Presynaptic Dopaminergic Imaging Characterizes Patients with REM Sleep Behavior Disorder Due to Synucleinopathy.

OBJECTIVE: To apply a machine learning analysis to clinical and presynaptic dopaminergic imaging data of patients with rapid eye movement (REM) sleep behavior disorder (RBD) to predict the development of Parkinson disease (PD) and dementia with Lewy bodies (DLB). METHODS: In this multicenter study of the International RBD study group, 173 patients (mean age 70.5 ± 6.3 years, 70.5% males) with polysomnography-confirmed RBD who eventually phenoconverted to overt alpha-synucleinopathy (RBD due to synucleinopathy) were enrolled, and underwent baseline presynaptic dopaminergic imaging and clinical assessment, including motor, cognitive, olfaction, and constipation evaluation. For comparison, 232 RBD non-phenoconvertor patients (67.6 ± 7.1 years, 78.4% males) and 160 controls (68.2 ± 7.2 years, 53.1% males) were enrolled. Imaging and clinical features were analyzed by machine learning to determine predictors of phenoconversion. RESULTS: Machine learning analysis showed that clinical data alone poorly predicted phenoconversion. Presynaptic dopaminergic imaging significantly improved the prediction, especially in combination with clinical data, with 77% sensitivity and 85% specificity in differentiating RBD due to synucleinopathy from non phenoconverted RBD patients, and 85% sensitivity and 86% specificity in discriminating PD-converters from DLB-converters. Quantification of presynaptic dopaminergic imaging showed that an empirical z-score cutoff of -1.0 at the most affected hemisphere putamen characterized RBD due to synucleinopathy patients, while a cutoff of -1.0 at the most affected hemisphere putamen/caudate ratio characterized PD-converters. INTERPRETATION: Clinical data alone poorly predicted phenoconversion in RBD due to synucleinopathy patients. Conversely, presynaptic dopaminergic imaging allows a good prediction of forthcoming phenoconversion diagnosis. This finding may be used in designing future disease-modifying trials. ANN NEUROL 2024;95:1178-1192.

Is cancer an intelligent species?

Some relevant emerging properties of intelligent systems are "adaptation to a changing environment," "reaction to unexpected situations," "capacity of problem solving," and "ability to communicate." Single cells have remarkable abilities to adapt, make adequate context-dependent decision, take constructive actions, and communicate, thus theoretically meeting all the above-mentioned requirements. From a biological point of view, cancer can be viewed as an invasive species, composed of cells that move from primary to distant sites, being continuously exposed to changes in the environmental conditions. Blood represents the first hostile habitat that a cancer cell encounters once detached from the primary site, so that cancer cells must rapidly carry out multiple adaptation strategies to survive. The aim of this review was to deepen the adaptation mechanisms of cancer cells in the blood microenvironment, particularly referring to four adaptation strategies typical of animal species (phenotypic adaptation, metabolic adaptation, niche adaptation, and collective adaptation), which together define the broad concept of biological intelligence. We provided evidence that the required adaptations (either structural, metabolic, and related to metastatic niche formation) and "social" behavior are useful principles allowing putting into a coherent frame many features of circulating cancer cells. This interpretative frame is described by the comparison with analog behavioral traits typical of various animal models.

Dormancy, stemness, and therapy resistance: interconnected players in cancer evolution.

The biological complexity of cancer represents a tremendous clinical challenge, resulting in the frequent failure of current treatment protocols. In the rapidly evolving scenario of a growing tumor, anticancer treatments impose a drastic perturbation not only to cancer cells but also to the tumor microenvironment, killing a portion of the cells and inducing a massive stress response in the survivors. Consequently, treatments can act as a double-edged sword by inducing a temporary response while laying the ground for therapy resistance and subsequent disease progression. Cancer cell dormancy (or quiescence) is a central theme in tumor evolution, being tightly linked to the tumor's ability to survive cytotoxic challenges, metastasize, and resist immune-mediated attack. Accordingly, quiescent cancer cells (QCCs) have been detected in virtually all the stages of tumor development. In recent years, an increasing number of studies have focused on the characterization of quiescent/therapy resistant cancer cells, unveiling QCCs core transcriptional programs, metabolic plasticity, and mechanisms of immune escape. At the same time, our partial understanding of tumor quiescence reflects the difficulty to identify stable QCCs biomarkers/therapeutic targets and to control cancer dormancy in clinical settings. This review focuses on recent discoveries in the interrelated fields of dormancy, stemness, and therapy resistance, discussing experimental evidences in the frame of a nonlinear dynamics approach, and exploring the possibility that tumor quiescence may represent not only a peril but also a potential therapeutic resource.

PCN-Miner: an open-source extensible tool for the analysis of Protein Contact Networks.

MOTIVATION: Protein Contact Network (PCN) is a powerful method for analysing the structure and function of proteins, with a specific focus on disclosing the molecular features of allosteric regulation through the discovery of modular substructures. The importance of PCN analysis has been shown in many contexts, such as the analysis of SARS-CoV-2 Spike protein and its complexes with the Angiotensin Converting Enzyme 2 (ACE2) human receptors. Even if there exist many software tools implementing such methods, there is a growing need for the introduction of tools integrating existing approaches. RESULTS: We present PCN-Miner, a software tool implemented in the Python programming language, able to (i) import protein structures from the Protein Data Bank; (ii) generate the corresponding PCN; (iii) model, analyse and visualize PCNs and related protein structures by using a set of known algorithms and metrics. The PCN-Miner can cover a large set of applications: from clustering to embedding and subsequent analysis. AVAILABILITY AND IMPLEMENTATION: The PCN-Miner tool is freely available at the following GitHub repository: https://github.com/hguzzi/ProteinContactNetworks. It is also available in the Python Package Index (PyPI) repository.

Role of brain 2-[18F]fluoro-2-deoxy-D-glucose-positron-emission tomography as survival predictor in amyotrophic lateral sclerosis.

PURPOSE: The identification of prognostic tools in amyotrophic lateral sclerosis (ALS) would improve the design of clinical trials, the management of patients, and life planning. We aimed to evaluate the accuracy of brain 2-[18F]fluoro-2-deoxy-D-glucose-positron-emission tomography (2-[18F]FDG-PET) as an independent predictor of survival in ALS. METHODS: A prospective cohort study enrolled 418 ALS patients, who underwent brain 2-[18F]FDG-PET at diagnosis and whose survival time was available. We discretized the survival time in a finite number of classes in a data-driven fashion by employing a k-means-like strategy. We identified "hot brain regions" with maximal power in discriminating survival classes, by evaluating the Laplacian scores in a class-aware fashion. We retained the top-m features for each class to train the classification systems (i.e., a support vector machine, SVM), using 10% of the ALS cohort as test set. RESULTS: Data were discretized in three survival profiles: 0-2 years, 2-5 years, and > 5 years. SVM resulted in an error rate < 20% for two out of three classes separately. As for class one, the discriminant clusters included left caudate body and anterior cingulate cortex. The most discriminant regions were bilateral cerebellar pyramid in class two, and right cerebellar dentate nucleus, and left cerebellar nodule in class three. CONCLUSION: Brain 2-[18F]FDG-PET along with artificial intelligence was able to predict with high accuracy the survival time range in our ALS cohort. Healthcare professionals can benefit from this prognostic tool for planning patients' management and follow-up. 2-[18F]FDG-PET represents a promising biomarker for individual patients' stratification in clinical trials. The lack of a multicentre external validation of the model warrants further studies to evaluate its generalization capability.

Stem cell-derived small extracellular vesicles embedded into methacrylated hyaluronic acid wound dressings accelerate wound repair in a pressure model of diabetic ulcer.

Over the past years, the development of innovative smart wound dressings is revolutionizing wound care management and research. Specifically, in the treatment of diabetic foot wounds, three-dimensional (3D) bioprinted patches may enable personalized medicine therapies. In the present work, a methacrylated hyaluronic acid (MeHA) bioink is employed to manufacture 3D printed patches to deliver small extracellular vesicles (sEVs) obtained from human mesenchymal stem cells (MSC-sEVs). The production of sEVs is maximized culturing MSCs in bioreactor. A series of in vitro analyses are carried out to demonstrate the influence of MSC-sEVs on functions of dermal fibroblasts and endothelial cells, which are the primary functional cells in skin repair process. Results demonstrate that both cell populations are able to internalize MSC-sEVs and that the exposure to sEVs stimulates proliferation and migration. In vivo experiments in a well-established diabetic mouse model of pressure ulcer confirm the regenerative properties of MSC-sEVs. The MeHA patch enhances the effectiveness of sEVs by enabling controlled release of MSC-sEVs over 7 days, which improve wound epithelialization, angiogenesis and innervation. The overall findings highlight that MSC-sEVs loading in 3D printed biomaterials represents a powerful technique, which can improve the translational potential of parental stem cell in terms of regulatory and economic impact.

Identifying toggle genes from transcriptome-wide scatter: A new perspective for biological regulation.

The study of gene expression variability, especially for cancer and cell differentiation studies, has become important. Here, we investigate transcriptome-wide scatter of 23 cell types and conditions across different levels of biological complexity. We focused on genes that act like toggle switches between pairwise replicates of the same cell type, i.e. genes expressed in one replicate and not expressed in the other, sometimes also referred as ON/OFF genes. The proportion of these toggle genes dramatically increases from unicellular to multicellular organization, especially for development and cancer cells. A relevant portion of toggle switches are non-coding genes: in unicellular systems the most represented classes are tRNA and rRNA, while multicellular systems more frequently show lncRNA, sncRNA and pseudogenes. Notably, disease associated microRNAs (miRNAs), pseudogenes and numerous uncharacterized transcripts are present in both development and cancer cells. On top of the known intrinsic and extrinsic factors, our work indicates toggle genes as a novel collective component creating transcriptome-wide variability. This requires further investigation for elucidating both evolutionary and disease processes.

Special Issue "Advances in Genome Regulation in Cancer".

Cancer is globally increasing [...].

Synchronization between Attractors: Genomic Mechanism of Cell-Fate Change.

Herein, we provide a brief overview of complex systems theory approaches to investigate the genomic mechanism of cell-fate changes. Cell trajectories across the epigenetic landscape, whether in development, environmental responses, or disease progression, are controlled by extensively coordinated genome-wide gene expression changes. The elucidation of the mechanisms underlying these coherent expression changes is of fundamental importance in cell biology and for paving the road to new therapeutic approaches. In previous studies, we pointed at dynamic criticality as a plausible characteristic of genome-wide transition dynamics guiding cell fate. Whole-genome expression develops an engine-like organization (genome engine) in order to establish an autonomous dynamical system, capable of both homeostasis and transition behaviors. A critical set of genes behaves as a critical point (CP) that serves as the organizing center of cell-fate change. When the system is pushed away from homeostasis, the state change that occurs at the CP makes local perturbation spread over the genome, demonstrating self-organized critical (SOC) control of genome expression. Oscillating-Mode genes (which normally keep genome expression on pace with microenvironment fluctuations), when in the presence of an effective perturbative stimulus, drive the dynamics of synchronization, and thus guide the cell-fate transition.

Spatial-Temporal Genome Regulation in Stress-Response and Cell-Fate Change.

Complex functioning of the genome in the cell nucleus is controlled at different levels: (a) the DNA base sequence containing all relevant inherited information; (b) epigenetic pathways consisting of protein interactions and feedback loops; (c) the genome architecture and organization activating or suppressing genetic interactions between different parts of the genome. Most research so far has shed light on the puzzle pieces at these levels. This article, however, attempts an integrative approach to genome expression regulation incorporating these different layers. Under environmental stress or during cell development, differentiation towards specialized cell types, or to dysfunctional tumor, the cell nucleus seems to react as a whole through coordinated changes at all levels of control. This implies the need for a framework in which biological, chemical, and physical manifestations can serve as a basis for a coherent theory of gene self-organization. An international symposium held at the Biomedical Research and Study Center in Riga, Latvia, on 25 July 2022 addressed novel aspects of the abovementioned topic. The present article reviews the most recent results and conclusions of the state-of-the-art research in this multidisciplinary field of science, which were delivered and discussed by scholars at the Riga symposium.

Molecular mechanisms of skin wound healing in non-diabetic and diabetic mice in excision and pressure experimental wounds.

Experimental models for chronic skin lesions are excision and pressure ulcer, defined as "open" and "closed" lesions, respectively, only the latter characterized by tissue hypoxia. Moreover, systemic diseases, such as diabetes mellitus, affect wound repair. Thus, models for testing new therapies should be carefully selected according to the expected targets. In this study, we present an extensive and comparative histological, immunohistochemical, and molecular characterization of these two lesions in diabetic (db/db) and non-diabetic (C57BL/6 J) mice. In db/db mice, we found significant reduction in PGP9.5-IR innervation, reduction of capillary network, and reduced expression of NGF receptors. We found an increase in VEGF receptor Kdr expression, and the PI3K-Akt signaling pathway at the core of the altered molecular network. Db/db mice with pressure ulcers showed an impairment in the molecular regulation of hypoxia-related genes (Hif1a, Flt1, and Kdr), while extracellular matrix encoding genes (Itgb3, Timp1, Fn1, Col4a1) were upregulated by hyperglycemia and lesions. Overall, the molecular analysis suggests that db/db mice have a longer inflammatory phase of the wound repair process, delaying the progression toward the proliferation and remodeling phases.

Biodynamic Interfaces Are Essential for Human-Environment Interactions.

The environment impacts human health in profound ways, yet few theories define the form of the relationship between human physiology and the environment. It is conjectured that such complex systems cannot interact directly, but rather their interaction requires the formation of an intermediary "interface." This position contrasts with current epidemiological constructs of causation, which implicitly assume that two complex systems transfer information directly while remaining separate entities. Further, it is contended that dynamic, process-based interfaces incorporate components from all the interacting systems but exhibit operational independence. This property has many consequences, the foremost being that characteristics of the interface cannot be fully resolved by only studying the systems involved in the interaction. The interface itself must be the subject of inquiry. Without refocusing the attention on biodynamic interfaces, how the environment impacts health cannot be discerned. Also see the video abstract here https://youtu.be/XeyjeZeyo4o.

Constraints Shape Cell Function and Morphology by Canalizing the Developmental Path along the Waddington's Landscape.

Studies performed in absence of gravitational constraint show that a living system is unable to choose between two different phenotypes, thus leading cells to segregate into different, alternative stable states. This finding demonstrates that the genotype does not determine by itself the phenotype but requires additional, physical constraints to finalize cell differentiation. Constraints belong to two classes: holonomic (independent of the system's dynamical states, as being established by the space-time geometry of the field) and non-holonomic (modified during those biological processes to which they contribute in shaping). This latter kind of "constraints", in which dynamics works on the constraint to recreate them, have emerged as critical determinants of self-organizing systems, by manifesting a "closure of constraints." Overall, the constraints act by harnessing the "randomness" represented by the simultaneous presence of equiprobable events restraining the system within one attractor. These results cast doubt on the mainstream scientific concept and call for a better understanding of causation in cell biology.

The Transcriptome and Proteome Networks of Malignant Tumours Reveal Atavistic Attractors of Polyploidy-Related Asexual Reproduction.

The expression of gametogenesis-related (GG) genes and proteins, as well as whole genome duplications (WGD), are the hallmarks of cancer related to poor prognosis. Currently, it is not clear if these hallmarks are random processes associated only with genome instability or are programmatically linked. Our goal was to elucidate this via a thorough bioinformatics analysis of 1474 GG genes in the context of WGD. We examined their association in protein-protein interaction and coexpression networks, and their phylostratigraphic profiles from publicly available patient tumour data. The results show that GG genes are upregulated in most WGD-enriched somatic cancers at the transcriptome level and reveal robust GG gene expression at the protein level, as well as the ability to associate into correlation networks and enrich the reproductive modules. GG gene phylostratigraphy displayed in WGD+ cancers an attractor of early eukaryotic origin for DNA recombination and meiosis, and one relative to oocyte maturation and embryogenesis from early multicellular organisms. The upregulation of cancer-testis genes emerging with mammalian placentation was also associated with WGD. In general, the results suggest the role of polyploidy for soma-germ transition accessing latent cancer attractors in the human genome network, which appear as pre-formed along the whole Evolution of Life.

Analysis of Dormancy-Associated Transcriptional Networks Reveals a Shared Quiescence Signature in Lung and Colorectal Cancer.

Quiescent cancer cells (QCCs) are a common feature of solid tumors, representing a major obstacle to the long-term success of cancer therapies. We isolated QCCs ex vivo from non-small cell lung cancer (NSCLC) and colorectal cancer (CRC) xenografts with a label-retaining strategy and compared QCCs gene expression profiles to identify a shared "quiescence signature". Principal Component Analysis (PCA) revealed a specific component neatly discriminating quiescent and replicative phenotypes in NSCLC and CRC. The discriminating component showed significant overlapping, with 688 genes in common including ZEB2, a master regulator of stem cell plasticity and epithelial-to-mesenchymal transition (EMT). Gene set enrichment analysis showed that QCCs of both NSCLC and CRC had an increased expression of factors related to stemness/self renewal, EMT, TGF-ß, morphogenesis, cell adhesion and chemotaxis, whereas proliferating cells overexpressed Myc targets and factors involved in RNA metabolism. Eventually, we analyzed in depth by means of a complex network approach, both the 'morphogenesis module' and the subset of differentially expressed genes shared by NCSLC and CRC. This allowed us to recognize different gene regulation network wiring for quiescent and proliferating cells and to underpin few genes central for network integration that may represent new therapeutic vulnerabilities. Altogether, our results highlight common regulatory pathways in QCCs of lung and colorectal tumors that may be the target of future therapeutic interventions.

Reconstruction of the Temporal Correlation Network of All-Cause Mortality Fluctuation across Italian Regions: The Importance of Temperature and Among-Nodes Flux.

All-cause mortality is a very coarse grain, albeit very reliable, index to check the health implications of lifestyle determinants, systemic threats and socio-demographic factors. In this work, we adopt a statistical-mechanics approach to the analysis of temporal fluctuations of all-cause mortality, focusing on the correlation structure of this index across different regions of Italy. The correlation network among the 20 Italian regions was reconstructed using temperature oscillations and traveller flux (as a function of distance and region's attractiveness, based on GDP), allowing for a separation between infective and non-infective death causes. The proposed approach allows monitoring of emerging systemic threats in terms of anomalies of correlation network structure.

A Statistical Journey through the Topological Determinants of the ß2 Adrenergic Receptor Dynamics.

Activation of G-protein-coupled receptors (GPCRs) is mediated by molecular switches throughout the transmembrane region of the receptor. In this work, we continued along the path of a previous computational study wherein energy transport in the ß2 Adrenergic Receptor (ß2-AR) was examined and allosteric switches were identified in the molecular structure through the reorganization of energy transport networks during activation. In this work, we further investigated the allosteric properties of ß2-AR, using Protein Contact Networks (PCNs). In this paper, we report an extensive statistical analysis of the topological and structural properties of ß2-AR along its molecular dynamics trajectory to identify the activation pattern of this molecular system. The results show a distinct character to the activation that both helps to understand the allosteric switching previously identified and confirms the relevance of the network formalism to uncover relevant functional features of protein molecules.

Translation, cross-cultural adaptation, and validation of the Italian version of the anterior cruciate ligament-return to sport after injury (ACL-RSI) scale and its integration into the K-STARTS test.

BACKGROUND: The timing of a return to sport (RTS) after anterior cruciate ligament reconstruction (ACLR) represents a major subject of debate in sports medicine practice. Recently, the Knee Santy Athletic Return to Sport (K-STARTS) composite test was validated. This consists of a battery of physical tests and a psychological evaluation using the anterior cruciate ligament-return to sport after injury scale (ACL-RSI). This study aimed to translate the ACL-RSI and K-STARTS from English to Italian and determine the scale's reliability and validity in an Italian context. METHODS: The translation and cultural adaptation process was performed according to the guidelines for the cross-cultural adaptation of self-report measures. The patients were asked to fill an anonymized online form created for this purpose that included the KOOS, the Lysholm, the IKDC-SKF, and the Italian translation of the ACL-RSI (ACL-RSI-It). After 1 week, the attendees were asked to repeat the ACL-RSI-It to investigate the test-retest reliability. RESULTS: The final study population comprised 115 patients who underwent ACLR, with a mean follow-up of 37.37 ± 26.56 months. The ACL-RSI-It showed axcellent internal consistency (Cronbach's α = 0.963), reliability (test-retest ICC = 0.966), and good construct validity (positive correlations with the other scales were above 75%). CONCLUSIONS: The ACL-RSI-It is valid, reliable, and comparable to the original English version of the questionnaire for Italian-speaking patients. It can be used to assess the psychological readiness of patients for a RTS after primary and unilateral ACLR, and can be integrated into the Italian K-STARTS test. LEVEL OF EVIDENCE: Level II.

Differentiating cancer cells reveal early large-scale genome regulation by pericentric domains.

Finding out how cells prepare for fate change during differentiation commitment was our task. To address whether the constitutive pericentromere-associated domains (PADs) may be involved, we used a model system with known transcriptome data, MCF-7 breast cancer cells treated with the ErbB3 ligand heregulin (HRG), which induces differentiation and is used in the therapy of cancer. PAD-repressive heterochromatin (H3K9me3), centromere-associated-protein-specific, and active euchromatin (H3K4me3) antibodies, real-time PCR, acridine orange DNA structural test (AOT), and microscopic image analysis were applied. We found a two-step DNA unfolding after 15-20 and 60 min of HRG treatment, respectively. This behavior was consistent with biphasic activation of the early response genes (c-fos - fosL1/myc) and the timing of two transcriptome avalanches reported in the literature. In control, the average number of PADs negatively correlated with their size by scale-free distribution, and centromere clustering in turn correlated with PAD size, both indicating that PADs may create and modulate a suprachromosomal network by fusing and splitting a constant proportion of the constitutive heterochromatin. By 15 min of HRG treatment, the bursting unraveling of PADs from the nucleolus boundary occurred, coinciding with the first step of H3K4me3 chromatin unfolding, confirmed by AOT. The second step after 60 min of HRG treatment was associated with transcription of long noncoding RNA from PADs and peaking of fosL1/c-myc response. We hypothesize that the bursting of PAD clusters under a critical silencing threshold pushes the first transcription avalanche, whereas the destruction of the PAD network enables genome rewiring needed for differentiation repatterning, mediated by early response bivalent genes.

NGF and Endogenous Regeneration: From Embryology Toward Therapies.

The self-repair ability of tissues and organs in case of injury and disease is a fundamental biological mechanism and an important therapeutic target. The tissue plasticity and the presence of adult stem cell niches open a new path in the development of pharmacological and non-pharmacological treatments finalized to improve the intrinsic regeneration.In this context, nerve growth factor (NGF) is widely studied for its capability of driving endogenous regeneration of ectoderm-derived tissues, directly acting on the cell targets and through the regulation of the stem cell niches. In fact, this growth factor is very promising for its key role in the development and multiplicity of the cellular targets.In this chapter, we have traveled across the recent history of NGF pleiotropic role in ectodermal tissue generation and repair, from embryonic development to skin wound healing, axonal regrowth, and remyelination.The better understanding of both the biological mechanisms underlying regeneration and the physiological role of NGF in development and injury response will open new therapeutic strategies, driven by the potential applications of this growth factor as an agent for improving endogenous regeneration processes.