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Abstract Background The Subglottic Cysts (SGCs) are a rare cause of respiratory distress in infants. Typical risk factors include male gender, extreme prematurity, gastro-oesophageal reflux and invasive ventilation, the latter being associated with mucosal damage and blockage of the subglottic cysts’ ducts. We describe a case of acquired subglottic cysts in a premature infants presented with respiratory distress. Case presentation A premature male infant was born at 25 weeks + 2 days with a history of monochorionic diamniotic twin pregnancy with twin-to-twin transfusion syndrome. During hospitalization, invasive mechanical ventilation was necessary for a total of 18 days; the patient was discharged at postmenstrual age of 40 weeks + 1 day in good condition. At 43 weeks post-menstrual age, he presented to our department with mixed stridor and worsening of respiratory dynamics. A laryngotracheoscopy evaluation was performed. The exam showed the presence of multiple SGCs causing an almost complete obstruction of the airway. Because of the significant reduction of the airway’s patency, the child underwent a tracheotomy and thereafter cysts’ removal using cold steel microinstruments. A better airway patency was restored although a slight glottic edema persisted. The histopathology confirmed the benign nature of the lesions. Successive controls showed a completely patent airway and absence of SGCs. Conclusion In conclusion, SGCs should be considered in preterm infants with respiratory distress previously intubated, which cannot be explained by the most common causes. Early diagnosis and treatment are fundamental to reducing the morbidity and mortality associated with this disease.

Summary: Controlled myogenic differentiation is integral to the development, maintenance and repair of skeletal muscle, necessitating precise regulation of myogenic progenitors and resident stem cells. The transformation of proliferative muscle progenitors into multinuclear syncytia involves intricate cellular processes driven by cytoskeletal reorganization. While actin and microtubles have been extensively studied, we illuminate the role of septins, an essential yet still often overlooked cytoskeletal component, in myoblast architecture. Notably, Septin9 emerges as a critical regulator of myoblast differentiation during the initial commitment phase. Knock-down of Septin9 in C2C12 cells and primary mouse myoblasts accelerates the transition from proliferation to committed progenitor transcriptional programs. Furthermore, we unveil significant reorganization and downregulation of Septin9 during myogenic differentiation. Collectively, we propose that filmamentous septin structures and their orchestrated reorganization in myoblasts are part of a temporal regulatory mechanism governing the differentiation of myogenic progenitors. This study sheds light on the dynamic interplay between cytoskeletal components underlying controlled myogenic differentiation.

Purpose: Glioblastoma is an aggressive brain tumor with high mortality and a median survival of about 15 months. Starting from our previous published compound, MV1035 that inhibited migration and invasiveness of glioblastoma U87 cells, and also exhibited a synergic effect in combination with the alkylating agent Temozolomide, we identified new active molecules, with the aim to understand the key motifs responsible for MV1035 activity against the DNA repair protein ALKBH2 and the RNA demethylase ALKBH5. Materials and methods: We modified the original structure of MV1035, synthesizing new molecules that have been tested through MTT assay, cell-free ALKBH2 assay and cell-free ALKBH5 assay. Results: We found that compound 6 is able to reduce the activity of both ALKBH2 and ALKBH5. Conclusion: We obtained important information about the key motifs responsible for the activity of these inhibitors. However, considering the complexity, heterogeneity and plasticity of GBM and GSC cells, the new identified compound will need to be validated in vivo.

Background/Objectives: Monoclonal antibodies (mAbs) have revolutionized multiple myeloma (MM) treatment. However, post-marketing data on their neuropsychiatric safety are limited. This study aimed to evaluate neuropsychiatric adverse events (AEs) related to mAbs used for MM through a retrospective pharmacovigilance analysis using the Food and Drug Administration (FDA) Adverse Events Reporting System (FAERS) database. Methods: Individual case safety reports (ICSRs) from 2015 to 2023 with at least one neuropsychiatric AE and one of the MM-approved mAbs as the suspected drug (i.e., daratumumab, elotuzumab, isatuximab, belantamab mafodotin, teclistamab, elranatamab, and talquentamab) were analyzed using descriptive and disproportionality approaches. Results: Unknown signals of disproportionate reporting (SDR) included the following: cerebral infarction for daratumumab (n = 45; reporting odds ratio (ROR) = 2.39, 95% confidence interval (CI) = 1.79–3.21; information component (IC) = 1.54, IC025–IC075 = 1.05–1.9), elotuzumab (25; 7.61, 5.13–11.28; 3.03, 2.37–3.51), and isatuximab (10; 2.56, 1.38–4.76; 1.67, 0.59–2.4); mental status changes for daratumumab (40; 2.66, 1.95–3.63; 1.67, 1.14–2.04) and belantamab mafodotin (10; 4.23, 2.28–7.88; 2.3, 1.22–3.03); an altered state of consciousness for daratumumab (32; 1.97, 1.39–2.78; 1.32, 0.73–1.74) and belantamab mafodotin (6; 2.35, 1.05–5.23; 1.6, 0.19–2.52); Guillain-Barre syndrome (GBS) for daratumumab (23; 6.42, 4.26–9.69; 2.81, 2.11–3.3), isatuximab (8; 10.72, 5.35–21.48; 3.57, 2.35–4.37), and elotuzumab (3; 4.74, 1.53–14.7; 2.59, 0.52–3.8); and orthostatic intolerance for daratumumab (10; 12.54, 6.71–23.43; 3.75, 2.67–4.48) and elotuzumab (4; 28.31, 10.58–75.73; 5, 3.24–6.08). Conclusions: Our analysis highlighted several previously unacknowledged SDRs for MM-approved mAbs. Given the complex and not entirely understood etiology of some neuropsychiatric AEs, including GBS, further investigations are necessary.

In the last few decades, the cuttlefish market has grown to approximately 14% of the world’s fisheries, and operators have begun to express concerns about the decline of this resource. In this context, the production of cuttlefish through aquaculture could offer a diversifying and valuable response to the increasing market demand and help alleviate the environmental pressure on this species. Therefore, the aim of this study is to identify a dry, cost-effective, and easy-to-administer diet that can successfully support the initial phases of cuttlefish growth and provide a similar performance to a krill-based diet, which closely mimics their natural diet. To achieve this objective, cuttlefish hatchlings were distributed among different experimental tanks, each receiving one of the five different diets (namely Diets A to E). Mortality and morphological parameters were monitored until day 10 post hatching, and the two most effective diets (Diets A and B) were chosen for further trials. The results indicated that Diet B had similar survival and growth rates to Diet A, which was based on frozen krill. Histological analysis revealed a comparable degree of gut maturity between the organisms fed the two diets. Likewise, levels of amylase and trypsin enzymes and hsp70, cat, and sod mRNA did not exhibit significant differences between the two groups. In conclusion, our findings provide preliminary evidence supporting the possibility of cultivating cuttlefish in captivity using a pelleted diet, representing a promising starting point for larger-scale breeding efforts.

Despite advancements in therapeutic strategies, the development of drug resistance and metastasis remains a serious concern for the efficacy of chemotherapy against colorectal cancer (CRC). We have previously demonstrated that low expression of ribosomal protein uL3 positively correlates with chemoresistance in CRC patients. Here, we demonstrated that the loss of uL3 increased the metastatic capacity of CRC cells in chick embryos. Metabolomic analysis revealed large perturbations in amino acid and glutathione metabolism in resistant uL3-silenced CRC cells, indicating that uL3 silencing dramatically triggered redox metabolic reprogramming. RNA-Seq data revealed a notable dysregulation of 108 genes related to ferroptosis in CRC patients. Solute Carrier Family 7 Member 11 (SLC7A11) is one of the most dysregulated genes; its mRNA stability is negatively regulated by uL3, and its expression is inversely correlated with uL3 levels. Inhibition of SLC7A11 with erastin impaired resistant uL3-silenced CRC cell survival by inducing ferroptosis. Of interest, the combined treatment erastin plus uL3 enhanced the chemotherapeutic sensitivity of uL3-silenced CRC cells to erastin. The antimetastatic potential of the combined strategy was evaluated in chick embryos. Overall, our study sheds light on uL3-mediated chemoresistance and provides evidence of a novel therapeutic approach, erastin plus uL3, to induce ferroptosis, establishing individualized therapy by examining p53, uL3 and SLC7A11 profiles in tumors.

Abstract When it was first introduced in 2000, reverse vaccinology was defined as an in silico approach that begins with the pathogen's genomic sequence. It concludes with a list of potential proteins with a possible, but not necessarily, list of peptide candidates that need to be experimentally confirmed for vaccine production. During the subsequent years, reverse vaccinology has dramatically changed: now it consists of a large number of bioinformatics tools and processes, namely subtractive proteomics, computational vaccinology, immunoinformatics, and in silico related procedures. However, the state of the art of reverse vaccinology still misses the ability to predict the efficacy of the proposed vaccine formulation. Here, we describe how to fill the gap by introducing an advanced immune system simulator that tests the efficacy of a vaccine formulation against the disease for which it has been designed. As a working example, we entirely apply this advanced reverse vaccinology approach to design and predict the efficacy of a potential vaccine formulation against influenza H5N1. Climate change and melting glaciers are critical due to reactivating frozen viruses and emerging new pandemics. H5N1 is one of the potential strains present in icy lakes that can raise a pandemic. Investigating structural antigen protein is the most profitable therapeutic pipeline to generate an effective vaccine against H5N1. In particular, we designed a multi-epitope vaccine based on predicted epitopes of hemagglutinin and neuraminidase proteins that potentially trigger B-cells, CD4, and CD8 T-cell immune responses. Antigenicity and toxicity of all predicted CTL, Helper T-lymphocytes, and B-cells epitopes were evaluated, and both antigenic and non-allergenic epitopes were selected. From the perspective of advanced reverse vaccinology, the Universal Immune System Simulator, an in silico trial computational framework, was applied to estimate vaccine efficacy using a cohort of 100 digital patients.

Daridorexant (dari), as the first dual orexin receptor antagonist (DORA) marketed in Europe, offers a novel therapeutic approach to insomnia. However, data regarding its real-world safety are scarce. Thus, this study was aimed at assessing its safety profile using a large-scale pharmacovigilance database. Dari-related adverse drug reaction (ADR) reports from the Food and Drug Administration Adverse Event Reporting System were scrutinized, and ADRs were selected using reporting odds ratio (ROR) as a measure of disproportionality. Frequencies of events related to dari were compared to all other drugs (reference group, RG1) and only to other DORAs (RG2). Only significant disproportionalities to both RGs were evaluated in-depth. A total of 845 dari-related reports were selected; nightmares (n = 146; dari vs. RG1: ROR = 113.74; 95%CI [95.13, 136]; dari vs. RG2: ROR = 2.35; 95 CI% [1.93, 2.85]), depression (n = 22; dari vs. RG1: 2.13; [1.39, 3.25]; dari vs. RG2: ROR = 2.31; 95 CI% [1.45, 3.67]), and hangover (n = 20; dari vs. RG1: ROR = 127.92; 95 CI% [81.98, 199.62]; and dari vs. RG2: 3.38; [2.04, 5.61]) were considered as safety signals. These data provide valuable insights into the real-world safety profile of daridorexant, supporting the existence of safety signals related to nightmares, depression, and hangovers.

IntroductionNew oral tyrosine kinase inhibitors (TKIs) are approved for metastatic colorectal cancer (mCRC). The aim of this study was to assess the neuropsychiatric adverse drug reactions (ADRs) of these drugs reported in the FDA Adverse Event Reporting System (FAERS) database.MethodsAll reports with regorafenib (REG) and encorafenib (ENC) as the primary suspect, and reported in the FAERS between 2012 and 2022, were collected. A descriptive and disproportionality analyses were conducted.ResultsOut of 4,984 cases, 1,357 (30.2%) reported at least one neuropsychiatric ADR. New potential signals for REG included neuropathy peripheral (n = 265; reporting odds ratio, ROR = 19.48, 95% confidence interval, CI 95% = 17.52-22.47; information component, IC = 2.89, IC025-IC075 = 2.77-3.02), hyperesthesia (n = 18; ROR = 12.56, CI 95% = 7.90-19.96; IC = 2.25, IC025-IC075 = 1.79-2.72), taste disorder (n = 41; ROR = 9.91, CI 95% = 7.29-13.49; IC = 2.18, IC025-IC075 = 1.88-2.49), poor quality sleep (n = 18; ROR = 6.56, CI 95% = 4.13-10.42; IC = 1.74, IC025-IC075 = 1.27-2.20), altered state of consciousness (n = 15; ROR = 5.50, CI 95% = 3.31-9.14; IC = 1.57, IC025-IC075 = 1.06-2.07), depressed mood (n = 13; ROR = 1.85, CI 95% = 1.07-3.19; IC = 0.58, IC025-IC075 = 0.04-1.13) and insomnia (n = 63; ROR = 1.48, CI 95% = 1.15-1.89; IC = 0.38, IC025-IC075 = 0.13-0.63). For ENC comprised depressed mood (n = 4; ROR = 5.75, CI 95% = 2.15-15.39; IC = 1.74, IC025-IC075 = 0.76-2.73) and cognitive disorders (n = 3; ROR = 4.71, CI 95% = 1.51-14.66; IC = 1.54, IC025-IC075 = 0.41-2.68).DiscussionThis study identified new unknown potential neuropsychiatric ADRs. Further investigations are required to better define the neurotoxicity of TKIs in mCRC patients.

In cancer, a patient is considered a survivor from the time of initial diagnosis until the end of life. With improvements in early diagnosis and treatment, the number of cancer survivors (CS) has grown considerably and includes: (1) Patients cured and free from cancer who may be at risk of late-onset cancer therapy-related cardiovascular toxicity (CTR-CVT); (2) Patients with long-term control of not-curable cancers in whom CTR-CVT may need to be addressed. This paper highlights the importance of the cancer care continuum, of a patient-centered approach and of a prevention-oriented policy. The ultimate goal is a personalized care of CS, achievable only through a multidisciplinary-guided survivorship care plan, one that replaces the fragmented management of current healthcare systems. Collaboration between oncologists and cardiologists is the pillar of a framework in which primary care providers and other specialists must be engaged and in which familial, social and environmental factors are also taken into account.

Multiple sclerosis is an autoimmune inflammatory disease that affects the central nervous system through chronic demyelination and loss of oligodendrocytes. Since the relapsing-remitting form is the most prevalent, relapse-reducing therapies are a primary choice for specialists. Universal Immune System Simulator is an agent-based model that simulates the human immune system dynamics under physiological conditions and during several diseases, including multiple sclerosis. In this work, we extended the UISS-MS disease layer by adding two new treatments, i.e., cladribine and ocrelizumab, to show that UISS-MS can be potentially used to predict the effects of any existing or newly designed treatment against multiple sclerosis. To retrospectively validate UISS-MS with ocrelizumab and cladribine, we extracted the clinical and MRI data from patients included in two clinical trials, thus creating specific cohorts of digital patients for predicting and validating the effects of the considered drugs. The obtained results mirror those of the clinical trials, demonstrating that UISS-MS can correctly simulate the mechanisms of action and outcomes of the treatments. The successful retrospective validation concurred to confirm that UISS-MS can be considered a digital twin solution to be used as a support system to inform clinical decisions and predict disease course and therapeutic response at a single patient level.

COVID-19 was declared a pandemic in March 2020, and since then, it has not stopped spreading like wildfire in almost every corner of the world, despite the many efforts made to stem its spread. SARS-CoV-2 has one of the biggest genomes among RNA viruses and presents unique characteristics that differentiate it from other coronaviruses, making it even more challenging to find a cure or vaccine that is efficient enough. This work aims, using RNA sequencing (RNA-Seq) data, to evaluate whether the expression of specific human genes in the host can vary in different grades of disease severity and to determine the molecular origins of the differences in response to SARS-CoV-2 infection in different patients. In addition to quantifying gene expression, data coming from RNA-Seq allow for the discovery of new transcripts, the identification of alternative splicing events, the detection of allele-specific expression, and the detection of post-transcriptional alterations. For this reason, we performed differential expression analysis on different expression profiles of COVID-19 patients, using RNA-Seq data coming from NCBI public repository, and we obtained the lists of all differentially expressed genes (DEGs) emerging from 7 experimental conditions. We performed a Gene Set Enrichment Analysis (GSEA) on these genes to find possible correlations between DEGs and known disease phenotypes. We mainly focused on DEGs coming out from the analysis of the contrasts involving severe conditions to infer any possible relation between a worsening of the clinical picture and an over-representation of specific genes. Based on the obtained results, this study indicates a small group of genes that result up-regulated in the severe form of the disease. EXOSC5, MESD, REXO2, and TRMT2A genes are not differentially expressed or not present in the other conditions, being for that reason, good biomarkers candidates for the severe form of COVID-19 disease. The use of specific over-expressed genes, whether up-regulated or down-regulated, which have an individual role in each different condition of COVID-19 as a biomarker, can assist in early diagnosis.

Abstract Background The last few decades have seen the approval of many new treatment options for Relapsing-Remitting Multiple Sclerosis (RRMS), as well as advances in diagnostic methodology and criteria. These developments have greatly improved the available treatment options for today’s Relapsing-Remitting Multiple Sclerosis patients. This increased availability of disease modifying treatments, however, has implications for clinical trial design in this therapeutic area. The availability of better diagnostics and more treatment options have not only contributed to progressively decreasing relapse rates in clinical trial populations but have also resulted in the evolution of control arms, as it is often no longer sufficient to show improvement from placebo. As a result, not only have clinical trials become longer and more expensive but comparing the results to those of “historical” trials has also become more difficult. Methods In order to aid design of clinical trials in RRMS, we have developed a simulator called MS TreatSim which can simulate the response of customizable, heterogeneous groups of patients to four common Relapsing-Remitting Multiple Sclerosis treatment options. MS TreatSim combines a mechanistic, agent-based model of the immune-based etiology of RRMS with a simulation framework for the generation and virtual trial simulation of populations of digital patients. Results In this study, the product was first applied to generate diverse populations of digital patients. Then we applied it to reproduce a phase III trial of natalizumab as published 15 years ago as a use case. Within the limitations of synthetic data availability, the results showed the potential of applying MS TreatSim to recreate the relapse rates of this historical trial of natalizumab. Conclusions MS TreatSim’s synergistic combination of a mechanistic model with a clinical trial simulation framework is a tool that may advance model-based clinical trial design.

Abstract Background Decisions in healthcare usually rely on the goodness and completeness of data that could be coupled with heuristics to improve the decision process itself. However, this is often an incomplete process. Structured interviews denominated Delphi surveys investigate experts' opinions and solve by consensus complex matters like those underlying surgical decision-making. Natural Language Processing (NLP) is a field of study that combines computer science, artificial intelligence, and linguistics. NLP can then be used as a valuable help in building a correct context in surgical data, contributing to the amelioration of surgical decision-making. Results We applied NLP coupled with machine learning approaches to predict the context (words) owning high accuracy from the words nearest to Delphi surveys, used as input. Conclusions The proposed methodology has increased the usefulness of Delphi surveys favoring the extraction of keywords that can represent a specific clinical context. It permits the characterization of the clinical context suggesting words for the evaluation process of the data.

Abstract Background Nowadays, the inception of computer modeling and simulation in life science is a matter of fact. This is one of the reasons why regulatory authorities are open in considering in silico trials evidence for the assessment of safeness and efficacy of medicinal products. In this context, mechanistic Agent-Based Models are increasingly used. Unfortunately, there is still a lack of consensus in the verification assessment of Agent-Based Models for regulatory approval needs. VV&UQ is an ASME standard specifically suited for the verification, validation, and uncertainty quantification of medical devices. However, it can also be adapted for the verification assessment of in silico trials for medicinal products. Results Here, we propose a set of automatic tools for the mechanistic Agent-Based Model verification assessment. As a working example, we applied the verification framework to an Agent-Based Model in silico trial used in the COVID-19 context. Conclusions Using the described verification computational workflow allows researchers and practitioners to easily perform verification steps to prove Agent-Based Models robustness and correctness that provide strong evidence for further regulatory requirements.

Abstract Background Influenza A virus is one of the leading causes of annual mortality. The emerging of novel escape variants of the influenza A virus is still a considerable challenge in the annual process of vaccine production. The evolution of vaccines ranks among the most critical successes in medicine and has eradicated numerous infectious diseases. Recently, multi-epitope vaccines, which are based on the selection of epitopes, have been increasingly investigated. Results This study utilized an immunoinformatic approach to design a recombinant multi-epitope vaccine based on a highly conserved epitope of hemagglutinin, neuraminidase, and membrane matrix proteins with fewer changes or mutate over time. The potential B cells, cytotoxic T lymphocytes (CTL), and CD4 T cell epitopes were identified. The recombinant multi-epitope vaccine was designed using specific linkers and a proper adjuvant. Moreover, some bioinformatics online servers and datasets were used to evaluate the immunogenicity and chemical properties of selected epitopes. In addition, Universal Immune System Simulator (UISS) in silico trial computational framework was run after influenza exposure and recombinant multi-epitope vaccine administration, showing a good immune response in terms of immunoglobulins of class G (IgG), T Helper 1 cells (TH1), epithelial cells (EP) and interferon gamma (IFN-g) levels. Furthermore, after a reverse translation (i.e., convertion of amino acid sequence to nucleotide one) and codon optimization phase, the optimized sequence was placed between the two EcoRV/MscI restriction sites in the PET32a+ vector. Conclusions The proposed “Recombinant multi-epitope vaccine” was predicted with unique and acceptable immunological properties. This recombinant multi-epitope vaccine can be successfully expressed in the prokaryotic system and accepted for immunogenicity studies against the influenza virus at the in silico level. The multi-epitope vaccine was then tested with the Universal Immune System Simulator (UISS) in silico trial platform. It revealed slight immune protection against the influenza virus, shedding the light that a multistep bioinformatics approach including molecular and cellular level is mandatory to avoid inappropriate vaccine efficacy predictions.

In many domains regulating chemicals and chemical products, there is a legal requirement to determine skin sensitivity to allergens. While many in vitro assays to detect contact hypersensitivity have been developed as alternatives to animal testing over the past ten years and significant progress has been made in this area, there is still a need for continued investment in the creation of techniques and strategies that will allow accurate identification of potential contact allergens and their potency in vitro. In silico models are promising tools in this regard. However, none of the state-of-the-art systems seems to function well enough to serve as a stand-alone hazard identification tool, especially in evaluating the possible allergenicity effects in humans.The Universal Immune System Simulator, a mechanistic computational platform that simulates the human immune system response to a specific insult, provides a means of predicting the immunotoxicity induced by skin sensitisers, enriching the collection of computational models for the assessment of skin sensitization.Here, we present a specific disease layer implementation of the Universal Immune System Simulator for the prediction of allergic contact dermatitis induced by specific skin sensitizers.

Immunotoxicity hazard identification of chemicals aims to evaluate the potential for unintended effects of chemical exposure on the immune system. Perfluorinated alkylate substances (PFAS), such as perfluorooctane sulfonate (PFOS) and perfluorooctanoic acid (PFOA), are persistent, globally disseminated environmental contaminants known to be immunotoxic. Elevated PFAS exposure is associated with lower antibody responses to vaccinations in children and in adults. In addition, some studies have reported a correlation between PFAS levels in the body and lower resistance to disease, in other words an increased risk of infections or cancers.In this context, modelling and simulation platforms could be used to simulate the human immune system with the aim to evaluate the adverse effects that immunotoxicants may have.Here, we show the conditions under which a mathematical model developed for one purpose and application (e.g., in the pharmaceutical domain) can be successfully translated and transferred to another (e.g., in the chemicals domain) without undergoing significant adaptation. In particular, we demonstrate that the Universal Immune System Simulator was able to simulate the effects of PFAS on the immune system, introducing entities and new interactions that are biologically involved in the phenomenon. This also revealed a potentially exploitable pathway for assessing immunotoxicity through a computational model.

As cardio-oncology imposed itself as the reference specialty for a comprehensive cardiovascular approach to all patients with cancer, a more specific and careful cardiac evaluation of women entering their journey into cancer care is needed. Gender medicine refers to the study of how sex-based biological and gender-based socioeconomic and cultural differences influence people’s health. Gender-related aspects could account for differences in the development, progression, and clinical signs of diseases as well as in the treatment of adverse events. Gender also accounts for major differences in access to healthcare. As for medicine and healthcare in general, gender-related characteristics have gained significance in cardio-oncology and should no longer be neglected in both clinical practice and research. We aimed to review the most relevant cardiovascular issues in women related to the cardio-oncology approach to offer a specific gender-related point of view for clinicians involved in the care process for both cancer and cardiovascular disease.

Background: this study assessed the nephrotoxicity of regorafenib (REG) and encorafenib (ENC) in metastatic colorectal cancer (mCRC) through an analysis of reports from the US Food and Drug Administration’s Adverse Event Reporting System (FAERS) database. Methods: descriptive and disproportional analyses were performed for all reports using ENC and REG as the primary suspect. Results: A total of 379 reports had at least one renal adverse drug reaction (ADR), and these ADRs were mainly related to REG (93.1%). Potential safety signals for REG included chromaturia (n = 44; ROR = 12.00, CI 95% = 8.92–16.16; IC = 2.36, IC025–IC075 = 2.06–2.66), hydronephrosis (10; 8.70, 4.67–16.19; 1.85, 1.23–2.47), nephrotic syndrome (7; 5.73, 2.73–12.03; 1.47, 0.73–2.21), renal impairment (53; 4.16, 3.17–5.45; 1.39, 1.12–1.66), dysuria (19; 3.06, 1.95–4.81; 1.06, 0.61–1.52), renal failure (38; 1.66, 1.20–2.28; 0.49, 0.17–0.81), and acute kidney injury (AKI) (43; 1.46, 1.08–1.97; 0.37, 0.07–0.67). For ENC, consistent disproportionalities were observed for AKI (n = 11; ROR = 3.79, CI 95% = 2.09–6.90; IC = 1.32, IC025–IC075 = 0.72–1.91) and dysuria (4; 6.50, 2.43–17.39; 1.86, 0.88–2.85). Conclusions: these findings highlight some not extensively reported renal ADRs that require further investigations to better characterize the safety profiles of REG and ENC in patients with mCRC.

Abstract The value of in silico methods in drug development and evaluation has been demonstrated repeatedly and convincingly. While their benefits are now unanimously recognized, international standards for their evaluation, accepted by all stakeholders involved, are still to be established. In this white paper, we propose a risk‐informed evaluation framework for mechanistic model credibility evaluation. To properly frame the proposed verification and validation activities, concepts such as context of use, regulatory impact and risk‐based analysis are discussed. To ensure common understanding between all stakeholders, an overview is provided of relevant in silico terminology used throughout this paper. To illustrate the feasibility of the proposed approach, we have applied it to three real case examples in the context of drug development, using a credibility matrix currently being tested as a quick‐start tool by regulators. Altogether, this white paper provides a practical approach to model evaluation, applicable in both scientific and regulatory evaluation contexts.

Background: Screening of tuberculosis infection (TBI) among migrants from high-incidence countries is a cornerstone of tuberculosis control in low-incidence countries. However, the optimal screening strategy has not been defined yet. Methods: A quasi-experimental study involving migrants residing in the province of Brescia was carried out that aimed at assessing the completion rate, time to completion, preventive treatment initiation rate, and cost-effectiveness of two strategies for TBI screening. They underwent TBI screening with the IGRA-only strategy (arm 1) or with the sequential strategy (tuberculin skin test, TST, followed by IGRA in case of a positive result—arm 2). The two strategies were compared in terms of screening completion, time to complete the screening process, therapy initiation, and cost-effectiveness. Results: Between May 2019 and May 2022, 657 migrants were evaluated, and 599 subjects were included in the study, with 358 assigned to arm 1 and 237 to arm 2. Screening strategy was the only factor associated with screening completion in a multivariable analysis, with the subjects assigned to the IGRA-only strategy more likely to complete the screening cascade (n = 328, 91.6% vs. n = 202, 85.2%, IRR 1.08, 95% CI (1.01–1.14), p = 0.019). The time to complete the screening process was significantly longer for patients assigned to the sequential strategy arm (74 days vs. 46 days, p = 0.002). Therapy initiation did not significantly differ between the two arms, and cost-effectiveness was higher for the sequential strategy. Conclusion: Sequential strategy implementation for TBI screening among migrants may be justified by its higher cost-effectiveness in spite of the lower completion of the screening cascade.

Abstract Background In 2018, about 10 million people were found infected by tuberculosis, with approximately 1.2 million deaths worldwide. Despite these numbers have been relatively stable in recent years, tuberculosis is still considered one of the top 10 deadliest diseases worldwide. Over the years, Mycobacterium tuberculosis has developed a form of resistance to first-line tuberculosis treatments, specifically to isoniazid, leading to multi-drug-resistant tuberculosis. In this context, the EU and Indian DBT funded project STriTuVaD—In Silico Trial for Tuberculosis Vaccine Development—is supporting the identification of new interventional strategies against tuberculosis thanks to the use of Universal Immune System Simulator (UISS), a computational framework capable of predicting the immunity induced by specific drugs such as therapeutic vaccines and antibiotics. Results Here, we present how UISS accurately simulates tuberculosis dynamics and its interaction within the immune system, and how it predicts the efficacy of the combined action of isoniazid and RUTI vaccine in a specific digital population cohort. Specifically, we simulated two groups of 100 digital patients. The first group was treated with isoniazid only, while the second one was treated with the combination of RUTI vaccine and isoniazid, according to the dosage strategy described in the clinical trial design. UISS-TB shows to be in good agreement with clinical trial results suggesting that RUTI vaccine may favor a partial recover of infected lung tissue. Conclusions In silico trials innovations represent a powerful pipeline for the prediction of the effects of specific therapeutic strategies and related clinical outcomes. Here, we present a further step in UISS framework implementation. Specifically, we found that the simulated mechanism of action of RUTI and INH are in good alignment with the results coming from past clinical phase IIa trials.

Abstract Background The STriTuVaD project, funded by Horizon 2020, aims to test through a Phase IIb clinical trial one of the most advanced therapeutic vaccines against tuberculosis. As part of this initiative, we have developed a strategy for generating in silico patients consistent with target population characteristics, which can then be used in combination with in vivo data on an augmented clinical trial. Results One of the most challenging tasks for using virtual patients is developing a methodology to reproduce biological diversity of the target population, ie, providing an appropriate strategy for generating libraries of digital patients. This has been achieved through the creation of the initial immune system repertoire in a stochastic way, and through the identification of a vector of features that combines both biological and pathophysiological parameters that personalise the digital patient to reproduce the physiology and the pathophysiology of the subject. Conclusions We propose a sequential approach to sampling from the joint features population distribution in order to create a cohort of virtual patients with some specific characteristics, resembling the recruitment process for the target clinical trial, which then can be used for augmenting the information from the physical the trial to help reduce its size and duration.

Abstract The 3rd edition of the computational methods for the immune system function workshop has been held in San Diego, CA, in conjunction with the IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2019) from November 18 to 21, 2019. The workshop has continued its growing tendency, with a total of 18 accepted papers that have been presented in a full day workshop. Among these, the best 10 papers have been selected and extended for presentation in this special issue. The covered topics range from computer-aided identification of T cell epitopes to the prediction of heart rate variability to prevent brain injuries, from In Silico modeling of Tuberculosis and generation of digital patients to machine learning applied to predict type-2 diabetes risk.

Abstract Background SARS-CoV-2 is a severe respiratory infection that infects humans. Its outburst entitled it as a pandemic emergence. To get a grip on this outbreak, specific preventive and therapeutic interventions are urgently needed. It must be said that, until now, there are no existing vaccines for coronaviruses. To promptly and rapidly respond to pandemic events, the application of in silico trials can be used for designing and testing medicines against SARS-CoV-2 and speed-up the vaccine discovery pipeline, predicting any therapeutic failure and minimizing undesired effects. Results We present an in silico platform that showed to be in very good agreement with the latest literature in predicting SARS-CoV-2 dynamics and related immune system host response. Moreover, it has been used to predict the outcome of one of the latest suggested approach to design an effective vaccine, based on monoclonal antibody. Universal Immune System Simulator (UISS) in silico platform is potentially ready to be used as an in silico trial platform to predict the outcome of vaccination strategy against SARS-CoV-2. Conclusions In silico trials are showing to be powerful weapons in predicting immune responses of potential candidate vaccines. Here, UISS has been extended to be used as an in silico trial platform to speed-up and drive the discovery pipeline of vaccine against SARS-CoV-2.

Herein, we assess the gene expression changes activated in thyroid tumors through a computational approach, using the MapReduce algorithm. Through this predictive analysis, we identified the TfR1 gene as a critical mediator of thyroid tumor progression. Then, we investigated the effect of TfR1 gene silencing through small interfering RNA (siRNA) in the expression of extracellular signal-regulated kinase 1/2 (Erk1/2) pathway and c-Myc in human differentiated follicular and undifferentiated anaplastic thyroid cancer. The expression levels of cyclin D1, p53, and p27, proteins involved in cell cycle progression, were also evaluated. The effect of TfR1 gene silencing through siRNA on the apoptotic pathway activation was also tested. Computational prediction and in vitro studies demonstrate that TfR1 plays a key role in thyroid cancer and that its downregulation was able to inhibit the ERK pathway, reducing also c-Myc expression, which blocks the cell cycle and activates the apoptotic pathway. We demonstrate that TfR1 plays a crucial role for a rapid and transient activation of the ERK signaling pathway, which induces a deregulation of genes involved in the aberrant accumulation of intracellular free iron and in drug resistance. We also suggest that TfR1 might represent an important target for thyroid cancer therapy. Keywords: human thyroid cancer, TfR1 gene silencing, in silico studies

The pathophysiology of some non-communicable diseases (NCDs) such as hypertension, cardiovascular disease (CVD), diabetes, and cancer includes an alteration of the endothelial function. COVID-19 is a pulmonary and vascular disease with a negative impact on patients whose damaged endothelium is particularly vulnerable. The peculiar SARS-CoV-2-induced “endothelitis” triggers an intriguing immune-thrombosis that affects both the venous and arterial vascular beds. An increased liability for infection and an increased likelihood of a worse outcome have been observed during the pandemic in patients with active cancer and in cancer survivors. “Overlapping commonalities” between COVID-19 and Cardio-Oncology have been described that include shared phenotypes of cardiovascular toxicities such as left ventricular dysfunction, ischemic syndromes, conduction disturbances, myocarditis, pericarditis and right ventricular failure; shared pathophysiologic mechanisms such as inflammation, release of cytokines, the renin-angiotensin-aldosterone-pathway, coagulation abnormalities, microthrombosis and endothelial dysfunction. For these features and for the catalyst role of NCDs (mainly CVD and cancer), we should refer to COVID-19 as a “syndemic.” Another challenging issue is the persistence of the symptoms, the so-called “long COVID” whose pathogenesis is still uncertain: it may be due to persistent multi-organ viral attacks or to an abnormal immune response. An intensive vaccination campaign is the most successful pharmacological weapon against SARS-CoV-2, but the increasing number of variants has reduced the efficacy of the vaccines in controlling SARS-CoV-2 infections. After a year of vaccinations we have also learned more about efficacy and side-effects of COVID-19 vaccines. An important byproduct of the COVID-19 pandemic has been the rapid expansion of telemedicine platforms across different care settings; this new modality of monitoring cancer patients may be useful even in a post pandemic era. In this paper we analyze the problems that the cardio-oncologists are facing in a pandemic scenario modified by the extensive vaccination campaign and add actionable recommendations derived from the ongoing studies and from the syndemic nature of the infection.

Abstract Background Tuberculosis (TB) represents a worldwide cause of mortality (it infects one third of the world’s population) affecting mostly developing countries, including India, and recently also developed ones due to the increased mobility of the world population and the evolution of different new bacterial strains capable to provoke multi-drug resistance phenomena. Currently, antitubercular drugs are unable to eradicate subpopulations of Mycobacterium tuberculosis (MTB) bacilli and therapeutic vaccinations have been postulated to overcome some of the critical issues related to the increase of drug-resistant forms and the difficult clinical and public health management of tuberculosis patients. The Horizon 2020 EC funded project “In Silico Trial for Tuberculosis Vaccine Development” (STriTuVaD) to support the identification of new therapeutic interventions against tuberculosis through novel in silico modelling of human immune responses to disease and vaccines, thereby drastically reduce the cost of clinical trials in this critical sector of public healthcare. Results We present the application of the Universal Immune System Simulator (UISS) computational modeling infrastructure as a disease model for TB. The model is capable to simulate the main features and dynamics of the immune system activities i.e., the artificial immunity induced by RUTI® vaccine, a polyantigenic liposomal therapeutic vaccine made of fragments of Mycobacterium tuberculosis cells (FCMtb). Based on the available data coming from phase II Clinical Trial in subjects with latent tuberculosis infection treated with RUTI® and isoniazid, we generated simulation scenarios through validated data in order to tune UISS accordingly to STriTuVaD objectives. The first case simulates the establishment of MTB latent chronic infection with some typical granuloma formation; the second scenario deals with a reactivation phase during latent chronic infection; the third represents the latent chronic disease infection scenario during RUTI® vaccine administration. Conclusions The application of this computational modeling strategy helpfully contributes to simulate those mechanisms involved in the early stages and in the progression of tuberculosis infection and to predict how specific therapeutical strategies will act in this scenario. In view of these results, UISS owns the capacity to open the door for a prompt integration of in silico methods within the pipeline of clinical trials, supporting and guiding the testing of treatments in patients affected by tuberculosis.

Background. Data on leadless pacemaker (LPM) implantation in an emergency setting are currently lacking. Objective. We aimed to investigate the feasibility of LPM implantation for emergency bradyarrhythmia, in patients referred for urgent PM implantation, in a large, multicenter, real-world cohort of LPM recipients. Methods. Two cohorts of LPM patients, stratified according to the LPM implantation scenario (patients admitted from the emergency department (ED+) vs. elective patients (ED−)) were retrieved from the iLEAPER registry. The primary outcome of the study was a comparison of the peri-procedural complications between the groups. The rates of peri-procedural characteristics (overall procedural and fluoroscopic duration) were deemed secondary outcomes. Results. A total of 1154 patients were enrolled in this project, with patients implanted due to an urgent bradyarrhythmia (ED+) representing 6.2% of the entire cohort. Slow atrial fibrillation and complete + advanced atrioventricular blocks were more frequent in the ED+ cohort (76.3% for ED+ vs. 49.7% for ED−, p = 0.025; 37.5% vs. 27.3%, p = 0.027, respectively). The overall procedural times were longer in the ED+ cohort (60 (45–80) mins vs. 50 (40–65) mins, p < 0.001), showing higher rates of temporary pacing (94.4% for ED+ vs. 28.9% for ED−, p < 0.001). Emergency LPM implantation was not correlated with an increase in the rate of major complications compared to the control group (6.9% ED+ vs. 4.2% ED−, p = 0.244). Conclusion. LPM implantation is a feasible procedure for the treatment of severe bradyarrhythmia in an urgent setting. Urgent LPM implantation was not correlated with an increase in the rate of major complications compared to the control group, but it was associated with longer procedural times.

Cytokinesis mediates the final separation of a mother cell into two daughter cells. Septins are recruited to the cleavage furrow at an early stage. During cytokinetic progression the septin cytoskeleton is constantly rearranged, ultimately leading to a concentration of septins within the intercellular bridge (ICB), and to the formation of two rings adjacent to the midbody that aid ESCRT-dependent abscission. The molecular mechanisms underlying this behavior are poorly understood. Based on observations that septins can associate with actin, microtubules and associated motors, we review here established roles of septins in mammalian cytokinesis, and discuss, how septins may support cytokinetic progression by exerting their functions at particular sites. Finally, we discuss how this might be assisted by phosphoinositide-metabolizing enzymes.

We propose a Bayesian hierarchical method for combining in silico and in vivo data onto an augmented clinical trial with binary end points. The joint posterior distribution from the in silico experiment is treated as a prior, weighted by a measure of compatibility of the shared characteristics with the in vivo data. We also formalise the contribution and impact of in silico information in the augmented trial. We illustrate our approach to inference with in silico data from the UISS-TB simulator, a bespoke simulator of virtual patients with tuberculosis infection, and synthetic physical patients from a clinical trial.

Aims: Cardio-oncology has achieved a pivotal role in science, but real world data on its clinical impact are still limited.Methods: A questionnaire was sent out to all cardio-oncology services across Italy (n = 120). The questionnaire was made up of 28 questions divided into four blocks: (A) general information on hospitals and service, (B) the inner organization of cardio-oncology and its relationships with out-of-hospital cardiologists and general practitioners, (C) educational needs and referral guidelines, and (D) activities/specific workload.Results: Ninety-six out of 120 (80%) completed the questionnaire; 9.4% were cancer centers while 90.6% were general hospitals. A cardio-oncology team was present in 56% of the cancer centers and in 20% only of general hospitals, and a cardio-oncology pathway was active in 55% of cancer centers and in just 14% of the general hospitals. Relationships with out-of-hospital cardiologists and general practitioners were lacking. The guidelines of reference were ESC and ANMCO/AIOM. Patients receiving anthracycline chemotherapy underwent scheduled monitoring by means of echocardiography in 58% of cases. Routine use of cardiac damage biomarkers was overall low, ranging from 22 to 33% while the use of global longitudinal strain reached 44%.Conclusions: Italian cardio-oncology showed a growing influence on clinical practice but still has room for improvement. Cardio-oncology teams are still scarce, and the application of dedicated paths is poor. The need for specific training has been highlighted.

Abstract The 2nd Computational Methods for the Immune System function Workshop has been held in Madrid in conjunction with the IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2018) in Madrid, Spain, from December 3 to 6, 2018. The workshop has been obtained 100% more submissions in respect to the first edition, highlighting a growing interest for the treated topics. The best papers (9) have been selected for extension in this special issue, with themes about immune system and disease simulation, computer-aided design of novel candidate vaccines, methods for the analysis of immune system involved diseases based on statistical methods, meta-heuristics and game theory, and modelling strategies for improving the simulation of the immune system dynamics.

Abstract Background DNA methylation is an epigenetic mechanism of genomic regulation involved in the maintenance of homeostatic balance. Dysregulation of DNA methylation status is one of the driver alterations occurring in neoplastic transformation and cancer progression. The identification of methylation hotspots associated to gene dysregulation may contribute to discover new prognostic and diagnostic biomarkers, as well as, new therapeutic targets. Results We present EpiMethEx (Epigenetic Methylation and Expression), a R package to perform a large-scale integrated analysis by cyclic correlation analyses between methylation and gene expression data. For each gene, samples are segmented according to the expression levels to select genes that are differentially expressed. This stratification allows to identify CG methylation probesets modulated among gene-stratified samples. Subsequently, the methylation probesets are grouped by their relative position in gene sequence to identify wide genomic methylation events statically related to genetic modulation. Conclusions The beta-test study showed that the global methylation analysis was in agreement with scientific literature. In particular, this analysis revealed a negative association between promoter hypomethylation and overexpression in a wide number of genes. Less frequently, this overexpression was sustained by intragenic hypermethylation events.

It is now well established that the urothelium does not act as a passive barrier but contributes to bladder homeostasis by releasing several signaling molecules in response to physiological and chemical stimuli. Here, we investigated the potential contribution of the hydrogen sulfide (H2S) pathway in regulating human urothelium function in β3 adrenoceptor-mediated relaxation. The relaxant effect of BRL 37344 (0.1–300 µM), a selective β3 adrenoceptor agonist, was evaluated in isolated human bladder strips in the presence or absence of the urothelium. The relaxant effect of BRL 37344 was significantly reduced by urothelium removal. The inhibition of cystathionine-γ-lyase (CSE), but not cystathionine-β-synthase (CBS), significantly reduced the BRL 37344 relaxing effect to the same extent as that given by urothelium removal, suggesting a role for CSE-derived H2S. β3 adrenoceptor stimulation in the human urothelium or in T24 urothelial cells markedly increased H2S and cAMP levels that were reverted by a blockade of CSE and β3 adrenoceptor antagonism. These findings demonstrate a key role for urothelium CSE-derived H2S in the β3 effect on the human bladder through the modulation of cAMP levels. Therefore, the study establishes the relevance of urothelial β3 adrenoceptors in the regulation of bladder tone, supporting the use of β3 agonists in patients affected by an overactive bladder.

Myotubular myopathy is a severe muscle disease for which no effective treatment exists. Here, the authors show that tamoxifen ameliorates pathology and extends survival in a mouse model of the disease, and that the effect is mediated via estrogen receptor signaling and involves modulation of DNM2 expression.

Introduction: Arbuscular mycorrhizal (AM) symbiosis between soil fungi and the majority of plants is based on a mutualistic exchange of organic and inorganic nutrients. This takes place inside root cortical cells that harbor an arbuscule: a highly branched intracellular fungal hypha enveloped by an extension of the host cell membrane—the perifungal membrane—which outlines a specialized symbiotic interface compartment. The perifungal membrane develops around each intracellular hypha as the symbiotic fungus proceeds across the root tissues; its biogenesis is the result of an extensive exocytic process and shows a few similarities with cell plate insertion which occurs at the end of somatic cytokinesis.Materials and Methods: We here analyzed the subcellular localization of a GFP fusion with TPLATE, a subunit of the endocytic TPLATE complex (TPC), a central actor in plant clathrin-mediated endocytosis with a role in cell plate anchoring with the parental plasma membrane.Results: Our observations demonstrate that Daucus carota and Medicago truncatula root organ cultures expressing a 35S::AtTPLATE-GFP construct accumulate strong fluorescent green signal at sites of symbiotic interface construction, along recently formed perifungal membranes and at sites of cell-to-cell hyphal passage between adjacent cortical cells, where the perifungal membrane fuses with the plasmalemma.Discussion: Our results strongly suggest that TPC-mediated endocytic processes are active during perifungal membrane interface biogenesis—alongside exocytic transport. This novel conclusion, which might be correlated to the accumulation of late endosomes in the vicinity of the developing interface, hints at the involvement of TPC-dependent membrane remodeling during the intracellular accommodation of AM fungi.

Abstract Background Patients who underwent a successful repair of the aortic coarctation (CoA) show high risk for cardiovascular (CV) events. Mechanical and structural abnormalities in the ascending aorta (Ao) might have a role in the prognosis of CoA patients. We analyzed the elastic properties of Ao measured as aortic stiffness index (AoSI) in CoA patients in the long-term period and we compared AoSI with a cohort of 38 patients with rheumatoid arthritis (RA) and 38 non-RA matched controls. Methods Data from 19 CoA patients were analyzed 28 ± 13 years after surgery. Abnormally high AoSI was diagnosed if AoSI > 6.07% (95th percentile of the AoSI detected in our reference healthy population). AoSI was assessed at the level of the aortic root by two-dimensional guided M-mode evaluation. Results CoA patients showed more than two-fold higher AoSI compared to RA and controls (9.8 ± 12.6 vs 4.8 ± 2.5% and 3.1 ± 2.0%, respectively; all p

Abstract Background Human papillomavirus infection is a global social burden that, every year, leads to thousands new diagnosis of cancer. The introduction of a protocol of immunization, with Gardasil and Cervarix vaccines, has radically changed the way this infection easily spreads among people. Even though vaccination is only preventive and not therapeutic, it is a strong tool capable to avoid the consequences that this pathogen could cause. Gardasil vaccine is not free from side effects and the duration of immunity is not always well determined. This work aim to enhance the effects of the vaccination by using a new class of adjuvants and a different administration protocol. Due to their minimum side effects, their easy extraction, their low production costs and their proven immune stimulating activity, citrus-derived molecules are valid candidates to be administered as adjuvants in a vaccine formulation against Hpv. Results With the aim to get a stronger immune response against Hpv infection we built an in silico model that delivers a way to predict the best adjuvants and the optimal means of administration to obtain such a goal. Simulations envisaged that the use of Neohesperidin elicited a strong immune response that was then validated in vivo. Conclusions We built up a computational infrastructure made by a virtual screening approach able to preselect promising citrus derived compounds, and by an agent based model that reproduces HPV dynamics subject to vaccine stimulation. This integrated methodology was able to predict the best protocol that confers a very good immune response against HPV infection. We finally tested the in silico results through in vivo experiments on mice, finding good agreement.

The antiproliferative G-quadruplex aptamers are a promising and challenging subject in the framework of the anticancer therapeutic oligonucleotides research field. Although several antiproliferative G-quadruplex aptamers have been identified and proven to be effective on different cancer cell lines, their mechanism of action is still unexplored. We have recently described the antiproliferative activity of a heterochiral thrombin binding aptamer (TBA) derivative, namely, LQ1. Here, we investigate the molecular mechanisms of LQ1 activity and the structural and antiproliferative properties of two further TBA derivatives, differing from LQ1 only by the small loop base-compositions. We demonstrate that in p53 deleted colon cancer cells, LQ1 causes nucleolar stress, impairs ribosomal RNA processing, leading to the accumulation of pre-ribosomal RNAs, arrests cells in the G2/M phase and induces early apoptosis. Importantly, the depletion of uL3 abrogates all these effects, indicating that uL3 is a crucial player in the mechanism of action of LQ1. Taken together, our findings identify p53-independent and uL3-dependent nucleolar stress as a novel stress response pathway activated by a specific G-quadruplex TBA derivative. To the best of our knowledge, this investigation reveals, for the first time, the involvement of the nucleolar stress pathway in the mechanism of action of antiproliferative G-quadruplex aptamers.

As of today, 20 disease-modifying drugs (DMDs) have been approved for the treatment of relapsing multiple sclerosis (MS) and, based on their efficacy, they can be grouped into moderate-efficacy DMDs and high-efficacy DMDs. The choice of the drug mostly relies on the judgment and experience of neurologists and the evaluation of the therapeutic response can only be obtained by monitoring the clinical and magnetic resonance imaging (MRI) status during follow up. In an era where therapies are focused on personalization, this study aims to develop a modeling infrastructure to predict the evolution of relapsing MS and the response to treatments. We built a computational modeling infrastructure named Universal Immune System Simulator (UISS), which can simulate the main features and dynamics of the immune system activities. We extended UISS to simulate all the underlying MS pathogenesis and its interaction with the host immune system. This simulator is a multi-scale, multi-organ, agent-based simulator with an attached module capable of simulating the dynamics of specific biological pathways at the molecular level. We simulated six MS patients with different relapsing−remitting courses. These patients were characterized based on their age, sex, presence of oligoclonal bands, therapy, and MRI lesion load at the onset. The simulator framework is made freely available and can be used following the links provided in the availability section. Even though the model can be further personalized employing immunological parameters and genetic information, we generated a few simulation scenarios for each patient based on the available data. Among these simulations, it was possible to find the scenarios that realistically matched the real clinical and MRI history. Moreover, for two patients, the simulator anticipated the timing of subsequent relapses, which occurred, suggesting that UISS may have the potential to assist MS specialists in predicting the course of the disease and the response to treatment.

The nucleolus is a distinct sub-cellular compartment structure in the nucleus. First observed more than 200 years ago, the nucleolus is detectable by microscopy in eukaryotic cells and visible during the interphase as a sub-nuclear structure immersed in the nucleoplasm, from which it is not separated from any membrane. A huge number of studies, spanning over a century, have identified ribosome biogenesis as the main function of the nucleolus. Recently, novel functions, independent from ribosome biogenesis, have been proposed by several proteomic, genomic, and functional studies. Several works have confirmed the non-canonical role for nucleoli in regulating important cellular processes including genome stability, cell-cycle control, the cellular senescence, stress responses, and biogenesis of ribonucleoprotein particles (RNPs). Many authors have shown that both canonical and non-canonical functions of the nucleolus are associated with several cancer-related processes. The association between the nucleolus and cancer, first proposed by cytological and histopathological studies showing that the number and shape of nucleoli are commonly altered in almost any type of cancer, has been confirmed at the molecular level by several authors who demonstrated that numerous mechanisms occurring in the nucleolus are altered in tumors. Recently, therapeutic approaches targeting the nucleolus in cancer have started to be considered as an emerging “hallmark” of cancer and several therapeutic interventions have been developed. This review proposes an up-to-date overview of available strategies targeting the nucleolus, focusing on novel targeted therapeutic approaches. Finally, a target-based classification of currently available treatment will be proposed.

Septins constitute a family of GTP-binding proteins, which assemble into non-polar filaments in a nucleotide-dependent manner. These filaments can be recruited to negatively charged membrane surfaces. When associated with membranes septin filaments can act as diffusion barriers, which confine subdomains of distinct biological functions. In addition, they serve scaffolding roles by recruiting cytosolic proteins and other cytoskeletal elements. Septins have been implicated in a large variety of membrane-dependent processes, including cytokinesis, signaling, cell migration, and membrane traffic, and several family members have been implicated in disease. However, surprisingly little is known about the molecular mechanisms underlying their biological functions. This review summarizes evidence in support of regulatory roles of septins during endo-lysosomal sorting, with a particular focus on phosphoinositides, which serve as spatial landmarks guiding septin recruitment to distinct subcellular localizations.