The legal discourse on the case Romina Tejerina: a look at key gender

El objetivo de este artículo es reponer y problematizar un conjunto de discursos jurídicos referidos al caso Romina Tejerina, atendiendo especialmente a la dimensión generizada de los mismos. Proponemos indagar el modo en el que la figura jurídica de infanticidio opera en tanto configuradora de identidades genéricas y cómo dichas identidades se entrecruzan en el discurso del derecho con otras, histórica y discursivamente constituidas, como la clase y la edad. El análisis del discurso jurídico se servirá entonces del género en tanto clivaje desde donde pensar las valoraciones que el derecho propone en relación con el cuerpo de las mujeres y, puntualmente, sobre su capacidad reproductiva y las explicaciones propuestas cuando el infanticidio irrumpe en escena.It is the aim of this article to replace and problematize on some legal discourses about the case of Romina Tejerina, providing special attention to the gendered dimension on them. We propose inquire how the legal figure of infanticide operates setting generic identities and how those identities cross at legal discourse with other ones: age and social class. The analysis of legal discourse will use the gender to think on the judgments that the legal discourse proposes about women’s bodies, their reproductive capacity and the explanations for infanticide

Reflexiones sobre los modos de representación del caso Romina Tejerina en la prensa gráfica

El presente artículo se propone como instancia de reflexión acerca de ciertos modos de visibilización pública del caso Romina Tejerina, una joven jujeña que, en febrero de 2003, mató a la beba que parió en el baño de su casa, tras ocultar su embarazo, producto de una violación, y fue condenada por homicidio agravado por el vínculo a catorce años de prisión. Nos hemos detenido especialmente en las articulaciones y en las continuidades identificadas entre los decibles propuestos por tres medios gráficos y aquellos que provienen de otros campos discursivos, igualmente hegemónicos, sobre las mujeres en relación con unos roles sociales históricamente esperados y esperables, tales como el discurso jurídico.Facultad de Periodismo y Comunicación Socia

Reflexiones sobre los modos de representación del caso Romina Tejerina en la prensa gráfica

El objetivo de este trabajo es reponer y problematizar los modos de visibilización pública del caso Romina Tejerina en tres medios gráficos. El análisis otorga especial relevancia a la dimensión generizada de los discursos que allí se proponen y al modo en el cual el género se intersecta en ellos con otro tipo de identidades discursivamente constituidas: la edad y la clase.Asimismo, hemos indagado en las articulaciones y en las continuidades identificadas entre los decibles propuestos por la prensa y aquellos que provienen de otros campos discursivos, igualmente hegemónicos, tales como el discurso jurídico.La problematización de los modos de dar visibilidad al caso cobra especial relevancia al permitirnos pensar una estrategia política con miras a la reincorporación de la figura de infanticidio al Código Penal, superadora de argumentos tanto estigmatizantes como victimizantes, así como del binomio mujer-madre, del complejo vínculo maternidad-naturaleza y sus consecuencias para la demanda de derechos

Reflexiones sobre los modos de representación del caso Romina Tejerina en la prensa gráfica

El presente artículo se propone como instancia de reflexión acerca de ciertos modos de visibilización pública del caso Romina Tejerina, una joven jujeña que, en febrero de 2003, mató a la beba que parió en el baño de su casa, tras ocultar su embarazo, producto de una violación, y fue condenada por homicidio agravado por el vínculo a catorce años de prisión. Nos hemos detenido especialmente en las articulaciones y en las continuidades identificadas entre los decibles propuestos por tres medios gráficos y aquellos que provienen de otros campos discursivos, igualmente hegemónicos, sobre las mujeres en relación con unos roles sociales históricamente esperados y esperables, tales como el discurso jurídico.Facultad de Periodismo y Comunicación Socia

Hierarchy of baby-linked immunogenetic risk factors in the vertical transmission of hepatitis C virus.

Mother-to-infant transmission of Hepatitis C Virus (HCV) represents the major cause of pediatric HCV infection today. Immunogenetic influence has been poorly investigated and mainly confined to HLA-class II serological polymorphisms. Among 290 parities, 135 from Pavia and 155 from Bergamo, of HCV-RNA-infected Italian women, 21 babies (7.24%) were HCV-RNA positive at birth and steadily positive over 20 months of life. All the 21 infected babies and 44 randomly selected uninfected ones, born to HCV-RNA+ mothers but steadily negative for HCV-RNA during a follow-up of 2 years, and their mothers were investigated for HLA-G, -C, -DRB1, -DQA1 and -DQB1 genomic polymorphisms. Among the different covariates, HLA-Cw*07, -G*010401, -DRB1*0701, -DRB1*1401 and homozigosity for HLA-G 14bp deletion can be considered as risk factors for HCV vertical transmission. On the contrary, protection was conferred by the HLA-DQB1*06, -G*0105N, -Cw*0602, DRB1*1104 and -DRB1*1302 alleles. Our initial question was: has the immunogenetic profile any role in the protection of the fetus growing in an infected milieu and, if so, is it independent from the other non-immunogenetic parameters? The answer to both questions should be yes

Real-world data to build explainable trustworthy artificial intelligence models for prediction of immunotherapy efficacy in NSCLC patients

IntroductionArtificial Intelligence (AI) methods are being increasingly investigated as a means to generate predictive models applicable in the clinical practice. In this study, we developed a model to predict the efficacy of immunotherapy (IO) in patients with advanced non-small cell lung cancer (NSCLC) using eXplainable AI (XAI) Machine Learning (ML) methods. MethodsWe prospectively collected real-world data from patients with an advanced NSCLC condition receiving immune-checkpoint inhibitors (ICIs) either as a single agent or in combination with chemotherapy. With regards to six different outcomes - Disease Control Rate (DCR), Objective Response Rate (ORR), 6 and 24-month Overall Survival (OS6 and OS24), 3-months Progression-Free Survival (PFS3) and Time to Treatment Failure (TTF3) - we evaluated five different classification ML models: CatBoost (CB), Logistic Regression (LR), Neural Network (NN), Random Forest (RF) and Support Vector Machine (SVM). We used the Shapley Additive Explanation (SHAP) values to explain model predictions. ResultsOf 480 patients included in the study 407 received immunotherapy and 73 chemo- and immunotherapy. From all the ML models, CB performed the best for OS6 and TTF3, (accuracy 0.83 and 0.81, respectively). CB and LR reached accuracy of 0.75 and 0.73 for the outcome DCR. SHAP for CB demonstrated that the feature that strongly influences models' prediction for all three outcomes was Neutrophil to Lymphocyte Ratio (NLR). Performance Status (ECOG-PS) was an important feature for the outcomes OS6 and TTF3, while PD-L1, Line of IO and chemo-immunotherapy appeared to be more important in predicting DCR. ConclusionsIn this study we developed a ML algorithm based on real-world data, explained by SHAP techniques, and able to accurately predict the efficacy of immunotherapy in sets of NSCLC patients

AIRO Breast Cancer Group Best Clinical Practice 2022 Update

Introduction: Breast cancer is the most common tumor in women and represents the leading cause of cancer death. Radiation therapy plays a key-role in the treatment of all breast cancer stages. Therefore, the adoption of evidence-based treatments is warranted, to ensure equity of access and standardization of care in clinical practice.Method: This national document on the highest evidence-based available data was developed and endorsed by the Italian Association of Radiation and Clinical Oncology (AIRO) Breast Cancer Group.We analyzed literature data regarding breast radiation therapy, using the SIGN (Scottish Intercollegiate Guidelines Network) methodology (www.sign.ac.uk). Updated findings from the literature were examined, including the highest levels of evidence (meta-analyses, randomized trials, and international guidelines) with a significant impact on clinical practice. The document deals with the role of radiation therapy in the treatment of primary breast cancer, local relapse, and metastatic disease, with focus on diagnosis, staging, local and systemic therapies, and follow up. Information is given on indications, techniques, total doses, and fractionations.Results: An extensive literature review from 2013 to 2021 was performed. The work was organized according to a general index of different topics and most chapters included individual questions and, when possible, synoptic and summary tables. Indications for radiation therapy in breast cancer were examined and integrated with other oncological treatments. A total of 50 questions were analyzed and answered.Four large areas of interest were investigated: (1) general strategy (multidisciplinary approach, contraindications, preliminary assessments, staging and management of patients with electronic devices); (2) systemic therapy (primary, adjuvant, in metastatic setting); (3) clinical aspects (invasive, non-invasive and micro-invasive carcinoma; particular situations such as young and elderly patients, breast cancer in males and cancer during pregnancy; follow up with possible acute and late toxicities; loco-regional relapse and metastatic disease); (4) technical aspects (radiation after conservative surgery or mastectomy, indications for boost, lymph node radiotherapy and partial breast irradiation).Appendixes about tumor bed boost and breast and lymph nodes contouring were implemented, including a dedicated web application. The scientific work was reviewed and validated by an expert group of breast cancer key-opinion leaders.Conclusions: Optimal breast cancer management requires a multidisciplinary approach sharing therapeutic strategies with the other involved specialists and the patient, within a coordinated and dedicated clinical path. In recent years, the high-level quality radiation therapy has shown a significant impact on local control and survival of breast cancer patients. Therefore, it is necessary to offer and guarantee accurate treatments according to the best standards of evidence-based medicine

Real-world data to build explainable trustworthy artificial intelligence models for prediction of immunotherapy efficacy in NSCLC patients

IntroductionArtificial Intelligence (AI) methods are being increasingly investigated as a means to generate predictive models applicable in the clinical practice. In this study, we developed a model to predict the efficacy of immunotherapy (IO) in patients with advanced non-small cell lung cancer (NSCLC) using eXplainable AI (XAI) Machine Learning (ML) methods.MethodsWe prospectively collected real-world data from patients with an advanced NSCLC condition receiving immune-checkpoint inhibitors (ICIs) either as a single agent or in combination with chemotherapy. With regards to six different outcomes - Disease Control Rate (DCR), Objective Response Rate (ORR), 6 and 24-month Overall Survival (OS6 and OS24), 3-months Progression-Free Survival (PFS3) and Time to Treatment Failure (TTF3) - we evaluated five different classification ML models: CatBoost (CB), Logistic Regression (LR), Neural Network (NN), Random Forest (RF) and Support Vector Machine (SVM). We used the Shapley Additive Explanation (SHAP) values to explain model predictions.ResultsOf 480 patients included in the study 407 received immunotherapy and 73 chemo- and immunotherapy. From all the ML models, CB performed the best for OS6 and TTF3, (accuracy 0.83 and 0.81, respectively). CB and LR reached accuracy of 0.75 and 0.73 for the outcome DCR. SHAP for CB demonstrated that the feature that strongly influences models’ prediction for all three outcomes was Neutrophil to Lymphocyte Ratio (NLR). Performance Status (ECOG-PS) was an important feature for the outcomes OS6 and TTF3, while PD-L1, Line of IO and chemo-immunotherapy appeared to be more important in predicting DCR.ConclusionsIn this study we developed a ML algorithm based on real-world data, explained by SHAP techniques, and able to accurately predict the efficacy of immunotherapy in sets of NSCLC patients

Time to Switch to Second-line Antiretroviral Therapy in Children With Human Immunodeficiency Virus in Europe and Thailand.

Background: Data on durability of first-line antiretroviral therapy (ART) in children with human immunodeficiency virus (HIV) are limited. We assessed time to switch to second-line therapy in 16 European countries and Thailand. Methods: Children aged <18 years initiating combination ART (≥2 nucleoside reverse transcriptase inhibitors [NRTIs] plus nonnucleoside reverse transcriptase inhibitor [NNRTI] or boosted protease inhibitor [PI]) were included. Switch to second-line was defined as (i) change across drug class (PI to NNRTI or vice versa) or within PI class plus change of ≥1 NRTI; (ii) change from single to dual PI; or (iii) addition of a new drug class. Cumulative incidence of switch was calculated with death and loss to follow-up as competing risks. Results: Of 3668 children included, median age at ART initiation was 6.1 (interquartile range (IQR), 1.7-10.5) years. Initial regimens were 32% PI based, 34% nevirapine (NVP) based, and 33% efavirenz based. Median duration of follow-up was 5.4 (IQR, 2.9-8.3) years. Cumulative incidence of switch at 5 years was 21% (95% confidence interval, 20%-23%), with significant regional variations. Median time to switch was 30 (IQR, 16-58) months; two-thirds of switches were related to treatment failure. In multivariable analysis, older age, severe immunosuppression and higher viral load (VL) at ART start, and NVP-based initial regimens were associated with increased risk of switch. Conclusions: One in 5 children switched to a second-line regimen by 5 years of ART, with two-thirds failure related. Advanced HIV, older age, and NVP-based regimens were associated with increased risk of switch