BD). A comprehensive assessment of mental imagery in BD is lacking. We aimed to test whether (i) mental imagery abnormalities  occur in BD relative to non‐clinical controls; and (ii) to determine the specificity of any abnormalities in BD relative to depression and anxiety disorders.Mental imagery abnormalities occur across psychopathologies and are hypothesized to drive emotional difficulties in bipolar disorder , subjects with unipolar depression (n=26), subjects with anxiety disorders (n=25), and non‐clinical controls (n=27) matched for age, gender, ethnicity, education, and premorbid IQ. Experimental tasks assessed cognitive  measures of mental imagery (cognitive stages). Questionnaires, experimental tasks, and a phenomenological interview assessed subjective domains including spontaneous imagery use, interpretation bias, and emotional mental imagery.Participants included 54 subjects in the BD combined group reported a greater impact of intrusive prospective imagery in daily life, more vivid and “real” negative images (prospective imagery task), and higher self‐involvement (picture‐word task). The BD combined group showed no clear abnormalities in cognitive stages of mental imagery. (ii) When depressed individuals with BD were compared to the depressed or anxious clinical control groups, no significant differences remained—across all groups, imagery differences were associated with affective lability and anxiety.(i) Compared to non‐clinical controls, the BD is characterized by abnormalities in aspects of emotional mental imagery within the context of otherwise normal cognitive aspects. When matched for depression and anxiety, these abnormalities are not specific to BD—rather, imagery may reflect a transdiagnostic marker of emotional psychopathology.Compared to non‐clinical controls,  Pearson et al.“Rediscovering” mental imagery in clinical practice can improve assessment.The current study aimed to investigate: (i) whether individuals with BD have mental imagery abnormalities compared to non‐clinical controls and (ii) whether mental imagery abnormalities (when present) are specific to individuals with BD compared to clinical controls with depression and anxiety. To address these questions, we compared (i) patients with BD and non‐clinical controls; (ii‐a) patients with BD and patients with unipolar depression with equivalent levels of depressive symptoms; and (ii‐b) patients with BD and patients with anxiety disorders with equivalent levels of anxiety symptoms. We also explored whether clinical variables such as depressive and anxious symptomatology, bipolar phenotype traits, affective lability and general functioning levels predicted scores on mental imagery measures in the whole sample combined. A range of tests were used encompassing both cognitive stages of mental imagery and assessment of subjective and emotional domains.22.1Participants completed pre‐screening questions via email or phone to assess potential eligibility, based on which 175 were invited to attend a screening session. At the beginning of the session, all participants provided written informed consent  and the Structured Clinical Interview for DSM‐IV (SCID) Axis I DisordersBD group: DSM‐IV diagnosis of bipolar I disorder, bipolar II disorder, or bipolar disorder not otherwise specified, not current (hypo)manic episode; unipolar depression group: DSM‐IV diagnosis of major depressive episode (MDE); anxiety disorder group: DSM‐IV diagnosis of anxiety disorder in the absence of a present or past history of BD and of a current primary MDE; non‐clinical control group: no past or present Axis I disorder based on DSM‐IV diagnosis. Exclusion criteria for all participants were active suicidal risk, psychotic symptoms, current substance abuse, all assessed during the SCID, and severe neurological impairment reported during the screening session. Of the 175 participants who attended the screening session, 24 were excluded based on these criteria.The screening session was used to determine whether participants met the following DSM‐IV diagnostic criteria: Allocation to one of the experimental groups was confirmed by a clinician (in the case of queries about the SCID), corroborated by scores of current affective state , unipolar depression (n=26), or anxiety disorders (n=25), and 26 non‐clinical controls, aged 18–65 years.2.22.2.1Clinical characteristics were assessed using the SCID for DSM‐IV Axis I disorders, including main diagnosis and lifetime and current comorbid disorders, as above. Current medication was recorded. Depressive, (hypo)manic, and anxiety symptoms were assessed using the HAM‐D, the Young Mania Rating Scale,2.2.2The National Adult Reading Test2.2.3If I am looking for new furniture in a store, I always visualize what the furniture would look like in particular places in my home.). Each item is rated on a five‐point scale, with total scores ranging from 12 to 60. Higher scores indicate more use of mental imagery in daily life. The SUIS has an internal consistency of α=0.98 and good convergent validity.not at all) to 9  scale.The spontaneous use of mental imagery in everyday life was assessed via the Spontaneous Use of Imagery Scale (SUIS)1=You go to a wedding where you know very few other guests. After the party, you reflect on how the other guests behaved.), and then rate each image's pleasantness from 1 (extremely unpleasant) to 9 (extremely pleasant) and vividness from 1  to 7 (extremely vivid). The AST‐D has good internal consistency (α=0.82).The Ambiguous Scenarios Test (AST‐D)Emotional mental imagery was assessed using a Picture Word Cue (PW) task,not at all) to 9 (extremely) how much they found themselves thinking in mental images, or in verbal thoughts, and how emotional they found the picture−word combination. Average tendency to use images and verbal thoughts and average emotionality of the picture−word combinations were computed.The PW task is a computer‐based task examining self‐reported spontaneous use of imagery in response to emotional information and emotional context. Participants were presented with 20 ambiguous/neutral pictures with negative word captions and instructed to “combine the picture with the word” . They then rated from 1  to 4 (extremely). The IFES has acceptable test−retest reliability (0.73) and a good internal consistency (α=0.87).On the IFES, participants were asked to identify three future events they had thought about/imagined over the past 7 days and state whether each was positive or negative. Participants then responded to 24 statements about prospective imagery in relation to the past week, on a scale from 0 .The MII is a semi‐structured interview, which assesses content and characteristics of mental images and verbal thoughts experienced when the participant has been most anxious, most low and most high in mood. Participants are first asked to describe their most significant mental image anchored to each affect state and rate characteristics of the image such as valence, general emotionality of the image and intensity of one specific associated emotion per each affect state . They are then asked to rate overall characteristics of mental imagery and verbal thoughts for each affect state  such as frequency, realness, and compellingness. All ratings use nine‐point Likert scales, with higher ratings indicating more frequent, real (etc.) imagery or thoughts.2.2.4The following tasks were administered to assess the four cognitive stages of mental imagery.Image Generation Task (IGT)The The ability to maintain mental images in mind was assessed using two visual working memory tasks. The Short Term Memory (STM) task The The Letter Corner Classification (LCC) taskTwo tasks measuring the ability to manipulate mental images were administered. A computerized version of the classic Mental Rotation Task (MRT)The Creative Mental Synthesis (CMS) task2.2.5First, we tested (i) if participants with BD had imagery abnormalities by comparing the BD group (euthymic and depressed combined) to non‐clinical control participants on measures of cognitive and subjective domains of mental imagery. To test for between‐group differences on these aspects of imagery abnormalities, 55 statistical tests were performed. A BD group combining euthymic and depressed individuals was used to test replication of previous data.t tests if the residuals obtained using these t tests achieved normality with P‐values above .05 using both the Kolmogorov–Smirnov and Shapiro–Wilk tests. Where the group variances were found to differ using Levene's test, Satterthwaite's correction was applied to the degrees of freedom of the t test. Where the residuals of a pairwise comparison on an untransformed response did not achieve normality, log, square root and reciprocal transformations were applied and normality of the residuals reassessed. Where transformations failed to achieve normal residuals, Mann–Whitney U tests were used to analyze group differences. For the CMS task, Fisher's exact test was used to identify group differences in the number of CMS trials that were judged as recognizable, creative, having good correspondence, having a correct pattern and having a present pattern.Pairwise differences between variables in the different groups as outlined in our aims were analyzed using unpaired Limitations section).To explore the specificity of differences in mental imagery between diagnostic groups further, we computed correlations between the mental imagery variables that showed significant group differences in the initial comparison  and clinical variables for depression (QIDS and HAM‐D), anxiety (BAI), hypomanic experiences (MDQ), mood instability (ALS), and overall functioning (FAST). Pearson's correlations were used, or Kendall's tau, where inspection of scatterplots did not suggest a linear relationship (96 correlations computed). The unique contribution of these clinical variables in predicting scores on the mental imagery measures across groups was explored by conducting a series of multiple regression analyses with each of the mental imagery measures as the dependent variable (16 regression models) and with all clinical variables entered as predictor variables simultaneously. Non‐significant predictors were then removed from the model stepwise until only significant predictors remained. Mania measures were not included in this analysis as all participants presented with levels of manic symptoms below clinical significance =2.58, P=.012, d=0.62. The two groups did not differ in their performance on the digit span task: digit span forward P=.94; digit span backwards P=.72. There were no differences in any of the general cognitive functioning measures between the BD depressed group and the unipolar depression group  or between the BD depressed group and the anxiety disorders group .Participants with BD (combined group) had a lower total score on the verbal fluency task  compared to non‐clinical controls ; 3.3Scores on assessments of cognitive  stages and subjective domains of mental imagery of participants with BD and non‐clinical controls, and results of between‐group comparisons are summarized in Tables 3.3.1All results related to the subjective domain of mental imagery are detailed in Table Participants with BD did not significantly differ from non‐clinical controls in their imagery interpretation bias as assessed by pleasantness or vividness ratings on the AST‐D. Non‐clinical control participants reported a higher number of benign homographs which was marginally significant compared to those with BD. The two groups did not significantly differ in other interpretation bias ratings from the HIT.On measures of emotional mental imagery, participants with BD scored higher on the PW self‐involvement scale compared to non‐clinical control participants. The two groups did not differ in any of the other PW task scales. Participants with BD reported a stronger impact of emotional prospective imagery on the IFES compared to non‐clinical controls. They also reported higher ratings of vividness and sense of experiencing for negative future images, and lower ratings of likelihood for positive future scenarios on the PIT. The two groups did not significantly differ on the remaining PIT scales.low, participants with BD rated their most significant mental image as more negative and more demotivating compared to non‐clinical controls. For the time when their mood was most anxious, participants with BD rated their most significant mental image as more negative, threatening and emotional compared to non‐clinical controls. They also rated overall thinking in mental images to be more frequent and more “real” compared to non‐clinical controls. For the time when their mood was most high, participants with BD rated their most significant image as more exciting compared to non‐clinical controls. They also rated overall mental imagery as more “real” compared to non‐clinical controls. Full results are reported in Table All results on the MII are detailed in Table 3.3.2All results related to the cognitive  stages of mental imagery are detailed in Table Of the two imagery maintenance tasks, participants with BD had a higher recall rate on the visual STM task compared to those in the non‐clinical control group, indicating that participants with BD in this study had a greater likelihood of remembering visual target cues in a non‐emotional visual short‐term memory task. The groups did not differ significantly in memory precision. Instead, on the VPT task participants with BD did not significantly differ in accuracy scores from non‐clinical controls, suggesting that participants with BD in this study had no abnormalities in visual short‐term memory as assessed with the VPT.Participants with BD did not significantly differ from non‐clinical controls in their accuracy or completion time on the LCC, indicating that participants with BD in this study had no dysfunctions in imagery inspection.F=3.70, P=.058], indicating that the higher error rate of patients with BD on the MRT might be in part explained by deficits in general cognitive functioning.On imagery manipulation tasks, participants with BD did not significantly differ from non‐clinical controls on any indices of mental rotation speed, but on average had a higher error percentage compared to those in the non‐clinical control group. As, compared to non‐clinical controls, the BD group performed worse on the verbal fluency test, a task of executive function considered to be an indirect measure of general cognitive functioning, we tested if this could account for the higher error percentage on the MRT. The verbal fluency test total score was entered as a covariate in an ANCOVA testing group differences between participants with BD and non‐clinical controls in the error percentage of the MRT. After adding verbal fluency as a covariate, the main effect of group became marginally non‐significant .Across all groups, higher levels of hypomanic experiences (measured by the MDQ scores) were associated with worse performance on imagery maintenance as measured by a higher recall rate on the STM task .Across all groups, higher levels of affective lability (measured by scores on the ALS) were associated with better performance on 3.5.2t(114)=2.068, P=.041], and on how exciting the most significant image was at times of elated mood .Across all groups, higher levels of hypomanic experiences (measured by the MDQ scores) were associated with higher ratings on how threatening the most significant image was at times of anxious affect on the MII . Higher affective lability levels were also associated with higher ratings on the MII of how negative the most significant image was at times of low mood , and how frequently participants were thinking in mental images at times of anxious affect  On the PW task, higher affective lability was associated with higher ratings of how self‐involved participants felt when generating picture−word combinations .Across all groups, higher affective lability scores (measured on the ALS) were associated with greater impact of emotional prospective imagery scores on the IFES ; higher vividness ratings of negative events on the PIT , and a stronger sense of experiencing imagined negative events on the PIT .Across all groups, higher anxiety scores (measured on the BAI) were associated with greater impact of emotional prospective imagery scores on the IFES . Higher depression scores instead were significantly associated with ratings of how demotivating the most significant image was at times of low mood .Across all groups, lower depression scores (measured on the QIDS) were associated with higher likelihood ratings of positive imagined events to happen on the PIT ; and with how real mental images were rated at times of anxious affect on the MII .Across all groups, lower general functioning (measured using the FAST scores) was associated with greater impact of emotional prospective imagery scores on the IFES .Clinical and functioning variables across all groups were not related to how real mental images were rated at times of high mood [44.1across diagnostic groups. Results show that, compared to non‐clinical controls, individuals with BD show largely intact performance on experimental tasks measuring the cognitive  stages of mental imagery. However, in the subjective domains of mental imagery, compared to non‐clinical controls, individuals with BD do show some abnormalities in emotional mental imagery: namely, a greater impact of intrusive prospective imagery in daily life, more vivid and “real” negative images on a prospective imagery task, and higher levels of self‐involvement in imagery on a picture−word task. Moreover, on a phenomenological interview about times of intense affect , it was characteristics of mental imagery, but not of verbal thoughts, that distinguished individuals with BD from non‐clinical controls. Results further indicate that, when compared to clinical control groups matched for depression and anxiety, abnormalities in emotional mental imagery were not specific to BD but associated with increasing psychopathology.Our study investigated, first, whether BD is associated with abnormalities in mental imagery compared to non‐clinical controls; second, whether any such abnormalities are specific to BD when compared to clinical control groups matched for depression and anxiety. Further, we explored whether abnormalities in mental imagery are associated with clinical variables transdiagnostic feature of psychopathology, and associated in particular with affective lability across clinical and non‐clinical populations. This finding is particularly interesting given that affect lability (including concurrent anxiety) represents a particularly challenging feature across different mental disorders.Interestingly, our results show that, across all clinical and non‐clinical groups, mental imagery abnormalities are associated with severity of depression and anxiety, as well as with BD phenotype and affective lability traits, and general functioning. This raises the possibility that the subjective experience of highly emotional mental imagery (assessed by a range of measures across different affect states) is a 4.2We replicated previous findings that individuals with BD (euthymic and depressed combined) experience a greater impact of intrusive prospective mental imagery in everyday life,Unlike previous studies, we did not find evidence of greater spontaneous use of non‐emotional mental imagery in BD compared to non‐clinical controls, although mean values were in the same direction as in a previous study.Overall our BD sample reported imagery abnormalities particularly for prospective imagery and during anxious affect. This is consistent with the relationship between anxiety and future thinking.4.3Finally, and novel to the literature  stages of mental imagery, previous studies have reported biases in imagery generation and manipulation in unipolar depressed individuals compared to controlsOverall, our study indicates that mental imagery characteristics representing features of greater emotionality and intensity  may represent a marker for general emotional psychopathology, and general functioning. This supports our idea that “bringing back the mind's eye” to psychiatric assessmentsOur results on the association between BD phenotype and affective lability traits, and greater imagery frequency and emotionality, are in keeping with previous findings that individuals with a BD phenotype are more susceptible to intrusive imagery and to spontaneous use of imagery.5A limitation of our study is the absence of statistical correction for multiple comparisons. Moreover, we did not include a (hypo)manic BD group that would allow us to establish the presence of mental imagery abnormalities associated with mania state diagnosis. With regard to results from the MII, it should also be noted that these were based on retrospective accounts of times of intense affect and could have been subject to recall/memory biases. Future qualitative studies are needed to analyze in detail potential differences in the image contents exemplified in Table In conclusion, this first comprehensive investigation of a range of mental imagery measures in BD compared to both non‐clinical and clinical controls confirms that imagery abnormalities are present in patients with BD in the emotional aspects of mental imagery, while the cognitive processes underpinning mental imagery experience remain largely intact. Biases in emotional mental imagery appear as a transdiagnostic feature of our clinical groups matched on depression and anxiety levels related to clinical dysfunction. We suggest that imagery abnormalities are a transdiagnostic processes driving affective lability, and that imagery can be targeted via novel psychological treatment techniques. Imagery‐focused techniques hold promise across psychiatric disorders,The authors of this paper do not have any commercial associations that might pose a conflict of interest in connection with this manuscript. Click here for additional data file.


Methods such as electron microscopy and electrophysiology led to the understanding that gap junctions were dense arrays of channels connecting the intracellular environments within almost all animal tissues. The characteristics of gap junctions were remarkably similar in preparations from phylogenetically diverse animals such as cnidarians and chordates. Although few studies directly compared them, minor differences were noted between gap junctions of vertebrates and invertebrates. For instance, a slightly wider gap was noted between cells of invertebrates and the spacing between invertebrate channels was generally greater. Connexins were identified as the structural component of vertebrate junctions in the 1980s and innexins as the structural component of pre‐chordate junctions in the 1990s. Despite a lack of similarity in gene sequence, connexins and innexins are remarkably similar. Innexins and connexins have the same membrane topology and form intercellular channels that play a variety of tissue‐ and temporally specific roles. Both protein types oligomerize to form large aqueous channels that allow the passage of ions and small metabolites and are regulated by factors such as pH, calcium, and voltage. Much more is currently known about the structure, function, and structure–function relationships of connexins. However, the innexin field is expanding. Greater knowledge of innexin channels will permit more detailed comparisons with their connexin‐based counterparts, and provide insight into the ubiquitous yet specific roles of gap junctions. © 2016 Wiley Periodicals, Inc. Develop Neurobiol 77: 522–547, 2017 Gap junctions are dense arrays of hundreds or thousands of intercellular channels in regions where cell membranes are closely apposed. The earliest structural studies of gap junctions involved thin section electron microscopy (EM). In most cases thin sections were studied after tissues were treated with an electron‐opaque material involving lanthanum hydroxide or ruthenium red, which permeates the gap between cells providing contrast at regions of close apposition  and an extracellular face (e/face). Vertebrate gap junctions yield a particle‐embedded p/face containing the polygonal lattice of subunits and an e/face with the complementary set of pits or depressions Gilula, . Some ofIn almost all preparations, gap junctions include hundreds or thousands of channels that appear as tightly packed recessions or pits Flower, . In cleaWhen combined with more recent studies involving methods such as cryo‐EM  and worms (Caenorhabditis elegans) were identified with phenotypes resulting from abnormal intercellular communication   and Shaking‐B were definitively correlated with gap junctions   compared to a cutoff in the range of 16–20 A° for mammalian gap junctions .There are differences in the size exclusion limits of vertebrate and invertebrate gap junctions. For instance Schwarzmann et al.  conducteThe structural differences observed between vertebrate and invertebrate junctions had functional consequences in terms of communication specificity. Epstein and Gilula  demonstrSome of the most notable early functional assays included the following observationsThese and other studies are described below with references and reviews listed in Table 2.in vivo or in cell culture  or arachidonic acid and using biophysical analyses noted that the mechanism of inhibition was related to modification of a Vm ‐sensitive gate within the gap junction channel.A wide range of pharmaceutical agents are known to modulate gap junction intercellular communication  mediating transport across the plasma membrane of cells Fig. . For insXenopus oocytes. It was shown that the Vm‐sensitive channel gate functions independently of the Vj‐gate and that each hemichannel in a gap junction contains an independent Vm‐gate. As well as characterizing the relationship between Vj‐ and Vm‐dependent gating, the study provided evidence that voltage gating properties diverged during vertebrate evolution  and regulation by transjuntional voltage (Vj). Vm‐sensitivity indicates that junctional conductance is dependent on the membrane potential of the coupled cells. This phenomenon appears to be common for connexin‐ and innexin‐based junctions . All connexins and innexins identified so far exhibit sensitivity to Vj although in many cases the response is minor and/or not likely to have physiological significance. Each gap junction protein (connexin or innexin) appears to impart a unique time‐ and voltage‐dependent response to Vj  allowing many potential interactions. Interactions between gap junction proteins commonly result in heteromeric and/or heterotypic gap junction channels Fig. . HeteromDrosophila  assuming hexagonal packing was estimated to be 111 Å for INX‐6 channels compared to 94 Å and 77 Å for Cx26 and Cx43‐GFP, respectively. Oshima et al. (2013) noted that while INX‐6 channels appeared to be arranged in a hexagonal lattice, care should be taken in assigning an oligomeric number to innexin channels.Only two studies have specifically targeted the structure of innexin‐based channels. These both relate to junctions composed of The structure of INX‐6 channels was later resolved at about 10 Å resolution using cryo‐electron microscopy. The amino terminus was truncated and the proteins were expressed, purified and crystalized. As predicted the pore was found to be wider than that of connexin‐based channels and the gap junction channel itself was both wider and longer , Shaking‐B, and Shaking‐B. Shaking‐B does not readily form functional channels on its own  with the goal of identifying the role of this domain in voltage gating and junctional rectification . This mutant failed to form functional homotypic channels , while amenable to crystallization, also fail to function in dye‐transfer assays  is required for innexin function . The NT replacement resulted in rectifying junctions with properties similar to those of ShakBL/ShakBN16 junctions  did not induce the predicted response in heterotypic pairing with ShakBL The NT of ShakBL failed to confer properties of voltage‐gating and rectification to ShakBN16 channels. These observations ruled out the possibility that the NT of ShakB innexins mediates Vj gating independently . Altered sensitivity to transmembrane voltage (Vm‐sensitivity) was also apparent after one mutation in TM1 of ShakBL but is not discussed further because it is not a phenotype commonly noted in studies of connexins.The tryptophan scanning analyses described above provide compelling evidence for structural differences between connexins and innexins, but interestingly, also identified interesting similarities in terms of mutant phenotypes  form a short parahelix   in Cx32 and Cx26  of connexins is more tightly packed than in innexins, however, mutations within TM1 can produce similar effects on function. For instance mutations within TM1 of both connexins and innexins can produce channels that are closed, but open in response to transjunctional voltage, a phenomenon thought to be related to partial collapse of the channel via disruption of interactions between helices. In addition, point mutations at some locations within the transmembrane domains of both connexins and innexins can induce calcium‐sensitive leak currents across the plasma membrane. These similarities are particularly interesting in light of the uncertain evolutionary origins of innexins and connexins.Given their nonhomologous genetic origins, innexins and connexins are remarkably similar. They have the same membrane topology. They oligomerize around a central pore to form a channel permeable to small molecules and ions. Innexins and connexins are the only known proteins to form intercellular channels, a feat that requires complex recognition and docking interactions to produce a tightly sealed channel spanning the extracellular space. While the molecular interactions underlying these process are poorly understood, it is interesting to note that connexins contain three conserved cysteines in each extracellular loop while innexins contain two. The intercellular channels produced by different members of the innexin and connexin families have unique properties, attesting to the need for specialized transport between cells of different tissues and organs in diverse animal phyla. There is also evidence that both connexins and innexins may, under some circumstances, expand their function from building intercellular channels to function as transmembrane  pores. Innexins appear to form larger channels involving more subunits (16 innexins per gap junction channel versus 12 connexins), however, the topoogy of each subunit is similar in innexins and connexins. Four transmembrane domains anchor the protein in the membrane, extracellular loops are involved in docking and cytoplasmic domains contribute to regulation by factors such as protons, phosphorylation, and voltage. Both connexins and innexins display Vj‐dependent gating and selective formation of heterotypic channels, two properties related to the interesting phenomenon of voltage‐dependent rectification. For instance heterotypic channels formed by Cx26 and Cx32 rectify as do junctions resulting from heterotypic pairing of


Fish dietary burden calculation is therefore an important prerequisite to decide on further experimental testing as part of the consumer risk assessment. In this review, the different aquaculture production systems are compared with regard to their specific feeding practices and the principles of dietary burden calculation are described. © 2016 Fraunhofer‐Institut für Molekularbiologie und Angewandte Oekologie. Journal of the Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.Fish farming is increasingly dependent on plant commodities as a source of feed leading to an increased risk for pesticide residues in aquaculture diets and consequently their transfer into aquaculture food products. The European pesticide regulation requires fish metabolism and fish feeding studies where residues in fish feed exceed 0.1 mg kg Global aquaculture underwent a steady increase within the last three decades with an average annual production rise of 8.8%.In extensive aquaculture, the cultured fish species are mainly from lower trophic levels and feed solely on natural food resources  without substantial external inputs. In semi‐intensive aquaculture, the cultured fish species (mostly omnivorous species) are grown on a combination of natural food resources supplemented by external feeds. The quantity and quality of external feed resources are chosen to supplement the diet of fish with nutrients, which are lacking in the natural food resources.Particularly in the feeding of carnivorous species in intensive aquaculture, fish meal and fish oil are the traditional source of animal protein and fatty acids, especially omega‐3 fatty acids. Both fish meal and fish oil are mainly produced from pelagic forage/trash fish, but the amount of these fish landed worldwide fell from 30 million tons in 1994 to about 15 million tons in 2010 with large annual fluctuations in production caused by climatic circumstances, such as El Niño.In extensive aquaculture systems there is no transfer of pesticide residues from feed into cultured organisms due to the absence of supplementary feeding. However, the direct treatment of water bodies or spray‐drift/run‐off/drainage after treatment along water bodies may result in fish exposure. Fish are very efficient in bioconcentrating dissolved chemicals from the surrounding medium via the gills which may lead to significant residues in fish tissues especially of lipophilic substances. However, the potential of pesticides to bioaccumulate in fish is evaluated as part of the environmental risk assessment, which is not within the scope of this publication.Under semi‐intensive aquaculture conditions, mainly plant‐based supplemental feeds are used to supply dietary energy to the fish. These feed commodities are often of lower nutritional quality and are processed little. They range from cereals in the traditional semi‐intensive pond carp culture in Central–Eastern Europe to farm by‐products (e.g. bran) and leaves/grasses from agricultural fields in the traditional Asian poly‐carp culture.In intensive aquaculture the fish are fed by aquafeeds which are formulated to fulfil the nutritional requirements of a particular species at its specific life stage. The feed industry uses a range of feed ingredients, which are combined according to their nutritional quality (nutrient content and digestibility) and market price in order to produce cost optimised aquafeeds with a standardised quality. The feed ingredients range from marine protein sources , processed animal protein sources , plant protein sources , starch sources from cereals, pulses and legumes  to oils and fats .−1 body weight day−1 (and being largely comparable to the formerly used trigger of 0.1 mg kg−1 feed). Livestock metabolism studies according to OECD Test Guideline 503 are established for poultry, ruminants, and pigs and are carried out to determine the qualitative and quantitative metabolism and/or degradation of the pesticide when contained in feedstuffs.Kow = 3) and the dietary burden is likely to be higher than 0.1 mg kg−1 feed dry matter (DM).Oncorhynchus mykiss) or common carp (Cyprinus carpio), which are both important aquaculture species reared for human consumption, are the recommended test species in the working document. Pilot trials with both species to study the metabolism of pesticides in farmed fish were carried out by Schlechtriem et al.−1 fresh matter may be reasonably expected in edible tissues. Feeding studies are required to determine the magnitude of residues in products of fish origin in order to assess possible consumer risks arising from ingestion of these products and to establish MRLs for edible fish commodities which still need to be defined. An official test protocol for feeding studies is currently only available for terrestrial livestock species such as poultry, ruminants and pigs.The Regulation (EU) No 283/2013−1 feed DM do not result in measurable residues in fish commodities, while this cannot be ruled out in cases of higher residues in feed. It is therefore important to calculate the level of residues in fish feed which might be reasonably expected from the approved uses of the pesticide in question. The calculation follows a conservative approach in assuming that all fish feedstuffs which could have been treated with the pesticide have in fact been treated at the maximum admissible rate. The anticipated dietary burden of a pesticide is calculated based on a ‘maximum reasonably balanced diet (MRBD)’ approach for intensive feeding practices or according to the ‘reasonably worst case diet/feed (RWCF)’ approach for semi‐intensive diets.It is anticipated that residues in fish feed which are lower than 0.1 mg kgSeveral agricultural commodities such as forage/fodder and root and tubers, are of only limited value as ingredients for aquaculture feeds. Feed commodities can be classified as carbohydrate concentrates (CC with protein contents <30%), protein concentrates (PC with protein contents >30%), and fat (F). As described above, fish in intensive aquaculture are commonly fed based on a MRBD approach using fixed dietary levels of protein and fat. The target composition of formulated feed for rainbow trout in grow‐out culture should consist of around 42% crude protein and 15% crude fat (% of DM).−1 DM) for each feedstuff ,Recommended maximum inclusion rates are provided for the various plant commodities which should not be exceeded in rainbow trout and common carp diets to avoid adverse effects on growth performance and health condition.−1 DM) are listed for each feedstuff. Second, those protein concentrates (PC) and carbohydrate concentrates (CC) with the highest STMR and STMR‐P values are chosen to formulate the MRBD containing the target protein concentration of 42% or 35% of DM for rainbow trout and common carp, respectively. If the target CC or PC concentration cannot be achieved with one commodity, a further ingredient from the same group (PC or CC) is additionally considered which provides the second‐highest contribution to the overall residue and the formulation is then recalculated. Finally, the fat content of the formulated diet containing PC and CC commodities is calculated based on the lipid content of the individual ingredients. If required, the fat content of the diet is adjusted by further addition of plant derived oil (again chosen according to the highest median residue) to reach the target dietary lipid content of 15% or 10% of DM for rainbow trout and common carp, respectively. In return, PC and CC need to be aligned to maintain the target protein concentration.First, all feedstuffs potentially treated with the pesticide are selected and the specific STMR and STMR‐P values . This is not always an easy task, since the same pesticidal active substance might be contained in a variety of plant protection products with a variety of uses and information on these uses is sometimes limited. In the EU the most complete picture of feed‐relevant uses is normally obtained in the framework of evaluations of MRLs according to Art. 12 of Regulation (EC) No 396/2005.Dietary burden calculation as outlined by the EU working documentDietaryBurdenCalculator follows a realistic dietary optimisation scenario and allows the determination of the worst case feed composition made of plant derived feedstuffs leading to the maximum dietary burden of pesticide residues.Due to the increased amount of plant‐derived materials in aquaculture diets, fish might increasingly become exposed to pesticide residues through their diets. Reasonable worst case estimates of the fish dietary burden are therefore important to decide on further testing such as fish metabolism or feeding studies, which might be required to enable a reasonable consumer risk assessment and the setting of appropriate MRLs in fish commodities. A reasonably worst case diet can be obtained based on a MRBD approach for intensive feeding practices. The software


TSP‐1), a matricellular protein and one of the first endogenous anti‐angiogenic molecules identified, has long been considered a potent modulator of human diseases. While the therapeutic effect of TSP‐1 to suppress cancer was investigated in both research and clinical settings, the mechanisms of how TSP‐1 is regulated in cancer remain elusive, and the scientific answers to the question of whether TSP‐1 expressions can be utilized as diagnostic or prognostic marker for patients with cancer are largely inconsistent. Moreover, TSP‐1 plays crucial functions in angiogenesis, inflammation and tissue remodelling, which are essential biological processes in the progression of many cardiovascular diseases, and therefore, its dysregulated expressions in such conditions may have therapeutic significance. Herein, we critically analysed the literature pertaining to TSP‐1 expression in circulating blood and pathological tissues in various types of cancer as well as cardiovascular and inflammation‐related diseases in humans. We compare the secretion rates of TSP‐1 by different cancer and non‐cancer cells and discuss the potential connection between the expression changes of TSP‐1 and vascular endothelial growth factor (VEGF) observed in patients with cancer. Moreover, the pattern and emerging significance of TSP‐1 profiles in cardiovascular disease, such as peripheral arterial disease, diabetes and other related non‐cancer disorders, are highlighted. The analysis of published TSP‐1 data presented in this review may have implications for the future exploration of novel TSP‐1‐based treatment strategies for cancer and cardiovascular‐related diseases.Thrombospondin‐1 ( Thrombospondin‐1 (TSP‐1), a matricellular protein, is often induced at sites of injury and tissue remodelling, and it is secreted by circulating, stromal and parenchymal cells at very different quantities.The major cell‐surface receptors for TSP‐1, namely CD36, CD47 and integrins, participate in important cellular processes including apoptosis, angiogenesis, blood flow, phagocytosis, migration and immune regulation.TSP‐1 is known to inhibit angiogenesis and endothelial cell survival.Cancer patient data on TSP‐1 in blood and cancerous tissues suggest that the patterns of TSP‐1 expression compared to non‐cancer controls are highly heterogeneous across different cancer types and that the correlations between TSP‐1 levels in patients and survival are also cancer type‐specific.Human TSP‐1 protein expression in circulating blood is uniformly up‐regulated in a variety of cardiovascular and inflammatory diseases and is often associated with worse patient outcomes.1Complex multicellular organisms require surface adhesion and a three‐dimensional support system. The extracellular matrix provides these necessary biomechanical structural elements.A quintessential and founding member of this group is thrombospondin‐1 (TSP‐1), a protein first identified in the particulate fraction of thrombin‐activated plateletsRenewed appreciation of TSP‐1 in the pathophysiology of diseases has encouraged research into the expression of this protein in different cells and body compartments. However, a systematic characterization and quantification of published TSP‐1 expression data in diseases, both amount and rate of production, has not been previously approached. Such an analysis is important, and it can provide insight into the sometimes conflicting activity of this molecule and serve to guide therapeutic interventions that target pathways mediated by TSP‐1; it is also important for systems biology computational studies of TSP‐1.2Thrombospondin‐1 is reported to be expressed and secreted by a variety of normal cell types in human including ECs, fibroblasts, muscle cells, immune cells, platelets (and megakaryocytes) as well as transformed parenchymal cells in many types of cancer  and peripheral arterial disease (PAD). One hypothesis offered to explain the pathophysiology of CAD and PAD is that anti‐angiogenic factors (eg TSP‐1) may be highly up‐regulated in the ischaemic tissue, in addition to the insufficient induction of pro‐angiogenic factors .3.3Paired data on quantitative TSP‐1 and VEGF protein expressions in cancers and PAD are shown in Table 4Herein, we systematically reviewed the literature characterizing human TSP‐1 expressions in the circulation and in tissues, its cell type‐specific secretion and its significance and correlations with outcomes in human diseases. This analysis is driven by quantitative data and demonstrated some interesting findings. In cancer, TSP‐1 expression patterns in general are quite variable and, thus, appear to have limited prognostic or diagnostic value, although in specific cancer types (eg breast cancer), TSP‐1 up‐regulation is relatively consistent across independent datasets and is associated with malignancy and metastasis. In addition, a similar paradox in expression patterns pertains to TSP‐1 and VEGF in general cancer conditions. Contrary to the situation in cancer, TSP‐1 expression is uniformly up‐regulated in cardiovascular and inflammatory diseases and is associated with worse outcomes, albeit the studies testing the latter hypothesis are of limited number. Interpretation of these results should be tempered as expression data may not distinguish between changes in TSP‐1 production/secretion and uptake/degradation/cleavage. Although TSP‐1 in blood could likely have an effect on circulating inflammatory cells, red blood cells and platelets to increase inflammation, adhesion and aggregation, since TSP‐1 binds to various components in the extracellular matrix, its up‐ and down‐regulations as measured in circulating blood may not reflect the actual changes of TSP‐1 abundance and its functional activities in the matrix. A further limitation is that very few quantitative data on tissue TSP‐1 in diseases are available in the literature, and it should be pointed out that the protein expression levels may not correlate with activation of downstream signalling. Finally, being obtained from human subjects, the majority of these expression data lack time course analysis that could contribute to a better understanding of the changes noted. These caveats aside, the literature data collected and presented in our quantitative analysis remain the first of their kind and should serve to guide future basic and translational research.−1 range.Specific domains of TSP‐1 interact with different proteins and non‐protein molecules in the extracellular matrix, and the affinity Kd values of these interactions are mostly in the nmol LBesides diseases, many natural biological processes can also contribute to the endogenous regulation of TSP‐1. Preclinical studies in mice have demonstrated age‐associated up‐regulation of TSP‐1 in kidney,165b have emerged as new promising targets in ischaemic vascular diseases (eg PAD).The inconsistent pattern of TSP‐1 expression observed in different types of cancer is reflected in the equally controversial role of tumour TSP‐1 expression as a survival predictor. In accordance to its anti‐angiogenic property, high tumour expression of TSP‐1 is correlated with increased patient survival in colon,J.S.I. serves as Chair of the Scientific Advisory Board of Radiation Control Technologies, Inc.  and has equity interest in RCTI and Tioma Therapeutics  that licensed CD47 technology for development. The other authors have declared that no competing interests exist.


ECS) is an endogenous signalling pathway involved in the control of several gastrointestinal (GI) functions at both peripheral and central levels. In recent years, it has become apparent that the ECS is pivotal in the regulation of GI motility, secretion and sensitivity, but endocannabinoids (ECs) are also involved in the regulation of intestinal inflammation and mucosal barrier permeability, suggesting their role in the pathophysiology of both functional and organic GI disorders. Genetic studies in patients with irritable bowel syndrome (IBS) or inflammatory bowel disease have indeed shown significant associations with polymorphisms or mutation in genes encoding for cannabinoid receptor or enzyme responsible for their catabolism, respectively. Furthermore, ongoing clinical trials are testing EC agonists/antagonists in the achievement of symptomatic relief from a number of GI symptoms. Despite this evidence, there is a lack of supportive RCTs and relevant data in human beings, and hence, the possible therapeutic application of these compounds is raising ethical, political and economic concerns. More recently, the identification of several EC‐like compounds able to modulate ECS function without the typical central side effects of cannabino‐mimetics has paved the way for emerging peripherally acting drugs. This review summarizes the possible mechanisms linking the ECS to GI disorders and describes the most recent advances in the manipulation of the ECS in the treatment of GI diseases.The endocannabinoid system ( Cannabis sativa plant is the most commonly used illicit drug for recreational purposes worldwide, with estimated 16 million users in the United States N‐arachidonoylethanolamine  and 2‐arachidonoylglycerol (2‐AG), their best‐characterized endogenous ligands N‐arachidonoyl‐dopamine (NADA) and O‐arachidonoylethanolamine (virodhamine) N‐linoleylethanolamine (LEA), N‐oleoylethanolamine (OEA), N‐palmitoylethanolamine (PEA) and N‐stearoylethanolamine (SEA)] are structurally related to classical ECs and have been shown to act synergistically, either enhancing the effects of prototypic ECs  or displaying unique effects (seethe ‘Endocannabinoid‐related compounds’ section). An overview of the principal ECs and of the enzymes responsible for their metabolism is proposed in Figure In vitro studies showed that AEA, noladin and virodhamine are receptor agonists to PPARα, while 2‐AG binds to PPARβ/δ in vivo.N‐acylethanolamides (NAEs), have a close structural resemblance with classical ECs, but display no activity on CB receptors via the ‘entourage effect’ by either competing with stereotypical ECs for enzymatic degradation or increasing their receptor binding affinity EC‐like compounds, such as via the activation of presynaptic CB1 In both animal and human GI tract, the ECs exert marked antipropulsive effects. This result is mainly mediated by the reduction in the release of acetylcholine et al. have shown that after colorectal distension, orally administered probiotics were able to reduce visceral sensation in rats in a CB2‐dependent fashion Undoubtedly, the most documented effect of the ECS is the control of visceral sensitivity and, although empirically grounded, phytocannabinoid‐based treatments have been used for centuries in a number of conditions featured by chronic pain. In recent years, several studies have elucidated the molecular mechanism by which ECs are able to reduce visceral sensation and pain. The reduction in visceral sensitivity threshold to colorectal distension was found to be dependent on both CB1 activation and CB2 activation ex vivo studies have demonstrated a significantly increased expression of CB and EC levels in chronic inflammatory conditions, including IBDs, diverticulitis and coeliac disease Over the past decade, many lines of evidence highlighting the role of the ECS in intestinal inflammation have been produced in both animal and pre‐clinical models The homoeostatic role of ECS, able to regulate GI functions peripherally and centrally, represents both a blessing and a curse, making it an appealing therapeutic target and, at the same time, a challenge in selectively modulating GI functions without altering the functionality of other organs. We will now discuss in detail the evidence produced on the role of the ECS in GI disorders, namely functional dyspepsia (FD) and irritable bowel syndrome (IBS), two of the main functional gastrointestinal disorders (FGIDs), IBDs and non‐alcoholic fatty liver disease (NAFLD). We will also review the most recent advances in the possible therapeutic exploitation of manipulating ECS in the treatment of these GI disorders.et al. have demonstrated a sustained increase in CB1 receptor availability in cerebral regions involved in the control of food intake and visceral sensitivity, suggesting for the first time a long‐term dysfunction in ECS signalling pathways in FD Although only few studies have investigated the potential effects of ECS in FD, there is evidence suggesting that the ECS might be an intriguing target in FD treatment, as it is involved in the modulation of some of the proposed mechanisms underlying FD pathophysiology et al. have tested the efficacy of dronabinol in visceral sensitivity in a randomized, double‐blind, placebo‐controlled trial showing its ability to increase colonic compliance and relaxation in vivoAlthough the pathophysiology of IBS is still not completely understood, gut motility impairment, visceral hyperalgesia, low‐grade inflammation and gut–brain axis alterations have all been associated with symptoms onset in vitro studies showed that AEA and other CB1 agonists promote wound closure in human colonic epithelium and hence might improve mucosal healing in patients with IBD in vitro experiments showed that anandamide and 2‐AG increased intestinal permeability when apically administered on Caco‐2 cells, and an in vivo study in obese mice, a model of leaky gut, showed that the CB1 antagonist rimonabant was able to reduce plasmatic LPS level, confirming the role of ECs in regulating gut permeability The lines of evidence showing the involvement of ECs in the regulation of inflammatory and immune response in the digestive tract inevitably promoted research on the role of ECs in IBD. The first evidence came from CB1 and CB2 knockout mice that showed a higher susceptibility to chemically induced colitis, suggesting that ECs play a key protective role against chronic inflammation via CB1 activation, have been associated with cirrhosis‐induced vasodilation, and increased levels of AEA have been found in peripheral blood of patients with cirrhosis via an increased TGF‐β production −/− knockout mice are more sensitive to acute liver injury, showing a low regenerative response via CB1 activation, specific CB2 agonists might slow liver fibrotic evolution.Liver plays a major role in human homoeostasis with numerous functions, including regulation of lipid and carbohydrate metabolism, plasma protein synthesis, hormone production and detoxification. The emerging role of ECs in homoeostasis and lipid metabolism led several authors to investigate the interactions between the ECS and liver functions in normal and pathological conditions. The cannabinoid receptors are widely distributed on both hepatocytes and cholangiocytes, as on Kupffer and stellate cells, and their expression is modified during liver injury The emblematic role of ECS in metabolic syndrome and obesity is already known; indeed, the CB1 antagonist rimonabant has been proposed in obesity treatment due to its beneficial effects on both bodyweight and lipid profile. However, the neuropsychiatric adverse effects have limited the clinical use of this compound. Non‐alcoholic fatty liver disease (NAFLD) and non‐alcoholic steatohepatitis (NASH) are strongly associated with metabolic syndrome, representing the ‘liver response’ to obesity, dyslipidaemia and altered carbohydrate metabolism. As ECs play a key role in liver lipid metabolism, a great interest is raised on effects of ECs on fatty liver diseases in vivo, convincing evidence suggests that pharmacological manipulation of this multifaceted system might provide new therapeutic options in treating GI diseases. The complexity and the redundancy of ECS make the manipulation of this complex system an appealing target for therapeutic purposes, although the possibility of central side effects strongly limited the current use of these compounds in clinical settings. Using peripherally acting drugs with no affinity on central cannabinoid receptors is an intriguing strategy, and as PEA formulations are already available for the treatment of chronic pain, further in vivo studies to test the clinical efficacy of these compounds are strongly warranted.In the last years, accumulating lines of evidence have pointed out the homoeostatic role of the ECS in regulating intestinal motility, sensitivity and inflammation. An impairment of ECS signalling has been suggested to play a key role in several gastrointestinal disorders, such as FGIDs, IBDs and liver diseases. Even if conflicting results have been produced The authors have no conflicting interests to declare.


Nanoparticulate drug/gene carriers have gained much attention in the past decades because of their versatile and tunable properties. However, efficacy of the therapeutic agents can be further enhanced using naturally occurring materials‐based nanoparticles. Polysaccharides are an emerging class of biopolymers; therefore, they are generally considered to be safe, non‐toxic, biocompatible and biodegradable. Considering that the target of nanoparticle‐based therapeutic strategies is localization of biomedical agents in subcellular compartments, a detailed understanding of the cellular mechanism involved in the uptake of polysaccharide‐based nanoparticles is essential for safe and efficient therapeutic applications. Uptake of the nanoparticles by the cellular systems occurs with a process known as endocytosis and is influenced by the physicochemical characteristics of nanoparticles such as size, shape and surface chemistry as well as the employed experimental conditions. In this study, we highlight the main endocytosis mechanisms responsible for the cellular uptake of polysaccharide nanoparticles containing drug/gene. One significant obstacle for the development of effective drug/gene therapies, particularly anticancer therapies, has been their inability to cross the plasma membranes of cells. Plasma membrane provides a boundary between the cell and its environment to maintain the activities that are critical for the normal functioning of different types of cells via adsorption or chemical conjugation to the surface Many polymeric nanoparticulate systems have been investigated to be appropriate for cell research and applications. Polymeric nanoparticles are ultrafine colloidal particles with the size range between 1–1000 nm and have different properties compared to their source materials, in which the therapeutic agents can be entrapped intra‐nanoparticles or can be incorporated Following incorporation into the body, nanocarriers can translocate from their site of deposition to the elsewhere, such as the brain and bone marrow, by blood circulation system Among natural polymers, proteins and polysaccharides tend to be associated with cells, rapidly internalized and degraded, thus enabling the intracellular release of the incorporated drug/gene from the transporter The plasma membrane is a highly selective and effective barrier that protects all living cells from the surrounding environment and strongly limits the entry and exit of large macromolecular substances via membrane penetration are directly transferred into the cytoplasm, which can be the preferred choice particularly for the targeted drug delivery It is well known that nanoparticulate systems are capable to enter live cells, often through the several endocytic pathways. However, passive penetration of the plasma membrane may occur as an alternative route. Upon endocytosis, nanomaterials are enclosed within the early endocytic vesicles and are thus not directly carried into the cytosol. In contrast, the nanomaterials internalized The term ‘endocytosis’ can be broadly divided into pinocytosis (cell drinking) and phagocytosis (cell eating). Pinocytosis is commonly involved in the internalization of fluids and molecules by small vesicles, and phagocytosis is the process by which the cells such as monocytes/macrophages, neutrophils and dendritic cells engulf large particulate matter and are able to form intracellular phagosomes via trancytosis ‐mediated pathway and macropinocytosis which are somewhat non‐specific, and neither acidic nor digestive and can preferentially internalize nanoparticles through an alternative pathway, preventing lysosomal degradation after internalization Macropinocytosis is a form of actin‐driven endocytic mechanism by which extracellular fluid and its debris are internalized in a non‐specific manner within large, heterogeneous vesicles, called macropinosomes in vitro quantitative assessment of cellular uptake, the nanoparticles could be labelled by fluorescent dyes or radioisotopes Notably, for The efficiency of endocytosis depends on not only the size of nanoparticles, but also the charge, and surface coating The size of nanoparticles is of high importance for the evaluation of the performance and biological fate, particularly for addressing the efficacy of cellular internalization mechanism Likewise, shape has been found to dictate the biodistribution, blood residence time as well as the cellular uptake of nanoparticles ‐charged nanoparticles. Generally, positively charged nanoparticles exhibit better internalization level , for freely passing through the cell membranes in a non‐toxic manner suggests that they can be used for improving the intracellular availability of various cargoes such as small molecules, plasmid DNA (pDNA) and nanoparticles. Therefore, CPPs attached to the nanoparticles have been reported as an appealing strategy to enhance drug/gene delivery to and across biological barriers when compared with the non‐modified CPPs‐based nanoparticles Effective delivery of drug‐loaded nanoparticles into specific cells and subcellular targets under different conditions is of high importance in the field of biomedicine. For example, the main challenge in the treatment methods of cancer is to translocate pharmaceutical agents into cancer tumours without damaging healthy tissues Beyond the physicochemical characteristics of nanoparticles, the composition of common cellular culture media and the origin of serum mediate the nanoparticles uptake and cellular distribution Polysaccharides have been extensively used in pharmaceutics for development of drug/gene delivery systems. Polysaccharide materials can be classified in two groups including polyelectrolytes and non‐polyelectrolytes. Polyelectrolytes can be additionally divided based on their intrinsic charge including cationic (chitosan), anionic  and neutral  Because of the amphiphilic nature, polysaccharide‐based materials can self‐assemble into ordered aggregates within aqueous environment and have various derivable groups on their molecular chains which can be easily adopted and modified with other chemical agents in vivo degradation in vitro study (Caco‐2 cell line) and also an ex vivo study (excised rat jejunum). The authors reported that the loading capacity increased with increasing particle size, while transport of nanoparticles through Caco‐2 cells and also the cellular uptake in excised rat jejunum reduced . Alginates can electrostatically interact with the positively charged entities as a result of their negative charge, so they can be successfully used as an platform for delivery of cationic drugs and molecules in vivo by enzymes such as lysozyme and chitosanase, into oligomers and finally to N‐glucosamine, which is endogenously present in the human body Chitosan (CS) is a naturally occurring linear polysaccharide composed primarily of repeating units of D‐glucosamine The most common method to prepare CS nanoparticles is ionic gelation. This method offers a simple and rapid preparation technique in the aqueous environment and is based on the electrostatic interaction of the amine groups of CS and the negatively charged groups of a polyanion such as tripolyphosphate (TPP). The size and surface characteristics of particles can be easily adjusted by varying the ratio between the polymer and polyanion In vitro data demonstrated that CS nanoparticles with positive surface and good spherical monodispersity enhanced the cellular uptake of the molecular cargos, including the anti‐cancer drug gefitinib and the lysosomal targeting drug chloroquine through the caveolae‐mediated endocytosis and macropinocytosis pathway It has been shown that CS nanoparticles with positive charge tend to make interactions with the negatively charged proteins at the cell surface to form clathrin vesicles. Whenever vesicles fall off from the plasma membrane into the cytoplasm, they can fuse with endosomes/lysosomes compartments. Then, acidity of the environment enhances the breaking of chemical bonds and structure of particle by enzymes, leading to the rapid release of cargo. Comparing the cellular uptake of CS molecules and nanoparticles and hence their capability to mediate insulin passage through Caco‐2 cell monolayers showed two times higher interaction with nanoparticles than that of CS molecules upon 2‐hrs incubation at the loading concentration of 1 mg/ml. Using chlorpromazine to reduce the number of coated pit‐associated receptors on the cell surface by disrupting the regulation of clathrin assembly/disassembly, it was concluded that clathrin is the major route for cellular uptake of the CS nanoparticles. These findings suggest that the structural transformation of CS molecules arranged in microscale linear chains into the condensed nanoscale particle results in a greatly improved cellular interaction and transport across the Caco‐2 cell monolayers The effectiveness of CS at absorption site is limited because of poor water solubility at pH > 9. As the pH increases above 6, CS starts to lose its positive charge density, induces rapid formation of aggregates and precipitates. To solve the issue above, thiolated CS (TCS) have been developed as a new generation of bioadhesive polymers +/H+ exchange to block the specific endocytic pathways. The results showed that HGCS nanoparticles do not forcefully follow one of the main endocytic pathways and the majority of them were taken up through the macropinocytosis which is a non‐destructive route as compared to the clathrin‐mediated endocytosis. Notably, HGCS nanoparticles exhibited different internalization efficiencies and also intracellular behaviours depending on their uptake route and were able to impair the lysosomal degradation process via fusion –conjugated GCS nanoparticles (GC‐Ce6) were synthesized as two kinds of tumour‐targeting nanoparticles containing photosensitizers for photodynamic therapy. Both nanoparticles had a spherical morphology  conjugates (LHSA) for cell uptake of anticancer drug, docetaxel, wherein the LMWH was the hydrophilic segment and SA as its hydrophobic counterpart. A hydrophobic minor core could facilitate interaction with the plasma membrane and enhance cellular uptake efficiency. As a result, the LHSA nanoparticles loaded with coumarin 6 exhibited significantly increased accumulation in 6 MCF‐7 and MDA‐MB‐231 human breast cancer cells when compared with the coumarin 6 solution Hyaluronic acid (HA), also called hyaluronan, is one of the main constituent components of the extracellular matrix, present abundantly in the various organs including connective, epithelial and neural tissues Core–shell polymeric structures can be prepared by conjugation of hydrophobic moieties such as tetradecylamine or bile acids with the carboxylic acid groups of HA through carbodiimide chemistry, thereby encapsulating of therapeutic and/or imaging molecules into inner hydrophobic cores (RHAMM) receptors overexpressed by a number of tumour cells and hence the high passive targeting ability towards tumour cells et al. ‐mediated endocytosis mechanism. Similarly, authors exhibited experimental data for binding and uptake of the near‐infrared Cy5.5–labelled 5β‐cholanic acid–conjugated HA (HACA) nanoparticles by liver sinusoidal endothelial cells expressing HA receptors as well as phagocytic cells of the reticuloendothelial system. Meanwhile, this study compared the tumour targetability of PEGylated‐ and non‐PEGylated HA nanoparticles as application of HA nanoparticles for tumour therapy and diagnosis is limited because of their preferential accumulation in the liver site after systemic administration. The experiment revealed that PEGylated HA nanoparticles resulted in a 1.6‐fold higher accumulation in the cancer cells  when compared to the bare HA nanoparticles et al. in vivo tumour targetability of nanoparticles was also demonstrated in MCF‐7/tumour‐bearing mice by non‐invasive near‐infrared fluorescence imaging , and its disintegration occurs mainly by dextranase enzyme which is found in liver, spleen, kidney and bottom section of the gastrointestinal tract Dextran is an unbranched water‐soluble polysaccharide and has been used in a range of biomedical applications because of its excellent biocompatibility, biodegradability, non‐antigenicity and non‐immunogenicity properties et al. Mannosylated dextran nanoparticles have been shown to involve enhanced cellular association as well as higher antigen delivery to dendritic cells (DCs) when compared to unmodified particles or particles modified with a non‐specific sugar residue for design and development of optimally modulated vaccine delivery system in vitro through their electrostatic interactions with cell membranes Dextran–spermine is a biodegradable and water‐soluble cationic polymer which is prepared by reductive amination synthesis between oxidized dextran and the naturally occurring tetramine spermine. Dextran–spermine complexes have been found to be active in transfecting a wide range of cell lines Aureobasidium pullulanset al., performed recently to assess intracellular distribution of pullulan–DOX conjugate nanoparticles in HeLa, HepG2 and L929 cells. It was observed that uptake of nanoparticles by HepG2 cells was significantly higher than HeLa and L929 cells. These results provide evidence that pullulan residues of nanoparticle shell act as targeting moieties and are able to mediate uptake of nanoparticles by receptor‐mediated endocytosis through ASGPR receptor recognition on HepG2 cells. The ASGPR is not highly expressed at the surface of HeLa and L929 cells Pullulan is a highly water‐soluble linear neutral polysaccharide produced from the fermentation activity of strains of fungus N‐trimethyl CS chloride, CS glutamate, CS chloride) showed a significantly low cytotoxic activity in respiratory cells  than that of the CS derivatives, alone. Much stronger complexation between N‐trimethyl CS chloride and CMP resulted in smaller particle size when compared with CS salts. In mouse macrophages (J774A.1), the highest uptake efficiency was found with N‐trimethyl CS chloride–CMP composite particles after 2‐hrs incubation which could be explained by their smaller dimension and more narrow particle size distribution Carboxymethyl pullulan (CMP) was reported as a polyanion for the first time to prepare composite nanoparticles for delivery of vaccines , which chemically modified with hydrophobic cholesteryl moieties et al. reported on the immune‐enhancing ability of the tumour necrosis factor‐α–encapsulated CHP nanoparticles to act as a vaccine adjuvant for inducing systemic IgG1 as well as mucosal IgA via the nasal route of administration. As a result, these nanoparticles promoted antigen uptake by DCs and moderately increased the expression of inflammation‐related genes in the nasopharynx lymphoid tissue, the inductive site of common mucosal immune responses in vitro experiments suggested that clathrin‐mediated endocytosis and macropinocytosis were involved in the uptake of CHP nanoparticles and the degree of uptake was clearly concentration‐, time‐ and temperature‐dependent. Besides, it was found that nanoparticles were mostly entrapped within the lysosomal apparatus. So, these nanoparticles are a good choice for drug delivery for the treatment of lysosomal storage diseases, cancer and Alzheimer's disease Cholesteryl pullulan (CHP) is the naturally occurring polysaccharide, pullulanIn vitro study on human nasopharyngeal epidermal carcinoma cell line demonstrated that PA nanoparticles enhanced cellular uptake and mainly intracytoplasmic distribution of epirubicin (EPI) under the same condition when compared with free EPI. As, PA/EPI nanoparticles were taken up by the cells through an endocytic mechanism, hence these particles escape from the endosome/lysosome compartment to enter the cytosol Pullulan acetate (PA) is known as another important hydrophobized pullulan, which can form self‐aggregated nanoparticles having small particle size, with a narrow size distribution, and a low precipitation rate. Pectins typically consist of a complex family of structural polysaccharides present in all plant primary cell walls and contain large quantities of poly‐ linked by α‐1,4‐glycosidic bonds. They are random and heterogeneous moieties in terms of chemical composition and molecular mass and can be subdivided as high methoxy (HM), low methoxy (LM) and amidated pectins Ionotropic gelation and gel coating have been especially suggested to produce pectin‐based drug delivery carriers Recently, citrus pectin and pH‐responsive polymer Eudragit S‐100 have been used to manufacture nanoparticulate carriers for the site‐specific delivery of 5‐fluorouracil (5‐FU) for treatment of colorectal cancer. The results confirmed the ability of nanoparticles to protect the drug loss in the upper parts of GI tract and to deliver 5‐FU when they reach colon owing to the amiable pH of the colonic fluid. Besides, citrus pectin is a specific ligand for galectin‐3 receptors overexpressed in colorectal cancer cells and enhances cellular uptake of the nanoparticles through receptor‐mediated endocytosis Many nanotechnology‐based delivery systems have been designed for the intracellular delivery and subcellular localization of drug/gene. Among these, polysaccharide‐based nanoparticles appear to be a promising carrier in delivering their contents to intracellular targets. The mucoadhesive nature of polysaccharides can provide an opportunity to improve the residence time and to increase binding/uptake properties of the nanoparticles at the absorption site. Moreover, receptor‐targeted polysaccharide nanoparticles can be further applied to enhance the preferential uptake and intracellular accumulation of the pharmaceutical agents. However, a few studies have been conducted to evaluate interaction of the polysaccharide nanoparticles with cell membranes as well as to address their uptake mechanism and their intracellular fate that must be considered.No ethical issues to be promulgated.The authors declare that there are no conflicts of interests.


The specific role of the perirhinal (PRC), entorhinal (ERC) and parahippocampal cortices (PHC) in supporting familiarity‐based recognition remains unknown. An fMRI study explored whether these medial temporal lobe (MTL) structures responded in the same way or differentially to familiarity as a function of stimulus type at recognition. A secondary aim was to explore whether the hippocampus responds in the same way to equally strong familiarity and recollection and whether this is influenced by the kind of stimulus involved. Univariate and multivariate analyses revealed that familiarity responses in the PRC, ERC, PHC and the amygdala are material‐specific. Specifically, the PRC and ERC selectively responded to object familiarity, while the PHC responded to both object and scene familiarity. The amygdala only responded to familiarity memory for faces. The hippocampus did not respond to stimulus familiarity for any of the three types of stimuli, but it did respond to recollection for all three types of stimuli. This was true even when recollection was contrasted to equally accurate familiarity. Overall, the findings suggest that the role of the MTL neocortices and the amygdala in familiarity‐based recognition depends on the kind of stimulus in memory, whereas the role of the hippocampus in recollection is independent of the type of cuing stimulus. © 2016 The Authors Hippocampus Published by Wiley Periodicals, Inc. ERCentorhinal cortexGPCGaussian Process ClassificationMTLmedial temporal lobeMVPAmulti‐voxel pattern analysisPHCparahippocampal corticePRCperirhinal cortexRecognizing a stimulus, such as a face, an object or a scene , as something that has been encountered before involves a pivotal human ability called recognition memory. This can be supported by a feeling of memory that the stimulus has been encountered before and/or by the recall of specific contextual details about a previous encounter with it. These two kinds of memory are called familiarity and recollection, respectively, and have been proposed to depend on partially distinct psychological and neural encoding, storage and retrieval processes Mandler, . FamiliaMaterial‐specific effects have so far been studied almost exclusively for recollection or recollection‐related processes, such as in associative tasks requiring the retrieval of different kinds of source information  as recollection and whether this is consistent for object, face and scene recognition memory. In our analyses we combined univariate‐GLM and multivariate (pattern recognition) approaches. The combination of the two methods of analysis has the potential to provide complementary findings and bridge inconsistencies reported in previous studies.In total, 20 right‐handed healthy volunteers gave informed consent and participated in this experiment. All participants were native English speakers, with no self‐reported psychiatric or neurological disorders and normal or corrected‐to‐normal vision (with contact lenses). Data from three participants were excluded from further analyses; one due to excessive movement during fMRI (more than 3 mm), one due to a technical problem affecting the recording of the fMRI data and another one due to chance memory performance at retrieval. The mean age of the remaining 17 participants  was 23.28 years (SD = 3.40 years). All participants received £20 after completing the testing session. The National Research Ethics Service (North West‐GM South) approved all the procedures followed in this experiment.A total of 420 color stimuli (15 for practice) were used in this experiment. As the aim of the study was to explore the brain networks that support familiarity‐based and recollection‐based recognition for different stimulus types, three stimulus categories were used: outdoor scenes, objects  and faces. For each stimulus type 140 stimuli (five for practice) were presented. The scene and the object stimuli  were royalty‐free images with transferable copyrights collected from various online databases  and a retrieval phase completed in the MRI scanner Fig. . At encotry to recollect at any time , spontaneous recollection (R) and new (N) options  along with 135 new foils . For each stimulus type, 135 stimuli per category (90 studied) were presented at retrieval while participants provided responses using the three levels of increasing familiarity  and two buttons on the other hand were used for the extra two responses (R and N). The assignment of these responses to left and right hand was counterbalanced across participants.At retrieval, stimuli were presented in a pseudo‐random sequence of face, object and scene blocks, separated by short fixation periods (10s). Within this sequence each block was followed by a different stimulus block. Each of these blocks comprised 15 trials intermixed with three implicit baseline fixation trials (null events). In total, 81 null events were presented across all the blocks. Each trial (including the null events) lasted for 3s followed by a 1s fixation cross. Participants were instructed to provide a response for each stimulus trial within this period, using a special MR‐compatible button box. As the recognition task included five possible responses, three buttons on one hand were used for the familiarity responses (Scanning was conducted on a 3T Philips (Achieva) scanner. A gradient echo‐planar pulse sequence was used for the acquisition of the functional data using the blood oxygenation level dependent (BOLD) contrast. In total, 840 volumes were acquired, for each participant, across two sessions with TR = 2.5s, TE = 35ms, 2.5mm × 2.5mm × 3.5mm voxel size and 40 slices per volume covering the whole brain . High‐resolution T1 images were also acquired prior to the functional run (180 slices with a voxel size of 1mm isotropic and matrix size 256 × 256). Soft pads were used to minimize head motion during scanning and earplugs were provided to reduce MRI scanner noise.ArtRepair software (http://cibsr.stanford.edu/tools/human-brain-project/artrepair-software.html). Fewer than 5% of the slices from two subjects were repaired using ArtRepair algorithms implementing linear interpolation of the adjacent (preceding and following) slices within the time‐series. The other 15 participants did not have any major artifacts in their functional data and no repair algorithms were applied. The EPI data from each participant were pre‐processed and analysed using SPM8 software . The fMRI time‐series were realigned to the mean image (registration) using a six‐parameter rigid body transformation, resliced using sinc interpolation and slice‐time corrected (to the middle slice) to account for differences in slice acquisition times. Residual movement artefacts were also obtained from the ArtRepair toolbox and used as nuisance regressors in the first‐level analysis (see below). Individual T1 images were coregistered to the corresponding mean EPI image. Spatial normalization of the EPI and T1 images to the MNI template was performed using the DARTEL toolbox implemented in SPM8 . Specifically, the event‐related functional data were modelled separately for each participant using a canonical hemodynamic response function , with misses used as the level reflecting zero familiarity (F0). All participants had a minimum of 9 trials in each response category for each stimulus type enabling reliable parametric analyses . Parametric t contrasts were created at the first‐level for monotonic increases or decreases in activity across familiarity strength for each stimulus type. Non‐linear quadratic effects were also modeled to capture residual variance not explained by the linear function; however, these produced no significant additional activations and are not reported separately. Finally, the parametric analyses were also conducted using three levels of strength  for each type of stimulus, but these produced very similar results to the main analyses and are not presented separately.Brain activity modulations by familiarity strength were investigated using the parametric model and involved three parametric analyses, exploring monotonic increases or decreases in activity across familiarity, separately for scenes, objects and faces  to each parametric contrast. In the case of scene familiarity, the parametric responses were exclusively masked by object and face familiarity activations. Similarly, object familiarity activations and deactivations were exclusively masked by scene and face familiarity activation and deactivation patterns. Finally, parametric responses to familiarity for faces were exclusively masked by familiarity responses to scenes and objects.In the parametric analyses both common  activations across all stimulus types as well as material‐specific familiarity activations for each type of stimulus were examined. Specifically, shared familiarity activity was explored by means of a conjunction analysis , a direct contrast between these two conditions was run for objects (Robjects > F3objects) and scenes (Rscenes > F3scences) and collapsed across the three types of stimuli (R > F3) using the categorical model. Furthermore, two conjunction analyses were conducted to assess the overlap of the hippocampal responses for scene and object stimuli, one using the R > F3 contrast and the other using the R > M contrast for the two types of stimuli. As faces produced very few R responses, these were not analyzed separately or in the conjunction analyses, but were included in the analysis with the collapsed R responses. Furthermore, F3 and R responses were also contrasted versus misses (M) again for each stimulus type  and collapsed across type (F3 > M and R > M). For the recollection analyses, data from 16 participants were used as one participant did not give enough recollection responses at retrieval. The individual parametric and categorical contrasts of interest were entered into a one‐sample t‐test in the second‐level analysis treating participants as a random effect. All the produced SPM(t) maps, for all the analyses reported here, were initially thresholded at an uncorrected voxel level of P < 0.001 and clusters are reported as significant when at least 8 contiguous voxels were active unless noted differently. In the case of activations surviving a cluster‐wise FWE‐correction for multiple comparisons these are denoted separately.To explore whether the hippocampus preferentially responds to recollection or to both recollection and strong familiarity  responses across the three types of stimuli (scenes vs. objects vs. faces). The same analysis was also conducted for the collapsed familiarity responses and is presented in the supplement . To control for any potential systematic bias favoring the classification of one stimulus type over the other two types of stimuli in the multiclass GPC classification model, separate binary SVM (Support Vector Machine) classifications were also performed between all the possible stimulus combinations  and an aggregate classification accuracy  for each stimulus type was calculated. As the results produced from this approach are very similar to those from the main Multiclass GPC, they are not reported separately in the Results but can be found in Supporting Information Table 2. Finally, a separate analysis examined pattern classification for familiar stimuli using binary SVM between F3 responses and misses (M) separately for each stimulus type. This analysis, which is presented in Supporting Information Table 5, complemented the main GCP classification reported in the Results below and produced similar findings to it. However, any discrepancies are noted and discussed (see Results and Discussion).To investigate the two main questions of the present study, two sets of classification analyses were performed using in each case the condition‐specific fMRI beta images generated for each subject in the GLM analysis. First, to explore whether familiarity‐related brain responses within the different ROIs vary as a function of stimulus type, we used a Multiclass Gaussian Process Classification (GPC)  collapsed for the three types of stimuli using a binary SVM (Support Vector Machine) algorithm. Finally, to explore any differences in the classification outcome for Rscenes and Robjects in the hippocampus, a separate binary SVM model was also run. Each classification was performed separately for each ROI and included all voxels within each ROI (no feature selection was used). In these classification analyses the data were mean centered and a leave‐one‐subject‐out (LOSO) cross‐validation procedure was performed to ensure independence between training and test data sets. Specifically, this cross‐validation procedure involves repeated repartitioning of the training and test data to derive an estimate of the accuracy and the generalization error of the model across subjects. This group analysis, treating subjects as a random factor, enables the generalization of the classification results to the population. Statistical significance of the classifications within each ROI was tested using permutation testing (1000 permutations) for each model (classifier).To approach the second aim of this study regarding the role of the hippocampus in coding for recollection and/or equally strong familiarity, a second set of classification analyses compared classification performance for F1, F2, F3) as the within‐subjects factors showed significant main effects of type  and strength . Pairwise comparisons revealed higher familiarity accuracy for objects than faces (P = 0.007), but no other difference across the three types, and increased memory accuracy with increased familiarity strength . Importantly, as presented in Figure F3 responses were characterized by matched memory accuracy with R responses, across all stimuli types collapsed  and separately for scenes  and objects . Recollection responses for faces were very rare and therefore are not evaluated separately.Memory accuracy [Hit rate/(Hit rate + FA rate)] for familiarity and recollection responses is presented in Figure F2,30 = 54.31, P < 0.001), with longer latencies for scenes  than both objects  and faces  and a significant effect of strength , indicating shorter latencies for more confident responses (F1 > F2 > F3). Matched RTs characterized recollection and F3 responses across all stimulus types collapsed  and separately for scenes  and objects .The 3 × 3 ANOVA on the RTs showed a significant main effect of stimulus type (F3) were analyzed separately for scene, face and object stimuli (see Methods). Shared activation patterns within the MTL across all stimulus types as well as material‐specific familiarity activations for each type of stimulus were explored. In the conjunction analysis, no overlapping MTL region was found to respond to familiarity for the three types of stimuli. Instead, only material‐specific responses in the MTL were found during familiarity decisions. This means that structures of the MTL only provide material‐specific support when involved in familiarity decisions.In the univariate analysis, parametric increases or decreases across familiarity strength  increased their activity across familiarity strength selectively for the scene stimuli. In contrast, unique parametric deactivation patterns for object stimuli  as well as in an area of the anterior PRC/ERC (x = 21 y = −6 z = −27) at a lower threshold . Finally, a cluster within the left amygdala  and another cluster within the fusiform gyrus  uniquely responded to face familiarity .Specifically, a variety of familiarity responses across the three stimulus types emerged within the MTL. As shown in Figure F3 (strongly familiar) responses for scenes, objects and faces across participants . The classification profile, in terms of classification accuracy and classification errors, for each anatomical ROI is summarized in Figure P = 0.01) and significant classification accuracy for scenes , objects  and faces . This indicates that activation patterns within the whole brain successfully discriminated F3 responses across the three types of stimuli. In the hippocampus, classification accuracy for F3 responses to scenes, objects and faces was low and not significant  and the left PHC  and for objects in the right PHC . Similar results were obtained when partitioning the parahippocampal gyrus (including both PRC and PHC) into anterior, middle and posterior portions. The anterior aspect (corresponding to the PRC/ERC) showed selective classification sensitivity to object familiarity . The posterior aspect (corresponding to the PHC) showed significant classification accuracy for both objects  and scenes , while the middle aspect of the gyrus, corresponding to the transitional zone between PRC and PHC, was also found to code for both object  and scene familiarity . In the amygdala  and the right amygdala  but not for the other two stimulus types. Similar multivariate classification findings were obtained when the same analysis was conducted for the familiarity responses collapsed across the three levels of strength  and when F3 responses were classified relative to misses separately for scenes, objects and faces (Supporting Information Table 5). The only difference between the main analysis, as reported above, and the one classifying familiar (F3) versus missed stimuli (reported in Supporting Information Table 5), was the accurate classification of familiar faces in the left ERC .Multivariate classification was conducted for the whole brain and a priori ROIs including the hippocampus, the PRC, the ERC, the PHC, and the amygdala. A multi‐class Gaussian Process Classification (GPC) algorithm was trained to classify R were found in the hippocampus in a series of contrasts between R versus accuracy‐matched F3 responses and R versus misses (M). Specifically, the bilateral hippocampus  selectively responded to R versus F3 responses collapsed across the three stimulus types  yielded only a significant cluster in the PHC  responding more to Rscenes than Robjects , separate analyses were run contrasting R versus misses (M) and F3 versus M, both collapsed across stimulus type and separately for objects and scenes (and faces for F3faces versus Mfaces). As shown in Figure Rscenes > Mscenes: x = −27, y = −9, z = −21, P < 0.05, FWE‐corrected, 20 voxels; Robjects > Mobjects: x = −15, y = −36, z = 0 and x = −24, y = −27, z = −6, P < 0.001, 18 voxels; Rall > Mall: x = −18, y = −27, z = −9 and x = −24, y = −6, z = −21, P < 0.05 FWE‐corrected, 60 voxels). In contrast, none of the contrasts between F3 and misses for each stimulus type, separately and collapsed, yielded any significant activation within the hippocampus even at a considerably lower threshold .To further validate the selectiveness of the hippocampal response to Robjects > F3objects and Rscenes > F3scenes, while the second one between Robjects > Mobjects and Rscenes > Mscenes. Both conjunction analyses  confirmed that overlapping areas within the hippocampus respond to recollection for objects and scenes .Overall, these findings stress that the hippocampus selectively supports recollection (versus familiarity) and it does so in a non‐material specific fashion. To further explore the degree of overlap of the recollection activations in the hippocampus for the two types of stimuli , two conjunction analyses were further conducted. The first one was performed between F3 and R responses within each ROI and specifically within the hippocampus, binary SVM analyses were used (see Methods) to classify F3 and R responses versus misses collapsed across the three types of stimuli  and the right hippocampus . In contrast, F3 responses were classified very poorly in the hippocampus producing low and non‐significant classification accuracy , whereas R responses were reliably classified only in the left PRC . In the PHC, classification within the left PHC yielded significant classification accuracy for both F3  and R , while within the whole PHC significant classification accuracy was found only for R responses . In the ERC, classification within the whole ERC mask was significant for R , but no other significant classification outcome for R or F3 was found either in the left or the right ERC. Finally, classification accuracy in the amygdala was low and non‐significant for both F3 and R responses.To compare classification performance for Robjects and Rscenes specifically in the hippocampus. Consistent with the conjunction analyses reported above for scene and object recollection and the lack of any difference in the hippocampus when contrasting Rscenes and Robjects, this analysis yielded a very low overall model accuracy in the hippocampus  denoting the very poor discrimination between recollection for objects and scenes within the hippocampus. This is consistent with the hippocampus supporting recollection in a non‐material specific way. Indeed, when Robjects and Rscenes were examined separately, relative to misses, they produced equally good classification outcomes in the hippocampus .An SVM analysis was also performed to compare In this fMRI study we employed a recognition memory paradigm to explore the interaction between stimulus content and the kind of memory engaged at retrieval. Our primary aim was to investigate whether familiarity for different kinds of visual stimulus is mediated by a common MTL neural network or whether there are at least partially non‐overlapping MTL networks mediating familiarity for different kinds of stimulus. This question is particularly important because different models of MTL functional organization currently make different predictions about the contribution of MTL structures in familiarity‐based recognition for different stimulus types (see Introduction). The findings presented here point toward a degree of specialization, with respect to stimulus type, within the MTL structures  for familiarity. On the other hand, overlapping regions of the hippocampus mediated recollection, regardless of the kind of visual stimulus to which it related. However, no response to familiarity was found in the hippocampus, even when recollection was contrasted to equally accurate familiarity. These findings have important implications for current theories of recognition memory and for evaluating the extent of functional specialization within the MTL. These are further discussed below.As discussed in the Introduction, different models of recognition memory make different predictions with respect to the role of PHC in supporting familiarity memory with some models stressing its role in supporting recollection  to selectively code for face familiarity. The amygdala cluster in the univariate analysis also included voxels (9 out of 35 active voxels) falling within the ERC (BA 34). This finding may agree with recent evidence that areas within the anterior temporal lobe (including portions of the ERC and PRC) have a role in face discrimination and identification  was found. Instead, other, more posterior areas of the inferior temporal lobe (including the fusiform gyrus), were activated by faces  may indicate that the role of PRC in face processing is limited to face discrimination and identification  to misses (M) for each type of stimulus separately (Supporting Information Table 5), similar findings to those reported in the main analysis are revealed. In this case the type of stimulus is the same between F3 and M and therefore the successful classification and discrimination of these two responses (F3 vs. M) cannot be attributed to the stimulus type, but only to the existence or not of familiarity for the stimulusOne unique aspect of the present study is the emphasis on investigating the role of the PRC, ERC and PHC selectively in familiarity‐based recognition and not on visual discrimination or recollection memory retrieval as in all previous studies that have explored material‐specificity effects in the MTL . Indeed, some evidence for this comes from a recent study . As described in the Introduction, although strong neuroimaging evidence supports the selective role of the hippocampus in recollection, but not in familiarity  responses. These patterns of results are not compatible with the predictions suggested by the strength confound view, but join the previous evidence for a selective role of the hippocampus in supporting recollection  the kind of stimulus that is recognized as familiar.Supporting InformationClick here for additional data file.