Input: Claim: The blood-brain barrier protects the brain from harmful substances. [SEP] Text: 7(Modified from Figure 9 in [41])Proposals to explain rapid transfer of markers via periarterial spaces: a the original proposal; b proposed perivascular convection and interstitial diffusion c the glymphatic proposal. In a the blood–brain barrier secretes fluid which flows out of the parenchyma via preferred routes (here the perivascular routes). In b transport in the perivascular spaces is assisted by convective stirring or mixing. In c (see Figure 5 of Iliff et al. [25]) there is preferential inflow via the space between the arterial wall and the pial sheath and preferential outflow via spaces surrounding veins. Red lines represent pial membranes, grey lines the layer of glial end-feet or glia limitans, black arrows are fluxes of markers carried or assisted by convection, green arrows are primarily diffusion. The location of the pial barriers is based on Zhang et al. [23]. The anatomical basis of the perivascular spaces remains controversialFull size image Proposal 1 The first proposal (Fig. 7a) was that secretion of fluid by the blood–brain barrier provides a small pressure gradient for outflow of ISF along preferential routes (see [83, 126, 127, 129, 130]). These routes could be perivascular spaces or the extracellular spaces parallel to the axons in nerve fibre tracts. When this proposal was put forward more than 30 years ago (see e. g. [83]) it was believed that the half-life for clearance of marker solutes by outflow was of the order of 12 h. However, all of these early studies were performed on animals anaesthetized using barbiturates. Using either conscious animals or those anaesthetized with ketamine/zylazine or halothane, the half-lives are much shorter, 2–4 h [25, 62, 85, 131]. Perivascular efflux of solutes is considerably faster than envisaged by Cserr and coworkers. It should also be pointed out that Proposal 1 does not and was never intended to provide any explanation for the rapid influx of solutes. 1 (and in Proposal 3, see below) the solutes are swept out of the parenchyma by the flow through the perivascular system.

Output: pass


Input: Claim: Proteomics studies the entire set of proteins expressed in a cell. [SEP] Text: The complete list of identified proteins and their fold change differences with both the quantitative analysis data among SLE patients and healthy controls were presented in Table S2. software generated a heat map of the differentially expressed proteins by comparing the patients and controls were shown in Fig. 2. The FDR specified for the identified proteins was <1%. The complete comparative proteomic analysis using PEAKS 8. 0 and emPAI quantitative evaluations of the up and down-regulated proteins were presented in Table 3. Figure 1: A representative LC-MS/MS base peak chromatogram. (A) SLE patients compared to (B) healthy controls. Download full-size image DOI: 10. 7717/peerj. 4730/fig-1 Figure 2: An overview of the plasma protein profile of the SLE patients. The heat map was generated using 8. 0 displaying the differentially expressed proteins identified using LC-MS/MS label-free proteomic analysis between SLE patients and controls. The color scale representing the relative expression level of each protein across SLE and controls; red and green colors indicate the higher and lower levels of expressions. The intensity of the color represents the degree of protein up- and down-regulation when SLE patients and controls are compared. Download full-size image DOI: 10. 7717/peerj. 4730/fig-2 Table 3: The list of statistically significantly up and down-regulated proteins (p < 0. 05, 0. 01) between SLE patients and healthy control plasma samples. Protein name Gene name Uniprot accessiona Mascot scoreb Matched peptidesc Msequence coveragee Average area of the triplicate analysisf Fold change SLE/controls EmPAI (triplicates average) EmPAI fold change Protein regulation Up(+), Down (−) Function p-valueg kappa chain C variable region 315_HUMAN 212 77 12. 49 42. 7 81657. 3 ± 30951. 1 28738. 8 ± 2422. 5 2. 84 0. 90 ± 0. 1 0. 382 ± 0. 01 2. 35 + Immune response and regulation 0. 04 Ig heavy chain G4 IGHG4 IGHG4_HUMAN 141 17 35. 4 23. 97 407207. 9 ± 142838. 3 118916. 6 ± 10435. 2 3. 42 0.

Output: corroborate


Input: Claim: All behaviors can be understood solely through neural circuitry. [SEP] Text: We have clarified this information in lines 310-311. (11) Finally, the discussion contains a statement that is not supported by the data: "We have discovered dual modes of Sema7A function in vivo. " They have discovered evidence that there are two isoforms, that loss of both disrupts connectivity, and that overexpression of only the secreted form can elicit growth from a distance. However, there is no direct evidence that the membrane-bound form is responsible for local effects. It is formally possible still that the phenotypes are a result of dual roles for the secreted form. It is clear that another manuscript is forthcoming that will expand on the role of the transmembrane form, but for this manuscript, the authors should make firm conclusions only about the data presented herein. Thank you for this suggestion. We have modified the manuscript in lines 425-434. Reviewer #4 (The Authors): The authors have made significant changes to the manuscript based on the comments of the reviewers. It is now suitable for publication.

Output: contrast


Input: Claim: The blood-brain barrier protects the brain from harmful substances. [SEP] Text: Even the bottom of this range is somewhat more than twice the rate of production of CSF. There is no other reason to suspect that there is a rate of secretion of fluid across the blood–brain barrier that exceeds the rate of fluid secretion by the choroid plexuses (see Section 4. 1 in [4]). The rate of fluid secretion across the blood–brain barrier is very unlikely to be this large and is almost certain to be insufficient to account for perivascular clearance of solutes. Proposal 2 (Fig. 7b) The second suggestion, recently revived, is that convection in the perivascular spaces, arterial and possibly venous, leads to convective mixing of the fluid in the spaces allowing relatively rapid movements of solutes both inwards and outwards [41, 78, 82, 96, 132]. Such mixing probably presupposes that perivascular spaces are compressible. Convective mixing is perhaps better called dispersion [78]. Papisov [133] and Asgari et al. [134] discuss a similar effect in the spinal cord allowing transport of solutes down their concentration gradients against the direction of net flow of CSF and at rates much greater than allowed by diffusion. In this proposal diffusion is taken to be adequate to explain movements within the interstitial spaces in the parenchyma because the distances involved are sufficiently short (see Sect. 3. 2. 1). In this proposal (and in Proposal 3, see below), an important part of the mechanism is thought to be convection in spaces whose dimensions are changed by periodic compression resulting from the changes in blood pressure during the cardiac cycle [13, 25, 70, 82, 96, 132]. The length of space around a cortical vessel that is compressed at one time is as long as the vessel [78, 82]. Bradbury et al. [82] were of the opinion that periodic compression and reexpansion of this space “would cause to-and-fro movement of fluid in and out of the brain” such that “A basis would be provided for substances in solution or suspension to be moved either out of or into the brain depending on the relative concentration in subarachnoid CSF. ” Another variation on this theme may be possible if there are layers of differing compressibility, both connected via relatively low resistance pathways to the brain surface.

Output: pass


Input: Claim: Proteomics studies the entire set of proteins expressed in a cell. [SEP] Text: Therefore, the identified proteins are likely to play a significant role in SLE disease development and/or pathogenesis. Figure 4: Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis of the proteins identified showing differential expression. The majority of the identified proteins were enriched in relation to the complement and coagulation cascades and acute immune responses. The horizontal bars represent the number of differentially expressed proteins involved in various pathways. Download full-size image DOI: 10. 7717/peerj. 4730/fig-4 Additionally, the network analysis demonstrated a tight PPI network when the medium PPI confidence score of 0. 4 was applied in database, whereas at the high confidence score of 0. 7 a significant association of PPT networks was identified among the differentially expressed proteins as shown in Fig. 5. This PPI network suggests that the identified proteins have strong interactions with the proteins that contribute to numerous BP and have a wide range of MFs. Figure 5: The protein–protein interactions for the differentially expressed proteins identified by LC-MS/MS label-free proteomics were analyzed using software V9. 1. In the network analysis the differentially expressed proteins were represented as nodes. Each color of the lines connecting the nodes indicates strong evidence of the tight network of proteins. (A) The tight protein–protein interaction network obtained when the medium confidence level of 0. 4 was applied. (B) The high confidence (0. 7) PPI network of the identified significant proteins in SLE. Download full-size image DOI: 10. 7717/peerj. 4730/fig-5 comparative mass-based proteomic analysis investigated the proteomic profiles of SLE plasma samples were compared with healthy controls using the LC-ESI-MS/MS technique with label-free quantification. We were able to identify 122 differentially expressed proteins, and among these 19 proteins showed significant changes in expression with 14 of these being up-regulated and five being down-regulated in the SLE samples. When these proteins were subjected to the functional analysis, this protein profile was predominantly enriched with biological regulation, catalytic, and binding activity.

Output: corroborate


Input: Claim: All behaviors can be understood solely through neural circuitry. [SEP] Text: : 2572-4983 Neonatal and -in-for Manuscript 10. 4172/2572-4983. 1000171 Rewarding the Autistic through Understanding the Neural Cognitive, Emotional, Motor binding Circuitry in the *Specialist in Dermatology, Academy of *Corresponding Author: Michael Chan, Specialist in Dermatology, Academy of : +85221482882, Email: pioneerskin@ymail. com Received: 26-Oct-2018 Accepted Date: 01-Nov-2018 Published Date: 09-Nov-2018 DOI: 10. 4172/2572-4983. 1000171 : Autism spectrum disorder syndrome; Cerebellar corticoemotional motor neural circuits; Reward; Adaptive time delay; Theory of mind; Early detection is a complex spectrum disorder; mostly observed at 2-3 years of age with characteristic anomalous, deviant cognitive, emotional, behavioural and neuro-motor developments till adulthood. Each autistic is different. Increasing prevalence up to 2% in children with a greater association and severity in male gender is noted. Asperger’s syndrome, Rett syndrome, childhood disintegrative disorder, pervasive developmental disorder and autism are all grouped under Disorders (ASD) [1]. ASD sufferers can be readily recognised by their repetitive, sometimes aloof and servant behaviour; echolalia, inappropriate language response and impaired attention to other. The overall consequences deprived the ASD individuals with adaptive learning, social, relationship and communication skills. ASD are frequently stigmatized as mentally insane in our community. Academy of Pediatrics (AAP) recommends children be screened for developmental disorders at wellchild preventive visits before age three [2]. for and Prevention (CDC) of have identified possible clinical alerts or red flags for ASD [1,2] (Table 1). S. N. Alerts or for ASD 1 Not responding to his/her name by 12 months of age 2 Not pointing at objects to show interest by 14 months 3 Not playing "pretend" games by 18 months 4 Avoiding eye contact or preferring to be alone 5 Getting upset by minor changes 6 Flapping their hands, rocking their body or spinning in circles 7 Having unusual and sometimes intense reactions to the way things smell, taste, feel and/or look Table 1: Clinical signs that parents should alert the possibilities of ASD.

Output: contrast


Input: Claim: The blood-brain barrier protects the brain from harmful substances. [SEP] Text: Back-and-forth convective movements in perivascular spaces would only be apparent using techniques with both good spatial resolution and time resolution better than a fraction of a second. Such movements have been observed in perivascular spaces very close to the cortical surface using india ink [84] and in the periarterial spaces at the cortical surfaces using microspheres [108]. But with techniques now available for viewing, if perivascular spaces exist that allow convective back and forth movements, all that would be seen within the parenchyma would be accelerated movement down the concentration gradient regardless of its direction, i. e. the periarterial influxes and effluxes that have been observed. Proposal 3 (Fig. 7c) The third proposal, the glymphatic hypothesis [25, 109, 135,136,137], asserts. There is an inward flow of CSF along periarterial spaces; The flow is driven across the layer of astrocyte endfeet into the parenchyma aided by the presence of Aqp4 in the endfeet; The flow propels the waste products of metabolism into the perivenous space again crossing the layer of endfeet, presumably again aided by the presence of Aqp4; The flow exits the parenchyma by the perivenous route and reaches lymphatic vessels in the neck. As indicated when considering Proposal 1, a flow of ~ 0. 6 µL g−1 min−1 or more would be required to remove the efflux markers at the observed rate. For a 1400 g brain, that is c. 1. 2 L day−1 roughly twice the generally accepted rate of CSF production. Thus even if the rest of this proposal is correct, either the glymphatic flow does not direct ISF out of the brain directly to lymphatic vessels or the rate of CSF production is greater than is generally accepted.

Output: pass


Input: Claim: Proteomics studies the entire set of proteins expressed in a cell. [SEP] Text: The AAP proteins which are down-regulated in this study are APOA1 and APOA2, these are major constituents of the high-density lipoprotein (HDL) complex, which has a specific role in lipid metabolism and has anti-inflammatory properties during both acute and chronic inflammation. Moreover, these are known to be immune regulators and suppress the generation of pro-inflammatory cytokines by activated T-cells (Barry et al. , 2004) have been demonstrated in various autoimmune diseases. Furthermore, previous proteomic studies of RA and SLE have reported down-regulated APOA1 expressions may responsible for the active phase of the disease. These proteins also seem to have a key role in anti-inflammation (Abe et al. , 2001; Kazemipour et al. , 2015). Our results on APOA1 expression levels agree with the previous studies and seem to confirm the active SLE disease state of the patients used in this study. A great deal of evidence has demonstrated that extreme oxidative stress leads to severe inflammation. Moreover, SLE is known to cause severe persistent inflammation in many major organs of the body. If we examine earlier SLE proteomic studies, some of the identified protein expressions by this study are consistent with previous reports, examples being ORM1/A1AG, TF, and CP, all of which have been detected in urine and renal biopsy samples obtained from SLE samples and were reported to act as biomarkers for class IV LN (Brunner et al. , 2012; Alaiya et al. , 2015; Suzuki et al. , 2007). Our study identified the similar changes in expression of these proteins in our plasma SLE samples. In addition to these, it has been shown that increased expression of 3/A1ACT and A1AT/1 seems to play an important role in moderating inflammatory responses, and reducing the production of inflammatory mediators and the blockage of inflammatory cells. Aggarwal et al. recently reported the increased expressions of 3/A1ACT in LN patients and demonstrated A1ACT as the best marker to differentiate active renal lupus patients from active non-renal patients (Aggarwal et al. , 2017). Thus, the identified differentially regulated antiprotease class of proteins may be relevant to renal dysregulation and inflammation in active lupus patients. HP is also involved in immune system regulation, homeostasis, and tissue repair.

Output: corroborate


Input: Claim: All behaviors can be understood solely through neural circuitry. [SEP] Text: Despite its increasing prevalence, researchers are still unable to unveil the exact aetiologies of ASD. Genetics with chromosome 1q, 2q, 7q, 2q, 15q11-13, 16q, TRIO gene mutations and other hereditary conditions like fragile X syndrome, tuberous sclerosis and phenylketonuria (PKU), early in-utero environmental insults like viral infections, metabolic imbalances and exposure to chemicals like aluminium, mercury, ethyl alcohol, pesticides, thalidomide, misoprostol and valproic acid are all reported [3,4]. Interestingly, ASD individuals also have an increase odd with immune dysfunction resulting allergic sensitivities, skin allergies like eczema, infections, gastrointestinal symptoms like constipation and diarrhoea, low muscle tone, pain, pica, epileptic fits, sensory and hearing impairments, seizures, anxieties and sleep problems [5] (Figure 1). Triangulating these epidemiological data, one may put forward a falsifiable model on the pathogenesis of ASD: multiple related genetic mutations and developmental insults from the environment resulting in an incoherent, fragmented excitatory and inhibitory neuronal circuitries in the responsible anatomical brain structures; namely, the cerebellum, neocortex, thalamus and its adjacent limbic structures especially the amygdala which primary physiological function are to facilitate motor planning, cognition, attention, emotion, body basic autonomic nervous system and neuro-endocrine pathways (Figure 2). Figure 1: Spectrum (ADS) and [10]. Figure 2: Schematic feedback relations whereby particular brain imbalances can ramify throughout other brain regions, thereby sustaining the imbalance by feedback and also creating or maintaining other symptoms [11]. The cerebellum, orbitofrontal cortex of the neocortex, thalamus, amygdala and hypothalamus and its neuro circuits are implicated in the pathogenesis of ASD. The integrated closeness and adaptation of these multidimensional circuitry sent matched coherent excitatory and inhibitory signals mainly in form of the glutamate GABA, acetylcholine, dopamine and serotonin neurotransmitters chemically and bind these relatively distantly located parts of the brain together through their multi-dimensional synaptic networks so as to maintain a state of stability, survival adaptiveness, learning, socialization and learning.

Output: contrast


Input: Claim: The blood-brain barrier protects the brain from harmful substances. [SEP] Text: The earlier evidence for and against the glymphatic hypothesis was discussed in [41] where it was argued that while a recirculation of CSF could explain influx and efflux of substances much faster than by simple diffusion, it did not explain either the observed outward movements of solutes along arteries [70, 71, 82, 83, 87, 130] or the observed continuation of rapid inward periarterial movement of large solutes when the proposed glymphatic circulation was interrupted at the level of the astrocyte endfeet by global knockout of Aqp4 [25]. Proposal 4 (not shown in Fig. 7) The most recent proposal [101] is that vasomotion, waxing and waning contraction of the smooth muscle fibres in the arterial wall, propels fluid towards the brain surface along the basement membranes of the vessel wall. This proposal does not seek to explain the rapid influx of markers along arterial walls, possibly by a different pathway. 3. 2. 1 Is movement within the parenchyma determined by diffusion or by flow from periarterial to perivenular spaces? It is unclear how the flow required for the glymphatic hypothesis to be correct, at least 0. 6 µL g−1 min−1 (see Proposal 3 above), could be driven through the parenchyma. Jin et al. [77] and Holter et al. [80] have calculated fluid flows within the parenchyma using, respectively, 2-D and 3-D models of the geometry and dimensions of the interstitial spaces. Jin et al. concluded that “little or no advective solute transport is predicted to occur with physiological paravascular pressure differences” taken to be < 5 mmHg. (Strictly advection corresponds to flow while convection includes both flow and diffusion). Furthermore they concluded that the water permeability of the endfeet membrane facing the microvessels, i. e. the membrane containing Aqp4, could have little direct effect on water flow into the parenchyma. Footnote 7 Jin et al. assumed that the ISF between the cells behaves as a free fluid with the viscosity of water.

Output: pass


Input: Claim: Gene expression analysis helps understand cellular responses to stimuli. [SEP] Text: Full text Figures and data Peer review Side by side Figures 4 figures Figures Figure 1 with 5 supplements Download asset Open asset Redundancy and synergy in a gene expression code. (A) Information content depends on the overlap between gene expression distributions under different environmental conditions, which in turn depends on both the response magnitude (signal) and the variability across the population (noise). (B) Diagrams illustrating redundancy versus synergy, calculated as the difference between the whole (combinatorial information in NSM/ASI/ADF; darkest bar) and the sum of parts (information in NSM + ASI + ADF; stacked bars). (C–E) Analysis of redundancy and synergy based on tph-1 expression in ADF and NSM, and daf-7 expression in ASI. Genotype color key: Wild-type (black), tph-1(-) (blue), daf-7(-) (red), and tph-1(-); daf-7(-) (purple). (C) Effect of tph-1(-) and daf-7(-) mutations on food encoding in the whole circuit (darkest bars) and the sum of parts (lighter stacked bars). (D) Effect of tph-1(-) and daf-7(-) on redundancy and synergy among and ASI, as defined in Equation 2 and (B). As described in Equation 2 and in the main text, redundancy and synergy are indicated by positive and negative R values, respectively. (E) Fraction of redundant or synergistic information in and ASI, which is the amount of redundancy or synergy in (D) normalized to the information encoded. (F–H) Analysis of redundancy and synergy only in the tph-1 expressing neurons, ADF, and NSM. (F) Effect of daf-7(-) in the information encoded by tph-1 expression in ADF and NSM (darkest bars) and the sum of their parts (lighter stacked bars). (G) Effect of daf-7(-) on redundancy/synergy of ADF and NSM. (H) Fraction of redundant or synergistic information in tph-1 expression in ADF and NSM, which is the amount of redundancy or synergy in (G) normalized to the total information encoded from (F).

Output: corroborate


Input: Claim: All behaviors can be understood solely through neural circuitry. [SEP] Text: Disruption of this binding or incoherence of neuronal networks due to genetic mutations, chemicals intoxications, miswiring of neuronal circuitry and other yet undiscovered causes may result ASD [6-9]. Embryogenesis of the human brain in a normal, healthy symmetrical and timely multiple synaptic development following the natural ontogeny will produce a coherent cognitively neural motor bind well-being with evolutionary survival advantage. The cerebellum In humans, the cerebellum is involved in motor control, cognitive functions such as attention and language as well as in regulating fear and pleasure responses. It is essential for several types of motor learning especially changes in sensorimotor relationships. The cerebellum is a complicated structure consisting of the anterior lobe, posterior lobe and flocculonodular lobe. The medial zone of the anterior and posterior lobes receives proprioceptive input from the spinal cord, cranial trigeminal nerve, visual and auditory systems. It sends sensory afferents to deep cerebellar nuclei which project to both the cerebral cortex and the brain stem, thus providing modulation of descending motor systems. The lateral zone, also known as neocerebellum contributes the cerebrocerebellum receives input exclusively from the cerebral parietal cortex via the pontine nuclei; forming the important cortico-ponto-cerebellar pathways; and sends output to the ventrolateral thalamus which in turn connected to motor areas of the cerebral cortex and to the red nucleus. Thus, the lateral cerebellum is involved in planning future movement, evaluating sensory information for future action and higher cognitive functions. Post mortem anatomical studies showed that ASD individuals have diminished Purkinje cell in terms of size, number and branching patterns especially in cerebellum VI and VII lobules. Functional MRI (f-MRI) showed dysplasia; hypo or hyperplasia of the cerebellar vermis in ASD compared with norm. Purkinje cells have rich serotonin contents, reduction in serotonin neurotransmitters may disinhibited arousal and emotional behaviour in autism [12-14]. Low serotonin level predicts anxiety, unhappiness and depression. Emotional facial expressions using f-MRI in high functioning autistic adults showed under activation of the left cerebellum [15]. Magnetic resonance spectroscopy (MRS) showed decreased cerebellar N-acetyl-aspartame (NAA); a neuronal indicator of function and maturity [16].

Output: contrast


Input: Claim: The blood-brain barrier protects the brain from harmful substances. [SEP] Text: If instead ISF in the interstitial spaces in the brain has properties similar to those of extracellular fluid in tissues in the rest of the body (see [138, 139], discussion in [41] and,Footnote 8 the pressure required for flow would be much larger than that calculated by Jin et al. making bulk flow (advection) even less likely (compare [140]). Holter et al. [80] have investigated what they consider to be a more realistic model of the parenchyma than that evaluated by Jin et al. One aspect is undeniably more realistic, it treats movement in three dimensions rather than two. It is also asserted that treating the obstacles to flow as being much smaller and more numerous than in Jin et al’s simulation produces a more faithful result. Jin et al. used barriers sized like cell bodies, while Holter et al. have adopted the smaller objects used in Kinney’s construction of the extracellular space [141], which allows for cell bodies and processes. (Smaller objects may be analogous to the increased resistance to flow resulting from macromolecules dissolved in peripheral extracellular fluid, see Footnote 8). Holter et al. conclude that flow makes a much smaller contribution than calculated by Jin et al. However, while Jin et al. treat the entrance and exit of fluid across the endfoot layers explicitly, this is missing from the treatment given by Holter et al. Given that the conclusion is “no flow” in both studies this difference between them may be of no consequence. It should be noted that neither Jin et al. [77] nor Holter et al. [80] have considered flow along the basement membranes surrounding capillaries presumably because the total area available for such flow is less than for flow via the interstitial spaces (and flow along basement membranes wasn’t considered in the glymphatic hypothesis). Asgari et al. [73] assumed that the resistance to flow of the basement membranes would be the same as for slabs of ®Matrigel of the same dimensions, and on this basis concluded that flow via basement membranes would be less than through the interstitium (compare the discussion in [16]). That flow through the parenchyma is not needed to explain the delivery of solutes to perivascular spaces was suggested by the results obtained using integrative optical imaging (see e. g.

Output: pass


Input: Claim: Gene expression analysis helps understand cellular responses to stimuli. [SEP] Text: (I) Loss of tph-1 and daf-7 degrades information about food abundance at the level of lifespan responses. Figure 1—source data 1 Information and redundancy across genotypes. (Tab 1) Combinatorial mutual information in the NSM/ASI/ADF neural circuit (‘Whole’ column) and the individual mutual information in and NSM neurons across different genotypes. (Tab 2) Combinatorial information in the NSM and ADF neurons (‘Whole’ column) and the individual information in ADF and NSM neurons in wild-type and daf-7(-) strains. (Tab 3) Mutual information in the lifespan response of different genotypes. All values are presented as bits ± error. Download elife-24040-fig1-data1-v1. xlsx Figure 1—source data 2 Fluorescence values for animals carrying both Pdaf-7::mCherry and Pdaf-7::Venus across four food levels for Figure 1—figure supplement 2. Download elife-24040-fig1-data2-v1. xlsx Figure 1—source data 3 Optimal input distributions for and NSM neurons across genotypes (data for Figure 1—figure supplement 3). Optimal input distributions obtained by maximizing the information encoded individually by and NSM neurons. Values are presented as probabilities ± uncertainty. Download elife-24040-fig1-data3-v1. xlsx Figure 1—source data 4 Validation of information and redundancy estimates for Figure 1—figure supplement 4. (Tab 1) Information (MI/channel capacity) and redundancy encoded by food-responsive gene expression in wild-type animals computed using different methodologies for density estimation. From left to right: plug-in method, least squares cross-validation, and smoothing cross-validation (kernel density estimation with fixed bandwidth selection), balloon estimator (kNN), Jack-knife correction of sample size bias. (Tab 2) Jack-knife analysis for information and redundancy across all genotypes. Values are calculated using a fraction of the total dataset indicated in first column. Download elife-24040-fig1-data4-v1. xlsx Figure 1—source data 5 Information, redundancy, and optimal input distribution by food level across genotypes. Data for Figure 1—figure supplement 5.

Output: corroborate


Input: Claim: All behaviors can be understood solely through neural circuitry. [SEP] Text: An inability to shift attention in a timely manner is one of the primary problems in autism. Adaptive timing response which critically involved the cerebellum was absent as illustrated in the classical eye blink reflex was impaired in ASD. Autistic may take more time to shift their attention from one stimulus to another in the changing environment full of multiple stimuli. This delay disables the autistic important contents and context informational cues which is essential for their adaptive learning. The difficulty of ASD in controlling timely response to stimuli is a motor behavioural function of cerebellum in associative learning. Auditory, visual and oculomotor response also failed to be modulated and reproduced consistently independent of the stimulus duration again strengthened the assertion that adaptive timing function as controlled by cerebellum was missing in ASD. The defective lesions are believed to be localized to a specific part of the interposed nucleus in the deep cerebellar nuclei (DCN) [17-20]. Lastly, individuals resulted from cerebellar injuries clinically behave with similar cognitive developmental impairments as in autism [21,22]. At this juncture, emotional disinhibition, associative learning, motor planning, visual, auditory and verbal disability was evidently shown to be correlated with cerebellar developmental aberrancy, dysfunction and morphological abnormalities in ASD which may take place as early as in-utero neonatal period. The pathogenetic role of the cerebellum in the development in ASD is also in consistent with its long embryological ontological development as endogenous sonic hedgehog signalling stimulates rapid proliferation of cerebellar granule neuron progenitors (CGNPs) in the external granule layer (EGL) during early in utero neonatal development into late neonatal period [23]. This prolonged period of embryogenesis theoretically provides a long window to mutagenesis and probable exposure to environmental toxic insults. The importance of the cerebellum in the motor development in ASD is also related to the evolution of humans into bipedalism which is believed to be a requisite for higher cognitive functions as explained by the cerebellum expansion theory. An upright posture mandated Homo sapiens to have a smaller rostral neocortex but bigger volume cerebellum caudally. An expansion of the lateral lobes of the cerebellum act as a back-fire station actively feedforward input to the neocortex in motor planning, higher cognitive activities, sensorimotor and emotional modulation.

Output: contrast


Input: Claim: The blood-brain barrier protects the brain from harmful substances. [SEP] Text: [24, 76, 142, 143]). That technique showed that in apparently isotropic regions of brain the spread of fluorescent indicators appears symmetrical over distances of at least 100 µm from a point source (for examples see [24]), indicating that molecules within ISF can reach perivascular spaces in any direction and in good time by diffusion with no evidence for preferential movement towards either arterioles or venules. However, that technique was applied using a water immersion microscope objective after opening the skull and dura to allow access [142]. The open skull and dura may have perturbed flow in the parenchyma. (There is good evidence that cisternal puncture changes flow in the basal cisterns and subarachnoid spaces [25, 89]). Symmetrical spread has now been convincingly confirmed in a systematic study using both direct observation through a cranial window after injection of fluorescently labelled dextrans and recovery from photobleaching [79]. However, it should be noted that the window was glazed after dye injection and hence only shortly before observations were made. Smith et al. [79] have also found (1) that the dependence of the rate of movements within the parenchyma on the size of the solute is close to that expected if the movement occurs by diffusion; (2) that, in contrast to the report of Iliff et al. [25], the amounts of solutes entering the parenchyma are similar in Aqp4+/+ and Aqp4−/− mice; and (3) that local movement of solutes in the parenchyma is not impaired just after cardiorespiratory arrest. They conclude that “these results do not support glymphatic, convective solute transport in brain parenchyma. ” In reply to point (2) a group of researchers have posted an un-refereed summary of their experience that comparing three different Aqp4 knockout transgenic lines, including the cell line used by Smith et al. [79], Aqp4 does support “fluid and solute transport and efflux in brain in accordance with the glymphatic system model” [144]. The role of Aqp4 is discussed further in [140]. Pizzo et al. [16] have looked at the distribution of IgG and much smaller single domain antibodies after cisternal infusion.

Output: pass


Input: Claim: Gene expression analysis helps understand cellular responses to stimuli. [SEP] Text: Mutual information of and NSM neurons, redundancy and optimal input distribution of the whole circuit by food level across genotypes. Download elife-24040-fig1-data5-v1. xlsx Figure 1—figure supplement 1 Download asset Open asset Schematic of experimental and analytical workflow. (A) Experimental procedure for imaging gene expression responses to different food levels in adult C. elegans. Animals carrying fluorescent reporters were cultured and exposed to six food levels. A custom microfluidics-based platform was used for quantitative high-throughput imaging of the reporters. (B) Image analysis pipeline to identify individual neurons and quantify their fluorescence. (C) Information theoretic analysis for dissecting coding strategy in multicellular gene expression circuits. We first used a kernel density estimator to obtain gene expression response probabilities from our data. Next, we obtained theoptimal food distributions and the maximal mutual information between food stimuli and gene expression response. This analysis highlights the relationships between several parameters that describe the multi-neuron gene expression responses (light green boxes) and their contributions to the overall encoding strategy (dark green box). Figure 1—figure supplement 2 Download asset Open asset Experimental variability. (A) Animals carrying Pdaf-7::mCherry and Pdaf-7::Venus at different genomic locations were used to estimate experimental variability. (B) The strain described in (A) was shifted to four different food levels (legend) and then imaged simultaneously for mCherry and Venus fluorescence. The graph shows a good correlation between mCherry and Venus reporter expression (R=0. 8319). A total of 400 animals were imaged in this experiment. Figure 1—figure supplement 3 Download asset Open asset Neurons differ in their optimal input distributions. Optimal input distributions obtained by maximizing the information encoded individually by and NSM neurons qualitatively differ. This feature may allow different neurons to detect different food input levels to broaden the sensory range of the whole circuit. The optimal input distribution for each neuron also differ by genotype: (A) wild-type, (B) tph-1(-) mutants, (C) daf-7(-) mutants, and (D) tph-1(-); daf-7(-) double mutants. Uncertainties are obtained from sampling the 80% of the data and taking the standard deviation.

Output: corroborate


Input: Claim: All behaviors can be understood solely through neural circuitry. [SEP] Text: The most recent period of human evolution showed a disproportionate increase in the relative size of the cerebellum to neocortex. The cerebellum compared to rest of the brain, has been increasing while the cerebral cortex decreasing in size. The cerebellum lateral hemispheres are three times bigger in size in humans than monkeys. Thus, the expansion of the cerebellum is an important milestone during Hominidae evolution especially in the evolvment of motor tasks, visual-spatial skills, higher cognitive emotional skills and learning which is tightly bind to the rest of the brain [24,25]. The neocortex Anatomical mapping of the cerebellum using functional MRI suggest more than half of the cerebellar cortex is interconnected with association zones of the cerebral cortex [26]. Post mortem anatomical survey has shown smaller cortical cell column in the prefrontal and temporal cortex in ASD [27]. Brain volume growth is also different compared with the norm with a smaller head circumference at birth followed by a rapid increase in size and volume of brain especially the white matter after one month of age; 37% of autistic children were reported to have developmental macrocephaly by 4 years of age [28,29]. This is in contrast with the previously discussed evolutionary reduction in size of neocortex compared to cerebellum. The most striking cortical feature in ASD is neocortical asymmetries with the greatest amounts of cortical cells in higher-order association cortices and a disproportional rightward asymmetrical cortex in the autistic individuals [30]. Reversal of the normal language-related frontal cortex asymmetry was also noted [31]. fMRI showed a reduction of activation in the dorsolateral prefrontal cortex and reduction of both superior temporal cortex and temporal frontal cortical areas in making inferences from viewing another individual eye; hence absence of eye contact with other [32,33]. More delicate visually paced finger movements which needed refined coordination was reduced like writing in the activated cortical area but involved in a different area [34]. During sentence comprehension task, a reverse weighted activation in Wernicke’s area more than the normally used Broca’s area was seen [35]. Event-related potential (ERP) studies, which have been used to study brain dynamics, showed that higher brain cognitive functions in ASD were altered. ERP P300 covaries with stimulus probability and task relevance showed that language stimuli at left hemisphere were smaller and not at right hemisphere.

Output: contrast


Input: Claim: The blood-brain barrier protects the brain from harmful substances. [SEP] Text: They found that the antibodies rapidly enter the perivascular spaces of blood vessels of all sizes be they arteries, veins or capillaries. The distribution within the parenchyma was as expected for diffusion including the differences between the profiles for different sizes of fluorescent marker. Further discussion supporting the importance of diffusion over bulk flow in the extracellular spaces of the parenchyma can be found in [40]. Perivascular solute movements are considered further in Sect. 5. 7. 1. 2. 3. 2. 2 Is there a glymphatic circulation? The answer depends partly on what one means by glymphatic circulation. If the meaning is “Convective glymphatic fluxes of CSF and ISF propel the waste products of neuron metabolism into the paravenous space” [136], then the answer is almost certainly no (compare [40, 140], though it should be noted that [54, 137] still argue in favour of the original glymphatic hypothesis). However, if glymphatic circulation is taken to mean only that there is a net inward periarterial flow, a net outward perivenous flow, and some connection between them, then the answer still isn’t known with any certainty. The results discussed above [24, 76, 79, 142, 143] provide powerful experimental support for the widely held view that a glymphatic circulation is not needed to explain solute movements over the short distances that are important in the parenchyma. Furthermore the calculations of Asgari et al. [73, 78], Jin et al. [77] and Holter et al. [80] (see also Footnote 8) suggest that flow through the interstitial spaces of grey matter or along the basement membranes of microvessels in the parenchyma is negligible. However, it is not yet clear that the available experimental results exclude the possibility that there is a net flow between the perivascular spaces of arterioles and venules that is large enough to complete a recirculation pathway inwards from CSF via periarterial routes and back to CSF via perivenous routes. Footnote 9 If that flow exists it could be important for transport of solutes over the relatively large distances encountered along the perivascular spaces (see e. g. [76]) while still being negligible relative to diffusion for transport over the relatively short distances within the parenchyma.

Output: pass


Input: Claim: Gene expression analysis helps understand cellular responses to stimuli. [SEP] Text: Figure 1—figure supplement 4 Download asset Open asset Robustness of information theoretic analyses. (A) Information (MI/channel capacity) encoded by food-responsive gene expression in wild-type animals computed using different methodologies for density estimation. From left to right: plug-in method, least squares cross-validation, and smoothing cross-validation (kernel density estimation with fixed bandwidth selection), balloon estimator (kNN), Jack-knife correction of sample size bias. All this methods result in similar information values. (B) Information encoded by food-responsive gene expression in wild-type, tph-1(-), daf-7(-), and tph-1(-); daf-7(-) animals. The relative changes in information between different approaches do not display significant differences. (C) and (D) illustrate the same analysis for redundancy. The switch from redundancy in wild-type to synergy in daf-7(-) is consistently present for all the methodologies used. (E) Details of jack-knife analysis for information and redundancy across all genotypes. Information and redundancy values are calculated using a fraction of the total data indicated in the x-axis. Dashed line (bottom) indicates a redundancy value of zero, separating redundancy and synergy. Both information and redundancy are stable to the sample size, as indicated by the flat lines of best fit. Error bars are standard deviation derived from sampling 80% of the data. Figure 1—figure supplement 5 Download asset Open asset Information and redundancy by food level. (A) The sum of information encoded by and NSM for each food level across different genotypes is indicated by stacked bars. Information in each neuron is indicated by the legend (bottom right). Dashed lines indicate the information encoded by the combinatorial gene expression in the whole circuit, which is constant across food levels (see Supplemental Materials and methods for mathematical details). (B) Redundancy values across food levels for each genotype. (C) The optimal distribution of food input that maximizes information encoded by the whole circuit. Figure 2 Download asset Open asset Signal and noise correlations influence redundancy and synergy. (A–B) Hypothetical expression distributions of two neurons at three food levels, illustrating signal and noise correlations and their effects on redundancy (Schneidman et al. , 2003). Centre: their 2D distributions. Top and side: the distributions of each neuron.

Output: corroborate


Input: Claim: All behaviors can be understood solely through neural circuitry. [SEP] Text: However, no differences were found for musical chord stimuli consistent with the notion that adaptive timing for musical cord stimuli (non-language) develop normally in ASD and involved in different circuitry whereas phonetic stimuli (language-related) auditory stimuli is affected in autism [36]. This inappropriateness of phonetic language response greatly affected the ASD individual’s socialization, communication, restricted patterns behaviour and learning skills [37]. Cortical deficiencies also impaired the ASD from symbolic thinking, learning, imaginary play to even mental retardation. The thalamus, amygdala and limbic system Post mortem studies revealed abnormalities in the amygdala, hippocampus and ventral temporal cortex. fMRI has shown altered in the size and volume in amygdala in autism [38,39]. The amygdala is of particular significance in ASD as negative emotional reactivity secondary to noise, smells or light will cause instantaneous arousal in some ASD. It has been proposed that an under aroused emotional depression in the amygdala and related affected area typify the neural dynamics autistic behaviour [11,40,41]. The limbic system which better described as the paleomammalian cortex, consists of the thalamus, olfactory bulbs, hippocampus, hypothalamus, anterior thalamic nuclei, mammillary body and the septum pellucidum, the amygdala and its associated nuclei control emotions, body internal motivation, drive like desires, olfaction and long-term memory. The anterior nuclei of the thalamus are actively involved in the memory process. The thalamus with its different nuclei regulates many body vital autonomic functions like sleep, autonomic nervous, cardiac, respiratory, intestinal and auto-immune functions. As the thalamus is involved in ASD, many bodily innate unconscious autonomic defense and survival neuro-endocrine pathways may be affected in various degrees like autoimmunity, allergic hypersensitization, gut motility, pain and ultimately sleep disturbances. Neuronal circuits aberrancy between the cerebellum, neocortex, thalamus, amygdala associated with cognitive, motor and emotional behaviour in ASD The existence of a cerebello-thalamic circuitry with increasing activation was seen in ASD [42]. Activation of the ipsilateral anterior cerebellar hemisphere is increased in magnitude in spatial extent during motor task in ASD individuals in addition to atypical activation in contralateral and posterior cerebellar regions.

Output: contrast


Input: Claim: The blood-brain barrier protects the brain from harmful substances. [SEP] Text: Footnote 11 Fong [161] has reviewed many of the attempts to predict permeabilities of the blood–brain barrier to solutes. He concludes that the most important factors for neutral solutes are: the free energy required to remove the solute from water; the free energy gained from the interactions of the solute with the membrane core, usually modelled by its interaction with n-octanol; the dipole moment of the solute; and lastly its molecular volume. Increases in molecular volume per se decrease permeability. Geldenhuys et al. [172] has provided many useful 4. 2 Transporters at the blood–brain barrierThe membranes of the endothelial cells that constitute the blood–brain barrier possess transporters for many different types of solutes. These transporters may be present on luminal, abluminal or both surfaces of the endothelial cells. Prominent among them are transporters for common nutrients and waste products of metabolism: GLUT1 for glucose, MCT1 for lactic acid and other small monocarboxylic acids, a range of transporters for amino acids, and several for nucleosides. There are also ion transporters involved in maintenance of the ionic composition of the brain fluids. Many of the transporters are specific and are involved in moving the normal constituents of brain extracellular fluid. Some of these are considered in Sect. 5. In addition there are also less specific transporters. Many of these can mediate efflux of a variety of other substrates including many exogenous substances and toxic occasional products of metabolism. Evidence concerning the presence and identity of many of these transporters has been reviewed elsewhere with studies being conducted primarily at the level of transcript [173,174,175,176,177,178], protein [31, 44, 58, 176, 179,180,181,182,183,184,185,186,187,188] and/or function [4, 20, 31, 46, 55,56,57, 179, 189,190,191,192,193,194,195,196,197,198,199,200]. The reports by Roberts et al. [180] and Kubo et al. [58] and reviews by Hawkins et al.

Output: pass


Input: Claim: Gene expression analysis helps understand cellular responses to stimuli. [SEP] Text: Signal correlation between two neurons across three food levels, and noise correlation at one selected food level are denoted by dotted lines marked ‘S’ and ‘N’ in (A) and (B), respectively. (C) shows how signal and noise correlations are related to redundancy and synergy as previously established (Schneidman et al. , 2003). When signal correlations are higher (A), each neuron provides similar information (top and side distributions), reflecting redundancy. When noise correlations are higher (B), the combinatorial expression shows reduced overlaps and contains more information than individual neurons, providing synergy. (D–E) The effects of daf-7 and tph-1 on redundancy and synergy are explained by their effects on the signal correlation (D) and noise correlation (E). (F) Signal and noise correlation in each genotype and their relation to redundancy and synergy as indicated in (C). Figure 2—source data 1 Signal and noise correlations across genotypes. Download elife-24040-fig2-data1-v1. xlsx Figure 3 with 1 supplement Download asset Open asset Interplay between noise and correlation affects redundancy. (A) Heat maps showing redundancy when correlation and noise are scaled from their baseline values in wild-type and mutants. Redundancy values are indicated by legend. Contour lines denote equal redundancy. The number of contour lines crossed along each axis indicates the sensitivity to that parameter. (B) The steps leading from genes to coding strategy. Figure 3—figure supplement 1 Download asset Open asset Sensitivity analysis of channel capacity, signal, and noise correlation. Heat maps showing how channel capacity (A), signal correlation (B) and noise correlation (C) vary under a rescaling of the baseline covariance matrix. For this analysis, response distributions were modeled using multivariate normal distributions (see 10. 7554/eLife. 24040. 016 Figure 4 with 1 supplement Download asset Open asset Computational model reveals advantages of redundancy. (A) Model for information encoding and transmission, where three sensors activate one target that integrates their signals linearly (see 10. 7554/eLife. 24040. 017 Figure 4—figure supplement 1 Download asset Open asset Gaussian model of sensory neurons and information transmission. (A) Illustration of the model. Sk represent single sensors receiving information from the binary input. The sensor response is then combined linearly by the output.

Output: corroborate


Input: Claim: All behaviors can be understood solely through neural circuitry. [SEP] Text: Moreover, increased activation was correlated with the degree of cerebellar structural abnormality. This provides good evidence dysfunction of the autistic cerebellum may be reflection of cerebellar anatomical abnormality. Neurofunctional deficit might be a key contributor to the development of certain diagnostic features of autism like impaired communication and social interaction, restricted interests, and repetitive behaviours [43]. Social impairment was negatively correlated with the degree of anisotropy of the superior cerebellar peduncle, the primary output path of the cerebellum. Thus, cerebellar white matter decreases, ASD symptoms increases [44,45]. The thalamic nuclei like the relay nuclei receive specific definitive electrical signals and project this to the corresponding functional domains of distinct area in the cerebral cortex. The ventral posterolateral nuclei (VPL), ventral posteromedial nuclei (VPM), medial geniculate (MG) and lateral geniculate (LG) nuclei are thalamic nuclei which relay primary sensations to the cortex. The ventral lateral (VL) nuclei give feedback signals to the cerebellum while the ventral anterior nucleus (VAN) feedback basal ganglion output. Thus, a synaptic connective wiring networks are in place between the motor regions; cerebellum, basal ganglion and the conscious executor of the brain; the cerebral cortex. The association nuclei receive signals input from the cerebral cortex which can be inhibitory and project back to the latter in cortex association areas so as to regulate activity. The reticular nucleus encapsulated most of the thalamus and receives input from the cerebral cortex and dorsal thalamic nuclei. The thalamic reticular nucleus receives neuronal projections from the external segment of the Globus Pallidus. Pallidus is a component of basal ganglion of the brain which involved in the regulation of voluntary movement. Through disinhibition, neuronal signals were sent to the thalamus resulting in initiation of movement [46]. Thus, each nucleus of the thalamus is capable at rest in dispatching electrical signals and communications to specific anatomical domains to the corresponding cerebral cortex and areas of motor function. Through its association neurons, the signals are feedback to the thalamus and wired to the other structures like the amygdala which in turn flow back to the cortex.

Output: contrast


Input: Claim: The blood-brain barrier protects the brain from harmful substances. [SEP] Text: The principal known transporters in the rat are shown. In human OAT3 is abluminal, while both OATP1A4 and OATP2B1 are present on both membranes. The ABC efflux pumps, P-gp, 4 and MRP5, are all localized to the luminal, plasma facing, membrane. and Oatp transporters are exchangers (see Footnote 12). Localizations from [180] and the 3. 2). There is ample further evidence (see the 4. 3 Efflux by transcytosisTranscytosis is much less prevalent across the endothelial cells of the blood–brain barrier than across those of peripheral capillaries [248,249,250,251]. Nevertheless both adsorptive mediated transcytosis (AMT) and receptor mediated transcytosis (RMT) are still likely to be important mechanisms for the transfer of some large substrates across the blood–brain barrier. The initial event in AMT is the adsorption of usually positive substrates onto the surfaces of caveolae, while that for RMT is binding of the substrate to specific receptors that are in or become incorporated into clathrin coated pits. In both cases at the blood–brain barrier this leads to endocytosis followed by delivery of a substantial fraction of the contents of the resulting vesicles to the opposite membrane for exit, possibly by exocytosis [49, 63, 252]. AMT is thought to account for much of the influx into the brain of histones [253], “cell penetrating peptides” [49, 251, 254], HIV [255, 256], and cargos conjugated to the lectin wheat germ agglutinin [257] and to underlie the increase in “generalized permeability” caused by protamine [258]. The downsides of AMT are that it is relatively non-selective for substrates [256] and that it occurs in many cells throughout the body. In addition there is little if any evidence that it occurs in the direction from brain to blood [257, 259]. While RMT also occurs throughout the body, transport by this mechanism depends on interaction of the substrates with specific receptors that may be found primarily in specific locations such as the blood–brain barrier. In addition there is evidence that RMT can occur in either direction, i. e.

Output: contrast


Input: Claim: Gene expression analysis helps understand cellular responses to stimuli. [SEP] Text: -19 PreprintsProtocolsVideosJournalsTools & a 10. 21203/rs. 3. rs-403172/v1This work is licensed under a CC BY 4. 0 LicenseStatus:PostedVersion 1posted You are reading this latest preprint versionAbstractLeishmania donovani is an obligate intracellular parasite of human that causes a dreadful visceral infection that may involve liver, spleen, bone marrow, and lymph nodes. The specific feature of the species influences its genetics. Changes in parasite adaptation to different environment, development of silent genes and parasite progression through its lifecycle may be determined by transcriptional organizations affecting its gene expression. Hence, Insilco analysis of Leishmania donovani BPK282A1 genome was performed to predict the promoter and regulatory elements involved in gene expression. Forty putative genes of Leishmania donovani BPK282A1 genes were obtained from for and investigated using bioinformatic tools, such as suite, CpG island finder, GOMo and CLC Genomics Workbench. In this analysis, the number of Sites (TSSs) in promoter regions of Leishmania donovani BPK282A1 varied greatly between 1 and 4 with majority (60%) of them having two or more TSSs. The study also revealed seven candidate motifs in the promoter regions of the gene. The common promoter motif for all Leishmania donovani BPK282A1 genes was MI with an E-value of 4. 0e-116. Six of the identified motifs were related to zinc finger proteins that bind to the GC-rich regions in DNA. The study also revealed that most of both the promoter and the gene body regions contain at least one CpG island. Restriction analysis using MspI enzyme showed that Leishmania donovani BPK282A1 genes were CpG rich. In conclusion, the investigation unfolded expression regulation of Leishmania donovani BPK282A1 genes contributing to development of a robust drug and vaccine that targets the regulatory regions. ParasitologyEpigenetics & GenomicsLeishmania donovaniPromoter regionTranscription factorMotifCpGFiguresFigure 1Figure 2Figure 31. spp.

Output: corroborate


Input: Claim: All behaviors can be understood solely through neural circuitry. [SEP] Text: However, in the case of ASD with its multifactorial aetiologies, hypoactivity of orbitofrontal cortex or amygdala which provides motivationally directed goals, incentives or intentions drive improperly function, and this initially movement driven, thalamus modulated cortical emotional conscious motivational neuronal circuit will be disrupted and may result an arena of behaviour, emotional, cognitive, movement and autonomic nervous system pathological states. Some authorities have reviewed this as an exhibition of failure of reward processing noted in individuals diagnosed with ASD [47-49]. As the ASD amygdala emotionally depressed, hypofrontal blocking fails; individuals become mindless; pleasantness, security and reward signals are not feedback and received by the amygdala; without reward subsequent social learning become non-existent. Individuals with ASD exhibited a specific behavioral insensitivity to social rewards like nonresponse to a smiling greeting face. ASD individual autonomic response was also impaired during social reward studies as children with autism exhibited decreased pupillary dilation when looking at happy faces [50,51]. This may be due to inactivity of the amygdala and incoherence and mismatching of thalamocortical circuitry. Similarly, children with autism failed to gaze orient to naturally occurring social stimuli also provide further evidence this reward circuits interconnecting, the neocortex, thalamus, cerebellum and amygdala are deficit in ASD. Even in the case of hunger as a drive to amygdala is emotionally depressed with compared to normal control children. All these suggested that the impaired social skills, learning and motor behavior may result from a reduced reward feeling in response to social stimuli. The involvements of cerebellum in deficits in social reward has previously exemplified by the paradigm of eyeblink conditioning which is absent in the afferents to the cerebellum can be readily explained by the diminution of the adaptive timely response. This absence of adaptive timely response which is crucial in a vast array of motor behavioural function of cerebellum in associative, auditory, visual and oculomotor learning may be secondary to inactivation of the cerebellar dentate nuclei operant to a food reward within its interposed nuclei in deep cerebellar complex.

Output: contrast


Input: Claim: The blood-brain barrier protects the brain from harmful substances. [SEP] Text: So though there is general agreement that holo-transferrin interacts with TfR, which then mediates endocytosis of the iron/transferrin/receptor complex into the endothelial cells, there has been controversy over the subsequent steps in the transfers of transferrin and iron into the brain. Assuming that holo-transferrin is indeed directly transcytosed across the blood–brain barrier, then the limited net entry observed of transferrin to the brain implies that there must be transcytosis of transferrin without iron, apo-transferrin, back out of the brain. Alternatively if the iron is dissociated from the transferrin within the endothelial cells, it is likely that there is exocytosis of apo-transferrin on both sides of the cells (see [280,281,282] and the footnoteFootnote 13 for further discussion). Little is known about transport of transferrin out of the brain. There have been reports that labelled apo-transferrin injected into the brain can be transported from brain to blood, but it is not clear how important this is under normal conditions. Banks et al. [60] found that the apo-transferrin was removed from the brain faster than albumin, implying the existence of a route other than washout via CSF. However, subsequently Moos and Morgan [278] did not confirm this result. By contrast Zhang and Pardridge [61] found an early component of loss of injected apo-transferrin, half-life 39 min, which was much faster than that for loss of injected 70 kDa-dextran. Furthermore this rapid component was inhibited by cold apo-transferrin, i. e. there was competition, with an apparent dissociation constant of less than 30 nM implying interaction with a specific receptor which was presumed to be the receptor protein detected by OX26, i. e. TfR. As these studies on transferrin efflux are substantially older than the studies on iron uptake linked to transferrin, further investigation of transferrin transport from brain to blood might be informative. 5 Clearance of specific substancesThere are certain species that are critical for normal brain function and that must be transported into or out of the brain rapidly and in large quantities. The most prominent of these are O2, CO2, water and glucose.

Output: pass


Input: Claim: Gene expression analysis helps understand cellular responses to stimuli. [SEP] Text: Leishmania donovani appears to have two distinct genomic features influencing its genetics; where there are different copy numbers within an individual chromosome or where chromosome dosage varies among clonal population of a cell. On the other hand, once infection occurs it develops a mechanism that weakens microbicidal activity of macrophages interfering with the expression of Major Histocompatibility-II (MHC II) molecules after subsequent stimulation with interferon-γ (IFN-γ) (Buates and Matlashewski 2001). The parasites utilize various proteins and glycoproteins to interact with host cells establishing a long term infection with a clinical presentation of visceral Leishmaniasis (Mukherjee, Chakraborty, and Chakrabarti 2016). Several complications may result from visceral Leishmaniasis that include hepatic cirrhosis, necrotizing oral infection, pulmonary tuberculosis, ocular complications, disseminated intravascular coagulations, nephritic syndrome, glomerulonephritis, neutropenia (Meyers et al. 2016), immunosuppression and pancytopenia (Mcgwire and Satoskar 2013) leading to concurrent or inter-current infections finally culminating in death (Meyers et al. 2016). There are various types of therapies to treat leishmaniasis that include first line and second line regimens. The use of the drugs available may rely on regional guidelines and varies among several localities. Despite availability and accessibility of the drugs, ineffectiveness of treatment is increasing due to parasite resistance to the available drugs (Mcgwire and Satoskar 2013). Changes in parasite adaptation to different environment, development of silent genes and parasite progression through its lifecycle may be determined by transcriptional organizations where regulatory elements are located; i. e. the Sites (TSS) (Duncan et al. 2011). Leishmania donovani mainly loses its virulence through transcriptional and translational regulations (Sinha et al. 2018). Therefore, understanding the regulatory elements such as (TFs), (TFBSs) and CpG islands in Leishmania donovani genome that determines its gene expression is helpful to fully characterize its molecular mechanisms and design effective drugs, vaccines and other control strategies. 1. 1 1. 1.

Output: corroborate


Input: Claim: All behaviors can be understood solely through neural circuitry. [SEP] Text: sum, the above revisit of the inter-connectiveness and relationship between human cerebellum, neocortex, thalamus, amygdala and its associated excitatory feed forward and inhibitory feedback circuitries incorporating the rewarding hypothesis, emotionally depressed amygdala, adaptive timing failed processing in cerebellum and no theory of mind is not to imply that this is what exactly happening in the pathogenesis of ASD. In fact, as ASD is such a diverse, complex and progressive cognitive, emotional, motor and autonomic syndrome, it is difficult to solve all the observed phenomenon in one coherent theory. On the contrary, it is hope that this mini-review may spark discussion, falsification and better models through scientific arguments and repeatable controlled experiments; serve as a move forward exploration and enquiry about the entangled puzzling causes of ADS, in addition to the already known genetic, neurotransmitters and toxins corroboration. 395. Chast P, (2012) Autism risk factors; genes environment and gene-environment interactions. Neurosci 14: 281-292. (2017) Environmental risk factors for autism; an evidence-based review of systematic reviews and meta-analyses. 8: 13. (2003) Model of autism: Increased ratio of excitation/inhibition in key neural systems. Behav 2: 255-267. (2012) Glutamate mediated signaling in the pathoâ€physiology of autism spectrum disorders. Behav 100: 841-849. (2012) GABA system dysfunction in autism and related disorders: from synapse to symptoms. Rev 36: 2044â€“2055. (2001) Postmortem brain abnormalities of the glutamate neurotransmitter system in autism. Neurology 57: 1618-1628. Grossberg S, (2006) Neural dynamics of Autistic Bahaviors; Cognitive, Emotional, and timing substrates. 113: 483-525. (2002) Purkinje cell size is reduced in cerebellum of patients in autism. Neurobiol 22: 171-175. Courchesne E, Yeung-(1988) Hypoplasia of cerebellar vermal lobules VI and VII in autism. N Med 318: 1349-1354. (2011) Spectrum of neurodevelopmental disabilities in children with cerebellar malformations. 53: 409-416.

Output: contrast


Input: Claim: The blood-brain barrier protects the brain from harmful substances. [SEP] Text: GLUT1 and MCT1 are present on endothelial cells; GLUT1 and MCT4 on astrocytesFull size image It has long been known that glucose is able to cross the blood–brain barrier rapidly [189, 299,300,301,302]. Crone [299] found that at low concentrations as much as 50% of the glucose arriving in the arterial blood could be extracted in a single pass, but that this percentage decreased with concentration, falling to 28% at 5 mM and ~ 14% at 14 mM. This extensive but saturable transport implies the presence of a specific transporter, which as stated above is GLUT1 (SLC2A1) [303,304,305]. The expression of GLUT1 in the endothelial cell membranes has been measured in several different ways: by cytochalasin-B binding, by specific antibody binding, and by proteomic methods (see Table 2 for 0. 55 mol day−1 = 380 µmol min−1 [295, 296] or, for a 1400 g brain, 270 nmol g−1 min−1. For a difference between the concentrations in plasma and ISF of 5 mM this corresponds to CL ~ 54 µL g−1 min−1. In isolated perfused dog brains Betz et al. [302] measured the loss of glucose from the blood flow through the brain and found about 0. 6 µmol g−1 min−1 at 6 mM from which at this concentration CL = 100 µL g−1 min−1. Hawkins [307] lists values ranging from 158 to 352 µL g−1 min−1 (at 6 mM glucose) depending on brain region (inferior colliculus the highest). Note that the first two of the estimates above are based on the net flux of glucose while the values listed by Hawkins are based on the unidirectional influx. Because all of these estimates far exceed the clearance expected for perivascular efflux, ~ 1 µL g−1 min−1 (see Sect. 3 and Table 1), the perivascular route is likely to be of minor importance. Cutler and Sipe [301] using anaesthetized cats, Bachelard et al. [308, 309] using anaesthetized rats and Betz et al.

Output: pass


Input: Claim: Gene expression analysis helps understand cellular responses to stimuli. [SEP] Text: 1 General objective The general objective of this study was to predict promoter and regulatory elements involved in Leishmania donovani BPK282A1 genes expression 1. 1. 2 Specific objectives To detect transcription start sites and determine promoter regions of Leishmania donovani BPK282A1 genes To recognize common motifs and transcription factors among Leishmania donovani BPK282A1 genes To quest for gene ontology for identified regulatory elements To quest for CpG islands in Leishmania donovani BPK282A1 gene body and promoter regions 2. Method2. 1 TSSs and promotor regions determination for Leishmania donovani BPK282A1 genes Forty functionally putative genes of Leishmania donovani BPK282A1 genome were obtained from for (NCBI) genome database (for n. d. ) on Nov 3, 2020 and analyzed using online regulatory elements determination tools. The corresponding TSS of each gene was analyzed using an online (NNPP version 2. 2) (BDGP: n. d. ), a tool that helps to find promoters in a (DNA) sequences of eukaryotic and prokaryotic cells. Herein, at least 1kb upstream of the start codon for each gene was excised as it was done by Dinku and colleague (Dinka and Milkesa 2020). The excised segments were fitted to NNPP version 2. 2 by setting the minimum standard predictive score (between 0 and 1) with a cut off value of 0. 8 (Kanhere and Bansal 2005). In conditions where there were two or more TSSs, the one having the highest prediction value was considered as statistically significant (Michaloski et al. 2011). 2. 2 Motifs and transcription factors identification The identified promoter sequences were transferred to another online resource, motifs for (MEME) suit version 5. 3. 0 (Introduction - MEME Suite n. d. ); and analyzed for common candidate motifs (- MEME Suite n. d. ). Motif is an approximate sequence pattern that occurs repeatedly in a group of related sequences. MEME discovers novel, un-gapped motifs (recurring, fixed-length patterns) in the identified sequences being submitted. It is a motif-based sequence analysis tool that splits variable-length patterns into two or more separate motifs.

Output: corroborate


Input: Claim: All behaviors can be understood solely through neural circuitry. [SEP] Text: (2000) The functional neuro-anatomy of social behaviour: Changes in cerebral blood flow when people with autistic disorder process facial expressions. Brain 123: 2203-2212. (1999) Evidence of altered energy metabolism in autistic children. Progress in Neuropsychopharmacology and Biological Psychiatry. 23: 635-641. (2004) Temporal processing deficits in high-functioning children in autism. Psychol 95: 269-282. (2015) Cerebellar associative sensory learning defects in five mouse autism models. eLife 4: e06085. . (1994) A neural model of timed response learning in the cerebellum. 7: 1101-1114. (1996) Metabotropic glutamate receptor activation in cerebellar Purkinje cells as substrate for adaptive timing of the classically conditioned eye blink response. Journal of Neuroscience 16: 3760-3774. (2010) Cognitive and affective disturbances following focal cerebellar damage in adults; a neuropsychological and SPECT study. Cortex 46; 869-879. (1995) Developmental injury to the cerebellum following perinatal Borna diseases virus infection. Res 90: 45-53. (2004) Spatial pattern of sonic hedgehog signaling through Gli genes during cerebellum development. Development 131: 5581-5590. (2016) Thinking, Walking, Talking: Function. Health 4: 94. Mendoza G, (2014) Motor system evolution and the emergence of high cognitive functions. 122: 73-93. (2011) The organization of the human cerebellum estimated by intrinsic functional connectivity. J Neurophysiol 106: 2322-2345. (2002) Minicolumnar pathology in autism. Neurology 58: 428-432. (2003) Evidence of Brain overgrowth in the first year of life in autism. JAMA 290: 337-344. (1997) Macrocephaly in children and adults with autism. 36: 282-290. â€™Brien LM, kennedy D, et al. (2005) Brain asymmetries in autism and developmental language disorder: a nested whole-brain analysis. Brain 128: 213-226. (2004) Language-association cortex asymmetry in autism and specific language impairment. 56: 755-756.

Output: contrast


Input: Claim: The blood-brain barrier protects the brain from harmful substances. [SEP] Text: The possibility that water permeability of GLUT1 may or may not be important at the blood–brain barrier [320] was considered in Section 4. 3. 6, footnote 17 of [4]). While arguments for “why a carrier” are speculative, the structural and kinetic evidence, reviewed in the following subsections, leave little doubt but that glucose transport across the membranes of the endothelial cells of the blood–brain barrier is mediated by a carrier. 5. 3. 1 Structure of GLUT1 (SLC2A1) and the kinetics of the glucose transport it mediates in red blood cellsA crystal structure for GLUT1 has been obtained using a GLUT1 construct purified from an expression system (see Fig. 12) [321]. In this structure a bundle of α-helices spans the membrane surrounding an inner cavity open at the cytoplasmic end. This structure and those for related transporters (for 1. The structure of full-length human GLUT1 containing two point mutations (N45T, E329Q) was determined in an inward-open conformation. The side and cytoplasmic views are shown. The corresponding transmembrane segments in the four 3-helix repeats are coloured the same. The extracellular and intracellular helices are coloured blue and orange, respectively. A slab of cut- open view of the surface electrostatic potential, which was calculated with PyMol50, is shown on the right to facilitate visualization of the inward-facing cavity. IC indicates intracellular helix. Reprinted by permission from from Nature 510, 121–126, Crystal structure of the human glucose transporter GLUT1 by Deng et al. [321]Full size image Since GLUT1 is highly expressed in red blood cells, they have been used as the most convenient system in which to study the kinetics of its transport. There are two prominent features revealed by these studies that must be accommodated in any model. On the one hand the normal net transport of glucose occurs without input of energy from any source other than the concentration gradient, on the other hand downhill movement of one type of sugar can be coupled to uphill movement of another (see Fig. 13), a phenomenon called counter-flow or counter-transport [322,323,324,325].

Output: pass


Input: Claim: Gene expression analysis helps understand cellular responses to stimuli. [SEP] Text: donovani BPK282A1 genome promoter regions with their respective binding sites and e-values Discovered motif Number (%) of promoters containing each one of the motifs E-value Motif width Total number of binding sites MI 34 (85) 4. 0e-116 27 34 MII 40 (100) 2. 6e-095 41 40 MIII 39 (97. 5) 5. 4e-051 41 39 MIV 40 (100) 8. 8e-044 21 40 MV 29 (72. 5) 9. 9e-038 21 29 MVI 40 (100) 3. 4e-032 21 40 MVII 29 (72. 5) 5. 0e-020 29 29 a web-based application was used for further analysis of the similarities between the identified common motif and other similar motifs which are publicly available in known registered biological databases of eukaryotes. Accordingly, the web-based tool was used three different databases, namely; jolma2013, 2018_CORE_vertebrates_non-redundant and uniprobe_mouse to search for similarities and 843, 579 and 386 motifs were used from each of the databases respectively and only seven matches similar to the submitted MI motif were identified. Six of the identified matches were closely related to zinc finger proteins that bind to the GC-rich regions in DNA and regulate various cellular functions. The remaining one of the matches was found to be related to AP2/B3-like transcriptional factor family protein which is found in Hordeum vulgare (barley) and the gene functions in vernalization. The possible binding candidate motifs of MI, suggested species, e-value and gene functions were presented in table 3. Table 3 Possible transcription factors that could bind to common candidate motif -value Corresponding gene Function zf-C2H2 Mus musculus 1. 36e+00 Gm397 Not specified C2H2 zinc finger factors Homo sapiens 2. 05e+00 RREB1 Increases expression of calcitonin, which may be involved in Ras/Raf-mediated cell differentiation AP2/B3-like transcriptional factor family protein Hordeum vulgare 3.

Output: corroborate


Input: Claim: All behaviors can be understood solely through neural circuitry. [SEP] Text: Neural systems underlying conflict processing have been well studied in the cognitive realm, but the extent to which these overlap with those underlying emotional conflict processing remains unclear. A novel adaptation of the AX Task (AX-CPT), a stimulus-response incompatibility paradigm, was examined that permits close comparison of emotional and cognitive conflict conditions, through the use of affectively-valenced facial expressions as the response modality. Methodology/Brain activity was monitored with functional magnetic resonance imaging (fMRI) during performance of the emotional AX-CPT. Emotional conflict was manipulated on a trial-by-trial basis, by requiring contextually pre-cued facial expressions to emotional probe stimuli (IAPS images) that were either affectively compatible (low-conflict) or incompatible (high-conflict). The emotion condition was contrasted against a matched cognitive condition that was identical in all respects, except that probe stimuli were emotionally neutral. Components of the brain cognitive control network, including dorsal anterior cingulate cortex (ACC) and lateral prefrontal cortex (PFC), showed conflict-related activation increases in both conditions, but with higher activity during emotion conditions. In contrast, emotion conflict effects were not found in regions associated with affective processing, such as rostral ACC. Conclusions/activation patterns provide evidence for a domain-general neural system that is active for both emotional and cognitive conflict processing. In line with previous behavioural evidence, greatest activity in these brain regions occurred when both emotional and cognitive influences additively combined to produce increased interference. Citation: (2011) of Emotional and Revealed through Facial Expressions. 6(3): e17635. de Beeck, University of Leuven, BelgiumReceived: December 5, 2010; Accepted: February 4, 2011; Published: March 9, 2011Copyright: © 2011 Chiew, Braver. This is an open-access 25. 5 years, SD = 5. 63) were scanned using fMRI while participating in the task. All fMRI participants were right-handed, native English speakers, and screened to ensure no neurological or psychiatric disorders, psychotropic medications, or other factors were present that contraindicated fMRI. Participants performed an emotional (Emotion condition) and non-emotional (Neutral condition) variant of the AX-CPT.

Output: contrast


Input: Claim: The blood-brain barrier protects the brain from harmful substances. [SEP] Text: A closely related phenomenon is trans-stimulation, an increase in influx when internal concentration is increased or an increase in efflux when external concentration is increased (see Fig. 13 and, for a quantitative example, 5. 5). The kinetics of the simple carrier model are complex even in the steady-state [325,326,327,328,329]. GLUT1 (SLC2A1) kinetics are complicated further by the added twist that the GLUT1 protein may exist in the membranes as part of a homo-tetramer, each capable of transport, but in a coupled manner such that transport through one affects the transport through the others [322, 330]. Given these and further complexities considered in the next section, it should not be surprising that definitive characterization of glucose transport at the blood–brain barrier remains elusive (see 5. 3. 2 Glucose transport kinetics at the blood–brain barrierTransport of glucose into and out of the brain is clearly more complex than that into and out of red blood cells. Firstly GLUT1 is needed in both membranes of the endothelial cells of the blood–brain barrier to allow the glucose to enter on one side and leave on the other. However, because the endothelial cells are very thin and correspondingly contain very little glucose, provided that the properties of the transport in the two membranes are similar, it is thought that the transport can still be described, at least qualitatively, as transport across a single barrier [331,332,333]. Secondly once across the blood–brain barrier, glucose is metabolized at a rate comparable to the rates of influx and efflux across the barrier while in red blood cells transport is much faster than metabolism. Thirdly there is also the technical difficulty that, with the important exception of the study in 1975 by Betz et al. [327], it has not proved possible to manipulate interstitial fluid glucose concentrations during the experiments. In most studies all that has been done is either to measure the extraction of glucose (total or labelled) from blood as described above or to measure the variation in the total amount of glucose present in the parenchyma with time as a function of glucose concentration in plasma. Mason et al. [334] compare the results obtained in many studies performed prior to 1992 but with the surprising omission of reference to studies from Betz’s group.

Output: pass


Input: Claim: Gene expression analysis helps understand cellular responses to stimuli. [SEP] Text: As stated by Dinka and colleague, genes may have one or more TSSs contributing to genetic variation of an organism (Dinka and Le 2018) which is in agreement with this study where the analysis revealed about forty (40%) percent of the genes had one TSS and sixty percent of them had two or more TSSs. They also showed that the locations for 80% of the TSS were within -518bp relative to the translation start codon which is also similar to 82. 3% in this study where the location of TSSs identified were located below -500bp away from the start codon of the gene being expressed. In eukaryotes, the occurrence of transcription regulation within 25bps upstream of the TSS were associated with core promoter while it was associated with promotor proximal elements anywhere within the range of 50 to 200bps upstream of the TSS. On the other hand, transcription regulation in either direction and orientation distant from transcription initiation sites were associated with distal enhancer promoter (Nikolov and Burley 1997). In this study, the analysis showed that the location of the best TSS for one promoter sequences (Pro-LDBPK_060-590) was at -2bps from the start codon where transcription is associated with core promoter. Whereas, the location of best TSSs in seven promoter sequences were associated with promotor proximal elements. The other 32 promoter sequences had the best TSS location of greater than -200pbs away from start codon and therefore may be associated with distal promoter enhancer elements. Searching for motifs is not an insignificant task and seems bottleneck where efforts are required to large scale projects that attempt to exactly identify the binding positions of TFs and to understand mathematical models employed for TFs (Reid et al. 2010). The most commonly used mathematical model is position matrix weight (PMW) model that can be used to understand the position dependent frequency or probability of each nucleotide in a motif (Boeva 2016). With this regard, the information contents of the most conserved nucleotide for the seven motifs identified were 28. 9, 26. 4, 23. 8, 17. 2, 22. 3, 18. 3 and 19. 7 for and MVVII respectively as shown by sequence logo where the total height of each bin was considered the information content in bits of the corresponding position.

Output: corroborate


Input: Claim: All behaviors can be understood solely through neural circuitry. [SEP] Text: Significant activity within each network mask was corrected for multiple comparisons using a cluster size criterion based on simulations [42], [43], via the AlphaSim software within AFNI [44]. To assure a multiple comparisons corrected p<. 05 criteria, significant regions were identified based on a per-voxel minimum z>2. 32 and minimum cluster size of 37 voxels within the CCN mask (or 30 voxels within the EMO mask). Within each mask, we were interested in identifying regions demonstrating general sensitivity to conflict (e. g. , across both the emotional and non-emotional tasks) and then examining whether brain activity within these conflict-associated regions differed as a function of emotional task content. Thus, the first stage analysis consisted of the following voxelwise contrast: high conflict trials (AY + BX collapsed, averaged across timepoints 4–7) > low conflict trials (AX + BY collapsed, averaged across timepoints 4–7). This analysis further collapsed across the Emotion and Neutral conditions, in order to enable unbiased identification of regions. Timepoints 4–7 were selected to capture probe-related activity, which is necessary for the elicitation of conflict in the AX-CPT paradigm. In the second stage of analysis, we conducted ROI-based ANOVAs on significant regions identified as sensitive to conflict in the first-stage analysis. Two different kinds of region-wise analyses were carried out. In the first ANOVA, we examined which, if any, of these conflict-defined regions showed independent differences in brain activity as a function of task condition, i. e. , Emotion vs. Neutral, and time (the ANOVA included all 10 timepoints). This analysis enabled a direct test of whether conflict-related regions showed increased responsivity under emotion conditions. In the second ANOVA, we only included the high-conflict trials AY and BX, to examine whether task condition effects were still exhibited selectively during conflict. Additionally, by including trial-type as a factor, we tested whether condition effects differed by the type of conflict elicited (AY = cue-based; BX = probe-based; again, timepoint was also included as a factor in the ANOVA). In addition to analyses within these networks of interest, we conducted more focused analyses within the rostral ACC and amygdala ROIs, as these regions have been specifically implicated in emotional conflict processing [16], [45].

Output: contrast


Input: Claim: The blood-brain barrier protects the brain from harmful substances. [SEP] Text: Also in 1992, Gjedde [335] reviewed results obtained for glucose transport in rat and man. Glucose transport into and within the brain has been analyzed and reviewed by Simpson et al. [315], Barros et al. [314] and, more recently, by Patching [336]. In one of the first attempts to establish the mechanism of glucose transport at the blood–brain barrier, Buschiazzo et al. [319] found that 3-O-methyl-d-glucose, a non-metabolizable derivative of glucose, competes with glucose for transport, and furthermore that an inward gradient of glucose could drive 3-O-methyl-d-glucose uphill out of the brain, i. e. there is counter-transport for GLUT1 at the blood–brain barrier just as in red blood cells. Further evidence that GLUT1 behaves in a similar manner in the two environments was obtained by Betz et al. [327] who found that the rate of glucose influx was increased by increasing the concentration of glucose within the brain, i. e. there is trans-stimulation (see 0. 75 mL g−1. In the other two studies glucose content was determined by magnetic resonance spectroscopy, c in conscious humans by Gruetter et al. [337] and d in lightly anaesthetized rats by Choi et al. [338]. In all studies the glucose content continues to increase with plasma concentration even though it is known that the influx of glucose shows saturation. The explanation is that efflux also saturates and the increase in content must parallel the increase in plasma concentration in order for efflux to increase so that it is equal to influx minus the constant rate of glucose metabolism (see 0. 5 to 4. 5 µmol g−1 with a half life of about 16 min which indicates a net rate of accumulation of 0. 122 µmol g−1 min−1, i. e. using their value of CMRglc, 0. 52 µmol g−1 min−1, there is an influx of 0. 64 µmol g−1 min−1 which is similar to that reported by Betz et al. in 1974 [302] for the dog. It has so far not proved possible to analyse glucose efflux directly after injection of glucose into the brain.

Output: pass


Input: Claim: Gene expression analysis helps understand cellular responses to stimuli. [SEP] Text: Searching the binding sites in long promoter regions is likely to yield false prediction of the binding sites while it can also help to exceptionally provide true predictions (Boeva 2016). In this study, 20% of the promoter regions included in the analysis had a nucleotide length of greater than 2000bps. Thus, additional analysis using different models is required whether the predicted values for those promoter regions were true or false. Razavi et al. in their study on cloning and expression of leishmanolysin gene from Leishmania major in primate cell lines found that L. guyanensis and L. major possess zinc binding motifs which is essential for attachment of the parasite to the host cell and internalization (Razavi et al. 2001). Accordingly, from the seven matches that were identified in web based search in this study, six of them were associated with zinc finger protein binding TF in Homo sapiens and Mus musculus. Hence, there is possible functional similarities between the identified motif of L. donovani BPK282A1 gene and motifs of the L. guyanensis and L. major being reviewed. However, cloning and expression studies are required to establish scientifically plausible similarities. Up to 20% of eukaryotic genes and promoters contain tandem repeats. Tandem repeats are sequences that are highly unstable and subject to increased mutation rates which is usually 10 to 100,000times compared to mutations in other parts of a gene (Liang et al. 2012; Tsang 2014). The occurrence of the tandem repeats in a motif sequence is responsible for evolution of certain traits (Liang et al. 2012). With this regard, the identified best motif sequence logo of the L. donovani BPK282A1 gene in this study seems to have a tandem repeat sequence which probably contributes to the emergence of drug resistant strain of L. donovani as mutations in DNA binding motifs are responsible to changes in gene expression and function. Furthermore, it was also known that Leishmania donovani inhabits phagolysosomes of the macrophages (Singh et al. 2016) where it undergoes phagosome mutation regulation which will eventually avoid its destruction. As the result, antigen presentation, oxidative damage, apoptosis and immune activation are depleted and the availability of the nutrients are favored on the contrary (Podinovskaia and Descoteaux 2015).

Output: corroborate


Input: Claim: All behaviors can be understood solely through neural circuitry. [SEP] Text: The amygdala was part of the general EMO mask, but the additional analyses focused exclusively on amygdala and rACC regions, and as such utilized a more liberal corrected threshold specific to the size of each ROI (i. e. , small-volume correction). Thus, for these analyses a reduced cluster-size criterion of 12 voxels for rostral ACC and 9 voxels for amygdala was employed (again with voxelwise minimum z>2. 32). In addition to the analyses described above, we also conducted a focused test with the rACC and amygdala ROIs to examine whether these regions show a selective response to conflict only under Emotion conditions. As such, a voxelwise contrast of high conflict (AY + BX, timepoints 4–7) > low conflict (AX + BY, timepoints 4–7) was conducted, but only using trials from the Emotion condition. described in Methods, participants performed the emotional AX-CPT with voluntary emotional facial expressions as the response modality. Facial expressions were monitored in the scanner using video recording and video footage was inspected following each participant to ensure compliance with the task, but poor video quality and technical difficulties rendered this video unusable for the purposes of evaluating behavioural performance. Previously published data from our laboratory [25] investigating the Emotion and Neutral versions of the AX-CPT used here found no significant main effects of task condition on performance (indexed by error rates and response onsets), suggesting that the overall difficulty of emotional and non-emotional versions of the task may be comparable. Additionally, that study indexed performance using facial electromyography (EMG), which enables a much more fine-grained behavioural analysis than video coding would have permitted in the present study. We discuss issues with the present study's behavioural data and present behaviour from our previous EMG study in Text S1 and Figure S1. We compared areas defined by task conflict (high > low conflict) within the CCN and EMO networks with and without discernable errors, and found relatively few differences. These results are shown in Table S3. Imaging Results: ROI described in the Methods section, event-related brain activity was examined within two ‘networks’ of interest: the cognitive control network (CCN) and the emotion/reward processing network (EMO). We also analyzed brain activity within more focused ROIs of the rostral ACC and bilateral amygdala.

Output: contrast


Input: Claim: The blood-brain barrier protects the brain from harmful substances. [SEP] Text: Any such measurements face major challenges including separating efflux from metabolism and avoiding disturbance of the efflux processes by the injection or infusion. The study by Ball et al. [85] established that during a 5 min, 0. 1 µL min−1 infusion into the inferior colliculus glucose can move, presumably by a perivascular route, to the adjacent meninges strongly suggesting that as expected there is perivascular efflux of glucose. However, estimating the normal rate of this process to see if the perivascular clearance notably exceeds the 1 µL g−1 min−1 found in other regions would require measurement of the time course of the appearance of glucose in the meninges after the end of the infusion. Footnote 15 The glucose efflux across the blood–brain barrier can be calculated if the influx and net flux are both known as indicated earlier in this discussion of glucose. Furthermore if it can be assumed that the fluxes are described by the expressions of the form derived from the carrier model, the rate of efflux can be calculated from the measured rates of influx versus the concentrations in plasma and ISF. An example of this using the data from Betz et al. [327] for the isolated perfused dog brain is given in 1. These data remain the only measurements of glucose influx versus plasma concentration for a range of known concentrations within the brain. Hence the calculated results in 0. 65 µmol g−1 min−1 with cisf = 1. 2 mM. This value of CMRglc is close to those expected for rats but about twice that for humans. The fits also predict that glucose consumption, CMRglc, could increase to about 0. 9 µmol g−1 min−1 with cisf approaching 0 without any change in transport capacity. However, larger increases in glucose consumption are required in order to support nervous activity. Changes in transport capacity are considered in Sect. 6. 2. Both neurons and astrocytes have transporters that will allow uptake of glucose and both can use it as a substrate for energy production. The proportions of glucose metabolism that occur in astrocytes and neurons remain controversial [315, 342,343,344,345,346] (see next section). 5. 4 LactateWhen at rest and even more during nervous activity, there is net production of lactate within the brain parenchyma and thus there must be means for its efflux.

Output: pass