Inferring gene regulatory networks using transcriptional profiles as dynamical attractors.

Genetic regulatory networks (GRNs) regulate the flow of genetic information from the genome to expressed messenger RNAs (mRNAs) and thus are critical to controlling the phenotypic characteristics of cells. Numerous methods exist for profiling mRNA transcript levels and identifying protein-DNA binding interactions at the genome-wide scale. These enable researchers to determine the structure and output of transcriptional regulatory networks, but uncovering the complete structure and regulatory logic of GRNs remains a challenge. The field of GRN inference aims to meet this challenge using computational modeling to derive the structure and logic of GRNs from experimental data and to encode this knowledge in Boolean networks, Bayesian networks, ordinary differential equation (ODE) models, or other modeling frameworks. However, most existing models do not incorporate dynamic transcriptional data since it has historically been less widely available in comparison to "static" transcriptional data. We report the development of an evolutionary algorithm-based ODE modeling approach (named EA) that integrates kinetic transcription data and the theory of attractor matching to infer GRN architecture and regulatory logic. Our method outperformed six leading GRN inference methods, none of which incorporate kinetic transcriptional data, in predicting regulatory connections among TFs when applied to a small-scale engineered synthetic GRN in Saccharomyces cerevisiae. Moreover, we demonstrate the potential of our method to predict unknown transcriptional profiles that would be produced upon genetic perturbation of the GRN governing a two-state cellular phenotypic switch in Candida albicans. We established an iterative refinement strategy to facilitate candidate selection for experimentation; the experimental results in turn provide validation or improvement for the model. In this way, our GRN inference approach can expedite the development of a sophisticated mathematical model that can accurately describe the structure and dynamics of the in vivo GRN.

A prognostic model for hepatocellular carcinoma patients based on polyunsaturated fatty acid-related genes.

OBJECTIVE: Polyunsaturated fatty acids (PUFAs) have attracted increasing attention for their role in liver cancer development. The objective of this study is to develop a prognosis prediction model for patients with liver cancer based on PUFA-related metabolic gene characteristics. METHOD: Transcriptome data and clinical data were obtained from public databases, while gene sets related to PUFAs were acquired from the gene set enrichment analysis (GSEA) database. Univariate Cox analysis was conducted on the training set, followed by LASSO logistic regression and multivariate Cox analysis on genes with p < .05. Subsequently, the stepwise Akaike information criterion method was employed to construct the model. The high- and low-risk groups were divided based on the median score, and the model's survival prediction ability, diagnostic efficiency, and risk score distribution of clinical features were validated. The above procedures were also validated in the validation set. Immune infiltration levels were evaluated using four algorithms, and the immunotherapeutic potential of different groups was explored. Significant enrichment pathways among different groups were selected based on the GSEA algorithm, and mutation analyses were conducted. Nomogram prognostic models were constructed by incorporating clinical factors and risk scores using univariate and multivariate Cox regression analysis, validated through calibration curves and clinical decision curves. Additionally, sensitivity analysis of drugs was performed to screen potential targeted drugs. RESULTS: We constructed a prognostic model comprising eight genes (PLA2G12A, CYP2C8, ABCCI, CD74, CCR7, P2RY4, P2RY6, and YY1). Validation across multiple datasets indicated the model's favorable prognostic prediction ability and diagnostic efficiency, with poorer grading and staging observed in the high-risk group. Variations in mutation status and pathway enrichment were noted among different groups. Incorporating Stage, Grade, T.Stage, and RiskScore into the nomogram prognostic model demonstrated good accuracy and clinical decision benefits. Multiple immune analyses suggested greater benefits from immunotherapy in the low-risk group. We predicted multiple targeted drugs, providing a basis for drug development. CONCLUSION: Our study's multifactorial prognostic model across multiple datasets demonstrates good applicability, offering a reliable tool for personalized therapy. Immunological and mutation-related analyses provide theoretical foundations for further research. Drug predictions offer important insights for future drug development and treatment strategies. Overall, this study provides comprehensive insights into tumor prognosis assessment and personalized treatment planning.

Recent advances of nanodrug delivery system in the treatment of hematologic malignancies.

Although the survival rate of hematological malignancies (HM) has increased in recent years, the unnecessary adverse effect to the body is usually generated by the traditional chemotherapy for HM due to the lack of specificity to tumor tissue. Nanodrug delivery systems have exhibited unique advantages in targetability, stability and reducing toxicity, attracting wide concern, which is expected to be the prevalent alternative for the treatment of HM. In this review, we systemically introduced the current therapeutic strategies and the categories of HM. Subsequently, five key factors including circulation, targeting, penetration, internalization and release involving in tailoring nanoparticles were demonstrated, followed by the introduction of the development of nanodrug delivery-traditional synthetic nanomaterilas, biomimetic cell membrane coating nanomaterials, cell-based nanomaterials as well as immunotherapy combined with nanodrug. Afterwards, the recent advances of nanodrug delivery system for the treatment of HM were introduced. Moreover, the challenge and prospect of nanodrug delivery system in treating HM were discussed. The promising drug delivery system will provide new therapeutic avenues for the treatment of HM.

CDGSH iron sulfur domain 2 over-expression alleviates neuronal ferroptosis and brain injury by inhibiting lipid peroxidation via AKT/mTOR pathway following intracerebral hemorrhage in mice.

Ferroptosis has been implicated in the pathogenesis of secondary brain injury following intracerebral hemorrhage (ICH), and regulating this process is considered a potential therapy for alleviating further brain injury. A previous study showed that CDGSH iron sulfur domain 2 (CISD2) can inhibit ferroptosis in cancer. Thus, we investigated the effects of CISD2 on ferroptosis and the mechanisms underlying its neuroprotective role in mice after ICH. CISD2 expression markedly increased after ICH. CISD2 over-expression significantly decreased the number of Fluoro-Jade C-positive neurons and alleviated brain edema and neurobehavioral deficits at 24 h after ICH. In addition, CISD2 over-expression up-regulated the expression of p-AKT, p-mTOR, ferritin heavy chain 1, glutathione peroxidase 4, ferroportin, glutathione, and glutathione peroxidase activity, which are markers of ferroptosis. Additionally, CISD2 over-expression down-regulated the levels of malonaldehyde, iron content, acyl-CoA synthetase long-chain family member 4, transferrin receptor 1, and cyclooxygenase-2 at 24 h after ICH. It also alleviated mitochondrial shrinkage and decreased the density of the mitochondrial membrane. Furthermore, CISD2 over-expression increased the number of GPX4-positive neurons following ICH induction. Conversely, knockdown of CISD2 aggravated neurobehavioral deficits, brain edema, and neuronal ferroptosis. Mechanistically, MK2206, an AKT inhibitor, suppressed p-AKT and p-mTOR and reversed the effects of CISD2 over-expression on markers of neuronal ferroptosis and acute neurological outcome. Taken together, CISD2 over-expression alleviated neuronal ferroptosis and improved neurological performance, which may be mediated through the AKT/mTOR pathway after ICH. Thus, CISD2 may be a potential target to mitigate brain injury via the anti-ferroptosis effect after ICH.

The construction of Fe-porphyrin nanozymes with peroxidase-like activity for colorimetric detection of glucose.

As a type of nanomaterials with enzyme-mimetic catalytic properties, nanozymes have attracted wide concern in biological detection. H2O2 was the characteristic product of diverse biological reactions, and the quantitative analysis for H2O2 was an important way to detect disease biomarkers, such as acetylcholine, cholesterol, uric acid and glucose. Therefore, there is of great significance for developing a simple and sensitive nanozyme to detect H2O2 and disease biomarkers by combining with corresponding enzyme. In this work, Fe-TCPP MOFs were successfully prepared by the coordination between iron ions and porphyrin ligands (TCPP). In addition, the peroxidase (POD) activity of Fe-TCPP was proved, in detail, Fe-TCPP could catalyze H2O2 to produce ·OH. Herein, glucose oxidase (GOx) was chosen as the model to build cascade reaction by combining Fe-TCPP to detect glucose. The results indicated glucose could be detected by this cascade system selectively and sensitively, and the limit of detection of glucose was achieved to 0.12 µM. Furthermore, a portable hydrogel (Fe-TCPP@GEL) was further established, which encapsulated Fe-TCPP MOFs, GOx and TMB in one system. This functional hydrogel could be applied for colorimetric detection of glucose by coupling with a smartphone easily.

Is catheter-based foam sclerotherapy more effective than direct foam sclerotherapy when combined with high ligation for the treatment of primary great saphenous vein incompetence?

BACKGROUND: To retrospectively analyze the short-term outcomes of catheter-based versus direct foam sclerotherapy when combined with high ligation (HL) for the treatment of great saphenous vein (GSV) incompetence. METHODS: From July 2018 to October 2019, a total of 82 lower limbs of 70 patients with GSV incompetence received HL combined with catheter-based foam sclerotherapy (CFS group) or direct foam sclerotherapy (DFS group) for GSV proximal trunk. Among them, 40 limbs of 36 patients were treated with CFS, and 42 limbs of 34 patients were treated with DFS. The occlusion of GSV proximal trunk was evaluated with venous duplex ultrasound examinations; Venous Clinical Severity Scores (VCSS) was used to assess clinical improvement; Aberdeen Varicose Veins Questionnaire (AVVQ) was used to assess quality-of-life scores; and Complications was used for the safety evaluation. RESULTS: At day 7 post-operatively, complete occlusion of proximal trunk of the GSV was achieved in 92.5% legs of the CFS group and 71.4% of the DFS group (p = 0.014). Additionally, anterograde flow was found in 7.5% legs of the CFS group and 26.2% of the DFS group (p = 0.025). No significant differences in the occurrence of complications were observed between the two groups. The median follow-up was 285.5 days in the DFS group and 318 days in the CFS group (p = 0.140). VCSS and AVVQ reduction were significant in both CFS group and DFS group (5.3 ± 2.5, 5.5 ± 2.4, p < 0.001 for VCSS; 15.9 ± 8.0, 16.3 ± 8.6, p < 0.001 for AVVQ), but no significant difference were observed between two groups (p = 0.655 for VCSS, p = 0.934 for AVVQ). CONCLUSIONS: Although the occlusion of great saphenous vein proximal trunk were different, two modalities result in similar clinical and quality-of-life improvements. DFS is a feasible alternative to CFS when combined with HL.

ESVIO: Event-Based Stereo Visual-Inertial Odometry.

The emerging event cameras are bio-inspired sensors that can output pixel-level brightness changes at extremely high rates, and event-based visual-inertial odometry (VIO) is widely studied and used in autonomous robots. In this paper, we propose an event-based stereo VIO system, namely ESVIO. Firstly, we present a novel direct event-based VIO method, which fuses events' depth, Time-Surface images, and pre-integrated inertial measurement to estimate the camera motion and inertial measurement unit (IMU) biases in a sliding window non-linear optimization framework, effectively improving the state estimation accuracy and robustness. Secondly, we design an event-inertia semi-joint initialization method, through two steps of event-only initialization and event-inertia initial optimization, to rapidly and accurately solve the initialization parameters of the VIO system, thereby further improving the state estimation accuracy. Based on these two methods, we implement the ESVIO system and evaluate the effectiveness and robustness of ESVIO on various public datasets. The experimental results show that ESVIO achieves good performance in both accuracy and robustness when compared with other state-of-the-art event-based VIO and stereo visual odometry (VO) systems, and, at the same time, with no compromise to real-time performance.

Quantum Interference-Controlled Conductance Enhancement in Stacked Graphene-like Dimers.

Stacking interactions are of significant importance in the fields of chemistry, biology, and material optoelectronics because they determine the efficiency of charge transfer between molecules and their quantum states. Previous studies have proven that when two monomers are π-stacked in series to form a dimer, the electrical conductance of the dimer is significantly lower than that of the monomer. Here, we present a strong opposite case that when two anthanthrene monomers are π-stacked to form a dimer in a scanning tunneling microscopic break junction, the conductance increases by as much as 25 in comparison with a monomer, which originates from a room-temperature quantum interference. Remarkably, both theory and experiment consistently reveal that this effect can be reversed by changing the connectivity of external electrodes to the monomer core. These results demonstrate that synthetic control of connectivity to molecular cores can be combined with stacking interactions between their π systems to modify and optimize charge transfer between molecules, opening up a wide variety of potential applications ranging from organic optoelectronics and photovoltaics to nanoelectronics and single-molecule electronics.

An engineered genetic circuit for lactose intolerance alleviation.

BACKGROUND: Lactose malabsorption occurs in around 68% of the world's population, causing lactose intolerance (LI) symptoms, such as abdominal pain, bloating, and diarrhea. To alleviate LI, previous studies have mainly focused on strengthening intestinal ß-galactosidase activity while neglecting the inconspicuous drop in the colon pH caused by the fermentation of non-hydrolyzed lactose by the gut microbes. A drop in colon pH will reduce the intestinal ß-galactosidase activity and influence intestinal homeostasis. RESULTS: Here, we synthesized a tri-stable-switch circuit equipped with high ß-galactosidase activity and pH rescue ability. This circuit can switch in functionality between the expression of ß-galactosidase and expression of L-lactate dehydrogenase in response to an intestinal lactose signal and intestinal pH signal, respectively. We confirmed that the circuit functionality was efficient in bacterial cultures at a range of pH levels, and in preventing a drop in pH and ß-galactosidase activity after lactose administration to mice. An impact of the circuit on gut microbiota composition was also indicated. CONCLUSIONS: Due to its ability to flexibly adapt to environmental variation, in particular to stabilize colon pH and maintain ß-galactosidase activity after lactose influx, the tri-stable-switch circuit can serve as a promising prototype for the relief of lactose intolerance.

Strain of Supramolecular Interactions in Single-Stacking Junctions.

Supramolecular electronics provide opportunities to integrate molecular building blocks into electronic circuits, and investigations of the mechanical properties of the non-covalent interactions are necessary to understand the role of the assembly configuration in the electronic coupling among different assembly blocks. However, the mechanical characterization of supramolecular interactions remains experimentally challenging. We investigated the strain distribution of the supramolecular interactions through a series of single-stacking junctions. The alpha values exhibit a clear odd-even effect versus the numbers of thiophene rings. The theoretical calculations demonstrated that a larger rotational barrier of the single-stacking junctions with an even number of thiophene rings leads to limited torsional freedom and thus a smaller strain distribution. These results provide new insights into the control of supramolecular interactions by the design of the basic molecular building blocks.

M2-Like TAMs Function Reversal Contributes to Breast Cancer Eradication by Combination Dual Immune Checkpoint Blockade and Photothermal Therapy.

Immune checkpoint inhibitor (ICI) therapy is considered to be a revolutionary anti-tumor strategy that may surpass other traditional therapies. Breast cancer is particularly suitable for it theoretically due to upregulation of programmed cell death 1 (PD-1) / programmed cell death ligand 1 (PD-L1) immune checkpoint pathway which exhausts the adaptive immune response mediated by T lymphocytes. However, its blockades exhibit very little effect in breast cancer, owing to the lack of T lymphocytes pre-infiltration and co-existing of intricate immune negative microenvironment including the macrophage-suppressed "Don't eat me" CD47 signal overexpression. Herein, a stimuli-responsive multifunctional nanoplatform (ZIF-PQ-PDA-AUN) is built. Its photothermal therapy can promote the infiltration of T lymphocytes in addition to ablating tumor cells and AUNP-12 and PQ912 further boost both the innate and adaptive immune reactions by cutting off PD-L1 and CD47 signals, respectively. In contrast to earlier single immunotherapy, the nanocomposites exhibit a stronger anti-tumor immune effect without obvious autoimmune side effects, promoting infiltration of T lymphocyte into the tumor site and strengthening phagocytosis of macrophages, even more exciting, significantly reversing pro-tumor M2-like tumor-associated macrophages (TAMs) to anti-tumor M1-like TAMs. The research may provide a promising strategy to develop high-efficient and low-toxic immunotherapy based on nanotechnology.

Metal-Polyphenol-Network Coated Prussian Blue Nanoparticles for Synergistic Ferroptosis and Apoptosis via Triggered GPX4 Inhibition and Concurrent In Situ Bleomycin Toxification.

Given that traditional anticancer therapies fail to significantly improve the prognoses of triple negative breast cancer (TNBC), new modalities with high efficiency are urgently needed. Herein, by mixing the metal-phenolic network formed by tannic acid (TA), bleomycin (BLM), and Fe3+ with glutathione peroxidase 4 (GPX4) inhibitor (ML210) loaded hollow mesoporous Prussian blue (HMPB) nanocubes, the HMPB/ML210@TA-BLM-Fe3+ (HMTBF) nanocomplex is prepared to favor the ferroptosis/apoptosis synergism in TNBC. During the intracellular degradation, Fe3+ /Fe2+ conversion mediated by TA can initiate the Fenton reaction to drastically upregulate the reactive oxygen species level in cells, subsequently induce the accumulation of lipid peroxidation, and thereby cause ferroptotic cell death; meanwhile, the released ML210 efficiently represses the activity of GPX4 to activate ferroptosis pathway. Besides, the chelation of Fe2+ with BLM leads to in situ BLM toxification at tumor site, then triggers an effective apoptosis to synergize with ferroptosis for tumor therapy. As a result, the superior in vivo antitumor efficacy of HMTBF is corroborated in a 4T1 tumor-bearing mice model regarding tumor growth suppression, indicating that the nanoformulations can serve as efficient ferroptosis and apoptosis inducers for use in combinatorial TNBC therapy.

Effect of statins on the risk of recurrent venous thromboembolism: A systematic review and meta-analysis.

BACKGROUND: Recent studies have suggested that statins may be associated with a lower risk of recurrent venous thromboembolism (VTE). METHODS: We systematically searched PubMed, Web of Science and Cochrane Library from inception until May 2020 to identify any eligible studies that reported the association between statin use and the risk of recurrent VTE, and conducted a comprehensive systematic review and meta-analysis (PROSPERO registration number: CRD42020190169) on this matter. RESULTS: A total of 14 observational studies were included for qualitative review and 12 of them qualified for meta-analyses. The main meta-analysis found that statin use was associated with a lower risk of disease recurrence among patients with VTE (pooled adjusted HR: 0.76, 95% CI: 0.69-0.83), which was robust in sensitivity analyses and free of significant publication bias. Additionally, such association was present when restricting to periods after anticoagulation withdrawal (pooled adjusted HR: 0.78, 95% CI: 0.70-0.88) and when separately analyzing recurrent deep vein thrombosis (pooled adjusted HR: 0.71, 95% CI: 0.62-0.81) and recurrent pulmonary embolism (pooled adjusted HR: 0.80, 95% CI: 0.66-0.97; P = 0.027). Furthermore, statin use in patients with VTE was also found to be associated with a lower risk of all-cause mortality (adjusted HR: 0.65, 95% CI: 0.56-0.77), and possibly an even lower risk of bleeding (adjusted HR: 0.88, 95% CI: 0.73-1.07), albeit not statistically significant. CONCLUSION: Statins have the potential to reduce recurrent events among patient with VTE. Randomized clinical trials to better explore the effect of statins in secondary prevention of VTE are warranted.

A self-amplified nanocatalytic system for achieving "1 + 1 + 1 > 3" chemodynamic therapy on triple negative breast cancer.

BACKGROUND: Chemodynamic therapy (CDT), employing Fenton or Fenton-like catalysts to convert hydrogen peroxide (H2O2) into toxic hydroxyl radicals (·OH) to kill cancer cells, holds great promise in tumor therapy due to its high selectivity. However, the therapeutic effect is significantly limited by insufficient intracellular H2O2 level in tumor cells. Fortunately, ß-Lapachone (Lapa) that can exert H2O2-supplementing functionality under the catalysis of nicotinamide adenine dinucleotide (phosphate) NAD(P)H: quinone oxidoreductase-1 (NQO1) enzyme offers a new idea to solve this problem. However, extensive DNA damage caused by high levels of reactive oxygen species can trigger the "hyperactivation" of poly(ADP-ribose) polymerase (PARP), which results in the severe interruption of H2O2 supply and further the reduced efficacy of CDT. Herein, we report a self-amplified nanocatalytic system (ZIF67/Ola/Lapa) to co-deliver the PARP inhibitor Olaparib (Ola) and NQO1-bioactivatable drug Lapa for sustainable H2O2 production and augmented CDT ("1 + 1 + 1 > 3"). RESULTS: The effective inhibition of PARP by Ola can synergize Lapa to enhance H2O2 formation due to the continuous NQO1 redox cycling. In turn, the high levels of H2O2 further react with Co2+ to produce the highly toxic ·OH by Fenton-like reaction, dramatically improving CDT. Both in vitro and in vivo studies demonstrate the excellent antitumor activity of ZIF67/Ola/Lapa in NQO1 overexpressed MDA-MB-231 tumor cells. Importantly, the nanocomposite presents minimal systemic toxicity in normal tissues due to the low NQO1 expression. CONCLUSIONS: This design of nanocatalytic system offers a new paradigm for combing PARP inhibitor, NQO1-bioactivatable drug and Fenton-reagents to obtain sustained H2O2 generation for tumor-specific self-amplified CDT.

Nonadditive Transport in Multi-Channel Single-Molecule Circuits.

As stated in the classic Kirchhoff's circuit laws, the total conductance of two parallel channels in an electronic circuit is the sum of the individual conductance. However, in molecular circuits, the quantum interference (QI) between the individual channels may lead to apparent invalidity of Kirchhoff's laws. Such an effect can be very significant in single-molecule circuits consisting of partially overlapped multiple transport channels. Herein, an investigation on how the molecular circuit conductance correlates to the individual channels is conducted in the presence of QI. It is found that the conductance of multi-channel circuit consisting of both constructive and destructive QI is significantly smaller than the addition of individual ones due to the interference between channels. In contrast, the circuit consisting of destructive QI channels exhibits an additive transport. These investigations provide a new cognition of transport mechanism and manipulation of transport in multi-channel molecular circuits.

Automatic classification of single-molecule charge transport data with an unsupervised machine-learning algorithm.

Single-molecule electrical characterization reveals the events occurring at the nanoscale, which provides guidelines for molecular materials and devices. However, data analysis to extract valuable information from the nanoscale measurement data remained as a major challenge. Herein, an unsupervised deep leaning method, a deep auto-encoder K-means (DAK) algorithm, is developed to distinguish different events from single-molecule charge transport measurements. As validated by three single-molecule junction systems, the method applies to the recognition for multiple compounds with various events and offers an effective data analysis method to track reaction kinetics at the single-molecule scale. This work opens the possibility of using deep unsupervised approaches to studying the physical and chemical processes at the single-molecule level.

Light-Driven Reversible Intermolecular Proton Transfer at Single-Molecule Junctions.

Photoresponsive molecular systems are essential for molecular optoelectronic devices, but most molecular building blocks are non-photoresponsive. Employed here is a photoinduced proton transfer (PIPT) strategy to control charge transport through single-molecule azulene junctions with visible light under ambient conditions, which leads to a reversible and controllable photoresponsive molecular device based on non-photoresponsive molecules and a photoacid. Also demonstrated is the application of PIPT in two single-molecule AND gate and OR gate devices with electrical signal as outputs.

Turning the Tap: Conformational Control of Quantum Interference to Modulate Single-Molecule Conductance.

Together with the more intuitive and commonly recognized conductance mechanisms of charge-hopping and tunneling, quantum-interference (QI) phenomena have been identified as important factors affecting charge transport through molecules. Consequently, establishing simple and flexible molecular-design strategies to understand, control, and exploit QI in molecular junctions poses an exciting challenge. Here we demonstrate that destructive quantum interference (DQI) in meta-substituted phenylene ethylene-type oligomers (m-OPE) can be tuned by changing the position and conformation of methoxy (OMe) substituents at the central phenylene ring. These substituents play the role of molecular-scale taps, which can be switched on or off to control the current flow through a molecule. Our experimental results conclusively verify recently postulated magic-ratio and orbital-product rules, and highlight a novel chemical design strategy for tuning and gating DQI features to create single-molecule devices with desirable electronic functions.

Switching of Charge Transport Pathways via Delocalization Changes in Single-Molecule Metallacycles Junctions.

To explore the charge transport through metalla-aromatics building blocks, three metallacycles complexes were synthesized, and their single-molecule conductances were characterized by using mechanically controllable break junction technique. It is found that the conductance of the metallacycles junction with phosphonium group is more than 1 order of magnitude higher than that without phosphonium group. X-ray diffraction and UV-vis absorption spectroscopy suggested that the attached phosphonium group makes metallacycles more delocalized, which shortened the preferred charge transport pathway and significantly enhanced the single-molecule conductance. This work revealed that the delocalization of metalla-aromatics could be used to switch the charge transport pathway of single-molecule junctions and thus tune the charge transport abilities significantly.

Radical-Enhanced Charge Transport in Single-Molecule Phenothiazine Electrical Junctions.

We studied the single-molecule conductance through an acid oxidant triggered phenothiazine (PTZ-) based radical junction using the mechanically controllable break junction technique. The electrical conductance of the radical state was enhanced by up to 200 times compared to the neutral state, with high stability lasting for at least two months and high junction formation probability at room-temperature. Theoretical studies revealed that the conductance increase is due to a significant decrease of the HOMO-LUMO gap and also the enhanced transmission close to the HOMO orbital when the radical forms. The large conductance enhancement induced by the formation of the stable PTZ radical molecule will lead to promising applications in single-molecule electronics and spintronics.