Effects of conservative-militant defection strategies on the evolution of cooperation in social dilemma.

Competition in the international arena and business realm offers avenues for individual growth and advancement. Individuals using different means of competition can obtain unequal rewards. This paper claims that when no consensus is reached in business activities, defectors will choose conservative or militant defection strategies during market competition. Conservative defectors, who are in a comparatively weak position, need to pay the costs brought by market share losses. However, their personal abilities cannot be ignored, which prompts them to bravely choose the conservative defection strategy. This brings rewards to conservative defectors. Militant defectors, typically in stronger positions, also receive greater rewards. Research results establish an evolutionary game model of three strategies, the cooperation strategy, the conservative defection strategy, and the militant defection strategy. After the system is stable, this model displays two stable states. Through numerical simulation, it can be found that the personal abilities of conservative defectors play a decisive role in promoting cooperation. However, the market share losses of conservative defectors have periodical impacts on cooperation. Moreover, the threats of militant defectors to cooperation should be comprehensively considered in combination with the personal abilities of conservative defectors.

Transcriptional bursting dynamics in gene expression.

Gene transcription is a stochastic process that occurs in all organisms. Transcriptional bursting, a critical molecular dynamics mechanism, creates significant heterogeneity in mRNA and protein levels. This heterogeneity drives cellular phenotypic diversity. Currently, the lack of a comprehensive quantitative model limits the research on transcriptional bursting. This review examines various gene expression models and compares their strengths and weaknesses to guide researchers in selecting the most suitable model for their research context. We also provide a detailed summary of the key metrics related to transcriptional bursting. We compared the temporal dynamics of transcriptional bursting across species and the molecular mechanisms influencing these bursts, and highlighted the spatiotemporal patterns of gene expression differences by utilizing metrics such as burst size and burst frequency. We summarized the strategies for modeling gene expression from both biostatistical and biochemical reaction network perspectives. Single-cell sequencing data and integrated multiomics approaches drive our exploration of cutting-edge trends in transcriptional bursting mechanisms. Moreover, we examined classical methods for parameter estimation that help capture dynamic parameters in gene expression data, assessing their merits and limitations to facilitate optimal parameter estimation. Our comprehensive summary and review of the current transcriptional burst dynamics theories provide deeper insights for promoting research on the nature of cell processes, cell fate determination, and cancer diagnosis.

Screening and modification of (+)-germacrene A synthase for the production of the anti-tumor drug (-)-ß-elemene in engineered Saccharomyces cerevisiae.

(-)-ß-Elemene is a primary bioactive compound derived from Curcuma wenyujin and has been widely utilized as an anti-tumor agent for various types of cancer. Due to the inefficiency of plant extraction methods for ß-elemene, significant efforts have been directed toward the heterogeneous biosynthesis of ß-elemene using microbial cell factories. However, there has been less emphasis on the stereochemical configuration of germacrene A and its rearranged product, ß-elemene. In this study, we constructed a yeast cell factory to produce (-)-ß-elemene by optimizing the mevalonate pathway and screening for germacrene A synthases (GASs) from both plant and microbial sources. Notably, we discovered that the rearranged products of GASs exhibited different conformations, and only (+)-germacrene A produced by plant-derived GASs could rearrange to form (-)-ß-elemene. Building on this discovery, we further investigated the catalytic mechanisms of GASs and developed an efficient catalytic gene module for generating (+)-germacrene A. Ultimately, the engineered yeast produced 1152 mg/L of (-)-ß-elemene, marking the highest titer reported in yeast to date. Overall, this work highlights the differences in the stereoconformations of catalytic products between plant- and microbial-derived germacrene A synthases and establishes a foundation for the green and efficient production of ß-elemene with a specific stereochemical configuration.

The media risk of infodemic in public health emergencies: Consequences and mitigation approaches.

This study explores the nuances of information sharing in the context of infodemics, with a concentrated examination of the effects of opinion leaders and information attention on users' disposition towards sharing information during public health emergencies. The research adopts a quantitative methodology, employing Structural Equation Modeling (SEM) to empirically test the proposed hypotheses. By employing a rigorous analytical framework, the research also scrutinizes the mediating role of risk perception in shaping users' intentions to disseminate information related to public health emergencies. Additionally, it investigates the moderating effect of perceived usefulness, shedding light on how it influences the strength of the relationship between information attention and risk perception. The findings underscore the significance for public health communication strategies, emphasizing targeted messaging utilizing trusted opinion leaders and emphasizing information utility to foster responsible sharing. This research contributes to the academic conversation on infodemic management, providing empirical insights to guide policies and practices in mitigating misinformation during public health emergencies.

Flexible Resistive Gas Sensor Based on Molybdenum Disulfide-Modified Polypyrrole for Trace NO2 Detection.

High sensitivity and selectivity and short response and recovery times are important for practical conductive polymer gas sensors. However, poor stability, poor selectivity, and long response times significantly limit the applicability of single-phase conducting polymers, such as polypyrrole (PPy). In this study, PPy/MoS2 composite films were prepared via chemical polymerization and mechanical blending, and flexible thin-film resistive NO2 sensors consisting of copper heating, fluorene polyester insulating, and PPy/MoS2 sensing layers with a silver fork finger electrode were fabricated on a flexible polyimide substrate using a flexible electronic printer. The PPy/MoS2 composite films were characterized using X-ray diffraction, Fourier-transform infrared spectroscopy, and field-emission scanning electron microscopy. A home-built gas sensing test platform was built to determine the resistance changes in the composite thin-film sensor with temperature and gas concentration. The PPy/MoS2 sensor exhibited better sensitivity, selectivity, and stability than a pure PPy sensor. Its response to 50 ppm NO2 was 38% at 150 °C, i.e., 26% higher than that of the pure PPy sensor, and its selectivity and stability were also higher. The greater sensitivity was attributed to p-n heterojunction formation after MoS2 doping and more gas adsorption sites. Thus, PPy/MoS2 composite film sensors have good application prospects.

Dynamic analysis and optimal control of knowledge diffusion model in regional innovation ecosystem under digitalization.

Knowledge diffusion in regional innovation ecosystems is an important factor that influences the regional innovation efficiency. In regional innovation ecosystems under digital empowerment, the knowledge diffusion enables the optimal allocation of innovation resources and promotes the sustainable development and ecological evolution of regional innovation ecosystems. In this paper, a SEIR (Susceptible-Exposed-Infected-Recovered) model is proposed for knowledge diffusion in regional innovation ecosystems under digitization. The basic reproduction number of the proposed model is calculated and its stability is validated. Finally, the expressions for the optimal control system and the optimal control parameters are presented. According to the research conclusions of this paper, the knowledge-diffusion ability of innovation agents in an innovation ecosystem affects the knowledge diffusion in a system; the contact rate between innovation agents affects the efficiency of knowledge diffusion in the system and the structure of the system; the digital transmission ability of innovation agents affects the breadth of knowledge diffusion in the system; and the self-learning ability of innovation agents affects the efficiency of knowledge diffusion in the system.The digital technologies help heterogeneous innovation agents in regional innovation ecosystems to break down the knowledge silos. At the same time, the digital technologies enhance the ability of innovation agents to absorb and learn knowledge in regional innovation ecosystems under digitization, thereby increasing the infection rate of knowledge diffusion in such systems.These conclusions extend the theoretical boundaries of innovation ecosystems and knowledge diffusion and offer management implications for enterprises and governments in decision-making.

Nanoparticle-hydrogel composite as dual-drug delivery system for the potential application of corneal graft rejection.

Immune rejection remains the major cause of corneal graft failure. Immunosuppressants (such as rapamycin; RAPA) adjunctive to antibiotics (such as levofloxacin hydrochloride; Lev) are a clinical mainstay after corneal grafts but suffer from poor ocular bioavailability associated with severe side effects. In this study, we fabricated a Lev@RAPA micelle loaded cationic peptide-based hydrogel (NapFFKK) as a dual-drug delivery system by integrating RAPA micelles with Lev into a cationic NapFFKK hydrogel to potentially reduced the risk of corneal graft rejection. The properties of the resulting hydrogels were characterized using transmission electronmicroscopy and rheometer. Lev@RAPA micelles loaded NapFFKK hydrogel provided sustained in vitro drug release without compromising their inherent pharmacological activities. Topical instillation of Lev@RAPA micelles loaded NapFFKK hydrogel resulted in the great ocular tolerance and extended precorneal retention over 60 min, thus significantly enhancing the ocular bioavailability of both Lev and RAPA. Overall, such dual-drug delivery system might be a promising formulation for the suppression of corneal graft failure.

Exploration of identifying individual tumor tissue based on probabilistic model.

Variations in the tumor genome can result in allelic changes compared to the reference profile of its homogenous body source on genetic markers. This brings a challenge to source identification of tumor samples, such as clinically collected pathological paraffin-embedded tissue and sections. In this study, a probabilistic model was developed for calculating likelihood ratio (LR) to tackle this issue, which utilizes short tandem repeat (STR) genotyping data. The core of the model is to consider tumor tissue as a mixture of normal and tumor cells and introduce the incidence of STR variants (φ) and the percentage of normal cells (Mxn) as a priori parameters when performing calculations. The relationship between LR values and φ or Mxn was also investigated. Analysis of tumor samples and reference blood samples from 17 colorectal cancer patients showed that all samples had Log 10(LR) values greater than 1014. In the non-contributor test, 99.9% of the quartiles had Log 10(LR) values less than 0. When the defense's hypothesis took into account the possibility that the tumor samples came from the patient's relatives, LR greater than 0 was still obtained. Furthermore, this study revealed that LR values increased with decreasing φ and increasing Mxn. Finally, LR interval value was provided for each tumor sample by considering the confidence interval of Mxn. The probabilistic model proposed in this paper could deal with the possibility of tumor allele variability and offers an evaluation of the strength of evidence for determining tumor origin in clinical practice and forensic identification.

Dynamic analysis and optimal control of stochastic information cross-dissemination and variation model with random parametric perturbations.

Information dissemination has a significant impact on social development. This paper considers that there are many stochastic factors in the social system, which will result in the phenomena of information cross-dissemination and variation. The dual-system stochastic susceptible-infectious-mutant-recovered model of information cross-dissemination and variation is derived from this problem. Afterward, the existence of the global positive solution is demonstrated, sufficient conditions for the disappearance of information and its stationary distribution are calculated, and the optimal control strategy for the stochastic model is proposed. The numerical simulation supports the results of the theoretical analysis and is compared to the parameter variation of the deterministic model. The results demonstrate that cross-dissemination of information can result in information variation and diffusion. Meanwhile, white noise has a positive effect on information dissemination, which can be improved by adjusting the perturbation parameters.

An innovative label-free electrochemical aptamer sensor: utilizing Ti3C2Tx/MoS2/Au NPs for accurate interleukin-6 detection.

In the medical field, changes in interleukin-6 (IL-6) concentration serve as essential biomarkers for monitoring and diagnosing various conditions, including acute inflammatory responses such as those seen in trauma and burns, and chronic illnesses like cancer. This paper detailed a label-free electrochemical aptamer sensor designed for IL-6 quantification. A composite material consisting of Ti3C2Tx and MoS2 was successfully synthesized to fabricate this sensor. The synergistic effect of MoS2's catalytic action on hydrogen peroxide (H2O2), used as a signalling marker, when combined with the exceptional conductivity and large specific surface area of Ti3C2Tx, not only enables an increased loading of MoS2 but also significantly boosts the electrochemical response. The in situ-reduced Au NPs provided stable immobilization sites for DNA aptamers (DNAapt) and facilitated electron transfer, ensuring accurate IL-6 recognition. Under optimal conditions, the aptamer sensor exhibited a wide linear range (5 pg/mL to 100 ng/mL) and a low limit of detection (LOD) of 2.9 pg/mL. Its sensing performance in human serum samples highlights its potential as a promising clinical analysis tool.

General anesthetic agents induce neurotoxicity through oligodendrocytes in the developing brain.

General anesthetic agents can impact brain function through interactions with neurons and their effects on glial cells. Oligodendrocytes perform essential roles in the central nervous system, including myelin sheath formation, axonal metabolism, and neuroplasticity regulation. They are particularly vulnerable to the effects of general anesthetic agents resulting in impaired proliferation, differentiation, and apoptosis. Neurologists are increasingly interested in the effects of general anesthetic agents on oligodendrocytes. These agents not only act on the surface receptors of oligodendrocytes to elicit neuroinflammation through modulation of signaling pathways, but also disrupt metabolic processes and alter the expression of genes involved in oligodendrocyte development and function. In this review, we summarize the effects of general anesthetic agents on oligodendrocytes. We anticipate that future research will continue to explore these effects and develop strategies to decrease the incidence of adverse reactions associated with the use of general anesthetic agents.

Design, Synthesis, Biological Evaluation, and Molecular Docking Studies of Pleuromutilin Derivatives Containing Thiazole.

In this study, we designed and synthesized a series of pleuromutilin derivatives containing thiazole. The in vitro antimicrobial efficacy of these synthesized compounds was examined by using four strains. Compared with tiamulin (MIC = 0.25 µg/mL), compound 14 exhibited potency in inhibiting MRSA growth (MIC = 0.0625 µg/mL) in these derivatives. Meanwhile, the time-killing kinetics further demonstrated that compound 14 could efficiently inhibit the MRSA growth. After exposure at 4 × MIC, the postantibiotic effect (PAE) of compound 14 was 1.29 h. Additionally, in thigh-infected mice, compound 14 exhibited a more potent antibacterial efficacy (-1.78 ± 0.28 log10 CFU/g) in reducing MRSA load compared to tiamulin (-1.21 ± 0.23 log10 CFU/g). Moreover, the MTT assay on RAW 264.7 cells demonstrated that compound 14 (8 µg/mL) had no significant cytotoxicity. Docking studies indicated the strong affinity of compound 14 toward the 50S ribosomal subunit, with a binding free energy of -9.63 kcal/mol. Taken together, it could be deduced that compound 14 was a promising candidate for treating MRSA infections.

A Self-Amplifying ROS-Responsive Nanoplatform for Simultaneous Cuproptosis and Cancer Immunotherapy.

Cuproptosis is an emerging cell death pathway that depends on the intracellular Cu ions. Elesclomol (ES) as an efficient Cu ionophore can specifically transport Cu into mitochondria and trigger cuproptosis. However, ES can be rapidly removed and metabolized during intravenous administration, leading to a short half-life and limited tumor accumulation, which hampers its clinical application. Here, the study develops a reactive oxygen species (ROS)-responsive polymer (PCP) based on cinnamaldehyde (CA) and polyethylene glycol (PEG) to encapsulate ES-Cu compound (EC), forming ECPCP. ECPCP significantly prolongs the systemic circulation of EC and enhances its tumor accumulation. After cellular internalization, the PCP coating stimulatingly dissociates exposing to the high-level ROS, and releases ES and Cu, thereby triggering cell death via cuproptosis. Meanwhile, Cu2+-stimulated Fenton-like reaction together with CA-stimulated ROS production simultaneously breaks the redox homeostasis, which compensates for the insufficient oxidative stress treated with ES alone, in turn inducing immunogenic cell death of tumor cells, achieving simultaneous cuproptosis and immunotherapy. Furthermore, the excessive ROS accelerates the stimuli-dissociation of ECPCP, forming a positive feedback therapy loop against tumor self-alleviation. Therefore, ECPCP as a nanoplatform for cuproptosis and immunotherapy improves the dual antitumor mechanism of ES and provides a potential optimization for ES clinical application.

Reprogramming the Metabolism of Yeast for High-Level Production of Miltiradiene.

Miltiradiene serves as a crucial precursor in the synthesis of various high-value abietane-type diterpenes, exhibiting diverse pharmacological activities. Previous efforts to enhance miltiradiene production have primarily focused on the mevalonate acetate (MVA) pathway. However, limited emphasis has been placed on optimizing the supply of acetyl-CoA and NADPH. In this study, we constructed a platform yeast strain for miltiradiene production by reinforcing the biosynthetic pathway of geranylgeranyl diphosphate (GGPP) and acetyl-CoA, and addressing the imbalance between the supply and demand of the redox cofactor NADPH within the cytoplasm, resulting in an increase in miltiradiene yield to 1.31 g/L. Furthermore, we conducted modifications to the miltiradiene synthase fusion protein tSmKSL1-CfTPS1. Finally, the comprehensive engineering strategies and protein modification strategies culminated in 1.43 g/L miltiradiene in the engineered yeast under shake flask culture conditions. Overall, our work established efficient yeast cell factories for miltiradiene production, providing a foothold for heterologous biosynthesis of abietane-type diterpenes.

Identification of Plasma hsa_circ_0001230 and hsa_circ_0023879 as Potential Novel Biomarkers for Focal Segmental Glomerulosclerosis and circRNA-miRNA-mRNA Network Analysis.

INTRODUCTION: Focal segmental glomerulosclerosis (FSGS) is a common glomerulopathy with an unclear mechanism. The demand for FSGS clinical diagnostic biomarkers has not yet been met. Circular RNA (circRNA) is a novel non-coding RNA with multiple functions, but its diagnostic value for FSGS remains unexplored. This study aimed to identify circRNAs that could aid in early clinical diagnosis and to investigate their mechanisms in podocyte injury. METHODS: The signature of plasma circRNAs for FSGS was identified by circRNA microarray. The existence of circRNAs was confirmed by quantitative real-time polymerase chain reaction (qRT-PCR), RNase R assay, and DNA sequencing. Plasma levels of circRNAs were evaluated by qRT-PCR. The diagnostic value was appraised by the receiver operating characteristic curve. The circRNA-miRNA-mRNA network was built with Cytoscape 7.3.2. Statistically significant differences were calculated by the Mann-Whitney U test. RESULTS: A total of 493 circRNAs (165 upregulated, 328 downregulated) were differentially expressed in the plasma of FSGS patients (n = 3) and normal controls (n = 3). Eight candidate circRNAs were demonstrated to be circular and stable transcripts. Among them, hsa_circ_0001230 and hsa_circ_0023879 were significantly upregulated in FSGS patients (n = 29) compared to normal controls (n = 51). The areas under the curve value of hsa_circ_0001230 and hsa_circ_0023879 were 0.668 and 0.753, respectively, while that of the two-circRNA panel was 0.763. The RNA pull-down analysis revealed that hsa_circ_0001230 and hsa_circ_0023879 could sponge hsa-miR-106a. Additionally, hsa_circ_0001230 and hsa_circ_0023879 positively regulated hsa-miR-106a target genes phosphatase and tensin homolog (PTEN) and Bcl-2-like protein 11 (BCL2L11) in podocytes. CONCLUSION: hsa_circ_0001230 and hsa_circ_0023879 are novel blood biomarkers for FSGS. They may regulate podocyte apoptosis by competitively binding to hsa-miR-106a.

Core-Shell MnFe Nanocatalyst Derived from Prussian Blue Analogs for Peroxymonosulfate Activation: Nonradical Mechanism and Bimetallic Valence Cycle.

Sulfamethazine (SAT) is widely present in sediment, soil, rivers, and groundwater. Unfortunately, traditional water treatment technologies are inefficient at eliminating SAT from contaminated water. Therefore, developing an effective and ecologically friendly treatment procedure to effectively remove SAT is critical. This has raised concerns about its potential impact on the environment and human health. In this study, metal-organic-inorganic composites consisting of graphene-encapsulated Fe-Mn metal catalyst (Mn3Fe1-NC) were synthesized by calcining MnFe Prussian blue analogs (PBA) under a nitrogen atmosphere. The composites were applied to activate peroxymonosulfate (PMS) and facilitate the degradation of SAT in aquatic environments. The Mn3Fe1-NC, dosed with 5 mg, in combination with PMS, dosed with 1.5 mmol L-1, achieved a 91.8% degradation efficiency of SAT. The transformation of the CN skeleton led to the formation of a carbon shell structure, which consequently reduced metal ion leaching from the material. At various pH levels, the iron and manganese ions were observed to leach out at levels lower than 0.1392 and 0.0580 mg L-1, respectively. In contrast, the Mn3Fe1-NC was found to be minimally impacted by pH levels and coexisting ions present in the aqueous environment. Radical burst experiments and electrochemical analysis tests verified that degradation primarily occurs through the nonradical pathway of electron transfer. The active sites responsible for this process were identified as the Mn (IV) and graphitic-N atoms on the material, which facilitate direct electron transfer. Additionally, the presence of Fe atoms promotes the valence cycling of Mn atoms. This study introduces new insights into the reaction mechanism and the constitutive relationship of catalytic centers in nonradical oxidation reactions.

Using simulated microhaplotype genotyping data to evaluate the value of machine learning algorithms for inferring DNA mixture contributor numbers.

Inferring the number of contributors (NoC) is a crucial step in interpreting DNA mixtures, as it directly affects the accuracy of the likelihood ratio calculation and the assessment of evidence strength. However, obtaining the correct NoC in complex DNA mixtures remains challenging due to the high degree of allele sharing and dropout. This study aimed to analyze the impact of allele sharing and dropout on NoC inference in complex DNA mixtures when using microhaplotypes (MH). The effectiveness and value of highly polymorphic MH for NoC inference in complex DNA mixtures were evaluated through comparing the performance of three NoC inference methods, including maximum allele count (MAC) method, maximum likelihood estimation (MLE) method, and random forest classification (RFC) algorithm. In this study, we selected the top 100 most polymorphic MH from the Southern Han Chinese (CHS) population, and simulated over 40 million complex DNA mixture profiles with the NoC ranging from 2 to 8. These profiles involve unrelated individuals (RM type) and related pairs of individuals, including parent-offspring pairs (PO type), full-sibling pairs (FS type), and second-degree kinship pairs (SE type). Our results indicated that how the number of detected alleles in DNA mixture profiles varied with the markers' polymorphism, kinship's involvement, NoC, and dropout settings. Across different types of DNA mixtures, the MAC and MLE methods performed best in the RM type, followed by SE, FS, and PO types, while RFC models showed the best performance in the PO type, followed by RM, SE, and FS types. The recall of all three methods for NoC inference were decreased as the NoC and dropout levels increased. Furthermore, the MLE method performed better at low NoC, whereas RFC models excelled at high NoC and/or high dropout levels, regardless of the availability of a priori information about related pairs of individuals in DNA mixtures. However, the RFC models which considered the aforementioned priori information and were trained specifically on each type of DNA mixture profiles, outperformed RFC_ALL model that did not consider such information. Finally, we provided recommendations for model building when applying machine learning algorithms to NoC inference.

A 2-year mental health follow-up study subsequent to COVID-19.

The COVID-19 pandemic has profoundly impacted the mental health and education of college students. This study examined the interrelationships among loneliness, resilience, and COVID-19 fear among college students in Northern Michigan, a region of the United States severely affected by the pandemic. Data were collected from two student cohorts (n = 258), with half surveyed in early 2022 and the other half in mid-2022, two years after pandemic's onset. The Omicron wave peaked in Michigan in January 2022, but by June 2022, cases, hospitalizations, and deaths had significantly declined. Students completed measures of loneliness, resilience, learning difficulty, and psychological symptoms. Key findings are: 1) Participants' fear, loneliness, and academic difficulty decreased over time, reflecting fluctuations in acute situational and emotional states; 2) Unexpectedly, resilience declined from early to mid-2022, suggesting its diminishing protective role under prolonged, pandemic-induced stress; 3) Despite improvements, students continued reporting high academic difficulties. Loneliness, heightened fear, and dampened happiness together contributed to greater academic difficulties; 4) Pre-existing sex differences equalized two years after the pandemic's onset. While modest improvements were noted, enduring academic and mental health impacts signal a need for continued support.

General anesthetic agents induce neurotoxicity through astrocytes.

ABSTRACT: Neuroscientists have recognized the importance of astrocytes in regulating neurological function and their influence on the release of glial transmitters. Few studies, however, have focused on the effects of general anesthetic agents on neuroglia or astrocytes. Astrocytes can also be an important target of general anesthetic agents as they exert not only sedative, analgesic, and amnesic effects but also mediate general anesthetic-induced neurotoxicity and postoperative cognitive dysfunction. Here, we analyzed recent advances in understanding the mechanism of general anesthetic agents on astrocytes, and found that exposure to general anesthetic agents will destroy the morphology and proliferation of astrocytes, in addition to acting on the receptors on their surface, which not only affect Ca2+ signaling, inhibit the release of brain-derived neurotrophic factor and lactate from astrocytes, but are even involved in the regulation of the pro- and anti-inflammatory processes of astrocytes. These would obviously affect the communication between astrocytes as well as between astrocytes and neighboring neurons, other neuroglia, and vascular cells. In this review, we summarize how general anesthetic agents act on neurons via astrocytes, and explore potential mechanisms of action of general anesthetic agents on the nervous system. We hope that this review will provide a new direction for mitigating the neurotoxicity of general anesthetic agents.

A novel nomogram for predicting the prolonged length of stay in post-anesthesia care unit after elective operation.

BACKGROUND: Prolonged length of stay in post-anesthesia care unit (PLOS in PACU) is a combination of risk factors and complications that can compromise quality of care and operating room efficiency. Our study aimed to develop a nomogram to predict PLOS in PACU of patients undergoing elective surgery. METHODS: Data from 24017 patients were collected. Least absolute shrinkage and selection operator (LASSO) was used to screen variables. A logistic regression model was built on variables determined by a combined method of forward selection and backward elimination. Nomogram was designed with the model. The nomogram performance was evaluated with the area under the receiver operating characteristic curve (AUC) for discrimination, calibration plot for consistency between predictions and actuality, and decision curve analysis (DCA) for clinical application value. RESULTS: A nomogram was established based on the selected ten variables, including age, BMI < 21 kg/m2, American society of Anesthesiologists Physical Status (ASA), surgery type, chill, delirium, pain, naloxone, operation duration and blood transfusion. The C-index value was 0.773 [95% confidence interval (CI) = 0.765 - 0.781] in the development set and 0.757 (95% CI = 0.744-0.770) in the validation set. The AUC was > 0.75 for the prediction of PLOS in PACU. The calibration curves revealed high consistencies between the predicted and actual probability. The DCA showed that if the threshold probability is over 10% , using the models to predict PLOS in PACU and implement intervention adds more benefit. CONCLUSIONS: This study presented a nomogram to facilitate individualized prediction of PLOS in PACU for patients undergoing elective surgery.