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

Effects of Low-Protein, and Supplemented Very Low–Protein Diets, on Muscle Protein Turnover in Patients With CKD

Introduction: Early studies have shown that patients with chronic kidney disease (CKD) are able to maintain nitrogen balance despite significantly lower protein intake, but how and to what extent muscle protein metabolism adapts to a low-protein diet (LPD) or to a supplemented very LPD (sVLPD) is still unexplored. Methods: We studied muscle protein turnover by the forearm perfusion method associated with the kinetics of 2H-phenylalanine in patients with CKD: (i) in a parallel study in subjects randomized to usual diet (1.1 g protein/kg, n = 5) or LPD (0.55 g protein/kg, n = 6) (Protocol 1); (ii) in a crossover, self-controlled study in subjects on a 0.55 g/kg LPD followed by a sVLPD (0.45 g/kg + amino/ketoacids 0.1 g/kg, n = 6) (Protocol 2). Results: As compared with a 1.1 g/kg containing diet, a 0.55 g/kg LPD induced the following: (i) a 17% to 40% decrease in muscle protein degradation and net protein balance, respectively, (ii) no change in muscle protein synthesis, (iii) a slight (by approximately 7%, P < 0.06) decrease in whole-body protein degradation, and (iv) an increase in the efficiency of muscle protein turnover. As compared with an LPD, an sVLPD induced the following: (i) no change in muscle protein degradation, and (ii) an approximately 50% decrease in the negative net protein balance, and an increase in the efficiency of muscle protein turnover. Conclusion: The results of these studies indicate that in patients with CKD the adaptation of muscle protein metabolism to restrained protein intake can be obtained via combined responses of protein degradation and the efficiency of recycling of amino acids deriving from protein breakdown. Keywords: amino acids, chronic kidney disease, ketoacids, low-protein diet, nutritio

An eHealth project on invasive pneumococcal disease: Comprehensive evaluation of a promotional campaign

Background: The recently launched Pneumo Rischio eHealth project, which consists of an app, a website, and social networking activity, is aimed at increasing public awareness of invasive pneumococcal disease (IPD). The launch of this project was prompted by the inadequate awareness of IPD among both laypeople and health care workers, the heavy socioeconomic burden of IPD, and the far from optimal vaccination coverage in Italy, despite the availability of safe and effective vaccines. Objective: The objectives of our study were to analyze trends in Pneumo Rischio usage before and after a promotional campaign, to characterize its end users, and to assess its user-rated quality. Methods: At 7 months after launching Pneumo Rischio, we established a 4-month marketing campaign to promote the project. This intervention used various approaches and channels, including both traditional and digital marketing strategies. To highlight usage trends, we used different techniques of time series analysis and modeling, including a modified Mann-Kendall test, change-point detection, and segmented negative binomial regression of interrupted time series. Users were characterized in terms of demographics and IPD risk categories. Customer-rated quality was evaluated by means of a standardized tool in a sample of app users. Results: Over 1 year, the app was accessed by 9295 users and the website was accessed by 143,993 users, while the project's Facebook page had 1216 fans. The promotional intervention was highly effective in increasing the daily number of users. In particular, the Mann-Kendall trend test revealed a significant (P 64.01) increasing trend in both app and website users, while change-point detection analysis showed that the first significant change corresponded to the start of the promotional campaign. Regression analysis showed a significant immediate effect of the intervention, with a mean increase in daily numbers of users of 1562% (95% CI 456%-4870%) for the app and 620% (95% CI 176%-1777%) for the website. Similarly, the postintervention daily trend in the number of users was positive, with a relative increase of 0.9% (95% CI 0.0%-1.8%) for the app and 1.4% (95% CI 0.7%-2.1%) for the website. Demographics differed between app and website users and Facebook fans. A total of 69.15% (10,793/15,608) of users could be defined as being at risk of IPD, while 4729 users expressed intentions to ask their doctor for further information on IPD. The mean app quality score assigned by end users was approximately 79.5% (397/500). Conclusions: Despite its specific topic, Pneumo Rischio was accessed by a considerable number of users, who ranked it as a high-quality project. In order to reach their target populations, however, such projects should be promoted

A Deep Learning Approach to Optimize Recombinant Protein Production in <i>Escherichia coli</i> Fermentations

Fermentation is a widely used process in the biotechnology industry, in which sugar-based substrates are transformed into a new product through chemical reactions carried out by microorganisms. Fermentation yields depend heavily on critical process parameter (CPP) values which need to be finely tuned throughout the process; this is usually performed by a biotech production expert relying on empirical rules and personal experience. Although developing a mathematical model to analytically describe how yields depend on CPP values is too challenging because the process involves living organisms, we demonstrate the benefits that can be reaped by using a black-box machine learning (ML) approach based on recurrent neural networks (RNN) and long short-term memory (LSTM) neural networks to predict real time OD600nm values from fermentation CPP time series. We tested both networks on an E. coli fermentation process (upstream) optimized to obtain inclusion bodies whose purification (downstream) in a later stage will yield a targeted neurotrophin recombinant protein. We achieved root mean squared error (RMSE) and relative error on final yield (REFY) performances which demonstrate that RNN and LSTM are indeed promising approaches for real-time, in-line process yield estimation, paving the way for machine learning-based fermentation process control algorithms

Addressing docking pose selection with structure-based deep learning: Recent advances, challenges and opportunities

Molecular docking is a widely used technique in drug discovery to predict the binding mode of a given ligand to its target. However, the identification of the near-native binding pose in docking experiments still represents a challenging task as the scoring functions currently employed by docking programs are parametrized to predict the binding affinity, and, therefore, they often fail to correctly identify the ligand native binding conformation. Selecting the correct binding mode is crucial to obtaining meaningful results and to conveniently optimizing new hit compounds. Deep learning (DL) algorithms have been an area of a growing interest in this sense for their capability to extract the relevant information directly from the protein-ligand structure. Our review aims to present the recent advances regarding the development of DL-based pose selection approaches, discussing limitations and possible future directions. Moreover, a comparison between the performances of some classical scoring functions and DL-based methods concerning their ability to select the correct binding mode is reported. In this regard, two novel DL-based pose selectors developed by us are presented

Pharmacogenomics-Guided Pharmacotherapy in Patients with Major Depressive Disorder or Bipolar Disorder Affected by Treatment-Resistant Depressive Episodes: A Long-Term Follow-Up Study

Treatment-resistant depression (TRD) reduces affected patients’ quality of life and leads to important social health care costs. Pharmacogenomics-guided treatment (PGT) may be effective in the cure of TRD. The main aim of this study was to evaluate the clinical changes after PGT in patients with TRD (two or more recent failed psychopharmacological trials) affected by bipolar disorder (BD) or major depressive disorder (MDD) compared to a control group with treatment as usual (TAU). We based the PGT on assessing different gene polymorphisms involved in the pharmacodynamics and pharmacokinetics of drugs. We analyzed, with a repeated-measure ANOVA, the changes between the baseline and a 6 month follow-up of the efficacy index assessed through the Clinical Global Impression (CGI) scale, and depressive symptoms through the Hamilton Depression Rating Scale (HDRS). The PGT sample included 53 patients (26 BD and 27 MDD), and the TAU group included 52 patients (31 BD and 21 MDD). We found a significant within-subject effect of treatment time on symptoms and efficacy index for the whole sample, with significant improvements in the efficacy index (F = 8.544; partial η² = 0.077, p p p = 0.019) and remission (χ² = 10.351; p = 0.001) rates in the PGT vs. the TAU group. PGT may be an important option for the long-term treatment of patients with TRD affected by mood disorders, providing information that can better define drug treatment strategies and increase therapeutic improvement