The implementation of different hypertension thresholds (e.g. ESC/ESH: 140:90 or ACC/AHH: 130:80) substantially increased hypertension prevalence donation of pharmacological treatment across various populations. Under narrow margins of only 10mmHg, measurement accuracy and reliability become decisive for clinical decision-making. However, detailed information on systematic and random errors naturally occurring in clinical practice under repeated testing conditions remain widely limited.To provide practically relevant insights, 65 participants were recruited for visited the lab four times with one un-standardized arrival measurement to mimic oftentimes observed clinical real-world scenarios followed by four standardized measurements performed in adherence with current guidelines. Tests were performed with two certified blood pressure devices, each on two testing days to quantify intra- and interday, as well as interdevice measurement errors via relative reliability and systematic and random measurement errors.Insufficient pre-measurement rest periods caused clinically relevant systematic blood pressure enhancements. Within a subsequent 10-18 min rest, the blood pressure was reliably reduced with about 10 mmHg on both days and both devices. However, the Boso Medicus testing device showed consistently higher blood pressure values with 13mmHg compared to the Welch Allyn monitor.Although measurements could be replicated inter-day in both devices, substantial interdevice discrepancies and clinically relevant random errors were observed, that can cause false-positive hypertension diagnoses, especially when pre-measurement rest was insufficient. Results underscore the relevance of performing several blood pressure assessments (per day and on different days) to account for random measurement errors and reduce the risk of inappropriate clinical decision-making and unnecessary treatment escalation.

Identifying transcriptional enhancers and their target genes is essential for understanding gene regulation and the effect of human genetic variation on disease^1-6. Here we create and evaluate a resource of more than 92 million enhancer-gene regulatory interactions across 1,458 biosamples covering 369 cell types and tissues, by integrating predictive models, chromatin states, three-dimensional contacts and large-scale genetic perturbations generated by the ENCODE Consortium⁷. We first create a systematic benchmarking pipeline to compare predictive models, assembling a dataset of 10,356 element-gene pairs measured in CRISPR perturbation experiments, more than 30,000 fine-mapped expression quantitative trait loci and 569 fine-mapped genome-wide association study (GWAS) variants linked to a probable causal gene. Using this framework, we develop ENCODE-rE2G, a predictive model achieving state-of-the-art performance across several prediction tasks, demonstrating that iterative perturbations and supervised machine learning can build increasingly accurate predictive models of enhancer regulation. Using ENCODE-rE2G, we build an encyclopedia of enhancer-gene regulatory interactions in the human genome, revealing global properties of enhancer networks, identifying differences in regulatory complexity across genes and improving analyses linking noncoding variants to target genes and cell types for common complex diseases. By interpreting the model, we find that beyond enhancer activity and three-dimensional enhancer-promoter contacts, additional features that guide enhancer-promoter communication include promoter class and enhancer-enhancer synergy. These genome-wide maps of enhancer-gene regulatory interactions, benchmarking software, predictive models and insights about enhancer function provide a valuable resource for future studies of gene regulation and human genetics.

Retinol-binding protein 4 (RBP4) is a key transporter of all-trans-retinol (vitamin A), circulating in blood as either holo-RBP4 (retinol-bound) or apo-RBP4 (retinol-free). Dysregulated RBP4 levels, particularly an imbalance between apo- and holo-RBP4, have been implicated in a range of metabolic and cardiovascular diseases. Current detection methods such as ELISA and Western blot lack the specificity to distinguish these two forms. Here, we present an aptamer-based biosensing strategy that overcomes this limitation by using selected single aptamer sequences for the precise and selective quantification of apo- and holo-RBP4 on graphene field-effect transistor (gFET) sensors. The specific contribution to this study is the identification of individual apo- and holo-RBP4-binding aptamers from previously enriched polyclonal libraries, their computational evaluation by molecular docking and molecular dynamics simulations, as well as their implementation as isoform-selective recognition elements on gFET sensors. The polyclonal aptamer libraries previously were generated using FluMag-SELEX (FluMag- Systematic Evolution of Ligands by Exponential Enrichment) that are specific to each RBP4 conformer. Next-generation sequencing and bioinformatic enrichment analyses identified two highly specific and high-affinity aptamers, which were further characterized via computational modelling, including molecular docking and molecular dynamics simulations. This structural approach elucidated the conformer-specific binding mechanisms, demonstrating aptamers' capacity to differentiate subtle protein conformational changes. The selected aptamers were immobilized on gFET devices, enabling label-free, real-time detection with picomolar sensitivity-a 100-fold improvement over the original libraries. Increased aptamer density on the sensor surface further enhanced signal sensitivity by an order of magnitude. These findings validate the use of aptamers as high-performance biorecognition elements in biosensors, offering a path toward precise RBP4 isoform monitoring.

This study aimed to investigate the associations between dietary fat quantity and quality and the incidence of metabolic syndrome (MetS) over a 2-year follow-up period. Additionally, we explored the cross-sectional association between dietary fat characteristics and MetS prevalence at baseline. This prospective cohort study followed 1,090 adults aged 18-65 years for 2 years. Dietary fat intake (quantity and quality) was assessed at baseline using a validated food frequency questionnaire. Anthropometric, blood pressure, and biochemical measurements were collected annually. Associations with incident and prevalent of MetS were analyzed using multivariable logistic regression and prospective cox-regression adjusted for major confounders. Among adults (mean age 39.6 ± 10.2 years; 45% men), higher intake of vegetable oils at baseline was associated with greater MetS prevalence (highest vs. lowest tertile: OR = 1.46; 95% CI 1-2.15; P-trend = 0.04). However, no significant associations were observed between overall dietary fat quantity and quality indices and the incidence of MetS during the 2 year follow-up. we found that while specific dietary fat sources like vegetable oils may relate to the current metabolic status (prevalence), their role in the development (incidence) of MetS requires further investigation with potentially different methodologies or longer follow-up periods.Please check and confirm the edit made in article title.

Monitoring home non-invasive ventilation (NIV) typically relies on commercial ventilator software that processes raw signals to estimate key respiratory parameters. However, the algorithms used by different manufacturers can distort the signals, particularly in the presence of leaks, potentially leading to misdiagnosis. This study compared the performance of built-in software from various ventilators and assessed expert agreement in interpreting processed signals. A lung simulator was used to test ventilators under different conditions: continuous leaks, intermittent leaks, asymmetric inspiratory leaks, circuit disconnection, and upper airway obstruction. A polygraph recorded raw signals for comparison with the software-processed data. Nine NIV experts analyzed 57 randomized ventilator traces, classifying the events without prior knowledge of the simulated conditions. Expert agreement was calculated and statistically analyzed. Expert agreement was high for most scenarios but significantly lower for asymmetric leaks (mean agreement 0.48), which were the main source of error in signal interpretation. Software from the ventilators tended to overestimate tidal volume and misreport leak patterns. Asymmetric leaks caused an upward shift in the baseline flow, mimicking air trapping. No major differences were observed between ventilator manufacturers. The processing of raw signals by built-in software during home NIV can lead to misinterpretations, especially in the presence of asymmetric leaks. These inaccuracies may result in clinical misdiagnoses, such as incorrect detection of asynchrony or air trapping. Improvements in software algorithms are needed to ensure more accurate signal interpretation and to reduce diagnostic errors in home NIV monitoring.

Cancer therapy has dramatically changed over the past many decades, not only in efficacy but also complexity, with targeted therapeutics that have novel mechanisms of action. As a direct result of these remarkable treatments that have extended the lives of many patients, the increased recognition of cancer therapy-related cardiac dysfunction as well as the broader description of cancer therapy-related cardiovascular toxicity (CTR-CVT) has become obvious. The discipline of cardio-oncology has accepted the challenge to provide excellent cardiovascular (CV) protection for our patients being treated for cancer in order to achieve the best overall outcomes. The successful application of optimal CV protection by cardio-oncology needs to incorporate basic principles to realise these improved overall outcomes. Critical paradigm principles include: (1) using effective CV therapy; (2) targeting the likely mechanisms of action responsible for CTR-CVT; and (3) documenting cancers and cancer therapies associated with high CTR-CVT. Such a CV protection paradigm is likely to have the biggest impact and confirm an improved overall outcome. In addition, it is important to emphasise that knowing those cancers with high CTR-CVT risk requires careful comparative study of CV endpoints during exploratory cancer trials. Furthermore, astute clinical observations of specific CTR-CVT should be routinely reported to allow the development of strategies that minimise the negative impact of CTR-CVT. Lastly, coordinated efforts that allow realistic goals of cancer treatment while minimising the impact of CTR-CVT are the end goal in order to eliminate CV disease as a barrier to effective cancer treatment.

Familial hypercholesterolemia (FH) is an autosomal-dominant disorder with elevated low-density lipoprotein cholesterol (LDL-C), contributing to premature atherosclerotic cardiovascular disease. The Dutch Lipid Clinic Network (DLCN) score and an LDL-C cutoff of 190 mg/dL are used in FH screening. However, LDL-C can be overestimated because of cholesterol content from lipoprotein(a) (Lp(a)-C), which may affect diagnostic accuracy.

We examined how correcting LDL-C for Lp(a) influenced the ability of the DLCN score to discriminate between genetically confirmed (FH/M+) and genetically unconfirmed (FH/M-) patients with FH.

We analyzed 384 German patients with suspected FH (237 women, 147 men) who underwent genetic testing. LDL-C and DLCN scores were corrected by 17.3%, 30%, and 45% of measured Lp(a). For both, we evaluated and compared model discrimination and calibration using receiver operating characteristic statistics and calibration plots.

LDL-C correction mainly reclassified patients with FH/M- (23-46), while FH/M+ reclassification was significantly less (7-20), depending on the correction level (17.3%, 30%, or 45%). 18 to 36 patients with FH/M- were reclassified from "Possible" to "Unlikely," whereas FH/M+ reclassification was rare (0-4). LDL-C correction improved specificity with minimal sensitivity loss. Areas under the curve for DLCN (0.782-0.803) and LDL-C (0.791-0.797) were similar, with no significant differences in calibration, indicating comparable performance for FH/M+ prediction.

Correcting LDL-C for Lp(a) improves diagnostic accuracy, especially by reducing false positives. A 17.3% correction effectively improved the specificity of DLCN and LDL-C while minimizing FH/M+ misclassification. LDL-C alone showed comparable performance to the DLCN score, supporting its potential as a practical diagnostic tool in clinical FH assessment.

Whether primary aldosteronism (PA), the most common endocrine cause of hypertension (HTN), contributes to HTN and cardiovascular disease burden in systemic sclerosis (SSc) has never been explored. We aimed to assess the prevalence and management of HTN, prevalence of positive PA screening test results and the associations between markers of PA with HTN and SSc-related outcomes in SSc.

Data from adult SSc patients and normotensive healthy controls (HC) were analysed in this single-centre study. HTN was defined as blood pressures ≥140/90 mm Hg on two visits or as documented in medical records. PA screening was performed using the aldosterone:renin ratio (ARR). Associations between biomarkers of PA (renin, aldosterone, ARR, hybrid steroid 18-hydroxycortisol (18OHF)) with HTN and SSc-related outcomes were assessed using multivariable regression modelling.

Data from 112 SSc patients (median (IQR) age 60 (49, 69) years, 79% female) and 48 HC (median (IQR) age 42.5 (31, 57) years, 52% female) were analysed. At baseline, 41 SSc patients (37%) had HTN, increasing to 52% of the cohort at the last follow-up visit (median follow-up 5.1 years). The prevalence of positive baseline ARR in SSc was 8% (9/112), corresponding to 12% (5/41) in the hypertensive subset. No associations were observed between biomarkers of PA and SSc-related renal and cardiovascular outcomes or HTN at last follow-up visit.

HTN was common in this SSc cohort, and prevalence of positive PA screening test was estimated at 12% among hypertensive SSc patients, supporting consideration of PA screening in this population.

Pulmonary alveolar proteinosis (PAP) is a rare disease of inappropriate alveolar surfactant accumulation. The study objective was to compare Greece-Türkiye-Cyprus cohorts, followed-up for 20 years.

Data were retrieved retrospectively by chart review.

One hundred and thirty patients, Greece 39, Türkiye 87, Cyprus 4, were included; 115 (89%) autoimmune (a)PAP, 13 (10%) secondary, 1 (1%) hereditary. Abnormal anti-GM-CSF antibody titre was available in 86/115 patients, further analyzed for aPAP. Forty (46%) were male, with median (IQR) age at diagnosis of 40 (31-50) years. At median (IQR) duration of clinical follow-up of 39 (18-78) months, three patients died. Non-survivors had higher rates of cardiovascular disease [67% vs. 5%, p < 0.001], LTOT (67% vs. 13%, p = 0.001), pulmonary fibrosis [67% vs. 5%] and worse functional status at follow-up [FVC% pred 49 (29) vs. 87 (74-97); p = 0.026, DLCO% pred 21 (46) vs. 72 (58-82); p = 0.016]. aPAP patients were stratified by therapy group (no WLL-no i-GM-CSF, WLL alone, i-GMCSF alone and both WLL and iGM-CSF). WLL was more frequently performed in Türkiye and i-GMCSF alone in Greece (p = 0.006). All therapies were effective. No difference was detected on outcome when sole iGM-CSF was compared to WLL alone or in combination with iGM-CSF [deceased/alive 0%/100% vs. 7%/93%, p = 0.491]. Sole iGM-CSF significantly ameliorated clinical and functional parameters of disease severity [DLCO% (p = 0.013), SatO₂ (p = 0.002), 6MWT (p = 0.026)]. Across all therapy groups, pulmonary fibrosis eliminated beneficial response to treatment.

This first real-life comparison of aPAP cohorts originating from three countries showed the non-inferiority of sole iGM-CSF treatment. Fibrosis negatively affects response to treatment and survival.

Cellular senescence is a cell fate marked by a prolonged and generally irreversible cessation of the cell cycle in reaction to stressors and certain physiological events. Senescent cells accumulate with age and contribute to the pathogenesis of various age-related diseases, such as neurodegeneration and cardiovascular disorders. In this context, eliminating senescent cells has emerged as a promising therapeutic approach, giving rise to the development of senolytic agents. Nevertheless, current senolytics lack precise selectivity and may induce off-target toxicity, highlighting the need for more precise interventions. This review summarizes recent progress in targeted elimination of senescent cells, including immunotherapy, engineered extracellular vesicles, and nano-based drug delivery systems. Additionally, we introduce their potential applications across various age-related diseases, then discuss the limitations and future development directions at length. STATEMENT OF SIGNIFICANCE: As the global population ages, age-related diseases pose a significant threat to human health and socioeconomic systems. Currently, eliminating senescent cells has become a promising therapeutic strategy. However, traditional senolytics lack precise selectivity and result in off-target toxicity and considerable side effects, highlighting the importance of targeted elimination. Building upon previous contributions, our study moves the field forward because we provide a systematic overview of recent advances in targeted strategies, including immunotherapy, engineered extracellular vesicles, and nano-based drug delivery systems. These strategies employ and process biomaterials to achieve precise clearance of senescent cells. Besides, we elucidate the molecular mechanisms of action and discuss the challenges and prospects, offering insights for improving biomaterials and therapeutic strategies.