103 research outputs found
Tinder: Un desliz(ar) amoroso
Este trabajo se propone analizar a partir de la ecología de los medios, la app Tinder, no solo como un espacio de citas, sino como un ambiente de interacción social. A partir de ella ver cómo se establecen, modifican o evolucionan los vínculos sociales en un contexto de conectividad. Entendemos que realizar una comparativa en su totalidad sería muy extenso por lo cual decidimos partir de algunos puntos entre la app y la ecología de los mediosThis work aims to analyze the Tinder app from The Ecology of the Media, not only as a dating space, but as an environment for social interaction. From it, see how social ties are established, modified or evolve in a context of connectivity. We understand that making a comparison in its entirety would be very extensive, so we decided to start from some points between the app and The Ecology of the Medi
Tinder: a swiping love
Este trabajo se propone analizar a partir de la ecología de los medios, la app Tinder, no solo como un espacio de citas, sino como un ambiente de interacción social. A partir de ella ver cómo se establecen, modifican o evolucionan los vínculos sociales en un contexto de conectividad. Entendemos que realizar una comparativa en su totalidad sería muy extenso por lo cual decidimos partir de algunos puntos entre la app y la ecología de los medios.This work aims to analyze the Tinder app from The Ecology of the Media, not only as a dating space, but as an environment for social interaction. From it, see how social ties are established, modified or evolve in a context of connectivity. We understand that making a comparison in its entirety would be very extensive, so we decided to start from some points between the app and The Ecology of the Media.Facultad de Periodismo y Comunicación Socia
Effects of IPR by mechanical oscillating strips system on biological structures: a quantitative and qualitative evaluation
Circular RNAs in embryogenesis and cell differentiation with a focus on cancer development
In the recent years thousands of non-coding RNAs have been identified, also thanks to highthroughput sequencing technologies. Among them, circular RNAs (circRNAs) are a well-represented class characterized by the high sequence conservation and cell type specific expression in eukaryotes. They are covalently closed loops formed through back-splicing. Recently, circRNAs were shown to regulate a variety of cellular processes
functioning as miRNA sponges, RBP binding molecules, transcriptional regulators, scaffold for protein translation, as well as immune regulators. A growing number of studies are showing that deregulated expression of circRNAs plays important and decisive actions during the development of several human diseases, including cancer.
The research on their biogenesis and on the various molecular mechanisms in which they are involved is going very fast, however, there are still few studies that address their involvement in embryogenesis and eukaryotic development. This review has the intent to describe the most recent progress in the study of the biogenesis and molecular activities of circRNAs providing insightful information in the field of embryogenesis and cell differentiation. In addition, we describe the latest research on circRNAs as novel promising biomarkers in diverse types of tumors
The Addition of Venetoclax to Induction Chemotherapy in No Low-Risk AML Patients: A Propensity Score-Matched Analysis of the Gimema AML1718 and AML1310 Trials
Venetoclax combined with intensive chemotherapy proved to be safe with promising activity in fit patients with no-low-risk newly diagnosed acute myeloid leukemia (AML), as demonstrated also by an intermediate analysis of the GIMEMA AML1718 trial (NCT03455504). The latter trial, still ongoing, is based on the administration of venetoclax-FLAI to intermediate/high-risk ELN2017 AML and produced a complete remission (CR) rate of 84%, a minimal residual disease (MRD)-negativity rate of 74% and a 12-month Overall Survival (OS) and disease-free survival (DFS) of 75.7% (95%CI: 64.1%, 89.5%) and 80.7% (95%CI: 67.9%, 95.9%), respectively.
In order to evaluate the actual advantage of the addition of venetoclax to chemotherapy, the GIMEMA AML1718 was matched to AML1310, which entailed a "3+7"-like induction and a risk-adapted, MRD-directed post-remission transplant allocation (NCT01452646, Venditti et al - Blood 2019). To generate a reliable comparison, AML1718 and AML1310 were matched by using a propensity score and then compared in terms of CR achievement, MRD-negativity and survival outcomes.
Patient-level data from GIMEMA AML1718 (n=57) and AML1310 (N=445) with ELN2017 risk classification available were used to conduct a propensity score matching analysis, widely used for reducing the effects of confounding when estimating the effects of treatment on outcomes. Conditional on the propensity score, the distribution of measured variables is expected to be the same in treated (i.e. AML1718) and control (i.e. AML1310) subjects.
In the present propensity score model, we included the following variables: age at diagnosis, gender, ELN2017 risk classification and transplant. Different methods for matching were attempted, including 1:1 nearest neighbor, full-matching, optimal matching (1:2, 1:3 and 1:4) and 1:2 genetic matching. The methods employed for assessing balancing were: i) Standardized Mean Difference - Love plot, ii) Empirical cumulative density function, iii) Variance ratio, iv) Empirical QQ-plot. Weights were calculated with probit or logit regression models according to the propensity score method used. Weights obtained from full-matching were used to adjust outcomes (CR, MRD negativity and survival outcomes). No patients were dropped in the full-matching process. A standardized bias score less than 0.25 was used as a criterion for adequate balancing. We used balance tables and Love plots to assess for covariate balance before and after matching. Survival curves were compared by Log-rank test and Restricted Mean Survival Time (RMST) at 12 months.
AML1718 and AML1310 cohorts differed in terms of age (median: 54 vs 49 years, p=0.003) and risk category (p< .0001) - since the low risk was not represented in AML1718 trial - and female sex (35% vs 48%, p=0.069), though to a lesser extent. Contrariwise, the percentage of transplanted patients was comparable before matching (49% vs 49%, p=0.96). Being more recent, AML1718 median follow-up was shorter than AML1310 (10.5 vs 75.8 months).
Full-matching, 1:2 optimal matching and 1:2 genetic matching produced the best balancing. Table 1 shows the results of the analysis for the unmatched and matched data. After balancing, according to all matching methods, the CR rate observed in the AML1718 was significantly higher than AML1310, as well as MRD-negativity rate. Comparing survival outcomes at 12 months, emerged that, upon matching, OS and DFS estimates of the AML1718 were higher than those of AML1310, though a slight statistical significance was reached only with the optimal matching on DFS (p=0.042). This result was confirmed by a statistically significant difference between the two RMST at 12 months (p=0.036). Despite this, a longer AML1718 follow-up is needed to provide a robust comparison between the two protocols.
Our propensity-score analysis showed that combining venetoclax with chemotherapy in newly diagnosed AML patients resulted in improved outcomes in terms of CR rate and MRD-negativity: these achievements are crucial to allow transition to allogenic transplantation in first remission. With regards to survival outcomes, a solid conclusion will be drawn when a longer AML1718 follow-up is available. These preliminary results highlight the incremental benefit of venetoclax added to intensive induction chemotherapy and paves the way to novel combination regimens based on venetoclax
Italian Physicians' Perceptions about the Role of Asciminib in Later Lines Chronic Myeloid Leukemia in Clinical Practice: A GIMEMA Survey
Unmet needs remain in later lines chronic myeloid leukemia (CML): the response rate and the overall survival of resistant patients in the chronic phase who changed a second-generation TKI in the second line with another TKI with similar action are usually poor, while the off-target toxicities and the potential development of mutations increase. The recent approval of asciminib, a STAMP inhibitor, in the third line, has the potential to soon change the therapeutic algorithm for this subset of patients. Here, we report the results of a GIMEMA survey assessing the number of patients currently treated in the third line in Italy, the current approach in later lines by Italian physicians, and the future role of this drug according to the reason to switch to asciminib (resistance and/or intolerance), as well as the perceptions about the future position of this agent
P495: UNLOCKING THE POTENTIAL OF SYNTHETIC PATIENTS FOR ACCELERATING CLINICAL TRIALS: RESULTS OF THE FIRST GIMEMA EXPERIENCE
Background: Artificial intelligence is contributing to improve different medicine areas including clinical trial design. One field that holds a great potential is represented by the use of digital data as an alternative to real ones. The generation of a virtual cohort of patients might be advantageous since an artificial group of patients resembles the real dataset in all the key features but it does not include any identifiable real-patient data, tackling - by a privacy standpoint – the “burden” of collecting data subjects’ consent as well as the shortcomings of common anonymization techniques.
Aims: To test the feasibility of this approach and evaluate its potential in clinical trial design, we built an in-silico cohort based on the large dataset of patients enrolled in the GIMEMA AML1310 study (Venditti et al. 2019), which entailed a “3 + 7”-like induction and a risk-adapted, MRD-directed post-remission transplant allocation.
Methods: To create the synthetic cohort of patients, a machine learning generative model was constructed from the real individual-level data of the AML1310 study, capturing its patterns and statistical properties. AML1310 enrolled 500 patients (median age 49 years old) in 55 GIMEMA Institutions. All patients were NCCN2009 risk classified and analyzed by morphology, cytogenetics, molecular biology and multiparametric flow cytometry. The subset of 445 patients with ELN2017 risk classification available was used.
To this purpose, the R package “synthpop” was used considering a parametric method: for binary data the logistic regression, for a factor with > 2 levels the polytomous logistic regression, for an ordered factor with > 2 levels the ordered polytomous logistic regression. For time to event variables the classification and regression trees method was used.
Next, we verified the adherence of the virtual cohort to the original one in terms of age, gender, PS, WBC count, FLT3 and NPM1 mutations, risk category, CR achievement, MRD, transplant rate. Virtual and real cohorts were also compared in terms of survival outcomes.
Results: By using the real-patient dataset from the AML1310 trial, a virtual cohort of 850 patients, named synthAML1310, was generated. By comparing the two cohorts, we observed that the clinico-biological characteristics and response evaluations (CR and MRD rates) did not differ significantly. Moreover, as depicted in Figure 1, the curves of OS and DFS were superimposable. Indeed, at 2 years, OS was 57% (52.5%-61.9%) in the original and 59.1% (55.9%-62.6%) in the synthAML1310 cohort. DFS was 55.1% (49.8%-60.9%) in the original and 55.1% (51.3%-59.2%) in the synthetic cohort.
Summary/Conclusion: These results demonstrate the success of this approach in producing a virtual dataset that perfectly mimics the original and that, from a “privacy by design” perspective, minimizes the risk of re-identification of patients. Mirroring an AML population treated with a conventional chemotherapeutic approach, synthAML1310 is suitable to represent the control group when testing novel innovative treatments, most likely in an in-silico randomized trial, but also in other settings like propensity score matching analyses in observational studies. Shifting to an in-silico trial would overcome the challenges of randomized trials and it would be beneficial also for patients. since, they would receive only the experimental treatment without being exposed to the “less active“ therapy, thus limiting treatment failures and toxicity. Also, enrolment and the attainment of final results would be faster
Therapy with high-dose dexamethasone (HD-DXM) in previously untreated patients affected by idiopathic thrombocytopenic purpura: a GIMEMA experience
Abstract
In idiopathic thrombocytopenic purpura (ITP), corticosteroids have been widely recognized as the most appropriate first-line treatment, even if the best therapeutic approach is still a matter of debate. Recently, a single high-dose dexamethasone (HD-DXM) course was administered as first-line therapy in adult patients with ITP. In this paper we show the results of 2 prospective pilot studies (monocentric and multicentric, respectively) concerning the use of repeated pulses of HD-DXM in untreated ITP patients. In the monocenter study, 37 patients with severe ITP, age at least 20 years and no more than 65 years, were enrolled. HD-DXM was given in 4-day pulses every 28 days, for 6 cycles. Response rate was 89.2%; relapse-free survival (RFS) was 90% at 15 months; long-term responses, lasting for a median time of 26 months (range 6-77 months) were 25 of 37 (67.6%). In the multicenter study, 95 patients with severe ITP, age at least 2 years and no more than 70 years, were enrolled. HD-DXM was given in 4-day pulses every 14 days, for 4 cycles; 90 patients completed 4 cycles. Response rate (85.6%) was similar in patients classified by age (< 18 years, 36 of 42 = 85.7%; ≥ 18 years, 41 of 48 = 85.4%, P = not significant), with a statistically significant difference between the second and third cycle (75.8% vs 89%, P = .018). RFS at 15 months 81%; long-term responses, lasting for a median time of 8 months (range 4-24 months) were 67 of 90 (74.4%). In both studies, therapy was well tolerated. A schedule of 3 cycles of HD-DXM pulses will be compared with standard prednisone therapy (eg, 1 mg/kg per day) in the next randomized Gruppo Italiano Malattie EMatologiche dell'Adulto (GIMEMA) trial
Unlocking the potential of synthetic patients for accelerating clinical trials: Results of the first GIMEMA experience on acute myeloid leukemia patients
artificial Intelligence has the potential to reshape the landscape of clinical trials
through innovative applications, with a notable advancement being the emergence
of synthetic patient generation. this process involves simulating cohorts of virtual
patients that can either replace or supplement real individuals within trial settings. by
leveraging synthetic patients, it becomes possible to eliminate the need for obtaining
patient consent and creating control groups that mimic patients in active treatment
arms. this method not only streamlines trial processes, reducing time and
costs but also fortifies the protection of sensitive participant data. furthermore, integrating synthetic patients amplifies trial efficiency by expanding the sample size.
these straightforward and cost-effective methods also enable the development of
personalized subject-specific models, enabling predictions of patient responses to
interventions. synthetic data holds great promise for generating real-world evidence
in clinical trials while upholding rigorous confidentiality standards throughout the process.
therefore, this study aims to demonstrate the applicability and performance
of these methods in the context of onco-hematological research, breaking through
the theoretical and practical barriers associated with the implementation of artificial
intelligence in medical trials
MALAT1-dependent hsa_circ_0076611 regulates translation rate in triple-negative breast cancer
Vascular Endothelial Growth Factor A (VEGFA) is the most commonly expressed angiogenic growth factor in solid tumors and is generated as multiple isoforms through alternative mRNA splicing. Here, we show that lncRNA MALAT1 (metastasis-associated lung adenocarcinoma transcript 1) and ID4 (inhibitor of DNA-binding 4) protein, previously referred to as regulators of linear isoforms of VEGFA, induce back-splicing of VEGFA exon 7, producing circular RNA circ_0076611. Circ_0076611 is detectable in triple-negative breast cancer (TNBC) cells and tissues, in exosomes released from TNBC cells and in the serum of breast cancer patients. Circ_0076611 interacts with a variety of proliferation-related transcripts, included MYC and VEGFA mRNAs, and increases cell proliferation and migration of TNBC cells. Mechanistically, circ_0076611 favors the expression of its target mRNAs by facilitating their interaction with components of the translation initiation machinery. These results add further complexity to the multiple VEGFA isoforms expressed in cancer cells and highlight the relevance of post-transcriptional regulation of VEGFA expression in TNBC cells
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