The Multifunction of TRIM26: From Immune Regulation to Oncology.

Ubiquitination, a crucial post-translational modification, plays a role in nearly all physiological processes. Its functional execution depends on a series of catalytic reactions involving numerous proteases. TRIM26, a protein belonging to the TRIM family, exhibits E3 ubiquitin ligase activity because of its RING structural domain, and is present in diverse cell lineages. Over the last few decades, TRIM26 has been documented to engage in numerous physiological and pathological processes as a controller, demonstrating a diverse array of biological roles. Despite the growing research interest in TRIM26, there has been limited attention given to examining the protein's structure and function in existing reviews. This review begins with a concise overview of the composition and positioning of TRIM26 and then proceeds to examine its roles in immune response, viral invasion, and inflammatory processes. Simultaneously, we demonstrate the contribution of TRIM26 to the progression of various diseases, encompassing numerous malignancies and neurologic conditions. Finally, we have investigated the potential areas for future research on TRIM26.

Multigenerational Adaptation Can Enhance the Pathogen Resistance of Plants via Changes in Rhizosphere Microbial Community Assembly.

Plants withstand pathogen attacks by recruiting beneficial bacteria to the rhizosphere and passing their legacy on to the next generation. However, the underlying mechanisms involved in this process remain unclear. In our study, we combined microbiomic and transcriptomic analyses to reveal how the rhizosphere microbiome assembled through multiple generations and defense-related genes expressed in Arabidopsis thaliana under pathogen attack stress. Our results showed that continuous exposure to the pathogen Pseudomonas syringae pv tomato DC3000 led to improved growth and increased disease resistance in a third generation of rps2 mutant Arabidopsis thaliana. It could be attributed to the enrichment of specific rhizosphere bacteria, such as Bacillus and Bacteroides. Pathways associated with plant immunity and growth in A. thaliana, such as MAPK signaling pathways, phytohormone signal transduction, ABC transporter proteins, and flavonoid biosynthesis, were activated under the influence of rhizosphere bacterial communities. Our findings provide a scientific basis for explaining the relationship between beneficial microbes and defense-related gene expression. Understanding microbial communities and the mechanisms involved in plant responses to disease can contribute to better plant management and reduction of pesticide use.

[Bibliometrics Analysis of Studies on Hypertrophic Cardiomyopathy From 2018 to 2022].

Objective To analyze the research progress and hot topics in hypertrophic cardiomyopathy from 2018 to 2022.Methods The publications in the field of hypertrophic cardiomyopathy from January 1,2018 to December 31,2022 were retrieved from Web of Science core collection database and included for a bibliometric analysis.Results A total of 6355 publications were included,with an average citation frequency of 7 times.The year 2021 witnessed the most publications (1406).The analysis with VOSviewer showed that the research on sudden death related to hypertrophic cardiomyopathy,especially the predictive value of late gadolinium-enhanced cardiac MRI in sudden death,was a hot topic.In addition,gene detection and the new drug mavacamten became hot research topics.The United States was the country with the largest number of publications and the highest citation frequency in this field.Chinese scholars produced the second largest number of publications,which,however,included few high-quality research results.Conclusions Risk stratification and prevention of sudden death is still an important and hot research content in the field of hypertrophic cardiomyopathy.Chinese scholars should carry out multi-center cooperation in the future to improve the research results.

Study on Pharmacological Activities and Mechanisms of the Essential Oil of the Flowers of Hemerocallis citrina Baroni (EOFHCB) in the Treatment of Anxiety Disorders by GC-MS, Network Pharmacology, and Molecular Docking.

BACKGROUND: Hemerocallis citrina Baroni (Huanghuacai), a plant of the genus Hemerocallis in the family Asphodelaceae, is widely planted in China. Based on our survey results, the chemical compounds in the essential oil of the flowers of Hemerocallis citrina Baroni (EOFHCB) and relevant pharmacological activities have never been studied systematically. OBJECTIVE: To preliminarily decipher the pharmacological activities and mechanisms of EOFHCB in the treatment of anxiety disorders by GC-MS, Network Pharmacology, and Molecular docking. METHODS: EOFHCB compositions were identified using GC-MS, and their targets were predicted using Swiss Target Prediction databases. The targets of anxiety disorders were obtained by GeneCards, DisGeNET, and OMIM databases. The STRING database was used to construct the protein-protein interaction networks, and the DAVID database was used to carry out GO enrichment and KEGG pathway enrichment analysis. The EOFHCB-components-targetspathways- anxiety disorders network was constructed by Cytoscape software (Version 3.10.0). Finally, the result was verified by molecular docking. RESULTS: 28 chemical components were identified by GC-MS, including 3-furanmethanol (28.43%), 2-methyl-1-butanol (27.13%), nerolidol (10.62%), and so on, which correspond to 241 potential targets. Several 2440 biological processes, 187 cellular compositions, and 311 molecular functions were enriched by GO enrichment analysis and 174 pathways by KEGG enrichment analysis. The key targets are PTGS 2, SRC, DRD 2, ESR 1, MAOB, and SLC6A4. The most important pathway is the neuroactive ligand-receptor interaction. CONCLUSION: EOFHCB exerts its therapeutic effects on anxiety disorders through multicomponents, multi-targets, and multi-pathways, which provided new ideas and methods for the in-depth research of aromatic Chinese medicine in the treatment of anxiety disorders.

Prognostic prediction and comparison of three staging programs for patients with advanced (T2-T4) esophageal squamous carcinoma after radical resection.

Purpose: Lymph node-based staging protocols are frequently employed to evaluate the prognosis of esophageal cancer, yet their accuracy remains contentious. The present study was conducted to assess the prognostic significance of three lymph node staging systems, namely N stage, lymph node rate (LNR), and log odds of positive lymph nodes (LODDS), in patients diagnosed with advanced (T2-T4) esophageal squamous cell carcinoma (ESCC). Methods: This cohort comprised 319 eligible patients, with an additional 409 individuals retrieved from the Surveillance, Epidemiology, and End Results (SEER) database, forming the validation cohort. Differences in overall survival (OS) of patients between groups were assessed using the log-rank test. Prognostic independent risk variables were identified, and lymph nodes (LN) prognostic models were built using multivariate Cox regression analysis. Besides, the predictive accuracy of each model was evaluated utilizing the (-2) log-likelihood ratio (-2LLR), the likelihood ratio χ2 score (LRχ2), the Akaike information criterion (AIC), and Harrell's concordance index (C-index). To further evaluate the potential superiority of the model, a nomogram was constructed for comparison with the conventional Tumor Node Metastasis (TNM) staging approach. Results: Independent prognostic factors for advanced ESCC include the N stage, LNR, and LODDS. Herein, LODDS presented higher values for C-index and LRχ2, and lower values for AIC and -2LLR in OS compared to the others. Consequently, a nomogram was constructed based on LODDS. Calibration curves exhibited strong agreement, and assessment through C-index, receiver operating characteristic (ROC) curves, and clinical decision curve analysis (DCA) demonstrated promising clinical applicability. Conclusion: LODDS emerges as a promising future prognostic indicator. After surgery, the proposed model holds the potential to provide valuable treatment recommendations for patients with advanced ESCC.

Binding sites and design strategies for small molecule GLP-1R agonists.

Glucagon-like peptide-1 receptor (GLP-1R) is a pivotal receptor involved in blood glucose regulation and influencing feeding behavior. It has received significant attention in the treatment of obesity and diabetes due to its potent incretin effect. Peptide GLP-1 receptor agonists (GLP-1RAs) have achieved tremendous success in the market, driving the vigorous development of small molecule GLP-1RAs. Currently, several small molecules have entered the clinical research stage. Additionally, recent discoveries of GLP-1R positive allosteric modulators (PAMs) are also unveiling new regulatory patterns and treatment methods. This article reviews the structure and functional mechanisms of GLP-1R, recent reports on small molecule GLP-1RAs and PAMs, as well as the optimization process. Furthermore, it combines computer simulations to analyze structure-activity relationships (SAR) studies, providing a foundation for exploring new strategies for designing small molecule GLP-1RAs.

Glycomol: A pervasive tool for structure predication of natural saponin products basing on MS data.

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Research Progress on Mechanical Strength of Rice Stalks.

As one of the most important food crops in the world, rice yield is directly related to national food security. Lodging is one of the most important factors restricting rice production, and the cultivation of rice varieties with lodging resistance is of great significance in rice breeding. The lodging resistance of rice is directly related to the mechanical strength of the stalks. In this paper, we reviewed the cell wall structure, its components, and its genetic regulatory mechanism, which improved the regulatory network of rice stalk mechanical strength. Meanwhile, we analyzed the new progress in genetic breeding and put forward some scientific problems that need to be solved in this field in order to provide theoretical support for the improvement and application of rice breeding.

Baseline hepatobiliary MRI for predicting chemotherapeutic response and prognosis in initially unresectable colorectal cancer liver metastases.

PURPOSE: To evaluate the performance of hepatobiliary MRI parameters as predictors of clinical response to chemotherapy in patients with initially unresectable colorectal cancer liver metastases (CRLM). METHODS: Eighty-five patients with initially unresectable CRLM were retrospectively enrolled from two hospitals and scanned using gadobenate dimeglumine-enhanced MRI before treatment. Therapy response was evaluated based on the Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1. Conventional parameters (i.e., signal intensity [SI]) and radiomics features of portal venous phase (PVP) and hepatobiliary phase (HBP) images were analyzed between the responders and non-responders. Next, the combined model was constructed, and the area under the receiver operating characteristic (ROC) curve (AUC) was calculated. The relationship between the combined model and progression-free survival (PFS) was analyzed using Cox regression. RESULTS: Of the 85 patients from two hospitals, 42 were in the response group, and 43 were in the non-response group. Upon conducting five-fold cross-validation, the normalized relative enhancement (NRE) of CRLM during the PVP yielded an AUC of 0.625. Additionally, a radiomics feature derived from the tumor area in the HBP achieved an AUC of 0.698, while a separate feature extracted from the peritumoral region in the HBP recorded an AUC of 0.709. The model that integrated these three features outperformed the individual features, achieving an AUC of 0.818. Furthermore, the combined model exhibited a significant correlation with PFS (P < 0.001). CONCLUSION: The combined model, based on baseline hepatobiliary MRI, aids in predicting chemotherapeutic response and PFS in patients with initially unresectable CRLM.

ScribSD+: Scribble-supervised medical image segmentation based on simultaneous multi-scale knowledge distillation and class-wise contrastive regularization.

Despite that deep learning has achieved state-of-the-art performance for automatic medical image segmentation, it often requires a large amount of pixel-level manual annotations for training. Obtaining these high-quality annotations is time-consuming and requires specialized knowledge, which hinders the widespread application that relies on such annotations to train a model with good segmentation performance. Using scribble annotations can substantially reduce the annotation cost, but often leads to poor segmentation performance due to insufficient supervision. In this work, we propose a novel framework named as ScribSD+ that is based on multi-scale knowledge distillation and class-wise contrastive regularization for learning from scribble annotations. For a student network supervised by scribbles and the teacher based on Exponential Moving Average (EMA), we first introduce multi-scale prediction-level Knowledge Distillation (KD) that leverages soft predictions of the teacher network to supervise the student at multiple scales, and then propose class-wise contrastive regularization which encourages feature similarity within the same class and dissimilarity across different classes, thereby effectively improving the segmentation performance of the student network. Experimental results on the ACDC dataset for heart structure segmentation and a fetal MRI dataset for placenta and fetal brain segmentation demonstrate that our method significantly improves the student's performance and outperforms five state-of-the-art scribble-supervised learning methods. Consequently, the method has a potential for reducing the annotation cost in developing deep learning models for clinical diagnosis.

Modeling the dynamic impacts of maritime network blockage on global supply chains.

Recent phenomena such as pandemics, geopolitical tensions, and climate change-induced extreme weather events have caused transportation network interruptions, revealing vulnerabilities in the global supply chain. A salient example is the March 2021 Suez Canal blockage, which delayed 432 vessels carrying cargo valued at $92.7 billion, triggering widespread supply chain disruptions. Our ability to model the spatiotemporal ramifications of such incidents remains limited. To fill this gap, we develop an agent-based complex network model integrated with frequently updated maritime data. The Suez Canal blockage is taken as a case study. The results indicate that the effects of such blockages go beyond the directly affected countries and sectors. The Suez Canal blockage led to global losses of about $136.9 ($127.5-$147.3) billion, with India suffering 75% of these losses. Global losses show a nonlinear relationship with the duration of blockage and exhibit intricate trends post blockage. Our proposed model can be applied to diverse blockage scenarios, potentially acting as an early-alert system for the ensuing supply chain impacts. Furthermore, high-resolution daily data post blockage offer valuable insights that can help nations and industries enhance their resilience against similar future events.

Two Cases of False Elevation of MCHC.

BACKGROUND: Mean corpuscular hemoglobin concentration (MCHC) is one of the parameters detected by blood cell analyzers, often used together with mean corpuscular volume (MCV) and mean corpuscular hemoglobin content (MCH) as diagnostic indicators for anemia classification. It has important clinical value in early detection of the cause of anemia and the underlying etiology of anemia. Therefore, the accuracy of MCHC results is of great significance for the diagnosis and treatment of diseases. METHODS: We reported two cases of false elevation of MCHC. Considering the possibility of cold agglutination and lipid blood interference detection, we used 37℃ water bath and plasma exchange to correct for interference on the sample. RESULTS: After correcting the interference, MCHC returned to normal, consistent with the patient's disease status. Therefore, the two cases of abnormal elevation of MCHC are considered to be pseudo elevation caused by interference. CONCLUSIONS: For specimens with abnormally elevated MCHC levels, experimenters should first analyze possible interfering factors and choose effective methods to correct different interferences, providing accurate testing reports for doctors and patients.

Metagenomic and culture-dependent analysis of Rhinopithecius bieti gut microbiota and characterization of a novel genus of Sphingobacteriaceae.

Culture-dependent and metagenomic binning techniques were employed to gain an insight into the diversification of gut bacteria in Rhinopithecius bieti, a highly endangered primate endemic to China. Our analyses revealed that Bacillota_A and Bacteroidota were the dominant phyla. These two phyla species are rich in carbohydrate active enzymes, which could provide nutrients and energy for their own or hosts' survival under different circumstances. Among the culturable bacteria, one novel bacterium, designated as WQ 2009T, formed a distinct branch that had a low similarity to the known species in the family Sphingobacteriaceae, based on the phylogenetic analysis of its 16S rRNA gene sequence or phylogenomic analysis. The ANI, dDDH and AAI values between WQ 2009T and its most closely related strains S. kitahiroshimense 10CT, S. pakistanense NCCP-246T and S. faecium DSM 11690T were significantly lower than the accepted cut-off values for microbial species delineation. All results demonstrated that WQ 2009T represent a novel genus, for which names Rhinopithecimicrobium gen. nov. and Rhinopithecimicrobium faecis sp. nov. (Type strain WQ 2009T = CCTCC AA 2021153T = KCTC 82941T) are proposed.

The Effects of Different Durations of Night-Time Supplementary Lighting on the Growth, Yield, Quality and Economic Returns of Tomato.

To achieve higher economic returns, we employ inexpensive valley electricity for night-time supplementary lighting (NSL) of tomato plants, investigating the effects of various durations of NSL on the growth, yield, and quality of tomato. Tomato plants were treated with supplementary light for a period of 0 h, 3 h, 4 h, and 5 h during the autumn-winter season. The findings revealed superior growth and yield of tomato plants exposed to 3 h, 4 h, and 5 h of NSL compared to their untreated counterparts. Notably, providing lighting for 3 h demonstrated greater yields per plant and per trough than 5 h exposure. To investigate if a reduced duration of NSL would display similar effects on the growth and yield of tomato plants, tomato plants received supplementary light for 0 h, 1 h, 2 h, and 3 h at night during the early spring season. Compared to the control group, the stem diameter, chlorophyll content, photosynthesis rate, and yield of tomatoes significantly increased upon supplementation with lighting. Furthermore, the input-output ratios of 1 h, 2 h, and 3 h NSL were calculated as 1:10.11, 1:4.38, and 1:3.92, respectively. Nonetheless, there was no detectable difference in yield between the 1 h, 2 h, and 3 h NSL groups. These findings imply that supplemental LED lighting at night affects tomato growth in the form of light signals. Night-time supplemental lighting duration of 1 h is beneficial to plant growth and yield, and its input-output ratio is the lowest, which is an appropriate NSL mode for tomato cultivation.

Vision-Based Estimation of Force Balance of Near-Suspended Melt Pool for Drooping and Collapsing Prediction.

Wire-arc additive manufacturing (WAAM) is favored by the industry for its high material utilization rate and low cost. However, wire-arc additive manufacturing of lattice structures faces problems with forming accuracy such as broken rod and surface morphology defects, which cannot meet the industrial demand. This article innovatively combines the melt pool stress theory with visual perception algorithms to visually study the force balance of the near-suspended melt pool to predict the state of the melt pool. First, the method for melt pool segmentation was studied. The results show that the optimized U-net achieved high accuracy in melt pool segmentation tasks, with accuracies of 98.18%, MIOU 96.64%, and Recall 98.34%. In addition, a method for estimating melt pool force balance and predicting normal, sagging, and collapsing states of the melt pool is proposed. By combining experimental testing with computer vision technology, an analysis of the force balance of the melt pool during the inclined rod forming process was conducted, showing a prediction rate as high as 90% for the testing set. By using this method, monitoring and predicting the state of the melt pool is achieved, preemptively avoiding issues of broken rods during the printing process. This approach can effectively assist in adjusting process parameters and improving welding quality. The application of this method will further promote the development of intelligent unmanned WAAM and provide some references for the development of artificial intelligence monitoring systems in the manufacturing field.

A Pseudo Elevation of CEA Caused by Epidemic Hemorrhagic Fever.

BACKGROUND: Heterophilic antibodies (HA) are one of the main substances that interfere with immunology, especially chemiluminescence immunoassay. Non-specific binding, labeling antibodies, bridging to capture antibodies, or labeling antigens can interfere with the detection process, leading to serious discrepancies between the measured results and clinical manifestations, and even delaying clinical diagnosis and treatment. METHODS: This paper is a case of epidemic hemorrhagic fever causing pseudo CEA elevation caused by heterophagy induced antibodies in the body. RESULTS: The patient's CEA detected on the ABBOTT detection platform was 51.1 ng/mL, and on the ROCHE detection platforms it was 4.66 ng/mL, and treated by PEG precipitation it was 45.2 ng/mL, after diluting the sample the CEA was 50.2 ng/mL, meanwhile the patient's platelets were 96 x 109/L and serum creatinine was 188.4 µmol/L, epidemic hemorrhagic fever IgM antibody was positive. CONCLUSIONS: When the test results do not match clinical symptoms, further confirmation is required through additional testing. Patients who use mouse monoclonal antibody preparations for diagnosis or treatment may have human anti-mouse antibodies in their serum, and the test results may falsely increase or decrease.

Analysis of the combined effect of rs699 and rs5051 on angiotensinogen expression and hypertension.

Background: Hypertension (HTN) involves genetic variability in the renin-angiotensin system and influences antihypertensive response. We previously reported that angiotensinogen (AGT) messenger RNA (mRNA) is endogenously bound by miR-122-5p and rs699 A > G decreases reporter mRNA in the microRNA functional-assay PASSPORT-seq. The AGT promoter variant rs5051 C > T is in linkage disequilibrium (LD) with rs699 A > G and increases AGT transcription. The independent effect of these variants is understudied due to their LD therefore we aimed to test the hypothesis that increased AGT by rs5051 C > T counterbalances AGT decreased by rs699 A > G, and when these variants occur independently, it translates to HTN-related phenotypes. Methods: We used in silico, in vitro, in vivo, and retrospective models to test this hypothesis. Results: In silico, rs699 A > G is predicted to increase miR-122-5p binding affinity by 3%. Mir-eCLIP results show rs699 is 40-45 nucleotides from the strongest microRNA-binding site in the AGT mRNA. Unexpectedly, rs699 A > G increases AGT mRNA in an AGT-plasmid-cDNA HepG2 expression model. Genotype-Tissue Expression (GTEx) and UK Biobank analyses demonstrate liver AGT expression and HTN phenotypes are not different when rs699 A > G occurs independently from rs5051 C > T. However, GTEx and the in vitro experiments suggest rs699 A > G confers cell-type-specific effects on AGT mRNA abundance, and suggest paracrine renal renin-angiotensin-system perturbations could mediate the rs699 A > G associations with HTN. Conclusions: We found that rs5051 C > T and rs699 A > G significantly associate with systolic blood pressure in Black participants in the UK Biobank, demonstrating a fourfold larger effect than in White participants. Further studies are warranted to determine if altered antihypertensive response in Black individuals might be due to rs5051 C > T or rs699 A > G. Studies like this will help clinicians move beyond the use of race as a surrogate for genotype.

Advanced Design, Synthesis, and Evaluation of Highly Selective Wee1 Inhibitors: Enhancing Pharmacokinetics and Antitumor Efficacy.

Wee1 is a kinase that regulates cell cycle arrest in response to DNA damage. Wee1 inhibition is a potential strategy to suppress the growth of tumors with defective p53 or DNA repair pathways. However, the development of Wee1 inhibitors faces some challenges. AZD1775, the first-in-class Wee1 inhibitor, has poor kinase selectivity and dose-limiting toxicity. Here, we report the discovery of 12h, a highly selective and potent Wee1 inhibitor with a favorable pharmacokinetic profile. 12h showed strong antiproliferative effects against Lovo cells, a colorectal cancer cell line, both in vitro and in vivo. Moreover, 12h showed a clean kinase profile and effectively induced cell apoptosis. Our results suggest that 12h is a promising drug candidate for further development as a novel anticancer agent.

Enhanced reduction of Cd uptake by wheat plants using iron and manganese oxides combined with citrate in Cd-contaminated weakly alkaline arable soils.

Iron (Fe) and manganese (Mn) oxides can be used to remediate Cd-polluted soils due to their excellent performance in heavy metal adsorption. However, their remediation capability is rather limited, and a higher content of available Mn and Fe in soils can reduce Cd accumulation in wheat plants due to the competitive absorption effect. In this study, goethite and cryptomelane were first respectively used to immobilize Cd in Cd-polluted weakly alkaline soils, and sodium citrate was then added to increase the content of available Mn and Fe content for further reduction of wheat Cd absorption. In the first season, the content of soil-available Cd and Cd in wheat plants significantly decreased when cryptomelane, goethite and their mixture were used as the remediation agents. Cryptomelane showed a better remediation effect, which could be attributed to its higher adsorption performance. The grain Cd content could be decreased from 0.35 mg kg-1 to 0.25 mg kg-1 when the content of cryptomelane was controlled at 0.5%. In the second season, when sodium citrate at 20 mmol kg-1 was further added to the soils with 0.5% cryptomelane treatment in the first season, the content of soil available Cd was increased by 14.8%, and the available Mn content was increased by 19.5%, leading to a lower Cd content in wheat grains (0.16 mg kg-1) probably due to the competitive absorption. This work provides a new strategy for the remediation of slightly Cd-polluted arable soils with safe and high-quality production of wheat.

Decoding the Role of Secondary Motor Cortex Neuronal Ensembles during Cocaine Self-Administration: Insights from Longitudinal in vivo Calcium Imaging via Miniscopes.

Recent findings in our lab demonstrated that the risk of cocaine relapse is closely linked to the hyperexcitability of cortical pyramidal neurons in the secondary motor cortex (M2), noticeable 45 days after cocaine intravenous self-administration (IVSA). The present study was designed to explore the underlying mechanisms of neuronal alterations in M2. Our hypothesis was that M2 neurons were affected directly by cocaine taking behaviors. This hypothesis was tested by monitoring individual neuronal activity in M2 using MiniScopes for in vivo Ca 2+ imaging in C57BL/6J mice when they had access to cocaine IVSA as a reinforcement (RNF) contingent to active lever press (ALP) but not to inactive lever press (ILP). With support of our established pipeline to processing Ca 2+ imaging data, the current study was designed to monitor M2 neuronal ensembles at the single-neuron level in real time with high temporal resolution and high throughput in each IVSA session and longitudinally among multiple IVSA sessions. Specifically, five consecutive 1-hr daily IVSA sessions were used to model the initial cocaine taking behaviors. Besides detailed analyses of IVSA events (ALP, ILP, and RNF), the data from Ca 2+ imaging recordings in M2 were analyzed by (1) comparing neuronal activation within a daily IVSA session (i.e., the first vs. the last 15 min) and between different daily sessions (i.e., the first vs. the last IVSA day), (2) associating Ca 2+ transients with individual IVSA events, and (3) correlating Ca 2+ transients with the cumulative effects of IVSA events. Our data demonstrated that M2 neurons are exquisitely sensitive to and significantly affected by concurrent operant behaviors and the history of drug exposure, which in turn sculpt the upcoming operant behaviors and the response to drugs. As critical nodes of the reward loop, M2 neurons appear to be the governing center orchestrating the establishment of addiction-like behaviors.