A Non-Disposable Electrochemical Sensor Based on Laser-Synthesized Pd/LIG Nanocomposite-Modified Screen-Printed Electrodes for the Detection of H2O2.

There have been many studies on the significant correlation between the hydrogen peroxide content of different tissues or cells in the human body and the risk of disease, so the preparation of biosensors for detecting hydrogen peroxide concentration has been a hot topic for researchers. In this paper, palladium nanoparticles (PdNPs) and laser-induced graphene (LIG) were prepared by liquid-phase pulsed laser ablation and laser-induced technology, respectively. The complexes were prepared by stirring and used for the modification of screen-printed electrodes to develop a non-enzymatic hydrogen peroxide biosensor that is low cost and mass preparable. The PdNPs prepared with anhydrous ethanol as a solvent have a uniform particle size distribution. The LIG prepared by laser direct writing has good electrical conductivity, and its loose porous structure provides more adsorption sites. The electrochemical properties of the modified electrode were characterized by cyclic voltammetry, chronoamperometry, and electrochemical impedance spectroscopy. Compared with bare screen-printed electrodes, the modified electrodes are more sensitive for the detection of hydrogen peroxide. The sensor has a linear response range of 5 µM-0.9 mM and 0.9 mM-5 mM. The limit of detection is 0.37 µM. The above conclusions indicate that the hydrogen peroxide electrochemical biosensor prepared in this paper has great advantages and potential in electrochemical catalysis.

Electronic Nose Drift Suppression Based on Smooth Conditional Domain Adversarial Networks.

Anti-drift is a new and serious challenge in the field related to gas sensors. Gas sensor drift causes the probability distribution of the measured data to be inconsistent with the probability distribution of the calibrated data, which leads to the failure of the original classification algorithm. In order to make the probability distributions of the drifted data and the regular data consistent, we introduce the Conditional Adversarial Domain Adaptation Network (CDAN)+ Sharpness Aware Minimization (SAM) optimizer-a state-of-the-art deep transfer learning method.The core approach involves the construction of feature extractors and domain discriminators designed to extract shared features from both drift and clean data. These extracted features are subsequently input into a classifier, thereby amplifying the overall model's generalization capabilities. The method boasts three key advantages: (1) Implementation of semi-supervised learning, thereby negating the necessity for labels on drift data. (2) Unlike conventional deep transfer learning methods such as the Domain-adversarial Neural Network (DANN) and Wasserstein Domain-adversarial Neural Network (WDANN), it accommodates inter-class correlations. (3) It exhibits enhanced ease of training and convergence compared to traditional deep transfer learning networks. Through rigorous experimentation on two publicly available datasets, we substantiate the efficiency and effectiveness of our proposed anti-drift methodology when juxtaposed with state-of-the-art techniques.

Preoperative contrast-enhanced CT-based radiomics nomogram for differentiating benign and malignant primary retroperitoneal tumors.

OBJECTIVES: This study evaluated the ability of a preoperative contrast-enhanced CT (CECT)-based radiomics nomogram to differentiate benign and malignant primary retroperitoneal tumors (PRT). METHODS: Images and data from 340 patients with pathologically confirmed PRT were randomly placed into training (n = 239) and validation sets (n = 101). Two radiologists independently analyzed all CT images and made measurements. Key characteristics were identified through least absolute shrinkage selection combined with four machine-learning classifiers (support vector machine, generalized linear model, random forest, and artificial neural network back propagation) to create a radiomics signature. Demographic data and CECT characteristics were analyzed to formulate a clinico-radiological model. Independent clinical variables were merged with the best-performing radiomics signature to develop a radiomics nomogram. The discrimination capacity and clinical value of three models were quantified by the area under the receiver operating characteristics (AUC), accuracy, and decision curve analysis. RESULTS: The radiomics nomogram was able to consistently differentiate between benign and malignant PRT in the training and validation datasets, with AUCs of 0.923 and 0.907, respectively. Decision curve analysis manifested that the nomogram achieved higher clinical net benefits than did separate use of the radiomics signature and clinico-radiological model. CONCLUSIONS: The preoperative nomogram is valuable for differentiating between benign and malignant PRT; it can also aid in treatment planning. KEY POINTS: • A noninvasive and accurate preoperative determination of benign and malignant PRT is crucial to identifying suitable treatments and predicting disease prognosis. • Associating the radiomics signature with clinical factors facilitates differentiation of malignant from benign PRT with improved diagnostic efficacy (AUC) and accuracy from 0.772 to 0.907 and from 0.723 to 0.842, respectively, compared with the clinico-radiological model alone. • For some PRT with anatomically special locations and when biopsy is extremely difficult and risky, a radiomics nomogram may provide a promising preoperative alternative for distinguishing benignity and malignancy.

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.

ALKBH5 regulates cardiomyocyte proliferation and heart regeneration by demethylating the mRNA of YTHDF1.

N6-methyladenosine (m6A) RNA modification, a dynamic and reversible process, is essential for tissue development and pathogenesis. However, the potential involvement of m6A in the regulation of cardiomyocyte (CM) proliferation and cardiac regeneration remains unclear. In this study, we aimed to investigate the essential role of m6A modification in heart regeneration during postnatal and adult injury. Methods and results: In this study, we identified the downregulation of m6A demethylase ALKBH5, an m6A "eraser" that is responsible for increased m6A methylation, in the heart after birth. Notably, ALKBH5 knockout mice exhibited decreased cardiac regenerative ability and heart function after neonatal apex resection. Conversely, forced expression of ALKBH5 via adeno-associated virus-9 (AAV9) delivery markedly reduced the infarct size, restored cardiac function and promoted CM proliferation after myocardial infarction in juvenile (7 days old) and adult (8-weeks old) mice. Mechanistically, ALKBH5-mediated m6A demethylation improved the mRNA stability of YTH N6-methyladenosine RNA-binding protein 1 (YTHDF1), thereby increasing its expression, which consequently promoted the translation of Yes-associated protein (YAP). The modulation of ALKBH5 and YTHDF1 expression in human induced pluripotent stem cell-derived cardiomyocytes consistently yielded similar results. Conclusion: Taken together, our findings highlight the vital role of the ALKBH5-m6A-YTHDF1-YAP axis in the regulation of CMs to re-enter the cell cycle. This finding suggests a novel potential therapeutic strategy for cardiac regeneration.

Melatonin promotes cardiomyocyte proliferation and heart repair in mice with myocardial infarction via miR-143-3p/Yap/Ctnnd1 signaling pathway.

The neonatal heart possesses the ability to proliferate and the capacity to regenerate after injury; however, the mechanisms underlying these processes are not fully understood. Melatonin has been shown to protect the heart against myocardial injury through mitigating oxidative stress, reducing apoptosis, inhibiting mitochondrial fission, etc. In this study, we investigated whether melatonin regulated cardiomyocyte proliferation and promoted cardiac repair in mice with myocardial infarction (MI), which was induced by ligation of the left anterior descending coronary artery. We showed that melatonin administration significantly improved the cardiac functions accompanied by markedly enhanced cardiomyocyte proliferation in MI mice. In neonatal mouse cardiomyocytes, treatment with melatonin (1 µM) greatly suppressed miR-143-3p levels. Silencing of miR-143-3p stimulated cardiomyocytes to re-enter the cell cycle. On the contrary, overexpression of miR-143-3p inhibited the mitosis of cardiomyocytes and abrogated cardiomyocyte mitosis induced by exposure to melatonin. Moreover, Yap and Ctnnd1 were identified as the target genes of miR-143-3p. In cardiomyocytes, inhibition of miR-143-3p increased the protein expression of Yap and Ctnnd1. Melatonin treatment also enhanced Yap and Ctnnd1 protein levels. Furthermore, Yap siRNA and Ctnnd1 siRNA attenuated melatonin-induced cell cycle re-entry of cardiomyocytes. We showed that the effect of melatonin on cardiomyocyte proliferation and cardiac regeneration was impeded by the melatonin receptor inhibitor luzindole. Silencing miR-143-3p abrogated the inhibition of luzindole on cardiomyocyte proliferation. In addition, both MT1 and MT2 siRNA could cancel the beneficial effects of melatonin on cardiomyocyte proliferation. Collectively, the results suggest that melatonin induces cardiomyocyte proliferation and heart regeneration after MI by regulating the miR-143-3p/Yap/Ctnnd1 signaling pathway, providing a new therapeutic strategy for cardiac regeneration.

Epigenetic Mechanisms Contribute to Evolutionary Adaptation of Gene Network Activity under Environmental Selection.

How evolution can be facilitated by epigenetic mechanisms has received refreshed attention recently. To explore the role epigenetic inheritance plays in evolution, we subject isogenic wild-type yeast cells expressing PGAL1-YFP (yellow fluorescent protein) to selection by daily sorting based on reporter expression. We observe expression-level reductions in multiple replicates sorted for the lowest expression that persist for several days, even after lifting the selection pressure. Reduced expression is due to factors in the galactose (GAL) network rather than global factors. Results using a constitutively active GAL network are in overall agreement with findings with the wild-type network. We find that the local chromatin environment of the reporter has a significant effect on the observed phenotype. Genome sequencing, chromatin immunoprecipitation (ChIP)-qPCR, and sporulation analysis provide further insights into the epigenetic and genetic contributors to the expression changes observed. Our work provides a comprehensive example of the role played by epigenetic mechanisms on gene network evolution.

Targeting LncDACH1 promotes cardiac repair and regeneration after myocardium infarction.

Neonatal mammalian heart maintains a transient regeneration capacity after birth, whereas this regeneration ability gradually loses in the postnatal heart. Thus, the reactivation of cardiomyocyte proliferation is emerging as a key strategy for inducing heart regeneration in adults. We have reported that a highly conserved long noncoding RNA (lncRNA) LncDACH1 was overexpressed in the failing hearts. Here, we found that LncDACH1 was gradually upregulated in the postnatal hearts. Cardiac-specific overexpression of LncDACH1 (TG) in mice suppressed neonatal heart regeneration and worsened cardiac function after apical resection. Conversely, in vivo cardiac conditional knockout of LncDACH1 (CKO) and adenovirus-mediated silencing of endogenous LncDACH1 reactivated cardiomyocyte-proliferative potential and promoted heart regeneration after myocardial infarction (MI) in juvenile and adult mice. Mechanistically, LncDACH1 was found to directly bind to protein phosphatase 1 catalytic subunit alpha (PP1A), and in turn, limit its dephosphorylation activity. Consistently, PP1A siRNA or pharmacological blockers of PP1A abrogated cardiomyocyte mitosis induced by LncDACH1 silencing. Furthermore, LncDACH1 enhanced yes-associated protein 1 (YAP1) phosphorylation and reduced its nuclear translocation by binding PP1A. Verteporfin, a YAP1 inhibitor decreased LncDACH1 silencing-induced cardiomyocyte proliferation. In addition, targeting a conserved fragment of LncDACH1 caused cell cycle re-entry of human iPSC-derived cardiomyocytes. Collectively, LncDACH1 governs heart regeneration in postnatal and ischemic hearts via regulating PP1A/YAP1 signal, which confers a novel therapeutic strategy for ischemic heart diseases.

Stochastic modeling of aging cells reveals how damage accumulation, repair, and cell-division asymmetry affect clonal senescence and population fitness.

BACKGROUND: Asymmetry during cellular division, both in the uneven partitioning of damaged cellular components and of cell volume, is a cell biological phenomenon experienced by many unicellular organisms. Previous work based on a deterministic model claimed that such asymmetry in the partitioning of cell volume and of aging-associated damage confers a fitness benefit in avoiding clonal senescence, primarily by diversifying the cellular population. However, clonal populations of unicellular organisms are already naturally diversified due to the inherent stochasticity of biological processes. RESULTS: Applying a model of aging cells that accounts for natural cell-to-cell variations across a broad range of parameter values, here we show that the parameters directly controlling the accumulation and repair of damage are the most important factors affecting fitness and clonal senescence, while the effects of both segregation of damaged components and division asymmetry are frequently minimal and generally context-dependent. CONCLUSIONS: We conclude that damage segregation and division asymmetry, perhaps counterintuitively, are not necessarily beneficial from an evolutionary perspective.

Insights into Bidirectional Gene Expression Control Using the Canonical GAL1/GAL10 Promoter.

Despite advances made in understanding the effects of promoter structure on transcriptional activity, limited knowledge exists regarding the role played by chromatin architecture in transcription. Previous work hypothesized that transcription from the bidirectional GAL1/GAL10 promoter is controlled through looping of its UAS region around a nonstandard nucleosome. Here, by editing the GAL1/GAL10 promoter at high resolution, we provide insights into bidirectional expression control. We demonstrate that the first and fourth Gal4 binding sites within the UAS do not functionally contribute to promoter activation. Instead, these sites, along with nearby regulatory regions, contribute to the directional regulation of gene expression. Furthermore, Gal4 binding to the third binding site is critical for gene expression, while binding to the other three sites is not sufficient for transcriptional activation. Because the GAL1/GAL10 UAS can activate gene expression in many eukaryotes, the regulatory mechanism presented is expected to operate broadly across the eukaryotic clade.

Multi-component gene network design as a survival strategy in diverse environments.

BACKGROUND: Gene-environment interactions are often mediated though gene networks in which gene expression products interact with other network components to dictate network activity levels, which in turn determines the fitness of the host cell in specific environments. Even though a gene network is the right context for studying gene-environment interactions, we have little understanding on how systematic genetic perturbations affects fitness in the context of a gene network. RESULTS: Here we examine the effect of combinatorial gene dosage alterations on gene network activity and cellular fitness. Using the galactose utilization pathway as a model network in diploid yeast, we reduce the copy number of four regulatory genes (GAL2, GAL3, GAL4, GAL80) from two to one, and measure the activity of the perturbed networks. We integrate these results with competitive fitness measurements made in six different rationally-designed environments containing different galactose concentrations representing the natural induction spectrum of the galactose network. In the lowest galactose environment, we find a nonlinear relationship between gene expression and fitness while high galactose environments lead to a linear relationship between the two with a saturation regime reached at a sufficiently high galactose concentration. We further uncover environment-specific relevance of the different network components for dictating the relationship between the network activity and organismal fitness, indicating that none of the network components are redundant. CONCLUSIONS: These results provide experimental support to the hypothesis that dynamic changes in the environment throughout natural evolution is key to structuring natural gene networks in a multi-component fashion, which robustly provides protection against population extinction in different environments.

The Systems Biology of Single-Cell Aging.

Aging is a leading cause of human morbidity and mortality, but efforts to slow or reverse its effects are hampered by an incomplete understanding of its multi-faceted origins. Systems biology, the use of quantitative and computational methods to understand complex biological systems, offers a toolkit well suited to elucidating the root cause of aging. We describe the known components of the aging network and outline innovative techniques that open new avenues of investigation to the aging research community. We propose integration of the systems biology and aging fields, identifying areas of complementarity based on existing and impending technological capabilities.

Fundamental Characteristics of Single-Cell Aging in Diploid Yeast.

Single-cell-level experimentation can elucidate key biological insights about cellular aging that are masked in population-level studies. However, the extensive time requirement of tracking single cells has historically prevented their long-term longitudinal observation. Using a microfluidic device that automates microscopic monitoring of diploid Saccharomyces cerevisiae cells throughout their replicative lifespan, here we report the fundamental characteristics of single-cell aging for diploid yeast. We find that proteins with short versus long half-lives exhibit distinct dynamics as cells age and that the intercellular gene expression noise increases during aging, whereas the intracellular noise stays unchanged. A stochastic model provides quantitative mechanistic insights into the observed noise dynamics and sheds light on the age-dependent intracellular noise differences between diploid and haploid yeast. Our work elucidates how a set of canonical phenotypes dynamically change while the host cells are aging in real time, providing essential insights for a comprehensive understanding on and control of lifespan at the single-cell level.

Noise reduction as an emergent property of single-cell aging.

Noise-induced heterogeneity in gene expression is an inherent reality for cells. However, it is not well understood how noise strength changes for a single gene while the host cell is aging. Using a state-of-the-art microfluidic platform, we measure noise dynamics in aging yeast cells by tracking the generation-specific activity of the canonical GAL1 promoter. We observe noise reduction during normal aging of a cell, followed by a short catastrophe phase in which noise increased. We hypothesize that aging-associated increases in chromatin state transitions are behind the observed noise reduction and a stochastic model provides quantitative support to the proposed mechanism. Noise trends measured from strains with altered GAL1 promoter dynamics (constitutively active, synthetic with nucleosome-disfavoring sequences, and in the absence of RPD3, a global remodeling regulator) lend further support to our hypothesis. Observing similar noise dynamics from a different promoter (HHF2) provides support to the generality of our findings.Gene expression is a noisy process, but it is not known how noise in gene expression changes during the aging of single cells. Here the authors show that noise decreases during normal aging, and provide support for aging-associated increases in chromatin state transitions governing noise reduction.

A Precise Genome Editing Method Reveals Insights into the Activity of Eukaryotic Promoters.

Despite the availability of whole-genome sequences for almost all model organisms, making faithful predictions of gene expression levels based solely on the corresponding promoter sequences remains a challenge. Plasmid-based approaches and methods involving selection markers are not ideal due to copy-number fluctuations and their disruptive nature. Here, we present a genome editing method using the CRISPR/Cas9 complex and elucidate insights into the activity of canonical promoters in live yeast cells. The method involves the introduction of a novel cut site into a specific genomic location, followed by the integration of an edited sequence into the same location in a scarless manner. Using this method to edit the GAL1 and GAL80 promoter sequences, we found that the relative positioning of promoter elements was critically important for setting promoter activity levels in single cells. The method can be extended to other organisms to decode genotype-phenotype relationships in various gene networks.

Noise reduction facilitated by dosage compensation in gene networks.

Genetic noise together with genome duplication and volume changes during cell cycle are significant contributors to cell-to-cell heterogeneity. How can cells buffer the effects of these unavoidable epigenetic and genetic variations on phenotypes that are sensitive to such variations? Here we show that a simple network motif that is essential for network-dosage compensation can reduce the effects of extrinsic noise on the network output. Using natural and synthetic gene networks with and without the network motif, we measure gene network activity in single yeast cells and find that the activity of the compensated network is significantly lower in noise compared with the non-compensated network. A mathematical analysis provides intuitive insights into these results and a novel stochastic model tracking cell-volume and cell-cycle predicts the experimental results. Our work implies that noise is a selectable trait tunable by evolution.

A cell size- and cell cycle-aware stochastic model for predicting time-dynamic gene network activity in individual cells.

BACKGROUND: Despite the development of various modeling approaches to predict gene network activity, a time dynamic stochastic model taking into account real-time changes in cell volume and cell cycle stages is still missing. RESULTS: Here we present a stochastic single-cell model that can be applied to any eukaryotic gene network with any number of components. The model tracks changes in cell volume, DNA replication, and cell division, and dynamically adjusts rates of stochastic reactions based on this information. By tracking cell division, the model can maintain cell lineage information, allowing the researcher to trace the descendants of any single cell and therefore study cell lineage effects. To test the predictive power of our model, we applied it to the canonical galactose network of the yeast Saccharomyces cerevisiae. Using a minimal set of free parameters and across several galactose induction conditions, the model effectively captured several details of the experimentally-obtained single-cell network activity levels as well as phenotypic switching rates. CONCLUSION: Our model can readily be customized to model any gene network in any of the commonly used cells types, offering a novel and user-friendly stochastic modeling capability to the systems biology field.

Network-dosage compensation topologies as recurrent network motifs in natural gene networks.

BACKGROUND: Global noise in gene expression and chromosome duplication during cell-cycle progression cause inevitable fluctuations in the effective number of copies of gene networks in cells. These indirect and direct alterations of network copy numbers have the potential to change the output or activity of a gene network. For networks whose specific activity levels are crucial for optimally maintaining cellular functions, cells need to implement mechanisms to robustly compensate the effects of network dosage fluctuations. RESULTS: Here, we determine the necessary conditions for generalized N-component gene networks to be network-dosage compensated and show that the compensation mechanism can robustly operate over large ranges of gene expression levels. Furthermore, we show that the conditions that are necessary for network-dosage compensation are also sufficient. Finally, using genome-wide protein-DNA and protein-protein interaction data, we search the yeast genome for the abundance of specific dosage-compensation motifs and show that a substantial percentage of the natural networks identified contain at least one dosage-compensation motif. CONCLUSIONS: Our results strengthen the hypothesis that the special network topologies that are necessary for network-dosage compensation may be recurrent network motifs in eukaryotic genomes and therefore may be an important design principle in gene network assembly in cells.

Coverage tradeoffs and power estimation in the design of whole-genome sequencing experiments for detecting association.

MOTIVATION: Whole-genome sequencing (WGS) allows direct interrogation of previously undetected uncommon or rare variants, which potentially contribute to the missing heritability of human disease. However, cost of sequencing large numbers of samples limits its application in case-control association studies. Here, we describe theoretical and empirical design considerations for such sequencing studies, aimed at maximizing the power of detecting association under the constraint of study-wide cost. RESULTS: We consider two cost regimes. First, assuming cost is proportional to the total amount of base pairs to be sequenced across all samples, which is a practical model for whole-genome sequencing, we explored the tradeoff in terms of study power between increasing the number of subjects and increasing depth coverage. We demonstrate that the optimal power of detecting association is achieved at medium depth coverage under a wide range of realistic conditions for case-only sequencing designs. Second, if cost is fixed per sample, which is approximately the case in exome sequencing, we show that in a simple case+control sequencing study, the optimal design should include cases totaling 1/e of all subjects. AVAILABILITY: A web tool implementing the methods is available at http://www.cs.columbia.edu/~itsik/OPERA/.