Pulmonary Hypertension Detection Non-Invasively at Point-of-Care Using a Machine-Learned Algorithm.

Artificial intelligence, particularly machine learning, has gained prominence in medical research due to its potential to develop non-invasive diagnostics. Pulmonary hypertension presents a diagnostic challenge due to its heterogeneous nature and similarity in symptoms to other cardiovascular conditions. Here, we describe the development of a supervised machine learning model using non-invasive signals (orthogonal voltage gradient and photoplethysmographic) and a hand-crafted library of 3298 features. The developed model achieved a sensitivity of 87% and a specificity of 83%, with an overall Area Under the Receiver Operator Characteristic Curve (AUC-ROC) of 0.93. Subgroup analysis showed consistent performance across genders, age groups and classes of PH. Feature importance analysis revealed changes in metrics that measure conduction, repolarization and respiration as significant contributors to the model. The model demonstrates promising performance in identifying pulmonary hypertension, offering potential for early detection and intervention when embedded in a point-of-care diagnostic system.

Clinical Validation of a Machine-Learned, Point-of-Care System to IDENTIFY Functionally Significant Coronary Artery Disease.

Many clinical studies have shown wide performance variation in tests to identify coronary artery disease (CAD). Coronary computed tomography angiography (CCTA) has been identified as an effective rule-out test but is not widely available in the USA, particularly so in rural areas. Patients in rural areas are underserved in the healthcare system as compared to urban areas, rendering it a priority population to target with highly accessible diagnostics. We previously developed a machine-learned algorithm to identify the presence of CAD (defined by functional significance) in patients with symptoms without the use of radiation or stress. The algorithm requires 215 s temporally synchronized photoplethysmographic and orthogonal voltage gradient signals acquired at rest. The purpose of the present work is to validate the performance of the algorithm in a frozen state (i.e., no retraining) in a large, blinded dataset from the IDENTIFY trial. IDENTIFY is a multicenter, selectively blinded, non-randomized, prospective, repository study to acquire signals with paired metadata from subjects with symptoms indicative of CAD within seven days prior to either left heart catheterization or CCTA. The algorithm's sensitivity and specificity were validated using a set of unseen patient signals (n = 1816). Pre-specified endpoints were chosen to demonstrate a rule-out performance comparable to CCTA. The ROC-AUC in the validation set was 0.80 (95% CI: 0.78-0.82). This performance was maintained in both male and female subgroups. At the pre-specified cut point, the sensitivity was 0.85 (95% CI: 0.82-0.88), and the specificity was 0.58 (95% CI: 0.54-0.62), passing the pre-specified endpoints. Assuming a 4% disease prevalence, the NPV was 0.99. Algorithm performance is comparable to tertiary center testing using CCTA. Selection of a suitable cut-point results in the same sensitivity and specificity performance in females as in males. Therefore, a medical device embedding this algorithm may address an unmet need for a non-invasive, front-line point-of-care test for CAD (without any radiation or stress), thus offering significant benefits to the patient, physician, and healthcare system.

Development of a Non-Invasive Machine-Learned Point-of-Care Rule-Out Test for Coronary Artery Disease.

The current standard of care for coronary artery disease (CAD) requires an intake of radioactive or contrast enhancement dyes, radiation exposure, and stress and may take days to weeks for referral to gold-standard cardiac catheterization. The CAD diagnostic pathway would greatly benefit from a test to assess for CAD that enables the physician to rule it out at the point of care, thereby enabling the exploration of other diagnoses more rapidly. We sought to develop a test using machine learning to assess for CAD with a rule-out profile, using an easy-to-acquire signal (without stress/radiation) at the point of care. Given the historic disparate outcomes between sexes and urban/rural geographies in cardiology, we targeted equal performance across sexes in a geographically accessible test. Noninvasive photoplethysmogram and orthogonal voltage gradient signals were simultaneously acquired in a representative clinical population of subjects before invasive catheterization for those with CAD (gold-standard for the confirmation of CAD) and coronary computed tomographic angiography for those without CAD (excellent negative predictive value). Features were measured from the signal and used in machine learning to predict CAD status. The machine-learned algorithm achieved a sensitivity of 90% and specificity of 59%. The rule-out profile was maintained across both sexes, as well as all other relevant subgroups. A test to assess for CAD using machine learning on a noninvasive signal has been successfully developed, showing high performance and rule-out ability. Confirmation of the performance on a large clinical, blinded, enrollment-gated dataset is required before implementation of the test in clinical practice.

Bacteriophage P22 SieA-mediated superinfection exclusion.

Many temperate phages encode prophage-expressed functions that interfere with superinfection of the host bacterium by external phages. Salmonella phage P22 has four such systems that are expressed from the prophage in a lysogen that are encoded by the c2 (repressor), gtrABC, sieA, and sieB genes. Here we report that the P22-encoded SieA protein is necessary and sufficient for exclusion by the SieA system and that it is an inner membrane protein that blocks DNA injection by P22 and its relatives, but has no effect on infection by other tailed phage types. The P22 virion injects its DNA through the host cell membranes and periplasm via a conduit assembled from three "ejection proteins" after their release from the virion. Phage P22 mutants that overcome the SieA block were isolated, and they have amino acid changes in the C-terminal regions of the gene 16 and 20 encoded ejection proteins. Three different single-amino acid changes in these proteins are required to obtain nearly full resistance to SieA. Hybrid P22 phages that have phage HK620 ejection protein genes are also partially resistant to SieA. There are three sequence types of extant phage-encoded SieA proteins that are less than 30% identical to one another, yet comparison of two of these types found no differences in phage target specificity. Our data strongly suggest a model in which the inner membrane protein SieA interferes with the assembly or function of the periplasmic gp20 and membrane-bound gp16 DNA delivery conduit.IMPORTANCEThe ongoing evolutionary battle between bacteria and the viruses that infect them is a critical feature of bacterial ecology on Earth. Viruses can kill bacteria by infecting them. However, when their chromosomes are integrated into a bacterial genome as a prophage, viruses can also protect the host bacterium by expressing genes whose products defend against infection by other viruses. This defense property is called "superinfection exclusion." A significant fraction of bacteria harbor prophages that encode such protective systems, and there are many different molecular strategies by which superinfection exclusion is mediated. This report is the first to describe the mechanism by which bacteriophage P22 SieA superinfection exclusion protein protects its host bacterium from infection by other P22-like phages. The P22 prophage-encoded inner membrane SieA protein prevents infection by blocking transport of superinfecting phage DNA across the inner membrane during injection.

Bacteriophage P22 SieA mediated superinfection exclusion.

Many temperate phages encode prophage-expressed functions that interfere with superinfection of the host bacterium by external phages. Salmonella phage P22 has four such systems that are expressed from the prophage in a lysogen that are encoded by the c2 (repressor), gtrABC, sieA, and sieB genes. Here we report that the P22-encoded SieA protein is the only phage protein required for exclusion by the SieA system, and that it is an inner membrane protein that blocks DNA injection by P22 and its relatives, but has no effect on infection by other tailed phage types. The P22 virion injects its DNA through the host cell membranes and periplasm via a conduit assembled from three "ejection proteins" after their release from the virion. Phage P22 mutants were isolated that overcome the SieA block, and they have amino acid changes in the C-terminal regions of the gene 16 and 20 encoded ejection proteins. Three different single amino acid changes in these proteins are required to obtain nearly full resistance to SieA. Hybrid P22 phages that have phage HK620 ejection protein genes are also partially resistant to SieA. There are three sequence types of extant phage-encoded SieA proteins that are less than 30% identical to one another, yet comparison of two of these types found no differences in target specificity. Our data are consistent with a model in which the inner membrane protein SieA interferes with the assembly or function of the periplasmic gp20 and membrane-bound gp16 DNA delivery conduit.

Soil Protists Can Actively Redistribute Beneficial Bacteria along Medicago truncatula Roots.

The rhizosphere is the region of soil directly influenced by plant roots. The microbial community in the rhizosphere includes fungi, protists, and bacteria: all play significant roles in plant health. The beneficial bacterium Sinorhizobium meliloti infects growing root hairs on nitrogen-starved leguminous plants. Infection leads to the formation of a root nodule, where S. meliloti converts atmospheric nitrogen to ammonia, a bioavailable form. In soil, S. meliloti is often found in biofilms and travels slowly along the roots, leaving developing root hairs at the growing root tips uninfected. Soil protists are an important component of the rhizosphere system, able to travel quickly along roots and water films, who prey on soil bacteria and have been known to egest undigested phagosomes. We show that a soil protist, Colpoda sp., can transport S. meliloti down Medicago truncatula roots. Using model soil microcosms, we directly observed fluorescently labeled S. meliloti along M. truncatula roots and tracked the displacement of the fluorescence signal over time. Two weeks after co-inoculation, this signal extended 52 mm farther down plant roots when Colpoda sp. was also present versus treatments that contained bacteria but not protists. Direct counts also showed protists are required for viable bacteria to reach the deeper sections of our microcosms. Facilitating bacterial transport may be an important mechanism whereby soil protists promote plant health. IMPORTANCE Soil protists are an important part of the microbial community in the rhizosphere. Plants grown with protists fare better than plants grown without protists. Mechanisms through which protists support plant health include nutrient cycling, alteration of the bacterial community through selective feeding, and consumption of plant pathogens. Here, we provide data in support of an additional mechanism: protists act as transport vehicles for bacteria in soil. We show that protist-facilitated transport can deliver plant-beneficial bacteria to the growing tips of roots that may otherwise be sparsely inhabited with bacteria originating from a seed-associated inoculum. By co-inoculating Medicago truncatula roots with both S. meliloti, a nitrogen-fixing legume symbiont, and Colpoda sp., a ciliated protist, we show substantial and statistically significant transport with depth and breadth of bacteria-associated fluorescence as well as transport of viable bacteria. Co-inoculation with shelf-stable encysted soil protists may be employed as a sustainable agriculture biotechnology to better distribute beneficial bacteria and enhance the performance of inoculants.

Electrocardiogram Detection of Pulmonary Hypertension Using Deep Learning.

BACKGROUND: Pulmonary hypertension (PH) is life-threatening, and often diagnosed late in its course. We aimed to evaluate if a deep learning approach using electrocardiogram (ECG) data alone can detect PH and clinically important subtypes. We asked: does an automated deep learning approach to ECG interpretation detect PH and its clinically important subtypes? METHODS AND RESULTS: Adults with right heart catheterization or an echocardiogram within 90 days of an ECG at the University of California, San Francisco (2012-2019) were retrospectively identified as PH or non-PH. A deep convolutional neural network was trained on patients' 12-lead ECG voltage data. Patients were divided into training, development, and test sets in a ratio of 7:1:2. Overall, 5016 PH and 19,454 patients without PH were used in the study. The mean age at the time of ECG was 62.29 ± 17.58 years and 49.88% were female. The mean interval between ECG and right heart catheterization or echocardiogram was 3.66 and 2.23 days for patients with PH and patients without PH, respectively. In the test dataset, the model achieved an area under the receiver operating characteristic curve, sensitivity, and specificity, respectively of 0.89, 0.79, and 0.84 to detect PH; 0.91, 0.83, and 0.84 to detect precapillary PH; 0.88, 0.81, and 0.81 to detect pulmonary arterial hypertension, and 0.80, 0.73, and 0.76 to detect group 3 PH. We additionally applied the trained model on ECGs from participants in the test dataset that were obtained from up to 2 years before diagnosis of PH; the area under the receiver operating characteristic curve was 0.79 or greater. CONCLUSIONS: A deep learning ECG algorithm can detect PH and PH subtypes around the time of diagnosis and can detect PH using ECGs that were done up to 2 years before right heart catheterization/echocardiogram diagnosis. This approach has the potential to decrease diagnostic delays in PH.

A machine learning approach to identifying patients with pulmonary hypertension using real-world electronic health records.

BACKGROUND: This study aimed to develop a machine learning (ML) model to identify patients who are likely to have pulmonary hypertension (PH), using a large patient-level US-based electronic health record (EHR) database. METHODS: A gradient boosting model, XGBoost, was developed using data from Optum's US-based de-identified EHR dataset (2007-2019). PH and disease control adult patients were identified using diagnostic, treatment and procedure codes and were randomly split into the training (90%) or test set (10%). Model features included patient demographics, physician visits, diagnoses, procedures, prescriptions, and laboratory test results. SHapley Additive exPlanations values were used to determine feature importance. RESULTS: We identified 11,279,478 control and 115,822 PH patients (mean age, respectively: 62 and 68 years, both 53% female). The final model used 165 features, with the most important predictive features including diagnosis of heart failure, shortness of breath and atrial fibrillation. The model predicted PH with an area under the receiver operating characteristic curve (AUROC) of 0.92. AUROC remained above 0.80 for the prediction of PH up to and beyond 18 months before diagnosis. Among the PH patients, we also identified 955 pulmonary arterial hypertension (PAH) and 1432 chronic thromboembolic pulmonary hypertension (CTEPH) patients, and the range of AUROCs obtained for these cohorts was 0.79-0.90 and 0.87-0.96, respectively. CONCLUSIONS: This model to detect PH based on patients' EHR records is viable and performs well in subgroups of PAH and CTEPH patients. This approach has the potential to improve patient outcomes by reducing diagnostic delay in PH.

In-ear infrasonic hemodynography with a digital health device for cardiovascular monitoring using the human audiome.

Human bodily mechanisms and functions produce low-frequency vibrations. Our ability to perceive these vibrations is limited by our range of hearing. However, in-ear infrasonic hemodynography (IH) can measure low-frequency vibrations (<20 Hz) created by vital organs as an acoustic waveform. This is captured using a technology that can be embedded into wearable devices such as in-ear headphones. IH can acquire sound signals that travel within arteries, fluids, bones, and muscles in proximity to the ear canal, allowing for measurements of an individual's unique audiome. We describe the heart rate and heart rhythm results obtained in time-series analysis of the in-ear IH data taken simultaneously with ECG recordings in two dedicated clinical studies. We demonstrate a high correlation (r = 0.99) between IH and ECG acquired interbeat interval and heart rate measurements and show that IH can continuously monitor physiological changes in heart rate induced by various breathing exercises. We also show that IH can differentiate between atrial fibrillation and sinus rhythm with performance similar to ECG. The results represent a demonstration of IH capabilities to deliver accurate heart rate and heart rhythm measurements comparable to ECG, in a wearable form factor. The development of IH shows promise for monitoring acoustic imprints of the human body that will enable new real-time applications in cardiovascular health that are continuous and noninvasive.

Draft Genome Sequences of Dysgonomonas sp. Strains GY75 and GY617, Isolated from the Hindgut of Reticulitermes flavipes.

Dysgonomonas species are facultative heterotrophs capable of growth on lignocellulose-derived polysaccharides. Dysgonomonas species harbor myriad genes involved in glycan modification and are well suited to the lignocellulose-rich conditions within the termite hindgut. Here, we report draft genome sequences for Dysgonomonas sp. strains GY75 and GY617, isolated from the hindgut of Reticulitermes flavipes.

Optogenetics in Sinorhizobium meliloti Enables Spatial Control of Exopolysaccharide Production and Biofilm Structure.

Microorganisms play a vital role in shaping the soil environment and enhancing plant growth by interacting with plant root systems. Because of the vast diversity of cell types involved, combined with dynamic and spatial heterogeneity, identifying the causal contribution of a defined factor, such as a microbial exopolysaccharide (EPS), remains elusive. Synthetic approaches that enable orthogonal control of microbial pathways are a promising means to dissect such complexity. Here we report the implementation of a synthetic, light-activated, transcriptional control platform using the blue-light responsive DNA binding protein EL222 in the nitrogen fixing soil bacterium Sinorhizobium meliloti. By fine-tuning the system, we successfully achieved optical control of an EPS production pathway without significant basal expression under noninducing (dark) conditions. Optical control of EPS recapitulated important behaviors such as a mucoid plate phenotype and formation of structured biofilms, enabling spatial control of biofilm structures in S. meliloti. The successful implementation of optically controlled gene expression in S. meliloti enables systematic investigation of how genotype and microenvironmental factors together shape phenotype in situ.

Draft Genome Sequences of Dysgonomonas sp. Strains BGC7 and HGC4, Isolated from the Hindgut of a Lower Termite.

Dysgonomonas spp. are facultative heterotrophs which colonize diverse environments, including the hindgut of the lower termite Reticulitermes flavipes Dysgonomonas genomes are enriched for genes involving oligo- and polysaccharide utilization, enabling modification of a wide array of complex glycans. Here, we report draft genome sequences for Dysgonomonas sp. strains BGC7 and HGC4.

Development and application of aerobic, chemically defined media for Dysgonomonas.

Members of Dysgonomonas are Gram-stain-negative, non-motile, facultatively anaerobic coccobacilli originally described in relation to their isolation from stool and wounds of human patients (CDC group DF-3). More recently, Dysgonomonas have been found to be widely distributed in terrestrial environments and are particularly enriched in insect systems. Their prevalence in xylophagous insects such as termites and wood-feeding cockroaches, as well as in soil-fed microbial fuel cells, elicit interest in lignocellulose degradation and biofuel production, respectively. Their occurrence in mosquito and fruit fly have implications relating to symbiosis, host immunology and developmental biology. Additionally, their presence in termite, mosquito and nematode present novel opportunities for pest and vector control. Currently, the absolute growth requirements of Dysgonomonas are unknown, and they are commonly cultured under anaerobic conditions on complex media containing blood, peptones, tryptones, and yeast, plant or meat extracts. Restrictive and undefined culturing conditions preclude physiological and genetic studies, and thus further understanding of their metabolic potential. Here we describe the requirements for growth of termite-derived Dysgonomonas isolates and create parallel complex, defined and minimal media that permit vigorous and reliable aerobic growth. Furthermore, we show that these media can be used to easily enrich for Dysgonomonas isolates from densely-colonized and microbially-diverse environmental samples.

Effects of genetic transfection on calcium cycling pathways mediated by double-stranded adeno-associated virus in postinfarction remodeling.

OBJECTIVE: Restoring calcium sensor protein (S100A1) activity in failing hearts poses a promising therapeutic strategy. We hypothesize that cardiac overexpression of the S100A1 gene mediated by a double-stranded adeno-associated virus (scAAV) results in better functional and molecular improvements compared with the single-stranded virus (ssAAV). METHODS: Heart failure was induced by coronary artery ligation. Then, intramyocardial injections of saline, AAV9 empty capsid, scAAV9.S100A1, and ssAAV9.S100A1 were performed. Ten weeks postinfarction, all rats received cardiac evaluation; serum and tissue were collected for genetic analysis, cytokine profiling, and assessments of mitochondrial function and structure. RESULTS: Overexpression of AAV9.S100A1 improved systolic and diastolic function. Compared with control, ejection fraction was greater in treated groups (54.8% vs 32.3%, P < .05). Similarly, end-diastolic volume index was significantly less in the treated group than in control (1.14 vs 1.59 mL/cm2), whereas fractional shortening was greater in treated groups than control (26% vs 38%, P < .05). Interestingly, cardiac mechanics were significantly better when treated with double-stranded virus compared with single-stranded. Quantitative polymerase chain reaction demonstrated robust transfection of myocardium with the S100A1 gene, with more infection in the self-complimentary group compared with the single-stranded group (5.68 ± 0.44 vs 4.09 ± 0.25 log10 genome copies per 100 ng of DNA; P < .0001). Concentrations of the inflammatory cytokines were elevated in the ssAAV9/S100A1 group compared with the scAAV9/S100A1. Assessment of mitochondrial respiration and morphology demonstrated that injection of self-complementary vector saved both mitochondrial structure and function. CONCLUSIONS: Gene therapy of S100A1 can prevent pathologic postmyocardial infarction remodeling and decrease inflammatory response in ischemic heart failure.

Surgical and physiological challenges in the development of left and right heart failure in rat models.

Rodent surgical animal models of heart failure (HF) are critically important for understanding the proof of principle of the cellular alterations underlying the development of the disease as well as evaluating therapeutics. Robust, reproducible rodent models are a prerequisite to the development of pharmacological and molecular strategies for the treatment of HF in patients. Due to the absence of standardized guidelines regarding surgical technique and clear criteria for HF progression in rats, objectivity is compromised. Scientific publications in rats rarely fully disclose the actual surgical details, and technical and physiological challenges. This lack of reporting is one of the main reasons that the outcomes specified in similar studies are highly variable and associated with unnecessary loss of animals, compromising scientific assessment. This review details rat circulatory and coronary arteries anatomy, the surgical details of rat models that recreate the HF phenotype of myocardial infarction, ischemia/reperfusion, left and right ventricular pressure, and volume overload states, and summarizes the technical and physiological challenges of creating HF. The purpose of this article is to help investigators understand the underlying issues of current HF models in order to reduce variable results and ensure successful, reproducible models of HF.

The Left Pneumonectomy Combined with Monocrotaline or Sugen as a Model of Pulmonary Hypertension in Rats.

In this protocol, we detail the correct procedural steps and necessary precautions to successfully perform a left pneumonectomy and induce PAH in rats with the additional administration of monocrotaline (MCT) or SU5416 (Sugen). We also compare these two models to other PAH models commonly used in research. In the last few years, the focus of animal PAH models has moved towards studying the mechanism of angioproliferation of plexiform lesions, in which the role of increased pulmonary blood flow is considered as an important trigger in the development of severe pulmonary vascular remodeling. One of the most promising rodent models of increased pulmonary flow is the unilateral left pneumonectomy combined with a "second hit" of MCT or Sugen. The removal of the left lung leads to increased and turbulent pulmonary blood flow and vascular remodeling. Currently, there is no detailed procedure of the pneumonectomy surgery in rats. This article details a step-by-step protocol of the pneumonectomy surgical procedure and post-operative care in male Sprague-Dawley rats. Briefly, the animal is anesthetized and the chest is opened. Once the left pulmonary artery, pulmonary vein, and bronchus are visualized, they are ligated and the left lung is removed. The chest then closed and the animal recovered. Blood is forced to circulate only on the right lung. This increased vascular pressure leads to a progressive remodeling and occlusion of small pulmonary arteries. The second hit of MCT or Sugen is used one week post-surgery to induce endothelial dysfunction. The combination of increased blood flow in the lung and endothelial dysfunction produces severe PAH. The primary limitation of this procedure is that it requires general surgical skills.

Targeted Gene Delivery through the Respiratory System: Rationale for Intratracheal Gene Transfer.

Advances in DNA- and RNA-based technologies have made gene therapy suitable for many lung diseases, especially those that are hereditary. The main objective of gene therapy is to deliver an adequate amount of gene construct to the intended target cell, achieve stable transduction in target cells, and to produce a clinically therapeutic effect. This review focuses on the cellular organization in the normal lung and how gene therapy targets the specific cell types that are affected by pulmonary disorders caused by genetic mutations. Furthermore, it examines the pulmonary barriers that can compromise the absorption and transduction of viral vectors and genetic agents by the lung. Finally, it discusses the advantages and limitations of direct intra-tracheal gene delivery with different viral vectors in small and large animal models and in clinical trials.

Technique of Complete Heart Isolation with Continuous Cardiac Perfusion During Cardiopulmonary Bypass: New Opportunities for Gene Therapy.

Cardiopulmonary bypass (CPB) featuring complete heart isolation and continuous cardiac perfusion is a very promising approach for solving the problem of efficient gene delivery. In the technique presented here, separate pumps are used for the systemic and cardiac circuits. This system permits continuous isolated arrested heart perfusion through optimizing a number of delivery parameters including temperature, flow rate, driving pressure, ionic composition, and exposure time to the cardiac vessels. During complete cardiac isolation, the blood vector concentration trended from 11.51 ± 1.73 log genome copies (GCs)/cm3 to 9.84 ± 1.65 log GC/cm3 (p > .05). Despite restructuring a very high concentration to the heart, GCs were detectable in the systemic circuit. These values over time were near negligible by comparison but detectable 1.66 ± .26 during 20 minutes of recirculation and did not change (p > .05). After the completion of the recirculation interval and subsequent washing procedure, the initial systemic blood vector GC concentration slightly increased to 2.08 ± .38 log GCs/cm3 (p > .05). During the recirculation period, we supported flow via the cardiac circuit around 300 mL/min. In this technique of heart isolation with continuous cardiac perfusion, >99% of the vector remains in coronary circulation during recirculation period. The animal's non recirculation blood, or that in the system, was routinely tested during and after recirculation to contain much less than 1% of the original dose obtained via logging concentration of therapeutic over time. All of the sheep in this group recovered from anesthesia and received critical postoperative care, including all organ function, in the first 24-36 hours. Twenty-one sheep (84%) survived to euthanasia at 12 weeks. Average CPB time was 107 ± 19.0 minutes and cross-clamp time was 49 ± 7.9 minutes. This technology readily provides multiple pass recirculation of genes through the heart with minimal side effects of collateral expression of other organs.

Scar Size and Other Parameters for Tracking Left Ventricular Dysfunction after Induction of Myocardial Infarcts in Sheep (Ovisaries).

In humans, cardiovascular disease (CVD) is the most frequent cause of death worldwide. Myocardial infarction (MI) is a leading cause of heart failure due to myocardial impairment, yet the progression of the resultant dysfunction is often undetected after incidental or induced myocardial infarction. In this study we tracked the progression of left-sided heart failure in 6-mo-old male castrated sheep in which we created 2 models of myocardial infarction, small and large. Myocardial infarction was induced through ligation of a single branch (obtuse marginal [OM] 1) of the left circumflex coronary artery to create small (mild) infarcts and of 2 branches (OM1 and OM2) for large (severe) infarcts. Progression of heart failure was evaluated by assessing scar size, the left ventricular ejection fraction, hematology, cardiac serum biochemical biomarkers, ST elevation, and clinical observation. All parameters were assessed at baseline and at 3 wk and 3 mo after infarction, except that clinical observation of the animals was conducted daily. The different parameters differed in their usefulness: some verified appropriate creation of the model, whereas others enabled assessment of the progression of heart disease. We hypothesize that myocardial scar size, as a function of induced ischemia, coupled with left ventricular ejection fraction are predictive indicators of postinfarction cardiac dysfunction.