Many attempts have been made to define nature of viruses and to uncover their origin. Our aim within this work was to show that there are different perceptions of viruses and many concepts to explain their emergence: the virus-first concept , the escape and the reduction theories. Moreover, a relatively new concept of polyphyletic virus origin called “three RNA cells, three DNA viruses” proposed by Forterre is described herein. In this paper, not only is each thesis supported by a body of evidence but also counter-argued in the light of various findings to give more insightful considerations to the readers. As the origin of viruses and that of living cells are most probably interdependent, we decided to reveal ideas concerning nature of cellular last universal common ancestor (LUCA). Furthermore, we discuss monophyletic ancestry of cellular domains and their relationships at the molecular level of membrane lipids and replication strategies of these three types of cells. In this review, we also present the emergence of DNA viruses requiring an evolutionary transition from RNA to DNA and recently discovered giant DNA viruses possibly involved in eukaryogenesis. In the course of evolution viruses emerged many times. They have always played a key role through horizontal gene transfer in evolutionary events and in formation of the tree of life or netlike routes of evolution providing a great deal of genetic diversity. In our opinion, future findings are crucial to better understand past relations between viruses and cells and the origin of both. Nowadays, to give a concise definition of virus nature is troublesome. Researchers of different standpoints have proposed several interpretations. Viruses by their nature seem to be entities somewhere in between inert and living worlds . For decThe range of viral genome sizes spans three orders of magnitude and simple size-based distinction between viruses and cells valid for over a century cannot be used any longer after the discovery of giant viruses, also known as giruses . One of Many researchers postulate that viruses are of polyphyletic origin and different RNA and DNA viruses derived independently as opposed to monophyletic cellular domains coming from one ancient ancestor LUCA , which is a logical consequence of the binary mechanism of cell division . There iWith the advent of this new knowledge it was a bit unthoughtfully proposed by Carl Woese that cellular evolution could not be solely explained by the classical Darwinian mode of thinking . However9 virions/ml), it can be determined that 1031 bacteriophages infect 1024 bacteria cells per second [Phycodnaviridae  as well as by Amoeba and Algae. It suggests that these viruses could mediate horizontal transfers between different cellular genomes [If we imagine that 1 ml of seawater contains 1 million bacteria cells and ten or even a thousand times more viral sequences  genes with detectable homologues in cellular life forms, 2) virus-specific genes such as ORFans and 3) viral hallmark genes with only distant homologues in cellular organisms . None ofAvsunviroidae possess a hammerhead ribozyme structure and can carry out cleavage of oligomeric forms of RNA to the monomeric forms, which potentially makes them descendants of the earliest biomolecules present on Earth [The virus-first (or co-evolution) hypothesis was first proposed by d’Herelle who claimed that viruses are ancestral to cells . Others on Earth , 49. VirEven though we have no insight, whether there were the same rules in this ancient realm, according to our knowledge of the current living world there is a strong inverse relationship between genome size and mutation rate across all replication systems, therefore it is possible that pre-LUCA genomes were both small and highly error prone and hence RNA virus-like . In the There is a growing body of evidence that viruses arose even before LUCA, that more appropriately should be denoted as Last Universal Cellular Ancestral State (LUCAS) . MoreoveThe escape or vagrancy (cell-first) hypothesis describes viruses as derived from cellular RNA or/and DNA fragments such as plasmids and transpozons, which escaped from cells. When such RNA or DNA fragments acquired protein coat they became independent entities capable of infecting cells from which they had escaped previously . As alreBacillus subtilis bacteriophage Ф29, use a similar atypical protein-priming mechanism to replicate their DNA (unknown in the cellular world) and encode a unique type of DNA polymerase from the subfamily of polymerases B. It can use such a DNA template to initiate its own replication and has no representatives in currently living cells [The reduction or degeneracy (cell-first) hypothesis states that viruses come from small primordial cells (not necessarily primitive), which lost their cellular elements in the course of evolution. They maintained, however, their genetic material and certain elements needed for replication. For a long time it has been believed that there is no intermediary form between a cell and a virus, because parasites known for the three domains of life have kept their cellular character; they still have ribosomes and are able to synthesize ATP. It is also for that reason that the reduction theory can be easily counter-argued. But then again, it is much easier to imagine this reduction leading to a virus emergence in a world of RNA cells, because these cells were much simpler than the modern ones. RNA-cell living as a parasitic endosymbiont in another RNA cell could have lost its own machinery for protein synthesis and for energy production, using instead those of the host . The preng cells . It seemng cells , and thang cells . Howeverng cells .Acanthamoeba polyphaga mimivirus (APMV) [Megavirus chilensis) [In recent years, the reduction hypothesis was revived by the discovery and genomic characterization of s (APMV)  with a vs (APMV) . Furthers (APMV) . The diss (APMV) , Megavirilensis) , Pandorailensis) , and Pitilensis)  created ilensis) –72. It hilensis) . That isilensis) .Tectiviridae as it is shown by homology of the major capsid protein (MCP) in these groups. The evolution of giant viruses had been pushed to the extreme, which explains their big genome size [However, this evolutionary theory suffers from several major weaknesses. More than 93 % of Pandoraviruses genes resemble nothing known in all available sequence databases, therefore their origin cannot be traced back to any known cellular lineage , quite some size , 78. To 2/CO2 couple, and being naturally chemiosmotic is among many other hypotheses. This point goes a long way towards explaining why chemiosmosis, and the proteins that harness ion gradients, are universal among living cells [The co-evolution of viral elements and cellular forms has also been described as incessant arms race with various forms of cooperation . It starng cells . LUCA cong cells . Howeverng cells , 86 as wng cells , 87. Theng cells . The folng cells . Two virng cells .Viruses can be considered as living organisms only when they redirect cellular metabolism to reproduce virions, hence infection transforms the ribocell (cell encoding ribosomes and dividing by binary fission) into a virocell (cell producing virions) or ribovirocell (cell that produces virions but can still divide by binary fission) , 5. ThisLater, it was proposed that DNA replication machineries of each domain could have also originated from three different viruses that helped create three major branches of life: LACA – last archaeal common ancestor, LBCA – last bacterial common ancestor, and finally LECA – last eukaryotic common ancestor . This coIt is legitimate to say that the tree of life is composed of cells/organisms coding for ribosomes and multiplying by binary fission, and viruses are excluded from the tree of life (cells) as entities encoding capsid proteins and undergoing intracellular process in order to propagate . They ar


High-grade serous ovarian cancer remains the most common sub-type of ovarian cancer and, characterized by high degrees of genomic instability and heterogeneity, is typified by a transition from early response to acquired resistance to platinum-based chemotherapy. Conventional models for the study of ovarian cancer have been largely limited to a set of relatively poorly characterized immortalized cell lines and recent studies have called into question the validity of some of these as reliable models. Here, we review new approaches and models systems that take into account advances in our understanding of ovarian cancer biology and advances in the technology available for their generation and study. We discuss primary cell models, 2D, 3D, and organotypic models, and “paired” sample approaches that capture the evolution of chemotherapy failure within single cases. We also overview new methods for non-invasive collection of representative tumor material from blood samples. Adoption of such methods and models will improve the quality and clinical relevance of ovarian cancer research. The mortality rate for ovarian cancer is high as disease largely remains undetected, due to the vague nature of its symptoms and lack of reliable biomarkers, until patients finally present with high volume, disseminated disease. The current standard care for ovarian cancer involves cytoreductive surgery followed by combination chemotherapy with platinum compounds and taxanes. However, chemoresistant disease typically recurs in patients, most commonly in the high-grade serous (HGS) sub-type, with a low 5-year average survival rate of less than 40%. Ovarian cancer is a very heterogeneous disease, with the four most common sub-types of epithelial ovarian cancer (EOC) being serous, endometrioid, mucinous, and clear cell. They can be further divided into low-grade type I (relatively resistant to platinum-based chemotherapy) and the more common high-grade type II  tumors. Type I tumors, including low-grade serous and endometrioid, mucinous and clear cell histotypes, make up 10–20% of EOC, present at early stage (FIGO I-II), genetically have near normal gene copy number, are usually wild type for p53 and harbor characteristic mutations in genes such as Ras (mucinous and low-grade serous) and PTEN (endometrioid) among others. Type II lesions including HGS cancers, undifferentiated cancers, carcinosarcomas, and high-grade endometrioid, typically present at advanced stage (FIGO III–IV), are characterized by high genomic instability (near 50% deficiency in Homologous Recombination repair), near 100% p53 mutation rate, and have extensive DNA copy number changes  or solid tumor allows us to derive primary tumor cell cultures that closely resemble the patient situation, therefore representing a more experimentally accurate model than poorly characterized immortalized cell lines, often of uncertain origin. Primary tumor cell cultures are kept for a relatively short period of time and can be cumbersome to start and maintain in culture, but can be developed into well-annotated secondary immortalized cultures. Different methodologies have been developed for the isolation of EOC tumor cells from ascites and solid tumors. Here, we outline a number of recently published methods to retrieve and culture EOC tumor cells, the methods for development of immortalized cell lines from primary cultures and options available for 3D cell culture systems that attempt to more closely model the in vivo setting.The clinical relevance of cell line models is a topic that is often debated. The use of established cell lines, while certainly not without their merits, may misrepresent responses to targeted therapies and users should research carefully the nature of the cell line models they chose, and how closely they relate to the clinical condition. To uncover the molecular mechanisms driving EOC development and treatment, suitable disease models must be available to faithfully mirror the disease Ascites fluid can be a rich source of tumor cells that are highly accessible following paracentesis from the patient. Isolation and primary culturing of tumor cells from ascites have become more widespread and several different methods have been established to achieve this aim –8. A widDifferent media can also influence the growth of primary tumor cells. Originally optimized for the growth of primary ovarian surface epithelial (OSE) cells , a combiA significant problem that arises however in the growth of EOC tumor cells following isolation from ascites is the presence of other contaminating cells such as fibroblasts or mesothelial cells. Careful monitoring of tumor cells in culture from any culturing technique is required to prevent contamination of the cultures from these cell types. Proliferation of fibroblasts will cease after a number of passages; however, if not contained from initial culturing, fibroblasts can outgrow the tumor cells and take over the culture. Selective trypsinization with low concentrations of trypsin can be used to remove contaminating fibroblasts or mesothelial cells from primary cultures, as they tend to detach more rapidly from plastic than tumor cells . HoweverRecent advances have lead to the use of magnetic enrichment for detection or purification of cells from fluid specimens . The EpCSeveral laboratories over the previous decades have developed various methods for EOC tumor cell isolation from solid tumor and metastatic deposits. Langdon et al. have advocated mechanical dissociation of tumor fragments using crossed scalpels, with cell suspensions filtered through sterile gauze to remove any remaining cell clumps before placing in culture , 10. Thead infinitum. Establishment of a secondary culture can be achieved either by spontaneous or induced transformation of cells, e.g., SV40 T antigen induced immortalization. Spontaneous immortalization of cells can occur as cells maintained in culture over time can overcome senescence without the addition of exogenous agents to induce immortalization  are expected to become commonplace and to be developed and validated for prognostication and patient stratification in future clinical trials without the need for invasive diagnostic procedures.ex vivo and relevant in vitro models must be developed that more closely resemble the in vivo tumor environment, an opinion shared by others in recent reviews  models  models  and pati) models , to adva) models , whereasn cancer . IdeallyThe 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.


Acetylcholinesterase inhibitors (AChEIs) are widely used to delay cognitive decline in Alzheimer's disease. Observational studies in routine clinical practice have shown cognitive improvement in some groups of patients receiving these agents but longitudinal trajectories before and after AChEI initiation have not previously been considered.To compare trajectories of cognitive function before and after AChEI initiation and investigate predictors of these differences.A retrospective longitudinal study was constructed using data from 2460 patients who received AChEIs and who had routine data on cognitive function  before and after AChEI initiation. Longitudinal MMSE change was modelled using three-piece linear mixed models with the following segments: 0–12 months prior to AChEI initiation, 0–6 months and 6–36 months after initiation.MMSE decline was reversed  during the 6-month period following AChEI initiation compared with the slope in the one year period before AChEI initiation. The slope in the period from 6–36 months following AChEI initiation returned to the pre-initiation downward trajectory. The differences in slopes in the 1 year period prior to AChEI initiation and in the 6 months after initiation were smaller among those with higher MMSE scores at the time of AChEI initiation, among those who received a vascular dementia diagnosis at any point, and among those receiving antipsychotic agents.In this naturalistic observational study, changes in cognitive trajectories around AChEI initiation were similar to those reported in randomised controlled trials. The magnitude of the difference in slopes between the 1 year period prior to AChEI initiation and the 6 month period after AChEI initiation was related to level of cognitive function at treatment initiation, vascular comorbidity and antipsychotic use. Dementia is a major challenge because of its increasing prevalence, substantial disability and high cost. Acetyl cholinesterase inhibitors (AChEIs) remain the mainstay of pharmacotherapy whose wide clinical use is largely justified by 3- to 6-month improvements in cognitive and global function in Alzheimer's disease with a Cochrane review estimating a 1.37  Mini-Mental State Examination (MMSE) score improvement at 6 months after AChEI initiation This study made use of a routine clinical data resource sourced from a large provider of dementia care, describing and comparing trajectories in MMSE scores before and after AChEI initiation followed by an investigation of factors associated with these changes in slope.The study was approved as an anonymized dataset for secondary analysis by the Oxfordshire Research Ethics Committee C (reference 08/H0606/71).A retrospective observational study was conducted using data from the South London and Maudsley NHS Foundation Trust (SLAM) Biomedical Research Centre (BRC) Case Register. This data resource has been described in detail Using keyword searching functionality in the SLAM BRC Case Register, records were retrieved on all patients who had received AChEI drugs  during 2003–2010 and information was manually retrieved including all recorded measures of cognitive function within 12 months before and 36 months after AChEI initiation. In UK clinical practice, AChEI agents were licensed for the treatment of Alzheimer's disease during the period of observation; however, in routine clinical practice there was flexibility in interpretation of this diagnosis – for example, in relation to comorbidity with vascular dementia. The sample for this analysis was of all people receiving these agents and recorded diagnoses were not applied as inclusion/exclusion criteria. In British dementia treatment services, cognitive function continues to be primarily monitored in routine clinical practice using the Mini-Mental State Examination (MMSE) All MMSE scores during the 4-year observation period were used to model cognitive trajectories. Entries describing scores with below-30 denominators due to missing items were corrected by the number of missing items. For example, if a 28 denominator was cited, 2 points were added to the numerator for analysis. In addition, the MMSE score closest to the date of AChEI initiation was categorised as a covariate into standard groups  for stratified analyses. The following additional information was extracted from the record using both structured fields and manual text review: age (at AChEI initiation), sex, ethnicity (white vs. other), and marital status (married/cohabiting vs. other). Highest educational qualification was categorised into three groups: i) no qualification, ii) standard qualification , iii) advanced qualification . As a proxy measure of socio-economic status, area-level deprivation scores in 2007 were available through an anonymised link created between lower super output area residence code (an address unit representing between 1500–2000 residents) and summary data for that area from 2001 UK Census output. The index of multiple deprivation is derived from seven domains: income, employment, health, education, housing and services, crime, and environment . Patients not infrequently received more than one diagnosis during the course of their treatment and the presence of Alzheimer's disease, vascular dementia and Lewy body dementia diagnoses were ascertained as non-exclusive binary variables. The presence or not of a vascular dementia diagnosis at any point was considered as a proxy measure of comorbid cerebrovascular disease. Recorded medication was categorised into the following groups: antidepressants, antipsychotics, diabetes drugs, gastrointestinal drugs, lipid regulators, cardiovascular disease drugs, other central nervous system drugs, respiratory drugs, and antiplatelet, fibrinolytic or anticoagulant drugs.The analysed cohort was initially compared to the wider cohort of all patients receiving AChEI treatment. The trajectory of MMSE scores in the sample was initially modelled for observational purposes using a non-parametric regression method: the Generalised Additive Model for Location, Scale and Shape (GAMLSS) introduced by Rigby and Stasinopoulos Within the years of data examined, a total of 3416 patients had received AChEI treatment of whom 2460 had sufficient MMSE scores for analysis. Characteristics of these samples are described and compared in From parametric (piecewise linear mixed) models, the three MMSE slopes were calculated to be a decline of −2.45  points per year during the 12 months prior to AChEI initiation, an increase of 1.73  points per year during the 6 months after initiation, and a decline of −2.68  points per year during the 6–36 month period. Differences in slopes for the whole sample and by MMSE strata are displayed in Considering the 6-month MMSE slope improvement, further interactions with socio-demographic and clinical covariates are summarized in In this large observational study of routine AChEI treatment provision, we investigated the difference between pre- and post-treatment trajectories of cognitive function and predictors of these slope differences. On average, a significant improvement was observed in the MMSE trajectory by 4.16 points per year in patients who received AChEIs during the 6 months after treatment compared with the 12 months before treatment. However, MMSE slopes after 6 months were near-identical to pre-treatment slopes in most cases. When stratified by MMSE score at AChEI initiation, people with higher scores (MMSE scores 21 or over) at the time of AChEI initiation on average had a smaller improvement  than peoRandomised controlled trials of AChEI treatment in Alzheimer's disease specifically have demonstrated an improvement in MMSE score in the intervention arm at 6 months. In our naturalistic sample from routine clinical practice, the pattern was interestingly similar with a slope of 1.73 MMSE points per year improvement over the 6 months after treatment initiation. As previously stated, observational studies to date have only described slopes following treatment, but have given rise to heterogeneous findings. One UK study found an improvement of 1.8 MMSE points per year among 939 patients with a mean follow up period of 4 months Several studies have suggested that MMSE score at baseline is a predictor of response to AChEIs Cognitive improvement following AChEI treatment was found to be stronger in patients from non-white compared to white ethnic groups. In the geographic catchment covered by SLAM, non-white elders are predominantly African-Caribbean, although it was not possible to break down non-white groupings into more specific subtypes. Higher prevalence of dementia has been found in older African- Caribbean compared to white UK-born residents as well as a dementia onset in African-Caribbean patients nearly, on average, 8 years younger than their white counterparts Considering dementia diagnoses as covariates, the presence of vascular dementia was associated with a significantly weaker difference between pre- and post-treatment slopes. Previous longitudinal studies in dementia have found accelerated cognitive decline associated with cerebral infarcts and congophilic angiopathy Analyses of other medications found that receipt of gastrointestinal drugs, anticoagulant agents, and antipsychotic agents was associated with smaller MMSE slope differences after AChEI initiation. In a pooled analysis of the placebo arms of six AD trials, antipsychotic use was found to be associated with significantly lower cognitive function Our study found that a better improvement in MMSE score after AChEI treatment was present in patients of non-white ethnicity, those without vascular dementia diagnosis at any point, those not receiving antipsychotic agents, those not receiving gastrointestinal drugs, and those not receiving anti-platelet, fibrinolytic and anticoagulant agents. However, although these MMSE trajectory differences were statistically significant, they were relatively small in size and detectable as a group-level effect over a large sample. It cannot therefore be concluded from these data that they were sufficiently clinically significant to warrant alterations in routine practice – this would require a longer-term comparative evaluation of subsequent disease course and of broader outcomes beyond cognitive function, which was outside the scope of this study.This study had considerable advantages over other comparable cohorts, not only in the data available on pre-treatment MMSE slopes but also in the substantial accumulated follow-up – approximately 5900 person years in total . Although case registers have a long history and are widely used in mental health and dementia research, we believe that the SLAM BRC Case Register is likely to be the largest in Europe at least containing the necessary depth of data for this type of study The key limitations concern the observational nature of the study and the fact that data were from routine clinical care rather than obtained through a research study. However, errors in measurement (for example the limitation of the MMSE in comparison with more in-depth measures) will have obscured rather than exaggerated associations of interest. Considering sample representativeness, under the UK National Health Service structure, SLAM provides all mental health care (including dementia services) to its geographic catchment. Because there was minimal AChEI prescription by general practitioners during the period these data were collected, the sample represents all people in the catchment receiving these agents. However, people who receive AChEI intervention are only a subset of cases with dementia in the community. Perceived likelihood of a given outcome might have had an influence on inclusion, although this is unlikely because there are no commonly agreed factors predicting good or poor response . Considering pre-treatment MMSE slopes, more precipitous decline might predict someone with dementia coming to medical attention and it is possible that this accounted at least in part for the slope improvement around AChEI initiation In terms of loss to follow-up, mortality rates were relatively low (26.8% by the end of the observation period). Although analyses were of all cognitive data during the observation period rather than restricted to those during AChEI treatment, withdrawal from treatment would render discharge and loss to follow-up more likely. Withdrawal from AChEIs is also an issue for the primary analyses. In long-term studies of AChEI, high rates of withdrawal from treatment have been reported Another limitation in this study was related to statistical concepts. We used models that assumed that the MMSE has linear scaling properties, which is an assumption that has frequently been argued. One study In summary, in this naturalistic observational study, changes in cognitive trajectories around AChEI initiation were interestingly similar to those reported in randomised controlled trials. Clearly the effect of these agents on cognitive decline in dementia has to be concluded from the trial evidence. However, sample sizes in trials are too small, even when combined, to provide data on predictors of good/poor response to treatments. Addressing these questions relies on large observational datasets and our findings suggest that the growing use of electronic health records, coupled with the ability to extract automated data from text fields on routine measures such as the MMSE, provides important potential opportunities for advancing research into routine interventions and their real-world outcomes.


Yersinia species Yersinia pseudotuberculosis and Yersinia enterocolitica and the causative agent of plague, Yersinia pestis, are able to survive in a large variety of environmental reservoirs  as well as warm-blooded animals  with a particular preference for lymphatic tissues. In order to manage rapidly changing environmental conditions and interbacterial competition, Yersinia senses the nutritional composition during the course of an infection by special molecular devices, integrates this information and adapts its metabolism accordingly. In addition, nutrient availability has an impact on expression of virulence genes in response to C-sources, demonstrating a tight link between the pathogenicity of yersiniae and utilization of nutrients. Recent studies revealed that global regulatory factors such as the cAMP receptor protein (Crp) and the carbon storage regulator (Csr) system are part of a large network of transcriptional and posttranscriptional control strategies adjusting metabolic changes and virulence in response to temperature, ion and nutrient availability. Gained knowledge about the specific metabolic requirements and the correlation between metabolic and virulence gene expression that enable efficient host colonization led to the identification of new potential antimicrobial targets.Deciphering the principles how pathogenic bacteria adapt their metabolism to a specific host microenvironment is critical for understanding bacterial pathogenesis. The enteric pathogenic  Yersinia species  as well as studies on the molecular and cellular aspects of Yersinia pathogenesis have considerably increased our knowledge of how yersiniae establish infections and cause diseases. Over the last decades a large set of specific pathogenicity factors has been identified, which mediate efficient resistance against the host defense systems, manipulate host cell processes and enable the bacteria to colonize, invade and multiply in host tissues. The structure, function and regulation of many of those classical virulence factors have been characterized and their role in pathogenesis has been analyzed using different animal models. However, a simple additional premise for their fitness and success is that they are able to obtain nutrients (C-/N-/energy sources) and ions at the infection site. As a consequence, bacterial pathogens have evolved efficient host-adapted nutrient retrieval strategies to optimize their metabolism and maximize the harvest of essential ions, energy sources and biomass building blocks from tissues encountered during infection. Here, we will discuss recent advances in our knowledge of (i) nutritional adaptation strategies of human pathogenic yersiniae and (ii) molecular mechanisms dedicated to control and adjust metabolic processes with virulence functions.Intensive work on the virulence strategies of all three human pathogenic Yersinia belongs to the family of Enterobacteriaceae and encompasses 17 species, whereby only Y. pseudotuberculosis, Y. enterocolitica, and Y. pestis are known to cause diseases in mammals  acquisition of similar virulence determinants, e.g., the virulence plasmid pYV that encodes the main virulence genes of Yersinia and the chromosomally-encoded cell adhesion and invasion protein Ail, and (ii) functional gene loss and reduced metabolic flexibility  commonly called yersiniosis. Only in very rare cases they can lead to systemic infections and induce extra-intestinal sequelae such as erythema nodosum and reactive arthritis  which enables the bacteria to be transmitted from person-to-person via contaminated droplets , Ail, the homotrimeric autotransporter adhesin YadA, and the PsaA/Myf fimbriae seem to contribute to the dissemination process  plasmid that enables Y. pestis to replicate in and be transmitted by the flea  to deliver anti-phagocytic Yop effector proteins into host cells, mainly professional phagocytes  and is absolutely required for virulence of all three pathogenic Yersinia species. This is based on the fact that the translocated Yop effectors are exotoxins that disable the phagocytic machinery by (i) destabilizing the actin cytoskeleton, (ii) suppression of cytokine production and (iii) induction of apoptosis of phagocytic cells  that supports survival in the flea , induce similar gastrointestinal disease symptoms, whereas Y. pestis and Y. pseudotuberculosis which are very similar genetically (>97% nt identity) exhibit markedly different pathogenicities  triggered in response of the availability of readily digestible sugars  was shown to modulate metabolism and is used to coordinately control the expression of virulence factors via the cAMP receptor protein (Crp) .One prerequisite to succeed in the their hosts is the ability of Yersinia species are chemoheterotrophs, consuming organic molecules for energy and carbon. They possess a complex metabolic system with a full complement of often redundant or alternative catabolic and biosynthetic pathways that render them very flexible and robust against changing nutrient concentrations and genetic manipulations. Early studies revealed that all pathogenic yersiniae are able to catabolize glucose by the Emden–Meyerhof and Entner–Doudoroff pathway with a complete tricarboxylic acid (TCA) cycle and a functional glyoxylate bypass  under anaerobiosis and can degrade 1,2-propanediol and ethanolamine by cobalamine-dependent enzymes using tetrathionate as terminal electron acceptor  dehydrogenase) are under thermal control . Phosphotransferase system (PTS)-encoding genes, glycolysis and phosphoenolpyruvate (PEP)-dependent systems were found to be upregulated  and insecticidal-like toxin genes are upregulated  surface carbohydrate, a major component of biofilms, were found to be induced at moderate temperature and within fleas. Thus, hms-dependent biofilms were assumed to support colonization of the proventriculus and facilitate transmission of plague bacteria  transporter mutants further suggest that there are additional not yet identified transport systems that also contribute to this process  released by polymorphonuclear neutrophils (PMNs). Expression of the nrdHIEF operon encoding for the ribonucleotide reductase and hmp which encodes a flavohemoglobin that detoxifies RNS was highly increased and required for full virulence of Y. pestis  stress in the buboes   did not impact Y. pestis virulence  were essential for competition with the wildtype in vivo , acnA (acotinase A), and fumC (fumarase C) did not affect virulence, that (ii) most of the genes of the TCA were downregulated in vivo  are able to sense external stimuli and convert them into a cellular response, typically by controlling expression of multiple metabolic, but also virulence-associated genes. Some TCS have been reported to influence metabolism and virulence in Y. pseudotuberculosis (see below), and Crp in Y. pestis (see below)  and phosphorylates the cytoplasmic response regulator PhoP  that counteract the activity of CsrA. CsrA acts by binding to conserved (N)GGA motifs in the loop of hairpin structures found close to the ribosomal binding site of the target mRNA thereby affecting translation and/or stability of the transcript. The Csr-RNAs contain multiple CsrA-binding sites and can sequester and inactivate CsrA , a protein encoded by the galETKM operon important for the conversion of galactose to glucose 1-phosphate is repressed in the presence of glucose. Repression is mediated by binding of the Crp-dependent Spot42 sRNA to the leader of the galK mRNA which prevents its translation . However, loss of both RyhB variants had no obvious effect on the dissemination capacity and survival of the bacteria after subcutaneous and intranasal infection. It has been assumed that this is due to redundant iron uptake systems  and YscM2 regulate expression of the Yop effector proteins. Under non-secretion conditions YscM1/YscM2 repress the synthesis of the Yops. This suppression is relieved when both proteins are secreted upon cell contact   pyruvate formation via glycolysis or the Entner–Doudoroff pathway, (ii) oxaloacetate formation via the TCA and (iii) amino acid biosynthesis. This indicates that both Yops are involved in the repletion of central carbon metabolism. Modulation of PEPC activity might be important for the metabolic adaptation process of Yersinia during the infection. The authors proposed a “load-and-shoot” cycle: In order to prepare the bacteria against the phagocytic attack, PEPC is active and replenishes the TCA cycle, as amino acid synthesis is required (loading). During cell contact, the pre-synthesized Yops are rapidly secreted (shooting). As maintaining the energy charge is more needed than biosynthesis during this process, PEPC is inhibited resulting in a shut down of anaplerosis  has significantly increased our knowledge about the complex crosstalk between the primary metabolism and virulence in bacteria. However, current knowledge of host-adapted metabolic functions is still limited since most results are derived from “omic” data obtained in vitro under different virulence-relevant conditions, but not during infection. Thus, future efforts are needed to define growth conditions in the infections sites, tackle utilized C/N sources and identify essential metabolic pathways in the different stages of the infection, e.g., by establishment of in vivo “omics” and fluxome analysis. Furthermore, high-throughput screens aimed to identify metabolic genes essential for infection were often performed with a single strain isolate and a particular animal model. Based on observed strain-specific variations and different types, routes, and animals used for the infection obtained results cannot easily be generalized and requests a comparative analysis of multiple strains per species. Other important issues that need to be addressed are: (i) how certain metabolic traits confer a fitness advantage for enteric Yersinia when faced with different gut commensals or certain host defense mechanisms, (ii) how do yersiniae interfere with the carbon and nitrogen metabolism when they are internalized in host cells, and (iii) how gained information can be exploited to develop novel antimicrobial therapies based on the interference with host-adapted metabolic pathways. Interference with global regulators  or blockage of essential metabolic pathways is an attractive but still unexploited way of controlling plague and other fatale diseases of related pathogens.The analysis of bacterial metabolism specific to infection is most important to fully understand bacterial pathogenesis to design more effective therapies against pathogens. Use of novel technologies (e.g., deep sequencing, 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.


During this period, fewer protein engineering attempts for DNA ligases have been made, as compared to those for DNA polymerases. We summarize the recent progress in the elucidation of the DNA ligation mechanisms obtained from the tertiary structures solved thus far, in each step of the ligation reaction scheme. We also present some examples of engineered DNA ligases, developed from the viewpoint of their three-dimensional structures.DNA ligases are indispensable in all living cells and ubiquitous in all organs. DNA ligases are broadly utilized in molecular biology research fields, such as genetic engineering and DNA sequencing technologies. Here we review the utilization of DNA ligases in a variety of  DNA DNA ligases share a common mechanism and a high degree of structural similarity with other members of the nucleotidyltransferase superfamily, including RNA ligases and RNA-capping enzymes . Like otThe details of each step in the DNA ligation reaction sequence have been clarified by many efforts performed by numerous researchers. Above all, Shuman's group has made extensive contributions toward the elucidation of the DNA ligation mechanisms . We desc in situ investigations of protein-protein interactions ..103].Archaea live in extreme conditions, even in the temperature range of 80°C to 100°C, and have yielded many useful enzymes for gene technology, such as hyperthermostable DNA polymerases and DNA ligases. In this review, we have described the utilization of thermostable DNA ligases in common molecular biology protocols and the structural mechanism of DNA ligase and shown some examples of protein-engineered DNA ligases. Improvements of these enzymes are potentially effective for advancing the existing methods mentioned above and beneficial for constructing novel biotechnological methods. Several protein engineering strategies, such as fusion with other proteins or site-direct mutagenesis based on structural information, may facilitate the construction of application-specific DNA ligases in the future. The enzymes can be improved artificially, based on their three-dimensional structures, even if they have naturally evolved for a long period of time.As many Archaea thrive in extreme environments, it will be very interesting to learn how the fidelity mechanisms of these extremophilic organisms have adapted to overcome these harsh conditions. Therefore, archaeal enzymes will continue to play an important role in future research and will be employed in numerous aspects of gene technology.


Non-invasive brain stimulation (NIBS) may enhance motor recovery after neurological injury through the causal induction of plasticity processes. Neurological injury, such as stroke, often results in serious long-term physical disabilities, and despite intensive therapy, a large majority of brain injury survivors fail to regain full motor function. Emerging research suggests that NIBS techniques, such as transcranial magnetic (TMS) and direct current (tDCS) stimulation, in association with customarily used neurorehabilitative treatments, may enhance motor recovery. This paper provides a general review on TMS and tDCS paradigms, the mechanisms by which they operate and the stimulation techniques used in neurorehabilitation, specifically stroke. TMS and tDCS influence regional neural activity underlying the stimulation location and also distant interconnected network activity throughout the brain. We discuss recent studies that document NIBS effects on global brain activity measured with various neuroimaging techniques, which help to characterize better strategies for more accurate NIBS stimulation. These rapidly growing areas of inquiry may hold potential for improving the effectiveness of NIBS-based interventions for clinical rehabilitation. Stroke is a leading cause of serious long-term adult disability around the world. Recovery of motor function remains highly variable despite standardized rehabilitation programs . We then delve into recent work exploring the effects of local application of NIBS on activity under the stimulating site and in distant brain regions. We discuss the evidence for the application of NIBS techniques in motor rehabilitation and provide a map of possible future research directions, including the combined use of NIBS with neuroimaging techniques, and the use of transcranial random noise stimulation and transcranial alternating current stimulation, among others.Non-invasive brain stimulation (NIBS) has been explored as a possible technical adjuvant of customarily used neurorehabilitative treatments. NIBS, which employs electrical or magnetically-induced currents to stimulate the brain through the scalp, can temporarily excite or inhibit activity in target brain regions. In this review, we first introduce the use of NIBS in basic science and clinical neuroscience, focusing on the two most commonly used NIBS techniques , one single stimulus is applied, for example, over the primary motor cortex  can also be used as a neuromodulatory tool. Low-frequency rTMS (≤1 Hz) can be used to transiently perturb the stimulated brain region inducing a so-called “virtual lesion” , in which short bursts of 50 Hz rTMS are applied at a rate in the theta range (5 Hz)  positioned over the scalp. It is thought that low amplitude currents (ranging from 0.5 to 2.0 mA) applied at the scalp can partially penetrate and reach cortical tissues  generator connected to two relatively large anodal and cathodal sponge-enclosed rubber electrodes . It is now known that patterns of functional connectivity are predictive of successful motor behaviors and motor recovery in healthy individuals and in patients with stroke   for example increases BOLD signal locally, under the stimulating coil, and in distant regions like the right PMd, bilateral ventral premotor cortex, SMA  and the DLPFC in healthy individuals  vs. unilateral tDCS  with fMRI was done in healthy volunteers . In addition, there is significant interindividual variability in results depending on the state of the subject's or network's activity (state-dependency), and the task performed. Evaluation of connectivity effects of tDCS in clinical populations may contribute to the understanding of behavioral deficits in these patients  (Herrmann et al., While tDCS influences neuronal firing rates in a bimodal manner depending on its polarity, tACS seems to up- and down-regulate the firing rate affecting neuronal spike timing (Reato et al., In contrast, tRNS involves the application of alternating currents at different, random frequencies to the scalp. Due to its oscillatory, rather than direct current, nature, it has been proposed that tRNS ensures the application of stimulation is polarity-independent (i.e., neither anodal or cathodal; Miniussi et al., Following stroke, patients with the most successful recovery of motor function are those whose patterns of brain activity as measured by fMRI most resemble those present in healthy volunteers (Johansen-Berg et al., Given these neuroimaging patterns after stroke, it has been proposed that upregulation of activity in the ipsilesional M1 or downregulation in the contralesional M1 might contribute to improved motor control (Ward and Cohen, Similarly, downregulating excitability in the contralesional motor cortex in chronic stroke patients was also associated with improvements in motor function, along with increased cortical motor excitability in the ipsilesional M1 and decreased cortical excitability in the contralesional M1 (Fregni et al., It is also possible to use simultaneous stimulation of the ipsilesional cortex, with inhibition of the contralesional M1. This appears to also produce motor gains when combined with physiotherapy which last for 1 week (Lindenberg et al., To this end, it should be kept in mind that there is by no means agreement on the extent or universality of these beneficial effects and that well-controlled multicenter clinical trials are required to assess this issue (Wallace et al., NIBS represents a novel and exciting tool to modulate cortical excitability, in specific local and distant brain regions and has been shown to alter connectivity with areas interconnected with the stimulated site. One exciting new application of NIBS is this ability to modulate functional connectivity between different interconnected regions and its proposed impact on behavior. For instance, dual-site stimulation paradigms, such as paired pulse stimulation applied repetitively could potentially modulate connectivity between two specific regions (Buch et al., Another line of research is based on the ability of NIBS to modulate brain intrinsic oscillatory activity as in the framework of brain-computer interface applications (Soekadar et al., A recent feasibility study demonstrated that it was possible to combine tDCS with MEG recording, and in addition, provide a chronic stroke patient with neurofeedback about her brain activity in motor regions in the form of a visual stimulus and a robotic orthosis that opened and closed as her hand moved Figure ,b. This The use of NIBS in conjunction with other methods like neuroimaging or genetic analyses may prove particularly useful, not only to study what NIBS does to distributed brain activity, but also to identify predictors of response to NIBS interventions. For instance, O'Shea et al.  used MR Finally, emerging combinations of new methods are afforded by improvements in technology, computing, and mathematical modeling, such as simultaneous tDCS stimulation with MEG recordings (Soekadar et al., 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.


It remains unclear whether cell death related to dysfunctional macropinocytosis occurs in normal physiological contexts. However, the finding that some types of cancer cells are particularly vulnerable to this unusual form of cell death has raised the possibility that small molecules capable of altering macropinosome trafficking or function might be useful as therapeutic agents against cancers that are resistant to drugs that work by inducing apoptosis. Herein we review examples of cell death associated with dysfunctional macropinocytosis and summarize what is known about the underlying mechanisms.Although macropinocytosis is widely recognized as a distinct form of fluid-phase endocytosis in antigen-presenting dendritic cells, it also occurs constitutively in many other normal and transformed cell types. Recent studies have established that various genetic or pharmacological manipulations can hyperstimulate macropinocytosis or disrupt normal macropinosome trafficking pathways, leading to accumulation of greatly enlarged cytoplasmic vacuoles. In some cases, this extreme vacuolization is associated with a unique form of non-apoptotic cell death termed “methuosis,” from the Greek  Macropinocytosis is a clathrin-independent endocytic process whereby mammalian cells internalize extracellular fluid inside vesicles formed by closure of actin-rich plasma membrane protrusions termed ruffles . Instead of a growth stimulatory effect, Chi et al.  found thmethuo, which means to drink to intoxication) to describe this form of cell death.Glioblastoma cells expressing RasG12V) lost viability over a period of 4–6 days  can cause death of neurons in the central nervous system, Nara et al.  observedIn a follow-up study, the same investigators provided evidence that hyperstimulation of macropinocytosis in neuroblastoma cells exposed to METH involves activation of Ras and Rac1, based on immunofluorescence localization of activated forms of these GTPases on the METH-induced vacuoles  did not prevent the accumulation of vacuoles or cell death in NGF-stimulated medulloblastoma cells , we identified a series of small molecules that induced a very similar form of cell death in a Ras-independent manner  suggests that the effects of these compounds are due to interactions with specific intracellular protein targets, rather than general covalent protein modification by Michael addition. However, the identities of the targets have not yet been established.Our continuing studies with synthetic libraries of MIPP-related compounds have identified more potent derivatives   can induce the methuosis phenotype directly, independent of Ras. This requires interaction of Rac1 with specific effectors, since neither Cdc42(G12V) nor RhoA(G14V) produced the same phenotype (Kaul et al., With the identification of small molecules, exemplified by MIPP, MOMIPP, and Vacqinol-1, which may have therapeutic potential to induce methuosis-like cell death in cancer, future efforts undoubtedly will focus on identifying the targets of these compounds. Although such studies are in their early stages, we have noted that induction of methuosis by MIPP is distinct from Ras-induced methuosis insofar as it does not entail alterations in the activation states of Rac1 or Arf6. On the other hand, MIPP causes a marked decline in active Rab5 (Overmeyer et al., What is the relationship between vacuolization of macropinosome-derived compartments and cell death? All of the examples of cell death associated with perturbations of macropinocytosis share some common features, which are summarized in the model depicted in Figure Although it is well established that macropinocytosis plays a vital role in many different types of cells under normal physiological circumstances, the recognition that artificial perturbation of macropinocytosis can lead to a novel form of non-apoptotic death in cancer cells is a relatively recent development. Figure Even if agents that hyperstimulate macropinocytosis or interfere with macropinosome recycling pathways do not always lead directly to cell death, one might speculate that such agents could have benefits in other contexts. One possibility is that stimulation of macropinocytosis might be utilized to increase fluid-phase drug uptake in resistant cancer cells where induction of ABC transporters promotes rapid efflux of drugs entering via conventional transmembrane routes. Alternatively, one might envision that stimulation of macropinocytosis could be harnessed to facilitate uptake of drugs packaged in nanoparticle delivery vehicles. Finally, recent studies have established that cancer cells utilize Arf6-dependent mechanisms to generate and release plasma-membrane derived microvesicles containing proteases and other factors that can promote invasion and tumor progression (Muralidharan-Chari et al., 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.


Cancer is now increasingly studied from the perspective of dysregulated pathways, rather than as a disease resulting from mutations of individual genes. A pathway-centric view acknowledges the heterogeneity between genomic profiles from different cancer patients while assuming that the mutated genes are likely to belong to the same pathway and cause similar disease phenotypes. Indeed, network-centric approaches have proven to be helpful for finding genotypic causes of diseases, classifying disease subtypes, and identifying drug targets. In this review, we discuss how networks can be used to help understand patient-to-patient variations and how one can leverage this variability to elucidate interactions between cancer drivers. PLOS Computational Biology.Teresa M. Przytycka is an Associate Editor of Biological networks provide a natural representation of complex biological systems and thus have been used in a variety of applications, from gene function prediction to identifying disease genes. In particular, complex diseases such as cancer can be better understood from the perspective of dysregulated pathways, rather than as a disease resulting from alterations of individual genes. One of the most popular types of biological networks used in disease studies is a gene interaction network. In a gene interaction network, genes are represented as nodes, and edges connect pairs of genes that are physically interacting or functionally related. Physical interaction networks can be constructed based on physical interactions, such as protein-protein interactions, protein-DNA interactions, and phosphorylation –3. FunctInteraction networks can be generic or condition-dependent. Generic networks, such as protein-protein interaction networks, summarize existing knowledge of the system that is typically not state or tissue-specific. Such static interaction maps between genes provide a scaffold for disease studies. Combined with additional disease related features, they can guide the identification of genes and pathways affected by a disease. For example, gene expression data have been shown to be useful for identifying network markers of a disease in the form of connected subnetworks that have significantly differential gene expression in two disease phenotypes –20. ImpoOne of the critical and challenging problems in disease studies is the identification and explanation of genotype-phenotype relationships. In cancer datasets, the relationships between genetic alterations and phenotypes are typically not one-to-one. Different genetic aberrations in different cancer patients can lead to the same disease phenotype, which makes it difficult to uncover genotype-phenotype relationships. One explanation of the heterogeneity between cancer cases is that different genetic alterations can dysregulate the same pathways, resulting in similar disease phenotypes. A network-centric view of diseases helps overcome the challenges posed by the complex genotype-phenotype relationships and facilitates finding genotypic causes of diseases ,20,21. IAnother challenge in cancer studies relates to differentiating cancer-driving mutations from passenger mutations. It is generally assumed that while somatic cancer cells typically contain many genomic aberrations, only a few of them are driver mutations, i.e., mutations that provide a growth advantage for tumor cells and thus are causal with respect to cancer progression. In contrast, the mutations that do not confer growth advantages are referred to as passenger mutations. For example, linkage disequilibrium accompanying some types of genomic aberrations, such as copy number variations, results in many passenger mutations. In addition, cancer cell divisions accumulate random mutations—most of them passengers. A faulty gene in the DNA repair mechanism or environmental factors such as UVC exposure can result in both passenger and driver mutations. Identification of drivers among such mutations is fundamental to cancer studies. While a high mutation rate in cancer samples is an indicator of possible driver activity, information on mutation rates alone does not suffice to correctly identify all cancer drivers. It is believed that there are many cancer driving mutations that occur at relatively low frequency, making it difficult to distinguish them from background noise. By placing the mutated genes in the context of other genes and identifying closely connected clusters of mutated genes in interaction networks, network approaches have been used to find defective gene modules in complex diseases such as cancer, autism, and autoimmune diseases –27.http://cancergenome.nih.gov) and ICGC , are currently available. These publicly available datasets offer comprehensive genomic profiles, including gene expression, somatic mutations, copy number variations, and DNA methylation, for an unprecedented number of patients. Integration of such datasets together with interaction networks can offer great opportunities to advance our understanding of the cause of diseases, classification of disease subtypes, and identifying drug targets [Several large-scale, cancer-related datasets, such as the data generated by TCGA  mutated subnetworks that are likely to be driver pathways. One approach to solve this problem is the propagation technique, in which the “influence” of each mutation disseminates through an interaction network, leading to the identification of a consistently perturbed group of genes . HotNet,One of the challenges in designing and interpreting information propagation algorithms is related to the nonuniform distribution of node degrees in interaction networks. The existence of hubs in the network reduces distances between genes, implying that simple distance-based algorithms may not be sufficient to identify driver gene modules. Additional information, such as gene expression or genetic alterations , can be One of the key insights contributed by network-centric approaches has been the extension of the concept of cancer drivers from individual genes to mutated pathways. Indeed, gene and gene products do not act in isolation, and the effect of a perturbation in a gene propagates through the interaction network, affecting the functions of other genes in its vicinity. By simulating the perturbation process in an interaction network, information propagation techniques are powerful tools that can recover true signals coming from different sources and even correct missing and uncertain information in incomplete interaction networks.In complex diseases such as cancer, different cancer types can have different genetic causes, despite their phenotypic similarity in disease manifestation. This makes the development of methods that move towards finding personalized disease subnetworks a necessity. Such methods can lead to novel drug targets by capturing similarities and differences between patient subgroups.Several approaches to capture the trade-off between individual differences and common principles build on the “set cover” problem, an optimization approach also known as the “hitting set” problem –50. The The original set cover definition does not account for relationships between covering elements . Genes are connected via an interaction network, with interactions possibly weighted by their confidence or strength. Additional relationships between genes can also be implied by mutual exclusivity of mutations . The prize-collecting Steiner tree (PCST) algorithm has been previously applied to find response networks –55, in wBoth the Module Cover and personalized PCST algorithms find dysregulated subnetworks while considering cancer heterogeneity by approaching the problem from different angles. The former collects information from different patients simultaneously, aiming to discover gene modules while allowing individual patients to be covered by different gene modules. The personalized PCST algorithm, on the other hand, looks for a personalized network for each patient individually and uses information from other patients to bias the cost function and capture similarity between patients.While cancer heterogeneity among patients makes uncovering genetic causes challenging, the principle that different genetic alterations lead to similar disease phenotypes might also be utilized to find previously unknown interactions between genes. It was often observed that mutations in cancer driver genes appear in mutually exclusive sets of cancer patients. One explanation for mutual exclusivity is that only one such mutation in a pathway is sufficient for cancer progression. A proposed alternative explanation is that mutually exclusive pairs may have a relationship of synthetic lethality or sickness, in which mutations in each gene separately promote cell growth but simultaneous mutation in both genes is lethal or detrimental. Note, however, that a synthetic lethal partner of a cancer driver does not necessarily have to be a cancer driver itself. Algorithms that predict synthetic lethality or sickness from mutational data typically infer mutual exclusivity patterns using additional information about gene expression patterns, effects on disease manifestation, and/or information from shRNA experiments in cancer cell lines ,58.Genes with mutually exclusive mutation patterns are often functionally related. This observation led the mutual exclusivity principle to be used as a tool to find cancer driver modules. Several computational methods have been developed to detect mutually exclusive gene sets ,50,59–66Based on the assumption that mutual exclusivity can predict novel functional relationships, several approaches do not restrict the search space to gene pairs with known interactions but instead look for gene modules using only mutual exclusivity information of genomic aberrations ,62–66. SGiven the utility of mutual exclusivity principle for uncovering important relationships between cancer drivers, one can also leverage datasets from multiple cancer types for integrated analysis. The TCGA Pan-Cancer initiative compiled datasets from multiple tumor types, aiming to identify the similarities and differences among them and to uncover cancer driving genes that are rarely mutated and may not be recognized in the small number of samples of individual cancer types . For mutIn another approach to analyze mutual exclusivity in the context of Pan-cancer data, Park et al. asked if some gene pairs are mutually exclusive in a specific cancer type more often. They found that some highly mutated gene pairs may have tissue type bias in mutual exclusivity patterns, which can be attributed to type specific interactions for the tissue type .Modeling disease heterogeneity can also naturally start from the perspective of phenotypic similarity of individuals. Organisms or individuals whose phenotypes are determined by genomic elements can be represented as nodes and connected by edges if they have similar phenotypes. For example, Roque et al.  construcSuch a simple phenotype-based clustering approach provides valuable information but still has some shortcomings. For example, while the above-mentioned study found that several subnetworks have schizophrenia as one of their underlying features, it is not clear if the different subnetworks correspond to subtypes of schizophrenia or if phenotypic features unrelated to the disease define the subnetworks. In modeling heterogeneity of complex diseases, it is critical to find the causal relationships of disease phenotypes rather than simply clustering the phenotypes of patients. In the context of cancer, the cause is typically a tumor genotype, but other factors such as epigenetics, age, environment, etc., should also be considered when data permits.The first approach to use a patient network to infer genotype–phenotype relationships was proposed by Cho and Przytycka . By combSo far we have discussed using patient networks in which patient similarity scores are computed based on the combination of their phenotypic similarity features. An alternative approach was recently proposed by Wang et al., in which they constructed patient similarity networks independently for three different data types , then fused them into one similarity network . More spThe two methods of utilizing patient similarity described above have their unique advantages. The topic model-based method can be thought of as a subtype-centric approach, as it allows probabilistic disease subtypes to be defined based on the frequencies of putative causal features while representing each patient as a mixture of these subtypes. On the other hand, the network fusion algorithm is a more patient-centric approach, which allows, for each patient, other individuals that are most similar to the patient in question to be identified and therefore enabling the information from neighboring patients to be transferred.Disease similarity networks are a natural extension of patient similarity networks. Rather than considering individual patients, diseases are considered as nodes and edges are created based on similarities between the diseases. Considering diseases in the context of other related diseases can offer insights for better understanding their genotypic causes and further provide a way for repurposing existing drugs in similar diseases.Similarity in disease networks may be measured based on various factors, such as shared disease genes ,36,81, dDisease networks are often used in conjunction with a gene interaction network to improve the quality of disease-gene associations or to better predict disease similarities ,13. MencOverall, disease similarity networks are helpful for uncovering relationships between diseases, which in turn can shed light on finding common genetic causes among similar diseases. Another benefit of considering similarities and differences of diseases is that a large-scale disease interaction map can provide valuable guide for drug repositioning and help predict their side effects.Cancer heterogeneity poses a significant challenge for analyzing and interpreting cancer patient data. Cancer is now commonly understood as a disease of pathways rather than a result of defects in individual genes. Therefore, network-based approaches can be employed to find explanations for how different mutations result in similar disease phenotypes. Gene interaction networks have been used to identify defective pathways, classify subtypes based on subnetworks, and predict treatment and survival outcomes. In addition to gene networks, patient similarity networks are gaining importance and can offer different perspectives for understanding cancer.Currently, networks used in cancer studies are typically static, and network topology remains fixed during the analysis while changes associated with diseases may be mapped as changes in properties of the nodes or edges of such network. However, interactions between biological entities may differ at multiple levels, depending on spatial and/or temporal conditions . RecentlDynamic network analysis can help in deciphering fundamental mechanisms of diseases, such as increasing disease susceptibility with age. As a step in this direction, Faisal and Milenkovic exploited network dynamics to study age progression . By combIn cancer data analysis, utilization of network dynamics is still limited. Obtaining interactions in different tissue types and putting them together can advance therapeutics by predicting the effects of chemotherapy in specific tissues. For example, Greene et al.  used a sOne of the most widely acknowledged problems with currently available gene networks is their noisiness. Physical interaction networks obtained from large-scale experiments are not only noisy but also incomplete. Relative to physical interaction networks, functional interaction networks are more complete but may lose specific information about directly interacting pairs because these networks integrate many different functional relationships together. Studies that focus more on mechanistic aspects of signal propagation may benefit from leveraging physical interaction networks, but they need to be aware of the limitations that these networks currently have. In contrast, analyses that focus on identification of broadly related groups of genes typically utilize functional networks, which cover a wide spectrum of interactions between molecules.One of the main advantages of network-based approaches is their capability to uncover cancer-related associations, including genotype-phenotype relationships, despite the heterogeneity of the disease. Such large-scale associations can suggest potential treatment options and can generate testable hypothesizes, but at present, they can rarely provide full explanations of observed relationships. Indeed, current interaction networks not only lack context dependency but also cannot usually provide accurate mechanistic interpretations. It is anticipated, however, that as the coverage and information encoded in these networks improves, the predictive and explanatory power of network-based cancer analysis will increase accordingly.


As predicted by the temporal difference learning models, dopamine neurons respond during the early stages of classical and operant conditioning with a burst of action potentials (a phasic-like response) after reward presentation   , phasic DA stimulation enhanced the effects of food-reward seeking . Interestingly, they also found that after a series of extinction sessions during which no food reward or phasic DA stimulation occurred, preferential lever pressing  could be reestablished by DA stimulation in the absence of both external cues and, critically, food reward. Finally, the authors used a reversal learning session where the relationship between the active  and inactive  levers were switched, and demonstrated that ChR2 mice switched their lever pressing to the previously inactive lever compared to control mice. This finding is particularly important because it suggests that not only is the phasic DA signal driving and enhancing simple stimulus-reward associations but it is also causally involved in flexible behavioral adaptations that occur as a result of changes in stimulus-reward contingencies.With regards to the causal role of DA in behavioral flexibility, in a recent study  dopamine D1 and D2 function in the striatum is another important component to take into account when trying to establish a causal link between neural activity and behavior. Dopamine depletion, for example, in the dorsomedial striatum results in reversal learning impairments (O'Neill and Brown, Studies that have looked at increasing dopamine concentration have demonstrated that DA stimulation by injection of amphetamine in the NAc core or shell increased instrumental responding to a conditioned stimulus predictive of reward (Pecina and Berridge, In conclusion, increasing evidence from optogenetic, voltammetry, and pharmacological studies over the recent years have added a new dimension to the established but mostly correlation role between the midbrain DA neurons and reward learning. This evidence suggests that this phasic response may have a causal role not only in reward prediction error signaling, but also in driving flexible behavioral adaptations to changes in stimulus-reward contingencies.The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Considerable overlap in diagnostic criteria and shared psychopathologic symptoms in attention deficit hyperactivity disorder (ADHD) and borderline personality disorder (BPD) have stimulated research activities in this field. Longitudinal studies have shown that BPD is frequently diagnosed in adult patients who had been diagnosed with ADHD in childhood. The question of whether ADHD and BPD randomly co-occur as comorbidities, have similar origins or share common pathological mechanisms remains unresolved. Some authors suggest that ADHD contributes to the development of BPD via various mechanisms, and therefore consider it a risk factor for later BPD development.In this article the evidence for the co-occurrence of these disorders will be reviewed as well as studies on their common genetic and environmental influences. Temperamental and developmental issues will be reviewed, and shared features such as impulsivity and emotion dysregulation discussed. From a therapeutic perspective, few studies have investigated psychotherapeutic treatment of the comorbid condition, though the issue is highly important to the management of patients suffering from both disorders. Some thought is given to how therapeutic methods and approaches can be modified to benefit patients, and to their possible succession. In recent years, shared symptoms and considerable overlap in clinical presentation between attention deficit hyperactivity disorder (ADHD) and borderline personality disorder (BPD) have stimulated research activities in this field. Since the 1980s numerous studies have furnished evidence on the persistence of ADHD symptoms in adulthood . ADHD syOn the one hand, since the publication of the Wender Utah Criteria  emotion Discussion is continuing on whether ADHD and BPD occasionally co-occur as comorbidities and have common origins, possibly with ADHD traits being the precursor of later BPD, or share common pathological mechanisms. Against this background there has been discussion about which therapeutic approach would be the most beneficial, even if research activities in this field are still scarce.This article gives an overview of current knowledge about the close links, subtle distinctions and significant differences between the two disorders. It deals with different aspects of the association between ADHD and BPD, taking into account possible common origins in neurobiology and inborn temperament as well as common mechanisms concerning neuropsychology and emotion regulation. As we consider this a very important issue to improve and broaden knowledge of therapeutic options for patients with both ADHD and BPD, this basic information is provided as a starting point for clinicians dealing with patients suffering from both conditions. The article will also give some thought to therapeutic aspects and formulate some tentative recommendations.Marked tendency to act unexpectedly and without consideration of the consequences,To engage in quarrelsome behavior and to have conflicts with others, especially when impulsive acts are thwarted or criticized,Liability to outbursts of anger or violence, with inability to control the resulting behavioral explosions,Difficulty in maintaining any course of action that offers no immediate reward andUnstable and capricious  moodBPD is classified as a personality disorder (PD). The DSM-V defines the main features of BPD as a “pattern of instability in interpersonal relationships, self-image, and affects, and marked impulsivity” . ADHD acDifficulty waiting his or her term (e. g. while waiting in a line)Blurting out answers before a question has been completed or blurting out inappropriate comments without regard to consequences andInterrupting or intruding on othersThe criteria of the impulsivity domain in ADHD according to the DSM-V are quite similar (see the criteria of the impulsivity domain of ADHD according to DSM-V):Affective lability or mood shiftsHot temper outbursts or short-lived explosive outbursts or constant irritability andEmotional over reactivity in the sense of over reactivity to routine life stressBecause of this apparent overlap the phenomenological differentiation between “borderline-impulsivity” and “ADHD-impulsivity” is merely possible from a clinical viewpoint. Both patient groups often seem to act without taking into consideration the consequences of their behavior. According to the ICD definition of the impulsive subtype of emotionally instable PD, the cited impulsivity criteria also comprise emotion control/regulation difficulties (outbursts of anger). The aspect of emotion dysregulation was added to the definition of adult ADHD when the Wender-Utah criteria were published. Wender et al. proposed a set of characteristics :to specify current ADHD symptoms in adults which are not only based on the behavioral criteria outlined in DSM-V, but also comprise associated features and subjective symptoms .Thus, it is evident that there is a descriptive overlap with the affective instability domain in BPD. Wender’s proposal has been tested, and evidence has emerged to affirm that in adult ADHD there is an elevated risk for deficient emotional self-regulation (DESR) , 17–19. The considerable overlap between symptoms of ADHD and BPD in the core domains of impulsivity and emotional dysregulation led to the idea that both disorders might be the result of different developmental pathways based on common underlying pathologic mechanisms and differing in symptom severity .Psychopathological presentation was therefore investigated in adult patients with ADHD compared to BPD patients and control subjects with a focus on Borderline symptomatology . SeveritGiven the similarities in symptom presentation, one might think that ADHD and BPD are different modes of the same disorder. However, states of inner tension  which arWe searched relevant registers for studies on ADHD. Furthermore, we screened the reference lists of relevant articles manually. Included were papers in English, German and French. Studies of any design focusing on ADHD and BPD were screened and categorized. We used the categories research on comorbidity, etiopathology, temperament and development, neuropsychology and treatment to summarize the findings.A search for studies dealing with ADHD and BPD was conducted for the following bibliographic databases: Pubmed, Embase, Medline, PsychInfo, Central . The following terms were used: (ADHD OR (attention deficit) OR (attention-deficit) OR hyperactivity*) AND  OR borderline*). The search included all fields in Pubmed, Embase, Medline and PsychInfo databases and abstract, title and keywords in the Central bibliography : 11660, Medline (ME95) see Pubmed, Psychinfo 418, Central  19, NCBI webside 420).By 1979, a connection between minimal brain dysfunction and BPD was assumed to exist . InvestiIn adult ADHD, PDs are frequent comorbidities , 29. JacThe association between ADHD and BPD has been primarily studied on a phenotypic level. Recently a study investigated the genetic and environmental contributions to this association using a dimensional approach. Borderline personality traits and ADHD symptoms were assessed in a sample of 7233 twins and siblings from the Netherlands. The phenotypic correlation between ADHD and BPD symptoms was high (r = 0.59) and was the same for both genders. According to the authors, 49% of the high phenotypic correlation can be explained by genetic influences and 51% by environmental factors . It seemTo study environmental influences on ADHD symptoms, Lehn and colleagues conducted a longitudinal study in monozygotic twins . Twins wOther environmental risk factors that contribute to or influence the development of BPD include traumatic experiences. It has been found that the lifetime prevalence of Posttraumatic Stress Disorder (PTSD) and BPD in a nationally representative sample of the U. S. population is 6.6% and 5.9% respectively  Wave II, N = 34.653, ). PTSD aA recently published large longitudinal study followed children with and without ADHD and their siblings for 10 years (mean age at follow-up: 22 years). This study revealed that ADHD was an independent risk factor for later PTSD with an OR of 2.23 . RucklidPredictive data concerning the development of BPD comes from prospective studies. Burke and Stepp, for example, report on longitudinal data from a clinical sample of 177 boys, first diagnosed at ages 7 to 12 and followed up annually to age 18 and reassessed at age 24 . DiagnosA study of 103 female adult patients meeting DSM-IV criteria for ADHD or BPD used a latent class analysis (LCA) and identified four subgroups. Hyperactivity was present in all four subgroups and thus does not discriminate between ADHD and BPD. Developmental pathways were also investigated. One possible pathway leads from combined ADHD symptoms or mainly inattention symptoms in childhood to an adult profile containing only symptoms of ADHD and not BPD. Another possible pathway leads from a childhood profile with low levels of hyperactive/impulsive symptoms but no inattention problems to an adult profile with symptoms of BPD . TemperaOf the official diagnostic criteria defining ADHD and BPD, the highest overlap between the two disorders seems to be in the domain of impulsivity. But what is meant by impulsivity? A comprehensive definition of impulsivity does not exist. The presentation of impulsive behaviour is manifold, and comprises behaviours that often result in undesirable outcomes because they are not sufficiently thought-out or inappropriate or occur in an untimely fashion –53. ImpuMoreover, Krause-Utz and colleagues reported stress-dependent increase in state impulsivity in patients with BPD  in comparison to an ADHD only group and healthy controls . BPD seeAs emotion dysregulation is often considered the core feature of borderline psychopathology, components of emotion dysregulation have been intensively studied in BPD (for Review see ). EvidenIn ADHD research evidence in the field of emotional dysregulation is relatively sparse. Negative emotions seem to contribute to or aggravate ADHD symptoms , 81 via It can be assumed that individuals suffering from ADHD, easily overwhelmed by emotions, might struggle with emotional regulation strategies designed to suppress the expression of emotion. Evidence comes from a study of boys suffering from ADHD compared to a control group. Both groups were observed during a frustrating competitive Puzzle Task and randomised to direct instruction to either control their emotional expressions or let them run their natural course. The ADHD group was not as successful in doing so as the control sample. In the ADHD group the difference in emotional dysregulation between the condition instructed to control their emotions and the natural course condition was not as pronounced as in the control group. The effect of suppression on the level of emotional dysregulation in ADHD children was rather small, which points to the conclusion that ADHD children are less effective in suppressing their emotional expressions .It is currently not possible to compare emotion regulation in BPD and adult ADHD because more evidence for its role in ADHD is required, and no direct comparison studies have been carried out Table In clinical practice, ADHD may frequently be missed in patients with a diagnosis of BPD. As ADHD is a frequent comorbidity in BPD and entails additional problems and impairing consequences in daily life, in therapeutic contexts careful diagnostic assessment of symptoms and problems is necessary. In each individual patient a decision about the necessity of treating the ADHD symptoms needs to be made based on a balanced evaluation of the severity of impairments due to ADHD, the patient’s resources, compensatory strategies and the patient’s demands . FrequenADHD in adults can be treated effectively with stimulant medication and atomoxetine. International guidelines propose methylphenidate (MPH) as the first line treatment in adult ADHD –91. MPH Case-reports of successful methylphenidate treatment in patients with co-morbid BPD and ADHD have been published , 94. GolIt can be assumed that BPD patients suffering from ADHD are hindered in the accomplishment of psychotherapeutic steps because ADHD implicates difficulties in planning, structuring, concentrating, arranging timetables and pursuing schemes. Motivation is often fragile, initial enthusiasm is followed by frustration and boredom, and focusing on central themes often remains a challenge. To avoid early discontinuation of treatment and disappointment, ADHD should be kept in mind and included in the planning of treatment steps.BPD traits  and BPD For adults with ADHD a number of different psychotherapeutic programs are available, mostly group therapies (for Review see –108). AnPsychoeducation on both disorders and treatment options;Pharmacological treatment of ADHD symptoms if their severity indicates a treatment and if psychotherapeutic approaches might be facilitated by treating ADHD conditioned impairments. Stimulants are the treatment of choice for adults with ADHD, with long-lasting, extended release formulations preferred to avoid rebound with the risk of enhancement of mood swings and dysfunctional behavior, and for protection against abuse ;Coaching on ADHD related therapy-interfering behaviors ;Individual psychotherapy and/or group therapy with the aim to improve behavioral, social and functional impairments; andLong-term follow-up to avoid early discontinuation and repeated disappointing experiences.A systematic approach to treatment can be proposed, including:There has been little scientific research on systematic treatment approaches for comorbid patients suffering from BPD and ADHD, and more research in this area is needed.ADHD and BPD share some clinical features, particularly impulsivity and emotional instability. These disorders often co-occur. Patients with both diagnoses have more pronounced difficulties which are intertwined and often difficult to treat. In particular, impulsivity seems to be a severely impairing characteristic of patients suffering from both disorders. In BPD, impulsivity is primarily driven by affective and interpersonally sensitive aspects. In ADHD, deficits in attentional and cognitive processing account for behavior inhibition problems, referred to as impulsivity. Systematic treatment programs for patients with both ADHD and BPD are lacking, and there is a need for more research in this area. To stimulate research in the field of co-morbid ADHD and BPD we consider it important to further address the questions of gene-environment interactions, vulnerability to emotional neglect and abuse, and to broaden knowledge about temperament and the risk for traumatic experiences. Future research on impulsivity should include direct comparisons between ADHD, BPD and comorbid ADHD + BPD groups. The field of emotion regulation research in ADHD needs to be expanded to better understand interrelations between executive function deficits as well as (under-)stimulation and emotion regulation. The family interactions between parents and children with ADHD need to be considered from an emotion regulation perspective. Treatment options for comorbid patients suffering from ADHD and BPD should be developed and evaluated. Current knowledge emphasizes that therapeutic approaches need to take both disorders into consideration. Moreover, therapeutic planning needs to carefully consider symptom domains and selection of therapeutic steps and their succession.