General public, often called consumers, are increasingly seeking health information online. To be satisfactory, answers to health-related questions often have to go beyond informational needs. Automated approaches to consumer health question answering should be able to recognize the need for social and emotional support. Recently, large scale datasets have addressed the issue of medical question answering and highlighted the challenges associated with question classification from the standpoint of informational needs. However, there is a lack of annotated datasets for the non-informational needs. We introduce a new dataset for non-informational support needs, called CHQ-SocioEmo. The Dataset of Consumer Health Questions was collected from a community question answering forum and annotated with basic emotions and social support needs. This is the first publicly available resource for understanding non-informational support needs in consumer health-related questions online. We benchmark the corpus against multiple state-of-the-art classification models to demonstrate the dataset’s effectiveness. For example, when someone with a severe, life-threatening condition interacts with others who have experienced similar medical conditions, they feel more supported5. Although consumers may find the information they need about the disease, such as treatments, symptoms, and side effects on authoritative health-related websites, getting emotional support or social networking support has been shown to add value, but can currently be obtained mostly through online interactions with peers. Previous studies have shown that social support is associated with improved well-being and better health outcomes8. The advent of medical Question Answering (QA) Systems has been considered as a promising solution and an efficient approach for retrieving relevant and precise answers from several health-related information sources9. Automated medical QA may support clinical decision making providing necessary information that otherwise is hard to find. Several research efforts tackled the problem of medical QA and highlighted the challenges related to question understanding, answer retrieval, and answer generation from the perspective of informational needs12. To the best of our knowledge, no studies were previously dedicated to medical QA and social and emotional support needs.Health Consumers may turn to online resources to satisfy not only their informational needs, but also seek emotional or social support. The benefits of social and emotional support have been well documented in the literature13, we believe that questions containing social and emotional needs have unique characteristics that require analysis and evaluation in a dedicated study. These characteristics include (i) variety of emotional states , (ii) emotion causes that may differ from the topic of the question, (iii) different types of social support needs , and (iv) a need for different answers based on the social support needs sought.While such consumer health questions (CHQ) have been included in a variety of earlier studies as part of broader and more diverse QA tasksTo illustrate, consider the consumer question from Yahoo! Answers Q&A in Fig. 12. To date, only a handful of works have considered emotional and social support in different contexts. For example, Sharma et al.14 introduced a dataset of 10,000 online conversations in which the responses were annotated using an empathy framework to indicate whether the response post contained no communication, weak communication, or strong communication of empathy. Another dataset introduced by Hosseini and Caragea15 includes messages in online support groups annotated as seeking or expressing support. The dataset contains 5,007 sentences, each annotated with one of the three empathy labels: seeking-empathy, providing-empathy, or none. Sun et al.16 annotated 4,012 answers with a set of mental health support strategies based on psychological counseling theories. Another dataset created by Liu et al.17 is based on 1,053 statements from a dialog system labeled as help-seeker or supporter mode, based on helping skill theory. These previous studies have provided useful references for emotional and social support corpus development. However, the existing collections’ coverage was insufficient in terms of available annotated consumer health questions to train and build efficient systems to answer beyond informational needs.Due to the importance of annotated questions for medical QA research, several efforts have focused on this task and collected some relevant datasetsTo this end, we introduce CHQ-SocioEmo, a manually constructed consumer health questions dataset covering social and emotional support needs. CHQ-SocioEmo was collected from a community question answering forum and therefore it is a valuable resource for understanding non-informational support needs in consumer health-related questions online. The CHQ-SocioEmo dataset consists of (a) various aspects of questions annotated based on demographic information, question focus, emotional states and evidence statement, emotion causes, social support needs and (b) annotated answer based emotional support provided. In addition to releasing CHQ-SocioEmo, we include experiments using baseline and state-of-the-art classification approaches, focusing on identification of social support needs, in order to demonstrate the value of CHQ-SocioEmo and benchmark the dataset for future researchers. The flow of building the CHQ-SocioEmo dataset is shown in Fig. 18. The dataset is made available by Yahoo! Research Alliance Webscope program to the researchers upon providing consent for using data for non-commercial research purposes only. The Yahoo! Answers L6 dataset contains about 4.4 million anonymized questions across various topics along with the answers. Additionally, the dataset provides various question-specific meta-data information such as best answers, number of answers, question category, question-subcategory, and question language. Since the focus of this study is on consumer health, we restricted ourselves to the questions whose category is “Healthcare” and the language is “English”. To further ensure that the questions are from diverse health topics and are informative, we devised a multi-step filtering strategy. In the first step of filtration, we aim to identify the medical entities in the questions. Towards this, we use Stanza19 Biomedical and Clinical model trained on the NCBI-Disease corpus for identifying medical entities. Next, we selected only those question threads with at least one medical entity present in the question. With this process, we obtained 22, 257 question threads from Yahoo! Answers corpus. In the final step, we remove any low-content question threads. Specifically, we retained the questions having more than 400 characters, because longer questions tend to include a variety of needs and background information of health consumers. The final data includes 5,000 question threads.We utilized the popular community question answering, “Yahoo! Answers L6” datasetWe used our own annotation interface for all annotation stages. We deployed the interface as a Heroku application with PostgreSQL database. Each annotator received a secure account through which they could annotate and save their progress. We started with smaller batches of 20 questions, and gradually increased the batch size to 100 questions as the annotators became more familiar with the task. The first 20 questions  were the same among all annotators, so the annotators worked on the task in parallel. Their annotations were first validated on a trial batch, and they were given feedback to help them correct their mistakes. They were qualified for the main annotation rounds after demonstrating satisfactory performance on the trial batch. In addition, group meetings were conducted to discuss disagreements and document their resolution before the next batches were assigned.The following aspects of the questions were annotated:Demographic information includes the age and sex mentioned in consumer health questions.Question Focus is the named entity that denotes the central theme (topic) of the question. For example, infertility is the focus of the question in Fig. 20, annotators label a question with all emotions contained. The annotators were allowed to assign none, one or more emotions to a single consumer health question, for example, a question could be annotated as exhibiting sadness or a combination of sadness and fear. Below are the included emotional states along with their definitions.Sadness: Sadness is an emotional pain associated with, or characterized by, feelings of disadvantage, loss, despair, grief, helplessness, disappointment, and sorrow.Joy: A feeling of great pleasure and happiness.Fear: An unpleasant emotion caused by the belief that someone or something is dangerous, likely to cause pain, or a threat.Anger. It is an intense emotional state involving a strong uncomfortable and non-cooperative response to a perceived provocation, hurt or threat.Surprise. It is a brief mental and physiological state, a startle response experienced by animals and humans as the result of an unexpected event.Disgust. It is an emotional response of rejection or revulsion to something potentially contagious or something considered offensive, distasteful, or unpleasant.Trust. Firm belief in the reliability, truth, ability, or strength of someone or something. That does not include mistrust or trust issues.Anticipation. Anticipation is an emotion involving pleasure or anxiety in considering or awaiting an expected event.Denial. Denial is defined as refusing to accept or believe something.Confusion. A feeling that you do not understand something or cannot decide what to do. That includes lack of understanding or communication issues.Neutral. If no emotion is indicated.Given a predefined set of Plutchik-8 basic emotionsEmotion evidence is a part of the text that indicates the presence of an emotion in the health consumer question, so annotators highlight a span of text that indicates the emotion and cues to label the emotion.Emotion cause is a part of the text expressing the reason for the health consumer to feel the emotion given by the emotion evidence. That can be an event, person, or object that causes the emotion.Alongside, we distinguish between emotion evidence and emotion cause, and we ask annotators to label both accordingly.infertility. As can be seen in this example, the evidence and the causes are not always found within one sentence. The annotation interface, however, ties them together.For example, the sentence, “Do you think my outlook is a good one?”, shown in Fig. 21, social support exchanged in different settings can be classified as follows:Informational support Emotional support Esteem support Network support .Tangible support According to Cutrona and Suhr’s Social Support Behavior CodeExamples of the five social support needs are represented in Table The following aspect of the answers was annotated:Emotional support in the answer. For each answer, annotators had to read the answer and indicate if it is responding to the emotional/esteem/network/tangible support needs by following:Yes: if the answer is responding to the emotional, esteem, network, or tangible support needs. The answers were not judged on the completeness or quality with respect to the informational needs. The text span that cued the annotator to the positive response was annotated in the answer.No: if the answer is not responding to the emotional, esteem, network, or tangible support needs.Not applicable: if questions only seek informational support needs. Thus, no need for the non-informational aspects of the question to be answered.22 was conducted by 9 annotators. It captured three dimensions in state empathy of annotators including affective, cognitive, and associative empathy. According to the instrument, the affective empathy presents one’s personal affective reactions to others’ experiences or expressions of emotions. Cognitive empathy refers to adopting others’ perspectives by understanding their circumstances whereas associative empathy encompasses the sense of social bonding with another person. According to the results shown in Table The annotation task was completed by 10 annotators . As Table 23.To measure inter-annotator agreement (IAA), we sampled 129 questions from the whole collection annotated by three annotators and asked three additional different annotators to annotate the same questions. IAA is calculated using overall agreement. Table The dataset contains a total of 1,500 questions and answers pairs. The questions include 8.8 sentences per health questions, 156.33 words per question, on average, whereas the answers on average include 7.3 sentences per answer and 156.33 words per answer.Distribution of the social support needs is imbalanced with 995 questions seeking informational support, 624 questions seeking emotional support, 207 questions seeking esteem support, 444 questions seeking network support, and 15 questions seeking tangible support. Therefore, we group questions of CHQ-SocioEmo dataset into the three dominant support needs including informational needs, emotional needs, and social needs. Because question counts of tangible support needs are very few compared to other needs, we do not include them in the model. Emotional and esteem support needs were used interchangeably in the literature which are having similar definitions and characteristics. Thus, we group the two types of social support needs, emotional and esteem under the same label.UMLS concepts (and associated semantic types) were extracted from the annotated data using Python (3.10.2), MetaMapLite (3.6.2rc6), and the Python MetaMap wrapper. Concepts were filtered out based on semantic type – only concepts that had at least one relevant semantic type were preserved. We used all the semantic types in UMLS , the details are available in GitHub. No additional cleaning was done on the extracted concepts. R (4.0.2) and RStudio (2022.02.3 + 492) were used for the creation of visualizations.Figure Figure Figure Figure Figure 24. The dataset is saved in JSON format and is organized according to a health consumer question ID. Each question ID is associated with a nested JSON object. This nested object includes a list of annotated aspects of the questions and answers, which contains question focus, age, gender, fine-grained labels of emotions, emotion evidence, emotion cause, types of social support needs in questions and emotional support in answers. The details of each annotated aspect are provided in the README file. Table The Consumer Health Questions Dataset for Social and Emotional Needs (CHQ-SocioEmo) dataset is available through the Open Science Foundation (OSF) at 10.17605/OSF.IO/3DX2SNaïve Bayes. Naive Bayes classifier is a simple classifier that was most commonly used in the field of text classfication25.LSTM. Long Short-Term Memory network (LSTM)26 is a type of Recurrent Neural Networks (RNN) capable of capturing long-term dependencies. LSTM cell can be used in the sequence-to-sequence model to remember the previous words in the sequence. LSTM processes one word at a time, calculating the possible values for the next word in the sequence.BERT. The Bidirectional Encoder Representations from Transformers (BERT)27 which uses encoders in a transformer as a sub-structure to pre-train models for NLP tasks. BERT’s execution of these tasks is divided into two phases: pre-training for language comprehension and fine-tuning for a specific task. BERT was trained using 16GB datasets from Books Corpus28 and the English Wikipedia. BERT has the advantage of being able to handle contextual information extraction due to its bi-directional capability, so it trains faster than other models.RoBERTa. The Robustly Optimized BERT pre-training Approach (RoBERTa)29 is a BERT variant that aims to optimize BERT by tweaking various key parameters in the early form of BERT and training on more data. The model was trained using 160GB of uncompressed text from five English language data sources: the data sources for the BERT model, the CC-News data, the Stories dataset30 and the Open Web data.DistilBERT. Is a distilled version of BERT31, with comparable performance but fewer parameters. DistilBERT employs distillation, a compression technique in which a compact model is trained to mimic the behaviour of a larger model.We conducted a series of experiments using various classification approaches to benchmark the CHQ-SocioEmo dataset and demonstrate how it can be used to automatically identify non-informational or emotional support needs from questions. We used the pre-trained language models that have shown state-of-the-art performance on the various classification tasks.To model the social support needs in CHQ-SocioEmo, we train classifiers to assign one of 3 labels: informational needs, emotional needs, and social needs. We then perform a 60/20/20 split to build the train, validation, and test sets.32. Precision is the fraction of correct (relevant) questions among all extracted questions; and recall is the fraction of successfully extracted questions among all correct (relevant) questions. The harmonic mean of precision and recall is called F1 score. The weighted-F1 score is considered for class imbalance in our corpus which calculates the F1 score for each class independently and when it adds them together uses a weight that depends on the number of correct questions of each class32. The following are equations for the benchmarking metrics:We have evaluated the performance of the classifier using precision, recall and weighted-F1 scoreTP is the true positive count (the number of questions that are correctly extracted), FP is the false positive count (the number of questions that are incorrectly extracted), and FN is the false negative count (the number of correct questions that are not extracted).We present the performance of models in Table Detecting emotions and emotional needs in text is considered a complex task due to many reasons. One reason is that emotions are subjective and differ among people. Treating the same health consumer question, people may feel different emotions according to their own experience. All these reasons make it hard to detect the emotions, which may impact the evaluation and result in lower performance compared to other three-way classification tasks. The state-of-the-art results for emotion detection tasks range from 44.4% to 70.9%. Yet, the DistillBERT model achieves an average F1-score of 0.58 which is higher, compared to the state-of-the-art datasets such as the GoEmotions dataset. Goemotion achieves an average F1-score of 0.46.1, and can be accessed after signing the Yahoo agreements.We have detailed instructions on how to process the CHQ-SocioEmo dataset in the README file provided with the dataset. The data will support other NLP tasks of interest, such as emotion detection, emotion causes, emotion span detection, question focus, etc. We are unable to directly share the Yahoo original questions due to copyright issues, but instead we provide questions IDs. These questions, however, are publicly available here


Herein, weemployed two in vitro BBB models of increasing complexityto investigate the bionano interactions with graphene oxide (GO) andfew-layer graphene (FLG): a 2D murine Transwell model, followed bya 3D human multicellular assembloid, to mimic the complexity of the in vivo architecture and intercellular crosstalk. We developedspecific methodologies to assess the translocation of GO and FLG ina label-free fashion and a platform applicable to any nanomaterial.Overall, our results show good biocompatibility of the two GRMs, whichdid not impact the integrity and functionality of the barrier. Sufficientlydispersed subpopulations of GO and FLG were actively uptaken by endothelialcells; however, the translocation was identified as a rare event.Thanks to their biocompatibility and high cargo capability,graphene-basedmaterials (GRMs) might represent an ideal brain delivery system. Thecapability of GRMs to reach the brain has mainly been investigated  The BBB is an essentialregulatory layer at the neural interface with the brain vasculature,which acts as a selective barrier. The tight junctions forming betweenadjacent cells prevent molecules from moving paracellularly, forcingthem to take a transcellular route for their translocation.19 In the nanosize range, the engagement with the biological membranesallows for active transport mechanisms of internalization and transcytosisthat are compatible with the process of BBB translocation. Althoughthis phenomenon is often observed as a rare event,22 nanomaterialsoffer a plethora of opportunities that might allow boosting the BBBcrossing, such as surface chemistry engineering, downsizing, and hybridconstructs decorated with endogenous motifs.28The idea of exploiting nanomaterials to overcome the BBB hasattractedgrowing interest in the past decade.33In this context, colloidal graphene-based materials (GRMs),withtheir proven biocompatibility and excellent cargo capability, areconsidered very promising.38 Despite a certain consensus, some controversial results can be foundacross the literature, reporting BBB transient disruption or brainaccumulation.40 However, to date, detailed knowledgeof the molecular interactions between GRMs and BBB cells and architectureis missing.41Several reports so far have investigated the biodistributionofvarious colloidal GRMs injected systemically, suggesting that it isunlikely for GRMs to cross the BBB and accumulate in the brain.in vitro investigationof two GRM interactions with the BBB. To this aim, we employed twoGRMs with different surface chemistry and stability, both murine andhuman models of increasing complexity, and a portfolio of complementarylabel-free analytical techniques. The use of label-free strategiesallows the avoidance of fluorescent tag interference and leaching,which makes the results of the bionano interactions hard to interpret.43 The workflow developed in this paper is widely applicable to thestudy of the translocation of different micro- and nanomaterials andrepresents a valuable method to reduce the more expensive and ethicallyconcerning in vivo biodistribution studies.In this work, we performedan Figure S1.45 Reduced graphene oxide (RGO)was also employed for some initial investigations. RGO material isobtained from GO, reduced at high temperatures (800 °C), as describedelsewhere .46 The surface chemistry ofRGO should then be more similar to FLG, but it can still present oxygendefects on the surface. As shown in the Turbiscan analysis of Figure S3, the colloidal stability of RGO inthe biological environment over time was very poor compared to thatof FLG and GO.For this study, two main graphene-based materials (GRMs) were employed:few-layer graphene (FLG) and graphene oxide (GO). These materialspresent similar sizes and morphological features but different surfacechemistry, and their characterization is extensively described inour previous works and also reported in Methods in the SupportingInformation). Cells were incubated with 10 μg/mL of each GRMat different time points. No effects on cell viability, monolayerorganization, cell morphology, or polarization were observed after24 h of exposure, as reported in Figure S4.The first BBB model that we employed was a monolayerculture ofmurine brain endothelial cells (bEnd.3). We initially checked whetherGO and FLG had any detrimental effects on the barrier features, suchas cell viability, morphology, tight junction expression, and barrierfunctionality. For imaging purposes, bEnd.3 cells were cultured onglass coverslips, while functional tests were performed using Transwellmembranes  was alsomeasured upon exposure to the two GRMs, using a fluorescent probe(dextran 4 kDa FITC labeled (FD4); Papp results related to RGO are reported in Figure S7.For bEnd.3 cells cultured on Transwell membranes,the barrier propertieswere assessed by measuring the trans-endothelial electrical resistance(TEER). As shown in 50 For this reason, following the exposure of bEnd.3 cells to eitherFLG or GO, we explored the cell proteome by obtaining label-free high-resolutionLC-MS data on the cell lysates.Previous studies reported theinfluence of pristine graphene andGO on signaling pathways and their role in inducing changes in theexpression and regulation of genes and proteins in various mammaliancells.Supplementary File P1 andcan also be found in the PRIDE database (data set identifier PXD038297).We detected only minor changes in the bEnd.3 proteome following exposureto GO (134 proteins) and FLG (43 proteins), corresponding to about2.6% and 0.8% of the total observed bEnd.3 proteome, respectively.The volcano plots reported in Figure S8 show the proteins (red dots) that were significantly (p < 0.05) altered compared to the total quantified proteome (graydots) for GO and FLG exposure, respectively. The full sets of alteredproteins are reported in Supplementary Files P2 and P3. A subsequent gene enrichmentanalysis failed to highlight any cell process or function significantlyaltered by the exposure to GO or FLG.We quantified a total of 5153protein groups in all three groups, with a total protein abundance profile thatspans over roughly 4.5 logs. The full list of quantified proteinsis reported in Once the persistenceof the barrier functionality and the tightnessof the paracellular spaces under our GRM exposure conditions wereassessed, we then moved to investigate the capability of the two GRMsto cross the BBB through transcellular transport. The stability ofthe GRM dispersion plays a crucial role in the processes of internalizationand translocation.51 Additional representative TEM images are reportedin Figure S9.First, we evaluated the cellular uptake ofGO and FLG. 55 The instability of the RGO suspension in cell culture media  probably affected the material uptake.Due to the absence of uptake after 4 h of incubation , RGO was excluded from the followingexperiments.The presence of such vesicles containing the twoGRMs makes itpossible to measure the uptake in a label-free fashion by measuringthe side scattering (SSC) values by flow cytometry. These values area recognized proxy for the increased cellular granularity upon materialinternalization.Figure S11) and mechanical properties. Indeed, SSC is mainlyinfluenced by the augmented size of intracellular vesicles engulfingmaterials (augmented granularity of the cells), but the influenceof the intrinsic scattering of the internalized material is unclear.For both FLG and GO, the uptake kinetics were evaluatedfrom 2to 48 h, and the measured uptake was already significant after 2 h.For both materials, a plateau was reached after 24 h of incubationwith 10 μg/mL of material, as shown in Figure S3) and tothe different mechanical properties of the aggregates.From a qualitative point of view, by TEM observation, the FLG-treatedsample presented a remarkable number of holes in the cells, correspondingto some visible material accumulation. This might indicate that largeragglomerations of FLG are removed during the microtome slicing process(slice thickness is set as 70 nm). Such observations were less frequentin the case of GO-treated samples, possibly due to the lower dispersibilityof FLG over time . Cells were pretreated for 30min with the inhibitor and exposed to 10 μg/mL FLG and GO for2 h before the evaluation of the uptake by flow cytometry. The resultsfor both GO and FLG internalization pathways are reported in 60For asufficiently dispersed subpopulation of smaller flakes, theendolysosomal uptake pathway might be involved in the internalizationprocess, as for most nanomaterials. Therefore, we evaluated the GRMuptake in the presence of inhibitors of phagocytosis , micropinocytosis , and clathrin-mediated endocytosis .61 Although the quantitative study of the translocationof label-free GRMs is a challenging task, some qualitative observationscan be attempted. As schematically shown in The translocation of fluorescent nanomaterials across the BBB througha transcellular way has been observed.Z-stack images with the light reflection (LR) acquisitionmode at the confocal microscope and positioning in the nuclear planein order to detect flakes internalized in the intracellular space, we could spot some rare LR signals associated with thepresence of graphene materials across the membrane.GO and FLG can be visualized by acquiring three-dimensional ar space3B, to de–1) and G (1580 cm–1) bands with different relative intensities indicating the presenceof GO and FLG.Finally,we analyzed the basolateral fractions of the Transwell.The collected fractions were deposited on glass slides and observedat the optical microscope, where it was possible to spot a few darkagglomerates, as presented in representative insets in Method sectionin the Supporting Information).62We implemented a second, more realistic, humanBBB 3D model basedon human multicellular assembloids (hMCAs). hMCAs were prepared from2D cultures of primary human astrocytes (NHA), human pericytes (hBVP),and human brain endothelial cells (hCMEC/D3) and validated as previouslyreported  images of The assembloids were incubated with 10 μg/mLof either GOor FLG for 24 h. At the end of the incubation, about 50–90organoids per condition were collected, washed to remove the excessexternal GO and FLG, fixed, and sliced at the cryostat. The slicingprocedure allowed accessing the hMCA core for further confocal analysis. Methods in the Supporting Information, was developedin house and validated using prestained NHA and hBVP that allowedseparating clusters for the three cell populations, as shown in We decided to complement ourobservations by employing flow cytometryand TEM imaging, as done in the 2D murine model. To evaluate the uptakeof materials in the different layers of hMCA by SSC by flow cytometry,we dissociated the hMCAs after incubation with either GO or FLG andwashing steps, as illustrated in Figure S14). Theseagglomerations are localized in cells situated at the periphery ofthe slice that, according to the architectural organization of hMCA,correspond to the endothelial cell layer. No sign of GO and FLG inthe internal core was found by TEM analysis. Even in this case, itcan be noticed how FLG (and not GO) produced bigger/stiffer agglomerates,producing holes when encountering the blade during the microtome slicingprocedure.TEM analysis further confirmed these observations.Although themicrographs depicted in in vitro models of increasing complexity hasbeen thoroughly investigated. GO and FLG do not induce any obviousharm to the BBB cells in terms of viability, tight junction expression,barrier morphology, and functionality, adding an essential brick tothe safe use of graphene in neuroscience. However, despite their excellentcargo capability and ease of functionalization, our GRMs do not seemto be promising carriers for BBB translocation.The interaction of two different colloidal GRMs,GO and FLG, withBBB in In this work,we employed an array of complementary techniques,all label-free, to study GO and FLG behavior in 2D and 3D models ofBBB. By means of confocal microscopy, flow cytometry, and electronmicroscopy, we found that graphene is internalized by endothelialcells, depending on its dispersion state, in large vesicles, whichis compatible with the micropinocytosis uptake mechanism. However,the export and the cell-to-cell exchange of this material rarely occur,especially in more sophisticated models of primary human cells mimickingthe complexity of the 3D BBB architecture.in vivo investigations. This work, complementing the existing in vivo literature, can contribute to guiding the graphenecommunity to focus their efforts toward graphene use more orientedto regenerative medicine, prosthetics, and sensors, rather than purenanomedicine.66The workflow developedhere can be applied to any fluorescent orlabel-free nanomaterial and will ensure thorough screening of potentialnanocarriers to the brain, bypassing costs and ethical concerns of


Such graphene film also exhibits a superhigh electromagnetic interference shielding effectiveness of ∼90 dB at a thickness of 10 μm, outperforming all the synthetic materials of comparable thickness including MXene films. This work not only paves the way for the technological application of highly conductive graphene films but also provides a general strategy to efficiently improve the synthesis and properties of other carbon materials such as graphene fibers, carbon nanotube fibers, carbon fibers, polymer-derived graphite and highly oriented pyrolytic graphite.Fabricating highly crystalline macroscopic films with extraordinary electrical and thermal conductivities from graphene sheets is essential for applications in electronics, telecommunications and thermal management. High-temperature graphitization is the only method known to date for the crystallization of all types of carbon materials, where defects are gradually removed with increasing temperature. However, when using graphene materials as precursors, including graphene oxide, reduced graphene oxide and pristine graphene, even lengthy graphitization at 3000°C can only produce graphene films with small grain sizes and abundant structural disorders, which limit their conductivities. Here, we show that high-temperature defects substantially accelerate the grain growth and ordering of graphene films during graphitization, enabling ideal AB stacking as well as a 100-fold, 64-fold and 28-fold improvement in grain size, electrical conductivity and thermal conductivity, respectively, between 2000°C and 3000°C. This process is realized by nitrogen doping, which retards the lattice restoration of defective graphene, retaining abundant defects such as vacancies, dislocations and grain boundaries in graphene films at a high temperature. With this approach, a highly ordered crystalline graphene film similar to highly oriented pyrolytic graphite is fabricated, with electrical and thermal conductivities (∼2.0 × 10 The high-temperature defects induced by nitrogen doping significantly accelerate the grain growth and ordering of graphene films during graphitization, enabling highly-oriented-pyrolytic-graphite-like highly conductive films. Graphene is well known for its extraordinary in-plane electron and phonon transport on a honeycomb lattice . Transfe2O, CO and CO2 during the thermal annealing process. The resulting structure expansion prohibits grain growth and ordering of the graphene film during graphitization. As alternative precursors, graphene materials with less functional groups, such as reduced GO (rGO) [Graphene oxide (GO) ,21–23 isGO (rGO) , a mixtuGO (rGO) , pristinGO (rGO)  and evenGO (rGO) , have beGO (rGO) . NeverthGO (rGO) , which a4 S cm−1; ∼1.7 × 103 W m−1 K−1) of the resulting graphene films are approximately six and two times better, respectively, compared to those fabricated by the commonly used GO precursor. Such a graphene film also exhibits a superhigh EMI-shielding effectiveness (SE) of ∼90 dB at a thickness of 10 μm, outperforming all synthetic materials of comparable thickness, including MXene films.Here, we show that nitrogen doping can retard the restoration of defects in graphene films below 2000°C and therefore retain abundant vacancies, dislocations and GBs at the beginning of graphitization. Such high-temperature defects substantially accelerate the grain growth and ordering of graphene films during graphitization, producing a HOPG-like highly crystalline film with electrical and thermal conductivities approaching the limit of single-crystal graphite within 10 min of graphitization at 3000°C. From 2000°C to 3000°C, the grain size of graphene films increases 100-fold, along with well-ordered AB-stacked layers being formed, leading to a 64- and 28-fold increase in electrical and thermal conductivities, respectively. The electrical and thermal conductivities  and elemental analysis were used to monitor the evolution of carbon, oxygen and nitrogen species in the films during annealing Fig. . Notably2 graphene domains surrounded by oxidized sp3 regions that are decorated by epoxide and hydroxyl groups on their basal plane, and its edges are decorated with carbonxyles and carbonyls [2O, CO and CO2 to generate a great number of vacancies in the carbon lattice, corresponding to the increased intensity ratio of D peak to G peak (ID/IG) at 1000°C. However, the ID/IG significantly declines from 1000°C to 2000°C, indicating that the in-plane defects are well-repaired below 2000°C  for disordered turbostratic stacking, while AB stacking leads to an asymmetrical 2D peak composed of two subpeaks at ∼2680 cm−1 of (2D1) and ∼2720 cm−1 (2D2) [We then studied the structure evolution of N-rGO and GO films during annealing from 2000°C to 3000°C. The Raman 2D peak, as the second harmonic of D peak, is usually used for measuring the degree of stacking order. A symmetrical 2D peak appears at 2700 cm−1 (2D2) ,29. As sTherefore, we further characterized the in-plane and through-plane microstructures of GO and N-rGO films after 2000°C annealing by using scanning tunneling microscopy (STM) and HRTEM, respectively. For the N-rGO films, nanometer-STM images show many edges Fig. , which aLa). X-ray diffraction (XRD) has been previously used to evaluate the through-plane grain size (Lc) of graphene films and other carbon materials based on the Scherrer equation [Lc, such as experimental resolution, grain shape, grain size distribution, degree of stacking order, microstrain and other defects [Lc.Bright-field TEM (BF-TEM), annular dark-field scanning TEM (ADF-STEM), HRTEM and scanning electron microscopy-electron channel contrast (SEM-ECC) imaging were then used to record the evolution of the graphite grain in N-rGO films during the graphitization process above 2000°C Fig. . In SEM-equation ,13,22,34 defects . Thus, A defects . As a reLc   decreases from ∼85.1% to 29.4%, the AB-stacking ratio increases to 45.8%, and the electrical and thermal conductivities increase ∼26 and 17 times, respectively. More importantly, Lc and La further enlarge ∼5- and 14-fold, respectively, and Pdisorder further decreases by ∼4 times with ideal AB stacking being formed, as the temperature increases from 2500°C to 3000°C. Accordingly, the electrical and thermal conductivities are further increased 2.5- and 1.7-fold, respectively. In total, the grain size, electrical conductivity and thermal conductivity are increased 100-, 64- and 28-fold, respectively, during graphitization from 2000°C to 3000°C.We further quantified the evolution of ges Fig. . At the ata Fig. , performDT) Fig. , and meaDT) Fig. . NotablyLc is increased only ∼9-fold in total, along with a moderate decrease in Pdisorder from 84.0% to 28.7% and a subtle improvement in crystallinity   . All theIt is well accepted that AB stacking is the most thermodynamically stable structure of graphite, while stacking faults and rotational mismatch can induce significant interlayer strain energy, which results in the crystals having a high-energy metastable state . Previou−3. These structural features are significantly different from those of the GO-derived graphene films, which feature abundant wrinkles, kinks and voids , giving strong evidence of grain growth through interlayer migration and arrangement of carbon atoms, as discussed above.Using the high-temperature defect-enabled highly efficient graphitization approach, we fabricated large-area HOPG-like graphene films with N-rGO as precursor Fig.  and 15. nd voids . Althougnd voids . Moreovend voids . Meanwhind voids , and thend voids . Notably μm Fig. , respect μm Fig. . It is a2 structure  indicate predominant AB stacking with only ∼8.8% turbostratic-stacked regions  and single-crystal graphite (∼2.5 × 104 S cm−1 and ∼2.0 × 103 W m−1 K−1) [For graphene-based materials, heat conduction mainly depends on the phonon transport from lattice vibrations of the spne layer ,11. It hne layer ,11, degrm−1 K−1) .Emerging 5G devices can provide ultrafast data transmission rates, more reliable and ubiquitous communications and ultralow latency, allowing various innovative services such as smart cities, the Internet of Things, artificial intelligence and satellite services ,9. Howev3CNTx MXene film is the best known EMI shielding material with EMI SE values of ∼75, 83, 97 and 116 dB at a thickness of 10, 20, 30 and 40 μm [−1 K−1 [Tind 40 μm , respect [−1 K−1 ). We mea [−1 K−1 . Signifiin-situ experiments such as TEM observations, which is essential for precise control of the structure of graphene films.Our work provides a new strategy to substantially accelerate the graphitization of graphene films by using N-doping to retain high-temperature defects, leading to significant improvements in their crystallinity, ordering, electrical and thermal conductivities, and EMI shielding performances. These findings pave the way for the practical application of graphene films to meet the rapid advancement of electronics and telecommunications. In principle, other heteroatoms—which can substitute the carbon atoms in a graphene lattice, hinder the restoration of defects and then be removed at elevated temperatures—could also be used to realize high efficiency graphitization. More generally, graphitization is the only method, known to date, for the crystallization of other types of carbon materials , includinwad147_Supplemental_FileClick here for additional data file.


Like the charge process of capacitor, the N‐doped carbon can capture the photogenerated electron of CISe, and the strong interfacial coupling between CISe and N‐doped carbon can modulate the charge migration and separation. The optimized the CISe/N‐C photoanode achieves a maximum photocurrent of 4.28 mA cm−2 at 1.23 V versus reversible hydrogen electrode (RHE) in neutral electrolyte solution under AM 1.5 G simulated sunlight (100 mW cm‐2), which is 8.4 times higher than that of the CuInSe2 photoanode (0.51 mA cm‐2). And a benefit of the strong electronic coupling between CISe and N‐doped carbon, the charge transfer rate is increased to 1.3–13 times higher than that of CISe in the range of 0.6–1.1 V versus RHE. The interfacial coupling effects on modulating the carrier transfer dynamics are investigated by Kelvin probe force microscopy analysis and density functional theory calculation. This work provides new insights into bulk phase carrier modulation to improve the performance of photoanode for PEC water splitting.Regulating the charge migration and separation in photoactive materials is a great challenge for developing photoelectrochemical (PEC) applications. Herein, inspired by capacitors, well‐defined CuInSe 2/N‐doped carbon nanorod arrays are designed as the reservoirs to capture and store the photogenerated electrons of CuInSe2 by the N‐doped carbon, and the strong interface coupling can pave a specific “bridge” between components to promote carrier migration and separation for PEC water splitting.Inspired by capacitors, well‐defined CuInSe The construction of heterojunctions by coupling different materials with diverse energy level structure including type II heterojunction, Z‐type heterojunction, and S‐type heterojunction have been regarded as one of the most promising strategy to improve the electron‐hole separation, and affording a specific redox potential for the catalytic reaction.  However, it is still faces serious challenges originating from the unreasonable energy band structure, and large interface energy resistance, which inhibit the spontaneous migration and separation of photogenerated carriers. Accordingly, it is highly desirable to design a suitable interface structure with spontaneous carrier migration for efficient solar water splitting.Photoelectrochemical (PEC) water splitting for hydrogen generation is of great significance in the field of carbon‐neutral technology for zero‐emission renewable energy evolution. 1, 22S4, CuInSe2 have emerged as one of the most promising candidates for photocatalytic water splitting. CuInSe2 (CISe) is a typical n‐type semiconductor with adjustable bandgap of 1.0–2.0 eV. The maximum value of the conduction band position is as high as about ‐1.0 eV, which endows the strong reducing capacity for the photogenerated electrons. The bulk carrier recombination in CISe seriously limits its photo‐to‐electric conversion efficiency. The strategy of coupling suitable materials with CISe to build the interfacial heterojunction is thought to be a feasible way to regulate the carrier spontaneous migration. Carbon material with π‐conjugated structure presents an attractive electron mobility, tunable electronic local structure, and good catalytic economical applicability. Some pioneer composites including activated Carbon‐TiO2 carbon spheres‐BiVO4, N‐C/In2O3‐CuO, In2Se3@N‐C  have been proposed for improving their photocatalytic performances. As electron acceptor, the carbon material could capture the photoinduced electrons, whereas, the lack of a tight interaction between the carbon material and the semiconductor interface can weaken the ability to capture electrons due to the high energy barriers at the interface. The continuous distribution of carbon in the composite and their interface contact are the current big questions. The poor interfacial contact is like stacking a “wall” between the composites, seriously preventing the trajection of charge flow. The intimate interface combination, such as in strong chemical bonds, could pave a specific “bridge” to promote carrier migration between components, and facilitate modulating the interface electronic structure and space charge density distribution. We also have reported that engineering the heterogeneous interfaces via in‐situ reaction protocols could largely decrease the phase boundary thermal resistance for the migration and separation of electron and holes. To this end, constructing carbon continuous distribution in CISe with intimate interfacial contact might be an effective approach to regulate the charge spontaneous migration and separation for highly efficient PEC water splitting.Ternary metal selenide or chalcogenide semiconductors, such as ZnInlectrons.7, 8 It works as follows: the carbon electrode adsorbs electrons in the charging stage, and then release electrons in the discharging stage. Inspired by this, we reported the CuInSe2/N‐doped carbon (CISe/N‐C) nanorod arrays by using the N‐doped carbon as the reservoirs to capture and store the photogenerated electrons of CISe. The strong interfacial coupling between CISe and N‐doped carbon could facilitate the migration and separation of electrons and holes. The typical CISe/N‐C photoanode shows a maximum photocurrent density of 4.28 mA cm‐2 at 1.23 V versus reversible hydrogen electrode (RHE) in neutral electrolyte solution under AM 1.5 G simulated sunlight (100 mW cm‐2), an 8.4 times enhancement relative to that of the CISe sample. In addition, the photo‐stability is also greatly improved in the redox electrolyte solution, 98.11% initial value is maintained even after 3600 s continuous light illumination at an applied potential of 1.0 V versus RHE. As compared to the similar photoelectrodes, the activity of the CISe/N‐C sample is superior to the most reports in recent literature. The prominent performances of the CISe/N‐C photoanode can be ascribed to the high carrier separation efficiency, low interfacial resistance driven by the berried continuous electrons reservoirs, and the strong interfacial coupling interactions, the charge separation mechanism of which is understood from the electrochemical analysis and the density functional theory (DFT) simulation. This work might be important for understanding the interfacial charge migration within nanostructured photoelectrodes boosting the high PEC applications.Electric double‐layer capacitor is an efficient energy storage device for the uneven power demand in sustainable energy systems.22 It 2Figure From TEM images . The Raman spectra . As shown in Figure s Figure , it can s Figure , a clears Figure  indicated Figure  exhibit Figure2 (JCPDS 40‐1487). In Cu 2p spectra  and Se  in CISe/N‐C also exhibit a slight positive shift. It might be aroused by the carbon component, which adsorbs the electron cloud of CISe to its surface, and resulting in the adjacent atoms shift to a high binding energy position. The high resolution C 1s spectra  in CISe/N‐C implies a strong interfacial coupling effect between CISe and N‐doped carbon.The microstructures of CISe, CISe‐C, and CISe/N‐C samples are characterized by X‐ray diffraction (XRD), X‐ray photoelectron spectroscopy (XPS) analysis. As shown in a Figure , the Cu a Figure  are compa Figure  can be a2SO4 electrolyte under 1.5G illumination with a standard three‐electrode system. As shown in Figurein‐situ formed carbon layer, the photocurrent density is only about 1.66 mA cm‐2 at 1.23 V versus RHE . However, for the typical CISe/N‐C photoanode, the value gets to as high as 4.28 mA cm‐2 at 1.23 V versus RHE and the onset potential also negatively shifted, the value is 8.4 times higher than that of the pure CISe photoanode. Meanwhile, the current density of CISe/N‐C photoanode is also higher than that of CISe in dark  is calculated by the open‐circuit photovoltage measurements in dark as shown in Figure τ value of the CISe/N‐C photoanode is significantly prolonged than those samples, indicating that the interfacial coupling interactions promote the carrier transfer. The stability curves are also used to evaluated the activity of the as‐prepared photoanodes. As seen from Figure ‐2) test, further demonstrating that the interfacial coupling protocol is a promising way to improve the stability. In addition, CISe/N‐C photoanode still maintains a current retention rate of about 88% even prolonging to 3 h . The ctR values can be calculated from the equivalent circuit model based on the EIS data  spectra is performed as shown in absJ obtained from 1.5 G solar spectrum integration:absJ is the photon adsorption rate, and q is the charge of an electron, h is the Plank constant, c is the light speed, λϕ is the photon flux of the AM 1.5 G solar spectrum, and absη is the light absorption efficiency. As shown in Figure sepη) of the CISe is only 29.4% at 1.23 V versus RHE, whereas, the value is as high as 72.21% for the CISe/N–C photoanode. It confirms that the N‐doped carbon as electron reservoir and the strong interfacial coupling effect plays a key role in the migration and separation of charge carriers. The surface injection efficiency of the electrodes also has been evaluated as displayed in Figure injη) of the CISe/N–C electrode can reach 92.12% at 1.23 V versus RHE, which is 3.4 times as compared to the pure CISe electrode (26.97%). Cyclic voltammetry (CV) tests are further used to confirm that the N‐doped carbon possesses the ability to extract electrons as displayed in Figure ‐1), and is obviously larger than that of pure CISe electrode in the potential region, indicating that higher capacitance can be obtained in CISe/N–C than in CISe under light irradiation. Furthermore, the capacity of the photoelectrode can be calculated based on the following equation:I is the current density of cyclic voltammetry, ψ is the potential range, S is the working area of photoelectrode, v is the scan rate, ΔV is the potential window. The photocapacitance of CISe/N‐C is 0.57 mF cm2 at 0.03 V s‐1, which is 14.6 times higher than that of the CISe (0.039 mF cm2). The large capacitance means that the N‐doped carbon can capture more photoinduced electrons from CISe. Under dark conditions, the capacitance of CISe/N‐C is obvious higher than that of CISe, which reflects that the electron spontaneously migrate to the N‐doped carbon layer  curves of the electrodes at different potentials is shown in Figure transk value of CISe/N‐C electrode is 1.3‐13 times higher than that of CISe electrode at the potential range of 0.6–1.1 V versus RHE, indicating significantly promoting the bulk charge transport kinetics by the strong interfacial coupling between CISe and N‐doped carbon. The recombination rate constant (reck) curves  as shown in s Figure  graduallFigure2 with chalcopyrite structure is shown in Figure  Three situations of substitution sites are predicted: surface Se atoms  calculation as e Figure  confirmsFigure It can be seen that the degradation efficiency of DOX for CISe/N‐C sample is as high as 94.2% within 90 min under visible light illumination  value of rate‐determining step (RDS) for the naked CISe from OOH* to O2 is as high as 1.85 V, which inhibits the release of oxygen. After the introduction of N‐doped carbon layer, the RDS of CISe/N‐C changes from OH* to O*, indicating that it is favorable for O2 production. And the η value is obviously reduced to 1.31 V, further indicating that the strong interfacial coupling effect promotes the OER activity of photoanode. The catalytic reaction mechanism is proposed as shown in Figure The antibiotic contaminant Adriamycin hydrochloride (DOX) is used as a model pollutant to evaluated the photoactivity of CISe/N‐C sample as shown in n Figure . Howevern Figure , the ints Figure  and the s Figure  further l Figure . The O2 3‐2 at 1.23 V versus RHE in neutral electrolyte solution under AM 1.5 G illumination. DFT calculations suggest that interfacial Cu‐N bonds between CISe and N‐doped carbon efficiently suppress carrier recombination for PEC water splitting. This work provides a rational protocol to modulate the bulk charge migration and separation by interfacial coupling for obtaining highly efficient photoelectrodes.In summary, well‐defined CISe/N‐C nanorod arrays have been successfully synthesized via a two‐step method. Like capacitor, the photogenerated electrons of CISe can be stored by the adjacent N‐doped carbon, and the strong interfacial coupling creates direct charge transfer channels between CISe and N‐doped carbon for the charge migration and separation. The optimized CISe/N‐C sample exhibits a maximum photocurrent of 4.28 mA cm4 First, 0.193 g Cu(NO3)2·3H2O, 0.481 g In(NO3)3·xH2O, 0.3 g PVP, and 0.185 g PTA were dissolved in a mixed solvent (DMF: EG: H2O=2: 2: 1) and stirred for 30 min. Then, 530 µL HNO3 was slowly added to the solution. The obtained solution was transferred into a 100 mL Teflon‐lined stainless‐steel autoclave with a piece of clean FTO and maintained at 120 °C for 12 h. After cooling down to the room temperature, the samples were washed with deionized water and ethanol for several times, and dried at 60 °C overnight in air.Cu/In‐MOF were prepared with some modifications.35 Fir‐1 in Ar atmospheres. The synthesized samples were labeled as CISe/N‐C(x), x represents the time. Specially, CISe/N‐C(6) are recorded as CISe/N‐C.The obtained Cu/In‐MOF nanoarray and 0.1 g Se powder were placed in the tube furnace with the Se powder in the atmosphere inlet. The temperature was set to 500 °C for 4‐7 h with the increasing rate of 2 °C·min3)3·xH2O, 0.024 g Cu(NO3)2·3H2O, and 0.0158 g Se powder were dissolved in 20 mL ethylenediamine and 20 mL anhydrous ethanol, then stirring for 60 min. The obtained solution was transferred into a 50 mL Teflon‐lined stainless‐steel autoclave and maintained at 200 °C for 24 h. After cooling down to the room temperature, the samples were washed with deionized water and ethanol for several times, and dried at 60 °C overnight in air. The samples were heat‐treated in argon at 500 °C for 6 h. Specifically, the obtained sample was dispersed in ethanol to form a solution of 10 mg mL‐1. Then 0.15 mL was coated on the conductive surface of the glass slide, with a deposition area of about 1 cm × 1 cm. Spin coating speed 800 rpm min‐1, spin coating time 30 s, then dry in vacuum at 60 °C. The obtained porous CISe film was exhibited in Figure 0.03 g In. AM 1.5 G simulated sunlight illumination (100 mW cm‐2), which was provided by a solar simulator. Electrochemical impedance spectroscopy (EIS), and intensity‐modulated photocurrent spectroscopy (IMPS) were all measured by Zahner IM6 , in which IMPS was excited by monochromatic light at the excitation wavelength of 455 nm. The stability test was measured at 0.25 m Na2S and 0.35 m Na2SO3 (pH 12.8).The performance of PEC was measured on the electrochemical workstation CHI 660E  using a three‐electrode system . The electrolyte was 0.5 2SO4 and a 300 W Xe lamp (100 mW cm‐2) at an applied bias of 1.2 V versus RHE. The electrolyte was previously purged with Ar for 30 min to remove any dissolved oxygen and cooling system maintained a 4 °C temperature in the reaction device. The PEC rate was determined by measuring the O2 created at 30 min intervals.Oxygen evolution on photoanodes was measured using a sealed quartz reactor equipped with a typical three‐electrode cell connected to an Ar cycle and a cooling device. In this cell, 0.5 M NaThe authors declare no conflict of interest.Supporting InformationClick here for additional data file.


Many mechanisms have been proposed to explain acute antidepressantdrug-induced activation of TrkB neurotrophin receptors, but severalquestions remain. In a series of pharmacological experiments, we observedthat TrkB activation induced by antidepressants and several otherdrugs correlated with sedation, and most importantly, coinciding hypothermia.Untargeted metabolomics of pharmacologically dissimilar TrkB activatingtreatments revealed effects on shared bioenergetic targets involvedin adenosine triphosphate (ATP) breakdown and synthesis, demonstratinga common perturbation in metabolic activity. Both activation of TrkBsignaling and hypothermia were recapitulated by administration ofinhibitors of glucose and lipid metabolism, supporting a close relationshipbetween metabolic inhibition and neurotrophic signaling. Drug-inducedTrkB phosphorylation was independent of electroencephalography slow-waveactivity and remained unaltered in knock-in mice with the brain-derivedneurotrophic factor (BDNF) Val66Met allele, which have impaired activity-dependentBDNF release, alluding to an activation mechanism independent fromBDNF and neuronal activity. Instead, we demonstrated that the activemaintenance of body temperature prevents activation of TrkB and othertargets associated with antidepressants, including p70S6 kinase downstreamof the mammalian target of rapamycin (mTOR) and glycogen synthasekinase 3β (GSK3β). Increased TrkB, GSK3β, and p70S6Kphosphorylation was also observed during recovery sleep followingsleep deprivation, when a physiological temperature drop is knownto occur. Our results suggest that the changes in bioenergetics andthermoregulation are causally connected to TrkB activation and mayact as physiological regulators of signaling processes involved inneuronal plasticity. A core molecular mechanism of plasticity is the signaling oftropomyosin-related kinase B (TrkB), which acts as the cognate receptorfor the brain-derived neurotrophic factor (BDNF).6 Subsequent research suggested thatketamine induces rapid BDNF translation and release.7 Certain drugs, like amitriptyline and 7,8-dihydroxyflavone, havealso been proposed to act as direct agonists of TrkB.9 However, as many in vitro studies have proven unreliable in demonstratingconvincing pharmacodynamic interaction of the drugs and TrkB receptor,there have been calls to reevaluate whether these drugs actually bindto the receptor in vivo at all and whether the observed downstreamsignaling is initiated in a canonical manner.12 Another morerecent hypothesis suggests that antidepressants facilitate neuronalresponsiveness to BDNF by binding to a novel transmembrane site ofTrkB.13 Casarotto and colleagues proposethat rapid-acting antidepressants bind to TrkB more readily than traditionalantidepressants, which require chronic administration and accumulationin the brain tissue in order to reach TrkB signaling-promoting concentrations.However, earlier findings demonstrate that the intraperitoneal administrationof conventional antidepressants prominently activates brain TrkB receptorsrapidly within an hour5 and without any involvement ofBDNF.12Several mechanisms have been proposedto govern the antidepressant-inducedTrkB activation. Initially, chronic administration of conventionalantidepressants was shown to enhance BDNF expression in several brainareas.2O, “laughing gas”)14 and flurothyl—considered “a chemical electroconvulsivetherapy” (ECT),15 as it producesepileptiform activity and significant electroencephalography (EEG)slowing during the subsequent postictal state—converge in activatingTrkB signaling only after their acute pharmacological effects havedissipated.16 Although both flurothyl andN2O are eliminated from the body within minutes and haveno active metabolites, TrkB becomes and remains phosphorylated longafter the drug delivery.16 These findingssuggest that the treatments render TrkB active through a mechanismthat does not involve activity-dependent BDNF release and/or directbinding of the drug ligand to TrkB.To complicate the interpretationof past research further, theeffects of some clinically effective antidepressants are problematicto explain using the principles of conventional receptor pharmacology.For example, according to our recent findings, nitrous oxide ,16 a neurophysiological signature of deep sleep17 and reduced brain energy utilization18 and a biomarker associated with therapeuticefficacy of ECT.20 Notably, sleep deprivation (SD)—anothernonpharmacological rapid-acting antidepressant21—also increases SWA during the following bout ofsleep.22 Furthermore, there appears tobe a strong association with activation of TrkB signaling and thepotency of EEG suppression produced by several anesthetic agents,including putative rapid-acting antidepressant isoflurane25 and subanesthetic ketamine.26 Similarto earlier findings on NMDA receptor antagonists,27 we have observed in rodents how EEG slowing—inducedby subanesthetic ketamine, N2O, and flurothyl—emergesgradually after their acute effects begin to fade out.16 Therefore, these findings have raised the possibilityof an association between reduced electrophysiological activity andneurotrophic signaling.30TrkB activation inducedby flurothyl and N31 This response, besides beingcharacterized by EEG slowing and neurotrophic signaling, co-associateswith other physiological changes connected with deep slow-wave sleep:behavioral immobility,32 attenuated brainenergy expenditure,33 and reduced bodytemperature.34 Here, we present evidencefrom molecular studies in mice showing that a range of pharmacologicalagents possessing sedative properties can activate neurotrophic signalingirrespective of their primary pharmacological target. We further demonstratethat similar mechanisms may be associated with physiological processessuch as sleep, metabolism, and thermoregulation. This work providesnew insights into the physiological changes underlying TrkB activationand urges to examine the antidepressant signaling from the perspectiveof brain physiology instead of being solely a conventional ligand-receptorinteraction.Collectively, emergingevidence suggests that antidepressant-inducedTrkB activation may not involve a straightforward ligand release and/orreceptor binding mechanism but could instead be associated with somecomponents of the physiological state evoked by the pharmacologicaltreatment.35 Tothis end, we administered mice drugs commonly classified as stimulants,antidepressants, sedatives, and volatile anesthetics, in dosages commonlyutilized in the available literature. At 30 min after administrationor continuous inhalation anesthesia, we collected samples from themedial prefrontal cortex (mPFC) for western blot (A receptor modulator), medetomidine(α2-adrenergic agonist), hydroxyzine (H1 receptor inverse agonist), isoflurane (volatile anesthetic), gamma-hydroxybutyrate, and antipsychotics suchas clozapine  and chlorpromazine  activated TrkB signaling . Several drugsclassified as antidepressants also increased TrkB signaling or had a trend for increase (mirtazapine).However, antidepressants paroxetine and duloxetine, or stimulantssuch as amphetamine (dopaminergic stimulant) or atipamezole (α2-adrenergic antagonist) had no acute effect on TrkB signalingat the selected dose and time point. Notably, selective serotoninreuptake inhibitors (SSRIs) like fluoxetine are often considered nonsedativein the clinical context, but high acute doses commonly used in rodentantidepressant literature have shown to significantly reduce locomotoractivity.36 Moreover, tricyclic antidepressantslike amitriptyline are known to be sedatives.37 To screen for an association between sedation and TrkB phosphorylation,we tested selected compounds for their effects on locomotor activity andGSK3β.ern blot 1A. We foignaling 1A and it16 whereas isofluranedose-dependently suppresses neuronal activity, resulting in anesthesia.25 TrkB signaling was observed to be unaffectedin brain samples collected immediately after the flurothyl-inducedseizure, suggesting that the acute convulsive activity and the precedingexcitation, during which there should conceivably be more activity-dependentrelease of BDNF, do not have an immediate effect on the phosphorylationlevels of TrkB 45 or inhibiting complex IV46 andincreasing energy-consuming cellular processes47 (ketamine). The metabolomic profile after flurothyl seizure,on the other hand, suggests that the decrease in the metabolic rateis a result of homeostatic inhibition of the complex II (succinatedehydrogenase) in response to the preceding excitatory insult. A similarinhibitory mechanism has been recently described during mammalianhibernation.48To further understand the mechanism behind TrkB activation, we analyzedthe molecular signaling events after treatment with two volatile drugssharing a similar chemical structure but opposite pharmacologicaleffect: flurothyl and isoflurane. Inhalation of flurothyl vapor overa period of few minutes evokes a generalized seizure by progressiveexcitation of the brain, of TrkB 2A. Howev of TrkB 2A. Our p49 and a combination of metabolic inhibitors 2-deoxy-d-glucoseand mercaptoacetate (2DG + MA).50 Systemicdelivery of ATP slows down the TCA cycle through allosteric inhibitionof pyruvate hydrogenase,51 producing astate characterized by immobility52 andincreased slow EEG activity , after which a subsetof animals was allowed to enter recovery sleep in their home cage,monitored remotely for behavioral immobility and a sleeping posture.As expected, recovery sleep after SD increased the spectral powerof the slowest EEG bands, most notably in the SWA range . This suggests that the mere presence ofcortical SWA is not sufficient to explain the observed TrkB phosphorylation,and we continued to investigate whether the sedation-activated TrkBsignaling could be prevented by reversing other physiological changesassociated with deep sleep or sedation. To this end, we used medetomidine,an alpha-2 receptor agonist, due to its ability to induce a sleeplikestate coinciding with SWA and TrkB signaling,56 and amphetamine, which is known to augment EEG activity,57 wakefulness,58 andthermogenesis.59 We replicated the previouslyobserved medetomidine-induced upregulation of TrkBY816,GSK3βS9, and p70SK6T421/S424 in samplescollected from the PFC and hippocampus.16 Furthermore, we detected comparable signaling changes in both thesynaptosome preparations and total homogenates of the samples, suggestingthat the observed response is not isolated to the synaptic fraction. Pre-treatment with amphetamineabolished the medetomidine-induced increase in EEG delta power butdid not significantly affect TrkB phosphorylation in the mPFC , which were collectedto illustrate the occurrence of sedation-induced TrkB signaling throughoutthe brain in different structures. Together, these results furthersupport the hypothesis that SWA is not causally connected with TrkBphosphorylation. However, body temperature measurements recorded duringthe experiment suggested that while the effect on EEG was abolishedwith amphetamine pre-treatment, it had only a small effect on themedetomidine-induced decrease in the rectally measured core body temperature or an incubator maintained at an elevatedtemperature (37 ± 1 °C). Core body temperature was measuredrectally at 10 min intervals, and the mice were terminated for biochemicalanalyses at 30 min after administration. Again, medetomidine induceda progressive reduction in body temperature of the animals at roomtemperature, which was not seen in the heated animals . Remarkably, prevention of the medetomidine-induceddecrease in body temperature also reduced the phosphorylation of TrkBY816, GSK3βS9, and p70SK6T421/S424 .Homeothermic animals maintain a relatively constant body temperaturein a wide range of ambient temperatures by altering their metabolicrate. Consequently, the cerebral metabolic rate, for example, changeslinearly with the surrounding temperature and energy-consuming functionalactivity of the neurons.8 Westudied the acute effects of amitriptyline using a dose  used in previous preclinical antidepressant research.64 The treatment produced marked sedation and hypothermia in mice atroom temperature, accompanied by phosphorylation of TrkBY816, GSK3βS9, and p70SK6T421/S424 in themPFC samples . Thus, we screened selected drugs and treatments that have previouslydemonstrated robust TrkB activation, including 2DG + MA, chlorpromazine,isoflurane, and flurothyl, for their effects on the body temperatureand found that they all induced prominent decrease in either rectalor skin temperature when administered to animals housed at room temperature. We also repeated the experimentwith isoflurane anesthesia in a temperature-controlled setting andobserved a similar pattern of abolished TrkB phosphorylation whenthe body temperature was maintained . These observations question the widely accepted claims, accordingto which the effects of amitriptyline and various other antidepressantsor sedative-anesthetic drugs are mediated by direct pharmacodynamicaction with the TrkB receptor, suggesting instead a causal effectfrom their ability to impair energy metabolism, and consequently,lower body temperature.Next, we set to investigatethe role of temperature and metabolic rate in the antidepressant-inducedTrkB signaling. We decided to use the tricyclic antidepressant amitriptyline,as it has been claimed to be—among many other drugs—adirect agonist of the TrkB receptor. samples 4A. Akin  samples 4A, with 24 alluding insteadto a BDNF-independent transactivation mechanism. To test this notionfurther, we administered an acute dose of amitriptyline to adult micecarrying Met66Met mutation in the Bdnf gene, whichimpairs activity-dependent BDNF release.66 The magnitude of the TrkB signaling and thermoregulatory responsesinduced by amitriptyline were indistinguishable between the met66metBdnf and control mice   4B.67 as wellas mediating temperature-associated changes in the metabolic rate,68 we assessed the active phosphorylation of Srcin brain homogenates that showed increased TrkB phosphorylation. Indeed,SrcY416 phosphorylation was rapidly induced by amitriptyline,isoflurane, metabolic inhibitors 2-DG + MA, and during recovery fromSD and flurothyl seizure (S7). Conversely, thekinase phosphorylation in medetomidine- and amitriptyline-treatedanimals was reduced by warm ambient temperature, although the changewas not statistically significant with amitriptyline , whichis a well-established downstream target of BDNF-induced TrkB activation.69Finally, considering the role of Src familykinases in the neurotrophin-independentTrk receptor transactivation, seizure 4A and S7iptyline 4A. A non5 yet the underlyingmechanisms have remained enigmatic. Attempts to explain the effectsof antidepressants on TrkB signaling have revolved around canonicalprinciples of receptor pharmacology, with some studies suggestingthat all antidepressants, including structurally different amitriptyline,9 fluoxetine,13 and ketamine,13 directly bind to the receptor. Rodent studieshave also indicated that antidepressant-like effects and their associatedmolecular and structural changes are coupled to TrkB downstream signalingpathways, most notably the activation of mTOR and its effector P70S6Kand the inhibition of GSK3β.35 In this study, we show that the phosphorylation ofTrkB, P70S6K, and GSK3β is regulated in mice by various classicalantidepressants, as well as numerous sedative-anesthetic drugs lackingany established clinical value in the treatment of depression. Moreover,we demonstrate that the activation of neurotrophic signaling cascadeoccurs independently of any direct pharmacodynamic action during recoveryfrom a convulsion or in physiological sleep following sleep deprivation.The ability of antidepressants to acutelyactivate neurotrophicfactor receptor TrkB in rodents was established in the seminal observationsby Saarelainen et al.,71As suggested by the four key findings of this report, the TrkB-activatinginterventions appear to be connected by their capability of producingsedation and decreasing metabolic rate. First, a range of pharmacodynamicallydistinct sedative agents were found to activate TrkB irrespectiveof the drugs known for the clinical antidepressant effect. Second,flurothyl and isoflurane, despite their distinct mechanism of actionand timeframe of activating TrkB, led to a similar metabolomic profilethat suggested perturbed bioenergetics. Third, activation of TrkBsignaling was observed during a sedative-hypothermic state inducedby specific metabolic inhibitors, which are routinely used to modelhypothermia. Fourth, the activation of TrkB can be prevented by controllingthe ambient temperature to reverse the drug-induced hypothermia. Thisnovel hypothesis of a noncanonical drug-induced activation mechanismis reinforced by our results, showing that the antidepressant-inducedTrkB signaling is not compromised in animals with impaired activity-dependentBDNF release but instead can be readily prevented through the manipulationof ambient temperature, conceivably by its effect on body temperature,which is determined by the metabolic activity.72 and locomotor activity in rodents,36 conceivably reflecting its effect on bioenergetics.Small laboratory rodents spend a considerably higher proportion oftheir basal metabolic rate to maintain their body temperature, incomparison to humans; thus, clinically insignificant perturbationsto central and peripheral thermoregulatory mechanisms can have a considerablydifferent effect in preclinical studies,75 which are conductedat an ambient temperature far below the animals’ thermoneutrality.Since our screening was limited to a single dose of each drug andwas designed to address TrkB phosphorylation, rather than sedationand other complex interactions of physiology and environment, subsequentdose–response studies in a controlled experimental settingare warranted. Nevertheless, we found that the sedation induced byclozapine and amitriptyline, as measured by a decrease in locomotoractivity, was reflected in increased TrkB phosphorylation, whereasstimulants amphetamine and atipamezole did not alter the signaling.Similarly, increased TrkB signaling and decreased locomotor activityand body temperature were observed after the administration of metabolicinhibitors 2DG and MA. These findings are in line with previous studiesassociating TrkB activation induced by medetomidine, nitrous oxide,and ketamine with increased SWA in mice.26 Strikingly, we have not observed acute activation of TrkB signalingusing subanesthetic doses of ketamine, commonly used in antidepressantresearch, but instead with anesthetic doses that have been shown toelicit hypothermia.77From a pharmacological perspective, drugs that produced consistentTrkB activation belonged to the general categories of either sedative-anesthetics,metabolic inhibitors, or antidepressants and antipsychotics that havesedating properties at high doses. Out of drugs categorized as antidepressants,fluoxetine, mirtazapine, amitriptyline, and mianserin increased TrkB,p70S6K, and GSK3β phosphorylation, while duloxetine and paroxetinedid not. Mirtazapine, amitriptyline, and mianserin are generally consideredto have pronounced sedative properties and are sometimes used to treatinsomnia, while the SSRIs fluoxetine and paroxetine, and the selectiveserotonin and noradrenaline reuptake inhibitor (SNRI) duloxetine,are generally considered to be nonsedative. However, high acute dosesof fluoxetine have been shown to significantly reduce body temperature78 further research on the thermal dynamics of TrkB signaling and sleepcould perchance shed light on the putative physiological role of temperatureregulation in neuroplasticity and possibly in producing antidepressanteffects. Notably, recent studies have shown that brief therapeutichyperthermia can elicit antidepressant effects in depressed patients,79 which have been associated with the subsequentfacilitation of thermoregulatory cooling.80 Temperature-induced antidepressant-like effects have also been observedin rodents.81 As a limitation of this study,we used naïve mice and focused solely on characterizing thetemperature-dependent signaling phenomena. Future studies investigatingthe functional significance of the observed phenomena in animal modelsof depression, and in producing antidepressant-like behavioral outcomes,are warranted.While the functional roleof the observed phenomenon remains unclear,our findings implicate that TrkB activation occurs during naturaldeep slow-wave sleep, known to coincide with decreasing body temperature,as evidenced by our experiment using sleep deprivation. By using amphetamineto block medetomidine-induced increase in SWA and atropine to inducerobust cortical SWA, we demonstrated that SWA is not, however, inand of itself a sufficient causal explanation for the increased signaling.Instead, TrkB signaling induced by the antidepressant amitriptylineand sedative-anesthetics medetomidine and isoflurane was specificallyabolished by the active maintenance of body temperature. Given thatthe depth of sedation is dependent on ambient temperature and NREMsleep is accompanied by brain cooling,82 has been shown to rescue the brain from various insultsand is associated with significant physiological structural plasticity.84 The therapeutic effects of hypothermia are widely considered tobe mediated through attenuated energy expenditure, oxidative stress,and inflammation, with recent studies also highlighting the involvementof TrkB signaling. In particular, Peretti and colleagues have shownthat RNA-binding motif 3 (RBM3)—a major inducer of cold-inducedstructural plasticity and neuroprotection85—controls the phospholipase-Cγ signaling downstreamof TrkB.86 The authors used a combinationof pharmacological (adenosine monophosphate [5′-AMP]) and environmental(low ambient temperature) means to induce and maintain hypothermia,respectively, observing upregulated BDNF release and TrkB signalingboth in vivo and in vitro. In contrast to the considerably longer,up to 24 h-long time frames used in the previous experiments, ourfindings demonstrate that even an acute decrease in body temperaturecan upregulate TrkB signaling within minutes.The findings of this study may also provide furtherinsight intothe neurobiological mechanisms of therapeutic hypothermia. Hypothermia,among the oldest known neuroprotective treatments,87 Furthermore, we observed a concomitant reduction—rather thanan increase—of ERK phosphorylation, distinguishing the currentphenomenon from canonical BDNF-mediated activation of TrkB.89 This report therefore extendsour previous observations that support the hypothesis of BDNF-independentactivation of TrkB by antidepressants.24 While theprecise mechanism of the activation remains to be fully elucidated,one possibility is the involvement of Src family kinases, which havebeen previously associated with transactivation of the TrkB.67 Previous studies have shown that Src, as wellas several other targets associated with TrkB signaling (most notablyGSK3β), are indeed regulated by the metabolic milieu throughmechanisms such as oxidative stress and altered neuronal lipid environment.91This report contradictswith previous hypotheses, according towhich the acute effects of antidepressants on TrkB signaling are mediatedby a direct receptor-ligand interaction, or via BDNF release, dueto two major reasons. (1) The effect of amitriptyline on TrkB signalingis abolished if the hypothermic reaction is prevented by adjustingambient temperature. (2) There is an identical signaling responseseen in animals with genetically abated BDNF release or function.TA of 22 °C.92 Thus, themice grown and experimented with in a constant cold environment differin their phenotype, metabolism, and thermal responses from those raised,akin to humans, closer to their thermoneutral zone (∼30 °C).93 Further variability is introduced by the nonstandardizedtiming of experiments, as the thermoneutrality of laboratory rodentsundergoes circadian variation. Thus, it is conceivable that the availableliterature on TrkB signaling is significantly affected by varyingconditions related to animal housing group sizes, thermal, and aircirculation conditions.94 Moreover, previousstudies have demonstrated that chronic stress, used to study depression-likebehavior in rodents, modulates thermoregulatory cooling mechanisms,95 which may further influence drug effects. Currently,the reporting of these fundamental experimental factors is lackingin the pharmacological literature, and data regarding the thermalresponses produced by common psychopharmacological agents are verylimited.Beyond the implications to therapeutic mechanisms of variousdrugs,the findings of this report raise crucial questions regarding thereproducibility and translational value of the neuropharmacologicalresearch. Over a third of the energy expenditure of a mouse goes tomaintenance of body temperature at a standard laboratory In conclusion, by studying various antidepressantsand sedative-anestheticdrugs, we found that their propensity to activate TrkB receptor signalingis coupled to their ability to alter the thermal physiology in mice.Maintaining the animals at elevated temperatures during acute drugeffects was found to completely abolish the signaling previously associatedwith the drugs’ pharmacological action. Moreover, our preliminaryfindings suggest that analogous TrkB activation is observed duringphysiological sleep, uncoupling the effect from solely a pharmacologicaldomain. Most importantly, this report proposes a new hypothesis foracute antidepressant-induced TrkB activation by highlighting the roleof bioenergetics and thermoregulation in the modulation of neurochemicalsignaling. This notion raises critical questions about the mechanisticaspects of TrkB signaling and calls for more carefully controlledexperimental settings to re-evaluate the established understandingof drug-induced TrkB signaling by antidepressants and other treatments.Further study of these physiological processes may uncover novel waysto utilize such physiological adaptations in the treatment of neuropsychiatricconditions and recovery from brain insults.ad libitum. BDNF Val66Metmice were generated as previously described.66 Briefly, BDNF Val/Met mice were interbred, and the offspring weregenotyped by polymerase chain reaction (PCR) analysis of tail tip-derivedgenomic DNA. The experiment involving BDNF Val66Met mice was conductedin female BDNFVal/Val and BDNFMet/Met mice.The animal experiments were carried out in compliance with the EuropeanCommunities Council Directive of 22 September 2010 (Directive 2010/63/EU),according to the guidelines of the Society for Neuroscience and approvedby the County Administrative Board of Southern Finland (Licenses ESAVI/9793/04.10.07/2016and ESAVI/5844/2019).Unless otherwise stated, 10–16-week-oldC57BL/6JRccHsd mice  were used. Animalswere maintained under standard housing conditions  in filtered plastic cages, with wood shavings and accessto food and water available d-glucose , adenosine triphosphate ,amitriptyline-HCl , (S)-amphetamine-HCl, atipamezole-HCl , atropine sulfate chlorpromazine-HCl , (S)-duloxetine-HCl , fluoxetine-HCl , gamma-hydroxybutyrate sodium , hydroxyzine-HCl ,medetomidine-HCl , mercaptoacetate, mianserin-HCl , mirtazapine-HCl , paroxetine-HCl, and urethane . Clozapine  was dissolved in 0.1 M hydrochloric acid,adjusted to pH ∼7 with 0.1 M sodium hydroxide, and then dilutedto a concentration of 1.2 mg/mL with sterile saline. An equivalentvehicle solution was prepared without the active drug for clozapinecontrol animals.The following drugs were dilutedin isotonic saline and administered intraperitoneally (i.p.) in avolume of 10 mL/kg: 2-deoxy-24 Briefly, isoflurane anesthesia was induced using 2% isoflurane  and maintained under constant flow of 1.5% isoflurane.24 Sevoflurane anesthesia was induced using 6%sevoflurane  and maintainedunder 4.5%.96 Volatile anesthetics wereadministered in an induction chamber of a small-animal anesthesiasystem  containinga preheated pad to prevent hypothermia. Sham-treated control animalsreceived pressurized room air. Seizure was induced by injecting 10%flurothyl (in 90% ethanol) at a steady rate into a cotton pad placedinside the lid of an airtight Plexiglass chamber (13 × 13 ×13 cm) until the animals went into a myoclonic seizure. The lid wasremoved to terminate the seizure, after which the animals were movedto recover in their home cages. For control animals, 90% ethanol withoutflurothyl was injected to the pad as a sham treatment. All treatmentswere administered 3–7 h after the light onset (6 A.M.) in standardlaboratory conditions, with animals brought to the room to habituatefor at least 30 min before experiments.Isoflurane, sevoflurane, and flurothyl ether; Sigma-Aldrich) were administered as previously described.The locomotor activityof a group of animals was recorded after administration of amitriptyline–HCl,amphetamine–HCl, clozapine, or atipamezole–HCl. Controlanimals were injected with isotonic sterile saline or clozapine vehiclesolution. The treatments were selected from the array of pharmacologicalagents previously tested for their effects on TrkB signaling 1, and do16 Briefly, electrodes were implanted under isofluraneanesthesia using lidocaine (10 mg/mL) for local anesthesia and buprenorphine and carprofen  for postoperativepain care. Two epidural screw EEG electrodes were placed above thefronto-parietal cortex. A third screw was installed as the mountingsupport. Two silver wire electrodes were implanted in the nuchal musclesto monitor electromyographic activity (EMG). After a recovery period(5–7 days), animals were connected to flexible counterbalancedcables for EEG/EMG recording and habituated to recording cables forthree days. Recordings were conducted in the home-cages of the animals.The EEG and EMG signals were amplified (gain 5/10 K) and filtered with a 16-channelAC amplifier , sampled at 254 Hz or 70 Hzwith 1401 interface , and recorded and processed using Spike2 software . EEG power spectra were calculatedwithin the 1–50 Hz frequency range by fast Fourier transform. Oscillation powerin each bandwidth  was computed in 30–300-secondepochs from spectrograms (FFT size = 1024 points) for each animal.Representative sonograms were computed using a Hanning window witha block size of 512.EEG-recordings were performed as described.Animals were kept awake in theirhome cages at standard housing conditions for 6 h starting from lightonset (9 A.M.) by introducing novel objects or gentle handling wheneverthe animals began to display signs of sleepiness. Animals for biochemicalanalyses were euthanized using rapid cervical dislocation either immediatelyfollowing the sleep deprivation or after 15 min of recovery sleep.The entry to recovery sleep was determined for each animal individuallyusing a remote infrared camera based on their immobility and crouchedposture typical for sleep. For EEG studies of SD, the power spectrumof the wake baseline was continuously recorded for 24 h to establisha baseline, followed by a 6 h SD and 1.5 h long recovery sleep period.Corebody temperature was measured using small-animal rectal probe thermometers. The temperaturemeasurements, lasting less than 10 s, were performed by experiencedpersonnel in order to minimize the impact of handling stress on bodytemperature. For longitudinal analysis of body temperature, whole-bodythermal imaging was used to assess the surface temperature of theanimals. Thermal images were acquired using a forward-looking infrared(FLIR) P640 thermal camera , with a reported thermalsensitivity of 0.06 °C at 30 ° C and a reading accuracyof ±2%. The camera was equipped with a 45° field of view,19 mm focal length lens, and positioned perpendicular to the imagedplane above the recording chambers. Thermal data were acquired ata rate of one image per 30 s, for 3–5 min before and followingtimes after treatment initiation; 2-DG + MA receiving animals wererecorded for 50 min after injection; animals recovering from flurothyl-inducedseizure were recorded for 45 min after the end of convulsing; andanimals subjected to 1 and 20 min of isoflurane anesthesia were recordedfor 7 and 10 min, respectively. Images were analyzed using eitherFLIR Tools software (version 6.4.18039.1003), where the highest radiometricpixel temperature was manually acquired for each rodent cage/imageusing the rectangle tool or ThermaCAM Researcher Pro (version 2.10),where the rectangle tool was used to automatically acquire the highestpixel temperatures for each rodent cage/image.75 to account for sedation-associated hypothermia.An external thermometer placed on the incubator floor was used toconfirm the chamber temperature, recording TA range of 33–34 °C during the experiments. Controlanimals were placed in empty plastic containers of roughly the samesize as the incubator, kept at TA of 22°C. The temporary conditions did not include other mice or woodshavings affecting the microenvironment of the animals. Core temperaturemeasurements at the time of termination were acquired using rectalprobes as described above.In the experimentsinvolving controlled ambient temperature, animals were heated usinga ventilated incubator  set to maintain the temperature of the chamber at the upperlimit of animals’ thermoneutral zone (35 °C)2O, Pierce Protease Inhibitor Mini Tablet , Pierce Phosphatase Inhibitor Mini Tablet). After ∼15 min incubationon ice, samples were centrifuged , and the resulting supernatant was collected forwestern blot analysis.Animalswere euthanized at indicated times by a rapid cervical dislocationfollowed by decapitation and removal of the brain. Bilateral mPFC was rapidly dissectedon a cooled dish and stored at −80 °C until further processing.For some experiments, hippocampal (HC), cerebellar (CB), and/or midbrain(MB) samples were collected and processed with the same protocol.For the analysis of crude brain homogenates, the samples were homogenizedin lysis buffer  ice-cold buffer containing 0.32 M sucrose,20 mM HEPES pH 7.4, 1 mM EDTA, 1× protease inhibitor cocktail, 5 mM NaF, 1 mM Na3VO4, and 5 mM Na2HPO4. After centrifugation , the supernatant was further centrifugedat 15,300×g for 10 min. The supernatant (cytosolicfraction) was removed and the remaining pellets, corresponding tothe crude synaptosomal fraction, were resuspended in a lysis buffer.Crude synaptosomes were prepared as previouslydescribed.24 Membranes were incubated overnightin +4 °C with following primary phosphoprotein antibodies: anti-p-TrkAY785/p-TrkBY816 , anti-p-GSK3βS9 , anti-p-p70S6KT421/S424 , anti-p-ERK1/2T202/Y204 ,and anti-p-SrcY416 .For normalization, the following total protein antibodies were used:anti-TrkB , anti-mTrkB , anti-GSK3β , anti-p70S6K , anti-ERK1/2, anti-β-Actin , and anti-GAPDH .The membranes were washed with TBS containing 0.1% Tween (TBST) andincubated with horseradish peroxidase conjugated secondary antibodies. Secondary antibodies were visualized using enhancedchemiluminescence  fordetection using the Biorad ChemiDoc MP camera (Bio-Rad Laboratories).Sample protein concentrations were measuredusing the Bio-Rad DC protein assay . Proteins (40 μg) were separated with SDS-PAGE under reducingand denaturing conditions and blotted to a PVDF membrane as previouslydescribed.97 Briefly, weighed tissue samples were extracted using 100 μLof 80% methanol  per 10 mg of tissue under sonication. After vortexing and centrifugation, the supernatant was collected andfiltered to HPLC bottles through an Acrodisc CR 4 mm (0.45 μm)filter. Samples were analyzed with a UHPLC-qTOF-MS system (AgilentTechnologies) using two different chromatographic techniques, i.e.,reversed phase (RP) and hydrophilic interaction (HILIC) chromatographyand acquired data in both positive and negative polarity. Welch’sANOVA was used for statistical analysis. Principal component analysis(PCA) was used for metabolite profiling data to analyze the overallvariance between all the samples, and partial least sum of squaresdiscriminant analysis (PLS-DA) was used to calculate VIP values, identifyingmolecular features explaining the variance between the study groups.Fifteen principal components were needed to explain 95% of the variancein the metabolomics data; therefore, the α level was adjustedto 0.0033 to account for multiple testing. Cohen’s d effect sizes were calculated between the treatment andcontrol groups. MassHunter Acquisition was used for data acquisition, Profinder was used for feature extraction and peak alignment, the Mass ProfilerProfessional  for statistics, SIMCA to perform multivariate analyses, and MS-DIAL(ver.2.90) for metabolite identification.The nontargeted metabolomicsmethod has been described in detail before.t-test and one- ortwo-way analysis of variance (ANOVA) with Tukey’s post hoctest using Graphpad Prism . Comparisonsof groups with unequal variances were corrected using Welch’s,Dunnett’s, or Dunnett’s T3 tests, depending on the numberof groups and comparisons. When multiple individual pairwise comparisonsto their respective control treatments were performed, for examplein p values are described in figure legends, and details of statisticaltests and n numbers are presented in Table S1.The data were primarily analyzedwith Student’s unpaired The animal experiments were carriedout in compliance with theEuropean Communities Council Directive of 22 September 2010 (Directive2010/63/EU), according to the guidelines of the Society for Neuroscience,and approved by the County Administrative Board of Southern Finland(Licenses ESAVI/9793/04.10.07/2016 and ESAVI/5844/2019).