Diseases that affect both wild and domestic animals can be particularly difficult to prevent, predict, mitigate, and control. Such multi-host diseases can have devastating economic impacts on domestic animal producers and can present significant challenges to wildlife populations, particularly for populations of conservation concern. Few mathematical models exist that capture the complexities of these multi-host pathogens, yet the development of such models would allow us to estimate and compare the potential effectiveness of management actions for mitigating or suppressing disease in wildlife and/or livestock host populations. We conducted a workshop in March 2014 to identify the challenges associated with developing models of pathogen transmission across the wildlife-livestock interface. The development of mathematical models of pathogen transmission at this interface is hampered by the difficulties associated with describing the host-pathogen systems, including: (1) the identity of wildlife hosts, their distributions, and movement patterns; (2) the pathogen transmission pathways between wildlife and domestic animals; (3) the effects of the disease and concomitant mitigation efforts on wild and domestic animal populations; and (4) barriers to communication between sectors. To promote the development of mathematical models of transmission at this interface, we recommend further integration of modern quantitative techniques and improvement of communication among wildlife biologists, mathematical modelers, veterinary medicine professionals, producers, and other stakeholders concerned with the consequences of pathogen transmission at this important, yet poorly understood, interface. Increasing human population growth, the subsequent increasing demand for food production , and the conversion of natural habitats to agricultural land uses have all altered interactions between domestic and wild animal populations. Historically, transmissions of pathogens from livestock to wildlife have led to the maintenance of introduced livestock diseases in wildlife populations for up to a century or more , and vicDiseases affecting domestic animal populations are important from a variety of perspectives. For individual producers, disease-related morbidity and mortality of livestock negatively affects the production of animals and animal products, and, ultimately, may have animal welfare and financial implications ,5,6. FroSimilarly, disease emergence, or re-emergence, among wildlife populations can negatively impact ecological systems and functions, as well as disrupt economic activities. Stakeholders such as hunters and wildlife-watchers can be affected by disease-mediated declines in wildlife populations with significant economic impacts; losses due to invasive animals and associated pathogens in the United States are estimated to cost $35 billion annually . SpillovModels are useful for predicting the effects of disease on populations, estimating the effects of management outcomes, and providing a framework within which trade-offs between different actions (including no action) can be evaluated ,24. HoweBrucella abortus transmission between domestic livestock and wild elk (Cervus canadensis) has occurred through contact with infectious birth materials at shared feeding sites [A number of diseases have a shared component at the common boundary—or interface—between domestic and wild animal populations. The wildlife-livestock interface can be fundamentally defined as the continuum of direct and indirect contact between free-ranging wildlife and domestic livestock (or poultry). Indirect contact can occur through exposure to infected materials  or through environmental reservoirs, such as soil water . Overlapng sites ,34,35, ang sites ,37. One ng sites ,16 becauThe complexities of the wildlife-livestock interface, the increased rate of the transfer of pathogens among wildlife, livestock, and humans, and the challenges associated with pathogen detection and disease management in wildlife, all necessitate a collaborative, transdisciplinary effort to develop novel, science-based methods to address disease concerns within these systems. The use of mathematical models is one such method and is increasingly recognized as a valuable tool for synthesizing information to better understand pathogen transmission routes and to support policies and programs aimed at the prevention and/or management of animal diseases . In thisConsidering the diversity of perspectives required to understand pathogen transmission at the wildlife-livestock interface, we approached our objectives by compiling ideas from both subject matter experts and the peer-reviewed literature. During a 2014 international workshop, we gathered a group of veterinarians, biologists, epidemiologists, statisticians, and mathematicians to evaluate the gaps and challenges in understanding and modeling pathogen transmission at the interface between free-ranging wildlife populations and livestock and poultry populations. A central focus of the group was to identify deficiencies in modeling transmission in livestock-wildlife disease systems using, as examples, FMD, bTB, highly pathogenic avian influenza (HPAI), and CSF; these diseases formed a foundation for discussion from which this broader paper emerged.Mathematical models are being applied with increasing frequency to improve our understanding of complex multi-host disease systems ,39. ModeThe development of predictive models of disease outbreaks caused by multi-host pathogens is hampered by the difficulty in determining: (1) the identity of hosts and pathogens, their distributions, and movement patterns; (2) the transmission pathways and rates between wildlife and domestic animals; (3) the effects of disease caused by pathogens and concomitant disease mitigation efforts on wildlife and livestock populations; and (4) barriers to communication among these sectors. Below, we explore these sources of uncertainty and gaps in our knowledge, as well as analytical approaches that have been used to deepen our understanding of disease in livestock, wildlife, or at the interface of both groups; a summary with some key examples is provided in Accurate identification of species that play a role in multi-host disease dynamics is an important and practical challenge. Identifying these species in wildlife disease systems is difficult and can often only be done by perturbing the system, for example, with an intervention technique and then intensively monitoring the system . Our inaOnce key species involved in the transmission and maintenance of pathogens are identified, we still often lack knowledge about their spatial and temporal distribution; information which is critical for predicting when and where disease might emerge. Systematic surveys for the presence of wildlife species can be logistically difficult and expensive, and such efforts are often constrained by limited available resources. Precise and accurate data on the locations of livestock hosts are not always available, either due to producer confidentiality and privacy concerns or due to a lack of infrastructure to obtain such information . DistribSome surveillance programs, such as those for HPAIV and chronic wasting disease (CWD), have used hunter-killed samples to increase sample sizes at a low cost ,78; howePathogen distributions in livestock hosts can be equally difficult to estimate. Underreporting may occur due to the infrequent observation of livestock and lead to delayed detection. Non-compliance in the reporting of notifiable diseases may also be an issue that can lead to underreporting of disease. Reporting of disease by livestock producers may be influenced by a number of factors, including an inability to recognize the disease , the potPseudogymnoascus destructans, or Pd (the causative agent of white-nose syndrome), in the summer at roost locations to avoid disturbing hibernating colonies or due to a lack of knowledge regarding where winter hibernacula are located. Detecting Pd, however, is more difficult in the summer and it may be unknown where roosting bats overwinter [The spatial or temporal resolution of the data may also influence our understanding of where and when a pathogen is present in a host population. For example, bats may be sampled for erwinter . TherefoMost available population or host distribution data are incomplete or reflect imperfect detection . ImperfeImperfect detection of pathogens may occur through the same mechanisms as imperfect detection of hosts; however, pathogens can also be subject to diagnostic testing bias. Tests used in wildlife are often only validated in domestic animals and are often not optimized for wildlife species. In the case of serologic tests, a positive result may only indicate a previous exposure or infection event and does not indicate an active infection . Tests fOther techniques for the estimation of species distributions (including pathogens) are resource selection functions (RSFs) , generalModelling transmission at the interface between wild and domestic species is particularly challenging due to a lack of data on inter-species contacts, both direct and indirect, that might lead to pathogen transmission . The forB. abortus can be passed along from aborted bison fetal material on the landscape to cattle long after bison have vacated an area [Identifying and describing indirect transmission routes such as the environment can be challenging for interface diseases. The environment can serve as a reservoir such that the indirect transmission of the pathogen to wild and domestic animal hosts may be an important and overlooked component of some disease ecosystems, including anthrax , low pat an area .R0 (the basic reproductive ratio), representing the average number of secondary cases caused by an infectious individual in a susceptible population. In terms of interface disease, SIR models have been used to examine the effects of alternative management scenarios on the risk of at least one bighorn sheep respiratory disease case resulting from contact with a domestic sheep [The traditional model of disease dynamics is the susceptible-infected-resistant model or SIR model ,110. Indic sheep  and to aic sheep . These mic sheep ; specifiic sheep ,112 and Parameterizing SIR models can be difficult, for example, because capturing individual wild animals repeatedly to assess disease status, particularly animals that move large distances like migratory birds or bats, is often not possible. This can limit studies to a cross-sectional design which provides prevalence data for only a single point in time . EstimatIn general, SIR models assume homogeneous mixing of populations and are not spatially explicit. Network theory provides a method for describing the structure of social contacts in a population ,113,115.Network models can also be used to inform agent-based models (ABMs) or individual-based models (IBMs), which are a type of spatially explicit model where agents  move within the landscape and interact with other agents according to a set of rules determined by the modeler ,120. ConB. abortus, the causative agent of brucellosis, revealed that the pathogen was historically introduced to wildlife on at least five occasions in the Greater Yellowstone Ecosystem, but that contemporary livestock cases were coming from elk [Escherichia coli have been used to establish social contact patterns in giraffe (Giraffe camelopardis) [Mungos mungo) and humans [Salmonella infection and risk factors in a wild pig population using genetic methods and Blackburn et al. [Bacillus anthracis to verify the role of blowflies in the transmission cycle of B. anthracis. Other studies have combined pathogen genetic and epidemiological information to estimate transmission trees for an avian influenza outbreak among poultry farms in the Netherlands [Realistic parameterizations of some model components of wildlife-livestock disease dynamics may be possible using population genetics approaches. Examining the genetics of microbes and pathogens is a promising avenue forward for identifying potential transmission pathways between species . For exafrom elk . The genopardis)  and poted humans . Cowled d humans  studied n et al.  used genherlands  and FMD herlands .Finally, though most modeling efforts focus on one disease-one host systems, when evaluating the impacts of disease and mitigation strategies, it is important to consider that disease systems may include multiple hosts . The dynEstimating the impacts of disease on host populations at several levels can also be biased by imperfect detectability. Diseased individuals may hide, become isolated from healthy individuals, be depredated or scavenged, or die before detection and confirmation of the individual’s disease state. These are all scenarios under which the impact of disease on a population  would be underestimated . EstimatEvaluating and modelling population-level impacts of disease may be complicated by genetic variability among hosts or pathogens. Comparisons among studies may lead to different conclusions regarding the lethality of the disease if different types of host or strains of pathogen are grouped together. For example, some strains of pathogen may be more virulent than others , while gFor wildlife species, detecting the effects of fast-acting and highly pathogenic diseases can be difficult if individual sampling is intermittent . Individuals are likely to be infected and then die prior to being tested (or re-tested), and, as such, may be misclassified as uninfected prior to death. In many wildlife cases, disease may be a predisposing factor reducing survival, but the proximate cause of death may be interspecific competition, road kill, predation, starvation, or co-infection, etc., such that evaluating the impacts of disease on host populations may require experimental manipulation of the system to demonstrate whether disease regulates a host population . In the An essential element for developing a mitigation plan is a model of how the system “works”. At a minimum, a host-pathogen model requires the integration of knowledge regarding the spatial distribution of the disease agent and the hosts, the transmission dynamics of the pathogen causing the disease, and the changes in demographic rates and/or behavior associated with infection ,97,141. Both field- and laboratory-based experiments can be used to inform models by providing estimates for these important parameters, though effective wildlife experiments can be challenging to accomplish. For laboratory experiments, some pathogens can only be manipulated under strict conditions, animals can be difficult to obtain, and maintaining populations of wildlife species under laboratory conditions can require new animal husbandry procedures . In addiApplying disease mitigation strategies in the field and conducting field-based experiments can be difficult , ethical concerns that result in small samples sizes or lack of replication among study sites, and difficulty in controlling animal movements between control and treatment sites . FinallyDecision theory offers an established framework for evaluating the trade-offs between potential mitigation actions, determining which factors in the system under consideration are most likely to affect the outcome of the model and/or the optimal decision, and, most importantly, accounting for the societal values associated with different predicted outcomes . DecisioEffective communication across disciplines is critical for bringing together different data streams and different perspectives on wildlife-livestock diseases, which enhances our understanding of the processes that lead to the emergence of disease and the ways to mitigate the effects of disease. Data sharing, along with consistent methodologies and protocols that allow comparisons among data sets, development and use of a common lexicon, and incentivization of transdisciplinary collaborations are necessary for effective communication to occur. Data sharing is an essential aspect of fostering research that crosses the boundaries of traditional disciplines. In order to share data, standards of data management must be adopted by practitioners and researchers , and dathttp://www.oie.int/our-scientific-expertise/certification-of-diagnostic-tests/the-register-of-diagnostic-tests/) and standards and guidelines for diagnostic tests are provided . Adherence to these guidelines should be encouraged, and perhaps required, for publication, to make comparisons among studies possible. At the same time, these tests are typically only fully validated in livestock; a consensus among collaborators regarding which diagnostic techniques and metrics will be used in studies involving wildlife disease should be formed in the initial stages of a project to encourage the deepest level of understanding about the disease system.In addition to data management practices, standard protocols for the collection of pathogen and disease data, and quality control procedures, such as proficiency testing, sending samples to different laboratories to be tested , and usiBatrachochytrium salamandrivorans) [Ursus maritimus) and how the establishment of a distinct definition of health can improve the management for this species. Practices such as those outlined in Patyk et al. [In addition to standard protocols, the establishment of a common lexicon for describing disease promotes and enhances effective communication among disciplines. For example, case definitions (such as that for ivorans)  ensure tivorans) , for exak et al.  will leahttp://www.nimbios.org/), as well as other organizations that promote and fund work that draws multiple disciplines together for disease research . Participation in collaborative work, especially when a researcher may be one of many collaborators across an array of disciplines, is gaining increasing recognition by—and inclusion in—promotion and tenure processes in academia [Finally, although there is general agreement that transdisciplinary collaboration is necessary to improve our understanding of diseases at the wildlife-livestock interface, several impediments to true transdisciplinarity have been identified. These impediments include a lack of funding for research among disciplines , a lack academia . In summModeling diseases across the wildlife-livestock interface involves many challenges. We have identified four key components necessary for effectively modeling disease at the wildlife-livestock interface: (1) host and pathogen distributions and movement patterns, (2) transmission rates and pathways, (3) estimates of disease effects, and (4) effective communication, and we have summarized the challenges associated with describing these components for wildlife-livestock diseases . ManagemThe development of a model to describe how the system works, whether conceptual or mathematical, is a crucial step for managing shared diseases. Models can help with predicting long-term outcomes of disease, informing trade-offs between different management strategies, estimating the potential effects of mitigation, and identifying key parameters in the system where further research is necessary. Management of diseases at the interface should make considerations for evaluating long-term success, impacts to stakeholders, cost, species and conservation impacts, and ecological consequences ,163. ModCommunication among disciplines is key to successfully modelling diseases at the wildlife-livestock interface. Ecologists, veterinarians, economists, computer programmers, policy advisers, disease specialists , agricultural specialists, wildlife managers, emergency planners, social scientists, modelers, statisticians, and mathematicians, among others, will all have valuable perspectives to contribute and their perspectives should be engaged in the earliest stages of disease emergence. Incentives for collaborative work, increased opportunities for professionals to develop working relationships with those in other fields, recognition of the scientific advancements that a transdisciplinary approach can provide, and the intrinsic value of working as part of a team will all be necessary for the successful management of these diseases.


Deregulation of cell growth and development lead to cancer, a severe condition that claims millions of lives worldwide. Targeted or selective approaches used during cancer treatment determine the efficacy and outcome of the therapy. In order to enhance specificity and targeting and obtain better treatment options for cancer, novel modalities are currently under development. Photodynamic therapy has the potential to eradicate cancer, and combination therapy would yield even greater outcomes. Nanomedicine-aided cancer therapy shows enhanced specificity for cancer cells and minimal side-effects coupled with effective cancer destruction both in vitro and in vivo. Nanocarriers used in drug-delivery systems are very capable of penetrating the cancer stem cell niche, simultaneously killing cancer cells and eradicating drug-resistant cancer stem cells, yielding therapeutic efficiency of up to 100-fold against drug-resistant cancer in comparison with free drugs. Safety precautions should be considered when using nano-mediated therapy as the effects of extended exposure to biological environments are still to be determined. Cancer is a major cause of death worldwide, with a projected increase to 19.3 million new cases in the year 2025 with the most vulnerable being the low- and middle-income populations . Other cCancer recurrence can be a useful tool to assess the suitability of cancer burden and treatment. Nowadays, large numbers of cancer deaths occur as a result of cancer recurrence in patients who had previously completed treatment programs and thereafter appeared to be disease-free . Cancer According to the stem cell theory of cancer, a marginal and undifferentiated side-population of cells known as cancer stem cells (CSCs) or tumor initiation cells (TICs), possessing stem-like properties, could be held responsible for initiating, propagating, and sustaining cancer . On top Surgical resection and chemotherapy are the most common conventional cancer treatments and cure less than 50% of all patients with cancer . SurgicaPhotodynamic therapy (PDT) is a treatment approach suitable for certain types of conditions which are not cured by surgical resection and include various cancer types. PDT is considered as a promising treatment modality, presenting significant effectiveness and limited side effects, while numerous side effects are associated with chemotherapy ,28. In PAmong the most commonly used PSs for PDT, those with tetrapyrrolic structures are particularly interesting. They are natural pigmented molecules with four pyrrole rings, joined by carbon-carbon interactions, and both linear and cyclic tetrapyrroles may be found. The linear form may or may not undergo configurational changes such as stereochemical, homosequential, or stereohomosequential changes and/or Fischer-Rosanoff conventions to give rise to their cyclic counterparts . PorphyrObtained through the cyclotetramerization of phthalic acid derivatives and phthalimides, phthalocyanines are structurally similar to porphyrins and porphyrazines . This faAs discussed earlier, miRNAs play essential roles in cancer development as well as regulatory roles by targeting mRNA for cleavage or translational repression. The increased expression level of miRNA-210, miRNA-296, and induced apoptosis related-miRNA were demonstrated after PDT-mediated treatment of Hela cells. PDT-prompted hypoxia led to a subsequent increased expression of miRNA-210 as well as vascular endothelial growth factor (VEGF). The miRNA-210 is a predominant miRNA activated under hypoxic environments. VEGF stimulated the expression of miRNA-296 and restored blood supply to cells that have become deprived of oxygenated blood ,46. ThusNanotechnology is a multidisciplinary field and has emerged from the junction of chemistry, biology, applied physics, optics, digital analysis, and materials science. This evolving and interdisciplinary field mainly involves the design, characterization, manufacture, manipulation, and application of structures at the nanometer scale (nano: one billionth). Such structures are known as nanoparticles and are of particular interest as seen by the growing popularity and publications on nanoparticles or nanomaterials ,49,50. TNanoparticles used for medical applications are multifunctional, and the drug-delivery function is undoubtedly the most frequently used. The utilization of nano-carriers during cancer therapy alleviates the non-specific accumulation and side effects of anticancer drugs into normal cells, thus, offering better tumor targeting and enhancement of therapeutic efficiency. The increasing utilization of nanoparticles in drug-delivery is justified by the inadequacy of conventional therapeutic agents alone to target affected tumor tissues and effectively treat the condition. Currently used nano-drug delivery systems include micelles, dendrimers, liposomes nanotubes, and various other carriers  ,60. SuchThe usage of targeted anticancer agents aims to improve the therapeutic outcomes and release the active form of the drug at its lowermost dose with minimal activity loss and side effects. The prolonged accumulation of drugs into cancer cells and their subsequent improved therapeutic index are counted among the direct benefits of targeted anticancer therapy. Thus, the nature of bioconjugation and bonds between the carriers and drugs in one hand, and between carriers-drug systems and cancer cells on the other hand, are of crucial importance . Both coThioester bond formation between nanocarriers and ligands yields high selectivity of delivery systems and prolonged biodistribution. Such formation requires adequate chemical reactions, with potential molecular rearrangement and disulfide bond formation ,68. DisuDespite significant progress in cancer management observed over the past years, the curative efficiency has not improved concurrently. This may be due to a minor CSCs population with distinctive abilities, responsible for treatment resistance, metastatic growth, and tumor recurrence . Thus, tSimilarly to other noble metals, gold nanoparticles (GNPs) have outstanding potential in enhancing the efficacy of cancer therapy, due to their ability to exhibit exclusive physiochemical and optical features, particularly their plasmonic properties. Thus, they are utilized in targeted drug and gene therapy; and their roles include the incorporation of PSs in multi-component delivery systems and the facilitation of PS’s transcytosis across epithelial and endothelial barriers. PDT is emerging as a therapeutic solution for cancer and other diseases. However, several PSs used in PDT are highly hydrophobic and require carrier systems to enhance cellular targeting and uptake by the cell. GNPs can enhance not only the cellular uptake of PSs but also the singlet oxygen generation and efficiency of PDT ,80. The Although the use of GNPs and other nanomaterials have shown beneficial properties for the management of cancers among other conditions, clarification on a number of safety issues is still needed. First, the exact amount of nanomaterials in targeted diseased areas should be determined prior to the proper determination and application of other parameters such as irradiation of the targeted areas during combination therapies. The irradiation of deep cancer tissues and monitoring of the therapy still require much technological development to assess the targeted cellular sites . ContrarThe success observed with the use of conventional therapeutic approaches to cancer is mostly due to early screening and diagnosis. Late detection and increasing prevalence of drug resistant cancers require further research and treatment development. Nanomedicine used in conjunction with other upgraded therapies would be a better alternative for cancer eradication, providing that all the setbacks and clarifications are dealt with. The preeminence of nanomedicine in cancer therapy over current treatment options will continue to increase and possibly result in the effective eradication of drug-resistant cancers. Nanoparticles-based medical applications have already shown tremendous benefits in fighting various conditions. In cancer therapy, this new technology offers the potential to alleviate the persisting problems of cancer recurrence and drug-resistance. GNPs stand as distinguished intracellular targeting carriers due to size-tailoring, multiple surface-functionalities, and exceptional light-dependent features. The fantasy of the prolonged effects of nanoparticles in desired cells, tissues, and organs creates a safety issue, which is the major limitation; therefore, rendering the technology unattractive for some advanced applications. Purification of delivery systems post-modification, as well as post-delivery clearance, seem to be ignored. Whether nanomedicine is a boon or bane for cancer therapy, can only be addressed after further investigation and expansion of the technology. However, the feasibility of this technology leaves plenty of room for improvement and modification to achieve a strong affinity to cancer cells, render delivery systems able to endure immunologic attacks and yield even better therapeutic outcomes. Nanomedicine is the future of cancer therapy as it offers the prospect to overcome the current limitations, which require detailed insights for specific targeting approaches, improved cellular uptake for all tumors, including CSC populations, and an optimal remedy with enhanced efficiency.


Despite their seemingly elementary roles, the colon and rectum undertake a variety of key processes to ensure our overall wellbeing. Such processes are coordinated by the transmission of sensory signals from the periphery to the central nervous system, allowing communication from the gut to the brain via the “gut-brain axis”. These signals are transmitted from the peripheral terminals of extrinsic sensory nerve fibers, located within the wall of the colon or rectum, and via their axons within the spinal splanchnic and pelvic nerves to the spinal cord. Recent studies utilizing electrophysiological, anatomical and gene expression techniques indicate a surprisingly diverse set of distinct afferent subclasses, which innervate all layers of the colon and rectum. Combined these afferent sub-types allow the detection of luminal contents, low- and high-intensity stretch or contraction, in addition to the detection of inflammatory, immune, and microbial mediators. To add further complexity, the proportions of these afferents vary within splanchnic and pelvic pathways, whilst the density of the splanchnic and pelvic innervation also varies along the colon and rectum. In this review we traverse this complicated landscape to elucidate afferent function, structure, and nomenclature to provide insights into how the extrinsic sensory afferent innervation of the colon and rectum gives rise to physiological defecatory reflexes and sensations of discomfort, bloating, urgency, and pain. Neural control of the colon and rectum is provided by distinct neuronal populations, whose cell bodies lie either within the gut wall  Furness, , 2012 orExtrinsic sensory afferents that innervate the colon and rectum are subdivided based on the location of their soma. Splanchnic nerve cell bodies are located within the thoracolumbar dorsal root ganglia (DRG), whilst pelvic afferents have cell bodies within the lumbosacral DRG , and rectum have demonstrated the presence of afferents with function characteristics compatible with serosal  is located in mucosal nerve fibers  , and TRPV1 , ASIC3, TRPV4, TRPA1, TRPV1 are all integral to high-threshold afferent function and also contribute to afferent sensitization , interleukin (IL)-2, IL-6, IL-1β  (Malin et al., 2O in flat sheet preparations (Zagorodnyuk et al., Malin et al.  reportedPopulations of afferents were responsive to pelvic or rectal nerve stimulation but not to distension or focal tissue compression. These cells remain to be characterized in detail and may include high-threshold serosal afferents, mechanically-insensitive silent afferents, and/or afferents whose axons pass through pelvic or rectal nerves en passant to other pelvic visceral organs. All such cells recorded by Hibberd et al.  containeThe colon and rectum are innervated by a surprisingly diverse and distinct set of sensory afferent subclasses. These afferents innervate all layers of the colon and rectum and have activation thresholds ranging from the imperceptible through to the noxious range. Although further work is required to conclusively document the combined structure, function, and molecular profile of each afferent subtype within the splanchnic and pelvic nerves, our current knowledge provides us with fundamental information of how mechanical and chemical stimuli are detected within the colon and rectum. New technologies may also allow greater understanding of the functional properties of colonic afferents as well as the integration of their sensory inputs into higher levels (Makadia et al., All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.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.


Red blood cells (RBCs) generate microvesicles to remove damaged cell constituents such as oxidized hemoglobin and damaged membrane constituents, and thereby prolong their lifespan. Damage to hemoglobin, in combination with altered phosphorylation of membrane proteins such as band 3, lead to a weakening of the binding between the lipid bilayer and the cytoskeleton, and thereby to membrane budding and microparticle shedding. Microvesicle generation is disturbed in patients with RBC-centered diseases, such as sickle cell disease, glucose 6-phosphate dehydrogenase deficiency, spherocytosis or malaria. A disturbance of the membrane-cytoskeleton interaction is likely to be the main underlying mechanism, as is supported by data obtained from RBCs stored in blood bank conditions. A detailed proteomic, lipidomic and immunogenic comparison of microvesicles derived from different sources is essential in the identification of the processes that trigger vesicle generation. The contribution of RBC-derived microvesicles to inflammation, thrombosis and autoimmune reactions emphasizes the need for a better understanding of the mechanisms and consequences of microvesicle generation. Proteomic analysis of aging RBCs and RBC-derived microvesicles purified from the plasma support this model , but also show the involvement of phosphorylation networks in RBC homeostasis. The involvement of various signaling pathways in RBC vesiculation was supported by the relative large numbers of signaling proteins in microvesicles obtained from the plasma of a healthy donor . In this context, it should be emphasized that not all RBC-derived microvesicles expose detectable amounts of phosphatidylserine . This suggests that an exhaustive study of RBC-derived microvesicles will offer insights into the molecular mechanisms of their generation in vivo, and thereby into the physiological and pathological triggers. Also, RBC-derived microvesicles may constitute a model for the study of the biological, biophysical and clinical properties of microvesicles in general. This model will benefit from the comparison of the composition and characteristics of RBC-derived microvesicles with microvesicles generated by other cell types, and with exosomes. RBC-derived microvesicles are potentially sensitive and specific biomarkers for the clinical severity of RBC-centered diseases such as sickle cell disease, thalassemia or spherocytosis (Red blood cells form microvesicles in response to a variety of physiological and pathological triggers. Although the inventory of the composition of microvesicles generated in different circumstances is far from complete, the available data indicate that they all are enriched in damaged RBC components, depending on the various stimuli (ocytosis . Also, mocytosis .Where RBC-derived microvesicles may be actively involved in pathology, e.g., by their procoagulant, proinflammatory or autoimmune activity , pharmacGB conceived the topic and wrote the final version. GB, JL, and MA-H wrote parts 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.


In the last decade, it has been demonstrated that long non-coding RNAs (lncRNAs) are involved in cancer development. The great majority of studies on lncRNAs report alterations, principally on their expression profiles, in several tumor types with respect to the normal tissues of origin. Conversely, since lncRNAs constitute a relatively novel class of RNAs compared to protein-coding transcripts (mRNAs), the landscape of their mutations and variations has not yet been extensively studied. However, in recent years an ever-increasing number of articles have described mutations of lncRNAs. Single-nucleotide polymorphisms (SNPs) that occur within the lncRNA transcripts can affect the structure and function of these RNA molecules, while the presence of a SNP in the promoter region of a lncRNA could alter its expression level. Also, somatic mutations that occur within lncRNAs have been shown to exert important effects in cancer and preliminary data are promising. Overall, the evidence suggests that SNPs and somatic mutation on lncRNAs may play a role in the pathogenesis of cancer, and indicates strong potential for further development of lncRNAs as biomarkers. Since 2010, genome-wide association studies (GWAS) have identified a large panel of single nucleotide polymorphisms (SNPs) across the human genome, that are associated with cancer susceptibility, prognosis and drug response . FurtherLncRNAs are emerging as a major class of non-coding transcripts. They are defined as non-protein-coding RNAs, more than 200 nt in length, and lacking an open reading frame of significant length (less than 100 nucleotides). The majority of lncRNAs appear indistinguishable from mRNAs, since they present 5′ cap structures and 3′ poly(A) tails; however, lncRNAs without a poly(A) tail have also been described . Due to The most recent research from the ENCODE project reports that the human genome encodes more than 28,000 distinct lncRNAs, the majority of which are yet to be annotated . By analSNPs are genotyped by analyzing groups of individuals and studying the association of SNPs with specific traits . By measPolymorphisms in human genes have been described in remarkable numbers. Association studies to determine which polymorphisms are associated with cancer need to be designed according to strict protocols to obtain reliable results . A genetIn this review, we summarize the current literature on the lncRNA-SNP axis in cancer from 2017 to the present as shown in the PRISMA diagram in Hepatocellular carcinoma (HCC) is one of the most frequently diagnosed cancers, and the most common type of primary liver cancer, and originates from chronic liver injury [r injury . SNPs inr injury , suggestr injury . HULC exr injury  analysisr injury . A gene r injury . eQTL (er injury . Anotherr injury .Prostate cancer (PCa) is the second most common malignancy diagnosed in men, and is one of the major causes of cancer-related morbidity and mortality [ortality . Thus, sortality . In partortality . In a reortality . The rs1ortality . In thisortality . The lncRNA prostate cancer associated non-coding RNA 1 (PRNCR1) is often up-regulated in PCa and modulates androgen receptor activity. Moreover, rs13252298, rs1456315 and rs7841060 polymorphisms in PRNCR1 were found to increase the risk of tumors in an Iranian population . Again, Lung cancer, including non-small-cell lung cancer (NSCLC) and small-cell lung cancer (SCLC), is a major cause of cancer-related death and has a very poor overall survival rate [val rate . So far,val rate . Also, tval rate . Conversval rate . LncRNA val rate . The autval rate . A separval rate . Severalval rate . Neuroblastoma is the most frequently diagnosed extra-cranial cancer in children, after leukemias and cancer of the central nervous system [s system . Polymors system . Recentls system . Also, is system .Medulloblastoma, which is defined as an embryonal tumor of the cerebellum, is the single most common form of malignant brain tumor of childhood, and constitutes 20% of all primary central nervous system tumors [m tumors . The germ tumors .Colorectal cancer (CRC) is the development of a tumor in the large part of the intestine, namely the colon and rectum [d rectum . Three ad rectum . The secd rectum . The thid rectum . LncRNA d rectum .Tissue differentiation-inducing non-protein-coding RNA (TINCR) is a key lncRNA required for somatic tissue differentiation and tumor progression, that is involved in the risk and progression of CRC. There are two SNPs on it, rs2288947 and rs8105637, that have been found to be associated with the decrease or increase of cancer risk respectively, validating its key role in the development of CRC .bladder cancer [In r cancer , the SNPr cancer .Breast cancer (BC) is the most common cancer and the second leading cause of cancer-related mortality in women worldwide. Both genetic risk and environmental factors contribute to its occurrence [currence . It has currence .oral squamous cell carcinoma (OSCC) and osteosarcoma risk with different alleles. OSCC is a malignant epithelial neoplasm affecting the oral cavity and osteosarcoma is a bone malignancy which occurs primarily in adolescents [H19-rs217727 SNP was associated with susceptibility for lescents ,57. Theslescents ,59.pancreatic cancer [A study of c cancer  and pairc cancer . rs18591c cancer .gastric cancer [Recently, the effects of c cancer  associatc cancer . In the c cancer .Owing to recent developments in machine-learning technologies, next generation sequencing of pan-cancer data provides vast resources that aid the discrimination of somatic variants from germline variants, within non-coding regions. Thus, non-coding somatic mutations can be differentiated from background genomic regions, and associated features, such as copy number variations, conservation, substitution types and histone marker features, can be assessed . To dateMost of the tumor types we briefly discussed in the paragraphs above lack effective therapies and methods for early screening and stratification of patients, amenable for a precision medicine approach. Thus, implementing the panel of SNPs confirmed for any association with tumor risk, even in selected subgroups of patients, could certainly help to develop new strategies for clinical applications. Although preliminary and still incomplete, the set of data on the association of polymorphism in lncRNAs with cancer susceptibility might suggest that SNPs in lncRNAs hold great potential as prognostic biomarkers for cancer. Due to the novelty of the projects and studies on these recently discovered non-coding transcripts, much of the data on lncRNA mutations associated with cancer need, of course, to be further validated in prospective studies on larger sets of cohorts of patients, and for different ethnicities to obtain higher reliability. It is in fact possible that many of the reported observations might not be cross-validated or might not be generalizable to different populations worldwide. Moreover, the risks attached to SNPs describe only a minor component of the overall risk in cancer. Nonetheless, these genetic studies might be some of the very few that can implicate the otherwise elusive lncRNAs in the molecular pathways of cancer. It is indeed very difficult to assign a function to a lncRNA; for example as that of a regulator of RNA interactions or that of a scaffold and a protein binder.The great majority of experimental data on variant genotypes, collected to date, consist principally of association studies, with a significant number evidencing only a tendency for altered expression or function of lncRNAs in cancers due to SNPs or other somatic mutations. Moreover, they require an inclusive analysis of public databases to confirm the preliminary observations in patients or to provide supporting evidence of a SNP role in other tissues, indicating that they could be functional. On the other hand, public databases often report incomplete information on lncRNAs, due to both the still limited repositories available today, and the lack of effective and complete annotation of lncRNAs in the human genome.Overall, there is still little experimental data that clearly demonstrates the cancer relevance of SNPs and somatic alterations in lncRNA. The most frequently mutated lncRNAs in cancers with a large impact in healthcare were undoubtedly HOTAIR, HOTTIP, and MALAT1, whose SNPs were detected in several studies, confirming their involvement in relevant cancer functions. Otherwise, SNPs in other lncRNAs were specific to selected cancer types, indicating they could operate in specific signaling mechanisms. The substantial knowledge gap that still exists between the SNP association and the molecular mechanism contributing to disease risk represents both a question and an opportunity in the identification of lncRNAs with key roles in cancer. A polymorphism in a regulatory element might alter the abundance of a gene transcript. However, a great number of SNPs are positioned in intergenic or intronic regions, and the relationship of these with lncRNA function in the cell context might be much more circumspect. To analyze the action of SNPs in this respect, expression quantitative trait locus (eQTL) mapping can be applied. With eQTL the relation of RNA expression with genotype data is measured to determine if a variant is correlated with gene transcription .In parallel, bioinformatic approaches have frequently been used to predict the potential effects of genetic variations in the structure of lncRNAs. Despite the secondary structure of many lncRNAs have been resolved by using the SHAPE-directed RNA chemistry prediction tool ,73, the Overall, no data are currently available on the biological functions of the SNPs we describe in this review. Also, studies on somatic mutations of lncRNAs and their impact on cancer are still at an early stage.As of today the most relevant implications of lncRNAs SNP studies include the cancer risk assessment and susceptibility. However, due to the evolution of next-generation sequencing and the advent of single cell sequencing, it is likely that a host of discoveries on the involvement of lncRNAs in cancer are finally on the horizon. In the near future, clinical applications of SNP detection in lncRNAs might include early cancer diagnosis, risk prediction for relapse or progression, monitoring the effects of systemic therapies, and patient stratification. Eventually, these studies could also lead to the identification of novel targets for the development of innovative therapies. This research field remains one of the major challenges for the study of SNPs and other variants of lncRNAs involved in cancer.


The endocannabinoid system (ECS) has been recently recognized as a prominent promoter of the emotional homeostasis, mediating the effects of different environmental signals including rewarding and stressing stimuli. The ECS modulates the rewarding effects of environmental stimuli, influencing synaptic transmission in the dopaminergic projections to the limbic system, and mediates the neurophysiological and behavioral consequences of stress. Notably, the individual psychosocial context is another key element modulating the activity of the ECS. Finally, inflammation represents an additional factor that could alter the cannabinoid signaling in the CNS inducing a “sickness behavior,” characterized by anxiety, anhedonia, and depressive symptoms. The complex influences of the ECS on both the environmental and internal stimuli processing, make the cannabinoid-based drugs an appealing option to treat different psychiatric conditions. Although ample experimental evidence shows beneficial effects of ECS modulation on mood, scarce clinical indication limits the use of cannabis-based treatments. To better define the possible clinical indications of cannabinoid-based drugs in psychiatry, a number of issues should be better addressed, including genetic variability and psychosocial factors possibly affecting the individual response. In particular, better knowledge of the multifaceted effects of cannabinoids could help to understand how to boost their therapeutic use in anxiety and depression treatment. The endocannabinoid system (ECS) consists of endocannabinoids (eCBs), cannabinoid receptors (CBRs), biosynthesizing, and degrading enzymes. The main eCBs, anandamide (AEA) and 2-arachidonoyl-glycerol (2-AG), are degraded by distinct enzymes, the fatty-acid amide hydrolase (FAAH) and monoacylglycerol lipase (MAGL), respectively. eCBs interact with a number of different molecular targets  axis activation in response to stressing stimuli  and FAAH have been identified , and HPA activation in the stress response , are critically involved in mediating reward  axis represents the typical response to stress. While the HPA axis activity could be modulated by the ECS, conversely both stress and glucocorticoids could induce eCBs signaling in brain areas critically involved in behavioral responses, such as the hypothalamus and the amygdala . Anxiety and depression, are more frequent in MS patients compared to both general population , differing in THC and CBD composition. Cannabis-derived treatments are currently approved for several clinical conditions, including spasticity, pain, nausea, and some epileptic conditions  and cannabidiol (CBD) represent the main phytocannabinoids Huestis, . In addiThe limited approved clinical indications contrast with the ample evidence, derived by preclinical studies and also from anecdotal observations, showing beneficial effects of ECS modulation on mood. It should be considered that a number of factors may contribute to the lack of clear findings. It has been observed that most clinical studies were considered as at high risk of bias, generally for incomplete report of outcome measures and for inadequate blinding procedure (Whiting et al., A specific confounding factor that limits the clinical evidences supporting the beneficial effects of cannabinoids on mood is the difficulty in controlling the placebo effect. It is worth noting that the placebo response could significantly influence the clinical effect of drugs acting on the ECS (Benedetti et al., Finally, concerns about the risks associated to cannabis use have limited the clinical indications of medical marijuana. In particular, acute cannabis use has also been associated with worsening of anxiety (Crippa et al., Emotional homeostasis is crucially modulated by the activity of the ECS. In particular, different environmental and endogenous stimuli could influence the emotional state by modulating the sensitivity to eCBs of different neurotransmitter pathways in multiple brain areas. Cannabis-based compounds could exert antidepressant effects through complex influences on different behavioral responses, such as those associated to reward, stress and inflammation, also depending on the individual psychosocial context. Overall, these issues make it difficult to demonstrate unequivocal relationships between ECS modulation and the effects on mood. Although targeting the ECS could represent a promising treatment option in different psychiatric conditions, future clinical trials should be designed to explore specific outcome measures, to reduce the individual variability and to consider the placebo response. In the last years, the ample diffusion of smoked or vaporized cannabis for recreational and therapeutic purposes has not been accompanied by measures aimed at promoting information about medical marijuana use. In this view, it is important to design specific interventions to overcome the gap between preclinical studies and clinical evidences on the potential therapeutic use of cannabinoids.MS and EI: work conception and design, drafting the work, work revision, final approval, and global agreement. LG: work conception and design, work revision, final approval, and global agreement. PM, ED, AB, and FB: work revision, final approval, and global agreement. DC: work conception and design, guarantor of integrity of entire study, manuscript revision for important intellectual content, final approval.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.


We also present a quantitative comparison of non-linear filtering techniques applied to synthetic gel images, through analyzing the performance of the filters under specific conditions. Synthetic proteins were modeled into a two-dimensional Gaussian distribution with adjustable parameters for changing the size, intensity, and degradation. Three types of noise were added to the images: Gaussian, Rayleigh, and exponential, with signal-to-noise ratios (SNRs) ranging 8–20 decibels (dB). We compared the performance of wavelet, contourlet, total variation (TV), and wavelet-total variation (WTTV) techniques using parameters SNR and spot efficiency. In terms of spot efficiency, contourlet and TV were more sensitive to noise than wavelet and WTTV. Wavelet worked the best for images with SNR ranging 10–20 dB, whereas WTTV performed better with high noise levels. Wavelet also presented the best performance with any level of Gaussian noise and low levels (20–14 dB) of Rayleigh and exponential noise in terms of SNR. Finally, the performance of the non-linear filtering techniques was evaluated using a real 2-DGE image with previously identified proteins marked. Wavelet achieved the best detection rate for the real image.Various methods and specialized software programs are available for processing two-dimensional gel electrophoresis (2-DGE) images. However, due to the anomalies present in these images, a reliable, automated, and highly reproducible system for 2-DGE image analysis has still not been achieved. The most common anomalies found in 2-DGE images include vertical and horizontal streaking, fuzzy spots, and background noise, which greatly complicate computational analysis. In this paper, we review the  A number of different aspects of protein analysis are covered in proteomics, including the analysis of protein expression. The presence or absence of proteins, and the direct measurement of relative protein abundances can help understand cellular processes, and may be useful for identifying drug targets and diagnostic/prognostic markers Proteomics is the analysis of the complete set of proteins  2-DGE was initially employed for protein separation and analysis approximately in 1975 Many computational applications are available for processing and analyzing 2-DGE images, such as MELANIE, PDQuest, Z3, Progenesis Workstation, ProteomeWeaver, ProteinMine, Delta2D, and DeCyder For 2-DGE image analysis, techniques are required to detect protein spots, to segment and to quantify the protein expression level based on the number of pixels i.e., pixel intensity regularization , background correction, and noise reduction (filtration) There are three common objectives for the 2-DGE image preprocessing, 2-DGE images inevitably exhibit anomalies caused by sample preparation techniques and the imaging system used to acquire the digital images Intensity normalization of 2-DGE images aims to normalize the intensity of protein spots to facilitate processing. The spot intensities may vary due to differences in the exposure of the gel during the staining process and data saturation, among other reasons To avoid saturation caused by high protein concentrations, it is necessary to make sure that most of the data are represented by levels slightly below the maximum possible intensity. Highly abundant proteins often mask fainter spots that represent proteins with low abundance. Usually, these low-abundance proteins are also relevant, but pose difficulties in accurate quantification, if the spots are too faint The normalization process helps to reduce noise, which distorts the detection of protein spots in 2-DGE images according to criteria of statistical significance, thus allowing the outline of the spots of interest to be delineated The aim of 2-DGE image processing is to detect spots, and define the location, border, and intensity of each spot. However, in some conditions, defining the limits of the spot border is difficult due to the varied background, noise, and saturation of protein spots Background correction with polynomial adjustment has been widely accepted in the scientific community For background adjustment using histograms, the distribution of intensities in an image is used to identify the background. The maximum peak in the intensity distribution is the intensity of background pixels. The challenge of this technique is to establish the intensity threshold of the background that is usually set by an optimization process 2-DGE image filtering is the most commonly used approach within the scientific community, with the most diversified techniques The first techniques reported for 2-DGE image’ preprocessing were based on linear filters, which are the most widely used techniques in commercial software programs. These kinds of filters compute the output pixel as a linear relation of the surrounding pixels Orthogonal regression methods have been used as a simple and efficient option that can adapt to a linear model With the Wiener filter, it is possible to obtain satisfactory results with a low level of distortion of the image, but the noise reduction is compromised Nonlinear filters have fewer limitations, but generally increase the degree of complexity and the need to define parameters more thoroughly. Some nonlinear filtering techniques used in 2-DGE images include contourlet transform The total variation technique, proposed by Chan Despite the simplicity of noise suppression methods based on spatial filtering, the image tends to be severely distorted after processing. As these types of images have local features with high variation, it is almost impossible to discriminate between information of interest and noise, when the processing considered only the spatial or spectral domain Different derivations of the wavelet transform Due to the limitations of these techniques and the need for parameter adjustments, advanced techniques such as genetic algorithms The lack of performance indicators with which the various techniques can be fairly compared greatly hinders the selection of preprocessing techniques. In fact, performance comparison of many commonly used techniques has not yet been reported in the literature However, with the SNR indicator, important factors regarding the retention of relevant information are not considered. Daszykowski thus proposed a measure called false discovery rate (FDR), defined as a ratio of the number of stable variables from the permuted data to the number of stable variables from the original dataset Another measure is spot efficiency The performance of several noise reduction techniques was compared using synthetic images. Experiments were developed under controlled conditions and the quantitative indicators SNR and spot efficiency were used to determine the performance of the filtering techniques with a perturbation of impulsive-type noise. To generate a cloud of spots, we used a model of uniform distribution, which simulates proteins in 2-D gels, and allowed overlapping between spots. The synthetic spot model is a Gaussian distribution N) was performed, using image processing techniques with a filter of displacement vector To obtain images with a blurring effect, a linear approximation of the camera movements in pixels (The SNR and spot efficiency for the images with noise and filtered with nonlinear techniques wavelet, contourlet, TV, and WVTV are presented in In terms of spot efficiency, wavelet and WVTV techniques have a lower sensitivity to noise than the contourlet and TV techniques, as reflected by the best performance of wavelet and WTTV techniques. Wavelet was the best for images with noise levels between 12 and 20 dB, and WVTV was best for images with high-level noise. A real 2-DGE image taken from the LECB 2-D PAGE Gel Images Datasets was used to compare the performance of the aforementioned filtering techniques The first step in most commercial 2-DGE image analysis software programs is spot detection. Often, false positive spots are detected due to noise and other artifacts in the image, and conversely, some real data may be missed. Therefore, image preprocessing is a fundamental step for proteomic analysis using 2-DGE, as the performance of the subsequent analysis is directly affected by the quality of the image. The development of image acquisition systems and optimal sample preparation protocols greatly improves image quality, reducing the intensity and frequency of unwanted anomalies. However, some anomalies are unavoidable and affect the accuracy and reproducibility of the proteomic characterization of the sample. Each of the preprocessing approaches meets particular needs. Nonetheless, the order these preprocessing stages should be implemented in, and whether all of them are actually necessary or some could be excluded without affecting the final performance, is still not clear. In conclusion, a methodology that adequately integrates these preprocessing approaches is needed.Even though several specialized image processing software programs are available for 2-DGE, these still require considerable human intervention, which affects reproducibility of the results as well. The wide range of anomalies in 2-DGE images, such as fuzzy spots, vertical and horizontal streaking, and noise, make it difficult to process the image. Therefore, it is important to implement advanced preprocessing techniques that could help mitigate the effect of these anomalies. In this review, we grouped three approaches of preprocessing: filtering, image regularization, and background correction, which are suited to different purposes such as noise reduction, regularization of the intensity of the pixels, and background correction. If these preprocessing procedures are not implemented, negative effects are observed during the image processing stage, such as image distortion, loss of relevant information, and changes in the contour of the spots of interest, yielding non-representative data. Noise reduction is successful when filtering techniques are applied. Although linear filters are easy and simple for reducing noise in 2-DGE images, these filters tend to distort the edges of the spots of interest. Techniques such as Gaussian filters, orthogonal regression, and PCA often remove small details such as low-abundance proteins in the process. Thus, nonlinear noise reduction techniques are presented as more appropriate solutions. Nonlinear filters are more robust, but also more complex to use; they require the definition of parameters that depend on the image. It is clear that there is still a great scope for improving the performance of preprocessing techniques for 2-DGE images, as well as for proposing new ones, since the decision to implement these techniques in 2-DGE image processing is based on their performance with other types of images. Therefore, 2-DGE images are an attractive alternative for testing new algorithms for noise reduction, background correction, and image adjustment.In this article, we validated the quantitative performance of the most representative preprocessing techniques for noise reduction of 2-DGE images. By comparing the performance of wavelet, contourlet, TV, and WVTV techniques using SNR and spot efficiency indicators, we conclude that spot efficiency is more appropriate for evaluating the noise reduction techniques applied to 2-DGE images. This index provides information about the effect of the noise reduction technique on the process of protein detection. Quantitative performance comparison using synthetic images indicates that wavelet filtering is the best technique under the test conditions, which achieves good results for the images with different types and levels of noise evaluated.Taking into account the results obtained for the images with a blurring effect, and the fact that this anomaly is recurrent The authors have declared no competing interests.


In recent decades, care policy in the Netherlands reduced budgets for residential care and formal home care, which increased the demand for informal care. Women use formal care more often than men, but we lack information on the extent to which the gender gap in care use is explained by differences in individual chracteristics and changes in care policy. Data from the Longitudinal Aging Study Amsterdam (LASA) were employed to explore the gender gap in the use of informal, formal and private home care, community services, and residential care in the years 1996-2016, analyzed using Generalized Estimating Equations (GEE). The data consisted of 9,497 observations, gathered from 3,369 respondents aged 65-85. Women used all types of formal care more than men. The gender differences persisted even when individual characteristics were taken into account; however, only in residential care the differences diminished after care preferences were included in the analysis. During the study years, the gender gap increased in formal home care and in non-use of care, as women increasingly used formal home care and the proportion of men without care expanded. The gender gap in informal care use reversed, with men using more informal care during the earlier years and women using more in the later years. The persistent and even increasing gender differences in care use deserve further exploration of the role of gender in current care culture. The growing gender gab in non-use of care raises concern for older men and their possible increase in unmet care needs.


Basilar invagination (BI) and Chiari malformation type I (CM-I) are very important anomalies that introduce instability and compression in the occipitocervical transition region and have complex clinical characteristics. These anomalies vary according to the affected structures. The present study revises current knowledge regarding the anatomy, anatomo-physiology, clinical manifestations, and radiological findings of these entities and the associated surgical treatment approaches. A bibliographic survey was performed through a search in the Medline, PubMed, SciELO, Science and LILACS databases. When associated, these craniovertebral malformations result in neurological deficits due to neural parenchyma compression; however, the presence of microtraumas due to repetitive lesions caused by the bulb and cervical marrow instability has been highlighted as a determinant dysfunction. Surgical treatment is controversial and has many technical variations. Surgery is also challenging due to the complex anatomical characteristics and biomechanics of this region. Nevertheless, advances have been achieved in our understanding of related mechanisms, and compression and atlantoaxial instability are considered key elements when selecting the surgical approach. Basilar invagination (BI) is an important occipitocervical malformation characterized by odontoid apophysis displacement of the axis inwards towards the foramen magnum and posterior displacement of the bulb; cerebellar BI is generally a congenital pathology, but it can be acquired in rare cases –3. This Chiari  describeThe incidence of CM-I is estimated to be 1/1,000 births . In rareCraniometric studies have shown that such malformations present common characteristics, including underdevelopment of the occipital bone and compression of cerebrospinal fluid (CSF) at the craniocervical junction ,8,10.Even when congenital, these interrelated changes can trigger symptoms in adulthood, and the complex clinic al characteristics vary in accordance with the involved structures. Clinical manifestations, either when isolated or combined, can include headache, neck pain, neck stiffness, diplopia, dysphagia, rhinolalia, paresthesia of the face and limbs, vertigo, sexual disorders and progressive cerebellar ataxia ,11.Treatment is complex, and the surgical approach varies according to the condition of the craniovertebral malformations ,9,12. HoThe aim of this study was to review the anatomo-physiology, clinical manifestations, and radiological findings of BI associated with CM-I and the corresponding surgical approaches.“Craniovertebral Junction, Basilar Impression, Chiari Malformation, Surgical Decompression” and their correspondents in other languages, either alone or in combination.This is a review of BI and CM-I. A bibliographic survey was carried out in the Medline, PubMed, SciELO, Science and LILACS databases. Articles ranged from early records of the malformations in question to the most current approaches to this topic. The descriptors used were The inclusion criteria were as follows: original articles regarding the association between BI and CM-I corresponding to publications on anatomical aspects of the craniocervical region, vascular relationships, types of compression, radiological findings and types of surgical approaches. The exclusion criteria included articles that reported none of the previously mentioned correlations, those focusing on other types of Chiari malformation, and/or duplications among the databases.All the bibliographic material included in this review was analyzed by critically reading the data to frame the inclusion criteria and interpret and compare the findings.Anatomic recognition of the craniocervical region  becomes indispensable in acute basilar impressions with CM-I.To simplify our study, the craniocervical junction included only the clivus, foramen magnum, occipital condyles and upper cervical vertebrae (atlas and axis), which, apart from their function as joints, surround and protect the arterial and venous vascular tree as well as nervous structures  within the craniovertebral subarachnoid space. Knowledge of the muscles surrounding this site and the vessels adjacent to the spinal cord, in addition to the bulb and the nerves that operate in the region, is essential when performing various surgical approaches –20.In particular, with BI, anatomical changes can occur in the foramen magnum, clivus and upper cervical spine. Skeletal defects in this region affecting the odontoid process (axis) and the clivus have been observed, reflecting various types of BI –15.–Anterior basilar impressions have been found in clivus hypoplasia with shortening of the posterior base of the skull but without alterations in the occipital foramen .–Medial basilar impressions can move upwards from the anterior wall of the foramen magnum, and the condyles can slide medially against the lateral parts of the condyles at the base of the skull . When thThe association of BI with CM-I invagination syndrome may result in neurological deficits due to neural parenchyma compression because of tonsillar herniation or due to hydrodynamic changes in the CSF at the level of the craniovertebral junction. However, an isolated measurement of the invagination depth will not necessarily be correlated with the severity of neurological symptoms, and patients with symptoms similar to CM-I have been found to have less than five millimeters of hernia .In 2009, Goel and Shah  suggesteThe vascular network modifications in the posterior fossa observed in cases of BI and CM-I likely account for most pathophysiological neurological and clinical signals as well as postoperative complications because they can lead to disturbances in the structures that supply blood to this region. In these cases, the posteroinferior cerebellar artery is likely to have an abnormal position and descend in the caudal direction, and it may or may not accompany cerebellar tonsil herniation .In contrast, in Chiari syndrome I, elongation of the cerebellar tonsils around the bulb has been observed, with these structures descending together with the spinal canal. This pressure within the spinal canal in the presence of a basilar impression further reinforces the functional loss of CSF circulation, generating real signs of hydrocephalus, syringobulbia and syringomyelia as consequences of increased intracranial cerebrospinal pressure . In adulAmong other etiologies , syringoThe first reports of BI were based on postmortem findings . In 1911In 1939, Chamberlain  defined Imaging methods, such as X-ray, computed tomography, magnetic resonance imaging and other examinations used to evaluate these malformations, have shown that the volume of the posterior fossa is lower in patients with BI and CM-I than that in normal individuals. Milhorat et al.  detectedbasion to the opisthion. However, the normal limit of tonsillar migration remains controversial, with the normal limit considered a distance smaller than 3 mm, a borderline limit between 3 and 5 mm, and a pathological limit higher than 5 mm. Some authors consider herniation of 3 mm pathological if accompanied by typical clinical symptoms, such as lengthening of the cerebellar tonsils, syringomyelia, or an abnormally elongated IV ventricle  Constructive Interference in Steady State (CISS), or another) from a line drawn on the foramen magnum running from the entricle ,33  and diastole (upward), with impaired liquoric flow in the diastolic phase. Currently, however this liquoric flow study is not routinely used in therapeutic planning in these patients .To institute appropriate BI surgical treatment in cases associated with or without malformations, a better understanding of the pathogenesis of this condition is needed. Ebenius  reportedIn 1939, Chamberlain  reportedIn the following years, patients were treated for craniovertebral abnormalities with decompression of the posterior fossa by enlargement of the opening of the foramen magnum and C1 arch removal. Since then, the optimal treatment for symptomatic cases of BI and/or CM-I is considered surgery with opening of the dura mater , 45.Attempts to use conservative treatment have not produced convincing results according to a report by Phillips  in 1955.In northeast Brazil, Caetano de Barros et al.  documentTenuto et al.  publisheIn 1977, Gonçalves da Silva  applied In a study on atlantoaxial instability in rheumatic inflammatory processes entitled “Basilar Pseudo invagination”, Brito et al.  reportedIn BI cases in which the atlantoaxial joint with odontoid process protrusion and brainstem compression are considered fixed or irreducible, anterior decompressive surgery becomes a treatment priority, which has shed light on the events occurring during the years following surgery involving odontoid apophysis resection using a transoral approach ,52. ThisMenezes et al.  proposedGoel and Laheri  expandedIn 1998, Goel et al.  evaluateIn 2005, Kassam et al.  performeIn 2009, Goel and Shah  reportedIn 2011, da Silva et al.  showed pTo improve our understanding of BI mechanisms and the ability to carry out treatment, Goel  proposedConsidering the embryonic development of the bone and central nervous system, a malformation can occur in either one of these components or in both systems. For example, differences exist in interpretations of BI pathogenesis associated with Arnold-Chiari malformation, and this serves to illustrate the difficulty in establishing the priority of the nervous or bone system. In fact, several theories about how these damages originate exist.For a long time, BI was viewed as an anatomical and radiological phenomenon requiring clarification. However, in recent years, this disease has entered the field of neurosurgery. With the advent of computerized imaging, particularly helicoidal CT with bone reconstruction and magnetic resonance imaging, demonstrating the anatomical and biomechanical peculiarities and describing the compromised vascular relationships of the craniovertebral region in these malformations have become possible.Advances in research in the area have also provided us with a better understanding of the pathophysiological mechanisms and profiles of the clinical presentations of these patients, which is essential to directing surgical treatment. Considering BI/CM-I without instability or posterior compressions, symptomatology resolution benefits from simple posterior decompression, in cases with instability cranial-cervical or atlantoaxial, fixation is necessary. Using the anterior approach  in patients with brain stem compression without instability, and posterior arthrodesis is then reserved for patients with functional instability.


The neocortex is the largest part of the mammalian brain and is the seat of our higher cognitive functions. This outstanding neural structure increased massively in size and complexity during evolution in a process recapitulated today during the development of extant mammals. Accordingly, defects in neocortical development commonly result in severe intellectual and social deficits. Thus, understanding the development of the neocortex benefits from understanding its evolution and disease and also informs about their underlying mechanisms. Here, I briefly summarize the most recent and outstanding advances in our understanding of neocortical development and focus particularly on dorsal progenitors and excitatory neurons. I place special emphasis on the specification of neural stem cells in distinct classes and their proliferation and production of neurons and then discuss recent findings on neuronal migration. Recent discoveries on the genetic evolution of neocortical development are presented with a particular focus on primates. Progress on all these fronts is being accelerated by high-throughput gene expression analyses and particularly single-cell transcriptomics. I end with novel insights into the involvement of microglia in embryonic brain development and how improvements in cultured cerebral organoids are gradually consolidating them as faithful models of neocortex development in humans. The cerebral cortex, or neocortex, is the part of our brains primarily responsible for abstract thinking and our unique cognitive abilities as human beings. It is by far the most complex biological structure, and it forms during embryonic development following a sequence of genetically predefined molecular and cellular events. This process of embryonic development recapitulates the emergence of the human cerebral cortex during evolution. Thus, understanding neocortical development in humans and other species tells us about the magnitude of its complexity, how it differs from neocortical development in non-humans, how it emerged during evolution from simpler brains, and what goes wrong in developmental brain disease.Through the use of informative experimental animal species, much has been learned about the basic processes of neocortical development: neural stem and progenitor cell (NSPC) proliferation, generation, and migration of neurons from their place of birth to their final location in neocortical layers and the growth of neural processes and establishment of nerve connections. Recent advances in genome editing, tissue culture, and DNA sequencing have accelerated our understanding of neocortical development at many levels. Here, I briefly summarize some of the most significant advances in our understanding of neocortical development generated recently by the international community, and I give special attention to progenitor proliferation and neurogenesis of dorsal progenitors and projection neurons. Although much remains to be learned, the emerging picture shows that the evolutionary and developmental emergence of the human neocortex involved a plethora of genetic and epigenetic changes, including novel genes and variants, functional gene networks, and novel cell types and cellular specializations.Development of the neocortex begins with the proliferation of NSPCs, which amplify their own pool prior to generating neurons. Recent work shows that the proliferation of NSPCs and their mode of neuron production vary across species, and previously unsuspected mechanisms of molecular regulation have been identified. Novel insights about the diversity of progenitor cells and how their neuronal output contributes to build the cerebral cortex are also emerging.2, intermediate progenitor cells (IPCs) were identified5. IPCs are transit-amplifying progenitors expressing the transcription factor Tbr2 and producing the majority of excitatory neurons in the mouse and rat neocortex7. Most IPCs cluster and undergo mitosis in a layer basal from the ventricular zone (VZ), the subventricular zone (SVZ), although a subset reside in the VZ and undergo apical mitosis, named short neural precursors8. Further studies in primates led to the discovery of an expanded and specialized SVZ, subdivided in inner and outer domains 9. These layers were later identified in other species with an expanded neocortex, like ferret, cat, and sheep10 and even in New World monkeys and the Amazonian rodent agouti12. Progenitor cell lineage tracings in human, macaque, ferret, and mouse led to the discovery of additional types of basal progenitor cells in the developing neocortex, which are bound by complex lineage relationships. These include various types of basal radial glial cells (bRGCs)15 and subapical progenitor cells16. The relative abundance and proliferative capacity of these progenitor cell types are much greater in species with a neocortex that is large and folded (carnivores and primates) than in those where it is small and smooth (mouse and rat). This has been proposed to contribute to the evolutionary increase in complexity, or complexification, of the neocortex18.Work in the last decade has identified a diversity of NSPC types and their lineage relationships. Following the seminal discovery of apical radial glial cells (aRGCs) as the primary type of cortical progenitor cell23. This illustrated the profound diversity of transcriptional landscapes in cortical development at all levels, including folding and across phylogeny, and set the conceptual foundations for the next technological leap: transcriptomics of single cells. The advent of single-cell transcriptomic analyses has revolutionized our approach to studying cortical development by providing a global and unbiased picture of cell diversity with unprecedented resolution26. This technology has enabled identification of multiple sets of transcriptionally distinct progenitor cell classes in the cortical primordium, generating excitatory neurons29, and in the basal ganglia, generating inhibitory interneurons31.Pioneer transcriptomic studies of the developing cerebral cortex using bulk tissue, identified differences in gene expression between germinal layers, cortical areas, developmental stages, and mammalian species36. Early experimental studies of these fundamental questions indicated that the fate potential of cortical progenitors is temporally restricted, such that early progenitors can produce neurons for all cortical layers but late progenitors can produce neurons for superficial layers only37. Such late fate restriction would be cell-autonomous as late cortical progenitors continued producing superficial-layer neurons even when transplanted into the new cellular environment of a young host cortex37. The identification of a subset of RGCs that expressedCux2 and that were fate-restricted to produce upper-layer neurons further supported this model35. However, such fate-restricted progenitors have not been identified in single-cell transcriptomic studies38. Rather, some of these studies support the existence of epigenetically regulated temporal molecular birthmarks in RGCs, which act in their daughter neurons as seeds for neuronal diversity. It is proposed that these conserved differentiation programs may then be integrated with environmental (non-cell-autonomous) cues to ultimately define the identity of the neuronal progeny40. Nevertheless, controversial points of view on these and related issues remain because of differences in single-cell data processing, analysis, and interpretation41.Single-cell analyses are also beginning to shed light on long-standing hypotheses about the heterogeneity of cortical progenitor cells and the dynamics of their lineage and fate potential during development43. Recent studies reveal that indirect neurogenesis is the major mode of producing deep as well as superficial cortical layers in mouse44 and that it also exists in non-mammals, albeit at lower levels and mostly in birds45. At the molecular level, regulation of the balance between direct and indirect neurogenesis is phylogenetically conserved across amniotes, from snakes to birds and mammals, including humans, where high Robo1/2 signaling promotes expression of the Notch ligands Jag1/2 while repressing the canonical ligand Dll144. Blockade of this signaling system drives indirect neurogenesis, increasing neuron numbers and cortex size. Intriguingly, indirect neurogenesis also correlates with hyperpolarization of apical progenitor cells, which represses Wnt signaling40. Changes in the mode of neurogenesis are responsible for the reduced cortex size in developmental brain disease, like microcephaly induced by Zika virus infection. In this case, activation of the unfolded protein response drives direct neurogenesis, leading to premature and limited neuron production and to a small cortex48.Cortical excitatory neurons may be generated directly from the primary progenitor cells (aRGCs) or indirectly via secondary basal progenitors such as IPCs and bRGCs. Indirect neurogenesis is considered a milestone of mammalian cortical evolution, enabling a phenomenal increase in the numbers of neurons produced, particularly those destined to superficial layers, and leading to cortical expansion50. Similarly, regulation of chromatin accessibility and other mechanisms related to non-coding genomic regions critically determines levels and patterns of gene expression in the developing cortex, defining neuron production, cortex size, and area identity52.Cerebral cortex size depends on the mode of neurogenesis and also on the proliferative activity of cortical progenitor cells. Multiple mechanisms regulating progenitor cell proliferation have recently been uncovered. Regulation of gene transcription by epigenetic mechanisms has emerged as a key factor where histone deacetylases and methyltransferases regulate the generation and position of IPCs, neuron migration, and cortical lamination55. This includes proteins regulating the cell cycle, like Ccnd2, and lengthening of G1, S, and M phases of the cell cycle, which depletes progenitor cells causing premature neurogenesis or apoptosis58.One of the most exciting findings has been the identification of mRNA species transported within the long basal process of aRGCs and locally translated at their basal endfeet, next to the pial membranes59, and bRGCs are usually depicted as having a single smooth and unbranched basal process62. Recent observations demonstrate that the degree of process branching and elaboration in both IPCs and bRGCs is greater in ferret and human (which have a large and folded cortex) than in mouse  and this is linked to a greater proliferation rate of these cortical progenitor cells64. Basal progenitor process growth and proliferation are related to the membrane-bound protein PALMD, enabling these cells to receive pro-proliferative signals related to integrin function65. Indeed, modulation of cortical progenitor cell proliferation by cell-extrinsic signals has now been demonstrated to occur from multiple sources, including growing axons and migrating neurons67, extracellular neurotransmitters and ions69, and Notch, Wnt, Fgf, and Shh signals70.IPCs are usually depicted as round cells extending few short processes71, YAP72, Insm1 via the apical adherens protein Plekha773, and the centrosome-associated protein Akna74.Once IPCs and neurons are born from aRGCs, they must first delaminate and migrate away from the VZ toward the SVZ. This critical process is regulated by several signaling mechanisms, including Roboet al.67 [2019] for an excellent review on neuron migration.)Once neurons are born, they must migrate from their place of birth in the germinal layers to their final location in the neuronal layers. Neuronal migration is a multi-step process that begins with neuronal delamination from the VZ and movement to the SVZ. (See Silva75.New advances in understanding cortical development have identified the microtubule-associated protein Lszts as a master regulator of cellular dynamics, promoting the delamination of neurons and bRGCs born from aRGCs by altering apical junction organization76. During this process, NeuroD1 expressed by multipolar cells represses Prdm16, which regulates mitochondrial reactive oxygen species, and this signaling axis is crucial for the regulation of the multipolar phase migration77. Dbnl, a protein interacting with F-actin, is another key regulator of neuronal multipolar morphology, polarity, and migration by regulating the levels of N-cadherin78.Once newborn neurons delaminate from the VZ, they enter the SVZ and undergo a transition phase displaying multipolar morphology80 has been challenged by new observations, demonstrating frequent branching and thus more complex migratory behaviors than previously reported81. In fact, leading process branching is much more frequent in the developing cortex of ferret than mouse and is related to the tangential displacement of radially migrating neurons. Thus, this seems directly related to the maintenance of the radial organization of the cerebral cortex during the tangential expansion and folding of the neocortex82. However, an excessive tangential displacement of cortical neurons is deleterious, and the horizontal tiling of the developing cerebral cortex, or regular distribution of its radial units, must be actively maintained. The microtubule stability regulator protein Memo1 plays key functions in the maintenance of RGC structure and cortical tiling by repressing the hyperbranching of the basal process of RGCs and the excessive dispersion of radially migrating neurons83. On the other hand, it was recently shown that the chromatin-modifying enzyme Prdm16 is also necessary for transcriptional silencing in RGCs and to promote the migration of late-born cortical neurons and cortical layering49.Cortical neurons resume radial migration by re-acquiring polarity and extending a single leading process as they exit the SVZ. This leading process establishes intimate adhesive interactions with the basal process of RGCs for guidance in their migratory displacement. The long-held concept that the leading process of these radially migrating neurons is single and unbranched44. Mechanisms regulating this critical balance, including transcriptional programs regulated by progenitor cell membrane polarity40 and canonical signaling pathways like the unfolded protein response46, some of which are highly conserved across amniotes like Robo and Dll144, are beginning to be identified.A fundamental feature of the evolution of cerebral cortex in amniotes is the phenomenal increase in neuron number and expansion in size. This process is recapitulated during embryonic development, and recent work demonstrates the importance of the balance between direct and indirect neurogenesis84. Likewise, innovations in progenitor cell lineages are critical for the emergence and expansion of the OSVZ85, the basal germinal layer typical of big and folded brains, which is absent in mice and is perturbed in human diseases that affect brain size85.Beyond the emergence of indirect neurogenesis, cortical evolution involved additional key mechanisms. Cell lineage labeling and single-cell transcriptional analyses have revealed a remarkable evolutionary increase in diversity of cortical progenitor cells, particularly at the genetic level. This includes, for example, multiple subtypes of aRGCs and bRGCs identified in human, macaque, or ferret but not in mouse or rat22 and also miRNA-mRNA modules in the embryonic human brain that undergo dynamic transitions during development and that identify expression networks in specific cell types87. As for protein-coding genes, recent studies have identified genes that emerged in the recent human lineage by means of total or partial duplication, and that promote cortical progenitor cell proliferation. Other studies have identified programs of gene expression in cortical progenitor cells that are human-specific91.The search for genetic mechanisms evolved in primate and human phylogeny which are likely relevant in the evolution of their neocortex, has led to the identification of primate-specific and human-specific genetic programs expressed in the developing cerebral cortex. These include whole collections of primate-specific miRNAs targeting cell cycle genesSCN3A function in progenitor cells68, of gliogenesis92, and of extracellular matrix proteins93, in the mechanical aspect of tissue folding. Intriguingly, the organization of folds in the frontal cortex is widely conserved from Old World monkeys to hominoids94, which offers a remarkable opportunity to study cortical evolution and the acquisition of higher brain functions in primates.Species with large brains have a tendency of being folded, and knowledge of specific mechanisms involved in cortex folding has also increased recently. This highlights the relevance of the sodium ion channel97. Microglia may also contribute to progenitor cell delamination and expansion of ISVZ/OSVZ in primates95. Moreover, microglia are critical regulators of brain wiring, contributing to the specification of neural circuits and relaying information from the periphery, including the microbiota99.Largely ignored previously in the field of neocortical development, microglia have become a new relevant component in our understanding of this process. Microglial cells are found in the developing neocortex at much earlier stages and at much greater abundance than previously considered; there, they interact intimately with progenitor cells and regulate their number, hence emerging as important players in the regulation of neurogenesis100, these have become the Rosetta stone to study and manipulate human brain development101. Not only can we now grow human cerebral organoids for many months, recapitulating many of the early features of cortical development, but they can be grown to form functional circuits and be responsive to sensory stimuli102. Most importantly, the recent design of a culture protocol to generate highly reproducible cerebral organoids is a fundamental milestone for the consolidation of this as a faithful model of human brain development103. Comparison between organoids grown from human and chimpanzee cells reveal human-specific features of cortical progenitor cells104 and the validity of these organoids to advance our understanding of human brain evolution106.Although it is not possible to study the development of the human neocortex at the experimental level, major technological breakthroughs in the last few years on stem cell reprogramming and tissue culture offer possibilities that were previously unthinkable. Following the first protocol to generate cerebral organoids from human embryonic stem cells and induced pluripotent stem cells107, and patient-derived iPSCs are used to model and hopefully rescue the disease108. Only through our ability to use and combine these amazing tools in creative ways will we decipher what makes us human and what genetic changes occurred during evolution that led to the development and emergence of the human neocortex.Understanding neocortical development requires working at many different levels, from single-cell transcriptomics to tissue mechanics, and this must be applied to studying histogenesis at multiple levels, from neurogenesis to connectivity and cortex folding. Understanding neocortical evolution and disease requires understanding development across relevant informative species and in the context of genetic or contextual failure. Recent technological advances offer unprecedented opportunities for conducting this research; for example, single-cell genomic analyses help elucidate molecular changes in human brain disease at the resolution of cell typesaRGC, apical radial glial cell; bRGC, basal radial glial cell; IPC, intermediate progenitor cell; ISVZ, inner subventricular zone; NSPC, neural stem and progenitor cell; OSVZ, outer subventricular zone; RGC, radial glial cell; SVZ, subventricular zone; VZ, ventricular zone