Effect of Counterion Size on Knotted Polyelectrolyte Conformations

Using Langevin dynamics simulations and a coarse-grained primitive model of electrolytes, we show that the behavior of knotted circular strong polyelectrolytes (PEs) in diluted aqueous solution is largely affected by the diameter of the counterions (CIs), σCI. Indeed, we observe that both gyration radius and knot length vary nonmonotonically with σCI, with both small and bulky CIs favoring knot localization, while medium-sized ones promote delocalized knots. We also show that the conformational change from delocalized to tight knots occurs via the progressive coalescence of the knot's essential crossings. The emerging conformers correspond to the minima of the free energy landscape profiled as a function of the knot length or PE size. We demonstrate that different conformational states can coexist, the transition between them appearing first-order-like and controlled by the enthalpic and entropic trade-off of the amount of CIs condensed on the PE. Such balance can be further altered by varying CI concentrations, thus providing an additional and more convenient tuning parameter for the system properties. Our results lay the foundation for achieving broader and more precise external adjustability of knotted PE size and shape by choosing the nature of its CIs. Thus, they offer new intriguing possibilities for designing novel PE-based materials that are capable of responding to changes in ionic solution properties.

Unraveling the Influence of Topology and Spatial Confinement on Equilibrium and Relaxation Properties of Interlocked Ring Polymers

We use Langevin dynamics simulations to study linked ring polymers in channel confinement. We address the in- and out-of-equilibrium behavior of the systems for varying degrees of confinement and increasing topological and geometrical complexity of the interlocking. The main findings are three. First, metric observables of different link topologies collapse onto the same master curve when plotted against the crossing number, revealing a universal response to confinement. Second, the relaxation process from initially stretched states is faster for more complex links. We ascribe these properties to the interplay of several effects, including the dependence of topological friction on the link complexity. Finally, we show that transient forms of geometrical entanglement purposely added to the initial stressed state can leave distinctive signatures in force-spectroscopy curves. The insight provided by the findings could be leveraged in single-molecule nanochannel experiments to identify geometric entanglement within topologically linked rings.

Retraction Note: The potential preventive role of a dietary supplement containing hydroxytyrosol in COVID-19: a multi-center study

The article "The potential preventive role of a dietary supplement containing hydroxytyrosol in COVID-19: a multi-center study", by K. Dhuli, C. Micheletti, M.C. Medori, G. Madeo, G. Bonetti, K. Donato, F. Gaffuri, G.M. Tartaglia, S. Michelini, A. Fiorentino, D. Cesarz, S.T. Connelly, N. Capodicasa, M. Bertelli, published in Eur Rev Med Pharmacol Sci 2023; 27 (6 Suppl): 33-38-DOI: 10.26355/eurrev_202312_34687-PMID: 38112946 has been retracted by the Editor in Chief for the following reasons. Following some concerns raised on PubPeer, the Editor in Chief has started an investigation to assess the validity of the results. The outcome of the investigation revealed that the manuscript presented major flaws in the following: -       Issues with ethical approval -       Issues in methodology -       Undeclared conflict of interest Consequently, the Editor in Chief mistrusts the results presented and has decided to withdraw the article. The authors disagree with this retraction. https://www.europeanreview.org/article/34687 This article has been retracted. The Publisher apologizes for any inconvenience this may cause.

Retraction Note: Presence of viral spike protein and vaccinal spike protein in the blood serum of patients with long-COVID syndrome

The article "Presence of viral spike protein and vaccinal spike protein in the blood serum of patients with long-COVID syndrome", by K. Dhuli, M.C. Medori, C. Micheletti, K. Donato, F. Fioretti, A. Calzoni, A. Praderio, M.G. De Angelis, G. Arabia, S. Cristoni, S. Nodari, M. Bertelli, published in Eur Rev Med Pharmacol Sci 2023; 27 (6 Suppl): 13-19-DOI: 10.26355/eurrev_202312_34685-PMID: 38112944 has been retracted by the Editor in Chief for the following reasons. Following some concerns raised on PubPeer, the Editor in Chief has started an investigation to assess the validity of the results. The outcome of the investigation revealed that the manuscript presented major flaws in the following: -       Unclear methodology and patient recruitment -       Discrepancies among data reported in the text and tables -       Unreliable results -       Undeclared conflict of interest Consequently, the Editor in Chief mistrusts the results presented and has decided to withdraw the article. The authors disagree with this retraction. The Publisher apologizes for any inconvenience this may cause. https://www.europeanreview.org/article/34685.

Author Correction: Genetic variants identified in novel candidate genes for anorexia nervosa and analysis of molecular pathways for diagnostic applications

Correction to: Eur Rev Med Pharmacol Sci 2023; 27 (6 Suppl): 77-88-DOI: 10.26355/eurrev_202312_34692 After publication and following some post-publication concerns, the authors have applied the following corrections to the galley proof. The conflict of interest section has been amended as follows: K. Donato is employee at MAGI EUREGIO and MAGISNAT. G. Marceddu is employee at MAGI EUREGIO. M. Bertelli is president of MAGI EUREGIO, MAGISNAT, and MAGI's LAB. M.C. Medori, A. Macchia, S. Cecchin, C. Micheletti, K. Dhuli, G. Madeo, G. Bonetti are employees at MAGI's LAB. M. Bertelli, M.R. Ceccarini, and P. Chiurazzi are patent inventors (US20220362260A11). M. Bertelli, P.E. Maltese, G. Marceddu, and S. Cecchin are patent inventors (US20230173003A1). M. Bertelli, K. Dhuli, and P.E. Maltese are patent inventors (WO2022079498A1). M. Bertelli, K. Donato, M.C. Medori, M.R. Ceccarini, T. Beccari, P. Chiurazzi, C. Micheletti, K. Dhuli, G. Bonetti, G. Marceddu are patent applicants (Application Number: 18/466.879). The remaining authors have no conflict of interest to disclose. Since the current study shares the same NGS panel for the genetic analysis as the study cited in Ref. 5 (Ceccarini MR, Precone V, Manara E, Paolacci S, Maltese PE, Benfatti V, Dhuli K, Donato K, Guerri G, Marceddu G, Chiurazzi P, Dalla Ragione L, Beccari T, Bertelli M. A next generation sequencing gene panel for use in the diagnosis of anorexia nervosa. Eat Weight Disord 2022; 27: 1869-1880), the authors amend the following sentence: "A subset comprising 163 genes from a dedicated Next-Generation Sequencing (NGS) panel was analyzed5" in "A subset comprising 163 genes from a dedicated Next-Generation Sequencing (NGS) panel, previously used in the study by Ceccarini et al5, was analyzed". The authors clarify that the analyzed patients of the two articles are completely independent. To clarify the data reported in Table II, the authors amend the following sentence: "Genetic variants identified in the AN population are reported in Table II." In "The genomic sequencing NGS was performed in all 135 patients recruited in the study. After obtaining the raw data, based on the ACMG guidelines (https://www.acmg.net/ACMG/Medical-Genetics-Practice-Resources/Practice-Guidelines.aspx), the results were filtered, and Table II reports the variants considered Pathogenic (P), likely pathogenic (LP), and Variable with Uncertain Significance (VUS), 61 patients in total". Consequently, to improve clarity, the legend of Table II has been amended as follows: Genetic variants identified in 61 patients out of the total 135 patients analyzed by NGS. There are amendments to this paper. The Publisher apologizes for any inconvenience this may cause. https://www.europeanreview.org/article/34692.

Topology-Based Detection and Tracking of Deadlocks Reveal Aging of Active Ring Melts

Connecting the viscoelastic behavior of stressed ring melts to the various forms of entanglement that can emerge in such systems is still an open challenge. Here, we consider active ring melts, where stress is generated internally, and introduce a topology-based method to detect and track consequential forms of ring entanglements, namely, deadlocks. We demonstrate that, as stress accumulates, more and more rings are co-opted in a growing web of deadlocks that entrap many other rings by threading, bringing the system to a standstill. The method ought to help the study of topological aging in more general polymer contexts.

Presence of viral spike protein and vaccinal spike protein in the blood serum of patients with long-COVID syndrome

OBJECTIVE

COVID-19 patients experience, in 10-20% of the cases, a prolonged long-COVID syndrome, defined as the persistence of symptoms for at least two months after the infection. The underlying biological mechanisms of this syndrome remain poorly understood. Several hypotheses have been proposed, among which are the potential autoimmunity resulting from molecular mimicry between viral spike protein and human proteins, the reservoir and viral reproduction hypothesis, and the viral integration hypothesis. Although official data state that vaccinal spike protein is harmless and remains at the site of infection, several studies proposed spike protein toxicity and found it in blood circulation several months after the vaccination. To search for the presence of viral and vaccine spike protein in a cohort of long-COVID patients.

PATIENTS AND METHODS

In this study, we employed a proteomic-based approach utilizing mass spectrometry to analyze the serum of 81 patients with long-COVID syndrome. Moreover, viral integration in patients' leukocytes was assessed with a preliminary study, without further investigation.

RESULTS

We identified the presence of the viral spike protein in one patient after infection clearance and negativity of COVID-19 test and the vaccine spike protein in two patients two months after the vaccination.

CONCLUSIONS

This study, in agreement with other published investigations, demonstrates that both natural and vaccine spike protein may still be present in long-COVID patients, thus supporting the existence of a possible mechanism that causes the persistence of spike protein in the human body for much longer than predicted by early studies. According to these results, all patients with long-COVID syndrome should be analyzed for the presence of vaccinal and viral spike protein.

Linking pathogenic and likely pathogenic gene variants to long-COVID symptoms

OBJECTIVE

Long-COVID is a clinical syndrome characterized by the presence of symptoms related to SARS-CoV-2 infection that persist for at least four weeks after recovery from COVID-19. Genetics have been proposed to play an important role in long-COVID syndrome onset. This study aimed to identify genetic pathogenetic and likely pathogenetic causative variants of Mendelian genetic diseases in patients with Long-COVID syndrome. Additionally, we aimed to establish an association between these genetic variants and the clinical symptoms manifested during long-COVID syndrome.

PATIENTS AND METHODS

95 patients affected by long-COVID syndrome were analyzed with a Next-Generation Sequencing (NGS) panel comprising 494 genes. The analyzed genes and the symptoms of the patients collected with an ad-hoc questionnaire were divided into four groups (cardiological, respiratory, immunological, and neurological). Finally, a statistical analysis comprising descriptive statistics, classification based on reported symptoms, and comparative analysis against a control group of healthy individuals was conducted.

RESULTS

12 patients resulted positive for genetic testing with an autosomal dominance (8) or autosomal recessive (4) inheritance, showing a higher prevalence of cardiovascular genetic diseases (9) in the analyzed cohort compared to the normal population. Moreover, the onset of the long-COVID syndrome and its cardiovascular manifestations was compliant with the onset reported in the literature for the identified genetic diseases, suggesting that COVID-19 could manifest late-onset genetic diseases associated with their appearance. Apart from the 12 positive patients, 57 were healthy carriers of genetic diseases. Analyzing the whole cohort, a statistical correlation between prevalent symptomatology and the gene class was established, suggesting an association between the genetic susceptibility of an individual and the possibility of developing specific long-COVID syndrome symptoms, especially cardiovascular symptoms. Furthermore, 17 genetic variants were identified in CFTR. Finally, we identified genetic variants in IFNAR2 and POLG, supporting their respective involvement in inflammation and mitochondria mechanisms, correlated with long-COVID syndrome according to literature data.

CONCLUSIONS

This study proposed COVID-19 to act as a manifest of underlying late-onset genetic diseases Mendelian associated with carrier status. Moreover, according to our results, mutations in cardiological genes are more present in patients who show cardiological symptoms during the syndrome. This underscores the necessity for cardiological investigation and genetic screening in long-COVID patients to address existing or potential clinical implications.

Metabolomic profiling of amino acid alterations in anorexia nervosa: implications for appetite regulation and therapeutic strategies

OBJECTIVE

Anorexia nervosa (AN), a severe psychiatric disorder primarily affecting adolescents and young adults, is characterized by extreme dietary restriction and distorted body image. While the psychological aspects of AN are well-documented, its intricate metabolic underpinnings remain less explored. We think that metabolomic analysis of hair samples emerges as a promising tool to unveil the complex physiological alterations in AN. This study aims to comprehensively profile amino acid concentrations in hair samples from AN patients and healthy controls. Additionally, it seeks to elucidate potential correlations between amino acid alterations and appetite dysregulation in AN, thereby shedding light on the physiological basis of this debilitating disorder.

PATIENTS AND METHODS

A total of 25 AN patients and 25 age-matched healthy controls were recruited for this study. Hair samples were collected, and metabolites were extracted and analyzed using high-resolution liquid chromatography-mass spectrometry. Clinical data and biochemical markers were also gathered to characterize participants' demographic and clinical profiles.

RESULTS

Metabolomic analysis revealed significant alterations in amino acid concentrations in AN patients compared to healthy controls. Notably, deficiencies in essential amino acids (EAAs) and branched-chain amino acids (BCAAs) were observed, highlighting potential contributors to muscle wasting and appetite dysregulation. Further analysis identified specific amino acids as robust biomarkers capable of distinguishing AN patients with high sensitivity and specificity.

CONCLUSIONS

This study unveils the complex metabolic disturbances associated with AN and underscores the role of amino acid dysregulation in the disorder's pathophysiology. The identified biomarkers hold promise for diagnostic screening and potential therapeutic interventions, opening avenues for personalized approaches in AN treatment. Ultimately, this research contributes to our understanding of chronic disorders through the lens of metabolomics and the chemosensory underpinnings of appetite regulation.

Serum proteomic profiling reveals potential inflammatory biomarkers in long-COVID patients: a comparative analysis with healthy controls

OBJECTIVE

The highly transmissible severe acute respiratory syndrome-Coronavirus-2 was responsible for the 2020 COVID-19 pandemic. COVID-19 mostly affects the respiratory system; however, this infection also affects several other organs. In addition, the sequelae of this disease affect patients for several months after recovery, resulting in long-COVID syndrome.

PATIENTS AND METHODS

In order to characterize the differences between healthy control individuals and long-COVID patients, proteomic profiling of the serum of both groups was performed by mass spectrometry. The obtained data were analyzed with multivariate and univariate statistical analyses.

RESULTS

Initially, performing a partial latent square discriminant analysis (PLS-DA) made it possible to identify thirty-three proteins of interest, which were then subjected to a receiver operating characteristic (ROC) analysis. Four proteins were identified as potential stand-alone biomarkers: Sirtuin 1, Natriuretic Peptide B, Hemopexin, and Arachidonate 5-Lipoxygenase. Moreover, a multivariate ROC analysis identified a panel of biomarkers composed of Natriuretic Peptide B, Anterior Gradient 2 Protein, Adiponectin, Endothelin Converting Enzyme 1, Interferon Induced Transmembrane Protein 1, Mannose Binding Lectin 2, Prostaglandin-Endoperoxide Synthase 2, Pirin, Prostaglandin Reductase 1 and Cystatin C.

CONCLUSIONS

The identified biomarkers are associated with inflammatory processes, corroborating literature evidence that long-COVID patients develop an inflammatory state that damages many tissues. Nevertheless, these data should be validated in a larger cohort.

Autoantibodies detection in patients affected by autoimmune retinopathies

OBJECTIVE

Autoimmune retinopathies (ARs) encompass a spectrum of immune diseases that are characterized by the presence of autoantibodies against retinal proteins in the bloodstream. These autoantibodies (AAbs) lead to a progressive and sometimes rapid loss of vision. ARs commonly affect subjects over 50 years of age, but also rare cases of kids under 3 years of age have been reported.

PATIENTS AND METHODS

In this study, 47 unrelated Caucasian patients were enrolled. All subjects showed negative cancer diagnoses and negative results in their genetic screenings. We studied 8 confirmed retinal antigens using Western blotting analysis, with α-enolase followed by carbonic anhydrase II being the two most frequently found in the patients' sera.

RESULTS

Nineteen patients were positive (40.4%), thirteen uncertain (27.7%), and fifteen were negative (31.9%). Their gender did not correlate with the presence of AAbs (p=0.409).

CONCLUSIONS

AAbs are responsible for retinal degeneration in some cases, while in others, they contribute to exacerbating the progression of the disease; however, their detection is crucial to reaching a better diagnosis and developing more effective treatments for these conditions. Moreover, finding good biomarkers is important not only for AR monitoring and prognosis, but also for helping with early cancer diagnosis.

Correlation between COVID-19 and air pollution: the effects of PM2.5 and PM10 on COVID-19 outcomes

OBJECTIVE

Given its effects on long-term illnesses, like heart problems and diabetes, air pollution may be among the reasons that led COVID-19 to get worse and kill a larger number of people. Experiments have shown that breathing in polluted air weakens the immune system, making it easier for viruses to enter the body and grow. Viruses may be able to survive in the air by interacting in complex ways with particles and gases. These interactions depend on the air's chemical makeup, the particles' electric charges, and environmental conditions like humidity, UV light, and temperature. Moreover, exposure to UV rays and air pollution may reduce the organism's production of antimicrobial molecules, thus supporting viral infections. More epidemiological studies are needed to determine what effects air pollution has on COVID-19. In this review, we will discuss how air pollutants such as PM2.5 and PM10 contribute to the transmission of COVID-19.

MATERIALS AND METHODS

We have used nine target cities in the Tuscany region to verify this certainty, and in all these cases, the air pollution factors were found to be strongly correlated with COVID-19 cases. For each city, we applied a multivariate analysis and found an appropriate model that better fits the data.

RESULTS

This review underlines that both short-term and long-term exposure to air pollution may be crucial exasperating factors for SARS-CoV-2 transmission and COVID-19 severity and lethality. The statistical analysis concludes that air pollution should be accounted for as a possible risk factor in future COVID-19 investigations, and it should be avoided as much as possible by the general population.

CONCLUSIONS

Our research highlighted the correlation between COVID-19 and air pollution. Reducing air pollution exposure should be one of the first measures against COVID-19 spread.

The potential preventive role of a dietary supplement containing hydroxytyrosol in COVID-19: a multi-center study

OBJECTIVE

COVID-19 is a disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which emerged as a global pandemic in 2019. Its main symptoms include fever, cough, fatigue, and, in severe cases, pneumonia, acute respiratory distress syndrome, and organ failure, which can be life-threatening. Various therapies have been proposed for treating COVID-19, among which antiviral drugs and monoclonal antibodies, but natural molecules have gained attention for their potential antiviral properties against various viral infections, including COVID-19. The use of hydroxytyrosol (HT), a polyphenol from the olive tree possessing antioxidant, anti-inflammatory, and anti-viral properties, has been proposed to reduce COVID-19 infection.

SUBJECTS AND METHODS

A total of 443 subjects were recruited from four centers, located in Albania, Germany, and Italy (Milan and Trento provinces). The participants were randomly assigned to receive either the dietary supplement containing HT or a placebo for a duration of one month.

RESULTS

Analysis of the study data revealed that, among the subjects who tested positive for COVID-19 during the study, 36% belonged to the group that received the dietary supplement containing HT, while 64% belonged to the placebo group. The difference was statistically significant. These findings suggest that the use of a dietary supplement containing HT may have a possible preventive effect against COVID-19 infection.

CONCLUSIONS

The study's results indicate that the dietary supplement containing HT shows promise as a possible preventive measure against COVID-19 infection. Large-scale, randomized clinical trials and animal studies could be useful to provide more definitive conclusions on HT's possible potential preventive effects against COVID-19, which could potentially supplement existing therapies and contribute to fighting COVID-19 infection.

Autoantibodies in patients with post-COVID syndrome: a possible link with severity?

OBJECTIVE

Coronavirus disease 2019 is an infectious disease associated with the respiratory system caused by the SARS-CoV-2 virus. Right now, an increasing number of patients with Post-COVID Syndrome show, without clear evidence of organ dysfunction, a plethora of severe symptoms, such as fatigue, pain, shortness of breath, cognitive impairment, and sleep disturbance. It has already been demonstrated that SARS-CoV-2 virus can disrupt the self-tolerance mechanism of the immune system, thus triggering autoimmune conditions. Several studies have recently documented the presence of autoantibodies in the sera of post-COVID patients, but until now, it is unclear whether the persistence of symptoms could be directly correlated with the presence of autoantibodies.

PATIENTS AND METHODS

In this study, serum autoantibodies (AAbs) levels against four G protein-coupled receptors in 78 patients with post-COVID syndrome have been analyzed. The AAbs investigated are clustered in two groups: adrenergic receptors (α1 and β2) and muscarinic acetylcholine receptors (M3 and M4).

RESULTS

At least one or more AAbs were detected in 60.3% (47/78) of patients diagnosed with post-COVID syndrome, whereas 37.2% (29/78) of patients were positive for all receptors investigated. Interestingly, a strong correlation has been found between AAbs and pain intensity feeling by the patients measured by Visual Analogic Scale. A significant association was also obtained with insomnia and AABS-positive patients.

CONCLUSIONS

The identification of AAbs and their correlation with pathological symptoms seriousness underly the possible role of AAbs as future therapeutic targets.

Omics sciences and precision medicine in pancreas cancer

Abstract

Pancreatic cancer is a leading cause of death worldwide, associated with poor prognosis outcomes and late treatment interventions. The pathological nature and extreme tissue heterogeneity of this disease has hampered all efforts to correctly diagnose and treat it. Omics sciences and precision medicine have revolutionized our understanding of pan-creatic cancer, providing a new hope for patients suffering from this devastating disease. By analyzing large-scale biological data sets and developing personalized treatment strategies, researchers and clinicians are working together to improve patient outcomes and ultimately find a cure for pancreatic cancer.

X-linked genodermatoses from diagnosis to tailored therapy

Background

Genodermatoses are rare heterogeneous genetic skin diseases with multiorgan involvement. They severely impair an individual's well-being and can also lead to early death.

Methods

During the progress of this review, we have implemented a targeted research approach, diligently choosing the most relevant and exemplary articles within the subject matter. Our method entailed a systematic exploration of the scientific literature to ensure a compre-hensive and accurate compilation of the available sources.

Results

Among genodermatoses, X-linked ones are of particular importance and should always be considered when pediatric males are affected. Regardless of other syndromic forms without prevalence of skin symptoms, X-linked genodermatoses can be classified in three main groups: keratinization defects, pigmentation defects, and inflammatory skin diseases. Typical examples are dyskeratosis congenita, keratosis follicularis spinulosa decalvans, hypohidrotic ectodermal dysplasia, chondrodysplasia punctata, hypohidrotic ectodermal dysplasia, incontinentia pigmenti, chronic granulomatous disease, CHILD syndrome and ichthyosis. In this field, genetic diagnosis of the specific disease is important, also considering that numerous clinical trials of orphan drugs and genetic therapies are being proposed for these rare genetic diseases.

Conclusions

Thus, this chapter starts from clinical to molecular testing and ends with a review of all clinical trials on orphan drugs and gene therapy for genodermatoses.

Omics sciences and precision medicine in glioblastoma

Abstract

Glioblastoma is a highly aggressive and malignant type of brain cancer with a poor prognosis, despite current treatment options of surgery, radiation therapy, and chemotherapy. These treatments have limitations due to the aggressive nature of the cancer and the difficulty in completely removing the tumor without damaging healthy brain tissue. Personalized medicine, using genomic profiling to tailor treatment to the patient's specific tumor, and immunotherapy have shown promise in clinical trials. The blood-brain barrier also poses a challenge in delivering treatments to the brain, and researchers are exploring various approaches to bypass it. More effective, personalized treatment approaches are needed to improve outcomes for glioblastoma patients. This tumor is studied using genomics, transcriptomics, and proteomics techniques, to better understand its underlying molecular mechanisms. Recent studies have used these techniques to identify potential therapeutic targets, molecular subtypes, and heterogeneity of tumor cells. Advancements in omics sciences have improved our understanding of glioblastoma biology, and precision medicine approaches have impli-cations for more accurate diagnoses, improved treatment outcomes, and personalized preventive care. Precision medicine can match patients with drugs that target specific genetic mutations, improve clinical trials, and identify individuals at higher risk for certain diseases. Precision medicine, which involves customizing medical treatment based on an individual's genetic makeup, lifestyle, and environmental factors, has shown promise in improving treatment outcomes for glioblastoma patients. Identifying biomarkers is essential for patient stratification and treatment selection in precision medicine approaches for glioblastoma, and several biomarkers have shown promise in predicting patient response to treatment. Targeted therapies are a key component of precision medicine approaches in glioblastoma, but there is still a need to improve their effectiveness. Technical challenges, such as sample quality and availability, and challenges in analyzing and interpreting large amounts of data remain significant obstacles in omics sciences and precision medicine for glioblastoma. The clinical implementation of precision medicine in glioblastoma treatment faces challenges related to patient selection, drug development, and clinical trial design, as well as ethical and legal considerations related to patient privacy, informed consent, and access to expensive treatments.

Nutrigenomics: SNPs correlated to physical activity, response to chiropractic treatment, mood and sleep

Abstract

Nutrigenomics, a rapidly evolving field that bridges genetics and nutrition, explores the intricate interactions between an individual's genetic makeup and how they respond to nutrients. At its core, this discipline focuses on investigating Single Nucleotide Polymorphisms (SNPs), the most common genetic variations, which significantly influence a person's physiological status, mood regulation, and sleep patterns, thus playing a pivotal role in a wide range of health out-comes. Through decoding their functional implications, researchers are able to uncover genetic factors that impact physical fitness, pain perception, and susceptibility to mood disorders and sleep disruptions. The integration of nutrigenomics into healthcare holds the promise of transformative interventions that cater to individual well-being. Notable studies shed light on the connection between SNPs and personalized responses to exercise, as well as vulnerability to mood disorders and sleep disturbances. Understanding the intricate interplay between genetics and nutrition informs targeted dietary approaches, molding individual health trajectories. As research advances, the convergence of genetics and nourishment is on the brink of reshaping healthcare, ushering in an era of personalized health management that enhances overall life quality. Nutrigenomics charts a path toward tailored nutritional strategies, fundamentally reshaping our approach to health preservation and preventive measures.

Omics sciences and precision medicine in prostate cancer

Abstract

In the last decade, Prostate Cancer (PCa) has emerged as the second most prevalent and serious medical condition, and is considered one of the leading factors contributing to global mortality rates. Several factors (genetic as well as environmental) contribute to its development and seriousness. Since the disease is usually asymptomatic at early stages, it is typically misdiagnosed or over-diagnosed by the diagnostic procedures currently in use, leading to improper treatment. Effective biomarkers and diagnostic techniques are desperately needed in clinical settings for better management of PCa patients. Studies integrating omics sciences have shown that the accuracy and dependability of diagnostic and prognostic evaluations have increased because of the use of omics data; also, the treatment plans using omics can be facilitated by personalized medicine. The present review emphasizes innovative multi-omics methodologies, encompassing proteomics, genomics, microbiomics, metabolomics, and transcriptomics, with the aim of comprehending the molecular alterations that trigger and contribute to PCa. The review shows how early genomic and transcriptomic research has made it possible to identify PCa-related genes that are controlled by tumor-relevant signaling pathways. Proteomic and metabolomic analyses have recently been integrated, advancing our understanding of the complex mechanisms at play, the multiple levels of regulation, and how they interact. By applying the omics approach, new vulnerabilities may be discovered, and customized treatments with improved efficacy will soon be accessible.

Nutrigenomics: SNPs Correlated to Lipid and Carbohydrate Metabolism

Background

Nutrigenomics - the study of the interactions between genetics and nutrition - has emerged as a pivotal field in personalized nutrition. Among various genetic variations, single-nucleotide polymorphisms (SNPs) have been extensively studied for their probable relationship with metabolic traits.

Methods

Throughout this review, we have employed a targeted research approach, carefully handpicking the most representative and relevant articles on the subject. Our methodology involved a systematic review of the scientific literature to ensure a comprehensive and accurate overview of the available sources.

Results

SNPs have demonstrated a significant influence on lipid metabolism, by impacting genes that encode for enzymes involved in lipid synthesis, transport, and storage. Furthermore, they have the ability to affect enzymes in glycolysis and insulin signaling pathways: in a way, they can influence the risk of type 2 diabetes. Thanks to recent advances in genotyping technologies, we now know numerous SNPs linked to lipid and carbohydrate metabolism. The large-scale studies on this topic have unveiled the potential of personalized dietary recommendations based on an individual's genetic makeup. Personalized nutritional interventions hold promise to mitigate the risk of various chronic diseases; however, translating these scientific insights into actionable dietary guidelines is still challenging.

Conclusions

As the field of nutrigenomics continues to evolve, collaborations between geneticists, nutritionists, and healthcare providers are essential to harness the power of genetic information for improving metabolic health. By unraveling the genetic basis of metabolic responses to diet, this field holds the potential to revolutionize how we approach dietary recommendations and preventive healthcare practices.

Unraveling the Role of Prickly Pear Extract as a Potent Nutraceutical Agent Against Metabolic Syndromes

Background

Prickly pear (Opuntia) extracts have garnered con-siderable attention in recent years due to their promising medicinal and nutritional properties. This comprehensive review explores the multifaceted potential of prickly pear extracts in mitigating various chronic diseases, including cardiovascular diseases (CVDs), diabetes, obesity, cancer, neuronal diseases, and renal diseases.

Methods

This review provides a comprehensive overview of the diverse therapeutic applications of Opuntia extracts in managing chronic diseases. The collective evidence underscores the potential of prickly pear as a valuable natural resource for addressing global health challenges. Further research and clinical investigations are warranted to unlock the full potential of Opuntia in the prevention and treatment of chronic diseases.

Results

Studies have suggested that the bioactive compounds within prickly pear may influence glucose metabolism by improving insulin sensitivity, reducing insulin resistance, and modulating gut microbiota composition. These pathways exhibit potential in the reduction of hyperglycemia, which is a fundamental aspect of metabolic syndromes. Opuntia extracts demonstrate also antioxidant, anti-inflammatory capabilities that can contribute to improving health in various conditions.

Conclusion

Further research and clinical investigations are warranted to unlock the full potential of Opuntia in the prevention and treatment of chronic diseases.

Omics sciences and precision medicine in lung cancer

Abstract

Lung cancer is a complex disease, with a wide range of genetic alterations and clinical presentations. Understanding the natural and clinical history of the disease is crucial for developing effective diagnostic and treatment strategies. Omics approaches, such as genomics, transcriptomics, proteomics, and metabolomics, have emerged as powerful tools for understanding the molecular mechanisms underlying lung cancer and for identifying novel biomarkers and therapeutic targets. These approaches enable researchers to examine the entire genome, transcriptome, proteome, or metabolome of a cell or tissue, providing a comprehensive view of the biological processes involved in lung cancer development and progression. Targeted therapies that address specific genetic mutations and pathways hold promise for improving the diagnosis and treatment of this disease.

The Role of Olive Tree Polyphenols In The Prevention of COVID-19: A Scoping Review Part 2

Abstract

The recent COVID-19 pandemic caused by SARS-CoV-2 affected hundreds of millions of people and caused millions of deaths. There are few effective medications against SARS-CoV-2, and several studies attempted to make drugs based on natural components, such as olive leaves. Olive leaves are rich in polyphenolic compounds, which were proposed as a viable co-therapy supplement to treat and improve clinical symptoms in COVID-19 patients. Polyphenols have renown anti-inflammatory and multitarget antiviral effects on several virus families, which could be among the reasons of the beneficial effects of the Mediterranean diet against COVID-19. This scoping review is focused on the effect of olive tree polyphenols as a natural remedy to inhibit SARS-CoV-2, mainly discussing their influence on the process of viral entry into host cells by endocytosis.

Effects of Carob Extract on the Intestinal Microbiome and Glucose Metabolism: A Systematic Review and Meta-Analysis

Abstract

The legume tree known as carob (Ceratonia siliqua L.) is indigenous to the Mediterranean area and over the centuries its pods had been traditionally used mostly as animal feed. However, it has gained great attention in human nutrition due to the molecular compounds it contains, which could offer many potential health benefits: for example, carob is renowned for its high content of fiber, vitamins, and minerals. Moreover, in traditional medicine it is credited with the ability to control glucose metabolism and gut microbiome. Modern science has also extensively acknowledged the numerous health advantages deriving from its consumption, including its anti-diabetic, anti-inflammatory, and antioxidant properties. Due to its abundant contents of pectin, gums, and polyphenols (such as pinitol), carob has garnered significant attention as a well-researched plant with remarkable therapeutic properties. Notably, carob is extensively used in the production of semi-finished pastry products, particularly in ice cream and other creams (especially as a substitute for cocoa/chocolate): these applications indeed facilitate the exploration of its positive effects on glucose metabolism. Our study aimed at examining the effects of carob extract on intestinal microbiota and glucose metabolism. In this review, we conducted a thorough examination, comprising in vitro, in vivo, and clinical trials to appraise the consequences on human health of polyphenols and pectin from different carob species, including recently discovered ones with high polyphenol contents. Our goal was to learn more about the mechanisms through which carob extract can support a balanced gut flora and improve one's glucose metabolism. These results could influence the creation of novel functional foods and dietary supplements, to help with the management and prevention of chronic illnesses like diabetes and obesity.

Omics sciences and precision medicine in kidney cancer

Abstract

In the last decade, renal carcinoma has become more prevalent in European and North American regions. Kidney tumors are usually categorized based on histological features, with renal cell carcinoma being the most common subtype in adults. Despite conventional diagnostic and therapeutic strategies, a rise in cancer incidence and recurrence necessitates a fresh approach to diagnosing and treating kidney cancer. This review focuses on novel multi-omics approaches, such as genomics, transcriptomics, proteomics, metabolomics, and microbiomics, to better understand the molecular and clinical features of renal cell carcinoma. Studies integrating omics sciences have shown early promise in enhancing prognostic and therapeutic outcomes for various kidney cancer subtypes and providing insight into fundamental pathophysiological mechanisms occurring at different molecular levels. This review highlights the importance of utilizing omics sciences as a revolutionary concept in diagnostics and therapeutics and the clinical implications of renal cell carcinoma. Finally, the review presents the most recent findings from large-scale multi-omics studies on renal cell carcinoma and its associations with patient subtyping and drug development.

Characterization of somatic mutations in the pathogenesis of lipedema

Background

Lipedema, a complex and enigmatic adipose tissue disorder, remains poorly understood despite its significant impact on the patients' quality of life. Genetic investigations have uncovered potential contributors to its pathogenesis, including somatic mutations, which are nonheritable genetic alterations that can play a pivotal role in the development of this disease.

Aim

This review aims to elucidate the role of somatic mutations in the etiology of lipedema by examining their implications in adipose tissue biology, inflammation, and metabolic dysfunction.

Results

Studies focusing on leukocyte clones, genetic alterations like TET2 and DNMT3A, and the intricate interplay between adipose tissue and other organs have shed light on the underlying mechanisms driving lipedema. From the study of the scientific literature, mutations to genes correlated to three main pathways could be involved in the somatic development of lipedema: genes related to mitochondrial activity, genes related to localized disorders of subcutaneous adipose tissue, and genes of leukocyte clones.

Conclusions

The insights gained from these diverse studies converge to highlight the complex genetic underpinnings of lipedema and offer potential avenues for therapeutic interventions targeting somatic mutations to alleviate the burden of this condition on affected individuals.

Nutrigenomics: SNPs correlated to vitamins' deficiencies

Abstract

Nutrients can influence the physiological processes in the body by interacting with molecular systems. Including nutrigenetics and nutrigenomics, nutritional genomics focuses on how bio-active food components interact with the genome. The purpose of this study is to clarify how nutrigenomics and vitamin dietary deficits relate to one another. Food tolerances among human sub-populations are known to vary due to genetic variation, which may also affect dietary needs. This raises the prospect of tailoring a person's nutritional intake for optimum health and illness prevention, based on their unique genome. To better understand the interplay between genes and nutrients and to plan tailored weight loss, nutrigenetic testing may soon become a key approach.

Omics sciences and precision medicine in Urothelial Carcinoma

Abstract

This comprehensive review explores the potential of omics sciences - such as genomics, transcriptomics, proteomics, and metabolomics - in advancing the diagnosis and therapy of urothelial carcinoma (UC), a prevalent and heterogeneous cancer affecting the urinary tract. The article emphasizes the significant advancements in understanding the molecular mechanisms underlying UC development and progression, obtained through the application of omics approa-ches. Genomic studies have identified recurrent genetic alterations in UC, while transcriptomic analyses have revealed distinct gene expression profiles associated with different UC subtypes. Proteomic investigations have recognized protein biomarkers with diagnostic and prognostic potential, and metabolomic profiling has found metabolic alterations that are specific to UC. The integration of multi-omics data holds promises in refining UC subtyping, identifying therapeutic targets, and predicting treatment response. However, challenges like the standardization of omics technologies, validation of biomarkers, and ethical considerations need to be addressed to successfully translate these findings into clinical practice. Omics sciences offer tremendous potential in revolutionizing the diagnosis and therapy of UC, enabling more precise diagnostic methods, prognostic evaluations, and personalized treatment selection for UC patients. Future research efforts should focus on overcoming these challenges and translating omics discoveries into meaningful clinical applications to improve outcomes for UC patients.

Targeting Mast Cells: Sodium Cromoglycate as a Possible Treatment of Lipedema

Background

Mast cells are immune cells that mediate hypersensi-tivity and allergic reactions in the body, secreting histamine and other inflammatory molecules. They have been associated with different inflammatory conditions such as obesity and other adipose tissue di-sorders. Lipedema is a chronic disease characterized by an abnormal accumulation of adipose tissue on the legs and arms, pain, and other symptoms. Mast cells may play a role in the pathology of lipedema.

Objective

Pilot study to determine levels of histamine and its metabolites in lipedema subcutaneous adipose tissue (SAT) biopsy samples, and to test sodium cromoglycate for the treatment of mast cells in women with lipedema.

Methods

Biopsies from lipedema and control SAT were collected and analyzed histologically for the presence of mast cells. Mass spec-trometry was used to measure the levels of histamine, a key marker of mast cells, and its metabolites in SAT in women with lipedema and controls, and after a group of women with lipedema were administered oral and topical doses of sodium cromoglycate for two weeks.

Results

Histological examination of biopsies from lipedema patients confirmed the presence of mast cells. Metabolomic analysis revealed high levels of histamine and its metabolites in samples from women with lipedema compared to controls. Following a two-week treatment period, lipedema tissue samples exhibited reduced levels of histamine, suggesting a reduction of mast cell activity.

Conclusion

Sodium cromoglycate has the ability to stabilize mast cells and reduce histamine levels in lipedema patients, which could be useful in lowering the symptoms of lipedema.

Quantum-inspired encoding enhances stochastic sampling of soft matter systems

Quantum advantage in solving physical problems is still hard to assess due to hardware limitations. However, algorithms designed for quantum computers may engender transformative frameworks for modeling and simulating paradigmatically hard systems. Here, we show that the quadratic unconstrained binary optimization encoding enables tackling classical many-body systems that are challenging for conventional Monte Carlo. Specifically, in self-assembled melts of rigid lattice ring polymers, the combination of high density, chain stiffness, and topological constraints results in divergent autocorrelation times for real-space Monte Carlo. Our quantum-inspired encoding overcomes this problem and enables sampling melts of lattice rings with fixed curvature and compactness, unveiling counterintuitive topological effects. Tackling the same problems with the D-Wave quantum annealer leads to substantial performance improvements and advantageous scaling of sampling computational cost with the size of the self-assembled ring melts.

Topological Entanglement of Linear Catenanes: Knots and Threadings

We used molecular dynamics simulations to investigate the self-entanglements of the collapsed linear catenanes. We found two different types of topologically complex states. First, we observed numerous long-lived knotting events of the catenane backbone. However, comparison with conventional polymers reveals that knots are suppressed in catenanes. Next, we observed topologically complex states with no analogue in polymers, where a concatenated ring was threaded by other near or distal rings sliding through it. Differently from knots, these threaded states can disentangle by becoming fully tightened. A detailed thermodynamic and microscopic analysis is employed to rationalize the persistence of threaded states, which can survive significant internal reorganizations of the entire catenane. We finally discuss the broader implications of these previously unreported types of entanglements for other systems, such as noncollapsed and interacting catenanes.

RNA folding pathways from all-atom simulations with a variationally improved history-dependent bias

Atomically detailed simulations of RNA folding have proven very challenging in view of the difficulties of developing realistic force fields and the intrinsic computational complexity of sampling rare conformational transitions. As a step forward in tackling these issues, we extend to RNA an enhanced path-sampling method previously successfully applied to proteins. In this scheme, the information about the RNA's native structure is harnessed by a soft history-dependent biasing force promoting the generation of productive folding trajectories in an all-atom force field with explicit solvent. A rigorous variational principle is then applied to minimize the effect of the bias. Here, we report on an application of this method to RNA molecules from 20 to 47 nucleotides long and increasing topological complexity. By comparison with analog simulations performed on small proteins with similar size and architecture, we show that the RNA folding landscape is significantly more frustrated, even for relatively small chains with a simple topology. The predicted RNA folding mechanisms are found to be consistent with the available experiments and some of the existing coarse-grained models. Due to its computational performance, this scheme provides a promising platform to efficiently gather atomistic RNA folding trajectories, thus retain the information about the chemical composition of the sequence.

Structure and elasticity of model disordered, polydisperse, and defect-free polymer networks

The elasticity of disordered and polydisperse polymer networks is a fundamental problem of soft matter physics that is still open. Here, we self-assemble polymer networks via simulations of a mixture of bivalent and tri- or tetravalent patchy particles, which result in an exponential strand length distribution analogous to that of experimental randomly cross-linked systems. After assembly, the network connectivity and topology are frozen and the resulting system is characterized. We find that the fractal structure of the network depends on the number density at which the assembly has been carried out, but that systems with the same mean valence and same assembly density have the same structural properties. Moreover, we compute the long-time limit of the mean-squared displacement, also known as the (squared) localization length, of the cross-links and of the middle monomers of the strands, showing that the dynamics of long strands is well described by the tube model. Finally, we find a relation connecting these two localization lengths at high density and connect the cross-link localization length to the shear modulus of the system.

Nonequilibrium Thermodynamics of DNA Nanopore Unzipping

Using theory and simulations, we carried out a first systematic characterization of DNA unzipping via nanopore translocation. Starting from partially unzipped states, we found three dynamical regimes depending on the applied force f: (i) heterogeneous DNA retraction and rezipping (f<17  pN), (ii) normal (17  pN<f<60  pN), and (iii) anomalous (f>60  pN) drift-diffusive behavior. We show that the normal drift-diffusion regime can be effectively modeled as a one-dimensional stochastic process in a tilted periodic potential. We use the theory of stochastic processes to recover the potential from nonequilibrium unzipping trajectories and show that it corresponds to the free-energy landscape for single-base-pair unzipping. Applying this general approach to other single-molecule systems with periodic potentials ought to yield detailed free-energy landscapes from out-of-equilibrium trajectories.

Density-tunable pathway complexity in a minimalistic self-assembly model

An open challenge in self-assembly is learning how to design systems that can be conditionally guided towards different target structures depending on externally-controlled conditions. Using a theoretical and numerical approach, here we discuss a minimalistic self-assembly model that can be steered towards different types of ordered constructs at the equilibrium by solely tuning a facile selection parameter, namely the density of building blocks. Metadynamics and Langevin dynamics simulations allow us to explore the behavior of the system in and out of equilibrium conditions. We show that the density-driven tunability is encoded in the pathway complexity of the system, and specifically in the competition between two different main self-assembly routes. A comprehensive set of simulations provides insight into key factors allowing to make one self-assembling pathway prevailing on the other (or vice versa), determining the selection of the final self-assembled products. We formulate and validate a practical criterion for checking whether a specific molecular design is predisposed for such density-driven tunability of the products, thus offering a new, broader perspective to realize and harness this facile extrinsic control of conditional self-assembly.

Topological Friction and Relaxation Dynamics of Spatially Confined Catenated Polymers

We study catenated ring polymers confined inside channels and slits with Langevin dynamics simulations and address how the contour position and size of the interlocked or physically linked region evolve with time. We show that the catenation constraints generate a drag, or topological friction, that couples the contour motion of the interlocked regions. Notably, the coupling strength decreases as the interlocking is made tighter, but also shorter, by confinement. Though the coupling strength differs for channel and slit confinement, the data outline a single universal curve when plotted against the size of the linked region. Finally, we study how the relaxation kinetics changes after one of the rings is cut open and conclude that considering interlocked circular polymers is key for isolating the manifestations of topological friction. The results ought to be relevant for linked biomolecules in experimental or biological confining conditions.

Tunable Knot Segregation in Copolyelectrolyte Rings Carrying a Neutral Segment

We use Langevin dynamics simulations to study the knotting properties of copolyelectrolyte rings carrying neutral segments. We show that by solely tuning the relative length of the neutral and charged blocks, one can achieve different combinations of knot contour position and size. Strikingly, the latter is shown to vary nonmonotonically with the length of the neutral segment; at the same time, the knot switches from being pinned at the block's edge to becoming trapped inside it. Model calculations relate both effects to the competition between two adversarial mechanisms: the energy gain of localizing one or more of the knot's essential crossings on the neutral segment and the entropic cost of such localization. Tuning the length of the neutral segment sets the balance between the two mechanisms and hence the number of localized essential crossings, which in turn modulates the knot's size. This general principle ought to be useful in more complex systems, such as multiblock copolyelectrolytes, to achieve a more granular control of topological constraints.

Topological and physical links in soft matter systems

Linking, or multicomponent topological entanglement, is ubiquitous in soft matter systems, from mixtures of polymers and DNA filaments packedin vivoto interlocked line defects in liquid crystals and intertwined synthetic molecules. Yet, it is only relatively recently that theoretical and experimental advancements have made it possible to probe such entanglements and elucidate their impact on the physical properties of the systems. Here, we review the state-of-the-art of this rapidly expanding subject and organize it as follows. First, we present the main concepts and notions, from topological linking to physical linking and then consider the salient manifestations of molecular linking, from synthetic to biological ones. We next cover the main physical models addressing mutual entanglements in mixtures of polymers, both linear and circular. Finally, we consider liquid crystals, fluids and other non-filamentous systems where topological or physical entanglements are observed in defect or flux lines. We conclude with a perspective on open challenges.

Polymer Physics by Quantum Computing

Sampling equilibrium ensembles of dense polymer mixtures is a paradigmatically hard problem in computational physics, even in lattice-based models. Here, we develop a formalism based on interacting binary tensors that allows for tackling this problem using quantum annealing machines. Our approach is general in that properties such as self-avoidance, branching, and looping can all be specified in terms of quadratic interactions of the tensors. Microstates' realizations of different lattice polymer ensembles are then seamlessly generated by solving suitable discrete energy-minimization problems. This approach enables us to capitalize on the strengths of quantum annealing machines, as we demonstrate by sampling polymer mixtures from low to high densities, using the D-Wave quantum annealer. Our systematic approach offers a promising avenue to harness the rapid development of quantum machines for sampling discrete models of filamentous soft-matter systems.

Unfolding and Translocation of Knotted Proteins by Clp Biological Nanomachines: Synergistic Contribution of Primary Sequence and Topology Revealed by Molecular Dynamics Simulations

We use Langevin dynamics simulations to model, at an atomistic resolution, how various natively knotted proteins are unfolded in repeated allosteric translocating cycles of the ClpY ATPase. We consider proteins representative of different topologies, from the simplest knot (trefoil 3₁), to the three-twist 5₂ knot, to the most complex stevedore, 6₁, knot. We harness the atomistic detail of the simulations to address aspects that have so far remained largely unexplored, such as sequence-dependent effects on the ruggedness of the landscape traversed during knot sliding. Our simulations reveal the combined effect on translocation of the knotted protein structure, i.e., backbone topology and geometry, and primary sequence, i.e., side chain size and interactions, and show that the latter can dominate translocation hindrance. In addition, we observe that due to the interplay between the knotted topology and intramolecular contacts the transmission of tension along the polypeptide chain occurs very differently from that of homopolymers. Finally, by considering native and non-native interactions, we examine how the disruption or formation of such contacts can affect the translocation processivity and concomitantly create multiple unfolding pathways with very different activation barriers.

RNA Pore Translocation with Static and Periodic Forces: Effect of Secondary and Tertiary Elements on Process Activation and Duration

We use MD simulations to study the pore translocation properties of a pseudoknotted viral RNA. We consider the 71-nucleotide-long xrRNA from the Zika virus and establish how it responds when driven through a narrow pore by static or periodic forces applied to either of the two termini. Unlike the case of fluctuating homopolymers, the onset of translocation is significantly delayed with respect to the application of static driving forces. Because of the peculiar xrRNA architecture, activation times can differ by orders of magnitude at the two ends. Instead, translocation duration is much smaller than activation times and occurs on time scales comparable at the two ends. Periodic forces amplify significantly the differences at the two ends, for both activation times and translocation duration. Finally, we use a waiting-times analysis to examine the systematic slowing downs in xrRNA translocations and associate them to the hindrance of specific secondary and tertiary elements of xrRNA. The findings provide a useful reference to interpret and design future theoretical and experimental studies of RNA translocation.

essHi-C: Essential component analysis of Hi-C matrices

MOTIVATION

Hi-C matrices are cornerstones for qualitative and quantitative studies of genome folding, from its territorial organization to compartments and topological domains. The high dynamic range of genomic distances probed in Hi-C assays reflects in an inherent stochastic background of the interactions matrices, which inevitably convolve the features of interest with largely non-specific ones.

RESULTS

Here we introduce and discuss essHi-C, a method to isolate the specific, or essential component of Hi-C matrices from the non-specific portion of the spectrum that is compatible with random matrices. Systematic comparisons show that essHi-C improves the clarity of the interaction patterns, enhances the robustness against sequencing depth of topologically associating domains identification, allows the unsupervised clustering of experiments in different cell lines and recovers the cell-cycle phasing of single-cells based on Hi-C data. Thus, essHi-C provides means for isolating significant biological and physical features from Hi-C matrices.

AVAILABILITY

The essHi-C software package is available at: https://github.com/stefanofranzini/essHIC .

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Separation of Geometrical and Topological Entanglement in Confined Polymers Driven out of Equilibrium

We use Brownian dynamics simulations and advanced topological profiling methods to characterize the out-of-equilibrium evolution of self-entanglement in linear polymers confined into nanochannels and under periodic compression. By introducing suitable observables, we can distinguish two main forms of entanglement that we term geometrical and topological. The latter is measured by the number of (essential) crossings of the physical knot detected after a suitable bridging of the chain termini. The former is instead measured as the average number of times a linear chain appears to cross itself when viewed under all projections and is irrespective of the physical knotted state. The key discovery of our work is that these two forms of entanglement are uncoupled and evolve with distinct dynamics. While geometrical entanglement is typically in phase with the compression-elongation cycles and it is primarily sensitive to its force f, the topological measure is mildly sensitive to cyclic modulation but strongly depends on both compression force f and duration k. The findings could assist the interpretation of experiments using fluorescence molecular tracers to track physical knots in polymers. Furthermore, we identify optimal regions in the experimentally controllable parameter space in which to obtain more/less topological and geometrical entanglement; this may help designing polymers with targeted topology.

Directional translocation resistance of Zika xrRNA

xrRNAs from flaviviruses survive in host cells because of their exceptional dichotomic response to the unfolding action of different enzymes. They can be unwound, and hence copied, by replicases, and yet can resist degradation by exonucleases. How the same stretch of xrRNA can encode such diverse responses is an open question. Here, by using atomistic models and translocation simulations, we uncover an elaborate and directional mechanism for how stress propagates when the two xrRNA ends, [Formula: see text] and [Formula: see text], are driven through a pore. Pulling the [Formula: see text] end, as done by replicases, elicits a progressive unfolding; pulling the [Formula: see text] end, as done by exonucleases, triggers a counterintuitive molecular tightening. Thus, in what appears to be a remarkable instance of intra-molecular tensegrity, the very pulling of the [Formula: see text] end is what boosts resistance to translocation and consequently to degradation. The uncovered mechanistic principle might be co-opted to design molecular meta-materials.

Transcriptional supercoiling boosts topoisomerase II-mediated knotting of intracellular DNA

Recent studies have revealed that the DNA cross-inversion mechanism of topoisomerase II (topo II) not only removes DNA supercoils and DNA replication intertwines, but also produces small amounts of DNA knots within the clusters of nucleosomes that conform to eukaryotic chromatin. Here, we examine how transcriptional supercoiling of intracellular DNA affects the occurrence of these knots. We show that although (−) supercoiling does not change the basal DNA knotting probability, (+) supercoiling of DNA generated in front of the transcribing complexes increases DNA knot formation over 25-fold. The increase of topo II-mediated DNA knotting occurs both upon accumulation of (+) supercoiling in topoisomerase-deficient cells and during normal transcriptional supercoiling of DNA in TOP1 TOP2 cells. We also show that the high knotting probability (P^kn ≥ 0.5) of (+) supercoiled DNA reflects a 5-fold volume compaction of the nucleosomal fibers in vivo. Our findings indicate that topo II-mediated DNA knotting could be inherent to transcriptional supercoiling of DNA and other chromatin condensation processes and establish, therefore, a new crucial role of topoisomerase II in resetting the knotting–unknotting homeostasis of DNA during chromatin dynamics.