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BACKGROUND: The choice of an appropriate strategy for intracanalicular vestibular schwannoma (ICVS) is still debated. We conducted a systematic review and meta-analysis with the aim to compare treatment outcomes amongst management strategies (conservative surveillance (CS), microsurgical resection (MR), or stereotactic radiosurgery (SRS)) aiming to inform guideline recommendations on behalf of the International Stereotactic Radiosurgery Society (ISRS). METHODS: Using PRISMA guidelines, we reviewed manuscripts published between January 1990 and October 2021 referenced in PubMed or Embase. Inclusion criteria were peer-reviewed clinical studies or case series reporting a cohort of ICVS managed with CS, MR, or SRS. Primary outcome measures included tumor control, the need for additional treatment, hearing outcomes, and posttreatment neurological deficits. These were pooled using meta-analytical techniques and compared using meta-regression with random effect. RESULTS: Forty studies were included (2371 patients). The weighted pooled estimates for tumor control were 96% and 65% in SRS and CS series, respectively (P

BackgroundThe Critical Assessment of Genome Interpretation (CAGI) aims to advance the state-of-the-art for computational prediction of genetic variant impact, particularly where relevant to disease. The five complete editions of the CAGI community experiment comprised 50 challenges, in which participants made blind predictions of phenotypes from genetic data, and these were evaluated by independent assessors.ResultsPerformance was particularly strong for clinical pathogenic variants, including some difficult-to-diagnose cases, and extends to interpretation of cancer-related variants. Missense variant interpretation methods were able to estimate biochemical effects with increasing accuracy. Assessment of methods for regulatory variants and complex trait disease risk was less definitive and indicates performance potentially suitable for auxiliary use in the clinic.ConclusionsResults show that while current methods are imperfect, they have major utility for research and clinical applications. Emerging methods and increasingly large, robust datasets for training and assessment promise further progress ahead.

Abstract Background Seafood is increasingly traded worldwide, but its supply chain is particularly prone to frauds. To increase consumer confidence, prevent illegal trade, and provide independent validation for eco-labelling, accurate tools for seafood traceability are needed. Here we show that the use of microbiome profiling (MP) coupled with machine learning (ML) allows precise tracing the origin of Manila clams harvested in areas separated by small geographic distances. The study was designed to represent a real-world scenario. Clams were collected in different seasons across the most important production area in Europe (lagoons along the northern Adriatic coast) to cover the known seasonal variation in microbiome composition for the species. DNA extracted from samples underwent the same depuration process as commercial products (i.e. at least 12 h in open flow systems). Results Machine learning-based analysis of microbiome profiles was carried out using two completely independent sets of data (collected at the same locations but in different years), one for training the algorithm, and the other for testing its accuracy and assessing the temporal stability signal. Briefly, gills (GI) and digestive gland (DG) of clams were collected in summer and winter over two different years (i.e. from 2018 to 2020) in one banned area and four farming sites. 16S DNA metabarcoding was performed on clam tissues and the obtained amplicon sequence variants (ASVs) table was used as input for ML MP. The best-predicting performances were obtained using the combined information of GI and DG (consensus analysis), showing a Cohen K-score > 0.95 when the target was the classification of samples collected from the banned area and those harvested at farming sites. Classification of the four different farming areas showed slightly lower accuracy with a 0.76 score. Conclusions We show here that MP coupled with ML is an effective tool to trace the origin of shellfish products. The tool is extremely robust against seasonal and inter-annual variability, as well as product depuration, and is ready for implementation in routine assessment to prevent the trade of illegally harvested or mislabeled shellfish.

Abstract Genome interpretation (GI) encompasses the computational attempts to model the relationship between genotype and phenotype with the goal of understanding how the first leads to the second. While traditional approaches have focused on sub-problems such as predicting the effect of single nucleotide variants or finding genetic associations, recent advances in neural networks (NNs) have made it possible to develop end-to-end GI models that take genomic data as input and predict phenotypes as output. However, technical and modeling issues still need to be fixed for these models to be effective, including the widespread underdetermination of genomic datasets, making them unsuitable for training large, overfitting-prone, NNs. Here we propose novel GI models to address this issue, exploring the use of two types of transfer learning approaches and proposing a novel Biologically Meaningful Sparse NN layer specifically designed for end-to-end GI. Our models predict the leaf and seed ionome in A.thaliana, obtaining comparable results to our previous over-parameterized model while reducing the number of parameters by 8.8 folds. We also investigate how the effect of population stratification influences the evaluation of the performances, highlighting how it leads to (1) an instance of the Simpson’s Paradox, and (2) model generalization limitations.

IntroductionProstate cancer (PCa) is the most frequent tumor among men in Europe and has both indolent and aggressive forms. There are several treatment options, the choice of which depends on multiple factors. To further improve current prognostication models, we established the Turin Prostate Cancer Prognostication (TPCP) cohort, an Italian retrospective biopsy cohort of patients with PCa and long-term follow-up. This work presents this new cohort with its main characteristics and the distributions of some of its core variables, along with its potential contributions to PCa research.MethodsThe TPCP cohort includes consecutive non-metastatic patients with first positive biopsy for PCa performed between 2008 and 2013 at the main hospital in Turin, Italy. The follow-up ended on December 31st 2021. The primary outcome is the occurrence of metastasis; death from PCa and overall mortality are the secondary outcomes. In addition to numerous clinical variables, the study’s prognostic variables include histopathologic information assigned by a centralized uropathology review using a digital pathology software system specialized for the study of PCa, tumor DNA methylation in candidate genes, and features extracted from digitized slide images via Deep Neural Networks.ResultsThe cohort includes 891 patients followed-up for a median time of 10 years. During this period, 97 patients had progression to metastatic disease and 301 died; of these, 56 died from PCa. In total, 65.3% of the cohort has a Gleason score less than or equal to 3 + 4, and 44.5% has a clinical stage cT1. Consistent with previous studies, age and clinical stage at diagnosis are important prognostic factors: the crude cumulative incidence of metastatic disease during the 14-years of follow-up increases from 9.1% among patients younger than 64 to 16.2% for patients in the age group of 75-84, and from 6.1% for cT1 stage to 27.9% in cT3 stage.DiscussionThis study stands to be an important resource for updating existing prognostic models for PCa on an Italian cohort. In addition, the integrated collection of multi-modal data will allow development and/or validation of new models including new histopathological, digital, and molecular markers, with the goal of better directing clinical decisions to manage patients with PCa.

Genetic markers (especially short tandem repeats or STRs) located on the X chromosome are a valuable resource to solve complex kinship cases in forensic genetics in addition or alternatively to autosomal STRs. Groups of tightly linked markers are combined into haplotypes, thus increasing the discriminating power of tests. However, this approach requires precise knowledge of the recombination rates between adjacent markers. The International Society of Forensic Genetics recommends that recombination rate estimation on the X chromosome is performed from pedigree genetic data while taking into account the confounding effect of mutations. However, implementations that satisfy these requirements have several drawbacks: they were never publicly released, they are very slow and/or need cluster-level hardware and strong computational expertise to use. In order to address these key concerns we developed Recombulator-X, a new open-source Python tool. The most challenging issue, namely the running time, was addressed with dynamic programming techniques to greatly reduce the computational complexity of the algorithm. Compared to the previous methods, Recombulator-X reduces the estimation times from weeks or months to less than one hour for typical datasets. Moreover, the estimation process, including preprocessing, has been streamlined and packaged into a simple command-line tool that can be run on a normal PC. Where previous approaches were limited to small panels of STR markers (up to 15), our tool can handle greater numbers (up to 100) of mixed STR and non-STR markers. In conclusion, Recombulator-X makes the estimation process much simpler, faster and accessible to researchers without a computational background, hopefully spurring increased adoption of best practices.

BackgroundStereotactic radiosurgery (SRS) for benign intracranial meningiomas is an established treatment.ObjectiveTo summarize the literature and provide evidence-based practice guidelines on behalf of the International Stereotactic Radiosurgery Society (ISRS).MethodsArticles in English specific to SRS for benign intracranial meningioma, published from January 1964 to April 2018, were systematically reviewed. Three electronic databases, PubMed, EMBASE, and the Cochrane Central Register, were searched.ResultsOut of the 2844 studies identified, 305 had a full text evaluation and 27 studies met the criteria to be included in this analysis. All but one were retrospective studies. The 10-yr local control (LC) rate ranged from 71% to 100%. The 10-yr progression-free-survival rate ranged from 55% to 97%. The prescription dose ranged typically between 12 and 15 Gy, delivered in a single fraction. Toxicity rate was generally low.ConclusionThe current literature supporting SRS for benign intracranial meningioma lacks level I and II evidence. However, when summarizing the large number of level III studies, it is clear that SRS can be recommended as an effective evidence-based treatment option (recommendation level II) for grade 1 meningioma.

BackgroundNo guidelines have been published regarding stereotactic radiosurgery (SRS) in the management of Spetzler-Martin grade I and II arteriovenous malformations (AVMs).ObjectiveTo establish SRS practice guidelines for grade I-II AVMs on the basis of a systematic literature review.MethodsPreferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)-compliant search of Medline, Embase, and Scopus, 1986-2018, for publications reporting post-SRS outcomes in ≥10 grade I-II AVMs with a follow-up of ≥24 mo. Primary endpoints were obliteration and hemorrhage; secondary outcomes included Spetzler-Martin parameters, dosimetric variables, and "excellent" outcomes (defined as total obliteration without new post-SRS deficit).ResultsOf 447 abstracts screened, 8 were included (n = 1, level 2 evidence; n = 7, level 4 evidence), representing 1102 AVMs, of which 836 (76%) were grade II. Obliteration was achieved in 884 (80%) at a median of 37 mo; 66 hemorrhages (6%) occurred during a median follow-up of 68 mo. Total obliteration without hemorrhage was achieved in 78%. Of 836 grade II AVMs, Spetzler-Martin parameters were reported in 680: 377 were eloquent brain and 178 had deep venous drainage, totaling 555/680 (82%) high-risk SRS-treated grade II AVMs.ConclusionThe literature regarding SRS for grade I-II AVM is low quality, limiting interpretation. Cautiously, we observed that SRS appears to be a safe, effective treatment for grade I-II AVM and may be considered a front-line treatment, particularly for lesions in deep or eloquent locations. Preceding publications may be influenced by selection bias, with favorable AVMs undergoing resection, whereas those at increased risk of complications and nonobliteration are disproportionately referred for SRS.

BackgroundThis systematic review reports on outcomes and toxicities following stereotactic radiosurgery (SRS) for non-functioning pituitary adenomas (NFAs) and presents consensus opinions regarding appropriate patient management.MethodsUsing the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses, a systematic review was performed from articles of ≥10 patients with NFAs published prior to May 2018 from the Medline database using the key words "radiosurgery" and "pituitary" and/or "adenoma." Weighted random effects models were used to calculate pooled outcome estimates.ResultsOf the 678 abstracts reviewed, 35 full-text articles were included describing the outcomes of 2671 patients treated between 1971 and 2017 with either single fraction SRS or hypofractionated stereotactic radiotherapy (HSRT). All studies were retrospective (level IV evidence). SRS was used in 27 studies (median dose: 15 Gy, range: 5-35 Gy) and HSRT in 8 studies (median total dose: 21 Gy, range: 12-25 Gy, delivered in 3-5 fractions). The 5-year random effects local control estimate after SRS was 94% (95% CI: 93.0-96.0%) and 97.0% (95% CI: 93.0-98.0%) after HSRT. The 10-year local control random effects estimate after SRS was 83.0% (95% CI: 77.0-88.0%). Post-SRS hypopituitarism was the most common treatment-related toxicity observed, with a random effects estimate of 21.0% (95% CI: 15.0-27.0%), whereas visual dysfunction or other cranial nerve injuries were uncommon (range: 0-7%).ConclusionsSRS is an effective and safe treatment for patients with NFAs. Encouraging short-term data support HSRT for select patients, and mature outcomes are needed before definitive recommendations can be made. Clinical practice opinions were developed on behalf of the International Stereotactic Radiosurgery Society (ISRS).

BackgroundThis systematic review reports on outcomes and toxicities following stereotactic radiosurgery (SRS) for non-functioning pituitary adenomas (NFAs) and presents consensus opinions regarding appropriate patient management.MethodsUsing the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses, a systematic review was performed from articles of ≥10 patients with NFAs published prior to May 2018 from the Medline database using the key words "radiosurgery" and "pituitary" and/or "adenoma." Weighted random effects models were used to calculate pooled outcome estimates.ResultsOf the 678 abstracts reviewed, 35 full-text articles were included describing the outcomes of 2671 patients treated between 1971 and 2017 with either single fraction SRS or hypofractionated stereotactic radiotherapy (HSRT). All studies were retrospective (level IV evidence). SRS was used in 27 studies (median dose: 15 Gy, range: 5-35 Gy) and HSRT in 8 studies (median total dose: 21 Gy, range: 12-25 Gy, delivered in 3-5 fractions). The 5-year random effects local control estimate after SRS was 94% (95% CI: 93.0-96.0%) and 97.0% (95% CI: 93.0-98.0%) after HSRT. The 10-year local control random effects estimate after SRS was 83.0% (95% CI: 77.0-88.0%). Post-SRS hypopituitarism was the most common treatment-related toxicity observed, with a random effects estimate of 21.0% (95% CI: 15.0-27.0%), whereas visual dysfunction or other cranial nerve injuries were uncommon (range: 0-7%).ConclusionsSRS is an effective and safe treatment for patients with NFAs. Encouraging short-term data support HSRT for select patients, and mature outcomes are needed before definitive recommendations can be made. Clinical practice opinions were developed on behalf of the International Stereotactic Radiosurgery Society (ISRS).

Diversity and inclusion are addressed within the economics of innovation in an evolutive perspective, by focusing a specific theme (access to information) along the diagonal line between the Gutenberg printing and the network digital technologies. Technology and the market modify the trade-off between diversity and inclusion and the degree of the system’s variety as well. In the transition from the analogic space (pluralism of standards, intermediaries, markets) to the network digital space (inclusive standardized ecosystems, oligopoly of technological intermediaries) variety of access to information has increased, but it is lower than the potential variety.

Abstract Amyotrophic lateral sclerosis (ALS) is a highly complex and heterogeneous neurodegenerative disease that affects motor neurons. Since life expectancy is relatively low, it is essential to promptly understand the course of the disease to better target the patient’s treatment. Predictive models for disease progression are thus of great interest. One of the most extensive and well-studied open-access data resources for ALS is the Pooled Resource Open-Access ALS Clinical Trials (PRO-ACT) repository. In 2015, the DREAM-Phil Bowen ALS Prediction Prize4Life Challenge was held on PRO-ACT data, where competitors were asked to develop machine learning algorithms to predict disease progression measured through the slope of the ALSFRS score between 3 and 12 months. However, although it has already been successfully applied in several studies on ALS patients, to the best of our knowledge deep learning approaches still remain unexplored on the ALSFRS slope prediction in PRO-ACT cohort. Here, we investigate how deep learning models perform in predicting ALS progression using the PRO-ACT data. We developed three models based on different architectures that showed comparable or better performance with respect to the state-of-the-art models, thus representing a valid alternative to predict ALS disease progression.

Collectively, rare genetic disorders affect a substantial portion of the world’s population. In most cases, those affected face difficulties in receiving a clinical diagnosis and genetic characterization. The understanding of the molecular mechanisms of these diseases and the development of therapeutic treatments for patients are also challenging. However, the application of recent advancements in genome sequencing/analysis technologies and computer-aided tools for predicting phenotype-genotype associations can bring significant benefits to this field. In this review, we highlight the most relevant online resources and computational tools for genome interpretation that can enhance the diagnosis, clinical management, and development of treatments for rare disorders. Our focus is on resources for interpreting single nucleotide variants. Additionally, we present use cases for interpreting genetic variants in clinical settings and review the limitations of these results and prediction tools. Finally, we have compiled a curated set of core resources and tools for analyzing rare disease genomes. Such resources and tools can be utilized to develop standardized protocols that will enhance the accuracy and effectiveness of rare disease diagnosis.

Background: The exposome drivers are less studied than its consequences but may be crucial in identifying population subgroups with unfavourable exposures. Objectives: We used three approaches to study the socioeconomic position (SEP) as a driver of the early-life exposome in Turin children of the NINFEA cohort (Italy). Methods: Forty-two environmental exposures, collected at 18 months of age (N = 1989), were classified in 5 groups (lifestyle, diet, meteoclimatic, traffic-related, built environment).We performed cluster analysis to identify subjects sharing similar exposures, and intra-exposome-group Principal Component Analysis (PCA) to reduce the dimensionality. SEP at childbirth was measured through the Equivalised Household Income Indicator.SEP-exposome association was evaluated using: 1) an Exposome Wide Association Study (ExWAS), a one-exposure (SEP) one-outcome (exposome) approach; 2) multinomial regression of cluster membership on SEP; 3) regressions of each intra-exposome-group PC on SEP. Results: In the ExWAS, medium/low SEP children were more exposed to greenness, pet ownership, passive smoking, TV screen and sugar; less exposed to NO2, NOX, PM25abs, humidity, built environment, traffic load, unhealthy food facilities, fruit, vegetables, eggs, grain products, and childcare than high SEP children.Medium/low SEP children were more likely to belong to a cluster with poor diet, less air pollution, and to live in the suburbs than high SEP children.Medium/low SEP children were more exposed to lifestyle PC1 (unhealthy lifestyle) and diet PC2 (unhealthy diet), and less exposed to PC1s of the built environment (urbanization factors), diet (mixed diet), and traffic (air pollution) than high SEP children. Conclusions: The three approaches provided consistent and complementary results, suggesting that children with lower SEP are less exposed to urbanization factors and more exposed to unhealthy lifestyles and diet. The simplest method, the ExWAS, conveys most of the information and is more replicable in other populations. Clustering and PCA may facilitate results interpretation and communication.

Abstract Background Genomic DNA has been shaped by mutational processes through evolution. The cellular machinery for error correction and repair has left its marks in the nucleotide composition along with structural and functional constraints. Therefore, the probability of observing a base in a certain position in the human genome is highly context-dependent. Results Here we develop context-dependent nucleotide models. We first investigate models of nucleotides conditioned on sequence context. We develop a bidirectional Markov model that use an average of the probability from a Markov model applied to both strands of the sequence and thus depends on up to 14 bases to each side of the nucleotide. We show how the genome predictability varies across different types of genomic regions. Surprisingly, this model can predict a base from its context with an average of more than 50% accuracy. For somatic variants we show a tendency towards higher probability for the variant base than for the reference base. Inspired by DNA substitution models, we develop a model of mutability that estimates a mutation matrix (called the alpha matrix) on top of the nucleotide distribution. The alpha matrix can be estimated from a much smaller context than the nucleotide model, but the final model will still depend on the full context of the nucleotide model. With the bidirectional Markov model of order 14 and an alpha matrix dependent on just one base to each side, we obtain a model that compares well with a model of mutability that estimates mutation probabilities directly conditioned on three nucleotides to each side. For somatic variants in particular, our model fits better than the simpler model. Interestingly, the model is not very sensitive to the size of the context for the alpha matrix. Conclusions Our study found strong context dependencies of nucleotides in the human genome. The best model uses a context of 14 nucleotides to each side. Based on these models, a substitution model was constructed that separates into the context model and a matrix dependent on a small context. The model fit somatic variants particularly well.

An open challenge of computational and experimental biology is understanding the impact of non-synonymous DNA variations on protein function and, subsequently, human health. The effects of these variants on protein stability can be measured as the difference in the free energy of unfolding (ΔΔG) between the mutated structure of the protein and its wild-type form. Throughout the years, bioinformaticians have developed a wide variety of tools and approaches to predict the ΔΔG. Although the performance of these tools is highly variable, overall they are less accurate in predicting ΔΔG stabilizing variations rather than the destabilizing ones. Here, we analyze the possible reasons for this difference by focusing on the relationship between experimentally-measured ΔΔG and seven protein properties on three widely-used datasets (S2648, VariBench, Ssym) and a recently introduced one (S669). These properties include protein structural information, different physical properties and statistical potentials. We found that two highly used input features, i.e., hydrophobicity and the Blosum62 substitution matrix, show a performance close to random choice when trying to separate stabilizing variants from either neutral or destabilizing ones. We then speculate that, since destabilizing variations are the most abundant class in the available datasets, the overall performance of the methods is higher when including features that improve the prediction for the destabilizing variants at the expense of the stabilizing ones. These findings highlight the need of designing predictive methods able to exploit also input features highly correlated with the stabilizing variants. New tools should also be tested on a not-artificially balanced dataset, reporting the performance on all the three classes (i.e., stabilizing, neutral and destabilizing variants) and not only the overall results.

The high cosine similarity between some single-base substitution mutational signatures and their characteristic flat profiles could suggest the presence of overfitting and mathematical artefacts. The newest version (v3.3) of the signature database available in the Catalogue Of Somatic Mutations In Cancer (COSMIC) provides a collection of 79 mutational signatures, which has more than doubled with respect to previous version (30 profiles available in COSMIC signatures v2), making more critical the associations between signatures and specific mutagenic processes. This study both provides a systematic assessment of the de novo extraction task through simulation scenarios based on the latest version of the COSMIC signatures and highlights, through a novel approach using archetypal analysis, which COSMIC signatures are redundant and more likely to be considered as mathematical artefacts. 29 archetypes were able to reconstruct the profile of all the COSMIC signatures with cosine similarity >0.8. Interestingly, these archetypes tend to group similar original signatures sharing either the same aetiology or similar biological processes. We believe that these findings will be useful to encourage the development of new de novo extraction methods avoiding the redundancy of information among the signatures while preserving the biological interpretation.

Abstract Aims Risk stratification in patients with advanced chronic heart failure (HF) is an unmet need. Circulating microRNA (miRNA) levels have been proposed as diagnostic and prognostic biomarkers in several diseases including HF. The aims of the present study were to characterize HF‐specific miRNA expression profiles and to identify miRNAs with prognostic value in HF patients. Methods and results We performed a global miRNome analysis using next‐generation sequencing in the plasma of 30 advanced chronic HF patients and of matched healthy controls. A small subset of miRNAs was validated by real‐time PCR (P

Background Phoenician and Punic expansions have been protagonists of intense trade networks and settlements in the Mediterranean Sea. Aims The maternal genetic variability of ancient Punic samples from the Sardinian necropolis of Tharros was analysed, with the aim to explore genetic interactions and signatures of past population events. Subjects and methods The mtDNA HVS-I and coding region SNPs were analysed in 14 Punic samples and 74 modern individuals from Cabras and Belvì (for which the HVS-II region was also analysed). The results were compared with 5,590 modern Euro-Mediterranean sequences and 127 ancient samples. Results While contemporary groups fall within the genetic variability of other modern Sardinians, our Punic samples reveal proximity to present-day North-African and Iberian populations. Furthermore, Cabras and Belvì cluster mainly with pre-Phoenician groups, while samples from Tharros project with other Punic Sardinian individuals. Conclusion This study provides the first preliminary insights into the population dynamics of the Punic site of Tharros. While the number of currently available samples does not allow definitive investigation of the connection with indigenous Sardinian groups, our results seem to confirm internal migratory phenomena in the central-western Mediterranean and female participation in the Punic mobility.

Abstract Background Identifying variants that drive tumor progression (driver variants) and distinguishing these from variants that are a byproduct of the uncontrolled cell growth in cancer (passenger variants) is a crucial step for understanding tumorigenesis and precision oncology. Various bioinformatics methods have attempted to solve this complex task. Results In this study, we investigate the assumptions on which these methods are based, showing that the different definitions of driver and passenger variants influence the difficulty of the prediction task. More importantly, we prove that the data sets have a construction bias which prevents the machine learning (ML) methods to actually learn variant-level functional effects, despite their excellent performance. This effect results from the fact that in these data sets, the driver variants map to a few driver genes, while the passenger variants spread across thousands of genes, and thus just learning to recognize driver genes provides almost perfect predictions. Conclusions To mitigate this issue, we propose a novel data set that minimizes this bias by ensuring that all genes covered by the data contain both driver and passenger variants. As a result, we show that the tested predictors experience a significant drop in performance, which should not be considered as poorer modeling, but rather as correcting unwarranted optimism. Finally, we propose a weighting procedure to completely eliminate the gene effects on such predictions, thus precisely evaluating the ability of predictors to model the functional effects of single variants, and we show that indeed this task is still open.

Abstract This short report includes 5 eyes of 5 patients (mean age 63.2 ± 12 years) who underwent a tectonic keratoplasty [deep anterior lamellar keratoplasty (DALK) or penetrating keratoplasty (PK)] in order to rehabilitate the eye after the extrusion of the non-perforating keratoprosthesis (Kpro) KeraKlear (KeraMed, USA). The non-perforating Kpro was extruded after a mean period of 21.4 ± 21.8 months due to melting. In two cases, the keratoplasty was performed the same day of the non-perforating Kpro removal due to a severe melting, while in the other three cases it was performed one to 3 months later. Two eyes received a DALK, but in 3 eyes a macroscopic Descemet membrane perforation forced the conversion into a PK. The mean follow-up period after the keratoplasty was 16.8 ± 6.6 months. No cases of rejection were recorded. All the 5 eyes achieved “anatomical success” (transparent graft, with no signs of infection or inflammation). Two eyes showed limited “functional success” because the achievement of the best visual potential was prevented by the development of glaucomatous optic atrophy during the follow-up period. In conclusion, this short report presents an unexpected success of a keratoplasty performed with a tectonic purpose after the extrusion of the non-perforating Kpro because the corneal graft remained transparent, without neovascularization or scarring during the follow-up period. This initial evidence shows some encouraging results regarding graft survival rate and the achievement of a useful visual rehabilitation with keratoplasty after a non-perforating Kpro failure instead of repeating the Kpro implantation.

Abstract Background To analyze the clinical results of an artificial neural network (ANN) that has been processed in order to improve the predictability of intracorneal ring segments (ICRS) implantation in keratoconus. Methods This retrospective, comparative, nonrandomized, pilot, clinical study included a cohort of 20 keratoconic eyes implanted with intracorneal ring segments KeraRing (Mediphacos, Belo Horizonte, Brazil) using the ANN (ANN group) and 20 keratoconic eyes implanted with KeraRing using the manufacturer’s nomograms (nomogram group). Uncorrected distance visual acuity (UDVA), corrected distance visual acuity (CDVA) (visual acuity is expressed in decimal value and in LogMAR value in brackets), manifest refraction, corneal topography, tomography, aberrometry, pachymetry and volume analysis (Sirius System. CSO, Firenze, Italy) were performed during the preoperative visit; and the two groups, ANN group and nomogram group, did not differ significantly preoperatively in all of the parameters evaluated. These preoperative values were compared with the results obtained at the third-month visit. Mann-Whitney test and Wilcoxon test were used for the statistical analyses. Results The spherical equivalent and the keratometric values decreased significantly in both groups. The CDVA improved from 0.60 ± 0.23 (0.22 LogMAR) pre-operatively to 0.73 ± 0.21 (0.14 LogMAR) post-operatively in the ANN group (p

Protein stability predictions are becoming essential in medicine to develop novel immunotherapeutic agents and for drug discovery. Despite the large number of computational approaches for predicting the protein stability upon mutation, there are still critical unsolved problems: 1) the limited number of thermodynamic measurements for proteins provided by current databases; 2) the large intrinsic variability of ΔΔG values due to different experimental conditions; 3) biases in the development of predictive methods caused by ignoring the anti-symmetry of ΔΔG values between mutant and native protein forms; 4) over-optimistic prediction performance, due to sequence similarity between proteins used in training and test datasets. Here, we review these issues, highlighting new challenges required to improve current tools and to achieve more reliable predictions. In addition, we provide a perspective of how these methods will be beneficial for designing novel precision medicine approaches for several genetic disorders caused by mutations, such as cancer and neurodegenerative diseases.

Abstract Background Single session radiosurgery represents a widely accepted treatment for intracranial meningiomas. However, this approach could involve a high risk of treatment-related complications when applied to large volume lesions. In these cases and for those not suitable for surgical resection, radiosurgery in multisession setting could represents a viable option. The literature results are reassuring in terms of correlated adverse events as well as in terms of tumor control. However, no prospective long-term results are available. In this scenario, we design a prospective monocentric phase II study, in order to verify the safety of a multisession radiosurgery schedule delivering 25 Gy in 5 daily fractions. Methods Patients diagnosed with large and/or near to critical structures, intracranial meningiomas have been treated by means of multisession radiosurgery in both exclusive and postoperative settings. The primary study aim is safety that has been being prospectively scored based on international scales, including NCI Common Toxicity criteria, version 4.03, Barrow Neurological Institute pain intensity score, Barrow Neurological Institute facial numbness score and House-Brackmann Facial Nerve Grading System for qualitative analysis. Secondary aim is treatment efficacy in terms of local control that has been being assessed on volumetric analysis. Discussion This is the first prospective phase II trial on multisession radiosurgery for large and/or near to critical structures intracranial meningiomas. If positive results will be found, this study could represent the starting point for a phase III trial exploring the role of multisession radiosurgery in the exclusive and postoperative radiation therapy treatment of intracranial meningiomas. Trial registration Trial registration: clinicaltrials.gov platform (Multisession Radiosurgery in Large Meningiomas –MuRaLM- identifier NCT02974127). Registered: November 28, 2016. Retrospectively registered, https://clinicaltrials.gov/ct2/show/NCT02974127?term=radiosurgery&cond=Intracranial+Meningioma&draw=2&rank=1

V Pinzi,1 L Fariselli,1 M Marchetti,1 M Scorsetti,2 P Navarria2 1Neurosurgery Department, Radiotherapy Unit, Fondazione IRCCS Istituto Neurologico C. Besta, Milan, Italy; 2Radiotherapy and Radiosurgery Department, Humanitas Cancer Center and Research Hospital, Rozzano, Milan, ItalyCorrespondence: V PinziNeurosurgery Department, Radiotherapy Unit, Fondazione IRCCS Istituto Neurologico C. Besta, Via G. Celoria 11, Milan 20131, ItalyTel +390223942312Email valentinapinzi@yahoo.itAbstract: Treatment options for intracranial meningiomas are surgical resection alone, surgery followed by adjuvant radiation therapy (RT), or exclusive RT. Parasagittal and parafalcine meningiomas are a subgroup of meningeal disease located close to the vascular structures. Considering the frequent venous invasion, a complete resection is not possible in the majority of cases, and even if a Simpson Grade I resection can be performed, the risk of recurrence is relevant. To date, few studies are focused on parasagittal and parafalcine meningiomas. Because of their specific related issues, particular considerations on decision-making process, outcome, and toxicity follow-up are mandatory. In fact, parasagittal and parafalcine meningiomas require a clear-cut radiological assessment, as well as a tailored toxicity risk evaluation. Moreover, similarly to other meningioma sites, also for parasagittal and parafalcine ones, a standardization of local control, toxicity, and quality of life evaluation is needed in order to lead to a pooled analysis of the results. In this context, our aim was to review the literature data regarding the role of both single-session and multisession radiosurgery (RS), and stereotactic radiotherapy (SRT) for parasagittal and parafalcine meningioma management, summarizing available data on safety and efficacy. It was also discussed how RS and SRT can be performed in a setting of evolving views concerning the treatment paradigm of the parasagittal and parafalcine meningiomas.Keywords: meningioma, parasagittal meningioma, parafalcine meningioma, stereotactic radiotherapy, radiosurgery, radiotherapy

Abstract Background Predicting the effect of single point variations on protein stability constitutes a crucial step toward understanding the relationship between protein structure and function. To this end, several methods have been developed to predict changes in the Gibbs free energy of unfolding (∆∆G) between wild type and variant proteins, using sequence and structure information. Most of the available methods however do not exhibit the anti-symmetric prediction property, which guarantees that the predicted ∆∆G value for a variation is the exact opposite of that predicted for the reverse variation, i.e., ∆∆G(A → B) = −∆∆G(B → A), where A and B are amino acids. Results Here we introduce simple anti-symmetric features, based on evolutionary information, which are combined to define an untrained method, DDGun (DDG untrained). DDGun is a simple approach based on evolutionary information that predicts the ∆∆G for single and multiple variations from sequence and structure information (DDGun3D). Our method achieves remarkable performance without any training on the experimental datasets, reaching Pearson correlation coefficients between predicted and measured ∆∆G values of ~ 0.5 and ~ 0.4 for single and multiple site variations, respectively. Surprisingly, DDGun performances are comparable with those of state of the art methods. DDGun also naturally predicts multiple site variations, thereby defining a benchmark method for both single site and multiple site predictors. DDGun is anti-symmetric by construction predicting the value of the ∆∆G of a reciprocal variation as almost equal (depending on the sequence profile) to -∆∆G of the direct variation. This is a valuable property that is missing in the majority of the methods. Conclusions Evolutionary information alone combined in an untrained method can achieve remarkably high performances in the prediction of ∆∆G upon protein mutation. Non-trained approaches like DDGun represent a valid benchmark both for scoring the predictive power of the individual features and for assessing the learning capability of supervised methods.

The IBA myQA® SRS high-resolution solid-state detector was evaluated in the context of robotic radiosurgery delivered using CyberKnife®. The performance was investigated for periodic machine delivery quality assurance (DQA) and patient-specific treatment verification. myQA® SRS is a 140 × 120 mm CMOS matrix with 400 µm resolution, allocated in a cylindrical ABS phantom topped by a hemispheric cap. Evaluations included: periodic DQA tests, angular response, dose-rate dependence and Iris variable aperture collimator field size measurements. For patient-specific QA various intracranial targets were studied (Gamma Index, 3%/1 mm agreement criteria), taking into account also the detector’s angular response. Results for periodic DQA were in accordance with the machine commissioning data. Dose-rate dependence was confirmed, and angular response tests resulted in a signal decay >5% when beams were delivered outside a ±50° amplitude cone with respect to the vertical direction. Concerning patient-specific QA, >50° angled beams elimination led to a Gamma Index passing rates improvement ranging between +3% and +115%. IBA myQA® SRS proved to be a suitable device for many CyberKnife® constancy DQA checks, providing high-resolution real-time results. Patient-specific Gamma tests showed high passing rates once angular dependence corrections were performed, even in high complexity treatments such as those for trigeminal neuralgia targets.