A generalized deep learning model for heart failure diagnosis using dynamic and static ultrasound.

Objective:Echocardiography (ECG) is the most common method used to diagnose heart failure (HF). However, its accuracy relies on the experience of the operator. Additionally, the video format of the data makes it challenging for patients to bring them to referrals and reexaminations. Therefore, this study used a deep learning approach to assist physicians in assessing cardiac function to promote the standardization of echocardiographic findings and compatibility of dynamic and static ultrasound data.Methods:A deep spatio-temporal convolutional model r2plus1d-Pan (trained on dynamic data and applied to static data) was improved and trained using the idea of "regression training combined with classification application," which can be generalized to dynamic ECG and static cardiac ultrasound views to identify HF with a reduced ejection fraction (EF < 40%). Additionally, three independent datasets containing 8976 cardiac ultrasound views and 10085 cardiac ultrasound videos were established. Subsequently, a multinational, multi-center dataset of EF was labeled. Furthermore, model training and independent validation were performed. Finally, 15 registered ultrasonographers and cardiologists with different working years in three regional hospitals specialized in cardiovascular disease were recruited to compare the results.Results:The proposed deep spatio-temporal convolutional model achieved an area under the receiveroperating characteristic curve (AUC) value of 0.95 (95% confidence interval [CI]: 0.947 to 0.953) on the training set of dynamic ultrasound data and an AUC of 1 (95% CI, 1 to 1) on the independent validation set. Subsequently, the model was applied to the static cardiac ultrasound view (validation set) with simultaneous input of 1, 2, 4, and 8 images of the same heart, with classification accuracies of 85%, 81%, 93%, and 92%, respectively. On the static data, the classification accuracy of the artificial intelligence (AI) model was comparable with the best performance of ultrasonographers and cardiologists with more than 3 working years (P = 0.344), but significantly better than the median level (P = 0.0000008).Conclusion:A new deep spatio-temporal convolution model was constructed to identify patients with HF with reduced EF accurately (< 40%) using dynamic and static cardiac ultrasound images. The model outperformed the diagnostic performance of most senior specialists. This may be the first HF-related AI diagnostic model compatible with multi-dimensional cardiac ultrasound data, and may thereby contribute to the improvement of HF diagnosis. Additionally, the model enables patients to carry "on-the-go" static ultrasound reports for referral and reexamination, thus saving healthcare resources.

Flexible electronics for cardiovascular healthcare monitoring.

Cardiovascular diseases (CVDs) are one of the most urgent threats to humans worldwide, which are responsible for almost one-third of global mortality. Over the last decade, research on flexible electronics for monitoring and treatment of CVDs has attracted tremendous attention. In contrast to conventional medical instruments in hospitals that are usually bulky, hard to move, monofunctional, and time-consuming, flexible electronics are capable of continuous, noninvasive, real-time, and portable monitoring. Notable progress has been made in this emerging field, and thus a number of significant achievements and concomitant research prospects deserve attention for practical implementation. Here, we comprehensively review the latest progress of flexible electronics for CVDs, focusing on new functions provided by flexible electronics. First, the characteristics of CVDs and flexible electronics and the foundation of their combination are briefly reviewed. Then, four representative applications of flexible electronics for CVDs are elaborated: blood pressure (BP) monitoring, electrocardiogram (ECG) monitoring, echocardiogram monitoring, and direct epicardium monitoring. Their operational principles, progress, merits and demerits, and future efforts are discussed. Finally, the remaining challenges and opportunities for flexible electronics for cardiovascular healthcare are outlined.

Analysis and prediction of research hotspots and trends in pediatric medicine from 2,580,642 studies published between 1940 and 2021.

Wearable ultrasound bioelectronics for healthcare monitoring.

Genetic overlap for ten cardiovascular diseases: A comprehensive gene-centric pleiotropic association analysis and Mendelian randomization study.

Recent studies suggest that pleiotropic effects may explain the genetic architecture of cardiovascular diseases (CVDs). We conducted a comprehensive gene-centric pleiotropic association analysis for ten CVDs using genome-wide association study (GWAS) summary statistics to identify pleiotropic genes and pathways that may underlie multiple CVDs. We found shared genetic mechanisms underlying the pathophysiology of CVDs, with over two-thirds of the diseases exhibiting common genes and single-nucleotide polymorphisms (SNPs). Significant positive genetic correlations were observed in more than half of paired CVDs. Additionally, we investigated the pleiotropic genes shared between different CVDs, as well as their functional pathways and distribution in different tissues. Moreover, six hub genes, including ALDH2, XPO1, HSPA1L, ESR2, WDR12, and RAB1A, as well as 26 targeted potential drugs, were identified. Our study provides further evidence for the pleiotropic effects of genetic variants on CVDs and highlights the importance of considering pleiotropy in genetic association studies.

Mapping the early life gut microbiome in neonates with critical congenital heart disease: multiomics insights and implications for host metabolic and immunological health.

BACKGROUND:The early life gut microbiome is crucial in maintaining host metabolic and immune homeostasis. Though neonates with critical congenital heart disease (CCHD) are at substantial risks of malnutrition and immune imbalance, the microbial links to CCHD pathophysiology remain poorly understood. In this study, we aimed to investigate the gut microbiome in neonates with CCHD in association with metabolomic traits. Moreover, we explored the clinical implications of the host-microbe interactions in CCHD.METHODS:Deep metagenomic sequencing and metabolomic profiling of paired fecal samples from 45 neonates with CCHD and 50 healthy controls were performed. The characteristics of gut microbiome were investigated in three dimensions (microbial abundance, functionality, and genetic variation). An in-depth analysis of gut virome was conducted to elucidate the ecological interaction between gut viral and bacterial communities. Correlations between multilevel microbial features and fecal metabolites were determined using integrated association analysis. Finally, we conducted a subgroup analysis to examine whether the interactions between gut microbiota and metabolites could mediate inflammatory responses and poor surgical prognosis.RESULTS:Gut microbiota dysbiosis was observed in neonates with CCHD, characterized by the depletion of Bifidobacterium and overgrowth of Enterococcus, which was highly correlated with metabolomic perturbations. Genetic variations of Bifidobacterium and Enterococcus orchestrate the metabolomic perturbations in CCHD. A temperate core virome represented by Siphoviridae was identified to be implicated in shaping the gut bacterial composition by modifying microbial adaptation. The overgrowth of Enterococcus was correlated with systemic inflammation and poor surgical prognosis in subgroup analysis. Mediation analysis indicated that the overgrowth of Enterococcus could mediate gut barrier impairment and inflammatory responses in CCHD.CONCLUSIONS:We demonstrate for the first time that an aberrant gut microbiome associated with metabolomic perturbations is implicated in immune imbalance and adverse clinical outcomes in neonates with CCHD. Our data support the importance of reconstituting optimal gut microbiome in maintaining host metabolic and immunological homeostasis in CCHD. Video Abstract.

Suppression of Myocardial Hypoxia-Inducible Factor-1α Compromises Metabolic Adaptation and Impairs Cardiac Function in Patients With Cyanotic Congenital Heart Disease During Puberty.

BACKGROUND:Cyanotic congenital heart disease (CCHD) is a complex pathophysiological condition involving systemic chronic hypoxia (CH). Some patients with CCHD are unoperated for various reasons and remain chronically hypoxic throughout their lives, which heightens the risk of heart failure as they age. Hypoxia activates cellular metabolic adaptation to balance energy demands by accumulating hypoxia-inducible factor 1-α (HIF-1α). This study aims to determine the effect of CH on cardiac metabolism and function in patients with CCHD and its association with age. The role of HIF-1α in this process was investigated, and potential therapeutic targets were explored.METHODS:Patients with CCHD (n=25) were evaluated for cardiac metabolism and function with positron emission tomography/computed tomography and magnetic resonance imaging. Heart tissue samples were subjected to metabolomic and protein analyses. CH rodent models were generated to enable continuous observation of changes in cardiac metabolism and function. The role of HIF-1α in cardiac metabolic adaptation to CH was investigated with genetically modified animals and isotope-labeled metabolomic pathway tracing studies.RESULTS:Prepubertal patients with CCHD had glucose-dominant cardiac metabolism and normal cardiac function. In comparison, among patients who had entered puberty, the levels of myocardial glucose uptake and glycolytic intermediates were significantly decreased, but fatty acids were significantly increased, along with decreased left ventricular ejection fraction. These clinical phenotypes were replicated in CH rodent models. In patients with CCHD and animals exposed to CH, myocardial HIF-1α was upregulated before puberty but was significantly downregulated during puberty. In cardiomyocyte-specific Hif-1α-knockout mice, CH failed to initiate the switch of myocardial substrates from fatty acids to glucose, thereby inhibiting ATP production and impairing cardiac function. Increased insulin resistance during puberty suppressed myocardial HIF-1α and was responsible for cardiac metabolic maladaptation in animals exposed to CH. Pioglitazone significantly reduced myocardial insulin resistance, restored glucose metabolism, and improved cardiac function in pubertal CH animals.CONCLUSIONS:In patients with CCHD, maladaptation of cardiac metabolism occurred during puberty, along with impaired cardiac function. HIF-1α was identified as the key regulator of cardiac metabolic adaptation in animals exposed to CH, and pubertal insulin resistance could suppress its expression. Pioglitazone administration during puberty might help improve cardiac function in patients with CCHD.

Impact of Family Socioeconomic Status on Health-Related Quality of Life in Children With Critical Congenital Heart Disease.

Background Socioeconomic status ( SES ) is associated with health-related quality of life ( HRQOL ) for children with critical congenital heart disease; however, literature from newly industrialized countries is scarce. Methods and Results This cross-sectional study included 2037 surviving patients operated on for critical congenital heart disease at a tertiary hospital in China between May 2012 and December 2015. All eligible patients were aged 2 to 12 years. HRQOL was measured by the Pediatric Quality of Life Inventory 4.0 generic and 3.0 cardiac modules. Family SES was assessed by a composite of household income in the past year and occupation and education level of each parent in the family. Mean scores of major domains in HRQOL were significantly lower in the low- SES group than in the medium- and high- SES groups (total generic scores: 71.2±7.9 versus 75.0±8.0 and 76.0±7.9, respectively [ P<0.001]; psychosocial functioning: 70.8±9.0 versus 74.4±8.4 and 75.3±8.4 [ P<0.001]; physical functioning: 71.6±10.4 versus 76.0±9.7 and 77.1±9.4 [ P<0.001]; heart symptoms: 71.9±11.6 versus 75.7±11.0 and 76.8±10.3 [ P<0.001]; cognitive problems: 65.4±11.1 versus 69.4±12.1 and 74.6±13.6 [ P<0.001]). After adjustment for other clinical and demographic variables in the multivariable linear regression model, family SES significantly affected all dimensions of HRQOL except for treatment barriers, treatment anxiety, physical appearance and communication. Conclusions Family SES is an important factor associated with HRQOL in patients with critical congenital heart disease. Further targeted interventions to improve HRQOL that consider the family and environmental issues confronted by those who are economically disadvantaged might help these patients have better outcomes.

Transthoracic Pulmonary Artery Denervation for Pulmonary Arterial Hypertension.

Objective- Pulmonary arterial hypertension is characterized by progressive pulmonary vascular remodeling and persistently elevated mean pulmonary artery pressures and pulmonary vascular resistance. We aimed to investigate whether transthoracic pulmonary artery denervation (TPADN) attenuated pulmonary artery (PA) remodeling, improved right ventricular (RV) function, and affected underlying mechanisms. We also explored the distributions of sympathetic nerves (SNs) around human PAs for clinical translation. Approach and Results- We identified numerous SNs in adipose and connective tissues around the main PA trunks and bifurcations in male Sprague Dawley rats, which were verified in samples from human heart transplant patients. Pulmonary arterial hypertensive rats were randomized into TPADN and sham groups. In the TPADN group, SNs around the PA trunk and bifurcation were completely and accurately removed under direct visualization. The sham group underwent thoracotomy. Hemodynamics, RV function, and pathological changes in PA and RV tissues were measured via right heart catheterization, cardiac magnetic resonance imaging, and pathological staining, respectively. Compared with the sham group, the TPADN group had lower mean pulmonary arterial pressures, less PA and RV remodeling, and improved RV function. Furthermore, TPADN inhibited neurohormonal overactivation of the sympathetic nervous system and renin-angiotensin-aldosterone system and regulated abnormal expressions and signaling of neurohormone receptors in local tissues. Conclusions- There are numerous SNs around the rat and human main PA trunks and bifurcations. TPADN completely and accurately removed the main SNs around PAs and attenuated pulmonary arterial hypertensive progression by inhibiting excessive activation of the sympathetic nervous system and renin-angiotensin-aldosterone system neurohormone-receptor axes.

A generalized deep learning model for heart failure diagnosis using dynamic and static ultrasound.

Objective:Echocardiography (ECG) is the most common method used to diagnose heart failure (HF). However, its accuracy relies on the experience of the operator. Additionally, the video format of the data makes it challenging for patients to bring them to referrals and reexaminations. Therefore, this study used a deep learning approach to assist physicians in assessing cardiac function to promote the standardization of echocardiographic findings and compatibility of dynamic and static ultrasound data.Methods:A deep spatio-temporal convolutional model r2plus1d-Pan (trained on dynamic data and applied to static data) was improved and trained using the idea of "regression training combined with classification application," which can be generalized to dynamic ECG and static cardiac ultrasound views to identify HF with a reduced ejection fraction (EF < 40%). Additionally, three independent datasets containing 8976 cardiac ultrasound views and 10085 cardiac ultrasound videos were established. Subsequently, a multinational, multi-center dataset of EF was labeled. Furthermore, model training and independent validation were performed. Finally, 15 registered ultrasonographers and cardiologists with different working years in three regional hospitals specialized in cardiovascular disease were recruited to compare the results.Results:The proposed deep spatio-temporal convolutional model achieved an area under the receiveroperating characteristic curve (AUC) value of 0.95 (95% confidence interval [CI]: 0.947 to 0.953) on the training set of dynamic ultrasound data and an AUC of 1 (95% CI, 1 to 1) on the independent validation set. Subsequently, the model was applied to the static cardiac ultrasound view (validation set) with simultaneous input of 1, 2, 4, and 8 images of the same heart, with classification accuracies of 85%, 81%, 93%, and 92%, respectively. On the static data, the classification accuracy of the artificial intelligence (AI) model was comparable with the best performance of ultrasonographers and cardiologists with more than 3 working years (P = 0.344), but significantly better than the median level (P = 0.0000008).Conclusion:A new deep spatio-temporal convolution model was constructed to identify patients with HF with reduced EF accurately (< 40%) using dynamic and static cardiac ultrasound images. The model outperformed the diagnostic performance of most senior specialists. This may be the first HF-related AI diagnostic model compatible with multi-dimensional cardiac ultrasound data, and may thereby contribute to the improvement of HF diagnosis. Additionally, the model enables patients to carry "on-the-go" static ultrasound reports for referral and reexamination, thus saving healthcare resources.

Flexible electronics for cardiovascular healthcare monitoring.

Cardiovascular diseases (CVDs) are one of the most urgent threats to humans worldwide, which are responsible for almost one-third of global mortality. Over the last decade, research on flexible electronics for monitoring and treatment of CVDs has attracted tremendous attention. In contrast to conventional medical instruments in hospitals that are usually bulky, hard to move, monofunctional, and time-consuming, flexible electronics are capable of continuous, noninvasive, real-time, and portable monitoring. Notable progress has been made in this emerging field, and thus a number of significant achievements and concomitant research prospects deserve attention for practical implementation. Here, we comprehensively review the latest progress of flexible electronics for CVDs, focusing on new functions provided by flexible electronics. First, the characteristics of CVDs and flexible electronics and the foundation of their combination are briefly reviewed. Then, four representative applications of flexible electronics for CVDs are elaborated: blood pressure (BP) monitoring, electrocardiogram (ECG) monitoring, echocardiogram monitoring, and direct epicardium monitoring. Their operational principles, progress, merits and demerits, and future efforts are discussed. Finally, the remaining challenges and opportunities for flexible electronics for cardiovascular healthcare are outlined.

Analysis and prediction of research hotspots and trends in pediatric medicine from 2,580,642 studies published between 1940 and 2021.

Wearable ultrasound bioelectronics for healthcare monitoring.

Genetic overlap for ten cardiovascular diseases: A comprehensive gene-centric pleiotropic association analysis and Mendelian randomization study.

Recent studies suggest that pleiotropic effects may explain the genetic architecture of cardiovascular diseases (CVDs). We conducted a comprehensive gene-centric pleiotropic association analysis for ten CVDs using genome-wide association study (GWAS) summary statistics to identify pleiotropic genes and pathways that may underlie multiple CVDs. We found shared genetic mechanisms underlying the pathophysiology of CVDs, with over two-thirds of the diseases exhibiting common genes and single-nucleotide polymorphisms (SNPs). Significant positive genetic correlations were observed in more than half of paired CVDs. Additionally, we investigated the pleiotropic genes shared between different CVDs, as well as their functional pathways and distribution in different tissues. Moreover, six hub genes, including ALDH2, XPO1, HSPA1L, ESR2, WDR12, and RAB1A, as well as 26 targeted potential drugs, were identified. Our study provides further evidence for the pleiotropic effects of genetic variants on CVDs and highlights the importance of considering pleiotropy in genetic association studies.

Mapping the early life gut microbiome in neonates with critical congenital heart disease: multiomics insights and implications for host metabolic and immunological health.

BACKGROUND:The early life gut microbiome is crucial in maintaining host metabolic and immune homeostasis. Though neonates with critical congenital heart disease (CCHD) are at substantial risks of malnutrition and immune imbalance, the microbial links to CCHD pathophysiology remain poorly understood. In this study, we aimed to investigate the gut microbiome in neonates with CCHD in association with metabolomic traits. Moreover, we explored the clinical implications of the host-microbe interactions in CCHD.METHODS:Deep metagenomic sequencing and metabolomic profiling of paired fecal samples from 45 neonates with CCHD and 50 healthy controls were performed. The characteristics of gut microbiome were investigated in three dimensions (microbial abundance, functionality, and genetic variation). An in-depth analysis of gut virome was conducted to elucidate the ecological interaction between gut viral and bacterial communities. Correlations between multilevel microbial features and fecal metabolites were determined using integrated association analysis. Finally, we conducted a subgroup analysis to examine whether the interactions between gut microbiota and metabolites could mediate inflammatory responses and poor surgical prognosis.RESULTS:Gut microbiota dysbiosis was observed in neonates with CCHD, characterized by the depletion of Bifidobacterium and overgrowth of Enterococcus, which was highly correlated with metabolomic perturbations. Genetic variations of Bifidobacterium and Enterococcus orchestrate the metabolomic perturbations in CCHD. A temperate core virome represented by Siphoviridae was identified to be implicated in shaping the gut bacterial composition by modifying microbial adaptation. The overgrowth of Enterococcus was correlated with systemic inflammation and poor surgical prognosis in subgroup analysis. Mediation analysis indicated that the overgrowth of Enterococcus could mediate gut barrier impairment and inflammatory responses in CCHD.CONCLUSIONS:We demonstrate for the first time that an aberrant gut microbiome associated with metabolomic perturbations is implicated in immune imbalance and adverse clinical outcomes in neonates with CCHD. Our data support the importance of reconstituting optimal gut microbiome in maintaining host metabolic and immunological homeostasis in CCHD. Video Abstract.

Suppression of Myocardial Hypoxia-Inducible Factor-1α Compromises Metabolic Adaptation and Impairs Cardiac Function in Patients With Cyanotic Congenital Heart Disease During Puberty.

BACKGROUND:Cyanotic congenital heart disease (CCHD) is a complex pathophysiological condition involving systemic chronic hypoxia (CH). Some patients with CCHD are unoperated for various reasons and remain chronically hypoxic throughout their lives, which heightens the risk of heart failure as they age. Hypoxia activates cellular metabolic adaptation to balance energy demands by accumulating hypoxia-inducible factor 1-α (HIF-1α). This study aims to determine the effect of CH on cardiac metabolism and function in patients with CCHD and its association with age. The role of HIF-1α in this process was investigated, and potential therapeutic targets were explored.METHODS:Patients with CCHD (n=25) were evaluated for cardiac metabolism and function with positron emission tomography/computed tomography and magnetic resonance imaging. Heart tissue samples were subjected to metabolomic and protein analyses. CH rodent models were generated to enable continuous observation of changes in cardiac metabolism and function. The role of HIF-1α in cardiac metabolic adaptation to CH was investigated with genetically modified animals and isotope-labeled metabolomic pathway tracing studies.RESULTS:Prepubertal patients with CCHD had glucose-dominant cardiac metabolism and normal cardiac function. In comparison, among patients who had entered puberty, the levels of myocardial glucose uptake and glycolytic intermediates were significantly decreased, but fatty acids were significantly increased, along with decreased left ventricular ejection fraction. These clinical phenotypes were replicated in CH rodent models. In patients with CCHD and animals exposed to CH, myocardial HIF-1α was upregulated before puberty but was significantly downregulated during puberty. In cardiomyocyte-specific Hif-1α-knockout mice, CH failed to initiate the switch of myocardial substrates from fatty acids to glucose, thereby inhibiting ATP production and impairing cardiac function. Increased insulin resistance during puberty suppressed myocardial HIF-1α and was responsible for cardiac metabolic maladaptation in animals exposed to CH. Pioglitazone significantly reduced myocardial insulin resistance, restored glucose metabolism, and improved cardiac function in pubertal CH animals.CONCLUSIONS:In patients with CCHD, maladaptation of cardiac metabolism occurred during puberty, along with impaired cardiac function. HIF-1α was identified as the key regulator of cardiac metabolic adaptation in animals exposed to CH, and pubertal insulin resistance could suppress its expression. Pioglitazone administration during puberty might help improve cardiac function in patients with CCHD.

Impact of Family Socioeconomic Status on Health-Related Quality of Life in Children With Critical Congenital Heart Disease.

Background Socioeconomic status ( SES ) is associated with health-related quality of life ( HRQOL ) for children with critical congenital heart disease; however, literature from newly industrialized countries is scarce. Methods and Results This cross-sectional study included 2037 surviving patients operated on for critical congenital heart disease at a tertiary hospital in China between May 2012 and December 2015. All eligible patients were aged 2 to 12 years. HRQOL was measured by the Pediatric Quality of Life Inventory 4.0 generic and 3.0 cardiac modules. Family SES was assessed by a composite of household income in the past year and occupation and education level of each parent in the family. Mean scores of major domains in HRQOL were significantly lower in the low- SES group than in the medium- and high- SES groups (total generic scores: 71.2±7.9 versus 75.0±8.0 and 76.0±7.9, respectively [ P<0.001]; psychosocial functioning: 70.8±9.0 versus 74.4±8.4 and 75.3±8.4 [ P<0.001]; physical functioning: 71.6±10.4 versus 76.0±9.7 and 77.1±9.4 [ P<0.001]; heart symptoms: 71.9±11.6 versus 75.7±11.0 and 76.8±10.3 [ P<0.001]; cognitive problems: 65.4±11.1 versus 69.4±12.1 and 74.6±13.6 [ P<0.001]). After adjustment for other clinical and demographic variables in the multivariable linear regression model, family SES significantly affected all dimensions of HRQOL except for treatment barriers, treatment anxiety, physical appearance and communication. Conclusions Family SES is an important factor associated with HRQOL in patients with critical congenital heart disease. Further targeted interventions to improve HRQOL that consider the family and environmental issues confronted by those who are economically disadvantaged might help these patients have better outcomes.

Transthoracic Pulmonary Artery Denervation for Pulmonary Arterial Hypertension.

Objective- Pulmonary arterial hypertension is characterized by progressive pulmonary vascular remodeling and persistently elevated mean pulmonary artery pressures and pulmonary vascular resistance. We aimed to investigate whether transthoracic pulmonary artery denervation (TPADN) attenuated pulmonary artery (PA) remodeling, improved right ventricular (RV) function, and affected underlying mechanisms. We also explored the distributions of sympathetic nerves (SNs) around human PAs for clinical translation. Approach and Results- We identified numerous SNs in adipose and connective tissues around the main PA trunks and bifurcations in male Sprague Dawley rats, which were verified in samples from human heart transplant patients. Pulmonary arterial hypertensive rats were randomized into TPADN and sham groups. In the TPADN group, SNs around the PA trunk and bifurcation were completely and accurately removed under direct visualization. The sham group underwent thoracotomy. Hemodynamics, RV function, and pathological changes in PA and RV tissues were measured via right heart catheterization, cardiac magnetic resonance imaging, and pathological staining, respectively. Compared with the sham group, the TPADN group had lower mean pulmonary arterial pressures, less PA and RV remodeling, and improved RV function. Furthermore, TPADN inhibited neurohormonal overactivation of the sympathetic nervous system and renin-angiotensin-aldosterone system and regulated abnormal expressions and signaling of neurohormone receptors in local tissues. Conclusions- There are numerous SNs around the rat and human main PA trunks and bifurcations. TPADN completely and accurately removed the main SNs around PAs and attenuated pulmonary arterial hypertensive progression by inhibiting excessive activation of the sympathetic nervous system and renin-angiotensin-aldosterone system neurohormone-receptor axes.