Relevant bibliographies by topics / Singola molecola

Academic literature on the topic 'Singola molecola'

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Published: 9 March 2023
Last updated: 10 March 2023

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Journal articles on the topic "Singola molecola"

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Marcucci, Guido, Drew Watson, Shweta Kapoor, Swaminathan Rajagopalan, Rajan Parashar, Aktar Alam, Diwyanshu Sahu, et al. "Superior therapy response predictions for patients with acute myeloid leukemia (AML) using Cellworks Singula: MyCare-009-01." Journal of Clinical Oncology 38, no. 15_suppl (May 20, 2020): e19502-e19502. http://dx.doi.org/10.1200/jco.2020.38.15_suppl.e19502.

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e19502 Background: Despite using cytogenetic and molecular-risk stratification and precision medicine, the current overall outcome of AML patients remains relatively poor. Therapy selection is often based on information considering only cytogenetics and single molecular aberrations and ignoring other patient-specific omics data that could potentially enable more effective treatments. The Cellworks Singula™ report predicts response for physician prescribed therapies (PPT) using the novel Cellworks Omics Biology Model (CBM) to simulate downstream molecular effects of cell signaling, drugs, and radiation on patient-specific in silico diseased cells. We test the hypothesis that Singula is a more accurate predictor of patient-specific therapy response than PPT. Methods: Singula’s ability to predict response was evaluated in an independent, randomly selected, retrospective cohort of 494 AML patients aged 2 to 85 years (median 54) treated with PPT. Patient omics data was available from PubMed. The accuracy of Singula was compared to that of PPT using McNemar’s test to account for the correlation between Singula and PPT. Multivariate logistic regression modeled complete response (CR) as a function of patient age, PPT, and Singula against any non-response (NR). Likelihood ratio tests were performed to further validate if Singula provides predictive information beyond PPT or patient age. Similar analyses were performed for overall survival (OS) using proportional hazards regression. Results: Singula was a better predictor for CR than PPT (McNemar’s χ2 = 72.0, p-value < 0.0001), with an overall accuracy of 88.5% (95% CI: 85.3%, 91.1%) compared to 70.2% (95% CI: 66.0%, 74.2%) for PPT. Singula exhibited a sensitivity and specificity of 97.1% and 68.0%, respectively. In multivariate regression analysis, Singula (p < 0.0001) remained an independent predictor for CR after adjusting for patient age (p = 0.0329) while PPT became not significant (p = 0.75). Singula was also an independent predictor for OS (p < 0.0001) after adjusting for patient age (p = 0.0018) and PPT (p = 0.0011). For all 100 true negatives, Singula generated alternative standard of care therapy selections with predicted clinical response. Conclusions: Singula is a superior independent predictor for CR and OS compared to PPT in AML patients. The Singula report can also validate therapy selection, correctly identify non-responders to PPT and further provide alternative therapy selections.
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Stein, Anthony Selwyn, Drew Watson, Shweta Kapoor, Kunal Ghosh Ghosh Roy, Aftab Alam, Diwyanshu Sahu, Kabya Basu, et al. "Superior therapy response predictions for patients with myelodysplastic syndrome (MDS) using Cellworks Singula: MyCare-009-02." Journal of Clinical Oncology 38, no. 15_suppl (May 20, 2020): e19528-e19528. http://dx.doi.org/10.1200/jco.2020.38.15_suppl.e19528.

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e19528 Background: Despite using cytogenetic and molecular-risk stratification and precision medicine, the current overall outcome of MDS patients remains relatively poor. Therapy selection is often based on information considering only cytogenetics and single molecular aberrations and ignoring other patient-specific omics data that could potentially enable more effective treatments. The Cellworks Singula™ report predicts response for physician prescribed therapies (PPT) using the novel Cellworks Omics Biology Model (CBM) to simulate downstream molecular effects of cell signaling, drugs, and radiation on patient-specific in silico diseased cells. We test the hypothesis that Singula is a more accurate predictor of patient-specific therapy response than PPT. Methods: Singula’s ability to predict response was evaluated in an independent, randomly selected, retrospective cohort of 146 MDS patients aged 28 to 89 years (median 69) treated with PPT. Patient omics data was available from PubMed and TCGA. The accuracy of Singula was compared to that of PPT using McNemar’s test to account for the correlation between Singula and PPT. Multivariate logistic regression modeled complete response (CR) as a function of patient age, PPT, and Singula against any non-response (NR). Likelihood ratio tests were performed to further validate if Singula provides predictive information beyond PPT or patient age. Similar analyses were performed for overall survival (OS) using proportional hazards regression. Results: Singula was a better predictor for CR than PPT (McNemar’s χ2 = 42.0, p-value < 0.0001), with an overall accuracy of 73.3% (Exact 95% CI: 65.3%, 80.2%) compared to 37.7% (95% CI: 30.0%, 46.1%) for PPT. Singula exhibited a sensitivity and specificity of 90.9% (95% CI: 80.0%, 97.0%) and 62.6% (95% CI: 51.8%, 72.6%), respectively. In multivariate regression analysis, Singula (p < 0.0001) remained an independent predictor for CR after adjusting for patient age (p = 0.0759) and PPT (p = 0.0496). Singula provided alternative therapy selections for 17 of 53 true negative detected by Cellworks. Conclusions: Singula is a superior independent predictor for CR compared to PPT in MDS patients. The Singula report can also validate therapy selection, correctly identify non-responders to PPT and further provide alternative therapy selections.
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Wen, Patrick Y., Drew Watson, Shweta Kapoor, Aftab Alam, Aktar Alam, Deepak Anil Lala, Diwyanshu Sahu, et al. "Superior therapy response predictions for patients with glioblastoma (GBM) using Cellworks Singula: MyCare-009-03." Journal of Clinical Oncology 38, no. 15_suppl (May 20, 2020): 2519. http://dx.doi.org/10.1200/jco.2020.38.15_suppl.2519.

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2519 Background: Despite using cytogenetic and molecular-risk stratification and precision medicine, the current overall outcome of GBM patients remains relatively poor. Therapy selection is often based on information considering only a single aberration and ignoring other patient-specific omics data which could potentially enable more effective treatment selection. The Cellworks Singula™ report predicts response for physician prescribed therapies (PPT) using the novel Cellworks Omics Biology Model (CBM) to simulate downstream molecular effects of cell signaling, drugs, and radiation on patient-specific in silico diseased cells. We test the hypothesis that Singula is a superior predictor of progression-free survival (PFS) and overall survival (OS) compared to PPT. Methods: Singula’s ability to predict response was evaluated in an independent, randomly selected, retrospective cohort of 109 GBM patients aged 17 to 83 years treated with PPT. Patient omics data was available from TCGA. Singula uses PubMed to generate protein interaction network activated and inactivated disease pathways. We simulated PPT for each patient and calculated the quantitative drug effect on a composite GBM disease inhibition score based on specific phenotypes while blinded to clinical response. Univariate and multivariate proportional hazards (PH) regression analyses were performed to determine if Singula provides predictive information for PFS and OS, respectively, above and beyond age and PPT. Results: In univariate analyses, Singula was a significant predictor of both PFS (HR = 4.130, p < 0.000) and OS (HR = 2.418, p < 0.0001). In multivariate PH regression analyses, Singula (HR = 4.033, p < 0.0001) remained an independent predictor of PFS after adjustment for PPT (p = 0.1453) and patient age (p = 0.4273). Singula (HR = 1.852, p = 0.0070) was also a significant independent predictor of OS after adjustment for PPT (p = 0.4127) and patient age (p = 0.0003). Results indicate that Singula is a superior predictor of both PFS and OS compared to PPT. Singula provided alternative therapy selections for 29 of 52 disease progressors detected by Cellworks. Conclusions: Singula is a superior predictor of PFS and OS in GBM patients compared to PPT. Singula can identify non-responders to PPT and provide alternative therapy selections.
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Ahluwalia, Manmeet Singh, Drew Watson, Shweta Kapoor, Rajan Parashar, Kunal Ghosh Ghosh Roy, Aftab Alam, Swaminathan Rajagopalan, et al. "Superior therapy response predictions for patients with low-grade glioma (LGG) using Cellworks Singula: MyCare-009-04." Journal of Clinical Oncology 38, no. 15_suppl (May 20, 2020): 2569. http://dx.doi.org/10.1200/jco.2020.38.15_suppl.2569.

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2569 Background: Despite using cytogenetic and molecular-risk stratification and precision medicine, the current overall outcome of LGG patients remains relatively poor. Therapy selection is often based on information considering only a single aberration and ignoring other patient-specific omics data which could potentially enable more effective treatments. The Cellworks Singula report predicts response for physician prescribed therapies (PPT) using the novel Cellworks Omics Biology Model (CBM) to simulate downstream molecular effects of cell signaling, drugs, and radiation on patient-specific in silico diseased cells. We test the hypothesis that Singula is a superior predictor of progression-free survival (PFS) and overall survival (OS) compared to PPT. Methods: Singula’s ability to predict response was evaluated in an independent, randomly selected, retrospective cohort of 137 LGG patients aged 14 to 73 years treated with PPT. Patient omics data was available from TCGA. Singula uses PubMed to generate protein interaction network activated and inactivated disease pathways. We simulated the PPT for each patient and calculated the quantitative drug effect on a composite LGG disease inhibition score based on specific phenotypes while blinded to clinical response. Univariate and multivariate proportional hazards (PH) regression analyses were performed to determine if Singula provides predictive information for PFS and OS, respectively, above and beyond age and PPT. Results: In univariate analyses, Singula was a significant predictor of both PFS (HR = 3.587, p < 0.0001) and OS (HR = 3.044, p = 0.0007). In multivariate PH regression analyses, Singula (HR = 3.707, p < 0.0001) remained an independent predictor of PFS after adjustment for PPT (p = 0.3821) and patient age (p = 0.0020). Singula (HR = 2.970, p = 0.0013) was also a significant independent predictor of OS after adjustment for PPT (p = 0.0540) and patient age (p < 0.0001). Results indicate that Singula is a superior predictor of both PFS and OS compared to PPT. Singula provided alternative standard of care therapy selections for all 34 disease progressors. Conclusions: Singula is a superior predictor of PFS and OS in LGG patients compared to PPT. Singula can correctly identify non-responders to PPT and provide alternative therapy selections.
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Marcucci, Guido, Drew Watson, Prashant Ramachandran Nair, Kabya Basu, Yashaswini S. Ullal, Adity Ghosh, Yugandhara Narvekar, et al. "Assessment of Cellworks Omics Biosimulation Therapy Response Predictions for Patients with Acute Myeloid Leukemia (AML) Using Cellworks Singula™: Mycare-020-01." Blood 136, Supplement 1 (November 5, 2020): 35. http://dx.doi.org/10.1182/blood-2020-142184.

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Background. In addition to clinical considerations (e.g., age, de novo vs secondary disease, comorbidities), therapy selection for AML patients is often based on information considering only cytogenetics and/or molecular aberrations and ignoring other patient-specific omics information that could potentially enable selection of more effective treatments. In turn, despite using cytogenetic and molecular-risk stratification, the current overall outcome of AML patients remains relatively poor. The Cellworks Singula™ report predicts clinical response to physician-prescribed treatments using the novel Cellworks Omics Biology Model (CBM) that simulate in silico downstream molecular effects on cell signaling and survival of drug treatments in patient-specific diseased cells. Methods. The performance of Singula™ was evaluated in a cohort of 474 AML patients aged 2 to 85. The pre-defined Singula™ Classifier utilizes individual patients' next-generation sequencing (NGS) profiles to provide a dichotomous prediction of response or non-response to the physician prescribed treatments. The clinical outcome data for these subjects, i.e., complete response (CR) and overall survival (OS), were obtained from the TCGA and other 144 PubMed publications, each including also information on patients' cytogenetics, targeted gene mutations, and/or whole exome sequencing. Blinded to clinical outcomes, Cellworks utilized the cytogenetic and molecular data to generate a Singula™ predicted response (i.e., CR vs non-response) classification for each patient. Statistical analyses, including assessments of accuracy, sensitivity, specificity, and negative (NPV) and positive predictive (PPV) values were performed to compare the Singula™ predicted clinical response to the actual observed clinical response. Kaplan-Meier curves, associated log rank tests and median OS are provided for patients stratified by Singula™ predicted response. Multivariate Cox proportional hazards regression was used to further test the hypothesis that Singula™ is an independent predictor for OS once adjusted for patient age and actual prescribed treatment. Results. Data are summarized in Table 1. The Singula™ classifier had 92.3% (90.6%, 95.3%) accuracy in predicting correctly observed patient complete response to the prescribed treatment. with 97.3% (95.0%, 98.8%) sensitivity. Singula™ had 83.3% (76.1%, 89.1%) specificity for the non-responder patients (n=138; 29.1%). For each of the non-responders, Singula™ provided an alternative treatment therapy predicted to produce clinical response. Assuming at least 2% of the non-responders would have responded to the alternative Singula™ prescribed treatment, Singula™ improves CR rates compared to the original physician prescribed treatment (McNemar's p-value &lt; 0.05). Figure 1 provides the Kaplan-Meier curves of Singula-predicted responders vs non-responders for a subset of 292 subjects that had OS data available. In multivariate Cox proportional hazards models, the Singula Classifier remained a significant predictor of overall survival (HR = 2.171, p-value &lt; 0.0001) once adjusted for patient age and physician prescribed treatment. Conclusions. Cellworks Singula™ has high accuracy and sensitivity in predicting CR for AML patient. Singula also has high specificity in identifying patients who are unlikely to respond physician and may prescribed potentially effective therapies. The Singula™ predicted responders have a significantly longer OS than the predicted non responders. Thus, Cellworks Singula™ can accurately predict AML response, be used to validate or reject a physician's therapy selection decision and, eventually, provide alternative treatment recommendations. Disclosures Marcucci: Novartis: Speakers Bureau; Abbvie: Speakers Bureau; Iaso Bio: Membership on an entity's Board of Directors or advisory committees; Takeda: Other: Research Support (Investigation Initiated Clinical Trial); Pfizer: Other: Research Support (Investigation Initiated Clinical Trial); Merck: Other: Research Support (Investigation Initiated Clinical Trial). Watson:Mercy Bioanalytics, Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees; SEER Biosciences, Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees; BioAI Health Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees; Cellmax Life Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees; Cellworks Group Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees. Nair:Cellworks Research India Private Limited: Current Employment. Basu:Cellworks Research India Private Limited: Current Employment. Ullal:Cellworks Research India Private Limited: Current Employment. Ghosh:Cellworks Research India Private Limited: Current Employment. Narvekar:Cellworks Research India Private Limited: Current Employment. Grover:Cellworks Research India Private Limited: Current Employment. Sahu:Cellworks Research India Private Limited: Current Employment. Amara:Cellworks Research India Private Limited: Current Employment. Pampana:Cellworks Research India Private Limited: Current Employment. Roy:Cellworks Research India Private Limited: Current Employment. Rajagopalan:Cellworks Research India Private Limited: Current Employment. Alam:Cellworks Research India Private Limited: Current Employment. Parashar:Cellworks Research India Private Limited: Current Employment. Mundkur:Cellworks Group Inc.: Current Employment. Christie:Cellworks Group Inc.: Current Employment. Macpherson:Cellworks Group Inc.: Current Employment. Kapoor:Cellworks Research India Private Limited: Current Employment. Stein:Stemline: Consultancy, Speakers Bureau; Amgen: Consultancy, Speakers Bureau.
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Stein, Anthony S., Drew Watson, Prashant Ramachandran Nair, Kabya Basu, Yashaswini S. Ullal, Adity Ghosh, Yugandhara Narvekar, et al. "Superior Therapy Response Predictions for Patients with Myelodysplastic Syndrome (MDS) Using Cellworks Singula™: Mycare-020-02." Blood 136, Supplement 1 (November 5, 2020): 9–10. http://dx.doi.org/10.1182/blood-2020-142214.

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Background: Therapy selection for MDS patients is often based on information considering only cytogenetics and single molecular aberrations and ignoring other patient-specific omics data that could potentially enable more effective treatments. In turn, despite using cytogenetic and molecular-risk stratification and precision medicine, the current overall outcome of MDS patients remains relatively poor. The Cellworks Singula™ report predicts response for physician prescribed treatments using the novel Cellworks Omics Biology Model (CBM) to simulate downstream molecular effects of cell signaling, drugs, and radiation on patient-specific in silico diseased cells. Methods: The performance of Singula™ was evaluated in an independent, randomly selected, retrospective cohort of 144 MDS patients aged 28 to 89 years (median 69). The pre-defined Singula™ Classifier utilizes an individual's genomics profile to provide a dichotomous prediction of response or non-responses to a given physician prescribed treatment (PPT). Outcome data for these subjects, including measurement of complete response (CR), were obtained from 42 PubMed publications, each including patient genomics data of either karyotyping, targeted gene panels, and/or whole exome sequencing. Blinded to clinical outcomes, Cellworks utilized these data to generate a Singula™ classifier of responder vs non-responder in this MDS cohort. Statistical analyses, including assessments of accuracy, sensitivity, specificity, negative (NPV) and positive predictive (PPV) values were performed on the merged data to compare the Singula™ predicted response with the actual observed CR. Multivariate logistic regression models of complete response were performed incorporating covariates for patient age, PPT, and the Singula™ Classifier. Results: Table 1 reveals that the pre-defined Singula™ classifier had 90.3% (Exact 95% CI: 84.2%, 94.6%) accuracy in predicting observed patient response from the physician prescribed treatment. In this study, Singula™ was able to accurately identify responders with 90.0% (81.2%, 95.6%) sensitivity. Importantly, Singula™ had 90.6% (80.7%, 96.5%) specificity for the subset of 64 patients (44.4%) that had a non-response. For 32% (17/54) of the non-responders patients, Singula™ provided an alternative Standard of Care treatment therapy, as shown in Table 2. The remaining 37 patients were predicted to be non-responders to all remaining Standard of Care options, so did not have alternate treatment predictions. Assuming at least 4% of these non-responding patients would have responded to the alternative Singula™ prescribed therapy, then these data support that Singula™ improves prediction of CR compared to the original PPT (McNemar's p-value &lt; 0.05). In multivariate logistic regression models of CR that included patient age and prescribed drug therapy, the Singula™ Classifier remained an independent, significant predictor of CR (OR &gt; 100, p-value &lt; 0.0001), while both patient age (p = 0.372) and drug therapy (p = 0.720) fell off the model. Conclusions: Cellworks Singula™ has high accuracy and sensitivity in predicting CR for MDS patient response to physician prescribed therapies. Singula™ also has high specificity in identifying patients who are unlikely to respond to physician prescribed therapies and provides alternative treatment recommendations for these patients. The Singula™ Classifier is an independent and superior predictor of CR compared with other clinical (age) or therapeutic (PPT) factors. Figure Disclosures Stein: Amgen: Consultancy, Speakers Bureau; Stemline: Consultancy, Speakers Bureau. Watson:BioAI Health Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees; Mercy Bioanalytics, Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees; SEER Biosciences, Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees; Cellworks Group Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees; Cellmax Life Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees. Nair:Cellworks Research India Private Limited: Current Employment. Basu:Cellworks Research India Private Limited: Current Employment. Ullal:Cellworks Research India Private Limited: Current Employment. Ghosh:Cellworks Research India Private Limited: Current Employment. Narvekar:Cellworks Research India Private Limited: Current Employment. Grover:Cellworks Research India Private Limited: Current Employment. Sahu:Cellworks Research India Private Limited: Current Employment. Prakash:Cellworks Research India Private Limited: Current Employment. Behura:Cellworks Research India Private Limited: Current Employment. Balakrishnan:Cellworks Research India Private Limited: Current Employment. Roy:Cellworks Research India Private Limited: Current Employment. Rajagopalan:Cellworks Research India Private Limited: Current Employment. Alam:Cellworks Research India Private Limited: Current Employment. Parashar:Cellworks Research India Private Limited: Current Employment. Mundkur:Cellworks Group Inc.: Current Employment. Christie:Cellworks Group Inc.: Current Employment. Macpherson:Cellworks Group Inc.: Current Employment. Kapoor:Cellworks Research India Private Limited: Current Employment. Marcucci:Abbvie: Speakers Bureau; Novartis: Speakers Bureau; Pfizer: Other: Research Support (Investigation Initiated Clinical Trial); Merck: Other: Research Support (Investigation Initiated Clinical Trial); Takeda: Other: Research Support (Investigation Initiated Clinical Trial); Iaso Bio: Membership on an entity's Board of Directors or advisory committees.
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Velcheti, Vamsidhar, Michael Castro, Drew Watson, Shweta Kapoor, Anuj Tyagi, Mohammed Sauban, Aftab Alam, et al. "Superior overall survival (OS), progression-free survival (PFS), and clinical response (CR) predictions for patients with non-small cell lung cancer (NSCLC) using Cellworks Singula: myCare-022-05." Journal of Clinical Oncology 39, no. 15_suppl (May 20, 2021): 9117. http://dx.doi.org/10.1200/jco.2021.39.15_suppl.9117.

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9117 Background: The Cellworks Singula Therapeutic Response Index (TRI) has been developed to assist clinicians and NSCLC patients in choosing between competing therapeutic options. In contrast to approaches that consider single aberrations, which often yield limited benefit, Cellworks utilizes an individual patient’s next generation sequencing results and a mechanistic multi-omics biology model, the Cellworks Omics Biology Model (CBM), to biosimulate downstream molecular effects of cell signaling, drugs, and radiation on patient-specific in silico diseased cells. For any individual patient and alternative therapy, Cellworks integrates this biologically modeled multi-omics information into a continuous Singula TRI Score, scaled from 0 (low therapeutic benefit) to 100 (high therapeutic benefit). We demonstrate that Singula is strongly associated with overall survival, progression-free survival and relative therapeutic benefit beyond standard clinical factors, including patient age, gender, and physician prescribed treatments (PPT). Methods: In this study, Singula’s ability to predict response was evaluated in a retrospective cohort of 446 NSCLC patients with OS, PFS, and CR data from The Cancer Genome Atlas (TCGA) project, treated with PPT. As a primary analysis of the CBM and TRI Score, Cox Proportional Hazards (PH) regression and likelihood ratio (LR) tests were used to assess the hypothesis that Singula is predictive of OS, PFS, and CR above and beyond standard clinical factors. A p-value < 0.05 for the corresponding likelihood ratio statistic was required to be considered significant. Results: Multivariate analyses were performed to assess the performance of the Singula Therapy Response Index above and beyond physician’s choice of treatment. The same Singula TRI algorithm and clinical cutoffs were used for all clinical outcome measures. For OS the median survival times for the high and low benefit groups were 60.16 and 28.57 months respectively, based on the median Singula value. Also, the hazard ratio per 25 Singula units for OS was 0.5103 (95% CI: 0.3337 - 0.7804) and the odds ratio for CR was 1.6161. These and further analyses, shown in Table, suggest that Singula TRI provides predictive value of OS, PFS, and CR above and beyond standard clinical factors. Conclusions: The Singula TRI Score provides a continuous measure for alternative NSCLC therapeutic options. In this retrospective cohort, Singula was strongly predictive of OS, PFS, and CR and provided predictive value of OS beyond PPT, patient age and gender. These results will be further validated in prospective clinical studies.[Table: see text]
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Wen, Patrick Y., Michael Castro, Drew Watson, Shweta Kapoor, Ashish Agrawal, Aftab Alam, Kunal Ghosh Roy, et al. "Superior overall survival (OS) and disease-free survival (DFS) predictions for patients with glioblastoma multiforme (GBM) using Cellworks Singula: myCare-022-03." Journal of Clinical Oncology 39, no. 15_suppl (May 20, 2021): 2017. http://dx.doi.org/10.1200/jco.2021.39.15_suppl.2017.

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2017 Background: The Cellworks Singula Therapeutic Response Index (TRI) has been developed to assist clinicians and GBM patients in choosing between competing therapeutic options. In contrast to approaches that consider single aberrations, which often yield limited benefit, Cellworks utilizes an individual patient’s next generation sequencing results and a mechanistic multi-omics biology model, the Cellworks Omics Biology Model (CBM), to biosimulate downstream molecular effects of cell signaling, drugs, and radiation on patient-specific in silico diseased cells. For any individual patient and alternative therapy, Cellworks integrates this biologically modeled multi-omics information into a continuous Singula TRI Score, scaled from 0 (low therapeutic benefit) to 100 (high therapeutic benefit). We demonstrate that Singula is strongly associated with OS and DFS beyond standard clinical factors, including patient age, patient gender, and physician prescribed treatments (PPT). Methods: In this study, Singula’s ability to predict response was evaluated in a retrospective cohort of 100 GBM patients with OS and DFS data from The Cancer Genome Atlas (TCGA) project, treated with PPT. As a primary analysis of the CBM and TRI Score, Cox Proportional Hazards (PH) regression and likelihood ratio (LR) tests were used to assess the hypothesis that Singula is predictive of OS and DFS above and beyond patient age, patient gender, and PPT. A p-value < 0.05 for the corresponding likelihood ratio statistic was required to be considered significant. Results: Multivariate analyses were performed to assess the performance of the Singula Therapy Response Index after adjusting for the contribution of standard clinical factors. The same Singula TRI algorithm and clinical cutoffs were used for all clinical outcome measures. These analyses, shown in the table, suggests that the proposed Singula TRI provides predictive value of OS and DFS above and beyond patient age, patient gender, and PPT. Conclusions: The Singula TRI Score provides a continuous measure scaled from 0 (low benefit) to 100 (high benefit) for alternative GBM therapeutic options. In this retrospective cohort, Singula was strongly predictive of OS and DFS and provided predictive value beyond PPT, patient age and gender. These results will be further validated in larger scale, prospectively designed clinical studies.[Table: see text]
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Su Yuting, 苏玉婷, and 盖宏伟 Gai Hongwei. "单分子计数免疫分析." Laser & Optoelectronics Progress 59, no. 6 (2022): 0617011. http://dx.doi.org/10.3788/lop202259.0617011.

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Yanagida, Toshio. "S2h1-2 Single molecule study for elucidating the mechanism involved in utilizing fluctuations by biosystems(S2-h1: "Single Molecule Analysis of Molecular Motor",Symposia,Abstract,Meeting Program of EABS & BSJ 2006)." Seibutsu Butsuri 46, supplement2 (2006): S127. http://dx.doi.org/10.2142/biophys.46.s127_1.

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Dissertations / Theses on the topic "Singola molecola"

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CHOUDHARY, DHAWAL. "Studio a livello di singola molecola del folding, misfolding e aggregazione di proteine e dell’attività chaperonica della HSPB8." Doctoral thesis, Università degli studi di Modena e Reggio Emilia, 2020. http://hdl.handle.net/11380/1199862.

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Negli ultimi decenni le pinze ottiche si sono rivelate una tecnica sperimentale estremamente efficace per eseguire studi di spettroscopia di forza a livello di singola molecola. In particolare, un’applicazione delle pinze ottiche che sta avendo una rilevanza biomedica sempre più importante è quella relativa allo studio dei processi di ripiegamento corretto (folding), non corretto (misfolding) e dell’aggregazione di proteine. Di forte rilevanza biomedica è anche la possibilità offerta dalle pinze ottiche di caratterizzare in grande dettaglio i meccanismi molecolari che mediano le interazioni tra due o più biomolecole, come ad esempio tra uno chaperone molecolare e il suo substrato. La rilevanza medica di questi studi deriva dal fatto che l'errato ripiegamento e l'aggregazione delle proteine sono processi deleteri, spesso associati a neurodegenerazione. Gli chaperoni molecolari si sono evoluti come strumento molecolare per combattere sia il misfolding che l’aggregazione proteica. Un funzionamento non corretto degli chaperoni molecolari spesso causa perdita di proteostasi e l’insorgenza di varie patologie umane. Il lavoro descritto in questa tesi spiega in maniera dettagliata l’approccio sperimentale utilizzato per utilizzare le pinze ottiche per lo studio del folding, misfolding e aggregazione di proteine. In particolare in questa tesi vengono descritti: i) i risultati di esperimenti mirati alla elucidazione del processo di ripiegamento corretto e non del sensore al calcio NCS-1 (Neuronal Calcium Sensor 1; ii) l'approccio sperimentale adottato per descrivere la dinamica strutturale e funzionale di vari chaperoni molecolari utilizzando le pinze ottiche e la microscopia a forza atomica; iii) recenti sviluppi tecnici che hanno ampliato le possibili applicazioni delle pinze ottiche in campo biologico; iv) i risultati di esperimenti mirati a far luce sui meccanismi molecolari che mediano l’attività chaperonica dello chaperone molecolare HSPB8. In quest’ultimi esperimenti abbiamo manipolato meccanicamente monomeri e tetrameri della Maltose Binding Protein (MBP) e analizzato i loro processi di folding, misfolding e aggregazione in presenza e assenza del HSPB8 wild-type e del suo mutante HSPB8-K141E. I nostri risultati dimostrano una forte attività antiaggregante (holdase activity) della HSPB8 che riduce significativamente l'aggregazione delle molecole di MBP e un’attività antiaggregante molto ridotta del mutante HSPB8-K141E. Inoltre, i nostri studi rivelano una inaspettata attività pro-folding (foldase activity) sia della forma mutata che di quella wild-type della HSPB8. Questi dati sperimentali evidenziano nuovi meccanismi di interazione tra HSPB8 e i suoi substrati e suggeriscono un ruolo fisiologico più complesso per questo chaperone molecolare di quanto precedentemente ipotizzato.
Optical tweezers have evolved as an exemplary Single Molecule Force Spectroscopy (SMFS) technique over the past three decades. A distinct and bio medically relevant application of Optical Tweezers is their ability to observe directly at single molecule level the folding, misfolding and aggregation of protein molecules. Additionally the dynamic approach of Optical Tweezer setup also allows for the isolated study of interactions between two or more biomolecules, such as chaperone-protein interactions, in real time. The medical relevance of such studies stems from the fact that misfolding and aggregation of proteins are deleterious processes and have been linked to many neurodegenerative disorders. While molecular chaperones have evolved as an evolutionarily conserved sword and shield mechanism against such deleterious processes, wherein their holdase action acts as a shield preventing further aggregation of misfolded protein species and their foldase action acts as a sword and actively assists misfolded structure to regains their natively folded state. The dysfunction of this chaperone activity is also cytotoxic and can lead to loss of proteostasis. The present thesis dwells deeper in this specific application of Optical tweezer. The thesis will elaborate upon how optical tweezers can extract the mechanistic details of the folding and misfolding of protein molecules by reviewing the experiments performed on NCS-1 (Neuronal Calcium Sensor 1). It will also discuss the experimental approach taken by SMFS techniques like Optical Tweezers and AFM (Atomic Force Microscopy) to study the structural and functional dynamics of molecular chaperones. Furthermore, the thesis will explore the recent developments in Optical Tweezers and their biological applications. Finally, I describe the results of experiments we have carried out on the maltose binding protein to elucidate the mechanism of action of the chaperone HSPB8. We have mechanically denatured homotetramers of MBP as well as single MBP molecules and analyzed their folding and aggregation processes in the presence and absence of wild-type HSPB8 and its mutant form HSPB8-K141E/N. Our results reveal a strong holdase activity of wild type HSPB8, which either prevents completely the aggregation of denatured MBP molecules or allows the substrate to form only small and mechanically weak aggregates while this holdase activity is significantly suppressed in the mutant. Moreover, and importantly, a careful analysis of the data also discloses an unexpected foldase activity of both wild type and mutated forms of HSPB8, which guides the folding process of denatured MBP molecules into their native states. Our findings highlight new mechanisms of interaction between HSPB8 and its substrates and suggest a more complex physiological role for this chaperone than previously assumed.
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BUGLIONE, ENRICO. "Nanomeccanica per la Ricerca sul Cancro." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2021. http://hdl.handle.net/10281/304787.

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Nonostante gli enormi passi avanti sulla comprensione dei meccanismi d’azione del cancro e nello sviluppo di farmaci antitumorali, la maggior parte delle forme di cancro è ancora incurabile. La ragione di tale insuccesso è radicata nella complessità di questa malattia, che è ancora poco conosciuta sia in fase di insorgenza, dovuta alla misregolazione di oncogeni, sia in fase di metastatizzazione delle cellule cancerose. Lo studio di tali caratteristiche da un punto di vista meccanico può fornire una visione differente dei meccanismi di azione del cancro ed aiutare a contestualizzarli all’interno di processi estremamente complessi. L’insorgenza del cancro è dovuta ad una mancata regolazione del ciclo cellulare, che a sua volta dipende spesso da un’alterata espressione dei cosiddetti oncogeni. Ne è un esempio il proto-oncogene c-KIT, che codifica per un fattore di crescita delle cellule staminali. La regolazione della sua espressione è controllata dal suo promotore prossimale, la cui struttura è caratterizzata dalla presenza di 3 superstrutture tridimensionali complesse che si formano su uno dei due filamenti della sua sequenza, chiamate G-quadruplexes. Tali strutture sembrerebbero avere un ruolo nel riconoscimento del promotore da parte della polimerasi e nell’assemblaggio della macchina trascrizionale, ma la loro funzione non è ancora chiara. Lo studio della nanomeccanica di tali strutture a livello di singola molecola (grazie al Magnetic Tweezers) può fornire importanti informazioni sul loro ruolo e sulle modalità con cui regolano l’espressione dell’oncogene. In seguito all’insorgenza del cancro, le cellule coinvolte subiscono forti cambiamenti strutturali: iniziano a dividersi velocemente e a migrare incontrollatamente. Entrambi questi processi richiedono un grande cambiamento nella struttura cellulare ed in particolare nella rigidità della cellula. La leucemia linfoide cronica (CLL) rappresenta un caso esemplare di tali capacità migratorie, non solo nell cellule cancerose, ma anche in quelle sane. Anche in questo caso, la nanomeccanica offre numerosi strumenti che permettono di studiare tali modifiche a livello di singola cellula, in particolare il microscopio a forza atomica (AFM) e il citofluorimetro a pressione deformante (RT-DC) offrono la possibilità di studiare le dinamiche cellulari in differenti condizioni e di osservare gli effetti dei farmaci di prima linea direttamente sulle cellule di pazienti malati.
With the term cancer are intended many species of diseases having quite different properties from each other. Despite such vast differences, the mechanisms beyond the onset of any kind of cancer are very similar and can be classified in two main groups depending on their stage. The first is related to the dysregulation of particular genes (oncogenes), that results in an impairment of the cell cycle. The second concerns the ability of cancer cells to continuously divide and migrate through tissues, that results in a highly invasive potential. From a mechanical point of view, the investigation of such features can be crucial for a deeper understanding of cancer onset and progression as well as for the study of novel pharmacological treatments. The outbreak of cancer is caused by a deficiency in the regulation of the cell cycle which, in turn, often depends on an abnormal expression of oncogenes. It is the case of the proto-oncogene c-KIT, that encodes for a mast/stem cell growth factor receptor. Its regulation relies mainly on its promoter, which is constituted by 3 distinct three-dimensional DNA structures called G-quadruplexes (G4s). Those structures can be studied by means of nanomechanical tools such as Magnetic Tweezers, which can recognize folded G4s at single-molecule level, thus enabling to study their role in the regulation of the oncogene. After the onset of cancer, a generic cell undergoes mechanical changes: it divides quickly, and it starts migrating. Both phenomena require a modification in the cell structural phenotype, eventually modifying its rigidity. Chronic lymphocytic leukemia is a case in point: malignant B lymphocytes continuously traffic between peripheral blood and lymphoid tissues. Such frequent migrations require a change in the rigidity of cells. In this case, Atomic Force Microscopy can provide a nanomechanical approach allowing to measure the stiffness of single cells from patients with leukemia, which is slightly decreased if compared to rigidity of cells from healthy donors. This feature can also allow to observe the effect of targeted therapies on the cells, evaluating their effect from a mechanical point of view.
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CORTI, ROBERTA. "Single molecule force spectroscopy of proteins and DNA." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2020. http://hdl.handle.net/10281/273770.

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Negli ultimi decenni, lo sviluppo di nuove tecniche di singola molecola ha creato le basi per nuovi paradigmi nel campo della biofisica. In particolare, la nanomanipolazione di singole biomacromolecole ha permesso la caratterizzazione meccanica di proteine e DNA, cercando di evidenziare la relazione fondamentale tra struttura e funzione biologica. Nel corso degli anni sono stati sviluppati diversi metodi di nanomanipolazione: tra questi, il Microscopio a Forza Atomica (AFM), il Magnetic Tweezers (MT) e il Flow-Stretching (F-S) accoppiato a fluorescenza. Queste tre tecniche sono state utilizzate per la caratterizzazione di singole biomacromolecole con tecniche di spettroscopia di forza a livello di singola molecola (SMFS) in quattro diversi progetti. In questa Tesi mi sono occupata principalmente di caratterizzare strutturalmente diverse proteine e correlarne la conformazione alla funzione biologica. In questa ottica, sono state studiate le diverse conformazioni strutturali di una proteina intrinsecamente disordinata (IDP) coinvolta nella malattia del Parkison’s (PD), chiamata alfa-synucleina (AS) e il riarrangiamento strutturale di una proteina coinvolta nel mantenimento strutturale cromosomico, la condensina, durante la condensazione di singoli filamenti di DNA. Inoltre, è stata studiata la struttura di un DNA-analogo sia caratterizzandone la stabilità termica sia attraverso studi di nanomeccanica in SMFS. Infine, è stata descritta una implementazione tecnica di un apparato di F-S accoppiato con illuminazione TIRF, per ottenere una rapida sostituzione di soluzioni durante esperimenti di microfluidica, ottenendo un setup particolarmente indicato per studi di interazione tra DNA e proteine. Durante lo studio della proteina AS in SMFS, il problema della mancanza di una struttura secondaria ben definita è stato risolto con l’impego di una singola poliproteina, contenente un modulo di AS umana. Sono state caratterizzati tre diversi stati conformazionali per AS, da uno stato totalmente destrutturato a una conformazione altamente strutturata. I riarrangiamenti conformazionali di AS sono stati studiati anche in presenza di gallato epigallocatechina (EGCG) e dopamina (DA). Una particolare attenzione è stata quindi riservata al confronto tra i risultati ottenuti da tecniche di SMFS e quelli precedentemente ricavati da analisi di spettroscopia di massa. La proteina AS è stata caratterizzata anche in presenza di tre diverse mutazioni puntuali legate al PD (A30P, A53T e E83A). Nel secondo progetto, un analogo del DNA (DAP) è stato caratterizzato sia con metodi di stabilità termica che di nanomeccanica, studiando il comportamento del DAP-DNA in presenza di forze esterne. L’estensione e la rigidità delle due molecole di DNA (DAP e WT) sono state caratterizzate a basse forze (AFM e MT) e alte forze (MT), dove è stata descritta la transizione di overstretching. Nel terzo progetto è stato studiato l’effetto della condensina sulla condensazione di singoli filamenti di DNA. In particolare, è stato effettuato uno studio di singola molecola per seguire, in tempo reale, la riduzione di estensione di DNA in presenza di condensina e ATP. Considerato che la maggior parte delle curve sono caratterizzate da improvvisi e ben evidenti salti durante la condensazione, sono stati sviluppati e validati due diversi algoritmi per l’identificazione automatica dei gradini. Infine, diverse celle fluidiche sono state testate nell’apparato di F-S, nell’ottica di studi di interazione tra proteine e DNA. Queste celle sono state caratterizzate sia in termini di rapidità di scambio di flussi laminari che di forza capaci di generare sul campione. Sono stati infine visualizzate singole molecole di DNA fluorescenti in presenza di flussi di diversa portata.
In the last few decades, the constant development of novel single molecule techniques has created the basis for a new paradigm in the field of biophysics. Among all, the nanomanipulation of individual biomolecules revealed new insights into the mechanics of biological molecules, in particular proteins and DNA, improving the understanding of the fundamental relation between structural properties and biological functions. Therefore, several single-molecule nanomanipulation methods have been developed, including Atomic Force Microscopy (AFM), Magnetic Tweezers (MT) and Flow Stretching (F-S) coupled with fluorescence. All these technique were employed in this Thesis for the characterisation of biological macromolecules by single molecule force spectroscopy (SMFS). In this Thesis I focus mainly on several aspects of a few different proteins trying to depict a frame in which the strong link between proteins function and their structure can be clarified. With this aim, I study the conformational states of an intrinsically disordered protein (IDP) involved in Parkinson's Disease, the a-synuclein (AS) and the structural change driving the DNA compaction mediated by structural maintenance protein, the condensin. Finally, I present a structural study of a DNA-analogue by thermal shifting essays and single molecule experiments. I included also a technical implementation of a (F-S) combined with TIRF set up to promote the high-speed exchanging buffer for study protein DNA interactions. In the AS single molecule force spectroscopy (SMFS) study, I afford the problem of AS lacking of well defined structure by stretching and unfolding a single polyprotein containing the human AS by employing a SMFS approach. The analysis of the different unfolding pathways gives information about the structural conformation of the protein before the mechanical denaturation. The AS was found to assume three distinct conformational states ranging from a random coil to a highly structured conformation. Since ligands, such as Epigallocatechin-3-Gallate (EGCG) and Dopamine (DA), are known to affect the fibrillation process of AS, I used this single molecule technique to investigate the effect of EGCG and DA on the conformational ensemble of the WT AS. Moreover, knowing from several studies that the presence of point mutations, linked to familial PD, correlate with the gaining of structure and therefore with AS aggregation, I SMFS studies also on AS with three different single point mutations (A30P, A53T and E83A). A particular emphasis was given to the comparison between SMFS results and native mass spectrometry data for the conformational changes of AS in the presence of both DA and EGCG. In the following part, related to the DAP: diaminopurine-substituted DNA, a systematic comparison between a wild-type DNA and DAP DNA is performed, in terms of thermal stability and nanomechanical properties, measured at low and high forces. At low forces the DNA extension and bending rigidity were investigated, by using both MT and AFM, while at high forces the overstretching transition behaviour was explored. In the section related to condensin mediated DNA collapsing, I present a single-molecule MT study to measure, in real-time, the compaction of individual DNA molecules by the condensin complex in the presence of ATP. Since many compaction traces showed sudden distinct decreases in the DNA end-to-end length, I present and validate two different very conservative user-bias-independent step-finding algorithm to extract the size of these compaction steps. Finally, a DNA flow stretching implementation is presented. Briefly, several flow cells were tested to achieve a fast buffer exchange in both MT and F-S coupled with TIRF, in the frame of visualisation of DNA:proteins interactions. We validated our flow cells in term of boundary exchange and applied force. We also visualized fluorescent DNA molecules stretched in the presence of several flow rates.
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Murello, Anna. "La spettroscopia di forza basata sull'AFM nello studio dello spazio conformazionale e dei processi aggregativi di proteine prioniche." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2015. http://amslaurea.unibo.it/8878/.

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Le malattie neurodegenerative sono caratterizzate da aggregazione proteica, dipendente dalla perdita della usuale struttura fisiologica funzionale delle proteine coinvolte, a favore di conformazioni tossiche (patologiche). Il modello corrente descrive questi cambiamenti conformazionali come eventi rari e ritiene che non esista una sola conformazione patogena, ma che tali possibili conformazioni siano piuttosto eterogenee. La caratterizzazione di queste strutture è, di conseguenza, difficile con le tradizionali tecniche in bulk che permettono di studiare solo la conformazione media e non rendono possibile il riconoscimento delle caratteristiche dei conformeri individuali. Lo sviluppo delle tecniche di singola molecola ha permesso di studiare in modo approfondito le conformazioni possibili. In questo lavoro la spettroscopia di forza di singola molecola basata sull'AFM viene applicata a PrP (proteina responsabile delle encefalopatie spongiformi trasmissibili). Si studiano gli equilibri conformazionali del monomero e quelli di costrutti oligomerici, allo scopo di caratterizzare gli step iniziali dei processi aggregativi. Nel corso di questo lavoro di tesi è stato, in particolare, sviluppato un sistema di analisi dati, al fine di studiare in modo quantitativo le distribuzioni di eventi ottenute. Grazie a tale strumento è stato possibile riconoscere i segnali di unfolding della conformazione nativa del monomero e notare come essa sia presente anche in costrutti oligomerici, ad indicare come questo ripiegamento sia stabile anche in presenza di più monomeri ravvicinati. Si è osservato l'effetto del pH sulla stabilità di tale struttura, notando come pH acidi destabilizzino il ripiegamento nativo. Inoltre si è studiato il ruolo dell'orientazione dei monomeri nella formazione di strutture dimeriche. Monomeri e oligomeri di PrP sono stati descritti come proteine parzialmente strutturate il cui panorama energetico contiene molti minimi locali, dando origine a parecchie conformazioni transienti.
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Rajagopal, Senthil Arun. "SINGLE MOLECULE ELECTRONICS AND NANOFABRICATION OF MOLECULAR ELECTRONIC DEVICES." Miami University / OhioLINK, 2006. http://rave.ohiolink.edu/etdc/view?acc_num=miami1155330219.

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Sikor, Martin. "Single-molecule fluorescence studies of Protein Folding and Molecular Chaperones." Diss., lmu, 2011. http://nbn-resolving.de/urn:nbn:de:bvb:19-138521.

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Ökten, Zeynep. "Single molecule mechanics and the myosin family of molecular motors." [S.l.] : [s.n.], 2006. http://www.diss.fu-berlin.de/2006/6/index.html.

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Zhao, Xiaotao. "The synthesis and single-molecule conductance of conjugated molecular wires." Thesis, Durham University, 2014. http://etheses.dur.ac.uk/10634/.

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The past decades have seen the fast development of electronic devices in the industrial sector. There is increasingly rapid growth in the demand for alternative electronic building blocks to compliment, and possibly replace, the conventional silicon-based products. Electronic devices based on organic molecules, especially those based on single molecules, receive intense studies both theoretically and experimentally. In this presented work, a new family of oligo(aryleneethenylene)s (OAE)s with molecular lengths (N…N distance) of ca. 2-6 nm were designed to investigate the length dependence of conductance at the single molecule level. X-ray molecular structures of OAEs with a molecular length up to 5.3 nm were successfully analysed and presented. Secondly, four groups of pyridyl terminated oligo(phenyleneethylene) (OPE) derivatives were studied for the quantum interference effects. A dramatic destructive quantum interference effect was observed which decreased the single molecule conductance by several orders of magnitude. Unsymmetrical molecules with only one anchor group were noticed to form π-π stacking between two molecules. Thirdly, amino terminated OPEs bearing various substituents on the central phenyl rings were explored to present the robustness of the central OPE backbone towards various functionalising substituents. Fourthly, diaryloligoynes with different anchor groups were synthesised and the single-molecule conductances were studied. The stability of the tetrayne compounds is discussed and X-ray crystal structures of the stable tetraynes are presented. Finally, pyridyl terminated OAE derivatives bearing an anthraquinone core were synthesised to investigate the charge transport through the central anthraquinone core, with special purpose of investigating quantum interference effects and the switching process of the central anthraquinone core.
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Lange, Jeffrey J. "Studies of molecular motions by fluorescence microscopy at single molecule and single fiber levels." Diss., Manhattan, Kan. : Kansas State University, 2009. http://hdl.handle.net/2097/1629.

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Rüttinger, Steffen. "Confocal microscopy and quantitative single molecule techniques for metrology in molecular medicine." [S.l.] : [s.n.], 2006. http://opus.kobv.de/tuberlin/volltexte/2007/1434.

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Books on the topic "Singola molecola"

1

Fresh air: And, The story of molecule. Manchester: Carcanet Press Limited, 2012.

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Molecular imaging: Radiopharmaceuticals for PET and SPECT. Berlin: Springer-Verlag, 2009.

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service), SpringerLink (Online, ed. Structured Light Fields: Applications in Optical Trapping, Manipulation, and Organisation. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.

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Dinman, Jonathan D. Biophysical approaches to translational control of gene expression. New York, NY: Springer New York, 2013.

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Imaging dopamine. Cambridge: Cambridge University Press, 2009.

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Kaila, M. M. Molecular Imaging of the Brain: Using Multi-Quantum Coherence and Diagnostics of Brain Disorders. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013.

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Michel, Laguës, and SpringerLink (Online service), eds. Scale Invariance: From Phase Transitions to Turbulence. Berlin, Heidelberg: Springer-Verlag Berlin Heidelberg, 2012.

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Wernsdorfer, W. Molecular nanomagnets. Edited by A. V. Narlikar and Y. Y. Fu. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780199533060.013.4.

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This article describes the quantum phenomena observed in molecular nanomagnets. Molecular nanomagnets, or single-molecule magnets (SMMs), provides a fundamental link between spintronics and molecular electronics. SMMs combine the classic macroscale properties of a magnet with the quantum properties of a nanoscale entity. The resulting field, molecular spintronics, aims at manipulating spins and charges in electronic devices containing one or more molecules. This article first considers molecular nanomagnets and the giant spin model for nanomagnets before discussing the quantum dynamics of a dimer of nanomagnets, resonant photon absorption in Cr7Ni antiferromagnetic rings, and photon-assisted tunnelling in a single-molecule magnet. It also examines environmental decoherence effects in nanomagnets and concludes by highlighting the new trends towards molecular spintronics using junctions and nano-SQUIDs.
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Launay, Jean-Pierre, and Michel Verdaguer. The localized electron: magnetic properties. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198814597.003.0002.

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After preliminaries about electron properties, and definitions in magnetism, one treats the magnetism of mononuclear complexes, in particular spin cross-over, showing the role of cooperativity and the sensitivity to external perturbations. Orbital interactions and exchange interaction are explained in binuclear model systems, using orbital overlap and orthogonality concepts to explain antiferromagnetic or ferromagnetic coupling. The phenomenologically useful Spin Hamiltonian is defined. The concepts are then applied to extended molecular magnetic systems, leading to molecular magnetic materials of various dimensionalities exhibiting bulk ferro- or ferrimagnetism. An illustration is provided by Prussian Blue analogues. Magnetic anisotropy is introduced. It is shown that in some cases, a slow relaxation of magnetization arises and gives rise to appealing single-ion magnets, single-molecule magnets or single-chain magnets, a route to store information at the molecular level.
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(Editor), John E. Gilbert, Y. S. Han (Editor), J. A. Hogan (Editor), Joseph D. Lakey (Editor), D. Weiland (Editor), and G. Weiss (Editor), eds. Smooth Molecular Decompositions of Functions and Singular Integral Operators. American Mathematical Society, 2002.

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Book chapters on the topic "Singola molecola"

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Pilizota, Teuta, Yoshiyuki Sowa, and Richard M. Berry. "Single-Molecule Studies of Rotary Molecular Motors." In Handbook of Single-Molecule Biophysics, 183–216. New York, NY: Springer US, 2009. http://dx.doi.org/10.1007/978-0-387-76497-9_7.

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Hornung, Tassilo, James Martin, David Spetzler, Robert Ishmukhametov, and Wayne D. Frasch. "Microsecond Resolution of Single-Molecule Rotation Catalyzed by Molecular Motors." In Single Molecule Enzymology, 273–89. Totowa, NJ: Humana Press, 2011. http://dx.doi.org/10.1007/978-1-61779-261-8_18.

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Duwez, Anne-Sophie. "Single-Molecule Measurements of Synthetic Molecular Machines at Work." In Single Molecular Machines and Motors, 1–16. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-13872-5_1.

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Ganzhorn, Marc, and Wolfgang Wernsdorfer. "Molecular Quantum Spintronics Using Single-Molecule Magnets." In NanoScience and Technology, 319–64. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-40609-6_13.

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Taran, Gheorghe, Edgar Bonet, and Wolfgang Wernsdorfer. "Single-Molecule Magnets and Molecular Quantum Spintronics." In Handbook of Magnetism and Magnetic Materials, 979–1009. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-63210-6_18.

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Xie, X. S., and H. P. Lu. "Single-Molecule Enzymology." In Single Molecule Spectroscopy, 227–40. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/978-3-642-56544-1_13.

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Dovichi, N. J., R. Polakowski, A. Skelley, D. B. Craig, and J. Wong. "Single-Molecule Enzymology." In Single Molecule Spectroscopy, 241–56. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/978-3-642-56544-1_14.

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Taniguchi, Masateru. "Single-Molecule Sequencing." In Single-Molecule Electronics, 217–35. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-0724-8_9.

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Webb, Watt W. "Single Molecule Spectroscopy Illuminating the Molecular Dynamics of Life." In Single Molecule Spectroscopy in Chemistry, Physics and Biology, 107–17. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02597-6_5.

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Rapenne, Gwénaël, and Christian Joachim. "Single Rotating Molecule-Machines: Nanovehicles and Molecular Motors." In Molecular Machines and Motors, 253–77. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/128_2013_510.

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Conference papers on the topic "Singola molecola"

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Marchetti, Laura, Fulvio Bonsignore, Rosy Amodeo, Chiara Schirripa Spagnolo, Aldo Moscardini, Francesco Gobbo, Antonino Cattaneo, Fabio Beltram, and Stefano Luin. "Single molecule tracking and spectroscopy unveils molecular details in function and interactions of membrane receptors." In Single Molecule Spectroscopy and Superresolution Imaging XIV, edited by Ingo Gregor, Rainer Erdmann, and Felix Koberling. SPIE, 2021. http://dx.doi.org/10.1117/12.2578193.

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DREWSEN, M. "COLD MOLECULAR IONS: SINGLE MOLECULE STUDIES." In Proceedings of the XXI International Conference on Atomic Physics. WORLD SCIENTIFIC, 2009. http://dx.doi.org/10.1142/9789814273008_0031.

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Hill, S. C., M. D. Barnes, W. B. Whitten, and J. M. Ramsey. "Modeling Fluorescence Collection from Single Molecules in Liquid Microspheres." In Laser Applications to Chemical and Environmental Analysis. Washington, D.C.: Optica Publishing Group, 1996. http://dx.doi.org/10.1364/lacea.1996.lwd.7.

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Optimization of molecular detection efficiencies is of central importance in analytical applications involving single molecule detection.1 In addition to limitations imposed on the fraction of molecules which can be detected by the average signal-to-noise ratio, experimental factors such as excitation inhomogeneity and molecular diffusion conspire to further limit "molecular detectability." Recent single molecule detection experiments in microdroplets suggest that such experimental limitations can be significantly reduced primarily because the molecule cannot diffuse away from the excitation volume. However, unlike fluorescence detection from bulk streams where the fluorescence intensity is isotropic in space, the large refractive index change at the surface of microdroplets implies that the fluorescence intensity collected by a lens will be strongly dependent on the position of the molecule within the droplet. In addition, the same refractive index discontinuity at the droplet surface produces a complicated excitation intensity distribution within the droplet as a result of interference between refracted and totally-internally-reflected rays. Thus, issues such as whether molecules near the surface of the sphere can "hide" from the detector as a result of total internal reflection of emission near the droplet surface, or poor excitation efficiency due to the molecule being located in a "shadow" region of the droplet will have a potential effect on molecular detection efficiencies. These questions are nontrivial to address in a quantitative way. Here we discuss development of numerical tools for modeling the fluorescence collected from a single molecule within a microdroplet as a function of position, orientation, and detection geometry based on the semiclassical electrodynamics formalism developed by Chew2 for light scattering in dielectric microspheres. In addition we also examine effects of excitation inhomogeneity within the sphere, molecular diffusion, and transition rate modification in order to obtain a realistic model of molecular detection efficiencies in microdroplets.
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Kamenetska, Maria. "Self-Assembled Organometallic Molecular Wires in Single Molecule Circuits." In 2021 IEEE 16th Nanotechnology Materials and Devices Conference (NMDC). IEEE, 2021. http://dx.doi.org/10.1109/nmdc50713.2021.9677552.

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Hall, Drew A., Nagaraj Ananthapad Manabhan, Chulmin Choi, Le Zheng, Paul P. Pan, Carl W. Fuller, Pius P. Padayatti, et al. "A CMOS Molecular Electronics Chip for Single-Molecule Biosensing." In 2022 IEEE International Solid- State Circuits Conference (ISSCC). IEEE, 2022. http://dx.doi.org/10.1109/isscc42614.2022.9731770.

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Yildiz, Ahmet. "Dissecting the Molecular Mechanism of Kinesin with Single Molecule Imaging." In Laser Science. Washington, D.C.: OSA, 2009. http://dx.doi.org/10.1364/ls.2009.lsthf3.

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Rivera, Monica, Whasil Lee, Piotr E. Marszalek, Daniel G. Cole, and Robert L. Clark. "Aligning Molecular Attachment Sites in Single Molecule Force Spectroscopy Measurements." In ASME 2008 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2008. http://dx.doi.org/10.1115/detc2008-50019.

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In atomic force microscopy (AFM) -based single molecule force spectroscopy, it is assumed that the pulling angle is negligible and that the force applied to the molecule is equivalent to the force measured by the instrument. Although this assumption may hold for flexible, compact molecules, studies have shown that it may not be appropriate for fairly rigid molecules, where measured forces can be a fraction of the actual values experienced by the molecule. Previously, we have proposed a method to align a molecule’s substrate and cantilever attachment sites and tested it in a simulated environment. Here we continue our work and test the alignment program in an experimental environment. In this paper we demonstrate that circling-induced force fluctuations are the result of stretching and relaxing a tethered molecule and we present the results of an alignment trial. Combined, these preliminary results demonstrate the feasibility of the alignment program and are a promising step towards correcting pulling geometry errors in single molecule force spectroscopy studies.
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Netti, A. P., I. De Santo, M. S. Panemi, S. Pricl, Alberto D’Amore, Domenico Acierno, and Luigi Grassia. "MOLECULAR MOTION IN NANOCHANNELS: SINGLE MOLECULE EVIDENCE AND MULTISCALE SIMULATION." In IV INTERNATIONAL CONFERENCE TIMES OF POLYMERS (TOP) AND COMPOSITES. AIP, 2008. http://dx.doi.org/10.1063/1.2989088.

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Lermer, N., M. D. Barnes, C.-Y. Kung, W. B. Whitten, and J. M. Ramsey. "High-Speed Single Molecule Detection in Microdroplet Streams." In Laser Applications to Chemical and Environmental Analysis. Washington, D.C.: Optica Publishing Group, 1996. http://dx.doi.org/10.1364/lacea.1996.lwb.7.

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The detection of individual fluorescent molecules in liquids has been of great interest in recent years. Various fluorescence-based techniques shown to provide single molecule sensitivities include confocal microscopy [1], flow cell techniques [2], and levitated microdroplets [3]. The application of the microdroplet technique to single molecule detection offers many advantages. First, fluoresence decay rates and total fluoresence yield have been shown to be enhanced in glycerol microdroplets [4]. Additionally, the droplet confines the single fluorophore to a small volume thereby removing difficulties arising from diffusion of the fluorophore. Furthermore, the discrete detection unit of the droplet is ideally suited to the application of digital molecular detection for the analysis of ultradilute solutions [5]. Previous liquid microdroplet work has exhibited single molecule detection with signal-to-noise ratios in the range of 10-40 [3]. In our previous work, an electrodynamic trap was employed to trap glycerol microdroplets for a period much longer than the average photochemical lifetime, thus obtaining the maximum possible signal from the analyte. However, the application of digital molecular analysis to real systems requires tens of thousands of droplet measurements [5]; the time required to trap (and to size) the droplet in a levitated system prohibits its application in a high-speed molecular counting technique. In addition, many biological applications of single molecule fluorescence detection require aqueous samples. The present work discusses the development of an instrument designed to permit single molecule detection in water microdroplets at count rates in the range of 10 - 1000 Hz.
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Hou, Shangguo, Jack Exell, and Kevin Welsher. "Untethering single molecule spectroscopy with 3D-SMART." In Single Molecule Spectroscopy and Superresolution Imaging XIV, edited by Ingo Gregor, Rainer Erdmann, and Felix Koberling. SPIE, 2021. http://dx.doi.org/10.1117/12.2578699.

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Reports on the topic "Singola molecola"

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Iancu, Violeta. Single Molecule Switches and Molecular Self-Assembly: Low Temperature STM Investigations and Manipulations. Office of Scientific and Technical Information (OSTI), August 2006. http://dx.doi.org/10.2172/955626.

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Darrow, C., T. Huser, C. Campos, M. Yan, S. Lane, and R. Balhorn. Single Fluorescent Molecule Confocal Microscopy: A New Tool for Molecular Biology Research and Biosensor Development. Office of Scientific and Technical Information (OSTI), March 2000. http://dx.doi.org/10.2172/792442.

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Jeans, C., M. Thelen, and A. Noy. Single Molecule Studies of Chromatin. Office of Scientific and Technical Information (OSTI), February 2006. http://dx.doi.org/10.2172/877892.

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Lu, H. Peter. Single-Molecule Interfacial Electron Transfer. Office of Scientific and Technical Information (OSTI), November 2017. http://dx.doi.org/10.2172/1410506.

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Ho, Wilson. Single-Molecule Interfacial Electron Transfer. Office of Scientific and Technical Information (OSTI), February 2018. http://dx.doi.org/10.2172/1419408.

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Castro, A., and E. B. Shera. Single-molecule electrophoresis. Final report. Office of Scientific and Technical Information (OSTI), May 1996. http://dx.doi.org/10.2172/272560.

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Chen, Peng. Single-Molecule Visualization of Living Polymerization. Fort Belvoir, VA: Defense Technical Information Center, February 2014. http://dx.doi.org/10.21236/ada606984.

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Michael Holman, Ling Zang, Ruchuan Liu, and David M. Adams. Single Molecule Spectroscopy of Electron Transfer. Office of Scientific and Technical Information (OSTI), October 2009. http://dx.doi.org/10.2172/966129.

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Lee, Ji-Young. Single Molecule Screening of Disease DNA Without Amplification. Office of Scientific and Technical Information (OSTI), January 2006. http://dx.doi.org/10.2172/897373.

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Hollars, C. W., L. Stubbs, K. Carlson, X. Lu, and E. Wehri. Single Molecule Techniques for Advanced in situ Hybridization. Office of Scientific and Technical Information (OSTI), February 2003. http://dx.doi.org/10.2172/15007308.

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