Small renal masses in Latin-American population : Characteristics and prognostic factors for survival, recurrence and metastasis - A multi-institutional study from LARCG database

To evaluate demographic, clinical and pathological characteristics of small renal masses (SRM) (≤ 4 cm) in a Latin-American population provided by LARCG (Latin-American Renal Cancer Group) and analyze predictors of survival, recurrence and metastasis. A multi-institutional retrospective cohort study of 1523 patients submitted to surgical treatment for non-metastatic SRM from 1979 to 2016. Comparisons between radical (RN) or partial nephrectomy (PN) and young or elderly patients were performed. Kaplan-Meier curves and log-rank tests estimated 10-year overall survival. Predictors of local recurrence or metastasis were analyzed by a multivariable logistic regression model. PN and RN were performed in 897 (66%) and 461 (34%) patients. A proportional increase of PN cases from 48.5% (1979-2009) to 75% (after 2009) was evidenced. Stratifying by age, elderly patients (≥ 65 years) had better 10-year OS rates when submitted to PN (83.5%), than RN (54.5%), p = 0.044. This disparity was not evidenced in younger patients. On multivariable model, bilaterality, extracapsular extension and ASA (American Society of Anesthesiologists) classification ≥3 were predictors of local recurrence. We did not identify significant predictors for distant metastasis in our series. PN is performed in Latin-America in a similar proportion to developed areas and it has been increasing in the last years. Even in elderly individuals, if good functional status, sufficiently fit to surgery, and favorable tumor characteristics, they should be encouraged to perform PN. Intending to an earlier diagnosis of recurrence or distant metastasis, SRM cases with unfavorable characteristics should have a more rigorous follow-up routine

Spain: Valle De Los Caidos (Valley of the Fallen)

A landmark of of 20th century architecture, the Valley of the Fallen was constructed in memorial to those who fell in the Spainish Civil War. Francisco Franco wanted the monument to be built on a scale like that, “of the monuments of old, which defy time and forgetfulness,” in their grandeur. Work on the monument took 18 years, and was inaugurated in 1958. The monument has been controvertial because a percentage of the construction workforce was made up of convicts, some of which were Popular Front political prisoners.https://digitalcommons.ric.edu/smolski_images/1541/thumbnail.jp

Exploiting the use of the decarboxylative S-alkylation reaction to produce self-blowing, recyclable polycarbonate foams

Polymeric foams are widely used in many industrial applications due to their light weight and superior thermal, mechanical, and optical properties. Currently, increasing research efforts is being directed towards the development of greener foam formulations that circumvent the use of isocyanates/blowing agents that are commonly used in the production of foam materials. Here, a straightforward, one-pot method is presented to prepare self-blown polycarbonate (PC) foams by exploiting the (decarboxylative) S-alkylation reaction for in situ generation of the blowing agent (CO2). The concomitant formation of a reactive alcohol intermediate promotes a cascade ring-opening polymerization of the cyclic carbonates to yield a cross-linked polymer network. It is shown that these hydroxyl-functionalized polycarbonate-based foams can be easily recycled into films through thermal compression molding. Furthermore, it is demonstrated that complete hydrolytic degradation of the foams is possible, thus offering the potential for zero-waste materials. This straightforward and versatile process broadens the scope of isocyanate-free, self-foaming materials, opening a new pathway for next-generation environmentally friendly foams.The research leading to these results has received funding from the VITRIMAT program of the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie Grant agreement No 860911

MLe-KCNQ2: An Artificial Intelligence Model for the Prognosis of Missense <i>KCNQ2</i> Gene Variants

Despite the increasing availability of genomic data and enhanced data analysis procedures, predicting the severity of associated diseases remains elusive in the absence of clinical descriptors. To address this challenge, we have focused on the KV7.2 voltage-gated potassium channel gene (KCNQ2), known for its link to developmental delays and various epilepsies, including self-limited benign familial neonatal epilepsy and epileptic encephalopathy. Genome-wide tools often exhibit a tendency to overestimate deleterious mutations, frequently overlooking tolerated variants, and lack the capacity to discriminate variant severity. This study introduces a novel approach by evaluating multiple machine learning (ML) protocols and descriptors. The combination of genomic information with a novel Variant Frequency Index (VFI) builds a robust foundation for constructing reliable gene-specific ML models. The ensemble model, MLe-KCNQ2, formed through logistic regression, support vector machine, random forest and gradient boosting algorithms, achieves specificity and sensitivity values surpassing 0.95 (AUC-ROC > 0.98). The ensemble MLe-KCNQ2 model also categorizes pathogenic mutations as benign or severe, with an area under the receiver operating characteristic curve (AUC-ROC) above 0.67. This study not only presents a transferable methodology for accurately classifying KCNQ2 missense variants, but also provides valuable insights for clinical counseling and aids in the determination of variant severity. The research context emphasizes the necessity of precise variant classification, especially for genes like KCNQ2, contributing to the broader understanding of gene-specific challenges in the field of genomic research. The MLe-KCNQ2 model stands as a promising tool for enhancing clinical decision making and prognosis in the realm of KCNQ2-related pathologies