Microalgae have been widely recognized as a valuable source of natural, bioactive molecules that can benefit human health. Some molecules of commercial value synthesized by the microalgal metabolism have been proven to display anti-inflammatory activity, including the carotenoids lutein and astaxanthin, the fatty acids EPA (eicosapentaenoic acid) and DHA (docosahexaenoic acid), and sulphated polysaccharides. These molecules can accumulate to a certain extent in a diversity of microalgae species. A production process could become commercially feasible if the productivity is high and the overall production process costs are minimized. The productivity of anti-inflammatory molecules depends on each algal species and the cultivation conditions, the latter being mostly related to nutrient starvation and/or extremes of temperature and/or light intensity. Furthermore, novel bioprocess tools have been reported which might improve the biosynthesis yields and productivity of those target molecules and reduce production costs simultaneously. Such novel tools include the use of chemical triggers or enhancers to improve algal growth and/or accumulation of bioactive molecules, the algal growth in foam and the surfactant-mediated extraction of valuable compounds. Taken together, the recent findings suggest that the combined use of novel bioprocess strategies could improve the technical efficiency and commercial feasibility of valuable microalgal bioproducts production, particularly anti-inflammatory compounds, in large scale processes. In recent years, the pharmacy of the sea has become a new paradigm for the discovery and development of novel drugs and bioactive compounds. The increasing need for getting drugs with no or minimal toxic side effects is one of the main reasons that motivates the search for bioactive compounds from natural sources, including anti-inflammatory active molecules from microalgae.Much has been written about the outstanding metabolic properties of microalgae that make them particularly attractive as a natural source for bioactive molecules production ,2,3. RegIt is apparent that the proven anti-inflammatory activity of the biomolecules listed in One of the main advantages of microalgae when used for the production of valuable compounds in large scale production systems is the high areal biomass productivities. The systematic production of microalgae biomass at large scale in addition to the high productivity of microalgal cultures under well established and controlled cultivation conditions  make theChlorella, Spirulina (Arthrospira), Dunaliella, Haematococcus, Nannochloropsis, Scenedesmus, Isochrysis, Porphyridium and Phaeodactylum [Phaeodactylum tricornutum reached the market based on its anti-inflammatory properties only [Only a few microalgae species are currently being produced with a commercial purpose in spite of the huge diversity existing in nature which according to literature accounts for about 300,000 species, out of which only 10%  have been documented . Thus, mdactylum . Until 2ies only . Thus, tWith no doubt genetic engineering techniques currently offer a large number of procedures to obtain modified strains which are designed to display specific functionalities. However, several factors still make the use of genetically modified microalgae difficult at commercial production scale; for instance, a still little positive consumer perception towards genetically modified organisms and the restrictive regulations on genetically modified organisms in many countries slow down development of industrial production of microalgae enriched in high-value compounds. However, the huge diversity of wild microalgae species that remain unexplored and unexploited should still for a long time allow addressing research on their natural potential for the production of target molecules by means of triggering key biosynthetic pathways through the use of specific chemicals and cultivation conditions ,23. ThisDunaliella salina is an outstanding example of extremophilic microalga commercially used for the production of a high value compound which displays anti-inflammatory activity, β-carotene [The biotechnological potential of most marketed microalgae species is actually very well known, and the expectations to unveil novel, abundant bioactive compounds from non-extremophilic microalgae are decreasing. In coming years, the production of novel microalgal compounds should expectedly be carried out from novel microalgal species isolated from locations where they could eventually be further produced at large scale. In this respect, extremophilic microalgae are microorganisms with unique metabolic capabilities yet unexploited, with a competitive advantage (as compared to non-extremophiles) to grow in open systems under restrictive cultivation conditions  which limit microbial contamination. For instance, carotene .Marketing of anti-inflammatory compounds obtained from microalgae is possible only if commercial feasibility of the product production process is achieved. A production process could become commercially feasible if the biosynthesis yields and productivity of target molecules are high and the overall production process costs are minimized. The productivity of anti-inflammatory molecules depends on each microalgal species and the specific cultivation conditions that boost the biosynthesis pathways involved. These conditions must be optimized for each microalgal species.A number of anti-inflammatory molecules obtained from microalgae have also been shown to display high antioxidant capacity, thus they could in theory be produced under oxidative stress conditions. A list of the most abundant microalgal molecules with both anti-inflammatory and antioxidant activities should include the pigments β-carotene , astaxanPorphyridium [Rhodella [In addition to the aforementioned antioxidant pigments, LC-PUFAs  have also been proven to exert antioxidant activity, which for instance was exemplified by studies in human vascular endothelial cells demonstrating reduced excretion of lipid peroxidation products after omega 3-intake and superoxide scavenging by LC-PUFAs . The thihyridium  and RhodRhodella  are notiIn addition to the above mentioned compounds, a number of other microalgal molecules have recently been reported which also have high antioxidant capacity besides anti-inflammatory activity: Phenolic compounds (flavonoids) , peptideAccording to the aforementioned antioxidant capacity of a large number of microalgal molecules which also display anti-inflammatory activity, some of the main chemical strategies to enhance their biosynthesis and intracellular accumulation could be based on inducing oxidative stress in the cells which might result in increased production rates of antioxidant molecules. In this sense, ROS can act as chemical signals to specifically induce the biochemical production of antioxidant molecules, including the enzymes of the antioxidant cellular response to stress . TherefoIn microalgal cultures, oxidative stress can be induced by a range of strategies which involve the use of chemicals. The knowledge of the chemical properties and reactivity of the main added-value molecules obtained from microalgae, as well as the principal metabolic steps of their biosynthesis have allowed to carry out novel research aimed at searching for chemical triggers that enhance accumulation of those molecules. The chemical triggers are different in nature and action mechanisms. According to the latter, these chemicals can be classified into several groups : OxidatiIn a recent study, Franz et al.  describeAn increasing interest exists about how microalgae can cope with oxidative stress. Such interest is related to the microalgal potential for the large scale production of valuable molecules accumulated under oxidative stress, the so-called antioxidants. The primary microalgal antioxidant response to oxidative stress conditions imposed to their cultures consists of producing a range of enzymes, such as superoxide dismutase, ascorbate peroxidase, catalase, glutathione reductase and peroxidase, as well as other molecules, such as phytochelatins, pigments, polysaccharides, and polyphenols . In addiThe simple fact that life occurs in an oxygenated atmosphere results in the continuous presence of oxygen in living cells. As a reactive molecule, oxygen takes part in many chemical and biochemical reactions by means of which ROS permanently arise. ROS are chemically reactive species containing oxygen. ROS include species with unpaired electrons and non-radical species, e.g., hydrogen peroxide, and form during oxygen metabolism through several well identified enzymatic pathways. DNA, proteins and membrane lipids, among other biomolecules, are direct targets of ROS which can alter the normal biological functions of those principal biomolecules: This is the so-called oxidative stress. In photosynthetic cells like those of unicellular microalgae and cyanobacteria, ROS are produced in plastids, mitochondria and cytosol, among other organelles . It is aIn order to minimize the ROS damage to key cellular processes and functionalities, the cells express diverse antioxidant biochemical mechanisms to neutralize, or at least minimize, the harmful effects of ROS . The prThe AsA-dependent enzyme-catalyzed reduction of hydrogen peroxide to water is a crucial step to produce an efficient detoxification of ROS. As shown in 2O2, OH∙, O2) must interact with specific molecular targets. The mechanisms of such interactions and whether each ROS is specifically recognized by a given mechanism or receptors remain unknown [Some reports have been published which provide evidence of direct involvement of ROS in the enhanced biosynthesis of microalgal molecules with both antioxidant and anti-inflammatory properties, namely carotenoids and PUFAs. In 1994, Asada  describe unknown .The role of antioxidants in inflammation has been recently reviewed by Arulselvan et al. . In thisThe nature of chemicals that can induce oxidative stress in photosynthetic cells is diverse and the number of those can be enormous. Those being most commonly used in laboratory experiments currently are listed in In addition to the latter, other chemical strategies producing oxidative stress and addressing the accumulation of microalgal molecules with anti-inflammatory activity are commonly based on nutrient limitation or starvation. It should be noticed that nutrient starvation, particularly inorganic nitrogen, is an effective chemical tool to induce accumulation of lipids—including carotenes and xantophylls—and polysaccharides in microalgae. This subject has been widely reviewed ,67. In tHaematococcus pluvialis, has been proven effective as an anti-inflammatory [Carotenoids have been found to positively impact the anti-inflammatory cellular response mechanisms and the immunoresponse modulation ,68,69. Iammatory ,75,76,77ammatory ,78. The ammatory .In photosynthetic organisms, carotenoids may act as accessory pigments in light harvesting functions during the light phase of photosynthesis and may also exert protection of the photosynthetic machinery from excess light and from other oxidative stress chemical factors , by scavenging reactive oxygen species (ROS) ,15,79. IHaematococcus for astaxanthin, Chlorella, Scenedesmus and Botryococcus for lutein, and Dunaliella for β-carotene [Haematococcus pluvialis [Chlorococcum [Chlorella zofingiensis [H. pluvialis as part of the cellular antioxidant response [Only a limited number of microalgae genera are commonly used in research to test pigment accumulation under oxidative stress, such as carotene . A few rluvialis , Chlorocrococcum  and Chlongiensis , showingresponse . Thus, tHaematococcus [Chlorococcum [2−), hydrogen peroxide and 2,2′-azo-bis(2-amidinopropane)-dihydrochloride for peroxy radical (AO2), and Fe (II), were capable of boosting astaxanthin accumulation in H. pluvialis. These chemical species might be playing a role as oxidizers in the oxidative enzyme reactions chain leading to astaxanthin biosynthesis [The increased intracellular content of ROS that is required to boost astaxanthin accumulation can also be achieved by the addition of herbicides to microalgal cultures. Herbicides, such as methyl viologen, are commonly used in laboratory research and have been reported to enhance accumulation of astaxanthin in tococcus  and Chlorococcum  though irococcum  demonstrrococcum  demonstrynthesis .H. pluvialis [Chromochloris zofingiensis [The use of ferrous iron-Fe (II) as astaxanthin biosynthesis inducer is of particular interest. Fe (II) is an essential metal ion required for microalgal growth, therefore included in the culture medium composition. As described by Kobayashi et al. , Fe (II)luvialis  and Chrongiensis . One of ngiensis .Nitrogen limitation or starvation and high salinity levels induce oxidative stress in microalgal cells and also the subsequent cellular antioxidant responses, including enhanced biosynthesis and accumulation of anti-inflammatory carotenes and xanthophylls . Indeed,Chlorella zoofingiensis was shown to increase in response to ROS generated by low concentrations of H2O2 or NaClO [C. onubensis. Interestingly, lutein accumulates at a high intracellular concentration in Fe (II) or Cu (II)-added cultures of C. onubensis, an extremophilic microalgal species isolated from the highly acidic environment of Río Tinto (Southwestern Spain) [In spite of lutein being one of the most valuable carotenoids, chemically-induced accumulation of lutein has not been extensively studied in microalgae. Considering the valuable applications of lutein and the increasing market demand of natural sources of this pigment , this isor NaClO . The culor NaClO , or incrn Spain) . The larn Spain) .Dunaliella salina which makes the search for novel chemical triggers unnecessary.Almost no studies have been published dealing with ROS-mediated induction of β-carotene biosynthesis, probably due to the efficient chemical strategies applied for β-carotene mass production at industrial scale and the high intracellular β-carotene content and productivities achieved by the only β-carotene producing microalga The anti-inflammatory properties of PUFA from microalgae have been widely described and recently reviewed by several authors ,32. A laIn photosynthetic cells, PUFA carry out a variety of cellular key functions. Besides the principal roles of PUFA as energy storage molecules, cell membrane components and in the physiology of photosynthetic cells, their antioxidant capacity is one of the cellular defense mechanisms against the harmful presence of ROS. In fact, PUFA show affinity towards ROS generated in algal cells subjected to oxidative stress conditions . Indeed,Thus, together with carotenoids and polysaccharides, PUFA are included among the wide range of antioxidant compounds that are produced by microalgal cells to diminish the harmful consequences derived from oxidative stress . HoweverSchizochytrium sp. Alternatively, simultaneous growth and PUFA production can be carried out at a constant, average oxygen concentration optimized in order to achieve maximal productivities, as described by Huang et al. [Besides the negative impact of ROS in the growth and high-value compounds accumulation of microalgae, ROS seem to play a relevant role in triggering lipid accumulation in microalgae ,94 thougg et al.  for growPhaeodactylum tricornutum cultures under nitrogen limitation [Pavlova lutheri [As previously described above, chemical factors other than oxygen and ROS also generate oxidative stress. For example, nutrient limitation or deprivation  and high salinity cause increased intracellular ROS level in microalgae ,97, thusmitation , and a t lutheri , both reIn spite of this negative correlation between accumulation of anti-inflammatory PUFA and nutrient limitation or salinity level, the accumulation of these compounds in microalgae can also be enhanced under nitrogen limitation or relatively high salinity but only if these conditions are optimized and applied to the right time of the stress phase, the accumulation being also species-dependent ,100. AltNannochloropsis oceanica  [Pavlova lutheri  [Tetraselmis marina [Conversely, the reduced oxidative damage of microalgal cells growing in a replete culture medium can explain the highest EPA content displayed under nitrogen repletion conditions by content) , the higcontent)  and the s marina . Both nis marina .Chlorella and Phaeodactylum [The anti-inflammatory properties of sPS from microalgae have been recently reviewed . The antdactylum ,104. Accdactylum  and thusdactylum .Rhodella reticulata [Porphyridium [In cyanobacteria, a large fraction of assimilated carbon can be diverted to the synthesis of polysaccharides . Polysacticulata  and Porphyridium .−1 [Cyanobacterial polysaccharides are also included among the antioxidant molecules produced by microalgae in response to oxidative stress. Cyanobacteria produce exopolysaccharides, which according to literature are sPS, up to more than 20 g·L−1 ,109 in r−1 , which m−1 , though −1 ,112. As −1 , almost Aphanocapsa, Anabaena or Synechocystis [As explained above, salinity induces oxidative stress in microalgae. Accordingly, and considering the antioxidant character of microalgal polysaccharides, salinity could act as polysaccharide accumulation inducer in microalgae which could use the produced polysaccharides for protective roles. Indeed, the polysaccharide layer around the cells can limit the diffusion of ions through the cell cover . Such thhocystis ,114,115,hocystis .Phenolic compounds are secondary metabolites produced by photosynthetic organisms and have awaked interest in recent years, particularly due to their antioxidant character. Based on such properties, the phenolic compounds are known for their benefits to human health. Specifically, the anti-inflammatory properties of microalgal phenolic compounds have been recently reported  and contThe action mechanism of anti-inflammatory compounds is performed by a variety of inhibitory activities of pro-inflammatory mediators and/or gene expression . In inflPhenolic compounds accumulation in microalgae has been directly related to the antioxidant response mechanisms of the cells to increased intracellular oxidative states. Indeed, the anti-inflammatory activity of phenolic compounds is directly related to their antioxidant activity against ROS. Phenolic compounds have been described as radical scavengers based on their role as donors of hydrogen atoms or electrons, producing stable radical intermediates. They can also inhibit iron-mediated ROS formation to prevent the subsequent oxidative stress .Spirulina was stimulated by nitrogen, both in inorganic (NaNO3) or organic  forms. Particularly, the authors reported the presence of phenolic acids and flavonoids predominantly with gallate, chlorogenate, cinnamate and p-OH-benzoates. Moreover, in relation to the microalgal antioxidant response, accumulation of phenolic compounds has been described in Dunaliella tertiolecta in response to stress produced by addition of Cu (II) or Fe (II). Cu-exposed (790 nmol·L−1) D. tertiolecta cultures contained 1.4-fold higher intracellular levels of phenolic compounds than standard cultures [However, only a few studies have been reported so far which deal with the accumulation of phenolic compounds in microalgae as a specific cellular response to ROS generated under oxidative stress conditions, for instance, exposure to metal stress . In thiscultures , thus suMicroalgae cultivation in foam is a novel concept that consists of growing microalgal cells in surfactant-based foam . A surfaThe foam-bed photobioreactor is a novel bioengineering concept originally emerged at Wageningen University . In a foIn the foam formed, the microalgal cells grow in the liquid layer that surrounds foam bubbles . The foaIn a foam-bed photobioreactor, once foam reaches the top part of the cultivation vessel it has to be continuously broken to release the gas contained in the foam bubbles which can produce growth inhibition by oxygen, or lowered growth by carbon limitation. Foam can be broken at the top of the reactor by means of different procedures . Thus, t2 levels in the gas supplied to the cultures, among other factors.The chemical interaction between the polar groups of surfactant molecules and the microalgal cell wall obviously results in a reduced charge density of the microalgal cell cover. In the case of positively charged groups in the surfactant structure, it has been speculated that their neutralization at the cell surface by negatively charged groups should be a reason for better surfactant adsorption to the algal cells . AccordiBesides being used as feed and food, microalgae are currently recognized as natural producers of highly valuable bioactive compounds. Several biomolecules produced by microalgae, namely carotenoids, polyunsaturated fatty acids, sulphated polysaccharides and phenolic compounds, have been found to display anti-inflammatory activity. This finding expands the range of applications of microalgal biomass from healthy diet ingredient in food to nutraceuticals that contribute to diminish the intensity of specific symptoms and/or to prevent specific pathologies related to inflammation processes. Many of those anti-inflammatory biomolecules have also high antioxidant capacity that has been reported to impact human health positively, in particular at advanced ages. Consequently, microalgae are considered to play a relevant role in the future map of novel strategies for the prevention and treatment of inflammatory diseases that includes the use of natural products obtained through well controlled biotechnological processes. The number of microalgae species still to be isolated from nature that could be promising for the accumulation of anti-inflammatory compounds is enormous. To achieve high productivities of target compounds, the isolation of fast-growth species and the enhancement of metabolic fluxes leading to increased biosynthesis of those target products are key aspects. In this sense, chemical tools such as specific triggers of target products and cell growth in foam, are being developed which will be very promising in the short term in order to exploit the production of microalgae enriched in molecules displaying anti-inflammatory activity.


Escherichia coli (n = 241). By modelling the diversity of bacterial genes encoding virulence and antimicrobial resistance (AMR) against ecological and anthropogenic forms of urban environmental change, we demonstrate that communities of avian-borne bacterial genes are shaped by the assemblage of co-existing avian, livestock and human communities, and the habitat within which they exist. In showing that non-random processes structure bacterial genetic communities in urban wildlife, these findings suggest that it should be possible to forecast the effects of urban land-use change on microbial diversity.Land-use change is predicted to act as a driver of zoonotic disease emergence through human exposure to novel microbial diversity, but evidence for the effects of environmental change on microbial communities in vertebrates is lacking. We sample wild birds at 99 wildlife-livestock-human interfaces across Nairobi, Kenya, and use whole genome sequencing to characterise bacterial genes known to be carried on mobile genetic elements (MGEs) within avian-borne  E. coli from wild birds near households in Nairobi and show that antimicrobial resistance gene diversity is correlated with human and lifestock density, while virulence gene diversity is correlated with avian species richness.Disease transmission is particularly complex at the human-livestock-wildlife interface. Here the authors sample  As one such process, urbanisation is characterised by extreme habitat fragmentation, which can have profound impacts on the distribution of host populations and epidemiology of infectious disease. In developing cities such as Nairobi, where urban livestock-keeping is commonly practiced as a result of growing demand for animal-sourced food products2, wildlife frequently co-exist with humans and livestock, forming interfaces across which infectious diseases can pass4. Changes in the composition and distribution of these host assemblages likely have important implications for microbial epidemiology, determining how pathogens are distributed within their reservoir, and dictating opportunities for spillover into non-reservoir hosts (such as humans)7. However, there is little empirical evidence that directly links changes in the function of abiotic and biotic systems to the structure of host communities, and dynamics of microbes living within them. Detecting the processes underlying the structure of microbial communities in wildlife and domestic animal populations would bring us a step closer to developing a predictive framework for pathogen emergence at urban wildlife-livestock-human interfaces8.Deterministic  processes play a central role in shaping how species communities interact with one-another and their environment(AMR) and virulence9. The distribution of MGE-borne genes amongst bacteria can therefore provide insight into the community structure of these micro-organisms, an approach that has been successfully used in conjunction with typing tools and time-scaled evolutionary analyses to infer bacterial transmission between hosts12. The wealth of genetic data generated by WGS could therefore provide an optimal approach to identify key drivers (such as land-use change) that influence the structure of bacterial populations at high risk wildlife-livestock-human interfaces, and assist in untangling the complexity of epidemiological processes, regardless of the taxonomic distance between hosts.Recent advances in sequencing technology, such as whole-genome sequencing (WGS), offer the potential to study the community of genes carried on mobile genetic elements (MGEs) within prokaryote genomes. MGE-borne genes can be horizontally transferred between organisms via recombination mechanisms, and may confer adaptive functional traits such as antimicrobial resistance 13. As such, if wildlife-borne bacteria are under higher selective pressure to adopt genes encoding AMR in urban areas where greater volumes of antibiotics are consumed, and antibiotic use is more widespread15, the community structure of MGEs encoding AMR would be hypothesised to respond to changes in human activity and the presence of livestock, rather than natural processes occurring in wildlife communities. In contrast, the diversity of genes encoding virulence traits (for which wildlife-borne bacteria are assumed not to be subjected to such strong anthropogenic selection pressure) would be hypothesised to reflect changes in wildlife host community structure – following the broadly accepted principal that host and microbial community diversity are correlated16, as wildlife host species diversity increases, the pool of virulence-associated MGEs to which they are exposed to should become more diverse.In this study, we apply principals from evolutionary ecology and molecular epidemiology to investigate whether urban ecological processes  and anthropogenic processes  occurring across the city of Nairobi, Kenya, are associated with non-random structuring of wildlife-borne bacterial genetic communities. We consider the diversity of MGE-borne genes as a proxy for the diversity of microbial communities within hosts, with the view that the ability of such genes to move relatively freely between bacterial cells through horizontal gene transfer mimics, to an extent, the movement of directly transmitted pathogens between hosts. For commensal bacteria, determinism would be expected in two classes of MGE-borne genes: those encoding AMR and virulence traits, each of which would be expected to respond differently to urban environmental change. Contamination of the external environment with AMR bacteria excreted from humans and livestock treated with antimicrobials , is considered an important route of wildlife exposure to AMREscherichia coli, collected from wild birds in household compounds across Nairobi. As likely points of contact  between vertebrate wildlife, livestock, and humans, household interfaces are chosen as sampling units representative of complex multi-host communities that are widely distributed across a gradient of urban environmental change, and thus suitable for testing our hypotheses. Wild birds are chosen as wildlife hosts in this urban study system, since diverse avian communities distribute widely across urban landscapes17, demonstrating epidemiological and ecological responses to land-use change18, and interacting closely with livestock and humans19. Aside from investigating processes underlying determinism in bacterial genetic diversity, studying the diversity of two sets of genes which may confer adaptive traits to bacteria will enable us to assess whether an association exists between urban land use and the genetic determinants of bacterial selection, with potential implications for human and animal health9.Adopting the null hypothesis that communities of wildlife-borne bacterial genes are structured by random processes, we test the above expectations by considering variation in the diversity of MGE-borne virulence and AMR genes in commensal n = 547) were collected from 57 avian species in 99 households across Nairobi, that were participating in the UrbanZoo project20. Households were selected in such a way that they captured variation in urban land use, wildlife assemblages, human demographics, and livestock-keeping practices across the city  or AMR (n = 47), were identified in 98% (n = 236) and 44% (n = 107) of these E. coli respectively. E. coli population structure across hosts was explored using multi-locus sequence typing (MLST). 128 unique sequence types (STs) were identified, representing a high genetic diversity of E. coli in avian samples across the city .Faecal samples (n = 239).To test whether microbial genetic communities in avian hosts were deterministically structured in association with the environmental conditions and structure of host communities at household interfaces within which avian hosts resided, the α-diversity of each set of genes  was calculated for individual hosts, and regressed against ecological and anthropogenic characteristics of households using generalised linear mixed effects models (GLMMs). Ecological and anthropogenic factors that were selected as indicators of variation in household environmental conditions, and used as fixed effects in the models, included: α-diversity (richness) of avian species present, biotic habitat diversity, artificial land-use cover (%), wealth indices, livestock-keeping status of each household, livestock density, and human density. Variation in bacterial genetic diversity introduced by differences in the feeding ecology and ranging behaviour of avian hosts was accounted for by including membership of avian hosts to epidemiologically relevant functional groups, and allometrically scaled estimates of each species home range, as fixed effects in each model. Two isolates for which host identity could not be confirmed were excluded from the statistical analyses . To further explore determinants of virulence gene diversity in seed-eating birds , a separate Poisson-distributed GLMM was built considering only the genetic diversity of sequences derived from this functional group (n = 152). This also had the effect of removing variation associated with functional group membership. Once other functional groups had been excluded, habitat diversity had a significant inverse relationship with diversity of virulence genes in seed-eating birds; as habitat diversity decreased, diversity of virulence genes in seed-eating birds increased .We found that the diversity of virulence genes present in birds varied between host functional groups, and increased with α-diversity of household avian communities , in which the presence or absence of AMR genes (the zero-inflated component) and increasing diversity of AMR genes  were modelled separately. The conditional model demonstrated that α-diversity of AMR genes was significantly associated with increasing human density, but only in households keeping livestock  and non-seed-eating birds. This indicated that the relationship between AMR gene diversity, livestock keeping and human density was only present for seed-eating birds  that was used to decompose variance attributed to avian diversity, livestock density, and human density within households across Nairobi. The first principal component (PC1) accounted for 72.9% of variation, clearly separating households with high avian diversity from households with high human and livestock density. Relating city-wide trends in host community structure to associations between diversity of virulence genes and avian diversity, and diversity of AMR genes and livestock and human density, reveals opposing epidemiological gradients of bacterial genetic diversity across Nairobi Fig. .Fig. 3EpUnderstanding the influence of environmental change on the diversity and distribution of microbial communities in wildlife is of fundamental importance to understanding how zoonotic diseases spillover into humans. Here, spatially explicit data on land use, the ecology of host populations, and high resolution microbial sequencing in individual hosts, is linked to explore this question across a developing city. We found that deterministic forces, both ecological (wildlife species assemblages and biotic habitat diversity) and anthropogenic (human and livestock density), operating across the urban landscape of Nairobi are associated with variation in the structure of bacterial genetic communities within avian host communities.E. coli isolates, with increases in avian diversity being associated with a higher diversity of virulence genes within their E. coli. This follows an expected pattern for communities of hosts and their microbial diversity. Assuming each vertebrate host harbours at least some E. coli bearing unique virulence genes, increasing vertebrate species diversity will increase the diversity of virulence genes circulating in the population21 (reviewed by Ostfeld & Keesing16). Our results are consistent with the hypothesis that, in this study system, increased vertebrate diversity results in avian-borne E. coli acquiring a greater diversity of virulence genes, because of exposure to a larger pool of available genes in the vertebrate host community. The composition and size of this pool of available genes would be hypothesised to vary across a gradient of urban land use, as the structure of avian communities change in response to the changes in habitat structure and biotic resource provision. However, our results also suggest that the relationship between microbial and host community diversity is subject to variation in host functional ecology. For frugivorous birds, which had higher mean diversities of virulence genes, virulence gene diversity was negatively correlated with avian diversity, perhaps because their exposure to E. coli harbouring novel virulence genes is driven by dietary exposure rather than transmission between hosts.For virulence genes, the species richness of host communities was positively correlated with the diversity of genes present in E. coli derived from seed-eating birds, which show more synanthropic behaviour than other functional groups, was predicted by changes in biotic habitat diversity rather than avian community diversity: in seed-eating birds, increasing virulence gene diversity was linked to decreasing biotic complexity of habitats. Further evidence for the role of host taxa in shaping the response of microbial genetics to variation in urban land use was provided by considering MGEs conferring AMR in E. coli. Increasing human and livestock density were associated with higher AMR gene diversity in avian-borne E. coli, but this only applied to isolates recovered from seed-eating birds. Importantly, the significant relationship between AMR gene diversity and human density was only found amongst household which kept livestock, providing evidence to suggest that households may act as an interface for the exchange of genes encoding AMR between livestock and wild birds. Livestock and human density could therefore be responsible for influencing the diversity (or pool) of AMR genes present and/or promoting contact with synanthropic wildlife, resulting in spillover of bacteria and/or their genetic elements from livestock to wildlife within household compounds.The results of this study also indicate that differences in the response of wildlife species to changes in urban land use could play a part in determining how microbial genetic diversity is related to host community diversity. For example, the diversity of virulence genes in 23, and increasing diversity of helminth parasitism in Southeast Asian murids has been positively correlated with a gradient of anthropogenic habitat change24.Our findings are important for several reasons. First, they point towards the presence of opposing epidemiological gradients for AMR and virulence genes across the urban landscape, in which communities of mobile microbial genes are correlated with changes in the richness and density of vertebrate host communities  Fig. . AlthougE. coli, exposure to larger pools of genetic diversity that promote uptake and fixing of AMR genes can confer adaptive advantages such as drug resistance25, whilst acquisition of virulence determinents in the accessory genome has been frequently implicated in the emergence of pathogenic lineages of E. coli. Divergence associated with horizontal gene transfer between closely related microbial strains can lead to the emergence of novel pathogens27.Second, our results provide evidence for a mechanism by which anthropogenic processes tied to variation in urban land use result in spillover of MGEs  between vertebrate host compartments at wildlife-livestock-human interfaces Fig. . And thi28. However, the focus of this study was on patterns of diversity in terms of gene presence or absence rather than characterising individual genes and the genetic context of their transfer. The sensitivity of commensal E. coli in identifying transmission pathways for other pathogens should also be considered with caution. Differences in characteristics (such as shedding rates and effects on host behaviour) between commensal and pathogenic organisms may have epidemiological consequences that reduce their representation of one another. In addition, by only sequencing a single E. coli isolate from each host, the within-host genetic diversity of E. coli was not considered. Previous molecular studies on E. coli , have demonstrated considerable within-host diversity across vertebrate taxa31. However, the decision to sequence a single isolate from each host was made as a necessary, cost-based trade-off between genetic resolution, depth of sampling E. coli genetic diversity within each individual, and the number of unique wildlife individuals from which samples could be included. Under sampling within-host diversity would only be likely to lead to a signal being missed, rather than changes to the positive results that we report in this study.In this study, high resolution genetic data collected as part of a structured epidemiological study, was used to study bacterial epidemiology in a multi-host urban system. Whilst the scale of sampling conducted in this study  provided the opportunity to explore hypotheses that, until recently could not have been tested, this dataset is not without epidemiological limitations, and the results presented in this study should be interpreted with the following considerations in mind. To better contextualise the transfer of MGE-borne genes, in particular those borne on plasmids, longer read sequencing  would provide an advantage over short-read Illumina data in making epidemiological inferencesEnterobacteriaceae as a proxy for parasite diversity, this study has necessarily taken a reductionist approach to address important hypotheses that otherwise could not have been answered using this dataset. The limitations in using a model organism such as E. coli could be addressed through utilising recent advances in metagenomics, which permit sequencing of bacterial and viral microbiomes, to characterise the structural response of microbial communities to the environmental drivers of urban land-use change. Such methods could be utilised in the future to understand how changes in microbial diversity, and the uptake and fixing of genes by pathogens, translate to emergence and manifestation of clinical disease in wildlife, livestock and humans.In demonstrating that it is possible to link epidemiological processes in wildlife to environmental drivers across urban landscapes, this study has taken the first step towards forecasting the effects of urban land-use change on disease emergence within a developing city. Whilst the focus of this study was on wildlife, understanding how urban environmental change structures microbial communities in human and livestock hosts is equally important, and extending analysis of the diversity of genes carried on MGEs to humans and livestock would provide valuable insight into the epidemiological responses of these compartments to variation in land use. By considering genetic diversity in a single species of The collection of data adhered to the legal requirements of the country in which the research was conducted. Wildlife were trapped under approval of an International Livestock Research Institute (ILRI) Institutional Animal Care and Use Protocol (2015.12).Questionnaire data was collected under ILRI Institutional Research Ethics Committee approval (2015-09), and prior informed consent was gained for each individual participating in the project.n = 547) were collected from 57 avian species from 99 households across Nairobi, that were participating in the UrbanZoo project20. The UrbanZoo project, based in Nairobi, Kenya from 2012–2017, aimed to utilise a landscape genetics approach to understanding the movement and sharing of pathogens in a major developing city. A key component of this project, within which this study was nested, was the ’99 household project’, which focused on informal livestock keeping practices in urban households as a route of zoonotic disease emergence in humans. As such, households were selected with the aim of maximising the spatial distribution and diversity of livestock keeping practices across Nairobi, and were chosen to capture three main criteria: socio-economic diversity, population distribution and livestock keeping practices. Geospatial mapping data, generated as part of a technical report produced by Institut Français de Recherche en Afrique (IFRA), was used to identify 17 classes of residential neighbourhood in Nairobi based on physical landscape attributes, which were subsequently verified by 817 household questionnaires32. Each of the 17 classes of neighbourhood were then ranked by average income and reduced into seven wealth groups. Administrative sublocations were mapped onto each wealth group, identifying a total of 70 possible sublocations, for which dominant wealth groups were calculated by extracting the proportion of population belonging to each neighbourhood class within the sub-location boundaries . Households had to meet strict inclusion criteria of keeping either large ruminants (cattle), large monogastrics (pigs), small ruminants (goats/sheep), small monogastrics (poultry/rabbits), or no livestock species. To ensure an equal sample of both cattle and pig-keeping households, the combination of livestock keeping households represented in each sublocation was randomised, and had to consist of either large ruminant and small monogastric, or large monogastric and small ruminant species. For sublocations in which households keeping large ruminant or large monogastric species were absent, a replacement household keeping either small monogastic or small ruminant species was recruited. Sampling of households took place between September 2015 and September 2016.E. coli; plant/seed-eating, omnivorous, fruit/nectar-eating, invertebrate-eating, vertebrate/fish-eating/scavenger. Allocation of avian species to functional groups was based upon the EltonTraits database33. Home range estimates for all avian species were calculated by allometric scaling of body weight34. Scaling factors published for functionally different birds by Ottoviani et al.35 were used, and species mean body weights were either collected during sampling, or sourced from published datasets when unavailable36.A dedicated field team was responsible for collecting data on humans, livestock and wildlife in each household, consisting of veterinarians, animal health technicians and clinicians. Mist nets were set at dawn to trap birds, with nets being positioned outside the house and around livestock keeping facilities. Once caught, all birds were live-sampled in the field under manual restraint, before being released unharmed. Morphometric data were collected for identification purposes, and a suite of biological samples  were collected from each animal. Due to large variation in the size of household compounds, trapping effort  was maintained such that it was proportional to the size of the household compound. Ecological surveys were used, alongside trapping data, to estimate the diversity of avian species present within households. Avian species counts (presence/absence) were conducted by a trained ornithologist from the National Museums of Kenya, in which species were identified based on audio-visual identification over a 20-minute period spent walking transects of each household compound. Surveys were conducted between 6:30am and 9:30am, over the course of two months in the dry season, ensuring that bird activity and weather conditions were constant. The species richness of avian communities  was calculated for each household. Avian species were also grouped into five functional groups, deemed relevant for the epidemiology of a directly transmitted gastrointestinal parasite such as i) livestock ownership, management, sourcing, sales and antimicrobial use, and ii) household composition and socio-economic data. Abundance (counts) of livestock species and humans were derived from this data for each household. Dividing livestock and human abundance by household area  generated an estimate of density of livestock and humans. Household composition and socio-economic data were used to generate wealth and ruralness indices for each household sampled20. These indices were calculated based on methods used to create the Demographic and Health Surveys (DHS) wealth index, which is derived from a Principal Component Analysis (PCA) of easily measurable households assets 37. A modification was made to the original set of household assets included in the DHS index to better capture household variation in Nairobi. All field data was recorded using Open Data Kit (ODK) Collect software , on electronic tablets, and uploaded to databases held on servers at the International Livestock Research Institute (ILRI).A nominated member of each household completed a questionnaire, detailing Mus and rattus spp., estimates of which vary from 1 m to 30 m)39. Visual classification of land-use types within the compound and buffer area were conducted at 1:500 scale on a 1 m resolution ESRI World Imagery satellite-image available in ArcGIS 10.5 (ESRI). Characterisation of ecological characteristics along a perimeter around the household compound was considered as important, because the ecological setting within which the household exists extends beyond the boundaries of the compound. The extent to which this influential area of habitat outside the compound extends is unknown, and as such it was standardised across study sites. Within the boundary, the areas of nine different land-use types were visually identified and sketched as polygons; water-body, wetland, crops, mature trees, shrubs, grassland, bare ground, artificial ground and rubbish  or University of Nairobi (UoN)). Samples were enriched in buffered peptone water for 24 hours, and plated onto eosin methylene blue agar (EMBA). Plates were incubated for 24 hours at 37 °C, after which five colonies were selected from each EMBA plate. After a further sub-culture on EMBA to purify the isolates, the pure isolates were sub-cultured on Müller-Hinton (MH) agar and archived at −80 °C in cryovials containing Soy broth supplemented with 15% glycerol.E. coli. DNA was extracted from bacterial isolates using commercial kits  and transported under licence to The Wellcome Trust Centre for Human Genetics, Oxford, UK. Whole genome sequencing (WGS) was carried out at the Wellcome Trust Centre for Human Genetics on the Illumina HiSeq 2500 platform. 150 base-pair paired-end reads were generated and short-read WGS data were pre-processed using an automated protocol developed by the Modernising Medical Microbiology Oxford (MMM) Group to: (i) perform standard quality control checks using fastQC (https://www.bioinformatics.babraham.ac.uk/projects/fastqc/) with default settings; (ii) trim reads to remove remnant adaptor sequences using bbduk40  and (iii) perform a Kraken41 speciation analysis against with an in-house database of bacterial reads downloaded from the NCBI sequence read archive (www.ncbi.nlm.nih.gov/sra/), with an automated step for removal of contaminant  reads. De novo assembly was performed using SPAdes v3.642 . The assemblies were run through the batch upload mode of the Centre for Genetic Epidemiology web interface hosted by the Technical University of Denmark (https://cge.cbs.dtu.dk/services/cge/) which performs speciation analysis43, multilocus sequence typing (MLST)44, detection of resistance genes45 and detection of virulence genes46. The threshold of AMR gene detection was set to 90% identity and 60% coverage, as this is shown to be the optimal threshold for this method. A 60% coverage threshold was used to ensure that AMR genes spread over two contigs, and/or located on the edge of the contig, were not missed45. Virulence genes were identified using VirulenceFinder with 90% minimum match and 60% minimum length. Samples deemed as non-E. coli on the basis of the speciation analysis with kmerFinder47 in the Centre for Genetic Epidemiology pipeline were excluded from further analysis. Potentially mixed E. coli samples were identified as those with an unusually large assembly size (greater than 6 megabases (Mb)) and were removed from the dataset. Supplementary Table E. coli isolates included in the study.A single colony was picked from each original sample (referred to as an isolate) and biochemical tests  were run for identification as 48. The response variables diversity of virulence and AMR genes, were regressed against explanatory variables in generalised linear mixed effects models (GLMMs). Isolates for which AMR or virulence genes were not detected were included in these analyses. To address the fact that genes co-mobilised on the same MGE might not represent independent acquisition events without having access to long-read sequencing (which would enable identification of the location of genes on plasmids), we combined all pairs of genes with 100% co-occurrence . To account for the dependency structure of the data, the household and sublocation in which samples were collected were included as nested random effects. To account for the relationship between bacterial population structure and MGE diversity, we also included a measure of bacterial population structure as a random effect in each model. Due to high MLST diversity in the dataset , sequence type could not be included as a random effect, and as such, each isolate was assigned to a less stringent cluster using the BURST algorithm, on the basis of 3 rather than 7 genetic loci. This composite measure of genetic structure was included as a random effect in each model. Models of virulence gene diversity were fitted with a Poisson distribution in the R package lme449. Preliminary data exploration indicated substantial zero-inflation in the response variable α-diversity of AMR genes , and as such a zero-inflated Poisson model (ZIP) was initially fitted to the data (56% of data comprising the response variable were zeros). However, residuals from the optimal ZIP model obtained through step-wise selection showed considerable overdispersion . Dispersion parameters were stabilised by fitting zero-inflated mixture and hurdle models available in the R package glmmTMB50 to the data. These classes of model are frequently used to model zero-inflated count data in ecological datasets. The fit of these models were compared using Akaike’s information criteria (AIC).All statistical analyses were conducted using R v3.3.22) where possible. Model assumptions were verified by plotting residuals versus fitted values, and by assessing models for overdispersion. Non-linear relationships were checked by fitting a generalized additive model (GAM) between the response and explanatory variables, featuring a nonlinear smoother, in R package mgcv51. The residuals were also assessed for spatial dependency by plotting them against geographic coordinates, and examining the results of a semivariogram.Optimal models were constructed using stepwise, backwards elimination from the full model based upon (AIC). Significance of model terms were tested by the maximum likelihood test, and the fit of each model was reported as marginal regression coefficients of multiple determination , was performed on avian diversity, livestock density, and human density within households across Nairobi, in the R package veganFurther information on research design is available in the Supplementary Informationpeer review fileReporting Summary


As FDA-approved small RNA drugs start to enter clinical medicine, ongoing studies for the microRNA (miRNA) class of small RNAs expand its preclinical and clinical research applications. A growing number of reports suggest a significant utility of miRNAs as biomarkers for pathogenic conditions, modulators of drug resistance, and/or as drugs for medical intervention in almost all human health conditions. The pleiotropic nature of this class of nonprotein-coding RNAs makes them particularly attractive drug targets for diseases with a multifactorial origin and no current effective treatments. As candidate miRNAs begin to proceed toward initiation and completion of potential phase 3 and 4 trials in the future, the landscape of both diagnostic and interventional medicine will arguably continue to evolve. In this mini-review, we discuss miRNA drug discovery development and their current status in clinical trials. Groundbreaking results from the Human Genome Project revealed extensive complexity in our DNA sequence and unleashed new opportunities in biomedical and clinical trial studies . CorrespFuture clinical trials will likely continue to capitalize on the revolutionary findings from the Human Genome Project that RNA transcripts far outnumber protein-encoding genes. This is a significant paradigm shift from the decades-old “central dogma” that one RNA makes one protein. Further, the classes of these nonprotein-coding RNAs (ncRNAs) have vastly expanded with ongoing research studies and now include transcripts such as microRNAs (miRNAs), natural antisense transcripts, Piwi-interacting RNA (piRNAs), and long ncRNAs (lncRNAs) . Arguablin vitro prior to testing in preclinical animal models. A growing number of databases are available to predict miRNA regulatory targets  cells are readily available for epigenetic manipulation of target transcripts. IPS cells allow for modulation and monitoring of biological pathways along distinct stem cell lineages from a skin tissue source   .A growing number of reports have shown that subsets of miRNAs may have clinical relevance as biomarkers. These biomarkers can be used to indicate presence of a pathology and even the stage, progression, or genetic link of pathogenesis . In certclinicaltrials.gov database for miRNA biomarkers have been completed; this includes phase 4 trials that monitored select miRNAs as biomarkers for disease progression in patients receiving FDA-approved drugs. Trials have assessed or are actively recruiting patients to examine the profiles of these ncRNA transcripts in a range of health conditions such as diabetes, coronary heart disease, breast cancer, lupus, epilepsy, depressive disorder, stroke, Addison’s disease, influenza, liver disease, and even toxic exposure to agents such as acetaminophen. Additionally, as miRNAs are ubiquitously expressed throughout the body, they can readily be measured from peripheral blood, tissue biopsies, saliva, urine, cerebrospinal fluid (CSF), and other biological samples  . OngoingThis is an exciting time for therapeutic small RNA (less than 200 nucleotides in length) drugs, as the first small-interfering RNA (siRNA) was recently granted FDA approval in 2018. The siRNA drug, Patisiran, is approved for a rare polyneuropathy caused by hereditary transthyretin-mediated (hATTR) amyloidosis and works by binding and degrading the messenger RNA transcript for transthyretin . AlthougTo date, there is reported clinical utility in peripheral tissues for miRNA mimics (to overexpress the transcript) as well as miRNA repressors (to silence the transcript function). Systemic delivery methods of miRNA drugs parallel those of traditional therapeutics with injection or intravenous administration. For cancer-related pathologies, intratumoral injections of miRNA drugs directly into the pathogenic site can enhance target specificity, efficacy, and minimize side effects . ArguablPutative miRNA drugs have exhibited significant efficacy in a range of health conditions, including cancer, hepatitis C, heart abnormalities, kidney disease, pathologic fibrosis, and even keloid formation. In line with other clinical trials, some miRNA candidates have shown potential, while some have failed and the study was terminated. For example, in 2016, the biotech company MiRNA Therapeutics (now Synlogic) halted phase 1 trials of its miRNA-34 drug mimic, MRX34, for use in cancer after severe adverse events (SAE) were reported in five patients experiencing serious immune responses. Due to the development of SAE, future phase 2 trials of MRX34 for melanoma were also terminated.clinicaltrials.gov database for phase 3 trials to date, there are active earlier phase trials to investigate new miRNA drug candidates in addition to the previously mentioned miR-122/Miravirsen studies. There is ongoing recruitment of patients for a phase 1 trial of the drug MRG 110, a locked nucleic acid (LNA)-modified antisense oligonucleotide to inhibit the function of miR-92. The company miRagen recently announced a second phase 1 trial with MRG 110 with a future potential clinical application toward wound healing as well as heart failure. Miragen also has an active phase 1 study for miR-29 (MRG-201) to treat keloid and scar tissue formation as well as a phase 2 trial for miR-155  for patients with a form of T-cell lymphoma. This year (2019), Regulus announced their new miRNA drug candidate nominee RGLS5579 that targets miR-10b for potential trials in patients diagnosed with glioblastoma multiforme, one of the most aggressive forms of brain cancer with a median survival of approximately 14.6 months . In the first human trial of a TargomiR drug, MesomiR-1, the miRNA mimic was the reported tumor suppressing transcript miR-16 and the targeting moiety was an antibody to the epidermal growth factor receptor (EGFR) that is consistently deregulated in lung cancer cells . These sA problem that continues to plague current treatment options in clinical medicine is drug resistance, including life-saving chemotherapeutics in patients with cancer. A number of published reports show that manipulating expression of specific miRNAs can alter the drug sensitivity or that miRNAs are themselves biologically involved in the body’s resistance response. Many of the standard therapies for breast cancer, such as Doxorubicin, Cisplatin, and Taxol, are all associated with deregulated miRNAs which may modulate resistance to the drug . EvidencThe role of miRNA transcripts in drug resistance is reportedly not restricted to cancer pathologies. The expression of miRNAs is associated with drug resistance in treatment of conditions such as epilepsy , multidrSpecific mechanisms of drug resistance mediated by miRNAs are under ongoing investigation. Accumulating evidence, however, shows that the ATP-binding cassette (ABC) transporter family of proteins that activate drug resistance are regulated by miRNAs . The ABCin vitro and in vivo preclinical research models, has helped expedite the translation of miRNAs into clinical medicine. The first siRNA human trial was conducted in 2004 and in 2018 the first siRNA drug was approved (As the pioneering discoveries from the Human Genome Project shift the landscape of clinical research, emerging miRNA therapeutics are offering new promise in health conditions that remain elusive to current treatment options. Development of bioinformatic programs for identification of miRNA-binding sites in target genes and their corresponding implicated biological pathways, along with an expanding platform of approved , paving JK, JH, and GH wrote and edited the manuscript.GH is the CEO of Nova Clinical Research, LLC, and is not currently involved in any research projects involving miRNA.The remaining 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.


Brain functional imaging data, especially functional magnetic resonance imaging (fMRI) data, have been employed to reflect functional integration of the brain. Alteration in brain functional connectivity (FC) is expected to provide potential biomarkers for classifying or predicting brain disorders. In this paper, we present a comprehensive review in order to provide guidance about the available brain FC measures and typical classification strategies. We survey the state-of-the-art FC analysis methods including widely used static functional connectivity (SFC) and more recently proposed dynamic functional connectivity (DFC). Temporal correlations among regions of interest (ROIs), data-driven spatial network and functional network connectivity (FNC) are often computed to reflect SFC from different angles. SFC can be extended to DFC using a sliding-window framework, and intrinsic connectivity states along the time-varying connectivity patterns are typically extracted using clustering or decomposition approaches. We also briefly summarize window-less DFC approaches. Subsequently, we highlight various strategies for feature selection including the filter, wrapper and embedded methods. In terms of model building, we include traditional classifiers as well as more recently applied deep learning methods. Moreover, we review representative applications with remarkable classification accuracy for psychosis and mood disorders, neurodevelopmental disorder, and neurological disorders using fMRI data. Schizophrenia, bipolar disorder, autism spectrum disorder (ASD), attention deficit hyperactivity disorder (ADHD), Alzheimer's disease and mild cognitive impairment (MCI) are discussed. Finally, challenges in the field are pointed out with respect to the inaccurate diagnosis labeling, the abundant number of possible features and the difficulty in validation. Some suggestions for future work are also provided. Brain disorders such as schizophrenia (SZ) and bipolar disorder (BP) are considered in terms of disruptions of the normal-range operation of brain functions. While psychiatric disorders are diagnosed based on symptom scores from clinical interview, there are no existing gold standards that can be used for definitive validation. Brain functional neuroimaging techniques including functional magnetic resonance imaging (fMRI)  among brain regions using fMRI data , and most previous fMRI studies applied a static functional connectivity (SFC) analysis. Until recently, more emerging exciting work have proven that regarding brain functional connectivity as dynamic over time can be successful in uncovering the disruptions to the normal human brain in disease condition  or voxels   is another method which optimizes the independence among each subject's components and the dependence among corresponding components of different subjects. Several advancements of IVA have been made for achieving reliable source separation for linearly dependent Gaussian and non-Gaussian sources  to a new subject that is not included in the original training set is an important issue. In the case of applying individual ICA on each subject separately, the obtained components from each coming subject have to be well-matched with the components from the training set using some matching rules so that their used features are consistent. In group ICA framework, there are several ways to do this, one can use spatio-temporal regression to generate spatial and temporal features from new subjects   other meaningful measurements have also been proposed. For example, the regional homogeneity (ReHo)  and generate a static value to reflect the connection strength. In recent years, there have been much interests in computing time-resolved connectivity measures and successful applications in identifying biomarkers from dynamic connectivity  has emerged as a promising topic in the recent fMRI literature, there are also some critical comments on the theory of dynamic connectivity. Laumann et al.  suggesteThere are numerous methods which can be used to estimate DFC  is so far the most popular method  is another widely used classifier  is popular in the classification of patients using fMRI data , and also include some work distinguishing multiple different disorders . We mainly summarize studies relating to schizophrenia, bipolar disorder, autism spectrum disorder (ASD), attention deficit hyperactivity disorder (ADHD), Alzheimer's disease (AD) and mild cognitive impairment (MCI), some of which share very similar symptoms and common changes in the brain that can confound diagnosis, such as SZ vs. BP, ASD vs. ADHD, and AD vs. MCI. Although other brain disorders such as depression also deserve review in the future, our primary goal here is to provide an overview on how far brain functional connectivity features have been used to classify brain disorders and how well the classification frameworks have worked. Figure https://www.nimh.nih.gov/health/topics/bipolar-disorder/index.shtml). The root causes of bipolar disorder are not clearly understood, although it is known that both environmental and genetic factors are involved. There is no standard clinical test for either schizophrenia or bipolar disorder. Therefore, it is important to investigate the possibility of using neuroimaging data in the automatic diagnosis of these two brain disorders.Schizophrenia is a severe chronic brain disorder whose symptoms can include delusions, disorganized thinking, hallucinations and social withdrawal . The reduced features were then used as input of a probabilistic Bayesian classifiers classifier. The experimental results showed that the average three-way correct classification rate (CCR) is in the range of 70–72%, demonstrating their proposed method to be a reliable framework on classification analyses of both schizophrenia and bipolar disorder patients. More recently, time-varying patterns in the functional connectivity have been used to distinguish SZ from BP patients. Rashid et al. proposed a framework for classification of schizophrenia, bipolar and healthy subjects based on their static and dynamic FNC  . Even if feature selection is performed using a supervised method, the resulting features are not necessarily able to show a clustering property within each group as expected, since there are usually abundant unrelated and redundant measures considered. In the event the diagnosis is inaccurate, selection of features so that they can show clustering (or similar) patterns within the same group and distinct patterns between different groups is more difficult. Without using group labeling, Clementz et al.  construcOnce the biomarkers and biologically-derived classification are obtained, validating the biomarkers and categories (or classification) is another important issue. Most related studies have classified independent subjects based on the identified biomarkers and a well-trained model, and then compared the classification outputs with the diagnosis labels. However, researchers should be aware that the diagnosis labels used as ground-truth could be inaccurate. Some work  template. However, these registration methods cannot guarantee fully accurate inter-subject functional consistency, although the following spatial smoothing of fMRI data can reduce the inter-subject functional variability to some extent. Therefore, functional connectivity computed between given brain regions may not accurately correspond across subjects, although the adaptive ICA-based methods are likely more robust to this than ROI or voxel based approaches. In the future, advanced normalization methods  for classification and prediction were clearly summarized for each method. Furthermore, we surveyed various feature selection and classifier building strategies in order to provide guidance on how to perform the classification and predication problem in practice. After that, an updated overview on applications of classifying SZ, BP, ASD, ADHD, were shown. Finally, we discussed gaps in the research and areas that particularly deserve improvement.YD proposed the framework and wrote the paper. ZF drafted and revised the paper. VC revised the manuscript and gave 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.


Climatic stresses limit plant growth and productivity. In the past decade, tree improvement programs were mainly focused on yield but it is obvious that enhanced stress resistance is also required. In this review we highlight important drought avoidance and tolerance mechanisms in forest trees. Genomes of economically important trees species with divergent resistance mechanisms can now be exploited to uncover the mechanistic basis of long-term drought adaptation at the whole plant level. Molecular tree physiology indicates that osmotic adjustment, antioxidative defense and increased water use efficiency are important targets for enhanced drought tolerance at the cellular and tissue level. Recent biotechnological approaches focused on overexpression of genes involved in stress sensing and signaling, such as the abscisic acid core pathway, and down-stream transcription factors. By this strategy, a suite of defense systems was recruited, generally enhancing drought and salt stress tolerance under laboratory conditions. However, field studies are still scarce. Under field conditions trees are exposed to combinations of stresses that vary in duration and magnitude. Variable stresses may overrule the positive effect achieved by engineering an individual defense pathway. To assess the usability of distinct modifications, large-scale experimental field studies in different environments are necessary. To optimize the balance between growth and defense, the use of stress-inducible promoters may be useful. Future improvement programs for drought resistance will benefit from a better understanding of the intricate networks that ameliorate molecular and ecological traits of forest trees. Forests cover about 30% of the terrestrial land FAO, . They haThe negative consequences of drought become even more urgent in current times of climate change because projections suggest that such events will occur more frequently and be more extreme  and pedunculate oak (Quercus robur) have recently been published ], signaling and response factors such as DREB1, bZIP, AP2/ERF, MYB, NAC, and WRKY , I-214 (P. × canadensis), Pallara et al., P. alba accompanied reductions in predawn leaf water potentials and stem dehydration  is beneficial for water-use efficiency (WUE) and results in enhanced drought resistance in several plant species   and proline dehydrogenase] accumulate under osmotic stress  under the RD29 promoter activated osmolytes (sugars) and enhanced the performance of transgenic plants under drought stress  or choline oxidase (from bacteria) were overexpressed under an oxidative stress-inducible promoter , Phyllostachys edulis (bamboo), Morus spp. , Hevea brasiliensis (rubber), Picea and Pinus (conifers), and Cicer arietium (herbaceous legume crop such chikpea). The target species were model species such as poplars, Arabidopsis and Nicotiana tabacum, but also crops such as alfalfa, cotton, lotus, tomato and rice. Transformation of non-model tree species for enhanced stress tolerance is still rare but recent results showed promise. Overexpression of DREB2A, a gene that forms a hub for drought-stress related gene expression in Robinia pseudoacacia resulted in enhanced drought resistance  contributed to salt-induced leaf succulence  CaXTH3 in guard cells reduced transpiration under dehydration stress, thus, supporting a role of XTHs in drought resistance , CUC (cup-shaped cotyledon) superfamily, Wang et al., ERF  to improve drought tolerance are still in their infancy but hold promise for new discoveries. For example, lignin deposition was reduced in poplars in which P. euphratica, gene duplication, and evolutionary recruitment of distinct metabolites such as ABA for stomatal regulation could also be important avenues for future research. Furthermore, long-term studies under field conditions are still scarce. There is obviously a strong need for testing genetically modified trees in their natural environment because the combination of stress factors such as heat and drought together may overrule the effects of single stressors present under laboratory conditions.Trees are capable of responding to drought stress through a wide variety of cellular and physiological acclimation strategies, which form the basis for genetic improvements of drought tolerance. In particular, overexpression of drought sensing, signal transduction, and drought responsive transcription factors can enhance drought tolerance in a variety of model systems and some economically important woody species. Our overview on transgenic modifications revealed that modifications at the cellular level were the main targets, often using genes from drought or salt tolerant woody species for overexpression. However, systematic studies to clarify if these genes perform better than those from drought sensitive species are lacking. Comparative studies suggest that amplification of distinct gene families such as the SOS pathway in At a wider scale, we have to assert that our mechanistic understanding of the interplay among osmotic regulation, hydraulic adjustment and uptake systems for water and nutrients is still in its infancy. In particular, the root-to-shoot communication that sets off a suite of responses leading to morphological changes of the root system is not clear. Therefore, an important future task will be to uncover the genetic basis for an optimized resource allocation between biochemical defenses and production of new structures such as deep rooting systems under stressful climatic conditions. Next-generation genomics and phenomics approaches will facilitate a better understanding of phenotype-genotype maps and help to formulate genomic-assisted breeding strategies in forest trees for resistance to drought stress and other osmotic cues.AP, SC, CE, and AH drafted and wrote the manuscript together. All authors agreed on the final version of this review.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.


Clinical and basic research on regulation of pituitary hormones, extra-pituitary release of these hormones, distribution of their receptors and cell signaling pathways recruited upon receptor binding suggests that pituitary hormones can regulate mechanisms of nociceptive transmission in multiple orofacial pain conditions. Moreover, many pituitary hormones either regulate glands that produce gonadal hormones (GnH) or are regulated by GnH. This implies that pituitary hormones may be involved in sex-dependent mechanisms of orofacial pain and could help explain why certain orofacial pain conditions are more prevalent in women than men. Overall, regulation of nociception by pituitary hormones is a relatively new and emerging area of pain research. The aims of this review article are to: (1) present an overview of clinical conditions leading to orofacial pain that are associated with alterations of serum pituitary hormone levels; (2) discuss proposed mechanisms of how pituitary hormones could regulate nociceptive transmission; and (3) outline how pituitary hormones could regulate nociception in a sex-specific fashion. Pituitary hormones are routinely used for hormonal replacement therapy, while both receptor antagonists and agonists are used to manage certain pathological conditions related to hormonal imbalance. Administration of these hormones may also have a place in the treatment of pain, including orofacial pain. Hence, understanding the involvement of pituitary hormones in orofacial pain, especially sex-dependent aspects of such pain, is essential to both optimize current therapies as well as provide novel and sex-specific pharmacology for a diversity of associated conditions. Orofacial pain conditions dramatically impact basic daily life activities such as talking and chewing, which leads to debilitating physiological and psychological consequences  females could have different pain tolerance/thresholds than men and they may also seek out health care services at higher rates than do men. While there is evidence that this can be the case for humans, animal data do not convincingly show differences in tolerance/threshold between sexes so it may be unlikely that sensitivity alone explains higher female pain prevalence Mogil, ; and (2)A third factor, and the subject of this review article, is that the distinct sexual differences seen in orofacial pain conditions are mediated by hormone-based mechanisms. In fact, changes in gonadal hormones (GnH) such as estrogen, progesterone and androgens are shown to be associated with changes in pain experience in many orofacial pain conditions , PRL, follicle stimulating hormone (FSH), luteinizing hormone (LH) and other pituitary hormones has not been explored to the same depth. Hormones produced by the pituitary were originally named and characterized according to their primary biological function at the time of discovery: PRL is linked to milk production in females, GH is associated with cell growth, proliferation, differentiation and regeneration and other pituitary hormones, such as FSH, LH and adrenocorticotropic hormones (ACTHs) are master controllers of critical glands. Later studies established that pituitary hormones play critical roles in a much wider variety of physiologic and pathophysiologic processes. Thus, many of pituitary hormones have been associated with pain conditions across the entire body. This review article focuses on several pituitary hormones which according to human and animal studies are known to be involved in the regulation of orofacial pain. Particular emphasis will be placed on hormones regulating GnH production or those regulated by GnH, since they are viable candidates for the sexually-dimorphic regulation of orofacial pain.The main variant of PRL is a 23 kDa protein  or functional (hormone secreting) with symptomology dependent on the specific hormone(s) secreted. Headache and facial allodynia are common in patients with functional adenomas  for how elevated endogenous PRL causes pain is not fully known, but clear links between PRL and the somatosensory system exist. Prlr is known to be expressed in a subset of rat and mouse sensory neurons of dorsal root ganglia (DRG) and trigeminal ganglia (TG) neurons, although the precise Prlred Table . Neverthed Table , and TRPed Table . TRPA1 aed Table . Importaed Table . Behavioed Table . This inAs mentioned previously, sources of endogenous PRL can originate from pituitary  or extra-pituitary (EPit PRL) tissues , which is mainly produced by the paraventricular nucleus (PVN) of the hypothalamus and the posterior pituitary  is a 22 kDa protein produced by somatotrophs located in the anterior pituitary. GH production and secretion is regulated by myriad factors including hormones, sex hormones, stress, deep sleep, fasting, vigorous exercise, etc  ACTH is a key component of the hypothalamic-pituitary-adrenal (HPA) axis, which is a chief controller of physiologic responses to both physical and emotional stress  periods  controls tissue metabolism via production of thyroxine (T4) through iodination of thyroglobulin in thyroid gland follicles. T4 is later converted into the active hormone triiodothyronine (T3) at target tissues, and acts via a combination of transport and nuclear receptors Brent, . ReleaseSeveral diseases are characterized by misbalanced TSH, T3 and/or T4. All forms of thyroid disease are at least 3–4 times more prevalent in women than in men  by the ovaries and testes. LH and FSH are heterodimers with alpha and beta subunits. The alpha subunits (92 AA) are identical in LH, FSH and TSH, leading to high levels of cross-reactivity between hormones and receptors. FSH and LH production and secretion are controlled by GnRH supplied by specialized hypothalamic neurons. GnRH is in turn strictly regulated (inhibited) by GnHs, especially estradiol and testosterone. LH and FSH are regulated by virtually every pituitary hormone via numerous pathways. Generally, these regulations occur either through GnRH or GnH pathways. Because of their diverse regulation, LH and FSH levels are often affected during pain conditions, especially chronic ones. However, clinical reports are not as consistent as basic research data. Some studies reported reduction of LH and increase in FSH basal levels in headache patients , Somatostatins, Dopamine agonists (to block PRL), TH (synthroid), FSH, LH, FSH/LH combos (menopur), FSH receptor antagonists, GnRH agonists and antagonists, ACTH, OXT and many more.AA wrote the first draft of the manuscript. AA, JB and GD prepared final version 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.


Recent studies have accomplished the extraordinary feat of measuring the exact status of DNA replication in individual cells. We outline how these studies have revealed surprising uniformity in how cells replicate their DNA, and consider the implications of this remarkable technological advance. The DNA of eukaryotic genomes is replicated in a characteristic temporal order. In mammalian cells, clusters of replication origins initiate synchronously, leading to regions of chromosomal DNA that replicate at a particular time during S-phase; these are referred to as replication-timing domains. The pattern of replication-timing domains leads to a genome-wide replication timing profile that, although generally fairly stable for the genome of a particular organism, does show some differences that are dependent upon cell type and developmental status. In particular, genomic loci have been identified that undergo clear transitions in their replication timing during differentiation, sometimes correlating with the expression status of the genes they contain. Early-replicating domains tend to be euchromatic and enriched for marks of open and active chromatin, whereas late-replicating domains are enriched for closed, inactive heterochromatic marks. One special case is the X chromosome, where the inactive X of mammalian females becomes almost entirely late-replicating as its transcription is shut down. There are multiple links between replication timing and genome stability: replication time correlates with mutation rate and timing profiles are often disrupted in cancer cells , potentiIn the past two decades, many studies have analyzed replication timing genome-wide , 3, most1-phase cells—then revealed which sequences had been replicated in the particular cell being assessed  heterogeneity between cells and between homologous chromosomes does exist but is limited so that sequences almost always replicate close to their scheduled time; (ii) there are developmental differences in replication timing; and (iii) replication timing correlates with euchromatic or heterochromatin status and with subnuclear chromosome organization. The main excitement lies in what this technology will permit. Several factors are known or suspected to control the replication-timing program, but their precise impact on specific sites and replication-origin types remains unclear, partly because population methods have not permitted exact effects to be resolved . When a What this analysis does not yet provide is detailed initiation site information: because origins fire in clusters, new bubble structures rapidly merge, preventing the actual initiation sites from being detected by a snapshot approach. In addition, pinpointing initiation events that could be ‘caught in the act’ would require higher resolution than that presented to date. However, another remarkable new technology, ultra-long nanopore sequencing identification of nascent DNA, is set to advance our understanding of replication initiation site specification greatly in the near future . Single Overall, recent studies have provided an ultra high-resolution view of how cells progress through the replication program. By parsing within-cell variability from population effects, the combination of single-cell and single-molecule approaches to analyze replication holds enormous potential. The resolution and accuracy now offered by such methods will open a new and exciting era in understanding how cells replicate their genomes.