Building on converging fields in molecular neuroscience, we discuss the substantial evidence implicating mitochondrial dysfunction in ASC to propose a novel role for mitochondrial allostatic load in the relationship between autism and psychopathology. An interplay between mitochondrial, neuroimmune and neuroendocrine signaling is increasingly implicated in stress-related psychopathologies, and these molecular players are also associated with neurodevelopmental, neurophysiological and neurochemical aspects of ASC. Together, this suggests an increased exposure and underlying molecular susceptibility to ELS that increases the risk of psychopathology in ASC. This article describes an integrative framework shaped by autistic experiences that highlights novel avenues for molecular research into mechanisms that directly affect the quality of life and wellbeing of autistic individuals. Moreover, this framework emphasizes the need for increased access to diagnoses, accommodations, and resources to improve mental health outcomes in autism.Molecular autism research is evolving toward a biopsychosocial framework that is more informed by autistic experiences. In this context, research aims are moving away from correcting external autistic behaviors and toward alleviating internal distress. Autism Spectrum Conditions (ASCs) are associated with high rates of depression, suicidality and other comorbid psychopathologies, but this relationship is poorly understood. Here, we integrate emerging characterizations of internal autistic experiences within a molecular framework to yield insight into the prevalence of psychopathology in ASC. We demonstrate that descriptions of social camouflaging and autistic burnout resonate closely with the accepted definitions for early life stress (ELS) and chronic adolescent stress (CAS). We propose that social camouflaging could be considered a distinct form of CAS that contributes to allostatic overload, culminating in a pathophysiological state that is experienced as autistic burnout. Autistic burnout is thought to contribute to psychopathology   Research into autism spectrum conditions (ASCs) spans disparate psychosocial and biomedical disciplines that traditionally work in isolation. However, the complex and rapidly evolving sociological context of autism research calls for a more integrative approach. Psychosocial and clinical conceptualizations of ASC fundamentally define the parameters of molecular autism research. Therefore, it is essential to integrate evolving understandings of autistic experiences within a molecular framework. Historically, ASC has been defined by the external perceptions of neurotypical observers rather than an understanding of internal autistic experiences . This haHowever, this paradigm shift is yet to be fully integrated into the medical and molecular fields of autism research, since these disciplines require unambiguous definitions of disease, reductionist animal and cell culture models, and highly specific questions with limited scope. The challenges of biomedical research are already compounded by the etiological heterogeneity of ASC , 16 and Nevertheless, molecular research has demonstrated potential to be relevant, useful and transformative for the autistic community. Genetic insight into the heritability of ASC has been instrumental in improving access to early diagnoses, and shifting blame away from caregivers or autistic individuals themselves for their differences. Moreover, an understanding of molecular ASC etiology has been used to mitigate common comorbidities that reduce quality of life. For example, molecular therapies have been developed to treat tumors and epilepsy in individuals with a monogenic form of autism called tuberous sclerosis . Concurrin vitro and in vivo molecular studies have failed to translate into reproducible results in human clinical trials  in ASC. Both ELS and CAS are known to contribute to psychopathology and a molecular interplay between mitochondrial allostatic load (MAL), the Hypothalamic-Pituitary-Adrenal (HPA) axis, and neuroinflammation is increasingly implicated in this association . NotablyASC is associated with a high prevalence of comorbid psychopathologies that substantially impair functioning and decrease quality of life –43. In pEmerging research has begun to characterize the distinct phenomena known as autistic burnout and social camouflaging, based on the lived experiences of autistic individuals. Importantly, this nascent research has intrinsic limitations in that it does not yet represent the diversity of experiences across the autism spectrum . Ongoinga state of physiological and psychological incapacitation, exhaustion, and distress in every area of life”  in both nuclear and mtDNA  and the activation of anti-inflammatory genes like annexin 1  or the NLRP3 inflammasome , culminating in disruptions to synaptogenesis, synaptic pruning, and neurotransmission , 164. Exvia mTOR-dependent mechanisms  metabolites  384). S. S384). ve state . Mitochove state ; conversve state . A pathove state . Moreoveve state . Altogetve state , 393.Thus, these neurotransmitter systems are intrinsically coupled to, and mediators of, the relationship between mitochondrial dysfunction, neuroinflammation and HPA axis signaling that is implicated in ELS and ASC. This discussion highlights that MAL plays a central role in the link between molecular stress signatures and neurophysiological- and neurochemical- mechanisms that lead to psychopathology. Moreover, these mechanisms are known to contribute to distinct neurological and behavioral aspects of ASC etiology and could function as an underlying susceptibility to allostatic load. This provides a preliminary conceptual framework for a molecular signature that may underly autistic burnout, mediate the relationship between social camouflaging and suicidality, or predispose autistic individuals to psychopathology. The interactions between environmental, psychological, physiological and molecular processes involved in ASC are notably understudied and the hypothesis proposed here remains to be further investigated. However, this model does illustrate the necessity for an interdisciplinary framework in molecular autism research. Moreover, our hypothesis describes a mechanistic interplay between MAL, HPA and neuroimmune signaling that could be an important target for future research toward improving quality of life in ASC.Molecular research into ELS is increasingly integrating various paradigms from disparate scientific disciplines in order to develop a cohesive understanding of pathological stress responses . While EThere is substantial evidence that autistic children are more likely to be exposed to ELS and psychosocial stress, while also having inadequate internal resources to cope with these stressors. The recent characterization of concepts like social camouflaging and autistic burnout further highlights that autistic children are exposed to chronic and distinct forms of stress throughout adolescence that often go unrecognized. Chronic social camouflaging creates an increasing mismatch between internal capacity and external expectations, culminating in autistic burnout. Importantly, both social camouflaging and autistic burnout are known to contribute to the development of psychopathology and suicidality in ASC. However, the physiological mechanisms that are involved in these phenomena, or their relationship to each other, remain unknown and largely unexplored by molecular researchers.The molecular mechanisms that mediate the relationship between ELS, CAS and psychopathology revolve around interdependent signaling between mitochondrial metabolism, inflammatory immune responses and stress-responsive HPA signaling. MAL is emerging as a central modulator of the neurophysiological processes that are disrupted by ELS and contribute to psychopathology. Notably, mitochondrial dysfunction is an underlying component of ASC physiology that is sensitive to GC signaling and plays a central role in regulating HPA axis and innate immune responses. Mitochondria function as essential regulators of neurodevelopment by facilitating the metabolic shift toward OXPHOS that is required for neuronal differentiation. Mitochondria also modulate microglial activation, which is necessary for synaptogenesis and synaptic pruning during neurodevelopment. Moreover, the relationship between mitochondrial metabolism and microglial activation regulates myelin turnover, neuronal function, redox homeostasis and glial inflammatory state throughout childhood and adolescence. The HPA axis is intrinsically coupled to both mitochondrial metabolism and inflammatory signaling, and this relationship is consistently shown to be disrupted by ELS and altered in psychopathology. Notably, the serotonergic, dopaminergic and glutamatergic neurotransmitter systems that are directly involved in many psychological disorders are closely coupled to mitochondrial metabolism, modulated by the HPA axis and represent independent mechanisms that contribute to gliosis and excitotoxicity. This article has highlighted how these molecular mechanisms are implicated in the neurophysiology and neurochemistry of autism and contribute to the development of psychopathology following ELS.Considering both the increased risk of exposure and underlying vulnerability to ELS in autism emphasizes how psychosocial and biological factors converge to increase the risk of psychopathology. This interplay could act as a novel mechanism that contributes to the high rates of depression and suicidality in autistic individuals and may reveal a biological signature that underlies autistic burnout. Autistic burnout, depression and suicidality are factors that directly impair health and wellbeing for people with autism. Much of the literature highlights the importance of improved access to accommodations, earlier diagnosis and decreased stigmatization of autistic traits in mitigating psychopathology in ASC. In addition, our framework proposes that investigating an underlying susceptibility to ELS could inform research into novel molecular interventions. Targeted therapeutic strategies could potentially protect autistic children from the development of psychopathology, facilitate recovery from autistic burnout, or identify diagnostic tools to differentiate autistic burnout from clinical depression. In particular, this framework highlights the potential to harness recent advances in mitochondrial psychobiology to better characterize the molecular determinants of mental health in autism. Ultimately, this highlights the utility of molecular research that foregrounds autistic experiences to work toward strategies that tangibly improve the quality of life of autistic individuals.The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.CM reviewed the relevant literature, developed the conceptual framework, and wrote the paper. CO'R refined the conceptual framework, wrote the paper, coordinated project supervision, and administration and acquisition of funding. Both authors contributed to the article and approved the submitted version.This work was supported by the University of Cape Town and the National Research Foundation, South Africa (Grant No. 138010).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.


Health is a fundamental human right and is a global goal to which extensive research effort is devoted in all fields. Chemistry plays a key role in understanding the mechanisms ruling health and disease conditions at the molecular level, as well as in discovering substances with pharmacological potential which can restore health status or mitigate pathology-related damage. One of the major challenges is to understand, rationalize, and control those molecular features which are crucial for a specific drug action. This problem is rooted in the well-known chemical ambition of establishing structure–activity relationships of general validity, although other relevant aspects must be considered, such as solubility, targeting efficiency, and toxicity.Stitching to the first essential aspect, we assist the continuous evolution of the chemical design approach, which was mainly based on the expensive ‘trial and error’ method only few decades ago. It is commonly accepted that the trials can be efficiently delegated to computers. Machine-assisted drug design has gained importance with the implementation of different methodologies, ranging from quantum chemistry to classic and continuum approaches, and, more recently, with the application of artificial intelligence algorithms. Despite the fact that there is plenty of room for improvement, large-scale screenings, protein–ligand and protein–protein docking, simulations, and molecular- and multi-scale mechanistic studies play an important role in research progress and receive a large consensus in health sciences.When we conceived this Special Issue, it became apparent for us to choose a topic and title which reflect our different background in medicinal and theoretical computational chemistry and is close to our joint collaboration. Combining our complementary expertise, we recently developed a project repurposing or better redesigning a popular antidepressant drug molecule, i.e., fluoxetine, which is better known by its commercial name, Prozac. We designed in silico a series of selenoderivatives of fluoxetine and assessed their enhanced antioxidant capacity through chemical and computational protocols ,2, and, Eucheuma gelatinae [O-glucuronide against cisplatin cytotoxicity in renal tubular cells [The Special Issue collected contributions from researchers all over the world, demonstrating the flourishing interest of the international scientific community towards the abovementioned aims and scopes. Amalia Stefaniu and colleagues reported a computer-aided screening of benzoic acid derivatives and semisynthetic alkyl gallates against SARS-CoV-2 main protease . Furtherelatinae . Daniel ar cells . Ivan Yuar cells . In the ar cells . In theiar cells .As a conclusive note as Guest Editors, we would like to sincerely thank all the authors for choosing our Special Issue to share the results of their research work, as well as the reviewers and the assistant editors for their valuable support.


SEM images confirmed the nanofibrous structure of samples with 100 ± 5 to 212 ± 25 nm in average diameter. Elemental analysis of nanofibers showed a good distribution of ZnO along nanofibers which not only caused decreasing in nanofiber diameter but also increased tensile strength of nanofibers up to 2.9 ± 0.5 MPa and with good elongation at break of 39 ± 2.9. ZnO nanoparticles also facilitated the interaction of nanofibers with water, and this led to the highest water vapor transition rate, which was equal to 0.28 ± 0.02 g cm−2 day−1. The sample containing 3 wt% Cur had the highest water uptake value (367 ± 15%) and the lowest water contact angle (78 ± 3.7°), although Cur has a hydrophobic nature. The release profile of Cur showed a two-stage release and the Peppas model predicted a non-fickian diffusion. Simultaneous incorporation of CS, ZnO, and Cur effectively inhibited bacterial growth. In addition, in vitro studies represented that high content of Cur decreases cell viability and cell attachment. The outcomes from the fabricated nanofibrous scaffolds demonstrated appropriate properties for application as a wound dressing.The potential of the nanoscale structure is utilized by electrospun nanofibers, which are promising materials for wound dressings. Here, we prepared wound dressings constituting polycaprolactone (PCL) and chitosan (CS). Curcumin (Cur) and zinc oxide nanoparticles (ZnO) as antibacterial agents were embedded in PCL/CS electrospun nanofibers and different properties including morphology, physicomechanical, interaction with water, antibacterial efficiency, and  In light of the advancements made in tissue engineering, the topic of electrospinning is gaining popularity in the biomedical world. The high available surface area and high porosity of electrospun nanofibers, being affordable and easy to handle, make electrospun nanofibers an ideal option for wound dressing . ElectroElectrospinning of pure CS is accompanied by several challenges associated with the limited solubility of pure CS in most organic solvents, its typically large molecular weights, and strong physical networks from hydrogen bonds . To addrvia electrospinning which showed a sustained release of the drug with minimized burst release. In recent years, electrospun PCL/CS has received a great deal of attention for the preparation of nanofiber scaffolds . PCL/CS In addition, with the development of electrospun nanocomposite scaffolds containing nickel nanoparticles , graphenIn this study, we electrospun a homogeneous mixture of CS and PCL and evaluated the success of creating nanofibrous scaffolds with the desired morphology. For the first time, Cur and ZnO were simultaneously added to the PCL/CS nanofibrous scaffolds because the antibacterial activity of CS-containing nanofibers is limited by the NH2 groups of the CS backbone . The fin−1, and density of 1.145 g cm3, CS with medium molecular weight and degree of deacetylation of 80%–85% (CAS Number: 9012-76-4), Cur drug, Hexafluoroisopropanol (HFIP), 3- -2,5 diphenyltetrazolium bromide (MTT), Phosphate-buffered saline (PBS), methanol, and ethanol were purchased from Sigma-Aldrich (Germany). ZnO with particles size of 10–30 nm, specific surface area of 20–60 m2 g−1 and purity of 99+% was purchased from US Research Nanomaterials, Inc (United States). The Staphylococcus aureus , Escherichia coli , and Fibroblast cells (L929) were purchased from the Pasteur Institute of Tehran (Iran).PCL granules with average molecular weight (Mn) of 80,000 g mol−1, respectively. The needle-to-collector distance and collector speed were fixed at 15 cm and 300 rpm, respectively. To prepare the electrospinning solution, a 15 wt% PCL solution in HFIP was first prepared by stirring (500 rpm) at ambient temperature for 120 min. Then CS was gradually added to the previous solution to reach a total concentration of 3 wt% and stirred (500 rpm) for 90 min. In the case of samples containing Cur and ZnO, they were added to the PCL/CS solution and sonicated for 30 min before electrospinning. A transition from yellow to orange was seen after the sonication process was finished. Finally, the prepared solutions were loaded in a 5 ml syringe with a standard blunt end needle (20 G) in the electrospinning setup. The electrospun nanofibers were placed in an oven for 24 h to dry completely. The sample codes and concentrations are listed in To determine the optimum condition of electrospinning a full factorial design experiment was conducted. Additional information is provided in the −1 and in the range of 600–4000 cm−1 by FTIR spectrometer of Thermo Nicolet Nexus 670 .The chemical structure of samples was investigated by attenuated total reflectance Fourier transform spectroscopy (ATR-FTIR). The spectrum was recorded through 64 scans at a resolution of 4 cmThe morphology of scaffold surfaces was evaluated with a scanning electron microscope  with an acceleration voltage of 20 kV. The distribution of ZnO nanoparticles incorporated into samples was investigated by using a scanning electron microscope with energy dispersive X-ray spectroscopy  with an accelerating voltage of 10 kV.The physical state of ZnO incorporated in samples was analyzed with X-ray diffraction  in the 2θ range of 5–80°. Applied radiation was Cu Kα with 40 kV, λ = 0.15418 nm, and 30 mA at room temperature.−1 until the fracture point according to ASTM D882 on a universal material testing machine .To investigate the mechanical properties, 5 replicates of each sample (50 mm × 10 mm × 2 mm) were stretched at a rate of 5 mm min−1 from 25 to 550°C.Thermogravimetric analysis was used to assess the thermal behavior of the materials . Under a nitrogen atmosphere, the pre-weighed samples (15 mg) were heated at a rate of 10°C.min2) using a 0.3 ml syringe. The contact angle of water drop on the surface of the samples was recorded after a few seconds from both sides of the drop. The reported contact angle was the mean of 5 replicates at 5 different sites of a sample.The hydrophilicity of the samples was evaluated using the sessile drop method by contact angle goniometer . To this end, a drop of distilled water was placed on the surface of samples , and Δt is the test time (day).To investigate the ability to control water loss, the water vapor transmission rate (WVTR) of samples was analyzed according to ASTM E96/E96M-10. The samples covered the opening of the 5 ml glass vial containing 1 ml distilled water. The container was placed in the humidity chamber with a constant temperature of 37°C and humidity of 25% for 48 h. A similar container without any sample was also placed in the humidity chamber as a control. WVTR was calculated using the in vitro degradation behavior of samples under physiological conditions, the samples (20 × 20 mm2) were immersed in PBS (pH = 7.4) and incubated at 37°C. The PBS solution was refreshed every 48 h. At each time point, the sample was removed from the solution and dried at 50°C. the weight loss of samples was calculated based on the i and Wt are the initial dry weight and the final dry weight of the samples (n = 3).To investigate the 2) were immersed in 5 ml of PBS (pH = 7.4) and incubated at 37°C. At specific time points, 1 ml of the media was extracted and replaced with 1 ml of fresh media. To determine the concentration of the sample, 5 solutions of Cur were prepared with different concentrations, and their maximum absorbance at 425 nm was measured by UV-Vis .To investigate the release profile of Cur drug, samples  and a Gram-negative (E. coli) according to agar diffusion method at 37°C. The strip-shaped samples (202) were immersed in methanol (90%) and PBS (pH = 7.4) for 15 min to neutralize and then sterilized by Gama radiation with a dose of 15 kGy. The samples were then suspended in bacterium solution and incubated in at 37°C in a shaking incubator for 24 h. The control was a suspension culture without any samples. The optical density of the samples was read by spectrophotometer at wavelength of 600 nm. The antibacterial efficiency was calculated based on the 1 and OD2 are the optical densities of the control medium and the bacteria in the solution-containing sample, respectively.The antibacterial activity of samples was investigated using two types of bacteria, a Gram-positive . After 24 h, the medium of each well was replaced with 200 μL of 0.5% MTT solution and incubated for 4 h. The MTT solution of each well was replaced with 150 µL isopropanol and the absorbance was read by ELISA at wavelengths of 490 and 630 nm as reference. Cell viability of samples was calculated by the s and ODc are absorption of sample and control, respectively.Cell viability of samples was investigated by MTT assay in direct mode. First, samples were sterilized using Gama radiation with a dose of 15 kGy. Suspensions of L929 cell line were seeded on the sterilized samples with a density of 5 × 10To investigate cell adhesion of samples, after 7 days of seeding cells on them, the media was extracted. The cells were fixed with glutaraldehyde (2.5% v/v) for 24 h. Then samples were dried with a series of ethanol solutions from 10 to 100% v/v and coated with gold to prepare for SEM analysis.−1 which are attributed to C-O stretching, asymmetric stretching of C-O-C bridge, CH2 deformation, and carbonyl ester bonds (C=O), respectively  compared to other samples. The results also revealed that Cur weakened the mechanical properties of electrospun nanofibers in a dose-dependent manner. The tensile strength, tensile modulus, and elongation at break of the nanofibrous scaffold containing 1 and 3 wt% Cur were 2.5 ± 0.4 and 2.6 ± 0.3 MPa, 0.18 ± 0.03 and 0.22 ± 0.02 MPa and 25 ± 2.2 and 22 ± 1.6%, respectively.The TGA curve of samples up to 550°C is shown in The addition of ZnO shifted starting point of degradation to higher temperatures (from 160°C to about 200°C). The ZnO nanoparticles are inorganic compounds with high thermal conductivity that accelerates heat transfer to other parts of the electrospun nanofibers and delays degradation. The effect of 1 wt% Cur on the thermal degradation of electrospun nanofibers is negligible, but for 3 wt% Cur an enhancement is shown. Notably, thermogravimetric analysis of the nanofibers verified the lack of HFIP solvent in them (boiling point = 58.2°C), which guarantees the biocompatibility of electrospun nanofibers.in vivo interaction between the surface of the damaged tissue and the wound dress. In general, increasing the hydrophilicity of the wound dressing surface leads to facilitated and improved cell adhesion and proliferation. The water contact angle (WCA) values of electrospun nanofibers are summarized in The contact angle between the water and the wound dressing provides useful information about the The results of water uptake are summarized in A dry wound or a wound infection can result from an imbalance of moisture and secretions between the wound dressing and the wound. To determine the gas exchange to the wound site, the WVTR of electrospun samples was investigated and summarized in 2 and OH groups that are found along the CS chains, which improve its hydrophilicity, CS can significantly contribute to boosting the degradation of electrospun nanofibers. In the other words, CS chains leak out of the scaffolds by dissolving in water over time (ver time . The eff2) and the best fitting  and Staphylococcus aureus (S. aureus), was investigated (E. coli and S. aureus, respectively. This is due to the interaction of NH2 groups of CS with PCL chains. Moreover, CS is an effective natural antibacterial agent against both bacteria and chitosan’s positive charge interacts with the negatively charged cell membranes to kill bacteria (The antibacterial activity of electrospun nanofibers against two types of bacteria, stigated . As expebacteria .E. coli while decreasing antibacterial effectiveness against S. aureus. It means that ZnO had a better performance against E. coli bacteria, which is due to their thin-walled nature (E. coli and S. aureus bacteria, respectively. These findings demonstrated that all nanofibers had appropriate antibacterial activity, making them viable scaffolds for use in wound dressings.ZnO nanoparticles had different effects on the antibacterial activity of the scaffolds against bacteria, increasing antibacterial activity against d nature . IncorpoIn order to study the cell viability of electrospun scaffolds, L929 cells were cultured directly on the nanofibers for 24 h. The cell viability of electrospun nanofibers is shown in The cell morphology on the electrospun nanofibers is illustrated in in vitro properties were investigated. SEM analysis showed smooth nanofibers with a bead-free morphology. The elemental analysis also proved a good distribution of ZnO in scaffolds. By adding ZnO, WVTR and nanofibers’ tensile characteristics were significantly improved, while the highest water uptake value was achieved for the sample containing 3 wt% Cur. The Cur drug released rapidly and reached a steady state about 24 h. The Peppas model provided the best fitting results on experimental data. Simultaneous incorporation of Cs, ZnO, and Cur effectively inhibited bacterial growth. The outcomes showed that electrospun nanofibers made of PCL, CS, ZnO, and Cur had a high potential for use as wound dressings.In this study, the PCL and CS mixture was successfully electrospun using a 15 wt% PCL and a 3 wt% CS in HFIP solvent to improve the hydrophilicity of PCL nanofibers for use in wound dressing applications. Afterward, Cur and ZnO were incorporated into the electrospun nanofibers, and their structural, physicomechanical, antibacterial activity, and


The richness of social media data has opened a new avenue for social science research to gain insights into human behaviors and experiences. In particular, emerging data-driven approaches relying on topic models provide entirely new perspectives on interpreting social phenomena. However, the short, text-heavy, and unstructured nature of social media content often leads to methodological challenges in both data collection and analysis. In order to bridge the developing field of computational science and empirical social research, this study aims to evaluate the performance of four topic modeling techniques; namely latent Dirichlet allocation (LDA), non-negative matrix factorization (NMF), Top2Vec, and BERTopic. In view of the interplay between human relations and digital media, this research takes Twitter posts as the reference point and assesses the performance of different algorithms concerning their strengths and weaknesses in a social science context. Based on certain details during the analytical procedures and on quality issues, this research sheds light on the efficacy of using BERTopic and NMF to analyze Twitter data. With its limitless availability of constantly growing datasets and simultaneous increase in computing power, the era of digital transformation has brought about the potential to alter social science structured analysis, different methods of reasoning, and big data analytics , hashtags, unknown signs, and emojis were removed. It is important to note that, up to this point, original sentences were used for BERTopic and Top2Vec since both algorithms rely on an embedding approach, and keeping the original structure of the text is vital for transformer models.Data collection was conducted in November 2021 by using the data extraction software tool Phantombuster and searching for the terms #covidtravel as well as the combination of #covid and #travel to fetch tweets. The initial datasets included a total of 50,000 tweets posted in English; however, after cleaning the data and removing duplicate posts, the final datasets consisted of 31,800 unique tweets. After that, the data underwent preprocessing in which all mentions  was removed, and tokenization was performed. Following this step, stemming and lemmatization were then conducted. The former process used Porter Stemmer to remove suffixes from words , whereas the latter used WordNet Lemmatizer to remove inflectional endings and to return a word to its base form . Lastly, the text was converted into term frequency-inverse document frequency (TF-IDF) weight for information retrieval based on the importance of a keyword.LDA, the most popular topic modeling technique, is a generative probabilistic model for discrete datasets such as text corpora  as well as for beta and alpha. The higher the beta, the more words the topics consist of; likewise, the higher the alpha, the more diverse the topics are. The search for an optimal number of topics started with a range from two to 15, with a step of one. In the first step of the learning process, K was pre-defined, and the search for beta and alpha was applied accordingly. During the process, only one hyperparameter varied, and the other remained unchanged until reaching the highest coherence score. The coherence score, referring to the quality of the extracted topics, presented itself for 14 topics with a value of 0.52. The grid search then yielded a symmetric distribution with a value of 0.91 for both alpha and beta. Finally, to facilitate a clear interpretation of the extracted information from a fitted LDA topic model, pyLDAvis was used to generate an intertropical distance map , into a product of a terms-topics matrix (W) and a topics-documents matrix (H) , a dimension reduction was performed before density clustering. By using uniform manifold approximation and projection (UMAP), the dimensions were reduced to the extent that hierarchical density-based spatial clustering of applications with noise (HDBSCAN) could be used to identify dense regions in the documents Angelov, . FinallyNotably, because words that appear in multiple documents cannot be assigned to one single document, they were recognized by HDBSCAN as noise. Therefore, Top2Vec does not require any preprocessing , or stemming and lemmatization  LDA and NMF and (2) Top2Vec and BERTopic. The latter highlights the term search function as one of the pros of using a guided/seeding approach to delve deeper into a specific topic.R(t) values, and travel restrictions in different countries. Taking “government response” as an example, tweets seem to focus on people's expectations toward the White House  and the US president . Although both models refer to the chance to reunite with their loved ones , LDA, in particular, points out how the COVID-19 pandemic has influenced the Diversity Visa Program  application. Likewise, while both models disclose Twitter users' opinions on travel ban restrictions and quarantine, the LDA results appear to be more geographically oriented. For instance, when discussing the reproduction number, European countries, India, and the UK are more frequently mentioned. On the other hand, England and Scotland appear to be the main focal point concerning travel restrictions, and as for tweets related to quarantine, LDA reveals issues surrounding the Australian border.Still, in spite of LDA performing seemingly better up to this point, the model produces more universal and irrelevant topics that, at the same time, barely offer any meaningful implications. This can be evidenced from the final four LDA topics listed in 0.50], followed by Topic 20 [0.37], Topic 7 [0.33], Topic 123 [0.32], and Topic 57 [0.30].By relying on an embedding model, BERTopic and Top2Vec require an interactive process for topic inspection. As such, both algorithms allow researchers to discover highly relevant topics revolving around a specific term for a more in-depth understanding. Using Top2Vec for demonstration purposes, this section begins with the intuition behind the search query. Presuming that there is an interest in topics related to the term “cancel” during COVID-19, the Top2Vec model produces relevant outputs (topics) based on the order of their cosine similarity . No Refund since then […]”) has a similarity score of 0.8518. This information allows one to gain deeper insights directly from the raw data. Meanwhile, in order to find more suitable keywords based on “cancel” for even further analysis, words that are most similar can be output with their similarity, such as “canceled [0.60],” “refund [0.49],” “booked [0.47],” “due [0.46],” and “ticket [0.43].”In order to acquire an overview of the importance of each term, a word cloud can be produced for better visualization see ; but, ulFollowing the search process, a topic comparison between Top2Vec and BERTopic could be established. This time, “flight” and “travel bubble” were taken as other examples. Since cosine similarity has previously been introduced, the following section merely lists some of the keywords that facilitate topic naming. As mentioned above, this is because the results require human interpretation to make sense of the data , they can, in fact, provide valuable insights, especially for the process of topic naming. Mostly, the content of a topic can be understood based on frequently-repeated keywords. Moreover, regarding the logic of the algorithm, since BERTopic and Top2Vec should not be preprocessed, conjunction words  are helpful for connecting the context. However, a major drawback without preprocessing is that (in)definite articles or be-verbs appearing in the keywords lists are often meaningless in comprehending a topic.Finally, it is worth noting that both Top2Vec and BERTopic allow for hierarchical reduction. Echoing this study's results, the number of extracted topics tends to be relatively large, thereby necessitating the need for intensive qualitative analysis. In order to streamline the analysis, the algorithms offer the possibility to reduce these topics further Angelov, . StartinTurning to BERTopic, since some of the topics are close in proximity, as could be observed in the intertopic distance map , visualiHowever, for both algorithms, the underlying meanings of the topics are still subject to human interpretation. Nevertheless, although the intuition is to provide the best possible results, an optimal number of topics could not be established because most of the topics overlap with one another and cover a mixture of two to three different aspects. For instance, the results from Top2Vec  present As shown in Baring the difficulties of extracting useful information from short and unstructured texts in mind, this research intends to confront such challenges by comparing the results of four topic modeling algorithms. For an overall evaluation based on human interpretation, this study supports the potency of BERTopic and NMF, followed by Top2Vec and LDA, in analyzing Twitter data. While, in general, both BERTopic and NMF provide a clear cut between any identified topics, the results obtained from NMF can still be considered relatively “standard.” Contrarily, in addition to the expected outcomes , BERTopic was able to generate novel insights using its embedding approach. Although Top2Vec also uses pretrained embedding models, the results cover more topics that overlap and contain multiple concepts. On the other side of the spectrum, similar to NMF, the topics produced by LDA do not seem to be very intriguing, either. Thus, despite some Top2Vec topics appearing as irrelevant and difficult to understand, the model, even so, is capable of producing a few interesting findings rarely mentioned by other algorithms . As a result, in favor of extracting novel conclusions, this research recommends Top2Vec over LDA. To provide a more solid foundation for these reasonings, a detailed evaluation for each algorithm will now be given.First and foremost, compared to other techniques, BERTopic works exceptionally with pretrained embeddings (Sánchez-Franco and Rey-Moreno, Slightly different from BERTopic and the implementation of c-TF-IDF, Top2Vec creates jointly embedded word, document, and topic vectors to find topic descriptions Angelov, . The intWith regards to NMF and LDA, notwithstanding that both algorithms do not require social scientists to have prior domain knowledge, several topics identified by LDA in this study yielded either universal (Rizvi et al., Lastly, when comparing BERTopic to NMF, a major shortcoming of NMF revolves around its low capability to identify embedded meanings within a corpus (Blair et al., Based on the outcomes of this study, as discussed above, via a thorough comparison of four different algorithms (Reisenbichler and Reutterer, In light of the expansion of user-generated content, social media has broadened the horizons for human interaction and provoked new phenomena and social research for further investigation Murthy, . AlthougForeseeing that social scientists may indeed hesitate to choose an appropriate algorithm when analyzing social media data, this study presents possible methodological issues and promotes the efficacy of two different types of topic models. To be more precise, applying BERTopic to generate insights from short and unstructured text offers the most potential when it comes to embedding-based topic models. Thus, this study acknowledges the capability of BERTopic to encode contextual information (Chong and Chen, This research is certainly not without its limitations. While this study responds to a need to utilize Top2Vec and BERTopic for the analysis of short-text data (Egger and Yu, The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.RE collected and analyzed the data. JY wrote the manuscript in consultation with RE and interpreted the data. Both authors designed the study and were responsible for the overall management and planning. All authors contributed to the article and approved the submitted version.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.


He gave birth to a boy by intracytoplasmic sperm injection (ICSI) using his ejaculated sperm purified to high density and motility by Percoll density gradient centrifugation. In conclusion, this case is a unique non-mosaic KS patient who had a normal sperm motility, experienced a natural fertility, and received a successful ICSI outcome, which enlarges our knowledges on non-mosaic KS.Klinefelter syndrome (KS) is the most common sex chromosome abnormality, which occurs in about one in 660 newly born males, and it is the most common genetic cause of infertility in infertile men, accounting for 11%. It is rare for non-mosaic KS patients to have sperm and reproduce naturally, and there are currently no reports of KS patients with normal motile sperm. Microdissection testicular sperm extraction associated with intracytoplasmic sperm injection (micro-TESE-ICSI) is currently the main assisted reproductive method for patients with KS. In this study, we describe a patient of non-mosaic KS  who had given birth to a healthy girl naturally. The patient had normal male characteristics and did not have the symptoms of hypogonadism commonly seen in KS. He had high levels of serum follicle stimulating hormone and luteinizing hormone, a low level of serum testosterone, and a normal level of prolactin. Semen analysis showed that this case had normal motile sperm  but low sperm concentration (1.7 × 10 Klinefelter’s syndrome (KS) is a common sex chromosome abnormality and occurs in about 0.10–0.15% of males . KS inclA 31-year-old man and his 29-year-old wife were admitted to the Reproductive Medicine Center of Jiangxi Maternal and Child Health Hospital affiliated with Nanchang University in 2018 for subfertility assessment. The couple participating in this study provided signed informed consent. This study was approved by the Institutional Ethics Committee on human subjects of Jiangxi Maternal and Child Health Hospital. The couple had been married for 8 years and had had a girl naturally in the second year of marriage. After 3 years of marriage, they wanted a second child, so they stopped using contraception, but had not succeeded in giving birth for 5 years. They had no significant medical or surgical history and were not on any long-term medications. The wife was checked to ensure that both fallopian tubes were unblocked, and her reproductive function was normal. Classic karyotyping of metaphases by Giemsa(G)-banding was performed as described elsewhere . G-bandiThe patient underwent andrology examination, semen analysis, and endocrine evaluation. The patient has a laryngeal knot and normal male breasts. The pubic hair is distributed in male characteristics, the penis developed normally, and the bilateral epididymis and vas deferens developed normally. According to testicular ultrasonography, the volumes of the left and right testes are calculated to be 6.6 ml and 7 ml, respectively . Semen aSufficient clinical evidence has found that patients with KS usually present with symptoms of hypogonadism such as tall height, small, hard testes, and disproportion between upper and lower body . NotablyAfter consulting with the genetics department, we recommended the treatment of preimplantation genetic testing (PGT). The couple decided against PGT for economic reasons and insisted on ICSI. Because the husband’s sperm motility is normal, but the sperm concentration is low, Percoll density gradient centrifugation on his spermatozoa was performed to increase the sperm concentration. Seven metaphase II oocytes were retrieved for ICSI and four oocytes were fertilized. Three transplantable embryos formed after standard embryo culture and one high-quality embryo was transferred. Eleven days after embryo transplantation, beta-human chorionic gonadotropin was determined to be positive. The wife later gave birth to a boy.The etiology of nonmosaic KS is an increase in the number of X chromosomes caused by errors during meiosis . The genTESE-ICSI is the main method of assisting the reproduction of patients with KS . CompareIn both the case presented and another case reported by Another notable thing in this case is that the patient did not have typical symptoms of hypogonadism. The clinical features depend on the extra X chromosome and the effects of hypogonadism . HoweverThis study reports the first case of a non-mosaic KS male who had ever given birth naturally, a boy born after ICSI using his normally motile ejaculate sperm. This case shows that sperm quality in KS patients declines over time. And hypogonadism is not the defining symptom of KS. This case reminds the study of the effect of extra X chromosome inactivation on spermatogenesis and sperm motility in KS patients, provides more clinical data for KS assisted reproductive therapy, and reminded that the early intervention treatment of KS patients may be a new idea to help future fertility.


EPHX2 gene) in the metabolism of polyunsaturated fatty acids (PUFAs) plays a key role in inflammation, which, in turn, plays a part in the pathogenesis of neuropsychiatric disorders. Meanwhile, epoxy fatty acids such as epoxyeicosatrienoic acids (EETs), epoxyeicosatetraenoic acids (EEQs), and epoxyeicosapentaenoic acids (EDPs) have been found to exert neuroprotective effects in animal models of neuropsychiatric disorders through potent anti-inflammatory actions. Soluble expoxide hydrolase, an enzyme present in all living organisms, metabolizes epoxy fatty acids into the corresponding dihydroxy fatty acids, which are less active than the precursors. In this regard, preclinical findings using sEH inhibitors or Ephx2 knock-out (KO) mice have indicated that the inhibition or deficiency of sEH can have beneficial effects in several models of neuropsychiatric disorders. Thus, this review discusses the current findings of the role of sEH in neuropsychiatric disorders, including depression, autism spectrum disorder (ASD), schizophrenia, Parkinson’s disease (PD), and stroke, as well as the potential mechanisms underlying the therapeutic effects of sEH inhibitors.It has been found that soluble epoxide hydrolase (sEH; encoded by the  Neuropsychiatric disorders, including depression, autism spectrum disorder (ASD), schizophrenia, and Parkinson’s disease (PD), are common brain diseases characterized by cognitive deficits, psychiatric symptoms, and somatoform symptoms . MeanwhiIn 2020, as COVID-19 spread throughout the world, the increasing SARS-CoV-2 infection rates and decreasing human mobility contributed to a significant increase in the prevalence of neuropsychiatric disorders . NeuroloIn general, fatty acids are the major products of lipid metabolism . AdditioThe biologically important long-chain PUFAs include docosahexaenoic acid DHA or 22:6 n-3) see , which r:6 n-3 seEPHX2 gene). For example, 19,20-epoxydocosapentaenoic acid  synthesized from DHA through the CYP pathway is metabolized into 19,20-dihydroxydocosapentaenoic acid  by sEH [Specifically, PUFAs are metabolized into bioactive derivatives by main enzymes such as cyclooxygenases (COXs), lipoxygenases (LOXs), and cytochrome P450s (CYPs) see  26,27,2,227,28, ) by sEH ,30. ARA ) by sEH . Further) by sEH .Since DHETs dramatically reduce biologic activity, sEH inhibitors have been extensively used to prolong the anti-inflammatory function of EETs in the ARA cascade ,34. SuchAccording to the 2021 Global Health Data Exchange, depression is one of the most common psychiatric disorders in the world, with an estimated 3.8% of the population affected, including 5.0% of adults and 5.7% of adults 60 years and older . CurrentThe cytochrome P450 epoxygenase CYP2J2 converts ARA into four regioisomeric EETs see , while sEphx2 KO mice did not show depression-like behaviors after CSDS, suggesting stress resilience [Ephx2 KO mice, indicating that the administration of “depression-related microbes” can contribute to the conversion of resilient Ephx2 KO mice into KO mice with depression-like phenotype [In a related study, the expression of sEH protein in the brain was higher in a sample of susceptible mice after chronic social defeat stress (CSDS) compared to the control mice . Other fsilience . Intereshenotype . Altogethenotype ,39,50.The downregulation of hepatic sEH in mice caused a reduction in sucrose preference and coat deterioration compared with the control group . MoreoveImmunoreactivity of sEH was also detected in astrocytes throughout the brain , whereasIn other research, pretreatment with TPPU attenuated the increase of pro-inflammatory cytokine IL-1β and rescued neuronal and dendritic spine loss in the hippocampus by increasing the expression of the N-methyl-D-aspartate receptor, the extracellular-signal-regulated kinase (ERK)1/2, and the CREB (cAMP response element binding protein) . In the Accumulating evidence has suggested that maternal immune activation (MIA) such as maternal infection can increase the risk of neuropsychiatric disorders  in offspring ,73,74,75EPHX2 mRNA in induced pluripotent stem cell-derived neurospheres was higher among schizophrenia patients than the controls [EPHX2 mRNA in the postmortem brain samples of ASD patients than that of the controls [Meanwhile, MIA using poly(I:C) has been widely used as animal models of ASD and schizophrenia ,81. For controls . There wcontrols . Additiocontrols ,53. CollIn related research, repeated treatment with TPPU in juvenile offspring from prenatal days P28 to P56 prevented cognitive deficits and loss of parvalbumin (PV)-immunoreactivity in the medial PFC of adult offspring, especially after MIA . AdditioEpidemiological studies have suggested that exposure to herbicides  during pregnancy might increase the risk of ASD in offspring. For instance, a population-based case study in California (USA) reported that the risk of ASD was associated with the use of glyphosate (odds ratio = 1.16) . It was Finally, the potent sEH inhibitor AS2586114 improved schizophrenia-like behavioral abnormalities  in a sample of phencyclidine (PCP)-treated mice, suggesting that sEH inhibitor might have antipsychotic-like activity . FurtherParkinson’s disease (PD) is a neurodegenerative disease characterized by the deposition of the aggregates of α-synuclein (termed “Lewy bodies”) and the loss of dopaminergic neurons in the substantia nigra (SN), which results in motor dysfunction and non-motor dysfunction ,91,92. PMultiple evidence has supported neuroinflammation-related oxidative stress in the pathogenesis of PD ,99,100. EPHX2 mRNA in human PARK2 (Parkinson’s disease protein 2) iPSC-derived neurons were significantly higher compared to the control groups [MPTP -induced neurotoxicity in the striatum and SNc of a sample of rodents has been a well-established preclinical in vivo model to study the pathogenesis of PD ,106. Higl groups , while tl groups . Interesl groups . Since Pl groups . In thisl groups ,108.MPTP-induced neurotoxicity in the striatum and SN, including the loss of the DA transporter (DAT), loss of tyrosine hydrolase (TH)-positive cells, and increased endoplasmic reticulum (ER) stress, was attenuated by repeated oral administration of TPPU . AdditioStroke, constituting a loss of blood flow to the brain, is the leading cause of disability and death worldwide. In fact, the global prevalence of stroke in 2019 alone was 101.5 million people . Acute eDespite extensive efforts to discover better therapies for stroke, treatment options are still limited. The primary current treatment for ischemic stroke is thrombolysis with the tissue plasminogen activator (tPA), which was approved by the Food and Drug Administration. However, it must be administered within a relatively short time window before neuronal loss occurs . While tEPHX2 gene variants in the Turkish population [As for sEH, it catalyzes the metabolism of EETs, which exhibit potentially beneficial actions in stroke via vasodilation, neuroprotection, promotion of angiogenesis, suppression of platelet aggregation, oxidative stress, and post-ischemic inflammation . In relapulation . Moreovepulation . CollectThe inhibition of sEH is also effective for reducing infarct volume, improving memory deficits, and alleviating cognitive impairment and microvasculature augmentation by suppressing neuroinflammation and increasing reparative cytokines and growth factors such as BDNF and doublecortin ,124,125.Finally, administration of TPPU or AUDA significantly promoted M2 polarization of microglial cells, which indicates a shift from pro-inflammatory polarized microglia to microglia that primarily release anti-inflammatory cytokines. This can result in the differentiation of oligodendrocytes, protection against white matter integrity, and remyelination against chronic hypoperfusion ,130,131.As discussed in this review, sEH inhibitors can exert a neuroprotective effect through potent anti-inflammatory actions, including BDNF-TrkB activation for inflammation-related endoplasmic reticulum stress and mitochondrial dysfunction . For exaCurrently, clinical studies using two sEH inhibitors  see  in human


Then, Lipofectamine/pDNA complexes were immobilized on the nanofibers through immersion in the solution containing the pDNA complexes, resulting in transfection and sustained delivery of pDNA. Cells cultured on the resultant nanofibers expressed genome-editing molecules including Cas9 protein and guide RNA (gRNA), resulting in targeted gene knock-in and knock-out. These results demonstrated the potential of Gelatin-Ph nanofibers obtained through electrospinning and subsequent HRP-mediated cross-linking for gene therapy and tissue regeneration by genome editing.The delivery of nucleic acids is indispensable for tissue engineering and gene therapy. However, the current approaches involving DNA/RNA delivery by systemic and local injections face issues such as clearance, off-target distribution, and tissue damage. In this study, we report plasmid DNA (pDNA) delivery using gelatin electrospun nanofibers obtained through horseradish peroxidase (HRP)-mediated insolubilization. The nanofibers were obtained through the electrospinning of an aqueous solution containing gelatin possessing phenolic hydroxyl (Ph) moieties (Gelatin-Ph) and HRP with subsequent HRP-mediated cross-linking of the Ph moieties by exposure to air containing 16 ppm H Delivery of nucleic acids such as DNA and RNA is an attractive technique for tissue engineering , wound hScaffolds, such as hydrogels ,10 and nElectrospinning is a technique for producing nanofibers by applying high voltage to a polymer solution. Electrospun nanofibers have several advantages, such as an ultrathin diameter and a high surface-to-volume ratio . In addi2O2 . T. T11]. T2O2 through HRP-mediated cross-linking. The cross-linked nanofibers showed excellent cytocompatibility. Immobilization of Lipofectamine/pDNA complexes on the nanofibers prevented the complexation of pDNA with serum proteins, which resulted in the sustained delivery of pDNA. Additionally, gene knock-in and knock-out could be achieved using the cross-linked nanofibers. Therefore, Gelatin-Ph electrospun nanofibers with Lipofectamine/pDNA complexes may be a potential candidate for gene delivery and genome editing. In summary, we developed Gelatin-Ph electrospun nanofibers with Lipofectamine/pDNA complexes for pDNA delivery. Gelatin-Ph electrospun nanofibers were insolubilized by exposure to air containing H


Tobacco smoking is a major public health burden. The first-line pharmacological treatment for tobacco smoking is nicotine replacement therapy ). Nicotine acts on nicotinic-acetylcholine receptors on dopamine terminals to release dopamine in the ventral and dorsal striatum encoding reward and habit formation, respectively.11C]raclopride positron emission tomography scan and smoked a cigarette while in the scanner. Identical procedures were followed for the PBO scan. A time-varying kinetic model was used at the voxel level to model transient dopamine release peaking instantaneously at the start of the stimulus and decaying exponentially. Magnitude and spatial extent of dopamine release were estimated. Smokers were subcategorized by nicotine dependence level and nicotine metabolism rate.To better understand treatment efficacy, a naturalistic experimental design combined with a kinetic model designed to characterize smoking-induced dopamine release in vivo was used. Thirty-five tobacco smokers  wore a NIC  for 1-week and a placebo patch (PBO) for 1-week in a randomized, counter-balanced order. Following 1-week under NIC and then overnight abstinence, smokers participated in a 90-minute [Dopamine release magnitude was enhanced by NIC in ventral striatum and diminished by NIC in dorsal striatum. More-dependent smokers activated more voxels than the less-dependent smokers under both conditions. Under PBO, fast metabolizers activated more voxels in ventral striatum and fewer voxels in dorsal striatum compared to slow metabolizers.These findings demonstrate that the model captured a pattern of transient dopamine responses to cigarette smoking which may be different across smoker subgroup categorizations.This is the first study to show that NIC alters highly localized patterns of cigarette smoking-induced dopamine release and that levels of nicotine dependence and nicotine clearance rate contribute to these alterations. This current work included a homogeneous subject sample with regards to demographic and smoking variables, as well as a highly sensitive model capable of detecting significant acute dopamine transients. The findings of this study add support to the recent identification of biomarkers for predicting the effect of nicotine replacement therapies on dopamine function which could help refine clinical practice for smoking cessation. All available treatments for smoking cessation have limited success rates3 and most smokers relapse within 6 months of a quit attempt.4 One of the most widely-used smoking cessation treatments is the transdermal nicotine patch (NIC). NIC is a type of nicotine replacement therapy that releases a steady, low dose of nicotine that is absorbed through the skin. Just like cigarette smoking, NIC releases dopamine in reward regions of the brain. There is evidence that nicotine replacement therapies reduce cigarette use.5 It may be possible that NIC alters reward via its own effect on dopamine to reduce cigarette use, but smoking-induced dopamine release in the striatum during NIC treatment has not been thoroughly investigated. Certain traits, such as nicotine dependence level and nicotine clearance rate, have been identified as predictors of treatment efficacy. Higher nicotine consumption level is strongly associated with higher nicotine dependence and both are associated with poorer treatment outcomes.7 Nicotine metabolism ratio (NMR) has recently been identified as a biomarker for predicting the success of smoking cessation with NIC compared to varenicline, an FDA-approved smoking cessation treatment that modulates dopamine release.9Tobacco smoking is the world’s leading cause of preventable death. It is largely driven by the reinforcing effects of nicotine—the primary addictive chemical in cigarettes—which activates nicotinic acetylcholine receptors located on dopamine neurons to release dopamine in mesolimbic brain regions such as the striatum which encodes reward.10–12 These studies used amphetamine as a test stimulus that releases robust amounts of dopamine via several neurobiological mechanisms. Unlike amphetamine, nicotine or cigarettes release much smaller amounts of dopamine lasting only minutes.13 Some studies have investigated smoking-induced dopamine-release14–18 and a few other studies have assessed the smoking-induced dopamine response to cessation treatments.19–21 However, the results of these studies have been inconsistent. The inconsistencies may be attributed to: (1) an inability of conventional tracer kinetic models to detect small and short-lived dopamine responses, (2) a weakness of nicotine as a test-stimulus and/or, (3) an excessive delay between the stimulus and the PET scan. First, studies that use conventional time-invariant tracer kinetic models, such as simplified reference tissue model,22 measure the average smoking-induced changes in dopamine binding over the scan duration. The parametric endpoint used in these studies, BPND (receptor availability), is a steady-state parameter that fails to accurately capture the small and transient (on the order of minutes) alterations in the dopamine system elicited by cigarette smoking.23 Second, many routes of nicotine delivery including nicotine gum, NIC, IV nicotine, and cigarette smoking have been tried. Administering nicotine in unnatural ways  may not produce a sufficiently robust dopamine response. Third, the dopamine response to cigarette smoking is brief so PET scanning too long after smoking may simply miss the response. In the present study, we used an appropriate model, a naturalistic stimulus, and a rigorous experimental design.Several positron emission tomography (PET) studies have examined the dopamine response in vivo in tobacco smokers.25 We also used the time-varying kinetic model LSRRM (linearized simplified reference region model),26 which models transient dopamine release peaking instantaneously at the start of the stimulus and decaying exponentially. Our two outcome measures were magnitude of dopamine release, and spatial extent of dopamine release in the precommissural striatum.27 We expected that the presence of NIC would alter the magnitude and location of the dopamine response to smoking, based on previous microdialysis and PET literature showing that repeated nicotine injections increase dopamine release in mesolimbic brain regions.29 We also expected that the putative biomarkers for treatment success (dependence level and nicotine metabolism rate) would affect the magnitude or spatial extent of the dopamine response, based on prior literature demonstrating the dopamine release was related to nicotine dependence20 and nicotine metabolism.31The current study is the first double-blind crossover design, including two PET scans per subject—one following 1-week on NIC and one following 1-week on a placebo patch (PBO)—to assess the effect of NIC on the striatal cigarette-induced dopamine response, at the voxel resolution. We evaluated whether nicotine dependence level (assessed as smoking pack-years), and nicotine clearance rate (assessed via NMR), affected NIC-induced changes to the transient dopamine response. We used motion-tracking technology and list-mode reconstruction to correct any intra-frame motion that might have occurred while subjects smoked inside the scanner during the scan.33 scores of 5.1 ± 0.4, indicating moderate dependence  were studied. Subjects had no history or evidence of significant medical disorders on physical exam and did not meet Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) criteria for current or past psychiatric or substance abuse diagnosis (except nicotine dependence). Smokers on average (±SE) smoked 14 ± 1.4 cigarettes per day for 18 ± 2.3 years and had Fagerström Test for Cigarette Dependence (FTCD)pendence . On inta11C]raclopride PET scan while continuing to wear the NIC/PBO from the previous day. While lying in the scanner during continuous scanning they smoked a cigarette, as previously described.24 Briefly, subjects smoked one cigarette of their own brand, with their dominant hand, at their own pace , starting at mid-session (35-min after scan start) without leaving the scanner. To remove secondhand smoke, an air filter  was positioned in front of the scanner and above the subject’s mouth for the entire scan duration. Identical procedures were followed for PBO condition. Smokers reported subjective ratings of craving, enjoyment of, and energized by the cigarette  pre- and post-cigarette smoking. Pre-scan withdrawal and craving measures were collected using the Minnesota Nicotine Withdrawal Scale (MNWQ)34 and Questionnaire of Smoking Urge (QSU),35 respectively.The study was approved by the Yale Human Investigation and Radiation Safety Committees. Subjects wore a NIC  for 1-week and a PBO for 1-week in a double-blind, randomized, counterbalanced, placebo-controlled, cross-over design. Following 1-week on NIC and then overnight abstinence, smokers participated in a 90-minute raclopride, a D2/3 antagonist, was synthesized as previously described in Ref. 13. Before each PET scan, a 6-min transmission scan was acquired for attenuation correction. [11C]raclopride was administered as a bolus by a computer-controlled pump  and collection of emission data for 90-min in 3-min time bins. The mean radioactivity dose was 19.2 ± 0.2 mCi . PET was performed with the High-Resolution Research Tomograph .A 3T structural magnetic resonance imaging (MRI) scan for anatomical localization was collected from each subject . raclopride concentration (in mass units) in the reference region (cerebellum) and the affinity (kD) of raclopride for the D2 receptor,36 to calculate the largest possible occupancy of the D2 receptor by unlabeled raclopride , and de-noised with a 3 × 3 × 3 voxel HighlY constrained backPRojection (HYPR) filter,39 according to the methods previously described.39 A 3D Gaussian filter (σ = 2 voxels) and was applied. PET data were aligned to the subject’s MRI and then spatially normalized to a standard MNI-152 template. A standardized 1004-voxel mask delineating the precommissural striatum and its subregions , based on Martinez et al.,27 was applied to all subject images in template space prior to analysis.PET data were reconstructed using Motion-compensation OSEM (ordered subset expectation maximization) List-mode Algorithm for Resolution-recovery reconstruction (MOLAR),26 was fitted to the PET time-activity curve at each voxel. LSRRM parses the PET signal into a steady-state radiotracer component and a transient dopamine component. The transient component models dopamine release (starting and) peaking instantaneously at the start time of the stimulus  and decaying exponentially.40The LSRRM model41 was determined by model comparison between LSRRM and multilinear reference tissue model,42 using the Akaike information criterion corrected for small data sets.43 LSRRM estimates four parameters; multilinear reference tissue model (nested within LSRRM) estimates three. A cluster-size threshold (CST = 15 voxels) was applied to all significant voxels to correct for multiple comparisons.41 For a lengthy discussion of CST to correct for multiple comparisons, see paper by our group41 as well as others.44–46SignificanceParametric images were created for two endpoints: magnitude of dopamine release and spatial extent of dopamine release.“Magnitude of Dopamine Release” Images.Images of 48 These images were produced for each subject and condition. The change in magnitude of release between conditions, 1. Scans from 25 subjects were used to create “Magnitude of Dopamine Release” images. Three subjects were excluded because data were only available for one condition. Another subject was declared an outlier (>3 standard deviations from the mean number of activated voxels per subject on PBO) and removed. Six subjects did not have any voxels with a statistically significant level of detectable dopamine signal for either condition and their responses were deemed “below the level of detectability” (BLD) and excluded. All other subjects had at least one cluster with a significant dopamine response, for either condition.“Spatial Extent of Dopamine Release” Images. Images were produced by summing the binary masks for all subjects and dividing by the number of subjects, for each condition. “Spatial Extent of Dopamine Release” induced by smoking was defined as the number of voxels activated by smoking and compared between groups and conditions, by subregion. All 35 subjects were used to create “Spatial Extent of Dopamine Release” images. “Spatial Extent of Dopamine Release” images were also created for low and high pack-years groups, and slow and fast metabolizer groups, for each condition. Statistical significance in the mean number of voxels activated by smoking in each subregion of the mask was assessed with a permutation test , as previously described.24 For each permutation test, one hundred thousand random re-samplings scans were performed to achieve a zero mean difference between conditions in each subregion. Each set of re-samplings was used to create a null distribution for two arbitrary groups reflecting the actual sizes of the two experimental cohorts. To assess the likelihood of any given difference occurring by chance, we tested whether the mean value of the difference between PBO and NIC conditions was different from the zero (the null distribution) for each subregion. The null hypothesis of all permutations tests was that the mean difference in number of smoking-induced activated voxels between conditions was not different from zero, in a given subregion.2. R1 and BPss, are available from LSRRM. R1 describes the relative radiotracer delivery to the target region and BPss describes the receptor availability, absent the effects of the smoking stimulus. They were produced to compare the steady-state levels of radiotracer delivery and available dopamine receptors between conditions , nor did it change any findings of significance between subgroups (Twenty-eight (excluding outlier and BLD) smokers  were included in the final analysis. The exclusion of the outlier and BLD subjects did not change demographic or smoking measure data (ubgroups .p = .002) and PBO  patches relative to baseline , demonstrating compliance with, and possibly effectiveness of, the patch protocol.On average, subjects smoked less cigarettes per day during the week they were on NIC , demonstrating compliance with the patch usage protocol (p > .53). Smoking measures  were also not different between conditions (p > .41). The exclusion of outlier and BLD subjects did not impact significant and nonsignificant NIC versus PBO differences.Plasma nicotine and cotinine levels were higher under NIC than PBO condition  was only 5.7%.On average, there were no significant differences in injected radiotracer activity between low and high pack-years, fast and slow metabolizers, first and second scans, or NIC and PBO scans . The excSteady-state parameter images were not different between conditions (see increased under the NIC compared to PBO condition (p < .05). The average decreased under the NIC compared to PBO condition (p < .05). The overall pattern of p < .05). Within the low pack-years group, under PBO compared to NIC, fewer voxels were activated in bilateral VS (p < .05), whereas more voxels were activated in bilateral DC and left DP (p < .05). Within the high pack-years group, more voxels were activated under PBO compared to NIC in bilateral DC and bilateral DP (p < .05). See p < .05). Yet, the slow metabolizers activated more voxels than fast metabolizers under PBO in bilateral DP and left DC (p < .05). Among the slow metabolizers, more voxels were activated under PBO compared to NIC in the bilateral DC and bilateral DP (p < .05). Among the fast metabolizers, more voxels were activated under PBO compared to NIC in the bilateral VS, bilateral DC, and bilateral DP (p < .05). See 5 In-scanner cigarette smoking decreased craving and increased enjoyment and energy ratings, as expected. Because subjective ratings of craving, enjoyment, and energy were not different between conditions, we did not predict that they would be related to brain changes. Subgroups and conditions were well-matched on injection parameters. This study has three main findings: (1) Among all smokers, the magnitude of dopamine release was enhanced by NIC in VS and diminished by NIC in DC and DP. (2) The more-dependent smokers activated more voxels than the less-dependent smokers under both conditions and less-dependent smokers activated more voxels in VS and fewer in DC and DP under NIC compared to PBO. (3) Fast and slow metabolizers activated more voxels under PBO compared to NIC in whole and dorsal striatum, respectively. Under the PBO condition only, fast metabolizers activated more voxels in VS and fewer voxels in DC and DP compared to slow metabolizers. Overall, our model captured mild, brief, and spatially localized dopamine responses to cigarette smoking which differed, regionally, by patch conditions and smoker subgroup categorizations, such as pack-years and nicotine metabolite ratio.This is the first double-blind, randomized, placebo-controlled, cross-over study to examine cigarette-induced dopamine release following short-term nicotine replacement therapy. Smokers complied with the medication regimen, as evidenced by higher blood nicotine and cotinine levels under NIC condition compared to PBO and reduced smoking during the patch protocols relative to baseline, consistent with prior literature.R1 and BPss) occurred between treatment conditions, throughout the striatum, as expected. R1 describes relative radiotracer delivery to the target region and BPss describes the receptor availability, absent the effects of the smoking stimulus. Both parameters represent the system at steady-state as opposed to effects of transient changes in available receptors caused by smoking-induced dopamine release. NIC may alter cigarette-induced dopamine release but is not expected to affect steady-state binding conditions appreciably. R1 and BPss images can be thought of as negative controls. These images  on the first scan.an first .BPND assume a constant concentration of dopamine throughout the scan, and thus can only provide a crude estimate of changes in neurotransmitter level.23 An unintended consequence of using a time-invariant endpoint to describe a time-varying signal is that the endpoint is dependent on the duration of the scan.51 Relatively weak elevations in dopamine concentration, such as those caused by cigarette smoking, may be missed entirely. For example, studies have shown no dopamine release following a nicotine stimulus, for example, Ref.52, or no group differences in smoking-induced dopamine release, for example, Ref.21. The parameter presented herein, BPND in the literature because it evaluates the change in the level of dopamine binding. However, The ability to capture subtle fluctuations in endogenous dopamine concentration within a single-scan is novel and possible thanks to sophisticated modeling techniques. The presence of a time-varying term in LSRRM makes the model sensitive to brief dopamine competition with the radiotracer. Traditional kinetic models fail to capture transient disturbances of equilibrium caused by transient  dopamine release. Conventional time-invariant endpoints such as 29 regardless of the effects of treatment.15 Rollema et al. theorized that despite chronically elevated nicotine levels due to NIC, cigarette smoking still causes steep increases in nicotine levels and in dopamine release, thus, maintaining its reinforcing effect.53 This additive rewarding effect may be critical for driving smoking behavior and may decrease the likelihood of successful cessation. It is also important to note that subjects were overnight abstinent. Thus, the cigarette smoked in the scanner was the first cigarette of the day, which is the most pleasurable.54 Further, we found subregional variation in the effect of NIC on smoking-induced dopamine release consistent with previous reports. One study found that continuous microinjections of nicotine into the rat brain both increased and decreased [11C]raclopride dopamine release in the striatum, suggesting that local extracellular dopamine levels may have increased but extracellular levels of dopamine in the whole striatum may have decreased.55 An functional MRI study found that NIC increased smoking cue-induced activation in the caudate while decreasing putamen activation relative to PBO,56 supporting our findings. Heterogeneity in the spatial pattern of pharmacologically-induced dopamine release has also been reported for other drugs. For example, Yoder et al.57 found that individual dopamine responses to alcohol in the striatum were highly localized and varied widely by subject. Taken together, we can deduce that the pattern of cigarette-induced dopamine release is a complicated, highly localized phenomenon such that NIC treatment may not necessarily affect the striatum homogeneously, or even in a single direction.We found that the magnitude of cigarette-induced dopamine release was greater under NIC compared to PBO condition in VS, suggesting an additive reinforcing effect of nicotine on the brain’s dopamine system. This is consistent with previous microdialysis and PET literature showing that a nicotine challenge following repeated daily injections increases dopamine release in a dose-dependent manner,20. Animal studies have demonstrated that repeated nicotine administration enhances psychomotor responses, the rewarding effects of nicotine, and striatal dopamine release in response to nicotine.28 In humans, nicotine gum-induced dopamine release in the VS was shown to be positively correlated with the degree of nicotine dependence.20Nicotine dependence level was related to cigarette-induced dopamine release. More-dependent smokers activated more voxels than less-dependent smokers regardless of the condition, suggesting that the longer people engage in their addictive behavior, the more of the striatum they must recruit to process rewarding and enjoyable stimuli. This is consistent with prior literature, for example, Ref. 58 We believe our finding links previous work in cocaine-dependent animals to nicotine-dependent humans who are dependent on nicotine for years as opposed to weeks/months in animals. Regardless of nicotine dependence level, smokers had a more widespread response across the dorsal striatum  under PBO compared to NIC condition, suggesting that in response to a cigarette, more of the habit-related striatum was recruited when nicotine concentrations were lower in the blood, and presumably the brain.Our study also showed that more-dependent smokers activated more voxels in dorsolateral as opposed to ventral regions of the striatum than less-dependent smokers, suggesting a migration of dopamine activation from the goal-directed to the habit-formation striatum over time.59 This is consistent with studies showing that fast metabolizers have a greater dopamine or neural response than slow metabolizers when viewing smoking cues.31In the present work, nicotine clearance rate was associated with cigarette-induced dopamine release. Under PBO, fast metabolizers activated more voxels than slow metabolizers in the entire striatum, suggesting an enhanced dopamine response to cigarette smoking in individuals that clear nicotine faster. Fast metabolizers of nicotine experience a more rapid rate of absorption, entry of nicotine into the brain, a greater rush, and thus, greater reinforcement.11C]-(+)-PHNO BPND between fast and slow metabolizers.21 However, this could be explained by a number of methodological differences between this study and our study including a less sensitive analysis method and a lengthy delay between cigarette smoking and PET scanning in the work by Di Ciano and colleagues. Fast metabolizers experience greater daily fluctuations in nicotine concentrations which may explain why they experience greater reward from smoking.60 Among slow metabolizers, NIC contributed to a greater spatial extent of dopamine response than PBO while the opposite was observed in the fast metabolizers in VS, DC, and DP. This finding could explain why, for slow metabolizers NIC is more efficacious whereas for fast metabolizers better smoking outcomes are achieved on therapies such as varenicline and bupropion, both of which increase dopamine concentration in the blood and presumably the brain.59 An improved understanding of the mechanisms underlying NMR associations with treatment response such as NIC, could help refine clinical practice for smoking cessation.One study previously examined cigarette-induced dopamine release between fast and slow metabolizers. No differences were found in post-cigarette [This study included a number of limitations that were primarily related to PET scanning and analyses.One of the goals of this study was to examine sex differences. We found that the overall pattern of 53. The true range of start-times and peak-times for the dopamine response is unknown and may vary based on treatment and subject. Our group has developed a suite of time-varying “ntPET” models that are specifically tailored to characterize the transient changes in neurotransmitter binding caused by a drug stimulus, for example, Ref. 61. We have used the lp-ntPET model, for example, Ref. 41 to not only detect, but also characterize brief smoking-induced dopamine transients at the voxel level—revealing novel sex differences in the spatiotemporal signature of the dopamine response.24 However, for the sake of parameter parsimony, we chose to model the dopamine response with a fixed start-time and peak-time with LSRRM. There is a tradeoff between sensitive detection and accurate characterization of the dopamine response. The reduced number of estimated parameters in LSRRM allows for greater detection sensitivity of the dopamine response, using the current significance testing approach that relies on model comparison.LSRRM models the dopamine response as starting (and peaking) at the time of stimulus and decaying exponentially thereafter. The assumption of an instantaneously-peaking response may be too restrictive for our data. Microdialysis experiments suggest that the peak magnitude of the dopamine response following a pharmacological stimulus could have a latency period, for example, Ref. 62This study was intended to capture the brief, small, dopamine response caused by a smoking stimulus. The transient nature of the dopamine response and sparseness of detected responses suggests that the smoking-induced dopamine response is at the limits of voxel-level detection with the current PET scanner technology. Due to the challenges in detection, each subject’s binary significance mask was sparsely populated within the precommissural striatum. That is, only a small fraction of subjects contained a significant t-test or Wilcoxon sign-rank test (two-tailed). No statistical differences in This is the first study to show that NIC alters highly localized patterns of cigarette smoking-induced dopamine release and that levels of nicotine dependence and nicotine clearance rate contribute to these alterations. This current work included a homogeneous subject sample with regards to demographic and smoking variables, an absence of comorbidities, and subject compliance with treatment, as well as a highly sensitive model capable of detecting significant acute dopamine transients. The findings of this study add support to recent identification of biomarkers for predicting the effect of nicotine replacement therapies on dopamine function.https://academic.oup.com/ntr.A Contributorship Form detailing each author’s specific involvement with this content, as well as any supplementary data, are available online at ntac026_suppl_Supplementary_MaterialClick here for additional data file.ntac026_suppl_Supplementary_DataClick here for additional data file.