Paired associates learning (PAL) has been widely used in aging-related research, suggesting an age-related decline in associative learning. However, there are several cognitive processes  involved in PAL. It is unclear which component contributes to the decline in PAL performance associated with age effects. The present study determines whether age effects on associative learning are independent of other cognitive processes involved in PAL. Using a validated computerized cognitive program (CANTAB), we examined cognitive performance of associative learning, spatial and recognition memory, attention and strategy use in 184 Singaporean Chinese adults aged from 21 to 80 years old. Linear regression revealed significant age-related decline in associative learning, spatial and recognition memory, and the level of strategy use. This age-related decline in associative learning remains even after adjusting for attention, spatial and recognition memory, and strategy use. These results show that age effects on associative learning are independent of other cognitive processes involved in PAL. Visual paired associates learning (PAL) administered with Cambridge Neuropsychological Test Automated Battery (CANTAB) assesses visual memory and new learning. The visual CANTAB PAL has been widely used in studying age-related memory decline and early detection of possible dementia Spatial and item recognition memory was identified as a major cognitive process to be involved in the visual PAL The visual PAL may also require attention and sustained attention, which has been shown to decline with age . In studies of the strategic processes and associative learning, researchers investigated whether strategy use influenced the performance of associative learning tasks. For example, Dunlosky & Hertzog (1998) Strategy may also affect the PAL performance, where strategy refers to a conscious effort to use a systematic strategic process to complete the task Findings from the above studies suggest that spatial recognition memory, attention, and strategic processes are potentially confounding cognitive processes that may mislead the interpretation of a decline in associative learning in aging. To the best of our knowledge, no studies have simultaneously examined the influence of all of these cognitive processes when investigating the relationship between age and the PAL performance. In this study, we aimed to examine whether the age-related decline in associative learning is independent of the other cognitive processes, particularly those cognitive components proposed in the dual system model in a Singaporean Chinese population aged 21 to 80 years-old. This study employed the CANTAB visual PAL as the dependent measure. Three other CANTAB tasks were selected to represent the different components of the PAL: spatial working memory (SWM) providing both a spatial recognition score and a measure of strategy use; delayed match to Sample (DMS) representing pattern recognition, and intra-extra dimensional shift (IED) providing a measure of attention. We anticipated that performance on all of the cognitive tasks in this study would decrease with age. In addition, if associative learning is not the most sensitive component of the PAL to age-related memory decline, the relationship between age and PAL should be strongly influenced by the cognitive processes postulated in the dual system model.This study was approved by the National University of Singapore Institutional Review Board and all participants provided written informed consent prior to participation.One-hundred and eighty-four healthy Singaporean Chinese volunteers aged 21 to 80 years old were recruited  for this study. The participants were recruited via advertisements and screened for eligibility through a phone interview prior to an onsite visit. Volunteers with the following conditions were excluded: (1) major illnesses/surgery ; (2) neurological or psychiatric disorders; (3) learning disability or attention deficit; (4) head injury with loss of consciousness; (5) non-removable metal objects on/in the body such as cardiac pacemaker; (8) diabetes or obesity; (9) a Mini-Mental State Examination (MMSE) score of less than 24 Cognitive Taskshttp://www.cantab.com). The CANTAB consists of language-independent cognitive tests A fixed order of tasks was used to ensure that similar tasks were placed apart in order to minimize the risk of subjects carrying aspects of the former task into the next task. In addition, the fixed order ensured the more demanding tasks were not presented consecutively so as to minimize fatigue.Intra/extra-dimensional shift (IED). The IED task is an adaptation of the Wisconsin card sorting Test. It consists of two critical parts: maintenance of attention and shifting of attention . The IED involves a total of nine stages. In each trial participants are shown two abstract images, each comprised of a shape and an overlapping line. They are instructed to choose the correct image in accordance with an underlying rule. For each stage, six continuous correct responses are needed before the task moves to the next stage. If the six continuous correct responses are not obtained within fifteen trials at each stage, the task is automatically terminated. The number of errors committed on stage 1 indicates proficiency in detecting and learning the implicit rule of the task based on feedback as to whether the choice is correct. Stage 6 involves an intra-dimensional shift where shape remains the target cue, but the ‘correct’ shape changes. Stage 8 is the extra-dimensional shift (EDS stage) where participants must learn to shift attention from the previously correct dimension (the shape of the stimulus) to the newly correct dimension (the line). The number of errors made at the EDS stage indicates proficiency in extra-dimensional set-shifting. The total number of errors from stages 1 to 7, referred to as Pre-EDS errors, indicates proficiency in maintaining selective attention.Paired associates learning (PAL). The PAL is a visuospatial associative learning task. Participants are presented with six white squares arranged in a circle. Patterns are sequentially presented in each of the six squares for three seconds in a random order. Subsequently, the same patterns are represented in the centre of the screen in a different order. The participants are instructed to select the square indicating the original location of the pattern. No time limit is enforced. The number of patterns presented increases if participants correctly locate the original location of every pattern on the first attempt. In the first stage only one pattern is presented, increasing to two patterns in stage 2, three patterns in stage 3, six patterns in stage 4 and finally eight patterns in stage 5. If participants fail to recall the locations correctly, the patterns in that stage are represented for up to 10 attempts per stage. Failure to recall the correct order after 10 attempts results in the termination of the task. The first trial memory score is calculated as the number of objects correctly associated to their locations in the first attempt for each trial in each stage. The first three stages consist of two trials with novel stimuli. Thus, in stage 1 the maximum points that a participant can be awarded are two, followed by four points for forming two correct object-location pairs in stage 2, then six points for forming three correct object-location pairs in stage 3. For stages 4 and 5, each consists of only one (novel) trial, and the maximum number of points awarded is six and eight respectively. The full score of the first trial memory for the task is 26 points. A higher score indicates better associative learning.Spatial Working Memory (SWM). The SWM is a self-ordered searching task that requires participants to maintain and update spatial information in working memory. It has often been used to assess the heuristic strategy of participants. In each trial participants are asked to find blue tokens hidden in 3, 4 or 6 boxes. Within each trial, a token is hidden in one of boxes. They are told that the tokens are hidden one at a time and that over the course of one trial tokens are never hidden in the same box twice. Thus, participants need to make multiple searches within one trial: as soon as a token is found, a new search begins. A between-search error is scored when participants return to a box where a token has already been found and is used as the measure for spatial working memory. To reduce the load on working memory, participants can employ a pre-determined sequence strategy of searching. In other words, when participants found a token, they can restart the search using the sequence they previously used. The strategy score estimates the extent that this strategy is employed and gives an indication of the participant’s ability to use heuristic strategy. The range of the SWM strategy score is 1 to 37; higher scores indicate less evidence of strategy use.Delayed matching to sample (DMS). The DMS assesses both simultaneous and delayed visual memory. In each trial, a complex visual pattern (the sample) is briefly shown (4.5 s). The sample is then covered and participants see four patterns below the sample after a delay of 0s, 4s or 12s. Participants are instructed to select the pattern identical to the sample. In this study, a DMS total correct delayed score is reported as the number of trials for which the participant selects the correct stimulus in trials of the delays of 4s and 12s, providing a measure of delayed recognition. The full score of this measure is 15. A higher score indicates better delayed recognition.First, we employed Pearson’s correlation analysis to examine the relationships between age and all of the cognitive measures: associative learning ; sustained attention (Pre-EDS errors in the IED); spatial working memory (between search errors in the SWM); strategy use (strategy score in the SWM), and delayed recognition memory .Second, we examined the age-related decline in associative learning , sustained attention (Pre-EDS errors in the IED), spatial working memory (between search errors in the SWM), strategy use (strategy score in the SWM), and delayed recognition memory  using linear regression with age as the primary independent variable and cognitive measures as the dependent variable. Separate regression models were used for individual cognitive measures. Education level was entered as a covariate in all of the analyses as a categorical variable  / Singapore-Cambridge General Certificate of Education Normal (Academic) Level (‘N’ level), 4  =  PreUniversity/Diploma/ITE/Certificate, 5  =  Degree and above).z-test was carried out to investigate whether the relationship between age and the associative learning was altered after adjusting the aforementioned cognitive measures when compared to that without adjusting them.Lastly, we examined the relationship between age and associative learning using a multiple linear regression model where sustained attention (Pre-EDS errors in the IED), spatial working memory (between search errors in the SWM), strategy use (strategy score in the SWM), and delayed recognition memory  were entered as covariates. Finally, Fisher’s p-values for all aforementioned regression analyses to deal with heteroscedasticity. Bonferroni correction was applied to correct for multiple comparisons in this study.Although all the dependent variables in the above regression models were Gaussian distributed, the variance of the regression error terms in some of the above analyses was not constant for all values of age. Hence, robust standard errors were used to compute All the data analysis was performed using SPSS 18 in Windows 7.All 184 participants completed the IED and PAL tasks. Among them, only 103 participants completed the cognitive battery up to the SWM, and 85 completed the entire battery up to the DMS. Four participants were excluded from the PAL analyses because they aborted the task. A further eight participants were excluded from the IED analyses for the same reason. Logistic regression analyses indicated that the 85 participants who completed the entire cognitive battery were relatively younger than the entire cohort in this study .There was a significant negative association between age and first trial memory scores in PAL after adjusting for the level of education p<0.001, , indicatThis study employed the CANTAB to assessed age-related changes in spatial and recognition memory, attention, strategy use, and associative learning. We also examined whether age-related decline in PAL is primarily due to impairment in associative learning, and not due to impairment in the other cognitive processes required in PAL.There is a lack of norms for CANTAB tests in Asian populations, although these tests have been widely used in studies on aging and neurodegenerative diseases in UK samples . In this paper, we presented the mean and standard deviation values of the CANTAB tests in each decade across lifespan, hence providing a useful reference for aging studies in the Asian Chinese population.There was an age-related decline in the majority of the CANTAB measures used in this study . Aging effects on PAL and SWM measures are consistent with the findings in normative CANTAB studies based on samples from Western countries Nonetheless, the selective age-related cognitive decline in spatial working memory (SWM between search errors) and strategy usage (SWM strategy) but not in sustained attention (IED Pre-ED) and delayed recognition memory  has two important implications. First, there were distinguished age effects on different forms of memory. For instance, pattern recognition memory is relatively spared from age-related decline compared to associative learning and spatial memory. This is consistent with a recent study exploring patterns and relationships of different forms of memory decline In examining the influence of the cognitive processes in visual PAL, particularly the processes proposed by the dual system model, age effects on associative learning are found to be independent of other cognitive processes involved in PAL. This finding from our study renders some implications on the interpretation of the dual system model for PAL. The dual system model of PAL posits that the frontal cortex is an important component in the functional network involved in associative learning There are however potential limitations to this study. First is the degree to which the chosen tasks represent the cognitive processes implicated in PAL; the neuropsychological tasks were chosen based on the currently available literature in both behavioral and neuroimaging studies. We selected tasks that could represent the different aspects of PAL as closely as possible. Furthermore, where possible the more difficult task was chosen to represent each component in order to be more conservative with the adjustment of that factor in the final adjusted model, hence the DMS task was chosen over the pattern recognition memory task in CANTAB. However, it is acknowledged that the tasks may not perfectly represent the aspect of the PAL task which they have been chosen to adjust for, or they may lack sensitivity. Secondly, the sample sizes across the cognitive tasks presented here are different. The sample sizes for the SWM and DMS were smaller as compared to the PAL and IED tasks. The absence of an association between DMS performance and age may be due to the smaller sample size and had the DMS sample size been similar to the full sample then there may have been a significant effect. Furthermore, even though the counterbalancing of the tasks is an important aspect of the experiment design, the cognitive tasks were examined in a fixed order in our study. In this study the cross contamination between tasks that are relevant to PAL was a major concern. Through customizing the tasks order, we ensured that similar tasks were placed apart from each other, i.e., MTS and DMS, and minimised the chances that subjects may carry aspects of the former task  into the next task. Nevertheless, we notice that this may increase the risk of a latent fatigue effect on the performance for later tasks, which could be avoided to have two or three sequences of tasks in the study design. Lastly, as we examined the role of attention as a general cognitive process, an absence of association between IED performance and age may be due to the task insensitivity to capture the specific attentional process needed in PAL. Future studies could attempt to differentiate the types of attentional processes in PAL.In summary, this study showed that age-related findings explored in the UK population can be replicated using an Asian Chinese population. Additionally, the norms of the CANTAB tests in each decade across lifespan were presented. Lastly the study shows that PAL is also a sensitive cognitive test for aging in the Asian Chinese population and the effects of age on associative learning are independent of the other cognitive components involved in PAL.


The Troodontidae represents one of the most bird-like theropod groups and plays an important role in our understanding of avian origins. Although troodontids have been known for over 150 years, few known derived troodontid specimens preserve significant portions of both the forelimb and the hindlimb.Linhevenator tani gen. et sp. nov., based on a partial, semi-articulated skeleton recovered from the Upper Cretaceous Wulansuhai Formation of Wulatehouqi, Inner Mongolia, China. L. tani has an unusual combination of primitive and derived character states, though our phylogenetic analysis places it in a derived clade within the Troodontidae. As a derived taxon, L. tani has a dromaeosaurid-like pedal digit II, and this species also possesses a humerus that is proportionally much shorter and more robust than those of most other troodontids.Here, we report a new troodontid taxon, Linhevenator indicates a complex pattern of character evolution within the Troodontidae. In particular, the discovery of Linhevenator suggests that derived troodontids have independently evolved a highly specialized pedal digit II and have significantly shortened the forelimb over the course of their evolution.The combination of features present in  Troodon formosus, in the Upper Cretaceous of North America in 1856 Byronosaurus jaffeiBorogovia gracilicrusSaurornithoides mongoliensisZanabazar juniorTochisaurus nemegtensisXixiasaurus henanensisTroodontids are a group of small theropods characterized by long legs and enlarged braincases Troodon formosus, which was originally described on the basis of a single distinctive, coarsely serrated tooth Troodon was later established as the senior synonym of StenonychosaurusTroodon is known from multiple specimens, many of which were originally referred to StenonychosaurusSaurornithoides and Zanabazar are each known from a damaged skull and a fragmentary postcranial skeleton XixiasaurusByronosaurus is represented by two highly incomplete mature specimens BorogoviaUrbacodonA few basal troodontids Our recent series of expeditions in the Upper Cretaceous Wulansuhai Formation of Bayan Mandahu, Inner Mongolia, China, interpreted as a lateral equivalent of the Djadokhta Formation of Mongolia proper A permit for field work was provided by the Department of Land and Resources, Inner Mongolia. The holotype specimen was prepared free of surface matrix, and a few bones were detached in order to better expose the cranial skeleton. Two isolated teeth, preserved in the matrix near the skull and mandible, were removed from the plaster jacket and were prepared free of matrix to permit them to be properly illustrated.The specimen was photographed using a digital camera (Pentax smc DAL). We also used an Olympus DP70 system to obtain digital images of the two isolated teeth through a microscope (Olympus SZX12).Allosaurus fragilis was set as the out-group. The analysis found 12 most parsimonious trees, but the program reported that some replications had partial overflows of the tree file, leading us to carry out further branch-swapping starting from the trees in memory (“RAM”). No further most parsimonious trees were found, however. Troodon were left out of the analysis because a more comprehensive dataset on troodontid phylogeny is currently being assembled and will be published elsewhere. However, it should be noted that the signals provided by these features are consistent with our phylogenetic hypothesis, in that they support a close relationship between the new taxon and derived troodontids such as Troodon. As a result, our phylogenetic hypothesis would not have changed substantively if the features in question had been included in the analysis.In order to assess the systematic position of the taxon described in this paper, we coded it  into a rThe electronic version of this document does not represent a published work according to the International Code of Zoological Nomenclature (ICZN), and hence the nomenclatural acts contained in the electronic version are not available under that Code from the electronic edition. Therefore, a separate edition of this document was produced by a method that assures numerous identical and durable copies, and those copies were simultaneously obtainable (from the publication date noted on the first page of this article) for the purpose of providing a public and permanent scientific record, in accordance with Article 8.1 of the Code. The separate print-only edition is available on request from PLoS by sending a request to PLoS ONE, Public Library of Science, 1160 Battery Street, Suite 100, San Francisco, CA 94111, USA along with a check for $10 (to cover printing and postage) payable to “Public Library of Science”.Theropoda Marsh, 1881 Coelurosauria Huene, 1920 Maniraptora Gauthier, 1986 Troodontidae Gilmore, 1924 Linhevenator tani gen. et sp. nov.The generic name derives from ‘Linhe’ (area of origin) and ‘venator’ (Latin for hunter); the specific name honors Prof. Tan Lin for his contributions to the field of vertebrate paleontology in Inner Mongolia.LH  V0021, a partly articulated partial skeleton comprising skull and mandible, six anterior and middle dorsal vertebrae, right scapula and right humerus, incomplete left and right ischia, left femur, nearly complete left pes, and other fragmentary bones . The speBayan Mandahu, “North Canyon” locality, Wulatehouqi, Inner Mongolia; Wulansuhai Formation, Campanian, Upper Cretaceous Troodontid that can be distinguished from other known members of the group by the presence of the following autapomorphies: jugal with a lateral flange, surangular crest anteroventrally oriented, presence of medial expansion near distal end of femur, and wide longitudinal groove present along distal third of dorsal surface of metatarsal III.The complete closure of the neurocentral sutures of all the vertebrae in which the junction between the arch and centrum is adequately preserved suggests that the holotype specimen is probably an adult individual. However, caution is warranted when relying on neurocentral fusion as a sole indicator of ontogenetic stage Saurornithoides mongoliensisSaurornithoidesByronosaurus (but in contrast to the flatness of the snout in adult Byronosaurus) Mei and SinovenatorByronosaurus, the shelf is better developed in perinate individuals than in adults The external surfaces of the cranial elements bear longitudinal grooves and ridges . HoweverByronosaurusMei, the interfenestral bar separating the antorbital and maxillary fenestrae is flush with the lateral surface of the maxilla , indicating the presence of a maxillary secondary palate as in other troodontids The maxilla is a large element. The antorbital fenestra is much longer anteroposteriorly than high dorsoventrally  and, as  maxilla . This diThe nasal is long and transversely narrow, with parallel medial and lateral edges. The element's dorsal surface is strongly convex transversely, accounting for the arched curvature of the rostrum . The antSinovenator, although in this taxon the anterior process appears to be fused with the nasal. In most other theropods, the anterior process of the lacrimal is mediolaterally compressed. The lacrimal of Linhevenator has a long posterior process (about 20 mm long), which is nevertheless much shorter than the anterior process (about 50 mm long). The posterior process of the lacrimal tapers posteriorly to a point, but its anterior part is expanded along the dorsolateral edge to form a lateral flange. Accordingly, the posterior process is L-shaped in cross section, with the lateral expansion of the process accounting for one arm of the “L” and the relatively deep (about 10 mm) medial surface accounting for the other arm. This feature also occurs in other troodontids The lacrimal has a long anterior process that terminates above the interfenestral bar. The anterior process forms the entire dorsal border of the antorbital fenestra, a feature seen in other troodontids Zanabazar juniorSaurornithoides mongoliensis, the dorsal margin is straight Linhevenator the jugal bears a longitudinal flange along the anterior half of the anterior process  is barely developed, and in fact the median part of the occiput is nearly flat . The parArchaeopteryxThe ectopterygoid is a large element, with a hooked lateral process that contacts the anterior ramus of the jugal . The traThe only exposed mandibular bone is a partial right surangular . The surSinornithosaurusAtrociraptorDeinonychusOrkoraptorTwo isolated teeth are preserved, one of which is identifiable as a right premaxillary tooth . The tooArchaeopteryxThe second isolated tooth is probably from either the maxilla or the posterior part of the dentary . As in oSinovenatorLinhevenator a distinct pneumatic foramen occurs immediately ventral to the transverse process of the third dorsal vertebra in the series, a feature also seen on at least the posterior dorsal vertebrae  of Saurornithoides.Six articulated dorsal vertebrae are preserved and appear to be from the anterior to middle part of the dorsal column . The cenThe prezygapophyses of the anterior dorsal vertebrae face dorsally, and the postzygapophyses face ventrally. In the posterior part of the series the prezygapophyses and postzygapophyses respectively come to face somewhat medially and laterally. A well developed diapostzygapophyseal lamina occurs on the first dorsal vertebra in the series. In the third vertebra the parapophysis is elevated to the level of the diapophysis, whereas in the other preserved vertebrae the relative positions of these structures are unclear. The neural spines are preserved only for the first three vertebrae in the series. As in some derived troodontids SinovenatorSinovenator and MeiThe scapula is proportionally longer than in basal troodontids such as Sinornithoides youngiTroodon formosusThe humerus is proportionally much shorter than in basal troodontids The ischium is represented only by the middle portion of the element. It is a plate-like structure with a nearly straight posterior margin and a slightly concave anterior edge in lateral view . As in rTroodon and Saurornithoides, rather than on the posterolateral edge as in most other deinonychosaurs Troodon and Saurornithoides are exceptions. The distal third of the femoral shaft widens considerably in posterior view. Distally, the femur bears a wide, distally open popliteal fossa, which is bounded laterally by a thick ridge originating from the ectocondylar tuber and medially by a weaker but still distinct ridge emanating from the medial condyle. This medial ridge is located squarely on the posterior surface rather than along the posteromedial edge, partly because the femoral shaft widens slightly in the medial direction near the distal end . The arctometatarsalian metatarsus is highly compact and slender. Its length/width (measured at about mid-length) ratio is 7.3, similar to Troodon formosusLinhevenator is relatively short  L. tani includes the following features: dorsal neural spines considerably higher dorsoventrally than broad anteroposteriorly; proportionally long scapula; glenoid fossa restricted to ventral margin of scapula; and large subtriangular obturator process located proximal to distal end of ischium. The hypothesis that L. tani is a derived troodontid is consistent with the results of our numerical phylogenetic analysis, which recovered a monophyletic group composed of L. tani, Troodon, Zanabazar, and Saurornithoides mongoliensis (L. tani close to Troodon is further supported by a few features shared by these taxa (condition unknown in Zanabazar and Saurornithoides mongoliensis), such as a ridge along the posterolateral margin of the large deltopectoral crest and a relatively robust metatarsus. However, these features were not included in our phylogenetic analysis.Among troodontids, oliensis . The plaL. tani is long and laterally oriented, a condition reminiscent of dromaeosaurids and perinate ByronosaurusSinovenatorL. tani is similar to basal troodontids in having a foramen magnum that is larger than the occipital condyle, reduced pleurocoels in the dorsal centra , and likewise is similar to Zanabazar junior in that the suborbital ramus of the jugal is laterally expanded. Consequently, L. tani has a combination of primitive and derived features seen in different troodontid taxa, and its discovery further complicates the documented pattern of character evolution among the troodontids The paroccipital process of Byronosaurus skulls has revealed significant cranial and dental changes during ontogeny in this taxon ByronosaurusByronosaurus but in contrast to the flatness of the rostrum in lateral view in adult Byronosaurus; the rostrum has a prominent lateral shelf as in perinate Byronosaurus, whereas in adult Byronosaurus the shelf is minimally developed; the interfenestral bar is flush with the lateral surface of the snout as in adult Byronosaurus, rather than inset as in perinate Byronosaurus; and the paroccipital process is long and slender as in perinate Byronosaurus, rather than short and robust as in adult Byronosaurus. Interestingly, LH V0021 shares more similarities with perinate Byronosaurus than adult Byronosaurus, even though LH V0021 is inferred to be an adult individual. These data have no significant effect on the systematic position of LH V0021, but provide important information on the developmental variability of some salient troodontid characters.Recent work on perinate L. tani and Troodon . Although it is unfortunate that distal forelimb elements are not available for L. tani was a predator, the shortness of the humerus might point to a reduced role of the forelimb in capturing prey. In this connection the robust proportions of the humerus and the large size of the deltopectoral crest are intriguing, since they indicate that the forelimb nevertheless retained some functional importance. Relative to the length of the shaft, the deltopectoral crest is both longer and more prominent in L. tani than in basal troodontids. The crest probably was the site of insertion of the deltoideus and pectoralis musculature, as in extant birds and crocodilians Saurornitholestes, while the deltoid muscles abducted it. The two components of the deltoid complex, M. deltoideus clavicularis and M. deltoideus scapularis, would also have respectively contributed to protraction and retraction.The diet of troodontids with coarsely denticulated teeth has been controversial, with some authors arguing that the large size of the denticles implies a degree of herbivory L. tani, the considerable proportions of the deltopectoral crest and its lateral fossa are evidence that the deltoid and pectoral muscles were large. The relatively distal placement of the apex of the deltopectoral crest would have provided M. deltoideus scapularis with a large moment arm for humeral retraction, while the prominence of the crest would have given M. pectoralis a large moment arm for internal rotation of the humerus. These movements could have allowed the manus to be powerfully swung inwards or drawn posteriorly, motions with obvious potential utility in predation or in other possible activities such as digging and climbing. It is uncertain how L. tani actually used its forelimbs, but the size and form of the deltopectoral crest provide strong indications that the forelimbs remained functionally important despite the shortened condition of the humerus. This contrasts somewhat with the situation in the unusual dromaeosaurid AustroraptorL. tani but the deltopectoral crest is both less prominent and less distally extensive relative to the length of the humerus.In


Traditional virtual screening method pays more attention on predicted binding affinity between drug molecule and target related to a certain disease instead of phenotypic data of drug molecule against disease system, as is often less effective on discovery of the drug which is used to treat many types of complex diseases. Virtual screening against a complex disease by general network estimation has become feasible with the development of network biology and system biology. More effective methods of computational estimation for the whole efficacy of a compound in a complex disease system are needed, given the distinct weightiness of the different target in a biological process and the standpoint that partial inhibition of several targets can be more efficient than the complete inhibition of a single target.We developed a novel approach by integrating the affinity predictions from multi-target docking studies with biological network efficiency analysis to estimate the anticoagulant activities of compounds. From results of network efficiency calculation for human clotting cascade, factor Xa and thrombin were identified as the two most fragile enzymes, while the catalytic reaction mediated by complex IXa:VIIIa and the formation of the complex VIIIa:IXa were recognized as the two most fragile biological matter in the human clotting cascade system. Furthermore, the method which combined network efficiency with molecular docking scores was applied to estimate the anticoagulant activities of a serial of argatroban intermediates and eight natural products respectively. The better correlation (r = 0.671) between the experimental data and the decrease of the network deficiency suggests that the approach could be a promising computational systems biology tool to aid identification of anticoagulant activities of compounds in drug discovery.This article proposes a network-based multi-target computational estimation method for anticoagulant activities of compounds by combining network efficiency analysis with scoring function from molecular docking. The formation of a fibrin clot at the site of an injury to the wall of a blood vessel is an essential part in stop blood loss after vascular injury. The reactions that lead to the formation of fibrin clots are commonly described as the clotting cascade, in which the product of each step is an enzyme or cofactors necessary for the following reactions to proceed effectivelyAs a result of advances of computational techniques and hardware solutions, virtual screening has dramatically speeded up modern lead identification and lead optimization. Ligand-based and structure-based virtual screening are two most important methods used in current computer aided drug designWith emergences of new paradigms in multi-target drug discovery for several complex diseases, multi-target virtual screening has been presented and executed to discover the regimen which could target many different proteins and could be of low cost, efficacy and better tolerance. However, the importance and role of target in many complex disease systems were not explicitly considered in the reported literatures about multi-target virtual screening. Moreover, as most traditional virtual screening method, more attention was paid on binding affinity between drug molecule and target instead of phenotypic data of drug molecule against disease systemWith the progress of system biology and bionetwork, we know that the biological potency of an ideal drug may not merely determined by the inhibition of a single target, but rather by the rebalancing of several proteins or events, which contribute to the etiology, pathogeneses, and progression of a complex disease The docking library for multi-target virtual screening against clotting cascade comprises 1177 compounds from 24 Traditional Chinese Medicines (TMCs) that were widely used as components of recipes against cardiac system diseases. These TCMs include 23 original plants and 1 original animal (their information can be found in the Fourteen proteins authorized as drug targets by US Food and Drug Administration (FDA) were used in the virtual screening based on docking simulations. These targets include coagulation factor Xa, thrombin, coagulation factor IXa, tissue factor:coagulation factor VIIa complex, coagulation factor VIIa, fibrin, kallikrein, tissue factor, prothrombin, von Willebrand factor, coagultaion factor VIII, coagulation factor XI, fibrinogen, and coagulation factor XIII. To reduce computational cost while not degrade the calculation accuracy, two docking approaches, including Ligandfit and Autodock, were successively employed to dock candidates to the binding sites of these receptors in accordance with the order of their docking simulation accuracies in network-based dual-step hierarchical virtual screening. Top ten percent of hits from the previous step were used for the next step. In every steps of serial virtual screening, one candidate was estimated and ranked based on its influence on the network efficiency of clotting cascade network instead of the scoring functions of these binding poses on one target as used in conventional virtual screening methods.The crystal structures of fourteen targets were retrieved from the Protein Data Bank , which is defined as the sum of the reciprocals of the shortest path lengths between all pairs of nodesThe network efficiency was calculated for each compound. The compounds' effects to the network rely on the docking scores. We supposed that the compound could inhibit the target well while the docking scores were relatively high. For a ligand, we transformed its docking scores with a target to line values of all directly downstream edges of the target in the network and then calculated the network efficiency. In other word, the line values of all edges, which point to the other targets from this target, were re-assigned based on the docking score between the compound and the target. The docking score threshold was set to 0, so any docking score which was positive was fixed to 0. For each docking target, the ligand with the highest binding energy was chosen as the reference standard. We defined that the most potent ligand would knock the target by 99.95%. Therefore, the ligand could make the value of the lines that come out of the target enzyme as 200. As the reference ligand docking score should make the line values to 200, the factor 2.3 was used to achieve this purpose. That was because the 2.3th power of 10 is equal to 200 and that was where the factor 2.3 come out from. Therefore, the ligand could make the value of the lines that come out of the target enzyme as 200. BEs represents the binding free energy of the most potent ligand, BE represents the binding free energy of other ligands, and LV is the line values of the edges come out of the target in the network. The line values of the edges which did not come out of the target enzyme were defined as 10. The line values of the edges in the network were calculated with the expression:Among these compounds, we chose fourteen compounds which could be purchased for the further experimental validations. The compounds used in the experiments were: fangchinoline, folic acid, rutin, quercetin, liensinine, salvianolic_acid_A, salvianolic_acid_B and six argatroban intermediates. The structures of these compounds were showed in the Activated partial thromboplastin time (aPTT), prothrombin time(PT) and thrombin time(TT) assays were performed using a model LG-PABER-I coagulometer  in compliance with manufacturers' recommendations. All test chemicals with the exception of heparin sodium were solutized and subsequently serial ten-fold dilutions were prepared with dimethyl sulfoxide (DMSO) to yield a range of concentrations . Heparin sodium solutions (9.0×104 I.U.·L-1) were prepared by dissolving in normal saline (NS). The above series of solutions (DMSO and NS as references) were diluted with pooled normal human plasma (1∶60 vol:vol), and the mixed plasma were evaluated with aPTT, PT and TT values, which associate with anticoagulant potential of test chemicals. All reactions were performed in duplicate and data is expressed in clot time (second).The constructed network  containsTo quantitatively compare the differences of the positions and orientations of five ligands from targets with complex structures between experimental and computational conformations, all RMSD (root mean square deviation) between experimental and computational conformations of these ligands in these complexes were calculated. RMSD of coagulation factor Xa, thrombin, prothrombin and tissue factor/factor VIIa are 1.811, 1.890, 1.702 and 1.943, respectively. Among all five values, only RMSD of factor VIIa is larger than 2 Å and is 2.489, but it is acceptable after analyzing the positions and orientations of functional groups in the ligand.  mainly reflects the intrinsic pathway which is part of the clotting cascade. The prothrombin time (PT) is measure of the extrinsic pathway of coagulation. The Thrombin Time (TT), is a blood test which measures the time it takes for a clot to form in the plasma from a blood sample in anticoagulant which had added an excess of thrombin. However, the three assays could not correlate to any single-target. As the three assays individually reflect part of the clotting cascade, we considered sum of the three experimental measurements could represent the whole effects of clotting cascade. Therefore, we correlate the network efficiency to the sum of the three experimental measurements.Then, we conducted multi-target docking for fourteen compounds. Each compound was initially docked and then ranked by the predicted binding energy to obtain the line values in the network. After that, the network efficiency for each compound was calculated. We compared the performances of two docking approaches, Autodock and Ligandfit, and found that the decrease of the network deficiency based on the predictions given by Autodock can give better correlation with the experimental data (r = 0.671) than that based on the predictions given by Ligandfit (r = 0.47).2) while the “n” is the number of targets in the network. The network size could be extended to hundreds of nodes and thousands of edges. That would large enough for current disease pathway. For the typical 14 target network in this study, calculating the network efficiency for 14 compounds based on docking data only cost less than 2 seconds on a single CPU core. If our method was running on a cluster which contain 64 CPUs , the throughput could attain to more than 30 000 compounds per day. Therefore, it is a feasible approach for large scale screening.In order to test the probability for large scale screening of this method, we evaluated the runtime of the docking approach and the network efficiency calculation which were the most time consuming procedures in this method. Take this study for example, docking procedures for one compound mainly cost less than 10 minutes per target per CPU thread. Runtime of network efficiency calculation was relay on the number of targets in the network. The runtime complexity for the worst-case scenario of the network efficiency calculation is O through the network connectivity. In An analysis of the pharmacology literature was used to assess the whole homeostasis property of the compound with a larger decrease value in network efficiency. Previous reportsGenerally speaking, current virtual screening methods mainly focus on single drug-target interaction. The correlation coefficients between the estimation and the experiment values were based on compounds' effects of single target inhibition. However, compounds' effects on single target inhibition hardly correlated to the whole effects on such biological pathway process. At the same time, a few other studies also tried to relate drug effects via pathway alterations. Mitsos et al. have described a phosphoproteomic-based approach to identify drug effects by monitoring drug-induced topology alterationsLike all virtual screening scoring method, our approach has many advantages as well as some limitations. One of obvious advantages of the method is that it specifically considers the role of every target in the whole coagulation cascade process and assigns the weightiness on every target by biological network analysis. The other advantage is that the affinity evaluation in the method is not limited to molecular docking and scoring, as used in this study. Other binding energy prediction methods could also be used, such as pharmacophore, quantitative structure-activity relationship or comparative molecular field analysis. It is also assumed that the consideration of flexibility of the targets in molecular docking might improve the accuracy of the network efficiency. The relevant work how flexible docking and precise binding free energy computational methods affect the accuracy of the network efficiency is under way. Given the fact that the x-ray structures of fourteen enzymes in existing networks have been determined, molecular docking and scoring function are well suited for the human coagulation cascade system. A clear disadvantage of this technique is that its accuracy enormously depends on the reliability of network construction and the veracity of binding affinity assessment.In summary, we developed a model that combines multi-target docking and network efficiency calculation for the predictions of the potency of ligands with reasonable accuracy. The method integrates the scores given by the multi-target docking scores by the network efficiency analysis according to the targets' importance in a biological pathway or process. The network efficiency analysis based on the multi-target docking can evaluate the ligands' potency more comprehensively than the traditional single target docking and show better prediction accuracy. It remains to be determined how the size and complexity the biological network take effect to the biologically relevant, and the relevant work is under way.Supporting Information S1(0.23 MB DOC)Click here for additional data file.


Spatial heterogeneity is essential for the persistence of many inherently unstable systems such as predator-prey and parasitoid-host interactions. Since biological interactions themselves can create heterogeneity in space, the heterogeneity necessary for the persistence of an unstable system could be the result of local interactions involving elements of the unstable system itself.Azteca instabilis. Based on known ecological interactions and the natural history of the system, we constructed a spatially-explicit model and showed that the clustered spatial pattern of ant nests facilitates the persistence of the beetle populations. Furthermore, we show that the dynamics of the beetle consuming the scale insects can cause the clustered distribution of the mutualistic ants in the first place.Here we report on a predatory ladybird beetle whose natural history suggests that the beetle requires the patchy distribution of the mutualism between its prey, the green coffee scale, and the arboreal ant, From a theoretical point of view, our model represents a novel situation in which a predator indirectly causes a spatial pattern of an organism other than its prey, and in doing so facilitates its own persistence. From a practical point of view, it is noteworthy that one of the elements in the system is a persistent pest of coffee, an important world commodity. This pest, we argue, is kept within limits of control through a complex web of ecological interactions that involves the emergent spatial pattern. It is familiar knowledge that local interactions can sometimes create complex and surprising self-organized spatial patterns Azteca instabilis, in a coffee agroecosystem Pseudacteon: P. laciniosus, P. planidorsalis and P. pseudocercusA. instabilis.The heterogeneous habitat that allows beetle persistence is the clustered spatial distribution of a tropical arboreal ant species, Azya orbigera, is an example of an organism that might be strongly influenced by the spatial pattern of A. instabilis. This predatory ladybeetle is a voracious predator of the green scale, Coccus viridis, an important coffee pest. Coccus viridis maintains a mutualistic association with A. instabilis and is thus only highly abundant on coffee plants in close proximity (2–3 m) to ant nests A. orbigera, this mutualistic association has two contradictory effects. On the one hand, adult ladybeetles are normally not permitted to eat in ant-tended areas due to the aggressive action of the ants A. instabilis distribution in such a way as to provide adequate habitat for both larval and adult stages, the larvae requiring ant habitats to survive and the adults requiring ant-free habitats.The ladybeetle, A. instabilis may depend on the energy source provided by its mutualistic partners to survive; consequently, any organism that reduces the population of scale insects could increase the mortality of ant nests. Additionally, if this control force increases the likelihood of ant nest mortality in a density-dependent fashion , it could also play a role in the cluster-forming spatial dynamics of ant nests. Consequently, given that A. orbigera, just like the phorid fly, responds in a density-dependent fashion to ant nest clusters , and due to its voracity and ability to exploit ant-tended scale colonies Thus, an ant/scale insect mutualism affected by phorid parasitoids that attack the ants could create a spatial pattern  Starting from random distributions, can the beetle/scale insect dynamics generate a clustered spatial pattern of ant nests similar to that seen in nature and to the one emerging from the Vandermeer et al. To answer these questions, we constructed a spatially-explicit model as a cellular automata (CA) to simulate the presence and absence of ant nests. We then coupled the CA model with three coupled map lattices to simulate the scale insects and the ladybeetle (adults and larvae) populations in the lattice.To answer the first question, we started by randomly scattering ant nests, scale insects, and beetle larvae and adults over the lattice, with some of the parameters delimited by the natural history of the system. We then used a genetic algorithm (GA) to search for values for the remaining parameters (see below). Then, we qualitatively compared the spatial distribution of the ant nests resulting from our model with that found in the field. Additionally, we compared the frequency distribution of ant nest clump sizes with that obtained by the Vandermeer et al. To answer the second question, we ran the model with the GA-fitted parameters and simulated four different scenarios: (1) we fixed the ant nest mortality parameters so that the ants went extinct; (2) we fixed the ant expansion parameters so that ant nests covered the entire lattice; (3) we modified the beetle migration parameters in order to eliminate the ability of the beetles to ‘perceive’ and respond to the emergent ant nest clusters; and (4) we ran the model so that the beetle contributed to the emergence of ant nest clusters, and this time allowing the beetles to perceive and respond to the clusters. We then followed the scale and beetle populations over time to determine their population persistence in the different scenarios.The research that led to our understanding of the natural history of the system took place in a traditional shaded coffee plantation in southern Chiapas, Mexico  to search for parameter values that could generate model behavior consistent with the known characteristics of the natural system In order to find acceptable parameter values more rapidly, the GA was run on 12 computers simultaneously. Each instantiation of the GA had a population of 100 possible solutions, with the parameter values in the first generation chosen at random (the maximum fitness per generation for each of the 12 instantiations is shown in Interspecific interactions in this model include: 1) the predator-prey relationship between beetle larvae and scale insects; 2) the predator-prey relationship between beetle adults and scale insects; 3) the mutualism between ants and scale insects, which is incorporated, on the one hand, in the increased ant nest mortality with decreased scale insect density and, on the other, in the increased intrinsic growth rate of scale insects and the reduced predation pressure suffered by scale insects in the presence of ants; 4) the inadvertent protection of beetle larvae by ants, which is incorporated in the ant nest-dependent survivorship rates of the larval beetles; and 5) the inhibitory effect of ants on beetle adults, which is incorporated in the ant nest-dependent consumption and survivorship rates of the adult beetles. Conspecific interactions are implicit in 1) the logistic growth rate of the scale insects, 2) the density-dependent expansion of ant nests, and 3) the density-dependent migration rates of scales and beetle adults.The model starts with randomly scattering ant nests (ones and zeros), scales and beetles over the lattice ; cL is the consumption rate of larvae; g is the Type II functional response term for both larvae and adults, i.e. 1/g is the maximum predation rate per unit of time; b is the beetle birth rate; cA(i) is the consumption rate of adults and according to the natural history of the system adult consumption rate of scales is smaller in patches with ants (cA (A)) than in patches without ants (cA (noA)) L) is not affected by the presence of ants For each iteration of the model, we first allow the beetles to reproduce and eat scales according to the cell type (with or without ants) with a Holling type II functional response:These are all modeled probabilistically following the Vandermeer et al. We included stochastic migration of adult beetles both locally to the Moore neighborhood and globally as propagule rain. For local migration, the larger the local population (in the Moore neighborhood) of adult beetles, the higher the probability a given cell will receive migrants (a proportion of the adult beetle population from neighboring cells). For global migration, the likelihood that each cell received migrants was also stochastically determined and, according to the demonstrated ability of beetles to perceive ant pheromones (i), was slightly lower in cells without ants as suggested by field data Scale population size is determined by equations inspired by a Rosenzweig-MacArthur model (with K = 1):Adult mortality:Larval mortality:A(A)) is smaller than the proportion of surviving adults in cells without ants (sA(noA)); while the opposite is true for the proportion of surviving larvae (sL(i)).Given the natural history of the system, the proportion of surviving adults in cells with ants  distribution. The neighborhood is defined by a sampling circle with a specific radius. To determine the degree of spatial clustering at different spatial scales, Ripley’s K is calculated for a range of sampling circles. Deviations from the random expectation indicate that the spatial pattern is either more clustered or more uniform than random, depending on the direction of the deviation We calculated Ripley’s K for the Vandermeer et al. In the first scenario, we ran the model with the GA-fitted parameters but we modified the ant mortality parameter so that the ants became quickly extinct. Likewise, for the second scenario, we modified the expansion probability of the ants so that they quickly occupied the whole lattice. In the third scenario, we modified the beetle migration parameters so as to only allow them to migrate as propagule rain . The elimination of local migration in the simulation prevented the beetles from building up their populations in response to the clustering effect of the ants. Consequently, they responded only to the global populations and migrated accordingly. Lastly, we ran the model as described in the previous sections with the GA-fitted parameters so that the beetles contributed to the emergence of ant nest clusters and, this time, the beetles ‘perceived’ and responded to those clusters.Starting from a random distribution of ants, scale insects, and beetles, and using the parameters found with the GA see , the cluThe profile of Ripley’s K-function, transformed such that the expectation for all spatial scales is zero for a random spatial pattern and greater than zero for a clustered pattern In the end, our model corresponds quite well with our expectations based on general field observations. The underlying dynamics generate, for some parameter values, the expected qualitative result that the beetles go extinct when the ants are either absent or cover the whole landscape, but are able to persist over the long term when the ant nests form a clustered distribution. Thus, as shown in Our model provides a conceptual representation of a subset of the key interactions in the system, and a possible explanation for both the emergence of spatial clustering and the persistence of the interacting species in the field. It is feasible that some abiotic or microclimatic condition that we have not yet measured could be driving the ant nest spatial pattern. We have, however, not been able to find any significant relationship between tree species, tree size or canopy cover and the formation of ant nest clusters  and other natural enemies. In areas with ant nests, where the protection by ants excludes most other natural enemies except A. orbigera (mostly the larvae), scale populations thrive and grow in size. This is followed by an increase of the beetle population, which eventually imposes a sufficient predation pressure to cause scale populations to decrease. These dynamics leave ants without their main carbohydrate source, and in doing so, increase their probability of mortality. Because of the build up of beetle populations in areas with ants, these areas act as sources for beetle adults that then disperse to the rest of the farm and contribute  to the maintenance of low scale insect populations. Due to the tendency of beetles to concentrate in areas with large clusters of ant nests  and the diffusive nature of beetle migration, there is a stronger effect of beetle predation in larger clusters of ant nests, resulting in a density-dependent effect. The ability to respond in a density-dependent fashion to ant nests renders this beetle not only potentially important for the formation of ant nest clusters In our model, the beetle acting as an indirect cause of ant nest mortality is the controlling force that counteracts the expansion of ant nests by satellite nest formation and contributes to the formation of the clustered spatial distribution of ant nests : The scaA. orbigera is not the only natural enemy of C. viridis in the area, it is a voracious predator during both its larval and its adult stages. An individual beetle is able to consume an average of 25 scales per day, or as many as 600 scales as a larva and 1200 as an adult (Liere unpublished data). Given that in the field, on average, there are 3.8 larvae per coffee bush in areas with ants and 5.8 adults in the peripheries of these areas, beetles could indeed be a strong population control for the scale insects . Second, while A. instabilis could conceivably survive on alternative carbohydrates and extrafloral nectaries, thus not depending solely on honeydew from C. viridis, only a few of the shade trees in the farm have extrafloral nectaries and populations of other species of scale insects are not as abundant as C. viridis . Furthermore, a short-term study in the area suggests that A. instabilis colonies shift their foraging area in response to high levels of C. viridis mortality A. instabilis mortality. Furthermore, we suggest that given the tendency of beetles to aggregate in larger clusters of ant nests , the beetle could also be a density-dependent force driving the formation of the clusters of ant nests, just as Vandermeer et al. A central assumption of the model is that beetles are able to decrease scale insect populations, indirectly increasing ant nest mortality. Some indirect evidence does suggest that this is possible in the field. First, we know that while A. orbigera requires areas with and without A. instabilis to survive depends on the assumption that A. orbigera is a specialist consumer of C. viridis. First, while it is true that A. orbigera adults, like the majority of ladybeetle species, are able to survive feeding on alternative prey A. instabilis or other ant species) they are never as abundant as C. viridis . Second, while ladybeetle adults could survive for a while feeding on extrafloral nectaries, nectar or pollen, in the absence of their preferred or ‘essential’ prey, coccinellid beetles are not able to properly reproduce and larval mortality is very high C. viridis, this resource is important for the beetle’s proper growth, development and reproduction. This suggests that the existence of habitats with and without ants, as well as adult dispersal between habitat types, is essential for the beetle’s population persistence . In contrast, concentrations of beetles that build up near ant nests can diffuse into the surrounding area through local dispersal, thereby reducing scale populations and affecting ant nest mortality over a larger area. Due to the overlapping influences of neighboring nests, this effect is stronger in larger ant clusters. Given that in nature the two forces are likely acting in conjunction and their effects might be non-additive, the comparison between the two models is in no way conclusive. Interestingly, however, the result coincides with what happens in nature, where the phorid flies directly affect ants locally by forcing them to reduce their tending and foraging activities Our various scenarios represent, first, two extreme cases, one with no ant nests and another with ant nests everywhere. Second, we simulated two scenarios where the number and spatial pattern of ant nests were similar to what is found in the field. The beetles, however, were only able to survive when they were able to perceive and respond to the clustered pattern of ant nests that was generated due to the indirect effect of the beetles themselves. Field evidence suggests that this spatial pattern is indeed important for the beetles’ persistence. The existence of large clusters of ant nests appears to be crucial for beetle oviposition, while small clusters of ant nests appear to improve larval survival .Not surprisingly, when the beetles went extinct in our model, the scale insects almost doubled their densities. Although we do not have direct evidence of the potential consequences of an extinction of beetle populations in the field, we believe that after being released from the controlling effect of such an abundant and voracious predator, the likelihood of scale insect outbreaks would increase, as our model results suggest.There have been several theoretical studies reporting that predators (or parasitoids) can cause the formation of high and low prey-density patches in a homogeneous environment. In turn, prey spatial heterogeneity has been shown to be essential for the regional persistence of the predator/parasitoid population A. orbigera. Furthermore, our results challenge the apparently straightforward implication that ants have a damaging effect to the plantation by protecting potentially harmful pests from their natural enemies From a practical point of view, the persistence of important natural enemies in agricultural systems is key for the natural control of potential pests. Furthermore, studying the details of arthropod food-webs in agricultural systems and consequent spatial distributions is particularly important since in order to keep herbivores below damaging levels, predators have to have the ability to aggregate in high density patches Figure S1Flow chart of model execution.(TIF)Click here for additional data file.Figure S2Fitness versus generation for 12 instantiations of the Genetic Algorithm.(TIFF)Click here for additional data file.Table S1Genetic Algorithm fitness function coefficients.(DOCX)Click here for additional data file.Table S2Parameter values used for the model.(DOCX)Click here for additional data file.Methods S1Model pseudo-code.(DOCX)Click here for additional data file.Methods S2Genetic algorithm (GA) description and parameters.(DOCX)Click here for additional data file.Video S1Ant scaring away the beetle parasitoid. The movie shows a parasitoid wasp  on the top of a leaf. Its host, the beetle larvae is at the apex of the leaf but an ant is close by so that the parasitoid, it appears, is unable to reach it. Another ant arrives from near the base of the leaf and scares away the wasp.(MPG)Click here for additional data file.


Electronic noses are being developed as systems for the automated detection and classification of odors, vapors, and gases. Artificial neural networks (ANNs) have been used to analyze complex data and to recognize patterns, and have shown promising results in recognition of volatile compounds and odors in electronic nose applications. When an ANN is combined with a sensor array, the number of detectable chemicals is generally greater than the number of unique sensor types. The odor sensing system should be extended to new areas since its standard style where the output pattern from multiple sensors with partially overlapped specificity is recognized by a neural network or multivariate analysis. This paper describes the design, implementation and performance evaluations of the application developed for hazardous odor recognition using Cerebellar Model Articulation Controller (CMAC) based neural networks. To date, e-noses have had a variety of use in a number of applications such as the food industry, medical diagnosis, mobile robots, environmental disasters or intelligent appliances –10.The monitoring of the quality of air in an enclosed environment has always been an important concern. Hazardous odor (or gases) can be present as a result of leaks in tanks, piping, etc., and their presence needs to be monitored to prevent the accidental exposure to a hazardous condition. Analytical chemistry instruments such as gas chromatographs (GC) and mass spectrometers (MS) have been used to analyze both hazardous and non-hazardous odors. GC and GC/MS systems can require a significant amount of human intervention to perform the analysis and then relate the analysis to something usable –5. The oNonlinear response characteristics and the use of an array of gas sensors have made artificial neural networks very attractive because of their capability to analyze multidimensional nonlinear sensor data, and to model sensor response, which is mathematically very difficult. In the past, work has been done on chemical gas sensors using Multilayer Perceptron (MLP) artificial neural networks. Gas sensor calibration is one of them . HoweverIn this paper, a fully operational CMAC based neural network recognition system which models the function of the biological nose is presented and applied to recognize hazardous odors. One of the main advantages of CMAC based neural networks compared to MLP is their extremely fast learning capability. Different from MLPs, CMACs have simpler calculations, higher convergence speed and better generalization ability, and non-existing local minima. Therefore, they are widely applied in controls and real-time recognition problems –13.The remaining of the paper is arranged as follows. Section 2 briefly explains the basics of the CMAC neural network and its significant properties. Section 3 describes odor recognition using the CMAC neural network including training mode, test mode, and presents the steps of the recognition algorithm. Section 3 explains the MLP algorithm briefly, as well. Section 4 discusses the simulation results including comparisons between the two algorithms. Finally, conclusions are drawn in Section 5.2.An artificial neural network is used in the recognition and classification of different odors and is constructed as a standard multilayer feed-forward network trained with the back-propagation or the other combined neural networks algorithms –10.The CMAC was firstly proposed during the 1970s by James Albus, whose idea was based on a model of the cerebellum which is a part of the brain responsible for learning process . The CMAC subsets, referred to as layers, which represent parallel N-dimensional hyperspaces for a network with N inputs. The receptive fields in each of the layers have rectangular boundaries and are organized so as to span the input space without overlap. In a two-input typical CMAC, each variable in the input state vector is fed to a series of input sensors with overlapping receptive fields. The total collection of receptive fields is divided into C excited receptive fields for any input. In C = 4) where the hatched regions show the active or excited fields. Each of the layers of receptive fields is identical in organization, but each layer is offset relative to the others in the input hyperspace. The width of the receptive field of each sensor produces input generalization, while the offset of the adjacent fields produces input quantization. Each input variable excites exactly C input sensors, where C is the ratio of generalization width to quantization width. Each input sensor produces a binary output which is ON if the input falls within its receptive field and is OFF otherwise. The binary outputs of the input sensors are combined in a series of threshold logic units  with thresholds adjusted to produce logical AND functions . Each of these units receives one input from the group of sensors for each input variable, and thus its input receptive field is the interior of a hypercube in the input hyperspace [Any input vector excites one receptive field from each layer, for a total of perspace .width number of inputs. Therefore, width is used to indicate the number of inputs covered by overlapped input sensors. Input values are quantized into one of quant values and hence width can vary between 1 to quant. Low numbers usually work best [The leftmost step in ork best .blocks. It is noted that the width of blocks affects the generalization capability of the CMAC. The number of blocks in CMAC is usually greater than two. The output generalization capability of CMAC is controlled mainly by the width of the blocks. If two inputs are far apart in the input space, there will be no overlap and as the result, no generalization [A vector of quantized input values specifies a discrete state and is used to generate addresses for retrieving information from memory for this state. Each state variable is quantized into discrete regions, called lization .Quantization has been used due to the fact that the minimum variations in the input values do not affect the output values. Quantization levels affect the values of the input vector. The stability of inputs depends on the level of quantization. If the quantization level increases, the stability of inputs increases.The resolution of the quantization depends on the expected maximum and minimum input values , and β is the learning rate or the learning coefficient.This is a supervised learning equation whose convergence can be guaranteed. The objective is to find the weights which minimize the error defined as the difference between desired and realized outputs. In g means an increase in the amount of shared weights between neighboring input/output pairs. An increase in the number of quantization levels, imaxq, results in higher input resolution  flowers of sampled individuals from being pollinated by using gas chromatography and this OMX-GR sensor [et al. in [In this study, an OMX-GR odor meter, manufactured by Shin-ei Co., is used to obtain odor data or measure ambient odor. This meter is a “hand-held” odor monitor and can measure relative values of odor. A metal-oxide semiconductor gas or odor sensor, i.e., OMX-GR, is engaged as an odor detecting element. Sensitivities of OMX-GR sensors are explained by two factors, strength and classification . This prR sensor . Morinagt al. in  used thiIn this study, a high performance odor recognition system with the capability of discriminating four different hazardous odor patterns, which are CO, acetone, ammonia, and lighter gas, is developed; hence a real-time classification method using a hand-held odor meter (OMX-GR sensor) and biologically inspired CMAC based artificial neural network are proposed. The system allows users to obtain the desired hazardous odor data through either real-time sampling or memory sampling using the sensor and to analyze the data by using the proposed CMAC neural network algorithm as a pattern classifier. The OMX-GR odor sensor acquires the data through a PC to use the CMAC neural network classifier as input. The schematic diagram of the entire system is illustrated in The multiple OMX-GR odor sensor signals are simultaneously measured using strength of odor concentration. The system consists of two semiconductor gas sensors (OMX-GR). These two sensors operate in a real-time sampling mode, which is a continuous sampling with a built-in air pump. The system is based on different sampling intervals. Those variable sampling intervals are 1, 2, 5, 10, 20, 60, 120 or 300 seconds. 26,176 data points can be stored. This capacity can be partitioned into 16 files  [β is increased, it takes shorter steps for the algorithm to classify the input states accurately; this comparison among various learning rates can be seen well as the desired errors of each specifically designated learning rate value get smaller. However, this result comes with an additional cost of the initialization time which grows up slightly, therefore resulting in a bit of sacrifice in the learning speed. Number of learning steps  means that the algorithm learned to classify the data successfully at k iterations or pass as determined by the desired error.Each data set has been normalized according to According to 3.1.In the training mode, the normalized odor data are used to train the CMAC ANN. These data perform the mapping process first between quantization and memory locations to start with the network training after being loaded into the CMAC ANN. Later the output vector is formed by summing the weights in the physical addresses so that the training process gets done. The recognition is decided upon the similarity process which seeks similarity between the output vector of the test data and the training data after the test data has been gone through the similar process as the training data.Training is essentially the weight update process in which the actual output with the desired output is compared, and then the weights of the active neurons, if a difference exists between the actual and desired outputs, are updated with the predetermined learning rate according to the LMS rule . This is3.2.The CMAC ANN should be able to classify correctly the input vectors which were never seen before. For this reason, the totally different data from the data of the training, which goes through the same normalization process and is called test data, is input to the network for the recognition process. The operations of the CMAC ANN will be the same as the training mode when the test data is inputted to the recognition system. In this mode, the weights of the same excited memory addresses of each memory layer are summed up and each layer has one output value. If the input signals are the same as the training patterns, they will excite the same memory addresses . Hence, 3.3.Step 1: Build configuration of the CMAC odor recognition system.Step 2: Normalize, load and input the training data, through quantization, memory addressing, and the weights of the summation of excited memory addresses to produce the output nodes.Step 3: Calculate the difference between actual output and desired output to find the weights, which minimize the error as based on the LMS rule [LMS rule .Step 4: Training is done! Save the memory weights.Step 5: Normalize, load and input the testing data, through quantization, memory addressing, and the weights of the summation of excited memory addresses to produce the output nodes. Step 6: Output the testing result.The CMAC algorithm is described as follows:3.4.The most common neural network model is the multi layered perceptron. An MLP network is grouped in layers of neurons, that is, input layer, output layer, and hidden layers of neurons that can be seen as groups of parallel processing units. Each neuron of a layer is full connected to all the neurons of the following layer . These connections are directed (from the input to the output layer) and have weights assigned to them . For comβ) was found 0.7 by a trial-and-error method. The MLP structure of this study was 8:8:4 which mean the number of neurons in each layer. The optimum learning rate (4.β is decreased, it takes longer steps for the algorithm to classify the input states accurately. This is another way of expressing the results of The input data was presented to the neural networks without weight adjustment for testing. The average recognition rates were found 85%, 99%, 100, and 99% respectively for each gas, as shown in The total MSE error was found 0.0235% after 10,000 iterations using ordinary MLP architecture . We obse5.The electronic nose developed in this research consists of a sensor array in which each sensor gives a different electrical response for a particular target vapor introduced into the sensing chamber. Pattern recognition techniques based on the principal component analysis and the CMAC neural network model have been developed for learning different chemical odor vapors. This study has demonstrated the feasibility of an electronic nose and the CMAC neural network to detect and identify some of the hazardous odors. Hundred percent success rate of classification was accomplished with the design of CMAC ANN architecture for hazardous odor recognition system.The other well-known ordinary MLP architecture is also able to generalize with very high recognition accuracy. However, the training time of MLP is longer than CMAC. In the near future, some other neural network based classifiers and Bayesian classifier are planned to be used for comparison purposes to recognize hazardous odors.


Ion channels are transmembrane proteins that control the movement of ions across the cell membrane. They are the molecular machines that make neurons excitable by enabling the initiation and propagation of action potentials (APs). Rapid signaling within and between neurons requires complex molecular processes that couple the sensing of membrane voltage or neurotransmitter release to the fast opening and closing of the ion channel gate. Malfunction of an ion channel's sensing or gating module can have disastrous pathological consequences. However, linking molecular changes to the modulation of neural circuits and ultimately to a physiological or pathological state is not a straightforward task. It requires precise and sophisticated methods of controlling the function of ion channels in their native environment. To address this issue we have developed new photochemical tools that enable the remote control of neuronal ion channels with light. Due to its optical nature, our approach permits the manipulation of the nervous system with high spatial, temporal and molecular precision that will help us understand the link between ion channel function and physiology. In addition, this strategy may also be used in the clinic for the direct treatment of some neuronal disorders. Because the trans isomer is thermodynamically more stable than the cis isomer, it is the highly predominant form in the dark (>99.99%).Photochromic ligands (PCLs) are light-sensitive molecules that can photo-isomerize after absorption of a photon. Photoisomerization induces a modification of the spectral, chemical, electronic and steric properties of the ligand, in a manner that can affect its biological activity  in a photo-reversible fashion   in the late 1960s  Figure  (Fortin ) Figure . The rea Figures . AAQ is v blockers can be easily modified using the power of organic chemistry, enabling us to generate a small library of compounds with various pharmacological and photophysical properties   and activate only after illumination with the appropriate wavelength of light. Understanding the molecular features necessary for the recognition of the cis or the trans isomer by various ion channels is crucial to the rational design of more selective PCLs. Alas, this is not a straightforward task, since it requires the synthesis and screening of a large library of compounds in addition to molecular modeling of the PCLs bound to the channel.Chemical modifications can also affect the pharmacology of the PCLs. AAQ photosensitizes most, but not all K Scholz, . Of all rs Table . In the trans to cis is in the near-UV range (380 nm), which is compatible with biological systems. However, there is a clear interest in developing PCLs with a red-shifted spectrum, as longer wavelengths of light are less phototoxic and penetrate deeper into tissue. Many of the phenyl ring substituents are known to alter the spectral characteristics of azobenzenes and this effect can be rationally utilized to design novel azobenzene derivatives   is in the 7 min range, but can be extended to hours and even days after adding methyl groups in the ortho position  and IC50(380 nm), respectively) /IC50(dark) ratio to be 28 and 42 for AAQ and BzAQ, respectively. Assuming cis AAQ and cis BzAQ bind to Shaker K+ channels with negligible affinity, the percentage of the trans molecule under 380 nm light illumination is 1/28 = 3.5% for AAQ, and 1/42 = 2.4% for BzAQ. If the affinity of cis AAQ or cis BzAQ for Shaker K+ channels is not negligible, then the percentage of the trans PCL under 380 nm light is even lower. Hence, it is possible to obtain more than 96% photoisomerization to the cis form using AAQ, BzAQ or other PCLs with similar photoswitches. As mentioned above, the situation may be different with quickly relaxing compounds like DENAQ or PhENAQ.What fraction of the vs quickly open and sodium ions rush into the cell, depolarizing the membrane even further. After a slight delay, Navs inactivate and Kvs start to open, thus generating a potassium efflux that repolarizes the cell membrane. Kvs and other K+ channels  do not close immediately after the membrane returns to its resting membrane voltage, generating a hyperpolarization phase called afterhyperpolarization (AHP), during which the neuron is refractive to subsequent AP. Therefore, the influx and efflux of sodium and potassium ions shape APs, and rapidly photoregulating their flux should give us control over AP firing.The molecular mechanism underlying the initiation and propagation of AP is the opening and closing of voltage-gated ion channels Hille, . When exvs, notably the low-voltage activated ones, are open and play a role in maintaining and regulating the membrane potential   both The various voltage- and ligand-gated ion channels found in neurons have very distinct biophysical properties as well as different subcellular and cellular distributions, but often share overlapping pharmacology. The limited selectivity of pharmacological agents has hindered the understanding of their physiological roles. Traditional drugs often cannot differentiate between different receptor types or subtypes. Some of them, such as toxins, do show good receptor selectivity, but their temporal action profile cannot mimic the rapid rise and fall in neurotransmitter concentrations in the brain, as they persist in the tissue for an extended period of time and cannot be washed out quickly. In addition, the effect of traditional pharmacological agents cannot be easily restricted to a specific cell type or tissue; for example, there is no method for selectively controlling post- vs. pre-synaptic receptors. The relationship between receptor function and behavior can also be studied via the generation of transgenic organisms, but this strategy lacks temporal specificity and can produce animal phenotypes where undesirable developmental defects and compensatory changes are superimposed on the true effects of receptor removal. The development of spatially and temporally targeted activation/inactivation of specific receptors will help to overcome this problem and produce a better understanding of the function of receptors in adult animals.in vitro and in vivo, it still suffers from the lack of fine spatiotemporal control of receptor activity, due to the inability to control ligand diffusion into or out of a region of interest or manipulate the dynamics of ligand binding/unbinding. Light is the perfect modality for achieving such precise spatiotemporal control, as it allows for micrometer spatial and millisecond temporal resolution. We thus decided to combine the power of chemical genetics with the precision of optical control in order to develop a series of photoswitchable tethered ligands (PTLs) for the optochemical genetic control of ion channels  on one end of the molecule, a central photoisomerizable azobenzene core, and a cysteine-reactive group on the other end of the molecule. The PTL can react with engineered cysteine point mutations in the ion channel of interest, covalently tethering the ligand to the receptor. In addition to the shape and dipole moment changes, the end-to-end distance of the + channel, resulting in synthetic photoisomerizable azobenzene-regulated K+ (SPARK) channels  which can be conjugated with photoswitchable agonists or antagonists, allowing for powerful bidirectional control of receptor activity  viral vectors, or the in utero electroporation technique  they lack specificity for motor vs. sensory neurons and also for different sensory modalities  (2) block duration or intensity cannot be regulated . They are also promising clinical candidates for treating blindness and pathological pain. In contrast, PTLs are highly sophisticated molecular tools that enable the optical control of a defined ion channel in a targeted cell population. This ability to specifically control a given receptor in a defined neuronal population and monitor changes in behavior due to its activation or inhibition should provide an unprecedented ability to uncover the functional connectivity of the nervous system. Our studies will thus be crucial to the design of novel, targeted drugs for treating neurological and neuropsychiatric disorders.We have developed multiple one-component PCL and two-component PTL systems for photosensitizing ion channels naturally present in neurons. Both of these strategies work well The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Breast cancer is one of the leading causes of cancer death for women all over the world and mammography is thought of as one of the main tools for early detection of breast cancer. In order to detect the breast cancer, computer aided technology has been introduced. In computer aided cancer detection, the detection and segmentation of mass are very important. The shape of mass can be used as one of the factors to determine whether the mass is malignant or benign. However, many of the current methods are semi-automatic. In this paper, we investigate fully automatic segmentation method.In this paper, a new mass segmentation algorithm is proposed. In the proposed algorithm, a fully automatic marker-controlled watershed transform is proposed to segment the mass region roughly, and then a level set is used to refine the segmentation. For over-segmentation caused by watershed, we also investigated different noise reduction technologies. Images from DDSM were used in the experiments and the results show that the new algorithm can improve the accuracy of mass segmentation.The new algorithm combines the advantages of both methods. The combination of the watershed based segmentation and level set method can improve the efficiency of the segmentation. Besides, the introduction of noise reduction technologies can reduce over-segmentation. Breast cancer is one of the leading causes of cancer death for women all over the world  and earlIn computer aided cancer diagnosis, the detection and segmentation of mass are very important. The shape of mass can be used as one of the factors to determine whether the mass is malignant or benign. In the past, many methods for mass segmentation algorithms have been proposed. These algorithms include manual segmentation , semi-auAlthough many other results on mass segmentation have been published, automatic segmentation of mass is still considered difficult because of the ill-defined boundaries and overlapping with fibro-glandular tissue of many masses . In thisIn the experiments, we selected 200 mammograms randomly from the DDSM database  to verifA program was developed using Matlab to run on all the test images without user intervention. The results show that all cases of segmentation were accurate in comparison with the radiologist-marked on the mammograms. Figure In the past, there have proposed many segmentation evaluation methods, however, segmentation evaluation is still an open topic ,26. TherHitting denotes the ratio of correct segmentation, Missing denotes the ratio of missing mass, OverHitting denotes the ratio of false mass segmented, RelativeHitting denotes relative correct ratio against segmentation results, and RelativeMissing denotes relative missing ratio against segmentation results [where TP, FP and FN are True Positives, False Positives, and False Negatives respectively. Figure  results .The comparisons of the segmentation results between the proposed method and the manually segmented image by radiologist are shown in Figure Besides the comparison of the proposed algorithm with the human segmentation, we also compared the effectiveness of different noise reduction technologies for over-segmentation reduction. The comparison results are shown in Figure In this paper, we propose a mass segmentation algorithm which combines watershed method and level set method. The new method is divided into two steps: a marker-controlled watershed transform is first used to segment the mass region roughly, and then a level set is used to refine the segmentation.Watershed based segmentation algorithm has many advantages which can overcome the disadvantage in the level set based segmentation. As we know, level set method usually needs hundreds of iterations to get a good segmentation result. With a good initialization provided by watershed segmentation, the level set method can converge more quickly, thus greatly speed up the whole segmentation procedure. Besides, by using watershed segmentation as the initialization step, we can remove the manual initialization step in general level set segmentation and we can obtain a full automatic segmentation algorithm.However, the proposed algorithm still has a few limitations. In the proposed algorithm, the object to be segmented is already ROI images which have been preliminarily cut from the whole mammograms. Thus a mass detection step needs to be merged into the algorithm in the future. Although Noise reduction technologies are introduced into the algorithms, over-segmentation still happens on some mammographic images. Over-segmentation affects the efficiency of the algorithm and thus an effective over-segmentation algorithm is needed in the future. Another issue is the time complexity of the level set. By using the result from watershed we can save a lot time but much longer computation time is still needed to achieve the accurate segmentation results.In this paper, we have developed a hybrid method to segment the mammograms which used watershed algorithm and level set method. We used watershed transform to provide a coarse and fast pre-segmentation, and used the resultant segmentation as the initial contour for the level set segmentation. Automatic selection of the starting point from watershed transform can reduce the user interaction. The combination of the two segmentation methods speeds up the entire segmentation processing and improves the segmentation efficiency. Besides, the method has good topological adaptability; it can deal with complex and changing shapes of the segmentation of the mammograms well and get high segmentation accuracy. Experimental results show that the proposed segmentation method can obtain good results.Mass segmentation includes two steps in the proposed algorithm. The first step is to use watershed transform for rough segmentation and the second step is to use level set based method to refine the segmentation obtained by watershed transform. Watershed based algorithms are mathematical morphology methods for image segmentation and they have many advantages in comparison with other image segmentation methods. For example, watershed transform based segmentation methods generally have high computation speed and can obtain closed contour lines and accurate position. Besides, watershed based image segmentation algorithms can handle weak edges very well .χ be a gray image, ||∇χ|| is the gradient image obtained from χ. In order to segment the objects in the image, the foreground markers will be computed for the objects. After the markers are obtained, the flood waves will propagate from the set of markers to cover the topographic surface ||∇χ|| [The basic idea of watershed can be described as follows : let χ be ||∇χ|| . When thIn the implementation of the watershed algorithm, if we only use gradient of watershed for segmentation, there are too many ridgelines which will cause over-segmentation  and outside(C) are the regions inside and outside the contour.Where Although the proposed level set method could produce successful segmentation, it needs powerful initialization techniques. In order to solve the problem, in the proposed method, we use the contour obtained from watershed segmentation step as the initial contour of the level set. We resolve the drawbacks of the two methods mentioned above by combining them.Besides the initialization issue, there is also noise issue. In general, the mammograms have a lot of noise. If the watershed algorithm was applied on the image directly, over-segmentation will happen because the watershed algorithm is very sensitive to noise. To avoid over-segmentation, we need to remove the noise. When the noise is removed, we can get the coarse segmentation using watersheds. The noise reduction methods investigated in the proposed paper include average filter, Gaussian filter and anisotropic diffusion . AnisotrThe proposed algorithm is shown in Figure The authors declare that they have no competing interests.JL, XL, LC and JC developed the algorithm using watershed and level let and wrote the original the paper. JT proposed the investigation of over-segmentation issue and revised the paper. YD did data analysis. All authors read and approved the final manuscript.