Ser-23/24 phosphorylation are not clear. To understand the in vivo role of decreased TnI Ser-23/24 phosphorylation, mice expressing TnI with Ser-23/24 mutated to alanine (TnI S23/24A) that lack the ability to be phosphorylated at these residues were subjected to echocardiography and pressure-volume hemodynamic measurements in the absence or presence of physiological (pacing increasing heart rate or adrenergic stimulation) or pathological (transverse aortic constriction (TAC)) stress. In the absence of pathological stress, the lack of TnI Ser-23/24 phosphorylation impaired systolic and diastolic function. TnI S23/24A mice also had an impaired systolic and diastolic response upon stimulation increased heart rate and an impaired adrenergic response upon dobutamine infusion. Following pathological cardiac stress induced by TAC, TnI S23/24A mice had a greater increase in ventricular mass, worse diastolic function, and impaired systolic and diastolic function upon increasing heart rate. These findings demonstrate that mice lacking the ability to phosphorylate TnI at Ser-23/24 have impaired in vivo systolic and diastolic cardiac function, a blunted cardiac reserve and a worse response to pathological stress supporting decreased TnI Ser23/24 phosphorylation is a modulator of these processes in vivo.

A Novel Mathematical Model That Predicts the Protection Time of SARS-CoV-2 Antibodies.

Infectious diseases such as SARS-CoV-2 pose a considerable threat to public health. Constructing a reliable mathematical model helps us quantitatively explain the kinetic characteristics of antibody-virus interactions. A novel and robust model is developed to integrate antibody dynamics with virus dynamics based on a comprehensive understanding of immunology principles. This model explicitly formulizes the pernicious effect of the antibody, together with a positive feedback stimulation of the virus-antibody complex on the antibody regeneration. Besides providing quantitative insights into antibody and virus dynamics, it demonstrates good adaptivity in recapturing the virus-antibody interaction. It is proposed that the environmental antigenic substances help maintain the memory cell level and the corresponding neutralizing antibodies secreted by those memory cells. A broader application is also visualized in predicting the antibody protection time caused by a natural infection. Suitable binding antibodies and the presence of massive environmental antigenic substances would prolong the protection time against breakthrough infection. The model also displays excellent fitness and provides good explanations for antibody selection, antibody interference, and self-reinfection. It helps elucidate how our immune system efficiently develops neutralizing antibodies with good binding kinetics. It provides a reasonable explanation for the lower SARS-CoV-2 mortality in the population that was vaccinated with other vaccines. It is inferred that the best strategy for prolonging the vaccine protection time is not repeated inoculation but a directed induction of fast-binding antibodies. Eventually, this model will inform the future construction of an optimal mathematical model and help us fight against those infectious diseases.

More or less deadly? A mathematical model that predicts SARS-CoV-2 evolutionary direction.

SARS-CoV-2 has caused tremendous deaths globally. It is of great value to predict the evolutionary direction of SARS-CoV-2. In this paper, we proposed a novel mathematical model that could predict the evolutionary trend of SARS-CoV-2. We focus on the mutational effects on viral assembly capacity. A robust coarse-grained mathematical model is constructed to simulate the virus dynamics in the host body. Both virulence and transmissibility can be quantified in this model. A delicate equilibrium point that optimizes the transmissibility can be numerically obtained. Based on this model, the virulence of SARS-CoV-2 might further decrease, accompanied by an enhancement of transmissibility. However, this trend is not continuous; its virulence will not disappear but remains at a relatively stable range. A virus assembly model which simulates the virus packing process is also proposed. It can be explained why a few mutations would lead to a significant divergence in clinical performance, both in the overall particle formation quantity and virulence. This research provides a novel mathematical attempt to elucidate the evolutionary driving force in RNA virus evolution.

Ectonucleoside triphosphate diphosphohydrolase-1 (CD39) impacts TGF-ß1 responses: insights into cardiac fibrosis and function following myocardial infarction.

Extracellular purine nucleotides and nucleosides released from activated or injured cells influence multiple aspects of cardiac physiology and pathophysiology. Ectonucleoside triphosphate diphosphohydrolase-1 (ENTPD1; CD39) hydrolyzes released nucleotides and thereby regulates the magnitude and duration of purinergic signaling. However, the impact of CD39 activity on post-myocardial infarction (MI) remodeling is incompletely understood. We measured the levels and activity of ectonucleotidases in human left ventricular samples from control and ischemic cardiomyopathy (ICM) hearts and examined the impact of ablation of Cd39 expression on post-myocardial infarction remodeling in mice. We found that human CD39 levels and activity are significantly decreased in ICM hearts (n = 5) compared with control hearts (n = 5). In mice null for Cd39, cardiac function and remodeling are significantly compromised in Cd39-/- mice following myocardial infarction. Fibrotic markers including plasminogen activator inhibitor-1 (PAI-1) expression, fibrin deposition, α-smooth muscle actin (αSMA), and collagen expression are increased in Cd39-/- hearts. Importantly, we found that transforming growth factor ß1 (TGF-ß1) stimulates ATP release and induces Cd39 expression and activity on cardiac fibroblasts, constituting an autocrine regulatory pathway not previously appreciated. Absence of CD39 activity on cardiac fibroblasts exacerbates TGF-ß1 profibrotic responses. Treatment with exogenous ectonucleotidase rescues this profibrotic response in Cd39-/- fibroblasts. Together, these data demonstrate that CD39 has important interactions with TGF-ß1-stimulated autocrine purinergic signaling in cardiac fibroblasts and dictates outcomes of cardiac remodeling following myocardial infarction. Our results reveal that ENTPD1 (CD39) regulates TGF-ß1-mediated fibroblast activation and limits adverse cardiac remodeling following myocardial infarction.NEW & NOTEWORTHY We show that CD39 is a critical modulator of TGF-ß1-mediated fibroblast activation and cardiac remodeling following myocardial infarction via modulation of nucleotide signaling. TGF-ß1-induced CD39 expression generates a negative feedback loop that attenuates cardiac fibroblast activation. In the absence of CD39 activity, collagen deposition is increased, elastin expression is decreased, and diastolic dysfunction is worsened. Treatment with ecto-apyrase attenuates the TGF-ß1-induced profibrotic cardiac fibroblast phenotype, revealing a novel approach to combat post-myocardial infarction cardiac fibrosis.

Statistical analysis supports UTR (untranslated region) deletion theory in SARS-CoV-2.

It was noticed that the mortality rate of SARS-CoV-2 infection experienced a significant declination in the early stage of the epidemic. We suspect that the sharp deterioration of virus toxicity is related to the deletion of the untranslated region (UTR) of the virus genome. It was found that the genome length of SARS-CoV-2 engaged a significant truncation due to UTR deletion after a mega-sequence analysis. Sequence similarity analysis further indicated that short UTR strains originated from its long UTR ancestors after an irreversible deletion. A good correlation was discovered between genome length and mortality, which demonstrated that the deletion of the virus UTR significantly affected the toxicity of the virus. This correlation was further confirmed in a significance analysis of the genetic influence on the clinical outcomes. The viral genome length of hospitalized patients was significantly more extensive than that of asymptomatic patients. In contrast, the viral genome length of asymptomatic was considerably longer than that of ordinary patients with symptoms. A genome-level mutation scanning was performed to systematically evaluate the influence of mutations at each position on virulence. The results indicated that UTR deletion was the primary driving force in alternating virus virulence in the early evolution. In the end, we proposed a mathematical model to explain why this UTR deletion was not continuous.

A Continuous Markov-Chain Model for the Simulation of COVID-19 Epidemic Dynamics.

To address the urgent need to accurately predict the spreading trend of the COVID-19 epidemic, a continuous Markov-chain model was, for the first time, developed in this work to predict the spread of COVID-19 infection. A probability matrix of infection was first developed in this model based upon the contact frequency of individuals within the population, the individual's characteristics, and other factors that can effectively reflect the epidemic's temporal and spatial variation characteristics. The Markov-chain model was then extended to incorporate both the mutation effect of COVID-19 and the decaying effect of antibodies. The developed comprehensive Markov-chain model that integrates the aforementioned factors was finally tested by real data to predict the trend of the COVID-19 epidemic. The result shows that our model can effectively avoid the prediction dilemma that may exist with traditional ordinary differential equations model, such as the susceptible-infectious-recovered (SIR) model. Meanwhile, it can forecast the epidemic distribution and predict the epidemic hotspots geographically at different times. It is also demonstrated in our result that the influence of the population's spatial and geographic distribution in a herd infection event is needed in the model for a better prediction of the epidemic trend. At the same time, our result indicates that no simple derivative relationship exists between the threshold of herd immunity and the virus basic reproduction number R0. The threshold of herd immunity achieved through natural immunity is significantly higher than 1 - 1/R0. These not only explain the theoretical misconceptions of herd immunity thresholds in herd immunity theory but also provide a guidance for predicting the optimal vaccination coverage. In addition, our model can predict the temporal and spatial distribution of infections in different epidemic waves. It is implied from our model that it is challenging to eradicate COVID-19 in the short term for a large population size and a wide spatial distribution. It is predicted that COVID-19 is likely to coexist with humans for a long time and that it will exhibit multipoint epidemic effects at a later stage. The statistical evidence is consistent with our prediction and strongly supports our modeling results.

The complete mitochondrial genome of Cochylidia moguntiana (Rössler, 1864) (Lepidoptera: Tortricidae).

The complete mitogenome of Cochylidia moguntiana (Rössler, 1864) was sequenced and analyzed. The genome is 15,433 bp long with a high A + T content (80.6%), and consists of 13 protein-coding genes, 22 tRNA genes, 2 rRNA genes, and a noncoding control region. A phylogenetic analysis of 18 tortricid species for which mitogenes are available showed strong support for the monophyly of Tortricinae.

Multi-Satellite Relative Navigation Scheme for Microsatellites Using Inter-Satellite Radio Frequency Measurements.

The inter-satellite relative navigation method-based on radio frequency (RF) range and angle measurements-offers good autonomy and high precision, and has been successfully applied to two-satellite formation missions. However, two main challenges occur when this method is applied to multi-microsatellite formations: (i) the implementation difficulty of the inter-satellite RF angle measurement increases significantly as the number of satellites increases; and (ii) there is no high-precision, scalable RF measurement scheme or corresponding multi-satellite relative navigation algorithm that supports multi-satellite formations. Thus, a novel multi-satellite relative navigation scheme based on inter-satellite RF range and angle measurements is proposed. The measurement layer requires only a small number of chief satellites, and a novel distributed multi-satellite range measurement scheme is adopted to meet the scalability requirement. An inter-satellite relative navigation algorithm for multi-satellite formations is also proposed. This algorithm achieves high-precision relative navigation by fusing the algorithm and measurement layers. Simulation results show that the proposed scheme requires only three chief satellites to perform inter-satellite angle measurements. Moreover, with the typical inter-satellite measurement accuracy and an inter-satellite distance of around 1 km, the proposed scheme achieves a multi-satellite relative navigation accuracy of ~30 cm, which is about the same as the relative navigation accuracy of two-satellite formations. Furthermore, decreasing the number of chief satellites only slightly degrades accuracy, thereby significantly reducing the implementation difficulty of multi-satellite RF angle measurements.

Spatiotemporal delivery of basic fibroblast growth factor to directly and simultaneously attenuate cardiac fibrosis and promote cardiac tissue vascularization following myocardial infarction.

Following myocardial infarction (MI), the destruction of vasculature in the infarcted heart muscle and progression of cardiac fibrosis lead to cardiac function deterioration. Vascularization of the damaged tissue and prevention of cardiac fibrosis represent promising strategies to improve cardiac function. Herein we have developed a bFGF release system with suitable release kinetics to simultaneously achieve the two goals. The release system was based on an injectable, thermosensitive, and fast gelation hydrogel and bFGF. The hydrogel had gelation time <7 s. It can quickly solidify upon injection into tissue so as to increase drug retention in the tissue. Hydrogel complex modulus can be tuned by hydrogel solution concentration. The complex modulus of 176.6 Pa and lower allowed cardiac fibroblast to maintain its phenotype. Bioactive bFGF was able to gradually release from the hydrogel for 4 weeks. The released bFGF promoted cardiac fibroblast survival under ischemic conditions mimicking those of the infarcted hearts. It also attenuated cardiac fibroblasts from differentiating into myofibroblasts in the presence of TGFß when tested in 3D collagen model mimicking the scenario when the bFGF release system was injected into hearts. Furthermore, the released bFGF stimulated human umbilical endothelial cells to form endothelial lumen. After 4 weeks of implantation into infarcted hearts, the bFGF release system significantly increased blood vessel density, decreased myofibroblast density and collagen content, augmented cardiac cell survival/proliferation, and reduced macrophage density. In addition, the bFGF release system significantly increased cardiac function. These results demonstrate that delivery of bFGF with appropriate release kinetics alone may represent an efficient approach to control cardiac remodeling after MI.

Computational design of enhanced detoxification activity of a zearalenone lactonase from Clonostachys rosea in acidic medium.

Computational design of pH-activity profiles for enzymes is of great importance in industrial applications. In this research, a computational strategy was developed to engineer the pH-activity profile of a zearalenone lactonase (ZHD101) from Clonostachys rosea to promote its activity in acidic medium. The active site pK a values of ZHD101 were computationally designed by introducing positively charged lysine mutations on the enzyme surface, and the experimental results showed that two variants, M2(D157K) and M9(E171K), increased the catalytic efficiencies of ZHD101 modestly under acidic conditions. Moreover, two variants, M8(D133K) and M9(E171K), were shown to increase the turnover numbers by 2.73 and 2.06-fold with respect to wild type, respectively, though their apparent Michaelis constants were concomitantly increased. These results imply that the active site pK a value change might affect the pH-activity profile of the enzyme. Our computational strategy for pH-activity profile engineering considers protein stability; therefore, limited experimental validation is needed to discover beneficial mutations under shifted pH conditions.

A Murine Model of Myocardial Ischemia-Reperfusion Injury.

Ligation of the left anterior descending (LAD) coronary artery in the mouse heart is a widely used model to simulate myocardial infarction and ischemia-reperfusion injury. Here we describe a ligation technique routinely performed in our laboratory to induce myocardial infarction that may be used to study ischemia-reperfusion injury in the myocardium. The methods described enhance location of the LAD coronary artery to allow for accurate ligation, thus increasing reproducibility of infarct size and location.

An Injectable Oxygen Release System to Augment Cell Survival and Promote Cardiac Repair Following Myocardial Infarction.

Oxygen deficiency after myocardial infarction (MI) leads to massive cardiac cell death. Protection of cardiac cells and promotion of cardiac repair are key therapeutic goals. These goals may be achieved by re-introducing oxygen into the infarcted area. Yet current systemic oxygen delivery approaches cannot efficiently diffuse oxygen into the infarcted area that has extremely low blood flow. In this work, we developed a new oxygen delivery system that can be delivered specifically to the infarcted tissue, and continuously release oxygen to protect the cardiac cells. The system was based on a thermosensitive, injectable and fast gelation hydrogel, and oxygen releasing microspheres. The fast gelation hydrogel was used to increase microsphere retention in the heart tissue. The system was able to continuously release oxygen for 4 weeks. The released oxygen significantly increased survival of cardiac cells under the hypoxic condition (1% O2) mimicking that of the infarcted hearts. It also reduced myofibroblast formation under hypoxic condition (1% O2). After implanting into infarcted hearts for 4 weeks, the released oxygen significantly augmented cell survival, decreased macrophage density, reduced collagen deposition and myofibroblast density, and stimulated tissue angiogenesis, leading to a significant increase in cardiac function.

Non-contrast estimation of diffuse myocardial fibrosis with dual energy CT: A phantom study.

BACKGROUND: Estimation of diffuse myocardial fibrosis, substrate for adverse events such as heart failure and arrhythmias in patients with various cardiac disorders, is presently done by histopathology or cardiac magnetic resonance. We sought to develop a non-contrast method to estimate the amount of diffuse myocardial fibrosis leveraging dual energy computed tomography (DECT) in phantoms and a suitable small animal model. METHODS AND RESULTS: Phantoms consisted of homogenized bovine myocardium with varying amounts of Type 1 collagen. Fifteen mice underwent sham surgery, no procedure, or transverse aortic constriction (TAC) for 5 or 8 weeks to produce moderate or severe fibrosis, respectively. Phantoms and ex vivo mouse hearts were imaged on a single source, DECT scanner equipped with kVp switching. Monochromatic images were reconstructed at 40-140 keV. Linear discriminant analysis (LDA) was performed on mean myocardial CT numbers derived from single energy (70 keV) images as well as images reconstructed across multiple energies. Classification of myocardial fibrosis severity as low, moderate or severe was more often correct using the multi-energy CT/LDA approach vs. single energy CT/LDA in both phantoms (80.0% vs. 70.0%) and mice (93.3% vs. 33.3%). CONCLUSIONS: DECT myocardial imaging with multi-energy analysis better classifies myocardial fibrosis severity compared to a single energy-based approach. Non-contrast DECT can accurately and non-invasively estimate the extent of diffuse myocardial fibrosis in phantom and animal models. These data support further evaluation of this approach for in vivo myocardial fibrosis estimation.

Sustained Release of a Peptide-Based Matrix Metalloproteinase-2 Inhibitor to Attenuate Adverse Cardiac Remodeling and Improve Cardiac Function Following Myocardial Infarction.

Following myocardial infarction (MI), degradation of extracellular matrix (ECM) by upregulated matrix metalloproteinases (MMPs) especially MMP-2 decreases tissue mechanical properties, leading to cardiac function deterioration. Attenuation of cardiac ECM degradation at the early stage of MI has the potential to preserve tissue mechanical properties, resulting in cardiac function increase. Yet the strategy for efficiently preventing cardiac ECM degradation remains to be established. Current preclinical approaches have shown limited efficacy because of low drug dosage allocated to the heart tissue, dose-limiting side effects, and cardiac fibrosis. To address these limitations, we have developed a MMP-2 inhibitor delivery system that can be specifically delivered into infarcted hearts at early stage of MI to efficiently prevent MMP-2-mediated ECM degradation. The system was based on an injectable, degradable, fast gelation, and thermosensitive hydrogel, and a MMP-2 specific inhibitor, peptide CTTHWGFTLC (CTT). The use of fast gelation hydrogel allowed to completely retain CTT in the heart tissue. The system was able to release low molecular weight CTT over 4 weeks possibly due to the strong hydrogen bonding between the hydrogel and CTT. The release kinetics was modulated by amount of CTT loaded into the hydrogel, and using chondroitin sulfate and heparin that can interact with CTT and the hydrogel. Both glycosaminoglycans augmented CTT release, while heparin more greatly accelerated the release. After it was injected into the infarcted hearts for 4 weeks, the released CTT efficiently prevented cardiac ECM degradation as it not only increased tissue thickness but also preserved collagen composition similar to that in the normal heart tissue. In addition, the delivery system significantly improved cardiac function. Importantly, the delivery system did not induce cardiac fibrosis. These results demonstrate that the developed MMP-2 inhibitor delivery system has potential to efficiently reduce adverse myocardial remodeling and improve cardiac function.