Deep generative modeling and clustering of single cell Hi-C data.

Deciphering 3D genome conformation is important for understanding gene regulation and cellular function at a spatial level. The recent advances of single cell Hi-C technologies have enabled the profiling of the 3D architecture of DNA within individual cell, which allows us to study the cell-to-cell variability of 3D chromatin organization. Computational approaches are in urgent need to comprehensively analyze the sparse and heterogeneous single cell Hi-C data. Here, we proposed scDEC-Hi-C, a new framework for single cell Hi-C analysis with deep generative neural networks. scDEC-Hi-C outperforms existing methods in terms of single cell Hi-C data clustering and imputation. Moreover, the generative power of scDEC-Hi-C could help unveil the differences of chromatin architecture across cell types. We expect that scDEC-Hi-C could shed light on deepening our understanding of the complex mechanism underlying the formation of chromatin contacts.

DeepAEG: a model for predicting cancer drug response based on data enhancement and edge-collaborative update strategies.

MOTIVATION: The prediction of cancer drug response is a challenging subject in modern personalized cancer therapy due to the uncertainty of drug efficacy and the heterogeneity of patients. It has been shown that the characteristics of the drug itself and the genomic characteristics of the patient can greatly influence the results of cancer drug response. Therefore, accurate, efficient, and comprehensive methods for drug feature extraction and genomics integration are crucial to improve the prediction accuracy. RESULTS: Accurate prediction of cancer drug response is vital for guiding the design of anticancer drugs. In this study, we propose an end-to-end deep learning model named DeepAEG which is based on a complete-graph update mode to predict IC50. Specifically, we integrate an edge update mechanism on the basis of a hybrid graph convolutional network to comprehensively learn the potential high-dimensional representation of topological structures in drugs, including atomic characteristics and chemical bond information. Additionally, we present a novel approach for enhancing simplified molecular input line entry specification data by employing sequence recombination to eliminate the defect of single sequence representation of drug molecules. Our extensive experiments show that DeepAEG outperforms other existing methods across multiple evaluation parameters in multiple test sets. Furthermore, we identify several potential anticancer agents, including bortezomib, which has proven to be an effective clinical treatment option. Our results highlight the potential value of DeepAEG in guiding the design of specific cancer treatment regimens.

Mycorrhizal associations relate to stable convergence in plant-microbial competition for nitrogen absorption under high nitrogen conditions.

Nitrogen (N) immobilization (Nim, including microbial N assimilation) and plant N uptake (PNU) are the two most important pathways of N retention in soils. The ratio of Nim to PNU (hereafter Nim:PNU ratio) generally reflects the degree of N limitation for plant growth in terrestrial ecosystems. However, the key factors driving the pattern of Nim:PNU ratio across global ecosystems remain unclear. Here, using a global data set of 1018 observations from 184 studies, we examined the relative importance of mycorrhizal associations, climate, plant, and soil properties on the Nim:PNU ratio across terrestrial ecosystems. Our results show that mycorrhizal fungi type (arbuscular mycorrhizal (AM) or ectomycorrhizal (EM) fungi) in combination with soil inorganic N mainly explain the global variation in the Nim:PNU ratio in terrestrial ecosystems. In AM fungi-associated ecosystems, the relationship between Nim and PNU displays a weaker negative correlation (r = -.06, p < .001), whereas there is a stronger positive correlation (r = .25, p < .001) in EM fungi-associated ecosystems. Our meta-analysis thus suggests that the AM-associated plants display a weak interaction with soil microorganisms for N absorption, while EM-associated plants cooperate with soil microorganisms. Furthermore, we find that the Nim:PNU ratio for both AM- and EM-associated ecosystems gradually converge around a stable value (13.8 ± 0.5 for AM- and 12.1 ± 1.2 for EM-associated ecosystems) under high soil inorganic N conditions. Our findings highlight the dependence of plant-microbial interaction for N absorption on both plant mycorrhizal association and soil inorganic N, with the stable convergence of the Nim:PNU ratio under high soil N conditions.

Genome-wide mapping of quantitative trait loci conferring resistance to stripe rust in spring wheat line PI 660072.

KEY MESSAGE: Two major QTL for resistance to stripe rust were mapped on chromosome 2BL and 4BL in spring wheat PI 660072, and their KASP markers were developed. Stripe rust, caused by Puccinia striiformis f. sp. tritici (Pst), is one of the most devastating diseases of wheat worldwide. Identifying resistance genes is crucial for developing resistant cultivars to control the disease. Spring wheat PI 660072 (Triticum aestivum) has been identified to possess both adult-plant resistance (APR) and all-stage resistance (ASR) to stripe rust. To elucidate the genetic basis of the resistance in PI 660072, a mapping population consisting of 211 F5-F7 recombinant-inbred lines (RILs) was developed from a cross of PI 660072 with susceptible spring wheat Avocet S. The mapping population was phenotyped for stripe rust responses across five field environments from 2020 to 2022 and genotyped using the 15 K SNP (single nucleotide polymorphism) array to map stripe rust resistance loci. The mapping population was also tested at the seedling stage with predominant Chinese Pst races CYR31, CYR32, CYR34 and PST-YX1-3-1 in the greenhouse. Stripe rust resistance genes were identified using the quantitative trait locus (QTL) mapping approach. Two QTL were identified with QYrPI660072.swust-2BL mapped on the long arm of chromosome 2B for ASR and QYrPI660072.swust-4BL on the long arm of chromosome 4B for APR. To facilitate marker-assisted selection breeding, Kompetitive allele specific PCR (KASP) markers, KASP-1269 for QYrPI660072.swust-2BL and KASP-3209 for QYrPI660072.swust-4BL, were developed. These markers could be used to introgress the effective resistance QTL into new wheat cultivars.

Methane Production Is More Sensitive to Temperature Increase than Aerobic and Anaerobic Methane Oxidation in Chinese Paddy Soils.

Methane emissions from paddy fields can increase under future warming scenarios. Nevertheless, a comprehensive comparison of the temperature sensitivity of methane-related microbial processes remains elusive. Here, we revealed that the temperature sensitivity of methane production (activation energy (Ea) = 0.94 eV; 95% confidence interval (CI), 0.78-1.10 eV) and aerobic (Ea = 0.49 eV; 95% CI, 0.34-0.65 eV) and anaerobic (Ea = 0.46 eV; 95% CI, 0.30-0.62 eV) methane oxidation exhibited notable spatial heterogeneity across 12 Chinese paddy fields spanning 35° longitude and 18° latitude. In addition, the Ea values of aerobic and anaerobic methane oxidation were significantly positively and negatively correlated to the latitude, respectively, while there was no significant correlation between the Ea of methane production and the latitude. Overall, there were no soil factors that had a significant effect on the Ea of methane production. The Ea of aerobic methane oxidation was primarily influenced by the contents of ammonium and clay, whereas the Ea of anaerobic methane oxidation was mainly influenced by the conductivity. Despite the variation, the overall temperature sensitivity of methane production was significantly higher than that of oxidation at a continental scale; therefore, an increase in the emission of methane from paddy fields will be predicted under future warming. Taken together, our study revealed the characteristics of temperature sensitivity of methane production and aerobic and anaerobic methane oxidation simultaneously in Chinese paddy fields, highlighting the potential roles of soil factors in influencing temperature sensitivity.

Acetylcytidine modification of Amotl1 by N-acetyltransferase 10 contributes to cardiac fibrotic expansion in mice after myocardial infarction.

Cardiac fibrosis is a pathological scarring process that impairs cardiac function. N-acetyltransferase 10 (Nat10) is recently identified as the key enzyme for the N4-acetylcytidine (ac4C) modification of mRNAs. In this study, we investigated the role of Nat10 in cardiac fibrosis following myocardial infarction (MI) and the related mechanisms. MI was induced in mice by ligation of the left anterior descending coronary artery; cardiac function was assessed with echocardiography. We showed that both the mRNA and protein expression levels of Nat10 were significantly increased in the infarct zone and border zone 4 weeks post-MI, and the expression of Nat10 in cardiac fibroblasts was significantly higher compared with that in cardiomyocytes after MI. Fibroblast-specific overexpression of Nat10 promoted collagen deposition and induced cardiac systolic dysfunction post-MI in mice. Conversely, fibroblast-specific knockout of Nat10 markedly relieved cardiac function impairment and extracellular matrix remodeling following MI. We then conducted ac4C-RNA binding protein immunoprecipitation-sequencing (RIP-seq) in cardiac fibroblasts transfected with Nat10 siRNA, and revealed that angiomotin-like 1 (Amotl1), an upstream regulator of the Hippo signaling pathway, was the target gene of Nat10. We demonstrated that Nat10-mediated ac4C modification of Amotl1 increased its mRNA stability and translation in neonatal cardiac fibroblasts, thereby increasing the interaction of Amotl1 with yes-associated protein 1 (Yap) and facilitating Yap translocation into the nucleus. Intriguingly, silencing of Amotl1 or Yap, as well as treatment with verteporfin, a selective and potent Yap inhibitor, attenuated the Nat10 overexpression-induced proliferation of cardiac fibroblasts and prevented their differentiation into myofibroblasts in vitro. In conclusion, this study highlights Nat10 as a crucial regulator of myocardial fibrosis following MI injury through ac4C modification of upstream activators within the Hippo/Yap signaling pathway.

Incidence of metabolic syndrome in patients with unilateral or bilateral staghorn renal stones and its impact on percutaneous nephrolithotomy outcomes.

BACKGROUND: To evaluate the incidence of metabolic syndrome (MetS) in patients with unilateral and bilateral staghorn calculi (SC) and evaluate the impact on the outcome of percutaneous nephrolithotomy (PCNL). METHODS: The clinical data of patients who underwent PCNL for the treatment of SC between 2019 and 2022 were retrospectively reviewed. SC was divided into unilateral and bilateral. The incidence of MetS was compared between the patients with unilateral SC and the patients with bilateral SC, and the impact on the outcome of PCNL was assessed. RESULTS: A total of 1778 patients underwent PCNL between 2019 and 2022. After screening computed tomography, 379 patients were confirmed to have SC, finally, leaving 310 patients with follow-up and complete data to be included in the study. Eighty-four had bilateral SC and 226 had unilateral SC. The patients with bilateral SC had a significantly higher body mass index and higher rates of complete staghorn stones and metabolic syndrome. Higher body mass index, hypertension, diabetes mellitus, hyperlipidaemia, and MetS were present in 62.58%, 44.84%, 21.94%, 60.65% and 27.42% of all patients, respectively. The number of MetS components remained significantly associated with bilateral SC. Specifically, when the number of MetS components increases from 0 to 3-4, the likelihood of developing bilateral staghorn calculi increases by 21.967 times. Eighty-five patients with MetS( +) had a higher rate of overall complications (number (N)(%), 29 (34.12) vs.33 (14.46), P < 0.001) and a comparable stone-free rate to 225 MetS(-) patients. Multivariable analysis confirmed that hyperlipidaemia (P = 0.044, odds ratio [OR] = 1.991, 95% confidence interval [CI] 1.020-3.888) and MetS (P = 0.005, OR = 2.427, 95% CI 1.316-4.477) were independent risk factors for overall complications. CONCLUSIONS: MetS is correlated with the formation of bilateral SC and is the main predictor for complications of PCNL especially for low-grade complications (I-II).

Chemical Composition and Phytotoxic Activity of Mentha vagans Boriss. Essential Oil.

This study explored the composition of essential oil (EO) and the first phytotoxic screening of EO obtained from the stems and leaves of Mentha vagans Boriss (MVEO) via hydro-distillation technique. The EO ingredients were detected through Gas Chromatography-Mass Spectrometry (GC-MS). GC-MS analysis revealed that MVEO contained 49 constituents, constituting 93.95 % of the total oil. Among MVEO constituents, dihydrocarvone was observed as the dominant constituent (24.14 %), followed by D-carvone (16.28 %) and piperitone (18.14 %). The phytotoxic effects of MVEO and its dominant compounds were examined against Amaranthus retroflexus, Lolium perenne, and Poa annua. Significant inhibition was observed by MVEO in comparison with the major constituents and their mixture, suppressing the seedling growth of tested species at the lowest dosage (0.01 mg/mL); in general, seedling growth of all tested species was markedly inhibited when applied concentration of the EO and its constituents reached 0.05 mg/mL. Our results also indicated that constituents other than the dominant compounds of MVEO possessed considerable phytotoxic effects because the EO's activity was stronger than its major constituents and their mixture. Thus, additional studies are required to investigate MVEO and its constituents and commercialize them as environment-friendly bio-herbicides.

A Calculation Method of Bearing Balls Rotational Vectors Based on Binocular Vision Three-Dimensional Coordinates Measurement.

The rotational speed vectors of the bearing balls affect their service life and running performance. Observing the actual rotational speed of the ball is a prerequisite for revealing its true motion law and conducting sliding behavior simulation analysis. To address the need for accuracy and real-time measurement of spin angular velocity, which is also under high-frequency and high-speed ball motion conditions, a new measurement method of ball rotation vectors based on a binocular vision system is proposed. Firstly, marker points are laid on the balls, and their three-dimensional (3D) coordinates in the camera coordinate system are calculated in real time using the triangulation principle. Secondly, based on the 3D coordinates before and after the movement of the marker point and the trajectory of the ball, the mathematical model of the spin motion of the ball was established. Finally, based on the ball spin motion model, the three-dimensional vision measurement technology was first applied to the measurement of the bearing ball rotation vector through formula derivation, achieving the analysis of bearing ball rolling and sliding characteristics. Experimental results demonstrate that the visual measurement system with the frame rate of 100 FPS (frames per second) yields a measurement error within ±0.2% over a speed range from 5 to 50 RPM (revolutions per minute), and the maximum measurement errors of spin angular velocity and linear velocity are 0.25 °/s and 0.028 mm/s, respectively. The experimental results show that this method has good accuracy and stability in measuring the rotation vector of the ball, providing a reference for bearing balls' rotational speed monitoring and the analysis of the sliding behavior of bearing balls.

Opposite effects of soil pH on bacteria and fungi ß diversity in forests at a continental scale.

Soil microbial diversity is crucial for regulating biogeochemical cycles, including soil carbon (C) dynamics and nutrient cycling. However, how climate, plants, and soil properties influence the microbiome in forests remains unclear, especially at the continental scale, hindering us to better understand forest C-climate change feedback. Here, we investigated the spatial patterns of microbial diversity across China's forests and explored the controlling factors of microbial ß diversity and network complexity. Our results showed that soil pH strongly influenced bacterial and fungal ß diversity compared to climate, soil nutrient and plant properties. To further investigate the environmental preference of the microbial networks, we classified the amplicon sequence variants (ASVs) into five groups ranging from acidic to alkaline soils. Co-occurrence network analysis revealed that the topological structure of the bacterial network (e.g., edge and degree) increased with pH and was negatively correlated with ß diversity but not for fungal diversity. Soil fungi exhibited higher ß diversity and network complexity (i.e., degree and betweenness) than bacteria in acidic soils (pH < 5.1), and vice versa in neutral and alkaline soils (pH > 5.5). Within the pH range of 5.1-5.5, the bacterial-fungal network displayed the highest network complexity with the lowest fungal ß diversity, and significant positive correlations were found between fungal ß diversity and soil properties. In addition, bacterial growth in acidic soil (pH < 5.5) showed positive correlations with acid phosphatase (AP), but negative ones with ß-1,4-glucosidase (BG), and vice versa in neutral and alkaline soils (pH > 5.5). Furthermore, 46 bacterial core species were identified, and their abundance had significant correlation with soil pH. These findings highlight the critical role of soil pH in driving soil microbial ß diversity across China's forests and reveal the effects of pH thresholds on changes in the soil microbial network and core species.

CurvAGN: Curvature-based Adaptive Graph Neural Networks for Predicting Protein-Ligand Binding Affinity.

Accurately predicting the binding affinity between proteins and ligands is crucial for drug discovery. Recent advances in graph neural networks (GNNs) have made significant progress in learning representations of protein-ligand complexes to estimate binding affinities. To improve the performance of GNNs, there frequently needs to look into protein-ligand complexes from geometric perspectives. While the "off-the-shelf" GNNs could incorporate some basic geometric structures of molecules, such as distances and angles, through modeling the complexes as homophilic graphs, these solutions seldom take into account the higher-level geometric attributes like curvatures and homology, and also heterophilic interactions.To address these limitations, we introduce the Curvature-based Adaptive Graph Neural Network (CurvAGN). This GNN comprises two components: a curvature block and an adaptive attention guided neural block (AGN). The curvature block encodes multiscale curvature informaton, then the AGN, based on an adaptive graph attention mechanism, incorporates geometry structure including angle, distance, and multiscale curvature, long-range molecular interactions, and heterophily of the graph into the protein-ligand complex representation. We demonstrate the superiority of our proposed model through experiments conducted on the PDBbind-V2016 core dataset.

Low soil moisture suppresses the thermal compensatory response of microbial respiration.

The thermal compensatory response of microbial respiration contributes to a decrease in warming-induced enhancement of soil respiration over time, which could weaken the positive feedback between the carbon cycle and climate warming. Climate warming is also predicted to cause a worldwide decrease in soil moisture, which has an effect on the microbial metabolism of soil carbon. However, whether and how changes in moisture affect the thermal compensatory response of microbial respiration are unexplored. Here, using soils from an 8-year warming experiment in an alpine grassland, we assayed the thermal response of microbial respiration rates at different soil moisture levels. The results showed that relatively low soil moisture suppressed the thermal compensatory response of microbial respiration, leading to an enhanced response to warming. A subsequent moisture incubation experiment involving off-plot soils also showed that the response of microbial respiration to 100 d warming shifted from a slight compensatory response to an enhanced response with decreasing incubation moisture. Further analysis revealed that such respiration regulation by moisture was associated with shifts in enzymatic activities and carbon use efficiency. Our findings suggest that future drought induced by climate warming might weaken the thermal compensatory capacity of microbial respiration, with important consequences for carbon-climate feedback.

Apparent thermal acclimation of soil heterotrophic respiration mainly mediated by substrate availability.

Multiple lines of existing evidence suggest that increasing CO2 emission from soils in response to rising temperature could accelerate global warming. However, in experimental studies, the initial positive response of soil heterotrophic respiration (RH ) to warming often weakens over time (referred to apparent thermal acclimation). If the decreased RH is driven by thermal adaptation of soil microbial community, the potential for soil carbon (C) losses would be reduced substantially. In the meanwhile, the response could equally be caused by substrate depletion, and would then reflect the gradual loss of soil C. To address uncertainties regarding the causes of apparent thermal acclimation, we carried out sterilization and inoculation experiments using the soil samples from an alpine meadow with 6 years of warming and nitrogen (N) addition. We demonstrate that substrate depletion, rather than microbial adaptation, determined the response of RH to long-term warming. Furthermore, N addition appeared to alleviate the apparent acclimation of RH to warming. Our study provides strong empirical support for substrate availability being the cause of the apparent acclimation of soil microbial respiration to temperature. Thus, these mechanistic insights could facilitate efforts of biogeochemical modeling to accurately project soil C stocks in the future climate.

Cold-adapted enzymes: mechanisms, engineering and biotechnological application.

Most cold-adapted enzymes display high catalytic activity at low temperatures (20-25 °C) and can still maintain more than 40-50% of their maximum activity at lower temperatures (0-10 °C) but are inactivated after a moderate increase in temperature. The activity of some cold-adapted enzymes increases significantly in the presence of high salt concentrations and metal ions. Interestingly, we also observed that some cold-adapted enzymes have a wide range of optimum temperatures, exhibiting not only maximum activity under low-temperature conditions but also the ability to maintain high enzyme activity under high-temperature conditions, which is a novel feature of cold-adapted enzymes. This unique property of cold-adapted enzymes is generally attractive for biotechnological and industrial applications because these enzymes can reduce energy consumption and the chance of microbial contamination, thereby lowering the production costs and maintaining the flavor, taste and quality of foods. How high catalytic activity is maintained at low temperatures remains unknown. The relationship between the structure of cold-adapted enzymes and their activity, flexibility and stability is complex, and thus far, a unified explanation has not been provided. Herein, we systematically review the sources, catalytic characteristics and cold adaptation of enzymes from four enzymes categories systematically and discuss how these properties may be exploited in biotechnology. A thorough understanding of the properties, catalytic mechanisms, and engineering of cold-adapted enzymes is critical for future biotechnological applications in the detergent industry and food and beverage industries.

Local Peaks Search Method for Solving Lamb Waves' Dispersion Equation of Laminated Structures and the Application.

To study the acoustic characteristics of sound scattered from laminated structures such as elastic plates and shells, it is usually required to solve the Lamb waves' dispersion equations. Many traditional root-finding methods such as bisection, the Newton-Raphson method, and the Muller method are not able to tackle the problem completely. A simple but powerful method named local peaks search (LPS) is proposed to overcome their drawbacks. Firstly, the non-zero part of the dispersion equation is defined as the dispersion function, and its reciprocal is used to transform the zeros (i.e., roots) into local peaks. Secondly, the chosen complex domain is discretized, and the coarse local domains where the local peaks exist are determined by the direct search method globally. Thirdly, the Muller method is applied to obtain the refined locations of local peaks. Lastly, in order to refine the results, a hierarchical scheme is designed and the iteration of the above procedures is implemented; the error is set to be 10-16 as the stop criteria. The accuracy of the LPS method is validated by comparing it with the bisection method for the problem of elastic plates in the vacuum. The acoustic echo structures are analyzed experimentally. By computation of Lamb waves' phase velocity, the critical angles are derived numerically and compared with the results acquired by an experiment using monostatic sound transducers. In this way, it is validated that the elastic scattered wave components are the highlights shown in the time-angle figure. Furthermore, the work can be applied for non-destructive testing, especially underwater structural health monitoring.

Microbial respiratory thermal adaptation is regulated by r-/K-strategy dominance.

Microbial thermal adaptation is considered to be one of the core mechanisms affecting soil carbon cycling. However, the role of microbial community composition in controlling thermal adaptation is poorly understood. Using microbial communities from the rhizosphere and bulk soils in an 8-year warming experiment as a model, we experimentally demonstrate that respiratory thermal adaptation was much stronger in microbial K-strategist-dominated bulk soils than in microbial r-strategist-dominated rhizosphere soils. Soil carbon availability exerted strong selection on the dominant ecological strategy of the microbial community, indirectly influencing respiratory thermal adaptation. Our findings shed light on the linchpin of the dominant ecological strategy exhibited by the microbial community in determining its respiratory thermal adaptation, with implications for understanding soil carbon losses under warming.

Aberrant expression of GSTM5 in lung adenocarcinoma is associated with DNA hypermethylation and poor prognosis.

BACKGROUND: Glutathione-S transferases (GSTs) comprise a series of critical enzymes involved in detoxification of endogenous or xenobiotic compounds. Among several GSTs, Glutathione S-transferases mu (GSTM) has been implicated in a number of cancer types. However, the prognostic value and potential functions of the GSTM family genes have not been investigated in lung adenocarcinoma (LUAD). METHODS: We examined the expression of GSTM5 in LUAD and identified associations among GSTM5 expression, clinicopathological features, survival data from the Cancer Genome Atlas (TCGA). The correlation between GSTM5 DNA methylation and its expression was analyzed using the MEXPRESS tool and UCSC Xena browser. The methylation status of GSTM5 in the promoter region in lung cancer cells was measured by methylation-specific PCR (MSP). After 5-aza-2'-deoxycytidine treatment of lung cancer cells, expression of GSTM5, cell proliferation and migration were assessed by RT-PCR, CCK-8 and transwell assays, respectively. RESULTS: The results showed that GSTM5 was abnormally down-regulated in LUAD patients' tissues, and patients with low GSTM5 expression level had significantly shorter OS. Cox regression analyses revealed that GSTM5 was associated with overall survival (OS) of LUAD patients, which expression was an independent prognostic indicator in terms of OS (hazard ratio: 0.848; 95% CI: 0.762-0.945; P = 0.003). In addition, we found the promoter region of GSTM5 was hypermethylated in the tumor tissue compared with adjacent normal tissues, and the average methylation level of GSTM5 were moderately correlated with its expression. Moreover, methylation-specific PCR also showed that the GSTM5 gene promoter was hypermethylated in lung cancer cells, and treatment with 5-Aza-CdR can restore the gene expression and inhibit cell proliferation and migration. Finally, Gene Set Enrichment Analysis (GSEA) revealed that low GSTM5 expression was significantly related to DNA repair pathways. CONCLUSION: Our data demonstrate that low GSTM5 expression and its high DNA methylation status may act as a novel putative molecular target gene for LUAD.

Oxidant stress-sensitive circRNA Mdc1 controls cardiomyocyte chromosome stability and cell cycle re-entry during heart regeneration.

Targeting cardiomyocyte plasticity has emerged as a new strategy for promoting heart repair after myocardial infarction. However, the precise mechanistic network underlying heart regeneration is not completely understood. As noncoding RNAs, circular RNAs (circRNAs) play essential roles in regulating cardiac physiology and pathology. The present study aimed to investigate the potential roles of circMdc1 in cardiac repair after injury and elucidate its underlying mechanisms. Here, we identified that circMdc1 levels were upregulated in postnatal mouse hearts but downregulated in the regenerative myocardium. The expression of circMdc1 in cardiomyocytes is sensitive to oxidative stress, which was attenuated by N-acetyl-cysteine. Enforced circMdc1 expression inhibited cardiomyocyte proliferation, while circMdc1 silencing led to cardiomyocyte cell cycle re-entry. In vivo, the cardiac-specific adeno-associated virus-mediated knockdown of circMdc1 promoted cardiac regeneration and heart repair accompanied by improved heart function. Conversely, circMdc1 overexpression blunted the regenerative capacity of neonatal hearts after apex resection. Moreover, circMdc1 was able to block the translation of its host gene Mdc1 specifically by binding to PABP, affecting DNA damage and the chromosome stability of cardiomyocytes. Furthermore, overexpression of Mdc1 caused damaged mouse hearts to regenerate and repair after myocardial infarction in vivo. Oxidative stress-sensitive circMdc1 plays an important role in cardiac regeneration and heart repair after injury by regulating DNA damage and chromosome stability in cardiomyocytes by blocking the translation of the host gene Mdc1.

Light Emitting Diodes Irradiation Regulates miRNA-877-3p to Promote Cardiomyocyte Proliferation.

Mammalian cardiomyocytes (CMs) maintain a low capacity for self-renewal in adulthood, therefore the induction of CMs cycle re-entry is an important approach to promote myocardial repair after injury. Recently, photobiomodulation (PBM) has been used to manipulate physiological activities of various tissues and organs by non-invasive means. Here, we demonstrate that conditioned PBM using light-emitting diodes with a wavelength of 630 nm (LED-Red) was capable of promoting the proliferation of neonatal CMs. Further studies showed that low-power LED-Red affected the expression of miR-877-3p and promoted the proliferation of CMs. In contrast, silencing of miR-877-3p partially abolished the pro-proliferative actions of LED-Red irradiation on CMs. Mechanistically, GADD45g was identified as a downstream target gene of miR-877-3p. Conditioned LED-Red irradiation also inhibited the expression of GADD45g in neonatal CMs. Moreover, GADD45g siRNA reversed the positive effect of LED-Red on the proliferation of neonatal CMs. Taken together, conditioned LED-Red irradiation increased miR-877-3p expression and promoted the proliferation of neonatal CMs by targeting GADD45g. This finding provides a new insight into the role of LED-Red irradiation in neonatal CMs biology and suggests its potential application in myocardial injury repair.

Comparison of noninvasive continuous arterial blood pressure measured by NICAP with arterial line in elderly patients.

BACKGROUND: Non-Invasive Continuous Arterial Pressure system (NICAP) allows continuous monitoring, timely detection of hypotension, and avoiding risks from invasive procedures. A previous study showed good comparability of NICAP with arterial line in people with no evidence of cardiovascular disease. Therefore, the goal of this study was to investigate whether NICAP could be accurately applied to elderly patients. METHODS: In this single-centered observational study, forty-one patients above 65 undergoing elective surgeries requiring artery catheterizations were enrolled from July 17, 2020, to June 25, 2021. Radial artery cannulation and NICAP monitoring were started before anesthesia. Blood pressure during the anesthesia induction and the whole surgery, trend of blood pressure changes, time needed for establishing continuous monitoring, and complications were recorded. RESULTS: A total of 6751 valid pairs of blood pressure measurements were analyzed. In the Bland-Altman analysis, the arithmetic means for systolic, diastolic, and mean arterial pressure were 2.2, 3.3, and 2.8 mmHg, respectively. NICAP and arterial line correlation coefficients for systolic, diastolic, and mean arterial pressure were 0.49, 0.33, and 0.45, respectively. In the trending analysis, the polar concordance rates at 30 degrees were 70.9% for systolic, 67.7% for diastolic, and 69.3% for mean arterial blood pressure. During the anesthesia induction, the arithmetic means for systolic, diastolic, and mean arterial pressure in the Bland-Altman analysis were 1.7, -0.2, and 0.5 mmHg, respectively. NICAP and arterial line correlation coefficients for systolic, diastolic, and mean arterial pressure were 0.78, 0.61 and 0.75, respectively. No severe complications occurred. CONCLUSIONS: NICAP has a poor correlation with the arterial line in elderly patients for the whole surgery or during anesthesia induction. Moreover, it showed poor comparability in the detection of blood pressure change trends with arterial lines. Our findings suggest that NICAP might not be sufficiently accurate to be applied clinically in elderly patients with comorbidities. More accurate calibration and iteration are needed.