Left atrial and ventricular longitudinal strain by cardiac magnetic resonance feature tracking improves prognostic stratification of patients with ST-segment elevation myocardial infarction.

We aimed to investigate the predictive value of left atrium (LA) and left ventricle (LV) longitudinal strain derived by CMR-FT early after ST-segment elevation myocardial infarction (STEMI) treated with primary percutaneous coronary intervention (pPCI). Patients with STEMI who received pPCI and completed CMR within the following week were enrolled. LA and LV longitudinal strain parameters were derived from cine CMR by FT; conventional CMR indexes were also performed. The primary endpoint was the occurrence of major cardiovascular adverse events (MACE), defined as a composite of death, reinfarction, and congestive heart failure (HF). 276 participants (median age, 57 years, IQR, 48-66 years; 85% men) were included in this study. CMR was usually completed on the 5 (IQR,4-7) days after pPCI. During a median follow-up of 16 months, MACE occurred in 35 (12.7%) participants. Multivariable Cox regression analysis showed that LA conduit strain (HR 0.91, 95%CI: 0.84, 0.98, p = 0.013) and LV global longitudinal strain (HR 1.17, 95%CI: 1.03, 1.34, p = 0.016) remained independently associated with MACE. Participants with impaired LA conduit strain (≤ 12.8%) and LV global longitudinal strain (> -13.1%) had a higher risk of MACE than those with preserved. Longitudinal strain of LA and LV could provide independent prognostic information in STEMI patients, and comprehensive assessment of Left atrial and ventricular longitudinal strain significantly improved the prognosis.

Knowledge of Alzheimer's disease and associated factors among adults in Zhuhai, China: a cross-sectional analysis.

BACKGROUND: This study aimed to assess the public knowledge regarding Alzheimer's Disease (AD) in Zhuhai, China, focusing on identifying knowledge gaps and the influence of demographic and health factors. METHODS: A cross-sectional study was conducted in Zhuhai, China, from October to November 2022. A total of 1986 residents from 18 communities were selected employing stratified multi-stage equi-proportional sampling. Questionnaires covering general information and the Alzheimer's Disease Knowledge Scale (ADKS) were investigated face-to-face. Ordinal multiclass logistic regression was applied to assess the relationship between AD awareness and demographic and health characteristics. RESULTS: The average ADKS score was 18.5 (SD = 3.36) in Zhuhai. The lowest awareness rates were observed in the "Symptoms" and "Caregiving" subdomains of ADKS, with rates of 51.01% and 43.78%, respectively. The correct rates for the 30 ADKS questions ranged from 16.62 to 92.6%, showing a bimodal pattern with clusters around 80% and 20%. Women (OR = 1.203, 95% CI: 1.009-1.435), individuals aged 60 years or older (OR = 2.073, 95% CI: 1.467-2.932), those living in urban areas (OR = 1.361, 95% CI: 1.117-1.662), higher average monthly household income per capita (OR = 1.641, 95% CI: 1.297-2.082), and without any neurological or mental disorders (OR = 1.810, 95% CI: 1.323-2.478) were more likely to have higher levels of awareness about Alzheimer's disease. CONCLUSIONS: Adults in Zhuhai show a limited knowledge of AD, particularly in the 'Symptoms' and 'Caregiving' subdomains. Upcoming health campaigns must focus on bridging the knowledge gaps in different subdomains of AD, especially among subgroups with lower awareness, as identified in our study.

Nanobody Mediated Atrazine Resistance in Plants.

In planta expression of recombinant antibodies has been proposed as a strategy for herbicide resistance but is not well advanced yet. Here, an atrazine nanobody gene fused with a green fluorescent protein tag was transformed to Arabidopsis thaliana, which was confirmed with PCR, ELISA, and immunoblotting. High levels of nanobody accumulation were observed in the nucleus, cytoderm, and cytosol. The nanobody expressed in the plant had similar affinity, sensitivity, and selectivity as that expressed in Escherichia coli. The T3 homozygous line showed resistance in a dose-dependent manner up to 380 g ai/ha of atrazine, which is approximately one-third of the recommended field application rate. This is the first report of utilizing a nanobody in plants against herbicides. The results suggest that utilizing a high-affinity herbicide nanobody gene rather than increasing the expression of nanobodies in plants may be a technically viable approach to acquire commercial herbicide-resistant crops and could be a useful tool to study plant physiology.

Discovery of RXFP2 genetic association in resistant hypertensive men and RXFP2 antagonists for the treatment of resistant hypertension.

Hypertension remains a leading cause of cardiovascular and kidney diseases. Failure to control blood pressure with ≥ 3 medications or control requiring ≥ 4 medications is classified as resistant hypertension (rHTN) and new therapies are needed to reduce the resulting increased risk of morbidity and mortality. Here, we report genetic evidence that relaxin family peptide receptor 2 (RXFP2) is associated with rHTN in men, but not in women. This study shows that adrenal gland gene expression of RXFP2 is increased in men with hypertension and the RXFP2 natural ligand, INSL3, increases adrenal steroidogenesis and corticosteroid secretion in human adrenal cells. To address the hypothesis that RXFP2 activation is an important mechanism in rHTN, we discovered and characterized small molecule and monoclonal antibody (mAb) blockers of RXFP2. The novel chemical entities and mAbs show potent, selective inhibition of RXFP2 and reduce aldosterone and cortisol synthesis and release. The RXFP2 mAbs have suitable rat pharmacokinetic profiles to evaluate the role of RXFP2 in the development and maintenance of rHTN. Overall, we identified RXFP2 activity as a potential new mechanism in rHTN and discovered RXFP2 antagonists for the future interrogation of RXFP2 in cardiovascular and renal diseases.

Effects of nitrogen application on ammonium assimilation and microenvironment in the rhizosphere of drip-irrigated sunflower under plastic mulch.

This study investigated the effect of nitrogen application on the rhizosphere soil microenvironment of sunflower and clarified the relationship between ammonium assimilation and the microenvironment. In a field experiment high (HN, 190 kg/hm2), medium (MN, 120 kg/hm2) and low nitrogen (CK, 50 kg/hm2) treatments were made to replicate plots of sunflowers using drip irrigation. Metagenomic sequencing was used to analyze the community structure and functional genes involved in the ammonium assimilation pathway in rhizosphere soil. The findings indicated that glnA and gltB played a crucial role in the ammonium assimilation pathway in sunflower rhizosphere soil, with Actinobacteria and Proteobacteria being the primary contributors. Compared with CK treatment, the relative abundance of Actinobacteria increased by 15.57% under MN treatment, while the relative abundance decreased at flowering and maturation stages. Conversely, the relative abundance of Proteobacteria was 28.57 and 61.26% higher in the MN treatment during anthesis and maturation period, respectively, compared with the CK. Furthermore, during the bud stage and anthesis, the abundance of Actinobacteria, Proteobacteria, and their dominant species were influenced mainly by rhizosphere soil EC, ammonium nitrogen (NH4+-N), and nitrate nitrogen (NO3--N), whereas, at maturity, soil pH and NO3--N played a more significant role in shaping the community of ammonium-assimilating microorganisms. The MN treatment increased the root length density, surface area density, and root volume density of sunflower at the bud, flowering, and maturity stages compared to the CK. Moreover, root exudates such as oxalate and malate were positively correlated with the dominant species of Actinobacteria and Proteobacteria during anthesis and the maturation period. Under drip irrigation, applying 120 kg/hm2 of nitrogen to sunflowers effectively promoted the community structure of ammonium-assimilating microorganisms in rhizosphere soil and had a positive influence on the rhizosphere soil microenvironment and sunflower root growth.

Study on the evaluation and influencing factors of contracted residents on the coordination of primary medical institutions.

Background: The implementation of family doctor contract service is a pivotal measure to enhance primary medical services and execute the hierarchical diagnosis and treatment system. Achieving service coordination among various institutions is both a fundamental objective and a central element of contract services. Objective: The study aims to assess residents' evaluations and determining factors related to the coordination of health services within primary medical institutions across different regions of Shandong Province. The findings intend to serve as a reference for enhancing the coordination services offered by these institutions. Methods: The study employed a multi-stage stratified random sampling method to select three prefecture-level cities in Shandong Province with different economic levels. Within each city, three counties (districts) were randomly sampled using the same method. Within each county (district), three community health service centers and township health centers implementing family doctor contract services were selected randomly. Face-to-face questionnaire surveys were conducted with contracted residents using the coordination dimension of the revised Primary Care Assessment Tools Scale (PCAT) developed by the research team. Data analysis was conducted using such methods as one-way analysis of variance and multiple linear regression. Results: The sample included 3,859 contracted residents. The coordination dimension score of primary medical institutions averaged 3.41 ± 0.18, with the referral service sub-dimension scoring 3.60 ± 0.58 and the information system sub-dimension scoring 3.34 ± 0.65. The overall score of the referral service sub-dimension surpassed that of the information system sub-dimension. Regression results indicated that the city's economic status, the type of contracted institutions, gender, education, marital status, income, occupation, health status, and endowment insurance payment status significantly influenced the coordinated service score of primary medical institutions (p < 0.05). Conclusion: The coordination of primary medical institutions in Shandong Province warrants further optimization. Continued efforts should focus on refining the referral system, expediting information infrastructure development, enhancing the service standards of primary medical institutions, and fostering resident trust. These measures aim to advance the implementation of the hierarchical diagnosis and treatment and two-way referral system.

Dehydration of Organic Solvents from Ternary Mixtures Containing Toluene/Methanol/Water by Pervaporation.

The separation of a toluene/methanol/water ternary mixture is a difficult task due to the toluene/water and toluene/methanol azeotropes. In this article, low-energy pervaporation is proposed for the separation of the ternary azeotrope toluene-methanol-water. This work investigates the effects of feed temperature, feed flow rate, and vacuum on pervaporation and compares the energy consumption of pervaporation with that of distillation. The results showed that at the optimized flow rate of 50 L/h and a permeate side vacuum of 60 kPa at 50 °C, the water and methanol content in the permeate was about 63.2 wt.% and 36.8 wt.%, respectively, the water/ methanol separation factor was 24.04, the permeate flux was 510.7 g/m2·h, the water content in the feed out was reduced from 2.5 wt.% to less than 0.66 wt.%, and the dehydration of toluene methanol could be realized. Without taking into account the energy consumption of pumps and other power equipment, pervaporation requires an energy consumption of 43.53 kW·h to treat 1 ton of raw material, while the energy consumption of distillation to treat 1 ton of raw material is about 261.5 kW·h. Compared to the existing distillation process, the pervaporation process consumes much less energy (about one-sixth of the energy consumption of distillation). There is almost no effect on the surface morphology and chemical composition of the membrane before and after use. The method provides an effective reference for the dehydration of organic solvents from ternary mixtures containing toluene/methanol/water.

Distal Immunization and Systemic Cytokines Establish a Transient Immune Alert State in the Intestine.

Conventionally, immune responses are studied in the context of inflamed tissues and their corresponding draining lymph nodes (LNs). However, little is known about the effects of systemic inflammatory signals generated during local inflammation on distal tissues and nondraining LNs. Using a mouse model of cutaneous immunization, we found that systemic inflammatory stimuli triggered a rapid and selective distal response in the small intestine and the mesenteric LN (mesLN). This consisted of increased permeability of intestinal blood vessels and lymphatic drainage of bloodborne solutes into the mesLN, enhanced activation and migration of intestinal dendritic cells, as well as amplified T cell responses in the mesLNs to systemic but not orally derived Ags. Mechanistically, we found that the small intestine endothelial cells preferentially expressed molecules involved in TNF-α signaling and that TNF-α blockade markedly diminished distal intestinal responses to cutaneous immunization. Together, these findings reveal that the intestinal immune system is rapidly and selectively activated in response to inflammatory cues regardless of their origin, thus identifying an additional layer of defense and enhanced surveillance of a key barrier organ at constant risk of pathogen encounter.

Layer-by-Layer-Processed All-Polymer Solar Cells with Enhanced Performance Enabled by Regulating the Microstructure of Upper Layer.

The layer-by-layer (LBL) fabrication method allows for controlled microstructure morphology and vertical component distribution, and also offers a reproducible and efficient technique for fabricating large-scale organic solar cells (OSCs). In this study, the polymers D18 and PYIT-OD are employed to fabricate all-polymer solar cells (all-PSCs) using the LBL method. Morphological studies reveal that the use of additives optimizes the microstructure of the active layer, enhancing the cells' crystallinity and charge transport capability. The optimized device with 2% CN additive significantly reduces bimolecular recombination and trap-assisted recombination. All-PSCs fabricated by the LBL method based on D18/PYIT-OD deliver a power conversion efficiency (PCE) of 15.07%. Our study demonstrates the great potential of additive engineering via the LBL fabrication method in regulating the microstructure of active layers, suppressing charge recombination, and enhancing the photovoltaic performance of devices.

High-Performance Liquid Chromatographic Quantification of the Plant Hormone Abscisic Acid at ppb Levels in Plant Samples after a Single Immunoaffinity Column Cleanup.

High-performance liquid chromatography with ultraviolet detection (HPLC-UV) is a common analysis technique due to its high versatility and simple operation. In the present study, HPLC-UV detection was integrated with immunoaffinity cleanup (IAC) of the sample extracts. The matrix effect was greatly reduced, and the limit of detection was as low as 1 ng/g of free abscisic acid (ABA) in fresh plant tissues. A monoclonal antibody 3F1 (mAb 3F1) was developed to specifically recognize free ABA but not ABA analogues. The mAb 3F1-immobilized immunoaffinity column exhibited a capacity of 850 ng/mL and an elution efficiency of 88.8-105% for standards. The extraction recoveries of the column for ABA ranged from 80.4 to 108.9%. ABA content was detected in various plant samples with IAC-HPLC-UV. The results were verified with ultraperformance liquid chromatography-electrospray tandem mass spectrometry. IAC-HPLC-UV can be a sensitive and cost-efficient method for plant hormone analysis.

PMBC: a manually curated database for prognostic markers of breast cancer.

Breast cancer is notorious for its high mortality and heterogeneity, resulting in different therapeutic responses. Classical biomarkers have been identified and successfully commercially applied to predict the outcome of breast cancer patients. Accumulating biomarkers, including non-coding RNAs, have been reported as prognostic markers for breast cancer with the development of sequencing techniques. However, there are currently no databases dedicated to the curation and characterization of prognostic markers for breast cancer. Therefore, we constructed a curated database for prognostic markers of breast cancer (PMBC). PMBC consists of 1070 markers covering mRNAs, lncRNAs, miRNAs and circRNAs. These markers are enriched in various cancer- and epithelial-related functions including mitogen-activated protein kinases signaling. We mapped the prognostic markers into the ceRNA network from starBase. The lncRNA NEAT1 competes with 11 RNAs, including lncRNAs and mRNAs. The majority of the ceRNAs in ABAT belong to pseudogenes. The topology analysis of the ceRNA network reveals that known prognostic RNAs have higher closeness than random. Among all the biomarkers, prognostic lncRNAs have a higher degree, while prognostic mRNAs have significantly higher closeness than random RNAs. These results indicate that the lncRNAs play important roles in maintaining the interactions between lncRNAs and their ceRNAs, which might be used as a characteristic to prioritize prognostic lncRNAs based on the ceRNA network. PMBC renders a user-friendly interface and provides detailed information about individual prognostic markers, which will facilitate the precision treatment of breast cancer. PMBC is available at the following URL: http://www.pmbreastcancer.com/.

Statistical methods for gene-environment interaction analysis.

Most human complex phenotypes result from multiple genetic and environmental factors and their interactions. Understanding the mechanisms by which genetic and environmental factors interact offers valuable insights into the genetic architecture of complex traits and holds great potential for advancing precision medicine. The emergence of large population biobanks has led to the development of numerous statistical methods aiming at identifying gene-environment interactions (G × E). In this review, we present state-of-the-art statistical methodologies for G × E analysis. We will survey a spectrum of approaches for single-variant G × E mapping, followed by various techniques for polygenic G × E analysis. We conclude this review with a discussion on the future directions and challenges in G × E research.

Joint effect of abnormal systemic immune-inflammation index (SII) levels and diabetes on cognitive function and survival rate: A population-based study from the NHANES 2011-2014.

OBJECTIVE: The purpose of this study was to investigate whether the combination of abnormal systemic immune-inflammation index (SII) levels and hyperglycemia increased the risk of cognitive function decline and reduced survival rate in the United States. METHODS: This cross-sectional study used data from the National Health and Nutrition Examination Survey (NHANES) database from 2011-2014 and enrolled 1,447 participants aged 60 years or older. Restricted cubic splines (RCS), linear regression and kaplan-meier(KM) curve were employed to explore the combined effects of abnormal SII and hyperglycemia on cognitive function and survival rate, and subgroup analysis was also conducted. RESULTS: The RCS analysis revealed an inverted U-shaped relationship between lgSII levels and cognitive function. Linear regression analysis indicated that neither abnormal SII nor diabetes alone significantly contributed to the decline in cognitive function compared to participants with normal SII levels and blood glucose. However, when abnormal SII coexisted with diabetes (but not prediabetes), it resulted to a significant decline in cognitive function. After adjusting for various confounding factors, these results remained significant in Delayed Word Recall (ß:-0.76, P<0.05) and Digit Symbol Substitution tests (ß:-5.02, P<0.05). Nevertheless, these results showed marginal significance in Total Word Recall test as well as Animal Fluency test. Among all subgroup analyses performed, participants with both abnormal SII levels and diabetes exhibited the greatest decline in cognitive function compared to those with only diabetes. Furthermore, KM curve demonstrated that the combination of abnormal SII levels and diabetes decreased survival rate among participants. CONCLUSION: The findings suggest that the impact of diabetes on cognitive function/survival rate is correlated with SII levels, indicating that their combination enhances predictive power.

Factors Associated with Long COVID Recovery among US Adults.

BACKGROUND: While factors associated with long COVID (LC) continue to be illuminated, little is known about recovery. This study used national survey data to assess factors associated with recovery from LC. METHODS: We used data from the 2022 National Health Interview Survey, a cross-sectional sample of noninstitutionalized US adults. Survey analysis was used to account for oversampling and nonresponse bias and to obtain nationally representative estimates. A multivariable logistic regression model was used to identify potential predictors of LC recovery. RESULTS: Among those reporting ever having COVID-19, 17.7% or an estimated 17.5 million American adults reported ever having LC, and among those with LC, 48.5% or an estimated 8.5 million reported having recovered. Multivariable logistic regression analysis showed that Hispanic adults were significantly more likely than White adults to report recovery from LC. At the same time, those with severe COVID-19 symptoms and those who had more than a high school degree, were aged 40 years or older, or were female were less likely to report recovery. CONCLUSION: Significant variations in LC recovery were noted across age, sex, race and ethnicity, education, and severity of COVID-19 symptoms. Further work is needed to elucidate the causes of these differences and identify strategies to increase recovery rates.

Correlation of epicardial adipose tissue and inflammatory indices in patients with STEMI and implications for atrial arrhythmias.

BACKGROUND: Epicardial adipose tissue(EAT) is associated with inflammation in previous studies but is unknown in patients with ST-segment elevation myocardial infarction(STEMI).This study investigated the correlation between epicardial fat and inflammatory cells obtained by cardiac magnetic resonance (CMR) and the effect on atrial arrhythmias in patients with STEMI. METHODS: This was a single-center, retrospective study. We consecutively selected patients who all completed CMR after Percutaneous Coronary Intervention (PCI) from January 2019 to December 2022 and then had regular follow-ups at 1, 3, 6, 9, and 12 months. The enrolled patients were grouped according to the presence or absence of atrial arrhythmia and divided into atrial and non-atrial arrhythmia groups. RESULTS: White blood cell, neutrophil, lymphocyte, C-reactive protein, EATV, LVES, LVED were higher in the atrial arrhythmia group than in the non-atrial arrhythmia group, and LVEF was lower than that in the non-atrial arrhythmia group (p < 0.05); EATV was significantly positively correlated with each inflammatory indices (white blood cell: r = 0.415 p < 0.001, neutrophil:r = 0.386 p < 0.001, lymphocyte:r = 0.354 p < 0.001, C-reactive protein:r = 0.414 p < 0.001); one-way logistic regression analysis showed that risk factors for atrial arrhythmias were age, heart rate, white blood cell, neutrophil, lymphocyte, C-reactive protein, EATV, LVES, LVED; multifactorial logistic regression analysis showed that neutrophil, lymphocyte, C-reactive protein, EATV, and LVES were independent risk factors for atrial arrhythmias; ROC analysis showed that the area under the curve (AUC) for neutrophil was 0.862; the AUC for lymphocyte was 1.95; and the AUC for C-reactive protein was 0.862. reactive protein was 0.852; AUC for LVES was 0.683; and AUC for EATV was 0.869. CONCLUSION: In patients with STEMI, EAT was significantly and positively correlated with inflammatory indices; neutrophil, lymphocyte, C-reactive protein, EATV, and LVES were independent risk factors for atrial arrhythmias and had good predictive value.

Molecular imprinting-based triple-emission ratiometric fluorescence sensor with aggregation-induced emission effect for visual detection of doxycycline.

The development of high-performance sensors for doxycycline (DOX) detection is necessary because its residue accumulation will cause serious harm to human health and the environment. Here, a novel tri-emission ratiometric fluorescence sensor was proposed by using "post-mixing" strategy of different emissions fluorescence molecularly imprinted polymers with salicylamide as dummy template (DMIPs). BSA was chosen as assistant functional monomer, and also acted as sensitizers for the aggregation-induced emission (AIE) effect of DOX. The blue-emitting carbon dots and the red-emitting CdTe quantum dots were separately introduced into DMIPs as the response signals. Upon DOX recognition within 2 min, blue and red fluorescence of the tri-emission DMIPs sensor were quenched while green fluorescence of DOX was enhanced, resulting in a wide range of color variations observed over bluish violet-rosered-light pink-orange-yellow-green with a detection limit of 0.061 µM. The sensor possessed highly selective recognition and was successfully applied to detect DOX in complicated real samples. Moreover, with the fluorescent color collection and data processing, the smartphone-assisted visual detection of the sensors showed satisfied sensitivity with low detection limit. This work provides great potential applications for rapid and visual detection of antibiotics in complex substrates.

Molecularly imprinted metal-organic frameworks assisted cloth and paper hybrid microfluidic devices for visual detection of gonyautoxin.

Marine algal toxin contamination is a major threat to human health. Thus, it is crucial to develop rapid and on-site techniques for detecting algal toxins. In this work, we developed colorimetric cloth and paper hybrid microfluidic devices (µCPADs) for rapid detection of gonyautoxin (GTX1/4) combined with molecularly imprinted polymers. In addition, the metal-organic frameworks (MOFs) composites were applied for this approach by their unique features. Guanosine serves as a dummy template for surface imprinting and has certain structural advantages in recognizing gonyautoxin. MOF@MIPs composites were able to perform a catalytic color reaction using hydrogen peroxide-tetramethylbenzidine for the detection of GTX1/4. The cloth-based sensing substrates were assembled on origami µPADs to form user-friendly, miniaturized colorimetric µCPADs. Combined with a smartphone, the proposed colorimetric µCPADs successfully achieved a low limit of detection of 0.65 µg/L within the range of 1-200 µg/L for rapid visual detection of GTX1/4. Moreover, the GTX1/4 of real shellfish and seawater samples were satisfactorily detected to indicate the application prospect of the µCPADs. The proposed method shows good potential in the low-cost, stable establishment of assays for the rapid detection of environmental biotoxins.

Beyond synthetic aperture focusing: deconvolution-based elevation resolution enhancement using simulated point spread function for linear array-based three-dimensional photoacoustic imaging.

This paper introduces a deconvolution-based method to enhance the elevation resolution of a linear array-based three-dimensional (3D) photoacoustic (PA) imaging system. PA imaging combines the high contrast of optical imaging with the deep, multi-centimeter spatial resolution of ultrasound (US) imaging, providing structural and functional information about biological tissues. Linear array-based 3D PA imaging is easily accessible and applicable for ex vivo studies, small animal research, and clinical applications in humans. However, its elevation resolution is limited by the acoustic lens geometry, which establishes a single elevation focus. Previous work used synthetic aperture focusing (SAF) to enhance elevation resolution, but the resolution achievable by SAF is constrained by the size of the elevation focus. Here, we introduce the application of Richardson-Lucy deconvolution, grounded in simulated point-spread-functions, to surpass the elevation resolution attainable with SAF alone. We validated this approach using both simulation and experimental data, demonstrating that the full-width-at-half-maximum of point targets on the elevation plane was reduced compared to using SAF only, suggesting resolution improvement. This method shows promise for improving 3D image quality of existing linear array-based PA imaging systems, offering potential benefits for disease diagnosis and monitoring.

Enhanced Ca2+-Driven Arrhythmias in Female Patients with Atrial Fibrillation: Insights from Computational Modeling.

BACKGROUND AND AIMS: Substantial sex-based differences have been reported in atrial fibrillation (AF), with female patients experiencing worse symptoms, increased complications from drug side effects or ablation, and elevated risk of AF-related stroke and mortality. Recent studies revealed sex-specific alterations in AF-associated Ca2+ dysregulation, whereby female cardiomyocytes more frequently exhibit potentially proarrhythmic Ca2+-driven instabilities compared to male cardiomyocytes. In this study, we aim to gain a mechanistic understanding of the Ca2+-handling disturbances and Ca2+-driven arrhythmogenic events in males vs females and establish their responses to Ca2+-targeted interventions. METHODS AND RESULTS: We incorporated known sex differences and AF-associated changes in the expression and phosphorylation of key Ca2+-handling proteins and in ultrastructural properties and dimensions of atrial cardiomyocytes into our recently developed 3D atrial cardiomyocyte model that couples electrophysiology with spatially detailed Ca2+-handling processes. Our simulations of quiescent cardiomyocytes show increased incidence of Ca2+ sparks in female vs male myocytes in AF, in agreement with previous experimental reports. Additionally, our female model exhibited elevated propensity to develop pacing-induced spontaneous Ca2+ releases (SCRs) and augmented beat-to-beat variability in action potential (AP)-elicited Ca2+ transients compared with the male model. Parameter sensitivity analysis uncovered precise arrhythmogenic contributions of each component that was implicated in sex and/or AF alterations. Specifically, increased ryanodine receptor phosphorylation in female AF cardiomyocytes emerged as the major SCR contributor, while reduced L-type Ca2+ current was protective against SCRs for male AF cardiomyocytes. Furthermore, simulations of tentative Ca2+-targeted interventions identified potential strategies to attenuate Ca2+-driven arrhythmogenic events in female atria (e.g., t-tubule restoration, and inhibition of ryanodine receptor and sarcoplasmic/endoplasmic reticulum Ca2+-ATPase), and revealed enhanced efficacy when applied in combination. CONCLUSIONS: Our sex-specific computational models of human atrial cardiomyocytes uncover increased propensity to Ca2+-driven arrhythmogenic events in female compared to male atrial cardiomyocytes in AF, and point to combined Ca2+-targeted interventions as promising approaches to treat AF in female patients. Our study establishes that AF treatment may benefit from sex-dependent strategies informed by sex-specific mechanisms.

Factors Associated With Long COVID: Insights From Two Nationwide Surveys.

BACKGROUND: Long COVID is a multisystemic condition that affects the lives of millions of people globally, yet factors associated with it are poorly defined. Our purpose in this study was to identify factors associated with long COVID. METHODS: This cross-sectional study used data from the 2022 Behavioral Risk Factor Surveillance System (BRFSS) and the 2022 National Health Interview Survey (NHIS). We restricted the sample to individuals aged 18 and older who reported a positive COVID-19 test or doctor's diagnosis. Individuals who reported symptoms of at least 3 months were assumed to have long COVID. We identified demographic and clinical characteristics associated with long COVID, in unadjusted and adjusted analyses. RESULTS: The study included 124,313 individuals in the BRFSS cohort and 10,131 in the NHIS cohort who reported a COVID-19 infection, with 26,783 (21.5%) and 1797 (17.7%) reporting long COVID, respectively. We found middle age, female sex, lack of a college degree, and severity of acute COVID-19 infection to be associated with long COVID. In contrast, non-Hispanic Asian and Black Americans were less likely to report long COVID compared with non-Hispanic White individuals. These findings were consistent across datasets. CONCLUSIONS: Several demographic features were associated with long COVID, which may be the result of social, clinical, or biological influences.