Transcription regulation programs require the functional interaction of distal and proximal regulatory regions, interacting by specific 3D chromatin configurations. Enhancers are cis-acting regulatory elements able to promote gene expression regardless their orientation and distance from the transcription starting site. Their systematic mapping by genome-wide chromatin profiling and chromosome conformation analysis, combined with the development of gene-editing approaches to modulate their function, revealed that many enhancers work together to fine-tune the expression of their target genes. This review aim to describe the functions of different types of enhancers and the modalities of enhancers’ interaction, focusing on their role in the regulation of complex biological processes like cancer development.The control of gene expression at a transcriptional level requires a widespread landscape of regulatory elements. Central to these regulatory circuits are enhancers (ENHs), which are defined as cis-acting DNA elements able to increase the transcription of a target gene in a distance- and orientation-independent manner. ENHs are not independent functional elements but work in a complex and dynamic cooperative network, constituting the building blocks of multimodular domains of gene expression regulation. The information from each of these elements converges on the target promoter, contributing to improving the precision and sharpness of gene modulation. ENHs’ interplay varies in its nature and extent, ranging from an additive to redundant effect depending on contexts. Moving from super-enhancers that drive the high expression levels of identity genes, to shadow-enhancers, whose redundant functions contribute to buffering the variation in gene expression, this review aims to describe the different modalities of ENHs’ interaction and their role in the regulation of complex biological processes like cancer development. The human genome encodes the blueprint of human beings. Cell fates and complex body plans are established through an elaborate succession of signals that define multidimensional and precise patterns of gene expression . The samCentral to the precise execution of these multidimensional circuitries are the enhancers (ENHs) . They haSystematic mapping of ENHs by genome-wide chromatin profiling and chromosome conformation across cell types revealed that these elements outnumber genes by at least an order of magnitude, underlining the existence of multimodal cooperative, convergent and/or redundant relationships among them ,18. IndeCurrently, the understanding of the complicated nature of ENHs’ interplay is limited by a lack of genome-wide strategies for the systematic study of these elements in their native genomic context. However, the available information indicates that ENHs’ interplay varies in nature and extent, ranging from complete redundancy, like shadow-ENHs during embryonic development, to tight functional interdependence, as among the elements composing super-ENHs (SEs). The type of functional interaction among ENHs seems to be dictated by the function of the target gene in the cell-specific or time-specific context. During embryogenesis, shadow-ENHs are responsible for the regulation of genes that drive morphogenesis. Their redundancy serves to ensure phenotypic robustness and to buffer potential alteration and prevent deleterious developmental consequences ,23. MultInteraction modalities among ENHs seem to have evolved following the complexity of the system in which they operate to fulfill requirements of timely and highly differentiated expression modulations ,22. In cIn the present work, we aim to discuss the emerging evidence about the complexity of ENHs’ interplay and their context-specific effect on transcription regulation. We also report on the main features of the ENH networks and on the models that have been proposed to explain their function.In the functional study of the genome, ENHs represent a major challenge. While assigning each promoter to its target gene based on spatial proximity looks to be quite easy, far more complicated is to functionally annotate ENHs and to match them to their targets. Reporter assays, either for single or—when combined with high-throughput sequencing —multiple ENHs, and classical mutagenesis approaches have represented for long time the most powerful tool to explore transactivation properties of ENHs and to dissect their mechanism of action ,30,31,32(1)map ENHs and their functional status through the genome-wide analysis of specific DNA features such as the distribution of histone markers, chromatin modifiers, and TFs  ,36,37,38(2)detect the interactions between genomic elements in a 3D space, mapping the multi-connections established between functional elements independently of their linear distance  ,40,41;(3)interfere with the function of single or multiple ENHs to evaluate the context-specific effects at a global genomic level (CRISPR-based genome editing approaches) ,42,43,44Recent technical improvements have revolutionized the ability to study ENHs, enabling us to:Such information, exponentially multiplied for a massive number of different cell types and conditions, has rendered a picture of striking complexity. ENHs’ activity and their interconnections throughout the genome are dependent on highly specific modalities dictated by the cellular context and precise timing. This plasticity likely holds a large part of the secret of life and represents a source of diversification during development and complex diseases like cancer .Understanding the modalities of ENHs’ cooperation on a genome-wide scale and the consequences in terms of gene expression and complex phenotypes constitutes a fundamental goal of modern biology.The recent characterization of SEs supports the hypothesis that transcription is founded on ENHs’ teamwork. Studying the genomic distribution of master TFs in murine embryonic stem cells (mESC), Whyte and colleagues noticed the existence of scattered clusters of consecutive ENHs . At the SEs differ from classical ENHs in several ways. SEs have an average length that is an order of magnitude higher than canonical enhancers (10–60 Kb vs. 1–4 Kb). They are also characterized by higher levels of active chromatin markers such as H3K4me1 and H3K27ac and a higher occupancy of master TFs and RNA-PolII. In addition, SEs show an unusually high binding of chromatin organizers like BRD4 and components of the Mediator complex compared to classical ENHs ,25,26,47SEs are not static genomic elements but their existence is highly context dependent ,25,50. SConstituted by close stretches of single ENHs within a defined genomic region, SEs are organized as modular elements. Single regulatory units within SEs interact with each other and with the target transcription starting site (TSS), maximizing the transcriptional effect.Sierbsbaek et al. demonstrated that the single functional units constituting SEs have features of “TF hotspots”. Each of these elements cooperates in the constitution of SE by loading a rich repertoire of TFs , transcription activators, and co-activators , concentrating a high amount of transcriptional promoting factors on a precise genomic region, which modify the chromatin structure, maximizing transcriptional efficiency . In thisOCT4 affects the expression of SE-associated genes in mESC [Within SEs, single regulatory modules are generally not redundant and establish complex interactions producing specific outputs . Each mo in mESC .CTCF dimers and cohesins [To avoid leaking to unrelated neighboring genes, SEs usually reside near their target TSS within specialized chromosome domains with features of a topologically associating domain (TAD). These SE target-domains do not establish contacts outside the TAD and appear as chromosome loops, the boundaries of which are maintained by cohesins ,54,55  MYC overexpression is driven by a NOTCH1-dependent SE located 1427 Kb downstream of the MYC locus [SWI/SNF-dependent SE located 1.7 Kb downstream of the MYC locus [MYC upregulation depends on a RUNX2-associated and IgH lineage-specific SE [MYC regulation requires a CTCF binding site 2 Kb upstream of the MYC promoter to allow the interaction of the SE with the proximal cis-acting regulatory elements [∂Np63 SEs characterizes the aggressive squamous variant of pancreatic cancer and is associated with poor survival [The plastic use of SEs in cancer is not limited to the need for timely rewire transcription in response to specific conditions. In case of essential genes, different types of cancer use different SEs to drive their activation. The best example is the YC locus , while iYC locus . Finallycific SE ,67. In aelements . Intereselements . Similarsurvival .Cancer is a genetic disease that evolves through the progressive accumulation of mutations and genomic alterations. Similar to what happens for the coding part of the genome, where DNA aberrations may change the function of crucial proteins, genetic alterations may modify the functional status of a non-coding element, leading to the generation of novel SEs.KLF5 DNA-binding domain alters the DNA-binding specificity and causes the formation of new SEs in the FOXE1, NAMPT, EPHB3, and GASB oncogenes [Point mutations in non-coding DNA regions can generate de-novo TF binding sites, priming their binding and the downstream cascade of events, leading to SE formation . As wellncogenes .KLF5 and KLF12 was described in distinct types of tumors as responsible for the acquisition of KLF5 SE [Focal amplifications within a chromosome can result in new SEs. Amplification in the intergenic region between  KLF5 SE .TAL1 locus creates a new binding site for MYB, with the subsequent formation of a new SE that drives TAL1 overexpression [New SEs can arise from small insertions/deletions or point mutations that create new TF binding sites. In T-cell acute lymphoblastic leukemia, an insertion in the pression .MYC under the control of RUNX2 SEs [CTCF binding sites has been described as the cause of the ectopic SE-promoter interactions determining proto-oncogenes’ overexpression [Chromosome rearrangements, such as translocations, large deletions, or inversions, determine the relocation of the genetic loci within the genome. In many cases, these structural alterations have been shown to translocate the locus of an oncogene near to a pre-existing SE, resulting in its overexpression ,73,74,75UNX2 SEs . The spepression .The discovery of SEs profoundly modified our way of imagining transcription regulation and opened up new perspectives to understand the complex molecular mechanisms that govern genome function. Bringing together multiple ENHs in the same genomic space can exponentially increase the transcriptional strength of these regulatory elements through internal cooperation and boosted transcription of peculiar sets of key genes. However, after an initial phase of enthusiasm, critics questioned this model according to which the high transcriptional performance of SEs primarily relies on cooperation among single constituents, rather than on their intrinsic transcriptional capacity ,76.Early works demonstrated that single elements within SEs are more enriched in MED1, BRD4, and H3K27ac than classical ENHs, suggesting that the intrinsic properties of these elements could be relevant in determining SE transcriptional strength. Furthermore, luciferase assays demonstrated that fragments of SEs can drive luciferase activities more efficiently than classical ENHs, consolidating this hypothesis . FinallyBased on this information, a question remains open: are SEs new functional paradigms in gene expression regulation, or is their activity just the result of clustering together multiple classical ENHs ? The truIn this regard, improving our ability to functionally target these elements on a genome-wide scale will be fundamental.MYC ENHs represent one of the best examples of plasticity and cooperation. Beside the previously described SEs, multiple additional regulatory elements have been described in a 3 Mb TAD surrounding the MYC gene [MYC TSS and each able to transactivate it in a luciferase assay. Deletion of each one of these elements led to a strong effect on MYC expression and on cancer cell proliferation, indicating that each of these seven interspersed ENHs is required to sustain MYC’s robust expression in this setting [RUNX2 expression in thyroid and breast cancer [RUNX2 genomic locus as potential regulatory elements of this gene. A luciferase assay and histone modification profiling defined that three  of these were active and able to transactivate the RUNX2 proximal (P2) promoter in both breast and thyroid cancer cell lines. Also, 3C experiments showed that these three ENHs interact with the RUNX2 P2 promoter. CRISPR/Cas9-mediated depletion of these elements demonstrated that loss of function of each of them caused a dramatic drop of RUNX2 expression without affecting syntenic SUPT3H expression. As already proven for other examples of ENHs’ cooperative interactions, the activity of these elements was coordinated by the same TF (c-JUN) that binds and controls each of these elements, but choosing different transcription partners. In this way, different signals can converge on the same mechanism to induce RUNX2 upregulation [RUNX2 expression in thyroid and breast cancer can be functionally relevant in other settings using different types of interplays.The discovery of SEs demonstrated that closely spaced regulatory elements functionally connect to form higher-order and more efficient regulatory units. The genome is not a mono-dimensional entity but occupies a three-dimensional space in which elements, even if located at a great distance on the linear sequence, are brought together by chromatin folding ,83,84. TMYC gene ,68. With setting . We recet cancer . Fourteegulation  , partaking in a 3D chromosome loop with an MYC promoter. Targeting this element with sgRNA for CRISPRi does not impact MYC expression, suggesting it holds a secondary redundant role in driving MYC transcription [The additive models discussed above are unable to fully recapitulate the complexity of long-range ENHs’ interactions. The genome wide CRISPRi approaches revealed that some elements of the ENHs’ network have redundant functions, appearing not to be essential for the target gene’s transcriptional regulation ,21. In acription .Shavenbaby expression, allowing the correct trichomes’ development in an embryo grown at suboptimal temperatures or with a reduction of Wingless signaling [SNAIL, conferring phenotypic stability in growth temperatures of 37 °C [ATOH7 ENH impairs the retinal development and causes nonsyndromic congenital retinal nonattachment [HOXB cluster [PAX6, which drives stemness in lung cancer adenocarcinoma [Regulatory elements’ redundancy appears to be a pervasive feature of gene expression regulation, particularly evident in embryonic development ,94. In Dignaling . Furtherof 37 °C . In mammof 37 °C ,98,101. tachment . Little  cluster , known f cluster ,105. As arcinoma , has beearcinoma . The proarcinoma . In thesarcinoma .Kruppel pair of ENHs, the interaction modalities of which switch along the anterior-posterior axis of the embryo. While these two regulatory elements act anteriorly in a synergic manner, posteriorly, the distal shadow ENH attenuates the primary one, drawing the posterior boundary of the Kruppel gene expression profile [Overall, ENHs may functionally interact in many different ways that result in a variety of effects that range from additive to sub-additive (in the case of negative interference of secondary-ENHs on the primary element) to redundant. To attempt to define common rules that may explain such complexity, Bothma and colleagues developed a mathematical model proposing that ENHs’ behavior depends on the strength of their interaction with the target promoter. Weak ENHs contact a target promoter with a low frequency. Thus, they likely contribute to gene expression in an additive way to primary elements. By contrast, strong ENHs have highly frequent interactions and compete for their target promoter, thus resulting in a sub-additive relationship . The sam profile ,111.Considering the organizational differences, proximal or long-range ENHs’ interactions rely on the same foundation and achieve the same functional output . Either ENHs are organized as modular elements hosting many sequential binding sites and loading many molecules of cooperative transcription regulators that are themselves organized as multi-domain modular structures ,112,113.Bringing together several ENHs drastically amplifies the spatial density of these functional modules, increasing the number of occasions od protein-protein or protein-nucleic acids’ cooperative contact ,25,26. RHnisz and colleagues proposed a mathematical model to explain SE assembly and function based on the number and valency of the interactions among components. According to this model, phase separation is a function of valency that expresses the number of residues in each molecule taking part in the SE assembly, which can potentially be modified and/or engaged in a cross-link with other components . The perThis liquid-liquid phase separation model could also provide an explanation for the way the same ENH can promote the synchronous boosting of two separated promoters, conceptualizing the incorporation of both target promoters within the same droplet-assembly triggered by the regulatory unit.Cramer extended this concept, theorizing that not just transcription initiation but also elongation occurs through transient condensates. The machinery that allows progression of RNA-PolII along the gene body during transcription is a high-density complex in which the reciprocal interaction between proteins and nucleic acids promotes a phase separation similar to the one that occurs at the TSS . RNA-PolVis unita fortior”, that is “union is strenght”.The genome is an operating platform. It receives multiple signals from the surrounding environment and integrates them to generate adequate responses in a very short time with highly efficient modalities. Within this system, cooperation between ENHs is the operating language that allows the precise execution of the program, guaranteeing plasticity of the system and rigor in the implementation of procedures. As the Ancient Romans used to say, “


In neurodegenerative diseases, neurodegeneration has been related to several mitochondrial dynamics imbalances such as excessive fragmentation of mitochondria, impaired mitophagy, and blocked mitochondria mitochondrial transport in axons. Mitochondria are dynamic organelles, and essential for energy conversion, neuron survival, and cell death. As mitochondrial dynamics have a significant influence on homeostasis, in this review, we mainly discuss the role of mitochondrial dynamics in several neurodegenerative diseases. There is evidence that several mitochondrial dynamics-associated proteins, as well as related pathways, have roles in the pathological process of neurodegenerative diseases with an impact on mitochondrial functions and metabolism. However, specific pathological mechanisms need to be better understood in order to propose new therapeutic strategies targeting mitochondrial dynamics that have shown promise in recent studies. Neurodegenerative diseases are a kind of incurable and devastating neurological disorders, in these diseases, neurons gradually lose their function and ultimately cause death. The increased longevity of people’s lives has contributed to a rising incidence rate of neurodegenerative disorders associated with aging over the past 50 years. Due to the complexity of brain function, disease-modifying treatments of neurodegenerative diseases remain elusive despite concerted attempts to rescue brain energy, counter neuroinflammation or neurotoxic protein.Mitochondria undergoing coordinated cycles of fission and fusion, the balance of fission/fusion events is referred to as the “mitochondrial dynamic.” Energy for neurons is provided by mitochondria, who generate adenosine triphosphate (ATP) via oxidative phosphorylation. Excessive fragmentation or dysfunction of mitochondria may have an impact on the ATP biogenesis and lead to mitochondrial dysfunction, which can be disastrous for the survival viability of neurons. In this review, three mitochondrial dynamic related events are discussed: the fusion/fission event, movement within the neuronal axon, and disintegration of mitochondria (mitophagy).Due to the essential nature of mitochondrial functions, excessive mitochondrial fission leads to brain dysfunction. Characteristic hallmarks in the brains of patients with neurodegenerative diseases such as the accumulation of a-synuclein, hyperphosphorylated tau, and amyloid beta (Aβ) plaques, have been proven to be related to the activity of mitochondrial fission proteins. We focus on the impaired mitophagy pathway represented by PINK/parkin defects in neurodegenerative diseases, the important role of the ubiquitin protease system (UPS), and the potential connection between mitochondrial dynamics and the pathological process of neurodegenerative diseases. In addition to its role in quality control, deficiencies in PINK/Parkin may also lead to neuroinflammation, thus exacerbating neurodegenerative disease progression. The mechanisms of mitochondrial dynamics cause an imbalance in several neurodegenerative diseases and allow us to have a better understanding of the pathogenesis, while altered peripheral blood mitochondrial dynamics provide a potential diagnostic approach for Alzheimer’s disease.Finally, we propose possible future research directions for mitochondrial dynamics and consider the challenge of translating promising therapeutic targets toward the dual goals of symptom relief and disease modification in Neurodegenerative diseases.Mitochondrial fission and fusion play critical roles in creating new mitochondria and removing damaged mitochondria. In mammalian cells, fission/fusion events are mainly mediated by several large dynamin-related GTPase proteins, including conserved dynamin-related GTPase (Drp1), conserved dynamin-related GTPase mitofusion (Mfn), and optic dominant atrophy 1 (Opa1). In addition to the GTPase activity of these proteins, fission/fusion processes are regulated by multiple mechanisms, and this review provides a short description of the mechanisms that control mitochondrial fission and fusion.In the initial stage of mitochondrial fission, the endoplasmic reticulum (ER) makes contact with the outer mitochondrial membrane (OMM) at the ER-mitochondria contact sites (EMCS) and causes mitochondrial constrictions  Figure . Some miPost-translational modification is an important mechanism for GTPase activation, phosphorylation of Drp1 is the most widely discussed example. During mitosis, serine 616 on the GED of Drp1 is phosphorylated by cdk1/cyclin B kinase, stimulating its oligomerization and results in mitochondrial fission . InteresMitochondrial fusion includes two inseparable progressions. In mammals, OMM fusion is ensured by Mfn1 and Mnf2– dynamin-like GTPases with conserved catalytic domains and the fusion of the inter mitochondrial membrane (IMM) is mediated by OPA1 and mitochondria-specific cardiolipin (CL) .Similarly, the GTPase activity of Mfn1 is regulated by ubiquitination and acetylation, Mfn2 can also be ubiquitinated . Long foNotably, IMM fusion occurs downstream of OMM fusion, and OPA1-mediated IMM fusion depends on Mfn2 but not Mfn1 , Mfn1 anThe role of phospholipids like cardiolipin (CL) and phosphatidic acid (PA) in remodeling and regulating mitochondrial dynamics has been revealed in past research . PA can A recent study shows other substances that affect mitochondrial dynamics include ceramides (C18 and C16), CerS1, ER/mitochondria trafficking, and sphingosine-1-phosphate in mitochondria . Other sMitochondria are commonly known as the “powerhouse” of the cell. This is beause mitochondrial quality is important for energy production. In 2005, the scientific community first proposed the term “Mitophagy” to describe a subcellular process involving specific sequestering and degradation of the aged and damaged mitochondria. In normal physiological conditions, mitochondria maintain the quality control process via mitophagy to replenish vital macromolecular precursors for cells and protect against both neuronal cell death and the accumulation of dysfunctional mitochondria simultaneously . On the Previous studies strongly focus on the partnership between the PINK1[Phosphatase and Tensin homologue (PTEN)-induced kinase 1] and the ubiquitin E3 ligase Parkin. Mutations in this cytoprotective PINK-Parkin pathway are a common cause of Parkinsons disease . Under cAdditional E3 ligases other than Parkin –such as Mitochondrial ubiquitin ligase 1 (MUL1) – can ubiquitinate mitochondrial membrane proteins and inhibit the mutant phenotypes of Parkin in the ubiquitin-mediated pathway . KnockinMitochondrial molecular mechanisms of the PINK1-independent pathway have been revealed by studies in human cell lines and animal models . On the In addition to receptor-mediated or ubiquitin-mediated mitophagy, the roles of non-selective mitochondrial clearance, the endosome-lysosome pathway, and mitochondrial derived vesicles (MDV) in mitochondrial quality control processes have attracted the attention of researchers. The latter two maintain mitochondrial health by transporting impaired mitochondria to lysosomes for degradation or selective clearance of the impaired parts of mitochondria . These pMitochondria serve as local energy sources and maintain various essential functions at synaptic terminals. Lack of synaptic mitochondria is a common feature of some instances of age-related neurodegeneration. Because neuronal synapses require healthy mitochondria to maintain their functions, the transport and degradation of damaged mitochondria and the correct distribution of healthy mitochondria are essential processes.The mechanism underlying mitochondrial maintenance at synaptic terminals is poorly understood. Newly synthesized organelles should transport along the axon to supplement mitochondria at the remote end of the axon . In prevSimilarly, retrograde transport may also be essential to mitochondrial clearance and repair. The latest research shows mitophagy coordination with retrograde transport of mitochondria . Three pThe bidirectional movement of axonal mitochondria via long-distance transportation is regulated by mitochondrial Rho (Miro) and trafficking kinesin-binding protein (TRAK)1 and 2 . InteresAlzheimer’s disease (AD) is characterized by the progressive loss of cholinergic neurons in brain regions that are critical for memory, language, and learning, resulting in early memory loss, which can even progress to broad cognitive impairment. Two major hallmarks of AD are hyperphosphorylated tau and amyloid beta (Aβ) plaques in Neurofibrillary tangle . By the Impairment of Mitochondrial quality control is an early salient feature in susceptible neurons of an AD patient brain, characterized by distinct mitochondrial fragmentation, abnormal mitochondrial distribution, and mitochondrial dysfunction , culminaIn the early stage of AD, studies have revealed that there is a greater increase in Drp1 compared to Marf (homologous to human MFN2) expression. However, with disease progression, both Mfn2 and Mfn1 levels are downregulated markedly in the brain of AD patients . A reducThe expression of PINK1 was markedly lower in the brains of patients with AD or APP transgenic mice than controls . AD modeAccumulating experimental data suggest that the impairment of the PINK/Parkin-dependent or -independent mitophagy pathway is critical in AD pathology. Here, some outstanding questions deserve further exploration—Is defective mitophagy in AD an early preceding event and cause of the subsequent accumulation of toxic proteins? What are other possible molecular mechanisms of defective mitophagy in AD?Neuroinflammation is a common pathological feature of neurodegeneration. Immune training induced by peripheral inflammatory stimuli exacerbates cerebral β-amyloidosis . MitophaIn addition to the brain, peripheral tissues can also generate Aβ, and the hypothesis that Alzheimer’s disease is a systemic disease has been proposed. Using a model of parabiosis between AD mice and controls, researchers observed that Aβ entered the brains of wild mice and subsequently formed Aβ plaques . ClinicaParkinson’s Disease  neurons in the substantia nigra and the accumulation of a-synuclein in DA neurons, characterized by a deficit in a patient’s ability to move . Mutant Fly models of PINK1 and Parkin mutations summarize the dominant hallmarks of PD, including mitochondrial dysfunction, motor impairment, loss of dopaminergic neurons, and shortened lifespan , impairmA critical mechanism by which Parkin activation is regulated is ubiquitination, which is dependent on the ubiquitination of ubiquitinating enzymes. De-ubiquitination is mediated by de-ubiquitinating enzymes (DUBs), it is the reverse of ubiquitination and in charge of reversing mono- or polyubiquitination in proteins. Almost 100 DUBs have been identified in human genes, and the ubiquitin-specific protease (USP) family is the largest branch of them. The general theory is that DUBS affects mitophagy by regulating: (i) activity of Parkin, (ii) stability of Parkin, (iii) proteasome activity, and autophagy. Under normal conditions, a-synuclein is ubiquitinated and circulates in the brain; USP13 may reverse the ubiquitination of a-synuclein and exacerbate the process of neurodegeneration . USP15 mMutations in VPS35 play a key role in the retromer complex. It has been reported that mutant VPS35 increases the clearance of inactive Drp1 complexes, which leads to mitochondrial fragmentation . AnotherHuntington’s disease (HD) is a dominantly inherited neurodegenerative disease caused by mutations that result in a duplication of the CAG triplet in the polyglutamine (polyQ) region of the huntingtin protein (Htt) . HD is cAnother study has suggested a possible mechanism of this interaction, they discovered that mutant Htt may contribute to the overproduction of NO. Drp1 reacts with NO, leading to S-nitrosylation of Drp1, leading to excessive mitochondrial fission and neuronal injury. Remarkably, this SNO-Drp1 has also been observed in AD. In addition, this study also shows that mutant Htt can also be S-nitrosylated, so that it may transnitrosylate or transfer NO to Drp1, leading to S-nitrosylation of Drp1. The study also suggested that S-nitrosylation of Drp1 could facilitate the interaction between Drp1and the mutant Htt . ConsistMutant Htt directly impairs the potential of the mitochondrial membrane, and calcium homeostasis. Increased levels of cytoplasmic calcium could activate Drp1 through dephosphorylation by the calcium-dependent protein phosphatase calcineurin, and promote its association with mitochondria . MoreoveHtt has been proposed as a scaffold protein with multiple protein-protein interaction regions participation in axonal vesicle transport, autophagosome, and mitochondria . RecentlAbnormalities of mitochondrial dynamics seem to be a common feature of many neurodegenerative diseases. Changes in the number and GTPase activity of Drp1 frequently appear in the early pathological process of neurodegenerative disease, accompanied by excessive mitochondrial division, mitochondrial transport damage, and abnormal mitochondria mitophagy , etc. VaIn this review, we discussed the interaction between three types of mitochondrial dynamics and three typical neurodegenerative diseases. We also discussed the internal interactions of mitochondrial dynamics, and it seems to point in one direction—mitochondrial quality control. Several proteins have been frequently mentioned in previous studies, such as Drp1 and PINK, which have been shown to influence mitochondrial dynamics through multiple mechanisms. At the same time, with the study of new mitophagy pathways, a growing number of researchers are starting to notice the effects of other pathways on mitochondrial dynamics. This may bring forth new targets for alleviating, and perhaps even curing, neurodegenerative diseases.The role of astrocytes has been shown during the mitophagic degradation of damaged mitochondria from adjacent neurons . In the Previous studies of mitochondrial dynamics types have focused on synaptic mitochondrial transport. Mitochondrial transport between astrocytes and microglia shows that mitochondrial fragments can not only cause mitochondrial quality control disorders at neuronal synapses but also that they can be transmitted as a “diffusible signal,” which contributes to the occurrence of neurodegenerative diseases. This suggests that mitochondrial dynamics are linked with cell fate .In conclusion, although we cannot completely cure neurodegenerative diseases at the current level of technology, previous studies have demonstrated that mitochondrial dynamic abnormalities and dysfunction can affect the pathogenesis of neurodegenerative diseases in many ways. More importantly, there are complex and inseparable relationships between various types of mitochondrial dynamics disorders. Therefore, it is particularly important to clarify the cause-and-effect relationships between them, pointing us to future directions for the treatment of neurodegenerative diseases.The manuscript has not been published previously, in whole or in part, and it is not under consideration by any other journal. All authors are aware of and accept responsibility for the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


This cross-sectional study compares alcohol pharmacokinetics in patients who underwent sleeve gastrectomy with control participants who did not undergo surgery. While gastrectomy eliminates alcohol FPM,1 it is unclear whether this is because of the removal of the gastric source of FPM or the saturation of the hepatic source of FPM by the delivery of alcohol as a bolus in the absence of the gastric pylorus.5There is broad agreement that a fraction of ingested alcohol is metabolized before reaching the bloodstream; this is known as first-pass metabolism (FPM).6Because sleeve gastrectomy (SG) reduces approximately 80% of the stomach but preserves the pylorus, we compared alcohol pharmacokinetics in patients who underwent SG with control participants who did not undergo surgery and achieved comparable time-to-peak BAC (Tmax) after drinking. This design allowed differentiation of the effects of gastric emptying rate on hepatic vs gastric FPM. In addition, to control for association of SG with potential changes in systemic alcohol elimination rates (AER) that could confound differences in the bioavailability of ingested alcohol between groups, we used an intravenous (IV) alcohol clamp that estimates AER independent of variations in alcohol absorption.STROBE) guideline.This cross-sectional study included 12 women who had SG surgery within the past 5 years at Carle Foundation Hospital (CFH) in Urbana, Illinois, and 9 women who did not undergo surgery and had equivalent age, body max index, and alcohol drinking patterns . Partici2 For the clamp, an IV catheter was inserted into the antecubital vein to infuse 6%v/v alcohol in half-normal saline. Using the computer-assisted alcohol infusion system,6 a target breath alcohol concentration of 60 mg/dL was achieved at 15 minutes and maintained for 135 minutes. AER was estimated from the steady state portion of the last 40 minutes of the clamp.6 We used analyses of variance and Kruskal-Wallis test to compare pharmacokinetic parameters and other outcomes between groups  and an alcohol clamp session approximately 1 week apart. For the oral challenge, an IV catheter was inserted into a hand vein to obtain serial arterialized venous blood samples, the alcohol dose was ingested over 10 minutes, and BAC was measured using headspace-gas chromatography as previously described.Compared with the control group, the SG group had a shorter Tmax, higher peak BAC, and greater area under the curve (AUC) but a similar AER . In the 4 after bariatric surgery. Given that most patients who undergo metabolic surgery are women, this evaluation included solely women, which is a limitation of the study. Studies in male patients who have undergone SG are needed to better understand sex differences in FPM.The findings of this study suggest that alcohol FPM occurs in the stomach in women. Despite the overnight fast, which minimizes alcohol FPM, the bioavailability of ingested alcohol increased by 34% in women who had undergone SG compared with women who had not undergone surgery. The increased bioavailability was not explained by systemic AER or rate of gastric emptying; differences between groups remained when matching Tmax. These data help clarify where alcohol FPM occurs and provide a plausible mechanism for the observed increased in alcohol-related disease


Voltage-dependent anion-selective channels (VDAC) are pore-forming proteins located in the outer mitochondrial membrane. Three isoforms are encoded by separate genes in mammals (VDAC1-3). These proteins play a crucial role in the cell, forming the primary interface between mitochondrial and cellular metabolisms. Research on the role of VDACs in the cell is a rapidly growing field, but the function of VDAC3 remains elusive. The high-sequence similarity between isoforms suggests a similar pore-forming structure. Electrophysiological analyzes revealed that VDAC3 works as a channel; however, its gating and regulation remain debated. A comparison between VDAC3 and VDAC1-2 underlines the presence of a higher number of cysteines in both isoforms 2 and 3. Recent mass spectrometry data demonstrated that the redox state of VDAC3 cysteines is evolutionarily conserved. Accordingly, these residues were always detected as totally reduced or partially oxidized, thus susceptible to disulfide exchange. The deletion of selected cysteines significantly influences the function of the channel. Some cysteine mutants of VDAC3 exhibited distinct kinetic behavior, conductance values and voltage dependence, suggesting that channel activity can be modulated by cysteine reduction/oxidation. These properties point to VDAC3 as a possible marker of redox signaling in the mitochondrial intermembrane space. Here, we summarize our current knowledge about VDAC3 predicted structure, physiological role and regulation, and possible future directions in this research field. The Voltage-dependent anion-selective channels (VDACs) are pore-forming proteins, also known as porins, localized in the mitochondrial outer membrane (MOM). These small proteins (30–35 kDa) are the main pathway for the flux of ions and metabolites between mitochondria and the cytoplasm. VDACs are involved in many cellular functions, including Adenosine DiPhosphate and Adenosine TriPhosphate transfer, Reactive Oxygen Species (ROS) signaling, hexokinase anchoring, and apoptosis . In mammThe data emerging in the last decades denote that VDAC isoforms in mammals show differences in (i) the mitochondrial localization: VDAC1 and VDAC2 are colocalized within the same restricted area in the MOM, while VDAC3 is widely distributed on the MOM ; (ii) thThis review will report progress in understanding the VDAC3 function, focusing on its structure, and discussing various models proposed for voltage gating, its modulation, and its overall role as a channel see .In higher eukaryotes, the structure of VDAC genes is very similar. The genes have the same coding-exon organization, the same size, with the VDAC2 gene containing an additional first exon encoding for the short presequence of 11 amino acids, a feature of this isoform. The size of the VDACs introns varies, but the exon-intron organization is conserved among the whole group . EvolutiVDAC3 promoter exhibits the highest transcriptional activity compared to VDAC2 and, particularly, VDAC1. In this regard, it has been hypothesized that VDAC3 transcripts could be less stable than VDAC1 ones or that their levels are kept constitutively high to readily increase VDAC3 expression in response to specific stimuli  was obtained . The outcome revealed that hVDAC3 has lower protein stability than hVDAC1 when solubilized in LDAO. The lower Tm value of hVDAC3 may explain the formation of noisy channels in the PLM due to the insertion of the unproperly folded hVDAC3. In this paper, the authors suggested that the best insertion yield is achieved using lipid bicelles made from 2-dimyristoyl-sn-glycero-3-phosphocholine (Initially, obtained . Carefulobtained . Very reobtained . When cyocholine .More often, the protein appears to form aggregates during protein purification. Another possible reason for such strange channel behavior of VDAC3 was attributed to the number and endomitochondrial location of exposed cysteine residues, which predominantly protrude toward IMS. According to mass spectrometry analysis, these amino acids follow an oxidative pattern that is conserved throughout evolution and does not include irreversible oxidations, as it was instead found in VDAC1 and VDAC2 cysteines . In hVDAA pivotal role for VDAC3 cysteines in modulating mitochondrial ROS has also been proposed . To dateTo address their physiological role  analyzedProtein interaction networks are crucial to understanding cell functions and pathways and developing successful therapies to treat human diseases.in vivo by a TAP-Tag immunoprecipitation strategy and mass spectrometry identification (In 2014, the VDAC3 interactome was defined fication . The crufication .In the context of PPIs, it has recently been reported that the main difference between VDAC3 and the other VDAC isoforms concerns associations with cytosolic proteins involved in mitochondrial metabolism, especially α-syn and the dimeric tubulin . SeveralVoltage-dependent anion selective channel 3 is involved in the recruitment of PINK1/Parkin, cytosolic proteins involved in a pathway regulating mitochondrial quality control and promoting the selective autophagy of depolarized mitochondria (mitophagy; Another important VDAC-interactor is the VCP, a central and important element of the ubiquitin system. VCP is implicated in numerous neurodegenerative disorders. For example, its gene mutations cause frontotemporal dementia associated with inclusion body myopathy, early-onset Paget disease, familial ALS, and FTLD. Furthermore, VCP seems to act on VDAC3, addressing it toward microtubules through the traffic of cytoplasmic granules and enriching near the centrosome .in vivo functions of the VDAC3 isoform hitherto unexplored.All these PPIs interactions are of great interest. They can have significant implications for mitochondrial bioenergetics and open the way to discover new possible specific 1. However, alterations in VDAC isoform 3 mRNA levels have also been registered in pathologies different from cancer, such as chronic unpredictable stress (Due to its crucial role in cellular metabolism and apoptosis, VDAC proteins are implicated in a wide range of diseases , includie stress , cerebrae stress , and vire stress .A peculiar expression of VDAC3 isoform was observed in cells and tissue in the germinal lines of different organisms. Although VDAC1 is predominantly located in cells of reproductive organs required for the development of gametes , VDAC2 aAlthough VDACs are highly conserved between species, the specific function of each isoform remains unknown. To understand the specialized biological role of VDACs isoforms, recently, using the main available public resource reporting high-throughput data of international collaborative projects  was perfIn general, the data available nowadays confirm that the VDAC3 function is still not fully discernible. In the beginning, VDAC isoforms were considered rescue vessels to make up for deficiencies in other abundant isoforms. Whether or not VDAC3 knockout or overexpression could alter the expression of other isoforms has been addressed by Craigen’s group : accordiSeveral hints make the study of this protein a very intriguing and promising field for acquiring deeper basic knowledge and for the development of diagnostic and therapeutic approaches to a wealth of pathologies such as cancer, respiratory or reproductive system diseases, renal or dermatological diseases, some myopathies, frontotemporal dementia, and neurodegenerative disorders.Both authors contributed to the writing of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Hydra vulgaris (Cnidaria: Hydrozoa), endowed with an early evolved nervous system, are discussed in relation to possible interactions with the microbiota, a stable component of Hydra polyps; their contribution to the evolution of nervous systems through microbe–neuronal interactions is proposed.Neuronal excitability is controlled primarily by γ-aminobutyric acid (GABA) in the central and peripheral nervous systems of vertebrate as well as invertebrate organisms. Besides its recognized neurotransmitter functions, GABA also plays a fundamental role in neurogenesis and synaptogenesis during embryonic development. In addition, GABAergic mechanisms are also involved in disorders of various peripheral tissues, ranging from diabetes to hypothyroidism to inflammatory responses. The discovery of the molecule and the history of its biosynthetic pathways in vertebrate and invertebrate phyla are summarized here. The occurrence and distribution of GABA, GABA-synthesizing enzymes, and receptors to GABA in the freshwater polyp  Invertebrate research has greatly contributed to our present understanding of brain function. In the second half of the last century, comparative studies carried out in various invertebrate organisms added or, in several cases, provided evidence of new biological and physiological properties of neurons and, more importantly, indicated that the elementary unit of nervous systems, the nerve cell, shares similar or equal structural and functional mechanisms in vertebrates and invertebrates, even in distantly related species . In moreHydra vulgaris Pallas (Cnidaria: Hydrozoa).Here, I will attempt a brief outline of the contribution to these new exciting developments coming from new and old knowledge of the biological functions of γ-aminobutyric acid (GABA), the major inhibitory neurotransmitter in the vertebrate central nervous system (CNS) and from studies on GABAergic systems in the freshwater polyp A receptors GABA was specific (70% specific binding), reversible, and saturable. A Scatchard analysis of saturation data indicated the presence of only one population of binding sites with high affinity (KD = 76 nM) and low capacity (Bmax = 4.75 pmol/mg of protein). A systematic screening of GABAA receptor allosteric modulators provided evidence that: (a) the benzodiazepine (BZ) ligands diazepam, clonazepam, and abecarnil enhanced [3H]GABA binding to Hydra membranes by 20–24%, effects abolished by the specific central BZ antagonist flumazenil. On the contrary, the peripheral BZ receptor ligand 4’chlorodiazepam failed to affect [3H]GABA binding to Hydra membranes; (b) the neuroactive steroids allopregnanolone and tetrahydrodeoxycorticosterone increased [3H]GABA binding to Hydra membranes with nanomolar potency and high efficacy, whereas the 3β-hydroxy epimer of allopregnanolone was ineffective; (c) the general anesthetics alphaxalone, barbiturates, and propofol similarly increased [3H]GABA binding.Receptors to GABA were identified in membrane preparations from 3H]GABA binding was completely inhibited by the GABA agonist muscimol and by the GABAA receptor antagonist gabazine, whereas bicuculline was ineffective; baclofen, a GABAB receptor antagonist, weakly (>30%) inhibited [3H]GABA binding [Finally, competition experiments showed that [ binding .Hydra GABA receptor proteins by these various drugs in vitro correlated with their effects in living animals. GABA had an inhibitory role on muscle contraction: GABA, muscimol, and diazepam were shown to decrease the frequency of contraction burst pulses in the ectodermal pacemaker system, (GABA), and the frequency of rhythmic potentials in the endodermal rhythmic potentials system ; none of the ligands affected tentacle pulse frequency, i.e., the electrical activity of the tentacles. Interestingly, the inhibitory action of GABA was suppressed by bicuculline, per se ineffective [The modulation of ffective .AR agonists and positive allosteric modulators mimicked or potentiated these effects of GABA in a dose-dependent manner. The classical GABAA receptor antagonist bicuculline, per se inactive, was able to suppress the GABA-induced increase in response duration. Another GABAA receptor antagonist, gabazine, suppressed the effects of GABA and GABA agonists in a 1–10 μM concentration range; in the absence of GABA, it shortened response duration. The specific Cl− channel blockers, picrotoxin (10 μM) and t-butylbyciclophosphorothionate (TBPS) (1 µM), which per se shortened the duration of the response, also abolished the increase in response duration induced by GABA and counteracted the effects of muscimol, neurosteroids, and general anesthetics [In the living polyp, GABA affects the duration of the feeding behavior, possibly acting on the muscle fibers that control mouth opening upon prey capture or exposure to reduced glutathione (GSH). Administration of 100 μM GABA significantly increased the duration of mouth opening induced by GSH. As predicted from biochemical experiments, GABAsthetics .in vivo experiments. Similarly, GABA and the metabotropic GABABR agonist baclofen significantly increased the rate of distant desmoneme (stinging cells) discharge in Hydra tentacles [B receptors [BR antagonist phaclofen, per se ineffective at 10-μM or 100-μM concentrations both in isolated heads and in whole polyps [Thus, the apparent insensitivity to bicuculline shown in competition experiments was not supported by entacles  by actineceptors . In whole polyps .Hydra tissues whose pharmacological properties are typical of canonical GABAARs. An immunohistochemical study indicates that receptor subpopulations of different subunit composition, α3, β1, γ3, and δ subunits, are found in different body regions of Hydra polyps [− channel blockers suggests a role of endogenous GABA in modulation of the response in physiological conditions.Taken together, these data provide evidence that, besides putative metabotropic GABA receptors, a class of GABA receptor proteins, the ligand-gated ion channel (LGIC) superfamily is present in a polyps . The occHydra, a group studying epithelial and stem cell lineages, led by Thomas Bosch, was becoming very concerned with bacterial “contamination”: were bacteria occasional intruders or stable symbionts? What was the bacterial contribution to cell metabolism? Did bacteria contribute to host physiology and behavior? How did polyps defend themselves from eventual bacterial aggression? The answer to these and other questions led to an impressive series of results showing that “the presence and structure of Hydra’s microbiota are critical for tissue homeostasis and health of the polyps…epithelia and components of the innate immune system play an active role in selecting the inhabitant microbiota via a complex genetic network” . The reain axis . Especiaolecules . In fact species . Hydra tissues. However, several questions should be answered in order to establish a neurotransmitter role for GABA, such as the presence and cellular localization of GABA and its metabolic machinery, and related genes. The biochemical and functional characterization of GABA receptor proteins should enable the identification of the corresponding genes. Finally, the synaptic and/or eventual extrasynaptic localization of GABA receptors would help in understanding the regulatory role exerted by GABA on the electrical activity of the neuronal pacemakers and muscle fibers.The data so far obtained suggest that GABAergic signaling regulates muscle fibers and the nerve net in Hydra polyps has not been established by our studies, apart from some preliminary experiments by gas chromatography/mass spectrometry analysis of tissue homogenates revealing the presence of three fragmentation peaks perfectly coincident with those obtained from synthetic GABA at the same time of elution; this result was reproduced with two different derivatization methods. However, at the time, we considered these findings inconclusive, since we were not able to confirm these findings by convincing autoradiographic localization of GABA in nerve cells. In fact, Hydra neurons are not clustered in ganglia or in an anatomically distinguishable brain but are dispersed in the two epithelial layers that comprise the polyp body; as a consequence, biochemical experiments need to be carried out on whole body homogenates. A stable bacterial community colonizes the body surface [The occurrence of GABA itself in the nerve net and/or in tissues of  surface ; also, tHydra genome is still in its infancy. A systematic analysis of the Nematostella genome [B receptors comparable to their vertebrate and invertebrate counterparts; (b) more GABAA receptor sequences with low identity in residues important for GABA binding; (c) two apparent splice variants of GAD, with more conserved residues with prokaryote than with eukaryote GAD. A large number of inhibitory amino acid transporters were also identified; their sequence is highly conserved, with high residue similarity and identity with the GABA transporter GAT1 orthologues.The molecular identification of GABA receptor proteins and genes in the a genome  showed  have entered the genome by horizontal transfer and later be stabilized as a functional component of the GABAergic machinery? I am not entirely alone in this thought: a recent study reports that transposable elements contribute to genome expansion in a subgroup of the genus, the brown hydras, to which Hydra vulgaris belongs, finding no evidence of genome duplication [While these findings should be corroborated by genomic analysis of other cnidarian representatives—and, in particular, of lication .Transfer of genetic material between non-mating species is increasingly recognized as an important contribution to the evolution of eukaryotic genomes. Internalization of multicellular tissues, including the neural plate in vertebrates, is a crucial morphogenetic process in development and organ formation; the contribution of microbes to internalization of nervous systems has been proposed as a working hypothesis . The rol


The goal was to determine how PECs interact with age and injury severity to influence short-term outcomes. A further goal was to determine whether number of PECs, or specific PEC clusters contributed to worse outcomes within the TBI cohort, compared with orthopedic injury alone. Primary findings indicate that PECs significantly influenced mortality within the TBI cohort; patients having four or more PECs were associated with approximately a two times greater likelihood of dying in acute care (odds ratio [OR] 1.9). Additionally, cluster analyses revealed four distinct PEC clusters that are age and TBI severity dependent. Overall, the likelihood of zero PECs hovers at ∼25%, which is critical to consider in TBI outcomes work and could potentially contribute to the challenges facing intervention science with regard to reproducibility of findings.Health factors impacting both the occurrence of, and recovery from traumatic brain injury (TBI) vary in complexity, and present genuine challenges to researchers and healthcare professionals seeking to characterize injury consequences and determine prognosis. However, attempts to clarify causal links between injury characteristics and clinical outcomes  often compel researchers to exclude pre-existing health conditions (PECs) in their samples, including psychiatric history, medication usage, and other comorbid conditions. In this pre-registered population-based study (total starting  Health conditions co-occurring with injury increase as a function of advancing age, and contribute to variability in both post-injury trajectories as well as heterogeneous factors involved in recovery.9–14 Emerging research has demonstrated that comorbidities can complicate functional recovery and symptom resolution. However, these studies frequently focus on select (notably psychiatric) PECs, or examine the contribution of TBI to exacerbated systemic disorders or illness rather than the opposing directionality.16 Similarly, incongruity in the terminology utilized to discuss PECs, combined with diversity in identification and classification methods of these conditions , can also complicate our ability to reconcile findings from existing studies. For our purposes, the term PEC is used to signify conditions or disorders present, self-reported, or otherwise diagnosed before the time of injury. This is in contrast to “nosocomial conditions,” which are healthcare-associated conditions originating during or as a result of a hospital stay,17–19 and “comorbid” conditions such as substance abuse and psychiatric response to injury that are the focus months to years after the injury occurred.20–24Despite the dense literatures examining the role of demographic and injury related/severity factors that influence early recovery from traumatic brain injury (TBI),25 Over the last 10 years, cardiac conditions, psychiatric conditions, diabetes, respiratory disorders, and musculoskeletal conditions have remained stable as the most frequent chronic conditions.26 Further, the NCCDPHP denotes heart disease, dementias, diabetes, arthritis, and cancer as the leading contributors of disability, death, and healthcare costs in the United States, with age conferring increased risk of these disease conditions.25The Centers for Disease Control and Prevention's (CDC's) National Center for Chronic Disease Prevention and Health Promotion (NCCDPHP) estimates that 6 out of every 10 adults (18 years or older) in the United States have at least one chronic disease, and 4 out of 10 adults have at least two chronic conditions.27 In addition, the impact of PECs does not appear limited to the acute period following TBI. Patients with moderate-to-severe TBI (msTBI) with a greater total disease burden reported reduced levels of functioning and life satisfaction up to 10 years following injury.28 Together, these studies add to the growing literature examining the impacts of both psychiatric29 and other medical conditions30–34 on outcomes following TBI. Such multi-morbidity adds complexity to the care required for these TBI patients in comparison to individuals with singular or no reported PECs and provides evidence for a systemic disease burden on the individual. Similarly, clinical care focused on a single diagnosis may not accurately depict the patient's comprehensive clinical picture or rehabilitative needs.35–37Understanding the influence of the increased disease burden introduced by the development and progression of these PECs is critical across all severities of TBI.27 In elderly patients with TBI, not only are PECs associated with worse outcomes, but morbidity is more highly linked to PEC complications than complications from the injury.38 In a cohort of elderly patients with TBI following treatment in a neurosurgical department, patients with comorbid cardiac, pulmonary, or renal conditions and malignancy were almost three times more likely to die or enter a vegetative state post-injury.39 Related work has shown that patients age 50 years or older are significantly more likely to have diabetes, elevated cholesterol, osteoarthritis, and hypertension in comparison with individuals under the age of 50 who sustain TBI.40In patients older than age 50 years with msTBI, hypertension emerged as a primary PEC and along with related medical complications, predicted hospitalization at 1 year post-injury.41–43 and how this interplay may confer risk of pathological aging in the form of subsequent injury, disease progression, or exacerbated recovery.44–46 Studying TBI without understanding or incorporating PECs not only has broad implications for the reproducibility of findings,47 but also risks undermining the detection of important pre-injury and recovery phenotypes.48 Similarly, it may also play a role in the near complete failure in advancing phase 2 clinical trials for brain injury interventions.50Although it may be difficult to directly link the onset of these conditions post-injury as a result of TBI or aging, what does emerge is evidence for reciprocal impacts of central and peripheral nervous system functioning,Given the importance of understanding how the presence of PECs can contribute to the heterogeneity of TBI recovery trajectories, we conducted a population-based study to identify the base rates of PECs in TBI, to examine the influence of PECs on TBI outcome, and to confirm the previously identified prevalence of PECs in individuals with TBI. Although we examined all cases of TBI during those years, we focused on moderate and severe TBI in analyses to determine the interaction between PEC and injury severity in predicting mortality and functional outcomes. We also sought to determine if PECs interact specifically with moderate and severe TBI compared with orthopedic injury to confer specific risk of prolonged hospital stay and diminished functional status at discharge.1.Mortality rate and days spent in the hospital will be positively correlated with the quantity of PECs.2.Patients with TBI with a greater number of PECs will perform worse on measures of independence, compared with patients with TBI with fewer PECs.3.PEC subtypes will be associated with poor outcomes in elderly patients with TBI.1.What can the results of K-modes clustering demonstrate regarding specific characteristics of patients with TBI presenting with a higher number of PECs?2.Does TBI (as opposed to trauma-only) select for certain PECs when examining all patients?3.Does the frequency of PEC profiles change over the lifespan?n = 939,123 cases): trauma patients entering emergency departments (EDs) with a documented TBI , and a second group of patients without a documented TBI at admission . The TBI and orthopedic injury cases were selected according to codes specific to TBI . When the PTSF provided the data, they included the binary variable “TBI” denoting patients with a diagnosis code from the requested code range, whereas patients with orthopedic injury were those without any of the listed codes. Due to the size of the raw dataset , data cleaning and analysis required a multi-step process implemented through several software applications.Beginning in October 1986, the Pennsylvania Trauma Systems Foundation (PTSF) initiated a trauma registry  to receive data from participating hospitals, in an effort to evaluate patient outcomes through research and education across comparable centers state-wide. At the authors' request, the PTSF provided de-identified data collected from 1986 to June 2019 comprising two approximately equal-sized patient cohorts . Simple CSV validity checks were performed on the data with csv-kit,53 then the two cohort files were converted to TSV to increase speed and efficiency of use, and then were combined. Initial evaluation of the data was performed via a Docker54 based Elasticsearch55 and Kibana56 configuration, using Logstash57 to consume the raw data, and to index the resulting records to Elasticsearch.55 Kibana56 was used as an explorational tool for the data and data cleaning, and normalization was then implemented using a combination of Python58 and R.59 All codes used to alter the data were tracked in git,51 with original source data all subsequent revised versions tracked through git annex.52 Docker54 compose configuration files were created to automate the use of the Elasticsearch55 and Kibana56 tools to provide consistency in the software environment across all computing resources.For the framework outlined below, version control and data provenance were performed through git60 for compliance with data entry guidelines. Data cleaning steps were applied where the unique values differed from the operational manual's allowed values, in the following ways:1.“<n/a>,” “<UNK>,” and “–,” were set to “–1,” −2,” and “–3,” respectively, in integer fields.2.“<UNK>” and “<n/a>” were replaced with an empty string in text fields.3.Date and Time fields were converted from several conventions to conform to ISO 8601 format. If the date or time was “<UNK>” or “<n/a>,” it was converted to an empty string.To facilitate further processing and reporting on the data, sub-datasets were created through selection of limited numbers of columns, selection of records based on column values (post-cleaning), and normalization of the data within columns . For data fields of interest, all unique values present in the data were collated, and compared with the “2017 Pennsylvania Trauma Systems Foundation Operational Manual for the Database Collection System”After list-wise deletion of cases with missing data , 257,089n = 257,089), regardless of the presence of TBI or injury severity together, to implement a data-driven approach 59 to aggregate clusters of PEC profiles. Only a binary matrix representing the presence or absence of each PEC for each patient was included in the K-modes analysis; demographic or injury variables were not included. We then sought to validate the optimal number of clusters in the manner consistent with one of the traditional validation methods of examining elbow plots of the within-cluster sum of squares (wss) implemented in K-means clustering,62 given K-modes has been presented as an extended application of the original K-means algorithm.64 Within the K-modes function, we set an initial seed randomly at the value of (12345), estimated an initial number of clusters (K) equal to 4, and requested a maximum of 10 iterations. To confirm the optimal number of clusters, we repeated these steps, with the exception of changing the value of K to 3, 5, and then 6, and subsequently plotted the wss values returned by the K-modes function for each of our runs. The resulting plots are those presented in Given that the PTOS permits coding of up to 10 distinct PEC entries, we elected to include all patients  data dictionary.60 Further, during the process of data cleaning, the PEC category of Pregnancy was dropped from the dataset to remove bias in PEC count for female trauma patients represented in the database, leaving a total of 18 PEC categories for the current analyses across 43 different participating trauma centers throughout the state.A comprehensive list of the 19 PEC categories, which the PTOS defines as “pre-existing comorbid factors present before patient arrival at the Emergency Department (ED)/hospital,” are provided in n = 150,721) and orthopedic injury cases , we conducted logistic regression with total count of PECs as the independent variable for hypotheses examining the impact of PECs on mortality in patients with msTBI , using the glm function in R.59 To ensure comparable cell sizes for the logistic regression, we collapsed PEC quantities 6 through 10 into one group with a PEC count value of 6 or greater (≥6). For the remaining hypotheses regarding functional independence (FIM) and other hospital outcomes variables , we conducted linear regression on each of the three dependent variables with either PEC count or K-modes cluster assignment as the independent variables.After filtering out mild TBI (mTBI) cases . Logistic regression revealed a significant overall effect of PEC quantity in predicting mortality . Individual Wald's tests for each level of PEC confirmed each additional PEC significantly increased the odds of patients with msTBI being discharged dead in comparison with patients with msTBI admitted with zero PECs. When comparing patients with TBI without any PECs , the ORs for TBI cases with one or more diagnosed PEC were (from 1 to 6 PECs): 1.3, 1.5, 1.6, 1.9, 1.7, and 1.7, respectively. For example, individuals with 4 PECs were nearly twice (1.9 times) more likely to die compared with those with no PECs. Separate Wald's tests also confirmed that the differences in the coefficients for each additional level of PEC  were all statistically significant, with the exception of the difference in coefficients for PEC quantities 5 and 6 .We analyzed mortality within a cohort of adult patients with msTBI . For each additional PEC, FIM scores were predicted to decrease by half a point . Similarly, PEC counts of patients with msTBI significantly predicted total days spent in the ICU, . More specifically, each additional PEC is expected to decrease days spent in the ICU by 4.8 h, . To examine the impact of the number of PECs on total days spent in the hospital, we collapsed patients with PEC counts of 3 or more into one group with an assigned PEC count value of 3. The total number of diagnosed PECs did not significantly impact the number of days patients with msTBI spent in the hospital, .The percentages of patients across injury sub-samples reported for each PEC category are presented in n = 6387), and individuals whose primary diagnosed PECs were Substance Use Disorder and/or Current Smoker (n = 5087); 2) Psychiatric and Substance Use Risk; 3) Cardiovascular Risk; and 4) Elevated Cardiovascular and Neuropsychiatric Risk, which consists of patients with a combination of three or more comorbid PEC diagnoses. Additional information regarding characteristic PEC sub-categories and demographics of these clusters is provided in Comparison of the four elbow plots generated by the various K-modes clustering runs confirmed four as the optimal number of PEC profiles . We subsExamination of PEC counts  regardless of cluster membership reveals descriptive differences across the three groups with respect to demographics, but not hospital outcomes variables. Increasing PEC counts are positively associated with age and the proportion of female patients, but not with increasing stays in the ICU or total hospital days. However, the average hospital lengths of stay and days spent in the ICU were approximately 14 total days in the hospital and around 8 days in the ICU for all three PEC count groups.Comparison of the entire TBI sample with the orthopedic injury sample reveals similar frequencies of PEC categories across both groups, supporting the decision to include all patients regardless of injury status in the K-modes clustering algorithm. The four most frequently reported PECs categories for both orthopedic patients and patients with mTBI were cardiac, psychiatric, hematologic, and vascular risk (predominantly smoking) conditions. These same frequencies, however, did not hold for patients with msTBI, with cardiac, substance use, psychiatric, vascular risk (again predominantly smoking), and neurological conditions reported in the msTBI group.K-modes results demonstrate a clear demographic shift in the qualitative and quantitative characteristics (type and count) of the PEC clusters within msTBI see . More spF), we randomly sampled 500 cases per cluster from the total sub-sample of patients with msTBI . Results revealed cluster group differences in FIM  and lengths of stay both in the ICU  as well as the hospital overall . Post hoc tests with Bonferroni correction revealed mean differences in FIM scores between the Behavioral Risk cluster ( and Elevated Cardiovascular and Neuropsychiatric Risk (p < 0.001), but no significant differences in mean FIM scores when compared with the Psychiatric and Substance Use Risk cluster . Similarly, the Psychiatric and Substance Use Risk cluster mean FIM score was also significantly higher than the two oldest clusters (both p < 0.001). Finally, mean FIM scores did not differ significantly between the Cardiovascular Risk and Elevated Cardiovascular and Neuropsychiatric Risk, p = 0.08.To ensure equal cell sizes for the one-way analysis of variance (ANOVA) tests (Welch's p > 0.05), but did so for each of these clusters when compared with the Elevated Cardiovascular and Neuropsychiatric Risk cluster . Finally, although days in the ICU for the two younger groups  or from the Cardiovascular Risk cluster ; patients in all three clusters spent more time in the ICU in comparison with the Elevated Cardiovascular and Neuropsychiatric Risk cluster .With respect to total days in the hospital, mean differences did not reach significance for comparisons across the Behavioral Risk  and PEC clusters (symptom groupings) are critically influenced by age and even injury severity, but their respective effects on post-injury outcomes may emerge months to years following hospital discharge, and thus are not captured in these hospital admission data.Within the patients with msTBI who were examined, the sheer number and types of PECs had consequence for outcomes. First, as the number of PECs increases, mortality rate climbs incrementally by a factor of 1.7–1.9. Second, distinct PEC cluster types confer differential risk for recovery following injury, and perhaps unsurprisingly, age plays a critical role in the emergence of PECs . In the 65 More specifically, although the younger PEC profiles present with lower total number of PEC sub-categories, they also have a greater proportion of severe TBI cases in comparison with the two older PEC profiles, representing a trade-off between decreasing injury severity with age, and increased aggregation of age-dependent PECs. Further, only 6% or fewer of patients with TBI endorsed one PEC exclusively. More specifically, it appears that PEC diagnoses frequently co-occur, and this comorbidity does not appear restricted solely to a function of advanced age.Given the preponderance of mTBI injuries (more than 60%) across all four clusters in the initial K-modes clustering results, we also suggest these data may speak to differences in injury mechanism as a result of both age and PEC types.38Patient sex proportions also appear to shift within the PEC clusters. Although the Behavioral Risk cluster contains the largest proportion of injured males, the Psychiatric and Substance Use Risk cluster demonstrates an increased number of injured females despite being of similar mean age and proportions of TBI severity. A key sex-by-PEC sub-category difference between these two clusters is the Psychiatric/Personality Disorder diagnosis; 43% of patients within this cluster endorsing this trait were female. Within the Cardiovascular Risk and Elevated Cardiovascular Risk clusters, an increase in mean age also emerges alongside a switch from a greater number of males to more female injuries, and an increase in the total number of reported PECs, aligning with prior research in both TBI and aging.66–69 Despite established research examining reciprocal impacts between central and peripheral inflammatory processes,71 research protocols frequently detail omission of potential participants with diagnosed PECs, notably psychiatric conditions. As global populations continue to age, understanding the impact of multiple morbidity, and the interactions between timing and type of PEC onset, notably with advancing age, remain critical avenues for research determining both risk of and recovery from injuries.73Accumulation of PECs induces necessary inflammatory processes in the acute phase; however, prolonged exposure to sub-clinical hyper-inflammation resulting from chronic conditions compromises the body's ability to effectively respond to additional physical and neurological insults.75 For example, Isokourtti and colleagues74 demonstrated that in a Finnish cohort of patients with mTBI (n = 3023), only 2.5% (76 patients) met criteria for isolated mTBI, that is a patient with mTBI absent of any pre-existing medical or mental health problems. The broad PEC categories described by Isokourtti and colleagues74 are consistent with both our findings here and mirror research in TBI and non-TBI patient cohorts across the lifespan.77 Patients with msTBI presenting with no diagnosed PECs comprise only about 25% of the TBI sample analyzed here, so continued focus on “isolated TBI” samples for research protocols will not only exclude a majority of affected patients with TBI , but also eliminate opportunities to examine the comorbidities complicating patient recovery and the associated costs. Further, TBI research is under-served by the under-representation of geriatric patient samples,78–80 often due to restrictive inclusion criteria.82 This poses significant challenges to understanding post-injury outcomes that may emerge years to decades post-injury.84 This is particularly concerning, given the increase in TBI-related hospitalizations and deaths in geriatric populations in comparison with other age demographics over the last several years.81More specifically, overly restrictive exclusion criteria can eliminate the variability imparted by the presence of PECs, and impact understanding of health mechanisms that influence outcomes trajectory.15 implemented Treelet Transform classification, which resulted in three clusters, which they broadly classified as “acute medical diseases/infections, chronic conditions, and substance abuse disorders.” Similarities between our results and the Treelet Transform clusters offered by Kumar and colleagues include the emergence of chronic conditions, specifically those impacting cardiovascular health, such as cardiac conditions (including heart disease) and diabetes. Additional commonalities include the emergence of substance use disorders, a prominent feature in two of our four clusters. Two important distinctions between our classification methods, however, warrant mention. First, our resulting clusters from K-modes clustering do not permit patients to belong to more than one cluster, whereas Treelet Transform clustering undertaken by Kumar and colleagues27 does permit patients to have overlapping cluster membership. Second, the PTOS defines PECs as conditions present before admission to the hospital, and thereby does not code for hospital-acquired infections ; this is in contrast to the data analyzed by Kumar and colleagues,15 which included hospital codes documenting health conditions present prior to hospital entry and those acquired during patients' hospital stays.Our findings align with a growing literature examining the impact of pre-existing health conditions on recovery following TBI. More specifically, Kumar and colleagues28 Although our work presented here stems from trauma center data in the acute stage post-injury, and Kumar and colleagues28 examined outcomes 10 years post-injury, our findings speak to the importance of studying multi-morbidity as it better simulates real-world conditions. Further, Kumar and colleagues28 also argue that physical and mental health conditions may reciprocally exacerbate one another, a qualitative aspect that is illustrated within our K-modes clustering results, and is highlighted in the discussion offered in this article regarding exclusion criteria that prohibit individuals with these conditions from enrolling in research.Further, one of our overarching research aims of descriptively examining all PECs rather than focusing on an individual or subset of conditions aligns with yet additional work by Kumar and colleagues.29 Additionally, given the emergency/trauma center environment, the cases analyzed here do not have pre-injury functional status data available to assess change in functional status from before hospital admission. Further, the cross-sectional data here do not delineate when patients were diagnosed with PECs, precluding our ability establish direct causality of specific PECs on either chronological acquisition of systemically related PECs or injury specifically.83The results and proposed clinical implications should be considered in the context of the following caveats. The hospital-based data analyzed here may be impacted by an inherent selection bias of individuals who are more likely to seek medical services. Similarly, the de-identified nature of the data prevented assessment of whether the cases analyzed here were repetitive admissions for trauma. Repetitive experiences of TBI, and both neurological and psychiatric conditions have been demonstrated to confer greater risk of hospital re-entry for TBI.60 ranging from those without insurance coverage to those with a private indemnity, and the data presented here are from patients from every possible category of insurance . As a final point, prior work in our lab demonstrates that these differences in insurance exert influence on post-discharge outcomes, rather than the outcomes linked to acute hospital stay presented here.85Relatedly, the availability of insurance (and access to care) may also impact whether PECs can be diagnosed, subsequently disclosed by these patients when they present for care, and may impact inclusion in research examining the questions presented here. The PTOS data permit coding for an array of insurance types,86 Given the known impact of race and ethnicity status on TBI outcomes, neurotrauma investigators should be proactive about how to guarantee that aggregated data are representative of brain injury as it occurs in the population, and that includes all race and socioeconomic demographics.Further, the proportion of African-American patients without recorded PEC data, and the degree to which Hispanic ethnicity was missing from the data make it difficult to generalize these analyses to non-Caucasian patient populations. This data gap remains both concerning and critically important, considering current statistics that non-Caucasian patients are more likely to suffer from a greater number of PECs, have a higher incidence of TBI, and are at greater risk for developing dementia-related conditions (for which both prior TBI and pre-existing conditions confer greater risk).The findings presented across the aims of this study demonstrate that implementing a data-driven approach revealed distinct groups (clusters) of PECs across the lifespan. The prominent PECs present in these four clusters emerge at specific ages, with increasing age associated with a simultaneous increase in the quantity of specific age-related conditions, but also decreasing TBI severity. Similarly, PEC quantity and type were significantly, yet weakly associated with measures of functional independence and hospital stay. These findings add to the literature examining the impact of pre-existing conditions on risk of and recovery from TBI, and infer the importance of re-conceptualizing the impact of PECs on recovery above and beyond a single number or solitary condition. Continued inclusion of individuals absent any diagnosed PECs in TBI research captures only a limited scope of the population, indirectly omitting older and non-Caucasian patients with TBI who may be at greater risk for exacerbated recovery or pathological aging, and presents salient challenges to understanding recovery mechanisms post-TBI as well as for reproducibility of findings.