Synergistic Combination Research Articles

Personalised use of repurposed non-anticancer drugs in colorectal cancer based on up-regulated signalling pathways: A real world cohort feasibility study.

833 Background: Targeting signaling pathways in colorectal cancers is a common therapeutic strategy. In addition to targeted drugs, non- anticancer drugs approved for use in other health conditions can inhibit key pathways. De novo tumor transcriptome analysis can identify patient-specific up- and down-regulated transcripts, based on which the corresponding repurposed drugs can be used in synergistic combinations with standard of care (SoC) regimens. Methods: This retrospective study was conducted on a real-world cohort of 459 colorectal cancer cases (218 females, 241 males; median age 56 years) who had taken Exacta multi-omics tumor profiling for selection of personalized treatments. Transcriptome analysis was performed as part of the evaluations to determine up and down-regulated gene transcripts for selecting targeted, endocrine, and cytotoxic anticancer agents as well as non-anticancer (repurposed) drugs and phytochemicals that could be used for tandem targeting of the dysregulated signaling pathways, as indicated in the table below. Results: Transcriptome analysis of this cohort revealed dysregulation of ≥1 pathway in 391 patients (85.2%). MAPKs (n = 244, 53.2%) and MMPs (n = 210, 45.8%) were most frequently upregulated. Celecoxib (n = 292, 63.6%), Atorvastatin (n = 255, 55.6%), and Doxycycline (n = 208, 45.3%) were the most frequently indicated repurposed drugs for targeting the identified dysregulated pathways. Potential indications for ≥1 repurposed drugs were seen in 353 patients (76.9%). Conclusions: Several cellular signaling pathways are known or potential therapeutic targets in cancers. The present study indicates that it may be possible to use multi-omics analyses to create personalized treatment strategies using a synergistic combination of repurposed drugs to potentiate the action of SoC systemic anticancer agents in colorectal cancer. Biomarkers for non anti-cancer drugs selection. Drug Biomarker/Gene Expression Aspirin PTGS2 (COX2) Atorvastatin HMGCR, MAPK Bromelain PTGS2 (COX2) Celecoxib PTGS2 (COX2), FZD, WNT, ΜΑΡΚ Chloroquine HMGB1 Curcumin MMP, BIRC5, BCL2 Doxycycline MMP Metformin MMP, BCL2, ΜΑΡΚ Quercetin FZD, WNT Resveratrol MMP, BCL2, PCNA, PTGS2 (COX2) Vitamin C SLC2A1 (GLUT1) Artesunate FZD, WNT, MMP, BCL2 Cannabidiol MMP Epigallocatechin gallate MMP, MAPK Mebendazole XIAP, MMP, MAPK

Promoting macrophage phagocytosis of cancer cells for effective cancer immunotherapy.

Cancer therapy has been revolutionized by immunotherapeutic agents exploiting adaptive antitumor immunity in the past two decades. However, the overall response rate of these immunotherapies is limited, and patients also develop resistance upon treatment, promoting a rapidly growing exploration of anti-tumor innate immunity for effective cancer therapy. Among these, macrophage immunotherapy through harnessing macrophage phagocytosis has been thrust into the spotlight due to its potential for simultaneously inducing cancer cell killing effect and mobilizing adaptive antitumor responses. Here in this review, we summarize the current macrophage immunotherapy such as therapeutic antibodies, phagocytosis checkpoint blockades, and CAR-macrophages with a particular emphasis on the resistant mechanisms limiting their therapeutic effects. Moreover, we further survey the efforts being placed to seek synergistic mechanisms and combination strategies for promoting macrophage phagocytosis which might stand as next-generation cancer immunotherapy.

Synergistic Multi-Drug Combination Prediction Based on Heterogeneous Network Representation Learning with Contrastive Learning

Synergistic Multi-Drug Combination Prediction Based on Heterogeneous Network Representation Learning with Contrastive Learning

Frontiers in therapeutic interventions for epilepsy: Nanocarriers as a pivotal catalyst in the synergistic combination of conventional antiepileptics and herbal drugs

Frontiers in therapeutic interventions for epilepsy: Nanocarriers as a pivotal catalyst in the synergistic combination of conventional antiepileptics and herbal drugs

Seeking innovative concepts in development of antiviral drug combinations.

Antiviral drugs are crucial for managing viral infections, but current treatment options remain limited, particularly for emerging viruses. These drugs can be classified based on their chemical composition, including neutralizing antibodies (nAbs), recombinant human receptors (rhRs), antiviral CRISPR/Cas systems, interferons, antiviral peptides (APs), antiviral nucleic acid polymers, and small molecules. Some of these agents target viral factors, host factors, or both. A major challenge for virus-targeted treatments is their narrow-spectrum effectiveness and the potential for drug resistance, while host-directed and virus/host-targeted therapies often suffer from significant side effects. The synergistic combination of multiple antiviral drugs holds promise for improving treatment outcomes by targeting different stages of the viral life cycle, reducing resistance, and minimizing side effects. However, developing such drug combinations presents its own set of challenges. Several drug combinations could be optimized, and new combinations developed by using AI, to more effectively treat both emerging and re-emerging viral infections.

Perturbation of Pseudomonas aeruginosa peptidoglycan recycling by anti-folates and design of a dual-action inhibitor.

To combat the alarming global increase in superbugs amid the simultaneous scarcity of new drugs, we can create synergistic combinations of currently available antibiotics or chimeric molecules with dual activities, to minimize resistance. Here we show that older anti-folate drugs synergize with specific cell wall biosynthesis inhibitors to kill the priority pathogen, Pseudomonas aeruginosa. Anti-folate drugs caused a dose-dependent loss of rod cell shape followed by explosive lysis, and synergized with β-lactams that target D,D-carboxypeptidases required to tailor the cell wall. Anti-folates impaired cell wall recycling and subsequent downstream expression of the chromosomally encoded β-lactamase, AmpC, which normally destroys β-lactam antibiotics. Building on the anti-folate-like scaffold of a metallo-β-lactamase inhibitor, we created a new molecule, MLLB-2201, that potentiates β-lactams and anti-folates and restores meropenem activity against metallo-β-lactamase-expressing Escherichia coli. These strategies are useful ways to tackle the ongoing rise in dangerous bacterial pathogens.

Leveraging Network Target Theory for Efficient Prediction of Drug-Disease Interactions: A Transfer Learning Approach.

Efficient virtual screening methods can expedite drug discovery and facilitate the development of innovative therapeutics. This study presents a novel transfer learning model based on network target theory, integrating deep learning techniques with diverse biological molecular networks to predict drug-disease interactions. By incorporating network techniques that leverage vast existing knowledge, the approach enables the extraction of more precise and informative drug features, resulting in the identification of 88,161 drug-disease interactions involving 7,940 drugs and 2,986 diseases. Furthermore, this model effectively addresses the challenge of balancing large-scale positive and negative samples, leading to improved performance across various evaluation metrics such as an Area under curve (AUC) of 0.9298 and an F1 score of 0.6316. Moreover, the algorithm accurately predicts drug combinations and achieves an F1 score of 0.7746 after fine-tuning. Additionally, it identifies two previously unexplored synergistic drug combinations for distinct cancer types in disease-specific biological network environments. These findings are further validated through in vitro cytotoxicity assays, demonstrating the potential of the model to enhance drug development and identify effective treatment regimens for specific diseases.

Synergistic antimicrobial activity of essential oils mixture of Moringa oleifera, Cinnamomum verum and Nigella sativa against Staphylococcus aureus using L-optimal mixture design

The urgent need to address the growing problem of antimicrobial resistance in multidrug-resistant bacteria requires the development of pioneering approaches to treatment. The present study aims to evaluate the antimicrobial potential of the essential oils (EOs) of Moringa oleifera (moringa), Cinnamomum verum (cinnamon), and Nigella sativa (black seed) and the synergistic effect of the mixture of these oils against Staphylococcus aureus MCC 1351. Statistical modeling revealed cinnamon oil had the highest individual antimicrobial potency, followed by black seed oil. The combination of the three EOs exhibited significant synergistic effects compared to the individual oils, with a Fractional Inhibitory Concentration (∑FIC) index of 0.27. L-Optimal mixture design of response surface methodology (RSM) identified the optimal mixture as moringa: cinnamon: black seed oils by the ratio of (1:1:1) in run 15 (0.338:0.307:0.355 mL) (v/v). This mixture exhibited significant antibacterial efficacy, outperforming individual oils and conventional antibiotics like tetracycline. Specifically, the combination reduced the MIC values from 3.12, 0.78, and 6.25 to 0.25, 0.06, and 0.78 μg/mL for moringa, cinnamon, and black seed oil, respectively. Synergistic interactions between oils further boosted efficacy, with moringa-cinnamon and cinnamon-black seed pairings exhibiting the strongest synergies. The developed predictive models for IZD and MIC showed excellent fit, with R2 values of 0.9843 and 0.9958, respectively. Pareto chart analysis highlighted the predominant individual and synergistic effects, with the Moringa-Cinnamon interaction exhibiting the highest positive synergy. Notably, the oil mixture of run 15 demonstrated excellent biocompatibility, maintaining 97.6% viability of normal human skin fibroblasts (HSF) after 24 h exposure to 200 μL EOs of the mixture per mL. Gas chromatography mass spectrometry (GC/MS) identified abundant bioactive phytochemicals like cinnamaldehyde, linoleic acid, and palmitic acid methyl esters underlying the observed antimicrobial effects. This rationally designed, synergistic phytochemical combination presents a promising natural therapeutic against antibiotic-resistant S. aureus while exhibiting minimal cytotoxicity. The results underscore how combining essential oils could help address the issue of antibiotic resistance in S. aureus.

A guide for active learning in synergistic drug discovery

Synergistic drug combination screening is a promising strategy in drug discovery, but it involves navigating a costly and complex search space. While AI, particularly deep learning, has advanced synergy predictions, its effectiveness is limited by the low occurrence of synergistic drug pairs. Active learning, which integrates experimental testing into the learning process, has been proposed to address this challenge. In this work, we explore the key components of active learning to provide recommendations for its implementation. We find that molecular encoding has a limited impact on performance, while the cellular environment features significantly enhance predictions. Additionally, active learning can discover 60% of synergistic drug pairs with only exploring 10% of combinatorial space. The synergy yield ratio is observed to be even higher with smaller batch sizes, where dynamic tuning of the exploration-exploitation strategy can further enhance performance. The code can be found at https://github.com/LBiophyEvo/DrugSynergy

Photoelectrocatalyzed Alkylation of Phosphonites by Direct Decarboxylative C(sp3)-P Coupling.

A photoelectrocatalytic method is presented that achieves direct decarboxylative C(sp3)-P coupling, providing a modular route to alkylphosphinates and alkylphosphonates from readily available carboxylic acids. The success of this reaction hinges on the synergistic combination of electrochemical anodic oxidation and photocatalytic ligand to metal charge transfer (LMCT) decarboxylation. By employing P(III) reagents as limiting reagents, our approach enables efficient alkyl modification of medicinally important nucleosides and complex molecules derived phosphonites, which were challenging to access by existing methods. Detailed mechanistic studies elucidate the critical roles of Fe catalysts and additives, offering valuable insights into the reaction pathway and laying the foundation for future advancements in photoelectrocatalytic C(sp3)-heteroatom bond-forming reactions.

Photoelectrocatalyzed Alkylation of Phosphonites by Direct Decarboxylative C(sp3)‐P Coupling

A photoelectrocatalytic method is presented that achieves direct decarboxylative C(sp3)–P coupling, providing a modular route to alkylphosphinates and alkylphosphonates from readily available carboxylic acids. The success of this reaction hinges on the synergistic combination of electrochemical anodic oxidation and photocatalytic ligand to metal charge transfer (LMCT) decarboxylation. By employing P(III) reagents as limiting reagents, our approach enables efficient alkyl modification of medicinally important nucleosides and complex molecules derived phosphonites, which were challenging to access by existing methods. Detailed mechanistic studies elucidate the critical roles of Fe catalysts and additives, offering valuable insights into the reaction pathway and laying the foundation for future advancements in photoelectrocatalytic C(sp3)–heteroatom bond‐forming reactions.

Hierarchically Enhanced Plasmonic Absorber with Abundant Nanomirrors for Effective Photoelectrochemical Performance

The synergistic combination of plasmonic metals and semiconductors demonstrates marvelous potential for nanocomposite design, particularly in enhancing photoelectrochemical performance through rich interfacial modifications and component properties adjustments. In terms of it, nanocomplexes of metal/insulator or semiconductor/metal have emerged heatedly, commonly depicted as nanomirror structures. In this work, a sandwiched nanomirror structure comprising a core Ag nanorods, a TiO2 middle nanogap, and dual types of Au and Ag particles outermost is presented, putting forward a novel design idea of rolling the planar complex up to amplify the potential interaction systems. The TiO2 middle layer enables the intrinsic generation of charge carriers upon light exposure, while the established heterojunctions promote their efficient separation. Additionally, both the inner Ag NRs and outer metal nanoparticles exhibit localized surface plasma resonance effects to realize enhancement of electric fields, where plasmonic coupling between them generates field hotspots within TiO2 layer, thereby expanding light absorption range and enhancing light capture intensity. Beyond, hot electrons from plasmonic metals traverse Schottky barriers into TiO2 to participate in further reactions, all of which contribute to heightened PEC performance of the nanostructure. In this work, the path is paved for innovative nanostructure design integrating plasmonic metals with semiconductors, offering promising implications for energy‐related applications.

A Near‐Single‐Ion Conducting Protective Layer for Dendrite‐Free Zinc Metal Anodes

AbstractThe instability of zinc metal anodes, including dendrite formation and corrosion, limits their application in aqueous zinc‐ion batteries (AZIBs). Here, a near‐single zinc‐ion conducting (NSIC) protective layer that enables dendrite‐free Zn anodes by integrating Zn2⁺‐conducting polymer matrices with counter‐anion trapping agents is presented. Sulfonic acid groups, covalently bonded to polymeric backbones enhance Zn2⁺ ion mobility while counter‐anions are immobilized by amine‐functionalized metal‐organic frameworks embedded within the polymer layer. This synergistic combination enables near single zinc ion transport (tZn2⁺ = 0.91). The NSIC layer extends sand's time and promotes uniform Zn deposition along the (002) orientation, preventing dendrite formation. Consequently, full cells with thin Zn@NSIC anodes (14 µm) exhibit stable cycling performance over 5000 cycles at 5 A g⁻¹, with a low negative‐to‐positive areal capacity (NP) ratio of 3.3 and a Zn depth of discharge exceeding 30%. Furthermore, the NSIC layer is also adapted for enlarged Zn anodes (80 cm2) in large‐sized full cells, delivering stable operation with a capacity of ≈300 mAh at 1 A g⁻¹. These results offer valuable insights into ion transport control within protective layers, advancing the development of practical AZIBs with high anode reversibility.

Universal Phase Identification of Block Copolymers From Physics‐Informed Machine Learning

ABSTRACTBlock copolymers play a vital role in materials science due to their diverse self‐assembly behavior. Traditionally, exploring the block copolymer self‐assembly and associated structure–property relationships involve iterative synthesis, characterization, and theory, which is labor‐intensive both experimentally and computationally. Here, we introduce a versatile, high‐throughput workflow toward materials discovery that integrates controlled polymerization and automated chromatographic separation with a novel physics‐informed machine‐learning algorithm for the rapid analysis of small‐angle X‐ray scattering data. Leveraging the expansive and high‐quality experimental data sets generated by fractionating polymers using automated chromatography, this machine‐learning method effectively reduces data dimensionality by extracting chemical‐independent features from SAXS data. This new approach allows for the rapid and accurate prediction of morphologies without repetitive and time‐consuming manual analysis, achieving out‐of‐sample predictive accuracy of around 95% for both novel and existing materials in the training data set. By focusing on a subset of samples with large predictive uncertainty, only a small fraction of the samples needs to be inspected to further improve accuracy. Collectively, the synergistic combination of controlled synthesis, automated chromatography, and data‐driven analysis creates a powerful workflow that markedly expedites the discovery of structure–property relationships in advanced soft materials.

Combined Effect of Conventional Chemotherapy with Epigenetic Modulators on Glioblastoma

Background/Objectives: Glioblastoma is the most common malignant primary brain tumor, characterized by necrosis, uncontrolled proliferation, infiltration, angiogenesis, apoptosis resistance, and genomic instability. Epigenetic modifiers hold promise as adjuvant therapies for gliomas, with synergistic combinations being explored to enhance efficacy and reduce toxicity. This study aimed to evaluate the effects of single or combined treatments with various anticancer drugs (Carboplatin, Paclitaxel, Avastin), natural compounds (Quercetin), and epigenetic modulators (suberoylanilide hydroxamic acid and 5-Azacytidine) on the expression of some long noncoding RNAs and methylation drivers or some functional features in the U87-MG cell line. Methods: Treated and untreated U87-MG cells were used for the evaluation of drug-induced cytotoxicity, apoptotic events, and distribution in cell cycle phases, detection of cytokine release, and assessment of gene expression and global methylation. Results: Cytotoxicity assays led to the selection of drug concentrations to be used in further experiments. Expression analysis revealed distinct downregulation of nearly all investigated genes and long noncoding RNAs following treatments. All treatments resulted in a higher percentage of global methylation compared to untreated controls. All treatments effectively increased levels of apoptosis, while the epigenetic modulators exhibited a lower proliferation profile, with combined treatments showing elevated values of cell lysis. Conclusions: The results indicate a link between Carboplatin and Avastin treatments and DNA methylation mechanisms involving EZH2, DNMT3A, and DNMT3B, with Avastin’s direct impact on these enzymes warranting further study. This research underscores the promise of platinum-based therapies combined with epigenetic drugs to reactivate silenced tumor suppressor genes and optimize methylation profiles.

Synergistic combination of orally available safe-in-man pleconaril, AG7404, and mindeudesivir inhibits enterovirus infections in human cell and organoid cultures

Enteroviruses can infect various human organs, causing diseases such as meningitis, the common cold, hand-foot-and-mouth disease, myocarditis, pancreatitis, hepatitis, poliomyelitis, sepsis, and type 1 diabetes. Currently, there are no approved treatments for enterovirus infections. In this study, we identified a synergistic combination of orally available, safe-in-man pleconaril, AG7404, and mindeudesivir, that at non-toxic concentrations effectively inhibited enterovirus replication in human cell and organoid cultures. Importantly, the cocktail did not alter glucose and insulin levels in the culture medium of pancreatic β-cells and preserved the contraction rhythm of infected heart organoids. These findings highlight a promising drug cocktail for further preclinical studies and clinical trials targeting a broad range of enterovirus-mediated diseases.

Effect of porphyrin metalation and synergistic combination with fluconazole in antifungal PDT against Candida spp

Effect of porphyrin metalation and synergistic combination with fluconazole in antifungal PDT against <i>Candida spp</i>

Bioactive Compounds in Herbal Shampoos: A Comprehensive Review of their Efficacy in Promoting Hair Growth and Controlling Dandruff

Herbal shampoos have emerged as a sustainable alternative to synthetic formulations, leveraging the therapeutic properties of natural ingredients for hair health. This systematic review explores the formulation and evaluation of herbal shampoos for promoting hair growth and combating dandruff. Traditional uses of herbs such as Neem, Bhringraj, and Aloe Vera are highlighted, emphasizing their antifungal, anti-inflammatory, and hair-strengthening benefits. Modern formulation techniques, including natural surfactants and nanotechnology, enhance the stability and efficacy of these products. Evaluation parameters such as pH, viscosity, antimicrobial activity, and hair growth assays are discussed, providing a comprehensive framework for quality assessment. Recent advancements in ingredient selection, synergistic herb combinations, and clinical validation underscore the growing scientific interest in herbal shampoos. The review also identifies challenges such as ingredient variability, regulatory compliance, consumer expectations, and strategies for addressing them. It also highlights future directions, including personalized formulations, exploration of underutilized herbs, and integration of AI and biotechnological tools. Herbal shampoos represent a fusion of traditional knowledge and scientific innovation, offering a safe and eco-friendly solution for diverse hair concerns. By addressing current limitations and leveraging technological advancements, these products have the potential to revolutionize the hair care industry.

Exploring the Benefits and Prescribing Informations of Combining East Asian Herbal Medicine with Conventional Medicine in the Treatment of Rheumatoid Arthritis: A Systematic Review and Multifaceted Analysis of 415 Randomized Controlled Trials.

Notwithstanding progress in conventional medicine (CM), the management of rheumatoid arthritis (RA) continues to be problematic due to factors such as limited patient response to treatment and restricted medication access. This study aimed to evaluate the extent to which East Asian herbal medicine with CM combination therapy (EACM) provides additional benefits in effectiveness and safety. We conducted a comprehensive search across 11 databases in English, Chinese, Korean, and Japanese for randomized controlled trials. The review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, using the American College of Rheumatology (ACR) 20/50/70 Response Criteria and the incidence of adverse events (AEI) as primary outcomes. This meta-analysis was performed using a random-effects model. The quality of each study was assessed according to the RoB 2. Of the 1,036 full-text articles screened, 415 were included in the review. This review included data from 37,839 participants. EACM was associated with higher ACR responses: ACR 20 (RR: 1.2332; 95% CI: 1.1852 to 1.2831, p < 0.0001), ACR 50 (RR: 1.3782; 95% CI: 1.2936 to 1.4684, p < 0.0001), and ACR 70 (RR: 1.7084; 95% CI: 1.5555 to 1.8762, p < 0.0001), as well as a favorable AEI (OR: 0.3977; 95% CI: 0.3476 to 0.4551, p < 0.0001), indicating both better efficacy and safety compared to CM alone. These patterns were consistent across eight secondary outcomes measuring pain, inflammation, and disease activity in RA. Subgroup analyses showed that EACM's effects were independent of the control CM type. Through a comprehensive analysis of a polyherbal prescription dataset, we identified 18 key herbs and 16 significant combination rules, further supported by relevant preclinical evidence. These herbs and synergistic herbal combinations were anticipated to be the most pharmacologically influential in contributing to the meta-analysis outcomes, as substantiated by analytical metrics including network topology and intricate association pattern evaluations. The findings suggest that EACM may serve as a valuable complementary strategy for RA patients insufficiently managed by CM alone. In particular, given that the ACR index integrates multiple aspects of RA patients, the results are expected to provide valuable complementary decision support for the management of RA patients who do not respond well to CM therapy, both for medical and economic reasons. Additionally, the key herbs derived through the multifaceted analysis, which actively reflect clinicians' implicit preferences for prescribing EACMs, may serve as important hypotheses for further research and clinical application. However, additional qualitative and quantitative improvements in research are needed for more definitive conclusions. Further analysis of the herbal prescriptions presented in this study will provide valuable direction for future research.

Exploring Singlet Carbyne Anions and Related Low-Valent Carbon Species Utilizing a Cyclic Phosphino Substituent.

ConspectusThe advancement of synthetic methodologies is fundamentally driven by a deeper understanding of the structure-reactivity relationships of reactive key intermediates. Carbyne anions are compounds featuring a monovalent anionic carbon possessing four nonbonding valence electrons, which were historically confined to theoretical constructs or observed solely within the environment of gas-phase studies. These species possess potential for applications across diverse domains of synthetic chemistry and ancillary fields. This Account details our focused efforts to isolate singlet carbyne anions and explores our isolation of a range of related low-valent carbon species. Our achievements include the synthesis and characterization, under normal laboratory conditions, of gold-substituted free carbenes, copper carbyne anion complexes, ketenyl anions, keteniminyl anions, and a free stannyne. These have been accomplished using a bulky cyclic phosphino substituent, which effectively stabilizes these reactive species.Our journey commenced with the isolation of gold-substituted phosphinocarbenes, characterized by a robust carbon-gold covalent single bond, and progressed to the isolation of copper carbyne anion complexes featuring a carbon-copper ionic bond. This was realized through the synergistic combination of a bulky cyclic phosphino group and a closed-shell electron-rich late transition metal. The robustness of the carbon-gold bond contrasts markedly with the susceptibility of the carbon-copper bond, which imparts to the copper complexes the behavior characteristic of a phosphinocarbyne anion within the coordination sphere of copper, thereby enabling unique carbyne anion transfer reactions. The tri-active ambiphilic nature of the anionic carbon in these copper carbyne complexes enables the formation of three chemical bonds at the carbon center through one-pot reactions. Subsequent investigations unveiled ligand exchange reactions at the carbyne anion site, leading to the generation of stable crystalline ketenyl and keteniminyl anions. These species emerge as potent synthons capable of producing a diverse array of derivatives. In addition, we isolated a free phosphinostannyne, a rare species featuring a carbon-tin multiple bond and two adjacent ambiphilic centers. Collectively, these compounds have demonstrated a remarkable propensity for engaging in a spectrum of unique reactions, underscoring their versatility and confirming their utility in synthesizing uncharted, unique main group species.The methodologies and insights derived from our research contribute to the broader understanding of low-valent carbon species and may provide a platform for future innovations in synthetic chemistry, catalytic processes, and novel materials. As we continue to explore and develop this area of study, we hope that these low-valent carbon species might follow in the footsteps of stable singlet carbenes, potentially finding applications across various fields in the future.