The motivation is straightforward. Implantable sensors that monitor organs continuously are increasingly seen as a way to catch disease before symptoms appear, but the devices that could enable such monitoring face a fundamental materials problem. Conventional magnetic implants rely on metals such as iron, cobalt or nickel, which raise concerns about long-term toxicity, corrosion, interference with magnetic resonance imaging, and the need for a second surgery to remove them. Metal-free molecular magnets, by contrast, promise biocompatibility and resorbability, yet until now they have lacked the ferromagnetic strength needed for high-fidelity sensing at clinically relevant tissue depths.

The key to the new material lies in a chemical transformation called de-nitrogenation. By removing nitrogen atoms from the graphitic carbon nitride framework, the researchers create unpaired electron spin centres that become coupled through a reconstructed network of alternating pi and sigma conjugated bonds. This coupling confers robust spontaneous magnetization, meaning the material is ferromagnetic at room temperature without any external field, and that magnetization remains stable under physiological conditions. The authors verified the origin of the ferromagnetism theoretically, using first-principles calculations including crystal orbital Hamilton population analysis, and confirmed experimentally that the magnetism is strong enough to produce visible, macroscopic magnetic responses in bulk powder form.

To turn the material into a practical medical platform, the team embedded it in two well-established biodegradable polymers: poly(lactic-co-glycolic acid), or PLGA, and silk fibroin, the protein that gives silk its strength. The resulting composites can be fabricated as flexible epicardial patches that are foldable for catheter delivery. Supplementary videos accompanying the paper show a pre-folded, rose-petal-shaped patch held in a sheath mimicking a catheter lumen; when the sheath retracts, the patch blooms open within seconds, unfolding radially to enlarge its contact area against tissue. This bloomable design allows minimally invasive deployment and conformal attachment to organ surfaces without sutures.

The sensing architecture works in pairs. The internal implant, driven by the mechanical deformation of the organ it sits on, generates a time-varying magnetic flux that passes through the closed chest wall. Outside the body, a skin-interfaced array of Hall-effect sensors captures that flux and converts it into continuous readouts of organ motion. The signals are transmitted wirelessly to a smartphone-linked reader and a cloud-based analytics platform. Because the approach relies on magnetic coupling rather than acoustic, optical or electrical transduction, it requires no coupling gel, no vascular access and no optical alignment, and the authors report that it is robust against motion artifacts and variations in tissue impedance.

The team tested the system in porcine models, the standard large-animal platform for cardiovascular research. Epicardial patches deployed on the heart enabled continuous, untethered monitoring of myocardial dynamics over four weeks, during which the researchers tracked ejection fraction, a key clinical measure of how much blood the heart pumps with each beat. When benchmarked against standard-of-care echocardiography, the magnetic sensing approach delivered trajectories of clinical grade, suggesting it could support longitudinal physiological monitoring outside hospital infrastructure. Cardiac magnetic resonance imaging at day 28 confirmed that the patch remained conformally attached to the epicardium throughout repeated cycles of systolic contraction and diastolic relaxation, without detachment or migration.

Beyond the heart, the researchers showed that the material can be dispersed into injectable hydrogels for organ-scale sensing. Under ultrasound guidance, a BioMFM-integrated sodium alginate hydrogel was injected percutaneously onto the surface of a porcine liver, where the bolus appeared as a distinct hyperechoic region against the liver parenchyma, allowing precise minimally invasive placement. The hydrogel preserved the shear-thinning behaviour needed to flow through narrow-gauge clinical syringes even at loadings up to ten percent by weight, extruding smoothly without clogging. In the liver experiments, the magnetic markers enabled three-dimensional reconstruction of localized hepatic pathologies, pointing toward a future in which injected tracers map disease geometry inside solid organs.

What happens after the monitoring period is arguably the most distinctive feature. The material is designed to bioresorb, degrading benignly once its sensing mission is complete, which eliminates the retrieval surgery that metallic implants require and avoids the chronic foreign-body burden of permanent devices. The authors frame this as part of a broader degradation-by-design strategy in two-dimensional materials, in which chemical functionalization is used to tune biodegradability and safety. In the porcine studies, four weeks of continuous cardiac assessment were followed by benign bioresorption, closing the loop between function and disappearance.

The theoretical foundation of the work draws on a decade of research into metal-free magnetism in carbon nitride. Earlier studies predicted intrinsic half-metallicity and defect-related ferromagnetism in graphitic carbon nitride nanosheets, and recent work achieved strong ferromagnetism through atomic manipulation. The new study extends this line by engineering a molecular magnet whose spontaneous magnetization survives integration into polymer composites and physiological environments, a step that earlier radical-based organic magnets had not reached at clinically useful strength. The authors also employed machine-learning tools from cheminformatics, including ChemBERTa-style pretrained models, in their analysis workflow, and released their analysis code, firmware for an ESP32-S3 microcontroller and installation instructions on GitHub.

The clinical implications reach beyond cardiology. Acute heart failure and post-discharge follow-up after acute coronary syndrome remain areas where continuous, infrastructure-independent monitoring could change outcomes, and existing tools such as pulmonary artery catheters and periodic echocardiography offer only snapshots or require invasive access. A resorbable magnetic patch that reports ejection fraction continuously, read through the skin by a wearable sensor array, could in principle bring intensive-care-grade hemodynamic tracking to ordinary wards or even to patients at home. The injectable hydrogel variant extends the same logic to the liver, where elastography-based stiffness measurements are currently the dominant non-invasive tool but offer limited spatial resolution. The researchers caution that the work is at the large-animal stage, and human translation will require further safety and accuracy studies. Still, the demonstration that a metal-free, fully resorbable molecular magnet can deliver clinical-grade physiological trajectories over weeks marks a notable convergence of molecular magnetism, biodegradable electronics and wireless sensing, and suggests that the next generation of implantable diagnostics may be designed to vanish rather than endure.

Subject of Research: A bioresorbable metal-free molecular magnet for wireless deep-tissue and cardiac monitoring

Article Title: Bioresorbable metal-free molecular magnets enable untethered organ monitoring

Article References: Wu, Y., Yue, Z., Xing, S., Yang, D., Wang, J., Liu, Y., Cohen, H., Liu, L., Jiao, Q., Li, Z., Ali, H., Perera, C., Vahl, T. P., Ranard, L. S., Zhang, Z., Einstein, A. J., Zhang, A., Dashnaw, S., Huang, Y., … Bai, W. (2026). Bioresorbable metal-free molecular magnets enable untethered organ monitoring. Nature Materials. https://doi.org/10.1038/s41563-026-02759-4

Image Credits: AI Generated

DOI: 10.1038/s41563-026-02759-4

Keywords: molecular magnets, graphitic carbon nitride, bioresorbable materials, cardiac monitoring, implantable sensors, Hall effect sensing, ferromagnetism, PLGA, silk fibroin, injectable hydrogels, ejection fraction, Nature Materials

The therapy under scrutiny is Qili Qiangxin Capsule, a Chinese patent medicine that has been widely prescribed in China as an add-on treatment for heart failure. The review, conducted by researchers from Beijing University of Chinese Medicine, Shandong University of Traditional Chinese Medicine and collaborating institutions, focused specifically on patients whose heart failure developed after an acute myocardial infarction, a high-risk population in which roughly a quarter of patients with ST-segment elevation myocardial infarction go on to develop heart failure.

Heart failure following a heart attack remains a major cause of illness and death despite advances in conventional therapy. Epidemiological data cited in the review indicate that the rehospitalisation rate due to heart failure after myocardial infarction reaches 16.7 percent, and the risks of ventricular remodelling, recurrent hospitalisation and adverse cardiovascular events remain high even with guideline-directed medical therapy, coronary revascularisation and device-based interventions.

The researchers searched seven databases from their inception to January 2026 and included only randomised controlled trials comparing Qili Qiangxin plus conventional Western medicine against the same Western medicine alone. The primary outcome was N-terminal pro-B-type natriuretic peptide, or NT-proBNP, a widely used biomarker of heart failure severity and treatment response. Secondary outcomes spanned left ventricular ejection fraction, cardiac chamber dimensions, B-type natriuretic peptide, high-sensitivity C-reactive protein, quality of life, clinical response rate, all-cause mortality, heart failure-related hospitalisation and adverse events.

The pooled results suggested meaningful short-term gains. Compared with Western medicine alone, the combination therapy was associated with greater reductions in NT-proBNP, BNP, left ventricular end-diastolic diameter, left ventricular end-systolic diameter and hs-CRP, along with improvements in ejection fraction, quality of life and clinical response rate. Ejection fraction, a key measure of the heart’s pumping capacity, improved by an average of 6.04 percentage points in the combined-therapy group. No statistically significant differences emerged for left ventricular end-diastolic volume, all-cause mortality or adverse events, and not a single included study reported heart failure-related hospitalisation.

These apparent benefits align with plausible biological mechanisms. Experimental studies suggest Qili Qiangxin can attenuate myocardial fibrosis by suppressing remodelling-related factors such as TGF-β1 and MMP-9, protect cardiomyocytes from apoptosis through PI3K/Akt and ROS/AMPK/mTOR signalling, and dampen inflammation via the TMAO/NF-κB pathway, reducing pro-inflammatory cytokines including TNF-α, IL-6 and IL-1β. The review’s authors note these mechanisms are consistent with the observed reductions in natriuretic peptides and inflammatory markers.

The findings also echo results from the larger QUEST trial, a multicentre, double-blind, placebo-controlled study published in Nature Medicine, which found that Qili Qiangxin reduced the risk of heart failure hospitalisation or cardiovascular death in patients with reduced ejection fraction, with generally consistent effects in patients with an ischaemic aetiology. The review team deliberately excluded the ischaemic subgroup from QUEST, however, because an ischaemic aetiology does not necessarily mean heart failure developed secondary to a prior heart attack, and including it would have altered the predefined study population.

Despite the encouraging surrogate signals, the certainty of evidence for every outcome was rated as low or very low under the GRADE framework. None of the 16 trials reported allocation concealment or blinding, and seven did not adequately describe their randomisation process. Substantial heterogeneity plagued several outcomes, particularly the primary NT-proBNP endpoint, and subgroup analyses based on treatment duration failed to explain it. Funnel plot asymmetry also suggested potential publication bias. Because NT-proBNP was reported in different units across studies, the pooled effect was expressed as a standardised mean difference, which cannot be read as an absolute reduction in clinical units.

The limitations extend beyond methodology. All included trials were conducted in China, limiting generalisability to other populations and healthcare settings. Definitions of clinical response varied across studies and involved relatively subjective assessments. Most importantly, the statistically significant outcomes in the review, including NT-proBNP, ejection fraction and inflammatory markers, are surrogate or intermediate measures, and improvements in such measures cannot be assumed to translate into reduced mortality or rehospitalisation. Only one small trial reported all-cause mortality, finding no significant difference between groups.

The authors conclude that the current evidence is inadequate to determine whether Qili Qiangxin improves long-term clinical prognosis and should not be considered sufficient to inform changes in clinical practice or guideline recommendations. They call for large-scale, multicentre randomised trials with rigorous randomisation, allocation concealment and blinding, longer follow-up, standardised treatment protocols and clinically meaningful endpoints such as mortality and heart failure-related hospitalisation. Until such trials are completed, the capsule’s apparent short-term benefits remain hypothesis-generating rather than definitive proof of efficacy.

Subject of Research: Efficacy and safety of Qili Qiangxin Capsule as adjunctive therapy for heart failure after acute myocardial infarction

Article Title: Qili Qiangxin capsule as adjunctive therapy for heart failure after acute myocardial infarction: a GRADE-assessed systematic review and meta-analysis of randomised controlled trials

Article References: Yu, J.-H., Yu, H.-Y., Zhang, J.-C., Chen, Z.-Y., Wang, C., Wu, Y.-Q., Wang, Y.-F., Robinson, N., Liu, J.-P., Li, Y.-L., & Liang, S.-B. (2026). Qili Qiangxin capsule as adjunctive therapy for heart failure after acute myocardial infarction: a GRADE-assessed systematic review and meta-analysis of randomised controlled trials. Frontiers in Pharmacology, 17, Article 1959187. https://doi.org/10.3389/fphar.2026.1959187

Image Credits: AI Generated

DOI: 10.3389/fphar.2026.1959187

Keywords: Qili Qiangxin Capsule, heart failure, acute myocardial infarction, meta-analysis, systematic review, GRADE, traditional Chinese medicine, NT-proBNP, ventricular remodelling, randomised controlled trials, ejection fraction, evidence certainty

The research team, led by Tímea K. Turschl and Béla Merkely, enrolled 300 patients scheduled for TAVI at their institute between April 2020 and December 2023, with a mean age of 78.7 years. Each patient underwent detailed transthoracic echocardiography and blood pressure measurement 24 to 48 hours before the procedure. Over a median follow-up of 25 months, 62 patients died from any cause. The investigators then asked a deceptively simple question: could a novel echocardiographic index, computed from routine images and a blood pressure cuff, predict who would survive and who would not?

To understand the innovation, it helps to trace the evolution of cardiac function assessment. The gold standard for measuring the heart’s intrinsic contractility is the pressure–volume loop, obtained by threading a conductance catheter into the left ventricle during cardiac catheterization. This invasive technique plots ventricular pressure against volume throughout the cardiac cycle, yielding load-independent indices of myocardial performance. Because of its complexity and risk, it is reserved for a handful of selected patients and cannot be used routinely. Echocardiography, by contrast, is cheap, safe and ubiquitous, but its most popular outputs, ejection fraction and global longitudinal strain, are strongly load-dependent, meaning they reflect not only the muscle’s contractile power but also the hemodynamic conditions imposed on it.

Pressure–strain loop-derived myocardial work analysis was introduced to bridge this gap. The method estimates the left ventricular pressure curve non-invasively by scaling a normalized reference pressure curve to the patient’s measured brachial systolic pressure, adding the Doppler-derived transvalvular gradient in aortic stenosis patients. This pressure trace is then integrated with strain curves obtained from speckle-tracking echocardiography, producing pressure–strain loops from which indices such as global work index, global constructive work, global wasted work and global work efficiency are calculated. Constructive work represents myocardial shortening during systole and lengthening during diastole, while wasted work captures the energetically futile deformation that occurs when segments contract against uncoordinated loads. Previous studies have shown these indices correlate well with invasive measures of contractility and outperform conventional parameters in predicting outcomes across cardiovascular diseases.

But the Hungarian team identified a blind spot: standard myocardial work indices ignore ventricular geometry and preload entirely. In aortic stenosis, chronic pressure overload drives concentric remodeling, and many elderly patients also carry volume overload and altered chamber sizes that fundamentally change how strain and pressure translate into actual mechanical output. Building on their earlier translational work in rodent models of heart failure, where pressure–strain–volume loops correlated even more strongly with gold-standard contractility than conventional work metrics, the researchers multiplied the pressure–strain loops by instantaneous left ventricular volume, frame by frame, before integration. The resulting volume-adjusted indices, GWIVi and GCWVi, were normalized to body surface area, yielding values expressed in mmHg%L per square meter.

The first striking result emerged when the cohort was divided into the three classic hemodynamic phenotypes of severe aortic stenosis: normal-flow high-gradient, classical low-flow low-gradient, and paradoxical low-flow low-gradient. Conventional measures told a familiar but incomplete story. Global longitudinal strain and standard work index were significantly reduced only in the classical low-flow low-gradient group, while paradoxical low-flow patients, who typically present with small, stiff, seemingly hypercontractile ventricles, looked comparable to normal-flow patients. The volume-adjusted GWIVi, however, revealed that both low-flow subgroups shared a similarly depressed myocardial work capacity, at 46.98 and 51.99 mmHg%L/m² respectively, compared with 63.74 in the normal-flow high-gradient group, a difference that was highly significant. In other words, the new index unmasked ventricular dysfunction that standard echocardiographic parameters underestimated in the paradoxical phenotype.

The prognostic findings were equally compelling. In univariate analysis, ejection fraction failed to predict mortality at all, while global longitudinal strain, global constructive work, GWIVi and GCWVi were all significantly associated with survival. When the researchers constructed fully adjusted multivariable Cox regression models incorporating clinically relevant factors such as age, male sex, hemoglobin, atrial fibrillation and diabetes mellitus, only the volume-adjusted indices remained significant independent predictors. GWIVi carried a hazard ratio of 0.955 per unit increase, and adding either index significantly improved the fit of the clinical reference model according to likelihood-ratio testing, whereas ejection fraction, strain and standard work indices did not. GCWVi also predicted mortality independently of low-flow low-gradient status, demonstrating that its prognostic power was not simply a proxy for the hemodynamic subtype.

Perhaps most clinically relevant was the performance of the new index in patients with preserved ejection fraction, a notoriously difficult group in whom conventional markers often appear reassuring despite adverse outcomes. Among the 157 patients with an ejection fraction of 50 percent or higher, 32 died during follow-up. In this subgroup, only GCWVi and atrial fibrillation emerged as predictors of mortality, and GCWVi remained an independent predictor even after adjustment for age and sex. Kaplan–Meier analysis showed that patients with GCWVi values above the cohort median had significantly better survival, both in the total population and in the preserved ejection fraction subgroup, with log-rank p-values of 0.017 and 0.007 respectively. A representative case pair illustrated the point vividly: one patient with preserved ejection fraction and strain but low volume-adjusted work died 17 months after TAVI, while another with moderately reduced conventional measures but high GWIVi survived the entire follow-up period.

The implications extend beyond prognostication. TAVI has become the most common valvular procedure worldwide, yet no dedicated perioperative risk stratification system has gained general acceptance, and the widely used EuroSCORE II was designed for open-heart surgery. The authors argue that in hemodynamic overload states such as aortic stenosis, pressure–strain–volume analysis may provide a more physiologically accurate depiction of left ventricular function, precisely because it accounts for the chamber’s size and filling state rather than deformation alone. Encouragingly, the technique requires only minimal additional post-processing on top of routine echocardiography, using images and blood pressure data already collected before the procedure.

Important caveats remain. The study was single-center, all procedures used one ultrasound vendor, and the technique depends on adequate image quality for speckle-tracking and endocardial border contouring, which may have introduced selection bias toward patients with better echocardiographic windows. The authors themselves call for multicenter validation and methodological standardization before broader clinical implementation, and note that atrial and right ventricular strain, which are relevant prognostic markers in TAVI candidates, were not assessed. Still, the message is clear: by folding ventricular volume into the calculation of myocardial work, cardiologists may gain a window into the aging heart’s true contractile reserve, one that ejection fraction has never provided. For the growing population of elderly patients facing valve replacement, that window could mean better-informed decisions about when, and whether, to intervene.

Subject of Research: Non-invasive pressure-strain-volume loop analysis for predicting survival after transcatheter aortic valve implantation in aortic stenosis

Article Title: Integrating volumes into myocardial work: the prognostic role of non-invasive pressure-strain-volume analysis in transcatheter aortic valve implantation

Article References: Turschl, T. K., Ladányi, Z., Ferencz, A., Fábián, A., Tokodi, M., Szijártó, Á., Ruppert, M., Nagy, A., Molnár, A. Á., Molnár, L., Zima, E., Kovács, A., Lakatos, B. K., & Merkely, B. (2026). Integrating volumes into myocardial work: the prognostic role of non-invasive pressure-strain-volume analysis in transcatheter aortic valve implantation. GeroScience. https://doi.org/10.1007/s11357-026-02583-3

Image Credits: AI Generated

DOI: 10.1007/s11357-026-02583-3

Keywords: aortic stenosis, TAVI, echocardiography, myocardial work, pressure-strain-volume loops, left ventricular function, ejection fraction, global longitudinal strain, prognosis, valvular heart disease, cardiac contractility, GeroScience

The study, led by Roksana Gozdowska and Marek Kuch together with colleagues at the Medical University of Warsaw and collaborating institutions, focused on circulating microRNAs, tiny fragments of non-coding RNA that drift through the bloodstream inside membrane-wrapped vesicles or bound to carrier proteins. MicroRNAs are short molecules, roughly 18 to 25 nucleotides long, that never get translated into proteins. Instead, they act as fine-tuners of gene expression: each microRNA can bind to matching sequences on messenger RNA transcripts and suppress their translation or trigger their degradation. Because a single microRNA can regulate dozens of target genes, and because their levels change in response to tissue injury, inflammation and stress, they have become prime suspects in the search for biomarkers that capture complex biological processes such as cardiac healing.

To find out whether these molecules could flag patients destined for recovery, the researchers enrolled 39 patients who had just experienced their first myocardial infarction. Everyone in the cohort completed a structured cardiac rehabilitation program, the standard supervised combination of exercise training and lifestyle support given after a heart attack. The team then applied strict echocardiographic criteria to define who had achieved reverse remodeling by the eight-week follow-up: either an absolute increase in left ventricular ejection fraction of at least 10 percentage points, or a reduction in left ventricular end-systolic volume of at least 15 percent. Ejection fraction measures the proportion of blood the ventricle ejects with each beat, while end-systolic volume reflects how much blood remains in the chamber after contraction, so together they capture both the pumping strength and the size of the recovering ventricle.

From the original cohort, ten patients who met the reverse remodeling criteria were matched with ten patients whose left ventricular status remained stable over the same period. The twenty analyzed patients had a mean age of 57 years, with a standard deviation of nine years. At baseline, before rehabilitation began, the two groups looked meaningfully different on standard imaging: the stable group started with a significantly higher ejection fraction of 53 percent, compared with 44 percent in the group that would go on to recover, a difference that reached statistical significance with a p-value of 0.013. That starting gap makes the subsequent recovery all the more notable, because the patients who improved began from a weaker position.

The echocardiographic follow-up added a second layer of evidence. Regional contractility impairment, meaning localized areas of the ventricular wall that move abnormally because of infarct damage, was present in all of the patients who later achieved reverse remodeling. By the eight-week mark, 70 percent of those patients had reversed this regional dysfunction, their previously stunned or hibernating heart muscle segments regaining movement. This pattern suggests that a substantial share of early post-infarction dysfunction is not permanent cell death but recoverable injury, and that the patients who recover are those whose hearts successfully re-activate this dormant tissue during rehabilitation.

The molecular heart of the study lay in the blood samples. Using quantitative reverse transcription polymerase chain reaction, a technique that amplifies and measures specific RNA sequences with high sensitivity, the team quantified 375 circulating microRNAs in each patient at baseline. They then searched for molecules that were more abundant in the patients who would later recover, reasoning that a higher starting level of a recovery-associated microRNA might act as an early signal of a heart poised to heal. This screen yielded fourteen candidate biomarkers: miR-15b-5p, miR-24-3p, miR-29c-3p, miR-99b-5p, miR-127-3p, miR-146a-5p, miR-199a-3p, miR-361-5p, miR-502-5p, miR-625-5p, miR-376c-3p, miR-18b-5p, miR-342-5p and miR-429. Several of these, including miR-502-5p, miR-376c-3p and miR-18b-5p, had not previously been implicated in human cardiac reverse remodeling, making them genuinely novel candidates.

Identifying the microRNAs was only the first step; the researchers also wanted to know what these molecules might actually be doing. Because individual microRNAs repress many target genes, the team performed enrichment analysis, a computational method that asks whether the genes targeted by a set of microRNAs cluster within particular biological pathways more often than chance would predict. The analysis pointed squarely at four major signaling networks: the PI3K-Akt pathway, the MAPK cascade, FoxO signaling and HIF-1 signaling. These are not obscure corners of cell biology. PI3K-Akt is a central pro-survival route that protects heart muscle cells from programmed death and drives growth and metabolism; MAPK pathways transmit stress and growth signals from the cell surface to the nucleus; FoxO transcription factors govern cell survival, autophagy and oxidative stress responses; and HIF-1 is the master regulator of the cellular response to low oxygen, a condition the infarcted heart knows intimately.

The convergence of the fourteen candidate microRNAs on these pathways paints a coherent biological picture. A heart recovering from an infarction must simultaneously limit further cell death, clear damaged tissue, stimulate repair, and re-vascularize oxygen-starved regions, and each of the enriched pathways contributes to one or more of those tasks. Circulating microRNAs, in this framing, are not merely passive debris shed from injured tissue; they are potentially active participants in intercellular communication, capable of being delivered to recipient cells and shifting gene expression programs there. If baseline microRNA profiles genuinely reflect the heart’s reparative capacity, a simple blood draw taken days after a heart attack could eventually help clinicians identify which patients are most likely to benefit from intensive rehabilitation and which need closer surveillance or additional therapies.

The authors are careful to frame the work as a bridge between laboratory findings and clinical practice rather than a definitive answer. Preclinical studies in cell cultures and animal models have long implicated microRNAs in cardiac remodeling, but translating those findings to patients has been difficult, partly because human heart attack patients are heterogeneous in age, infarct size, medication and comorbidities. By measuring microRNAs directly in patients and linking them to objectively defined echocardiographic outcomes, the study connects preclinical biology to real clinical settings. At the same time, the sample size is small, with only twenty patients in the final matched analysis, and the candidate biomarkers were identified in a pooled discovery design. The authors themselves emphasize that validation in larger, independent, non-pooled cohorts is essential before any of these molecules could move toward clinical use as a diagnostic or prognostic test.

Even with those caveats, the study adds an appealing piece to one of cardiology’s most consequential puzzles. Reverse remodeling after a heart attack represents the heart’s innate capacity for self-repair, a capacity that varies dramatically between patients for reasons that remain poorly understood. If a panel of fourteen circulating microRNAs, measured from a routine blood sample, can flag that capacity early, it could reshape how patients are triaged after infarction, personalize rehabilitation programs, and even identify candidates for emerging regenerative therapies. It would also reinforce a broader shift in medicine toward liquid biopsies, in which molecular signals circulating in blood replace or complement invasive and imaging-based assessments. For now, the fourteen microRNAs remain candidates rather than validated tools, but they offer a molecular fingerprint of cardiac recovery and a concrete starting point for the larger studies that will determine whether that fingerprint can be read reliably at the bedside.

Subject of Research: Circulating microRNAs as candidate biomarkers of left ventricular reverse remodeling after myocardial infarction

Article Title: Circulating microRNAs as potential candidate biomarkers of left ventricular reverse remodeling after myocardial infarction: A pilot study

Article References: Gozdowska, R., Konopka, M., Hojka-Osińska, A., Jas, G., Czarzasta, K., Cudnoch-Jędrzejewska, A., Braksator, W., Klimczak-Tomaniak, D., & Kuch, M. (2026). Circulating microRNAs as potential candidate biomarkers of left ventricular reverse remodeling after myocardial infarction: A pilot study. PLOS One, 21(10), e0360414. https://doi.org/10.1371/journal.pone.0360414

Image Credits: AI Generated

DOI: 10.1371/journal.pone.0360414

Keywords: microRNAs, myocardial infarction, left ventricular reverse remodeling, biomarkers, cardiac rehabilitation, echocardiography, ejection fraction, PI3K-Akt pathway, MAPK, FoxO signaling, HIF-1, non-coding RNA

The study, published in Frontiers in Signal Processing, hinges on photoplethysmography, or PPG, the optical technique that underlies the heart-rate sensors in most consumer wearables. A PPG sensor pairs a light-emitting diode with a photodiode placed against the skin, illuminating the tissue beneath and measuring the changing volume of blood flowing through it with each heartbeat. Because the hardware is cheap, non-invasive, and unobtrusive, PPG has become ubiquitous in smartwatches, rings, and finger clips. It reliably yields heart rate and heart rate variability, and it can even be measured remotely from video recordings. Yet the technique has well-known weaknesses. Wrist-based recordings are easily contaminated by motion artifacts, and the signal lacks a true physical unit: it reflects relative changes in blood volume rather than absolute quantities, and the amount of light reaching the photodiode depends on skin pigmentation, sensor contact, posture, peripheral vascular resistance, blood pressure, and cardiac output. For that reason, most PPG applications rely on relative measures such as amplitude ratios rather than absolute values.

The physiology behind PESP begins with the premature beat itself. A PVC typically has a shortened filling time and ejects little blood, because the cardiac muscle cells have not fully recovered from the previous contraction and venous return during the abbreviated diastole is limited. The compensatory pause that follows allows the ventricle to fill more completely, and the next beat arrives with augmented contractility and output. Part of this augmentation can be explained by the Bowditch effect, in which cardiac inotropy depends on heart rate, and by the Frank-Starling principle, in which stroke volume depends on left ventricular end-diastolic pressure. But PESP behaves as a phenomenon in its own right, acting separately from these classical mechanisms. PVCs are common in the general population and become more frequent with age, underlying heart disease, and comorbidities such as hypertension or coronary artery disease. Crucially, a higher occurrence of PVCs and an enhanced PESP are typical findings in heart failure.

After the potentiated beat, the extra contractility fades over the next few heartbeats, returning to baseline within several cycles. Earlier work on human cardiac tissue showed that this decay follows an inverse exponential function with a time constant of roughly 800 milliseconds, and that in heart failure the mechanical restitution is slower, corresponding to a larger time constant. More striking still, researchers have observed oscillations in the maximum arterial blood pressure following a PVC in patients with severe heart failure. This oscillating behavior is attributed to disrupted calcium cycling, specifically a sarcoplasmic reticulum depleted of calcium through leaky ryanodine receptors and reduced calcium uptake, partly compensated by upregulation of the sodium-calcium exchanger in the plasma membrane. Animal studies have reproduced the same oscillatory signature. Until now, however, observing these oscillations required invasive blood pressure measurement, which rules out continuous monitoring in daily life.

The Dutch team hypothesized that the oscillating pressure behavior seen in severe heart failure should also leave a trace in the amplitude of PPG signals, which are influenced by cardiac contractility, cardiac output, and blood pressure. Their approach models the decay of potentiation after a PVC as a second-order system, the same mathematical framework that describes a mass-spring-damper mechanism or an RLC electrical circuit. Such a system can capture both the gradual increase associated with mechanical restitution and the oscillatory response to an extrasystolic beat seen in severe heart failure. The researchers then reduced the model to a single meaningful parameter, the damping factor, and investigated how it relates to the ejection fraction, the standard clinical measure of how much blood the heart expels with each contraction, in patients diagnosed with heart failure with reduced ejection fraction.

The data came from an internal dataset collected during percutaneous electrophysiological ablation procedures, in which the heart is paced at a fixed interbeat interval. The fixed pacing keeps cardiac output constant, minimizing the confounding influences of the Bowditch and Frank-Starling effects, before a PVC is deliberately introduced and pacing is paused to let the heart respond with its compensatory pause. Electrocardiogram and arterial blood pressure were recorded at 1000 Hz with a GE Mac-Lab Hemodynamic Recording System, while PPG was captured at 32 Hz by a Philips Elan device worn on the wrist like a watch. Ejection fractions were obtained by echocardiography up to six months before the procedure, as clinical routine, with the patients clinically stable so that no significant change in ejection fraction was expected. The dataset comprised seven patients, all male, with ejection fractions ranging from 24 to 56 percent, contributing a total of 394 PVCs whose post-extrasystolic responses were undisturbed by large artifacts.

Signal processing began with bandpass filtering of the raw PPG between 0.07 and 12 Hz to suppress baseline wander and high-frequency noise, and low-pass filtering of the arterial blood pressure above 12 Hz. Pulses were detected with a peak detector, and each pulse was defined as the signal between consecutive systolic upslopes. An expert annotator, guided by the electrocardiogram where the large electrical activation of a PVC is easily recognized, labeled each pulse as a PVC pulse, a potentiated pulse, or a normal pulse. Only PVCs preceded by a normal pulse and followed by five non-PVC pulses were included, ensuring that the modeled recovery was uncontaminated. For each event, the pulse amplitude was defined as the absolute difference between the systolic peak and the start-of-diastole value, and the sequence of amplitudes following the PVC was fitted with the second-order model, treating the PVC as a Dirac delta input with an amplitude offset. Model parameters were estimated by minimizing the mean squared error using the limited-memory BFGS algorithm in Python, first per event and then across all of a patient’s events to handle large amplitude variations caused by posture changes or wristband tightness.

Two simplifications made the model practical. First, following earlier suggestions, the time axis was normalized by beat number rather than by interbeat interval, which fixes the natural frequency of the system and reduces the number of free parameters. Second, because oscillations in pulse amplitudes occur between consecutive pulses, the input was shifted by half a beat so that the model’s extreme values coincide with the pulse peaks. The result is an optimization problem in which only the damping factor describes the behavior of the PESP decay between patients. When the system is overdamped, the response rises quickly but falls short of its full gain-determined value and decays exponentially back to baseline; increasing the damping slows the rise and delays the decay. When the system is underdamped, the response overshoots and oscillates around the baseline with decaying amplitude, and lower damping produces stronger, longer-lasting oscillations. To guard against artifacts and outliers, the researchers ran the entire procedure 256 times per patient on randomly sampled subsets containing 70 percent of the PESP responses, a bootstrapping strategy that yields a distribution of damping values for each patient.

The results revealed a clear pattern. For both the invasive arterial blood pressure signal and the non-invasive PPG signal, the damping factor increased as ejection fraction decreased, until a critical point at an ejection fraction of roughly 30 percent, which the authors call the collapsing point. Below that threshold, the damping factor dropped below one, the mathematical signature of an underdamped system, indicating persistent oscillations in the pulse amplitudes. The variance of the damping estimates was larger for PPG than for arterial blood pressure, as expected given PPG’s lower signal-to-noise ratio and greater susceptibility to confounders, but the same trend and the same collapsing point remained visible. The findings echo earlier work by Sinnecker and colleagues, who found that oscillations in systolic blood pressure after a PVC appeared only in the non-survivor group of their cardiac cohort, suggesting that such oscillations may indicate severe heart failure.

The authors are careful to frame the study as exploratory. With only seven patients, strong conclusions cannot be drawn, and even 394 PVCs cannot be guaranteed to be fully independent events. The method also currently depends on PVC-induced disturbances and an otherwise normal heart rhythm, and PVC detection in PPG signals alone remains non-trivial, since the reduced blood expelled during a PVC can make it appear merely as an extended diastole of the preceding pulse. The data were recorded in a controlled clinical environment, and everyday motion artifacts may complicate real-world application. Still, the correspondence between damping values derived from invasive blood pressure and from a wrist-worn optical sensor suggests the phenomenon is robust to measurement modality, because the model’s scaling factor absorbs amplitude differences. If validated in larger cohorts, including datasets such as MIMIC-III, the approach could turn the smartwatch already on millions of wrists into an early-warning system for declining cardiac contractility, shrinking the interval between a silent deterioration and a hospital admission.

Subject of Research: Non-invasive assessment of post-extrasystolic potentiation via PPG to gauge cardiac contractility and heart failure severity

Article Title: Modeling the post-extrasystolic potentiation to determine heart failure

Article References: Montree, R. J. H., Peri, E., Dekker, L. R. C., Long, X., Haakma, R., & Vullings, R. (2026). Modeling the post-extrasystolic potentiation to determine heart failure. Frontiers in Signal Processing, 6, Article 1909928. https://doi.org/10.3389/frsip.2026.1909928

Image Credits: AI Generated

DOI: 10.3389/frsip.2026.1909928

Keywords: heart failure, post-extrasystolic potentiation, photoplethysmography, premature ventricular contractions, ejection fraction, damping factor, second-order system, wearable devices, cardiac contractility, biomedical signal processing, smartwatch, calcium cycling

The technology behind the study is worth unpacking. Rubidium-82 is a radioactive tracer produced on demand from a strontium-82 generator, which means hospitals can perform quantitative cardiac PET without an on-site cyclotron. When the tracer is injected at rest and again during pharmacological stress induced by adenosine, dynamic imaging allows software to compute myocardial blood flow in absolute physiological units of milliliters per minute per gram of tissue. From rest and stress values, the myocardial flow reserve, or MFR, is derived as the ratio between them. Professional societies in nuclear cardiology now recommend incorporating these quantitative measures into routine reporting, yet in many laboratories the categorical perfusion read and the left ventricular ejection fraction remain the dominant basis for clinical decisions.

The Kuwaiti cohort is particularly interesting because of where it comes from. The Arabian Gulf carries one of the world’s heaviest burdens of diabetes and obesity; Kuwait’s age-standardized diabetes prevalence stood at 25.6 percent in 2024, and the average body mass index in this study cohort was about 31.5 kilograms per square meter, well into the obese range. Both diabetes and obesity impair the microscopic vessels of the heart and lower baseline blood flow. Existing reference values for rubidium-82 flow measurements derive almost entirely from North American and European populations, so the researchers set out to ask whether absolute flow behaves differently in a population that has been largely absent from the normative datasets.

The study’s design was deliberately conservative. From 330 consecutive scans performed between January 2018 and December 2023, the team deduplicated repeat studies and excluded scans with internally inconsistent flow values, yielding 292 source-verified patients with a mean age of 63.1 years. Every quantitative value in the analysis file was checked against the original clinical PET report. Within this cohort, 84 patients had what the researchers called normal-appearing studies: a C1 perfusion category, meaning visually normal perfusion with a flow reserve of at least 2.0, combined with a resting ejection fraction of 50 percent or higher. Of these, 38 had a documented history of cardiac disease and 46 had none. The primary analysis compared these two subgroups directly.

The results were striking. Patients with prior cardiac disease had a median global stress myocardial blood flow of 2.25 milliliters per minute per gram, compared with 2.99 in patients without cardiac history, a difference corresponding to a Cohen’s d effect size of negative 0.78, which is conventionally considered a large effect. The deficit was even larger in the territory supplied by the right coronary artery, where stress flow was 2.25 versus 3.29, an effect size of negative 1.02. Resting flow was also lower in the cardiac history group. Crucially, however, the myocardial flow reserve itself did not differ significantly between the groups, and neither did ejection fraction or left ventricular volumes. The association survived multivariable adjustment for age, sex and body mass index, with prior cardiac disease independently associated with roughly half a milliliter per minute per gram lower global stress flow.

The pattern of the deficit matters as much as its size. Because both rest and stress flow fell together while their ratio remained preserved, the signature does not match the classic picture of coronary microvascular dysfunction, in which resting flow is typically maintained but the reserve capacity to increase flow under stress is blunted. A proportional reduction in both rest and stress flow is what one would expect instead from a lower rate-pressure product, from medication effects such as beta-blockade or nitrates, or from a reduction in viable myocardial mass after infarction. The researchers were candid about this ambiguity: resting heart rate, blood pressure and medication use were not recorded in the imaging database, and the composite cardiac history variable could not be decomposed into its constituent diagnoses. They therefore explicitly inferred no mechanism.

A second, exploratory comparison underscored the power of quantitative flow measurement. When the 46 truly normal patients were compared with the remaining 246 classified as abnormal, absolute stress flow was the strongest single discriminator, with global stress flow achieving an area under the receiver operating characteristic curve of about 0.85 and flow reserve 0.81, both substantially outperforming ejection fraction, which reached only 0.74. The authors were careful to note that because the abnormal categories are defined in part by perfusion and flow reserve, this separation is partly circular and does not represent diagnostic accuracy. Still, the magnitude of the separation, and the fact that flow parameters beat ejection fraction significantly in paired statistical testing, reinforces the argument that quantitative reporting adds genuine information beyond the conventional read.

The study also illuminated a diagnostic gray zone that has long puzzled cardiologists. Forty-five patients showed the C3 pattern: normal perfusion on visual reading but reduced global flow reserve. This pattern can reflect either genuine microvascular dysfunction with clean epicardial arteries, or balanced three-vessel epicardial disease that lowers flow uniformly without creating a regional defect, and PET alone cannot distinguish the two. In this cohort, only four C3 patients underwent coronary angiography, and all four had obstructive epicardial disease, including two with balanced triple-vessel disease. Yet resting echocardiograms, available in 24 of the C3 patients, told a more nuanced story: seven showed regional wall-motion abnormalities suggesting prior infarction, while ten had explicitly preserved regional function, the pattern expected in true microvascular disease. The C3 category, in other words, appears to be a genuine mixture of both phenotypes in this population.

The limitations of the work are as instructive as its findings. Referral indication was almost perfectly confounded with cardiac history: 84 percent of the prior-disease group was referred for revascularization assessment, versus 7 percent of those without, and patients undergoing revascularization assessment are more likely to be on flow-lowering medications. The perfusion categories were assigned during routine clinical reporting without blinding, the subgroups were small, and no outcome data were collected, so the study cannot say whether reduced absolute stress flow predicts heart attacks or death. The authors frame their conclusions as hypothesis-generating and call for prospective, outcome-linked studies with recorded hemodynamics and medication data.

Even with those caveats, the message for cardiovascular medicine is resonant. A heart that pumps normally and lights up evenly on a perfusion scan may still be running on a reduced blood supply, and a single absolute number, stress myocardial blood flow, can expose that hidden deficit in a population where metabolic disease makes such deficits especially likely. As quantitative PET becomes more widely available and professional guidance increasingly endorses flow reporting, studies like this one from the Arabian Gulf suggest that the era of reading the heart by eye alone is drawing to a close, and that the numbers behind the images may hold the key to disease that has been hiding in plain sight.

Subject of Research: Quantitative rubidium-82 PET measurement of absolute myocardial blood flow in patients with prior cardiac disease and normal-appearing perfusion studies in an Arabian Gulf cohort

Article Title: Absolute stress myocardial blood flow is reduced in patients with prior cardiac disease despite normal perfusion and ejection fraction on rubidium-82 PET: an Arabian Gulf cohort

Article References: Alenezi, A., Garashi, M., Ghadenfer, L., Panchadar, S., Biswas, G., & Ali, K. (2026). Absolute stress myocardial blood flow is reduced in patients with prior cardiac disease despite normal perfusion and ejection fraction on rubidium-82 PET: an Arabian Gulf cohort. Frontiers in Nuclear Medicine, 6, Article 1957482. https://doi.org/10.3389/fnume.2026.1957482

Image Credits: AI Generated

DOI: 10.3389/fnume.2026.1957482

Keywords: rubidium-82 PET, myocardial blood flow, myocardial flow reserve, coronary microvascular dysfunction, cardiac PET, ejection fraction, myocardial perfusion imaging, Arabian Gulf, diabetes, coronary artery disease, nuclear cardiology, Kuwait

The study, published as a letter to the editors of Clinical Research in Cardiology, comes from a team at the University Medical Centre Mannheim led by Henning Johann Steffen and Tobias Schupp. The researchers focused on a specific and often overlooked group of patients: those with heart failure and mildly reduced ejection fraction, abbreviated HFmrEF, in which the heart’s left ventricular ejection fraction, a measure of pumping efficiency, sits between 41 and 49 percent. This phenotype was only formally recognized as a distinct category by the European Society of Cardiology in 2016, renamed from mid-range to mildly reduced in 2021, and, in a twist that gives the new findings added urgency, discontinued as a separate entity in the 2026 ESC guidelines, which merged it into an expanded heart failure with reduced ejection fraction spectrum covering all patients with an ejection fraction below 50 percent.

Almost all previous evidence on seasonality in heart failure derives from cohorts dominated by patients with reduced or preserved ejection fraction, and it relies on coarse seasonal categories rather than granular temperature measurements. Whether seasonality influences the profile or short-term prognosis of HFmrEF patients had never been specifically examined. The Mannheim team set out to fill that gap using their HARMER registry, a single-center database established in 2016 specifically to investigate the newly defined HFmrEF entity. The registry’s design allowed comprehensive collection of echocardiographic, laboratory, and comorbidity parameters in this population, which is a significant advantage when studying a phenotype that has historically been lumped together with its neighbors.

The researchers retrospectively analyzed 2,184 consecutive patients hospitalized with HFmrEF between January 2016 and December 2022 at their center, which sits in one of the warmest regions of Germany. Admissions were stratified by season of presentation: spring from March to May, summer from June to August, autumn from September to November, and winter from December to February. Crucially, the team went beyond simple seasonal buckets. They obtained daily meteorological data from the German Meteorological Service climate station in Mannheim and defined extreme temperature as the lowest and highest 5th percentile of the temperature at admission, as well as of the three-day mean temperature preceding admission. Day-to-day temperature fluctuation was defined analogously. Mortality analysis used multivariable Cox regression, adjusted for age, sex, acute decompensated heart failure, myocardial infarction, and ischemic etiology, with a sensitivity analysis additionally adjusting for calendar year.

The first striking finding was what the researchers did not see. Admissions were distributed almost perfectly evenly across the year: 556 in spring, 548 in summer, 518 in autumn, and 562 in winter. A calendar-month-level analysis confirmed the absence of clustering, with monthly admissions ranging from 149 in May to 213 in March, the modal month, and no discernible winter predominance. Baseline characteristics were closely balanced across seasons, with sex distribution, heart failure etiology, valvular disease burden, NYHA functional class, and the large majority of comorbidities showing no meaningful differences. Only diabetes mellitus, ranging from 32.5 percent in summer to 40.7 percent in winter, and current smoking, ranging from 15.8 percent in autumn to 22.3 percent in spring, differed statistically, and neither followed a consistent seasonal gradient. Discharge prescription of guideline-directed heart failure medications was likewise similar year-round.

At 30 days, 92 patients, or 4.2 percent of the cohort, had died. Season of admission showed no association whatsoever with 30-day mortality, in either univariable or multivariable analysis, with a log-rank p-value of 0.809. This null result stands in sharp contrast to the pronounced winter excess mortality described in French and American cohorts dominated by reduced ejection fraction or undifferentiated heart failure. The authors propose several explanations. First, HFmrEF is pathophysiologically distinctive: preserved contractile reserve relative to more severely reduced ejection fraction may buffer the hemodynamic and infection-related stressors implicated in winter decompensation of advanced phenotypes. Consistent with this, neither C-reactive protein nor N-terminal pro-B-type natriuretic peptide concentrations at admission showed any seasonal gradient, arguing against subclinical, season-driven inflammatory or congestive priming. Second, guideline-directed medical therapy was prescribed at similar rates throughout the year, removing a potential seasonal treatment gap.

But the granular temperature analysis revealed something the seasonal categories had hidden. Admission during extreme cold, defined as the lowest 5th percentile of ambient temperature at or below 0.8 degrees Celsius, was associated with significantly higher 30-day mortality: 8.6 percent among the 105 patients admitted during such cold snaps, compared with 4.0 percent among the remaining 1,972 patients. The association held in both univariable analysis, with a hazard ratio of 2.216, and multivariable analysis, with a hazard ratio of 2.012 and a p-value of 0.049. A similar association emerged for extreme cold in the three-day mean temperature preceding admission, at or below 1.33 degrees Celsius, with a multivariable hazard ratio of 2.058. In other words, patients admitted during the coldest days, or after several days of sustained cold, faced roughly double the risk of dying within a month, regardless of their age, sex, or underlying cardiac pathology.

Equally notable was what did not predict death. Extreme heat, defined as the highest 5th percentile at or above 23.3 degrees Celsius, showed no association with 30-day mortality, with a multivariable hazard ratio of 0.849. Day-to-day temperature fluctuation in the top 5th percentile was similarly uninformative, with a hazard ratio of 0.854. A sensitivity analysis additionally adjusting for calendar year left the extreme cold estimates materially unchanged, and calendar year itself was not independently associated with mortality. The pattern suggests that short-term extreme cold exposure, rather than coarse seasonal categorization, may be the more sensitive determinant of early risk in HFmrEF. This aligns with recent evidence that ambient temperature and atmospheric pressure predict heart failure hospitalization and decompensation severity across exposure windows of days rather than months.

The picture is not entirely uniform across the literature. A recent Austrian cohort found that ambient temperature predicted emergency decompensations in patients with reduced and preserved ejection fraction but not in those with mildly reduced ejection fraction, suggesting that cold sensitivity may depend on the specific outcome, exposure window, and population studied. Divergent findings from Japan, where heart failure mortality peaks in summer rather than winter, together with heterogeneous regional patterns in the United States, further indicate that seasonality in heart failure is climate-dependent and phenotype-dependent rather than a fixed biological law. The Mannheim findings add an important data point: in a warm-region German cohort, the calendar season was irrelevant, but the thermometer was not.

The authors are candid about the limitations. The retrospective, single-center design means residual confounding cannot be excluded. Respiratory infection surveillance data, a presumed mediator of winter seasonality, were unavailable. The temperature analysis relied on a single weather station and therefore does not capture individual-level exposure, humidity, or air pollution coexposures. Most importantly, the extreme temperature subgroups were small, with 105 and 107 patients in the lowest and highest 5th percentiles respectively, and the resulting wide confidence intervals warrant cautious interpretation and external replication. The registry also lacks a directly comparable reduced or preserved ejection fraction cohort within the same dataset, although the broader literature documents substantial parallels between HFmrEF and reduced ejection fraction heart failure, including a higher prevalence of ischemic etiology, which reached 57.6 percent in this cohort, and similar benefit from neurohormonal therapies, reflected here in high discharge prescription rates of beta-blockers at 74.9 percent and ACE inhibitors or ARBs at 71.3 percent.

The takeaway is both scientifically intriguing and practically actionable. Season of admission carried no prognostic weight in this HFmrEF population, whereas extreme cold doubled the short-term mortality risk, and extreme heat carried none. If confirmed prospectively in multicenter settings, this reframing could sharpen how clinicians and health systems target preventive resources: not at winter as a blanket category, but at the specific cold snaps that precede dangerous decompensations. It also raises a pressing question for the post-2026 guideline era, in which HFmrEF has been absorbed into an expanded reduced ejection fraction spectrum: whether the temperature-mortality association documented here extends to the full range of patients with an ejection fraction below 50 percent, or whether cold sensitivity remains a fingerprint of this particular phenotype.

Subject of Research: Seasonal and temperature-related variation in short-term mortality among patients hospitalized with heart failure and mildly reduced ejection fraction

Article Title: Seasonal variation and extreme cold exposure in heart failure with mildly reduced ejection fraction

Article References: Steffen, H. J., Behnes, M., Duerschmied, D., Akin, I., & Schupp, T. (2026). Seasonal variation and extreme cold exposure in heart failure with mildly reduced ejection fraction. Clinical Research in Cardiology. https://doi.org/10.1007/s00392-026-03038-7

Image Credits: AI Generated

DOI: 10.1007/s00392-026-03038-7

Keywords: heart failure, HFmrEF, ejection fraction, seasonal variation, extreme cold, 30-day mortality, cardiology, ambient temperature, ESC guidelines, Cox regression, hospitalization, climate

The research, published in BMC Medical Imaging by Adrian Krenzer, Viktoria Wieser, and Tobias Friedetzki, introduces a pipeline called CAFEx, short for contrastive-augmented feature extraction. The central idea is deceptively simple. Instead of letting a neural network learn whatever features it finds convenient in the raw pixel data, the authors force the model to pass through an anatomical bottleneck: it must first segment the left ventricle, then derive explicit anatomical features from that segmentation mask, and only then regress the ejection fraction over time. This architectural constraint, they hypothesized, would make the learned representation less sensitive to the idiosyncrasies of any single dataset and more anchored to the actual physics and geometry of the beating heart.

The training strategy is what the authors call weakly supervised. Fully annotating echocardiography videos, tracing the endocardial border of the left ventricle frame by frame at end-diastole and end-systole, is expensive and time-consuming, which is precisely why large public datasets such as EchoNet-Dynamic provide only video-level ejection fraction labels for most clips. CAFEx was trained on EchoNet-Dynamic using these coarse video-level labels, with only a limited set of dense segmentation annotations reserved for the anatomical component of the pipeline. A contrastive learning component augments the feature extraction, encouraging the network to learn representations that are stable under the kinds of transformations ultrasound images actually undergo, such as changes in gain, cropping, and probe positioning, rather than superficial texture cues.

Echocardiography-specific augmentation played a crucial role in this design. Generic image augmentations borrowed from natural image benchmarks, such as aggressive color shifts or random erasure, can destroy clinically meaningful information in ultrasound data. The Würzburg team instead applied transformations tailored to the modality, preserving the relationship between the ventricular cavity and the surrounding myocardium while simulating realistic variation in acquisition. The goal was to teach the model that a heart is a heart, whether it was imaged on a high-end scanner at a university hospital or a portable machine in a community clinic.

The true test, and the most scientifically interesting part of the study, was external validation. The researchers trained their models on EchoNet-Dynamic, a large dataset of apical two-chamber and four-chamber videos curated under one set of imaging and annotation conventions, and then evaluated them on CAMUS, the Cardiac Acquisitions for Multi-structure Ultrasound Segmentation dataset, which was acquired under entirely different conditions. Before any model saw the external data, the authors performed careful harmonization: images were preprocessed to reduce domain shift, and the ejection fraction endpoint was recalculated as an apical-four-chamber monoplane measurement so that the target variable itself was defined consistently across both datasets. This step matters because much of the apparent failure of cross-dataset models in prior literature may reflect mismatched definitions of the quantity being predicted rather than genuine degradation of learned features.

The results showed a clear pattern. Anatomically constrained models degraded less when moving from the training dataset to the external one than direct video-regression baselines, which attempt to predict ejection fraction straight from raw video without any segmentation intermediate. The authors reproduced a broad set of competing approaches for comparison, including segmentation-based pipelines, direct regression networks, graph-based methods, transformer architectures, and other feature-extraction designs, and evaluated all of them with three metrics: Dice score for segmentation quality, mean absolute error for ejection fraction accuracy, and the coefficient of determination, R-squared, for how much of the variance in true ejection fraction the model explains.

CAFEx achieved a Dice score of 90.73 percent on the external CAMUS dataset, indicating that the anatomical component generalized well to unseen acquisition conditions. More importantly for clinical relevance, it improved ejection fraction prediction on CAMUS over the strongest reproduced feature-extraction baseline, raising R-squared from 0.38 to 0.54 and reducing the mean absolute error from 7.89 to 6.70 percentage points. In practical terms, the average prediction error of the model shrank by more than a full percentage point, and the proportion of variance it captured rose substantially, though an R-squared of 0.54 still leaves considerable room for improvement before such a system could stand in for a cardiologist.

The study is equally candid about where the approach struggles. Poor-quality videos remained a persistent challenge, as did extreme ejection fraction values at both ends of the clinical spectrum. This is a familiar pattern in medical AI: the bulk of the data clusters around mid-range values where models learn the statistics of the population well, while the severely impaired and hyperdynamic hearts that matter most for triage are underrepresented and harder to characterize. The authors note that quality-control mechanisms, calibration, and further prospective validation are needed before any clinical deployment, a caution that distinguishes this work from the more breathless claims that sometimes accompany medical deep learning papers.

Why does an anatomical bottleneck help generalization? The intuition is that raw-pixel regression models can latch onto dataset-specific artifacts, such as the particular layout of on-screen overlays, the depth settings common in one lab, or the texture signature of one ultrasound vendor. These shortcuts work well in-distribution but collapse when the imaging environment changes. A model that must first outline the left ventricle and compute features from that outline is forced to encode geometry, cavity area change over the cardiac cycle, and ventricular shape, quantities that are physically meaningful and therefore more portable across scanners and protocols. The limited dense annotations act as scaffolding: a small investment in expert tracings steers the entire representation toward anatomy rather than artifact.

The broader significance of the study lies less in the specific numbers than in its methodological stance. The authors argue for controlled external validation under explicit image and target harmonization, a practice that remains rare in a field where many papers report impressive metrics on a single held-out split of a single dataset. As deep learning systems for cardiac imaging move toward real-world use, the question that matters is not how well a model performs on data that looks like its training set, but how gracefully it degrades when confronted with the messy diversity of clinical practice. By showing that weak supervision plus anatomical structure can narrow that gap with only a modest annotation budget, the Würzburg team offers a practical template for building echocardiography AI that travels, and a reminder that the path to trustworthy medical AI runs through other hospitals’ data, not around it.

Subject of Research: Weakly supervised anatomical deep learning for cross-dataset estimation of cardiac ejection fraction from echocardiography videos

Article Title: Weakly supervised anatomical feature learning for cross-dataset ejection fraction estimation from echocardiography videos

Article References: Krenzer, A., Wieser, V., & Friedetzki, T. (2026). Weakly supervised anatomical feature learning for cross-dataset ejection fraction estimation from echocardiography videos. BMC Medical Imaging, 26(1), Article 470. https://doi.org/10.1186/s12880-026-02781-7

Image Credits: AI Generated

DOI: 10.1186/s12880-026-02781-7

Keywords: echocardiography, ejection fraction, weak supervision, deep learning, left ventricle segmentation, cross-dataset evaluation, contrastive learning, medical image analysis, cardiology, EchoNet-Dynamic, CAMUS, heart failure

The puzzle centers on the right ventricle, the muscular chamber that pumps deoxygenated blood into the pulmonary arteries. Clinical studies stretching back roughly eight decades have consistently documented that the right ventricle’s ejection fraction, the gold-standard measure of its pumping efficiency, drops after lung resection, typically by around twelve percent on average. What has remained fiercely debated is why. One school of thought holds that removing lung tissue raises the afterload, the resistance and stiffness the ventricle must work against, because the same cardiac output must now squeeze through fewer vessels. Another suspects that the surgery itself injures the heart muscle, perhaps through an inflammatory cascade, blunting its contractility. Because these two mechanisms cannot be independently manipulated in a living patient, the debate has stalled.

The Glasgow team, led by Shiting Huang and Ankush Aggarwal, attacked the problem with a lumped parameter model, a mathematical representation of the cardiovascular system built on a hydraulic-electrical analogy in which voltage stands for pressure and current for blood flow. Their closed-loop simulation contains four heart chambers governed by time-varying elastance functions, four valves modeled with turbulence and inertance effects, and two circulations, systemic and pulmonary, each represented by a three-element Windkessel network capturing resistance, compliance, and characteristic impedance. Fourteen state variables, including chamber volumes, valve flows, and valve opening states, evolve through coupled differential equations integrated over ten cardiac cycles until the system reaches a steady state.

Getting the baseline right was itself a serious undertaking. Because parameters in closed-loop models interact rather than acting in isolation, values lifted directly from the literature produced non-physiological results. The researchers therefore ran an exhaustive search over more than half a million Sobol-sampled parameter combinations, selecting the set whose outputs best matched reference values for ventricular pressures, stroke volumes, ejection fractions, and pulmonary arterial pressures. They then stress-tested the model with both local sensitivity analysis, perturbing each parameter by one percent, and a global Sobol analysis spanning nearly 3.7 million parameter sets. Two parameters dominated: pulmonary vascular resistance and maximal right ventricular elastance, the mathematical embodiment of contractility.

To simulate surgery, the team treated the lung as a set of parallel segments and removed a fraction of them, which raises effective resistance and impedance while shrinking compliance in proportion to the tissue lost. For the alternative mechanism, they simply reduced the right ventricle’s maximal elastance, mimicking a loss of contractile strength. The striking result is that the two mechanisms produce nearly identical trends across almost every clinically routine measurement. Right ventricular volumes balloon in both scenarios, with end-systolic volume rising by up to thirty-four percent, and ejection fraction falls by roughly twelve percent either way. On the left side of the heart, changes remain modest, consistent with clinical reports that left ventricular function is largely preserved.

But three measurements split the mechanisms decisively. Right ventricular systolic pressure and pulmonary arterial systolic and diastolic pressures rise sharply under afterload increase, by nearly fifty percent in the pulmonary artery, yet fall under contractility loss. The timing differs too: afterload elevation raises pressures across the whole of systole, whereas contractility loss depresses them mainly in early systole. Pressure-volume loops tell the same story from a different angle, with the right ventricular loop shifting toward higher pressures and volumes under afterload increase but toward lower pressures and higher volumes under contractility loss. In principle, then, a simple pressure measurement in the pulmonary artery could reveal which mechanism, or what mixture of both, is driving an individual patient’s decline.

When the team compared their simulations against the published clinical literature, the agreement was encouraging. The model reproduces the observed five to twenty percent declines in ejection fraction and the reported increases in right ventricular volumes. It even accommodates the contradictory pressure findings scattered through the literature: studies reporting rising pulmonary pressures align with the afterload scenario, while the one study that recorded a slight decrease fits the contractility-loss scenario. This suggests that the historical confusion in clinical data may not reflect measurement error so much as genuine heterogeneity, with different patients experiencing different blends of the two mechanisms.

The clinical implications could be substantial. If pressure measurements can quantify the precise combination of afterload increase and contractility loss in a given patient, treatment could be tailored accordingly: pulmonary vasodilators and careful fluid management for afterload-driven dysfunction, inotropic support for contractility-driven failure. Animal studies have shown that right ventricular function can remain depressed even after afterload normalizes, hinting that contractile injury is real and persistent, and the new model provides a framework for testing how much each mechanism contributes. The researchers emphasize that the model is deliberately simple, a first step rather than a finished clinical tool.

Limitations remain. The baseline assumes a healthy heart, whereas lung cancer patients often carry comorbidities; compensatory mechanisms and long-term adaptation are absent; the ventricles are not coupled; and a lumped model cannot capture localized wave reflections in the pulmonary tree, which recent clinical work has implicated in right ventricular impairment. Quantitative validation against patient-specific cohorts is still needed. Yet the significance of the study lies less in its numbers than in its proof of concept: for the first time, the cardiovascular consequences of lung resection can be simulated, decomposed, and compared against eight decades of clinical observation. As the model is refined with real patient data, it could evolve into a decision-support system that identifies vulnerable right ventricles before they fail, turning a long-standing surgical mystery into a manageable, measurable risk.

Subject of Research: Computational modeling of right ventricular dysfunction mechanisms following lung resection surgery

Article Title: Cardiovascular function changes following lung resection: a computational model to compare afterload increase and contractility loss mechanisms

Article References: Huang, S., Pant, S., McGinty, S., Good, R., Shelley, B., & Aggarwal, A. (2026). Cardiovascular function changes following lung resection: a computational model to compare afterload increase and contractility loss mechanisms. Medical & Biological Engineering & Computing. https://doi.org/10.1007/s11517-026-03682-1

Image Credits: AI Generated

DOI: 10.1007/s11517-026-03682-1

Keywords: lung resection, right ventricle, RV dysfunction, afterload, contractility, lumped parameter model, cardiovascular modeling, pulmonary circulation, lung cancer surgery, ejection fraction, hemodynamics, sensitivity analysis

The technique at the center of the study, cardiovascular magnetic resonance, is widely regarded as the gold standard for measuring the heart’s structure and function. Unlike echocardiography, which relies on ultrasound beams that must be angled through the chest wall and can be distorted by poor acoustic windows, cardiac MRI captures the beating heart in full three dimensions. The researchers used a steady-state free precession sequence, often abbreviated SSFP, which produces bright blood pools against darker muscle tissue and allows the borders of the ventricles to be traced with high precision. From these tracings, the team could calculate end-diastolic volume, the amount of blood in each ventricle when it is fully relaxed; end-systolic volume, the amount remaining after contraction; stroke volume, the difference between the two; and ejection fraction, the fraction of blood expelled with each beat. Ventricular mass, essentially the weight of the heart muscle, can also be quantified directly from the images.

Establishing what is normal, however, requires more than sophisticated hardware. It requires a carefully screened cohort of healthy volunteers, and this is where the study makes its most distinctive contribution. The participants were enrolled at a single center in Lanzhou, in northwest China, with a median age of ten years and a range spanning from just three months to eighteen years. Recruiting very young children for MRI is a formidable logistical challenge, because the technique demands that subjects lie motionless inside a noisy magnet for several minutes at a time. Infants and toddlers typically require sedation or careful feeding-and-swaddling protocols, and ethical oversight is correspondingly strict. The study was conducted according to the principles of the Declaration of Helsinki, approved by the hospital’s institutional ethics committee, and written informed consent was obtained from participants or their legal guardians. All data were anonymized before analysis.

The analytical approach deserves particular attention because it shapes how the results will be used in clinics. Rather than reporting a single average value for each measurement, the researchers constructed age-related reference curves using the lambda mu sigma method, often called the LMS method. This statistical framework, originally developed for pediatric growth charts, models three parameters simultaneously: the median of the measurement at each age, the spread around that median, and the skewness of the distribution. The result is a smooth set of percentile curves, analogous to the height and weight charts pediatricians pin to their office walls, against which any individual child’s ventricular volume, mass, or wall thickness can be plotted. Because children’s bodies grow in bursts and at different rates in different tissues, such continuous curves capture physiological change far more faithfully than coarse age brackets alone.

The findings reveal a striking pattern of sex differences that emerges and disappears depending on the parameter and the age group examined. Across the entire cohort, boys showed significantly larger values than girls for the left ventricular long diameter, the anteroposterior diameter of the right atrium, the thickness of the left ventricular free wall, left ventricular mass, right ventricular end-diastolic volume, right ventricular stroke volume, and the indexed right ventricular end-systolic volume. When the researchers restricted their comparison to children aged six to twelve, the last four of these differences persisted, suggesting that the divergence in right ventricular size and pumping output becomes apparent during the early school years. Yet the picture is not uniform: in the youngest group, from birth to six years, and in the oldest group, from twelve to eighteen, biventricular functional reference values showed no statistically significant sex differences at all.

Perhaps the most clinically reassuring result concerns ejection fraction, the single most quoted number in cardiac imaging. For both the left and right ventricles, the age groups were statistically comparable, meaning that the heart’s pumping efficiency remains remarkably stable throughout childhood even as chamber volumes and muscle mass expand several-fold. This stability matters because it gives clinicians a relatively fixed target: a child whose ejection fraction drifts below the expected percentile band is signaling trouble regardless of age. By contrast, absolute volumes and masses must always be interpreted against the age- and sex-specific curves, since a right ventricular volume that is perfectly normal for a sixteen-year-old boy would be alarming in a toddler. The study’s stratified reporting, which presents values across defined age bands as well as continuous percentiles, is designed to support both styles of interpretation.

The right ventricle, in particular, stands to benefit from this new dataset. It is the ventricle most often implicated in congenital heart disease, from tetralogy of Fallot to pulmonary valve disorders, and it is also the chamber whose function is hardest to assess with ultrasound because of its crescent shape and position directly behind the sternum. Conditions such as arrhythmogenic right ventricular cardiomyopathy, a rare but serious disorder in which heart muscle is progressively replaced by fat and fibrous tissue, are diagnosed in part by detecting subtle enlargement of the right ventricle. Without pediatric reference values, distinguishing early disease from normal variation has been one of the most difficult judgment calls in pediatric cardiology. Percentile curves derived from healthy children directly address this gap, giving follow-up protocols a quantitative anchor for deciding when a dilated ventricle truly warrants intervention.

The study also fills a population-specific need. Reference values for cardiac dimensions are known to vary with body size, body composition, ethnicity, and environmental factors, and most existing pediatric MRI norms have been derived from North American or European cohorts. Chinese children have historically been underrepresented in such databases, leaving clinicians in China and in Chinese diaspora communities to apply standards that may not perfectly fit. By enrolling a healthy Chinese pediatric population and reporting both raw and indexed measurements, the Lanzhou team has created a resource that can be cross-referenced against international norms, potentially illuminating how cardiac growth differs across populations and refining the global picture of pediatric cardiovascular development.

Several limitations are worth keeping in view. The cohort was drawn from a single center, which ensures consistent imaging protocols but means the curves may need validation in multicenter samples before being adopted universally. The published version is also an early-release, peer-reviewed accepted manuscript that will be replaced by a final version of record, so some details may be refined. Nevertheless, the core contribution is unlikely to change: a systematically acquired, openly accessible set of biventricular MRI reference values spanning the entire pediatric age range. Because the article is published open access under a Creative Commons license, clinicians and researchers anywhere can consult the full percentile tables without subscription barriers.

The broader significance of the work lies in how it converts a fundamental gap in medical knowledge into a practical tool. Growth charts for height and weight transformed pediatrics in the twentieth century by making deviation from normal visible at a glance. Reference curves for the child’s heart, built from magnetic resonance images of both ventricles, promise a similar transformation for pediatric cardiology in the years ahead. For the family of a child undergoing follow-up after congenital heart surgery, or for the teenager with an incidental finding on a sports screening, the difference between anxiety and reassurance may now rest on a curve drawn from hundreds of healthy hearts, each one imaged, measured, and folded into a map of what a growing heart should look like.

Subject of Research: Cardiac MRI reference values for biventricular structure and function in healthy children aged 0 to 18 years

Article Title: Cardiac magnetic resonance imaging reference values of biventricular structural and functional parameters for children aged 0–18 years

Article References: Li, S., Zhang, X., Wang, J., Tao, J., Guo, R., Zhang, H., Ma, Y., Yue, S., Liu, G., Wang, J., & Zhang, J. (2026). Cardiac magnetic resonance imaging reference values of biventricular structural and functional parameters for children aged 0–18 years. BMC Pediatrics. https://doi.org/10.1186/s12887-026-07718-1

Image Credits: AI Generated

DOI: 10.1186/s12887-026-07718-1

Keywords: cardiac MRI, pediatrics, reference values, biventricular function, SSFP sequence, ventricular volumes, ejection fraction, LMS method, Chinese children, pediatric cardiology, growth charts, congenital heart disease