Given the high global disease burden of coronary artery disease (CAD), a major problem facing healthcare economic policy is identifying the most cost-effective diagnostic strategy for patients with suspected CAD. The aim of this review is to assess the long-term cost-effectiveness of coronary computed tomography angiography (CCTA) when compared with other diagnostic modalities and to define the cost and effective diagnostic utilization of computed tomography-fractional flow reserve (CT-FFR). A search was conducted through the MEDLINE database using PubMed with 16 of 119 manuscripts fitting the inclusion and exclusion criteria for review. An analysis of the data included in this review suggests that CCTA is a cost-effective strategy for both low risk acute chest pain patients presenting to the emergency department (ED) and low-to-intermediate risk stable chest pain outpatients. For patients with intermediate-to-high risk, CT-FFR is superior to CCTA in identifying clinically significant stenosis. In low-to-intermediate risk patients, CCTA provides a cost-effective diagnostic strategy with the potential to reduce economic burden and improve long-term health outcomes. CT-FFR should be utilized in intermediate-to-high risk patients with stenosis of uncertain clinical significance. Long-term analysis of cost-effectiveness and diagnostic utility is needed to determine the optimal balance between the cost-effectiveness and diagnostic utility of CT-FFR. Coronary artery disease (CAD) is the leading cause of death in the United States, often associated with angina, stroke, and myocardial infarction ,2. In thThe diagnosis of CAD is guided by several invasive and non-invasive imaging modalities that look for evidence of decreased myocardial perfusion, impaired myocardial contractility, and other anatomical changes. Coronary angiography (CAG) is considered the gold standard in the diagnosis of CAD, as it is both diagnostic and therapeutic . HoweverThere are alternative non-invasive options that provide diagnostic and prognostic information to guide risk stratification, subsequent testing, and disease intervention . Non-invCCTA has been recommended as a “gatekeeper” diagnostic test for invasive CAG ,10. It iIn recent years, the Coronary Artery Disease Reporting and Data System (CAD-RADS) classification has been developed to standardize the reporting of CCTA findings in the evaluation of CAD and to facilitate the decision-making process surrounding further patient management ,15. The The Prospective Multicenter Imaging Study for Evaluation of Chest Pain (PROMISE) trial revealed that CCTA used in conjunction with CAD-RADS classification can identify cases of prognostically significant lesions that would be otherwise missed by functional testing ,17. In lEstablishing the absence of CAD carries a high negative predictive value for MACE during index hospitalization and a low likelihood of such events in the next two years . AlternaA major question facing healthcare economic policy today is defining the role of CCTA in diagnosing CAD, especially in the light of national efforts to pursue more conservative diagnostic initiatives where “less is more” ,20,21. CA search was conducted through the MEDLINE database using PubMed. A total of 119 manuscripts were located in this database by using a combination of several key terms including “computed tomography,” “CT,” “coronary,” “angiography,” “CCTA,” and “cost-effectiveness.” Studies were selected if they conducted cost-effectiveness analysis (CEA) on the utility of CCTA in diagnosing CAD compared to other diagnostic modalities. The three inclusion criteria were determined as (1) the study must have employed their own data and/or data from a registry or healthcare institution to examine the cost-effectiveness of CCTA, (2) CAD must be the primary pathology being diagnosed by CCTA, and (3) all studies must be in English as demonstrated in the flow diagram  24]. Th. Th24]. In the U.S. alone, millions of patients present to the ED each year with complaints of acute chest pain, and many of these patients undergo unnecessary admission, additional testing, and inappropriate discharge, which leads to an increased economic burden on the healthcare system ,27,28,29Multiple studies meeting the inclusion criteria for this review attempted to assess the long-term utility of CCTA when used in acute chest pain patients presenting to the ED. Goehler et al. (2020) utilized a Markov simulation model based on patients with low-intermediate risk of ACS to assess the long-term cost-effectiveness of CCTA relative to standard of care (SOC) and other management strategies. These strategies included SOC , expedited ED discharge with close outpatient follow-up, and American College of Cardiology (ACC)/AHA guidelines . RelativLadapo et al. (2008) used a Monte-carlo microsimulation model to compare CCTA to SOC  in low risk patients with acute chest pain and found that CCTA was cost-saving in women  and associated with low incremental cost-effectiveness ratio (ICER) in men USD 6400/QALY) . This st00/QALY .Taken together, these results suggest that while CCTA may cost more upfront, and lead to increased revascularization rates, it may improve outcomes and provide a more cost-effective approach over a lifetime in low-to-intermediate risk patients. When compared to SOC, this is likely due to the ability of CCTA to safely exclude ACS in the ED, and prevent unnecessary downstream admission and testing, while also decreasing the time to correct diagnosis and identifying appropriate candidates for invasive CAG  23,27,2,29.For patients presenting with stable chest pain in the outpatient setting, functional testing with SPECT, stress echocardiography or exercise ECG has traditionally been used to diagnose CAD and act as a “gatekeeper” to invasive CAG. However, growing evidence suggests that in low-to-intermediate risk patients, CCTA may provide a more accurate and efficient diagnosis of CAD while improving health outcomes related to cardiovascular death and myocardial infarction  30,31,3,331,32. Lee et al. (2015) performed a retrospective cohort study comparing CCTA to SPECT in 1632 patients with a pretest probability between 10 and 90% that presented to the outpatient clinic with chest pain . A MarkoDewey and Hamm (2007) used a hypothetical patient cohort and a decision tree model to compare the use of CCTA, coronary artery calcium score (CACS), or stress MRI to traditional tests including exercise ECG, stress echocardiography, and invasive CAG . CCTA waSeveral studies included in this review also compared sequential diagnostic strategies involving CCTA or other modalities to evaluate patients with stable angina. Bertoldi et al. (2016) used a Markov simulation model to compare eleven different diagnostic strategies in a hypothetical patient cohort with pretest probabilities ranging from 20 to 70% . The diaCCTA has also demonstrated great diagnostic accuracy in several of the aforementioned studies, albeit not as accurate as the gold standard of coronary angiography . This isThere are a number of limitations to take into account when considering CCTA as a diagnostic strategy. First, although advancements in technology and image acquisition have led to a considerable reduction in CCTA-related radiation exposure over the last decade ,42,43, iCT-FFR is a novel non-invasive testing technique that applies computational fluid dynamics to traditional CCTA in order to predict pressure gradients across stenotic vessels. This allows CT-FFR to bridge the gap between CCTA and functional testing by measuring the hemodynamic significance of coronary artery stenoses. Recent meta-analyses have shown that CT-FFR demonstrates a 2-fold increase in specificity for flow-restricting lesions and an improved diagnostic index overall ,50,51. FA recent meta-analysis assessed the use of CCTA and CT-FFR in confirming or excluding ischemic CAD across different pretest probabilities . CCTA anDECT is an innovation in computed tomography technology that provides several benefits to the investigation of CAD when compared to single-energy computed tomography ,56. DECTThe investigation of CAD with DECT provides improvements to many limitations associated with single-energy computed tomography, while also providing the option for functional assessment of coronary stenoses. Moreover, emerging evidence suggests that dynamic myocardial perfusion imaging may be complementary to the use of CT-FFR in increasing specificity of CCTA for identifying functionally significant stenoses . HoweverArtificial Intelligence (AI) within the field of radiology has experienced extensive growth over the past decade, and with cardiac radiology experiencing sharp increases in imaging volume, AI applications have aimed to optimize workflow, increasing radiologists’ productivity while reducing cost and improving patient care . Most AIWith respect to anatomic testing, there are a number of machine learning applications that have shown potential to improve the diagnostic performance of CT-FFR ,64,65, aData from the above studies suggest that CCTA may be a cost-effective diagnostic strategy when used alone for the initial evaluation of CAD, or as part of a sequential diagnostic strategy. In low-to-intermediate risk patients with stable chest pain, CCTA provides a diagnostic option with the potential to reduce economic burden and improve long-term health outcomes when compared to functional testing. At pretest probabilities higher than 70-80%, CAG remains the most cost-effective option. Given the limited data in the current literature, and due to increased cost and added time to diagnosis, CT-FFR should be utilized in intermediate-to-high risk patients with stenosis of uncertain clinical significance. Long-term analysis of cost-effectiveness and diagnostic utility is needed in the future to determine the optimal balance between the cost-effectiveness and diagnostic utility of this new modality.While the above studies provide useful insight into the long-term benefits of anatomical testing compared to functional testing, there are several limitations to be considered. First, the simulation and decision-analytic models used in these studies rely on inherent assumptions that may not replicate real-life variability in model inputs or clinical decision-making. Therefore, conclusions being derived from these models must be considered in the context of their respective sensitivity analyses to account for the possible influence of model assumptions on results. Second, variations in healthcare costs limit the generalizability of these studies to the geographical region and healthcare system from which the patient population was obtained. Lastly, due to variability in study design, clinical practice, test availability, patient presentation, patient preference, available expertise of interpretation, and follow-up due to extracardiac findings ,69,70, tRecently, Karády et al. (2020) performed an individual-based Markov microsimulation using patient data from the PROMISE trial to compare anatomic and functional testing in patients presenting with suspicion of obstructive CAD ,72. The


Interventions that elevate glycine levels and target the glycine receptor (GlyR) in the nucleus Accumbens (nAc) reduce ethanol intake in rats, supposedly by acting on the brain reward system via increased basal and attenuated ethanol-induced nAc dopamine release. Glycine transport across the blood brain barrier (BBB) appears inefficient, but glycine-containing dipeptides elevate whole brain tissue dopamine levels in mice. This study explores whether treatment with the glycine-containing dipeptides leucine-glycine (Leu-Gly) and glycine-leucine (Gly-Leu) by means of a hypothesized, facilitated BBB passage, alter nAc glycine and dopamine levels and locomotor activity in two rodent models. The acute effects of Leu-Gly and Gly-Leu  alone or Leu-Gly in combination with ethanol on locomotion in male NMRI mice were examined in locomotor activity boxes. Striatal and brainstem slices were obtained for ex vivo HPLC analyses of tissue levels of glycine and dopamine. Furthermore, the effects of Leu-Gly i.p. (1–1000 mg/kg) on glycine and dopamine output in the nAc were examined using in vivo microdialysis coupled to HPLC in freely moving male Wistar rats. Leu-Gly and Gly-Leu did not significantly alter locomotion, ethanol-induced hyperlocomotor activity or tissue levels of glycine or dopamine, apart from Gly-Leu 10 mg/kg that slightly raised nAc dopamine. Microdialysis revealed no significant alterations in nAc glycine or dopamine levels when regarding all rats as a homogenous group. In a subgroup of rats defined as dopamine responders, a significant elevation of nAc dopamine (20%) was seen following Leu-Gly 10–1000 mg/kg i.p, and this group of animals presented lower baseline dopamine levels compared to dopamine non-responders. To conclude, peripheral injection of glycine-containing dipeptides appears inefficient in elevating central glycine levels but raises accumbal dopamine levels in a subgroup of rats with a lower endogenous dopamine tone. The tentative relationship between dopamine baseline and ensuing response to glycinergic treatment and presumptive direct interactions between glycine-containing dipeptides and the GlyR bear insights for refinement of the glycinergic treatment concept for alcohol use disorder (AUD). A central mechanism for how alcohol and other drugs of abuse elicit reward revolves around their actions on the mesolimbic dopamine system  alter locomotion and ethanol-induced locomotor activity in mice, (2) alter ex vivo accumbal glycine and dopamine content in mice and (3) elevate in vivo extracellular levels of glycine and dopamine in rat nAc. We hypothesized that systemic treatment with Leu-Gly would elevate striatal glycine and dopamine levels due to its glycine content and presumable GlyR-mediated dopamine response, in line with its documented effects on whole brain dopamine levels . For in vivo microdialysis, a total number of 54 male Wistar rats weighing 260–280 g at arrival were supplied by Envigo (Netherlands). Mice were housed eight to a cage whereas rats were housed four to a cage prior to surgery and single-housed after surgery, under controlled environmental conditions comprising constant room temperature of 20–22 °C, humidity of 50–65% and regular light-dark conditions with lights on at 07:00 a.m. and off at 07:00 p.m. Before any experimental procedures were initiated, animals were allowed at least one week of acclimatization to the facilities. All animals had access to regular chow  and tap water ad libitum. The experiments were approved by the Ethics Committee for Animal Experiments, Gothenburg, Sweden.Leu-Gly and Gly-Leu  were dissolved in 0.9% NaCl solution to a desired dose of 1, 10, 100 or 1000 mg/kg and administered i.p. in a volume of 2.0 ml/kg. In previous studies of Leu-Gly isomers in mice, ex vivo dopamine levels in whole brain were elevated after treatment with either 1 or 10 mg/kg i.p. of either isomer  was applied locally for analgesic purposes and 2 ml NaCl 0.9% was injected subcutaneously to prevent dehydration. After surgery, the rats were single housed and allowed to recover for two days prior to initiating the microdialysis experiments.The rats were anesthetized with 4% isoflurane , mounted onto a stereotactic instrument  and placed on a heating pad to prevent hypothermia during surgery. Three holes were drilled for the placement of a probe and two anchoring screws. An I-shaped, custom-made probe with a semi-permeable membrane was gently lowered into the nAc core–shell borderline region  via a swivel allowing the animal to move around freely. The probes were perfused with Ringer solution for 2 h prior to sampling to obtain a balanced fluid exchange before baseline sampling began. During the entire experiment, the infusion rate for the Ringer solution was set at 2 μl/min and dialysate samples (40 μl) were collected every 20 min. When at least three consecutive stable values of dopamine were obtained, systemic treatment with Leu-Gly or vehicle was initiated. Baseline levels for each animal was set to 100%. Microdialysate dopamine content was separated and quantified using HPLC with an electrochemical cell detector as previously described  were evaluated by a two-way analysis of variance (ANOVA) followed by Tukey’s multiple comparison test when applicable. Glycine and dopamine data derived from mice post-mortem analysis were evaluated by a one-way ANOVA followed by Dunnett’s post hoc. Extracellular glycine and dopamine measurements over time (t = 0–120 min) from in vivo microdialysis were evaluated by a two-way ANOVA followed by Dunnett’s multiple comparison test whereas area under the curve (AUC) data were analyzed using one-way ANOVA. In the microdialysis study, rats were classified as dopamine responders if dopamine was elevated more than 10% compared to baseline within the first hour after injection, in line with previous subdivision for rats that received local (into the nAc) or systemic treatment with glycine  < 0.05 was considered statistically significant. Statistics were performed using GraphPad Prism, version 9.0.1 for Mac OS .Locomotor activity measurements over time  = 14.52, p < 0.0001, time effect F = 19.36, p < 0.0001, interaction term F = 1.32, p = 0.111; Tukey’s post hoc vehicle vs EtOH; p < 0.0001. However, in contrary to what was hypothesized, the addition of Leu-Gly 100 or 1000 mg/kg did not attenuate the ethanol-induced hyperlocomotion; vehicle vs EtOH + LG100; p = 0.001, vehicle vs EtOH + LG1000; p = 0.0001. These effects were also evident upon comparison of AUCs, one-way ANOVA; F(3100) = 13.74, p < 0.0001, Tukey’s post hoc vehicle vs EtOH; p < 0.0001; vehicle vs EtOH + LG100; p = 0.0019; vehicle vs EtOH + LG1000; p = 0.0002  = 3.83, p = 0.023. A subsequent Dunnett’s post hoc test revealed a significant effect for the intermediate dose of Gly-Leu, vehicle vs Gly-Leu 10 mg/kg; p = 0.017  = 2.04, p = 0.114, time effect F(6186) = 4.20, p < 0.001, interaction term F = 1.66, p = 0.033,  = 5.38, p = 0.002, time effect F(6174) = 6.46, p < 0.001, interaction term F = 1.07, p = 0.380. Dunnett’s post hoc revealed significant effects produced by the three highest doses, Leu-Gly 10 mg/kg vs vehicle p = 0.007, Leu-Gly 100 mg/kg vs vehicle p = 0.010 and Leu-Gly 1000 mg/kg vs vehicle p = 0.009  = 4.31, p = 0.007, Dunnett’s post hoc Leu-Gly 10 mg/kg vs vehicle p = 0.016, Leu-Gly 100 mg/kg vs vehicle p = 0.024, Leu-Gly 1000 mg/kg vs vehicle p = 0.021  = 4.77, p < 0.001, time effect F(6150) = 6.70, p < 0.001, interaction term F = 3.33, p < 0.001, Dunnett’s post hoc Leu-Gly 1000 mg/kg vs vehicle p = 0.001  = 11.45, p < 0.0001, Dunnett’s post hoc Leu-Gly 1000 mg/kg vs vehicle p < 0.0001  = 3.59, p = 0.023, Leu-Gly 10 mg/kg vs vehicle p = 0.029  = 3.63, p < 0.001 (Fig. The accumbal dopamine response for each individual rat was scrutinized to investigate whether a subpopulation of animals presented elevated extracellular dopamine levels of more than 10%, a heterogenous response that has previously been observed following glycine administered i.p. or locally into the nAc (Molander and Soderpalm, F42 = 5.38, F42 = 5.38, F42 = 5.38, F42 = 5.38, Repeated findings from animal models suggest that compounds that elevate brain glycine levels may be implicated for the treatment of AUD and schizophrenia, targeting preferentially GlyRs in the nAc or the co-agonist site on NMDA-Rs in the prefrontal cortex and hippocampus, respectively Balu . HoweverOn these premises, treatment with glycine anchored onto an amino acid that more readily passes the BBB, such as Leu-Gly that has previously been demonstrated to elevate whole brain tissue dopamine levels ex vivo, conceivably as a down-stream effect of nAc GlyR signaling, presented as a viable next step. In further support of this concept, it has previously been demonstrated that glycine-containing dipeptides pass the BBB (Tanaka et al. Notably, when previously administering a GlyT1-inhibitor i.p. or glycine itself either i.p. or locally into the nAc, only a subpopulation of the rats displayed a distinct dopamine response, i.e. a dopamine elevation by 10% or more compared to baseline during the first hour after injection, hence motivating a division between dopamine responders and non-responders (Molander and Soderpalm . low ongoing stimulation of ligands at these receptors or neighboring G-protein-coupled receptors with intracellular signaling pathways modulating GlyR function (Yevenes et al. Interestingly, when comparing baseline dopamine levels of dopamine responding and non-responding rats, rats classified as responders exhibited a significantly lower basal dopamine tone. It could be argued that larger percental fluctuations for rats presenting a low basal dopamine tone may merely reflect a methodological artifact. On the other hand, a low, endogenous dopamine tone in the nAc has previously been associated with high ethanol-intake in rats and may be an important determinant of alcohol drinking behavior (Weiss et al. The smaller divergencies compared to the findings of Han et al. The underlying rational behind the locomotor activity study was to explore whether Leu-Gly interfered with animal behavior associated with ethanol-induced activation of central dopaminergic systems. In line with the psychomotor stimulant theory of addiction, most substances that interact with the mesolimbic dopamine system and are addictive, e.g. ethanol and amphetamine, may increase locomotion (Wise and Bozarth To conclude, this study shows that systemic treatment with Leu-Gly does not elevate accumbal dopamine and glycine levels in vivo when the animals are regarded as a homogenous group, nor interferes with a behavior associated with activation of the mesolimbic reward system. In a subset of rats denoted dopamine-responders, dopamine levels were significantly elevated by much lower doses of Leu-Gly than previously observed following glycine itself (Olsson et al.


This paper proposes a text-mining framework to systematically identify vanishing or newly formed topics in highly interdisciplinary and diverse fields like cognitive science. We apply topic modeling via non-negative matrix factorization to cognitive science publications before and after 2012; this allows us to study how the field has changed since the revival of neural networks in the neighboring field of AI/ML. Our proposed method represents the two distinct sets of topics in an interpretable, common vector space, and uses an entropy-based measure to quantify topical shifts. Case studies on vanishing  and newly emerged  topics are presented. Our framework can be applied to any field or any historical event considered to mark a major shift in thought. Such findings can help lead to more efficient and impactful scientific discoveries. The science of science uses quantitative and computational approaches to examine science itself. It measures and models the interactions between scientific agents and entities in order to understand scientific practices, improve scientific processes, and promote scientific innovation  analysis done in Núñez et al.  methods and well-established mathematical procedures  through a new lens to detect topic trends from text data.t, e.g., publication of a seminal paper.Identify a historical event of interest t, then assign each paper to its most represented topic. Repeat the process with the entire dataset to get reference topic clusters.Apply topic modeling to publications before and after Represent each topic as a vector, whose elements count the number of papers shared with the reference clusters. This represents topics from non-overlapping time periods in a common mathematical space that is easy to understand and robust to vocabulary changes.t. This quantifies topic similarities without relying on human labeling or keyword matching.Compute a cosine similarity matrix for every pair of topic clusters from before and after t can be “explained away” by a single topic from after t, and vice versa. For example, maximum entropy will be achieved when the pre-t topic is equally similar to all post-t topic vectors, or when the post-t topic is equally similar to all pre-t topics. This captures an element of surprise and therefore a potential topical shift.Calculate the entropy of each row and each column of the similarity matrix to measure how much a topic from before Investigate content (keywords) and context  of topics with high entropy.The following sections explain the process in further detail, as applied to studying how content discussed in cognitive science papers has shifted since the publication of Krizhevsky et al. .cognitive science were accessed from the Microsoft Academic Graph   matrices with non-negative elements. The ith column of W gives the weights of the words in the ith topic, while the jth column of H gives the weights of the topics in the jth abstract. We assign each paper to its most weighted topic based on H, and describe each topic with its top weighted words from W. Each paper is assigned to exactly one topic. The topics are ordered based on the number of assigned papers, which gives us paper groups i = 1, …, n. For example, n = 10, 50, 100, 200, 500, we chose n = 50, as it gave us clear and diverse topics that are neither too broad or too specific by inspection.where the dictionary matrix c1, c2, …, cn. This allows us to compute similarities and dis-similarities, and finally the entropy in a way that is robust to semantic changes and human biases; topics are represented by their usage in modeling specific texts in the corpus. Let c1, c2, …, cn. The k-th entry of ck and In order to compare topics before and after 2012, we represent clusters Sij and assemble the matrix ith row of S describes how similar jth column represents S is non-negative, the rows and columns of S can be treated as a probability distribution once they are normalized to sum to one. Therefore, we compute entropy for each row and column of the matrix S to get We denote the cosine similarity Singhal,  between ith topic from before t can be “explained away” by a single topic from after t. For example, the entropy is at its minimum, 0, when the similarity between the ith pre-t topic is non-zero for only one post-t topic; let's say with ck, a compelling argument for a one-to-one matching between did not depend on any human comparison of keywords. Meanwhile, the maximum entropy (logn) is achieved when the ith pre-t topic is equally similar to all post-t topic vectors. We interpret this uncertainty to mean that the papers have spread out and the topic has potentially dissipated after t. On the other hand, if t. The “high entropy" cases could perhaps be interpreted as (mini-) paradigm shifts . It further shows that the topic was quite promising at one point before it disappeared. We also note that almost none of the top keywords except “AI” appear as a top key word in any of the topics after 2012. The “symbolic/connectionist" topic seems to disappear after new deep learning methods demonstrated their practical efficacy, offering a pragmatic (and perhaps premature) conclusion to philosophical debates about the best approach to AI. AI remains a hot topic, of course, while previously pressing discussions of the major “paradigms” of “symbolic” AI and “connectionist” AI have faded into obscurity.Based on the keywords in Leonardo, is a journal published by MIT Press covering the applications of technologies to arts and music, which matches our interpretation of the keywords. As technology becomes more prominent and powerful in people's daily lives, discussions on art, technology and aesthetic practices have also increased–a trend we can only imagine will continue with the rise of Midjourney . Finally, we can use prediction models to predict whether a topic is likely to appear or disappear in the future; this would be hugely beneficial to funders and practicing scientists alike.https://github.com/HarlinLee/cogsci-missed-connections.Publicly available datasets were analyzed in this study. This data can be found at: LC, HL, and JF contributed to the conception and design of the study and revised the manuscript. LC and HL performed the data analysis. LC wrote the first draft of the manuscript. All authors contributed to the article and approved the submitted version.This work was supported by grant TWCF0333 from the Templeton World Charity Foundation.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


A major hallmark of aging-associated diseases is the inability to evoke cellular defense responses. Transcriptional protein Nrf2 (nuclear factor erythroid-derived 2-related factor) plays a pivotal role in the oxidative stress response, cellular homeostasis, and health span. Nrf2’s activation has been identified as a therapeutic target to restore antioxidant defense in aging. Here, we demonstrated that FDA-approved drug, hydralazine (Hyd), was a reactivator of the Nrf2/ARE (antioxidant response element) pathway in various ages and types of mouse (m) or human (h) lens epithelial cells (LECs) and mice lenses in-vitro/in-vivo. This led to Hyd-driven abatement of carbonyls, reduced reactive oxygen species (ROS), and reduced 4-HNE/MDA-adducts with cytoprotection, and extended lens healthspan by delaying/preventing lens opacity against aging/oxidative stress. We elucidated that Hyd activated the protective signaling by inducing Nrf2 to traverse from the cytoplasm to the nucleus and potentiated the ARE response by direct interaction of Nrf2 and ARE sequences of the promoter. Loss-of-function study and cotreatment of Hyd and antioxidant, N-acetyl cysteine (NAC) or Peroxiredoxin (Prdx)6, specified that Nrf2/ARE-driven increase in the promoter activity was Hyd-dependent. Our study provides proof-of concept evidence and, thereby, paves the way to repurposing Hyd as a therapeutic agent to delay/prevent aging and oxidative-related disorders. Preservation of redox homeostasis is central to maintaining cellular integrity and physiological function. An imbalance between oxidation and reduction phenomenon can lead to cell/tissue damage . This imMany increasing age-related pathologies or diseases share common risk factor(s). With advancing age, oxidant generation from several environmental and cellular sources is increased, while, at the same point, the Nrf2/ARE-mediated antioxidant protective pathway, the primary line of defense, is repressed. Studies have demonstrated that aging-related amplification of ROS-driven oxidative damage and accumulation of intracellular oxidized proteins aggregates occur due to loss of antioxidant expression and lesser capacity to mitigate oxidative load ,24,25,26Nevertheless, the major molecular event underlying deranged physiological functions and failure of cellular homeostasis in aging-related diseases is chronic elevation of ROS-driven oxidative stress due to unresponsiveness protective antioxidant response ,48,49,50The eye is a prime target for environmental stress and highly exposed to oxidative inductors, sunlight, or pollutants. Compared to other tissues, the ocular lens contains a potent antioxidant system to combat oxidative stress-induced damage. However, with advancing age, deterioration of the antioxidant system results in higher oxidative load-driven failure of the lens’ homeostasis and onset of lens opacity ,57,58,59In this study, therefore by using a variety of LECs of variable ages as well as in-vivo Hyd-treated mouse lenses facing oxidative stress ex-vivo as model systems and assessments, we addressed the effect and efficacy of Hyd in restoring aging/oxidative stress-related adverse signaling causing pathobiology of the eye lens. We found that the Nrf2 antioxidant pathway acts as a driver mechanism in aging/oxidative-related signaling. We identified that Hyd treatment corrected impaired transcriptional activity of Nrf2/ARE in aging LECs and lenses in-vivo as well as prevented oxidative stress-induced lens opacity ex-vivo. Thus, our finding showed that Hyd instillation in the eye (in the form of eye drops) resulted in increased cellular protection and extended the healthspan of eye lenses and LECs (prevention or delay of lens opacity). Altogether, our studies demonstrated that repression of the Nrf2-mediated antioxidative response is a plausible key player of the initiation or progression of etiopathologies during aging and oxidative stress. Finally, our findings build a point that therapies aimed at Nrf2 antioxidant pathway reactivation by Hyd should have the promising potential to protect or prevent cell/organ damage leading to aging/oxidative-related disease conditions.2, as described previously [Human LECs cell line ((SRA01/04) immortalized with SV40 , a kind eviously ,74. In tPrimary hLECs were isolated from normal eye lenses of deceased persons or healthy donors of different ages (22 years (y), 23 y, 25 y, 55 y, 57 y, 59 y, 69 y, 68 y, 67 y, 70 y old) received from the Lions Eye Bank, Nebraska Medical Center, Omaha, NE, and National Development and Research Institute (NDRI), Inc., Philadelphia, PA, USA. Primary LECs isolated from these lenses were used for the present study. According to regulation HHS45CFR 46.102(f), studies involving lenses or LECs from deceased subjects are not considered human subject(s) research as stated under 45CFR46.102(f) 10(2) and, therefore, do not require IRB oversight. Primary LECs were isolated from the lenses as described previously ,54,75,76All animal studies followed the recommendations set forth in the “Statement for the Use of Animals in Ophthalmic and Visual Research” by the Association for Research in Vision and Ophthalmology and were approved by the Institutional Animal Care and Use Committee (IACUC), University of Nebraska Medical Center (UNMC), Omaha, NE. LECs were isolated from C57BL/6 mice and maintained in DMEM with 10% FBS, as described earlier ,74,76,79C57BL/6 mice of 6 months (M), 16M, and 22 M were purchased from Charles River Laboratories  and were maintained at a stable temperature and humidity under specific pathogen-free conditions in a cleaned animal facility, as described earlier ,31. Prim2O2-mediated toxicity was analyzed using MTS assay. In brief, cell viability of Hyd -treated or untreated LECs facing H2O2-induced oxidative stress was evaluated using a colorimetric MTS assay  according to the manufacturer’s method and as described previously [Cell growth or Heviously ,80,81. T2O2-driven stress in absence or presence of Hyd were assessed with H2-DCF-DA (2′-7′-dichlorodihydrofluorescein diacetate) dye, a non-fluorescent fluorescein derivative as described in our published report [2-DCF-DA dye for 30 min at 37 °C. After diffusion into the cells, H2-DCF-DA is deacetylated by cellular esterase into a non-fluorescent compound that was later oxidized by ROS into 2′-7′-dichloroflurescein (DCF). ROS levels were quantified at Ex485 nm/Em530 with a Spectra Max Gemini EM .Intracellular ROS levels of LECs facing Hd report ,31. On t2-DCF-DA according to our published protocol [2-DCF-DA  dye was added and incubated for 30 min. Intracellular fluorescence was detected at O.D., Ex485 nm/Em530, with a Spectra Max Gemini EM .To measure the intracellular redox state levels of lenses isolated from Hyd-administered C57BL/6 mice eye, lenses were carefully isolated and immediately frozen at −80 °C. The intracellular levels of ROS were quantified by Hprotocol ,31. Brie2O2 in absence or presence of Hyd was carried out according to manufacturer’s instructions  and our published report [Lipid peroxidation (LPO) assay is based on the reaction of N-methyl-2-phenylindole, a chromogenic reagent with MDA  and 4-HNE  at 45 °C. Either MDA or 4-HNE reacts with two molecules of N-methyl-2-phenylindole to yield a stable chromophore with maximal absorbance at 586 nm. LPO assay in LECs/lenses exposed with Hd report ,80. Tota2O2 in absence or presence of Hyd using Protein Carbonyl Content Assay Kit  following the company’s protocol. The protein content of LECs (samples) were determined using the BCA assay. Samples were treated with 10% streptozocin solution to remove interfering nucleic acid. Purified water served as background control. Dinitrophenylhydrazine (DNPH) solution was added to each sample and incubated for 10 min, and then 87% TCA solution was added to the sample. Supernatant was removed by high centrifugation, and ice-cold acetone was added to each pellet and was placed for 30 s in a sonication bath and then further incubated at −20 °C for 5 min. Carefully, acetone was removed from each pellet by high centrifugation, and 6M guanidine solution was added to the pellet and sonicated. An amount of 100 µL of each sample was transferred to the 96-well plate, and reading was measured at 375 nm (absorbance) with a plate reader .The protein carbonyl content was measured in LECs/lenses exposed to H2O2 with or without Hyd treatment using The OxiSelect™ Oxidative DNA Damage Elisa kit . To prepare a standard curve, different concentrations (0–20 ng/mL) of 8-OHdG standard was prepared by diluting in assay diluent as mentioned in the company’s protocol. In brief, genomic DNA was isolated from LECs/lenses treated with H2O2 in absence or presence of Hyd and converted to single stranded DNA. DNA samples were digested with nuclease P1  followed by the incubation with 10 units of alkaline phosphatase  at 37 °C for 1 h in 100 mM Tris, pH 7.5. The 8-OHdG standards (50 µL) or samples (50 µL) were added to the well of the 8-OHdG conjugate coated plate and incubated at room temperature (RT) for 10 min with shaking. Thereafter, diluted anti-8-OHdG (50 µL) antibody was added to each well and incubated for 1 h on an orbital shaker at RT. The wells were washed, and diluted secondary antibody-enzyme conjugate (100 µL) was added and incubated on a shaker for 1 h at RT. After washing the wells, 8-OHdG activity was recorded by the addition of 100 µL warm substrate solution. Enzymatic reaction was stopped by the addition of 100 µL of stop solution, and absorbance was measured at 450 nm with a microplate reader .DNA is a biologically significant target of oxidative stress. The generation of 8-Hydroxydeoxyguanosine (8-OHdG) is a ubiquitous marker of oxidative stress among numerous types of oxidative DNA damage. We measured the levels of 8-OHdG in LECs/lenses exposed to HRenilla, pRL-TK vector  using Neon transfection system . After 14 h, cells were washed and treated with Hyd for 24 h. Luciferase activity was measured using Dual-Glo luciferase assay system with 96-well plate  submitted to a microplate reader  [SRA-hLECs, mLECs, or different ages of primary hLECs were transfected with pRBGP2 3x ARE-LUC) containing three ARE sites or its mutant pRBGP4 (3x mut ARE- LUC) plasmids, a kind gift from Dr. Hozumi Motohashi, Japan)  along wix ARE-LUCProtein expression was examined by Western blot analysis as described previously ,18,20,23® LC480 Sequence detector system . RT-qPCR was performed using program condition of 5 min hot start at 95 °C, followed by 45 cycles for 10 s (seconds) at 95 °C, 30 s at 60 °C, and 10 s at 72 °C. Data were analyzed by LightCycler480 software by Roche. All data analysis was performed in triplicate. The relative values of target genes were normalized to the control using corresponding β-actin as an internal control.The relative levels of Nrf2 and its target genes mRNA were measured by quantitative real-time PCR (RT-qPCR). Total RNA was isolated from Hyd-treated SRA-hLECs as well as mLECs/lenses derived from C57BL/6 mice by using the single-step guanidine thiocyanate/phenol/chloroform extraction method , as described previously ,31. cDNA2 (PLA2) activity was carried out in accordance with the manufacturer’s protocol  and our published protocol [2 was made by diluting PLA2 stock solution (500 Units/mL) with 1 × reaction buffer up to 50 µL. For sample preparation, an equal amount of protein was diluted with 1 × PLA2 reaction buffer to make volume up to 50 µL. The reaction was started by adding 50 µL of the substrate-liposome mix to each microplate well consisting of control, standard, and the samples with 100 µL total reaction volume. The fluorescence units were measured at optical density (O.D.), Ex485 nm/Em535 nm, using a microplate reader .Phospholipase Aprotocol ,81,83. BGlutathione (GSH) peroxidase activity was quantified according to company’s protocol  and our published protocol ,81,83. T0) with DTX 880 Multimode Detector . The plate was incubated at room temperature in the dark for 60 min, and, again, the O.D. was measured at 440 nm (OD60). Each standard and sample well were calculated using the following formula, ΔOD60 = OD60 − OD0, and was presented in percentage.Superoxide Dismutase (SOD) enzymatic activity was measured as mentioned in the manufacturer’s protocol (Superoxide Dismutase (SOD) Assay, Kit, LS-K224, LifeSpan BioSciences, Inc., Seattle, WA, USA) . To prep2O2  of each standard and 90 µL of assay buffer were added into separate wells of a 96-well plate and proceeded for detection. For samples, 10 µL of an equal amount of total protein isolated from Hyd-treated SRA-hLECs and mLECs were separately added into wells of a 96-well plate. To initiate the catalase reaction, 90 µL of freshly prepared 50 µM H2O2 substrate (1 µL of the 4.8 mM H2O2 with 95 µL assay buffer) was added to the blank, control, and sample wells. A 96-well plate was incubated for 30 min at room temperature. After quick mix, the plates were submitted for detection. For standard, samples, and controls detection, 100 µL of detection reagent  was added to each reaction well of standard, samples, and controls. After 10 min incubation, optical density (O.D.) was measured at 570 nm with DTX 880 Multimode Detector .Catalase activity was determined following the manufacturer’s instructions  . To prepv/v) Nonidet P-40, 1 mM DTT, 0.5 mM phenylmethylsulfonyl fluoride (PMSF) and protease inhibitor). After a brief incubation on ice, it was centrifuged at 10,000 rpm for 10 min. Supernatant comprising the cytosolic fraction was transferred to a fresh tube. The pellet obtained was lysed in nuclear extract buffer (20 mM HEPES (adjusted pH at 7.9), 1 mM EDTA, 0.4 M NaCl, 10% (v/v) glycerol, 1 mM DTT, 0.5 mM PMSF and protease inhibitor) and subjected to continuous vortexing at 4 °C for 2 h to obtain the nuclear protein fraction. Finally, the extract was spun at 14,000 rpm for 15 min to pellet the nuclei. After centrifugation, the nuclear extract was aliquoted, and aliquots were stored at −80 °C. Protein was estimated according to the Bradford protein assay method, and the extract was used for the present study.Cytosolic or nuclear fraction was isolated following our previously published methods ,10,19,84The nuclear fraction was isolated, as noted above in ® Express kit  and ChIP-IT® qPCR analysis kit  following manufacturer’s protocol and as described previously [ChIP analysis was conducted by using the ChIP-ITeviously ,80,85. B® Genomic PCR Kit . The PCR product obtained was amplified and verified by sequencing as described previously [SacI and XhoI sites. Primers used were as follows: forward primer 5′-GACAGAGTTGAGCTCCACACAG-3′ and reverse primer 5′-CACGTCCTCGAGAAGCAGAC-3′. Expression and purification of recombinant protein TAT-HA-Prdx6 was prepared as described in our published report [Human genomic DNA was used to construct pCAT-hPrdx6 promoter plasmid, as reported previously in our published protocol ,10,31. Ieviously ,74. To ed report ,86. Hyd shRNA  plasmid. A scrambled shRNA was used as negative control . SRA-hLECs were transfected with control shRNA or Nrf2 shRNA by using NeonTM Transfection System. After 2 days of transfection, transfectants were used for the study or selected with selection marker puromycin to make stable cell lines. SRA-hLECs were transfected by using the Neon Transfection System  as described in our published protocol [To generate Nrf2-depleted SRA-hLECs, Nrf2 was knocked down using human Nrf2 specific protocol ,31,81.2O2-induced oxidative stress. The lenses were observed routinely. After 48 h, oxidative stress lenses were photographed using Nikon SMZ 745T microscope fitted with a Nikon camera and a computer loaded with an analysis software program [Hyd (left eye) or buffered saline (7.2) (right eye) was topically instilled in 16 or 22-M-old mice eyes for 7 or 15 days once daily (please see illustration in Results Section). At day 8 or 16, lenses were carefully isolated and were cultured in 48-well culture plates containing 199 media without any supplements. After 24 h, the clear lenses were subjected to H program ,54,83,87p value < 0.05 and <0.001 was considered statistically significant.All experiments were performed with at least three independent biological replicas. Results are expressed as the average mean ± standard deviation (S.D.). Statistical analyses were performed by Sigma plot. For post-hoc statistical tests, we performed Bonferroni and Holm–Sidak test using one-way ANOVA, these tests can be used for both comparisons versus a control group  and pairwise comparisons (comparison of the mean responses to the different treatment groups). Statistical significance between control and treatment groups was assessed, and 2-DCF-DA dye revealed that Hyd treatment itself does not augment intracellular ROS levels in the cells, but it reduces the levels of ROS when examined after 8 h of treatment. The results indicated that Hyd does not act as a pro-oxidant. Next, to determine the functional significance of Hyd treatment, we assessed the survival levels of Hyd-treated or untreated LECs (SRA-hLECs or mLECs) using MTS assay against oxidative stress, as shown in 2O2-induced oxidative stress. Furthermore, assessment by H2-DCF-DA dye showed a significant reduction of ROS in these treated cells compared to untreated ones, suggesting that Hyd protected the LECs by reducing intracellular ROS. Our experiments also indicated that 20 µM could be a more effective concentration in defending LECs from oxidative damage. It is worth noting that LECs treated with Hyd displayed a significant reduction in the ROS levels of the cells untreated with H2O2, indicating that Hyd is not a pro-oxidant. Based on these observations, we surmised that Hyd might provide its protective effect by activating the antioxidant pathway in LECs as reported previously in other model systems. Thus, we focused our present study to understand Hyd-mediated molecular event(s), which might be involved in the activation of Nrf2/ARE antioxidant pathway and cellular protection.In addition to antihypertensive property, Hyd has been shown to exert its cytoprotective and antiaging effects by activating the Nrf2/ARE antioxidant pathway in various cell types ,22,88,892O2 for 24 h, and the levels of MDA+4-HNE, protein carbonyls, as well as DNA damage, were quantified. We observed that H2O2-treated LECs displayed a significant increase in MDA plus 4-HNE levels /4-HNE  or protein carbonylation. To achieve this end, we exposed Hyd-pretreated or untreated LECs to HRenilla, pRL-TK vector . Transfectants treated with different concentrations of Hyd for 24 h were assayed for luciferase activity using Dual-Glo luciferase assay system . Data analysis disclosed that Hyd significantly up-regulated the Nrf2/ARE-mediated transcription in a dose-dependent manner, as shown in Previously, we have reported that Nrf2/ARE activation-dependent increased antioxidant gene transcription is directly related to expression and activities of antioxidants ,19,21,31The results derived from the above experiments implied that Hyd can reactivate Nrf2/ARE-mediated transcription in general. This argues that Hyd may exert its protective function by up-regulating Nrf2/antioxidant expression in LECs. To examine this, we used multiple LECs types, primary hLECs, SRA-hLECs, and mLECs. At first, we quantified Nrf2 and its target gene, Prdx6, at protein levels in Hyd treated/untreated LECs. Immunoblot analysis revealed that the cellular extracts of LECs treated with different concentrations of Hyd  had a concentration-dependent effect(s) on the increase in Nrf2 and Prdx6 protein expression A,B. Howe2  assay to examine the enrichment of Nrf2 on ARE sequences of the hPrdx6 gene promoter. Primary hLECs of variable ages treated with Hyd for 24 h were subjected to ChIP assay with antibody specific to Nrf2. As shown in ng cells B. As expng cells A. Taken Nrf2-depleted SRA-hLECs facing oxidative stress. To achieve this, we employed ShNrf2 to knock down Nrf2 and generated Nrf2-depleted SRA-hLECs. Expression assays analyses, Western blot  and Sh-Nrf2 SRA-hLECs (Nrf2-depleted SRA-hLECs) were exposed to H2O2 in the absence or presence of Hyd for 24 h. Cell viability (MTS assay) assessment disclosed that Hyd was significantly ineffective in protecting Nrf2-depleted SRA-hLECs , suggesting that Hyd exerts its protective effects specifically via the activation of the Nrf2/ARE antioxidant pathway.To examine the impact of the Hyd-induced amplification of the Nrf2 antioxidant protective pathway, we carried out Hyd-mediated cytoprotective assay using ern blot A, and RTern blot B revealeRA-hLECs C, while 2O2-induced oxidative stress. Cell viability assessment using MTS assay  and 22 M old C57BL/6 male mouse were treated with Hyd for 24 h. Data analysis disclosed that Hyd significantly reduced the ROS production in primary aging/aged mLECs as shown in TS assay D showed TS assay D. Our fiIt is evident from the above experiments that Hyd treatment activates the Nrf2/ARE-mediated protective pathway in vitro; we envisage that the results obtained from in vitro studies can be appraised if they could be reproducible in vivo. It is worth mentioning that to identify the aging-related adverse signaling linked molecular targets and to determine the protective molecular mechanism of small molecules, eye lenses/LECs have been suggested to be the best biological model system. In this study, we selected Hyd to be delivered in the form of eye drops, as this route of application will be acceptable to the subjects. In addition, we reason that this will avoid administration orally or by other routes, which may cause adverse effects in persons who do not have hypertension. Furthermore, distinct biological ages of organs have been identified, and aging of these organs have diverse genetic architectures and occurs at different rates ,92. In t2-DCF-DA dye method. Hyd-instilled eye lenses showed a significant reduction in ROS levels -induced stress. Then, 48 h later, the lenses were photographed and presented as shown in 2O2, and 48 h later the lenses were subjected to measure the levels of ROS  involved in Hyd-mitigated ROS levels, our data revealed that Hyd suppresses intracellular ROS levels. This rules out the involvement of a ROS-dependent hormetic mechanism ,3,10 Fi. Surprispathways . Alternapathways . AlthougRecently, a comprehensive body of experimental work reveals that the protective activity of Hyd is mainly attributed to its ability to amplify the Nrf2-mediated antioxidant pathway and its carbonyl scavenging property ,70,124. One of the most important findings of our present study is that topical instillation of Hyd in mouse eyes could efficiently up-regulate the Nrf2 antioxidant pathway in the lenses/LECs , resultiIn conclusion, we reported for the first time, using in vitro and in vivo/ex vivo experiments with multiple LECs derived from mouse and human lenses along with eye lenses, that Hyd regulates redox signaling in favor of cell/organ health by activating the Nrf2 antioxidant pathway. Our data disclosed that Hyd halts ROS amplification-mediated protein or DNA damage, as well as suppresses the levels of carbonyl products, implicated for the onset of aging pathologies. This beneficial molecular event resulted in increased cellular protection and eye lens healthspan by preventing/delaying lens opacity. Furthermore, we established that the mechanism(s) driving the changes in antioxidant gene expression was related to Hyd-induced nuclear accumulation of Nrf2 and, thereby, functional enrichment of Nrf2 at ARE sequences of the antioxidant gene promoters, such as Prdx6; however, it will be necessary to unravel the exact molecular events and pathways by which Hyd promotes and regulates these changes with the involved mechanistic function of Hyd on the Nrf2 nuclear localization and antioxidant pathway activation. As Hyd is a proposed antiaging compound and effective at lower concentrations, thereby avoiding off-targets compared to other known Nrf2 activators, it is tempting to propose that Hyd deserves to be considered as a viable therapeutic molecule to ablate oxidative-/aging-associated pathogenesis and disease conditions .


Targeted to the product’s weight-average relative molecular mass (wM), the response surface methodology (RSM) was used to optimize the preparation process. The optimal process conditions were obtained as follows: w (M) = 80.0%, m (V50):m (M) = 0.00700%, m (Na4EDTA):m (M) = 0.00350%, 1T = 50.0 °C, 2T = 60.0 °C, and 3T = 72.5 °C. The intrinsic viscosity ([η]) of the product was 1.780 dL/g, and the corresponding double bond conversion (Conv.) was 90.25 %. Poly (DMDAAC-co-DAMBAC) (9:1) revealed a highest wM of 5.637 × 105, together with the polydispersity index w/Mn)d  (9:1) could reach 97.73%. Our study has illustrated that the copolymerization of DMDAAC and a small amount of DAMBAC with poor reactivity could significantly improve the relative molecular weight of the polymer, enhance its lipophilicity, and thus the application scope of the polymer.Utilizing the copolymerization modification of dimethyl diallyl ammonium chloride (DMDAAC), the high positive charge density of the copolymer could be maintained, thereby facilitating the deficiency of its monomer in the application. In this paper, poly (DMDAAC- As a class of critical functional polymers, cationic quaternary ammonium salt polymers are extensively applied in industrial production and daily life, such as in petrochemical, wastewater treatment, textile printing and dyeing, and daily chemical industries ,2,3,4. AIn the past few decades, research has been performed to modify DMDAAC’s structure and the preparation of its homopolymers and related copolymers to expand the application capability of this type of polyelectrolyte in the fields of sterilization, drug transportation, and fuel cells ,12. LezoDue to the limited lipophilicity of diallyl quaternary ammonium salt homopolymers, to pursue better application efficiency, researchers usually use copolymerization with other lipophilic monomers to improve the application efficiency of this kind of polymer. Yang et al.  developeN,N-diallyl-N-methyl benzyl ammonium chloride (DAMBAC) was obtained based on DMDAAC by replacing a methyl group on quaternary ammonium nitrogen with benzyl, which can effectively improve the former’s deficiencies in lipophilicity. Jia et al. ) and monomer double bond conversion rate (Conv.) of the product were measured.According to the molar ratio of DMDAAC and DAMBAC (n(DMDAAC):n(DAMBAC) = 9:1, the best result was obtained. The synthesis process conditions were: w (M) = 80.0%, m (V50): m (M) = 0.7 %, m (Na4EDTA):m (M) = 0.0035%, 1T = 50.0 °C, 2T = 60.0 °C, and 3T = 72.5 °C. Meanwhile, the corresponding product had an intrinsic viscosity value of 1.78 dL/g and a double bond conversion (Conv.) of 90.25%.According to the preparation process in w (M) (1A), m (V50): m (M) (1B), and m (Na4EDTA): m (M) (1C), as response variables. The optimum feed ratio of the polymerization process was obtained by taking the product’s molecular weight per weight (wM) as the response value. Factor codes and levels of feeding ratio are shown in Based on the results of the single-factor exploration experiment in 1T(2A), 2T(2B), and 3T(2C) of the polymerization reaction as response variables, and a mathematical regression model was established. The optimal three-stage temperature data of the polymerization process were obtained by taking wM as the response value for optimization. The codes and levels of temperature factors are shown in Based on the optimal feed ratio, a three-factor and three-level experiment was designed with the three-stage temperature Ubbelohde viscometer) and mercury calibration volume  were also used.The instruments used in the characterization experiments included a Nicolet IS-10 Fourier infrared transform spectrometer , an Avance II 500 MHz Superconducting nuclear magnetic resonance spectrometer , a DAWN HELLOS Gel Permeation chromatography-multi-angle laser light scattering instrument (GPC-MALLS) , and a YYS-300E biological microscope . A capillary dilatometer (0.5–0.6 mm co-DAMBAC) (9:1) was weighed into a 100 mL volumetric flask with an allowable error range of (±0.002 g). Then, 1.000 mol/L and 0.1000 mol/L NaCl solutions were selected to the volume and shaken until the copolymer was dissolved. The Ubbelohde viscometer was placed in a constant-temperature water bath at (30 ± 0.1) °C. At the same time, the retention time of the solution to be tested in the Ubbelohde viscometer was recorded and calculated using the single-point method.According to “GB/T 33085-2016 Water Treatment Agent-Polydimethyldiallylammonium Chloride”, 0.1 g of poly  was considered and placed in a 500 mL conical flask. After that, 100 mL of distilled water was added to the conical flask and shaken well. This determination method was referred to as “GB/T 22312-2008 Plastics-Determination of Residual Acrylamide Content of Polyacrylamide”.A certain amount of copolymer product was weighed into a 100 mL beaker, and a small amount of distilled water was added until the product was completely dissolved. Once the product was completely dissolved, acetone should have been added by degrees. As long as white viscous polymer was precipitated, acetone should have been added in 3–5 batches. Finally, the solution was stirred well until the polymer precipitated. After completing the above steps, we poured the acetone and repeated the above method three more times. After the above operations, the polymer was placed in a vacuum-drying oven at 40 °C. Without drying, the sample could not be taken out and pulverized to obtain the corresponding refined product. Usually, the purified product could be stored in a desiccator. After the product was refined, the solid content, intrinsic viscosity, relative molecular mass, and double bond conversion rate were used to determine the subsequent product structure and property characterization.−1 to 400 cm−1. The advanced product was tested using an NMR spectrum with D2O as solvent and tetramethylsilane as internal standard.The structure and relative molecular mass of the refined product was characterized via infrared spectroscopy using the KBr method, in which the wave number ranged from 4000 cmV (methanol):V (water) = 75:25, 0.1 mol/L NaCl, and 0.01 mol/L NaH2PO4 as the mobile phase and polyethene glycol as the standard sample, GPC-MALLS was used to determine the relative molecular mass and distribution of the products under the conditions of 25 °C column temperature and 0.5 mol/min flow rate.With The experiments were carried out in light of the Petroleum and Natural Gas Industry Standard of the People’s Republic of China . Meanwhile, O/W-type oil-bearing wastewater emulsions were prepared, and a standard curve is presented in R is the demulsification rate, w0 is the oil content before demulsification, and w1 is the oil content after demulsification.According to Lambert Beer’s law, the absorbance of the tested substance at its maximum absorption wavelength is different at different concentrations. Therefore, to calculate the demulsification degrees, the absorbance of the emulsion before and after demulsification could be measured. Then, the oil content of the emulsion before and after demulsification could be obtained through the standard curve of oil. The specific process is shown in Equation (1).2R = 0.9993, indicating that the linear relationship between absorbance and oil content was excellent, which could be used for further experiments.It could be seen from wM = 63.11 + 1.07A1 + 1.96B1 + 0.059C1 − 1.46A1B1 + 0.49A1C1 + 1.49B1C1 − 9.8A12 − 6.95B12 − 8.13C12. The overall analysis of variance for the factor model of the feed ratio is shown in The experimental design was optimized based on the feeding ratio factor, and the polymer product’s weight-average molecular weight was regressed using Design Expert 8.0 software. Afterwards, the fitting equation of the feeding ratio factor was obtained: 2R was 0.9132, indicating that the predicted value correlates well with the measured value. Nevertheless, this model could not represent 8.18 % of the total variation of the response value. The P-value indicated the model terms were significant. The “Lack of Fit F-value” of 1.24 implied a 40.43% chance that a “Lack of Fit F-value” this large could occur, which was insignificant. The above indicated that the predicted and measured values were well correlated, and the model was significant. The partial derivative of the fitting equation was equal to 0, and the best conditions for solving the equation were as follows: 1A = 80.11%, 1B = 0.71%, and 1C = 0.004%.Further analysis of wM in the polymerization process in wM and obtain the best level of each feed ratio factor. It could be seen from 1A and 1B, the wM first increased and then decreased, growing relatively slowly. The wM reached the highest point when 1A and 1B were 80.11% and 0.71%. It is shown in wM first increased and then decreased with the increase in 1A and 1C. The wM reached the highest point when 1A and 1C were 80.11% and 0.004%. As seen from 1B and 1C, the wM of the copolymer first increased and then decreased and finally reached the highest point when 1B and 1C were 0.71% and 0.004%, respectively.We demonstrate the response surface diagram of the interaction of various factors on Parallel verification experiments were performed on the optimal process conditions to verify the optimal conditions. The results are displayed in 5 g/mol to 6.450 × 105 g/mol, with an average value of 6.240 × 105 g/mol.From the results in wM = 71.63 + 4.57A2 − 8.84B2 + 0.08C2 + 1.18A2B2 − 0.21A2C2 + 2.21B2C2 − 12.60A22 − 31.12B22 − 14.25C22. The overall variance analysis of the temperature factor model is shown in The experimental design was optimized according to the temperature factor, and the Design Expert 8.0 software regressed the weight-average molecular weight of the polymer product. Afterwards, the fitting equation of the temperature factor was obtained as follows: 2R was 0.9328, indicating that the predicted value correlated well with the measured value. Nevertheless, this model could not represent 6.72% of the total variation of the response value. The P-value indicated the model terms were significant. The “Lack of Fit F-value” of 5.42 implied a 6.80% chance that a “Lack of Fit F-value” this large could occur, which was insignificant. The above indicated that the predicted and measured values were well correlated, and the model was significant. The partial derivative of the fitting equation was equal to 0, and the best conditions for solving the equation were as follows: 2A = 50.0 °C, 2B = 60.0 °C, and 2C = 72.5 °C.Further analysis of co-DAMBAC) (9:1). The analysis of co-DAMBAC) (9:1). The influence of weight-average relative molecular mass obtained the best level of each temperature factor. It could be seen from 2A and 2B, the weight-average relative molecular weight of the copolymerized product first increased and then decreased. The molecular weight reached the highest point. It could be seen from 2A and 2C, the weight-average relative molecular weight of the copolymerized product increased and decreased.2A = 51.2 °C and 2C = 72.4 °C, it reached the highest point. It could be seen from 1B and 1C, the weight-average molecular weight of the copolymerization product first increased and then decreased. When 2B = 59.2 °C and 2C = 72.4 °C, it reached the highest point.Meanwhile, the increase and decrease trends were relatively gentle. When Parallel verification experiments were performed on the optimal process conditions to verify the correctness of the optimal conditions. The overall verification results are exhibited in 5 g/mol to 6.590 × 105 g/mol, with an average value of 6.390 × 105 g/mol.The results in wM of the copolymerization product was: 1B > 1A > 1C. The initiator accounted for the monomer mass fraction (1B) on the copolymerization product weight average. The relative molecular mass had the most significant effect. Furthermore, the order of the polymerization process temperature influencing the wM of the copolymerized product was: 2B > 2A > 2C. That is, the polymerization temperature (2B) significantly affected the wM of the copolymer.According to the analysis of variance, under our experimental conditions, the order of the feed ratio factor influencing the The reason for this was that according to Arrhenius’s empirical formula and polymerization rate equation  when thew (M) = 80.1%, m (V50):m (M) = 0.710%, m (Na4EDTA):m (M) = 0.00400%, 1T = 50.0 °C, 2T = 60.0 °C, and 3T = 72.5 °C, corresponding theoretical weight-average relative molecular mass wM = 6.330 × 105 g/mol.The above analysis summarizes the optimization experiments on the polymerization process’s feed ratio and temperature factors. Overall, the results revealed that the best process conditions were: co-DAMBAC) (9:1) were subjected to FTIR measurement, and the obtained FTIR is exhibited in −1 was the expansion vibration absorption peak of O-H, and there was an absorption peak here to indicate the presence of water in the copolymer product. The peak around 2979 cm−1 was the C-H vibration absorption peak in the methyl group, and the peak at 1638 cm−1 was the vibration absorption peak of the C=C double bond. The height of the copolymer product at this place was significantly weakened, indicating that the double bond had been opened. The peak around 1467 cm−1 was the in-plane bending vibration absorption peak of methylene C-H connected to quaternary ammonium nitrogen.  (9:1).Two monomers and poly (DMDAAC-trogen.  b A new a1H NMR spectra of DMDAAC (a), DAMBAC (b), and poly (DMDAAC-co-DAMBAC) (9:1) (c) are exhibited in δ = 1.52 (1) and δ = 2.75 (2). δ = 1.52 (1) was the H atomic absorption peak of -CH2- on the polymer backbone, and δ = 2.75 (2) was the H atomic absorption peak on the five-membered ring -C=H-. The peaks of the spectral pattern (a) and spectral (b) δ = 6.00(1) and δ = 5.74(2) were H atomic absorption peaks on allyl double bonds, and the two absorption peaks associated with C=C bonds in spectrum (c) disappeared. The peak of the δ = 7.50(6) was the absorption peak of H atoms on the benzene ring, and the intensity of the absorption peak at the spectral 13C NMR spectra of DMDAAC (a), DAMBAC (b), and poly (DMDAAC-co-DAMBAC) (9:1) (c) are shown in δ = 27.32 (1), δ = 38.42 (2), and δ = 53.56 (3) around the emergence of new absorption peaks. δ = 27.32 (1) was the absorption peak of -CH2- on the polymer backbone, and the peaks at δ = 38.42 (2) and 53.56 (3) were the double absorption peaks of -C=H- and -CH2- on the pendant ring and the absorption peak of the C atom on the benzene ring at δ = 127.57~137.56 (6~8), respectively. The absorption peak intensity at the spectra in δ = 124.52 and 129.35 disappeared, and the above results showed that the monomers polymerized.The characterization principle of GPC-MALLS is simple and easy to understand. The molecules are separated according to the relative molecular weight when the polymer solution flows through the chromatographic column (gel particles). The ones with higher molecular weights are in the front , and the ones with lower molecular weights are in the rear  ,23.co-DAMBAC) (9:1)  = 91.32%) was determined. Meanwhile, the flow time and cumulative distribution curve of the relative molecular weight of PMPDAAC were also obtained. According to the outflow time diagram, the outflow time of poly (DMDAAC-co-DAMBAC) (9:1) ranged from 12.4 min to 21.4 min, and the signal reached the highest value when the outflow time was 16.7 min. The relative molecular weight of poly (DMDAAC-co-DAMBAC) (9:1) polymer was 5.637 × 105 g/mol, and the polydispersity index w/Mn)d(M was 1.464. It could be seen that the relative molecular weight distribution of poly (DMDAAC-co-DAMBAC) (9:1) was relatively narrow, and the polymerization process conditions were appropriate.As shown in co-DAMBAC) (9:1) polymers. At the same time, the copolymers between DMDAAC and DAMBAC contained less. The structure of poly (DMDAAC-co-DAMBAC) (9:1) is shown in According to the cumulative distribution curve of relative molecular weight, the homopolymers of PDMDAAC and PDAMBAC were dominant in poly (DMDAAC-co-DAMBAC) copolymers. The optimum polymerization conditions of the copolymers with different copolymerization ratios and the homopolymerized products’ relative molecular weight and conversion were compared, as shown in Different molar ratios of DAMBAC (substituent is benzyl) in the copolymer would lead to a tremendous difference in the characteristic viscosity of poly  of the copolymer product became lower and lower. It confirmed that as the proportion of DAMBAC in the copolymer increased, polymerization became more difficult. In addition, the enhancement of the steric hindrance effect made it challenging to prepare polymers with high molecular weights.In the meantime, the copolymer’s highest intrinsic viscosity (relative molecular weight) was DMDAAC, the inherent viscosity was 3.44 dL/g, and the relative molecular weight was 1.144 × 10co-DAMBAC) (9:1) copolymer for O/W oil emulsion with different characteristic viscosities. The results are exhibited in We also studied the optimum demulsification conditions and corresponding demulsification efficiency of the poly (DMDAAC-co-DAMBAC) (9:1) copolymer, when the intrinsic viscosity increased from [η] = 0.31 dL/g to [η] = 2.75 dL/g, the dosage decreased from 1.0 g/L to 0.1 g/L, the demulsification temperature decreased from 55.0 °C to 45.0 °C, and the demulsification time also reduced from 7 h to 5 h. The demulsification rate decreased slightly, from 97.73% to 96.81%. The main reason for this was that the molecular main chain length would rise with increased polymer characteristic viscosity (relative molecular weight). Meanwhile, the more polymer molecules that could achieve effective demulsification at the exact dosage, the higher the demulsification efficiency.It could be seen from ƞ] = 0.32 dL/g and [ƞ] = 0.33 dL/g were selected for comparison in this paper.To further investigate the demulsification performance of the copolymer prepared in this paper, it was compared with the demulsification performance of two monomer homopolymers, PDMDAAC and PDAMBAC, and the commercially available demulsifier, BQ-05. The results are shown in co-DAMBAC) (9:1) copolymer was not only higher than that of PDAMBAC, BQ-05, and PDMDAAC but also higher than the highest value of the BQ-05 demulsifier reported in the literature, which was 92.04% [It could be seen from s 92.04% .co-DAMBAC) (9:1) were selected for experiments, and the morphologies of oil droplets before and after the demulsification of the emulsion were photographed under a microscope. The results are shown in To compare the demulsification effects of different demulsifiers, PDMDAAC, BQ-05, and poly  in a copolymer could effectively improve the lipophilicity of the polymer, reduce the emulsion’s interfacial energy , and impw (M) = 80.0%, m (V50):m (M) = 0.700%, m (Na4EDTA):m (M) = 0.00350%, 1T = 50.0 °C, 2T = 60.0 °C, and 3T = 72.5 °C. The intrinsic viscosity of the product obtained under this process condition was 1.78 dL/g, and the double bond conversion (Conv.) was 90.25%. Through the characterization of the product structure and relative molecular mass, the results show that a poly (DMDAAC-co-DAMBAC) (9:1) product with a high, close molecular mass was synthesized, of which the relative molecular mass was wM = 5.637 × 105 g/mol and the polydispersity index was w/Mn)d (9:1) copolymer prepared in this paper was lower than that of PDMDAAC.Since the substituent of DAMBAC was benzyl, as the proportion of DAMBAC in the copolymer increased, the steric hindrance effect significantly reduced the polymerization activity. The intrinsic viscosity (relative molecular mass) of the poly (DMDAAC-co-DAMBAC) (9:1) copolymer was significantly improved, and its demulsification rate was up to 97.73% and 96.81%.Compared with PDMDAAC and PDMABAC, the demulsification performance of poly (DMDAAC-This work could lay a foundation for preparing diallyl cationic polymers and expanding the structure and application properties of such polymers.


Molecules with pleasant odors, unacceptable odors, and even serious toxicity are closely related to human social life. It is impractical to identify the odors of molecules in large quantities (particularly hazardous odors) using experimental methods. Computer-aided methods have currently attracted increasing attention for the prediction of molecular odors. Here, through models based on multilayer perceptron (MLP) and physicochemical descriptors (MLP-Des), MLP and molecular fingerprint, and convolutional neural network (CNN), we conduct the two-class prediction of odor/no odor, fruity/no odor, floral/no odor, and woody/no odor, and the multi-class prediction of fruity/flowery/woody/no odor on our newly refined molecular odor datasets. We show that three kinds of predictors can robustly predict molecular odors. The MLP-Des model not only exhibits the best prediction results  but can also well reflect the characteristics of the structure–odor relationship of molecules. The CNN model takes 2D molecular images as input and can automatically extract the structural features related to molecular odors. The proposed models are of great help for the prediction of molecular odorants, understanding the underlying relationship between chemical structure and odor perception, and the discovery of new odorous and/or hazardous molecules. In daily life, all kinds of molecular odors, including the attractive aromas of food and spices, the special odors, such as deodorant, body spray, soap, lotion and laundry liquid, or the rotten smell or unpleasant smells in garbage, not only affect our emotions, memories and behaviors but also have a certain impact on biological evolution . The ideIn the past, researchers generally identified the odor of compounds through sensory experiments; however, large-scale sensory evaluation tests require a great deal of time and effort. In recent years, researchers have used electronic noses to test molecular odors and even designed manual feature extractors to predict the odor characteristics of molecules. Otherwise, the above method depends on manual design and designer’s experience, with the poor universality and missing prediction in real time . At presIt is worth mentioning that the structure–odor relationship model can establish a link between molecular structure characteristics and odor perceptions. It can also be employed to identify toxic odors emitted by hazardous materials and the discovery odorous molecules . Due to Wu et al. constructed a CNN-based model for odor prediction using the response signal generated by an electronic nose, achieving a 99.9% accuracy in distinguishing between pleasant and unpleasant odors. Zhang et al.  developeAnother study by Sharma et al.  focused A set of descriptors for the target chemicals was successfully predicted by a series of computer simulations by Nozaki et al. . The modTo date, deep learning has achieved some pioneering results; however, it is still in the early exploration stage in the field of odor prediction; moreover, few studies have focused on the structure–odor relationship modeling of molecules. Deep-learning modeling requires high-quality molecular odor datasets as well as appropriate structural features that are closely related to molecular odors to ensure the predictive ability of the model. Certainly, it is necessary to improve the prediction accuracy of molecular odor; meanwhile, the in-depth investigation on the structure–odor relationships of molecules should be emphasized.Here, according to The molecular odor datasets were retrieved from FlavorDB  and PubCFirst, the positive and negative samples were assembled and then randomly disordered. Then, all the samples were divided into training set and test set according to 4:1, where the training set was used for modeling and the test set was employed to evaluate the predictive ability of the model. Additionally, the training set were divided into five sets for 5-fold cross-validation  or hold-As shown in For the MLP-Des model, variable loading analysis was applied for feature screening. First, the features with repeated meanings were removed according to the eigenvalues of the correlation coefficient matrix, and then the rotated component matrix was obtained by oblique rotation . The 75%Generally, MLP  updates the parameters by a back propagation algorithm and optimizes the model by a gradient descent algorithm. Here, the binary-classification MLP models were composed of three fully connected layers, and the weights were initialized by uniform distribution. The output layer used a Sigmoid activation function, while the rest used a ReLU activation function. In parallel, the multi-classification MLP models encompassed an input layer, two fully connected layers, and a four classified Softmax layer output layer . The twoThe basic component of CNN included a convolution layer, a pooling layer, and a full connected layer . The conThe ReLU activation function and the Sigmoid activation function were used for the intermediate layer and the output layer, respectively. The CNN-based multi-classification model was composed of five convolution layers and three pooling layers, and the last part was composed of two fully connected layers. The five convolution layers contained 32, 64, 64, 128, and 128 hidden neurons, respectively, and the fully connected layer contained 512 hidden neurons. The ReLU activation function was used for the intermediate layer, while the Softmax activation function was applied for the final fully connected layer, with the output value being the probabilities of the four categories.AUC) by receiver operating characteristics (ROC) [MCC) [A series of statistical parameters, including the Accuracy, Precision, Sensitivity, Specificity, Area under curve (cs (ROC) , and MatC) [MCC) , were usBased on the parameters  optimizeaccuracy of 0.98 (AUC of 0.99 (AUC of 0.96)  .accuracy values larger than 94.0% and AUC values greater than 0.98 for the prediction of odor/no odor, fruity/no odor, floral/no odor, and woody/no odor in the test set, suggesting that the model can better solve the issue of imbalance between odorous and odorless samples  [Accuracy = 0.90) [Accuracy = 0.75) [Accuracy = 0.97) [We compared the prediction results of molecular odors between the models established in this study and the methods reported in the literature. As shown in  = 0.94) , GA-ANN  = 0.90) , MILP/MI = 0.97) .AUC value of the multi-class prediction based on the MLP-Des model was equivalent to that of the SOR model.It was worth mentioning that the SOR model listed in Our MLP-Des model had the highest prediction ability, which was equivalent to or better than the results of the models listed in Molecular weight, electronegativity, and surface interactions were of great importance for odor recognition. In the odor/odorless prediction model, four extracted common factors explained more than 75% variance , atomic number (HeavyAtomCount), and molecular weight  were molecular composition descriptors; VSA_EState9, PEOE_VSA, and EState_VSA were related to the electronegativity and electrostatic interaction of the backbone atoms; LabuteASA, SlogP_VSA, SMR_VSA, and TPSA described the surface area, hydrophobic interaction, hydrophilic interaction, and polarizability. BertzCT was a quantitative indicator of the molecular complexity. Therefore, the molecular weight, electronegativity, and surface interactions played crucial roles in characterizing odorous molecules.Molecular charge, surface interaction, and shape were practicable for the identification of fruity odors. Seven common factors conducive to identifying fruity molecules were obtained by variable load analysis , molecular weights , atomic and valence electronic information (Chi-like descriptors), SMR_VSA (polarizability), PEOE_VSA (direct electrostatic interactions), and EState_VSA (electronegativity of skeleton atoms). The common factor 2 mainly reflected the characteristics of eight variables involving local charge , charge information (MinEStateIndex), the molecular shape used to characterize the graphic descriptors , HallKierAlpha, and Morgan fingerprint density (FpDensityMorgan 3). Thus, the features, such as molecular charge, surface interaction, and shape can be applied to identify fruity molecules.Molecular hydrophobic characteristics, composition, and charge were helpful in the identification of floral odors. A total of six common factors were extracted from the molecular descriptors in the floral/no odor prediction model . Therefore, molecular surface interactions, charge and molecular shape boosted the identification of woody odors.ss odors . What wess odors . The comMolecular charge, composition, shape, and surface interaction were suitable for multi-classification of molecular odors. In the multi-classification model, total ten common factors were extracted (xtracted . The resxtracted  exhibite3 hybridized carbon atoms (FractionCSP3), characterized molecular shape , and Morgan fingerprint (FpDensityMorgan) descriptors. In conclusion, the variable characteristics, including the molecular charge, composition, shape, and surface interaction, were beneficial to the multi-classification of molecular odors.The variables that had great influence on the common factor 2 mainly included the molar refractive index (MolMR), atomic and valence electronic information (Chi-like descriptors), molecular complexity (BertzCT), molecular fragment counts , rotatable bond count (NumRotatableBonds), proportion of spThe prediction of molecular odor based on computational methods has important practical significance for discovery of molecules with specific odors, in particular molecules with hazardous odors. The prediction modeling of molecular odor first requires high-quality molecular odor datasets. In recent years, the public molecular odor database has become an important source of datasets as used in this study. We combined the multi-step screening strategy to establish the molecular odor dataset , which wOur models based on deep-learning algorithms can well predict the odorous/odorless, fruity/odorless, floral/odorless, and woody/odorless characteristics of molecules. The models can be used to detect the odor of molecules and identify the molecules with specific odors to meet the need of food flavor, cosmetic fragrance, material preparation, etc. More importantly, the proposed models can be used to discern the molecules with toxic odor, and to clarify the structure–odor relationship of molecules, thereby, understanding the underlying mechanism targeting different odor receptors.MCC, AUC, and other indicators. Second, over-fitting was further avoided by the following means: (i) Molecular images were widely collected from multiple databases, and the datasets were cut, flipped, and illuminated to increase the diversity of samples. (ii) The weight was processed by L2 regularization to punish the features that were not important for molecular odors. (iii) Dropout was used to reset weight of some neurons in each training process to reduce the amount of parameters and avoid over-fitting. (iv) The training was terminated in advance by early stopping to avoid the increase of error rate on test set on the account of the excessive learning of the characteristics of training set, thereby, obtaining the best generalization model.Over-fitting is an issue to be solved in deep learning. Here, we took multiple steps to avoid overfitting. First, the generalization ability of the model was evaluated by a 5-fold cross validation, and the predictive ability of the model on the test set was evaluated by The MLP-Des model not only had the highest prediction ability for molecular odors but could also quantitatively describe the molecular structure–odor relationship. The structure–odor relationship investigations revealed that charge information played a crucial role in the identification of molecular odors in both the binary-classification  and the multi-classification (no/fruity/flowery/woody odor). Moreover, it is noteworthy that the characteristics representing four kinds of molecular odors cover those of the binary-classification prediction of molecular odors—that is, the characteristics conducive to identifying a single odor are also beneficial to identifying multi-class odors, which demonstrates the reliability of the extracted odor recognition characteristics from the side.The CNN model based on 2D molecular images exhibited high accuracy and stability for predicting molecular odors. In this study, the SMILES string was used to generate molecular image, which is mainly composed of two parts: the molecular pixel and background color. Molecular pixel is the key feature that the model needed to learn (about 10% of the whole image area), while the background color is invalid input or noise interference (about 90%). When image resolution is too low, the image is too fuzzy to effectively reflect the characteristics of molecular pixel. With the continuous improvement of resolution, the molecular pixel features are easier to be learned by the model. However, it must be noted that the increased area of molecular pixel is much smaller than that of background color every time resolution is improved. If the resolution is increased and transited, the dimension of input variables will soar up, resulting in many invalid background interference inputs, which will raise the difficulty of model training. Thus, the selection of molecular image resolution must be a process of gradual increase and then gradual decrease, and there is a peak optimal value. We attempted to construct images with different resolutions from 30 × 30 to 300 × 300; as a result, the prediction results are the best when the resolution is 32 × 32. The model can not only precisely identify the key molecular features related to odors but also efficiently deal with the interference of background color noise. Furthermore, CNN has the advantage in image recognition, that is, it can extract the key features of molecules without special high resolution to achieve high predictions. Therefore, CNN can automatically extract structural information related to molecular odors, thereby, avoiding the manual input of molecular structural parameters and obtaining a robust prediction model for molecular odors.Taking the visualization of Triacetin as an example , the feaWe constructed three kinds of predictors based on MLP-Des, MLP-Fin, and CNN to predict molecular odors. The results show that the MLP-Des model had the highest accuracy for the binary-classification prediction of odor/no odor, fruity/no odor, floral/no odor, and woody/no odor, as well as the multi-classification prediction of no/fruity/flowery/woody odor. The structure–odor relationship derived from the MLP-Des model revealed that molecular charge, weight, composition, shape, surface interaction, and hydrophobic interaction were closely related to the molecular odor characteristics. The CNN could automatically extract molecular image features, which could avoid large errors caused by screening features according to the designer’s experience; moreover, it was able to establish a close relationship between 2D images and molecular odors.In the future, with the development of separation and identification technology, more odor datasets will be obtained, which will lay a foundation for establishing more accurate prediction models. How to characterize the molecular structure and improve the modeling method is still an urgent problem that needs to be solved. The application of artificial intelligence provides a powerful tool for the prediction and modeling of various molecular odors. This study gives a theoretical basis for identifying potential molecules with specific odors and a methodological basis for predicting the odors of hazardous components in an environment.