Mytilus spp. by a bioinformatics approach. In both laboratory and field studies, we could show that TNT induces a strong and concentration-dependent induction of gene expression of carbonyl reductase in the blue mussel. Carbonyl reductase may thus serve as a biomarker for TNT exposure on a molecular level which is useful to detect TNT contaminations in the environment and to perform a risk assessment both for the ecosphere and the human seafood consumer.Millions of tons of all kind of munitions, including mines, bombs and torpedoes have been dumped after World War II in the marine environment and do now pose a new threat to the seas worldwide. Beside the acute risk of unwanted detonation, there is a chronic risk of contamination, because the metal vessels corrode and the toxic and carcinogenic explosives (trinitrotoluene (TNT) and metabolites) leak into the environment. While the mechanism of toxicity and carcinogenicity of TNT and its derivatives occurs through its capability of inducing oxidative stress in the target biota, we had the idea if TNT can induce the gene expression of carbonyl reductase in blue mussels. Carbonyl reductases are members of the short-chain dehydrogenase/reductase (SDR) superfamily. They metabolize xenobiotics bearing carbonyl functions, but also endogenous signal molecules such as steroid hormones, prostaglandins, biogenic amines, as well as sugar and lipid peroxidation derived reactive carbonyls, the latter providing a defence mechanism against oxidative stress and reactive oxygen species (ROS). Here, we identified and cloned the gene coding for carbonyl reductase from the blue mussel  Stegastes adustus) and sea urchin (Diadema antillarum) collected at the naval gunnery and bombing range of Isla de Vieques, Puerto Rico.Trinitrotoluene (TNT) is one of the most used explosives worldwide, nowadays and in the past, both in civil and military activities (Juhasz and Naidu Danio rerio). Schuster et al. (Mytilus spp.). Interestingly, the mechanism of toxicity and carcinogenicity of TNT and its derivatives occurs through its capability of inducing oxidative stress and reactive oxygen species (ROS) in the target biota  was first characterized by Wermuth . Later, Mytilus spp.) which had been exposed for several weeks in three active biomonitoring studies at Kolberger Heide  and 4-amino-2,6-dinitrotoluene (4-ADNT) were detected in blue mussels . The carbonyl reductase gene obtained from Mytilus spp. was verified by Sanger sequencing at the Institute of Clinical Molecular Biology, Kiel, Germany , 20 pmol of primers as described in Table 1, and 200 µM dNTPs in a total of volume 20 µL. Thermo cycling was performed using the following conditions: initial denaturation at 98 °C for 30 s followed by 35 amplification cycles  and a final extension step at 72 °C for 10 min. The PCR product (765 bp) was cloned into a pJET 1.2/blunt cloning vector using the CloneJET PCR Cloning Kit  and NEB 5-alpha Competent Mytilus spp.) were purchased from a commercial mussel farm in Kiel Fjord. The mussels were transferred to the laboratory in an aerated cooling box with ambient seawater eight days before the experiments started. At the farm, water temperature and salinity were measured and recorded. Corresponding to the measured temperature, mussels were kept in a temperature-controlled lab using two 20-L aquaria filled with ambient seawater from the farm site. After 48 h, ambient seawater was exchanged by half of the volume using premixed artificial seawater with an equal to ambient salinity of 18 psu. This procedure was repeated every 24 h until the experiments started.Blue mussels , and pre-cooled before usage. The salinity was checked before water exchange using a conductivity meter. Every 48 h, mussels were fed with 6 ml live phytoplankton (Premium Reef Blend) per aquarium two hours prior to the water exchange. Twenty-four hours before the start of the exposure experiments, mussels were transferred to 15-L aquaria filled with 10 L of artificial seawater. During exposure, the room was kept constantly at 9 °C (96 h exposure) and 3 °C (21 days exposure), with a light/dark rhythm of 8:16 according to the ambient conditions at the mussel farm.Three aquaria were used for each of the treatment concentrations and seven mussels were exposed per aquarium. The artificial seawater in the aquaria was spiked with different concentrations of a TNT solution, except for the three control aquaria. Water exchange and re-dosing of dissolved TNT was conducted on a daily basis by emptying and refilling the aquaria. To yield the required TNT concentration in the artificial seawater, a corresponding amount of TNT solution was transferred from the stock solution to the aquaria. The stock solution of 100 mg/L TNT was produced by the GEKA mbH  by dissolving TNT crumbs received from grenades from WW II in dichloromethane. Aliquots were removed from the solution, evaporated at room temperature and re-dissolved in water at 80 °C.The following exposure experiments were performed: (1) an acute toxicity test (96 h) with aquaria concentrations of 0; 0.31; 0.62; 1.25; 2.5, 5; 10 mg/L TNT solution following the guidelines of the OECD  and (2) The field exposure study was conducted at the munitions dumpsite Kolberger Heide in Kiel Bight at the entrance to Kiel Fjord, Germany Fig. . In thislater® reagent  were added to each tube and incubated overnight. Tissues were then removed from the reagent, transferred to 2 mL Eppendorf tubes and stored until further processing at − 80 °C. RNA was isolated using the commercially available Roti®-Prep RNA MINI kit . After addition of lysis buffer, the tissues were homogenized using a T25 Ultra-Turrax . RNA was purified according to the manufacturer’s protocol and quantified with Qubit® HS RNA Assay kit  on a Qubit® 2.0 Fluorometer . RNA was stored at − 80 °C until further use. An amount of 1000 ng of RNA was reverse transcribed using RevertAid H minus reverse transcriptase  with 400 ng of Random Primers  for 10 min at 25 °C, followed by 60 min at 42 °C and at − 20 °C.Mussels were opened and a maximum of 20 mg tissue of each, gills, hepatopancreas, mantle and muscle, were transferred into 1.5 mL Eppendorf tubes. Up to three samples of each tissue and mussel were taken. For stabilization of RNA, 200 µL of RNA. M. edulis 18 s RNA served as housekeeping gene  using 1.5 µL cDNA, 20 pmol primers and 200 µM dNTPs in a total volume of 20 µL. Thermo cycling was performed using the following conditions: initial denaturation at 98 °C for 30 s followed by varying amplification cycles . The temperature program during the amplification cycles was performed at 98 °C for 5 s, 50 °C for 5 s, 72 °C for 15 s. A final extension step was performed at 72 °C for 1 minThe chemical tissue analysis was performed as described in Strehse et al. : Mussel Values of the measured concentrations of TNT and the metabolites 2-ADNT and 4-ADNT in the mussel tissues are expressed as mean ± standard deviation. Descriptive statistics of the densitometric results obtained from the RT-PCR experiments were computed with GraphPad Prism 8 (version 8.4.2).Mytilus species occurring in the Baltic Sea are obviously a hybrid form of Mytilus trossulus and Mytilus edulis, we aimed, at first, on the identification and cloning of the carbonyl reductase gene of the Mytilus species used in the present study. By a bioinformatics approach, we obtained a “proposed” carbonyl reductase gene sequence . Mussels were dissected to obtain the following tissues of interest: mantle, muscle, gills and hepatopancreas. While muscle tissue contained the lowest levels of carbonyl reductase expression, and intermediate levels were observed for mantle tissue and the hepatopancreas, the highest expression was observed in the gills  in 7U mussels compared to 7 O mussels , the other at a height of one meter (7 O). This is important because mussel exposure towards TNT and its metabolites could be expected to be higher at 7 U compared to 7 O  per g mussel tissue.Initial TNT concentrations in the exposure aquaria, given as mg/L, in most cases resulted in 3–5 fold accumulation of TNT plus metabolites in the corresponding mussels Table . This fiAsteroidea sp.), algae and tunicates collected at Kolberger Heide as well as in the bile of dab (Limanda limanda L.) caught in this area, TNT and other explosive residues were found  treated with TNT in two laboratory studies. This multi-biomarker approach comprised genetic, cellular and metabolic effects in correlation to TNT exposure were observed. Likewise, elevated levels of unspecific oxidative damages were seen. Nonetheless, neither one of the observed biomarkers alone nor the entire biomarker approach as such were able to serve as a specific indicator for a possible TNT contamination in the marine environment.In previous investigations, we have established the mussel In the present investigation we, therefore, focused on the metabolic antioxidant defence system on a molecular level and concentrated on the induction of the carbonyl reductase gene which is known to respond to oxidative stress and reactive oxygen species (ROS)   were exposed to TNT in two laboratory experiments and in a field study and then investigated in terms of their response in form of carbonyl reductase gene induction. As the third step, we determined the occurrence of TNT and derivatives thereof in the mussel tissues and to relate the concentrations of these explosives to the extent of carbonyl reductase gene induction. Our results indeed indicate that carbonyl reductase is induced upon TNT exposure and could possibly serve as the first molecular biomarker for this explosive compound.Since the mechanism of toxicity and carcinogenicity of TNT and its derivatives occurs through its capability of inducing oxidative stress in the target biota, we had the idea if TNT can induce the gene expression of carbonyl reductase in blue mussels. As a first step, we were able to identify and clone the gene coding for carbonyl reductase in the blue mussel (p.) Fig. . The MytMussels were dissected, and gills, hepatopancreas, mantle and muscle tissue were investigated individually for carbonyl reductase gene expression. Especially in the gills, the respiratory organ with intensive blood circulation and first contact with pollutants from the surrounding water, we found significant correlations between TNT exposure and carbonyl reductase gene induction. This indicates a high sensitivity of carbonyl reductase to TNT exposure. Interestingly, the extent of carbonyl reductase gene induction showed a strong correlation to the initial TNT concentrations in the different aquaria. Likewise, carbonyl reductase gene induction was seen for hepatopancreas as the main digestive and metabolic organ in mussels. Basal carbonyl reductase expression could also be observed in mantle and muscle tissue, but compared to gills and hepatopancreas this expression was much weaker and induction was hardly shown. In general, the metabolic activity in mantle and muscle tissues is relatively low, therefore, they served as a comparison for the tissue-dependent basal and induced expression of carbonyl reductase in our study.To relate the level of gene induction to the content of TNT in the mussel tissues, we determined the tissue concentrations of TNT and metabolites thereof via GC–MS/MS analysis. Although for the laboratory exposure studies only TNT  itself was dissolved in the aquaria, mussel tissue determination by GC–MS/MS analysis yielded the two TNT metabolites 2-amino-4,6-dinitrotoluene (2-ADNT) and 4-amino-2,6-dinitrotoluene (4-ADNT) as the principal explosives. This finding does also apply for the field experiment. While in mussels placed directly on the ground, TNT itself, as well as 2- and 4-ADNT was observed, in mussels placed one meter above the seabed at the same position, only 4-ADNT but neither TNT nor 2-ADNT could be detected. It is well known, that transformation processes of parent TNT include photolysis, hydrolysis, oxidation, reduction, and biological transformation  in all analyzed tissues  compared to mussels from one meter above at the same mooring. Although the mussels from 7 U and 7 O were only one meter apart from each other, this difference can be explained with the differing TNT water concentrations pattern in this area. Beck et al.  are more or less comparable to the (higher) concentrations of TNT in the lab studies, indicating that carbonyl reductase gene induction in the field study is indeed a result of the high TNT concentration at this position (7 U). This is supported by the fact that significant carbonyl reductase gene expression occurs already at tissue concentrations below 5 µg of explosives (sum of TNT plus 2-ADNT and 4-ADNT) per g (wet weight) of mussel tissue.TNT leaking from dumped conventional munitions poses a major threat to the marine environment (Nipper et al.


In this March 2021 issue, we start with interesting papers on non-communicable diseases.Thus, Jian Ma and colleagues have a meta-analysis on the efficacy of dapagliflozin in type 1 diabetes mellitus.16Nyoni-Kachambwa's paper on skin bleaching18Papers on sickle cell anemiaOlusegun-Joseph et. al have written on mortality in an emergency department in NigeriaNow to infections. Yes, you guessed right! We have failed to resist the temptation and included papers on Covid-19: roles of exercise and immunity 28We have several papers on TB: hearing-threshold in drug-resistant TBNow to reproductive and child health. There are papers on ectopic pregnancy in the Gambia48EucalyptusThen we have a cocktail of papers on anti-inflammatory potential of surgical issues: intestinal stoma in UgandaThis ushers in


The pathophysiology of heart failure with preserved ejection fraction (HFpEF) is complex and poorly understood. There is a high prevalence of Diabetes Mellitus (DM) in patients with HFpEF, and the presence of DM has been shown to increase mortality of patients with HFpEF by 30%-50% even after adjustment for age, gender, hospital factors, and other patient characteristics. Since the prevalence of both entities is increasing worldwide, there is a need to explore their intricate relationship in order to elucidate potential management strategies to reduce the morbidity and mortality associated with this duo. In this review article, we explore the role of DM in the pathophysiology of HFpEF, ethnic and gender differences, and some therapeutic strategies in the management of patients with HFpEF and DM. The incidence of type 2 DM and HFpEF has been on the rise over the last several decades. According to the World Health Organization (WHO), there were 422 million diabetic patients worldwide in 2014, which is a rise from 108 million in 1980. In 2014, more than 8.5% of adults aged 18 years and older had DM, and DM is the direct cause of death in 1.5 million patients .HFpEF is a subtype of heart failure in which there is insufficient cardiac output for the metabolic needs of the body. The typical clinical features of DM associated with cardiac dysfunction include reduced ventricular compliance with increased systemic and pulmonary venous pressures and congestion despite preserved systolic function. This manifests as a clinical syndrome of volume overload associated with shortness of breath, orthopnea, paroxysmal nocturnal dyspnea (PND), rales/crackles, and at times with peripheral edema . The cliBecause all heart failure syndromes are inherently associated with diastolic dysfunction, the old term “diastolic heart failure” or “systolic heart failure” are being phased out in preference for categorization based on ejection fraction. There is heart failure with reduced ejection fraction , heart failure with mid-range ejection fraction , and heart failure with preserved ejection fraction . The hallmark of HFpEF is diastolic dysfunction which entails impaired left ventricular (LV) relaxation and compliance. This leads to increased LV end-diastolic pressure and pulmonary capillary wedge pressure by invasive measurements. Non-invasively, diastolic dysfunction in HFpEF is diagnosed with three out of the four echocardiographic criteria: 1) decreased septal and lateral tissue doppler velocity (<7 and <10cm/s respectively); 2) elevated left atrial volume index > 34mL/m2; 3) average mitral inflow/tissue doppler velocity > 14; and 4) tricuspid regurgitation velocity > 2.8m/s [The diagnosis of HFpEF can be challenging in symptomatic but euvolemic patients, who present with non-specific symptoms such as dyspnea on exertion . BecauseThe incidence of heart failure in the United States each year is about 650,000, and at least half of them have HFpEF . Each yeSeveral hypotheses have been proposed, including macroscopic changes that result from altered glucose and free-fatty acid (FFA) metabolism in diabetic patients. The macroscopic remodeling that results from altered glucose and FFA metabolism include increased deposition and reduced degradation of extracellular collagen; interstitial fibrosis; myocyte hypertrophy; and intramyocardial microangiopathy. The absence of effective treatment for HFpEF represents an unmet medical need and has led to increased interest in this condition, its pathophysiology, and treatment strategies. In this literature review, we summarize the pathophysiologic mechanisms, the racial/ethnic and gender differences, and therapeutic implications.A systematic review of the literature was performed using PubMed and Medline computerized databases. Published literature relating to DM and HFpEF was obtained using keywords “heart failure”, “heart failure with preserved ejection fraction”, “diastolic dysfunction”, “heart failure and diabetes”, heart failure with normal ejection fraction” in association with “Diabetes”, “Diabetes Mellitus” and “DM”. All literature was screened for appropriateness by title. There were 15,527 articles identified on the initial search. After duplicates were removed, the remaining 10,275 were screened by title for relevance to the subject matter. Out of the remaining publications, 10,225 were deemed irrelevant to the subject and were removed. Articles removed due to relevance addressed DM and other forms of heart failure other than HFpEF. Articles not written in the English language were also excluded. Abstracts without full articles were excluded. The remaining 50 articles were then reviewed in full and five were further excluded because they did not address the mechanistic relationship between DM and HFpEF or treatment options. Forty-five full articles were reviewed and included in this article. The article inclusion/exclusion process is shown in Figure Mechanisms: genetic, transcriptional, and translational changesAt the transcription level, DM can lead to diastolic dysfunction by its action on cellular proliferation through interaction between insulin-like growth factors (IGFs) and growth hormones (GH) . The RELIn addition to the above transcriptional and translational changes, there are other possible mechanisms, including upregulation of fetal gene programming involving an increase in beta-myosin heavy chain gene (MHG) and deregulation of fast-contracting isoforms, all of which lead to an impaired rate of myocardial relaxation and worse diastolic dysfunction in HFpEF .Mechanisms: multi-protein interactions and cellular changesDue to altered glucose and free fatty acids (FFA) metabolism, there is increased utilization of FFA in myocytes of patients with diabetes and HFpEF. Because the metabolism of FFA utilizes more oxygen compared to the metabolism of glucose, there is increased oxidative stress and the formation of oxidative free radicals within myocytes that lead to cell injury and diastolic dysfunction . Over tiIn addition to the formation of cardiotoxic oxidative free radicals in patients with HFpEF, DM also promotes the formation of advanced glycosylation end-products (AGEs), activation of polyol, and NADP-pathways ,19. ThesChronic oxidative stress leads to myocardial fibrosis and increased intracellular and extracellular matrix deposition. Several pathways involved in the downregulation of matrix degradation are also activated, further causing a worsened imbalance between matrix deposition and degradation. LV diastolic dysfunction and HFpEF are partly due to this imbalance .DM is associated with diffuse microangiopathy that is not readily apparent on traditional coronary angiography, which detects macrovascular disease. Due to coronary microangiopathy and associated endothelial dysfunction, there is impaired oxygen delivery and utilization by myocytes. There is also a decrease in coronary flow reserve associated with blunted effects of adenosine and endogenous nitrates -22. ThesMacrovascular disease is a well-known contributor to diastolic dysfunction and HFpEF. Diabetes leads to accelerated macrovascular disease that worsens atherosclerotic build-up seen in obstructive coronary artery disease (CAD) . With thMechanisms: neurohormonal dysregulationDiabetes is related to a wide array of several neurohormonal dysregulations that contribute to adverse outcomes in patients with HFpEF. Through increased angiotensinogen released from the adrenal glands and upregulation of cardiac angiotensin II receptors, DM is associated with advanced hypertensive heart disease and diastolic dysfunction . HyperglMechanisms: heightened inflammatory milieuIncreasing evidence exists to support the role of the heightened inflammatory milieu present in DM with progression of diastolic dysfunction. DM is associated with increased concentration of serum inflammatory markers such as C-reactive protein (CRP), soluble suppression of tumorgenesis-2 (sST2), galectin-3, C-terminal propeptide of procollagen type I (PICP), N-terminal propeptide of procollagen type III (PIIINP), matrix metalloproteinase-9 (MMP-9) and tissue inhibitor of matrix proteinase-1 (TIMP-1) . It has Racial and ethnic factorsThe lifetime risk for new incidence of HFpEF is higher in white than in black patients, but black patients have worse heart failure readmissions compared to white patients . A sub-aGender differencesThe lifetime incidence of HFpEF is similar in both men and women, but the female sex is associated with worse outcomes, including higher rates of HFpEF hospitalizations . The ratSeveral epidemiological and associative studies highlight the role of estrogens in diabetic heart disease as a sex- and age-dependent event ,31. HoweTherapeutic implicationsThere is currently no consensus regarding the most effective preventive or therapeutic approaches to treat HFpEF, let alone those with concomitant DM. For that reason, guidelines recommend diuretics for fluid removal and symptom relief, and management of associated comorbidities . Currently, the management of high blood glucose levels in patients with DM and CV risk and CVD is tailored to minimize the risk of CV complications, with metformin as first-line therapy . Few oraOther oral hypoglycemic agents have neutral cardiovascular outcomes and does not show to improve or worsen ischemic and heart failure outcomes. These neutral classes of medications include DPP-4 inhibitors ,44; insuSeveral trials and meta-analyses have established that metformin, the only publicly available biguanide, is safe, efficacious, and is associated with improved cardiovascular outcomes in heart failure patients, making metformin first-line therapy for the treatment of DM in HFpEF patients -38. A reRecently, SGLT2 inhibitors, especially empagliflozin, have also been shown to improve diastolic dysfunction and heart failure outcomes in both rodent models and humans with HFpEF through a reduction in wall stress by decreasing preload and altered hemodynamics . Trials It is important to note that the use of thiazolidinediones (TZDs) in heart failure patients has been shown to increase heart failure hospitalizations . The proHFpEF and DM commonly co-exist, and the presence of DM independently and significantly increases mortality in patients with HFpEF. The presence of DM in HFpEF patients worsens diastolic dysfunction through several mechanisms involving altered glucose and FFA metabolism; transcriptional and translational changes; increased oxidative stress through actions of free radicals; neurohormonal dysregulation; heightened inflammatory milieu, and microvascular/macrovascular alterations and injury. There are racial differences in HFpEF patients with DM. The lifetime risk for incident HFpEF is higher in non-blacks than in black patients, but black patients have worse heart failure readmissions compared to non-blacks. Females are also associated with worse outcomes, including the rate of HFpEF hospitalizations, although the prevalence of HFpEF is comparable in men and women. Therapeutic strategies for the management of diabetes that have been shown to improve cardiovascular outcomes include biguanides and SGLT2 inhibitors, while TZDs are associated with adverse heart failure outcomes and should be avoided in heart failure patients. Other medication classes, including DPP-4 inhibitors; insulin (glargine); alpha-glucosidase inhibitors; glinides; D2-dopamine agonists; GLP-1 agonist; and sulfonylurea are neutral to heart failure outcomes.


Human Pose Estimation (HPE) has received considerable attention during the past years, improving its performance thanks to the use of Deep Learning, and introducing new interesting uses, such as its application in Sport and Physical Exercise (SPE). The aim of this systematic review is to analyze the literature related to the application of HPE in SPE, the available data, methods, performance, opportunities, and challenges. One reviewer applied different inclusion and exclusion criteria, as well as quality metrics, to perform the paper filtering through the paper databases. The Association for Computing Machinery Digital Library, Web of Science, and dblp included more than 500 related papers after the initial filtering, finally resulting in 20. In addition, research was carried out regarding the publicly available data related to this topic. It can be concluded that even if related public data can be found, much more data is needed to be able to obtain good performance in different contexts. In relation with the methods of the authors, the use of general purpose systems as base, such as Openpose, combined with other methods and adaptations to the specific use case can be found. Finally, the limitations, opportunities, and challenges are presented. Human Pose Estimation (HPE) consists of estimating the position of different parts of the body, such as the joints in a 2D or 3D space depending on the estimation type, normally from visual information, such as images, and sometimes through other additional data obtained by different types of sensors, such as inertial sensors or depth sensors. This field of research can be considered a combination of Data Processing and Artificial Intelligence, more specifically, Computer Vision.Since 2014, and mainly the past 5 years, the use and interest in HPE has increased, mainly due to the introduction of Deep Learning to the field [There are some available surveys that give an overall view on the papers as well as the State Of The Art (SOTA) systems, such as ,3. The fBoth surveys and preliminary analysis of the available papers about HPE show how the applications of HPE have increased. Different uses of these types of systems can be found, such as in the field of health , Human CThis paper consists of a systematic review based on the PRISMA guidelines, in which the objective is to provide a similar analysis of the literature as provided by other HPE survey or literature review papers, but that is focused on the application of HPE to the field of SPE, highlighting some aspects related with these systems as well as applying an analysis and review that follows the criteria specified throughout the paper. The importance of the evaluation, taking into account the used metrics and data, as well as the provided information and detail of the process, is highlighted, but other aspects related to the quality of the work and the paper are considered too. The innovations and evolution of this specific field, as well as the problems and opportunities, will be presented. As it can be seen in the literature reviews related to general-purpose HPE systems, those systems are trained in a variety of contexts and actions, but they are not specifically focused on SPE. The movements in sport and during physical exercise tend to be different from the “standard” movements, sometimes being very explosive movements, others including occlusions of other players or tools, and others including more challenging body positions, such as in gymnastics or yoga. So, even if a general-purpose system can be applied in those contexts, depending on the sport, exercise, or specific needs, it will not perform as well as a more specialized system that is adapted to each context and trained with specific data. This is why it is important to analyze if a general-purpose system can be used in SPE, in which sports it performs better as well as getting to know the needs of adaptations to improve the performance, even if the evaluation metrics and base architectures are the same.Several research questions are presented in The structure of this paper is as follows. As mentioned previously, before presenting the used methodology for the systematic review, it will be interesting to analyze the evaluation methods used by most authors, to understand how the performance of this type of system is evaluated. There are two key elements involved in the evaluation of an HPE system: metrics and data.OKS):○Commonly used in the COCO Keypoint Challenge.○It is formulated as Equation (1):○id is the Euclidean distance between the detected keypoint and the corresponding ground truth, iv is the visibility flag of the ground truth, iks a per-keypoint constant that controls falloff.Where ○50AP (Average Precision at OKS = 0.50) 75AP, AP , MAP for medium objects, LAP for large objects, and Average recall (AR) at OKS = 0.50, 0.55..., 0.90, 0.955.To put it simply, OKS plays the same role that Intersection over Union plays in object detection. It is calculated from the distance between predicted points and ground truth points normalized by the scale of the person. Typically, standard average precision and recall scores are reported in papers: Object Keypoint Similarity (PCK): A detected joint is considered correct if the distance between the predicted and the true joint is within a certain threshold.○◾PCKh@0.5 is when the threshold = 50% of the head bone link◾PCK@0.2 = Distance between predicted and true joint < 0.2 * torso diameterSome examples:○Sometimes 150 mm is taken as the threshold.○This alleviates the shorter limb problem since shorter limbs have smaller torsos and head bone links.○PCK is used for 2D and 3D (PCK3D). Again, the higher the better.Percentage of Correct Keypoints  and Mean Per Joint Position Error (MPJPE) , or theiOther metrics are used apart from the estimation of the joints of the body, such as in ,18 focusJust like metrics, data is another key point of the evaluation of these types of systems. It is probably one of the most important elements related to the development of any deep learning system, as, apart from conforming the comparison tool between systems, the data is what gives to the system samples from which it should learn. Having good quality publicly available datasets is essential for the machine learning field; thus, taking into account its importance, a summary of the most important and high quality publicly available datasets related to the application of HPE in the field of sport are provided in Additionally, an overall analysis of the data type and sources used by some of the most remarkable papers has been performed, providing a summary in As it can be seen in Regarding publicly available 2D HPE dataset specifically developed for its application in sport, only 2 general sports datasets have been found, which, even being more than what has been found in relation with 3D, can still be considered insufficient for the development of those systems. In this case, the images of the datasets include different types of sport and actions, which could be beneficial for the generalization of the problem in the field of sport. Apart from that, another publicly available dataset is focused on football. As for the 3D dataset, a lack of variety in specialized datasets exists, as some sports need a big data amount including use cases in which the most common problems of those cases are faced, as in yoga for rare positions, gymnastics for different body orientations, swimming for underwater conditions, and specific conditions and wearable tools of different sports.Most of the 2D datasets are created using manual annotations, while most 3D datasets are generated using a MoCap system, such as Kinect or other more complex commercial ones. This could be the reason to have more 2D datasets available and more variety from the point of view of actions, actors, scenarios, and so on. As the process of manual annotation is easier from the technological point of view and can be applied in different contexts easily, it allows authors to work in this area in a deeper and wider way, while authors that want to work with 3D data need to use public datasets created using a MoCap system, and because of this have a limited amount of variety, or get their own MoCap system, and still have the limitations of the needed setup for its use. The only work that addresses the problem of generating ground truth for 3D HPE outside the lab environment is , generatA deeper analysis of In the following sections, the methodology that has been followed for the systematic review will be explained, including what has been analyzed, how and the sources of the papers. For this systematic review, one reviewer screened each record of the literature, the main author of this paper, being 2021/08/01 the last date when the different paper databases were consulted.Date: only papers from the year 2014 to 2021 have been included in the search, as 2014 is the year in which authors started to use Deep Learning for HPE tasks, so, the performance improved and its use started to increase.Publication type: only papers published in journals and conferences with high impact in the field of Computer Science have been included.Estimation type: only HPE has been considered, understood as an overall body pose estimation, as explained in the introduction. So, for example, no eye-pose estimation or hand-pose estimation has been considered during the research. In any case, only general-purpose systems have been found related to those two pose estimation systems, not specifically applied in SPE.Three exclusion criteria have been applied for the review:The inclusion criteria are explained in the following paragraphs, but, in summary, any paper from 2014 to 2021, and published in a journal or a conference of high impact, is included, and if it includes any of the terms explained in the next lines and are related with the topic of HPE applied to SPE, which includes a high variety of sports and physical exercise activities, such as running, walking and jumping, not being necessary to practice them in a competitive way.In order to search for the papers related to the topic of this literature review, the following terms were used, in conjunction with the term ‘Human Pose Estimation’: sport, martial art, soccer, basketball, football, tennis, squash, athlete, athletics, sprint, olympics, swimming, jump, hockey, rowing, cycling, rugby, badminton, baseball, volleyball, boxing, dance, gymnastics, climbing, running cricket, golf, and padel. It should be taken into account that the search took place using the terms as conjunction, so, including different terms will not limit the obtained results. The main term to be searched is ‘sport’, as it should appear in the keywords or other relevant sections of any other paper including any other term searched. Anyway, as some papers could be focused in terms such as ‘athlete’ or ‘olympics’, more than in the term ‘sport’, they have been included as an added value, including the most common sports. In total, more than 500,000 papers were obtained as results of the search in the Association for Computing Machinery Digital Library (ACM DL), more than 280 in the Web of Science (WOS), and more than 25 in dblp. In the case of ACM DL, a big part of the papers was not directly related with the topic, as they are related with general HPE or with hand or objectpost estimation, while in WOS and dblp, mostly all the papers were related with the topic. An initial filtering was applied to the first 160 most relevant papers from each paper dataset from 2014 to 2020, and the first most relevant 80 papers from 2021, removing duplicated or very similar ones, obtaining 20 papers as output. This process can be easily visualized in the flow diagram contained in Other paper repositories were considered for inclusion in the research, but as most of them were not as specialized in Computer Science as ACM DL, WOS and dblp are, the number of relevant papers was not so big and the quality was not so high. For example, Pubmed was considered to be included in the research, but the focus of this search engine is on medicine, so the number of papers related to the current topic was not so high, and the perspective of the work was different, so it has was not included.It is considered essential to specify how the evaluation of the papers from the first filtering was applied, to be completely transparent and as objective as possible. With this objective, a table of classification criteria see , with thThe criteria were selected looking at the most important aspects of the works related to the topic, and the filtering described in As expressed before in the paper, the evaluation of the systems is considered very important when analyzing the work done, as it serves as a way of comparison with other systems as well as a tool to measure the quality of the work. So, as it can be seen in the table, not providing information related to the evaluation process would mean a reduction of the result of the paper evaluation of at least 3.5 points out of 11, so, applying these eligibility criteria the paper would be considered at least 30% worse.As seen in As indicated earlier, three paper databases with high-quality computer science papers were selected, which are summarized in First, Openpose* has a multi-stage CNN architecture. The image is analyzed by a CNN , generating a set of feature maps that is input to the first stage. The first stage produces a set of PAFs iteratively concatenating the prediction with the original image features to produce refined predictions. The second stage predicts confidence maps, using the same iterative process of the first stage. PAFs are very useful for part association, while confidence maps are used for part detection. Each stage is composed of several convolution blocks, which, at the same time, are formed by 3 3 × 3 convolutional kernels, concatenated following an approach similar to DenseNet , which rAfter the first filtering of the papers, which removed all the papers that are not directly related to HPE applied to sport and physical activity, the duplications and very similar papers were deleted. Finally, 20 papers were obtained, taking into account the previously presented eligibility criteria, to present the most interesting papers of the field. The application of the eligibility criteria can be seen in As seen in In addition, data about the years and countries of the publications is provided in It is interesting to analyze as well where the papers were published, in a journal or a conference. With this purpose, OpenPose [action detection or positional predictions of different elements in the sports practice, such as for badminton in [In addition to the papers presented in OpenPose  for actiinton in , volleybinton in , and teninton in . There ainton in . Other winton in  for athlinton in  and Yogainton in . These wIn this section, the objective is to answer the questions in hot topic, which is attracting the interest of the research community, mainly since the year 2017.First of all, as a conclusion regarding the provided statistical information in the previous section, it can be said that taking into account the number of papers published in general about this topic, the topic of this systematic review can be considered a in terms of overall form and content of the papers, it can be concluded that concerning paper quality, implementation, use of HPE in SPE, performed evaluation, and obtained results, [After analyzing the review results,  can be canalysis of the limitations of the study, or the faced problems, is missing. This can be interpreted as an intend to show only the positive aspects of the work to make it more attractive but analyzing the negative aspects and showing them can be a very good habit to improve the quality of the systems by the research community. In any case, most of the papers provide innovative solutions applicable in sport or physical exercise, with good results.In general, all the papers provide a good abstract and explain their experiments and evaluation properly, but, in a lot of cases, the As this topic is quite specific, and, as most of the works are quite recent and there is not a big amount of research papers per year, the citations per paper are quite low. In some cases, there are not citations, but, as explained in a previous paragraph, this can be because some papers have been recently published.the lack of publications regarding the specific topic of HPE applied to SPE can be detected. Even if hundreds of papers can be found using related terms for the search, finally, few related high-quality papers are available.Different conclusions can be reached regarding different aspects of the analyzed information during the literature review. First of all, as a general conclusion, A bigger amount of 3D data is needed.A higher variety in the type of actions/sports present in 3D datasets is needed.The amount of 2D data could be enough for the development of a generic 2D HPE system to be applied in sports, but, when applying that system to specific sports, with their specific characteristics and problems, the error could be higher than expected from the overall sport evaluation. So, more variety of sports is needed, and a bigger amount of data per action/activity, including different challenges for the task of HPE.Regarding the topic of the evaluation data, the conclusions that can be reached after the analysis of its availability are:Publishing the datasets developed by each author could be a very good way of contributing to solving this lack of publicly available data. Each contribution will be part of the data that could be used by different systems to solve the problems faced by the dataset authors or related problems of similar sports or activities.most of the HPE systems applied to sport or exercise are 2D systems, and those which are 3D systems have developed their own dataset for the specific use case, usually not making it available for the research community. This predominance of 2D systems can be due to the previously mentioned lack of 3D HPE datasets for SPE, so, there is a need for a bigger number of samples as well as an increase in the variety of activities. In addition, there are publicly available high-accuracy and fast systems such as OpenPose, introducing their method in [As seen in ethod in , a paperethod in , in whicethod in  has beenethod in , which aOne of the most surprising aspects of the available literature is that a big part of the papers does not use publicly available datasets to evaluate their systems, or they do not make their developed datasets public. As explained previously, data is a key aspect in the concept of replicability of work, as well as in terms of comparison with other systems, so, not including any evaluation with a dataset that can be accessed by other authors can be considered a quite negative aspect. Another key point regarding replicability is making the code available to other authors, and the code of the analyzed papers is not available in any case. When analyzing the literature of general use HPE systems, the code of several systems can be found. In any case, it is understandable that some authors do not consider publishing their code due to potential patent or product possibilities.used data for the development and testing of the systems, on the one hand, several papers such as [Regarding the  such as ,37,38,42 such as ,30. A biCNNs are the base of the methodology of most of the systems, in combination with different methods, such as the use of heatmaps and physical constraints to reduce the error by estimating only feasible body positions. Most of the authors use approaches previously introduced by other authors, and pretrained with public datasets, as the base of their system, and then apply methods to improve the usability of those systems in specific sports or exercise movements. It is common as well to use HPE as a tool to generate new information regarding performance parameters, location of the CoM of the athlete, application of forces, etc.Obviously, and as found in the case of general use HPE systems, solve specific estimation problems in different environments, such as the ones for basketball [HPE and hockey. Some of the authors of [Several approaches are trying to sketball , diving sketball , hockey sketball , etc, whsketball ,41. Takithors of ,60,61 arthors of  is publiFrom the technical point of view, considering the carried-out research, and the results presented in directly apply general-purpose HPE systems for a specific sport in a specific context, trying to measure the applicability of those systems in that specific use case. On the other hand, several papers try to improve existing systems or architectures that have shown good performance in general-purpose contexts, by applying different methods focused on solving specific problems of specific contexts, which includes the type of exercise or sport, the environment, the involved tools, or the objective of the pose estimation. For example, [example, , to solvexample,  create aexample,  implemenexample, ,42 both example, , the autThus, it can be concluded that the need for a specialized HPE system will depend highly on the context in which it is going to be applied, as well as the objective of its application. Sometimes, using a general-purpose system could be enough to get acceptable performance, but, in other cases, with special needs/objectives or challenging characteristics, the implementation of some methods will be necessary. In any case, more experimentation is needed in this field, as the variety of contexts to apply HPE is high, and the needs differ.could be especially interesting in the case of some sports or the practice of physical exercise, and probably is the reason why the authors decide on using this use case to test their system. In a lot of sports, there are sequences in which some “body configurations” are repeated in a cyclic way, such as in the case of rowing or running. In these cases, using a method similar to the one introduced in that paper could improve the performance of the system, as well as serve as a tool that can make easier the process of human labeling of body parts.In addition, we can see a very interesting method to reduce the needed amount of estimations or manual interactions when constructing a dataset in the paper . This coThe paper  obtainedAnother aspect to be highlighted is the focus of most of the systems in obtaining a higher accuracy or lower error, while there are few systems that take into account other aspects such as the lightness of the speed of the system, such as . We thinapplicability and possibilities of HPE in sport are just at the early stages, there are still several sports and applications to test and systems to be developed. The number of sports in which HPE has not been applied, or has been barely applied, is huge, and, as previously explained, the development focused on different aspects than accuracy or low error, such as the speed or the lightness of a system, the specialized setup to a concrete problem, or the use of low-cost hardware, could be a great opportunity to study.In terms of results obtained by each paper, it can be said that the use of HPE in sports and exercise activities is very beneficial, as, apart from the biomechanical aspects of the body by the pose estimation itself, different parameters and value information can be generated for the athlete, as well as for the coaches and other sports experts. The problems faced by different authors when applying HPE to specific sports or movements during physical exercise, apart from the interest in getting a higher accuracy in terms of low error regarding the prediction of the position of the joints, implementing methods to avoid the problems generated by occlusions could be an interesting branch of the field to research and develop. For example, in [Taking into account the mple, in , in whicmple, in , that trfuture, there are interesting paths to be explored and methods to be exploited, such as the use of GANs and synthetic datasets as a way of increasing the available data to train and test systems. As an example, there are works such as [Looking at the  such as , in whic such as . Being a


We further divided the patients into those who continued the CR program (continued group) and those who did not (discontinued group) in the HFpEF and non-HFpEF groups. The clinical outcomes at 5 months were compared among the groups. Results: There were no significant differences in patient characteristics at baseline between the continued and discontinued groups in the HFpEF and non-HFpEF groups except for % diabetes mellitus in the non-HFpEF group. The rates of all-cause death and hospital admissions in the continued group in both the HFpEF and non-HFpEF groups were significantly lower than those in the discontinued group. The all-cause death and hospital admissions in each group were independently associated with the continuation of the CR program. Conclusions: The continuation of a 5-month CR program was associated with the prevention of all-cause death and hospital admissions in both the HFpEF and non-HFpEF groups.Background: Cardiac rehabilitation (CR) is a requisite component of care for patients with heart failure (HF). We aimed to evaluate the clinical outcomes in outpatients with HF with preserved ejection fraction (HFpEF) compared to those in patients with non-HFpEF who did and did not continue a 5-month CR program. Methods: 173 outpatients with HF who participated in a 5-month CR program were registered. We divided them into two groups: HFpEF ( Cardiac rehabilitation (CR) is a requisite component of care for patients with heart failure (HF) and a class A recommendation in several guidelines ,2. CR imWe have studied CR for more than eight years and reported some beneficial effects in patients with cardiovascular diseases (CVD) ,15,16,17It is confirmed and clearly evidenced that CR is associated with the prognosis of HFrEF patients, whereas the evidence in HFpEF patients is relatively weak. Recently, it has been reported that CR improves the exercise capacity and QOL of HFpEF patients ,19,20, an = 84, HFpEF group) and <50% LVEF . In addition, we further divided the patients into those who continued the 5-month CR program (continued group) and those who did not (discontinued group). The clinical outcomes were compared between the groups for up to 5 months. The primary endpoint was all-cause death and hospital admission. This study was approved by the ethics committee of Fukuoka University Hospital.This single-center retrospective cohort study evaluated the efficacy of CR in HFpEF and non-HFpEF patients. One hundred and seventy-three outpatients who had HF and participated in a 5-month CR program at Fukuoka University Hospital were enrolled from 2011 to 2019. We divided the patients into two groups according to LVEF at the beginning of the CR program: ≥50% LVEF  using Cpex1  and a stress test system with an ML9000 electrocardiogram . The CR program was the same as in our previous report . In briePatient characteristics, including comorbidities, medications, LVEF and plasma BNP, were assessed at baseline. Patients with low-density lipoprotein cholesterol ≥140 mg/dL, triglyceride ≥150 mg/dL or high-density lipoprotein cholesterol <40 mg/dL and lipid-lowering therapy were diagnosed with dyslipidemia (DL). Patients with systolic and/or diastolic blood pressure (SBP/DBP) ≥140/90 mmHg or who were under antihypertensive treatment were considered to have HTN. Patients who were being treated for diabetes mellitus (DM) or who had symptoms of DM and a hemoglobin A1c ≥6.5% and/or a fasting glucose concentration ≥126 mg/dL were considered to have DM. Otherwise, the results of a 75 g oral glucose tolerance test were used to diagnose DM. Coronary artery disease (CAD) was defined as lumen diameter stenosis >50% in at least one major coronary artery as determined by coronary angiography and as diagnosed by anterior myocardial infarctions. Medications included angiotensin converting enzyme inhibitor (ACE-I)/angiotensin II receptor blockers (ARB), β-blockers, diuretics, calcium channel blockers (CCBs) and statins. LVEF obtained by the modified Simpson’s method was analyzed by a Vivid E9 echocardiogram . BNP was analyzed via enzymatic methods in the clinical laboratory of Fukuoka University Hospital.p < 0.05 was considered significant.All of the data analyses were performed using the SAS  Software Package  at Fukuoka University . Continuous variables with a normal distribution are expressed as mean ± standard deviation, and differences between groups were compared using a Student’s t-test. Differences in categorical variables between groups were compared by chi-square analysis. To identify the factors associated with all-cause death and hospital admission, we performed a Cox regression analysis and obtained hazard ratios. Age, gender, BMI, CAD and medications were also subjected to a multivariate analysis to identify independent factors related to all-cause death and hospital admission. A Kaplan–Meier analysis (log-rank test) was applied to verify the time-dependent occurrence of clinical outcomes in groups stratified according to whether they did, or did not, complete a 5-month CR program. A value of p = 0.001). Although there was no difference in comorbidities except for CAD between the groups, the patients in the HFpEF group had less drug interventions, except for statins, than those in the non-HFpEF group . The BNP at baseline in all the patients was 390 ± 494.9 pg/mL, and that in the HFpEF group was significantly lower than that in the non-HFpEF group . There was no significant difference in the AT peak VO2 between the groups.The patient characteristics at baseline are shown in p = 0.65). In addition, all-cause death and hospital admissions occurred in 16 patients (19.0%) in the HFpEF group and 19 patients (21.3%) in the non-HFpEF group. There was no significant difference in all-cause death and hospital admissions between the groups (p = 0.85).The continuation of 5 months of CR and all-cause death and hospital admissions in all the patients and in the HFpEF and non-HFpEF groups are shown in The patient characteristics at baseline in the continued and discontinued groups in all patients and in the HFpEF and non-HFpEF groups are shown in The mean follow-up periods were 136 ± 33 days in all the patients. During follow-up, there were 35 composite outcomes, including 3 all-cause mortalities (1.7%) and 32 hospital admissions (18.5%).p = 0.0003). The Kaplan–Meier curves for patients in the HFpEF and non-HFpEF groups are shown in p = 0.0084; non-HFpEF group: p = 0.0126).p = 0.0007; HFpEF patients: p = 0.02; non-HFpEF patients: p = 0.02) and the use of diuretics in all the patients (p = 0.04).Regarding the relationships between various parameters, all-cause death and hospital admissions , signifip = 0.0002; HFpEF patients: p = 0.02; non-HFpEF patients: p = 0.046) and diuretics in all the patients (p = 0.03).In The continuation of a 5-month CR program was associated with the prevention of all-cause death and hospital admissions in both the HFpEF and non-HFpEF groups. While it is clearly important to introduce CR, these results suggest that it is also important to continue CR in HF patients, including HFpEF patients.To date, no pharmacological intervention has been demonstrated to improve the prognosis of patients with HFpEF. Recently, it has been suggested that CR may improve the prognosis of these cases . HoweverCR has been reported to reduce peripheral vascular resistance , improveThe discontinuation of a 5-month CR program was significantly associated with the presence of DM in all the patients and non-HFpEF patients. However, all-cause death and hospital admissions were not associated with the presence of DM. It was unclear why the CR continuation rate of DM patients was low, but an increase in this rate may lead to an improved prognosis. DM patients frequently discontinue their pharmacological treatment; in a previous study, 12% dropped out after the initial visit to the hospital and 33% of the residual cohort dropped out during each subsequent 6-month period . Multifap = 0.65). All-cause death and hospital admissions occurred in 16 patients (19.0%) in the HFpEF group and 19 patients (21.3%) in the non-HFpEF group. There were no significant differences in all-cause death and hospital admissions between the groups (p = 0.85). A previous study reported that patients with HFpEF and non-HFpEF had nearly identical prognoses [There was no significant difference in the rate of continuation between the HFpEF and non-HFpEF groups p = 0.5. All-can = 15), the lowering of motivation (n = 15), problems with access to the hospital (n = 8), being busy with work (n = 4), frailty (n = 3), changing to home rehabilitation (n = 2), self-will (n = 2) and others (n = 3). Thus, 33 patients had unknown reasons for discontinuation. It is undeniable that some patients may be too frail or vulnerable to continue CR, and a worse outcome may result from their patient baseline. Therefore, a large-scale long-term study should be performed to confirm these results.This study has several limitations. First, this was a retrospective study from a single center with a relatively small sample size. Second, we did not perform long-term follow-ups. Third, the patients received different kinds and doses of medications. Fourth, there were many patients whose reasons for CR discontinuation were unknown. Among 85 patients with CR discontinuation, the reasons for discontinuation of CR were the onset of non-cardiac diseases without hospitalization (In this study, the continuation of a 5-month CR program was associated with the prevention of all-cause death and hospital admissions in both HFpEF patients and non-HFpEF patients.


Heart failure with preserved ejection fraction (HFpEF) is a growing public health concern, with rising incidence alongside high morbidity and mortality. However, the pathophysiology of HFpEF is not yet fully understood. The association between HFpEF and the metabolic syndrome (MetS) suggests that dysregulated lipid metabolism could drive diastolic dysfunction and subsequent HFpEF. Herein we summarise recent advances regarding the pathogenesis of HFpEF in the context of MetS, with a focus on impaired lipid handling, myocardial lipid accumulation and subsequent lipotoxicity. Across the globe, the burden of obesity is increasing at an alarming rate. Obesity rates have almost tripled since 1975, accompanied by an ever-increasing incidence of the metabolic syndrome (MetS) , that isHFpEF is a complex clinical condition in which the myocardium cannot relax sufficiently during diastole to adequately fill with blood. As a result, cardiac output is reduced, reducing perfusion of peripheral respiring tissues and thereby generating debilitating symptoms such as fatigue, exercise intolerance and dyspnoea. This trajectory is in contrast with the perhaps more well-known – and certainly better understood – form of heart failure, heart failure with reduced ejection fraction (HFrEF), in which cardiac output is reduced due to impaired myocardial contractile function during systole, most commonly secondary to myocardial damage following myocardial infarction.Two components broadly determine diastole and, therefore, the propensity to generate diastolic dysfunction and subsequent HFpEF. The first is the ability of the left ventricle (LV) to relax, governed by the dissociation of myofilaments which is largely dependent on cytosolic calcium dynamics. The second is the passive compliance of the LV itself, governed primarily by ventricular wall thickness, the structure of the extracellular matrix (ECM) and the particular isoform and post-translational modifications of the cardiomyocytic protein, titin. We will discuss each of these in turn, before addressing how they may be elicited by altered myocardial lipid homeostasis.2+) release into, and reuptake from, the cardiomyocytic cytoplasm. This sequence relies on continual cycles of activation and deactivation of multiple calcium channels, such as the sarcoplasmic reticular Ca2+ channel (SERCA2a), the plasmalemmal sodium-calcium exchanger (NCX) and the ryanodine receptor (RyR). However, diastolic dysfunction in HFpEF is associated with impaired calcium handling. A reduction in SERCA2a function is observed in HFpEF, reducing the rate of diastolic Ca2+ reuptake and resulting in a state of cytoplasmic Ca2+ overload during diastole [2+ levels cause a persistent increase in actin-myosin crossbridge activation, thereby increasing resting diastolic tension and resulting in impaired cardiac filling, which characterises diastolic dysfunction [in vitro and in vivo by adenoviral and lentiviral gene transfer of SERCA2a, respectively [Normal cardiac inotropy and lusitropy are governed by a tightly regulated cycle of calcium  of the myocardium is enhanced in HFpEF patients relative to controls ,17. In cWithin the I-band of striated muscle sarcomeres, myosin molecules are held in place by a giant protein called titin . As a liHeart failure as a whole affects approximately 0.83% of the global population; in the UK alone, more than 920,000 people are estimated to be living with heart failure, with 200,000 new diagnoses made each year ,27. Of tThis difficulty in identifying drug targets for HFpEF is extremely problematic. Despite multiple trials, there are no available pharmacological agents that significantly impact outcomes in HFpEF. This presents many challenges. Studies have shown that each ambulatory HFpEF patient costs €1118 per year on average in direct healthcare expenditure in high-income countries, with each day in hospital costing $2411 ,33. ThisThe pathogenic mechanisms underlying HFpEF are not well characterised. The traditional theory posits that HFpEF occurs as due to pressure overload: systemic hypertension increases LV afterload, leading to LVH and subsequent diastolic dysfunction . HoweverThe most credited hypothesis of HFpEF pathogenesis involves coronary microvascular dysfunction (CMD) and reduced nitric oxide (NO) bioavailability. The theory proposes that the high comorbidity burden of HFpEF triggers a systemic pro-inflammatory state that impairs the physiology of the coronary endothelium, activating complex molecular pathways that converge to generate myocardial stiffening and fibrosis, thereby causing diastolic dysfunction . Severalin vitro and in vivo models of HFpEF in which augmenting the cGMP-PKG pathway attenuates or prevents cardiomyocyte hypertrophy, interstitial fibrosis and diastolic stiffness [This hypothesis posits that CMD results in a reduction in NO bioavailability, which subsequently drives diastolic dysfunction and HFpEF. Numerous studies support this. The NO-dependent vasodilator response is impaired in the coronary microvasculature of HFpEF patients, associated with diastolic dysfunction, whilst coronary infusions of NO donors in humans acutely lowers diastolic stiffness ,48. Furttiffness ,53,54.The aforementioned CMD paradigm of HFpEF pathogenesis hypothesises that multimorbidity induces systemic inflammation, which can in turn drive diastolic dysfunction. Given that many of the comorbidities that accompany HFpEF are associated with low-grade chronic inflammation, and that the presence of inflammatory markers is associated with CMD in a number of patient cohorts, this model appears reasonable . InflammHowever, there is reason to believe that these observations are associative, and do not necessarily point to causation. While serum pentraxin-3 levels are increased in HFpEF patients, levels are highest at the coronary sinus, suggestive of its production by the coronary circulation itself, thereby suggesting that this inflammatory marker could be a consequence of dysfunction instead of a cause . Serum IOne key point to consider when searching for ‘the driving factor’ of HFpEF is that there is a high likelihood that there is no single mechanism that underlies its pathogenesis due to the aetiological and phenotypic heterogeneity of the condition. This is supported by the fact that just over 25% of HFpEF patients have no clinical signs of CMD, suggesting that CMD may not be required for the pathogenesis of HFpEF ,46. The In the particular case of the HFpEF phenogroup affected by MetS, we must consider that, whilst being a condition associated with systemic inflammation, MetS is also a condition associated with significant dysregulation in whole-body lipid metabolism. During overnutrition, adipose tissue depots expand to store excess energy. However, once the maximum capacity of adipose tissue expansion is reached, lipids ‘spillover’ into the circulation. This results in changes in both the quantity and quality of serum lipids, leading to enhanced lipid uptake by non-adipose organs, and ectopic lipid deposition. These ectopic lipids may then induce organ dysfunction through lipotoxicity. Lipotoxicity is the process by which lipid accumulation in non-adipose organs results in oxidative stress, mitochondrial dysfunction and apoptosis, leading to cellular and tissue dysfunction. This ‘lipid spillover’ from overwhelmed adipose tissue and subsequent lipotoxicity is proposed to be the mechanism underlying the pathogenesis of skeletal muscle insulin resistance, pancreatic beta-cell dysfunction and non-alcoholic fatty liver disease during MetS . HoweverThe heart is a metabolically demanding organ. In order to sustain continuous cardiac contraction, it requires 0.5 μmol/g/s of ATP, over 95% of which is obtained from oxidative phosphorylation . Given tIn order to be used to generate ATP in the heart, FAs can passively transfer across the cardiomyocytic plasma membrane, but their uptake is supported by both the FA translocase (CD36) and FA binding protein (FABP) . In the Studies looking at substrate utilisation in the failing heart are often inconsistent. Whilst data regarding metabolism during systolic dysfunction is extensive, the data on myocardial metabolism during diastolic dysfunction are relatively minimal. Data suggest that both types of dysfunction are characterised by reduced mitochondrial oxidative metabolism, resulting in reduced ATP production, which is compensated for to some extent by increasing glycolysis . During Increased FAO in the context of MetS-associated HFpEF likely occurs due to enhanced substrate availability. Circulating free fatty acids (FFAs) and TG-rich very low-density lipoproteins (VLDL) are increased in MetS due to the aforementioned ‘lipid spillover’ from overwhelmed adipose tissue, increasing their availability for uptake by the heart ,83. SeruDespite this upregulation of FAO, evidence suggests that FAO is often insufficient to prevent myocardial TG accumulation in HFpEF. In a study using CMR to assess cardiac lipids, HFpEF patients had 2.3-fold higher myocardial lipid content than control subjects which was independently associated with diastolic strain rate . SimilarAs demonstrated by the studies listed above, HFpEF is associated with myocardial steatosis. Given that ectopic lipid accumulation in non-adipose organs is known to trigger organ dysfunction through lipotoxicity, it is plausible that myocardial steatosis may, at least in part, mediate diastolic dysfunction in this context.Several clinical studies have suggested that lipid accumulation in the heart is associated with subsequent cardiac morphological changes and diastolic dysfunction. For example, patients with congenital lipodystrophy display significant lipid accumulation in the heart in the absence of obesity, and often go on to develop hypertrophic cardiomyopathy . In otheIn obese mice generated both genetically and using high-fat diet, an increase in myocardial lipid content is observed in concert with diastolic dysfunction and oxidative stress, whilst prediabetic mice exhibit diastolic dysfunction and cardiac hypertrophy in association with early changes in mitophagy and consequent cardiac lipid accumulation . These sInhibition of FAO using whole-body CPT-1β-knockout mice induces myocardial lipid accumulation and exacerbates pressure overload-induced cardiac hypertrophy . When FAGlobal genetic inactivation of adipose triglyceride lipase (ATGL) results in lipid accumulation in the heart due to a reduction in lipolytic activity, leading to LVH, myocardial fibrosis and dysfunction, and premature death . This dyGSK3α overexpression in the heart enhances myocardial FA uptake and thereby induces lipid accumulation. This results in lipotoxic cardiomyopathy, as demonstrated by enhanced fibrosis, hypertrophy and increased deceleration time . SimilarThe evidence presented above suggests that myocardial lipid deposition is detrimental to cardiac morphology and diastolic function, regardless of the mechanism by which the lipid accumulation occurs. Whilst the data are convincing, evidence to the contrary must also be considered. Perhaps the most obvious contradiction to this lipotoxicity hypothesis is the paradox that exists in relation to HFpEF, in which one’s risk of developing HFpEF is increased in obesity, but one's prognosis following diagnosis is improved . As obesBscl2−/− lipodystrophic mouse model have demonstrated a reduction in myocardial lipid content in these animals [Bscl2−/− animals resulting in glucotoxicity, and that preventing this through administration of the SGLT2 inhibitor dapagliflozin reverses the HFpEF phenotype [per se, but instead glucose homeostasis. However, these studies additionally highlight the importance of considering the potential effects that altered lipid homeostasis can have on cardiac metabolism as a whole when analysing data regarding myocardial lipid overload.Further contradictory evidence comes from preclinical studies. Recent studies of the  animals  alongsid animals . The add animals . Howeverhenotype , this surEF, and are not usually associated with HFpEF. Given that lipid handling in HFrEF is distinct from that observed in HFpEF - for example, FAO is reduced in HFrEF - myocardial lipids likely have a different effect on the progression of HFrEF relative to HFpEF, thus this model may not be a good indicator of the role of lipids in HFpEF specifically. Together, whilst these studies suggest that we cannot state for certain that lipid accumulation is a driving factor of diastolic dysfunction, they provide insufficient contradictory evidence to rule out the role of lipids in the pathogenesis of HFpEF.It has additionally been found that CPT-I inhibition by oxfenicine combined with a high-fat diet induces mild myocardial lipid accumulation but is not associated with LVH or changes in cardiac function . HoweverTogether, the data outlined above demonstrate that increasing myocardial lipid storage is associated with diastolic dysfunction, whilst preventing it is sufficient to prevent functional impairments, indicating that myocardial lipotoxicity may be pivotal in the pathogenesis of HFpEF. However, it may not be TGs themselves that cause the problem. Generally, it is thought that TGs are relatively inert, thus do not mediate lipotoxicity themselves, but rather it is the accumulation of reactive lipid intermediates such as diacylglycerols (DAG), ceramides and acylcarnitines that is responsible.per se that mediates lipotoxic cardiomyopathy, but in fact the presence of intermediary toxic lipid species. However, the relative importance of each intermediate in triggering or worsening diastolic dysfunction remains to be established.Several studies support this concept . SignifiThere are numerous pathways by which lipid intermediates can elicit deleterious effects in cardiomyocytes that lie outside the scope of this review but have been excellently reviewed elsewhere . HoweverMyocardial steatosis is known to enhance ROS production: multiple models of cardiac lipid accumulation – such as ATGL deficiency, palmitate treatment, overexpression of ceramide synthase and genetic models of obesity and diabetes – all result in increased ROS production ,123,75. 2+ uptake, and increases diastolic cytosolic Ca2+, all of which can contribute to calcium mishandling in HFpEF [Once produced, ROS can affect myocardial function in a number of ways . ROS canin HFpEF . ROS arein HFpEF . This isin HFpEF . Furtherin HFpEF ,129.ROS can also potentiate lipid intermediate-induced PKC activation due to the redox-sensitivity of PKCs . In turnMitochondrial dysfunction is widely observed in heart failure, as it is in studies of cardiac lipotoxicity . In ATGLin vitro, suggesting that ROS can damage mitochondria themselves [It may be that the ROS produced by excess lipid intermediates are responsible for mitochondrial damage and dysfunction in this context. Reducing lipid-induced ROS production by inhibiting NOX2 prevents mitochondrial dysfunction in cardiomyocytes treated with palmitate emselves . This maemselves . This isemselves . The mitemselves . Howeveremselves .2+ channels, increasing non-contractile ATP hydrolysis due to the need to actively maintain Ca2+ homeostasis [Mitochondrial dysfunction could be responsible for wider myocardial dysfunction in two key ways . First, eostasis ,147. Togeostasis .The weight of the evidence supporting the current paradigm of HFpEF pathogenesis – that systemic inflammation induces CMD, which reduces NO bioavailability and induces diastolic dysfunction – cannot be ignored. However, when combined with the evidence presented on the contribution of lipotoxicity to the pathogenesis of cardiac dysfunction, we must ask ourselves whether the two paradigms may be linked, particularly given that myocardial steatosis has been shown to be associated with CMD . In the in vivo, in vitro and clinical studies have all shown that elevated FFAs reduce NO bioavailability in ECs [Conditions of high circulating FFAs are associated with endothelial dysfunction . TG-enriy in ECs .de novo synthesis of DAGs and ceramides in ECs, both of which activate PKC and thereby inhibit eNOS signalling [The mechanisms by which lipids reduce NO bioavailability in ECs are varied. Excess lipids can significantly increase endothelial ROS production, which can then react with NO to form peroxynitrite, depleting NO supply . ROS cangnalling . Excess gnalling . These sin vitro models to investigate the particular lipid species that exert cytotoxic effects, and the precise cellular mechanisms underlying this dysfunction, with a focus on oxidative stress and subsequent mitochondrial dysfunction. Further studies will also be required to establish the interplay between lipids and inflammatory mediators in this context. In light of this, future therapeutic strategies should seek to improve cardiomyocyte lipid handling as a method by which to prevent or ameliorate HFpEF, particularly in the context of the MetS phenogroup. This may include strategies to enhance lipid use, to limit myocardial lipid uptake, or to ensure that lipid is stored as ‘inert’ species. Many previous studies have not shown great promise for these strategies, but this is likely due to a lack of focus on this particular form and aetiology of heart failure. As such, we must first focus on defining the hallmarks of the MetS phenogroup of HFpEF patients and strive to generate murine models that accurately mimic the metabolic and cardiovascular phenotype observed in this condition. Without this, we run the risk of discounting potential therapeutics due to their lack of efficacy in other phenogroups, thereby delaying the identification of much-needed treatments for patients suffering from MetS-associated HFpEF.Whilst the mechanisms underlying the pathogenesis of HFpEF remain contentious, impaired lipid handling and subsequent lipotoxicity in both cardiomyocytes and coronary ECs play a key role in mediating diastolic dysfunction. It is likely that these processes drive the CMD and reduced NO bioavailability described in the current paradigm, particularly in the context of MetS, alongside exerting myriad detrimental effects on cardiomyocytes themselves. Whether lipids drive this phenotype independently of, or in concert with, systemic inflammation remains to be established, but these data demonstrate that lipids must be considered as key players in the pathogenesis of HFpEF. Efforts must now be made using


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Heart failure with preserved ejection fraction (HFpEF) is an emerging disease with signs of nonresolving inflammation, endothelial dysfunction, and multiorgan defects. Moreover, based on the clinical signs and symptoms and the rise of the obesity epidemic, the number of patients developing HFpEF is increasing. From recent molecular and cellular studies, it becomes evident that HFpEF is not a single and homogenous disease but a cluster of heterogeneous pathophysiology with aging at the base of the pyramid. Obesity superimposed on aging drives the number of inflammatory pathways that intersect with metabolic dysfunction and suboptimal inflammation. Here, we compiled information on obesity-directed macrophage dysfunction that coincide with metabolic defects. Obesity-associated proinflammatory stimuli facilitates heart and interorgan inflammation in HFpEF. Furthermore, diversified mechanisms that drive heart failure urge the need of studying pervasive and unresolved inflammation in animal models to understand HFpEF. A broad and system-based approach will help to study major translational aspects of HFpEF, since no single animal model recapitulates all signs of differential HFpEF stages in the clinical setting. Here, we covered experimental models that target HFpEF and emphasized the advances observed with formyl peptide 2 (FPR2) receptor, a prime sensor that is important in inflammation-resolution signaling. Dysfunction of FPR2 led to the development of spontaneous obesity, impaired macrophage function, and triggered kidney fibrosis, providing evidence of multiorgan defects in HFpEF in an obesogenic aging experimental model. Obesity serves as an incubator for many cardiometabolic and cardiorenal defects. Hypertension, insulin resistance, diabetes, and dysplasia are major metabolic diseases that are strongly linked to obesity. The prevalence of metabolic defects is exponentially rising parallel to the trend of obesity epidemic . EpidemiIn this minireview, first, we highlight inflammation-mediated pathogenesis in the emerging heart failure with preserved ejection fraction (HFpEF) syndrome. Second, we cover the concept of non-resolving and multiorgan chronic inflammation with an updated list of experimental animal models of HFpEF syndrome.In the last five decades, epidemiological and systemic research helped in clarifying that obesity is closely associated with multiple changes in the structure and function of the heart of obese individuals. Clinicians and scientists described HF as a pathological remodeling of left ventricle (LV) cardiomyocytes. This remodeling is a result of heart adaptation to blood hemodynamics along with the increase in fat mass accumulation. With the advances in ultrasound and magnetic resonance imaging techniques, a clear evolution of LV shape remodeling was observed ranging from one-dimensional view to multidimensional subtypes of HF with specific nomenclature that reflects the corresponding remodeling . FurtherFrom the one-dimensional perspective, HF is classified into three types based on geometry metamorphosis of the LV: (1) atrophy of the heart (contractile dysfunction), (2) concentric hypertrophy of the LV , and 3) eccentric hypertrophy of the LV  or ischemia-induced wall thinning. However, some rare cases of cardiac angiosarcoma can also lead to HF  eccentri. This reAtrophy of the aging heart is a consequence of sarcopenic heart remodeling following muscle wasting. In the elderly, the size of a tissue or organ decreases due to cellular shrinkage . The preCardiac atrophy can occur not only in pathological conditions  but alsoEnlargement of the left ventricle (LV) is an adaptive process that evolves into maladaptive remodeling, which has long been recognized as one of the prime dysfunction mechanisms leading to HF. The heart is an extremely plastic organ and changes its geometry to compensate for either pressure or volume overload, normally resulting from exercise or obesity-related mechanical impact. This compensation has often been viewed as a feedback loop . ConcentEven though LV geometry is at the center of heart remodeling in HF, the LV EF is taking over on clinical classification of HFrEF or HFpEF . Both foTechnically, if the EF is preserved, evidence of altered cardiac structure and function should be sought to provide further objective evidence toward HF syndrome. At the functional level, Doppler echocardiographic evidence of diastolic dysfunction is appearing as a digital biopsy. This is reflected in echocardiography by slow ventricular relaxation and increased diastolic stiffness or elevated left atrial pressure, which is common in HFpEF  with mulIn the USA, more than 50% of HF patients have HFpEF with primary signs of obesity and heterogeneous metabolic syndrome  , 47. In HFrEF and HFpEF are end-stage disease pathologies with many confounding and overarching metabolic defects, thus, termed here as heart failure syndrome rather than disease. The pathophysiology of HFpEF is multifaceted signatures and heterogeneous, complex, and progressive. The increasing prevalence of HFpEF patients with aging and obesity defines a burden on healthcare systems . In the In response to an ischemic event, unresolved inflammation after cardiac injury is one of the common causal contributors in HFrEF . In the The other side of HFpEF is systemic inflammation and is an inherent phenotype in HFpEF patients. In clinical trials, in a group of patients with HF, it was confirmed that TNFR 2 plasma levels were significantly associated with the degree of diastolic dysfunction in patients with HFpEF but not HFrEF , 69. BesHFrEF patients are prone to pathogen-directed systemic inflammation like sepsis . There ain vivo studies have shown that increasing plasma FFA levels activate NF-κB in human skeletal muscle, which leads to an increased expression of proinflammatory cytokines and elevated circulating levels of MCP-1  elicited an antihypertensive effect correlated with improved endothelial function, as indicated by an enhanced vasodilatory response to acetylcholine in isolated aortic rings , sleep–wake up cycle (circadian rhythm), and physical activity (exercise/sedentary lifestyle) are key determinants of total health and specifically for cardiovascular health . Recent GH conceptualized the outline, edited the multiple drafts, prepared/edited the figures, and approved for submission. BT prepared the first draft and re-edited after the input from GH. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.